Assisting the analysis of insertions and deletions using regional allele frequencies

Accurate estimation of population allele frequency (AF) is crucial for gene discovery and genetic diagnostics. However, determining AF for frameshift-inducing small insertions and deletions (indels) faces challenges due to discrepancies in mapping and variant calling methods. Here, we propose an innovative approach to assess indel AF. We developed CRAFTS-indels (Calculating Regional Allele Frequency Targeting Small indels), an algorithm that combines AF of distinct indels within a given region and provides "regional AF" (rAF). We tested and validated CRAFTS-indels using three independent datasets: gnomAD v2 (n=125,748 samples), an internal dataset (IGM; n=39,367), and the UK BioBank (UKBB; n=469,835). By comparing rAF against standard AF, we identified rare indels with rAF exceeding standard AF (sAF≤10-4 and rAF>10-4) as "rAF-hi" indels. Notably, a high percentage of rare indels were "rAF-hi", with a higher proportion in gnomAD v2 (11-20%) and IGM (11-22%) compared to the UKBB (5-9% depending on the CRAFTS-indels' parameters). Analysis of the overlap of regions based on their rAF with low complexity regions and with ClinVar classification supported the pertinence of rAF. Using the internal dataset, we illustrated the utility of CRAFTS-indel in the analysis of de novo variants and the potential negative impact of rAF-hi indels in gene discovery. In summary, annotation of indels with cohort specific rAF can be used to handle some of the limitations of current annotation pipelines and facilitate detection of novel gene disease associations. CRAFTS-indels offers a user-friendly approach to providing rAF annotation. It can be integrated into public databases such as gnomAD, UKBB and used by ClinVar to revise indel classifications.

Combined Serologic and Genetic Risk Score and Prognostication of Phospholipase A2 receptor-Associated Membranous Nephropathy

INTRODUCTION

The aim of this study was to test whether a combined risk score on the basis of genetic risk and serology can improve the prediction of kidney failure in phospholipase A2 receptor (PLA2R)-associated primary membranous nephropathy.

METHODS

We performed a retrospective analysis of 519 biopsy-proven PLA2R-associated primary membranous nephropathy patients with baseline eGFR ≥25 ml/min per 1.73 m 2 . The combined risk score was calculated by combining the genetic risk score with PLA2R ELISA antibody titers. The primary end point was kidney disease progression defined as a 50% reduction in eGFR or kidney failure. Cox proportional hazard regression analysis and C-statistics were applied to compare the performance of PLA2R antibody, genetic risk score, and combined risk score, as compared with clinical factors alone, in predicting primary outcomes.

RESULTS

The median age was 56 years (range, 15-82 years); the male-to-female ratio was 1:0.6, the median eGFR at biopsy was 99 ml/min per 1.73 m 2 (range: 26-167 ml/min per 1.73 m 2 ), and the median proteinuria was 5.3 g/24 hours (range: 1.5-25.8 g/24 hours). During a median follow-up of 67 (5-200) months, 66 (13%) had kidney disease progression. In Cox proportional hazard regression models, PLA2R antibody titers, genetic risk score, and combined risk score were all individually associated with kidney disease progression with and without adjustments for age, sex, proteinuria, eGFR, and tubulointerstitial lesions. The best-performing clinical model to predict kidney disease progression included age, eGFR, proteinuria, serum albumin, diabetes, and tubulointerstitial lesions (C-statistic 0.76 [0.69-0.82], adjusted R 2 0.51). Although the addition of PLA2R antibody titer improved the performance of this model (C-statistic: 0.78 [0.72-0.84], adjusted R 2 0.61), replacing PLA2R antibody with the combined risk score improved the model further (C-statistic: 0.82 [0.77-0.87], adjusted R 2 0.69, difference of C-statistics with clinical model=0.06 [0.03-0.10], P < 0.001; difference of C-statistics with clinical-serologic model=0.04 [0.01-0.06], P < 0.001).

CONCLUSIONS

In patients with PLA2R-associated membranous nephropathy, the combined risk score incorporating inherited risk alleles and PLA2R antibody enhanced the prediction of kidney disease progression compared with PLA2R serology and clinical factors alone.

Return of polygenic risk scores in research: Stakeholders' views on the eMERGE-IV study

Research on polygenic risk scores (PRSs) for common, genetically complex chronic diseases aims to improve health-related predictions, tailor risk-reducing interventions, and improve health outcomes. Yet, the study and use of PRSs in clinical settings raise equity, clinical, and regulatory challenges that can be greater for individuals from historically marginalized racial, ethnic, and other minoritized communities. As part of the National Human Genome Research Institute-funded Electronic Medical Records and Genomics IV Network, we conducted online focus groups with patients/community members, clinicians, and members of institutional review boards to explore their views on key issues, including PRS research, return of PRS results, clinical translation, and barriers and facilitators to health behavioral changes in response to PRS results. Across stakeholder groups, our findings indicate support for PRS development and a strong interest in having PRS results returned to research participants. However, we also found multi-level barriers and significant differences in stakeholders' views about what is needed and possible for successful implementation. These include researcher-participant interaction formats, health and genomic literacy, and a range of structural barriers, such as financial instability, insurance coverage, and the absence of health-supporting infrastructure and affordable healthy food options in poorer neighborhoods. Our findings highlight the need to revisit and implement measures in PRS studies (e.g., incentives and resources for follow-up care), as well as system-level policies to promote equity in genomic research and health outcomes.

Risk factors affecting polygenic score performance across diverse cohorts

Apart from ancestry, personal or environmental covariates may contribute to differences in polygenic score (PGS) performance. We analyzed effects of covariate stratification and interaction on body mass index (BMI) PGS (PGS BMI ) across four cohorts of European (N=491,111) and African (N=21,612) ancestry. Stratifying on binary covariates and quintiles for continuous covariates, 18/62 covariates had significant and replicable R 2 differences among strata. Covariates with the largest differences included age, sex, blood lipids, physical activity, and alcohol consumption, with R 2 being nearly double between best and worst performing quintiles for certain covariates. 28 covariates had significant PGS BMI -covariate interaction effects, modifying PGS BMI effects by nearly 20% per standard deviation change. We observed overlap between covariates that had significant R 2 differences among strata and interaction effects - across all covariates, their main effects on BMI were correlated with their maximum R 2 differences and interaction effects (0.56 and 0.58, respectively), suggesting high-PGS BMI individuals have highest R 2 and increase in PGS effect. Using quantile regression, we show the effect of PGS BMI increases as BMI itself increases, and that these differences in effects are directly related to differences in R 2 when stratifying by different covariates. Given significant and replicable evidence for context-specific PGS BMI performance and effects, we investigated ways to increase model performance taking into account non-linear effects. Machine learning models (neural networks) increased relative model R 2 (mean 23%) across datasets. Finally, creating PGS BMI directly from GxAge GWAS effects increased relative R 2 by 7.8%. These results demonstrate that certain covariates, especially those most associated with BMI, significantly affect both PGS BMI performance and effects across diverse cohorts and ancestries, and we provide avenues to improve model performance that consider these effects.

Glomerular transcriptomics predicts long term outcome and identifies therapeutic strategies for patients with assumed benign IgA nephropathy

Some patients diagnosed with benign IgA nephropathy (IgAN) develop a progressive clinical course, not predictable by known clinical or histopathological parameters. To assess if gene expression can differentiate between progressors and non-progressors with assumed benign IgAN, we tested microdissected glomeruli from archival kidney biopsy sections from adult patients with stable clinical remission (21 non-progressors) or from 15 patients that had undergone clinical progression within a 25-year time frame. Based on 1 240 differentially expressed genes from patients with suitable sequencing results, we identified eight IgAN progressor and nine non-progressor genes using a two-component classifier. These genes, including APOL5 and ZXDC, predicted disease progression with 88% accuracy, 75% sensitivity and 100% specificity on average 21.6 years before progressive disease was clinically documented. APOL lipoproteins are associated with inflammation, autophagy and kidney disease while ZXDC is a zinc-finger transcription factor modulating adaptive immunity. Ten genes from our transcriptomics data overlapped with an external genome wide association study dataset, although the gene set enrichment test was not statistically significant. We also identified 45 drug targets in the DrugBank database, including angiotensinogen, a target of sparsentan (dual antagonist of the endothelin type A receptor and the angiotensin II type 1 receptor) currently investigated for IgAN treatment. Two validation cohorts were used for substantiating key results, one by immunohistochemistry and the other by nCounter technology. Thus, glomerular mRNA sequencing from diagnostic kidney biopsies from patients with assumed benign IgAN can differentiate between future progressors and non-progressors at the time of diagnosis.

Cell subtype-specific effects of genetic variation in the Alzheimer's disease brain

The relationship between genetic variation and gene expression in brain cell types and subtypes remains understudied. Here, we generated single-nucleus RNA sequencing data from the neocortex of 424 individuals of advanced age; we assessed the effect of genetic variants on RNA expression in cis (cis-expression quantitative trait loci) for seven cell types and 64 cell subtypes using 1.5 million transcriptomes. This effort identified 10,004 eGenes at the cell type level and 8,099 eGenes at the cell subtype level. Many eGenes are only detected within cell subtypes. A new variant influences APOE expression only in microglia and is associated with greater cerebral amyloid angiopathy but not Alzheimer's disease pathology, after adjusting for APOEε4, providing mechanistic insights into both pathologies. Furthermore, only a TMEM106B variant affects the proportion of cell subtypes. Integration of these results with genome-wide association studies highlighted the targeted cell type and probable causal gene within Alzheimer's disease, schizophrenia, educational attainment and Parkinson's disease loci.

Developing a genetic testing panel for evaluation of morbidities in kidney transplant recipients

Cardiovascular disease, infection, malignancy, and thromboembolism are major causes of morbidity and mortality in kidney transplant recipients (KTR). Prospectively identifying monogenic conditions associated with post-transplant complications may enable personalized management. Therefore, we developed a transplant morbidity panel (355 genes) associated with major post-transplant complications including cardiometabolic disorders, immunodeficiency, malignancy, and thrombophilia. This gene panel was then evaluated using exome sequencing data from 1590 KTR. Additionally, genes associated with monogenic kidney and genitourinary disorders along with American College of Medical Genetics (ACMG) secondary findings v3.2 were annotated. Altogether, diagnostic variants in 37 genes associated with Mendelian kidney and genitourinary disorders were detected in 9.9% (158/1590) of KTR; 25.9% (41/158) had not been clinically diagnosed. Moreover, the transplant morbidity gene panel detected diagnostic variants for 56 monogenic disorders in 9.1% KTRs (144/1590). Cardiovascular disease, malignancy, immunodeficiency, and thrombophilia variants were detected in 5.1% (81), 2.1% (34), 1.8% (29) and 0.2% (3) among 1590 KTRs, respectively. Concordant phenotypes were present in half of these cases. Reviewing implications for transplant care, these genetic findings would have allowed physicians to set specific risk factor targets in 6.3% (9/144), arrange intensive surveillance in 97.2% (140/144), utilize preventive measures in 13.2% (19/144), guide disease-specific therapy in 63.9% (92/144), initiate specialty referral in 90.3% (130/144) and alter immunosuppression in 56.9% (82/144). Thus, beyond diagnostic testing for kidney disorders, sequence annotation identified monogenic disorders associated with common post-transplant complications in 9.1% of KTR, with important clinical implications. Incorporating genetic diagnostics for transplant morbidities would enable personalized management in pre- and post-transplant care.

Pathologic-genomic correlation identified a novel variant in FN1 and established the diagnosis of recurrent fibronectin glomerulopathy in the kidney allograft

Fibronectin glomerulopathy is a rare inherited kidney disease, characterized by abnormal accumulation of fibronectin in the glomeruli. We report an exceptional case of recurrent fibronectin glomerulopathy first diagnosed in the kidney allograft. The presence of IgA staining in the native kidney biopsy and the reported family history of IgA nephropathy had led to initial pretransplant diagnosis of IgA nephropathy. At 4.5 years posttransplant, the patient presented with kidney insufficiency and minimal proteinuria. The allograft biopsy revealed glomerular deposits with very weak staining for immunoglobulins and vague filamentous material. Immunostaining for fibronectin was positive, and genetic studies showed a variant of unknown significance in the fibronectin 1 gene. Proteomic analyses of the glomeruli in the native kidney biopsy demonstrated large amount of fibronectin with abundant accumulation of the peptide synthesized by the detected variant. These findings established the diagnosis of recurrent fibronectin glomerulopathy secondary to a novel variant in the fibronectin 1 gene. This report sheds light on recurrent fibronectin glomerulopathy in the allograft, highlights the diagnostic pitfalls of the disease, and underscores the importance of pathologic-genomic correlation to establish the correct diagnosis.

Genetic versus self-reported African ancestry of the recipient and neighborhood predictors of kidney transplantation outcomes in 2 multiethnic urban cohorts

African American (AA) kidney recipients have a higher risk of allograft rejection and failure compared to non-AAs, but to what extent these outcomes are due to genetic versus environmental effects is currently unknown. Herein, we tested the effects of recipient self-reported race versus genetic proportion of African ancestry (pAFR), and neighborhood socioeconomic status (SES) on kidney allograft outcomes in multiethnic kidney transplant recipients from Columbia University (N = 1083) and the University of Pennsylvania (N = 738). All participants were genotyped with SNP arrays to estimate genetic admixture proportions. US census tract variables were used to analyze the effect of neighborhood factors. In both cohorts, self-reported recipient AA race and pAFR were individually associated with increased risk of rejection and failure after adjustment for known clinical risk factors and neighborhood SES factors. Joint analysis confirmed that self-reported recipient AA race and pAFR were both associated with a higher risk of allograft rejection (AA: HR 1.61 (1.31-1.96), P = 4.05E-06; pAFR: HR 1.90 (1.46-2.48), P = 2.40E-06) and allograft failure (AA: HR 1.52 (1.18-1.97), P = .001; pAFR: HR 1.70 (1.22-2.35), P = .002). Further research is needed to disentangle the role of genetics versus environmental, social, and structural factors contributing to poor transplantation outcomes in kidney recipients of African ancestry.

Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations

Polygenic risk scores (PRSs) have improved in predictive performance, but several challenges remain to be addressed before PRSs can be implemented in the clinic, including reduced predictive performance of PRSs in diverse populations, and the interpretation and communication of genetic results to both providers and patients. To address these challenges, the National Human Genome Research Institute-funded Electronic Medical Records and Genomics (eMERGE) Network has developed a framework and pipeline for return of a PRS-based genome-informed risk assessment to 25,000 diverse adults and children as part of a clinical study. From an initial list of 23 conditions, ten were selected for implementation based on PRS performance, medical actionability and potential clinical utility, including cardiometabolic diseases and cancer. Standardized metrics were considered in the selection process, with additional consideration given to strength of evidence in African and Hispanic populations. We then developed a pipeline for clinical PRS implementation (score transfer to a clinical laboratory, validation and verification of score performance), and used genetic ancestry to calibrate PRS mean and variance, utilizing genetically diverse data from 13,475 participants of the All of Us Research Program cohort to train and test model parameters. Finally, we created a framework for regulatory compliance and developed a PRS clinical report for return to providers and for inclusion in an additional genome-informed risk assessment. The initial experience from eMERGE can inform the approach needed to implement PRS-based testing in diverse clinical settings.

Participant-guided development of bilingual genomic educational infographics for Electronic Medical Records and Genomics Phase IV study

OBJECTIVE

Developing targeted, culturally competent educational materials is critical for participant understanding of engagement in a large genomic study that uses computational pipelines to produce genome-informed risk assessments.

MATERIALS AND METHODS

Guided by the Smerecnik framework that theorizes understanding of multifactorial genetic disease through 3 knowledge types, we developed English and Spanish infographics for individuals enrolled in the Electronic Medical Records and Genomics Network. Infographics were developed to explain concepts in lay language and visualizations. We conducted iterative sessions using a modified "think-aloud" process with 10 participants (6 English, 4 Spanish-speaking) to explore comprehension of and attitudes towards the infographics.

RESULTS

We found that all but one participant had "awareness knowledge" of genetic disease risk factors upon viewing the infographics. Many participants had difficulty with "how-to" knowledge of applying genetic risk factors to specific monogenic and polygenic risks. Participant attitudes towards the iteratively-refined infographics indicated that design saturation was reached.

DISCUSSION

There were several elements that contributed to the participants' comprehension (or misunderstanding) of the infographics. Visualization and iconography techniques best resonated with those who could draw on prior experiences or knowledge and were absent in those without. Limited graphicacy interfered with the understanding of absolute and relative risks when presented in graph format. Notably, narrative and storytelling theory that informed the creation of a vignette infographic was most accessible to all participants.

CONCLUSION

Engagement with the intended audience who can identify strengths and points for improvement of the intervention is necessary to the development of effective infographics.

The chromatin landscape of healthy and injured cell types in the human kidney

There is a need to define regions of gene activation or repression that control human kidney cells in states of health, injury, and repair to understand the molecular pathogenesis of kidney disease and design therapeutic strategies. Comprehensive integration of gene expression with epigenetic features that define regulatory elements remains a significant challenge. We measure dual single nucleus RNA expression and chromatin accessibility, DNA methylation, and H3K27ac, H3K4me1, H3K4me3, and H3K27me3 histone modifications to decipher the chromatin landscape and gene regulation of the kidney in reference and adaptive injury states. We establish a spatially-anchored epigenomic atlas to define the kidney's active, silent, and regulatory accessible chromatin regions across the genome. Using this atlas, we note distinct control of adaptive injury in different epithelial cell types. A proximal tubule cell transcription factor network of ELF3, KLF6, and KLF10 regulates the transition between health and injury, while in thick ascending limb cells this transition is regulated by NR2F1. Further, combined perturbation of ELF3, KLF6, and KLF10 distinguishes two adaptive proximal tubular cell subtypes, one of which manifested a repair trajectory after knockout. This atlas will serve as a foundation to facilitate targeted cell-specific therapeutics by reprogramming gene regulatory networks.

Polygenic risk alters the penetrance of monogenic kidney disease

Chronic kidney disease (CKD) is determined by an interplay of monogenic, polygenic, and environmental risks. Autosomal dominant polycystic kidney disease (ADPKD) and COL4A-associated nephropathy (COL4A-AN) represent the most common forms of monogenic kidney diseases. These disorders have incomplete penetrance and variable expressivity, and we hypothesize that polygenic factors explain some of this variability. By combining SNP array, exome/genome sequence, and electronic health record data from the UK Biobank and All-of-Us cohorts, we demonstrate that the genome-wide polygenic score (GPS) significantly predicts CKD among ADPKD monogenic variant carriers. Compared to the middle tertile of the GPS for noncarriers, ADPKD variant carriers in the top tertile have a 54-fold increased risk of CKD, while ADPKD variant carriers in the bottom tertile have only a 3-fold increased risk of CKD. Similarly, the GPS significantly predicts CKD in COL4A-AN carriers. The carriers in the top tertile of the GPS have a 2.5-fold higher risk of CKD, while the risk for carriers in the bottom tertile is not different from the average population risk. These results suggest that accounting for polygenic risk improves risk stratification in monogenic kidney disease.

Mouse and human studies support DSTYK loss of function as a low-penetrance and variable expressivity risk factor for congenital urinary tract anomalies

PURPOSE

Previous work identified rare variants in DSTYK associated with human congenital anomalies of the kidney and urinary tract (CAKUT). Here, we present a series of mouse and human studies to clarify the association, penetrance, and expressivity of DSTYK variants.

METHODS

We phenotypically characterized Dstyk knockout mice of 3 separate inbred backgrounds and re-analyzed the original family segregating the DSTYK c.654+1G>A splice-site variant (referred to as "SSV" below). DSTYK loss of function (LOF) and SSVs were annotated in individuals with CAKUT, epilepsy, or amyotrophic lateral sclerosis vs controls. A phenome-wide association study analysis was also performed using United Kingdom Biobank (UKBB) data.

RESULTS

Results demonstrate ∼20% to 25% penetrance of obstructive uropathy, at least, in C57BL/6J and FVB/NJ Dstyk-/- mice. Phenotypic penetrance increased to ∼40% in C3H/HeJ mutants, with mild-to-moderate severity. Re-analysis of the original family segregating the rare SSV showed low penetrance (43.8%) and no alternative genetic causes for CAKUT. LOF DSTYK variants burden showed significant excess for CAKUT and epilepsy vs controls and an exploratory phenome-wide association study supported association with neurological disorders.

CONCLUSION

These data support causality for DSTYK LOF variants and highlights the need for large-scale sequencing studies (here >200,000 cases) to accurately assess causality for genes and variants to lowly penetrant traits with common population prevalence.

Mendelian randomization for nephrologists

Confounding is a major limitation of observational studies. Mendelian randomization (MR) is a powerful study design that uses genetic variants as instrumental variables to enable examination of the causal effect of an exposure on an outcome in observational data. With the emergence of large-scale genome-wide association studies in nephrology over the past decade, MR has become a popular method to establish causal inferences. However, MR is a complex and challenging methodology that requires careful consideration to ensure robust results. This review article aims to summarize the basic concepts of MR, its application and relevance in nephrology, and the methodological challenges and limitations as well as discuss the current guidelines for design and reporting. With reference to a clinically relevant example of examining the causal relationship between the estimated glomerular filtration rate and cancer, this review outlines the key steps to conducting an MR study, including the key considerations and potential pitfalls at each step. These include defining the clinical question, selecting the data sources, identifying and refining appropriate genetic variants by considering linkage disequilibrium and associations with potential confounders, harmonization of variants across data sets, validation of the genetic instrument by assessing its strength, estimation of the causal effects, confirming the validity of the findings, and interpreting and reporting results.

Strong protective effect of the APOL1 p.N264K variant against G2-associated focal segmental glomerulosclerosis and kidney disease

African Americans have a significantly higher risk of developing chronic kidney disease, especially focal segmental glomerulosclerosis -, than European Americans. Two coding variants (G1 and G2) in the APOL1 gene play a major role in this disparity. While 13% of African Americans carry the high-risk recessive genotypes, only a fraction of these individuals develops FSGS or kidney failure, indicating the involvement of additional disease modifiers. Here, we show that the presence of the APOL1 p.N264K missense variant, when co-inherited with the G2 APOL1 risk allele, substantially reduces the penetrance of the G1G2 and G2G2 high-risk genotypes by rendering these genotypes low-risk. These results align with prior functional evidence showing that the p.N264K variant reduces the toxicity of the APOL1 high-risk alleles. These findings have important implications for our understanding of the mechanisms of APOL1-associated nephropathy, as well as for the clinical management of individuals with high-risk genotypes that include the G2 allele.

Dimension-agnostic and granularity-based spatially variable gene identification using BSP

Identifying spatially variable genes (SVGs) is critical in linking molecular cell functions with tissue phenotypes. Spatially resolved transcriptomics captures cellular-level gene expression with corresponding spatial coordinates in two or three dimensions and can be used to infer SVGs effectively. However, current computational methods may not achieve reliable results and often cannot handle three-dimensional spatial transcriptomic data. Here we introduce BSP (big-small patch), a non-parametric model by comparing gene expression pattens at two spatial granularities to identify SVGs from two or three-dimensional spatial transcriptomics data in a fast and robust manner. This method has been extensively tested in simulations, demonstrating superior accuracy, robustness, and high efficiency. BSP is further validated by substantiated biological discoveries in cancer, neural science, rheumatoid arthritis, and kidney studies with various types of spatial transcriptomics technologies.

Single Nucleus RNA Sequencing of Remnant Kidney Biopsies and Urine Cell RNA Sequencing Reveal Cell Specific Markers of Covid-19 Acute Kidney Injury

Acute kidney injury (AKI) in COVID-19 patients is associated with high mortality and morbidity. Critically ill COVID-19 patients are at twice the risk of in-hospital mortality compared to non-COVID AKI patients. We know little about the cell-specific mechanism in the kidney that contributes to worse clinical outcomes in these patients. New generation single cell technologies have the potential to provide insights into physiological states and molecular mechanisms in COVID-AKI. One of the key limitations is that these patients are severely ill posing significant risks in procuring additional biopsy tissue. We recently generated single nucleus RNA-sequencing data using COVID-AKI patient biopsy tissue as part of the human kidney atlas. Here we describe this approach in detail and report deeper comparative analysis of snRNAseq of 4 COVID-AKI, 4 reference, and 6 non-COVID-AKI biopsies. We also generated and analyzed urine transcriptomics data to find overlapping COVID-AKI-enriched genes and their corresponding cell types in the kidney from snRNA-seq data. We identified all major and minor cell types and states by using by using less than a few cubic millimeters of leftover tissue after pathological workup in our approach. Differential expression analysis of COVID-AKI biopsies showed pathways enriched in viral response, WNT signaling, kidney development, and cytokines in several nephron epithelial cells. COVID-AKI profiles showed a much higher proportion of altered TAL cells than non-COVID AKI and the reference samples. In addition to kidney injury and fibrosis markers indicating robust remodeling we found that, 17 genes overlap between urine cell COVID-AKI transcriptome and the snRNA-seq data from COVID-AKI biopsies. A key feature was that several of the distal nephron and collecting system cell types express these markers. Some of these markers have been previously observed in COVID-19 studies suggesting a common mechanism of injury and potentially the kidney as one of the sources of soluble factors with a potential role in disease progression.

Translational Statement

The manuscript describes innovation, application and discovery that impact clinical care in kidney disease. First, the approach to maximize use of remnant frozen clinical biopsies to inform on clinically relevant molecular features can augment existing pathological workflow for any frozen tissue without much change in the protocol. Second, this approach is transformational in medical crises such as pandemics where mechanistic insights are needed to evaluate organ injury, targets for drug therapy and diagnostic and prognostic markers. Third, the cell type specific and soluble markers identified and validated can be used for diagnoses or prognoses in AKI due to different etiologies and in multiorgan injury.

Prospective, multi-site study of healthcare utilization after actionable monogenic findings from clinical sequencing

As large-scale genomic screening becomes increasingly prevalent, understanding the influence of actionable results on healthcare utilization is key to estimating the potential long-term clinical impact. The eMERGE network sequenced individuals for actionable genes in multiple genetic conditions and returned results to individuals, providers, and the electronic health record. Differences in recommended health services (laboratory, imaging, and procedural testing) delivered within 12 months of return were compared among individuals with pathogenic or likely pathogenic (P/LP) findings to matched individuals with negative findings before and after return of results. Of 16,218 adults, 477 unselected individuals were found to have a monogenic risk for arrhythmia (n = 95), breast cancer (n = 96), cardiomyopathy (n = 95), colorectal cancer (n = 105), or familial hypercholesterolemia (n = 86). Individuals with P/LP results more frequently received services after return (43.8%) compared to before return (25.6%) of results and compared to individuals with negative findings (24.9%; p < 0.0001). The annual cost of qualifying healthcare services increased from an average of $162 before return to $343 after return of results among the P/LP group (p < 0.0001); differences in the negative group were non-significant. The mean difference-in-differences was $149 (p < 0.0001), which describes the increased cost within the P/LP group corrected for cost changes in the negative group. When stratified by individual conditions, significant cost differences were observed for arrhythmia, breast cancer, and cardiomyopathy. In conclusion, less than half of individuals received billed health services after monogenic return, which modestly increased healthcare costs for payors in the year following return.

Anti-PLA2R Antibody Levels and Clinical Risk Factors for Treatment Nonresponse in Membranous Nephropathy

BACKGROUND

The 2021 Kidney Disease Improving Global Outcomes (KDIGO) guidelines recommend following anti-phospholipase A2 receptor (PLA2R) antibody levels as a marker of treatment response in membranous nephropathy; however, the optimal timing to evaluate antibody levels and how to combine them with other clinical variables are currently unknown.

METHODS

We used a cohort of 85 patients from the Membranous Nephropathy Trial Of Rituximab (MENTOR) with anti-PLA2R antibodies ≥14 RU/ml to identify risk factors for not experiencing proteinuria remission after 12 months of treatment with cyclosporine or rituximab. Three landmark times were considered: at baseline and after 3 and 6 months of treatment. Logistic regression model performance was evaluated using C-statistics and model fit (Akaike information criterion [AIC], R 2 ).

RESULTS

The model at baseline that best predicted no remission included anti-PLA2R antibodies >323 RU/ml and creatinine clearance; the best model after 3 months included the change from baseline in both antibody and albumin levels; and the best model after 6 months included antibody levels >14 RU/ml, creatinine clearance, and the change from baseline in albumin. Compared with the model at baseline, the model at 3 months had better model fit (AIC 70.9 versus 96.4, R 2 51.8% versus 30.1%) and higher C-statistic (0.93 versus 0.83, P = 0.008). The model at 6 months had no difference in performance compared with the model at 3 months (AIC 68.6, R 2 53.0%, C-statistic 0.94, P = 0.67).

CONCLUSIONS

In patients with membranous nephropathy treated with cyclosporine or rituximab in the MENTOR trial, we found that the optimal method to evaluate risk factors for the probability of treatment response was to use anti-PLA2R antibody levels combined with albumin levels after 3 months of treatment, which was significantly better than using antibody levels alone or risk factor evaluation at baseline, with no added benefit of waiting until 6 months of treatment.

PODCAST

This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2023_10_09_CJN0000000000000237.mp3.

Projecting genetic associations through gene expression patterns highlights disease etiology and drug mechanisms

Genes act in concert with each other in specific contexts to perform their functions. Determining how these genes influence complex traits requires a mechanistic understanding of expression regulation across different conditions. It has been shown that this insight is critical for developing new therapies. Transcriptome-wide association studies have helped uncover the role of individual genes in disease-relevant mechanisms. However, modern models of the architecture of complex traits predict that gene-gene interactions play a crucial role in disease origin and progression. Here we introduce PhenoPLIER, a computational approach that maps gene-trait associations and pharmacological perturbation data into a common latent representation for a joint analysis. This representation is based on modules of genes with similar expression patterns across the same conditions. We observe that diseases are significantly associated with gene modules expressed in relevant cell types, and our approach is accurate in predicting known drug-disease pairs and inferring mechanisms of action. Furthermore, using a CRISPR screen to analyze lipid regulation, we find that functionally important players lack associations but are prioritized in trait-associated modules by PhenoPLIER. By incorporating groups of co-expressed genes, PhenoPLIER can contextualize genetic associations and reveal potential targets missed by single-gene strategies.

Defining the molecular correlate of arteriolar hyalinosis in kidney disease progression by integration of single cell transcriptomic analysis and pathology scoring

Arteriolar hyalinosis in kidneys is an independent predictor of cardiovascular disease, the main cause of mortality in chronic kidney disease (CKD). The underlying molecular mechanisms of protein accumulation in the subendothelial space are not well understood. Using single cell transcriptomic data and whole slide images from kidney biopsies of patients with CKD and acute kidney injury in the Kidney Precision Medicine Project, the molecular signals associated with arteriolar hyalinosis were evaluated. Co-expression network analysis of the endothelial genes yielded three gene set modules as significantly associated with arteriolar hyalinosis. Pathway analysis of these modules showed enrichment of transforming growth factor beta / bone morphogenetic protein (TGFβ / BMP) and vascular endothelial growth factor (VEGF) signaling pathways in the endothelial cell signatures. Ligand-receptor analysis identified multiple integrins and cell adhesion receptors as over-expressed in arteriolar hyalinosis, suggesting a potential role of integrin-mediated TGFβ signaling. Further analysis of arteriolar hyalinosis associated endothelial module genes identified focal segmental glomerular sclerosis as an enriched term. On validation in gene expression profiles from the Nephrotic Syndrome Study Network cohort, one of the three modules was significantly associated with the composite endpoint (> 40% reduction in estimated glomerular filtration rate (eGFR) or kidney failure) independent of age, sex, race, and baseline eGFR, suggesting poor prognosis with elevated expression of genes in this module. Thus, integration of structural and single cell molecular features yielded biologically relevant gene sets, signaling pathways and ligand-receptor interactions, underlying arteriolar hyalinosis and putative targets for therapeutic intervention.

Strong protective effect of the APOL1 p.N264K variant against G2-associated focal segmental glomerulosclerosis and kidney disease

Black Americans have a significantly higher risk of developing chronic kidney disease (CKD), especially focal segmental glomerulosclerosis (FSGS), than European Americans. Two coding variants (G1 and G2) in the APOL1 gene play a major role in this disparity. While 13% of Black Americans carry the high-risk recessive genotypes, only a fraction of these individuals develops FSGS or kidney failure, indicating the involvement of additional disease modifiers. Here, we show that the presence of the APOL1 p.N264K missense variant, when co-inherited with the G2 APOL1 risk allele, substantially reduces the penetrance of the G1G2 and G2G2 high-risk genotypes by rendering these genotypes low-risk. These results align with prior functional evidence showing that the p.N264K variant reduces the toxicity of the APOL1 high-risk alleles. These findings have important implications for our understanding of the mechanisms of APOL1 -associated nephropathy, as well as for the clinical management of individuals with high-risk genotypes that include the G2 allele.

Global Incidence of IgA Nephropathy by Race and Ethnicity: A Systematic Review

Key Points

In 16 studies conducted abroad, IgA nephropathy incidence varied from 0.06 in South Africa to 4.2 per 100,000 in Japan. Globally, the incidence of IgA nephropathy seemed higher in Asians than in non-Asians and higher in male patients than in female patients. Five studies conducted in the United States found no consistent difference in incidence between Black patients and White patients.

Background

The reported incidence of IgA nephropathy varies widely across studies and may vary on the basis of race/ethnicity. This study systematically reviewed the incidence of IgA nephropathy in the United States and other countries and explored variability on the basis of the racial/ethnic composition and other demographic characteristics of different populations.

Methods

This was a systematic review. Studies were eligible for inclusion if they contained data collected from January 1, 1974, to December 31, 2021, and reported IgA nephropathy incidence at a population level (i.e. , cases of IgA nephropathy per 100,000 population).

Results

Five US and 16 international studies were included; three of the US studies reported the race-specific incidence of IgA nephropathy. In the United States, the reported incidence of IgA nephropathy ranged from 0.39 per 100,000 in Tennessee to 1.4 per 100,000 in Minnesota; internationally, IgA nephropathy ranged from 0.06 per 100,000 in South Africa to 4.2 per 100,000 in Japan. Findings regarding the incidence of IgA nephropathy in the United States by race were inconsistent: One study found a higher incidence among White patients compared with Black patients, one study found a lower incidence in White patients, and one study found no difference. Globally, the incidence of IgA nephropathy seemed to be higher in Asian than in non-Asian populations and higher in male patients than in female patients.

Conclusions

Reported incidence of IgA nephropathy varies widely; there is no consensus regarding the relationship between race and IgA nephropathy. Incidence rates seemed to be higher in Asians than non-Asians and in male patients than female patients. We recommend that future studies should report IgA nephropathy incidence rates by race/ethnicity and account for the demographic characteristics of the background population.

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.

A metadata framework for computational phenotypes

With the burgeoning development of computational phenotypes, it is increasingly difficult to identify the right phenotype for the right tasks. This study uses a mixed-methods approach to develop and evaluate a novel metadata framework for retrieval of and reusing computational phenotypes. Twenty active phenotyping researchers from 2 large research networks, Electronic Medical Records and Genomics and Observational Health Data Sciences and Informatics, were recruited to suggest metadata elements. Once consensus was reached on 39 metadata elements, 47 new researchers were surveyed to evaluate the utility of the metadata framework. The survey consisted of 5-Likert multiple-choice questions and open-ended questions. Two more researchers were asked to use the metadata framework to annotate 8 type-2 diabetes mellitus phenotypes. More than 90% of the survey respondents rated metadata elements regarding phenotype definition and validation methods and metrics positively with a score of 4 or 5. Both researchers completed annotation of each phenotype within 60 min. Our thematic analysis of the narrative feedback indicates that the metadata framework was effective in capturing rich and explicit descriptions and enabling the search for phenotypes, compliance with data standards, and comprehensive validation metrics. Current limitations were its complexity for data collection and the entailed human costs.

An atlas of healthy and injured cell states and niches in the human kidney

Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.

Genome-wide association analyses define pathogenic signaling pathways and prioritize drug targets for IgA nephropathy

IgA nephropathy (IgAN) is a progressive form of kidney disease defined by glomerular deposition of IgA. Here we performed a genome-wide association study of 10,146 kidney-biopsy-diagnosed IgAN cases and 28,751 controls across 17 international cohorts. We defined 30 genome-wide significant risk loci explaining 11% of disease risk. A total of 16 loci were new, including TNFSF4/TNFSF18, REL, CD28, PF4V1, LY86, LYN, ANXA3, TNFSF8/TNFSF15, REEP3, ZMIZ1, OVOL1/RELA, ETS1, IGH, IRF8, TNFRSF13B and FCAR. The risk loci were enriched in gene orthologs causing abnormal IgA levels when genetically manipulated in mice. We also observed a positive genetic correlation between IgAN and serum IgA levels. High polygenic score for IgAN was associated with earlier onset of kidney failure. In a comprehensive functional annotation analysis of candidate causal genes, we observed convergence of biological candidates on a common set of inflammatory signaling pathways and cytokine ligand-receptor pairs, prioritizing potential new drug targets.

The chromatin landscape of healthy and injured cell types in the human kidney

There is a need to define regions of gene activation or repression that control human kidney cells in states of health, injury, and repair to understand the molecular pathogenesis of kidney disease and design therapeutic strategies. However, comprehensive integration of gene expression with epigenetic features that define regulatory elements remains a significant challenge. We measured dual single nucleus RNA expression and chromatin accessibility, DNA methylation, and H3K27ac, H3K4me1, H3K4me3, and H3K27me3 histone modifications to decipher the chromatin landscape and gene regulation of the kidney in reference and adaptive injury states. We established a comprehensive and spatially-anchored epigenomic atlas to define the kidney's active, silent, and regulatory accessible chromatin regions across the genome. Using this atlas, we noted distinct control of adaptive injury in different epithelial cell types. A proximal tubule cell transcription factor network of ELF3 , KLF6 , and KLF10 regulated the transition between health and injury, while in thick ascending limb cells this transition was regulated by NR2F1 . Further, combined perturbation of ELF3 , KLF6 , and KLF10 distinguished two adaptive proximal tubular cell subtypes, one of which manifested a repair trajectory after knockout. This atlas will serve as a foundation to facilitate targeted cell-specific therapeutics by reprogramming gene regulatory networks.

Selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse populations

Polygenic risk scores (PRS) have improved in predictive performance supporting their use in clinical practice. Reduced predictive performance of PRS in diverse populations can exacerbate existing health disparities. The NHGRI-funded eMERGE Network is returning a PRS-based genome-informed risk assessment to 25,000 diverse adults and children. We assessed PRS performance, medical actionability, and potential clinical utility for 23 conditions. Standardized metrics were considered in the selection process with additional consideration given to strength of evidence in African and Hispanic populations. Ten conditions were selected with a range of high-risk thresholds: atrial fibrillation, breast cancer, chronic kidney disease, coronary heart disease, hypercholesterolemia, prostate cancer, asthma, type 1 diabetes, obesity, and type 2 diabetes. We developed a pipeline for clinical PRS implementation, used genetic ancestry to calibrate PRS mean and variance, created a framework for regulatory compliance, and developed a PRS clinical report. eMERGE's experience informs the infrastructure needed to implement PRS-based implementation in diverse clinical settings.

CARMA is a new Bayesian model for fine-mapping in genome-wide association meta-analyses

Fine-mapping is commonly used to identify putative causal variants at genome-wide significant loci. Here we propose a Bayesian model for fine-mapping that has several advantages over existing methods, including flexible specification of the prior distribution of effect sizes, joint modeling of summary statistics and functional annotations and accounting for discrepancies between summary statistics and external linkage disequilibrium in meta-analyses. Using simulations, we compare performance with commonly used fine-mapping methods and show that the proposed model has higher power and lower false discovery rate (FDR) when including functional annotations, and higher power, lower FDR and higher coverage for credible sets in meta-analyses. We further illustrate our approach by applying it to a meta-analysis of Alzheimer's disease genome-wide association studies where we prioritize putatively causal variants and genes.

Rare Single Nucleotide and Copy Number Variants and the Etiology of Congenital Obstructive Uropathy: Implications for Genetic Diagnosis

SIGNIFICANCE STATEMENT

Congenital obstructive uropathy (COU) is a prevalent human developmental defect with highly heterogeneous clinical presentations and outcomes. Genetics may refine diagnosis, prognosis, and treatment, but the genomic architecture of COU is largely unknown. Comprehensive genomic screening study of 733 cases with three distinct COU subphenotypes revealed disease etiology in 10.0% of them. We detected no significant differences in the overall diagnostic yield among COU subphenotypes, with characteristic variable expressivity of several mutant genes. Our findings therefore may legitimize a genetic first diagnostic approach for COU, especially when burdening clinical and imaging characterization is not complete or available.

BACKGROUND

Congenital obstructive uropathy (COU) is a common cause of developmental defects of the urinary tract, with heterogeneous clinical presentation and outcome. Genetic analysis has the potential to elucidate the underlying diagnosis and help risk stratification.

METHODS

We performed a comprehensive genomic screen of 733 independent COU cases, which consisted of individuals with ureteropelvic junction obstruction ( n =321), ureterovesical junction obstruction/congenital megaureter ( n =178), and COU not otherwise specified (COU-NOS; n =234).

RESULTS

We identified pathogenic single nucleotide variants (SNVs) in 53 (7.2%) cases and genomic disorders (GDs) in 23 (3.1%) cases. We detected no significant differences in the overall diagnostic yield between COU sub-phenotypes, and pathogenic SNVs in several genes were associated to any of the three categories. Hence, although COU may appear phenotypically heterogeneous, COU phenotypes are likely to share common molecular bases. On the other hand, mutations in TNXB were more often identified in COU-NOS cases, demonstrating the diagnostic challenge in discriminating COU from hydronephrosis secondary to vesicoureteral reflux, particularly when diagnostic imaging is incomplete. Pathogenic SNVs in only six genes were found in more than one individual, supporting high genetic heterogeneity. Finally, convergence between data on SNVs and GDs suggest MYH11 as a dosage-sensitive gene possibly correlating with severity of COU.

CONCLUSIONS

We established a genomic diagnosis in 10.0% of COU individuals. The findings underscore the urgent need to identify novel genetic susceptibility factors to COU to better define the natural history of the remaining 90% of cases without a molecular diagnosis.

Polygenic risk affects the penetrance of monogenic kidney disease

Background

Chronic kidney disease (CKD) is a genetically complex disease determined by an interplay of monogenic, polygenic, and environmental risks. Most forms of monogenic kidney diseases have incomplete penetrance and variable expressivity. It is presently unknown if some of the variability in penetrance can be attributed to polygenic factors.

Methods

Using the UK Biobank (N=469,835 participants) and the All of Us (N=98,622 participants) datasets, we examined two most common forms of monogenic kidney disorders, autosomal dominant polycystic kidney disease (ADPKD) caused by deleterious variants in the PKD1 or PKD2 genes, and COL4A-associated nephropathy (COL4A-AN caused by deleterious variants in COL4A3, COL4A4, or COL4A5 genes). We used the eMERGE-III electronic CKD phenotype to define cases (estimated glomerular filtration rate (eGFR) <60 mL/min/1.73m2 or kidney failure) and controls (eGFR >90 mL/min/1.73m2 in the absence of kidney disease diagnoses). The effects of the genome-wide polygenic score (GPS) for CKD were tested in monogenic variant carriers and non-carriers using logistic regression controlling for age, sex, diabetes, and genetic ancestry.

Results

As expected, the carriers of known pathogenic and rare predicted loss-of-function variants in PKD1 or PKD2 had a high risk of CKD (ORmeta=17.1, 95% CI: 11.1-26.4, P=1.8E-37). The GPS was comparably predictive of CKD in both ADPKD variant carriers (ORmeta=2.28 per SD, 95%CI: 1.55-3.37, P=2.6E-05) and non-carriers (ORmeta=1.72 per SD, 95% CI=1.69-1.76, P< E-300) independent of age, sex, diabetes, and genetic ancestry. Compared to the middle tertile of the GPS distribution for non-carriers, ADPKD variant carriers in the top tertile had a 54-fold increased risk of CKD, while ADPKD variant carriers in the bottom tertile had only a 3-fold increased risk of CKD. Similarly, the GPS was predictive of CKD in both COL4-AN variant carriers (ORmeta=1.78, 95% CI=1.22-2.58, P=2.38E-03) and non-carriers (ORmeta=1.70, 95%CI: 1.68-1.73 P

Conclusions

Variable penetrance of kidney disease in ADPKD and COL4-AN is partially explained by differences in polygenic risk profiles. Accounting for polygenic factors has the potential to improve risk stratification in monogenic kidney disease and may have implications for genetic counseling.

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Key Words

• APOL1
• GWAS
• chronic kidney disease (CKD)
• polygenic risk score (PRS)

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MESH Headings Collapse

Grants

• OT2 OD026556 NIH HHS
• U2C OD023196 NIH HHS
• OT2 OD026551 NIH HHS
• U24 OD023121 NIH HHS
• OT2 OD026552 NIH HHS
• OT2 OD026549 NIH HHS
• OT2 OD025337 NIH HHS
• OT2 OD025277 NIH HHS
• OT2 OD026555 NIH HHS
• OT2 OD026550 NIH HHS
• OT2 OD026553 NIH HHS
• OT2 OD023205 NIH HHS
• U01 HG008680 NHGRI NIH HHS
• OT2 OD025276 NIH HHS
• OT2 OD026557 NIH HHS
• U24 OD023163 NIH HHS
• OT2 OD023206 NIH HHS
• R01 LM013061 NLM NIH HHS
• U24 OD023176 NIH HHS
• OT2 OD026548 NIH HHS
• OT2 OD025315 NIH HHS
• K25 DK128563 NIDDK NIH HHS
• OT2 OD026554 NIH HHS
• UL1 TR001873 NCATS NIH HHS

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Affiliation(s)

Atlas Khan Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
Ning Shang Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
Jordan G. Nestor Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
Chunhua Weng Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
George Hripcsak Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
Peter C. Harris Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota 55905, USA
Ali G. Gharavi Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
Krzysztof Kiryluk Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY

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Clinical and Genetic Characteristics of CKD Patients with High-Risk APOL1 Genotypes

SIGNIFICANCE STATEMENT

APOL1 high-risk genotypes confer a significant risk of kidney disease, but variability in patient outcomes suggests the presence of modifiers of the APOL1 effect. We show that a diverse population of CKD patients with high-risk APOL1 genotypes have an increased lifetime risk of kidney failure and higher eGFR decline rates, with a graded risk among specific high-risk genotypes. CKD patients with high-risk APOL1 genotypes have a lower diagnostic yield for monogenic kidney disease. Exome sequencing revealed enrichment of rare missense variants within the inflammasome pathway modifying the effect of APOL1 risk genotypes, which may explain some clinical heterogeneity.

BACKGROUND

APOL1 genotype has significant effects on kidney disease development and progression that vary among specific causes of kidney disease, suggesting the presence of effect modifiers.

METHODS

We assessed the risk of kidney failure and the eGFR decline rate in patients with CKD carrying high-risk ( N =239) and genetically matched low-risk ( N =1187) APOL1 genotypes. Exome sequencing revealed monogenic kidney diseases. Exome-wide association studies and gene-based and gene set-based collapsing analyses evaluated genetic modifiers of the effect of APOL1 genotype on CKD.

RESULTS

Compared with genetic ancestry-matched patients with CKD with low-risk APOL1 genotypes, those with high-risk APOL1 genotypes had a higher risk of kidney failure (Hazard Ratio [HR]=1.58), a higher decline in eGFR (6.55 versus 3.63 ml/min/1.73 m 2 /yr), and were younger at time of kidney failure (45.1 versus 53.6 years), with the G1/G1 genotype demonstrating the highest risk. The rate for monogenic kidney disorders was lower among patients with CKD with high-risk APOL1 genotypes (2.5%) compared with those with low-risk genotypes (6.7%). Gene set analysis identified an enrichment of rare missense variants in the inflammasome pathway in individuals with high-risk APOL1 genotypes and CKD (odds ratio=1.90).

CONCLUSIONS

In this genetically matched cohort, high-risk APOL1 genotypes were associated with an increased risk of kidney failure and eGFR decline rate, with a graded risk between specific high-risk genotypes and a lower rate of monogenic kidney disease. Rare missense variants in the inflammasome pathway may act as genetic modifiers of APOL1 effect on kidney disease.

Multi-population genome-wide association study implicates immune and non-immune factors in pediatric steroid-sensitive nephrotic syndrome

Pediatric steroid-sensitive nephrotic syndrome (pSSNS) is the most common childhood glomerular disease. Previous genome-wide association studies (GWAS) identified a risk locus in the HLA Class II region and three additional independent risk loci. But the genetic architecture of pSSNS, and its genetically driven pathobiology, is largely unknown. Here, we conduct a multi-population GWAS meta-analysis in 38,463 participants (2440 cases). We then conduct conditional analyses and population specific GWAS. We discover twelve significant associations-eight from the multi-population meta-analysis (four novel), two from the multi-population conditional analysis (one novel), and two additional novel loci from the European meta-analysis. Fine-mapping implicates specific amino acid haplotypes in HLA-DQA1 and HLA-DQB1 driving the HLA Class II risk locus. Non-HLA loci colocalize with eQTLs of monocytes and numerous T-cell subsets in independent datasets. Colocalization with kidney eQTLs is lacking but overlap with kidney cell open chromatin suggests an uncharacterized disease mechanism in kidney cells. A polygenic risk score (PRS) associates with earlier disease onset. Altogether, these discoveries expand our knowledge of pSSNS genetic architecture across populations and provide cell-specific insights into its molecular drivers. Evaluating these associations in additional cohorts will refine our understanding of population specificity, heterogeneity, and clinical and molecular associations.

Returning integrated genomic risk and clinical recommendations: The eMERGE study

PURPOSE

Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk.

METHODS

To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results.

RESULTS

GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022.

CONCLUSION

Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

Genomic Disorders in CKD across the Lifespan

SIGNIFICANCE STATEMENT

Pathogenic structural genetic variants, also known as genomic disorders, have been associated with pediatric CKD. This study extends those results across the lifespan, with genomic disorders enriched in both pediatric and adult patients compared with controls. In the Chronic Renal Insufficiency Cohort study, genomic disorders were also associated with lower serum Mg, lower educational performance, and a higher risk of death. A phenome-wide association study confirmed the link between kidney disease and genomic disorders in an unbiased way. Systematic detection of genomic disorders can provide a molecular diagnosis and refine prediction of risk and prognosis.

BACKGROUND

Genomic disorders (GDs) are associated with many comorbid outcomes, including CKD. Identification of GDs has diagnostic utility.

METHODS

We examined the prevalence of GDs among participants in the Chronic Kidney Disease in Children (CKiD) cohort II ( n =248), Chronic Renal Insufficiency Cohort (CRIC) study ( n =3375), Columbia University CKD Biobank (CU-CKD; n =1986), and the Family Investigation of Nephropathy and Diabetes (FIND; n =1318) compared with 30,746 controls. We also performed a phenome-wide association analysis (PheWAS) of GDs in the electronic MEdical Records and GEnomics (eMERGE; n =11,146) cohort.

RESULTS

We found nine out of 248 (3.6%) CKiD II participants carried a GD, replicating prior findings in pediatric CKD. We also identified GDs in 72 out of 6679 (1.1%) adult patients with CKD in the CRIC, CU-CKD, and FIND cohorts, compared with 199 out of 30,746 (0.65%) GDs in controls (OR, 1.7; 95% CI, 1.3 to 2.2). Among adults with CKD, we found recurrent GDs at the 1q21.1, 16p11.2, 17q12, and 22q11.2 loci. The 17q12 GD (diagnostic of renal cyst and diabetes syndrome) was most frequent, present in 1:252 patients with CKD and diabetes. In the PheWAS, dialysis and neuropsychiatric phenotypes were the top associations with GDs. In CRIC participants, GDs were associated with lower serum magnesium, lower educational achievement, and higher mortality risk.

CONCLUSION

Undiagnosed GDs are detected both in children and adults with CKD. Identification of GDs in these patients can enable a precise genetic diagnosis, inform prognosis, and help stratify risk in clinical studies. GDs could also provide a molecular explanation for nephropathy and comorbidities, such as poorer neurocognition for a subset of patients.

Abstract MP19: An eGFR Polygenic Score Predicts Chronic Kidney Disease in African Americans

Chronic kidney disease (CKD) is a risk factor for cardiovascular disease and early death. Genetic factors contribute to CKD, and recently, polygenic scores (PGS) have been developed to quantify risk for complex diseases, such as CKD. However, African ancestry populations are underrepresented in both CKD genetic studies and PGS development overall; moreover, European-ancestry derived PGSs demonstrate diminished predictive performance in African ancestry populations. This study aimed to develop a PGS for CKD using genotype and phenotype data from African American (AA) participants of observational cohort studies. We obtained score weights from a meta-analysis of genome-wide association studies (GWAS) for estimated glomerular filtration rate (eGFR) in the Million Veteran Program (MVP) and Reasons for Geographical and Racial Differences in Stroke (REGARDS) Study (total n~66,000). We then optimized the PGS in a cohort of AAs from the Hypertension Genetic Epidemiology Network (HyperGEN) Study (n~1,900) using the PRS-CS software and evaluated the predictive performance of the PGS at multiple global shrinkage parameters. We further adjusted the PGS for APOL1 risk status. In HyperGEN, the eGFR-based PGS was significantly associated with the odds of prevalent CKD—defined as baseline eGFR <60 mL/min/1.73m 2 — in logistic regression models adjusted for age, sex, and population structure. Further, accounting for APOL1 risk status—a putative variant for CKD unique to those of sub-Saharan African descent—improved the score’s accuracy, with the APOL1 -adjusted PGS explaining 1.9% (1.1% without APOL1 ) of the variance in CKD and an area under the curve (AUC) of 58.9% [95% CI: 53.0%-64.9%] (without APOL1 , 58.2% [95% CI: 52.3%-64.1%]). Sensitivity analyses and validation in external cohorts, as well as comparisons to previously published PGS, are ongoing. In this study, we developed a PGS that was significantly associated with CKD with improved predictive accuracy in AAs over previously published PGS.

BIGKnock: fine-mapping gene-based associations via knockoff analysis of biobank-scale data

We propose BIGKnock (BIobank-scale Gene-based association test via Knockoffs), a computationally efficient gene-based testing approach for biobank-scale data, that leverages long-range chromatin interaction data, and performs conditional genome-wide testing via knockoffs. BIGKnock can prioritize causal genes over proxy associations at a locus. We apply BIGKnock to the UK Biobank data with 405,296 participants for multiple binary and quantitative traits, and show that relative to conventional gene-based tests, BIGKnock produces smaller sets of significant genes that contain the causal gene(s) with high probability. We further illustrate its ability to pinpoint potential causal genes at [Formula: see text] of the associated loci.

Evaluation of the portability of computable phenotypes with natural language processing in the eMERGE network

The electronic Medical Records and Genomics (eMERGE) Network assessed the feasibility of deploying portable phenotype rule-based algorithms with natural language processing (NLP) components added to improve performance of existing algorithms using electronic health records (EHRs). Based on scientific merit and predicted difficulty, eMERGE selected six existing phenotypes to enhance with NLP. We assessed performance, portability, and ease of use. We summarized lessons learned by: (1) challenges; (2) best practices to address challenges based on existing evidence and/or eMERGE experience; and (3) opportunities for future research. Adding NLP resulted in improved, or the same, precision and/or recall for all but one algorithm. Portability, phenotyping workflow/process, and technology were major themes. With NLP, development and validation took longer. Besides portability of NLP technology and algorithm replicability, factors to ensure success include privacy protection, technical infrastructure setup, intellectual property agreement, and efficient communication. Workflow improvements can improve communication and reduce implementation time. NLP performance varied mainly due to clinical document heterogeneity; therefore, we suggest using semi-structured notes, comprehensive documentation, and customization options. NLP portability is possible with improved phenotype algorithm performance, but careful planning and architecture of the algorithms is essential to support local customizations.

Genetic regulation of serum IgA levels and susceptibility to common immune, infectious, kidney, and cardio-metabolic traits

Immunoglobulin A (IgA) mediates mucosal responses to food antigens and the intestinal microbiome and is involved in susceptibility to mucosal pathogens, celiac disease, inflammatory bowel disease, and IgA nephropathy. We performed a genome-wide association study of serum IgA levels in 41,263 individuals of diverse ancestries and identified 20 genome-wide significant loci, including 9 known and 11 novel loci. Co-localization analyses with expression QTLs prioritized candidate genes for 14 of 20 significant loci. Most loci encoded genes that produced immune defects and IgA abnormalities when genetically manipulated in mice. We also observed positive genetic correlations of serum IgA levels with IgA nephropathy, type 2 diabetes, and body mass index, and negative correlations with celiac disease, inflammatory bowel disease, and several infections. Mendelian randomization supported elevated serum IgA as a causal factor in IgA nephropathy. African ancestry was consistently associated with higher serum IgA levels and greater frequency of IgA-increasing alleles compared to other ancestries. Our findings provide novel insights into the genetic regulation of IgA levels and its potential role in human disease.

Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

Multiancestral polygenic risk score for pediatric asthma

BACKGROUND

Asthma is the most common chronic condition in children and the third leading cause of hospitalization in pediatrics. The genome-wide association study catalog reports 140 studies with genome-wide significance. A polygenic risk score (PRS) with predictive value across ancestries has not been evaluated for this important trait.

OBJECTIVES

This study aimed to train and validate a PRS relying on genetic determinants for asthma to provide predictions for disease occurrence in pediatric cohorts of diverse ancestries.

METHODS

This study applied a Bayesian regression framework method using the Trans-National Asthma Genetic Consortium genome-wide association study summary statistics to derive a multiancestral PRS score, used one Electronic Medical Records and Genomics (eMERGE) cohort as a training set, used a second independent eMERGE cohort to validate the score, and used the UK Biobank data to replicate the findings. A phenome-wide association study was performed using the PRS to identify shared genetic etiology with other phenotypes.

RESULTS

The multiancestral asthma PRS was associated with asthma in the 2 pediatric validation datasets. Overall, the multiancestral asthma PRS has an area under the curve (AUC) of 0.70 (95% CI, 0.69-0.72) in the pediatric validation 1 and AUC of 0.66 (0.65-0.66) in the pediatric validation 2 datasets. We found significant discrimination across pediatric subcohorts of European (AUC, 95% CI, 0.60 and 0.66), African (AUC, 95% CI, 0.61 and 0.66), admixed American (AUC, 0.64 and 0.70), Southeast Asian (AUC, 0.65), and East Asian (AUC, 0.73) ancestry. Pediatric participants with the top 5% PRS had 2.80 to 5.82 increased odds of asthma compared to the bottom 5% across the training, validation 1, and validation 2 cohorts when adjusted for ancestry. Phenome-wide association study analysis confirmed the strong association of the identified PRS with asthma (odds ratio, 2.71, PFDR = 3.71 × 10-65) and related phenotypes.

CONCLUSIONS

A multiancestral PRS for asthma based on Bayesian posterior genomic effect sizes identifies increased odds of pediatric asthma.

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.

Incorporating genetics services into adult kidney disease care

Studies have shown that as many as 1 in 10 adults with chronic kidney disease has a monogenic form of disease. However, genetic services in adult nephrology are limited. An adult Kidney Genetics Clinic was established within the nephrology division at a large urban academic medical center to increase access to genetic services and testing in adults with kidney disease. Between June 2019 and December 2021, a total of 363 patients were referred to the adult Kidney Genetics Clinic. Of those who completed genetic testing, a positive diagnostic finding was identified in 27.1%, a candidate diagnostic finding was identified in 6.7% of patients, and a nondiagnostic positive finding was identified in an additional 8.6% of patients, resulting in an overall yield of 42.4% for clinically relevant genetic findings in tested patients. A genetic diagnosis had implications for medical management, family member testing, and eligibility for clinical trials. With the utilization of telemedicine, genetic services reached a diverse geographic and patient population. Genetic education efforts were integral to the clinic's success, as they increased visibility and helped providers identify appropriate referrals. Ongoing access to genomic services will remain a fundamental component of patient care in adults with kidney disease.

Cystatin C is associated with adverse COVID-19 outcomes in diverse populations

COVID-19 has highly variable clinical courses. The search for prognostic host factors for COVID-19 outcome is a priority. We performed logistic regression for ICU admission against a polygenic score (PGS) for Cystatin C (CyC) production in patients with COVID-19. We analyzed the predictive value of longitudinal plasma CyC levels in an independent cohort of patients hospitalized with COVID-19. In four cohorts spanning European and African ancestry populations, we identified a significant association between CyC-production PGS and odds of critical illness (n cases=2,319), with the strongest association captured in the UKB cohort (OR 2.13, 95% CI 1.58-2.87, p=7.12e-7). Plasma proteomics from an independent cohort of hospitalized COVID-19 patients (n cases = 131) demonstrated that CyC production was associated with COVID-specific mortality (p=0.0007). Our findings suggest that CyC may be useful for stratification of patients and it has functional role in the host response to COVID-19.

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Cystatin C varies independently of renal function in COVID-19

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A polygenic score for cystatin C production predicts critical COVID-19 illness

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Elevated serum cystatin C is associated with COVID-19 mortality

Clinicopathologic Significance of Predominant Lambda Light Chain Deposition in IgA Nephropathy

Introduction

IgA nephropathy (IgAN) differs from other glomerular diseases by the frequently predominant lambda over kappa light chain deposition. Using the Cure Glomerulonephropathy (CureGN) IgAN cohort, we aimed to determine whether predominant lambda chain deposition is associated with worse clinical outcomes or histopathologic markers of more active disease.

Methods

Patients were categorized based on the intensity of light chain staining. The lambda dominant (LD) group was defined by a difference in intensity score of lambda minus kappa ≥ 1+ and the kappa-lambda codominant (KL) group by a difference < 1+. We compared the clinical course of patients in each category from the time of kidney biopsy and time of enrollment into CureGN to the time of remission (proteinuria < 0.3 g/g), 50% reduction in estimated glomerular filtration rate (eGFR), or progression to end-stage kidney disease (ESKD). We also analyzed differences in histopathologic characteristics between the 2 groups.

Results

Among 440 patients, we found no significant differences between groups in baseline clinical characteristics nor in rates of remission, 50% reduction in eGFR, or progression to ESKD. Patients in the LD group had a modestly greater frequency of IgG staining ≥ 1+. The biopsy results of 234 patients reviewed by CureGN pathologists revealed a greater frequency of endocapillary hypercellularity (51.1% vs. 36.3%, P = 0.04) in the LD group, but no other significant difference in histopathologic features.

Conclusion

In IgAN, we found an association between lambda predominance and increased endocapillary hypercellularity, but no association with clinical outcomes.

Genome-wide polygenic score to predict chronic kidney disease across ancestries

Chronic kidney disease (CKD) is a common complex condition associated with high morbidity and mortality. Polygenic prediction could enhance CKD screening and prevention; however, this approach has not been optimized for ancestrally diverse populations. By combining APOL1 risk genotypes with genome-wide association studies (GWAS) of kidney function, we designed, optimized and validated a genome-wide polygenic score (GPS) for CKD. The new GPS was tested in 15 independent cohorts, including 3 cohorts of European ancestry (n = 97,050), 6 cohorts of African ancestry (n = 14,544), 4 cohorts of Asian ancestry (n = 8,625) and 2 admixed Latinx cohorts (n = 3,625). We demonstrated score transferability with reproducible performance across all tested cohorts. The top 2% of the GPS was associated with nearly threefold increased risk of CKD across ancestries. In African ancestry cohorts, the APOL1 risk genotype and polygenic component of the GPS had additive effects on the risk of CKD.