Interferon-γ induces combined pyroptotic angiopathy and APOL1 expression in human kidney disease.

Elevated interferon (IFN) signaling is associated with kidney diseases including COVID-19, HIV, and apolipoprotein-L1 (APOL1) nephropathy, but whether IFNs directly contribute to nephrotoxicity remains unclear. Using human kidney organoids, primary endothelial cells, and patient samples, we demonstrate that IFN-γ induces pyroptotic angiopathy in combination with APOL1 expression. Single-cell RNA sequencing, immunoblotting, and quantitative fluorescence-based assays reveal that IFN-γ-mediated expression of APOL1 is accompanied by pyroptotic endothelial network degradation in organoids. Pharmacological blockade of IFN-γ signaling inhibits APOL1 expression, prevents upregulation of pyroptosis-associated genes, and rescues vascular networks. Multiomic analyses in patients with COVID-19, proteinuric kidney disease, and collapsing glomerulopathy similarly demonstrate increased IFN signaling and pyroptosis-associated gene expression correlating with accelerated renal disease progression. Our results reveal that IFN-γ signaling simultaneously induces endothelial injury and primes renal cells for pyroptosis, suggesting a combinatorial mechanism for APOL1-mediated collapsing glomerulopathy, which can be targeted therapeutically.

Single-cell RNA sequencing uncovers heterogenous transcriptional signatures in macrophages during efferocytosis.

Efferocytosis triggers cellular reprogramming, including the induction of mRNA transcripts which encode anti-inflammatory cytokines that promote inflammation resolution. Our current understanding of this transcriptional response is largely informed from analysis of bulk phagocyte populations; however, this precludes the resolution of heterogeneity between individual macrophages and macrophage subsets. Moreover, phagocytes may contain so called "passenger" transcripts that originate from engulfed apoptotic bodies, thus obscuring the true transcriptional reprogramming of the phagocyte. To define the transcriptional diversity during efferocytosis, we utilized single-cell mRNA sequencing after co-cultivating macrophages with apoptotic cells. Importantly, transcriptomic analyses were performed after validating the disappearance of apoptotic cell-derived RNA sequences. Our findings reveal new heterogeneity of the efferocytic response at a single-cell resolution, particularly evident between F4/80+ MHCIILO and F4/80- MHCIIHI macrophage sub-populations. After exposure to apoptotic cells, the F4/80+ MHCIILO subset significantly induced pathways associated with tissue and cellular homeostasis, while the F4/80- MHCIIHI subset downregulated these putative signaling axes. Ablation of a canonical efferocytosis receptor, MerTK, blunted efferocytic signatures and led to the escalation of cell death-associated transcriptional signatures in F4/80+ MHCIILO macrophages. Taken together, our results newly elucidate the heterogenous transcriptional response of single-cell peritoneal macrophages after exposure to apoptotic cells.

Profiling APOL1 Nephropathy Risk Variants in Genome-Edited Kidney Organoids with Single-Cell Transcriptomics.

BACKGROUND: DNA variants in APOL1 associate with kidney disease, but the pathophysiologic mechanisms remain incompletely understood. Model organisms lack the APOL1 gene, limiting the degree to which disease states can be recapitulated. Here we present single-cell RNA sequencing (scRNA-seq) of genome-edited human kidney organoids as a platform for profiling effects of APOL1 risk variants in diverse nephron cell types. METHODS: We performed footprint-free CRISPR-Cas9 genome editing of human induced pluripotent stem cells (iPSCs) to knock in APOL1 high-risk G1 variants at the native genomic locus. iPSCs were differentiated into kidney organoids, treated with vehicle, IFN-γ, or the combination of IFN-γ and tunicamycin, and analyzed with scRNA-seq to profile cell-specific changes in differential gene expression patterns, compared with isogenic G0 controls. RESULTS: Both G0 and G1 iPSCs differentiated into kidney organoids containing nephron-like structures with glomerular epithelial cells, proximal tubules, distal tubules, and endothelial cells. Organoids expressed detectable APOL1 only after exposure to IFN-γ. scRNA-seq revealed cell type-specific differences in G1 organoid response to APOL1 induction. Additional stress of tunicamycin exposure led to increased glomerular epithelial cell dedifferentiation in G1 organoids. CONCLUSIONS: Single-cell transcriptomic profiling of human genome-edited kidney organoids expressing APOL1 risk variants provides a novel platform for studying the pathophysiology of APOL1-mediated kidney disease.

Complexities of Understanding Function from CKD-Associated DNA Variants.

Genome-wide association studies (GWASs) have facilitated the unbiased discovery of hundreds of genomic loci associated with CKD and kidney function. The vast majority of disease-associated DNA variants are noncoding. Those that are causal in CKD pathogenesis likely modulate transcription of target genes in a cell type-specific manner. To gain novel biological insights into mechanisms driving the development of CKD, the causal variants (which are usually not the most significant variant reported in a GWAS), their target genes, and causal cell types need to be identified. This functional validation requires a large number of new data sets, complex bioinformatics analyses, and experimental cellular and in vivo studies. Here, we review the basic principles and some of the current approaches being leveraged to assign functional significance to a genotype-phenotype association.

Picking Up the Slack: Collaboration Tools to Build Community and Increase Productivity in Nephrology.

With a growing need to recruit the future nephrology workforce, medical educators and members of the nephrology community are turning to innovative approaches to improve communication and stimulate dialogue in the field. One feasible strategy is the use of electronic collaboration tools such as Slack (Slack Technologies, San Francisco, CA), which facilitates real-time conversational communication in a private or semiprivate virtual workspace. The potential uses of Slack for nephrology education, research collaboration, and community building are outlined in this overview.

Ten years in: APOL1 reaches beyond the kidney.

PURPOSE OF REVIEW: APOL1 nephropathy risk variants drive most of the excess risk of chronic kidney disease (CKD) seen in African Americans, but whether the same risk variants account for excess cardiovascular risk remains unclear. This mini-review highlights the controversies in the APOL1 cardiovascular field. RECENT FINDINGS: In the past 10 years, our understanding of how APOL1 risk variants contribute to renal cytotoxicity has increased. Some of the proposed mechanisms for kidney disease are biologically plausible for cells and tissues relevant to cardiovascular disease (CVD), but cardiovascular studies published since 2014 have reported conflicting results regarding APOL1 risk variant association with cardiovascular outcomes. In the past year, several studies have also contributed conflicting results from different types of study populations. SUMMARY: Heterogeneity in study population and study design has led to differing reports on the role of APOL1 nephropathy risk variants in CVD. Without consistently validated associations between these risk variants and CVD, mechanistic studies for APOL1's role in cardiovascular biology lag behind.

From Genotype to Phenotype: A Primer on the Functional Follow-up of Genome-Wide Association Studies in Cardiovascular Disease.

Genome-wide association studies (GWASs) have implicated many human genomic loci in the development of complex traits. The loci identified by these studies are potentially involved in novel pathways that contribute to disease pathophysiology. However, eventual therapeutic targeting of these pathways relies on bridging the gap between genetic association and function, a task that first requires validation of causal genetic variants, casual genes, and directionality of effect. Executing this task requires basic knowledge of interpreting GWAS results and prioritizing candidates for further study, in addition to understanding the experimental methods available for evaluating candidate variants. Here we review the basic genetic principles of genome-wide association studies, the computational and experimental tools used for identifying causal variants and genes, and salient illustrative examples of how cardiovascular loci have undergone functional investigation.

Interrogation of nonconserved human adipose lincRNAs identifies a regulatory role of linc-ADAL in adipocyte metabolism.

Long intergenic noncoding RNAs (lincRNAs) have emerged as important modulators of cellular functions. Most lincRNAs are not conserved among mammals, raising the fundamental question of whether nonconserved adipose-expressed lincRNAs are functional. To address this, we performed deep RNA sequencing of gluteal subcutaneous adipose tissue from 25 healthy humans. We identified 1001 putative lincRNAs expressed in all samples through de novo reconstruction of noncoding transcriptomes and integration with existing lincRNA annotations. One hundred twenty lincRNAs had adipose-enriched expression, and 54 of these exhibited peroxisome proliferator-activated receptor γ (PPARγ) or CCAAT/enhancer binding protein α (C/EBPα) binding at their loci. Most of these adipose-enriched lincRNAs (~85%) were not conserved in mice, yet on average, they showed degrees of expression and binding of PPARγ and C/EBPα similar to those displayed by conserved lincRNAs. Most adipose lincRNAs differentially expressed (n = 53) in patients after bariatric surgery were nonconserved. The most abundant adipose-enriched lincRNA in our subcutaneous adipose data set, linc-ADAL, was nonconserved, up-regulated in adipose depots of obese individuals, and markedly induced during in vitro human adipocyte differentiation. We demonstrated that linc-ADAL interacts with heterogeneous nuclear ribonucleoprotein U (hnRNPU) and insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) at distinct subcellular locations to regulate adipocyte differentiation and lipogenesis.

Fluctuating Carbonaceous Networks with a Persistent Molecular Shape: A Saddle-Shaped Geodesic Framework of 1,3,5-Trisubstituted Benzene (Phenine).

A saddle-shaped macromolecule has been synthesized. The molecule was designed as a geodesic saddle with 1,3,5-trisubstituted benzene (named phenine) as the fundamental unit. The phenines were woven into a polygonal framework that was composed of 168 sp2 -hybridized carbon atoms. The saddle-shaped structure with unique symmetry showed atypical conformational changes. The biaryl linkages in this molecule had a small energy barrier for rotation, and these structural fluctuations resulted in seven 1 H NMR resonances representing 84 aromatic hydrogen atoms. Nevertheless, the overall saddle shape of the molecule was persistent, and the "up" and "down" orientations of phenine moieties circulated to give average 1 H resonances. The structural characteristics of this molecule, including the anomalous entropy-driven dimerization, may deepen our understanding of defect-rich graphitic sheets.

PennDiff: detecting differential alternative splicing and transcription by RNA sequencing.

Motivation: Alternative splicing and alternative transcription are a major mechanism for generating transcriptome diversity. Differential alternative splicing and transcription (DAST), which describe different usage of transcript isoforms across different conditions, can complement differential expression in characterizing gene regulation. However, the analysis of DAST is challenging because only a small fraction of RNA-seq reads is informative for isoforms. Several methods have been developed to detect exon-based and gene-based DAST, but they suffer from power loss for genes with many isoforms. Results: We present PennDiff, a novel statistical method that makes use of information on gene structures and pre-estimated isoform relative abundances, to detect DAST from RNA-seq data. PennDiff has several advantages. First, grouping exons avoids multiple testing for 'exons' originated from the same isoform(s). Second, it utilizes all available reads in exon-inclusion level estimation, which is different from methods that only use junction reads. Third, collapsing isoforms sharing the same alternative exons reduces the impact of isoform expression estimation uncertainty. PennDiff is able to detect DAST at both exon and gene levels, thus offering more flexibility than existing methods. Simulations and analysis of a real RNA-seq dataset indicate that PennDiff has well-controlled type I error rate, and is more powerful than existing methods including DEXSeq, rMATS, Cuffdiff, IUTA and SplicingCompass. As the popularity of RNA-seq continues to grow, we expect PennDiff to be useful for diverse transcriptomics studies. Availability and implementation: PennDiff source code and user guide is freely available for download at https://github.com/tigerhu15/PennDiff. Supplementary information: Supplementary data are available at Bioinformatics online.

Deep RNA Sequencing Uncovers a Repertoire of Human Macrophage Long Intergenic Noncoding RNAs Modulated by Macrophage Activation and Associated With Cardiometabolic Diseases.

BACKGROUND: Sustained and dysfunctional macrophage activation promotes inflammatory cardiometabolic disorders, but the role of long intergenic noncoding RNA (lincRNA) in human macrophage activation and cardiometabolic disorders is poorly defined. Through transcriptomics, bioinformatics, and selective functional studies, we sought to elucidate the lincRNA landscape of human macrophages. METHODS AND RESULTS: We used deep RNA sequencing to assemble the lincRNA transcriptome of human monocyte-derived macrophages at rest and following stimulation with lipopolysaccharide and IFN-γ (interferon γ) for M1 activation and IL-4 (interleukin 4) for M2 activation. Through de novo assembly, we identified 2766 macrophage lincRNAs, including 861 that were previously unannotated. The majority (≈85%) was nonsyntenic or was syntenic but not annotated as expressed in mouse. Many macrophage lincRNAs demonstrated tissue-enriched transcription patterns (21.5%) and enhancer-like chromatin signatures (60.9%). Macrophage activation, particularly to the M1 phenotype, markedly altered the lincRNA expression profiles, revealing 96 lincRNAs differentially expressed, suggesting potential roles in regulating macrophage inflammatory functions. A subset of lincRNAs overlapped genomewide association study loci for cardiometabolic disorders. MacORIS (macrophage-enriched obesity-associated lincRNA serving as a repressor of IFN-γ signaling), a macrophage-enriched lincRNA not expressed in mouse macrophages, harbors variants associated with central obesity. Knockdown of MacORIS, which is located in the cytoplasm, enhanced IFN-γ-induced JAK2 (Janus kinase 2) and STAT1 (signal transducer and activator of transcription 1) phosphorylation in THP-1 macrophages, suggesting a potential role as a repressor of IFN-γ signaling. Induced pluripotent stem cell-derived macrophages recapitulated the lincRNA transcriptome of human monocyte-derived macrophages and provided a high-fidelity model with which to study lincRNAs in human macrophage biology, particularly those not conserved in mouse. CONCLUSIONS: High-resolution transcriptomics identified lincRNAs that form part of the coordinated response during macrophage activation, including specific macrophage lincRNAs associated with human cardiometabolic disorders that modulate macrophage inflammatory functions.

Transcriptome-Wide Analysis Reveals Modulation of Human Macrophage Inflammatory Phenotype Through Alternative Splicing.

OBJECTIVE: Human macrophages can shift phenotype across the inflammatory M1 and reparative M2 spectrum in response to environmental challenges, but the mechanisms promoting inflammatory and cardiometabolic disease-associated M1 phenotypes remain incompletely understood. Alternative splicing (AS) is emerging as an important regulator of cellular function, yet its role in macrophage activation is largely unknown. We investigated the extent to which AS occurs in M1 activation within the cardiometabolic disease context and validated a functional genomic cell model for studying human macrophage-related AS events. APPROACH AND RESULTS: From deep RNA-sequencing of resting, M1, and M2 primary human monocyte-derived macrophages, we found 3860 differentially expressed genes in M1 activation and detected 233 M1-induced AS events; the majority of AS events were cell- and M1-specific with enrichment for pathways relevant to macrophage inflammation. Using genetic variant data for 10 cardiometabolic traits, we identified 28 trait-associated variants within the genomic loci of 21 alternatively spliced genes and 15 variants within 7 differentially expressed regulatory splicing factors in M1 activation. Knockdown of 1 such splicing factor, CELF1, in primary human macrophages led to increased inflammatory response to M1 stimulation, demonstrating CELF1's potential modulation of the M1 phenotype. Finally, we demonstrated that an induced pluripotent stem cell-derived macrophage system recapitulates M1-associated AS events and provides a high-fidelity macrophage AS model. CONCLUSIONS: AS plays a role in defining macrophage phenotype in a cell- and stimulus-specific fashion. Alternatively spliced genes and splicing factors with trait-associated variants may reveal novel pathways and targets in cardiometabolic diseases.

Genome engineering tools for building cellular models of disease.

With the recent development of methods for genome editing of human pluripotent stem cells, study of the genetic basis of human diseases has been rapidly advancing. Genome-edited differentiated stem cells have provided new and more accurate insights into genomic underpinnings of diseases for which there have not been adequate treatments, and moving toward clinical application of genome editing holds great promise for acceleration of therapeutic translation. Here, we review recent advances in genome-editing technologies and their application to human biology in disease modeling and beyond.

False-Positive Rate of AKI Using Consensus Creatinine-Based Criteria.

BACKGROUND AND OBJECTIVES: Use of small changes in serum creatinine to diagnose AKI allows for earlier detection but may increase diagnostic false-positive rates because of inherent laboratory and biologic variabilities of creatinine. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We examined serum creatinine measurement characteristics in a prospective observational clinical reference cohort of 2267 adult patients with AKI by Kidney Disease Improving Global Outcomes creatinine criteria and used these data to create a simulation cohort to model AKI false-positive rates. We simulated up to seven successive blood draws on an equal population of hypothetical patients with unchanging true serum creatinine values. Error terms generated from laboratory and biologic variabilities were added to each simulated patient's true serum creatinine value to obtain the simulated measured serum creatinine for each blood draw. We determined the proportion of patients who would be erroneously diagnosed with AKI by Kidney Disease Improving Global Outcomes creatinine criteria. RESULTS: Within the clinical cohort, 75.0% of patients received four serum creatinine draws within at least one 48-hour period during hospitalization. After four simulated creatinine measurements that accounted for laboratory variability calculated from assay characteristics and 4.4% of biologic variability determined from the clinical cohort and publicly available data, the overall false-positive rate for AKI diagnosis was 8.0% (interquartile range =7.9%-8.1%), whereas patients with true serum creatinine ≥1.5 mg/dl (representing 21% of the clinical cohort) had a false-positive AKI diagnosis rate of 30.5% (interquartile range =30.1%-30.9%) versus 2.0% (interquartile range =1.9%-2.1%) in patients with true serum creatinine values <1.5 mg/dl (P<0.001). CONCLUSIONS: Use of small serum creatinine changes to diagnose AKI is limited by high false-positive rates caused by inherent variability of serum creatinine at higher baseline values, potentially misclassifying patients with CKD in AKI studies.

The long noncoding RNA landscape in hypoxic and inflammatory renal epithelial injury.

Long noncoding RNAs (lncRNAs) are emerging as key species-specific regulators of cellular and disease processes. To identify potential lncRNAs relevant to acute and chronic renal epithelial injury, we performed unbiased whole transcriptome profiling of human proximal tubular epithelial cells (PTECs) in hypoxic and inflammatory conditions. RNA sequencing revealed that the protein-coding and noncoding transcriptomic landscape differed between hypoxia-stimulated and cytokine-stimulated human PTECs. Hypoxia- and inflammation-modulated lncRNAs were prioritized for focused followup according to their degree of induction by these stress stimuli, their expression in human kidney tissue, and whether exposure of human PTECs to plasma of critically ill sepsis patients with acute kidney injury modulated their expression. For three lncRNAs (MIR210HG, linc-ATP13A4-8, and linc-KIAA1737-2) that fulfilled our criteria, we validated their expression patterns, examined their loci for conservation and synteny, and defined their associated epigenetic marks. The lncRNA landscape characterized here provides insights into novel transcriptomic variations in the renal epithelial cell response to hypoxic and inflammatory stress.

Relation of atherogenic lipoproteins with estimated glomerular filtration rate decline: a longitudinal study.

BACKGROUND: Chronic kidney disease (CKD) is associated with dyslipidemia, but the role of atherogenic lipid fractions in CKD progression remains unclear. Here we assess whether baseline plasma levels of lipoprotein(a) [Lp(a)] and apolipoprotein C-III (apoC-III), causal cardiovascular (CV) risk factors being studied as therapeutic targets, are associated with decreasing estimated glomerular filtration rate (eGFR) over time. METHODS: In the Penn Diabetes Heart Study (PDHS), a single-center observational cohort of type 2 diabetes patients without clinical CV disease or pre-existing CKD, we performed linear mixed effects modeling with incremental multivariable analysis to evaluate the effects of baseline plasma Lp(a) and apoC-III on the slope of eGFR over time for subjects with longitudinal data (N = 400). RESULTS: Each two-fold higher plasma Lp(a) level was associated with an additional decline in eGFR by 0.50 mL/min/year in the fully adjusted model (p < 0.001). Baseline Lp(a) levels greater than the atherogenic cut-point of 30 mg/dL were associated with a decline in eGFR by 2.75 mL/min/year compared to 1.01 mL/min/year in subjects with baseline Lp(a) less than 30 mg/dL (p < 0.001). Although each two-fold higher apoC-III level was also associated with statistically significant decline in eGFR over time, as expected the association was attenuated after adjusting for baseline triglycerides, the key lipid intermediary regulated by apoC-III in circulation. CONCLUSIONS: Elevated baseline plasma Lp(a) levels are associated with a decrease in eGFR over time independent of race, lipid medication use, and albuminuria, whereas elevated baseline apoC-III levels are associated with eGFR decline in a triglyceride-dependent fashion.

Automated, electronic alerts for acute kidney injury: a single-blind, parallel-group, randomised controlled trial.

BACKGROUND: Acute kidney injury often goes unrecognised in its early stages when effective treatment options might be available. We aimed to determine whether an automated electronic alert for acute kidney injury would reduce the severity of such injury and improve clinical outcomes in patients in hospital. METHODS: In this investigator-masked, parallel-group, randomised controlled trial, patients were recruited from the hospital of the University of Pennsylvania in Philadelphia, PA, USA. Eligible participants were adults aged 18 years or older who were in hospital with stage 1 or greater acute kidney injury as defined by Kidney Disease Improving Global Outcomes creatinine-based criteria. Exclusion criteria were initial hospital creatinine 4·0 mg/dL (to convert to µmol/L, multiply by 88·4) or greater, fewer than two creatinine values measured, inability to determine the covering provider, admission to hospice or the observation unit, previous randomisation, or end-stage renal disease. Patients were randomly assigned (1:1) via a computer-generated sequence to receive an acute kidney injury alert (a text-based alert sent to the covering provider and unit pharmacist indicating new acute kidney injury) or usual care, stratified by medical versus surgical admission and intensive care unit versus non-intensive care unit location in blocks of 4-8 participants. The primary outcome was a composite of relative maximum change in creatinine, dialysis, and death at 7 days after randomisation. All analyses were by intention to treat. This study is registered with ClinicalTrials.gov, number NCT01862419. FINDINGS: Between Sept 17, 2013, and April 14, 2014, 23,664 patients were screened. 1201 eligible participants were assigned to the acute kidney injury alert group and 1192 were assigned to the usual care group. Composite relative maximum change in creatinine, dialysis, and death at 7 days did not differ between the alert group and the usual care group (p=0·88), or within any of the four randomisation strata (all p>0·05). At 7 days after randomisation, median maximum relative change in creatinine concentrations was 0·0% (IQR 0·0-18·4) in the alert group and 0·6% (0·0-17·5) in the usual care group (p=0·81); 87 (7·2%) patients in the alert group and 70 (5·9%) patients in usual care group had received dialysis (odds ratio 1·25 [95% CI 0·90-1·74]; p=0·18); and 71 (5·9%) patients in the alert group and 61 (5·1%) patients in the usual care group had died (1·16 [0·81-1·68]; p=0·40). INTERPRETATION: An electronic alert system for acute kidney injury did not improve clinical outcomes among patients in hospital. FUNDING: Penn Center for Healthcare Improvement and Patient Safety.