Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals

Causal relationship between chronic kidney disease, renal function, and venous thromboembolism: a bidirectional Mendelian randomization study

BACKGROUND

Chronic kidney disease (CKD) and impaired renal function have been implicated in venous thromboembolism (VTE), but their causal relationships remain uncertain. This study employs Mendelian randomization (MR) to elucidate the potential bidirectional causal effects between CKD, renal function biomarkers, and VTE.

METHODS

We collated datasets from genome-wide association studies conducted among European individuals to perform MR analyses. The primary method utilized was the random-effect inverse variance-weighted (IVW) approach, with MR-Egger and the weighted median approaches employed as supplemental techniques. Several sensitivity studies were performed to assess the findings' robustness.

RESULTS

We identified a link between elevated serum creatinine levels and both VTE (OR: 1.14, 95% CI: 1.05-1.24, p = 0.001) and PE (OR: 1.20, 95% CI: 1.08-1.33, p = 0.001). After outlier removal and Bonferroni correction, the Cr-VTE association lost significance (p = 0.005). A suggestive causal relationship was found between eGFR and VTE (OR: 0.38, 95% CI: 0.20-0.73, p = 0.004), DVT (OR: 0.37, 95% CI: 0.16-0.87, p = 0.022), and PE (OR: 0.29, 95% CI: 0.12-0.66, p = 0.004). No causal effects of CKD or BUN on VTE or its subtypes were observed. Reverse causality inferences did not reveal any meaningful results.

CONCLUSIONS

This MR analysis provides evidence that elevated serum creatinine is associated with a higher risk of VTE and PE, while reduced eGFR may be a potential risk factor for VTE and its subtypes. These findings highlight the need for proactive monitoring and preventive strategies in individuals with impaired renal function. Further studies are warranted to confirm these associations and explore underlying mechanisms.

Causal associations between circulating metabolites and chronic kidney disease: a Mendelian randomization study

BACKGROUND

Circulating metabolites have been associated with cross-sectional renal function in population-based research. Nevertheless, there is currently little proof to support the idea that metabolites either cause or prevent renal function. New treatment targets and ways to screen individuals with impaired renal function will be made possible via an in-depth analysis of the causal relationship between blood metabolites and renal function.

METHODS

We assessed the causal relationship between 452 serum metabolites and six renal phenotypes (CKD, rapid progression to CKD [CKDi25], rapid eGFR decline [CKD rapid3], dialysis, estimated glomerular filtration rate, and blood urea nitrogen) using univariate Mendelian randomization, primarily employing the inverse variance weighted method with robust sensitivity analyses. Heterogeneity and pleiotropy were examined via Cochrane's Q test and MR-Egger regression, and statistical significance was adjusted using Bonferroni correction. To assess potential adverse effects of metabolite modulation, we conducted a phenome-wide Mendelian randomization analysis, followed by multivariate Mendelian randomization to adjust for confounders.

RESULTS

We identified glycine and N-acetylornithine as potential causal mediators of CKD and renal dysfunction. Notably, lowering glycine levels may increase the risk of cholelithiasis and cholecystitis, while reducing N-acetylornithine could have unintended effects on tinnitus.

CONCLUSION

Glycine and N-acetylornithine represent promising therapeutic targets for CKD and renal function preservation, but their modulation requires careful risk-benefit assessment to avoid adverse effects.

Association between estrogen and kidney function: population based evidence and mutual bidirectional Mendelian randomization study

BACKGROUND

Previous studies have suggested a potential role of estrogen in the pathophysiology of chronic kidney disease (CKD); however, the association and causality between estrogen and kidney function remain unclear.

METHODS

The cross-sectional correlation between serum estradiol concentration and estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (ACR) was analyzed using data from the National Health and Nutrition Examination Survey 2013-2016. Causality was tested using mutual bidirectional Mendelian randomization (MR) approaches based on six large-scale GWAS studies. Weighted generalized multivariate linear regression was employed to estimate the association between estradiol and eGFR and ACR, and a restricted cubic spline analysis was utilized to investigate potential nonlinear relationships.

RESULTS

A total of 8932 participants were included. Serum estradiol concentration was positively associated with eGFR after adjusting for potential covariates (β, 0.76; 95% CI 0.24 to 1.27) and with ACR (β, 5.99; 95% CI 1.62 to 10.36). A nonlinear positive association was found between estradiol and eGFR, while an inverse "V"-shaped relationship was seen with ACR. Sensitivity analyses confirmed the stability of the relationship between estradiol and eGFR but indicated a less robust association with ACR. Stratified analysis showed that the association between estradiol and eGFR was particularly significant in populations with CKD and hypertension. All forward MR analyses demonstrated a positive causal relationship between estradiol and eGFR, but no causality was found between estradiol and ACR. No reverse causal association was observed.

CONCLUSIONS

Serum estradiol concentration was causally associated with eGFR. Further longitudinal research is needed to validate these findings.

New composite phenotypes enhance chronic kidney disease classification and genetic associations

Chronic kidney disease (CKD) is a multifactorial condition driven by diverse etiologies that lead to a gradual loss of kidney function. Although genome-wide association studies (GWAS) have identified numerous genetic loci linked to CKD, a large portion of its genetic basis remains unexplained. This knowledge gap may partly arise from the reliance on single biomarkers, such as estimated glomerular filtration rate (eGFR), to assess kidney function. To address this limitation, we developed and applied a novel multi-phenotype approach, combinatorial Principal Component Analysis (cPCA), to better understand the complex genetic architecture of CKD. Using UK Biobank dataset (n = 337,112), we analyzed 21 CKD-related phenotypes, generating over 2 million composite phenotypes (CPs) through cPCA. Nearly 50,000 of these CPs demonstrated significantly higher classification power for clinical CKD compared to individual biomarkers. The top-ranked CP-a combination of albumin, cystatin C, eGFR, gamma-glutamyltransferase, HbA1c, low-density lipoprotein, and microalbuminuria, achieved an AUC of 0.878 (95% CI: 0.873-0.882), significantly outperforming eGFR alone (AUC: 0.830, 95% CI: 0.825-0.835). Genetic association analysis of the ~ 50,000 high-performing CPs identified all major eGFR-associated loci, except for the SH2B3 locus rs3184504, a loss-of-function variant, which was uniquely identified in CPs (p = 3.1[Formula: see text]10-56) but not in eGFR within the same sample size. In addition, SH2B3 locus showed strong evidence of colocalization with eGFR, supporting its role in kidney function. These results highlight the power of the multi-phenotype cPCA approach in understanding the genetic basis of CKD, with potential applications to other complex diseases.

Renal-Cardiac Crosstalk in the Pathogenesis and Progression of Heart Failure

Chronic kidney disease (CKD) represents a global health issue with a high socioeconomic impact. Beyond a progressive decline of kidney function, patients with CKD are at increased risk of cardiovascular diseases, including heart failure (HF) and sudden cardiac death. HF in CKD can manifest both as HF with reduced ejection fraction and HF with preserved ejection fraction, with the latter further increasing in relative importance in the more advanced stages of CKD. Typical cardiac remodeling characteristics in uremic cardiomyopathy include left ventricular hypertrophy, myocardial fibrosis, cardiac electrical dysregulation, capillary rarefaction, and microvascular dysfunction, which are triggered by increased cardiac preload, cardiac afterload, and preload and afterload-independent factors. The pathophysiological mechanisms underlying cardiac remodeling in CKD are multifactorial and include neurohormonal activation (with increased activation of the renin-angiotensin-aldosterone system, the sympathetic nervous system, and mineralocorticoid receptor signaling), cardiac steroid activation, mitochondrial dysfunction, inflammation, innate immune activation, and oxidative stress. Furthermore, disturbances in cardiac metabolism and calcium homeostasis, macrovascular and microvascular dysfunction, increased cellular profibrotic responses, the accumulation of uremic retention solutes, and mineral and bone disorders also contribute to cardiovascular disease and HF in CKD. Here, we review the current knowledge of HF in CKD, including the clinical characteristics and pathophysiological mechanisms revealed in animal studies. We also elaborate on the detrimental impact of comorbidities of CKD on HF using hypertension as an example and discuss the clinical characteristics of hypertensive heart disease and the genetic predisposition. Overall, this review aims to increase the understanding of HF in CKD to support future research and clinical translational approaches for improved diagnosis and therapy of this vulnerable patient population.

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

AIMS

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Causal Effects From Kidney Function to Plasma Proteome: Integrated Observational and Mendelian Randomization Analysis With >50,000 UK Biobank Participants

PURPOSE

Chronic kidney disease (CKD) causes detrimental systemic effects, including inflammation or apoptosis, which lead to substantial morbidity and mortality. However, the causal effect of reduced kidney function on systemic proteomic signatures is incompletely understood.

METHODS

We performed an integrated Mendelian randomization (MR) and observational analyses to identify the causal association between kidney function and plasma protein levels, based on 1815 plasma protein profiles in 50,407 UK Biobank participants and the CKDGen Phase 4 genome-wide association study (GWAS) meta-analysis for the genetic instruments of eGFR.

RESULTS

The MR analysis revealed 383 plasma proteins causally associated with eGFR. Reduced kidney function was found to be causally associated with an increase in the plasma levels of 381 proteins, among which TNF and IGFBP4 were increased, while the level of two proteins, NPHS1 and SPOCK1, decreased. Apoptosis-related pathway was significantly enriched in the gene-set enrichment analysis. In network analysis, TNF was identified as a hub protein with multiple linkages to molecules included in the TNF-signaling pathways, involved in inflammation, fibrosis, and apoptosis.

CONCLUSIONS

In this proteo-genomic analysis, we identified 383 plasma proteins causally associated with eGFR, highlighting TNF-associated pathways as pathologically relevant processes in kidney disease progression, systemic inflammation, and organ fibrosis, warranting further investigation.

Causal effects of obesity on estimated glomerular filtration rate: a Mendelian randomization and image data analysis study

Background

Obesity has been associated with onset and progression of chronic kidney disease (CKD) but causal relationship remains uncertain. This study investigated how obesity causally affects estimated glomerular filtration rate.

Methods

Cross-sectional and magnetic resonance imaging (MRI) data analyses were performed within the Prospective Investigation of Obesity, Energy, and Metabolism (POEM) study (502 participants, all aged 50 years). Additionally Mendelian randomization was performed using published summary data. Outcomes were creatinine- and cystatin C-based eGFR. Body mass index (BMI) and waist circumference (WC) were used as exposure variables in the cross-sectional and Mendelian randomization analyses. In the imaging data analyses, eGFR was regressed non-parametrically on tissue volume for each 3D voxel and visualized as a correlation "Imiomics" map.

Results

Negative correlations were shown between cystatin C-based eGFR and BMI [beta = -0.190 (95% CI: -0.280 to -0.100)] and WC [beta = -0.160 (95% CI: -0.250 to -0.060)] in an adjusted model. In contrast, a positive association was found for creatinine-based eGFR [BMI beta = 1.20 (95% CI: 0.030 to 0.210) and WC beta = 0.160 (95% CI: 0.070 to 0.260)]. Similar patterns were found using MRI analysis (Imiomics map). Mendelian randomization implied a negative causal effect of obesity-related measures on cystatin C-based eGFR [BMI beta = -0.031 (95% CI: -0.037 to -0.026) and WC beta = -0.038 (95% CI: -0.045 to -0.031)], but no statistically significant effect was found for creatinine-based eGFR.

Conclusion

This study suggests a causal negative effect of obesity on cystatin C-based, but not creatinine-based eGFR. These findings warrant further research regarding estimations of kidney function when assessing obesity and CKD.

Unveiling the Causal Relationship between Thyroid and Kidney Function: A Multivariable Mendelian Randomization

Key Points

Background

Recent studies suggest an association between thyroid dysfunction and kidney function, but the causal relationship remains uncertain. The complex interactions between thyroid-stimulating hormone (TSH), free thyroxine (fT4), and thyroid peroxidase antibodies (TPOAb) complicate the assessment of this link. This study employed multivariable Mendelian randomization (MVMR) to elucidate the causal relationship between thyroid dysfunction and kidney function in East Asian and European populations.

Methods

We conducted a cross-sectional study and MVMR analysis using data from 17,733 participants in the Taiwan Biobank. Thyroid function was assessed by measuring TSH, fT4 and TPOAb levels, with hypothyroidism classified as subclinical or overt. The primary outcome was creatinine-based eGFR, calculated using the CKD Epidemiology Collaboration equation. Observational analyses were adjusted for age, sex, body mass index, and metabolic and cardiovascular factors. MVMR analyses used genetic variants associated with TSH, fT4, and TPOAb levels to assess their causal effects on eGFR. Data from the ThyroidOmics and CKD Genetics Consortium were used to replicate findings in European populations.

Results

Both TSH and fT4 levels were inversely associated with eGFR, and hypothyroidism was correlated with lower eGFR. Conversely, TPOAb was positively associated with eGFR. Mendelian randomization analyses, using 26 genetic variants for TSH, four for fT4, and eight for TPOAb confirmed a causal relationship between TSH and eGFR. Significant causal effects of TSH were observed across various MVMR methods (P values from <0.001 to 0.01), whereas fT4 and TPOAb showed no significant causal effects (both P > 0.05). These findings were consistent in European populations.

Conclusions

The study found that elevated TSH levels are causally associated with reduced kidney function, highlighting the potential importance of thyroid function in kidney health. These findings suggest that thyroid dysfunction should be considered in managing patients with CKD.

Genetic analysis of elevated levels of creatinine and cystatin C biomarkers reveals novel genetic loci associated with kidney function

The rising prevalence of chronic kidney disease (CKD), affecting an estimated 37 million adults in the United States, presents a significant global health challenge. CKD is typically assessed using estimated Glomerular Filtration Rate (eGFR), which incorporates serum levels of biomarkers such as creatinine and cystatin C. However, these biomarkers do not directly measure kidney function; their elevation in CKD results from diminished glomerular filtration. Genome-wide association studies (GWAS) based on eGFR formulas using creatinine (eGFRcre) or cystatin C (eGFRcys) have identified distinct non-overlapping loci, raising questions about whether these loci govern kidney function or biomarker metabolism. In this study, we show that GWAS on creatinine and cystatin C levels in healthy individuals reveal both nonoverlapping genetic loci impacting their metabolism as well as overlapping genetic loci associated with kidney function; whereas GWAS on elevated levels of these biomarkers uncover novel loci primarily associated with kidney function in CKD patients.

Improving polygenic risk prediction of renal function by removing biomarker-specific effects

Biomarkers are frequently used in clinical practice; however, it is essential to consider the genetics that may independently impact their baseline levels in-turn impacting interpretation of results. For example, estimated glomerular filtration rate (eGFR) equations are based on two biomarkers, cystatin C and creatinine, and widely employed in clinical practice. In this work we demonstrate how genetics of the underlying biomarkers impact measurement variability and may explain some of the discrepancies among eGFR equations. To do this we used shared genetic-architecture to identify "shared" (renal-specific) and "biomarker-specific" regions of the genome. The shared polygenic risk score (PRS) explained 60% more of the variability in the most-common creatinine-derived eGFR estimates than either the biomarker-specific PRS or a PRS including all regions. Our findings highlight the necessity of considering biomarker-specific genetics when constructing PRS for eGFR and other biomarker-derived clinical risk estimates.

Preschool age-specific obesity and later-life kidney health: a Mendelian randomization and colocalization study

OBJECTIVES

While the association between obesity and kidney diseases has been found in previous studies, the relationship between preschool-age obesity and later-life kidney health remains unclear, posing challenges for effective interventions in this critical life period.

METHODS

Utilizing the hitherto largest genome-wide association studies, we conducted two-sample mendelian randomization (MR) to estimate the association of preschool age-specific obesity on kidney health and diseases, including blood urea nitrogen (BUN), eGFRcrea, eGFRcys, chronic kidney disease (CKD), IgA nephropathy, and diabetic nephropathy. Then, we applied multivariable Mendelian randomization (MVMR) and stepwise MR to elucidate the role of adult obesity and 12 other potential factors in the pathway between preschool age-specific obesity and kidney health. Finally, we employed colocalization analysis to understand the mechanism of preschool age-specific obesity and kidney damage further by detecting shared causal variants.

RESULTS

Our two-sample MR results indicated that preschool obesity could be associated with kidney health and disease. In addition, we observed a switch in the direction of associations between age-specific body mass index (BMI) and CKD, manifesting as negative associations before 3 years old and positive associations after 3 years old. Furthermore, MVMR and stepwise MR results suggested potential pathways linking preschool obesity to kidney health, involving factors such as adult BMI, circulating high-density lipoprotein cholesterol levels, and circulating C-reactive protein levels. Finally, we detected that preschool-age BMI and kidney function could share causal variants such as rs76111507, rs62107261, rs77165542 in the region of chromosome 2, and rs571312 in the region of chromosome 18.

CONCLUSION

Our study supports the association between preschool obesity and kidney health, emphasizing the role of adult BMI in this relationship. These findings underscore the importance of interventions starting in early childhood and continuing through adulthood to reduce the long-term risk of obesity-related kidney damage.

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

Background

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

Methods

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

Results

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

Conclusions

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

Estimated Glomerular Filtration Rate Decline is Causally Associated with Acute Pulmonary Embolism: A Nested Case-Control and Mendelian Randomization Study

Renal dysfunction is highly prevalent among patients with pulmonary embolism (PE). This study combined population-based study and Mendelian randomization (MR) to observe the relationship between renal function and PE.A nested case-control study were performed using data of PE patients and controls were from two nationwide cohorts, the China pUlmonary thromboembolism REgistry Study (CURES) and China Health and Retirement Longitudinal Survey (CHARLS). Baseline characteristics were balanced using propensity score matching and inverse probability of treatment weighting. Restricted cubic spline models were applied for the relationship between estimated glomerular filtration rate (eGFR) decline and the risk of PE. Bidirectional two-sample MR analyses were performed using genome-wide association study summary statistics for eGFR involving 1,201,909 individuals and for PE from the FinnGen consortium.The nested case-control study including 17,547 participants (6,322 PE patients) found that eGFR distribution was significantly different between PE patients and controls (p < 0.001), PE patients had a higher proportion of eGFR < 60 mL/min/1.73 m2. eGFR below 88 mL/min/1.73 m2 was associated with a steep elevation in PE risk. MR analyses indicated a potential causal effect of eGFR decline on PE (odds ratio = 4·26, 95% confidence interval: 2·07-8·79), with no evidence of horizontal pleiotropy and reverse causality.Our findings support the hypothesis that renal function decline contributes to an elevated PE risk. Together with the high prevalence of chronic kidney diseases globally, there arises the necessity for monitoring and modulation of renal function in effective PE prevention.

Anoctamin 9 determines Ca2+ signals during activation of T-lymphocytes

Background

Activation of T-cells is initiated by an increase in intracellular Ca2+, which underlies positive and negative regulation. Because the phospholipid scramblase and ion channel ANO9 (TMEM16J) was shown previously to regulated Ca2+ signals in renal epithelial cells, we asked whether ANO9 demonstrates a similar regulation in T-cells.

Methods

We used measurements of the intracellular Ca2+ concentration to examine the effects of ANO9 on intracellular Ca2+ signaling and demonstrated expression of ANO9 and its effects on cellular and molecular parameters.

Results

ANO9 was found to be expressed in human lymphocytes, including the Jurkat T-lymphocyte cell line and mouse lymphocytes. ANO9 has been shown to affect intracellular Ca2+ signals in renal epithelial cells. Here we demonstrate the essential role of ANO9 during initiation of intracellular Ca2+ signals in Jurkat T-cells and isolated mouse lymphocytes. ANO9 is essential for the initial rise in intracellular Ca2+ due to influx of extracellular Ca2+ through store-operated ORAI1 Ca2+ entry channels. ANO9 is indispensable for T-cell function, independent on whether cells are activated by stimulation of the T-cell receptor with CD3-antibody or by PMA/phytohemagglutinin.

Conclusions

Upon activation of T-cells and formation of the immunological synapse, ANO9 recruits the Ca2+-ATPase (PMCA) to the plasma membrane, which is supported by the scaffolding protein discs large 1 (DLG1). PMCAs maintain low Ca2+ levels near ORAI1 channels thereby suppressing Ca2+-inhibition of ORAI1 and thus retaining store-operated Ca2+ entry (SOCE). It is suggested that ANO9 has a role in interorganelle communication and regulation of cellular protein trafficking, which probably requires its phospholipid scramblase function.

PPDPF preserves integrity of proximal tubule by modulating NMNAT activity in chronic kidney diseases

Genome-wide association studies (GWAS) have identified loci associated with kidney diseases, but the causal variants, genes, and pathways involved remain elusive. Here, we identified a kidney disease gene called pancreatic progenitor cell differentiation and proliferation factor (PPDPF) through integrating GWAS on kidney function and multiomic analysis. PPDPF was predominantly expressed in healthy proximal tubules of human and mouse kidneys via single-cell analysis. Further investigations revealed that PPDPF functioned as a thiol-disulfide oxidoreductase to maintain cellular NAD+ levels. Deficiency in PPDPF disrupted NAD+ and mitochondrial homeostasis by impairing the activities of nicotinamide mononucleotide adenylyl transferases (NMNATs), thereby compromising the function of proximal tubules during injuries. Consequently, knockout of PPDPF notably accelerated the progression of chronic kidney disease (CKD) in mouse models induced by aging, chemical exposure, and obstruction. These findings strongly support targeting PPDPF as a potential therapy for kidney fibrosis, offering possibilities for future CKD interventions.

Metabolomics profiling in multi-ancestral individuals with type 2 diabetes in Singapore identified metabolites associated with renal function decline

AIMS/HYPOTHESIS

This study aims to explore the association between plasma metabolites and chronic kidney disease progression in individuals with type 2 diabetes.

METHODS

We performed a comprehensive metabolomic analysis in a prospective cohort study of 5144 multi-ancestral individuals with type 2 diabetes in Singapore, using eGFR slope as the primary outcome of kidney function decline. In addition, we performed genome-wide association studies on metabolites to assess how these metabolites could be genetically influenced by metabolite quantitative trait loci and performed colocalisation analysis to identify genes affecting both metabolites and kidney function.

RESULTS

Elevated levels of 61 lipids with long unsaturated fatty acid chains such as phosphatidylethanolamines, triacylglycerols, diacylglycerols, ceramides and deoxysphingolipids were prospectively associated with more rapid kidney function decline. In addition, elevated levels of seven amino acids and three lipids in the plasma were associated with a slower decline in eGFR. We also identified 15 metabolite quantitative trait loci associated with these metabolites, within which variants near TM6SF2, APOE and CPS1 could affect both metabolite levels and kidney functions.

CONCLUSIONS/INTERPRETATION

Our study identified plasma metabolites associated with prospective renal function decline, offering insights into the underlying mechanism by which the metabolite abnormalities due to fatty acid oversupply might reflect impaired β-oxidation and associate with future chronic kidney disease progression in individuals with diabetes.

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.

SPAGRM: effectively controlling for sample relatedness in large-scale genome-wide association studies of longitudinal traits

Sample relatedness is a major confounder in genome-wide association studies (GWAS), potentially leading to inflated type I error rates if not appropriately controlled. A common strategy is to incorporate a random effect related to genetic relatedness matrix (GRM) into regression models. However, this approach is challenging for large-scale GWAS of complex traits, such as longitudinal traits. Here we propose a scalable and accurate analysis framework, SPAGRM, which controls for sample relatedness via a precise approximation of the joint distribution of genotypes. SPAGRM can utilize GRM-free models and thus is applicable to various trait types and statistical methods, including linear mixed models and generalized estimation equations for longitudinal traits. A hybrid strategy incorporating saddlepoint approximation greatly increases the accuracy to analyze low-frequency and rare genetic variants, especially in unbalanced phenotypic distributions. We also introduce SPAGRM(CCT) to aggregate the results following different models via Cauchy combination test. Extensive simulations and real data analyses demonstrated that SPAGRM maintains well-controlled type I error rates and SPAGRM(CCT) can serve as a broadly effective method. Applying SPAGRM to 79 longitudinal traits extracted from UK Biobank primary care data, we identified 7,463 genetic loci, making a pioneering attempt to conduct GWAS for these traits as longitudinal traits.

Separating the Effects of Early-Life and Adult Body Size on Chronic Kidney Disease Risk: A Mendelian Randomization Study

Background

Whether there is a causal relationship between childhood obesity and increased risk of chronic kidney disease (CKD) remains controversial. This study sought to explore how body size in childhood and adulthood independently affects CKD risk in later life using a Mendelian randomization (MR) approach.

Methods

Univariate and multivariate MR was used to estimate total and independent effects of body size exposures. Genetic associations with early-life and adult body size were obtained from a genome-wide association study of 453,169 participants in the U.K. Biobank, and genetic associations with CKD were obtained from the CKDGen and FinnGen consortia.

Results

A larger genetically predicted early-life body size was associated with an increased risk of CKD (odds ratio [OR], 1.27; 95% confidence interval [CI], 1.14 to 1.41; P=1.70E-05) and increased blood urea nitrogen (BUN) levels (β=0.010; 95% CI, 0.005 to 0.021; P=0.001). However, the association between the impact of early-life body size on CKD (OR, 1.12; 95% CI, 0.95 to 1.31; P=0.173) and BUN level (β=0.001; 95% CI, -0.010 to 0.012; P=0.853) did not remain statistically significant after adjustment for adult body size. Larger genetically predicted adult body size was associated with an increased risk of CKD (OR, 1.37; 95% CI, 1.21 to 1.54; P=4.60E-07), decreased estimated glomerular filtration rate (β=-0.011; 95% CI, -0.017 to -0.006; P=5.79E-05), and increased BUN level (β=0.010; 95% CI, 0.002 to 0.019; P=0.018).

Conclusion

Our research indicates that the significant correlation between early-life body size and CKD risk is likely due to maintaining a large body size into adulthood.

Epigenome-wide association study of Chinese monozygotic twins identifies DNA methylation loci associated with estimated glomerular filtration rate

BACKGROUND

DNA methylation (DNAm) has been shown in multiple studies to be associated with the estimated glomerular filtration rate (eGFR). However, studies focusing on Chinese populations are lacking. We conducted an epigenome-wide association study to investigate the association between DNAm and eGFR in Chinese monozygotic twins.

METHODS

Genome-wide DNAm level was detected using Reduced Representation Bisulfite Sequencing test. Generalized estimation equation (GEE) was used to examine the association between Cytosine-phosphate-Guanines (CpGs) DNAm and eGFR. Inference about Causation from Examination of FAmiliaL CONfounding was employed to infer the causal relationship. The comb-p was used to identify differentially methylated regions (DMRs). GeneMANIA was used to analyze the gene interaction network. The Genomic Regions Enrichment of Annotations Tool enriched biological functions and pathways. Gene expression profiling sequencing was employed to measure mRNA expression levels, and the GEE model was used to investigate the association between gene expression and eGFR. The candidate gene was validated in a community population by calculating the methylation risk score (MRS).

RESULTS

A total of 80 CpGs and 28 DMRs, located at genes such as OLIG2, SYNGR3, LONP1, CDCP1, and SHANK1, achieved genome-wide significance level (FDR < 0.05). The causal effect of DNAm on eGFR was supported by 12 CpGs located at genes such as SYNGR3 and C9orf3. In contrast, the causal effect of eGFR on DNAm is proved by 13 CpGs located at genes such as EPHB3 and MLLT1. Enrichment analysis revealed several important biological functions and pathways related to eGFR, including alpha-2A adrenergic receptor binding pathway and corticotropin-releasing hormone receptor activity pathway. GeneMANIA results showed that SYNGR3 was co-expressed with MLLT1 and had genetic interactions with AFF4 and EDIL3. Gene expression analysis found that SYNGR3 expression was negatively associated with eGFR. Validation analysis showed that the MRS of SYNGR3 was positively associated with low eGFR levels.

CONCLUSIONS

We identified a set of CpGs, DMRs, and pathways potentially associated with eGFR, particularly in the SYNGR3 gene. These findings provided new insights into the epigenetic modifications related to the decline in eGFR and chronic kidney disease.

Genome-wide characterization of 54 urinary metabolites reveals molecular impact of kidney function

Dissecting the genetic mechanisms underlying urinary metabolite concentrations can provide molecular insights into kidney function and open possibilities for causal assessment of urinary metabolites with risk factors and disease outcomes. Proton nuclear magnetic resonance metabolomics provides a high-throughput means for urinary metabolite profiling, as widely applied for blood biomarker studies. Here we report a genome-wide association study meta-analysed for 3 European cohorts comprising 8,011 individuals, covering both people with type 1 diabetes and general population settings. We identify 54 associations (p < 9.3 × 10-10) for 19 of 54 studied metabolite concentrations. Out of these, 33 were not reported previously for relevant urinary or blood metabolite traits. Subsequent two-sample Mendelian randomization analysis suggests that estimated glomerular filtration rate causally affects 13 urinary metabolite concentrations whereas urinary ethanolamine, an initial precursor for phosphatidylcholine and phosphatidylethanolamine, was associated with higher eGFR lending support for a potential protective role. Our study provides a catalogue of genetic associations for 53 metabolites, enabling further investigation on how urinary metabolites are linked to human health.

The impact of homocysteine on patients with diabetic nephropathy: a mendelian randomization study

BACKGROUND/AIMS

Homocysteine (Hcy) has been associated with an increased risk of diabetic nephropathy (DN) in patients, but there is still controversy. This study aims to investigate the causal relationship between plasma Hcy and DN.

METHODS

A Mendelian randomization (MR) study using data from 2 samples was employed to infer causal relationships. The aggregated genetic data associated with Hcy was derived from the largest genome-wide association study (GWAS) to date, involving 44,147 individuals of European ancestry.Data on SNP-diabetic nephropathy, creatinine, and urea nitrogen were obtained from the IEU GWAS database. The analysis method employed a fixed-effect or random-effect inverse variance-weighted approach to estimate effects.Additional analysis methods were used to assess stability and sensitivity. The potential for pleiotropy was evaluated using the MR-Egger intercept test.

RESULTS

Using 12 SNPs as instrumental variables, two-sample MR analysis revealed no evidence of a causal relationship between genetically predicted plasma Hcy levels and diabetic nephropathy, as well as creatinine and blood urea nitrogen levels. This finding is consistent with the results obtained from other testing methods.

CONCLUSIONS

Two-sample Mendelian Randomization analysis found no evidence of a causal relationship between plasma homocysteine levels and diabetic nephropathy, creatinine, or urea.

UMOD Genotype and Determinants of Urinary Uromodulin in African Populations

Introduction

Single-nucleotide polymorphisms (SNPs) in the UMOD -PDILT genetic locus are associated with chronic kidney disease (CKD) in European populations, through their effect on urinary uromodulin (uUMOD) levels. The genetic and nongenetic factors associated with uUMOD in African populations remain unknown.

Methods

Clinical parameters, 3 selected UMOD-PDILT SNPs and uUMOD levels were obtained in 1202 young Black and White adults from the African-PREDICT study and 1943 middle aged Black adults from the PURE-NWP-SA study, 2 cross-sectional, observational studies.

Results

Absolute uUMOD and uUMOD/creatinine levels were lower in Black participants compared to White participants. The prime CKD-risk allele at rs12917707 was more prevalent in Black individuals, with strikingly more risk allele homozygotes compared to White individuals. Haplotype analysis of the UMOD-PDILT locus predicted more recombination events and linkage disequilibrium (LD) fragmentation in Black individuals. Multivariate testing and sensitivity analysis showed that higher uUMOD/creatinine associated specifically with risk alleles at rs12917707 and rs12446492 in White participants and with higher serum renin and lower urine albumin-to-creatinine ratio in Black participants, with a significant interaction of ethnicity on the relationship between all 3 SNPs and uUMOD/creatinine. The multiple regression model explained a greater percentage of the variance of uUMOD/creatinine in White adults compared to Black adults (23% vs. 8%).

Conclusion

We evidenced ethnic differences in clinical and genetic determinants of uUMOD levels, in particular an interaction of ethnicity on the relationship between CKD-risk SNPs and uUMOD. These differences should be considered when analyzing the role of uromodulin in kidney function, interpreting genome-wide association studies (GWAS), and precision medicine recommendations.

Renal function and risk of dementia: a Mendelian randomization study

BACKGROUND

The burgeoning recognition of the nexus between renal functionality and the prevalence of dementia has precipitated a surge in research endeavors. This study aims to substantiate the causal relationship between kidney functionality and dementia.

METHODS

We utilized clinical renal function metrics from the Chronic Kidney Disease Genetics (CKDGen) Consortium and diverse dementia types (Alzheimer's disease [AD] and vascular dementia) from the FinnGen Biobank by using Mendelian randomization analysis. At the stratum of genetic susceptibility, we tested the causal relationship between variations index in renal function and the occurrence of dementia. Inverse-variance weighted (IVW) method was the main analysis, and several supplementary analyses and sensitivity analyses were performed to test the causal estimates.

RESULTS

The findings indicate a significant correlation between each unit increase in cystatin C-based estimated glomerular filtration rate (eGFR-cys) levels was significantly associated with a reduction in the incidence of late-onset Alzheimer's disease (LOAD) (IVW: OR = 0.35, 95% CI: 0.13-0.91, p = 0.031). After adjusting for creatinine-based eGFR (eGFR-cre) and urinary albumin-to-creatinine ratio (UACR), a causal relationship was still identified between elevated levels of eGFR-cys and decreased risk of LOAD (IVW: OR: 0.08; 95% CI: 0.01-0.97, p = 0.047). Sensitivity tests demonstrated the reliability of causal estimates.

CONCLUSIONS

The association between renal function based on cystatin C and the augmented risk of developing AD lends support to the perspective that regular monitoring of cystatin C may be a valuable investigative biomarker.

Elucidating the causal nexus and immune mediation between frailty and chronic kidney disease: integrative multi-omics analysis

BACKGROUND

Empirical research has consistently documented the concurrent manifestation of frailty and chronic kidney disease (CKD). However, the existence of a reverse causal association or the influence of confounding variables on these correlations remains ambiguous.

METHODS

Our analysis of 7,078 participants from National Health and Nutrition Examination Survey(NHANES) (1999-2018) applied weighted logistic regression and Mendelian Randomization (MR) to investigate the correlation between the frailty index (FI) and renal function. The multivariate MR analysis was specifically adjusted for type 2 diabetes and hypertension. Further analysis explored 3282 plasma proteins to link FI to CKD. A two-step network MR highlighted immune cells' mediating roles in the FI-CKD relationship.

RESULT

Genetically inferred FI and various renal function markers are significantly correlated, as supported by NHANES analyses. Multivariate MR analysis revealed a direct causal association between the FI and CKD. Additionally, our investigation into plasma proteins identified Tmprss11D and MICB correlated with FI and CKD, respectively. A two-step network MR to reveal 15 immune cell types, notably Central Memory CD4+ T cells and Lymphocytes, as crucial mediators between FI and CKD.

CONCLUSION

Our work establishes a causal connection between frailty and CKD, mediated by specific immune cell profiles. These findings highlight the importance of immune mechanisms in the frailty-CKD interplay and suggest that targeting shared risk factors and immune pathways could improve management strategies for these conditions. Our research contributes to a more nuanced understanding of frailty and CKD, offering new avenues for intervention and patient care in an aging population.

Analyzing longitudinal trait trajectories using GWAS identifies genetic variants for kidney function decline

Understanding the genetics of kidney function decline, or trait change in general, is hampered by scarce longitudinal data for GWAS (longGWAS) and uncertainty about how to analyze such data. We use longitudinal UK Biobank data for creatinine-based estimated glomerular filtration rate from 348,275 individuals to search for genetic variants associated with eGFR-decline. This search was performed both among 595 variants previously associated with eGFR in cross-sectional GWAS and genome-wide. We use seven statistical approaches to analyze the UK Biobank data and simulated data, finding that a linear mixed model is a powerful approach with unbiased effect estimates which is viable for longGWAS. The linear mixed model identifies 13 independent genetic variants associated with eGFR-decline, including 6 novel variants, and links them to age-dependent eGFR-genetics. We demonstrate that age-dependent and age-independent eGFR-genetics exhibit a differential pattern regarding clinical progression traits and kidney-specific gene expression regulation. Overall, our results provide insights into kidney aging and linear mixed model-based longGWAS generally.

Genome-wide association analysis of cystatin c and creatinine kidney function in Chinese women

BACKGROUND

With increasing incidence and treatment costs, chronic kidney disease (CKD) has become an important public health problem in China, especially in females. However, the genetic determinants are very limited. The estimated glomerular filtration rate (eGFR) based on creatinine is commonly used as a measure of renal function but can be easily affected by other factors. In contrast, eGFR based on both creatinine and cystatin C (eGFRcr-cys) improved the diagnostic accuracy of CKD. To our knowledge, no genome-wide association analysis of eGFRcr-cys has been conducted in the Chinese population.

METHODS

By conducting a Genome-Wide association study(GWAS), a method used to identify associations between genetic regions (genomes) and traits/diseases, we examined the relationship between genetic factors and eGFRcr-cys in Chinese women, with 1983 participants and 3,838,121 variants included in the final analysis.

RESULT

One significant locus (20p11.21) was identified in the Chinese female population, which has been reported to be associated with eGFR based on cystatin C (eGFRcys) in the European population. More importantly, we found two new suggestive loci (1p31.1 and 11q24.2), which have not yet been reported. A total of three single nucleotide polymorphisms were identified as the most important variants in these regions, including rs2405367 (CST3), rs66588571(KRT8P21), and rs626995 (OR8B2).

CONCLUSION

We identified 3 loci 20p11.21, 1p31.1, and 11q24.2 to be significantly associated with eGFRcr-cys. These findings and subsequent functional analysis describe new biological clues related to renal function in Chinese women and provide new ideas for the diagnosis and treatment development of CKD.

T2DM/CKD genetic risk scores and the progression of diabetic kidney disease in T2DM subjects

This study aimed at understanding the predictive potential of genetic risk scores (GRS) for diabetic kidney disease (DKD) progression in patients with type 2 diabetes mellitus (T2DM) and Major Cardiovascular Events (MCVE) and All-Cause Mortality (ACM) as secondary outcomes. We evaluated 30 T2DM and CKD GWAS-derived single nucleotide polymorphisms (SNPs) and their association with clinical outcomes in a central European cohort (n = 400 patients). Our univariate Cox analysis revealed significant associations of age, duration of diabetes, diastolic blood pressure, total cholesterol and eGFR with progression of DKD (all P < 0.05). However, no single SNP was conclusively associated with progression to DKD, with only CERS2 and SHROOM3 approaching statistical significance. While a single SNP was associated with MCVE - WSF1 (P = 0.029), several variants were associated with ACM - specifically CANCAS1, CERS2 and C9 (all P < 0.02). Our GRS did not outperform classical clinical factors in predicting progression to DKD, MCVE or ACM. More precisely, we observed an increase only in the area under the curve (AUC) in the model combining genetic and clinical factors compared to the clinical model alone, with values of 0.582 (95 % CI 0.487-0.676) and 0.645 (95 % CI 0.556-0.735), respectively. However, this difference did not reach statistical significance (P = 0.06). This study highlights the complexity of genetic predictors and their interplay with clinical factors in DKD progression. Despite the promise of personalised medicine through genetic markers, our findings suggest that current clinical factors remain paramount in the prediction of DKD. In conclusion, our results indicate that GWAS-derived GRSs for T2DM and CKD do not offer improved predictive ability over traditional clinical factors in the studied Czech T2DM population.

TET2 germline variants promote kidney disease by impairing DNA repair and activating cytosolic nucleotide sensors

Genome-wide association studies (GWAS) have identified over 800 loci associated with kidney function, yet the specific genes, variants, and pathways involved remain elusive. By integrating kidney function GWAS with human kidney expression and methylation quantitative trait analyses, we identified Ten-Eleven Translocation (TET) DNA demethylase 2 (TET2) as a novel kidney disease risk gene. Utilizing single-cell chromatin accessibility and CRISPR-based genome editing, we highlight GWAS variants that influence TET2 expression in kidney proximal tubule cells. Experiments using kidney/tubule-specific Tet2 knockout mice indicated its protective role in cisplatin-induced acute kidney injury, as well as in chronic kidney disease and fibrosis induced by unilateral ureteral obstruction or adenine diet. Single-cell gene profiling of kidneys from Tet2 knockout mice and TET2-knockdown tubule cells revealed the altered expression of DNA damage repair and chromosome segregation genes, notably including INO80, another kidney function GWAS target gene itself. Remarkably, both TET2-null and INO80-null cells exhibited an increased accumulation of micronuclei after injury, leading to the activation of cytosolic nucleotide sensor cGAS-STING. Genetic deletion of cGAS or STING in kidney tubules, or pharmacological inhibition of STING, protected TET2-null mice from disease development. In conclusion, our findings highlight TET2 and INO80 as key genes in the pathogenesis of kidney diseases, indicating the importance of DNA damage repair mechanisms.

Single-Ancestry versus Multi-Ancestry Polygenic Risk Scores for CKD in Black American Populations

Key Points

The predictive performance of an African ancestry–specific polygenic risk score (PRS) was comparable to a European ancestry–derived PRS for kidney traits. However, multi-ancestry PRSs outperform single-ancestry PRSs in Black American populations. Predictive accuracy of PRSs for CKD was improved with the use of race-free eGFR.

Background

CKD is a risk factor of cardiovascular disease and early death. Recently, polygenic risk scores (PRSs) have been developed to quantify risk for CKD. However, African ancestry populations are underrepresented in both CKD genetic studies and PRS development overall. Moreover, European ancestry–derived PRSs demonstrate diminished predictive performance in African ancestry populations.

Methods

This study aimed to develop a PRS for CKD in Black American populations. We obtained score weights from a meta-analysis of genome-wide association studies for eGFR in the Million Veteran Program and Reasons for Geographic and Racial Differences in Stroke Study to develop an eGFR PRS. We optimized the PRS risk model in a cohort of participants from the Hypertension Genetic Epidemiology Network. Validation was performed in subsets of Black participants of the Trans-Omics in Precision Medicine Consortium and Genetics of Hypertension Associated Treatment Study.

Results

The prevalence of CKD—defined as stage 3 or higher—was associated with the PRS as a continuous predictor (odds ratio [95% confidence interval]: 1.35 [1.08 to 1.68]) and in a threshold-dependent manner. Furthermore, including APOL1 risk status—a putative variant for CKD with higher prevalence among those of sub-Saharan African descent—improved the score's accuracy. PRS associations were robust to sensitivity analyses accounting for traditional CKD risk factors, as well as CKD classification based on prior eGFR equations. Compared with previously published PRS, the predictive performance of our PRS was comparable with a European ancestry–derived PRS for kidney traits. However, single-ancestry PRSs were less predictive than multi-ancestry–derived PRSs.

Conclusions

In this study, we developed a PRS that was significantly associated with CKD with improved predictive accuracy when including APOL1 risk status. However, PRS generated from multi-ancestry populations outperformed single-ancestry PRS in our study.

Integrative genomic analysis of RNA-modification-single nucleotide polymorphisms associated with kidney function

Introduction

Increasing evidence suggests that RNA modification plays a significant role in the kidney and may be an ideal target for the treatment of kidney diseases. However, the specific mechanisms underlying RNA modifications in the pathogenesis of kidney disease remain unclear. Genome-wide association studies (GWAS) have identified numerous genetic loci involved in kidney function and RNA modifications. The identification and exploration of RNA modification-related single-nucleotide polymorphisms (RNAm-SNPs) associated with kidney function can help us to comprehensively understand the underlying mechanism of kidney disease and identify potential therapeutic targets.

Methods

First, we examined the association of RNAm-SNPs with eGFR. Second, we performed expression quantitative trait locus (eQTL) and protein quantitative trait locus (pQTL) analyses to explore the functions of the identified RNAm-SNPs. Finally, we evaluated the causality between RNAm-SNP-associated gene expression and circulating proteins and kidney function using a Mendelian randomization (MR) analysis.

Results

A total of 252 RNA m-SNPs related to m6A, m1A, A-to-I, m5C, m7G, and m5U were identified. All these factors were significantly associated with the eGFR. A total of 119(47.22 %) RNAm-SNPs showed cis-eQTL effects in blood cells, whereas 72 (28.57 %) RNAm-SNPs showed cis-pQTL effects in plasma. 47 (18.65 %) RNAm-SNPs exhibited cis-eQTL and cis-pQTL effects. In addition, we demonstrated a causal association between RNAm-SNP-associated gene expression, circulating protein levels, and eGFR decline. Some of the identified genes and proteins have been reported to be associated with kidney diseases, such as CDK10 and SDCCAG8.

Conclusions

This study reveals an association between RNAm-SNPs and kidney function. These SNPs regulate gene expression and protein levels through RNA modifications, eventually leading to kidney dysfunction. Our study provides novel insights that connect the genetic risk of kidney disease to RNA modification and suggests potential therapeutic targets for the prevention and treatment of kidney disease.

Discovery and prioritization of genetic determinants of kidney function in 297,355 individuals from Taiwan and Japan

Current genome-wide association studies (GWAS) for kidney function lack ancestral diversity, limiting the applicability to broader populations. The East-Asian population is especially under-represented, despite having the highest global burden of end-stage kidney disease. We conducted a meta-analysis of multiple GWASs (n = 244,952) on estimated glomerular filtration rate and a replication dataset (n = 27,058) from Taiwan and Japan. This study identified 111 lead SNPs in 97 genomic risk loci. Functional enrichment analyses revealed that variants associated with F12 gene and a missense mutation in ABCG2 may contribute to chronic kidney disease (CKD) through influencing inflammation, coagulation, and urate metabolism pathways. In independent cohorts from Taiwan (n = 25,345) and the United Kingdom (n = 260,245), polygenic risk scores (PRSs) for CKD significantly stratified the risk of CKD (p < 0.0001). Further research is required to evaluate the clinical effectiveness of PRSCKD in the early prevention of kidney disease.

Discovering Novel Loci of Chronic Kidney Disease via Principal Component Analysis-Based Multiple-Trait Genome-Wide Association Study

INTRODUCTION

Chronic kidney diseases (CKD) encompass a spectrum of complex pathophysiological processes. While numerous genome-wide association studies (GWASs) have focused on individual traits such as albuminuria, estimated glomerular filtration rate (eGFR), and eGFR change, there remains a paucity of genetic studies integrating these traits collectively for comprehensive evaluation.

METHODS

In this study, we performed individual GWASs for albuminuria, baseline eGFR, and eGFR slope utilizing data from non-diabetic individuals enrolled from the Taiwan Biobank (TWB). Subsequently, we employed principal component analysis to transform these three quantitative traits into principal components (PCs) and performed GWAS based on these principal components (PC-based GWAS).

RESULTS

The individual GWAS analyses of albuminuria, baseline eGFR, and eGFR slope identified 10, 13, and 210 candidate loci respectively, with 2, 3, and 99 of them representing previously reported loci. PC-based GWAS identified additional 20 novel candidate loci linked to CKD (p values ranging from 5.8 × 10-7 to 9.1 × 10-6). Notably, 4 of these 20 single nucleotide polymorphisms (rs9332641, rs10737429, rs117231653, and rs73360624) exhibited significant associations with kidney expression quantitative trait loci.

CONCLUSION

To our knowledge, this study represents the first PC-based GWAS integrating albuminuria, baseline eGFR, and eGFR slope. Our approach found 20 novel candidate loci suggestively associated with CKD, underscoring the value of integrating multiple kidney traits in unraveling the pathophysiology of this complex disorder.

Genetic architecture of routinely acquired blood tests in a British South Asian cohort

Understanding the genetic basis of routinely-acquired blood tests can provide insights into several aspects of human physiology. We report a genome-wide association study of 42 quantitative blood test traits defined using Electronic Healthcare Records (EHRs) of ~50,000 British Bangladeshi and British Pakistani adults. We demonstrate a causal variant within the PIEZO1 locus which was associated with alterations in red cell traits and glycated haemoglobin. Conditional analysis and within-ancestry fine mapping confirmed that this signal is driven by a missense variant - chr16-88716656-G-TT - which is common in South Asian ancestries (MAF 3.9%) but ultra-rare in other ancestries. Carriers of the T allele had lower mean HbA1c values, lower HbA1c values for a given level of random or fasting glucose, and delayed diagnosis of Type 2 Diabetes Mellitus. Our results shed light on the genetic basis of clinically-relevant traits in an under-represented population, and emphasise the importance of ancestral diversity in genetic studies.

Causal relationship between beta-2 microglobulin and B-cell malignancies: genome-wide meta-analysis and a bidirectional two-sample Mendelian randomization study

Background

Beta-2 microglobulin (β2M) is acknowledged as a prognostic biomarker for B-cell malignancies. However, insights into the impact of β2M on B-cell malignancy risk, and vice versa, are limited.

Methods

We conducted a genome-wide meta-analysis (GWMA), bidirectional two-sample Mendelian randomization (TSMR) analysis, and pathway enrichment analysis to explore the causal relationship between β2M and B-cell malignancies and the underlying biological processes.

Results

The GWMA identified 55 lead SNPs across five genomic regions (three novel: WDR72, UMOD, and NLRC5) associated with β2M. In the UKB, genetically predicted β2M showed a positive association with diffuse large B-cell lymphoma (DLBCL; odds ratio [OR]: 1.742 per standard deviation increase in β2M; 95% confidence interval [CI]: 1.215-2.498; P = 3.00 × 10-3; FDR = 7.50× 10-3) and Hodgkin lymphoma (HL; OR: 2.270; 95% CI: 1.525-3.380; P = 5.15 × 10-5; FDR =2.58 × 10-4). However, no associations were found with follicular lymphoma (FL), chronic lymphoid leukemia (CLL), or multiple myeloma (MM). Reverse TSMR analysis revealed no association between genetically predicted B-cell malignancies and β2M. In FinnGen, β2M was found to be associated with an increased risk of DLBCL (OR: 2.098; 95% CI: 1.358-3.242; P = 8.28 × 10-4; FDR = 4.14 × 10-3), HL (OR: 1.581; 95% CI: 1.167-2.142; P = 3.13 × 10-3; FDR = 5.22 × 10-3), and FL (OR: 2.113; 95% CI: 1.292-3.455; P = 2.90 × 10-3; FDR = 5.22 × 10-3). However, no association was found with CLL or MM. Reverse TSMR analysis indicated that genetically predicted DLBCL, FL, and MM may perturb β2M levels. Pathway enrichment analysis suggested that the innate immune system represents a convergent biological process underlying β2M, DLBCL, and HL.

Conclusions

Our findings suggested that elevated levels of β2M were associated with an increased risk of DLBCL and HL, which is potentially linked to dysfunction of the innate immune system.

Estimation of a genetic Gaussian network using GWAS summary data

A genetic Gaussian network of multiple phenotypes, constructed through the inverse matrix of the genetic correlation matrix, is informative for understanding the biological dependencies of the phenotypes. However, its estimation may be challenging because the genetic correlation estimates are biased due to estimation errors and idiosyncratic pleiotropy inherent in GWAS summary statistics. Here, we introduce a novel approach called estimation of genetic graph (EGG), which eliminates the estimation error bias and idiosyncratic pleiotropy bias with the same techniques used in multivariable Mendelian randomization. The genetic network estimated by EGG can be interpreted as shared common biological contributions between phenotypes, conditional on others. We use both simulations and real data to demonstrate the superior efficacy of our novel method in comparison with the traditional network estimators.

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.

Variants in tubule epithelial regulatory elements mediate most heritable differences in human kidney function

Kidney failure, the decrease of kidney function below a threshold necessary to support life, is a major cause of morbidity and mortality. We performed a genome-wide association study (GWAS) of 406,504 individuals in the UK Biobank, identifying 430 loci affecting kidney function in middle-aged adults. To investigate the cell types affected by these loci, we integrated the GWAS with human kidney candidate cis-regulatory elements (cCREs) identified using single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq). Overall, 56% of kidney function heritability localized to kidney tubule epithelial cCREs and an additional 7% to kidney podocyte cCREs. Thus, most heritable differences in adult kidney function are a result of altered gene expression in these two cell types. Using enhancer assays, allele-specific scATAC-seq and machine learning, we found that many kidney function variants alter tubule epithelial cCRE chromatin accessibility and function. Using CRISPRi, we determined which genes some of these cCREs regulate, implicating NDRG1, CCNB1 and STC1 in human kidney function.

Proteome-wide mendelian randomization identifies novel therapeutic targets for chronic kidney disease

There is an urgent need to pinpoint novel targets for drug discovery in the context of chronic kidney disease (CKD), and the proteome represents a significant pool of potential therapeutic targets. To address this, we performed proteome-wide analyses using Mendelian randomization (MR) and colocalization techniques to uncover potential targets for CKD. We extracted summary-level data from the ARIC study, focusing on 7213 European American (EA) individuals and 4657 plasma proteins. To broaden our analysis, we incorporated genetic association data from Icelandic cohorts, thereby enhancing our investigation into the correlations with chronic kidney disease (CKD), creatinine-based estimated glomerular filtration rate (eGFRcrea), and estimated glomerular filtration rate (eGFR). We utilized genetic association data from the GWAS Catalog, including CKD (765,348, 625,219 European ancestry and 140,129 non-European ancestry), eGFRcrea (1,004,040, European ancestry), and eGFR (567,460, European ancestry). Employing MR analysis, we estimated the associations between proteins and CKD risk. Additionally, we conducted colocalization analysis to evaluate the existence of shared causal variants between the identified proteins and CKD. We detected notable correlations between levels predicted based on genetics of three circulating proteins and CKD, eGFRcrea, and eGFR. Notably, our colocalization analysis provided robust evidence supporting these associations. Specifically, genetically predicted levels of Transcription elongation factor A protein 2 (TCEA2) and Neuregulin-4 (NRG4) exhibited an inverse relationship with CKD risk, while Glucokinase regulatory protein (GCKR) showed an increased risk of CKD. Furthermore, our colocalization analysis also supported the associations of TCEA2, NRG4, and GCKR with the risk of eGFRcrea and eGFR.

Association between GATM gene polymorphism and progression of chronic kidney disease: a mitochondrial related genome-wide Mendelian randomization study

Chronic Kidney Disease (CKD) stands as a substantial challenge within the global health landscape. The elevated metabolic demands essential for sustaining normal kidney function have propelled an increasing interest in unraveling the intricate relationship between mitochondrial dysfunction and CKD. However, the authentic causal relationship between these two factors remains to be conclusively elucidated. This study endeavors to address this knowledge gap through the Mendelian Randomization (MR) method. We utilized large-scale QTL datasets (including 31,684 eQTLs samples, 1980 mQTLs samples, and 35,559 pQTLs samples) to precisely identify key genes related to mitochondrial function as exposure factors. Subsequently, we employed GWAS datasets (comprising 480,698 CKD samples and 1,004,040 eGFRcrea samples) as outcome factors. Through a comprehensive multi-level analysis (encompassing expression, methylation, and protein quantification loci), we evaluated the causal impact of these genes on CKD and estimated glomerular filtration rate (eGFR). The integration and validation of diverse genetic data, complemented by the application of co-localization analysis, bi-directional MR analysis, and various MR methods, notably including inverse variance weighted, have collectively strengthened our confidence in the robustness of these findings. Lastly, we validate the outcomes through examination in human RNA sequencing datasets encompassing various subtypes of CKD. This study unveils significant associations between the glycine amidinotransferase (GATM) and CKD, as well as eGFR. Notably, an augmentation in GATM gene and protein expression corresponds to a diminished risk of CKD, whereas distinct methylation patterns imply an increased risk. Furthermore, a discernible reduction in GATM expression is observed across diverse pathological subtypes of CKD, exhibiting a noteworthy positive correlation with GFR. These findings establish a causal relationship between GATM and CKD, thereby highlighting its potential as a therapeutic target. This insight lays the foundation for the development of potential therapeutic interventions for CKD, presenting substantial clinical promise.

A new perspective on selenium's impact on renal function: European population-based analysis of plasma proteome-mediated Mendelian randomization study

Background

The relationship between selenium and renal function has always attracted widespread attention. Increased selenium level has been found to cause impaired renal function in our previous study, but the mechanism is not clear. In this study, we evaluate the potential mediating effects of plasma proteome in the association of selenium level and renal function to understand the mechanisms of selenium's effect on renal function.

Methods

Utilizing two-sample two-step mediating mendelian randomization (MR) methodology to investigate the genetically causal relationship between selenium level and renal function as well as the role of the plasma proteome in mediating them. Additionally, the mediating proteins were enriched and analyzed through bioinformatics to understand the potential mechanisms of selenium effects on renal function.

Results

In the MR analysis, an increase in selenium level was found to decrease estimated glomerular filtration rate (eGFR). Specifically, for each standard deviation (SD) increase in selenium levels, eGFR levels are reduced by 0.003 SD [Beta (95% CI): -0.003 (-0.004 ~ -0.001), P=0.001, with no observed heterogeneity and pleiotropy]. Through mediation analysis, 35 proteins have been determined mediating the genetically causal effects of selenium on the levels of eGFR, including Fibroblast growth factor receptor 4 (FGFR4), Fibulin-1, Cilia- and flagella-associated protein 45, Mothers against decapentaplegic homolog 2 (SMAD2), and E3 ubiquitin-protein ligase ZNRF3, and the mediation effect rates of these proteins ranged from 1.59% to 23.70%. In the enrichment analysis, 13 signal transduction pathways, including FGFR4 mutant receptor activation and Defective SLC5A5 causing thyroid dyshormonogenesis 1, were involved in the effect of selenium on eGFR levels.

Conclusion

Our finding has revealed the underlying mechanism by which increased selenium level lead to deterioration of renal function, effectively guiding the prevention of chronic kidney disease and paving the way for future studies.

Causal effects of obstructive sleep apnea on chronic kidney disease and renal function: a bidirectional Mendelian randomization study

Background

Observational studies have suggested an association between obstructive sleep apnea (OSA), chronic kidney disease (CKD), and renal function, and vice versa. However, the results from these studies are inconsistent. It remains unclear whether there are causal relationships and in which direction they might exist.

Methods

We used a two-sample Mendelian randomization (MR) method to investigate the bidirectional causal relation between OSA and 7 renal function phenotypes [creatinine-based estimated glomerular filtration rate (eGFRcrea), cystatin C-based estimated glomerular filtration rate (eGFRcys), blood urea nitrogen (BUN), rapid progress to CKD, rapid decline of eGFR, urinary albumin to creatinine ratio (UACR) and CKD]. The genome-wide association study (GWAS) summary statistics of OSA were retrieved from FinnGen Consortium. The CKDGen consortium and UK Biobank provided GWAS summary data for renal function phenotypes. Participants in the GWAS were predominantly of European ancestry. Five MR methods, including inverse variance weighted (IVW), MR-Egger, simple mode, weighted median, and weighted mode were used to investigate the causal relationship. The IVW result was considered the primary outcome. Then, Cochran's Q test and MR-Egger were used to detect heterogeneity and pleiotropy. The leave-one-out analysis was used for testing the stability of MR results. RadialMR was used to identify outliers. Bonferroni correction was applied to test the strength of the causal relationships (p < 3.571 × 10-3).

Results

We failed to find any significant causal effect of OSA on renal function phenotypes. Conversely, when we examined the effects of renal function phenotypes on OSA, after removing outliers, we found a significant association between BUN and OSA using IVW method (OR: 2.079, 95% CI: 1.516-2.853; p = 5.72 × 10-6).

Conclusion

This MR study found no causal effect of OSA on renal function in Europeans. However, genetically predicted increased BUN is associated with OSA development. These findings indicate that the relationship between OSA and renal function remains elusive and requires further investigation.

Assessment of the effect of the SLC5A2 gene on eGFR: a Mendelian randomization study of drug targets for the nephroprotective effect of sodium-glucose cotransporter protein 2 inhibition

Aim

Sodium-glucose cotransporter protein 2 (SGLT2) inhibitors have been shown to have renoprotective effects in clinical studies. For further validation in terms of genetic variation, drug-targeted Mendelian randomization (MR) was used to investigate the causal role of SGLT2 inhibition on eGFR effects.

Methods

Genetic variants representing SGLT2 inhibition were selected as instrumental variables. Drug target Mendelian randomization analysis was used to investigate the relationship between SGLT2 inhibitors and eGFR. The IVW method was used as the primary analysis method. As a sensitivity analysis, GWAS pooled data from another CKDGen consortium was used to validate the findings.

Results

MR results showed that hemoglobin A1c (HbA1c) levels, regulated by the SLC5A2 gene, were negatively correlated with eGFR (IVW β -0.038, 95% CI -0.061 to -0.015, P = 0.001 for multi-ancestry populations; IVW β -0.053, 95% CI -0.077 to -0.028, P = 2.45E-05 for populations of European ancestry). This suggests that a 1-SD increase in HbA1c levels, regulated by the SLC5A2 gene, is associated with decreased eGFR. Mimicking pharmacological inhibition by lowering HbA1c per 1-SD unit through SGLT2 inhibition reduces the risk of eGFR decline, demonstrating a renoprotective effect of SGLT2 inhibitors. HbA1c, regulated by the SLC5A2 gene, was negatively correlated with eGFR in both validation datasets (IVW β -0.027, 95% CI -0.046 to -0.007, P=0.007 for multi-ancestry populations, and IVW β -0.031, 95% CI -0.050 to -0.011, P=0.002 for populations of European origin).

Conclusions

The results of this study indicate that the SLC5A2 gene is causally associated with eGFR. Inhibition of SLC5A2 gene expression was linked to higher eGFR. The renoprotective mechanism of SGLT2 inhibitors was verified from the perspective of genetic variation.

Admixture Mapping of Chronic Kidney Disease and Risk Factors in Hispanic/Latino Individuals From Central America Country of Origin

BACKGROUND

Chronic kidney disease (CKD) is highly prevalent in Central America, and genetic factors may contribute to CKD risk. To understand the influences of genetic admixture on CKD susceptibility, we conducted an admixture mapping screening of CKD traits and risk factors in US Hispanic and Latino individuals from Central America country of origin.

METHODS

We analyzed 1023 participants of HCHS/SOL (Hispanic Community Health Study/Study of Latinos) who reported 4 grandparents originating from the same Central America country. Ancestry admixture findings were validated on 8191 African Americans from WHI (Women's Health Initiative), 3141 American Indians from SHS (Strong Heart Study), and over 1.1 million European individuals from a multistudy meta-analysis.

RESULTS

We identified 3 novel genomic regions for albuminuria (chromosome 14q24.2), CKD (chromosome 6q25.3), and type 2 diabetes (chromosome 3q22.2). The 14q24.2 locus driven by a Native American ancestry had a protective effect on albuminuria and consisted of 2 nearby regions spanning the RGS6 gene. Variants at this locus were validated in American Indians. The 6q25.3 African ancestry-derived locus, encompassing the ARID1B gene, was associated with increased risk for CKD and replicated in African Americans through admixture mapping. The European ancestry type 2 diabetes locus at 3q22.2, encompassing the EPHB1 and KY genes, was validated in European individuals through variant association.

CONCLUSIONS

US Hispanic/Latino populations are culturally and genetically diverse. This study focusing on Central America grandparent country of origin provides new loci discovery and insights into the ancestry-of-origin influences on CKD and risk factors in US Hispanic and Latino individuals.

Common genetic variants associated with urinary phthalate levels in children: A genome-wide study

INTRODUCTION

Phthalates, or dieters of phthalic acid, are a ubiquitous type of plasticizer used in a variety of common consumer and industrial products. They act as endocrine disruptors and are associated with increased risk for several diseases. Once in the body, phthalates are metabolized through partially known mechanisms, involving phase I and phase II enzymes.

OBJECTIVE

In this study we aimed to identify common single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) associated with the metabolism of phthalate compounds in children through genome-wide association studies (GWAS).

METHODS

The study used data from 1,044 children with European ancestry from the Human Early Life Exposome (HELIX) cohort. Ten phthalate metabolites were assessed in a two-void pooled urine collected at the mean age of 8 years. Six ratios between secondary and primary phthalate metabolites were calculated. Genome-wide genotyping was done with the Infinium Global Screening Array (GSA) and imputation with the Haplotype Reference Consortium (HRC) panel. PennCNV was used to estimate copy number variants (CNVs) and CNVRanger to identify consensus regions. GWAS of SNPs and CNVs were conducted using PLINK and SNPassoc, respectively. Subsequently, functional annotation of suggestive SNPs (p-value < 1E-05) was done with the FUMA web-tool.

RESULTS

We identified four genome-wide significant (p-value < 5E-08) loci at chromosome (chr) 3 (FECHP1 for oxo-MiNP_oh-MiNP ratio), chr6 (SLC17A1 for MECPP_MEHHP ratio), chr9 (RAPGEF1 for MBzP), and chr10 (CYP2C9 for MECPP_MEHHP ratio). Moreover, 115 additional loci were found at suggestive significance (p-value < 1E-05). Two CNVs located at chr11 (MRGPRX1 for oh-MiNP and SLC35F2 for MEP) were also identified. Functional annotation pointed to genes involved in phase I and phase II detoxification, molecular transfer across membranes, and renal excretion.

CONCLUSION

Through genome-wide screenings we identified known and novel loci implicated in phthalate metabolism in children. Genes annotated to these loci participate in detoxification, transmembrane transfer, and renal excretion.

Causal effects of plasma metabolites on chronic kidney diseases and renal function: a bidirectional Mendelian randomization study

Background

Despite the potential demonstrated by targeted plasma metabolite modulators in halting the progression of chronic kidney disease (CKD), a lingering uncertainty persists concerning the causal relationship between distinct plasma metabolites and the onset and progression of CKD.

Methods

A genome-wide association study was conducted on 1,091 metabolites and 309 metabolite ratios derived from a cohort of 8,299 unrelated individuals of European descent. Employing a bidirectional two-sample Mendelian randomization (MR) analysis in conjunction with colocalization analysis, we systematically investigated the associations between these metabolites and three phenotypes: CKD, creatinine-estimated glomerular filtration rate (creatinine-eGFR), and urine albumin creatinine ratio (UACR). In the MR analysis, the primary analytical approach employed was inverse variance weighting (IVW), and sensitivity analysis was executed utilizing the MR-Egger method and MR-pleiotropy residual sum and outlier (MR-PRESSO). Heterogeneity was carefully evaluated through Cochrane's Q test. To ensure the robustness of our MR results, the leave-one-out method was implemented, and the strength of causal relationships was subjected to scrutiny via Bonferroni correction.

Results

Our thorough MR analysis involving 1,400 plasma metabolites and three clinical phenotypes yielded a discerning identification of 21 plasma metabolites significantly associated with diverse outcomes. Specifically, in the forward MR analysis, 6 plasma metabolites were determined to be causally associated with CKD, 16 with creatinine-eGFR, and 7 with UACR. Substantiated by robust evidence from colocalization analysis, 6 plasma metabolites shared causal variants with CKD, 16 with creatinine-eGFR, and 7 with UACR. In the reverse analysis, a diminished creatinine-eGFR was linked to elevated levels of nine plasma metabolites. Notably, no discernible associations were observed between other plasma metabolites and CKD, creatinine-eGFR, and UACR. Importantly, our analysis detected no evidence of horizontal pleiotropy.

Conclusion

This study elucidates specific plasma metabolites causally associated with CKD and renal functions, providing potential targets for intervention. These findings contribute to an enriched understanding of the genetic underpinnings of CKD and renal functions, paving the way for precision medicine applications and therapeutic strategies aimed at impeding disease progression.

Multi-omics characterization of type 2 diabetes associated genetic variation

Discerning the mechanisms driving type 2 diabetes (T2D) pathophysiology from genome-wide association studies (GWAS) remains a challenge. To this end, we integrated omics information from 16 multi-tissue and multi-ancestry expression, protein, and metabolite quantitative trait loci (QTL) studies and 46 multi-ancestry GWAS for T2D-related traits with the largest, most ancestrally diverse T2D GWAS to date. Of the 1,289 T2D GWAS index variants, 716 (56%) demonstrated strong evidence of colocalization with a molecular or T2D-related trait, implicating 657 cis-effector genes, 1,691 distal-effector genes, 731 metabolites, and 43 T2D-related traits. We identified 773 of these cis- and distal-effector genes using either expression QTL data from understudied ancestry groups or inclusion of T2D index variants enriched in underrepresented populations, emphasizing the value of increasing population diversity in functional mapping. Linking these variants, genes, metabolites, and traits into a network, we elucidated mechanisms through which T2D-associated variation may impact disease risk. Finally, we showed that drugs targeting effector proteins were enriched in those approved to treat T2D, highlighting the potential of these results to prioritize drug targets for T2D. These results represent a leap in the molecular characterization of T2D-associated genetic variation and will aid in translating genetic findings into novel therapeutic strategies.

Identification of novel therapeutic targets for chronic kidney disease and kidney function by integrating multi-omics proteome with transcriptome

BACKGROUND

Chronic kidney disease (CKD) is a progressive disease for which there is no effective cure. We aimed to identify potential drug targets for CKD and kidney function by integrating plasma proteome and transcriptome.

METHODS

We designed a comprehensive analysis pipeline involving two-sample Mendelian randomization (MR) (for proteins), summary-based MR (SMR) (for mRNA), and colocalization (for coding genes) to identify potential multi-omics biomarkers for CKD and combined the protein-protein interaction, Gene Ontology (GO), and single-cell annotation to explore the potential biological roles. The outcomes included CKD, extensive kidney function phenotypes, and different CKD clinical types (IgA nephropathy, chronic glomerulonephritis, chronic tubulointerstitial nephritis, membranous nephropathy, nephrotic syndrome, and diabetic nephropathy).

RESULTS

Leveraging pQTLs of 3032 proteins from 3 large-scale GWASs and corresponding blood- and tissue-specific eQTLs, we identified 32 proteins associated with CKD, which were validated across diverse CKD datasets, kidney function indicators, and clinical types. Notably, 12 proteins with prior MR support, including fibroblast growth factor 5 (FGF5), isopentenyl-diphosphate delta-isomerase 2 (IDI2), inhibin beta C chain (INHBC), butyrophilin subfamily 3 member A2 (BTN3A2), BTN3A3, uromodulin (UMOD), complement component 4A (C4a), C4b, centrosomal protein of 170 kDa (CEP170), serologically defined colon cancer antigen 8 (SDCCAG8), MHC class I polypeptide-related sequence B (MICB), and liver-expressed antimicrobial peptide 2 (LEAP2), were confirmed. To our knowledge, 20 novel causal proteins have not been previously reported. Five novel proteins, namely, GCKR (OR 1.17, 95% CI 1.10-1.24), IGFBP-5 (OR 0.43, 95% CI 0.29-0.62), sRAGE (OR 1.14, 95% CI 1.07-1.22), GNPTG (OR 0.90, 95% CI 0.86-0.95), and YOD1 (OR 1.39, 95% CI 1.18-1.64,) passed the MR, SMR, and colocalization analysis. The other 15 proteins were also candidate targets (GATM, AIF1L, DQA2, PFKFB2, NFATC1, activin AC, Apo A-IV, MFAP4, DJC10, C2CD2L, TCEA2, HLA-E, PLD3, AIF1, and GMPR1). These proteins interact with each other, and their coding genes were mainly enrichment in immunity-related pathways or presented specificity across tissues, kidney-related tissue cells, and kidney single cells.

CONCLUSIONS

Our integrated analysis of plasma proteome and transcriptome data identifies 32 potential therapeutic targets for CKD, kidney function, and specific CKD clinical types, offering potential targets for the development of novel immunotherapies, combination therapies, or targeted interventions.