Finding no head-to-head research evaluating the cardiovascular and renal benefits of sodium-glucose cotransporter 2 inhibitors (SGLT-2i) and glucagon-like peptide 1 receptor agonists (GLP-1RA) in patients with type 2 diabetes (T2D) at different baseline renal function, we performed a network meta-analysis to compare the two drugs indirectly. Systematic literature searches were conducted of the PubMed, Cochrane Library, Web of Science, and Embase databases, covering their inception until 7 January 2025. Randomized controlled trials (RCTs) comparing the effects of SGLT-2i and GLP-1RA in T2D with different glomerular filtration rates (eGFRs) were selected. Results were reported as risk ratios (RRs) with corresponding 95% CIs. Finally, 10 RCTs involving 87,334 patients with T2D were included. In patients with an eGFR >90 mL/min/1.73 m2, GLP-1RA exhibited a superior ability to reduce the risk of all-cause death compared with SGLT-2i (RR 0.75; 95% CI 0.58, 0.97), but it was less effective in reducing the risk of renal outcome (RR 1.80; 95% CI 1.15, 2.84) in patients with an eGFR 60-90 mL/min/1.73 m2. Conversely, in patients with eGFR 30-60 and 60-90 mL/min/1.73 m2, GLP-1RA did not show an advantage in reducing the risk of hospitalization for heart failure (RR 1.87 [95% CI 1.15, 3.04] and 1.37 [95% CI 1.05, 1.78], respectively).

The prevalence of type 2 diabetes (T2D) poses a significant health challenge, yet the contribution of air pollutants to T2D epidemics remains under-studied. Several studies demonstrated a correlation between exposure to volatile organic compounds (VOCs) in indoor/outdoor environments and T2D. Here, we conducted the first meta-analysis, establishing a robust association between exposure to benzene, a prevalent airborne VOC, and insulin resistance in humans across all ages. We used a controlled benzene exposure system, continuous glucose monitoring approach, and indirect calorimetry in mice, to investigate the underlying mechanisms. Following exposure, disruptions in energy homeostasis, accompanied by modifications in the hypothalamic transcriptome and alterations in insulin and immune signaling, were observed exclusively in males, leading to a surge in blood glucose levels. In agreement, RNA sequencing of microglia revealed increased expression of genes associated with immune response and NF-κB signaling. Selective ablation of IKKβ in immune cells (Cx3cr1GFPΔIKK) or exclusively in microglia (Tmem119ERΔIKK) in adult mice alleviated benzene-induced gliosis, restored energy homeostasis and hypothalamic gene expression, and protected against hyperglycemia. We conclude that the microglial NF-κB pathway plays a critical role in chemical-induced metabolic disturbances, revealing a vital pathophysiological mechanism linking exposure to airborne toxicants and the onset of metabolic diseases.

Proteomics has been used to study type 2 diabetes, but the majority of available data are from White participants. Here, we extend prior work by analyzing a large cohort of self-identified African Americans in the Jackson Heart Study (n = 1,313). We found 325 proteins associated with incident diabetes after adjusting for age, sex, and sample batch (false discovery rate q < 0.05) measured using a single-stranded DNA aptamer affinity-based method on fasting plasma samples. A subset was independent of established markers of diabetes development pathways, such as adiposity, glycemia, and/or insulin resistance, suggesting potential novel biological processes associated with disease development. Thirty-six associations remained significant after additional adjustments for BMI, fasting plasma glucose, cholesterol levels, hypertension, statin use, and renal function. Twelve associations, including the top associations of complement factor H, formimidoyltransferase cyclodeaminase, serine/threonine-protein kinase 17B, and high-mobility group protein B1, were replicated in a meta-analysis of two self-identified White cohorts-the Framingham Heart Study and the Malmö Diet and Cancer Study-supporting the generalizability of these biomarkers. A selection of these diabetes-associated proteins also improved risk prediction. Thus, we uncovered both novel and broadly generalizable associations by studying a diverse population, providing a more complete understanding of the diabetes-associated proteome.