The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals

Association of GLP1R locus with mental ill-health endophenotypes and cardiometabolic traits: A trans-ancestry study in UK Biobank

AIMS

Glucagon-like peptide 1 receptor agonists (GLP1RA), used to treat type 2 diabetes and obesity, have been associated with off-target behavioural effects. We systematically assessed genetic variation in the GLP1R locus for impact on mental ill-health (MIH) and cardiometabolic phenotypes across diverse populations within UK Biobank.

MATERIALS AND METHODS

All genetic variants with minor allele frequency >1% in the GLP1R locus were investigated for associations with MIH phenotypes and cardiometabolic phenotypes. Linear or Logistic regression analyses (adjusted for age, sex, population structure and genotyping chip) were conducted separately in unrelated individuals of self-reported white British (N = 408 774), white European (N = 50 314), South Asian (N = 7667), multiple-ancestry groups (N = 10 437) or African-Caribbean (N = 7641) subsets. All ancestries were subsequently combined in an inverse variance-weighted fixed effects meta-analysis. Bonferroni correction for multiple testing was applied (for number of independent genetic variants).

RESULTS

Associations were identified between GLP1R variants and body mass index (BMI), blood pressure and type 2 diabetes in all ancestries. All ancestries except South Asian had significant MIH associations (mood instability: rs111265626-G, odds ratio [OR] 0.851 [confidence interval, CI 0.79-0.92], risk-taking behaviour: rs75408972-T, OR 1.05 [CI 1.03-1.08] or chronic pain: rs9296280-C, OR 0.645 [CI 0.54-0.78]). The trans-ancestry meta-analysis showed mainly consistent effect sizes and directions for metabolic traits, but discordant directions MIH associations. Only signals for chronic pain, stroke and BMI influenced expression of GLP1R.

CONCLUSIONS

GLP1R variants have consistent cardiometabolic effects across ancestries, but effects on MIH phenotypes are more varied. Any observed behavioural changes with GLP1RA are likely not acting directly through GLP1R.

Sex differences in risk factor relationships with subarachnoid haemorrhage and intracranial aneurysms: A Mendelian randomization study

Background

The prevalence of intracranial aneurysms (IAs) and incidence of aneurysmal subarachnoid haemorrhage (aSAH) is higher in women than in men. Although several cardiometabolic and lifestyle factors have been related to the risk of IAs or aSAH, it is unclear whether there are sex differences in causal relationships of these risk factors.

Aims

The aim of this study was to determine sex differences in causal relationships between cardiometabolic and lifestyle factors and risk of aSAH and IA.

Methods

We conducted a sex-specific two-sample Mendelian randomization study using summary-level data from genome-wide association studies. We analysed low-density lipoprotein cholesterol, high-density lipoprotein cholesterol [HDL-C], triglycerides, non-HDL-C, total cholesterol, fasting glucose, systolic and diastolic blood pressure, smoking initiation, and alcohol use as exposures, and aSAH and IA (i.e. aSAH and unruptured IA combined) as outcomes.

Results

We found statistically significant sex differences in the relationship between genetically proxied non-HDL-C and aSAH risk, with odds ratios (ORs) of 0.72 (95% confidence interval 0.58, 0.88) in women and 1.01 (0.77, 1.31) in men (p-value for sex difference 0.044). Moreover, genetic liability to smoking initiation was related to a statistically significantly higher risk of aSAH in men compared to women (p-value for sex difference 0.007) with ORs of 3.81 (1.93, 7.52) and 1.12 (0.63, 1.99), respectively, and to a statistically significantly higher IA risk in men compared to women (p-value for sex difference 0.036) with ORs of 3.58 (2.04, 6.27) and 1.61 (0.98, 2.64), respectively. In addition, higher genetically proxied systolic and diastolic blood pressure were related to a higher risk of aSAH and IA in both women and men.

Conclusions

Higher genetically proxied non-HDL-C was related to a lower risk of aSAH in women compared to men. Moreover, genetic liability to smoking initiation was associated with a higher risk for aSAH and IA in men compared to women. These findings may help improve understanding of sex differences in the development of aSAH and IA.

2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2025 AHA Statistical Update is the product of a full year's worth of effort in 2024 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. This year's edition includes a continued focus on health equity across several key domains and enhanced global data that reflect improved methods and incorporation of ≈3000 new data sources since last year's Statistical Update.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Preclinical toxicity evaluation of the novel anti-hypertensive compound KSD179019

The Secretin receptor (SCTR) presents a promising path for hypertension management, with KSD179019 as identified as a Positive Allosteric Modulator (PAM) of SCTR, demonstrating anti-hypertensive effects in animal models. Our objective was to comprehensively evaluate the potential toxicity of KSD179019 through in vitro and in vivo investigations. Initial in vitro studies showed minimal toxicity in liver and kidney cells and non-mutagenicity in bacterial assays. A 14-day acute toxicity test indicated an LD50 over 5000 mg/kg body weight, suggesting a safe profile, yet necessitating further in vivo analysis before progressing to human trials. Following OECD protocols, we conducted sub-chronic (90 days) and chronic (180 days) toxicity studies in male and female C57 mice at various dosages. These included comprehensive hematological, biochemical, macroscopic, urinalysis, and histopathological examinations. The sub-chronic study reported minimal toxicity except at the highest doses (700 and 1000 mg/kg), while the chronic study suggested a no-observed-adverse-effect-level (NOAEL) at 250 mg/kg with limitations. QSAR analysis supported the non-mutagenic nature of KSD179019. KSD179019 demonstrated a favorable general toxicity profile at a dose of 250 mg/kg in a 180-day chronic testing study. However, further preclinical investigations, including assessments of in vivo mutagenicity, reproductive and developmental toxicity, and carcinogenicity, are required to comprehensively establish its safety profile.

Epigenome-wide association study of objectively measured physical activity in peripheral blood leukocytes

BACKGROUND

Few studies have explored the association between DNA methylation and physical activity. The aim of this study was to evaluate the association of objectively measured hours of sedentary behavior (SB) and moderate physical activity (MPA) with DNA methylation. We further aimed to explore the association between SB or MPA related CpG sites and cardiometabolic traits, gene expression, and genetic variation.

RESULTS

For discovery, we performed cross sectional analyses in pregnant women from the Epigenetics in pregnancy (EPIPREG) sample with both DNA methylation (Illumina MethylationEPIC BeadChip) and objectively measured physical activity data (SenseWear™ Pro 3 armband) (European = 244, South Asian = 109). For EWAS of SB and MPA, two main models were designed: model (1) a linear mixed model adjusted for age, smoking, blood cell composition, including ancestry as random intercept, and model (2) which was additionally adjusted for the total number of steps per day. In model 1, we did not identify any CpG sites associated with neither SB nor MPA. In model 2, SB was positively associated (false discovery rate, FDR < 0.05) with two CpG sites within the VSX1 gene. Both CpG sites were positively associated with BMI and were associated with several genetic variants in cis. MPA was associated with 122 significant CpG sites at FDR < 0.05 (model 2). We further analyzed the ten most statistically significant MPA related CpG sites and found that they presented opposite associations with sedentary behavior and BMI. We were not able to replicate the SB and MPA-related CpG sites in the Avon Longitudinal Study of Parents and Children (ALSPAC). ALSPAC had available objectively measured physical activity data from Actigraph (without steps/day available) and leucocyte DNA methylation data collected during adolescence (n = 408, European).

CONCLUSION

This study suggests associations of objectively measured SB and MPA with maternal DNA methylation in peripheral blood leukocytes, that needs to be confirmed in larger samples of similar study design.

Molecular Imaging of Renin Activity using Fluorogenic Nanoprobes for Precision Antihypertensive Therapy

Life-threatening hypertension remains inadequately controlled in clinics due to its heterogeneous renin levels. Rapid stratification of hypertension through renin analysis is crucial for effective personalized treatment, yet an ultrasensitive detection approach is currently lacking. Here, we report activatable renin nanoprobes (ARNs) for non-invasive and ultrasensitive profiling of renin activity and guiding antihypertensive treatment decision through near-infrared fluorescence (NIRF) in vivo imaging and in vitro urinalysis. ARNs are intrinsically non-fluorescent due to NIRF reporter connected to a gold nanocluster through a renin-responsive peptide. In hyperreninemia mouse models, ARNs specifically react with renin to liberate the renal clearable NIRF reporter for accurate renin detection that outperforms the gold standard radioimmunoassay. Such specific and sensitive detection also enables imaging-based high-throughput screening of antihypertensive drugs. In hypertensive rat models, ARNs enable ultrasensitive detection of both plasma and urinary renin, facilitating renin-guided precision treatment and significantly improving hypertension control rate (90 % versus 58 %). Our nanoprobe platform holds great potential for assisting clinicians in rapidly and accurately classifying hypertensive patients and improving outcomes through tailored treatment selection.

Atheroma transcriptomics identifies ARNTL as a smooth muscle cell regulator and with clinical and genetic data improves risk stratification

BACKGROUND AND AIMS

The role of vascular smooth muscle cells (SMCs) in atherosclerosis has evolved to indicate causal genetic links with the disease. Single cell RNA sequencing (scRNAseq) studies have identified multiple cell populations of mesenchymal origin within atherosclerotic lesions, including various SMC sub-phenotypes, but it is unknown how they relate to patient clinical parameters and genetics. Here, mesenchymal cell populations in atherosclerotic plaques were correlated with major coronary artery disease (CAD) genetic variants and functional analyses performed to identify SMC markers involved in the disease.

METHODS

Bioinformatic deconvolution was done on bulk microarrays from carotid plaques in the Biobank of Karolinska Endarterectomies (BiKE, n = 125) using public plaque scRNAseq data and associated with patient clinical data and follow-up information. BiKE patients were clustered based on the deconvoluted cell fractions. Quantitative trait loci (QTLs) analyses were performed to predict the effect of CAD associated genetic variants on mesenchymal cell fractions (cfQTLs) and gene expression (eQTLs) in plaques.

RESULTS

Lesions from symptomatic patients had higher fractions of Type 1 macrophages and pericytes, but lower fractions of classical and modulated SMCs compared with asymptomatic ones, particularly females. Presence of diabetes or statin treatment did not affect the cell fraction distribution. Clustering based on plaque cell fractions, revealed three patient groups, with relative differences in their stability profiles and associations to stroke, even during long-term follow-up. Several single nucleotide polymorphisms associated with plaque mesenchymal cell fractions, upstream of the circadian rhythm gene ARNTL were identified. In vitro silencing of ARNTL in human carotid SMCs increased the expression of contractile markers and attenuated cell proliferation.

CONCLUSIONS

This study shows the potential of combining scRNAseq data with vertically integrated clinical, genetic, and transcriptomic data from a large biobank of human plaques, for refinement of patient vulnerability and risk prediction stratification. The study revealed novel CAD-associated variants that may be functionally linked to SMCs in atherosclerotic plaques. Specifically, variants in the ARNTL gene may influence SMC ratios and function, and its role as a regulator of SMC proliferation should be further investigated.

Large-scale brainstem neuroimaging and genetic analyses provide new insights into the neuronal mechanisms of hypertension

While brainstem regions are central regulators of blood pressure, the neuronal mechanisms underlying their role in hypertension remain poorly understood. Here, we investigated the structural and genetic relationships between global and regional brainstem volumes and blood pressure. We used magnetic resonance imaging data from n = 32,666 UK Biobank participants, and assessed the association of volumes of the whole brainstem and its main regions with blood pressure. We applied powerful statistical genetic tools, including bivariate causal mixture modeling (MiXeR) and conjunctional false discovery rate (conjFDR), to non-overlapping genome-wide association studies of brainstem volumes (n = 27,034) and blood pressure (n = 321,843) in the UK Biobank cohort. We observed negative associations between the whole brainstem and medulla oblongata volumes and systolic blood and pulse pressure, and positive relationships between midbrain and pons volumes and blood pressure traits when adjusting for the whole brainstem volume (all partial correlation coefficients ∣r∣ effects between 0.03 and 0.05, p ≤ 0.0042). We observed the largest genetic overlap for the whole brainstem, sharing 77% of its trait-influencing variants with blood pressure. We identified 65 shared loci between brainstem volumes and blood pressure traits and mapped these to 71 genes, implicating molecular pathways linked to sympathetic nervous system development, metal ion transport, and vascular homeostasis. The present findings support a link between brainstem structures and blood pressure and provide insights into their shared genetic underpinnings. The overlapping genetic architectures and mapped genes offer mechanistic information about the roles of brainstem regions in hypertension.

Genetic variation in circadian regulator gene BMAL1 in psychiatric, psychological and cardiometabolic traits: a trans-ancestry UK Biobank study

BACKGROUND

The link between cardiometabolic disease and mental illness has been well established but remains incompletely explained. One hypothesis suggests that circadian rhythm dysregulation links cardiometabolic disease and mental illnesses. BMAL1 is a circadian rhythm regulatory gene. Human genetic studies have implicated BMAL1 in depression, schizophrenia, bipolar disorder as well as body mass index, blood pressure and lipid levels.

OBJECTIVE

We investigated the BMAL1 locus genetic variants for associations with both cardiometabolic and mental illness.

METHODS

Genetic and phenotypic data from UK Biobank (~500 000 participants) of White British, African-Caribbean, South Asian, white European and Multiple ancestries were used. Regression analyses using Plink 1.09 was used to identify significant associations, with Bonferroni multiple testing correction. Multiple ancestry meta-analyses using METAL software was used to investigate trans-ancestry consistency in genetic effects.

FINDINGS

We identified associations for body mass index, anhedonia, diastolic and systolic blood pressure, waist-hip ratio, major depressive disorder, neuroticism and risk-taking. Meta-analyses indicated that there are ancestry-wide and ancestry-specific effects on cardiometabolic, mental illness and related traits.

CONCLUSIONS

Our results suggest that the associations for mental illness (and related traits) and those for cardiometabolic traits are distinct rather than shared and that these associations were consistent across ancestry groups.

CLINICAL IMPLICATIONS

Further investigation into the tissue-specific roles of BMAL1 is required to fully understand the clinical impact of these findings.

Genome-Wide Approach of Gene-Nutrient Intake Interaction Study for Essential Hypertension in a Large Korean Cohort (KoGES)

Background/Objectives: There is limited evidence on gene-nutrient interaction associated with hypertension (HTN). We examined interactions between genotypes and various nutrients that influenced high blood pressure (BP). Methods: Data were obtained from a total of 50,808 participants from the Korean Genome and Epidemiology Study (KoGES). Dietary intake was assessed by a food frequency questionnaire, and dietary reference intakes (DRIs) were set. We performed genome-wide association analyses (GWAS) and subsequent interaction analyses with genome-wide significant SNPs to identify genomic loci that interact with specific nutrients associated with HTN. Results: We identified one locus near the CUB and Sushi Multiple Domains 1 (CSMD1) gene that showed interaction with dietary iron and vitamin B6 (Vit.B6) intake and significantly influenced HTN risk. Among the individuals consuming iron above DRI (9.5 mg/day for men, 9.25 mg/day for women), carriers of the rs13282715 minor allele (A) at 8p23.2 showed a lower risk of HTN than those who did not (odds ratio [OR] 0.723, 95% confidence interval [CI] (0.644-0.813), p-value 4.858 × 10-8; interaction p-value 1.336 × 10-3). Among the individuals consuming Vit.B6 above DRI (1.5 mg/day for men, 1.4 mg/day for women), carriers of the same variant rs13282715 minor allele (A) also showed a lower risk of HTN (OR 0.733, 95% CI 0.733 (0.656-0.819), p-value 4.121 × 10-8; interaction p-value 7.183 × 10-4). Conclusions: We identified a novel gene-nutrient interaction regarding dietary iron and Vit.B6 intake affecting the risk of HTN in Korean adults. This suggests individuals with the variant may benefit from lower HTN risk from dietary intervention of iron and Vit.B6 intake. Further studies with larger diverse populations are warranted to validate our findings.

The Genetic Variants Influencing Hypertension Prevalence Based on the Risk of Insulin Resistance as Assessed Using the Metabolic Score for Insulin Resistance (METS-IR)

Insulin resistance is a major indicator of cardiovascular diseases, including hypertension. The Metabolic Score for Insulin Resistance (METS-IR) offers a simplified and cost-effective way to evaluate insulin resistance. This study aimed to identify genetic variants associated with the prevalence of hypertension stratified by METS-IR score levels. Data from the Korean Genome and Epidemiology Study (KoGES) were analyzed. The METS-IR was calculated using the following formula: ln [(2 × fasting blood glucose (FBG) + triglycerides (TG)) × body mass index (BMI)]/ ln [high-density lipoprotein cholesterol (HDL-C)]. The participants were divided into tertiles 1 (T1) and 3 (T3) based on their METS-IR scores. Genome-wide association studies (GWAS) were performed for hypertensive cases and non-hypertensive controls within these tertile groups using logistic regression adjusted for age, sex, and lifestyle factors. Among the METS-IR tertile groups, 3517 of the 19,774 participants (17.8%) at T1 had hypertension, whereas 8653 of the 20,374 participants (42.5%) at T3 had hypertension. A total of 113 single-nucleotide polymorphisms (SNPs) reached the GWAS significance threshold (p < 5 × 10-8) in at least one tertile group, mapping to six distinct genetic loci. Notably, four loci, rs11899121 (chr2p24), rs7556898 (chr2q24.3), rs17249754 (ATP2B1), and rs1980854 (chr20p12.2), were significantly associated with hypertension in the high-METS-score group (T3). rs10857147 (FGF5) was significant in both the T1 and T3 groups, whereas rs671 (ALDH2) was significant only in the T1 group. The GWASs identified six genetic loci significantly associated with hypertension, with distinct patterns across METS-IR tertiles, highlighting the role of metabolic context in genetic susceptibility. These findings underscore critical genetic factors influencing hypertension prevalence and provide insights into the metabolic-genetic interplay underlying this condition.

Matrix sketching framework for linear mixed models in association studies

Linear mixed models (LMMs) have been widely used in genome-wide association studies to control for population stratification and cryptic relatedness. However, estimating LMM parameters is computationally expensive, necessitating large-scale matrix operations to build the genetic relationship matrix (GRM). Over the past 25 years, Randomized Linear Algebra has provided alternative approaches to such matrix operations by leveraging matrix sketching, which often results in provably accurate fast and efficient approximations. We leverage matrix sketching to develop a fast and efficient LMM method called Matrix-Sketching LMM (MaSk-LMM) by sketching the genotype matrix to reduce its dimensions and speed up computations. Our framework comes with both theoretical guarantees and a strong empirical performance compared to the current state-of-the-art for simulated traits and complex diseases.

Mapping biological influences on the human plasma proteome beyond the genome

Broad-capture proteomic platforms now enable simultaneous assessment of thousands of plasma proteins, but most of these are not actively secreted and their origins are largely unknown. Here we integrate genomic with deep phenomic information to identify modifiable and non-modifiable factors associated with 4,775 plasma proteins in ~8,000 mostly healthy individuals. We create a data-driven map of biological influences on the human plasma proteome and demonstrate segregation of proteins into clusters based on major explanatory factors. For over a third (N = 1,575) of protein targets, joint genetic and non-genetic factors explain 10-77% of the variation in plasma (median 19.88%, interquartile range 14.01-31.09%), independent of technical factors (median 2.48%, interquartile range 0.78-6.41%). Together with genetically anchored causal inference methods, our map highlights potential causal associations between modifiable risk factors and plasma proteins for hundreds of protein-disease associations, for example, COL6A3, which possibly mediates the association between reduced kidney function and cardiovascular disease. We provide a map of biological and technical influences on the human plasma proteome to help contextualize findings from proteomic studies.

Cardiac Molecular Analysis Reveals Aging-Associated Metabolic Alterations Promoting Glycosaminoglycans Accumulation via Hexosamine Biosynthetic Pathway

Age is a prominent risk factor for cardiometabolic disease, often leading to heart structural and functional changes. However, precise molecular mechanisms underlying cardiac remodeling and dysfunction exclusively resulting from physiological aging remain elusive. Previous research demonstrated age-related functional alterations in baboons, analogous to humans. The goal of this study is to identify early cardiac molecular alterations preceding functional adaptations, shedding light on the regulation of age-associated changes. Unbiased transcriptomics of left ventricle samples are performed from female baboons aged 7.5-22.1 years (human equivalent ≈30-88 years). Weighted-gene correlation network and pathway enrichment analyses are performed, with histological validation. Modules of transcripts negatively correlated with age implicated declined metabolism-oxidative phosphorylation, tricarboxylic acid cycle, glycolysis, and fatty-acid β-oxidation. Transcripts positively correlated with age suggested a metabolic shift toward glucose-dependent anabolic pathways, including hexosamine biosynthetic pathway (HBP). This shift is associated with increased glycosaminoglycan synthesis, modification, precursor synthesis via HBP, and extracellular matrix accumulation, verified histologically. Upregulated extracellular matrix-induced signaling coincided with glycosaminoglycan accumulation, followed by cardiac hypertrophy-related pathways. Overall, these findings revealed a transcriptional shift in metabolism favoring glycosaminoglycan accumulation through HBP before cardiac hypertrophy. Unveiling this metabolic shift provides potential targets for age-related cardiac diseases, offering novel insights into early age-related mechanisms.

Identification of a novel immune infiltration-related gene signature, MCEMP1, for coronary artery disease

Background

This study aims to identify a novel gene signature for coronary artery disease (CAD), explore the role of immune cell infiltration in CAD pathogenesis, and assess the cell function of mast cell-expressed membrane protein 1 (MCEMP1) in human umbilical vein endothelial cells (HUVECs) treated with oxidized low-density lipoprotein (ox-LDL).

Methods

To identify differentially expressed genes (DEGs) of CAD, datasets GSE24519 and GSE61145 were downloaded from the Gene Expression Omnibus (GEO) database using the R "limma" package with p < 0.05 and |log2 FC| > 1. Gene ontology (GO) and pathway analyses were conducted to determine the biological functions of DEGs. Hub genes were identified using support vector machine-recursive feature elimination (SVM-RFE) and least absolute shrinkage and selection operator (LASSO). The expression levels of these hub genes in CAD were validated using the GSE113079 dataset. CIBERSORT program was used to quantify the proportion of immune cell infiltration. Western blot assay and qRT-PCR were used to detect the expression of hub genes in ox-LDL-treated HUVECs to validate the bioinformatics results. Knockdown interference sequences for MCEMP1 were synthesized, and cell proliferation and apoptosis were examined using a CCK8 kit and Muse® Cell Analyzer, respectively. The concentrations of IL-1β, IL-6, and TNF-α were measured with respective enzyme-linked immunosorbent assay (ELISA) kits.

Results

A total of 73 DEGs (four down-regulated genes and 69 up-regulated genes) were identified in the metadata (GSE24519 and GSE61145) cohort. GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis results indicated that these DEGs might be associated with the regulation of platelet aggregation, defense response or response to bacterium, NF-kappa B signaling pathway, and lipid and atherosclerosis. Using SVM-RFE and LASSO, seven hub genes were obtained from the metadata. The upregulated expression of DIRC2 and MCEMP1 in CAD was confirmed in the GSE113079 dataset and in ox-LDL-treated HUVECs. The associations between the two hub genes (DIRC2 and MCEMP1) and the 22 types of immune cell infiltrates in CAD were found. MCEMP1 knockdown accelerated cell proliferation and suppressed cell apoptosis for ox-LDL-treated HUVECs. Additionally, MCEMP1 knockdown appeared to decrease the expression of inflammatory factors IL-1β, IL-6, and TNF-α.

Conclusions

The results of this study indicate that MCEMP1 may play an important role in CAD pathophysiology.

Genetic variation in CCDC93 is associated with elevated central systolic blood pressure, impaired arterial relaxation, and mitochondrial dysfunction

Genetic studies of blood pressure (BP) traits to date have been performed on conventional measures by brachial cuff sphygmomanometer for systolic BP (SBP) and diastolic BP, integrating several physiologic occurrences. Genetic associations with central SBP (cSBP) have not been well-studied. Genetic discovery studies of BP have been most often performed in European-ancestry samples. Here, we investigated genetic associations with cSBP in a Chinese population and functionally validated the impact of a novel associated coiled-coil domain containing 93 (CCDC93) gene on BP regulation. An exome-wide association study (EWAS) was performed using a mixed linear model of non-invasive cSBP and peripheral BP traits in a Han Chinese population (N = 5,954) from Beijing, China genotyped with a customized Illumina ExomeChip array. We identified four SNP-trait associations with three SNPs, including two novel associations (rs2165468-SBP and rs33975708-cSBP). rs33975708 is a coding variant in the CCDC93 gene, c.535C>T, p.Arg179Cys (MAF = 0.15%), and was associated with increased cSBP (β = 29.3 mmHg, P = 1.23x10-7). CRISPR/Cas9 genome editing was used to model the effect of Ccdc93 loss in mice. Homozygous Ccdc93 deletion was lethal prior to day 10.5 of embryonic development. Ccdc93+/- heterozygous mice were viable and morphologically normal, with 1.3-fold lower aortic Ccdc93 protein expression (P = 0.0041) and elevated SBP as compared to littermate Ccdc93+/+ controls (110±8 mmHg vs 125±10 mmHg, P = 0.016). Wire myography of Ccdc93+/- aortae showed impaired acetylcholine-induced relaxation and enhanced phenylephrine-induced contraction. RNA-Seq transcriptome analysis of Ccdc93+/- mouse thoracic aortae identified significantly enriched pathways altered in fatty acid metabolism and mitochondrial metabolism. Plasma free fatty acid levels were elevated in Ccdc93+/- mice (96±7mM vs 124±13mM, P = 0.0031) and aortic mitochondrial dysfunction was observed through aberrant Parkin and Nix protein expression. Together, our genetic and functional studies support a novel role of CCDC93 in the regulation of BP through its effects on vascular mitochondrial function and endothelial function.

Interactive molecular causal networks of hypertension using a fast machine learning algorithm MRdualPC

BACKGROUND

Understanding the complex interactions between genes and their causal effects on diseases is crucial for developing targeted treatments and gaining insight into biological mechanisms. However, the analysis of molecular networks, especially in the context of high-dimensional data, presents significant challenges.

METHODS

This study introduces MRdualPC, a computationally tractable algorithm based on the MRPC approach, to infer large-scale causal molecular networks. We apply MRdualPC to investigate the upstream causal transcriptomics influencing hypertension using a comprehensive dataset of kidney genome and transcriptome data.

RESULTS

Our algorithm proves to be 100 times faster than MRPC on average in identifying transcriptomics drivers of hypertension. Through clustering, we identify 63 modules with causal driver genes, including 17 modules with extensive causal networks. Notably, we find that genes within one of the causal networks are associated with the electron transport chain and oxidative phosphorylation, previously linked to hypertension. Moreover, the identified causal ancestor genes show an over-representation of blood pressure-related genes.

CONCLUSIONS

MRdualPC has the potential for broader applications beyond gene expression data, including multi-omics integration. While there are limitations, such as the need for clustering in large gene expression datasets, our study represents a significant advancement in building causal molecular networks, offering researchers a valuable tool for analyzing big data and investigating complex diseases.

Genome-Wide Methylation Analysis Reveals a KCNK3-Prominent Causal Cascade on Hypertension

BACKGROUND

Despite advances in understanding hypertension's genetic structure, how noncoding genetic variants influence it remains unclear. Studying their interaction with DNA methylation is crucial to deciphering this complex disease's genetic mechanisms.

METHODS

We investigated the genetic and epigenetic interplay in hypertension using whole-genome bisulfite sequencing. Methylation profiling in 918 males revealed allele-specific methylation and methylation quantitative trait loci. We engineered rs1275988T/C mutant mice using CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 (CRISPR-associated protein 9), bred them for homozygosity, and subjected them to a high-salt diet. Telemetry captured their cardiovascular metrics. Protein-DNA interactions were elucidated using DNA pull-downs, mass spectrometry, and Western blots. A wire myograph assessed vascular function, and analysis of the Kcnk3 gene methylation highlighted the mutation's role in hypertension.

RESULTS

We discovered that DNA methylation-associated genetic effects, especially in non-cytosine-phosphate-guanine (non-CpG) island and noncoding distal regulatory regions, significantly contribute to hypertension predisposition. We identified distinct methylation quantitative trait locus patterns in the hypertensive population and observed that the onset of hypertension is influenced by the transmission of genetic effects through the demethylation process. By evidence-driven prioritization and in vivo experiments, we unearthed rs1275988 in a cell type-specific enhancer as a notable hypertension causal variant, intensifying hypertension through the modulation of local DNA methylation and consequential alterations in Kcnk3 gene expression and vascular remodeling. When exposed to a high-salt diet, mice with the rs1275988C/C genotype exhibited exacerbated hypertension and significant vascular remodeling, underscored by increased aortic wall thickness. The C allele of rs1275988 was associated with elevated DNA methylation levels, driving down the expression of the Kcnk3 gene by attenuating Nr2f2 (nuclear receptor subfamily 2 group F member 2) binding at the enhancer locus.

CONCLUSIONS

Our research reveals new insights into the complex interplay between genetic variations and DNA methylation in hypertension. We underscore hypomethylation's potential in hypertension onset and identify rs1275988 as a causal variant in vascular remodeling. This work advances our understanding of hypertension's molecular mechanisms and encourages personalized health care strategies.

Sex differences in risk factor relationships with subarachnoid haemorrhage and intracranial aneurysms: A Mendelian Randomisation study

Background

The prevalence of intracranial aneurysms (IAs) and incidence of aneurysmal subarachnoid haemorrhage (aSAH) is higher in women than in men. Although several cardiometabolic and lifestyle factors have been related to the risk of IAs or aSAH, it is unclear whether there are sex differences in causal relationships of these risk factors.

Aims

The aim of this study was to determine sex differences in causal relationships between cardiometabolic and lifestyle factors and risk of aSAH and IA.

Methods

We conducted a sex-specific two-sample Mendelian randomisation study using summary-level data from genome-wide association studies. We analysed low-density lipoprotein cholesterol, high-density lipoprotein cholesterol [HDL-C], triglycerides, non-HDL-C, total cholesterol, fasting glucose, systolic and diastolic blood pressure, smoking initiation, and alcohol use as exposures, and aSAH and IA (i.e., aSAH and unruptured IA combined) as outcomes.

Results

We found statistically significant sex differences in the relationship between genetically proxied non-HDL-C and aSAH risk, with odds ratios (ORs) of 0.72 (95% confidence interval 0.58, 0.88) in women and 1.01 (0.77, 1.31) in men (P-value for sex difference 0.044). Moreover, genetic liability to smoking initiation was related to a statistically significantly higher risk of aSAH in men compared to women (P-value for sex difference 0.007) with ORs of 3.81 (1.93, 7.52) and 1.12 (0.63, 1.99), respectively, and to a statistically significantly higher IA risk in men compared to women (P-value for sex difference 0.036) with ORs of 3.58 (2.04, 6.27) and 1.61 (0.98, 2.64), respectively. In addition, higher genetically proxied systolic and diastolic blood pressure were related to a higher risk of aSAH and IA in both women and men.

Conclusions

Higher genetically proxied non-HDL-C was related to a lower risk of aSAH in women compared to men. Moreover, genetic liability to smoking initiation was associated with a higher risk for aSAH and IA in men compared to women. These findings may help improve understanding of sex differences in the development of aSAH and IA.

Using Machine Learning to Evaluate the Value of Genetic Liabilities in the Classification of Hypertension within the UK Biobank

Background and Objective: Hypertension increases the risk of cardiovascular diseases (CVD) such as stroke, heart attack, heart failure, and kidney disease, contributing to global disease burden and premature mortality. Previous studies have utilized statistical and machine learning techniques to develop hypertension prediction models. Only a few have included genetic liabilities and evaluated their predictive values. This study aimed to develop an effective hypertension classification model and investigate the potential influence of genetic liability for multiple risk factors linked to CVD on hypertension risk using the random forest and the neural network. Materials and Methods: The study involved 244,718 European participants, who were divided into training and testing sets. Genetic liabilities were constructed using genetic variants associated with CVD risk factors obtained from genome-wide association studies (GWAS). Various combinations of machine learning models before and after feature selection were tested to develop the best classification model. The models were evaluated using area under the curve (AUC), calibration, and net reclassification improvement in the testing set. Results: The models without genetic liabilities achieved AUCs of 0.70 and 0.72 using the random forest and the neural network methods, respectively. Adding genetic liabilities improved the AUC for the random forest but not for the neural network. The best classification model was achieved when feature selection and classification were performed using random forest (AUC = 0.71, Spiegelhalter z score = 0.10, p-value = 0.92, calibration slope = 0.99). This model included genetic liabilities for total cholesterol and low-density lipoprotein (LDL). Conclusions: The study highlighted that incorporating genetic liabilities for lipids in a machine learning model may provide incremental value for hypertension classification beyond baseline characteristics.

Genome-wide analysis in over 1 million individuals of European ancestry yields improved polygenic risk scores for blood pressure traits

Hypertension affects more than one billion people worldwide. Here we identify 113 novel loci, reporting a total of 2,103 independent genetic signals (P < 5 × 10-8) from the largest single-stage blood pressure (BP) genome-wide association study to date (n = 1,028,980 European individuals). These associations explain more than 60% of single nucleotide polymorphism-based BP heritability. Comparing top versus bottom deciles of polygenic risk scores (PRSs) reveals clinically meaningful differences in BP (16.9 mmHg systolic BP, 95% CI, 15.5-18.2 mmHg, P = 2.22 × 10-126) and more than a sevenfold higher odds of hypertension risk (odds ratio, 7.33; 95% CI, 5.54-9.70; P = 4.13 × 10-44) in an independent dataset. Adding PRS into hypertension-prediction models increased the area under the receiver operating characteristic curve (AUROC) from 0.791 (95% CI, 0.781-0.801) to 0.826 (95% CI, 0.817-0.836, ∆AUROC, 0.035, P = 1.98 × 10-34). We compare the 2,103 loci results in non-European ancestries and show significant PRS associations in a large African-American sample. Secondary analyses implicate 500 genes previously unreported for BP. Our study highlights the role of increasingly large genomic studies for precision health research.

Polygenic risk scores associate with blood pressure traits across the lifespan

AIMS

Hypertension is a major modifiable cause of morbidity and mortality that affects over 1 billion people worldwide. Blood pressure (BP) traits have a strong genetic component that can be quantified with polygenic risk scores (PRSs). To date, the performance of BP PRSs has mainly been assessed in adults, and less is known about polygenic hypertension risk in childhood.

METHODS AND RESULTS

Multiple PRSs for systolic BP (SBP), diastolic BP (DBP), and pulse pressure were developed using either genome-wide significant weights, pruning and thresholding, or Bayesian regression. Among 87 total PRSs, the top performer for each trait was applied in independent cohorts of children and adult to assess genotype-phenotype associations and disease risk across the lifespan. Differences between those with low (1st decile), average (2nd-9th decile), and high (10th decile) PRS emerge in the first years of life and are maintained throughout adulthood. These diverging BP trajectories also seem to affect cardiovascular and renal disease risk, with increased risk observed among those in the top decile and reduced risk among those in the bottom decile of the polygenic risk distribution compared with the rest of the population.

CONCLUSION

Genetic risk factors are associated with BP traits across the lifespan, beginning in the first years of life. Given the importance of exposure time in disease pathogenesis and the early rise in BP levels among those genetically susceptible, PRSs may help identify high-risk individuals prior to hypertension onset, facilitate primordial prevention, and reduce the burden of this public health challenge.

Hereditary causes of hypertension due to increased sodium transport

PURPOSE OF REVIEW

Hypertension, commonly known as high blood pressure, is a widespread health condition affecting a large number of individuals across the globe. Although lifestyle choices and environmental factors are known to have a significant impact on its development, there is growing recognition of the influence of genetic factors in the pathogenesis of hypertension. This review specifically focuses on the hereditary causes of hypertension that are associated with increased sodium transport through the thiazide-sensitive NaCl cotransporter (NCC) or amiloride-sensitive epithelial sodium channel (ENaC), crucial mechanisms involved in regulating blood pressure in the kidneys. By examining genetic mutations and signaling molecules linked to the dysregulation of sodium transport, this review aims to deepen our understanding of the hereditary causes of hypertension and shed light on potential therapeutic targets.

RECENT FINDINGS

Liddle syndrome (LS) is a genetic disorder that typically manifests early in life and is characterized by hypertension, hypokalemic metabolic alkalosis, hyporeninemia, and suppressed aldosterone secretion. This condition is primarily caused by gain-of-function mutations in ENaC. In contrast, Pseudohypoaldosteronism type II (PHAII) is marked by hyperkalemia and hypertension, alongside other clinical features such as hyperchloremia, metabolic acidosis, and suppressed plasma renin levels. PHAII results from overactivations of NCC, brought about by gain-of-function mutations in its upstream signaling molecules, including WNK1 (with no lysine (K) 1), WNK4, Kelch-like 3 (KLHL3), and cullin3 (CUL3).

SUMMARY

NCC and ENaC are integral components, and their malfunctions lead to disorders like LS and PHAII, hereditary causes of hypertension. Current treatments for LS involve ENaC blockers (e.g., triamterene and amiloride) in conjunction with low-sodium diets, effectively normalizing blood pressure and potassium levels. In PHAII, thiazide diuretics, which inhibit NCC, are the mainstay treatment, albeit with some limitations and potential side effects. Ongoing research in developing alternative treatments, including small molecules targeting key regulators, holds promise for more effective and tailored hypertension solutions.

Current RNA strategies in treating cardiovascular diseases

Cardiovascular disease (CVD) continues to impose a significant global health burden, necessitating the exploration of innovative treatment strategies. Ribonucleic acid (RNA)-based therapeutics have emerged as a promising avenue to address the complex molecular mechanisms underlying CVD pathogenesis. We present a comprehensive review of the current state of RNA therapeutics in the context of CVD, focusing on the diverse modalities that bring about transient or permanent modifications by targeting the different stages of the molecular biology central dogma. Considering the immense potential of RNA therapeutics, we have identified common gene targets that could serve as potential interventions for prevalent Mendelian CVD caused by single gene mutations, as well as acquired CVDs developed over time due to various factors. These gene targets offer opportunities to develop RNA-based treatments tailored to specific genetic and molecular pathways, presenting a novel and precise approach to address the complex pathogenesis of both types of cardiovascular conditions. Additionally, we discuss the challenges and opportunities associated with delivery strategies to achieve targeted delivery of RNA therapeutics to the cardiovascular system. This review highlights the immense potential of RNA-based interventions as a novel and precise approach to combat CVD, paving the way for future advancements in cardiovascular therapeutics.

Sex-specific genetic architecture of blood pressure

The genetic and genomic basis of sex differences in blood pressure (BP) traits remain unstudied at scale. Here, we conducted sex-stratified and combined-sex genome-wide association studies of BP traits using the UK Biobank resource, identifying 1,346 previously reported and 29 new BP trait-associated loci. Among associated loci, 412 were female-specific (Pfemale ≤ 5 × 10-8; Pmale > 5 × 10-8) and 142 were male-specific (Pmale ≤ 5 × 10-8; Pfemale > 5 × 10-8); these sex-specific loci were enriched for hormone-related transcription factors, in particular, estrogen receptor 1. Analyses of gene-by-sex interactions and sexually dimorphic effects identified four genomic regions, showing female-specific associations with diastolic BP or pulse pressure, including the chromosome 13q34-COL4A1/COL4A2 locus. Notably, female-specific pulse pressure-associated loci exhibited enriched acetylated histone H3 Lys27 modifications in arterial tissues and a female-specific association with fibromuscular dysplasia, a female-biased vascular disease; colocalization signals included Chr13q34: COL4A1/COL4A2, Chr9p21: CDKN2B-AS1 and Chr4q32.1: MAP9 regions. Sex-specific and sex-biased polygenic associations of BP traits were associated with multiple cardiovascular traits. These findings suggest potentially clinically significant and BP sex-specific pleiotropic effects on cardiovascular diseases.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Protein-protein interaction network-based integration of GWAS and functional data for blood pressure regulation analysis

BACKGROUND

It is valuable to analyze the genome-wide association studies (GWAS) data for a complex disease phenotype in the context of the protein-protein interaction (PPI) network, as the related pathophysiology results from the function of interacting polyprotein pathways. The analysis may include the design and curation of a phenotype-specific GWAS meta-database incorporating genotypic and eQTL data linking to PPI and other biological datasets, and the development of systematic workflows for PPI network-based data integration toward protein and pathway prioritization. Here, we pursued this analysis for blood pressure (BP) regulation.

METHODS

The relational scheme of the implemented in Microsoft SQL Server BP-GWAS meta-database enabled the combined storage of: GWAS data and attributes mined from GWAS Catalog and the literature, Ensembl-defined SNP-transcript associations, and GTEx eQTL data. The BP-protein interactome was reconstructed from the PICKLE PPI meta-database, extending the GWAS-deduced network with the shortest paths connecting all GWAS-proteins into one component. The shortest-path intermediates were considered as BP-related. For protein prioritization, we combined a new integrated GWAS-based scoring scheme with two network-based criteria: one considering the protein role in the reconstructed by shortest-path (RbSP) interactome and one novel promoting the common neighbors of GWAS-prioritized proteins. Prioritized proteins were ranked by the number of satisfied criteria.

RESULTS

The meta-database includes 6687 variants linked with 1167 BP-associated protein-coding genes. The GWAS-deduced PPI network includes 1065 proteins, with 672 forming a connected component. The RbSP interactome contains 1443 additional, network-deduced proteins and indicated that essentially all BP-GWAS proteins are at most second neighbors. The prioritized BP-protein set was derived from the union of the most BP-significant by any of the GWAS-based or the network-based criteria. It included 335 proteins, with ~ 2/3 deduced from the BP PPI network extension and 126 prioritized by at least two criteria. ESR1 was the only protein satisfying all three criteria, followed in the top-10 by INSR, PTN11, CDK6, CSK, NOS3, SH2B3, ATP2B1, FES and FINC, satisfying two. Pathway analysis of the RbSP interactome revealed numerous bioprocesses, which are indeed functionally supported as BP-associated, extending our understanding about BP regulation.

CONCLUSIONS

The implemented workflow could be used for other multifactorial diseases.

Gene-Environment Interactions: My Unique Journey

I am deeply honored to be invited to write this scientific autobiography. As a physician-scientist, pediatrician, molecular biologist, and geneticist, I have authored/coauthored more than 600 publications in the fields of clinical medicine, biochemistry, biophysics, pharmacology, drug metabolism, toxicology, molecular biology, cancer, standardized gene nomenclature, developmental toxicology and teratogenesis, mouse genetics, human genetics, and evolutionary genomics. Looking back, I think my career can be divided into four distinct research areas, which I summarize mostly chronologically in this article: (a) discovery and characterization of the AHR/CYP1 axis, (b) pharmacogenomics and genetic prediction of response to drugs and other environmental toxicants, (c) standardized drug-metabolizing gene nomenclature based on evolutionary divergence, and (d) discovery and characterization of the SLC39A8 gene encoding the ZIP8 metal cation influx transporter. Collectively, all four topics embrace gene-environment interactions, hence the title of my autobiography.

Genetic Variants of Adrenoceptors

Adrenoceptors are class A G-protein-coupled receptors grouped into three families (α1-, α2-, and β-adrenoceptors), each one including three members. All nine corresponding adrenoceptor genes display genetic variation in their coding and adjacent non-coding genomic region. Coding variants, i.e., nucleotide exchanges within the transcribed and translated receptor sequence, may result in a difference in amino acid sequence thus altering receptor function and signaling. Such variants have been intensely studied in vitro in overexpression systems and addressed in candidate-gene studies for distinct clinical parameters. In recent years, large cohorts were analyzed in genome-wide association studies (GWAS), where variants are detected as significant in context with specific traits. These studies identified two of the in-depth characterized 18 coding variants in adrenoceptors as repeatedly statistically significant genetic risk factors - p.Arg389Gly in the β1- and p.Thr164Ile in the β2-adrenoceptor, along with 56 variants in the non-coding regions adjacent to the adrenoceptor gene loci, the functional role of which is largely unknown at present. This chapter summarizes current knowledge on the two coding variants in adrenoceptors that have been consistently validated in GWAS and provides a prospective overview on the numerous non-coding variants more recently attributed to adrenoceptor gene loci.

Polygenic risk alters the penetrance of monogenic kidney disease

Chronic kidney disease (CKD) is determined by an interplay of monogenic, polygenic, and environmental risks. Autosomal dominant polycystic kidney disease (ADPKD) and COL4A-associated nephropathy (COL4A-AN) represent the most common forms of monogenic kidney diseases. These disorders have incomplete penetrance and variable expressivity, and we hypothesize that polygenic factors explain some of this variability. By combining SNP array, exome/genome sequence, and electronic health record data from the UK Biobank and All-of-Us cohorts, we demonstrate that the genome-wide polygenic score (GPS) significantly predicts CKD among ADPKD monogenic variant carriers. Compared to the middle tertile of the GPS for noncarriers, ADPKD variant carriers in the top tertile have a 54-fold increased risk of CKD, while ADPKD variant carriers in the bottom tertile have only a 3-fold increased risk of CKD. Similarly, the GPS significantly predicts CKD in COL4A-AN carriers. The carriers in the top tertile of the GPS have a 2.5-fold higher risk of CKD, while the risk for carriers in the bottom tertile is not different from the average population risk. These results suggest that accounting for polygenic risk improves risk stratification in monogenic kidney disease.

Cardiac Molecular Analysis Reveals Aging-Associated Metabolic Alterations Promoting Glycosaminoglycans Accumulation Via Hexosamine Biosynthetic Pathway

Age is a prominent risk factor for cardiometabolic disease, and often leads to heart structural and functional changes. However, precise molecular mechanisms underlying cardiac remodeling and dysfunction resulting from physiological aging per se remain elusive. Understanding these mechanisms requires biological models with optimal translation to humans. Previous research demonstrated that baboons undergo age-related reduction in ejection fraction and increased heart sphericity, mirroring changes observed in humans. The goal of this study was to identify early cardiac molecular alterations that precede functional adaptations, shedding light on the regulation of age-associated changes. We performed unbiased transcriptomics of left ventricle (LV) samples from female baboons aged 7.5-22.1 years (human equivalent ~30-88 years). Weighted-gene correlation network and pathway enrichment analyses were performed to identify potential age-associated mechanisms in LV, with histological validation. Myocardial modules of transcripts negatively associated with age were primarily enriched for cardiac metabolism, including oxidative phosphorylation, tricarboxylic acid cycle, glycolysis, and fatty-acid β-oxidation. Transcripts positively correlated with age suggest upregulation of glucose uptake, pentose phosphate pathway, and hexosamine biosynthetic pathway (HBP), indicating a metabolic shift towards glucose-dependent anabolic pathways. Upregulation of HBP commonly results in increased glycosaminoglycan precursor synthesis. Transcripts involved in glycosaminoglycan synthesis, modification, and intermediate metabolism were also upregulated in older animals, while glycosaminoglycan degradation transcripts were downregulated with age. These alterations would promote glycosaminoglycan accumulation, which was verified histologically. Upregulation of extracellular matrix (ECM)-induced signaling pathways temporally coincided with glycosaminoglycan accumulation. We found a subsequent upregulation of cardiac hypertrophy-related pathways and an increase in cardiomyocyte width. Overall, our findings revealed a transcriptional shift in metabolism from catabolic to anabolic pathways that leads to ECM glycosaminoglycan accumulation through HBP prior to upregulation of transcripts of cardiac hypertrophy-related pathways. This study illuminates cellular mechanisms that precede development of cardiac hypertrophy, providing novel potential targets to remediate age-related cardiac diseases.

New Insights into Polygenic Score-Lifestyle Interactions for Cardiometabolic Risk Factors from Genome-Wide Interaction Analyses

The relationship between lifestyles and cardiometabolic outcomes varies between individuals. In 382,275 UK Biobank Europeans, we investigate how lifestyles interact with polygenic scores (PGS) of cardiometabolic risk factors. We identify six interactions (PGS for body mass index with meat diet, physical activity, sedentary behaviour and insomnia; PGS for high-density lipoprotein cholesterol with sedentary behaviour; PGS for triglycerides with meat diet) in multivariable linear regression models including an interaction term and show stronger associations between lifestyles and cardiometabolic risk factors among individuals with high PGSs than those with low PGSs. Genome-wide interaction analyses pinpoint three genetic variants (FTO rs72805613 for BMI; CETP rs56228609 for high-density lipoprotein cholesterol; TRIB2 rs4336630 for triglycerides; PInteraction < 5 × 10-8). The associations between lifestyles and cardiometabolic risk factors differ between individuals grouped by the genotype of these variants, with the degree of differences being similar to that between individuals with high and low values for the corresponding PGSs. This study demonstrates that associations between lifestyles and cardiometabolic risk factors can differ between individuals based upon their genetic profiles. It further suggests that genetic variants with interaction effects contribute more to such differences compared to those without interaction effects, which has potential implications for developing PGSs for personalised intervention.

Genetic architecture of DCC and influence on psychological, psychiatric and cardiometabolic traits in multiple ancestry groups in UK Biobank

BACKGROUND

People with severe mental illness have a higher risk of cardiometabolic disease than the general population. Traditionally attributed to sociodemographic, behavioural factors and medication effects, recent genetic studies have provided evidence of shared biological mechanisms underlying mental illness and cardiometabolic disease. We aimed to determine whether signals in the DCC locus, implicated in psychiatric and cardiometabolic traits, were shared or distinct.

METHODS

In UK Biobank, we systematically assessed genetic variation in the DCC locus for association with metabolic, cardiovascular and psychiatric-related traits in unrelated "white British" participants (N = 402,837). Logistic or linear regression were applied assuming an additive genetic model and adjusting for age, sex, genotyping chip and population structure. Bonferroni correction for the number of independent variants was applied. Conditional analyses (including lead variants as covariates) and trans-ancestry analyses were used to investigate linkage disequilibrium between signals.

RESULTS

Significant associations were observed between DCC variants and smoking, anhedonia, body mass index (BMI), neuroticism and mood instability. Conditional analyses and linkage disequilibrium structure suggested signals for smoking and BMI were distinct from each other and the mood traits, whilst individual mood traits were inter-related in a complex manner.

LIMITATIONS

Restricting analyses in non-"white British" individuals to the phenotypes significant in the "white British" sample is not ideal, but the smaller samples sizes restricted the phenotypes possible to analyse.

CONCLUSIONS

Genetic variation in the DCC locus had distinct effects on BMI, smoking and mood traits, and therefore is unlikely to contribute to shared mechanisms underpinning mental and cardiometabolic traits.

Integration of genetic fine-mapping and multi-omics data reveals candidate effector genes for hypertension

Genome-wide association studies of blood pressure (BP) have identified >1,000 loci, but the effector genes and biological pathways at these loci are mostly unknown. Using published association summary statistics, we conducted annotation-informed fine-mapping incorporating tissue-specific chromatin segmentation and colocalization to identify causal variants and candidate effector genes for systolic BP, diastolic BP, and pulse pressure. We observed 532 distinct signals associated with ≥2 BP traits and 84 with all three. For >20% of signals, a single variant accounted for >75% posterior probability, 65 were missense variants in known (SLC39A8, ADRB2, and DBH) and previously unreported BP candidate genes (NRIP1 and MMP14). In disease-relevant tissues, we colocalized >80 and >400 distinct signals for each BP trait with cis-eQTLs and regulatory regions from promoter capture Hi-C, respectively. Integrating mouse, human disorder, gene expression and tissue abundance data, and literature review, we provide consolidated evidence for 436 BP candidate genes for future functional validation and discover several potential drug targets.

Genetic Markers Regulating Blood Pressure in Extreme Discordant Sib Pairs

Genome-wide scans performed in affected sib pairs have revealed small and often inconsistent clues to the loci responsible for the inherited components of hypertension. Since blood pressure is a quantitative trait regulated by many loci, two siblings at opposite extremes of the blood pressure distribution are more likely to have inherited different alleles at any given locus. Hence, we investigated an extreme discordant sib pair strategy to analyse markers from two previous loci of interest: (1) the Gordons syndrome locus that includes the WNK4 gene and (2) the ROMK locus identified in our first genome-wide scan. For this study, 24 sib pairs with strong family histories of essential hypertension were selected from the top and bottom 10% of the blood pressure distribution and genotyped for highly polymorphic microsatellite markers on chromosomes 11 and 17. The mean age of the population was 39.8 ± 7.8 years. A significant inverse correlation was found between the squared difference in pulse pressure and the number of alleles shared by IBD between the siblings for the DS11925 marker (r = -0.44, p = 0.031), systolic pressure and chromosome 17 markers (D17S250: r = -0.42, p = 0.040; D17S799 (r = -0.51, p = 0.011), and this relationship persisted after correcting for age and gender. Markers on chromosome 17 (D17S250, D17S928 and D17S1301) and 11 (D11S1999) also correlated with diastolic pressure. These results illustrate the successful use of discordant sib pair analysis to detect linkage within relatively small numbers of pedigrees with hypertension. Further analysis of this cohort may be valuable in complementing findings from the large genome wide scans in affected sib pairs.

Polygenic genetic variation affecting antibody formation underlies hypertensive renal injury in the stroke-prone spontaneously hypertensive rat

During development of the spontaneously hypertensive rat (SHR), several distinct but closely related lines were generated. Most lines are resistant to hypertensive renal disease. However, the SHR-A3 line (stroke-prone SHR) experiences end-organ injury (EOI) and provides a model of injury susceptibility that can be used to uncover genetic causation. In the present study, we generated a congenic line in which three distinct disease loci in SHR-A3 are concurrently replaced with homologous loci from an injury-resistant SHR line (SHR-B2). Verification that all three loci were homozygously replaced in this triple congenic line [SHR-A3(Trip B2)] while the genetic background of SHR-A3 was fully retained was obtained by whole genome sequencing. Congenic genome substitution was without effect on systolic blood pressure [198.9 ± 3.34 mmHg, mean ± SE, SHR-A3(Trip B2) = 194.7 ± 2.55 mmHg]. Measures of renal injury (albuminuria, histological injury scores, and urinary biomarker levels) were reduced in SHR-A3(Trip B2) animals, even though only 4.5 Mbases of the 2.8 Gbases of the SHR-B2 genome (0.16% of the genome) was transferred into the congenic line. The gene content of the three congenic loci and the functional effects of gene polymorphism within suggest a role of immunoglobulin in EOI pathogenesis. To prove the role of antibodies in EOI in SHR-A3, we generated an SHR-A3 line in which expression from the immunoglobulin heavy chain gene was knocked out (SHR-A3-IGHKO). Animals in the SHR-A3-IGHKO line lack B cells and immunoglobulin, but the hypertensive phenotype is not affected. Renal injury, however, was reduced in this line, confirming a pathogenic role for immunoglobulin in hypertensive EOI in this model of heritable risk.NEW & NOTEWORTHY Here, we used a polygenic animal model of hypertensive renal disease to show that genetic variation affecting antibody formation underlies hypertensive renal disease. We proved the genetic thesis by generating an immunoglobulin knockout in the susceptible animal model.

Systematic characterization of regulatory variants of blood pressure genes

High blood pressure (BP) is the major risk factor for cardiovascular disease. Genome-wide association studies have identified genetic variants for BP, but functional insights into causality and related molecular mechanisms lag behind. We functionally characterize 4,608 genetic variants in linkage with 135 BP loci in vascular smooth muscle cells and cardiomyocytes by massively parallel reporter assays. High densities of regulatory variants at BP loci (i.e., ULK4, MAP4, CFDP1, PDE5A) indicate that multiple variants drive genetic association. Regulatory variants are enriched in repeats, alter cardiovascular-related transcription factor motifs, and spatially converge with genes controlling specific cardiovascular pathways. Using heuristic scoring, we define likely causal variants, and CRISPR prime editing finally determines causal variants for KCNK9, SFXN2, and PCGF6, which are candidates for developing high BP. Our systems-level approach provides a catalog of functionally relevant variants and their genomic architecture in two trait-relevant cell lines for a better understanding of BP gene regulation.

Association of genetically-predicted placental gene expression with adult blood pressure traits

OBJECTIVE

Blood pressure is a complex, polygenic trait, and the need to identify prehypertensive risks and new gene targets for blood pressure control therapies or prevention continues. We hypothesize a developmental origins model of blood pressure traits through the life course where the placenta is a conduit mediating genomic and nongenomic transmission of disease risk. Genetic control of placental gene expression has recently been described through expression quantitative trait loci (eQTL) studies which have identified associations with childhood phenotypes.

METHODS

We conducted a transcriptome-wide gene expression analysis estimating the predicted gene expression of placental tissue in adult individuals with genome-wide association study (GWAS) blood pressure summary statistics. We constructed predicted expression models of 15 154 genes from reference placenta eQTL data and investigated whether genetically-predicted gene expression in placental tissue is associated with blood pressure traits using published GWAS summary statistics. Functional annotation of significant genes was generated using FUMA.

RESULTS

We identified 18, 9, and 21 genes where predicted expression in placenta was significantly associated with systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP), respectively. There were 14 gene-tissue associations (13 unique genes) significant only in placenta.

CONCLUSIONS

In this meta-analysis using S-PrediXcan and GWAS summary statistics, the predicted expression in placenta of 48 genes was statistically significantly associated with blood pressure traits. Notable findings included the association of FGFR1 expression with increased SBP and PP. This evidence of gene expression variation in placenta preceding the onset of adult blood pressure phenotypes is an example of extreme preclinical biological changes which may benefit from intervention.

meQTL mapping in the GENOA study reveals genetic determinants of DNA methylation in African Americans

Identifying genetic variants that are associated with variation in DNA methylation, an analysis commonly referred to as methylation quantitative trait locus (meQTL) mapping, is an important first step towards understanding the genetic architecture underlying epigenetic variation. Most existing meQTL mapping studies have focused on individuals of European ancestry and are underrepresented in other populations, with a particular absence of large studies in populations with African ancestry. We fill this critical knowledge gap by performing a large-scale cis-meQTL mapping study in 961 African Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. We identify a total of 4,565,687 cis-acting meQTLs in 320,965 meCpGs. We find that 45% of meCpGs harbor multiple independent meQTLs, suggesting potential polygenic genetic architecture underlying methylation variation. A large percentage of the cis-meQTLs also colocalize with cis-expression QTLs (eQTLs) in the same population. Importantly, the identified cis-meQTLs explain a substantial proportion (median = 24.6%) of methylation variation. In addition, the cis-meQTL associated CpG sites mediate a substantial proportion (median = 24.9%) of SNP effects underlying gene expression. Overall, our results represent an important step toward revealing the co-regulation of methylation and gene expression, facilitating the functional interpretation of epigenetic and gene regulation underlying common diseases in African Americans.

Polygenic risk affects the penetrance of monogenic kidney disease

Background

Chronic kidney disease (CKD) is a genetically complex disease determined by an interplay of monogenic, polygenic, and environmental risks. Most forms of monogenic kidney diseases have incomplete penetrance and variable expressivity. It is presently unknown if some of the variability in penetrance can be attributed to polygenic factors.

Methods

Using the UK Biobank (N=469,835 participants) and the All of Us (N=98,622 participants) datasets, we examined two most common forms of monogenic kidney disorders, autosomal dominant polycystic kidney disease (ADPKD) caused by deleterious variants in the PKD1 or PKD2 genes, and COL4A-associated nephropathy (COL4A-AN caused by deleterious variants in COL4A3, COL4A4, or COL4A5 genes). We used the eMERGE-III electronic CKD phenotype to define cases (estimated glomerular filtration rate (eGFR) <60 mL/min/1.73m2 or kidney failure) and controls (eGFR >90 mL/min/1.73m2 in the absence of kidney disease diagnoses). The effects of the genome-wide polygenic score (GPS) for CKD were tested in monogenic variant carriers and non-carriers using logistic regression controlling for age, sex, diabetes, and genetic ancestry.

Results

As expected, the carriers of known pathogenic and rare predicted loss-of-function variants in PKD1 or PKD2 had a high risk of CKD (ORmeta=17.1, 95% CI: 11.1-26.4, P=1.8E-37). The GPS was comparably predictive of CKD in both ADPKD variant carriers (ORmeta=2.28 per SD, 95%CI: 1.55-3.37, P=2.6E-05) and non-carriers (ORmeta=1.72 per SD, 95% CI=1.69-1.76, P< E-300) independent of age, sex, diabetes, and genetic ancestry. Compared to the middle tertile of the GPS distribution for non-carriers, ADPKD variant carriers in the top tertile had a 54-fold increased risk of CKD, while ADPKD variant carriers in the bottom tertile had only a 3-fold increased risk of CKD. Similarly, the GPS was predictive of CKD in both COL4-AN variant carriers (ORmeta=1.78, 95% CI=1.22-2.58, P=2.38E-03) and non-carriers (ORmeta=1.70, 95%CI: 1.68-1.73 P

Conclusions

Variable penetrance of kidney disease in ADPKD and COL4-AN is partially explained by differences in polygenic risk profiles. Accounting for polygenic factors has the potential to improve risk stratification in monogenic kidney disease and may have implications for genetic counseling.

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Key Words

• APOL1
• GWAS
• chronic kidney disease (CKD)
• polygenic risk score (PRS)

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MESH Headings Collapse

Grants

• OT2 OD026556 NIH HHS
• U2C OD023196 NIH HHS
• OT2 OD026551 NIH HHS
• U24 OD023121 NIH HHS
• OT2 OD026552 NIH HHS
• OT2 OD026549 NIH HHS
• OT2 OD025337 NIH HHS
• OT2 OD025277 NIH HHS
• OT2 OD026555 NIH HHS
• OT2 OD026550 NIH HHS
• OT2 OD026553 NIH HHS
• OT2 OD023205 NIH HHS
• U01 HG008680 NHGRI NIH HHS
• OT2 OD025276 NIH HHS
• OT2 OD026557 NIH HHS
• U24 OD023163 NIH HHS
• OT2 OD023206 NIH HHS
• R01 LM013061 NLM NIH HHS
• U24 OD023176 NIH HHS
• OT2 OD026548 NIH HHS
• OT2 OD025315 NIH HHS
• K25 DK128563 NIDDK NIH HHS
• OT2 OD026554 NIH HHS
• UL1 TR001873 NCATS NIH HHS

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Affiliation(s)

Atlas Khan Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
Ning Shang Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
Jordan G. Nestor Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
Chunhua Weng Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
George Hripcsak Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
Peter C. Harris Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota 55905, USA
Ali G. Gharavi Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
Krzysztof Kiryluk Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY

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Collaborators Collapse

Risk Effects of rs1799945 Polymorphism of the HFE Gene and Intergenic Interactions of GWAS-Significant Loci for Arterial Hypertension in the Caucasian Population of Central Russia

The aim of this case-control replicative study was to investigate the link between GWAS-impact for arterial hypertension (AH) and/or blood pressure (BP) gene polymorphisms and AH risk in Russian subjects (Caucasian population of Central Russia). AH (n = 939) and control (n = 466) cohorts were examined for ten GWAS AH/BP risk loci. The genotypes/alleles of these SNP and their combinations (SNP-SNP interactions) were tested for their association with the AH development using a logistic regression statistical procedure. The genotype GG of the SNP rs1799945 (C/G) HFE was strongly linked with an increased AH risk (ORrecGG = 2.53; 95%CIrecGG1.03-6.23; ppermGG = 0.045). The seven SNPs such as rs1173771 (G/A) AC026703.1, rs1799945 (C/G) HFE, rs805303 (G/A) BAG6, rs932764 (A/G) PLCE1, rs4387287 (C/A) OBFC1, rs7302981 (G/A) CERS5, rs167479 (T/G) RGL3, out of ten regarded loci, were related with AH within eight SNP-SNP interaction models (<0.001 ≤ pperm-interaction ≤ 0.047). Three polymorphisms such as rs8068318 (T/C) TBX2, rs633185 (C/G) ARHGAP42, and rs2681472 (A/G) ATP2B1 were not linked with AH. The pairwise rs805303 (G/A) BAG6-rs7302981 (G/A) CERS5 combination was a priority in determining the susceptibility to AH (included in six out of eight SNP-SNP interaction models [75%] and described 0.82% AH entropy). AH-associated variants are conjecturally functional for 101 genes involved in processes related to the immune system (major histocompatibility complex protein, processing/presentation of antigens, immune system process regulation, etc.). In conclusion, the rs1799945 polymorphism of the HFE gene and intergenic interactions of BAG6, CERS5, AC026703.1, HFE, PLCE1, OBFC1, RGL3 have been linked with AH risky in the Caucasian population of Central Russia.

Sex-Specific Features of the Correlation between GWAS-Noticeable Polymorphisms and Hypertension in Europeans of Russia

The aim of the study was directed at studying the sex-specific features of the correlation between genome-wide association studies (GWAS)-noticeable polymorphisms and hypertension (HTN). In two groups of European subjects of Russia (n = 1405 in total), such as men (n = 821 in total: n = 564 HTN, n = 257 control) and women (n = 584 in total: n = 375 HTN, n = 209 control), the distribution of ten specially selected polymorphisms (they have confirmed associations of GWAS level with blood pressure (BP) parameters and/or HTN in Europeans) has been considered. The list of studied loci was as follows: (PLCE1) rs932764 A > G, (AC026703.1) rs1173771 G > A, (CERS5) rs7302981 G > A, (HFE) rs1799945 C > G, (OBFC1) rs4387287 C > A, (BAG6) rs805303 G > A, (RGL3) rs167479 T > G, (ARHGAP42) rs633185 C > G, (TBX2) rs8068318 T > C, and (ATP2B1) rs2681472 A > G. The contribution of individual loci and their inter-locus interactions to the HTN susceptibility with bioinformatic interpretation of associative links was evaluated separately in men's and women's cohorts. The men-women differences in involvement in the disease of the BP/HTN-associated GWAS SNPs were detected. Among women, the HTN risk has been associated with HFE rs1799945 C > G (genotype GG was risky; OR_GG = 11.15 p_permGG = 0.014) and inter-locus interactions of all 10 examined SNPs as part of 26 intergenic interactions models. In men, the polymorphism BAG6 rs805303 G > A (genotype AA was protective; OR_AA = 0.30 p_permAA = 0.0008) and inter-SNPs interactions of eight loci in only seven models have been founded as HTN-correlated. HTN-linked loci and strongly linked SNPs were characterized by pronounced polyvector functionality in both men and women, but at the same time, signaling pathways of HTN-linked genes/SNPs in women and men were similar and were represented mainly by immune mechanisms. As a result, the present study has demonstrated a more pronounced contribution of BP/HTN-associated GWAS SNPs to the HTN susceptibility (due to weightier intergenic interactions) in European women than in men.

Hypertension and periodontitis: A joint report by the Italian society of hypertension (SIIA) and the Italian society of periodontology and implantology (SIdP)

An accumulating body of evidence supports an independent association between high blood pressure (BP) and periodontitis, possibly mediated by low-grade inflammation. This joint report by the Italian Society of Hypertension (SIIA) and the Italian Society of Periodontology and Implantology (SIdP) working group on Hypertension and Periodontitis (Hy-Per Group) provides a review of the evidence on this topic encompassing epidemiology, biological plausibility, relevance, magnitude, and treatment management. Consensus recommendations are provided for health professionals on how to manage BP in individuals showing signs of poor oral health. In summary, (1) large epidemiological studies highlight that individuals with periodontal diseases have increased risk for high/uncontrolled BP independent of confounders; (2) mechanistically, low-grade inflammation might have a causal role in the association; (3) BP profile and control might benefit from periodontal treatment in pre-hypertensive and hypertensive individuals; (4) oral health status should be evaluated as a potential risk factor for high/uncontrolled BP, and effective oral care should be included as an adjunct lifestyle measure during hypertension management. Further research is needed to optimize BP management in individuals with poor oral health.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Assessment of polygenic risk of hypertension

Hypertension (HTN) is a leading risk factor for the development of cardiovascular diseases. In recent decades, the rapid development of genetic tests, in particular genome-wide association study (GWAS), has made it possible to identify hundreds of nucleotide sequence variants associated with the development of HTN. One approach to improve the predictive power of genetic testing is to combine information about many nucleotide sequence variants into a single risk assessment system, often referred to as a genetic risk score. Within the framework of this review, the most significant publications on the study of the genetic risk score for HTN will be considered, and the features of their development and application will be discussed.

Genetic heterogeneity in cardiovascular disease across ancestries: Insights for mechanisms and therapeutic intervention

Cardiovascular diseases (CVDs) are complex in their aetiology, arising due to a combination of genetics, lifestyle and environmental factors. By nature of this complexity, different CVDs vary in their molecular mechanisms, clinical presentation and progression. Although extensive efforts are being made to develop novel therapeutics for CVDs, genetic heterogeneity is often overlooked in the development process. By considering molecular mechanisms at an individual and ancestral level, a richer understanding of the influence of environmental and lifestyle factors can be gained and more refined therapeutic interventions can be developed. It is therefore expedient to understand the molecular and clinical heterogeneity in CVDs that exists across different populations. In this review, we highlight how the mechanisms underlying CVDs vary across diverse population ancestry groups due to genetic heterogeneity. We then discuss how such genetic heterogeneity is being leveraged to inform therapeutic interventions and personalised medicine, highlighting examples across the CVD spectrum. Finally, we present an overview of how polygenic risk scores and Mendelian randomisation can foster more robust insight into disease mechanisms and therapeutic intervention in diverse populations. Fulfilment of the vision of precision medicine requires more exhaustive leveraging of the genetic variability across diverse ancestry populations to improve our understanding of disease onset, progression and response to therapeutic intervention.

mRNA Metabolism and Hypertension

Hypertension is the most frequent cardiovascular risk factor all over the world. It remains a leading contributor to the risk of cardiovascular events and death. In the year 2015, about 1.5 billion of adult people worldwide had hypertension (as defined by office systolic blood pressure ≥ 140 mmHg or office diastolic blood pressure ≥ 90 mmHg). Moreover, the number of hypertensive patients with age ranging from 30 to 79 years doubled in the last 30 years (from 317 million men and 331 million women in the year 1990 to 652 million men and 626 million women in 2019) despite stable age-standardized prevalence worldwide. Despite such impressive growth, the proportion of controlled hypertension is very low. A better understanding of the pathogenesis of hypertension may contribute to the development of innovative therapeutic strategies. In this context, alterations of the messenger RNA metabolism have been recently evaluated as contributors to the pathogenesis of hypertension, and pharmacological modulation of RNA metabolism is under investigation as potential and novel therapeutic armamentarium in hypertension.

Anti-Epileptic Drug Target Perturbation and Intracranial Aneurysm Risk: Mendelian Randomization and Colocalization Study

BACKGROUND

In a genome-wide association study of intracranial aneurysms (IA), enrichment was found between genes associated with IA and genes encoding targets of effective anti-epileptic drugs. Our aim was to assess if this pleiotropy is driven by shared disease mechanisms that could potentially highlight a treatment strategy for IA.

METHODS

Using 2-sample inverse-variance weighted Mendelian randomization and genetic colocalization analyses we assessed: (1) if epilepsy liability in general affects IA risk, and (2) whether changes in gene- and protein-expression levels of anti-epileptic drug targets in blood and arterial tissue may causally affect IA risk.

RESULTS

We found no overall effect of epilepsy liability on IA. Expression of 21 genes and 13 proteins corresponding to anti-epileptic drug targets supported a causal effect (P<0.05) on IA risk. Of those genes and proteins, genetic variants affecting CNNM2 levels showed strong evidence for colocalization with IA risk (posterior probability>70%). Higher CNNM2 levels in arterial tissue were associated with increased IA risk (odds ratio, 3.02; [95% CI, 2.32-3.94]; P=3.39×10^-16). CNNM2 expression was best proxied by rs11191580. The magnitude of the effect of this variant was greater than would be expected if systemic blood pressure was the sole IA-causing mechanism in this locus.

CONCLUSIONS

CNNM2 is a driver of the pleiotropy between IA and anti-epileptic drug targets. Administration of the anti-epileptic drugs phenytoin, valproic acid, or carbamazepine may be expected to decrease CNNM2 levels and therefore subsequently decrease IA risk. CNNM2 is therefore an important target to investigate further for its role in the pathogenesis of IA.

Haplotypic variants of COVID-19 related genes are associated with blood pressure and metabolites levels

The genetic association of coronavirus disease 2019 (COVID-19) with its complications has not been fully understood. This study aimed to identify variants and haplotypes of candidate genes implicated in COVID-19 related traits by combining the literature review and pathway analysis. To explore such genes, the protein-protein interactions and relevant pathways of COVID-19-associated genes were assessed. A number of variants on candidate genes were identified from Genome-wide association studies (GWASs) which were associated with COVID-19 related traits (p ˂ 10^-6 ). Haplotypic blocks were assessed using haplotypic structures among the 1000 Genomes Project (r²  ≥ 0.8, D' ≥ 0.8). Further functional analyses were performed on the selected variants. The results demonstrated that a group of variants in ACE and AGT genes were significantly correlated with COVID-19 related traits. Three haplotypes were identified to be involved in the blood metabolites levels and the development of blood pressure. Functional analyses revealed that most GWAS index variants were expression quantitative trait loci and had transcription factor binding sites, exonic splicing enhancers or silencer activities. Furthermore, the proxy haplotype variants, rs4316, rs4353, rs4359, and three variants, namely rs2493133, rs2478543, and rs5051, were associated with blood metabolite and systolic blood pressure, respectively. These variants exerted more regulatory effects compared with other GWAS variants. The present study indicates that the genetic variants and candidate haplotypes of COVID-19 related genes are associated with blood pressure and blood metabolites. However, further observational studies are warranted to confirm these results.

Effects of Pre-Pregnancy Overweight/Obesity on the Pattern of Association of Hypertension Susceptibility Genes with Preeclampsia

The aim of this study was to explore the effects of pre-pregnancy overweight/obesity on the pattern of association of hypertension susceptibility genes with preeclampsia (PE). Ten single-nucleotide polymorphisms (SNPs) of the 10 genome-wide association studies (GWAS)-significant hypertension/blood pressure (BP) candidate genes were genotyped in 950 pregnant women divided into two cohorts according to their pre-pregnancy body mass index (preBMI): preBMI ≥ 25 (162 with PE and 159 control) and preBMI < 25 (290 with PE and 339 control). The PLINK software package was utilized to study the association (analyzed four genetic models using logistic regression). The functionality of PE-correlated loci was analyzed by performing an in silico database analysis. Two SNP hypertension/BP genes, rs805303 BAG6 (OR: 0.36−0.66) and rs167479 RGL3 (OR: 1.86), in subjects with preBMI ≥ 25 were associated with PE. No association between the studied SNPs and PE in the preBMI < 25 group was determined. Further analysis showed that two PE-associated SNPs are functional (have weighty eQTL, sQTL, regulatory, and missense values) and could be potentially implicated in PE development. In conclusion, this study was the first to discover the modifying influence of overweight/obesity on the pattern of association of GWAS-significant hypertension/BP susceptibility genes with PE: these genes are linked with PE in preBMI ≥ 25 pregnant women and are not PE-involved in the preBMI < 25 group.