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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Cardiovasc. Med.</journal-id>
<journal-title>Frontiers in Cardiovascular Medicine</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Cardiovasc. Med.</abbrev-journal-title>
<issn pub-type="epub">2297-055X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fcvm.2022.859979</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Cardiovascular Medicine</subject>
<subj-group>
<subject>Systematic Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Systematic Review and Meta-Analysis of <italic>SERPINE1</italic> 4G/5G Insertion/Deletion Variant With Circulating Lipid Levels</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Luo</surname> <given-names>Zhi</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="author-notes" rid="fn002"><sup>&#x2020;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1407275/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Liu</surname> <given-names>Yang</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="author-notes" rid="fn002"><sup>&#x2020;</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Li</surname> <given-names>Hang</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Zhou</surname> <given-names>Yawen</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1693640/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Peng</surname> <given-names>Yuanyuan</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Lin</surname> <given-names>Xuan</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Fang</surname> <given-names>Ying</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Wan</surname> <given-names>Jing</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Wei</surname> <given-names>Baozhu</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<xref ref-type="corresp" rid="c002"><sup>&#x002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1529453/overview"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Department of Cardiology, Zhongnan Hospital of Wuhan University, Wuhan University</institution>, <addr-line>Wuhan</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>Department of Endocrinology, China Resources and WISCO General Hospital</institution>, <addr-line>Wuhan</addr-line>, <country>China</country></aff>
<aff id="aff3"><sup>3</sup><institution>Department of Geratology, Zhongnan Hospital of Wuhan University, Wuhan University</institution>, <addr-line>Wuhan</addr-line>, <country>China</country></aff>
<aff id="aff4"><sup>4</sup><institution>Institute of Myocardial Injury and Repair, Wuhan University</institution>, <addr-line>Wuhan</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Neil Morgan, University of Birmingham, United Kingdom</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Guangyu Zhang, City of Hope National Medical Center, United States; Yingfeng Wan, University of Michigan, United States</p></fn>
<corresp id="c001">&#x002A;Correspondence: Jing Wan, <email>wanjing2017@163.com</email></corresp>
<corresp id="c002">Baozhu Wei, <email>wbz9810@163.com</email></corresp>
<fn fn-type="equal" id="fn002"><p><sup>&#x2020;</sup>These authors have contributed equally to this work and share first authorship</p></fn>
<fn fn-type="other" id="fn004"><p>This article was submitted to Cardiovascular Genetics and Systems Medicine, a section of the journal Frontiers in Cardiovascular Medicine</p></fn>
</author-notes>
<pub-date pub-type="epub">
<day>23</day>
<month>06</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>9</volume>
<elocation-id>859979</elocation-id>
<history>
<date date-type="received">
<day>17</day>
<month>02</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>30</day>
<month>05</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2022 Luo, Liu, Li, Zhou, Peng, Lin, Fang, Wan and Wei.</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Luo, Liu, Li, Zhou, Peng, Lin, Fang, Wan and Wei</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p></license>
</permissions>
<abstract>
<sec>
<title>Background</title>
<p>Recent studies have shown that the 4G/5G insertion/deletion variant of <italic>SERPINE1</italic> (rs1799889) is closely linked to coronary artery disease (CAD). This study aims to clarify the effects of the rs1799889 variant on lipid levels and to insight into the mechanisms underlying the rs1799889 variant and CAD.</p>
</sec>
<sec>
<title>Methods and Results</title> 
<p>By searching PubMed and the Cochrane databases for studies published before 31 October 2021, 40 studies conducted on a total of 13,117 subjects were included for the analysis. The consistent findings for the effects of the 5G allele of rs1799889 variant on lipid metabolism were the significantly decreased triglycerides (TG) [standardized mean difference (SMD) = &#x2013;0.12, 95% CI = &#x2013;0.21 to 0.03, <italic>P</italic> = 0.01], total cholesterol (TC) (SMD = &#x2013;0.12, 95% CI = &#x2013;0.17 to 0.06, <italic>P</italic> &#x003C; 0.001), and low-density lipoprotein cholesterol (LDL-C) (SMD = &#x2013;0.13, 95% CI = &#x2013;0.23 to 0.03, <italic>P</italic> = 0.01) levels. Intriguingly, the significant effects of the rs1799889 variant on LDL-C (SMD = &#x2013;0.15, 95% CI = &#x2013;0.26 to 0.05, <italic>P</italic> &#x003C; 0.01) and TC (SMD = &#x2013;0.17, 95% CI = &#x2013;0.27 to 0.07, <italic>P</italic> &#x003C; 0.01) levels were primarily observed in the Asian population. However, the significant effect of the rs1799889 variant on high-density lipoprotein cholesterol (HDL-C) (SMD = 0.26, 95% CI = 0.03&#x2013;0.48, <italic>P</italic> = 0.03) levels was detected only in female subjects.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>The rs1799889 variant of <italic>SERPINE1</italic> is a protective genetic factor against CAD, the Asian population with the 5G allele of the rs1799889 variant may have a reduced CAD risk.</p>
</sec>
</abstract>
<kwd-group>
<kwd>rs1799889</kwd>
<kwd>polymorphism</kwd>
<kwd>lipid</kwd>
<kwd>coronary artery disease</kwd>
<kwd>Asian</kwd>
</kwd-group>
<counts>
<fig-count count="5"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="29"/>
<page-count count="9"/>
<word-count count="4437"/>
</counts>
</article-meta>
</front>
<body>
<sec id="S1" sec-type="intro">
<title>Introduction</title>
<p>The plasminogen activator inhibitor-1 (<italic>PAI-1</italic>), also known as <italic>SERPINE1</italic>, is a member of the serine protease inhibitor superfamily and plays a major role in regulating fibrinolysis by inhibiting plasminogen activity.</p>
<p>The <italic>SERPINE1</italic> gene is located on the long arm of human chromosome 7 (7q21.3-22). The most-studied rs1799889 variant, also known as 4G/5G insertion/deletion sequence, is located in the <italic>SERPINE1</italic> promoter region and formed by the 5th guanine (G base) insertion or deletion in the 4G sequence at position-675th base. The 5G allele has lower transcriptional activity than the 4G allele (<xref ref-type="bibr" rid="B1">1</xref>) and subjects with homozygous 5G allele have about 25% lower circulating PAI-1 concentrations than subject&#x2019;s possession of homozygous 4G allele (<xref ref-type="bibr" rid="B2">2</xref>).</p>
<p>Notably, a set of elegant experiments showed that SERPINE1 may affect lipid metabolism. For instance, <italic>SERPINE1</italic> knockout (<italic>SERPINE1</italic>&#x2013;<italic><sup>/</sup></italic>&#x2013;) inhibits the expression of adipogenic genes (<xref ref-type="bibr" rid="B3">3</xref>) and ameliorates dyslipidemia (<xref ref-type="bibr" rid="B4">4</xref>) in mice. Consistently, transplanting white adipose tissue from <italic>SERPINE1</italic>&#x2013;<italic><sup>/</sup></italic>&#x2013; mice into obese mice reduces plasma triglycerides (TG) and total cholesterol (TC) levels (<xref ref-type="bibr" rid="B5">5</xref>). Moreover, inhibition of <italic>SERPINE1</italic> expression decreases proprotein convertase subtilisin/kexin type 9 (PCSK9) and increases low-density lipoprotein receptor (LDLR) levels (<xref ref-type="bibr" rid="B6">6</xref>). Taken together, these indicate that the expression levels of SERPINE1 are closely linked to lipid metabolism. Therefore, the 5G allele of the rs1799889 variant may affect lipid levels due to its profound impact on SERPINE1 expression levels (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>).</p>
<p>Currently, a series of meta-analyses (<xref ref-type="bibr" rid="B7">7</xref>&#x2013;<xref ref-type="bibr" rid="B10">10</xref>) showed that the 5G allele of the rs1799889 variant largely decreased coronary artery disease (CAD) risk; however, the specific mechanism is unknown. Therefore, this study is conducted to investigate the effects of the rs1799889 variant on lipid levels and to clarify the mechanistic basis for the correlations between the rs1799889 variant and CAD.</p>
</sec>
<sec id="S2" sec-type="materials|methods">
<title>Materials and Methods</title>
<p>The study design followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (<xref ref-type="bibr" rid="B11">11</xref>).</p>
<sec id="S2.SS1">
<title>Literature Search</title>
<p>The literature search was carried out by using PubMed, Medline, Embase, Cochrane Library, Web of Science, Google Scholar, Foreign Medical Journal Service, and Excerpta Medica for manuscripts published before 31 October 2021, by entering the following keywords: (&#x201C;SERPINE1,&#x201D; &#x201C;PAI-1,&#x201D; or &#x201C;plasminogen activator inhibitor-1&#x201D;), (&#x201C;4G/5G,&#x201D; &#x201C;insertion/deletion,&#x201D; or &#x201C;rs1799889&#x201D;), (&#x201C;variant,&#x201D; &#x201C;mutant,&#x201D; or &#x201C;polymorphism&#x201D;), and (&#x201C;lipid,&#x201D; &#x201C;lipids,&#x201D; &#x201C;lipid metabolism,&#x201D; &#x201C;lipoprotein,&#x201D; &#x201C;cholesterol,&#x201D; &#x201C;blood lipid,&#x201D; &#x201C;serum lipid,&#x201D; or &#x201C;circulating lipid&#x201D;).</p>
</sec>
<sec id="S2.SS2">
<title>Inclusion Criteria and Exclusion Criteria</title>
<p>The inclusion criteria of this meta-analysis were as follows. (1) The studies investigated the effects of the rs1799889 variant on lipid levels. (2) The studies at least provided one of the four lipid parameters (TG, TC, LDL-C, and HDL-C). (3) The studies provided the genotype frequencies of the rs1799889 variant. (4) The rs1799889 variant offered the mean lipid levels with standard deviation (SD) or standard error (SE) by genotypes. (5) The interventional studies provided pre-intervention data. (6) The language of eligible studies was restricted to English or Chinese. The exclusion criteria of this meta-analysis include (1) studies that were not related to the rs1799889 variant, (2) studies that were not related to lipid levels, (3) studies not presenting genotype or allele counts, (4) studies having invalid data, (5) studies having incomplete data, (6) pedigree studies (7), overlapping studies, and (8) abstract, review, case report, meta-analysis, and animal studies.</p>
</sec>
<sec id="S2.SS3">
<title>Subgroup Analysis</title>
<p>Subgroup analysis was carried out by ethnicity, gender, and health status. The ethnicity was divided into Caucasian, Asian, Turkish, and other ethnics. The healthy status was divided into patients with CAD, patients with type 2 diabetes mellitus (T2DM), and healthy subjects.</p>
</sec>
<sec id="S2.SS4">
<title>Other Items</title>
<p>Refer to the previous publication (<xref ref-type="bibr" rid="B12">12</xref>) for more details about data extraction, data analysis, heterogeneity processing, and publication bias tests.</p>
</sec>
</sec>
<sec id="S3" sec-type="results">
<title>Results</title>
<sec id="S3.SS1">
<title>Study Selection</title>
<p>By searching the PubMed and Cochrane database, 2,598 studies were screened; after excluding duplicates, 2,386 studies were removed by their title and abstract. Then, 46 full-text studies were included for assessing eligibility, in which two studies (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B14">14</xref>) provided lipid data by the genotype of rs1799889 but expressed as a median and interquartile range, 1 study (<xref ref-type="bibr" rid="B15">15</xref>) provided lipid data by the genotype of rs1799889 but expressed as mean and 95% CI, 1 study (<xref ref-type="bibr" rid="B16">16</xref>) provided lipid levels by the genotype of rs1799889 but in an aberrant genetic model [(4G5G + 4G4G) vs. 5G5G], 1 study (<xref ref-type="bibr" rid="B17">17</xref>) provided invalid data, and 1 study (<xref ref-type="bibr" rid="B18">18</xref>) had subjects overlapping with other publications (<xref ref-type="bibr" rid="B19">19</xref>). Therefore, six studies were further excluded. Finally, 40 studies (13,117 subjects) were eligible for the analysis (<xref ref-type="fig" rid="F1">Figure 1</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption><p>Flow diagram of the articles selection process.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fcvm-09-859979-g001.tif"/>
</fig>
<p>The characteristics of the eligible studies were summarized in <xref ref-type="supplementary-material" rid="TS1">Supplementary Table 1</xref>. The circulating lipid levels by the genotype of the <italic>SERPINE1</italic> rs1799889 variant were presented in <xref ref-type="supplementary-material" rid="DS1">Supplementary Table 2</xref>.</p>
</sec>
<sec id="S3.SS2">
<title>Effects of the rs1799889 Variant on Circulating Lipid Levels</title>
<p>The consistent findings for the effects of the rs1799889 variant on lipid metabolism were the significantly decreased LDL-C [standardized mean difference (SMD) = &#x2013;0.13, 95% CI = &#x2013;0.23 to 0.03, <italic>P</italic> = 0.01], TC [SMD = &#x2013;0.12, 95% CI = &#x2013;0.17 to 0.06, <italic>P</italic> &#x003C; 0.001], and TG [SMD = &#x2013;0.12, 95% CI = &#x2013;0.21 to 0.03, <italic>P</italic> = 0.01] levels (<xref ref-type="table" rid="T1">Table 1</xref> and <xref ref-type="fig" rid="F2">Figures 2</xref>&#x2013;<xref ref-type="fig" rid="F4">4</xref>). After excluding the population that deviated from Hardy&#x2013;Weinberg equilibrium (HWE), the significant effects of the rs1799889 variant on LDL-C, TC, and TG levels were also detected (<xref ref-type="table" rid="T1">Table 1</xref>).</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption><p>Forest plot of the meta-analysis between <italic>SERPINE1</italic> rs1799889 polymorphism and circulating LDL-C levels.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fcvm-09-859979-g002.tif"/>
</fig>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption><p>Forest plot of the meta-analysis between <italic>SERPINE1</italic> rs1799889 polymorphism and circulating TC levels.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fcvm-09-859979-g003.tif"/>
</fig>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption><p>Forest plot of the meta-analysis between <italic>SERPINE1</italic> rs1799889 polymorphism and circulating TG levels.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fcvm-09-859979-g004.tif"/>
</fig>
<table-wrap position="float" id="T1">
<label>TABLE 1</label>
<caption><p>Meta-analysis of <italic>SERPINE1</italic> rs1799889 polymorphism with lipid levels.</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<thead>
<tr>
<td valign="top" align="left">Groups or subgroups</td>
<td valign="top" align="center">Comparisons (Subjects)</td>
<td valign="top" align="center"><italic>P</italic><sub>H</sub></td>
<td valign="top" align="center">SMD (95% CI)</td>
<td valign="top" align="center"><italic>P</italic><sub>SMD</sub></td>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left" colspan="5"><bold>TG</bold></td>
</tr>
<tr>
<td valign="top" align="left">All</td>
<td valign="top" align="center">45 (11 597)</td>
<td valign="top" align="center">&#x003C;0.001</td>
<td valign="top" align="center">&#x2212;0.12 (&#x2212;0.21 to &#x2212;0.03)</td>
<td valign="top" align="center">0.01</td>
</tr>
<tr>
<td valign="top" align="left">Studies in HWE</td>
<td valign="top" align="center">33 (9 502)</td>
<td valign="top" align="center">&#x003C;0.001</td>
<td valign="top" align="center">&#x2212;0.11 (&#x2212;0.22 to &#x2212;0.00)</td>
<td valign="top" align="center">0.05</td>
</tr>
<tr>
<td valign="top" align="left">Caucasian</td>
<td valign="top" align="center">16 (6 551)</td>
<td valign="top" align="center">&#x003C;0.001</td>
<td valign="top" align="center">&#x2212;0.18 (&#x2212;0.37 to 0.00)</td>
<td valign="top" align="center">0.06</td>
</tr>
<tr>
<td valign="top" align="left">Asian</td>
<td valign="top" align="center">19 (3 823)</td>
<td valign="top" align="center">0.07</td>
<td valign="top" align="center">&#x2212;0.09 (&#x2212;0.17 to 0.00)</td>
<td valign="top" align="center">0.06</td>
</tr>
<tr>
<td valign="top" align="left">Turkish</td>
<td valign="top" align="center">4 (458)</td>
<td valign="top" align="center">0.11</td>
<td valign="top" align="center">&#x2212;0.31 (&#x2212;0.59 to &#x2212;0.04)</td>
<td valign="top" align="center">0.03</td>
</tr>
<tr>
<td valign="top" align="left">Other ethnic</td>
<td valign="top" align="center">6 (765)</td>
<td valign="top" align="center">0.03</td>
<td valign="top" align="center">&#x2212;0.00 (&#x2212;0.25 to 0.25)</td>
<td valign="top" align="center">0.99</td>
</tr>
<tr>
<td valign="top" align="left">Male</td>
<td valign="top" align="center">2 (461)</td>
<td valign="top" align="center">0.05</td>
<td valign="top" align="center">&#x2212;0.03 (&#x2212;0.42 to 0.37)</td>
<td valign="top" align="center">0.89</td>
</tr>
<tr>
<td valign="top" align="left">Female</td>
<td valign="top" align="center">6 (1 118)</td>
<td valign="top" align="center">0.47</td>
<td valign="top" align="center">&#x2212;0.12 (&#x2212;0.26 to 0.01)</td>
<td valign="top" align="center">0.07</td>
</tr>
<tr>
<td valign="top" align="left">CAD</td>
<td valign="top" align="center">5 (595)</td>
<td valign="top" align="center">0.80</td>
<td valign="top" align="center">&#x2212;0.10 (&#x2212;0.26 to 0.07)</td>
<td valign="top" align="center">0.25</td>
</tr>
<tr>
<td valign="top" align="left">T2DM</td>
<td valign="top" align="center">7 (2 472)</td>
<td valign="top" align="center">&#x003C;0.01</td>
<td valign="top" align="center">0.01 (&#x2212;0.17 to 0.19)</td>
<td valign="top" align="center">0.94</td>
</tr>
<tr>
<td valign="top" align="left">Healthy subjects</td>
<td valign="top" align="center">14 (4 819)</td>
<td valign="top" align="center">&#x003C;0.001</td>
<td valign="top" align="center">&#x2212;0.15 (&#x2212;0.31 to 0.01)</td>
<td valign="top" align="center">0.07</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold>TC</bold></td>
</tr>
<tr>
<td valign="top" align="left">All</td>
<td valign="top" align="center">47 (9 482)</td>
<td valign="top" align="center">0.01</td>
<td valign="top" align="center">&#x2212;0.12 (&#x2212;0.17 to &#x2212;0.06)</td>
<td valign="top" align="center">&#x003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Studies in HWE</td>
<td valign="top" align="center">32 (6 425)</td>
<td valign="top" align="center">0.01</td>
<td valign="top" align="center">&#x2212;0.13 (&#x2212;0.20 to &#x2212;0.05)</td>
<td valign="top" align="center">&#x003C;0.01</td>
</tr>
<tr>
<td valign="top" align="left">Caucasian</td>
<td valign="top" align="center">13 (3 753)</td>
<td valign="top" align="center">0.25</td>
<td valign="top" align="center">&#x2212;0.06 (&#x2212;0.15 to 0.03)</td>
<td valign="top" align="center">0.18</td>
</tr>
<tr>
<td valign="top" align="left">Asian</td>
<td valign="top" align="center">20 (3 970)</td>
<td valign="top" align="center">&#x003C;0.01</td>
<td valign="top" align="center">&#x2212;0.17 (&#x2212;0.27 to &#x2212;0.07)</td>
<td valign="top" align="center">&#x003C;0.01</td>
</tr>
<tr>
<td valign="top" align="left">Turkish</td>
<td valign="top" align="center">6 (791)</td>
<td valign="top" align="center">0.24</td>
<td valign="top" align="center">&#x2212;0.15 (&#x2212;0.32 to 0.02)</td>
<td valign="top" align="center">0.09</td>
</tr>
<tr>
<td valign="top" align="left">Other ethnic</td>
<td valign="top" align="center">8 (968)</td>
<td valign="top" align="center">0.71</td>
<td valign="top" align="center">&#x2212;0.07 (&#x2212;0.21 to 0.07)</td>
<td valign="top" align="center">0.33</td>
</tr>
<tr>
<td valign="top" align="left">Male</td>
<td valign="top" align="center">2 (461)</td>
<td valign="top" align="center">0.70</td>
<td valign="top" align="center">&#x2212;0.06 (&#x2212;0.26 to 0.14)</td>
<td valign="top" align="center">0.57</td>
</tr>
<tr>
<td valign="top" align="left">Female</td>
<td valign="top" align="center">7 (1 175)</td>
<td valign="top" align="center">0.34</td>
<td valign="top" align="center">&#x2212;0.08 (&#x2212;0.22 to 0.06)</td>
<td valign="top" align="center">0.27</td>
</tr>
<tr>
<td valign="top" align="left">CAD</td>
<td valign="top" align="center">5 (595)</td>
<td valign="top" align="center">0.01</td>
<td valign="top" align="center">&#x2212;0.31 (&#x2212;0.66 to 0.04)</td>
<td valign="top" align="center">0.08</td>
</tr>
<tr>
<td valign="top" align="left">T2DM</td>
<td valign="top" align="center">8 (1 698)</td>
<td valign="top" align="center">0.30</td>
<td valign="top" align="center">&#x2212;0.09 (&#x2212;0.20 to 0.03)</td>
<td valign="top" align="center">0.14</td>
</tr>
<tr>
<td valign="top" align="left">Healthy subjects</td>
<td valign="top" align="center">14 (3 270)</td>
<td valign="top" align="center">0.69</td>
<td valign="top" align="center">&#x2212;0.09 (&#x2212;0.17 to &#x2212;0.02)</td>
<td valign="top" align="center">0.02</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold>LDL-C</bold></td>
</tr>
<tr>
<td valign="top" align="left">All</td>
<td valign="top" align="center">26 (4 309)</td>
<td valign="top" align="center">&#x003C;0.001</td>
<td valign="top" align="center">&#x2212;0.13 (&#x2212;0.23 to &#x2212;0.03)</td>
<td valign="top" align="center">0.01</td>
</tr>
<tr>
<td valign="top" align="left">Studies in HWE</td>
<td valign="top" align="center">16 (2 226)</td>
<td valign="top" align="center">&#x003C;0.001</td>
<td valign="top" align="center">&#x2212;0.13 (&#x2212;0.23 to &#x2212;0.03)</td>
<td valign="top" align="center">0.02</td>
</tr>
<tr>
<td valign="top" align="left">Caucasian</td>
<td valign="top" align="center">5 (1 453)</td>
<td valign="top" align="center">&#x003C;0.001</td>
<td valign="top" align="center">&#x2212;0.20 (&#x2212;0.56 to 0.16)</td>
<td valign="top" align="center">0.28</td>
</tr>
<tr>
<td valign="top" align="left">Asian</td>
<td valign="top" align="center">11 (1 737)</td>
<td valign="top" align="center">0.36</td>
<td valign="top" align="center">&#x2212;0.15 (&#x2212;0.26 to &#x2212;0.05)</td>
<td valign="top" align="center">&#x003C;0.01</td>
</tr>
<tr>
<td valign="top" align="left">Turkish</td>
<td valign="top" align="center">4 (458)</td>
<td valign="top" align="center">0.13<break/> 0.13</td>
<td valign="top" align="center">&#x2212;0.10 (&#x2212;0.36 to 0.17)</td>
<td valign="top" align="center">0.48</td>
</tr>
<tr>
<td valign="top" align="left">Other ethnicity</td>
<td valign="top" align="center">6 (661)</td>
<td valign="top" align="center">0.45</td>
<td valign="top" align="center">&#x2212;0.05 (&#x2212;0.22 to 0.12)</td>
<td valign="top" align="center">0.55</td>
</tr>
<tr>
<td valign="top" align="left">Female</td>
<td valign="top" align="center">5 (874)</td>
<td valign="top" align="center">0.88</td>
<td valign="top" align="center">&#x2212;0.11 (&#x2212;0.25 to 0.04)</td>
<td valign="top" align="center">0.16</td>
</tr>
<tr>
<td valign="top" align="left">CAD</td>
<td valign="top" align="center">4 (554)</td>
<td valign="top" align="center">0.08</td>
<td valign="top" align="center">&#x2212;0.16 (&#x2212;0.42 to 0.10)</td>
<td valign="top" align="center">0.23</td>
</tr>
<tr>
<td valign="top" align="left">T2DM</td>
<td valign="top" align="center">3 (771)</td>
<td valign="top" align="center">0.15</td>
<td valign="top" align="center">0.01 (&#x2212;0.23 to 0.26)</td>
<td valign="top" align="center">0.91</td>
</tr>
<tr>
<td valign="top" align="left">Healthy subjects</td>
<td valign="top" align="center">10 (1 717)</td>
<td valign="top" align="center">0.44</td>
<td valign="top" align="center">&#x2212;0.09 (&#x2212;0.19 to 0.02)</td>
<td valign="top" align="center">0.10</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold>HDL-C</bold></td>
</tr>
<tr>
<td valign="top" align="left">All</td>
<td valign="top" align="center">36 (7 287)</td>
<td valign="top" align="center">&#x003C;0.001</td>
<td valign="top" align="center">0.07 (&#x2212;0.03 to 0.16)</td>
<td valign="top" align="center">0.17</td>
</tr>
<tr>
<td valign="top" align="left">Studies in HWE</td>
<td valign="top" align="center">23 (4 795)</td>
<td valign="top" align="center">&#x003C;0.001</td>
<td valign="top" align="center">0.07 (&#x2212;0.05 to 0.19)</td>
<td valign="top" align="center">0.25</td>
</tr>
<tr>
<td valign="top" align="left">Caucasian</td>
<td valign="top" align="center">9 (2 850)</td>
<td valign="top" align="center">&#x003C;0.01</td>
<td valign="top" align="center">&#x2212;0.01 (&#x2212;0.18 to 0.16)</td>
<td valign="top" align="center">0.91</td>
</tr>
<tr>
<td valign="top" align="left">Asian</td>
<td valign="top" align="center">13 (2 678)</td>
<td valign="top" align="center">&#x003C;0.001</td>
<td valign="top" align="center">0.14 (&#x2212;0.02 to 0.31)</td>
<td valign="top" align="center">0.09</td>
</tr>
<tr>
<td valign="top" align="left">Turkish</td>
<td valign="top" align="center">6 (791)</td>
<td valign="top" align="center">&#x003C;0.001</td>
<td valign="top" align="center">0.10 (&#x2212;0.23 to 0.43)</td>
<td valign="top" align="center">0.54</td>
</tr>
<tr>
<td valign="top" align="left">Other ethnicity</td>
<td valign="top" align="center">8 (968)</td>
<td valign="top" align="center">0.20</td>
<td valign="top" align="center">&#x2212;0.00 (&#x2212;0.17 to 0.17)</td>
<td valign="top" align="center">0.97</td>
</tr>
<tr>
<td valign="top" align="left">Female</td>
<td valign="top" align="center">5 (874)</td>
<td valign="top" align="center">0.11</td>
<td valign="top" align="center">0.26 (0.03 to 0.48)</td>
<td valign="top" align="center">0.03</td>
</tr>
<tr>
<td valign="top" align="left">CAD</td>
<td valign="top" align="center">4 (554)</td>
<td valign="top" align="center">&#x003C;0.01</td>
<td valign="top" align="center">0.07 (&#x2212;0.32 to 0.46)</td>
<td valign="top" align="center">0.72</td>
</tr>
<tr>
<td valign="top" align="left">T2DM</td>
<td valign="top" align="center">5 (1 984)</td>
<td valign="top" align="center">0.08</td>
<td valign="top" align="center">&#x2212;0.03 (&#x2212;0.19 to 0.14)</td>
<td valign="top" align="center">0.74</td>
</tr>
<tr>
<td valign="top" align="left">Healthy subjects</td>
<td valign="top" align="center">12 (1 873)</td>
<td valign="top" align="center">&#x003C;0.001</td>
<td valign="top" align="center">0.09 (&#x2212;0.12 to 0.30)</td>
<td valign="top" align="center">0.40</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p><italic>SERPINE1, plasminogen activator inhibitor-1; SMD, standardized mean difference; 95% CI, 95% confidence interval; HWE, Hardy-Weinberg equilibrium; CAD, coronary artery disease; T2DM, type 2 diabetes mellitus; TG, triglycerides; TC, total cholesterol; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol.</italic></p></fn>
</table-wrap-foot>
</table-wrap>
<p>Subgroup analysis by ethnicity showed that the significant effects of the rs1799889 variant on LDL-C (SMD = &#x2013;0.15, 95% CI = &#x2013;0.26 to 0.05, <italic>P</italic> &#x003C; 0.01) and TC (SMD = &#x2013;0.17, 95% CI = &#x2013;0.27 to 0.07, <italic>P</italic> &#x003C; 0.01) levels were only observed in the Asian population. Meanwhile, the significant effect of the rs1799889 variant on TG (SMD = &#x2013;0.31, 95% CI = &#x2013;0.59 to 0.04, <italic>P</italic> = 0.03) level was only observed in the Turkish population. Moreover, a marginally significant effect of the rs1799889 variant on TG (SMD = &#x2013;0.09, 95% CI = &#x2013;0.17 to 0.00, <italic>P</italic> = 0.06) and HDL-C [SMD = 0.14, 95% CI = &#x2013;0.02 to 0.31, <italic>P</italic> = 0.09; <xref ref-type="fig" rid="F5">Figure 5</xref>] levels was observed in the Asian population (<xref ref-type="table" rid="T1">Table 1</xref>). Subgroup analysis by gender showed that the significant effect of the rs1799889 variant on HDL-C level was only detected in female subjects (<xref ref-type="table" rid="T1">Table 1</xref>).</p>
<fig id="F5" position="float">
<label>FIGURE 5</label>
<caption><p>Forest plot of the meta-analysis between <italic>SERPINE1</italic> rs1799889 polymorphism and circulating HDL-C levels.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fcvm-09-859979-g005.tif"/>
</fig>
<p>The analyses were re-performed after excluding the studies with heterogeneity (<xref ref-type="table" rid="T2">Table 2</xref>). Notably, the effects of the rs1799889 variant on lipid levels did not change substantially (<xref ref-type="table" rid="T2">Table 2</xref>), indicating the synthetic results (the analysis data reflect the effect of the rs1799889 variant on lipid profile at total or subgroup level) were robust (refer to <xref ref-type="table" rid="T2">Table 2</xref> for more details).</p>
<table-wrap position="float" id="T2">
<label>TABLE 2</label>
<caption><p>Meta-analysis of <italic>SERPINE1</italic> rs1799889 polymorphism with lipid levels (after eliminating the studies with heterogeneity).</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<thead>
<tr>
<td valign="top" align="left">Groups or subgroups<break/></td>
<td valign="top" align="center">Comparisons (Subjects)</td>
<td valign="top" align="center"><italic>P</italic><sub>H</sub></td>
<td valign="top" align="center">SMD (95% CI)</td>
<td valign="top" align="center"><italic>P</italic><sub>SMD</sub></td>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left" colspan="5"><bold>TG</bold></td>
</tr>
<tr>
<td valign="top" align="left">All</td>
<td valign="top" align="center">38 (9 749)</td>
<td valign="top" align="center">0.43</td>
<td valign="top" align="center">&#x2212;0.05 (&#x2212;0.09 to &#x2212;0.00)</td>
<td valign="top" align="center">0.04</td>
</tr>
<tr>
<td valign="top" align="left">Studies in HWE</td>
<td valign="top" align="center">27 (7 763)</td>
<td valign="top" align="center">0.38</td>
<td valign="top" align="center">0.05 (0.02 to 0.09)</td>
<td valign="top" align="center">&#x003C;0.01</td>
</tr>
<tr>
<td valign="top" align="left">Caucasian</td>
<td valign="top" align="center">12 (5 105)</td>
<td valign="top" align="center">0.23</td>
<td valign="top" align="center">&#x2212;0.02 (&#x2212;0.09 to 0.04)</td>
<td valign="top" align="center">0.43</td>
</tr>
<tr>
<td valign="top" align="left">Asian</td>
<td valign="top" align="center">18 (3 647)</td>
<td valign="top" align="center">0.35</td>
<td valign="top" align="center">&#x2212;0.05 (&#x2212;0.12 to 0.02)</td>
<td valign="top" align="center">0.18</td>
</tr>
<tr>
<td valign="top" align="left">Turkish</td>
<td valign="top" align="center">3 (349)</td>
<td valign="top" align="center">0.80</td>
<td valign="top" align="center">&#x2212;0.17 (&#x2212;0.39 to 0.05)</td>
<td valign="top" align="center">0.13</td>
</tr>
<tr>
<td valign="top" align="left">Other ethnic</td>
<td valign="top" align="center">5 (648)</td>
<td valign="top" align="center">0.73</td>
<td valign="top" align="center">&#x2212;0.13 (&#x2212;0.30 to 0.04)</td>
<td valign="top" align="center">0.14</td>
</tr>
<tr>
<td valign="top" align="left">Male</td>
<td valign="top" align="center">2 (461)</td>
<td valign="top" align="center">0.05</td>
<td valign="top" align="center">&#x2212;0.06 (&#x2212;0.26 to 0.14)</td>
<td valign="top" align="center">0.58</td>
</tr>
<tr>
<td valign="top" align="left">Female</td>
<td valign="top" align="center">6 (1 118)</td>
<td valign="top" align="center">0.47</td>
<td valign="top" align="center">&#x2212;0.12 (&#x2212;0.26 to 0.01)</td>
<td valign="top" align="center">0.07</td>
</tr>
<tr>
<td valign="top" align="left">CAD</td>
<td valign="top" align="center">5 (595)</td>
<td valign="top" align="center">0.80</td>
<td valign="top" align="center">&#x2212;0.10 (&#x2212;0.26 to 0.07)</td>
<td valign="top" align="center">0.25</td>
</tr>
<tr>
<td valign="top" align="left">T2DM</td>
<td valign="top" align="center">5 (1 288)</td>
<td valign="top" align="center">0.13</td>
<td valign="top" align="center">&#x2212;0.11 (&#x2212;0.22 to 0.01)</td>
<td valign="top" align="center">0.08</td>
</tr>
<tr>
<td valign="top" align="left">Healthy subjects</td>
<td valign="top" align="center">12 (4 621)</td>
<td valign="top" align="center">0.55</td>
<td valign="top" align="center">&#x2212;0.01 (&#x2212;0.08 to 0.05)</td>
<td valign="top" align="center">0.73</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold>TC</bold></td>
</tr>
<tr>
<td valign="top" align="left">All</td>
<td valign="top" align="center">45 (9 283)</td>
<td valign="top" align="center">0.37</td>
<td valign="top" align="center">&#x2212;0.08 (&#x2212;0.13 to &#x2212;0.04)</td>
<td valign="top" align="center">&#x003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Studies in HWE</td>
<td valign="top" align="center">30 (6 226)</td>
<td valign="top" align="center">0.50</td>
<td valign="top" align="center">&#x2212;0.07 (&#x2212;0.13 to &#x2212;0.02)</td>
<td valign="top" align="center">0.01</td>
</tr>
<tr>
<td valign="top" align="left">Caucasian</td>
<td valign="top" align="center">13 (3 753)</td>
<td valign="top" align="center">0.25</td>
<td valign="top" align="center">&#x2212;0.06 (&#x2212;0.13 to 0.01)</td>
<td valign="top" align="center">0.09</td>
</tr>
<tr>
<td valign="top" align="left">Asian</td>
<td valign="top" align="center">18 (3 771)</td>
<td valign="top" align="center">0.31</td>
<td valign="top" align="center">&#x2212;0.09 (&#x2212;0.16 to &#x2212;0.02)</td>
<td valign="top" align="center">0.01</td>
</tr>
<tr>
<td valign="top" align="left">Turkish</td>
<td valign="top" align="center">6 (791)</td>
<td valign="top" align="center">0.24</td>
<td valign="top" align="center">&#x2212;0.13 (&#x2212;0.27 to 0.01)</td>
<td valign="top" align="center">0.08</td>
</tr>
<tr>
<td valign="top" align="left">Other ethnic</td>
<td valign="top" align="center">8 (968)</td>
<td valign="top" align="center">0.71</td>
<td valign="top" align="center">&#x2212;0.07 (&#x2212;0.21 to 0.07)</td>
<td valign="top" align="center">0.33</td>
</tr>
<tr>
<td valign="top" align="left">Male</td>
<td valign="top" align="center">2 (461)</td>
<td valign="top" align="center">0.70</td>
<td valign="top" align="center">&#x2212;0.06 (&#x2212;0.26 to 0.14)</td>
<td valign="top" align="center">0.57</td>
</tr>
<tr>
<td valign="top" align="left">Female</td>
<td valign="top" align="center">7 (1 175)</td>
<td valign="top" align="center">0.34</td>
<td valign="top" align="center">&#x2212;0.08 (&#x2212;0.21 to 0.05)</td>
<td valign="top" align="center">0.23</td>
</tr>
<tr>
<td valign="top" align="left">CAD</td>
<td valign="top" align="center">4 (509)</td>
<td valign="top" align="center">0.03</td>
<td valign="top" align="center">&#x2212;0.13 (&#x2212;0.32 to 0.05)</td>
<td valign="top" align="center">0.15</td>
</tr>
<tr>
<td valign="top" align="left">T2DM</td>
<td valign="top" align="center">8 (1 698)</td>
<td valign="top" align="center">0.30</td>
<td valign="top" align="center">&#x2212;0.07 (&#x2212;0.18 to 0.03)</td>
<td valign="top" align="center">0.17</td>
</tr>
<tr>
<td valign="top" align="left">Healthy subjects</td>
<td valign="top" align="center">14 (3 270)</td>
<td valign="top" align="center">0.69</td>
<td valign="top" align="center">&#x2212;0.09 (&#x2212;0.17 to &#x2212;0.02)</td>
<td valign="top" align="center">0.02</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold>LDL-C</bold></td>
</tr>
<tr>
<td valign="top" align="left">All</td>
<td valign="top" align="center">24 (3 662)</td>
<td valign="top" align="center">0.41</td>
<td valign="top" align="center">&#x2212;0.11 (&#x2212;0.18 to &#x2212;0.04)</td>
<td valign="top" align="center">&#x003C;0.01</td>
</tr>
<tr>
<td valign="top" align="left">Studies in HWE</td>
<td valign="top" align="center">14 (1 579)</td>
<td valign="top" align="center">0.38</td>
<td valign="top" align="center">&#x2212;0.10 (&#x2212;0.15 to &#x2212;0.05)</td>
<td valign="top" align="center">&#x003C;0.01</td>
</tr>
<tr>
<td valign="top" align="left">Caucasian</td>
<td valign="top" align="center">3 (806)</td>
<td valign="top" align="center">0.62</td>
<td valign="top" align="center">&#x2212;0.07 (&#x2212;0.22 to 0.08)</td>
<td valign="top" align="center">0.39</td>
</tr>
<tr>
<td valign="top" align="left">Asian</td>
<td valign="top" align="center">11 (1 737)</td>
<td valign="top" align="center">0.36</td>
<td valign="top" align="center">&#x2212;0.15 (&#x2212;0.25 to &#x2212;0.05)</td>
<td valign="top" align="center">&#x003C;0.01</td>
</tr>
<tr>
<td valign="top" align="left">Turkish</td>
<td valign="top" align="center">4 (458)</td>
<td valign="top" align="center">0.13</td>
<td valign="top" align="center">&#x2212;0.09 (&#x2212;0.29 to 0.10)</td>
<td valign="top" align="center">0.34</td>
</tr>
<tr>
<td valign="top" align="left">Other ethnicity</td>
<td valign="top" align="center">6 (661)</td>
<td valign="top" align="center">0.45</td>
<td valign="top" align="center">&#x2212;0.05 (&#x2212;0.22 to 0.12)</td>
<td valign="top" align="center">0.55</td>
</tr>
<tr>
<td valign="top" align="left">Female</td>
<td valign="top" align="center">5 (874)</td>
<td valign="top" align="center">0.88</td>
<td valign="top" align="center">&#x2212;0.14 (&#x2212;0.31 to 0.03)</td>
<td valign="top" align="center">0.16</td>
</tr>
<tr>
<td valign="top" align="left">CAD</td>
<td valign="top" align="center">4 (554)</td>
<td valign="top" align="center">0.08</td>
<td valign="top" align="center">0.03 (&#x2212;0.07 to 0.12)</td>
<td valign="top" align="center">0.10</td>
</tr>
<tr>
<td valign="top" align="left">T2DM</td>
<td valign="top" align="center">2 (224)</td>
<td valign="top" align="center">0.96<break/></td>
<td valign="top" align="center">&#x2212;0.15 (&#x2212;0.42 to 0.13)</td>
<td valign="top" align="center">0.29</td>
</tr>
<tr>
<td valign="top" align="left">Healthy subjects</td>
<td valign="top" align="center">10 (1 717)</td>
<td valign="top" align="center">0.44</td>
<td valign="top" align="center">&#x2212;0.09 (&#x2212;0.19 to 0.02)</td>
<td valign="top" align="center">0.10</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold>HDL-C</bold></td>
</tr>
<tr>
<td valign="top" align="left">All</td>
<td valign="top" align="center">28 (5 897)</td>
<td valign="top" align="center">0.12</td>
<td valign="top" align="center">&#x2212;0.02 (&#x2212;0.08 to 0.03)</td>
<td valign="top" align="center">0.41</td>
</tr>
<tr>
<td valign="top" align="left">Studies in HWE</td>
<td valign="top" align="center">19 (4 238)</td>
<td valign="top" align="center">0.05</td>
<td valign="top" align="center">&#x2212;0.03 (&#x2212;0.12 to 0.07)</td>
<td valign="top" align="center">0.57</td>
</tr>
<tr>
<td valign="top" align="left">Caucasian</td>
<td valign="top" align="center">7 (2 554)</td>
<td valign="top" align="center">0.23</td>
<td valign="top" align="center">&#x2212;0.02 (&#x2212;0.10 to 0.07)</td>
<td valign="top" align="center">0.70</td>
</tr>
<tr>
<td valign="top" align="left">Asian</td>
<td valign="top" align="center">8 (1 693)</td>
<td valign="top" align="center">0.10</td>
<td valign="top" align="center">&#x2212;0.05 (&#x2212;0.15 to 0.05)</td>
<td valign="top" align="center">0.33</td>
</tr>
<tr>
<td valign="top" align="left">Turkish</td>
<td valign="top" align="center">5 (682)</td>
<td valign="top" align="center">0.27</td>
<td valign="top" align="center">&#x2212;0.02 (&#x2212;0.17 to 0.14)</td>
<td valign="top" align="center">0.81</td>
</tr>
<tr>
<td valign="top" align="left">Other ethnicity</td>
<td valign="top" align="center">8 (968)</td>
<td valign="top" align="center">0.20</td>
<td valign="top" align="center">0.01 (&#x2212;0.13 to 0.15)</td>
<td valign="top" align="center">0.89</td>
</tr>
<tr>
<td valign="top" align="left">Female</td>
<td valign="top" align="center">3 (238)</td>
<td valign="top" align="center">0.05</td>
<td valign="top" align="center">0.14 (&#x2212;0.17 to 0.44)</td>
<td valign="top" align="center">0.37</td>
</tr>
<tr>
<td valign="top" align="left">CAD</td>
<td valign="top" align="center">3 (468)</td>
<td valign="top" align="center">0.02</td>
<td valign="top" align="center">&#x2212;0.05 (&#x2212;0.24 to 0.14)</td>
<td valign="top" align="center">0.60</td>
</tr>
<tr>
<td valign="top" align="left">T2DM</td>
<td valign="top" align="center">5 (1 984)</td>
<td valign="top" align="center">0.08</td>
<td valign="top" align="center">&#x2212;0.02 (&#x2212;0.12 to 0.07)</td>
<td valign="top" align="center">0.64</td>
</tr>
<tr>
<td valign="top" align="left">Healthy subjects</td>
<td valign="top" align="center">9 (1 526)</td>
<td valign="top" align="center">0.34</td>
<td valign="top" align="center">0.00 (&#x2212;0.11 to 0.11)</td>
<td valign="top" align="center">0.99</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p><italic>SERPINE1, plasminogen activator inhibitor-1; SMD, standardized mean difference; 95% CI, 95% confidence interval; HWE, Hardy-Weinberg equilibrium; CAD, coronary artery disease; T2DM, type 2 diabetes mellitus; TG, triglycerides; TC, total cholesterol; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol.</italic></p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="S3.SS3">
<title>Evaluation of Heterogeneity</title>
<p>In analyzing the effects of the rs1799889 variant on lipid profile, significant heterogeneity was observed (<xref ref-type="table" rid="T1">Table 1</xref>). Seven (Segu&#x00ED;, 2000; van Harmelen, 2000; Lopes, 2003; Wang, 2007; Katranc&#x0131;o&#x011F;lu, 2011; Borisova, 2018; Khalaf, 2019), two (Zhang, 2003, 2004), two (Zietz, 2006; Borisova, 2018), and eight (Margaglione, 1997; Chen, 2003; Zhang, 2003, 2004; Katranc&#x0131;o&#x011F;lu, 2011; Sun, SK1 2013, Sun SK2 2013, Karabouta, 2016) comparisons (refer to <xref ref-type="supplementary-material" rid="TS1">Supplementary Material</xref> for more details about reference citations) were identified as the potential sources of heterogeneity to TG, TC, LDL-C, and HDL-C, respectively. However, the recalculated results did not change significantly after excluding these comparisons (refer to <xref ref-type="table" rid="T2">Table 2</xref> for more details).</p>
</sec>
<sec id="S3.SS4">
<title>Publication Bias Test</title>
<p>There was no publication bias in the synthetic results (refer to <xref ref-type="supplementary-material" rid="DS1">Supplementary Figures 1</xref>&#x2013;<xref ref-type="supplementary-material" rid="DS1">4</xref> for more details), indicating the synthetic results were reliable.</p>
</sec>
</sec>
<sec id="S4" sec-type="discussion">
<title>Discussion</title>
<p>Our data showed that the rs1799889 variant had significant effects on circulating TG, TC, and LDL-C levels. Subgroup analysis further indicated the significant effects of the rs1799889 variant on TC and LDL-C levels primarily in the Asian population.</p>
<p>Several underlying mechanisms could be proposed to explain the effects of the rs1799889 variant on lipids levels. (1) By repressing peroxisome proliferator-activated receptor &#x03B3; (PPAR&#x03B3;) expression: PPAR&#x03B3;, a known adipogenic gene (<xref ref-type="bibr" rid="B20">20</xref>), plays a major role in TG synthesis (<xref ref-type="bibr" rid="B21">21</xref>), the inhibition of PAI-1 activity caused by rs1799889 (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>) may repress the expression of PPAR&#x03B3; (<xref ref-type="bibr" rid="B3">3</xref>). As a result, the synthesis of TG was reduced; accordingly, the plasma levels of TG were decreased (<xref ref-type="table" rid="T1">Tables 1</xref>, <xref ref-type="table" rid="T2">2</xref>). (2) By disturbing the expression of PCSK9: PCSK9 plays a central role in the degradation of LDLR; the decreased PAI-1 activity caused by rs1799889 (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>) may reduce PCSK9 expression (<xref ref-type="bibr" rid="B6">6</xref>), therefore, upregulating LDLR; therefore, circulating LDL-C levels was decreased (<xref ref-type="table" rid="T1">Tables 1</xref>, <xref ref-type="table" rid="T2">2</xref>). (3) By modulating the expression of low-density lipoprotein receptor-related protein (LRP). SERPINE1 contains a high-affinity binding site for LRP (<xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B23">23</xref>), and the fulfilling of some important physiological functions depends on the cooperation between SERPINE1 and LRP (<xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B25">25</xref>). Therefore, the largely decreased PAI-1 activity caused by rs1799889 (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>) may affect the expression of LRP.</p>
<p>This analysis indicated the 5G allele of the rs1799889 variant significantly decreased TG, TC, and LDL-C levels (<xref ref-type="table" rid="T1">Tables 1</xref>, <xref ref-type="table" rid="T2">2</xref>), when combined with previous meta-analyses (<xref ref-type="bibr" rid="B7">7</xref>&#x2013;<xref ref-type="bibr" rid="B10">10</xref>), indicating the 5G allele of the rs1799889 variant was a causal genetic marker for decreased CAD risk.</p>
<p>According to the 2018 ACC/AHA (<xref ref-type="bibr" rid="B26">26</xref>), the 2019 ESC/EAS (<xref ref-type="bibr" rid="B27">27</xref>), and the adult treatment panel III (ATP III) cholesterol guidelines (<xref ref-type="bibr" rid="B28">28</xref>), LDL-C was regarded as the major initiating factor for CAD and used as the main intervention target, while TC, HDL-C, and TG were used as the secondary targets. In this study, significantly reduced LDL-C levels were observed in subjects with the rs1799889 variant (<xref ref-type="table" rid="T1">Tables 1</xref>, <xref ref-type="table" rid="T2">2</xref>), indicating the 4G/5G insertion/deletion sequence of <italic>SERPINE1</italic> potentially be the target for CAD therapy. Moreover, subgroup analysis by ethnicity showed that the significant effects of the rs1799889 variant on LDL-C and TC levels were primarily in Asians (<xref ref-type="table" rid="T1">Tables 1</xref>, <xref ref-type="table" rid="T2">2</xref>), indicating the Asians with the 5G allele of the rs1799889 variant may have a reduced CAD risk. Intriguingly, this speculation was verified by Li et al. (<xref ref-type="bibr" rid="B29">29</xref>).</p>
<sec id="S4.SS1">
<title>Strengths and Limitations</title>
<p>To the best of our knowledge, this is the first meta-analysis to investigate the effects of the <italic>SERPINE1</italic> 4G/5G insertion/deletion sequence on circulating lipid levels. Several strengths of the meta-analysis should be noted. For instance, all data were recalculated after excluding the studies with heterogeneity, which no doubt advances the preciseness of conclusions drawn in this manuscript. In addition, the analysis results benefit insight into the mechanism underlying the rs1799889 variant and CAD. More importantly, our data indicate that the 4G/5G insertion/deletion sequence of the <italic>SERPINE1</italic> gene potentially be the target for CAD therapy. However, this meta-analysis did not investigate the interaction between the rs1799889 variant and environmental factors on lipid levels due to the lack of available data from the included studies.</p>
</sec>
</sec>
<sec id="S5" sec-type="conclusion">
<title>Conclusion</title>
<p>The rs1799889 variant of <italic>SERPINE1</italic> is a protective genetic factor against CAD, and the Asian population with the 5G allele of the rs1799889 variant may have a reduced CAD risk.</p>
</sec>
<sec id="S6" sec-type="data-availability">
<title>Data Availability Statement</title>
<p>The original contributions presented in this study are included in the article/<xref ref-type="supplementary-material" rid="TS1">Supplementary Material</xref>, further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec id="S7">
<title>Author Contributions</title>
<p>ZL, BW, JW, and YL conceived and designed this study as well as drafted the manuscript and performed the statistical analyses. HL, YZ, YP, XL, and YF carried out the searches and collected the data. All authors reviewed and approved the final manuscript.</p>
</sec>
<sec id="conf1" sec-type="COI-statement">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="pudiscl1" sec-type="disclaimer">
<title>Publisher&#x2019;s Note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
</body>
<back>
<sec id="S8" sec-type="supplementary-material">
<title>Supplementary Material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fcvm.2022.859979/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fcvm.2022.859979/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Table_1.docx" id="TS1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Data_Sheet_1.docx" id="DS1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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