Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies

Plasma metals, genetic risk, and rapid kidney function decline among type 2 diabetes

BACKGROUND

Rapid kidney function decline (RKFD) is a main clinical feature of early chronic kidney disease (CKD) in type 2 diabetes (T2D). Environmental and genetic factors influencing RKFD remain inadequately elucidated.

OBJECTIVES

This study aimed to examine the associations of metals with RKFD among T2D and to further investigate the effect of metal mixtures on RKFD with the modifying effect of genetic susceptibility.

METHODS

This study included 2209 people with T2D (1942 had genotyping data) free of CKD at baseline from the Dongfeng-Tongji cohort. We used inductively coupled plasma-mass spectrometry (ICP-MS) to measure 23 metals in baseline plasma. Using elastic net (ENET), multivariate logistic regression, and Bayesian kernel machine regression (BKMR) model, we examined independent associations of multiple metals with RKFD. We calculated the environmental risk score (ERS) to assess the effects of metal mixtures on RKFD and the genetic risk score (GRS) to assess genetic susceptibility. RKFD was defined as estimated glomerular filtration rate (eGFR) loss > 3 mL/min/1.73 m2/year.

RESULTS

During a median of 9.8 years follow-up, 262 participants developed RKFD. Aluminum, vanadium, zinc, selenium, rubidium, tin, barium, and tungsten were screened from ENET. In multivariate logistic models, vanadium, selenium, and tungsten were negatively associated with RKFD, while zinc, tin, and rubidium were positively associated. The BKMR showed a nonlinear association of vanadium and rubidium with RKFD and interactions between metals (barium‑vanadium, barium‑rubidium). The ERS was positive associated with RKFD (per SD increase in ERS, OR = 1.94, 95% CI: 1.66, 2.27). No significant interaction between ERS and GRS was observed on RKFD, however, participants in the highest ERS and GRS group had the highest RKFD risk.

CONCLUSION

Vanadium and rubidium were associated with RKFD in T2D. Metal mixtures was associated with an increased risk of RKFD in T2D, particularly in those at high genetic risk.

Exploring the impact and utility of genomic sequencing in established CKD

Clinical genetics is increasingly recognized as an important area within nephrology care. Clinicians require awareness of genetic kidney disease to recognize clinical phenotypes, consider use of genomics to aid diagnosis, and inform treatment decisions. Understanding the broad spectrum of clinical phenotypes and principles of genomic sequencing is becoming increasingly required in clinical nephrology, with nephrologists requiring education and support to achieve meaningful patient outcomes. Establishment of effective clinical resources, multi-disciplinary teams and education is important to increase application of genomics in clinical care, for the benefit of patients and their families. Novel applications of genomics in chronic kidney disease include pharmacogenomics and clinical translation of polygenic risk scores. This review explores established and emerging impacts and utility of genomics in kidney disease.

Monogenic and polygenic concepts in chronic kidney disease (CKD)

Kidney function is strongly influenced by genetic factors with both monogenic and polygenic factors contributing to kidney function. Monogenic disorders with primarily autosomal dominant inheritance patterns account for 10% of adult and 50% of paediatric kidney diseases. However, kidney function is also a complex trait with polygenic architecture, where genetic factors interact with environment and lifestyle factors. Family studies suggest that kidney function has significant heritability at 35-69%, capturing complexities of the genome with shared environmental factors. Genome-wide association studies estimate the single nucleotide polymorphism-based heritability of kidney function between 7.1 and 20.3%. These heritability estimates, measuring the extent to which genetic variation contributes to CKD risk, indicate a strong genetic contribution. Polygenic Risk Scores have recently been developed for chronic kidney disease and kidney function, and validated in large populations. Polygenic Risk Scores show correlation with kidney function but lack the specificity to predict individual-level changes in kidney function. Certain kidney diseases, such as membranous nephropathy and IgA nephropathy that have significant genetic components, may benefit most from polygenic risk scores for improved risk stratification. Genetic studies of kidney function also provide a potential avenue for the development of more targeted therapies and interventions. Understanding the development and validation of genomic scores is required to guide their implementation and identify the most appropriate potential implications in clinical practice. In this review, we provide an overview of the heritability of kidney function traits in population studies, explore both monogenic and polygenic concepts in kidney disease, with a focus on recently developed polygenic risk scores in kidney function and chronic kidney disease, and review specific diseases which are most amenable to incorporation of genomic scores.

Primary sclerosing cholangitis causally affects kidney function decline: A Mendelian randomization study

BACKGROUND AND AIM

The causal linkage between primary sclerosing cholangitis (PSC) and kidney function is unexplored despite their potential for long-term detrimental effects on kidney function.

METHODS

Two-sample summary-level Mendelian randomization (MR) study was conducted to identify the association between PSC and kidney function. The genetic variants were extracted from the PSC-specific multi-trait analyzed genome-wide association study (GWAS) of European ancestry. Summary-level data for kidney function traits, including estimated glomerular filtration rate (eGFR), annual eGFR decline, and chronic kidney disease (CKD), were obtained from the CKDGen consortium. Multiplicative random-effects inverse-variance weighted (MR-IVW), and a series of pleiotropy-robust analyses were performed to investigate the causal effects and ascertain their robustness.

RESULTS

Significant causal associations between genetically predicted PSC and kidney function traits were identified. Genetically predicted PSC was associated with decreased log-transformed eGFR (MR-IVW; beta = -0.41%; standard error [SE] = 0.02%; P < 0.001), increased rate of annual eGFR decline (MR-IVW; beta = 2.43%; SE = 0.18%; P < 0.001), and higher risk of CKD (MR-IVW; odds ratio = 1.07; 95% confidence interval = 1.06-1.08; P < 0.001). The main findings were supported by pleiotropy-robust analysis, including MR-Egger with bootstrapped error and weighted median.

CONCLUSIONS

Our study demonstrates that genetically predicted PSC is causally associated with kidney function impairment. Further studies are warranted to identify the underlying mechanisms.

A novel multi-ancestry proteome-wide Mendelian randomization study implicates extracellular proteins, tubular cells, and fibroblasts in estimated glomerular filtration rate regulation

Estimated glomerular filtration rate (eGFR) impacts the concentration of plasma biomarkers confounding biomarker association studies of eGFR with reverse causation. To identify biomarkers causally associated with eGFR, we performed a proteome-wide Mendelian randomization study. Genetic variants nearby biomarker coding genes were tested for association with plasma concentration of 1,161 biomarkers in a multi-ancestry sample of 12,066 participants from the Prospective Urban and Rural Epidemiological (PURE) study. Using two-sample Mendelian randomization, individual variants' effects on biomarker concentration were correlated with their effects on eGFR and kidney traits from published genome-wide association studies (GWAS). Genetically altered concentrations of 22 biomarkers were associated with eGFR above a Bonferroni-corrected significance threshold. Five biomarkers were previously identified by GWAS (UMOD, FGF5, LGALS7, NINJ1, COL18A1). Nine biomarkers were within 1 Mb of the lead GWAS variant but the gene for the biomarker was unidentified as the candidate for the GWAS signal (INHBC, TNFRSF11A, TCN2, PXN1, PRTN3, PSMD9, TFPI, ITGB6, CA3). Single-cell transcriptomic data indicated the 22 biomarkers are expressed in kidney tubules, collecting duct, fibroblasts, and immune cells. Pathway analysis showed significant enrichment of identified biomarkers in the extracellular kidney parenchyma. Thus, using genetic regulators of biomarker concentration via proteome-wide Mendelian randomization, we identified 22 biomarkers that appear to causally impact eGFR in either a beneficial or adverse manner. The current study provides rationale for novel therapeutic targets for eGFR and emphasized a role for extracellular proteins produced by tubular cells and fibroblasts for impacting eGFR.

Hypoxia and renal fibrosis

Renal fibrosis is the final stage of most progressive kidney diseases. Chronic kidney disease (CKD) is associated with high comorbidity and mortality. Thus, preventing fibrosis and thereby preserving kidney function increases the quality of life and prolongs the survival of patients with CKD. Many processes such as inflammation or metabolic stress modulate the progression of kidney fibrosis. Hypoxia has also been implicated in the pathogenesis of renal fibrosis, and oxygen sensing in the kidney is of outstanding importance for the body. The dysregulation of oxygen sensing in the diseased kidney is best exemplified by the loss of stimulation of erythropoietin production from interstitial cells in the fibrotic kidney despite anemia. Furthermore, hypoxia is present in acute or chronic kidney diseases and may affect all cell types present in the kidney including tubular and glomerular cells as well as resident immune cells. Pro- and antifibrotic effects of the transcription factors hypoxia-inducible factors 1 and 2 have been described in a plethora of animal models of acute and chronic kidney diseases, but recent advances in sequencing technologies now allow for novel and deeper insights into the role of hypoxia and its cell type-specific effects on the progression of renal fibrosis, especially in humans. Here, we review existing literature on how hypoxia impacts the development and progression of renal fibrosis.

KidneyGPS: a user-friendly web application to help prioritize kidney function genes and variants based on evidence from genome-wide association studies

BACKGROUND

Genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with kidney function. By combining these findings with post-GWAS information (e.g., statistical fine-mapping to identify independent association signals and to narrow down signals to causal variants; or different sources of annotation data), new hypotheses regarding physiology and disease aetiology can be obtained. These hypotheses need to be tested in laboratory experiments, for example, to identify new therapeutic targets. For this purpose, the evidence obtained from GWAS and post-GWAS analyses must be processed and presented in a way that they are easily accessible to kidney researchers without specific GWAS expertise. MAIN: Here we present KidneyGPS, a user-friendly web-application that combines genetic variant association for estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics consortium with annotation of (i) genetic variants with functional or regulatory effects ("SNP-to-gene" mapping), (ii) genes with kidney phenotypes in mice or human ("gene-to-phenotype"), and (iii) drugability of genes (to support re-purposing). KidneyGPS adopts a comprehensive approach summarizing evidence for all 5906 genes in the 424 GWAS loci for eGFR identified previously and the 35,885 variants in the 99% credible sets of 594 independent signals. KidneyGPS enables user-friendly access to the abundance of information by search functions for genes, variants, and regions. KidneyGPS also provides a function ("GPS tab") to generate lists of genes with specific characteristics thus enabling customizable Gene Prioritisation (GPS). These specific characteristics can be as broad as any gene in the 424 loci with a known kidney phenotype in mice or human; or they can be highly focussed on genes mapping to genetic variants or signals with particularly with high statistical support. KidneyGPS is implemented with RShiny in a modularized fashion to facilitate update of input data ( https://kidneygps.ur.de/gps/ ).

CONCLUSION

With the focus on kidney function related evidence, KidneyGPS fills a gap between large general platforms for accessing GWAS and post-GWAS results and the specific needs of the kidney research community. This makes KidneyGPS an important platform for kidney researchers to help translate in silico research results into in vitro or in vivo research.

Genome-Wide Association Study of CKD Progression

SIGNIFICANCE STATEMENT

Rapid progression of CKD is associated with poor clinical outcomes. Most previous studies looking for genetic factors associated with low eGFR have used cross-sectional data. The authors conducted a meta-analysis of genome-wide association studies of eGFR decline among 116,870 participants with CKD, focusing on longitudinal data. They identified three loci (two of them novel) associated with longitudinal eGFR decline. In addition to the known UMOD/PDILT locus, variants within BICC1 were associated with significant differences in longitudinal eGFR slope. Variants within HEATR4 also were associated with differences in eGFR decline, but only among Black/African American individuals without diabetes. These findings help characterize molecular mechanisms of eGFR decline in CKD and may inform new therapeutic approaches for progressive kidney disease.

BACKGROUND

Rapid progression of CKD is associated with poor clinical outcomes. Despite extensive study of the genetics of cross-sectional eGFR, only a few loci associated with eGFR decline over time have been identified.

METHODS

We performed a meta-analysis of genome-wide association studies of eGFR decline among 116,870 participants with CKD-defined by two outpatient eGFR measurements of <60 ml/min per 1.73 m 2 , obtained 90-365 days apart-from the Million Veteran Program and Vanderbilt University Medical Center's DNA biobank. The primary outcome was the annualized relative slope in outpatient eGFR. Analyses were stratified by ethnicity and diabetes status and meta-analyzed thereafter.

RESULTS

In cross-ancestry meta-analysis, the strongest association was rs77924615, near UMOD / PDILT ; each copy of the G allele was associated with a 0.30%/yr faster eGFR decline ( P = 4.9×10 -27 ). We also observed an association within BICC1 (rs11592748), where every additional minor allele was associated with a 0.13%/yr slower eGFR decline ( P = 5.6×10 -9 ). Among participants without diabetes, the strongest association was the UMOD/PDILT variant rs36060036, associated with a 0.27%/yr faster eGFR decline per copy of the C allele ( P = 1.9×10 -17 ). Among Black participants, a significantly faster eGFR decline was associated with variant rs16996674 near APOL1 (R 2 =0.29 with the G1 high-risk genotype); among Black participants with diabetes, lead variant rs11624911 near HEATR4 also was associated with a significantly faster eGFR decline. We also nominally replicated loci with known associations with eGFR decline, near PRKAG2, FGF5, and C15ORF54.

CONCLUSIONS

Three loci were significantly associated with longitudinal eGFR change at genome-wide significance. These findings help characterize molecular mechanisms of eGFR decline and may contribute to the development of new therapeutic approaches for progressive CKD.

Mendelian randomization uncovers a protective effect of interleukin-1 receptor antagonist on kidney function

Interleukins (ILs), key cytokine family of inflammatory response, are closely associated with kidney function. However, the causal effect of various ILs on kidney function needs further investigation. Here we show two-sample summary-level Mendelian randomization (MR) analysis that examined the causality between serum IL levels and kidney function. Genetic variants with strong association with serum IL levels were obtained from a previous genome-wide association study meta-analysis. Summary-level data for estimated glomerular filtration rate (eGFR) were obtained from CKDGen database. As a main MR analysis, multiplicative random-effects inverse-variance weighted method was performed. Pleiotropy-robust MR analysis, including MR-Egger with bootstrapped error and weighted median methods, were also implemented. We tested the causal estimates from nine ILs on eGFR traits. Among the results, higher genetically predicted serum IL-1 receptor antagonist level was significantly associated with higher eGFR values in the meta-analysis of CKDGen and the UK Biobank data. In addition, the result was consistent towards eGFR decline phenotype of the outcome database. Otherwise, nonsignificant association was identified between other genetically predicted ILs and eGFR outcome. These findings support the clinical importance of IL-1 receptor antagonist-associated pathway in relation to kidney function in the general individuals, particularly highlighting the importance of IL-1 receptor antagonist.

Association of polygenic scores with chronic kidney disease phenotypes in a longitudinal study of older adults

Risk of chronic kidney disease (CKD) is influenced by environmental and genetic factors and increases sharply in individuals 70 years and older. Polygenic scores (PGS) for kidney disease-related traits have shown promise but require validation in well-characterized cohorts. Here, we assessed the performance of recently developed PGSs for CKD-related traits in a longitudinal cohort of healthy older individuals enrolled in the Australian ASPREE randomized controlled trial of daily low-dose aspirin with CKD risk at baseline and longitudinally. Among 11,813 genotyped participants aged 70 years or more with baseline eGFR measures, we tested associations between PGSs and measured eGFR at baseline, clinical phenotype of CKD, and longitudinal rate of eGFR decline spanning up to six years of follow-up per participant. A PGS for eGFR was associated with baseline eGFR, with a significant decrease of 3.9 mL/min/1.73m2 (95% confidence interval -4.17 to -3.68) per standard deviation (SD) increase of the PGS. This PGS, as well as a PGS for CKD stage 3 were both associated with higher risk of baseline CKD stage 3 in cross-sectional analysis (Odds Ratio 1.75 per SD, 95% confidence interval 1.66-1.85, and Odds Ratio 1.51 per SD, 95% confidence interval 1.43-1.59, respectively). Longitudinally, two separate PGSs for eGFR slope were associated with significant kidney function decline during follow-up. Thus, our study demonstrates that kidney function has a considerable genetic component in older adults, and that new PGSs for kidney disease-related phenotypes may have potential utility for CKD risk prediction in advanced age.

Genetic and epigenetic background of diabetic kidney disease

Diabetic kidney disease (DKD) is a severe diabetic complication that affects up to half of the individuals with diabetes. Elevated blood glucose levels are a key underlying cause of DKD, but DKD is a complex multifactorial disease, which takes years to develop. Family studies have shown that inherited factors also contribute to the risk of the disease. During the last decade, genome-wide association studies (GWASs) have emerged as a powerful tool to identify genetic risk factors for DKD. In recent years, the GWASs have acquired larger number of participants, leading to increased statistical power to detect more genetic risk factors. In addition, whole-exome and whole-genome sequencing studies are emerging, aiming to identify rare genetic risk factors for DKD, as well as epigenome-wide association studies, investigating DNA methylation in relation to DKD. This article aims to review the identified genetic and epigenetic risk factors for DKD.

Novel Genetic Variants Associated with Chronic Kidney Disease Progression

SIGNIFICANCE STATEMENT

eGFR slope has been used as a surrogate outcome for progression of CKD. However, genetic markers associated with eGFR slope among patients with CKD were unknown. We aimed to identify genetic susceptibility loci associated with eGFR slope. A two-phase genome-wide association study identified single nucleotide polymorphisms (SNPs) in TPPP and FAT1-LINC02374 , and 22 of them were used to derive polygenic risk scores that mark the decline of eGFR by disrupting binding of nearby transcription factors. This work is the first to identify the impact of TPPP and FAT1-LINC02374 on CKD progression, providing predictive markers for the decline of eGFR in patients with CKD.

BACKGROUND

The incidence of CKD is associated with genetic factors. However, genetic markers associated with the progression of CKD have not been fully elucidated.

METHODS

We conducted a genome-wide association study among 1738 patients with CKD, mainly from the KoreaN cohort study for Outcomes in patients With CKD. The outcome was eGFR slope. We performed a replication study for discovered single nucleotide polymorphisms (SNPs) with P <10 -6 in 2498 patients with CKD from the Chronic Renal Insufficiency Cohort study. Several expression quantitative trait loci (eQTL) studies, pathway enrichment analyses, exploration of epigenetic architecture, and predicting disruption of transcription factor (TF) binding sites explored potential biological implications of the loci. We developed and evaluated the effect of polygenic risk scores (PRS) on incident CKD outcomes.

RESULTS

SNPs in two novel loci, TPPP and FAT1-LINC02374 , were replicated (rs59402340 in TPPP , Pdiscovery =7.11×10 -7 , PCRIC =8.13×10 -4 , Pmeta =7.23×10 -8 ; rs28629773 in FAT1-LINC02374 , Pdiscovery =6.08×10 -7 , PCRIC =4.33×10 -2 , Pmeta =1.87×10 -7 ). The eQTL studies revealed that the replicated SNPs regulated the expression level of nearby genes associated with kidney function. Furthermore, these SNPs were near gene enhancer regions and predicted to disrupt the binding of TFs. PRS based on the independently significant top 22 SNPs were significantly associated with CKD outcomes.

CONCLUSIONS

This study demonstrates that SNP markers in the TPPP and FAT1-LINC02374 loci could be predictive markers for the decline of eGFR in patients with CKD.

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

AIM

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Kidney disease progression and collider bias in GWAS

New genome-wide meta-analysis for longitudinal kidney function decline identified several genetic loci related to kidney disease progression. The study illustrated the complexity of modeling longitudinal traits in genome-wide association studies and highlighted the issue of a collider bias that can be introduced when a kidney disease progression phenotype is adjusted for baseline kidney function. Herein, we briefly outline the key findings of this study, their limitations, and implications for future studies.