1. Polygenic risk score analysis for amyotrophic lateral sclerosis leveraging cognitive performance, educational attainment and schizophrenia
- Author
-
Anjali K. Henders, Pamela A. McCombe, Nigel G. Laing, Perminder S. Sachdev, Allan F. McRae, Garth A. Nicholson, Fleur C. Garton, Beben Benyamin, Wouter van Rheenen, Anna A. E. Vinkhuyzen, Frederik J. Steyn, Restuadi Restuadi, Leanne Wallace, Dominic B. Rowe, Susan Mathers, Robert D. Henderson, Zhihong Zhu, Shyuan T. Ngo, Kelly L. Williams, Tian Lin, Karen A. Mather, Ian P. Blair, Merrilee Needham, Naomi R. Wray, Roger Pamphlett, Peter M. Visscher, Restuadi, Restuadi, Garton, Fleur C, Benyamin, Beben, Lin, Tian, and McRae, Allan F
- Subjects
Oncology ,medicine.medical_specialty ,Genome-wide association study ,Disease ,Logistic regression ,Polymorphism, Single Nucleotide ,Genetic correlation ,Article ,03 medical and health sciences ,Cognition ,Risk Factors ,Internal medicine ,Genetics ,medicine ,Humans ,Genetic Predisposition to Disease ,Effects of sleep deprivation on cognitive performance ,Amyotrophic lateral sclerosis ,Genetics (clinical) ,0303 health sciences ,business.industry ,Amyotrophic Lateral Sclerosis ,030305 genetics & heredity ,Australia ,Neurodegenerative Diseases ,medicine.disease ,Schizophrenia ,Cohort ,business ,Genome-Wide Association Study - Abstract
Amyotrophic Lateral Sclerosis (ALS) is recognised to be a complex neurodegenerative disease involving both genetic and non-genetic risk factors. The underlying causes and risk factors for the majority of cases remain unknown; however, ever-larger genetic data studies and methodologies promise an enhanced understanding. Recent analyses using published summary statistics from the largest ALS genome-wide association study (GWAS) (20,806 ALS cases and 59,804 healthy controls) identified that schizophrenia (SCZ), cognitive performance (CP) and educational attainment (EA) related traits were genetically correlated with ALS. To provide additional evidence for these correlations, we built single and multi-trait genetic predictors using GWAS summary statistics for ALS and these traits, (SCZ, CP, EA) in an independent Australian cohort (846 ALS cases and 665 healthy controls). We compared methods for generating the risk predictors and found that the combination of traits improved the prediction (Nagelkerke-R-2) of the case-control logistic regression. The combination of ALS, SCZ, CP, and EA, using the SBayesR predictor method gave the highest prediction (Nagelkerke-R-2) of 0.027 (P value = 4.6 x 10(-8)), with the odds-ratio for estimated disease risk between the highest and lowest deciles of individuals being 3.15 (95% CI 1.96-5.05). These results support the genetic correlation between ALS, SCZ, CP and EA providing a better understanding of the complexity of ALS. Refereed/Peer-reviewed
- Published
- 2021
- Full Text
- View/download PDF