A comprehensive map of genetic relationships among diagnostic categories based on 48.6 million relative pairs from the Danish genealogy

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  • Georgios Athanasiadis
  • Joeri J. Meijsen
  • Dorte Helenius
  • Andrew J. Schork
  • Andrés Ingason
  • Wesley K. Thompson
  • Daniel H. Geschwind
  • Werge, Thomas
  • Alfonso Buil

For more than half a century, Denmark has maintained population-wide demographic, health care, and socioeconomic registers that provide detailed information on the interaction between all residents and the extensive national social services system. We leverage this resource to reconstruct the genealogy of the entire nation based on all individuals legally residing in Denmark since 1968. We cross-reference 6,691,426 individuals with nationwide health care registers to estimate heritability and genetic correlations of 10 broad diagnostic categories involving all major organs and systems. Heritability estimates for mental disorders were consistently the highest across demographic cohorts (average h2 = 0.406, 95% CI = [0.403, 0.408]), whereas estimates for cancers were the lowest (average h2 = 0.130, 95% CI = [0.125, 0.134]). The average genetic correlation of each of the 10 diagnostic categories with the other nine was highest for gastrointestinal conditions (average rg = 0.567, 95% CI = [0.566, 0.567]) and lowest for urogenital conditions (average rg = 0.386, 95% CI = [0.385, 0.388]). Mental, pulmonary, gastrointestinal, and neurological conditions had similar genetic correlation profiles.

OriginalsprogEngelsk
Artikelnummere2118688119
TidsskriftPNAS
Vol/bind119
Udgave nummer6
Antal sider9
ISSN0027-8424
DOI
StatusUdgivet - 2022

Bibliografisk note

Funding Information:
ACKNOWLEDGMENTS. This study was supported by grants from European Union’s Horizon 2020 Research and Innovation Programme: the "predicting comorbid cardiovascular disease in individuals with mental disorder by decoding disease mechanisms" project (CoMorMent, grant number 847776) and the "using real-world big data from eHealth, biobanks and national registries, integrated with clinical trial data to improve outcome of severe mental disorders" project (REALMENT, grant number 964874). The study was also supported by the Danish National Research Foundation (grant number DNRF148).

Funding Information:
This study was supported by grants from European Union's Horizon 2020 Research and Innovation Programme: the "predicting comorbid cardiovascular disease in individuals with mental disorder by decoding disease mechanisms" project (CoMorMent, grant number 847776) and the "using real-world big data from eHealth, biobanks and national registries, integrated with clinical trial data to improve outcome of severe mental disorders" project (REALMENT, grant number 964874). The study was also supported by the Danish National Research Foundation (grant number DNRF148).

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© 2022 National Academy of Sciences. All rights reserved.

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