Accounting for age of onset and family history improves power in genome-wide association studies

Emil M Pedersen, Esben Agerbo, Oleguer Plana-Ripoll, Jakob Grove, Julie W Dreier, Katherine L Musliner, Marie Bækvad-Hansen, Georgios Athanasiadis, Andrew Schork, Jonas Bybjerg-Grauholm, David M Hougaard, Thomas Werge, Merete Nordentoft, Ole Mors, Søren Dalsgaard, Jakob Christensen, Anders D Børglum, Preben B Mortensen, John J McGrath, Florian PrivéBjarni J Vilhjálmsson*

*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

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Abstract

Genome-wide association studies (GWASs) have revolutionized human genetics, allowing researchers to identify thousands of disease-related genes and possible drug targets. However, case-control status does not account for the fact that not all controls may have lived through their period of risk for the disorder of interest. This can be quantified by examining the age-of-onset distribution and the age of the controls or the age of onset for cases. The age-of-onset distribution may also depend on information such as sex and birth year. In addition, family history is not routinely included in the assessment of control status. Here, we present LT-FH++, an extension of the liability threshold model conditioned on family history (LT-FH), which jointly accounts for age of onset and sex as well as family history. Using simulations, we show that, when family history and the age-of-onset distribution are available, the proposed approach yields statistically significant power gains over LT-FH and large power gains over genome-wide association study by proxy (GWAX). We applied our method to four psychiatric disorders available in the iPSYCH data and to mortality in the UK Biobank and found 20 genome-wide significant associations with LT-FH++, compared to ten for LT-FH and eight for a standard case-control GWAS. As more genetic data with linked electronic health records become available to researchers, we expect methods that account for additional health information, such as LT-FH++, to become even more beneficial.

Original languageEnglish
JournalAmerican Journal of Human Genetics
Volume109
Issue3
Pages (from-to)417-432
Number of pages16
ISSN0002-9297
DOIs
Publication statusPublished - 3 Mar 2022

Keywords

  • ADHD
  • LT-FH
  • LT-FH++
  • UKBB
  • age-of-onset
  • family history
  • genome-wide association study
  • iPSYCH
  • liability threshold model
  • mortality
  • Medical History Taking
  • Genetic Predisposition to Disease
  • Humans
  • Case-Control Studies
  • Genome-Wide Association Study/methods
  • Age of Onset

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