ArticleDiabetology & metabolic syndrome2026
Genetic variants associated with type 2 diabetes mellitus: a meta-analysis of Egyptian and Levant populations.
Article in Diabetology & metabolic syndrome, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundType 2 diabetes mellitus (T2DM) is a major cause of morbidity in the Middle East; however, Arab populations remain underrepresented in genomic studies. We synthesized evidence on single-nucleotide polymorphisms (SNPs) associated with T2DM risk in Egyptian and Levant (Jordan, Lebanon, Palestine, and Syria) cohorts to identify shared and population-specific loci.
methodsWe conducted a PRISMA-aligned systematic review and meta-analysis (PROSPERO CRD420251162068) of case-control genetic studies published until July 2025. Eligible studies enrolled ≥ 60 participants, reported odds ratios (ORs) with 95% confidence intervals (CIs), and satisfied the Hardy-Weinberg equilibrium in controls. Pooled effects used fixed- and random-effects models according to heterogeneity (Cochran's Q, I², and τ²). Publication bias was assessed using Egger's and Begg's tests and funnel plot symmetries. Sensitivity analyses included leave-one-out procedures and meta-regression using study-level moderators (case/control counts). Exploratory clustering and random forest models were used to examine gene/SNP features related to effect size.
resultsIn Egyptians (45 SNPs), between-study heterogeneity was negligible (Q = 35.32, df = 43, p = 0.79; I² = 0%; τ² = 0). Strong risk associations were observed for IGFB rs2854843 (OR = 13.30, p = 0.001), MTHFR rs1801133 (OR = 4.60, p = 0.001), GCKR rs780094 (OR = 3.99, p = 0.001), and TCF7L2 rs12255372 (OR = 2.06, p = 0.0001); additional signals were observed for ADIPOQ and KCNJ11. Egger's test suggested minor small-study effects (p = 0.0184), whereas Begg's test did not (p = 0.721). Meta-regression indicated that larger case counts and smaller control counts were associated with inflated ORs (R² ≈ 0.15). In the Levant cohort (29 SNPs), heterogeneity was high (Q = 302.32, df = 28, p < 0.0001; I² = 90.7%). Notable loci included NAT2 rs1799931 (OR = 13.72, p = 0.043) and SH2B1 rs565131715 (OR = 7.55), with lower magnitude associations for ADIPOQ and KCNQ1. No significant publication bias was detected.
conclusionsEgyptian findings revealed consistent large-effect SNP associations with T2DM, whereas Levant populations showed variable context-dependent effects. Shared markers (TCF7L2, ADIPOQ, and KCNJ11) and population-specific candidates (IGFB, NAT2, and SH2B1) may inform targeted screening and risk stratification. Harmonized, adequately powered multicenter studies are needed to validate these findings and accelerate precision medicine in underrepresented Arab populations.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.