Lo Min-Tzu, Wang Yunpeng, Kauppi Karolina, Sanyal Nilotpal, Fan Chun-Chieh, Smeland Olav B, Schork Andrew, Holland Dominic, Hinds David A, Tung Joyce Y, Andreassen Ole A, Dale Anders M, Chen Chi-Hua
Department of Radiology, Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA 92037, USA.
NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo 0407, Norway.
Hum Mol Genet. 2017 Nov 15;26(22):4530-4539. doi: 10.1093/hmg/ddx340.
Neuroticism reflects emotional instability, and is related to various mental and physical health issues. However, the majority of genetic variants associated with neuroticism remain unclear. Inconsistent genetic variants identified by different genome-wide association studies (GWAS) may be attributable to low statistical power. We proposed a novel framework to improve the power for gene discovery by incorporating prior information of single nucleotide polymorphisms (SNPs) and combining two relevant existing tools, relative enrichment score (RES) and conditional false discovery rate (FDR). Here, SNP's conditional FDR was estimated given its RES based on SNP prior information including linkage disequilibrium (LD)-weighted genic annotation scores, total LD scores and heterozygosity. A known significant locus in chromosome 8p was excluded before estimating FDR due to long-range LD structure. Only one significant LD-independent SNP was detected by analyses of unconditional FDR and traditional GWAS in the discovery sample (N = 59 225), and notably four additional SNPs by conditional FDR. Three of the five SNPs, all identified by conditional FDR, were replicated (P < 0.05) in an independent sample (N = 170 911). These three SNPs are located in intronic regions of CADM2, LINGO2 and EP300 which have been reported to be associated with autism, Parkinson's disease and schizophrenia, respectively. Our approach using a combination of RES and conditional FDR improved power of traditional GWAS for gene discovery providing a useful framework for the analysis of GWAS summary statistics by utilizing SNP prior information, and helping to elucidate the links between neuroticism and complex diseases from a genetic perspective.
神经质反映了情绪的不稳定性，并且与各种身心健康问题相关。然而，与神经质相关的大多数基因变异仍不清楚。不同的全基因组关联研究（GWAS）所识别出的基因变异不一致，这可能归因于统计效能较低。我们提出了一个新的框架，通过纳入单核苷酸多态性（SNP）的先验信息并结合两个相关的现有工具，即相对富集分数（RES）和条件错误发现率（FDR），来提高基因发现的效能。在此，基于包括连锁不平衡（LD）加权基因注释分数、总LD分数和杂合性在内的SNP先验信息，在给定RES的情况下估计SNP的条件FDR。由于存在长程LD结构，在估计FDR之前排除了8号染色体短臂上一个已知的显著位点。在发现样本（N = 59225）中，通过无条件FDR分析和传统GWAS仅检测到一个显著的LD独立SNP，而通过条件FDR则额外检测到四个SNP。在一个独立样本（N = 170911）中，通过条件FDR识别出的五个SNP中有三个得到了重复验证（P < 0.05）。这三个SNP分别位于CADM2、LINGO2和EP300的内含子区域，据报道它们分别与自闭症、帕金森病和精神分裂症相关。我们结合RES和条件FDR的方法提高了传统GWAS进行基因发现的效能，通过利用SNP先验信息为GWAS汇总统计分析提供了一个有用的框架，并有助于从遗传学角度阐明神经质与复杂疾病之间的联系。
