Identifying insomnia-related chemicals through integrative analysis of genome-wide association studies and chemical–genes interaction information. Issue 9 (14th March 2020) - Kafle, Om Prakash; Cheng, Shiqiang; Ma, Mei; Li, Ping; Cheng, Bolun; Zhang, Lu; Wen, Yan; Liang, Chujun; Qi, Xin; Zhang, Feng
Abstract: Study Objectives: Insomnia is a common sleep disorder and constitutes a major issue in modern society. We provide new clues for revealing the association between environmental chemicals and insomnia. Methods: Three genome-wide association studies (GWAS) summary datasets of insomnia ( n = 113, 006, n = 1, 331, 010, and n = 453, 379, respectively) were driven from the UK Biobank, 23andMe, and deCODE. The chemical–gene interaction dataset was downloaded from the Comparative Toxicogenomics Database. First, we conducted a meta-analysis of the three datasets of insomnia using the METAL software. Using the result of meta-analysis, transcriptome-wide association studies were performed to calculate the expression association testing statistics of insomnia. Then chemical-related gene set enrichment analysis (GSEA) was used to explore the association between chemicals and insomnia. Results: For GWAS meta-analysis dataset of insomnia, we identified 42 chemicals associated with insomnia in brain tissue ( p < 0.05) by GSEA. We detected five important chemicals such as pinosylvin ( p = 0.0128), bromobenzene ( p = 0.0134), clonidine ( p = 0.0372), gabapentin ( p = 0.0372), and melatonin ( p = 0.0404) which are directly associated with insomnia. Conclusion: Our study results provide new clues for revealing the roles of environmental chemicals in the development of insomnia.