Cell Research

Mainland China experienced multiple waves of COVID19 pandemic during 2020 2022, driven by emerging variants and changes in public health and social measures (PHSMs). We developed a hypergraph-based Susceptible Vaccinated Exposed Infectious Recovered Susceptible (SVEIRS) model to reconstruct epidemic dynamics across 31 provinces, capturing transmission heterogeneity associated with clustered contacts. We assessed key characteristics of transmission at national and provincial levels during four outbreak periods: initial, localized predelta, Delta, and widespread Omicron, which accounted for 96.7% of all infections. We found significant diversity in transmission contributions across cluster sizes, with a small fraction of larger clusters responsible for a disproportionate share of infections. Counterfactual analyses showed that reducing clustersize heterogeneity, while holding overall exposure constant, could have lowered national infections by 11.70 to 30.79%, with the largest effects during Omicron period. Ascertainment rates increased over time but remained spatially heterogeneous with a range: (14.40, 71.93)%. Population susceptibility declined following mass vaccination (to 42.49% in Aug 2021, nationally) and rebounded (to 89.89% in Nov 2022) due to waning immunity with variations across the provinces. Effective reproduction numbers displayed marked temporal and spatial variability, with higher estimates during Omicron. Overall, these results highlight critical role of group contact heterogeneity in shaping epidemic dynamics.

Osteoarthritis (OA) is a prevalent musculoskeletal disorder and a leading cause of global disability. Although meniscal damage is a major risk factor of OA pathogenesis, genetic regulatory studies have remained largely confined to articular cartilage. Here, we establish the first comprehensive expression quantitative trait locus (eQTL) map integrating whole-genome sequencing and bulk transcriptomics from human meniscus (n=112) and cartilage (n=113). Supported by single-nucleus multiomics (cartilage: 56,549 nuclei; meniscus: 34,343 nuclei), we uncovered highly tissue-specific genetic risk architectures. Colocalization with OA GWAS identified 27 meniscus-specific, 28 shared, and 20 cartilage-specific causal genes. Chromatin-informed fine-mapping and deconvolution elucidated distinct pathogenic mechanisms; notably, meniscus-specific signals converged on VEGFA via rare promoter variants and an enhancer in fibrochondrocyte progenitors, alongside a shared eQTL for CLEC18A. Exploratory analysis suggested candidate compounds to reverse pathogenic gene expression. Our findings underscore the meniscus as a distinct genetic driver, molecularly reinforcing OA as an entire joint organ failure.

Gene networks (GNs) encode diverse molecular relationships and are central to interpreting cellular function and disease. The heterogeneity of interaction types has led to computational methods specialized for particular network contexts. Large language models (LLMs) offer a unified, language-based formulation of GN inference by leveraging biological knowledge from large-scale text corpora, yet their effectiveness remains sensitive to prompt design. Here, we introduce Gene-Relation Adaptive Soft Prompt (GRASP), a parameter-efficient and trainable framework that conditions inference on each gene pair through only three virtual tokens. Using factorized gene-specific and relation-aware components, GRASP learns to map each pair's biological context into compact soft prompts that combine pair-specific signals with shared interaction patterns. Across diverse GN inference tasks, GRASP consistently outperforms alternative prompting strategies. It also shows a stronger ability to recover unannotated interactions from synthetic negative sets, suggesting its capacity to identify biologically meaningful relationships beyond existing databases. Together, these results establish GRASP as a scalable and generalizable prompting framework for LLM-based GN inference.

Background: Patient-ventilator synchrony, an essential prerequisite for non-invasive mechanical ventilation, requires an accurate matching of every phase of the respiration between patient and the ventilator. Methods: We developed a long short-term memory (LSTM)-based model that can predict the inspiratory and expiratory time of the patient. This model consisted of two hidden layers, each with eight LSTM units, and was trained using a dataset of approximately 27000 of 500-ms-long flow signals that captured both inspiratory and expiratory events. Results: The LSTM model achieved 97% accuracy and F1 score in the test data, and the average trigger error was less than 2.20%. In the first trial, 10 volunteers were enrolled. In "Compliance" mode, 78.6% of the triggering by the LSTM model was compatible with neuronal respiration, which was higher than Auto-Trak model (74.2%). Auto-Trak model performed marginally better in the modes of pressure support = 5 and 10 cmH2O. Considering the success in the first clinical trial, we further tested the models by including five patients with acute respiratory distress syndrome (ARDS). The LSTM model exhibited 60.6% of the triggering in the 33%-box, which is better than 49.0% of Auto-Trak model. And the PVI index of the LSTM model was significantly less than Auto-Trak model (36.5% vs 52.9%). Conclusions: Overall, the LSTM model performed comparable to, or even better than, Auto-Trak model in both latency and PVI index. While other mathematical models have been developed, our model was effectively embedded in the chip to control the triggering of ventilator. Trial registration: Approval Number: 2023ZDSYLL348-P01; Approval Date: 28/09/2023. Clinical Trial Registration Number: ChiCTR2500097446; Registration Date: 19/02/2025.

Neuronal migration is a vital process that positions billions of neurons to create a functional brain. To navigate the constrained microenvironments within the cortex, precise control over the nuclear mechanics in migrating neurons is indispensable. Here, we show that Lamin B1 (LB1) regulates neuronal migration by modulating nuclear deformability. Excess LB1 in neurons halted migration without altering laminar identity or overall gene expressions in vivo, while in vitro, it elevated nuclear stiffness and impaired neuronal motility in confined spaces. Moreover, mispositioned neurons resulted in electrophysiological defects in the brain. Computational modeling predicted a temporal relationship between nuclear deformation and enhanced migration velocity, which was validated experimentally through live imaging. Notably, cerebral organoid assays using iPS cells established from patients with LMNB1 duplication exhibited impaired neuronal migration in a human model. Collectively, these findings demonstrate that LB1 is a critical regulator of nuclear mechanics, ensuring the accurate spatiotemporal positioning of neurons.

Stroke-associated pneumonia (SAP) is a common, severe complication in acute ischemic stroke (AIS) patients receiving bridging therapy (intravenous thrombolysis + mechanical thrombectomy), worsening prognosis and increasing mortality. Current SAP prediction models rely heavily on subjective clinical factors, limiting accuracy. This study developed an interpretable machine learning (ML) model combining inflammatory biomarkers to stratify SAP risk in AIS patients undergoing bridging therapy. We retrospectively enrolled AIS patients who received bridging therapy, collected baseline clinical data and inflammatory biomarkers, and constructed ML models (including XGBoost, random forest) with SHAP analysis for interpretability. The model integrating inflammatory biomarkers achieved excellent predictive performance (AUC=0.XX, 95%CI: XX-XX), outperforming traditional clinical models. SHAP analysis identified key biomarkers driving SAP risk, enhancing model transparency. This interpretable ML model provides an objective, accurate tool for SAP risk stratification in AIS patients, helping clinicians identify high-risk individuals early and implement targeted interventions to improve outcomes.

Cervical spinal cord injury (SCI) causes profound and persistent loss of hand function, and effective neuromodulation strategies remain limited. We report the first-in-human implantation of a 32-contact cervical epidural paddle array in two individuals with severe chronic SCI. Individualized motor pool recruitment maps, derived from systematic bipolar and multipolar configurations, enabled person-specific stimulation parameters. Optimized stimulation restored volitional hand opening, closing and coordinated upper-limb movements that were previously unattainable. This approach achieved a >91% success rate in complex reach-grasp-lift-release sequences, supported by substantial gains in range of motion, grip, and pinch strength. Electrophysiological and kinematic analyses demonstrated parameter-dependent, selective recruitment of flexor and extensor motor pools. Personalized stimulation programs integrated with goal-directed activities enabled functional hand use in home and community settings, sustained over several months of continued autonomous use. These findings establish a mechanistically grounded and translational framework for restoring upper-limb function after chronic severe SCI.

COVID-19 has spread rapidly and caused a global pandemic making it one of the deadliest in history. Early identification of patients with coronavirus disease 2019 who may develop critical illness is of immense importance. Therefore, novel biomarkers were needed to identify patients who will suffer rapid disease progression to severe complications and death. Many treatments were adopted including the antiviral Remdesivir, the antiretroviral Lopinavir /Ritonavir and Tocilizumab. Our study aimed not only to specify high-risk factors and biomarkers of fatal outcome in hospitalized subjects with coronavirus but also to compare the efficacy of the three considered treatments to help clinicians better choose a therapeutic strategy and reduce mortality. We divided the population (n=711) into four main groups based according to the WHO ordinal severity scale. The percentage of mortality, in and out the hospital, the length of stay in the hospital, the pulmonary inflammatory lesion and its distribution, the SARS-CoV-2 IgM and IgG variations at admission, the inflammatory markers, the complete blood count, the coagulation factors and enzymes, proteins and electrolytes profile, glucose and lipid profile, and other relevant markers were measured. The significance of the observed variation was assessed by multivariate and ANOVA analyses. We succeeded to establish a novel predictive scoring model of disease progression based on a cohort of Lebanese hospitalized patients relying on the pulmonary inflammatory lesions, inflammation biomarkers such as LDH, D-Dimer, CRP, IL-6 and the lymphocyte count, the number of comorbidities and the age of the patient which all were significantly correlated with the illness severity showing best outcomes with immunomodulatory and anticoagulant treatments by the results. As top tier, Tocilizumab was more efficient than the two other treatments in non-severe cases but none of the used treatments was insanely effective alone to reduce mortality in severe cases.

PurposeIdiopathic hypogonadotropic hypogonadism (IHH) is characterized by impaired reproductive maturation, and approximately half of all cases lack an identified genetic cause. We investigated the genetic basis of IHH in two large cohorts to identify novel disease-causing genes. MethodsWe analyzed exome and genome sequencing data from 1,822 patients with IHH from two independent cohorts. Rare variants were filtered using pedigree-informed inheritance models. PLEKHA6 expression in the postmortem human hypothalamus were tested at the mRNA and protein level. Functional studies assessed kisspeptin secretion in cell-based assays. ResultsWe identified 18 distinct PLEKHA6 variants in 24 patients from 20 unrelated families (1.3% of cohort). Variants segregated with disease under autosomal recessive and autosomal dominant (with variable penetrance) inheritance patterns. PLEKHA6 was robustly expressed in the hypothalamus and showed clear colocalization with neurokinin B, which served as the marker for the GnRH pulse generator. Functional studies demonstrated that patient variants significantly impaired kisspeptin secretion. ConclusionPLEKHA6 is a novel IHH gene and the first reported regulator of kisspeptin secretion from the kisspeptin-neurokinin B-dynorphin (KNDy) neurons, which have recently been established as the GnRH pulse generator. These findings establish impaired kisspeptin release as a new disease mechanism in IHH and highlight the critical role of neuropeptide trafficking in reproductive function.

ELF4 is an ETS family transcription factor involved in immune regulation, and germline loss-of-function mutations in ELF4 have been known as deficiency in ELF4, X-linked (DEX). To date, ELF4-related disease has been exclusively associated with germline mutations. Here, we report a pediatric patient with recurrent mucocutaneous inflammation and periodic fever caused by a somatic truncating mutation in ELF4. By directly comparing ELF4-mutant and wild-type immune cells within the same individual using full-length single-cell RNA sequencing, we identified mutation-associated transcriptional alterations across multiple immune cell types. Pathway analyses revealed cell type-specific immune alterations, characterized by reduced antiviral and interferon-related signaling in NK cells and enhanced inflammatory pathways related to Th17 differentiation and inflammatory bowel disease in CD16 monocytes. This study expands the disease spectrum of ELF4 deficiency by identifying somatic truncation of ELF4 as a genetic mechanism underlying autoinflammatory diseases and biased immune programs.

Targeted protein degradation (TPD) is a therapeutic strategy to remove disease-causing proteins by routing them to the ubiquitin-proteasome, autophagy, or lysosme machineries. For instance, proteolysis-targeting chimeras (PROTACs) are synthetic hetero-bifunctional small molecules that simultaneously bind the target and an E3 ubiquitin ligase to drive ubiquitination and degradation by the proteasome. Despite considerable success, designing such molecules is challenging and the number of currently addressable ubiquitin E3 ligases is limited. Here we demonstrate hetero-bifunctional de novo designed proteins as alternatives for TPD to access more targets and ligases. First, we develop a stable and highly adaptable helix-turn-helix scaffold for presenting different binding sites. Next, we use computational protein design to incorporate and embellish hot-spot- binding sites to target BCL-xL, plus short linear motifs (SLiMs) for KLHL20 ligase recruitment. The resulting mono- and bi-functionalised proteins bind the targets in vitro, and the latter degrade BCL-xL in cells leading to apoptosis.

Obtaining novel antibodies against specific protein targets is a widely important yet experimentally laborious process. Meanwhile, computational methods for antibody design have been limited by low success rates that currently require resource-intensive screening. Here, we introduce Germinal, a broadly enabling generative pipeline that designs antibodies against specific epitopes with nanomolar binding affinities while requiring only low-n experimental testing. Our method co-optimizes antibody structure and sequence by integrating a structure predictor with an antibody-specific protein language model to perform de novo design of functional complementarity-determining regions (CDRs) onto a user-specified structural framework. When tested against four diverse protein targets, Germinal successfully designed functional antibodies across all targets and binder formats, testing only 43-101 designs for each antigen. Validated designs also exhibited robust expression in mammalian cells and high sequence and structural novelty. We provide open-source code and full computational and experimental protocols to facilitate wide adoption. Germinal represents a milestone in efficient, epitope-targeted de novo antibody design, with notable implications for the development of molecular tools and therapeutics.

Mitral valve prolapse (MVP) is the most common cause of primary mitral regurgitation and is associated with the development of malignant arrhythmias, often in the context of myocardial fibrosis. The genetic architecture of MVP, and whether there are genetic factors explaining why only some individuals with MVP have adverse outcomes, remains poorly understood. We performed a meta-analysis of genome-wide association studies (GWAS) for MVP encompassing 21,517 cases among a total sample size of over 2.2 million individuals. We discovered 89 genomic risk loci for MVP, of which 72 were novel findings. Prioritization of causal genes and pathways using epigenetic and transcriptomic data from mitral valve and extra-valvular tissues replicated known gene associations to MVP including those involved in TGF-{beta} signaling and extracellular matrix biology, but additionally emphasized a role in MVP for biological pathways relevant to cardiomyocyte biology. Accordingly, we identified several MVP risk loci with pleiotropy to cardiomyopathies, especially hypertrophic cardiomyopathy, and demonstrated a significant genetic correlation between MVP and hypertrophic cardiomyopathy. Finally, we interrogated snRNA-seq data in human papillary muscle tissue from two individuals with severe MVP, characterizing genes associated with both risk of papillary muscle fibrosis and MVP.

BackgroundPleuroparenchymal fibroelastosis (PPFE) is a rare, fibrotic lung disease with poor prognosis, usually affecting adults which most commonly occurs idiopathically. Biallelic pathogenic variants in DGUOK cause mitochondrial DNA (mtDNA) depletion syndrome, predominantly affecting infants with severe hepatic and neurological symptoms. Detailed description of pulmonary manifestations with late-onset presentation have not been reported. MethodsWe describe nine patients with PPFE and DGUOK-associated mitochondriopathy. Clinical, radiological, histopathological, and genetic data were systematically collected from all patients. Functional studies, single nucleus RNA sequencing (snRNAseq), immunofluorescence staining, transmission electron microscopy and respiratory chain enzyme activity assays were conducted on patient-derived fibroblasts, muscle or lung tissues. mtDNA content quantification was performed on whole genome sequencing (WGS) data. ResultsAll patients (ages 5-36) presented with progressive dyspnea, weight loss and some with spontaneous pneumothoraces. Chest computed tomography and lung biopsies showed features of PPFE. Biallelic pathogenic DGUOK variants were identified in all patients, seven of them carry an unreported intronic variant leading to mtDNA depletion. snRNAseq of lung tissue from four pediatric patients identified Aberrant Basaloid cells and intermediate cells as their precursor localized at the fibrotic edge. Mitochondrial alterations were identified by electron microscopy. ConclusionPPFE in children and young adults is associated with DGUOK-related mitochondriopathy. For the first time, we demonstrate Aberrant Basaloid cells in pediatric fibrotic lung tissue. Since pulmonary involvement may be underrecognized or misinterpreted and the clinical presentation may not always be typical of a mitochondriopathy, we recommend genetic testing in all patients with PPFE of unknown origin.

BackgroundWe explored the efficacy of AS01E-adjuvanted respiratory syncytial virus prefusion F protein-based vaccine (adjuvanted RSVPreF3) in subpopulations of participants with underlying medical conditions in the multi-country, phase 3 AReSVi-006 trial (conducted May/2021-May/2024). MethodsMedically stable [≥]60-year-olds were 1:1-randomised to receive one adjuvanted RSVPreF3 or placebo dose pre-RSV season 1. In exploratory post-hoc analyses in subgroups of participants with underlying conditions (including COPD, asthma, diabetes, obesity [BMI[≥]30 kg/m2]), we evaluated efficacy of one vaccine dose against RSV-related lower respiratory tract disease (RSV-LRTD), acute respiratory illness (RSV-ARI), and RSV-ARI-related complications (e.g., pneumonia, COPD/asthma exacerbation, cardiovascular events). We also evaluated (post-hoc) RSV-ARI-related systemic corticosteroid and antibiotics use in participants with COPD or asthma. ResultsThe efficacy analyses comprised 12,468 vaccine and 12,498 placebo recipients. Efficacy against RSV-LRTD over three RSV seasons was similar among participants with COPD (75.1%, 95% CI: 40.2-91.4), asthma (65.8%, 31.0-84.7), diabetes (69.8%, 37.5-87.1), and obesity (74.1%, 56.4-85.5) as in the overall study population (62.9%, 97.5% CI: 46.7-74.8). Efficacy was also observed against RSV-ARI in these subgroups. Efficacy against RSV-ARI-related complications was 74.4% (95% CI: 11.2-95.2) in participants with COPD and 60.8% (-9.9-88.7) in those with asthma. Among participants with COPD, 15.4% (1.9-45.4) of RSV-ARI episodes in vaccine vs 22.4% (12.5-35.3) in placebo recipients were treated with systemic corticosteroids, and 46.2% (19.2-74.9) vs 56.9% (43.2-69.8) with antibiotics. ConclusionsPost-hoc analyses of the AReSVi-006 trial suggest that adjuvanted RSVPreF3 may help prevent RSV-ARI, RSV-LRTD, and RSV-related complications in medically stable older adults with underlying medical conditions like COPD and asthma. Trial registrationClinicalTrials.gov: NCT04886596 SummaryPost-hoc analyses of the AReSVi-006 trial suggest that 1 dose of adjuvanted RSVPreF3 may help prevent RSV-related illness and complications over 3 consecutive RSV seasons in subgroups of [≥]60-year-olds with chronic medical conditions, e.g., COPD and asthma.

Tourette Syndrome and other tic disorders (TD) are common, highly heritable neurodevelopmental conditions with complex genetic architectures. We conducted a genome-wide association study of 13,247 TD cases and 536,217 European ancestry controls and identified six independent genome-wide significant loci, including a pleiotropic signal at 3p21 shared with attention-deficit/hyperactivity disorder, among other traits. Gene prioritization highlighted 20 genes, including PCDH9, HCN1, NCKIPSD, WDR6, DALRD3, and CELSR3. Integrative analyses provide genetic support for the role of cortico-striato-thalamo-cortical circuits in TD pathophysiology and further localize TD genetic risk to specific cell types, including dopamine D1- and D2-receptor-positive medium spiny neurons, cortical pyramidal neurons, and oligodendrocyte-lineage cells. We further demonstrate extensive genetic correlations with neurodevelopmental and psychiatric traits, but not with neurological disorders. These findings advance our understanding of the genetic basis of TD, pinpointing specific genes and cell types that drive pathophysiology and providing a foundation for future mechanistic studies.

Our understanding of human mucosal T cell clonotype distribution in health and disease has centered on immunodominant antigens. We performed single cell T cell receptor (TCR) and RNA sequencing as an untargeted approach to define distributions of T cell clonal groups in health and ulcerative colitis (UC) across 333,088 T cells in colon and peripheral blood. Healthy donor-specific TCR repertoires had limited blood-colon clonal sharing, which was highest in cytotoxic T effector memory (Tem) populations and lowest in regulatory T cells (Tregs), reflecting tissue-based compartmentalization. Within healthy colon, TCR repertoires showed high T cell clonal sharing independent of anatomic distance, associated with high intra-clonal phenotypic diversity. Colon cytotoxic and Th17 populations showed high dispersion across sites, while Tregs were compartmentalized. Clonal lineages dispersed across blood and colon upregulated trafficking markers, suggesting active movement between tissues, while those dispersed across colon sites upregulated residency markers, suggesting intra-colon repertoire sharing is mediated by long-term, slow moving clonal groups. In UC, Tregs were expanded across inflamed sites, and increased CD8 Tem clonal groups showed increased dispersion regardless of inflammation. These findings reveal principles of T cell clonal organization in the human colon during health and disease, identifying opposing patterns of clonal dispersion among Treg and Th17 clonal groups, high phenotypic diversity within dispersed clonal groups, and elevated cross-colon dispersion of CD8 Tem clonotypes in UC.

The transcription coregulator OCA-B promotes CD4+ T cell memory recall responses and autoimmunity. OCA-B T cell deletion prevents spontaneous type-1 diabetes (T1D) onset in non-obese diabetic (NOD) mice and blunts T1D in a subset of more aggressive models. However, the role of OCA-B in diabetes induced by treatment with immune checkpoint inhibitors (ICIs), and the role of OCA-B in the control of tumors with and without ICI treatment, has not been studied. Here we show that islet and pancreatic lymph node T cells from T1D individuals express measurable POU2AF1 mRNA. Deletion of OCA-B in T cells fully insulates 8-week-old non-obese diabetic (NOD) mice against ICI-induced diabetes and partially protects 12-week-old mice. Salivary and lacrimal gland infiltration and inflammation were also reduced. Protection was associated with a block in the differentiation of progenitor exhausted CD8+ T cells (TPEX) into terminally exhausted CD8+ T cells (TEX). We show that OCA-B T cell loss preserves anti-tumor immune responses following PD-1 blockade in different tumors and mouse strains. These findings point to a potential therapeutic window in which pharmaceuticals targeting OCA-B could be used to block the emergence of both spontaneous and ICI-induced autoimmunity while sparing anti-tumor immunity. We develop first-in-class small molecule inhibitors of Oct1/OCA-B transcription complexes and show that administration into NOD mice also blocks diabetes emergence following PD-1 blockade. These results identify OCA-B as a promising therapeutic target for the prevention of autoimmunity and immune-related adverse events (irAEs).

Background Higher levels of sedentary behaviour, such as leisure screen time (LST), and lower levels of physical activity are associated with diseases across multiple body systems which contribute to a large global health burden. Whether these associations are causal is unclear. The primary aim of this study is to investigate the causal effects of higher LST (given greater power) and, secondarily, lower moderate-to-vigorous intensity physical activity (MVPA), on a wide range of diseases in a hypothesis-free approach. Methods A two-sample Mendelian randomisation phenome-wide association study was conducted for the main analyses. Genetic single nucleotide polymorphisms (SNPs) were first selected as exposure genetic instruments for LST (hours of television watched per day; 117 SNPs) and MVPA (higher vs. lower; 18 SNPs) based on the genome-wide significant threshold (p < 5*10-8) from the largest relevant genome-wide association study (GWAS). For disease outcomes, we used summary results from FinnGen GWAS, including 1,719 diseases defined by hospital discharge International Classification of Diseases (ICD) codes in 453,733 European participants. For the main analyses, we used the inverse-variance weighting method with a Bonferroni corrected p-value of p [&le;] 3.47*10-4. Sensitivity analyses included Steiger filtering, MR-Egger and weighted median analyses, and data from UK Biobank were used to explore replication. Findings Genetically predicted higher LST was associated with increased risk of 87 (5.1% of the 1,719) diseases. Most of these diseases were in musculoskeletal and connective tissue (n=37), genitourinary (n=12) and respiratory (n=8) systems. Genetic liability to lower MVPA was associated with six diseases: three in musculoskeletal and connective tissue and genitourinary systems (with greater risk of these diseases also identified with higher LST), and three in respiratory and genitourinary systems. Sensitivity analyses largely supported the main analyses. Results replicated in UK Biobank, where data available. Conclusions Higher levels of sedentary behaviour, and lower levels of physical activity, causally increase the risk of diseases across multiple body systems, making them promising targets for reducing multimorbidity.

BackgroundNegative symptoms are core features of schizophrenia that relate strongly to functional impairment, yet interventions targeting these symptoms remain largely ineffective. Emerging theoretical work highlights how environmental factors may shape and maintain negative symptoms. Although racial disparities in schizophrenia diagnosis among Black Americans are well documented and linked to racial stress and psychosis, the impact of racial stress on negative symptoms has not been examined. This study provides an initial test of a novel theory proposing that racial stress - here measured by racial discrimination - influences negative symptom severity through exacerbation of negative cognitions about the self, particularly defeatist performance beliefs (DPB). Study DesignParticipants diagnosed with schizophrenia-spectrum disorder (SSD) (N = 208; 80 Black, 128 White) completed the Positive and Negative Syndrome Scale (PANSS), the Defeatist Beliefs Scale, and self-report measures of subjective racial and ethnic discrimination (Racial and Ethnic Minority Scale and General Ethnic Discrimination Scale). Relationships among variables were tested using linear regression and mediation analysis. Study ResultsBlack participants exhibited significantly greater total and experiential negative symptoms than White participants with no group difference in DPB. Racial discrimination explained 46% of the relationship between race and negative symptoms. Among Black participants, higher DPB were associated with greater negative symptom severity. Discrimination was positively related to both DPB and negative symptoms. DPB partially mediated the relationship between discrimination and negative symptoms. ConclusionsFindings suggest that racial stress contributes to negative symptom severity via defeatist beliefs among Black individuals, highlighting potential targets for culturally informed interventions.