Diabetic kidney disease is the leading cause of kidney failure worldwide; in the USA, it accounts for over 50% of individuals entering dialysis or transplant programmes. Unlike other complications of diabetes, the prevalence of diabetic kidney disease has failed to decline over the past 30 years. Hyperglycaemia is the primary aetiological factor responsible for the development of diabetic kidney disease. Once hyperglycaemia becomes established, multiple pathophysiological disturbances, including hypertension, altered tubuloglomerular feedback, renal hypoxia, lipotoxicity, podocyte injury, inflammation, mitochondrial dysfunction, impaired autophagy and increased activity of the sodium–hydrogen exchanger, contribute to progressive glomerular sclerosis and the decline in glomerular filtration rate. The quantitative contribution of each of these abnormalities to the progression of diabetic kidney disease, as well as their role in type 1 and type 2 diabetes mellitus, remains to be determined. Sodium–glucose co-transporter 2 (SGLT2) inhibitors have a beneficial impact on many of these pathophysiological abnormalities; however, as several pathophysiological disturbances contribute to the onset and progression of diabetic kidney disease, multiple agents used in combination will likely be required to slow the progression of disease effectively. Multiple pathophysiological disturbances contribute to the onset and progression of diabetic kidney disease (DKD). This Review describes these pathogenic processes and discusses the ability of sodium–glucose co-transporter 2 (SGLT2) inhibitors to correct or improve many of these processes, which are likely to underlie the ability of these agents to slow progression of established diabetic kidney disease.

http://www-nature-com-443.webvpn.bjmu.tsg211.com/articles/s41581-021-00393-8.pdf

Pathophysiology of diabetic kidney disease: impact of SGLT2 inhibitors.

Introduction: Diabetic kidney disease (DKD) is a major cause of morbidity and mortality in diabetes and is the most common cause of proteinuric and non-proteinuric forms of end-stage renal disease (ESRD). Control of risk factors such as blood glucose and blood pressure is not always achievable or effective. Significant research efforts have attempted to understand the pathophysiology of DKD and develop new therapies. Areas covered: We review DKD pathophysiology in the context of existing and emerging therapies that affect hemodynamic and metabolic pathways. Renin-angiotensin system (RAS) inhibition has become standard care. Recent evidence for renoprotective activity of SGLT2 inhibitors and GLP-1 agonists is an exciting step forward while endothelin receptor blockade shows promise. Multiple metabolic pathways of DKD have been evaluated with varying success; including mitochondrial function, reactive oxygen species, NADPH oxidase (NOX), transcription factors (NF-B and Nrf2), advanced glycation, protein kinase C (PKC), aldose reductase, JAK-STAT, autophagy, apoptosis-signaling kinase 1 (ASK1), fibrosis and epigenetics. Expert opinion: There have been major advances in the understanding and treatment of DKD. SGLT2i and GLP-1 agonists have demonstrated renoprotection, with novel therapies under evaluation. Addressing the interaction between hemodynamic and metabolic pathways may help achieve prevention, attenuation or even reversal of DKD.

Diabetic nephropathy: an insight into molecular mechanisms and emerging therapies

In recent years, osteosarcoma survival rates have failed to improve significantly with conventional treatment modalities because of the development of chemotherapeutic resistance. The human breast cancer resistance protein/ATP binding cassette subfamily G member 2 (BCRP/ABCG2), a member of the ATP-binding cassette family, uses ATP hydrolysis to expel xenobiotics and chemotherapeutics from cells. CCN family member 2 (CCN2) is a secreted protein that modulates the biological function of cancer cells, enhanced ABCG2 protein expression and activation in this study via the α6β1 integrin receptor and increased osteosarcoma cell viability. CCN2 treatment downregulated miR-519d expression, which promoted ABCG2 expression. In a mouse xenograft model, knockdown of CCN2 expression increased the therapeutic effect of doxorubicin, which was reversed by ABCG2 overexpression. Our data show that CCN2 increases ABCG2 expression and promotes drug resistance through the α6β1 integrin receptor, whereas CCN2 downregulates miR-519d. CCN2 inhibition may represent a new therapeutic concept in osteosarcoma.

CCN2 promotes drug resistance in osteosarcoma by enhancing ABCG2 expression.

Background: Understanding how socioeconomic events influence cause-specific mortality is essential for optimizing disease-control strategies. We characterized long-term trends in cause-specific mortality in a stable population from a very large urban centre. Methods: We derived population data from 1974 to 2015 on vital status, demographics and causes of death from the death registration system in Yangpu District, Shanghai, China. We examined temporal trends in mortality and assessed the effects of age, period and birth cohort. Results: Over 41 879 864 person-years of follow-up, we analyzed 290 332 deaths: 3.80% from communicable conditions (group 1), 86.50% from noncommunicable diseases (group 2), and 5.56% from injuries (group 3). Age-standardized mortality decreased after 1988 for group 1 (average annual percentage change [AAPC] −6.7, 95% confidence interval [CI] −9.3 to −4.1), after 1995 for group 2 (AAPC −2.9, 95% CI −3.5 to −2.3), and after 1994 for group 3 (AAPC −5.4, 95% CI −6.3 to −4.5), after improvements in public health and clinical service infrastructure and the removal of polluting industries during the 1980s. We observed increased mortality from group 2 and group 3 causes in those born between 1955 and 1965, a period that included the Great Chinese Famine. Cause-specific mortality risks increased in those born after 1949 for cancer and diabetes only. Interpretation: Birth cohorts exposed to extreme starvation in early life had increased premature cause-specific mortality in later life. Decreased cause-specific mortality followed improvements in public health, medical infrastructure and pollution control, but not for cancer or diabetes, likely because of exposure to new risk factors.

/pdf/influence-of-socioeconomic-events-on-cause-specific-3z0ymzuk9v.pdf

Influence of socioeconomic events on cause-specific mortality in urban Shanghai, China, from 1974 to 2015: a population-based longitudinal study.

ABSTRACT Introduction Diabetic kidney disease (DKD) is the most common cause of end-stage renal disease (ESRD) worldwide. Currently, there is no effective treatment to completely prevent DKD progression to ESRD. Renal fibrosis and inflammation are the major pathological features of DKD, being pursued as potential therapeutic targets for DKD. Areas covered Inflammation and renal fibrosis are involved in the pathogenesis of DKD. Anti-inflammatory drugs have been developed to combat DKD but without efficacy demonstrated. Thus, we have focused on the mechanisms of TGF-β-induced renal fibrosis in DKD, as well as discussing the important molecules influencing the TGF-β signaling pathway and their potential development into new pharmacotherapies, rather than targeting the ligand TGF-β and/or its receptors, such options include Smads, microRNAs, histone deacetylases, connective tissue growth factor, bone morphogenetic protein 7, hepatocyte growth factor, and cell division autoantigen 1. Expert opinion TGF-β is a critical driver of renal fibrosis in DKD. Molecules that modulate TGF-β signaling rather than TGF-β itself are potentially superior targets to safely combat DKD. A comprehensive elucidation of the pathogenesis of DKD is important, which requires a better model system and access to clinical samples via collaboration between basic and clinical researchers.

Renal fibrosis as a hallmark of diabetic kidney disease: potential role of targeting transforming growth factor-beta (TGF-β) and related molecules

Connective tissue growth factor (CTGF), is a secreted matricellular factor that has been linked to increased risk of cardiovascular disease in diabetic subjects. Despite the biological role of CTGF in diabetes, it still remains unclear how CTGF expression is regulated. In this study, we aim to identify the clinical parameters that modulate plasma CTGF levels measured longitudinally in type 1 diabetic patients over a period of 10 years. A number of patients had negligible measured values of plasma CTGF that formed a point mass at zero, whereas others had high positive values of CTGF that were measured on a continuous scale. The observed combination of excessive zero and continuous positively distributed non-zero values in the CTGF outcome is referred to as semicontinuous data. We propose a novel application of a marginalized two-part model (mTP) extended to accommodate longitudinal semicontinuous data in which the marginal mean is expressed in terms of the covariates and estimates of their effect on the mean responses are generated. The continuous component is assumed to follow distributions that stem from the generalized gamma family whereas the binary measure is analyzed using logistic model and both have correlated random effects. Other approaches including the one- and two-part with uncorrelated and correlated random effects models were also applied and their estimates were all compared. Our results using the mTP model identified intensive glucose control treatment and smoking as clinical factors that were associated with decreased and increased odds of observing non-zero CTGF values respectively. In addition, hemoglobin A1c, systolic blood pressure, and high density lipoprotein were all shown to be significant risk factors that contribute to increasing CTGF levels. These findings were consistently observed under the mTP model but varied with the distributions for the other models. Accuracy and precision of the mTP model was further validated using simulation studies. The mTP model identified new clinical determinants that modulate the levels of CTGF in diabetic subjects. Applicability of this approach can be extended to other biomarkers measured in patient populations that display a combination of negligible zero and non-zero values.

/pdf/analysis-of-longitudinal-semicontinuous-data-using-fcuiolnzp0.pdf

Analysis of longitudinal semicontinuous data using marginalized two-part model.

Connective tissue growth factor (CTGF) is a member of the CCN family of matricellular proteins that has been implicated in the inflammatory process, response to injury and wound healing. An emerging role of CTGF is that of a profibrotic factor implicated in the development of kidney disease. Our objective was to determine the role of CTGF as a predictor of macroalbuminuria (ACR ≥300µg/mg twice) and chronic kidney disease (CKD) stage 3 (GFR Disclosure K.J. Hunt: None. M.A. Jaffa: None. S.M. Garrett: None. D.K. Luttrell: None. K.E. Lipson: Employee; Self; FibroGen, Inc.. Stock/Shareholder; Self; AbbVie Inc., Abbott, Becton, Dickinson and Company, Bristol-Myers Squibb Company, General Electric, Gilead Sciences, Inc., Medtronic, Nestle, Novartis AG, Oracle, Pfizer Inc., Quest Diagnostics. Consultant; Spouse/Partner; Diabesen. M.F. Lopes-Virella: None. L.M. Luttrell: None. A.A. Jaffa: None.

Levels of Connective Tissue Growth Factor (CTGF) Predict Development of Kidney Dysfunction in Type 2 Diabetes-The VADT Study

OBJECTIVE Connective tissue growth factor (CTGF), also known as CCN2, is a potent chemotactic and extracellular matrix-inducing matricellular protein that has been implicated in progression of inflammatory and fibroproliferative disorders. An emerging role of CTGF/CCN2 is that of a prosclerotic factor implicated in the development of cardiac disease. Our objective was to determine the role of CTGF/CCN2 as a predictor of cardiovascular events in type 2 diabetes in the Veterans Affairs Diabetes Trial (VADT) cohort. RESEARCH DESIGN AND METHODS Levels of CTGF/CCN2 were measured in 952 VADT patients a median of 1.9 years after entry into the study. Participants were followed for an average of 3.3 years for vascular outcomes. CTGF/CCN2 categories were defined as below the detectable limit (referent, 54.5%), lower half of detectable values (22.8%), and upper half of detectable values (22.7%). Hazard ratios (HRs) for cardiovascular end points in relation to CTGF/CCN2 categories were calculated by Cox proportional hazards models. RESULTS During follow-up, 4.8% had a myocardial infarction (MI), 6.9% had an MI or cardiovascular death, and 6.9% died. After adjustments by conventional risk factors, individuals in the highest category of CTGF/CCN2 were at higher risk of MI (HR 2.43 [95% CI 1.15, 5.14]), MI or cardiovascular death (HR 2.71 [95% CI 1.44, 5.08]), and all-cause mortality (HR 2.70 [95% CI 1.43, 5.08]) relative to individuals with CTGF below the detectable limit. CONCLUSIONS Our study indicates that high levels of CTGF/CCN2 predict future MI and cardiovascular death in patients with type 2 diabetes.

/pdf/plasma-connective-tissue-growth-factor-ctgf-ccn2-levels-4oc8xtoxum.pdf

Plasma Connective Tissue Growth Factor (CTGF/CCN2) Levels Predict Myocardial Infarction in the Veterans Affairs Diabetes Trial (VADT) Cohort.

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Analysis of longitudinal semicontinuous data using marginalized two-part model.

Levels of Connective Tissue Growth Factor (CTGF) Predict Development of Kidney Dysfunction in Type 2 Diabetes-The VADT Study

Plasma Connective Tissue Growth Factor (CTGF/CCN2) Levels Predict Myocardial Infarction in the Veterans Affairs Diabetes Trial (VADT) Cohort.