Author Of 2 Presentations
P0090 - Immune cell profiles associated with CIS progression and stability using RNA-seq single-cell analysis (ID 577)
Abstract
Background
Clinically Isolated Syndrome (CIS) can be an initial multiple sclerosis (MS) presentation, but the risk for developing future demyelinating episodes is often uncertain. The singular clinical episode of demyelination is thought to be driven by acute inflammation brought about by proinflammatory macrophages, autoreactive CD8+ and CD4+ T cells, and B cells crossing the blood-brain-barrier.
Objectives
To use single-cell transcriptome analyses to identify immune cell profiles in CIS patients associated with a higher risk of developing an MS relapse or new central nervous system (CNS) disease activity on brain MRI.
Methods
Cryopreserved peripheral blood mononuclear cells (PBMC) were collected at study entry and six months from six CIS participants from the ITN020AI STAyCIS trial of atorvastatin. Three participants met the primary endpoint defined as ≥ 3 new T2 lesions on MRI or an MS relapse within 12 months, while the other three did not. RNA from about 10,000 PBMC per sample were sequenced at the single-cell level using the 10X Genomics Chromium platform and analyzed using Cell Ranger software. Seurat R software package was used for downstream analysis, with cell type annotated both computationally (SingleR) and by matching differentially expressed genes with canonical markers using online genomics databases.
Results
Approximately 30 clusters of differentially expressed transcripts were assigned as specific cell types; baseline frequencies of seven clusters enriched >2-fold for macrophage, NK, NKT, CD4+ T cell, and B cell transcripts were associated with disparate outcomes at six months. Several clusters assigned as B cells, CD4+ and CD8+ T cells were expanded from baseline at six months in participants with CNS disease activity at that time point, while no notable changes were observed in those with stable disease.
Conclusions
An understanding of the immunological changes associated with future disease activity in CIS may be useful for making early treatment decisions. Our preliminary data suggest that participants with disparate clinical outcomes exhibited different frequencies of innate and adaptive leukocyte populations in PBMC, which may represent a predictive biomarker for aggressive early intervention. Also, expanded clusters of CD4+ and CD8+ T cells and B cells in blood at the time of disease activity may identify biomarkers that contribute to acute demyelination. Follow-up studies are underway to increase sample size and incorporate protein expression data to better define cell subtypes and clonality of T and B cells associated with disparate outcomes in the STAyCIS trial.
P0180 - Utility of neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) in tracking treatment response in PPMS patients (ID 1447)
Abstract
Background
There is growing evidence that serum neurofilament light chain (sNfL) and serum glial fibrillary acidic protein (sGFAP) are useful biomarkers in multiple sclerosis (MS). While these biomarkers have been studied in cohorts of MS patients including all disease subtypes (relapsing remitting, secondary progressive, and primary progressive [PP]), few studies have examined biomarker response to treatment in a cohort of exclusively PPMS patients.
Objectives
To assess how sNfL and sGFAP change over time in PPMS patients who transition from no medication to high potency medication.
Methods
Serum samples were collected from 25 patients biannually for 5 years. sNfL and sGFAP were measured using a sensitive single molecule array platform (Quanterix), and log-transformed to assume a normal distribution. Patients were split into two groups based on medication status: patients switched from no medication to a high-potency drug (n=5) versus patients never on medication for the study duration (n=14). Patients on platform drugs or high-potency drugs for the duration of the study were excluded. High-potency drugs include natalizumab, ocrelizumab, fingolimod, and dimethyl fumarate. Statistical analyses were performed in R.
Results
Linear models found sNfL positively associated with age (β=0.024, p=0.004), while higher sGFAP levels were seen in women (β=-0.737, p=0.037). Spaghetti plots examining change in sNfL and sGFAP over five years displayed no trend in either group. Paired Wilcoxon Tests comparing biomarker levels at first versus last available sample showed no significant difference for any group (‘No Drug’ NfL p=0.296, ‘High Potency’ NfL p=0.188; ‘No Drug’ GFAP p=0.583, ‘High Potency’ GFAP p=0.063).
Conclusions
Low levels of NfL are known to accumulate in blood of healthy individuals over time, so the association between sNfL and age is not surprising and has been previously reported. However, sGFAP showed a strong association with female sex; this may be related to a slightly higher average age at enrollment among women. Overall, the spaghetti plots showed little change in either group, with no statistically significant difference in any group over 5 years. This may indicate that these drugs do not affect biomarker level in PPMS. This is further supported by evidence that these immunosuppressive drugs are effective in preventing relapse and inflammatory activity, but may not help to prevent progression. These findings suggest that these biomarkers may have a limited role in judging treatment efficacy in PPMS patients who do not experience flares or new symptoms.