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A new era in the science and care of kidney diseases

Nature Reviews Nephrology (2024)Cite this article

Abstract

Notable progress in basic, translational and clinical nephrology research has been made over the past five decades. Nonetheless, many challenges remain, including obstacles to the early detection of kidney disease, disparities in access to care and variability in responses to existing and emerging therapies. Innovations in drug development, research technologies, tissue engineering and regenerative medicine have the potential to improve patient outcomes. Exciting prospects include the availability of new drugs to slow or halt the progression of chronic kidney disease, the development of bioartificial kidneys that mimic healthy kidney functions, and tissue engineering techniques that could enable transplantable kidneys to be created from the cells of the recipient, removing the risk of rejection. Cell and gene therapies have the potential to be applied for kidney tissue regeneration and repair. In addition, about 30% of kidney disease cases are monogenic and could potentially be treated using these genetic medicine approaches. Systemic diseases that involve the kidney, such as diabetes mellitus and hypertension, might also be amenable to these treatments. Continued investment, communication, collaboration and translation of innovations are crucial to realize their full potential. In addition, increasing sophistication in exploring large datasets, implementation science, and qualitative methodologies will improve the ability to deliver transformational kidney health strategies.

Key points

  • In the past 5 decades, notable progress has been made in basic, translational and clinical nephrology research.

  • Remaining challenges in nephrology include obstacles to the early detection of kidney disease, inconsistency in access to care and variability in responses to established and emerging therapies.

  • A new approach to medical research based on close collaboration between basic and clinical scientists and clinicians is fundamental to ensure patient-centred care and improve clinical outcomes.

  • Deeper understanding and analyses of individual patients, including use of genetic profiles, biomarkers and sophisticated imaging technologies, can aid prediction of disease progression, identify risk factors and enable tailoring of treatment plans.

  • Promising future approaches to the treatment of kidney diseases include cell and gene therapies, xenotransplantation and bioartificial kidneys.

  • In-depth knowledge of the values and preferences of patients, such as their treatment goals, communication preferences, cultural beliefs and financial considerations, is essential to improving kidney care; disadvantaged populations must receive specific attention to avoid widening health inequities.

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Fig. 1: Integrated kidney care.

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References

  1. Levey, A. S. et al. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am. J. Kidney Dis. 39, 1–266 (2002).

  2. Kidney Disease. Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int. Suppl. 3, 1–150 (2013).

    Google Scholar 

  3. Bagheri, B. et al. Sodium‐glucose cotransporter 2 inhibitors: a comprehensive review from cells to bedside. Fundam. Clin. Pharmacol. 37, 481–492 (2023).

    Article  CAS  PubMed  Google Scholar 

  4. Parfianowicz, D. et al. Finerenone: a new era for mineralocorticoid receptor antagonism and cardiorenal protection. Curr. Probl. Cardiol. 47, 101386 (2022).

    Article  PubMed  Google Scholar 

  5. Fakhouri, F., Schwotzer, N., Golshayan, D. & Frémeaux-Bacchi, V. The rational use of complement inhibitors in kidney diseases. Kidney Int. Rep. 7, 1165–1178 (2022).

    Article  PubMed Central  PubMed  Google Scholar 

  6. Zhang, Z., Xu, Q. & Huang, L. B cell depletion therapies in autoimmune diseases: monoclonal antibodies or chimeric antigen receptor-based therapy? Front. Immunol. 14, 1126421 (2023).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  7. Salvadori, M. & Tsalouchos, A. Innovative immunosuppression in kidney transplantation: a challenge for unmet needs. World J. Transpl. 12, 27–41 (2022).

    Article  Google Scholar 

  8. Sánchez-Álvarez, E. et al. Survival with low- and high-flux dialysis. Clin. Kidney J. 14, 1915–1923 (2021).

    Article  PubMed  Google Scholar 

  9. Blankestijn, P. J. et al. Effect of hemodiafiltration or hemodialysis on mortality in kidney failure. N. Engl. J. Med. 389, 700–709 (2023).

    Article  CAS  PubMed  Google Scholar 

  10. Bello, A. K. et al. Epidemiology of peritoneal dialysis outcomes. Nat. Rev. Nephrol. 18, 779–793 (2022).

    Article  PubMed Central  PubMed  Google Scholar 

  11. Lewis, A. et al. Organ donation in the US and Europe: the supply vs demand imbalance. Transpl. Rev. 35, 100585 (2021).

    Article  Google Scholar 

  12. O’Hare, A. M. Patient-centered care in renal medicine: five strategies to meet the challenge. Am. J. Kidney Dis. 71, 732–736 (2018).

    Article  PubMed  Google Scholar 

  13. Kellum, J. A. et al. Acute kidney injury. Nat. Rev. Dis. Prim. 7, 52 (2021).

    Article  PubMed  Google Scholar 

  14. Pouwels, X. G. L. V. et al. Cost-effectiveness of home-based screening of the general population for albuminuria to prevent progression of cardiovascular and kidney disease. eClinicalMedicine 68, 102414 (2024).

    Article  PubMed Central  PubMed  Google Scholar 

  15. Yeo, S. C., Wang, H., Ang, Y. G., Lim, C. K. & Ooi, X. Y. Cost-effectiveness of screening for chronic kidney disease in the general adult population: a systematic review. Clin. Kidney J. 17, sfad137 (2023).

    Article  PubMed Central  PubMed  Google Scholar 

  16. Ekrikpo, U. et al. Epidemiology and outcomes of glomerular diseases in low- and middle-income countries. Semin. Nephrol. 42, 151316 (2022).

    Article  PubMed  Google Scholar 

  17. Mapes, D. L. et al. Health-related quality of life in the dialysis outcomes and practice patterns study (DOPPS). Am. J. Kidney Dis. 44, 54–60 (2004).

    Article  PubMed  Google Scholar 

  18. Lloveras, J., Arcos, E., Comas, J. & Crespo, M. et al. A paired survival analysis comparing hemodialysis and kidney transplantation from deceased elderly donors older than 65 years. Transplantation 99, 991–996 (2015).

    Article  CAS  PubMed  Google Scholar 

  19. Tonelli, M. et al. Comparison of the complexity of patients seen by different medical subspecialists in a universal health care system. JAMA Netw. Open. 1, e184852 (2018).

    Article  PubMed Central  PubMed  Google Scholar 

  20. Crews, D. C. et al. Burden, access and disparities in kidney disease. Clin. Kidney J. 12, 160–166 (2019).

    Article  PubMed Central  PubMed  Google Scholar 

  21. International Society of Nephrology. Global kidney health atlas. https://www.theisn.org/initiatives/global-kidney-health-atlas/ (accessed 27 March 2024).

  22. Kasiske, B. L., London, W. & Ellison, M. D. Race and socioeconomic factors influencing early placement on the kidney transplant waiting list. J. Am. Soc. Nephrol. 9, 2142–2147 (1998).

    Article  CAS  PubMed  Google Scholar 

  23. Malek, S. K., Keys, B. J., Kumar, S., Milford, E. & Tullius, S. G. Racial and ethnic disparities in kidney transplantation. Transpl. Int. 24, 419–424 (2011).

    Article  PubMed  Google Scholar 

  24. Daw, J. Explaining the persistence of health disparities: social stratification and the efficiency-equity trade-off in the kidney transplantation system. Am. J. Sociol. 120, 1595–1640 (2015).

    Article  Google Scholar 

  25. Davison, S. N., Jhangri, G. S. & Koffman, J. Knowledge of and attitudes towards palliative care and hospice services among patients with advanced chronic kidney disease. BMJ Support. Palliat. Care 6, 66–74 (2016).

    Article  PubMed  Google Scholar 

  26. Köttgen, A. et al. Genetics in chronic kidney disease: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) controversies conference. Kidney Int. 101, 1126–1141 (2022).

    Article  Google Scholar 

  27. Bergmann, C. et al. Polycystic kidney disease. Nat. Rev. Dis. Prim. 4, 50 (2018).

    Article  PubMed  Google Scholar 

  28. Bergmann, C. Genetics of autosomal recessive polycystic kidney disease and its differential diagnoses. Front. Pediatr. 5, 221 (2018).

    Article  PubMed Central  PubMed  Google Scholar 

  29. Warady, B. A. et al. Alport syndrome classification and management. Kidney Med. 2, 639–649 (2020).

    Article  PubMed Central  PubMed  Google Scholar 

  30. Živná, M. et al. Autosomal dominant tubulointerstitial kidney disease: a review. Am. J. Med. Genet. C. Semin. Med. Genet. 190, 309–324 (2022).

    Article  PubMed Central  PubMed  Google Scholar 

  31. Elliott, M. D. et al. Clinical and genetic characteristics of CKD patients with high-risk APOL1 genotypes. J. Am. Soc. Nephrol. 34, 909–919 (2023).

    Article  PubMed  Google Scholar 

  32. Wu, M. Y., Chen, Y. C., Chiu, I. J. & Wu, M. S. Genetic insight into primary glomerulonephritis. Nephrology 27, 649–657 (2022).

    Article  CAS  PubMed  Google Scholar 

  33. Chen, L. et al. Genome-wide assessment of genetic risk for systemic lupus erythematosus and disease severity. Hum. Mol. Genet. 29, 1745–1756 (2020).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  34. Liao, L.-N. et al. Genetic risk score for risk prediction of diabetic nephropathy in Han Chinese type 2 diabetes patients. Sci. Rep. 9, 19897 (2019).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  35. Genovese, G. et al. Association of Trypanolytic ApoL1 variants with kidney disease in African Americans. Science 329, 841–845 (2010).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  36. Egbuna, O. et al. Inaxaplin for proteinuric kidney disease in persons with two APOL1 variants. N. Engl. J. Med. 388, 969–979 (2023).

    Article  CAS  PubMed  Google Scholar 

  37. ClinGen. Clinical domain working groups: kidney disease CDWG. https://clinicalgenome.org/working-groups/clinical-domain/clingen-kidney-disease-clinical-domain-working-group/ (2024).

  38. Vanholder, R. et al. A policy call to address rare kidney disease in health care plans. Clin. J. Am. Soc. Nephrol. 18, 1510–1518 (2023).

    Article  PubMed  Google Scholar 

  39. Abe, S. et al. Explainable AI for estimating pathogenicity of genetic variants using large-scale knowledge graphs. Cancers 15, 1118 (2023).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  40. Khan, A. et al. Genome-wide polygenic score to predict chronic kidney disease across ancestries. Nat. Med. 28, 1412–1420 (2022).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  41. Wei, L., Han, Y. & Tu, C. Molecular pathways of diabetic kidney disease inferred from proteomics. Diabetes Metab. Syndr. Obes. 16, 117–128 (2023).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  42. Bai, Y. et al. Urinary proteome analysis of acute kidney injury in post-cardiac surgery patients using enrichment materials with high-resolution mass spectrometry. Front. Bioeng. Biotechnol. 10, 1002853 (2022).

    Article  PubMed Central  PubMed  Google Scholar 

  43. Moledina, D. G. et al. Identification and validation of urinary CXCL9 as a biomarker for diagnosis of acute interstitial nephritis. J. Clin. Invest. 133, e168950 (2023).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  44. Pontillo, C. & Mischak, H. Urinary peptide-based classifier CKD273: towards clinical application in chronic kidney disease. Clin. Kidney J. 10, 192–201 (2017).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  45. Zürbig, P., Mischak, H., Menne, J. & Haller, H. CKD273 enables efficient prediction of diabetic nephropathy in nonalbuminuric patients. Diabetes Care 42, e4–e5 (2019).

    Article  PubMed  Google Scholar 

  46. Critselis, E., Vlahou, A., Stel, V. S. & Morton, R. L. Cost-effectiveness of screening type 2 diabetes patients for chronic kidney disease progression with the CKD273 urinary peptide classifier as compared to urinary albumin excretion. Nephrol. Dial. Transpl. 33, 441–449 (2018).

    Article  Google Scholar 

  47. Hocher, B. & Adamski, J. Metabolomics for clinical use and research in chronic kidney disease. Nat. Rev. Nephrol. 13, 269–284 (2017).

    Article  CAS  PubMed  Google Scholar 

  48. Vanholder, R., Pletinck, A., Schepers, E. & Glorieux, G. Biochemical and clinical impact of organic uremic retention solutes: a comprehensive update. Toxins 10, 33 (2018).

    Article  PubMed Central  PubMed  Google Scholar 

  49. Glorieux, G., Nigam, S. K., Vanholder, R. & Verbeke, F. Role of the microbiome in gut-heart-kidney cross talk. Circ. Res. 132, 1064–1083 (2023).

    Article  CAS  PubMed  Google Scholar 

  50. Zoccali, C. et al. Cardiovascular complications in chronic kidney disease: a review from the European Renal and Cardiovascular Medicine Working Group of the European Renal Association. Cardiovasc. Res. 119, 2017–2032 (2023).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  51. Angelotti, M. L., Antonelli, G., Conte, C. & Romagnani, P. Imaging the kidney: from light to super-resolution microscopy. Nephrol. Dial. Transpl. 36, 19–28 (2021).

    Article  CAS  Google Scholar 

  52. van Timmeren, C. D., Tanadini-Lang, S., Alkadhi, H. & Baessler, B. Radiomics in medical imaging: “how-to” guide and critical reflection. Insights Imaging 11, 91 (2020).

    Article  PubMed Central  PubMed  Google Scholar 

  53. Arimura, H., Soufi, M., Kamezawa, H., Ninomiya, K. & Yamada, M. Radiomics with artificial intelligence for precision medicine in radiation therapy. J. Radiat. Res. 60, 150–157 (2019).

    Article  PubMed  Google Scholar 

  54. Prasad, P. V., Li, L.-P., Hack, B., Leloudas, N. & Sprague, S. M. Quantitative blood oxygenation level dependent magnetic resonance imaging for estimating intra-renal oxygen availability demonstrates kidneys are hypoxemic in human CKD. Kidney Int. Rep. 8, 1057–1067 (2023).

    Article  PubMed Central  PubMed  Google Scholar 

  55. A research study to find out how semaglutide works in the kidneys compared to placebo, in people with type 2 diabetes and chronic kidney disease (the REMODEL trial) (REMODEL). ClinicalTrials.gov https://www.clinicaltrials.gov/study/NCT04865770 (2024).

  56. Heydari, Z. et al. Organoids: a novel modality in disease modeling. Biodes Manuf. 4, 689–716 (2021).

    Article  PubMed Central  PubMed  Google Scholar 

  57. Osafune, K. iPSC technology-based regenerative medicine for kidney diseases. Clin. Exp. Nephrol. 25, 574–584 (2021).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  58. Wang, J., Lin, Y., Chen, X., Liu, Y. & Zhou, T. Mesenchymal stem cells: a new therapeutic tool for chronic kidney disease. Front. Cell Dev. Biol. 10, 910592 (2022).

    Article  PubMed Central  PubMed  Google Scholar 

  59. Zhou, T. et al. Challenges and advances in clinical applications of mesenchymal stromal cells. J. Hematol. Oncol. 14, 24 (2021).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  60. Huang, J., Kong, Y., Xie, C. & Zhou, L. Stem/progenitor cell in kidney: characteristics, homing, coordination, and maintenance. Stem Cell Res. Ther. 12, 197 (2021).

    Article  PubMed Central  PubMed  Google Scholar 

  61. Poulsom, R. et al. Bone marrow contributes to renal parenchymal turnover and regeneration. J. Pathol. 195, 229–235 (2001).

    Article  CAS  PubMed  Google Scholar 

  62. Zhu, W., Li, Y., Han, M. & Jang, J. Regulatory mechanisms and reversal of CD8+ T cell exhaustion: a literature review. Biology 12, 541 (2023).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  63. Kelley, R. et al. A population of selected renal cells augments renal function and extends survival in the ZSF1 model of progressive diabetic nephropathy. Cell Transpl. 22, 1023–1039 (2013).

    Article  Google Scholar 

  64. Bruce, A. T. et al. Selected renal cells modulate disease progression in rodent models of chronic kidney disease via NF-κB and TGF-β1 pathways. Regen. Med. 10, 815–839 (2015).

    Article  CAS  PubMed  Google Scholar 

  65. Stenvinkel, P. et al. Implantation of autologous selected renal cells in diabetic chronic kidney disease stages 3 and 4-clinical experience of a ‘First in Human’ study. Kidney Int. Rep. 1, 105–113 (2016).

    Article  PubMed Central  PubMed  Google Scholar 

  66. A long-term follow-up study of participants exposed to REACT. ClinicalTrials.gov https://www.clinicaltrials.gov/study/NCT05918523 (2024).

  67. Köllner, S. M. S., Seifert, L., Zahner, G. & Tomas, N. M. Strategies towards antigen-specific treatments for membranous nephropathy. Front. Immunol. 13, 822508 (2022).

    Article  PubMed Central  PubMed  Google Scholar 

  68. Peek, J. L. & Wilson, M. H. Cell and gene therapy for kidney disease. Nat. Rev. Nephrol. 19, 451–462 (2023).

    Article  PubMed Central  PubMed  Google Scholar 

  69. Rao, V. K., Kapp, D. & Schroth, M. Gene therapy for spinal muscular atrophy: an emerging treatment option for a devastating disease. J. Manag. Care Spec. Pharm. 24, S3–S16 (2018).

    PubMed  Google Scholar 

  70. Li, J., Qi, G., Tu, G., Yang, C. & Rong, R. Gene therapy in kidney transplantation: evidence of efficacy and future directions. Curr. Gene Ther. 17, 434–441 (2018).

    Article  Google Scholar 

  71. Abordo-Adesida, E. et al. Stability of lentiviral vector-mediated transgene expression in the brain in the presence of systemic antivector immune responses. Hum. Gene Ther. 16, 741–751 (2005).

    Article  CAS  PubMed  Google Scholar 

  72. Bulcha, J. T., Wang, Y., Ma, H., Tai, P. W. L. & Gao, G. Viral vector platforms within the gene therapy landscape. Signal. Transduct. Target. Ther. 6, 53 (2021).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  73. Yuzefovych, Y. et al. Genetic engineering of the kidney to permanently silence MHC transcripts during ex vivo organ perfusion. Front. Immunol. 11, 265 (2020).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  74. Xiang, H., Zhang, C. & Xiong, J. Emerging role of extracellular vesicles in kidney diseases. Front. Pharmacol. 13, 985030 (2022).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  75. Montgomery, R. A., Mehta, S. A., Parent, B. & Griesemer, A. Next steps for the xenotransplantation of pig organs into humans. Nat. Med. 28, 1533–1536 (2022).

    Article  CAS  PubMed  Google Scholar 

  76. Perico, N., Casiraghi, F. & Remuzzi, G. Clinical kidney xenotransplantation Major progress but more work needs to be done. Nephron 146, 610–615 (2022).

    Article  PubMed  Google Scholar 

  77. Cooper, D. K., Ekser, B. & Ramsoondar, J. et al. The role of genetically engineered pigs in xenotransplantation research. J. Pathol. 238, 288–299 (2016).

    Article  PubMed  Google Scholar 

  78. Wijkstrom, M., Iwase, H., Paris, W. & Hara, H. et al. Xenotransplantation: experimental progress and clinical prospects. Kidney 91, 790–796 (2017).

    CAS  Google Scholar 

  79. Xi, J., Zheng, W., Chen, M. & Zou, Q. et al. Genetically engineered pigs for xenotransplantation: hopes and challenges. Front. Cell Dev. Biol. 10, 1093534 (2022).

    Article  PubMed  Google Scholar 

  80. Anand, R. P., Layer, J. V., Heja, D. & Hirose, T. et al. Design and testing of a humanized porcine donor for xenotransplantation. Nature 622, 393–401 (2023).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  81. Montgomery, R. A., Stern, J. M., Lonze, B. E. & Tatapudi, V. S. et al. Results of two cases of pig-to-human kidney xenotransplantation. N. Engl. J. Med. 386, 1889–1898 (2022).

    Article  CAS  PubMed  Google Scholar 

  82. Porrett, P. M., Orandi, B. J., Kumar, V. & Houp, J. et al. First clinical-grade porcine kidney xenotransplant using a human decedent model. Am. J. Transpl. 22, 1037–1053 (2022).

    Article  Google Scholar 

  83. Hawthorne, W. J. World first pig‐to‐human cardiac xenotransplantation. Xenotransplantation 29, e12733 (2022).

    Article  PubMed Central  PubMed  Google Scholar 

  84. Griffith, B. P., Goerlich, C. E., Singh, A. K. & Rothblatt, M. et al. Genetically modified porcine-to-human cardiac xenotransplantation. N. Engl. J. Med. 387, 35–44 (2022).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  85. Loupy, A., Goutaudier, V., Giarraputo, A. & Mezine, F. et al. Immune response after pig-to-human kidney xenotransplantation: a multimodal phenotyping study. Lancet 402, 1158–1169 (2023).

    Article  CAS  PubMed  Google Scholar 

  86. Mohiuddin, M. M., Singh, A. K., Scobie, L. & Goerlich, C. E. et al. Graft dysfunction in compassionate use of genetically engineered pig-to-human cardiac xenotransplantation: a case report. Lancet 29, 397–410 (2023).

    Article  Google Scholar 

  87. Fransen, M. F. J. et al. Bioprinting of kidney in vitro models: cells, biomaterials, and manufacturing techniques. Essays Biochem. 65, 587–602 (2021).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  88. Tang, Y. S., Tsai, Y. C., Chen, T. W. & Li, S. Y. Artificial kidney engineering: the development of dialysis membranes for blood purification. Membranes 12, 177 (2022).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  89. Jin, Q., Leaman, R. & Lu, Z. Retrieve, summarize, and verify: how will chatGPT affect information seeking from the medical literature? J. Am. Soc. Nephrol. 34, 1302–1304 (2023).

    Article  PubMed  Google Scholar 

  90. Kashani, K. & Herasevich, V. Sniffing out acute kidney injury in the ICU: do we have the tools? Curr. Opin. Crit. Care 19, 531–536 (2013).

    Article  PubMed  Google Scholar 

  91. Rahman, M., Shad, F. & Smith, M. C. Acute kidney injury: a guide to diagnosis and management. Am. Fam. Physician 86, 631–639 (2012).

    PubMed  Google Scholar 

  92. Koyner, J. L., Carey, K. A., Edelson, D. P. & Churpek, M. M. The development of a machine learning inpatient acute kidney injury prediction model. Crit. Care Med. 46, 1070–1077 (2018).

    Article  PubMed  Google Scholar 

  93. Segal, Z. et al. Machine learning algorithm for early detection of end-stage renal disease. BMC Nephrol. 21, 518 (2020).

    Article  PubMed Central  PubMed  Google Scholar 

  94. Chuah, A. et al. Machine learning improves upon clinicians’ prediction of end stage kidney disease. Front. Med. 9, 837232 (2022).

    Article  Google Scholar 

  95. Yoo, K. D. et al. A machine learning approach using survival statistics to predict graft survival in kidney transplant recipients: a multicenter cohort study. Sci. Rep. 7, 8904 (2017).

    Article  PubMed Central  PubMed  Google Scholar 

  96. Chaudhuri, S. et al. Machine learning directed interventions associate with decreased hospitalization rates in hemodialysis patients. Int. J. Med. Inform. 153, 104541 (2021).

    Article  PubMed  Google Scholar 

  97. Bozzetto, M. et al. Clinical use of computational modeling for surgical planning of arteriovenous fistula for hemodialysis. BMC Med. Inf. Decis. Mak. 17, 26 (2017).

    Article  Google Scholar 

  98. Zhang, H. et al. Deep learning to classify arteriovenous access aneurysms in hemodialysis patients. Clin. Kidney J. 15, 829 (2022).

    Article  PubMed  Google Scholar 

  99. Barbieri, C. et al. An international observational study suggests that artificial intelligence for clinical decision support optimizes anemia management in hemodialysis patients. Kidney Int. 90, 422–429 (2016).

    Article  PubMed  Google Scholar 

  100. Zhang, H. et al. Real-time prediction of intradialytic hypotension using machine learning and cloud computing infrastructure. Nephrol. Dial. Transpl. 38, 1761–1769 (2023).

    Article  Google Scholar 

  101. Huo, Y., Deng, R., Liu, Q., Fogo, A. B. & Yang, H. AI applications in renal pathology. Kidney Int. 99, 1309–1320 (2021).

    Article  PubMed Central  PubMed  Google Scholar 

  102. Xi, I. L. et al. Deep learning to distinguish benign from malignant renal lesions based on routine MR imaging. Clin. Cancer Res. 26, 1944–1952 (2020).

    Article  PubMed  Google Scholar 

  103. Fuertinger, D. H., Topping, A., Kappel, F., Thijssen, S. & Kotanko, P. The virtual anemia trial: an assessment of model‐based in silico clinical trials of anemia treatment algorithms in patients with hemodialysis. CPT Pharmacomet. Syst. Pharmacol. 7, 219 (2018).

    Article  CAS  Google Scholar 

  104. Kamel Boulos, M. N. & Zhang, P. Digital twins: from personalised medicine to precision public health. J. Pers. Med. 11, 745 (2021).

    Article  PubMed Central  PubMed  Google Scholar 

  105. Bohr, A. & Memarzadeh, K. The rise of artificial intelligence in healthcare applications. In Artificial Intelligence in Healthcare (eds Bohr, A. & Memarzadeh, K.) Ch. 2, 25–60 (Academic, 2020); https://doi.org/10.1016/B978-0-12-818438-7.00002-2.

  106. INCLUSION. 10 steps to more ethical artificial intelligence. https://inclusioncloud.com/insights/blog/ethical-artificial-intelligence (accessed 1 March 2024).

  107. Glaser, J. et al. Climate change and the emergent epidemic of CKD from heat stress in rural communities: the case for heat stress nephropathy. Clin. J. Am. Soc. Nephrol. 11, 1472–1483 (2016).

    Article  PubMed Central  PubMed  Google Scholar 

  108. Lunyera, J. et al. CKD of uncertain etiology: a systematic review. Clin. J. Am. Soc. Nephrol. 11, 379–385 (2016).

    Article  CAS  PubMed  Google Scholar 

  109. Xia, J. et al. Cigarette smoking and chronic kidney disease in the general population: a systematic review and meta-analysis of prospective cohort studies. Nephrol. Dial. Transplant. 32, 475–487 (2017).

    Article  CAS  PubMed  Google Scholar 

  110. Xu, Y. et al. Associations between long-term exposure to low-level air pollution and risk of chronic kidney disease-findings from the Malmö Diet and Cancer cohort. Env. Int. 160, 107085 (2022).

    Article  CAS  Google Scholar 

  111. Kim, Y. J., Choi, W.-J., Ham, S., Kang, S.-K. & Lee, W. Association between occupational or environmental noise exposure and renal function among middle-aged and older Korean adults: a cross-sectional study. Sci. Rep. 11, 24127 (2021).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  112. Yang, T., Richards, E. M., Pepine, C. J. & Raizada, M. K. The gut microbiota and the brain-gut-kidney axis in hypertension and chronic kidney disease. Nat. Rev. Nephrol. 14, 442–456 (2018).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  113. Gryp, T. et al. Gut microbiota generation of protein-bound uremic toxins and related metabolites is not altered at different stages of chronic kidney disease. Kidney Int. 97, 1230–1242 (2020).

    Article  CAS  PubMed  Google Scholar 

  114. Hall, G., Wang, L. & Spurney, R. F. TRPC channels in proteinuric kidney diseases. Cells 9, 44 (2019).

    Article  PubMed Central  PubMed  Google Scholar 

  115. Reilly, D. F. & Breyer, M. D. The use of genomics to drive kidney disease drug discovery and development. Clin. J. Am. Soc. Nephrol. 15, 1342–1351 (2020).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  116. Yu, M. et al. Discovery of a potent and selective TRPC5 inhibitor, efficacious in a focal segmental glomerulosclerosis model. ACS Med. Chem. Lett. 10, 1579–1585 (2019).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  117. Willer, C. J. et al. Discovery and refinement of loci associated with lipid levels. Nat. Genet. 45, 1274–1283 (2013).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  118. Katzmann, J. L. & Laufs, U. PCSK9-directed therapies: an update. Curr. Opin. Lipidol. https://doi.org/10.1097/MOL.0000000000000919 (2024).

  119. Pinto, N. & Eileen Dolan, M. Clinically relevant genetic variations in drug metabolizing enzymes. Curr. Drug. Metab. 12, 487–497 (2011).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  120. Song, I. S., Shin, H. J. & Shin, J. G. Genetic variants of organic cation transporter 2 (OCT2) significantly reduce metformin uptake in oocytes. Xenobiotica 38, 1252–1262 (2008).

    Article  CAS  PubMed  Google Scholar 

  121. Kajiwara, M. et al. Identification of multidrug and toxin extrusion (MATE1 and MATE2-K) variants with complete loss of transport activity. J. Hum. Genet. 54, 40–46 (2009).

    Article  CAS  PubMed  Google Scholar 

  122. Wu, R. et al. Impact of HLA-B*58:01 allele and allopurinol-induced cutaneous adverse drug reactions: evidence from 21 pharmacogenetic studies. Oncotarget 7, 81870–81879 (2016).

    Article  PubMed Central  PubMed  Google Scholar 

  123. Min, S. et al. An integrated clinical and genetic prediction model for tacrolimus levels in pediatric solid organ transplant recipients. Transplantation 106, 597–606 (2022).

    Article  CAS  PubMed  Google Scholar 

  124. Dean, L. Azathioprine therapy and TPMT genotype. Medical Genetics Summaries https://www.ncbi.nlm.nih.gov/books/NBK100661/bin/20160503azathioprine.pdf (NCBI, 2012).

  125. Genvigir, F. D. V., Cerda, A., Hirata, T. D. C., Hirata, M. H. & Hirata, R. D. C. Mycophenolic acid pharmacogenomics in kidney transplantation. J. Transl. Genet. Genom. 4, 320–355 (2020).

    Google Scholar 

  126. Anaya, B. J. et al. Engineering of 3D printed personalized polypills for the treatment of the metabolic syndrome. Int. J. Pharm. 642, 123194 (2023).

    Article  CAS  PubMed  Google Scholar 

  127. De Jong, W. H. & Borm, P. J. A. Drug delivery and nanoparticles: applications and hazards. Int. J. Nanomed. 3, 133–149 (2008).

    Article  Google Scholar 

  128. Li, W. et al. Targeted drug delivery systems for kidney diseases. Front. Bioeng. Biotechnol. 9, 683247 (2021).

    Article  PubMed Central  PubMed  Google Scholar 

  129. Valentijn, P. P., Biermann, C. & Bruijnzeels, M. A. Value-based integrated (renal) care: setting a development agenda for research and implementation strategies. BMC Health Serv. Res. 16, 330 (2016).

    Article  PubMed Central  PubMed  Google Scholar 

  130. Collister, D. et al. Multidisciplinary chronic kidney disease clinic practices: a scoping review. Can. J. Kidney Health Dis. 6, 205435811988266 (2019).

    Article  Google Scholar 

  131. Morton, R. L. & Sellars, M. From patient-centered to person-centered care for kidney diseases. Clin. J. Am. Soc. Nephrol. 14, 623–625 (2019).

    Article  PubMed Central  PubMed  Google Scholar 

  132. Diamantidis, C. J. & Becker, S. Health information technology (IT) to improve the care of patients with chronic kidney disease (CKD). BMC Nephrol. 15, 7 (2014).

    Article  PubMed Central  PubMed  Google Scholar 

  133. Burgos-Calderón, R., Depine, S. Á. & Aroca-Martínez, G. Population kidney health. a new paradigm for chronic kidney disease management. Int. J. Env. Res. Public. Health 18, 6786 (2021).

    Article  Google Scholar 

  134. Levin, A. et al. Perspectives on early detection of chronic kidney disease: the facts, the questions, and a proposed framework for 2023 and beyond. Kidney Int. 103, 1004–1008 (2023).

    Article  PubMed  Google Scholar 

  135. Brenner, B. M., Garcia, D. L. & Anderson, S. Glomeruli and blood pressure. Less of one, more the other? Am. J. Hypertens. 1, 335–347 (1988).

    Article  CAS  PubMed  Google Scholar 

  136. Lu, E. & Chai, E. Kidney supportive care in peritoneal dialysis: developing a person-centered kidney disease care plan. Kidney Med. 4, 100392 (2022).

    Article  PubMed  Google Scholar 

  137. Nagai, K. & Itsubo, N. Environmental impact of care for end-stage kidney disease on the earth and humans. JMA J. 5, 109–113 (2022).

    Article  PubMed  Google Scholar 

  138. Vanholder, R. et al. Inequities in kidney health and kidney care. Nat. Rev. Nephrol. 19, 694–708 (2023).

    Article  PubMed  Google Scholar 

  139. Langham, R. G. et al. Kidney health for all: bridging the gap in kidney health education and literacy. Nephrol. Dial. Transpl. 37, 605–612 (2022).

    Article  Google Scholar 

  140. Consideration of sex differences is necessary to achieve health equity. Nat. Rev. Nephrol. 20, 1 (2024).

    Article  Google Scholar 

  141. Mallamaci, F. & Tripepi, G. Shedding a light on sex disparity in clinical trials in CKD patients. Clin. Kidney J. 16, 1369–1371 (2023).

    Article  PubMed Central  PubMed  Google Scholar 

  142. Yeates, K., Ghosh, S. & Kilonzo, K. Developing nephrology programs in very low-resource settings: challenges in sustainability. Kidney Int. Suppl. 3, 202–205 (2013).

    Article  Google Scholar 

  143. Kam-Tao Li, P. et al. Kidney health for everyone everywhere from prevention to detection and equitable access to care. Nephrology 24, 9–21 (2020).

    Google Scholar 

  144. Orach, C. G. Health equity: challenges in low income countries. Afr. Health Sci. 9, S49–S51 (2009).

    PubMed  Google Scholar 

  145. Luyckx, V. A., Tonelli, M. & Stanifer, J. W. The global burden of kidney disease and the sustainable development goals. Bull. World Health Organ. 96, 414–422D (2018).

    Article  PubMed Central  PubMed  Google Scholar 

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Author information

Authors and Affiliations

  1. Kidney Research Institute, New York City, NY, USA

    Carmine Zoccali

  2. Institute of Molecular Biology and Genetics (Biogem), Ariano Irpino, Italy

    Carmine Zoccali

  3. Associazione Ipertensione Nefrologia Trapianto Kidney (IPNET), c/o Nefrologia, Grande Ospedale Metropolitano, Reggio Calabria, Italy

    Carmine Zoccali

  4. Nephrology, Dialysis and Transplantation Unit Azienda Ospedaliera “Bianchi-Melacrino-Morelli”, Reggio Calabria, Italy

    Francesca Mallamaci

  5. CNR-IFC, Institute of Clinical Physiology, Research Unit of Clinical Epidemiology and Physiopathology of Kidney Diseases and Hypertension of Reggio Calabria, Reggio Calabria, Italy

    Francesca Mallamaci

  6. Department of Immunology and Inflammation, Imperial College London, London, UK

    Liz Lightstone

  7. Imperial College Healthcare NHS Trust, Hammersmith Hospital, London, UK

    Liz Lightstone

  8. George Institute for Global Health, UNSW, New Delhi, India

    Vivek Jha

  9. School of Public Health, Imperial College, London, UK

    Vivek Jha

  10. Prasanna School of Public Health, Manipal Academy of Medical Education, Manipal, India

    Vivek Jha

  11. Kolling Institute, Royal North Shore Hospital University of Sydney, Sydney, NSW, Australia

    Carol Pollock

  12. Providence Medical Research Center, Providence Inland Northwest, Spokane, Washington, USA

    Katherine Tuttle

  13. Department of Medicine, University of Washington, Seattle, Spokane, Washington, USA

    Katherine Tuttle

  14. Kidney Research Institute, Institute of Translational Health Sciences, University of Washington, Seattle, Washington, USA

    Katherine Tuttle

  15. Kidney Research Institute, New York, NY, USA

    Peter Kotanko

  16. Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Peter Kotanko

  17. Department of Nephrology, Transplantation and Internal Medicine, Medical University of Silesia, 40-027, Katowice, Poland

    Andrzej Wiecek

  18. Division of Nephrology, Department of Medicine IV, Hospital of the Ludwig Maximilians University Munich, Munich, Germany

    Hans Joachim Anders

  19. Istituto di Ricerche Farmacologiche Mario Negri IRCSS, Bergamo, Italy

    Giuseppe Remuzzi

  20. Harold Simmons Center for Kidney Disease Research and Epidemiology, California, USA

    Kamyar Kalantar-Zadeh

  21. Division of Nephrology and Hypertension, University of California Irvine, School of Medicine, Orange, Irvine, USA

    Kamyar Kalantar-Zadeh

  22. Veterans Affairs Healthcare System, Division of Nephrology, Long Beach, California, USA

    Kamyar Kalantar-Zadeh

  23. University of British Columbia, Vancouver General Hospital, Division of Nephrology, Vancouver, British Columbia, Canada

    Adeera Levin

  24. British Columbia, Provincial Kidney Agency, Vancouver, British Columbia, Canada

    Adeera Levin

  25. European Kidney Health Alliance, Brussels, Belgium

    Raymond Vanholder

  26. Nephrology Section, Department of Internal Medicine and Paediatrics, University Hospital Ghent, Ghent, Belgium

    Raymond Vanholder

Authors
  1. Carmine Zoccali
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  2. Francesca Mallamaci
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  12. Adeera Levin
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  13. Raymond Vanholder
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Contributions

C.Z. wrote the article. C.Z. and F.M. researched the data, which were subsequently integrated by the other authors. All authors made substantial contributions to discussion of the content and reviewed or edited the manuscript before submission.

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Correspondence to Carmine Zoccali.

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Nature Reviews Nephrology thanks Richard Glassock, Tetsuhiro Tanaka and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Zoccali, C., Mallamaci, F., Lightstone, L. et al. A new era in the science and care of kidney diseases. Nat Rev Nephrol (2024). https://doi.org/10.1038/s41581-024-00828-y

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