TY - JOUR
T1 - Accounting for age of onset and family history improves power in genome-wide association studies
AU - Pedersen, Emil M
AU - Agerbo, Esben
AU - Plana-Ripoll, Oleguer
AU - Grove, Jakob
AU - Dreier, Julie W
AU - Musliner, Katherine L
AU - Bækvad-Hansen, Marie
AU - Athanasiadis, Georgios
AU - Schork, Andrew
AU - Bybjerg-Grauholm, Jonas
AU - Hougaard, David M
AU - Werge, Thomas
AU - Nordentoft, Merete
AU - Mors, Ole
AU - Dalsgaard, Søren
AU - Christensen, Jakob
AU - Børglum, Anders D
AU - Mortensen, Preben B
AU - McGrath, John J
AU - Privé, Florian
AU - Vilhjálmsson, Bjarni J
N1 - Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.
PY - 2022/3/3
Y1 - 2022/3/3
N2 - 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.
AB - 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.
KW - Age of Onset
KW - Case-Control Studies
KW - Genetic Predisposition to Disease
KW - Genome-Wide Association Study/methods
KW - Humans
KW - Medical History Taking
UR - http://www.scopus.com/inward/record.url?scp=85125234199&partnerID=8YFLogxK
U2 - 10.1016/j.ajhg.2022.01.009
DO - 10.1016/j.ajhg.2022.01.009
M3 - Journal article
C2 - 35139346
SN - 0002-9297
VL - 109
SP - 417
EP - 432
JO - American Journal of Human Genetics
JF - American Journal of Human Genetics
IS - 3
ER -