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Polygenic risk score analysis for amyotrophic lateral sclerosis leveraging cognitive performance, educational attainment and schizophrenia

Restuadi, R., Garton, F.C., Benyamin, B., Lin, T., Williams, K.L., Vinkhuyzen, A., van Rheenen, W., Zhu, Z., Laing, N.G., Mather, K.A., Sachdev, P.S., Ngo, S.T., Steyn, F.J., Wallace, L., Henders, A.K., Visscher, P.M., Needham, M., Mathers, S., Nicholson, G., Rowe, D.B., Henderson, R.D., McCombe, P.A., Pamphlett, R., Blair, I.P., Wray, N.R. and McRae, A.F. (2021) Polygenic risk score analysis for amyotrophic lateral sclerosis leveraging cognitive performance, educational attainment and schizophrenia. European Journal of Human Genetics .

Link to Published Version: https://doi.org/10.1038/s41431-021-00885-y
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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-R2) of the case–control logistic regression. The combination of ALS, SCZ, CP, and EA, using the SBayesR predictor method gave the highest prediction (Nagelkerke-R2) of 0.027 (P value = 4.6 × 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.

Item Type: Journal Article
Murdoch Affiliation(s): Institute for Immunology and Infectious Diseases
Publisher: Nature Publishing Group
Copyright: © 2021 Springer Nature Limited
URI: http://researchrepository.murdoch.edu.au/id/eprint/60843
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