The Relationship Between Tumor Necrosis Factor-Alpha (-308G/A, +488G/A, -857C/T, and -1031T/C) Gene Polymorphisms and Risk of Intracerebral Hemorrhage in the North Indian Population: A Hospital-Based Case-Control Study
Correspondence Address: Source of Support: None, Conflict of Interest: None DOI: 10.4103/0028-3886.279665
Source of Support: None, Conflict of Interest: None
Keywords: Cytokine, inflammatory gene, intracerebral hemorrhage, single nucleotide polymorphisms, stroke, tumor necrosis factor-alphaKey Messages: Tumour Necrosis Factor Alpha (TNF-α) +488G/A polymorphism is an important risk factor for ICH in the North Indian population and may be used as a genetic marker for identifying individuals at increased risk for developing ICH.
Stroke is the major leading cause of morbidity and mortality worldwide. The estimated prevalence of stroke in India ranges from 44 to 843 per 100,000 population. Intracerebral hemorrhage (ICH) accounts for 15–20% of stroke, and its pathophysiology is regulated by a combination of lifestyle, environmental, and unclear genetic risk factors. Inflammation and genetics are both prominent mechanisms in the pathogenesis of ICH.,,,,, Tumor necrosis factor-alpha (TNF-α) is one of the main proinflammatory cytokines and it plays a central role in initiating and regulating the cascade of events leading to an inflammatory response. The TNF-α gene is located on 6p21.3, which consists of four small exons and encodes the protein of 233 amino acid residues. TNF-α exerts several long-term effects, including developmental regulation of the immune system and tumor proliferation. Studies in experimental animals have shown several properties of TNF-α, including modulation of the blood–brain barrier, reduction in tissue water diffusion, regulation of cerebral blood flow, inflammatory response, and activation of blood coagulation, that may be of relevance for the pathogenesis of ICH. Therefore, TNF-α is an important candidate gene for stroke. Genetic screening has revealed four polymorphic regions (-308G/A, +488G/A, -857C/T, and -1031T/C)in the promoter region of TNF-α gene.
Few studies have been conducted for investigating the association between TNF-α gene polymorphism and the risk of hemorrhagic stroke in multiple ethnicities.,,,, To our knowledge, no information is available from North India on the association between these four single nucleotide polymorphisms (SNPs) and the risk of ICH. Hence, this case-control study was undertaken to investigate the association of -308G/A, +488G/A, -857C/T, and -1031T/C polymorphisms in TNF-α gene with the risk of ICH.
This was a hospital-based case-control study and was completed in one and a half years (October 2013 to April 2015). The study was conducted in the Department of Neurology, All India Institute of Medical Sciences (AIIMS), New Delhi in collaboration with the Institute of Genomics and Integrative Biology (IGIB), New Delhi. All participants underwent standardized clinical evaluations. The study was approved by the Local Institutional Ethics Committee. Informed consent was obtained from each patient/control or from the relatives or a legal authorized representative in the case of critically disabled patients. Inclusion and exclusion criteria for cases and controls and definition of variables were the same, as reported in a previously published study.
DNA isolation and genotyping
Four milliliter (ml) venous blood samples were collected from ICH patients and controls in a tube containing ethylenediamine tetraacetic acid (EDTA). Genomic DNA was isolated from whole blood through the standard phenol-chloroform method. The primers were designed for the four selected SNPs using the Primer3 online tool, (http://bioinfo.ut.ee/primer3-0.4.0/). The TNF-α regions were amplified in T-100 thermal cycler (Bio-Rad) using the primer sequences; the conditions for polymerase chain reaction (PCR) are listed in [Table 1]. PCR amplified products were purified using polyethylene glycol (PEG), and standard cycling conditions were used for SNaPshot reaction. The SNaPshot reaction was set using 0.8 μl of 5× dilution buffer (200 mM Tris; pH 9.0; 5 mM Mgcl2), 0.5 μl of SNaPshot ready reaction mix, 2.0 μl of SNaPshot primer (2pm/μl), and milliQ water to make up the volume to 5 μl. One μl of the SNaPshot products were mixed with 10 μl of HiDi formamide and loaded on 3130xl automated DNA sequencer (Applied Biosystems).
Conditional logistic regression analysis was used to estimate odds ratio (OR) and 95% confidence intervals (CIs) for the strength of association between TNF-α gene polymorphisms and risk of ICH. Multivariate logistic regression was used to control the confounding effects of demographic and risk factor variables. The Chi-square test was used to determine whether the allelic frequencies were in accordance with the Hardy–Weinberg equilibrium (HWE). Tests were considered significant at P < 0.05. Data was analyzed using STATA, version 13.0 (StataCorp. 2013. Stata Statistical Software: Release 13. College Station, TX: StataCorp LP). Haplotypes were reconstructed by PHASE 2.0 (Stephens M et al., 2001), and patterns of linkage disequilibrium (LD) were performed using HaploView 4.2 software. The threshold value of the frequencies of the haplotypes included in the analysis was set at 2%.
One hundred ICH cases and 100 age and sex-matched ICH-free controls were recruited in the study. The mean age of ICH patients was 50.56 ± 11.58 years and that of the control group was 50.50 ± 11.46 years; both the groups consisted of 74 males and 26 females. Risk factor variables such as history of hypertension (cases 42.0% vs controls 18.0%), diabetes (cases 25.0% vs controls 9.0%), smoking (cases 20.0% vs controls 5.0%), alcohol intake (cases 19.0% vs controls 14%), dyslipidemia (cases 17.0% vs controls 5.0%), and low socioeconomic status (cases 23.0% vs controls 5.0%) were found significantly more often in cases than in controls (P< 0.05) [Table 2]. Out of 100 cases, 34 (34.0%) were recruited from outpatient department (OPD) and 66 (66.0%) cases were recruited from inpatient department (IPD).
All genotype and allelic frequencies were in HWE in both ICH patients and controls. Genetic analysis for TNF-α (-308G/A, +488G/A, -857C/T, and -1031T/C) gene polymorphisms were conducted for all 100 ICH cases and 100 age and sex-matched controls and are summarized in [Table 3]. TNF-α +488G/A gene polymorphism was found to be independently associated with the risk of ICH under dominant [GG + GA vs. AA] (OR = 3.1; 95% CI = 1.2–8.2; P = 0.001) and allelic [G vs. A] (OR = 2.2; 95% CI = 1.2–4.2; P = 0.007), models and borderline association was found between TNF-α -857C/T gene polymorphism and the risk of ICH under allelic (OR = 1.6; 95% CI = 0.9–2.7; P = 0.05) model. However, no significant association between -308G/A and -1031T/C gene polymorphisms and risk of ICH was observed. Haplotype analysis showed that 308A-488G-857C-1031T and 308G-488A-857T-1031T haplotypes were significantly associated with an increased risk of ICH. Strong LD was observed for + 488G/A and -857C/T TNF-α polymorphisms (D' = 0.72, r2= 0.01) [Figure 1].
The present study was the first study conducted in North India which revealed that TNF-α +488G/A gene polymorphism was significantly associated with an increased risk of ICH. Case-control genetic association studies are being used for investigating the genetic basis of complex diseases. TNF-α has been associated with an increased susceptibility to a variety of conditions characterized by inflammation including stroke. Polymorphisms in the promoter regulatory region may affect TNF-α production. These four SNPs (-308G/A, +488G/A, -857C/T, and -1031T/C) have been shown to be associated with increased TNF-α expression., The possible phenomenon that may affect the expression of TNF-α may come from substances binding to regulatory elements, such as nuclear factor κB, organic cation transporter-1, and alteration of the secondary structure of DNA to affect the accession of cis-acting transcription factor to the promoter/enhancer region of the TNF-α gene.,
ICH is a complex multifactorial disease and its genetic association has not been completely studied. Only few studies have demonstrated the association of genetic polymorphisms in the promoter region of TNF-α gene with the risk of hemorrhagic stroke. The study by Yamada et al. (2006) investigated only a single SNP (-863C/A) of TNF-α gene with the risk of both ischemic and hemorrhagic stroke, suggesting a significant association with the risk of stroke. Numerous genetic studies have been conducted regarding the risk of stroke in the Indian population and have been summarized in a recently published review article. A review published by Liu et al. (2012) highlighted the role of candidate gene polymorphisms in causing ICH risk. Recently, Kumar et al. (2014) published a case-control study which highlighted the significant role of angiotensin converting enzyme gene insertion/deletion (ACE I/D) polymorphism in causing risk of ICH in the North Indian population The author also conducted a meta-analysis which indicated that ACE I/D polymorphism might be a risk factor of ICH in the Asian population. Another study published by the same author showed a significant association of Gln27Glu polymorphism of beta-2 adrenergic receptor with the risk of ICH in the North Indian population. According to a study published by Kalita et al. (2011), ACE (rs464994) gene polymorphisms were significantly associated with the risk of ICH whereas α ADDUCIN (rs4961) was not associated with the risk of ICH in the North Indian population.
Till date, only one study performed by Chen et al. (2010) showed significant association among the four SNPs (-308G/A, -863C/A, -857C/T, and -1031T/C) of TNF-α gene and spontaneous deep ICH risk in Taiwanese population. One recent meta-analysis of 18 studies has been published depicting the association of TNF-α (-238 G/A and -308G/A), gene polymorphisms, and the risk of ischemic stroke. This meta-analysis showed a protective effect of -308G/A polymorphism of TNF-α gene with ischemic stroke, however, a significant risk was observed between the -238G/A polymorphism of TNF-α gene and risk of ischemic stroke. To our knowledge, no study till date has investigated the association between + 488G/A along with -308G/A, -857C/T, and -1031T/C polymorphisms of TNF-α gene and the risk of ICH in North Indian population.
The strength of our present study was that it provides preliminary evidence for the association between TNF-α +488G/A gene polymorphism and risk of ICH in a North Indian population. We performed an adjusted logistic regression analysis by adjusting multiple demographic and risk factor variables, including hypertension, alcohol, diabetes, dyslipidemia, migraine without aura, family history of stroke, sedentary lifestyle, and low socioeconomic status. A borderline association between TNF-α -857C/T gene polymorphism and risk of ICH under allelic (OR = 1.6; 95% CI = 0.9–2.7; P = 0.05) model was observed. A high degree of LD was observed between the two SNPs + 488G/A (rs1800610) and -857C/T (rs1799724) in our study.
However, there were a few limitations in our study. First, there was a relatively small sample size; a case-control study is not a high level of evidence for supporting the conclusion. Second, the study was conducted in a single hospital and the participants might not have been representative of different geographical areas. Third, no functional analysis was performed to understand the mechanism of association between the SNPs with stroke. Moreover, in addition to the SNPs explored in this study, several other polymorphisms may also be present which may play a role in developing atherosclerosis. Therefore, a larger sample size, multicenter genome-wide association studies are needed to confirm our findings. Despite these limitations, our study provides preliminary evidence for the association between TNF-α +488G/A gene polymorphism and risk of ICH in a North Indian population.
Our findings suggest that TNF-α +488G/A gene polymorphism may be an important risk factor for ICH, whereas -308G/A, -857C/T, and -1031T/C gene polymorphisms may not be associated with the risk of ICH in North Indian population.
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Conflicts of interest
There are no conflicts of interest.
[Table 1], [Table 2], [Table 3], [Table 4]