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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
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Brain Morphology of Cannabis Users With or Without Psychosis: A Pilot MRI Study
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S-GMAS: Genome-Wide Mediation Analysis With Brain Subcortical Shape Mediators.

Shengxian Ding1, Rongjie Liu2, Anuj Srivastava3

  • 1Department of Biostatistics, Yale University, New Haven, Connecticut, USA.

Human Brain Mapping
|July 31, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new framework for genome-wide mediation analysis using brain shape data. It helps uncover how genetic variations influence neurological diseases through brain structure changes.

Keywords:
Alzheimer's diseasecorpus callosumelastic shape representationgenome‐wide mediation analysis

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Area of Science:

  • Neuroscience
  • Genetics
  • Medical Imaging

Background:

  • Mediation analysis is crucial for understanding neurological pathways from genetic factors to clinical outcomes using brain imaging.
  • Challenges exist in genome-wide mediation analysis involving numerous genetic variants (SNPs) and complex brain shape data.

Purpose of the Study:

  • To develop a novel genome-wide mediation analysis framework tailored for brain subcortical shape mediators.
  • To address challenges of high-dimensional genetic data, nonlinear shape spaces, and statistical inference in mediation analysis.

Main Methods:

  • A fast genome-wide association analysis identifies significant genetic variants.
  • Square-root velocity functions represent brain subcortical shapes in a linear Hilbert subspace.
  • A shape mediation analysis framework (shape-on-scalar and scalar-on-shape models) with bootstrap resampling is employed.

Main Results:

  • The proposed framework effectively handles large-scale genetic data and complex shape mediators.
  • It enables robust statistical inference for direct and indirect effects in mediation pathways.
  • The analysis identified significant global and spatial mediation effects.

Conclusions:

  • The developed framework provides a powerful tool for genome-wide mediation analysis in neuroscience.
  • It facilitates the investigation of genetic influences on clinical outcomes via brain structure.
  • Application to Alzheimer's Disease Neuroimaging Initiative data demonstrates its utility.