Large-Scale Multi-Omics Studies Provide New Insights into Blood Pressure Regulation

GWAS for Defining the Etiology of Hypertension: Have They Delivered?

Genome-wide association studies have identified >3500 associated single nucleotide polymorphisms and over 1000 independent loci associated with hypertension. These individually have small effect sizes, and few associated loci have been experimentally tested for causal roles in hypertension using animal models or in humans. Thus, methods to prioritize and maximize the relevance of identified single nucleotide polymorphisms and associated loci are critical to determine their importance in hypertension. We propose several approaches to aid in these efforts, including: (1) integration of genome-wide association study data with multiomic data sets, including proteomics, transcriptomics, and epigenomics, (2) utilizing linked clinical and genetic data sets to determine genetic contributions to hypertension subphenotypes with distinct drivers, and (3) performing whole exome/genome sequencing on cohorts of individuals with severe hypertension to enrich for rare variants with larger effect sizes. Rather than creating longer lists of hypertension-associated single nucleotide polymorphisms, these approaches are needed to identify key mediators of hypertension pathophysiology.

Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues

Non-communicable diseases (NCDs) such as cardiovascular diseases, chronic respiratory diseases, cancers, diabetes, and mental health disorders pose a significant global health challenge, accounting for the majority of fatalities and disability-adjusted life years worldwide. These diseases arise from the complex interactions between genetic, behavioral, and environmental factors, necessitating a thorough understanding of these dynamics to identify effective diagnostic strategies and interventions. Although recent advances in multi-omics technologies have greatly enhanced our ability to explore these interactions, several challenges remain. These challenges include the inherent complexity and heterogeneity of multi-omic datasets, limitations in analytical approaches, and severe underrepresentation of non-European genetic ancestries in most omics datasets, which restricts the generalizability of findings and exacerbates health disparities. This scoping review evaluates the global landscape of multi-omics data related to NCDs from 2000 to 2024, focusing on recent advancements in multi-omics data integration, translational applications, and equity considerations. We highlight the need for standardized protocols, harmonized data-sharing policies, and advanced approaches such as artificial intelligence/machine learning to integrate multi-omics data and study gene-environment interactions. We also explore challenges and opportunities in translating insights from gene-environment (GxE) research into precision medicine strategies. We underscore the potential of global multi-omics research in advancing our understanding of NCDs and enhancing patient outcomes across diverse and underserved populations, emphasizing the need for equity and fairness-centered research and strategic investments to build local capacities in underrepresented populations and regions.

Multiomics Analysis of the Molecular Response to Glucocorticoids: Insights Into Shared Genetic Risk From Psychiatric to Medical Disorders

BACKGROUND

Alterations in the effects of glucocorticoids have been implicated in mediating some of the negative health effects associated with chronic stress, including increased risk for psychiatric disorders and cardiovascular and metabolic diseases. In this study, we investigated how genetic variants influence gene expression and DNA methylation in response to glucocorticoid receptor (GR) activation and their association with disease risk.

METHODS

We measured DNA methylation (n = 199) and gene expression (n = 297) in peripheral blood before and after GR activation with dexamethasone, with matched genotype data available for all samples. A comprehensive molecular quantitative trait locus (QTL) analysis was conducted, mapping GR-response methylation (me)QTLs, GR-response expression (e)QTLs, and GR-response expression quantitative trait methylation (eQTMs). A multilevel network analysis was employed to map the complex relationships between the transcriptome, epigenome, and genetic variation.

RESULTS

We identified 3772 GR-response meCpGs corresponding to 104,828 local GR-response meQTLs that did not strongly overlap with baseline meQTLs. eQTM and eQTL analyses revealed distinct genetic influences on gene expression and DNA methylation. Multilevel network analysis uncovered GR-response network trio QTLs, characterized by SNP-CpG-transcript combinations where meQTLs act as both eQTLs and eQTMs. GR-response trio variants were enriched in a genome-wide association study for psychiatric, respiratory, autoimmune, and cardiovascular diseases and conferred a higher relative heritability per SNP than GR-response meQTL and baseline QTL SNPs.

CONCLUSIONS

Genetic variants modulating the molecular effects of glucocorticoids are associated with psychiatric as well as medical diseases and not uncovered in baseline QTL analyses.

A genome-wide association study of hand eczema identifies locus 20q13.33 and reveals genetic overlap with atopic dermatitis

BACKGROUND

Twin studies revealed that genetic effects play a role in hand eczema (HE), but the responsible genetic factors are unknown.

OBJECTIVES

To identify and characterise genetic loci associated with HE and to provide insight into the genetic overlap between HE and atopic dermatitis (AD).

METHODS

We used questionnaire-derived and genotype data from the European population-based Lifelines cohort and biobank. We performed a discovery genome-wide association study (GWAS) of HE (2879 cases and 16 249 controls) and of AD (1706 cases and 17 190 controls). We replicated our findings in an independent Lifelines sample for HE (1188 cases and 6431 controls) and AD (757 cases and 6747 controls). We conducted several post-GWAS analyses and performed genetic correlation analyses between our HE results and independent AD data.

RESULTS

The two-step GWAS of HE, regardless of adjusting for AD, identified one independent locus 20q13.33, likely driven by a number of causal single-nucleotide polymorphisms. For the AD GWAS, we replicated a known stop-gained rs61816761 at locus 1q21.3 (FLG, FLGAS1). We found a strong genetic correlation (p < 0.01) between HE and AD (rg = 0.65), regardless of adjusting for AD (rg = 0.63).

CONCLUSIONS

Locus 20q13.33 is associated with HE, and there is a large genetic overlap between HE and AD.

Prioritization of Kidney Cell Types Highlights Myofibroblast Cells in Regulating Human Blood Pressure

Introduction

Blood pressure (BP) is a highly heritable trait with over 2000 underlying genomic loci identified to date. Although the kidney plays a key role, little is known about specific cell types involved in the genetic regulation of BP.

Methods

Here, we applied stratified linkage disequilibrium score (LDSC) regression to connect BP genome-wide association studies (GWAS) results to specific cell types of the mature human kidney. We used the largest single-stage BP genome-wide analysis to date, including up to 1,028,980 adults of European ancestry, and single-cell transcriptomic data from 14 mature human kidneys, with mean age of 41 years.

Results

Our analyses prioritized myofibroblasts and endothelial cells, among the total of 33 annotated cell type, as specifically involved in BP regulation (P < 0.05/33, i.e., 0.001515). Enrichment of heritability for systolic BP (SBP) was observed in myofibroblast cells in mature human kidney cortex, and enrichment of heritability for diastolic BP (DBP) was observed in descending vasa recta and peritubular capillary endothelial cells as well as stromal myofibroblast cells. The new finding of myofibroblast, the significant cell type for both BP traits, was consistent in 8 replication efforts using 7 sets of independent data, including in human fetal kidney, in East-Asian (EAS) ancestry, using mouse single-cell RNA sequencing (scRNA-seq) data, and when using another prioritization method.

Conclusion

Our findings provide a solid basis for follow-up studies to further identify genes and mechanisms in myofibroblast cells that underlie the regulation of BP.

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.

Plasma-Free Blood as a Potential Alternative to Whole Blood for Transcriptomic Analysis

RNA sequencing (RNAseq) technology has become increasingly important in precision medicine and clinical diagnostics, and emerged as a powerful tool for identifying protein-coding genes, performing differential gene analysis, and inferring immune cell composition. Human peripheral blood samples are widely used for RNAseq, providing valuable insights into individual biomolecular information. Blood samples can be classified as whole blood (WB), plasma, serum, and remaining sediment samples, including plasma-free blood (PFB) and serum-free blood (SFB) samples that are generally considered less useful byproducts during the processes of plasma and serum separation, respectively. However, the feasibility of using PFB and SFB samples for transcriptome analysis remains unclear. In this study, we aimed to assess the suitability of employing PFB or SFB samples as an alternative RNA source in transcriptomic analysis. We performed a comparative analysis of WB, PFB, and SFB samples for different applications. Our results revealed that PFB samples exhibit greater similarity to WB samples than SFB samples in terms of protein-coding gene expression patterns, detection of differentially expressed genes, and immunological characterizations, suggesting that PFB can serve as a viable alternative to WB for transcriptomic analysis. Our study contributes to the optimization of blood sample utilization and the advancement of precision medicine research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-023-00121-1.

Microbial influence on blood pressure: unraveling the complex relationship for health insights

Hypertension, a critical global health concern, is characterized by persistent high blood pressure and is a major cause of cardiovascular events. This perspective explores the multifaceted implications of hypertension, its association with cardiovascular diseases, and the emerging role of the gut microbiota. The gut microbiota, a dynamic community in the gastrointestinal tract, plays a pivotal role in hypertension by influencing blood pressure through the generation of antioxidant, anti-inflammatory, and short-chain fatty acids metabolites, and the conversion of nitrates into nitric oxide. Antihypertensive medications interact with the gut microbiota, impacting drug pharmacokinetics and efficacy. Prebiotics and probiotics present promising avenues for hypertension management, with prebiotics modulating blood pressure through lipid and cholesterol modulation, and probiotics exhibiting a general beneficial effect. Personalized choices based on individual factors are crucial for optimizing prebiotic and probiotic interventions. In conclusion, the gut microbiota's intricate influence on blood pressure regulation offers innovative perspectives in hypertension therapeutics, with targeted strategies proving valuable for holistic blood pressure management and health promotion.

A genome-wide association meta-analysis implicates Hedgehog and Notch signaling in Dupuytren's disease

Dupuytren's disease (DD) is a highly heritable fibrotic disorder of the hand with incompletely understood etiology. A number of genetic loci, including Wnt signaling members, have been previously identified. Our overall aim was to identify novel genetic loci, to prioritize genes within the loci for functional studies, and to assess genetic correlation with associated disorders. We performed a meta-analysis of six DD genome-wide association studies from three European countries and extensive bioinformatic follow-up analyses. Leveraging 11,320 cases and 47,023 controls, we identified 85 genome-wide significant single nucleotide polymorphisms in 56 loci, of which 11 were novel, explaining 13.3-38.1% of disease variance. Gene prioritization implicated the Hedgehog and Notch signaling pathways. We also identified a significant genetic correlation with frozen shoulder. The pathways identified highlight the potential for new therapeutic targets and provide a basis for additional mechanistic studies for a common disorder that can severely impact hand function.

Deciphering the genetic landscape of obesity: a data-driven approach to identifying plausible causal genes and therapeutic targets

OBJECTIVES

Genome-wide association studies (GWAS) have successfully revealed numerous susceptibility loci for obesity. However, identifying the causal genes, pathways, and tissues/cell types responsible for these associations remains a challenge, and standardized analysis workflows are lacking. Additionally, due to limited treatment options for obesity, there is a need for the development of new pharmacological therapies. This study aimed to address these issues by performing step-wise utilization of knowledgebase for gene prioritization and assessing the potential relevance of key obesity genes as therapeutic targets.

METHODS AND RESULTS

First, we generated a list of 28,787 obesity-associated SNPs from the publicly available GWAS dataset (approximately 800,000 individuals in the GIANT meta-analysis). Then, we prioritized 1372 genes with significant in silico evidence against genomic and transcriptomic data, including transcriptionally regulated genes in the brain from transcriptome-wide association studies. In further narrowing down the gene list, we selected key genes, which we found to be useful for the discovery of potential drug seeds as demonstrated in lipid GWAS separately. We thus identified 74 key genes for obesity, which are highly interconnected and enriched in several biological processes that contribute to obesity, including energy expenditure and homeostasis. Of 74 key genes, 37 had not been reported for the pathophysiology of obesity. Finally, by drug-gene interaction analysis, we detected 23 (of 74) key genes that are potential targets for 78 approved and marketed drugs.

CONCLUSIONS

Our results provide valuable insights into new treatment options for obesity through a data-driven approach that integrates multiple up-to-date knowledgebases.

Pathogenesis of Hypertension in Metabolic Syndrome: The Role of Fructose and Salt

Metabolic syndrome is manifested by visceral obesity, hypertension, glucose intolerance, hyperinsulinism, and dyslipidemia. According to the CDC, metabolic syndrome in the US has increased drastically since the 1960s leading to chronic diseases and rising healthcare costs. Hypertension is a key component of metabolic syndrome and is associated with an increase in morbidity and mortality due to stroke, cardiovascular ailments, and kidney disease. The pathogenesis of hypertension in metabolic syndrome, however, remains poorly understood. Metabolic syndrome results primarily from increased caloric intake and decreased physical activity. Epidemiologic studies show that an enhanced consumption of sugars, in the form of fructose and sucrose, correlates with the amplified prevalence of metabolic syndrome. Diets with a high fat content, in conjunction with elevated fructose and salt intake, accelerate the development of metabolic syndrome. This review article discusses the latest literature in the pathogenesis of hypertension in metabolic syndrome, with a specific emphasis on the role of fructose and its stimulatory effect on salt absorption in the small intestine and kidney tubules.