Proteomics Reveals Age as Major Modifier of Inflammatory CSF Signatures in Multiple Sclerosis

Abstract

Background and objectives: Multiple sclerosis (MS) can start as relapsing or progressive. While their clinical features and treatment responses are distinct, it has remained uncertain whether their pathomechanisms differ. A notable age-related effect on MS phenotype and response to immunotherapies is well acknowledged, but the underlying pathophysiologic reasons are yet to be fully elucidated. We aimed to identify disease-specific and age-related proteomic signatures using a comprehensive targeted proteomic analysis.

Methods: In our retrospective cohort study, we analyzed the CSF and serum proteome of age-matched individuals with treatment-naïve relapsing-remitting and primary progressive MS, neurologic controls (NC), and individuals with neuroborreliosis using targeted proteomics and validated findings in an independent cohort. Proteomic results were integrated with clinical and laboratory covariates.

Results: Among 2,500 proteins, 47 CSF proteins were distinct between individuals with MS (n = 60) and NC (n = 20), with a subset also differing from those with neuroborreliosis (n = 8). We identified MS-associated proteins, including novel candidate biomarkers such as LY9 and JCHAIN, and putative treatment targets, such as SLAMF7, BCMA, and IL5RA, for which drugs are already licensed in other indications. The CSF proteome differences between relapsing and progressive MS were minimal, but major changes were noted in individuals older than 50 years, indicating a shift from MS-associated inflammatory to age-related protein signature. NEFL was the only serum protein that differed between individuals with MS and controls.

Discussion: This study unveils a unique CSF proteomic signature in MS, providing new pathophysiologic insights and identifying novel biomarker candidates and potential therapeutic targets. Our findings highlight similar immunologic mechanisms in relapsing and progressive MS and underscore aging's profound effect on the intrathecal immune response. This aligns with the observed lower efficacy of immunotherapies in the elderly, thus emphasizing the necessity for alternative therapeutic approaches in treating individuals with MS beyond the age of 50.

Figure 1. Study Design

Individuals with RRMS were selected alongside age-matched individuals with PPMS and NC and individuals with LNB to assess MS-specific protein abundance using a proximity extension assay, a targeted proteomic approach. Data acquisition was followed by data analysis to identify the effect of confounding variables and to discern MS-specific and age-related protein signatures. CSF findings were validated in independent age-matched cohorts and further compared with serum proteomic profiles. LNB, Lyme neuroborreliosis; NC, neurologic controls; PPMS, primary progressive MS; RRMS, relapsing-remitting MS.

Figure 2. Influence of Demographics and Diagnostic Parameters on CSF Proteome

(A) Extent of the overall CSF proteome variability explained by demographics and diagnostic CSF parameters. (B) Effect of sex. (C) Age effect. (D) Effect of Qalb. The dashed line represents the level of significance: adjusted p < 0.05 (FDR). FDR, false discovery rate; Qalb, albumin quotient.

Figure 3. MS-Specific Alterations of the CSF and Serum Proteome

Proteins with higher abundance in MS are displayed in red and those with lower abundance in green. (A) Comparative analysis of the CSF proteome from individuals with MS and NC was conducted separately in the discovery cohort (left) (individuals with RRMS/PPMS n = 59, NC n = 20, proteins n = 1998), the validation cohort (middle) (individuals with RRMS/PPMS n = 20, NC n = 8, proteins n = 1,625), and the combined CSF data set of the discovery and validation cohort (right) (individuals with RRMS/PPMS n = 79, NC n = 28, proteins n = 1,625). (B) Targeted analysis of the serum proteome from individuals with MS and NC in paired serum samples of the validation cohort (proteins n = 47). The dashed line represents the level of significance: adjusted p < 0.05 (FDR). (C) Hierarchical clustering of selected MS-associated CSF proteins in individuals with MS vs NC in the discovery cohort (first column), the validation cohort (second column), both cohorts combined (third column), and individuals with MS compared with LNB cohort (fourth column; individuals with RRMS/PPMS n = 59, individuals with LNB n = 8, proteins n = 47). The color indicates the direction of the association and stars the level of significance (adjusted p *** <0.001, ** <0.01, and * <0.05 [FDR]). (D) Enrichment of annotations for inflammation and immunity in the protein regulation in individuals with MS vs NC conducted in the combined CSF data set. Stars indicate significant enrichments (adjusted p *< 0.05 [FDR]). FDR = false discovery rate; LNB = Lyme neuroborreliosis; NC = neurologic controls; PPMS = primary progressive MS; RRMS = relapsing-remitting MS.

Figure 4. Association of CSF Immune Cells and Immunoglobulin Synthesis With CSF Proteome in MS

Influence of (A) CSF pleocytosis, (B) intrathecal IgG synthesis, (C) elevated percentage of B lymphocytes, and (D) elevated percentage of PB/PC on the identified 33 MS-associated proteins in the combined CSF MS cohort (individuals with RRMS/PPMS n = 79). The dashed line represents the level of significance: adjusted p < 0.05 (FDR). FDR = false discovery rate; PPMS = primary progressive MS; RRMS = relapsing-remitting MS.

Figure 5. Association of MS Subtypes With CSF Proteome

Differences between PPMS and RRMS were calculated separately in the (A) discovery cohort (individuals with RRMS n = 29, individuals with PPMS n = 30, proteins n = 1998) and (B) combined data set (individuals with RRMS n = 39, individuals with PPMS n = 40, proteins n = 1,625), without showing any group differences. (C) Secondary analysis focusing solely on the 33 validated MS-associated proteins in individuals with RRMS (n = 39) compared with those with PPMS (n = 40) in the combined MS CSF data set revealed group differences, enhancing the detection of significant differences due to increased specificity and statistical power. The dashed line represents the level of significance: adjusted p < 0.05 (FDR). FDR = false discovery rate; PPMS = primary progressive MS; RRMS = relapsing-remitting MS.

Figure 6. Analysis of Protein Abundance Across Age Groups and Age-Dependent Levels

(A) CSF proteomic changes in individuals with MS stratified for age (≤/> 50 years) were calculated separately in the discovery cohort (left) (≤50 y: n = 39; >50 y: n = 20) and combined CSF data set (middle) (≤50 y n = 43; >50 y: n = 36). Most identified inflammatory MS CSF proteins were more abundant in younger individuals compared with those aged 50 and beyond. This effect became more pronounced in a secondary analysis by focusing only on the 33 validated MS-associated proteins (right) in the combined data set. The dashed line represents the level of significance: adjusted p < 0.05 (FDR). (B) Boxplots representing the quantitative levels (y-axis: NPX values) of selected proteins (TNFSF13B [left] and TNFRSF13B [right]) stratified by age groups (x-axis) and diagnosis groups (MS, blue; NC, orange). Although protein levels of TNFRSF13B decline in the age group older than 50 years, TNFSF13B levels are higher in older individuals with MS. (C) Linear regression analysis of GDF15 and age in MS and NC cohorts. FDR = false discovery rate; NC = neurologic controls.