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PubMed2026

Sugar-sweetened beverage consumption and incident depression: an exploratory multi-omics analysis of candidate biological mediators.

BACKGROUND: Depression is a leading cause of mental and physical disability globally, with its onset and progression influenced by a complex interplay of dietary, psychological, and biological factors. Recent research suggests a link between sugar-sweetened beverage (SSB) consumption and depression risk, although the potential biological pathways underlying this association remain poorly understood. METHODS: This study utilized data from 192,045 participants in the UK Biobank to examine the prospective association between SSB consumption and incident depression using Cox proportional hazards models. SSBs were defined as the sum of five beverage categories assessed via the Oxford WebQ 24-hour dietary recall. Directional consistency of the association was further examined across three external supporting datasets encompassing diverse populations: NHANES, YRBSS, and the Lianyungang Municipal School Health and Risk Factor Surveillance Study Dataset. We further investigated whether proteins, metabolites, inflammatory markers, and brain imaging phenotypes may serve as candidate mediators statistically consistent with mediation of the SSB-depression association. RESULTS: High SSB consumption was associated with an 18% higher risk of incident depression compared with non-consumers (HR = 1.18; 95% CI: 1.11-1.25), with consistent directional associations observed across external supporting datasets. A plasma proteomic signature comprising 229 proteins was constructed using elastic net regularization and was associated with an increased risk of incident depression. Exploratory mediation analyses identified 72 proteins, 36 metabolites, and 5 inflammatory markers as candidate mediators, with IL1RN showing the strongest protein-level candidate mediating effect (9.6%), and Unsaturation and neutrophil count showing the strongest metabolite- and inflammatory marker-level effects, respectively. CONCLUSIONS: This study provides preliminary evidence that proteins, metabolites, and inflammatory markers may serve as candidate mediators statistically consistent with mediation of the association between SSB consumption and incident depression. These findings are exploratory and hypothesis-generating, and future experimental studies are needed to validate these candidate pathways and assess their potential as targets for dietary interventions in depression prevention.

Humans↗

PubMed2026

Meta-ERS: an exposome-based risk score using non-genetic factors to guide osteoporosis prevention.

BACKGROUND: Osteoporosis is influenced by both genetic and environmental factors, yet the relative contribution of the exposome remains unclear. This study aimed to systematically identify non-genetic exposures related to osteoporosis and develop an exposome risk score (ERS) to evaluate individual osteoporosis susceptibility. METHODS: We conducted an exposome-wide analysis of 477,792 UK Biobank participants to identify key exposures associated with osteoporosis. The selected exposures were combined into a weighted Meta-ERS and validated in the Scotland/Wales cohort. The Meta-ERS was further compared with polygenic risk scores (PRS) and linked to plasma proteomics to explore underlying biological pathways. RESULTS: We identified 41 independent non-genetic exposures spanning socioeconomic status, mental health, sleep, diet, smoking, physical activity, environment, and marital status, with socioeconomic status and mental health emerging as the most significant drivers. Based on the identified exposures, we constructed eight domain-specific exposure risk scores and integrated them into a weighted Meta-ERS. The Meta-ERS (R2 = 5.1%; Proportion of Chi-Square = 14.3%) demonstrated an ability to explain osteoporosis variation that was on par with polygenic risk scores (R2 = 4.8%; Proportion of Chi-Square = 12.0%). Importantly, modifying unfavorable exposures mitigated the negative effect of PRS on osteoporosis, particularly among high PRS individuals (1.5- to 1.8-fold greater absolute risk reduction than in those with low PRS). Proteomic analyses further revealed potential mechanisms through which the exposome influences osteoporosis, including hormonal regulation, inflammation, ossification, muscle development, lipid metabolism, and accelerated bone aging. Among these, growth/differentiation factor 15 was identified as a key mediator protein, with a mediation proportion of 13.13%-36.52%. CONCLUSIONS: The Meta-ERS facilitates the quantification of individual osteoporosis risk and identifies modifiable exposures for targeted prevention. Its application can enable personalized risk stratification and guide lifestyle or environmental interventions.

Aged↗

PubMed2026

Exploring the use of machine and deep learning in genome-wide association studies: a comprehensive review.

The advent of high-throughput sequencing technologies has generated increasingly large and complex genomic datasets, necessitating analytical approaches capable of capturing high-dimensional and potentially nonlinear genetic interactions. This situation has significantly impacted the entire field of Genome-Wide Association Study (GWAS), whose primary goal is the identification of genomic traits and variants that are statistically associated with the risk of a disease. However, traditional GWAS methods may show reduced performance when applied to highly polygenic and nonlinear genetic architectures. Computational strategies from Artificial Intelligence (AI) and, in particular, from machine- and deep-learning may provide a powerful tool to overcome such limitations, especially by capturing nonlinear interactions and complex hidden regularities in large-scale data, which traditional GWAS approaches might overlook. To date, only a few approaches have been introduced and systematically assessed. In this review, we describe the main characteristics and limitations of standard statistical approaches for GWAS, the main uses of AI methods in computational genomics, and recent attempts to leverage AI strategies in GWAS. Particular attention will be devoted to key issues, such as the interpretability of methods and results, and the curse of dimensionality. More specifically, the review presents 30 methods designed to leverage AI in GWAS, as well as presenting a comprehensive set of evaluation metrics for their performance, also providing references to the most frequently used databases, and biobanks. Overall, this work may serve as a starting point for both dry- and wet-lab researchers, aiming to extract deeper insights from genomic data by moving beyond traditional linear additive assumptions, and leveraging large-scale datasets through AI-driven approaches.

Artificial intelligence↗

PubMed2026

Genome-wide association study of sarcopenia index reveals sex-stratified genetic architecture.

BACKGROUND: The sarcopenia index (SI), defined as the ratio of serum creatinine to cystatin C, is a proposed biomarker of muscle mass and sarcopenia, yet its genomic basis and genetic architecture remain largely unexplored. METHODS: We performed combined-sex and sex-stratified genome-wide association studies of SI in the UK Biobank. We examined the overlap between SI-associated loci and loci previously reported for sarcopenia-related traits. We assessed sexually dimorphic effects and gene-sex interactions, performed fine-mapping, and conducted credible gene prioritization, motif and transcription factor binding enrichment, gene-set enrichment, linkage disequilibrium score regression, and cross-phenotype colocalization. RESULTS: We identified 774 unique independent SI-associated loci across all analyses, with 747 detected in the combined-sex GWAS, 283 in the male-stratified GWAS, and 311 in the female-stratified GWAS; 367 of these loci had not been previously reported for conventional sarcopenia-related traits. Sex-stratified analyses highlighted the rs1145093-chr15q21.1-GATM region, where CARMA identified sex-differentiated causal variants. We prioritized 17 male-biased and 11 female-biased credible genes. Enrichment analyses implicated androgen receptor and GATA4 in males, and ESR1 and MYOD1 in females. Enrichment revealed shared pathways involving inflammation, cellular stress, and aging-related processes. LDSC showed inverse genetic correlations between SI and heart failure (rg = -0.19, p = 2.30 × 10- 9) and metabolic syndrome (rg = -0.12, p = 8.49 × 10- 8), and a positive correlation with chronic kidney disease. Compared with female SI, male SI exhibited two additional loci showing colocalization with four metabolic traits. CONCLUSIONS: These findings clarify the genetic architecture of SI and reveal sex-dependent mechanisms underlying sarcopenia, supporting precision risk assessment and targeted interventions.

Humans↗

PubMed2025

Associations Between Walking Pace, APOE-ε4 Genotype, and Brain Health in Middle-Aged to Older Adults.

PURPOSE: This study aimed to investigate whether self-reported walking pace (a marker of physical function) and the presence of APOE-ε4 allele interact to modify brain health outcomes. METHODS: We used data from a prospective cohort study of middle-aged to older adults from the UK Biobank who self-reported walking pace (slow or steady-to-brisk) and who were initially free of dementia ( n = 415,110). Incident all-cause dementia was obtained from hospital and death registry records, and structural brain volumes (right and left hippocampus volumes, total gray matter volume, and volume of white matter hyperintensities) were measured from a subset of participants ( n = 33,113). Cox proportional hazard models and generalized linear models were used to assess associations between exposures and outcomes. RESULTS: Slow walking pace and the presence of APOE-ε4 allele were associated with increased dementia risk (HR = 1.79 [95% CI = 1.66-1.93], P < 0.001; HR = 3.06 [2.90-3.23], P < 0.001, respectively), and there was an interaction between these associations, indicating that the association of walking pace with dementia risk is modified by APOE-ε4 status (reference group: HR Steady-Brisk/APOE-ε4- = 1; HR Slow/APOE-ε4- = 2.03 [1.84-2.25], P < 0.001; HR Steady-Brisk/APOE-ε4+ = 3.21 [3.02-3.41], P < 0.001; HR Slow/APOE-ε4+ = 4.99 [4.48-5.58], P < 0.001). Slow self-reported walking pace was associated with worse brain volume outcomes, and these associations were not modified by APOE-ε4 genotype. CONCLUSIONS: These results suggest walking pace and APOE-ε4 status independently influence brain volume outcomes, but both factors independently and jointly contribute to increased dementia risk. Individuals with both risk factors (slow walking pace and APOE-ε4 allele) show the strongest associations with dementia risk.

Self Report↗

PubMed2025

Psychological Resilience and Mental Wellbeing Mitigate the Risk of Irritable Bowel Syndrome.

INTRODUCTION: Comorbidities between mental disorders and irritable bowel syndrome (IBS) have been widely reported, yet associations between mental wellbeing and IBS, particularly regarding underlying genetic modification and proteomic signatures, remain underexplored. METHODS: This prospective cohort study analyzed 75,842 IBS-free participants aiming to investigate the prospective association between mental wellbeing and the risk of IBS in UK Biobank. Mental wellbeing was assessed through life satisfaction, positive affect, neuroticism, and depressive/anxiety symptoms. Cox models evaluate the hazard ratio (HR) for mental wellbeing and plasma proteome in relation to incident IBS during follow-up. Proteomic profiling identified mental wellbeing-associated proteins, with pathway enrichment analysis revealing biological mechanisms. Mediation and Mendelian randomization analyses further examine intermediate pathways and causality. RESULTS: With a 12.4-year follow-up period, 1,400 cases of incident IBS were documented. Better mental wellbeing mitigated IBS risk dose-dependently (low risk group: HR, 0.37; 95% confidence interval [CI]: 0.31-0.43). Higher life satisfaction (HR, 0.41; 95% CI: 0.30-0.56) and positive affect (HR, 0.50; 95% CI: 0.41-0.62) were inversely associated with IBS risk, whereas neuroticism (HR, 2.35; 95% CI: 1.92-2.88) and depressive/anxiety symptoms (HR, 3.09; 95% CI: 2.17-4.42) increased the risk. Findings remained consistent in across prevalent IBS and IBS subtypes. Mental wellbeing effects were independent of genetic predisposition. Mediation analyses revealed about 27% of protective effect of mental wellbeing were mediated through reduced depression and anxiety. Mendelian randomization supports causal protective effects of positive mental wellbeing on IBS. Proteomic profiling identified mental wellbeing-associated proteins mainly enriched in cytokine-cytokine receptor interactions. Chromogranin A and gastrin emerged as key protein biomarkers, showing significant associations with both mental wellbeing components and IBS risk. DISCUSSION: Our study demonstrates that enhanced mental wellbeing confers substantial protection against IBS development, highlighting psychological interventions as potential primary prevention strategies.

Humans↗

PubMed2026

Discovery and validation of a multi-protein panel for predicting non-fatal major adverse cardiovascular events in diabetic kidney disease.

OBJECTIVE: To identify plasma protein biomarkers associated with incident non-fatal major adverse cardiovascular events (MACE) in diabetic kidney disease (DKD) patients. RESEARCH DESIGN AND METHODS: We analyzed 317 DKD patients from the UK Biobank. Plasma proteomics and clinical data (demographics, metabolism, renal function) were integrated. In an exploratory discovery phase, three sequential Cox regression models (crude, socio-demographic-adjusted, socio-demographic-metabolic adjusted) screened non-fatal MACE-associated proteins. To prevent information leakage, the cohort was then randomly split into training (70%) and testing (30%) sets; machine-learning feature selection, hyperparameter optimization, and final model development were performed exclusively within the training set. The associated proteins were input into the four-step machine-learning pipeline (LASSO-Cox, random survival forest, Boruta, XGBoost-Cox). Predictive performance was validated using Kaplan-Meier survival analyses, longitudinal trajectory modeling, and ROC benchmarking. An interactive web application was deployed for clinical implementation. RESULTS: Of 1,463 plasma proteins, 561 were associated with non-fatal MACE across Cox models, with 14 overlapping proteins. Nine core proteins (ANG, IL1R1, CXCL14, ESAM, PTGDS, HAVCR1, FGFR2, IGSF8, CCL3) were validated: ANG showed the strongest non-fatal MACE association (HR = 3.88, 95%CI 2.33-6.48, p<0.001), and all high-expression groups had elevated non-fatal MACE risk. GO/KEGG enrichment highlighted inflammatory-immune pathways like positive regulation of MAPK cascade, Cytokine-cytokine receptor interaction and PI3K-Akt signaling pathway as key mechanisms. The model integrating proteins, demographic factors, and clinical variables achieved the highest predictive performance across non-fatal MACE (AUC = 0.768), myocardial infarction (MI) (0.808), and stroke (0.816) outcomes, with superior stability in cross-validation. CoxBoost + Elastic Net framework was selected as the optimal framework via benchmarking of 101 algorithms. The model demonstrated favorable calibration in high-risk patients and yielded positive net clinical benefit across decision thresholds of 5% to 45%. The web tool (https://jiangli2941.github.io/MACE-prediction-v2/) enables input of 28 variables, outputs non-fatal MACE risk status, risk probability, and highlights abnormal indicators. CONCLUSION: Plasma proteomics combined with machine learning identifies robust non-fatal MACE predictors in DKD.

Humans↗

PubMed2026

A Common CD36 Variant and the Genetic Landscape of Dilated Cardiomyopathy in Individuals of African Ancestry.

IMPORTANCE: Dilated cardiomyopathy (DCM) is a major cause of heart failure that disproportionately affects individuals of African genetic ancestry (AFR), among whom familial clustering of disease is also more pronounced relative to those of European ancestry (EUR). However, established monogenic DCM genes, identified primarily in EUR populations, explain a smaller proportion of DCM cases in AFR populations. A recent study identified a common AFR-specific nonsense variant in CD36 that accounts for a substantial burden of DCM in AFR. How the risk and population impact of this variant compare with those of established genetic causes of DCM is unknown. OBJECTIVE: To compare the contribution of a CD36 nonsense variant to DCM risk with that of truncating variants in TTN and pathogenic or likely pathogenic (P/LP) variants in other established DCM genes. DESIGN SETTING AND PARTICIPANTS: Multicohort genetic association study including AFR and EUR participants with exome or genome sequence and DCM case status from four datasets: All of Us, Million Veteran Program, Penn Medicine Biobank, and the DCM Precision Medicine Study. EXPOSURE: Carrier status for TTN truncating variants, P/LP variants in 11 high confidence DCM genes, and the CD36 nonsense variant (Y325*; 0, 1, or 2 copies). MAIN OUTCOMES AND MEASURES: Odds of DCM; prevalence of risk-variant carriers among DCM cases; and population attributable fraction (PAF) for DCM. RESULTS: Among 82,623 AFR individuals across four studies, the mean age was 53.4 years and 1,625 had DCM. CD36 Y325* risk-allele homozygotes had 4.8-fold (95% CI, 3.1-7.3) increased odds of DCM, and CD36 Y325* heterozygotes had 1.4-fold (95% CI, 1.2-1.7) increased odds. TTN truncating variants also conferred elevated risk of DCM in AFR participants (OR, 8.46; 95% CI, 5.3-12.3). Among AFR DCM cases, 2.5% were CD36 homozygotes, second only to TTN truncating variants (4.3%) and exceeding all other high-confidence DCM genes combined (1.5%). In population-level analyses incorporating both heterozygous and homozygous CD36 Y325* carriers, the population-attributable fraction for CD36 (9.0%) surpassed that of TTN truncating variants (3.6%). CONCLUSIONS AND RELEVANCE: An ancestry-specific CD36 variant contributes more to DCM burden in AFR ancestry than established DCM genes, including TTN truncating variants, typically considered the most common genetic cause of DCM. These findings reshape the known genetic architecture of DCM in individuals of African ancestry and highlight the importance of representation in genomic research.

Journal Article↗

PubMed2025

Genetic Predisposition to Low-Density Lipoprotein Cholesterol and Incident Type 2 Diabetes.

IMPORTANCE: Treatment to lower high levels of low-density lipoprotein cholesterol (LDL-C) reduces incident coronary artery disease (CAD) risk but modestly increases the risk for incident type 2 diabetes (T2D). The extent to which genetic factors across the cholesterol spectrum are associated with incident T2D is not well understood. OBJECTIVE: To investigate the association of genetic predisposition to increased LDL-C levels with incident T2D risk. DESIGN, SETTING, AND PARTICIPANTS: In this large prospective, population-based cohort study, UK Biobank participants who underwent whole-exome sequencing and genome-wide genotyping were included. Participants were separated into 7 groups with familial hypercholesterolemia (FH), predicted loss of function (pLOF) in APOB or PCSK9 variants, and LDL-C polygenic risk score (PRS) quintiles. Data were collected between 2006 and 2010, with a median follow-up of 13.7 (IQR, 12.9-14.5) years. Data were analyzed from March 1 to November 1, 2024. EXPOSURES: LDL-C level, LDL-C PRS, FH, or pLOF variant status. MAIN OUTCOMES AND MEASURES: Cox proportional hazards regression models adjusted for age, sex, genotyping array, lipid-lowering medication use, and the first 10 genetic principal components were fitted to assess the association between LDL-C genetic factors and incident T2D and CAD risks. RESULTS: Among the 361 082 participants, mean (SD) age was 56.8 (8.0) years, 194 751 (53.9%) were female, and mean (SD) baseline LDL-C level was 138.0 (33.6) mg/dL. During the follow-up period, 22 619 (6.3%) participants developed incident T2D and 17 966 (5.0%) developed incident CAD. The hazard ratio for incident T2D was lowest in the FH group (0.65; 95% CI, 0.54-0.77), while the highest risk was in the pLOF group (1.48; 95% CI, 1.18-1.86). The association between LDL-C PRS and incident T2D was 0.72 (95% CI, 0.66-0.79) for very high LDL-C PRS, 0.87 (95% CI, 0.84-0.90) for high LDL-C PRS, 1.13 (95% CI, 1.09-1.17) for low LDL-C PRS, and 1.26 (95% CI, 1.15-1.38) for very low LDL-C PRS. CAD risk increased directly with the LDL-C PRS. CONCLUSIONS AND RELEVANCE: In this cohort study, LDL-C and T2D risks were inversely associated across genetic mechanisms for LDL-C variation. Further elucidation of the mechanisms associating low LDL-C risk with increased risk of T2D is warranted.

Humans↗

PubMed2025

Clonal Hematopoiesis and Risk of New-Onset Myocarditis and Pericarditis.

IMPORTANCE: Clonal hematopoiesis of indeterminate potential (CHIP) is the age-related clonal expansion of hematopoietic stem cells with leukemia-associated mutations. Certain CHIP mutations promote atherosclerosis and heart failure through immune-related pathways. OBJECTIVE: To test whether CHIP is associated with the development of myocarditis and pericarditis. DESIGN, SETTING, AND PARTICIPANTS: This observational population-based cohort study used data from the UK Biobank. Enrollment occurred between 2006 and 2010. Participants with whole-exome sequencing, no prevalent cardiovascular disease or hematological malignancy, and complete covariate data were included. Follow-up occurred for a median of 13.6 (IQR, 12.8-14.2) years. Analyses were conducted from November 2024 to July 2025. EXPOSURES: Any CHIP (variant allele frequency [VAF] ≥2%) and large CHIP (VAF ≥10%) constituted coprimary study exposures. Secondary analyses considered DNMT3A and TET2 CHIP as separate exposures. MAIN OUTCOMES AND MEASURES: The primary outcome was a composite of incident myocarditis and pericarditis. Cox regression tested associations of CHIP with myocarditis and pericarditis, adjusting for age, sex, race and ancestry, and cardiovascular risk factors. Secondary analyses considered myocarditis and pericarditis as separate outcomes. Additional analyses compared associations of CHIP with myocarditis and pericarditis with those with other cardiovascular diseases, and tested the bidirectional associations between CHIP and noncardiac immune-mediated inflammatory diseases. RESULTS: Among 335 426 participants (mean age, 56.1 years; 185 429 female [55.3%] and 149 997 male [44.7%]), 11 057 had any CHIP (3.3%), 7271 had large CHIP (2.2%), and 382 developed myocarditis or pericarditis (0.11%). Any and large CHIP were associated with multivariable-adjusted hazard ratios of 1.75 (95% CI, 1.14-2.68; P = .01) and 2.07 (95% CI, 1.28-3.33; P = .003), respectively, for the primary composite outcome of incident myocarditis and pericarditis. Increased risks were observed for DNMT3A and TET2 CHIP, with hazard ratios of 2.22 (95% CI, 1.17-4.21; P = .01) for DNMT3A with pericarditis and 3.65 (95% CI, 1.16-11.49; P = .03) for TET2 with myocarditis. CHIP associated with myocarditis and pericarditis more strongly than with other cardiovascular diseases (eg, coronary artery disease and heart failure). Any CHIP was also associated with 1.27-fold risk (95% CI, 1.16-1.39; P < .001) of developing noncardiac immune-mediated inflammatory diseases, without evidence for reverse causation. CONCLUSIONS AND RELEVANCE: In this study, CHIP was a strong risk factor for myocarditis and pericarditis among middle-aged adults. Targeting CHIP and its downstream pathways may represent a strategy for preventing or treating pericarditis and myocarditis.

Adult↗

PubMed2026

Physical Activity and Cardiovascular Outcomes in Phenotype-Negative Cardiomyopathy Variant Carriers.

IMPORTANCE: Exercise may lead to disease progression and higher risk of sudden death in individuals with genetic cardiomyopathies, but the effects of exercise among individuals carrying a cardiomyopathy-associated variant without clinical manifestations (G+P-) are unclear. OBJECTIVE: To examine whether the effects of moderate to vigorous physical activity (MVPA) on cardiovascular (CV) outcomes, cardiac structure and function, and risk of developing overt cardiomyopathy and malignant ventricular arrhythmias (VAs) vary by G+P- status. DESIGN, SETTING, AND PARTICIPANTS: UK Biobank participants with whole-genome sequencing providing 1 week of accelerometer-based physical activity data and without prevalent heart failure (HF), atrial fibrillation (AF), cardiomyopathy, VAs, or implantable cardioverter-defibrillators were included in this cohort study. The study was conducted at 22 assessment centers throughout the UK from February 2013 to December 2015 with a median follow-up of 8 years. Data were analyzed from March 2024 to June 2025. EXPOSURE: Accelerometer-measured MVPA (minutes/week). MAIN OUTCOMES AND MEASURES: Associations were analyzed between MVPA volume and future incidence of adverse CV outcomes (AF, HF, myocardial infarction [MI], and stroke), cardiac magnetic resonance (CMR)-based measures of cardiac remodeling, and surrogates for clinical cardiomyopathy onset (cardiomyopathy and VA). Associations were compared between G+P- carriers and noncarriers. RESULTS: Among 84 699 individuals (mean [SD] age, 62 [8] years; 48 353 [57%] women; 3979 G+P- carriers), greater MVPA was associated with a lower risk of adverse CV outcomes over a median (IQR) 8.0 (7.5-8.5) years, irrespective of genotype. In multivariable models, higher MVPA was broadly associated with lower risk of incident CV disease in G+P- carriers (hazard ratio [HR] at optimal MVPA level vs zero [95% CI], AF: 0.68 [0.58-0.79]; HF: 0.58 [0.47-0.71]; MI: 0.49, [0.24-1.00]; stroke: 0.35 [0.12-0.99]). For G+P- carriers, MVPA in the range of 100 to 400 minutes per week was generally associated with lowest risk. Among individuals with CMR imaging, MVPA was associated with a similar pattern and extent of cardiac remodeling (eg, left ventricular dilation and left ventricular hypertrophy) in G+P- carriers vs noncarriers. Among G+P- carriers, higher MVPA was associated with lower risk of incident cardiomyopathy (HR at optimal MVPA vs 0, 0.03; 95% CI, 0.00-0.98) with no increase in risk of VA (eg, HR at 400 minutes of MVPA vs 0, 0.98; 95% CI, 0.83-1.14). Findings were generally consistent across variants associated with dilated cardiomyopathy, hypertrophic cardiomyopathy, or arrhythmogenic right ventricular cardiomyopathy, although precision of estimates for arrhythmogenic right ventricular cardiomyopathy were limited. CONCLUSIONS AND RELEVANCE: In this cohort study, MVPA within the general range of guideline-based recommendations was associated with lower risk of adverse CV outcomes and similar degrees of cardiac remodeling for G+P- carriers compared to noncarriers. Findings support the appropriateness of guideline-based MVPA recommendations for G+P- carriers.

Humans↗

PubMed2026

Clonal Hematopoiesis and Incident Heart Failure.

IMPORTANCE: Clonal hematopoiesis of indeterminate potential (CHIP), the age-related clonal expansion of hematopoietic cells with acquired preleukemic variants, has been associated with cardiometabolic diseases, including heart failure (HF). However, prior studies have lacked power to examine less common CHIP driver variants and have not investigated potential mediators of the CHIP-HF association. OBJECTIVE: To test whether specific CHIP subtypes are associated with incident HF and determine the extent to which CHIP-associated comorbidities mediate this association. DESIGN, SETTING, AND PARTICIPANTS: This was a UK Biobank prospective population-based cohort study of community-dwelling adults in the UK, with enrollment from 2006 to 2010 and follow-up through 2020. Included were participants with whole-exome sequencing (WES) and without prevalent HF, hematologic malignancy, or other CHIP-associated comorbidities (coronary artery disease [CAD], atrial fibrillation [AF], type 2 diabetes [T2D], or chronic kidney disease [CKD]) at baseline. Study data were analyzed from April through October 2025. EXPOSURES: Presence of CHIP and gene-specific CHIP subtypes (DNMT3A, non-DNMT3A, TET2, ASXL1, JAK2, DNA damage repair genes, and spliceosome genes). Mediation analyses examined CHIP-associated comorbidities (CAD, AF, T2D, and CKD). MAIN OUTCOMES AND MEASURES: The primary outcome was incident HF. Cox regression tested associations of CHIP and CHIP subtypes with incident HF, adjusted for age, sex, race, and cardiovascular risk factors. RESULTS: Among 417 616 participants (mean [SD] age, 56.1 [8.1] years; 234 868 female [56.2%]), 7183 (1.7%) developed incident HF over a median (IQR) of 11.1 (10.4-11.8) years of follow-up. CHIP was associated with HF risk (adjusted hazard ratio [aHR], 1.27; 95% CI, 1.15-1.40; P < .001), driven by non-DNMT3A subtypes (aHR, 1.52; 95% CI, 1.33-1.75; P < .001), including associations with TET2, ASXL1, JAK2, and spliceosome CHIP. DNMT3A CHIP was more modestly associated with HF (aHR, 1.15; 95% CI, 1.00-1.31; P = .04). In mediation analyses, development of CAD, AF, T2D, and/or CKD collectively accounted for 28.2% of the association (95% CI, 11.6%-45.4%; P = .001) between non-DNMT3A CHIP and HF. CONCLUSIONS AND RELEVANCE: Results of this cohort study suggest that CHIP, especially non-DNMT3A CHIP, was associated with incident HF. Other CHIP-associated comorbidities explained only a minority of the association between non-DNMT3A CHIP and HF. These findings suggest that CHIP is an HF risk factor and potential therapeutic target.

Adult↗

PubMed2026

Hidradenitis Suppurativa and Smoking, Obesity, Psoriasis, Inflammatory Bowel Disease, and Systemic Sclerosis: Results From A 2-Sample Mendelian Randomization Study.

IMPORTANCE: Smoking and obesity are associated with risk of hidradenitis suppurativa, and both are considered important environmental risk factors. However, a causal relationship remains unproven. OBJECTIVE: To primarily investigate the relationship between body mass index (BMI, calculated as weight in kilograms divided by height in meters squared) and smoking and HS, and secondarily to investigate potential relationships between 3 inflammatory diseases (psoriasis, inflammatory bowel disease [IBD], and systemic sclerosis [SSc]) and HS. DESIGN, SETTING, AND PARTICIPANTS: A mendelian randomization (MR) study conducted in 2024 on 5 exposure phenotypes (BMI, smoking, psoriasis, IBD, and SSc) on the outcome of phenotype HS was conducted. The MR analyses used large genetic White European cohorts from genome-wide association studies (GWAS) of each of the 6 phenotypes. Initial analyses were conducted May, 2024, and were updated in May, 2025. EXPOSURE: The 5 exposure phenotypes using predetermined genome-wide significant single-nucleotide variants as proxies for each particular exposure. RESULTS: The GWAS on HS included 4814 case patients and more than 1.2 million controls from Denmark, Iceland, Finland, the UK, and the US. The BMI GWAS involved 700 000 individuals from the UK Biobank and GIANT consortium. Smoking data were obtained from 1.23 million participants in an international consortium. The psoriasis GWAS analyzed 39 498 case patients and 286 769 controls from White European populations and a DNA genetic testing company. The IBD GWAS meta-analysis included 38 155 case patients and 48 485 controls from the International Inflammatory Bowel Disease (IBD) Genetics Consortium. The SSc GWAS included 9095 case patients and 17 584 controls from White European populations. Genetic correlations (rg) were found between HS and all exposure phenotypes except SSc (BMI: rg = 0.36, P < .001; smoking: rg = 0.33, P < .001; IBD: rg = 0.25, P < .001; psoriasis: rg = 0.34, P < .001; SSc: rg = 0.33, P = .22). MR analyses supported an effect of BMI on HS (β = 0.87; odds ratio [OR] per BMI unit, 1.20; 95% CI, 1.17-1.23; P < .001) without signs of pleiotropy (slope: β = 0.91, P < .001, P for intercept = .76). Smoking showed a significant causal estimate (β = 0.59, P < .001), but results became inconclusive in subsequent sensitivity analyses. Among IBD, psoriasis, and SSc, results supported a causal effect of IBD on HS (β = 0.18, OR = 1.20; 95% CI, 1.15-1.24; P < .001), without signs of pleiotropy. CONCLUSIONS AND RELEVANCE: These findings indicate causal effects of IBD and increased BMI on the risk of HS. This information may help physicians inform patients about disease risk contributed by modifiable lifestyle behaviors, which can be beneficial for planning lifestyle interventions.

Humans↗

PubMed2000

Sequential analysis of matched dichotomous data from prospective case-control studies.

Sequential analysis of randomized controlled clinical trials and epidemiological prospective (matched) case-control studies can have ethical or economical advantages above a fixed sample size approach. It offers the possibility to stop early when enough evidence for an apparent effect of the risk factor or lack of the expected effect is achieved. In clinical trials it is well accepted to stop the trial early in favour of the alternative hypothesis. In epidemiological studies, in general, the need is not felt to stop early in case of a clear exposure effect. Little attention has been paid, however, to early stopping and accepting the null hypothesis. In metabolic epidemiological studies, where analysis destroys the biological material, the question of efficient use of samples, for example, those stored in a biobank, becomes crucial. Also a slow accrual of cases or the costs of follow-up of a cohort nested study can make it desirable to stop a study early once it becomes clear that no relevant exposure effect will be found. Matching can further reduce the amount of information necessary to reach a conclusion. We derived test statistics Z (efficient score) and V (Fisher's information) for the sequential analysis of studies with dichotomous data where each case can be matched to one or more controls. A variable matching ratio is allowed. These test statistics can be entered into the software PEST to monitor the course of the study. The double sequential probability ratio test and the double triangular test were evaluated with simulated data for odds ratios equal to 1.5, 2.0 and 2.5 and various type I and type II error probabilities both under H(0) and under H(1). Our simulations resulted in average and median values for the amount of information (V) that are far less than those for a fixed sample size study. Efficiency gain ranges from 32 per cent to 60 per cent. The proposed sequential analysis was applied in an investigation on the possible relationship between the polymorphism of the MTHFR-gene and rectal cancer in a cohort of women with cases matched by age to one and to three controls. A sequential analysis of matched data can lead to early stopping in favour of H(0) or H(1), thus conserving valuable resources for future testing. A sequentially designed study can be more economical and less arbitrary than a study that makes use of conditional power or conditional coverage probability calculations to decide early stopping.

Aged↗

PubMed2025

Plasma Proteomic Profiles Predict Individual Future Osteoarthritis Risk.

OBJECTIVE: Osteoarthritis (OA) is a widespread degenerative joint disease that causes a considerable socioeconomic burden. Despite progress in genetic and environmental insights, early diagnosis is still limited by the lack of evident symptoms during the initial phases and accurate biomarkers. This study aims to identify plasma proteins associated with future risk of OA and develop a predictive model. METHODS: We conducted a large-scale proteomic analysis of 45,307 participants from the UK Biobank, excluding those with baseline OA. Plasma samples were assayed using the Olink Explore Proximity Extension Assay targeting 1,463 unique proteins. Clinical variables and OA outcomes were extracted and linked to electronic health records. A predictive model was constructed using the LightGBM machine learning method, and SHapley Additive exPlanations (SHAP) were applied to evaluate the importance of variables. RESULTS: We identified a panel of proteins significantly associated with the risk of developing OA. Notably, after adjusting for multiple confounders, collagen type IX alpha 1 chain (COL9A1) and cartilage acidic protein 1 (CRTAC1) were the most significant predictors of incident OA, with hazard ratios of 1.54 (95% confidence interval [CI] 1.48-1.61) and 1.65 (95% CI 1.54-1.78), respectively. SHAP analysis allowed a profound interpretation of the contribution of each protein and clinical variable to the model, revealing the multifactorial nature of OA risk prediction. The temporal trajectories of plasma proteins indicated that the levels of COL9A1 and CRTAC1 began to deviate from normal for more than a decade before OA onset, suggesting their potential use in early detection strategies. The predictive model, developed using the LightGBM algorithm, integrated proteins with clinical covariates and demonstrated an area under the curve (AUC) of 0.729 for 5-year OA prediction, 0.721 for 10-year prediction, and 0.723 for all incident OA. The predictive accuracy of the model was further enhanced for hip and knee OA, achieving AUCs of 0.820 and 0.803 for 5-year predictions. CONCLUSION: Our study identified the role of plasma proteomics in predicting future OA risk, which could contribute to preemptive measures. The innovative model, which integrates proteomic biomarkers with clinical data, offers a potential tool for risk assessment, potentially optimizing OA management strategies and enhancing prevention efforts.

Humans↗

PubMed2024

Mendelian randomization study of lipid metabolism characteristics and migraine risk.

BACKGROUND: The association between serum lipids and migraine is controversial. However, randomized controlled trials have suggested that statins may be efficacious for the prevention of migraine. In this study, we aim to investigate the relationship between lipids metabolism and migraine risk. METHODS: Single-nucleotide polymorphisms (SNPs), relating to the serum lipid traits and the effect of lipid-lowering drugs that target APOB, CETP, HMGCR, NPC1L1, and PCSK9, were extracted from genome-wide association studies (GWAS) summary data. The GWAS summary data were obtained from the Global Lipids Genetic Consortium (GLGC), the UK Biobank, and the FinnGen study, respectively. Mendelian randomization (MR) analysis was performed to evaluate the association between serum lipid traits and lipid-lowering drugs with migraine risk. RESULTS: Regarding serum lipids, it was found that SNPs related to high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), total cholesterol (TC), or triglycerides (TG) levels were not associated with migraine, migraine with aura (MA) or migraine without aura (MO). In addition, genotypes of HMGCR related to higher LDL-C levels were associated with increased risk of migraine (OR = 1.46, p = 0.035) and MA (OR = 2.03, p = 0.008); However, genotypes of PCSK9 related to higher LDL-C levels were associated with decreased risk of migraine (OR = 0.75, p = 0.001) and MA (OR = 0.69, p = 0.004); And genotypes of APOB related to higher LDL-C levels were associated with decreased risk of MO (OR = 0.62, p = 0.000). CONCLUSIONS: There is a relationship between lipid metabolism characteristics and migraine risk. SIGNIFICANCE: Based on the genome-wide association summary data, single-nucleotide polymorphisms (SNPs) related to high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), total cholesterol (TC), or triglycerides (TG) level were not associated with risk of migraine, migraine with aura (MA) or migraine without aura (MO). However, genotypes of HMGCR related to higher LDL-C levels have shown an increased risk on migraine and MA. And genotypes of APOB or PCSK9 related to higher LDL-C levels have shown a decreased risk on MO, or migraine and MA, respectively. These results suggested that there may be a relationship between lipid metabolism characteristics and the risk for migraine development.

Humans↗

PubMed2004

Power of direct vs. indirect haplotyping in association studies.

Haplotype analysis is essential to studies of the genetic factors underlying human disease, but requires a large sample size of phase-known data. Recently, directly haplotyping individuals was suggested as a means of maximizing the phase-known data from a sample. Haplotyping, however, is much more labor-intensive than indirectly inferring haplotypes from genotypes (genotyping). This study uses simulations to compare the power of each methodology to detect associations between a haplotype and a trait or disease locus under conditions of varying linkage disequilibrium. The relative power of haplotyping over genotyping in association studies increases with decreasing sample size, decreasing linkage disequilibrium, increasing [corrected] numbers of marker loci, and decreasing numbers of different haplotypes. In addition, the frequency of the haplotype of interest and the magnitude of its association with the disease affect the power. From a cost-benefit standpoint, genotyping would be favored with large multiplicative risks (relative risk of haplotype >2.5). If case numbers are limiting rather than cost, haplotyping would maximize the information obtained. At small haplotype frequencies (e.g., <0.05), haplotyping is relatively more efficient, but there is little absolute power to detect associations under either methodology. Given the much larger laboratory resources required for direct haplotyping, genotyping would probably be favored under most conditions, but this must be balanced against the unit costs associated with recruitment and phenotyping. In the context of multipurpose, prospective cohort studies (e.g., the UK Biobank study), there may be a general value in establishing a series of directly haplotyped individuals to serve as controls for a number of alternative studies.

Algorithms↗

PubMed2002

Circulating enterolactone and prostate cancer risk: a Nordic nested case-control study.

Enterolactone, a phytoestrogen belonging to the class of lignans, is produced by the intestinal microflora from precursors in plant foods and has been implicated in protection against cancer. We study the effect of enterolactone on the risk of a subsequent diagnosis of prostate cancer. We conducted a longitudinal, nested case-control study by linkage of 3 biobanks to the cancer registries in Finland, Norway and Sweden, respectively. Enterolactone concentrations were measured by time-resolved fluoroimmunoassay in serum from 794 men who had a diagnosis of prostate cancer at a mean follow-up time of 14.2 years after blood collection and among 2,550 control men matched within each cohort for age (+/-2 years), date of blood collection (+/-2 months) and county. The median enterolactone concentrations did not differ between case and control subjects in the full study group (8.4 nmol/L [25th-75th percentile = 4.5-15.0] vs. 8.5 nmol/L [25th-75th percentile = 4.3-15.9]), nor in the national groups. Odds ratios of prostate cancer risk estimated by conditional logistic regression for increasing concentrations of enterolactone in quartiles in the full study group were 1.00 (referent), 1.21 (95% confidence interval [CI] = 0.96-1.52), 1.16 (95% CI = 0.91-1.47) and 1.08 (95% CI = 0.83-1.39). The OR estimate for the highest vs. the lowest quartile of enterolactone in separate analyses of the Norwegian, Finnish and Swedish cohort was 1.21 (95% CI = 0.91-1.60), 1.02 (95% CI = 0.59-1.76) and 0.87 (95% CI = 0.45-1.67), respectively. No support for the hypothesis that high circulating enterolactone is protective against prostate cancer was found.

4-Butyrolactone↗