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PubMed2026

Spatially Distinct Bone Marrow Sites Are Asymmetrically Impacted by Inflammatory Cardiovascular Disease.

Cardiovascular disease, a leading cause of mortality globally, is increasingly recognized to involve complex bone marrow-driven inflammatory mechanisms, yet the impact on spatially distinct bone marrow sites and comorbidities remains poorly understood. To address this, we developed MarrowMet, a methodology for whole-body, site-specific quantification of bone marrow activity. The approach involves intravenously injecting the metabolic tracer 18F-fluorodeoxyglucose (18F-FDG) in mice, followed by bone excision to quantify site-specific bone marrow activity, with values then superimposed on a whole-body mouse atlas. After establishing that 18F-FDG bone marrow uptake strongly correlated with inflammatory activity, we applied MarrowMet to map site-specific activation patterns across diverse cardiovascular pathologies, including mouse models of inflammatory atherosclerosis, acute ischemic events, acute respiratory distress syndrome, metabolic syndrome, and aging. MarrowMet guided the selection of bone marrow regions of interest for in-depth mass cytometric analyses, with the skull and sternum emerging as critical sites exhibiting distinct immune and metabolic profiles in cardiovascular disease. These results challenge the prevailing view that femoral marrow represents systemic activity. Together, this work lays a foundation for whole-body exploration of bone marrow heterogeneity, yielding critical insights into cardiovascular disease and associated inflammatory responses, and MarrowMet can be readily adopted to profile other immune mechanisms in a variety of pathologies, including cancer and autoimmune diseases.

(18)F-FDG↗

PubMed2025

Post-genome-wide association study dissects genetic vulnerability and risk gene expression of Sjögren's disease for cardiovascular disease.

OBJECTIVES: This study aims to clarify the genetic associations between Sjögren's Disease (SD) and cardiovascular disease (CVD) outcomes, and to conduct an in-depth exploration of specific pleiotropic susceptibility genes. METHODS: We performed two-sample and multivariable Mendelian randomization (MR) analysis to investigate the association between SD and the risk of ischemic heart disease (IHD) and stroke. Linkage disequilibrium score regression (LDSC) and Bayesian co-localization analyses were employed to assess the genetic associations between traits. Cross-phenotype analyses were employed to identify shared variants and genes, followed by a Transcriptome-Wide Association Study (TWAS) and Multi-marker Analysis of Genomic Annotation (MAGMA) based on Multi-Trait Analysis of GWAS (MTAG) results. To validate the pleiotropic genes, we further analyzed tissue-specific differentially expressed genes (DEGs) related to SD using RNA sequencing data. RESULTS: The two-sample and multivariable MR analyses revealed that SD confers a genetic vulnerability to IHD and stroke. LDSC and co-localization analyses indicated a strong genetic linkage between SD and CVDs. Cross-phenotype analyses identified 38 and 37 pleiotropic single nucleotide polymorphisms (SNPs) for SD-Stroke and SD-IHD, respectively, primarily located within the MHC class region on 6p21.32:33 loci. Additionally, TWAS and MAGMA analyses identified pleiotropic genes located outside the MHC regions-seven associated with stroke (UHRF1BP1, SNRPC, BLK, FAM167A, ARHGAP27, C8orf12, and PLEKHM1) and two associated with IHD (UHRF1BP1 and SNRPC). Proxy variants within these genes in SD suggested an increased causal risk for stroke or IHD. Co-localization analysis further reinforced that SD and stroke share significant SNPs within the loci of FAM167A, BLK, C8orf12, SNRPC, and UHRF1BP1. DEG analysis revealed a significant up-regulation of the identified genes in SD-specific tissues. CONCLUSIONS: SD appears genetically predisposed to an increased risk of CVDs. Moreover, this research not only identified pleiotropic genes shared between SD and CVDs, but also, for the first time, detected key gene expressions that elevate CVD risk in SD patients-findings that may offer promising therapeutic targets for patient management.

Humans↗

PubMed2023

Causal Associations of Sleep Apnea with Alzheimer's Disease and Cardiovascular Disease: a Bidirectional Mendelian Randomization Analysis.

BACKGROUND: Sleep apnea (SA) has been linked to an increased risk of dementia in numerous observational studies; whether this is driven by neurodegenerative, vascular or other mechanisms is not clear. We sought to examine the bidirectional causal relationships between SA, Alzheimer's disease (AD), coronary artery disease (CAD), and ischemic stroke using Mendelian randomization (MR). METHODS: Using summary statistics from four recent, large genome-wide association studies of SA (n=523,366), AD (n=64,437), CAD (n=1,165,690), and stroke (n=1,308,460), we conducted bidirectional two-sample MR analyses. Our primary analytic method was fixed-effects inverse variance weighted MR; diagnostics tests and sensitivity analyses were conducted to verify the robustness of the results. RESULTS: We identified a significant causal effect of SA on the risk of CAD (odds ratio (OR IVW ) =1.35 per log-odds increase in SA liability, 95% confidence interval (CI) =1.25-1.47) and stroke (OR IVW =1.13, 95% CI =1.01-1.25). These associations were somewhat attenuated after excluding single-nucleotide polymorphisms associated with body mass index (BMI) (OR IVW =1.26, 95% CI =1.15-1.39 for CAD risk; OR IVW =1.08, 95% CI =0.96-1.22 for stroke risk). SA was not causally associated with a higher risk of AD (OR IVW =1.14, 95% CI =0.91-1.43). We did not find causal effects of AD, CAD, or stroke on risk of SA. CONCLUSIONS: These results suggest that SA increased the risk of CAD, and the identified causal association with stroke risk may be confounded by BMI. Moreover, no causal effect of SA on AD risk was found. Future studies are warranted to investigate cardiovascular pathways between sleep disorders, including SA, and dementia.

Preprint↗

PubMed2026

Drug repurposing using transcriptomics: principles and unmet needs in cardiovascular disease.

Although cardiovascular disease is the leading cause of death globally, therapeutic development in this field is slow. Given the high cost of developing new drugs and running clinical trials for cardiovascular disease, repurposing of drugs with approved safety profiles is an attractive strategy for therapeutic development that can significantly reduce the time and cost investment before phase II clinical trials. In the era of "Omics," various new methods and several large databases have been developed to enable the use of transcriptomics data for drug repurposing. This review summarizes the principles and workflow of signature mapping, which forms the foundation of statistical models used for transcriptome-based drug repurposing. We highlight the features of different analysis pipelines and databases that have been developed for signature mapping. These analysis pipelines prioritize genes that are statistically important, an approach that fundamentally differs from the pharmacological approach of identifying disease-driving and therapeutically targetable pathways. Outcomes of signature mapping pipelines are sensitive to the quality of input data, and results are not always reproducible. Moreover, all widely used RNA-seq databases are derived from cancer research and lack high-quality molecular data for cardiovascular disease. These unmet needs call for interdisciplinary collaboration and large networks of cardiovascular research-oriented biobanks to create the databases needed for transcriptomic-based signature mapping for drug repurposing efforts.

Drug Repositioning↗

PubMed2025

Phenotypic and Genetic Associations Between Cardiovascular Disease Subtypes and Alzheimer's Disease.

BACKGROUND: Cardiovascular disease (CVD) and Alzheimer's disease (AD) are major public health concerns that share overlapping risk factors and potential mechanistic pathways. While vascular contributions to cognitive decline are well-documented, the specific relationships between AD and different CVD subtypes remain poorly understood. METHODS: We examined associations between AD and 11 CVD subtypes using logistic regression models in two large biobanks: the UK Biobank (n = 502,133) and the All of Us Research Program (n = 287,011). Models were adjusted for demographic, lifestyle, and clinical covariates. We also explored genetic overlap between AD and CVD traits through colocalization of significant single nucleotide polymorphisms (SNPs) (p < 5×10-8) using genome-wide association study (GWAS) data. RESULTS: Most CVD subtypes were significantly associated with AD in both cohorts. Hypotension had the strongest and most consistent association, followed by hypertension and cerebral infarction. Acute myocardial infarction was the only subtype not significantly linked to AD. Genetic analyses revealed shared loci between AD and CVD-related traits, particularly in regions near APOE, MAPT, and genes influencing myocardial structure and vascular function. CONCLUSIONS: This study identifies subtype-specific CVD associations with AD across two diverse cohorts and highlights shared genetic architecture underlying heart-brain interactions. These findings underscore the importance of vascular health in AD risk and suggest that certain CVD subtypes, especially hypotension, may play underrecognized roles in cognitive decline.

Alzheimer’s disease↗

PubMed2025

Epigenetic mechanisms underlying variation of IL-6, a well-established inflammation biomarker and risk factor for cardiovascular disease.

BACKGROUND AND AIMS: Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality worldwide, yet the underlying molecular mechanisms remain less understood. Chronic low-grade inflammation is a complex immune response contributing to the pathophysiology of cardiovascular disease. This response is signaled in part by interleukin-6 (IL-6), a pleiotropic, pro-inflammatory cytokine. Phenotypic variance in circulating IL-6 level may be explained in part by DNA methylation which is increasingly being associated with cardiovascular effects. METHODS: In this study we evaluated methylated DNA (CpG sites) associated with blood IL-6 levels across ∼4,400 ancestrally diverse individuals (81 % self-reported White; 9 % Black or African American, 8 % Hispanic or Latino/a, and 2 % Chinese American). RESULTS: We identified 178 CpG sites associated with IL-6 (p<0.05/∼395,000). Among the sites, cg04437762 is located within the transcription unit of IL6R, a current therapeutic target for inflammatory disease, and cg26692003 and cg00464927 were significant for IL6 and IL6ST trans-CpG-gene transcripts. Functional gene expression downstream of methylation identified cellular response to IL-6 and B-cell regulation and activation pathways. Four genes were linked with both a genetic component of cardiovascular disease and an IL-6 associated CpG site. Three CpG sites identified through Mendelian randomization analyses supported inference of a causal effect on IL-6 levels, including the LYN gene that regulates immune cell signaling and has been previously associated with atherosclerosis. CONCLUSIONS: Overall, we identified several novel IL-6-CpG sites and downstream pathways affected by methylation. Follow-up functional studies including the regulation of IL-6 would complement current knowledge of CVD pathophysiology and potential therapeutic targets.

Humans↗

PubMed2026

Multi-omic biomarkers in cardiovascular disease: Discovery to clinical translation.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, necessitating improved risk stratification and early detection strategies. Multiomics approaches that integrate genomics, transcriptomics, proteomics, metabolomics, and epigenomics offer unprecedented opportunities for biomarker discovery and precision medicine in cardiovascular care. This narrative review examines the current landscape of multiomics biomarkers for CVD, tracing their evolution from discovery to clinical translation. We synthesize evidence from recent studies evaluating the clinical utility of integrated omics approaches across diverse cardiovascular conditions, including atherosclerotic cardiovascular disease, heart failure, and atrial fibrillation. High-throughput proteomics has identified novel protein signatures that enhance cardiovascular risk prediction beyond traditional risk factors. Metabolomics has revealed pathway-specific biomarkers, including trimethylamine N-oxide and lipid species, associated with atherogenesis. Polygenic risk scores derived from genomic data demonstrate incremental value when combined with clinical risk scores. Multiomics biomarkers represent a transformative approach to cardiovascular risk assessment and disease management.

Humans↗

PubMed2026

Multiomics approaches to cardiovascular disease: technological innovations and clinical translation.

Cardiovascular diseases (CVDs) remain the leading cause of global morbidity and mortality, reflecting a persistent gap between clinical phenotyping and the molecular mechanisms that govern disease initiation, progression, and interindividual variability. Recent advances in emerging technologies have fundamentally reshaped cardiovascular physiology by enabling high-resolution, cross-layer profiling of the heart and vasculature across genomic, epigenomic, transcriptomic, proteomic, metabolomic, lipidomic, glycomic, and fluxomic layers, increasingly at single-cell and spatial resolution. These approaches reveal CVD as a coordinated, multilayered process driven by dynamic interactions among cell types, regulatory programs, and metabolic states, rather than isolated gene-level defects. In this review, we synthesize how emerging multiomic, computational, and functional genomic technologies are redefining the study of cardiovascular disease across molecular, cellular, and tissue levels. We highlight recent innovations in single-cell and spatial atlases, long-read sequencing, proteomics and metabolomics, integrative data modeling, and functional omics approaches, including genome-scale perturbation screens and single-cell perturbation frameworks. These platforms enable mechanistic dissection of regulatory circuits, distinguish primary disease drivers from secondary adaptations, and directly assess therapeutic reversibility, advancing the field beyond associative biomarker discovery toward mechanism-guided target prioritization. We further discuss key methodological and translational challenges accompanying high-dimensional cardiovascular data, including preanalytical variability, control selection, temporal misalignment across molecular layers, population diversity, and reference bias. By integrating technological innovation with computational rigor and functional validation, this review frames emerging omics-enabled strategies as a unified, physiologically grounded framework for translating molecular insight into clinically meaningful cardiovascular phenotypes and advancing precision cardiovascular medicine.

Humans↗

PubMed2026

State of Cardiovascular Disease and Stroke in Hispanic/Latino Adults in the United States: A Scientific Statement From the American Heart Association.

Cardiovascular disease became the leading cause of death among Hispanic individuals in the United States in 2022. Hispanic adults experience a disproportionate burden of cardiometabolic risk factors, including obesity, diabetes, and dyslipidemia. Hispanic populations are highly heterogeneous, with substantial variations in genetic ancestry and sociocultural influences that shape cardiovascular disease risk and outcomes. The "Hispanic paradox," describing lower cardiovascular disease mortality despite higher risk factor burden, is increasingly recognized as an oversimplification that does not apply uniformly across Hispanic heritage groups, sexes, or disease types. Disaggregated data reveal substantial differences in risk profiles and disease burden among Hispanic heritage groups, emphasizing the limitations of treating this population as a monolithic unit. Recent evidence demonstrates widening disparities in hypertension control, obesity, diabetes, and metabolic diseases among Hispanic populations, threatening this prior mortality advantage. Advancing cardiovascular and equitable health will require developing a deeper understanding of the unique drivers of cardiovascular disease within diverse Hispanic communities, addressing barriers such as language and insurance access, and implementing culturally tailored interventions and policies. This scientific statement summarizes current cardiovascular disease epidemiology in Hispanic populations, emphasizing heritage group variation and social and structural determinants of health, and presents strategies to improve prevention and healthcare delivery. Key priorities for advancing cardiovascular health in Hispanic adults include expanding disaggregated data collection, increasing representation in research, and ensuring equitable implementation of precision medicine approaches, including genomics, multi-omics, and artificial intelligence, while addressing environmental exposures, psychosocial stressors, and policy-related drivers of risk in order to achieve the American Heart Association's 2028 Impact Goals to advancing health and hope for everyone, everywhere.

AHA Scientific Statements↗

PubMed2010

Site-specific gene therapy for cardiovascular disease.

Gene therapy holds considerable promise for the treatment of cardiovascular disease and may provide novel therapeutic solutions for both genetic disorders and acquired pathophysiologies such as arteriosclerosis, heart failure and arrhythmias. Recombinant DNA technology and the sequencing of the human genome have made a plethora of candidate therapeutic genes available for cardiovascular diseases. However, progress in the field of gene therapy for cardiovascular disease has been modest; one of the key reasons for this limited progress is the lack of gene delivery systems for localizing gene therapy to specific sites to optimize transgene expression and efficacy. This review summarizes progress made toward the site-specific delivery of cardiovascular gene therapy and highlights selected promising novel approaches.

Animals↗

PubMed2026

Effect of Semaglutide on the Inflammatory Biomarker High-Sensitivity CRP in Patients With Established Cardiovascular Disease and Overweight or Obesity in SELECT: A Prespecified Secondary Analysis.

BACKGROUND: In SELECT (Semaglutide Effects on Heart Disease and Stroke in Patients With Overweight or Obesity), among 17 604 patients with known atherosclerotic cardiovascular disease and overweight or obesity, but not diabetes, randomization to the glucagon-like peptide-1 receptor agonist semaglutide significantly reduced the primary outcome of major adverse cardiovascular events (MACE; cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke) compared with placebo (mean follow-up, 39.8 months). Inflammation, as indicated by plasma hsCRP (high-sensitivity C-reactive protein) level, is implicated as a biomarker predicting cardiovascular risk in obesity and atherosclerotic cardiovascular disease. SELECT provides a unique opportunity to study the relationship among hsCRP, obesity, weight loss, and MACE outcomes in semaglutide versus placebo groups. METHODS: In this prespecified SELECT substudy, we evaluated whether baseline hsCRP levels predicted MACE risk and examined the relationships between changes in hsCRP levels and time to first MACE, baseline body weight, weight loss, and other clinical measures among treatment groups over time (104, 208 weeks) using multiple approaches, including Cox modeling. RESULTS: Baseline hsCRP level, which was similar in the semaglutide (geometric mean 1.96 mg/L) and placebo (geometric mean 1.91 mg/L) groups, was prognostic of future MACE. The risk of MACE increased across baseline hsCRP level <2, 2-<10, and ≥10 mg/L subgroups, including significant associations with cardiovascular and all-cause death. Semaglutide reduced hsCRP levels (-37.8% [104 weeks]) and risk of MACE across all hsCRP subgroups. Greater reductions in ratio-to-baseline hsCRP with semaglutide were associated with greater weight loss, but preceded major weight loss, evident by 4 and 8 weeks, and occurred among those without weight loss. Semaglutide-associated changes in hsCRP were independent of low-density lipoprotein cholesterol levels, statin use, and atherosclerotic cardiovascular disease entry criteria. hsCRP reductions were found to be prognostic of decreased risk of MACE. Modeling suggests decreased inflammation as contributing in part to the benefits seen with semaglutide in SELECT. CONCLUSIONS: In SELECT, hsCRP data at baseline and in response to treatment with semaglutide support inflammation as a potential prognostic factor associated with cardiovascular risk in these generally well-treated patients with atherosclerotic cardiovascular disease and overweight or obesity but not diabetes. These findings suggest that the MACE reduction observed with semaglutide versus placebo in SELECT may have partially involved a decrease in inflammation. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03574597.

Humans↗

PubMed2026

Dissecting the shared genetic architecture between migraine subtypes and cardiovascular diseases: a multi-layered genomic analysis.

BACKGROUND: Epidemiological studies have linked migraine to an increased risk of cardiovascular disease (CVD); however, the shared genetic basis and putative causal relationships between migraine subtypes and cardiovascular traits remain poorly understood. METHODS: Leveraging large-scale GWAS summary statistics for migraine phenotypes (overall migraine, migraine with aura [MA], and migraine without aura [MO]) from FinnGen R12, along with seven cardiovascular diseases from publicly available consortia, we conducted a multi-layered genetic analysis. This integrative framework encompassed genetic correlation [linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL)], cross-trait meta-analysis (CPASSOC and PLACO), Bayesian colocalization, summary-data-based Mendelian randomization (SMR) using GTEx v8 eQTL data, and bidirectional two-sample Mendelian randomization (MR). RESULTS: Significant genetic correlations were identified between migraine and multiple cardiovascular traits, with hypertension and coronary artery disease (CAD) showing the most robust associations. MA exhibited broader genetic overlap with cardiovascular diseases than MO, including a notably stronger correlation with ischemic stroke, whereas MO demonstrated a stronger correlation with hypertension. Cross-trait meta-analysis identified 160 pleiotropic loci across 17 of 21 trait pairs. Colocalization analysis confirmed 32 loci harboring shared causal variants, mapped to 13 candidate genes, of which 7 (PHACTR1, LRP1, SOX7, ABO, FHOD3, MEI1, XKR6) were further validated by SMR as exhibiting tissue-specific regulatory effects. Among these, PHACTR1 displayed the broadest pleiotropic profile across migraine phenotypes and vascular diseases. After MR-PRESSO outlier removal, bidirectional MR identified 10 MR-supported associations, two of which (genetic liability to hypertension on overall migraine, and CAD on MA) survived Bonferroni correction, all free of detectable horizontal pleiotropy. Genetic liability to hypertension was associated with increased migraine risk (OR = 1.90, 95% CI 1.25-2.90, P = 2.64 × 10⁻³), atherosclerotic diseases showed subtype-specific effects (inverse for MO, positive for MA), and, in the reverse direction, migraine was associated with increased ischemic stroke risk. CONCLUSIONS: This study provides a comprehensive and systematic characterization of the shared genetic architecture between migraine subtypes and cardiovascular diseases. By identifying pleiotropic genes and bidirectional putative causal relationships with subtype-specific patterns, our findings carry implications for the development of targeted therapeutics and subtype-specific cardiovascular risk stratification.

Humans↗

PubMed2025

Association of genetically proxied cancer-targeted drugs with cardiovascular diseases through Mendelian randomization analysis.

BACKGROUND: Cancer-targeted therapies are progressively pivotal in oncological care. Observational studies underscore the emergence of cancer therapy-related cardiovascular toxicity (CTR-CVT), impacting patient outcomes. We aimed to investigate the causal relationship between different types of cancer-targeted therapies and cardiovascular disease (CVD) outcomes through a two-sample Mendelian randomization (MR) study. METHODS: This genome-wide association study was conducted using a two-sample Mendelian randomization framework. Genetic instruments for drug target gene expression were extracted from the eQTLGen consortium (31684 individuals, 37 cohorts). Genome-wide association study (GWAS) summary statistics for 19 cardiovascular diseases were derived from the FinnGen database. Primary analysis was carried out using the summary-data-based MR (SMR) method, with sensitivity analysis for validation. Colocalization analysis identifies shared causal variants between exposure eQTLs and CVD-associated single-nucleotide polymorphisms (SNPs). RESULTS: Among the 39 drug target genes, 8 were identified with detectable cis-eQTLs and were subsequently validated through positive control analysis for further investigation. In the SMR and sensitivity analyses, genetically proxied VEGFA inhibition showed significantly strong association with stroke (odds ratio [OR] = 1.17, 95% confidence interval [CI] = 1.09-1.26, p = 1.33 × 10- 5). Additionally, the inhibition of FGFR1, FLT1, and MAP2K2 exhibited suggestive association with corresponding cardiovascular disease outcomes. Nevertheless, only VEGFA expression and stroke shared a causal variant (93.6%), whereas FGFR1, MAP2K2, and FLT1 did not share causal variants with corresponding cardiovascular diseases in the colocalization analysis. CONCLUSIONS: This genetic association study revealed evidence supporting the genetic association between the use of VEGFA inhibitors and increased stroke risk, highlighting the need for enhanced pharmacovigilance. These findings underscore the delicate balance between cardiovascular toxicity risk and the benefits of cancer-targeted therapy.

Humans↗

PubMed2026

Bridging genotype, phenotype, and clinical insight: the role of multi-omics in cardiovascular disease.

INTRODUCTION: It is increasingly evident that the multifactorial nature of cardiovascular disease requires the combination of different omics approaches for improving our mechanistic understanding, identifying novel drug targets, and developing accurate diagnostic, predictive, and prognostic biomarker panels. AREAS COVERED: We review the current state and the potential of multi-omics in cardiovascular disease, with a specific focus on plasma-, spatial-, and single-cell approaches. We discuss lipidomics as a genotype‑to‑phenotype bridge, the utility of remote longitudinal monitoring via microsampling/dried blood spots, and emerging clinical‑trial integrations of multi-omics approaches. We outline critical gaps in standardization and how to overcome these, pre‑analytical challenges and constraints that are often neglected, and data‑integration methods spanning from canonical correlation analysis to modern machine learning approaches. EXPERT OPINION: Multi‑omics can shape cardiovascular care by identifying drug targets in diseased tissue and by yielding small, usable biomarker panels.

Humans↗

PubMed2026

Process evaluation of a nurse-led transitional care model (Cardiolotse) within a randomized controlled trial aiming to improve care coordination for patients with cardiovascular diseases in Germany.

BACKGROUND: Patients with higher age suffering from cardiovascular disease discharged from hospital are at greater risk of readmission within 30 days. We evaluated an innovative care program providing post-discharge support and helping patients to navigate through the healthcare system. This paper reports the findings of the process evaluation of the randomized controlled trial Cardiolotse, a nurse-led transitional care model improving care coordination for patients with cardiovascular diseases in Germany. METHODS: A process evaluation, following the guidelines of the Medical Research Council (MRC) Framework, was performed. Semi-structured interviews with all relevant target groups were conducted to gain more insight about implementation processes. Questionnaires and medical records were used to explore mechanisms of impact and understand how change was produced in the intervention. Qualitative data were analysed using content analysis with deductive and inductive categories. Descriptive statistics and subgroup analyses were utilized to explore quantitative data. RESULTS: Overall, the designed training programme was perceived positively by the study nurses, so called Cardiolotsen (CLs). Patients receiving support by the CLs reported positive satisfaction ratings. Interactions between CLs and patients were reported as trustworthy and reliable. A total of approximately 12,500 contacts were made over the course of the intervention. However, changes in satisfaction scores between intervention and control groups in terms of medical treatment or the interaction between medical health providers involved in the treatment could not be determined. Furthermore, data suggested reach issues with respect to office-based physicians, as regular CL contact could not be achieved with 90% of the participating general practitioners and cardiologists. CONCLUSIONS: The CLs served as an important source of support for the participating patients throughout the intervention. At regular intervals, they checked a patient's health status and their adherence to therapies after discharge. However, the process evaluation identified cross-sectoral communication and information exchange between CLs and office-based physicians as an implementation challenge. TRIAL REGISTRATION: The study was retrospectively registered at German Clinical Trial Register, http://www.drks.de/DRKS00020424 (Trial Registration Number DRKS00020424) on 18 June 2020.

Humans↗

PubMed2025

Risk of Cardiovascular Disease Mortality in Patients With Diagnosed Cancer and Associated Genetic and Proteomic Mechanisms: A UK Biobank-Based Cohort Study.

BACKGROUND: Previous studies have identified a link between cancer and cardiovascular disease; however, the underlying genetic and proteomic mechanisms remain unclear. Therefore, this study aimed to investigate the association between cancer diagnosis and cardiovascular mortality and to explore the potential mechanisms involved. METHODS: A total of 379 944 participants without cardiovascular disease at baseline, including 65 047 individuals with cancer, were recruited from the UK Biobank database. The primary end point was cardiovascular death. Multivariate Cox regression was performed to evaluate the risk of cardiovascular death in populations with and without cancer. Genome-wide association studies, phenome-wide association studies, and proteomic analyses were applied to investigate the underlying genetic and proteomic mechanisms. RESULTS: Multivariate Cox regression analysis showed an increased risk of cardiovascular death in the group with cancer (hazard ratio, 1.50 [95% CI, 1.40-1.61]) after multivariable adjustment. Proteomic analysis confirmed a strong association between cancer and cardiovascular disease, primarily involving pathways related to complement and coagulation cascades, and various inflammatory processes. In contrast, genome-wide association studies and phenome-wide association studies revealed only a limited number of shared genetic variations between cancer and cardiovascular conditions, such as hypertension and cardiac dysrhythmias. CONCLUSIONS: Cardiovascular risk is increased in patients with cancer and may be related to altered expression of inflammation- and coagulation-related proteins. In clinical practice, it is recommended to emphasize the management of endocrine, kidney, and inflammation-related risk factors in the population with cancer.

Humans↗

PubMed2026

Genetic overlap between estimated glomerular filtration rate and cardiovascular disease identifies potential targets for cardiorenal syndrome.

Heart and kidney diseases frequently coexist, but the genetic basis of this relationship remains unclear. We analyzed genetic data from large-scale studies to investigate how kidney function (estimated glomerular filtration rate, eGFR) and six common cardiovascular diseases share genetic risk factors. Using MiXeR method, and conjunctional false discovery rate (conjFDR) to identify overlapping genetic regions, we found 478 shared genomic loci between eGFR and cardiovascular diseases. These shared genes are involved in tissue development and structure. We also identified 29 genes that could be targeted by existing medications approved by the US Food and Drug Administration, such as PRKAG2, PDE1A, and IGF1R. Among these, genetically predicted higher level of IGF1R expression is associated with a higher eGFR, which reflects good kidney function and is protective against cardiorenal diseases, such as atrial fibrillation, and myocardial infarction. These findings reveal genetic overlap between kidney function and cardiovascular diseases, highlighting potential targets for understanding and treating cardiorenal syndrome.

Humans↗

PubMed2026

RNA splicing and cardiovascular disease: a guide for cardiologists.

Alternative splicing (AS) is a fundamental RNA processing mechanism, which generates different RNA transcripts and consequently different protein isoforms from a single gene. This increases the diversity of proteins within an organism and can fine-tune biological processes. This review examines how cardiac-enriched RNA-binding proteins establish heart-specific splicing programs governing aspects of cardiac development, function, and disease. Developmentally, coordinated sarcomeric isoform switches underpin the foetal-to-adult transition and further isoform rewiring in ion channel and kinase genes determine electrophysiology and excitation-contraction coupling. AS contributes to the pathogenesis of several cardiomyopathies and emerging datasets suggest that pathological hypertrophy engages distinct splicing signatures compared with physiological hypertrophy. This review summarizes diagnostic and prognostic opportunities arising from bulk, long-read, and single-cell/nucleus transcriptomics, which resolve cell type-specific isoforms and disease-associated switches. Circulating RNA biomarkers (including splice ratios and circularRNAs) may signify myocardial remodelling and arrhythmic risk. Integrative approaches that link AS with proteomics and genomics improve variant interpretation, reveal previously unannotated protein isoforms, and enable tracking of disease progression and therapy response. Finally, an outline of therapeutic strategies to modulate AS in cardiovascular disease (CVD), including antisense oligonucleotides, small molecules, and genome-editing modalities (CRISPR, base, and prime editing), is provided. The major challenges that remain before splice-targeting therapeutics can be targeted to treat cardiovascular disease are highlighted. Lessons from neuromuscular indications establish clinical feasibility of splicing correction and motivate translation to cardiology. Together, mechanistic insight, biomarker development, and therapeutic innovation position RNA splicing as a tractable axis for precision cardiovascular medicine.

Humans↗