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1. Profiling of insulin-resistant kidney models and human biopsies reveals common and cell-type-specific mechanisms underpinning Diabetic Kidney Disease

Author

Lay, Abigail C., Tran, Van Du T., Nair, Viji, Betin, Virginie, Hurcombe, Jennifer A., Barrington, Alexandra F., Pope, Robert JP, Burdet, Frédéric, Mehl, Florence, Kryvokhyzha, Dmytro, Ahmad, Abrar, Sinton, Matthew C., Lewis, Philip, Wilson, Marieangela C., Menon, Rajasree, Otto, Edgar, Heesom, Kate J., Ibberson, Mark, Looker, Helen C., Nelson, Robert G., Ju, Wenjun, Kretzler, Matthias, Satchell, Simon C., Gomez, Maria F., and Coward, Richard J. M.

Published
2024
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3. Progression of Coronary Artery Calcification and Risk of Clinical Events in CKD: The Chronic Renal Insufficiency Cohort Study

Author

Anderson, Amanda H., Appel, Lawrence J., Chen, Jing, Cohen, Debbie, Dember, Laura M., Go, Alan S., Nelson, Robert G., Rahman, Mahboob, Rao, Panduranga S., Shah, Vallabh O., Unruh, Mark L., Tian, Ling, Jaeger, Byron C., Scialla, Julia J., Budoff, Matthew J., Mehta, Rupal C., Jaar, Bernard G., Saab, Georges, Dobre, Mirela A., Reilly, Muredach P., Rader, Daniel J., Townsend, Raymond R., Lash, James P., Greenland, Philip, Isakova, Tamara, and Bundy, Joshua D.

Published
2025
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4. A generalized covariate-adjusted top-scoring pair algorithm with applications to diabetic kidney disease stage classification in the Chronic Renal Insufficiency Cohort (CRIC) Study

Author

Kwan, Brian, Fuhrer, Tobias, Montemayor, Daniel, Fink, Jeffery C, He, Jiang, Hsu, Chi-yuan, Messer, Karen, Nelson, Robert G, Pu, Minya, Ricardo, Ana C, Rincon-Choles, Hernan, Shah, Vallabh O, Ye, Hongping, Zhang, Jing, Sharma, Kumar, and Natarajan, Loki

Subjects
Mathematical Sciences, Information and Computing Sciences, Statistics, Machine Learning, Kidney Disease, Diabetes, Clinical Research, Renal and urogenital, Humans, Diabetic Nephropathies, Betaine, Algorithms, Metabolomics, Renal Insufficiency, Chronic, Diabetes Mellitus, Biomarker, Classification, Feature selection, Kidney disease, Order statistics, Ranking algorithm, Biological Sciences, Bioinformatics, Biological sciences, Information and computing sciences, Mathematical sciences
Abstract

BackgroundThe growing amount of high dimensional biomolecular data has spawned new statistical and computational models for risk prediction and disease classification. Yet, many of these methods do not yield biologically interpretable models, despite offering high classification accuracy. An exception, the top-scoring pair (TSP) algorithm derives parameter-free, biologically interpretable single pair decision rules that are accurate and robust in disease classification. However, standard TSP methods do not accommodate covariates that could heavily influence feature selection for the top-scoring pair. Herein, we propose a covariate-adjusted TSP method, which uses residuals from a regression of features on the covariates for identifying top scoring pairs. We conduct simulations and a data application to investigate our method, and compare it to existing classifiers, LASSO and random forests.ResultsOur simulations found that features that were highly correlated with clinical variables had high likelihood of being selected as top scoring pairs in the standard TSP setting. However, through residualization, our covariate-adjusted TSP was able to identify new top scoring pairs, that were largely uncorrelated with clinical variables. In the data application, using patients with diabetes (n = 977) selected for metabolomic profiling in the Chronic Renal Insufficiency Cohort (CRIC) study, the standard TSP algorithm identified (valine-betaine, dimethyl-arg) as the top-scoring metabolite pair for classifying diabetic kidney disease (DKD) severity, whereas the covariate-adjusted TSP method identified the pair (pipazethate, octaethylene glycol) as top-scoring. Valine-betaine and dimethyl-arg had, respectively, ≥ 0.4 absolute correlation with urine albumin and serum creatinine, known prognosticators of DKD. Thus without covariate-adjustment the top-scoring pair largely reflected known markers of disease severity, whereas covariate-adjusted TSP uncovered features liberated from confounding, and identified independent prognostic markers of DKD severity. Furthermore, TSP-based methods achieved competitive classification accuracy in DKD to LASSO and random forests, while providing more parsimonious models.ConclusionsWe extended TSP-based methods to account for covariates, via a simple, easy to implement residualizing process. Our covariate-adjusted TSP method identified metabolite features, uncorrelated from clinical covariates, that discriminate DKD severity stage based on the relative ordering between two features, and thus provide insights into future studies on the order reversals in early vs advanced disease states.

Published
2023

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

Author

Sandholm, Niina, Cole, Joanne B, Nair, Viji, Sheng, Xin, Liu, Hongbo, Ahlqvist, Emma, van Zuydam, Natalie, Dahlström, Emma H, Fermin, Damian, Smyth, Laura J, Salem, Rany M, Forsblom, Carol, Valo, Erkka, Harjutsalo, Valma, Brennan, Eoin P, McKay, Gareth J, Andrews, Darrell, Doyle, Ross, Looker, Helen C, Nelson, Robert G, Palmer, Colin, McKnight, Amy Jayne, Godson, Catherine, Maxwell, Alexander P, Groop, Leif, McCarthy, Mark I, Kretzler, Matthias, Susztak, Katalin, Hirschhorn, Joel N, Florez, Jose C, and Groop, Per-Henrik

Subjects
Human Genome, Kidney Disease, Prevention, Genetics, Diabetes, Biotechnology, 2.1 Biological and endogenous factors, Aetiology, Renal and urogenital, Metabolic and endocrine, Good Health and Well Being, Diabetes Mellitus, Type 2, Diabetic Nephropathies, Doublecortin-Like Kinases, Fibrosis, Genome-Wide Association Study, Humans, Intracellular Signaling Peptides and Proteins, Kidney, Polymorphism, Single Nucleotide, Protein Serine-Threonine Kinases, Diabetes complications, Diabetic kidney disease, Genome-wide association study, Meta-analysis, Transcriptomics, GENIE Consortium, Genome-wide association study, Meta-analysis, Transcriptomics, Clinical Sciences, Paediatrics and Reproductive Medicine, Public Health and Health Services, Endocrinology & Metabolism
Abstract

Aims/hypothesisDiabetic 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.MethodsWe 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.ResultsThe meta-analysis identified a novel intronic variant (rs72831309) in the TENM2 gene associated with a lower risk of the combined chronic kidney disease (eGFR9.3×10-9). Gene-level analysis identified ten genes associated with DKD (COL20A1, DCLK1, EIF4E, PTPRN-RESP18, GPR158, INIP-SNX30, LSM14A and MFF; p

Published
2022

8. Neighborhood Socioeconomic Status and Cardiovascular Events in Adults With CKD: The CRIC Study

Author

Chen, Jing, Cohen, Debbie L., Dember, Laura M., Anderson, Amada H., Go, Alan S., Nelson, Robert G., Rahman, Mahboob, Rao, Panduranga S., Shah, Vallabh O., Unruh, Mark L., Aronov, Avi G., Saunders, Milda R., Hsu, Jesse Y., Sha, Daohang, Daviglus, Martha, Fischer, Michael J., Appel, Lawrence J., Sondheimer, James, He, Jiang, Rincon-Choles, Hernan, Horwitz, Edward J., Kelly, Tanika N., Ricardo, Ana C., and Lash, James P.

Published
2024
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10. Kidney Energetics and Cyst Burden in Autosomal Dominant Polycystic Kidney Disease: A Pilot Study

Author

Bjornstad, Petter, Richard, Gabriel, Choi, Ye Ji, Nowak, Kristen L., Steele, Cortney, Chonchol, Michel B., Nadeau, Kristen J., Vigers, Timothy, Pyle, Laura, Tommerdahl, Kalie, van Raalte, Daniel H., Hilkin, Allison, Driscoll, Lynette, Birznieks, Carissa, Hopp, Katharina, Wang, Wei, Edelstein, Charles, Nelson, Robert G., Gregory, Adriana V., Kline, Timothy L., Blondin, Denis, and Gitomer, Berenice

Published
2024
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11. Matrix Metalloproteinase-2 and CKD Progression: The Chronic Renal Insufficiency Cohort (CRIC) Study

Author

Appel, Lawrence J., Cohen, Debbie, Dember, Laura, Go, Alan S., Lash, James P., Nelson, Robert G., Rahman, Mahboob, Rao, Panduranga S., Shah, Vallabh O., Unruh, Mark L., Baudier, Robin L., Orlandi, Paula F., Yang, Wei, Chen, Hsiang-Yu, Bansal, Nisha, Blackston, J. Walker, Chen, Jing, Deo, Rajat, Dobre, Mirela, He, Hua, He, Jiang, Ricardo, Ana C., Shafi, Tariq, Srivastava, Anand, Xie, Dawei, Susztak, Katalin, Feldman, Harold I., and Anderson, Amanda H.

Published
2024
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12. Metabolites Associated With Uremic Symptoms in Patients With CKD: Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study

Author

Dember, Laura M., Landis, J. Richard, Townsend, Raymond R., Appel, Lawrence, Fink, Jeffrey, Rahman, Mahboob, Horwitz, Edward J., Taliercio, Jonathan J., Rao, Panduranga, Sondheimer, James H., Lash, James P., Chen, Jing, Go, Alan S., Parsa, Afshin, Rankin, Tracy, Wulczyn, Kendra E., Shafi, Tariq, Anderson, Amanda, Rincon-Choles, Hernan, Clish, Clary B., Denburg, Michelle, Feldman, Harold I., He, Jiang, Hsu, Chi-yuan, Kelly, Tanika, Kimmel, Paul L., Mehta, Rupal, Nelson, Robert G., Ramachandran, Vasan, Ricardo, Ana, Shah, Vallabh O., Srivastava, Anand, Xie, Dawei, Rhee, Eugene P., and Kalim, Sahir

Published
2024
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14. KDOQI US Commentary on the KDIGO 2020 Clinical Practice Guideline for Diabetes Management in CKD

Author

Mottl, Amy K, Alicic, Radica, Argyropoulos, Christos, Brosius, Frank C, Mauer, Michael, Molitch, Mark, Nelson, Robert G, Perreault, Leigh, and Nicholas, Susanne B

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Kidney Disease, Comparative Effectiveness Research, Patient Safety, Diabetes, Prevention, Health Services, Clinical Research, Renal and urogenital, Metabolic and endocrine, Good Health and Well Being, Diabetes Mellitus, Humans, Hypoglycemic Agents, Kidney, Nephrology, Renal Insufficiency, Chronic, Sodium-Glucose Transporter 2 Inhibitors, SGLT2 inhibitors, blood pressure control, chronic kidney disease, commentary, evidence-based recommendation, glucagon-like peptide 1 receptor agonists, glycemic targets, guideline implementation, guidelines, metformin, nephrology best practices, physical activity, protein intake, smoking, sodium intake, Public Health and Health Services, Urology & Nephrology, Clinical sciences
Abstract

In October 2020, KDIGO (Kidney Disease: Improving Global Outcomes) published its first clinical practice guideline directed specifically to the care of patients with diabetes and chronic kidney disease (CKD). This commentary presents the views of the KDOQI (Kidney Disease Outcomes Quality Initiative) work group for diabetes in CKD, convened by the National Kidney Foundation to provide an independent expert perspective on the new guideline. The KDOQI work group believes that the KDIGO guideline takes a major step forward in clarifying glycemic targets and use of specific antihyperglycemic agents in diabetes and CKD. The purpose of this commentary is to carry forward the conversation regarding optimization of care for patients with diabetes and CKD. Recent developments for prevention of CKD progression and cardiovascular events in people with diabetes and CKD, particularly related to sodium/glucose cotransporter 2 (SGLT2) inhibitors, have filled a longstanding gap in nephrology's approach to the care of persons with diabetes and CKD. The multifaceted benefits of SGLT2 inhibitors have facilitated interactions between nephrology, cardiology, endocrinology, and primary care, underscoring the need for innovative approaches to multidisciplinary care in these patients. We now have more interventions to slow kidney disease progression and prevent or delay kidney failure in patients with diabetes and kidney disease, but methods to streamline their implementation and overcome barriers in access to care, particularly cost, are essential to ensuring all patients may benefit.

Published
2022

15. Plasma Kidney Injury Molecule 1 in CKD: Findings From the Boston Kidney Biopsy Cohort and CRIC Studies

Author

Schmidt, Insa M, Srivastava, Anand, Sabbisetti, Venkata, McMahon, Gearoid M, He, Jiang, Chen, Jing, Kusek, John W, Taliercio, Jonathan, Ricardo, Ana C, Hsu, Chi-yuan, Kimmel, Paul L, Liu, Kathleen D, Mifflin, Theodore E, Nelson, Robert G, Vasan, Ramachandran S, Xie, Dawei, Zhang, Xiaoming, Palsson, Ragnar, Stillman, Isaac E, Rennke, Helmut G, Feldman, Harold I, Bonventre, Joseph V, Waikar, Sushrut S, and Investigators, Chronic Kidney Disease Biomarkers Consortium and the CRIC Study

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Kidney Disease, Clinical Research, Renal and urogenital, Good Health and Well Being, Biomarkers, Biopsy, Boston, Cohort Studies, Cross-Sectional Studies, Disease Progression, Humans, Kidney, Prospective Studies, Renal Insufficiency, Chronic, Chronic Kidney Disease Biomarkers Consortium and the CRIC Study Investigators, Public Health and Health Services, Urology & Nephrology, Clinical sciences
Abstract

Rationale & objectivePlasma kidney injury molecule 1 (KIM-1) is a sensitive marker of proximal tubule injury, but its association with risks of adverse clinical outcomes across a spectrum of kidney diseases is unknown.Study designProspective, observational cohort study.Setting & participants524 individuals enrolled into the Boston Kidney Biopsy Cohort (BKBC) Study undergoing clinically indicated native kidney biopsy with biopsy specimens adjudicated for semiquantitative scores of histopathology by 2 kidney pathologists and 3,800 individuals with common forms of chronic kidney disease (CKD) enrolled into the Chronic Renal Insufficiency Cohort (CRIC) Study.ExposureHistopathologic lesions and clinicopathologic diagnosis in cross-sectional analyses, baseline plasma KIM-1 levels in prospective analyses.OutcomesBaseline plasma KIM-1 levels in cross-sectional analyses, kidney failure (defined as initiation of kidney replacement therapy) and death in prospective analyses.Analytical approachMultivariable-adjusted linear regression models tested associations of plasma KIM-1 levels with histopathologic lesions and clinicopathologic diagnoses. Cox proportional hazards models tested associations of plasma KIM-1 levels with future kidney failure and death.ResultsIn the BKBC Study, higher plasma KIM-1 levels were associated with more severe acute tubular injury, tubulointerstitial inflammation, and more severe mesangial expansion after multivariable adjustment. Participants with diabetic nephropathy, glomerulopathies, and tubulointerstitial disease had significantly higher plasma KIM-1 levels after multivariable adjustment. In the BKBC Study, CKD in 124 participants progressed to kidney failure and 85 participants died during a median follow-up time of 5 years. In the CRIC Study, CKD in 1,153 participants progressed to kidney failure and 1,356 participants died during a median follow-up time of 11.5 years. In both cohorts, each doubling of plasma KIM-1 level was associated with an increased risk of kidney failure after multivariable adjustment (hazard ratios of 1.19 [95% CI, 1.03-1.38] and 1.10 [95% CI, 1.06-1.15] for BKBC and CRIC, respectively). There was no statistically significant association of plasma KIM-1 levels with death in either cohort.LimitationsGeneralizability and unmeasured confounding.ConclusionsPlasma KIM-1 is associated with underlying tubulointerstitial and mesangial lesions and progression to kidney failure in 2 cohort studies of individuals with kidney diseases.

Published
2022

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

Author

Smyth, Laura J, Dahlström, Emma H, Syreeni, Anna, Kerr, Katie, Kilner, Jill, Doyle, Ross, Brennan, Eoin, Nair, Viji, Fermin, Damian, Nelson, Robert G, Looker, Helen C, Wooster, Christopher, Andrews, Darrell, Anderson, Kerry, McKay, Gareth J, Cole, Joanne B, Salem, Rany M, Conlon, Peter J, Kretzler, Matthias, Hirschhorn, Joel N, Sadlier, Denise, Godson, Catherine, Florez, Jose C, Forsblom, Carol, Maxwell, Alexander P, Groop, Per-Henrik, Sandholm, Niina, and McKnight, Amy Jayne

Subjects
Biological Sciences, Genetics, Autoimmune Disease, Diabetes, Human Genome, Kidney Disease, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Renal and urogenital, Humans, DNA Methylation, Epigenome, Diabetic Nephropathies, Epigenesis, Genetic, Diabetes Mellitus, Type 1, Biomarkers, DNA, Genome-Wide Association Study, CpG Islands, GENIE consortium
Abstract

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.

Published
2022

17. Adherence to Plant-Based Diets and Risk of CKD Progression and All-Cause Mortality: Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study

Author

Chen, Jing, Cohen, Debbie L., Feldman, Harold I., Go, Alan S., Lash, James P., Nelson, Robert G., Rahman, Mahboob, Rao, Panduranga S., Shah, Vallabh O., Unruh, Mark L., Amir, Saira, Kim, Hyunju, Hu, Emily A., Ricardo, Ana C., Mills, Katherine T., He, Jiang, Fischer, Michael J., Pradhan, Nishigandha, Tan, Thida C., Navaneethan, Sankar D., Dobre, Mirela, Anderson, Cheryl A.M., Appel, Lawrence J., and Rebholz, Casey M.

Published
2024
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18. Depressive Symptoms, Antidepressants, and Clinical Outcomes in Chronic Kidney Disease: Findings from the CRIC Study

Author

Appel, Lawrence J., Chen, Jing, Cohen, Debbie L., Feldman, Harold I., Go, Alan S., Nelson, Robert G., Rahman, Mahboob, Rao, Panduranga S., Shah, Vallabh O., Unruh, Mark L., Hernandez, Rosalba, Xie, Dawei, Wang, Xue, Jordan, Neil, Ricardo, Ana C., Anderson, Amanda H., Diamantidis, Clarissa J., Kusek, John W., Yaffe, Kristine, Lash, James P., and Fischer, Michael J.

Published
2024
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21. Single-cell transcriptomics reveals a mechanosensitive injury signaling pathway in early diabetic nephropathy

Author

Liu, Shuya, Zhao, Yu, Lu, Shun, Zhang, Tianran, Lindenmeyer, Maja T., Nair, Viji, Gies, Sydney E., Wu, Guochao, Nelson, Robert G., Czogalla, Jan, Aypek, Hande, Zielinski, Stephanie, Liao, Zhouning, Schaper, Melanie, Fermin, Damian, Cohen, Clemens D., Delic, Denis, Krebs, Christian F., Grahammer, Florian, Wiech, Thorsten, Kretzler, Matthias, Meyer-Schwesinger, Catherine, Bonn, Stefan, and Huber, Tobias B.

Published
2023
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22. New Creatinine- and Cystatin C–Based Equations to Estimate GFR without Race

Author

Inker, Lesley A, Eneanya, Nwamaka D, Coresh, Josef, Tighiouart, Hocine, Wang, Dan, Sang, Yingying, Crews, Deidra C, Doria, Alessandro, Estrella, Michelle M, Froissart, Marc, Grams, Morgan E, Greene, Tom, Grubb, Anders, Gudnason, Vilmundur, Gutiérrez, Orlando M, Kalil, Roberto, Karger, Amy B, Mauer, Michael, Navis, Gerjan, Nelson, Robert G, Poggio, Emilio D, Rodby, Roger, Rossing, Peter, Rule, Andrew D, Selvin, Elizabeth, Seegmiller, Jesse C, Shlipak, Michael G, Torres, Vicente E, Yang, Wei, Ballew, Shoshana H, Couture, Sara J, Powe, Neil R, and Levey, Andrew S

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Clinical Research, Kidney Disease, Renal and urogenital, Adult, Aged, Algorithms, Black People, Creatinine, Cystatin C, Datasets as Topic, Female, Glomerular Filtration Rate, Humans, Male, Middle Aged, Racial Groups, Renal Insufficiency, Chronic, United States, Black or African American, Chronic Kidney Disease Epidemiology Collaboration, Medical and Health Sciences, General & Internal Medicine, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundCurrent equations for estimated glomerular filtration rate (eGFR) that use serum creatinine or cystatin C incorporate age, sex, and race to estimate measured GFR. However, race in eGFR equations is a social and not a biologic construct.MethodsWe developed new eGFR equations without race using data from two development data sets: 10 studies (8254 participants, 31.5% Black) for serum creatinine and 13 studies (5352 participants, 39.7% Black) for both serum creatinine and cystatin C. In a validation data set of 12 studies (4050 participants, 14.3% Black), we compared the accuracy of new eGFR equations to measured GFR. We projected the prevalence of chronic kidney disease (CKD) and GFR stages in a sample of U.S. adults, using current and new equations.ResultsIn the validation data set, the current creatinine equation that uses age, sex, and race overestimated measured GFR in Blacks (median, 3.7 ml per minute per 1.73 m2 of body-surface area; 95% confidence interval [CI], 1.8 to 5.4) and to a lesser degree in non-Blacks (median, 0.5 ml per minute per 1.73 m2; 95% CI, 0.0 to 0.9). When the adjustment for Black race was omitted from the current eGFR equation, measured GFR in Blacks was underestimated (median, 7.1 ml per minute per 1.73 m2; 95% CI, 5.9 to 8.8). A new equation using age and sex and omitting race underestimated measured GFR in Blacks (median, 3.6 ml per minute per 1.73 m2; 95% CI, 1.8 to 5.5) and overestimated measured GFR in non-Blacks (median, 3.9 ml per minute per 1.73 m2; 95% CI, 3.4 to 4.4). For all equations, 85% or more of the eGFRs for Blacks and non-Blacks were within 30% of measured GFR. New creatinine-cystatin C equations without race were more accurate than new creatinine equations, with smaller differences between race groups. As compared with the current creatinine equation, the new creatinine equations, but not the new creatinine-cystatin C equations, increased population estimates of CKD prevalence among Blacks and yielded similar or lower prevalence among non-Blacks.ConclusionsNew eGFR equations that incorporate creatinine and cystatin C but omit race are more accurate and led to smaller differences between Black participants and non-Black participants than new equations without race with either creatinine or cystatin C alone. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases.).

Published
2021

23. Frailty and Cardiovascular Outcomes in Adults With CKD: Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study

Author

Chen, Jing, Cohen, Debbie L., Feldman, Harold I., Go, Alan S., Nelson, Robert G., Rahman, Mahboob, Rao, Panduranga S., Shah, Vallabh O., Unruh, Mark L., Hannan, Mary, Chen, Jinsong, Hsu, Jesse, Zhang, Xiaoming, Saunders, Milda R., Brown, Julia, McAdams-DeMarco, Mara, Mohanty, Madhumita Jena, Vyas, Rahul, Hajjiri, Zahraa, Carmona-Powell, Eunice, Meza, Natalie, Porter, Anna C., Ricardo, Ana C., and Lash, James P.

Published
2024
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25. Hospitalization Trajectories and Risks of ESKD and Death in Individuals With CKD

Author

Srivastava, Anand, Cai, Xuan, Mehta, Rupal, Lee, Jungwha, Chu, David I, Mills, Katherine T, Shafi, Tariq, Taliercio, Jonathan J, Hsu, Jesse Y, Schrauben, Sarah J, Saunders, Milda R, Diamantidis, Clarissa J, Hsu, Chi-yuan, Waikar, Sushrut S, Lash, James P, Isakova, Tamara, Investigators, CRIC Study, Appel, Lawrence J, Feldman, Harold I, Go, Alan S, He, Jiang, Nelson, Robert G, Rahman, Mahboob, Rao, Panduranga S, Shah, Vallabh O, Townsend, Raymond R, and Unruh, Mark L

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Health Sciences, Kidney Disease, Prevention, Renal and urogenital, Good Health and Well Being, chronic kidney disease, end-stage kidney disease, hospital utilization, hospitalization, trajectory, CRIC Study Investigators, Biomedical and clinical sciences, Health sciences
Abstract

IntroductionManagement of chronic kidney disease (CKD) entails high medical complexity and often results in high hospitalization burden. There are limited data on the associations of longitudinal hospital utilization patterns with adverse clinical outcomes in individuals with CKD.MethodsWe derived cumulative all-cause hospitalization trajectory groups using latent class trajectory analysis in 3012 participants of the Chronic Renal Insufficiency Cohort (CRIC) Study who were alive and did not reach end-stage kidney disease (ESKD) within 4 years of study entry. Cox proportional hazards models tested the associations between hospitalization trajectory groups and risks of ESKD and death prior to the onset of ESKD (ESKD-censored death).ResultsWithin 4 years of study entry, there were 5658 hospitalizations among 3012 participants. We identified 3 distinct subgroups of individuals with CKD based on cumulative all-cause hospitalization trajectories over 4 years: low-utilizer (n = 1066), intermediate-utilizer (n = 1802), and high-utilizer (n = 144). High-utilizers represented a patient population of lower socioeconomic status who had a greater prevalence of comorbid conditions and lower kidney function compared with intermediate- and low-utilizers. After the 4-year ascertainment period to form the trajectory subgroups, there were 544 ESKD events and 437 ESKD-censored deaths during a median follow-up time of 5.1 years. Compared with low-utilizers, intermediate-utilizers and high-utilizers were at 1.49-fold (95% confidence interval [CI] 1.22-1.84) and 1.75-fold (95% CI 1.20-2.56) higher risk of ESKD in adjusted analyses, respectively. Compared with low-utilizers, intermediate-utilizers and high-utilizers were at 1.48-fold (95% CI 1.17-1.87) and 2.58-fold (95% CI 1.74-3.83) higher risk of ESKD-censored death in adjusted analyses, respectively.ConclusionsTrajectories of cumulative all-cause hospitalization identify subgroups of individuals with CKD who are at high risk of ESKD and death.

Published
2021

27. Fibroblast Growth Factor 23 and Risk of Heart Failure Subtype: The CRIC (Chronic Renal Insufficiency Cohort) Study

Author

Appel, Lawrence J., Chen, Jing, Cohen, Debbie L., Feldman, Harold I., Go, Alan S., Lash, James P., Nelson, Robert G., Rahman, Mahboob, Rao, Panduranga S., Shah, Vallabh O., Unruh, Mark L., Leidner, Alexander S., Cai, Xuan, Zelnick, Leila R., Lee, Jungwha, Bansal, Nisha, Pasch, Andreas, Kansal, Mayank, Anderson, Amanda Hyre, Sondheimer, James H., Townsend, Raymond R., Shah, Sanjiv J., Wolf, Myles, Isakova, Tamara, and Mehta, Rupal C.

Published
2023
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28. Blood Pressure, Incident Cognitive Impairment, and Severity of CKD: Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study

Author

Appel, Lawrence J., Chen, Jing, Cohen, Debbie L., Feldman, Harold I., Go, Alan S., Lash, James P., Nelson, Robert G., Rao, Panduranga S., Shah, Vallabh O., Unruh, Mark L., Babroudi, Seda, Tighiouart, Hocine, Schrauben, Sarah J., Cohen, Jordana B., Fischer, Michael J., Rahman, Mahboob, Hsu, Chi-yuan, Sozio, Stephen M., Weir, Matthew, Sarnak, Mark, Yaffe, Kristine, Kurella Tamura, Manjula, and Drew, David

Published
2023
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31. Ultraprocessed Foods and Kidney Disease Progression, Mortality, and Cardiovascular Disease Risk in the CRIC Study

Author

Cohen, Debbie L., Feldman, Harold I., Go, Alan S., Nelson, Robert G., Rahman, Mahboob, Shah, Vallabh O., Sullivan, Valerie K., Appel, Lawrence J., Anderson, Cheryl A.M., Kim, Hyunju, Unruh, Mark L., Lash, James P., Trego, Marsha, Sondheimer, James, Dobre, Mirela, Pradhan, Nishigandha, Rao, Panduranga S., Chen, Jing, He, Jiang, and Rebholz, Casey M.

Published
2023
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32. Cardiac Structure and Function and Subsequent Kidney Disease Progression in Adults With CKD: The Chronic Renal Insufficiency Cohort (CRIC) Study

Author

Cohen, Debbie L., Feldman, Harold I., Lash, James P., Nelson, Robert G., Rao, Panduranga S., Shah, Vallabh O., Unruh, Mark L., Ishigami, Junichi, Kansal, Mayank, Mehta, Rupal, Srivastava, Anand, Rahman, Mahboob, Dobre, Mirela, Al-Kindi, Sadeer G., Go, Alan S., Navaneethan, Sankar D., Chen, Jing, He, Jiang, Bhat, Zeenat Yousuf, Jaar, Bernard G., Appel, Lawrence J., and Matsushita, Kunihiro

Published
2023
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34. Low concentrations of medium-sized HDL particles predict incident CVD in chronic kidney disease patients

Author

Kretzler, Matthias, Gipson, Debbie, Bitzer, Markus, Gadegbeku, Crystal, Bellovich, Keith, Bhat, Zeenat, Massengill, Susan, Perumal, Kalyani, Appel, Lawrence J., Cohen, Debbie L., Lash, James P., Nelson, Robert G., Rahman, Mahboob, Shah, Vallabh O., Unruh, Mark L., Shao, Baohai, Afshinnia, Farsad, Mathew, Anna V., Ronsein, Graziella E., Thornock, Carissa, Irwin, Angela D., Kansal, Mayank, Rao, Panduranga S., Dobre, Mirela, Al-Kindi, Sadeer, Weir, Matthew R., Go, Alan, He, Jiang, Chen, Jing, Feldman, Harold, Bornfeldt, Karin E., and Pennathur, Subramaniam

Published
2023
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37. Excess risk of cardiovascular events in patients in the United States vs. Japan with chronic kidney disease is mediated mainly by left ventricular structure and function

Author

Appel, Lawrence J., Chen, Jing, Cohen, Debbie L., Lash, James P., Nelson, Robert G., Rao, Panduranga S., Rahman, Mahboob, Shah, Vallabh O., Unruh, Mark L., Imaizumi, Takahiro, Fujii, Naohiko, Hamano, Takayuki, Yang, Wei, Taguri, Masataka, Kansal, Mayank, Mehta, Rupal, Shafi, Tariq, Taliercio, Jonathan, Go, Alan, Rao, Panduranga, Hamm, L. Lee, Deo, Rajat, Maruyama, Shoichi, Fukagawa, Masafumi, and Feldman, Harold I.

Published
2023
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42. Development of Risk Prediction Equations for Incident Chronic Kidney Disease

Author

Nelson, Robert G, Grams, Morgan E, Ballew, Shoshana H, Sang, Yingying, Azizi, Fereidoun, Chadban, Steven J, Chaker, Layal, Dunning, Stephan C, Fox, Caroline, Hirakawa, Yoshihisa, Iseki, Kunitoshi, Ix, Joachim, Jafar, Tazeen H, Köttgen, Anna, Naimark, David MJ, Ohkubo, Takayoshi, Prescott, Gordon J, Rebholz, Casey M, Sabanayagam, Charumathi, Sairenchi, Toshimi, Schöttker, Ben, Shibagaki, Yugo, Tonelli, Marcello, Zhang, Luxia, Gansevoort, Ron T, Matsushita, Kunihiro, Woodward, Mark, Coresh, Josef, and Shalev, Varda

Subjects
Clinical Research, Kidney Disease, Patient Safety, Prevention, Renal and urogenital, Good Health and Well Being, Aged, Female, Glomerular Filtration Rate, Humans, Male, Middle Aged, Models, Theoretical, Renal Insufficiency, Chronic, Risk Assessment, Risk Factors, CKD Prognosis Consortium, Medical and Health Sciences, General & Internal Medicine
Abstract

ImportanceEarly identification of individuals at elevated risk of developing chronic kidney disease (CKD) could improve clinical care through enhanced surveillance and better management of underlying health conditions.ObjectiveTo develop assessment tools to identify individuals at increased risk of CKD, defined by reduced estimated glomerular filtration rate (eGFR).Design, setting, and participantsIndividual-level data analysis of 34 multinational cohorts from the CKD Prognosis Consortium including 5 222 711 individuals from 28 countries. Data were collected from April 1970 through January 2017. A 2-stage analysis was performed, with each study first analyzed individually and summarized overall using a weighted average. Because clinical variables were often differentially available by diabetes status, models were developed separately for participants with diabetes and without diabetes. Discrimination and calibration were also tested in 9 external cohorts (n = 2 253 540).ExposuresDemographic and clinical factors.Main outcomes and measuresIncident eGFR of less than 60 mL/min/1.73 m2.ResultsAmong 4 441 084 participants without diabetes (mean age, 54 years, 38% women), 660 856 incident cases (14.9%) of reduced eGFR occurred during a mean follow-up of 4.2 years. Of 781 627 participants with diabetes (mean age, 62 years, 13% women), 313 646 incident cases (40%) occurred during a mean follow-up of 3.9 years. Equations for the 5-year risk of reduced eGFR included age, sex, race/ethnicity, eGFR, history of cardiovascular disease, ever smoker, hypertension, body mass index, and albuminuria concentration. For participants with diabetes, the models also included diabetes medications, hemoglobin A1c, and the interaction between the 2. The risk equations had a median C statistic for the 5-year predicted probability of 0.845 (interquartile range [IQR], 0.789-0.890) in the cohorts without diabetes and 0.801 (IQR, 0.750-0.819) in the cohorts with diabetes. Calibration analysis showed that 9 of 13 study populations (69%) had a slope of observed to predicted risk between 0.80 and 1.25. Discrimination was similar in 18 study populations in 9 external validation cohorts; calibration showed that 16 of 18 (89%) had a slope of observed to predicted risk between 0.80 and 1.25.Conclusions and relevanceEquations for predicting risk of incident chronic kidney disease developed from more than 5 million individuals from 34 multinational cohorts demonstrated high discrimination and variable calibration in diverse populations. Further study is needed to determine whether use of these equations to identify individuals at risk of developing chronic kidney disease will improve clinical care and patient outcomes.

Published
2019

43. Self-reported Physical Activity and Cardiovascular Events in Adults With CKD: Findings From the CRIC (Chronic Renal Insufficiency Cohort) Study

Author

Appel, Lawrence J., Chen, Jing, Cohen, Debbie L., Feldman, Harold I., Go, Alan S., Nelson, Robert G., Rahman, Mahboob, Rao, Panduranga S., Shah, Vallabh O., Unruh, Mark L., Bruinius, Jacob W., Hannan, Mary, Chen, Jinsong, Brown, Julia, Kansal, Mayank, Meza, Natalie, Saunders, Milda R., He, Jiang, Ricardo, Ana C., and Lash, James P.

Published
2022
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45. Aspirin for Primary and Secondary Prevention of Mortality, Cardiovascular Disease, and Kidney Failure in the Chronic Renal Insufficiency Cohort (CRIC) Study

Author

Appel, Lawrence J., Cohen, Debbie L., Feldman, Harold I., Lash, James P., Nelson, Robert G., Rao, Panduranga S., Shah, Vallabh O., Unruh, Mark L., Taliercio, Jonathan J., Nakhoul, Georges, Mehdi, Ali, Yang, Wei, Sha, Daohang, Schold, Jesse D., Kasner, Scott, Weir, Matthew, Hassanein, Mohamed, Navaneethan, Sankar D., Krishnan, Geetha, Kanthety, Radhika, Go, Alan S., Deo, Rajat, Lora, Claudia M., Jaar, Bernard G., Chen, Teresa K., Chen, Jing, He, Jiang, and Rahman, Mahboob

Published
2022
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46. Black and White Adults With CKD Hospitalized With Acute Kidney Injury: Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study

Author

Appel, Lawrence J., Chen, Jing, Cohen, Debbie L., Lash, James P., Nelson, Robert G., Rahman, Mahboob, Rao, Panduranga S., Shah, Vallabh O., Unruh, Mark L., Muiru, Anthony N., Yang, Jingrong, Derebail, Vimal K., Liu, Kathleen D., Feldman, Harold I., Srivastava, Anand, Bhat, Zeenat, Saraf, Santosh L., Chen, Teresa K., He, Jiang, Estrella, Michelle M., Go, Alan S., and Hsu, Chi-yuan

Published
2022
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47. Results of untargeted analysis using the SOMAscan proteomics platform indicates novel associations of circulating proteins with risk of progression to kidney failure in diabetes

Author

Kobayashi, Hiroki, Looker, Helen C., Satake, Eiichiro, Saulnier, Pierre Jean, Md Dom, Zaipul I., O’Neil, Kristina, Ihara, Katsuhito, Krolewski, Bozena, Galecki, Andrzej T., Niewczas, Monika A., Wilson, Jonathan M., Doria, Alessandro, Duffin, Kevin L., Nelson, Robert G., and Krolewski, Andrzej S.

Published
2022
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48. Aminoaciduria and metabolic dysregulation during diabetic ketoacidosis: Results from the diabetic kidney alarm (DKA) study

Author

Melena, Isabella, Piani, Federica, Tommerdahl, Kalie L., Severn, Cameron, Chung, Linh T., MacDonald, Alexis, Vinovskis, Carissa, Cherney, David, Pyle, Laura, Roncal-Jimenez, Carlos A., Lanaspa, Miguel A., Rewers, Arleta, van Raalte, Daniël H., Cara-Fuentes, Gabriel, Parikh, Chirag R., Nelson, Robert G., Pavkov, Meda E., Nadeau, Kristen J., Johnson, Richard J., and Bjornstad, Petter

Published
2022
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49. Endogenous adenine mediates kidney injury in diabetic models and predicts diabetic kidney disease in patients

Author

Sharma, Kumar, Zhang, Guanshi, Hansen, Jens, Bjornstad, Petter, Lee, Hak Joo, Menon, Rajasree, Hejazi, Leila, Liu, Jian-Jun, Franzone, Anthony, Looker, Helen C., Choi, Byeong Yeob, Fernandez, Roman, Venkatachalam, Manjeri A., Kugathasan, Luxcia, Sridhar, Vikas S., Natarajan, Loki, Zhang, Jing, Sharma, Varun S., Kwan, Brian, Waikar, Sushrut S., Himmelfarb, Jonathan, Tuttle, Katherine R., Kestenbaum, Bryan, Fuhrer, Tobias, Feldman, Harold I., de Boer, Ian H., Tucci, Fabio C., Sedor, John, Heerspink, Hiddo Lambers, Schaub, Jennifer, Otto, Edgar A., Hodgin, Jeffrey B., Kretzler, Matthias, Anderton, Christopher R., Alexandrov, Theodore, Cherney, David, Lim, Su Chi, Nelson, Robert G., Gelfond, Jonathan, and Iyengar, Ravi

Subjects
United States. National Center for Advancing Translational Sciences, Thermo Fisher Scientific Inc., Bayer AG, Boehringer Ingelheim GmbH, AstraZeneca PLC, Eli Lilly and Co., Novo Nordisk A/S, Sanofi S.A., Medical research -- Health aspects, Medicine, Experimental -- Health aspects, Scientific equipment and supplies industry -- Health aspects, Chronic kidney failure -- Health aspects, Medical colleges -- Health aspects, Type 2 diabetes -- Health aspects, Native Americans -- Health aspects, Pharmaceutical industry -- Health aspects, Purines -- Health aspects, Health care industry
Abstract

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality; however, few mechanistic biomarkers are available for high-risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from the Chronic Renal Insufficiency Cohort (CRIC) study, the Singapore Study of Macro-angiopathy and Micro-vascular Reactivity in Type 2 Diabetes (SMART2D), and the American Indian Study determined whether urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in the CRIC study and SMART2D. ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in the CRIC study, SMART2D, and the American Indian study. Empagliflozin lowered UAdCR in nonmacroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology, and single-cell transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mTOR. Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD., Introduction Progression to organ failure is marked by fibrosis and loss of architecture in solid organs, such as the kidney. In almost all progressive chronic kidney diseases (CKDs), the features [...]

Published
2023
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50. Emergency Department/Urgent Care as Usual Source of Care and Clinical Outcomes in CKD: Findings From the Chronic Renal Insufficiency Cohort Study

Author

Appel, Lawrence J., Feldman, Harold I., Go, Alan S., Nelson, Robert G., Rahman, Mahboob, Rao, Panduranga S., Shah, Vallabh O., Townsend, Raymond R., Unruh, Mark L., Toth-Manikowski, Stephanie M., Hsu, Jesse Y., Fischer, Michael J., Cohen, Jordana B., Lora, Claudia M., Tan, Thida C., He, Jiang, Greer, Raquel C., Weir, Matthew R., Zhang, Xiaoming, Schrauben, Sarah J., Saunders, Milda R., Ricardo, Ana C., and Lash, James P.

Published
2022
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