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Citation
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Zhang Z, Liu L, Zhang H, Li C, Chen Y, Zhang J, Pan C, Cheng S, Yang X, Meng P, Yao Y, Jia Y, Wen Y, Zhang F. J. Psychiatr. Res. 2022; 156: 547-556. |
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Abstract
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BACKGROUND: Comparing with the general population, the pain in depression patients has more complex biological mechanism. We aim to explore the etiological mechanism of pain in depression patients from the perspective of genetics.
METHODS: Utilizing the UK Biobank samples with self-reported depression status or PHQ score ≥10, we conducted genome-wide association studies (GWAS) of seven pain traits (N = 1,133-58,349). Additionally, we used FUSION pipeline to perform proteome-wide association study (PWAS) and transcriptome-wide association study (TWAS) by integrating GWAS summary data with two different proteome reference weights (ROS/MAP and Banner) and Rnaseq gene expression reference weights, respectively.
RESULTS: GWAS identified 3 significant genes associated with different pain traits in depression patients, including TRIOBP (P(GWAS) = 4.48 × 10(-8)) for stomach or abdominal pain, SLC9A9(P(GWAS) = 2.77 × 10(-8)) for multisite chronic pain (MCP) and ADGRF1 (P(GWAS) = 1.51 × 10(-8)) for neck or shoulder pain. In addition, PWAS and TWAS analysis also identified multiple candidate genes associated with different pain traits in depression patients, such as TPRG1L (P(PWAS-Banner) = 3.38 × 10(-2)) and SIRPA (P(PWAS-Banner) = 3.65 × 10(-2)) for MCP, etc. Notably, when comparing the results of PWAS and TWAS analysis, we found overlapping candidate genes in these pain traits, such as GSTM3 (P(PWAS)-(Banner) = 3.38 × 10(-2), P(TWAS) = 6.92 × 10(-3)) in the stomach or abdominal pain phenotype, ATG7 (P(PWAS)-(Rosmap) = 3.15 × 10(-2), P(TWAS) = 2.98 × 10(-2)) in the MCP, etc.
CONCLUSIONS: We identified multiple novel candidate genes for pain traits in depression patients from different perspectives of genetics, which provided novel clues for understanding the genetic mechanisms underlying the pain in depression patients.
Language: en |