Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits

Faecal metaproteomics analysis reveals a high cardiovascular risk profile across healthy individuals and heart failure patients

The gut microbiota is a crucial link between diet and cardiovascular disease (CVD). Using fecal metaproteomics, a method that concurrently captures human gut and microbiome proteins, we determined the crosstalk between gut microbiome, diet, gut health, and CVD. Traditional CVD risk factors (age, BMI, sex, blood pressure) explained < 10% of the proteome variance. However, unsupervised human protein-based clustering analysis revealed two distinct CVD risk clusters (low-risk and high-risk) with different blood pressure (by 9 mmHg) and sex-dependent dietary potassium and fiber intake. In the human proteome, the low-risk group had lower angiotensin-converting enzymes, inflammatory proteins associated with neutrophil extracellular trap formation and auto-immune diseases. In the microbial proteome, the low-risk group had higher expression of phosphate acetyltransferase that produces SCFAs, particularly in fiber-fermenting bacteria. This model identified severity across phenotypes in heart failure patients and long-term risk of cardiovascular events in a large population-based cohort. These findings underscore multifactorial gut-to-host mechanisms that may underlie risk factors for CVD.

Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management

Hypertension presents the largest modifiable public health challenge due to its high prevalence, its intimate relationship to cardiovascular diseases, and its complex pathogenesis and pathophysiology. Low awareness of blood pressure elevation and suboptimal hypertension diagnosis serve as the major hurdles in effective hypertension management. Advances in artificial intelligence in hypertension have permitted the integrative analysis of large data sets including omics, clinical (with novel sensor and wearable technologies), health-related, social, behavioral, and environmental sources, and hold transformative potential in achieving large-scale, data-driven approaches toward personalized diagnosis, treatment, and long-term management. However, although the emerging artificial intelligence science may advance the concept of precision hypertension in discovery, drug targeting and development, patient care, and management, its clinical adoption at scale today is lacking. Recognizing that clinical implementation of artificial intelligence-based solutions need evidence generation, this opinion statement examines a clinician-centric perspective of the state-of-art in using artificial intelligence in the management of hypertension and puts forward recommendations toward equitable precision hypertension care.

Genetically Proxied Phosphodiesterase Type 5 (PDE5) Inhibition and Risk of Dementia: A Drug Target Mendelian Randomization Study

Phosphodiesterase-5 (PDE5) inhibitors have gained interest as a potential treatment for dementia. However, current evidence is limited to observational and pre-clinical studies. We conducted a drug-target Mendelian randomization (MR) analysis to investigate the on-target effects of pharmacological PDE5 inhibition on dementia subtypes and related phenotypes. We selected variants from around the PDE5A locus associated with diastolic and systolic blood pressure, as well as circulating PDE5A levels, to create three instruments for genetically proxied PDE5A inhibition. Using two-sample MR, we validated the instruments against erectile dysfunction and pulmonary arterial hypertension before assessing their associations with dementia subtypes, dementia-related proteins, and neuroimaging traits. After correcting for multiple comparisons, genetically proxied PDE5 inhibition, per one SD lower in diastolic blood pressure, was associated with higher odds of Alzheimer's disease (OR 1.09, 95% CI 1.07-1.11) and Lewy body dementia (OR 1.32, 95% CI 1.23-1.41), but a trend towards lower odds of vascular dementia across all instruments. Genetically proxied PDE5 inhibition was associated with both beneficial and adverse effects on brain MRI traits. This included lower volumes of white matter hyperintensities (SD change - 0.035, 95% CI - 0.025, - 0.045), indicating potential benefits, but also reduced volumes of other structures, including the thalamus, suggesting potential adverse effects. PDE5 inhibition was associated with the concentrations of several proteins implicated in dementia pathophysiology. Our findings suggest that while PDE5 inhibition may be associated with a lower risk of vascular dementia, possibly by preventing white matter hyperintensities, it may increase risk of Alzheimer's disease and Lewy body dementia, warranting further investigation before clinical trials.

Comprehensive genome-wide analysis of retinal vessel caliber reveals microvascular-blood pressure pathways: advancing predictive, preventive, and personalized medicine

Background

Retinal vessel caliber is strongly associated with systemic blood pressure (BP); however, the causal relationship between retinal vascular caliber and BP remains unclear. Understanding this relationship is essential for advancing predictive, preventive, and personalized medicine (PPPM) approaches to effectively manage hypertension and its related complications.

Working hypothesis

Microvessel morphology is causally related to blood pressure. By integrating genome-wide association studies, Mendelian randomization analysis, transcriptomic data, and multivariate genomic approaches, this study aims to identify predictive biomarkers, uncover preventive strategies, and develop personalized intervention targets, thereby advancing the principles of 3P medicine for improved cardiovascular health management.

Methods and results

We conducted a comprehensive investigation into the genetic factors underlying retinal vessel calibers and their complex relationship with BP traits. Our genome-wide association study (GWAS) assess retinal vessel calibers-central retinal arteriolar equivalent (CRAE), central retinal venular equivalent (CRVE), and the arteriole-to-venule ratio (AVR)-in a subset of 36,223 individuals of European descent from the UK Biobank. The analysis identified 9, 5, and 4 SNPs located in TNS, Y_RNA, PBLD, C10orf32-ASMT:AS3MT, GNB3:CDCA3, NTN4, COL4 A2, CTD-2378E21.1, WNT7B, VTA1, FCF1, NPLOC4, FUT1 and CSK region, which are significantly associated with CRAE, CRVE, and AVR, respectively. Genetic correlation analysis revealed shared heritability between BP traits and both CRAE and AVR, but not CRVE. Mendelian randomization analysis confirmed bidirectional causal relationships between CRAE and BP traits, whereas CRVE was neither influenced by nor influenced BP traits. To explore the potential regulatory mechanisms, we leveraged transcriptomic data and identified the following causal pathways in vessel tissue: The expression of MRPL23-AS1 and ULK3 was correlated with the elevation of blood pressure SBP and narrowing of the CRAE. Finally, we constructed a multivariable genetic model including CRAE, AVR, SBP, and DBP, suggesting a common driving factor which underlies these traits.

Conclusions

Our study elucidates the complex relationship between BP and retinal vessel caliber, highlighting potential intervention targets for lowering BP and vascular narrowing-related diseases. These findings contribute to the development of tailored prevention and treatment strategies aligned with PPPM principles.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-025-00411-w.

Development and Validation of Polygenic Risk Scores for Blood Pressure Traits in Continental African Populations

BACKGROUND

Most polygenic risk scores (PRS) have been developed in European populations, frequently leading to limited transferability across diverse ancestry populations. This study aimed to develop and evaluate PRS for blood pressure (BP) traits in continental African (African) populations and investigate how African genetic diversity influences PRS performance.

METHODS

We generated PRS for systolic BP, diastolic BP, pulse pressure, and hypertension. We used a pan-African cohort as the target population and compared singleancestry and multiancestry PRS methods. We compared the performance of African ancestry-derived PRS against multiancestry PRS on the entire data set and within South, East, and West African subpopulations.

RESULTS

Multiancestry PRS demonstrated significantly higher predictive accuracy compared with singleancestry PRS models. PRS predictive accuracy varied across different African regions, with the highest performance observed in East Africa. In the combined population, the difference in mean BP values between the first multiancestry PRS quartile and the top quartile was 6.53 (95% CI, 5.3-7.74), 3.81 (95% CI, 3.9-4.52), and 3.59 (95% CI, 2.4-4.32) mm Hg for systolic BP, diastolic BP, and pulse pressure, respectively. Individuals in the highest PRS risk quartile had odds of hypertension that were 1.47 (95% CI, 1.7-1.69) times greater than those in the lowest risk quartile.

CONCLUSIONS

These findings highlight the importance of integrating diverse ancestries in PRS development and accounting for subpopulation genetic variation to improve the predictive accuracy of BP PRS in African populations.

Hypertension precision medicine: the promise and pitfalls of pharmacogenomics

Pharmacogenomics (PGx) has the potential to revolutionize hypertension management by tailoring antihypertensive therapy based on genetic profiles. Despite significant advances in genomic research, the clinical translation of PGx in hypertension remains challenging due to genetic complexity, variability in drug response, and implementation barriers. This review explores the genetic basis of hypertension, highlighting key pharmacogenomic markers that influence antihypertensive metabolism and efficacy, including CYP2D6, CYP3A4, UMOD, and ACE polymorphisms. We also examine the role of Mendelian randomization, polygenic risk scores in drug development and stratifying hypertension treatment response. While PGx offers opportunities for personalized medicine - such as reducing trial-and-error prescribing and improving adherence - several obstacles hinder its widespread adoption. These include limited clinical actionability, lack of large-scale randomized controlled trials, cost constraints, and concerns about equity and accessibility. Furthermore, drug-gene interactions and phenoconversion add complexity to implementation. Emerging technologies, including artificial intelligence-driven prescribing, microbiome integration, and pharmacoepigenomics, may enhance PGx precision in hypertension management. However, further research, clinical validation, and policy frameworks are necessary before PGx can be routinely incorporated into hypertension care. This review critically evaluates both the promise and limitations of PGx in hypertension, offering insights into the future of precision medicine in cardiovascular health.

Metabolomics insights into the causal associations between antihypertensive drugs and myocarditis

BACKGROUND

The role of various antihypertensive drug classes in myocarditis remains unclear. We aimed to investigate the causal effects of antihypertensive medications on myocarditis and identify potential metabolic pathways.

METHODS

We extracted single-nucleotide polymorphisms for systolic blood pressure (SBP) and diastolic BP (DBP) from a genome-wide association study (N = 757,601) and screened single-nucleotide polymorphisms associated with angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, β-blockers (BB), calcium channel blockers (CCB), and thiazides as instrumental variables. Summary-level statistics of myocarditis were sourced from the FinnGen study, encompassing 1847 cases and 231,952 controls. We subsequently performed a drug-targeted Mendelian randomization (MR) and a two-step network MR approach to investigate the causal impact of antihypertensive medications on myocarditis and to uncover metabolic mediators.

RESULTS

Our study revealed that elevated SBP (odds ratio [OR] = 1.05, 95 % confidence interval [CI] = 1.04-1.06, p = 4.75 × 10-14) and DBP (OR = 1.07, 95 % CI = 1.05-1.10, p = 1.54 × 10-10) significantly increased myocarditis risk. Conversely, the use of BB (OR = 0.86, 95 % CI = 0.82-0.90, p = 5.14 × 10-10) and CCB (OR = 0.95, 95 % CI = 0.92-0.99, p = 0.005) to lower BP was associated with a reduced risk of myocarditis. Network MR analyses identified four and seven metabolites mediating BB and CCB associations with myocarditis, respectively. Methyl indole-3-acetate mediated a significant portion of the relationships between BB and myocarditis (mediation proportion = 6.82 %), while phenylalanine to tyrosine ratio was the predominant mediator (mediation proportion = 11.35 %) linking CCB to myocarditis.

CONCLUSIONS

Our findings suggest that reducing BP through antihypertensive drugs, specifically BB and CCB, may hold potential for preventing myocarditis and have identified several metabolic pathways linking these associations.

Examining socioeconomic differences in sepsis risk and mediation by modifiable factors: a Mendelian randomization study

BACKGROUND

Educational attainment is inversely related to sepsis risk, but the causal nature is still unclear. We therefore conducted the first Mendelian randomization (MR) study of genetically predicted educational attainment on sepsis that also uses a within-family genetic instrument for education. To further explore possible mechanistic pathways that can inform strategies to reduce sepsis risk, we examined the mediating effects of factors that are modifiable or can be prevented.

METHODS

The association between genetically predicted educational attainment and sepsis was estimated using summary-level data from recent genome-wide association studies. Possible bias due to population stratification, dynastic effects, and assortative mating in the genetic instrument for education was evaluated using summary-level data from a within-sibship genome-wide association study. We used inverse variance weighted MR analysis to estimate the effect of one standard deviation increase in years of education on sepsis risk. The robustness of the findings was assessed in sensitivity analyses, applying weighted median, weighted mode, and MR Egger regression. Finally, we applied multivariable MR analyses to estimate the mediating effects of smoking initiation, alcohol consumption, body mass index, high-density lipoprotein (HDL)-cholesterol, systolic blood pressure and type 2 diabetes.

RESULTS

For each standard deviation increase in genetically predicted educational attainment (3.4 years), the odds ratio (OR) for sepsis was 0.72 (95% confidence interval (CI) 0.66 to 0.78). The results of the analysis using the within-sibship genetic instrument and other sensitivity analyses were in line with this finding: within-sibship OR 0.88 (95% CI 0.64 to 1.18), weighted median OR 0.70 (95% CI 0.62 to 0.80), weighted mode OR 0.70 (95% CI 0.43 to 1.13), and MR Egger OR 0.65 (95% CI 0.50 to 0.85). The mediation analysis showed that 56% of the effect of educational attainment on sepsis risk can be explained by modifiable or preventable factors.

CONCLUSIONS

Higher educational attainment is strongly associated with a reduced risk of sepsis, pointing to important socioeconomic differences in this disease. The results also suggest that interventions targeting modifiable or preventable factors could contribute to reducing the socioeconomic differences in sepsis risk.

The immune system in cardiovascular diseases: from basic mechanisms to therapeutic implications

Immune system plays a crucial role in the physiological and pathological regulation of the cardiovascular system. The exploration history and milestones of immune system in cardiovascular diseases (CVDs) have evolved from the initial discovery of chronic inflammation in atherosclerosis to large-scale clinical studies confirming the importance of anti-inflammatory therapy in treating CVDs. This progress has been facilitated by advancements in various technological approaches, including multi-omics analysis (single-cell sequencing, spatial transcriptome et al.) and significant improvements in immunotherapy techniques such as chimeric antigen receptor (CAR)-T cell therapy. Both innate and adaptive immunity holds a pivotal role in CVDs, involving Toll-like receptor (TLR) signaling pathway, nucleotide-binding oligomerization domain-containing proteins 1 and 2 (NOD1/2) signaling pathway, inflammasome signaling pathway, RNA and DNA sensing signaling pathway, as well as antibody-mediated and complement-dependent systems. Meanwhile, immune responses are simultaneously regulated by multi-level regulations in CVDs, including epigenetics (DNA, RNA, protein) and other key signaling pathways in CVDs, interactions among immune cells, and interactions between immune and cardiac or vascular cells. Remarkably, based on the progress in basic research on immune responses in the cardiovascular system, significant advancements have also been made in pre-clinical and clinical studies of immunotherapy. This review provides an overview of the role of immune system in the cardiovascular system, providing in-depth insights into the physiological and pathological regulation of immune responses in various CVDs, highlighting the impact of multi-level regulation of immune responses in CVDs. Finally, we also discuss pre-clinical and clinical strategies targeting the immune system and translational implications in CVDs.

Distinct pathway-based effects of blood pressure and body mass index on cardiovascular traits: comparison of novel Mendelian randomization approaches

BACKGROUND

Mendelian randomization (MR) leverages trait associated genetic variants as instrumental variables (IVs) to determine causal relationships in epidemiology. However, genetic IVs for complex traits are typically highly heterogeneous and, at a molecular level, exert effects on different biological processes. Exploration of the biological underpinnings of such heterogeneity can enhance our understanding of disease mechanisms and inform therapeutic strategies. Here, we introduce a new approach to instrument partitioning based on enrichment of Mendelian disease categories (pathway-partitioned) and compare it to an existing method based on genetic colocalization in contrasting tissues (tissue-partitioned).

METHODS

We employed individual- and summary-level MR methodologies using SNPs grouped by pathway informed by proximity to Mendelian disease genes affecting the renal system or vasculature (for blood pressure (BP)), or mental health and metabolic disorders (for body mass index (BMI)). We compared the causal effects of pathway-partitioned SNPs on cardiometabolic outcomes with those derived using tissue-partitioned SNPs informed by colocalization with gene expression in kidney, artery (BP), or adipose and brain tissues (BMI). Additionally, we assessed the likelihood that estimates observed for partitioned exposures could emerge by chance using random SNP sampling.

RESULTS

Our pathway-partitioned findings suggest the causal relationship between systolic BP and heart disease is predominantly driven by vessel over renal pathways. The stronger effect attributed to kidney over artery tissue in our tissue-partitioned MR hints at a multifaceted interplay between pathways in the disease aetiology. We consistently identified a dominant role for vessel (pathway) and artery (tissue) driving the negative directional effect of diastolic BP on left ventricular stroke volume and positive directional effect of systolic BP on type 2 diabetes. We also found when dissecting the BMI pathway contribution to atrial fibrillation that metabolic-pathway and brain-tissue IVs predominantly drove the causal effects relative to mental health and adipose in pathway- and tissue-partitioned MR analyses, respectively.

CONCLUSIONS

This study presents a novel approach to dissecting heterogeneity in MR by integrating clinical phenotypes associated with Mendelian disease. Our findings emphasize the importance of understanding pathway-/tissue-specific contributions to complex exposures when interpreting causal relationships in MR. Importantly, we advocate caution and robust validation when interpreting pathway-partitioned effect size differences.

Genetically proxied glucokinase activation and risk of diabetic complications: Insights from phenome-wide and multi-omics mendelian randomization

AIMS

This study aims to assess the benefits and adverse effects of long-term glucokinase (GK) activation from a genetic perspective.

METHODS

We identified genetic variants in the GCK gene associated with glycated hemoglobin (HbA1c) levels from a genome-wide association study (GWAS) involving 146,806 individuals, which served as proxies for glucokinase activation. To assess the effects and potential pathways of GK activation on a range of diabetic complications and safety outcomes, we integrated drug-target Mendelian randomization (MR), lipidome-wide and proteome-wide MR, phenome-wide MR, and colocalization analyses.

RESULTS

Genetically proxied GK activation was associated with reduced risks of several predefined diabetic complications, including cardiovascular diseases, stroke and diabetic retinopathy. No kidney-related benefits were observed. Safety analysis revealed a relationship between GK activation and elevated AST levels, while impaired interaction between GK and glucokinase regulatory protein (GKRP) was associated with dyslipidemia, increased liver fat content, AST, systolic blood pressure, and uric acid. Phenome-wide MR suggested that GK activation may have potential benefits for lung function and fluid intelligence score.

CONCLUSIONS

Our genetic evidence supports GK as a promising target for reducing the risk of specific diabetic complications. These findings require further validation through cohort studies and randomized controlled trials in patients with diabetes.

A Beneficial Role for Gluteofemoral Adipose Tissue in Cerebrovascular Disease: Causal Pathway and Mediation Analysis

BACKGROUND AND OBJECTIVES

Previous studies have shown that increased body fat is associated with stroke risk, with evidence suggesting that body fat distribution, rather than total body fat, exerts a more prominent role in cerebrovascular risk prediction. In this study, we explore causal associations between body mass index (BMI)-independent adipose tissue distribution profiles and cerebrovascular disease (CVD) risk, aiming to refine the association between body fat distribution and stroke.

METHODS

We selected variants associated with BMI-independent visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (ASAT), and gluteofemoral adipose tissue (GFAT) volumes in UK Biobank, and performed univariable and multivariable Mendelian randomization (MR) analyses with ischemic stroke (IS) and subtypes (large artery stroke [LAS], cardioembolic stroke [CES], and small vessel stroke [SVS]). We used coronary artery disease (CAD), carotid intima media thickness (cIMT), and MRI-confirmed lacunar stroke as positive controls. We explored the mediatory role of common cardiovascular (systolic blood pressure, diabetes, and low-density lipoprotein), insulin resistance, inflammatory (C-reactive protein), and adipose tissue-specific (adiponectin, leptin) factors by performing 2-step mediation MR analyses. Estimates were expressed per standard deviation increase in adjusted adipose tissue volume.

RESULTS

Genetic predisposition to higher GFAT volume was associated with lower risk of IS (odds ratio [OR] 0.92, 95% CI 0.86-0.98), LAS (OR 0.80, 95% CI 0.66-0.96), and SVS (OR 0.77, 95% CI 0.67-0.88), but not CES, consistent in multivariable analyses. Genetic predisposition to higher GFAT volume was also associated with lower risk of CAD (OR 0.82, 95% CI 0.76-0.88), lacunar stroke (OR 0.78, 95% CI 0.67-0.92), and mean cIMT (β = -0.073, 95% CI -0.114 to -0.031). Associations were largely consistent in sensitivity analyses. No association was observed between genetic predisposition to ASAT or VAT and IS risk. Although common vascular risk factors were the predominant mediators in the GFAT-CVD axis, adiponectin and leptin mediated a proportion of IS and CAD risk (∼15% (1.8%-57%) and ∼4.6% (0.8%-13.5%) mediated by adiponectin, respectively).

DISCUSSION

This study supports a protective role of gluteofemorally distributed fat volume in CVD risk. Although this role is predominantly mediated by common vascular risk factor modification, adipose tissue-specific factors may exert a mediatory effect, suggesting a possible novel target for attenuating adiposity-related CVD risk.

Alteration of gut microbiota associated with hypertension in children

BACKGROUND

The association of disturbance in gut microbiota with hypertension (HTN) defined on three separate occasions among children and adolescents remains unclear. In this study, we aimed to compare the differences in gut microbiota composition and diversity between children with HTN and those with normal blood pressure (BP).

METHODS

Data and stool samples were collected from the second follow-up of a childhood cardiovascular health cohort study in 2021. 16 S ribosomal RNA gene sequencing was conducted to determine the relative abundance of microbial taxa in 51 children aged 10-14 years with HTN and 51 children with normal BP.

RESULTS

Compared with children with normal BP, those with HTN had decreased gut microbiome diversity. At the genus level, after adjusting for the false discovery rate (FDR), the proportions of several gut microbiota such as Blautia (PFDR=0.042), Coprococcus (PFDR=0.042), Eubacterium_ventriosum_group (PFDR=0.027), Christensenellaceae_R-7_group (PFDR=0.027), and norank_f__Lachnospiraceae (PFDR=0.015) significantly decreased in children with HTN compared to those with normal BP. Receiver operating characteristic analysis, net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were performed and showed that the genera norank_f__Lachnospiraceae and Dorea significantly enhanced the ability of body mass index to differentiate between children with HTN and those with normal BP (area under the receiver operating characteristic curve: 0.95, 95% confidence interval 0.91-0.99; NRI > 0; IDI = 0.12, P < 0.05). Phylogenetic Investigation of Communities by Reconstruction of Unobserved States showed that the mean proportions of cofactors and vitamins metabolism pathway and the glycan anabolism pathway were higher in children with HTN.

CONCLUSIONS

Disturbances in the abundance and diversity of gut microbiota may contribute to the development of HTN in children. Gut microbiota biomarkers may be of significant importance in the early identification and diagnosis of childhood HTN.

CLINICAL TRIAL NUMBER

Not applicable.

Role of X chromosome and dosage-compensation mechanisms in complex trait genetics

The X chromosome (chrX) is often excluded from genome-wide association studies due to its unique biology complicating the analysis and interpretation of genetic data. Consequently, the influence of chrX on human complex traits remains debated. Here, we systematically assessed the relevance of chrX and the effect of its biology on complex traits by analyzing 48 quantitative traits in 343,695 individuals in UK Biobank with replication in 412,181 individuals from FinnGen. We show that, in the general population, chrX contributes to complex trait heritability at a rate of 3% of the autosomal heritability, consistent with the amount of genetic variation observed in chrX. We find that a pronounced male bias in chrX heritability supports the presence of near-complete dosage compensation between sexes through X chromosome inactivation (XCI). However, we also find subtle yet plausible evidence of escape from XCI contributing to human height. Assuming full XCI, the observed chrX contribution to complex trait heritability in both sexes is greater than expected given the presence of only a single active copy of chrX, mirroring potential dosage compensation between chrX and the autosomes. We find this enhanced contribution attributable to systematically larger active allele effects from chrX compared to autosomes in both sexes, independent of allele frequency and variant deleteriousness. Together, these findings support a model in which the two dosage-compensation mechanisms work in concert to balance the influence of chrX across the population while preserving sex-specific differences at a manageable level. Overall, our study advocates for more comprehensive locus discovery efforts in chrX.

Calbindin 2 as a Novel Biomarker and Therapeutic Target for Abdominal Aortic Aneurysm: Integrative Analysis of Human Proteomes and Genetics

BACKGROUND

Abdominal aortic aneurysm (AAA) is a clinical life-threatening issue. No pharmacological treatments are currently approved for the prevention and treatment of AAA. Therefore, identifying novel biomarkers and therapeutic targets is crucial for improving AAA management and outcomes.

METHODS

To identify plasma proteins with potential causal effects on AAA, we integrated genetic evidence from proteome-wide Mendelian randomization, genetic correlation, and colocalization analysis. The role of identified proteins in AAA was further explored through the phenome-wide association study and mediation analysis. Multiomics data analysis, including bulk RNA sequencing, single-cell/single-nucleus RNA sequencing, and spatial transcriptomics, was employed to characterize the expression patterns of these proteins. Experimental validation was performed using an AAA model in apolipoprotein E-deficient mice infused with angiotensin II. Druggability analysis was conducted to identify drug candidates, which were tested in preclinical mouse models.

RESULTS

CALB2 (calbindin 2) was identified as having a causal effect on AAA and may influence the progression of AAA through the regulation of lipid metabolism. Multiomics analysis revealed that CALB2 is predominantly expressed in the mesothelial cells of adipose tissues. Inhibition of CALB2 in an AAA mouse model alleviated AAA progression. Druggability analysis identified lenalidomide and genistein as potential therapeutic candidates, and experiments confirmed their efficacy in preventing AAA development.

CONCLUSIONS

This study identifies CALB2 as being associated with an increased risk of AAA and suggests that i might be a novel biomarker and therapeutic molecule for AAA management. Lenalidomide and genistein hold promising potential as treatments for patients with AAA.

Mapping disease loci to biological processes via joint pleiotropic and epigenomic partitioning

Genome-wide association studies (GWAS) have identified thousands of disease-associated loci, yet their interpretation remains limited by the heterogeneity of underlying biological processes. We propose Joint Pleiotropic and Epigenomic Partitioning (J-PEP), a clustering framework that integrates pleiotropic SNP effects on auxiliary traits and tissue-specific epigenomic data to partition disease-associated loci into biologically distinct clusters. To benchmark J-PEP against existing methods, we introduce a metric-Pleiotropic and Epigenomic Prediction Accuracy (PEPA)-that evaluates how well the clusters predict SNP-to-trait and SNP-to-tissue associations using off-chromosome data, avoiding overfitting. Applying J-PEP to GWAS summary statistics for 165 diseases/traits (average N = 290 K ), we attained 16-30% higher PEPA than pleiotropic or epigenomic partitioning approaches with larger improvements for well-powered traits, consistent with simulations; these gains arise from J-PEP's tendency to upweight correlated structure-signals present in both auxiliary trait and tissue data-thereby emphasizing shared components. For type 2 diabetes (T2D), J-PEP identified clusters refining canonical pathological processes while revealing underexplored immune and developmental signals. For hypertension (HTN), J-PEP identified stromal and adrenal-endocrine processes that were not identified in prior analyses. For neutrophil count, J-PEP identified hematopoietic, hepatic-inflammatory, and neuroimmune processes, expanding biological interpretation beyond classical immune regulation. Notably, integrating single-cell chromatin accessibility data refined bulk-based clusters, enhancing cell-type resolution and specificity. For T2D, single-cell data refined a bulk endocrine cluster to pancreatic islet β -cells, consistent with established β -cell dysfunction in insulin deficiency; for HTN, single-cell data refined a bulk endocrine cluster to adrenal cortex cells, consistent with a GO enrichment for neutrophil-mediated inflammation that implicates feedback between aldosterone production in the adrenal gland and local immune signaling. In conclusion, J-PEP provides a principled framework for partitioning GWAS loci into interpretable, tissue-informed clusters that provide biological insights on complex disease.

Emerging antihypertensive therapies and cardiovascular, kidney, and metabolic outcomes: a Mendelian randomization study

AIMS

Emerging antihypertensive drug classes offer new opportunities to manage hypertension; however, their long-term effects on cardiovascular, kidney, and metabolic (CKM) outcomes remain to be elucidated. This study aims to explore the effects of phosphodiesterase type 5 inhibitors (PDE5i), soluble guanylate cyclase stimulators (sGCs), endothelin receptor antagonists (ERAs), and angiotensinogen inhibitors (AGTis) on a range of CKM outcomes.

METHODS AND RESULTS

Mendelian randomization (MR), summary-based MR (SMR), and colocalization analyses were applied to assess the drug effect on coronary artery disease (CAD), myocardial infarction (MI), ischaemic stroke, atrial fibrillation (AF), heart failure (HF), type 2 diabetes (T2D), and chronic kidney disease (CKD). Genetic association and gene expression summary data were obtained from the largest European-ancestry genome-wide association studies (GWAS) and the genotype-tissue expression version 8 for 29 tissues relevant to the outcomes' pathophysiology.Genetically predicted systolic blood pressure (SBP) reduction was associated with reduced risks of all outcomes. PDE5i was associated with reduced risks of CAD (OR per 10-mmHg decrease in SBP: 0.348[95% confidence interval (CI): 0.199-0.607]) and ischaemic stroke (0.588[0.453-0.763]). sGCs showed protective effects against CAD (0.332[0.236-0.469]), MI (0.238[0.168-0.337]), and CKD (0.55[0.398-0.761]). ERA and AGTi showed protective effects against CAD and ischaemic stroke. SMR and colocalization supported the association of gene expression levels of GUCY1A3 and PDE5A with CAD and MI risk.

CONCLUSION

Our study highlights the potential of PDE5i, sGCs, ERA, and AGTi in reducing cardiovascular and renal risks. These findings underscore the necessity for targeted clinical trials to validate the efficacy and safety of these therapies.

Body mass index modifies genetic susceptibility to high systolic blood pressure in adolescents and young adults: results from an 18-year longitudinal study

Genome-wide association studies (GWAS) in adults have identified single nucleotide polymorphisms (SNPs) associated with systolic blood pressure (SBP), but it is unclear whether the findings apply in youth. Further, the role of body mass index (BMI) in these associations is understudied. Our objective was to determine whether BMI modifies genetic susceptibility to high SBP in young people. The sample comprised 714 participants of European ancestry recruited in 1999-2000 from 10 Montreal-area high schools for a longitudinal study. SBP was measured at ages 12, 15, 17, 24, and 30. Blood and saliva samples were collected at ages 14, 20, and 25. Two evidence-based genetic risk scores (GRS) were constructed based on GWAS results in adults: GRS22 used 22 SNPs and GRS182 added 160 additional SNPs to GRS22. Sex-specific associations between each GRS and repeated measures of SBP were estimated using linear mixed models including BMI and a GRS*BMI product term. GRS182 explained a greater proportion of SBP variance than GRS22, and a greater proportion in females than males. The associations increased monotonically with BMI values between 22 kg/m2 and 35 kg/m2. Results indicate that BMI modifies the association between a GRS and SBP levels from adolescence to adulthood.

Association among blood pressure, antihypertensive drugs, and amyotrophic lateral sclerosis

BACKGROUND

 Amyotrophic lateral sclerosis (ALS) is a fatal and incurable neurodegenerative disease. The impacts of antihypertensive drugs and blood pressure (BP) on ALS are currently debatable.

OBJECTIVE

 To evaluate the causal relationship involving antihypertensive drugs, BP, and ALS through a Mendelian randomization (MR) analysis.

METHODS

 The causal relationship between BP and ALS was evaluated by a bidirectional two-sample MR analysis. Then, a sensitivity analysis was performed using a secondary BP genome-wide association study. The drug-target MR was employed to evaluate the impact of antihypertensive drugs on ALS. Furthermore, we used cis-expression quantitative trait loci (cis-eQTLs) data from brain tissue and blood to validate the positive results by a summary-based MR method.

RESULTS

 We found that an increment in systolic BP (SBP) could elevate the risk of ALS (inverse-variance weighted [IVW] odds ratio [OR] = 1.003; 95% confidence interval [95%CI]: 1.001-1.006; per 10-mmHg increment) and ALS might be protected by angiotensin-converting enzyme inhibitors (ACEIs; OR = 0.970; 95%CI: 0.956-0.984; p = 1.96 × 10-5; per 10-mmHg decrement). A causal relationship was not observed between diastolic BP and other antihypertensive drugs in ALS.

CONCLUSION

 In the present study, genetic support for elevated SBP serves as a risk factor for ALS. Besides, ACEIs hold promise as a candidate for ALS.

Thyroid dysfunction in MASLD: Results of a nationwide study

Background & Aims

Thyroid hormones are known to be potent modulators of hepatic metabolism and targeting the thyroid hormone receptor was recently approved as the first treatment for metabolic-associated steatotic liver disease (MASLD); however, the exact relationship between thyroid disorders and biopsy-confirmed MASLD remains unclear.

Methods

We conducted a nationwide matched case-control study leveraging data from the Swedish Epidemiology Strengthened by histoPathology Reports in Sweden (ESPRESSO) cohort, which includes liver biopsy data spanning from 1969 to 2017. We identified 12,172 patients with MASLD and 56,831 matched general-population controls, including 5,478 patients with MASLD with 10,682 sibling controls. Conditional logistic regression was used to calculate odds ratios for hypothyroidism and hyperthyroidism defined through ICD codes or prescription records. Causal inference was examined using Mendelian randomization (MR). Both observational and MR mediation analyses were performed to explore the roles of metabolic features.

Results

Hypothyroidism was associated with 1.68-fold increased odds of MASLD (95% CI 1.36-2.06). The association remained stable in the analysis using siblings as controls. However, in absolute terms, hypothyroidism was uncommon and seen in 2.5% in people with MASLD and in 1.4% of controls. Higher genetically predicted thyroid-stimulating hormone levels and hypothyroidism were linked to increased MASLD risk. Mediation analysis showed that metabolic disorders contributed ∼41% to this risk. Furthermore, there was an inverse association between hyperthyroidism and MASLD (adjusted odds ratio 0.17, 95% CI 0.05-0.56); however, the association did not reach statistical significance in the MR analysis.

Conclusions

The findings suggest that hypothyroidism is associated with a heightened risk of MASLD and that hyperthyroidism is potentially protective against MASLD.

Impact and implications

The approval by the US FDA of resmetirom, a thyroid hormone receptor β-selective agonist for non-cirrhotic metabolic dysfunction-associated steatohepatitis with stage 2-3 fibrosis, highlights the potential role of thyroid dysfunction in metabolic-associated steatotic liver disease (MASLD). This study identified hypothyroidism as a risk factor for MASLD, especially in men and individuals younger than 40 years, with the association peaking at non-cirrhotic fibrosis. Metabolic disorders mediated ∼41% of the hypothyroidism-MASLD association. Hyperthyroidism was potentially inversely associated with MASLD. Despite its low prevalence (2.5% in MASLD cases, 1.4% in controls), the population health impact of hypothyroidism warrants further attention.

Proteome-Wide Genetic Study in East Asians and Europeans Identified Multiple Therapeutic Targets for Ischemic Stroke

BACKGROUND

Analyses of genomic and proteomics data in prospective biobank studies in diverse populations may discover novel or repurposing drug targets for stroke.

METHODS

We extracted individual cis-protein quantitative trait locus for 2923 proteins measured using Olink Explore panel from a genome-wide association study in prospective China Kadoorie Biobank and UK Biobank, both established ≈20 years ago. These cis-protein quantitative trait loci were used in ancestry-specific 2-sample Mendelian randomization analyses of ischemic stroke (IS) in East Asians (n=22 664 cases) and Europeans (n=62 100 cases). We further undertook colocalization analyses to examine the shared causal variants of cis-protein quantitative trait locus with stroke, along with various downstream analyses (eg, phenome-wide association study, drug development lookups) to clarify mechanisms of action and druggability.

RESULTS

In Mendelian randomization analyses, the genetically predicted plasma levels of 10 proteins were significantly associated with IS in East Asians (n=2) and Europeans (n=9), with 6 proteins (FGF5 [fibroblast growth factor 5], TMPRSS5 [transmembrane protease serine 5], FURIN, F11 [coagulation factor XI], ALDH2 [aldehyde dehydrogenase 2], and ABO) showing positive and 4 (GRK5 [G protein-coupled receptor kinase 5], KIAA0319 [dyslexia-associated protein KIAA0319], PROCR [endothelial protein C receptor], and MMP12 [macrophage metalloelastase 12]) showing inverse associations, all directionally consistent between East Asians and Europeans. Colocalization analyses provided strong evidence (posterior probabilities for the H4 hypothesis ≥0.7) of shared genetic variants with IS for 9 out of 10 proteins (except ABO). Moreover, 8 proteins were also causally associated, in the expected directions, with systolic blood pressure (positive/inverse: 4/2), low-density lipoprotein cholesterol (1 positive), body mass index (1 inverse), type 2 diabetes (2/1), or atrial fibrillation (3/1). Phenome-wide association study analyses and lookups in knock-out mouse models confirmed their importance for IS or stroke-related traits (eg, hematologic phenotypes). Of these 10 proteins, 1 was not druggable (ABO), 3 had known primary (F11) or potentially repurposed (ALDH2, MMP12) drug targets for stroke, and 6 (PROCR, GRK5, FGF5, FURIN, KIAA0319, and TMPRSS5) had no evidence of any drug targets.

CONCLUSIONS

Proteogenomic investigation in diverse ancestry populations identified the causal relevance of 10 proteins for IS, with several being potentially novel or repurposed targets that could be prioritized for further investigation.

Blood Pressure Lowering and Risk of Cancer: Individual Participant-Level Data Meta-Analysis and Mendelian Randomization Studies

BACKGROUND

Pharmacologic blood pressure (BP) lowering is typically a lifelong treatment, and both clinicians and patients may have concerns about the long-term use of antihypertensive agents and the risk for cancer. However, evidence from randomized controlled trials (RCTs) regarding the effect of long-term pharmacologic BP lowering on the risk for new-onset cancer is limited, with most knowledge derived from observational studies.

OBJECTIVES

The aim of this study was to assess whether long-term BP lowering affects the risk for new-onset cancer, cause-specific cancer death, and selected site-specific cancers.

METHODS

Individual-level data from 42 RCTs were pooled using a one-stage individual participant data meta-analysis. The primary outcome was incident cancer of all types, and secondary outcomes were cause-specific cancer death and selected site-specific cancers. Prespecified subgroup analyses were conducted to assess the heterogeneity of the BP-lowering effect by baseline variables and over follow-up time. Cox proportional hazards regression, stratified by trial, was used for the statistical analysis. For site-specific cancers, analyses were complemented with Mendelian randomization, using naturally randomized genetic variants associated with BP lowering to mimic the design of a long-term RCT.

RESULTS

Data from 314,016 randomly allocated participants without known cancer at baseline were analyzed. Over a median follow-up of 4 years (Q1-Q3: 3-5 years), 17,954 participants (5.7%) developed cancer, and 4,878 (1.5%) died of cancer. In the individual participant data meta-analysis, no associations were found between reductions in systolic or diastolic BP and cancer risk (HR per 5 mm Hg reduction in systolic BP: 1.03 [95% CI: 0.99-1.06]; HR per 3 mm Hg reduction in diastolic BP: 1.03 [95% CI: 0.98-1.07]). No changes in relative risk for incident cancer were observed over follow-up time, nor was there evidence of heterogeneity in treatment effects across baseline subgroups. No effect on cause-specific cancer death was found. For site-specific cancers, no evidence of an effect was observed, except a possible link with lung cancer risk (HR for systolic BP reduction: 1.17; 99.5% CI: 1.02-1.32). Mendelian randomization studies showed no association between systolic or diastolic BP reduction and site-specific cancers, including overall lung cancer and its subtypes.

CONCLUSIONS

Randomized data analysis provided no evidence to indicate that pharmacologic BP lowering has a substantial impact, either increasing or decreasing, on the risk for incident cancer, cause-specific cancer death, or selected site-specific cancers.

Evidence supporting the role of hypertension in the onset of migraine

BACKGROUND

The association between hypertension and migraine remains unclear.

OBJECTIVE

The aim of this study employ multi-layered evidence chain that revealed the association between hypertension and migraine.

METHODS

We first strictly included data from the NHANES 1999-2004 population and applied logistic regression, subgroup analysis and RCS to assess the correlation between hypertension, SBP, DBP and migraine. Meanwhile, LDSC and Mendelian randomization were conducted based on the GWAS to determine the causal relationship between hypertension and migraine. Inverse-variance weighted (IVW) was used as the primary method. Sensitivity analysis and Colocalization analysis were performed to confirm the robustness of the results. LDSC validated the genetic correlation between traits. Enrichment analysis revealed their underlying biological mechanisms.

RESULTS

After strict inclusion in NHANES, 10,743 participants were included. The logistic regression showed a significant correlation between hypertension (OR = 1.21 [95% CI, 1.08-1.36], FDR < 0.001)、DBP (OR = 1.01 [95% CI, 1.01-1.02], FDR < 0.001) and migraine. This association did not show significant group differences in subgroup. The MR results further supported the existence of a significant causal relationship between hypertension (OR = 1.77 [95% CI, 1.43-2.30], FDR < 0.001)、DBP (OR = 1.02 [95% CI, 1.01-1.03], FDR < 0.001) and migraine onset. Additionally, the RCS analysis showed a linear relationship (P non-linear = 0.897) between the two. The LDSC result showed a significant genetic correlation between the two (Rg = 0.1092, SE = 0.028, P < 0.001).

CONCLUSION

The development of migraine caused by hypertension is mainly realized through high DBP.

JointPRS: A data-adaptive framework for multi-population genetic risk prediction incorporating genetic correlation

Genetic risk prediction for non-European populations is hindered by limited Genome-Wide Association Study (GWAS) sample sizes and small tuning datasets. We propose JointPRS, a data-adaptive framework that leverages genetic correlations across multiple populations using GWAS summary statistics. It achieves accurate predictions without individual-level tuning data and remains effective in the presence of a small tuning set thanks to its data-adaptive approach. Through extensive simulations and real data applications to 22 quantitative and four binary traits in five continental populations evaluated using the UK Biobank (UKBB) and All of Us (AoU), JointPRS consistently outperforms six state-of-the-art methods across three data scenarios: no tuning data, same-cohort tuning and testing, and cross-cohort tuning and testing. Notably, in the Admixed American population, JointPRS improves lipid trait prediction in AoU by 6.46%-172.00% compared to the other existing methods.

Evidence to shared genetic correlation of ischemic stroke and intracerebral hemorrhage and cardiovascular related traits

BACKGROUND

Previous studies have demonstrated the genetic basis of stroke and also revealed their genetic correlation with some cardiovascular related diseases or traits at the entire genome, which, however, would not give the answer which regions may mainly account for the genetic overlap. This study aims to identify specific genetic loci that contribute to the shared genetic basis between ischemic stroke subtypes and common cardiovascular traits.

METHODS

We used Local Analysis of [co]Variant Annotation (LAVA), a recent developed local genetic correlation method, to perform a system local genetic correlation analysis on GWAS summary data of two major subtypes of stroke, including any ischemic stroke (AIS) and intracerebral hemorrhage (ICH), and ten common cardiovascular related diseases or traits (CRTs). We further used colocalization analysis to explore potential shared causal genes in loci with significant local genetic correlation. In addition, we also performed Transcriptome-wide association (TWAS) analysis and fine-mapping for each phenotype to functionally annotate significant loci.

RESULTS

LAVA analysis identified a total of 3 significant local genetic correlations (Bonferroni-adjusted P <  0.05) across 3 chromosomes between AIS and systolic blood pressure (SBP), AIS and hypertension (HT), and ICH and body mass index (BMI), among which locus 7.24 explicated to harbor a shared causal variant for AIS and SBP. TWIST1 in locus 7.24 was defined to be nominally associated with SBP, but not for AIS. Fine-mapping analysis also only identified TWIST1 a credible causal gene for BMI.

CONCLUSIONS

Our study revealed the local genetic correlations between two stroke subtypes and ten common CRTs. Gene-level analyses indicated that biological explanations underlying these identified local genetic correlations may existed elsewhere beyond a common pattern of genetic-gene expression regulation.

A multi-trait genome-wide association study of coronary artery disease and subclinical atherosclerosis traits

Measures of subclinical atherosclerosis, such as coronary artery calcification (CAC) and carotid intima-media thickness (CIMT), reflect the underlying pathophysiology of coronary artery disease (CAD) and are genetically correlated with CAD and related risk factors. Leveraging summary statistics from genome-wide association studies of CAD, CIMT, CAC, type 2 diabetes, low-density lipoprotein cholesterol, and systolic blood pressure, we performed 15 separate multi-trait GWAS to identify shared susceptibility loci and elucidate the pleiotropic architecture underlying atherosclerosis. We identified 442 shared risk loci across all analyses that met an experiment-wide Bonferroni threshold of 3.3 × 10-9, uncovering 195 novel atherosclerosis loci. Multi-trait colocalization confirmed a shared causal signal in 25 shared novel loci for atherosclerosis. Trait-eQTL colocalization identified evidence of a shared causal signal in arterial, subcutaneous adipose, and cardiac tissues, implicating genes such as PRRX2, BNC2, CLIC4, SCAI, and PPP6C, and pathways related to vascular remodeling, inflammation, and metabolic regulation.

A Mendelian randomization analysis of cardiac MRI measurements as surrogate outcomes for heart failure and atrial fibrillation

BACKGROUND

Drug development and disease prevention of heart failure (HF) and atrial fibrillation (AF) are impeded by a lack of robust early-stage surrogates. We determined to what extent cardiac magnetic resonance (CMR) measurements act as surrogates for the development of HF or AF.

METHODS

Genetic data were sourced on the association with 21 atrial and ventricular CMR measurements. Mendelian randomization was used to determine CMR associations with AF, HF, non-ischaemic cardiomyopathy (NICM), and dilated cardiomyopathy (DCM), noting that the definition of NICM includes DCM as a subset. Additionally, for the CMR surrogates of AF and HF, we explored their association with non-cardiac traits potentially influenced by cardiac disease liability.

RESULTS

In total we find that 7 CMR measures (biventricular ejection fraction (EF) and end-systolic volume (ESV), as well as LV systolic volume (SV), end-diastolic volume (EDV), and mass to volume ratio (MVR)) associate with the development of HF, 5 with the development of NICM (biventricular EDV and ESV, LV-EF), 7 with DCM (biventricular EF, ESV, EDV, and LV end-diastolic mass (EDM), and 3 associate with AF (LV-ESV, RV-EF, RV-ESV). Higher EF of both ventricles associate with lower risk of HF and DCM, with biventricular ESV associating with all four cardiac outcomes. Higher values of biventricular EDV associate with lower risk of HF, and DCM. Exploring the associations of these CMR cardiac disease surrogates with non-cardiac traits confirms a strong link with diastolic blood pressure, as well as more specific associations with lung function (LV-ESV), HbA1c (LV-EDM), and type 2 diabetes (LV-SV).

CONCLUSIONS

The current paper identifies key CMR measurements that may act as surrogate endpoints for the development of HF (including NICM and DCM) or AF.

Modularized Genes in an Adrenal Pathway Reveal a Novel Mechanism in Hypertension Pathogenesis

Human epidemiological studies have statistically localized a multitude of quantitative trait loci (QTLs) for blood pressure (BP). However, their potential pathogenic mechanisms causing hypertension remain mysterious. To fill this void, we utilized congenic knock-in genetics to physiologically analyze the BP effects of individual and combinational QTLs. The effect magnitude from a single QTL in vivo ranged from 33.8 to 59.8%. 'Double' and multiple combinations of QTLs exhibited the same BP impact as a single QTL alone. Consequently, the products of these QTLs seemed to belong to the same pathway involved in physiological BP regulations. From this, we identified a novel pathway of hypertension pathogenesis in vivo controlled by the CUE domain containing 1 protein (Cuedc1). This pathway physiologically modulates blood pressure, aldosterone production, and renal and cardiac functions. CUEDC1 originated from common mammalian ancestors, partly explaining similar blood pressures between humans and rodents on this shared mechanistic basis. A translation of CUEDC1 into diagnostic and treatment applications to humans seems individualized and mechanistic because humans and rats may utilize the same BP-regulating mechanisms involving CUEDC1. The future sustainability of post-GWAS will depend on a balanced and robust 'ecosystem' provided by model studies that are founded on the physiologies and mechanisms of BP regulations in vivo.

Genetic and training adaptations in the Haenyeo divers of Jeju, Korea

Natural selection and relative isolation have shaped the genetics and physiology of unique human populations from Greenland to Tibet. Another such population is the Haenyeo, the all-female Korean divers renowned for their remarkable diving abilities in frigid waters. Apnea diving induces considerable physiological strain, particularly in females diving throughout pregnancy. In this study, we explore the hypothesis that breath-hold diving has shaped physiological and genetic traits in the Haenyeo. We identified pronounced bradycardia during diving, a likely training effect. We paired natural selection and genetic association analyses to investigate adaptive genetic variation that may mitigate the effects of diving on pregnancy through an associated reduction of diastolic blood pressure. Finally, we identified positively selected variation in a gene previously associated with cold water tolerance, which may contribute to reduced hypothermia susceptibility. These findings highlight the importance of traditional diving populations for understanding genetic and physiological adaptation.

Meta-prediction of coronary artery disease risk

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide, and accurately predicting individual risk is critical for prevention. Here we aimed to integrate unmodifiable risk factors, such as age and genetics, with modifiable risk factors, such as clinical and biometric measurements, into a meta-prediction framework that produces actionable and personalized risk estimates. In the initial development of the model, ~2,000 predictive features were considered, including demographic data, lifestyle factors, physical measurements, laboratory tests, medication usage, diagnoses and genetics. To power our meta-prediction approach, we stratified the UK Biobank into two primary cohorts: first, a prevalent CAD cohort used to train predictive models for cross-sectional prediction at baseline and prospective estimation of contributing risk factor levels and diagnoses (baseline models) and, second, an incident CAD cohort using, in part, these baseline models as meta-features to train a final CAD incident risk prediction model. The resultant 10-year incident CAD risk model, composed of 15 derived meta-features with multiple embedded polygenic risk scores, achieves an area under the curve of 0.84. In an independent test cohort from the All of Us research program, this model achieved an area under the curve of 0.81 for predicting 10-year incident CAD risk, outperforming standard clinical scores and previously developed integrative models. Moreover, this framework enables the generation of individualized risk reduction profiles by quantifying the potential impact of standard clinical interventions. Notably, genetic risk influences the extent to which these interventions reduce overall CAD risk, allowing for tailored prevention strategies.

Regulation of blood pressure by METTL3 via RUNX1b-eNOS pathway in endothelial cells in mice

AIMS

Endothelial cells regulate vascular tone to control the blood pressure (BP) by producing both relaxing and contracting factors. Previously, we identified methyltransferase-like 3 (METTL3), a primary N6-methyladenosine (m6A) methyltransferase, as a key player in alleviating endothelial atherogenic progression. However, its involvement in BP regulation remains unclear.

METHODS AND RESULTS

To evaluate the role of METTL3 in vivo, mice with EC specific METTL3 deficiency (EC-Mettl3KO) with or without Ang II infusion were used to create a hypertensive model. Functional and MeRIP sequencing analysis was performed to explore the mechanism of METTL3-mediated hypertension. We observed a reduction in endothelial METTL3 activity by Ang II in vitro and in vivo. Endothelial METTL3-deficient mice exhibited higher BP than controls, with no gender disparity observed. The subsequent study was primarily conducted in male mice. Through m6A sequencing and functional analysis, we identified m6A modification of various RUNX1 monomers resulted in endothelial dysfunction. Mutations in the 3'UTR region of RUNX1b abolished its luciferase reporter activity and enhanced eNOS promoter luciferase reporter activity with or without METTL3 overexpression. Overexpression of METTL3 by adeno-associated virus reduced Ang II-induced BP elevation.

CONCLUSION

This study reveals that METTL3 alleviates hypertension through m6A-dependent stabilization of RUNX1b mRNA, leading to up-regulation of eNOS, thus underscoring the pivotal role of RNA transcriptomics in the regulation of hypertension.

Unbiased causal inference with Mendelian randomization and covariate-adjusted GWAS data

Mendelian randomization (MR) facilitates causal inference with observational data using publicly available genome-wide association study (GWAS) results. In a GWAS, one or more heritable covariates may be adjusted for to estimate the direct effects of SNPs on a focal trait or to improve statistical power, which may introduce collider bias in SNP-trait association estimates, thus affecting downstream MR analyses. Numerical studies suggested that using covariate-adjusted GWAS summary data might introduce bias in univariable Mendelian randomization (UVMR), which can be mitigated by multivariable Mendelian randomization (MVMR). However, it remains unclear and even mysterious why/how MVMR works; a rigorous theory is needed to explain and substantiate the above empirical observation. In this paper, we derive some analytical results when multiple covariates are adjusted for in the GWAS of exposure and/or the GWAS of outcome, thus supporting and explaining the empirical results. Our analytical results offer insights to how bias arises in UVMR and how it is avoided in MVMR, regardless of whether collider bias is present. We also consider applying UVMR or MVMR methods after collider-bias correction. We conducted extensive simulations to demonstrate that with covariate-adjusted GWAS summary data, MVMR had an advantage over UVMR by producing nearly unbiased causal estimates; however, in some situations it is advantageous to apply UVMR after bias correction. In real data analyses of the GWAS data with body mass index (BMI) being adjusted for metabolomic principal components, we examined the causal effect of BMI on blood pressure, confirming the above points.

Genetic causal effects of multi-site chronic pain on post-traumatic stress disorder: Evidence from a two-sample, two-step Mendelian randomization study

BACKGROUND

Existing evidence supports a correlation between multi-site chronic pain and post-traumatic stress disorder (PTSD), but it is yet to be determined if this correlation is causal and in what direction the causation works.

METHODS

Applying two-sample Mendelian randomization (MR) analysis to data from available genome-wide association studies in populations of European ancestry, we estimated the causal association between multi-site chronic pain and no pain versus PTSD. Moreover, we used multivariable and mediation MR analysis to assess the mediating effects of 13 lifestyle factors or diseases on the causal relationship between multi-site chronic pain and PTSD. The MR analyses were mainly conducted with the inverse variance weighted (IVW) method, followed by various sensitivity and validation analyses.

RESULTS

Multi-site chronic pain dramatically increases the risk of developing PTSD (odds ratio [OR]IVW = 2.39, 95 % confidence interval [CI] = 1.72-3.31, p = 2.10 × 10-7), and no pain significantly reduces the risk of developing PTSD (ORIVW = 0.12, 95 % CI = 0.05-0.30, p = 3.14 × 10-6). Multivariable MR found that 13 potential confounding factors do not influence the causal effect of multi-site chronic pain on PTSD. Moreover, body mass index (BMI) (6.98 %), educational attainment (8.79 %), major depressive disorder (MDD) (36.98 %) and insomnia (27.25 %) mediate the causal connection between multi-site chronic pain and PTSD.

CONCLUSION

Overall, individuals with multi-site chronic pain may be at a higher risk of developing PTSD, and this risk is partially influenced by the pathways involving BMI, educational attainment, MDD, and insomnia. These factors offer potential targets for therapeutic interventions.

An Alternatively Translated Isoform of PPARG Suggests AF-1 Domain Inhibition as an Insulin Sensitization Target

ARTICLE HIGHLIGHTS

Genetic screens were performed across PPARG to study how disruptive mutations across the full coding sequence affect function. An alternative translational start site in PPARG generates a truncated isoform, peroxisome proliferator-activated receptor γ (PPARγ) M135, which lacks the N-terminal activation function 1 (AF-1) domain and shows increased agonist-induced transactivation of target genes. In human carriers of rare PPARG variants, AF-1 domain-disrupting genetic variants increase agonist-induced PPARγ activity and decrease metabolic syndrome severity. Targeting the AF-1 domain is a potential therapeutic strategy for insulin sensitization.

Associations of Lipid-Lowering Drugs With Blood Pressure and Fasting Glucose: A Mendelian Randomization Study

BACKGROUND

Observational studies have linked LDL-C (low-density lipoprotein-cholesterol)-lowering drugs with lower blood pressure (BP) and higher fasting glucose, but the causality remains unclear. We conducted a drug target Mendelian randomization study to assess the causal associations of genetically proxied inhibition of HMGCR (3-hydroxy-3-methylglutaryl coenzyme A reductase), PCSK9 (proprotein convertase subtilisin/kexin type 9), and NPC1L1 (Niemann-Pick C1-Like 1) with BP and fasting glucose.

METHODS

Single-nucleotide polymorphisms in HMGCR, NPC1L1, and PCSK9 associated with LDL-C in a genome-wide association study meta-analysis from the Global Lipid Genetics Consortium (173 082 European individuals) were used to proxy LDL-C-lowering drug targets. BP and fasting glucose data were obtained from genome-wide association studies conducted by the International Consortium of Blood Pressure (757 601 European participants) and the Glucose and Insulin-related Traits Consortium (58 074 European participants). We used the inverse-variance weighted method and a series of sensitivity analyses for assessment.

RESULTS

Genetically proxied inhibition of HMGCR was negatively associated with systolic BP (β, -0.81 [95% CI, -1.26 to -0.37 mm Hg]; P=3.72×10-4) and diastolic BP (β, -1.58 [95% CI, -2.24 to -0.91 mm Hg]; P=3.23×10-6). Conversely, we observed a positive association between genetically proxied inhibition of HMGCR and high fasting glucose (β, 0.13 [95% CI, 0.08-0.17 mmol/L]; P=4.25×10-8). However, there was no association of PCSK9 and NPC1L1 inhibition with BP or fasting glucose.

CONCLUSIONS

Genetically proxied inhibition of HMGCR was significantly associated with low BP and high fasting glucose, while there was no effect of PCSK9 and NPC1L1 inhibition on BP or fasting glucose.

Roles of sensory receptors in non-sensory organs: the kidney and beyond

Olfactory receptors (ORs), taste receptors and opsins are well-known for their pivotal roles in mediating the senses of smell, taste and sight, respectively. However, in the past two decades, research has shown that these sensory receptors also regulate physiological processes in a variety of non-sensory tissues. Although ORs, taste receptors and opsins have all been shown to have physiological roles beyond their traditional locations, most work in the kidney has focused on ORs. To date, renal ORs have been shown to have roles in blood pressure regulation (OLFR78 and OLFR558) and glucose homeostasis (OLFR1393). However, sensory receptors remain drastically understudied outside of traditional sensory systems, in part because of inherent challenges in studying these receptors. Increased knowledge of the physiological and pathophysiological roles of sensory receptors has the potential to substantially improve understanding of the function of numerous organs and systems, including the kidney. In addition, most sensory receptors are G protein-coupled receptors, which are considered to be the most druggable class of proteins, and thus could potentially be exploited as future therapeutic targets.

Inhibition of Putative Ibrutinib Targets Promotes Atrial Fibrillation, Conduction Blocks, and Proarrhythmic Electrocardiogram Indices: A Mendelian Randomization Analysis

Background

The mechanism by which ibrutinib, a Bruton's tyrosine kinase inhibitor, can elevate the risk of arrhythmias is not fully elucidated. In this study, we explored how inhibition of off-target kinases can contribute to this phenomenon.

Methods

We performed a Mendelian randomization analysis to examine the causal associations between genetically proxied inhibition of six putative ibrutinib drug targets (ErbB2/HER2, CSK, JAK3, TEC, BLK, and PLCG2) and the atrial fibrillation (AF) risk, proarrhythmic ECG indices, and cardiometabolic traits and diseases. Inverse-variance weighted random-effects models and Wald ratio were used to examine the associations between genetically proxied inhibition of these drug targets and the risk of outcomes. Colocalization analyses were employed to examine the robustness of the causally significant findings. ELISAs were used to measure ErbB2 levels in intracardiac plasma samples.

Results

Genetically proxied ErbB2 inhibition was associated with an increased AF risk, higher P wave terminal force, and prolonged QTc interval. Patients with AF had significantly higher intracardiac ErbB2 levels compared with patients with paroxysmal supraventricular tachycardia. CSK inhibition prolonged the QRS duration, decreased the QTc interval, and was potentially linked to conduction blocks. PLCG2 inhibition led to decreased P wave terminal force, shorter QTc interval, and increased risk of left bundle branch block. BLK inhibition shortened the QTc interval and was also associated with atrioventricular block.

Conclusion

The off-target effects and downstream targets of ibrutinib, including CSK, PLCG2, ERBB2, TEC, and BLK, may lead to cardiac electrical homeostasis imbalances and lethal cardiovascular diseases. Using drugs that inhibit these targets should be given extra caution.

Role of Inflammatory Biomarkers in Mediating Causal Effect of Life Course Body Composition on Hypertension

BACKGROUND

The mediating role of inflammatory biomarkers in the causal relationship between body composition and hypertension remains unclear and requires further investigation.

METHODS

This study used a combination of retrospective observational analysis and Mendelian randomization approaches. Observational data were derived from 4717 Chinese children and adolescents aged 6 to 18 years who underwent dual-energy X-ray absorptiometry to assess body composition. Mendelian randomization analyses utilized summary statistics from large-scale data sets, including UK Biobank, deCODE2021, International Consortium of Blood Pressure, FinnGen, and other consortia. The inflammatory biomarkers included leptin, insulin, adiponectin, osteocalcin, FGF23 (fibroblast growth factor 23), and PTH (parathyroid hormone).

RESULTS

The observational analysis revealed that increased fat mass positively influenced diastolic blood pressure through osteocalcin, while fat-free mass had an inverse effect. Insulin mediated the association between fat mass and systolic blood pressure, diastolic blood pressure, and hypertension, with additional indirect effects observed for PTH (all P<0.05). The Mendelian randomization analyses demonstrated a causal relationship between childhood body mass index and hypertension mediated by insulin (indirect effect: odds ratio, 0.87 [95% CI, 0.78-0.97]) and adiponectin (odds ratio, 1.13 [95% CI, 1.04-1.23]). Adiponectin mediated the effects of fat-free mass (odds ratio, 0.81 [95% CI, 0.71-0.93]) and fat mass (odds ratio, 1.30 [95% CI, 1.11-1.51]) on hypertension. Leptin, adiponectin, and insulin also mediated the causal effects of body composition on systolic blood pressure, diastolic blood pressure, and hypertension.

CONCLUSIONS

These findings indicate that body composition influences blood pressure through distinct inflammatory biomarkers. Targeting inflammatory biomarkers may provide tailored strategies for managing body composition and hypertension.

Sex-Biased Admixture Followed by Isolation and Adaptive Evolution Shaped the Genomic and Blood Pressure Diversity of the LopNur People

The LopNur people are an ethnic group living on the edge of the Taklamakan Desert, and they are believed to demonstrate a unique genetic makeup due to their isolation and limited contact with neighboring populations. However, a lack of genetic studies on the LopNur people has resulted in limited knowledge about their ancestral origins and demographic history. Here, we conducted the first whole-genome sequencing study of 164 LopNur individuals (LOP) to gain insight into their genetic history and adaptive evolution in an isolated desert area. Our analysis revealed that the present-day LOP have experienced a complex history of admixture followed by long-term isolation, with their ancestry derived from East Asia (∼41.46%), West Eurasia (∼26.43%), Siberia (∼24.27%), and South Asia (∼7.82%). Notably, a remarkable sex-biased admixture occurred between Western males and Eastern females. In addition to complex admixture followed by long-term geographic isolation and further recent migrations, adaptive evolution jointly formed the gene pool and phenotypic diversity of the present-day LOP. Intriguingly, our analysis suggests that the USP35-GAB2 region may be correlated with blood pressure in LOP, based on a joint analysis of genomics and blood pressure data. Moreover, we identified two variants, rs7387065, and rs2229437, located on CSMD1 and PRCP, respectively. These variants exhibited frequency differences between Asian and European populations and were reported to be associated with antihypertensive drug absorption. Our results provide new insight into the complex history of the LOP, an admixed and isolated ethnic group residing at the crossroads of East and West, a case with ancient admixture, long-term isolation, adaptive evolution, and sex-biased gene flow.

A genome-wide association study of imaging-defined atherosclerosis

Imaging-defined atherosclerosis represents an intermediate phenotype of atherosclerotic cardiovascular disease (ASCVD). Genome-wide association studies (GWAS) on directly measured coronary plaques using coronary computed tomography angiography (CCTA) are scarce. In the so far largest population-based cohort with CCTA data, we performed a GWAS on coronary plaque burden as determined by the segment involvement score (SIS) in 24,811 European individuals. We identified 20 significant independent genetic markers for SIS, three of which were found in loci not implicated in ASCVD before. Further GWAS on coronary artery calcification showed similar results to that of SIS, whereas a GWAS on ultrasound-assessed carotid plaques identified both shared and non-shared loci with SIS. In two-sample Mendelian randomization studies using SIS-associated markers in UK Biobank and CARDIoGRAMplusC4D, one extra coronary segment with atherosclerosis corresponded to 1.8-fold increased odds of myocardial infarction. This GWAS data can aid future studies of causal pathways in ASCVD.

Adult Height, Cardiovascular Disease, and the Underlying Mechanism: A Comprehensive Epidemiological and Genetic Analysis

BACKGROUND

Adult height measures the complete growth of an individual and influences the development of cardiovascular disease (CVD). Despite recent within-sibling studies that have suggested minimal effects from environmental confounders, biological mechanisms underlying the height-CVD relationship remain elusive.

METHODS

Leveraging the large-scale UK Biobank data set and summary statistics from the latest genome-wide association studies, we reevaluated the effect of height on 8 major CVD subtypes. Phenotypic associations were determined using Cox proportional hazard analysis. Putative causal relationships were assessed using univariable Mendelian randomization. Mediation analysis and 2-step Mendelian randomization were further performed to investigate the mediation effect of 15 common cardiometabolic or pulmonary risk factors.

RESULTS

Height was consistently associated with a decreased risk of coronary artery disease (CAD), confirmed in epidemiological (hazard ratio, 0.90; 95% confidence interval [CI], 0.88-0.91) and genetic (odds ratio, 0.89, 95% CI, 0.86-0.92) analysis. Forced vital capacity was identified as the most significant mediator for the height-CAD relationship in epidemiological (proportion-mediated, 65.6%; 95% CI, 53.1%-78.0%) and genetic (proportion-mediated, 46.2%; 95% CI, 5.0%-87.5%) analysis. Notably, obesity, and blood pressure, lipid, and C-reactive protein levels also exhibited significant mediatory effects. Despite a consistent risk effect of height on atrial fibrillation and venous thromboembolism, no promising mediator was identified.

CONCLUSIONS

Our study confirms the health effects of height on CAD, atrial fibrillation, and venous thromboembolism and emphasizes forced vital capacity as the primary pathway that links height to CAD. Importantly, it indicates that the CAD risk associated with nonmodifiable height could be mitigated through enhanced lung function and cardiometabolic conditions.

Association between blood pressure traits, hypertension, antihypertensive drugs and calcific aortic valve stenosis: a mendelian randomization study

Background

Hypertension is associated with an increased risk of calcific aortic valve stenosis (CAVS). However, the directionality of causation between blood pressure traits and aortic stenosis is unclear, as is the benefit of antihypertensive drugs for CAVS.

Methods

Using genome-wide association studies (GWAS) summary statistics, we performed bidirectional two-sample univariable mendelian randomization (UVMR) to assess the causal associations of systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP) with CAVS. Multivariable mendelian randomization (MVMR) was conducted to evaluate the direct effect of hypertension on CAVS, adjusting for confounders. Drug target mendelian randomization (MR) and summary-level MR (SMR) were used to estimate the effects of 12 classes of antihypertensive drugs and their target genes on CAVS risk. Inverse variance weighting was the primary MR method, with sensitivity analyses to validate results.

Results

UVMR showed SBP, DBP, and PP have causal effects on CAVS, with no significant reverse causality. MVMR confirmed the causality between hypertension and CAVS after adjusting for confounders. Drug-target MR analyses indicated that calcium channel blockers (CCBs), loop diuretics, and thiazide diuretics via SBP lowering exerted protective effects on CAVS risk. SMR analysis showed that the CCBs target gene CACNA2D2 and ARBs target gene AGTR1 were positively associated with CAVS risk, while diuretics target genes SLC12A5 and SLC12A1 were negatively associated with aortic stenosis risk.

Conclusions

Hypertension has a causal relationship with CAVS. Managing SBP in hypertensive patients with CCBs may prevent CAVS. ARBs might exert protective effects on CAVS independent of blood pressure reduction. The relationship between diuretics and CAVS is complex, with opposite effects through different mechanisms.

Nanoformulation of valsartan-loaded tablet attenuates L-NAME-induced hypertension: role of Nrf2/PPARγ/AT1 signaling pathway

Hypertension is the most common entity globally, marked by high prevalence and heterogeneous pathophysiology. Oxidative stress is a crucial area of investigation among potential etiologies. We examined the hypothesis that blocking the angiotensin type 1 (AT1) receptor with valsartan (VST) in self-nanoemulsifying delivery systems (SNEDS) and loads in liquisolid tablets (LST-1) or valsartan and hydrochlorothiazide (VST/HCTZ) in SNEDS and loads in liquisolid tablets (LST-2) in comparison with non-SNEDS liquisolid tablets (DCT-3 and DCT-4) would lead to an improvement in hypertension management. The present study aims to explore the molecular mechanisms underlying their effect in N(G)-nitro-L-arginine methyl ester (L-NAME)-induced hypertensive rats. Male Sprague-Dawley rats were given L-NAME (40 mg/kg/day) orally for three weeks to inhibit the endogenous synthesis of nitric oxide (NO). Concurrent treatment with VST or VST/HCTZ liquisolid tablets (20 mg/kg/day for three weeks) resulted in lowering blood pressure (BP), reversing the L-NAME-induced serum NO suppression, enhancing lipid profile, and improving oxidative status. The antioxidant defense of paraoxonase was significantly increased in the LST-1- and LST-2-treated rats compared to the L-NAME-treated rats by 135% and 90%, respectively. Furthermore, SNEDS-loaded VST or SNEDS-loaded VST/HCTZ liquisolid tablets significantly lowered the elevated level of AT1 (P < 0.05), showed a marked Nrf2 expression (P < 0.01) and overexpressed PPARγ (P < 0.05), and suppressed iNOS expression (P < 0.0001). These results highlight the remarkable benefits of the novel formula, "SNEDS-loaded VST and SNEDS-loaded VST/HCTZ," as an alternative therapy in treating hypertension and its complications.

Leveraging large-scale biobank EHRs to enhance pharmacogenetics of cardiometabolic disease medications

Electronic health records (EHRs) coupled with large-scale biobanks offer great promises to unravel the genetic underpinnings of treatment efficacy. However, medication-induced biomarker trajectories stemming from such records remain poorly studied. Here, we extract clinical and medication prescription data from EHRs and conduct GWAS and rare variant burden tests in the UK Biobank (discovery) and the All of Us program (replication) on ten cardiometabolic drug response outcomes including lipid response to statins, HbA1c response to metformin and blood pressure response to antihypertensives (N = 932-28,880). Our discovery analyses in participants of European ancestry recover previously reported pharmacogenetic signals at genome-wide significance level (APOE, LPA and SLCO1B1) and a novel rare variant association in GIMAP5 with HbA1c response to metformin. Importantly, these associations are treatment-specific and not associated with biomarker progression in medication-naive individuals. We also found polygenic risk scores to predict drug response, though they explained less than 2% of the variance. In summary, we present an EHR-based framework to study the genetics of drug response and systematically investigated the common and rare pharmacogenetic contribution to cardiometabolic drug response phenotypes in 41,732 UK Biobank and 14,277 All of Us participants.

Leveraging pleiotropic clustering to address high proportion correlated horizontal pleiotropy in Mendelian randomization studies

Mendelian randomization harnesses genetic variants as instrumental variables to infer causal relationships between exposures and outcomes. However, certain genetic variants can affect both the exposure and the outcome through a shared factor. This phenomenon, called correlated horizontal pleiotropy, may result in false-positive causal findings. Here, we propose a Pleiotropic Clustering framework for Mendelian randomization, PCMR. PCMR detects correlated horizontal pleiotropy and extends the zero modal pleiotropy assumption to enhance causal inference in trait pairs with correlated horizontal pleiotropic variants. Simulations show that PCMR can effectively detect correlated horizontal pleiotropy and avoid false positives in the presence of correlated horizontal pleiotropic variants, even when they constitute a high proportion of the variants connecting both traits (e.g., 30-40%). In datasets consisting of 48 exposure-common disease pairs, PCMR detects horizontal correlated pleiotropy in 7 out of the exposure-common disease pairs, and avoids detecting false positive causal links. Additionally, PCMR can facilitate the integration of biological information to exclude correlated horizontal pleiotropic variants, enhancing causal inference. We apply PCMR to study causal relationships between three common psychiatric disorders as examples.

Heterogeneous effects of genetic variants and traits associated with fasting insulin on cardiometabolic outcomes

Elevated fasting insulin levels (FI), indicative of altered insulin secretion and sensitivity, may precede type 2 diabetes (T2D) and cardiovascular disease onset. In this study, we group FI-associated genetic variants based on their genetic and phenotypic similarities and identify seven clusters with distinct mechanisms contributing to elevated FI levels. Clusters fall into two types: "non-diabetogenic hyperinsulinemia," where clusters are not associated with increased T2D risk, and "diabetogenic hyperinsulinemia," where T2D associations are driven by body fat distribution, liver function, circulating lipids, or inflammation. In over 1.1 million multi-ancestry individuals, we demonstrated that diabetogenic hyperinsulinemia cluster-specific polygenic scores exhibit varying risks for cardiovascular conditions, including coronary artery disease, myocardial infarction (MI), and stroke. Notably, the visceral adiposity cluster shows sex-specific effects for MI risk in males without T2D. This study underscores processes that decouple elevated FI levels from T2D and cardiovascular risk, offering new avenues for investigating process-specific pathways of disease.

Causal Relationship Between Intelligence, Noncognitive Education, Cognition and Urinary Tract or Kidney Infection: A Mendelian Randomization Study

Background

The occurrence of urinary tract or kidney infection is correlated with intelligence, noncognitive education and cognition, but the causal relationship between them remains uncertain, and which risk factors mediate this causal relationship remains unknown.

Methods

The intelligence (n=269,867), noncognitive education (n=510,795) and cognition data (n=257,700) were obtained from genome-wide association studies (GWAS) conducted in individuals of European ethnicities. The genetic associations between these factors and urinary tract or kidney infection (UK Biobank, n=397,867) were analyzed using linkage disequilibrium score regression. We employed a two-sample univariate and multivariate Mendelian randomization to evaluate the causal relationship, and utilized a two-step Mendelian randomization to examine the involvement of 28 potential mediators and their respective mediating proportions.

Results

The genetic correlation coefficients of intelligence, noncognitive education, cognition, and urinary tract or kidney infection were -0.338, -0.218, and -0.330. The Mendelian randomization using the inverse variance weighted method revealed each 1-SD increase in intelligence, the risk of infection decreased by 15.9%, while after adjusting for noncognitive education, the risk decreased by 20%. For each 1-SD increase in noncognitive education, the risk of infection decreased by 8%, which further reduced to 7.1% after adjusting for intelligence and to 6.7% after adjusting for cognition. For each 1-SD increase in cognition, the risk of infection decreased by 10.8%, increasing to 11.9% after adjusting for noncognitive education. The effects of intelligence and cognition are interdependent. 2 out of 28 potential mediating factors exhibited significant mediation effects in the causal relationship between noncognitive education and urinary tract or kidney infection, with body mass index accounting for 12.1% of the mediation effect and smoking initiation accounting for 14.7%.

Conclusion

Enhancing intelligence, noncognitive education, and cognition can mitigate the susceptibility to urinary tract or kidney infection. Noncognitive education exhibited independent effect, while body mass index and smoking initiation assuming a mediating role.

Assessment of polygenic risk score performance in East Asian populations for ten common diseases

Polygenic risk score (PRS) uses genetic variants to assess disease susceptibility. While PRS performance is well-studied in Europeans, its accuracy in East Asians is less explored. This study evaluated PRSs for ten diseases in the Health Examinees (HEXA) cohort (n = 55,870) in Korea. Single-population PRSs were constructed using PRS-CS, LDpred2, and Lassosum based on East Asian GWAS summary statistics (sample sizes: 51,442-341,204), while cross-population PRSs were developed using PRS-CSx and CT-SLEB by integrating European and East Asian GWAS data. PRS-CS consistently outperformed other single-population methods across key metrics, including the likelihood ratio test (LRT), odds ratio per standard deviation (perSD OR), net reclassification improvement (NRI), and area under the curve (AUC). Cross-population PRSs further improved predictive performance, with average increases of 1.08-fold (LRT), 1.07-fold (perSD OR), and 1.15-fold (NRI) across seven diseases with statistical significance, and a 1.01-fold improvement in AUC. Differences in R² between single- and cross-population PRSs were statistically significant for five diseases, showing an average increase of 1.13%. Cross-population PRSs achieved 87.8% of the predictive performance observed in European PRSs. These findings highlight the benefits of integrating European GWAS data while underscoring the need for larger East Asian datasets to improve prediction accuracy.

Integrating genetics, metabolites, and clinical characteristics in predicting cardiometabolic health outcomes using machine learning algorithms - A systematic review

BACKGROUND

Machine learning (ML) integration of clinical, metabolite, and genetic data reveals variable results in predicting cardiometabolic health (CMH) outcomes. Therefore, we aim to (1) evaluate whether a multi-modal approach incorporating all three data types using ML algorithms can improve CMH outcome prediction compared to single-modal or paired-modal models, and (2) compare the methodologies used in existing prediction models.

METHODS

We systematically searched five databases from 1998 to 2024 for ML predictive modelling studies using the multi-modal approach for CMH outcomes. Risk-of-bias assessment tools were used to assess methodological quality. Study characteristics, ML algorithms, data preprocessing, evaluation methods and metrics, feature selections, and feature importance parameters were synthesized narratively to show methodological heterogeneity.

RESULTS

Of the four included studies (3 ML algorithms), three were at low risk of bias, and one was at high risk. The multi-modal approach consistently improved T2D and BP prediction compared to single-modal or paired-modal models. Genetics showed the lowest predictive performance in three studies. Logistic regression (n = 2 studies) and random forest (n = 1) were used in T2D studies, while XGBoost was used in one BP study. One study with missing data and variations in feature selection across all studies hindered a comprehensive comparison of feature importance.

CONCLUSIONS

Our review emphasizes the potential improvement in T2D and BP prediction using ML algorithms with the multi-modal approach. However, further studies using diverse ML algorithms with optimized methodologies on single-modal, paired-modal, and multi-modal models are needed to gain insights into biomarker selection for predicting CMH outcomes.

Evaluation of polygenic scores for hypertrophic cardiomyopathy in the general population and across clinical settings

Hypertrophic cardiomyopathy (HCM) is an important cause of morbidity and mortality, with pathogenic variants found in about a third of cases. Large-scale genome-wide association studies (GWAS) demonstrate that common genetic variation contributes to HCM risk. Here we derive polygenic scores (PGS) from HCM GWAS and genetically correlated traits and test their performance in the UK Biobank, 100,000 Genomes Project, and clinical cohorts. We show that higher PGS significantly increases the risk of HCM in the general population, particularly among pathogenic variant carriers, where HCM penetrance differs 10-fold between those in the highest and lowest PGS quintiles. Among relatives of HCM probands, PGS stratifies risks of developing HCM and adverse outcomes. Finally, among HCM cases, PGS strongly predicts the risk of adverse outcomes and death. These findings support the broad utility of PGS across clinical settings, enabling tailored screening and surveillance and stratification of risk of adverse outcomes.