Elicit: B-cell Biomarkers and Ocrelizumab Response
B-cell Biomarkers and Ocrelizumab Response
Which biomarkers of B-cell depletion correlate with clinical response to ocrelizumab?
Abstract
Multiple biomarkers of B-cell depletion correlate with clinical response to ocrelizumab, though their predictive value varies by clinical context. Total CD19+ B-cell depletion showed consistent associations with outcomes in RRMS, with higher ocrelizumab exposure producing lower B-cell counts and reduced disability progression (HR 0.64, p=0.0135). Baseline CD19+ counts predicted repopulation kinetics, with counts ≥12-14% identifying patients at risk for fast repopulation and higher MRI activity (17.39% vs. 2.53%, p=0.008). Plasmablast levels emerged as particularly informative: responders at 24 months had 3-fold lower plasmablasts at 6 months compared to non-responders (7.69% vs. 22.66%, p=0.043), and plasmablast populations correlated positively with 12-month EDSS scores (R=0.564, p=0.004). However, in PPMS, baseline inflammatory status determined which biomarkers mattered—B-cell repopulation and serum neurofilament levels predicted outcomes in Gd+ patients, while serum IgA levels and T-cell remodeling were more relevant in Gd- patients. Elevated baseline regulatory populations (CD49d+ T-cells, B-1a cells) predicted achievement of NEDA-3 status, while CD8+ T-cell modulation correlated with disability outcomes (OR=1.01, p=0.02). Treatment-naive patients demonstrated stronger biomarker-outcome correlations than previously treated patients (HR=2.53 for radiological activity with prior treatment, p=0.039), suggesting prior therapies modify B-cell compartment dynamics and diminish predictive accuracy of standard depletion metrics.
Methods
We analyzed 10 sources from an initial pool of 200, using 8 screening criteria. Each paper was reviewed for 5 key aspects that mattered most to the research question.
Records from Elicit search
n = 200 Papers screened using: Ocrelizumab Treatment, B-cell Depletion Biomarkers, Clinical Response Outcomes, Quantitative Correlation Analysis, Follow-up Biomarker Measurements, Adequate Sample Size, Full-text Publication, Ocrelizumab-specific Data
n = 200 Papers screened out
n = 190 Papers included for extraction
n = 10
Results
Characteristics of Included Studies
All 10 studies evaluated biomarkers of B-cell depletion in patients treated with ocrelizumab, though they varied in MS subtype, sample size, and follow-up duration.
| Study | Full text retrieved? | MS Subtype | Sample Size | Follow-up Duration | Previous Treatment | Baseline EDSS (median/mean) |
|---|---|---|---|---|---|---|
| S. Hauser et al., 2023 | Yes | RRMS and PPMS | Not specified | 96 weeks (RRMS), variable (PPMS) | Randomized to ocrelizumab or comparator | Not specified |
| Ece Akbayır et al., 2025 | Yes | RRMS | 31 | 12 months | Previously treated, resistant to first-line agents | Not specified |
| M. Boziki et al., 2022 | Yes | Active PPMS | 22 | 24 months | Treatment-naive for immunosuppressants | 4.91 (mean) |
| J. I. Fernández-Velasco et al., 2021 | Yes | PPMS | 53 | 6 months | Not specified | 6 (median) |
| Alice Willison et al., 2025 | Yes | RRMS | 34 OCR, 25 OFA, 20 treatment-naive | 12 months | Median 1 previous DMT (OCR and OFA groups); 25 treatment-naive | 2.00 (median) |
| M. Cellerino et al., 2021 | Yes | RRMS (n=93), PPMS (n=43), SPMS (n=17) | 153 | 1.9 years (median) | 76.95% previously treated | Lower baseline EDSS associated with better outcomes |
| Hany Mohammed Amin Aref et al., 2024 | No | RRMS | 30 | 12 months | Most had two previous DMTs; 13.3% treatment-naive | 4.5 (median) |
| G. Abbadessa et al., 2021 | Yes | RRMS (n=127), SPMS (n=43), PPMS (n=48) | 218 (155 at 12 months) | At least 6 months; 155 with 12-month follow-up | 76.95% previously treated; 23.04% treatment-naive | Not specified |
| J. I. Fernández-Velasco et al., 2022 | Yes | PPMS | 69 | 12 months | Not specified | 5.5 (median) |
| Nicola Capasso et al., 2022 | Yes | RRMS, SPMS, PPMS | 78 | 36.5 months (mean) | Previous DMTs collected at baseline | Not specified |
B-Cell Depletion Biomarkers Measured
Studies employed diverse approaches to quantify B-cell depletion, though CD19+ B cells emerged as the most commonly measured biomarker. S. Hauser et al. measured CD19+ B cells in cells/μL and categorized patients by median B-cell levels (0, 1-5, and >5 cells/μL). Hany Mohammed Amin Aref et al. reported baseline CD19 B cell counts of 65.98 ± 79.04 cells/μl, which depleted to 3.59 ± 2.94 cells/μl at 1 month, 25.6 ± 43.98 cells/μl at 6 months, and 11.11 ± 19.53 cells/μl at 12 months.
Key Findings
The studies reveal complex, context-dependent relationships between B-cell depletion biomarkers and clinical response to ocrelizumab. Rather than a single biomarker universally predicting outcomes, different markers appear relevant in different clinical contexts.
MS Subtype as a Context Modifier
The relevance of specific biomarkers varies by MS subtype. In RRMS populations, total B-cell depletion metrics (CD19+ counts, repopulation kinetics) showed strong associations with clinical outcomes. In PPMS populations, the pattern differed substantially. While some studies observed similar trends, the PPMS-specific studies revealed that baseline inflammatory status fundamentally altered which biomarkers mattered.
The Plasmablast Paradox
Multiple studies identified plasmablasts as paradoxically important despite representing a small fraction of circulating B cells. This apparent contradiction resolves when considering that ocrelizumab depletes CD20+ B cells but spares CD20-negative plasmablasts and plasma cells.
Treatment History as a Confounding Factor
Previous treatment exposure consistently modified biomarker-response relationships. This likely reflects that prior treatments alter the B-cell compartment’s composition and repopulation capacity.