Citations

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.

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.

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.

Abstract Alzheimer’s Disease (AD) 1 is a progressive neurodegenerative disorder with limited therapeutic options, driving interest in drug repurposing to accelerate treatment discovery. Drug repurposing has emerged as a promising strategy to accelerate therapeutic discovery by repositioning existing drugs for new clinical indications. Recent computational repurposing approaches, including knowledge graph reasoning, transcriptomic signature analysis, and integrative literature mining, have demonstrated strong predictive capabilities 2 . However, these methods often yield divergent drug rankings, which makes it difficult to decide which candidates to advance for experimental follow-up and results in substantial gaps between computational predictions and feasible in vivo validation 2 .To bridge this computational-experimental gap, we proposed an advanced prioritization framework leveraging large language models (LLMs). Our method systematically evaluated three state-of-the-art (SOTA) and representative computational methods (TxGNN 3 , Composition-based Graph Convolutional Network (CompGCN) 4 , and a regularized logistic regression (RLR) 5 , to analyze both their predictive performance and pharmaceutical class distributions. By integrating the strengths and divergences of these models, we generated a unified, streamlined list of 90 candidate drugs for further prioritization. We then utilized an LLM-based agent to perform evidence synthesis from biomedical literature abstracts for each candidate. This process mimics expert manual curation but significantly reduces human effort and time by efficiently distilling vast textual data into actionable insights. Applying consistent and transparent selection criteria, we obtained a refined and prioritized list of drug candidates suitable for subsequent in vivo experimental validation. The robustness and clinical relevance of our framework were validated using real-world data from Alzheimer’s patient cohorts, clinical trial registries, and expert pharmacological reviews. This comprehensive validation confirmed that our LLM-driven approach enhances efficiency, consistency, scalability, and generalizability. By integrating computational predictions with scalable evidence synthesis and multifaceted validation, our framework facilitated rapid and informed prioritization of repurposed drugs. Our framework can potentially accelerate the translational pathway toward viable AD therapeutics. Moreover, the versatility of our framework can also be applied to drug repurposing efforts for other diseases beyond AD.

Background: Cardiac fibrosis is a critical and independent driver of heart failure (HF), characterized by excessive extracellular matrix (ECM) deposition. Decreased CDCP1 (CUB domain-containing protein 1) expression has been associated with myocardial recovery in human genome wide association studies by attenuating PDGF-BB driven cardiac fibroblast proliferation with no effect on canonical TGF-beta mediated transdifferentiation in-vitro. In-vivo, Cdcp1 deletion significantly reduced cardiac fibrosis and dysfunction in an angiotensin II/phenylephrine-induced pressure overload mouse model. However, its upstream regulators and its downstream effects on molecular signaling pathways that modulate ECM remodeling are unknown. Hypothesis: CDCP1 promotes human cardiac fibroblast mediated ECM remodeling in the HF microenvironment. Methods: Human ventricular fibroblasts (HVF) were treated with PDGF-BB (20 ng/ml), TGF-β (10 ng/ml), or Angiotensin II (100 ng/ml) for 48 hours. CDCP1 knockdown (KD) was achieved through siRNA transfection. Gene expression analysis was performed using qRT-PCR and protein quantification by Western blot. Both intact HVF and decellularized ECM were immunostained for collagen 1 to evaluate for ECM compositional changes. Results: Individual and combination treatments with fibrotic stimuli significantly increased CDCP1 expression (Figure 1A-1B). CDCP1 KD resulted in reduction of key ECM markers COL1A1, CTGF, and LOX (Figure 1C) across all fibrotic stimuli . Immunostaining of HVF after treatment with fibrotic stimuli showed reduced collagen 1 production with CDCP1 KD (Figure 1D). Western blot analysis showed increased phosphorylation of Src (tyr416) with 6h of treatment with fibrotic stimuli which was nullified by silencing of CDCP1 (Figure 1E). Conclusion: Our findings demonstrate that CDCP1 is necessary for ECM synthesis and Src signaling across multiple profibrotic pathways. Selective targeting of CDCP1 to modulate Src signaling pathways could provide novel therapeutic avenues for HF and fibrosis treatment.

Background: Cardiac fibrosis is a central pathological process that leads to worse outcomes in various cardiomyopathies. Recent evidence shows that CDCP1 (CUB domain-containing protein 1) modulates myocardial recovery by attenuating human cardiac fibroblast (HCF) proliferation. This study investigates the hypothesis that selective targeting of the CDCP1 cleavage domain can mitigate fibroblast proliferation, thereby offering a novel therapeutic approach to reducing cardiac fibrosis. Methods: A high-throughput in silico screening was performed using the Enamine compound library, focusing on structural regions that include the cleavage and adjacent sites of CDCP1 . A total of 147 candidate compounds were prioritized based on docking scores and binding stability profiles. Selected compounds were subsequently evaluated in vitro using HCF cultures seeded at 3,000 cells/well in 96-well plates. Each compound was administered at 10 μM concentration, and cell proliferation and viability were assessed by time-lapse imaging in the Incucyte® system at 24 and 96 hours. All experiments were done in triplicate with appropriate DMSO vehicle controls. Results: Compound C3 significantly reduced HCF proliferation (Fig B) to 27.3±2.4% relative to DMSO controls (99.9±0.5%, P <0.001) at 96 hours. Detailed structural modeling indicated that C3 binds to the CDCP1 cleavage site (Fig C) with a favorable Glide XP docking score of -7.66 kcal/mol. The interaction is stabilized by hydrogen bonds with Lys365 and Cys374 (Fig D), and supplementary hydrophobic interactions between aromatic rings and aliphatic groups, which contribute to a strong inhibitory effect. Conclusion: Targeting the CDCP1 cleavage domain with compound C3 effectively diminishes HCF proliferation in vitro. Therefore, these results substantiate the therapeutic potential of CDCP1 inhibition in cardiac fibrosis. Ongoing in vivo studies will explore the translational relevance of these findings.

Cardiac fibrosis, a hallmark of heart failure and various cardiomyopathies, represents a complex pathological process that has long challenged therapeutic intervention. High-throughput omics technologies have begun revolutionizing our understanding of the molecular mechanisms driving cardiac fibrosis and are providing unprecedented insights into its heterogeneity and progression. This review provides a comprehensive analysis of how techniques—encompassing genomics, epigenomics, transcriptomics, proteomics, and metabolomics—are providing insight into our understanding of cardiac fibrosis. Genomic studies have identified novel genetic variants and regulatory networks associated with fibrosis susceptibility and progression, and single-cell transcriptomics has unveiled distinct cardiac fibroblast subpopulations with unique molecular signatures. Epigenomic profiling has revealed dynamic chromatin modifications controlling fibroblast activation states, and proteomic analyses have identified novel biomarkers and potential therapeutic targets. Metabolomic studies have uncovered important alterations in cardiac energetics and substrate utilization during fibrotic remodeling. The integration of these multi-omic data sets has led to the identification of previously unrecognized pathogenic mechanisms and potential therapeutic targets, including cell-type-specific interventions and metabolic modulators. We discuss how these advances are driving the development of precision medicine approaches for cardiac fibrosis while highlighting current challenges and future directions in translating multi-omic insights into effective therapeutic strategies. This review provides a systems-level perspective on cardiac fibrosis that may inform the development of more effective, personalized therapeutic approaches for heart failure and related cardiovascular diseases.

Background: Dilated Cardiomyopathy (DCM) is a major cause of heart failure (HF) and carries a high mortality rate. Drug treatment response for DCM-related HF patients is highly variable, with some patients having no response. A pharmacogenomic approach, genome-wide association study (GWAS) followed by biologically functional validation, can potentially identify genetic determinants of prognosis in DCM and might provide insight into novel biology of DCM pharmacotherapy. Methods: A GWAS was performed using DNA from 686 patients with recent onset DCM who were on standard HF therapy using change in left ventricular ejection fraction (LVEF) at a median of 6 months after initial diagnosis. Cultured human cardiac fibroblasts (HCFs) were used to functionally validate the GWAS findings in vitro . RNA-seq followed by pathway analysis after NAV3 knock-down (KD) using siRNA in HCFs were performed to explore potential biological mechanisms. Results: A genetic variant, rs11105445(G>A), identified from the GWAS, mapping to the neuron navigator 3 (NAV3) gene (rs11105445, p=2.37E-07; beta 2.74 ± 0.53) was associated with improvement in LVEF. Functional genomic experiments demonstrated that, both in LV tissue and in cultured fibroblasts, the minor allele A was associated with decreased transcription of NAV3 (pvalue: 0.0335 and 0.0432) suggesting that ↓NAV3 expression might be associated with improvement in LVEF. TGF-β1 can induce HCF transdifferentiation into myofibroblasts and we demonstrate that it also increases NAV3 expression. NAV3 KD which mimics the GWAS variant significantly suppressed TGF-β1 induced HCF transdifferentiation demonstrated by decreased expression of α-smooth muscle actin (ACTA2) and collagen I (COL1A1). RNA-seq after NAV3 KD followed by pathway analysis suggested that NAV3 exerted its effect by regulating ECM and cell cycle processes, especially G1/S transition. We demonstrate that NAV3 KD suppressed TGF-β1 induced G1/S arrest by regulating CDK4, CDK6 and INK4B (cyclin-dependent kinase inhibitor 2B/P15, CDK4 inhibitor). Conclusion: Decreased expression of NAV3 is associated with myocardial recovery in DCM, most likely due to its role in suppressing HCF differentiation by regulating TGF-β1 induced G1/S arrest. The role of NAV3 as a novel therapeutic target in DCM needs to be explored.

Background: CDCP1 has been associated with reverse remodeling in human dilated cardiomyopathy (DCM) mediating its effect by reducing cardiac fibrosis which has been demonstrated in-vitro using human cardiac fibroblasts (CF) and in-vivo histologically in mice. However, the role of and the molecular mechanisms by which CDCP1 attenuates cardiac fibrosis in-vivo is unknown. Methods: To characterize the transcriptomic profiles of CDCP1 in cardiac fibrosis, Cdcp1 KO FVB/NJ mice were generated, and implanted with osmotic minipumps containing angiotensin II and phenylephrine (Ang II/PE) or saline at age of 10 weeks. There were 4 experimental groups (6 mice each), Saline_WT, Saline_KO, AngII/PE_WT, and AngII/PE_KO. After 4 weeks of AngII/PE induction, mice were euthanized, RNA was extracted from their heart tissue followed by RNA-seq to explore transcriptomic profiles. Fibrosis was histologically determined using picosirius (PSR) staining and was quantified by percentage of fibrosis area. Results: Histological analysis demonstrated that Cdcp1 KO attenuated severe cardiac fibrosis by 32.7% determined by quantification of percentage of fibrosis area. When comparing the transcriptome-wide gene expression in WT mice hearts from Saline to AngII/PE induction, a total of 316 differentially expressed genes (DEGs) were identified ( Fig. 1A ). Expression of Nppb (encodes ProBNP), a marker for heart failure, was significantly upregulated. The most significantly upregulated DEG after AngII/PE induction was Crlf1 ( Fig. 1A ), a gene predominantly expressed in CF, consistent with previous findings. We next compared transcriptomic profiles of AngII/PE induction WT and Cdcp1 KO mice hearts, to explore the role of CDCP1 in cardiac fibrosis. A total of 163 DEGs were identified ( Fig. 1B ). Notably, Cdcp1 -mediated DEGs enriched GO Pathways associated with extracellular matrix organization (Biological Process) and collagen-containing extracellular matrix (Cellular Component) ( Figs. 1C, 1D ), pivotal processes in cardiac fibrosis. In addition, Cdcp1 KO resulted in several “top” DEGs (including Rnase1, Ccl7, Ccl12 Il21r , and Il6 ) which have known function in inflammation, suggesting that CDCP1 might attenuate cardiac fibrosis through immune regulation . Conclusion: Our findings underscore the pivotal role of CDCP1 in modulating cardiac fibrosis in-vivo, potentially through immune regulation. Targeting CDCP1 may offer promising therapeutic avenues for mitigating myocardial fibrosis.

Abstract Background Celiac disease (CeD) is a chronic autoimmune disorder triggered by the ingestion of gluten in persons with the genetic risk factors human leukocyte antigens (HLA)-DQ2 and DQ8. Diagnostic evaluation of patients with suspected CeD often includes serology tests for tissue transglutaminase (tTG) antibodies. While the presence of HLA-DQ2 or DQ8 is required for the initiation and development of CeD, the genetic risk associated with the various alleles is not equivalent. Previous studies in patients with normal total IgA demonstrated the risk gradients of various HLA-DQ2 and DQ8 heterodimers in CeD. However, the impact of both gene variants in IgA deficient patients has not been investigated. In this study, HLA-DQ2 and HLA-DQ8 as risk factors for tTG-IgG positivity in IgA deficient patients were evaluated. Methods Retrospective data was collected from a cohort of individuals (n=3,515) with IgA concentrations below the age-dependent reference interval with suspicion for CeD who were tested for HLA-DQ genotyping and tTG-IgG (reference interval &lt; 6 U/mL) at Mayo Clinic Laboratories. Total IgA was measured using quantitative nephelometry (Siemens BN™ II System); HLA typing was performed using the reverse SSO DNA typing assay (LABType SSO kits). tTG-IgG was determined by enzyme-linked immunosorbent assay (QUANTA Lite R h-tTG, Werfen Diagnostics) on the Dynex Agility System. The prevalence and frequency distribution of HLA-DQ2 and DQ8 haplotypes were determined and the odds ratio (OR) was calculated to evaluate the risk gradient for tTG-IgG positivity based on different HLA-DQ variants. Results Among IgA deficient patients, 58% (n=2,041) expressed HLA-DQ2 or DQ8 haplotypes. Relative to patients without permissive alleles, patients homozygous for HLA-DQ2.5 exhibited a significantly increased risk for tTG-IgG positivity (OR = 10.98, 95% CI: 6.56-18.18, p &lt; 0.001) while those homozygous for HLA-DQ2.2 and DQ8 did not (DQ2.2/DQ2.2_OR = 0.72, 95% CI: 0.04-3.44, p = 0.75; DQ8/DQ8_OR = 0.96, 95% CI: 0.05-4.64, p = 0.97). Patients heterozygous for HLA-DQ2.5 (DQ2.5/x) displayed a lower odds ratio relative to homozygous patients (OR = 3.31, 95% CI: 2.29-4.82, p &lt; 0.001); however, the risk for tTG-IgG positivity increased in the presence of HLA-DQ2.2 (DQ2.5/DQ2.2_OR = 7.59, 95% CI: 4.48-12.65, p &lt; 0.001) or HLA-DQ8 (DQ2.5/DQ8_OR = 6.26, 95% CI: 3.55-10.73, p &lt; 0.001) alleles. Conversely, in the absence of HLA-DQ2.5, HLA-DQ2.2 heterozygotes (DQ2.2/x_OR = 2.80, 95% CI: 1.77-4.39, p &lt; 0.001) and HLA-DQ8 heterozygotes (DQ8/x_OR = 0.99, 95% CI: 0.52-1.77, p = 0.99) displayed lower correlations with tTG-IgG positivity, suggesting a potential risk elevation for tTG-IgG positivity is associated with the combination of DQ2.5 and DQ2.2 or DQ8. Conclusions Our study indicates the risk gradient of HLA-DQ genes in IgA deficient patients. Overall, compared to patients without HLA-DQ2 or DQ8 haplotypes, the homozygous HLA-DQ2.5 genotype had the highest correlation with tTG-IgG positivity, followed by HLA-DQ2.5/DQ2.2 and HLA-DQ2.5/DQ8 heterodimers. The results suggest that HLA-DQ2.2 or HLA-DQ8 alone does not confer risk, but when in the presence of HLA-DQ2.5 these alleles may increase the risk for tTG-IgG positivity. Results from this study shed light on the risk of CeD in patients with IgA deficiency.