Li Zhang, Yiwen Pan, G. Huang, Zhen Liang, Linling Li, Zhiguo Zhang
{"title":"An Imaging Genetics Study Based on Brain-wide Genome-wide Association for Identifying Quantitative Trait Loci Related to Pain Sensitivity","authors":"Li Zhang, Yiwen Pan, G. Huang, Zhen Liang, Linling Li, Zhiguo Zhang","doi":"10.1109/CISP-BMEI53629.2021.9624411","DOIUrl":null,"url":null,"abstract":"Pain sensitivity has significant individual differences and it is associated with many factors, such as the differentiation of regional structural features of the brain and genetic variation among the population. Until now, a large part of the heritability of pain sensitivity remains unclear. This research focuses on exploring the genetic and neuroimage bases of pain sensitivity. A brain-wide genome-wide association study was carried out on 462 normal subjects, which were divided into high and low pain sensitivity groups according to the cold pain threshold from the cold pressor test. By using voxel-based morphometry (VBM), 116 brain structural features of grey matter (GM) densities were extracted based on high-resolution structural T1-weighted images from magnetic resonance imaging (MRI) scans. Afterward, a genome-wide association study (GWAS) was performed on each phenotype using quality-controlled genotype and analysis data including 755,875 single nucleotide polymorphisms (SNPs). Hierarchical clustering and heat maps were used to demonstrate the GWAS results. Significant associations between SNPs and phenotypes were reported at the threshold ($p < 10^{-6}$). SNPs in the NECTIN1 gene were identified to be strongly associated with various of brain regions, such as the amygdala, hippocampus, and regions at basal ganglia. These results suggest that the imaging genetics study is able to to reveal possible candidate genes and loci that may be associated with pain sensitivity.","PeriodicalId":131256,"journal":{"name":"2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP-BMEI53629.2021.9624411","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Pain sensitivity has significant individual differences and it is associated with many factors, such as the differentiation of regional structural features of the brain and genetic variation among the population. Until now, a large part of the heritability of pain sensitivity remains unclear. This research focuses on exploring the genetic and neuroimage bases of pain sensitivity. A brain-wide genome-wide association study was carried out on 462 normal subjects, which were divided into high and low pain sensitivity groups according to the cold pain threshold from the cold pressor test. By using voxel-based morphometry (VBM), 116 brain structural features of grey matter (GM) densities were extracted based on high-resolution structural T1-weighted images from magnetic resonance imaging (MRI) scans. Afterward, a genome-wide association study (GWAS) was performed on each phenotype using quality-controlled genotype and analysis data including 755,875 single nucleotide polymorphisms (SNPs). Hierarchical clustering and heat maps were used to demonstrate the GWAS results. Significant associations between SNPs and phenotypes were reported at the threshold ($p < 10^{-6}$). SNPs in the NECTIN1 gene were identified to be strongly associated with various of brain regions, such as the amygdala, hippocampus, and regions at basal ganglia. These results suggest that the imaging genetics study is able to to reveal possible candidate genes and loci that may be associated with pain sensitivity.