ADuLT: An efficient and robust time-to-event GWAS
Abstract 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 i...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-09-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-023-41210-z |
| _version_ | 1797558553891831808 |
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| author | Emil M. Pedersen Esben Agerbo Oleguer Plana-Ripoll Jette Steinbach Morten D. Krebs David M. Hougaard Thomas Werge Merete Nordentoft Anders D. Børglum Katherine L. Musliner Andrea Ganna Andrew J. Schork Preben B. Mortensen John J. McGrath Florian Privé Bjarni J. Vilhjálmsson |
| author_facet | Emil M. Pedersen Esben Agerbo Oleguer Plana-Ripoll Jette Steinbach Morten D. Krebs David M. Hougaard Thomas Werge Merete Nordentoft Anders D. Børglum Katherine L. Musliner Andrea Ganna Andrew J. Schork Preben B. Mortensen John J. McGrath Florian Privé Bjarni J. Vilhjálmsson |
| author_sort | Emil M. Pedersen |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-03-10T17:32:07Z |
| format | Article |
| id | doaj.art-eb3d95affd73451ea109b0d277fe474f |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-03-10T17:32:07Z |
| publishDate | 2023-09-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-eb3d95affd73451ea109b0d277fe474f2023-11-20T09:59:18ZengNature PortfolioNature Communications2041-17232023-09-0114111210.1038/s41467-023-41210-zADuLT: An efficient and robust time-to-event GWASEmil M. Pedersen0Esben Agerbo1Oleguer Plana-Ripoll2Jette Steinbach3Morten D. Krebs4David M. Hougaard5Thomas Werge6Merete Nordentoft7Anders D. Børglum8Katherine L. Musliner9Andrea Ganna10Andrew J. Schork11Preben B. Mortensen12John J. McGrath13Florian Privé14Bjarni J. Vilhjálmsson15National Centre for Register-Based Research, Aarhus UniversityNational Centre for Register-Based Research, Aarhus UniversityNational Centre for Register-Based Research, Aarhus UniversityNational Centre for Register-Based Research, Aarhus UniversityInstitute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital - Mental Health Services CPHDepartment for Congenital Disorders, Statens Serum InstitutInstitute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital - Mental Health Services CPHLundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCHLundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCHNational Centre for Register-Based Research, Aarhus UniversityInstitute for Molecular Medicine Finland, University of HelsinkiInstitute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital - Mental Health Services CPHNational Centre for Register-Based Research, Aarhus UniversityNational Centre for Register-Based Research, Aarhus UniversityNational Centre for Register-Based Research, Aarhus UniversityNational Centre for Register-Based Research, Aarhus UniversityAbstract 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.https://doi.org/10.1038/s41467-023-41210-z |
| spellingShingle | Emil M. Pedersen Esben Agerbo Oleguer Plana-Ripoll Jette Steinbach Morten D. Krebs David M. Hougaard Thomas Werge Merete Nordentoft Anders D. Børglum Katherine L. Musliner Andrea Ganna Andrew J. Schork Preben B. Mortensen John J. McGrath Florian Privé Bjarni J. Vilhjálmsson ADuLT: An efficient and robust time-to-event GWAS Nature Communications |
| title | ADuLT: An efficient and robust time-to-event GWAS |
| title_full | ADuLT: An efficient and robust time-to-event GWAS |
| title_fullStr | ADuLT: An efficient and robust time-to-event GWAS |
| title_full_unstemmed | ADuLT: An efficient and robust time-to-event GWAS |
| title_short | ADuLT: An efficient and robust time-to-event GWAS |
| title_sort | adult an efficient and robust time to event gwas |
| url | https://doi.org/10.1038/s41467-023-41210-z |
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