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

Observational or Genetically Predicted Higher Vegetable Intake and Kidney Function Impairment: An Integrated Population-Scale Cross-Sectional Analysis and Mendelian Randomization Study

BACKGROUND

Further exploration of the possible effects of vegetable intake on kidney function is warranted.

OBJECTIVE

We aimed to study the causality of the association between vegetable intake and kidney function by implementing Mendelian randomization (MR) analysis.

METHODS

This study comprised a cross-sectional dietary investigation using UK Biobank data and MR analysis. For the cross-sectional investigation, 432,732 participants aged 40-69 y from the UK Biobank cohort were included. Self-reported vegetable intake was the exposure, and the outcomes were the estimated glomerular filtration rate (eGFR) and chronic kidney disease (CKD). Next, we included 337,138 participants of white British ancestry in the UK Biobank, and a genome-wide association study (GWAS) was performed to generate a genetic instrument. For MR, we first performed polygenic score (PGS)-based 1-sample MR. In addition, 2-sample MR was performed with CKDGen GWAS for kidney function traits, and the inverse variance weighted method was the main MR method.

RESULTS

Higher vegetable intake was cross-sectionally associated with a higher eGFR (per heaped tablespoon increase; β: 0.154; 95% CI: 0.144, 0.165) and lower odds of CKD (OR: 0.975; 95% CI: 0.968, 0.982). A PGS for vegetable intake was significantly associated with a higher eGFR [per ordinal category increase (0, 1-3, 4-6, ≥7 tablespoons per day); β: 4.435; 95% CI: 2.337, 6.533], but the association with CKD remained nonsignificant (OR: 0.468; 95% CI: 0.143, 1.535). In the 2-sample MR, the causal estimates indicated that a higher genetically predicted vegetable intake was associated with a higher eGFR (percent change; β: 3.071; 95% CI: 0.602, 0.560) but nonsignificantly associated with the risk of CKD (OR: 0.560; 95% CI: 0.289, 1.083) in the European ancestry data from the CKDGen.

CONCLUSIONS

This study suggests that higher vegetable intake may have a causal effect on higher eGFRs in the European population.

Kidney function and obstructive lung disease: a bidirectional Mendelian randomisation study

BACKGROUND

Additional study is warranted to investigate the causal effects between kidney function and obstructive lung disease.

METHODS

This study was a bidirectional two-sample Mendelian randomisation (MR) analysis. The CKDGen genome-wide association study (GWAS) meta-analysis for estimated glomerular filtration rate (eGFR) including individuals of European ancestry (N=567 460) provided the genetic instrument for kidney function and outcome summary statistics. A GWAS for FEV1/FVC including individuals of European ancestry from the UK Biobank (N=321 047) provided the genetic instrument for FEV1/FVC and outcome data. A polygenic score (PGS) analysis was performed to test the causal estimates from kidney function to binary obstructive lung disease outcomes, including chronic obstructive pulmonary disease (COPD), asthma, and FEV1/FVC<70%, and to perform non-linear MR with individual-level UK Biobank data.

RESULTS

The causal estimates by summary-level MR indicated that genetically predicted increased kidney function was significantly associated with increased FEV1/FVC Z scores [10% increase in eGFR, beta 0.055 (0.024, 0.086)]. The PGS for increased eGFR showed a significant association with a reduced risk of FEV1/FVC<70% [OR 0.93 (0.87, 0.99)], COPD [OR 0.93 (0.87, 0.99)] and late-onset (≥50 years old) asthma [OR 0.93 (0.88, 0.99)]. The non-linear MR demonstrated that the causal effect from eGFR to FEV1/FVC was apparent in eGFR ranges lower than 60 mL/min/1.73 m². On the other hand, genetically predicted FEV1/FVC showed nonsignificant causal estimates of eGFR change [beta 0.568% (-0.458, 1.605%)].

CONCLUSION

This study supports kidney function impairment would be a causative factor for obstructive lung disease.

Associations of Genetic Factors, Educational Attainment, and Their Interaction With Kidney Function Outcomes

Both genetic predisposition and low educational attainment (EA) are associated with higher risk of chronic kidney disease. We examined the interaction of EA and genetic risk in kidney function outcomes. We included 3,597 participants from the Prevention of Renal and Vascular End-Stage Disease Cohort Study, a longitudinal study in a community-based sample from Groningen, the Netherlands (median follow-up, 11 years; 1997–2012). Kidney function was approximated by obtaining estimated glomerular filtration rate (eGFR) from serum creatinine and cystatin C. Individual longitudinal linear eGFR trajectories were derived from linear mixed models. Genotype data on 63 single-nucleotide polymorphisms, with known associations with eGFR, were used to calculate an allele-weighted genetic score (WGS). EA was categorized into high, medium, and low. In ordinary least squares analysis, higher WGS and lower EA showed additive effects on reduced baseline eGFR; the interaction term was nonsignificant. In analysis of eGFR decline, the significant interaction term suggested amplification of genetic risk by low EA. Adjustment for known renal risk factors did not affect our results. This study presents the first evidence of gene-environment interaction between EA and a WGS for eGFR decline and provides population-level insights into the mechanisms underlying socioeconomic disparities in chronic kidney disease.

Epigenome-wide association study of kidney function identifies trans-ethnic and ethnic-specific loci

BACKGROUND

DNA methylation (DNAm) is associated with gene regulation and estimated glomerular filtration rate (eGFR), a measure of kidney function. Decreased eGFR is more common among US Hispanics and African Americans. The causes for this are poorly understood. We aimed to identify trans-ethnic and ethnic-specific differentially methylated positions (DMPs) associated with eGFR using an agnostic, genome-wide approach.

METHODS

The study included up to 5428 participants from multi-ethnic studies for discovery and 8109 participants for replication. We tested the associations between whole blood DNAm and eGFR using beta values from Illumina 450K or EPIC arrays. Ethnicity-stratified analyses were performed using linear mixed models adjusting for age, sex, smoking, and study-specific and technical variables. Summary results were meta-analyzed within and across ethnicities. Findings were assessed using integrative epigenomics methods and pathway analyses.

RESULTS

We identified 93 DMPs associated with eGFR at an FDR of 0.05 and replicated 13 and 1 DMPs across independent samples in trans-ethnic and African American meta-analyses, respectively. The study also validated 6 previously published DMPs. Identified DMPs showed significant overlap enrichment with DNase I hypersensitive sites in kidney tissue, sites associated with the expression of proximal genes, and transcription factor motifs and pathways associated with kidney tissue and kidney development.

CONCLUSIONS

We uncovered trans-ethnic and ethnic-specific DMPs associated with eGFR, including DMPs enriched in regulatory elements in kidney tissue and pathways related to kidney development. These findings shed light on epigenetic mechanisms associated with kidney function, bridging the gap between population-specific eGFR-associated DNAm and tissue-specific regulatory context.

The impact of cell type and context-dependent regulatory variants on human immune traits

BACKGROUND

The vast majority of trait-associated variants identified using genome-wide association studies (GWAS) are noncoding, and therefore assumed to impact gene regulation. However, the majority of trait-associated loci are unexplained by regulatory quantitative trait loci (QTLs).

RESULTS

We perform a comprehensive characterization of the putative mechanisms by which GWAS loci impact human immune traits. By harmonizing four major immune QTL studies, we identify 26,271 expression QTLs (eQTLs) and 23,121 splicing QTLs (sQTLs) spanning 18 immune cell types. Our colocalization analyses between QTLs and trait-associated loci from 72 GWAS reveals that genetic effects on RNA expression and splicing in immune cells colocalize with 40.4% of GWAS loci for immune-related traits, in many cases increasing the fraction of colocalized loci by two fold compared to previous studies. Notably, we find that the largest contributors of this increase are splicing QTLs, which colocalize on average with 14% of all GWAS loci that do not colocalize with eQTLs. By contrast, we find that cell type-specific eQTLs, and eQTLs with small effect sizes contribute very few new colocalizations. To investigate the 60% of GWAS loci that remain unexplained, we collect H3K27ac CUT&Tag data from rheumatoid arthritis and healthy controls, and find large-scale differences between immune cells from the different disease contexts, including at regions overlapping unexplained GWAS loci.

CONCLUSION

Altogether, our work supports RNA splicing as an important mediator of genetic effects on immune traits, and suggests that we must expand our study of regulatory processes in disease contexts to improve functional interpretation of as yet unexplained GWAS loci.

Single cell regulatory landscape of the mouse kidney highlights cellular differentiation programs and disease targets

Determining the epigenetic program that generates unique cell types in the kidney is critical for understanding cell-type heterogeneity during tissue homeostasis and injury response. Here, we profile open chromatin and gene expression in developing and adult mouse kidneys at single cell resolution. We show critical reliance of gene expression on distal regulatory elements (enhancers). We reveal key cell type-specific transcription factors and major gene-regulatory circuits for kidney cells. Dynamic chromatin and expression changes during nephron progenitor differentiation demonstrates that podocyte commitment occurs early and is associated with sustained Foxl1 expression. Renal tubule cells follow a more complex differentiation, where Hfn4a is associated with proximal and Tfap2b with distal fate. Mapping single nucleotide variants associated with human kidney disease implicates critical cell types, developmental stages, genes, and regulatory mechanisms. The single cell multi-omics atlas reveals key chromatin remodeling events and gene expression dynamics associated with kidney development.

Medical records-based chronic kidney disease phenotype for clinical care and "big data" observational and genetic studies

Chronic Kidney Disease (CKD) represents a slowly progressive disorder that is typically silent until late stages, but early intervention can significantly delay its progression. We designed a portable and scalable electronic CKD phenotype to facilitate early disease recognition and empower large-scale observational and genetic studies of kidney traits. The algorithm uses a combination of rule-based and machine-learning methods to automatically place patients on the staging grid of albuminuria by glomerular filtration rate ("A-by-G" grid). We manually validated the algorithm by 451 chart reviews across three medical systems, demonstrating overall positive predictive value of 95% for CKD cases and 97% for healthy controls. Independent case-control validation using 2350 patient records demonstrated diagnostic specificity of 97% and sensitivity of 87%. Application of the phenotype to 1.3 million patients demonstrated that over 80% of CKD cases are undetected using ICD codes alone. We also demonstrated several large-scale applications of the phenotype, including identifying stage-specific kidney disease comorbidities, in silico estimation of kidney trait heritability in thousands of pedigrees reconstructed from medical records, and biobank-based multicenter genome-wide and phenome-wide association studies.

Causal effects of physical activity or sedentary behaviors on kidney function: an integrated population-scale observational analysis and Mendelian randomization study

BACKGROUND

An investigation for the causality of the effects of physical activity and specific sedentary activities on kidney function in the general population is warranted.

METHODS

In this observational cohort study, first, the clinical associations of the prevalence of stages 3-5 chronic kidney disease (CKD) and the eGFR with physical activity, determined by self-report or objective wrist-band accelerometer results, and sedentary activities (watching television, using a computer, and driving) were investigated in 329,758 UK Biobank participants. To assess causality, a two-sample Mendelian randomization (MR) analysis was performed to investigate the associations of a genetic predisposition to physical activity and a sedentary lifestyle with the risk of kidney function impairment in an independent CKDGen genome-wide association study (N = 567,460). The findings were replicated with the 321,024 UK white British Biobank participants in the allele-score-based one-sample MR.

RESULTS

A higher degree of self-reported or accelerometer-determined moderate-to-vigorous physical activity was associated with a higher eGFR, while a longer time spent watching television was significantly associated with a lower eGFR and a higher prevalence of CKD. The two-sample MR demonstrated that the genetic predisposition to a higher degree of physical activity was associated with a lower risk of CKD and a higher eGFR, while the genetically predicted television watching duration was associated with a higher risk of CKD and a lower eGFR. The other sedentary behaviors yielded inconsistent results. The findings were similarly replicated in the one-sample MR.

CONCLUSION

Physical activity and television watching causally affect kidney function in the general population.

Causal effects of relative fat, protein, and carbohydrate intake on chronic kidney disease: a Mendelian randomization study

BACKGROUND

The effects of specific macronutrients on kidney function independent of total calorie intake have rarely been studied, although the composition of macronutrient intake has been reported to affect health outcomes.

OBJECTIVES

We aimed to investigate the effects of macronutrient intake ratios on the risk of chronic kidney disease (CKD) by Mendelian randomization (MR) analysis.

METHODS

The study was an observational cohort study mainly based on the UK Biobank and including MR analysis. First, we evaluated the relative baseline macronutrient composition-that is, the number of calories from each macronutrient divided by total calorie intake-of the diets of UK Biobank participants, and we used Cox regression to assess the incidence of end-stage kidney disease (ESKD) in 65,164 participants with normal kidney function [estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2]. We implemented a genetic instrument for relative fat, protein, and carbohydrate intake developed by a previous genome-wide association study (GWAS) and performed MR analysis. Two-sample MR was performed with the summary statistics from independent CKDGen GWAS for kidney function traits (n = 567,460), including CKD (eGFR <60 mL/min/1.73 m2) and log-transformed eGFR.

RESULTS

The median relative macronutrient intake composition at baseline was 35% fats, 15% protein, and 50% carbohydrates. Higher relative protein intake in subjects with normal kidney function was significantly associated with a lower risk of incident ESKD (HR: 0.54; 95% CI: 0.30, 0.95) in the observational investigation. Two-sample MR indicated that increased relative fat intake causally increased the risk of kidney function impairment [CKD (OR: 1.94; 95% CI: 1.39, 2.71); log eGFR (β: -0.036; 95% CI: -0.048, -0.024)] and that higher relative protein intake was causally linked to a lower CKD risk [CKD (OR: 0.50; 95% CI: 0.35, 0.72); log eGFR (β: 0.044; 95% CI: 0.030, 0.058)].

CONCLUSIONS

A desirable macronutrient composition, including high relative protein intake and low relative fat intake, may causally reduce the risk of CKD in the general population.

Knockout of γ-Adducin Promotes NG-Nitro-L-Arginine-Methyl-Ester-Induced Hypertensive Renal Injury

Previous studies identified a region on chromosome 1 associated with NG-nitro-L-arginine methyl ester (L-NAME) hypertension-induced renal disease in fawn-hooded hypertensive (FHH) rats. This region contains a mutant γ-adducin (Add3) gene that impairs renal blood flow (RBF) autoregulation, but its contribution to renal injury is unknown. The present study evaluated the hypothesis that knockout (KO) of Add3 impairs the renal vasoconstrictor response to the blockade of nitric oxide synthase and enhances hypertension-induced renal injury after chronic administration of L-NAME plus a high-salt diet. The acute hemodynamic effect of L-NAME and its chronic effects on hypertension and renal injury were compared in FHH 1Brown Norway (FHH 1BN) congenic rats (WT) expressing wild-type Add3 gene versus FHH 1BN Add3 KO rats. RBF was well autoregulated in WT rats but impaired in Add3 KO rats. Acute administration of L-NAME (10 mg/kg) raised mean arterial pressure (MAP) similarly in both strains, but RBF and glomerular filtration rate (GFR) fell by 38% in WT versus 15% in Add3 KO rats. MAP increased similarly in both strains after chronic administration of L-NAME and a high-salt diet; however, proteinuria and renal injury were greater in Add3 KO rats than in WT rats. Surprisingly, RBF, GFR, and glomerular capillary pressure were 41%, 82%, and 13% higher in L-NAME-treated Add3 KO rats than in WT rats. Hypertensive Add3 KO rats exhibited greater loss of podocytes and glomerular nephrin expression and increased interstitial fibrosis than in WT rats. These findings indicate that loss of ADD3 promotes L-NAME-induced renal injury by altering renal hemodynamics and enhancing the transmission of pressure to glomeruli. SIGNIFICANCE STATEMENT: A mutation in the γ-adducin (Add3) gene in fawn-hooded hypertensive rats that impairs autoregulation of renal blood flow is in a region of rat chromosome 1 homologous to a locus on human chromosome 10 associated with diabetic nephropathy. The present results indicate that loss of ADD3 enhanced NG-nitro-L-arginine methyl ester-induced hypertensive renal injury by altering the transmission of pressure to the glomerulus.

Genetic insights into rapid kidney function decline

Gorski et al. report a meta-GWAS of rapid kidney function decline in 42 longitudinal studies from the CKDGen Consortium and UK Biobank, amounting to more than 270'000 individuals with two eGFRcrea measurements. They identified genome-wide significant variants associated with two indexes of rapid kidney function decline, involving genes with a high potential for causality. These data increase our understanding of kidney function and risk of disease.

Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline

Rapid decline of glomerular filtration rate estimated from creatinine (eGFRcrea) is associated with severe clinical endpoints. In contrast to cross-sectionally assessed eGFRcrea, the genetic basis for rapid eGFRcrea decline is largely unknown. To help define this, we meta-analyzed 42 genome-wide association studies from the Chronic Kidney Diseases Genetics Consortium and United Kingdom Biobank to identify genetic loci for rapid eGFRcrea decline. Two definitions of eGFRcrea decline were used: 3 mL/min/1.73m2/year or more ("Rapid3"; encompassing 34,874 cases, 107,090 controls) and eGFRcrea decline 25% or more and eGFRcrea under 60 mL/min/1.73m2 at follow-up among those with eGFRcrea 60 mL/min/1.73m2 or more at baseline ("CKDi25"; encompassing 19,901 cases, 175,244 controls). Seven independent variants were identified across six loci for Rapid3 and/or CKDi25: consisting of five variants at four loci with genome-wide significance (near UMOD-PDILT (2), PRKAG2, WDR72, OR2S2) and two variants among 265 known eGFRcrea variants (near GATM, LARP4B). All these loci were novel for Rapid3 and/or CKDi25 and our bioinformatic follow-up prioritized variants and genes underneath these loci. The OR2S2 locus is novel for any eGFRcrea trait including interesting candidates. For the five genome-wide significant lead variants, we found supporting effects for annual change in blood urea nitrogen or cystatin-based eGFR, but not for GATM or LARP4B. Individuals at high compared to those at low genetic risk (8-14 vs. 0-5 adverse alleles) had a 1.20-fold increased risk of acute kidney injury (95% confidence interval 1.08-1.33). Thus, our identified loci for rapid kidney function decline may help prioritize therapeutic targets and identify mechanisms and individuals at risk for sustained deterioration of kidney function.

Using Mendelian randomization study to assess the renal effects of antihypertensive drugs

BACKGROUND

Angiotensin-converting enzyme (ACE) inhibitors and/or in combination with calcium channel blockers (CCBs) are generally recommended as the first-line antihypertensive therapy for people with hypertension and kidney dysfunction. Evidence from large randomized controlled trials comprehensively comparing renal effects of different classes of antihypertensive drugs is lacking.

METHODS

We used a Mendelian randomization study to obtain unconfounded associations of genetic proxies for antihypertensives with kidney function. Specifically, we used published genetic variants in genes regulating target proteins of these drugs and then applied to a meta-analysis of the largest available genome-wide association studies of kidney function (estimated glomerular filtration rate (eGFR), urine albumin-to-creatinine ratio (UACR), and albuminuria). Inverse variance weighting was used as the main analysis and to combine estimates from different sources.

RESULTS

Genetically predicted ACE inhibition was associated with higher eGFR (effect size 0.06, 95% confidence interval (CI) 0.008, 0.11), while genetic proxies for beta-blockers were associated with lower eGFR (- 0.02, 95% CI - 0.04, - 0.004) when meta-analyzing the UK Biobank and CKDGen. Genetic proxies for CCBs were associated with lower UACR (- 0.15, 95% CI - 0.28, - 0.02) and lower risk of albuminuria (odds ratio 0.58, 95% CI 0.37, 0.90) in CKDGen. The associations were robust to using different analysis methods and different genetic instruments.

CONCLUSIONS

Our findings suggest the reno-protective associations of genetically proxied ACE inhibitors and CCBs, while genetic proxies for beta-blockers may be related to lower eGFR. Understanding the underlying mechanisms would be valuable, with implications for drug development and repositioning of treatments for kidney disease.

Genetic kidney diseases as an underrecognized cause of chronic kidney disease: the key role of international registry reports

Inherited kidney diseases (IKDs) are among the leading causes of early-onset chronic kidney disease (CKD) and are responsible for at least 10-15% of cases of kidney replacement therapy (KRT) in adults. Paediatric nephrologists are very aware of the high prevalence of IKDs among their patients, but this is not the case for adult nephrologists. Recent publications have demonstrated that monogenic diseases account for a significant percentage of adult cases of CKD. A substantial number of these patients have received a non-specific/incorrect diagnosis or a diagnosis of CKD of unknown aetiology, which precludes correct treatment, follow-up and genetic counselling. There are a number of reasons why genetic kidney diseases are difficult to diagnose in adulthood: (i) adult nephrologists, in general, are not knowledgeable about IKDs; (ii) existence of atypical phenotypes; (iii) genetic testing is not universally available; (iv) family history is not always available or may be negative; (v) lack of knowledge of various genotype-phenotype relationships and (vi) conflicting interpretation of the pathogenicity of many sequence variants. Registries can contribute to visualize the burden of IKDs by regularly grouping all IKDs in their annual reports, as is done for glomerulonephritis or interstitial diseases, rather than reporting only cystic disease and hiding other IKDs under labels such as 'miscellaneous' or 'other'. Any effort to reduce the percentage of patients needing KRT with a diagnosis of 'nephropathy of unknown etiology' or an unspecific/incorrect diagnosis should be encouraged as a step towards precision nephrology. Genetic testing may be of value in this context but should not be used indiscriminately, but rather on the basis of a deep knowledge of IKDs.

Causal Effects of Homocysteine, Folate, and Cobalamin on Kidney Function: A Mendelian Randomization Study

Blood homocysteine level and related vitamin levels are associated with various health outcomes. We aimed to assess causal effects of blood homocysteine, folate, and cobalamin on kidney function in the general population by performing Mendelian randomization (MR) analysis. Genetic instruments for blood homocysteine, folate, and cobalamin levels were introduced from a previous genome-wide association (GWAS) meta-analysis of European individuals. Summary-level MR analysis was performed for the estimated glomerular filtration rate (eGFR) from the CKDGen consortium GWAS that included 567,460 European ancestry individuals. For replication, allele-score-based MR was performed with an independent U.K. Biobank cohort of 337,138 individuals of white British ancestry. In summary-level MR for the CKDGen data, high genetically predicted homocysteine levels were significantly associated with low eGFR (per 1 standard deviation, beta for eGFR change -0.95 (-1.21, -0.69) %), supported by pleiotropy-robust MR sensitivity analysis. Genetically predicted high folate levels were significantly associated with high eGFR change (0.86 (0.30, 1.42) %); however, causal estimates from cobalamin were nonsignificant (-0.11 (-0.33, 0.11) %). In the U.K. Biobank data, the results were consistently identified. Therefore, a high blood homocysteine level causally decreases eGFR. Future trials with appropriate homocysteine-lowering interventions may be helpful for the primary prevention of kidney function impairment.

The effect of angiotensin-converting enzyme levels on COVID-19 susceptibility and severity: a Mendelian randomization study

Background

There has been uncertainty about the safety or benefit of angiotensin-converting enzyme (ACE) inhibitors during the COVID-19 pandemic. We used Mendelian randomization using genetic determinants of serum-ACE levels to test whether decreased ACE levels increase susceptibility to SARS-CoV-2 infection or COVID-19 severity, while reducing potential bias from confounding and reverse causation in observational studies.

Methods

Genetic variants strongly associated with ACE levels, which were nearby the ACE gene, were identified from the ORIGIN trial and a separate genome-wide association study (GWAS) of ACE levels from the AGES cohort. The ORIGIN trial included 4147 individuals of European and Latino ancestries. Sensitivity analyses were performed using a study of 3200 Icelanders. Cohorts from the COVID-19 Host Genetics Initiative GWAS of up to 960 186 individuals of European ancestry were used for COVID-19 susceptibility, hospitalization and severe-disease outcome.

Results

Genetic variants were identified that explain between 18% and 37% of variance in ACE levels. Using genetic variants from the ORIGIN trial, a standard-deviation decrease in ACE levels was not associated with an increase in COVID-19 susceptibility [odds ratio (OR): 1.02, 95% confidence interval (CI): 0.90, 1.15], hospitalization (OR: 0.86, 95% CI: 0.68, 1.08) or severe disease (OR: 0.74, 95% CI: 0.51, 1.06). Using genetic variants from the AGES cohort, the result was similar for susceptibility (OR: 0.98, 95% CI: 0.89, 1.09), hospitalization (OR: 0.86, 95% CI: 0.66, 1.11) and severity (OR: 0.75, 95% CI: 0.50, 1.14). Multiple-sensitivity analyses led to similar results.

Conclusion

Genetically decreased serum ACE levels were not associated with susceptibility to, or severity of, COVID-19 disease. These data suggest that individuals taking ACE inhibitors should not discontinue therapy during the COVID-19 pandemic.

Mendelian pathway analysis of laboratory traits reveals distinct roles for ciliary subcompartments in common disease pathogenesis

Rare monogenic disorders of the primary cilium, termed ciliopathies, are characterized by extreme presentations of otherwise common diseases, such as diabetes, hepatic fibrosis, and kidney failure. However, despite a recent revolution in our understanding of the cilium's role in rare disease pathogenesis, the organelle's contribution to common disease remains largely unknown. Hypothesizing that common genetic variants within Mendelian ciliopathy genes might contribute to common complex diseases pathogenesis, we performed association studies of 16,874 common genetic variants across 122 ciliary genes with 12 quantitative laboratory traits characteristic of ciliopathy syndromes in 452,593 individuals in the UK Biobank. We incorporated tissue-specific gene expression analysis, expression quantitative trait loci, and Mendelian disease phenotype information into our analysis and replicated our findings in meta-analysis. 101 statistically significant associations were identified across 42 of the 122 examined ciliary genes (including eight novel replicating associations). These ciliary genes were widely expressed in tissues relevant to the phenotypes being studied, and eQTL analysis revealed strong evidence for correlation between ciliary gene expression levels and laboratory traits. Perhaps most interestingly, our analysis identified different ciliary subcompartments as being specifically associated with distinct sets of phenotypes. Taken together, our data demonstrate the utility of a Mendelian pathway-based approach to genomic association studies, challenge the widely held belief that the cilium is an organelle important mainly in development and in rare syndromic disease pathogenesis, and provide a framework for the continued integration of common and rare disease genetics to provide insight into the pathophysiology of human diseases of immense public health burden.

Leveraging genetic data to elucidate the relationship between Covid-19 and ischemic stroke

BACKGROUND

The relationship between coronavirus disease 2019 (Covid-19) and ischemic stroke is poorly defined. We aimed to leverage genetic data to investigate reported associations.

METHODS

Genetic association estimates for liability to Covid-19 and cardiovascular traits were obtained from large-scale consortia. Analyses primarily focused on critical Covid-19, defined as hospitalization with Covid-19 requiring respiratory support or resulting in death. Cross-trait linkage disequilibrium score regression was used to estimate genetic correlations of critical Covid-19 with ischemic stroke, other related cardiovascular outcomes, and risk factors common to both Covid-19 and cardiovascular disease (body mass index, smoking and chronic inflammation, estimated using C-reactive protein). Mendelian randomization analysis was performed to investigate whether liability to critical Covid-19 was associated with increased risk of any of the cardiovascular outcomes for which genetic correlation was identified.

RESULTS

There was evidence of genetic correlation between critical Covid-19 and ischemic stroke (r g =0.29, FDR p -value=4.65×10 -3 ), body mass index (r g =0.21, FDR- p -value = 6.26×10 -6 ) and C-reactive protein (r g =0.20, FDR- p -value=1.35×10 -4 ), but none of the other considered traits. In Mendelian randomization analysis, liability to critical Covid-19 was associated with increased risk of ischemic stroke (odds ratio [OR] per logOR increase in genetically predicted critical Covid-19 liability 1.03, 95% confidence interval 1.00-1.06, p -value=0.03). Similar estimates were obtained when considering ischemic stroke subtypes. Consistent estimates were also obtained when performing statistical sensitivity analyses more robust to the inclusion of pleiotropic variants, including multivariable Mendelian randomization analyses adjusting for potential genetic confounding through body mass index, smoking and chronic inflammation. There was no evidence to suggest that genetic liability to ischemic stroke increased the risk of critical Covid-19.

CONCLUSIONS

These data support that liability to critical Covid-19 is associated with an increased risk of ischemic stroke. The host response predisposing to severe Covid-19 is likely to increase the risk of ischemic stroke, independent of other potentially mitigating risk factors.

Cardiometabolic risk factors for COVID-19 susceptibility and severity: A Mendelian randomization analysis

BACKGROUND

Epidemiological studies report associations of diverse cardiometabolic conditions including obesity with COVID-19 illness, but causality has not been established. We sought to evaluate the associations of 17 cardiometabolic traits with COVID-19 susceptibility and severity using 2-sample Mendelian randomization (MR) analyses.

METHODS AND FINDINGS

We selected genetic variants associated with each exposure, including body mass index (BMI), at p < 5 × 10-8 from genome-wide association studies (GWASs). We then calculated inverse-variance-weighted averages of variant-specific estimates using summary statistics for susceptibility and severity from the COVID-19 Host Genetics Initiative GWAS meta-analyses of population-based cohorts and hospital registries comprising individuals with self-reported or genetically inferred European ancestry. Susceptibility was defined as testing positive for COVID-19 and severity was defined as hospitalization with COVID-19 versus population controls (anyone not a case in contributing cohorts). We repeated the analysis for BMI with effect estimates from the UK Biobank and performed pairwise multivariable MR to estimate the direct effects and indirect effects of BMI through obesity-related cardiometabolic diseases. Using p < 0.05/34 tests = 0.0015 to declare statistical significance, we found a nonsignificant association of genetically higher BMI with testing positive for COVID-19 (14,134 COVID-19 cases/1,284,876 controls, p = 0.002; UK Biobank: odds ratio 1.06 [95% CI 1.02, 1.10] per kg/m2; p = 0.004]) and a statistically significant association with higher risk of COVID-19 hospitalization (6,406 hospitalized COVID-19 cases/902,088 controls, p = 4.3 × 10-5; UK Biobank: odds ratio 1.14 [95% CI 1.07, 1.21] per kg/m2, p = 2.1 × 10-5). The implied direct effect of BMI was abolished upon conditioning on the effect on type 2 diabetes, coronary artery disease, stroke, and chronic kidney disease. No other cardiometabolic exposures tested were associated with a higher risk of poorer COVID-19 outcomes. Small study samples and weak genetic instruments could have limited the detection of modest associations, and pleiotropy may have biased effect estimates away from the null.

CONCLUSIONS

In this study, we found genetic evidence to support higher BMI as a causal risk factor for COVID-19 susceptibility and severity. These results raise the possibility that obesity could amplify COVID-19 disease burden independently or through its cardiometabolic consequences and suggest that targeting obesity may be a strategy to reduce the risk of severe COVID-19 outcomes.

Chromatin architecture reveals cell type-specific target genes for kidney disease risk variants

BACKGROUND

Cell type-specific transcriptional programming results from the combinatorial interplay between the repertoire of active regulatory elements. Disease-associated variants disrupt such programming, leading to altered expression of downstream regulated genes and the onset of pathological states. However, due to the non-linear regulatory properties of non-coding elements such as enhancers, which can activate transcription at long distances and in a non-directional way, the identification of causal variants and their target genes remains challenging. Here, we provide a multi-omics analysis to identify regulatory elements associated with functional kidney disease variants, and downstream regulated genes.

RESULTS

In order to understand the genetic risk of kidney diseases, we generated a comprehensive dataset of the chromatin landscape of human kidney tubule cells, including transcription-centered 3D chromatin organization, histone modifications distribution and transcriptome with HiChIP, ChIP-seq and RNA-seq. We identified genome-wide functional elements and thousands of interactions between the distal elements and target genes. The results revealed that risk variants for renal tumor and chronic kidney disease were enriched in kidney tubule cells. We further pinpointed the target genes for the variants and validated two target genes by CRISPR/Cas9 genome editing techniques in zebrafish, demonstrating that SLC34A1 and MTX1 were indispensable genes to maintain kidney function.

CONCLUSIONS

Our results provide a valuable multi-omics resource on the chromatin landscape of human kidney tubule cells and establish a bioinformatic pipeline in dissecting functions of kidney disease-associated variants based on cell type-specific epigenome.

Heart Disease and Stroke Statistics-2021 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 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. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease.

RESULTS

Each of the 27 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, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Genetically predicted education attainment in relation to somatic and mental health

A deeper understanding of the causal links from education level to health outcomes may shed a light for disease prevention. In the present Mendelian randomization study, we found that genetically higher education level was associated with lower risk of major mental disorders and most somatic diseases, independent of intelligence. Higher education level adjusted for intelligence was associated with lower risk of suicide attempts, insomnia, major depressive disorder, heart failure, stroke, coronary artery disease, lung cancer, breast cancer, type 2 diabetes and rheumatoid arthritis but with higher risk of obsessive-compulsive disorder, anorexia nervosa, anxiety, bipolar disorder and prostate cancer. Higher education level was associated with reduced obesity and smoking, which mediated quite an extent of the associations between education level and health outcomes. These findings emphasize the importance of education to reduce the burden of common diseases.

Inhibition of interleukin 6 signalling and renal function: A Mendelian randomization study

Inhibition of interleukin 6 (IL‐6) signalling has been proposed as a potential cardioprotective strategy for patients with chronic kidney disease (CKD), but the direct effects of IL‐6 inhibition on renal function are not known. A Mendelian randomization (MR) study was performed to investigate the association of genetically proxied inhibition of IL‐6 signalling with estimated glomerular filtration rate (eGFR), CKD and blood urea nitrogen (BUN). Inverse‐variance weighted MR was used as the main analysis, with sensitivity analyses performed using simple median, weighted median and MR‐Egger methods. There was no evidence for an association of genetically proxied inhibition of IL‐6 signalling (scaled per standard deviation unit decrease in C‐reactive protein) with log eGFR (0.001, 95% confidence interval −0.004‐0.007), BUN (0.009, 95% confidence interval −0.003‐0.021) and CKD (odds ratio 0.948, 95% confidence interval 0.822‐1.094). These findings do not raise concerns for IL‐6 signalling having large adverse effects on renal function.

Uromodulin: Roles in Health and Disease

Uromodulin, a protein exclusively produced by the kidney, is the most abundant urinary protein in physiological conditions. Already described several decades ago, uromodulin has gained the spotlight in recent years, since the discovery that mutations in its encoding gene UMOD cause a renal Mendelian disease (autosomal dominant tubulointerstitial kidney disease) and that common polymorphisms are associated with multifactorial disorders, such as chronic kidney disease, hypertension, and cardiovascular diseases. Moreover, variations in uromodulin levels in urine and/or blood reflect kidney functioning mass and are of prognostic value for renal function, cardiovascular events, and overall mortality. The clinical relevance of uromodulin reflects its multifunctional nature, playing a role in renal ion transport and immunomodulation, in protection against urinary tract infections and renal stones, and possibly as a systemic antioxidant. Here, we discuss the multifaceted roles of this protein in kidney physiology and its translational relevance.

Epigenomics and the kidney

PURPOSE OF REVIEW

Epigenetic modifications are reversible changes to a cell's DNA or histones that alter gene expression but not DNA sequence. The present review will explore epigenomic profiling and bioinformatics techniques for the study of kidney development and disease.

RECENT FINDINGS

Reversible DNA and histone modifications influence chromatin accessibility and can be measured by a variety of recent techniques including DNase-seq, ATAC-seq, and single cell ATAC-seq. These approaches have been used to demonstrate that DNA methylation is critical for nephron progenitor maturation, for example. New bioinformatics techniques allow the prediction of chromatin loops that connect regulatory elements to target genes. Recent studies have demonstrated that DNA elements regulate transcription in the kidney via long-range physical interactions and create a new framework for understanding how genome wide association studies risk loci contribute to kidney disease. Increasingly, epigenomic approaches are being combined with transcriptomic analyses to generate multimodal datasets.

SUMMARY

Epigenomics has expanded our knowledge of gene architecture and regulation. Novel tools and techniques have led to the emergence of 'multiomics' in which epigenomic profiling, transcriptomics, and additional methods complement each other to improve our understanding of kidney disease and development.

The Nuclear Receptor ESRRA Protects from Kidney Disease by Coupling Metabolism and Differentiation

Kidney disease is poorly understood because of the organ's cellular diversity. We used single-cell RNA sequencing not only in resolving differences in injured kidney tissue cellular composition but also in cell-type-specific gene expression in mouse models of kidney disease. This analysis highlighted major changes in cellular diversity in kidney disease, which markedly impacted whole-kidney transcriptomics outputs. Cell-type-specific differential expression analysis identified proximal tubule (PT) cells as the key vulnerable cell type. Through unbiased cell trajectory analyses, we show that PT cell differentiation is altered in kidney disease. Metabolism (fatty acid oxidation and oxidative phosphorylation) in PT cells showed the strongest and most reproducible association with PT cell differentiation and disease. Coupling of cell differentiation and the metabolism was established by nuclear receptors (estrogen-related receptor alpha [ESRRA] and peroxisomal proliferation-activated receptor alpha [PPARA]) that directly control metabolic and PT-cell-specific gene expression in mice and patient samples while protecting from kidney disease in the mouse model.

Common genetic variants and modifiable risk factors underpin hypertrophic cardiomyopathy susceptibility and expressivity

Hypertrophic cardiomyopathy (HCM) is a common, serious, genetic heart disorder. Rare pathogenic variants in sarcomere genes cause HCM, but with unexplained phenotypic heterogeneity. Moreover, most patients do not carry such variants. We report a genome-wide association study of 2,780 cases and 47,486 controls that identified 12 genome-wide-significant susceptibility loci for HCM. Single-nucleotide polymorphism heritability indicated a strong polygenic influence, especially for sarcomere-negative HCM (64% of cases; h2g = 0.34 ± 0.02). A genetic risk score showed substantial influence on the odds of HCM in a validation study, halving the odds in the lowest quintile and doubling them in the highest quintile, and also influenced phenotypic severity in sarcomere variant carriers. Mendelian randomization identified diastolic blood pressure (DBP) as a key modifiable risk factor for sarcomere-negative HCM, with a one standard deviation increase in DBP increasing the HCM risk fourfold. Common variants and modifiable risk factors have important roles in HCM that we suggest will be clinically actionable.

Genetics of 35 blood and urine biomarkers in the UK Biobank

Clinical laboratory tests are a critical component of the continuum of care. We evaluate the genetic basis of 35 blood and urine laboratory measurements in the UK Biobank (n = 363,228 individuals). We identify 1,857 loci associated with at least one trait, containing 3,374 fine-mapped associations and additional sets of large-effect (>0.1 s.d.) protein-altering, human leukocyte antigen (HLA) and copy number variant (CNV) associations. Through Mendelian randomization (MR) analysis, we discover 51 causal relationships, including previously known agonistic effects of urate on gout and cystatin C on stroke. Finally, we develop polygenic risk scores (PRSs) for each biomarker and build 'multi-PRS' models for diseases using 35 PRSs simultaneously, which improved chronic kidney disease, type 2 diabetes, gout and alcoholic cirrhosis genetic risk stratification in an independent dataset (FinnGen; n = 135,500) relative to single-disease PRSs. Together, our results delineate the genetic basis of biomarkers and their causal influences on diseases and improve genetic risk stratification for common diseases.

Adiponectin affects estimated glomerular filtration rate: A two-sample bidirectional Mendelian randomization study

BACKGROUND

The causal relationship between adiponectin (ADPN) and estimated glomerular filtration rate (eGFR) is unclear. This study adopts a two-sample bidirectional Mendelian randomization (MR) study to explore the causal relationship between ADPN and eGFR.

METHODS

Using eight single nucleotide polymorphisms (SNP) of ADPN and 26 SNP of eGFR as instrumental variables, the study performs a two-sample bidirectional MR study using MR inverse-variance weighted (IVW), MR-Egger and weighted median approach to evaluate the causal relationship between ADPN and eGFR. Using the genetic risk score (GRS) of ADPN and eGFR as instrumental variables, the study performs a second MR analysis to assess the association between ADPN and eGFR.

RESULTS

In ADPN to eGFR MR analysis, the IVW, weighted median and GRS analysis all showed that ADPN had a causal effect on eGFR after removing potential confounders of the ADPN-eGFR relation (IVW: β = .016, P = .002; weighted median: β = .012, P = .022; GRS: β = .016, P = 1.48E-05). As both ADPN and eGFR were natural log-transformed in the corresponding GWAS, eGFR increased by 0.15% for any 10% increase in ADPN. In eGFR to ADPN MR analysis, eGFR had no causal effect on ADPN after removing potential confounders of the eGFR-ADPN relation (All P values > 0.05). The heterogeneity test and sensitivity analysis indicated some heterogeneity, but no directional pleiotropy.

CONCLUSION

Adiponectin has a causal effect on eGFR, while eGFR has no causal effect on ADPN. ADPN may be a clinical target for improving eGFR and treating chronic kidney disease caused by decreased eGFR.

Sept8/SEPTIN8 involvement in cellular structure and kidney damage is identified by genetic mapping and a novel human tubule hypoxic model

Chronic kidney disease (CKD), which can ultimately progress to kidney failure, is influenced by genetics and the environment. Genes identified in human genome wide association studies (GWAS) explain only a small proportion of the heritable variation and lack functional validation, indicating the need for additional model systems. Outbred heterogeneous stock (HS) rats have been used for genetic fine-mapping of complex traits, but have not previously been used for CKD traits. We performed GWAS for urinary protein excretion (UPE) and CKD related serum biochemistries in 245 male HS rats. Quantitative trait loci (QTL) were identified using a linear mixed effect model that tested for association with imputed genotypes. Candidate genes were identified using bioinformatics tools and targeted RNAseq followed by testing in a novel in vitro model of human tubule, hypoxia-induced damage. We identified two QTL for UPE and five for serum biochemistries. Protein modeling identified a missense variant within Septin 8 (Sept8) as a candidate for UPE. Sept8/SEPTIN8 expression increased in HS rats with elevated UPE and tubulointerstitial injury and in the in vitro hypoxia model. SEPTIN8 is detected within proximal tubule cells in human kidney samples and localizes with acetyl-alpha tubulin in the culture system. After hypoxia, SEPTIN8 staining becomes diffuse and appears to relocalize with actin. These data suggest a role of SEPTIN8 in cellular organization and structure in response to environmental stress. This study demonstrates that integration of a rat genetic model with an environmentally induced tubule damage system identifies Sept8/SEPTIN8 and informs novel aspects of the complex gene by environmental interactions contributing to CKD risk.

Kidney disease genetic risk variants alter lysosomal beta-mannosidase (MANBA) expression and disease severity

More than 800 million people in the world suffer from chronic kidney disease (CKD). Genome-wide association studies (GWAS) have identified hundreds of loci where genetic variants are associated with kidney function; however, causal genes and pathways for CKD remain unknown. Here, we performed integration of kidney function GWAS and human kidney-specific expression quantitative trait analysis and identified that the expression of beta-mannosidase (MANBA) was lower in kidneys of subjects with CKD risk genotype. We also show an increased incidence of renal failure in subjects with rare heterozygous loss-of-function coding variants in MANBA using phenome-wide association analysis of 40,963 subjects with exome sequencing data. MANBA is a lysosomal gene highly expressed in kidney tubule cells. Deep phenotyping revealed structural and functional lysosomal alterations in human kidneys from subjects with CKD risk alleles and mice with genetic deletion of Manba Manba heterozygous and knockout mice developed more severe kidney fibrosis when subjected to toxic injury induced by cisplatin or folic acid. Manba loss altered multiple pathways, including endocytosis and autophagy. In the absence of Manba, toxic acute tubule injury induced inflammasome activation and fibrosis. Together, these results illustrate the convergence of common noncoding and rare coding variants in MANBA in kidney disease development and demonstrate the role of the endolysosomal system in kidney disease development.

Tissue-Specific 1H-NMR Metabolomic Profiling in Mice with Adenine-Induced Chronic Kidney Disease

Chronic kidney disease (CKD) results in the impaired filtration of metabolites, which may be toxic or harmful to organs/tissues. The objective of this study was to perform unbiased 1H nuclear magnetic resonance (NMR)-based metabolomics profiling of tissues from mice with CKD. Five-month-old male C57BL6J mice were placed on either a casein control diet or adenine-supplemented diet to induce CKD for 24 weeks. CKD was confirmed by significant increases in blood urea nitrogen (24.1 ± 7.7 vs. 105.3 ± 18.3 mg/dL, p < 0.0001) in adenine-fed mice. Following this chronic adenine diet, the kidney, heart, liver, and quadriceps muscles were rapidly dissected; snap-frozen in liquid nitrogen; and the metabolites were extracted. Metabolomic profiling coupled with multivariate analyses confirm clear separation in both aqueous and organic phases between control and CKD mice. Severe energetic stress and apparent impaired mitochondrial metabolism were observed in CKD kidneys evidenced by the depletion of ATP and NAD+, along with significant alterations in tricarboxylic acid (TCA) cycle intermediates. Altered amino acid metabolism was observed in all tissues, although significant differences in specific amino acids varied across tissue types. Taken together, this study provides a metabolomics fingerprint of multiple tissues from mice with and without severe CKD induced by chronic adenine feeding.

Evolutionary genetics and acclimatization in nephrology

Evolutionary processes, including mutation, migration and natural selection, have influenced the prevalence and distribution of various disorders in humans. However, despite a few well-known examples, such as the APOL1 variants - which have undergone positive genetic selection for their ability to confer resistance to Trypanosoma brucei infection but confer a higher risk of chronic kidney disease - little is known about the effects of evolutionary processes that have shaped genetic variation on kidney disease. An understanding of basic concepts in evolutionary genetics provides an opportunity to consider how findings from ancient and archaic genomes could inform our knowledge of evolution and provide insights into how population migration and genetic admixture have shaped the current distribution and landscape of human kidney-associated diseases. Differences in exposures to infectious agents, environmental toxins, dietary components and climate also have the potential to influence the evolutionary genetics of kidneys. Of note, selective pressure on loci associated with kidney disease is often from non-kidney diseases, and thus it is important to understand how the link between genome-wide selected loci and kidney disease occurs in relation to secondary nephropathies.

Protective Role of Nrf2 in Renal Disease

Chronic kidney disease (CKD) is one of the fastest-growing causes of death and is predicted to become by 2040 the fifth global cause of death. CKD is characterized by increased oxidative stress and chronic inflammation. However, therapies to slow or prevent CKD progression remain an unmet need. Nrf2 (nuclear factor erythroid 2-related factor 2) is a transcription factor that plays a key role in protection against oxidative stress and regulation of the inflammatory response. Consequently, the use of compounds targeting Nrf2 has generated growing interest for nephrologists. Pre-clinical and clinical studies have demonstrated that Nrf2-inducing strategies prevent CKD progression and protect from acute kidney injury (AKI). In this article, we review current knowledge on the protective mechanisms mediated by Nrf2 against kidney injury, novel therapeutic strategies to induce Nrf2 activation, and the status of ongoing clinical trials targeting Nrf2 in renal diseases.

Familial Aggregation of CKD and Heritability of Kidney Biomarkers in the General Population: The Lifelines Cohort Study

RATIONALE & OBJECTIVE

Chronic kidney disease (CKD) has a heritable component. We aimed to quantify familial aggregation of CKD in the general population and assess the extent to which kidney traits could be explained by genetic and environmental factors.

STUDY DESIGN

Cross-sectional 3-generation family study.

SETTING & PARTICIPANTS

Data were collected at entry into the Lifelines Cohort Study from a sample of the general population of the northern Netherlands, composed predominantly of individuals of European ancestry.

EXPOSURE

Family history of CKD.

OUTCOMES

The primary outcome was CKD, defined as estimated glomerular filtration rate (eGFR)<60mL/min/1.73m², where GFR was estimated using the CKD Epidemiology Collaboration creatinine equation. Among a subsample for which urinary albumin concentration was available (n=59,943), urinary albumin excretion was expressed as the rate of urinary albumin excretion (UAE) per 24 hours or urinary albumin-creatinine ratio (UACR).

ANALYTICAL APPROACH

Familial aggregation of CKD was assessed by calculating the recurrence risk ratio (RRR), using adapted Cox proportional hazards models. Heritability of continuous kidney-related traits was estimated using linear mixed models and defined as the ratio of the additive genetic variance to total phenotypic variance. All models were adjusted for age, sex, and known risk factors for kidney disease.

RESULTS

Among 155,911 participants with available eGFR data, the prevalence of CKD was 1.19% (1,862 cases per 155,911). The risk of CKD in those with an affected first-degree relative was 3 timeshigher than the risk in the total sample (RRR, 3.04 [95% CI, 2.26-4.09). In those with an affected spouse, risk of CKD was also higher (RRR, 1.56 [95% CI, 1.20-1.96]), indicative of shared environmental factors and/or assortative mating. Heritability estimates of eGFR, UAE, and UACR were 44%, 20%, and 18%, respectively. For serum urea, creatinine, and uric acid, estimates were 31%, 37%, and 48%, respectively, whereas estimates for serum electrolytes ranged from 22% to 28%.

LIMITATIONS

Use of estimated rather than measured GFR. UAE data only available in a subsample.

CONCLUSIONS

In this large population-based family study, a positive family history was strongly associated with increased risk of CKD. We observed moderate to high heritability of kidney traits and related biomarkers. These results indicate an important role of genetic factors in CKD risk.

Causal effects of education on chronic kidney disease: a Mendelian randomization study

Background

Poor socio-economic status, including low education attainment, has been reported in chronic kidney disease (CKD) patients. We aimed to investigate the causal effects of education attainment on the risk of CKD.

Methods

The study was an observational cohort study including Mendelian randomization (MR) analysis. First, the clinical association between education attainment years as the exposure and prevalent CKD Stages 3–5 as the outcome was investigated by multivariable logistic regression in 308 741 individuals 40–69 years of age from the UK Biobank. MR analysis was performed with a previously reported genetic instrument from a genome-wide association meta-analysis of education attainment. Two-sample MR was performed with summary statistics for CKD in 567 460 individuals with European ancestry in the CKDGen genome-wide association meta-analysis. The findings were replicated by allele score–based MR in 321 260 individuals of white British ancestry in the UK Biobank with quality-controlled genetic data.

Results

Higher education attainment was significantly associated with lower adjusted odds for CKD in the clinical analysis {>17 years versus <16 years, adjusted odds ratio [OR] 0.910 [95% confidence interval (CI) 0.849–0.975]}. The causal estimates obtained by the inverse variance method in the two-sample MR indicated that higher genetically predicted education attainment causally reduced the risk of CKD [OR 0.934 (95% CI 0.873–0.999)]. Allele score–based MR also supported that higher education attainment was causally linked to a decreased risk of CKD [adjusted OR 0.944 (95% CI 0.922–0.966)].

Conclusion

The study suggests that higher education attainment causally reduces the risk of CKD development in the general population.

A Rare Kidney Disease To Cure Them All? Towards Mechanism-Based Therapies for Proteinopathies

Autosomal dominant tubulointerstitial kidney diseases (ADTKDs) are a group of rare genetic diseases that lead to kidney failure. Mutations in the MUC1 gene cause ADTKD-MUC1 (MUC1 kidney disease, MKD), a disorder with no available therapies. Recent studies have identified the molecular and cellular mechanisms that drive MKD disease pathogenesis. Armed with patient-derived cell lines and pluripotent stem cell (iPSC)-derived kidney organoids, it was found that MKD is a toxic proteinopathy caused by the intracellular accumulation of misfolded MUC1 protein in the early secretory pathway. We discuss the advantages of studying rare monogenic kidney diseases, describe effective patient-derived model systems, and highlight recent mechanistic insights into protein quality control that have implications for additional proteinopathies beyond rare kidney diseases.

Genetic architecture of host proteins involved in SARS-CoV-2 infection

Understanding the genetic architecture of host proteins interacting with SARS-CoV-2 or mediating the maladaptive host response to COVID-19 can help to identify new or repurpose existing drugs targeting those proteins. We present a genetic discovery study of 179 such host proteins among 10,708 individuals using an aptamer-based technique. We identify 220 host DNA sequence variants acting in cis (MAF 0.01-49.9%) and explaining 0.3-70.9% of the variance of 97 of these proteins, including 45 with no previously known protein quantitative trait loci (pQTL) and 38 encoding current drug targets. Systematic characterization of pQTLs across the phenome identified protein-drug-disease links and evidence that putative viral interaction partners such as MARK3 affect immune response. Our results accelerate the evaluation and prioritization of new drug development programmes and repurposing of trials to prevent, treat or reduce adverse outcomes. Rapid sharing and detailed interrogation of results is facilitated through an interactive webserver ( https://omicscience.org/apps/covidpgwas/ ).

Improved Detection of Potentially Pleiotropic Genes in Coronary Artery Disease and Chronic Kidney Disease Using GWAS Summary Statistics

The coexistence of coronary artery disease (CAD) and chronic kidney disease (CKD) implies overlapped genetic foundation. However, the common genetic determination between the two diseases remains largely unknown. Relying on summary statistics publicly available from large scale genome-wide association studies (n = 184,305 for CAD and n = 567,460 for CKD), we observed significant positive genetic correlation between CAD and CKD (r_g = 0.173, p = 0.024) via the linkage disequilibrium score regression. Next, we implemented gene-based association analysis for each disease through MAGMA (Multi-marker Analysis of GenoMic Annotation) and detected 763 and 827 genes associated with CAD or CKD (FDR < 0.05). Among those 72 genes were shared between the two diseases. Furthermore, by integrating the overlapped genetic information between CAD and CKD, we implemented two pleiotropy-informed informatics approaches including cFDR (conditional false discovery rate) and GPA (Genetic analysis incorporating Pleiotropy and Annotation), and identified 169 and 504 shared genes (FDR < 0.05), of which 121 genes were simultaneously discovered by cFDR and GPA. Importantly, we found 11 potentially new pleiotropic genes related to both CAD and CKD (i.e., ARHGEF19, RSG1, NDST2, CAMK2G, VCL, LRP10, RBM23, USP10, WNT9B, GOSR2, and RPRML). Five of the newly identified pleiotropic genes were further repeated via an additional dataset CAD available from UK Biobank. Our functional enrichment analysis showed that those pleiotropic genes were enriched in diverse relevant pathway processes including quaternary ammonium group transmembrane transporter, dopamine transport. Overall, this study identifies common genetic architectures overlapped between CAD and CKD and will help to advance understanding of the molecular mechanisms underlying the comorbidity of the two diseases.

Functionally informed fine-mapping and polygenic localization of complex trait heritability

Fine-mapping aims to identify causal variants impacting complex traits. We propose PolyFun, a computationally scalable framework to improve fine-mapping accuracy by leveraging functional annotations across the entire genome-not just genome-wide-significant loci-to specify prior probabilities for fine-mapping methods such as SuSiE or FINEMAP. In simulations, PolyFun + SuSiE and PolyFun + FINEMAP were well calibrated and identified >20% more variants with a posterior causal probability >0.95 than identified in their nonfunctionally informed counterparts. In analyses of 49 UK Biobank traits (average n = 318,000), PolyFun + SuSiE identified 3,025 fine-mapped variant-trait pairs with posterior causal probability >0.95, a >32% improvement versus SuSiE. We used posterior mean per-SNP heritabilities from PolyFun + SuSiE to perform polygenic localization, constructing minimal sets of common SNPs causally explaining 50% of common SNP heritability; these sets ranged in size from 28 (hair color) to 3,400 (height) to 2 million (number of children). In conclusion, PolyFun prioritizes variants for functional follow-up and provides insights into complex trait architectures.

Genome-Wide Association Studies of CKD and Related Traits

The past few years have seen major advances in genome-wide association studies (GWAS) of CKD and kidney function-related traits in several areas: increases in sample size from >100,000 to >1 million, enabling the discovery of >250 associated genetic loci that are highly reproducible; the inclusion of participants not only of European but also of non-European ancestries; and the use of advanced computational methods to integrate additional genomic and other unbiased, high-dimensional data to characterize the underlying genetic architecture and prioritize potentially causal genes and variants. Together with other large-scale biobank and genetic association studies of complex traits, these GWAS of kidney function-related traits have also provided novel insight into the relationship of kidney function to other diseases with respect to their genetic associations, genetic correlation, and directional relationships. A number of studies also included functional experiments using model organisms or cell lines to validate prioritized potentially causal genes and/or variants. In this review article, we will summarize these recent GWAS of CKD and kidney function-related traits, explain approaches for downstream characterization of associated genetic loci and the value of such computational follow-up analyses, and discuss related challenges along with potential solutions to ultimately enable improved treatment and prevention of kidney diseases through genetics.

Systematic integrated analysis of genetic and epigenetic variation in diabetic kidney disease

Poor metabolic control and host genetic predisposition are critical for diabetic kidney disease (DKD) development. The epigenome integrates information from sequence variations and metabolic alterations. Here, we performed a genome-wide methylome association analysis in 500 subjects with DKD from the Chronic Renal Insufficiency Cohort for DKD phenotypes, including glycemic control, albuminuria, kidney function, and kidney function decline. We show distinct methylation patterns associated with each phenotype. We define methylation variations that are associated with underlying nucleotide variations (methylation quantitative trait loci) and show that underlying genetic variations are important drivers of methylation changes. We implemented Bayesian multitrait colocalization analysis (moloc) and summary data-based Mendelian randomization to systematically annotate genomic regions that show association with kidney function, methylation, and gene expression. We prioritized 40 loci, where methylation and gene-expression changes likely mediate the genotype effect on kidney disease development. Functional annotation suggested the role of inflammation, specifically, apoptotic cell clearance and complement activation in kidney disease development. Our study defines methylation changes associated with DKD phenotypes, the key role of underlying genetic variations driving methylation variations, and prioritizes methylome and gene-expression changes that likely mediate the genotype effect on kidney disease pathogenesis.

Integrated multi-omics approaches to improve classification of chronic kidney disease

Chronic kidney diseases (CKDs) are currently classified according to their clinical features, associated comorbidities and pattern of injury on biopsy. Even within a given classification, considerable variation exists in disease presentation, progression and response to therapy, highlighting heterogeneity in the underlying biological mechanisms. As a result, patients and clinicians experience uncertainty when considering optimal treatment approaches and risk projection. Technological advances now enable large-scale datasets, including DNA and RNA sequence data, proteomics and metabolomics data, to be captured from individuals and groups of patients along the genotype-phenotype continuum of CKD. The ability to combine these high-dimensional datasets, in which the number of variables exceeds the number of clinical outcome observations, using computational approaches such as machine learning, provides an opportunity to re-classify patients into molecularly defined subgroups that better reflect underlying disease mechanisms. Patients with CKD are uniquely poised to benefit from these integrative, multi-omics approaches since the kidney biopsy, blood and urine samples used to generate these different types of molecular data are frequently obtained during routine clinical care. The ultimate goal of developing an integrated molecular classification is to improve diagnostic classification, risk stratification and assignment of molecular, disease-specific therapies to improve the care of patients with CKD.

Unravelling the complex genetics of common kidney diseases: from variants to mechanisms

Genome-wide association studies (GWAS) have identified hundreds of loci associated with kidney-related traits such as glomerular filtration rate, albuminuria, hypertension, electrolyte and metabolite levels. However, these impressive, large-scale mapping approaches have not always translated into an improved understanding of disease or development of novel therapeutics. GWAS have several important limitations. Nearly all disease-associated risk loci are located in the non-coding region of the genome and therefore, their target genes, affected cell types and regulatory mechanisms remain unknown. Genome-scale approaches can be used to identify associations between DNA sequence variants and changes in gene expression (quantified through bulk and single-cell methods), gene regulation and other molecular quantitative trait studies, such as chromatin accessibility, DNA methylation, protein expression and metabolite levels. Data obtained through these approaches, used in combination with robust computational methods, can deliver robust mechanistic inferences for translational exploitation. Understanding the genetic basis of common kidney diseases means having a comprehensive picture of the genes that have a causal role in disease development and progression, of the cells, tissues and organs in which these genes act to affect the disease, of the cellular pathways and mechanisms that drive disease, and of potential targets for disease prevention, detection and therapy.

Rare genetic causes of complex kidney and urological diseases

Although often considered a single-entity, chronic kidney disease (CKD) comprises many pathophysiologically distinct disorders that result in persistently abnormal kidney structure and/or function, and encompass both monogenic and polygenic aetiologies. Rare inherited forms of CKD frequently span diverse phenotypes, reflecting genetic phenomena including pleiotropy, incomplete penetrance and variable expressivity. Use of chromosomal microarray and massively parallel sequencing technologies has revealed that genomic disorders and monogenic aetiologies contribute meaningfully to seemingly complex forms of CKD across different clinically defined subgroups and are characterized by high genetic and phenotypic heterogeneity. Investigations of prevalent genomic disorders in CKD have integrated genetic, bioinformatic and functional studies to pinpoint the genetic drivers underlying their renal and extra-renal manifestations, revealing both monogenic and polygenic mechanisms. Similarly, massively parallel sequencing-based analyses have identified gene- and allele-level variation that contribute to the clinically diverse phenotypes observed for many monogenic forms of nephropathy. Genome-wide sequencing studies suggest that dual genetic diagnoses are found in at least 5% of patients in whom a genetic cause of disease is identified, highlighting the fact that complex phenotypes can also arise from multilocus variation. A multifaceted approach that incorporates genetic and phenotypic data from large, diverse cohorts will help to elucidate the complex relationships between genotype and phenotype for different forms of CKD, supporting personalized medicine for individuals with kidney disease.

Genetic Determinants of Antibody-Mediated Immune Responses to Infectious Diseases Agents: A Genome-Wide and HLA Association Study

BACKGROUND

Infectious diseases are causally related to a large array of noncommunicable diseases (NCDs). Identifying genetic determinants of infections and antibody-mediated immune responses may shed light on this relationship and provide therapeutic targets for drug and vaccine development.

METHODS

We used the UK biobank cohort of up to 10 000 serological measurements of infectious diseases and genome-wide genotyping. We used data on 13 pathogens to define 46 phenotypes: 15 seropositivity case-control phenotypes and 31 quantitative antibody measurement phenotypes. For each of these, we performed genome-wide association studies (GWAS) using the fastGWA linear mixed model package and human leukocyte antigen (HLA) classical allele and amino acid residue associations analyses using Lasso regression for variable selection.

RESULTS

We included a total of 8735 individuals for case-control phenotypes, and an average (range) of 4286 (276-8555) samples per quantitative analysis. Fourteen of the GWAS yielded a genome-wide significant (P < 5 ×10-8) locus at the major histocompatibility complex (MHC) on chromosome 6. Outside the MHC, we found a total of 60 loci, multiple associated with Epstein-Barr virus (EBV)-related NCDs (eg, RASA3, MED12L, and IRF4). FUT2 was also identified as an important gene for polyomaviridae. HLA analysis highlighted the importance of DRB1*09:01, DQB1*02:01, DQA1*01:02, and DQA1*03:01 in EBV serologies and of DRB1*15:01 in polyomaviridae.

CONCLUSIONS

We have identified multiple genetic variants associated with antibody immune response to 13 infections, many of which are biologically plausible therapeutic or vaccine targets. This may help prioritize future research and drug development.

Epigenome-wide association study identifies DNA methylation sites associated with target organ damage in older African Americans

Target organ damage (TOD) manifests as vascular injuries in the body organ systems associated with long-standing hypertension. DNA methylation in peripheral blood leukocytes can capture inflammatory processes and gene expression changes underlying TOD. We investigated the association between epigenome-wide DNA methylation and five measures of TOD (estimated glomerular filtration rate (eGFR), urinary albumin-creatinine ratio (UACR), left ventricular mass index (LVMI), relative wall thickness (RWT), and white matter hyperintensity (WMH)) in 961 African Americans from hypertensive sibships. A multivariate (multi-trait) model of eGFR, UACR, LVMI, and RWT identified seven CpGs associated with at least one of the traits (cg21134922, cg04816311 near C7orf50, cg09155024, cg10254690 near OAT, cg07660512, cg12661888 near IFT43, and cg02264946 near CATSPERD) at FDR q < 0.1. Adjusting for blood pressure, body mass index, and type 2 diabetes attenuated the association for four CpGs. DNA methylation was associated with cis-gene expression for some CpGs, but no significant mediation by gene expression was detected. Mendelian randomization analyses suggested causality between three CpGs and eGFR (cg04816311, cg10254690, and cg07660512). We also assessed whether the identified CpGs were associated with TOD in 614 African Americans in the Hypertension Genetic Epidemiology Network (HyperGEN) study. Out of three CpGs available for replication, cg04816311 was significantly associated with eGFR (p = 0.0003), LVMI (p = 0.0003), and RWT (p = 0.002). This study found evidence of an association between DNA methylation and TOD in African Americans and highlights the utility of using a multivariate-based model that leverages information across related traits in epigenome-wide association studies.