The research team, led by Kamil Wierzchowski and Łukasz Makowski, set out to answer a deceptively simple question: what shear rates do cells actually encounter in a rocking bioreactor, and how do those rates affect cell survival? The answer matters because rocking bioreactors are increasingly used for growing lymphocytes, stem cells, and other fragile cell types that cannot tolerate the impeller-driven turbulence of stirred tanks. Understanding the hydrodynamic microenvironment is essential for anyone attempting to scale up production of cell therapies or biologics in disposable systems.

To characterize the fluid dynamics, the researchers built a two-dimensional Computational Fluid Dynamics model employing the Volume of Fluid method. This approach tracks the interface between the liquid culture medium and the gas headspace inside the culture bag, allowing the simulation to capture the sloshing wave motion that defines rocking bioreactor operation. The model simulated the culture bag under various rocking angles and frequencies, computing velocity fields, mixing behavior, and shear rate distributions throughout the liquid volume. Crucially, the team validated their numerical predictions against experimental mixing time measurements, achieving an absolute mean percentage difference of 29.2 percent. The model demonstrated high predictive accuracy at very low and very high Reynolds numbers, though its performance degraded somewhat at medium Reynolds numbers, a limitation the authors acknowledge openly.

The shear rate findings are striking. Averaged shear rates across the liquid volume remained below 22.5 s⁻¹ under all studied rocking conditions, values that would seem entirely benign for animal cell cultures. But the local maximum shear rates told a very different story. Under intensified rocking, these localized peaks soared past 30,000 s⁻¹, dramatically exceeding the lethal threshold of 1500 s⁻¹ that the team identified for HL-60 lymphocytes. This means that even though the bulk fluid appears gentle, cells passing through narrow microzones near the bag walls, the wave crest, or the gas-liquid interface can be subjected to shear stresses hundreds of times greater than what the average suggests.

To determine exactly where cell death begins, the researchers used a rotational rheometer to expose HL-60 lymphocytes to controlled shear rates. Their experiments revealed a clear dose-response relationship: cell viability begins to decline at shear rates above 1000 s⁻¹, as cell membranes start to rupture. Above 1500 s⁻¹, the team observed total disintegration of cells. The mechanism is mechanical destruction rather than metabolic exhaustion: hydrodynamic stress physically tears apart the lipid bilayer that encloses each cell, releasing intracellular contents into the medium. The researchers confirmed this by measuring the activity of lactate dehydrogenase, an enzyme normally confined inside cells, in the culture supernatant. Elevated LDH activity served as a molecular fingerprint of membrane damage, correlating directly with the shear conditions the cells had experienced.

The consequences for actual cell culture are significant. When the team grew HL-60 lymphocytes in a rocking disposable bioreactor under conditions where local shear rates consistently exceeded lethal thresholds, they observed impaired cell growth and increased release of intracellular enzymes. The problem was particularly acute during intensified rocking, when higher rocking angles and frequencies were used to improve mixing and oxygen transfer. This creates a fundamental trade-off: the very conditions that enhance mixing intensification and mass transfer also generate the hydrodynamic hotspots that kill shear-sensitive cells.

This trade-off is not merely an academic curiosity. Rocking disposable bioreactors are widely used in biopharmaceutical manufacturing for growing mammalian cell lines, producing viral vectors, and expanding cell therapies. As the industry shifts toward personalized medicine and cell-based treatments, the ability to reliably culture fragile lymphocytes in disposable systems becomes increasingly important. HL-60 cells, a human promyelocytic leukemia cell line derived from a patient with acute promyelocytic leukemia, serve as a well-characterized model for lymphocyte-like cells in this context. Their sensitivity to hydrodynamic stress makes them an ideal sentinel for identifying conditions that would harm other shear-sensitive cell types.

The computational framework developed by the Warsaw team provides a valuable tool for navigating this optimization problem. By simulating shear rate distributions under different operating parameters, researchers can identify rocking angles and frequencies that balance mixing efficiency against hydrodynamic stress. The model can also guide bioprocess scale-up, helping engineers predict how changes in bag geometry, liquid volume, and rocking dynamics will affect the shear microenvironment as processes move from laboratory to production scale. Rather than relying on trial-and-error experimentation, the numerical approach allows systematic exploration of the design space before any cells are placed at risk.

The study also highlights the importance of looking beyond averaged hydrodynamic parameters when assessing bioreactor suitability for shear-sensitive cultures. Traditional scale-up criteria often rely on average shear rates or power input per volume, which can mask the localized extremes that actually determine cell fate. The finding that local maximum shear rates can exceed lethal thresholds while averages remain benign suggests that cell damage in rocking bioreactors may be far more common than previously appreciated. For bioprocess engineers, this means that successful application of rocking disposable bioreactors for fragile cell cultures requires a strategic balance between mixing intensification and the mitigation of lethal local shear effects, informed by detailed computational analysis of the true hydrodynamic microenvironment that cells experience.

Subject of Research: Numerical analysis of shear rate in a rocking bioreactor and its impact on HL-60 lymphocytes

Article Title: Numerical analysis of shear rate in a rocking bioreactor and its impact on HL-60 lymphocytes

Article References: Wierzchowski, K., Krzosa, R., Pawlukiewicz, S., Pilarek, M., & Makowski, Ł. (2026). Numerical analysis of shear rate in a rocking bioreactor and its impact on HL-60 lymphocytes. Applied Microbiology and Biotechnology. https://doi.org/10.1007/s00253-026-14076-6

Image Credits: AI Generated

DOI: 10.1007/s00253-026-14076-6

Keywords: Numerical, analysis, shear, rate, rocking, bioreactor, impact, HL-60, lymphocytes, scientific research

The study, published in Annals of Clinical and Translational Neurology, drew on participants from DAYBREAK, a phase 3 open-label extension trial that followed adults with relapsing forms of multiple sclerosis who had previously completed earlier ozanimod trials. Across the parent trials and the extension, participants accumulated up to 117.2 months, nearly a decade, of cumulative exposure to the drug. Of the 2,494 people who entered DAYBREAK, nearly 80 percent completed the study. The researchers focused on 1,679 participants who had at least one day of post-treatment safety follow-up and who did not transition to commercial ozanimod within 14 days of stopping the study drug, creating a window in which any returning disease activity could be observed.

The headline finding is striking in its simplicity: only 55 participants, or 3.3 percent of the analysis population, experienced an objectively confirmed relapse after permanently discontinuing ozanimod. When suspected relapses that failed to meet strict objective criteria were included, the figure rose only slightly, to 4.1 percent. Given that multiple sclerosis is, by its nature, a relapsing disease in these patients, the question the investigators set out to answer was not merely whether relapses occurred, but whether they occurred at a rate and severity beyond what would be expected from the underlying disease simply reasserting itself.

The timing of the relapses tells a story written in pharmacology. Ozanimod works by selectively modulating sphingosine 1-phosphate receptors 1 and 5, trapping lymphocytes inside lymphoid tissues and preventing them from migrating into the central nervous system, where they drive the inflammatory attacks that characterize multiple sclerosis. The drug itself has an elimination half-life of about 21 hours, but its major active metabolite lingers far longer, with a half-life of approximately 11 days. After discontinuation, blood lymphocyte counts return to normal after a median of 30 days, with 80 to 90 percent of patients back in the normal range within three months. True to that pharmacokinetic profile, relapses clustered at two to three months after stopping the drug, with a median onset of 61 days and a range of 3 to 141 days.

The granular breakdown is equally informative. Only five participants, 0.3 percent, relapsed within the first 28 days after discontinuation. Another 22 relapsed between days 29 and 60, representing 1.7 percent of those followed that long, and 26 more relapsed between days 61 and 90, or 2.2 percent of participants with follow-up beyond 60 days. Just two participants relapsed after 90 days, one of whom fell within the protocol’s permitted 10-day follow-up window and the other of whom had been nonadherent to follow-up because of COVID-19 travel restrictions. The pattern mirrors the waning of the drug’s immunological grip rather than any paradoxical overshoot.

Severity is where the rebound question is truly decided, and here the data lean strongly toward reassurance. Nearly all post-treatment relapses were judged mild or moderate by the treating investigators: 20 were mild and 34 were moderate, while only a single participant, 1.8 percent, had a relapse classified as severe. Even that case, the investigators concluded, did not represent higher-than-expected disease activity. The participant, a 44-year-old woman with a heavy pre-treatment disease burden, including 70 T2 lesions on MRI and substantial prior relapse activity, had already experienced a severe relapse while still taking ozanimod roughly a year before the post-treatment episode. Her disability worsened from an Expanded Disability Status Scale score of 7.5 to 8.0, she was not hospitalized, and she achieved partial recovery within 36 days.

Recovery outcomes across the relapsing group were similarly encouraging. Among the 55 participants with confirmed post-treatment relapse, 76.4 percent had completely recovered by their last safety follow-up, 20 percent had partially recovered, and only two participants had not recovered. Median relapse duration was 22 days, and the median increase in EDSS score at relapse was just one point. Four of the seven participants whose EDSS scores rose by two or more points went on to make complete recoveries. Notably, no MRI scans were performed at the time of relapse, and no tumefactive demyelinating lesions, the dramatic, mass-like brain lesions sometimes seen after fingolimod cessation, were ever reported during or after ozanimod treatment in the entire trial program.

The investigators went further, stress-testing their data against definitions of rebound used in earlier studies. Applying the criteria from the fingolimod FREEDOMS trials, where higher-than-expected disease activity rates of 4.0 and 3.5 percent were recorded but were matched by 4.4 and 4.1 percent in placebo groups, 1.4 percent of the ozanimod analysis population met the threshold. Of the 24 participants qualifying, 14 were hospitalized during relapse, but 11 of those hospitalizations occurred in Eastern Europe, where intravenous steroid treatment for relapses is routinely delivered on an inpatient basis regardless of severity, a practice pattern that inflates hospitalization counts compared with settings like the United States. An informal comparison of EDSS changes during relapse against historical data from untreated patients found no statistically significant difference, further supporting the conclusion that these episodes reflect ordinary disease reactivation, not rebound.

Who relapsed matters as much as how many. Participants who experienced post-treatment relapse were younger, diagnosed with multiple sclerosis at a younger age, and carried greater clinical and radiological disease burden, with more gadolinium-enhancing and T2 lesions at baseline and more relapses both during the trials and in the year before discontinuation. A multivariable logistic regression model identified three nominally significant predictors: younger age at diagnosis, a higher number of relapses during the extension trial, and a higher T2 lesion count at parent-trial baseline. This aligns with a consistent theme in the literature, that patients with more active disease before or during treatment face greater risk of relapse after stopping any disease-modifying therapy, and with the well-documented observation that relapse rates in multiple sclerosis peak in the twenties and thirties before declining with age.

The study’s limitations deserve honest acknowledgment. DAYBREAK was not designed to assess post-treatment relapse, the analysis is exploratory and post hoc, and the reported P values are nominal rather than confirmatory. Roughly one-fifth of the overall population lacked safety follow-up and was excluded, though their characteristics resembled those analyzed. About a quarter of the analysis population had fewer than 29 days of follow-up, meaning some relapses may have occurred after observation ended, and the strict requirement for objective neurological worsening may have undercounted milder episodes. The absence of MRI data limits conclusions to clinical activity. Still, the authors’ conclusion stands on a large, systematically assessed dataset: no case showed a pattern suggestive of rebound, and the return of disease activity after stopping ozanimod appears milder and less frequent than that reported after discontinuing natalizumab, where rebound rates of 8 to 22 percent have been reported, or fingolimod, where observational studies have ranged as high as 42.8 percent under varying definitions. For clinicians and patients weighing discontinuation, whether for family planning, side effects, or waning benefit, the message is clear: relapses cluster two to three months after the last dose, are usually mild to moderate, and usually resolve completely, which argues for prompt switching to another therapy and careful monitoring rather than fear of a pharmacological storm.

Subject of Research: Relapse activity and rebound risk after discontinuation of the multiple sclerosis therapy ozanimod in the DAYBREAK open-label extension trial

Article Title: Multiple Sclerosis Relapse Activity After Ozanimod Discontinuation in DAYBREAK Trial Participants

Article References: Gold, R., Selmaj, K. W., Berkovich, R., Cohen, J. A., Comi, G., Havrdová, E. K., Sheffield, J. K., Desai, H., Cheng, C.-Y., Riolo, J. V., Thorpe, A., DeBoer, E., & Cree, B. A. C. (2026). Multiple Sclerosis Relapse Activity After Ozanimod Discontinuation in DAYBREAK Trial Participants. Annals of Clinical and Translational Neurology, 13(10), 2017-2026. https://doi.org/10.1002/acn3.70366

Image Credits: AI Generated

DOI: 10.1002/acn3.70366

Keywords: multiple sclerosis, ozanimod, DAYBREAK trial, rebound, disease-modifying therapy, S1P receptor modulator, relapse, fingolimod, natalizumab, lymphocytes, pharmacokinetics, neurology

The review, authored by Yujing Li and Zhuoli Zhang of Peking University First Hospital together with Hong Yu of the University of Texas Health Science Center at San Antonio, synthesizes a growing body of experimental and clinical evidence linking nutrient metabolism to immune dysfunction. Its central claim is deceptively simple: the way immune cells process glutamine and convert it into glutamate is not a passive background process but an active regulatory network that shapes immune cell fate, differentiation, and effector function. When that network is disrupted, the result may be the loss of self-tolerance and persistent immune activation that define autoimmune rheumatic diseases.

To appreciate why this matters, it helps to understand what the glutamine-glutamate axis actually does. Glutamine is the most plentiful free amino acid in plasma, and immune cells consume it voraciously. Once transported into a cell, glutamine can be converted to glutamate through a reaction catalyzed by the enzyme glutaminase, releasing ammonia in the process. Glutamate then feeds into multiple downstream routes: it can be further converted to alpha-ketoglutarate, which enters the tricarboxylic acid cycle to generate energy and biosynthetic intermediates; it can supply nitrogen for the production of other amino acids, nucleotides, and the antioxidant glutathione; and it can participate in non-essential amino acid synthesis that rapidly dividing cells require. In effect, the axis is a metabolic junction connecting fuel supply, building-block production, and redox balance.

What has become increasingly clear over the past decade is that this junction does far more than keep cells alive. Metabolic reprogramming, the wholesale shift in how a cell generates and spends energy, is now recognized as a prerequisite for immune cell activation and lineage commitment. A resting lymphocyte and an activated lymphocyte look almost nothing alike on the inside, and much of that difference is driven by changes in glutamine flux. The same is true of monocytes and macrophages, the innate immune cells that patrol tissues and coordinate inflammatory responses. By controlling the availability of alpha-ketoglutarate and other metabolites, the glutamine-glutamate axis influences epigenetic modifications, signaling cascades, and transcriptional programs that determine which genes a cell expresses and, ultimately, what that cell becomes.

The review emphasizes that this regulation operates across multiple immune cell populations. In lymphocytes, glutamine metabolism supports the proliferation and differentiation needed for adaptive immune responses, and alterations in flux can bias cells toward inflammatory or regulatory fates. In monocytes and macrophages, the axis helps govern polarization, the process by which these cells adopt pro-inflammatory or tissue-repairing identities. Because autoimmune rheumatic diseases involve both arms of immunity, dysregulated glutamine metabolism provides a mechanistic bridge that can explain how nutrient utilization becomes entangled with immune pathology in conditions as heterogeneous as rheumatoid arthritis, lupus, and related disorders.

Autoimmune rheumatic diseases themselves are a formidable clinical challenge. They are characterized by the immune system’s loss of tolerance to the body’s own components, producing chronic inflammation that damages joints, skin, kidneys, blood vessels, and other organs. Current therapies, ranging from conventional immunosuppressants to modern biologics, have transformed outcomes for many patients, but they do not work for everyone, and long-term immunosuppression carries significant risks. This therapeutic gap has pushed researchers toward immunometabolism, the study of how metabolic pathways govern immune behavior, in the hope that rewiring cellular metabolism might calm inflammation more precisely than broadly blunting the immune system.

Accumulating experimental and clinical evidence, the authors write, associates dysregulated glutamine-glutamate metabolism with immune dysregulation and tissue injury in rheumatic diseases. In practical terms, this means that abnormalities in how immune cells take up glutamine, convert it to glutamate, and channel the resulting metabolites into energy production and biosynthesis appear to track with the inflammatory damage seen in patients. The review frames this axis as an immunometabolic regulatory network that links nutrient utilization and cellular metabolic remodeling to immune cell fate and function, positioning it as a candidate mechanism underlying the chronic immune activation that keeps these diseases smoldering.

The therapeutic implications are considerable. If the glutamine-glutamate axis drives immune pathology, then targeting it offers a strategy that is conceptually distinct from existing drugs. Rather than blocking a single cytokine or surface receptor, metabolic interventions could alter the fundamental operating conditions of overactive immune cells, starving them of the biosynthetic support they need to sustain inflammation while potentially sparing cells that are behaving normally. The authors suggest that a deeper understanding of these immunometabolic mechanisms may facilitate the development of precision metabolism-based therapeutic strategies for autoimmune rheumatic diseases, an approach that would tailor metabolic interventions to the specific metabolic fingerprints of a patient’s immune cells.

Precision is the operative word. Glutamine is not simply a villain to be eliminated; it is essential for gut integrity, kidney function, and the survival of many cell types, including regulatory immune cells that restrain autoimmunity. Blanket depletion of glutamine would almost certainly cause collateral harm. The challenge, and the opportunity, lies in identifying which enzymatic steps, transporters, and downstream pathways within the axis are selectively exploited by pathogenic immune cells, and in designing drugs or dietary strategies that exploit those vulnerabilities. The review’s comprehensive mapping of the axis across lymphocytes and monocytes/macrophages is intended to provide exactly that kind of mechanistic roadmap for future drug development.

The work also reflects a broader shift in how immunology is practiced. For much of the twentieth century, immune cells were studied primarily as signaling machines, with metabolism treated as housekeeping. The immunometabolism revolution has inverted that view, revealing that metabolic state and immune identity are two sides of the same coin. The glutamine-glutamate axis, sitting at the intersection of nutrition, bioenergetics, and gene regulation, exemplifies this new paradigm. As Li, Yu, and Zhang’s synthesis makes clear, understanding how a single amino acid and its conversion product orchestrate the behavior of the very cells that attack our own tissues may prove to be one of the more consequential ideas in modern rheumatology, and a promising frontier for patients whose diseases remain beyond the reach of current therapies.

Subject of Research: The role of the glutamine-glutamate metabolic axis in regulating immune cell function and autoimmune rheumatic disease pathogenesis

Article Title: The glutamine-glutamate metabolic axis in autoimmune rheumatic diseases: immunometabolic regulation and therapeutic potential

Article References: Li, Y., Yu, H., & Zhang, Z. (2026). The glutamine-glutamate metabolic axis in autoimmune rheumatic diseases: immunometabolic regulation and therapeutic potential. Journal of Translational Medicine. https://doi.org/10.1186/s12967-026-08904-6

Image Credits: AI Generated

DOI: 10.1186/s12967-026-08904-6

Keywords: glutamine, glutamate, immunometabolism, autoimmune rheumatic diseases, rheumatoid arthritis, systemic lupus erythematosus, metabolic reprogramming, lymphocytes, macrophages, inflammation, precision medicine, Journal of Translational Medicine

The research team, led by Antonio Esposito and Marcello Moccia of Federico II University of Naples, followed 34 adults with multiple sclerosis who started ofatumumab and remained on treatment for at least two years, with paired immune assessments at baseline and follow-up. Ofatumumab is administered as 20 milligram subcutaneous injections at weeks 0, 1, and 2, and monthly thereafter. Unlike intravenous anti-CD20 agents such as ocrelizumab and rituximab, ofatumumab acts primarily in the peripheral lymphatic compartment, and its distinct epitope binding and complement-dependent cytotoxicity have fueled speculation that its broader immunological footprint might differ from its intravenous cousins.

To map that footprint, the investigators used a standardized whole-blood flow-cytometry workflow. Fifty-microliter blood samples were incubated with fluorochrome-conjugated antibody mixtures, red blood cells were lysed, and the remaining nucleated cells were acquired on a Beckman Coulter Navios cytometer equipped with 405-, 488-, and 638-nanometer lasers. Sequential gating identified the major lymphocyte lineages: CD3-positive T cells and their CD4 and CD8 subsets, CD19- and CD20-positive B cells, CD56-positive natural killer cells, CD27-positive populations, memory B cells carrying both CD27 and CD19, and the small CD3-positive CD20-positive T-cell subset that anti-CD20 therapy is known to eliminate. Absolute counts were obtained using a double-platform approach under routine quality-control standards, including instrument calibration and participation in the UK-NEQAS external quality assessment scheme.

The longitudinal analysis relied on linear mixed-effects regression, with fixed effects for age, sex, follow-up duration, comorbidities, body mass index, and previous disease-modifying therapy, and a random intercept for each participant. The results were striking. Over roughly two years of treatment, total lymphocyte counts rose by an average of about 251 cells per microliter, while CD3-positive T cells increased by roughly 369, CD4-positive T cells by about 240, CD8-positive T cells by about 132, CD27-positive cells by about 275, and CD27-positive CD3-positive T cells by about 452. All of these increases were statistically significant, with confidence intervals that excluded the null. In parallel, the expected depletion was unmistakable: CD19-positive and CD20-positive B cells fell by about 182 cells per microliter, and CD27-positive CD19-positive memory B cells dropped sharply as well.

Not everything moved, however. The ratio of CD4 to CD8 T cells remained stable, as did CD56-positive natural killer cells and the CD3-positive CD20-positive T-cell subset. That stability of the CD4-to-CD8 ratio is important, because it suggests that no major rebalancing occurred between the two broad arms of the T-cell compartment, even as absolute T-cell numbers climbed. The authors are careful to note that the rise in CD27-positive cells cannot be taken as evidence of naive T-cell expansion. CD27 is expressed across both naive and central memory T-cell compartments and also appears on subsets of natural killer and natural killer T cells. Without additional differentiation markers such as CD45RA, CD45RO, and CCR7, the specific CD27-expressing population driving the increase cannot be resolved with the panel used.

What, then, explains the T-cell rise? The authors propose that the pattern may reflect broad reorganization of the T-cell compartment following sustained B-cell depletion, a phenomenon that has been hinted at in other anti-CD20 studies. Previous short-term real-world investigations of ofatumumab generally found CD3, CD4, and CD8 counts to be broadly stable, which makes the two-year increases reported here particularly noteworthy. The discrepancy may be a matter of timing: early immune kinetics differ from the intermediate and long-term reorganization that unfolds as the immune system adapts to life without circulating CD20-positive B cells. Other variables complicate the picture, including prior exposure to therapies such as natalizumab or fingolimod, which reshape peripheral immune pools and trafficking patterns, and differences in measurement approaches, such as whether studies use surface-epitope or intracellular CD20 staining, the latter avoiding steric hindrance by therapeutic antibodies still circulating in the blood.

The study also looked for clinical meaning behind these immune shifts. Using multivariable logistic regression, the team tested whether the annualized percentage change in each laboratory measure predicted relapses, magnetic resonance imaging activity, progression on the Expanded Disability Status Scale, improvement on that scale, or the composite outcome of no evidence of disease activity, known as NEDA-3. The answer, in every case, was no. No significant associations emerged between changes in any lymphocyte population and any clinical or radiological outcome. Several models could not be reliably estimated at all because clinical and MRI events were so rare, a consequence of treating patients with a highly effective therapy, and because near-complete B-cell depletion left little variability to model.

The authors are refreshingly candid about what these negative findings do and do not mean. With only 34 participants and a low frequency of disease-activity events, the study was never powered to detect subtle immunological-clinical relationships, and the absence of statistical significance should not be read as evidence that such relationships do not exist. The analyses were explicitly designed to be hypothesis-generating rather than to establish mechanistic pathways or predictive biomarkers. Most participants had prior exposure to other disease-modifying therapies, and although previous treatment was included as a covariate, residual carry-over effects on immune composition cannot be excluded. There was also no parallel comparator group receiving ocrelizumab or rituximab, which limits direct inference about how ofatumumab’s subcutaneous route and pharmacology might differ from intravenous anti-CD20 agents, and no standardized intermediate sampling at six and twelve months to reconstruct the early-to-late kinetics of immune change.

Those limitations point directly toward the next generation of experiments. The immunophenotyping panel used here captured broad lymphocyte populations but could not resolve the smaller, functionally critical subsets that other work has implicated in anti-CD20 responses, including Th17 and Th17.1 cells, T follicular helper cells, and their regulatory counterparts. Cross-sectional research during ofatumumab treatment has documented improved Th17.1-to-regulatory-T-cell and T follicular helper-to-follicular regulatory T-cell ratios, reduced pro-inflammatory cytokine production, and impaired migration of residual CD20-positive T cells across an inflamed model of the blood-brain barrier. A multicenter comparison of ocrelizumab and ofatumumab found more pronounced reductions of B and CD8-positive cells with ocrelizumab, while total lymphocytes, CD4 cells, and natural killer cells remained similar between the two drugs. Functional readouts such as cytokine profiling, migration assays, standardized immunoglobulin tracking, and assessments of vaccine responses and infection risk would round out the safety picture.

For now, the study delivers a clear and reassuring headline finding: two years of ofatumumab produces sustained, near-complete depletion of circulating CD19- and CD20-positive B cells, exactly as its mechanism of action predicts, alongside a measurable and statistically robust expansion of broad T-cell compartments that remains clinically silent, at least as far as conventional outcome measures can detect. Whether that T-cell expansion represents a benign consequence of B-cell depletion, a compensatory homeostatic response, or a subtle repositioning of the immune system toward a more anti-inflammatory profile remains an open question. Answering it will require larger prospective cohorts, repeated longitudinal sampling, deeper immunophenotyping panels, and the functional assays that can translate cell counts into biological meaning. Until then, this two-year window into the immune life of ofatumumab-treated patients stands as a valuable benchmark for what long-term B-cell depletion actually looks like in the blood of people living with multiple sclerosis.

Subject of Research: Longitudinal immune profiling of lymphocyte subsets in multiple sclerosis patients treated with the anti-CD20 antibody ofatumumab

Article Title: Ofatumumab in multiple sclerosis: 2-year immune profiling and clinical correlates

Article References: Esposito, A., Corsaro, L., Cave, I. D., Capasso, F., Corsini, G., Matrone, G., Cerbone, V., Petracca, M., Carotenuto, A., Lanzillo, R., Scalia, G., Castaldo, G., Morra, V. B., & Moccia, M. (2026). Ofatumumab in multiple sclerosis: 2-year immune profiling and clinical correlates. Journal of Neurology, 273(10), Article 579. https://doi.org/10.1007/s00415-026-14088-2

Image Credits: AI Generated

DOI: 10.1007/s00415-026-14088-2

Keywords: multiple sclerosis, ofatumumab, anti-CD20, B-cell depletion, T cells, flow cytometry, immune profiling, lymphocytes, NEDA-3, clinical outcomes, immunotherapy, Journal of Neurology