Present and future directions in diabetic kidney disease

Abstract

Diabetic kidney disease (DKD) is the leading cause of kidney failure and is associated with substantial risk of cardiovascular disease, morbidity, and mortality. Traditionally, DKD prevention and management have focused on addressing hyperglycemia, hypertension, obesity, and renin-angiotensin system activation as important risk factors for disease. Over the last decade, sodium-glucose cotransporter-2 inhibitors and glucagon-like peptide-1 receptor agonists have been shown to meaningfully reduce risk of diabetes-related kidney and cardiovascular complications. Additional agents demonstrating benefit in DKD such as non-steroidal mineralocorticoid receptor antagonists and endothelin A receptor antagonists are further contributing to the growing arsenal of DKD therapies. With the availability of greater therapeutic options comes the opportunity to individually optimize DKD prevention and management. Novel applications of transcriptomic, proteomic, and metabolomic/lipidomic technologies, as well as use of artificial intelligence and reinforced learning methods through consortia such as the Kidney Precision Medicine Project and focused studies in established cohorts hold tremendous promise for advancing our understanding and treatment of DKD. Specifically, enhanced understanding of the molecular mechanisms underlying DKD pathophysiology may allow for the identification of new mechanism-based DKD subtypes and the development and implementation of targeted therapies. Implementation of personalized care approaches has the potential to revolutionize DKD care.

Keywords: Chronic kidney disease; Diabetic kidney disease; Omics; Precision medicine.

Figure 1.. Timeline of current and future randomized controlled trials of sodium glucose cotransporter 2 inhibitors (SGLT2i) and glucagon-like receptor agonists (GLP-1 RA).

Reprinted with permission. Circulation.2020;142:e265-e286. ©2020 American Heart Association, Inc.

Figure 2.

Summary of KPMP technologies.

Figure 3.. Identification of lipid classes using mass spectrometry.

(a) Chemical structure of phosphatidylethanolamine (PE) 36:1. The fragments identified using tandem mass spectrometry (MS–MS) are highlighted. (b) MS1 spectra, identifying the [M–H] precursor ion with its expected m/z (highlighted in pink on the spectra). (c) MS–MS (or MS2) spectra, which identify the fragments of PE 36:1 derived from the precursor ions. Reprinted with permission from Springer Nature: Elsevier, from Nature Reviews Nephrology, “Lipidomic approaches to dissect dysregulated lipid metabolism in kidney disease,” Baek et al., 18:1, 2022; permission conveyed through Copyright Clearance Center, Inc.

Figure 4.

(A) Enrichment analysis of proximal tubular marker genes, proteins, and metabolites. Dynamic enrichment analysis of marker genes, proteins, and metabolites of each proximal tubule subtype/subsegment reveals corresponding top subcellular processes. (B) Tubular aerobic and anaerobic energy generation profiles by cell type. Energy profiles were generated by combining a novel ontology allowing for distinction of aerobic and anaerobic energy pathways with cell marker genes. Reprinted from Hansen J et al., Science Advances 2022. From Hansen et al., “A reference tissue atlas for the human kidney” Sci Adv. 2022 Jun 10;8(23):eabn4965. doi: 10.1126/sciadv.abn4965. Epub 2022 Jun 8. PMID: 35675394; PMCID: PMC9176741. © The Authors, some rights reserved; exclusive licensee AAAS. Distributed under a CC BY-NC 4.0 license http://creativecommons.org/licenses/by-nc/4.0/[creativecommons.org]”. Reprinted with permission from AAAS.

Figure 5.. Differences in carbon chain length and number of double bonds in complex lipids and acylcarnitines between adults with type 2 diabetes with and without progressive kidney function decline.

(A) Greater relative abundance of longer unsaturated triacylglycerols (TAGs) in the serum of adults with progressive (n = 32) versus non-progressive (n = 60) eGFR decline. (B) A similar pattern was found when all participants were grouped based on whether they achieved a sustained GFR <90 (n = 33), <60 (n = 13), and <30 mL/min (n = 6). (C) Lower relative abundance of longer unsaturated acylcarnitines (ACs) in adults with progressive versus non-progressive eGFR decline. (D) A similar trend was noted in abundance of ACs by carbon number, when all participants were grouped based on whether they achieved a sustained GFR <90 (n = 33), <60 (n = 13), or <30 mL/min (n = 6). Reprinted from Afshinnia F et al., JCI Insight 2019. Reprinted with permission of American Society for Clinical Investigation, from JCI Insight, “Increased lipogenesis and impaired β-oxidation predict type 2 diabetic kidney disease progression in American Indians,” Afshinnia et al., 21:4, 2019; permission conveyed through Copyright Clearance Center, Inc.