B-cell Biomarkers and Ocrelizumab Response

Which biomarkers of B-cell depletion correlate with clinical response to ocrelizumab?

CD19+ B-cell counts, plasmablast levels, baseline regulatory cell populations (CD49d+ T-cells and B-1a cells), and CD8+ T-cell depletion correlate with clinical response to ocrelizumab, with the relative importance of each biomarker varying by MS subtype and baseline inflammatory status.

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

Paper search

We performed a semantic search across over 138 million academic papers from the Elicit search engine, which includes all of Semantic Scholar and OpenAlex.

We ran this query: "Which biomarkers of B-cell depletion correlate with clinical response to ocrelizumab?"

The search returned 200 total results from Elicit. We retrieved 200 papers most relevant to the query for screening.

Data extraction

We asked a large language model to extract detailed data on:

1. B-Cell Depletion Biomarkers: Extract specific biomarkers and their measurement units, baseline values, follow-up values, depletion patterns, and categorizations used.
2. Clinical Response Measures: Include outcomes such as annualized relapse rate, EDSS scores, composite measures, etc., along with assessment timepoints.
3. Biomarker-Response Correlations: Report associations between biomarkers and clinical outcomes, including statistical measures like correlation coefficients and p-values.
4. Patient Characteristics: Collect data on MS subtype, disease duration, previous treatment, demographics, and sample size.
5. Key Findings: Summarize main conclusions, clinical implications, recommendations for monitoring or dosing strategies, limitations, and future research directions.

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.

The included studies represented diverse MS populations, with sample sizes ranging from 22 to 218 patients. Most studies (8 of 10) had full-text availability. Follow-up durations ranged from 6 months to 36.5 months. The majority of patients across studies had prior treatment exposure, though several studies included treatment-naive cohorts. Baseline disability varied substantially, with median/mean EDSS scores ranging from 2.00 to 6.0, reflecting heterogeneity in disease severity.

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. Specific findings included:

• Baseline CD19 B cell counts of 65.98 ± 79.04 cells/μl, depleting 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.
• Other studies quantified specific B-cell subsets beyond total CD19+ counts, measuring unique populations like plasmablasts and memory B cells.
• Patients were categorized based on repopulation kinetics with classifications of fast and slow repopulation.

Clinical Response Measures

Studies used heterogeneous outcome measures to assess clinical response to ocrelizumab:

• Disability Progression: Included measures like confirmed disability progression (CDP) and EDSS scores.
• Relapse-Related Outcomes: Annualized relapse rate (ARR) was analyzed and showed significant reductions across studies.
• MRI Outcomes: Variability in MRI outcomes assessed new/enlarging lesions and brain volume changes.
• Composite Measures: NEDA-3 defined as absence of relapses and confirmed disability worsening.

Biomarker-Clinical Response Correlations

Total B-Cell and CD19+ Depletion

Associations between ocrelizumab exposure, B-cell depletion, and clinical outcomes showed:

• Higher exposure correlated with lower B-cell counts and higher rates of disability progression.
• Statistically significant relationships between CD19 B cell counts and disability and radiological outcomes were observed.

B-Cell Subset Correlations

Significant roles of plasmablasts as predictors of treatment response across multiple studies were identified.

Regulatory Cell Populations

Elevated baseline populations of regulatory T cells were predictive of better outcomes, reinforcing the role of the immune environment post-treatment.

Patient-Level Predictors

Notably, lower baseline EDSS and treatment-naive status were associated with more favorable clinical responses, suggesting previous treatments may hinder the efficacy of ocrelizumab.

Synthesis

The studies reveal complex, context-dependent relationships between B-cell depletion biomarkers and clinical response to ocrelizumab. Furthermore, it highlights that different markers might be relevant depending on clinical context, suggesting a multifaceted immune response to treatment.

References

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