Novel Therapeutics for Type 2 Diabetes Mellitus-A Look at the Past Decade and a Glimpse into the Future.

Cardiovascular disease (CVD) and kidney disease are the main causes of morbidity and mortality in type 2 diabetes mellitus (T2DM). Globally, the incidence of T2DM continues to rise. A substantial increase in the burden of CVD and renal disease, alongside the socioeconomic implications, would be anticipated. Adopting a purely glucose-centric approach focusing only on glycemic targets is no longer adequate to mitigate the cardiovascular risks in T2DM. In the past decade, significant advancement has been achieved in expanding the pharmaceutical options for T2DM, with novel agents such as the sodium-glucose cotransporter type 2 (SGLT2) inhibitors and glucagon-like peptide receptor agonists (GLP-1 RAs) demonstrating robust evidence in cardiorenal protection. Combinatorial approaches comprising multiple pharmacotherapies combined in a single agent are an emerging and promising way to not only enhance patient adherence and improve glycemic control but also to achieve the potential synergistic effects for greater cardiorenal protection. In this review, we provide an update on the novel antidiabetic agents in the past decade, with an appraisal of the mechanisms contributing to cardiorenal protection. Additionally, we offer a glimpse into the landscape of T2DM management in the near future by providing a comprehensive summary of upcoming agents in early-phase trials.

Impact of Facilitation on Cognitive Flow in a Novel Diabetes Management Rehearsal Game for Health Professions Education: Mixed Methods, Open-Label, Superiority Randomized Controlled Trial.

BACKGROUND: Though the prevalence of diabetes is set to increase, most serious game solutions typically target patient self-management and education. Few games target health care professions education, and even fewer consider the factors that may increase their efficacies. The impact of facilitation, a prominent feature of health professions education, is examined in the context of a rehearsal-based diabetes management serious game. OBJECTIVE: In this mixed methods, open-label, superiority randomized controlled trial, we compare student performance, attitudes, and perceptions of a rehearsal-based diabetes management game for health care professionals. METHODS: Student participants were randomized into 2 groups to play a diabetes management game. The control group played the game alone, and the intervention group played the same game alongside a facilitator tasked to moderate overall challenge levels and address queries. Both groups were administered the Flow Short Scale, a 13-item measure rated on a 7-point Likert scale ranging from 1 ("not at all") to 7 ("very much") immediately after the game. Students were then invited to voluntary focus group discussions to elicit their attitudes and perceptions of the game. Findings were subject to between-group comparisons and inductive thematic analysis respectively. RESULTS: A total of 48 (26 control, 22 intervention) clinical-year undergraduates from the Lee Kong Chian School of Medicine in Singapore participated in this study, with 18 continuing to the focus group discussions. Flow Short Scale results indicated the superiority of the intervention group for overall flow (t46=-2.17, P=.04) and the absorption subdomain (t46=-2.6, P=.01). Qualitative results indicated students viewed facilitation as helpful and appropriate, and were able to identify improvable elements of the game's theoretical foundations and overall design. CONCLUSIONS: While serious games are efficacious means of rehearsing previously learned knowledge, facilitation allows for their efficiency to be greatly increased. Such increases are likely crucial in the coming years with the increased digitization of health care professions education and the prevalence of diabetes. TRIAL REGISTRATION: ClinicalTrials.gov NCT05637749; https://www.clinicaltrials.gov/study/NCT05637749.

Inflammatory risk contributes to post-COVID endothelial dysfunction through anti-ACKR1 autoantibody.

Subclinical vascular impairment can be exacerbated in individuals who experience sustained inflammation after COVID-19 infection. Our study explores the prevalence and impact of autoantibodies on vascular dysfunction in healthy COVID-19 survivors, an area that remains inadequately investigated. Focusing on autoantibodies against the atypical chemokine receptor 1 (ACKR1), COVID-19 survivors demonstrated significantly elevated anti-ACKR1 autoantibodies, correlating with systemic cytokines, circulating damaged endothelial cells, and endothelial dysfunction. An independent cohort linked these autoantibodies to increased vascular disease outcomes during a median 6.7-yr follow-up. We analyzed a single-cell transcriptome atlas of endothelial cells from diverse mouse tissues, identifying enriched Ackr1 expressions in venous regions of the brain and soleus muscle vasculatures, which holds intriguing implications for tissue-specific venous thromboembolism manifestations reported in COVID-19. Functionally, purified immunoglobulin G (IgG) extracted from patient plasma did not trigger cell apoptosis or increase barrier permeability in human vein endothelial cells. Instead, plasma IgG enhanced antibody-dependent cellular cytotoxicity mediated by patient PBMCs, a phenomenon alleviated by blocking peptide or liposome ACKR1 recombinant protein. The blocking peptide uncovered that purified IgG from COVID-19 survivors possessed potential epitopes in the N-terminal extracellular domain of ACKR1, which effectively averted antibody-dependent cellular cytotoxicity. Our findings offer insights into therapeutic development to mitigate autoantibody reactivity in blood vessels in chronic inflammation.

A digital twin model incorporating generalized metabolic fluxes to identify and predict chronic kidney disease in type 2 diabetes mellitus.

We have developed a digital twin-based CKD identification and prediction model that leverages generalized metabolic fluxes (GMF) for patients with Type 2 Diabetes Mellitus (T2DM). GMF digital twins utilized basic clinical and physiological biomarkers as inputs for identification and prediction of CKD. We employed four diverse multi-ethnic cohorts (n = 7072): a Singaporean cohort (EVAS, n = 289) and a North American cohort (NHANES, n = 1044) for baseline CKD identification, and two multi-center Singaporean cohorts (CDMD, n = 2119 and SDR, n = 3627) for 3-year CKD prediction and risk stratification. We subsequently conducted a comprehensive study utilizing a single dataset to evaluate the clinical utility of GMF for CKD prediction. The GMF-based identification model performed strongly, achieving an AUC between 0.80 and 0.82. In prediction, the GMF generated with complete parameters attained high performance with an AUC of 0.86, while with incomplete parameters, it achieved an AUC of 0.75. The GMF-based prediction model utilizing complete inputs is the standard implementation of our algorithm: HealthVector Diabetes®. We have established the GMF digital twin-based model as a robust clinical tool capable of predicting and stratifying the risk of future CKD within a 3-year time horizon. We report the correlation of GMF with basic input parameters, their ability to differentiate between future health states and medication status at baseline, and their capability to quantify CKD progression rates. This holistic methodology provides insights into patients' health states and CKD progression rates based on GMF metabolic profile differences, enabling personalized care plans.

Matrix metallopeptidase 9 contributes to the beginning of plaque and is a potential biomarker for the early identification of atherosclerosis in asymptomatic patients with diabetes.

Aims: To determine the roles of matrix metallopeptidase-9 (MMP9) on human coronary artery smooth muscle cells (HCASMCs) in vitro, early beginning of atherosclerosis in vivo in diabetic mice, and drug naïve patients with diabetes. Methods: Active human MMP9 (act-hMMP9) was added to HCASMCs and the expressions of MCP-1, ICAM-1, and VCAM-1 were measured. Act-hMMP9 (n=16) or placebo (n=15) was administered to diabetic KK.Cg-Ay/J (KK) mice. Carotid artery inflammation and atherosclerosis measurements were made at 2 and 10 weeks after treatment. An observational study of newly diagnosed drug naïve patients with type 2 diabetes mellitus (T2DM n=234) and healthy matched controls (n=41) was performed and patients had ultrasound of carotid arteries and some had coronary computed tomography angiogram for the assessment of atherosclerosis. Serum MMP9 was measured and its correlation with carotid artery or coronary artery plaques was determined. Results: In vitro, act-hMMP9 increased gene and protein expressions of MCP-1, ICAM-1, VCAM-1, and enhanced macrophage adhesion. Exogenous act-hMMP9 increased inflammation and initiated atherosclerosis in KK mice at 2 and 10 weeks: increased vessel wall thickness, lipid accumulation, and Galectin-3+ macrophage infiltration into the carotid arteries. In newly diagnosed T2DM patients, serum MMP9 correlated with carotid artery plaque size with a possible threshold cutoff point. In addition, serum MMP9 correlated with number of mixed plaques and grade of lumen stenosis in coronary arteries of patients with drug naïve T2DM. Conclusion: MMP9 may contribute to the initiation of atherosclerosis and may be a potential biomarker for the early identification of atherosclerosis in patients with diabetes. Clinical trial registration: https://clinicaltrials.gov, identifier NCT04424706.

High-Throughput Microfluidic Extraction of Platelet-free Plasma for MicroRNA and Extracellular Vesicle Analysis.

Cell-free RNAs and extracellular vesicles (EVs) are valuable biomarkers in liquid biopsies, but they are prone to preanalytical variabilities such as nonstandardized centrifugation or ex vivo blood degradation. Herein, we report a high-throughput and label-free inertial microfluidic device (ExoArc) for isolation of platelet-free plasma from blood for RNA and EV analysis. Unlike conventional inertial microfluidic devices widely used for cell sorting, a submicrometer size cutoff (500 nm) was achieved which completely removed all leukocytes, RBCs, platelets, and cellular debris based on differential lateral migration induced by Dean vortices. The single-step operation also reduced platelet-associated miRNAs (∼2-fold) compared to centrifugation. We clinically validated ExoArc for plasma miRNA profiling (39 samples) and identified a 7-miRNA panel that detects non-small cell lung cancer with ∼90% sensitivity. ExoArc was also coupled with size exclusion chromatography (SEC) to isolate EVs within 50 min with ∼10-fold higher yield than ultracentrifugation. As a proof-of-concept for EV-based transcriptomics analysis, we performed miRNA analysis in healthy and type 2 diabetes mellitus (T2DM) subjects (n = 3 per group) by coupling ExoArc and ExoArc+SEC with quantitative polymerase chain reaction (RT-qPCR) assay. Among 293 miRNAs detected, plasmas and EVs showed distinct differentially expressed miRNAs in T2DM subjects. We further demonstrated automated in-line EV sorting from low volume culture media for continuous EV monitoring. Overall, the developed ExoArc offers a convenient centrifugation-free workflow to automate plasma and EV isolation for point-of-care diagnostics and quality control in EV manufacturing.