Foo Jia Nee, Tan Louis C, Liany Herty, Koh Tat Hung, Irwan Ishak D, Ng Yen Yek, Ahmad-Annuar Azlina, Au Wing-Lok, Aung Tin, Chan Anne Y Y, Chong Siow-Ann, Chung Sun Ju, Jung Yusun, Khor Chiea Chuen, Kim Juyeon, Lee Jimmy, Lim Shen-Yang, Mok Vincent, Prakash Kumar-M, Song Kyuyoung, Tai E-Shyong, Vithana Eranga N, Wong Tien-Yin, Tan Eng-King, Liu Jianjun
Human Genetics, Genome Institute of Singapore, A*STAR, Singapore.
Department of Neurology, National Neuroscience Institute, Singapore.
Hum Mol Genet. 2014 Jul 15;23(14):3891-7. doi: 10.1093/hmg/ddu086. Epub 2014 Feb 23.
To evaluate the contribution of non-synonymous-coding variants of known familial and genome-wide association studies (GWAS)-linked genes for Parkinson's disease (PD) to PD risk in the East Asian population, we sequenced all the coding exons of 39 PD-related disease genes and evaluated the accumulation of rare non-synonymous-coding variants in 375 early-onset PD cases and 399 controls. We also genotyped 782 non-synonymous-coding variants of these genes in 710 late-onset PD cases and 9046 population controls. Significant enrichment of LRRK2 variants was observed in both early- and late-onset PD (odds ratio = 1.58; 95% confidence interval = 1.29-1.93; P = 8.05 × 10(-6)). Moderate enrichment was also observed in FGF20, MCCC1, GBA and ITGA8. Half of the rare variants anticipated to cause loss of function of these genes were present in healthy controls. Overall, non-synonymous-coding variants of known familial and GWAS-linked genes appear to make a limited contribution to PD risk, suggesting that clinical sequencing of these genes will provide limited information for risk prediction and molecular diagnosis.
为评估已知的家族性和全基因组关联研究（GWAS）相关基因的非同义编码变异对东亚人群帕金森病（PD）风险的贡献，我们对39个PD相关疾病基因的所有编码外显子进行了测序，并评估了375例早发性PD病例和399例对照中罕见非同义编码变异的累积情况。我们还对710例晚发性PD病例和9046例人群对照中这些基因的782个非同义编码变异进行了基因分型。在早发性和晚发性PD中均观察到LRRK2变异的显著富集（优势比 = 1.58；95%置信区间 = 1.29 - 1.93；P = 8.05 × 10(-6)）。在FGF20、MCCC1、GBA和ITGA8中也观察到中度富集。预计会导致这些基因功能丧失的罕见变异中有一半存在于健康对照中。总体而言，已知的家族性和GWAS相关基因的非同义编码变异对PD风险的贡献似乎有限，这表明对这些基因进行临床测序将为风险预测和分子诊断提供有限的信息。
