A transcription factor network regulates proliferation of glomerular endothelial cells in diabetic kidney disease.

The maintenance of a healthy epithelial-endothelial juxtaposition requires cross-talk within glomerular cellular niches. We sought to understand the spatially-anchored regulation and transition of endothelial and mesangial cells from health to injury in DKD. From 74 human kidney samples, an integrated multi-omics approach was leveraged to identify cellular niches, cell-cell communication, cell injury trajectories, and regulatory transcription factor (TF) networks in glomerular capillary endothelial (EC-GC) and mesangial cells.

Integration of spatial multiplexed protein imaging and transcriptomics in the human kidney tracks the regenerative potential timeline of proximal tubules.

The organizational principles of nephronal segments are based on longstanding anatomical and physiological attributes that are closely linked to the homeostatic functions of the kidney. Novel molecular approaches have recently uncovered layers of deeper signatures and states in tubular cells that arise at various timepoints on the spectrum between health and disease. For example, a dedifferentiated state of proximal tubular cells with mesenchymal stemness markers is frequently seen after injury.

A Phase I Trial of the Pharmacokinetic Interaction Between Cannabidiol and Tacrolimus.

One in six Americans uses cannabidiol-based or cannabis-derived products. Cannabidiol is a substrate of CYP3A, but its role as a potential CYP3A inhibitor remains unclear. We hypothesized that cannabidiol would inhibit CYP3A-mediated metabolism of tacrolimus.

PCCA variant rs16957301 is a novel AKI risk genotype-specific for patients who receive ICI treatment: Real-world evidence from all of us cohort.

Introduction: Immune checkpoint inhibitors (ICIs) enhance the immune system's ability to target and destroy cancer cells, but can also trigger immune-related adverse events (irAEs), such as acute kidney injury (ICI-AKI), complicating patient management. Limited knowledge of genetic predispositions to ICI-AKI highlights the need for genomic studies to improve therapeutic strategies.

Objective: To identify genetic predispositions for ICI-AKI using large-scale real-world data.

Health disparities in the risk of severe acidosis: real-world evidence from the All of Us cohort.

Objective: To assess the health disparities across social determinants of health (SDoH) domains for the risk of severe acidosis independent of demographical and clinical factors.

Materials And Methods: A retrospective case-control study (n = 13 310, 1:4 matching) is performed using electronic health records (EHRs), SDoH surveys, and genomics data from the All of Us participants. The propensity score matching controls confounding effects due to EHR data availability.

miRNA and mRNA Signatures in Human Acute Kidney Injury Tissue.

Acute kidney injury (AKI) is an important contributor to the development of chronic kidney disease (CKD). There is a need to understand molecular mediators that drive recovery and progression to CKD. In particular, the regulatory role of miRNAs in AKI is poorly understood.

The Kidney Precision Medicine Project and Single-Cell Biology of the Injured Proximal Tubule.

Single-cell RNA sequencing (scRNA-seq) has led to major advances in our understanding of proximal tubule subtypes in health and disease. The proximal tubule serves essential functions in overall homeostasis, but pathologic or physiological perturbations can affect its transcriptomic signature and corresponding tasks. These alterations in proximal tubular cells are often described within a scRNA-seq atlas as cell states, which are pathophysiological subclassifications based on molecular and morphologic changes in a cell's response to that injury compared with its native state.

A Precision Mixture Risk Model to Identify Adverse Drug Events in Subpopulations Using a Case-Crossover Design.

Despite the success of pharmacovigilance studies in detecting signals of adverse drug events (ADEs) from real-world data, the risks of ADEs in subpopulations warrant increased scrutiny to prevent them in vulnerable individuals. Recently, the case-crossover design has been implemented to leverage large-scale administrative claims data for ADE detection, while controlling both observed confounding effects and short-term fixed unobserved confounding effects. Additionally, as the case-crossover design only includes cases, subpopulations can be conveniently derived.

Plasma proteomics of acute tubular injury.

The kidney tubules constitute two-thirds of the cells of the kidney and account for the majority of the organ's metabolic energy expenditure. Acute tubular injury (ATI) is observed across various types of kidney diseases and may significantly contribute to progression to kidney failure. Non-invasive biomarkers of ATI may allow for early detection and drug development.

Implementing a pragmatic clinical trial to tailor opioids for chronic pain on behalf of the IGNITE ADOPT PGx investigators.

Chronic pain is a prevalent condition with enormous economic burden. Opioids such as tramadol, codeine, and hydrocodone are commonly used to treat chronic pain; these drugs are activated to more potent opioid receptor agonists by the hepatic CYP2D6 enzyme. Results from clinical studies and mechanistic understandings suggest that CYP2D6-guided therapy will improve pain control and reduce adverse drug events.

Development of a Multifaceted Program for Pharmacogenetics Adoption at an Academic Medical Center: Practical Considerations and Lessons Learned.

In 2019, Indiana University launched the Precision Health Initiative to enhance the institutional adoption of precision medicine, including pharmacogenetics (PGx) implementation, at university-affiliated practice sites across Indiana. The overarching goal of this PGx implementation program was to facilitate the sustainable adoption of genotype-guided prescribing into routine clinical care. To accomplish this goal, we pursued the following specific objectives: (i) to integrate PGx testing into existing healthcare system processes; (ii) to implement drug-gene pairs with high-level evidence and educate providers and pharmacists on established clinical management recommendations; (iii) to engage key stakeholders, including patients to optimize the return of results for PGx testing; (iv) to reduce health disparities through the targeted inclusion of underrepresented populations; (v) and to track third-party reimbursement.

: A web-based application for in-depth exploration of multi-omics data with brightfield histology.

Spatial -OMICS technologies facilitate the interrogation of molecular profiles in the context of the underlying histopathology and tissue microenvironment. Paired analysis of histopathology and molecular data can provide pathologists with otherwise unobtainable insights into biological mechanisms. To connect the disparate molecular and histopathologic features into a single workspace, we developed (unctional nit tate dentificati in WSIs [Whole Slide Images]), a web-based tool that provides users with a broad array of visualization and analytical tools including deep learning-based algorithms for in-depth interrogation of spatial -OMICS datasets and their associated high-resolution histology images.

Inflammation primes the murine kidney for recovery by activating AZIN1 adenosine-to-inosine editing.

The progression of kidney disease varies among individuals, but a general methodology to quantify disease timelines is lacking. Particularly challenging is the task of determining the potential for recovery from acute kidney injury following various insults. Here, we report that quantitation of post-transcriptional adenosine-to-inosine (A-to-I) RNA editing offers a distinct genome-wide signature, enabling the delineation of disease trajectories in the kidney.

TrajVis: a visual clinical decision support system to translate artificial intelligence trajectory models in the precision management of chronic kidney disease.

Objective: Our objective is to develop and validate TrajVis, an interactive tool that assists clinicians in using artificial intelligence (AI) models to leverage patients' longitudinal electronic medical records (EMRs) for personalized precision management of chronic disease progression.

Materials And Methods: We first perform requirement analysis with clinicians and data scientists to determine the visual analytics tasks of the TrajVis system as well as its design and functionalities. A graph AI model for chronic kidney disease (CKD) trajectory inference named DisEase PrOgression Trajectory (DEPOT) is used for system development and demonstration.

Analysis of the combined effect of rs699 and rs5051 on angiotensinogen expression and hypertension.

Background: Hypertension (HTN) involves genetic variability in the renin-angiotensin system and influences antihypertensive response. We previously reported that angiotensinogen () messenger RNA (mRNA) is endogenously bound by miR-122-5p and rs699 A > G decreases reporter mRNA in the microRNA functional-assay PASSPORT-seq. The promoter variant rs5051 C > T is in linkage disequilibrium (LD) with rs699 A > G and increases transcription.

Prognostic implications of unbiased molecular categorization in kidney disease.

In this commentary, a novel approach to the reclassification of chronic kidney disease is reviewed. In the revisited study, the investigators identify 4 distinct subtypes of kidney disease derived from an unbiased self-organizing map of transcriptomic data from kidney biopsy samples. These molecular subtypes then are characterized by biologic cell processes, clinical and histopathologic features, urinary proteomics, and disease progression.

Spatial transcriptomics in health and disease.

The ability to localize hundreds of macromolecules to discrete locations, structures and cell types in a tissue is a powerful approach to understand the cellular and spatial organization of an organ. Spatially resolved transcriptomic technologies enable mapping of transcripts at single-cell or near single-cell resolution in a multiplex manner. The rapid development of spatial transcriptomic technologies has accelerated the pace of discovery in several fields, including nephrology.

Plasma Proteins Associated with Chronic Histopathologic Lesions on Kidney Biopsy.

Key Points: Proteomic profiling identified 35 blood proteins associated with chronic histopathologic lesions in the kidney. Testican-2 was expressed in the glomerulus, released by the kidney into circulation, and inversely associated with glomerulosclerosis severity. NELL1 was expressed in tubular epithelial cells, released by the kidney into circulation, and inversely associated with interstitial fibrosis and tubular atrophy severity.

NAD activates renal metabolism and protects from chronic kidney disease in a model of Alport syndrome.

Chronic kidney disease (CKD) is associated with renal metabolic disturbances, including impaired fatty acid oxidation (FAO). Nicotinamide adenine dinucleotide (NAD ) is a small molecule that participates in hundreds of metabolism-related reactions. NAD levels are decreased in CKD, and NAD supplementation is protective.

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.

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.