Citations

Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood ( n = 6454) and lung ( n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank–derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.

Abstract Human genomic studies link reduced CUB domain-containing protein 1 (CDCP1) expression with myocardial recovery in heart failure. While CDCP1 regulates cardiac fibroblast proliferation in vitro, it’s in vivo role in cardiac fibrosis remains unclear. Using a Cdcp1 -knockout (KO) angiotensin II/phenylephrine mouse model, we show that Cdcp1 deletion reduces echocardiographic left ventricular mass, histologic cardiac fibrosis, and pro-fibrotic gene expression, along with decreased fibroblast activation and inflammatory markers. Spatial transcriptomics identified a pressure overload–expanded fibroblast subpopulation enriched for growth factor and TGF-β signaling (FB5), which was markedly attenuated in Cdcp1 -KO hearts, alongside reduction of a pro-inflammatory cardiomyocyte subtype (CM4). Complementary studies in human ventricular fibroblasts demonstrate that CDCP1 knockdown reduced extracellular matrix gene expression and collagen I deposition. These findings establish CDCP1 as a regulator of cardiac fibrotic remodeling in vivo and open avenues for its further investigation as a potential therapeutic target.

ABSTRACT Cataract is a leading cause of visual impairment worldwide, and its prevalence is increasing with population aging. The majority are age‐related cataracts (ARC), clinically classified into nuclear, cortical, and posterior subcapsular cataracts (PSC) by opacity location. Mechanisms of cataractogenesis remain incompletely understood. While cortical and nuclear cataracts are largely attributed to crystallin aggregation, such protein‐centric mechanisms fail to explain the early onset and axial location of PSC. Morphologically, PSC resembles posterior capsule opacification (PCO), a secondary cataract driven by epithelial–mesenchymal transition (EMT) of lens epithelial cells (LECs), suggesting LEC‐EMT may also contribute to PSC. Using clinically stratified human lens samples, we confirmed EMT marker expression across PSC subtypes. Transcriptomic profiling revealed that LECs, the lens's sole metabolically active cells, in age‐related PSC (ARC‐PSC), compared with age‐related nuclear cataract (ANC) and clear lenses, exhibit elevated EMT signatures tightly linked to senescence‐associated inflammatory signaling. Aqueous humor (AqH) profiling demonstrated a pro‐inflammatory milieu across PSC subtypes, with IL‐17A uniquely elevated in ARC‐PSC, consistent with transcriptomic findings. Integrated analyses support a model in which senescence functions as an upstream driver, whereby senescent LECs release SASP factors, including IL‐17A, that activate NF‐κB signaling to amplify inflammation, reinforce senescence, and drive EMT. In vitro, senolysis and IL‐17A blockade disrupted this loop, attenuating senescence‐ and EMT‐associated phenotypes. Collectively, our study demonstrates that senescent LECs sustain an IL‐17A–NF‐κB circuit that drives EMT and accelerates ARC‐PSC progression, positioning ARC‐PSC as a unique human context to study senescence‐induced epithelial remodeling in aging tissues.

Abstract Background Cardiomegaly is a clinically significant incidental finding on chest computed tomography (CT) associated with heart failure, arrhythmias, and sudden cardiac death. Qualitative radiologist assessment is variable, and automated AI tools may enable objective opportunistic cardiac volumetry. Purpose To evaluate whether AI-enabled total cardiac volume (TCVAI) derived from non-ECG-gated, non-contrast chest CT can identify cardiomegaly as defined by echocardiography. Materials and Methods This retrospective study included 307 consecutive patients (median age, 67 years; 56% male) who underwent non-contrast chest CT at a single center on 7 scanner types (4 vendors) and clinically indicated echocardiography within 31 days. A commercially available AI tool (AI-Rad Companion, Siemens Healthineers) automatically quantified TCVAI, indexed to body surface area (TCVAI/BSA). Echocardiography reports were reviewed for chamber dilation and left ventricular hypertrophy (LVH), collectively defined as cardiomegaly. Associations between TCVAI/BSA and echocardiographic findings were assessed using correlation, ordinal regression, and receiver operating characteristic (ROC). Interscan repeatability was evaluated in 248 patients with 544 repeat CT examinations. Prespecified sex-specific thresholds were tested in a temporally independent validation cohort of 50 patients. Results Median TCVAI was higher in patients with cardiomegaly than those without (1061.9 vs 798.4 mL; P < .001). TCVAI/BSA was associated with chamber dilation and LVH severity on univariate analysis and remained associated in multivariable ordinal models, except for right ventricular dilation. Discriminatory performance was fair to good, with area under the curve (AUC) 0.81 (95% CI, 0.75-0.87) in men and 0.77 (95% CI, 0.69-0.85) in women. Interscan repeatability was excellent (intraclass correlation coefficient [ICC]: 0.93). In independent validation, performance ranged from sensitivity 89.3%/specificity 27.3% at a high-sensitivity threshold to sensitivity 28.6%/specificity 100% at a high-specificity threshold. Conclusion AI-derived cardiac volume from routine chest CT shows fair to good performance for identifying echocardiography-defined cardiomegaly with high measurement repeatability, supporting a potential role for automated cardiac volumetry as an objective, opportunistic biomarker.

Abstract The phase 1/2 Intergroup study E4412 investigated checkpoint blockade with nivolumab (Nivo) and ipilimumab (Ipi) combined with the CD30 targeting antibody-drug conjugate brentuximab vedotin (BV) in relapsed/refractory classic Hodgkin lymphoma. A total of 147 patients aged ≥12 years were randomized between BV/Nivo and BV/Ipi/Nivo; 132 patients were included in the primary efficacy analysis. The complete response (CR) rate, was 64.7% (52.2, 75.9) for BV/Nivo and 70.3% (57.6, 81.1) for BV/Ipi/Nivo (1-sided P = .29). The median survival follow-up was 38.0 months (interquartile range, 32.6-48.1). Progression-free survival (PFS) did not significantly differ between the 2 arms (hazard ratio [HR], 0.78, confidence interval [CI], 0.39-1.57; 1-sided P = .24). Treatment-related grade 3+ toxicities in the adult cohort, excluding rash, were similar between both arms (38.5% BV/Nivo and 39.3% BV/Ipi/Nivo); there was a higher frequency of grade 3 rash with BV/Ipi/Nivo (24.6%) compared with BV/Nivo (9.2%). We compared PFS by stem cell transplantation (SCT) status in a planned before hoc comparison; 58 patients received SCT, and 36-month PFS (from SCT) was >90% for both arms. Sixty-six patients were progression free after the first scan and did not undergo SCT. The 36-month PFS was 73.0% (54.5, 85.0) for BV/Ipi/Nivo compared with 45.8% (26.3, 63.4) for BV/Nivo (HR, 0.45; CI, 0.19-1.08; 1-sided P = .03). The study did not meet its primary end point of superior CR rate for the triplet, but it supports the use of checkpoint antibody-drug conjugate induction prior to auto SCT, and there is an intriguing signal of disease control for patients wishing to defer or avoid SCT with the triplet of BV/Ipi/Nivo. This trial was registered at www.clinicaltrials.gov as NCT01896999.

This study uncovers a previously unrecognized role for NAV3 in TGF-β1-driven cardiac fibroblast activation. We show that NAV3 facilitates profibrotic remodeling through noncanonical signaling and cell cycle arrest, independently of SMAD2/3. These findings position NAV3 as a novel regulator of fibroblast phenotype and a potential modulator of cardiac fibrosis.

Abstract Background Risankizumab (RZB), a high-affinity humanised IgG1 monoclonal antibody targeting interleukin-23 p19, has demonstrated sustained efficacy, with a consistent safety profile supporting long-term use for patients (pts) with ulcerative colitis (UC).1-3 This interim analysis reports efficacy and safety through open-label extension (OLE) week (wks) 96 (3 years [yrs] of total maintenance) from the COMMAND OLE. Methods The OLE enrolled RZB-treated pts who completed the 52-wk maintenance substudies and/or responded to 12/24-wk induction therapy.1 All pts received subcutaneous RZB 180 mg (RZB180) starting at OLE wk 0, except those who received prior OLE RZB rescue therapy (1 RZB 1200 mg intravenous dose then RZB 360 mg [RZB360] every 8 wk) and continued RZB360 for 96 wks. Efficacy endpoints (clinical remission [CR] per Adapted Mayo Score [AMS], CR per Partial AMS [PAMS], corticosteroid-free CR per PAMS, clinical response per AMS, clinical response per PAMS, endoscopic improvement, and endoscopic remission) were assessed at OLE wks 0 and 96 and reported as observed (AO) prior to OLE RZB rescue therapy and nonresponder imputation (NRI), among the overall population and by inadequate response to advanced therapy (AT-IR vs non-AT-IR; data cutoff: 25Aug2025). The safety analysis included pts who received at least 1 dose of OLE RZB, with data presented as events/100 pt-yrs. Results At OLE wk 0, approximately 90% pts (N = 1003) completed the study visit; some differences were observed in the clinical characteristics of RZB180 and RZB360-treated pts, including mean AMS (2.0, 3.4); a numerically higher proportion of RZB360-pts were AT-IR (63.1%, 76.8%), and had an endoscopic score of ≥ 3 (12.1%, 31.1%). A lower proportion of RZB360-treated pts achieved CR per AMS (54.8%, 25.2%) at OLE wk 0, while a higher proportion of RZB360-treated pts received OLE rescue therapy (RZB180, 22.1%; RZB360, 34.5%). Efficacy rates remained stable at OLE wks 0 and 96 for CR per AMS; similar results were observed within each subgroup, AT-IR and non-AT-IR (Table 1). Numerically lower efficacy rates were observed in the AT-IR vs non-AT-IR pts at wk 96; efficacy was sustained through OLE wk 96 for all endpoints (AO, NRI; Table 1). Similar rates were observed for any adverse event (AE), severe AE, and serious AE in RZB180 and RZB360-treated pts. No new safety risks were identified in either treatment group (Table 2). Conclusion In the ongoing COMMAND OLE, sustained clinical and endoscopic benefit was observed in pts receiving up to 3 yrs of long-term RZB maintenance therapy, with numerically lower efficacy rates observed for AT-IR vs non-AT-IR vs pts. The long-term safety of RZB remains consistent with a favorable benefit-risk profile, supporting its long-term use in UC. References: 1.Louis E et al. JAMA. 2024;332:881-97. 2.Atreya R et al. J Crohn’s Colitis. 2025;19(S1):i108-i110. [Abstract]. 3.Panaccione R et. al. J Crohn’s and Colitis. 2025, 19(1):jjaf005. Conflict of interest: Atreya, Raja: RA has served as a speaker, or consultant, or received research grants from AbbVie, Abivax, AlfaSigma, Arena Pharmaceuticals, Astra-Zeneca, Biogen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Celltrion Healthcare, Dr Falk Pharma, Galapagos, Gilead, GlaxoSmithKline, InDex Pharmaceuticals, Johnson & Johnson, Lilly, Materia Prima, Merck Sharpe & Dohme, Pfizer, Roche Pharma, Takeda Pharma, Viatris. Louis, Edouard: Education and Reserach Grants for my department: Abbvie, Takeda, Johnson and Johnson, Pfizer, Fresenius-Kabi, Celltrion, EG pharma, Sandoz, Falk Personal Fees for conferences, advisory boards and consultancy: Abbvie, Takeda, Ferring, Pfizer, Johnson and Johnson, Lilly, Galapagos, Celltrion, Arena, BMS, Falk, Biokuris, Fresenius-Kabi, Thabor Loftus, Jr, Edward: Grant: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Genentech, Gilead, Janssen, Pfizer, Receptos, Robarts Clinical Trials, Takeda, Theravance, UCB. Personal Fees: AbbVie, Allergan, Amgen, Arena, Boehringer Ingelheim, Bristol-Myers Squibb, Calibr, Celgene, Celltrion, Eli Lilly, Genentech, Gilead, Iterative Scopes, Janssen, Ono Pharma, Pfizer, Sun Pharma, Takeda, UCB. Rubin, David T.: Grant support: Takeda Pharmaceuticals Consultant: Abbvie, Abivax SA, Altrubio, Athos Therapeutics, Inc, Bristol-Myers Squibb, Celltrion, Connect BioPharma, Eli Lilly & Co., Genentech (Roche) Inc., Iterative Health, Janssen Pharmaceuticals, Johnson & Johnson, Merck & Co., Mirador, Odyssey Therapeutics, Pfizer, Sanofi, Spyre, Takeda Pharmaceuticals, Vedanta Biosciences, and Ventyx. Dubinsky, Marla C: Personal Fees: Consultant or Advisory Board: Abbvie, Abivax, Astra Zeneca, BMS, Celltrion, Gilead, Genentech, Janssen, Johnson and Johnson, Lilly, Merck, Pfizer, Prometheus Biosciences, Sanofi, Spyre, Target RWE, Takeda Other: Shareholder, Co-founder, Board of Directors of Trellus Health Co-Founder Mi Test Health Hisamatsu, Tadakazu: Grant support: Mitsubishi Tanabe Pharma Corporation, EA pharma Co. Ltd., AbbVie, JIMRO Co. Ltd., Zeria Pharmaceutical Co. Ltd., Kyorin Pharmaceutical Co. Ltd., Takeda, Pfizer., Mochida, Boston Scientific Corporation, Kissei Pharmaceutical Co. Ltd. Consulting: Mitsubishi Tanabe Pharma Corporation, EA pharma Co. Ltd., AbbVie GK, Janssen Pharmaceutical K.K., Pfizer, Eli Lilly, Gilead Sciences, Bristol Myers Squibb, Abivax, MSD, Chugai. Lecture fee: Mitsubishi Tanabe Pharma Corporation, AbbVie GK, EA pharma Co. Ltd., Kyorin Pharmaceutical Co. Ltd., JIMRO Co., Janssen Pharmaceutical K.K., Mochida Pharmaceutical Co., Ltd., Takeda, Pfizer, Kissei Mambetsariev, Nurbek: Employee of AbbVie and may own stock and/or stock options. Kalabic, Jasmina: Employee of AbbVie and may own stock and/or stock options. Cheng, Peiyao: Employee of AbbVie and may own stock and/or stock options. Chen, Su: Employee of AbbVie and may own stock and/or stock options. O’Brien, Dan: Employee of AbbVie and may own stock and/or options. Morisset, Pierre: Employee of AbbVie and may own stock and/or stock options. Duan, W. Rachel: Employee of AbbVie and may own stock and/or stock options. Panaccione, Remo: Grant: Abbvie, Janssen, Pfizer, Takeda. Other: Consultant for: Abbott, AbbVie, Abbivax, Alimentiv (formerly Robarts), Amgen, AnaptysBio, Arena Pharmaceuticals, AstraZeneca, Biogen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Celltrion, Cosmos Pharmaceuticals, Eisai, Elan, Eli Lilly, Ferring, Galapagos, Fresenius Kabi, Genentech, Gilead Sciences, Glaxo-Smith Kline, JAMP Bio, Janssen, Merck, Mylan, Novartis, Oppilan Pharma, Organon, Pandion Pharma, Pendopharm, Pfizer, Progenity, Prometheus Biosciences, Protagonist Therapeutics, Roche, Sandoz, Satisfai Health, Shire, Sublimity Therapeutics, Spyre Therapeutics, Takeda Pharmaceuticals, Theravance Biopharma, Trellus, Union Biopharma, Viatris, Ventyx, UCB Speaker’s Fees for: AbbVie, Amgen, Arena Pharmaceuticals, Bristol-Myers Squibb, Celgene, Eli Lilly, Ferring, Fresenius Kabi, Gilead Sciences, Janssen, Merck, Organon, Pfizer, Roche, Sandoz, Shire, Takeda Pharmaceuticals Advisory Boards for: AbbVie, Alimentiv (formerly Robarts), Amgen, Arena Pharmaceuticals, AstraZeneca, Biogen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Ferring, Fresenius Kabi, Genentech, Gilead Sciences, Glaxo-Smith Kline, JAMP Bio, Janssen, Merck, Mylan, Novartis, Oppilan Pharma, Organon, Pandion Pharma, Pfizer, Progenity, Protagonist Therapeutics, Roche, SandozShire, Sublimity Therapeutics, Takeda Pharmaceuticals, Ventyx.

Background. Acute cellular rejection (ACR) remains a major cause of morbidity after heart transplantation despite advances in immunosuppression. Whole genome transcriptomic profiling offers a systems-based, unbiased approach to elucidate the molecular mechanisms underlying ACR. However, noninvasive, longitudinal biomarker assessments capable of capturing the temporal dynamics of rejection biology remain scarce. Methods. RNA sequencing of peripheral blood from heart transplant recipients before, during, and after ACR was compared with nonrejection controls. Pathway analysis was conducted using differentially expressed genes (DEGs), and a machine learning approach was applied to assess gene-based prediction of ACR. Results. A total of 235 rejection-specific significant DEGs and 863 postrejection DEGs (false discovery rate < 0.05) were identified. During ACR, DEGs were enriched for T-cell activation/differentiation, apoptosis, and B-cell receptor signaling pathways. By combining the 2 sets of DEGs, a panel of 71 common genes was identified that reflected the significant, longitudinal transcriptomic dynamics of ACR. In an elastic net machine learning–based classifier, DYNLL1 and SERF2 were identified as ACR predictive genes, and achieved a cross-validated area under the receiver operating characteristic curve of 0.63. Conclusions. Peripheral blood transcriptomics identify dynamic temporal responses in ACR including T- and B-cell pathways with potential ACR predictive genes that warrant further investigation.