A catalog of genetic loci associated with kidney function from analyses of a million individuals

Causal effects of gut microbiota on the risk of chronic kidney disease: a Mendelian randomization study

Background

Previous studies have reported that gut microbiota is associated with an increased risk of chronic kidney disease (CKD) progression. However, whether gut microbiota has a causal effect on the development of CKD has not been revealed. Thus, we aimed to analyze the potential causal effect of gut microbiota on the risk of CKD using mendelian randomization (MR) study.

Materials and Methods

Independent single nucleotide polymorphisms closely associated with 196 gut bacterial taxa (N = 18340) were identified as instrumental variables. Two-sample MR was performed to evaluate the causal effect of gut microbiota on CKD (N = 480698), including inverse-variance-weighted (IVW) method, weighted median method, MR-Egger, mode-based estimation and MR-PRESSO. The robustness of the estimation was tested by a series of sensitivity analyses including Cochran’s Q test, MR-Egger intercept analysis, leave-one-out analysis and funnel plot. Statistical powers were also calculated.

Results

The genetically predicted higher abundance of order Desulfovibrionales was causally associated with an increased risk of CKD (odds ratio = 1.15, 95% confidence interval: 1.05-1.26; p = 0.0026). Besides, we also detected potential causalities between nine other taxa (Eubacterium eligens group, Desulfovibrionaceae, Ruminococcaceae UCG-002, Deltaproteobacteria, Lachnospiraceae UCG-010, Senegalimassilia, Peptostreptococcaceae, Alcaligenaceae and Ruminococcus torques group) and CKD (p < 0.05). No heterogeneity or pleiotropy was detected for significant estimates.

Conclusion

We found that Desulfovibrionales and nine other taxa are associated with CKD, thus confirming that gut microbiota plays an important role in the pathogenesis of CKD. Our work also provides new potential indicators and targets for screening and prevention of CKD.

Phenome-wide Mendelian randomization study evaluating the association of circulating vitamin D with complex diseases

Background

Circulating vitamin D has been associated with multiple clinical diseases in observational studies, but the association was inconsistent due to the presence of confounders. We conducted a bidirectional Mendelian randomization (MR) study to explore the healthy atlas of vitamin D in many clinical traits and evaluate their causal association.

Methods

Based on a large-scale genome-wide association study (GWAS), the single nucleotide polymorphism (SNPs) instruments of circulating 25-hydroxyvitamin D (25OHD) from 443,734 Europeans and the corresponding effects of 10 clinical diseases and 42 clinical traits in the European population were recruited to conduct a bidirectional two-sample Mendelian randomization study. Under the network of Mendelian randomization analysis, inverse-variance weighting (IVW), weighted median, weighted mode, and Mendelian randomization (MR)–Egger regression were performed to explore the causal effects and pleiotropy. Mendelian randomization pleiotropy RESidual Sum and Outlier (MR-PRESSO) was conducted to uncover and exclude pleiotropic SNPs.

Results

The results revealed that genetically decreased vitamin D was inversely related to the estimated BMD (β = −0.029 g/cm2, p = 0.027), TC (β = −0.269 mmol/L, p = 0.006), TG (β = −0.208 mmol/L, p = 0.002), and pulse pressure (β = −0.241 mmHg, p = 0.043), while positively associated with lymphocyte count (β = 0.037%, p = 0.015). The results did not reveal any causal association of vitamin D with clinical diseases. On the contrary, genetically protected CKD was significantly associated with increased vitamin D (β = 0.056, p = 2.361 × 10−26).

Conclusion

The putative causal effects of circulating vitamin D on estimated bone mass, plasma triglyceride, and total cholesterol were uncovered, but not on clinical diseases. Vitamin D may be linked to clinical disease by affecting health-related metabolic markers.

Genetic impact on the association of sleep patterns and chronic kidney disease: A prospective cohort study of 157,175 UK Biobank participants

OBJECTIVES

The association between sleep pattern and chronic kidney disease (CKD) incidence, and whether the association is dependent on the genetic backgrounds has not been addressed. We sought to investigate the association of multidimensional sleep pattern with CKD in consideration of genetic polymorphisms.

METHODS

In this prospective cohort study of 157,175 participants from the UK Biobank, sleep patterns were derived by multiple correspondence analysis (MCA) and k-means clustering of individual sleep traits (sleep duration, insomnia, chronotype, daytime sleepiness, snoring, and night shift status). Cox proportional hazard regression was used to estimate the association between sleep patterns and CKD incidence. Gene-environment-wide interaction study (GEWIS) was performed to detect whether gene polymorphisms were modifiers on this association.

RESULTS

Compared with "healthy sleep" pattern, increased CKD incidence was observed in the clusters with "long sleep duration" (hazard ratios (HR) 1.42, 95% confidence intervals (CI), 1.18-1.72) and "night shift" (HR 1.23, 95% CI, 1.05-1.45) patterns, but not with the "short sleep duration" pattern. By GEWIS, we identified 167 SNPs as suggestive effect modifiers that interacted with unhealthy sleep patterns and affected the risk of CKD.

CONCLUSIONS

Unhealthy sleep patterns, with features of long sleep duration and night shift, may increase the risk of CKD. The study highlights the interaction of sleep and individual genetic risk to affect health outcomes.

Imputation-powered whole-exome analysis identifies genes associated with kidney function and disease in the UK Biobank

Genome-wide association studies have discovered hundreds of associations between common genotypes and kidney function but cannot comprehensively investigate rare coding variants. Here, we apply a genotype imputation approach to whole exome sequencing data from the UK Biobank to increase sample size from 166,891 to 408,511. We detect 158 rare variants and 105 genes significantly associated with one or more of five kidney function traits, including genes not previously linked to kidney disease in humans. The imputation-powered findings derive support from clinical record-based kidney disease information, such as for a previously unreported splice allele in PKD2, and from functional studies of a previously unreported frameshift allele in CLDN10. This cost-efficient approach boosts statistical power to detect and characterize both known and novel disease susceptibility variants and genes, can be generalized to larger future studies, and generates a comprehensive resource ( https://ckdgen-ukbb.gm.eurac.edu/ ) to direct experimental and clinical studies of kidney disease.

Improvement of Estrogen Deficiency Symptoms by the Intake of Long-Term Fermented Soybeans (Doenjang) Rich in Bacillus Species through Modulating Gut Microbiota in Estrogen-Deficient Rats

Traditionally made doenjang (TMD) produced by the long-term fermentation of soybeans with salt may improve symptoms of estrogen deficiency. We aimed to evaluate the effects of four TMD types, containing low and high amounts of Bacillus species and biogenic amines (HBHA, HBLA, LBHA, and LBLA), on energy, glucose, and lipid metabolism, by altering the gut microbiota in estrogen-deficient ovariectomized (OVX) rats. Their mechanisms were also examined. The OVX rats were divided into the control, cooked soybean (CSB), HBHA, LBHA, HBLA, and LBLA groups. Sham-operated rats were the normal control group. Serum 17β-estradiol concentrations were similar among all OVX groups. Tail skin temperatures, which are indicative of hot flashes, were higher in the control than the HBHA and HBLA groups and were similar to the normal control group. Weight gain and visceral fat mass were lower in the TMD and CSB intake groups but not as low as in the normal control group. Lean body mass showed a trend opposite to that of visceral fat in the respective groups. The hepatic triglyceride content decreased with the TMD intake compared to the control and CSB groups. mRNA expressions of the peroxisome proliferator-activated receptor-γ (PPAR-γ) and carnitine palmitoyltransferase-1 in the TMD and CSB groups were as high as in the normal control group, and the PPAR-γ mRNA expression was more elevated in the HBLA group than in the normal control group. The morphology of the intestines improved in the TMD groups compared to the control, and the HBHA and HBLA groups showed an enhanced improvement compared to the CSB group. The HBHA, HBLA, and LBHA groups increased the α-diversity of the cecal microbiota compared to the control. Akkermenia and Lactobacillus were higher in the HBLA and LBLA groups compared to the control. The expression of the estrogen, forkhead box proteins of the class-O subgroup, and insulin-signaling pathways were lower in the control group, and HBHA and HBLA prevented their decrement. In conclusion, long-term treatment with TMD containing high amounts of Bacillus potentially improves estrogen deficiency symptoms more than unfermented soybeans.

Effects of protein-coding variants on blood metabolite measurements and clinical biomarkers in the UK Biobank

Genome-wide association studies (GWASs) have established the contribution of common and low-frequency variants to metabolic blood measurements in the UK Biobank (UKB). To complement existing GWAS findings, we assessed the contribution of rare protein-coding variants in relation to 355 metabolic blood measurements-including 325 predominantly lipid-related nuclear magnetic resonance (NMR)-derived blood metabolite measurements (Nightingale Health Plc) and 30 clinical blood biomarkers-using 412,393 exome sequences from four genetically diverse ancestries in the UKB. Gene-level collapsing analyses were conducted to evaluate a diverse range of rare-variant architectures for the metabolic blood measurements. Altogether, we identified significant associations (p < 1 × 10^-8) for 205 distinct genes that involved 1,968 significant relationships for the Nightingale blood metabolite measurements and 331 for the clinical blood biomarkers. These include associations for rare non-synonymous variants in PLIN1 and CREB3L3 with lipid metabolite measurements and SYT7 with creatinine, among others, which may not only provide insights into novel biology but also deepen our understanding of established disease mechanisms. Of the study-wide significant clinical biomarker associations, 40% were not previously detected on analyzing coding variants in a GWAS in the same cohort, reinforcing the importance of studying rare variation to fully understand the genetic architecture of metabolic blood measurements.

Whole-genome sequencing reveals a complex African population demographic history and signatures of local adaptation

We conduct high coverage (>30×) whole-genome sequencing of 180 individuals from 12 indigenous African populations. We identify millions of unreported variants, many predicted to be functionally important. We observe that the ancestors of southern African San and central African rainforest hunter-gatherers (RHG) diverged from other populations >200 kya and maintained a large effective population size. We observe evidence for ancient population structure in Africa and for multiple introgression events from "ghost" populations with highly diverged genetic lineages. Although currently geographically isolated, we observe evidence for gene flow between eastern and southern Khoesan-speaking hunter-gatherer populations lasting until ∼12 kya. We identify signatures of local adaptation for traits related to skin color, immune response, height, and metabolic processes. We identify a positively selected variant in the lightly pigmented San that influences pigmentation in vitro by regulating the enhancer activity and gene expression of PDPK1.

High-throughput genetic clustering of type 2 diabetes loci reveals heterogeneous mechanistic pathways of metabolic disease

AIMS/HYPOTHESIS

Type 2 diabetes is highly polygenic and influenced by multiple biological pathways. Rapid expansion in the number of type 2 diabetes loci can be leveraged to identify such pathways.

METHODS

We developed a high-throughput pipeline to enable clustering of type 2 diabetes loci based on variant-trait associations. Our pipeline extracted summary statistics from genome-wide association studies (GWAS) for type 2 diabetes and related traits to generate a matrix of 323 variants × 64 trait associations and applied Bayesian non-negative matrix factorisation (bNMF) to identify genetic components of type 2 diabetes. Epigenomic enrichment analysis was performed in 28 cell types and single pancreatic cells. We generated cluster-specific polygenic scores and performed regression analysis in an independent cohort (N=25,419) to assess for clinical relevance.

RESULTS

We identified ten clusters of genetic loci, recapturing the five from our prior analysis as well as novel clusters related to beta cell dysfunction, pronounced insulin secretion, and levels of alkaline phosphatase, lipoprotein A and sex hormone-binding globulin. Four clusters related to mechanisms of insulin deficiency, five to insulin resistance and one had an unclear mechanism. The clusters displayed tissue-specific epigenomic enrichment, notably with the two beta cell clusters differentially enriched in functional and stressed pancreatic beta cell states. Additionally, cluster-specific polygenic scores were differentially associated with patient clinical characteristics and outcomes. The pipeline was applied to coronary artery disease and chronic kidney disease, identifying multiple overlapping clusters with type 2 diabetes.

CONCLUSIONS/INTERPRETATION

Our approach stratifies type 2 diabetes loci into physiologically interpretable genetic clusters associated with distinct tissues and clinical outcomes. The pipeline allows for efficient updating as additional GWAS become available and can be readily applied to other conditions, facilitating clinical translation of GWAS findings. Software to perform this clustering pipeline is freely available.

Host factors predisposing to kidney disease in people with HIV

PURPOSE OF REVIEW

To highlight advances in understanding of host factors, in particular host genetics, in the development of chronic kidney disease (CKD) in people with HIV.

RECENT FINDINGS

In Black populations, the G1 and G2 variants of the apolipoprotein L1 (APOL1) gene predispose to HIV-associated nephropathy (HIVAN). The risk of HIVAN is mostly confined to individuals with two APOL1 variants (kidney-risk genotypes). APOL1 kidney-risk genotypes are present in approximately 80% of patients with HIVAN and account for nearly half the burden of end-stage CKD in people of African ancestry with HIV. Progress has been made in elucidating the mechanisms of kidney injury in APOL1 nephropathy, and several targeted molecular therapies are being investigated in clinical trials. Genome- and epigenome-wide association studies are identifying additional genes and pathways that may be involved in the pathogenesis of CKD in people with HIV.

SUMMARY

Genetic variants of APOL1 are strongly associated with severe CKD and contribute to the high rates of CKD in Black populations with HIV. Most individuals with APOL1 kidney-risk genotypes, however, do not develop kidney disease and further studies are required to understand the role of additional genetic and environmental factors that may affect CKD risk in this population.

Association between psoriatic disease and lifestyle factors and comorbidities: cross-sectional analysis and Mendelian randomization

OBJECTIVES

To examine associations between PsA and psoriasis vs lifestyle factors and comorbidities by triangulating observational and genetic evidence.

METHODS

We analysed cross-sectional data from the UK Biobank (1836 PsA, 8995 psoriasis, 36 000 controls) to describe the association between psoriatic disease and lifestyle factors (including BMI and smoking) and 15 comorbidities [including diabetes and coronary artery disease (CAD)] using logistic models adjusted for age, sex and lifestyle factors. We applied bidirectional Mendelian randomization (MR) to genome-wide association data (3609 PsA and 7804 psoriasis cases, up to 1.2 million individuals for lifestyle factors and 757 601 for comorbidities) to examine causal direction, using the inverse-variance weighted method.

RESULTS

BMI was cross-sectionally associated with risk of PsA (OR 1.31 per 5 kg/m2 increase; 95% CI 1.26, 1.37) and psoriasis (OR 1.23; 1.20, 1.26), with consistent MR estimates (PsA OR 1.38; 1.14, 1.67; psoriasis OR 1.36; 1.18, 1.58). In both designs, smoking was more strongly associated with psoriasis than PsA. PsA and psoriasis were cross-sectionally associated with diabetes (OR 1.35 and 1.39, respectively) and CAD (OR 1.56 and 1.38, respective). Genetically predicted glycated haemoglobin (surrogate for diabetes) increased PsA risk (OR 1.18 per 6.7 mmol/mol increase; 1.02, 1.36) but not psoriasis. Genetic liability to PsA (OR 1.05; 1.003, 1.09) and psoriasis (OR 1.03; 1.001, 1.06) were associated with increased risk of CAD.

CONCLUSION

Observational and genetic evidence converge to suggest that BMI and glycaemic control are associated with increased psoriatic disease risk, while psoriatic disease is associated with increased CAD risk. Further research is needed to understand the mechanism of these associations.

Allometric body shape indices, type 2 diabetes and kidney function: A two-sample Mendelian randomization study

AIM

To examine the association between body mass index (BMI)-independent allometric body shape indices and kidney function.

MATERIALS AND METHODS

We performed a two-sample Mendelian randomization (MR) analysis, using summary statistics from UK Biobank, CKDGen and DIAGRAM. BMI-independent allometric body shape indices were: A Body Shape Index (ABSI), Waist-Hip Index (WHI) and Hip Index (HI). Kidney function outcomes were: urinary albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate and blood urea nitrogen. Furthermore, we investigated type 2 diabetes (T2D) as a potential mediator on the pathway to albuminuria. The main analysis was inverse variance-weighted random-effects MR in participants of European ancestry. We also performed several sensitivity MR analyses.

RESULTS

A 1-standard deviation (SD) increase in genetically predicted ABSI and WHI levels was associated with higher UACR (β = 0.039 [95% confidence interval: 0.016, 0.063] log [UACR], P = 0.001 for ABSI, and β = 0.028 [0.012, 0.044] log [UACR], P = 6 x 10^-4 for WHI) in women, but not in men. Meanwhile, a 1-SD increase in genetically predicted HI was associated with lower UACR in women (β = -0.021 [-0.041, 0.000] log [UACR], P = 0.05) and in men (β = -0.026 [-0.058, 0.005] log [UACR], P = 0.10). Corresponding estimates in individuals with diabetes were substantially augmented. Risk of T2D increased for genetically high ABSI and WHI in women (P < 6 x 10^-19 ) only, but decreased for genetically high HI in both sexes (P < 9 x 10^-3 ). No other associations were observed.

CONCLUSIONS

Genetically high HI was associated with decreased risk of albuminuria, mediated through decreased T2D risk in both sexes. Opposite associations applied to genetically high ABSI and WHI in women only.

Harnessing Genomic Analysis to Explore the Role of Telomeres in the Pathogenesis and Progression of Diabetic Kidney Disease

The prevalence of diabetes is increasing globally, and this trend is predicted to continue for future decades. Research is needed to uncover new ways to manage diabetes and its co-morbidities. A significant secondary complication of diabetes is kidney disease, which can ultimately result in the need for renal replacement therapy, via dialysis or transplantation. Diabetic kidney disease presents a substantial burden to patients, their families and global healthcare services. This review highlights studies that have harnessed genomic, epigenomic and functional prediction tools to uncover novel genes and pathways associated with DKD that are useful for the identification of therapeutic targets or novel biomarkers for risk stratification. Telomere length regulation is a specific pathway gaining attention recently because of its association with DKD. Researchers are employing both observational and genetics-based studies to identify telomere-related genes associated with kidney function decline in diabetes. Studies have also uncovered novel functions for telomere-related genes beyond the immediate regulation of telomere length, such as transcriptional regulation and inflammation. This review summarises studies that have revealed the potential to harness therapeutics that modulate telomere length, or the associated epigenetic modifications, for the treatment of DKD, to potentially slow renal function decline and reduce the global burden of this disease.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Genome-wide association study of the risk of chronic kidney disease and kidney-related traits in the Japanese population: J-Kidney-Biobank

Chronic kidney disease (CKD) is a syndrome characterized by a gradual loss of kidney function with decreased estimated glomerular filtration rate (eGFR), which may be accompanied by an increase in the urine albumin-to-creatinine ratio (UACR). Although trans-ethnic genome-wide association studies (GWASs) have been conducted for kidney-related traits, there have been few analyses in the Japanese population, especially for the UACR trait. In this study, we conducted a GWAS to identify loci related to multiple kidney-related traits in Japanese individuals. First, to detect loci associated with CKD, eGFR, and UACR, we performed separate GWASs with the following two datasets: 475 cases of CKD diagnosed at seven university hospitals and 3471 healthy subjects (dataset 1) and 3664 cases of CKD-suspected individuals with eGFR <60 ml/min/1.73 m² or urinary protein ≥ 1+ and 5952 healthy subjects (dataset 2). Second, we performed a meta-analysis between these two datasets and detected the following associated loci: 10 loci for CKD, 9 loci for eGFR, and 22 loci for UACR. Among the loci detected, 22 have never been reported previously. Half of the significant loci for CKD were shared with those for eGFR, whereas most of the loci associated with UACR were different from those associated with CKD or eGFR. The GWAS of the Japanese population identified novel genetic components that were not previously detected. The results also suggest that the group primarily characterized by increased UACR possessed genetically different features from the group characterized by decreased eGFR.

Impairment of kidney function and kidney cancer: A bidirectional Mendelian randomization study

BACKGROUND

Many observational epidemiology studies discovered that kidney cancer and impaired kidney function have a bidirectional relationship. However, it remains unclear whether these two kinds of traits are causally linked. In this study, we aimed to investigate the bidirectional causal relation between kidney cancer and kidney function biomarkers (creatinine-based estimated glomerular filtration rate (eGFRcrea), cystatin C-based estimated glomerular filtration rate (eGFRcys), blood urea nitrogen (BUN), serum urate, and urinary albumin-to-creatinine ratio (UACR)).

METHODS

For both directions, single-nucleotide polymorphisms (SNPs), as genetic instruments, for the five kidney function traits were selected from up to 1,004,040 individuals, and SNPs for kidney cancer were from 408,786 participants(1338 cases). In the main analysis, we applied two state-of-the-art MR methods, namely, contamination mixture and Robust Adjusted Profile Score to downweight the effect of weak instrument bias, pleiotropy, and extreme outliers. We additionally conducted traditional MR analyses as sensitivity analyses. Summary-level data of European ancestry were extracted from UK Biobank, Chronic Kidney Disease Genetics Consortium, and Kaiser Permanente.

RESULTS

Based on 99 SNPs, we found that the eGFRcrea had a significant negative causal effect on the risk of kidney cancer (OR = 0.007, 95% CI:2.6 × 10-4 -0.569, p = 0.041). After adjusting for body composition or diabetes, urate had a significant negative causal effect on kidney cancer (OR <1, p < 0.05). For UACR, it showed a strong causal effect on kidney cancer, after adjusting for body composition (OR = 14.503, 95% CI: 2.546-96.001, p = 0.032). Due to lacking significant signals and effect power for the reverse MR, further investigations are warranted.

CONCLUSIONS

Our study suggested a potential causal effect of damaged kidney function on kidney cancer. EGFRcrea and UACR might be causally associated with kidney cancer, especially when patients were comorbid with obesity or diabetes. We called for larger sample-size studies to further unravel the underlying causal relationship and the exact mechanism.

Impact of solute carrier transporter gene polymorphisms on serum creatinine concentrations in healthy volunteers

In this study, we investigated the impact of single nucleotide polymorphisms in solute carrier (SLC) transporters, that is, SLC22A7 c.1586 + 206A > G, SLC22A2 c.808G > T, SLC22A3 c.1233G > A, SLC47A1 c.922-158G > A, and SLC47A2 c.-130G > A, on serum creatinine (SCr) concentrations. This cross-sectional study included residents who participated as volunteers in a health promotion study. Lifestyle data, blood chemical analysis data, and SLC gene polymorphism information were collected from each participant. Univariate analyses were carried out to determine differences between groups and correlations in SCr. Stepwise multiple regression analysis was performed to confirm the independence of factors that were significantly different in the univariate analyses. In multiple regression analyses, muscle mass, serum cystatin C concentrations, body fat percentage, serum albumin concentrations, and SLC47A2 c.-130G/G had the highest contribution to SCr concentrations, in that order (standardized regression coefficients = .505, .332, -.234, .123, and .084, respectively). The final model explained 72.2% of the variability in SCr concentrations. The SLC47A2 c.-130G > A polymorphism may affect creatinine dynamics in the proximal tubules. Further studies are needed to determine the effects of SLC transporter gene polymorphisms on SCr concentrations in patients with various diseases in real-world clinical settings.

Cannabis Use and CKD: Epidemiological Associations and Mendelian Randomization

Rationale & Objective

The association between cannabis use and chronic kidney disease (CKD) is controversial. We aimed to assess association of CKD with cannabis use in a large cohort study and then assess causality using Mendelian randomization with a genome-wide association study (GWAS).

Study Design

Retrospective cohort study and genome-wide association study.

Setting & Participants

The retrospective study was conducted on the All of Us cohort (N=223,354). Genetic instruments for cannabis use disorder were identified from 3 GWAS: the Psychiatric Genomics Consortium Substance Use Disorders, iPSYCH, and deCODE (N=384,032). Association between genetic instruments and CKD was investigated in the CKDGen GWAS (N > 1.2 million).

Exposure

Cannabis consumption.

Outcomes

CKD outcomes included: cystatin-C and creatinine-based kidney function, proteinuria, and blood urea nitrogen.

Analytical Approach

We conducted association analyses to test for frequency of cannabis use and CKD. To evaluate causality, we performed a 2-sample Mendelian randomization.

Results

In the retrospective study, compared to former users, less than monthly (OR, 1.01; 95% CI, 0.87-1.18; P = 0.87) and monthly cannabis users (OR, 1.15; 95% CI, 0.86-1.52; P = 0.33) did not have higher CKD odds. Conversely, weekly (OR, 1.28; 95% CI, 1.01-1.60; P = 0.04) and daily use (OR, 1.25; 95% CI, 1.04-1.50; P = 0.02) was significantly associated with CKD, adjusted for multiple confounders. In Mendelian randomization, genetic liability to cannabis use disorder was not associated with increased odds for CKD (OR, 1.00; 95% CI, 0.99-1.01; P = 0.96). These results were robust across different Mendelian randomization techniques and multiple kidney traits.

Limitations

Likely underreporting of cannabis use. In Mendelian randomization, genetic instruments were identified in the GWAS that included individuals primarily of European ancestry.

Conclusions

Despite the epidemiological association between cannabis use and CKD, there was no evidence of a causal effect, indicating confounding in observational studies.

Genetics of Kidney Disease: The Unexpected Role of Rare Disorders

Hundreds of different genetic causes of chronic kidney disease are now recognized, and while individually rare, taken together they are significant contributors to both adult and pediatric diseases. Traditional genetics approaches relied heavily on the identification of large families with multiple affected members and have been fundamental to the identification of genetic kidney diseases. With the increased utilization of massively parallel sequencing and improvements to genotype imputation, we can analyze rare variants in large cohorts of unrelated individuals, leading to personalized care for patients and significant research advancements. This review evaluates the contribution of rare disorders to patient care and the study of genetic kidney diseases and highlights key advancements that utilize new techniques to improve our ability to identify new gene-disease associations.

Short-term air pollution exposure associated with death from kidney diseases: a nationwide time-stratified case-crossover study in China from 2015 to 2019

BACKGROUND

Long-term exposure to air pollution has been associated with the onset and progression of kidney diseases, but the association between short-term exposure to air pollution and mortality of kidney diseases has not yet been reported.

METHODS

A nationally representative sample of 101,919 deaths from kidney diseases was collected from the Chinese Center for Disease Control and Prevention from 2015 to 2019. A time-stratified case-crossover study was applied to determine the associations. Satellite-based estimates of air pollution were assigned to each case and control day using a bilinear interpolation approach and geo-coded residential addresses. Conditional logistic regression models were constructed to estimate the associations adjusting for nonlinear splines of temperature and relative humidity.

RESULTS

Each 10 µg/m3 increment in lag 0-1 mean concentrations of air pollutants was associated with a percent increase in death from kidney disease: 1.33% (95% confidence interval [CI]: 0.57% to 2.1%) for PM1, 0.49% (95% CI: 0.10% to 0.88%) for PM2.5, 0.32% (95% CI: 0.08% to 0.57%) for PM10, 1.26% (95% CI: 0.29% to 2.24%) for NO2, and 2.9% (95% CI: 1.68% to 4.15%) for SO2.  CONCLUSIONS: Our study suggests that short-term exposure to ambient PM1, PM2.5, PM10, NO2, and SO2 might be important environmental risk factors for death due to kidney diseases in China.

Bayesian mixed model analysis uncovered 21 risk loci for chronic kidney disease in boxer dogs

Chronic kidney disease (CKD) affects 10% of the human population, with only a small fraction genetically defined. CKD is also common in dogs and has been diagnosed in nearly all breeds, but its genetic basis remains unclear. Here, we performed a Bayesian mixed model genome-wide association analysis for canine CKD in a boxer population of 117 canine cases and 137 controls, and identified 21 genetic regions associated with the disease. At the top markers from each CKD region, the cases carried an average of 20.2 risk alleles, significantly higher than controls (15.6 risk alleles). An ANOVA test showed that the 21 CKD regions together explained 57% of CKD phenotypic variation in the population. Based on whole genome sequencing data of 20 boxers, we identified 5,206 variants in LD with the top 50 BayesR markers. Following comparative analysis with human regulatory data, 17 putative regulatory variants were identified and tested with electrophoretic mobility shift assays. In total four variants, three intronic variants from the MAGI2 and GALNT18 genes, and one variant in an intergenic region on chr28, showed alternative binding ability for the risk and protective alleles in kidney cell lines. Many genes from the 21 CKD regions, RELN, MAGI2, FGFR2 and others, have been implicated in human kidney development or disease. The results from this study provide new information that may enlighten the etiology of CKD in both dogs and humans.

Renal function and neurodegenerative diseases : a two-sample Mendelian randomization study

BACKGROUND

Observational studies showed renal function had associations with Alzheimer's disease (AD), Parkinson's disease (PD), Lewy body dementia (LBD) and multiple sclerosis (MS). However, it is unknown whether these associations are causal.

METHODS

We use a two-sample Mendelian randomization (MR) analysis to investigate causal relationships between renal function and 6 neurodegenerative diseases (NDDs): AD (including familial AD), PD, LBD, frontotemporal dementia (FTD), amyotrophic lateral sclerosis (ALS) and MS. Blood urea nitrogen (BUN), chronic kidney disease (CKD) and estimated glomerular filtration rate (eGFR) were used to measure renal function. The inverse-variance weighted (IVW) was the predominant estimation method. The results were further validated using sensitivity analysis (i.e. MR Egger regression, Cochran Q statistic of IVW, and leave-one-out method).

RESULTS

There was no indication of any causative relationship of BUN, CKD, or eGFR with AD, familial AD, PD, LBD, FTD and ALS (all P values >0.05). The IVW analysis demonstrated a causal relationship between eGFR and MS [odds ratio (OR), 4.89; 95% confidence interval (CI), 1.43 to 16.71; P = 0.01] that was not verified in the MR-Egger and weighted median (all P values >0.05). However, no causal association of MS with BUN (OR, 0.91; 95% CI, 0.40-2.07; P = 0.82) and CKD (OR,1.04; 95% CI, 0.88-1.23; P = 0.66) was found. There was no single SNP that affects the overall trend.

CONCLUSIONS

Our study showed that reduced eGFR was related to MS. The value of this study is that it provides a direction for further research on the relationship between reduced eGFR and MS.

Uromodulin and its association with urinary metabolites: the German Chronic Kidney Disease Study

BACKGROUND

The progression of chronic kidney disease (CKD), a global public health burden, is accompanied by a declining number of functional nephrons. Estimation of remaining nephron mass may improve assessment of CKD progression. Uromodulin has been suggested as a marker of tubular mass. We aimed to identify metabolites associated with uromodulin concentrations in urine and serum to characterize pathophysiologic alterations of metabolic pathways to generate new hypotheses regarding CKD pathophysiology.

METHODS

We measured urinary and serum uromodulin levels (uUMOD, sUMOD) and 607 urinary metabolites and performed cross-sectional analyses within the German Chronic Kidney Disease study (N = 4628), a prospective observational study. Urinary metabolites significantly associated with uUMOD and sUMOD were used to build weighted metabolite scores for urine (uMS) and serum uromodulin (sMS) and evaluated for time to adverse kidney events over 6.5 years.

RESULTS

Metabolites cross-sectionally associated with uromodulin included amino acids of the tryptophan metabolism, lipids and nucleotides. Higher levels of the sMS [hazard ratio (HR) = 0.73 (95% confidence interval 0.64; 0.82), P = 7.45e-07] and sUMOD [HR = 0.74 (95% confidence interval 0.63; 0.87), P = 2.32e-04] were associated with a lower risk of adverse kidney events over time, whereas uUMOD and uMS showed the same direction of association but were not significant.

CONCLUSIONS

We identified urinary metabolites associated with urinary and serum uromodulin. The sUMOD and the sMS were associated with lower risk of adverse kidney events among CKD patients. Higher levels of sUMOD and sMS may reflect a higher number of functional nephrons and therefore a reduced risk of adverse kidney outcomes.

Biomedical consequences of elevated cholesterol-containing lipoproteins and apolipoproteins on cardiovascular and non-cardiovascular outcomes

BACKGROUND

Higher concentrations of cholesterol-containing low-density lipoprotein (LDL-C) increase the risk of cardiovascular disease (CVD). The association of LDL-C with non-CVD traits remains unclear, as are the possible independent contributions of other cholesterol-containing lipoproteins and apolipoproteins.

METHODS

Nuclear magnetic resonance spectroscopy was used to measure the cholesterol content of high density (HDL-C), very low-density (VLDL-C), intermediate-density (IDL-C), as well as low-density lipoprotein fractions, the apolipoproteins Apo-A1 and Apo-B, as well as total triglycerides (TG), remnant-cholesterol (Rem-Chol) and total cholesterol (TC). The causal effects of these exposures were assessed against 33 outcomes using univariable and multivariable Mendelian randomization (MR).

RESULTS

The majority of cholesterol containing lipoproteins and apolipoproteins affect coronary heart disease (CHD), carotid intima-media thickness, carotid plaque, C-reactive protein (CRP) and blood pressure. Multivariable MR indicated that many of these effects act independently of HDL-C, LDL-C and TG, the most frequently measured lipid fractions. Higher concentrations of TG, VLDL-C, Rem-Chol and Apo-B increased heart failure (HF) risk; often independently of LDL-C, HDL-C or TG. Finally, a subset of these exposures associated with non-CVD traits such as Alzheimer's disease (AD: HDL-C, LDL-C, IDL-C, Apo-B), type 2 diabetes (T2DM: VLDL-C, IDL-C, LDL-C), and inflammatory bowel disease (IBD: LDL-C, IDL-C).

CONCLUSIONS

The cholesterol content of a wide range of lipoprotein and apolipoproteins associate with measures of atherosclerosis, blood pressure, CRP, and CHD, with a subset affecting HF, T2DM, AD and IBD risk. Many of the observed effects appear to act independently of LDL-C, HDL-C, and TG, supporting the targeting of lipid fractions beyond LDL-C for disease prevention.

Association of omega 3 polyunsaturated fatty acids with incident chronic kidney disease: pooled analysis of 19 cohorts

OBJECTIVE

To assess the prospective associations of circulating levels of omega 3 polyunsaturated fatty acid (n-3 PUFA) biomarkers (including plant derived α linolenic acid and seafood derived eicosapentaenoic acid, docosapentaenoic acid, and docosahexaenoic acid) with incident chronic kidney disease (CKD).

DESIGN

Pooled analysis.

DATA SOURCES

A consortium of 19 studies from 12 countries identified up to May 2020.

STUDY SELECTION

Prospective studies with measured n-3 PUFA biomarker data and incident CKD based on estimated glomerular filtration rate.

DATA EXTRACTION AND SYNTHESIS

Each participating cohort conducted de novo analysis with prespecified and consistent exposures, outcomes, covariates, and models. The results were pooled across cohorts using inverse variance weighted meta-analysis.

MAIN OUTCOME MEASURES

Primary outcome of incident CKD was defined as new onset estimated glomerular filtration rate <60 mL/min/1.73 m2. In a sensitivity analysis, incident CKD was defined as new onset estimated glomerular filtration rate <60 mL/min/1.73 m2 and <75% of baseline rate.

RESULTS

25 570 participants were included in the primary outcome analysis and 4944 (19.3%) developed incident CKD during follow-up (weighted median 11.3 years). In multivariable adjusted models, higher levels of total seafood n-3 PUFAs were associated with a lower incident CKD risk (relative risk per interquintile range 0.92, 95% confidence interval 0.86 to 0.98; P=0.009, I2=9.9%). In categorical analyses, participants with total seafood n-3 PUFA level in the highest fifth had 13% lower risk of incident CKD compared with those in the lowest fifth (0.87, 0.80 to 0.96; P=0.005, I2=0.0%). Plant derived α linolenic acid levels were not associated with incident CKD (1.00, 0.94 to 1.06; P=0.94, I2=5.8%). Similar results were obtained in the sensitivity analysis. The association appeared consistent across subgroups by age (≥60 v <60 years), estimated glomerular filtration rate (60-89 v ≥90 mL/min/1.73 m2), hypertension, diabetes, and coronary heart disease at baseline.

CONCLUSIONS

Higher seafood derived n-3 PUFA levels were associated with lower risk of incident CKD, although this association was not found for plant derived n-3 PUFAs. These results support a favourable role for seafood derived n-3 PUFAs in preventing CKD.

Polygenic risk scores and kidney traits in the Hispanic/Latino population: The Hispanic Community Health Study/Study of Latinos

Estimated glomerular filtration rate (eGFR) is used to evaluate kidney function and determine the presence of chronic kidney disease (CKD), a highly prevalent disease in the US^{1 , 2 , 3} that varies among subgroups of Hispanic/Latino individuals.^{4 , 5} The polygenic risk score (PRS) is a popular method that uses large genome-wide association studies (GWASs) to provide a strong estimate of disease risk.⁷ However, due to the limited availability of summary statistics from GWAS meta-analyses based on Hispanic/Latino populations, PRSs can only be computed using different ancestry GWASs. The performance of eGFR PRSs derived from other GWAS reference populations for Hispanic/Latino population has not been examined. We compared PRS constructions for eGFR prediction in Hispanic/Latino individuals using GWAS-significant variants, clumping and thresholding (C&T),⁸ and PRS-CS,²² as well as a combination of PRSs calculated with different reference GWAS meta-analyses from European and multi-ethnic studies in Hispanic/Latino individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). All eGFR PRSs were highly associated with eGFR (p < 1E-20). Additionally, eGFR PRSs were significantly associated with lower risk of prevalent CKD at visit 1 or 2 and incident CKD at visit 2, with the combined PRSs having the best performance. These PRS findings were replicated in an additional dataset of Hispanic/Latino individuals using data from the Women's Health Initiative SNP Health Association Resource (WHI-SHARe).¹⁷.

Causal Effects of Specific Gut Microbiota on Chronic Kidney Diseases and Renal Function-A Two-Sample Mendelian Randomization Study

BACKGROUND

Targeting the gut microbiota may become a new therapeutic to prevent and delay the progression of chronic kidney disease (CKD). Nonetheless, the causal relationship between specific intestinal flora and CKD is still unclear.

MATERIALS AND METHOD

To identify genetically predicted microbiota, we used summary data from genome-wide association studies on gut microbiota in 18340 participants from 24 cohorts. Furthermore, we genetically predicted the causal relationship between 211 gut microbiotas and six phenotypes (outcomes) (CKD, estimated glomerular filtration rate (eGFR), urine albumin to creatinine ratio (UACR), dialysis, rapid progress to CKD, and rapid decline of eGFR). Four Mendelian randomization (MR) methods, including inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode were used to investigate the casual relationship between gut microbiotas and various outcomes. The result of IVW was deemed as the primary result. Then, Cochrane's Q test, MR-Egger, and MR-PRESSO Global test were used to detect heterogeneity and pleiotropy. The leave-one method was used for testing the stability of MR results and Bonferroni-corrected was used to test the strength of the causal relationship between exposure and outcome.

RESULTS

Through the MR analysis of 211 microbiotas and six clinical phenotypes, a total of 36 intestinal microflora were found to be associated with various outcomes. Among them, Class Bacteroidia (=-0.005, 95% CI: -0.001 to -0.008, p = 0.002) has a strong causality with lower eGFR after the Bonferroni-corrected test, whereas phylum Actinobacteria (OR = 1.0009, 95%CI: 1.0003-1.0015, p = 0.0024) has a strong causal relationship with dialysis. The Cochrane's Q test reveals that there is no significant heterogeneity between various single nucleotide polymorphisms. In addition, no significant level of pleiotropy was found according to MR-Egger and MR-PRESSO Global tests.

CONCLUSIONS

Through the two-sample MR analysis, we identified the specific intestinal flora that has a causal relationship with the incidence and progression of CKD at the level of gene prediction, which may provide helpful biomarkers for early disease diagnosis and potential therapeutic targets for CKD.

Identification of Novel Genetic Risk Factors for Focal Segmental Glomerulosclerosis in Children: Results From the Chronic Kidney Disease in Children (CKiD) Cohort

RATIONALE & OBJECTIVE

Focal segmental glomerulosclerosis (FSGS) is a major cause of pediatric nephrotic syndrome, and African Americans exhibit an increased risk for developing FSGS compared with other populations. Predisposing genetic factors have previously been described in adults. Here we performed genomic screening of primary FSGS in a pediatric African American population.

STUDY DESIGN

Prospective cohort with case-control genetic association study design.

SETTING & PARTICIPANTS

140 African American children with chronic kidney disease from the Chronic Kidney Disease in Children (CKiD) cohort, including 32 cases with FSGS.

PREDICTORS

Over 680,000 common single-nucleotide polymorphisms (SNPs) were tested for association. We also ran a pathway enrichment analysis and a human leucocyte antigen (HLA)-focused association study.

OUTCOME

Primary biopsy-proven pediatric FSGS.

ANALYTICAL APPROACH

Multivariate logistic regression models.

RESULTS

The genome-wide association study revealed 169 SNPs from 14 independent loci significantly associated with FSGS (false discovery rate [FDR]<5%). We observed notable signals for genetic variants within the APOL1 (P=8.6×10^-7; OR, 25.8 [95% CI, 7.1-94.0]), ALMS1 (P=1.3×10^-7; 13.0% in FSGS cases vs 0% in controls), and FGFR4 (P=4.3×10^-6; OR, 24.8 [95% CI, 6.3-97.7]) genes, all of which had previously been associated with adult FSGS, kidney function, or chronic kidney disease. We also highlighted novel, functionally relevant genes, including GRB2 (which encodes a slit diaphragm protein promoting podocyte structure through actin polymerization) and ITGB1 (which is linked to renal injuries). Our results suggest a major role for immune responses and antigen presentation in pediatric FSGS through (1) associations with SNPs in PTPRJ (or CD148, P=3.5×10^-7), which plays a role in T-cell receptor signaling, (2) HLA-DRB1∗11:01 association (P=6.1×10^-3; OR, 4.5 [95% CI, 1.5-13.0]), and (3) signaling pathway enrichment (P=1.3×10^-6).

LIMITATIONS

Sample size and no independent replication cohort with genomic data readily available.

CONCLUSIONS

Our genetic study has identified functionally relevant risk factors and the importance of immune regulation for pediatric primary FSGS, which contributes to a better description of its molecular pathophysiological mechanisms.

Secondhand smoke, genetic susceptibility, and incident chronic kidney disease in never smokers: A prospective study of a selected population from the UK Biobank

INTRODUCTION

A large number of people around the world are exposed to the risks of passive smoking. This prospective study aimed to examine the association between secondhand smoke exposure, exposure time, and the incidence of chronic kidney disease (CKD) and determine whether this association was influenced by genetic susceptibility.

METHODS

The study included 214244 participants of the UK Biobank who were initially free of CKD. Cox proportional hazards model was used to estimate the associations between secondhand smoke exposure time and the risks of CKD in people who have never smoked. The genetic risk score for CKD was calculated by a weighted method. The likelihood ratio test comparing models was used to examine the cross-product term between secondhand smoke exposure and genetic susceptibility to CKD outcomes.

RESULTS

During a median of 11.9 years of follow-up, 6583 incidents of CKD were documented. Secondhand smoke exposure increased the risk of CKD (HR=1.09; 95% CI: 1.03-1.16, p<0.01), and a dose-response relationship between CKD prevalence and secondhand smoke exposure time was found (p for trend<0.01). Secondhand smoke exposure increases the risk of CKD even in people who never smoke and have a low genetic risk (HR=1.13; 95% CI: 1.02-1.26, p=0.02). There was no statistically significant interaction between secondhand smoke exposure and genetic susceptibility to CKD (p for interaction=0.80).

CONCLUSIONS

Secondhand smoke exposure is associated with higher risk of CKD, even in people with low genetic risk, and the relationship is dose dependent. These findings change the belief that people with low genetic susceptibility and without direct participation in smoking activities are not prone to CKD, emphasizing the need to avoid the harm of secondhand smoke in public places.

Alterations of gut microbes and their correlation with clinical features in middle and end-stages chronic kidney disease

Gut microecosystem has been shown to play an important role in human health. In recent years, the concept of the gut-kidney axis has been proposed to explain the potential association between gut microbiota and chronic kidney disease (CKD). Here, a cohort of fecal samples collected from patients with CKD (n = 13) were involved. The composition of gut microbial communities and clinical features in CKD and end-stage renal disease (ESRD) were characterized. Our study focused on the changes in gut microbiome and the correlation with clinical features in patients with CKD and ESRD by analyzing high-throughput sequencing results of collected feces. We elucidated the alterations of gut microbiota in CKD patients at different stages of disease and initially identified the gut microbiota associated with CKD progression. We also combined correlation analysis to identify clinical features closely related to the gut microbiome. Our results offered the possibility of using non-invasive gut microbiome in the early diagnosis of course from CKD to ESRD and provide new insights into the association between clinical features and gut microbiota in CKD.

Genetically predicted body selenium concentration and eGFR: A Mendelian randomization study

Introduction

Selenium is a trace mineral that is commonly included in micronutrient supplements. The effect of selenium on kidney function remains unclear. A genetically predicted micronutrient and its association with estimated glomerular filtration rate (eGFR) can be used to assess the causal estimates by Mendelian randomization (MR).

Methods

In this MR study, we instrumented 11 genetic variants associated with blood or total selenium levels from a previous genome-wide association study (GWAS). The association between genetically predicted selenium concentration and eGFR was first assessed by summary-level MR in the chronic kidney disease(CKDGen) GWAS meta-analysis summary statistics, including 567,460 European samples. Inverse-variance weighted and pleiotropy-robust MR analyses were performed, in addition to multivariable MR adjusted for the effects of type 2 diabetes mellitus. Replication analysis was performed with individual-level UK Biobank data, including 337,318 White individuals of British ancestry.

Results

Summary-level MR analysis indicated that a genetically predicted 1 SD increase in selenium concentration was significantly associated with lower eGFR (-1.05 [-1.28, -0.82] %). The results were similarly reproduced by pleiotropy-robust MR analysis, including MR-Egger and weighted-median methods, and consistent even in the multivariable MR adjusted for diabetes. In the UK Biobank data, genetically predicted higher selenium concentration was also significantly associated with lower eGFR (- 0.36 [-0.52, -0.20] %), and the results were similar when body mass index, waist circumference, hypertension, and diabetes mellitus covariates were adjusted (-0.33 [-0.50, -0.17] %).

Conclusion

This MR study supports the hypothesis that higher genetically predicted body selenium is causally associated with lower eGFR.

Combing Genome-Wide Association Studies and Single-Cell Analysis to Elucidate the Mechanisms of Kidney Disease: Proceedings of the Henry Shavelle Professorship

Background

Kidney diseases pose a significant global health burden; there is an urgent need to deepen our understanding of their underlying mechanisms.

Summary

This review focuses on new innovative approaches that merge genome-wide association studies (GWAS) and single-cell omics (including transcriptomics) in kidney disease research. We begin by detailing how GWAS has identified numerous genetic risk factors, offering valuable insight into disease susceptibility. Then, we explore the application of scRNA-seq, highlighting its ability to unravel how genetic variants influence cellular phenotypes. Through a synthesis of recent studies, we illuminate the synergy between these two powerful methodologies, demonstrating their potential in elucidating the complex etiology of kidney diseases. Moreover, we discuss how this integrative approach could pave the way for precise diagnostics and personalized treatments.

Key Message

This review underscores the transformative potential of combining GWAS and scRNA-seq in the journey toward a deeper understanding of kidney diseases.

Identification of a Functional Susceptibility Variant for Adolescent Idiopathic Scoliosis that Upregulates Early Growth Response 1 (EGR1)-Mediated UNCX Expression

Adolescent idiopathic scoliosis (AIS) is a serious health problem affecting 3% of live births all over the world. Many loci associated with AIS have been identified by previous genome wide association studies, but their biological implication remains mostly unclear. In this study, we evaluated the AIS-associated variants in the 7p22.3 locus by combining in silico, in vitro, and in vivo analyses. rs78148157 was located in an enhancer of UNCX, a homeobox gene and its risk allele upregulated the UNCX expression. A transcription factor, early growth response 1 (EGR1), transactivated the rs78148157-located enhancer and showed a higher binding affinity for the risk allele of rs78148157. Furthermore, zebrafish larvae with UNCX messenger RNA (mRNA) injection developed body curvature and defective neurogenesis in a dose-dependent manner. rs78148157 confers the genetic susceptibility to AIS by enhancing the EGR1-regulated UNCX expression. © 2022 American Society for Bone and Mineral Research (ASBMR).

Causal associations between polyunsaturated fatty acids and kidney function: A bidirectional Mendelian randomization study

BACKGROUND

PUFAs were suggested to be beneficial for kidney function in observational studies. However, whether these associations are causal remains unclear.

OBJECTIVES

This study explores the causality between PUFAs and chronic kidney disease (CKD) or estimated glomerular filtration rate (eGFR) using bidirectional 2-sample Mendelian randomization (MR).

METHODS

Single nucleotide polymorphisms associated with PUFAs and kidney function were obtained from the largest and most recent genome-wide association studies with sample sizes of 13,544, 13,506, 13,499, 13,527, and 13,549 for omega-3 fatty acids, omega-6 fatty acids, DHA, LA, and other PUFAs than 18:2 (otPUFA), and 480,698 and 1,201,909 for CKD and eGFR, respectively. MR inverse-variance weighted (IVW) and pleiotropy residual sum and outlier test (MR-PRESSO) were used for data analysis, supplemented with a weighted median estimator, MR-Egger regression, and multivariable MR, giving β or OR and their 95% CIs.

RESULTS

There was suggestive evidence that higher omega-6 fatty acids were associated with increased eGFR using MR-PRESSO [β: 0.005 log(mL/min/1.73 m²) per SD increase in omega-6 fatty acids; 95% CI: 0.002, 0.008; P = 0.008]. Higher LA level was also associated with higher eGFR [β: 0.005 log(mL/min/1.73 m²) per SD increase in LA; 95% CI: 0.003, 0.007; P = 0.0007] using MR-PRESSO. Neither association of the other PUFAs, i.e., omega-3 fatty acids, DHA, and otPUFA, with CKD or eGFR nor the association of CKD and eGFR with PUFAs was found. Similar results were found in sensitivity analyses.

CONCLUSIONS

Our results suggest that higher omega-6 fatty acids and LA may increase eGFR levels. Although the estimated effects were relatively small, the results provide public health and research relevance, indicating the need for further longitudinal cohorts or randomized controlled trials on omega-6 fatty acids in improving kidney function.

Four missense genetic variants in CUBN are associated with higher levels of eGFR in non-diabetes but not in diabetes mellitus or its subtypes: A genetic association study in Europeans

AIM

Rare genetic variants in the CUBN gene encoding the main albumin-transporter in the proximal tubule of the kidneys have previously been associated with microalbuminuria and higher urine albumin levels, also in diabetes. Sequencing studies in isolated proteinuria suggest that these variants might not affect kidney function, despite proteinuria. However, the relation of these CUBN missense variants to the estimated glomerular filtration rate (eGFR) is largely unexplored. We hereby broadly examine the associations between four CUBN missense variants and eGFR_creatinine in Europeans with Type 1 (T1D) and Type 2 Diabetes (T2D). Furthermore, we sought to deepen our understanding of these variants in a range of single- and aggregate- variant analyses of other kidney-related traits in individuals with and without diabetes mellitus.

METHODS

We carried out a genetic association-based linear regression analysis between four CUBN missense variants (rs141640975, rs144360241, rs45551835, rs1801239) and eGFR_creatinine (ml/min/1.73 m², CKD-EPI_{creatinine(2012)}, natural log-transformed) in populations with T1D (n ~ 3,588) or T2D (n ~ 31,155) from multiple European studies and in individuals without diabetes from UK Biobank (UKBB, n ~ 370,061) with replication in deCODE (n = 127,090). Summary results of the diabetes-group were meta-analyzed using the fixed-effect inverse-variance method.

RESULTS

Albeit we did not observe associations between eGFR_creatinine and CUBN in the diabetes-group, we found significant positive associations between the minor alleles of all four variants and eGFR_creatinine in the UKBB individuals without diabetes with rs141640975 being the strongest (Effect=0.02, P_{eGFR_creatinine}=2.2 × 10^-9). We replicated the findings for rs141640975 in the Icelandic non-diabetes population (Effect=0.026, P_{eGFR_creatinine}=7.7 × 10^-4). For rs141640975, the eGFR_creatinine-association showed significant interaction with albuminuria levels (normo-, micro-, and macroalbuminuria; p = 0.03). An aggregated genetic risk score (GRS) was associated with higher urine albumin levels and eGFR_creatinine. The rs141640975 variant was also associated with higher levels of eGFR_{creatinine-cystatin C} (ml/min/1.73 m², CKD-EPI₂₀₂₁, natural log-transformed) and lower circulating cystatin C levels.

CONCLUSIONS

The positive associations between the four CUBN missense variants and eGFR in a large population without diabetes suggests a pleiotropic role of CUBN as a novel eGFR-locus in addition to it being a known albuminuria-locus. Additional associations with diverse renal function measures (lower cystatin C and higher eGFR_{creatinine-cystatin C} levels) and a CUBN-focused GRS further suggests an important role of CUBN in the future personalization of chronic kidney disease management in people without diabetes.

Quality assessment and refinement of chromatin accessibility data using a sequence-based predictive model

Chromatin accessibility assays are central to the genome-wide identification of gene regulatory elements associated with transcriptional regulation. However, the data have highly variable quality arising from several biological and technical factors. To surmount this problem, we developed a sequence-based machine learning method to evaluate and refine chromatin accessibility data. Our framework, gapped k-mer SVM quality check (gkmQC), provides the quality metrics for a sample based on the prediction accuracy of the trained models. We tested 886 DNase-seq samples from the ENCODE/Roadmap projects to demonstrate that gkmQC can effectively identify "high-quality" (HQ) samples with low conventional quality scores owing to marginal read depths. Peaks identified in HQ samples are more accurately aligned at functional regulatory elements, show greater enrichment of regulatory elements harboring functional variants, and explain greater heritability of phenotypes from their relevant tissues. Moreover, gkmQC can optimize the peak-calling threshold to identify additional peaks, especially for rare cell types in single-cell chromatin accessibility data.

A Mendelian randomization study to assess the genetic liability of gastroesophageal reflux disease for cardiovascular diseases and risk factors

Observational studies have reported that gastroesophageal reflux disease (GERD) is a risk factor for cardiovascular diseases (CVD); however, the causal inferences between them remain unknown. We conducted a Mendelian randomization (MR) study to estimate the causal associations between GERD and 10 CVD outcomes, as well as 14 cardiovascular risk factors. We used summary statistics from genome-wide association studies for GERD and the FinnGen consortium for CVD. We further investigated whether GERD correlated with cardiovascular risk factors and performed multivariable MR and mediation analyses to estimate the mediating effects of these risk factors on GERD-CVD progression. Sensitivity analyses and replication analyses were also performed. Our results indicated that GERD was positively associated with seven CVD outcomes with odds ratios of 1.26 [95% confidence interval (CI), 1.15, 1.37] for coronary artery disease, 1.41 (95% CI, 1.28, 1.57) for myocardial infarction, 1.34 (95% CI, 1.19, 1.51) for atrial fibrillation, 1.34 (95% CI, 1.21, 1.50) for heart failure, 1.30 (95% CI, 1.18, 1.43) for any stroke, 1.19 (95% CI, 1.06, 1.34) for ischemic stroke and 1.29 (95% CI, 1.16, 1.44) for venous thromboembolism. Furthermore, GERD was associated with nine cardiovascular risk factors and major depressive disorder demonstrated significant mediation effects on the causal pathway linking GERD and any stroke. This study demonstrates that GERD is associated with seven CVD outcomes and nine cardiovascular risk factors. Importantly, GERD treatment may help prevent common CVD events.

Increased soluble urokinase plasminogen activator levels modulate monocyte function to promote atherosclerosis

People with kidney disease are disproportionately affected by atherosclerosis for unclear reasons. Soluble urokinase plasminogen activator receptor (suPAR) is an immune-derived mediator of kidney disease, levels of which are strongly associated with cardiovascular outcomes. We assessed suPAR's pathogenic involvement in atherosclerosis using epidemiologic, genetic, and experimental approaches. We found serum suPAR levels to be predictive of coronary artery calcification and cardiovascular events in 5,406 participants without known coronary disease. In a genome-wide association meta-analysis including over 25,000 individuals, we identified a missense variant in the plasminogen activator, urokinase receptor (PLAUR) gene (rs4760), confirmed experimentally to lead to higher suPAR levels. Mendelian randomization analysis in the UK Biobank using rs4760 indicated a causal association between genetically predicted suPAR levels and atherosclerotic phenotypes. In an experimental model of atherosclerosis, proprotein convertase subtilisin/kexin-9 (Pcsk9) transfection in mice overexpressing suPAR (suPARTg) led to substantially increased atherosclerotic plaques with necrotic cores and macrophage infiltration compared with those in WT mice, despite similar cholesterol levels. Prior to induction of atherosclerosis, aortas of suPARTg mice excreted higher levels of CCL2 and had higher monocyte counts compared with WT aortas. Aortic and circulating suPARTg monocytes exhibited a proinflammatory profile and enhanced chemotaxis. These findings characterize suPAR as a pathogenic factor for atherosclerosis acting at least partially through modulation of monocyte function.

Genetically predicted sex hormone levels and health outcomes: phenome-wide Mendelian randomization investigation

BACKGROUND

Sex hormone-binding globulin (SHBG), testosterone and oestradiol have been associated with many diseases in observational studies; however, the causality of associations remains unestablished.

METHODS

A phenome-wide Mendelian randomization (MR) association study was performed to explore disease outcomes associated with genetically proxied circulating SHBG, testosterone and oestradiol levels by using updated genetic instruments in 339 197 unrelated White British individuals (54% female) in the UK Biobank. Two-sample MR analyses with data from large genetic studies were conducted to replicate identified associations in phenome-wide MR analyses. Multivariable MR analyses were performed to investigate mediation effects of hormone-related biomarkers in observed associations with diseases.

RESULTS

Phenome-wide MR analyses examined associations of genetically predicted SHBG, testosterone and oestradiol levels with 1211 disease outcomes, and identified 28 and 13 distinct phenotypes associated with genetically predicted SHBG and testosterone, respectively; 22 out of 28 associations for SHBG and 10 out of 13 associations for testosterone were replicated in two-sample MR analyses. Higher genetically predicted SHBG levels were associated with a reduced risk of hypertension, type 2 diabetes, diabetic complications, coronary atherosclerotic outcomes, gout and benign and malignant neoplasm of uterus, but an increased risk of varicose veins and fracture (mainly in females). Higher genetically predicted testosterone levels were associated with a lower risk of type 2 diabetes, coronary atherosclerotic outcomes, gout and coeliac disease mainly in males, but an increased risk of cholelithiasis in females.

CONCLUSIONS

These findings suggest that sex hormones may causally affect risk of several health outcomes.

Kidney function and risk of dementia: Observational study, meta-analysis, and two-sample mendelian randomization study

Whether impaired kidney function is associated with increased risk of developing dementia is unclear. We investigated the association between estimated glomerular filtration rate (eGFR) and dementia. Using a triangulation approach, we performed (1) a prospective study in 90,369 Danes from the Copenhagen General Population Study (CGPS), (2) a meta-analysis in 468,699 Scandinavians (including CGPS) and (3) a two-sample Mendelian randomization study in 218,792-1,004,040 Europeans using summary data from largest publicly available genome wide association studies (GWASs). During up to 15 years of follow-up (CGPS), 2,468 individuals developed dementia. Age and sex standardized percentile of eGFR below versus above the median conferred a multifactorially adjusted hazard ratio of 1.09 (95% confidence interval: 1.01-1.18). In meta-analysis, random-effects risk of dementia was 1.14 (1.06-1.22) for mildly decreased eGFR (60-90 mL/min/1.73 m²), 1.31 (0.92-1.87) for moderately decreased eGFR (30-59 mL/min/1.73 m²) and 1.91 (1.21-3.01) for severely decreased eGFR (< 30 mL/min/1.73 m²), compared to reference eGFR (> 90 mL/min/1.73 m²). Using directly comparable eGFR measures (log[eGFR] scaled to one standard deviation, as well as eGFR below versus above 60 mL/min/1.73 m²), we found no association with risk of dementia in observational CGPS or in Mendelian randomization analyses. In conclusion, impaired kidney function was associated with modestly increased risk of developing dementia. This was not supported by causal, genetic analyses using a Mendelian randomization approach. However, future stronger genetic instruments for kidney function and larger GWASs with more dementia cases, particularly for the vascular dementia subtype, warrant a re-evaluation of the causal hypothesis.

Exome sequencing unravels genetic variants associated with chronic kidney disease in Saudi Arabian patients

The use of genetic testing within nephrology is increasing and its diagnostic yield depends on the methods utilized, patient selection criteria, and population characteristics. We performed exome sequencing (ES) analysis on 102 chronic kidney disease (CKD) patients with likely genetic kidney disease. Patients had diverse CKD subtypes with/without consanguinity, positive family history, and possible hereditary renal syndrome with extra-renal abnormalities or progressive kidney disease of unknown etiology. The identified genetic variants associated with the observed kidney phenotypes were then confirmed and reported. End-stage kidney disease was reported in 51% of the cohort and a family history of kidney disease in 59%, while known consanguinity was reported in 54%. Pathogenic/likely pathogenic variants were identified in 43 patients with a diagnostic yield of 42%, and clinically associated variants of unknown significance (VUS) were identified in further 21 CKD patients (21%). A total of eight novel predicted pathogenic variants and eight VUS were detected. The clinical utility of ES within the nephrology clinic was demonstrated allowing patient management to be disease-specific. In this cohort, ES detected a diagnostic molecular abnormality in 42% of patients with CKD phenotypes. Positive family history and high rates of consanguinity likely contributed to this high diagnostic yield.

Identifying Genetic Variants and Metabolites Associated with Rapid Estimated Glomerular Filtration Rate Decline in Korea Based on Genome-Metabolomic Integrative Analysis

Identifying the predisposing factors to chronic or end-stage kidney disease is essential to preventing or slowing kidney function decline. Therefore, here, we investigated the genetic variants related to a rapid decline in the estimated glomerular filtration rate (eGFR) (i.e., a loss of >5 mL/min/1.73 m2 per year) and verified the relationships between variant-related diseases and metabolic pathway signaling in patients with chronic kidney disease. We conducted a genome-wide association study that included participants with diabetes, hypertension, and rapid eGFR decline from two Korean data sources (N = 115 and 69 for the discovery and the validation cohorts, respectively). We identified a novel susceptibility locus: 4q32.3 (rs10009742 in the MARCHF1 gene, beta = −3.540, P = 4.11 × 10−8). Fine-mapping revealed 19 credible, causal single-nucleotide polymorphisms, including rs10009742. The pimelylcarnitine and octadecenoyl carnitine serum concentrations were associated with rs10009742 (beta = 0.030, P = 7.10 × 10−5, false discovery rate (FDR) = 0.01; beta = 0.167, P = 8.11 × 10−4, FDR = 0.08). Our results suggest that MARCHF1 is associated with a rapid eGFR decline in patients with hypertension and diabetes. Furthermore, MARCHF1 affects the pimelylcarnitine metabolite concentration, which may mediate chronic kidney disease progression by inducing oxidative stress in the endoplasmic reticulum.

Mild-to-Moderate Kidney Dysfunction and Cardiovascular Disease: Observational and Mendelian Randomization Analyses

BACKGROUND

End-stage renal disease is associated with a high risk of cardiovascular events. It is unknown, however, whether mild-to-moderate kidney dysfunction is causally related to coronary heart disease (CHD) and stroke.

METHODS

Observational analyses were conducted using individual-level data from 4 population data sources (Emerging Risk Factors Collaboration, EPIC-CVD [European Prospective Investigation into Cancer and Nutrition-Cardiovascular Disease Study], Million Veteran Program, and UK Biobank), comprising 648 135 participants with no history of cardiovascular disease or diabetes at baseline, yielding 42 858 and 15 693 incident CHD and stroke events, respectively, during 6.8 million person-years of follow-up. Using a genetic risk score of 218 variants for estimated glomerular filtration rate (eGFR), we conducted Mendelian randomization analyses involving 413 718 participants (25 917 CHD and 8622 strokes) in EPIC-CVD, Million Veteran Program, and UK Biobank.

RESULTS

There were U-shaped observational associations of creatinine-based eGFR with CHD and stroke, with higher risk in participants with eGFR values <60 or >105 mL·min-1·1.73 m-2, compared with those with eGFR between 60 and 105 mL·min-1·1.73 m-2. Mendelian randomization analyses for CHD showed an association among participants with eGFR <60 mL·min-1·1.73 m-2, with a 14% (95% CI, 3%-27%) higher CHD risk per 5 mL·min-1·1.73 m-2 lower genetically predicted eGFR, but not for those with eGFR >105 mL·min-1·1.73 m-2. Results were not materially different after adjustment for factors associated with the eGFR genetic risk score, such as lipoprotein(a), triglycerides, hemoglobin A1c, and blood pressure. Mendelian randomization results for stroke were nonsignificant but broadly similar to those for CHD.

CONCLUSIONS

In people without manifest cardiovascular disease or diabetes, mild-to-moderate kidney dysfunction is causally related to risk of CHD, highlighting the potential value of preventive approaches that preserve and modulate kidney function.

Machine learning for risk stratification in kidney disease

PURPOSE OF REVIEW

Risk stratification for chronic kidney is becoming increasingly important as a clinical tool for both treatment and prevention measures. The goal of this review is to identify how machine learning tools contribute and facilitate risk stratification in the clinical setting.

RECENT FINDINGS

The two key machine learning paradigms to predictively stratify kidney disease risk are genomics-based and electronic health record based approaches. These methods can provide both quantitative information such as relative risk and qualitative information such as characterizing risk by subphenotype.

SUMMARY

The four key methods to stratify chronic kidney disease risk are genomics, multiomics, supervised and unsupervised machine learning methods. Polygenic risk scores utilize whole genome sequencing data to generate an individual's relative risk compared with the population. Multiomic methods integrate information from multiple biomarkers to generate trajectories and prognostic different outcomes. Supervised machine learning methods can directly utilize the growing compendia of electronic health records such as laboratory results and notes to generate direct risk predictions, while unsupervised machine learning methods can cluster individuals with chronic kidney disease into subphenotypes with differing approaches to care.

Rare and undiagnosed diseases: From disease-causing gene identification to mechanism elucidation

Rare and undiagnosed diseases substantially decrease patient quality of life and have increasingly become a heavy burden on healthcare systems. Because of the challenges in disease-causing gene identification and mechanism elucidation, patients are often confronted with difficulty obtaining a precise diagnosis and treatment. Due to advances in sequencing and multiomics analysis approaches combined with patient-derived iPSC models and gene-editing platforms, substantial progress has been made in the diagnosis and treatment of rare and undiagnosed diseases. The aforementioned techniques also provide an operational basis for future precision medicine studies. In this review, we summarize recent progress in identifying disease-causing genes based on GWAS/WES/WGS-guided multiomics analysis approaches. In addition, we discuss recent advances in the elucidation of pathogenic mechanisms and treatment of diseases with state-of-the-art iPSC and organoid models, which are improved by cell maturation level and gene editing technology. The comprehensive strategies described above will generate a new paradigm of disease classification that will significantly promote the precision and efficiency of diagnosis and treatment for rare and undiagnosed diseases.

Relationships of Serum 25-Hydroxyvitamin D Concentrations, Diabetes, Genetic Susceptibility, and New-Onset Chronic Kidney Disease

OBJECTIVE

The prospective relation of vitamin D status with the risk of chronic kidney diseases (CKD) remains uncertain. We aimed to examine the association of serum 25-hydroxyvitamin D (25OHD) with new-onset CKD in participants with and without diabetes at baseline and examine the potential modifications by genetic susceptibility on the association.

RESEARCH DESIGN AND METHODS

Included were 348,243 adults from the UK Biobank without prior CKD at baseline. Serum 25OHD concentrations were measured by chemiluminescent immunoassay method. Genetic risk score of CKD was calculated by 263 single nucleotide polymorphisms, which showed significant associations with estimated glomerular filtration rate. The primary outcome was new-onset CKD.

RESULTS

During a median follow-up duration of 12.1 years, 9,344 new-onset CKD were documented. Overall, there was a significant inverse association between baseline serum 25OHD and new-onset CKD in participants with diabetes (per SD increment, adjusted hazard ratio [HR] 0.91; 95% CI 0.86-0.96), but not in those without diabetes (per SD increment, adjusted HR 0.98; 95% CI 0.96-1.01; P-interaction between serum 25OHD and diabetes = 0.004). Accordingly, among participants with diabetes, compared with those baseline serum 25OHD <25 nmol/L, a significantly lower risk of new-onset CKD was found in those with 25OHD ≥50 nmol/L (adjusted HR 0.77; 95% CI 0.67-0.89). Moreover, the genetic risk of CKD did not significantly modify the association between baseline serum 25OHD and new-onset CKD among participants with diabetes (P-interaction = 0.127).

CONCLUSIONS

There was an inverse association between baseline serum 25OHD and new-onset CKD in participants with diabetes. The inverse association was not found in participants without diabetes.

Role of Uromodulin in Salt-Sensitive Hypertension

The exclusive expression of uromodulin in the kidneys has made it an intriguing protein in kidney and cardiovascular research. Genome-wide association studies discovered variants of uromodulin that are associated with chronic kidney diseases and hypertension. Urinary and circulating uromodulin levels reflect kidney and cardiovascular health as well as overall mortality. More recently, Mendelian randomization studies have shown that genetically driven levels of uromodulin have a causal and adverse effect on kidney function. On a mechanistic level, salt sensitivity is an important factor in the pathophysiology of hypertension, and uromodulin is involved in salt reabsorption via the NKCC2 (Na+-K+-2Cl- cotransporter) on epithelial cells of the ascending limb of loop of Henle. In this review, we provide an overview of the multifaceted physiology and pathophysiology of uromodulin including recent advances in its genetics; cellular trafficking; and mechanistic and clinical studies undertaken to understand the complex relationship between uromodulin, blood pressure, and kidney function. We focus on tubular sodium reabsorption as one of the best understood and pathophysiologically and clinically most important roles of uromodulin, which can lead to therapeutic interventions.

Genome-Wide Association Study for eGFR in a Taiwanese Population

BACKGROUND AND OBJECTIVES

Chronic kidney disease (CKD) is a global public health issue associated with large economic burdens. CKD contributes to higher risks of cardiovascular complications, kidney failure, and mortality. The incidence and prevalence rates of kidney failure in Taiwan have remained the highest in the world.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Assessing genetic factors that influence kidney function in specific populations has substantial clinical relevance. We investigated associations of genetic variants with eGFR. The quality control filtering and genotype imputation resulted in 10,008 Taiwan Biobank participants and 6,553,511 variants for final analyses. We examined these loci with in silico replication in individuals of European and African ancestry.

RESULTS

Our results revealed one significant locus (4q21.1) and three suggestive significant loci (17q23.2, 22q13.2, and 3q29) for eGFR in the Taiwanese population. In total, four conditional-independent single nucleotide polymorphisms were identified as the most important variants within these regions, including rs55948430 (Coiled-Coil Domain Containing 158), rs1010269 (BCAS3), rs56108505 (MKL1), and rs34796810 (upstream of DLG1). By performing a meta-analysis, we found that the 4q21.1 and 17q23.2 loci were successfully replicated in the European population, whereas only the 17q23.2 locus was replicated in African ancestry. Therefore, these two loci are suggested to be transethnic loci, and the other two eGFR-associated loci (22q13.2 and 3q29) are likely population specific.

CONCLUSIONS

We identified four susceptibility loci on 4q21.1, 17q23.2, 22q13.2, and 3q29 that associated with kidney-related traits in a Taiwanese population. The 22q13.2 (MKL1) and 3q29 (DLG1) were prioritized as critical candidates. Functional analyses delineated novel pathways related to kidney physiology in Taiwanese and East Asian ancestries.

Rare and common genetic determinants of metabolic individuality and their effects on human health

Garrod's concept of 'chemical individuality' has contributed to comprehension of the molecular origins of human diseases. Untargeted high-throughput metabolomic technologies provide an in-depth snapshot of human metabolism at scale. We studied the genetic architecture of the human plasma metabolome using 913 metabolites assayed in 19,994 individuals and identified 2,599 variant-metabolite associations (P < 1.25 × 10-11) within 330 genomic regions, with rare variants (minor allele frequency ≤ 1%) explaining 9.4% of associations. Jointly modeling metabolites in each region, we identified 423 regional, co-regulated, variant-metabolite clusters called genetically influenced metabotypes. We assigned causal genes for 62.4% of these genetically influenced metabotypes, providing new insights into fundamental metabolite physiology and clinical relevance, including metabolite-guided discovery of potential adverse drug effects (DPYD and SRD5A2). We show strong enrichment of inborn errors of metabolism-causing genes, with examples of metabolite associations and clinical phenotypes of non-pathogenic variant carriers matching characteristics of the inborn errors of metabolism. Systematic, phenotypic follow-up of metabolite-specific genetic scores revealed multiple potential etiological relationships.