Citations

Introduction: Co-stimulatory proteins are master regulators of the immune system. We identified the co-stimulatory CD40-CD40L dyad as a key driver of inflammation during atherosclerosis and have shown that CD40 and CD40L exert cell-type divergent functions. Hypothesis: CD40 is abundantly expressed on endothelial cells (EC) undergoing endothelial mesenchymal transition (EndMT). We hypothesize that EC CD40 drives atherosclerosis via EndMT. Methods: We analyzed scRNAseq data from human carotid plaques, performed multiplex IHC, and used human aortic endothelial cells (HAECs) for in vitro studies. A tamoxifen-inducible EC specific CD40 deficient atherosclerotic mouse model (cadherin5 (cdh5)ERT2-CD40 flfl -ApoE -/- ) was generated. Results: Besides its presence on immune cells, CD40 is expressed on endothelial cells in both human and mouse atherosclerotic plaques. Analysis of scRNAseq data of human carotid atherosclerotic plaques showed that CD40 is highly expressed in COL1A2/FN1 expressing endothelial cells (ECs), a subset undergoing EndMT. Multiplex staining revealed that CD40 colocalized with the EndMT markers αSMA, NOTCH3, TWIST and VCAM1 in human plaques. In vitro , stimulation of human arterial endothelial cells (HAECs) with CD40L resulted in an increase in the EndMT markers markers fibronectin, vimentin, sm22α, FSP1 and snail. Using phosphoproteomics, CD40L was found to decrease phosphorylation of the junctional integrity proteins CTNNA1 [S652; S655] and ARHGAP21 [S1383]. To investigate the endothelial-specific effects of CD40 in atherosclerosis, 8-week-old cdh5ERT2-CD40 flfl -ApoE -/- mice and their CD40 flfl -ApoE -/- littermate controls were treated with tamoxifen and fed a high cholesterol diet for 10 wks. Deletion of EC-CD40 resulted in a significant reduction in plaque size. This reduction was accompanied by a shift from fibrous cap atheromas (FCA) towards intimal xanthoma (IX) and pathological intimal thickening (PIT). Flow cytometry analysis of the spleen showed that CD40 deletion in ECs results in a significant decrease in CD8 and CD4 effector T cells. This decrease in CD8 and CD4 effector T cells was accompanied by a diminished activation status, shown by a decrease in CD69 + CD8 + CD62 - CD44 + T cells, CD40L + CD8 + CD62 - CD44 + T cells and CD40L + CD4 + CD62 - CD44 + T cells. These findings demonstrate that endothelial CD40 drives atherosclerosis by inducing EndMT-driven plaque inflammation.

Abstract Cancer outcomes vary widely between individual patients, each accumulating an irregular record of treatments, diagnoses, measurements, and complications. Current prognostic models reduce this complexity into a single snapshot, focus on narrow clinical settings, and rarely generalize across hospitals. Here we introduce Chronicle , an explainable transformer that learns from entire patient trajectories to predict diverse clinical outcomes throughout the disease course while capturing both short- and long-term temporal dependencies. Trained on 53.7 million longitudinal data points from 51,711 patients spanning 67 cancer types, Chronicle operates natively on irregular data without imputation and jointly predicts eight endpoints within a flexible framework adaptable to additional outcomes. Chronicle outperformed cross-sectional models for overall survival prediction (C-index 0.84 vs 0.76-0.79), stratified patients more accurately than established prognostic systems, including TNM stage, and predicted seven adverse event and transfusion endpoints (AUC 0.80-0.92). Applied without retraining to 69,341 patients in Germany, Switzerland, and the United States, Chronicle generalized across healthcare systems and improved further with local fine-tuning. Integrated explainability traced each risk update to patient-specific clinical factors, revealing distinct temporal persistence of prognostic information, with relevance half-lives ranging from weeks for therapies to nearly one year for baseline characteristics. These findings demonstrate that learning from hospital-wide patient trajectories enables interpretable and continuously updated predictions, providing a scalable framework to support individualized treatment decisions.

ABSTRACT Tissue‐resident memory T cells (TRMs) are a distinct memory T‐cell subset that permanently reside in tissues such as the skin. In chronic immune‐mediated dermatoses, including psoriasis, atopic dermatitis, and vitiligo, TRMs are implicated in site‐specific “disease memory,” contributing to persistence and relapse at previously affected sites. This review synthesizes emerging concepts on TRMs in chronic inflammatory skin diseases and discusses clinical and translational implications, including TRM‐targeted therapies. Original human, animal, or in vitro studies evaluating TRMs in the pathogenesis or persistence of dermatologic diseases were included. In psoriasis, CD8 + TRMs (CD69 + CD103 + ) persisted in clinically healed skin. For atopic dermatitis, both CD4 + and CD8 + TRMs are implicated in maintaining Th2/Th22 inflammation. In vitiligo, autoreactive CD8 + TRMs at lesional margins mediate melanocyte destruction. Across dermatological diseases, TRMs share three core features: persistence in previously affected skin after clinical resolution, rapid reactivation by diverse triggers (stress, autoantigens, allergens, or cytokines) leading to site‐specific recurrence, and relative resistance to conventional therapies. Together, these properties provide a unifying framework linking tissue immune memory to the chronic, relapsing nature of inflammatory skin diseases. However, the dominant TRM pathways vary by disease, reflecting differences in immune polarization and antigen specificity. Targeting TRMs represents a promising strategy for disease control and serves as a biomarker of residual disease or flare. image

Abstract Colony-stimulating factor 1 receptor-related adult-onset leukoencephalopathy with axonal spheroids and pigmented glia (CSF1R-ALSP) is a rare, fatal, autosomal-dominant neurodegenerative disorder caused by pathogenic CSF1R variants and characterized by progressive cognitive, neuropsychiatric, and motor dysfunction, white matter lesions on brain imaging, and white matter demyelination, swollen axons, and pigmented glial cells on pathology. Limited data regarding clinical, biofluid or radiological biomarkers of disease severity are available, and no clinical trial endpoints have yet been validated. The objectives of this first-of-its-kind, prospective, observational natural history study were to characterize the clinical trajectory of CSF1R-ALSP and to identify and evaluate key biomarkers and clinical endpoints indicative of disease severity and progression. ILLUMINATE (NCT05020743) was a multicentre, noninterventional natural history study of adults with CSF1R-ALSP and prodromal carriers of CSF1R variants. Participants were followed for up to 36 months, with clinical assessments, fluid biomarkers and volumetric MRI assessments of brain atrophy collected at screening and every 6 months. This study was terminated early (4 June 2025). The analyses reported here include data collected through 19 February 2025. Of 53 participants, 19 were prodromal and 34 were symptomatic (11 of whom had a history of haematopoietic stem cell transplant and 23 who did not). Mean participant age was 47.8 (standard deviation, 4.5) years, and 36.4% were female. Prodromal participants remained relatively stable over 36 months, with little change in neurological function, neurodegeneration biomarkers or radiological disease burden. Impaired neurological function, MRI characteristics of CSF1R-ALSP, and elevated NfL (neurofilament light chain; neurodegeneration biomarker) and GFAP (glial fibrillary acidic protein; astrogliosis biomarker) levels were more pronounced at baseline and often showed progression over time among symptomatic participants who had not previously received haematopoietic stem cell transplant compared with participants who had previously received haematopoietic stem cell transplant. Significant correlations were observed at baseline and longitudinally between MRI measures of brain atrophy and clinical outcome measures. Based on the fluid biomarkers, MRI measures, and clinical outcome assessments evaluated here, active neurodegeneration, widespread changes visualized on brain MRI, and impaired cognitive and motor function were observed in symptomatic patients with CSF1R-ALSP. The neurological impairment can be assessed using the Montreal Cognitive Assessment and Cortical Basal ganglia Functional Scale. Our data suggest that quantification of brain atrophy using MRI volumetry is a potential biomarker of disease severity and progression in CSF1R-ALSP. It is hoped that this report will contribute to the understanding of disease progression in CSF1R-ALSP and inform future drug development.

Abstract Background Spinocerebellar ataxia type 3 (SCA3), the most common autosomal dominant ataxia, is driven by the accumulation of polyglutamine‐expanded (polyQ) ATXN3 proteins. While promising as biomarkers, their longitudinal trajectories across multiple biofluids remain poorly defined. Objectives To quantify polyQ ATXN3 levels in cerebrospinal fluid (CSF), plasma, and urine within a comprehensive cohort, utilizing serial measurements to map protein dynamics. Methods We employed a validated immunoassay to quantify polyQ ATXN3 in 97 symptomatic and 13 presymptomatic SCA3 patients, correlating levels with clinical features, ancestry, disease status, and longitudinal progression. Results Asian participants exhibited lower plasma but elevated urinary polyQ ATXN3 levels relative to other ancestries. While CSF levels were higher in symptomatic patients at baseline, they showed a significant longitudinal decline. Conclusions PolyQ ATXN3 is a viable multi‐biofluid biomarker. Declining CSF levels likely reflect neurodegeneration, supporting its role in tracking progression and emphasizing the need for ancestry‐based adjustment in trials. © 2026 International Parkinson and Movement Disorder Society.

Abstract Background Lysosomal dysfunction plays a crucial role in the pathogenesis of Parkinson’s disease (PD), particularly among GBA1 mutation carriers. Beyond GBA1 , genes such as TMEM175 , SCARB2 , and CTSB identified in genome-wide association studies (GWAS) are also implicated in lysosomal pathways contributing to PD risk, although their functional effects in patients remain unclear. Proteins encoded by these lysosome-related genes have been explored as potential therapeutic targets in experimental models. Biomarker profiles, including clinical measures, α-syn seeding activity, lysosomal proteins, and sphingolipids, may facilitate patient stratification and support therapeutic monitoring in future clinical trials. Aim The aim of this study is to investigate the impact of genetic variants of three lysosomal-related genes ( TMEM175 , SCARB2 , and CTSB ) on biomarker profiles in PD with and without GBA1 variants. Cross-sectional data from two German cohorts: the Tuebingen Parkinson Cohort (TUEPAC) and the DESCRIBE PD cohort of the German Center for Neurodegenerative Diseases were used as explorative cohorts, and data from Accelerating Medicines Partnership® Parkinson’s Disease (AMP-PD) were used as a validation cohort. The ultimate goal is to provide new data for patient stratification based on genetics, which might serve as a readout for target engagement and treatment efficiency assessment. Methods Three cohorts were analyzed: TUEPAC, DESCRIBE PD, and AMP-PD. TUEPAC and DESCRIBE PD were combined into a single German discovery cohort (TUEPAC-DESCRIBE-PD), while AMP-PD served as an independent validation cohort. Within each cohort, for subgroup analyses, PD patients were classified as the overall PD cohort (PD all ), and further stratified by GBA1 mutation status into PD patients without GBA1 mutations (PD GBA1 _wildtype ), and PD patients carrying GBA1 mutations (PD GBA1 ). We evaluated cognitive and motor function, as well as depression using the Montreal Cognitive Assessment (MoCA), Unified Parkinson Disease Rating Scale-part I II (UPDRS III), and Beck Depression Inventory-II(BDI-II) scales. Analyzed biomarkers included CSF α-syn seeding activity using seed amplification assay (SAA), CSF lysosomal protein levels of lysosomal integral membrane protein 2 (LIMP2), also known as SCARB2, cathepsin B (CTSB) and lysosome-associated membrane protein 2 (LAMP2), blood-based enzyme activity of the lysosomal glucocerebrosidase (GCase), and CSF sphingolipid profiles. PD patients carrying risk alleles in TMEM175 , SCARB2 , and CTSB were compared to non-carriers. Results Genotype-phenotype correlation analysis in TUEPAC-DESCRIBE-PD and AMP-PD revealed: (1) In PD all , the TMEM175 p.M393T risk variant was nominally associated with decreased cognitive function when adjusted for GBA1 mutation status in TUEPAC-DESCRIBE-PD; this association could not be replicated, although a similar trend was observed in the slightly smaller, but multicentric AMP-PD cohort; TMEM175 p.M393T was not significantly associated with BDI-I I or UPDRS-III scores in either cohort. (2) In PD GBA1 _wildtype , GCase activity was significantly lower in PD patients with SCARB2 rs6812193 risk allele in TUEPAC-DESCRIBE-PD, while a similar but non-significant trend was observed in AMP-PD; (3) In PD all , CSF levels of CTSB were nominally lower in carriers of CTSB rs1293298 risk allele compared to carriers of CTSB rs1293298 protective allele in TUEPAC-DESCRIBE-PD; in PD GBA1 _wildtype , LAMP2 was significantly lower in carriers of CTSB rs1293298 risk allele compared to carriers of CTSB rs1293298 protective allele in TUEPAC-DESCRIBE-PD; (4) In PD all , TMEM175 p.M393T risk allele was nominally associated with altered sphingolipid profiles across both TUEPAC-DESCRIBE-PD and AMP-PD cohorts. Conclusion These findings demonstrate that genetic variants in lysosomal-related genes ( TMEM175 , SCARB2 , and CTSB ) have a functional impact on biomarker profiles in PD patients. Integrating genetic characterization with biochemical profiling provides a framework for patient stratification and may serve as a translational strategy to monitor target engagement and evaluate treatment efficacy in future clinical trials.

Abstract GNE myopathy (GNEM) is a neuromuscular disorder caused by biallelic mutations in the gene GNE , which encodes a bifunctional enzyme essential for the biosynthesis of sialic acid. Despite extensive characterization, no effective therapies or validated biomarkers exist, and the molecular mechanisms driving disease pathology remain poorly understood. This study identifies the proteoglycan serglycin as a preliminary candidate biomarker in GNEM and investigates the mechanisms underlying its dysregulation. Proteomic analysis of serum samples from GNEM patients revealed reduced circulating serglycin levels. In contrast, increased intracellular serglycin was observed in GNE knockout and GNEM patient iPSC-derived myoblasts, suggesting impaired secretion and/or degradation. To investigate the basis of this accumulation, intracellular trafficking and autophagic pathways were examined. Proteomic profiling from HEK GNE knockout cells revealed alterations in pathways involved in membrane trafficking, Golgi function, and glycoprotein processing, consistent with broader disruptions in the secretory system that may impair serglycin export and contribute to its intracellular retention. In GNEM iPSC-derived myoblasts, serglycin overlapped with LAMP1-positive lysosomal compartments and the ER-phagy receptor FAM134B, suggesting association with lysosomal and ER-phagy related pathways. Functional assays further indicated impaired autophagic flux in mutant cells. Together, these findings support a model in which combined defects in secretion and autophagic clearance contribute to intracellular serglycin accumulation and reduced circulating levels. This study identifies serglycin as a potential circulating biomarker for GNEM and highlights dysregulation of secretory and degradative pathways as converging features of disease pathology.

Summary Functional ex vivo assays using live tumor tissues have demonstrated strong predictive accuracy for response to immune checkpoint inhibitors (ICIs) but are not scalable, requiring manual processing of large resections collected at academic centers. Here, an ex vivo live tumor fragment (LTF) platform was developed using standard-of-care biopsies from 228 patients with suspected malignancy collected across prospective, multicenter observational trials and biobanks. Hierarchical clustering of ICI-mediated changes in cytokine production identified two groups: responders and nonresponders. A binary classifier (elive index) using 8 cytokines achieved an AUC of 0.99 for cluster prediction. elive index correctly predicted clinical benefit in 93% (26/28) of patients ( P = 3.2x10 -5 ) and accurately identified 83% (10/12) of objective responders. Critically, elive responders were identified among biomarker-negative patients, highlighting the platform as a scalable approach that complements existing companion diagnostics and expands the population of patients identified to benefit from ICI therapy.