Uncovering genetic mechanisms of hypertension through multi-omic analysis of the kidney

GWAS for Defining the Pathogenesis 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.

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.

Kidney multiome-based genetic scorecard reveals convergent coding and regulatory variants

Kidney dysfunction is a major cause of mortality, but its genetic architecture remains elusive. In this study, we conducted a multiancestry genome-wide association study in 2.2 million individuals and identified 1026 (97 previously unknown) independent loci. Ancestry-specific analysis indicated an attenuation of newly identified signals on common variants in European ancestry populations and the power of population diversity for further discoveries. We defined genotype effects on allele-specific gene expression and regulatory circuitries in more than 700 human kidneys and 237,000 cells. We found 1363 coding variants disrupting 782 genes, with 601 genes also targeted by regulatory variants and convergence in 161 genes. Integrating 32 types of genetic information, we present the "Kidney Disease Genetic Scorecard" for prioritizing potentially causal genes, cell types, and druggable targets for kidney disease.

Identification of Circulating Proteins Associated With Blood Pressure

BACKGROUND

Circulating proteins in blood are involved in various physiological processes, but their contributions to blood pressure regulation remain partially understood. In traditional observational studies, identifying circulating proteins causally associated with blood pressure is challenging because of potentially unmeasured confounding and possible reverse causality.

METHODS

Two-sample Mendelian randomization analyses were conducted to estimate the causal effects of 2270 circulating proteins (data sourced from 8 genome-wide association studies) on diastolic blood pressure, systolic blood pressure, and pulse pressure. Colocalization analyses were then used to investigate whether the circulating proteins and blood pressure traits shared causal genetic variants. To further verify the findings, we subsequently performed Steiger filtering analyses, annotation of protein-altering variants, assessment of overlap between protein quantitative trait loci and expression quantitative trait loci, protein-protein interaction and functional enrichment analyses, and drug target evaluation. To provide more potential biomarkers, we further evaluated the epidemiological associations of 2923 circulating proteins with blood pressure and hypertension by cross-sectional and longitudinal analyses using individual data in the UK Biobank.

RESULTS

Mendelian randomization and colocalization analyses identified 121 circulating proteins with putative causal effects on at least 1 blood pressure trait. Many of the identified proteins are enriched in the pathways relevant to blood pressure regulation, and a majority of these proteins are either known drug targets or druggable candidates.

CONCLUSIONS

This study has uncovered numerous circulating proteins potentially causally associated with blood pressure, providing insights into the regulatory mechanisms of blood pressure and potential therapeutic targets to facilitate blood pressure management.

Transcriptome size matters for single-cell RNA-seq normalization and bulk deconvolution

The variation of transcriptome size across cell types significantly impacts single-cell RNA sequencing (scRNA-seq) data normalization and bulk RNA-seq cellular deconvolution, yet this intrinsic feature is often overlooked. Here we introduce ReDeconv, a computational algorithm that incorporates transcriptome size into scRNA-seq normalization and bulk deconvolution. ReDeconv introduces a scRNA-seq normalization approach, Count based on Linearized Transcriptome Size (CLTS), which corrects differential expressed genes typically misidentified by standard count per 10 K normalization, as confirmed by orthogonal validations. By maintaining transcriptome size variation, CLTS-normalized scRNA-seq enhances the accuracy of bulk deconvolution. Additionally, ReDeconv mitigates gene length effects and models expression variances, thereby improving deconvolution outcomes, particularly for rare cell types. Evaluated with both synthetic and real datasets, ReDeconv surpasses existing methods in precision. ReDeconv alters the practice and provides a new standard for scRNA-seq analyses and bulk deconvolution. The software packages and a user-friendly web portal are available.

Brain multi-omic Mendelian randomisation to identify novel drug targets for gliomagenesis

BACKGROUND

Genetic variants associated with molecular traits that are also associated with liability to glioma can provide causal evidence for the identification and prioritisation of drug targets.

METHODS

We performed comprehensive two-sample Mendelian randomisation (Wald ratio and/or IVW) and colocalisation analyses of molecular traits on glioma. Instrumentable traits (QTLs P < 5 × 10-8) were identified amongst 11 985 gene expression measures, 13 285 splicing isoforms and 10 198 protein abundance measures, derived from 15 brain regions. Glioma summary-level data was extracted from a genome-wide association meta-analysis of 12 496 cases and 18 190 controls.

RESULTS

We found evidence for causal effect of 22 molecular traits (across 18 genes/proteins) on glioma risk. Thirteen molecular traits have been previously linked with glioma risk and five were novel; HBEGF (5q31.3) expression and all glioma [OR 1.36 (95%CI 1.19-1.55); P = 4.41 × 10-6]; a CEP192 (18p11.21) splice isoform and glioblastoma [OR 4.40 (95%CI 2.28-8.48); P = 9.78 × 10-4]; a FAIM (3q22.3) splice isoform and all glioma [OR 2.72-3.43; P = 1.03 × 10-5 to 1.09 × 10-5]; a SLC8A1 (2p22.1) splice isoform and all glioma [OR 0.37 (95%CI 0.24-0.56; P = 5.72 × 10-6]; D2HGDH (2q37.3) protein and all glioma [OR 0.86 (95%CI 0.80-0.92); P = 5.94 × 10-6)].

CONCLUSIONS

We provide robust causal evidence for prioritising genes and their protein products in glioma research. Our results highlight the importance of alternative splicing as a mechanism in gliomagenesis and as an avenue for exploration of drug targets.

Calciprotein particle counts associate with vascular remodelling in chronic kidney disease

AIMS

Calciprotein particles (CPPs) are circulating calcium and phosphate nanoparticles associated with the development of vascular calcification (VC) in chronic kidney disease (CKD). Although recent studies have been focusing on associations of CPPs with the presence of VC in CKD, insights in the underlying processes and mechanisms by which CPPs might aggravate VC and vascular dysfunction in vivo are currently lacking. Here, we assessed the overall burden of abdominal VC in healthy kidney donors and CKD patients and subsequently performed transcriptome profiling in the vascular tissue obtained from these subjects, linking outcome to CPP counts and calcification propensity.

METHODS AND RESULTS

Calcification scores were quantified in renal arteries, iliac arteries, and abdominal aorta using computed tomography (CT) scans of kidney donors and CKD patients. The vascular tissue was collected from kidney donors (renal artery) and CKD patients (iliac artery), after which bulk RNA sequencing and gene set enrichment analysis (GSEA) were performed on a subset of patients. Calcification propensity (crystallization time, T50) was measured using nephelometry and CPP counts with microparticle flow cytometric analysis. Increased calcification scores (based on CT) were found in CKD patients compared to kidney donors. Transcriptome profiling revealed enrichment for processes related to endothelial activation, inflammation, extracellular matrix (ECM) remodelling, and ossification in CKD vascular biopsies compared to kidney donors. Calcification propensity was increased in CKD, as well as CPP counts, with the latter being significantly associated with markers of vascular remodelling.

CONCLUSION

Our findings reveal that CKD is characterized by systemic VC with increased calcification propensity and CPP counts. Transcriptome profiling showed altered vascular gene expression with enrichment for endothelial activation, inflammation, ECM remodelling, and ossification. Moreover, we demonstrate, for the first time, that vascular remodelling processes are associated with increased circulating CPP counts. Interventions targeting CPPs are promising avenues for alleviating vascular remodelling and VC in CKD.

Epigenetics of Hypertensive Nephropathy

Hypertensive nephropathy (HN) is a leading cause of chronic kidney disease (CKD) and end-stage renal disease (ESRD), contributing to significant morbidity, mortality, and rising healthcare costs. In this review article, we explore the role of epigenetic mechanisms in HN progression and their potential therapeutic implications. We begin by examining key epigenetic modifications-DNA methylation, histone modifications, and non-coding RNAs-observed in kidney disease. Next, we discuss the underlying pathophysiology of HN and highlight current in vitro and in vivo models used to study the condition. Finally, we compare various types of HN-induced renal injury and their associated epigenetic mechanisms with those observed in other kidney injury models, drawing inferences on potential epigenetic therapies for HN. The information gathered in this work indicate that epigenetic mechanisms can drive the progression of HN by regulating key molecular signaling pathways involved in renal damage and fibrosis. The limitations of Renin-Angiotensin-Aldosterone System (RAAS) inhibitors underscore the need for alternative treatments targeting epigenetic pathways. This review emphasizes the importance of further research into the epigenetic regulation of HN to develop more effective therapies and preventive strategies. Identifying novel epigenetic markers could provide new therapeutic opportunities for managing CKD and reducing the burden of ESRD.

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.

Integrated multi-omics with machine learning to uncover the intricacies of kidney disease

The development of omics technologies has driven a profound expansion in the scale of biological data and the increased complexity in internal dimensions, prompting the utilization of machine learning (ML) as a powerful toolkit for extracting knowledge and understanding underlying biological patterns. Kidney disease represents one of the major growing global health threats with intricate pathogenic mechanisms and a lack of precise molecular pathology-based therapeutic modalities. Accordingly, there is a need for advanced high-throughput approaches to capture implicit molecular features and complement current experiments and statistics. This review aims to delineate strategies for integrating multi-omics data with appropriate ML methods, highlighting key clinical translational scenarios, including predicting disease progression risks to improve medical decision-making, comprehensively understanding disease molecular mechanisms, and practical applications of image recognition in renal digital pathology. Examining the benefits and challenges of current integration efforts is expected to shed light on the complexity of kidney disease and advance clinical practice.

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.

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.

Immune and inflammatory mechanisms in hypertension

Hypertension is a global health problem, with >1.3 billion individuals with high blood pressure worldwide. In this Review, we present an inflammatory paradigm for hypertension, emphasizing the crucial roles of immune cells, cytokines and chemokines in disease initiation and progression. T cells, monocytes, macrophages, dendritic cells, B cells and natural killer cells are all implicated in hypertension. Neoantigens, the NLRP3 inflammasome and increased sympathetic outflow, as well as cytokines (including IL-6, IL-7, IL-15, IL-18 and IL-21) and a high-salt environment, can contribute to immune activation in hypertension. The activated immune cells migrate to target organs such as arteries (especially the perivascular fat and adventitia), kidneys, the heart and the brain, where they release effector cytokines that elevate blood pressure and cause vascular remodelling, renal damage, cardiac hypertrophy, cognitive impairment and dementia. IL-17 secreted by CD4+ T helper 17 cells and γδ T cells, and interferon-γ and tumour necrosis factor secreted by immunosenescent CD8+ T cells, exert crucial effector roles in hypertension, whereas IL-10 and regulatory T cells are protective. Effector mediators impair nitric oxide bioavailability, leading to endothelial dysfunction and increased vascular contractility. Inflammatory effector mediators also alter renal sodium and water balance and promote renal fibrosis. These mechanisms link hypertension with obesity, autoimmunity, periodontitis and COVID-19. A comprehensive understanding of the immune and inflammatory mechanisms of hypertension is crucial for safely and effectively translating the findings to clinical practice.

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.

Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets

Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes (SLC5A11, AGMAT, AGT, respectively). We showed that genetically determined reduction in renal expression may mimic the effects of rare loss-of-function variants on kidney mRNA/protein and lead to an increase in BP (e.g., ENPEP). We demonstrated a strong correlation (r = 0.81) in expression of protein-coding genes between cells harvested from urine and the kidney highlighting a diagnostic potential of urinary cell transcriptomics. We uncovered adenylyl cyclase activators as a repurposing opportunity for hypertension and illustrated examples of BP-elevating effects of anticancer drugs (e.g. tubulin polymerisation inhibitors). Collectively, our studies provide new biological insights into genetic regulation of BP with potential to drive clinical translation in hypertension.

Potential Role of the Skin in Hypertension Risk Through Water Conservation

Previous basic and clinical investigations have identified various pathogenic factors and determinants of risk that contribute to hypertension. Nevertheless, the pathogenesis of hypertension has not been fully elucidated. Moreover, despite the availability of antihypertensive medications for the management of blood pressure, treatments that address the full spectrum of the pathophysiological defects underpinning hypertension remain to be identified. To further investigate the mechanisms of primary hypertension, it is imperative to consider novel potential aspects, such as fluid management by the skin, in addition to the conventional risk factors. There is a close association between body fluid regulation and blood pressure, and the kidney, which, as the principal organ responsible for body fluid homeostasis, is the primary target for research in the field of hypertension. In addition, the skin functions as a biological barrier, potentially contributing to body fluid regulation. In this review, we propose the hypothesis that changes in skin water conservation are associated with hypertension risk based on recent findings. Further studies are required to clarify whether this novel hypothesis is limited to specific hypertension or applies to physiological blood pressure regulation.

A landscape of gene expression regulation for synovium in arthritis

The synovium is an important component of any synovial joint and is the major target tissue of inflammatory arthritis. However, the multi-omics landscape of synovium required for functional inference is absent from large-scale resources. Here we integrate genomics with transcriptomics and chromatin accessibility features of human synovium in up to 245 arthritic patients, to characterize the landscape of genetic regulation on gene expression and the regulatory mechanisms mediating arthritic diseases predisposition. We identify 4765 independent primary and 616 secondary cis-expression quantitative trait loci (cis-eQTLs) in the synovium and find that the eQTLs with multiple independent signals have stronger effects and heritability than single independent eQTLs. Integration of genome-wide association studies (GWASs) and eQTLs identifies 84 arthritis related genes, revealing 38 novel genes which have not been reported by previous studies using eQTL data from the GTEx project or immune cells. We further develop a method called eQTac to identify variants that could affect gene expression by affecting chromatin accessibility and identify 1517 regions with potential regulatory function of chromatin accessibility. Altogether, our study provides a comprehensive synovium multi-omics resource for arthritic diseases and gains new insights into the regulation of gene expression.

Comorbidity patterns in cardiovascular diseases: the role of life-stage and socioeconomic status

Cardiovascular diseases stand as a prominent global cause of mortality, their intricate origins often entwined with comorbidities and multimorbid conditions. Acknowledging the pivotal roles of age, sex, and social determinants of health in shaping the onset and progression of these diseases, our study delves into the nuanced interplay between life-stage, socioeconomic status, and comorbidity patterns within cardiovascular diseases. Leveraging data from a cross-sectional survey encompassing Mexican adults, we unearth a robust association between these variables and the prevalence of comorbidities linked to cardiovascular conditions. To foster a comprehensive understanding of multimorbidity patterns across diverse life-stages, we scrutinize an extensive dataset comprising 47,377 cases diagnosed with cardiovascular ailments at Mexico's national reference hospital. Extracting sociodemographic details, primary diagnoses prompting hospitalization, and additional conditions identified through ICD-10 codes, we unveil subtle yet significant associations and discuss pertinent specific cases. Our results underscore a noteworthy trend: younger patients of lower socioeconomic status exhibit a heightened likelihood of cardiovascular comorbidities compared to their older counterparts with a higher socioeconomic status. By empowering clinicians to discern non-evident comorbidities, our study aims to refine therapeutic designs. These findings offer profound insights into the intricate interplay among life-stage, socioeconomic status, and comorbidity patterns within cardiovascular diseases. Armed with data-supported approaches that account for these factors, clinical practices stand to be enhanced, and public health policies informed, ultimately advancing the prevention and management of cardiovascular disease in Mexico.

Unraveling the epigenetic code: human kidney DNA methylation and chromatin dynamics in renal disease development

Epigenetic changes may fill a critical gap in our understanding of kidney disease development, as they not only reflect metabolic changes but are also preserved and transmitted during cell division. We conducted a genome-wide cytosine methylation analysis of 399 human kidney samples, along with single-nuclear open chromatin analysis on over 60,000 cells from 14 subjects, including controls, and diabetes and hypertension attributed chronic kidney disease (CKD) patients. We identified and validated differentially methylated positions associated with disease states, and discovered that nearly 30% of these alterations were influenced by underlying genetic variations, including variants known to be associated with kidney disease in genome-wide association studies. We also identified regions showing both methylation and open chromatin changes. These changes in methylation and open chromatin significantly associated gene expression changes, most notably those playing role in metabolism and expressed in proximal tubules. Our study further demonstrated that methylation risk scores (MRS) can improve disease state annotation and prediction of kidney disease development. Collectively, our results suggest a causal relationship between epigenetic changes and kidney disease pathogenesis, thereby providing potential pathways for the development of novel risk stratification methods.

Genome-wide study investigating effector genes and polygenic prediction for kidney function in persons with ancestry from Africa and the Americas

Chronic kidney disease is a leading cause of death and disability globally and impacts individuals of African ancestry (AFR) or with ancestry in the Americas (AMS) who are under-represented in genome-wide association studies (GWASs) of kidney function. To address this bias, we conducted a large meta-analysis of GWASs of estimated glomerular filtration rate (eGFR) in 145,732 AFR and AMS individuals. We identified 41 loci at genome-wide significance (p < 5 × 10-8), of which two have not been previously reported in any ancestry group. We integrated fine-mapped loci with epigenomic and transcriptomic resources to highlight potential effector genes relevant to kidney physiology and disease, and reveal key regulatory elements and pathways involved in renal function and development. We demonstrate the varying but increased predictive power offered by a multi-ancestry polygenic score for eGFR and highlight the importance of population diversity in GWASs and multi-omics resources to enhance opportunities for clinical translation for all.

Decreased sympathetic nerve activity in young hypertensive rats reared by normotensive mothers

AIMS

Early postnatal development can be significantly compromised by changes in factors provided by the mother, leading to increased vulnerability to hypertension in her offspring. TGR(mRen-2)27 (TGR) mothers, characterised by an overactivated renin-angiotensin system, exhibit altered ion composition in their breast milk. Therefore, we aimed to analyse the impact of cross-fostering on cardiovascular parameters in hypertensive TGR and normotensive Hannover Sprague-Dawley (HanSD) offspring.

MATERIALS AND METHODS

We measured cardiovascular parameters in 5- to 10-week-old male offspring by telemetry. The expression of proteins related to vascular function was assessed by western blotting in the aortic samples obtained from 6- to 12-week-old male offspring. Plasma renin activity and plasma angiotensin II (Ang II) levels were evaluated by radioimmunoassay (RIA).

KEY FINDINGS

The development of hypertension was in TGR accompanied by increased low-to-high frequency ratio (LF/HF; a marker of sympathovagal balance; 0.51 ± 0.16 in week 10). Furthermore, TGR exhibited increased aortic expression of mineralocorticoid receptor (MR; p < 0.05) and transforming growth factor beta type 1 (TGF-β1; p = 0.002) compared to HanSD offspring. Fostering significantly decreased sympathovagal balance (0.23 ± 0.10 in week 10) and, transiently, plasma Ang II levels and MR expression in TGR offspring reared by HanSD mothers.

SIGNIFICANCE

These findings highlight the importance of understanding the complex interplay between early life experiences, maternal factors, and later cardiovascular function. Understanding the mechanisms behind the observed effects may help to identify potential interventions to prevent the development of hypertension later in life.

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.

Integration of artificial intelligence and multi-omics in kidney diseases

Kidney disease is a leading cause of death worldwide. Currently, the diagnosis of kidney diseases and the grading of their severity are mainly based on clinical features, which do not reveal the underlying molecular pathways. More recent surge of ∼omics studies has greatly catalyzed disease research. The advent of artificial intelligence (AI) has opened the avenue for the efficient integration and interpretation of big datasets for discovering clinically actionable knowledge. This review discusses how AI and multi-omics can be applied and integrated, to offer opportunities to develop novel diagnostic and therapeutic means in kidney diseases. The combination of new technology and novel analysis pipelines can lead to breakthroughs in expanding our understanding of disease pathogenesis, shedding new light on biomarkers and disease classification, as well as providing possibilities of precise treatment.

DNA methylation QTL mapping across diverse human tissues provides molecular links between genetic variation and complex traits

Studies of DNA methylation (DNAm) in solid human tissues are relatively scarce; tissue-specific characterization of DNAm is needed to understand its role in gene regulation and its relevance to complex traits. We generated array-based DNAm profiles for 987 human samples from the Genotype-Tissue Expression (GTEx) project, representing 9 tissue types and 424 subjects. We characterized methylome and transcriptome correlations (eQTMs), genetic regulation in cis (mQTLs and eQTLs) across tissues and e/mQTLs links to complex traits. We identified mQTLs for 286,152 CpG sites, many of which (>5%) show tissue specificity, and mQTL colocalizations with 2,254 distinct GWAS hits across 83 traits. For 91% of these loci, a candidate gene link was identified by integration of functional maps, including eQTMs, and/or eQTL colocalization, but only 33% of loci involved an eQTL and mQTL present in the same tissue type. With this DNAm-focused integrative analysis, we contribute to the understanding of molecular regulatory mechanisms in human tissues and their impact on complex traits.

Contributions of obesity to kidney health and disease: insights from Mendelian randomization and the human kidney transcriptomics

AIMS

Obesity and kidney diseases are common complex disorders with an increasing clinical and economic impact on healthcare around the globe. Our objective was to examine if modifiable anthropometric obesity indices show putatively causal association with kidney health and disease and highlight biological mechanisms of potential relevance to the association between obesity and the kidney.

METHODS AND RESULTS

We performed observational, one-sample, two-sample Mendelian randomization (MR) and multivariable MR studies in ∼300 000 participants of white-British ancestry from UK Biobank and participants of predominantly European ancestry from genome-wide association studies. The MR analyses revealed that increasing values of genetically predicted body mass index and waist circumference were causally associated with biochemical indices of renal function, kidney health index (a composite renal outcome derived from blood biochemistry, urine analysis, and International Classification of Disease-based kidney disease diagnoses), and both acute and chronic kidney diseases of different aetiologies including hypertensive renal disease and diabetic nephropathy. Approximately 13-16% and 21-26% of the potentially causal effect of obesity indices on kidney health were mediated by blood pressure and type 2 diabetes, respectively. A total of 61 pathways mapping primarily onto transcriptional/translational regulation, innate and adaptive immunity, and extracellular matrix and metabolism were associated with obesity measures in gene set enrichment analysis in up to 467 kidney transcriptomes.

CONCLUSIONS

Our data show that a putatively causal association of obesity with renal health is largely independent of blood pressure and type 2 diabetes and uncover the signatures of obesity on the transcriptome of human kidney.

SLC16A7 Promotes Triglyceride Deposition by De Novo Lipogenesis in Chicken Muscle Tissue

Triglyceride (TG) content in chicken muscle tissue signifies intramuscular fat (IMF) content, which is important for improving meat quality. However, the genetic basis of TG deposition in chicken is still unclear. Using 520 chickens from an artificially selected line with significantly increased IMF content and a control line, a genome-wide association study (GWAS) with TG content reports a region of 802 Kb located in chromosome 1. The XP-EHH and gene expression analysis together reveal that the solute carrier family 16 member A7 (SLC16A7) gene is the key candidate gene associated with TG content in chicken muscle tissue. Furthermore, the weighted gene co-expression network analysis (WGCNA) confirmed the regulatory effects of SLC16A7 on promoting TG deposition by de novo lipogenesis (DNL). Functional verification of SLC16A7 in vitro also supports this view, and reveals that this effect mainly occurs in myocytes. Our data highlight a potential IMF deposition pathway by DNL, induced by SLC16A7 in chicken myocytes. These findings will improve the understanding of IMF regulation in chicken and guide the formulation of breeding strategies for high-quality chicken.

Identification of intrinsic genes across general hypertension, hypertension with left ventricular remodeling, and uncontrolled hypertension

The purpose of the present article is to identify intrinsic genes across general hypertension (HT), hypertension with left ventricular remodeling (HT-LVR), and uncontrolled hypertension (UN-HT). In total, four microarray datasets (GSE24752, GSE75360, GSE74144, and GSE71994) were downloaded from the GEO database and were used to identify differentially expressed genes (DEGs), respectively. Furthermore, gene set enrichment analysis (GSEA) was utilized to screen for significantly enriched biological pathways across the four datasets above, respectively. Furthermore, weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were applied to screen out gene modules of interest and potential biological functions, respectively. Finally, a Metascape-based multiple gene list meta-analysis was used to investigate intrinsic genes at different stages of the progression of hypertension. A total of 75 DEGs (63 upregulated genes and 12 downregulated genes, GSE24752) and 23 DEGs (2 upregulated genes and 21 downregulated genes, GSE74144) were identified. However, there were few DEGs identified in GSE75360, GSE71994, and part of the GSE74144 datasets. GSEA and functional enrichment of gene module of interest have indicated that "Heme metabolism," "TNF alpha/NFkB," and "interferon alpha response signaling," and MYC target v1/v2 were enriched significantly in different stages of hypertension progression. Significantly, findings from the multiple gene list meta-analysis suggested that FBXW4 and other 13 genes were unique to the hypertension group, and TRIM11 and other 40 genes were mainly involved in hypertension with the left ventricular remodeling group, while the other 18 genes including F13A1 significantly enriched in uncontrolled hypertension. Collectively, the precise switch of the "immune-metabolic-inflammatory" loop pathway was the most significant hallmark across different stages of hypertension, thereby providing a potential therapeutic target for uncontrolled hypertension treatment.

Kidney omics in hypertension: from statistical associations to biological mechanisms and clinical applications

Hypertension is a major cardiovascular disease risk factor and contributor to premature death globally. Family-based investigations confirmed a significant heritable component of blood pressure (BP), whereas genome-wide association studies revealed >1000 common and rare genetic variants associated with BP and/or hypertension. The kidney is not only an organ of key relevance to BP regulation and the development of hypertension, but it also acts as the tissue mediator of genetic predisposition to hypertension. The identity of kidney genes, pathways, and related mechanisms underlying the genetic associations with BP has started to emerge through integration of genomics with kidney transcriptomics, epigenomics, and other omics as well as through applications of causal inference, such as Mendelian randomization. Single-cell methods further enabled mapping of BP-associated kidney genes to cell types, and in conjunction with other omics, started to illuminate the biological mechanisms underpinning associations of BP-associated genetic variants and kidney genes. Polygenic risk scores derived from genome-wide association studies and refined on kidney omics hold the promise of enhanced diagnostic prediction, whereas kidney omics-informed drug discovery is likely to contribute new therapeutic opportunities for hypertension and hypertension-mediated kidney damage.

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

Recent genome-wide association studies uncovered part of blood pressure’s heritability. However, there is still a vast gap between genetics and biology that needs to be bridged. Here, we followed up blood pressure genome-wide summary statistics of over 750,000 individuals, leveraging comprehensive epigenomic and transcriptomic data from blood with a follow-up in cardiovascular tissues to prioritise likely causal genes and underlying blood pressure mechanisms. We first prioritised genes based on coding consequences, multilayer molecular associations, blood pressure-associated expression levels, and coregulation evidence. Next, we followed up the prioritised genes in multilayer studies of genomics, epigenomics, and transcriptomics, functional enrichment, and their potential suitability as drug targets. Our analyses yielded 1880 likely causal genes for blood pressure, tens of which are targets of the available licensed drugs. We identified 34 novel genes for blood pressure, supported by more than one source of biological evidence. Twenty-eight (82%) of these new genes were successfully replicated by transcriptome-wide association analyses in a large independent cohort (n = ~220,000). We also found a substantial mediating role for epigenetic regulation of the prioritised genes. Our results provide new insights into genetic regulation of blood pressure in terms of likely causal genes and involved biological pathways offering opportunities for future translation into clinical practice.

Epigenomic and transcriptomic analyses define core cell types, genes and targetable mechanisms for kidney disease

More than 800 million people suffer from kidney disease, yet the mechanism of kidney dysfunction is poorly understood. In the present study, we define the genetic association with kidney function in 1.5 million individuals and identify 878 (126 new) loci. We map the genotype effect on the methylome in 443 kidneys, transcriptome in 686 samples and single-cell open chromatin in 57,229 kidney cells. Heritability analysis reveals that methylation variation explains a larger fraction of heritability than gene expression. We present a multi-stage prioritization strategy and prioritize target genes for 87% of kidney function loci. We highlight key roles of proximal tubules and metabolism in kidney function regulation. Furthermore, the causal role of SLC47A1 in kidney disease is defined in mice with genetic loss of Slc47a1 and in human individuals carrying loss-of-function variants. Our findings emphasize the key role of bulk and single-cell epigenomic information in translating genome-wide association studies into identifying causal genes, cellular origins and mechanisms of complex traits.

A Formative Study of the Implementation of Whole Genome Sequencing in Northern Ireland

Background: The UK 100,000 Genomes Project was a transformational research project which facilitated whole genome sequencing (WGS) diagnostics for rare diseases. We evaluated experiences of introducing WGS in Northern Ireland, providing recommendations for future projects. Methods: This formative evaluation included (1) an appraisal of the logistics of implementing and delivering WGS, (2) a survey of participant self-reported views and experiences, (3) semi-structured interviews with healthcare staff as key informants who were involved in the delivery of WGS and (4) a workshop discussion about interprofessional collaboration with respect to molecular diagnostics. Results: We engaged with >400 participants, with detailed reflections obtained from 74 participants including patients, caregivers, key National Health Service (NHS) informants, and researchers (patient survey n = 42; semi-structured interviews n = 19; attendees of the discussion workshop n = 13). Overarching themes included the need to improve rare disease awareness, education, and support services, as well as interprofessional collaboration being central to an effective, mainstreamed molecular diagnostic service. Conclusions: Recommendations for streamlining precision medicine for patients with rare diseases include administrative improvements (e.g., streamlining of the consent process), educational improvements (e.g., rare disease training provided from undergraduate to postgraduate education alongside genomics training for non-genetic specialists) and analytical improvements (e.g., multidisciplinary collaboration and improved computational infrastructure).

Genetics in chronic kidney disease: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference

Numerous genes for monogenic kidney diseases with classical patterns of inheritance, as well as genes for complex kidney diseases that manifest in combination with environmental factors, have been discovered. Genetic findings are increasingly used to inform clinical management of nephropathies, and have led to improved diagnostics, disease surveillance, choice of therapy, and family counseling. All of these steps rely on accurate interpretation of genetic data, which can be outpaced by current rates of data collection. In March of 2021, Kidney Diseases: Improving Global Outcomes (KDIGO) held a Controversies Conference on "Genetics in Chronic Kidney Disease (CKD)" to review the current state of understanding of monogenic and complex (polygenic) kidney diseases, processes for applying genetic findings in clinical medicine, and use of genomics for defining and stratifying CKD. Given the important contribution of genetic variants to CKD, practitioners with CKD patients are advised to "think genetic," which specifically involves obtaining a family history, collecting detailed information on age of CKD onset, performing clinical examination for extrarenal symptoms, and considering genetic testing. To improve the use of genetics in nephrology, meeting participants advised developing an advanced training or subspecialty track for nephrologists, crafting guidelines for testing and treatment, and educating patients, students, and practitioners. Key areas of future research, including clinical interpretation of genome variation, electronic phenotyping, global representation, kidney-specific molecular data, polygenic scores, translational epidemiology, and open data resources, were also identified.

Breast cancer chemotherapy induces vascular dysfunction and hypertension through NOX4 dependent mechanism

Cardiovascular disease is the major cause of morbidity and mortality in breast cancer survivors. Chemotherapy contributes to this risk. We aimed to define the mechanisms of long-term vascular dysfunction caused by neoadjuvant chemotherapy (NACT) and identify novel therapeutic targets.We studied arteries from postmenopausal women who had undergone breast cancer treatment using docetaxel, doxorubicin and cyclophosphamide (NACT), and women with no history of such treatment matched for key clinical parameters. Mechanisms were explored in wild-type and Nox4-/- mice and human microvascular endothelial cells.Endothelium-dependent vasodilatation is severely impaired in patients after NACT, while endothelium-independent responses remain normal. This was mimicked by 24-hour exposure of arteries to NACT agents ex-vivo. When applied individually, only docetaxel impaired endothelial function in human vessels. Mechanistic studies showed that NACT increased inhibitory eNOS phosphorylation of threonine 495 in a ROCK-dependent manner and augmented vascular superoxide and hydrogen peroxide production and NADPH oxidase activity. Docetaxel increased expression of NADPH oxidase NOX4 in endothelial and smooth muscle cells and NOX2 in the endothelium. NOX4 increase in human arteries may be mediated epigenetically by diminished DNA methylation of the NOX4 promoter. Docetaxel induced endothelial dysfunction and hypertension in mice. These were prevented in Nox4-/- and by pharmacological inhibition of Nox4 or Rock.Commonly used chemotherapeutic agents, and in particular, docetaxel, alter vascular function by promoting inhibitory phosphorylation of eNOS and enhancing ROS production by NADPH oxidases.

Integrating gene expression and clinical data to identify drug repurposing candidates for hyperlipidemia and hypertension

Discovering novel uses for existing drugs, through drug repurposing, can reduce the time, costs, and risk of failure associated with new drug development. However, prioritizing drug repurposing candidates for downstream studies remains challenging. Here, we present a high-throughput approach to identify and validate drug repurposing candidates. This approach integrates human gene expression, drug perturbation, and clinical data from publicly available resources. We apply this approach to find drug repurposing candidates for two diseases, hyperlipidemia and hypertension. We screen >21,000 compounds and replicate ten approved drugs. We also identify 25 (seven for hyperlipidemia, eighteen for hypertension) drugs approved for other indications with therapeutic effects on clinically relevant biomarkers. For five of these drugs, the therapeutic effects are replicated in the All of Us Research Program database. We anticipate our approach will enable researchers to integrate multiple publicly available datasets to identify high priority drug repurposing opportunities for human diseases.

Mendelian Randomization Analysis as a Tool to Gain Insights into Causes of Diseases: A Primer

Many Mendelian randomization (MR) studies have been published recently, with inferences on the causal relationships between risk factors and diseases that have potential implications for clinical research. In nephrology, MR methods have been applied to investigate potential causal relationships of traditional risk factors, lifestyle factors, and biomarkers from omics technologies with kidney function or CKD. This primer summarizes the basic concepts of MR studies, highlighting methods used in recent applications, and emphasizes key elements in conducting and reporting of MR studies that are important for interpreting the results.

Discovery and implications of polygenicity of common diseases

The sequencing of the human genome has allowed the study of the genetic architecture of common diseases: the number of genomic variants that contribute to risk of disease and their joint frequency and effect size distribution. Common diseases are polygenic, with many loci contributing to phenotype, and the cumulative burden of risk alleles determines individual risk in conjunction with environmental factors. Most risk loci occur in noncoding regions of the genome regulating cell- and context-specific gene expression. Although the effect sizes of most risk alleles are small, their cumulative effects in individuals, quantified as a polygenic (risk) score, can identify people at increased risk of disease, thereby facilitating prevention or early intervention.