Metabolic syndrome (MetS) is one of the most important risk factors for cardiovascular disease. The 11p23.3 chromosomal region plays a potential role in the pathogenesis of MetS. The present study aimed to assess the association between 18 single nucleotide polymorphisms (SNPs) located at the BUD13, ZPR1, and APOA5 genes with MetS in the Tehran Cardio-metabolic Genetics Study (TCGS). In 5421 MetS affected and non-affected participants, we analyzed the data using two models. The first model (MetS model) examined SNPs' association with MetS. The second model (HTg-MetS Model) examined the association of SNPs with MetS affection participants who had a high plasma triglyceride (TG). The four-gamete rules were used to make SNP sets from correlated nearby SNPs. The kernel machine regression models and single SNP regression evaluated the association between SNP sets and MetS. The kernel machine results showed two sets over three sets of correlated SNPs have a significant joint effect on both models (p < 0.0001). Also, single SNP regression results showed that the odds ratios (ORs) for both models are almost similar; however, the p-values had slightly higher significance levels in the HTg-MetS model. The strongest ORs in the HTg-MetS model belonged to the G allele in rs2266788 (MetS: OR = 1.3, p = 3.6 × 10–7; HTg-MetS: OR = 1.4, p = 2.3 × 10–11) and the T allele in rs651821 (MetS: OR = 1.3, p = 2.8 × 10–7; HTg-MetS: OR = 1.4, p = 3.6 × 10–11). In the present study, the kernel machine regression models could help assess the association between the BUD13, ZPR1, and APOA5 gene variants (11p23.3 region) with lipid-related traits in MetS and MetS affected with high TG.

Type 2 diabetes (T2D) is emerging as one of the serious public health issues in both developed and developing counties. Here, we surveyed the worldwide population differentiation in T2D-associated variants and assessed the genetic burden of the disease in an ongoing Tehran Cardio-Metabolic Genetic Study (TCGS) cohort represented the Iranian population. We found multiple SNPs that were significantly depleted or enriched in at least one of the five populations of 1,000 Genome Project (African, American, East Asian, European, and South Asian) as well as the Iranian population. Interestingly, TCF7L2, a well-known associated gene with T2D, harbors the highest number of enriched risk alleles almost in all populations except for East Asian, where this gene embraces the largest number of significantly depleted risk alleles. The polygenic risk score (PRS) of the enriched risk alleles was calculated for 1,867 diabetic and 2,855 non-diabetic participants in the TCGS cohort, interestingly demonstrating that the risk of developing T2D was almost two times higher in top PRS quintile compared with the lowest quintile after adjusting for other known risk factors. Type 2 diabetes (T2D) is one of the major life-threatening diseases globally, accounting for 4.2 million deaths worldwide in 2019 as assessed by International Diabetes Federation (IDF) consortium 1,2. According to the IDF report, among 20 countries belongs to the Middle East and North Africa (MENA) region, Iran is ranked third with the highest number of adults (5.4 million) who suffered from diabetes. The prevalence of diabetes in Iran's adult population was 11.4% in 2014, estimating 9.2 million Iranian individuals will have diabetes by the year 2030 3. Type 2 diabetes is a common multifactorial metabolic disease, resulting from both genetic and non-genetic (environmental) factors. The heritability of T2D ranges from 20 to 80%, suggesting the considerable role of genetic factors in the development of T2D; the heritable component of the disease is polygenic where many genes and their variants contribute to an enhanced risk of T2D development 4. The advent of high-throughput genotyping technologies has created a significant breakthrough in understanding the underlying genetic components of complex diseases, including T2D. A large number of common and low-frequency T2D susceptibility variants have been characterized by the genome-wide association studies (GWAS) and the whole-genome sequencing 5-9. Most of these variants are located near genes that were previously known to be involved in diabetes pathogenesis, such as TCF7L2, CDKAL1, CDKN1C, and IGF2BP2 10. Among them, TCF7L2 is responsible for the largest proportion of the T2D-associated variance in the various ethnic groups 11. TCF7L2 encodes a transcription factor played a central role in the Wnt signaling pathway to regulate glucose homeostasis 12. Since not all individuals are equally affected by type 2 diabetes through the unhealthy lifestyle and some are more sensitive than others, the corresponding genetic variants ...

Background Obesity is a major public health concern in developed and even developing countries worldwide. Adiponectin is a protein secreted by adipose tissue that modulates many metabolic processes and plays a vital role in obesity. This study aimed to determine the association of four variants of the ADIPOQ gene with serum adiponectin, cortisol levels and obesity status. Methods This case-control study was performed on 164 obese individuals compared by 156 control from the Tehran Lipid and Glucose Study (TLGS). Standard procedures obtained anthropometric measures and metabolic parameters. Cortisol and adiponectin levels were measured by ELISA method. rs1501299, rs266729, rs17300539, and rs17366743 on the ADIPOQ gene were genotyped using the PCR-RFLP. The correlation between adiponectin gene SNPs and obesity were calculated by Additive, dominant, and recessive genetic models. Pearson’s or Spearman’s found correlations between adiponectin levels and metabolic and anthropometric variables. Data were analyzed using SPSS software Version 20. Results Adiponectin and cortisol levels were significantly lower in obese subjects compared to the control group (p < 0.05). There was a significant negative correlation between serum adiponectin level and BMI, waist circumference (WC), waist-hip ratio, hip circumference (HC), Fasting blood sugar (FBS) Triglyceride (TG), Total cholesterol (TC), Systolic blood pressure (SBP), Diastolic blood pressure (DBP) (r = − 0.147, r = − 0.324, r = 0.371, r = − 0.179, r = − 0.299, r = − 0.277, r = − 0.041, r = − 0.134, and r = − 0.149, respectively). A positive correlation was found between adiponectin and high-density lipoprotein cholesterol (HDL-C) (r = 0.29), but no significant correlations were found between adiponectin and Low-density lipoprotein cholesterol(LDL-C) and cortisol. ADIPOQ variant rs1501299 was significantly associated with cortisol levels in subjects with BMI ≥ 25 (P-value =0.039). Conclusions Adiponectin and cortisol levels were associated with obesity. No ADIPOQ gene variants and haplotypes were associated with cortisol, Adiponectin, and obesity.

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Context: The relationship between polymorphisms in the location of the cytokine tumor necrosis factor (TNF-α) and lung cancer has been investigated in many studies. Accordingly, the present meta-analysis study focused on the relationship between the TNF-α-238 gene polymorphisms and lung cancer. Methods: Articles were collected from Google Scholar, Scopus, and PubMed electronic databases until 2022. The articles were searched based on the keywords “Lung cancer,” “238 Gene”, and “tumor necrosis factor.” The articles were selected based on the PRISMA flow diagram. Results: There was no bias in this study research. Two except for two studies were significantly different, while no significant difference was found in the other studies. However, the results of the final Overall OR with a value of (0.66; 1.88) OR = 1.11 indicate that the additive model in the TNF-α-238 (rs361525) SNP increases the risk of lung cancer in the random model (P < 0.01). Conclusions: The results of this meta-analysis study show the relationship between TNF-a-238 and lung cancer. The TNF-a-238 polymorphism increases the risk allele, and TNF-a-238 with an OR = 1.11 has an additive effect on lung cancer development and increases the risk of lung cancer.