Journal of Diabetes最新文献

Background

India ranks second in the global diabetes epidemic, with about 89 million individuals living with Type 2 diabetes mellitus (T2DM). We compared the efficacy and safety of fixed-dose combination (FDC) of glimepiride, voglibose, and extended-release metformin (GLIME+VOGLI+MET-ER) with voglibose and metformin (VOGLI+MET) and glimepiride and metformin (GLIME+MET).

Methods

A Phase IV, randomized, open-label, active-controlled study was performed in adult patients with T2DM poorly controlled with metformin. Patients received twice daily doses of GLIME+VOGLI+MET-ER (1 + 0.2 + 500 mg: Trivolib 1, 2 + 0.2 + 500 mg: Trivolib 2); or VOGLI+MET (0.2 + 500 mg, 0.3 + 500 mg) or GLIME+MET (1 + 500 mg, 2 + 500 mg). The primary endpoint was the change in HbA1c from baseline.

Results

Of the 458 patients screened, 399 were randomized (GLIME+VOGLI+MET-ER [n = 133], VOGLI+MET (n = 135), and GLIME+MET [n = 131]). The mean baseline HbA1c was ~8.35% (~67.77 mmol/mol). All the treatments showed a significant reduction in HbA1c at Weeks 12 and 24. Mean change in % (mmol/mol) HbA1c was significantly more with GLIME+VOGLI+MET-ER versus VOGLI+MET and GLIME+MET at Week 12 (−1.02 ± 0.60 [−11.2 ± 6.52] vs. −0.68 ± 0.64 [−7.49 ± 6.95], p < 0.001 and −0.88 ± 0.49 [−9.65 ± 5.34], p = 0.0154) and Week 24 (−1.57 ± 0.74 [−17.2 ± 8.14] vs. −1.11 ± 0.80 [−12.2 ± 8.79], p < 0.001 and −1.28 ± 0.60 [−14.0 ± 6.56], p = 0.0002). Overall, 49 adverse events (AEs) were reported in 32/399 (8.0%) patients. One patient each in GLIME+VOGLI+MET-ER and VOGLI+MET groups had level 1 hypoglycemia requiring no management. No severe or serious AEs were reported.

Conclusions

In adult patients with T2DM inadequately controlled on metformin monotherapy, GLIME+VOGLI+MET-ER demonstrated superior HbA1c reduction compared with VOGLI+MET and GLIME+MET at Weeks 12 and 24. Study medications were safe and well-tolerated.

Trial Registration: Clinical Trial Registry India—CTRI/2020/11/029080 [Registered on: 12/11/2020].

Background

The genetic basis of cardiovascular-kidney-metabolic syndrome (CKMs) involves complex pleiotropy, necessitating analytical approaches capable of dissecting shared genetic architectures across multiple cardiometabolic traits.

Methods

We employed genomic structural equation modeling (genomic SEM) to integrate summary statistics from six cardiometabolic traits. The model was assessed using standard fit indices. Genome-wide association analyses were performed on 1,862,425 SNPs under stringent quality control measures, with LD Score regression applied to evaluate polygenic heritability and confounding bias. Novel loci were identified using GWAS-by-Subtraction. Functional characterization included transcriptome-wide association analysis (TWAS), fine-mapping, pathway enrichment analysis, and cell-type specificity analysis.

Results

The genomic SEM model demonstrated excellent fit (CFI = 0.99, SRMR = 0.14). Quality control metrics confirmed that genomic inflation (Lambda GC = 1.591) was primarily attributable to polygenic heritability (h² = 0.3286 ± 0.0135) rather than population stratification (Intercept = 1.0176 ± 0.0169). This framework identified 2,212 significantly associated variants, encompassing 32 novel loci discovered via GWAS-by-Subtraction. Functional annotation indicated that the majority of these loci were located in intronic (57.92%) or intergenic (30.6%) regions. TWAS and fine-mapping nominated 188 high-confidence genes; SENP2 (TWAS Z = 12.5), KIF11 (Z = 11.5), and JAZF1 (Z = 11.38) exhibited the strongest positive associations with CKMs risk, whereas TCF7L2 (Z = −13.4) demonstrated the strongest inverse association. Pathway enrichment implicated lipid balance and ubiquitin-mediated proteolysis, and cell-type specificity analysis prominently localized genetic signals to pancreatic islet cells. Fine-mapping prioritized 18 causal variants with posterior probability ⟩ 0.95, including key signals within GCKR (rs1260333, rs780093) and INADL (rs2481665). Chromosomal regions 7 and 12 exhibited significant contributions.

Conclusions

Our study unravels the shared genetic architecture of CKMs, revealing novel risk loci and pathogenic mechanisms. The results establish a direct cellular link between the pleiotropic genetic basis of CKMs and endocrine metabolic regulation within pancreatic islets.