Adding blood chemistry to standard tests could improve long-term outlook tools
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The hands of a laboratory technician are seen while performing a general blood test. The biomaterial is in special tubes. (Photo by iStock)
Among people with clinically isolated syndrome (CIS) — an initial episode of symptoms suggestive of multiple sclerosis (MS) — lower levels of certain fatty molecules in the blood are associated with higher rates of future disease relapses, a new study found.
Adding these metabolic features to established demographic and clinical factors may modestly improve predictions of disease activity over the long term, researchers said in the study, “Serum metabolic profile at clinical onset as predictor of multiple sclerosis activity and progression after 5 years,” which was published in the Multiple Sclerosis Journal.
In most people with MS, the disease is marked by relapses where symptoms suddenly worsen, followed by periods of remission where symptoms ease. CIS refers to an initial attack of MS-like symptoms, and many people with this early manifestation will eventually be diagnosed with MS.
But doctors do not currently have very reliable ways of predicting future disease activity in individuals with CIS or early MS. In this study, researchers set out to identify markers of disease activity and progression using metabolomics — that is, detailed analyses of hundreds of small molecules produced during metabolism.
The study included data from 451 people with CIS who participated in BENEFIT (NCT00185211), a clinical trial run in the 2000s that tested the now-approved therapy Betaseron (interferon beta-1b). That trial was funded by Bayer, which markets Betaseron.
The researchers analyzed stored blood samples from the start of the study, then used detailed statistical tests to look for associations between blood markers at disease onset and clinical outcomes over the next five years of follow-up.
“To our knowledge, this is the first untargeted blood metabolomics study at the onset of clinical MS that prospectively evaluates disease activity and progression over 5 years in a sample of this size,” the researchers wrote.
Among the hundreds of small molecules measured, most showed no significant associations with clinical outcomes. However, there were 42 molecules whose levels showed inverse associations with total relapse numbers; in other words, patients with lower levels of these molecules tended to have more relapses during follow-up.
The researchers highlighted that many of these molecules were lipids (fat molecules), such as linolenic acid, oleic acid, and certain unsaturated triglycerides.
The analyses also identified eight molecules where higher levels were linked with higher relapse counts over five years. Again some of these were fatty molecules, including saturated triglycerides.
“Most associations did not remain statistically significant, except for several lipids and other metabolites related to the cumulative number of relapses,” the researchers wrote.
In statistical models aimed at predicting long-term outcomes, incorporating these metabolite signatures “modestly improved the prediction of MS severity beyond established predictors” such as smoking and vitamin D levels, the researchers said.
These common pathways may represent biologically relevant mechanisms … [and] could be interesting to confirm and pursue in future studies investigating mechanisms relevant to MS severity.
Based on levels of the various small molecules, the researchers also conducted analyses designed to evaluate the relative activity of various biological pathways. They found that greater activity in certain pathways — namely those used to make the molecules nicotinamide, histidine, and arginine — was consistently associated with more relapses, as well as MRI measures and disability scores.
“These common pathways may represent biologically relevant mechanisms,” the researchers wrote, adding that these pathways “could be interesting to confirm and pursue in future studies investigating mechanisms relevant to MS severity.”
A notable limitation of the analysis is that all the patients were white, so it’s unclear whether the results are applicable in other ethnic backgrounds.
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