<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">JBM</journal-id><journal-title-group><journal-title>Journal of Biosciences and Medicines</journal-title></journal-title-group><issn pub-type="epub">2327-5081</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/jbm.2023.112004</article-id><article-id pub-id-type="publisher-id">JBM-122994</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Biomedical&amp;Life Sciences</subject></subj-group></article-categories><title-group><article-title>
 
 
  Relationship of Toll-Like Receptors 2 and 4 Gene Polymorphisms with Essential Hypertension in Chinese Han Population
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Huabei</surname><given-names>Wu</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Shijie</surname><given-names>Yin</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>School of General Medical, Guangxi Medical University, Nanning, China</addr-line></aff><aff id="aff2"><addr-line>The First Affiliated Hospital of Guangxi University of Traditional Chinese Medicine, Nanning, China</addr-line></aff><pub-date pub-type="epub"><day>07</day><month>02</month><year>2023</year></pub-date><volume>11</volume><issue>02</issue><fpage>53</fpage><lpage>63</lpage><history><date date-type="received"><day>13,</day>	<month>January</month>	<year>2023</year></date><date date-type="rev-recd"><day>10,</day>	<month>February</month>	<year>2023</year>	</date><date date-type="accepted"><day>13,</day>	<month>February</month>	<year>2023</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  Objective: There are numerous studies suggesting that genetic polymor-phisms of inflammation factors Toll-like receptors 2 and 4 (
  <em>TLR</em>2, 
  <em>TLR</em>4) might play a role in the pathophysiological process of hypertension. In this study, we evaluated the association in a sample of members of the Chinese Han population. 
  Method: We selected four single nucleotide polymor-phisms (SNP) of 
  <em>TLR</em>2 (rs3804099, rs3804100, rs7656411) and 
  <em>TLR</em>4 (rs1927906) genes, and measured the distributions of genotypic and allelic frequencies in 1063 participants, including 391 essential hypertension pa-tients and 672 controls. 
  Result: No significant differences in the genotypic and allelic frequencies of the four SNPs were detected between cases and controls. However, three haplotypes, CCG, TTG and TTT of 
  <em>TLR</em>2, were significantly associated with a decrease in the risk of essential hyperten-sion (OR: 0.512, 95% CI: 0.397 - 0.660, 
  <em>P </em>&lt; 0.000; OR: 0.701, 95% CI: 0.550 - 0.892, 
  <em>P</em> = 0.0038; OR: 0.797, 95% CI: 0.667 - 0.952, 
  <em>P</em> = 0.0122, respectively). Inversely, the risk of essential hypertension increased sig-nificantly in patients with the CTG, TCG or TCT haplotypes (OR: 2.924, 95% CI: 2.157 - 3.963, 
  <em>P</em> &lt; 0.0000; OR: 3.955, 95% CI: 2.042 - 7.660, 
  <em>P</em> &lt; 0.0000; OR: 6.998, 95% CI: 4.137 - 11.838, 
  <em>P</em> &lt; 0.0000, respectively). 
  Conclusion: Our study suggested that haplotypes (CCG, TTG, TTT, CTG, TCG and TCT) of 
  <em>TLR</em>2 might have profound effects on the development of essential hypertension in the Chinese Han population.
 
</p></abstract><kwd-group><kwd>Toll-Like Receptor 2</kwd><kwd> Toll-Like Receptor 4</kwd><kwd> Single-Nucleotide Polymor-phisms</kwd><kwd> Essential Hypertension</kwd><kwd> Inflammation</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Essential hypertension (EH) is the most prevalent risk factor for cardiovascular morbidity and mortality worldwide [<xref ref-type="bibr" rid="scirp.122994-ref1">1</xref>] . Many studies have concentrated on the genetic and environmental factors that may lead to EH, attempting to find potential therapeutic targets and form prevention strategies. However, the aetiology of essential hypertension (EH) is still not completely known. Recently, there have been many studies that demonstrated how EH may be a low-degree inflammatory disease [<xref ref-type="bibr" rid="scirp.122994-ref2">2</xref>] [<xref ref-type="bibr" rid="scirp.122994-ref3">3</xref>] . A significant increase of a series of circulating inflammatory markers was observed in advanced EH. These markers included C-reactive protein (CRP), Interleukin-6 (IL-6), and so on. Both cross-sectional and prospective studies have shown that CRP is higher in hypertensive patients [<xref ref-type="bibr" rid="scirp.122994-ref4">4</xref>] , while IL-6 was correlated with blood pressure measures, as Chae [<xref ref-type="bibr" rid="scirp.122994-ref5">5</xref>] demonstrated. Despite an increase in clinical studies that support the link between inflammation and EH, the mechanisms underlying the process are still unclear.</p><p>Toll-like receptors (TLRs), which are part of the mediated innate immune transmembrane signalling receptor family, play an important role in signal transduction for the activation of inflammatory cells. They also form a bridge between innate immunity and acquired immunity, characterised by an extracellular leucine-rich repeat domain and an intracellular Toll/IL-1 receptor-like (TIR) domain [<xref ref-type="bibr" rid="scirp.122994-ref6">6</xref>] . TLRs have ubiquitously expressed pattern recognition receptors central to the inflammatory response in a broad array of species. In vertebrates, TLRs expression was originally described in immune system cells, such as macrophages and neutrophils, but it is now becoming apparent that they are widely expressed throughout the body in cells as diverse as hepatocytes, vascular smooth muscle cells, and neurons. TLR2 and TLR4 are important members of the Toll-like receptor family. TLR2 recognises various lipoproteins from bacteria, mycoplasma and fungi by forming a heterodimer with either TLR1 (TLR1/TLR2 to recognise triacyl lipoproteins) or TLR6 (TLR2/TLR6 to sense diacyl lipoproteins) [<xref ref-type="bibr" rid="scirp.122994-ref7">7</xref>] . TLR4, produced by monocytes and endothelial cells [<xref ref-type="bibr" rid="scirp.122994-ref8">8</xref>] , can ligate with lipopolysaccharide (LPS) and be activated by cellular fibronectin in response to tissue injury [<xref ref-type="bibr" rid="scirp.122994-ref9">9</xref>] and heat shock protein 60 [<xref ref-type="bibr" rid="scirp.122994-ref10">10</xref>] . At present, many studies have reported close relationships between TLR2 or TLR4 and cardiovascular diseases. Kuwahata et al. [<xref ref-type="bibr" rid="scirp.122994-ref11">11</xref>] reported that high TLR2 expression levels in monocytes might be an independent risk factor for atherogenesis. Dzumhur et al. [<xref ref-type="bibr" rid="scirp.122994-ref12">12</xref>] indicated that single nucleotide polymorphism (SNP) 1350T/C in TLR2 might play a protective role against acute myocardial infarction (AMI) and arterial hypertension. Even though TLR4 and TLR2 are reported to be associated with other inflammatory diseases, studies regarding the association between with EH have thus far been poor. TLR4 expression was reported to increase in hypertensive rats [<xref ref-type="bibr" rid="scirp.122994-ref13">13</xref>] . On the other hand, TLR4-deficient mice showed less susceptibly to developing pulmonary hypertension [<xref ref-type="bibr" rid="scirp.122994-ref14">14</xref>] . Moreover, Sollinger [<xref ref-type="bibr" rid="scirp.122994-ref15">15</xref>] suggested that cell damage-associated TLR4 signalling might act as a direct mediator for the vascular contractility linking inflammation to hypertension. For TLR2, increased expression was observed in pregnant women with hypertension, compared with controls [<xref ref-type="bibr" rid="scirp.122994-ref16">16</xref>] . These studies indicated that the TLR4 and TLR2 genes might have a role in EH, as well as in other inflammatory diseases.</p><p>So far, 290 SNPs have been identified in the human TLR4 gene (http://www.ncbi.nlm.nih.gov, as of the last access on 23 October 2011). Rs1927906 of TLR4 is located in the 3’-UTR of gene, which has been documented to differ significantly in pulmonary tuberculosis in the Sudanese [<xref ref-type="bibr" rid="scirp.122994-ref17">17</xref>] . However, to the best of our knowledge, our study is the first to focus on its association with EH. For the TLR2 gene, a total of 342 SNPs have been identified in humans to date (http://www.ncbi.nlm.nih.gov, as of the last access on 23 October 2011). Rs3804099 and rs3804100 of TLR2 are synonymous SNPs, and rs7656411 of TLR2 are located in the 3’-UTR of gene. Although the former SNPs did not lead to a change in the primary polypeptide sequence, many studies have confirmed that synonymous mutations have an impact on gene function and have been implicated in diseases [<xref ref-type="bibr" rid="scirp.122994-ref18">18</xref>] [<xref ref-type="bibr" rid="scirp.122994-ref19">19</xref>] [<xref ref-type="bibr" rid="scirp.122994-ref20">20</xref>] . In addition, some mutations located in the 3’-UTR of the gene have a close contact with EH [<xref ref-type="bibr" rid="scirp.122994-ref21">21</xref>] [<xref ref-type="bibr" rid="scirp.122994-ref22">22</xref>] [<xref ref-type="bibr" rid="scirp.122994-ref23">23</xref>] . In order to study the relationships between these two genes and EH, we investigated the relationship of the SNPs of TLR2 and TLR4 with EH in members of the Chinese Han population.</p></sec><sec id="s2"><title>2. Methods</title><sec id="s2_1"><title>2.1. Ethics Statement</title><p>The Guangxi Medical Ethics Committee in China approved this study. All of the patients provided written informed consent.</p></sec><sec id="s2_2"><title>2.2. Subjects</title><p>There were 391 EH patients and 672 normotensive controls that were recruited to participate in our study. The participants underwent a physical examination in the Guangxi hospital and two health care centres in the Guangxi province in Nangning between April 2021 and August 2021. The participants self-reported that they were of Han Chinese ethnicity. Hypertension was defined as currently receiving treatment with an antihypertensive drug or having a diastolic blood pressure (DBP) of a minimum of 90 mmHg and/or a systolic blood pressure (SBP) of a minimum of 140 mmHg [<xref ref-type="bibr" rid="scirp.122994-ref24">24</xref>] . The control subjects all had SBP &lt; 140 mmHg and DBP &lt; 90 mmHg [<xref ref-type="bibr" rid="scirp.122994-ref24">24</xref>] . Inclusion criteria: the case group was Han patients with essential hypertension who has been diagnosed, while the control group was Han healthy people with non-essential hypertension, and had no family genetic history of hypertension. Patients with diabetes, tumor, secondary hypertension, coronary heart disease, valvular heart disease, myocarditis and other inflammatory diseases were excluded from both groups. Data on demographic characteristics (age, gender, occupation, etc.), lifestyle (smoking, and alcohol consumption), health status, and medical history were collected using a standardised questionnaire. A family history of hypertension was considered positive if the participant’s parents or siblings had a history of hypertension. Blood pressure was measured three times by trained nurses with a mercury sphygmomanometer in a comfortable sitting position after five minutes of rest, and the mean values of the three trials were obtained for analysis. Participants were asked to avoid vigorous exercise, drinking, and smoking for at least 30 minutes before the measurements were taken. All participants were recruited from Nanning, Guangxi, and provided written informed consent. The Ethics Committee of Guangxi Medical University approved the study.</p></sec><sec id="s2_3"><title>2.3. DNA Extraction and Genotyping of the TLR4 and TLR2 Polymorphisms</title><p>The SNPs were selected from the National Center for Biotechnology Information db SNP, with minor allele frequencies (MAF) of more than 5%. The MAF was chosen based on the number of SNPs to be genotyped, the available sample size and the desire to ensure a reasonable study power (at least 80%).</p><p>Two millilitres of fasting venous blood was collected from the participants from 8 to 11 am in the morning, using ethylene-diamine-tetra-acetic acid (EDTA) as an anticoagulant. Genomic DNA was extracted according to the phenol-chloroform method. The primers for amplifying the TLR4 gene (rs1927906) and TLR2 gene (rs3804099, re3804100, rs7656411) were designed based on the National Center for Biotechnology Information gene database (Primer sequence of each SNP site is shown in <xref ref-type="table" rid="table1">Table 1</xref>). Amplification included 1.0 uL DNA, mixing with H<sub>2</sub>O 1.8 uL, 10&#215; Taq polymerase chain reaction (PCR) Master-mix 0.5 μL, MgCl<sub>2</sub> 0.4 uL, dNTP 0.1 uL, PCR enzyme 0.2uL, DNA 1 uL, and 1 uL of each primer. Cycle conditions involved an initial denaturation for 30 s at 94˚C, followed by 40 cycles of denaturing at 95˚C for 5 s, annealing at 52˚C for 5 s, primer extension at 80˚C for 5 s, 52˚C for 5 s, 80˚C for 1 min, followed by 5 cycles and a final extension at 72˚C for 3 min. The PCR products were purified using a SAP enzyme before being preserved at 4˚C. Genotyping of all SNPs was performed using Matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF MS) according to the manufacturer’s instructions, with an accuracy of more than 99%.</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Primer sequence of each SNP site</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >SNP_ID</th><th align="center" valign="middle" >2<sup>nd</sup>-PCRP</th><th align="center" valign="middle" >1<sup>st</sup>-PCRP</th><th align="center" valign="middle" >UEP_SEQ</th></tr></thead><tr><td align="center" valign="middle" >1927906-C</td><td align="center" valign="middle" >ACGTTGGATGTCCTTCCTATCAGTTCCCTC</td><td align="center" valign="middle" >ACGTTGGATGTGCTTGTCCACCTCACCTG</td><td align="center" valign="middle" >GTTCCCTCTCCCAGA</td></tr><tr><td align="center" valign="middle" >3804099-B</td><td align="center" valign="middle" >ACGTTGGATGCTGCTTCATATGAAGGATCAG</td><td align="center" valign="middle" >ACGTTGGATGGATCTACAGAGCTATGAGCC</td><td align="center" valign="middle" >ggTGAAGGATCAGATGACTTAC</td></tr><tr><td align="center" valign="middle" >7656411-A</td><td align="center" valign="middle" >ACGTTGGATGCCTTTAAATTACTGTGTATC</td><td align="center" valign="middle" >ACGTTGGATGGTACATGTGAGCTAAATAG</td><td align="center" valign="middle" >ggTTTTTGAGTCATTATGAGGAA</td></tr><tr><td align="center" valign="middle" >3804100-B</td><td align="center" valign="middle" >ACGTTGGATGTTCCAGTGTCTTGGGAATGC</td><td align="center" valign="middle" >ACGTTGGATGGTCAGTGGCCAGAAAAGATG</td><td align="center" valign="middle" >cccacCTTGGGAATGCAGCCTGTTAC</td></tr></tbody></table></table-wrap></sec><sec id="s2_4"><title>2.4. Statistical Analysis</title><p>Data was expressed as proportions, means and standard deviations (Mean &#177; SD). Clinical characteristics were compared between cases and controls using a Student t-test or χ<sup>2</sup> test. The Hardy-Weinberg equilibrium was tested for each SNP among the controls. Differences in allelic and genotypic frequencies between the cases and controls were assessed using the χ<sup>2</sup> test. A logistic regression analysis was used to test the relationships between genotypes, alleles and EH after adjustments were made to the potential confounders, including gender, age, smoking and alcohol consumption. Linkage disequilibrium and haplotypes were analysed using the SHEsis software (http://analysis2.bio-x.cn/myAnalysis.php). The statistical tests were 2-sides, and a P value &lt; 0.05 was considered statistically significant.</p></sec></sec><sec id="s3"><title>3. Results</title><p>The clinical characteristics of the case and control subjects are summarised in <xref ref-type="table" rid="table2">Table 2</xref>. Significant differences were observed in gender, age, smoking and alcohol consumption between the two groups. None of the four SNPs reported in the present study showed significant deviations from the Hardy-Weinberg equilibrium in control subjects (P &gt; 0.05).</p><p>The distributions of genotypic and allelic frequencies of the four SNPs in each group are shown in <xref ref-type="table" rid="table3">Table 3</xref>. No statistically significant differences were detected in each SNP between the cases and controls (all P values &gt; 0.05). Multiple logistic regression analyses revealed no significant associations (all P values &gt; 0.05) between these four SNPs with EH, even after adjusting for all confounding factors (As shown in <xref ref-type="table" rid="table3">Table 3</xref>).</p><p>The linkage disequilibrium (LD) analysis results assessed by the SHEsis programme demonstrated that three SNPs (rs3804099, rs3804100, rs7656411) of the TLR2 gene were in LD, and their pair-wise LD (D’) values are shown in <xref ref-type="fig" rid="fig1">Figure 1</xref>. Then, three SNPs (rs3804099, rs3804100, rs7656411) of the TLR2 gene were included in the haplotype analysis. In addition, six haplotypes with frequencies ≥ 0.03 were obtained (As shown in <xref ref-type="table" rid="table4">Table 4</xref>). The CCG, TTG and TTT haplotypes were significantly associated with a decrease in the risk of EH (OR: 0.512, 95% CI: 0.397 - 0.660, P &lt; 0.000; OR: 0.701, 95% CI: 0.550 - 0.892, P = 0.0038; OR: 0.797, 95% CI: 0.667 - 0.952, P = 0.0122, respectively). Inversely, the risk of EH</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Characteristics of study participants</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Confounding factors</th><th align="center" valign="middle" >Case (n = 391)</th><th align="center" valign="middle" >Control (n = 672)</th><th align="center" valign="middle" >P* value</th></tr></thead><tr><td align="center" valign="middle" >Gender (male/female)</td><td align="center" valign="middle" >153/238</td><td align="center" valign="middle" >309/363</td><td align="center" valign="middle" >0.03</td></tr><tr><td align="center" valign="middle" >Age (year)</td><td align="center" valign="middle" >56.98 &#177; 9.48</td><td align="center" valign="middle" >47.08 &#177; 10.21</td><td align="center" valign="middle" >0.00</td></tr><tr><td align="center" valign="middle" >Smoking (%)</td><td align="center" valign="middle" >15.9</td><td align="center" valign="middle" >21.1</td><td align="center" valign="middle" >0.04</td></tr><tr><td align="center" valign="middle" >Alcohol consumption (%)</td><td align="center" valign="middle" >43.2</td><td align="center" valign="middle" >65.8</td><td align="center" valign="middle" >0.00</td></tr></tbody></table></table-wrap><p>*P &lt; 0.05 was defined as a statistical significance.</p><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> The distributions of genotypic and allelic frequencies in cases and controls and their association with EH</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Polymorphisms</th><th align="center" valign="middle" ></th><th align="center" valign="middle" >Control</th><th align="center" valign="middle" >Case</th><th align="center" valign="middle" >P* value</th><th align="center" valign="middle" >Adjusted OR (95% CI)**</th></tr></thead><tr><td align="center" valign="middle"  rowspan="3"  >Rs3804099 genotypes</td><td align="center" valign="middle" >C/C</td><td align="center" valign="middle" >57 (0.085)</td><td align="center" valign="middle" >30 (0.077)</td><td align="center" valign="middle" >0.886</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle" >C/T</td><td align="center" valign="middle" >269 (0.400)</td><td align="center" valign="middle" >156 (0.399)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >0.922 (0.538 - 1.578)</td></tr><tr><td align="center" valign="middle" >T/T</td><td align="center" valign="middle" >346 (0.515)</td><td align="center" valign="middle" >205 (0.524)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >1.050 (0.620 - 1.778)</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Allelic</td><td align="center" valign="middle" >C</td><td align="center" valign="middle" >383 (0.285)</td><td align="center" valign="middle" >216 (0.276)</td><td align="center" valign="middle" >0.665</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle" >T</td><td align="center" valign="middle" >961 (0.715)</td><td align="center" valign="middle" >566 (0.724)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >1.072 (0.860 - 1.337)</td></tr><tr><td align="center" valign="middle"  rowspan="3"  >Rs3804100 genotypes</td><td align="center" valign="middle" >T/T</td><td align="center" valign="middle" >389 (0.579)</td><td align="center" valign="middle" >220 (0.563)</td><td align="center" valign="middle" >0.715</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle" >T/C</td><td align="center" valign="middle" >237 (0.353)</td><td align="center" valign="middle" >147 (0.376)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >1.056 (0.785 - 1.422)</td></tr><tr><td align="center" valign="middle" >C/C</td><td align="center" valign="middle" >46 (0.068)</td><td align="center" valign="middle" >24 (0.061)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >0.867 (0.484 - 1.555)</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Allelic</td><td align="center" valign="middle" >T</td><td align="center" valign="middle" >1015 (0.755)</td><td align="center" valign="middle" >587 (0.751)</td><td align="center" valign="middle" >0.814</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle" >C</td><td align="center" valign="middle" >329 (0.245)</td><td align="center" valign="middle" >195 (0.249)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >0.989 (0.787 - 1.244)</td></tr><tr><td align="center" valign="middle"  rowspan="3"  >Rs7656411 genotypes</td><td align="center" valign="middle" >G/G</td><td align="center" valign="middle" >151 (0.225)</td><td align="center" valign="middle" >73 (0.187)</td><td align="center" valign="middle" >0.181</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle" >G/T</td><td align="center" valign="middle" >319 (0.475)</td><td align="center" valign="middle" >207 (0.529)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >1.296 (0.896 - 1.875)</td></tr><tr><td align="center" valign="middle" >T/T</td><td align="center" valign="middle" >202 (0.301)</td><td align="center" valign="middle" >111 (0.284)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >1.137 (0.755 - 1.713)</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Allelic</td><td align="center" valign="middle" >G</td><td align="center" valign="middle" >621 (0.462)</td><td align="center" valign="middle" >353 (0.451)</td><td align="center" valign="middle" >0.635</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle" >T</td><td align="center" valign="middle" >723 (0.538)</td><td align="center" valign="middle" >429 (0.549)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >1.042 (0.853 - 1.272)</td></tr><tr><td align="center" valign="middle"  rowspan="3"  >Rs1927906 genotypes</td><td align="center" valign="middle" >A/A</td><td align="center" valign="middle" >620 (0.923)</td><td align="center" valign="middle" >370 (0.946)</td><td align="center" valign="middle" >0.283</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle" >A/G</td><td align="center" valign="middle" >51 (0.076)</td><td align="center" valign="middle" >21 (0.292)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >0.855 (0.475 - 1.538)</td></tr><tr><td align="center" valign="middle" >G/G</td><td align="center" valign="middle" >1 (0.010)</td><td align="center" valign="middle" >0 (0)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Allelic</td><td align="center" valign="middle" >A</td><td align="center" valign="middle" >1291 (0.961)</td><td align="center" valign="middle" >761 (0.973)</td><td align="center" valign="middle" >0.127</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle" >G</td><td align="center" valign="middle" >53 (0.039)</td><td align="center" valign="middle" >21 (0.027)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >0.836 (0.471 - 1.483)</td></tr></tbody></table></table-wrap><p>*P &lt; 0.05 was defined as statistically significant. **Adjusted OR (95% CI) were odds ratios and 95% confidence interval calculated by multiple logistic regression analyses after being adjusted for gender, age, smoking and alcohol consumption.</p><table-wrap id="table4" ><label><xref ref-type="table" rid="table4">Table 4</xref></label><caption><title> Estimated haplotype frequencies and association with the risk of EH in cases and controls</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Haplotypes*</th><th align="center" valign="middle" >Frequency in cases</th><th align="center" valign="middle" >Frequency in controls</th><th align="center" valign="middle" >P value**</th><th align="center" valign="middle" >OR 95% CI</th></tr></thead><tr><td align="center" valign="middle" >CCG</td><td align="center" valign="middle" >0.119</td><td align="center" valign="middle" >0.206</td><td align="center" valign="middle" >0.000</td><td align="center" valign="middle" >0.512 (0.397 - 0.660)</td></tr><tr><td align="center" valign="middle" >TTG</td><td align="center" valign="middle" >0.144</td><td align="center" valign="middle" >0.190</td><td align="center" valign="middle" >0.004</td><td align="center" valign="middle" >0.701 (0.131 - 0.490)</td></tr><tr><td align="center" valign="middle" >TTT</td><td align="center" valign="middle" >0.454</td><td align="center" valign="middle" >0.502</td><td align="center" valign="middle" >0.012</td><td align="center" valign="middle" >0.797 (0.667 - 0.952)</td></tr><tr><td align="center" valign="middle" >CTG</td><td align="center" valign="middle" >0.150</td><td align="center" valign="middle" >0.056</td><td align="center" valign="middle" >0.000</td><td align="center" valign="middle" >2.924 (2.157 - 3.963)</td></tr><tr><td align="center" valign="middle" >TCG</td><td align="center" valign="middle" >0.038</td><td align="center" valign="middle" >0.010</td><td align="center" valign="middle" >0.000</td><td align="center" valign="middle" >3.955 (2.042 - 7.660)</td></tr><tr><td align="center" valign="middle" >TCT</td><td align="center" valign="middle" >0.088</td><td align="center" valign="middle" >0.013</td><td align="center" valign="middle" >0.000</td><td align="center" valign="middle" >6.998 (4.137 - 11.838)</td></tr></tbody></table></table-wrap><p>*Haplotypes with frequency less than 0.03 in controls and cases were excluded. **P &lt; 0.05 was defined as statistically significant.</p><p>increased significantly in patients with the CTG, TCG or TCT haplotypes (OR: 2.924, 95% CI: 2.157 - 3.963, P &lt; 0.000; OR: 3.955, 95% CI: 2.042 - 7.660, P &lt; 0.000; OR: 6.998, 95% CI: 4.137 - 11.838, P &lt; 0.000, respectively).</p></sec><sec id="s4"><title>4. Discussion</title><p>Our study demonstrated no significant differences in any of the individual distributions of genotypic and allelic frequencies between the cases and controls for the four SNPs. Multiple logistic regression analyses suggested that these SNPs were not associated with EH. However, the LD analysis revealed that three SNPs of TLR2 were in LD, allowing for the construction of haplotype blocks. In addition, three protective haplotypes and three risk haplotypes of EH were found in the haplotype analysis. Therefore, we provided evidence for an association of TLR2 gene polymorphisms with the risk of EH, suggesting that the TLR2 gene might be involved in the pathogenesis of EH in the Han Chinese population.</p><p>As a major risk factor for atherosclerosis, hypertension is considered a low-degree inflammatory disease [<xref ref-type="bibr" rid="scirp.122994-ref25">25</xref>] . Some researchers reported that there was a close link between vascular inflammation caused by endothelial injury and the occurrence and development of hypertension [<xref ref-type="bibr" rid="scirp.122994-ref26">26</xref>] [<xref ref-type="bibr" rid="scirp.122994-ref27">27</xref>] . TLR2 can affect inflammatory cytokines and endothelial function. Sabroe et al. [<xref ref-type="bibr" rid="scirp.122994-ref28">28</xref>] confirmed that TLR2 agonists regulated important neutrophil functions, including adhesion, the generation of reactive oxygen species, and the release of chemokines, in addition to activating major proinflammatory signalling pathways, including the nuclear factor—κB pathway. Jiang [<xref ref-type="bibr" rid="scirp.122994-ref29">29</xref>] and colleagues demonstrated that fragmented hyaluronan (HA) generated by tissue injury required both TLR2 and TLR4 to stimulate mouse macrophages and produce inflammatory chemokines and cytokines. Mullick et al. [<xref ref-type="bibr" rid="scirp.122994-ref30">30</xref>] reported that TLR2 deficiency could reduce hyperlipidemic-induced changes in the morphology of the endothelium. Tzima et al. [<xref ref-type="bibr" rid="scirp.122994-ref31">31</xref>] found that the extent of endothelial cell disruption is proportional to the extent of endothelial cell TLR2 expression. Therefore TLR2 is closely associated with inflammation and vascular endothelial function. Considering the role of TLR2 in promoting vascular inflammation, we speculated that a reduced or increased of TLR2 expression, or a change in its protein structure, led to functional changes, and consequently, affected the regulation of inflammatory cytokines and endothelial function, resulting in vascular inflammation. This, thus, influenced the susceptibility towards EH. The six haplotypes that were found in our study may enhance or weaken the function of TLR2 via changing the protein structure or its expression, so as to affect susceptibility towards EH.</p><p>Our study has several limitations. First, we did not study other meaningful SNPs of TLR2 and TLR4, and therefore we cannot exclude the possibility that they may have linked inheritance with the SNPs in our study. Second, we failed to demonstrate whether the SNPs were related to functional alterations of TLR2 or TLR4. Third, our study did not clarify the mechanism of the six haplotypes regarding susceptibility towards EH. Thus, more extensive studies, including whole-genome analyses, are required to confirm our results.</p><p>In conclusion, there were no genotypic and allelic associations between the four SNPs in the TLR2 or TLR4 genes and the EH cases. However, the haplotypes, which are based on rs3804099, rs3804100 and rs7656411 of TLR2, CCG, TTG and TTT were protective factors regarding EH. Finally, CTG, TCG and TCT were risk factors for EH. These suggested the involvement of TLR2 in EH pathogenesis.</p></sec><sec id="s5"><title>Acknowledgements</title><p>We thank Hong Yang and her team from the CDC for their assistance in the field survey. We also thank Jinmei Huang and Yang Xu for their strong support of this experiment.</p></sec><sec id="s6"><title>Conflicts of Interest</title><p>The authors declare no conflicts of interest regarding the publication of this paper.</p></sec><sec id="s7"><title>Cite this paper</title><p>Wu, H.B. and Yin, S.J. (2023) Relationship of Toll-Like Receptors 2 and 4 Gene Polymorphisms with Essential Hypertension in Chinese Han Population. Journal of Biosciences and Medicines, 11, 53-63. https://doi.org/10.4236/jbm.2023.112004</p></sec></body><back><ref-list><title>References</title><ref id="scirp.122994-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Fagard, R.H., Celis, H., Thijs, L., et al. 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