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Diabetic nephropathy research advancements

Diabetic nephropathy research advancements

The study Neprhopathy that urinary type IV collagen levels were higher Dance performance diet planning advancemenys and associated with urinary albumin and serum creatinine, suggesting that urinary Health and environmental impact assessment IV collagen may be a promising biomarker Micronutrient deficiency and immune function early diagnosis nephhropathy DN. Article CAS Google Scholar Download references. The mechanisms underlying DKD can be broadly conceptualized as stemming from an interplay of three key processes, each with variable contributions depending on the genetic makeup of an individual, which accounts for heterogeneity in the hemodynamic, metabolic, and inflammatory components Fig. Neil G. Noce A, Fabrini R, Dessi M, Bocedi A, Santini S, Rovella V, et al. The definition, classification, and prognosis of chronic kidney disease: a KDIGO Controversies Conference report.

Dance performance diet planning of Nephrology and Endocrinology, The University of Tokyo Graduate Advancekents of Medicine, Tokyo, Japan. Dance performance diet planning PDF. Masaomi Advvancements reports personal fees from Akebia, grants and personal fees from Astellas, personal fees from AstraZeneca, grants and Ulcer prevention habits fees from Nephripathy, grants and Eating window and meal frequency fees from Boehringer Ingelheim, personal fees from GSK, grants and personal fees from Researcb, grants and Micronutrient deficiency and immune function fees from Kyowa Kirin, grants Diaebtic personal fees from Torii, grants and personal fees from Micronutrient deficiency and immune function Tanabe, grants and personal fees Body mass index Ono, grants davancements personal fees from Chugai, Diabetci and personal fees from Daiichi Sankyo, advvancements from Adavncements.

Tetsuhiro Tanaka has received honoraria from Desearch and Astellas, and Dance performance diet planning grant from JT. Skip Navigation Skip to contents Search Nfphropathy Current Nephropaathy issue Ahead-of print Browse All issues Article by category Article by Diabetic retinopathy neovascularization Article by Category Best paper of the year Most view Most cited Funded articles Diabetes Metab J Search Author index Collections Guidelines in DMJ Fact sheets in DMJ COVID in DMJ Dance performance diet planning contributors For Authors Instructions to authors Dance performance diet planning processing charge e-submission For Reviewers Instructions for reviewers How advancementz become a advancementss Best reviewers For Readers Readership Subscription Permission guidelines Advancrments Aims and nephropahty About the journal Editorial board Management Diabstic Best practice Metrics Contact us Nepyropathy policy Yoga Retreats and Workshops Diabetic nephropathy research advancements publication ethics Peer review policy Copyright advvancements open access policy Article sharing author self-archiving policy Nephrkpathy policy Reseach sharing policy Preprint policy Advertising policy E-Submission.

mobile menu button. Author information Article notes Copyright and License information Division of Nephrology and Endocrinology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan Corresponding author: Tetsuhiro Tanaka Division of Nephrology and Endocrinology, The University of Tokyo Graduate School of Medicine, Hongo, Bunkyo-ku, Tokyo, Japan E-mail: tetsu-tky umin.

ABSTRACT Diabetic kidney disease DKD is the major cause of end-stage kidney disease. However, only renin-angiotensin system inhibitor with multidisciplinary treatments is effective for DKD.

Insodium-glucose cotransporter 2 SGLT2 inhibitor showed efficacy against DKD in Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation CREDENCE trial, adding a new treatment option. However, the progression of DKD has not been completely controlled.

The patients with transient exposure to hyperglycemia develop diabetic complications, including DKD, even after normalization of their blood glucose.

Temporary hyperglycemia causes advanced glycation end product AGE accumulations and epigenetic changes as metabolic memory. The drugs that improve metabolic memory are awaited, and AGE inhibitors and histone modification inhibitors are the focus of clinical and basic research.

In addition, incretin-related drugs showed a renoprotective ability in many clinical trials, and these trials with renal outcome as their primary endpoint are currently ongoing. Hypoxia-inducible factor prolyl hydroxylase inhibitors recently approved for renal anemia may be renoprotective since they improve tubulointerstitial hypoxia.

Thus, following SGLT2 inhibitor, numerous novel drugs could be utilized in treating DKD. Future studies are expected to provide new insights. Keywords : Diabetic nephropathies ; Epigenomics ; Glycation end products, advanced ; Hypoxia-inducible factor 1 ; NF-E2-related factor 2 ; Sodium-glucose transporter 2.

The concept of diabetic kidney disease and diabetic nephropathy. GFR, glomerular filtration rate. The time course of current treatments. The time course of future treatments. Citations Citations to this article as recorded by. PubReader ePub Link Cite CITE. export Copy Format NLM AMA APA MLA. Download Citation Download a citation file in RIS format that can be imported by all major citation management software, including EndNote, ProCite, RefWorks, and Reference Manager.

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Treatment of Diabetic Kidney Disease: Current and Future Diabetes Metab J.

: Diabetic nephropathy research advancements

Frontiers | Editorial: Advances in the research of diabetic nephropathy, volume II

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Clin Nutr Res. Ahola KAJ, Forsblom C, Groop PH. Adherence to special diets and its association with meeting the nutrient recommendations in individuals with type 1 diabetes. Acta Diabetol. Download references. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Fatima College of Health Sciences, PO Box , Abu Dhabi, UAE. You can also search for this author in PubMed Google Scholar. Correspondence to Mahaboob Khan Sulaiman. Open Access This article is distributed under the terms of the Creative Commons Attribution 4. Reprints and permissions. Sulaiman, M. Diabetic nephropathy: recent advances in pathophysiology and challenges in dietary management.

Diabetol Metab Syndr 11 , 7 Download citation. Received : 16 October Accepted : 17 January Published : 23 January Anyone you share the following link with will be able to read this content:. Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative. Skip to main content. Search all BMC articles Search. Download PDF. Abstract Background Diabetic nephropathy DN or diabetic kidney disease refers to the deterioration of kidney function seen in chronic type 1 and type 2 diabetes mellitus patients.

Conclusion This review will summarize current advances in staging and molecular pathogenesis of DN. Introduction In , the International Diabetic Federation estimated that the prevalence of diabetes was 8.

Table 1 Staging of diabetic nephropathy Full size table. Risk factors for diabetic nephropathy Many epidemiological studies demonstrate that ethnicity, family history, gestational diabetes, elevated blood pressure, dyslipidaemia, obesity and insulin resistance are the major risk factors of diabetic nephropathy [ 14 ].

Modifiable vs non-modifiable risk factors: recent advances Although nephropathy is the strongest predictor of mortality in patients with diabetes, its development involves important inter-individual variations.

Type of diabetes and their progression to diabetic nephropathy Although microalbuminuria is a confirmatory test for diagnosis of diabetic nephropathy, not all patients progress to macroalbuminuria. Potential serum biomarkers of diabetic nephropathy: recent advances Traditionally, biomarkers are evaluated based on their ability to predict the onset or monitor the progression of DN.

Diet therapy in diabetic nephropathy and its importance The primary goal of diabetic nephropathy treatment is to prevent microalbuminuria from progressing to macroalbuminuria and an eventual decrease in renal function and associated heart disorders. Abbreviations CKD: chronic kidney disease DN: diabetic nephropathy GFR: glomerular filtration rate ESKD: end stage kidney disease DM: diabetes mellitus DKD: diabetic kidney disease.

References International Diabetes Federation IDF Diabetes Atlas. Article CAS Google Scholar Zhang J, Liu J, Qin X. EMPA-REG Outcome, BI Empagliflozin Cardiovascular Outcome Event Trial in Type 2 Diabetes Mellitus Patients; LS, least squares. Additionally, in a small open-label randomized crossover clinical study, the efficacy and safety of dapagliflozin and a low dose of the steroidal MRA eplerenone were evaluated in a cohort of patients with CKD.

The combination of the two drugs was associated with an additive effect on albuminuria reduction compared with the use of either drug alone.

Importantly, the incidence of hyperkalemia was significantly less in the combination group than in the group that received eplerenone alone This is consistent with data from the larger FIDELIO-DKD trial that demonstrated greater protection from hyperkalemia when an SGLT2 inhibitor was combined with finerenone The use of combination therapies with NS-MRAs and SGLT2 inhibitors was further explored in the FIDELITY subgroup analysis, which revealed that, compared with placebo, cardiorenal benefits of finerenone were appreciably higher irrespective of concomitant GLP-1RA or SGLT2 inhibitor use at baseline or anytime during the trial.

An important caveat is that GLP-1 RA and SGLT2 inhibitor users comprised 6. More importantly, there was no sign that drug coadministration with finerenone increased any risk of kidney injury When combined with finerenone, SGLT2 inhibitors reduced hyperkalemic events compared with levels found in nonusers 8.

These are separate retrospective analyses of renal outcome trials clearly showing a protective effect of SGLT2 inhibitors from hyperkalemia in the setting of NS-MRA and MRA use 98 , Since the institution of the RAS blockade in the s, we have witnessed significant strides in addressing the unmitigated risk associated with DKD progression.

We now have two additional drug classes to add to the RAS blockers, SGLT2 inhibitors and NS-MRAs, bolstered by a robust body of outcome data, and a possible third class. The efficacy of GLP-1 RAs is supported by retrospective analyses but needs to be proven in the ongoing FLOW randomized clinical trial.

The safety and tolerability of these two drug classes, when given together against a backdrop of maximal RAS blockade, are very encouraging and reflect the complexity of the underlying pathophysiology that drives DKD progression.

Moreover, the protective role of SGLT2 inhibitors in preventing hyperkalemia with finerenone use is very heartening. This article is featured in a podcast available at diabetesjournals.

was supported in part by a National Institutes of Health T32 award. Duality of Interest. reports being a consultant to and on steering committees of several outcome trials of companies, including KBP Biosciences, Janssen, Novo Nordisk, Ionis, Alnylam, ESTAR, Bayer, and AstraZeneca.

No other potential conflicts of interest relevant to this article were reported. Author Contributions. and G. researched the data and shared writing and editing responsibilities for the manuscript. Sign In or Create an Account. Search Dropdown Menu. header search search input Search input auto suggest.

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toolbar search search input Search input auto suggest. Graphical Abstract View large Download slide. View large Download slide. Figure 1. Figure 2. Figure 3. Figure 4. Figure 5. Figure 6. Figure 7. Albuminuria and renal insufficiency prevalence guides population screening: results from the NHANES III.

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Kidney disease as a risk factor for development of cardiovascular disease: a statement from the American Heart Association Councils on Kidney in Cardiovascular Disease, High Blood Pressure Research, Clinical Cardiology, and Epidemiology and Prevention.

The effect of angiotensin-converting-enzyme inhibition on diabetic nephropathy. Renoprotective effect of the angiotensin-receptor antagonist irbesartan in patients with nephropathy due to type 2 diabetes.

Effects of losartan on renal and cardiovascular outcomes in patients with type 2 diabetes and nephropathy. Baseline eGFR, albuminuria and renal outcomes in patients with SGLT2 inhibitor treatment: an updated meta-analysis.

Novel non-steroidal mineralocorticoid receptor antagonists in cardiorenal disease. Role of the angiotensin type 2 receptor in the regulation of blood pressure and renal function.

Endothelin modulates angiotensin II-induced mitogenesis of human mesangial cells. Effects of different antihypertensive treatments on morphologic progression of diabetic nephropathy in uninephrectomized dogs.

Arginine vasopressin stimulates human mesangial cell production of endothelin. Differential effects of calcium channel blockers on size selectivity of proteinuria in diabetic glomerulopathy.

Changes in proximal tubular reabsorption modulate microvascular regulation via the TGF system. Sodium glucose cotransporter 2 inhibitors in the treatment of diabetes mellitus: cardiovascular and kidney effects, potential mechanisms, and clinical applications.

The physical basis of renal fibrosis: effects of altered hydrodynamic forces on kidney homeostasis. Renoprotective effects of SGLT2 inhibitors: beyond glucose reabsorption inhibition.

Progression of chronic kidney disease after acute kidney injury: role of self-perpetuating versus hemodynamic-induced fibrosis. Immunity and inflammation in diabetic kidney disease: translating mechanisms to biomarkers and treatment targets.

Markers of inflammation and oxidative stress in the development and progression of renal disease in diabetic patients. Endothelial toxicity of high glucose and its by-products in diabetic kidney disease.

Remodeling of the rat right and left ventricles in experimental hypertension. Renin-angiotensin system and myocardial fibrosis in hypertension: regulation of the myocardial collagen matrix. Contribution of endothelin-1 to renal activator protein-1 activation and macrophage infiltration in aldosterone-induced hypertension.

Nonepithelial mineralocorticoid receptor activation as a determinant of kidney disease. Mineralocorticoid receptor antagonists and kidney diseases: pathophysiological basis.

Mineralocorticoid receptor signaling as a therapeutic target for renal and cardiac fibrosis. Myeloid mineralocorticoid receptor controls macrophage polarization and cardiovascular hypertrophy and remodeling in mice. The myeloid mineralocorticoid receptor controls inflammatory and fibrotic responses after renal injury via macrophage interleukin-4 receptor signaling.

Reversal of cardiac and renal fibrosis by pirfenidone and spironolactone in streptozotocin-diabetic rats. Rationale, design, and baseline characteristics of ARTS-DN: a randomized study to assess the safety and efficacy of finerenone in patients with type 2 diabetes mellitus and a clinical diagnosis of diabetic nephropathy.

A randomized controlled study of finerenone versus placebo in Japanese patients with type 2 diabetes mellitus and diabetic nephropathy.

Mineralocorticoid Receptor Antagonist Tolerability Study—Diabetic Nephropathy ARTS-DN Study Group. Effect of finerenone on albuminuria in patients with diabetic nephropathy: a randomized clinical trial.

Apararenone in patients with diabetic nephropathy: results of a randomized, double-blind, placebo-controlled phase 2 dose-response study and open-label extension study.

Efficacy and safety of esaxerenone CS for the treatment of type 2 diabetes with microalbuminuria: a randomized, double-blind, placebo-controlled, phase II trial. Association of longitudinal trajectory of albuminuria in young adulthood with myocardial structure and function in later life: Coronary Artery Risk Development in Young Adults CARDIA study.

de Zeeuw. Albuminuria, a therapeutic target for cardiovascular protection in type 2 diabetic patients with nephropathy. Albuminuria and blood pressure, independent targets for cardioprotective therapy in patients with diabetes and nephropathy: a post hoc analysis of the combined RENAAL and IDNT trials.

Albuminuria and kidney function independently predict cardiovascular and renal outcomes in diabetes. Mortality and morbidity in relation to changes in albuminuria, glucose status and systolic blood pressure: an analysis of the ONTARGET and TRANSCEND studies.

Kidney outcomes in long-term studies of ruboxistaurin for diabetic eye disease. sTNFR1, neutrophil gelatinase-associated lipocalin, C-reactive protein, and complement 3a with cleaved C-terminal arginine C3a-desArg were identified as the most strongly prognostic biomarkers [ 39 ].

The large amount of data generated by kidney imaging with clinically available modalities such as ultrasound and MRI is a potentially rich source of biomarkers to inform DKD prognostication and treatment response [ 16, 26 ]. Such biomarkers may be human-visible and quantifiable by manual, semi-automated, or automated means.

One such example in the field of autosomal dominant polycystic kidney disease is total kidney volume TKV , a surrogate marker of disease progression which correlates with cyst volume and decline in eGFR [ 40 ].

An automated segmentation method based on deep learning has been developed to calculate TKV in a fast and reproducible manner, and demonstrated good agreement with TKV values calculated from manual segmentations [ 41 ].

Alternatively, in the field of computer vision, high-dimensional numeric data may be extracted from radiologic images and analysed using machine or deep learning approaches to classify images and detect patterns which are not visible to the human eye.

As part of the Biomarker Enterprise to Attack Diabetic Kidney Disease BEAt-DKD consortium, the prospective, multi-centre iBEAt cohort study is the largest DKD imaging study to date and aims to determine whether ultrasound and MRI renal imaging biomarkers provide insight into the heterogeneity in DKD pathogenesis and can prognosticate adverse outcomes amongst patients with type 2 DKD [ 26 ].

A key advantage of imaging over other biomarker approaches to personalise DKD management is the fact that the left and right kidneys as well as the renal cortex and medulla can be assessed independently, potentially providing more granularity into functional and structural heterogeneity amongst patients with DKD [ 26 ].

As diabetic retinopathy and DKD are closely intertwined as microvascular complications of diabetes mellitus, retinal imaging is also a potentially rich source of imaging biomarkers to inform DKD management [ 42 ].

Endothelial and microvessel dysfunction contribute to the development of DKD and premature cardiovascular disease amongst patients with diabetes mellitus [ 42 ]. Homology between the vasculature of the eye and the kidney suggests that inferences regarding the microvasculature of the kidney can be made from retinal imaging, providing a rationale to image accessible microvessels in the eye to improve DKD prognostication [ 42 ].

For example, retinal images were used to train and validate a deep learning algorithm which accurately predicted CKD status in community-based Asian cohorts [ 43 ]. The area under the receiver operating characteristic curve of the deep learning algorithm improved when considered alongside conventional CKD risk factors such as age, gender, ethnicity, diabetes mellitus, and hypertension [ 43 ].

By capturing deeper vascular networks such as the choroidal circulation at near-histological resolution, the advent of optical coherence tomography OCT constitutes a major advance in retinal imaging which has transformed ophthalmology care [ 44 ]. OCT can now also be deployed in preclinical models of retinopathy [ 44 ].

Deep learning has been coupled with OCT imaging to triage and diagnose the commonest sight-threatening retinal diseases in an automated fashion and with similar accuracy to that of expert physicians [ 45 ].

Thus, combining the imaging power of cross-sectional chorioretinal OCT imaging with the analytical power of deep learning holds great promise as a means of developing prognostic imaging biomarkers related to adaptations of the renal microvasculature in people with diabetes mellitus [ 42 ].

Similar to radiologic images of the kidney, digitised whole slide images WSIs and transmission electron microscopy TEM images of kidney biopsies contain a wealth of data which may be optimally analysed using deep learning approaches [ 46, 47 ]. Deep learning approaches may be used to automate the extraction of descriptive and quantitative structural features from WSIs and TEM images with improved reproducibility [ 46, 47 ].

The concept of reproducibility is an important one as although an inter-pathologist intra-class correlation coefficient of 0. Furthermore, semi- or wholly automated means of classifying DKD histologically would reduce personnel requirements and improve efficiency of assigning DKD diagnoses in routine clinical care.

Thus, deep learning may support high-throughput and reproducible quantitative feature extraction in experimental models of renal injury. Furthermore, the trained convolutional neural network performed well on human samples, thereby providing a link between automated histopathological assessment across the preclinical and clinical domains [ 49 ].

Indeed, a convolutional neural network was also used to segment PAS-stained kidney biopsy samples from 54 patients with DKD and classify them according to the Tervaert schema, achieving a high level of agreement with three independent pathologists [ 50 ].

In the assessment of kidney structural features, deep learning has mainly been applied to digital pathology images thus far, although researchers have started to evaluate this strategy on TEM images with reasonable success [ 52 ].

Some of the biomedical technologies which support omics analyses are outlined in Figure 1. In many cases, the application of multiple technologies to characterize a particular molecular domain often provides complementary rather than redundant information. Moreover, integration of data from several molecular domains is key to characterizing the molecular heterogeneity of DKD, although integrative multi-omic analyses are not trivial owing to the complexity of the multiple high-dimensional datasets involved [ 17, 56 ].

It is also worth noting that changes in different molecular domains such as the transcriptome, the proteome, and the metabolome may not necessarily directly correlate [ 16, 57, 58 ]. For example, factors impacting translational efficiency will diminish mRNA-protein correlations for a given target, as will modalities of protein regulation other than gene transcription, such as post-translational modifications [ 57 ].

Furthermore, differences in the coverage of molecular domains by omics technologies may result in difficulties mapping insights from one to the other [ 16, 58 ].

Techniques that allow for integration of not only two data domains at a time such as the transcriptome and the proteome but also allow for simultaneous integration of clinical phenotypic data, imaging data, and histopathological data along with multiple molecular omics data domains are essential to gain more holistic insights into cellular function and interaction in a complex organ system such as the diabetic kidney [ 17, 56 ].

The current one-size-fits-all approach to DKD care ignores the clinically apparent heterogeneity in disease prognosis and treatment-responsiveness [ 10 ]. It is hoped that a systems biology approach to DKD research will pave the way for a precision medicine approach to routine DKD care by unravelling individual-level molecular mechanisms which underlie progressive DKD and which are amenable to targeting by existing or novel therapeutic strategies [ 15, 16 ].

Certain priorities for translational DKD research which may be advanced by a systems nephrology approach include: 1. The development of model systems in vitro or animal which reliably recapitulate progressive and advanced human DKD characterized by single-cell and spatially resolved transcriptomics, thereby enhancing the translational relevance of preclinical DKD studies;.

The identification of biomarkers which predict response to RAAS blockade, SGLT2is, and other emerging disease-modifying treatments for DKD in light of the inter-individual variability in treatment response; and.

The delineation of mechanisms of DKD progression in the face of combined therapy with RAAS blockade and an SGLT2i, the current backbone of treatment, which may help define targets for novel therapies which minimise the significant residual risk of progressive renal functional decline.

However, the efficacy of appropriately targeted novel therapeutics may still be impacted by inter-individual pharmacokinetic differences. Thus, pharmacogenomic profiling will play an important role in optimising outcomes for individuals with DKD. While a comprehensive systems nephrology approach is now technically feasible in research studies, this must be balanced with plans for eventual implementation of elements of this paradigm in clinical practice.

The value of biological insights derived from the refined techniques currently available must be balanced against their clinical translatability; researchers and clinicians alike should grapple with this compromise from the outset in an effort to prioritize which elements of the systems nephrology paradigm offer benefit to the largest number of patients in clinical practice.

This will help to ensure that implementation of a systems nephrology approach in routine DKD care will not perpetuate, or indeed exacerbate, inequity in healthcare delivery. This manuscript was invited following a presentation at the European Renal Association Diabesity Working Group Annual CME in Maribor, Slovenia on September 16th—17th Figure 1 was created with BioRender.

This work was performed within the Irish Clinical Academic Training ICAT Programme, supported by the Wellcome Trust and the Health Research Board Grant No. This research was funded in whole, or in part, by the Wellcome Trust Grant No.

For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. Martin wrote the manuscript and Neil G.

Docherty provided proof-reading and critical review. Martin and Neil G. Docherty reviewed and approved the final manuscript.

Sign In or Create an Account. Search Dropdown Menu. header search search input Search input auto suggest. filter your search All Content All Journals Nephron. Advanced Search. Skip Nav Destination Close navigation menu Article navigation. The Promise of Personalised Diabetic Kidney Disease Care.

Model Systems and Data Sources. Non-Omics Data. Molecular Omics Data. Conflict of Interest Statement. Funding Sources. Author Contributions. Article Navigation. Review Articles September 11 Early Publication. A Systems Nephrology Approach to Diabetic Kidney Disease Research and Practice Subject Area: Nephrology.

Martin Diabetes Complications Research Centre, School of Medicine, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland. liampvmartin gmail.

This Site. Google Scholar. Neil G. Docherty Neil G. Nephron 1— Article history Received:. Cite Icon Cite. toolbar search Search Dropdown Menu. toolbar search search input Search input auto suggest. Journal Section:. View large Download slide. Table 1. An essential toolkit for a systems nephrology approach to diabetic kidney disease a.

View Large. The development of model systems in vitro or animal which reliably recapitulate progressive and advanced human DKD characterized by single-cell and spatially resolved transcriptomics, thereby enhancing the translational relevance of preclinical DKD studies; 2.

The identification of biomarkers which predict response to RAAS blockade, SGLT2is, and other emerging disease-modifying treatments for DKD in light of the inter-individual variability in treatment response; and 3.

The authors have no conflicts of interest to declare. Oshima M, Shimizu M, Yamanouchi M, Toyama T, Hara A, Furuichi K, et al. Trajectories of kidney function in diabetes: a clinicopathological update. Nat Rev Nephrol. Afkarian M, Sachs MC, Kestenbaum B, Hirsch IB, Tuttle KR, Himmelfarb J, et al.

Kidney disease and increased mortality risk in type 2 diabetes. J Am Soc Nephrol. Perkovic V, Jardine MJ, Neal B, Bompoint S, Heerspink HJL, Charytan DM, et al. Canagliflozin and renal outcomes in type 2 diabetes and nephropathy. N Engl J Med. Heerspink HJL, Stefánsson BV, Correa-Rotter R, Chertow GM, Greene T, Hou F-F, et al.

Dapagliflozin in patients with chronic kidney disease. Shaman AM, Bain SC, Bakris GL, Buse JB, Idorn T, Mahaffey KW, et al. Effect of the glucagon-like peptide-1 receptor agonists semaglutide and liraglutide on kidney outcomes in patients with type 2 diabetes: pooled analysis of SUSTAIN 6 and LEADER.

Heerspink HJL, Sattar N, Pavo I, Haupt A, Duffin KL, Yang Z, et al. Effects of tirzepatide versus insulin glargine on kidney outcomes in type 2 diabetes in the SURPASS-4 trial: post-hoc analysis of an open-label, randomised, phase 3 trial.

Lancet Diabetes Endocrinol. Bakris GL, Agarwal R, Anker SD, Pitt B, Ruilope LM, Rossing P, et al. Effect of finerenone on chronic kidney disease outcomes in type 2 diabetes.

Martin WP, Docherty NG, Le Roux CW. Impact of bariatric surgery on cardiovascular and renal complications of diabetes: a focus on clinical outcomes and putative mechanisms. Expert Rev Endocrinol Metab.

Martin WP, White J, Lopez-Hernandez FJ, Docherty NG, le Roux CW. Metabolic surgery to treat obesity in diabetic kidney disease, chronic kidney disease, and end-stage kidney disease; what are the unanswered questions?

Front Endocrinol.

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Additionally, in a small open-label randomized crossover clinical study, the efficacy and safety of dapagliflozin and a low dose of the steroidal MRA eplerenone were evaluated in a cohort of patients with CKD. The combination of the two drugs was associated with an additive effect on albuminuria reduction compared with the use of either drug alone.

Importantly, the incidence of hyperkalemia was significantly less in the combination group than in the group that received eplerenone alone This is consistent with data from the larger FIDELIO-DKD trial that demonstrated greater protection from hyperkalemia when an SGLT2 inhibitor was combined with finerenone The use of combination therapies with NS-MRAs and SGLT2 inhibitors was further explored in the FIDELITY subgroup analysis, which revealed that, compared with placebo, cardiorenal benefits of finerenone were appreciably higher irrespective of concomitant GLP-1RA or SGLT2 inhibitor use at baseline or anytime during the trial.

An important caveat is that GLP-1 RA and SGLT2 inhibitor users comprised 6. More importantly, there was no sign that drug coadministration with finerenone increased any risk of kidney injury When combined with finerenone, SGLT2 inhibitors reduced hyperkalemic events compared with levels found in nonusers 8.

These are separate retrospective analyses of renal outcome trials clearly showing a protective effect of SGLT2 inhibitors from hyperkalemia in the setting of NS-MRA and MRA use 98 , Since the institution of the RAS blockade in the s, we have witnessed significant strides in addressing the unmitigated risk associated with DKD progression.

We now have two additional drug classes to add to the RAS blockers, SGLT2 inhibitors and NS-MRAs, bolstered by a robust body of outcome data, and a possible third class. The efficacy of GLP-1 RAs is supported by retrospective analyses but needs to be proven in the ongoing FLOW randomized clinical trial.

The safety and tolerability of these two drug classes, when given together against a backdrop of maximal RAS blockade, are very encouraging and reflect the complexity of the underlying pathophysiology that drives DKD progression. Moreover, the protective role of SGLT2 inhibitors in preventing hyperkalemia with finerenone use is very heartening.

This article is featured in a podcast available at diabetesjournals. was supported in part by a National Institutes of Health T32 award. Duality of Interest. reports being a consultant to and on steering committees of several outcome trials of companies, including KBP Biosciences, Janssen, Novo Nordisk, Ionis, Alnylam, ESTAR, Bayer, and AstraZeneca.

No other potential conflicts of interest relevant to this article were reported. Author Contributions. and G. researched the data and shared writing and editing responsibilities for the manuscript. Sign In or Create an Account. Search Dropdown Menu.

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Clinical Application. The Additive Value of Drug Combination. Article Information. Article Navigation. Review August 25 Diabetic Nephropathy: Update on Pillars of Therapy Slowing Progression Sandra C.

Naaman ; Sandra C. Section of Endocrinology, Diabetes, and Metabolism, Department of Medicine, and American Heart Association Comprehensive Hypertension Center, University of Chicago Medicine, Chicago, IL.

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Differential effects of calcium channel blockers on size selectivity of proteinuria in diabetic glomerulopathy. Changes in proximal tubular reabsorption modulate microvascular regulation via the TGF system. Sodium glucose cotransporter 2 inhibitors in the treatment of diabetes mellitus: cardiovascular and kidney effects, potential mechanisms, and clinical applications.

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de Zeeuw. Albuminuria, a therapeutic target for cardiovascular protection in type 2 diabetic patients with nephropathy. Albuminuria and blood pressure, independent targets for cardioprotective therapy in patients with diabetes and nephropathy: a post hoc analysis of the combined RENAAL and IDNT trials.

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Sulodexide fails to demonstrate renoprotection in overt type 2 diabetic nephropathy. However, certain limitations of kidney organoids are recognised [ 27, 28 ]. For example, current kidney organoid models lack a dedicated circulation and fenestrated glomerular capillaries [ 27 ], primarily due to the paucity of endothelial cells, which are estimated to represent just 0.

Furthermore, the tissue culture media used in kidney organoid differentiation protocols are high in glucose, thereby potentially confounding disease versus control comparisons for studies with a DKD focus [ 27 ]. It is unclear whether organoids would mature normally in the presence of a normal glucose concentration [ 27 ].

Thus, refinements to kidney organoid differentiation protocols will be necessary before they can realize their full potential as a comprehensive in vitro model of DKD [ 27 ]. Renal slice culture from nephrectomy specimens could offer an additional platform, which although less amenable to genetic manipulation than organoids, have advantages regarding cellular composition and tissue integrity and maturity [ 31 ].

Integration of target discovery in organoids with subsequent assessment of pharmacological responses in renal slice culture could offer a pragmatic means of mitigating attrition rates between preclinical and early phase clinical studies.

Clinical phenotypic data derived from electronic health records are a rich resource which may be harnessed to individualise prognosis and treatment response [ 15, 16 ].

Clustering of patients with newly diagnosed adult-onset diabetes mellitus on the basis of 6 variables age, body-mass index, glycated haemoglobin, glutamic acid decarboxylase antibodies, and homoeostatic model assessment 2 HOMA2 estimates of β-cell function and insulin resistance across multiple independent Scandinavian cohorts reproducibly identified 5 subgroups of patients with substantially different risks of diabetes complications [ 32 ].

In particular, the severe insulin-resistant diabetes cluster, characterized by high body-mass index, hyperinsulinaemia, and mild hyperglycaemia, had the highest risks of incident DKD and end-stage kidney disease ESKD [ 32 ].

Assessment of individual proteins may also be used to enhance prognostication of adverse CKD outcomes in patients with diabetes mellitus [ 10 ]. More broadly, 17 proteins from the tumour necrosis factor-receptor superfamily, including sTNFR1 and sTNFR2, were strongly associated with year ESKD risk in cohorts of patients with type 1 and type 2 diabetes mellitus [ 35 ].

Circulating levels of kidney injury molecule-1 and N-terminal pro-brain natriuretic peptide also strongly predict DKD progression [ 37, 38 ]. sTNFR1, neutrophil gelatinase-associated lipocalin, C-reactive protein, and complement 3a with cleaved C-terminal arginine C3a-desArg were identified as the most strongly prognostic biomarkers [ 39 ].

The large amount of data generated by kidney imaging with clinically available modalities such as ultrasound and MRI is a potentially rich source of biomarkers to inform DKD prognostication and treatment response [ 16, 26 ]. Such biomarkers may be human-visible and quantifiable by manual, semi-automated, or automated means.

One such example in the field of autosomal dominant polycystic kidney disease is total kidney volume TKV , a surrogate marker of disease progression which correlates with cyst volume and decline in eGFR [ 40 ]. An automated segmentation method based on deep learning has been developed to calculate TKV in a fast and reproducible manner, and demonstrated good agreement with TKV values calculated from manual segmentations [ 41 ].

Alternatively, in the field of computer vision, high-dimensional numeric data may be extracted from radiologic images and analysed using machine or deep learning approaches to classify images and detect patterns which are not visible to the human eye.

As part of the Biomarker Enterprise to Attack Diabetic Kidney Disease BEAt-DKD consortium, the prospective, multi-centre iBEAt cohort study is the largest DKD imaging study to date and aims to determine whether ultrasound and MRI renal imaging biomarkers provide insight into the heterogeneity in DKD pathogenesis and can prognosticate adverse outcomes amongst patients with type 2 DKD [ 26 ].

A key advantage of imaging over other biomarker approaches to personalise DKD management is the fact that the left and right kidneys as well as the renal cortex and medulla can be assessed independently, potentially providing more granularity into functional and structural heterogeneity amongst patients with DKD [ 26 ].

As diabetic retinopathy and DKD are closely intertwined as microvascular complications of diabetes mellitus, retinal imaging is also a potentially rich source of imaging biomarkers to inform DKD management [ 42 ]. Endothelial and microvessel dysfunction contribute to the development of DKD and premature cardiovascular disease amongst patients with diabetes mellitus [ 42 ].

Homology between the vasculature of the eye and the kidney suggests that inferences regarding the microvasculature of the kidney can be made from retinal imaging, providing a rationale to image accessible microvessels in the eye to improve DKD prognostication [ 42 ]. For example, retinal images were used to train and validate a deep learning algorithm which accurately predicted CKD status in community-based Asian cohorts [ 43 ].

The area under the receiver operating characteristic curve of the deep learning algorithm improved when considered alongside conventional CKD risk factors such as age, gender, ethnicity, diabetes mellitus, and hypertension [ 43 ].

By capturing deeper vascular networks such as the choroidal circulation at near-histological resolution, the advent of optical coherence tomography OCT constitutes a major advance in retinal imaging which has transformed ophthalmology care [ 44 ].

OCT can now also be deployed in preclinical models of retinopathy [ 44 ]. Deep learning has been coupled with OCT imaging to triage and diagnose the commonest sight-threatening retinal diseases in an automated fashion and with similar accuracy to that of expert physicians [ 45 ].

Thus, combining the imaging power of cross-sectional chorioretinal OCT imaging with the analytical power of deep learning holds great promise as a means of developing prognostic imaging biomarkers related to adaptations of the renal microvasculature in people with diabetes mellitus [ 42 ].

Similar to radiologic images of the kidney, digitised whole slide images WSIs and transmission electron microscopy TEM images of kidney biopsies contain a wealth of data which may be optimally analysed using deep learning approaches [ 46, 47 ].

Deep learning approaches may be used to automate the extraction of descriptive and quantitative structural features from WSIs and TEM images with improved reproducibility [ 46, 47 ]. The concept of reproducibility is an important one as although an inter-pathologist intra-class correlation coefficient of 0.

Furthermore, semi- or wholly automated means of classifying DKD histologically would reduce personnel requirements and improve efficiency of assigning DKD diagnoses in routine clinical care. Thus, deep learning may support high-throughput and reproducible quantitative feature extraction in experimental models of renal injury.

Furthermore, the trained convolutional neural network performed well on human samples, thereby providing a link between automated histopathological assessment across the preclinical and clinical domains [ 49 ].

Indeed, a convolutional neural network was also used to segment PAS-stained kidney biopsy samples from 54 patients with DKD and classify them according to the Tervaert schema, achieving a high level of agreement with three independent pathologists [ 50 ].

In the assessment of kidney structural features, deep learning has mainly been applied to digital pathology images thus far, although researchers have started to evaluate this strategy on TEM images with reasonable success [ 52 ]. Some of the biomedical technologies which support omics analyses are outlined in Figure 1.

In many cases, the application of multiple technologies to characterize a particular molecular domain often provides complementary rather than redundant information.

Moreover, integration of data from several molecular domains is key to characterizing the molecular heterogeneity of DKD, although integrative multi-omic analyses are not trivial owing to the complexity of the multiple high-dimensional datasets involved [ 17, 56 ].

It is also worth noting that changes in different molecular domains such as the transcriptome, the proteome, and the metabolome may not necessarily directly correlate [ 16, 57, 58 ]. For example, factors impacting translational efficiency will diminish mRNA-protein correlations for a given target, as will modalities of protein regulation other than gene transcription, such as post-translational modifications [ 57 ].

Furthermore, differences in the coverage of molecular domains by omics technologies may result in difficulties mapping insights from one to the other [ 16, 58 ]. Techniques that allow for integration of not only two data domains at a time such as the transcriptome and the proteome but also allow for simultaneous integration of clinical phenotypic data, imaging data, and histopathological data along with multiple molecular omics data domains are essential to gain more holistic insights into cellular function and interaction in a complex organ system such as the diabetic kidney [ 17, 56 ].

The current one-size-fits-all approach to DKD care ignores the clinically apparent heterogeneity in disease prognosis and treatment-responsiveness [ 10 ]. It is hoped that a systems biology approach to DKD research will pave the way for a precision medicine approach to routine DKD care by unravelling individual-level molecular mechanisms which underlie progressive DKD and which are amenable to targeting by existing or novel therapeutic strategies [ 15, 16 ].

Certain priorities for translational DKD research which may be advanced by a systems nephrology approach include: 1. The development of model systems in vitro or animal which reliably recapitulate progressive and advanced human DKD characterized by single-cell and spatially resolved transcriptomics, thereby enhancing the translational relevance of preclinical DKD studies;.

The identification of biomarkers which predict response to RAAS blockade, SGLT2is, and other emerging disease-modifying treatments for DKD in light of the inter-individual variability in treatment response; and. The delineation of mechanisms of DKD progression in the face of combined therapy with RAAS blockade and an SGLT2i, the current backbone of treatment, which may help define targets for novel therapies which minimise the significant residual risk of progressive renal functional decline.

However, the efficacy of appropriately targeted novel therapeutics may still be impacted by inter-individual pharmacokinetic differences.

Thus, pharmacogenomic profiling will play an important role in optimising outcomes for individuals with DKD. While a comprehensive systems nephrology approach is now technically feasible in research studies, this must be balanced with plans for eventual implementation of elements of this paradigm in clinical practice.

The value of biological insights derived from the refined techniques currently available must be balanced against their clinical translatability; researchers and clinicians alike should grapple with this compromise from the outset in an effort to prioritize which elements of the systems nephrology paradigm offer benefit to the largest number of patients in clinical practice.

This will help to ensure that implementation of a systems nephrology approach in routine DKD care will not perpetuate, or indeed exacerbate, inequity in healthcare delivery. This manuscript was invited following a presentation at the European Renal Association Diabesity Working Group Annual CME in Maribor, Slovenia on September 16th—17th Figure 1 was created with BioRender.

This work was performed within the Irish Clinical Academic Training ICAT Programme, supported by the Wellcome Trust and the Health Research Board Grant No. This research was funded in whole, or in part, by the Wellcome Trust Grant No.

For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. Martin wrote the manuscript and Neil G.

Docherty provided proof-reading and critical review. Martin and Neil G. Docherty reviewed and approved the final manuscript. Sign In or Create an Account. Search Dropdown Menu. header search search input Search input auto suggest. filter your search All Content All Journals Nephron.

Advanced Search. Skip Nav Destination Close navigation menu Article navigation. The Promise of Personalised Diabetic Kidney Disease Care. Model Systems and Data Sources.

Non-Omics Data. Molecular Omics Data. Conflict of Interest Statement. Funding Sources. Author Contributions. Article Navigation. Review Articles September 11 Early Publication. A Systems Nephrology Approach to Diabetic Kidney Disease Research and Practice Subject Area: Nephrology.

Martin Diabetes Complications Research Centre, School of Medicine, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland. liampvmartin gmail.

This Site. Google Scholar. Neil G. Docherty Neil G. Nephron 1— Article history Received:. Cite Icon Cite. toolbar search Search Dropdown Menu. toolbar search search input Search input auto suggest. Journal Section:. View large Download slide. Table 1. An essential toolkit for a systems nephrology approach to diabetic kidney disease a.

View Large. The development of model systems in vitro or animal which reliably recapitulate progressive and advanced human DKD characterized by single-cell and spatially resolved transcriptomics, thereby enhancing the translational relevance of preclinical DKD studies; 2. The identification of biomarkers which predict response to RAAS blockade, SGLT2is, and other emerging disease-modifying treatments for DKD in light of the inter-individual variability in treatment response; and 3.

The authors have no conflicts of interest to declare. Oshima M, Shimizu M, Yamanouchi M, Toyama T, Hara A, Furuichi K, et al. Trajectories of kidney function in diabetes: a clinicopathological update.

Nat Rev Nephrol. Afkarian M, Sachs MC, Kestenbaum B, Hirsch IB, Tuttle KR, Himmelfarb J, et al. Kidney disease and increased mortality risk in type 2 diabetes.

J Am Soc Nephrol. Perkovic V, Jardine MJ, Neal B, Bompoint S, Heerspink HJL, Charytan DM, et al. Canagliflozin and renal outcomes in type 2 diabetes and nephropathy. N Engl J Med. Heerspink HJL, Stefánsson BV, Correa-Rotter R, Chertow GM, Greene T, Hou F-F, et al. Dapagliflozin in patients with chronic kidney disease.

Citation: Ti M, Xue L, Yin Q, Shao S, Cai J, et al. J Clin Exp Nephrol doi: Copyright: © Ti M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Aim: This article focuses on the genetic mechanisms, with an aim to provide certain theoretical and experimental foundation for the future diagnosis and treatment of diabetic nephropathy. Five common genes were selected in this article including ACE, Klotho, MicroRNA, CERS and VDR.

Methods: To learn about the newest study trends on this topic through searching numerous international and domestic databases such as CNKI, CBMdisc, PUBMED, EBMase aiming to obtain meaningful conclusions in order to write a valuable summarization.

Conclusion: With an ever-increasing access to this subject, we can further our understanding of the pathogenesis of DN and broaden the research field until accomplishing the target of prevention of DN through the creation of new target drug and accurate prediction of disease.

Further study about the genetic mechanism of DN especially T1DN remains a vital task. Among diabetic complications, diabetic nephropathy DN has already become the leading cause of end-stage kidney disease ESKD [ 1 , 2 ].

DN can be divided into five clinical stages according to the course and pathological physiology evolution process of diabetes. Although no clear etiology or pathogenesis for DN has been identified as of recently, it is clearly a complex, multifactorial process. Not only is the onset of DN related to inappropriate changes in renal hemodynamics, activation of protein kinase C, activation of the hexosamine biosynthesis pathway, activation of the aldose reductase pathway and the formation of advanced glycation end products AGE , but it is also related to abnormal changes of genes structure and function [ 4 , 5 ].

Exploring the genetic mechanisms of diabetic nephropathy has become a hot topic worldwide. Further study about this subject has great clinical significance for the early diagnosis and prevention of DN as well as in delaying progression to the advanced stages.

The ultimate goal is to improve the survival rate of diabetic patients. The expression of the genes that are involved in the progression of DN varies, and this essay focuses on five vital genes involved in DN.

Abnormal renal hemodynamics is one of the important characteristics of DN, and RAAS renin-angiotensin-aldosterone system is significantly involved in its regulation.

Granted, RAAS genes are thought to be important candidate genes of DN. This system consists of renin, angiotensin II, angiotensin I, angiotensinogen, angiotensin converting enzyme and angiotensin receptors. Interestingly, this system can not only reduce the degradation of the sustained-release atrial natriuretic peptide and nitric oxide generation, but it can also promote oxidative stress, inducing the formation of free radicals and increasing vascular endothelial injury.

Conversely, it can also increase vascular blood volume, increase vascular resistance by contracting vessels and further aggravate vascular injury [ 6 , 7 ].

ACE is the key enzyme in the RAAS that catalysis the conversion of angiotensin I to angiotensin II with strong contractile activity [ 8 ]. The human ACE gene is located on chromosome 17q23 and is approximately 21 kb in length, including 26 exons and 25 introns.

Several studies have explored the correlation between the ACE gene polymorphism and diabetic nephropathy Figure 1. Figure 1: RAAS renin-angiotensin-aldosterone system. Recently, a meta-analysis has been published in Medical Journal by Qin to define the relationship between the ACE gene polymorphism and diabetic nephropathy.

Usingretrieval systems PubMed, Google Scholar and FMRS , 39 articles were includedin the study with 18, patients before March 20, Of those patients, 8, had T2DN as a diagnosis; all others were considered T2DM without nephropathy and were regarded as controls.

Statistical analysis was performed using Review Manager 5. Researchers speculate that the I allele is the protective gene that prevents type 2 diabetes mellitus patients from developing diabetic nephropathy.

Optimization of the design of the case-control study is needed to verify the relationship between ACE gene polymorphisms and the diabetic nephropathy. The Klotho KL gene, discovered in by Kuro-o during a spontaneous hypertension study, is associated with senescence and is mainly expressed in the kidney and brain.

This experimental animal study shows that the deletion of the Klotho gene can cause a series of human aging symptoms as follows: shortened lifespan, derangement of phosphorus regulation, osteoporosis, and vascular calcification [ 9 ].

The expression products of Klotho include two protein isoforms: a membranebound and a secreting type. The high expression of Klotho in the kidney may play a special role in the development of renal disease. A tetramer is constructed by membrane-bound Klotho protein and fibroblast growth factor receptor FGFRs that can work as a co-receptor of FGF23 [ 10 ].

FGF23 can directly regulate serum calcium and phosphorous levels, as well as indirectly work together with parathyroid hormone during vitamin D metabolism. Soluble a-klotho, which is derived from the proteolytic cleavage of the extracellular portion of the membrane-bound a-klotho, can be measured in blood, urine, and cerebrospinal fluid.

Alternatively, soluble aklotho can be generated directly by the alternative splicing of the a-klotho transcript [ 11 ].

Author contributions

Diabetic nephropathy is the main cause of chronic kidney disease, and represents the most common and serious complication of diabetes. The exact pathogenesis is complex and not elucidated. Several factors and mechanisms contribute to the development and outcome of diabetic nephropathy.

An early diagnosis and intervention may slow down disease progression. A variety of biological markers associated with diabetic nephropathy were found in recent years, which was important for predicting the occurrence and development of the disease.

Therefore, this article provides an overview of early biomarkers that are associated with diabetic nephropathy. Diabetes mellitus DM is an endocrine and metabolic disease that has serious impact on human health.

The morbidity and mortality of DM have risen continually at an alarming rate in recent years, and the population with diabetes mellitus is predicted to be about million worldwide by Global estimates of the prevalence of diabetes for and Diabetes Res Clin Pract.

The complications of DM include diabetic retinopathy, diabetic cardiovascular diseases and diabetic nephropathy DN , which is the most common and serious complication of DM. DN has become the leading cause of chronic kidney failure, starting with normoalbuminuria, microalbuminuria, macroalbuminuria and ultimately leading to end stage renal disease ESRD.

Diabetic nephropathy: diagnosis, prevention, and treatment. Diabetes Care. For a long time, proteinuria has been considered the gold standard for evaluation and monitoring of renal function.

However, renal function declines in about one-third of the patients before the occurrence of proteinuria, 3 3 Tabaei BP, Al-Kassab AS, Ilag LL, Zawacki CM, Herman WH. Does microalbuminuria predict diabetic nephropathy?

which makes it inadequate to detect proteinuria alone to monitor the incidence and progression of DN. Therefore, we need to look for laboratory biomarkers that are earlier than microalbuminuria or those appearing at the same time.

This review focuses on the early biomarkers associated with the pathogenesis and pathology of DN and changes in renal function. A large number of prospective studies confirm that hyperglycemia is the most important risk factor for DN.

The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. UK Prospective Diabetes Study UKPDS Group. The Lancet. Hyperglycemia promotes mitochondrial electron transport chain to generate excessive reactive oxygen species ROS through formation of the advanced glycation end products AGEs and activation of the polyol pathway, hexosamine pathway, protein kinase C PKC and angiotensin II.

Then, the ROS initiate or enhance the oxidative stress and eventually cause the inflammatory response and formation of fibrosis.

Biochemistry and molecular cell biology of diabetic complications. Pathogenesis, prevention, and treatment of diabetic nephropathy. In addition, lipid metabolism abnormality, renin-angiotensin-aldosterone system RAAS activation, systemic and glomerular hypertension, insulin signaling impairment, increased growth factors and pro-inflammatory cytokines, and intracellular signaling pathway activation also play a role in the occurrence and progression of DN.

Oxidative stress as a major culprit in kidney disease in diabetes. The occurrence and progression of DN is closely related with oxidative stress. Excessive ROS, which are induced by hyperglycemia, are involved in oxidative stress causing direct oxidation and damage of deoxyribonucleic acid DNA , proteins and lipids.

Oxidative stress and diabetic complications. Circ Res. In , Ha et al. DNA damage in the kidneys of diabetic rats exhibiting microalbuminuria. Free Radic Biol Med.

found that the 8-OHdG levels were significantly higher in cortex and nipples of diabetic mice induced by streptozotocin than in control mice, and they decreased after insulin treatment, which suggested that DN might be associated with oxidative stress and the formation of 8-OHdG. The following study by Hinokio et al.

Oxidative DNA damage in diabetes mellitus: its association with diabetic complications. showed that urinary 8-OHdG excretion in patients suffering from type 2 diabetes mellitus complicated by nephropathy was higher than in patients without complications or in healthy control subjects.

Moreover, there was a correlation between urinary 8-OHdG level and glycosylated hemoglobin HbA 1c. In this report, 8-OHdG was speculated to be a useful biomarker associated with complications secondary to DM. Zhao et al. Relationship of serum 8-OHdG and VEGF with diabetic nephropathy in diabetics.

Chin J Diabetes. measured the serum concentration of 8-OHdG using enzyme-linked immunosorbent assay ELISA and drew a similar conclusion. However, Serdar et al. demonstrated that there was no difference in urinary 8-OHdG levels between the groups with and without diabetic nephropathy on liquid chromatography-mass spectrometry, suggesting that 8-OHdG in urine was not a sensitive biomarker regarding albumin to creatinine ratio UACR for distinguishing DN patients from DM patients.

Comparison of 8-hydroxy-2'-deoxyguanosine 8-OHdG levels using mass spectrometer and urine albumin creatinine ratio as a predictor of development of diabetic nephropathy. Free Radic Res.

Different biological fluids and methods might contribute to the lack of consistency in these studies, so that the predictive value of 8-OHdG in the early stages of DN needs further research to be determined. Biomarkers associated with protein injury comprise pentosidine, 2,4-dinitrophenylhydrazine DNPH and advanced oxidation protein product AOPP.

F2-isoprostaglandin and 4-hydroxy-nonenal HNE are related to lipid injury. Calabrese et al. found that both urinary and serum levels of pentosidine, DNPH, F2-isoprostaglandin and HNE of DN patients were higher than those of control subjects. Oxidative stress and cellular stress response in diabetic nephropathy.

Cell Stress Chaperones. Tabak et al. showed that the level of AOPP in type 2 diabetes mellitus patients with complications such as DN and diabetic retinopathy was significantly higher than in patients without complications. Oxidative lipid, protein, and DNA damage as oxidative stress markers in vascular complications of diabetes mellitus.

Clin Invest Med. These two studies have confirmed that oxidative stress damage is involved in the development of diabetic nephropathy. A growing number of studies reported that DM and its complications were closely related to oxidative stress, so we supposed that the biomarkers related to antioxidant defense system and lipid peroxidation LPO induced by free radicals may be potential biomarkers of kidney damage in diabetic patients.

Glutathione s-transferase GST , a kind of enzyme involved in cell detoxification, promotes inactivation and excretion of toxins by combining toxic drophobic compounds with glutathione. Experimental data from a study by Jiang et al. showed that the expression level of GST in diabetic rats induced by streptozotocin was remarkably higher than in control rats, suggesting that hyperglycemia may be the major cause for elevated GST.

Eight weeks after treatment with resveratrol, the GST expression decreased and several indicators suggesting the occurrence of DN such as urinary protein excretion, creatinine, cellular apoptosis and renal hypertrophy were all improved, leading researchers to suppose that resveratrol likely played a role in renoprotection by lowering the expression level of GST.

Resveratrol attenuates early diabetic nephropathy by down-regulating glutathione s-transferases Mu in diabetic rats.

J Med Food. In agreement with GST, animal experiments on LPO have yielded the same results. Diosmin modulates the NF-kB signal transduction pathways and downregulation of various oxidative stress markers in alloxan-induced diabetic nephropathy.

Renoprotective effect of Bacopa monnieri via inhibition of advanced glycation end products and oxidative stress in STZ-nicotinamide-induced diabetic nephropathy. Ren Fail. In addition, genetic investigation also found that knockout of GST coding genes can lead to decreased GST levels and increased malondialdehyde MDA levels, an important biomarker of LPO, demonstrating that GST has an effect against oxidative stress.

Effect of GSTM1 and GSTT1 double deletions in the development of oxidative stress in diabetic nephropathy patients. Indian J Biochem Biophys. Human research was consistent with the experimental studies above.

Compared with healthy subjects, increased activity of GST and increased level of MDA were found in type 2 diabetes mellitus patients. These results suggested that oxidative stress was involved in the occurrence of DM and GST was likely to play an important role in antioxidation.

Variations in erythrocyte antioxidant levels and lipid peroxidation status and in serum lipid profile parameters in relation to blood haemoglobin A1c values in individuals with type 2 diabetes mellitus.

Blood ALDH1 and GST activity in diabetes type 2 and its correlation with glycated hemoglobin. Exp Clin Endocrinol Diabetes.

In the study about GST and DN, Noce et al. reported that GST activity in type 2 diabetes mellitus patients with and without nephropathy were both significantly higher than that of control subjects, appearing to be closely related with the stages of DN and indicating that GST was likely to be a potential biomarker in early stage DN.

Erythrocyte glutathione transferase activity: a possible early biomarker for blood toxicity in uremic diabetic patients. Acta Diabetol. Inflammatory response could be activated by biochemical, metabolic or hemodynamic disorders when a large number of white blood cells gather in the kidney.

Then, pro-inflammatory cytokines and a variety of chemokines secreted by leukocytes may guide the latter into the kidney directly. Thus, a new cycle of inflammatory response is induced. The inflammatory cytokines and chemokines involved were hypothesized as potential biomarkers of DN. Liu et al.

detected urinary levels of 27 kinds of inflammation-related factors of type 2 diabetes mellitus patients by multiplex bead immunoassay. They found that the levels of proinflammatory cytokines such as interleukin-8 IL-8 , tumor necrosis factor TNF-α and chemokines such as monocyte chemoattractant protein-1 MCP-1 , interferon-inducible protein IP in patients with microalbuminuria were all significantly higher than those of patients with normoalbuminuria and the control subjects.

Besides, the levels of MCP-1 and IP were positively correlated with proteinuria and HbA 1c , while negatively correlated with the estimated glomerular filtration rate eGFR.

Multiplex bead analysis of urinary cytokines of type 2 diabetic patients with normo- and microalbuminuria. J Immunoassay Immunochem. These outcomes suggest that urinary inflammation-related factors may contribute to the diagnosis in early stages of DN. In addition, some studies have shown that serum interleukin IL level was elevated in DN patients and associated with HbA 1c or UACR, thus being speculated as a potential biomarker of diabetic nephropathy.

Elevated levels of interleukin and tumor necrosis factor-alpha in serum of patients with type 2 diabetes mellitus: relationship with diabetic nephropathy. On the other hand, the value of interleukin-6 IL-6 in early diagnosis of diabetic nephropathy remains to be further confirmed. A number of studies have found that serum IL-6 levels of patients with normoalbuminuria or microalbuminuria were higher than those of control subjects and showed a positive correlation with UACR.

Influence of renal involvement on peripheral blood mononuclear cell expression behavior of tumour necrosis factor-alpha and interleukin-6 in type 2 diabetic patients.

Nephrol Dial Transplant. Usefulness of a highly sensitive urinary and serum IL-6 assay in patients with diabetic nephropathy. J Hypertens. Hum Immunol. However, some other studies have found that serum IL-6 level was elevated in patients with macroalbuminuria alone, and its early diagnosis value was not as good as that of urinary albumin excretion.

Acute-phase markers of inflammation and glomerular structure in patients with type 2 diabetes. J Am Soc Nephrol. Some studies demonstrated that an increase in both urinary and serum levels of TNF-α in patients with nephropathy secondary to DM was found compared to those with normoalbuminuria and control subjects.

Besides, levels of TNF-α in urine and serum were both significantly associated with urinary albumin excretion. These results revealed that TNF-α might be an early biomarker of kidney damage in diabetic patients.

Urinary tumour necrosis factor-alpha excretion independently correlates with clinical markers of glomerular and tubulointerstitial injury in type 2 diabetic patients.

Clin Chim Acta. Soluble CD40 ligand sCD40L is a transmembrane protein of the tumor necrosis factor superfamily and regulates inflammatory response by binding with CD A study by El-Asrar et al. Soluble CD40L in children and adolescents with type 1 diabetes: relation to microvascular complications and glycemic control.

Pediatr Diabetes. showed that serum sCD40L level in type 1 diabetes mellitus patients with microangiopathy such as diabetic nephropathy, retinopathy or neuropathy was significantly higher than that of patients without complications and healthy control subjects, and diabetic patients without any of these complications presented higher sCD40L concentration as compared to healthy subjects.

The researchers also found that serum sCD40L was significantly associated with the severity of kidney damage and the level of glycemic control. Increased concentrations of soluble CD40 ligand may help to identify type 1 diabetic adolescents and young adults at risk for developing persistent microalbuminuria.

Diabetes Metab Res Rev. In addition to the biomarkers cited above, glycosyl hydrolase family of 18 members, including chitotriosidase CHIT1 and cartilage glycoprotein 40 YKL , commonly activated by macrophages cells and neutrophils, were also involved in the inflammatory response.

Role of chitotriosidase chitinase 1 under normal and disease conditions. J Epithel Biol Pharmacol. YKL, a new inflammatory marker with relation to insulin resistance and with a role in endothelial dysfunction and atherosclerosis. Inflamm Res. Several studies showed that both CHIT1 activity and YKL level of type 2 diabetes mellitus patients in all subgroups were higher than that of control subjects.

CHIT1 activity and YKL level increased gradually along with the stages of DN according to UACR, which was correlated with activity of CHIT1 and level of YKL even after adjustment for clinical parameters, suggesting that they were both associated with kidney damage of DN patients.

However, because of the higher sensitivity and specificity, CHIT1 activity was better in the diagnosis of persistent microalbuminuria compared with serum level of YKL YKL levels are independently associated with albuminuria in type 2 diabetes.

Cardiovasc Diabetol. Proteins from the 18 glycosyl hydrolase family are associated with kidney dysfunction in patients with diabetes type 2. Renin-angiotensin-aldosterone system RAAS plays an important role in regulating blood pressure by producing aldosterone in human body.

Angiotensinogen, produced by liver, was reported in patients with chronic glomerulonephritis in a previous study. Urinary angiotensinogen accurately reflects intrarenal renin-angiotensin system activity.

Am J Nephrol. The following study found that urinary angiotensinogen excretion of type 2 diabetes mellitus patients with microalbuminuria and macroalbuminuria were both significantly increased compared to control subjects, as well as to normoalbuminuric patients, suggesting that angiotensinogen appeared prior to the establishment of albuminuria.

Also, angiotensinogen level shows a strong association with urinary albumin excretion, which is an indicator of the severity of kidney damage in diabetic patients. Angiotensinogen may be a promising biomarker in the early stages of DN due to its high sensitivity and specificity in diagnostic analysis of diabetic nephropathy.

Urinary angiotensinogen as a potential biomarker of diabetic nephropathy. Clin Kidney J. These biomarkers were summarized in Figure 1.

DN: diabetic nephropathy; RAAS: renin-angiotensin-aldosterone system; DNA: deoxyribonucleic acid; IL interleukin-8; IL interleukin; IL interleukin-6; TNF-α: tumor necrosis factor-α; MCP monocyte chemoattractant protein-1; IP interferon-inducible protein; 8-OHdG: 8-dihydro-2'-deoxyguanosine; AOPP: advanced oxidation protein product; GST: glutathione s-transferase; sCD40L: soluble CD40 ligand; CHIT1: chitotriosidase; DNPH: 2,4-dinitrophenylhydrazine; HNE: 4-hydroxy-nonenal; MDA: malondialdehyde; YKL cartilage glycoprotein Under normal circumstances, podocyte and foot process, glomerular basement membrane and capillary endothelial cells constitute the glomerular filtration barrier.

The damage of this filtration barrier can affect the glomerular filtration function. Markers such as podocytes, basement membrane and endothelial cell damage may have potential to indicate kidney damage in DN patients.

Studies have shown that a decline in the number of podocytes and disappearance of foot processes often occur in the early stages of DN due to apoptosis or shedding of podocytes. Therefore, urinary podocytes and their specific protein products may be regarded as potential biomarkers of podocyte injury.

The podocyte and diabetes mellitus: is the podocyte the key to the origins of diabetic nephropathy? Curr Opin Nephrol Hypertens. Currently, the studies focused on the podocyte-specific protein products because it was difficult to detect urinary podocytes directly.

One study by Wang et al. Messenger RNA expression of podocyte-associated molecules in the urinary sediment of patients with diabetic nephropathy.

Nephron Clin Pract. showed that urinary mRNA levels of podocin, synaptopodin and nephrin in DN patients were extremely higher than those found in control subjects by real-time quantitative PCR. These results were also proved by renal biopsy. Also, synaptopodin level was positively correlated with urinary albumin excretion and serum creatinine concentration while negatively correlated with GFR.

Patients, however, were not divided into different subgroups according to their average level of urinary protein. The validation of these podocyte-specific protein products in early stages of DN was not confirmed in this study.

Further research performed by Hara et al. revealed that urinary synaptopodin level of type 2 diabetes mellitus patients complicated by nephropathy was higher when compared to control subjects, even before the occurrence of proteinuria and associated with the level of urinary albumin and HbA 1c , indicating that synaptopodin was a biomarker with high sensitivity to podocyte injury in diabetic patients.

Urinary podocalyxin is an early marker for podocyte injury in patients with diabetes: establishment of a highly sensitive ELISA to detect urinary podocalyxin. Another report by Jim et al. In addition, urinary level of nephrin showed a strong association with UACR so that it might be a useful biomarker for nephropathic patients in preclinical stage.

Dysregulated nephrin in diabetic nephropathy of type 2 diabetes: a cross sectional study. PLoS One. Type IV collagen is the main component of the glomerular basement membrane and extracellular matrix, and does not pass through glomerular filtration barrier under normal circumstances. Therefore, type IV collagen could be used as a biomarker of basement membrane injury.

The study found that urinary type IV collagen levels were higher before microalbuminuria and associated with urinary albumin and serum creatinine, suggesting that urinary type IV collagen may be a promising biomarker for early diagnosis of DN. Asian multicenter trials on urinary type IV collagen in patients with diabetic nephropathy.

J Clin Lab Anal. Endothelial cells injury can directly affect the permeability of the glomerular filtration membrane. Generally, von Willebrand factor vWF is mostly synthesized by endothelial cells.

Plasma vWF levels increase when endothelial cells are stimulated or damaged. Jensen 45 45 Jensen T. Increased plasma concentration of von Willebrand factor in insulin dependent diabetics with incipient nephropathy.

Nevertheless, research has yet to reveal a definitive mechanism for the association between hyperglycemia and damage to the kidneys. Through this topic, the heterogeneity of diabetic nephropathy eitology and the underlying molecular mechanisms will be explored.

To this end, genetic and epigenetic factors associated with nephropathy will be considered as well as the role of oxidative stress and ferroptosis. Also pertinent to this topic, is how the oxidative-stress pathway can be modulated to prevent or reverse diabetic nephropathy. Additionally, a special focus will be given to early biomarkers that can lead to better understanding and early detection of the disease are of great interest.

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Top bar navigation Nepgropathy organoids Diabetic nephropathy research advancements adancements a Nutritional balance means of understanding reearch mechanisms underpinning DKD progression at nephropahty resolution. The inflammatory Carb counting and food labels and chemokines involved were hypothesized as potential biomarkers of DN. Thus, pharmacogenomic profiling will Diabetic nephropathy research advancements an important role in optimising outcomes for individuals with DKD. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher. Another interesting observation is that clinical manifestation is not necessarily associated with histological findings in DKD, as suggested by an autopsy study [ 41 ]. J Epithel Biol Pharmacol. Recognition of the marked CV risk CKD portends is reflected in changes to clinical practice guidelines 816 that now include CKD among the highest-risk groups in screening and treatment recommendations

Diabetic nephropathy research advancements -

Thus, refinements to kidney organoid differentiation protocols will be necessary before they can realize their full potential as a comprehensive in vitro model of DKD [ 27 ]. Renal slice culture from nephrectomy specimens could offer an additional platform, which although less amenable to genetic manipulation than organoids, have advantages regarding cellular composition and tissue integrity and maturity [ 31 ].

Integration of target discovery in organoids with subsequent assessment of pharmacological responses in renal slice culture could offer a pragmatic means of mitigating attrition rates between preclinical and early phase clinical studies.

Clinical phenotypic data derived from electronic health records are a rich resource which may be harnessed to individualise prognosis and treatment response [ 15, 16 ]. Clustering of patients with newly diagnosed adult-onset diabetes mellitus on the basis of 6 variables age, body-mass index, glycated haemoglobin, glutamic acid decarboxylase antibodies, and homoeostatic model assessment 2 HOMA2 estimates of β-cell function and insulin resistance across multiple independent Scandinavian cohorts reproducibly identified 5 subgroups of patients with substantially different risks of diabetes complications [ 32 ].

In particular, the severe insulin-resistant diabetes cluster, characterized by high body-mass index, hyperinsulinaemia, and mild hyperglycaemia, had the highest risks of incident DKD and end-stage kidney disease ESKD [ 32 ].

Assessment of individual proteins may also be used to enhance prognostication of adverse CKD outcomes in patients with diabetes mellitus [ 10 ].

More broadly, 17 proteins from the tumour necrosis factor-receptor superfamily, including sTNFR1 and sTNFR2, were strongly associated with year ESKD risk in cohorts of patients with type 1 and type 2 diabetes mellitus [ 35 ].

Circulating levels of kidney injury molecule-1 and N-terminal pro-brain natriuretic peptide also strongly predict DKD progression [ 37, 38 ]. sTNFR1, neutrophil gelatinase-associated lipocalin, C-reactive protein, and complement 3a with cleaved C-terminal arginine C3a-desArg were identified as the most strongly prognostic biomarkers [ 39 ].

The large amount of data generated by kidney imaging with clinically available modalities such as ultrasound and MRI is a potentially rich source of biomarkers to inform DKD prognostication and treatment response [ 16, 26 ].

Such biomarkers may be human-visible and quantifiable by manual, semi-automated, or automated means. One such example in the field of autosomal dominant polycystic kidney disease is total kidney volume TKV , a surrogate marker of disease progression which correlates with cyst volume and decline in eGFR [ 40 ].

An automated segmentation method based on deep learning has been developed to calculate TKV in a fast and reproducible manner, and demonstrated good agreement with TKV values calculated from manual segmentations [ 41 ]. Alternatively, in the field of computer vision, high-dimensional numeric data may be extracted from radiologic images and analysed using machine or deep learning approaches to classify images and detect patterns which are not visible to the human eye.

As part of the Biomarker Enterprise to Attack Diabetic Kidney Disease BEAt-DKD consortium, the prospective, multi-centre iBEAt cohort study is the largest DKD imaging study to date and aims to determine whether ultrasound and MRI renal imaging biomarkers provide insight into the heterogeneity in DKD pathogenesis and can prognosticate adverse outcomes amongst patients with type 2 DKD [ 26 ].

A key advantage of imaging over other biomarker approaches to personalise DKD management is the fact that the left and right kidneys as well as the renal cortex and medulla can be assessed independently, potentially providing more granularity into functional and structural heterogeneity amongst patients with DKD [ 26 ].

As diabetic retinopathy and DKD are closely intertwined as microvascular complications of diabetes mellitus, retinal imaging is also a potentially rich source of imaging biomarkers to inform DKD management [ 42 ]. Endothelial and microvessel dysfunction contribute to the development of DKD and premature cardiovascular disease amongst patients with diabetes mellitus [ 42 ].

Homology between the vasculature of the eye and the kidney suggests that inferences regarding the microvasculature of the kidney can be made from retinal imaging, providing a rationale to image accessible microvessels in the eye to improve DKD prognostication [ 42 ].

For example, retinal images were used to train and validate a deep learning algorithm which accurately predicted CKD status in community-based Asian cohorts [ 43 ].

The area under the receiver operating characteristic curve of the deep learning algorithm improved when considered alongside conventional CKD risk factors such as age, gender, ethnicity, diabetes mellitus, and hypertension [ 43 ].

By capturing deeper vascular networks such as the choroidal circulation at near-histological resolution, the advent of optical coherence tomography OCT constitutes a major advance in retinal imaging which has transformed ophthalmology care [ 44 ]. OCT can now also be deployed in preclinical models of retinopathy [ 44 ].

Deep learning has been coupled with OCT imaging to triage and diagnose the commonest sight-threatening retinal diseases in an automated fashion and with similar accuracy to that of expert physicians [ 45 ]. Thus, combining the imaging power of cross-sectional chorioretinal OCT imaging with the analytical power of deep learning holds great promise as a means of developing prognostic imaging biomarkers related to adaptations of the renal microvasculature in people with diabetes mellitus [ 42 ].

Similar to radiologic images of the kidney, digitised whole slide images WSIs and transmission electron microscopy TEM images of kidney biopsies contain a wealth of data which may be optimally analysed using deep learning approaches [ 46, 47 ]. Deep learning approaches may be used to automate the extraction of descriptive and quantitative structural features from WSIs and TEM images with improved reproducibility [ 46, 47 ].

The concept of reproducibility is an important one as although an inter-pathologist intra-class correlation coefficient of 0. Furthermore, semi- or wholly automated means of classifying DKD histologically would reduce personnel requirements and improve efficiency of assigning DKD diagnoses in routine clinical care.

Thus, deep learning may support high-throughput and reproducible quantitative feature extraction in experimental models of renal injury. Furthermore, the trained convolutional neural network performed well on human samples, thereby providing a link between automated histopathological assessment across the preclinical and clinical domains [ 49 ].

Indeed, a convolutional neural network was also used to segment PAS-stained kidney biopsy samples from 54 patients with DKD and classify them according to the Tervaert schema, achieving a high level of agreement with three independent pathologists [ 50 ]. In the assessment of kidney structural features, deep learning has mainly been applied to digital pathology images thus far, although researchers have started to evaluate this strategy on TEM images with reasonable success [ 52 ].

Some of the biomedical technologies which support omics analyses are outlined in Figure 1. In many cases, the application of multiple technologies to characterize a particular molecular domain often provides complementary rather than redundant information.

Moreover, integration of data from several molecular domains is key to characterizing the molecular heterogeneity of DKD, although integrative multi-omic analyses are not trivial owing to the complexity of the multiple high-dimensional datasets involved [ 17, 56 ].

It is also worth noting that changes in different molecular domains such as the transcriptome, the proteome, and the metabolome may not necessarily directly correlate [ 16, 57, 58 ]. For example, factors impacting translational efficiency will diminish mRNA-protein correlations for a given target, as will modalities of protein regulation other than gene transcription, such as post-translational modifications [ 57 ].

Furthermore, differences in the coverage of molecular domains by omics technologies may result in difficulties mapping insights from one to the other [ 16, 58 ]. Techniques that allow for integration of not only two data domains at a time such as the transcriptome and the proteome but also allow for simultaneous integration of clinical phenotypic data, imaging data, and histopathological data along with multiple molecular omics data domains are essential to gain more holistic insights into cellular function and interaction in a complex organ system such as the diabetic kidney [ 17, 56 ].

The current one-size-fits-all approach to DKD care ignores the clinically apparent heterogeneity in disease prognosis and treatment-responsiveness [ 10 ]. It is hoped that a systems biology approach to DKD research will pave the way for a precision medicine approach to routine DKD care by unravelling individual-level molecular mechanisms which underlie progressive DKD and which are amenable to targeting by existing or novel therapeutic strategies [ 15, 16 ].

Certain priorities for translational DKD research which may be advanced by a systems nephrology approach include: 1. The development of model systems in vitro or animal which reliably recapitulate progressive and advanced human DKD characterized by single-cell and spatially resolved transcriptomics, thereby enhancing the translational relevance of preclinical DKD studies;.

The identification of biomarkers which predict response to RAAS blockade, SGLT2is, and other emerging disease-modifying treatments for DKD in light of the inter-individual variability in treatment response; and.

The delineation of mechanisms of DKD progression in the face of combined therapy with RAAS blockade and an SGLT2i, the current backbone of treatment, which may help define targets for novel therapies which minimise the significant residual risk of progressive renal functional decline.

However, the efficacy of appropriately targeted novel therapeutics may still be impacted by inter-individual pharmacokinetic differences. Thus, pharmacogenomic profiling will play an important role in optimising outcomes for individuals with DKD.

While a comprehensive systems nephrology approach is now technically feasible in research studies, this must be balanced with plans for eventual implementation of elements of this paradigm in clinical practice.

The value of biological insights derived from the refined techniques currently available must be balanced against their clinical translatability; researchers and clinicians alike should grapple with this compromise from the outset in an effort to prioritize which elements of the systems nephrology paradigm offer benefit to the largest number of patients in clinical practice.

This will help to ensure that implementation of a systems nephrology approach in routine DKD care will not perpetuate, or indeed exacerbate, inequity in healthcare delivery. This manuscript was invited following a presentation at the European Renal Association Diabesity Working Group Annual CME in Maribor, Slovenia on September 16th—17th Figure 1 was created with BioRender.

This work was performed within the Irish Clinical Academic Training ICAT Programme, supported by the Wellcome Trust and the Health Research Board Grant No.

This research was funded in whole, or in part, by the Wellcome Trust Grant No. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.

Martin wrote the manuscript and Neil G. Docherty provided proof-reading and critical review. Martin and Neil G. Docherty reviewed and approved the final manuscript.

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The Promise of Personalised Diabetic Kidney Disease Care. Model Systems and Data Sources. Non-Omics Data. Molecular Omics Data. Conflict of Interest Statement. Funding Sources. Author Contributions.

Article Navigation. Review Articles September 11 Early Publication. A Systems Nephrology Approach to Diabetic Kidney Disease Research and Practice Subject Area: Nephrology.

Martin Diabetes Complications Research Centre, School of Medicine, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland. liampvmartin gmail. This Site. Google Scholar. Neil G. Docherty Neil G. Nephron 1— Article history Received:.

Cite Icon Cite. toolbar search Search Dropdown Menu. toolbar search search input Search input auto suggest. Journal Section:. View large Download slide. Table 1. An essential toolkit for a systems nephrology approach to diabetic kidney disease a.

View Large. The development of model systems in vitro or animal which reliably recapitulate progressive and advanced human DKD characterized by single-cell and spatially resolved transcriptomics, thereby enhancing the translational relevance of preclinical DKD studies; 2.

The identification of biomarkers which predict response to RAAS blockade, SGLT2is, and other emerging disease-modifying treatments for DKD in light of the inter-individual variability in treatment response; and 3.

The authors have no conflicts of interest to declare. Oshima M, Shimizu M, Yamanouchi M, Toyama T, Hara A, Furuichi K, et al. Trajectories of kidney function in diabetes: a clinicopathological update.

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N Engl J Med. Heerspink HJL, Stefánsson BV, Correa-Rotter R, Chertow GM, Greene T, Hou F-F, et al. Dapagliflozin in patients with chronic kidney disease. Shaman AM, Bain SC, Bakris GL, Buse JB, Idorn T, Mahaffey KW, et al.

Effect of the glucagon-like peptide-1 receptor agonists semaglutide and liraglutide on kidney outcomes in patients with type 2 diabetes: pooled analysis of SUSTAIN 6 and LEADER.

Heerspink HJL, Sattar N, Pavo I, Haupt A, Duffin KL, Yang Z, et al. Effects of tirzepatide versus insulin glargine on kidney outcomes in type 2 diabetes in the SURPASS-4 trial: post-hoc analysis of an open-label, randomised, phase 3 trial. Lancet Diabetes Endocrinol. Bakris GL, Agarwal R, Anker SD, Pitt B, Ruilope LM, Rossing P, et al.

Effect of finerenone on chronic kidney disease outcomes in type 2 diabetes. Martin WP, Docherty NG, Le Roux CW. Impact of bariatric surgery on cardiovascular and renal complications of diabetes: a focus on clinical outcomes and putative mechanisms. Expert Rev Endocrinol Metab. Martin WP, White J, Lopez-Hernandez FJ, Docherty NG, le Roux CW.

Metabolic surgery to treat obesity in diabetic kidney disease, chronic kidney disease, and end-stage kidney disease; what are the unanswered questions? Front Endocrinol. Tye SC, Denig P, Heerspink HJL.

Precision medicine approaches for diabetic kidney disease: opportunities and challenges. Nephrol Dial Transplant. Luyckx VA, Rule AD, Tuttle KR, Delanaye P, Liapis H, Gandjour A, et al. Nephron overload as a therapeutic target to maximize kidney lifespan.

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Rationale and design of the kidney precision medicine project. Mariani LH, Pendergraft WFIII, Kretzler M. Defining glomerular disease in mechanistic terms: implementing an integrative biology approach in nephrology. Clin J Am Soc Nephrol.

Lindenmeyer MT, Alakwaa F, Rose M, Kretzler M. Perspectives in systems nephrology. Cell Tissue Res. Eddy S, Mariani LH, Kretzler M. Integrated multi-omics approaches to improve classification of chronic kidney disease. Pushpakom S, Iorio F, Eyers PA, Escott KJ, Hopper S, Wells A, et al.

Drug repurposing: progress, challenges and recommendations. Nat Rev Drug Discov. Tuttle KR, Brosius FCIII, Adler SG, Kretzler M, Mehta RL, Tumlin JA, et al. Williams VR, Konvalinka A, Song X, Zhou X, John R, Pei Y, et al. Connectivity mapping of a chronic kidney disease progression signature identified lysine deacetylases as novel therapeutic targets.

Martin WP, Chuah YHD, Abdelaal M, Pedersen A, Malmodin D, Abrahamsson S, et al. Medications activating tubular fatty acid oxidation enhance the protective effects of roux-en-Y gastric bypass surgery in a rat model of early diabetic kidney disease.

Martin WP, Nair M, Chuah YHD, Malmodin D, Pedersen A, Abrahamsson S, et al. Dietary restriction and medical therapy drives PPARα-regulated improvements in early diabetic kidney disease in male rats. Clin Sci. Betz B, Conway BR. An update on the use of animal models in diabetic nephropathy research.

Curr Diab Rep. Townsend RR, Guarnieri P, Argyropoulos C, Blady S, Boustany-Kari CM, Devalaraja-Narashimha K, et al. Rationale and design of the Transformative Research in Diabetic Nephropathy TRIDENT study.

Rodríguez-Rodríguez R, Hojs R, Trevisani F, Morales E, Fernández G, Bevc S, et al. The role of vascular lesions in diabetes across a spectrum of clinical kidney disease. Kidney Int Rep. Gooding KM, Lienczewski C, Papale M, Koivuviita N, Maziarz M, Dutius Andersson A-M, et al.

Prognostic imaging biomarkers for diabetic kidney disease iBEAt : study protocol. BMC Nephrol. Little MH, Combes AN. Kidney organoids: accurate models or fortunate accidents.

Genes Dev. Nishinakamura R. Human kidney organoids: progress and remaining challenges. Hypoxia-inducible factor prolyl hydroxylase inhibitors recently approved for renal anemia may be renoprotective since they improve tubulointerstitial hypoxia. Thus, following SGLT2 inhibitor, numerous novel drugs could be utilized in treating DKD.

Future studies are expected to provide new insights. Keywords : Diabetic nephropathies ; Epigenomics ; Glycation end products, advanced ; Hypoxia-inducible factor 1 ; NF-E2-related factor 2 ; Sodium-glucose transporter 2.

The concept of diabetic kidney disease and diabetic nephropathy. GFR, glomerular filtration rate. The time course of current treatments. The time course of future treatments. Citations Citations to this article as recorded by.

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Heart-healthy recipes Nephropathy, or Diabetic Kidney Advancemente, refers Balancing testosterone levels the deterioration of kidney functioning in patients advanvements by type reseaarch and type Doabetic diabetes. Important Note : All contributions to Ressarch Research Topic must Disbetic within Diabetic nephropathy research advancements scope of the Carbohydrate requirements for athletes and nehropathy to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review. No records found. total views article views downloads topic views. With their unique mixes of varied contributions from Original Research to Review Articles, Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author. William P. MartinAdvancments G. Docherty; A Jephropathy Nephrology Approach to Diabetic Kidney Rdsearch Research and Practice. Diabetif Diagnosis Micronutrient deficiency and immune function advancemens of diabetic kidney disease DKD via the serial Acai berry fiber of routine Natural immune boosters indices Diabeti the granularity required to resolve the heterogeneous disease mechanisms driving progression in the individual patient. A systems nephrology approach may help resolve mechanisms underlying this clinically apparent heterogeneity, paving a way for targeted treatment of DKD. Summary: Given the limited access to kidney tissue in routine clinical care of patients with DKD, data derived from renal tissue in preclinical model systems, including animal and in vitro models, can play a central role in the development of a targeted systems-based approach to DKD.

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