research papers on diabetic nephropathy

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• Published: 02 January 2024

New and emerging therapies for diabetic kidney disease

• Ricardo Correa-Rotter 1 , 2 ,
• Louise J. Maple-Brown   ORCID: orcid.org/0000-0002-9067-2737 3 , 4 ,
• Rakesh Sahay 5 ,
• Katherine R. Tuttle   ORCID: orcid.org/0000-0002-2235-0103 6 , 7 &
• Ifeoma I. Ulasi   ORCID: orcid.org/0000-0001-7783-3025 8 , 9 , 10  

Nature Reviews Nephrology volume  20 ,  pages 156–160 ( 2024 ) Cite this article

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• Diabetic nephropathy
• Therapeutics

The theme of World Kidney Day 2024 is “kidney health for all — advancing equitable access to care and optimal medication practice”. To mark this event, Nature Reviews Nephrology invited five researchers from different geographical regions worldwide to discuss the impact of new and emerging therapies for diabetic kidney disease on patient care as well as the barriers that must be overcome to ensure equitable access to these therapies.

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Acknowledgements

L.J.M.-B.’s work was supported by an NHMRC Investigator grant (#1194698). The Diabetes across the Lifecourse: Northern Australian Partnership would not be possible without invaluable contributions from members of the Aboriginal and Torres Strait Islander Advisory Group, Steering Committee, Management Group, and partners including government, non-government and Aboriginal community-controlled health organizations. K.R.T.’s work is supported by NIH research grants R01MD014712, U2CDK114886, UL1TR002319, U54DK083912, U01DK100846, OT2HL161847, and UM1AI109568 and CDC contract 75D301-21-P-12254.

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Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico

Ricardo Correa-Rotter

Universidad Nacional Autónoma de México, Mexico City, Mexico

Menzies School of Health Research, Charles Darwin University, Darwin, Australia

Louise J. Maple-Brown

Department of Endocrinology, Royal Darwin and Palmerston Hospitals, NT Health, Darwin, Australia

Osmania Medical College, Hyderabad, India

Rakesh Sahay

Providence Medical Research Center, Providence Inland Northwest Health, Spokane, WA, USA

Katherine R. Tuttle

Kidney Research Institute and Institute of Translational Health Sciences, University of Washington, Seattle, WA, USA

Department of Medicine, College of Medicine, University of Nigeria, Ituku-Ozalla, Enugu, Enugu State, Nigeria

Ifeoma I. Ulasi

Renal Unit, Department of Medicine, University of Nigeria Teaching Hospital, Ituku-Ozalla, Enugu, Enugu State, Nigeria

Renal Unit, Department of Internal Medicine, Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Ebonyi State, Nigeria

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Ricardo Correa-Rotter is Professor of Medicine and Nephrology and National Researcher at the National Institute of Medical Sciences and Nutrition Salvador Zubirán (INCMNSZ), Mexico, and the National University of Mexico (UNAM). He is a member of the Academy of Medicine of Mexico, Past Secretary General of the International Society of Nephrology (ISN) and Past-President of the Latin American Society of Nephrology and Hypertension (SLANH). He serves on the editorial board of several nephrology journals and has contributed to 282 peer-reviewed articles and 65 book chapters.

Louise J. Maple-Brown is Deputy Director Research at Menzies School of Health Research, and Senior Endocrinologist at the Royal Darwin Hospital (Northern Territory, Australia). Louise has been a clinician-researcher in remote Australia for over 20 years. She established and has led the Diabetes across the Lifecourse: Northern Australian Partnership (which includes several large projects funded by Australia’s National Health and Medical Research Council) for the past 12 years.

Rakesh Sahay is Professor of Endocrinology at Osmania Medical College in Hyderabad, India. He is actively involved in research in the fields of diabetes, thyroid disorders and metabolic bone diseases. He is Past President of the Endocrine Society of India, President Elect of the Research Society for the Study of Diabetes in India, Section Editor of Tropical Endocrinology for Endotext and Associate Editor of the International Journal of Diabetes in Developing Countries .

Katherine R. Tuttle is the Executive Director for Research at Providence Inland Northwest Health and Professor of Medicine at the University of Washington, USA. She is internationally recognized for her contributions to science as well as to the care of patients with DKD. Her innovative work has produced >320 publications.

Ifeoma I. Ulasi is a nephrologist, teacher, researcher and author. She is Professor of Medicine at the College of Medicine, University of Nigeria, and is affiliated with two teaching hospitals. She is an international adviser of the Royal College of Physicians, London, a Member of the WHO Taskforce on Organ Donation and Transplantation and Past President of the Nephrology Association of Nigeria. She is also a member of various International Society of Nephrology (ISN) Committees, including the Executive Committee of the ISN (2021 to April 2023) and Deputy Chair of the ISN Advocacy Working Group (2023–2025), a member of the KDIGO CKD Guidelines Review Team (2022–2023) and a past Africa and Middle East representative of the Transplantation Society (2014–2018).

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Correspondence to Ricardo Correa-Rotter , Louise J. Maple-Brown , Rakesh Sahay , Katherine R. Tuttle or Ifeoma I. Ulasi .

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Competing interests.

R.C.R. reports consultancy for Astra Zeneca, Boehringer Ingelheim, Bayer, Chinook and Dimerix. He has received research funding from Astra Zeneca, Novo Nordisk, Baxter, Roche and GSK and speaker honoraria from Amgen, Astra Zeneca, Boehringer Ingelheim, Janssen, Sanofi and Bayer. He is a member of the steering committees of World Kidney Day (2023–2026), the DAPA CKD trial (Astra Zeneca), the FINE-REAL trial (Bayer) and the national leader of the ASCEND study (GSK) and the FLOW study (Novo Nordisk). L.J.M.-B. declares no competing interests. R.S. has received lecture fees from USV India Ltd, Novo Nordisk, Lupin, Torrent Pharma and Dr. Reddy’s Laboratories. K.R.T. reports consultancy for Eli Lilly, Boehringer Ingelheim and AstraZeneca; consultancy and grants from Bayer; consultancy and speaker fees for Novo Nordisk; and grants from Travere outside the submitted work. I.I.U. has received lecture fees from Astra Zeneca, Boehringer Ingelheim and Sonofi. She is also a Principal Investigator for the Astra Zeneca CaReMe Real-world Registry for patients with kidney disease.

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Correa-Rotter, R., Maple-Brown, L.J., Sahay, R. et al. New and emerging therapies for diabetic kidney disease. Nat Rev Nephrol 20 , 156–160 (2024). https://doi.org/10.1038/s41581-023-00782-1

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Published : 02 January 2024

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DOI : https://doi.org/10.1038/s41581-023-00782-1

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• Published: 29 April 2021

The evolution and future of diabetic kidney disease research: a bibliometric analysis

• Yi Wei 1 &
• Zongpei Jiang 1  

BMC Nephrology volume  22 , Article number:  158 ( 2021 ) Cite this article

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Diabetic kidney disease (DKD) is one of the most important complications of diabetic mellitus. It is essential for nephrologists to understand the evolution and development trends of DKD.

Based on the total cited numbers in the Web of Science Core Collection, which was searched through September 28th, 2020, we performed a bibliometric analysis of the top 100 most cited full-length original articles on the subject of DKD. The timespans, authors, contributions, subcategories, and topics of those 100 articles were analysed. In addition, the evolution of topics in DKD research was investigated.

There were 23,968 items under the subject of DKD in the Web of Science Core Collection. The top 100 cited articles, published from 1999 to 2017, were cited 38,855 times in total. Researchers from the USA contributed the most publications. The number of articles included in ‘Experimental studies (EG)’, ‘Clinical studies (CS)’, ‘Epidemiological studies (ES)’, and ‘Pathological and pathophysiological studies (PP)’ were 65, 26, 7, and 2, respectively. Among the 15 topics, the most popular topic is the renin-angiotensin-aldosterone system (RAAS), occurring in 26 articles, including 6 of the top 10 most cited articles. The evolution of topics reveals that the role of RAAS inhibitor is a continuous hotspot, and sodium-glucose cotransporter 2 (SGLT-2) inhibitor and glucagon-like peptide 1 (GLP-1) agonist are two renoprotective agents which represent novel therapeutic methods in DKD. In addition, the 26 clinical studies among the top 100 most cited articles were highlighted, as they help guide clinical practice to better serve patients.

Conclusions

This bibliometric analysis of the top 100 most cited articles revealed important studies, popular topics, and trends in DKD research to assist researchers in further understanding the subject.

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Diabetes mellitus (DM) is a severe global health problem and contributes to increased health care costs. It is estimated that more than 450 million people are affected by this disease, and this number will reach 700 million people by 2045 [ 1 ]. Diabetic kidney disease (DKD) is one of the most important complications of DM, and chronic kidney disease occurs in more than 20–40% of DM patients [ 2 ]. Thus, overall comprehension of the mechanism and treatment of DKD is essential for nephrologists, especially young researchers.

Recent reviews have helped researchers understand the mechanism, diagnosis, and treatment of DKD, as summarized in Table S1 . These studies highlight the vital roles of immunity and inflammation [ 3 , 4 , 5 ], oxidative stress (OS) [ 6 , 7 , 8 ], haemodynamic and metabolic shifts [ 9 ], epigenetic factors [ 10 ] and tubule function [ 11 ] in the pathogenesis and prognosis of DKD. However, these content-based reviews have 3 limitations. First, the review contents are deep but narrow, which makes it difficult for readers to understand the overall research status of the subject. Second, the articles referenced in the reviews were manually selected. The large workload leads to limited numbers. However, subjective judgement may lead to the loss of information. Authors may miss important research. Even if an article is cited, its importance and influence may be neglected. Third, readers cannot learn the evolution of the subject or evolution of popular topics and thus cannot develop a deeper comprehension of the subject.

Clinical and experimental studies on DKD have developed rapidly. In total, there were 23,968 items in the Web of Science Core Collection on the subject of DKD from 1999 to September 28th, 2020. In a sense, the citation time (CT) represents the influence and significance of the article. Bibliometric analysis is a method utilized in many fields to illustrate the landscape of subjects [ 12 , 13 ]. Based on CT, bibliometric analysis objectively includes articles of subject on subject in the analysis and reflects the evolution of a subject, trends of popular topics and collaborative relationships among researchers and countries [ 14 , 15 , 16 ]. To determine the influential research, the distribution of disparate topics and the evolution of research trends, we performed a bibliometric analysis of the top 100 most cited articles in clinical and experimental studies of DKD.

Materials and methods

Data collection and filtration.

To acquire literature data representing high-quality research, we retrieved publications on the subject of DKD from the Web of Science Core Collection using the search strategy: TOPIC: (DKD OR (diabetic NEAR/0 nephropathy) OR (diabetic NEAR/0 kidney)). Research results were ranked by CT, which was based on the absolute number of citations for each article through September 28th, 2020. Articles involving the following research objects were defined as publications on the subject of DKD and were manually selected: DKD populations; diabetes populations with proteinuria or kidney disease; tissue, blood, or urine from DKD and diabetes patients with proteinuria or kidney disease; diabetic animals with kidney injury; and renal cell models simulating diabetes injury. Only full-length original articles were included in this study while other types of articles, such as guidelines, reviews, and meta-analyses, were excluded. Finally, only the top 100 most cited full-length original articles written in English on the subject of DKD were included in this study.

Data analysis and visualization

Elements including the article title, author, address, abstract, keyword, journal, publication year and CT were included in the analysis. The article number was equal to the article rank among the 100 articles. The relevant countries were analysed according to the corresponding authors. If the corresponding authors came from the same country, the article was defined as a single-country publication; otherwise, it was defined as a multi-country publication. Subcategories and topics were manually summarized and counted. The average citation time (ACT) of each article was equal to the CT divided by the number of years the article was cited, and the number of years the article was cited was equal to 2020 plus 1 minus the number of the published year. In addition, the number of citations per article per year was equal to the sum of ACTs of all articles published in the same year divided by the number of articles. The author’s influence score was represented by the sum of the ACT, and one article was scored on only the publication year.

Bibliometric analysis was performed using the Bibliometric R Package [ 17 ]. Journal analysis was performed using the module of most relevant sources. Country analysis was performed using the module of the corresponding author’s country. The frequencies of key words included in the word cloud were determined using the module of most frequent words with abstract parameters.

Figures were made by Microsoft PowerPoint, ggplot2 R Package, and ggwordcloud R Package. The process of data preparation and analysis is shown in Fig.  1 .

Strategy for data preparation and analysis. We retrieved publications on the subject of DKD from the Web of Science Core Collection and ranked the top 100 most cited articles. After subcategory and topic identification, we performed analyses of the journals, countries, author contributions, distributions and topic evolution

Basic information of the top 100 most cited articles

As shown in Table  1 , the top 100 most cited articles were published in 26 journals, and 55% of the articles were published in the following 4 journals: Journal of the American Society of Nephrology (21%), Diabetes (16%), Kidney International (10%), and The New England Journal of Medicine (8%).

The 100 articles were published from 1999 to 2017 and were cumulatively cited 38,855 times. The publication time spans are shown in Fig.  2 . There were 20 articles published from 1999 to 2002, 38 articles published from 2003 to 2007, 31 articles published from 2008 to 2012 and 11 articles published from 2013 to 2017. In 2003, 13 articles were published, which made 2013 the year with the most publications.

Timespans of the top 100 most cited articles. The blue bars represent the number of publications for each year, and the yellow line represents the number of citations per article per year. The distributions of articles and citation in disparate years are shown in the figure

Finally, we analysed the authors, and their affiliations, of the top 100 most cited articles. The authors shown in Figure S1 were the top 10 most relevant authors ranked by the author’s influence score. The dot size represents the score of authors, and the dot colour reflects the number of works published by the author. In Table  2 , we found that scientists from the USA contributed the most publications.

Identification of the subcategories of the top 100 articles

We divided the articles into 4 subcategories according to the research type and content. The most abundant article subcategory was ‘Experimental studies (EG)’, which explained the phenotypic changes and mechanisms in experimental DKD and comprised 65 articles (49.62% of all citations). The second most abundant subcategory was ‘Clinical studies (CS)’, which focused on the clinical biomarkers and treatment strategies for DKD, and in this subcategory, 26 articles contributed to 41.55% of the total citations. Moreover, 7 articles with 2603 total citations were determined to belong to the subcategory ‘Epidemiological studies (ES)’, and 2 articles specifically describing the pathological and pathophysiological characteristics of DKD belonged to the subcategory ‘Pathological and pathophysiological studies (PP)’. In Table  3 , we list the article number and percentage of total citations for each subcategory.

To learn more about the contents of the 100 articles, we analysed the key words. Figure  3 shows the highly frequent words related to the top 100 most cited articles on DKD. To further determine the hotspots in DKD research, we analysed articles in the subcategories ‘EG’ and ‘CS’ by their topic. In Table  4 , we list the top 100 most cited articles and their topics.

Word cloud of the top 100 most cited articles. Key words were extracted from the abstracts of the top 100 most cited articles to illustrate a word cloud

Distributions of the top 100 most cited articles in regard to different subcategories, topics and periods

In Fig.  4 , we show the distribution of the top 100 most cited articles. We divided the year of publication into 4 periods. The distributions of the 100 articles are shown in Fig. 4 a. Most ‘CS’ articles were published from 2003 to 2007 (Fig. 4 b), while most ‘MG’ articles were published from 2008 to 2012 (Fig. 4 c).

Distributions of the subcategories, topics and time periods. The distributions of the 100 articles are shown in the figure ( a ). The distributions of clinical studies ( b ) and experimental studies ( c ) in different time periods are shown as pie charts. The distributions of topics in clinical ( d ) and experimental studies ( e ) are showed as Nightingale rose charts

Intriguingly, we revealed popular research fields via topic analysis. We found that the renin-angiotensin-aldosterone system (RAAS) was the most popular topic. Clinical trials on the application of RAAS blockade in DKD (article number 1, 2, 3, 7, 9, 10, 15, 27, 41, 52, 62, 64, 75, and 86, a total of 11,852 citations, 30.50% of the total citations) included 6 of the top 10 most cited articles, which contributed to 26.52% of the total citations. Correspondingly, 6 articles (article number 25, 39, 71, 84, 92, and 95, a total of 1579 citations, 4.06% of the total citations) explained the mechanism of RAAS in DKD. In addition, RAAS blockade-based combination treatment was also popular among researchers, as it was associated with 6 articles that were cited 1756 times (4.52% of the total citations). RAAS blockade combined with vitamin D analogues (article number 17, 97) and mineralocorticoid antagonism (article number 35, 80, 93) were recommended for renal function protection, but RAAS combined with the endothelin antagonist avosentan (article number 50) was considered to induce fluid overload. Taken together, these data indicated the crucial role of RAAS blockade in therapeutic strategies for DKD.

The next most important topic was how the OS participates in DKD, which was associated with 17 articles published from 2000 to 2013 (article number 5, 18, 22, 24, 45, 55, 63, 67, 70, 72, 73, 81, 85, 88, 89, 91, and 100, a total of 5080 citations, 13.07% of the total citations). In experimental DKD, the increase in reactive oxygen species (ROS) (article number 5) and NAD(P)H oxidase levels (article number 22, 63, 67, and 91), activation of PKC (article number 24 and 81), decrease in eNOS (article number 55, 85, and 100) and mitochondrial dysfunction (article number 70, 72, and 89) promote OS injury, while Nrf2 (article number 45, 73, and 88) protects the kidney from OS in DKD as an antioxidant factor. However, a phase 3 clinical study (article number 18) found that the Nrf2 activator bardoxolone methyl did not ameliorate the loss of renal function. Instead, bardoxolone methyl led to a higher cardiovascular risk.

The accumulation of advanced glycation end products (AGEs) is also a classic pathogenic mechanism in DKD. Among the top 100 most cited articles, 7 articles (article number 19, 21, 30, 38, 44, 51, and 60, a total of 2322 citations) focused on AGEs and the receptor for AGEs (RAGE), which constituted 5.98% of the total citations. Although they slowed the progression of experimental DKD, agents targeting AGEs/RAGE were not easily translated into the clinic. In a randomized clinical trial, pimagedine, an inhibitor of AGE formation, did not ameliorate nephropathy in patients with type 1 diabetic mellitus (T1DM) (article number 44).

In addition to therapies developed based on classic mechanisms, researchers have highlighted new drugs developed based on new mechanisms in recent years. The sodium-glucose cotransporter 2 (SGLT-2) inhibitor empagliflozin and glucagon-like peptide 1 (GLP-1) agonist liraglutide are two rising stars in DKD treatment. There were 2 articles on empagliflozin among the top 100 most cited articles, one clinical trial (article number 36, 324 citations) published in 2013 and one experimental study (article number 96, 219 citations) published in 2014. Moreover, the clinical trial of liraglutide published in 2017 (article number 32, 337 citations) was the latest among the 100 articles. These new drugs represent new trends in DKD research.

Some experimental studies uncovered the crucial mechanisms of DKD, but the clinical translations of these studies were not included in the top 100 most cited articles. Fifteen articles elucidated the important roles of podocyte dysfunction (article number 33, 37, 54, 59, 77, and 87, a total of 1637 citations), immune cells and inflammation (article number 31, 43, 53, 68, 79, and 90, a total of 1616 citations), and vascular endothelial growth factor (VEGF) (article number 23, 28, 74, totally cited 943 times) in DKD, and 4 articles that were cited 1858 times demonstrated that transforming growth factor (TGF)-β (article number 6), fibroblasts (article number 12), and connective tissue growth factor (CTGF) (article number 40, 42) contribute to renal fibrosis in DKD. A new mechanism drawing the attention of researchers was the role of microRNAs (miRs) in DKD, which was discussed in 8 articles published from 2007 to 2013 (article number 13, 20, 34, 48, 57, 78, 83, and 99, a total of 2503 citations). Furthermore, metabolomics and transcriptomics analyses deepened researchers’ understanding of DKD. Targeting metabolic alterations (article number 29, 56, 65, and 82, a total of 1085 citations) and novel transcription factors (TFs) (article number 49, 61, 69, and 94, a total of 998 citations) had therapeutic effects in experimental DKD.

The articles above revealed the mechanism of and treatment strategies for DKD. In the remaining clinical studies, one article (article number 8, 571 citations) emphasized the importance of blood pressure (BP) control in DKD, and 2 articles discussed microalbuminuria (article number 14, 66, a total of 744 citations) in T1DM. Figure  4 d and e show the distributions of topics in ‘CS’ and ‘MG’ articles respectively. Furthermore, in Table  5 , we separately list the information and results of clinical studies in regard to their critical roles in clinical guidance.

Regarding other article types, 9 articles subcategorized as ‘ES’ and ‘PP’ helped researchers understand DKD from disparate aspects. Seven articles (article number 4, 16, 26, 46, 58, 76, and 99, a total of 2603 citations) were based on the epidemiological aspects of DKD, and 2 articles (article number 11, 47, a total of 828 citations) defined the pathological characteristics and classifications of DKD. Four of the 9 articles (article number 4, 26, 47, and 58) were specifically on nephropathy in T1DM.

Evolution of topics in clinical and experimental studies of DKD

To elucidate the trends in DKD research, we analysed the distributions of topics of ‘CS’ and ‘MG’ articles in different periods and illustrated their evolution, as shown in Figure S2 . Interestingly, we found that RAAS and OS are continuous hotspots of DKD research, again emphasizing the significance of the two research fields. Although attention has been given in the past, the number of studies on AGEs and RAGE has declined in recent years, which may be due to the frustration of clinical translation. Articles on miRs were predominately concentrated from 2008 to 2012, indicating the trendy miR-related study outbreak and attraction of numerous researchers in those years. In addition, some topics have appeared in recent years, including SGLT-2 and GLP-1, which have become new hotspots and have led to novel breakthroughs in DKD studies.

In this study, we ranked the top 100 most cited articles on DKD according to the total number of citations in the Web of Science Core Collection. In addition, we analysed the journals, timespans, authors, countries and topics of the 100 articles. This bibliometric analysis helps readers quickly understand the influential studies in DKD research, which topics attract other researchers, and the evolution of the research trend, thus guiding researchers to find interesting research directions and may help facilitate international collaborations. Popular clinical studies guide readers in clinical practice to provide more benefits for patients. Important experimental studies provide laboratory evidence for clinical trials and deepen the comprehension of the development and progression of DKD. Although some studies have not yet been clinically translated, they may direct future research and provide potential biomarkers and therapeutic targets as the subject develops in the future.

Bibliometric analysis is an effective method that is utilized in diverse areas of study [ 12 , 13 , 14 , 15 , 16 , 18 , 19 , 20 ]. A bibliometric analysis performed in 2019 [ 19 ] showed that 3 of the top 10 most cited articles in nephrology were on the subject of RAAS blockade usage in DKD. A former bibliometric analysis of DKD [ 20 ] highlighted the authors and co-citation networks but not the subcategories or contents. In this study, we further performed a bibliometric analysis of the top 100 most cited articles to elucidate what has been done and what needs to be completed in DKD research. In addition, there were some limitations in this study. We performed this study based on data from the Web of Science Core Collection, which means that some high-quality articles that were published earlier or were not in English were potentially excluded from this study. Another limitation is that the drawback of the bibliometric citation analysis method may contain bias, as recent articles have less time to be cited. Thus, we also listed the number of citations for each article per year, which helps to highlight the influence of recent studies [ 21 ] in addition to the total number of citations. On the other hand, we discussed the recent advances in traditional topics and more findings in the latest hotspots.

The most relevant field and a persistent interest in DKD research is RAAS, which was associated with most articles and citations. In the latest Kidney Disease: Improving Global Outcomes guidelines [ 1 ], angiotensin-converting enzyme inhibitors (ACEis) and angiotensin-II receptor blockers (ARBs) are recommended for use in DKD patients. In addition to ACEis and ARBs, there are other types of RAAS blockades, including direct renin inhibitors and ectoenzyme neutral endopeptidase inhibitors. In 2008, a randomized study showed that the combination of losartan and aliskiren, a direct renin inhibitor, significantly reduced the mean urine albumin-to-creatinine ratio (UACR) compared with that achieved with losartan combined with placebo in T2DM patients (article number 3, 751 citations). In 2018, the intention-to-treat analysis of UK HARP-III [ 22 ] showed that sacubitril, an ectoenzyme neutral endopeptidase inhibitor, combined with valsartan had a similar renal benefit and additional heart function protection when compared to that achieved with irbesartan in patients with an estimated glomerular filtration rate of 60 to 20 mL/min/1.73 m 2 . The intention-to-treat analysis of PARADIGM-HF [ 23 ] showed that sacubitril combined with valsartan took advantage of delaying renal function decline and protecting heart function when compared with enalapril in patients with diabetes. Novel RAAS inhibitors have promising prospects in the treatment of DKD owing to their advantages.

Notably, article number 71 (239 citations) highlights the expression of angiotensin-converting enzyme 2 (ACE2) in DKD. However, the expression of ACE2 in DKD is controversial [ 24 , 25 ]. One recent study [ 26 ] found that the mRNA level of ACE2 was increased in the proximal tubular epithelial cells of DKD patients. In addition, some studies [ 27 , 28 ] have shown that RAAS inhibitors upregulate the expression of ACE2. ACE2 is the receptor for SARS-CoV-2 [ 29 , 30 , 31 ], which is responsible for the COVID-19 outbreak, giving rise to the following two questions: will renal injury be increased in COVID-19 patients with diabetes and will ACEi/ARB treatment have an impact on the renal outcome of COVID-19 patients with diabetes? COVID-19 patients with T2DM have higher acute kidney injury prevalence rates than individuals without diabetes [ 32 ], which may be explained by ACE2-mediated viral cytopathic effects [ 26 , 33 ]. Some studies [ 34 , 35 ] implied that RAAS inhibitors increased the risk of acute kidney injury, suggesting more concern about renal outcomes in patients with severe COVID-19 with diabetes who are treated with ACEis/ARBs. More studies are needed to further elucidate the roles of ACE2 and ACEi/ARB-induced ACE2 in DKD.

Strategies for protecting renal function are a permanent topic of DKD. Although RAAS blockade benefits a substantial population of patients, there are still some questions regarding DKD treatment. Unfortunately, the development of novel drugs based on new mechanisms in DKD treatment has been uneven. Fortunately, two novel types of drugs, SGLT-2 inhibitors and GLP-1 receptor agonists, may represent the future of DKD treatment methods. CREDENCE [ 36 ] and the following analysis of CREDENCE [ 37 , 38 ] revealed that canagliflozin reduces the risk of renal failure and cardiovascular events and decreases anaemia-associated outcomes in T2DM patients with kidney disease. DAPA-CKD [ 39 ] showed that dapagliflozin, another SGLT-2 inhibitor, reduces kidney and cardiovascular events in chronic kidney disease patients with and without T2DM. Intriguingly, the latest publication among the top 100 most cited articles is a clinical trial of another new drug, liraglutide, a GLP-1 receptor agonists (article number 32), which has been proven to reduce the occurrence of persistent macroalbuminuria. Encouragingly, the two novel types of agents showed more advantages for kidney function protection than dipeptidyl peptidase-4 inhibitor or sulfonylureas [ 40 ] and were recommended by the Kidney Disease: Improving Global Outcomes guidelines guidelines [ 1 ] and consensus report by American Diabetes Association and the European Association for the study of diabetes [ 41 , 42 ] in T2DM patients with chronic kidney disease. To develop more novel targets of DKD treatment, further comprehension of the mechanisms of DKD is indispensable.

Technological innovation promotes scientific development. High-throughput technology and multiomics studies help researchers further understand the pathogenesis and prognosis of DKD (article number 65, 69). The application of single-cell and single-nucleus transcriptomics [ 43 , 44 , 45 ] identifies novel types of cells, describes cell-to-cell crosstalk, discovers further mechanisms and provides new insight into renal diseases. Further understanding the disease will help researchers find potential biomarkers and novel therapeutic strategies in the future.

Moreover, artificial intelligence is widely applied in the analysis of clinical indicators, digital imaging data, and digital pathological data in renal diseases [ 46 , 47 ] and improves the diagnosis and prognostication of DKD [ 48 , 49 , 50 ]. High-performance models built by artificial intelligence may contribute to more effective and accurate interventions in the clinical practice of DKD.

In conclusion, this article focused on the top 100 most cited articles on the subject of DKD. By reviewing the popular studies over several decades, researchers can better understand the evolution of DKD research. The important roles of ACEis and ARBs were once again emphasized in this study, and the prospects of SGLT-2 inhibitors and GLP-1 receptor activators are promising. Influential studies deepen the understanding of DKD and provide evidence for novel biomarkers and potential therapeutic strategies. This study helps readers quickly understand the important studies on DKD research, the distribution of popular topics and the evolution of the subject, thus providing a guide for research direction, international collaboration and clinical practice to better server patients.

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Abbreviations

Diabetic mellitus

Diabetic kidney disease

Chronic kidney disease

Oxidative stress

Citation time

Average citation time

Experimental studies

Clinical studies

Epidemiological studies

Pathological and pathophysiological studies

Renin-angiotensin-aldosterone system

Reactive oxygen species

Advanced glycation end products

Receptor for advanced glycation end products

Type 1 diabetic mellitus

Sodium-glucose cotransporter 2

Glucagon-like peptide 1

Vascular endothelial growth factor

Transforming growth factor

Connective tissue growth factor

Transcriptional factor

Blood pressure

Type 2 diabetic mellitus

Angiotensin-converting enzyme inhibitors

Angiotensin-II receptor blockers

Urine albumin-to-creatinine ratio

Angiotensin-converting enzyme 2

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Additional file 1: figure s1..

The top 10 relevant authors who contributed to the top 100 most cited articles. The dot size represents the author’s score, and the dot colour reflets the number of articles. Black represents one article, blue represents two articles, yellow represents three articles, and orange represents four articles. The authors’ contributions are exhibited as a bubble plot.

Additional file 2: Figure S2.

The evolution of topics in DKD research. The distributions of the topics RAAS (A), OS (B), AGEs and RAGE (C), miR (D), podocyte (E), inflammation (F), metabolism (G), TF (H), SGLT-2 and GLP-1 (I), VEGF (J), T1DM (K), CTCF (L), TGF-β (M), fibroblast (N) and BP (O) in different time periods reflect the evolution of topics in DKD research.

Additional file 3: Table S1.

Recent reviews on the subject of DKD.

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Wei, Y., Jiang, Z. The evolution and future of diabetic kidney disease research: a bibliometric analysis. BMC Nephrol 22 , 158 (2021). https://doi.org/10.1186/s12882-021-02369-z

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Diabetic nephropathy: recent advances in pathophysiology and challenges in dietary management

• Mahaboob Khan Sulaiman 1  

Diabetology & Metabolic Syndrome volume  11 , Article number:  7 ( 2019 ) Cite this article

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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. The progression of the disease is known to occur in a series of stages and is linked to glycemic and blood pressure control. However, despite aggressive blood sugar control the prevalence of chronic kidney disease (CKD) in diabetic patients has not witnessed any decrease in the last two decades; which has lead to identification of additional factors in its progression. The nutritional status of patients is an important and modifiable factor that may influence CKD processes and outcome. It directly stems from the traditional dietary choices that patients make due to poor nutritional awareness. Dietary management of DN patients is challenging, as the twin factors of diet overload on kidney function needs to be balanced with malnutrition. Patient education seems to be the key in avoiding overindulgence of carbohydrate and protein-rich foods while favoring inclusion of essential fats in their diet.

This review will summarize current advances in staging and molecular pathogenesis of DN. It will highlight recent studies focusing on patient-customized dietary interventions that offer new hope as an effective tool in improving quality of life and delaying disease progression in DN patients.

Introduction

In 2015, the International Diabetic Federation estimated that the prevalence of diabetes was 8.8% from ages 20 to 79 years affecting a population of approximately 440 million people [ 1 ]. This is predicted to grow to over 550 million people by the year 2035 [ 2 ]. One of the most important clinical features of diabetes is its association with chronic tissue complications. A short-term increase in hyperglycemia does not result in serious clinical complications. The duration and severity of hyperglycemia is the major causative factor in initiating organ damage. Early morphological signs of renal damage include nephromegaly and a modified Doppler, but the degree of damage is best ascertained from proteinuria and Glomerular filtration rate (GFR) [ 3 ]. The average incidence of diabetic nephropathy is high (3% per year) during the first 10 to 20 years after diabetes onset [ 4 ]. Typically, it takes 15 years for small blood vessels in organs like kidney, eyes and nerves to get affected. It is estimated that more than 20 and up to 40% of diabetic patients will develop chronic kidney disease (CKD) [ 5 , 6 ], depending upon the population, with a significant number that develop end stage kidney disease (ESKD) requiring renal replacement therapies such as kidney transplantation. Incidentally, diabetes with no clinical sign of kidney damage during the initial 20 to 25 years is significantly less likely (1% a year) to cause major renal complication later in life [ 4 ].

Staging of diabetic nephropathy

Until recently, diabetic nephropathy was defined by the evidence of proteinuria ≥ 300 mg/day, in a diabetic patient [ 7 ]. Although urinary albumin is recognized as an early marker of DN, significant glomerular damage has already occurred when albumin appears in urine. Therefore, novel urinary biomarkers are needed to identify patients who are at risk of developing kidney damage. A proteomic study of the condition collectively termed as non-albumin proteinuria (NAP) identified several putative early biomarkers such as α-1 microglobulin, β-1 microglobulin, Nephrin, Cystatin C etc., [ 8 ]. While these markers can serve as sensitive early indicators of tubule damage, currently, they are neither calibrated nor universally available [ 9 ]. Moreover, precipitation of morning urine proteins and subsequent resolution by 2D electrophoresis also identified another putative urinary biomarker kininogen-1. This protein involved in the kallikrein-kinin system also awaits validation in larger cohorts [ 10 ].

Several recent studies have enabled a more robust and comprehensive stratification of DN. In 2010, Tervaert et al. reported a new pathological classification of kidney lesions that involved tubules, interstitium and/or the vessels as shown in Table  1 [ 11 ]. Such a classification was required, as a considerable percentage of patients with diabetes and impaired renal filtration do not exhibit elevated protein excretion. Also, many patients with Type 1 DM show proteinuria without concurrent GFR changes. Since diabetes mellitus studies are often observational and lack biopsy data to prove involvement of lesions, diabetic nephropathy is now classified as diabetic kidney disease (DKD). Interestingly, these classical stages of type 1 DM (T1DM) may not occur in type 2 DM (T2DM) patients as the latter is often diagnosed with concurrent disorders such as hypertension, proteinuria and renal failure [ 11 , 12 ]. Therefore, a new term diabetic chronic kidney disease (DCKD) was proposed to replace diabetic nephropathy to explain the extent of kidney damage. Additionally, in these patients with type 2 DM, it is recommended that screening should be performed at diagnosis and yearly thereafter. More recently, Gheith et al. [ 13 ] have proposed five stages of diabetic nephropathy after a comprehensive review of literature as summarized in Table  1 .

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 ]. Other putative risk factors include elevated glycosylated haemoglobin level (HbA1c), elevated systolic pressure, proteinuria and smoking [ 15 ].

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. Genome-wide transcriptome studies [ 16 ] and high-throughput technologies [ 17 ] indicate the activation of inflammatory signaling pathways and oxidative stress highlighting the role of genetic factors. Evidences suggest that epigenetic mechanisms such as DNA methylation, noncoding RNAs and histone modifications can also play a pivotal role in the pathogenesis of diabetic nephropathy. Accordingly, cytokine TNF-alpha, IL-6 and IL-1 beta gene promoter polymorphisms and modulation in expression have been linked to DN susceptibility in subjects.

Dysregulation of local metabolic environment triggered by inflammation and subsequent tissue remodeling may initiate kidney damage [ 18 ]. Excess intracellular glucose have been shown to activate cellular signaling pathways such as diacylglycerol (DAG)-protein kinase C (PKC) pathway, advanced glycation end-products (AGE), polyol pathway, hexosamine pathway and oxidative stress [ 19 ]. Many studies have linked these pathways to key steps in the development of glomerulosclerosis. In addition to these metabolic pathways, Rho-kinase, an effector of small-GTPase binding protein Rho, has been linked to various steps in the ultra structural damage of diabetic nephropathy by inducing endothelial dysfunction, mesangial excessive extracellular matrix (ECM) production, podocyte abnormality, and tubulointerstitial fibrosis. A review on the important pathways that lead to diabetic nephropathy can be found elsewhere [ 20 ].

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. In fact, some patients may regress to normoalbuminuria [ 21 ]. The progression of kidney disease in type 1 diabetes mellitus is unpredictable and seems to be connected to the intensity of blood sugar and pressure control. Accordingly, while initial studies reported that ~ 80% microalbuminuric patients progress to proteinuria over 6–14 years [ 22 , 23 ], recent studies have reported a regression as a result of better glycemic control. For example, the Joslin type 1 cohort and DCCT/EDIC study reported roughly similar results of 58% patients and 50% patients with microalbuminuria regressed to normoalbuminuria over 6 years and within 10 years, with or without renin–angiotensin–aldosterone system (RAAS) inhibitors respectively, solely with better control of diabetes, hypertension and lipids [ 24 , 25 ]. Improvement in microalbuminuria also resulted in 89% lower risk of developing a decreased GFR in type 1 DM patients.

In contrast, progression and regression of kidney disease in type 2 DM is highly variable as it is usually diagnosed with a secondary disorder, the onset of which is unrecorded. The UKPDS study reported microalbuminuria and reduced GFR in 38% and 29% patients respectively after a median follow-up of 15 years [ 26 ]. In terms of progression, the same study reported a change from microalbuminurea–macroalbuminuria-ESKD at 2.8% and 2.3% per year respectively. In contrast, the Pima Indians study reported that macroalbuminuria was 50% during a median follow-up of 20 years [ 27 ]. Also, a gradual loss of kidney damage with time was noticed as 7.3% patients were diagnosed with microalbuminuria at the onset, 17.3% at 5 years, 24.9% at 10, and 28% at 15 years. Epidemiological studies in Western and Pima Indian populations also suggest that the prevalence of overt nephropathy is about 21% in patients with type 1 DM, and 20–25% in patients with Type 2 DM, depending solely on the duration since onset of disease.

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. As albuminuria has certain limitations the quest for more reliable serum and renal biomarkers with higher sensitivity and specificity has led to an explosion of literature in this field. MacIssac et al. [ 28 ] have presented a detailed review of current literature on relevant biomarkers. Recently, Motawi et al. [ 29 ] estimated three new promising biomarkers: neutrophil gelatinase-associated lipocalin (NGAL), beta-trace protein (beta TP) and microRNA-130b (miR-130b) in type 2 DM. They concluded that serum NGAL and betaTP were significantly elevated in T2DM patients and can serve as early biomarkers of tubular and glomerular markers respectively. Other recent reviews on the promise of biomarkers in early detection of DKD can also be seen [ 30 ]. Such advances in biomarker research and metabolic phenotyping offer hope for multiparametric risk assessment of kidney injury and effective interventional strategies in future.

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. Consequently, intensive glycaemic control, antihypertensive treatment by blocking RAAS system and lipid-modifying statin therapy are the main cornerstones of treatment. A detailed discussion of the various treatment methods of diabetic nephropathy is beyond the scope of this article, and reviews on the subject are available [ 31 , 32 , 33 ].

The nutritional status of patients is an important and modifiable factor that may influence DN processes and outcome [ 34 ]. Diet is a crucial factor in influencing the nutritional status of an individual. Whereas diabetes advocates a healthy and balanced diet, diet of a CKD or diabetic nephropathy patient is challenging and designed to delay progression of kidney damage and the associated secondary conditions such as hypertension, hyperlipidemia, uremia, etc. It also needs continuous monitoring and must be personalized to the patients’ treatment regimen. As food intake could be a burden on kidney function, a delicate balance between nutrition and sustainable physiological load is essential to maintain quality of life for the patient. A common problem encountered in patients with renal failure and proteinuria is their lack of nutritional knowledge and continued adherence to traditional food choices that are rich in carbohydrate, proteins or minerals. Since a majority of patients are dyslipidemic the only control they exercise is on limiting fat intake. Such a skewed diet places a tremendous burden on kidney function that causes further problems in disease management.

An ideal diet recommended for diabetic nephropathy patients with compromised kidney function includes a proper amount of fat to prevent malnutrition. More so when total calories coming from protein and carbohydrate intake needs to be restricted. A total fat reduction as advised by earlier studies can be a very unhealthy practice. Thus, to achieve these goals nutritionists advice limiting saturated fatty acid consumption while taking vegetable oils and omega-rich fatty acid containing oils in moderation. Many clinical studies have highlighted the renoprotective effects of a low protein diet on DN, although protein restriction alone does not result in a positive outcome for patients [ 35 ]. Moreover, a protein-deficient diet (0.6 to 0.7 g/kg/day) needs to be integrated into the overall care of renal insufficiency with customized dietary interventions to avoid malnutrition [ 36 ]. Interestingly, in animal type 2 DM models a very low protein diet (VLPD) improved tubulo-interstitial damage, inflammation and fibrosis, through restoration of autophagy via reduction of a mammalian target of rapamycin complex 1 (mTORC1) activity [ 37 ]. Although a low protein diet slows progression of renal dysfunction in human subjects with chronic glomerular nephritis, VLPD has not been clinically validated. A low-salt diet that is devoid of salted and pickled foods is highly recommended for DN patients. Restricted sodium intake allows better blood pressure control in such patients. High salt intake and urinary protein excretion were associated with annual creatinine clearance decline in type 2 DKD patients as reported by Kanauchi et al. [ 38 ]. Potassium is an essential electrolyte involved in the contraction and relaxation of muscles. During a deficit in kidney function potassium excretion is reduced leading to an accumulation in body tissues. Therefore, potassium intake specifically from foods such as grains, potatoes, corn, soybean, nuts, tomatoes, banana, melons, kiwi etc. must be restricted. Like potassium, phosphorus excretion is also reduced during chronic kidney damage leading to increased blood phosphorus levels. Since phosphate is in homeostatic equilibrium with the skeletal muscle calcium levels, an imbalance leads to a significant calcium loss and debilitating bone disease. In summary, excessive carbohydrate and protein intake is managed with a target of 1600 kcal of energy per day in which 60 percent comes from carbohydrate and 40 percent from proteins. In a recent study, such a regimen achieved a commendable control in blood lipid and glucose values in a patient with stage 4 chronic kidney disease [ 39 ]. However, patient adherence to the recommended diet seems to be gender-specific. For example, Ahola et al. [ 40 ] assessed frequency of adherence to special diet in a large cohort Finnish DN study and reported that adherents were more frequently women, older, and had longer duration of diabetes. Therefore, effective adherence through patient education may be a crucial factor in the management of DN through diet.

In conclusion, this review summarizes the recent advances in the pathophysiology of diabetic nephropathy and the importance of dietary factors in modifying treatment outcomes for patients. A critical analysis of studies that emphasize the importance of patient-centered dietary intervention in successful management of advanced CKD patients has been presented. Large-scale cohort studies are necessary to evaluate the efficiency of diet as a new therapeutic paradigm. Nevertheless, proactive personalized diet-management plans tailored to the disease stage is likely to be the future trend in diabetic nephropathy therapy as it will have a large impact on the patient’s quality of life and may prolong survival. Notably, in newly diagnosed DN patients these dietary interventions may no longer be regarded as complementary measures but significant factors that delay progression of the disease.

Abbreviations

chronic kidney disease

diabetic nephropathy

glomerular filtration rate

end stage kidney disease

diabetes mellitus

diabetic kidney disease

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Sulaiman, M.K. Diabetic nephropathy: recent advances in pathophysiology and challenges in dietary management. Diabetol Metab Syndr 11 , 7 (2019). https://doi.org/10.1186/s13098-019-0403-4

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Screening and early diagnosis of ckd associated with type 2 diabetes, referral criteria and impact of early versus late referral on clinical outcomes, treatment goals: surrogate and clinically meaningful end points, lifestyle modifications and drug treatments to mitigate the risk of complications in type 2 diabetes, the pillar approach, article information, perspectives on chronic kidney disease with type 2 diabetes and risk management: practical viewpoints and a paradigm shift using a pillar approach.

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Javier Morales , Sam Dagogo-Jack , Vivian Fonseca , Joshua J. Neumiller , Sylvia E. Rosas; Perspectives on Chronic Kidney Disease With Type 2 Diabetes and Risk Management: Practical Viewpoints and a Paradigm Shift Using a Pillar Approach. Clin Diabetes 1 October 2023; 41 (4): 553–566. https://doi.org/10.2337/cd22-0110

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The American Diabetes Association’s (ADA’s) Standards of Medical Care in Diabetes is updated annually and as needed through Living Standards updates, as new evidence emerges that affects key recommendations ( 1 ). These standards provide the latest evidence-based guidance for diagnosing and treating patients with diabetes. The level of support for each recommendation is based on an evidence grading system ( 2 ). The 2022 Standards of Care included a new Chapter 11 focusing on the prevention and management of chronic kidney disease (CKD) in patients with diabetes ( 3 ). In the 2023 Standards of Care—the most recent update published as of this writing—Chapter 11 was updated further ( 4 ). These updates include changes to the urinary albumin-to-creatinine ratio (UACR) threshold for sodium– glucose cotransporter 2 (SGLT2) inhibitor use, which was reduced from a threshold of ≥300 to ≥200 mg/g (evidence grade A) ( Table 1 ) ( 3 – 5 ).

ADA Guidelines on CKD in Patients With Type 2 Diabetes: Key Changes From 2021 to 2023

An addendum to Chapter 11 published in May 2022 regarding the use of SGLT2 inhibitors changed the recommended eGFR threshold for SGT2 inhibitor use in CKD from ≥25 to ≥20 mL/min/1.73 m 2 (evidence grade A).

Finerenone is currently the only nsMRA used in CKD associated with type 2 diabetes.

Agents in the SGLT2 inhibitor drug class can reduce CKD progression and cardiovascular events. The estimated glomerular filtration rate (eGFR) threshold for SGLT2 inhibitor use in this context had already changed from ≥25 mL/min/1.73 m 2 in the ADA Standards of Care published in January 2022 ( 6 ) to ≥20 mL/min/1.73 m 2 in an addendum to Chapter 11 published in May 2022 ( 7 ). An above-normal UACR (normal is <30 mg/g; Figure 1 ) is a marker of kidney damage, whereas a lower-than-normal eGFR (normal is ≥90 mL/min/1.73 m 2 ; Figure 1 ) is a marker for impaired kidney function ( 8 – 10 ). Other updates to Chapter 11 include a change to the recommendation on use of the nonsteroidal mineralocorticoid receptor antagonist (nsMRA) finerenone in patients who are at an increased risk of cardiovascular events or CKD progression; the wording “or unable to use an SGLT2 inhibitor” was removed from the recommendation ( Table 1 ) ( 3 – 5 ). The recommendation for referral to a nephrologist was also updated ( Tables 1 and 2 ) ( 3 – 5 , 8 , 11 ).

Risk of CKD progression, frequency of visits, and treat and refer (to a nephrologist) recommendations according to GFR and albuminuria. a Grid depicts risk of progression, morbidity, and mortality by color from best to worst (green, yellow, orange, red, dark red). Numbers in boxes are a guide to frequency of visits (number of times per year). b Referring clinicians may wish to discuss with their nephology service, depending on local arrangements regarding treating or referring. Adapted from refs. 8 – 10 .

Recommendations on Referral to Specialists, as Stated in Three Guidelines

Defined based on one of more of the following: decline in GFR category (≥90 [G1], 60–89 [G2], 45–59 [G3a], 30–44 [G3b], 15–29 [G4], <15 [G5] mL/min/1.73 m 2 ). A certain drop in eGFR is defined as a drop in GFR category accompanied by a ≥25% drop in eGFR from baseline. Rapid progression is defined as a sustained decline in eGFR of >5 mL/min/1.73 m 2 /year. The confidence in assessing progression is increased with increasing number of serum creatinine measurements and duration of follow-up.

With ACE inhibitor/ARB or SGLT2 inhibitor.

The threshold for referral may vary depending on the frequency with which a provider encounters patients with diabetes and kidney disease.

Biopsy may be considered. ACR, albumin-to-creatinine ratio; AER, albumin excretion rate; AKI, acute kidney injury; PCR, protein-to-creatinine ratio; PER, protein excretion rate; RBC, red blood cell.

The United Kingdom’s National Institute for Health and Care Excellence (NICE) Chronic Kidney Disease: Assessment and Management guidelines are updated regularly, with topics prioritized according to need. The current version was published in August 2021, with an update concerning SGLT2 inhibitor use in patients with type 2 diabetes and CKD published in November 2021.

Kidney Disease Improving Global Outcomes (KDIGO) has published clinical practice guidelines since 2003. The guidelines are based on the Grading of Recommendations Assessment, Development and Evaluation system to evaluate the quality of evidence and the strength of recommendations. The 2022 update to the KDIGO guidelines (Clinical Practice Guideline on Diabetes Management in Chronic Kidney Disease) was published in November 2022 ( 12 ). Additionally, a consensus report by the ADA and KDIGO, published in 2022, aimed to harmonize recommendations on screening, diagnosis, comprehensive care, treatment targets, and drug treatments for CKD and diabetes ( 13 ).

In response to the publication of the ADA’s 2023 Standards of Care (and, where relevant, contrasting these to the ADA 2022 guidelines and May 2022 addendum), the KDIGO 2022 guidelines, and the 2022 ADA/KDIGO consensus report, we provide here practical viewpoints from five clinicians experienced in the field of type 2 diabetes and CKD about the screening, early diagnosis, and treatment of CKD. We also compare the CKD-specific aspects of the ADA guidelines with applicable aspects of the KDIGO and NICE guideline recommendations. Finally, we discuss a possible future treatment strategy for the treatment of CKD with diabetes.

CKD is defined as an abnormality in kidney structure and/or function based on the following criteria: eGFR <60 mL/min/1.73 m 2 and/or albuminuria (urinary albumin excretion rate ≥30 mg per 24 hours or UACR ≥30 mg/g) for >3 months ( 8 ).

Both UACR and eGFR are used for staging of CKD. As noted previously, eGFR is a marker of kidney function, and UACR is a marker of kidney damage. If the eGFR decreases from a patient’s baseline value (and this is replicated on retesting), this suggests worsening of kidney function; if the UACR increases from the baseline value (and this is replicated on retesting), this suggests worsening kidney damage. Of note, moderately increased urine albumin levels—previously called microalbuminuria and defined as UACR 30–300 mg/g—typically appears before a significant decline in eGFR in patients developing CKD ( 14 – 16 ). The KDIGO heat map ( Figure 1 ) can be used to establish whether decreases in eGFR and/or increases in UACR are clinically significant and can be used to support a CKD diagnosis and to guide treatment ( 4 , 8 – 10 , 12 ). CKD is commonly attributed to diabetes and/or hypertension, but other possible causes include glomerulonephritis, polycystic kidney disease, systemic infection, autoimmune disease, drug toxicity, vascular diseases, and environmental exposures ( 8 ).

Diabetic kidney disease (DKD) is defined with similar criteria as CKD but occurs in the setting of diabetes and in the absence of other causes of CKD ( 17 ). In most patients with diabetes, CKD should be attributable to diabetes if one of the following conditions applies: 1 ) UACR >300 mg/g, 2 ) UACR 30–300 mg/g in the presence of diabetic retinopathy (DR), or 3 ) UACR 30–300 mg/g in type 1 diabetes of at least 10 years’ duration ( 18 ). eGFR alone may be a less sensitive screening method for DKD because many patients with DKD may demonstrate normal eGFR in the early years after diagnosis ( 18 ). The term “CKD associated with type 2 diabetes” is now more commonly used than “DKD” and will be used hereafter in this article.

The term “diabetic nephropathy” may be used when referring to CKD associated with type 2 diabetes, but the terms are not fully interchangeable: “CKD associated with type 2 diabetes” refers to the structural and functional alterations associated with diabetes, whereas “diabetic nephropathy” refers to histological findings on biopsy ( 19 ). However, the 2022 KDIGO guidelines suggest that the term “diabetic nephropathy” is an “outdated term” with “no consensus definition” ( 12 ). Thus, to avoid possible confusion, we will not use this term in this review except when it is used in the reference cited.

Approximately one in three adults with type 2 diabetes may have CKD, and as many as 90% of adults with CKD and 40% of adults with severe CKD are unaware of their kidney disease ( 20 ). These statistics underscore the importance of informing patients with diabetes, as well as clinicians, about the significance of screening for CKD.

Abnormalities in kidney structure may precede reductions in kidney function, and both presentations may be associated with complications such as cardiovascular disease (CVD) and metabolic disease ( 8 , 21 ). The most widely used and generally accepted index of kidney function is the eGFR ( 8 ). An important test for kidney damage in CKD is the UACR test, where (as noted previously) an above-normal level of albuminuria is a marker of kidney damage ( 8 ). The UACR can be determined from a spot urine collection or via a 24-hour urine collection; generally, the spot UACR test is preferred because the 24-hour collections are more burdensome with minimal differences between the two techniques in prediction or accuracy ( 4 ). Therefore, albuminuria and eGFR independently influence prognosis of CKD associated with type 2 diabetes, as represented in the KDIGO heat map ( Figure 1 ), where albuminuria and/or a low eGFR indicate an increasing risk of CKD progression, frequency of visits, and need for referral to a nephrologist ( 8 – 10 ).

ADA Screening and Treatment Recommendations

The ADA 2023 Standards of Care recommends that patients with type 2 diabetes should be screened at least annually for albuminuria using the spot urine test for UACR and should have their eGFR assessed, and this should be done irrespective of treatment (evidence grade B) ( 4 ). Naturally, consideration should be made of factors other than kidney damage, such as infection or strenuous exercise, that may also elevate UACR ( 8 , 22 ). Patients with established CKD associated with type 2 diabetes should have their UACR and eGFR monitored one to four times per year depending on their CKD stage (evidence grade B) ( 4 ). referral criteria and impact of early versus late referral on clinical outcomes below and Table 2 provide the ADA’s criteria for specialist referral ( 4 , 8 , 11 ).

Other Screening and Treatment Recommendations

Nice guidelines.

NICE provides a comprehensive list of recommendations on the diagnosis, assessment, and initial investigations for CKD ( 11 , 23 ), which contrasts to the ADA’s summary recommendations (with evidence grading) in relation to CKD associated with type 2 diabetes. Screening (or initial investigations) should be considered for patients with risk factors for CKD (including type 2 diabetes), with incidental findings suggestive of kidney disease (e.g., elevated serum creatinine and/or eGFR <60 mL/min/1.73 m 2 ) and/or with possible clinical features of CKD ( 11 , 23 ). Albuminuria and/or eGFR should be followed up within 3 months to determine the CKD stage ( 11 , 23 ). Additionally, patients with CKD may have symptoms in late stages, such as uremic fetor, pallor, cachexia, cognitive impairment, tachypnea, dehydration, hypertension, peripheral edema, peripheral neuropathy, and/or foamy urine ( 11 , 23 ); such symptoms are rarely seen in early-stage CKD (stages 1 and 2). Clinicians should also check their patients’ nutritional status, BMI, blood pressure, A1C, and lipid profile to optimize CVD risk factors. NICE also provides detailed specialist referral criteria, which are described in referral criteria and impact of early versus late referral on clinical outcomes below and in Table 2 ( 4 , 8 , 11 ).

KDIGO guidelines

The 2012 and 2022 KDIGO guidelines ( 8 , 12 ) do not include formal recommendations regarding screening for CKD or how often testing for kidney disease markers should be done, but they do note that public health policies should include screening in high-risk populations such as those with diabetes ( 8 ). Furthermore, the KDIGO guidelines include a table that provides expanded criteria for the definition of CKD and can be used by nonnephrologist physicians and other health care professionals to assist in the detection of CKD. In addition to the definition of CKD described previously in this article, these criteria include urinary sediment abnormalities, renal tubular disorders, pathological and structural abnormalities (as markers of kidney damages), and history of kidney transplantation ( 8 ). Although not included as a formal recommendation, the KDIGO 2012 guidelines recognize the importance of early detection of CKD ( 8 ). Avoiding a delay in diagnosis or early intervention to prevent progression of CKD can confer morbidity and mortality benefit at a lower cost than kidney transplantation ( 8 ). KDIGO criteria for referral to a specialist are provided in referral criteria and impact of early versus late referral on clinical outcomes below and in Table 2 ( 4 , 8 , 11 ).

ADA–KDIGO 2022 Consensus Report

As noted previously, the ADA 2023, KDIGO 2022, and NICE clinical practice guidelines differ in some respects in their recommendations for screening and early diagnosis of CKD. Although treatment guidelines are not intended to define a standard of care ( 12 ), the implications to clinical practice of differences in recommendations may lead to confusion (in terms of which guideline to follow and when) and nonadherence ( 24 , 25 ). In the case of CKD with type 2 diabetes, the ADA and KDIGO are working together to harmonize their treatment guidelines ( 13 ). Regarding screening, the ADA/KDIGO consensus report notes that screening should occur annually from the point of diabetes diagnosis in people with type 2 diabetes, with persistent abnormalities defining CKD ( 13 ). This alignment elevates the importance of screening for CKD both at diagnosis of type 2 diabetes and every year thereafter.

Other CKD Screening Approaches in Diabetes: DR

The ADA 2023 Standards of Care recommends screening for DR via an initial dilated and comprehensive eye examination by an ophthalmologist or optometrist at the time of a type 2 diabetes diagnosis (Chapter 12; evidence grade B) ( 26 ). If there is no evidence of DR for ≥1 year of annual examinations and glycemia is well controlled, then examinations may be repeated every 1–2 years (evidence grade B) ( 26 ). However, retinopathy status should be reassessed when intensifying glycemic control. In the SUSTAIN-6 (Trial to Evaluate Cardiovascular and Other Long-term Outcomes with Semaglutide in Subjects with Type 2 Diabetes) study, the number of retinopathy complications was significantly higher with semaglutide, a glucagon-like peptide 1 (GLP-1) receptor agonist, than with placebo, and semaglutide profoundly reduced A1C versus placebo ( 27 ). However, it is important to note that the patients in the SUSTAIN-6 trial were at high cardiovascular risk, >82% had preexisting retinopathy, and >58% were taking insulin at baseline, so it is not clear whether the retinopathy complications seen with semaglutide are a direct drug effect or the result of reduced A1C. Indeed, the SUSTAIN-6 authors noted that application of such an association is unclear, but a direct effect of semaglutide still cannot be ruled out.

Although no formal recommendations on DR screening in relation to CKD are included in the ADA 2023 or KDIGO guidelines, DR has been shown to be a highly specific indicator for the diagnosis of diabetic nephropathy ( 28 ). Furthermore, several studies have suggested that DR severity in patients with type 2 diabetes can be used to predict CKD severity and/or progression risk at diagnosis ( 28 – 30 ). Thus, among other screenings, clinicians should evaluate DR severity in patients with type 2 diabetes at the time of diagnosis and monitor kidney function in patients with severe DR, as suggested ( 30 ).

The ADA ( 4 ), NICE ( 11 ), and KDIGO ( 8 ) have each provided detailed guidance regarding the timing or threshold for referral of patients to a nephrologist ( Table 2 ). For example, the ADA recommends consultation with a nephrologist when there is a continuously rising UACR and/or a continuously declining eGFR, if there is uncertainty about the etiology of kidney disease, for difficult management problems, for CKD progression to stage 4 (eGFR <30 mL/min/1.73 m 2 ), and/or when there is urinary sediment, nephrotic syndrome, or the absence of retinopathy in type 1 diabetes ( Table 2 ) ( 4 , 8 , 11 ).

Early, appropriate referral to a nephrologist is associated with reduced mortality and hospitalizations and better dialysis preparation ( 31 ). A meta-analysis of 40 studies involving 63,887 patients with CKD found that almost one-third ( n = 20,678) were referred late (defined as <1 to 6 months before starting dialysis) ( 31 ). Those referred early compared with those referred late had reduced mortality and hospitalizations, better uptake of peritoneal dialysis, and earlier placement of arteriovenous fistulae. Differences in mortality and hospitalizations were not explained by the prevalence of comorbid disease or serum phosphate levels.

Another study found that many patients with CKD are referred late ( 32 ). An analysis of electronic health records from 2017 to 2019 suggested that 54.6% of patients with an eGFR <30 mL/min/1.73 m 2 had not been referred to a nephrologist ( 32 ). The analysis also found that patients of younger age, with complex medical histories, and treated by primary care providers (PCPs) at an academic medical center were more likely to be referred ( 32 ). Furthermore, both a regional shortage of nephrologists ( 33 ) and a lack of PCP awareness of guideline recommendations for referral ( 34 ) may contribute to low rates of referral. Other barriers to (early) referral and overall effective comanagement of patients with CKD include a lack of effective collaboration tools for facilitating timely adequate information exchange between PCPs and specialist (nephrology) services, a lack of clear understanding of roles and responsibilities, and a need for greater access to specialist advice ( 35 ).

Referral for a Kidney Biopsy

Most people with diabetes and CKD do not get a kidney biopsy. According to the ADA, referral for a kidney biopsy is recommended in patients with type 1 diabetes when additional or nondiabetic causes of kidney disease are suspected ( 4 ). The NICE guidelines provide a list of kidney disease markers and symptoms and a requirement of family history of kidney disease as indications for referral for a renal ultrasound; here, a nephrologist may consider that the patient needs a kidney biopsy ( 11 ). The KDIGO 2012 guidelines provide some general guidance concerning kidney biopsy referral criteria. Patients with a decline in eGFR without markers for kidney damage may be referred for a biopsy to look for evidence of parenchymal lesions ( 8 ). However, although a kidney biopsy is required to diagnose diabetic glomerulopathy definitively, in most cases careful screening of patients with diabetes can identify those with a high likelihood having CKD associated with type 2 diabetes without the need for a kidney biopsy ( 18 ). A biopsy should only be performed if it is essential to confirm a diagnosis and the benefits outweigh the risks (such as bleeding) and costs ( Table 2 ) ( 4 , 8 , 11 ).

Although prevention of or reduction in the risk of end-stage kidney disease (ESKD) is an accepted clinically meaningful end point of CKD treatment, several surrogate end points have been developed to facilitate clinical trials ( 36 ). Levey et al. ( 37 ) proposed that a UACR reduction of 30% in 6 months or an eGFR slope reduction by 0.5–1.0 mL/min/1.73 m 2 over 2–3 years is a threshold reliably associated with significant treatment effects on kidney disease progression under certain conditions. (These numbers vary with sample size.) Using eGFR slope is also more appropriate and valid than changes of albuminuria, but it requires more attention to acute effects and a longer follow-up period ( 37 ). The ADA 2023 Standards of Care recommend that, in patients with CKD who have ≥300 mg/g urinary albumin, a reduction of ≥30% in mg/g urinary albumin is recommended to slow CKD progression (evidence grade B) ( 4 ).

Clinicians should be aware that, although these surrogate end points are intermediate outcomes (i.e., not final clinical outcomes of interest) that can be tested in a laboratory, a strong mathematical association between the surrogate and clinical end points does not always guarantee surrogacy in a clinical context ( 36 ). Surrogate markers can be influenced by the presence of acute drug effects ( 38 ), day-to-day fluctuation caused by analytical bias ( 39 , 40 ), beneficial effects of treatment in patients with fast progression of disease (proportional treatment effects) ( 41 ), and patients’ age ( 42 ).

In addition, criteria for CKD associated with type 2 diabetes that are based on albuminuria may not be applicable to all patients because some patients develop advanced disease without showing albuminuria, and others with albuminuria do not demonstrate pathological evidence of kidney damage ( 18 ). Among U.S. adults with diabetes from 1988 to 2014, although the overall prevalence of CKD associated with type 2 diabetes (defined as albuminuria ≥30 mg/g, reduced eGFR <60 mL/min/1.73 m 2 , or both) did not change significantly, the prevalence of albuminuria declined, and the prevalence of reduced eGFR increased ( 43 ). The ADA 2023 guidelines also note the existence of frequent cases of reduced eGFR without albuminuria in patients with diabetes ( 4 ).

Furthermore, the drugs used to treat CKD can cause multiple effects beyond the target effect, and off-target effects can contribute to the ultimate effect on clinically meaningful kidney outcomes ( 36 ). For example, renin– angiotensin system (RAS) inhibitors reduce blood pressure and albuminuria, both of which contribute to renoprotection, but may also elevate blood potassium levels. Therefore, multiple risk parameters and risk scores ( 36 ) that integrate all known drug-induced effects are potentially more reliable than single markers to help clinicians make more appropriate treatment decisions. A scoring system that integrates multiple short-term drug effects (i.e., changes in systolic blood pressure, albuminuria, potassium, hemoglobin, cholesterol, and uric acid) was generated to predict the long-term effect on kidney and cardiovascular outcomes. These scores provided better prediction of the drug effect on hard kidney outcomes than single markers ( 36 , 44 ).

Lifestyle modifications and self-management are important elements of risk reduction for type 2 diabetes– associated complications ( 12 , 45 ). Lifestyle modifications include losing excess weight, consuming fewer simple sugars and saturated fats, adopting healthy eating habits, increasing physical activity (to at least 150 minutes/week), and smoking cessation ( 6 , 12 , 45 ). Additionally, drug treatments that help to optimize blood glucose levels (such as SGLT2 inhibitors or metformin) and blood pressure (RAS inhibitors) and/or for lipid management (statins) may be needed if lifestyle modifications alone are not sufficient to reduce risk ( 6 , 12 , 45 , 46 ). Aspirin may be appropriate for those at high risk of atherosclerotic CVD. Risk factor reassessment should be completed every 3–6 months ( 12 ).

The use of drug treatments to support risk mitigation in type 2 diabetes (and in CKD associated with type 2 diabetes) is important, and treatment guidelines provide information on the treatment thresholds that should be reached before drug initiation. However, what may not be as clear in the guidelines is what the recommended approach should be when a patient is experiencing adverse effects. Should the drug be discontinued permanently? Should it be discontinued and reintroduced at a lower dose? Should an alternative drug be used? None of the guidelines provide specific detailed guidance on this point, perhaps because of the wide heterogeneity of the type 2 diabetes population. Thus, clinicians should continue to use a holistic and patient-centered approach when supporting high-risk patients.

The ADA/KDIGO consensus report does include summary guidance according to adverse event risk versus benefit for various drug classes ( 13 ). For example, using an SGLT2 inhibitor as a glucose-lowering drug also has the benefit of potentially reducing progression of CKD with no notable increased risk of adverse events, but if a thiazolidinedione is used as a glucose-lowering drug in patients with type 2 diabetes who are at high risk of heart failure, there is no evidence of overall benefit, but there is an increased risk of adverse effects.

Pharmacological management of chronic conditions such as type 2 diabetes usually follows a linear, or stepwise, approach through which drugs are added (and optimized) or stopped based on their toxicity, efficacy, and/or patient-reported quality of life. Each treatment step requires a period of waiting to ascertain these effects before moving on to the next step. However, is a linear treatment approach always the most appropriate strategy for patients with a chronic progressive condition? In this section, we discuss a hypothetical treatment approach that uses multiple drugs simultaneously, each targeting a different biological pathway associated with disease progression. We first discuss an established example of a pillars of therapy hypothesis (with each pillar representing a different drug class) in the treatment of heart failure with reduced ejection fraction (HFrEF). Next, we focus on a pillar approach hypothesis for pharmacological management of CKD with type 2 diabetes.

Recently, the “four pillars of heart failure” was proposed as a strategy to treat patients with HFrEF ( 47 ). This four-pillars approach could reduce the risk of treatment delays and offer patients a health benefit compared with the current linear (stepwise) treatment approach ( 47 ). The linear approach to treating HFrEF involves initiation of first-line drug therapy with an ACE inhibitor plus a β-blocker, which is followed by a waiting period during which assessments and checks are made to determine whether the patient is responding to and tolerating treatment. Angiotensin receptor- neprilysin (ARN) inhibitors may replace ACE inhibitors ( 48 ). Additional therapies (e.g., a mineralocorticoid receptor antagonist) are then recommended for patients who do not respond to first-line therapy ( 48 ). This linear approach is standard across treatment guidelines, but it does introduce a time delay before advancing treatment to the next step in a population of patients who already have an acute, life-limiting condition ( 47 ).

In the proposed four-pillars approach to HFrEF, all four agents (ARN inhibitor, β-blocker, MRA, and SGLT2 inhibitor) ( 49 ) are initiated simultaneously, followed by optimization of dosing, when required ( 47 ). Clinical trial data from various studies support this approach. A meta-analysis using data from 58 randomized clinical trials found that combinations of some of these drugs (e.g., ARN inhibitor + β-blocker + MRA) provided incremental benefit in mortality and all-cause hospitalizations in patients with HFrEF compared with placebo; furthermore, the benefit appeared greater than single-drug class therapies versus placebo ( 50 ). Comparing data from three pivotal heart failure trials indirectly, Vaduganathan et al. ( 51 ) speculated that a combination of drugs from all four classes potentially reduces cardiovascular death and heart failure hospitalizations compared with conventional therapy with an ACE inhibitor or angiotensin receptor blocker (ARB) plus a β-blocker.

Introducing a Pillar Approach Hypothesis for the Treatment of CKD Associated With Type 2 Diabetes

One of the main treatment goals for patients with type 2 diabetes is to maintain effective glycemic control, which reduces the risk of developing or slows the progression of diabetes-related complications such as CVD and/or CKD. The focus on glycemic control in type 2 diabetes is noted in the ADA 2023, KDIGO, and NICE guidelines ( 12 , 45 , 52 ). As noted previously, glycemic control in type 2 diabetes requires significant lifestyle changes on the part of patients, as well as pharmacological management ( 45 , 46 ).

Pharmacological management of type 2 diabetes follows a linear approach, and the initial drug therapy or therapies used depends on factors such as whether the patient has established CKD or CVD and/or their risk of developing either or both of these conditions based on factors such as their age, pregnancy status, and number and type of comorbidities ( 6 , 53 , 54 ). However, the progressive nature of type 2 diabetes means that first-line drug therapy may only be appropriate for a short period of time because of eventual loss of glycemic control ( 12 , 45 ).

Glucose toxicity resulting from chronic hyperglycemia ( 55 ) and failure to successfully treat patients with type 2 diabetes to their prescribed metabolic targets increase their risk of long-term microvascular and macrovascular complications such as CKD and cardiovascular events. Thus, delay before advancing to the next step in the linear treatment approach is a concern.

Once a CKD diagnosis is made, preventing kidney disease progression and reducing its cardiovascular impact are the focus of therapy, which includes maintaining glycemic and blood pressure control. Using the linear approach, drugs with different mechanisms of action may be introduced and optimized or removed in a step-up or step-down fashion guided by factors such as kidney function testing, tolerability, efficacy, and blood glucose levels. Regular testing can detect early signs of kidney damage and can also inform available treatment options at early stages.

A guide to the frequency of monitoring based on eGFR and albuminuria was provided in the KDIGO 2012 guidelines ( Figure 1 ) ( 8 – 10 ). This guide may need to be adjusted according to an individual’s history and the underlying cause of kidney disease ( 8 , 9 ). However, the linear treatment approach in CKD introduces a delay between treatment steps because the time between kidney function tests, for example, may be several months, potentially allowing kidney disease to worsen given its progressive nature, particularly in patients with no or mild symptoms who may not seek medical help. For example, the nsMRA finerenone was approved in 2021 for the treatment of CKD associated with type 2 diabetes and has shown cardiorenal protective effects; however, this drug may be reserved by some health care professionals as a later-stage or second-line treatment option, so patients may not receive this drug until their kidney disease has progressed further (although this suggestion requires further exploring through real-world studies).

A pillar approach could bring together the main drug classes much earlier or simultaneously while still allowing for dose optimization, thereby removing the delay between steps that occurs with linear treatment. Thus, the pillar approach may be appropriate for chronic progressive diseases such as CKD, although clinical research is needed to test this hypothesis in CKD associated with type 2 diabetes. Although current treatment guidelines largely support a linear approach for CKD associated with type 2 diabetes, it is worth considering the feasibility of implementing a pillar approach instead. Hereafter, we explore this question further.

Linear Versus Hypothetical Pillar Approach for Treatment of CKD Associated With Type 2 Diabetes

Glycemic and blood pressure control in patients with ckd associated with type 2 diabetes (linear approach).

In the linear treatment approach to CKD associated with type 2 diabetes, a drug is initiated based on baseline A1C, blood pressure, and/or kidney function, followed by periodic monitoring of whether individualized targets expected from the drug’s action are achieved without intolerable side effects ( 6 , 12 ). If the targets are not met with the drug, then dose adjustments and/or the addition or substitution of different drugs may be needed ( 12 , 56 ). For example, for patients with type 2 diabetes, the ADA 2023 guidelines (Chapter 9) recommend using drugs that provide adequate efficacy to achieve and maintain glycemic goals, such as metformin or other drugs, including combination therapy. For patients taking the maximum tolerated dose of an ACE inhibitor or ARB, an SGLT2 inhibitor is recommended to reduce CKD progression, or a GLP-1 receptor agonist with proven CVD benefit in cases where SGLT2 inhibitors are contraindicated/not tolerated ( 45 ). Similarly, for blood pressure control, the ADA guidelines (Chapter 10) recommend an ACE inhibitor or ARB at the maximum tolerated dose indicated for patients with hypertension, diabetes, and albuminuria, with at least annual monitoring of albuminuria, eGFR, and serum potassium levels ( 6 ). If patients do not meet blood pressure targets, then addition of or change to a calcium channel blocker and/or diuretic may be considered ( 6 ). MRAs are recommended for patients who do not meet targets after receiving three classes of antihypertensive medications (including a diuretic) ( 6 ). In these linear treatment strategies, different therapies are given to a patient depending on the patient’s response to medications and/or the extent of CKD progression.

CKD associated with type 2 diabetes: pharmacological management (linear approach)

For patients with type 2 diabetes and CKD, both the ADA 2023 guidelines and the ADA/KDIGO consensus report recommend use of an SGLT2 inhibitor in patients with an eGFR ≥20 mL/min/1.73 m 2 (and ≥200 mg/g urinary albumin [4]) to reduce CKD progression and cardiovascular risk ( 4 , 13 ). In the ADA 2023 guidelines, an nsMRA (finerenone) is recommended for patients with CKD who are at increased risk for cardiovascular events or CKD progression (evidence grade A) ( 4 ). The ADA/KDIGO consensus report also recommends an nsMRA for patients with type 2 diabetes and an eGFR ≥25 mL/min/1.73 m 2 , normal serum potassium levels, and albuminuria ( 13 ).

CKD associated with type 2 diabetes: pharmacological management (hypothetical pillar approach)

In contrast to a linear approach, taking a pillar approach in CKD treatment would mean that drugs that may slow CKD progression would be introduced at an early disease stage (ideally at CKD diagnosis), ultimately reducing the risk of CKD progression to ESKD. A drug class that targets a specific biological pathway associated with diabetes- related complications, including CKD progression, could be regarded as one pillar in a multipillar treatment. Patients with type 2 diabetes, CKD, and an eGFR ≥30 mL/min/1.73 m 2 may be receiving metformin ( 12 ) and an ACE inhibitor or ARB if there is hypertension and albuminuria, although in the ADA 2023 guidelines, metformin is not regarded as the first-line treatment for blood glucose control ( 45 ). For example, as soon as patients with diabetes and hypertension have confirmed abnormal kidney function, they could receive finerenone and/or an SGLT2 inhibitor in addition to metformin (and/or another antihyperglycemic agent) and an ACE inhibitor/ARB, with the intension of limiting progression of CKD ( Figure 2 ). An integrated approach involving multiple risk parameters and scores could be used for monitoring the efficacy and safety of multiple drugs ( Figure 2 ). It should be noted that, in the KDIGO guidelines, the combination of low doses of metformin and an SGLT2 inhibitor is suggested for patients with type 2 diabetes and an eGFR ≥30 mL/min/1.73 m 2 as “a practical approach” due to different mechanisms of action between the two drug classes ( 12 ).

Hypothetical pillar approach to CKD management in patients with type 2 diabetes and hypertension.

Pros and cons of a pillar approach in CKD associated with type 2 diabetes

In the CKD treatment of patients with diabetes, potential advantages of using a pillar approach are to 1 ) simultaneously target multiple pathways that contribute to CKD progression, 2 ) reduce some safety concerns (e.g., hyperkalemia caused by MRAs), 3 ) reduce the overall treatment duration by reducing the need for assessment and evaluation of kidney function between steps of therapy (discussed previously), and 4 ) minimize risks of silent CKD progression, which may not be captured by single surrogate markers (discussed previously). Potential disadvantages of a pillar approach to CKD treatment are 1 ) lack of safety and efficacy data from dedicated multicombination drug trials in real-world settings, 2 ) potential use of unnecessary drugs, 3 ) pushback from clinicians who are familiar with and prefer the current conventional approach, 4 ) resistance from patients who may reject the idea of polytherapy, and 5 ) costs and limitations in access to simultaneous drug treatments.

Feasibility: A hypothetical model in CKD

The current lack of clinical trials to evaluate the effect of combination therapies versus conventional first-line drug therapies for CKD associated with type 2 diabetes (and hence the opportunity to demonstrate additive or synergistic benefits) makes assessing the feasibility of the pillar approach challenging. However, guidelines have provided recommendations regarding the use of certain drug combinations (although not a three- or four-pillar combination). The KDIGO 2022 guidelines suggest a combination of an SGLT2 inhibitor and metformin for patients with type 2 diabetes (eGFR ≥30 mL/min/1.73 m 2 ) but warn against combining an ACE inhibitor with an ARB (due to higher risk and marginal benefit) or combining an ACE inhibitor or ARB with a direct renin inhibitor due to safety concerns ( 12 ).

An nsMRA (finerenone) as a potential fourth pillar in CKD treatment

The potential inclusion of finerenone as a pillar in the treatment of CKD associated with type 2 diabetes was discussed previously. Here we give an overview of finerenone clinical trials.

Finerenone was first approved by the U.S. Food and Drug Administration (FDA) in 2021, which led to the eventual inclusion of this drug in the ADA and KDIGO guidelines as a therapeutic option for CKD associated with type 2 diabetes. The Finerenone in Reducing Kidney Failure and Disease Progression in Diabetic Kidney Disease (FIDELIO-DKD) ( 57 – 59 ) and Finerenone in Reducing Cardiovascular Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) ( 60 – 62 ) studies demonstrated reduced CKD progression and cardiovascular events and hospitalization for heart failure in patients with CKD associated with type 2 diabetes who were treated with finerenone. The first approval of finerenone was based on the results of FIDELIO-DKD, which showed a reduced risk of sustained eGFR decline, kidney failure, cardiovascular death, nonfatal myocardial infarction, and hospitalization for heart failure compared with placebo in adults with CKD associated with type 2 diabetes.

Because patients treated with finerenone in FIDELIO-DKD and FIGARO-DKD received other types of drugs at baseline and/or post-baseline, the results from these trials may provide insight for researchers assessing the feasibility of pillar therapy for CKD associated with type 2 diabetes. All randomized patients in the trials received an ACE inhibitor or ARB at the optimized dose (per manufacturer’s protocol) at baseline ( 57 , 61 ). In FIDELIO-DKD, 4.4 and 10.9% of patients treated with finerenone also received an SGLT2 inhibitor at baseline or at any time during treatment (baseline + post-baseline), respectively ( 57 , 63 ). Importantly, although SGLT2 inhibitor use did not affect the reduction in UACR and key secondary composite outcomes, hyperkalemia events were fewer with finerenone in the SGLT2 inhibitor group ( 63 ). A subgroup analysis of patients receiving finerenone with an SGLT2 inhibitor at baseline showed a 55% lower risk of hyperkalemia compared with the overall group (hazard ratio 0.45, 95% CI 0.27–0.75) ( 64 ). Also in FIDELIO-DKD, 6.7 and 13.3% of patients treated with finerenone received a GLP-1 receptor agonist at baseline and at any time during the treatment (baseline + post-baseline), respectively ( 57 , 61 ). However, a subgroup analysis of patients receiving finerenone with a GLP-1 receptor agonist demonstrated no additional benefit of the GLP-1 receptor agonist for the primary kidney or secondary cardiovascular outcomes in patients treated with finerenone ( 65 ).

Need for multi-agent combination studies to test the pillar approach hypothesis in CKD

Because the supporting data for the pillar approach in CKD associated with type 2 diabetes are based largely on subgroup analyses derived from large studies in which multiple agents were not initiated simultaneously, dedicated carefully designed combination studies are necessary to evaluate the feasibility of a pillar approach. CONFIDENCE is an ongoing, parallel-group, double-blind, three-arm phase 2 trial to assess the efficacy and safety of finerenone plus the SGLT2 inhibitor empagliflozin compared with finerenone or empagliflozin alone in patients with CKD associated with type 2 diabetes. The primary end point is change from baseline in UACR, and secondary end points include changes in UACR and eGFR, acute kidney injury, hyperkalemia, and hypoglycemia. It will be interesting to see what the combined effect of an SGLT2 inhibitor plus finerenone has on outcomes compared with either treatment alone. Further subgroup analyses from FIDELIO-DKD and FIGARO-DKD and real-world data, possibly using multiple-risk parameters and scores, may provide further insight into the feasibility of a pillar approach in the treatment of CKD associated with diabetes.

In this review, we discussed the existing linear and hypothetical pillar treatment approaches to CKD associated with type 2 diabetes, with close reference to the ADA 2023 guidelines, supported where appropriate by the KDIGO guidelines (representing a global approach to kidney disease) and NICE guidelines (representing a country-specific approach to CKD outside of the United States). By simultaneously targeting the multiple pathways involved in CKD progression, as well as cardiovascular events, a pillar approach could potentially bring an additive/synergistic benefit to patients in the treatment of CKD associated with type 2 diabetes and its comorbidities. FDA approval of the nsMRA finerenone and a revised label indication for the SGLT2 inhibitor dapagliflozin, both in 2021, have expanded treatment options for patients with CKD, enabling clinicians to consider the possibility of a pillar therapy approach. Although it is still hypothetical and more clinical and real-world studies are needed, a pillar approach, combined with proactive early detection and early referral when needed, could enable the risks of disease progression and cardiovascular events in CKD associated with type 2 diabetes to be reduced and the condition to be more efficiently managed moving forward. A summary of the main themes of this article is presented in Figure 3 .

Summary of the main themes and concepts covered in this article. T2D, type 2 diabetes.

Acknowledgments

Medical writing support was provided by Tomo Sawado, PhD, of Alligent – Envision Pharma Group and funded by Bayer Corporation. Envision Pharma Group’s services complied with international guidelines for Good Publication Practice (GPP4).

Duality of Interest

J.M. is a consultant and promotional speaker for Bayer, Boehringer Ingelheim, Eli Lilly, and Novo Nordisk; has conducted clinical research for Novo Nordisk; and is an advisory board member for Abbott, Bayer, Boehringer Ingelheim, Eli Lilly, Intarcia, Novo Nordisk, and Sanofi. S.D.-J. has led clinical trials for AstraZeneca, Bayer, Boehringer Ingelheim, and Novo Nordisk; has received fees from AstraZeneca, Bayer, Boehringer Ingelheim, Janssen, Merck, and Sanofi; holds equity interests in Aerami Therapeutics and Jana Care; and serves on the editorial boards of the American Journal of the Medical Sciences , BMJ Diabetes Research & Care , Experimental Biology & Medicine , Frontiers in Endocrinology , and Scientific Reports . V.F. has received research support (to his institution) or grants from Fractyl Health and Jaguar Gene Therapy; has received honoraria for consulting and lectures from Abbott, Asahi Kasei Pharma, AstraZeneca, Bayer, Novo Nordisk, and Sanofi; holds stock options with BRAVO4Health and Mellitus Health; has stock in Abbott and Amgen; and has a patent with BRAVO Risk Engine for Predicting Diabetes Complications (pending). J.J.N. has received consulting fees from Bayer, Novo Nordisk, and Sanofi and served on a speaker’s bureau for Dexcom. S.E.R. has received research funds (to her institution) from AstraZeneca and Bayer; is a member of a scientific advisory board for AstraZeneca, Bayer, and Teladoc; is president-elect of the National Kidney Foundation; and is an employee of Beth Israel Lahey Health.

Author Contributions

All authors contributed to writing and reviewing the manuscript. J.M. is the guarantor of this work and, as such, had full access to all the data reported and takes responsibility for the integrity of the article content.

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Evaluation of lipid profile, liver function enzymes, and trace elements in Iraqi diabetic nephropathy patients

• Published: 23 August 2024

Cite this article

• Mohammed H. Zaid 1 ,
• Falah S. Al-Fartusie 2 ,
• Yaghub Pazhang 1 &
• Safaa Kader   ORCID: orcid.org/0000-0002-1913-4688 3  

Diabetic nephropathy, a common complication of type 2 diabetes (T2DM), is associated with abnormal lipid profiles, liver dysfunction, and kidney impairment. However, research on its association with trace elements in Iraqi patients is limited. The objective of the present study is to evaluate the association between lipid profile, liver function, and trace elements in diabetic nephropathy (DN) patients. In this study, 120 individuals were selected. Sixty of these individuals were labeled as the DN patient group, and 60 individuals were labeled as the healthy control group. A flame atomic absorption spectrophotometer (FAAS) was utilized to assess the levels of zinc (Zn), copper (Cu), and magnesium (Mg), whereas a flameless atomic absorption (FAA) was used to assess manganese (Mn). A colorimetric method was used based on the protocols included in the leaflets by Spinreact kits to determine the levels of lipid profiles and liver function enzymes in the serum. The mean value of high-density lipoprotein (HDL) decreased significantly in the DN patient group compared to the control group ( p  < 0.001) while cholesterol and low-density lipoprotein (LDL) decreased insignificantly. Conversely, the mean value of triglycerides (TGs) increased significantly in patient group (( p  < 0.001) while very low-density lipoprotein (VLDL) increased insignificantly. On the other hand, the mean values of aspartate aminotransferase (AST), alanine transferase (ALT), alkaline phosphatase (ALP), and γ- glutamyl transferase (GGT) were significantly greater in DN patients compared to the healthy controls. Conversely, the mean values of total protein (TP) and albumin (Alb) were significantly lower in the DN patient group. In terms of trace elements, the mean values of Zn, Mg, and Mn were significantly lower in each of the patient groups compared to the healthy group. Conversely, a significant elevation in the means of Cu and Fe was observed in patients compared to the healthy group. Additionally, the findings revealed no association between BMI and lipid profile, liver enzymes, or trace elements. However, an association with age was limited to TGs, ALP, and GGT. The study’s results show that the DN patients have abnormalities in their serum trace element levels. This means that these elements could be valuable indicators for monitoring and assessing the progression of DN. Understanding the correlation between lipid profile, liver function, and trace elements could offer valuable insights for managing and preventing diabetic nephropathy. More extensive studies, including an additional group of DM patients without nephropathy complications, are required, and could be used in practice due to the progression of the disease.

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Acknowledgements

The authors would like to thank Urmia University, Urmia, Iran, for support.

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Al-Fartusie, Pazhang, and Kader both contributed to the study's conceptualization and design. Zaid prepared the materials, ran the experimental part, and collected the data, while Al-Fartusie, Pazhang, and Kader analyzed the results. The drafts of the manuscript were written by Kader, while all the other authors commented on multiple versions of the manuscript. The final version of the manuscript was read and approved by all of the authors.

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Zaid, M.H., Al-Fartusie, F.S., Pazhang, Y. et al. Evaluation of lipid profile, liver function enzymes, and trace elements in Iraqi diabetic nephropathy patients. Biometals (2024). https://doi.org/10.1007/s10534-024-00626-w

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Hyperglycemia induced cathepsin L maturation linked to diabetic comorbidities and COVID-19 mortality

Affiliations.

• 1 Department of Endocrinology, Beijing Diabetes Institute, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
• 2 Department of Respiratory and Critical Care Medicine, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
• 3 Department of Science and Technology, Beijing Youan Hospital, Capital Medical University, Beijing, China.
• 4 Division of HIV/AIDS and Sex-Transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC), Beijing, China, Beijing, China.
• 5 Laboratory for Clinical Medicine, Capital Medical University, Beijing, China.
• PMID: 39150053
• PMCID: PMC11329274
• DOI: 10.7554/eLife.92826

Diabetes, a prevalent chronic condition, significantly increases the risk of mortality from COVID-19, yet the underlying mechanisms remain elusive. Emerging evidence implicates Cathepsin L (CTSL) in diabetic complications, including nephropathy and retinopathy. Our previous research identified CTSL as a pivotal protease promoting SARS-CoV-2 infection. Here, we demonstrate elevated blood CTSL levels in individuals with diabetes, facilitating SARS-CoV-2 infection. Chronic hyperglycemia correlates positively with CTSL concentration and activity in diabetic patients, while acute hyperglycemia augments CTSL activity in healthy individuals. In vitro studies reveal high glucose, but not insulin, promotes SARS-CoV-2 infection in wild-type cells, with CTSL knockout cells displaying reduced susceptibility. Utilizing lung tissue samples from diabetic and non-diabetic patients, alongside Lepr db/db mice and Lepr db/+ mice, we illustrate increased CTSL activity in both humans and mice under diabetic conditions. Mechanistically, high glucose levels promote CTSL maturation and translocation from the endoplasmic reticulum (ER) to the lysosome via the ER-Golgi-lysosome axis. Our findings underscore the pivotal role of hyperglycemia-induced CTSL maturation in diabetic comorbidities and complications.

Keywords: biochemistry; chemical biology; diabetic mice; hepatoma cell line; human; human blood sample; infectious disease; microbiology; mouse.

Plain language summary

People with diabetes are at greater risk of developing severe COVID-19 and dying from the illness, which is caused by a virus known as SARS-CoV-2. The high blood sugar levels associated with diabetes appear to be a contributing factor to this heightened risk. However, diabetes is a complex condition encompassing a range of metabolic disorders, and it is therefore likely that other factors may contribute. Previous research identified a link between an enzyme called cathepsin L and more severe COVID-19 in people with diabetes. Elevated cathepsin L levels are known to contribute to diabetes complications, such as kidney damage and vision loss. It has also been shown that cathepsin L helps SARS-CoV-2 to enter and infect cells. This raised the question of whether elevated cathepsin L is responsible for the increased COVID-19 vulnerability in patients with diabetes. To investigate, He, Zhao et al. monitored disease severity and cathepsin L levels in patients with COVID-19. This confirmed that people with diabetes had more severe COVID-19 and that higher levels of cathepsin L are linked to more severe disease. Analysis also revealed that cathepsin L activity increases as blood glucose levels increase. In laboratory experiments, cells exposed to glucose or fluid from the blood of people with diabetes were more easily infected with SARS-CoV-2, with cells genetically modified to lack cathepsin L being more resistant to infection. Further experiments revealed this was due to glucose promoting maturation and migration of cathepsin L in the cells. The findings of He, Zhao et al. help to explain why people with diabetes are more likely to develop severe or fatal COVID-19. Therefore, controlling blood glucose levels in people with diabetes may help to prevent or reduce the severity of the disease. Additionally, therapies targeting cathepsin L could also potentially help to treat COVID-19, especially in patients with diabetes, although more research is needed to develop and test these treatments.

© 2024, He, Zhao et al.

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Conflict of interest statement

QH, MZ, ML, XL, JJ, YF, LZ, WH, FY, JY No competing interests declared

Figure 1.. Disease severity and CTSL levels…

Figure 1.. Disease severity and CTSL levels in COVID-19 patients with or without diabetes.

Figure 2.. Impact of chronic and acute…

Figure 2.. Impact of chronic and acute hyperglycemia on CTSL concentration and activity.

Figure 3.. Hyperglycemia enhances SARS-CoV-2 infection through…

Figure 3.. Hyperglycemia enhances SARS-CoV-2 infection through CTSL.

Huh7 cells were infected with SARS-CoV-2 pseudovirus.…

Figure 4.. Elevation of glucose levels enhance…

Figure 4.. Elevation of glucose levels enhance CTSL activity.

Effects of high glucose levels on…

Figure 5.. High glucose levels stimulate CTSL…

Figure 5.. High glucose levels stimulate CTSL maturation.

( a ) Schematic of the CTSL…

Figure 5—figure supplement 1.. CTSL mRNA levels…

Figure 5—figure supplement 1.. CTSL mRNA levels remain unchanged under different glucose conditions.

Figure 5—figure supplement 2.. CTSL protein expression…

Figure 5—figure supplement 2.. CTSL protein expression in Huh7 cells under different D-glucose concentrations.

Figure 6.. High glucose promotes CTSL translocation…

Figure 6.. High glucose promotes CTSL translocation from endoplasmic reticulum to lysosome and enhances SARS-CoV-2…

Figure 6—figure supplement 1.. Immunofluorescent staining of…

Figure 6—figure supplement 1.. Immunofluorescent staining of organelle markers representing the endoplasmic reticulum (ER), Golgi…

Figure 6—figure supplement 2.. Immunofluorescent staining of…

Figure 6—figure supplement 2.. Immunofluorescent staining of CTSL in Huh7 cells.

( a ) CTSL…

Author response image 1.

Author response image 2.

Author response image 3.

Author response image 4.

• doi: 10.1101/2023.10.15.23297013
• doi: 10.7554/eLife.92826.1
• doi: 10.7554/eLife.92826.2

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Mental health and chronic diabetes complications strongly linked both ways

Researchers say there is a need for better screening of both risk factors

Heart attack, stroke, nerve damage.

These are just some of the complications for which millions of Americans with diabetes are at greater risk.

When a person has any of these chronic diabetes complications, they are more likely to have a mental health disorder, and vice versa , according to a University of Michigan-led study.

That is, the relationship goes both ways: having a mental health condition also increases the risk of developing chronic complications of diabetes.

“We wanted to see if chronic diabetes complications led to mental health disorders or if mental health disorders led to those diabetes complications – but we found that both relationships are true,” said Brian Callaghan, M.D., M.S., senior author and the Eva L. Feldman, M.D., Ph.D., Professor of Neurology at U-M Medical School.

“The findings highlight a need for clinicians to actively screen for mental health disorders in patients with diabetes in addition to screening for chronic complications, which is the recommended standard of care in diabetes.”

Three-times greater risk The research team, led by Michigan Medicine and the Department of Biostatistics at the U-M School of Public Health, examined insurance claims data from over 500,000 individuals with type 1 or type 2 diabetes and 350,000 people without diabetes.

Results published in Diabetes Care reveal that people with chronic diabetes complications had up to a three-times greater risk of having a mental health condition, such as anxiety or depression. This effect increased as adults got older.

Those with mental health disorders were up to 2.5 times more likely to experience sustained diabetes complications.

In adults younger than 60 years old, having type 1 diabetes was more associated with chronic complications. People with the more common type 2 diabetes were more likely to experience mental health difficulties.

A possible reason for this bi-directional relationship, researchers say, may be that having a diabetes complication or mental health condition has direct effects on developing the other complication.

“For instance, a stroke causes detrimental effects on the brain, which may directly lead to depression,” Callaghan said.

“And having a mental health condition and diabetes may affect a person’s self-management of their condition — like poor glycemic control or not taking medications — which, in turn, may increase their risk of diabetes complications.”

Common risk factors The relationship may also be less direct. Diabetes complications and mental health conditions share common risk factors; obesity, issues with glycemic control and social determinants of health can all increase the likelihood of developing both comorbidities.

“Most likely, a combination of direct and indirect effects and shared risk factors drive the association we are seeing,” said first author Maya Watanabe, M.S., a biostatistician at the Harvard T.H. Chan School of Public Health and former graduate student research assistant at U-M.  

“Diabetes care providers may be able to simultaneously prevent the risk of multiple complications by providing interventions to treat these shared risk factors.”

In any 18-month period, up to 50% of people with diabetes may have feelings of distress related to their condition, according to the CDC .

Several national diabetes centers have implemented depression and distress screening for their patients, but there is no universal screening process for mental health in diabetes care.

The researchers note that additional resources will be needed to screen and manage mental health conditions, as many clinicians who manage diabetes lack specific training to adequately identify and treat them.

Mental health care This echoes a statement from the U.S. Preventive Service Task Force, which said that if patients who screen positive for mental health conditions must be “appropriately diagnosed and treated with evidence based care or referred to a setting that can provide the necessary care.”

“Primary care providers and endocrinologists are already overworked; therefore, systems of care need to be in place to help provide mental health care when needed,” said co-author  Eva Feldman, M.D., Ph.D., Director of the ALS Center of Excellence and James W. Albers Distinguished University Professor at U-M.

“These systems should include mental health screening, easily accessible insurance coverage for mental health services and both physician and patient education programs. Action is needed, and our new research provides further evidence that this action needs to occur now.”

Additional authors: Mousumi Banerjee, Ph.D., Kara Mizokami-Stout, M.D., M.S., Lynn Ang, MBBS, Joyce M. Lee, M.D., M.P.H., Rodica Pop-Busui, M.D., Ph.D., all of University of Michigan, Evan L. Reynolds, Ph.D., of Michigan State University, Morten Charles, M.D., Ph.D., of Aarhus University, and Dana Albright, Ph.D., of Parkview Health.

Funding: This study was funded by JDRF.

Paper cited: “Bidirectional Associations Between Mental Health Disorders and Chronic Diabetic Complications in Individuals With Type 1 or Type 2 Diabetes,” Diabetes Care. DOI: 10.2337/dc24-0818

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Mendelian randomization based on immune cells in diabetic nephropathy

1 Department of Endocrinology, Zhaotong Hospital of Traditional Chinese Medicine, Zhaotong, Yunnan, China

Hengyan Zhang

2 Clinical Medical College, Yunnan University of Chinese Medicine, Kunming, Yunnan, China

Changxing Huang

Yangwen liu.

Jiayan Zhang, Los Angeles, United States

Hanxiao Sun, University of Texas Health Science Center at Houston, United States

Associated Data

The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author/s.

DKD, a leading cause of chronic kidney and end-stage renal disease, lacks robust immunological research. Recent GWAS utilizing SNPs and CNVs has shed light on immune mechanisms of kidney diseases. However, DKD’s immunological basis remains elusive. Our goal is to unravel cause-effect relationships between immune cells and DKD using Mendelian randomization.

Methodology

We analyzed FinnGen data (1032 DKD cases, 451,248 controls) with 731 immunocyte GWAS summaries (MP=32, MFI=389, AC=118, RC=192). We employed forward and reverse Mendelian randomization to explore causal links between immune cell traits and DKD. Sensitivity analysis ensured robustness, heterogeneity checks, and FDR correction minimized false positives.

Our study explored the causal link between diabetic nephropathy (DKD) and immunophenotypes using two-sample Mendelian Randomization (MR) with IVW. Nine immunophenotypes were significantly associated with DKD at p<0.05 after FDR correction. Elevated CD24, CD3 in Treg subsets, CD39+ CD4+, and CD33− HLA DR− AC correlated positively with DKD risk, while CD27 in B cells and SSC−A in CD4+ inversely correlated. Notably, while none showed significant protection, further research on immune cells’ role in DKD may provide valuable insights.

The results of this study show that the immune cells are closely related to DKD, which may be helpful in the future clinical study.

Introduction

Diabetes is a major public health problem. Diabetes Renal Disease (DKD), which is a more general diagnosis than DN, is the leading cause of CKD and end stage renal disease in the United States ( 1 ). About 40% of people with diabetes develop kidney disease (DKD). DKD is characterized by hyperfiltration of glomerular, progressive albuminuria, reduced glomerular filtration rate (GFR), and eventually end-stage renal disease (ESRD). Diabetes-Related metabolic changes result in glomerulonephritis, glomerulonephritis, tubulointerstitial inflammation and fibrosis ( 2 ). Prevention and treatment of chronic renal disease (CKD) in patients with diabetes is now the main goal of their overall treatment. Intensified treatment in patients with diabetes involves controlling blood glucose and blood pressure and blocking the renin-angiotensin-aldosterone system; this will reduce the occurrence and delay the development of renal disease (DKD).

In fact, the significant decline in the incidence of DKD and improvement in patient outcomes over the past 30 years are mainly attributed to improvements in diabetes care. However, the need for innovative treatment strategies to prevent, halt, treat, and reverse DKD remains unmet ( 3 ). It significantly impacts an individual’s overall health and daily functioning, which is also the focus of our research.

Recent studies have uncovered a complicated link between the immune system and renal disease in diabetes. Evidence from both clinical and experimental studies suggests that several innate immune pathways may be involved in the development and progression of DM (DKD). Toll-like receptors detect endogenous danger-associated molecular patterns that are produced in diabetic patients and induce sterile tubulointerstitial inflammation via NF-κB signaling ( 4 ). The NLRP3 inflammasome is associated with the induction of IL 1β and IL-18 in diabetic renal metabolism and the activation of proinflammatory cascades ( 5 ). In DKD, the kallikrein-kinin system promotes inflammation by producing bradykinin and activating bradykinin receptors, whereas thrombin, which activates protease-activated receptors on kidney cells, is involved in inflammation and fibrosis in the kidney ( 6 ). However, to date, only a few risk loci for diabetic kidney disease have been identified. In the past decade, genome-wide association studies (GWAS) have emerged as a powerful tool for identifying genetic risk factors for diabetic kidney disease (DKD). In recent years, GWAS have gained access to larger numbers of participants, thus enhancing the statistical power to detect more genetic risk factors ( 7 ). The objective of the research is also to find safer and more effective methods by means of Pharmacogenetics (PGP) to deal with the high non-response or partial response to existing medicines in patients with DM ( 8 ). Genome-Wide Association Studies (GWAS) are essential for the analysis of genetic variations across the whole genome in large groups, to identify promising genetic sites and pathways, and to improve our understanding of the complex genetic factors that underlie possible diseases ( 9 ). This will also help us to explore the relationship between susceptibility, inflammation, and genetics in patients with diabetes mellitus. We have conducted profound discussions on the relationship between immunity and diabetic kidney disease (DKD), and found that studies have revealed the critical role of Th17/Treg cell imbalance in DKD. Dapagliflozin (Dap) reverses this imbalance by inhibiting SGK1, leading to a decrease in Th17 cells and an increase in Treg cells. Consequently, it improves DKD symptoms such as proteinuria and fibrosis independently of glycemic control, indicating the potential of Dap in the prevention of DKD ( 10 ). Additional research has comprehensively analyzed the macrophage transcriptomic profile in the early stages of DKD, revealing an increase in renal resident and infiltrating macrophage subsets, as well as a subgroup-specific enhancement in the expression of proinflammatory and anti-inflammatory genes. The changes in macrophage polarization status are consistent with the continuity of activation and differentiation states, tending towards an undifferentiated phenotype but with an increase in the M1-like inflammatory phenotype over time. Validation of the mouse studies through RNAseq and immunostaining further elucidates the dynamic changes in macrophage phenotypes in DKD, emphasizing their crucial role in disease progression ( 11 ). Additional research has comprehensively analyzed the macrophage transcriptomic profile in the early stages of DKD, revealing an increase in renal resident and infiltrating macrophage subsets, as well as a subgroup-specific enhancement in the expression of proinflammatory and anti-inflammatory genes. The changes in macrophage polarization status are consistent with the continuity of activation and differentiation states, tending towards an undifferentiated phenotype but with an increase in the M1-like inflammatory phenotype over time. Validation of the mouse studies through RNAseq and immunostaining further elucidates the dynamic changes in macrophage phenotypes in DKD, emphasizing their crucial role in disease progression ( 12 ).

Mendelian randomization (MR) is a statistical approach primarily used to infer epidemiological causality based on Mendelian genetic principles ( 13 ). In the MR method, ensuring the logical order of causality is crucial. Previous observational studies have shown some association between immune cell properties and DM, which supports the hypothesis that they are related ( 14 ). DKD and immune system interactions are multifaceted, with potential reciprocal influences. For instance, DKD can induce immune responses that further exacerbate kidney damage, while immune dysregulation can drive the initiation and progression of DKD. To address these complexities between them, we selected bidirectional Mendelian Randomization tests rather than conventional or reverse MR approaches to investigate the cause and effect of immune cell characteristics and renal disease in DM ( 15 ). Conventional MR focuses solely on the causal effect of an exposure on an outcome, while reverse MR examines the effect of the outcome on the exposure. Bidirectional MR, on the other hand, allows us to simultaneously explore both directions, providing a clearer picture of the causal pathways involved. This is particularly important for conditions like DKD, where causality can flow in both directions. Furthermore, bidirectional MR ensures that we are not overlooking important causal effects in either direction, which could lead to incomplete or misleading conclusions.

Materials and methods

Study design.

In this paper, we analyzed the cause and effect of 731 immunocytes and diabetic nephropathy by means of Mendelian randomization (MR). MR utilizes genetic variations as proxies for risk and requires validating instrumental variables (IVs) that satisfy three key assumptions for causal inference: (1) exposure has a direct relationship with genetic variation; (2) there is no genetic association between exposure and outcome, which is a potential confounder; (3) no genetic effect on the outcome is produced by non-exposure pathways (show in Figure 1 ).

Overview of this bidirectional MR study design.

Sources of genome-wide association studies data encompassing immunity-related traits

All immunological characteristics in the GWAS catalogue, ranging from GCST0001391 to GCST0002121, are easily available ( 16 ). This GWAS included 3 757 European persons who did not overlap. About 22 million single nucleotide polymorphisms (SNPs) were estimated and statistically analyzed by means of a high density array based on a Sardinian sequence reference panel, taking into account the covariates of age, age, and gender. A total of 731 immunological phenotypes were examined, including 192 subtypes of RC, 32 subtypes of morphology (MP), 118 subtypes of absolute cell count (AC), and median fluorescence intensity (MFI) representing 389 surface antigen levels. In particular, the MP characteristics included CDC and TBNK panels, whereas the characteristics of MFI, RC and AC included B-cells, CDC, T-cell maturation, myeloid cells, monocyte, and TBNK (T-cells, B-cells, and naturally killer proteins).

Analysis of data sources from the genome-wide association study for diabetic kidney disease

Aggregated Diabetic Kidney Disease GWAS (DKD) statistics are available from FinnGen ( https://www.finngen.fi/en ). A total of 452280 samples were included in this study (Ncase = 1032, Ncontrol = 451,248), and more than 500,000 DKD phenotypes were included in the GWAS analysis, which identified over 20 million single nucleotide polymorphisms (SNPs).

Selection of instrumental variables

We employed a selectively chosen tool variable (IVs), with a linkage disequilibrium (LD) r2 threshold of less than 0.1 and a distance of 500 kb, to refine these SNPs, aiming to reduce collinearity and confounding bias, and thereby improve the accuracy and reliability of causal inference analysis. The 1000 Genomes Project served as the reference panel for calculating LD r2. A significance threshold of 5×10-8 was adopted for the new DKD analysis, which conformed to the accepted standards in genetic research. The intravenous injection intensity was evaluated to mitigate potential weak instrument bias. The F-statistic was calculated to assess the strength of the instrumental variables. The length of the instrument variables (IVs) for the immune phenotypes ranged from 3 to 1643, with an average explanatory power of 0.137% (ranging from 0.009% to 0.995%) for the differences in relevant immune characteristics.

Statistical analysis

We used R Version 4.4 ( http://www.Rproject.org ) in all of our studies. In order to specifically assess the causal association of 731 immunophenotypes with Diabetic Kidney Disease (DKD), we used the clumping procedure in PLINK package (version v1.90) to prune these SNPs and screening instrumental variables ( 17 ). Mendelian Randomization package (version 0.4.3) was used to perform median weighted analysis ( 18 ), pattern-weighted analysis ( 19 ) and Inverse Variance Weighted Analysis (IVW) ( 20 ). The Cochran Q statistic and its p-value (IV) were used for the assessment of the instrument heterogeneity among the variables, and the MR-Egger method was incorporated for the detection of horizontal pleiotropy, represented by a significant intercept term ( 21 ). In addition, using the MR-PRESSO package ( 22 ), we used MR-PRESSO, a robust MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) technique to detect and remove horizontal pleiotropy outliers that may significantly affect the estimation results. After these SNPs were deleted ( 19 ), the IVW analysis was re-performed. In addition, we searched the Phenoscanner V2 web site for SNPs showing suggestive associations (P < 10-5) ( http://www.phenoscanner.medschl.cam.ac.uk/ ) ( 23 ). Finally, funnel plots were used to test the correlation and heterogeneity, scatter plots were used to detect the outliers.

Exploring the causal relationship between diabetic nephropathy and immunophenotypes

In exploring the causal effects of diabetic nephropathy on immunophenotypes, we employed the IVW (inverse variance weighted) method as the primary approach in a two-sample Mendelian Randomization (MR) analysis. Despite applying multiple testing corrections via the False Discovery Rate (FDR) method, we detected nine suggestive immunophenotypes at a significance level of 0.05: four in the CD3 on CM CD4+ panel, three in the CD27 on memory B cell panel, three in the CD3 on secreting Treg panel, three in the SSC−A on CD4+ panel, two in the CD3 on CD39+ CD4+ panel, one in the CD28+ CD45RA+ CD8br %T cell panel, one in the CD33− HLA DR− AC panel, one in the CD3 on activated & secreting Treg panel, and one in the CD24 on switched memory panel.

Our findings suggest that the pathogenesis of diabetic kidney disease (DKD) is associated with increased levels of CD24 (OR=1.09, 95% CI=1.03-1.16, p=0.005), CD3 on activated & secreting Treg (OR=1.12, 95% CI=1.03-1.22, p=0.010), CD3 on CD39+ CD4+ (OR=1.11, 95% CI=1.03-1.19, p=0.006), CD3 on CM CD4+ (OR=1.11, 95% CI=1.03-1.20, p=0.007), CD3 on secreting Treg (OR=1.14, 95% CI=1.06-1.23, p<0.001), and CD33− HLA DR− AC (OR=1.16, 95% CI=1.06-1.28, p=0.002). Our study also revealed that diabetic kidney disease (DKD) is associated with decreased levels of CD27 on memory B cells (OR=0.91, 95% CI=0.86-0.97, p=0.006) and SSC−A on CD4+ cells (OR=0.81, 95% CI=0.73-0.91, p<0.001) ( Figure 2 ). Finally, The scatter plots showed minimal influence of outliers on the data, but the funnel plots showed high correlation and no heterogeneity.

Forest plots showed the causal relations between DKD and immune cell traits.

Examination of the causal relation of immunophenotypes on diabetic kidney disease

After FDR correction (FDR<0.05), we found that nine immunophenotypes did not exhibit significant protective effects against diabetic kidney disease (DKD). Among them CD24 (OR=1.02, 95% CI=0.96-1.09, p=0.446), CD3 on activated & secreting Treg (OR=0.97, 95% CI=0.91-1.02, p=0.231), CD3 on CD39+ CD4+ (OR=0.98, 95% CI=0.92-1.04, p=0.446), CD3 on CM CD4+ (OR=1.00, 95% CI=0.94-1.06, p=0.961), CD3 on secreting Treg (OR=0.97, 95% CI=0.92-1.03, p=0.332), CD33− HLA DR− AC (OR=1.03 95% CI=0.95-1.12, p=0.482), CD27 on memory B cells (OR=1.03, 95% CI=0.97-1.09, p=0.317) and SSC−A on CD4+ cells (OR=1.01, 95% CI=0.95-1.07, p=0.726). In addition, the MR-Egger intercept and the overall MR-PRESSO test ruled out the possibility of horizontal pleiotropic effects. The sensitivity analysis provided complete data confirming the strength of the established causality ( Figure 3 ).Finally, The scatter plots showed minimal influence of outliers on the data, but the funnel plots showed high correlation and no heterogeneity.

Forest plots showed the causal associations between immune cell traits and DKD by using different methods.

Disscussion

Based on a large number of publicly available genetic data, we examined the cause and effect of the disease in 731 immune cells. This is, so far, the only Mendelian randomization study that has investigated a causal relationship between multiple immune phenotypes and DM. Four classes of immunity (MFI, RC, AC and MP) were included in the study. Among them, 9 of the immunological phenotypes demonstrated a causal effect by Mendelian randomization, and one of them showed a strong causal relationship with DM.

Our research indicates a correlation between an increased percentage of CD24 cells and a heightened risk of diabetic kidney disease (DKD). CD24, a small glycosylphosphatidylinositol (GPI)-anchored glycoprotein, is broadly expressed in various cell types. Because of the differences in glycosylation, CD24 on the cell surface has been shown to interact with a variety of receptors to mediate multiple physiological functions ( 24 ). In particular, the inactivation of CD24-Siglec-E pathway may worsen the condition, whereas CD24Fc therapy may alleviate metabolic disturbances caused by diet, including obesity, dyslipidemia, insulin resistance, and nonalcoholic steatohepatitis (NASH).Mechanistically, Siglec-E’s sialic acid-dependent recognition of CD24 induces the recruitment of SHP-1, which in turn suppresses metabolic inflammation and prevents metabolic syndrome ( 25 ). While the use of CD24 as a target of immune checkpoint for cancer immunotherapy is still in its infancy, clinical trials have shown promising results. Monoclonal antibodies targeting CD24 have been found to possess excellent tolerability and safety profiles. In addition, preclinical research is exploring the use of CAR T cells, antibody drug conjugates, and gene therapy to target CD24 and strengthen the immune response to cancer ( 26 ).

Immunological memory can protect the human body from reinfection with previously recognized pathogens. This memory includes the maintenance of durable serum antibody titers provided by long-lived plasma cells, as well as memory T and B cells, which are supported by other cells. Memory B cells are the primary precursor cells for new plasma cells during secondary infections. CD27 is one of the most commonly used markers to define human memory B cells ( 27 ). Costimulation of CD8 T cells by CD27 in mice may promote immune activation and enhance primary, secondary, memory, and recall responses to viral infection ( 28 ). These research findings have provided new insights for our study on the association between diabetic kidney disease and CD27 ( 29 ).

Previous research has shown that there is a significant causal relationship between several immunological mediators and GDM (GDM). After FDR detection, CD127 on CD28 + CD45RA + CD8br and CD19 on PB/PC have been demonstrated to reduce the effects of GDM ( 30 ). However, the role of CD28+ CD45RA+ CD8br %T cells in diabetic kidney disease (DKD) has not yet been reported in research. Previous studies have found that CD3 is involved in the pathogenesis of diabetic chronic kidney disease (CKD) ( 31 ). However, research on the specific mechanism between diabetic nephropathy and CD3 has yet to be found.

The association between HLA-DR (human leukocyte antigen-DR) and diabetic nephropathy has attracted considerable attention. However, according to an early study, there is no direct correlation between HLA-DR and diabetic nephropathy ( 32 ). However, there are also studies indicating that diabetic end-stage renal disease (DESRD) in young AB subjects with type 2 diabetes mellitus (T2DM) has a genetic basis related to HLA, which aligns with our research findings ( 33 ). The identification of specific cell subsets is particularly crucial for immune profiling analysis, as abnormal DNA methylation in peripheral immune cells contributes to the progression of diabetic kidney disease (DKD) ( 34 ).

In this study, we used a two-sample Mendelian randomization analysis, using data from a large population of about 452280 individuals, ensuring significant statistical power. The results of the study were based on the genetic instrumental variables, and a variety of robust Mendelian randomization techniques were used to analyze the causal relationship between the two groups. In addition, to control for false positive results in multi-hypothesis testing, we used the FDR (False Discovery Rate) to control the statistical bias caused by multiple comparisons.

However, this study indeed has some shortcomings. Firstly, even after several sensitivity studies, a comprehensive assessment of horizontal pleiotropy remains difficult to achieve. Second, the lack of data at the individual level made it impossible to conduct a stratified population analysis. Third, reliance on European databases limits the generalization of the results to other nationalities. Finally, the flexible criteria used in this study might have resulted in a higher rate of false positives, but they also allowed for a more comprehensive assessment of the strong link between immunity and DM. In general, the next step of the study will be to conduct randomized controlled trials in DM to minimize the potential effect of confounding factors and achieve a higher degree of causality.

In summary, our comprehensive bidirectional MR analysis has revealed the causal links between various immunophenotypes and diabetic kidney disease (DKD), shedding light on the intricate web of relationships between DKD and the immune system. Furthermore, our study has successfully mitigated the impact of reverse causality, other variables, and other inevitable confounding factors, offering researchers a fresh perspective to delve into the biological underpinnings of DKD and potentially paving the way for early intervention and treatment strategies.

Data availability statement

Author contributions.

YZ: Writing – original draft. HZ: Data curation, Writing – review & editing. HY: Conceptualization, Writing – review & editing. CH: Methodology, Resources, Software, Writing – original draft. YL: Software, Writing – original draft.

Funding Statement

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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