Digitala Vetenskapliga Arkivet

Change search
Refine search result
12 1 - 50 of 65
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1. Ahmad, S
    et al.
    Poveda, A
    Shungin, Dmitry
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Umeå University, Faculty of Medicine, Department of Odontology. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University Diabetes Center, Lund University, Malmö, Sweden.
    Barroso, I
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Biobank Research. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University Diabetes Center, Lund University, Malmö, Sweden.
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University Diabetes Center, Lund University, Malmö, Sweden; Department of Nutrition, Harvard School of Public Health, Boston, MA, USA.
    Established BMI-associated genetic variants and their prospective associations with BMI and other cardiometabolic traits: the GLACIER Study2016In: International Journal of Obesity, ISSN 0307-0565, E-ISSN 1476-5497, Vol. 40, no 9, p. 1346-1352Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Recent cross-sectional genome-wide scans have reported associations of 97 independent loci with body mass index (BMI). In 3541 middle-aged adult participants from the GLACIER Study, we tested whether these loci are associated with 10-year changes in BMI and other cardiometabolic traits (fasting and 2-h glucose, triglycerides, total cholesterol, and systolic and diastolic blood pressures).

    METHODS: A BMI-specific genetic risk score (GRS) was calculated by summing the BMI-associated effect alleles at each locus. Trait-specific cardiometabolic GRSs comprised only the loci that show nominal association (P⩽0.10) with the respective trait in the original cross-sectional study. In longitudinal genetic association analyses, the second visit trait measure (assessed ~10 years after baseline) was used as the dependent variable and the models were adjusted for the baseline measure of the outcome trait, age, age(2), fasting time (for glucose and lipid traits), sex, follow-up time and population substructure.

    RESULTS: The BMI-specific GRS was associated with increased BMI at follow-up (β=0.014 kg m(-2) per allele per 10-year follow-up, s.e.=0.006, P=0.019) as were three loci (PARK2 rs13191362, P=0.005; C6orf106 rs205262, P=0.043; and C9orf93 rs4740619, P=0.01). Although not withstanding Bonferroni correction, a handful of single-nucleotide polymorphisms was nominally associated with changes in blood pressure, glucose and lipid levels.

    CONCLUSIONS: Collectively, established BMI-associated loci convey modest but statistically significant time-dependent associations with long-term changes in BMI, suggesting a role for effect modification by factors that change with time in this population.

  • 2.
    Ahmad, Shafqat
    et al.
    Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Malmö, Sweden.
    Zhao, Wei
    Philadelphia, PA, US.
    Renström, Frida
    Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Malmö, Sweden.
    Rasheed, Asif
    Karachi, Pakistan.
    Samuel, Maria
    Karachi, Pakistan.
    Zaidi, Mozzam
    Karachi, Pakistan.
    Shah, Nabi
    Karachi, Pakistan; Abbottabad, Pakistan.
    Mallick, Nadeem Hayyat
    Punjab Institute of Cardiology, Lahore, Pakistan.
    Zaman, Khan Shah
    Karachi, Pakistan.
    Ishaq, Mohammad
    Karachi, Pakistan.
    Rasheed, Syed Zahed
    Karachi, Pakistan.
    Memon, Fazal-ur-Rheman
    Karachi, Pakistan.
    Hanif, Bashir
    Karachi, Pakistan.
    Lakhani, Muhammad Shakir
    Karachi, Pakistan.
    Ahmed, Faisal
    Karachi, Pakistan.
    Kazmi, Shahana Urooj
    Karachi, Pakistan.
    Frossard, Philippe
    Karachi, Pakistan; Nazarbayev University, Astana, Kazakhstan.
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Malmö, Sweden; Department of Nutrition, Harvard School of Public Health, Boston, MA, USA.
    Saleheen, Danish
    Philadelphia, PA, US; Karachi, Pakistan.
    Physical activity, smoking, and genetic predisposition to obesity in people from Pakistan: the PROMIS study2015In: BMC Medical Genetics, E-ISSN 1471-2350, Vol. 16, article id 114Article in journal (Refereed)
    Abstract [en]

    Background: Multiple genetic variants have been reliably associated with obesity-related traits in Europeans, but little is known about their associations and interactions with lifestyle factors in South Asians.

    Methods: In 16,157 Pakistani adults (8232 controls; 7925 diagnosed with myocardial infarction [MI]) enrolled in the PROMIS Study, we tested whether: a) BMI-associated loci, individually or in aggregate (as a genetic risk score - GRS), are associated with BMI; b) physical activity and smoking modify the association of these loci with BMI. Analyses were adjusted for age, age(2), sex, MI (yes/no), and population substructure.

    Results: Of 95 SNPs studied here, 73 showed directionally consistent effects on BMI as reported in Europeans. Each additional BMI-raising allele of the GRS was associated with 0.04 (SE = 0.01) kg/m(2) higher BMI (P = 4.5 x 10(-14)). We observed nominal evidence of interactions of CLIP1 rs11583200 (P-interaction = 0.014), CADM2 rs13078960 (P-interaction = 0.037) and GALNT10 rs7715256 (P-interaction = 0.048) with physical activity, and PTBP2 rs11165643 (P-interaction = 0.045), HIP1 rs1167827 (P-interaction = 0.015), C6orf106 rs205262 (P-interaction = 0.032) and GRID1 rs7899106 (P-interaction = 0.043) with smoking on BMI.

    Conclusions: Most BMI-associated loci have directionally consistent effects on BMI in Pakistanis and Europeans. There were suggestive interactions of established BMI-related SNPs with smoking or physical activity.

    Download full text (pdf)
    fulltext
  • 3. Ali, Ashfaq
    et al.
    Varga, Tibor V.
    Stojkovic, Ivana A.
    Schulz, Christina-Alexandra
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Biobank Research.
    Barroso, Ines
    Poveda, Alaitz
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research.
    Orho-Melander, Marju
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA.
    Do Genetic Factors Modify the Relationship Between Obesity and Hypertriglyceridemia?: Findings From the GLACIER and the MDC Studies2016In: Circulation: Cardiovascular Genetics, ISSN 1942-325X, E-ISSN 1942-3268, Vol. 9, no 2, p. 162-171Article in journal (Refereed)
    Abstract [en]

    Background Obesity is a major risk factor for dyslipidemia, but this relationship is highly variable. Recently published data from 2 Danish cohorts suggest that genetic factors may underlie some of this variability.

    Methods and Results We tested whether established triglyceride-associated loci modify the relationship of body mass index (BMI) and triglyceride concentrations in 2 Swedish cohorts (the Gene-Lifestyle Interactions and Complex Traits Involved in Elevated Disease Risk [GLACIER Study; N=4312] and the Malmo Diet and Cancer Study [N=5352]). The genetic loci were amalgamated into a weighted genetic risk score (WGRS(TG)) by summing the triglyceride-elevating alleles (weighted by their established marginal effects) for all loci. Both BMI and the WGRS(TG) were strongly associated with triglyceride concentrations in GLACIER, with each additional BMI unit (kg/m(2)) associated with 2.8% (P=8.4x10(-84)) higher triglyceride concentration and each additional WGRS(TG) unit with 2% (P=7.6x10(-48)) higher triglyceride concentration. Each unit of the WGRS(TG) was associated with 1.5% higher triglyceride concentrations in normal weight and 2.4% higher concentrations in overweight/obese participants (P-interaction=0.056). Meta-analyses of results from the Swedish cohorts yielded a statistically significant WGRS(TG)xBMI interaction effect (P-interaction=6.0x10(-4)), which was strengthened by including data from the Danish cohorts (P-interaction=6.5x10(-7)). In the meta-analysis of the Swedish cohorts, nominal evidence of a 3-way interaction (WGRS(TG)xBMIxsex) was observed (P-interaction=0.03), where the WGRS(TG)xBMI interaction was only statistically significant in females. Using protein-protein interaction network analyses, we identified molecular interactions and pathways elucidating the metabolic relationships between BMI and triglyceride-associated loci.

    Conclusions Our findings provide evidence that body fatness accentuates the effects of genetic susceptibility variants in hypertriglyceridemia, effects that are most evident in females.

  • 4. Asli, Lene A.
    et al.
    Braaten, Tonje
    Olsen, Anja
    Tjonneland, Anne
    Overvad, Kim
    Nilsson, Lena Maria
    Umeå University, Arctic Research Centre at Umeå University. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Renstrom, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Department of Clinical Sciences, Lund University, Sweden.
    Lund, Eiliv
    Skeie, Guri
    Potato consumption and risk of pancreatic cancer in the HELGA cohort2018In: British Journal of Nutrition, ISSN 0007-1145, E-ISSN 1475-2662, Vol. 119, no 12, p. 1408-1415Article, review/survey (Refereed)
    Abstract [en]

    Potatoes have been a staple food in many countries throughout the years. Potatoes have a high glycaemic index (GI) score, and high GI has been associated with several chronic diseases and cancers. Still, the research on potatoes and health is scarce and contradictive, and we identified no prospective studies that had investigated the association between potatoes as a single food and the risk of pancreatic cancer. The aim of this study was to prospectively investigate the association between potato consumption and pancreatic cancer among 114 240 men and women in the prospective HELGA cohort, using Cox proportional hazard models. Information on diet (validated FFQ's), lifestyle and health was collected by means of a questionnaire, and 221 pancreatic cancer cases were identified through cancer registries. The mean follow-up time was 11.4 (95 % CI 0.3, 169) years. High consumption of potatoes showed a non-significantly higher risk of pancreatic cancer in the adjusted model (hazard ratio (HR) 1.44; 95 % CI 0.93, 2.22, P-for trend 0.030) when comparing the highest v. the lowest quartile of potato consumption. In the sex-specific analyses, significant associations were found for females (HR 2.00; 95 % CI 1.07, 3.72, P-for trend 0.020), but not for males (HR 1.01; 95 % CI 0.56, 1.84, P-for trend 0.34). In addition, we explored the associations by spline regression, and the absence of dose-response effects was confirmed. In this study, high potato consumption was not consistently associated with a higher risk of pancreatic cancer. Further studies with larger populations are needed to explore the possible sex difference.

  • 5. Bentley, Amy R.
    et al.
    Sung, Yun J.
    Brown, Michael R.
    Winkler, Thomas W.
    Kraja, Aldi T.
    Ntalla, Ioanna
    Schwander, Karen
    Chasman, Daniel, I
    Lim, Elise
    Deng, Xuan
    Guo, Xiuqing
    Liu, Jingmin
    Lu, Yingchang
    Cheng, Ching-Yu
    Sim, Xueling
    Vojinovic, Dina
    Huffman, Jennifer E.
    Musani, Solomon K.
    Li, Changwei
    Feitosa, Mary F.
    Richard, Melissa A.
    Noordam, Raymond
    Baker, Jenna
    Chen, Guanjie
    Aschard, Hugues
    Bartz, Traci M.
    Ding, Jingzhong
    Dorajoo, Rajkumar
    Manning, Alisa K.
    Rankinen, Tuomo
    Smith, Albert, V
    Tajuddin, Salman M.
    Zhao, Wei
    Graff, Mariaelisa
    Alver, Maris
    Boissel, Mathilde
    Chai, Jin Fang
    Chen, Xu
    Divers, Jasmin
    Evangelou, Evangelos
    Gao, Chuan
    Goel, Anuj
    Hagemeijer, Yanick
    Harris, Sarah E.
    Hartwig, Fernando P.
    He, Meian
    Horimoto, Andrea R. V. R.
    Hsu, Fang-Chi
    Hung, Yi-Jen
    Jackson, Anne U.
    Kasturiratne, Anuradhani
    Komulainen, Pirjo
    Kuehnel, Brigitte
    Leander, Karin
    Lin, Keng-Hung
    Luan, Jian'an
    Lyytikainen, Leo-Pekka
    Matoba, Nana
    Nolte, Ilja M.
    Pietzner, Maik
    Prins, Bram
    Riaz, Muhammad
    Robino, Antonietta
    Said, M. Abdullah
    Schupf, Nicole
    Scott, Robert A.
    Sofer, Tamar
    Stancakova, Alena
    Takeuchi, Fumihiko
    Tayo, Bamidele O.
    van der Most, Peter J.
    Varga, Tibor V.
    Wang, Tzung-Dau
    Wang, Yajuan
    Ware, Erin B.
    Wen, Wanqing
    Xiang, Yong-Bing
    Yanek, Lisa R.
    Zhang, Weihua
    Zhao, Jing Hua
    Adeyemo, Adebowale
    Afaq, Saima
    Amin, Najaf
    Amini, Marzyeh
    Arking, Dan E.
    Arzumanyan, Zorayr
    Aung, Tin
    Ballantyne, Christie
    Barr, R. Graham
    Bielak, Lawrence F.
    Boerwinkle, Eric
    Bottinger, Erwin P.
    Broeckel, Ulrich
    Brown, Morris
    Cade, Brian E.
    Campbell, Archie
    Canouil, Mickael
    Charumathi, Sabanayagam
    Chen, Yii-Der Ida
    Christensen, Kaare
    Concas, Maria Pina
    Connell, John M.
    de las Fuentes, Lisa
    de Silva, H. Janaka
    de Vries, Paul S.
    Doumatey, Ayo
    Duan, Qing
    Eaton, Charles B.
    Eppinga, Ruben N.
    Faul, Jessica D.
    Floyd, James S.
    Forouhi, Nita G.
    Forrester, Terrence
    Friedlander, Yechiel
    Gandin, Ilaria
    Gao, He
    Ghanbari, Mohsen
    Gharib, Sina A.
    Gigante, Bruna
    Giulianini, Franco
    Grabe, Hans J.
    Gu, C. Charles
    Harris, Tamara B.
    Heikkinen, Sami
    Heng, Chew-Kiat
    Hirata, Makoto
    Hixson, James E.
    Ikram, M. Arfan
    Jia, Yucheng
    Joehanes, Roby
    Johnson, Craig
    Jonas, Jost Bruno
    Justice, Anne E.
    Katsuya, Tomohiro
    Khor, Chiea Chuen
    Kilpelainen, Tuomas O.
    Koh, Woon-Puay
    Kolcic, Ivana
    Kooperberg, Charles
    Krieger, Jose E.
    Kritchevsky, Stephen B.
    Kubo, Michiaki
    Kuusisto, Johanna
    Lakka, Timo A.
    Langefeld, Carl D.
    Langenberg, Claudia
    Launer, Lenore J.
    Lehne, Benjamin
    Lewis, Cora E.
    Li, Yize
    Liang, Jingjing
    Lin, Shiow
    Liu, Ching-Ti
    Liu, Jianjun
    Liu, Kiang
    Loh, Marie
    Lohman, Kurt K.
    Louie, Tin
    Luzzi, Anna
    Magi, Reedik
    Mahajan, Anubha
    Manichaikul, Ani W.
    McKenzie, Colin A.
    Meitinger, Thomas
    Metspalu, Andres
    Milaneschi, Yuri
    Milani, Lili
    Mohlke, Karen L.
    Momozawa, Yukihide
    Morris, Andrew P.
    Murray, Alison D.
    Nalls, Mike A.
    Nauck, Matthias
    Nelson, Christopher P.
    North, Kari E.
    O'Connell, Jeffrey R.
    Palmer, Nicholette D.
    Papanicolau, George J.
    Pedersen, Nancy L.
    Peters, Annette
    Peyser, Patricia A.
    Polasek, Ozren
    Poulter, Neil
    Raitakari, Olli T.
    Reiner, Alex P.
    Renstrom, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Skåne University Hospital, Malmö, Sweden.
    Rice, Treva K.
    Rich, Stephen S.
    Robinson, Jennifer G.
    Rose, Lynda M.
    Rosendaal, Frits R.
    Rudan, Igor
    Schmidt, Carsten O.
    Schreiner, Pamela J.
    Scott, William R.
    Sever, Peter
    Shi, Yuan
    Sidney, Stephen
    Sims, Mario
    Smith, Jennifer A.
    Snieder, Harold
    Starr, John M.
    Strauch, Konstantin
    Stringham, Heather M.
    Tan, Nicholas Y. Q.
    Tang, Hua
    Taylor, Kent D.
    Teo, Yik Ying
    Tham, Yih Chung
    Tiemeier, Henning
    Turner, Stephen T.
    Uitterlinden, Andre G.
    van Heemst, Diana
    Waldenberger, Melanie
    Wang, Heming
    Wang, Lan
    Wang, Lihua
    Wei, Wen Bin
    Williams, Christine A.
    Wilson, Gregory, Sr.
    Wojczynski, Mary K.
    Yao, Jie
    Young, Kristin
    Yu, Caizheng
    Yuan, Jian-Min
    Zhou, Jie
    Zonderman, Alan B.
    Becker, Diane M.
    Boehnke, Michael
    Bowden, Donald W.
    Chambers, John C.
    Cooper, Richard S.
    de Faire, Ulf
    Deary, Ian J.
    Elliott, Paul
    Esko, Tonu
    Farrall, Martin
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Medicine. Return to work after interdisciplinary pain rehabilitation Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan; Department of Nutrition, Harvard T. H. Chan School of Public Health, Harvard University, Boston, MA, USA; OCDEM, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
    Freedman, Barry, I
    Froguel, Philippe
    Gasparini, Paolo
    Gieger, Christian
    Horta, Bernardo L.
    Juang, Jyh-Ming Jimmy
    Kamatani, Yoichiro
    Kammerer, Candace M.
    Kato, Norihiro
    Kooner, Jaspal S.
    Laakso, Markku
    Laurie, Cathy C.
    Lee, I-Te
    Lehtimaki, Terho
    Magnusson, Patrik K. E.
    Oldehinkel, Albertine J.
    Penninx, Brenda W. J. H.
    Pereira, Alexandre C.
    Rauramaa, Rainer
    Redline, Susan
    Samani, Nilesh J.
    Scott, James
    Shu, Xiao-Ou
    van der Harst, Pim
    Wagenknecht, Lynne E.
    Wang, Jun-Sing
    Wang, Ya Xing
    Wareham, Nicholas J.
    Watkins, Hugh
    Weir, David R.
    Wickremasinghe, Ananda R.
    Wu, Tangchun
    Zeggini, Eleftheria
    Zheng, Wei
    Bouchard, Claude
    Evans, Michele K.
    Gudnason, Vilmundur
    Kardia, Sharon L. R.
    Liu, Yongmei
    Psaty, Bruce M.
    Ridker, Paul M.
    van Dam, Rob M.
    Mook-Kanamori, Dennis O.
    Fornage, Myriam
    Province, Michael A.
    Kelly, Tanika N.
    Fox, Ervin R.
    Hayward, Caroline
    van Duijn, Cornelia M.
    Tai, E. Shyong
    Wong, Tien Yin
    Loos, Ruth J. F.
    Franceschini, Nora
    Rotter, Jerome, I
    Zhu, Xiaofeng
    Bierut, Laura J.
    Gauderman, W. James
    Rice, Kenneth
    Munroe, Patricia B.
    Morrison, Alanna C.
    Rao, Dabeeru C.
    Rotimi, Charles N.
    Cupples, L. Adrienne
    Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids2019In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 51, no 4, p. 636-+Article in journal (Refereed)
    Abstract [en]

    The concentrations of high- and low-density-lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene-smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 new loci associated with lipids, some of which were detected only because association differed by smoking status. Additionally, we demonstrate the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings.

  • 6.
    Brito, Ema C
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Lyssenko, V
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Berglund, G
    Nilsson, PM
    Groop, L
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Previously associated type 2 diabetes variants may interact with physical activity to modify the risk of impaired glucose regulation and type 2 diabetes: a study of 16,003 Swedish adults2009In: Diabetes, ISSN 0012-1797, E-ISSN 1939-327X, Vol. 58, no 6, p. 1411-1418Article in journal (Refereed)
  • 7. Brunkwall, Louise
    et al.
    Chen, Yan
    Hindy, George
    Rukh, Gull
    Ericson, Ulrika
    Barroso, Ines
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Odontology.
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden; Department of Nutrition, Harvard School of Public Health, Boston, MA.
    Orho-Melander, Marju
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.
    Sugar-sweetened beverage consumption and genetic predisposition to obesity in 2 Swedish cohorts2016In: American Journal of Clinical Nutrition, ISSN 0002-9165, E-ISSN 1938-3207, Vol. 104, no 3, p. 809-815Article in journal (Refereed)
    Abstract [en]

    Background: The consumption of sugar-sweetened beverages (SSBs), which has increased substantially during the last decades, has been associated with obesity and weight gain.

    Objective: Common genetic susceptibility to obesity has been shown to modify the association between SSB intake and obesity risk in 3 prospective cohorts from the United States. We aimed to replicate these findings in 2 large Swedish cohorts.

    Design: Data were available for 21,824 healthy participants from the Malmö Diet and Cancer study and 4902 healthy participants from the Gene-Lifestyle Interactions and Complex Traits Involved in Elevated Disease Risk Study. Self-reported SSB intake was categorized into 4 levels (seldom, low, medium, and high). Unweighted and weighted genetic risk scores (GRSs) were constructed based on 30 body mass index [(BMI) in kg/m2]-associated loci, and effect modification was assessed in linear regression equations by modeling the product and marginal effects of the GRS and SSB intake adjusted for age-, sex-, and cohort-specific covariates, with BMI as the outcome. In a secondary analysis, models were additionally adjusted for putative confounders (total energy intake, alcohol consumption, smoking status, and physical activity).

    Results: In an inverse variance-weighted fixed-effects meta-analysis, each SSB intake category increment was associated with a 0.18 higher BMI (SE = 0.02; P = 1.7 × 10−20n = 26,726). In the fully adjusted model, a nominal significant interaction between SSB intake category and the unweighted GRS was observed (P-interaction = 0.03). Comparing the participants within the top and bottom quartiles of the GRS to each increment in SSB intake was associated with 0.24 (SE = 0.04; P = 2.9 × 10−8n = 6766) and 0.15 (SE = 0.04; P = 1.3 × 10−4n = 6835) higher BMIs, respectively.

    Conclusions: The interaction observed in the Swedish cohorts is similar in magnitude to the previous analysis in US cohorts and indicates that the relation of SSB intake and BMI is stronger in people genetically predisposed to obesity.

    Download full text (pdf)
    fulltext
  • 8.
    Burén, Jonas
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine.
    Lindmark, Stina
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Eriksson, Jan W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    In vitro reversal of hyperglycemia normalizes insulin action in fat cells from type 2 diabetes patients: is cellular insulin resistance caused by glucotoxicity in vivo?2002In: Metabolism: Clinical and Experimental, ISSN 0026-0495, E-ISSN 1532-8600, Vol. 52, no 2, p. 239-245Article in journal (Refereed)
    Abstract [en]

    Chronic hyperglycemia promotes the development of insulin resistance. The aim of this study was to investigate whether cellular insulin resistance is secondary to the diabetic state in human type 2 diabetes. Subcutaneous fat biopsies were taken from 3 age-, sex-, and body mass index (BMI)-matched groups with 10 subjects in each group: type 2 diabetes patients with either good (hemoglobin A1c [HbA1c] [lt ] 7%, G) or poor (HbA1c [gt ] 7.5%, P) metabolic control and healthy control subjects (C). Insulin action in vitro was studied by measurements of glucose uptake both directly after cell isolation and following a 24-hour incubation at a physiological glucose level (6 mmol/L). The relationship with insulin action in vivo was addressed by employing the euglycemic clamp technique. Freshly isolated fat cells from type 2 diabetes patients with poor metabolic control had [sim ]55% lower maximal insulin response (1,000 [mu ]U/mL) on glucose uptake (P [lt ] .05) compared to C. Cells from P were more insulin-resistant (P [lt ] .05) than cells from G at a low (5 [mu ]U/mL) but not at a high (1,000 [mu ]U/mL) insulin concentration, suggesting insulin insensitivity. However, following 24 hours of incubation at physiological glucose levels, insulin resistance was completely reversed in the diabetes cells and no differences in insulin-stimulated glucose uptake were found among the 3 groups. Insulin sensitivity in vivo assessed with hyperinsulinemic, euglycemic clamp (M-value) was significantly associated with insulin action on glucose uptake in fresh adipocytes in vitro (r = 0.50, P [lt ] .01). Fasting blood glucose at the time of biopsy and HbA1c, but not serum insulin, were negatively correlated to insulin's effect to stimulate glucose uptake in vitro (r = [minus ]0.36, P = .064 and r = [minus ] 0.41, P [lt ].05, respectively) in all groups taken together. In the in vivo situation, fasting blood glucose, HbA1c, and serum insulin were all negatively correlated to insulin sensitivity (M-value; r = [minus ]0.62, P[lt ] .001, r= [minus ]0.61, P[lt ] .001, and r = [minus ]0.56, p [lt ] .01, respectively). Cell size, waist-to-hip ration (WHR), and BMI correlated negatively with insulin's effect to stimulate glucose uptake both in vitro (r = [minus ]0.55, P [lt ] .01, r = [minus ]0.54, P [lt ] .01, and r = [minus ]0.43, P [lt ] .05, respectively) and in vivo (r = [minus ]0.43, P [lt ] .05, r = [minus ]0.50, P [lt ] .01, and r = [minus ]0.36, P [lt ] .05, respectively). Multiple regression analyses revealed that adipocyte cell size and WHR independently predicted insulin resistance in vitro. Furthermore, insulin sensitivity in vivo could be predicted by fasting blood glucose and serum insulin levels. We conclude that insulin resistance in fat cells from type 2 diabetes patients is fully reversible following incubation at physiological glucose concentrations. Thus, cellular insulin resistance may be mainly secondary to the hyperglycemic state in vivo.

  • 9. Chen, Yan
    et al.
    Estampador, Angela C
    Keller, Maria
    Poveda, Alaitz
    Dalla-Riva, Jonathan
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Biobank Research.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University, Skåne University Hospital Malmö, Malmö, Sweden.
    Kurbasic, Azra
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Medicine. Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University, Skåne University Hospital Malmö, Malmö, Sweden; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston MA, USA.
    Varga, Tibor V
    The combined effects of FADS gene variation and dietary fats in obesity-related traits in a population from the far north of Sweden: the GLACIER Study2019In: International Journal of Obesity, ISSN 0307-0565, E-ISSN 1476-5497, Vol. 43, no 4, p. 808-820Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Recent analyses in Greenlandic Inuit identified six genetic polymorphisms (rs74771917, rs3168072, rs12577276, rs7115739, rs174602 and rs174570) in the fatty acid desaturase gene cluster (FADS1-FADS2-FADS3) that are associated with multiple metabolic and anthropometric traits. Our objectives were to systematically assess whether dietary polyunsaturated fatty acid (PUFA) intake modifies the associations between genetic variants in the FADS gene cluster and cardiometabolic traits, and to functionally annotate top-ranking candidates to estimate their regulatory potential.

    METHODS: Data analyses consisted of the following: interaction analyses between the 6 candidate genetic variants and dietary PUFA intake; gene-centric joint analyses to detect interaction signals in the FADS region; haplotype-centric joint tests across 30 haplotype blocks in the FADS region to refine interaction signals; and functional annotation of top-ranking loci from the previous steps. These analyses were undertaken in Swedish adults from the GLACIER Study (N = 5,160); data on genetic variation and eight cardiometabolic traits were used.

    RESULTS: Interactions were observed between rs174570 and n-6 PUFA intake on fasting glucose (Pint = 0.005) and between rs174602 and n-3 PUFA intake on total cholesterol (Pint = 0.001). Gene-centric analyses demonstrated a statistically significant interaction effect for FADS and n-3 PUFA on triglycerides (Pint = 0.005) considering genetic main effects as random. Haplotype analyses revealed three blocks (Pint < 0.011) that could drive the interaction between FADS and n-3 PUFA on triglycerides; functional annotation of these regions showed that each block harbours a number of highly functional regulatory variants; FADS2 rs5792235 demonstrated the highest functionality score.

    CONCLUSIONS: The association between FADS variants and triglycerides may be modified by PUFA intake. The intronic FADS2 rs5792235 variant is a potential causal variant in the region, having the highest regulatory potential. However, our results suggest that multiple haplotypes may harbour functional variants in a region, rather than a single causal variant.

    Download full text (pdf)
    fulltext
  • 10. deSchoolmeester, J.
    et al.
    Palming, J.
    Persson, T.
    Pereira, M. J.
    Wallerstedt, E.
    Brown, H.
    Gill, D.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Lundgren, M.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Svensson, M. K.
    Rees, A.
    Eriksson, J. W.
    Differences between men and women in the regulation of adipose 11 beta-HSD1 and in its association with adiposity and insulin resistance2013In: Diabetes, obesity and metabolism, ISSN 1462-8902, E-ISSN 1463-1326, Vol. 15, no 11, p. 1056-1060Article in journal (Refereed)
    Abstract [en]

    This study explored sex differences in 11-hydroxysteroid dehydrogenase type 1 (11-HSD1) activity and gene expression in isolated adipocytes and adipose tissue (AT), obtained via subcutaneous biopsies from non-diabetic subjects [58 M, 64 F; age 48.3 +/- 15.3years, body mass index (BMI) 27.2 +/- 3.9kg/m(2)]. Relationships with adiposity and insulin resistance (IR) were addressed. Males exhibited higher 11-HSD1 activity in adipocytes than females, but there was no such difference for AT. In both men and women, adipocyte 11-HSD1 activity correlated positively with BMI, waist circumference, % body fat, adipocyte size and with serum glucose, triglycerides and low-density lipoprotein:high-density lipoprotein (LDL:HDL) ratio. Positive correlations with insulin, HOMA-IR and haemoglobin A1c (HbA1c) and a negative correlation with HDL-cholesterol were significant only in males. Conversely, 11-HSD1 activity in AT correlated with several markers of IR and adiposity in females but not in males, but the opposite pattern was found with respect to 11-HSD1 mRNA expression. This study suggests that there are sex differences in 11-HSD1 regulation and in its associations with markers of obesity and IR.

  • 11. Ding, Ming
    et al.
    Huang, Tao
    Bergholdt, Helle K. M.
    Nordestgaard, Borge G.
    Ellervik, Christina
    Qi, Lu
    Frazier-Wood, Alexis C.
    Aslibekyan, Stella
    North, Kari E.
    Voortman, Trudy
    Graff, Mariaelisa
    Smith, Caren E.
    Lai, Chao-Qiang
    Varbo, Anette
    Lemaitre, Rozenn N.
    de Jonge, Ester A. L.
    Fumeron, Frederic
    Corella, Dolores
    Wang, Carol A.
    Tjonneland, Anne
    Overvad, Kim
    Sorensen, Thorkild I. A.
    Feitosa, Mary F.
    Wojczynski, Mary K.
    Kahonen, Mika
    Ahmad, Shafqat
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Department of Clinical Sciences, Lund University, Malmö, Sweden.
    Psaty, Bruce M.
    Siscovick, David S.
    Barroso, Ines
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Biobank Research.
    Hernandez, Dena
    Ferrucci, Luigi
    Bandinelli, Stefania
    Linneberg, Allan
    Sandholt, Camilla Helene
    Pedersen, Oluf
    Hansen, Torben
    Schulz, Christina-Alexandra
    Sonestedt, Emily
    Orho-Melander, Marju
    Chen, Tzu-An
    Rotter, Jerome I.
    Allison, Mathew A.
    Rich, Stephen S.
    Sorli, Jose V.
    Coltell, Oscar
    Pennell, Craig E.
    Eastwood, Peter R.
    Hofman, Albert
    Uitterlinden, Andre G.
    Zillikens, MCarola
    van Rooij, Frank J. A.
    Chu, Audrey Y.
    Rose, Lynda M.
    Ridker, Paul M.
    Viikari, Jorma
    Raitakari, Olli
    Lehtimaki, Terho
    Mikkila, Vera
    Willett, Walter C.
    Wang, Yujie
    Tucker, Katherine L.
    Ordovas, Jose M.
    Kilpelainen, Tuomas O.
    Province, Michael A.
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Department of Nutrition, Harvard School of Public Health, Boston, MA 02115, USA; Department of Clinical Sciences, Lund University, Malmö, Sweden.
    Arnett, Donna K.
    Tanaka, Toshiko
    Toft, Ulla
    Ericso, Ulrika
    Franco, Oscar H.
    Mozaffarian, Dariush
    Hu, Frank B.
    Chasman, Daniel I.
    Dairy consumption, systolic blood pressure, and risk of hypertension: Mendelian randomization study2017In: The BMJ, E-ISSN 1756-1833, Vol. 356, article id j1000Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE To examine whether previous observed inverse associations of dairy intake with systolic blood pressure and risk of hypertension were causal. DESIGN Mendelian randomization study using the single nucleotide polymorphism rs4988235 related to lactase persistence as an instrumental variable. SETTING CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium. PARTICIPANTS Data from 22 studies with 171 213 participants, and an additional 10 published prospective studies with 26 119 participants included in the observational analysis. MAIN OUTCOME MEASURES The instrumental variable estimation was conducted using the ratio of coefficients approach. Using metaanalysis, an additional eight published randomized clinical trials on the association of dairy consumption with systolic blood pressure were summarized. RESULTS Compared with the CC genotype (CC is associated with complete lactase deficiency), the CT/TT genotype (TT is associated with lactose persistence, and CT is associated with certain lactase deficiency) of LCT-13910 (lactase persistence gene) rs4988235 was associated with higher dairy consumption (0.23 (about 55 g/day), 95% confidence interval 0.17 to 0.29) serving/day; P<0.001) and was not associated with systolic blood pressure (0.31, 95% confidence interval -0.05 to 0.68 mm Hg; P=0.09) or risk of hypertension (odds ratio 1.01, 95% confidence interval 0.97 to 1.05; P=0.27). Using LCT-13910 rs4988235 as the instrumental variable, genetically determined dairy consumption was not associated with systolic blood pressure (beta=1.35, 95% confidence interval -0.28 to 2.97 mm Hg for each serving/day) or risk of hypertension (odds ratio 1.04, 0.88 to 1.24). Moreover, meta-analysis of the published clinical trials showed that higher dairy intake has no significant effect on change in systolic blood pressure for interventions over one month to 12 months (intervention compared with control groups: beta=-0.21, 95% confidence interval -0.98 to 0.57 mm Hg). In observational analysis, each serving/day increase in dairy consumption was associated with -0.11 (95% confidence interval -0.20 to -0.02 mm Hg; P=0.02) lower systolic blood pressure but not risk of hypertension (odds ratio 0.98, 0.97 to 1.00; P=0.11). CONCLUSION The weak inverse association between dairy intake and systolic blood pressure in observational studies was not supported by a comprehensive instrumental variable analysis and systematic review of existing clinical trials.

    Download full text (pdf)
    fulltext
  • 12. Ehret, Georg B.
    et al.
    Ferreira, Teresa
    Chasman, Daniel I.
    Jackson, Anne U.
    Schmidt, Ellen M.
    Johnson, Toby
    Thorleifsson, Gudmar
    Luan, Jian'an
    Donnelly, Louise A.
    Kanoni, Stavroula
    Petersen, Ann -Kristin
    Pihurl, Vasyl
    Strawbridge, Rona J.
    Shungin, Dmitry
    Umeå University, Faculty of Medicine, Department of Odontology. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Medicine. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden.
    Hughes, Maria F.
    Meirelles, Osorio
    Kaakinen, Marika
    Bouatia-Naji, Nabila
    Kristiansson, Kati
    Shah, Sonia
    Kleber, Marcus E.
    Guo, Xiuqing
    Lyytikainen, Leo-Pekka
    Fava, Cristiano
    Eriksson, Nidas
    Nolte, Ilja M.
    Magnusson, Patrik K.
    Salfati, Elias L.
    Rallidis, Loukianos S.
    Theusch, Elizabeth
    Smith, Andrew J. P.
    Folkersen, Lasse
    Witkowska, Kate
    Pers, Tune H.
    Joehanes, Roby
    Kim, Stuart K.
    Lataniotis, Lazaros
    Jansen, Rick
    Johnson, Andrew D.
    Warren, Helen
    Kim, Young Jin
    Zhao, Wei
    Wu, Ying
    Tayo, Bamidele O.
    Bochud, Murielle
    Absher, Devin
    Adair, Linda S.
    Amin, Najaf
    Arkingl, Dan E.
    Axelsson, Tomas
    Baldassarre, Damian
    Balkau, Beverley
    Bandinelli, Stefania
    Barnes, Michael R.
    Barroso, Ines
    Bevan, Stephen
    Bis, Joshua C.
    Bjornsdottir, Gyda
    Boehnke, Michael
    Boerwinkle, Eric
    Bonnycastle, Lori L.
    Boomsma, Dorret I.
    Bornstein, Stefan R.
    Brown, Morris J.
    Burnier, Michel
    Cabrera, Claudia P.
    Chambers, John C.
    Chang, I-Shou
    Cheng, Ching-Yu
    Chines, Peter S.
    Chung, Ren-Hua
    Collins, Francis S.
    Connell, John M.
    Doring, Angela
    Dallongeville, Jean
    Danesh, John
    de Faire, Ulf
    Delgado, Graciela
    Dominiczak, Anna F.
    Doney, Alex S. F.
    Drenos, Fotios
    Edkins, Sarah
    Eicher, John D.
    Elosua, Roberto
    Enroth, Stefan
    Erdmann, Jeanette
    Eriksson, Per
    Esko, Tonu
    Evangelou, Evangelos
    Evans, Alun
    Fai, Tove
    Farra, Martin
    Felixl, Janine F.
    Ferrieres, Jean
    Ferrucci, Luigi
    Fornage, Myriam
    Forrester, Terrence
    Franceschinil, Nora
    Franco, Oscar H.
    Franco-Cereceda, Anders
    Fraser, Ross M.
    Ganesh, Santhi K.
    Gao, He
    Gertow, Karl
    Gianfagna, Francesco
    Gigante, Bruna
    Giulianini, Franco
    Goe, Anuj
    Goodall, Alison H.
    Goodarzi, Mark
    Gorski, Mathias
    Grassler, Jurgen
    Groves, Christopher J.
    Gudnason, Vilmundur
    Gyllensten, Ulf
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Biobank Research.
    Hartikainen, Anna-Liisa
    Hassinen, Maija
    Havulinna, Aki S.
    Hayward, Caroline
    Hercberg, Serge
    Herzig, Karl-Heinz
    Hicks, Andrew A.
    Hingorani, Aroon D.
    Hirschhorn, Joel N.
    Hofmanl, Albert
    Holmen, Jostein
    Holmen, Oddgeir Lingaas
    Hottenga, Jouke-Jan
    Howard, Phil
    Hsiung, Chao A.
    Hunt, Steven C.
    Ikram, M. Arfan
    Illig, Thomas
    Iribarren, Carlos
    Jensen, Richard A.
    Kahonen, Mika
    Kang, Hyun Min
    Kathiresan, Sekar
    Keating, Brendan J.
    Khaw, Kay-Tee
    Kim, Yun Kyoung
    Kim, Eric
    Kivimaki, Mika
    Klopp, Norman
    Kolovou, Genovefa
    Komulainen, Pirjo
    Kooner, Jaspal S.
    Kosova, Gulum
    Krauss, Ronald M.
    Kuh, Diana
    Kutalik, Zoltan
    Kuusisto, Johanna
    Kvaloy, Kirsti
    Lakka, Timo A.
    Lee, Nanette R.
    Lee, I-Te
    Lee, Wen-Jane
    Levy, Daniel
    Li, Xiaohui
    Liang, Kae-Woei
    Lin, Honghuang
    Lin, Li
    Lindstrom, Jaana
    Lobbens, Stephane
    Mannisto, Satu
    Muller, Gabriele
    Muller-Nurasyid, Martina
    Mach, Francois
    Markus, Hugh S.
    Marouli, Eirini
    McCarthy, Mark I.
    McKenzie, Colin A.
    Meneton, Pierre
    Menni, Cristina
    Metspalu, Andres
    Mijatovic, Vladan
    Moilanen, Leena
    Montasser, May E.
    Morris, Andrew D.
    Morrison, Alanna C.
    Mulas, Antonella
    Nagaraja, Ramaiah
    Narisu, Narisu
    Nikus, Kjell
    O'Donnell, Christopher J.
    O'Reilly, Paul F.
    Ong, Ken K.
    Paccaud, Fred
    Palmer, Cameron D.
    Parsa, Afshin
    Pedersen, Nancy L.
    Penninx, Brenda W.
    Perola, Markus
    Peters, Annette
    Poulter, Neil
    Pramstaller, Peter P.
    Psaty, Bruce M.
    Quertermous, Thomas
    Rao, Dabeeru C.
    Rasheed, Asif
    Rayner, N. William
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden.
    Rettig, Rainer
    Rice, Kenneth M.
    Roberts, Robert
    Rose, Lynda M.
    Rossouw, Jacques
    Samani, Nilesh J.
    Sanna, Serena
    Saramies, Jouko
    Schunkert, Heribert
    Sebert, Sylvain
    Sheu, Wayne H-H
    Shin, Young-Ah
    Sim, Xueling
    Smit, Johannes H.
    Smith, Albert V.
    Sosa, Maria X.
    Spector, Tim D.
    Stancakova, Alena
    Stanton, Alice V.
    Stirrups, Kathleen E.
    Stringham, Heather M.
    Sundstrom, Johan
    Swift, Amy J.
    Syvanen, Ann-Christine
    Tai, E-Shyong
    Tanaka, Toshiko
    Tarasov, Kirill V.
    Teumer, Alexander
    Thorsteinsdottir, Unnur
    Tobin, Martin D.
    Tremoli, Elena
    Uitterlinden, Andre G.
    Uusitupa, Matti
    Vaez, Ahmad
    Vaidya, Dhananjay
    van Duijn, Cornelia M.
    van Iperen, Erik P. A.
    Vasan, Ramachandran S.
    Verwoert, Germaine C.
    Virtamo, Jarmo
    Vitart, Veronique
    Voight, Benjamin F.
    Vollenweider, Peter
    Wagner, Aline
    Wain, Louise V.
    Wareham, Nicholas J.
    Watldns, Hugh
    Weder, Alan B.
    Westra, Harm Jan
    Wilks, Rainford
    Wilsgaard, Tom
    Wilson, James F.
    Wong, Tien Y.
    Yang, Tsun-Po
    Yao, Jie
    Yengo, Loic
    Zhang, Weihua
    Zhao, Jing Hua
    Zhu, Xiaofeng
    Bovet, Pascal
    Cooper, Richard S.
    Mohlke, Karen L.
    Saleheen, Danish
    Lee, Jong-Young
    Elliott, Paul
    Gierman, Hinco J.
    Willer, Cristen J.
    Franke, Lude
    Hovingh, G. Kees
    Taylor, Kent D.
    Dedoussis, George
    Sever, Peter
    Wong, Andrew
    Lind, Lars
    Assimes, Themistocles L.
    Njolstad, Inger
    Schwarz, Peter E. H.
    Langenberg, Claudia
    Snieder, Harold
    Caulfield, Mark J.
    Melander, E.
    Laakso, Markku
    Saltevo, Juha
    Rauramaa, Rainer
    Tuomilehto, Jaakko
    Ingelsson, Erik
    Lehtimaki, Terho
    Hveem, Kristian
    Palmas, Walter
    Marz, Winfried
    Kumar, Meena
    Salomaa, Veikko
    Chen, Yii-Der I.
    Rotter, Jerome I.
    Froguel, Philippe
    Jarvelin, Marjo-Riitta
    Lakatta, Edward G.
    Kuulasmaa, Kari
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
    Hamsten, Anders
    Wichmann, H-Erich
    Palmer, Colin N. A.
    Stefansson, Kari
    Ridker, Paul M.
    Loos, Ruth J. F.
    Chalcravarti, Aravinda
    Deloukas, Panos
    Morris, Andrew P.
    Newton-Cheh, Christopher
    Munroe, Patricia B.
    The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals2016In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 48, no 10, p. 1171-1184Article in journal (Refereed)
    Abstract [en]

    To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure-associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target organ damage in multiple tissues but with minor effects in the kidney. Our findings expand current knowledge of blood pressure-related pathways and highlight tissues beyond the classical renal system in blood pressure regulation.

  • 13. Erzurumluoglu, A. Mesut
    et al.
    Liu, Mengzhen
    Jackson, Victoria E.
    Barnes, Daniel R.
    Datta, Gargi
    Melbourne, Carl A.
    Young, Robin
    Batini, Chiara
    Surendran, Praveen
    Jiang, Tao
    Adnan, Sheikh Daud
    Afaq, Saima
    Agrawal, Arpana
    Altmaier, Elisabeth
    Antoniou, Antonis C.
    Asselbergs, Folkert W.
    Baumbach, Clemens
    Bierut, Laura
    Bertelsen, Sarah
    Boehnke, Michael
    Bots, Michiel L
    Brazel, David M
    Chambers, John C
    Chang-Claude, Jenny
    Chen, Chu
    Corley, Janie
    Chou, Yi-Ling
    David, Sean P
    de Boer, Rudolf A
    de Leeuw, Christiaan A
    Dennis, Joe G
    Dominiczak, Anna F
    Dunning, Alison M
    Easton, Douglas F
    Eaton, Charles
    Elliott, Paul
    Evangelou, Evangelos
    Faul, Jessica D
    Foroud, Tatiana
    Goate, Alison
    Gong, Jian
    Grabe, Hans J
    Haessler, Jeff
    Haiman, Christopher
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Hammerschlag, Anke R
    Harris, Sarah E
    Hattersley, Andrew
    Heath, Andrew
    Hsu, Chris
    Iacono, William G
    Kanoni, Stavroula
    Kapoor, Manav
    Kaprio, Jaakko
    Kardia, Sharon L
    Karpe, Fredrik
    Kontto, Jukka
    Kooner, Jaspal S
    Kooperberg, Charles
    Kuulasmaa, Kari
    Laakso, Markku
    Lai, Dongbing
    Langenberg, Claudia
    Le, Nhung
    Lettre, Guillaume
    Loukola, Anu
    Luan, Jian'an
    Madden, Pamela A F
    Mangino, Massimo
    Marioni, Riccardo E
    Marouli, Eirini
    Marten, Jonathan
    Martin, Nicholas G
    McGue, Matt
    Michailidou, Kyriaki
    Mihailov, Evelin
    Moayyeri, Alireza
    Moitry, Marie
    Müller-Nurasyid, Martina
    Naheed, Aliya
    Nauck, Matthias
    Neville, Matthew J
    Nielsen, Sune Fallgaard
    North, Kari
    Perola, Markus
    Pharoah, Paul D P
    Pistis, Giorgio
    Polderman, Tinca J
    Posthuma, Danielle
    Poulter, Neil
    Qaiser, Beenish
    Rasheed, Asif
    Reiner, Alex
    Renstrom, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Genetic and Molecular Epidemiology Unit, Lund University.
    Rice, John
    Rohde, Rebecca
    Rolandsson, Olov
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Samani, Nilesh J
    Samuel, Maria
    Schlessinger, David
    Scholte, Steven H
    Scott, Robert A
    Sever, Peter
    Shao, Yaming
    Shrine, Nick
    Smith, Jennifer A
    Starr, John M
    Stirrups, Kathleen
    Stram, Danielle
    Stringham, Heather M
    Tachmazidou, Ioanna
    Tardif, Jean-Claude
    Thompson, Deborah J
    Tindle, Hilary A
    Tragante, Vinicius
    Trompet, Stella
    Turcot, Valerie
    Tyrrell, Jessica
    Vaartjes, Ilonca
    van der Leij, Andries R
    van der Meer, Peter
    Varga, Tibor V
    Verweij, Niek
    Völzke, Henry
    Wareham, Nicholas J
    Warren, Helen R
    Weir, David R
    Weiss, Stefan
    Wetherill, Leah
    Yaghootkar, Hanieh
    Yavas, Ersin
    Jiang, Yu
    Chen, Fang
    Zhan, Xiaowei
    Zhang, Weihua
    Zhao, Wei
    Department of Biostatistics and Epidemiology, University of Pennsylvania, Pennsylvania, PA, USA.
    Zhao, Wei
    Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
    Zhou, Kaixin
    Amouyel, Philippe
    Blankenberg, Stefan
    Caulfield, Mark J
    Chowdhury, Rajiv
    Cucca, Francesco
    Deary, Ian J
    Deloukas, Panos
    Di Angelantonio, Emanuele
    Ferrario, Marco
    Ferrières, Jean
    Franks, Paul W
    Frayling, Tim M
    Frossard, Philippe
    Hall, Ian P
    Hayward, Caroline
    Jansson, Jan-Håkan
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Medicine. Department of Public Health and Clinical Medicine, Skellefteå Research Unit, Umeå University, Umeå, Sweden..
    Jukema, J Wouter
    Kee, Frank
    Männistö, Satu
    Metspalu, Andres
    Munroe, Patricia B
    Nordestgaard, Børge Grønne
    Palmer, Colin N A
    Salomaa, Veikko
    Sattar, Naveed
    Spector, Timothy
    Strachan, David Peter
    van der Harst, Pim
    Zeggini, Eleftheria
    Saleheen, Danish
    Butterworth, Adam S
    Wain, Louise V
    Abecasis, Goncalo R
    Danesh, John
    Tobin, Martin D
    Vrieze, Scott
    Liu, Dajiang J
    Howson, Joanna M M
    Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci2020In: Molecular Psychiatry, ISSN 1359-4184, E-ISSN 1476-5578, Vol. 25, no 10, p. 2392-2409Article in journal (Refereed)
    Abstract [en]

    Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P < 5 × 10-8 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 × 10-8) in the discovery samples. Ten novel SNVs, including rs12616219 near TMEM182, were followed-up and five of them (rs462779 in REV3L, rs12780116 in CNNM2, rs1190736 in GPR101, rs11539157 in PJA1, and rs12616219 near TMEM182) replicated at a Bonferroni significance threshold (P < 4.5 × 10-3) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2. Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.

    Download full text (pdf)
    fulltext
  • 14.
    Estampador, Angela C.
    et al.
    Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Skåne University Hospital, Lund University, Malmö, Sweden .
    Pomeroy, Jeremy
    Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Skåne University Hospital, Lund University, Malmö, Sweden ; Phoenix Epidemiology and Clinical Research Branch, National Institutes of Health, Phoenix, AZ .
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Skåne University Hospital, Lund University, Malmö, Sweden .
    Nelson, Scott M.
    Reproductive and Maternal Medicine, Faculty of Medicine, University of Glasgow, Glasgow, U.K..
    Mogren, Ingrid
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Obstetrics and Gynaecology.
    Persson, Margareta
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Obstetrics and Gynaecology. Dalarna University, School of Health and Social Studies, Falun, Sweden.
    Sattar, Naveed
    British Heart Foundation Cardiovascular Research Center, University of Glasgow, Glasgow, U.K..
    Domellöf, Magnus
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Skåne University Hospital, Lund University, Malmö, Sweden ; Department of Nutrition, Harvard School of Public Health, Boston, MA.
    Infant body composition and adipokine concentrations in relation to maternal gestational weight gain2014In: Diabetes Care, ISSN 0149-5992, E-ISSN 1935-5548, Vol. 37, no 5, p. 1432-1438Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE: To investigate associations of maternal gestational weight gain and body composition and their impact on offspring body composition and adipocytokine, glucose, and insulin concentrations at age 4 months. RESEARCH DESIGN AND METHODS: This was a prospective study including 31 mother-infant pairs (N = 62). Maternal body composition was assessed using doubly labeled water. Infant body composition was assessed at 4 months using air displacement plethysmography, and venous blood was assayed for glucose, insulin, adiponectin, interleukin-6 (IL-6), and leptin concentrations. RESULTS: Rate of gestational weight gain in midpregnancy was significantly associated with infant fat mass (r = 0.41, P = 0.03); rate of gestational weight in late pregnancy was significantly associated with infant fat-free mass (r = 0.37, P = 0.04). Infant birth weight was also strongly correlated with infant fat-free mass at 4 months (r = 0.63, P = 0.0002). Maternal BMI and maternal fat mass were strongly inversely associated with infant IL-6 concentrations (r = -0.60, P = 0.002 and r = -0.52, P = 0.01, respectively). Infant fat-free mass was inversely related to infant adiponectin concentrations (r = -0.48, P = 0.008) and positively correlated with infant blood glucose adjusted for insulin concentrations (r = 0.42, P = 0.04). No significant associations for leptin were observed. CONCLUSIONS: Timing of maternal weight gain differentially impacts body composition of the 4-month-old infant, which in turn appears to affect the infant's glucose and adipokine concentrations.

  • 15. Fontaine-Bisson, B
    et al.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Rolandsson, Olov
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Payne, F
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Barroso, I
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Evaluating the discriminative power of multi-trait genetic risk scores for type 2 diabetes in a northern Swedish population.2010In: Diabetologia, ISSN 0012-186X, E-ISSN 1432-0428, Vol. 53, no 10, p. 2155-2162Article in journal (Refereed)
    Abstract [en]

    AIMS/HYPOTHESIS: We determined whether single nucleotide polymorphisms (SNPs) previously associated with diabetogenic traits improve the discriminative power of a type 2 diabetes genetic risk score. METHODS: Participants (n = 2,751) were genotyped for 73 SNPs previously associated with type 2 diabetes, fasting glucose/insulin concentrations, obesity or lipid levels, from which five genetic risk scores (one for each of the four traits and one combining all SNPs) were computed. Type 2 diabetes patients and non-diabetic controls (n = 1,327/1,424) were identified using medical records in addition to an independent oral glucose tolerance test. RESULTS: Model 1, including only SNPs associated with type 2 diabetes, had a discriminative power of 0.591 (p < 1.00 x 10(-20) vs null model) as estimated by the area under the receiver operator characteristic curve (ROC AUC). Model 2, including only fasting glucose/insulin SNPs, had a significantly higher discriminative power than the null model (ROC AUC 0.543; p = 9.38 x 10(-6) vs null model), but lower discriminative power than model 1 (p = 5.92 x 10(-5)). Model 3, with only lipid-associated SNPs, had significantly higher discriminative power than the null model (ROC AUC 0.565; p = 1.44 x 10(-9)) and was not statistically different from model 1 (p = 0.083). The ROC AUC of model 4, which included only obesity SNPs, was 0.557 (p = 2.30 x 10(-7) vs null model) and smaller than model 1 (p = 0.025). Finally, the model including all SNPs yielded a significant improvement in discriminative power compared with the null model (p < 1.0 x 10(-20)) and model 1 (p = 1.32 x 10(-5)); its ROC AUC was 0.626. CONCLUSIONS/INTERPRETATION: Adding SNPs previously associated with fasting glucose, insulin, lipids or obesity to a genetic risk score for type 2 diabetes significantly increases the power to discriminate between people with and without clinically manifest type 2 diabetes compared with a model including only conventional type 2 diabetes loci.

    Download full text (pdf)
    fulltext
  • 16.
    Franks, Paul W.
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine. Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Skåne University Hospital, Malmö, Sweden; Department of Nutrition, Harvard T.H. Chan School of Public Health, MA, Boston, United States.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Skåne University Hospital, Malmö, Sweden.
    Using genotype-based recall to estimate the effects of amy1 copy number variation in substrate metabolism2016In: Diabetes, ISSN 0012-1797, E-ISSN 1939-327X, Vol. 65, no 11, p. 3240-3242Article in journal (Other academic)
  • 17. Fretts, Amanda M.
    et al.
    Follis, Jack L.
    Nettleton, Jennifer A.
    Lemaitre, Rozenn N.
    Ngwa, Julius S.
    Wojczynski, Mary K.
    Kalafati, Ioanna Panagiota
    Varga, Tibor V.
    Frazier-Wood, Alexis C.
    Houston, Denise K.
    Lahti, Jari
    Ericson, Ulrika
    van den Hooven, Edith H.
    Mikkilae, Vera
    Kiefte-de Jong, Jessica C.
    Mozaffarian, Dariush
    Rice, Kenneth
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research. Department of Clinical Sciences Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden.
    North, Kari E.
    McKeown, Nicola M.
    Feitosa, Mary F.
    Kanoni, Stavroula
    Smith, Caren E.
    Garcia, Melissa E.
    Tiainen, Anna-Maija
    Sonestedt, Emily
    Manichaikul, Ani
    van Rooij, Frank J. A.
    Dimitriou, Maria
    Raitakari, Olli
    Pankow, James S.
    Djousse, Luc
    Province, Michael A.
    Hu, Frank B.
    Lai, Chao-Qiang
    Keller, Margaux F.
    Peraelae, Mia-Maria
    Rotter, Jerome I.
    Hofman, Albert
    Graff, Misa
    Kaehoenen, Mika
    Mukamal, Kenneth
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Odontology. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research. Umeå University, Faculty of Medicine, Department of Biobank Research.
    Ordovas, Jose M.
    Liu, Yongmei
    Maennistoe, Satu
    Uitterlinden, Andre G.
    Deloukas, Panos
    Seppaelae, Ilkka
    Psaty, Bruce M.
    Cupples, L. Adrienne
    Borecki, Ingrid B.
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Department of Clinical Sciences Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden; Department of Nutrition, Harvard School of Public Health, Boston, MA.
    Arnett, Donna K.
    Nalls, Mike A.
    Eriksson, Johan G.
    Orho-Melander, Marju
    Franco, Oscar H.
    Lehtimaeki, Terho
    Dedoussis, George V.
    Meigs, James B.
    Siscovick, David S.
    Consumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians2015In: American Journal of Clinical Nutrition, ISSN 0002-9165, E-ISSN 1938-3207, Vol. 102, no 5, p. 1266-1278Article in journal (Refereed)
    Abstract [en]

    Background: Recent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown. Objective: We investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus. Design: Fourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined l) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations. Results: Processed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-1n-pmon (95% CI: 0.035, 0.063-1n-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance. Conclusion: The association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms.

  • 18.
    Gradmark, Anna M I
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Rydh, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    De Lucia-Rolfe, Emanuella
    Sleigh, Alison
    Nordström, Peter
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Geriatric Medicine.
    Brage, Sören
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Computed tomography-based validation of abdominal adiposity measurements from ultrasonography, dual-energy X-ray absorptiometry and anthropometry2010In: British Journal of Nutrition, ISSN 0007-1145, E-ISSN 1475-2662, Vol. 104, no 4, p. 582-588Article in journal (Refereed)
    Abstract [en]

    Large-scale aetiological studies of obesity and its pathological consequences require accurate measurements of adipose mass, distribution and subtype. Here, we compared the validity of three abdominal obesity assessment methods (dual-energy X-ray absorptiometry (DXA), ultrasound and anthropometry) against the gold-standard method of computed tomography (CT) in twenty-nine non-diseased middle-aged men (BMI 26.5 (sd 3.1) kg/m(2)) and women (BMI 25.5 (sd 3.2) kg/m(2)). Assessments of adipose mass (kg) and distribution (total subcutaneous (TSAT), superficial subcutaneous (SSAT), deep subcutaneous (DSAT) and visceral (VAT)) were obtained. Spearman's correlations were performed adjusted for age and sex. VAT area that was assessed using ultrasound (r 0.79; P < 0.0001) and waist circumference (r 0.85; P < 0.0001) correlated highly with VAT from CT, as did BMI (r 0.67; P < 0.0001) and DXA (r 0.70; P < 0.0001). DXA (r 0.72; P = 0.0004), BMI (r 0.71; P = 0.0003), waist circumference (r 0.86; P < 0.0001) and ultrasound (r 0.52; P = 0.015) were less strongly correlated with CT TSAT. None of the comparison measures of DSAT was strongly correlated with CT DSAT (all r approximately 0.50; P < 0.02). BMI (r 0.76; P < 0.0001), waist circumference (r 0.65; P = 0.002) and DXA (r 0.75; P < 0.0001) were all fairly strongly correlated with the CT measure of SSAT, whereas ultrasound yielded a weaker yet statistically significant correlation (r 0.48; P = 0.03). Compared with CT, visceral and subcutaneous adiposity can be assessed with reasonable validity using waist circumference and BMI, respectively. Ultrasound or DXA does not generally provide substantially better measures of these traits. Highly valid assessments of DSAT do not appear to be possible with surrogate measures. These findings may help guide the selection of measures for epidemiological studies of obesity.

  • 19.
    Gradmark, Anna
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Pomeroy, J
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Steiginga, S
    Persson, M
    Wright, A
    Bluck, L
    Domellöf, M
    Kahn, SE
    Mogren, I
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Physical activity, sedentary behaviors, and estimated insulin sensitivity and secretion in pregnant and non-pregnant women2011Other (Other academic)
    Abstract [en]

    Aims Overweight and obesity during pregnancy raise the risk of gestational diabetes and birth complications. Lifestyle factors such as physical activity may decrease these risks through beneficial effects on systemic glucose homeostasis. Here we examined physical activity patterns and their relationships with measures of glucose homeostasis in late pregnancy compared to non-pregnant women.

    Methods Normal weight and overweight women without diabetes (N=108; aged 25-35 years) were studied; 35 were pregnant (in gestational weeks 28-32) and 73 were non-pregnant. An oral glucose tolerance test was conducted from which insulin sensitivity and β-cell response were estimated. Physical activity was measured during 10-days of free-living using a combined heart rate sensor and accelerometer. Total (TEE), resting (REE), and physical activity (PAEE) energy expenditure were measured using doubly-labeled water and expired gas indirect calorimetry.

    Results Total activity (counts/day) was associated with a reduced first-phase insulin response in both pregnant (r=-0.47; 95% CI: -0.70- to -0.15) and non-pregnant women (r=-0.36; 95% CI: -0.56- to -0.12). Pregnant women were estimated to have secreted more insulin (p=0.002) and had lower fasting glucose than non-pregnant women (p<0.0001). Measures of overall

    physical activity intensity were similar in both groups (p=0.547), but pregnant women spent more time sedentary (p<0.0001), less time in moderate-to-vigorous intensity activity (p<0.0001), had lower objectively measured total activity, and had lower physical activity energy expenditure (PAEE) than non-pregnant women (p=0.045).

    Conclusions Our findings suggest that physical activity conveys similar benefits on glucose homeostasis in pregnant and non-pregnant women, despite differences in subcomponents of physical activity.

  • 20.
    Gradmark, Anna
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Pomeroy, Jeremy
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Steiginga, Susanne
    Free University Medical Center, Amsterdam, the Netherlands.
    Persson, Margareta
    Umeå University, Faculty of Medicine, Department of Nursing. Umeå University, Faculty of Medicine, Department of Clinical Sciences.
    Wright, Antony
    MRC Human Nutrition Research, Cambridge, UK..
    Bluck, Les
    MRC Human Nutrition Research, Cambridge, UK..
    Domellöf, Magnus
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Kahn, Steven E
    Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, VA Puget Sound Health Care System and University of Washington, Seattle, WA, USA .
    Mogren, Ingrid
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Obstetrics and Gynaecology.
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Physical activity, sedentary behaviors, and estimated insulin sensitivity and secretion in pregnant and non-pregnant women2011In: BMC Pregnancy and Childbirth, ISSN 1471-2393, E-ISSN 1471-2393, Vol. 11, no 1, p. 44-Article in journal (Refereed)
    Abstract [en]

    Background: Overweight and obesity during pregnancy raise the risk of gestational diabetes and birth complications. Lifestyle factors like physical activity may decrease these risks through beneficial effects on glucose homeostasis. Here we examined physical activity patterns and their relationships with measures of glucose homeostasis in late pregnancy compared to non-pregnant women.

    Methods: Normal weight and overweight women without diabetes (N=108; aged 25-35 years) were studied; 35 were pregnant (in gestational weeks 28-32) and 73 were non-pregnant. Insulin sensitivity and beta-cell response were estimated from an oral glucose tolerance test. Physical activity was measured during 10-days of free-living using a combined heart rate sensor and accelerometer. Total (TEE), resting (REE), and physical activity (PAEE) energy expenditure were measured using doubly-labeled water and expired gas indirect calorimetry.

    Results: Total activity was associated with reduced first-phase insulin response in both pregnant (Regression r2=0.11; Spearman r=-0.47; p=0.007) and non-pregnant women (Regression r2=0.11; Spearman; r=-0.36; p=0.002). Relative to non-pregnant women, pregnant women were estimated to have secreted 67% more insulin and had 10% lower fasting glucose than non-pregnant women. Pregnant women spent 13% more time sedentary, 71% less time in moderate-to-vigorous intensity activity, had 44% lower objectively measured total activity,and 12% lower PAEE than non-pregnant women. Correlations did not differ significantly for any comparison between physical activity subcomponents and measures of insulin sensitivity or secretion.

    Conclusions: Our findings suggest that physical activity conveys similar benefits on glucose homeostasis in pregnant and non-pregnant women, despite differences in subcomponents of physical activity.

  • 21. Graff, Mariaelisa
    et al.
    Scott, Robert A.
    Justice, Anne E.
    Young, Kristin L.
    Feitosa, Mary F.
    Barata, Llilda
    Winkler, Thomas W.
    Chu, Audrey Y.
    Mahajan, Anubha
    Hadley, David
    Xue, Luting
    Workalemahu, Tsegaselassie
    Heard-Costa, Nancy L.
    den Hoed, Marcel
    Ahluwalia, Tarunveer S.
    Qi, Qibin
    Ngwa, Julius S.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Lund Univ, Genet & Mol Epidemiol Unit, Dept Clin Sci, Malmo, Sweden.
    Quaye, Lydia
    Eicher, John D.
    Hayes, James E.
    Cornelis, Marilyn
    Kutalik, Zoltan
    Lim, Elise
    Luan, Jian'an
    Huffman, Jennifer E.
    Zhang, Weihua
    Zhao, Wei
    Griffin, Paula J.
    Haller, Toomas
    Ahmad, Shafqat
    Marques-Vidal, Pedro M.
    Bien, Stephanie
    Yengo, Loic
    Teumer, Alexander
    Smith, Albert Vernon
    Kumari, Meena
    Harder, Marie Neergaard
    Justesen, Johanne Marie
    Kleber, Marcus E.
    Hollensted, Mette
    Lohman, Kurt
    Rivera, Natalia V.
    Whitfield, John B.
    Zhao, Jing Hua
    Stringham, Heather M.
    Lyytikainen, Leo-Pekka
    Huppertz, Charlotte
    Willemsen, Gonneke
    Peyrot, Wouter J.
    Wu, Ying
    Kristiansson, Kati
    Demirkan, Ayse
    Fornage, Myriam
    Hassinen, Maija
    Bielak, Lawrence F.
    Cadby, Gemma
    Tanaka, Toshiko
    Magl, Reedlk
    Van der Most, Peter J.
    Jackson, Anne U.
    Bragg-Gresham, Jennifer L.
    Vitart, Veronique
    Marten, Jonathan
    Navarro, Pau
    Bellis, Claire
    Pasko, Dorota
    Johansson, Asa
    Snitker, Soren
    Cheng, Yu-Ching
    Eriksson, Joel
    Lim, Unhee
    Aadahl, Mette
    Adair, Linda S.
    Amin, Najaf
    Balkau, Beverley
    Auvinen, Juha
    Beilby, John
    Bergman, Richard N.
    Bergmann, Sven
    Bertoni, Alain G.
    Blangero, John
    Bonnefond, Amelle
    Bonnycastle, Lori L.
    Borja, Judith B.
    Brage, Soren
    Busonero, Fabio
    Buyske, Steve
    Campbell, Harry
    Chines, Peter S.
    Collins, Francis S.
    Corre, Tanguy
    Smith, George Davey
    Delgado, Graciela E.
    Dueker, Nicole
    Doerr, Marcus
    Ebeling, Tapani
    Eiriksdottir, Gudny
    Esko, Tonu
    Faul, Jessica D.
    Fu, Mao
    Faerch, Kristine
    Gieger, Christian
    Glaeser, Sven
    Gong, Jian
    Gordon-Larsen, Penny
    Grallert, Harald
    Grammer, Tanja B.
    Grarup, Niels
    van Grootheest, Gerard
    Harald, Kennet
    Hastie, Nicholas D.
    Havulinna, Aki S.
    Hernandez, Dena
    Hindorff, Lucia
    Hocking, Lynne J.
    Holmens, Oddgeir L.
    Holzapfel, Christina
    Hottenga, Jouke Jan
    Huang, Jie
    Huang, Tao
    Hui, Jennie
    Huth, Cornelia
    Hutri-Kahonen, Nina
    James, Alan L.
    Jansson, John-Olov
    Jhun, Min A.
    Juonala, Markus
    Kinnunen, Leena
    Koistinen, Heikki A.
    Kolcic, Ivana
    Komulainen, Pirjo
    Kuusisto, Johanna
    Kvaloy, Kirsti
    Kahonen, Mika
    Lakka, Timo A.
    Launer, Lenore J.
    Lehne, Benjamin
    Lindgren, Cecilia M.
    Lorentzon, Mattias
    Luben, Robert
    Marre, Michel
    Milaneschi, Yuri
    Monda, Keri L.
    Montgomery, Grant W.
    De Moor, Marleen H. M.
    Mulas, Antonella
    Mueller-Nurasyid, Martina
    Musk, A. W.
    Mannikko, Reija
    Mannisto, Satu
    Narisu, Narisu
    Nauck, Matthias
    Nettleton, Jennifer A.
    Nolte, Ilja M.
    Oldehinkel, Albertine J.
    Olden, Matthias
    Ong, Ken K.
    Padmanabhan, Sandosh
    Paternoster, Lavinia
    Perez, Jeremiah
    Perola, Markus
    Peters, Annette
    Peters, Ulrike
    Peyser, Patricia A.
    Prokopenko, Inga
    Puolijoki, Hannu
    Raitakari, Olli T.
    Rankinen, Tuomo
    Rasmussen-Torvik, Laura J.
    Rawal, Rajesh
    Ridker, Paul M.
    Rose, Lynda M.
    Rudan, Igor
    Sarti, Cinzia
    Sarzynski, Mark A.
    Savonen, Kai
    Scott, William R.
    Sanna, Serena
    Shuldiner, Alan R.
    Sidney, Steve
    Silbernagel, Guenther
    Smith, Blair H.
    Smith, Jennifer A.
    Snieder, Harold
    Stancakova, Alena
    Sternfeld, Barbara
    Swift, Amy J.
    Tammelin, Tuija
    Tan, Sian-Tsung
    Thorand, Barbara
    Thuillier, Dorothee
    Vandenput, Liesbeth
    Vestergaard, Henrik
    van Vliet-Ostaptchouk, Jana V.
    Vohl, Marie-Claude
    Voelker, Uwe
    Waeber, Gerard
    Walker, Mark
    Wild, Sarah
    Wong, Andrew
    Wright, Alan F.
    Zillikens, M. Carola
    Zubair, Niha
    Haiman, Christopher A.
    Lemarchand, Loic
    Gyllensten, Ulf
    Ohlsson, Claes
    Hofman, Albert
    Rivadeneira, Fernando
    Uitterlinden, Andre G.
    Perusse, Louis
    Wilson, James F.
    Hayward, Caroline
    Polasek, Ozren
    Cucca, Francesco
    Hveem, Kristian
    Hartman, Catharina A.
    Toenjes, Anke
    Bandinelli, Stefania
    Palmer, Lyle J.
    Kardia, Sharon L. R.
    Rauramaa, Rainer
    Sorensen, Thorkild I. A.
    Tuomilehto, Jaakko
    Salomaa, Veikko
    Penninx, Brenda W. J. H.
    de Geus, Eco J. C.
    Boomsma, Dorret I.
    Lehtimaki, Terho
    Mangino, Massimo
    Laakso, Markku
    Bouchard, Claude
    Martin, Nicholas G.
    Kuh, Diana
    Liu, Yongmei
    Linneberg, Allan
    Maerz, Winfried
    Strauch, Konstantin
    Kivimaki, Mika
    Harris, Tamara B.
    Gudnason, Vilmundur
    Voelzke, Henry
    Qi, Lu
    Jarvelin, Marjo-Riitta
    Chambers, John C.
    Kooner, Jaspal S.
    Froguel, Philippe
    Kooperberg, Charles
    Vollenweider, Peter
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Biobank Research.
    Hansen, Torben
    Pedersen, Oluf
    Metspalu, Andres
    Wareham, Nicholas J.
    Langenberg, Claudia
    Weir, David R.
    Porteous, David J.
    Boerwinkle, Eric
    Chasman, Daniel I.
    Abecasis, Goncalo R.
    Barroso, Ines
    McCarthy, Mark I.
    Frayling, Timothy M.
    O'Connell, Jeffrey R.
    van Duijn, Cornelia M.
    Boehnke, Michael
    Heid, Iris M.
    Mohlke, Karen L.
    Strachan, David P.
    Fox, Caroline S.
    Liu, Ching-Ti
    Hirschhorn, Joel N.
    Klein, Robert J.
    Johnson, Andrew D.
    Borecki, Ingrid B.
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Harvard TH Chan Sch Publ Hlth, Dept Nutr, Boston, MA USA ; Lund Univ, Genet & Mol Epidemiol Unit, Dept Clin Sci, Malmo, Sweden.
    North, Kari E.
    Cupples, L. Adrienne
    Loos, Ruth J. F.
    Kilpelainen, Tuomas O.
    Genome-wide physical activity interactions in adiposity. A meta-analysis of 200,452 adults2017In: PLOS Genetics, ISSN 1553-7390, E-ISSN 1553-7404, Vol. 13, no 4, article id e1006528Article in journal (Refereed)
    Abstract [en]

    Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by similar to 30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

    Download full text (pdf)
    fulltext
  • 22. Grøntved, Anders
    et al.
    Koivula, Robert W
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Odontology.
    Wennberg, Patrik
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Østergaard, Lars
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Biobank Research. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University Skåne University Hospital Malmö, Malmö, Sweden.
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Biobank Research. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University Skåne University Hospital Malmö, Malmö, Sweden.
    Bicycling to Work and Primordial Prevention of Cardiovascular Risk: A Cohort Study Among Swedish Men and Women2016In: Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, ISSN 2047-9980, E-ISSN 2047-9980, Vol. 5, no 11, article id e004413Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Bicycling to work may be a viable approach for achieving physical activity that provides cardiovascular health benefits. In this study we investigated the relationship of bicycling to work with incidence of obesity, hypertension, hypertriglyceridemia, and impaired glucose tolerance across a decade of follow-up in middle-aged men and women.

    METHODS AND RESULTS: We followed 23 732 Swedish men and women with a mean age of 43.5 years at baseline who attended a health examination twice during a 10-year period (1990-2011). In multivariable adjusted models we calculated the odds of incident obesity, hypertension, hypertriglyceridemia, and impaired glucose tolerance, comparing individuals who commuted to work by bicycle with those who used passive modes of transportation. We also examined the relationship of change in commuting mode with incidence of these clinical risk factors. Cycling to work at baseline was associated with lower odds of incident obesity (odds ratio [OR]=0.85, 95% CI 0.73-0.99), hypertension (OR=0.87, 95% CI 0.79-0.95), hypertriglyceridemia (OR=0.85, 95% CI 0.76-0.94), and impaired glucose tolerance (OR=0.88, 95% CI 0.80-0.96) compared with passive travel after adjusting for putative confounding factors. Participants who maintained or began bicycling to work during follow-up had lower odds of obesity (OR=0.61, 95% CI 0.50-0.73), hypertension (OR=0.89, 95% CI 0.80-0.98), hypertriglyceridemia (OR=0.80, 95% CI 0.70-0.90), and impaired glucose tolerance (OR=0.82, 95% CI 0.74-0.91) compared with participants not cycling to work at both times points or who switched from cycling to other modes of transport during follow-up.

    CONCLUSIONS: These data suggest that commuting by bicycle to work is an important strategy for primordial prevention of clinical cardiovascular risk factors among middle-aged men and women.

    Download full text (pdf)
    fulltext
  • 23. Huang, Tao
    et al.
    Ding, Ming
    Bergholdt, Helle K. M.
    Wang, Tiange
    Heianza, Yoriko
    Sun, Dian-jianyi
    Frazier-Wood, Alexis C.
    Aslibekyan, Stella
    North, Kari E.
    Voortman, Trudy
    Graff, Mariaelisa
    Smith, Caren E.
    Lai, Chao-Qiang
    Varbo, Anette
    Lemaitre, Rozenn N.
    de Jonge, M. Ester A. L.
    Fumeron, Fredric
    Corella, Dolores
    Wang, Carol A.
    Tjonneland, Anne
    Overvad, Kim
    Sorensen, Thorkild I. A.
    Feitosa, Mary F.
    Wojczynski, Mary K.
    Kahonen, Mika
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.
    Psaty, Bruce M.
    Siscovick, David S.
    Barroso, Ines
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Odontology.
    Hernandez, Dena
    Ferrucci, Luigi
    Bandinelli, Stefania
    Linneberg, Allan
    Zillikens, M. Carola
    Sandholt, Camilla Helene
    Pedersen, Oluf
    Hansen, Torben
    Schulz, Christina-Alexandra
    Sonestedt, Emily
    Orho-Melander, Marju
    Chen, Tzu-An
    Rotter, Jerome I.
    Allison, Mathew A.
    Rich, Stephen S.
    Sorli, Jose V.
    Coltell, Oscar
    Pennell, Craig E.
    Eastwood, Peter
    Hofman, Albert
    Uitterlinden, Andre G.
    van Rooij, Frank J. A.
    Chu, Audrey Y.
    Rose, Lynda M.
    Ridker, Paul M.
    Viikari, Jorma
    Raitakari, Olli
    Lehtimaki, Terho
    Mikkila, Vera
    Willett, Walter C.
    Wang, Yujie
    Tucker, Katherine L.
    Ordovas, Jose M.
    Kilpelainen, Tuomas O.
    Province, Michael A.
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Department of Nutrition, Harvard School of Public Health, Boston, MA; Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.
    Arnett, Donna K.
    Tanaka, Toshiko
    Toft, Ulla
    Ericson, Ulrika
    Franco, Oscar H.
    Mozaffarian, Dariush
    Hu, Frank B.
    Chasman, Daniel I.
    Nordestgaard, Borge G.
    Ellervik, Christina
    Qi, Lu
    Dairy Consumption and Body Mass Index Among Adults: Mendelian Randomization Analysis of 184802 Individuals from 25 Studies2018In: Clinical Chemistry, ISSN 0009-9147, E-ISSN 1530-8561, Vol. 64, no 1, p. 183-191Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Associations between dairy intake and body mass index (BMI) have been inconsistently observed in epidemiological studies, and the causal relationship remains ill defined.

    METHODS: We performed Mendelian randomization (MR) analysis using an established dairy intake-associated genetic polymorphism located upstream of the lactase gene (LCT-13910 C/T, rs4988235) as an instrumental variable (IV). Linear regression models were fitted to analyze associations between (a) dairy intake and BMI, (b) rs4988235 and dairy intake, and (c) rs4988235 and BMI in each study. The causal effect of dairy intake on BMI was quantified by IV estimators among 184802 participants from 25 studies.

    RESULTS: Higher dairy intake was associated with higher BMI (β = 0.03 kg/m2 per serving/day; 95% CI, 0.00–0.06; P = 0.04), whereas the LCT genotype with 1 or 2 T allele was significantly associated with 0.20 (95% CI, 0.14–0.25) serving/day higher dairy intake (P = 3.15 × 10−12) and 0.12 (95% CI, 0.06–0.17) kg/m2 higher BMI (P = 2.11 × 10−5). MR analysis showed that the genetically determined higher dairy intake was significantly associated with higher BMI (β = 0.60 kg/m2 per serving/day; 95% CI, 0.27–0.92; P = 3.0 × 10−4).

    CONCLUSIONS: The present study provides strong evidence to support a causal effect of higher dairy intake on increased BMI among adults.

  • 24. Jonsson, A
    et al.
    Renström, Frida
    Umeå University, Faculty of Medicine, Public Health and Clinical Medicine, Medicine.
    Lyssenko, V
    Brito, Ema C
    Umeå University, Faculty of Medicine, Public Health and Clinical Medicine, Medicine.
    Isomaa, B
    Berglund, G
    Nilsson, P M
    Groop, L
    Franks, Paul W
    Umeå University, Faculty of Medicine, Public Health and Clinical Medicine, Medicine.
    Assessing the effect of interaction between an FTO variant (rs9939609) and physical activity on obesity in 15,925 Swedish and 2,511 Finnish adults.2009In: Diabetologia, ISSN 0012-186X, E-ISSN 1432-0428, Vol. 52, no 7, p. 1334-1338Article in journal (Refereed)
    Abstract [en]

    AIMS/HYPOTHESIS: Recent reports have suggested that genotypes at the FTO locus interact with physical activity to modify levels of obesity-related traits. We tested this hypothesis in two non-diabetic population-based cohorts, the first from southern Sweden and the second from the Botnia region of western Finland. METHODS: In total 2,511 Finnish and 15,925 Swedish non-diabetic middle-aged adults were genotyped for the FTO rs9939609 variant. Physical activity was assessed by questionnaires and standard clinical procedures were conducted, including measures of height and weight and glucose regulation. Tests of gene x physical activity interaction were performed using linear interaction effects to determine whether the effect of this variant on BMI is modified by physical activity. RESULTS: The minor A allele at rs9939609 was associated with higher BMI in both cohorts, with the per allele difference in BMI being about 0.13 and 0.43 kg/m(2) in the Swedish and Finnish cohorts, respectively (p < 0.0001). The test of interaction between physical activity and the rs9939609 variant on BMI was not statistically significant after controlling for age and sex in either cohort (Sweden: p = 0.71, Finland: p = 0.18). CONCLUSIONS/INTERPRETATION: The present report does not support the notion that physical activity modifies the effects of the FTO rs9939609 variant on obesity risk in the non-diabetic Swedish or Finnish adults studied here.

  • 25. Justice, Anne E
    et al.
    Winkler, Thomas W
    Feitosa, Mary F
    Graff, Misa
    Fisher, Virginia A
    Young, Kristin
    Barata, Llilda
    Deng, Xuan
    Czajkowski, Jacek
    Hadley, David
    Ngwa, Julius S
    Ahluwalia, Tarunveer S
    Chu, Audrey Y
    Heard-Costa, Nancy L
    Lim, Elise
    Perez, Jeremiah
    Eicher, John D
    Kutalik, Zoltan
    Xue, Luting
    Mahajan, Anubha
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, SE-205 02 Malmö, Sweden.
    Wu, Joseph
    Qi, Qibin
    Ahmad, Shafqat
    Alfred, Tamuno
    Amin, Najaf
    Bielak, Lawrence F
    Bonnefond, Amelie
    Bragg, Jennifer
    Cadby, Gemma
    Chittani, Martina
    Coggeshall, Scott
    Corre, Tanguy
    Direk, Nese
    Eriksson, Joel
    Fischer, Krista
    Gorski, Mathias
    Neergaard Harder, Marie
    Horikoshi, Momoko
    Huang, Tao
    Huffman, Jennifer E
    Jackson, Anne U
    Justesen, Johanne Marie
    Kanoni, Stavroula
    Kinnunen, Leena
    Kleber, Marcus E
    Komulainen, Pirjo
    Kumari, Meena
    Lim, Unhee
    Luan, Jian'an
    Lyytikainen, Leo-Pekka
    Mangino, Massimo
    Manichaikul, Ani
    Marten, Jonathan
    Middelberg, Rita P S
    Muller-Nurasyid, Martina
    Navarro, Pau
    Perusse, Louis
    Pervjakova, Natalia
    Sarti, Cinzia
    Smith, Albert Vernon
    Smith, Jennifer A
    Stancakova, Alena
    Strawbridge, Rona J
    Stringham, Heather M
    Sung, Yun Ju
    Tanaka, Toshiko
    Teumer, Alexander
    Trompet, Stella
    van der Laan, Sander W
    van der Most, Peter J
    Van Vliet-Ostaptchouk, Jana V
    Vedantam, Sailaja L
    Verweij, Niek
    Vink, Jacqueline M
    Vitart, Veronique
    Wu, Ying
    Yengo, Loic
    Zhang, Weihua
    Hua Zhao, Jing
    Zimmermann, Martina E
    Zubair, Niha
    Abecasis, Goncalo R
    Adair, Linda S
    Afaq, Saima
    Afzal, Uzma
    Bakker, Stephan J L
    Bartz, Traci M
    Beilby, John
    Bergman, Richard N
    Bergmann, Sven
    Biffar, Reiner
    Blangero, John
    Boerwinkle, Eric
    Bonnycastle, Lori L
    Bottinger, Erwin
    Braga, Daniele
    Buckley, Brendan M
    Buyske, Steve
    Campbell, Harry
    Chambers, John C
    Collins, Francis S
    Curran, Joanne E
    de Borst, Gert J
    de Craen, Anton J M
    de Geus, Eco J C
    Dedoussis, George
    Delgado, Graciela E
    den Ruijter, Hester M
    Eiriksdottir, Gudny
    Eriksson, Anna L
    Esko, Tonu
    Faul, Jessica D
    Ford, Ian
    Forrester, Terrence
    Gertow, Karl
    Gigante, Bruna
    Glorioso, Nicola
    Gong, Jian
    Grallert, Harald
    Grammer, Tanja B
    Grarup, Niels
    Haitjema, Saskia
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Hamsten, Anders
    Hansen, Torben
    Harris, Tamara B
    Hartman, Catharina A
    Hassinen, Maija
    Hastie, Nicholas D
    Heath, Andrew C
    Hernandez, Dena
    Hindorff, Lucia
    Hocking, Lynne J
    Hollensted, Mette
    Holmen, Oddgeir L
    Homuth, Georg
    Jan Hottenga, Jouke
    Huang, Jie
    Hung, Joseph
    Hutri-Kahonen, Nina
    Ingelsson, Erik
    James, Alan L
    Jansson, John-Olov
    Jarvelin, Marjo-Riitta
    Jhun, Min A
    Jorgensen, Marit E
    Juonala, Markus
    Kahonen, Mika
    Karlsson, Magnus
    Koistinen, Heikki A
    Kolcic, Ivana
    Kolovou, Genovefa
    Kooperberg, Charles
    Kramer, Bernhard K
    Kuusisto, Johanna
    Kvaloy, Kirsti
    Lakka, Timo A
    Langenberg, Claudia
    Launer, Lenore J
    Leander, Karin
    Lee, Nanette R
    Lind, Lars
    Lindgren, Cecilia M
    Linneberg, Allan
    Lobbens, Stephane
    Loh, Marie
    Lorentzon, Mattias
    Luben, Robert
    Lubke, Gitta
    Ludolph-Donislawski, Anja
    Lupoli, Sara
    Madden, Pamela A F
    Mannikko, Reija
    Marques-Vidal, Pedro
    Martin, Nicholas G
    McKenzie, Colin A
    McKnight, Barbara
    Mellstrom, Dan
    Menni, Cristina
    Montgomery, Grant W
    Musk, Aw Bill
    Narisu, Narisu
    Nauck, Matthias
    Nolte, Ilja M
    Oldehinkel, Albertine J
    Olden, Matthias
    Ong, Ken K
    Padmanabhan, Sandosh
    Peyser, Patricia A
    Pisinger, Charlotta
    Porteous, David J
    Raitakari, Olli T
    Rankinen, Tuomo
    Rao, D C
    Rasmussen-Torvik, Laura J
    Rawal, Rajesh
    Rice, Treva
    Ridker, Paul M
    Rose, Lynda M
    Bien, Stephanie A
    Rudan, Igor
    Sanna, Serena
    Sarzynski, Mark A
    Sattar, Naveed
    Savonen, Kai
    Schlessinger, David
    Scholtens, Salome
    Schurmann, Claudia
    Scott, Robert A
    Sennblad, Bengt
    Siemelink, Marten A
    Silbernagel, Gunther
    Slagboom, P Eline
    Snieder, Harold
    Staessen, Jan A
    Stott, David J
    Swertz, Morris A
    Swift, Amy J
    Taylor, Kent D
    Tayo, Bamidele O
    Thorand, Barbara
    Thuillier, Dorothee
    Tuomilehto, Jaakko
    Uitterlinden, Andre G
    Vandenput, Liesbeth
    Vohl, Marie-Claude
    Volzke, Henry
    Vonk, Judith M
    Waeber, Gerard
    Waldenberger, Melanie
    Westendorp, R G J
    Wild, Sarah
    Willemsen, Gonneke
    Wolffenbuttel, Bruce H R
    Wong, Andrew
    Wright, Alan F
    Zhao, Wei
    Zillikens, M Carola
    Baldassarre, Damiano
    Balkau, Beverley
    Bandinelli, Stefania
    Boger, Carsten A
    Boomsma, Dorret I
    Bouchard, Claude
    Bruinenberg, Marcel
    Chasman, Daniel I
    Chen, Yii-DerIda
    Chines, Peter S
    Cooper, Richard S
    Cucca, Francesco
    Cusi, Daniele
    Faire, Ulf de
    Ferrucci, Luigi
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, SE-205 02 Malmö, Sweden; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, USA.
    Froguel, Philippe
    Gordon-Larsen, Penny
    Grabe, Hans-Jorgen
    Gudnason, Vilmundur
    Haiman, Christopher A
    Hayward, Caroline
    Hveem, Kristian
    Johnson, Andrew D
    Wouter Jukema, J
    Kardia, Sharon L R
    Kivimaki, Mika
    Kooner, Jaspal S
    Kuh, Diana
    Laakso, Markku
    Lehtimaki, Terho
    Marchand, Loic Le
    Marz, Winfried
    McCarthy, Mark I
    Metspalu, Andres
    Morris, Andrew P
    Ohlsson, Claes
    Palmer, Lyle J
    Pasterkamp, Gerard
    Pedersen, Oluf
    Peters, Annette
    Peters, Ulrike
    Polasek, Ozren
    Psaty, Bruce M
    Qi, Lu
    Rauramaa, Rainer
    Smith, Blair H
    Sorensen, Thorkild I A
    Strauch, Konstantin
    Tiemeier, Henning
    Tremoli, Elena
    van der Harst, Pim
    Vestergaard, Henrik
    Vollenweider, Peter
    Wareham, Nicholas J
    Weir, David R
    Whitfield, John B
    Wilson, James F
    Tyrrell, Jessica
    Frayling, Timothy M
    Barroso, Ines
    Boehnke, Michael
    Deloukas, Panagiotis
    Fox, Caroline S
    Hirschhorn, Joel N
    Hunter, David J
    Spector, Tim D
    Strachan, David P
    van Duijn, Cornelia M
    Heid, Iris M
    Mohlke, Karen L
    Marchini, Jonathan
    Loos, Ruth J F
    Kilpelainen, Tuomas O
    Liu, Ching-Ti
    Borecki, Ingrid B
    North, Kari E
    Cupples, L Adrienne
    Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits2017In: Nature Communications, E-ISSN 2041-1723, Vol. 8, p. 14977-14977Article in journal (Refereed)
    Abstract [en]

    Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.

    Download full text (pdf)
    fulltext
  • 26. Kanoni, Stavroula
    et al.
    Masca, Nicholas G D
    Stirrups, Kathleen E
    Varga, Tibor V
    Warren, Helen R
    Scott, Robert A
    Southam, Lorraine
    Zhang, Weihua
    Yaghootkar, Hanieh
    Müller-Nurasyid, Martina
    Couto Alves, Alexessander
    Strawbridge, Rona J
    Lataniotis, Lazaros
    An Hashim, Nikman
    Besse, Céline
    Boland, Anne
    Braund, Peter S
    Connell, John M
    Dominiczak, Anna
    Farmaki, Aliki-Eleni
    Franks, Stephen
    Grallert, Harald
    Jansson, Jan-Håkan
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Karaleftheri, Maria
    Keinänen-Kiukaanniemi, Sirkka
    Matchan, Angela
    Pasko, Dorota
    Peters, Annette
    Poulter, Neil
    Rayner, Nigel W
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital Malmö, Malmö , Sweden.
    Rolandsson, Olov
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Sabater-Lleal, Maria
    Sennblad, Bengt
    Sever, Peter
    Shields, Denis
    Silveira, Angela
    Stanton, Alice V
    Strauch, Konstantin
    Tomaszewski, Maciej
    Tsafantakis, Emmanouil
    Waldenberger, Melanie
    Blakemore, Alexandra I F
    Dedoussis, George
    Escher, Stefan A
    Kooner, Jaspal S
    McCarthy, Mark I
    Palmer, Colin N A
    Hamsten, Anders
    Caulfield, Mark J
    Frayling, Timothy M
    Tobin, Martin D
    Jarvelin, Marjo-Riitta
    Zeggini, Eleftheria
    Gieger, Christian
    Chambers, John C
    Wareham, Nick J
    Munroe, Patricia B
    Franks, Paul W
    Samani, Nilesh J
    Deloukas, Panos
    Analysis with the exome array identifies multiple new independent variants in lipid loci2016In: Human Molecular Genetics, ISSN 0964-6906, E-ISSN 1460-2083, Vol. 25, no 18, p. 4094-4106Article in journal (Refereed)
    Abstract [en]

    It has been hypothesized that low frequency (1-5% minor allele frequency (MAF)) and rare (<1% MAF) variants with large effect sizes may contribute to the missing heritability in complex traits. Here, we report an association analysis of lipid traits (total cholesterol, LDL-cholesterol, HDL-cholesterol triglycerides) in up to 27 312 individuals with a comprehensive set of low frequency coding variants (ExomeChip), combined with conditional analysis in the known lipid loci. No new locus reached genome-wide significance. However, we found a new lead variant in 26 known lipid association regions of which 16 were >1000-fold more significant than the previous sentinel variant and not in close LD (six had MAF <5%). Furthermore, conditional analysis revealed multiple independent signals (ranging from 1 to 5) in a third of the 98 lipid loci tested, including rare variants. Addition of our novel associations resulted in between 1.5- and 2.5-fold increase in the proportion of heritability explained for the different lipid traits. Our findings suggest that rare coding variants contribute to the genetic architecture of lipid traits.

  • 27. Kanoni, Stavroula
    et al.
    Nettleton, Jennifer A
    Hivert, Marie-France
    Ye, Zheng
    van Rooij, Frank JA
    Shungin, Dmitry
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Umeå University, Faculty of Medicine, Department of Odontology. Department of Clinical Sciences, Lund University, Malmö, Sweden.
    Sonestedt, Emily
    Ngwa, Julius S
    Wojczynski, Mary K
    Lemaitre, Rozenn N
    Gustafsson, Stefan
    Anderson, Jennifer S
    Tanaka, Toshiko
    Hindy, George
    Saylor, Georgia
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Department of Clinical Sciences, Lund University, Malmö, Sweden; Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts.
    Bennett, Amanda J
    van Duijn, Cornelia M
    Florez, Jose C
    Fox, Caroline S
    Hofman, Albert
    Hoogeveen, Ron C
    Houston, Denise K
    Hu, Frank B
    Jacques, Paul F
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Odontology.
    Lind, Lars
    Liu, Yongmei
    McKeown, Nicola
    Ordovas, Jose
    Pankow, James S
    Sijbrands, Eric JG
    Syvänen, Ann-Christine
    Uitterlinden, André G
    Yannakoulia, Mary
    Zillikens, M Carola
    Wareham, Nick J
    Prokopenko, Inga
    Bandinelli, Stefania
    Forouhi, Nita G
    Cupples, L Adrienne
    Loos, Ruth J
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Dupuis, Josée
    Langenberg, Claudia
    Ferrucci, Luigi
    Kritchevsky, Stephen B
    McCarthy, Mark I
    Ingelsson, Erik
    Borecki, Ingrid B
    Witteman, Jacqueline CM
    Orho-Melander, Marju
    Siscovick, David S
    Meigs, James B
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Department of Clinical Sciences, Lund University, Malmö, Sweden; Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts.
    Dedoussis, George V
    Total zinc intake may modify the glucose-raising effect of a zinc transporter (SLC30A8) variant: a 14-cohort meta-analysis2011In: Diabetes, ISSN 0012-1797, E-ISSN 1939-327X, Vol. 60, no 9, p. 2407-2416Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE Many genetic variants have been associated with glucose homeostasis and type 2 diabetes in genome-wide association studies. Zinc is an essential micronutrient that is important for β-cell function and glucose homeostasis. We tested the hypothesis that zinc intake could influence the glucose-raising effect of specific variants.

    RESEARCH DESIGN AND METHODS We conducted a 14-cohort meta-analysis to assess the interaction of 20 genetic variants known to be related to glycemic traits and zinc metabolism with dietary zinc intake (food sources) and a 5-cohort meta-analysis to assess the interaction with total zinc intake (food sources and supplements) on fasting glucose levels among individuals of European ancestry without diabetes.

    RESULTS We observed a significant association of total zinc intake with lower fasting glucose levels (β-coefficient ± SE per 1 mg/day of zinc intake: -0.0012 ± 0.0003 mmol/L, summary P value = 0.0003), while the association of dietary zinc intake was not significant. We identified a nominally significant interaction between total zinc intake and the SLC30A8 rs11558471 variant on fasting glucose levels (β-coefficient ± SE per A allele for 1 mg/day of greater total zinc intake: -0.0017 ± 0.0006 mmol/L, summary interaction P value = 0.005); this result suggests a stronger inverse association between total zinc intake and fasting glucose in individuals carrying the glucose-raising A allele compared with individuals who do not carry it. None of the other interaction tests were statistically significant.

    CONCLUSIONS Our results suggest that higher total zinc intake may attenuate the glucose-raising effect of the rs11558471 SLC30A8 (zinc transporter) variant. Our findings also support evidence for the association of higher total zinc intake with lower fasting glucose levels.

  • 28. Kilpelainen, Tuomas O.
    et al.
    Carli, Jayne F. Martin
    Skowronski, Alicja A.
    Sun, Qi
    Kriebel, Jennifer
    Feitosa, Mary F.
    Hedman, Asa K.
    Drong, Alexander W.
    Hayes, James E.
    Zhao, Jinghua
    Pers, Tune H.
    Schick, Ursula
    Grarup, Niels
    Kutalik, Zoltan
    Trompet, Stella
    Mangino, Massimo
    Kristiansson, Kati
    Beekman, Marian
    Lyytikainen, Leo-Pekka
    Eriksson, Joel
    Henneman, Peter
    Lahti, Jari
    Tanaka, Toshiko
    Luan, Jian'an
    Del Greco M, Fabiola
    Pasko, Dorota
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö 20502, Sweden.
    Willems, Sara M.
    Mahajan, Anubha
    Rose, Lynda M.
    Guo, Xiuqing
    Liu, Yongmei
    Kleber, Marcus E.
    Perusse, Louis
    Gaunt, Tom
    Ahluwalia, Tarunveer S.
    Sung, Yun Ju
    Ramos, Yolande F.
    Amin, Najaf
    Amuzu, Antoinette
    Barroso, Ines
    Bellis, Claire
    Blangero, John
    Buckley, Brendan M.
    Boehringer, Stefan
    Chen, Yii-Der I.
    de Craen, Anton J. N.
    Crosslin, David R.
    Dale, Caroline E.
    Dastani, Zari
    Day, Felix R.
    Deelen, Joris
    Delgado, Graciela E.
    Demirkan, Ayse
    Finucane, Francis M.
    Ford, Ian
    Garcia, Melissa E.
    Gieger, Christian
    Gustafsson, Stefan
    Hallmans, Goran
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research. Umeå University, Faculty of Medicine, Department of Biobank Research.
    Hankinson, Susan E.
    Havulinna, Aki S.
    Herder, Christian
    Hernandez, Dena
    Hicks, Andrew A.
    Hunter, David J.
    Illig, Thomas
    Ingelsson, Erik
    Ioan-Facsinay, Andreea
    Jansson, John-Olov
    Jenny, Nancy S.
    Jorgensen, Marit E.
    Jorgensen, Torben
    Karlsson, Magnus
    Koenig, Wolfgang
    Kraft, Peter
    Kwekkeboom, Joanneke
    Laatikainen, Tiina
    Ladwig, Karl-Heinz
    LeDuc, Charles A.
    Lowe, Gordon
    Lu, Yingchang
    Marques-Vidal, Pedro
    Meisinger, Christa
    Menni, Cristina
    Morris, Andrew P.
    Myers, Richard H.
    Mannisto, Satu
    Nalls, Mike A.
    Paternoster, Lavinia
    Peters, Annette
    Pradhan, Aruna D.
    Rankinen, Tuomo
    Rasmussen-Torvik, Laura J.
    Rathmann, Wolfgang
    Rice, Treva K.
    Richards, J. Brent
    Ridker, Paul M.
    Sattar, Naveed
    Savage, David B.
    Söderberg, Stefan
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Cardiology.
    Timpson, Nicholas J.
    Vandenput, Liesbeth
    van Heemst, Diana
    Uh, Hae-Won
    Vohl, Marie-Claude
    Walker, Mark
    Wichmann, Heinz-Erich
    Widen, Elisabeth
    Wood, Andrew R.
    Yao, Jie
    Zeller, Tanja
    Zhang, Yiying
    Meulenbelt, Ingrid
    Kloppenburg, Margreet
    Astrup, Arne
    Sorensen, Thorkild I. A.
    Sarzynski, Mark A.
    Rao, D. C.
    Jousilahti, Pekka
    Vartiainen, Erkki
    Hofman, Albert
    Rivadeneira, Fernando
    Uitterlinden, Andre G.
    Kajantie, Eero
    Osmond, Clive
    Palotie, Aarno
    Eriksson, Johan G.
    Heliovaara, Markku
    Knekt, Paul B.
    Koskinen, Seppo
    Jula, Antti
    Perola, Markus
    Huupponen, Risto K.
    Viikari, Jorma S.
    Kahonen, Mika
    Lehtimaki, Terho
    Raitakari, Olli T.
    Mellstrom, Dan
    Lorentzon, Mattias
    Casas, Juan P.
    Bandinelli, Stefanie
    Maerz, Winfried
    Isaacs, Aaron
    van Dijk, Ko W.
    van Duijn, Cornelia M.
    Harris, Tamara B.
    Bouchard, Claude
    Allison, Matthew A.
    Chasman, Daniel I.
    Ohlsson, Claes
    Lind, Lars
    Scott, Robert A.
    Langenberg, Claudia
    Wareham, Nicholas J.
    Ferrucci, Luigi
    Frayling, Timothy M.
    Pramstaller, Peter P.
    Borecki, Ingrid B.
    Waterworth, Dawn M.
    Bergmann, Sven
    Waeber, Gerard
    Vollenweider, Peter
    Vestergaard, Henrik
    Hansen, Torben
    Pedersen, Oluf
    Hu, Frank B.
    Slagboom, P. Eline
    Grallert, Harald
    Spector, Tim D.
    Jukema, J. W.
    Klein, Robert J.
    Schadt, Erik E.
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachussetts 02115, USA; Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö 20502, Sweden.
    Lindgren, Cecilia M.
    Leibel, Rudolph L.
    Loos, Ruth J. F.
    Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels2016In: Nature Communications, E-ISSN 2041-1723, Vol. 7, article id 10494Article in journal (Refereed)
    Abstract [en]

    Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P < 10(-6) in 19,979 additional individuals. We identify five loci robustly associated (P < 5 x 10(-8)) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health.

    Download full text (pdf)
    fulltext
  • 29. Kilpeläinen, Tuomas O
    et al.
    Qi, Lu
    Brage, Soren
    Sharp, Stephen J
    Sonestedt, Emily
    Demerath, Ellen
    Ahmad, Tariq
    Mora, Samia
    Kaakinen, Marika
    Sandholt, Camilla Helene
    Holzapfel, Christina
    Autenrieth, Christine S
    Hyppönen, Elina
    Cauchi, Stéphane
    He, Meian
    Kutalik, Zoltan
    Kumari, Meena
    Stančáková, Alena
    Meidtner, Karina
    Balkau, Beverley
    Tan, Jonathan T
    Mangino, Massimo
    Timpson, Nicholas J
    Song, Yiqing
    Zillikens, M Carola
    Jablonski, Kathleen A
    Garcia, Melissa E
    Johansson, Stefan
    Bragg-Gresham, Jennifer L
    Wu, Ying
    van Vliet-Ostaptchouk, Jana V
    Onland-Moret, N Charlotte
    Zimmermann, Esther
    Rivera, Natalia V
    Tanaka, Toshiko
    Stringham, Heather M
    Silbernagel, Günther
    Kanoni, Stavroula
    Feitosa, Mary F
    Snitker, Soren
    Ruiz, Jonatan R
    Metter, Jeffery
    Larrad, Maria Teresa Martinez
    Atalay, Mustafa
    Hakanen, Maarit
    Amin, Najaf
    Cavalcanti-Proença, Christine
    Grøntved, Anders
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Jansson, John-Olov
    Kuusisto, Johanna
    Kähönen, Mika
    Lutsey, Pamela L
    Nolan, John J
    Palla, Luigi
    Pedersen, Oluf
    Pérusse, Louis
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Scott, Robert A
    Shungin, Dmitry
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Sovio, Ulla
    Tammelin, Tuija H
    Rönnemaa, Tapani
    Lakka, Timo A
    Uusitupa, Matti
    Rios, Manuel Serrano
    Ferrucci, Luigi
    Bouchard, Claude
    Meirhaeghe, Aline
    Fu, Mao
    Walker, Mark
    Borecki, Ingrid B
    Dedoussis, George V
    Fritsche, Andreas
    Ohlsson, Claes
    Boehnke, Michael
    Bandinelli, Stefania
    van Duijn, Cornelia M
    Ebrahim, Shah
    Lawlor, Debbie A
    Gudnason, Vilmundur
    Harris, Tamara B
    Sørensen, Thorkild I A
    Mohlke, Karen L
    Hofman, Albert
    Uitterlinden, André G
    Tuomilehto, Jaakko
    Lehtimäki, Terho
    Raitakari, Olli
    Isomaa, Bo
    Njølstad, Pål R
    Florez, Jose C
    Liu, Simin
    Ness, Andy
    Spector, Timothy D
    Tai, E Shyong
    Froguel, Philippe
    Boeing, Heiner
    Laakso, Markku
    Marmot, Michael
    Bergmann, Sven
    Power, Chris
    Khaw, Kay-Tee
    Chasman, Daniel
    Ridker, Paul
    Hansen, Torben
    Monda, Keri L
    Illig, Thomas
    Järvelin, Marjo-Riitta
    Wareham, Nicholas J
    Hu, Frank B
    Groop, Leif C
    Orho-Melander, Marju
    Ekelund, Ulf
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Loos, Ruth J F
    Physical activity attenuates the influence of FTO variants on obesity risk: a meta-analysis of 218,166 adults and 19,268 children2011In: PLoS Medicine, ISSN 1549-1277, E-ISSN 1549-1676, Vol. 8, no 11, p. e1001116-Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: The FTO gene harbors the strongest known susceptibility locus for obesity. While many individual studies have suggested that physical activity (PA) may attenuate the effect of FTO on obesity risk, other studies have not been able to confirm this interaction. To confirm or refute unambiguously whether PA attenuates the association of FTO with obesity risk, we meta-analyzed data from 45 studies of adults (n = 218,166) and nine studies of children and adolescents (n = 19,268).

    METHODS AND FINDINGS: All studies identified to have data on the FTO rs9939609 variant (or any proxy [r(2)>0.8]) and PA were invited to participate, regardless of ethnicity or age of the participants. PA was standardized by categorizing it into a dichotomous variable (physically inactive versus active) in each study. Overall, 25% of adults and 13% of children were categorized as inactive. Interaction analyses were performed within each study by including the FTO×PA interaction term in an additive model, adjusting for age and sex. Subsequently, random effects meta-analysis was used to pool the interaction terms. In adults, the minor (A-) allele of rs9939609 increased the odds of obesity by 1.23-fold/allele (95% CI 1.20-1.26), but PA attenuated this effect (p(interaction)  = 0.001). More specifically, the minor allele of rs9939609 increased the odds of obesity less in the physically active group (odds ratio  = 1.22/allele, 95% CI 1.19-1.25) than in the inactive group (odds ratio  = 1.30/allele, 95% CI 1.24-1.36). No such interaction was found in children and adolescents.

    CONCLUSIONS: The association of the FTO risk allele with the odds of obesity is attenuated by 27% in physically active adults, highlighting the importance of PA in particular in those genetically predisposed to obesity.

  • 30. Koivula, R. W.
    et al.
    Grontved, A.
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Odontology.
    Wennberg, Patrik
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Ostergaard, L.
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Biobank Research. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Renstrom, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Department of Clinical Sciences, Lund University, Malmö, Sweden.
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Medicine.
    Bicycling to work and primordial prevention of cardiovascular and type 2 diabetes risk: a cohort study from Northern Sweden2016In: Diabetologia, ISSN 0012-186X, E-ISSN 1432-0428, Vol. 59, p. S150-S150, article id 298Article in journal (Refereed)
  • 31. Kurbasic, Azra
    et al.
    Poveda, Alaitz
    Chen, Yan
    Ågren, Åsa
    Umeå University, Faculty of Medicine, Department of Biobank Research.
    Engberg, Elisabeth
    Umeå University, Faculty of Social Sciences, Demographic Data Base.
    Hu, Frank B
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Odontology.
    Barroso, Ines
    Brändström, Anders
    Umeå University, Faculty of Social Sciences, Demographic Data Base.
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Biobank Research. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research.
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Department of Nutrition, Harvard School of Public Health, Boston, MA, USA.
    Gene-Lifestyle Interactions in Complex Diseases: Design and Description of the GLACIER and VIKING Studies2014In: Current nutrition reports, ISSN 2161-3311, Vol. 3, no 4, p. 400-411Article in journal (Refereed)
    Abstract [en]

    Most complex diseases have well-established genetic and non-genetic risk factors. In some instances, these risk factors are likely to interact, whereby their joint effects convey a level of risk that is either significantly more or less than the sum of these risks. Characterizing these gene-environment interactions may help elucidate the biology of complex diseases, as well as to guide strategies for their targeted prevention. In most cases, the detection of gene-environment interactions will require sample sizes in excess of those needed to detect the marginal effects of the genetic and environmental risk factors. Although many consortia have been formed, comprising multiple diverse cohorts to detect gene-environment interactions, few robust examples of such interactions have been discovered. This may be because combining data across studies, usually through meta-analysis of summary data from the contributing cohorts, is often a statistically inefficient approach for the detection of gene-environment interactions. Ideally, single, very large and well-genotyped prospective cohorts, with validated measures of environmental risk factor and disease outcomes should be used to study interactions. The presence of strong founder effects within those cohorts might further strengthen the capacity to detect novel genetic effects and gene-environment interactions. Access to accurate genealogical data would also aid in studying the diploid nature of the human genome, such as genomic imprinting (parent-of-origin effects). Here we describe two studies from northern Sweden (the GLACIER and VIKING studies) that fulfill these characteristics.

  • 32. Lassale, Camille
    et al.
    Gunter, Marc J.
    Romaguera, Dora
    Peelen, Linda M.
    Van der Schouw, Yvonne T.
    Beulens, Joline W. J.
    Freisling, Heinz
    Muller, David C.
    Ferrari, Pietro
    Huybrechts, Inge
    Fagherazzi, Guy
    Boutron-Ruault, Marie-Christine
    Affret, Aurelie
    Overvad, Kim
    Dahm, Christina C.
    Olsen, Anja
    Roswall, Nina
    Tsilidis, Konstantinos K.
    Katzke, Verena A.
    Kuehn, Tilman
    Buijsse, Brian
    Quiros, Jose-Ramon
    Sanchez-Cantalejo, Emilio
    Etxezarreta, Nerea
    Maria Huerta, Jose
    Barricarte, Aurelio
    Bonet, Catalina
    Khaw, Kay-Tee
    Key, Timothy J.
    Trichopoulou, Antonia
    Bamia, Christina
    Lagiou, Pagona
    Palli, Domenico
    Agnoli, Claudia
    Tumino, Rosario
    Fasanelli, Francesca
    Panico, Salvatore
    Bueno-de-Mesquita, H. Bas
    Boer, Jolanda M. A.
    Sonestedt, Emily
    Nilsson, Lena Maria
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Weiderpass, Elisabete
    Skeie, Guri
    Lund, Eiliv
    Moons, Karel G. M.
    Riboli, Elio
    Tzoulaki, Ioanna
    Diet Quality Scores and Prediction of All-Cause, Cardiovascular and Cancer Mortality in a Pan-European Cohort Study2016In: PLOS ONE, E-ISSN 1932-6203, Vol. 11, no 7, article id e0159025Article in journal (Refereed)
    Abstract [en]

    Scores of overall diet quality have received increasing attention in relation to disease aetiology; however, their value in risk prediction has been little examined. The objective was to assess and compare the association and predictive performance of 10 diet quality scores on 10-year risk of all-cause, CVD and cancer mortality in 451,256 healthy participants to the European Prospective Investigation into Cancer and Nutrition, followed-up for a median of 12.8y. All dietary scores studied showed significant inverse associations with all outcomes. The range of HRs (95% CI) in the top vs. lowest quartile of dietary scores in a composite model including non-invasive factors (age, sex, smoking, body mass index, education, physical activity and study centre) was 0.75 (0.72-0.79) to 0.88 (0.84-0.92) for all-cause, 0.76 (0.69-0.83) to 0.84 (0.76-0.92) for CVD and 0.78 (0.73-0.83) to 0.91 (0.85-0.97) for cancer mortality. Models with dietary scores alone showed low discrimination, but composite models also including age, sex and other non-invasive factors showed good discrimination and calibration, which varied little between different diet scores examined. Mean C-statistic of full models was 0.73, 0.80 and 0.71 for all-cause, CVD and cancer mortality. Dietary scores have poor predictive performance for 10-year mortality risk when used in isolation but display good predictive ability in combination with other non-invasive common risk factors.

    Download full text (pdf)
    fulltext
  • 33. Lindgren, Cecilia M
    et al.
    Heid, Iris M
    Randall, Joshua C
    Lamina, Claudia
    Steinthorsdottir, Valgerdur
    Qi, Lu
    Speliotes, Elizabeth K
    Thorleifsson, Gudmar
    Willer, Cristen J
    Herrera, Blanca M
    Jackson, Anne U
    Lim, Noha
    Scheet, Paul
    Soranzo, Nicole
    Amin, Najaf
    Aulchenko, Yurii S
    Chambers, John C
    Drong, Alexander
    Luan, Jian'an
    Lyon, Helen N
    Rivadeneira, Fernando
    Sanna, Serena
    Timpson, Nicholas J
    Zillikens, M Carola
    Zhao, Jing Hua
    Almgren, Peter
    Bandinelli, Stefania
    Bennett, Amanda J
    Bergman, Richard N
    Bonnycastle, Lori L
    Bumpstead, Suzannah J
    Chanock, Stephen J
    Cherkas, Lynn
    Chines, Peter
    Coin, Lachlan
    Cooper, Cyrus
    Crawford, Gabriel
    Doering, Angela
    Dominiczak, Anna
    Doney, Alex S F
    Ebrahim, Shah
    Elliott, Paul
    Erdos, Michael R
    Estrada, Karol
    Ferrucci, Luigi
    Fischer, Guido
    Forouhi, Nita G
    Gieger, Christian
    Grallert, Harald
    Groves, Christopher J
    Grundy, Scott
    Guiducci, Candace
    Hadley, David
    Hamsten, Anders
    Havulinna, Aki S
    Hofman, Albert
    Holle, Rolf
    Holloway, John W
    Illig, Thomas
    Isomaa, Bo
    Jacobs, Leonie C
    Jameson, Karen
    Jousilahti, Pekka
    Karpe, Fredrik
    Kuusisto, Johanna
    Laitinen, Jaana
    Lathrop, G Mark
    Lawlor, Debbie A
    Mangino, Massimo
    McArdle, Wendy L
    Meitinger, Thomas
    Morken, Mario A
    Morris, Andrew P
    Munroe, Patricia
    Narisu, Narisu
    Nordström, Anna
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Sports Medicine. Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Geriatric Medicine.
    Nordström, Peter
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Sports Medicine. Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Geriatric Medicine.
    Oostra, Ben A
    Palmer, Colin N A
    Payne, Felicity
    Peden, John F
    Prokopenko, Inga
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Ruokonen, Aimo
    Salomaa, Veikko
    Sandhu, Manjinder S
    Scott, Laura J
    Scuteri, Angelo
    Silander, Kaisa
    Song, Kijoung
    Yuan, Xin
    Stringham, Heather M
    Swift, Amy J
    Tuomi, Tiinamaija
    Uda, Manuela
    Vollenweider, Peter
    Waeber, Gerard
    Wallace, Chris
    Walters, G Bragi
    Weedon, Michael N
    Witteman, Jacqueline C M
    Zhang, Cuilin
    Zhang, Weihua
    Caulfield, Mark J
    Collins, Francis S
    Davey Smith, George
    Day, Ian N M
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Hattersley, Andrew T
    Hu, Frank B
    Jarvelin, Marjo-Riitta
    Kong, Augustine
    Kooner, Jaspal S
    Laakso, Markku
    Lakatta, Edward
    Mooser, Vincent
    Morris, Andrew D
    Peltonen, Leena
    Samani, Nilesh J
    Spector, Timothy D
    Strachan, David P
    Tanaka, Toshiko
    Tuomilehto, Jaakko
    Uitterlinden, André G
    van Duijn, Cornelia M
    Wareham, Nicholas J
    Hugh Watkins,
    Waterworth, Dawn M
    Boehnke, Michael
    Deloukas, Panos
    Groop, Leif
    Hunter, David J
    Thorsteinsdottir, Unnur
    Schlessinger, David
    Wichmann, H-Erich
    Frayling, Timothy M
    Abecasis, Gonçalo R
    Hirschhorn, Joel N
    Loos, Ruth J F
    Stefansson, Kari
    Mohlke, Karen L
    Barroso, Inês
    McCarthy, Mark I
    Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution.2009In: PLoS genetics, ISSN 1553-7404, Vol. 5, no 6, p. e1000508-Article in journal (Refereed)
    Abstract [en]

    To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.

  • 34. Liu, Dajiang J.
    et al.
    Peloso, Gina M.
    Yu, Haojie
    Butterworth, Adam S.
    Wang, Xiao
    Mahajan, Anubha
    Saleheen, Danish
    Emdin, Connor
    Alam, Dewan
    Alves, Alexessander Couto
    Amouyel, Philippe
    Di Angelantonio, Emanuele
    Arveiler, Dominique
    Assimes, Themistocles L.
    Auer, Paul L.
    Baber, Usman
    Ballantyne, Christie M.
    Bang, Lia E.
    Benn, Marianne
    Bis, Joshua C.
    Boehnke, Michael
    Boerwinkle, Eric
    Bork-Jensen, Jette
    Bottinger, Erwin P.
    Brandslund, Ivan
    Brown, Morris
    Busonero, Fabio
    Caulfield, Mark J.
    Chambers, John C.
    Chasman, Daniel I.
    Chen, Y. Eugene
    Chen, Yii-Der Ida
    Chowdhury, Rajiv
    Christensen, Cramer
    Chu, Audrey Y.
    Connell, John M.
    Cucca, Francesco
    Cupples, L. Adrienne
    Damrauer, Scott M.
    Davies, Gail
    Deary, Ian J.
    Dedoussis, George
    Denny, Joshua C.
    Dominiczak, Anna
    Dube, Marie-Pierre
    Ebeling, Tapani
    Eiriksdottir, Gudny
    Esko, Tonu
    Farmaki, Aliki-Eleni
    Feitosa, Mary F.
    Ferrario, Marco
    Ferrieres, Jean
    Ford, Ian
    Fornage, Myriam
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden; Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA.
    Frayling, Timothy M.
    Frikke-Schmidt, Ruth
    Fritsche, Lars G.
    Frossard, Philippe
    Fuster, Valentin
    Ganesh, Santhi K.
    Gao, Wei
    Garcia, Melissa E.
    Gieger, Christian
    Giulianini, Franco
    Goodarzi, Mark O.
    Grallert, Harald
    Grarup, Niels
    Groop, Leif
    Grove, Megan L.
    Gudnason, Vilmundur
    Hansen, Torben
    Harris, Tamara B.
    Hayward, Caroline
    Hirschhorn, Joel N.
    Holmen, Oddgeir L.
    Huffman, Jennifer
    Huo, Yong
    Hveem, Kristian
    Jabeen, Sehrish
    Jackson, Anne U.
    Jakobsdottir, Johanna
    Jarvelin, Marjo-Riitta
    Jensen, Gorm B.
    Jorgensen, Marit E.
    Jukema, J. Wouter
    Justesen, Johanne M.
    Kamstrup, Pia R.
    Kanoni, Stavroula
    Karpe, Fredrik
    Kee, Frank
    Khera, Amit V.
    Klarin, Derek
    Koistinen, Heikki A.
    Kooner, Jaspal S.
    Kooperberg, Charles
    Kuulasmaa, Kari
    Kuusisto, Johanna
    Laakso, Markku
    Lakka, Timo
    Langenberg, Claudia
    Langsted, Anne
    Launer, Lenore J.
    Lauritzen, Torsten
    Liewald, David C. M.
    Lin, Li An
    Linneberg, Allan
    Loos, Ruth J. F.
    Lu, Yingchang
    Lu, Xiangfeng
    Magi, Reedik
    Malarstig, Anders
    Manichaikul, Ani
    Manning, Alisa K.
    Mantyselka, Pekka
    Marouli, Eirini
    Masca, Nicholas G. D.
    Maschio, Andrea
    Meigs, James B.
    Melander, Olle
    Metspalu, Andres
    Morris, Andrew P.
    Morrison, Alanna C.
    Mulas, Antonella
    Mueller-Nurasyid, Martina
    Munroe, Patricia B.
    Neville, Matt J.
    Nielsen, Jonas B.
    Nielsen, Sune F.
    Nordestgaard, Borge G.
    Ordovas, Jose M.
    Mehran, Roxana
    O'Donnell, Christoper J.
    Orho-Melander, Marju
    Molony, Cliona M.
    Muntendam, Pieter
    Padmanabhan, Sandosh
    Palmer, Colin N. A.
    Pasko, Dorota
    Patel, Aniruddh P.
    Pedersen, Oluf
    Perola, Markus
    Peters, Annette
    Pisinger, Charlotta
    Pistis, Giorgio
    Polasek, Ozren
    Poulter, Neil
    Psaty, Bruce M.
    Rader, Daniel J.
    Rasheed, Asif
    Rauramaa, Rainer
    Reilly, Dermot F.
    Reiner, Alex P.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden.
    Rich, Stephen S.
    Ridker, Paul M.
    Rioux, John D.
    Robertson, Neil R.
    Roden, Dan M.
    Rotter, Jerome I.
    Rudan, Igor
    Salomaa, Veikko
    Samani, Nilesh J.
    Sanna, Serena
    Sattar, Naveed
    Schmidt, Ellen M.
    Scott, Robert A.
    Sever, Peter
    Sevilla, Raquel S.
    Shaffer, Christian M.
    Sim, Xueling
    Sivapalaratnam, Suthesh
    Small, Kerrin S.
    Smith, Albert V.
    Smith, Blair H.
    Somayajula, Sangeetha
    Southam, Lorraine
    Spector, Timothy D.
    Speliotes, Elizabeth K.
    Starr, John M.
    Stirrups, Kathleen E.
    Stitziel, Nathan
    Strauch, Konstantin
    Stringham, Heather M.
    Surendran, Praveen
    Tada, Hayato
    Tall, Alan R.
    Tang, Hua
    Tardif, Jean-Claude
    Taylor, Kent D.
    Trompet, Stella
    Tsao, Philip S.
    Tuomilehto, Jaakko
    Tybjaerg-Hansen, Anne
    van Zuydam, Natalie R.
    Varbo, Anette
    Varga, Tibor V.
    Virtamo, Jarmo
    Waldenberger, Melanie
    Wang, Nan
    Wareham, Nick J.
    Warren, Helen R.
    Weeke, Peter E.
    Weinstock, Joshua
    Wessel, Jennifer
    Wilson, James G.
    Wilson, Peter W. F.
    Xu, Ming
    Yaghootkar, Hanieh
    Young, Robin
    Zeggini, Eleftheria
    Zhang, He
    Zheng, Neil S.
    Zhang, Weihua
    Zhang, Yan
    Zhou, Wei
    Zhou, Yanhua
    Zoledziewska, Magdalena
    Howson, Joanna M. M.
    Danesh, John
    McCarthy, Mark I.
    Cowan, Chad A.
    Abecasis, Goncalo
    Deloukas, Panos
    Musunuru, Kiran
    Willer, Cristen J.
    Kathiresan, Sekar
    Exome-wide association study of plasma lipids in > 300,000 individuals2017In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 49, no 12, p. 1758-1766Article in journal (Refereed)
    Abstract [en]

    We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-densitylipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.

  • 35. Lu, Yunxia
    et al.
    Cross, Amanda J
    Murphy, Neil
    Freisling, Heinz
    Travis, Ruth C
    Ferrari, Pietro
    Katzke, Verena A
    Kaaks, Rudolf
    Olsson, Åsa
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Odontology. Umeå University, Faculty of Medicine, Department of Biobank Research.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Skåne University Hospital Malmö, Malmö, Sweden.
    Panico, Salvatore
    Pala, Valeria
    Palli, Domenico
    Tumino, Rosario
    Peeters, Petra H
    Siersema, Peter D
    Bueno-de-Mesquita, H B
    Trichopoulou, Antonia
    Klinaki, Eleni
    Tsironis, Christos
    Agudo, Antonio
    Navarro, Carmen
    Sánchez, María-José
    Barricarte, Aurelio
    Boutron-Ruault, Marie-Christine
    Fagherazzi, Guy
    Racine, Antoine
    Weiderpass, Elisabete
    Gunter, Marc J
    Riboli, Elio
    Comparison of abdominal adiposity and overall obesity in relation to risk of small intestinal cancer in a European Prospective Cohort2016In: Cancer Causes and Control, ISSN 0957-5243, E-ISSN 1573-7225, Vol. 27, no 7, p. 919-927Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: The etiology of small intestinal cancer (SIC) is largely unknown, and there are very few epidemiological studies published to date. No studies have investigated abdominal adiposity in relation to SIC.

    METHODS: We investigated overall obesity and abdominal adiposity in relation to SIC in the European Prospective Investigation into Cancer and Nutrition (EPIC), a large prospective cohort of approximately half a million men and women from ten European countries. Overall obesity and abdominal obesity were assessed by body mass index (BMI), waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR). Multivariate Cox proportional hazards regression modeling was performed to estimate hazard ratios (HRs) and 95 % confidence intervals (CIs). Stratified analyses were conducted by sex, BMI, and smoking status.

    RESULTS: During an average of 13.9 years of follow-up, 131 incident cases of SIC (including 41 adenocarcinomas, 44 malignant carcinoid tumors, 15 sarcomas and 10 lymphomas, and 21 unknown histology) were identified. WC was positively associated with SIC in a crude model that also included BMI (HR per 5-cm increase = 1.20, 95 % CI 1.04, 1.39), but this association attenuated in the multivariable model (HR 1.18, 95 % CI 0.98, 1.42). However, the association between WC and SIC was strengthened when the analysis was restricted to adenocarcinoma of the small intestine (multivariable HR adjusted for BMI = 1.56, 95 % CI 1.11, 2.17). There were no other significant associations.

    CONCLUSION: WC, rather than BMI, may be positively associated with adenocarcinomas but not carcinoid tumors of the small intestine.

    IMPACT: Abdominal obesity is a potential risk factor for adenocarcinoma in the small intestine.

    Download full text (pdf)
    fulltext
  • 36. Marouli, Eirini
    et al.
    Graff, Mariaelisa
    Medina-Gomez, Carolina
    Lo, Ken Sin
    Wood, Andrew R.
    Kjaer, Troels R.
    Fine, Rebecca S.
    Lu, Yingchang
    Schurmann, Claudia
    Highland, Heather M.
    Rueger, Sina
    Thorleifsson, Gudmar
    Justice, Anne E.
    Lamparter, David
    Stirrups, Kathleen E.
    Turcot, Valerie
    Young, Kristin L.
    Winkler, Thomas W.
    Esko, Tonu
    Karaderi, Tugce
    Locke, Adam E.
    Masca, Nicholas G. D.
    Ng, Maggie C. Y.
    Mudgal, Poorva
    Rivas, Manuel A.
    Vedantam, Sailaja
    Mahajan, Anubha
    Guo, Xiuqing
    Abecasis, Goncalo
    Aben, Katja K.
    Adair, Linda S.
    Alam, Dewan S.
    Albrecht, Eva
    Allin, Kristine H.
    Allison, Matthew
    Amouyel, Philippe
    Appel, Emil V.
    Arveiler, Dominique
    Asselbergs, Folkert W.
    Auer, Paul L.
    Balkau, Beverley
    Banas, Bernhard
    Bang, Lia E.
    Benn, Marianne
    Bergmann, Sven
    Bielak, Lawrence F.
    Blueher, Matthias
    Boeing, Heiner
    Boerwinkle, Eric
    Boeger, Carsten A.
    Bonnycastle, Lori L.
    Bork-Jensen, Jette
    Bots, Michiel L.
    Bottinger, Erwin P.
    Bowden, Donald W.
    Brandslund, Ivan
    Breen, Gerome
    Brilliant, Murray H.
    Broer, Linda
    Burt, Amber A.
    Butterworth, Adam S.
    Carey, David J.
    Caulfield, Mark J.
    Chambers, John C.
    Chasman, Daniel I.
    Chen, Yii-Der Ida
    Chowdhury, Rajiv
    Christensen, Cramer
    Chu, Audrey Y.
    Cocca, Massimiliano
    Collins, Francis S.
    Cook, James P.
    Corley, Janie
    Galbany, Jordi Corominas
    Cox, Amanda J.
    Cuellar-Partida, Gabriel
    Danesh, John
    Davies, Gail
    de Bakker, Paul I. W.
    de Borst, Gert J.
    de Denus, Simon
    de Groot, Mark C. H.
    de Mutsert, Renee
    Deary, Ian J.
    Dedoussis, George
    Demerath, Ellen W.
    den Hollander, Anneke I.
    Dennis, Joe G.
    Di Angelantonio, Emanuele
    Drenos, Fotios
    Du, Mengmeng
    Dunning, Alison M.
    Easton, Douglas F.
    Ebeling, Tapani
    Edwards, Todd L.
    Ellinor, Patrick T.
    Elliott, Paul
    Evangelou, Evangelos
    Farmaki, Aliki-Eleni
    Faul, Jessica D.
    Feitosa, Mary F.
    Feng, Shuang
    Ferrannini, Ele
    Ferrario, Marco M.
    Ferrieres, Jean
    Florez, Jose C.
    Ford, Ian
    Fornage, Myriam
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Frikke-Schmidt, Ruth
    Galesloot, Tessel E.
    Gan, Wei
    Gandin, Ilaria
    Gasparini, Paolo
    Giedraitis, Vilmantas
    Giri, Ayush
    Girotto, Giorgia
    Gordon, Scott D.
    Gordon-Larsen, Penny
    Gorski, Mathias
    Grarup, Niels
    Grove, Megan L.
    Gudnason, Vilmundur
    Gustafsson, Stefan
    Hansen, Torben
    Harris, Kathleen Mullan
    Harris, Tamara B.
    Hattersley, Andrew T.
    Hayward, Caroline
    He, Liang
    Heid, Iris M.
    Heikkila, Kauko
    Helgeland, Oyvind
    Hernesniemi, Jussi
    Hewitt, Alex W.
    Hocking, Lynne J.
    Hollensted, Mette
    Holmen, Oddgeir L.
    Hovingh, G. Kees
    Howson, Joanna M. M.
    Hoyng, Carel B.
    Huang, Paul L.
    Hveem, Kristian
    Ikram, M. Arfan
    Ingelsson, Erik
    Jackson, Anne U.
    Jansson, Jan-Håkan
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Jarvik, Gail P.
    Jensen, Gorm B.
    Jhun, Min A.
    Jia, Yucheng
    Jiang, Xuejuan
    Johansson, Stefan
    Jorgensen, Marit E.
    Jorgensen, Torben
    Jousilahti, Pekka
    Jukema, J. Wouter
    Kahali, Bratati
    Kahn, Rene S.
    Kahonen, Mika
    Kamstrup, Pia R.
    Kanoni, Stavroula
    Kaprio, Jaakko
    Karaleftheri, Maria
    Kardia, Sharon L. R.
    Karpe, Fredrik
    Kee, Frank
    Keeman, Renske
    Kiemeney, Lambertus A.
    Kitajima, Hidetoshi
    Kluivers, Kirsten B.
    Kocher, Thomas
    Komulainen, Pirjo
    Kontto, Jukka
    Kooner, Jaspal S.
    Kooperberg, Charles
    Kovacs, Peter
    Kriebel, Jennifer
    Kuivaniemi, Helena
    Kury, Sebastien
    Kuusisto, Johanna
    La Bianca, Martina
    Laakso, Markku
    Lakka, Timo A.
    Lange, Ethan M.
    Lange, Leslie A.
    Langefeld, Carl D.
    Langenberg, Claudia
    Larson, Eric B.
    Lee, I-Te
    Lehtimaki, Terho
    Lewis, Cora E.
    Li, Huaixing
    Li, Jin
    Li-Gao, Ruifang
    Lin, Honghuang
    Lin, Li-An
    Lin, Xu
    Lind, Lars
    Lindstrom, Jaana
    Linneberg, Allan
    Liu, Yeheng
    Liu, Yongmei
    Lophatananon, Artitaya
    Luan, Jian'an
    Lubitz, Steven A.
    Lyytikainen, Leo-Pekka
    Mackey, David A.
    Madden, Pamela A. F.
    Manning, Alisa K.
    Mannisto, Satu
    Marenne, Gaelle
    Marten, Jonathan
    Martin, Nicholas G.
    Mazul, Angela L.
    Meidtner, Karina
    Metspalu, Andres
    Mitchell, Paul
    Mohlke, Karen L.
    Mook-Kanamori, Dennis O.
    Morgan, Anna
    Morris, Andrew D.
    Morris, Andrew P.
    Mueller-Nurasyid, Martina
    Munroe, Patricia B.
    Nalls, Mike A.
    Nauck, Matthias
    Nelson, Christopher P.
    Neville, Matt
    Nielsen, Sune F.
    Nikus, Kjell
    Njolstad, Pal R.
    Nordestgaard, Borge G.
    Ntalla, Ioanna
    O'Connel, Jeffrey R.
    Oksa, Heikki
    Loohuis, Loes M. Olde
    Ophoff, Roel A.
    Owen, Katharine R.
    Packard, Chris J.
    Padmanabhan, Sandosh
    Palmer, Colin N. A.
    Pasterkamp, Gerard
    Patel, Aniruddh P.
    Pattie, Alison
    Pedersen, Oluf
    Peissig, Peggy L.
    Peloso, Gina M.
    Pennell, Craig E.
    Perola, Markus
    Perry, James A.
    Perry, John R. B.
    Person, Thomas N.
    Pirie, Ailith
    Polasek, Ozren
    Posthuma, Danielle
    Raitakari, Olli T.
    Rasheed, Asif
    Rauramaa, Rainer
    Reilly, Dermot F.
    Reiner, Alex P.
    Renstrom, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research.
    Ridker, Paul M.
    Rioux, John D.
    Robertson, Neil
    Robino, Antonietta
    Rolandsson, Olov
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Rudan, Igor
    Ruth, Katherine S.
    Saleheen, Danish
    Salomaa, Veikko
    Samani, Nilesh J.
    Sandow, Kevin
    Sapkota, Yadav
    Sattar, Naveed
    Schmidt, Marjanka K.
    Schreiner, Pamela J.
    Schulze, Matthias B.
    Scott, Robert A.
    Segura-Lepe, Marcelo P.
    Shah, Svati
    Sim, Xueling
    Sivapalaratnam, Suthesh
    Small, Kerrin S.
    Smith, Albert Vernon
    Smith, Jennifer A.
    Southam, Lorraine
    Spector, Timothy D.
    Speliotes, Elizabeth K.
    Starr, John M.
    Steinthorsdottir, Valgerdur
    Stringham, Heather M.
    Stumvoll, Michael
    Surendran, Praveen
    t Hart, Leen M.
    Tansey, Katherine E.
    Tardif, Jean-Claude
    Taylor, Kent D.
    Teumer, Alexander
    Thompson, Deborah J.
    Thorsteinsdottir, Unnur
    Thuesen, Betina H.
    Toenjes, Anke
    Tromp, Gerard
    Trompet, Stella
    Tsafantakis, Emmanouil
    Tuomilehto, Jaakko
    Tybjaerg-Hansen, Anne
    Tyrer, Jonathan P.
    Uher, Rudolf
    Uitterlinden, Andre G.
    Ulivi, Sheila
    van der Laan, Sander W.
    Van Der Leij, Andries R.
    van Duijn, Cornelia M.
    van Schoor, Natasja M.
    van Setten, Jessica
    Varbo, Anette
    Varga, Tibor V.
    Varma, Rohit
    Edwards, Digna R. Velez
    Vermeulen, Sita H.
    Vestergaard, Henrik
    Vitart, Veronique
    Vogt, Thomas F.
    Vozzi, Diego
    Walker, Mark
    Wang, Feijie
    Wang, Carol A.
    Wang, Shuai
    Wang, Yiqin
    Wareham, Nicholas J.
    Warren, Helen R.
    Wessel, Jennifer
    Willems, Sara M.
    Wilson, James G.
    Witte, Daniel R.
    Woods, Michael O.
    Wu, Ying
    Yaghootkar, Hanieh
    Yao, Jie
    Yao, Pang
    Yerges-Armstrong, Laura M.
    Young, Robin
    Zeggini, Eleftheria
    Zhan, Xiaowei
    Zhang, Weihua
    Zhao, Jing Hua
    Zhao, Wei
    Zheng, He
    Zhou, Wei
    Rotter, Jerome I.
    Boehnke, Michael
    Kathiresan, Sekar
    McCarthy, Mark I.
    Willer, Cristen J.
    Stefansson, Kari
    Borecki, Ingrid B.
    Liu, Dajiang J.
    North, Kari E.
    Heard-Costa, Nancy L.
    Pers, Tune H.
    Lindgren, Cecilia M.
    Oxvig, Claus
    Kutalik, Zoltan
    Rivadeneira, Fernando
    Loos, Ruth J. F.
    Frayling, Timothy M.
    Hirschhorn, Joel N.
    Deloukas, Panos
    Lettre, Guillaume
    Rare and low-frequency coding variants alter human adult height2017In: Nature, ISSN 0028-0836, E-ISSN 1476-4687, Vol. 542, no 7640, p. 186-190Article in journal (Refereed)
    Abstract [en]

    Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.

  • 37. Nettleton, Jennifer A
    et al.
    Follis, Jack L
    Ngwa, Julius S
    Smith, Caren E
    Ahmad, Shafqat
    Tanaka, Toshiko
    Wojczynski, Mary K
    Voortman, Trudy
    Lemaitre, Rozenn N
    Kristiansson, Kati
    Nuotio, Marja-Liisa
    Houston, Denise K
    Perälä, Mia-Maria
    Qi, Qibin
    Sonestedt, Emily
    Manichaikul, Ani
    Kanoni, Stavroula
    Ganna, Andrea
    Mikkilä, Vera
    North, Kari E
    Siscovick, David S
    Harald, Kennet
    Mckeown, Nicola M
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Odontology. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Rissanen, Harri
    Liu, Yongmei
    Lahti, Jari
    Hu, Frank B
    Bandinelli, Stefania
    Rukh, Gull
    Rich, Stephen
    Booij, Lisanne
    Dmitriou, Maria
    Ax, Erika
    Raitakari, Olli
    Mukamal, Kenneth
    Männistö, Satu
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Biobank Research. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Jula, Antti
    Ericson, Ulrika
    Jacobs, David R, Jr
    Van Rooij, Frank J A
    Deloukas, Panos
    Sjögren, Per
    Kähönen, Mika
    Djousse, Luc
    Perola, Markus
    Barroso, Inês
    Hofman, Albert
    Stirrups, Kathleen
    Viikari, Jorma
    Uitterlinden, André G
    Kalafati, Ioanna P
    Franco, Oscar H.
    Mozaffarian, Dariush
    Salomaa, Veikko
    Borecki, Ingrid B
    Knekt, Paul
    Kritchevsky, Stephen B
    Eriksson, Johan G
    Dedoussis, George V
    Qi, Lu
    Ferrucci, Luigi
    Orho-Melander, Marju
    Zillikens, M Carola
    Ingelsson, Erik
    Lehtimäki, Terho
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Sweden.
    Cupples, L Adrienne
    Loos, Ruth J F
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Sweden; Department of Nutrition, Harvard Chan School of Public Health, Boston, MA, USA.
    Gene x dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry2015In: Human Molecular Genetics, ISSN 0964-6906, E-ISSN 1460-2083, Vol. 24, no 16, p. 4728-4738Article in journal (Refereed)
    Abstract [en]

    Obesity is highly heritable. Genetic variants showing robust associationswith obesity traits have been identified through genome wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphismswere genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjustedWHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjustedWHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.

    Download full text (pdf)
    fulltext
  • 38. Nettleton, Jennifer A.
    et al.
    Hivert, Marie-France
    Lemaitre, Rozenn N.
    McKeown, Nicola M.
    Mozaffarian, Dariush
    Tanaka, Toshiko
    Wojczynski, Mary K.
    Hruby, Adela
    Djousse, Luc
    Ngwa, Julius S.
    Follis, Jack L.
    Dimitriou, Maria
    Ganna, Andrea
    Houston, Denise K.
    Kanoni, Stavroula
    Mikkila, Vera
    Manichaikul, Ani
    Ntalla, Ioanna
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Sonestedt, Emily
    van Rooij, Frank J. A.
    Bandinelli, Stefania
    de Koning, Lawrence
    Ericson, Ulrika
    Hassanali, Neelam
    Kiefte-de Jong, Jessica C.
    Lohman, Kurt K.
    Raitakari, Olli
    Papoutsakis, Constantina
    Sjogren, Per
    Stirrups, Kathleen
    Ax, Erika
    Deloukas, Panos
    Groves, Christopher J.
    Jacques, Paul F.
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Odontology, Cariology.
    Liu, Yongmei
    McCarthy, Mark I.
    North, Kari
    Viikari, Jorma
    Zillikens, M. Carola
    Dupuis, Josee
    Hofman, Albert
    Kolovou, Genovefa
    Mukamal, Kenneth
    Prokopenko, Inga
    Rolandsson, Olov
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Seppala, Ilkka
    Cupples, L. Adrienne
    Hu, Frank B.
    Kahonen, Mika
    Uitterlinden, Andre G.
    Borecki, Ingrid B.
    Ferrucci, Luigi
    Jacobs, David R., Jr.
    Kritchevsky, Stephen B.
    Orho-Melander, Marju
    Pankow, James S.
    Lehtimaki, Terho
    Witteman, Jacqueline C. M.
    Ingelsson, Erik
    Siscovick, David S.
    Dedoussis, George
    Meigs, James B.
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Meta-analysis investigating associations between healthy diet and fasting glucose and insulin levels and modification by loci associated with glucose homeostasis in data from 15 cohorts2013In: American Journal of Epidemiology, ISSN 0002-9262, E-ISSN 1476-6256, Vol. 177, no 2, p. 103-115Article, review/survey (Refereed)
    Abstract [en]

    Whether loci that influence fasting glucose (FG) and fasting insulin (FI) levels, as identified by genome-wide association studies, modify associations of diet with FG or FI is unknown. We utilized data from 15 US and European cohort studies comprising 51,289 persons without diabetes to test whether genotype and diet interact to influence FG or FI concentration. We constructed a diet score using study-specific quartile rankings for intakes of whole grains, fish, fruits, vegetables, and nuts/seeds (favorable) and red/processed meats, sweets, sugared beverages, and fried potatoes (unfavorable). We used linear regression within studies, followed by inverse-variance-weighted meta-analysis, to quantify 1) associations of diet score with FG and FI levels and 2) interactions of diet score with 16 FG-associated loci and 2 FI-associated loci. Diet score (per unit increase) was inversely associated with FG ( 0.004 mmol/L, 95 confidence interval: 0.005, 0.003) and FI ( 0.008 ln-pmol/L, 95 confidence interval: 0.009, 0.007) levels after adjustment for demographic factors, lifestyle, and body mass index. Genotype variation at the studied loci did not modify these associations. Healthier diets were associated with lower FG and FI concentrations regardless of genotype at previously replicated FG- and FI-associated loci. Studies focusing on genomic regions that do not yield highly statistically significant associations from main-effect genome-wide association studies may be more fruitful in identifying diet-gene interactions.

  • 39. Nettleton, Jennifer A
    et al.
    McKeown, Nicola M
    Kanoni, Stavroula
    Lemaitre, Rozenn N
    Hivert, Marie-France
    Ngwa, Julius
    van Rooij, Frank J A
    Sonestedt, Emily
    Wojczynski, Mary K
    Ye, Zheng
    Tanaka, Toshiko
    Garcia, Melissa
    Anderson, Jennifer S
    Follis, Jack L
    Djousse, Luc
    Mukamal, Kenneth
    Papoutsakis, Constantina
    Mozaffarian, Dariush
    Zillikens, M Carola
    Bandinelli, Stefania
    Bennett, Amanda J
    Borecki, Ingrid B
    Feitosa, Mary F
    Ferrucci, Luigi
    Forouhi, Nita G
    Groves, Christopher J
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Harris, Tamara
    Hofman, Albert
    Houston, Denise K
    Hu, Frank B
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Odontology.
    Kritchevsky, Stephen B
    Langenberg, Claudia
    Launer, Lenore
    Liu, Yongmei
    Loos, Ruth J
    Nalls, Michael
    Orho-Melander, Marju
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Rice, Kenneth
    Riserus, Ulf
    Rolandsson, Olov
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Rotter, Jerome I
    Saylor, Georgia
    Sijbrands, Eric JG
    Sjögren, Per
    Smith, Albert
    Steingrímsdóttir, Laufey
    Uitterlinden, André G
    Wareham, Nicholas J
    Prokopenko, Inga
    Pankow, James S
    van Duijn, Cornelia M
    Flores, Jose C
    Witteman, Jaqueline CM
    Dupuis, Josée
    Dedoussis, George V
    Ordovas, Jose M
    Ingelsson, Erik
    Cupples, L Adrienne
    Siscovick, David S
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Meigs, James B
    Interactions of dietary whole-grain intake with fasting glucose- and insulin-related genetic loci in individuals of European descent: a meta-analysis of 14 cohort studies2010In: Diabetes Care, ISSN 0149-5992, E-ISSN 1935-5548, Vol. 33, no 12, p. 2684-2691Article in journal (Refereed)
    Abstract [en]

    Our results support the favorable association of whole-grain intake with fasting glucose and insulin and suggest a potential interaction between variation in GCKR and whole-grain intake in influencing fasting insulin concentrations.

  • 40. Pomeroy, Jeremy
    et al.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Gradmark, Anna
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Steiginga, S
    Persson, M
    Wright, A
    Bluck, L
    Domellöf, M
    Kahn, SE
    Mogren, I
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Metabolic risk-factor profiles in infants in relation to those of their mothers during pregnancy2011Other (Other academic)
    Abstract [en]

    Background Maternal characteristics during pregnancy such as BMI, weight gain, and glucose tolerance have been associated with anthropometric traits in their offspring. Here we extend these observations looking at the associations between maternal body composition, weight gain by trimester, and glucose tolerance and anthropometrics in their infants.

    Materials and methods Participants were 31 (16 female) singleton babies and their mothers (aged 25-35 yrs) in the eastern area of the county of Västerbotten in Sweden. Maternal weight was measured at gestational weeks 10-12, 28-32, and 37-41. Maternal body composition was assessed using isotope dilution and gestational glucose tolerance was assessed with a 2-hour, 75-gram oral glucose challenge at 28-32 weeks gestation. Infant body composition was assessed at 11-19 weeks of age using air- displacement plethysmography. The relationships between maternal and infant variables were assessed with Spearman correlations.

    Results Mid-pregnancy weight gain was significantly positively related to fat mass (r=0.41, p= 0.022) but not fat-free mass whereas late-pregnancy weight gain was significantly positively related to infant fat-free mass (r=0.37, p=0.04) but not fat mass. Maternal weight, body composition, or glucose tolerance was not significantly related to infant body composition. Early infancy growth (weight-for-length growth z-score) from 0 to 4 months was significantly related to infant percent fat (r=0.48, p=0.006). Gestational weight gain by trimester is differently related to body composition assessed in early infancy. Additionally, greater early infancy growth is associated with higher percent fat at 4 months of age. Both of these findings might identify targets for interventions conducted in pregnancy and during early life.

  • 41. Poveda, Alaitz
    et al.
    Atabaki-Pasdar, Naeimeh
    Ahmad, Shafqat
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research. Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden; Division of Endocrinology and Diabetes, Cantonal Hospital St. Gallen, St. Gallen, Switzerland.
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research. Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden Department of Nutrition, Harvard Chan School of Public Health, Boston, MA.
    Association of Established Blood Pressure Loci With 10-Year Change in Blood Pressure and Their Ability to Predict Incident Hypertension2020In: Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, ISSN 2047-9980, E-ISSN 2047-9980, Vol. 9, no 16, article id e014513Article in journal (Refereed)
    Abstract [en]

    Background: Genome‐wide association studies have identified >1000 genetic variants cross‐sectionally associated with blood pressure variation and prevalent hypertension. These discoveries might aid the early identification of subpopulations at risk of developing hypertension or provide targets for drug development, amongst other applications. The aim of the present study was to analyze the association of blood pressure‐associated variants with long‐term changes (10 years) in blood pressure and also to assess their ability to predict hypertension incidence compared with traditional risk variables in a Swedish population.

    Methods and Results: We constructed 6 genetic risk scores (GRSs) by summing the dosage of the effect allele at each locus of genetic variants previously associated with blood pressure traits (systolic blood pressure GRS (GRSSBP): 554 variants; diastolic blood pressure GRS (GRSDBP): 481 variants; mean arterial pressure GRS (GRSMAP): 20 variants; pulse pressure GRS (GRSPP): 478 variants; hypertension GRS (GRSHTN): 22 variants; combined GRS (GRScomb): 1152 variants). Each GRS was longitudinally associated with its corresponding blood pressure trait, with estimated effects per GRS SD unit of 0.50 to 1.21 mm Hg for quantitative traits and odds ratios (ORs) of 1.10 to 1.35 for hypertension incidence traits. The GRScomb was also significantly associated with hypertension incidence defined according to European guidelines (OR, 1.22 per SD; 95% CI, 1.10‒1.35) but not US guidelines (OR, 1.11 per SD; 95% CI, 0.99‒1.25) while controlling for traditional risk factors. The addition of GRScomb to a model containing traditional risk factors only marginally improved discrimination (Δarea under the ROC curve = 0.001–0.002).

    Conclusions: GRSs based on discovered blood pressure‐associated variants are associated with long‐term changes in blood pressure traits and hypertension incidence, but the inclusion of genetic factors in a model composed of conventional hypertension risk factors did not yield a material increase in predictive ability.

    Download full text (pdf)
    fulltext
  • 42. Poveda, Alaitz
    et al.
    Chen, Yan
    Brändström, Anders
    Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
    Engberg, Elisabeth
    Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Biobank Research.
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Biobank Research.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Clinical Research Centre, Lund University, Jan Waldenströms gata 35, Building 91, Skåne University Hospital, SE-20502 Malmö, Sweden.
    Kurbasic, Azra
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Clinical Research Centre, Lund University, Jan Waldenströms gata 35, Building 91, Skåne University Hospital, SE-20502 Malmö, Sweden; Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
    The heritable basis of gene-environment interactions in cardiometabolic traits2017In: Diabetologia, ISSN 0012-186X, E-ISSN 1432-0428, Vol. 60, no 3, p. 442-452Article in journal (Refereed)
    Abstract [en]

    Aims/hypothesis Little is known about the heritable basis of gene-environment interactions in humans. We therefore screened multiple cardiometabolic traits to assess the probability that they are influenced by genotype-environment interactions.

    Methods Fourteen established environmental risk exposures and 11 cardiometabolic traits were analysed in the VIKING study, a cohort of 16,430 Swedish adults from 1682 extended pedigrees with available detailed genealogical, phenotypic and demographic information, using a maximum likelihood variance decomposition method in Sequential Oligogenic Linkage Analysis Routines software.

    Results All cardiometabolic traits had statistically significant heritability estimates, with narrow-sense heritabilities (h (2)) ranging from 24% to 47%. Genotype-environment interactions were detected for age and sex (for the majority of traits), physical activity (for triacylglycerols, 2 h glucose and diastolic BP), smoking (for weight), alcohol intake (for weight, BMI and 2 h glucose) and diet pattern (for weight, BMI, glycaemic traits and systolic BP). Genotype-age interactions for weight and systolic BP, genotype-sex interactions for BMI and triacylglycerols and genotype-alcohol intake interactions for weight remained significant after multiple test correction.

    Conclusion/hypothesis Age, sex and alcohol intake are likely to be major modifiers of genetic effects for a range of cardiometabolic traits. This information may prove valuable for studies that seek to identify specific loci that modify the effects of lifestyle in cardiometabolic disease.

    Download full text (pdf)
    fulltext
  • 43. Poveda, Alaitz
    et al.
    Koivula, Robert W.
    Ahmad, Shafqat
    Barroso, Ines
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Biobank Research.
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Odontology.
    Renstrom, Frida
    Umeå University, Faculty of Medicine, Department of Biobank Research. Lund Univ, Dept Clin Sci, Genet & Mol Epidemiol Unit, Malmö, Sweden.
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Innate biology versus lifestyle behaviour in the aetiology of obesity and type 2 diabetes: the GLACIER Study2016In: Diabetologia, ISSN 0012-186X, E-ISSN 1432-0428, Vol. 59, no 3, p. 462-471Article in journal (Refereed)
    Abstract [en]

    Aims/hypothesis We compared the ability of genetic (established type 2 diabetes, fasting glucose, 2 h glucose and obesity variants) and modifiable lifestyle (diet, physical activity, smoking, alcohol and education) risk factors to predict incident type 2 diabetes and obesity in a population-based prospective cohort of 3,444 Swedish adults studied sequentially at baseline and 10 years later. Methods Multivariable logistic regression analyses were used to assess the predictive ability of genetic and lifestyle risk factors on incident obesity and type 2 diabetes by calculating the AUC. Results The predictive accuracy of lifestyle risk factors was similar to that yielded by genetic information for incident type 2 diabetes (AUC 75% and 74%, respectively) and obesity (AUC 68% and 73%, respectively) in models adjusted for age, age2 and sex. The addition of genetic information to the lifestyle model significantly improved the prediction of type 2 diabetes (AUC 80%; p = 0.0003) and obesity (AUC 79%; p < 0.0001) and resulted in a net reclassification improvement of 58% for type 2 diabetes and 64% for obesity. Conclusions/interpretation These findings illustrate that lifestyle and genetic information separately provide a similarly high degree of long-range predictive accuracy for obesity and type 2 diabetes.

  • 44.
    Poveda, Alaitz
    et al.
    Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden.
    Pomares-Millan, Hugo
    Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden.
    Chen, Yan
    Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden; Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Kurbasic, Azra
    Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden.
    Patel, Chirag J.
    Department of Biomedical Informatics, Harvard Medical School, MA, Boston, United States.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Medicine. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden; Division of Endocrinology and Diabetes, Cantonal Hospital St. Gallen, St. Gallen, Switzerland.
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Sustainable Health.
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Odontology.
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Sustainable Health. Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden; Department of Nutrition, Harvard T.H. Chan School of Public Health, MA, Boston, United States.
    Exposome-wide ranking of modifiable risk factors for cardiometabolic disease traits2022In: Scientific Reports, E-ISSN 2045-2322, Vol. 12, no 1, article id 4088Article in journal (Refereed)
    Abstract [en]

    The present study assessed the temporal associations of ~ 300 lifestyle exposures with nine cardiometabolic traits to identify exposures/exposure groups that might inform lifestyle interventions for the reduction of cardiometabolic disease risk. The analyses were undertaken in a longitudinal sample comprising > 31,000 adults living in northern Sweden. Linear mixed models were used to assess the average associations of lifestyle exposures and linear regression models were used to test associations with 10-year change in the cardiometabolic traits. ‘Physical activity’ and ‘General Health’ were the exposure categories containing the highest number of ‘tentative signals’ in analyses assessing the average association of lifestyle variables, while ‘Tobacco use’ was the top category for the 10-year change association analyses. Eleven modifiable variables showed a consistent average association among the majority of cardiometabolic traits. These variables belonged to the domains: (i) Smoking, (ii) Beverage (filtered coffee), (iii) physical activity, (iv) alcohol intake, and (v) specific variables related to Nordic lifestyle (hunting/fishing during leisure time and boiled coffee consumption). We used an agnostic, data-driven approach to assess a wide range of established and novel risk factors for cardiometabolic disease. Our findings highlight key variables, along with their respective effect estimates, that might be prioritised for subsequent prediction models and lifestyle interventions.

    Download full text (pdf)
    fulltext
  • 45.
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine.
    Fat cell insulin resistance: an experimental study focusing on molecular mechanisms in type 2 diabetes2007Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The aim of the present thesis was to further increase our understanding of mechanisms contributing to and maintaining cellular insulin resistance in type 2 diabetes (T2D). For this reason, the effects of high glucose and insulin levels on glucose transport capacity and insulin signaling, with emphasis on insulin receptor substrate 1 (IRS-1) were assessed in fat cells. Altered levels of IRS-1 have previously been observed in adipose tissue from insulin-resistant and T2D subjects.

    A high glucose level (≥15 mM) for 24 h exerted only a minor impairment on glucose transport capacity in human adipocytes, as opposed to rat adipocytes. However, when combined with a high insulin level (104 µU/ml), basal and insulin-stimulated glucose transport was significantly impaired in both human and rat adipocytes. This was associated with a depletion of IRS-1 and IRS-2 protein levels in rat adipocytes, as a result of post-translational changes and altered gene transcription, respectively. In human adipocytes was only IRS-1 protein levels reduced. The high glucose/high insulin setting achieved maximal impairment of glucose transport within 6 h. Subsequent incubations of rat adipocytes under physiological conditions could partially restore insulin sensitivity. Interestingly, in both human and rat fat cells, decreased levels of IRSs occurred after the establishment of impaired glucose transport, suggesting that the observed depletion of IRSs is a consequence rather than a cause of insulin resistance. Nonetheless, IRS depletion is likely to further aggravate insulin resistance.

    Tyrosine phosphorylation of IRS-1 upon insulin stimulation activates the signaling pathway that mediates glucose transport. Pre-treatment of human adipocytes with high glucose and insulin levels was not associated with any alterations in the total IRS-1 Tyr612 phosphorylation following 10 min insulin stimulation. However, a significant increase in basal Tyr612 phosphorylation was observed. Furthermore, a rise in basal IRS-1 Ser312 phosphorylation was found. This is associated with reduced IRS-1 function and is considered to target IRS-1 to degradation pathways, and thus could potentially explain the observed decrease in IRS-1 protein levels. Our results imply an enhanced activation of insulin’s negative-feedback control mechanism that inhibit IRS-1 function. This could potentially have contributed to the observed impairment of insulin action on glucose transport in these cells. Accordingly, we have also shown that the downstream activation of protein kinase B upon insulin-stimulation is significantly impaired in human adipocytes exposed to the high glucose/high insulin setting, indicating a defect in the signaling pathway mediating glucose transport.

    We also investigated whether there are humoral factors in the circulation of T2D patients that contribute to peripheral insulin resistance. Human adipocytes cultured for 24 h in medium supplemented with 25% serum from T2D subjects, as compared to serum from non-diabetic subjects, displayed significantly reduced insulin-stimulated glucose uptake capacity. The effect could neither be attributed to glucose, insulin, FFA, TNF-α or IL-6 levels in the serum, but other circulating factor(s) seem to be of importance.

    In conclusion, chronic conditions of elevated glucose and/or insulin levels all impair insulin action on glucose turnover, but to different extents. A clear distinction between rat and human fat cells in the response to these different milieus was also observed. Alterations in the function of the key insulin signaling protein IRS-1 might be involved in the mechanisms underlying the impaired glucose uptake capacity. IRS-1 reduction however, occurs after but probably aggravates the existing insulin resistance. The effects of high glucose and/or insulin levels may be of importance in T2D, but additional novel factors present in the circulation of T2D patients seem to contribute to cellular insulin resistance.

    Download full text (pdf)
    FULLTEXT01
  • 46.
    Renström, Frida
    et al.
    Umeå University, Faculty of Medicine, Public Health and Clinical Medicine, Medicine.
    Burén, Jonas
    Umeå University, Faculty of Medicine, Public Health and Clinical Medicine, Medicine.
    Svensson, M K
    Eriksson, J W
    Factors in serum from type 2 diabetes patients can cause cellular insulin resistance.2009In: Hormone and Metabolic Research, ISSN 0018-5043, E-ISSN 1439-4286, Vol. 41, no 10, p. 767-772Article in journal (Refereed)
    Abstract [en]

    This pilot study was aimed to investigate whether there are humoral factors in serum from type 2 diabetic subjects that, in addition to glucose, insulin and free fatty acids are able to induce or contribute to peripheral insulin resistance with respect to glucose transport. Isolated subcutaneous adipocytes from 11 type 2 diabetic subjects and 10 nondiabetic controls were incubated for 24-h in medium supplemented with 25 % serum from a control or a type 2 diabetic donor, in the presence of a low (5 mM) or a high (15 mM) glucose concentration, respectively. After the incubation period glucose uptake capacity was assessed. Serum from type 2 diabetic donors, compared to serum from controls, significantly reduced the maximal insulin eff ect to stimulate glucose uptake (approximately 40 %, p < 0.05) in adipocytes from control subjects, independent of surrounding glucose concentrations. Glucose uptake capacity in adipocytes isolated from type 2 diabetic subjects was similar regardless of culture condition. No significant alterations were found in cellular content of key proteins in the insulin signaling cascade (insulin receptor substrate-1 and -2, and glucose transporter 4) that could explain the impaired insulin-stimulated glucose transport in control adipocytes incubated with serum from type 2 diabetic donors. The present findings indicate the presence of biomolecules in the circulation of type 2 diabetic subjects, apart from glucose, insulin, and free fatty acids with the ability to induce peripheral insulin resistance. This further implies that even though normoglycemia is achieved other circulating factors can still negatively aff ect insulin sensitivity in type 2 diabetic patients.

  • 47.
    Renström, Frida
    et al.
    Umeå University, Faculty of Medicine, Department of Biobank Research. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research. Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
    Koivula, Robert W.
    Varga, Tibor V.
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Biobank Research. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Mulder, Hindrik
    Florez, Jose C.
    Hu, Frank B.
    Franks, Paul W.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
    Season-dependent associations of circadian rhythm-regulating loci (CRY1, CRY2 and MTNR1B) and glucose homeostasis: the GLACIER Study2015In: Diabetologia, ISSN 0012-186X, E-ISSN 1432-0428, Vol. 58, no 5, p. 997-1005Article in journal (Refereed)
    Abstract [en]

    Aims/hypothesis The association of single nucleotide polymorphisms (SNPs) proximal to CRY2 and MTNR1B with fasting glucose is well established. CRY1/2 and MTNR1B encode proteins that regulate circadian rhythmicity and influence energy metabolism. Here we tested whether season modified the relationship of these loci with blood glucose concentration. Methods SNPs rs8192440 (CRY1), rs11605924 (CRY2) and rs10830963 (MTNR1B) were genotyped in a prospective cohort study from northern Sweden (n = 16,499). The number of hours of daylight exposure during the year ranged from 4.5 to 22 h daily. Owing to the non-linear distribution of daylight throughout the year, season was dichotomised based on the vernal and autumnal equinoxes. Effect modification was assessed using linear regression models fitted with a SNP x season interaction term, marginal effect terms and putative confounding variables, with fasting or 2 h glucose concentrations as outcomes. Results The rs8192440 (CRY1) variant was only associated with fasting glucose among participants (n = 2,318) examined during the light season (beta = -0.04 mmol/l per A allele, 95% CI -0.08, -0.01, p = 0.02, p (interaction) = 0.01). In addition to the established association with fasting glucose, the rs11605924 (CRY2) and rs10830963 (MTNR1B) loci were associated with 2 h glucose concentrations (beta = 0.07 mmol/l per A allele, 95% CI 0.03, 0.12, p = 0.0008, n = 9,605, and beta = -0.11 mmol/l per G allele, 95% CI -0.15, -0.06, p < 0.0001, n = 9,517, respectively), but only in participants examined during the dark season (p (interaction) = 0.006 and 0.04, respectively). Repeated measures analyses including data collected 10 years after baseline (n = 3,500) confirmed the results for the CRY1 locus (p (interaction) = 0.01). Conclusions/interpretation In summary, these observations suggest a biologically plausible season-dependent association between SNPs at CRY1, CRY2 and MTNR1B and glucose homeostasis.

  • 48.
    Renström, Frida
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Payne, Felicity
    Metabolic Disease Group, The Wellcome Trust Sanger Institute, Cambridge CB10 1SA, UK.
    Nordström, Anna
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Sports Medicine.
    Brito, Ema C
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Rolandsson, Olov
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Barroso, Ines
    Metabolic Disease Group, The Wellcome Trust Sanger Institute, Cambridge CB10 1SA, UK.
    Nordström, Peter
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Geriatric Medicine.
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Replication and extension of genome-wide association study results for obesity in 4,923 adults from Northern Sweden.2009In: Human Molecular Genetics, ISSN 0964-6906, E-ISSN 1460-2083, Vol. 18, no 8, p. 1489-1496Article in journal (Refereed)
    Abstract [en]

    Recent genome-wide association studies (GWAS) have identified multiple risk loci for common obesity (FTO, MC4R, TMEM18, GNPDA2, SH2B1, KCTD15, MTCH2, NEGR1, and PCSK1). Here we extend those studies by examining associations with adiposity and type 2 diabetes in Swedish adults. The nine single nucleotide polymorphisms (SNPs) were genotyped in 3,885 non-diabetic and 1,038 diabetic individuals with available measures of height, weight and BMI. Adipose mass and distribution was objectively assessed using dual energy X-ray absorptiometry (DEXA) in a sub-group of non-diabetics (n=2,206). In models with adipose mass traits, BMI or obesity as outcomes, the most strongly associated SNP was FTO rs1121980 (P<0.001). Five other SNPs (SH2B1 rs7498665, MTCH2 rs4752856, MC4R rs17782313, NEGR1 rs2815752, and GNPDA2 rs10938397) were significantly associated with obesity. To summarize the overall genetic burden, a weighted risk score comprising a subset of SNPs was constructed; those in the top quintile of the score were heavier (+2.6kg) and had more total (+2.4kg), gynoid (+191g), and abdominal (+136g) adipose tissue than those in the lowest quintile (all P<0.001). The genetic burden score significantly increased diabetes risk, with those in the highest quintile (n=193/594 cases/controls) being at 1.55-fold (95% CI: 1.21-1.99; P<0.0001) greater risk of type 2 diabetes than those in the lowest quintile (n=130/655 cases/controls). In summary, we have statistically replicated six of the previously associated obese-risk loci and our results suggest that the weight-inducing effects of these variants are explained largely by increased adipose accumulation.

  • 49.
    Renström, Frida
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Shungin, Dmitry
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Johansson, Ingegerd
    Umeå University, Faculty of Medicine, Department of Odontology, Cariology.
    Florez, Jose C
    Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
    Hallmans, Göran
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Hu, Frank B
    Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts.
    Franks, Paul W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Genetic predisposition to long-term nondiabetic deteriorations in glucose homeostasis: Ten-year follow-up of the GLACIER study.2011In: Diabetes, ISSN 0012-1797, E-ISSN 1939-327X, Vol. 60, no 1, p. 345-54Article in journal (Refereed)
    Abstract [en]

    Our findings imply that genetic profiling might facilitate the early detection of persons who are genetically susceptible to deteriorating glucose control; studies of incident type 2 diabetes and discrete cardiovascular end points will help establish whether the magnitude of these changes is clinically relevant.

  • 50.
    Ruge, Toralph
    et al.
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Surgery.
    Lockton, J Andrew
    Renström, Frida
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Lystig, Theodore
    Sukonina, Valentina
    Svensson, Maria K
    Eriksson, Jan W
    Acute hyperinsulinemia raises plasma interleukin-6 in both nondiabetic and type 2 diabetes mellitus subjects, and this effect is inversely associated with body mass index.2009In: Metabolism: clinical and experimental, ISSN 1532-8600, Vol. 58, no 6, p. 860-866Article in journal (Refereed)
    Abstract [en]

    Hyperinsulinemia is a characteristic of type 2 diabetes mellitus (T2DM) and is believed to play a role in the low-grade inflammation seen in T2DM. The main aim was to study the effect of hyperinsulinemia on adipokines in individuals with different levels of insulin resistance, glycemia, and obesity. Three groups of sex-matched subjects were studied: young healthy subjects (YS; n = 10; mean age, 26 years; body mass index [BMI], 22 kg/m(2)), patients with T2DM (DS; n = 10; 61 years; BMI, 27 kg/m(2)), and age- and BMI-matched controls to DS (CS; n = 10; 60 years; BMI, 27 kg/m(2)). Plasma concentrations of adipokines were measured during a hyperinsulinemic euglycemic clamp lasting 4 hours. Moreover, insulin-stimulated glucose uptake in isolated adipocytes was analyzed to address adipose tissue insulin sensitivity. Plasma interleukin (IL)-6 increased significantly (P </= .01) in all 3 groups during hyperinsulinemia. However, the increase was smaller in both DS (P = .06) and CS (P < .05) compared with YS ( approximately 2.5-fold vs approximately 4-fold). A significant increase of plasma tumor necrosis factor (TNF) alpha was observed only in YS. There were only minor or inconsistent effects on adiponectin, leptin, and high-sensitivity C-reactive protein levels during hyperinsulinemia. Insulin-induced rise in IL-6 correlated negatively to BMI (P = .001), waist to hip ratio (P = .05), and baseline (fasting) insulin (P = .03) and IL-6 (P = .02) levels and positively to insulin-stimulated glucose uptake in isolated adipocytes (P = .07). There was no association with age or insulin sensitivity. In a multivariate analysis, also including T2DM/no T2DM, an independent correlation (inverse) was found only between BMI and fold change of IL-6 (r(2) = 0.41 for model, P < .005). Hyperinsulinemia per se can produce an increase in plasma IL-6 and TNFalpha, and this can potentially contribute to the low-grade inflammation seen in obesity and T2DM. However, obesity seems to attenuate the ability of an acute increase in insulin to further raise circulating levels of IL-6 and possibly TNFalpha.

12 1 - 50 of 65
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf