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Estimating heritability and genetic correlations from large health datasets in the absence of genetic data
Univ Chicago, IL 60637 USA.
King Abdullah Univ Sci and Technol, Saudi Arabia.
Univ Chicago, IL 60637 USA.
Univ Chicago, IL 60637 USA.
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2019 (English)In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 10, article id 5508Article in journal (Refereed) Published
Abstract [en]

Typically, estimating genetic parameters, such as disease heritability and between-disease genetic correlations, demands large datasets containing all relevant phenotypic measures and detailed knowledge of family relationships or, alternatively, genotypic and phenotypic data for numerous unrelated individuals. Here, we suggest an alternative, efficient estimation approach through the construction of two disease metrics from large health datasets: temporal disease prevalence curves and low-dimensional disease embeddings. We present eleven thousand heritability estimates corresponding to five study types: twins, traditional family studies, health records-based family studies, single nucleotide polymorphisms, and polygenic risk scores. We also compute over six hundred thousand estimates of genetic, environmental and phenotypic correlations. Furthermore, we find that: (1) disease curve shapes cluster into five general patterns; (2) early-onset diseases tend to have lower prevalence than late-onset diseases (Spearmans rho = 0.32, p amp;lt; 10(-16)); and (3) the disease onset age and heritability are negatively correlated (rho = -0.46, p amp;lt; 10(-16)).

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP , 2019. Vol. 10, article id 5508
National Category
Rheumatology and Autoimmunity
Identifiers
URN: urn:nbn:se:liu:diva-162726DOI: 10.1038/s41467-019-13455-0ISI: 000500497800001PubMedID: 31796735OAI: oai:DiVA.org:liu-162726DiVA, id: diva2:1380731
Note

Funding Agencies|DARPA Big Mechanism program under ARO [W911NF1410333]; National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [R01HL122712, 1P50MH094267, U01HL108634-01]; King Abdullah University of Science and Technology (KAUST)King Abdullah University of Science & Technology [FCC/1/1976-18-01, FCC/1/1976-23-01, FCC/1/1976-25-01, FCC/1/1976-26-01, FCS/1/4102-02-01]

Available from: 2019-12-19 Created: 2019-12-19 Last updated: 2020-01-22

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Benson, Mikael
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Division of Children's and Women's healthFaculty of Medicine and Health SciencesH.K.H. Kronprinsessan Victorias barn- och ungdomssjukhus Linköping/Motala
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