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Obesity-related genes are linked to heightened risk and progression of multiple sclerosis through metabolic and neuroinflammatory pathways.
Genetic markers linked to obesity show potential roles in multiple sclerosis (MS) development and disease course, according to findings from a systematic literature review. The study led by Ali Jafari et al. analyzed 6 genes—fat mass and obesity-associated (FTO), FAS apoptosis inhibitory molecule 2 (FAIM2), Niemann–Pick disease type C1-like 1 (NPC1), glucosamine-6-phosphate deaminase 2 (GNPDA2), melanocortin-4 receptor (MC4R), and brain-derived neurotrophic factor (BDNF)—that are commonly connected with obesity, suggesting that metabolic pathways may intersect with neuroinflammatory processes in MS.
Investigators executed a comprehensive search across 5 major databases—Embase, Scopus, Cochrane, Web of Science, and PubMed, using targeted keywords for each gene and MS. Out of 2,108 studies initially identified, 27 fulfilled the inclusion criteria and were encompassed in the final review. The review revealed that FTO may impact MS susceptibility via metabolic and inflammatory mechanisms. FAIM2 and NPC1 may also play roles in MS pathogenesis, although their specific functions remain ambiguous. Evidence on GNPDA2 suggests a potential link, but further investigation is required.
In contrast, MC4R illustrated clear neuroprotective and anti-inflammatory effects, making it a promising gene of interest for future MS research. Meanwhile, BDNF, known for its role in neuronal survival and regeneration, may modulate MS risk through its broader neurological impact. These findings point to a previously underexplored association between obesity-related genetic factors and MS. By uncovering shared biological pathways, this review paves the way for future studies targeting gene-environment interactions in MS and supports the requisition for more personalized approaches to treatment and prevention.
Brain and Behavior
Uncovering the Causal Link Between Obesity-Associated Genes and Multiple Sclerosis: A Systematic Literature Review
Ali Jafari et al.
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