Genetic Insights into Brain Morphology: a Genome-Wide Association Study of Cortical Thickness and T1-Weighted MRI Gray Matter-White Matter Intensity Contrast

In T<sub>1</sub>-weighted magnetic resonance imaging (MRI), cortical thickness (CT) and gray-white matter contrast (GWC) capture brain morphological traits and vary with age-related disease. To gain insight into genetic factors underlying brain structure and dynamics observed during neurodegeneration, this genome-wide association study (GWAS) quantifies the relationship between single nucleotide polymorphisms (SNPs) and both CT and GWC in UK Biobank participants (N = 43,002). To our knowledge, this is the first GWAS to investigate the genetic determinants of cortical T<sub>1</sub>-MRI GWC in humans. We found 251 SNPs associated with CT or GWC for at least 1% of cortical locations, including 42 for both CT and GWC; 127 for only CT; and 82 for only GWC. Identified SNPs include rs1080066 (THSB1, featuring the strongest association with both CT and GWC), rs13107325 (SLC39A8, linked to CT at the largest number of cortical locations), and rs864736 (KCNK2, associated with GWC at the largest number of cortical locations). Dimensionality reduction reveals three major gene ontologies constraining CT (neural signaling, ion transport, cell migration) and four constraining GWC (neural cell development, cellular homeostasis, tissue repair, ion transport). Our findings provide insight into genetic determinants of GWC and CT, highlighting pathways associated with brain anatomy and dynamics of neurodegeneration. These insights can assist the development of gene therapies and treatments targeting brain diseases.

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Publication Details

Journal
Neuroinformatics
Published
2025-04-01
DOI
https://doi.org/10.1007/s12021-025-09722-9
Citations
1
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
1.82

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article

Genetic Insights into Brain Morphology: a Genome-Wide Association Study of Cortical Thickness and T1-Weighted MRI Gray Matter-White Matter Intensity Contrast

Nahian F. Chowdhury, Kenneth H. Buetow, Andrei Irimia, Paul M. Thompson et al.
1 citations
Neuroinformatics
Genetic Associations and Epidemiology
1.82
article

Genetic Insights into Brain Morphology: a Genome-Wide Association Study of Cortical Thickness and T1-Weighted MRI Gray Matter-White Matter Intensity Contrast

Nahian F. Chowdhury, Kenneth H. Buetow, Andrei Irimia, Paul M. Thompson, Nicholas Kim
article en
1 citations

Abstract

In T<sub>1</sub>-weighted magnetic resonance imaging (MRI), cortical thickness (CT) and gray-white matter contrast (GWC) capture brain morphological traits and vary with age-related disease. To gain insight into genetic factors underlying brain structure and dynamics observed during neurodegeneration, this genome-wide association study (GWAS) quantifies the relationship between single nucleotide polymorphisms (SNPs) and both CT and GWC in UK Biobank participants (N = 43,002). To our knowledge, this is the first GWAS to investigate the genetic determinants of cortical T<sub>1</sub>-MRI GWC in humans. We found 251 SNPs associated with CT or GWC for at least 1% of cortical locations, including 42 for both CT and GWC; 127 for only CT; and 82 for only GWC. Identified SNPs include rs1080066 (THSB1, featuring the strongest association with both CT and GWC), rs13107325 (SLC39A8, linked to CT at the largest number of cortical locations), and rs864736 (KCNK2, associated with GWC at the largest number of cortical locations). Dimensionality reduction reveals three major gene ontologies constraining CT (neural signaling, ion transport, cell migration) and four constraining GWC (neural cell development, cellular homeostasis, tissue repair, ion transport). Our findings provide insight into genetic determinants of GWC and CT, highlighting pathways associated with brain anatomy and dynamics of neurodegeneration. These insights can assist the development of gene therapies and treatments targeting brain diseases.

NeuroinformaticsVol. 23(2)
University of Southern California (US), King's College London (GB), Arizona State University (US)
University of Southern California, King's College London, National Institutes of Health, Center for Undergraduate Research and Scholarship, Bowling Green State University
Openalex Percentile: Top 17%
Genetic Associations and Epidemiology
1.82
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