Assessment of the genetic contribution to brain magnetic resonance imaging lesion load and atrophy measures in multiple sclerosis patients. (8th June 2021) - Clarelli, Ferdinando; Rocca, Maria Assunta; Santoro, Silvia; De Meo, Ermelinda; Ferrè, Laura; Sorosina, Melissa; Martinelli Boneschi, Filippo; Esposito, Federica; Filippi, Massimo
Abstract: Background and purpose: Multiple sclerosis (MS) susceptibility is influenced by genetics; however, little is known about genetic determinants of disease expression. We aimed at assessing genetic factors influencing quantitative neuroimaging measures in two cohorts of progressive MS (PMS) and relapsing–remitting MS (RRMS) patients. Methods: Ninety‐nine PMS and 214 RRMS patients underwent a 3‐T brain magnetic resonance imaging (MRI) scan, with the measurement of five MRI metrics including T2 lesion volumes and measures of white matter, grey matter, deep grey matter, and hippocampal volumes. A candidate pathway strategy was adopted; gene set analysis was carried out to estimate cumulative contribution of genes to MRI phenotypes, adjusting for relevant confounders, followed by single nucleotide polymorphism (SNP) regression analysis. Results: Seventeen Kyoto Encyclopedia of Genes and Genomes pathways and 42 Gene Ontology (GO) terms were tested. We additionally included in the analysis genes with enriched expression in brain cells. Gene set analysis revealed a differential pattern of association across the two cohorts, with processes related to sodium homeostasis being associated with grey matter volume in PMS ( p  = 0.002), whereas inflammatory‐related GO terms such as adaptive immune response and regulation of inflammatory response appeared to be associated with T2 lesion volume in RRMS ( p  = 0.004 and p  = 0.008, respectively). As for SNPs, the rs7104613 T mapping to SPON1 gene was associated with reduced deep grey matter volume (β = −0.731, p  = 3.2*10 −7 ) in PMS, whereas we found evidence of association between white matter volume and rs740948 A mapping to SEMA3A gene (β = 22.04, p  = 5.5*10 −6 ) in RRMS. Conclusions: Our data suggest a different pattern of associations between MRI metrics and functional processes across MS disease courses, suggesting different phenomena implicated in MS. Abstract : This study evaluated the genetic contribution to brain MRI outcomes in patients of Italian origin affected by multiple sclerosis (MS), investigating T2 lesion volume measurements and white matter and whole and regional grey matter volume measurements. We stratified analyses in 214 relapsing‐remitting and 99 progressive MS patients, adopting a knowledge‐driven candidate pathways approach, selecting processes deemed as relevant to neurodegeneration and neuroinflammation. Analyses revealed a differential pattern of association across the two cohorts, with evidence of association for variants in SPON1 gene in the progressive cohort.