Analyses of protein levels in blood can help ID MS patient subgroups
Such groupings may help improve individualized treatment: Study
Analyses of protein levels in the blood can be used to identify groups of multiple sclerosis (MS) patients with distinct clinical features, new research shows.
Given the variability of symptoms among people with MS, such groupings could help to improve individualized care for patients, according to Octave, a California-based company that conducted the research into the blood protein levels with a team from the Rocky Mountain MS Clinic, in Utah.
Octave is working to develop tools to personalize treatment for people with MS and other diseases.
The company’s platform “generates, analyzes and combines data to create a new paradigm of MS care, leading to improved patient outcomes,” Octave said in a press release announcing the research results.
Those findings were presented at the Consortium of Multiple Sclerosis Centers (CMSC) Annual Meeting 2023 by John Foley, MD, founder of the Rocky Mountain clinic. His talk was titled, “Robustness of Emergent MS Phenotypes Derived from Multiprotein Serum Biomarker Data.”
1 analysis focused on protein levels in blood samples
Multiple sclerosis is characterized by inflammation in the brain and spinal cord that causes damage to nerve tissue, ultimately leading to disease symptoms. Researchers note, however, that there’s a huge amount of variability from person to person in how MS manifests and progresses. The reasons for this variability are poorly understood, making it hard to provide care tailored to the individual.
Identifying biological markers that can be used to objectively distinguish between different groups of patients with varying clinical manifestations could help in bettering individualized care. But it’s been difficult to identify markers that can reliably be used in this way.
Now, researchers at Octave and Rocky Mountain attempted to define subgroups of MS patients based on proteomic analyses. Proteomics involves global tests that measure levels of many different proteins in a blood, cells, or tissues, among other samples.
The team first performed proteomic analyses using blood samples from 220 people with MS. Computer-based analyses of these samples identified eight distinct clusters with different proteomic signatures.
The different clusters also showed notable differences in measures of MS disease activity, as well as age, sex, and the use of MS treatments. They also differed by MS disease activity (MSDA) index, a proteomics-based measure developed by Octave.
The analyses were then repeated using separate samples from 527 patients — and the results were consistent with the original analysis. The fact that consistent results were obtained in samples from disparate groups of patients “is reassuring evidence for the clinical utility of this methodology,” the researchers wrote.
According to Foley, “these clusters will serve as the kernel of patient profiles for further exploration in the clinical utility of variables of interest, including disease activity score distributions in clinically stable versus active patients, the impact of duration of disease-modifying therapy (DMT), and for comparisons of DMTs with diverse mechanisms of action.”
“With tools like the Octave MSDA Test, we are beginning to tease out an unprecedented amount of detail of not just a single patient’s disease, but an entire clinic’s population,” Foley added.
Inconsistent results found in neurologist reports in another
Other Octave-led research presented at the CMSC meeting highlighted variability that can occur during routine care for people with MS.
Clinicians will generally rely on MRI scans of the brain and spinal cord to help track MS disease activity and inform treatment decisions. However, interpreting MRI data can be somewhat subjective, which may influence the type of care that clinicians recommend for their patients.
In one poster, “Variability in Clinical Impressions and Decisions by Neurologists Interpreting MS MRI Brain Reports,” researchers collected MRI scan data for 90 people with MS, with a wide range of disease severities. The raw images were reviewed by expert radiologists to generate standardized reports. Then, these reports were sent for review by five expert neurologists. Unbeknownst to the neurologists, some of the reports were duplicated.
Based on the reports, the neurologists had to decide whether or not to recommend a change in treatment. The five neurologists all were in complete agreement for 33 patients — but for the remaining 57 patients, these specialists disagreed with each other on the best approach.
Furthermore, all five neurologists at one point gave contradictory recommendations for duplicated reports — for example, recommending a change on one report but not on its identical duplicate.
“There is evidence of differences within [and] between MS neurologists when reporting clinical decisions based on standard-of-care structured MRI reports,” the researchers concluded, noting that these discrepancies “may significantly impact patient outcomes and cost of care.”
It’s generally recommended that MS patients undergo regular MRI scans using the same setup — specifically, the same machine and settings — as variations in the MRI protocol or equipment can make it harder to interpret data.
Findings urge MRIs be done using same setting, equipment
In another poster, “Variability of Longitudinal Standard of Care Brain MRI Scans Ordered by a Single MS Center,” researchers assessed whether MRI settings and equipment were consistent among 173 people with MS at a single imaging facility. All of the patients underwent at least two separate MRI scans between 2018 and 2021.
The results showed that just 42% of these patients underwent repeated scans using the same equipment.
“Less than half of the patients in the study received longitudinal, comparable MRIs utilizing the same combination of major MRI parameters,” the researchers wrote.
“The results show that even when a patient is scanned at the same facility over time, variations in the scanner’s field strength, manufacturer, and model may vary, making the radiologists’ comparisons to prior scans difficult,” they added.
Such differences can make it harder for neurologists to track a patient’s progression.
“Image acquisition and reporting variability adds to the difficulties clinicians and patients face when interpreting MRI reports to make informed treatment decisions,” the team concluded.
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