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

Genome-wide association studies identify the role of caspase-9 in kidney disease

Genome-wide association studies (GWAS) have identified hundreds of genetic risk regions for kidney dysfunction [estimated glomerular filtration rate (eGFR)]; however, the causal genes, cell types, and pathways are poorly understood. Integration of GWAS and human kidney expression of quantitative trait analysis using Bayesian colocations, transcriptome-wide association studies, and summary-based Mendelian randomization studies prioritized caspase-9 (CASP9) as a kidney disease risk gene. Human kidney single-cell epigenetic and immunostaining studies indicated kidney tubule cells as a disease-causing cell type. Mice with genetic deletion or pharmacological inhibition of CASP9 showed lower apoptosis while having improved mitophagy, resulting in dampened activation of cytosolic nucleotide sensing pathways (cGAS-STING), reduction of inflammation, and protection from acute kidney disease or renal fibrosis. In summary, here, we prioritized CASP9 as an eGFR GWAS target gene and demonstrated the causal role of CASP9 in kidney disease development via improving mitophagy and lowering inflammation and apoptosis.

Integrative analysis of the plasma proteome and polygenic risk of cardiometabolic diseases

Cardiometabolic diseases are frequently polygenic in architecture, comprising a large number of risk alleles with small effects spread across the genome1-3. Polygenic scores (PGS) aggregate these into a metric representing an individual's genetic predisposition to disease. PGS have shown promise for early risk prediction4-7 and there is an open question as to whether PGS can also be used to understand disease biology8. Here, we demonstrate that cardiometabolic disease PGS can be used to elucidate the proteins underlying disease pathogenesis. In 3,087 healthy individuals, we found that PGS for coronary artery disease, type 2 diabetes, chronic kidney disease and ischaemic stroke are associated with the levels of 49 plasma proteins. Associations were polygenic in architecture, largely independent of cis and trans protein quantitative trait loci and present for proteins without quantitative trait loci. Over a follow-up of 7.7 years, 28 of these proteins associated with future myocardial infarction or type 2 diabetes events, 16 of which were mediators between polygenic risk and incident disease. Twelve of these were druggable targets with therapeutic potential. Our results demonstrate the potential for PGS to uncover causal disease biology and targets with therapeutic potential, including those that may be missed by approaches utilizing information at a single locus.

The genetic basis of urate control and gout: Insights into molecular pathogenesis from follow-up study of genome-wide association study loci

This review focuses on the post-genome-wide association study (GWAS) era in gout, i.e., the translation of GWAS genetic association signals into biologically informative knowledge. Analytical and experimental follow-up of individual loci, based on the identification of causal genetic variants, reveals molecular pathogenic pathways. We summarize in detail the largest GWAS in urate to date, then we review follow-up studies and molecular insights from ABCG2, HNF4A, PDZK1, MAF, GCKR, ALDH2, ALDH16A1, SLC22A12, SLC2A9, ABCC4, and SLC22A13, including the role of insulin signaling. One common factor in these pathways is the importance of transcriptional control, including the HNF4α transcription factor. The new molecular knowledge reveals new targets for intervention to manage urate levels and prevent gout.

Diabetic kidney disease: Are the reported associations with single-nucleotide polymorphisms disease-specific?

BACKGROUND

The genetic backgrounds of diabetic kidney disease (DKD) and end-stage kidney disease (ESKD) have not been fully elucidated.

AIM

To examine the individual and cumulative effects of single-nucleotide polymorphisms (SNPs) previously associated with DKD on the risk for ESKD of diabetic etiology and to determine if any associations observed were specific for DKD.

METHODS

Fourteen SNPs were genotyped in hemodialyzed 136 patients with diabetic ESKD (DKD group) and 121 patients with non-diabetic ESKD (NDKD group). Patients were also re-classified on the basis of the primary cause of chronic kidney disease (CKD). The distribution of alleles was compared between diabetic and non-diabetic groups as well as between different sub-phenotypes. The weighted multilocus genetic risk score (GRS) was calculated to estimate the cumulative risk conferred by all SNPs. The GRS distribution was then compared between the DKD and NDKD groups as well as in the groups according to the primary cause of CKD.

RESULTS

One SNP (rs841853; SLC2A1) showed a nominal association with DKD (P = 0.048; P > 0.05 after Bonferroni correction). The GRS was higher in the DKD group (0.615 ± 0.260) than in the NDKD group (0.590 ± 0.253), but the difference was not significant (P = 0.46). The analysis of associations between GRS and individual factors did not show any significant correlation. However, the GRS was significantly higher in patients with glomerular disease than in those with tubulointerstitial disease (P = 0.014) and in those with a combined group (tubulointerstitial, vascular, and cystic and congenital disease) (P = 0.018).

CONCLUSION

Our results suggest that selected SNPs that were previously associated with DKD may not be specific for DKD and may confer risk for CKD of different etiology, particularly those affecting renal glomeruli.

Kidney damage causally affects the brain cortical structure: A Mendelian randomization study

BACKGROUND

Alterations in the brain cortical structures of patients with chronic kidney disease (CKD) have been reported; however, the cause has not been determined yet. Herein, we used Mendelian randomization (MR) to reveal the causal effect of kidney damage on brain cortical structure.

METHODS

Genome-wide association studies summary data of estimated glomerular filtration rate (eGFR) in 480,698 participants from the CKDGen Consortium were used to identify genetically predicted eGFR. Data from 567,460 individuals from the CKDGen Consortium were used to assess genetically determined CKD; 302,687 participants from the UK Biobank were used to evaluate genetically predicted albuminuria. Further, data from 51,665 patients from the ENIGMA Consortium were used to assess the relationship between genetic predisposition and reduced eGFR, CKD, and progressive albuminuria with alterations in cortical thickness (TH) or surficial area (SA) of the brain. Magnetic resonance imaging was used to measure the SA and TH globally and in 34 functional regions. Inverse-variance weighted was used as the primary estimate whereas MR Pleiotropy RESidual Sum and Outlier, MR-Egger and weighted median were used to detect heterogeneity and pleiotropy.

FINDINGS

At the global level, albuminuria decreased TH (β = -0.07 mm, 95% CI: -0.12 mm to -0.02 mm, P = 0.004); at the functional level, albuminuria reduced TH of pars opercularis gyrus without global weighted (β = -0.11 mm, 95% CI: -0.16 mm to -0.07 mm, P = 3.74×10-6). No pleiotropy was detected.

INTERPRETATION

Kidney damage causally influences the cortex structure which suggests the existence of a kidney-brain axis.

FUNDING

This study was supported by the Science and Technology Planning Project of Guangdong Province (Grant No. 2020A1515111119 and 2017B020227007), the National Key Research and Development Program of China (Grant No. 2018YFA0902803), the National Natural Science Foundation of China (Grant No. 81825016, 81961128027, 81772719, 81772728), the Key Areas Research and Development Program of Guangdong (Grant No. 2018B010109006), Guangdong Special Support Program (2017TX04R246), Grant KLB09001 from the Key Laboratory of Malignant Tumor Gene Regulation and Target Therapy of Guangdong Higher Education Institutes, and Grants from the Guangdong Science and Technology Department (2020B1212060018).

Association of Coding Variants in Hydroxysteroid 17-beta Dehydrogenase 14 (HSD17B14) with Reduced Progression to End Stage Kidney Disease in Type 1 Diabetes

BACKGROUND

Rare variants in gene coding regions likely have a greater impact on disease-related phenotypes than common variants through disruption of their encoded protein. We searched for rare variants associated with onset of ESKD in individuals with type 1 diabetes at advanced kidney disease stage.

METHODS

Gene-based exome array analyses of 15,449 genes in five large incidence cohorts of individuals with type 1 diabetes and proteinuria were analyzed for survival time to ESKD, testing the top gene in a sixth cohort (n=2372/1115 events all cohorts) and replicating in two retrospective case-control studies (n=1072 cases, 752 controls). Deep resequencing of the top associated gene in five cohorts confirmed the findings. We performed immunohistochemistry and gene expression experiments in human control and diseased cells, and in mouse ischemia reperfusion and aristolochic acid nephropathy models.

RESULTS

Protein coding variants in the hydroxysteroid 17-β dehydrogenase 14 gene (HSD17B14), predicted to affect protein structure, had a net protective effect against development of ESKD at exome-wide significance (n=4196; P value=3.3 × 10-7). The HSD17B14 gene and encoded enzyme were robustly expressed in healthy human kidney, maximally in proximal tubular cells. Paradoxically, gene and protein expression were attenuated in human diabetic proximal tubules and in mouse kidney injury models. Expressed HSD17B14 gene and protein levels remained low without recovery after 21 days in a murine ischemic reperfusion injury model. Decreased gene expression was found in other CKD-associated renal pathologies.

CONCLUSIONS

HSD17B14 gene is mechanistically involved in diabetic kidney disease. The encoded sex steroid enzyme is a druggable target, potentially opening a new avenue for therapeutic development.

Multi-phenotype genome-wide association studies of the Norfolk Island isolate implicate pleiotropic loci involved in chronic kidney disease

Chronic kidney disease (CKD) is a persistent impairment of kidney function. Genome-wide association studies (GWAS) have revealed multiple genetic loci associated with CKD susceptibility but the complete genetic basis is not yet clear. Since CKD shares risk factors with cardiovascular diseases and diabetes, there may be pleiotropic loci at play but may go undetected when using single phenotype GWAS. Here, we used multi-phenotype GWAS in the Norfolk Island isolate (n = 380) to identify new loci associated with CKD. We performed a principal components analysis on different combinations of 29 quantitative traits to extract principal components (PCs) representative of multiple correlated phenotypes. GWAS of a PC derived from glomerular filtration rate, serum creatinine, and serum urea identified a suggestive peak (pmin = 1.67 × 10-7) that mapped to KCNIP4. Inclusion of other secondary CKD measurements with these three kidney function traits identified the KCNIP4 locus with GWAS significance (pmin = 1.59 × 10-9). Finally, we identified a group of two SNPs with increased minor allele frequencies as potential functional variants. With the use of genetic isolate and the PCA-based multi-phenotype GWAS approach, we have revealed a potential pleotropic effect locus for CKD. Further studies are required to assess functional relevance of this locus.

Cholesteryl ester transfer protein (CETP) as a drug target for cardiovascular disease

Development of cholesteryl ester transfer protein (CETP) inhibitors for coronary heart disease (CHD) has yet to deliver licensed medicines. To distinguish compound from drug target failure, we compared evidence from clinical trials and drug target Mendelian randomization of CETP protein concentration, comparing this to Mendelian randomization of proprotein convertase subtilisin/kexin type 9 (PCSK9). We show that previous failures of CETP inhibitors are likely compound related, as illustrated by significant degrees of between-compound heterogeneity in effects on lipids, blood pressure, and clinical outcomes observed in trials. On-target CETP inhibition, assessed through Mendelian randomization, is expected to reduce the risk of CHD, heart failure, diabetes, and chronic kidney disease, while increasing the risk of age-related macular degeneration. In contrast, lower PCSK9 concentration is anticipated to decrease the risk of CHD, heart failure, atrial fibrillation, chronic kidney disease, multiple sclerosis, and stroke, while potentially increasing the risk of Alzheimer's disease and asthma. Due to distinct effects on lipoprotein metabolite profiles, joint inhibition of CETP and PCSK9 may provide added benefit. In conclusion, we provide genetic evidence that CETP is an effective target for CHD prevention but with a potential on-target adverse effect on age-related macular degeneration.

Exploring the Pleiotropic Genes and Therapeutic Targets Associated with Heart Failure and Chronic Kidney Disease by Integrating metaCCA and SGLT2 Inhibitors' Target Prediction

Background

Previous studies have shown that heart failure (HF) and chronic kidney disease (CKD) have common genetic mechanisms, overlapping pathophysiological pathways, and therapeutic drug—sodium-glucose cotransporter 2 (SGLT2) inhibitors.

Methods

The genetic pleiotropy metaCCA method was applied on summary statistics data from two independent meta-analyses of GWAS comprising more than 1 million people to identify shared variants and pleiotropic effects between HF and CKD. Targets of SGLT2 inhibitors were predicted by SwissTargetPrediction and DrugBank databases. To refine all genes, we performed using versatile gene-based association study 2 (VEGAS2) and transcriptome-wide association studies (TWAS) for HF and CKD, respectively. Gene enrichment and KEGG pathway analyses were used to explore the potential functional significance of the identified genes and targets.

Results

After metaCCA analysis, 4,624 SNPs and 1,745 genes were identified to be potentially pleiotropic in the univariate and multivariate SNP-multivariate phenotype analyses, respectively. 21 common genes were detected in both metaCCA and SGLT2 inhibitors' target prediction. In addition, 169 putative pleiotropic genes were identified, which met the significance threshold both in metaCCA analysis and in the VEGAS2 or TWAS analysis for at least one disease.

Conclusion

We identified novel variants associated with HF and CKD using effectively incorporating information from different GWAS datasets. Our analysis may provide new insights into HF and CKD therapeutic approaches based on the pleiotropic genes, common targets, and mechanisms by integrating the metaCCA method, TWAS and VEGAS2 analyses, and target prediction of SGLT2 inhibitors.

Sex Differences in Hypertrophic Cardiomyopathy: Interaction With Genetics and Environment

Purpose of Review

We explore the sex-specific interaction of genetics and the environment on the clinical course and outcomes of hypertrophic cardiomyopathy (HCM).

Recent Findings

Women account for approximately one-third of patients in specialist HCM centres and reported in observational studies. As a result, evidence informing clinical guideline recommendations is based predominantly on risk factors and outcomes seen in men. However, disease progression appears to be different between the sexes. Women present at a more advanced stage of disease, are older at diagnosis, have higher symptom burden, carry greater risk for heart failure and are at greater risk of mortality compared to men. Women are more likely to be gene-positive, while men are more likely to be gene-negative. The risk of sudden cardiac death and access to specialised care do not differ between the sexes.

Summary

Reporting sex-disaggregated results is essential to identify the mechanisms leading to sex differences in HCM.

Mapping the genetic architecture of human traits to cell types in the kidney identifies mechanisms of disease and potential treatments

The functional interpretation of genome-wide association studies (GWAS) is challenging due to the cell-type-dependent influences of genetic variants. Here, we generated comprehensive maps of expression quantitative trait loci (eQTLs) for 659 microdissected human kidney samples and identified cell-type-eQTLs by mapping interactions between cell type abundances and genotypes. By partitioning heritability using stratified linkage disequilibrium score regression to integrate GWAS with single-cell RNA sequencing and single-nucleus assay for transposase-accessible chromatin with high-throughput sequencing data, we prioritized proximal tubules for kidney function and endothelial cells and distal tubule segments for blood pressure pathogenesis. Bayesian colocalization analysis nominated more than 200 genes for kidney function and hypertension. Our study clarifies the mechanism of commonly used antihypertensive and renal-protective drugs and identifies drug repurposing opportunities for kidney disease.

Genome-Wide Association Meta-Analysis Supports Genes Involved in Valve and Cardiac Development to Associate With Mitral Valve Prolapse

BACKGROUND

Mitral valve prolapse (MVP) is a common cardiac valve disease, which affects 1 in 40 in the general population. Previous genome-wide association study has identified 6 risk loci for MVP. But these loci explained only partially the genetic risk for MVP. We aim to identify additional risk loci for MVP by adding data set from the UK Biobank.

METHODS

We also incorporated 434 MVP cases and 4527 controls from the UK Biobank for discovery analyses. Genetic association was conducted using SNPTEST and meta-analyses using METAL. We used Functional Mapping and Annotation of Genome-Wide Association Studies for post-genome-wide association study annotations and Multi-marker Analysis of GenoMic Annotation for gene-based and gene-set analyses.

RESULTS

We found Trans-Omics for Precision Medicine imputation to perform better in terms of accuracy in the lower ranges of minor allele frequency below 0.1. Our updated meta-analysis included UK Biobank study for ≈8 million common single-nucleotide polymorphisms (minor allele frequency >0.01) and replicated the association on Chr2 as the top association signal near TNS1. We identified an additional risk locus on Chr1 (SYT2) and 2 suggestive risk loci on chr8 (MSRA) and chr19 (FBXO46), all driven by common variants. Gene-based association using Multi-marker Analysis of GenoMic Annotation revealed 6 risk genes for MVP with pronounced expression levels in cardiovascular tissues, especially the heart and globally part of enriched GO terms related to cardiac development.

CONCLUSIONS

We report an updated meta-analysis genome-wide association study for MVP using dense imputation coverage and an improved case-control sample. We describe several loci and genes with MVP spanning biological mechanisms highly relevant to MVP, especially during valve and heart development.

Proteins Associated with Risk of Kidney Function Decline in the General Population

BACKGROUND

Proteomic profiling may allow identification of plasma proteins that associate with subsequent changesin kidney function, elucidating biologic processes underlying the development and progression of CKD.

METHODS

We quantified the association between 4877 plasma proteins and a composite outcome of ESKD or decline in eGFR by ≥50% among 9406 participants in the Atherosclerosis Risk in Communities (ARIC) Study (visit 3; mean age, 60 years) who were followed for a median of 14.4 years. We performed separate analyses for these proteins in a subset of 4378 participants (visit 5), who were followed at a later time point, for a median of 4.4 years. For validation, we evaluated proteins with significant associations (false discovery rate <5%) in both time periods in 3249 participants in the Chronic Renal Insufficiency Cohort (CRIC) and 703 participants in the African American Study of Kidney Disease and Hypertension (AASK). We also compared the genetic determinants of protein levels with those from a meta-analysis genome-wide association study of eGFR.

RESULTS

In models adjusted for multiple covariates, including baseline eGFR and albuminuria, we identified 13 distinct proteins that were significantly associated with the composite end point in both time periods, including TNF receptor superfamily members 1A and 1B, trefoil factor 3, and β-trace protein. Of these proteins, 12 were also significantly associated in CRIC, and nine were significantly associated in AASK. Higher levels of each protein associated with higher risk of 50% eGFR decline or ESKD. We found genetic evidence for a causal role for one protein, lectin mannose-binding 2 protein (LMAN2).

CONCLUSIONS

Large-scale proteomic analysis identified both known and novel proteomic risk factors for eGFR decline.

Polygenic risk scores predict diabetes complications and their response to intensive blood pressure and glucose control

AIMS/HYPOTHESIS

Type 2 diabetes increases the risk of cardiovascular and renal complications, but early risk prediction could lead to timely intervention and better outcomes. Genetic information can be used to enable early detection of risk.

METHODS

We developed a multi-polygenic risk score (multiPRS) that combines ten weighted PRSs (10 wPRS) composed of 598 SNPs associated with main risk factors and outcomes of type 2 diabetes, derived from summary statistics data of genome-wide association studies. The 10 wPRS, first principal component of ethnicity, sex, age at onset and diabetes duration were included into one logistic regression model to predict micro- and macrovascular outcomes in 4098 participants in the ADVANCE study and 17,604 individuals with type 2 diabetes in the UK Biobank study.

RESULTS

The model showed a similar predictive performance for cardiovascular and renal complications in different cohorts. It identified the top 30% of ADVANCE participants with a mean of 3.1-fold increased risk of major micro- and macrovascular events (p = 6.3 × 10^-21 and p = 9.6 × 10^-31, respectively) and a 4.4-fold (p = 6.8 × 10^-33) higher risk of cardiovascular death. While in ADVANCE overall, combined intensive blood pressure and glucose control decreased cardiovascular death by 24%, the model identified a high-risk group in whom it decreased the mortality rate by 47%, and a low-risk group in whom it had no discernible effect. High-risk individuals had the greatest absolute risk reduction with a number needed to treat of 12 to prevent one cardiovascular death over 5 years.

CONCLUSIONS/INTERPRETATION

This novel multiPRS model stratified individuals with type 2 diabetes according to risk of complications and helped to target earlier those who would receive greater benefit from intensive therapy.

Atrial fibrillation and kidney function: a bidirectional Mendelian randomization study

AIMS

The aim of this study was to investigate the causal effects between atrial fibrillation (AF) and kidney function.

METHODS AND RESULTS

We performed a bidirectional summary-level Mendelian randomization (MR) analysis implementing the results from a large-scale genome-wide association study for estimated glomerular filtration rate (eGFR) by the CKDGen (N = 765 348) and AF (N = 588 190) to identify genetic instruments. The inverse variance weighted method was the main MR method used. For replication, an allele score-based MR was performed by individual-level data within a UK Biobank cohort of white British ancestry individuals (N = 337 138). A genetic predisposition to AF was significantly associated with decreased eGFR [for log-eGFR, beta -0.003 (standard error, 0.0005), P < 0.001] and increased risk of chronic kidney disease [beta 0.059 (0.0126), P < 0.001]. The significance remained in MR sensitivity analyses and the causal estimates were consistent when we limited the analysis to individuals of European ancestry. Genetically predicted eGFR did not show a significant association with the risk of AF [beta -0.366 (0.275), P = 0.183]. The results were similar in allele score-based MR, as allele score for AF was significantly associated with reduced eGFR [for continuous eGFR, beta -0.079 (0.021), P < 0.001], but allele score for eGFR did not show a significant association with risk of AF [beta -0.005 (0.008), P = 0.530].

CONCLUSIONS

Our study supports that AF is a causal risk factor for kidney function impairment. However, an effect of kidney function on AF was not identified in this study.

A single genetic locus controls both expression of DPEP1/CHMP1A and kidney disease development via ferroptosis

Genome-wide association studies (GWAS) have identified loci for kidney disease, but the causal variants, genes, and pathways remain unknown. Here we identify two kidney disease genes Dipeptidase 1 (DPEP1) and Charged Multivesicular Body Protein 1 A (CHMP1A) via the triangulation of kidney function GWAS, human kidney expression, and methylation quantitative trait loci. Using single-cell chromatin accessibility and genome editing, we fine map the region that controls the expression of both genes. Mouse genetic models demonstrate the causal roles of both genes in kidney disease. Cellular studies indicate that both Dpep1 and Chmp1a are important regulators of a single pathway, ferroptosis and lead to kidney disease development via altering cellular iron trafficking.

Spatial transcriptional mapping of the human nephrogenic program

Congenital abnormalities of the kidney and urinary tract are among the most common birth defects, affecting 3% of newborns. The human kidney forms around a million nephrons from a pool of nephron progenitors over a 30-week period of development. To establish a framework for human nephrogenesis, we spatially resolved a stereotypical process by which equipotent nephron progenitors generate a nephron anlage, then applied data-driven approaches to construct three-dimensional protein maps on anatomical models of the nephrogenic program. Single-cell RNA sequencing identified progenitor states, which were spatially mapped to the nephron anatomy, enabling the generation of functional gene networks predicting interactions within and between nephron cell types. Network mining identified known developmental disease genes and predicted targets of interest. The spatially resolved nephrogenic program made available through the Human Nephrogenesis Atlas (https://sckidney.flatironinstitute.org/) will facilitate an understanding of kidney development and disease and enhance efforts to generate new kidney structures.

Comparison of mouse models reveals a molecular distinction between psychotic illness in PWS and schizophrenia

Prader-Willi Syndrome (PWS) is a neurodevelopmental disorder caused by mutations affecting paternal chromosome 15q11-q13, and characterized by hypotonia, hyperphagia, impaired cognition, and behavioural problems. Psychotic illness is a challenging problem for individuals with PWS and has different rates of prevalence in distinct PWS genotypes. Previously, we demonstrated behavioural and cognitive endophenotypes of relevance to psychiatric illness in a mouse model for one of the associated PWS genotypes, namely PWS-IC, in which deletion of the imprinting centre leads to loss of paternally imprinted gene expression and over-expression of Ube3a. Here we examine the broader gene expression changes that are specific to the psychiatric endophenotypes seen in this model. To do this we compared the brain transcriptomic profile of the PWS-IC mouse to the PWS-cr model that carries a deletion of the PWS minimal critical interval spanning the snoRNA Snord116 and Ipw. Firstly, we examined the same behavioural and cognitive endophenotypes of relevance to psychiatric illness in the PWS-cr mice. Unlike the PWS-IC mice, PWS-cr exhibit no differences in locomotor activity, sensory-motor gating, and attention. RNA-seq analysis of neonatal whole brain tissue revealed a greater number of transcriptional changes between PWS-IC and wild-type littermates than between PWS-cr and wild-type littermates. Moreover, the differentially expressed genes in the PWS-IC brain were enriched for GWAS variants of episodes of psychotic illness but, interestingly, not schizophrenia. These data illustrate the molecular pathways that may underpin psychotic illness in PWS and have implications for potential therapeutic interventions.

Relationship between birth weight and chronic kidney disease: evidence from systematics review and two-sample Mendelian randomization analysis

Observational studies showed an inverse association between birth weight and chronic kidney disease (CKD) in adulthood existed. However, whether such an association is causal remains fully elusive. Moreover, none of prior studies distinguished the direct fetal effect from the indirect maternal effect. Herein, we aimed to investigate the causal relationship between birth weight and CKD and to understand the relative fetal and maternal contributions. Meta-analysis (n = ~22 million) showed that low birth weight led to ~83% (95% confidence interval [CI] 37-146%) higher risk of CKD in late life. With summary statistics from large scale GWASs (n = ~300 000 for birth weight and ~481 000 for CKD), linkage disequilibrium score regression demonstrated birth weight had a negative maternal, but not fetal, genetic correlation with CKD and several other kidney-function related phenotypes. Furthermore, with multiple instruments of birth weight, Mendelian randomization showed there existed a negative fetal casual association (OR = 1.10, 95% CI 1.01-1.16) between birth weight and CKD; a negative but non-significant maternal casual association (OR = 1.09, 95% CI 0.98-1.21) was also identified. Those associations were robust against various sensitivity analyses. However, no maternal/fetal casual effects of birth weight were significant for other kidney-function related phenotypes. Overall, our study confirmed the inverse association between birth weight and CKD observed in prior studies, and further revealed the shared maternal genetic foundation between low birth weight and CKD, and the direct fetal and indirect maternal causal effects of birth weight may commonly drive this negative relationship.

Silencing of ceramide synthase 2 in hepatocytes modulates plasma ceramide biomarkers predictive of cardiovascular death

Emerging clinical data show that three ceramide molecules, Cer d18:1/16:0, Cer d18:1/24:1, and Cer d18:1/24:0, are biomarkers of a fatal outcome in patients with cardiovascular disease. This finding raises basic questions about their metabolic origin, their contribution to disease pathogenesis, and the utility of targeting the underlying enzymatic machinery for treatment of cardiometabolic disorders. Here, we outline the development of a potent N-acetylgalactosamine-conjugated antisense oligonucleotide engineered to silence ceramide synthase 2 specifically in hepatocytes in vivo. We demonstrate that this compound reduces the ceramide synthase 2 mRNA level and that this translates into efficient lowering of protein expression and activity as well as Cer d18:1/24:1 and Cer d18:1/24:0 levels in liver. Intriguingly, we discover that the hepatocyte-specific antisense oligonucleotide also triggers a parallel modulation of blood plasma ceramides, revealing that the biomarkers predictive of cardiovascular death are governed by ceramide biosynthesis in hepatocytes. Our work showcases a generic therapeutic framework for targeting components of the ceramide enzymatic machinery to disentangle their roles in disease causality and to explore their utility for treatment of cardiometabolic disorders.

Birth weight is positively associated with adult osteoporosis risk: observational and Mendelian randomization studies

The relationship between birth weight and osteoporosis was inconsistent in previous observational studies. Therefore, we performed a systematic evaluation to determine the inconsistent relationship and further make causal inference based on the UK Biobank datasets (~500,000 individuals) and individual/summary-level genetic datasets. Observational analyses found consistent negative associations either between birth weight and estimated bone mineral density (eBMD) or between genetic risk score (GRS) of birth weight and eBMD in total subjects, and sex-stratified subgroups. Mediation analyses detected significant mediation effects of adult weight and height on associations between birth weight and eBMD. Birth weight was causally associated not only with three BMD phenotypes (eBMD, total body [TB]-BMD, and femoral neck [FN]-BMD) under two effect models (total and fetal effect), but also with the risk of fracture using different Mendelian randomization (MR) methods. Multivariable MR analyses detected the pleiotropic effects of some environmental factors (e.g., gestational duration, head circumference, hip circumference) on the associations between birth weight and BMD/fracture. Three BMD phenotypes (eBMD, TB-BMD, and FN-BMD) have significant mediation effects on the associations between birth weight and fracture by using a novel mediation MR analysis under the multivariable MR framework. This multistage systematic study found consistent causal associations between birth weight and osteoporosis risk, fetal origin of genetic effects underlying the associations, and several mediation factors on the detected associations. The results enhanced our understanding of the effects of fetal original phenotypes on outcomes in late adulthood and provided helpful clues for early prevention research on osteoporosis. © 2021 American Society for Bone and Mineral Research (ASBMR).

Role of the CX3CL1-CX3CR1 axis in renal disease

Excessive infiltration of immune cells into the kidney is a key feature of acute and chronic kidney diseases. The family of chemokines comprises key drivers of this process. Fractalkine [chemokine (C-X3-C motif) ligand 1 (CX3CL1)] is one of two unique chemokines synthesized as a transmembrane protein that undergoes proteolytic cleavage to generate a soluble species. Through interacting with its cognate receptor, chemokine (C-X3-C motif) receptor 1 (CX3CR1), CX3CL1 was originally shown to act as a conventional chemoattractant in the soluble form and as an adhesion molecule in the transmembrane form. Since then, other functions of CX3CL1 beyond leukocyte recruitment have been described, including cell survival, immunosurveillance, and cell-mediated cytotoxicity. This review summarizes diverse roles of CX3CL1 in kidney disease and potential uses as a therapeutic target and novel biomarker. As the CX3CL1-CX3CR1 axis has been shown to contribute to both detrimental and protective effects in various kidney diseases, a thorough understanding of how the expression and function of CX3CL1 are regulated is needed to unlock its therapeutic potential.

A Mendelian randomization study found causal linkage between telomere attrition and chronic kidney disease

Chronic kidney disease (CKD) is highly prevalent in the elderly population. However, it is rarely investigated whether kidney function is causally linked to biological aging itself. In this Mendelian randomization study, genetic instruments for telomere attrition were applied to a CKDGen genome wide association study results for 41,395 cases of CKD among 480,698 individuals as summary-level Mendelian randomization. A replicative analysis was performed by polygenic score analysis using independent United Kingdom Biobank data for 8,118 cases of CKD among 321,024 white individuals of British ancestry. Reverse-direction Mendelian randomization analysis was performed utilizing genetic instruments for log-estimated glomerular filtration rate change with Z-standardized telomere length outcome data for 326,075 participants in the UK Biobank. Genetic predisposition toward telomere attrition (one Z score decrease in length) was found to be a causative factor for a higher CKD risk [Odds Ratio 1.20 (95% confidence interval 1.08‒1.33)], as supported by pleiotropy-robust Mendelian randomization sensitivity analyses implemented using the CKDGen data. Based on United Kingdom Biobank data, the polygenic score for telomere attrition was significantly associated with a higher risk of CKD [1.20 (1.04‒1.39)]. In reverse-direction Mendelian randomization, the genetically predicted kidney function decrease was significantly associated with a higher degree of telomere attrition [beta 0.039 (0.009‒0.069)]. Thus, our study supports the causal linkage between telomere attrition and kidney function impairment.

Causal linkage between adult height and kidney function: An integrated population-scale observational analysis and Mendelian randomization study

As adult height is linked to various health outcomes, further investigation of its causal effects on kidney function later in life is warranted. This study involved a cross-sectional observational analysis and summary-level Mendelian randomization (MR) analysis. First, the observational association between height and estimated GFR determined by creatinine (eGFRcreatinine) or cystatin C (eGFRcystatinC) was investigated in 467,182 individuals aged 40-69 using UK Biobank. Second, the genetic instrument for adult height, as reported by the GIANT consortium, was implemented, and summary-level MR of eGFRcreatinine and CKDcreatinine in a CKDGen genome-wide association study was performed (N = 567,460), with multivariable MR being adjusted for the effects of genetic predisposition on body mass index. To replicate the findings, additional two-sample MR using the summary statistics of eGFRcystatinC and CKDcystatinC in UK Biobank was performed (N = 321,405). In observational analysis, adult height was inversely associated with both eGFRcreatinine (per 1 SD, adjusted beta -1.039, standard error 0.129, P < 0.001) and eGFRcystatinC (adjusted beta -1.769, standard error 0.161, P < 0.001) in a multivariable model adjusted for clinicodemographic, anthropometric, metabolic, and social factors. Moreover, multivariable summary-level MR showed that a taller genetically predicted adult height was causally linked to a lower log-eGFRcreatinine (adjusted beta -0.007, standard error 0.001, P < 0.001) and a higher risk of CKDcreatinine (adjusted beta 0.083, standard error 0.019, P < 0.001). Other pleiotropy-robust sensitivity MR analysis results supported the findings. In addition, similar results were obtained by two-sample MR of eGFRcystatinC (adjusted beta -1.303, standard error 0.140, P < 0.001) and CKDcystatinC (adjusted beta 0.153, standard error 0.025, P < 0.001) in UK Biobank. In conclusion, the results of this study suggest that a taller adult height is causally linked to worse kidney function in middle-aged to elderly individuals, independent of the effect of body mass index.

Genetically Predicted Insomnia in Relation to 14 Cardiovascular Conditions and 17 Cardiometabolic Risk Factors: A Mendelian Randomization Study

Background

This Mendelian randomization study aims to investigate causal associations between genetically predicted insomnia and 14 cardiovascular diseases (CVDs) as well as the potential mediator role of 17 cardiometabolic risk factors.

Methods and Results

Using genetic association estimates from large genome‐wide association studies and UK Biobank, we performed a 2‐sample Mendelian randomization analysis to estimate the associations of insomnia with 14 CVD conditions in the primary analysis. Then mediation analysis was conducted to explore the potential mediator role of 17 cardiometabolic risk factors using a network Mendelian randomization design. After correcting for multiple testing, genetically predicted insomnia was consistent significantly positively associated with 9 of 14 CVDs, those odds ratios ranged from 1.13 (95% CI, 1.08–1.18) for atrial fibrillation to 1.24 (95% CI, 1.16–1.32) for heart failure. Moreover, genetically predicted insomnia was consistently associated with higher body mass index, triglycerides, and lower high‐density lipoprotein cholesterol, each of which may act as a mediator in the causal pathway from insomnia to several CVD outcomes. Additionally, we found very little evidence to support a causal link between insomnia with abdominal aortic aneurysm, thoracic aortic aneurysm, total cholesterol, low‐density lipoprotein cholesterol, glycemic traits, renal function, and heart rate increase during exercise. Finally, we found no evidence of causal associations of genetically predicted body mass index, high‐density lipoprotein cholesterol, or triglycerides on insomnia.

Conclusions

This study provides evidence that insomnia is associated with 9 of 14 CVD outcomes, some of which may be partially mediated by 1 or more of higher body mass index, triglycerides, and lower high‐density lipoprotein cholesterol.

Discovery and fine-mapping of kidney function loci in first genome-wide association study in Africans

Genome-wide association studies (GWAS) of kidney function have uncovered hundreds of loci, primarily in populations of European ancestry. We have undertaken the first continental African GWAS of estimated glomerular filtration rate (eGFR), a measure of kidney function used to define chronic kidney disease (CKD). We conducted GWAS of eGFR in 3288 East Africans from the Uganda General Population Cohort (GPC) and replicated in 8224 African Americans from the Women's Health Initiative. Loci attaining genome-wide significant evidence for association (P < 5 × 10-8) were followed up with Bayesian fine-mapping to localize potential causal variants. The predictive power of a genetic risk score (GRS) constructed from previously reported trans-ancestry eGFR lead single nucleotide polymorphism (SNPs) was evaluated in the Uganda GPC. We identified and validated two eGFR loci. At the glycine amidinotransferase (GATM) locus, the association signal (lead SNP rs2433603, P = 1.0 × 10-8) in the Uganda GPC GWAS was distinct from previously reported signals at this locus. At the haemoglobin beta (HBB) locus, the association signal (lead SNP rs141845179, P = 3.0 × 10-8) has been previously reported. The lead SNP at the HBB locus accounted for 88% of the posterior probability of causality after fine-mapping, but did not colocalise with kidney expression quantitative trait loci. The trans-ancestry GRS of eGFR was not significantly predictive into the Ugandan population. In the first GWAS of eGFR in continental Africa, we validated two previously reported loci at GATM and HBB. At the GATM locus, the association signal was distinct from that previously reported. These results demonstrate the value of performing GWAS in continental Africans, providing a rich genomic resource to larger consortia for further discovery and fine-mapping. The study emphasizes that additional large-scale efforts in Africa are warranted to gain further insight into the genetic architecture of CKD.

Genetically Predicted Fibroblast Growth Factor 23 and Major Cardiovascular Diseases, Their Risk Factors, Kidney Function, and Longevity: A Two-Sample Mendelian Randomization Study

Introduction

Fibroblast growth factor 23 (FGF23), a potential biomarker for kidney function, is related to cardiovascular disease (CVD) and diabetes, although it is unclear whether the relation is causal. This study evaluated the associations of genetically predicted FGF23 with major CVDs, their risk factors, kidney function, and longevity using Mendelian randomization (MR).

Methods

This is a two-sample MR study using summary statistics from large genome-wide association studies. Primary outcomes included coronary artery disease (CAD), myocardial infarction, heart failure, and atrial fibrillation. Secondary outcomes included cardiovascular risk factors, kidney function, and longevity. We used four single-nucleotide polymorphisms (SNPs) predicting FGF23, excluding rs2769071 in the ABO gene, which likely violates the MR exclusion-restriction assumption. We used inverse-variance weighted (IVW) as the primary statistical method to assess associations of FGF23 with the outcomes. Sensitivity analyses included weighted median (WM) and MR-Egger. We repeated the analyses including all five SNPs. Last, we validated the positive findings from the main analyses in a smaller study, i.e., FinnGen.

Results

Using IVW, genetically predicted higher FGF23 was inversely associated with risk of CAD [odds ratio (OR): 0.69 per logtransformed FGF23 (pg/ml) increase, 95% confidence interval (CI): 0.52–0.91] and type 2 diabetes mellitus (T2DM) (OR: 0.70, 95% CI: 0.52–0.96), but not with the other outcomes. The WM and MR-Egger estimates were directionally consistent.

Conclusion

This study suggests that genetically predicted higher FGF23 may be protective against CAD and T2DM. Future studies should explore the underlying mechanisms related to the potential protective effect of FGF23. FGF23 was unlikely a cause of poorer renal function.

Distinct Mitochondrial Pathologies Caused by Mutations of the Proximal Tubular Enzymes EHHADH and GATM

The mitochondria of the proximal tubule are essential for providing energy in this nephron segment, whose ATP generation is almost exclusively oxygen dependent. In addition, mitochondria are involved in a variety of metabolic processes and complex signaling networks. Proximal tubular mitochondrial dysfunction can therefore affect renal function in very different ways. Two autosomal dominantly inherited forms of renal Fanconi syndrome illustrate how multifaceted mitochondrial pathology can be: Mutation of EHHADH, an enzyme in fatty acid metabolism, results in decreased ATP synthesis and a consecutive transport defect. In contrast, mutations of GATM, an enzyme in the creatine biosynthetic pathway, leave ATP synthesis unaffected but do lead to mitochondrial protein aggregates, inflammasome activation, and renal fibrosis with progressive renal failure. In this review article, the distinct pathophysiological mechanisms of these two diseases are presented, which are examples of the spectrum of proximal tubular mitochondrial diseases.

Chronic Kidney Disease Cohort Studies: A Guide to Metabolome Analyses

Kidney diseases still pose one of the biggest challenges for global health, and their heterogeneity and often high comorbidity load seriously hinders the unraveling of their underlying pathomechanisms and the delivery of optimal patient care. Metabolomics, the quantitative study of small organic compounds, called metabolites, in a biological specimen, is gaining more and more importance in nephrology research. Conducting a metabolomics study in human kidney disease cohorts, however, requires thorough knowledge about the key workflow steps: study planning, sample collection, metabolomics data acquisition and preprocessing, statistical/bioinformatics data analysis, and results interpretation within a biomedical context. This review provides a guide for future metabolomics studies in human kidney disease cohorts. We will offer an overview of important a priori considerations for metabolomics cohort studies, available analytical as well as statistical/bioinformatics data analysis techniques, and subsequent interpretation of metabolic findings. We will further point out potential research questions for metabolomics studies in the context of kidney diseases and summarize the main results and data availability of important studies already conducted in this field.

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

Genes underneath signals from genome-wide association studies (GWAS) for kidney function are promising targets for functional studies, but prioritizing variants and genes is challenging. By GWAS meta-analysis for creatinine-based estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics Consortium and UK Biobank (n = 1,201,909), we expand the number of eGFRcrea loci (424 loci, 201 novel; 9.8% eGFRcrea variance explained by 634 independent signal variants). Our increased sample size in fine-mapping (n = 1,004,040, European) more than doubles the number of signals with resolved fine-mapping (99% credible sets down to 1 variant for 44 signals, ≤5 variants for 138 signals). Cystatin-based eGFR and/or blood urea nitrogen association support 348 loci (n = 460,826 and 852,678, respectively). Our customizable tool for Gene PrioritiSation reveals 23 compelling genes including mechanistic insights and enables navigation through genes and variants likely relevant for kidney function in human to help select targets for experimental follow-up.

Characterizing a Common CERS2 Polymorphism in a Mouse Model of Metabolic Disease and in Subjects from the Utah CAD Study

CONTEXT

Genome-wide association studies have identified associations between a common single nucleotide polymorphism (SNP; rs267738) in CERS2, a gene that encodes a (dihydro)ceramide synthase that is involved in the biosynthesis of very-long-chain sphingolipids (eg, C20-C26) and indices of metabolic dysfunction (eg, impaired glucose homeostasis). However, the biological consequences of this mutation on enzyme activity and its causal roles in metabolic disease are unresolved.

OBJECTIVE

The studies described herein aimed to characterize the effects of rs267738 on CERS2 enzyme activity, sphingolipid profiles, and metabolic outcomes.

DESIGN

We performed in-depth lipidomic and metabolic characterization of a novel CRISPR knock-in mouse modeling the rs267738 variant. In parallel, we conducted mass spectrometry-based, targeted lipidomics on 567 serum samples collected through the Utah Coronary Artery Disease study, which included 185 patients harboring 1 (n = 163) or both (n = 22) rs267738 alleles.

RESULTS

In-silico analysis of the amino acid substitution within CERS2 caused by the rs267738 mutation suggested that rs267738 is deleterious for enzyme function. Homozygous knock-in mice had reduced liver CERS2 activity and enhanced diet-induced glucose intolerance and hepatic steatosis. However, human serum sphingolipids and a ceramide-based cardiac event risk test 1 score of cardiovascular disease were not significantly affected by rs267738 allele count.

CONCLUSIONS

The rs267738 SNP leads to a partial loss-of-function of CERS2, which worsened metabolic parameters in knock-in mice. However, rs267738 was insufficient to effect changes in serum sphingolipid profiles in subjects from the Utah Coronary Artery Disease Study.

Sclerostin Downregulation Globally by Naturally Occurring Genetic Variants, or Locally in Atherosclerotic Plaques, Does Not Associate With Cardiovascular Events in Humans

Inhibition of sclerostin increases bone formation and decreases bone resorption, leading to increased bone mass, bone mineral density, and bone strength and reduced fracture risk. In a clinical study of the sclerostin antibody romosozumab versus alendronate in postmenopausal women (ARCH), an imbalance in adjudicated serious cardiovascular (CV) adverse events driven by an increase in myocardial infarction (MI) and stroke was observed. To explore whether there was a potential mechanistic plausibility that sclerostin expression, or its inhibition, in atherosclerotic (AS) plaques may have contributed to this imbalance, sclerostin was immunostained in human plaques to determine whether it was detected in regions relevant to plaque stability in 94 carotid and 50 femoral AS plaques surgically collected from older female patients (mean age 69.6 ± 10.4 years). Sclerostin staining was absent in most plaques (67%), and when detected, it was of reduced intensity compared with normal aorta and was located in deeper regions of the plaque/wall but was not observed in areas considered relevant to plaque stability (fibrous cap and endothelium). Additionally, genetic variants associated with lifelong reduced sclerostin expression were explored for associations with phenotypes including those related to bone physiology and CV risk factors/events in a population-based phenomewide association study (PheWAS). Natural genetic modulation of sclerostin by variants with a significant positive effect on bone physiology showed no association with lifetime risk of MI or stroke. These data do not support a causal association between the presence of sclerostin, or its inhibition, in the vasculature and increased risk of serious cardiovascular events. © 2021 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Plasma Proteomics of Renal Function: A Transethnic Meta-Analysis and Mendelian Randomization Study

BACKGROUND

Studies on the relationship between renal function and the human plasma proteome have identified several potential biomarkers. However, investigations have been conducted largely in European populations, and causality of the associations between plasma proteins and kidney function has never been addressed.

METHODS

A cross-sectional study of 993 plasma proteins among 2882 participants in four studies of European and admixed ancestries (KORA, INTERVAL, HUNT, QMDiab) identified transethnic associations between eGFR/CKD and proteomic biomarkers. For the replicated associations, two-sample bidirectional Mendelian randomization (MR) was used to investigate potential causal relationships. Publicly available datasets and transcriptomic data from independent studies were used to examine the association between gene expression in kidney tissue and eGFR.

RESULTS

In total, 57 plasma proteins were associated with eGFR, including one novel protein. Of these, 23 were additionally associated with CKD. The strongest inferred causal effect was the positive effect of eGFR on testican-2, in line with the known biological role of this protein and the expression of its protein-coding gene (SPOCK2) in renal tissue. We also observed suggestive evidence of an effect of melanoma inhibitory activity (MIA), carbonic anhydrase III, and cystatin-M on eGFR.

CONCLUSIONS

In a discovery-replication setting, we identified 57 proteins transethnically associated with eGFR. The revealed causal relationships are an important stepping stone in establishing testican-2 as a clinically relevant physiological marker of kidney disease progression, and point to additional proteins warranting further investigation.

The causal effects of serum lipids and apolipoproteins on kidney function: multivariable and bidirectional Mendelian-randomization analyses

Background

The causal nature of the observed associations between serum lipids and apolipoproteins and kidney function are unclear.

Methods

Using two-sample and multivariable Mendelian randomization (MR), we examined the causal effects of serum lipids and apolipoproteins on kidney function, indicated by the glomerular-filtration rate estimated using creatinine (eGFRcrea) or cystatin C (eGFRcys) and the urinary albumin-to-creatinine ratio (UACR). We obtained lipid- and apolipoprotein-associated genetic variants from the Global Lipids Genetics Consortium (n = 331 368) and UK Biobank (n = 441 016), respectively, and kidney-function markers from the Trøndelag Health Study (HUNT; n = 69 736) and UK Biobank (n = 464 207). The reverse causal direction was examined using variants associated with kidney-function markers selected from recent genome-wide association studies.

Results

There were no strong associations between genetically predicted lipid and apolipoprotein levels with kidney-function markers. Some, but inconsistent, evidence suggested a weak association of higher genetically predicted atherogenic lipid levels [indicated by low-density lipoprotein cholesterol (LDL-C), triglycerides and apolipoprotein B] with increased eGFR and UACR. For high-density lipoprotein cholesterol (HDL-C), results differed between eGFRcrea and eGFRcys, but neither analysis suggested substantial effects. We found no clear evidence of a reverse causal effect of eGFR on lipid or apolipoprotein traits, but higher UACR was associated with higher LDL-C, triglyceride and apolipoprotein B levels.

Conclusion

Our MR estimates suggest that serum lipid and apolipoprotein levels do not cause substantial changes in kidney function. A possible weak effect of higher atherogenic lipids on increased eGFR and UACR warrants further investigation. Processes leading to higher UACR may lead to more atherogenic lipid levels.

Precision medicine approaches for diabetic kidney disease: opportunities and challenges

The prevalence of end-stage kidney disease (ESKD) continuously increases worldwide. The increasing prevalence parallels the growth in the number of people with diabetes, which is the leading cause of ESKD. Early diagnosis of chronic kidney disease (CKD) in patients with diabetes and appropriate intervention is important to delay the progression of kidney function decline and prevent ESKD. Rate of CKD progression and response to treatment varies among patients with diabetes, highlighting the need to tailor individual treatment. In this review, we describe recent advances and areas for future studies with respect to precision medicine in diabetic kidney disease (DKD). DKD is a multi-factorial disease that is subject in part to genetic heritability, but is also influenced by various exogenous mediators, such as environmental or dietary factors. Genetic testing so far has limited utility to facilitate early diagnosis, classify progression or evaluate response to therapy. Various biomarker-based approaches are currently explored to identify patients at high risk of ESKD and to facilitate decision-making for targeted therapy. These studies have led to discovery and validation of a couple of inflammatory proteins such as circulating tumour necrosis factor receptors, which are strong predictors of kidney disease progression. Moreover, risk and drug-response scores based on multiple biomarkers are developed to predict kidney disease progression and long-term drug efficacy. These findings, if implemented in clinical practice, will pave the way to move from a one-size-fits-all to a one-fit-for-everyone approach.

Genetic architecture of 11 organ traits derived from abdominal MRI using deep learning

Cardiometabolic diseases are an increasing global health burden. While socioeconomic, environmental, behavioural, and genetic risk factors have been identified, a better understanding of the underlying mechanisms is required to develop more effective interventions. Magnetic resonance imaging (MRI) has been used to assess organ health, but biobank-scale studies are still in their infancy. Using over 38,000 abdominal MRI scans in the UK Biobank, we used deep learning to quantify volume, fat, and iron in seven organs and tissues, and demonstrate that imaging-derived phenotypes reflect health status. We show that these traits have a substantial heritable component (8-44%) and identify 93 independent genome-wide significant associations, including four associations with liver traits that have not previously been reported. Our work demonstrates the tractability of deep learning to systematically quantify health parameters from high-throughput MRI across a range of organs and tissues, and use the largest-ever study of its kind to generate new insights into the genetic architecture of these traits.

Causal Inference Between Chronic Periodontitis and Chronic Kidney Disease: A Bidirectional Mendelian Randomization Analysis in a European Population

Background

Previous epidemiological studies have shown significant associations between chronic periodontitis (CP) and chronic kidney disease (CKD), but the causal relationship remains uncertain. Aiming to examine the causal relationship between these two diseases, we conducted a bidirectional two-sample Mendelian randomization (MR) analysis with multiple MR methods.

Methods

For the casual effect of CP on CKD, we selected seven single-nucleotide polymorphisms (SNPs) specific to CP as genetic instrumental variables from the genome-wide association studies (GWAS) in the GLIDE Consortium. The summary statistics of complementary kidney function measures, i.e., estimated glomerular filtration rate (eGFR) and blood urea nitrogen (BUN), were derived from the GWAS in the CKDGen Consortium. For the reversed causal inference, six SNPs associated with eGFR and nine with BUN from the CKDGen Consortium were included and the summary statistics were extracted from the CLIDE Consortium.

Results

No significant causal association between genetically determined CP and eGFR or BUN was found (all p > 0.05). Based on the conventional inverse variance-weighted method, one of seven instrumental variables supported genetically predicted CP being associated with a higher risk of eGFR (estimate = 0.019, 95% CI: 0.012-0.026, p < 0.001).

Conclusion

Evidence from our bidirectional causal inference does not support a causal relation between CP and CKD risk and therefore suggests that associations reported by previous observational studies may represent confounding.

Interpreting type 1 diabetes risk with genetics and single-cell epigenomics

Genetic risk variants that have been identified in genome-wide association studies of complex diseases are primarily non-coding1. Translating these risk variants into mechanistic insights requires detailed maps of gene regulation in disease-relevant cell types2. Here we combined two approaches: a genome-wide association study of type 1 diabetes (T1D) using 520,580 samples, and the identification of candidate cis-regulatory elements (cCREs) in pancreas and peripheral blood mononuclear cells using single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq) of 131,554 nuclei. Risk variants for T1D were enriched in cCREs that were active in T cells and other cell types, including acinar and ductal cells of the exocrine pancreas. Risk variants at multiple T1D signals overlapped with exocrine-specific cCREs that were linked to genes with exocrine-specific expression. At the CFTR locus, the T1D risk variant rs7795896 mapped to a ductal-specific cCRE that regulated CFTR; the risk allele reduced transcription factor binding, enhancer activity and CFTR expression in ductal cells. These findings support a role for the exocrine pancreas in the pathogenesis of T1D and highlight the power of large-scale genome-wide association studies and single-cell epigenomics for understanding the cellular origins of complex disease.

Childhood risk factors for adulthood chronic kidney disease

Chronic kidney disease (CKD) is a major public health challenge, affecting as much as 8 to 18% of the world population. Identifying childhood risk factors for future CKD may help clinicians make early diagnoses and initiation of preventive interventions for CKD and its attendant comorbidities as well as monitoring for complications. The purpose of this review is to describe childhood risk factors that may predict development of overt kidney disease later in life. Currently, there are multiple childhood risk factors associated with future onset and progression of CKD. These risk factors can be grouped into five categories: genetic factors (e.g., monogenic or risk alleles), perinatal factors (e.g., low birth weight and prematurity), childhood kidney diseases (e.g., congenital anomalies, glomerular diseases, and renal cystic ciliopathies), childhood onset of chronic conditions (e.g., cancer, diabetes, hypertension, dyslipidemia, and obesity), and different lifestyle factors (e.g., physical activity, diet, and factors related to socioeconomic status). The available published information suggests that the lifelong risk for CKD can be attributed to multiple factors that appear already during childhood. However, results are conflicting on the effects of childhood physical activity, diet, and dyslipidemia on future renal function. On the other hand, there is consistent evidence to support follow-up of high-risk groups.

Vitamin D and COVID-19 susceptibility and severity in the COVID-19 Host Genetics Initiative: A Mendelian randomization study

BACKGROUND

Increased vitamin D levels, as reflected by 25-hydroxy vitamin D (25OHD) measurements, have been proposed to protect against COVID-19 based on in vitro, observational, and ecological studies. However, vitamin D levels are associated with many confounding variables, and thus associations described to date may not be causal. Vitamin D Mendelian randomization (MR) studies have provided results that are concordant with large-scale vitamin D randomized trials. Here, we used 2-sample MR to assess evidence supporting a causal effect of circulating 25OHD levels on COVID-19 susceptibility and severity.

METHODS AND FINDINGS

Genetic variants strongly associated with 25OHD levels in a genome-wide association study (GWAS) of 443,734 participants of European ancestry (including 401,460 from the UK Biobank) were used as instrumental variables. GWASs of COVID-19 susceptibility, hospitalization, and severe disease from the COVID-19 Host Genetics Initiative were used as outcome GWASs. These included up to 14,134 individuals with COVID-19, and up to 1,284,876 without COVID-19, from up to 11 countries. SARS-CoV-2 positivity was determined by laboratory testing or medical chart review. Population controls without COVID-19 were also included in the control groups for all outcomes, including hospitalization and severe disease. Analyses were restricted to individuals of European descent when possible. Using inverse-weighted MR, genetically increased 25OHD levels by 1 standard deviation on the logarithmic scale had no significant association with COVID-19 susceptibility (odds ratio [OR] = 0.95; 95% CI 0.84, 1.08; p = 0.44), hospitalization (OR = 1.09; 95% CI: 0.89, 1.33; p = 0.41), and severe disease (OR = 0.97; 95% CI: 0.77, 1.22; p = 0.77). We used an additional 6 meta-analytic methods, as well as conducting sensitivity analyses after removal of variants at risk of horizontal pleiotropy, and obtained similar results. These results may be limited by weak instrument bias in some analyses. Further, our results do not apply to individuals with vitamin D deficiency.

CONCLUSIONS

In this 2-sample MR study, we did not observe evidence to support an association between 25OHD levels and COVID-19 susceptibility, severity, or hospitalization. Hence, vitamin D supplementation as a means of protecting against worsened COVID-19 outcomes is not supported by genetic evidence. Other therapeutic or preventative avenues should be given higher priority for COVID-19 randomized controlled trials.

Causal Effects of Positive Affect, Life Satisfaction, Depressive Symptoms, and Neuroticism on Kidney Function: A Mendelian Randomization Study

BACKGROUND

Further investigation of the causal effects of psychologic wellbeing on kidney function is warranted.

METHODS

In this Mendelian randomization (MR) study, genetic instruments for positive affect, life satisfaction, depressive symptoms, and neuroticism were introduced from a previous genome-wide association study meta-analysis of European individuals. Summary-level MR was performed using the CKDGen data of European ancestry (n=567,460), and additional allele score-based MR was performed in the individual-level data of White British UK Biobank participants (n=321,024).

RESULTS

In summary-level MR with the CKDGen data, depressive symptoms were a significant causative factor for kidney function impairment (CKD OR, 1.45; 95% confidence interval, 1.07 to 1.96; eGFR change [%] beta -2.18; 95% confidence interval, -3.61 to -0.72) and pleiotropy-robust sensitivity analysis results supported the causal estimates. A genetic predisposition for positive affect was significantly associated with better kidney function (CKD OR, 0.69; 95% confidence interval, 0.52 to 0.91), eGFR change [%] beta 1.50; 95% confidence interval, 0.09 to 2.93) and sensitivity MR analysis results supported the finding for CKD outcome, but was nonsignificant for eGFR. Life satisfaction and neuroticism exposures showed nonsignificant causal estimates. In the UK Biobank with covariate-adjusted allele score MR analysis, allele scores for positive affect and life satisfaction were causally associated with reduced risk of CKD and higher eGFR. In contrast, neuroticism allele score was associated with increased risk of CKD and lower eGFR, and depressive symptoms allele score was associated with lower eGFR, but showed nonsignificant association with CKD.

CONCLUSIONS

Health care providers in the nephrology field should be aware of the causal linkage between psychologic wellbeing and kidney function.

Causal inference for heritable phenotypic risk factors using heterogeneous genetic instruments

Over a decade of genome-wide association studies (GWAS) have led to the finding of extreme polygenicity of complex traits. The phenomenon that "all genes affect every complex trait" complicates Mendelian Randomization (MR) studies, where natural genetic variations are used as instruments to infer the causal effect of heritable risk factors. We reexamine the assumptions of existing MR methods and show how they need to be clarified to allow for pervasive horizontal pleiotropy and heterogeneous effect sizes. We propose a comprehensive framework GRAPPLE to analyze the causal effect of target risk factors with heterogeneous genetic instruments and identify possible pleiotropic patterns from data. By using GWAS summary statistics, GRAPPLE can efficiently use both strong and weak genetic instruments, detect the existence of multiple pleiotropic pathways, determine the causal direction and perform multivariable MR to adjust for confounding risk factors. With GRAPPLE, we analyze the effect of blood lipids, body mass index, and systolic blood pressure on 25 disease outcomes, gaining new information on their causal relationships and potential pleiotropic pathways involved.

Polymorphism in the GATM Locus Associated with Dialysis-Independent Chronic Kidney Disease but Not Dialysis-Dependent Kidney Failure

The ten most statistically significant estimated glomerular filtration rate (eGFRcrea)-associated loci from genome-wide association studies (GWAs) are tested for associations with chronic kidney disease (CKD) in 208 patients, including dialysis-independent CKD and dialysis-dependent end-stage renal disease (kidney failure). The allele A of intergenic SNP rs2453533 (near GATM) is more frequent in dialysis-independent CKD patients (n = 135, adjusted p = 0.020) but not dialysis-dependent kidney failure patients (n = 73) compared to healthy controls (n = 309). The allele C of intronic SNP rs4293393 (UMOD) is more frequent in healthy controls (adjusted p = 0.042) than in CKD patients. The Allele T of intronic SNP rs9895661 (BCAS3) is associated with decreased eGFRcys (adjusted p = 0.001) and eGFRcrea (adjusted p = 0.017). Our results provide further evidence of a genetic difference between dialysis-dialysis-independent CKD and dialysis-dependent kidney failure, and add the GATM gene locus to the list of loci associated only with dialysis-independent CKD. GATM risk allele carriers in the dialysis-independent group may have a genetic susceptibility to higher creatinine production rather than increased serum creatinine due to kidney malfunction, and therefore, do not progress to dialysis-dependent kidney failure. When using eGFRcrea for CKD diagnosis, physicians might benefit from information about creatinine-increasing loci.

Causal effect of renal function on venous thromboembolism: a two-sample Mendelian randomization investigation

Whether renal function is causally associated with venous thromboembolism (VTE) is not yet fully elucidated. We conducted a two-sample Mendelian randomization (MR) study to determine the causal effect of renal function, measured as estimated glomerular filtration rate (eGFR), on VTE. Single-nucleotide polymorphisms associated with eGFR were selected as instrumental variables at the genome-wide significance level (p < 5 × 10⁻⁸) from a meta-analysis of 122 genome-wide association studies including up to 1,046,070 individuals. Summary-level data for VTE were obtained from the FinnGen consortium (6913 VTE cases and 169,986 non-cases) and UK Biobank study (4620 VTE cases and 356,574 non-cases). MR estimates were calculated using the random-effects inverse-variance weighted method and combined using fixed-effects meta-analysis. Genetically predicted decreased eGFR was significantly associated with an increased risk of VTE in both FinnGen and UK Biobank. For one-unit decrease in log-transformed eGFR, the odds ratios of VTE were 2.93 (95% confidence interval (CI) 1.25, 6.84) and 4.46 (95% CI 1.59, 12.5) when using data from FinnGen and UK Biobank, respectively. The combined odds ratio was 3.47 (95% CI 1.80, 6.68). Results were consistent in all sensitivity analyses and no horizontal pleiotropy was detected. This MR-study supported a casual role of impaired renal function in VTE.

Association between MANBA Gene Variants and Chronic Kidney Disease in a Korean Population

Chronic kidney disease (CKD), a damaged condition of the kidneys, is a global public health problem that can be caused by diabetes, hypertension, and other disorders. Recently, the MANBA gene was identified in CKD by integrating CKD-related variants and kidney expression quantitative trait loci (eQTL) data. This study evaluated the effects of MANBA gene variants on CKD and kidney function-related traits using a Korean cohort. We also analyzed the association of MANBA gene variants with kidney-related traits such as the estimated glomerular filtration rate (eGFR), and blood urea nitrogen (BUN), creatinine, and uric acid levels using linear regression analysis. As a result, 14 single nucleotide polymorphisms (SNPs) were replicated in CKD (p < 0.05), consistent with previous studies. Among them, rs4496586, which was the most significant for CKD and kidney function-related traits, was associated with a decreased CKD risk in participants with the homozygous minor allele (CC), increased eGFR, and decreased creatinine and uric acid concentrations. Furthermore, the association analysis between the rs4496586 genotype and MANBA gene expression in human tubules and glomeruli showed high MANBA gene expression in the minor allele carriers. In conclusion, this study demonstrated that MANBA gene variants were associated with CKD and kidney function-related traits in a Korean cohort.

A Genome-Wide Association Study for Hypertensive Kidney Disease in Korean Men

Hypertension is one of the major risk factors for chronic kidney disease (CKD), and the coexistence of hypertension and CKD increases morbidity and mortality. Although many genetic factors have been identified separately for hypertension and kidney disease, studies specifically focused on hypertensive kidney disease (HKD) have been rare. Therefore, this study aimed to identify loci or genes associated with HKD. A genome-wide association study (GWAS) was conducted using two Korean cohorts, the Health Examinee (HEXA) and Korean Association REsource (KARE). Consequently, 19 single nucleotide polymorphisms (SNPs) were found to be significantly associated with HKD in the discovery and replication phases (p < 5 × 10⁻⁸, p < 0.05, respectively). We further analyzed HKD-related traits such as the estimated glomerular filtration rate (eGFR), creatinine, blood urea nitrogen (BUN), systolic blood pressure (SBP) and diastolic blood pressure (DBP) at the 14q21.2 locus, which showed a strong linkage disequilibrium (LD). Expression quantitative trait loci (eQTL) analysis was also performed to determine whether HKD-related SNPs affect gene expression changes in glomerular and arterial tissues. The results suggested that the FANCM gene may affect the development of HKD through an integrated analysis of eQTL and GWAS and was the most significantly associated candidate gene. Taken together, this study indicated that the FANCM gene is involved in the pathogenesis of HKD. Additionally, our results will be useful in prioritizing other genes for further experiments.

Transcriptome-wide association analysis identifies DACH1 as a kidney disease risk gene that contributes to fibrosis

Genome-wide association studies (GWAS) for kidney function identified hundreds of risk regions; however, the causal variants, target genes, cell types, and disease mechanisms remain poorly understood. Here, we performed transcriptome-wide association studies (TWAS), summary Mendelian randomization, and MetaXcan to identify genes whose expression mediates the genotype effect on the phenotype. Our analyses identified Dachshund homolog 1 (DACH1), a cell-fate determination factor. GWAS risk variant was associated with lower DACH1 expression in human kidney tubules. Human and mouse kidney single-cell open chromatin data (snATAC-Seq) prioritized estimated glomerular filtration rate (eGFR) GWAS variants located on an intronic regulatory region in distal convoluted tubule cells. CRISPR-Cas9-mediated gene editing confirmed the role of risk variants in regulating DACH1 expression. Mice with tubule-specific Dach1 deletion developed more severe renal fibrosis both in folic acid and diabetic kidney injury models. Mice with tubule-specific Dach1 overexpression were protected from folic acid nephropathy. Single-cell RNA sequencing, chromatin immunoprecipitation, and functional analysis indicated that DACH1 controls the expression of cell cycle and myeloid chemotactic factors, contributing to macrophage infiltration and fibrosis development. In summary, integration of GWAS, TWAS, single-cell epigenome, expression analyses, gene editing, and functional validation in different mouse kidney disease models identified DACH1 as a kidney disease risk gene.

Assessment of significance of conditionally independent GWAS signals

MOTIVATION

Multiple independently associated SNPs within a linkage disequilibrium (LD) region are a common phenomenon. Conditional analysis has been successful in identifying secondary signals. While conditional association tests are limited to specific genomic regions, they are benchmarked with genome-wide scale criterion, a conservative strategy.

METHOD

Within the weighted hypothesis testing framework, we developed a "quasi-adaptive" method that uses the pairwise correlation (r2) and physical distance (d) from the index association to construct priority functions G = G(r2, d), which assign a SNP-specific α-threshold to each SNP. Family-wise error rate (FWER) and power of the approach were evaluated via simulations based on real GWAS data. We compared a series of different G-functions.

RESULTS

Simulations under the null hypothesis on 1100 primary SNPs confirmed appropriate empirical FWER for all G-functions. A G-function with optimal r2 = 0.3 between index and secondary SNP which down-weighted SNPs at higher distance step-wise-strong and gave more emphasis on d than on r2 had overall best power. It also gave the best results in application to the real data sets. As a proof of concept, "quasi-adaptive" method was applied toGWAS on free thyroxine (FT4), inflammatory bowel disease (IBD), and human height. Application of the algorithm revealed 5 secondary signals in our example GWAS on FT4, 5 secondary signals in case of the IBD, and 19 secondary signals on human height, that would have gone undetected with the established genome-wide threshold (α = 5 ×10-8).

AVAILABILITY

https://github.com/sghasemi64/Secondary-Signal.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.