The CXCR2 Gene Polymorphism Is Associated with Stroke in Patients with Essential Hypertension

Hypertension is the major risk factor for stroke, and genetic factors contribute to its development. Inflammation has been hypothesized to be the key link between blood pressure elevation and stroke. We performed an analysis of the association between inflammatory mediator gene polymorphisms and the incidence of stroke in patients with essential hypertension (EH). The study group consisted of 625 individuals (296 patients with noncomplicated EH, 71 hypertensive patients with ischemic stroke, and 258 control subjects). Both patients and controls were ethnic Tatars originating from the Republic of Bashkortostan (Russian Federation). The analysis has shown that the risk of ischemic stroke was associated with the CXCR2 rs1126579 polymorphism. Our results indicate that among patients with EH, the heterozygous genotype carriers had a higher risk of stroke (OR = 1.72, 95% CI 1.01-2.92), whereas the CXCR2*C/C genotype was protective against stroke (OR = 0.32, 95% CI 0.12-0.83). As shown by the gene-gene interaction analysis, the CXCR2 rs1126579 polymorphism was also present in all genotype/allele combinations associated with the risk of stroke. Genetic patterns associated with stroke also included polymorphisms in the CCL2, CCL18, CX3CR1, CCR5, and CXCL8(IL8) genes, although no association between these loci and stroke was detected by individual analysis

Alu Deletions in LAMA2 and CDH4 Genes Are Key Components of Polygenic Predictors of Longevity

Longevity is a unique human phenomenon and a highly stable trait, characterized by polygenicity. The longevity phenotype occurs due to the ability to successfully withstand the age-related genomic instability triggered by Alu elements. The purpose of our cross-sectional study was to evaluate the combined contribution of ACE*Ya5ACE, CDH4*Yb8NBC516, COL13A1*Ya5ac1986, HECW1*Ya5NBC182, LAMA2*Ya5-MLS19, PLAT*TPA25, PKHD1L1*Yb8AC702, SEMA6A*Yb8NBC597, STK38L*Ya5ac2145 and TEAD1*Ya5ac2013 Alu elements to longevity. The study group included 2054 unrelated individuals aged from 18 to 113 years who are ethnic Tatars from Russia. We analyzed the dynamics of the allele and genotype frequencies of the studied Alu polymorphic loci in the age groups of young (18–44 years old), middle-aged (45–59 years old), elderly (60–74 years old), old seniors (75–89 years old) and long-livers (90–113 years old). Most significant changes in allele and genotype frequencies were observed between the long-livers and other groups. The search for polygenic predictors of longevity was performed using the APSampler program. Attaining longevity was associated with the combinations LAMA2*ID + CDH4*D (OR = 2.23, PBonf = 1.90 × 10−2) and CDH4*DD + LAMA2*ID + HECW1*D (OR = 4.58, PBonf = 9.00 × 10−3) among persons aged between 18 and 89 years, LAMA2*ID + CDH4*D + SEMA6A*I for individuals below 75 years of age (OR = 3.13, PBonf = 2.00 × 10−2), LAMA2*ID + HECW1*I for elderly people aged 60 and older (OR = 3.13, PBonf = 2.00 × 10−2) and CDH4*DD + LAMA2*D + HECW1*D (OR = 4.21, PBonf = 2.60 × 10−2) and CDH4*DD + LAMA2*D + ACE*I (OR = 3.68, PBonf = 1.90 × 10−2) among old seniors (75–89 years old). The key elements of combinations associated with longevity were the deletion alleles of CDH4 and LAMA2 genes. Our results point to the significance for human longevity of the Alu polymorphic loci in CDH4, LAMA2, HECW1, SEMA6A and ACE genes, involved in the integration systems

Multilocus associations of inflammatory genes with the risk of type 1 diabetes

BackgroundGenome-wide association studies have captured a large proportion of genetic variation related to type 1 diabetes mellitus (T1D). However, most of these studies are performed in populations of European ancestry and therefore the disease risk estimations can be inaccurate when extrapolated to other world populations.MethodsWe conducted a case-control study in 1866 individuals from the three major populations of the Republic of Bashkortostan (Russians, Tatars, and Bashkirs) in Russian Federation, using single-locus and multilocus approach to identify genetic predictors of T1D.ResultsWe found that LTA rs909253 and TNF rs1800629 polymorphisms were associated with T1D in the group of Tatars. Meta-analysis of the association study results in the three ethnic groups has confirmed the association between the T1D risk and LTA rs909253 genetic variant. LTA rs909253 and TNF rs1800629 loci were also featured in combinations most significantly associated with T1D.ConclusionOur findings suggest that LTA rs909253 and TNF rs1800629 polymorphisms are associated with the risk of T1D both independently and in combination with polymorphic markers in other inflammatory genes, and the analysis of multi-allelic combinations provides valuable insight in the study of polygenic traits

Variants of the Coagulation and Inflammation Genes Are Replicably Associated with Myocardial Infarction and Epistatically Interact in Russians.

In spite of progress in cardiovascular genetics, data on genetic background of myocardial infarction are still limited and contradictory. This applies as well to the genes involved in inflammation and coagulation processes, which play a crucial role in the disease etiopathogenesis.In this study we found genetic variants of TGFB1, FGB and CRP genes associated with myocardial infarction in discovery and replication groups of Russian descent from the Moscow region and the Republic of Bashkortostan (325/185 and 220/197 samples, correspondingly). We also found and replicated biallelic combinations of TGFB1 with FGB, TGFB1 with CRP and IFNG with PTGS1 genetic variants associated with myocardial infarction providing a detectable cumulative effect. We proposed an original two-component procedure for the analysis of nonlinear (epistatic) interactions between the genes in biallelic combinations and confirmed the epistasis hypothesis for the set of alleles of IFNG with PTGS. The procedure is applicable to any pair of logical variables, e.g. carriage of two sets of alleles. The composite model that included three single gene variants and the epistatic pair has AUC of 0.66 both in discovery and replication groups.The genetic impact of TGFB1, FGB, CRP, IFNG, and PTGS and/or their biallelic combinations on myocardial infarction was found and replicated in Russians. Evidence of epistatic interactions between IFNG with PTGS genes was obtained both in discovery and replication groups

The map of possible interactions between components of MI-associated biallelic combination <i>IFNG</i> and <i>PTGS1</i> (black circles) and ten relative partners (gray circles) generated by GeneMania online software [45].

<p>Possible physical interactions (pink), co-expression (violet), pathway (blue), genetic interactions (green), and shared protein domains (yellow) are shown. IDO1 –indoleamine 2,3–dioxygenase 1; IFNG–interferon gamma; IFNGR1 –interferon gamma receptor 1; IFNGR2 –interferon gamma receptor 2; IRF1 –interferon regulatory factor 1; MPO–myeloperoxidase; PTGIS–prostaglandin I2 (prostacyclin) synthase; PRKCD–protein kinase C delta; PTGS1 –prostaglandin–endoperoxide synthase 1; PTGS2 –prostaglandin–endoperoxide synthase 2; PTPN2 –protein tyrosine phosphatase, non–receptor type 2; PTPN6 –protein tyrosine phosphatase, non–receptor type 6.</p

ROC curves demonstrate usefulness of the additive composite model built from all identified genetic markers.

<p><b>A</b>. Comparing performance of the composite model to the performance of each single marker in the Moscow discovery sample. Combining the high specificity of <i>CRP</i> and <i>IFNG</i>+<i>PTGS</i> predictors (the left hump) with relatively high sensitivity of <i>TGFB1</i> and <i>FGB</i> (the right hump) yields a much better classifier. <b>B</b>. Performance of the model stays the same when tested on the independent replication sample (Bashkortostan).</p