Genetic risk score (GRS) constructed from polymorphisms in the PON1, IL-6, ITGB3, and ALDH2 genes is associated with the risk of coronary artery disease in Pakistani subjects

Abstract

BackgroundCoronary artery disease (CAD) is a major killer in today’s world. Pakistan is also affected by this non-communicable disease like other countries. It is a multifactorial disease and is influenced by many gene-gene and gene-environment interactions.MethodsA total of 623 (219 controls, 404 cases) Pakistani subjects were genotyped for four SNPs, rs662 (PON1), rs5918 (ITGB3), rs671 (ALDH2), rs1800795 (IL-6) by PCR-RFLP. Various anthropometric parameters were noted and serum lipid profile was measured using commercially available kits. Statistical analysis was done by SPSS version 22. A Genetic Risk Score (GRS) was calculated from individual SNPs. The association of the SNPs and the GRS with CAD was checked using logistic regression.ResultsThe results showed that the risk allele frequencies of all variants were higher in the cases than the controls, however the difference was not statistically significant association (p > 0.0125). The mean GRS in the controls was 3.99 ± 1.42 and in cases, it was 4.29 ± 1.39, the difference between the groups was significant (p = 0.0109). logistic regression of individual SNPs and GRS with the CAD showed that independent SNPs were not significantly associated with the CAD however, the GRS had a strong association (p = 1.4 × 10− 4). The subjects were divided into three groups based on GRS (Gp 1 with GRS 0–2, Gp 2 with GRS 3–5 and Gp 3 with GRS 6–8). The analysis of the effect of the individual SNPs and GRS groups on different lipid profile parameters revealed no significant association of any of the tested SNPs with any lipid parameter, however, the GRS groups showed marginally significant for TC and highly significant association for TG, LDL-c and HDL-c.ConclusionIn conclusion, use of a GRS can provide better information than individual SNPs. The larger the number of the SNPs included in the analysis, the better would be the risk prediction.

The effect of polymorphisms (174G> C and 572C> G) on the Interleukin-6 gene in coronary artery disease: a systematic review and meta-analysis

“…Cardiovascular diseases are known to be a top cause of human mortality worldwide. Studies have shown that cardiovascular disorders are more likely to cause death in the general population than other diseases such as infectious diseases, maternal and infant diseases, nutritional disorders, and cancers [1][2][3][4]. The mortality rate from cardiovascular diseases is reported to be 45% [5].…”

Machine learning-based genetic diagnosis models for hereditary hearing loss by the GJB2, SLC26A4 and MT-RNR1 variants

“…GRS is a summation of genotypic scores of disease-associated variants combining the genetic effects of multiple causal variants [23] . It is currently widely used in various diseases, and single nucleotide polymorphism (SNP) is often used as a genetic susceptibility factor for risk assessment [ 24 , 25 ]. In order to correspond to the machine learning model, in addition to SNPs, we also included the pathogenic sites as genetic susceptibility factors in our study.…”

Genetic Risk Score for Coronary Heart Disease: Review

“…For each individual SNP, no statistically significant associations with CHD were found, in contrast to the GRS constructed from them ( p = 1.4 × 10 −4 ). Nevertheless, those authors note that a panel of SNPs included in a GRS should be designed carefully, in particular, the predisposition to the disease in different ethnic groups should be taken into consideration [ 76 ].…”