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Year : 2013  |  Volume : 1  |  Issue : 1  |  Page : 3-6

SNP's and its correlation with hypertension: A comprehensive review

1 Department of Microbiology, Faculty of Medicine, Sebha University, Sebha, Libya
2 Department of Oral Pathology and Microbiology, Faculty of Dentistry, Sebha University, Sebha, Libya
3 Department of Microbiology, Kasturi Ram College, Kovilpatti, Tamil Nadu, India
4 Department of Environmental Microbiology, Annamalai University, Chidambaram, Tamil Nadu, India

Date of Web Publication14-Jan-2014

Correspondence Address:
Manohar Murugan
Department of Microbiology, Faculty of Medicine, Sebha University, Sebha
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Source of Support: None, Conflict of Interest: None

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Hypertension is a growing global problem, which mostly affects the adults. It is a risk factor for death from stroke, myocardial infarction, congestive heart failure, ischemic heart disease, peripheral vascular disease, and progressive renal damage. These diseases are responsible for considerable morbidity and high mortality rate. Human essential hypertension (EH) is a complex and multifactorial trait influenced by environmental and genetic determinants. Early detection of genetic predisposition in hypertensive patients will enable prompt treatment and avoidance of complications. The use of SNPs in genetic disease detection is facilitated by the recent discovery of more than 4 million SNPs in the human genome that have the potential to be a rich source of genetic markers to establish genetic linkage and as indicators of disease. Such genetic research will open the new frontiers in diagnosis and treatment of diseases like hypertension.

Keywords: Hypertension, single-nucleotide polymorphism, molecular genetics

How to cite this article:
Murugan M, Ramalingam K, Nazzuredin M, Rashed HA, Punamalai G. SNP's and its correlation with hypertension: A comprehensive review. Dent Med Res 2013;1:3-6

How to cite this URL:
Murugan M, Ramalingam K, Nazzuredin M, Rashed HA, Punamalai G. SNP's and its correlation with hypertension: A comprehensive review. Dent Med Res [serial online] 2013 [cited 2023 Apr 1];1:3-6. Available from: https://www.dmrjournal.org/text.asp?2013/1/1/3/124986

  Introduction Top

Hypertension affects 25% of most adult populations and is a risk factor for death from stroke, myocardial infarction and congestive heart failure. [1] It is a complex, polygenic disease in which one or more genes control the level of blood pressure. In the majority of patients with hypertension, there are no anatomic, metabolic, or endocrine derangement and described as a primary or essential hypertension (EH). At present, it is widely accepted that approximately 30-50% of cases of hypertension can arise from genetic susceptibility.

EH is a multifactorial disease. [2],[3] Among environmental factors influencing this disease, we note high dietary intake of sodium, alcohol, obesity, and stress.

Genetics of hypertension is complex, as there is no known single gene playing a major role. Many individual genes with mild effects reacting to different environmental stimuli contribute to blood pressure. Monogenic forms of hypertension provide a unique opportunity for studying the effects of single gene and identifying single pathways and mechanisms leading to blood pressure elevation. The gene locus responsible for Turkish family with autosomal dominantly inherited severe hypertension mapped on the short arm of chromosome 12. [4]

The heritable component of blood pressure documented in familial and twin studies suggesting that 30-50% of the variance of blood pressure readings is attributable to genetic heritability and about 50% to environmental factors. [5]

The Millennium Genome Project for Hypertension was started in 2000 to identify genetic variants conferring susceptibility to hypertension, pathogenesis, and to initiate genome-based personalized medical care. Two different approaches were launched, genome-wide association analysis using single-nucleotide polymorphisms (SNPs) and microsatellite markers, and systematic candidate gene analysis, under the hypothesis that common variants have an important role in the etiology of common diseases. [6]

Earlier studies in hypertension identified specific enzymes, channels, and receptors implicating sodium handling in the regulation of blood pressure. These include genes involved with the renin-angiotensin-aldosterone system controlling blood pressure and salt-water homeostasis, proteins in hormonal regulation of blood pressure like enzymes and receptors of the mineralocorticoid and glucocorticoid pathways, and proteins coded by genes involved in the structure and/or regulation of vascular tone like endothelins and their receptors. [5]

The field of molecular genetics has revolutionized the study of hypertension by identifying single gene syndromes or Mendelian forms and several candidate genes for blood pressure variance. Genes are localized to at least 20 chromosome regions. For example, recent genome-wide association studies (GWAS) of common genetic variants found 13 SNPs or variants in systolic and 20 for diastolic blood pressure readings representing different genes and genetic heterogeneity.

Role of SNPS in disease

Researchers have identified several chromosomal loci in the human genome linked to hypertension. SNPs are the most common type of DNA sequence variations that occur with alteration of a single nucleotide in the genome sequence. The presence of one SNP for every 500-1000 bases and 3-5 million SNPs in the entire human genome, with SNPs in around 500,000 gene regions. These regions still contain a large number of potential candidate genes, but genotyping methods will facilitate the detection and analysis of SNPs within these genes. These single base sequence variations occur at a frequency of approximately one SNP every 1,000 bp throughput the human genome. [7]

The high frequency of SNPs suggest that SNP genotyping will play a key role in future research aimed at identifying genetic variants involved in disease. The use of SNP will lead to a greater elucidation of the genetic basis for diseases and realize the potential for clinical diagnostics and pharmacogenetics. [8]

SNPs found within a gene may cause variation in the timing amount or function of the protein produced by that gene. SNP analysis at multiple loci can also be useful in the study of polygenic disease by targeting specific families of SNPs or by genome-wide linkage disequilibrium mapping. SNPs have evoked tremendous excitement because of the notion that they might allow identification of genes associated with complex diseases. The ultimate goal of being able to perform whole genome association studies using hundreds of thousands of SNPs in ultrahigh throughput assays is far from reality, due to the present deficit of SNPs and the lack of appropriate methods. SNPs are the most common type of human genetic variation. These single base sequence variations occur at a frequency of approximately one SNP every 1,000 bp throughput the human genome. [7]

SNPs can be of transition or transversion type. They may be responsible for the diversity among individuals, genome evolution, the most common familial traits such as curly hair, interindividual differences in drug response, and diseases such as diabetes, obesity, hypertension, and psychiatric disorders. SNPs may change the encoded amino acids (non-synonymous) or can be silent (synonymous) or simply occur in the noncoding regions. They may influence promoter activity (gene expression), messenger RNA (mRNA) conformation (stability), and subcellular localization of mRNAs and/or proteins; and hence may produce disease. Therefore, identification of numerous variations in genes and analysis of their effects may lead to a better understanding of their impact on gene function and health of an individual. This can lead to development of new, useful SNP markers for medical testing and a safer individualized treatment. [9]

SNP identification and functional assessment is an important tool in molecular diagnostics and biology. Several different genotyping approaches are in rapid development, such as fluorescence homogenous assays, pyrosequencing, real-time polymerase chain reaction (RT-PCR), and mass spectrometry. [10],[11],[12] Real-time PCR is the most used technology for detection of SNPs. [13] This assay requires only a small amount of human DNA in clinical samples. However, when the sources of DNA are samples with very small cell numbers or older samples that have not been stored under optimal conditions for DNA preservation, the amount of DNA may be too low to yield reliable SNP results with this method.

Several genes linked for hypertension include lipoprotein lipase (LPL), low-density lipoprotein (LDL), triglycerides (TG), [14],[15] ACTN-3 (actinin), [14],[16] kallikrein - KLK locus, [17],[18] angiotensin converting enzyme (ACE-2), [19] renin-angiotensin system (RAS genes), [20] angiotensinogen gene, [21] renin gene, [22] nitric oxide synthase gene (NO 3 S), [23] type B natriuretic peptide receptor (NPRB), [24] ATI gene, [25] and genes that encode folate-dependent proteins. [26]

Isaksson et al., [27] reported there are great hopes that SNPs can be used to improve radically, biological understanding, and to advance medicine. The 2 nd International SNP meeting emphasized the importance of considering population history when using SNPs to search for genetic risk factors.

Peter and Doris [28] reported the investigation of heritable susceptibility to disease is an effort to associate disease phenotype with underlying genotype. The influence of factors like locus and allelic diversity of hypertension, the weaker relationship between genotype and phenotype, the extensive role of nongenetic factors, the extent, and heterogeneous nature across the genome.

Yanbin et al., [29] investigated the association of SNPs in GNB3 gene and EH in 282 female Caucasian dizygotic twins. Regular association tests did not show a significant effect on blood pressure for any of the five SNPs. However, significant interactions between the A-350G, 825 C > T and 1429 C > T loci, and adiposity were observed for systolic blood pressure as well as diastolic blood pressure suggesting increases in adiposity amplify the effects of the SNPs on blood pressure.

Donald et al., [30] reported various methods for detection of SNPs based on fluorescence-resonance energy transfer. Foman et al., [31] investigated the effect of mutant 80A RFC allele on recumbent systolic and diastolic blood pressure. James et al., [32] identified a functional variant of the CYP4A11 20-HETE synthase and determined its association with hypertensive status in two independent human populations. The association of the T8590C variant with hypertension supports its role as a polygenic determinant of blood pressure control in humans.

Robert et al., [33] reported discovering the genes that contribute to complex polygenic diseases represent a significant challenge. Investigating the structural genetic variations associated with these disorders may not be sufficiently informative about vulnerability genes modulated by the environment. Characterizing gene expression patterns does not identify the primary differences in gene structure. The convergence of global screening of gene expression patterns with extensive structural genomic information may be necessary to identify the gene clusters that contribute to these pervasive diseases. These integrative efforts, though promising, are in their early phases and will require further refinement.

Studies on the genetic basis of hypertension have discovered multiple quantitative trait loci (QTLs) predominantly in rat models. The mouse QTLs are syntenic with the QTLs on rat chromosomes 2, 3, 8, and 18 and on predicted regions on human chromosomes 2q14-q23, 3p11-3p21.3, 3q21-q26.6, 4q25-q28, 5p14-q12, and 18q21-q23;, further suggesting conserved regions contributing to blood pressure regulation. The other genes that could be linked with hypertension are SA, SCNN1B, ANG III AT1 receptor, kKininogen, SLC2A2, FGF, ET-A receptor, aAldosterone receptor, NPY2R, FGFR2, aAnnexin, TIMP_3, IL6R, NPR1, IGF2R, SCL16A1, NRAS, TGFBR3, CALPONIN3, ECGF1, VCAM1, ADORA3, KCNA3, PTSG1, tTenascin C, DPP4, SCN2A1, ATPLG1, SLC4A2, LQT2, PPPIR3, TAC1R, JUN, CYP2UQ, AK2, JAK1, LEPR, ECE, CYP4A11, EDN2, ATP1G1, APOC3, HTR3, CYP1A1, CYP1A2, CYP11A, TPM1, PPP2R3, TGFBR2, SCNSA, NGFR, MYL4, NOS2, ATP1B2, SLC2A4, MYH3, CHRNB1, IL4, IL5, SPARC, ADRB1, C4BP, ADORA1, MYOG, ATP2B4, IL10, DAF, TNNT2, CACNA1S, TNNL, PTGS2, LAMC1, SELECTIN, APOA2, ATP1A2, EDNRB, 5HT2-receptorRECEPTOR, STATS, GLUD1, ATP4B, FGFR1, DRD1, SLC17A2, GRL1, FGF1, PDGFRB, EGR1, and ADRB2 among chromosomes 11q, 11p, 16p, 10q, 5p, 3q, 4q, 1q, 17q, 9q, 2q, 7q, 7p, 2p, 1p, 15q, 3p, 17p, 5q, 13q, 10q, 8p, and 5q. [34]

The α-actinins are a family of actin-binding and crosslinking proteins related to dystrophin, utrophin and spectrin. [16] The researchers have previously cloned and characterized two human α-actinin genes (ACTN2 and ACTN3). The two muscle specific sarcomeric isoforms, α-actinin-2 and α-actinin-3 are actin-binding proteins that constitute the predominant component of the Z-disc. Besides their mechanical role both proteins interact with proteins involved in numerous signaling and metabolic pathways.

Tabara et al., [6] identified ATP2B1 as a gene responsible for hypertension in not only Japanese but also Caucasians. The high blood pressure susceptibility conferred by certain alleles of ATP2B1 has been widely replicated in various populations. Reduced expression of this gene associated with the risk allele may be an underlying mechanism relating the ATP2B1 variant to hypertension.

Elton et al., [20] - MicroRNAs (miRNAs) are a family of small, ~21-nucleotide long, and nonprotein-coding RNAs that recognize target mRNAs through partial complementary elements in the 3'-untranslated region (3'-UTR) of mRNAs and inhibit gene expression by targeting mRNAs for translational repression or destabilization. miRNA SNPs (miRSNPs) can create, destroy, or modify miRNA binding sites and transcribed target SNPs harbored in RAS mRNAs, that alter miRNA gene regulation and consequently protein expression, may contribute to cardiovascular disease susceptibility.

Wang et al., [35] 2009, genotyped 105 simple deletions and SNPs from 64 candidate genes in 3,550 patients and 6,560 control subjects from six case-control association studies conducted in the United States, Europe, and China. Genotyping was performed using the same immobilized probe typing system and meta-analyses were based on summary logistic regressions for each study. The primary analyses were fixed-effects meta-analyses adjusting for age and sex with additive, dominant, and recessive models of inheritance. Although seven polymorphisms showed a nominal additive association, none remained statistically significant after adjustment for multiple comparisons. In contrast, after stratification for hypertension, two lymphotoxin-alpha polymorphisms, which are in strong linkage disequilibrium, were significantly associated among non-hypertensive individuals.

  Conclusion Top

A genetic screening test based on analysis of multiple SNPs to assess the likelihood of developing hypertension would be helpful for disease management. The genetic database of hypertension will expand with the use of advanced bioinformatics tools and genetic technology including SNP, exon, and noncoding (micro) RNA arrays. Newer approaches will allow for identification of structural and functional gene data sets from individuals with hypertension and development of new molecular targets for study and treatment.

We conclude that the amplification PCR-SNP analysis will be a convenient and useful method to significantly improve the reliable SNP detection in specimens containing very low concentrations.

  References Top

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