Oxidative stress and antioxidants play an important role in obesity etiopathology. Genetic variants, including single nucleotide polymorphisms (SNPs) of the antioxidant-related genes, may impact disease risk in several populations. This preliminary study aimed to explore the association of 12 SNPs related to superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPX), glutathione-S-transferase (GST), and nitric oxide synthase (NOS) genes with obesity susceptibility in a Saudi population. A total of 384 unrelated participants, including 154 (40.1%) obese individuals, were enrolled. TaqMan OpenArray Genotyping assays were used. Six SNPs were significantly more prevalent in obese cohorts: (1) GSTM1 rs1056806*C/T; (2) SOD1 rs2234694*A; (3) SOD2 rs4880*G; (4) SOD3 rs2536512*A; (5) GPX1 rs1800668*A; (6) NOS3 rs1799983*G. Four SNPs were associated with higher obesity risk under heterozygote and dominant models for GSTM1 rs1056806 (C/T), homozygote model for SOD2 rs4880 (A/G), and homozygote and recessive models for GPX1 rs1800668 (A/G). In contrast, SOD3 rs2536512 (A/G) were less likely to be obese under heterozygote and dominant models. The CGAG, CAAA, TGGG, and CGAG combined genotypes showed a higher risk of obesity. In conclusion, the present results suggest that oxidative-stress-related genetic determinants could significantly associate with obesity risk in the study population.

Metabolic syndrome (MetS) is a worldwide public health challenge. Accumulating evidence implicates elevated serum ferritin and disruptions in iron metabolism as potential elements linked to an increased risk of MetS. This study investigates the relationship between iron homeostasis—including hepcidin levels, serum iron concentration, unsaturated iron-binding capacity (UIBC), and the hepcidin/ferritin (H/F) ratio—and MetS. In this descriptive cross-sectional study, 209 participants aged 24–70 were categorized into two groups: 103 with MetS and 106 without MetS. All participants underwent medical assessment, including anthropometric measures, indices of glycemic control, lipid profiles, and iron-related parameters. Participants were further stratified by the Homeostasis Model Assessment—Insulin Resistance index into three subgroups: insulin-sensitive (IS) (1.9 to 2.9). Notable increments in serum ferritin and hepcidin were observed in the SIR group relative to the IS and EIR groups, with a significant association between metabolic parameters. The UIBC and serum ferritin emerged as significant predictors of MetS, particularly in men, with an area under the curve (AUC) of 0.753 and 0.792, respectively (p ≤ 0.001). In contrast, hepcidin was notably correlated with MetS in women, with an AUC of 0.655 (p = 0.007). The H/F ratio showed superior predictive capability for MetS across both sexes (at cutoff level = 0.67). Among women, this ratio had an AUC of 0.639 (p = 0.015), and for men, it had an AUC of 0.792 (p < 0.001). Hypertension proved an independent risk factor for MetS, affirming its role in metabolic dysregulation. The findings highlight a significant interconnection between iron homeostasis parameters and MetS, with sex-specific variations underscoring the importance of personalized diagnostic criteria. The crucial role of the H/F ratio and the UIBC as emerging predictive markers for MetS indicates their potential utility in identifying at-risk individuals. Further longitudinal research is essential to establish causality and explore the interplay between these biomarkers and MetS.

Type 2 diabetes mellitus (T2DM) is a multifactorial disease with a high global incidence. Hypertriglyceridemia is a major risk factor for both cardiovascular disease and T2DM. In this study, we determined the allele and genotype frequencies of apolipoprotein A5 (APOA5) single nucleotide polymorphism (SNP) rs662799 and perilipin 1 (PLIN1) SNPs rs894160, rs6496589, and rs1052700 and evaluated their association with T2DM risk in western Saudis. Only rs6496589 was found to be significantly associated with T2DM risk. We determined the risk allele for each SNP based on relative risk, and found that the G allele of rs662799, T allele of rs894160, G allele of r6496589, and T allele of rs1052700 correlated with T2DM risk. The effect of each SNP on T2DM risk and five of its clinical phenotypes was explored using multiple logistic regression. We found significant correlations between the C/G and G/G genotypes of rs6496589 and T2DM risk in the unadjusted model, whereas G/G was the only genotype that correlated with the risk of T2DM in the adjusted model. There was no significant correlation between rs662799, rs894160, and rs1052700 genotypes and T2DM risk. In conclusion, we have identified novel risk alleles and genotypes that contribute to genetic risk for T2DM in the western Saudi population.