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PubMed2005

Genetic epidemiology in Germany--from biobanking to genetic statistics.

OBJECTIVES: Genetic epidemiology investigates the role of genetic factors and their interaction with environmental factors (in a broad meaning) for the occurrence of diseases in human populations. Its aim is to undestand the influence of genetics on the development of diseases, their course and the clinical implications, with the final goal to improve prevention, diagnostics and therapy. METHODS: Originally genetic epidemiology was understood as a specialized discipline with the main focus on family-based studies. The extraordinary development of genetics in the last decades--with respect of the understanding of the meaning of genes for human health, as well as by the availability of cost-effective high throughput methods in the lab, has opened enormous opportunities to study genetic factors. Now, genetic epidemiology and genetic statistics have a much broader application. In addition, access to large samples of patients or from the population is needed. This can be realized via biobanks. RESULTS: Large biobanks with 500,000 or more patients or participants from the general population are being established or planned in the UK, Japan or the US. However, in Germany only two smaller activities are ongoing, KORA-gen in the south and POPGEN in the north. Possibilities to reach larger numbers, based on existing cohorts or disease networks are discussed. Ethical boundary conditions have to be taken into account, which seem to improve due to the Opinion of the German National Ethics Council on Biobanks for Research. Furthermore, the activities of the German centers for Genetic Epidemiological Methods (GEMs) as research and support units for genetic statistics and epidemiological methodology are described. CONCLUSIONS: Genetic epidemiology is based strongly on interdisciplinary collaboration and includes basics of genetics, elements of molecular biology to identify genes, population genetics, clinical medicine, and methodological disciplines as epidemiology, biostatistics and bioinformatics. In Germany the situation for this type of patient-based research has recently improved due to the National Genome Research Network (NGFN).

Bioethics↗

PubMed2025

Whole-genome sequencing of 490,640 UK Biobank participants.

Whole-genome sequencing provides an unbiased and complete view of the human genome and enables the discovery of genetic variation without the technical limitations of other genotyping technologies. Here we report on whole-genome sequencing of 490,640 UK Biobank participants, building on previous genotyping effort1. This advance deepens our understanding of how genetics associates with disease biology and further enhances the value of this open resource for the study of human biology and health. Coupling this dataset with rich phenotypic data, we surveyed within- and cross-ancestry genomic associations and identified novel genetic and clinical insights. Although most associations with disease traits were primarily observed in individuals of European ancestries, strong or novel signals were also identified in individuals of African and Asian ancestries. With the improved ability to accurately genotype structural variants and exonic variation in both coding and UTR sequences, we strengthened and revealed novel insights relative to whole-exome sequencing2,3 analyses. This dataset, representing a large collection of whole-genome sequencing data that is available to the UK Biobank research community, will enable advances of our understanding of the human genome, facilitate the discovery of diagnostics and therapeutics with higher efficacy and improved safety profile, and enable precision medicine strategies with the potential to improve global health.

Humans↗

PubMed2026

Genome-wide association, polygenic risk scores, and machine learning for chronic post-surgical pain risk stratification: A UK biobank study.

Chronic post-surgical pain is a prevalent and debilitating complication following surgery, representing a clinical challenge. Despite the established heritability of pain phenotypes, large-scale genetic studies remain limited. This study aimed to identify genetic variants associated with chronic post-surgical pain, develop polygenic risk scores, and integrate these with clinical features for risk prediction. UK Biobank data from 47,836 participants (2490 cases and 45,346 controls) were split into training (80%; n = 38,268) and validation (20%; n = 9568) sets prior to analysis. A genome-wide association study was conducted on the training set only, across 19 million variants, and polygenic risk scores were constructed and integrated with clinical features in a logistic regression framework. Two close, rare, imputed signals crossed the genome-wide significance threshold but lacked local linkage-disequilibrium support, while 220 variants crossed the suggestive threshold. In the held-out validation set, cases had higher mean polygenic risk scores than controls (0.138 vs. -0.021; Cohen's d = 0.16, p < 0.001). A logistic regression model integrating clinical features and polygenic risk scores achieved an area under the curve of 0.639 (95% CI: 0.583-0.693), higher than models using either feature set alone. The polygenic risk score for chronic post-surgical pain was among the most important predictors. Risk stratification revealed the top quartile had 3.84-fold higher odds of chronic post-surgical pain than the bottom quartile (95% CI: 2.00-7.37). These findings suggest a possible modest genetic contribution to chronic post-surgical pain. Polygenic risk scores may complement clinical factors in surgical risk stratification. PERSPECTIVE: Chronic post-surgical pain may have a modest genetic contribution. This UK Biobank study identified over 220 variants at suggestive significance and constructed a polygenic risk score that was significantly elevated in cases. A combined clinical-genomic model achieved a 3.84-fold difference in odds across predicted-risk quartiles.

Chronic post-surgical pain↗

PubMed2025

A genome-wide association study of stroke risk in Asian statin users: evidence from KoGES and UK Biobank.

BACKGROUND: Despite proven efficacy of statins in stroke prevention, genetic factors may influence individual stroke risk among statin users. With increasing precision medicine approaches and growing evidence of population-specific genetic variations, identifying genetic markers that predict stroke risk in statin-treated Asian populations has become critically important for personalized cardiovascular prevention strategies. METHODS: We conducted a genome-wide association study of 1,678 participants using lipid-lowering agents in the Korean Genome and Epidemiology Study (KoGES) cohort. Significant findings were replicated in 2,170 Asian participants on statins from the UK Biobank using an additive genetic model adjusted for relevant covariates. RESULTS: In the discovery analysis, 83 single nucleotide polymorphisms were suggestively associated with stroke (p <1.0 × 10-5). Among these, 21 SNPs in the CDH13 gene were associated with increased stroke risk. The lead SNP, rs7201829, was significantly replicated in the UK Biobank (odds ratio: 2.29, p = 2.39 × 10-5). CONCLUSIONS: This study identified CDH13 as a significant genetic marker associated with stroke risk among Asian statin users. These findings provide the first genome-wide evidence for genetic determinants of stroke susceptibility during statin therapy, supporting the development of personalized prevention strategies in Asian populations.

Aged↗

PubMed2025

Diet Changes and Colorectal Cancer Risk in the UK Biobank.

BACKGROUND: Modifying dietary behaviors into healthier habits may attenuate the risk of colorectal cancer. This study aimed to investigate the association between dietary changes and the risk of colorectal cancer. METHODS: Following dietary recommendations for red and processed meat, fruit and vegetables, and alcohol consumption, we classified 50,640 participants into poor and good adherence groups in the UK Biobank. Changes in dietary habits were defined as stable poor, poor to good, good to poor, and stable to good adherences. A Cox proportional hazard model was used to examine the association between dietary changes and colorectal cancer risk. RESULTS: Women were more likely to follow dietary recommendations than men. After a median of 3.3 years from the latest follow-up, 8,328 (16.4%) participants followed an improved dietary habit and 5,808 (11.5%) participants had a worsened diet. Compared with men who stably consumed fruit and vegetables <5 servings/day, those who increased their consumption to ≥5 servings/day were related to colorectal cancer risk reduction [HR: 0.24 (0.09-0.63)]. However, the beneficial associations of increased fruit and vegetable consumption were not statistically significant in women [HR: 0.41 (0.11-1.56)]. CONCLUSIONS: Our findings support the evidence that increasing fruit and vegetable intake could serve as a beneficial strategy to mitigate colorectal cancer risk in men. IMPACT: Participants from the UK Biobank significantly changed their adherence to dietary recommendations during the follow-up. Increasing fruit and vegetable consumption was inversely associated with colorectal cancer risk among men.

Humans↗

PubMed2005

The right to withdraw consent to research on biobank samples.

Ethical guidelines commonly state that research subjects should have a right to withdraw consent to participate. According to the guidelines we have studied, this right applies also to research on biological samples. However, research conducted on human subjects themselves differs in important respects from research on biological samples. It is therefore not obvious that the same rights should be granted research participants in the two cases. This paper investigates arguments for and against granting a right to withdraw consent to research on biobank samples. We conclude that (1) there are no explicit arguments for such a right in the guidelines we have studied, (2) the arguments against such a right are inconclusive, (3) considerations of autonomy, privacy, personal integrity, and trust in medical research provide sufficient reasons for granting a right to withdraw consent to research on biobank samples, (4) in certain cases, research participants should be allowed to waive this right.

Biological Specimen Banks↗

PubMed2006

Do we need a uniform regulatory system for biobanks across Europe?

Within Europe, there is currently no uniform regulatory system that applies to human biobanks used for genetic research purposes. This has resulted in considerable variation in the national law that applies to the use of DNA samples, personal information and medical records in the countries across Europe. This could result in a situation where researchers collaborating across Europe may be operating unlawfully if they share research data and samples across borders where different laws are in operation. There are also concerns that the lack of standardised guidelines inhibits cooperation among researchers across Europe but also restricts the sharing of DNA samples and information across national borders, which is problematic for multinational companies and institutions carrying out collaborative research. Ultimately, the lack of a uniform regulatory system may have implications for the viability and long-term competitiveness of collaborative European research. The purpose of this paper is to discuss some of the preliminary issues that would need to be considered before such a regulatory system for biobanks could be developed within Europe.

Biological Specimen Banks↗

PubMed2004

Informed consent and biobanks: a population-based study of attitudes towards tissue donation for genetic research.

AIMS: The procurement and usage of tissue samples has begun receiving increasing legal and ethical attention. The authors' aim was to develop an empirically based understanding of public attitudes to the use of tissue for research. METHOD: A questionnaire was distributed to a randomized sample (n=1,000) of the population in the age group 18-85 in Västerbotten County, Sweden. RESULTS: The response rate was approximately 60%. There was a general acceptance of genetic research based on biobank material (71%) but, though it is often a prerequisite for tissue-based research, a majority (62%) would not allow researchers to examine their healthcare records without specific consent. A majority (66.8%) accepted surrogate decisions by research ethical committees; 48% of the respondents estimated that they would feel respected if they were notified each time a sample was used. When compared and ranked with other issues, informed consent was a principal concern to a minority (4%) only. Should research efforts generate information on future health risks, a majority (55%) would want to be told only if treatment was available. CONCLUSION: Though genetic research in bioethical debate is often viewed as a potential threat to the integrity of the donor, the confidentiality of medical records still seems to concern donors more. Research ethical committees have support in the majority of the population for some surrogate decisions. The current emphasis on the question of informed consent in policy making for biobank-based research does not seem to be reflected unambiguously in the concerns of the general public.

Adolescent↗

PubMed2026

Interactive exploration of biobank-scale ancestral recombination graphs with Lorax.

MOTIVATION: Ancestral Recombination Graphs (ARGs) provide a comprehensive representation of genetic ancestry and underpin analyses of natural selection, disease association, and population history. However, existing visualization tools are limited in scalability and interactivity, making ARGs difficult to explore at biobank scale. RESULTS: We introduce Lorax, a GPU-accelerated, web-native platform for real-time visualization of population-scale ARGs. Lorax integrates genomic position, coalescent time, local genealogy, and metadata, enabling interactive exploration of ancestry and variant inheritance in biobank-scale datasets. AVAILABILITY AND IMPLEMENTATION: Lorax is freely available as a live demo at https://lorax.ucsc.edu/ and as a Python package "lorax-arg" on PyPI. The source code and documentation are available on GitHub at https://github.com/pratikkatte/lorax.

Software↗

PubMed2005

Genetic research and donation of tissue samples to biobanks. What do potential sample donors in the Swedish general public think?

BACKGROUND: The aim of this study was to identify perceptions of the general public regarding research involving human tissues; to assess the public's willingness to donate samples to biobanks; and to identify factors associated with the willingness to donate samples. METHODS: Cross-sectional survey. Postal questionnaires to a random sample of the general public in Sweden, 18-80 years of age (n = 6000) in October 2002 (response rate 49.4%; n = 2928). RESULTS: A majority of the respondents had a positive attitude towards genetic research. Their trust in authorities' capability to evaluate the risks and benefits of genetic research varied. Individual university/hospital-based researchers received the greatest trust, while the county councils (health care providers), and the Swedish Parliament received the lowest trust. Most respondents (86.0%) would donate a linked blood sample for research purposes. Another 3.0% would provide an anonymous sample. In total, 78% of the respondents would agree to both donation and storage. The most common motive was benefit of future patients. The majority was indifferent to the funding source for the research and would delegate this judgment to the research ethics committee. After adjusting for covariates, those more likely to donate a sample were middle-aged, had children, had personal experience of genetic disease, were blood donors, had a positive attitude toward genetic research, and had trust in experts/institutions. CONCLUSIONS: The majority of the general public is willing to donate a sample to a biobank. The willingness is mainly driven by altruism, and depends on the public being well-informed and having trust in experts and institutions.

Adolescent↗

PubMed2026

Exome sequencing and large-scale analysis of electronic medical record-linked biobank data identify candidate deafness genes.

INTRODUCTION: Rapid advances in whole-exome sequencing (WES) have enabled large-scale detection of pathogenic variants. Although hundreds of genes are implicated in hearing loss, up to half of inherited cases remain unsolved, limiting eligibility for gene therapy trials that require genetic diagnosis. Biobanks and electronic medical records (EMRs) offer opportunities to integrate genomic and clinical data at scale and expand the spectrum of hearing loss genes. Despite clinical value, EMRs often lack key information such as inheritance patterns, posing challenges for accurate interpretation. METHODS: WES was performed on DNA samples from 1038 hearing-impaired patients enrolled in the Maccabi Research and Innovation Center Tipa Biobank. Clinical data were extracted from EMRs. Audiograms were available for all cases, although data on age of onset, family history and mode of inheritance were mostly unavailable. We applied a scalable bioinformatics analysis strategy for high-throughput annotation, filtering and prioritisation of WES variants across more than 1000 patients, designed to accommodate incomplete and heterogeneous clinical records. RESULTS: Using this approach, 15% of cases were solved or potentially solved through known or novel variants in established deafness genes. Homozygous variants in novel candidate genes were identified in 3% of cases. Functional characterisation was performed for promising candidate genes to validate their role in the ear. CONCLUSION: These findings demonstrate that WES can determine disease aetiology in large, genetically heterogeneous populations, even in the context of incomplete clinical data. This approach supports large-scale genetic screening and provides a framework for identifying patients who may benefit from emerging gene-based therapies.

Genetic Testing↗

PubMed2006

From hype to mothballs in four years: troubles in the development of large-scale DNA biobanks in Europe.

This paper analyses the difficulties experienced by three large European DNA biobanks. The first, Icelandic-based deCode, generated immense commercial interest and intense ethical controversy. As a biotechnology company, deCode succeeded, but the Icelandic Health Sector Data Base failed. The second firm, Swedish UmanGenomics, marketed itself as the 'ethical' biotech company. Management problems including the inadequate recognition of intellectual property issues led to the company failing to secure adequate investment. The third and largest, UK Biobank, has, as a non-profit organization, not experienced these problems. But when the product - bio information--is marketed, the issue of ethically acceptable purchasers could well become contentious.

Computational Biology↗

PubMed2026

Genome-wide association study of asthma with high treatment burden and/or worse outcomes defined using electronic healthcare data in UK Biobank.

BACKGROUND: In ∼10% of asthma patients, symptoms remain uncontrolled despite maximal treatment, representing an unmet clinical need. The causal variants, genes and pathways underlying genetic risk factors have not been fully elucidated, and it is unclear whether there are unique genetic risk factors for this asthma subtype. METHODS: We used electronic healthcare records linked to UK Biobank to identify asthma patients with high treatment burden and/or worse outcomes. We performed a genome-wide association study (GWAS) with this case population and healthy controls. We sought replication for associated (p≤5×10-6) signals in four independent studies (12 152 cases and 32 316 controls). Replicated signals were fine-mapped and linked to genes and pathways. RESULTS: In total, 7681 participants met our case definition and showed enrichment for adult-onset asthma, female gender and higher body mass index compared to asthma individuals not meeting case criteria. GWAS with 7681 cases and 38 405 controls revealed 21 reproducible association signals that had previously been associated with asthma, but had a larger effect size in our study. Variant-to-gene mapping highlighted 85 candidate genes, five of which were considered high confidence (BACH2, D2HGDH, IL1RL1, RPS26, SMAD3). CONCLUSION: We present the first use of electronic healthcare records in UK Biobank to identify a subtype of asthma enriched for patients with high treatment burden and/or worse outcomes. Our findings support the role of known asthma genes, highlighting genetic risk variants with stronger effect in these groups of patients. The prioritised genes provide potential therapeutic opportunities for this difficult-to-treat patient population.

Journal Article↗

PubMed2026

Arrhythmia and cardiomyopathy risk in Taiwan with complementary biobank evidence on thyroid genetic susceptibility: an integrative population-based framework.

BACKGROUND: Arrhythmia-induced cardiomyopathy (AiCM) is a potentially reversible cause of ventricular dysfunction; however, only a subset of patients with arrhythmia develop cardiomyopathy. Emerging evidence suggests that endocrine factors, particularly thyroid dysfunction with genetic susceptibility, may contribute to inter-individual variability in arrhythmia-related myocardial outcomes. METHODS: We performed a dual-cohort population-based study using the National Health Insurance Research Database (NHIRD, 2000-2015) and the Taiwan Biobank (TWB). In NHIRD, we examined the association between newly diagnosed arrhythmia and incident cardiomyopathy using Cox proportional hazards models. In TWB, genome-wide data, thyroid-stimulating hormone (TSH), polygenic risk scores (PRSs), lifestyle factors, and metabolic comorbidities were analyzed using multivariable regression and interaction models to assess determinants of thyroid dysfunction. RESULTS: In the NHIRD cohort, arrhythmia was associated with a significantly increased risk of incident cardiomyopathy (adjusted hazard ratio (aHR): 2.49, 95% CI: 1.94-2.96), with atrial fibrillation showing the strongest association among arrhythmia subtypes. In the TWB cohort, a higher thyroid polygenic risk score was strongly associated with thyroid dysfunction (adjusted odds ratio (aOR): 6.64, 95% CI: 5.86-7.52). The association between genetic susceptibility and thyroid dysfunction was further modified by metabolic and lifestyle factors, including diabetes, hyperlipidemia, and dietary patterns. Genome-wide analysis identified multiple loci associated with thyroid-stimulating hormone regulation, consistent with a polygenic architecture of thyroid endocrine traits. CONCLUSION: Arrhythmia was associated with an increased risk of cardiomyopathy in a nationwide cohort, while thyroid genetic susceptibility was strongly associated with thyroid dysfunction in a biobank cohort and modified by metabolic and lifestyle factors. These findings provide complementary population-level evidence of parallel cardiovascular and endocrine-genetic associations. Because the two cohorts were not individually linked, causal inference cannot be established. The results support a systems-level framework of endocrine-cardiac interaction and suggest that integrated clinical and genetic risk assessment may help identify individuals who warrant closer monitoring.

arrhythmia↗

PubMed2026

Genetic Correlation Between Brain Imaging Phenotypes and Externalizing Behavior: A Large-Scale LDSC Analysis of UK Biobank IDPs.

Externalizing has been associated with differences in brain structure and function; however, it remains unclear whether these associations reflect shared common-variant genetic influences. Cross-trait linkage disequilibrium score regression was used to estimate genome-wide genetic correlations between externalizing genome-wide association study (GWAS) results and 3,935 brain imaging-derived phenotypes from the UK Biobank BIG40 resource. The imaging phenotypes covered structural magnetic resonance imaging (MRI), diffusion MRI, susceptibility-weighted imaging, resting-state functional MRI, and task-based functional MRI. Results were included in the primary analysis when the imaging phenotype had positive single-nucleotide polymorphism (SNP) heritability, a heritability Z statistic of at least 1.96, a mean GWAS chi-square statistic of at least 1.02, at least 200,000 regression SNPs, and a complete LDSC result without a fatal error. Technical imaging quality-control phenotypes were excluded from biological inference. Individual results were corrected using the Benjamini-Hochberg false discovery rate procedure. Aggregated Cauchy association tests (ACATs) were used to evaluate evidence across all imaging phenotypes and within predefined imaging categories. Statistical power, simultaneous confidence bounds, and alternative quality-control definitions were examined in sensitivity analyses. Of the 3,935 imaging phenotypes, 3,716 produced estimable genetic correlations, 2,980 met the primary LDSC quality-control criteria, and 2,967 were classified as biological imaging phenotypes. No individual phenotype survived false discovery rate correction. The smallest unadjusted P value was 0.0005, and the minimum adjusted q value was 0.486. The distribution of genetic correlations was centered near zero, with a median genetic correlation of 0.0014 and a median absolute genetic correlation of 0.0338. ACAT provided no evidence of an aggregate association across all biological imaging phenotypes (P = 0.302), and no predefined imaging category survived multiple-testing correction. The median minimum detectable genetic correlation at 80% power was 0.216. Bonferroni-adjusted simultaneous confidence intervals were fully contained within the interval [-0.30, 0.30] for 80.0% of phenotypes in the primary analysis and 88.0% under the stringent heritability quality-control definition. Broad and stringent sensitivity analyses produced the same overall conclusions. In this study, no statistically robust evidence of genome-wide genetic correlations between externalizing and individual UK Biobank brain imaging phenotypes was found. Nevertheless, small, localized, mixed-direction, or developmentally specific genetic effects remain possible.

Journal Article↗

PubMed2003

[Genetic research on blood samples stored for years in biobanks. Most people are willing to provide informed consent].

Genetic research involving biobanks has been the subject of numerous declarations, recommendations and guidelines produced by professionals, administrators, legislators and other decision-makers. Yet, there is little published empirical information on people's willingness to participate in genetic studies on blood samples that they donated many years ago, at a time when the informed consent did not include the possibility of genetic research. We here report on our experiences of obtaining informed consent for academic and as well as commercial genetic research on blood samples collected more than a decade ago. Participants in a population-based risk factor survey who had donated blood to a biobank in 1990 were contacted eleven years later (in 2001) and asked for informed consent for genetic studies. A total of 1,311 out of 1,409 participants (93%) gave their consent to use blood samples for academic genetic research, provided that an Ethics Committee had approved the research. Thirty-one participants (2.2%) did not give their consent for academic genetic research. Another 35 subjects (2.5%) did not consent to industrial genetic research even if their blood samples were anonymized. Sixty-four individuals did not reply or provided incomplete answers (together 4.8%). Of the 1,311 individuals that agreed to participate, 292 (22.3%) wanted to be informed and give their concent to every new specific project. All the others gave a general concent provided that an Ethics Committee had approved the research.

Adult↗

PubMed2026

Large-Scale Plasma Proteomics Enhances Prediction of Liver-Related Events Among Individuals With Prediabetes and Type 2 Diabetes: A Prospective Cohort Study in the UK Biobank.

OBJECTIVE: To develop a protein risk score (ProRS) for predicting liver-related events (LREs) in patients with diabetes and compare its predictive performance with the Fibrosis-4 Index (FIB-4) and an established polygenic risk score. RESEARCH DESIGN AND METHODS: This prospective cohort study included 13 516 individuals with prediabetes and type 2 diabetes (T2D) from the UK Biobank. Cox proportional hazards models and LASSO regression were applied to identify proteins associated with incident LREs and construct the ProRS. Predictive performance was assessed using Harrell's C-index, time-dependent area under the receiver operating characteristic curve, net reclassification improvement and integrated discrimination improvement. RESULTS: Over a median follow-up of 13.5 years, 171 (1.3%) incident LREs occurred. We identified 877 proteins associated with LRE risk, primarily enriched in inflammatory signalling, extracellular matrix remodelling and complement/coagulation cascades. In the training set, we developed a 24-protein ProRS (C-index, 0.842; 95% CI 0.797-0.884) that stratified individuals into low-, medium- and high-risk groups, with 10-year cumulative incidences of LREs of 0.2%, 1.2% and 14.2%, respectively. Compared with the low-risk group, the hazard ratio for LREs was 57.1 (95% CI 31.9-102) in the high-risk group. In the internal validation set, the ProRS model (C-index, 0.876; 95% CI 0.827-0.920) accurately predicted both short- and long-term LREs and outperformed FIB-4 index (C-index, 0.733; 95% CI 0.657-0.807) and polygenic risk score (C-index, 0.636; 95% CI 0.564-0.706). CONCLUSIONS: The protein risk score demonstrated superior performance compared with the FIB-4 index and the polygenic risk score in predicting incident LREs among individuals with prediabetes and T2D. The score allows stratification of individuals according to liver-related risk, though external validation in multi-ethnic cohorts is warranted.

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↗