TY - GEN
T1 - An Imaging Genetics Study Based on Brain-wide Genome-wide Association for Identifying Quantitative Trait Loci Related to Pain Sensitivity
AU - Zhang, Li
AU - Pan, Yiwen
AU - Huang, Gan
AU - Liang, Zhen
AU - Li, Linling
AU - Zhang, Zhiguo
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85123472448
U2 - 10.1109/CISP-BMEI53629.2021.9624411
DO - 10.1109/CISP-BMEI53629.2021.9624411
M3 - 会议稿件
AN - SCOPUS:85123472448
T3 - Proceedings - 2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2021
BT - Proceedings - 2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2021
A2 - Li, Qingli
A2 - Wang, Lipo
A2 - Wang, Yan
A2 - Li, Wenwu
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2021
Y2 - 23 October 2021 through 25 October 2021
ER -