Journal article
A Comparison of Ten Polygenic Score Methods for Psychiatric Disorders Applied Across Multiple Cohorts
G Ni, J Zeng, JA Revez, Y Wang, Z Zheng, T Ge, R Restuadi, J Kiewa, DR Nyholt, JRI Coleman, JW Smoller, S Ripke, BM Neale, A Corvin, JTR Walters, KH Farh, PA Holmans, P Lee, B Bulik-Sullivan, DA Collier Show all
Biological Psychiatry | Published : 2021
Abstract
Background: Polygenic scores (PGSs), which assess the genetic risk of individuals for a disease, are calculated as a weighted count of risk alleles identified in genome-wide association studies. PGS methods differ in which DNA variants are included and the weights assigned to them; some require an independent tuning sample to help inform these choices. PGSs are evaluated in independent target cohorts with known disease status. Variability between target cohorts is observed in applications to real data sets, which could reflect a number of factors, e.g., phenotype definition or technical factors. Methods: The Psychiatric Genomics Consortium Working Groups for schizophrenia and major depressiv..
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Funding Acknowledgements
This work was supported by the National Health and Medical Research Council (Grant Nos. 1173790, 1078901, and 108788 [to NRW] and Grant No. 1113400 [to NRW and PMV]) and the Australian Research Council (Grant No. FL180100072 [to PMV]). This work would not have been possible without the contributions of the investigators who comprise the PGC SCZ and PGC MDD Working Groups. For a full list of acknowledgments of all individual cohorts included in PGC SCZ and PGCMDD Working Groups, please see the original publications. The PGC has received major funding from the National Institute of Mental Health (Grant No. U01 MH109528). The Munster cohort was funded by the German Research Foundation (Grant No. FOR2107 DA1151/5-1 and DA1151/5-2 [to Udo Dannlowski] and Grant No. SFB-TRR58, Projects C09 and Z02 [to Udo Dannlowski]) and Interdisciplinary Center for Clinical Research of the Faculty of Medicine of Munster (Grant No. Dan3/012/17 [to Udo Dannlowski]). Some data used in this study were obtained from the database of Genotypes and Phenotypes (dbGaP). dbGaP Study Accession phs000021: Funding support for the Genome-Wide Association of Schizophrenia Study was provided by the National Institute of Mental Health (Grant Nos. R01 MH67257, R01 MH59588, R01 MH59571, R01 MH59565, R01 MH59587, R01 MH60870, R01 MH59566, R01 MH59586, R01 MH61675, R01 MH60879, R01 MH81800, U01 MH46276, U01 MH46289, U01 MH46318, U01 MH79469, and U01 MH79470), and the genotyping of samples was provided through the Genetic Association Information Network. Samples and associated phenotype data for the Genome-Wide Association of Schizophrenia Study were provided by the Molecular Genetics of Schizophrenia Collaboration (principal investigator P.V. Gejman, Evanston Northwestern Healthcare and Northwestern University, Evanston, IL). dbGaP accession phs000196: This work used in part data from the National Institute of Neurological Disorders and Stroke dbGaP database from the Center for Inherited Disease Research:NeuroGenetics Research Consortium Parkinson's Disease Study. dbGaP accession phs000187: High-Density SNP Association Analysis of Melanoma: Case-Control and Outcomes Investigation. Research support to collect data and develop an application to support this project was provided by the National Institutes of Health (Grant Nos. P50 CA093459, P50 CA097007, R01 ES011740, and R01 CA133996). Statistical analyses were carried out on the Genetic Cluster Computer (http://www.geneticcluster.org) hosted by SURFsara and financially supported by the Netherlands Scientific Organization (Grant No. 480-05-003) along with a supplement from the Dutch Brain Foundation and the VU University Amsterdam.