Prevalence and Prognostic Implications of Diabetes With Cardiomyopathy in Community-Dwelling Adults

Development and validation of a machine learning-based approach to identify high-risk diabetic cardiomyopathy phenotype

AIMS

Abnormalities in specific echocardiographic parameters and cardiac biomarkers have been reported among individuals with diabetes. However, a comprehensive characterization of diabetic cardiomyopathy (DbCM), a subclinical stage of myocardial abnormalities that precede the development of clinical heart failure (HF), is lacking. In this study, we developed and validated a machine learning-based clustering approach to identify the high-risk DbCM phenotype based on echocardiographic and cardiac biomarker parameters.

METHODS AND RESULTS

Among individuals with diabetes from the Atherosclerosis Risk in Communities (ARIC) cohort who were free of cardiovascular disease and other potential aetiologies of cardiomyopathy (training, n = 1199), unsupervised hierarchical clustering was performed using echocardiographic parameters and cardiac biomarkers of neurohormonal stress and chronic myocardial injury (total 25 variables). The high-risk DbCM phenotype was identified based on the incidence of HF on follow-up. A deep neural network (DeepNN) classifier was developed to predict DbCM in the ARIC training cohort and validated in an external community-based cohort (Cardiovascular Health Study [CHS]; n = 802) and an electronic health record (EHR) cohort (n = 5071). Clustering identified three phenogroups in the derivation cohort. Phenogroup-3 (n = 324, 27% of the cohort) had significantly higher 5-year HF incidence than other phenogroups (12.1% vs. 4.6% [phenogroup 2] vs. 3.1% [phenogroup 1]) and was identified as the high-risk DbCM phenotype. The key echocardiographic predictors of high-risk DbCM phenotype were higher NT-proBNP levels, increased left ventricular mass and left atrial size, and worse diastolic function. In the CHS and University of Texas (UT) Southwestern EHR validation cohorts, the DeepNN classifier identified 16% and 29% of participants with DbCM, respectively. Participants with (vs. without) high-risk DbCM phenotype in the external validation cohorts had a significantly higher incidence of HF (hazard ratio [95% confidence interval] 1.61 [1.18-2.19] in CHS and 1.34 [1.08-1.65] in the UT Southwestern EHR cohort).

CONCLUSION

Machine learning-based techniques may identify 16% to 29% of individuals with diabetes as having a high-risk DbCM phenotype who may benefit from more aggressive implementation of HF preventive strategies.

Diabetic cardiomyopathy: Emerging therapeutic options

Diabetic cardiomyopathy (DbCM) is a common but underrecognized compli-cation of patients with diabetes mellitus (DM). Although the pathobiology of other cardiac complications of diabetes such as ischemic heart disease and cardiac autonomic neuropathy are mostly known with reasonable therapeutic options, the mechanisms and management options for DbCM are still not fully understood. In its early stages, DbCM presents with diastolic dysfunction followed by heart failure (HF) with preserved ejection fraction that can progress to systolic dysfunction and HF with reduced ejection fraction in its advanced stages unless appropriately managed. Apart from prompt control of DM with lifestyle changes and antidiabetic medications, disease-modifying therapy for DbCM includes prompt control of hypertension and dyslipidemia inherent to patients with DM as in other forms of heart diseases and the use of treatments with proven efficacy in HF. A basic study by Zhang et al, in a recent issue of the World Journal of Diabetes elaborates the potential pathophysiological alterations and the therapeutic role of teneligliptin in diabetic mouse models with DbCM. Although this preliminary basic study might help to improve our understanding of DbCM and offer a potential new management option for patients with the disease, the positive results from such animal models might not always translate to clinical practice as the pathobiology of DbCM in humans could be different. However, such experimental studies can encourage more scientific efforts to find a better solution to treat patients with this enigmatic disease.

Targeting Rab7-Rilp Mediated Microlipophagy Alleviates Lipid Toxicity in Diabetic Cardiomyopathy

Diabetic cardiomyopathy (DbCM) is characterized by diastolic dysfunction, which progresses into heart failure and aberrant electrophysiology in diabetic patients. Dyslipidemia in type 2 diabetic patients leads to the accumulation of lipid droplets (LDs) in cardiomyocytes and results in lipid toxicity which has been suggested to drive DbCM. It is aimed to explore potential pathways that may boost LDs degradation in DbCM and restore cardiac function. LDs accumulation resulted in an increase in lipid toxicity in DbCM hearts is confirmed. Microlipophagy pathway, rather than traditional macrolipophagy, is activated in DbCM hearts. RNA-Seq data and Rab7-CKO mice implicate that Rab7 is a major modulator of the microlipophagy pathway. Mechanistically, Rab7 is phosphorylated at Tyrosine 183, which allows the recruitment of Rab-interacting lysosome protein (Rilp) to proceed LDs degradation by lysosome. Treating DbCM mice with Rab7 activator ML-098 enhanced Rilp level and rescued the observed cardiac dysfunction. Overall, Rab7-Rilp-mediated microlipophagy may be a promising target in the treatment of lipid toxicity in DbCM is suggested.

Effect of extracellular matrix stiffness on efficacy of Dapagliflozin for diabetic cardiomyopathy

BACKGROUND

Extracellular matrix (ECM) stiffness is closely related to the progress of diabetic cardiomyopathy (DCM) and the response of treatment of DCM to anti-diabetic drugs. Dapagliflozin (Dapa) has been proven to have cardio-protective efficacy for diabetes and listed as the first-line drug to treat heart failure. But the regulatory relationship between ECM stiffness and treatment efficacy of Dapa remains elusive.

MATERIALS AND METHODS

This work investigated the effect of ECM stiffness on DCM progression and Dapa efficacy using both in vivo DCM rat model and in vitro myocardial cell model with high glucose injury. First, through DCM rat models with various levels of myocardial injury and administration with Dapa treatment for four weeks, the levels of myocardial injury, myocardial oxidative stress, expressions of AT1R (a mechanical signal protein) and the stiffness of myocardial tissues were obtained. Then for mimicking the stiffness of myocardial tissues at early and late stages of DCM, we constructed cell models through culturing H9c2 myocardial cells on the polyacrylamide gels with two stiffness and exposed to a high glucose level and without/with Dapa intervention. The cell viability, reactive oxygen species (ROS) levels and expressions of mechanical signal sensitive proteins were obtained.

RESULTS

The DCM progression is accompanied by the increased myocardial tissue stiffness, which can synergistically exacerbate myocardial cell injury with high glucose. Dapa can improve the ECM stiffness-induced DCM progression and its efficacy on DCM is more pronounced on the soft ECM, which is related to the regulation pathway of AT1R-FAK-NOX2. Besides, Dapa can inhibit the expression of the ECM-induced integrin β1, but without significant impact on piezo 1.

CONCLUSIONS

Our study found the regulation and effect of biomechanics in the DCM progression and on the Dapa efficacy on DCM, providing the new insights for the DCM treatment. Additionally, our work showed the better clinical prognosis of DCM under early Dapa intervention.

Diabetic myocardial disorder. A clinical consensus statement of the Heart Failure Association of the ESC and the ESC Working Group on Myocardial & Pericardial Diseases

The association between type 2 diabetes mellitus (T2DM) and heart failure (HF) has been firmly established; however, the entity of diabetic myocardial disorder (previously called diabetic cardiomyopathy) remains a matter of debate. Diabetic myocardial disorder was originally described as the occurrence of myocardial structural/functional abnormalities associated with T2DM in the absence of coronary heart disease, hypertension and/or obesity. However, supporting evidence has been derived from experimental and small clinical studies. Only a minority of T2DM patients are recognized as having this condition in the absence of contributing factors, thereby limiting its clinical utility. Therefore, this concept is increasingly being viewed along the evolving HF trajectory, where patients with T2DM and asymptomatic structural/functional cardiac abnormalities could be considered as having pre-HF. The importance of recognizing this stage has gained interest due to the potential for current treatments to halt or delay the progression to overt HF in some patients. This document is an expert consensus statement of the Heart Failure Association of the ESC and the ESC Working Group on Myocardial & Pericardial Diseases. It summarizes contemporary understanding of the association between T2DM and HF and discuses current knowledge and uncertainties about diabetic myocardial disorder that deserve future research. It also proposes a new definition, whereby diabetic myocardial disorder is defined as systolic and/or diastolic myocardial dysfunction in the presence of diabetes. Diabetes is rarely exclusively responsible for myocardial dysfunction, but usually acts in association with obesity, arterial hypertension, chronic kidney disease and/or coronary artery disease, causing additive myocardial impairment.

Prevalence of diabetic cardiomyopathy in patients with type 2 diabetes in a large academic medical center

BACKGROUND

Diabetic cardiomyopathy (DbCM) is characterized by asymptomatic stage B heart failure (SBHF) caused by diabetes-related metabolic alterations. DbCM is associated with an increased risk of progression to overt heart failure (HF). The prevalence of DbCM in patients with type 2 diabetes (T2D) is not well established. This study aims to determine prevalence of DbCM in adult T2D patients in real-world clinical practice.

METHODS

Retrospective multi-step review of electronic medical records of patients with the diagnosis of T2D who had echocardiogram at UC San Diego Medical Center (UCSD) within 2010-2019 was conducted to identify T2D patients with SBHF. We defined "pure" DbCM when SBHF is associated solely with T2D and "mixed" SBHF when other medical conditions can contribute to SBHF. "Pure" DbCM was diagnosed in T2D patients with echocardiographic demonstration of SBHF defined as left atrial (LA) enlargement (LAE), as evidenced by LA volume index ≥ 34 mL/m2, in the presence of left ventricular ejection fraction (LVEF) ≥ 45%, while excluding overt HF and comorbidities that can contribute to SBHF.

RESULTS

Of 778,314 UCSD patients in 2010-2019, 45,600 (5.9%) had T2D diagnosis. In this group, 15,182 T2D patients (33.3%) had echocardiogram and, among them, 13,680 (90.1%) had LVEF ≥ 45%. Out of 13,680 patients, 4,790 patients had LAE. Of them, 1,070 patients were excluded due to incomplete data and/or a lack of confirmed T2D according to the American Diabetes Association recommendations. Thus, 3,720 T2D patients with LVEF ≥ 45% and LAE were identified, regardless of HF symptoms. In this group, 1,604 patients (43.1%) had overt HF and were excluded. Thus, 2,116 T2D patients (56.9% of T2D patients with LVEF ≥ 45% and LAE) with asymptomatic SBHF were identified. Out of them, 1,773 patients (83.8%) were diagnosed with "mixed" SBHF due to comorbidities such as hypertension (58%), coronary artery disease (36%), and valvular heart disease (17%). Finally, 343 patients met the diagnostic criteria of "pure" DbCM, which represents 16.2% of T2D patients with SBHF, i.e., at least 2.9% of the entire T2D population in this study.

CONCLUSIONS

Our findings provide insights into prevalence of DbCM in real-world clinical practice and indicate that DbCM affects a significant portion of T2D patients.

Methods to predict heart failure in diabetes patients

INTRODUCTION

Type 2 diabetes mellitus (T2DM) is one of the leading causes of cardiovascular disease and powerful predictor for new-onset heart failure (HF).

AREAS COVERED

We focus on the relevant literature covering evidence of risk stratification based on imaging predictors and circulating biomarkers to optimize approaches to preventing HF in DM patients.

EXPERT OPINION

Multiple diagnostic algorithms based on echocardiographic parameters of cardiac remodeling including global longitudinal strain/strain rate are likely to be promising approach to justify individuals at higher risk of incident HF. Signature of cardiometabolic status may justify HF risk among T2DM individuals with low levels of natriuretic peptides, which preserve their significance in HF with clinical presentation. However, diagnostic and predictive values of conventional guideline-directed biomarker HF strategy may be non-optimal in patients with obesity and T2DM. Alternative biomarkers affecting cardiac fibrosis, inflammation, myopathy, and adipose tissue dysfunction are plausible tools for improving accuracy natriuretic peptides among T2DM patients at higher HF risk. In summary, risk identification and management of the patients with T2DM with established HF require conventional biomarkers monitoring, while the role of alternative biomarker approach among patients with multiple CV and metabolic risk factors appears to be plausible tool for improving clinical outcomes.

Human umbilical cord-derived mesenchymal stromal cells improve myocardial fibrosis and restore miRNA-133a expression in diabetic cardiomyopathy

BACKGROUND

Diabetic cardiomyopathy (DCM) is a serious health-threatening complication of diabetes mellitus characterized by myocardial fibrosis and abnormal cardiac function. Human umbilical cord mesenchymal stromal cells (hUC-MSCs) are a potential therapeutic tool for DCM and myocardial fibrosis via mechanisms such as the regulation of microRNA (miRNA) expression and inflammation. It remains unclear, however, whether hUC-MSC therapy has beneficial effects on cardiac function following different durations of diabetes and which mechanistic aspects of DCM are modulated by hUC-MSC administration at different stages of its development. This study aimed to investigate the therapeutic effects of intravenous administration of hUC-MSCs on DCM following different durations of hyperglycemia in an experimental male model of diabetes and to determine the effects on expression of candidate miRNAs, target mRNA and inflammatory mediators.

METHODS

A male mouse model of diabetes was induced by multiple low-dose streptozotocin injections. The effects on severity of DCM of intravenous injections of hUC-MSCs and saline two weeks previously were compared at 10 and 18 weeks after diabetes induction. At both time-points, biochemical assays, echocardiography, histopathology, polymerase chain reaction (PCR), immunohistochemistry and enzyme-linked immunosorbent assays (ELISA) were used to analyze blood glucose, body weight, cardiac structure and function, degree of myocardial fibrosis and expression of fibrosis-related mRNA, miRNA and inflammatory mediators.

RESULTS

Saline-treated diabetic male mice had impaired cardiac function and increased cardiac fibrosis after 10 and 18 weeks of diabetes. At both time-points, cardiac dysfunction and fibrosis were improved in hUC-MSC-treated mice. Pro-fibrotic indicators (α-SMA, collagen I, collagen III, Smad3, Smad4) were reduced and anti-fibrotic mediators (FGF-1, miRNA-133a) were increased in hearts of diabetic animals receiving hUC-MSCs compared to saline. Increased blood levels of pro-inflammatory cytokines (IL-6, TNF, IL-1β) and increased cardiac expression of IL-6 were also observed in saline-treated mice and were reduced by hUC-MSCs at both time-points, but to a lesser degree at 18 weeks.

CONCLUSION

Intravenous injection of hUC-MSCs ameliorated key functional and structural features of DCM in male mice with diabetes of shorter and longer duration. Mechanistically, these effects were associated with restoration of intra-myocardial expression of miRNA-133a and its target mRNA COL1AI as well as suppression of systemic and localized inflammatory mediators.

Epidemiology of heart failure in diabetes: a disease in disguise

Left ventricular diastolic dysfunction (LVDD) without symptoms, and heart failure (HF) with preserved ejection fraction (HFpEF) represent the most common phenotypes of HF in individuals with type 2 diabetes mellitus, and are more common than HF with reduced ejection fraction (HFrEF), HF with mildly reduced ejection fraction (HFmrEF) and left ventricular systolic dysfunction (LVSD) in these individuals. However, diagnostic criteria for HF have changed over the years, resulting in heterogeneity in the prevalence/incidence rates reported in different studies. We aimed to give an overview of the diagnosis and epidemiology of HF in type 2 diabetes, using both a narrative and systematic review approach; we focus narratively on diagnosing (using the 2021 European Society of Cardiology [ESC] guidelines) and screening for HF in type 2 diabetes. We performed an updated (2016-October 2022) systematic review and meta-analysis of studies reporting the prevalence and incidence of HF subtypes in adults ≥18 years with type 2 diabetes, using echocardiographic data. Embase and MEDLINE databases were searched and data were assessed using random-effects meta-analyses, with findings presented as forest plots. From the 5015 studies found, 209 were screened using the full-text article. In total, 57 studies were included, together with 29 studies that were identified in a prior meta-analysis; these studies reported on the prevalence of LVSD (n=25 studies, 24,460 individuals), LVDD (n=65 studies, 25,729 individuals), HFrEF (n=4 studies, 4090 individuals), HFmrEF (n=2 studies, 2442 individuals) and/or HFpEF (n=8 studies, 5292 individuals), and on HF incidence (n=7 studies, 17,935 individuals). Using Hoy et al's risk-of-bias tool, we found that the studies included generally had a high risk of bias. They showed a prevalence of 43% (95% CI 37%, 50%) for LVDD, 17% (95% CI 7%, 35%) for HFpEF, 6% (95% CI 3%, 10%) for LVSD, 7% (95% CI 3%, 15%) for HFrEF, and 12% (95% CI 7%, 22%) for HFmrEF. For LVDD, grade I was found to be most prevalent. Additionally, we reported a higher incidence rate of HFpEF (7% [95% CI 4%, 11%]) than HFrEF 4% [95% CI 3%, 7%]). The evidence is limited by the heterogeneity of the diagnostic criteria over the years. The systematic section of this review provides new insights on the prevalence/incidence of HF in type 2 diabetes, unveiling a large pre-clinical target group with LVDD/HFpEF in which disease progression could be halted by early recognition and treatment.Registration PROSPERO ID CRD42022368035.

Diabetic Cardiomyopathy-From Basics through Diagnosis to Treatment

Diabetic cardiomyopathy (DCM) is the development of myocardial dysfunction in patients with diabetes despite the absence of comorbidities such as hypertension, atherosclerosis or valvular defect. The cardiovascular complications of poorly controlled diabetes are very well illustrated by the U.K. Prospective Diabetes Study (UKPDS), which showed a clear association between increasing levels of glycated hemoglobin and the development of heart failure (HF). The incidence of HF in patients with diabetes is projected to increase significantly, which is why its proper diagnosis and treatment is so important. Providing appropriate therapy focusing on antidiabetic and hypolipemic treatment with the consideration of pharmacotherapy for heart failure reduces the risk of CMD and reduces the incidence of cardiovascular complications. Health-promoting changes made by patients such as a low-carbohydrate diet, regular exercise and weight reduction also appear to be important in achieving appropriate outcomes. New hope for the development of therapies for DCM is offered by novel methods using stem cells and miRNA, which, however, require more thorough research to confirm their efficacy.

Characterizing diabetic cardiomyopathy: baseline results from the ARISE-HF trial

BACKGROUND

Diabetic cardiomyopathy (DbCM) is a form of Stage B heart failure (HF) at high risk for progression to overt disease. Using baseline characteristics of study participants from the Aldose Reductase Inhibition for Stabilization of Exercise Capacity in Heart Failure (ARISE-HF) Trial we sought to characterize clinical characteristics of individuals with findings consistent with DbCM.

METHODS

Among study participants meeting inclusion criteria, clinical characteristics, laboratory testing, imaging, Kansas City Cardiomyopathy Questionnaire (KCCQ), Physical Activity Scale of the Elderly (PASE) and cardiopulmonary exercise testing (CPET) results were tabulated. Cluster phenogroups were identified.

RESULTS

Among 691 study participants (mean age 67.4 years; 50% were female), mean duration of type 2 diabetes mellitus (T2DM) was 14.5 years. The median (Q1, Q3) N-terminal pro-B type natriuretic peptide and high sensitivity cardiac troponin T were 71 (35, 135) ng/L and 9 [6, 12] ng/L. The most common echocardiographic abnormalities were reduced global longitudinal strain in 25.3% and impaired diastolic relaxation in 17.7%. Despite rather well-preserved KCCQ scores the average PASE score was markedly impaired at 155 accompanied by an average maximal oxygen consumption of 15.7 mL/Kg/minute on CPET. In K-means clustering, 4 phenogroups were identified including a higher-risk group with more advanced age, greater elevation of cardiac biomarkers, and more prevalent evidence for diastolic dysfunction and left ventricular hypertrophy.

CONCLUSIONS

Baseline data from the ARISE-HF Trial provide clinical characterization of individuals with T2DM and features of stage B HF, and may help clarify the diagnosis of DbCM.

TRIAL REGISTRATION

ARISE-HF, NCT04083339.

Secreted frizzled-related protein 2 ameliorates diabetic cardiomyopathy by activating mitophagy

OBJECTIVES

Secreted frizzled-related protein 2 (SFRP2), a novel adipokine that used to be considered an inhibitor of the canonical Wnt pathway, may play a protective role in metabolic disorders. However, its effect on diabetic cardiomyopathy was still unclear. Accumulating evidence indicates that mitophagy can protect cardiac function in the diabetic heart. The present study aimed to explore the roles of SFRP2 on diabetic cardiomyopathy, focusing on the effects and mechanisms for regulating mitophagy.

METHODS

Wild-type H9c2 cells, Sfrp2 overexpression and knockdown H9c2 cells were exposed to a glucolipotoxic milieu. Reactive oxygen species (ROS) production, cell viability, apoptosis, mitophagy and lysosomal activity were detected. The interaction of SFRP2 with frizzled 5 (FZD5), and its effect on expression and intracellular localization of transcription factor EB (TFEB) and β-catenin were also explored. Diabetic rats and Sfrp2 overexpression diabetic rats were constructed to further document the findings from the in vitro study.

RESULTS

The expression of SFRP2 was low and mitophagy was inhibited in H9c2 cells in a glucolipotoxic milieu. Sfrp2 overexpression activated mitophagy and reduced H9c2 cells injury, whereas Sfrp2 deficiency inhibited mitophagy and worsened this injury. Consistent with the in vitro findings, Sfrp2 overexpression ameliorated the impairment in cardiac function of diabetic rats by activating mitophagy. Sfrp2 overexpression upregulated the expression of calcineurin and TFEB, but did not affect β-catenin in vitro and in vivo. The calcineurin inhibitor tacrolimus can inhibit mitophagy and worsen cell injury in Sfrp2 overexpression H9c2 cells. Furthermore, we found that FZD5 is required for the SFRP2-induced activation of the calcineurin/TFEB pathway and interacts with SFRP2 in H9c2 cells. Transfection with small interfering RNA targeting FZD5 opposed the effects of Sfrp2 overexpression on mitophagy and cell survival in a glucolipotoxic environment.

CONCLUSIONS

SFRP2 can protect the diabetic heart by interacting with FZD5 and activating the calcineurin/TFEB pathway to upregulate mitophagy in H9c2 cells.

Optimal Screening for Predicting and Preventing the Risk of Heart Failure Among Adults With Diabetes Without Atherosclerotic Cardiovascular Disease: A Pooled Cohort Analysis

BACKGROUND

The optimal approach to identify individuals with diabetes who are at a high risk for developing heart failure (HF) to inform implementation of preventive therapies is unknown, especially in those without atherosclerotic cardiovascular disease (ASCVD).

METHODS

Adults with diabetes and no HF at baseline from 7 community-based cohorts were included. Participants without ASCVD who were at high risk for developing HF were identified using 1-step screening strategies: risk score (WATCH-DM [Weight, Age, Hypertension, Creatinine, HDL-C, Diabetes Control, QRS Duration, MI, and CABG] ≥12), NT-proBNP (N-terminal pro-B-type natriuretic peptide ≥125 pg/mL), hs-cTn (high-sensitivity cardiac troponin T ≥14 ng/L; hs-cTnI ≥31 ng/L), and echocardiography-based diabetic cardiomyopathy (echo-DbCM; left atrial enlargement, left ventricular hypertrophy, or diastolic dysfunction). High-risk participants were also identified using 2-step screening strategies with a second test to identify residual risk among those deemed low risk by the first test: WATCH-DM/NT-proBNP, NT-proBNP/hs-cTn, NT-proBNP/echo-DbCM. Across screening strategies, the proportion of HF events identified, 5-year number needed to treat and number needed to screen to prevent 1 HF event with an SGLT2i (sodium-glucose cotransporter 2 inhibitor) among high-risk participants, and cost of screening were estimated.

RESULTS

The initial study cohort included 6293 participants (48.2% women), of whom 77.7% without prevalent ASCVD were evaluated with different HF screening strategies. At 5-year follow-up, 6.2% of participants without ASCVD developed incident HF. The 5-year number needed to treat to prevent 1 HF event with an SGLT2i among participants without ASCVD was 43 (95% CI, 29-72). In the cohort without ASCVD, high-risk participants identified using 1-step screening strategies had a low 5-year number needed to treat (22 for NT-proBNP to 37 for echo-DbCM). However, a substantial proportion of HF events occurred among participants identified as low risk using 1-step screening approaches (29% for echo-DbCM to 47% for hs-cTn). Two-step screening strategies captured most HF events (75-89%) in the high-risk subgroup with a comparable 5-year number needed to treat as the 1-step screening approaches (30-32). The 5-year number needed to screen to prevent 1 HF event was similar across 2-step screening strategies (45-61). However, the number of tests and associated costs were lowest for WATCH-DM/NT-proBNP ($1061) compared with other 2-step screening strategies (NT-proBNP/hs-cTn: $2894; NT-proBNP/echo-DbCM: $16 358).

CONCLUSIONS

Selective NT-proBNP testing based on the WATCH-DM score efficiently identified a high-risk primary prevention population with diabetes expected to derive marked absolute benefits from SGLT2i to prevent HF.

Preclinical Evidence for the Effectiveness of Mesenchymal Stromal Cells for Diabetic Cardiomyopathy: A Systematic Review and Meta-analysis

BACKGROUND

Diabetic cardiomyopathy (DCM) is a complication of diabetes mellitus that endangers human health. DCM results in cardiac dysfunction, which eventually progresses to heart failure. Mesenchymal stromal cells (MSCs), a type of multipotent stem cell, have shown promising therapeutic effects in various cardiovascular diseases and diabetic complications in preclinical studies due to their immunomodulatory and regenerative abilities. However, there is still a lack of evidence to summarize the effectiveness of MSCs in the treatment of DCM. Therefore, a meta-analysis and systematic review are warranted to evaluate the therapeutic potential of MSCs for DCM in preclinical studies.

METHODS

A comprehensive literature search in English or Chinese was conducted in PubMed, EMBASE, web of Science, Cochrane Library, and China National Knowledge Internet from inception to June 30, 2022. The summarized outcomes included echocardiography, morphology, and pathology. Data were independently extracted and analyzed by two authors. The software we adopted was Review Manager5.4.1. This systematic review was written in compliance with PRISMA 2020 and the review protocol was registered on PROSPERO, registration no. CRD42022350032.

RESULTS

We included 20 studies in our meta-analysis to examine the efficacy of MSCs in the treatment of DCM. The MSC-treated group showed a statistically significant effect on left ventricular ejection fraction (WMD=12.61, 95% CI 4.32 to 20.90, P=0.003) and short axis fractional shortening (WMD=6.84, 95% CI 4.09 to 9.59, P < 0.00001). The overall effects on the ratio of early to late diastolic mitral annular velocity, left ventricular end-diastolic pressure, maximum positive pressure development, maximum negative pressure development, left ventricular relaxation time constant, heart weight to body weight ratio, fibrosis area, and arteriole density were analyzed, suggesting that MSCs represent an effective therapy for the treatment of DCM.

CONCLUSION

Our results suggest a therapeutic role for MSCs in the treatment of DCM, and these results provide support for the use of MSCs in clinical trials of patients with DCM.

Prevalence and Predictors of Subclinical Cardiomyopathy in Patients With Type 2 Diabetes in a Health System

INTRODUCTION

Diabetic cardiomyopathy (DbCM) is characterized by subclinical abnormalities in cardiac structure/function and is associated with a higher risk of overt heart failure (HF). However, there are limited data on optimal strategies to identify individuals with DbCM in contemporary health systems. The aim of this study was to evaluate the prevalence of DbCM in a health system using existing data from the electronic health record (EHR).

METHODS

Adult patients with type 2 diabetes mellitus free of cardiovascular disease (CVD) with available data on HF risk in a single-center EHR were included. The presence of DbCM was defined using different definitions: (1) least restrictive: ≥1 echocardiographic abnormality (left atrial enlargement, left ventricle hypertrophy, diastolic dysfunction); (2) intermediate restrictive: ≥2 echocardiographic abnormalities; (3) most restrictive: 3 echocardiographic abnormalities. DbCM prevalence was compared across age, sex, race, and ethnicity-based subgroups, with differences assessed using the chi-squared test. Adjusted logistic regression models were constructed to evaluate significant predictors of DbCM.

RESULTS

Among 1921 individuals with type 2 diabetes mellitus, the prevalence of DbCM in the overall cohort was 8.7% and 64.4% in the most and least restrictive definitions, respectively. Across all definitions, older age and Hispanic ethnicity were associated with a higher proportion of DbCM. Females had a higher prevalence than males only in the most restrictive definition. In multivariable-adjusted logistic regression, higher systolic blood pressure, higher creatinine, and longer QRS duration were associated with a higher risk of DbCM across all definitions.

CONCLUSIONS

In this single-center, EHR cohort, the prevalence of DbCM varies from 9% to 64%, with a higher prevalence with older age and Hispanic ethnicity.

Precision subclassification of type 2 diabetes: a systematic review

BACKGROUND

Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients.

METHODS

We searched PubMed and Embase for publications that used 'simple subclassification' approaches using simple categorisation of clinical characteristics, or 'complex subclassification' approaches which used machine learning or 'omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical relevance of extracted full-text articles and qualitatively synthesised a summary of subclassification approaches.

RESULTS

Here we show data from 51 studies that demonstrate many simple stratification approaches, but none have been replicated and many are not associated with meaningful clinical outcomes. Complex stratification was reviewed in 62 studies and produced reproducible subtypes of type 2 diabetes that are associated with outcomes. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into clinically meaningful subtypes.

CONCLUSION

Critical next steps toward clinical implementation are to test whether subtypes exist in more diverse ancestries and whether tailoring interventions to subtypes will improve outcomes.

Molecular Processes Involved in the Shared Pathways between Cardiovascular Diseases and Diabetes

Cardiovascular diseases and diabetes mellitus are currently among the diseases with the highest morbidity and mortality. The pathogenesis and development of these diseases remain strongly connected, along with inflammation playing a major role. Therefore, the treatment possibilities showing a positive impact on both of these diseases could be especially beneficial for patients. SGLT-2 inhibitors and GLP-1 receptor agonists present this dual effect. Moreover, the hostile composition of the gut microbiota could influence the progression of these conditions. In this review, the authors present the latest knowledge on and innovations in diabetes mellitus and CVD-with the focus on the molecular mechanisms and the role of the microbiota.

Osteopontin levels correlate with severity of diabetic cardiomyopathy in early stage of diabetes

Diabetic cardiomyopathy (DbCM) is characterized by restrictive pattern and consistent risk of overt heart failure. We here focused osteopontin (OPN), which was tested independently associated with left ventricular diastolic dysfunction (LVDD). Overall, OPN increased with DbCM severity according with the presence of left atrial dilatation, LV hypertrophy and LVDD.

Predicting and preventing heart failure in type 2 diabetes

The burden of heart failure among people with type 2 diabetes is increasing globally. People with comorbid type 2 diabetes and heart failure often have worse outcomes than those with only one of these conditions-eg, higher hospitalisation and mortality rates. Therefore, it is essential to implement optimal heart failure prevention strategies for people with type 2 diabetes. A detailed understanding of the pathophysiology underlying the occurrence of heart failure in type 2 diabetes can aid clinicians in identifying relevant risk factors and lead to early interventions that can help prevent heart failure. In this Review, we discuss the pathophysiology and risk factors of heart failure in type 2 diabetes. We also review the risk assessment tools for predicting heart failure incidence in people with type 2 diabetes as well as the data from clinical trials that have assessed the efficacy of lifestyle and pharmacological interventions. Finally, we discuss the potential challenges in implementing new management approaches and offer pragmatic recommendations to help overcome these challenges.

The Nonlinear Relationship Between Body Mass Index (BMI) and Perceived Depression in the Chinese Population

Purpose

Existing studies on the association between BMI and depression report conflicting results with some demonstrating a positive relationship, while others a negative link or insignificant correlation. Very limited research on the nonlinear relationship between BMI and depression has yet to clarify the reliability and robustness of the potential nonlinearity and whether a more complex association exists. This paper aims to systematically investigate the nonlinear relationship between the two factors applying rigorous statistical methods, as well as explore the heterogeneity of their association.

Materials and Methods

A large-scale nationally representative dataset, Chinese General Social Survey, is used to empirically analyze the nonlinear relationship between BMI and perceived depression. Various statistical tests are employed to check the robustness of the nonlinearity.

Results

Results indicate that there is a U-shaped relationship between BMI and perceived depression, with the turning point (25.718) very close to while slightly larger than the upper limit of the range of healthy weight (18.500 ≤ BMI < 25.000) defined by World Health Organization. Both very high and low BMIs are associated with increased risk for depressive disorders. Furthermore, perceived depression is higher at almost all BMI levels among individuals who are older, female, lower educated, unmarried, in rural areas, belonging to ethnic minorities, non-Communist Party of China members, as well as those with lower income and uncovered by social security. In addition, these subgroups have smaller inflection points and their self-rated depression is more sensitive to BMI.

Conclusion

This paper confirms a significant U-shaped trend in the association between BMI and depression. Therefore, it is important to account for the variations in this relationship across different BMI categories when using BMI to predict depression risk. Besides, this study clarifies the management goals for achieving an appropriate BMI from a mental health perspective and identifies vulnerable subgroups at higher risk of depression.

YuNü-Jian attenuates diabetes-induced cardiomyopathy: integrating network pharmacology and experimental validation

Introduction

Diabetic cardiomyopathy (DCM) is one of the most prevalent complications of diabetes with complex pathogenesis. YuNü-Jian (YNJ) is a traditional Chinese medicinal formula widely used for diabetes with hypoglycemic and cardioprotective effects. This study aims to investigate the actions and mechanisms of YNJ against DCM which has never been reported.

Methods

Network pharmacology approach was used to predict the potential pathways and targets of YNJ on DCM. Molecular docking between hub targets and active components of YNJ was performed and visualized by AutoDock Vina and PyMOL. Then type 2 diabetic model was employed and intervened with YNJ for 10 weeks to further validate these critical targets.

Results

First, a total of 32 main ingredients of YNJ were identified and 700 potential targets were screened to construct herb-compound-target network. Then 94 differentially expressed genes of DCM were identified from GEO database. After that, PPI network of DCM and YNJ were generated from which hub genes (SIRT1, Nrf2, NQO1, MYC and APP) were assessed by topology analysis. Next, functional and pathway analysis indicated that the candidate targets were enriched in response to oxidative stress and Nrf2 signaling pathway. Furthermore, molecular docking revealed strong affinity between core targets and active components of YNJ. Finally, in rats with type 2 diabetes, YNJ obviously attenuated cardiac collagen accumulation and degree of fibrosis. Meanwhile, YNJ significantly upregulated protein expression of SIRT1, Nrf2 and NQO1 in diabetic myocardium.

Discussion

Collectively, our findings suggested that YNJ could effectively ameliorate cardiomyopathy induced by diabetes possibly through SIRT1/Nrf2/NQO1 signaling.

Systematic review of precision subclassification of type 2 diabetes

Heterogeneity in type 2 diabetes presentation, progression and treatment has the potential for precision medicine interventions that can enhance care and outcomes for affected individuals. We undertook a systematic review to ascertain whether strategies to subclassify type 2 diabetes are associated with improved clinical outcomes, show reproducibility and have high quality evidence. We reviewed publications that deployed 'simple subclassification' using clinical features, biomarkers, imaging or other routinely available parameters or 'complex subclassification' approaches that used machine learning and/or genomic data. We found that simple stratification approaches, for example, stratification based on age, body mass index or lipid profiles, had been widely used, but no strategy had been replicated and many lacked association with meaningful outcomes. Complex stratification using clustering of simple clinical data with and without genetic data did show reproducible subtypes of diabetes that had been associated with outcomes such as cardiovascular disease and/or mortality. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into meaningful groups. More studies are needed to test these subclassifications in more diverse ancestries and prove that they are amenable to interventions.

Emerging Therapy for Diabetic Cardiomyopathy: From Molecular Mechanism to Clinical Practice

Diabetic cardiomyopathy is characterized by abnormal myocardial structure or performance in the absence of coronary artery disease or significant valvular heart disease in patients with diabetes mellitus. The spectrum of diabetic cardiomyopathy ranges from subtle myocardial changes to myocardial fibrosis and diastolic function and finally to symptomatic heart failure. Except for sodium–glucose transport protein 2 inhibitors and possibly bariatric and metabolic surgery, there is currently no specific treatment for this distinct disease entity in patients with diabetes. The molecular mechanism of diabetic cardiomyopathy includes impaired nutrient-sensing signaling, dysregulated autophagy, impaired mitochondrial energetics, altered fuel utilization, oxidative stress and lipid peroxidation, advanced glycation end-products, inflammation, impaired calcium homeostasis, abnormal endothelial function and nitric oxide production, aberrant epidermal growth factor receptor signaling, the activation of the renin–angiotensin–aldosterone system and sympathetic hyperactivity, and extracellular matrix accumulation and fibrosis. Here, we summarize several important emerging treatments for diabetic cardiomyopathy targeting specific molecular mechanisms, with evidence from preclinical studies and clinical trials.

Rationale and design of the Aldose Reductase Inhibition for Stabilization of Exercise Capacity in Heart Failure Trial (ARISE-HF) in patients with high-risk diabetic cardiomyopathy

BACKGROUND

Diabetic cardiomyopathy (DbCM) is a specific form of heart muscle disease that may result in substantial morbidity and mortality in individuals with type 2 diabetes mellitus (T2DM). Hyperactivation of the polyol pathway is one of the primary mechanisms in the pathogenesis of diabetic complications, including development of DbCM. There is an unmet need for therapies targeting the underlying metabolic abnormalities that drive this form of Stage B heart failure (HF).

METHODS

Aldose reductase (AR) catalyzes the first and rate-limiting step in the polyol pathway, and AR inhibition has been shown to reduce diabetic complications, including DbCM in animal models and in patients with DbCM. Previous AR inhibitors (ARIs) were limited by poor specificity resulting in unacceptable tolerability and safety profile. AT-001 is a novel investigational highly specific ARI with higher binding affinity and greater selectivity than previously studied ARIs. ARISE-HF (NCT04083339) is an ongoing Phase 3 randomized, placebo-controlled, double blind, global clinical study to investigate the efficacy of AT-001 (1000 mg twice daily [BID] and 1500 mg BID) in 675 T2DM patients with DbCM at high risk of progression to overt HF. ARISE-HF assesses the ability of AT-001 to improve or prevent decline in exercise capacity as measured by functional capacity (changes in peak oxygen uptake [peak VO₂]) over 15 (and possibly 27) months of treatment. Additional endpoints include percentage of patients progressing to overt HF, health status metrics, echocardiographic measurements, and changes in cardiacbiomarkers.

RESULTS

The ARISE-HF Trial is fully enrolled.

CONCLUSIONS

This report describes the rationale and study design of ARISE-HF.

Association of biomarkers and risk scores with subclinical left ventricular dysfunction in patients with type 2 diabetes mellitus

BACKGROUND

Subclinical LV dysfunction (LVD) identifies heart failure (HF) risk in type 2 diabetes mellitus (T2DM). We sought the extent to which clinical scores (ARIC-HF, WATCH-DM), natriuretic peptides (NTpBNP) and troponin (hs-TnT) were associated with subclinical LV dysfunction (LVD). These associations could inform the ability of these tests to identify which patients should undergo echocardiography.

METHODS

Participants with T2DM were prospectively recruited from three community-based populations. ARIC-HF risk at 4 years and WATCH-DM scores were calculated from clinical data. NTpBNP and hs-TnT were measured using an electro-chemiluminescence assay. All underwent a comprehensive echocardiogram. We calculated the sensitivity and specificity of clinical scores and biomarkers to identify abnormal global longitudinal strain (GLS ≥ -16%)), diastolic function (E/e' ≥ 14 or e' < 8 cm/s), left atrial volume index (LAV > 34 ml/m2) and LV hypertrophy (LV mass index > 88 g/m2 (F) > 102 g/m2(M)).

RESULTS

Of 804 participants (median age 69 years [inter-quartile range (IQR) 65-73], 36% female), clinical scores suggested significant HF risk (median ARIC-HF 8% [IQR 4-12]; WATCH-DM 10 points [IQR 8-12]), and the median NTpBNP was 50 pg/mL [IQR 25-101] and hs-TnT 9.6 pg/mL [IQR 6.8-13.6]. Abnormal GLS was present in 126 (17%), elevated E/e' in 114 (15%), impaired e' in 629 (78%), increased LAV in 351 (44%) and LV hypertrophy in 113 (14%). After adjustments for age, body-mass index, and renal function, each standard deviation increase in NTpBNP was associated with a GLS increase of 0.32 (p < 0.001) and hs-TnT increase by 0.26 (p < 0.001). Similar trends were observed with ARIC-HF (standardised β = 0.22, p < 0.001) and WATCH-DM (standardised β = 0.22, p < 0.001) in univariable analyses. However, none of the risk assessment tools provided satisfactory discrimination for abnormal GLS (AUC 63%), diastolic indices (e' AUC 54-61%) or LV mass (AUC 59-67%). At a sensitivity of 90%, there was an unacceptably low (< 50%) specificity.

CONCLUSION

Although risk assessment based on clinical scores or biomarkers would be desirable to stratify HF risk in people with T2DM, they show a weak relationship with subclinical LVD.

Diabetes Status Modifies the Association Between Different Measures of Obesity and Heart Failure Risk Among Older Adults: A Pooled Analysis of Community-Based NHLBI Cohorts

BACKGROUND

Obesity and diabetes are associated with a higher risk of heart failure (HF). The interrelationships between different measures of adiposity-overall obesity, central obesity, fat mass (FM)-and diabetes status for HF risk are not well-established.

METHODS

Participant-level data from the ARIC study (Atherosclerosis Risk in Communities; visit 5) and the CHS (Cardiovascular Health Study; visit 1) cohorts were obtained from the National Heart, Lung, and Blood Institute Biologic Specimen and Data Repository Information Coordinating Center, harmonized, and pooled for the present analysis, excluding individuals with prevalent HF. FM was estimated in all participants using established anthropometric prediction equations additionally validated using the bioelectrical impedance-based FM in the ARIC subgroup. Incident HF events on follow-up were captured across both cohorts using similar adjudication methods. Multivariable-adjusted Fine-Gray models were created to evaluate the associations of body mass index (BMI), waist circumference (WC), and FM with risk of HF in the overall cohort as well as among those with versus without diabetes at baseline. The population attributable risk of overall obesity (BMI≥30 kg/m²), abdominal obesity (WC>88 and 102 cm in women and men, respectively), and high FM (above sex-specific median) for incident HF was evaluated among participants with and without diabetes.

RESULTS

The study included 10 387 participants (52.9% ARIC; 25.1% diabetes; median age, 74 years). The correlation between predicted and bioelectrical impedance-based FM was high (R²=0.90; n=5038). During a 5-year follow-up, 447 participants developed HF (4.3%). Higher levels of each adiposity measure were significantly associated with higher HF risk (hazard ratio [95% CI] per 1 SD higher BMI=1.15 [1.05, 1.27], WC=1.22 [1.10, 1.36]; FM=1.13 [1.02, 1.25]). A significant interaction was noted between diabetes status and measures of BMI (P interaction=0.04) and WC (P interaction=0.004) for the risk of HF. In stratified analysis, higher measures of each adiposity parameter were significantly associated with higher HF risk in individuals with diabetes (hazard ratio [95% CI] per 1 SD higher BMI=1.29 [1.14-1.47]; WC=1.48 [1.29-1.70]; FM=1.25 [1.09-1.43]) but not those without diabetes, including participants with prediabetes and euglycemia. The population attributable risk percentage of overall obesity, abdominal obesity, and high FM for incident HF was higher among participants with diabetes (12.8%, 29.9%, and 13.7%, respectively) versus those without diabetes (≤1% for each).

CONCLUSIONS

Higher BMI, WC, and FM are strongly associated with greater risk of HF among older adults, particularly among those with prevalent diabetes.

The Diabetes-Cardiovascular Connection in Women: Understanding the Known Risks, Outcomes, and Implications for Care

PURPOSE OF REVIEW

Cardiovascular disease (CVD) complications constitute about 50-70% of mortality in people with diabetes. However, there remains a persistently greater relative increase in CVD morbidity and mortality in women with diabetes than in their male counterparts. This review presents recent evidence for the risks, outcomes, and management implications for women with diabetes.

RECENT FINDINGS

Compared to men, women have higher BMI and more adverse cardiovascular risk profile at time of diabetes diagnosis with greater risk for coronary heart disease, stroke, vascular dementia, and heart failure. Pregnancy-specific risk factors of gestational diabetes and pre-eclampsia are associated with future type 2 diabetes (T2D) and CVD. Women with T2D may experience greater benefits than men from GLP-1 receptor agonists. Women with diabetes are at greater relative risk for CVD complications than men, with poorer outcomes, superimposed on preexisting gender disparities in social determinants of health, lower likelihood of being offered cardioprotective interventions, and enrollment in trials. Further research and the utilization of SGLT-2 inhibitors, GLP-1 receptor agonists, and other CVD prevention strategies will help reduce morbidity and mortality.

Incorporation of natriuretic peptides with clinical risk scores to predict heart failure among individuals with dysglycaemia

AIMS

To evaluate the performance of the WATCH-DM risk score, a clinical risk score for heart failure (HF), in patients with dysglycaemia and in combination with natriuretic peptides (NPs).

METHODS AND RESULTS

Adults with diabetes/pre-diabetes free of HF at baseline from four cohort studies (ARIC, CHS, FHS, and MESA) were included. The machine learning- [WATCH-DM(ml)] and integer-based [WATCH-DM(i)] scores were used to estimate the 5-year risk of incident HF. Discrimination was assessed by Harrell's concordance index (C-index) and calibration by the Greenwood-Nam-D'Agostino (GND) statistic. Improvement in model performance with the addition of NP levels was assessed by C-index and continuous net reclassification improvement (NRI). Of the 8938 participants included, 3554 (39.8%) had diabetes and 432 (4.8%) developed HF within 5 years. The WATCH-DM(ml) and WATCH-DM(i) scores demonstrated high discrimination for predicting HF risk among individuals with dysglycaemia (C-indices = 0.80 and 0.71, respectively), with no evidence of miscalibration (GND P ≥0.10). The C-index of elevated NP levels alone for predicting incident HF among individuals with dysglycaemia was significantly higher among participants with low/intermediate (<13) vs. high (≥13) WATCH-DM(i) scores [0.71 (95% confidence interval 0.68-0.74) vs. 0.64 (95% confidence interval 0.61-0.66)]. When NP levels were combined with the WATCH-DM(i) score, HF risk discrimination improvement and NRI varied across the spectrum of risk with greater improvement observed at low/intermediate risk [WATCH-DM(i) <13] vs. high risk [WATCH-DM(i) ≥13] (C-index = 0.73 vs. 0.71; NRI = 0.45 vs. 0.17).

CONCLUSION

The WATCH-DM risk score can accurately predict incident HF risk in community-based individuals with dysglycaemia. The addition of NP levels is associated with greater improvement in the HF risk prediction performance among individuals with low/intermediate risk than those with high risk.