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Related Concept Videos

Multiple Sclerosis l: Introduction01:19

Multiple Sclerosis l: Introduction

Multiple sclerosis is a chronic autoimmune disease of the central nervous system (CNS) that affects the brain, spinal cord, and optic nerves. It is an inflammatory demyelinating disorder and a leading cause of neurological disability in young adults.EpidemiologyMS commonly begins between 20 and 40 years of age and is twice as common in women. Its exact cause remains unclear, but genetic susceptibility contributes, with higher risk in first-degree relatives and identical twins. A greater...

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Related Experiment Video

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Comprehensive Autopsy Program for Individuals with Multiple Sclerosis
09:41

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Published on: July 19, 2019

Glutamate gene polymorphisms predict brain volumes in multiple sclerosis.

Eva M M Strijbis1, Becky Inkster, Maria Vounou

  • 1Department of Neurology, VU University Medical Centre, Amsterdam, The Netherlands.

Multiple Sclerosis (Houndmills, Basingstoke, England)
|August 2, 2012
PubMed
Summary

This study identifies genetic associations between GRIN2A single nucleotide polymorphisms (SNPs) and brain volume variations in multiple sclerosis (MS) patients. These findings highlight potential genetic drivers of MS phenotypes.

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Area of Science:

  • Neurogenetics
  • Neuroimaging
  • Statistical Genetics

Background:

  • Multiple sclerosis (MS) susceptibility is linked to several genetic markers, but its complex phenotypic expression remains challenging to elucidate.
  • Traditional mass-univariate linear modeling (MULM) in imaging genetics has limitations for complex trait analysis.

Purpose of the Study:

  • To apply a novel multivariate statistical model, sparse reduced-rank regression (sRRR), to explore associations between glutamate-related single nucleotide polymorphisms (SNPs) and MRI-derived phenotypes in MS.
  • To identify specific genetic variants influencing brain and lesion volumes in MS patients.

Main Methods:

  • Utilized sparse reduced-rank regression (sRRR) to analyze 3809 glutamate-related and control SNPs against seven MRI-derived phenotypes in 326 MS patients.
  • Employed Lasso regression and MULM for comparative analysis to validate the consistency of identified SNP associations.

Main Results:

  • Identified five SNPs within the NMDA-receptor-2A-subunit (GRIN2A) gene associated with normalized brain volume (NBV), normalized grey matter volume, and normalized white matter volume (NMWM).
  • Confirmed the association between GRIN2A SNPs and NBV/NMWM using MULM and Lasso regression.

Conclusions:

  • The novel multivariate sRRR model, validated by other methods, revealed significant associations between GRIN2A SNPs and phenotypic variations in NBV and NMWM in MS.
  • Further replication studies in independent datasets are required to confirm these initial findings.