Putting the Brakes Back On: What Common RRMS Drugs Do to CTLA-4 and PD-L1

A 2021 open-access study profiled inhibitory immune checkpoints in relapsing-remitting multiple sclerosis (RRMS). Compared with healthy controls, untreated (naïve) RRMS patients had lower CTLA-4 and PD-L1 mRNA in PBMCs. Several first-line therapies—especially fingolimod—were associated with higher expression of these “immune brakes,” potentially helping rein in autoreactive T cells. The work also re-analyzed single-cell RNA-seq data to map where these genes sit across immune cell types. Caveats: small cohorts, some internal inconsistencies in reported sample sizes and p-values, and mRNA≠protein.

Why checkpoints matter in MS
Immune checkpoints like CTLA-4 and PD-1/PD-L1 are the built-in brakes that keep T cells from overheating. In autoimmunity, those brakes can be too soft; in cancer, they can be too strong. The paper at hand set out to ask a straightforward question with therapeutic implications: How do common RRMS drugs relate to CTLA-4 and PD-L1 expression in blood?

What the authors did (in plain English)
Single-cell mapping (in silico): They re-analyzed a public single-cell RNA-seq dataset (GSE138266; Schafflick et al.) spanning blood and CSF, focusing on PBMCs. After QC they kept 40,515 cells, clustered them (PCA → kNN → Louvain, UMAP for visualization), and assigned cell identities.

Takeaway: CTLA-4 localized mainly to regulatory T cells (Tregs) and γδ T cells, while PD-L1 (CD274) appeared broadly expressed rather than tied to a single lineage.

PBMC qPCR (wet lab): They measured CTLA-4 and PD-L1 mRNA by RT-qPCR (2^-ΔCT normalized to GAPDH) in peripheral blood from RRMS patients on therapy vs naïve RRMS vs healthy controls. Significance threshold: p < 0.05.

Cohorts (as reported by the paper):

Treated RRMS: 10 each on fingolimod, IFNβ-1α, glatiramer acetate (GA), dimethyl fumarate (DMF).

Naïve RRMS: n = 5.

Healthy controls: the text lists 16 in Methods, 24 in Results, and a table fragment shows 6—an internal inconsistency the authors don’t resolve (likely a typesetting/aggregation error). Key results (with numbers where the paper provides them)

Naïve RRMS vs healthy:
• CTLA-4 lower in naïve RRMS than healthy (example means shown: 0.19 vs 0.32, p = 0.0004).

• PD-L1 lower in naïve RRMS than healthy (0.15 vs 0.72, p < 0.0001).

Therapy-associated changes vs naïve RRMS:

• Fingolimod: higher CTLA-4 (0.74 vs 0.19, p < 0.0001) and higher PD-L1 (0.69 vs 0.15, p < 0.0001). This was the most pronounced shift.

• DMF: higher CTLA-4 (0.47 vs 0.19, p < 0.0001) and higher PD-L1 (directionally ↑; reported significant).

• IFNβ-1α: higher CTLA-4 (0.35 vs 0.19, p < 0.0001) and higher PD-L1 (0.24 vs 0.15, p < 0.0001).

• GA: CTLA-4 lower than naïve (means 0.15 vs 0.19, ns), and for PD-L1 the text is internally inconsistent—one sentence lists 0.39 vs 0.15, p < 0.0001, another says the increase was not significant; in the Discussion the authors conclude GA had no significant effect on either checkpoint. Treat GA’s PD-L1 effect with caution.

Big picture claim: Drugs that help in RRMS may, in part, boost inhibitory checkpoint tone in circulating immune cells, potentially damping autoreactivity. The paper singles out fingolimod as the standout on both CTLA-4 and PD-L1.

How might this fit with what we already know?
Mechanistic plausibility: Fingolimod traps lymphocytes in lymph nodes via S1P receptor modulation, shifts cytokine profiles toward less inflammatory states, and has been linked to features of T-cell “exhaustion” (higher PD-1/TIM-3). Seeing higher CTLA-4/PD-L1 mRNA in PBMCs lines up with that immunoregulatory tilt.

Cellular context matters: The single-cell view showing CTLA-4 mainly in Tregs supports a narrative where therapies that preserve/expand Treg function could raise checkpoint expression systemically. PD-L1’s distribution across multiple immune subsets is consistent with its role as a broadly inducible ligand in peripheral tolerance.

Strengths to appreciate
Two-pronged approach: Pairing a single-cell atlas re-analysis with patient PBMC measurements adds interpretability: you see both “where” (cell types) and “how much” (bulk PBMC).

Clinical relevance: The comparison spans four widely used RRMS therapies, not just one.

Important limitations (read before over-interpreting)
mRNA ≠ protein/function. The study measured transcripts; checkpoint protein levels, surface localization, and ligand/receptor signaling weren’t tested.

Small, uneven groups and reporting inconsistencies. The healthy-control n varies by section, and GA’s PD-L1 significance is described both ways. Treat the exact effect sizes with caution; focus on directions and relative patterns.

PBMCs only. No CNS tissue or CSF validation for the qPCR arm; peripheral changes may not mirror CNS immunobiology. What this could mean for practice and research
Biomarker potential: If validated at the protein level and in larger cohorts, CTLA-4 and PD-L1 could be explored as pharmacodynamic readouts of “immune braking” in RRMS (e.g., does a patient who ramps up these checkpoints on therapy relapse less?).

Drug mechanism nuance: The particularly strong fingolimod signal hints that S1P-axis modulation may synergize with checkpoint pathways—worth probing in longitudinal, single-cell proteogenomic studies.

Therapeutic boundaries: Given the flipside of checkpoint inhibition in oncology (immune-related adverse events), dialing up checkpoints in autoimmunity is conceptually coherent—but it must be balanced against infection risk and immunosurveillance; this study doesn’t address safety.

Bottom line
In RRMS, the immune system’s brakes—CTLA-4 and PD-L1—look under-expressed in untreated patients and partly restored by several standard therapies, most notably fingolimod. It’s a tidy mechanistic thread tying clinical drugs to the biology of tolerance—but we still need protein-level validation, longitudinal outcomes, and cleaner reporting to translate these findings into biomarkers or therapeutic targets.

Disclaimer: This blog post is based on the provided research article and is intended for informational purposes only. It is not intended to provide medical advice. Please consult with a healthcare professional for any health concerns.

References:
Derakhshani, A., Asadzadeh, Z., Safarpour, H., Leone, P., Shadbad, M. A., Heydari, A., ... & Racanelli, V. (2021). Regulation of CTLA-4 and PD-L1 expression in relapsing-remitting multiple sclerosis patients after treatment with fingolimod, IFNβ-1α, glatiramer acetate, and dimethyl fumarate drugs. Journal of Personalized Medicine, 11(8), 721.