Open-label phase 4 trial evaluating nusinersen after onasemnogene abeparvovec in children with spinal muscular atrophy

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Abstract

BACKGROUND. Spinal muscular atrophy (SMA) is a rare genetic neuromuscular disease caused by deletions or mutations of the survival motor neuron 1 gene. Despite the availability of genetically-based treatments for SMA, functional impairments and weakness persist in treated symptomatic individuals. This study addresses whether additional treatment after gene transfer therapy could provide further clinical benefits. METHODS. Interim Day 302 findings are described from the phase 4 open-label RESPOND trial evaluating nusinersen in participants aged ≤ 36 months who had suboptimal clinical status following onasemnogene abeparvovec (OA) treatment, as determined by the investigator. RESULTS. Thirty-seven participants included in the interim analysis were symptomatic at the time of OA administration. Most (92%) had two survival motor neuron 2 gene copies. Age at first nusinersen dose (median [range]) was 9.1 (3–33) months for participants with two SMN2 copies and 34.2 (31–36) months for those with three SMN2 copies, while time from OA dose to first nusinersen dose (median [range]) was 6.3 (3–31) and 13.3 (10–22) months, respectively. Participants had elevated neurofilament light chain (NfL) levels and low compound muscle action potential (CMAP) amplitudes at baseline, suggesting active neurodegeneration and severe denervation at study entry. Improvements from baseline were observed across a range of outcomes at Day 302, including motor function outcomes (HINE-2 and CHOP-INTEND total score), achievement of independent sitting, NfL levels, CMAP, and investigator- and caregiver-reported outcomes. Mean NfL levels decreased rapidly from baseline to Day 183 and remained low at Day 302. Mean ulnar and peroneal CMAP amplitudes increased. No safety concerns were identified. CONCLUSION. Improvements in clinical and biomarker outcomes support the benefit of nusinersen treatment in infants and children with suboptimal clinical status following OA. TRIAL REGISTRATION. ClinicalTrials.gov ID, NCT04488133; EudraCT number, 2020-003492-18. FUNDING. This study was sponsored by Biogen (Cambridge, MA, USA).

Authors

Crystal M. Proud, Richard S. Finkel, Julie A. Parsons, Riccardo Masson, John F. Brandsema, Nancy L. Kuntz, Richard Foster, Wenjing Li, Ross Littauer, Jihee Sohn, Stephanie Fradette, Bora Youn, Angela D. Paradis

Statin-dependent and -independent pathways are associated with major adverse cardiovascular events in people with HIV

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Background. Statin therapy lowers the risk of major adverse cardiovascular events (MACE) among people with HIV (PWH). Residual risk pathways contributing to excess MACE beyond low-density lipoprotein cholesterol (LDL-C) are not well understood. Our objective was to evaluate the association of statin responsive and other inflammatory and metabolic pathways to MACE in the Randomized Trial to Prevent Vascular Events in HIV (REPRIEVE). Methods. Cox proportional hazards models were used to assess the relationship between MACE and proteomic measurements at study entry and year 2 adjusting for time-updated statin use and baseline 10-year atherosclerotic cardiovascular disease risk score. We built a machine learning (ML) model to predict MACE using baseline proteins values with significant associations. Results. In 765 individuals (age: 50.8±5.9 years, 82% males) among 7 proteins changing with statin vs. placebo, angiopoietin-related protein 3 (ANGPTL3) related most strongly to MACE (aHR: 2.31 per 2-fold higher levels; 95%CI: 1.11-4.80; p=0.03), such that lower levels of ANGPTL3 achieved with statin therapy were associated with lower MACE risk. Among 248 proteins not changing in response to statin therapy, 26 were associated with MACE at FDR<0.05. These proteins represented predominantly humoral immune response, leukocyte chemotaxis, and cytokine pathways. Our proteomic ML model achieved a 10-fold cross-validated c-index of 0.74±0.11 to predict MACE, improving on models using traditional risk prediction scores only (c-index: 0.61±0.18). Conclusions. ANGPTL3, as well as key inflammatory pathways may contribute to residual risk of MACE among PWH, beyond LDL-C. Trial registration. ClinicalTrials.gov: NCT02344290. Funding. NIH, Kowa, Gilead Sciences, ViiV.

Authors

Márton Kolossváry, Irini Sereti, Markella V. Zanni, Carl J. Fichtenbaum, Judith A Aberg, Gerald S. Bloomfield, Carlos D. Malvestutto, Judith S. Currier, Sarah M. Chu, Marissa R. Diggs, Alex B. Lu, Christopher deFilippi, Borek Foldyna, Sara McCallum, Craig A. Sponseller, Michael T. Lu, Pamela S. Douglas, Heather J. Ribaudo, Steven K. Grinspoon

A multi-omics recovery factor predicts long COVID in the IMPACC study

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Background. Following SARS-CoV-2 infection, ~10-35% of COVID-19 patients experience long COVID (LC), in which debilitating symptoms persist for at least three months. Elucidating biologic underpinnings of LC could identify therapeutic opportunities. Methods. We utilized machine learning methods on biologic analytes provided over 12-months after hospital discharge from >500 COVID-19 patients in the IMPACC cohort to identify a multi-omics “recovery factor”, trained on patient-reported physical function survey scores. Immune profiling data included PBMC transcriptomics, serum O-link and plasma proteomics, plasma metabolomics, and blood CyTOF protein levels. Recovery factor scores were tested for association with LC, disease severity, clinical parameters, and immune subset frequencies. Enrichment analyses identified biologic pathways associated with recovery factor scores. Results. LC participants had lower recovery factor scores compared to recovered participants. Recovery factor scores predicted LC as early as hospital admission, irrespective of acute COVID-19 severity. Biologic characterization revealed increased inflammatory mediators, elevated signatures of heme metabolism, and decreased androgenic steroids as predictive and ongoing biomarkers of LC. Lower recovery factor scores were associated with reduced lymphocyte and increased myeloid cell frequencies. The observed signatures are consistent with persistent inflammation driving anemia and stress erythropoiesis as major biologic underpinnings of LC. Conclusion. The multi-omics recovery factor identifies patients at risk of LC early after SARS-CoV-2 infection and reveals LC biomarkers and potential treatment targets. Trial Registration. ClinicalTrials.gov NCT04378777. Funding. This study was funded by NIH, NIAID and NSF.

Authors

Gisela Gabernet, Jessica Maciuch, Jeremy P. Gygi, John F. Moore, Annmarie Hoch, Caitlin Syphurs, Tianyi Chu, Naresh Doni Jayavelu, David B. Corry, Farrah Kheradmand, Lindsey R. Baden, Rafick-Pierre Sekaly, Grace A. McComsey, Elias K. Haddad, Charles B. Cairns, Nadine Rouphael, Ana Fernandez-Sesma, Viviana Simon, Jordan P. Metcalf, Nelson I. Agudelo Higuita, Catherine L. Hough, William B. Messer, Mark M. Davis, Kari C. Nadeau, Bali Pulendran, Monica Kraft, Chris Bime, Elaine F. Reed, Joanna Schaenman, David J. Erle, Carolyn S. Calfee, Mark A. Atkinson, Scott C. Brakenridge, Esther Melamed, Albert C. Shaw, David A. Hafler, Alison D. Augustine, Patrice M. Becker, Al Ozonoff, Steven E. Bosinger, Walter Eckalbar, Holden T. Maecker, Seunghee Kim-Schulze, Hanno Steen, Florian Krammer, Kerstin Westendorf, IMPACC Network, Bjoern Peters, Slim Fourati, Matthew C. Altman, Ofer Levy, Kinga K. Smolen, Ruth R. Montgomery, Joann Diray-Arce, Steven H. Kleinstein, Leying Guan, Lauren I.R. Ehrlich

Immune cell quantification of in situ inflammation partitions human lupus nephritis into mechanistic subtypes

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BACKGROUND. In human lupus nephritis (LuN), tubulointerstitial inflammation (TII) is prognostically more important than glomerular inflammation. However, a comprehensive understanding of both TII complexity and heterogeneity is lacking. METHODS. Herein, we used high-dimensional confocal microscopy, spatial transcriptomics and specialized computer vision techniques to quantify immune cell populations and localize these within normal and diseased renal cortex structures. With these tools, we compared LuN to renal allograft rejection (RAR) and normal kidney on 54 de-identified biopsies. RESULTS. In both LuN and RAR, the 33 characterized immune cell populations formed discrete subgroups whose constituents co-varied in prevalence across biopsies. In both diseases, these co-variant immune cell subgroups organized into the same unique niches. Therefore, inflammation could be resolved into trajectories representing the relative prevalence and density of cardinal immune cell members of each co-variant subgroup. Indeed, in any one biopsy, the inflammatory state could be characterized by quantifying constituent immune cell trajectories. Remarkably, LuN heterogeneity could be captured by quantifying a few myeloid immune cell trajectories while RAR was more complex with additional T cell trajectories. CONCLUSIONS. Our studies identify rules governing renal inflammation and thus provide an approach for resolving LuN into discrete mechanistic categories. FUNDING. NIH (U19 AI 082724 [MRC], R01 AI148705 [MRC and ASC]), Chan Zuckerberg Biohub (MRC) and Lupus Research Alliance (MRC)

Authors

Gabriel Casella, Madeleine S. Torcasso, Junting Ai, Thao P. Cao, Satoshi Hara, Michael S. Andrade, Deepjyoti Ghosh, Daming Shao, Anthony Chang, Kichul Ko, Anita S. Chong, Maryellen L. Giger, Marcus R. Clark

Localized high-risk prostate cancer harbors an androgen receptor activity-low subpopulation susceptible to HER2 inhibition

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BACKGROUND. Localized high-risk prostate cancer (PCa) often recurs despite neoadjuvant androgen deprivation therapy (ADT). We sought to identify baseline molecular programs that predict pathologic response and reveal targetable vulnerabilities. METHODS. We profiled 147 biopsy foci from 48 MRI-visible lesions in 37 patients before 6 months of ADT plus enzalutamide and radical prostatectomy. Residual cancer burden (RCB) at prostatectomy was the primary outcome. Analyses incorporated PTEN loss, TMPRSS2:ERG status, and HER2/androgen receptor (AR) immunohistochemistry on baseline and posttreatment tissues. Findings were evaluated in an external transcriptional cohort (n = 121) and by multiplex immunostaining in an independent cohort (n = 61). Functional assays tested enzalutamide-responsive enhancers near ERBB2 and sensitivity to HER2 inhibition. RESULTS. A baseline HER2-associated transcriptional program correlated with higher RCB and inversely with AR activity, independent of PTEN and ERG. Exceptional responders had lower HER2 protein in pretreatment biopsies. The inverse AR-HER2 relationship recurred across datasets and multiplex immunostaining, which revealed coexisting AR-high/HER2-low and HER2-high/AR-low subpopulations. Enzalutamide inhibited AR-mediated repression of ERBB2. HER2-high, AR-low cells present before therapy resisted ADT yet were sensitive to HER2 inhibitors; combining HER2 inhibitors with enzalutamide increased tumor cell killing. These findings were reproduced in the external cohort and orthogonal assays. CONCLUSION. Baseline HER2 activity marks intrinsic resistance to neoadjuvant ADT in localized high-risk PCa and identifies a preexisting, targetable AR-low subpopulation. HER2-directed therapy, alone or with AR blockade, warrants clinical evaluation. TRIAL REGISTRATION. ClinicalTrials.gov registration: NCT02430480. FUNDING. Prostate Cancer Foundation; Department of Defense Prostate Cancer Research Program; National Institutes of Health.

Authors

Scott Wilkinson, Anson T. Ku, Rosina T. Lis, Isaiah M. King, Daniel Low, Shana Y. Trostel, John R. Bright, Nicholas T. Terrigino, Anna Baj, Emily R. Summerbell, Kayla E. Heyward, Sumeyra Kartal, John M. Fenimore, Chennan Li, Cassandra Singler, BaoHan Vo, Caroline S. Jansen, Huihui Ye, Nichelle C. Whitlock, Stephanie A. Harmon, Nicole V. Carrabba, Rayann Atway, Ross Lake, David Y. Takeda, Haydn T. Kissick, Peter A. Pinto, Peter L. Choyke, Baris Turkbey, William L. Dahut, Fatima Karzai, Adam G. Sowalsky

Factors associated with resistance of HIV-1 reservoir viruses to neutralization by autologous IgG antibodies

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Antiretroviral therapy (ART) prevents HIV-1 replication but does not eliminate the latent reservoir, the source of viral rebound if treatment is stopped. Autologous neutralizing antibodies (aNAbs) can block in vitro outgrowth of a subset of reservoir viruses and therefore potentially affect viral rebound upon ART interruption. We investigated aNAbs in 31 people with HIV-1 (PWH) on ART. Participants fell into two groups based on a high or low fraction of aNAb-resistant reservoir isolates, with most isolates being aNAb-resistant (IC50 >100 μg/ml). Time on uninterrupted ART was associated with higher aNAb resistance. However, pharmacodynamic analysis predicted that many isolates would be partially inhibited at physiologic IgG concentrations, to the same degree as by single antiretroviral drugs. Steep dose-response curve slopes, an indication of cooperativity, were observed for the rare isolates that were very strongly inhibited (>5 logs) by aNAbs. Resistance to aNAbs was not fully explained by declining in aNAb titers and may be driven partially by ADCC-mediated elimination of infected cells carrying aNAb-sensitive viruses over long time intervals, leaving only aNAb-resistant viruses which can contribute to viral rebound.

Authors

Natalie F. McMyn, Joseph Varriale, Hanna W. S. Wu, Vivek Hariharan, Milica Moskovljevic, Toong Seng Tan, Jun Lai, Anushka Singhal, Kenneth Lynn, Karam Mounzer, Pablo Tebas, Luis J. Montaner, Rebecca Hoh, Xu G. Yu, Mathias Lichterfeld, Francesco R. Simonetti, Colin Kovacs, Steven G. Deeks, Janet M. Siliciano, Robert F. Siliciano

Reduced vaccine-induced germinal center outputs in inflammatory bowel disease patients treated with anti-TNF biologics

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Background: Anti-TNF biologics are widely used to treat patients with immune-mediated inflammatory diseases. In mouse models, the complete absence of TNF impairs germinal center (GC) responses. Less is known about the impact of anti-TNF therapy on specific immune responses in humans. Widespread vaccination against SARS-CoV-2 offered an unprecedented opportunity to investigate the effects of biological therapies on responses to specific immunization. Previous work demonstrated that inflammatory bowel disease (IBD) patients treated with anti-TNF biologics exhibit decreased Spike-specific antibody responses compared to IBD patients treated with anti-IL-12/23 or healthy controls, even after four doses of mRNA vaccine. Methods: Here we analyzed humoral responses to SARS-CoV-2 immunization using single-cell RNA-Sequencing and flow cytometry of Spike-specific memory B cells (MBC), as well as avidity measurements of plasma antibodies from IBD patients treated with anti-TNF or anti-IL-12/23 or from healthy controls. Results: We observed decreased somatic hypermutation in the B cell receptors of Spike-specific MBCs and decreased antigen-specific MBC accumulation following SARS-CoV-2 mRNA vaccination in anti-TNF treated IBD patients, compared to IBD patients treated with anti-IL-12/23 or healthy controls. This decreased somatic hypermutation in Spike-specific MBCs in anti-TNF treated patients correlated with decreased and delayed antibody affinity maturation and reduced neutralization activity. Conclusion: These data provide in vivo evidence that anti-TNF, but not anti-IL-12/23, therapy impairs the quantity and quality of antigen-specific GC outputs in humans. Funding: Juan and Stefania Speck (donation) and by Canadian Institutes of Health Research (CIHR)/COVID-Immunity Task Force (CITF) grants VR-1 172711, VS1-175545, GA2-177716, GA1-177703 and CIHR FDN 143301 &143350.

Authors

Michelle W. Cheung, Samantha Xu, Janna R. Shapiro, Freda Qi, Melanie Delgado-Brand, Karen Colwill, Roya Dayam, Ying Liu, Jenny Choi, Joanne M. Stempak, James M. Rini, Vinod Chandran, Mark S. Silverberg, Anne-Claude Gingras, Tania H. Watts

A predictive endocrine resistance index accurately stratifies luminal breast cancer treatment responders and non-responders

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BACKGROUND. Endocrine therapy (ET) with tamoxifen (TAM) or aromatase inhibitors (AI) is highly effective against hormone receptor (HR) positive early breast cancer (BC), but resistance remains a major challenge. The primary objectives of our study were to understand the underlying mechanisms of primary resistance and to identify potential biomarkers. METHODS. We selected >800 patients in three sub-cohorts (Discovery, N=364, matched pairs), Validation 1, N=270, Validation 2, N= 176) of the West German Study Group (WSG) Adjuvant Dynamic marker-Adjusted Personalized Therapy (ADAPT) trial who underwent short-term pre-operative TAM or AI treatment. Treatment response was assessed by immunohistochemical labeling of proliferating cells with Ki67 before and after ET. We performed comprehensive molecular profiling, including targeted next-generation sequencing (NGS) and DNA methylation analysis using EPIC arrays, on post-treatment tumor samples. RESULTS.TP53 mutations were strongly associated with primary resistance to both TAM and AI. In addition, we identified distinct DNA methylation patterns in resistant tumors, suggesting alterations in key signaling pathways and tumor microenvironment composition. Based on these findings and patient age, we developed the Predictive Endocrine ResistanCe Index (PERCI). PERCI accurately stratified responders and non-responders in both treatment groups in all three sub-cohorts and predicted progression-free survival in an external validation cohort and in the combined sub-cohorts. CONCLUSION. Our results highlight the potential of PERCI to guide personalized endocrine therapy and improve patient outcomes. TRIAL REGISTRATION. WSG-ADAPT, ClinicalTrials.gov NCT01779206, Registered 2013-01-25, retrospectively registered.

Authors

Guokun Zhang, Vindi Jurinovic, Stephan Bartels, Matthias Christgen, Henriette Christgen, Leonie Donata Kandt, Lidiya Mishieva, Hua Ni, Mieke Raap, Janin Klein, Anna-Lena Katzke, Winfried Hofmann, Doris Steinemann, Ronald E. Kates, Oleg Gluz, Monika Graeser, Sherko Kuemmel, Ulrike Nitz, Christoph Plass, Ulrich Lehmann, Christine zu Eulenburg, Ulrich Mansmann, Clarissa Gerhauser, Nadia Harbeck, Hans H. Kreipe

Integrative mapping of pre-existing influenza immune landscapes predicts vaccine response

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BACKGROUND. Predicting individual vaccine responses is a substantial public health challenge. We developed immunaut, an open-source, data-driven framework for systems vaccinologists to analyze and predict immunological outcomes across diverse vaccination settings, beyond traditional assessments. METHODS. Using a comprehensive live attenuated influenza vaccine (LAIV) dataset from 244 Gambian children, immunaut integrated pre- and post-vaccination humoral, mucosal, cellular, and transcriptomic data. Through advanced modeling, our framework provided a holistic, systems-level view of LAIV-induced immunity. RESULTS. The analysis identified three distinct immunophenotypic profiles driven by baseline immunity: (1) CD8 T-cell responders with strong pre-existing immunity boosting memory T-cell responses; (2) Mucosal responders with prior influenza A virus immunity developing robust mucosal IgA and subsequent influenza B virus seroconversion; and (3) Systemic, broad influenza A virus responders starting from immune naivety who mounted broad systemic antibody responses. Pathway analysis revealed how pre-existing immune landscapes and baseline features, such as mucosal preparedness and cellular support, quantitatively dictate vaccine outcomes. CONCLUSION. Our findings emphasize the power of integrative, predictive frameworks for advancing precision vaccinology. The immunaut framework is a valuable resource for deciphering vaccine response heterogeneity and can be applied to optimize immunization strategies across diverse populations and vaccine platforms. FUNDING. Wellcome Trust (110058/Z/15/Z); Bill & Melinda Gates Foundation (INV-004222); HIC-Vac consortium; NIAID (R21 AI151917); NIAID CEIRR Network (75N93021C00045).

Authors

Stephanie Hao, Ivan Tomic, Benjamin B. Lindsey, Ya Jankey Jagne, Katja Hoschler, Adam Meijer, Juan Manuel Carreño Quiroz, Philip Meade, Kaori Sano, Chikondi Peno, André G. Costa-Martins, Debby Bogaert, Beate Kampmann, Helder Nakaya, Florian Krammer, Thushan I. de Silva, Adriana Tomic

Blood-storage duration affects hematological and metabolic profiles in patients with sickle cell disease receiving transfusions

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Patients with sickle cell disease (SCD) frequently receive red blood cell (RBC) units stored near the end of their permissible storage life. To evaluate whether storage duration influences recipient metabolism, clinical chemistry and hematological parameters, we conducted a prospective, randomized, blinded trial comparing transfusions of RBC units stored for ≤10 days versus ≥30 days. Chronically transfused adults with SCD (N=24) received three consecutive outpatient transfusions with randomized-age RBCs, and blood samples from units and recipients were analyzed by metabolomics and clinical chemistry. Transfusion of short-stored units resulted in significantly higher circulating levels of 2,3-bisphosphoglycerate, an essential regulator of oxygen unloading, up to two weeks post-transfusion. Conversely, transfusions of long-stored RBCs were associated with lower hemoglobin and RBC increments, higher iron and transferrin saturation, pro-inflammatory cytokines and metabolites, oxidative stress and markers of renal dysfunction. Plasma and RBC metabolomic profiles revealed time- and storage-age-dependent alterations, particularly affecting glycolysis, purine, and sphingolipid metabolism. Transfusion of long-stored RBCs consistently worsened laboratory surrogates of oxygen delivery and RBC efficacy, and increased the circulating levels of immunomodulatory metabolites and pro-inflammatory cytokines. These findings highlight metabolic and hematologic advantages associated with transfusing fresher RBCs in adults with SCD, independent of immediate clinical outcomes.

Authors

Matthew S. Karafin, Abby L. Grier, Ross M. Fasano, Anton Ilich, David Wichlan, Ada Chang, Sonjile M. James, Hailly E. Butler, Oleg Kolupaev, Melissa C. Caughey, Daniel J Stephenson, Julie A. Reisz, Nigel S. Key, Joshua J. Field, Jane A. Little, Steven L. Spitalnik, Angelo D’Alessandro