A Drosophila model to screen Alport syndrome COL4A5 variants for their functional pathogenicity.

Alport syndrome is a hereditary chronic kidney disease, attributed to rare pathogenic variants in either of three collagen genes (COL4A3/4/5) with most localized in COL4A5. Trimeric type IV Collagen α3α4α5 is essential for the glomerular basement membrane that forms the kidney filtration barrier. A means to functionally assess the many candidate variants and determine pathogenicity is urgently needed. We used Drosophila, an established model for kidney disease, and identify Col4a1 as the functional homolog of human COL4A5 in the fly nephrocyte (equivalent of human podocyte). Fly nephrocytes deficient for Col4a1 showed an irregular and thickened basement membrane and significantly reduced nephrocyte filtration function. This phenotype was restored by expressing human reference (wildtype) COL4A5, but not by COL4A5 carrying any of three established pathogenic patient-derived variants. We then screened seven additional patient COL4A5 variants; their ClinVar classification was either likely pathogenic or of uncertain significance. The findings support pathogenicity for four of these variants; the three others were found benign. Thus, demonstrating the effectiveness of this Drosophila in vivo kidney platform in providing the urgently needed variant-level functional validation.

Unbiased kidney-centric molecular categorization of chronic kidney disease as a step towards precision medicine.

Current classification of chronic kidney disease (CKD) into stages using indirect systemic measures (estimated glomerular filtration rate (eGFR) and albuminuria) is agnostic to the heterogeneity of underlying molecular processes in the kidney thereby limiting precision medicine approaches. To generate a novel CKD categorization that directly reflects within kidney disease drivers we analyzed publicly available transcriptomic data from kidney biopsy tissue. A Self-Organizing Maps unsupervised artificial neural network machine-learning algorithm was used to stratify a total of 369 patients with CKD and 46 living kidney donors as healthy controls. Unbiased stratification of the discovery cohort resulted in identification of four novel molecular categories of disease termed CKD-Blue, CKD-Gold, CKD-Olive, CKD-Plum that were replicated in independent CKD and diabetic kidney disease datasets and can be further tested on any external data at kidneyclass.org. Each molecular category spanned across CKD stages and histopathological diagnoses and represented transcriptional activation of distinct biological pathways. Disease progression rates were highly significantly different between the molecular categories. CKD-Gold displayed rapid progression, with significant eGFR-adjusted Cox regression hazard ratio of 5.6 [1.01-31.3] for kidney failure and hazard ratio of 4.7 [1.3-16.5] for composite of kidney failure or a 40% or more eGFR decline. Urine proteomics revealed distinct patterns between the molecular categories, and a 25-protein signature was identified to distinguish CKD-Gold from other molecular categories. Thus, patient stratification based on kidney tissue omics offers a gateway to non-invasive biomarker-driven categorization and the potential for future clinical implementation, as a key step towards precision medicine in CKD.

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 focal segmental glomerulosclerosis, in the Nephrotic Syndrome Study Network (NEPTUNE) and Cure Glomerulonephropathy (CureGN) cohorts with >24 months of follow-up. Multivariable Cox proportional hazards models were fit for time to composite outcome (end-stage kidney disease or 40% decline in estimated glomerular filtration rate (eGFR) and eGFR <60 ml/min/1.73 m2) and proteinuria remission (UPCR <0.3 mg/mg). RESULTS: Among the 1,516 adults and children in the study, 528 (35%) participants had focal segmental glomerulosclerosis, 499 (33%) had minimal change disease, and 489 (32%) had membranous nephropathy. Median (IQR) time from biopsy until the initial study urinalysis was 260 days (49, 750), and 498 (33%) participants were positive for hematuria. Participants with hematuria compared to those without, were older (37 [16, 55] vs 33 years [12, 55]), more likely to have an underlying diagnosis of membranous nephropathy (44% vs 27%), had shorter time since biopsy (139 [27, 477] vs 325 [89, 878] days) and higher UPCR (3.8 [1.4, 8.0] vs 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 riskof reaching the composite outcome (HR 1.31 [1.04, 1.65], p-value 0.02) and lower rate of reaching proteinuria remission (HR 0.80 [0.65-0.98], 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 remission of proteinuria.

MLL-AF4 cooperates with PAF1 and FACT to drive high-density enhancer interactions in leukemia.

Aberrant enhancer activation is a key mechanism driving oncogene expression in many cancers. While much is known about the regulation of larger chromosome domains in eukaryotes, the details of enhancer-promoter interactions remain poorly understood. Recent work suggests co-activators like BRD4 and Mediator have little impact on enhancer-promoter interactions. In leukemias controlled by the MLL-AF4 fusion protein, we use the ultra-high resolution technique Micro-Capture-C (MCC) to show that MLL-AF4 binding promotes broad, high-density regions of enhancer-promoter interactions at a subset of key targets. These enhancers are enriched for transcription elongation factors like PAF1C and FACT, and the loss of these factors abolishes enhancer-promoter contact. This work not only provides an additional model for how MLL-AF4 is able to drive high levels of transcription at key genes in leukemia but also suggests a more general model linking enhancer-promoter crosstalk and transcription elongation.

An integrated organoid omics map extends modeling potential of kidney disease.

Kidney organoids are a promising model to study kidney disease, but their use is constrained by limited knowledge of their functional protein expression profile. Here, we define the organoid proteome and transcriptome trajectories over culture duration and upon exposure to TNFα, a cytokine stressor. Older organoids increase deposition of extracellular matrix but decrease expression of glomerular proteins. Single cell transcriptome integration reveals that most proteome changes localize to podocytes, tubular and stromal cells. TNFα treatment of organoids results in 322 differentially expressed proteins, including cytokines and complement components. Transcript expression of these 322 proteins is significantly higher in individuals with poorer clinical outcomes in proteinuric kidney disease. Key TNFα-associated protein (C3 and VCAM1) expression is increased in both human tubular and organoid kidney cell populations, highlighting the potential for organoids to advance biomarker development. By integrating kidney organoid omic layers, incorporating a disease-relevant cytokine stressor and comparing with human data, we provide crucial evidence for the functional relevance of the kidney organoid model to human kidney disease.

SGLT2 inhibitors mitigate kidney tubular metabolic and mTORC1 perturbations in youth-onset type 2 diabetes.

The molecular mechanisms of sodium-glucose cotransporter-2 (SGLT2) inhibitors (SGLT2i) remain incompletely understood. Single-cell RNA sequencing and morphometric data were collected from research kidney biopsies donated by young persons with type 2 diabetes (T2D), aged 12 to 21 years, and healthy controls (HCs). Participants with T2D were obese and had higher estimated glomerular filtration rates and mesangial and glomerular volumes than HCs. Ten T2D participants had been prescribed SGLT2i (T2Di[+]) and 6 not (T2Di[-]). Transcriptional profiles showed SGLT2 expression exclusively in the proximal tubular (PT) cluster with highest expression in T2Di(-) patients. However, transcriptional alterations with SGLT2i treatment were seen across nephron segments, particularly in the distal nephron. SGLT2i treatment was associated with suppression of transcripts in the glycolysis, gluconeogenesis, and tricarboxylic acid cycle pathways in PT, but had the opposite effect in thick ascending limb. Transcripts in the energy-sensitive mTORC1-signaling pathway returned toward HC levels in all tubular segments in T2Di(+), consistent with a diabetes mouse model treated with SGLT2i. Decreased levels of phosphorylated S6 protein in proximal and distal tubules in T2Di(+) patients confirmed changes in mTORC1 pathway activity. We propose that SGLT2i treatment benefits the kidneys by mitigating diabetes-induced metabolic perturbations via suppression of mTORC1 signaling in kidney tubules.

Single-cell transcriptomics reveals a mechanosensitive injury signaling pathway in early diabetic nephropathy.

BACKGROUND: Diabetic nephropathy (DN) is the leading cause of end-stage renal disease, and histopathologic glomerular lesions are among the earliest structural alterations of DN. However, the signaling pathways that initiate these glomerular alterations are incompletely understood. METHODS: To delineate the cellular and molecular basis for DN initiation, we performed single-cell and bulk RNA sequencing of renal cells from type 2 diabetes mice (BTBR ob/ob) at the early stage of DN. RESULTS: Analysis of differentially expressed genes revealed glucose-independent responses in glomerular cell types. The gene regulatory network upstream of glomerular cell programs suggested the activation of mechanosensitive transcriptional pathway MRTF-SRF predominantly taking place in mesangial cells. Importantly, activation of MRTF-SRF transcriptional pathway was also identified in DN glomeruli in independent patient cohort datasets. Furthermore, ex vivo kidney perfusion suggested that the regulation of MRTF-SRF is a common mechanism in response to glomerular hyperfiltration. CONCLUSIONS: Overall, our study presents a comprehensive single-cell transcriptomic landscape of early DN, highlighting mechanosensitive signaling pathways as novel targets of diabetic glomerulopathy.

A contiguous de novo genome assembly of sugar beet EL10 (Beta vulgaris L.).

A contiguous assembly of the inbred 'EL10' sugar beet (Beta vulgaris ssp. vulgaris) genome was constructed using PacBio long-read sequencing, BioNano optical mapping, Hi-C scaffolding, and Illumina short-read error correction. The EL10.1 assembly was 540 Mb, of which 96.2% was contained in nine chromosome-sized pseudomolecules with lengths from 52 to 65 Mb, and 31 contigs with a median size of 282 kb that remained unassembled. Gene annotation incorporating RNA-seq data and curated sequences via the MAKER annotation pipeline generated 24,255 gene models. Results indicated that the EL10.1 genome assembly is a contiguous genome assembly highly congruent with the published sugar beet reference genome. Gross duplicate gene analyses of EL10.1 revealed little large-scale intra-genome duplication. Reduced gene copy number for well-annotated gene families relative to other core eudicots was observed, especially for transcription factors. Variation in genome size in B. vulgaris was investigated by flow cytometry among 50 individuals producing estimates from 633 to 875 Mb/1C. Read-depth mapping with short-read whole-genome sequences from other sugar beet germplasm suggested that relatively few regions of the sugar beet genome appeared associated with high-copy number variation.

Epigenome-wide meta-analysis identifies DNA methylation biomarkers associated with diabetic kidney disease.

Type 1 diabetes affects over nine million individuals globally, with approximately 40% developing diabetic kidney disease. Emerging evidence suggests that epigenetic alterations, such as DNA methylation, are involved in diabetic kidney disease. Here we assess differences in blood-derived genome-wide DNA methylation associated with diabetic kidney disease in 1304 carefully characterised individuals with type 1 diabetes and known renal status from two cohorts in the United Kingdom-Republic of Ireland and Finland. In the meta-analysis, we identify 32 differentially methylated CpGs in diabetic kidney disease in type 1 diabetes, 18 of which are located within genes differentially expressed in kidneys or correlated with pathological traits in diabetic kidney disease. We show that methylation at 21 of the 32 CpGs predict the development of kidney failure, extending the knowledge and potentially identifying individuals at greater risk for diabetic kidney disease in type 1 diabetes.

Multi-Scalar Data Integration Links Glomerular Angiopoietin-Tie Signaling Pathway Activation With Progression of Diabetic Kidney Disease.

Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease (ESKD). Prognostic biomarkers reflective of underlying molecular mechanisms are critically needed for effective management of DKD. A three-marker panel was derived from a proteomics analysis of plasma samples by an unbiased machine learning approach from participants (N = 58) in the Clinical Phenotyping and Resource Biobank study. In combination with standard clinical parameters, this panel improved prediction of the composite outcome of ESKD or a 40% decline in glomerular filtration rate. The panel was validated in an independent group (N = 68), who also had kidney transcriptomic profiles. One marker, plasma angiopoietin 2 (ANGPT2), was significantly associated with outcomes in cohorts from the Cardiovascular Health Study (N = 3,183) and the Chinese Cohort Study of Chronic Kidney Disease (N = 210). Glomerular transcriptional angiopoietin/Tie (ANG-TIE) pathway scores, derived from the expression of 154 ANG-TIE signaling mediators, correlated positively with plasma ANGPT2 levels and kidney outcomes. Higher receptor expression in glomeruli and higher ANG-TIE pathway scores in endothelial cells corroborated potential functional effects in the kidney from elevated plasma ANGPT2 levels. Our work suggests that ANGPT2 is a promising prognostic endothelial biomarker with likely functional impact on glomerular pathogenesis in DKD.

Molecular programs associated with glomerular hyperfiltration in early diabetic kidney disease.

Hyperfiltration is a state of high glomerular filtration rate (GFR) observed in early diabetes that damages glomeruli, resulting in an iterative process of increasing filtration load on fewer and fewer remaining functional glomeruli. To delineate underlying cellular mechanisms of damage associated with hyperfiltration, transcriptional profiles of kidney biopsies from Pima Indians with type 2 diabetes with or without early-stage diabetic kidney disease were grouped into two hyperfiltration categories based on annual iothalamate GFR measurements. Twenty-six participants with a peak GFR measurement within two years of biopsy were categorized as the hyperfiltration group, and 26 in whom biopsy preceded peak GFR by over two years were considered pre-hyperfiltration. The hyperfiltration group had higher hemoglobin A1c, higher urine albumin-to-creatinine ratio, increased glomerular basement membrane width and lower podocyte density compared to the pre-hyperfiltration group. A glomerular 1240-gene transcriptional signature identified in the hyperfiltration group was enriched for endothelial stress response signaling genes, including endothelin-1, tec-kinase and transforming growth factor-ß1 pathways, with the majority of the transcripts mapped to endothelial and inflammatory cell clusters in kidney single cell transcriptional data. Thus, our analysis reveals molecular pathomechanisms associated with hyperfiltration in early diabetic kidney disease involving putative ligand-receptor pairs with downstream intracellular targets linked to cellular crosstalk between endothelial and mesangial cells.

Comparing Kidney Health Outcomes in Children, Adolescents, and Adults With Focal Segmental Glomerulosclerosis.

Importance: Focal segmental glomerulosclerosis (FSGS) is a common cause of end-stage kidney disease (ESKD) across the lifespan. While 10% to 15% of children and 3% of adults who develop ESKD have FSGS, it remains uncertain whether the natural history differs in pediatric vs adult patients, and this uncertainty contributes to the exclusion of children and adolescents in clinical trials. Objective: To examine whether there are differences in the kidney health outcomes among children, adolescents, and adults with FSGS. Design, Setting, and Participants: This cohort study used pooled and parallel analyses, completed July 5, 2022, from 3 complimentary data sources: (1) Nephrotic Syndrome Rare Disease Clinical Research Network (NEPTUNE); (2) FSGS clinical trial (FSGS-CT); and (3) Kidney Research Network (KRN). NEPTUNE is a multicenter US/Canada cohort study; FSGS-CT is a multicenter US/Canada clinical trial; and KRN is a multicenter US electronic health record-based registry from academic and community nephrology practices. NEPTUNE included 166 patients with incident FSGS enrolled at first kidney biopsy; FSGS-CT included 132 patients with steroid-resistant FSGS randomized to cyclosporine vs dexamethasone with mycophenolate; and KRN included 184 patients with prevalent FSGS. Data were collected from November 2004 to October 2019 and analyzed from October 2020 to July 2022. Exposures: Age: children (age <13 years) vs adolescents (13-17 years) vs adults (≥18 years). Covariates of interest included sex, disease duration, APOL1 genotype, urine protein-to-creatinine ratio, estimated glomerular filtration rate (eGFR), edema, serum albumin, and immunosuppressive therapy. Main Outcomes and Measures: ESKD, composite outcome of ESKD or 40% decline in eGFR, and complete and/or partial remission of proteinuria. Results: The study included 127 (26%) children, 102 (21%) adolescents, and 253 (52%) adults, including 215 (45%) female participants and 138 (29%) who identified as Black, 98 (20%) who identified as Hispanic, and 275 (57%) who identified as White. Overall, the median time to ESKD was 11.9 years (IQR, 5.2-19.1 years). There was no difference in ESKD risk among children vs adults (hazard ratio [HR], 0.67; 95% CI, 0.43-1.03) or adolescents vs adults (HR, 0.85; 95% CI, 0.52-1.36). The median time to the composite end point was 5.7 years (IQR 1.6-15.2 years), with hazard ratio estimates for children vs adults of 1.12 (95% CI, 0.83-1.52) and adolescents vs adults of 1.06 (95% CI, 0.75-1.50). Conclusions and Relevance: In this study, the association of FSGS with kidney survival and functional outcomes was comparable at all ages.

Genome-wide meta-analysis and omics integration identifies novel genes associated with diabetic kidney disease.

AIMS/HYPOTHESIS: Diabetic kidney disease (DKD) is the leading cause of kidney failure and has a substantial genetic component. Our aim was to identify novel genetic factors and genes contributing to DKD by performing meta-analysis of previous genome-wide association studies (GWAS) on DKD and by integrating the results with renal transcriptomics datasets. METHODS: We performed GWAS meta-analyses using ten phenotypic definitions of DKD, including nearly 27,000 individuals with diabetes. Meta-analysis results were integrated with estimated quantitative trait locus data from human glomerular (N=119) and tubular (N=121) samples to perform transcriptome-wide association study. We also performed gene aggregate tests to jointly test all available common genetic markers within a gene, and combined the results with various kidney omics datasets. RESULTS: The meta-analysis identified a novel intronic variant (rs72831309) in the TENM2 gene associated with a lower risk of the combined chronic kidney disease (eGFR<60 ml/min per 1.73 m2) and DKD (microalbuminuria or worse) phenotype (p=9.8×10-9; although not withstanding correction for multiple testing, p>9.3×10-9). Gene-level analysis identified ten genes associated with DKD (COL20A1, DCLK1, EIF4E, PTPRN-RESP18, GPR158, INIP-SNX30, LSM14A and MFF; p<2.7×10-6). Integration of GWAS with human glomerular and tubular expression data demonstrated higher tubular AKIRIN2 gene expression in individuals with vs without DKD (p=1.1×10-6). The lead SNPs within six loci significantly altered DNA methylation of a nearby CpG site in kidneys (p<1.5×10-11). Expression of lead genes in kidney tubules or glomeruli correlated with relevant pathological phenotypes (e.g. TENM2 expression correlated positively with eGFR [p=1.6×10-8] and negatively with tubulointerstitial fibrosis [p=2.0×10-9], tubular DCLK1 expression correlated positively with fibrosis [p=7.4×10-16], and SNX30 expression correlated positively with eGFR [p=5.8×10-14] and negatively with fibrosis [p<2.0×10-16]). CONCLUSIONS/INTERPRETATION: Altogether, the results point to novel genes contributing to the pathogenesis of DKD. DATA AVAILABILITY: The GWAS meta-analysis results can be accessed via the type 1 and type 2 diabetes (T1D and T2D, respectively) and Common Metabolic Diseases (CMD) Knowledge Portals, and downloaded on their respective download pages ( https://t1d.hugeamp.org/downloads.html ; https://t2d.hugeamp.org/downloads.html ; https://hugeamp.org/downloads.html ).

Discovery of Autoantibodies Targeting Nephrin in Minimal Change Disease Supports a Novel Autoimmune Etiology.

BACKGROUND: Failure of the glomerular filtration barrier, primarily by loss of slit diaphragm architecture, underlies nephrotic syndrome in minimal change disease. The etiology remains unknown. The efficacy of B cell-targeted therapies in some patients, together with the known proteinuric effect of anti-nephrin antibodies in rodent models, prompted us to hypothesize that nephrin autoantibodies may be present in patients with minimal change disease. METHODS: We evaluated sera from patients with minimal change disease, enrolled in the Nephrotic Syndrome Study Network (NEPTUNE) cohort and from our own institutions, for circulating nephrin autoantibodies by indirect ELISA and by immunoprecipitation of full-length nephrin from human glomerular extract or a recombinant purified extracellular domain of human nephrin. We also evaluated renal biopsies from our institutions for podocyte-associated punctate IgG colocalizing with nephrin by immunofluorescence. RESULTS: In two independent patient cohorts, we identified circulating nephrin autoantibodies during active disease that were significantly reduced or absent during treatment response in a subset of patients with minimal change disease. We correlated the presence of these autoantibodies with podocyte-associated punctate IgG in renal biopsies from our institutions. We also identified a patient with steroid-dependent childhood minimal change disease that progressed to end stage kidney disease; she developed a massive post-transplant recurrence of proteinuria that was associated with high pretransplant circulating nephrin autoantibodies. CONCLUSIONS: Our discovery of nephrin autoantibodies in a subset of adults and children with minimal change disease aligns with published animal studies and provides further support for an autoimmune etiology. We propose a new molecular classification of nephrin autoantibody minimal change disease to serve as a framework for instigation of precision therapeutics for these patients.

A glomerular transcriptomic landscape of apolipoprotein L1 in Black patients with focal segmental glomerulosclerosis.

Apolipoprotein L1 (APOL1)-associated focal segmental glomerulosclerosis (FSGS) is the dominant form of FSGS in Black individuals. There are no targeted therapies for this condition, in part because the molecular mechanisms underlying APOL1's pathogenic contribution to FSGS are incompletely understood. Studying the transcriptomic landscape of APOL1 FSGS in patient kidneys is an important way to discover genes and molecular behaviors that are unique or most relevant to the human disease. With the hypothesis that the pathology driven by the high-risk APOL1 genotype is reflected in alteration of gene expression across the glomerular transcriptome, we compared expression and co-expression profiles of 15,703 genes in 16 Black patients with FSGS at high-risk vs 14 Black patients with a low-risk APOL1 genotype. Expression data from APOL1-inducible HEK293 cells and normal human glomeruli were used to pursue genes and molecular pathways uncovered in these studies. We discovered increased expression of APOL1 and nine other significant differentially expressed genes in high-risk patients. This included stanniocalcin, which has a role in mitochondrial and calcium-related processes along with differential correlations between high- and low-risk APOL1 and metabolism pathway genes. There were similar correlations with extracellular matrix- and immune-related genes, but significant loss of co-expression of mitochondrial genes in high-risk FSGS, and an NF-κB-down regulating gene, NKIRAS1, as the most significant hub gene with strong differential correlations with NDUF family (mitochondrial respiratory genes) and immune-related (JAK-STAT) genes. Thus, differences in mitochondrial gene regulation appear to underlie many differences observed between high- and low-risk Black patients with FSGS.

A Rare Autosomal Dominant Variant in Regulator of Calcineurin Type 1 (RCAN1) Gene Confers Enhanced Calcineurin Activity and May Cause FSGS.

BACKGROUND: Podocyte dysfunction is the main pathologic mechanism driving the development of FSGS and other morphologic types of steroid-resistant nephrotic syndrome (SRNS). Despite significant progress, the genetic causes of most cases of SRNS have yet to be identified. METHODS: Whole-genome sequencing was performed on 320 individuals from 201 families with familial and sporadic NS/FSGS with no pathogenic mutations in any known NS/FSGS genes. RESULTS: Two variants in the gene encoding regulator of calcineurin type 1 (RCAN1) segregate with disease in two families with autosomal dominant FSGS/SRNS. In vitro, loss of RCAN1 reduced human podocyte viability due to increased calcineurin activity. Cells expressing mutant RCAN1 displayed increased calcineurin activity and NFAT activation that resulted in increased susceptibility to apoptosis compared with wild-type RCAN1. Treatment with GSK-3 inhibitors ameliorated this elevated calcineurin activity, suggesting the mutation alters the balance of RCAN1 regulation by GSK-3ß, resulting in dysregulated calcineurin activity and apoptosis. CONCLUSIONS: These data suggest mutations in RCAN1 can cause autosomal dominant FSGS. Despite the widespread use of calcineurin inhibitors in the treatment of NS, genetic mutations in a direct regulator of calcineurin have not been implicated in the etiology of NS/FSGS before this report. The findings highlight the therapeutic potential of targeting RCAN1 regulatory molecules, such as GSK-3ß, in the treatment of FSGS.

SARS-CoV-2 receptor networks in diabetic and COVID-19-associated kidney disease.

COVID-19 morbidity and mortality are increased via unknown mechanisms in patients with diabetes and kidney disease. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) for entry into host cells. Because ACE2 is a susceptibility factor for infection, we investigated how diabetic kidney disease and medications alter ACE2 receptor expression in kidneys. Single cell RNA profiling of kidney biopsies from healthy living donors and patients with diabetic kidney disease revealed ACE2 expression primarily in proximal tubular epithelial cells. This cell-specific localization was confirmed by in situ hybridization. ACE2 expression levels were unaltered by exposures to renin-angiotensin-aldosterone system inhibitors in diabetic kidney disease. Bayesian integrative analysis of a large compendium of public -omics datasets identified molecular network modules induced in ACE2-expressing proximal tubular epithelial cells in diabetic kidney disease (searchable at hb.flatironinstitute.org/covid-kidney) that were linked to viral entry, immune activation, endomembrane reorganization, and RNA processing. The diabetic kidney disease ACE2-positive proximal tubular epithelial cell module overlapped with expression patterns seen in SARS-CoV-2-infected cells. Similar cellular programs were seen in ACE2-positive proximal tubular epithelial cells obtained from urine samples of 13 hospitalized patients with COVID-19, suggesting a consistent ACE2-coregulated proximal tubular epithelial cell expression program that may interact with the SARS-CoV-2 infection processes. Thus SARS-CoV-2 receptor networks can seed further research into risk stratification and therapeutic strategies for COVID-19-related kidney damage.

SARS-CoV-2 receptor networks in diabetic and COVID-19 associated kidney disease.

COVID-19 morbidity and mortality is increased in patients with diabetes and kidney disease via unknown mechanisms. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) for entry into host cells. Since ACE2 is a susceptibility factor for infection, we investigated how diabetic kidney disease (DKD) and medications alter ACE2 receptor expression in kidneys. Single cell RNA profiling of healthy living donor (LD) and DKD kidney biopsies revealed ACE2 expression primarily in proximal tubular epithelial cells (PTEC). This cell specific localization was confirmed by in situ hybridization. ACE2 expression levels were unaltered by exposures to renin angiotensin aldosterone system inhibitors in DKD. Bayesian integrative analysis of a large compendium of public -omics datasets identified molecular network modules induced in ACE2-expressing PTEC in DKD (searchable at hb.flatironinstitute.org/covid-kidney) that were linked to viral entry, immune activation, endomembrane reorganization, and RNA processing. The DKD ACE2-positive PTEC module overlapped with expression patterns seen in SARS-CoV-2 infected cells. Similar cellular programs were seen in ACE2-positive PTEC obtained from urine samples of 13 COVID-19 patients who were hospitalized, suggesting a consistent ACE2-coregulated PTEC expression program that may interact with the SARS-CoV-2 infection processes. Thus SARS-CoV-2 receptor networks can seed further research into risk stratification and therapeutic strategies for COVID-19 related kidney damage.

A protein-centric approach for exome variant aggregation enables sensitive association analysis with clinical outcomes.

Somatic mutations are early drivers of tumorigenesis and tumor progression. However, the mutations typically occur at variable positions across different individuals, resulting in the data being too sparse to test meaningful associations between variants and phenotypes. To overcome this challenge, we devised a novel approach called Gene-to-Protein-to-Disease (GPD) which accumulates variants into new sequence units as the degree of genetic assault on structural or functional units of each protein. The variant frequencies in the sequence units were highly reproducible between two large cancer cohorts. Survival analysis identified 232 sequence units in which somatic mutations had deleterious effects on overall survival, including consensus driver mutations obtained from multiple calling algorithms. By contrast, around 76% of the survival predictive units had been undetected by conventional gene-level analysis. We demonstrate the ability of these signatures to separate patient groups according to overall survival, therefore, providing novel prognostic tools for various cancers. GPD also identified sequence units with somatic mutations whose impact on survival was modified by the occupancy of germline variants in the surrounding regions. The findings indicate that a patient's genetic predisposition interacts with the effect of somatic mutations on survival outcomes in some cancers.

iOmicsPASS: network-based integration of multiomics data for predictive subnetwork discovery.

Computational tools for multiomics data integration have usually been designed for unsupervised detection of multiomics features explaining large phenotypic variations. To achieve this, some approaches extract latent signals in heterogeneous data sets from a joint statistical error model, while others use biological networks to propagate differential expression signals and find consensus signatures. However, few approaches directly consider molecular interaction as a data feature, the essential linker between different omics data sets. The increasing availability of genome-scale interactome data connecting different molecular levels motivates a new class of methods to extract interactive signals from multiomics data. Here we developed iOmicsPASS, a tool to search for predictive subnetworks consisting of molecular interactions within and between related omics data types in a supervised analysis setting. Based on user-provided network data and relevant omics data sets, iOmicsPASS computes a score for each molecular interaction, and applies a modified nearest shrunken centroid algorithm to the scores to select densely connected subnetworks that can accurately predict each phenotypic group. iOmicsPASS detects a sparse set of predictive molecular interactions without loss of prediction accuracy compared to alternative methods, and the selected network signature immediately provides mechanistic interpretation of the multiomics profile representing each sample group. Extensive simulation studies demonstrate clear benefit of interaction-level modeling. iOmicsPASS analysis of TCGA/CPTAC breast cancer data also highlights new transcriptional regulatory network underlying the basal-like subtype as positive protein markers, a result not seen through analysis of individual omics data.