Association analysis and polygenic risk score evaluation of 38 GWAS-identified Loci in a Chinese population with Parkinson's disease. (25th September 2021)

• Record Type: Journal Article
• Authors: Zheng, Ran; Qiao, Song; Chen, Ying; Jin, Chongyao; Fang, Yi; Lin, Zhihao; Xue, Naijia; Yan, Yiqun; Gu, Luyan; Gao, Ting; Tian, Jun; Yan, Yaping; Yin, Xinzhen; Pu, Jiali; Zhang, Baorong
• Is Part Of: Neuroscience letters. Volume 762(2021)
• Publication Date: 2021-09-25
• Subjects: Association analysis -- Polygenic risk score -- FBRSL1 -- KCNS3 -- DYRK1A; Neurology -- Periodicals; Neurology -- Periodicals; Research -- Periodicals; Neurologie -- Périodiques; Neuroanatomie -- Périodiques; Neuropharmacologie -- Périodiques; Neurophysiologie -- Périodiques; Neurology; Periodicals; Electronic journals; 617.48
• DOI: 10.1016/j.neulet.2021.136150
• Languages: English
• ISSNs: 0304-3940

Abstract

Graphical abstract: Highlights: We first replicated the effects of 38 novel GWAS-identified PD-related Loci in a Chinese population. The rs2248244 of DYRK1A was a risk factor for sporadic PD in our study. The rs11610045 of FBRSL1 and rs76116224 of KCNS3 have protective effects on sporadic PD. We built GWAS-derived PRS models which had predictive value for PD risk in the Chinese population. Abstract: Objective: Recently, a meta-analysis of genome-wide association studies (GWASs) has identified 38 novel independent loci associated with risk of Parkinson's disease (PD) in European populations. We sought to investigate whether these genetic susceptibility variants could be replicated in the Chinese Han population. Methods: We genotyped 38 independent loci in 495 Chinese sporadic PD patients and 470 unrelated controls and performed allelic and genotypic association test using chi-square tests or Armitage test for trend. Polygenic risk score (PRS) models were built to evaluate the cumulative effects of the selected SNPs. Results: We found that the rs11610045 of FBRSL1 (p = 0.02, OR = 0.63, allele model), rs76116224 of KCNS3 (p < 0.01, OR = 0.09, allele model), and the rs2248244 of DYRK1A (p = 0.02, OR = 1.35, allele model) were significantly associated with PD. The PRS model of cumulative effects of the SNPs associated with PD in our study had the area under the curve (AUC) of 0.61. Conclusions: Our study revealed that rs11610045 of FBRSL1, rs76116224 of KCNS3 and rs2248244 of DYRK1A showed an impact on the risk of PD, and the GWAS-derived PRS models we built had predictive value for PD risk in the Chinese population. Further studies are needed to explore the pathogenesis of these potentially risk-associated variants.