The Michigan O’Brien Kidney Research Center: transforming translational kidney research through systems biology

Abstract

Research on kidney diseases is being transformed by the rapid expansion and innovations in omics technologies. The analysis, integration, and interpretation of big data, however, have been an impediment to the growing interest in applying these technologies to understand kidney function and failure. Targeting this urgent need, the University of Michigan O’Brien Kidney Translational Core Center (MKTC) and its Administrative Core established the Applied Systems Biology Core. The Core provides need-based support for the global kidney community centered on enabling incorporation of systems biology approaches by creating web-based, user-friendly analytic and visualization tools, like Nephroseq and Nephrocell, guiding with experimental design, and processing, analysis, and integration of large data sets. The enrichment core supports systems biology education and dissemination through workshops, seminars, and individualized training sessions. Meanwhile, the Pilot and Feasibility Program of the MKTC provides pilot funding to both early-career and established investigators new to the field, to integrate a systems biology approach into their research projects. The relevance and value of the portfolio of training and services offered by MKTC are reflected in the expanding community of young investigators, collaborators, and users accessing resources and engaging in systems biology-based kidney research, thereby motivating MKTC to persevere in its mission to serve the kidney research community by enabling access to state-of-the-art data sets, tools, technologies, expertise, and learning opportunities for transformative basic, translational, and clinical studies that will usher in solutions to improve the lives of people impacted by kidney disease.

INTRODUCTION

Chronic kidney disease (CKD) is estimated to affect more than 700 million people worldwide, leading to increased end-stage renal disease, cardiovascular disease, and related morbidity and premature death (1). The Michigan O’Brien Kidney Translational Core Center (MKTC; https://kidneycenter.med.umich.edu/) was first set up in 1988 and now is one of eight centers funded by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) in the United States (2). With the goal of providing necessary infrastructure and tools to support research on improving treatment options in CKD, the program has evolved into the current Core Center of Excellence (P30) since 2008. Each of these centers has developed around core expertise and institutional priorities that now contribute complementary and valuable resources to the kidney research community (3–5). The focus of the MKTC is to facilitate the analysis of signaling networks and large data sets for the scientific community, using a systems biology approach.

Leveraging pioneering research from podocyte biology (6) to biological mechanisms in diabetes (7, 8) and kidney transplantation (9, 10), the MKTC has focused on translational research mechanisms that have facilitated interactions between basic and clinical investigators. This complements the focus of the other O’Brien centers. The Vanderbilt O’Brien Kidney Center supports research aiming to understand mechanisms and to identify potential therapies for acute and chronic kidney disease (3), the Indiana O’Brien Center is focused on the development and dissemination of advanced methods of optical microscopy (4), and the University of Alabama at Birmingham-University of California-San Diego O’Brien Center provides resources for research related to acute kidney injury (5). Furthermore, the MKTC is also a venue for enrichment opportunities for young investigators and an incubator for new collaborations across scientific disciplines. Over the last three decades, the center has advanced its services and core expertise to be at the forefront of innovation in basic and translational nephrology research.

In keeping with expanding computational and data science resources and capabilities, the MKTC has pivoted toward growing systems biology and bioinformatics expertise to support innovative approaches in translational kidney medicine. Through its systems biology core, enrichment activities, and Pilot and Feasibility (P&F) grant programs, it has supported new discoveries and enhanced scientific progress by fostering basic, clinical, and translational research expertise, thereby linking hypothesis-generating with hypothesis-driven research. This is in keeping with the primary mission of the MKTC, to attract kidney researchers and others outside the area to learn and use omics technologies to drive discovery in the molecular pathogenesis and targeted treatments of kidney diseases.

To accomplish this mission, the MKTC has 1) created an environment that supports innovative kidney disease research; 2) attracted new scientific expertise to kidney disease research; 3) provided core services that leverage funding and contribute unique expertise to maximize the efficiency and effectiveness of the research base; 4) fostered interdisciplinary collaborations, especially in emerging areas of research, catalyzing new ideas and scientific approaches; and 5) promoted the translation of scientific discoveries from bench to bedside to community to improve public health.

WHY SYSTEMS BIOLOGY?

The genetic or environmental triggers, biological processes, rates of disease progression, and outcomes vary tremendously across the heterogeneous collection of disorders comprising CKD (11, 12). Current disease classifications and treatment options inadequately address this heterogeneity (13, 14). Central to the challenges in developing new treatments is the structural and functional complexity of the kidney.

The kidney harbors a complex structure consisting of hundreds of thousands of nephrons, each with internal heterogeneity to serve a multitude of specific functional needs. Systemic metabolic, vascular, and immune diseases all impact on kidney function, and, in turn, kidney disease profoundly alters the course of these diseases (15). Focused scientific efforts have led to the identification of many essential processes that are disrupted in CKD. However, this reductionist approach mandates evaluation of each process in isolation. Since most CKDs progress because of abnormalities in multiple interrelated pathways and networks, there is a need to go beyond isolated molecular analyses to identify the complex mechanisms underlying disease progression.

With the advent of genome-scale and multiomic analytic capabilities, it has become feasible to simultaneously investigate multiple regulatory biological systems with precision and depth. A precision medicine approach, in which the therapy is matched with the specific stage of the underlying biological disease process for each person, is needed to appropriately treat each individual with a CKD (16).

The MKTC has focused on integrating data across the entire translational spectrum encompassing basic and model organism research findings with various omics data linked to highly granular cross-sectional and longitudinal clinical and phenotypic data. This approach requires a multidisciplinary effort toward large-scale data generation and integration with clinical knowledge and entails successful collaborations between nephrologists, pathologists, biologists, epidemiologists, geneticists, bioinformaticians, biostatisticians, biochemists, and computer scientists (15).

STRUCTURE OF THE CENTER

A systems biology approach leverages computational methods to integrate diverse types of data, including demographic data, conventional clinical phenotypic data, and clinicopathological parameters, with omics data. Sophisticated information technology infrastructure and software tools requiring integrative workflows that involve a combination of statistical, computational, and mathematical techniques such as multiscalar data integrations, clustering algorithms, patient-level pathway activation scores, etc., are needed for analysis and interpretation (14, 15). Bioinformatic analytic workflows enable the exploration of the interplay of multiple genes, proteins, and molecular mechanisms involved in kidney function and disease progression (14). Our center is structured to provide the infrastructure, training, and support necessary for using systems biology tools and model systems of human kidney disease to advance translational research into patient care.

The three primary components of our center are 1) the Administrative Core, 2) the Applied Systems Biology Core (ASBC), and 3) the Enrichment Core. The Administrative Core also administers the P&F Program (Fig. 1). Each core provides critical pieces for expanding and sharing data and expertise to promote collaborations and scientific advances in kidney research, globally.

Figure 1.

The integrated cores within the Michigan Kidney Translational University of Michigan O’Brien Kidney Translational Core Center (MKTC). The major cores of the MKTC include the Administrative Core (which directs the overall center and administers the Pilot and Feasibility Program), the Applied Systems Biology Core, and the Enrichment Core.

Administrative Core

The Administrative Core organizes, stimulates, and evaluates interactions of the Center with researchers to ensure that the biomedical research cores and educational program provide optimal support. The Administrative Core also subsidizes University of Michigan centralized services to provide discount costs to investigators. The key roles of the core have been

• Providing administrative infrastructure to coordinate and integrate the research, cores, and P&F and enrichment activities of the MKTC.

• Providing clear guidance for use of MKTC services and easy access to subsidies on centralized services. This has been accomplished by a user-friendly, informative website redesign and updates, annual user surveys, outreach to core investigators with updates and improvements, and agile responses to user feedback.

• Recruiting new investigators to kidney research and the MKTC and supporting new and established investigators in kidney research.

• Raising awareness and interest in and advocating for research in kidney disease and related metabolic disorders, creating an environment that facilitates such research, and communicating significant scientific results with the support of the Enrichment Program.

• Assessing the productivity, quality, effectiveness, and appropriateness of MKTC activities.

Applied Systems Biology Core

Established in 2008, the ASBC has grown into the primary focus of the MKTC. The expanding relevance and need for systems biology infrastructure motivated the development of the ASBC as a key resource to the kidney research community at the University of Michigan, in the United States, and across the world.

As kidney research is transitioning to a data-rich science, with complex, often genome-scale data sets being generated from model systems and human disease research in an increasing number of studies, aligning findings across different technologies and platforms has become paramount for connecting the relevant kidney disease with its underlying biology. Considerable expertise and knowledge of the limitations of each platform are needed for meaningful integration. These integrative methods must extend beyond aligning different omics data sets (such as single-cell and bulk transcriptomic data) to also consider clinical data and histopathology to gain insights into disease processes (14). Appropriate statistical approaches can help mitigate false discoveries resulting from integrative “big data” approaches, whereas experimental systems like tissue culture, animal models, and kidney organoids are invaluable in demonstrating causality of observed associations from data integration methods. Databases like the LINCS consortium (lincsproject.org) and Connectivity Map (clue.io) provide additional data-rich open-source resources for validating findings (17–19).

The ASBC helps investigators access a variety of large-scale data sets generated by ongoing research projects, query the clinical, genetic, and molecular information related to their specific areas of interest, as well as customize analytic, computational, and biological support to bridge relevant gaps in successfully addressing their research questions (Fig. 2).

Figure 2.

The Applied Systems Biology Core (ASBC). The ASBC services bridge data, analytic, and technology gaps needed to advance kidney translational medicine and to serve the nephrology research community. QC, quality control.

Data generation and sources.

Originally established as one of the cores within the MKTC, the Clinical Phenotyping and Resource Biobank Core (C-PROBE) is a pioneering resource comprising rich clinical data collected longitudinally from >1,500 patients in seven Centers in the United States with CKD and acute kidney injury funded by the center award from 2013 to 2017. C-PROBE continues to serve as a rich source of digital pathology and molecular data (transcriptomic, proteomic, and metabolomic data) now being generated with independent funding from patients with kidney disease. These data continue to support investigation of molecular mechanisms and discovery and validation of biomarkers.

The ASBC routinely works with center investigators through a wide spectrum of ancillary studies to use diverse data sets from multiple cohorts spanning the globe. Studies have used, among others, information from the European Renal cDNA Bank with 2,800 renal biopsies for molecular studies from 24 European centers (20, 21), the Nephrotic Syndrome Study Network with 755 incipient nephrotic syndrome patients from 35 centers in North America (22), NIDDK’s American Indian Cohort study comprising 180 patients with diabetes (23–25), the H3 Africa CKD Network at seven African sites (26, 27), as well as the NIDDK’s Kidney Precision Medicine Project Network (28–30).

The ASBC, through projects and funding mechanisms of the investigator base, has also accumulated data sets derived from model systems of human disease such as two-dimensional cell cultures, three-dimensional organoids, and animal models, including models of type 1 and type 2 diabetic kidney disease (DKD), hypertension, transforming growth factor-β1 transgenic mice, uninephrectomy, and ischemia-reperfusion injury. All these data sets can be useful for kidney researchers and are accessible through appropriate collaborative arrangements depending on the data set ownership and funding.

Data integration and data quality control.

Advances in computational and bioinformatics technology have enabled the interrogation and organization of large-scale data sets. Bioinformatic tools, such as machine learning, enable the identification of patient subgroups based on similarities in molecular profiles representing underlying disease mechanisms (31). Several target mechanisms have been identified through combining molecular and clinical data (32) and have contributed to potential therapies (ClinicalTrials.gov: NCT03550443, NCT03749447, and NCT03019185). Similarly, subgroups of patients with kidney disease such as DKD, IgA nephropathy, lupus nephritis, and focal segmental glomerulosclerosis (FSGS) have been found to share common mechanisms that mediate kidney injury, providing opportunities for finding treatments that may work for multiple CKDs (33–35). Advances in molecular profiling technologies like single-cell and nuclear RNA sequencing (sc-RNAseq) and spatial profiling approaches have provided more granular insights into cell-level molecular processes in the context of a complex organ such as the kidney, which is composed of numerous, distinct cell types (36). The ASBC has been in the forefront of such efforts, developing and adapting tools for data integration that are best suited to the kidney research context (37). The ASBC supports the bioinformatics and computational biology capabilities needed to generate and analyze omics data along with other patient-level information such as histopathology and clinical data to understand molecular mechanisms and cellular sources of disease progression. Attention to data quality at every step, from collection of kidney tissue or biofluid samples with meticulously curated meta data sets through data generation, data integration, and data interpretation, is essential (38). The ASBC works to set standards and establish protocols that consider data quality and methodological limitations to support meaningful and qualified inferences from various analyses.

Analysis and visualization tools.

To prevent the lack of specialized training in bioinformatics and computational sciences from becoming a barrier to discovery, easy-to-navigate web-based data exploration platforms have been developed. These tools enable researchers to query data and explore clinically relevant disease variations to assess the relevance of biological pathways for discovering potential therapeutic targets and biomarkers.

The ASBC develops and maintains these tools to ensure relevance to more diverse research interests and provide for unmet needs within the research community. This includes an open-source, noncommercial analytic and data-sharing platform, tranSMART, for large-scale data analysis in renal disease cohort studies, which compiles genetic and molecular data along with longitudinal clinical data to facilitate the integration and interpretation of large-scale data sets by the respective user community. The tranSMART platform (https://i2b2transmart.org/) is a data management platform that provides tools for uploading a variety of molecular, morphometric, and clinical data organized on a deidentified individual patient level. The platform also includes a graphical interface, transformation utilities, and analytic web applications that enable users to easily compare and correlate variables across data types and patient subgroups. The ASBC has created study-specific tranSMART instances to facilitate collaboration across teams and institutions with a goal of accelerating research on healthy and disease processes.

Nephroseq disseminates and organizes data from published genomewide expression studies of human kidney diseases and kidney disease mouse models. This platform allows the user to find gene expression patterns that characterize specific disease processes, general mechanisms, or other modifying factors. Incorporating kidney biopsy gene expression data from participants with diverse ethnicities and rare as well as common diseases, Nephroseq is a valuable resource for the nephrology community and has been cited in >300 publications from investigators around the world (Fig. 3).

Figure 3.

The Nephroseq platform. Shown is the geographical distribution of registered Nephroseq users, illustrating the global relevance of this resource to the nephrology and scientific communities. Colors reflect numbers of users by country.

The ASBC has developed a viewer for single cell-derived data sources, Nephrocell (http://nephrocell.miktmc.org/). This resource provides sc-RNAseq data from human kidney tissue (36) and organoids (39). New single-cell data sets including single-cell profiles obtained from urine samples of patients with COVID-19 [sudden acute respiratory syndrome coronavirus-2 (SARS-CoV-2)] have recently been included (40).

Personalized research services.

Evaluating increasingly large and complex data sets requires sophisticated computational skills combined with bioinformatics and biostatistics training to mine these data to answer clinically relevant research questions. The ASBC provides personalized analytic support to enable highly integrated and successful translational research and to expand local, regional, and international research bases through improved integration of data from deep phenotyping to broad molecular profiling experiments. The ASBC provides guidance and assistance to researchers from experimental design to data generation and analysis of molecular profiling data. A web-based interface allows investigators to contact the ASBC for input on study design, analysis, and data sets. Additionally, the ASBC provides individualized project and grant support in statistical analyses, validations of study design, genome-scale data mapping and analyses (transcripts, proteins, metabolites, and pathways), integration of multiomic data sets to identify cross-cutting mechanisms, evaluation and validation of biomarkers, along with multivariate statistical analysis of data that is available through the MKTC partnership.

MKTC-supported research team publications demonstrate the impact of the ASBC’s contribution. One such report investigated mechanisms underlying kidney function and kidney failure in a multicenter research network (36). The group used sc-RNAseq of kidney biopsies to define molecular subtypes of glomerular diseases and focused on endothelial cell phenotypes, using in silico and in situ hybridization methods to assign and validate findings in an independent kidney disease tissue cohort. Molecular endothelial signatures suggested two distinct FSGS patient subgroups with α₂-macroglobulin as a key downstream mediator of the endothelial cell phenotype. Finally, glomerular α₂-macroglobulin transcript levels associated with lower proteinuria remission rates, linking endothelial function with long-term outcome in FSGS. The ASBC helped the investigators in defining distinct cell clusters that were linked to kidney and immune cell types with specific cell markers.

A critical part of precision medicine is developing biomarkers for accurate patient risk stratification and targeted treatment. As an example of the ASBC’s expertise in biomarker development, a team of ASBC researchers with the goal of detecting at-risk patients at early disease stages identified epidermal growth factor (EGF) as a kidney tubular cell-specific gene, whose mRNA expression in kidney tubulointerstitial cells correlated with urinary EGF (uEGF) protein level, and lower levels of uEGF predicted faster progression of CKDs, using end-stage kidney disease or a 40% reduction of baseline kidney function as end points. These results were validated in three independent kidney disease cohorts (41). The strength of this study was the use of kidney-derived molecular information as a tool suitable for clinical practice. The utility of uEGF as a prognostic biomarker has subsequently been confirmed by many other research groups in cohorts of patients with various CKDs, including DKD (42, 43), anti-neutrophil cytoplasmic antibody-associated vasculitis (44), lupus nephritis (45), Alport syndrome in children (46), nephrotic syndrome (47), and congenital anomalies of the kidney and urinary tract (48), among others. Furthermore, low uEGF was independently and inversely associated with the risk of graft failure in transplant patients and was highly predictive of this outcome (49). Finally, in two large cohorts drawn from the general population, low uEGF was independently associated with rapid kidney function loss (50), confirming its potential as a broadly applicable prognostic biomarker.

Bioinformatics and data mining are core services of the ASBC. These services played a key role in a study using human kidney organoids derived from pluripotent stem cells, which provide a novel model system for studying kidney diseases and regeneration (18). Transcriptional profiles of >12,000 cells isolated from human kidney organoid cultures were used to identify gene expression signatures shared with developing human kidneys. Bioinformatic analysis demonstrated that the gene expression signature characteristic of developing glomerular epithelial cells in organoids was observed in kidney biopsy tissue from a glomerular disease cohort. Further analysis discovered and validated that this gene signature correlated with kidney function parameters [proteinuria and estimated glomerular filtration rate (GFR)] (39).

The ASBC was able to rapidly respond to investigate mechanisms for the increased risk of COVID-19 infection among patients with diabetes and DKD. sc-RNAseq data from an early DKD cohort of participants from the Gila River Indian Community showed that cells expressing the main SARS-CoV-2 receptor, angiotensin-converting enzyme 2, and specific downstream signaling pathways were primed for viral infection and replication, explaining their greater susceptibility to the virus (40). The data generated in this study are available for open access through the Nephrocell data visualization tool. The MKTC supported a clinical biomarker study in which soluble urokinase plasminogen activator receptor levels at admission predicted in-hospital acute kidney injury and need for dialysis in COVID-19 (51). A larger multicenter International Study of Inflammation in COVID-19 observational study of 2,044 patients hospitalized with COVID-19 identified independent impact of hyperinflammation as well as glycemic control on adverse primary composite outcome of in-hospital death, need for mechanical ventilation, and need for renal replacement therapy (52). RNA-sequencing data generated from kidney tissue collected from experimental mouse models were analyzed. Self-organizing map and pairwise bioinformatic analyses were used to elucidate glomerular transcriptional changes associated with DKD (53). These analyses revealed a graded increase in inflammatory gene expression and a graded decrease in development gene expression with DKD progression that was not affected by renin-angiotensin system blockade. This result could partly explain the inadequate therapeutic efficacy of renin-angiotensin system blockers and support the need for additional therapies.

A series of publications supported by the ASBC highlighted multiomic data integration involving metabolomic/lipidomic data with transcriptional data, yielding novel metabolic/lipid pathways that are activated in CKD and DKD in both mouse model system studies as well as human cohorts including C-PROBE. The key findings include the following:

1. Tissue-specific changes in metabolism in complication-prone tissues in diabetes, with the diabetic kidney cortex exhibiting increased utilization of glycolytic fatty acid and mitochondrial metabolism, whereas nerves showed marked decline. Importantly, urinary tricarboxylic acid cycle intermediates were identified as potential prognostic biomarkers of human DKD progression (7).

2. In C-PROBE, increased abundance of saturated C16-C20 free fatty acids coupled with impaired β-oxidation and inverse partitioning into complex lipids were identified as mechanisms underpinning lipid metabolism changes that typify advancing human CKD (54).

3. Shared and distinct lipid-lipid interactions in plasma and affected organs (kidney, nerve, and retina) revealed unique pathogenic alterations in arachidonic acid and diacylglycerol and complex lipid metabolism in diabetic mouse models (55).

4. Identification of a unique triacylglycerol signature in DKD responsive to renin-angiotensin system inhibition (56) in mouse models.

5. Increased lipogenesis and impaired mitochondrial fatty acid oxidation as a predictor of type 2 DKD progression in Native American subjects with preserved GFR. Integrative transcriptomic analysis identified that renal acetyl-CoA carboxylase activation accompanies these lipidomic changes and suggests that it may be the underlying mechanism linking lipid abnormalities to DKD progression (23).

6. Functional enrichment studies identified in multiple human cohorts novel subnetworks of triacylglycerols and cardiolipins-phosphatidylethanolamines that precede the clinical outcome of end-stage kidney disease by several years (57).

7. Lipidomic integrative analysis from multiple human cohorts of type 1 DKD revealed distinct lipidomic markers that include differential incorporation of free fatty acids at the sn1 carbon of the phospholipids’ glycerol backbone as an independent predictor of rapid GFR decline in type 1 diabetes (58).

Enrichment Core

A critical function of the MKTC is to educate investigators and effectively disseminate novel approaches in systems biology and other translational research approaches in the study of CKD. The Enrichment Core arranges and supports scientific lectures and programs to stimulate, enrich, and encourage researchers at all stages of training to embark or expand on systems biology and other translational research efforts in kidney disease. The programs include the MKTC Annual Retreat, an annual symposium that serves as a major forum for the University of Michigan nephrology and translational research community to interact, learn about new methods, and initiate new collaborations, and the George O’Brien Kidney Center Research Seminar, which has been held since 1988 and features intramural and external investigators performing basic and translational research, with a focus on providing novel insights into disease mechanisms and introducing novel experimental methods. It also provides a platform for trainees and junior investigators to receive feedback for their research projects. The center also sponsors the Nephrology Grand Rounds, which showcases clinical and translational research as well as case conferences, geared toward trainees and faculty members in nephrology. The Summer Student Program allows medical and undergraduate students to participate in both clinical and basic research under supervision of MKTC faculty. Because of the COVID pandemic, students participated in research virtually in 2020 and a hybrid model was implemented in 2021. The program includes weekly lectures by faculty members on renal physiology and kidney research. On average, between six and eight students have participated in the program annually in the last 3 years. Furthermore, the MKTC participates in the National O’Brien Center Kidney Seminar Series, which includes monthly presentations from investigators of each O’Brien Center discussing specific research projects and aiming to enhance collaborations between the centers.

Pilot and Feasibility Program

The P&F Grant Program is offered to new and established investigators across the nation. This program is especially designed to bring investigators into the fields of systems biology and to enhance use of omics techniques in kidney translational research. The program targets 1) recently independent early-career investigators (at the clinical lecturer, instructor, or assistant professor levels) without current or past National Institutes of Health research support at the R01 level and 2) established investigators exploring a novel idea that represents a clear departure from their ongoing research efforts.

Over the past three cycles, successful applicants have come from the Departments of Cell and Developmental Biology, Computational Medicine and Bioinformatics, Pathology, and Internal Medicine at the University of Michigan as well as multiple departments from the University of Washington, University of Arizona, Baylor University, University of Texas Health Science Center at San Antonio, and Duke University.

Funding by the P&F Grant Program supported a recent study of the importance of protein folding and degradation in the endoplasmic reticulum to podocyte function (59). The research team uncovered a critical role of the SEL1L-HRD1 protein complex of endoplasmic reticulum-associated degradation in the maturation of nephrin, a membrane protein in podocytes that is critical for slit diaphragm formation and glomerular filtration function and is causally linked to congenital nephrotic syndrome. This study provided insights into how autosomal recessive mutations in nephrin can lead to protein misfolding and aggregation in the endoplasmic reticulum and to glomerular dysfunction by integrating findings from experiments in tissue culture and mouse model systems with sc-RNAseq and mutation analysis in patients with nephrotic syndrome. The sc-RNAseq data analysis services of the ASBC as well as the data visualization tool Nephrocell made it possible to identify which cell types in the kidney express the Sel1L-Hrd1 endoplasmic reticulum-associated degradation transcript. Confirmation of presence of this protein in podocytes with a sc-RNAseq approach provided the necessary impetus for further exploration of how this protein affected podocyte function. Two recent pilot and feasibility recipients, Dr. Beamish and Dr. Naik, used P&F grants to generate preliminary data to successfully compete for K08 awards.

FUTURE DIRECTIONS

Given the advent of single-cell technologies and their increasing use by investigators, the need for services provided by the MKTC will continue to grow. In response, the Center will expand its expertise and systems biology tools to support future needs to help translate basic science discoveries into clinically important insights that will benefit patients with kidney diseases.

GRANTS

This work was supported by the George M. O’Brien Michigan Kidney Translational Core Center, funded by National Institute of Diabetes and Digestive and Kidney Diseases Grant 2P30DK081943.

DISCLOSURES

M.K. reports grants and contracts outside the submitted work through the University of Michigan with NIH, Chan Zuckerberg Initiative, JDRF, AstraZeneca, NovoNordisk, Eli Lilly, Gilead, Goldfinch Bio, Janssen, Boehringer-Ingelheim, Moderna, European Union Innovative Medicine Initiative, Certa, Chinook, amfAR, Angion, RenalytixAI, Travere, Regeneron, and IONIS; consulting fees through the University of Michigan from Astellas, Poxel, Janssen, and UCB; and a patent, PCT/EP2014/073413 “Biomarkers and methods for progression prediction for chronic kidney disease,” licensed. D.S.G. reports grants outside of this work from Travere Therapeutics, Reata, Goldfinch Bio, Novartis, and Boehringer Ingelheim and serves on advisory or consultancy through the University of Michigan with Roche, Genentech, Astra-Zeneca, and Vertex. None of the other authors has any conflicts of interest, financial or otherwise, to disclose.

AUTHOR CONTRIBUTIONS

M.B., W.J., L.S., J.P.T., J.T., C.A.G., F.C.B., M.K., and S.P. conceived and designed research; M.B., M.K. and S.P. analyzed data; M.B., W.J., L.S., J.T., B.S., D.S.G., C.A.G., F.C.B., M.K., and S.P. prepared figures; M.B., W.J., L.S., J.P.T., J.T., B.S., R.C.W., D.S.G., C.A.G., F.C.B., M.K., and S.P. drafted manuscript; M.B., W.J., L.S., J.P.T., J.T., B.S., R.C.W., D.S.G., C.A.G. F.C.B., M.K., and S.P. edited and revised manuscript; M.B., W.J., L.S., J.P.T., J.T., B.S., R.C.W., D.S.G., C.A.G., F.C.B., M.K., and S.P. approved final version of manuscript.