An eQTL Landscape of Kidney Tissue in Human Nephrotic Syndrome

Applicability Assessment of Technologies for Predictive and Prescriptive Analytics of Nephrology Big Data

The integration of big data into nephrology research will open new avenues for analyzing and understanding complex biological datasets, driving advances in personalized management of kidney diseases. This paper describes the multifaceted challenges and opportunities by incorporating big data in nephrology, emphasizing the importance of data standardization, advanced storage solutions, and advanced analytical methods. We discuss the role of data science workflows, including data collection, preprocessing, integration, and analysis, in facilitating comprehensive insights into disease mechanisms and patient outcomes. Furthermore, we highlight predictive and prescriptive analytics, as well as the application of large language models (LLMs) in improving clinical decision-making and enhancing the accuracy of disease predictions. The use of high-performance computing (HPC) is also examined, showcasing its role in processing large-scale datasets and accelerating machine learning algorithms. Through this exploration, we aim to provide a comprehensive overview of the current state and future directions of big data analytics in nephrology, with a focus on enhancing patient care and advancing medical research.

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

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

Noninvasive Diagnostic Strategies for Membranous Nephropathy in the Nephrotic Syndrome Study Network

Key Points

Antiphospholipase A2 receptor antibody seropositivity by ELISA ≥2 and positive indirect immunofluorescence was optimal. Noninvasive diagnosis of phospholipase A2 receptor–associated membranous nephropathy among patients with proteinuria is feasible using both assays.

Background

Clinical practice guidelines recommend that a kidney biopsy is no longer required to confirm a diagnosis of membranous nephropathy (MN) in patients with nephrotic syndrome and a positive test for antiphospholipase A2 receptor antibodies (PLA2R-Ab). However, the optimal diagnostic strategy for using the PLA2R-Ab ELISA, PLA2R-Ab indirect immunofluorescence (IIF) test, and genetic risk score (GRS) for diagnosing MN, including the tests' optimal thresholds for positivity among incident patients with proteinuria, is still unknown.

Methods

We used serum samples at or before the first clinically indicated kidney biopsy from participants in the Nephrotic Syndrome Study Network to analyze test performance characteristics using different combinations and cutoffs of the PLA2R-Ab ELISA, IIF, and GRS for diagnosing MN. Secondary analyses included serum samples within 6 months after biopsy but before any immunosuppression use.

Results

There were 325 study participants with serum samples available on or before the day of kidney biopsy and an additional 143 study participants with samples within 6 months after biopsy but before any immunosuppression use. Of these participants, 26% (n =85) had biopsy-confirmed MN. The combination of ELISA ≥2 RU/ml and positive IIF was the optimal approach, with sensitivity of 0.60, specificity of 1.00, negative predictive value of 0.92, and positive predictive value of 1.00. Using IIF to confirm only borderline ELISA titers between 2 and 20 RU/ml resulted in similar sensitivity but specificity of >0.99. In our multiethnic study sample, we did not find improved diagnostic performance with the addition of GRSs.

Conclusions

In the Nephrotic Syndrome Study Network cohort, combined PLA2R-Ab testing with ELISA and IIF provided optimal test characteristics in making a noninvasive diagnosis of MN before or soon after kidney biopsy, including in patients with subnephrotic proteinuria. Further studies in multiethnic populations are needed to assess whether genetic data can augment this approach.

Expression quantitative trait loci (eQTL): from population genetics to precision medicine

Evidence has shown that differential transcriptomic profiles among human populations from diverse ancestries, supporting the role of genetic architecture in regulating gene expression alongside environmental stimuli. Genetic variants that regulate gene expression, known as expression quantitative trait loci (eQTL), are primarily shaped by human migration history and evolutionary forces, likewise, regulation of gene expression in principle could have been influenced by these events. Therefore, a comprehensive understanding of how human evolution impacts eQTL offers important insights into how phenotypic diversity is shaped. Recent studies, however, suggest that eQTL is enriched in genes that are selectively constrained. Whether eQTL is minimally affected by selective pressures remains an open question and requires comprehensive investigations. In addition, such studies are primarily dominated by the major populations of European ancestry, leaving many marginalized populations underrepresented. These observations indicate there exists a fundamental knowledge gap in the role of genomics variation on phenotypic diversity, which potentially hinders precision medicine. This article aims to revisit the abundance of eQTL across diverse populations and provide an overview of their impact from the population and evolutionary genetics perspective, subsequently discuss their influence on phenomics, as well as challenges and opportunities in the applications to precision medicine.

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

AIMS/HYPOTHESIS

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

METHODS

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

RESULTS

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

CONCLUSIONS/INTERPRETATION

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

Kidney multiome-based genetic scorecard reveals convergent coding and regulatory variants

Kidney dysfunction is a major cause of mortality, but its genetic architecture remains elusive. In this study, we conducted a multiancestry genome-wide association study in 2.2 million individuals and identified 1026 (97 previously unknown) independent loci. Ancestry-specific analysis indicated an attenuation of newly identified signals on common variants in European ancestry populations and the power of population diversity for further discoveries. We defined genotype effects on allele-specific gene expression and regulatory circuitries in more than 700 human kidneys and 237,000 cells. We found 1363 coding variants disrupting 782 genes, with 601 genes also targeted by regulatory variants and convergence in 161 genes. Integrating 32 types of genetic information, we present the "Kidney Disease Genetic Scorecard" for prioritizing potentially causal genes, cell types, and druggable targets for kidney disease.

A guide to studying 3D genome structure and dynamics in the kidney

The human genome is tightly packed into the 3D environment of the cell nucleus. Rapidly evolving and sophisticated methods of mapping 3D genome architecture have shed light on fundamental principles of genome organization and gene regulation. The genome is physically organized on different scales, from individual genes to entire chromosomes. Nuclear landmarks such as the nuclear envelope and nucleoli have important roles in compartmentalizing the genome within the nucleus. Genome activity (for example, gene transcription) is also functionally partitioned within this 3D organization. Rather than being static, the 3D organization of the genome is tightly regulated over various time scales. These dynamic changes in genome structure over time represent the fourth dimension of the genome. Innovative methods have been used to map the dynamic regulation of genome structure during important cellular processes including organism development, responses to stimuli, cell division and senescence. Furthermore, disruptions to the 4D genome have been linked to various diseases, including of the kidney. As tools and approaches to studying the 4D genome become more readily available, future studies that apply these methods to study kidney biology will provide insights into kidney function in health and disease.

Contribution of ECT2 to Tubulointerstitial Fibrosis in the Progression of Chronic Kidney Disease

OBJECTIVE

Chronic kidney disease (CKD) is a complex disorder resulting from a combination of various environmental and genetic factors. Considerable efforts have been dedicated to elucidating its etiological mechanisms. Nevertheless, the pathogenic mechanism of CKD remains poorly understood, which hinders the development of effective therapeutic strategies. In this study, we aimed to identify novel mediators that could contribute to the development of CKD.

METHODS

The ClinVar, STRING, MEME Suite, TRRUST, bedtools, GEO, and R Studio databases and software were used to analyze their common features and investigate potential CKD disease genes. Transcriptomic analysis, immunohistochemistry, qRT-PCR, and Western blotting were utilized to further validate the role of ECT2 in kidney fibrosis.

RESULTS

In total, 26 CKD disease genes were obtained from the ClinVar database, and the STRING, MEME Suite, TRRUST, bedtools, and GEO databases and software were used to analyze their common properties and explore potential CKD disease genes. Epithelial cell transforming sequence 2 (ECT2), cyclin B 1, caspase 7 and collagen alpha-1 (IV) were identified as potential candidates for CKD progression. Weighted correlation network analysis (WGCNA) subsequently revealed the relationships between potential genes and CKD. The results of the transcriptomic analysis further confirmed that ECT2 expression was greater in the kidney tissue of CKD patients than in that of healthy controls. Next, immunohistochemistry and Western blotting demonstrated that ECT2 was predominantly expressed in the renal tubules of a unilateral ureteral obstruction (UUO) mouse model. Consistently, in vitro experiments revealed that ECT2 was upregulated in TGF-β1-treated HK-2 cells. Moreover, ECT2 overexpression or knockdown in HK-2 cells altered the intensity of fibrosis markers.

CONCLUSION

ECT2 significantly affects the development and progression of CKD, particularly in association with tubulointerstitial fibrosis.

Optimal variable identification for accurate detection of causal expression Quantitative Trait Loci with applications in heart-related diseases

Gene expression plays a pivotal role in various diseases, contributing significantly to their mechanisms. Most GWAS risk loci are in non-coding regions, potentially affecting disease risk by altering gene expression in specific tissues. This expression is notably tissue-specific, with genetic variants substantially influencing it. However, accurately detecting the expression Quantitative Trait Loci (eQTL) is challenging due to limited heritability in gene expression, extensive linkage disequilibrium (LD), and multiple causal variants. The single variant association approach in eQTL analysis is limited by its susceptibility to capture the combined effects of multiple variants, and a bias towards common variants, underscoring the need for a more robust method to accurately identify causal eQTL variants. To address this, we developed an algorithm, CausalEQTL, which integrates L 0 +L 1 penalized regression with an ensemble approach to localize eQTL, thereby enhancing prediction performance precisely. Our results demonstrate that CausalEQTL outperforms traditional models, including LASSO, Elastic Net, Ridge, in terms of power and overall performance. Furthermore, analysis of heart tissue data from the GTEx project revealed that eQTL sites identified by our algorithm provide deeper insights into heart-related tissue eQTL detection. This advancement in eQTL mapping promises to improve our understanding of the genetic basis of tissue-specific gene expression and its implications in disease. The source code and identified causal eQTLs for CausalEQTL are available on GitHub: https://github.com/zhc-moushang/CausalEQTL.

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

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

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

BACKGROUND

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

METHODS

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

RESULT

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

CONCLUSION

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

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

INTRODUCTION

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

METHODS

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

RESULTS

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

CONCLUSION

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

A bootstrap model comparison test for identifying genes with context-specific patterns of genetic regulation

Understanding how genetic variation affects gene expression is essential for a complete picture of the functional pathways that give rise to complex traits. Although numerous studies have established that many genes are differentially expressed in distinct human tissues and cell types, no tools exist for identifying the genes whose expression is differentially regulated. Here we introduce DRAB (differential regulation analysis by bootstrapping), a gene-based method for testing whether patterns of genetic regulation are significantly different between tissues or other biological contexts. DRAB first leverages the elastic net to learn context-specific models of local genetic regulation and then applies a novel bootstrap-based model comparison test to check their equivalency. Unlike previous model comparison tests, our proposed approach can determine whether population-level models have equal predictive performance by accounting for the variability of feature selection and model training. We validated DRAB on mRNA expression data from a variety of human tissues in the Genotype-Tissue Expression (GTEx) Project. DRAB yielded biologically reasonable results and had sufficient power to detect genes with tissue-specific regulatory profiles while effectively controlling false positives. By providing a framework that facilitates the prioritization of differentially regulated genes, our study enables future discoveries on the genetic architecture of molecular phenotypes.

Uromodulin and progression of IgA nephropathy

BACKGROUND

This study investigates the link between genetic variants associated with kidney function and immunoglobulin A (IgA) nephropathy (IgAN) progression.

METHODS

We recruited 961 biopsy-proven IgAN patients and 651 non-IgAN end-stage renal disease (ESRD) patients from Ruijin Hospital. Clinical and renal pathological data were collected. The primary outcome was the time to ESRD. A healthy population was defined as estimated glomerular filtration rate >60 mL/min/1.73 m2 without albuminuria or hematuria. Fifteen single-nucleotide polymorphisms (SNPs) were selected from a genome-wide association study of kidney function and genotyped by the SNaPshot. Immunohistochemistry in renal tissue and ELISA in urine samples were performed to explore the potential functions of genetic variations.

RESULTS

The rs77924615-G was independently associated with an increased risk for ESRD in IgAN patients after adjustments for clinical and pathologic indices, and treatment (adjusted hazard ratio 2.10; 95% confidence interval 1.14-3.88). No significant differences in ESRD-free survival time were found among different genotypes in non-IgAN ESRD patients (log-rank, P = .480). Moreover, rs77924615 exhibited allele-specific enhancer activity by dual-luciferase reporter assay. Accordingly, the urinary uromodulin-creatinine ratio (uUCR) was significantly higher in healthy individuals with rs77924615 AG or GG than in individuals with AA. Furthermore, uromodulin expression in tubular epithelial cells was higher in patients with rs77924615 AG or GG. Finally, we confirmed that an increased uUCR (P = .009) was associated with faster IgAN progression.

CONCLUSION

The SNP rs77924615, which modulates the enhancer activity of the UMOD gene, is associated with renal function deterioration in IgAN patients by increasing uromodulin levels in both the renal tubular epithelium and urine.

A genomic association study revealing subphenotypes of childhood steroid-sensitive nephrotic syndrome in a larger genomic sequencing cohort

Dissecting the genetic components that contribute to the two main subphenotypes of steroid-sensitive nephrotic syndrome (SSNS) using genome-wide association studies (GWAS) strategy is important for understanding the disease. We conducted a multicenter cohort study (360 patients and 1835 controls) combined with a GWAS strategy to identify susceptibility variants associated with the following two subphenotypes of SSNS: steroid-sensitive nephrotic syndrome without relapse (SSNSWR, 181 patients) and steroid-dependent/frequent relapse nephrotic syndrome (SDNS/FRNS, 179 patients). The distribution of two single-nucleotide polymorphisms (SNPs) in ANKRD36 and ALPG was significant between SSNSWR and healthy controls, and that of two SNPs in GAD1 and HLA-DQA1 was significant between SDNS/FRNS and healthy controls. Interestingly, rs1047989 in HLA-DQA1 was a candidate locus for SDNS/FRNS but not for SSNSWR. No significant SNPs were observed between SSNSWR and SDNS/FRNS. Meanwhile, chromosome 2:171713702 in GAD1 was associated with a greater steroid dose (>0.75 mg/kg/d) upon relapse to first remission in patients with SDNS/FRNS (odds ratio = 3.14; 95% confidence interval, 0.97-9.87; P = 0.034). rs117014418 in APOL4 was significantly associated with a decrease in eGFR of greater than 20% compared with the baseline in SDNS/FRNS patients (P = 0.0001). Protein-protein intersection network construction suggested that HLA-DQA1 and HLA-DQB1 function together through GSDMA. Thus, SSNSWR belongs to non-HLA region-dependent nephropathy, and the HLA-DQA/DQB region is likely strongly associated with disease relapse, especially in SDNS/FRNS. The study provides a novel approach for the GWAS strategy of SSNS and contributes to our understanding of the pathological mechanisms of SSNSWR and SDNS/FRNS.

LIM Zinc Finger Domain Containing 1 Risk Genotype of Recipient Is Associated with Renal Tubular Inflammation in Kidney Transplantation

BACKGROUND

Homozygosity for LIMS1 rs893403-GG genotype is linked to an increased risk of allograft rejection after kidney transplantation. Ischemia-reperfusion of the kidney allograft leads to long term infiltration of activated and effector-memory T lymphocytes and resulting in rejection and long-term fibrosis. However, the genotype, LIMS1 expression under ischemic conditions and the long-term histopathological relationships remain ill-defined.

METHODS

We examined the impact of the recipient's LIMS1-rs893403 genotype with transplant kidney histopathology. The association of the LIMS1-rs893403 genotype and LIMS1 and GCC2 mRNA expression in ischemic donor kidneys were also examined. Recipients who underwent transplant kidney biopsy were genotyped for the LIMS1-rs893403 variant and associated deletion. Histopathological findings were compared between recipients with LIMS1 risk and non-risk genotypes. Real-time PCR and immunofluorescence staining for LIMS1 and GCC2 expression were performed in non-utilized donor kidneys.

RESULTS

Demographic, clinical, and treatment characteristics and the histopathological diagnosis were similar between recipients with rs893403 GG and AA/AG genotype. The Banff tubulitis score was higher in GG recipients (n = 24) compared to AA/AG (n = 86) recipients (1.42 ± 0.65 vs. 1.12 ± 0.66, p = 0.03). Ischemic kidneys with GG showed higher LIMS1 and GCC2 mRNA expression than kidneys with AG. Kidneys with rs893403-GG had higher tubular LIMS1 and GCC2 immunohistochemical staining compared to kidneys with rs893403-AG.

CONCLUSIONS

Our data supports the role of the LIMS1 locus in kidney transplant rejection, particularly in lymphocyte infiltration into the internal aspect of the tubular basement membranes. Increased LIMS1 and GCC2 expression in ischemic donor kidneys with the GG genotype require further studies.

Prioritization of Kidney Cell Types Highlights Myofibroblast Cells in Regulating Human Blood Pressure

Introduction

Blood pressure (BP) is a highly heritable trait with over 2000 underlying genomic loci identified to date. Although the kidney plays a key role, little is known about specific cell types involved in the genetic regulation of BP.

Methods

Here, we applied stratified linkage disequilibrium score (LDSC) regression to connect BP genome-wide association studies (GWAS) results to specific cell types of the mature human kidney. We used the largest single-stage BP genome-wide analysis to date, including up to 1,028,980 adults of European ancestry, and single-cell transcriptomic data from 14 mature human kidneys, with mean age of 41 years.

Results

Our analyses prioritized myofibroblasts and endothelial cells, among the total of 33 annotated cell type, as specifically involved in BP regulation (P < 0.05/33, i.e., 0.001515). Enrichment of heritability for systolic BP (SBP) was observed in myofibroblast cells in mature human kidney cortex, and enrichment of heritability for diastolic BP (DBP) was observed in descending vasa recta and peritubular capillary endothelial cells as well as stromal myofibroblast cells. The new finding of myofibroblast, the significant cell type for both BP traits, was consistent in 8 replication efforts using 7 sets of independent data, including in human fetal kidney, in East-Asian (EAS) ancestry, using mouse single-cell RNA sequencing (scRNA-seq) data, and when using another prioritization method.

Conclusion

Our findings provide a solid basis for follow-up studies to further identify genes and mechanisms in myofibroblast cells that underlie the regulation of BP.

Inhibition of Interleukin-33 to Reduce Glomerular Endothelial Inflammation in Diabetic Kidney Disease

Introduction

Inflammation is a significant contributor to cardiorenal morbidity and mortality in diabetic kidney disease (DKD). The pathophysiological mechanisms linking systemic, subacute inflammation and local, kidney injury-initiated immune maladaptation is partially understood.

Methods

Here, we explored the expression of proinflammatory cytokines in patients with DKD; investigated mouse models of type 1 and type 2 diabetes (T2D); evaluated glomerular signaling in vitro; performed post hoc analyses of systemic and urinary markers of inflammation; and initiated a phase 2b clinical study (FRONTIER-1; NCT04170543).

Results

Transcriptomic profiling of kidney biopsies from patients with DKD revealed significant glomerular upregulation of interleukin-33 (IL-33). Inhibition of IL-33 signaling reduced glomerular damage and albuminuria in the uninephrectomized db/db mouse model (T2D/DKD). On a cellular level, inhibiting IL-33 improved glomerular endothelial health by decreasing cellular inflammation and reducing release of proinflammatory cytokines. Therefore, FRONTIER-1 was designed to test the safety and efficacy of the IL-33-targeted monoclonal antibody tozorakimab in patients with DKD. So far, 578 patients are enrolled in FRONTIER-1. The baseline inflammation status of participants (N > 146) was assessed in blood and urine. Comparison to independent reference cohorts (N > 200) validated the distribution of urinary tumor necrosis factor receptor 1 (TNFR1) and C-C motif chemokine ligand 2 (CCL2). Treatment with dapagliflozin for 6 weeks did not alter these biomarkers significantly.

Conclusion

We show that blocking the IL-33 pathway may mitigate glomerular endothelial inflammation in DKD. The findings from the FRONTIER-1 study will provide valuable insights into the therapeutic potential of IL-33 inhibition in DKD.

A Neanderthal haplotype introgressed into the human genome confers protection against membranous nephropathy

Class 2 HLA and PLA2R1 alleles are exceptionally strong genetic risk factors for membranous nephropathy (MN), leading, through an unknown mechanism, to a targeted autoimmune response. Introgressed archaic haplotypes (introduced from an archaic human genome into the modern human genome) might influence phenotypes through gene dysregulation. Here, we investigated the genomic region surrounding the PLA2R1 gene. We reconstructed the phylogeny of Neanderthal and modern haplotypes in this region and calculated the probability of the observed clustering being the result of introgression or common descent. We imputed variants for the participants in our previous genome-wide association study and we compared the distribution of Neanderthal variants between MN cases and controls. The region associated with the lead MN risk locus in the PLA2R1 gene was confirmed and showed that, within a 507 kb region enriched in introgressed sequence, a stringently defined 105 kb haplotype, intersecting the coding regions for PLA2R1 and ITGB6, is inherited from Neanderthals. Thus, introgressed Neanderthal haplotypes overlapping PLA2R1 are differentially represented in MN cases and controls, with enrichment In controls suggesting a protective effect.

Multivariate canonical correlation analysis identifies additional genetic variants for chronic kidney disease

Chronic kidney diseases (CKD) have genetic associations with kidney function. Univariate genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with estimated glomerular filtration rate (eGFR) and blood urea nitrogen (BUN), two complementary kidney function markers. However, it is unknown whether additional SNPs for kidney function can be identified by multivariate statistical analysis. To address this, we applied canonical correlation analysis (CCA), a multivariate method, to two individual-level CKD genotype datasets, and metaCCA to two published GWAS summary statistics datasets. We identified SNPs previously associated with kidney function by published univariate GWASs with high replication rates, validating the metaCCA method. We then extended discovery and identified previously unreported lead SNPs for both kidney function markers, jointly. These showed expression quantitative trait loci (eQTL) colocalisation with genes having significant differential expression between CKD and healthy individuals. Several of these identified lead missense SNPs were predicted to have a functional impact, including in SLC14A2. We also identified previously unreported lead SNPs that showed significant correlation with both kidney function markers, jointly, in the European ancestry CKDGen, National Unified Renal Translational Research Enterprise (NURTuRE)-CKD and Salford Kidney Study (SKS) datasets. Of these, rs3094060 colocalised with FLOT1 gene expression and was significantly more common in CKD cases in both NURTURE-CKD and SKS, than in the general population. Overall, by using multivariate analysis by CCA, we identified additional SNPs and genes for both kidney function and CKD, that can be prioritised for further CKD analyses.

Rationale and design of the Nephrotic Syndrome Study Network (NEPTUNE) Match in glomerular diseases: designing the right trial for the right patient, today

Glomerular diseases are classified using a descriptive taxonomy that is not reflective of the heterogeneous underlying molecular drivers. This limits not only diagnostic and therapeutic patient management, but also impacts clinical trials evaluating targeted interventions. The Nephrotic Syndrome Study Network (NEPTUNE) is poised to address these challenges. The study has enrolled >850 pediatric and adult patients with proteinuric glomerular diseases who have contributed to deep clinical, histologic, genetic, and molecular profiles linked to long-term outcomes. The NEPTUNE Knowledge Network, comprising combined, multiscalar data sets, captures each participant's molecular disease processes at the time of kidney biopsy. In this editorial, we describe the design and implementation of NEPTUNE Match, which bridges a basic science discovery pipeline with targeted clinical trials. Noninvasive biomarkers have been developed for real-time pathway analyses. A Molecular Nephrology Board reviews the pathway maps together with clinical, laboratory, and histopathologic data assembled for each patient to compile a Match report that estimates the fit between the specific molecular disease pathway(s) identified in an individual patient and proposed clinical trials. The NEPTUNE Match report is communicated using established protocols to the patient and the attending nephrologist for use in their selection of available clinical trials. NEPTUNE Match represents the first application of precision medicine in nephrology with the aim of developing targeted therapies and providing the right medication for each patient with primary glomerular disease.

WNT-dependent interaction between inflammatory fibroblasts and FOLR2+ macrophages promotes fibrosis in chronic kidney disease

Chronic kidney disease (CKD) is a public health problem driven by myofibroblast accumulation, leading to interstitial fibrosis. Heterogeneity is a recently recognized characteristic in kidney fibroblasts in CKD, but the role of different populations is still unclear. Here, we characterize a proinflammatory fibroblast population (named CXCL-iFibro), which corresponds to an early state of myofibroblast differentiation in CKD. We demonstrate that CXCL-iFibro co-localize with macrophages in the kidney and participate in their attraction, accumulation, and switch into FOLR2+ macrophages from early CKD stages on. In vitro, macrophages promote the switch of CXCL-iFibro into ECM-secreting myofibroblasts through a WNT/β-catenin-dependent pathway, thereby suggesting a reciprocal crosstalk between these populations of fibroblasts and macrophages. Finally, the detection of CXCL-iFibro at early stages of CKD is predictive of poor patient prognosis, which shows that the CXCL-iFibro population is an early player in CKD progression and demonstrates the clinical relevance of our findings.

X-chromosome and kidney function: evidence from a multi-trait genetic analysis of 908,697 individuals reveals sex-specific and sex-differential findings in genes regulated by androgen response elements

X-chromosomal genetic variants are understudied but can yield valuable insights into sexually dimorphic human traits and diseases. We performed a sex-stratified cross-ancestry X-chromosome-wide association meta-analysis of seven kidney-related traits (n = 908,697), identifying 23 loci genome-wide significantly associated with two of the traits: 7 for uric acid and 16 for estimated glomerular filtration rate (eGFR), including four novel eGFR loci containing the functionally plausible prioritized genes ACSL4, CLDN2, TSPAN6 and the female-specific DRP2. Further, we identified five novel sex-interactions, comprising male-specific effects at FAM9B and AR/EDA2R, and three sex-differential findings with larger genetic effect sizes in males at DCAF12L1 and MST4 and larger effect sizes in females at HPRT1. All prioritized genes in loci showing significant sex-interactions were located next to androgen response elements (ARE). Five ARE genes showed sex-differential expressions. This study contributes new insights into sex-dimorphisms of kidney traits along with new prioritized gene targets for further molecular research.

The Significance of Hematuria in Podocytopathies

BACKGROUND

Hematuria is frequently present in podocytopathies, but its significance and prognostic value is not well described in these proteinuric kidney diseases. This study describes the prevalence and association between hematuria and kidney-related outcomes in these disorders.

METHODS

Hematuria was assessed at the initial urinalysis in participants with the following podocytopathies-membranous nephropathy, minimal change disease, and FSGS-in the Nephrotic Syndrome Study Network and Cure Glomerulonephropathy cohorts with >24 months of follow-up. Multivariable Cox proportional hazards models were fit for time to composite outcome (kidney failure or 40% decline in eGFR and eGFR <60 ml/min per 1.73 m 2 ) and proteinuria remission (urine protein-to-creatinine ratio [UPCR] <0.3 mg/mg).

RESULTS

Among the 1516 adults and children in the study, 528 participants (35%) had FSGS, 499 (33%) had minimal change disease, and 489 (32%) had membranous nephropathy. Median (interquartile range) time from biopsy until the initial study urinalysis was 260 (49-750) days, and 498 participants (33%) were positive for hematuria. Participants with hematuria compared with those without were older (37 [16-55] versus 33 [12-55] years), more likely to have an underlying diagnosis of membranous nephropathy (44% versus 27%), had shorter time since biopsy (139 [27-477] versus 325 [89-878] days), and had higher UPCR (3.8 [1.4-8.0] versus 0.9 [0.1-3.1] g/g). After adjusting for diagnosis, age, sex, UPCR, eGFR, time since biopsy, and study cohort, hematuria was associated with a higher risk of reaching the composite outcome (hazard ratio, 1.31; 95% confidence interval, 1.04 to 1.65; P value, 0.02) and lower rate of reaching proteinuria remission (hazard ratio, 0.80; 95% confidence interval, 0.65 to 0.98; P value, 0.03).

CONCLUSIONS

Hematuria is prevalent among participants with the three podocytopathies and is significantly and independently associated with worse kidney-related outcomes, including both progressive loss of kidney function and remission of proteinuria.

Osteoporosis and osteoarthritis: a bi-directional Mendelian randomization study

OBJECTIVE

To investigate the causal relationship between low bone mineral density (BMD) and osteoarthritis (OA) using Mendelian randomization (MR) design.

METHODS

Two-sample bi-directional MR analyses were performed using summary-level information on OA traits from UK Biobank and arcOGEN. Sensitivity analyses including MR-Egger, simple median, weighted median, MR pleiotropy residual sum, and outlier approaches were utilized in conjunction with inverse variance weighting (IVW). Gene ontology (GO) enrichment analyses and expression quantitative trait locus (eQTL) colocalization analyses were used to investigate the potential mechanism and shared genes between osteoporosis (OP) and OA.

RESULTS

The IVW method revealed that genetically predicted low femoral neck BMD was significantly linked with hip (β = 0.105, 95% CI: 0.023-0.188) and knee OA (β = 0.117, 95% CI: 0.049-0.184), but not with other site-specific OA. Genetically predicted low lumber spine BMD was significantly associated with OA at any sites (β = 0.048, 95% CI: 0.011-0.085), knee OA (β = 0.101, 95% CI: 0.045-0.156), and hip OA (β = 0.150, 95% CI: 0.077-0.224). Only hip OA was significantly linked with genetically predicted reduced total bone BMD (β = 0.092, 95% CI: 0.010-0.174). In the reverse MR analyses, no evidence for a causal effect of OA on BMD was found. GO enrichment analysis and eQTL analysis illustrated that DDN and SMAD-3 were the most prominent co-located genes.

CONCLUSIONS

These findings suggested that OP may be causally linked to an increased risk of OA, indicating that measures to raise BMD may be effective in preventing OA. More research is required to determine the underlying processes via which OP causes OA.

Genetics and epidemiology of mutational barcode-defined clonal hematopoiesis

Clonal hematopoiesis (CH) arises when a substantial proportion of mature blood cells is derived from a single hematopoietic stem cell lineage. Using whole-genome sequencing of 45,510 Icelandic and 130,709 UK Biobank participants combined with a mutational barcode method, we identified 16,306 people with CH. Prevalence approaches 50% in elderly participants. Smoking demonstrates a dosage-dependent impact on risk of CH. CH associates with several smoking-related diseases. Contrary to published claims, we find no evidence that CH is associated with cardiovascular disease. We provide evidence that CH is driven by genes that are commonly mutated in myeloid neoplasia and implicate several new driver genes. The presence and nature of a driver mutation alters the risk profile for hematological disorders. Nevertheless, most CH cases have no known driver mutations. A CH genome-wide association study identified 25 loci, including 19 not implicated previously in CH. Splicing, protein and expression quantitative trait loci were identified for CD164 and TCL1A.

Candidate Genes for IgA Nephropathy in Pediatric Patients: Exome-Wide Association Study

IgA nephropathy (IgAN) is an autoimmune disorder which is believed to be non-monogenic. We performed an exome-wide association study of 70 children with IgAN and 637 healthy donors. The HLA allele frequencies were compared between the patients and healthy donors from the bone marrow registry of the Pirogov University. We tested 78,020 gene markers for association and performed functional enrichment analysis and transcription factor binding preference detection. We identified 333 genetic variants, employing three inheritance models. The most significant association with the disorder was observed for rs143409664 (PRAG1) in the case of the additive and dominant models (PBONF = 1.808 × 10-15 and PBONF = 1.654 × 10-15, respectively), and for rs13028230 (UBR3) in the case of the recessive model (PBONF = 1.545 × 10-9). Enrichment analysis indicated the strongly overrepresented "immune system" and "kidney development" terms. The HLA-DQA1*01:01:01G allele (p = 0.0076; OR, 2.021 [95% CI, 1.322-3.048]) was significantly the most frequent among IgAN patients. Here, we characterized, for the first time, the genetic background of Russian IgAN patients, identifying the risk alleles typical of the population. The most important signals were detected in previously undescribed loci.

Leveraging molecular quantitative trait loci to comprehend complex diseases/traits from the omics perspective

Comprehending the molecular basis of quantitative genetic variation is a principal goal for complex diseases or traits. Molecular quantitative trait loci (molQTLs) have made it possible to investigate the effects of genetic variants hiding behind large-scale omics data. A deeper understanding of molQTL is urgently required in light of the multi-dimensionalization of omics data to more fully elucidate the pertinent biological mechanisms. Herein, we reviewed molQTLs with the corresponding resource from the omics perspective and further discussed the integrative strategy of GWAS-molQTL to infer their causal effects. Subsequently, we described the opportunities and challenges encountered by molQTL. The case studies showed that molQTL is essential for complex diseases and traits, whether single- or multi-omics QTLs. Overall, we highlighted the functional significance of genetic variants to employ the discovery of molQTL in complex diseases and traits.

Multiscale genetic architecture of donor-recipient differences reveals intronic LIMS1 mismatches associated with kidney transplant survival

Donor-recipient (D-R) mismatches outside of human leukocyte antigens (HLAs) contribute to kidney allograft loss, but the mechanisms remain unclear, specifically for intronic mismatches. We quantified non-HLA mismatches at variant-, gene-, and genome-wide scales from single nucleotide polymorphism (SNP) data of D-Rs from 2 well-phenotyped transplant cohorts: Genomics of Chronic Allograft Rejection (GoCAR; n = 385) and Clinical Trials in Organ Transplantation-01/17 (CTOT-01/17; n = 146). Unbiased gene-level screening in GoCAR uncovered the LIMS1 locus as the top-ranked gene where D-R mismatches associated with death-censored graft loss (DCGL). A previously unreported, intronic, LIMS1 haplotype of 30 SNPs independently associated with DCGL in both cohorts. Haplotype mismatches showed a dosage effect, and minor-allele introduction to major-allele-carrying recipients showed greater hazard of DCGL. The LIMS1 haplotype and the previously reported LIMS1 SNP rs893403 are expression quantitative trait loci (eQTL) in immune cells for GCC2 (not LIMS1), which encodes a protein involved in mannose-6-phosphase receptor (M6PR) recycling. Peripheral blood and T cell transcriptome analyses associated the GCC2 gene and LIMS1 SNPs with the TGF-β1/SMAD pathway, suggesting a regulatory effect. In vitro GCC2 modulation impacted M6PR-dependent regulation of active TGF-β1 and downstream signaling in T cells. Together, our data link LIMS1 locus D-R mismatches to DCGL via GCC2 eQTLs that modulate TGF-β1-dependent effects on T cells.

ONECUT1 variants beyond type 1 and type 2 diabetes: exploring clinical diversity and epigenetic associations in Arab cohorts

ONECUT1 gene, encoding hepatocyte nuclear factor 6, is involved in pancreas and liver development. ONECUT1 mutations impair the function of pancreatic β-cells and control a transcriptional/epigenetic machinery regulating endocrine development. Homozygous nonsense and missense mutations at ONECUT1_p.E231 and a homozygous frameshift mutation at ONECUT1_p.M289 were reported in neonatal diabetes individuals of French, Turkish, and Indian ethnicity, respectively. Additionally, heterozygous variants were observed in Northern European T2D patients, and Italian patients with neonatal diabetes and early-/late-onset T2D. Examining diverse populations, such as Arabs known for consanguinity, can generalize the ONECUT1 involvement in diabetes. Upon screening the cohorts of Kuwaiti T1D and MODY families, and of Kuwaiti and Qatari T2D individuals, we observed two homozygous variants-the deleterious missense rs202151356_p.H33Q in one MODY, one T1D, and two T2D individuals, and the synonymous rs61735385_p.P94P in two T2D individuals. Heterozygous variants were also observed. Examination of GTEx, NephQTL, mQTLdb and HaploReg highlighted the rs61735385_p.P94P variant as eQTL influencing the tissue-specific expression of ONECUT1, as mQTL influencing methylation at CpG sites in and around ONECUT1 with the nearest site at 677-bases 3' to rs61735385_p.P94P; as overlapping predicted binding sites for NF-kappaB and EBF on ONECUT1. DNA methylation profiles of peripheral blood from 19 MODY-X patients versus eight healthy individuals revealed significant hypomethylation at two CpG sites-one located 617-bases 3' to the p.P94P variant and 8,102 bases away from transcription start; and the other located 14,999 bases away from transcription start. Our study generalizes the association of ONECUT1 with clinical diversity in diabetes.

A BOOTSTRAP MODEL COMPARISON TEST FOR IDENTIFYING GENES WITH CONTEXT-SPECIFIC PATTERNS OF GENETIC REGULATION

Understanding how genetic variation affects gene expression is essential for a complete picture of the functional pathways that give rise to complex traits. Although numerous studies have established that many genes are differentially expressed in distinct human tissues and cell types, no tools exist for identifying the genes whose expression is differentially regulated. Here we introduce DRAB (Differential Regulation Analysis by Bootstrapping), a gene-based method for testing whether patterns of genetic regulation are significantly different between tissues or other biological contexts. DRAB first leverages the elastic net to learn context-specific models of local genetic regulation and then applies a novel bootstrap-based model comparison test to check their equivalency. Unlike previous model comparison tests, our proposed approach can determine whether population-level models have equal predictive performance by accounting for the variability of feature selection and model training. We validated DRAB on mRNA expression data from a variety of human tissues in the Genotype-Tissue Expression (GTEx) Project. DRAB yielded biologically reasonable results and had sufficient power to detect genes with tissue-specific regulatory profiles while effectively controlling false positives. By providing a framework that facilitates the prioritization of differentially regulated genes, our study enables future discoveries on the genetic architecture of molecular phenotypes.

Association of Interleukin-6 Genetic Polymorphisms (rs1800795, -174C > G and rs1800796, -572G > C) With Risk of Essential Hypertension in the Chinese Population

Background Interleukin-6 (IL-6) plays a critical role in essential hypertension (EH) and cardiovascular disease. Evidence suggests two hotspot single nucleotide polymorphisms (SNPs) of the IL-6 gene (rs1800795, -174C > G and rs1800796, -572G > C) might be associated with the susceptibility of EH. However, no consensus has yet been established. Thus, we aimed to investigate the potential association between IL-6 gene polymorphisms and the risk of EH based on a case-control study in a Chinese population. Materials and methods A total of 479 subjects (272 healthy controls and 207 EH patients) were randomly enrolled in our study. After extracting the genomic DNA, two SNPs of the IL-6 gene (rs1800795, -174C > G and rs1800796, -572G > C) were genotyped to analyze the potential association between these genetic variants and EH risk. Multiple genetic models were performed to investigate the strength of association by calculating the odds ratio (OR) and 95% confidence interval (95% CI). The potential effect of SNPs on gene expression was evaluated using expression quantitative trait loci (eQTL) analysis. Results The genotyping findings of IL-6 rs1800795, -174C > G polymorphism showed three study participants with CG genotype and 204 with GG genotype in the EH patients. The IL-6 -174C > G polymorphism was significantly associated with EH risk (P = 0.046) and conferred a reduced risk of EH development (OR = 0.99, 95%CI = 0.97-1.00). Conversely, no substantial association between IL-6 rs1800796, -572G > C polymorphism and the risk of EH was found in all genetic models (P > 0.05). Moreover, the eQTL analysis indicated that the -174C > G polymorphism was significantly associated with gene expression of IL-6 (P = 0.006), and the G allele corresponded to a reduced IL-6 gene expression (Beta = -0.397). Compared with -174C > G, the -572G > C polymorphism was not found to be significantly associated with IL-6 gene expression (Beta = -0.120, P = 0.560). Conclusions Our findings provide evidence that the rs1800795, -174C > G polymorphism can affect the expression levels of IL-6, and the risk of EH occurrence. However, the rs1800796, -572G > C polymorphism does not regulate the IL-6 gene expression levels and the susceptibility of EH.

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 meta-analysis identifies new candidate genes for sickle cell disease nephropathy

Sickle cell disease nephropathy (SCDN), a common SCD complication, is strongly associated with mortality. Polygenic risk scores calculated from recent transethnic meta-analyses of urinary albumin-to-creatinine ratio and estimated glomerular filtration rate (eGFR) trended toward association with proteinuria and eGFR in SCD but the model fit was poor (R2 < 0.01), suggesting that there are likely unique genetic risk factors for SCDN. Therefore, we performed genome-wide association studies (GWAS) for 2 critical manifestations of SCDN, proteinuria and decreased eGFR, in 2 well-characterized adult SCD cohorts, representing, to the best of our knowledge, the largest SCDN sample to date. Meta-analysis identified 6 genome-wide significant associations (false discovery rate, q ≤ 0.05): 3 for proteinuria (CRYL1, VWF, and ADAMTS7) and 3 for eGFR (LRP1B, linc02288, and FPGT-TNNI3K/TNNI3K). These associations are independent of APOL1 risk and represent novel SCDN loci, many with evidence for regulatory function. Moreover, GWAS SNPs in CRYL1, VWF, ADAMTS7, and linc02288 are associated with gene expression in kidney and pathways important to both renal function and SCD biology, supporting the hypothesis that SCDN pathophysiology is distinct from other forms of kidney disease. Together, these findings provide new targets for functional follow-up that could be tested prospectively and potentially used to identify patients with SCD who are at risk, before onset of kidney dysfunction.

Linkage analysis using whole exome sequencing data implicates SLC17A1, SLC17A3, TATDN2 and TMEM131L in type 1 diabetes in Kuwaiti families

Type 1 diabetes (T1D) is characterized by the progressive destruction of pancreatic β-cells, leading to insulin deficiency and lifelong dependency on exogenous insulin. Higher estimates of heritability rates in monozygotic twins, followed by dizygotic twins and sib-pairs, indicate the role of genetics in the pathogenesis of T1D. The incidence and prevalence of T1D are alarmingly high in Kuwait. Consanguineous marriages account for 50-70% of all marriages in Kuwait, leading to an excessive burden of recessive allele enrichment and clustering of familial disorders. Thus, genetic studies from this Arab region are expected to lead to the identification of novel gene loci for T1D. In this study, we performed linkage analyses to identify the recurrent genetic variants segregating in high-risk Kuwaiti families with T1D. We studied 18 unrelated Kuwaiti native T1D families using whole exome sequencing data from 86 individuals, of whom 37 were diagnosed with T1D. The study identified three potential loci with a LOD score of ≥ 3, spanning across four candidate genes, namely SLC17A1 (rs1165196:pT269I), SLC17A3 (rs942379: p.S370S), TATDN2 (rs394558:p.V256I), and TMEM131L (rs6848033:p.R190R). Upon examination of missense variants from these genes in the familial T1D dataset, we observed a significantly increased enrichment of the genotype homozygous for the minor allele at SLC17A3 rs56027330_p.G279R accounting for 16.2% in affected children from 6 unrelated Kuwaiti T1D families compared to 1000 genomes Phase 3 data (0.9%). Data from the NephQTL database revealed that the rs1165196, rs942379, rs394558, and rs56027330 SNPs exhibited genotype-based differential expression in either glomerular or tubular tissues. Data from the GTEx database revealed rs942379 and rs394558 as QTL variants altering the expression of TRIM38 and IRAK2 respectively. Global genome-wide association studies indicated that SLC17A1 rs1165196 and other variants from SLC17A3 are associated with uric acid concentrations and gout. Further evidence from the T1D Knowledge portal supported the role of shortlisted variants in T1D pathogenesis and urate metabolism. Our study suggests the involvement of SLC17A1, SLC17A3, TATDN2, and TMEM131L genes in familial T1D in Kuwait. An enrichment selection of genotype homozygous for the minor allele is observed at SLC17A3 rs56027330_p.G279R variant in affected members of Kuwaiti T1D families. Future studies may focus on replicating the findings in a larger T1D cohort and delineate the mechanistic details of the impact of these novel candidate genes on the pathophysiology of T1D.

Meta-analysis of African ancestry genome-wide association studies identified novel locus and validates multiple loci associated with kidney function

Despite recent efforts to increase diversity in genome-wide association studies (GWASs), most loci currently associated with kidney function are still limited to European ancestry due to the underlying sample selection bias in available GWASs. We set out to identify susceptibility loci associated with estimated glomerular filtration rate (eGFRcrea) in 80027 individuals of African-ancestry from the UK Biobank (UKBB), Million Veteran Program (MVP), and Chronic Kidney Disease genetics (CKDGen) consortia.We identified 8 lead SNPs, 7 of which were previously associated with eGFR in other populations. We identified one novel variant, rs77408001 which is an intronic variant mapped to the ELN gene. We validated three previously reported loci at GATM-SPATA5L1, SLC15A5 and AGPAT3. Fine-mapping analysis identified variants rs77121243 and rs201602445 as having a 99.9% posterior probability of being causal. Our results warrant designing bigger studies within individuals of African ancestry to gain new insights into the pathogenesis of Chronic Kidney Disease (CKD), and identify genomic variants unique to this ancestry that may influence renal function and disease.

Genome-wide Association Study for AKI

Key Points

Two genetic variants in the DISP1-TLR5 gene locus were associated with risk of AKI. DISP1 and TLR5 were differentially regulated in kidney biopsy tissue from patients with AKI compared with no AKI.

Background

Although common genetic risks for CKD are well established, genetic factors influencing risk for AKI in hospitalized patients are poorly understood.

Methods

We conducted a genome-wide association study in 1369 participants in the Assessment, Serial Evaluation, and Subsequent Sequelae of AKI Study; a multiethnic population of hospitalized participants with and without AKI matched on demographics, comorbidities, and kidney function before hospitalization. We then completed functional annotation of top-performing variants for AKI using single-cell RNA sequencing data from kidney biopsies in 12 patients with AKI and 18 healthy living donors from the Kidney Precision Medicine Project.

Results

No genome-wide significant associations with AKI risk were found in Assessment, Serial Evaluation, and Subsequent Sequelae of AKI (P < 5×10 −8 ). The top two variants with the strongest association with AKI mapped to the dispatched resistance-nodulation-division (RND) transporter family member 1 (DISP1) gene and toll-like receptor 5 (TLR5) gene locus, rs17538288 (odds ratio, 1.55; 95% confidence interval, 1.32 to 182; P = 9.47×10 −8 ) and rs7546189 (odds ratio, 1.53; 95% confidence interval, 1.30 to 1.81; P = 4.60×10 −7 ). In comparison with kidney tissue from healthy living donors, kidney biopsies in patients with AKI showed differential DISP1 expression in proximal tubular epithelial cells (adjusted P = 3.9× 10−2) and thick ascending limb of the loop of Henle (adjusted P = 8.7× 10−3) and differential TLR5 gene expression in thick ascending limb of the loop of Henle (adjusted P = 4.9× 10−30).

Conclusions

AKI is a heterogeneous clinical syndrome with various underlying risk factors, etiologies, and pathophysiology that may limit the identification of genetic variants. Although no variants reached genome-wide significance, we report two variants in the intergenic region between DISP1 and TLR5 , suggesting this region as a novel risk for AKI susceptibility.

Genetic studies of paired metabolomes reveal enzymatic and transport processes at the interface of plasma and urine

The kidneys operate at the interface of plasma and urine by clearing molecular waste products while retaining valuable solutes. Genetic studies of paired plasma and urine metabolomes may identify underlying processes. We conducted genome-wide studies of 1,916 plasma and urine metabolites and detected 1,299 significant associations. Associations with 40% of implicated metabolites would have been missed by studying plasma alone. We detected urine-specific findings that provide information about metabolite reabsorption in the kidney, such as aquaporin (AQP)-7-mediated glycerol transport, and different metabolomic footprints of kidney-expressed proteins in plasma and urine that are consistent with their localization and function, including the transporters NaDC3 (SLC13A3) and ASBT (SLC10A2). Shared genetic determinants of 7,073 metabolite-disease combinations represent a resource to better understand metabolic diseases and revealed connections of dipeptidase 1 with circulating digestive enzymes and with hypertension. Extending genetic studies of the metabolome beyond plasma yields unique insights into processes at the interface of body compartments.

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.

Genome-Wide Association Study in Acute Tubulointerstitial Nephritis

SIGNIFICANCE STATEMENT

Polymorphisms of HLA genes may confer susceptibility to acute tubulointerstitial nephritis (ATIN), but small sample sizes and candidate gene design have hindered their investigation. The first genome-wide association study of ATIN identified two significant loci, risk haplotype DRB1*14-DQA1*0101-DQB1*0503 (DR14 serotype) and protective haplotype DRB1*1501-DQA1*0102-DQB1*0602 (DR15 serotype), with amino acid position 60 in the peptide-binding groove P10 of HLA-DR β 1 key. Risk alleles were shared among different causes of ATIN and HLA genotypes associated with kidney injury and immune therapy response. HLA alleles showed the strongest association. The findings suggest that a genetically conferred risk of immune dysregulation is part of the pathogenesis of ATIN.

BACKGROUND

Acute tubulointerstitial nephritis (ATIN) is a rare immune-related disease, accounting for approximately 10% of patients with unexplained AKI. Previous elucidation of the relationship between genetic factors that contribute to its pathogenesis was hampered because of small sample sizes and candidate gene design.

METHODS

We undertook the first two-stage genome-wide association study and meta-analysis involving 544 kidney biopsy-defined patients with ATIN and 2346 controls of Chinese ancestry. We conducted statistical fine-mapping analysis, provided functional annotations of significant variants, estimated single nucleotide polymorphism (SNP)-based heritability, and checked genotype and subphenotype correlations.

RESULTS

Two genome-wide significant loci, rs35087390 of HLA-DQA1 ( P =3.01×10 -39 ) on 6p21.32 and rs2417771 of PLEKHA5 on 12p12.3 ( P =2.14×10 -8 ), emerged from the analysis. HLA imputation using two reference panels suggested that HLA-DRB1*14 mainly drives the HLA risk association . HLA-DRB1 residue 60 belonging to pocket P10 was the key amino acid position. The SNP-based heritability estimates with and without the HLA locus were 20.43% and 10.35%, respectively. Different clinical subphenotypes (drug-related or tubulointerstitial nephritis and uveitis syndrome) seemed to share the same risk alleles. However, the HLA risk genotype was associated with disease severity and response rate to immunosuppressive therapy.

CONCLUSIONS

We identified two candidate genome regions associated with susceptibility to ATIN. The findings suggest that a genetically conferred risk of immune dysregulation is involved in the pathogenesis of ATIN.

Mapping genomic regulation of kidney disease and traits through high-resolution and interpretable eQTLs

Expression quantitative trait locus (eQTL) studies illuminate genomic variants that regulate specific genes and contribute to fine-mapped loci discovered via genome-wide association studies (GWAS). Efforts to maximize their accuracy are ongoing. Using 240 glomerular (GLOM) and 311 tubulointerstitial (TUBE) micro-dissected samples from human kidney biopsies, we discovered 5371 GLOM and 9787 TUBE genes with at least one variant significantly associated with expression (eGene) by incorporating kidney single-nucleus open chromatin data and transcription start site distance as an "integrative prior" for Bayesian statistical fine-mapping. The use of an integrative prior resulted in higher resolution eQTLs illustrated by (1) smaller numbers of variants in credible sets with greater confidence, (2) increased enrichment of partitioned heritability for GWAS of two kidney traits, (3) an increased number of variants colocalized with the GWAS loci, and (4) enrichment of computationally predicted functional regulatory variants. A subset of variants and genes were validated experimentally in vitro and using a Drosophila nephrocyte model. More broadly, this study demonstrates that tissue-specific eQTL maps informed by single-nucleus open chromatin data have enhanced utility for diverse downstream analyses.

Omics are Getting Us Closer to Understanding IgA Nephropathy

During the last decade, thanks to omics technologies, new light has been shed on the pathogenesis of many diseases. Genomics, epigenomics, transcriptomics, and proteomics have helped to provide a better understanding of the origin and heterogeneity of several diseases. However, the risk factors for most autoimmune diseases remain unknown. The successes and pitfalls of omics have also been observed in nephrology, including immunoglobulin A nephropathy (IgAN), the most common form of glomerulonephritis and a principal cause of end-stage renal disease worldwide. Unfortunately, the immense progress in basic research has not yet been followed by the satisfactory development of a targeted treatment. Although, most omics studies describe changes in the immune system, there is still insufficient data to apply their results in the constantly evolving multi-hit pathogenesis model and thus do to provide a complete picture of the disease. Here, we describe recent findings regarding the pathophysiology of IgAN and link omics studies with immune system dysregulation. This review provides insights into specific IgAN markers, which may lead to the identification of potential targets for personalised treatment in the future.

Integration of artificial intelligence and multi-omics in kidney diseases

Kidney disease is a leading cause of death worldwide. Currently, the diagnosis of kidney diseases and the grading of their severity are mainly based on clinical features, which do not reveal the underlying molecular pathways. More recent surge of ∼omics studies has greatly catalyzed disease research. The advent of artificial intelligence (AI) has opened the avenue for the efficient integration and interpretation of big datasets for discovering clinically actionable knowledge. This review discusses how AI and multi-omics can be applied and integrated, to offer opportunities to develop novel diagnostic and therapeutic means in kidney diseases. The combination of new technology and novel analysis pipelines can lead to breakthroughs in expanding our understanding of disease pathogenesis, shedding new light on biomarkers and disease classification, as well as providing possibilities of precise treatment.

Identification of 969 protein quantitative trait loci in an African American population with kidney disease attributed to hypertension

Investigations into the causal underpinnings of disease processes can be aided by the incorporation of genetic information. Genetic studies require populations varied in both ancestry and prevalent disease in order to optimize discovery and ensure generalizability of findings to the global population. Here, we report the genetic determinants of the serum proteome in 466 African Americans with chronic kidney disease attributed to hypertension from the richly phenotyped African American Study of Kidney Disease and Hypertension (AASK) study. Using the largest aptamer-based protein profiling platform to date (6,790 proteins or protein complexes), we identified 969 genetic associations with 900 unique proteins; including 52 novel cis (local) associations and 379 novel trans (distant) associations. The genetic effects of previously published cis-protein quantitative trait loci (pQTLs) were found to be highly reproducible, and we found evidence that our novel genetic signals colocalize with gene expression and disease processes. Many trans- pQTLs were found to reflect associations mediated by the circulating cis protein, and the common trans-pQTLs are enriched for processes involving extracellular vesicles, highlighting a plausible mechanism for distal regulation of the levels of secreted proteins. Thus, our study generates a valuable resource of genetic associations linking variants to protein levels and disease in an understudied patient population to inform future studies of drug targets and physiology.

Genome-Wide Association Study for eGFR in a Taiwanese Population

BACKGROUND AND OBJECTIVES

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

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

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

RESULTS

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

CONCLUSIONS

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

TWAS Atlas: a curated knowledgebase of transcriptome-wide association studies

Transcriptome-wide association studies (TWASs), as a practical and prevalent approach for detecting the associations between genetically regulated genes and traits, are now leading to a better understanding of the complex mechanisms of genetic variants in regulating various diseases and traits. Despite the ever-increasing TWAS outputs, there is still a lack of databases curating massive public TWAS information and knowledge. To fill this gap, here we present TWAS Atlas (https://ngdc.cncb.ac.cn/twas/), an integrated knowledgebase of TWAS findings manually curated from extensive literature. In the current implementation, TWAS Atlas collects 401,266 high-quality human gene-trait associations from 200 publications, covering 22,247 genes and 257 traits across 135 tissue types. In particular, an interactive knowledge graph of the collected gene-trait associations is constructed together with single nucleotide polymorphism (SNP)-gene associations to build up comprehensive regulatory networks at multi-omics levels. In addition, TWAS Atlas, as a user-friendly web interface, efficiently enables users to browse, search and download all association information, relevant research metadata and annotation information of interest. Taken together, TWAS Atlas is of great value for promoting the utility and availability of TWAS results in explaining the complex genetic basis as well as providing new insights for human health and disease research.

PCA outperforms popular hidden variable inference methods for molecular QTL mapping

BACKGROUND

Estimating and accounting for hidden variables is widely practiced as an important step in molecular quantitative trait locus (molecular QTL, henceforth "QTL") analysis for improving the power of QTL identification. However, few benchmark studies have been performed to evaluate the efficacy of the various methods developed for this purpose.

RESULTS

Here we benchmark popular hidden variable inference methods including surrogate variable analysis (SVA), probabilistic estimation of expression residuals (PEER), and hidden covariates with prior (HCP) against principal component analysis (PCA)-a well-established dimension reduction and factor discovery method-via 362 synthetic and 110 real data sets. We show that PCA not only underlies the statistical methodology behind the popular methods but is also orders of magnitude faster, better-performing, and much easier to interpret and use.

CONCLUSIONS

To help researchers use PCA in their QTL analysis, we provide an R package PCAForQTL along with a detailed guide, both of which are freely available at https://github.com/heatherjzhou/PCAForQTL . We believe that using PCA rather than SVA, PEER, or HCP will substantially improve and simplify hidden variable inference in QTL mapping as well as increase the transparency and reproducibility of QTL research.

Kidney omics in hypertension: from statistical associations to biological mechanisms and clinical applications

Hypertension is a major cardiovascular disease risk factor and contributor to premature death globally. Family-based investigations confirmed a significant heritable component of blood pressure (BP), whereas genome-wide association studies revealed >1000 common and rare genetic variants associated with BP and/or hypertension. The kidney is not only an organ of key relevance to BP regulation and the development of hypertension, but it also acts as the tissue mediator of genetic predisposition to hypertension. The identity of kidney genes, pathways, and related mechanisms underlying the genetic associations with BP has started to emerge through integration of genomics with kidney transcriptomics, epigenomics, and other omics as well as through applications of causal inference, such as Mendelian randomization. Single-cell methods further enabled mapping of BP-associated kidney genes to cell types, and in conjunction with other omics, started to illuminate the biological mechanisms underpinning associations of BP-associated genetic variants and kidney genes. Polygenic risk scores derived from genome-wide association studies and refined on kidney omics hold the promise of enhanced diagnostic prediction, whereas kidney omics-informed drug discovery is likely to contribute new therapeutic opportunities for hypertension and hypertension-mediated kidney damage.

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

Estimated glomerular filtration rate (eGFR) reflects kidney function. Progressive eGFR-decline can lead to kidney failure, necessitating dialysis or transplantation. Hundreds of loci from genome-wide association studies (GWAS) for eGFR help explain population cross section variability. Since the contribution of these or other loci to eGFR-decline remains largely unknown, we derived GWAS for annual eGFR-decline and meta-analyzed 62 longitudinal studies with eGFR assessed twice over time in all 343,339 individuals and in high-risk groups. We also explored different covariate adjustment. Twelve genome-wide significant independent variants for eGFR-decline unadjusted or adjusted for eGFR-baseline (11 novel, one known for this phenotype), including nine variants robustly associated across models were identified. All loci for eGFR-decline were known for cross-sectional eGFR and thus distinguished a subgroup of eGFR loci. Seven of the nine variants showed variant-by-age interaction on eGFR cross section (further about 350,000 individuals), which linked genetic associations for eGFR-decline with age-dependency of genetic cross-section associations. Clinically important were two to four-fold greater genetic effects on eGFR-decline in high-risk subgroups. Five variants associated also with chronic kidney disease progression mapped to genes with functional in-silico evidence (UMOD, SPATA7, GALNTL5, TPPP). An unfavorable versus favorable nine-variant genetic profile showed increased risk odds ratios of 1.35 for kidney failure (95% confidence intervals 1.03-1.77) and 1.27 for acute kidney injury (95% confidence intervals 1.08-1.50) in over 2000 cases each, with matched controls). Thus, we provide a large data resource, genetic loci, and prioritized genes for kidney function decline, which help inform drug development pipelines revealing important insights into the age-dependency of kidney function genetics.