In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (FROH) for >1.4 million individuals, we show that FROH is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: FROH equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44–66%] in the odds of having children. Finally, the effects of FROH are confirmed within full-sibling pairs, where the variation in FROH is independent of all environmental confounding.

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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.

High blood pressure is the heritable risk factor for cardiovascular and kidney diseases. Genome-wide association studies(GWAS) on blood pressure traits increase our understanding of its underlying genetic basis. However, a large proportion of GWAS was conducted in Europeans, and some roadblocks deprive other populations to benefit from their results. Iranians population with a high degree of genomic specificity has not been represented in international databases to date, so to fill the gap, we explored the effects of 652,919 genomic variants on Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), and Hypertension (HTN) in 7694 Iranian adults aged 18 and over from Tehran Cardiometabolic Genetic Study (TCGS). We identified consistent signals on ZBED9 associated with HTN in the genome-wide borderline threshold after adjusting for different sets of environmental predictors. Moreover, strong signals on ABHD17C and suggestive signals on FBN1 were detected for DBP and SBP, respectively, while these signals were not consistent in different GWA analysis. Our finding on ZBED9 was confirmed for all BP traits by linkage analysis in an independent sample. We found significant associations with similar direction of effects and allele frequency of genetic variants on ZBED9 with DBP (genome-wide threshold) and HTN (nominal threshold) in GWAS summary data of UK Biobank. Although there is no strong evidence to support the function of ZBED9 in blood pressure regulation, it provides new insight into the pleiotropic effects of hypertension and other cardiovascular diseases.

In recent decades, ongoing GWAS findings discovered novel therapeutic modifications such as whole-genome risk prediction in particular. Here, we proposed a method based on integrating the traditional genomic best linear unbiased prediction (gBLUP) approach with GWAS information to boost genetic prediction accuracy and gene-based heritability estimation. This study was conducted in the framework of the Tehran Cardio-metabolic Genetic study (TCGS) containing 14,827 individuals and 649,932 SNP markers. Five SNP subsets were selected based on GWAS results: top 1%, 5%, 10%, 50% significant SNPs, and reported associated SNPs in previous studies. Furthermore, we randomly selected subsets as large as every five subsets. Prediction accuracy has been investigated on lipid profile traits with a tenfold and 10-repeat cross-validation algorithm by the gBLUP method. Our results revealed that genetic prediction based on selected subsets of SNPs obtained from the dataset outperformed the subsets from previously reported SNPs. Selected SNPs’ subsets acquired a more precise prediction than whole SNPs and much higher than randomly selected SNPs. Also, common SNPs with the most captured prediction accuracy in the selected sets caught the highest gene-based heritability. However, it is better to be mindful of the fact that a small number of SNPs obtained from GWAS results could capture a highly notable proportion of variance and prediction accuracy.

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OBJECTIVES: Cigarette smoking is an established, strong, and modifiable risk factor for coronary heart disease (CHD). However, little research has investigated CHD risk in former smokers who continue to be exposed to others’ cigarette smoke (former & secondhand smokers).METHODS: In the Tehran Lipid and Glucose Study, a prospective population-based cohort (n=20,069) was followed up for a median period of 14.6 years. A subset of 8,050 participants of 30 years of age and older was analyzed, with first CHD events as the study outcome. Participants were categorized as never, former, current, secondhand, and former & secondhand smokers. Data on smoking intensity (cigarette/d) were also collected. A Cox proportional hazards regression model was applied to estimate the risk of CHD, taking into account the main potential confounders.RESULTS: The mean age of participants was 46.10 ±11.38 years, and they experienced 1,118 first CHD events (with most CHD cases in former smokers) during the follow-up period. The risk of CHD was highest in current smokers, followed in order by former & secondhand, former, and secondhand smokers (hazard ratio [HR], 1.99; 95% confidence interval [CI], 1.65 to 2.39; HR, 1.55; 95% CI, 1.15 to 2.08; HR, 1.39; 95% CI, 1.12 to 1.72; HR, 1.27; 95% CI, 1.07 to 1.51, respectively), compared to never smokers. The risk of CHD increased with smoking intensity, which has been proposed as a preferable measure of smoking, indicating a dose-response pattern.CONCLUSIONS: The elevated risk of CHD in former & secondhand smokers was a noteworthy finding, with possible implications for health policy; however, further research is needed.