Poster No:
2503
Submission Type:
Abstract Submission
Authors:
Miguel Renteria1, Luis M. Garcia Marin2, Natalia Ogonowski2, Santiago Diaz-Torres2, Freddy Chafota2, Nicholas Martin2
Institutions:
1Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, 2QIMR Berghofer Medical Research Institute, Brisbane, QLD
First Author:
Miguel Renteria
Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute
Brisbane, QLD
Co-Author(s):
Freddy Chafota
QIMR Berghofer Medical Research Institute
Brisbane, QLD
Introduction:
Chronic pain is a complex condition with a substantial impact on quality of life, often associated with alterations in brain structure. However, the genetic underpinnings linking brain morphometry and chronic pain remain poorly understood. This study aims to elucidate the genetic correlations between brain morphometry and multisite chronic pain and to infer potential causal relationships.
Methods:
We leveraged summary statistics from the largest genome-wide association studies (GWAS) of multisite chronic pain and neuroimaging phenotypes, focusing on cortical thickness and surface area, subcortical volumes, and intracranial volume. Pairwise genetic correlations between these neuroimaging phenotypes and chronic pain were estimated using LD-Score Regression (LDSC). For brain phenotypes showing significant correlations, we applied the GWAS-Pairwise method to estimate local genetic correlations. Further, we employed the novel LHC-Mendelian Randomisation (LHC-MR) method, designed to perform bi-directional causal estimation while addressing limitations of traditional Mendelian Randomization, such as sample overlap and sensitivity to heritable confounders.
Results:
Our analyses revealed significant genetic correlations between several brain regions of interest and chronic pain. The GWAS-Pairwise method provided refined local genetic correlation estimates. Several genes, including RPP25, NFKB2, SCAMP5, PPCDC, ASXL3, and SLC44A2, were implicated as influencing chronic pain risk and at least one brain morphometric measure. The lHC-MR analysis indicated potential causal relationships between brain morphometry and chronic pain, with evidence of heritable factors influencing these associations.
Conclusions:
This study provides novel insights into the genetic relationship between brain morphometry and chronic pain and highlights the potential for genetic factors to contribute to both brain structural changes and the susceptibility to chronic pain, offering avenues for future research into targeted interventions and personalised pain management strategies.
Genetics:
Genetic Modeling and Analysis Methods 2
Genetics Other
Perception, Attention and Motor Behavior:
Perception: Pain and Visceral 1
Keywords:
ADULTS
Basal Ganglia
Cortex
Pain
1|2Indicates the priority used for review
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