Study May Reveal New Biomarkers Specific to SMA Types
New protein biomarkers that can distinguish between the different types of spinal muscular atrophy (SMA) were identified in a recent study.
According to researchers, the discovery supports further investigation to determine their utility as biomarkers for patient classification, monitoring treatment effectiveness, and identifying severity-specific treatments.
Findings were detailed in the study “The Proteome Signatures of Fibroblasts from Patients with Severe, Intermediate and Mild Spinal Muscular Atrophy Show Limited Overlap,” published in the journal Cells.
Nearly all cases of SMA (95%) are caused by mutations in the SMN1 gene, which leads to a deficiency in SMN, a protein found throughout the body, with the highest levels in the spinal cord. Motor neurons in the spinal cord — the nerve cells that control voluntary muscle movement — are particularly vulnerable to SMN deficiency.
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There are different types of SMA based on the age at which symptoms start, as well as on their severity. The number of copies of another gene that can be used to produce the SMN protein, called SMN2, also contribute to patient outcomes, with more SMN2 gene copies generally being associated with less-severe disease.
So far, research to uncover altered molecular pathways in SMA has focused on samples from severe cases. However, it is unclear whether molecular pathways implicated in severe SMA also are relevant in less-severe forms of the condition. As a result, whether biomarkers for patient classification would translate across the different SMA types remains unknown.
Because the SMN protein plays an essential role in protein production, researchers at Keele University in the U.K. analyzed protein production profiles across different SMA severities. Their goal was to assess whether a molecular response to SMN deficiency is similar across the different SMA types and to find differences between distinct disease types and severities.
The team collected and cultured fibroblasts — connective tissue cells — from five people with SMA type 1 (severe), five with SMA type 2 (intermediate), and four with SMA type 3 (mild). Cells also were collected from nine age-matched healthy individuals for comparison. In fibroblasts, the presence of different proteins, or proteomic profiles, then was investigated.
The analysis revealed that, compared with fibroblasts from SMA type 1 and type 3 patients, those from SMA type 2 had a wider variability in their proteomic profiles between individuals. This finding “could not be explained by SMN2 copy number, as all SMA [type 2] patients carried three SMN2 copies,” the researchers wrote.
SMA type 3 fibroblasts showed a statistically significant lower level of variation in the proteomic profiles between individual patients compared with SMA type 1 or type 2 fibroblasts. This was observed even though SMA type 3 patients had the most variability in SMN2 copy number (ranging from two to four copies), and the broadest range of ages (17–66 years).
SMN protein reduced
As expected, the level of total SMN protein was consistently reduced in patient fibroblasts across all SMA severities, compared with controls, but these levels did not differ between SMA types.
Differential protein expression analysis, which determined the relative abundance of different proteins in patient fibroblasts compared with controls, found 120 differentially expressed proteins in SMA type 1 fibroblasts, 49 in SMA type 2 fibroblasts, and 77 in the SMA type 3 cells.
However, none of these proteins consistently met the criteria for differential expression across all SMA types, indicating little overlap between proteomic profiles, the researchers noted.
Across all SMA types, no statistically significant commonalities were seen in proteomic profiles, but some profiles were enriched significantly across two of three datasets. In SMA type 1 and type 3 fibroblasts, enriched proteins were related to the mTOR signaling pathway, a central regulator of mammalian metabolism.
Also, in both SMA type 1 and type 3 cells, enrichment was found in the regulation of eIF4, a protein involved in protein production, and p70S6K signaling, a downstream target of mTOR signaling. eIF2 signaling, similar to eIF4, was enhanced in SMA type 1 and type 2 cells. Protein ubiquitination — a process in which proteins are marked for degradation — was enriched in SMA type 1 and type 2 fibroblasts and was slightly below the statistical cut-off for significance in SMA type 3 cells.
Four potential biomarkers
In an analysis of protein profiles that distinguish the three SMA types from each other, four proteins were selected from enrichment clusters as potential biomarkers for further study.
The protein IMP1 was significantly lower in SMA type 3 fibroblasts, but significantly higher in SMA type 1 cells, compared with controls. PYGB protein was increased significantly in SMA type 1 cells, but not changed in either SMA type 2 or type 3 cells. RAB3B was significantly increased in SMA type 2 fibroblasts compared with controls, with no changes detected in SMA type 1 or type 3 cells. STAT1 was significantly higher in SMA type 3 cells, but not in SMA type 1 or type 2 cells.
Finally, to establish whether the levels of these potential biomarkers could be altered in response to changing SMN protein levels, the team artificially overproduced the SMN protein in fibroblasts from each SMA type. Only RAB3B production in SMA type 2 fibroblasts demonstrated an SMN-dependent response.
“This work demonstrates that there is a limited core molecular response to reduced SMN levels across the different severities of SMA,” the researchers wrote, adding that this opens the field “for a more targeted approach to SMA treatment with respect to SMA type.”
“While four proteins from the datasets were verified,” they wrote, “there remains considerable potential for the remaining candidates found within this study to be explored as specific SMA type biosignatures and/or as biomarkers of both SMN-dependent and SMN-independent SMA treatment efficacy.”
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