Summary
Variants of 16 typical dopaminergic transcription factors might not be major genetic risk factors for PD in Chinese patients. However, we highlight the complexity of PD and the need for extensive research elucidating its etiology.
Original Article
Genetic analysis of transcription factors in dopaminergic neuronal development in Parkinson's disease
Chinese Medical Journal
Zhao, Yuwen; Qin, Lixia; Pan, Hongxu; Song, Tingwei; Wang, Yige; Zhou, Xiaoxia; Xiang, Yaqin; Li, Jinchen; Liu, Zhenhua; Sun, Qiying; Guo, Jifeng; Yan, Xinxiang; Tang, Beisha; Xu, Qian
Abstract
Background:
Genetic variants of dopaminergic transcription factor-encoding genes are suggested to be Parkinson's disease (PD) risk factors; however, no comprehensive analyses of these genes in patients with PD have been undertaken. Therefore, we aimed to genetically analyzed 16 dopaminergic transcription factor genes in Chinese patients with PD.
Methods:
Whole-exome sequencing (WES) was performed using a Chinese cohort comprising 1917 unrelated patients with familial or sporadic early-onset PD and 1652 controls. Additionally, whole-genome sequencing (WGS) was performed using another Chinese cohort comprising 1962 unrelated patients with sporadic late-onset PD and 1279 controls.
Results:
We detected 308 rare and 208 rare protein-altering variants in the WES and WGS cohorts, respectively. Gene-based association analyses of rare variants suggested that MSX1 is enriched in sporadic late-onset PD. However, the significance did not pass the Bonferroni correction. Meanwhile, 72 and 1730 common variants were found in the WES and WGS cohorts, respectively. Unfortunately, single-variant logistic association analyses did not identify significant associations between common variants and PD.
Conclusions:
Variants of 16 typical dopaminergic transcription factors might not be major genetic risk factors for PD in Chinese patients. However, we highlight the complexity of PD and the need for extensive research elucidating its etiology.
Acknowledgments
The authors are grateful to all the individuals who participated in this study. We are also grateful for computing resources from the High Performance Computing Center of Central South University.
