A better understanding of the genetic biomarkers underpinning multiple sclerosis (MS) may lead to predictors of disease that could improve management of the condition, according to new research presented at Physiatry ’23, the Association of Academic Physiatrists (AAP) annual meeting.
Defined by an auto-immune attack of myelin and subsequent axonal damage in the nervous system, MS is a debilitating condition commonly faced by physiatrists. But what if physiatrists had a clearer idea of the genetic drivers associated with the disease? To investigate this, a group of researchers at Windsor University School of Medicine in St. Kitts, West Indies, assessed key biological pathways linked to MS.
"Multiple sclerosis is a debilitating neurologic disorder that we can better understand through the power of big data,” says Mohammed Mohammed, a medical student at Windsor University and the study’s presenting author. “We mined publicly available patient samples to identify potential genes that may serve as potential therapeutic targets and hope will motivate future research."
The study employed the Search Tag Analyze Resource (STARGEO) platform to tag samples derived from the National Center for Biotechnology Information (NCBI)’s Gene Expression Omnibus (GEO) and performed two separate analyses of peripheral blood from general MS and primary progressive MS (PPMS) patients against healthy controls. The general MS analysis included 30 patient samples and 26 healthy controls and the PPMS analysis featured 49 patient samples and 57 healthy controls. The researchers then analyzed the signature using Ingenuity Pathway Analysis (IPA).
Among the MS samples, the top canonical pathway was adenosine monophosphate (AMP)-activated protein kinase signaling, critical for the process of remyelination. The protein coding genes fms-related receptor tyrosine kinase 1 (FLT1) and fibronectin 1 (FN1) were identified as top upstream regulators with predicted inhibition. The top upregulated genes involved in several cellular processes included those for signal transduction (RAB30, RABGEF2 and GNAS), transcription regulation (GATA2) and cellular proliferation (AZIN1).
As for the PPMS samples, the top canonical pathways included EIF2 and p70S6K cellular signaling, while top upstream regulators included the post-transcription regulator LARP1 and cell growth regulator RICTOR, with predicted inhibition. Top upregulated genes included HLA-DRB5, ribosomal protein RPS27, genes encoding inflammatory molecules (S100P, RNASE2 and RNASE3), and the ribosomal proteins RPS27 and RPL39. Lastly, the research team identified synthetic retinoids CD 437 and ST1926 as possible drugs for PPMS.
MS — which is classified in four categories consisting of clinically isolated syndrome (CIS), relapse-remitting MS (RRMS), PPMS and secondary progressive MS (SPMS) — is treated by physiatrists in various stages and having a more thorough understanding of the disease’s biomarkers and genetic drivers may lead to more efficacious care, summarized the researchers. (PB/Newswise)
