ADuLT: An efficient and robust time-to-event GWAS

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  • Emil M. Pedersen
  • Esben Agerbo
  • Oleguer Plana-Ripoll
  • Jette Steinbach
  • Morten D. Krebs
  • David M. Hougaard
  • Werge, Thomas
  • Nordentoft, Merete
  • Anders D. Børglum
  • Katherine L. Musliner
  • Andrea Ganna
  • Schork, Andrew Joseph
  • Preben B. Mortensen
  • John J. McGrath
  • Florian Privé
  • Bjarni J. Vilhjálmsson

Proportional hazards models have been proposed to analyse time-to-event phenotypes in genome-wide association studies (GWAS). However, little is known about the ability of proportional hazards models to identify genetic associations under different generative models and when ascertainment is present. Here we propose the age-dependent liability threshold (ADuLT) model as an alternative to a Cox regression based GWAS, here represented by SPACox. We compare ADuLT, SPACox, and standard case-control GWAS in simulations under two generative models and with varying degrees of ascertainment as well as in the iPSYCH cohort. We find Cox regression GWAS to be underpowered when cases are strongly ascertained (cases are oversampled by a factor 5), regardless of the generative model used. ADuLT is robust to ascertainment in all simulated scenarios. Then, we analyse four psychiatric disorders in iPSYCH, ADHD, Autism, Depression, and Schizophrenia, with a strong case-ascertainment. Across these psychiatric disorders, ADuLT identifies 20 independent genome-wide significant associations, case-control GWAS finds 17, and SPACox finds 8, which is consistent with simulation results. As more genetic data are being linked to electronic health records, robust GWAS methods that can make use of age-of-onset information will help increase power in analyses for common health outcomes.

OriginalsprogEngelsk
Artikelnummer5553
TidsskriftNature Communications
Vol/bind14
Antal sider12
ISSN2041-1723
DOI
StatusUdgivet - 2023

Bibliografisk note

Funding Information:
We would like to thank Jakob Grove, Doug Speed, Matthew Robinson, and Sven Erik Ojavee for valuable discussions. Parts of Fig. were created with BioRender.com . E.M.P, B.J.V. and F.P. were supported by the Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH (R102-A9118, R155-2014-1724 and R248-2017-2003), and a Lundbeck Foundation Fellowship (R335-2019-2339). J.M., B.J.V. and F.P. were also supported the Danish National Research Foundation (Niels Bohr Professorship to Prof. John McGrath). A.J.S. is supported by a Lundbeckfonden Fellowship (R335-2019-2318), and O.P.-R. is supported by a Lundbeck Foundation Fellowship (R345-2020-1588). K.L.M. is supported by grants from The Lundbeck Foundation (R303-2018-3551) and the Brain & Behavior Research Foundation (Young Investigator Award 2021). A.G. has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 945733), starting grant AI-Prevent. High-performance computer capacity for handling and statistical analysis of iPSYCH data on the GenomeDK HPC facility was provided by the Center for Genomics and Personalised Medicine and the Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark (grant to A.D.B.). B.J.V. is also supported by Independent Research Fund (2034-00241B).

Funding Information:
We would like to thank Jakob Grove, Doug Speed, Matthew Robinson, and Sven Erik Ojavee for valuable discussions. Parts of Fig. 1 were created with BioRender.com. E.M.P, B.J.V. and F.P. were supported by the Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH (R102-A9118, R155-2014-1724 and R248-2017-2003), and a Lundbeck Foundation Fellowship (R335-2019-2339). J.M., B.J.V. and F.P. were also supported the Danish National Research Foundation (Niels Bohr Professorship to Prof. John McGrath). A.J.S. is supported by a Lundbeckfonden Fellowship (R335-2019-2318), and O.P.-R. is supported by a Lundbeck Foundation Fellowship (R345-2020-1588). K.L.M. is supported by grants from The Lundbeck Foundation (R303-2018-3551) and the Brain & Behavior Research Foundation (Young Investigator Award 2021). A.G. has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 945733), starting grant AI-Prevent. High-performance computer capacity for handling and statistical analysis of iPSYCH data on the GenomeDK HPC facility was provided by the Center for Genomics and Personalised Medicine and the Centre for Integrative Sequencing, iSEQ, Aarhus University, Denmark (grant to A.D.B.). B.J.V. is also supported by Independent Research Fund (2034-00241B).

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© 2023, Springer Nature Limited.

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