Goal: Artificial intelligence (AI) is the ability of a computer to conduct complex tasks that humans are capable of performing. AI is useful in the field of pathology, which involves analyzing images of the microscopic structure of different tissues. However, AI can be difficult to setup and apply to the task. One specific task, segmentation, involves picking specific structures out of tissue images and is a prime candidate for automation with AI.
Results: In our study, we have created a tool for pathology image segmentation which runs in the cloud (is accessible over the web). We demonstrate the tool by using it to segment various structures from kidney tissue.
Implication for Patients: Our experiments show that the tool is easy to use, accurate, and can estimate the presence of one type of scarring as reliably as human experts. Doctors will be able to use our tool to consult patient diagnosis over the web with other colleagues, and offer objective diagnosis with the help of AI.
Kidney Precision Medicine Project (KPMP) is building a spatially-specified human tissue atlas at the single-cell resolution with molecular details of the kidney in health and disease. Here, we describe the construction of an integrated reference tissue map of cells, pathways and genes using unaffected regions of nephrectomy tissues and undiseased human biopsies from 55 subjects. We use single-cell and -nucleus transcriptomics, subsegmental laser microdissection bulk transcriptomics and proteomics, near-single-cell proteomics, 3-D nondestructive and CODEX imaging, and spatial metabolomics data to hierarchically identify genes, pathways and cells. Integrated data from these different technologies coherently describe cell types/subtypes within different nephron segments and interstitium. These spatial profiles identify cell-level functional organization of the kidney tissue as indicative of their physiological functions and map different cell subtypes to genes, proteins, metabolites and pathways. Comparison of transcellular sodium reabsorption along the nephron to levels of mRNAs encoding the different sodium transporter genes indicate that mRNA levels are largely congruent with physiological activity.This reference atlas provides an initial framework for molecular classification of kidney disease when multiple molecular mechanisms underlie convergent clinical phenotypes.
Goal: The goal of this study was to link the KPMP's molecular data to established clinical and pathologic assessments, providing a complete and individualized interpretation of a subject's kidney biopsy specimen.
Result: Despite a lack of overt pathologic evidence of diabetic kidney disease, early molecular features of diabetes were found within the kidney, consistent with the subject's clinical diagnosis.
Implication for patients: This is the first published example of the KPMP integrating molecular information into the clinical and pathologic evaluation of an individual patient's kidney disease.
Goal: To definemolecular and cellular features in a biopsy from an AKI patient using singlenucleus / cell RNA sequencing methods in conjunction with detailed histopathologicalanalysis and clinical course in order to gain mechanistic insights intocellular diversity, injury states, and clinical outcome.
Results: The molecular studies reveal remarkable cellularheterogeneity and presence of alteredcell states reflecting cellular injury and repair in a number of proximal and distal nephron celltypes, blood vessels, fibroblasts and immune cell. Correlates of the injured and regeneratingcells were identified by histopathology including features of regeneration, tubularinjury and remodeling in this patient. By leveraging the KPPMP+HuBMAP master kidney atlas, the molecularanalysis further permitted identification of genes and pathways associated withadaptive / maladaptive repair. Signatures associated with NSAID use were detected in altered tubuleseven after discontinuation of these medicines.
Implication for Patients: The molecular and pathologicalanalysis enables assessment of injury and repair processes and etiology of AKIat the time of the biopsy. Identificationof pathways that may be predictive of recovery or worsening kidney function canbe useful in assessing prognosis. Asmore of these datasets are obtained, we may be able to have a knowledge base torelate these pathways with clinical outcomes and potentially use therapeuticdrugs to inhibit those related to worsening kidney function.
Goal: Participation in the Kidney Precision Medicine Project(KPMP) means undergoing kidney biopsy and while the KPMP safety protocols are intended to minimize risk of this procedure, participants nonetheless accept some personal risk.
Results: Design and implementation of the KPMP has involved substantial ethical deliberation, and in this article, we use this experience as an example to understand the ethical foundation and implications of research that involves risk to participants.
Implication for Patients: Specifically, efforts to respect diverse participant values, support participants’ opportunity to act altruistically, and enhancing benefits to participants’ community are critical features of the KPMP research paradigm needed to respect and support participant in research that involves some personal risk.
Goal: In our paper (https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0258103), we tested three implementations of a tissue registration user interface (one on a 2D screen, two in virtual reality or VR) with regards to accuracy, completion time, and satisfaction with 42 human subjects.
Results: We found that while the VR implementations allow user to be significantly faster, more satisfied, and more accurate with regards to rotation, there was no difference regarding position accuracy, once again showing the viability of 2D interfaces for registering human tissue block inside 3D reference organs.
Implications for patients: Our incremental research and development towards accurate, quick, and satisfying 2D tissue registration enables the continued improvement of the user interfaces for building a Human Reference Atlas (https://hubmapconsortium.github.io/ccf/) in HuBMAP (https://commonfund.nih.gov/hubmap) with the goal of mapping the human body at single-cell level.
Goal: Kidney fibrosis can result in structural damage and impairment of kidney function but non-invasive biomarkers (e.g., proteins measured in a patient’s blood or urine) to assess kidney fibrosis are currently not available.
Results: In this study, we identified SMOC2, PEDF, and CDH11 as promising new biomarker proteins that may be used to estimate the degree of fibrosis in patients with kidney disease and identify patients at high risk of kidney disease progression.
Implication for Patients: These biomarkers may be used as markers of response to treatment, for example facilitating the investigation of new therapies that are under development for the treatment of kidney fibrosis
Goal: To develop a widely applicable way to stratify kidney disease severity. Chronic kidney damage is assessed by scoring the amount of interstitial fibrosis and tubular atrophy (IFTA) in a renal biopsy sample.
Results: A novel Artificial Intelligence (AI) tool was developed to predict the grade of IFTA, a known structural correlate of progressive and chronic kidney disease.
Implication for Patients: Having a computer model that can mimic an expert pathologist's workflow and assess disease grade can further the potential to increase efficiency in clinical practices. AI models that can automatically score the extent of chronic damage in the kidney can serve as a second opinion tool in clinical practices.
Goal: To guide scientific inquiry toward clinically meaningful benefit, patients are equal partners for priority setting, study design and conduct, and dissemination of findings.
Results: Patient partners in the Community Engagement Committee led the development of the informed consent process, the ethics statement, the return-of-results plan, a “patient primer” for scientists, and community advisory boards at the recruitment sites.
Implication for Patients: Patients’ viewpoints and priorities have been central in directing the KPMP to produce research that brings clinically meaningful benefit to them.
Goal: Describe the objectives and study design of the Kidney Precision Medicine Project, and the rationale for kidney precision medicine.
Results: This investigation focuses on kidney diseases that are most prevalent and therefore substantially burden the public health, including CKD attributed to diabetes or hypertension and AKI attributed to ischemic and toxic injuries.
Implication for Patients: All data from the Kidney Precision Medicine Project will be made readily available for broad use by scientists, clinicians, and patients.
Goal: Idiopathic nodular mesangial sclerosis, also called idiopathic nodular glomerulosclerosis (ING), is a rare clinical entity with an unclear pathogenesis.
Results: The hallmark of this disease is the presence of nodular mesangial sclerosis on histology without clinical evidence of diabetes kidney disease (DKD) or other predisposing diagnoses.
Implication for Patients: Despite similar clinical and histopathologic characteristics in ING and DKD, the uncovered transcriptomic signature suggests that ING has distinct molecular features from nodular DKD.
Goal: Describe patient and community engagement and the value they bring to the KPMP.
Results: The Community Engagement Committee guides KPMP research priorities from perspectives of patients and clinicians, and assures that the science is developed and conducted in a manner relevant to study participants and the clinical community.
Implications for Patients: Patients have guided the KPMP to produce research aligned with their priorities, and set new benchmarks for patient leadership in precision medicine research.
Goal: The goal was to study Proximal Tubular and Glomerular proteins using laser capture microdissection followed by mass spectrometry.
Results: We established near single-cell proteomics protocol kidney tissue and identified more than 2,500 human proteins of which 25 proteins) were specific to proximal tubules and 67 were specific to glomerulus (Glom; n = 67 proteins) regions.
Implication for Patients: This near-single-cell proteomics workflow can be extended to other kidney micro-compartments which ultimately will help understand changes in the proteomic landscape of normal kidneys as well as different etiologies of acute and chronic kidney disease.
Goal: To model the kidney disease using ontology.
Results: The development of two new community-based ontologies — the Kidney Tissue Atlas Ontology and the Ontology of Precision Medicine and Investigation —supports the creation of the Kidney Tissue Atlas, which aims to provide a comprehensive molecular, cellular and anatomical map of the kidney, leading to more advanced kidney disease modeling and analysis.
Implication for Patients: The usage of ontology supports the standard data integration and analysis of kidney precision medicine.
Goal: We sought to understand the optimal storage conditions for spatial lipidomic analysis of human kidney tissue sections, as it is common practice to share tissue among the consortium and between tissue interrogation sites.
Results: Overall, we found that molecular degradation of the tissue sections was unavoidable over time, regardless of storage conditions, but storing tissue sections in an inert gas at low temperatures can curtail molecular degradation within tissue sections.
Implications for Patients: By storing kidney tissue sections under these optimal conditions we can maximize the molecular readout from the kidney biopsies.
Interviews with three individuals who have been affected by kidney failure for their views on the importance of understanding the drivers of kidney disease, and what they hope might be achieved with this information.
Goal: The goal of this research was to develop a reliable and robust optimization strategy for our spatial metabolomics assay’s sample preparation steps that could be utilized universally for different tissue types.
Results: Through development of a novel experimental design coupled with mathematical modeling, we can optimize sample preparation for spatial metabolomics (via matrix-assisted laser desorption/ionization mass spectrometry imaging) with minimal time and tissue utilization.
Implication for Patients: This approach will ensure that we will obtain the highest quality spatial metabolomics data from the invaluable KPMP tissue biopsies.
Goal: To profile the diverse molecular cell type composition of human kidneys, we developed a reproducible method for isolating and sequencing RNA transcripts within single kidney nuclei.
Results: This enabled gene expression profiling of cell types spanning the major functional units of the kidney with minimal processing artifacts.
Implication for Patients: Using this approach, our analysis portrays remarkable cellular and molecular heterogeneity and insights into kidney organization, function and disease.
Goal: To reflect on two NIDDK consortia and the benefits of community-engaged research to nephrology.
Results: Putting patients first and meaningfully involving them in nephrology research as full partners may increase research relevance and efficiency, with particular benefits for studies addressing underserved or minority populations.
Implication for Patients: Inclusion of the patient and community perspective across the spectrum of nephrology research may benefit patients, investigators, and the nephrology field as a whole.
Goal: A review article covering the effects of GLP-1 receptor agonists on the diabetic kidney from clinical trial data to basic science and preclinical studies.
Results: These data set the stage for understanding mechanistic underpinnings, inclusive of tissue interrogation akin to KPMP, for kidney protection by GLP-1 receptor agonists.
Implication for Patients: Linking kidney disease mechanisms to therapeutic interventions helps to identify individuals who may benefit from a specific therapy.