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A brain-wide genome-wide association study of candidate quantitative trait loci associated with structural and functional phenotypes of pain sensitivity

  • Li Zhang
  • , Yiwen Pan
  • , Gan Huang
  • , Zhen Liang
  • , Linling Li
  • , Min Zhang
  • , Zhiguo Zhang*
  • *Corresponding author for this work
  • Shenzhen University
  • Harbin Institute of Technology Shenzhen
  • Peng Cheng Laboratory
  • Marshall Laboratory of Biomedical Engineering

Research output: Contribution to journalArticlepeer-review

Abstract

Individual pain sensitivity is modulated by the brain’s structural and functional features, but its heritability remains unclear. This paper conducted a brain-wide genome-wide association study (GWAS) to explore the genetic bases of neuroimage phenotypes of pain sensitivity. In total, 432 normal participants were divided into high and low pain sensitivity groups according to the laser quantitative test threshold. Then, the brain’s gray matter density (GMD) features correlated with pain sensitivity were identified. Next, GWAS was performed on each GMD phenotype using quality-controlled genotypes. Based on the heatmap and hierarchical clustering results, the right insula was identified for further refined analysis in terms of subregions GMD and resting-state functional connectivity (rs-FC) phenotypes. The results indicate that the right insula GMD in the high sensitivity group is significantly lower than that in the low sensitivity group. Also, the TT/TC group at locus rs187974 has lower right insula GMD than the CC group. Further, loci at gene CYP2D6 may lead to a variation of rs-FC between the right insula and left putamen. In conclusion, our study suggests that the right insula and multiple candidate loci may be importantly involved in pain sensitivity modulation, which may guide the future development of precision pain therapeutics.

Original languageEnglish
Pages (from-to)7297-7309
Number of pages13
JournalCerebral Cortex
Volume33
Issue number11
DOIs
StatePublished - 1 Jun 2023
Externally publishedYes

Keywords

  • GWAS
  • functional connectivity
  • gray matter density
  • imaging genetics
  • pain sensitivity

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