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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Oncol.</journal-id>
<journal-title>Frontiers in Oncology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Oncol.</abbrev-journal-title>
<issn pub-type="epub">2234-943X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fonc.2021.754162</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Oncology</subject>
<subj-group>
<subject>Systematic Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>The Prognosis of Leptin rs2167270 G &gt; A (G19A) Polymorphism in the Risk of Cancer: A Meta-Analysis</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Zhang</surname>
<given-names>Aiqiao</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1422532"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Shangren</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhang</surname>
<given-names>Fujun</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Wei</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Qian</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Liu</surname>
<given-names>Xiaoqiang</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Neonatology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine</institution>, <addr-line>Tianjin</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Neonatology, National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion</institution>, <addr-line>Tianjin</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Urology, Tianjin Medical University General Hospital</institution>, <addr-line>Tianjin</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Walter Hern&#xe1;n Pavicic, Consejo Nacional de Investigaciones Cient&#xed;ficas y T&#xe9;cnicas (CONICET), Argentina</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Manuel Pires Bicho, University of Lisbon, Portugal; Rajeev K. Singla, Sichuan University, China</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Xiaoqiang Liu, <email xlink:href="mailto:1291313638@qq.com">1291313638@qq.com</email>
</p>
</fn>
<fn fn-type="equal" id="fn003">
<p>&#x2020;These authors have contributed equally to this work</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Cancer Genetics, a section of the journal Frontiers in Oncology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>18</day>
<month>11</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>11</volume>
<elocation-id>754162</elocation-id>
<history>
<date date-type="received">
<day>06</day>
<month>08</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>29</day>
<month>10</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2021 Zhang, Wang, Zhang, Li, Li and Liu</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Zhang, Wang, Zhang, Li, Li and Liu</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>Although the effect of the LEP G19A (rs2167270) polymorphism on cancers is assumed, the results of its influence have been contradictory. A meta-analysis was conducted to precisely verify the relationships between LEP G19A and the development of digestion-related cancers.</p>
</sec>
<sec>
<title>Methods</title>
<p>Investigators systematically searched the literature in PubMed, Embase, and Web of Science and used STATA software 14.0 for the meta&#x2212;analysis. The odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to evaluate the associations. Subgroup analyses stratified by ethnicity, cancer type, and cancer system were further conducted to assess the relationship between the LEP G19A polymorphism and digestion-related cancers.</p>
</sec>
<sec>
<title>Results</title>
<p>In the overall population, we found a significant relationship with overall cancer (allele comparison: OR = 0.921, <italic>p</italic> = 0.000; dominant comparison: OR = 0.923, <italic>p</italic> = 0.004; recessive comparison: OR = 0.842, <italic>p</italic> = 0.000; homozygote model: OR = 0.0843, <italic>p</italic> = 0.001). In a subgroup analysis conducted by ethnicity, we obtained significant results in Asians (Asian allele comparison: OR = 0.885, <italic>p</italic> = 0.000; dominant comparison: OR = 0.862, <italic>p</italic> = 0.000; homozygote model: OR = 0.824, <italic>p</italic> = 0.039; and heterozygote comparison: OR = 0.868, <italic>p</italic> = 0.000) but not in Caucasians. In a subgroup analysis conducted by cancer type and cancer system, we obtained significant results that the LEP G19A polymorphism may decrease the risk of colorectal cancer, esophageal cancer, digestive system cancer, and urinary system cancer.</p>
</sec>
<sec>
<title>Conclusions</title>
<p>This meta-analysis revealed that the LEP G19A polymorphism may decrease the risk of cancer.</p>
</sec>
</abstract>
<kwd-group>
<kwd>leptin (LEP)</kwd>
<kwd>cancer</kwd>
<kwd>polymorphism</kwd>
<kwd>A19G</kwd>
<kwd>rs2167270</kwd>
</kwd-group>
<contract-sponsor id="cn001">Zhao Yi-Cheng Medical Science Foundation<named-content content-type="fundref-id">10.13039/501100016310</named-content>
</contract-sponsor>
<counts>
<fig-count count="5"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="47"/>
<page-count count="9"/>
<word-count count="4109"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>It is well known that cancer is one of major causes of death with over 6.1 million projected to die each year, and morbidity rates have increased gradually over the past decade (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>), so it has been a public health burden worldwide. The reason for cancer is complicated and the etiology and mechanism of carcinogenesis are not clearly elucidated to date. It was widely accepted that the interplay between environmental factors, genetics, and lifestyle plays an important role in the carcinogenesis according to epidemiology. There is mounting evidence indicating that many metabolic diseases such as obesity and diabetes may significantly increase the risk of cancer (<xref ref-type="bibr" rid="B3">3</xref>&#x2013;<xref ref-type="bibr" rid="B5">5</xref>). The polymorphism of obesity and diabetes gene may be associated with genetic susceptibility of cancer.</p>
<p>Leptin (LEP), a 16-kDa hormone of energy expenditure, is a balancing mediator of homeostasis by regulating acquisition and consumption of energy, which was a basic pathophysiological process in normal cells and cancer cells. Many epidemiological studies have revealed the link between LEP and the development of many kinds of cancers (<xref ref-type="bibr" rid="B6">6</xref>&#x2013;<xref ref-type="bibr" rid="B8">8</xref>). Among the pathophysiological mechanisms of cancer, LEP seems relevant to the proliferation of cancer stem cells (<xref ref-type="bibr" rid="B9">9</xref>). Some studies also revealed that LEP through its signal pathways regulating energy intake and expenditure [MAPK, PI3K, mTOR, and JAK/STAT (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B11">11</xref>)] produced an effect in angiogenesis processes that were critical in the genesis and development of cancer (<xref ref-type="bibr" rid="B12">12</xref>). Pathophysiological mechanisms of cancer such as inflammation, invasion, and metastasis are also favored by LEP (<xref ref-type="bibr" rid="B13">13</xref>&#x2013;<xref ref-type="bibr" rid="B15">15</xref>). So, LEP may be involved in various pathological processes of carcinogenesis.</p>
<p>Single-nucleotide polymorphism can change the functions of genes and the expression of protein. LEP G19A polymorphism, positioning at the 5&#x2032;-untranslated region of gene, may impact mRNA translation and change the serum level of LEP. With the development of molecular epidemiology, various studies have demonstrated that LEP G19A polymorphism is related to cancer risk (<xref ref-type="bibr" rid="B16">16</xref>&#x2013;<xref ref-type="bibr" rid="B19">19</xref>). However, results between G19A polymorphism with cancers have been inconsistent or inconclusive. Therefore, we performed a meta&#xad;analysis to verify the correlation between the G19A mutation of the LEP gene and susceptibility to cancers.</p>
<p>In this study, we conducted a meta-analysis to verify whether the G19A polymorphism of the LEP gene affects the risk of cancer.</p>
</sec>
<sec id="s2">
<title>Methods</title>
<sec id="s2_1">
<title>Literature Search</title>
<p>A comprehensive literature search of PubMed, Embase, and Web of Science was performed to search all potential studies that involved the relevance between the G19A polymorphism and cancers prior to June 2021. Our study contained the following terms: (&#x201c;leptin&#x201d; OR &#x201c;LEP&#x201d; OR &#x201c;G19A&#x201d; OR &#x201c;rs2167270&#x201d;) AND (&#x201c;polymorphism&#x201d; OR &#x201c;variant&#x201d; OR &#x201c;mutation&#x201d;) AND (&#x201c;malignancy&#x201d; OR &#x201c;cancer&#x201d; OR &#x201c;carcinoma&#x201d; OR &#x201c;neoplasm&#x201d;).</p>
</sec>
<sec id="s2_2">
<title>Inclusion and Exclusion Criteria</title>
<p>The inclusion criteria were as follows: (1) investigate the association between the LEP G19A (rs2167270) mutation and cancers; (2) meet cohort design or case&#x2013;control design; (3) abundant data should behave to estimate an odds ratio (OR) and 95% confidence interval; (4) results were reported in English; and (5) include human subjects. We adopted the following exclusion criteria: (1) duplicated studies; (2) studies in which subjects were not human; and (3) studies in which we could not obtain sufficient raw data.</p>
</sec>
<sec id="s2_3">
<title>Data Extraction</title>
<p>Investigators extracted genotype data independently, and every data point reached a consensus. The extracted data contained the (1) name of the first author; (2) year of publication; (3) ethnicity of cases and controls; (4) cancer type of studies; and (5) frequency of LEP G19A in genes.</p>
</sec>
<sec id="s2_4">
<title>Statistical Analysis</title>
<p>We computed ORs and their 95% CIs to estimate the association between the LEP G19A (rs2167270) mutation and cancers. The pooled ORs and their 95% CIs were computed for genes using the following five models: dominant model (AA + AG vs. GG), recessive model (AA vs. GG + AG), allele model (A vs. G), homozygous model (AA vs. GG), and heterozygote model (AG vs. GG).</p>
<p>The <italic>Q</italic> test was used to estimate heterogeneity between different studies, and <italic>p</italic> &lt; 0.05 was considered significant for heterogeneity. In addition, inconsistency was quantified by the <italic>I</italic>
<sup>2</sup> statistic. Twenty-five percent and 50% of the <italic>I</italic>
<sup>2</sup> values indicated low and high levels of heterogeneity, respectively. An <italic>I</italic>
<sup>2</sup> &lt; 50% suggested that no heterogeneity existed. When heterogeneity existed, the fixed effects model (FEM) was utilized; otherwise, the random-effects model (REM) was utilized for calculation.</p>
<p>To evaluate the specific effects of ethnicity, cancer type, and cancer system, investigators performed subgroup analyses by ethnicity, cancer type, and cancer system.</p>
<p>Sensitivity analyses were performed to evaluate the stability of the results. A funnel plot of Egger&#x2019;s or Begg&#x2019;s test was conducted to reveal possible publication bias. We used the Newcastle-Ottawa Scale to assess the including literature quality. All meta-analyses were performed using STATA software (Version 12.0, College Station, TX).</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<title>Results</title>
<sec id="s3_1">
<title>Study Characteristics</title>
<p>Depending on the search strategy, 633 articles were retrieved (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). Among them, 103 articles were eligible after excluding repeated publications. By reviewing the titles and study abstracts, 58 articles were excluded. Of the remaining 45 studies, 26 articles were excluded, including 11 studies that were not focused on the LEP G19A genetic mutation. Five studies were meta-analyses. Eight studies were on other disorders that were not cancer. Two articles did not provide raw data. Finally, 19 studies conformed to our meta-analyses, and <xref ref-type="table" rid="T1">
<bold>Tables&#xa0;1</bold>
</xref> and <xref ref-type="table" rid="T2">
<bold>2</bold>
</xref> summarize the extracted data (<xref ref-type="bibr" rid="B16">16</xref>&#x2013;<xref ref-type="bibr" rid="B34">34</xref>).</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Flowchart of literature selection.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-754162-g001.tif"/>
</fig>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>The characters of included studies in the meta-analysis.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" rowspan="2" align="left">Author</th>
<th valign="top" rowspan="2" align="center">Year</th>
<th valign="top" rowspan="2" align="center">Country</th>
<th valign="top" rowspan="2" align="center">Ethnicity</th>
<th valign="top" rowspan="2" align="center">Cancer type</th>
<th valign="top" rowspan="2" align="center">Cancer system</th>
<th valign="top" colspan="2" align="center">Genotype</th>
</tr>
<tr>
<th valign="top" align="center">Case</th>
<th valign="top" align="center">Control</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Skibola et&#xa0;al. (<xref ref-type="bibr" rid="B16">16</xref>)</td>
<td valign="top" align="center">2004</td>
<td valign="top" align="left">USA</td>
<td valign="top" align="left">Caucasians</td>
<td valign="top" align="left">Non-Hodgkin lymphoma</td>
<td valign="top" align="left">Hematopoietic malignancy</td>
<td valign="top" align="center">373</td>
<td valign="top" align="center">805</td>
</tr>
<tr>
<td valign="top" align="left">Willett et&#xa0;al. (<xref ref-type="bibr" rid="B17">17</xref>)</td>
<td valign="top" align="center">2005</td>
<td valign="top" align="left">UK</td>
<td valign="top" align="left">Caucasians</td>
<td valign="top" align="left">Non-Hodgkin lymphoma</td>
<td valign="top" align="left">Hematopoietic malignancy</td>
<td valign="top" align="center">590</td>
<td valign="top" align="center">754</td>
</tr>
<tr>
<td valign="top" align="left">Slattery et&#xa0;al. (<xref ref-type="bibr" rid="B18">18</xref>)</td>
<td valign="top" align="center">2008</td>
<td valign="top" align="left">USA</td>
<td valign="top" align="left">Mixed</td>
<td valign="top" align="left">Colorectal cancer</td>
<td valign="top" align="left">Digestive system cancer</td>
<td valign="top" align="center">1,567</td>
<td valign="top" align="center">1,965</td>
</tr>
<tr>
<td valign="top" align="left">Doecke et&#xa0;al. (<xref ref-type="bibr" rid="B20">20</xref>)</td>
<td valign="top" align="center">2008</td>
<td valign="top" align="left">Australia</td>
<td valign="top" align="left">Caucasians</td>
<td valign="top" align="left">Esophageal cancer</td>
<td valign="top" align="left">Digestive system cancer</td>
<td valign="top" align="center">774</td>
<td valign="top" align="center">1,352</td>
</tr>
<tr>
<td valign="top" align="left">Tsilidis et&#xa0;al. (<xref ref-type="bibr" rid="B19">19</xref>)</td>
<td valign="top" align="center">2009</td>
<td valign="top" align="left">USA</td>
<td valign="top" align="left">Mixed</td>
<td valign="top" align="left">Colorectal cancer</td>
<td valign="top" align="left">Digestive system cancer</td>
<td valign="top" align="center">204</td>
<td valign="top" align="center">362</td>
</tr>
<tr>
<td valign="top" align="left">Wang et&#xa0;al. (<xref ref-type="bibr" rid="B21">21</xref>)</td>
<td valign="top" align="center">2009</td>
<td valign="top" align="left">USA</td>
<td valign="top" align="left">Caucasians</td>
<td valign="top" align="left">Prostate cancer</td>
<td valign="top" align="left">Urinary system cancer</td>
<td valign="top" align="center">253</td>
<td valign="top" align="center">257</td>
</tr>
<tr>
<td valign="top" align="left">Moore et&#xa0;al. (<xref ref-type="bibr" rid="B22">22</xref>)</td>
<td valign="top" align="center">2009</td>
<td valign="top" align="left">Finland</td>
<td valign="top" align="left">Caucasians</td>
<td valign="top" align="left">Prostate cancer</td>
<td valign="top" align="left">Urinary system cancer</td>
<td valign="top" align="center">945</td>
<td valign="top" align="center">840</td>
</tr>
<tr>
<td valign="top" align="left">Partida-Perez et&#xa0;al. (<xref ref-type="bibr" rid="B23">23</xref>)</td>
<td valign="top" align="center">2010</td>
<td valign="top" align="left">Mexico</td>
<td valign="top" align="left">Caucasians</td>
<td valign="top" align="left">Colorectal cancer</td>
<td valign="top" align="left">Digestive system cancer</td>
<td valign="top" align="center">68</td>
<td valign="top" align="center">102</td>
</tr>
<tr>
<td valign="top" align="left">Kim et&#xa0;al. (<xref ref-type="bibr" rid="B24">24</xref>)</td>
<td valign="top" align="center">2012</td>
<td valign="top" align="left">Korea</td>
<td valign="top" align="left">Asian</td>
<td valign="top" align="left">Breast cancer</td>
<td valign="top" align="left">Others</td>
<td valign="top" align="center">400</td>
<td valign="top" align="center">452</td>
</tr>
<tr>
<td valign="top" align="left">Zhang et&#xa0;al. (<xref ref-type="bibr" rid="B25">25</xref>)</td>
<td valign="top" align="center">2012</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">Asian</td>
<td valign="top" align="left">Non-Hodgkin lymphoma</td>
<td valign="top" align="left">Hematopoietic malignancy</td>
<td valign="top" align="center">514</td>
<td valign="top" align="center">557</td>
</tr>
<tr>
<td valign="top" align="left">Qiu et&#xa0;al. (<xref ref-type="bibr" rid="B26">26</xref>)</td>
<td valign="top" align="center">2017</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">Asian</td>
<td valign="top" align="left">Esophageal cancer</td>
<td valign="top" align="left">Digestive system cancer</td>
<td valign="top" align="center">502</td>
<td valign="top" align="center">1,496</td>
</tr>
<tr>
<td valign="top" align="left">Zhang et&#xa0;al. (<xref ref-type="bibr" rid="B27">27</xref>)</td>
<td valign="top" align="center">2018</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">Asian</td>
<td valign="top" align="left">Hepatocellular carcinoma</td>
<td valign="top" align="left">Digestive system cancer</td>
<td valign="top" align="center">584</td>
<td valign="top" align="center">923</td>
</tr>
<tr>
<td valign="top" align="left">Huang et&#xa0;al. (<xref ref-type="bibr" rid="B28">28</xref>)</td>
<td valign="top" align="center">2018</td>
<td valign="top" align="left">USA</td>
<td valign="top" align="left">Mixed</td>
<td valign="top" align="left">Colorectal cancer</td>
<td valign="top" align="left">Digestive system cancer</td>
<td valign="top" align="center">134</td>
<td valign="top" align="center">259</td>
</tr>
<tr>
<td valign="top" align="left">Yang et&#xa0;al. (<xref ref-type="bibr" rid="B29">29</xref>)</td>
<td valign="top" align="center">2019</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">Asian</td>
<td valign="top" align="left">Esophageal cancer</td>
<td valign="top" align="left">Digestive system cancer</td>
<td valign="top" align="center">1,063</td>
<td valign="top" align="center">1,677</td>
</tr>
<tr>
<td valign="top" align="left">Lin et&#xa0;al. (<xref ref-type="bibr" rid="B30">30</xref>)</td>
<td valign="top" align="center">2020</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">Asian</td>
<td valign="top" align="left">Colorectal cancer</td>
<td valign="top" align="left">Digestive system cancer</td>
<td valign="top" align="center">1,003</td>
<td valign="top" align="center">1,303</td>
</tr>
<tr>
<td valign="top" align="left">Ma (<xref ref-type="bibr" rid="B31">31</xref>)</td>
<td valign="top" align="center">2020</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">Asian</td>
<td valign="top" align="left">Gastric cancer</td>
<td valign="top" align="left">Digestive system cancer</td>
<td valign="top" align="center">379</td>
<td valign="top" align="center">463</td>
</tr>
<tr>
<td valign="top" align="left">Al-Khatib et&#xa0;al. (<xref ref-type="bibr" rid="B32">32</xref>)</td>
<td valign="top" align="center">2020</td>
<td valign="top" align="left">Jordan</td>
<td valign="top" align="left">Caucasians</td>
<td valign="top" align="left">Large B-Cell lymphoma</td>
<td valign="top" align="left">Hematopoietic malignancy</td>
<td valign="top" align="center">118</td>
<td valign="top" align="center">228</td>
</tr>
<tr>
<td valign="top" align="left">Mao et&#xa0;al. (<xref ref-type="bibr" rid="B33">33</xref>)</td>
<td valign="top" align="center">2020</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">Asian</td>
<td valign="top" align="left">Bladder cancer</td>
<td valign="top" align="left">Urinary system cancer</td>
<td valign="top" align="center">353</td>
<td valign="top" align="center">433</td>
</tr>
<tr>
<td valign="top" align="left">Mhaidat et&#xa0;al. (<xref ref-type="bibr" rid="B34">34</xref>)</td>
<td valign="top" align="center">2021</td>
<td valign="top" align="left">Jordan</td>
<td valign="top" align="left">Caucasians</td>
<td valign="top" align="left">Colorectal cancer</td>
<td valign="top" align="left">Digestive system cancer</td>
<td valign="top" align="center">54</td>
<td valign="top" align="center">23</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Distribution of LEP G19A polymorphism genotype and allele.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<td valign="top" rowspan="3" align="left">Author</td>
<td valign="top" rowspan="3" align="left">Year</td>
<td valign="top" colspan="10" align="left">Genotype distribution</td>
<td valign="top" rowspan="3" align="left">HWE</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">Case</td>
<td valign="top" colspan="5" align="left">Control</td>
</tr>
<tr>
<td valign="top" align="left">AA</td>
<td valign="top" align="left">AG</td>
<td valign="top" align="left">GG</td>
<td valign="top" align="left">A</td>
<td valign="top" align="left">G</td>
<td valign="top" align="left">AA</td>
<td valign="top" align="left">AG</td>
<td valign="top" align="left">GG</td>
<td valign="top" align="left">A</td>
<td valign="top" align="left">G</td>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Skibola et&#xa0;al. (<xref ref-type="bibr" rid="B16">16</xref>)</td>
<td valign="top" align="center">2004</td>
<td valign="top" align="center">36</td>
<td valign="top" align="center">169</td>
<td valign="top" align="center">168</td>
<td valign="top" align="center">241</td>
<td valign="top" align="center">505</td>
<td valign="top" align="center">119</td>
<td valign="top" align="center">335</td>
<td valign="top" align="center">351</td>
<td valign="top" align="center">573</td>
<td valign="top" align="center">1,037</td>
<td valign="top" align="center">0.009</td>
</tr>
<tr>
<td valign="top" align="left">Willett et&#xa0;al. (<xref ref-type="bibr" rid="B17">17</xref>)</td>
<td valign="top" align="center">2005</td>
<td valign="top" align="center">79</td>
<td valign="top" align="center">276</td>
<td valign="top" align="center">235</td>
<td valign="top" align="center">434</td>
<td valign="top" align="center">746</td>
<td valign="top" align="center">122</td>
<td valign="top" align="center">357</td>
<td valign="top" align="center">275</td>
<td valign="top" align="center">601</td>
<td valign="top" align="center">907</td>
<td valign="top" align="center">0.734</td>
</tr>
<tr>
<td valign="top" align="left">Slattery et&#xa0;al. (<xref ref-type="bibr" rid="B18">18</xref>)</td>
<td valign="top" align="center">2008</td>
<td valign="top" align="center">190</td>
<td valign="top" align="center">766</td>
<td valign="top" align="center">611</td>
<td valign="top" align="center">1,146</td>
<td valign="top" align="center">1,988</td>
<td valign="top" align="center">304</td>
<td valign="top" align="center">867</td>
<td valign="top" align="center">794</td>
<td valign="top" align="center">1,475</td>
<td valign="top" align="center">2,455</td>
<td valign="top" align="center">0.009</td>
</tr>
<tr>
<td valign="top" align="left">Doecke et&#xa0;al. (<xref ref-type="bibr" rid="B20">20</xref>)</td>
<td valign="top" align="center">2008</td>
<td valign="top" align="center">34</td>
<td valign="top" align="center">130</td>
<td valign="top" align="center">94</td>
<td valign="top" align="center">198</td>
<td valign="top" align="center">318</td>
<td valign="top" align="center">176</td>
<td valign="top" align="center">622</td>
<td valign="top" align="center">541</td>
<td valign="top" align="center">974</td>
<td valign="top" align="center">1,704</td>
<td valign="top" align="center">0.633</td>
</tr>
<tr>
<td valign="top" align="left">Tsilidis et&#xa0;al. (<xref ref-type="bibr" rid="B19">19</xref>)</td>
<td valign="top" align="center">2009</td>
<td valign="top" align="center">33</td>
<td valign="top" align="center">91</td>
<td valign="top" align="center">80</td>
<td valign="top" align="center">157</td>
<td valign="top" align="center">251</td>
<td valign="top" align="center">61</td>
<td valign="top" align="center">170</td>
<td valign="top" align="center">131</td>
<td valign="top" align="center">292</td>
<td valign="top" align="center">432</td>
<td valign="top" align="center">0.940</td>
</tr>
<tr>
<td valign="top" align="left">Wang et&#xa0;al. (<xref ref-type="bibr" rid="B21">21</xref>)</td>
<td valign="top" align="center">2009</td>
<td valign="top" align="center">39</td>
<td valign="top" align="center">122</td>
<td valign="top" align="center">92</td>
<td valign="top" align="center">200</td>
<td valign="top" align="center">306</td>
<td valign="top" align="center">38</td>
<td valign="top" align="center">119</td>
<td valign="top" align="center">100</td>
<td valign="top" align="center">195</td>
<td valign="top" align="center">319</td>
<td valign="top" align="center">0.789</td>
</tr>
<tr>
<td valign="top" align="left">Moore et&#xa0;al. (<xref ref-type="bibr" rid="B22">22</xref>)</td>
<td valign="top" align="center">2009</td>
<td valign="top" align="center">113</td>
<td valign="top" align="center">404</td>
<td valign="top" align="center">428</td>
<td valign="top" align="center">630</td>
<td valign="top" align="center">1,260</td>
<td valign="top" align="center">107</td>
<td valign="top" align="center">387</td>
<td valign="top" align="center">346</td>
<td valign="top" align="center">601</td>
<td valign="top" align="center">1,079</td>
<td valign="top" align="center">0.644</td>
</tr>
<tr>
<td valign="top" align="left">Partida-Perez et&#xa0;al. (<xref ref-type="bibr" rid="B23">23</xref>)</td>
<td valign="top" align="center">2010</td>
<td valign="top" align="center">7</td>
<td valign="top" align="center">44</td>
<td valign="top" align="center">17</td>
<td valign="top" align="center">58</td>
<td valign="top" align="center">78</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">53</td>
<td valign="top" align="center">24</td>
<td valign="top" align="center">103</td>
<td valign="top" align="center">101</td>
<td valign="top" align="center">0.691</td>
</tr>
<tr>
<td valign="top" align="left">Kim et&#xa0;al. (<xref ref-type="bibr" rid="B24">24</xref>)</td>
<td valign="top" align="center">2012</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">110</td>
<td valign="top" align="center">269</td>
<td valign="top" align="center">134</td>
<td valign="top" align="center">648</td>
<td valign="top" align="center">18</td>
<td valign="top" align="center">147</td>
<td valign="top" align="center">284</td>
<td valign="top" align="center">183</td>
<td valign="top" align="center">715</td>
<td valign="top" align="center">0.851</td>
</tr>
<tr>
<td valign="top" align="left">Zhang et&#xa0;al. (<xref ref-type="bibr" rid="B25">25</xref>)</td>
<td valign="top" align="center">2012</td>
<td valign="top" align="center">26</td>
<td valign="top" align="center">166</td>
<td valign="top" align="center">322</td>
<td valign="top" align="center">218</td>
<td valign="top" align="center">810</td>
<td valign="top" align="center">29</td>
<td valign="top" align="center">190</td>
<td valign="top" align="center">338</td>
<td valign="top" align="center">248</td>
<td valign="top" align="center">866</td>
<td valign="top" align="center">0.733</td>
</tr>
<tr>
<td valign="top" align="left">Qiu et&#xa0;al. (<xref ref-type="bibr" rid="B26">26</xref>)</td>
<td valign="top" align="center">2017</td>
<td valign="top" align="center">19</td>
<td valign="top" align="center">165</td>
<td valign="top" align="center">318</td>
<td valign="top" align="center">203</td>
<td valign="top" align="center">801</td>
<td valign="top" align="center">67</td>
<td valign="top" align="center">528</td>
<td valign="top" align="center">894</td>
<td valign="top" align="center">662</td>
<td valign="top" align="center">2,316</td>
<td valign="top" align="center">0.764</td>
</tr>
<tr>
<td valign="top" align="left">Zhang et&#xa0;al. (<xref ref-type="bibr" rid="B27">27</xref>)</td>
<td valign="top" align="center">2018</td>
<td valign="top" align="center">34</td>
<td valign="top" align="center">198</td>
<td valign="top" align="center">343</td>
<td valign="top" align="center">266</td>
<td valign="top" align="center">884</td>
<td valign="top" align="center">36</td>
<td valign="top" align="center">321</td>
<td valign="top" align="center">564</td>
<td valign="top" align="center">393</td>
<td valign="top" align="center">1,449</td>
<td valign="top" align="center">0.448</td>
</tr>
<tr>
<td valign="top" align="left">Huang et&#xa0;al. (<xref ref-type="bibr" rid="B28">28</xref>)</td>
<td valign="top" align="center">2018</td>
<td valign="top" align="center">13</td>
<td valign="top" align="center">71</td>
<td valign="top" align="center">50</td>
<td valign="top" align="center">97</td>
<td valign="top" align="center">171</td>
<td valign="top" align="center">29</td>
<td valign="top" align="center">119</td>
<td valign="top" align="center">111</td>
<td valign="top" align="center">177</td>
<td valign="top" align="center">341</td>
<td valign="top" align="center">0.089</td>
</tr>
<tr>
<td valign="top" align="left">Yang et&#xa0;al. (<xref ref-type="bibr" rid="B29">29</xref>)</td>
<td valign="top" align="center">2019</td>
<td valign="top" align="center">29</td>
<td valign="top" align="center">334</td>
<td valign="top" align="center">678</td>
<td valign="top" align="center">392</td>
<td valign="top" align="center">1,690</td>
<td valign="top" align="center">73</td>
<td valign="top" align="center">603</td>
<td valign="top" align="center">998</td>
<td valign="top" align="center">749</td>
<td valign="top" align="center">2,599</td>
<td valign="top" align="center">0.109</td>
</tr>
<tr>
<td valign="top" align="left">Lin et&#xa0;al. (<xref ref-type="bibr" rid="B30">30</xref>)</td>
<td valign="top" align="center">2020</td>
<td valign="top" align="center">51</td>
<td valign="top" align="center">340</td>
<td valign="top" align="center">589</td>
<td valign="top" align="center">442</td>
<td valign="top" align="center">1,518</td>
<td valign="top" align="center">59</td>
<td valign="top" align="center">474</td>
<td valign="top" align="center">767</td>
<td valign="top" align="center">592</td>
<td valign="top" align="center">2,008</td>
<td valign="top" align="center">0.832</td>
</tr>
<tr>
<td valign="top" align="left">Ma (<xref ref-type="bibr" rid="B31">31</xref>)</td>
<td valign="top" align="center">2020</td>
<td valign="top" align="center">14</td>
<td valign="top" align="center">120</td>
<td valign="top" align="center">245</td>
<td valign="top" align="center">148</td>
<td valign="top" align="center">610</td>
<td valign="top" align="center">30</td>
<td valign="top" align="center">170</td>
<td valign="top" align="center">263</td>
<td valign="top" align="center">230</td>
<td valign="top" align="center">696</td>
<td valign="top" align="center">0.883</td>
</tr>
<tr>
<td valign="top" align="left">Al-Khatib et&#xa0;al. (<xref ref-type="bibr" rid="B32">32</xref>)</td>
<td valign="top" align="center">2020</td>
<td valign="top" align="center">19</td>
<td valign="top" align="center">50</td>
<td valign="top" align="center">49</td>
<td valign="top" align="center">88</td>
<td valign="top" align="center">148</td>
<td valign="top" align="center">19</td>
<td valign="top" align="center">102</td>
<td valign="top" align="center">107</td>
<td valign="top" align="center">140</td>
<td valign="top" align="center">316</td>
<td valign="top" align="center">0.307</td>
</tr>
<tr>
<td valign="top" align="left">Mao et&#xa0;al. (<xref ref-type="bibr" rid="B33">33</xref>)</td>
<td valign="top" align="center">2020</td>
<td valign="top" align="center">11</td>
<td valign="top" align="center">114</td>
<td valign="top" align="center">228</td>
<td valign="top" align="center">136</td>
<td valign="top" align="center">570</td>
<td valign="top" align="center">29</td>
<td valign="top" align="center">162</td>
<td valign="top" align="center">242</td>
<td valign="top" align="center">220</td>
<td valign="top" align="center">646</td>
<td valign="top" align="center">0.473</td>
</tr>
<tr>
<td valign="top" align="left">Mhaidat et&#xa0;al. (<xref ref-type="bibr" rid="B34">34</xref>)</td>
<td valign="top" align="center">2021</td>
<td valign="top" align="center">10</td>
<td valign="top" align="center">23</td>
<td valign="top" align="center">21</td>
<td valign="top" align="center">43</td>
<td valign="top" align="center">65</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">11</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">19</td>
<td valign="top" align="center">27</td>
<td valign="top" align="center">0.414</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>HWE, Hardy&#x2013;Weinberg equilibrium.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_2">
<title>Effect of the LEP G19A Polymorphism on Cancers</title>
<p>We investigated the effect of the LEP G19A mutation on cancer susceptibility in five genetic models. In all models, if the heterogeneity was less than 50%, the authors applied fixed models, whereas if the heterogeneity was greater than 50%, random models were used.</p>
<p>In the overall population, we found a significant relationship with cancer in four models (allele comparison: OR = 0.921, <italic>p</italic> = 0.000; dominant comparison: OR = 0.923, <italic>p</italic> = 0.004; recessive comparison: OR = 0.842, <italic>p</italic> = 0.000; homozygote model: OR = 0.0843, <italic>p</italic> = 0.001), and no relevance was observed in the heterozygote model (OR = 0.944, <italic>p</italic> = 0.05) (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref> and <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>).</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>The association between LEP G19A and cancer susceptibility.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" rowspan="2" align="left">G19A</th>
<th valign="top" rowspan="2" align="center">No</th>
<th valign="top" colspan="3" align="center">A vs. G</th>
<th valign="top" colspan="3" align="center">AA+AG vs. GG</th>
<th valign="top" colspan="3" align="center">AA vs. AG+GG</th>
<th valign="top" colspan="3" align="center">AA vs. GG</th>
<th valign="top" colspan="3" align="center">AG vs. GG</th>
</tr>
<tr>
<th valign="top" align="center">
<italic>p<sup>a</sup>
</italic>
</th>
<th valign="top" align="center">OR (95% CI)</th>
<th valign="top" align="center">
<italic>I</italic>
<sup>2</sup>
</th>
<th valign="top" align="center">
<italic>p</italic>
<sup>a</sup>
</th>
<th valign="top" align="center">OR (95% CI)</th>
<th valign="top" align="center">
<italic>I</italic>
<sup>2</sup>
</th>
<th valign="top" align="center">
<italic>p</italic>
<sup>a</sup>
</th>
<th valign="top" align="center">OR (95% CI)</th>
<th valign="top" align="center">
<italic>I</italic>
<sup>2</sup>
</th>
<th valign="top" align="center">
<italic>p</italic>
<sup>a</sup>
</th>
<th valign="top" align="center">OR(95% CI)</th>
<th valign="top" align="center">
<italic>I</italic>
<sup>2</sup>
</th>
<th valign="top" align="center">
<italic>p</italic>
<sup>a</sup>
</th>
<th valign="top" align="center">OR (95% CI)</th>
<th valign="top" align="center">
<italic>I</italic>
<sup>2</sup>
</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Overall</td>
<td valign="top" align="center">19</td>
<td valign="top" align="center">
<bold>0.000</bold>
</td>
<td valign="top" align="center">
<bold>0.921 (0.883&#x2013;0.961)</bold>
</td>
<td valign="top" align="center">43.60%</td>
<td valign="top" align="center">
<bold>0.004</bold>
</td>
<td valign="top" align="center">
<bold>0.923 (0.874&#x2013;0.975)</bold>
</td>
<td valign="top" align="center">33.70%</td>
<td valign="top" align="center">
<bold>0.000</bold>
</td>
<td valign="top" align="center">
<bold>0.842 (0.765&#x2013;0.927)</bold>
</td>
<td valign="top" align="center">44.10%</td>
<td valign="top" align="center">
<bold>0.001</bold>
</td>
<td valign="top" align="center">
<bold>0.843 (0.762&#x2013;0.933)</bold>
</td>
<td valign="top" align="center">43.30%</td>
<td valign="top" align="center">0.050</td>
<td valign="top" align="center">0.944 (0.890&#x2013;1.000)</td>
<td valign="top" align="center">29.30%</td>
</tr>
<tr>
<td valign="top" align="left">Begg&#x2019;s test<sup>b</sup>
</td>
<td valign="top" align="center">19</td>
<td valign="top" colspan="3" align="center">0.649</td>
<td valign="top" colspan="3" align="center">0.600</td>
<td valign="top" colspan="3" align="center">0.972</td>
<td valign="top" colspan="3" align="center">0.916</td>
<td valign="top" colspan="3" align="center">0.382</td>
</tr>
<tr>
<td valign="top" align="left">Egger&#x2019;s test<sup>c</sup>
</td>
<td valign="top" align="center">19</td>
<td valign="top" colspan="3" align="center">0.963</td>
<td valign="top" colspan="3" align="center">0.802</td>
<td valign="top" colspan="3" align="center">0.460</td>
<td valign="top" colspan="3" align="center">0.587</td>
<td valign="top" colspan="3" align="center">0.907</td>
</tr>
<tr>
<td valign="top" align="left">Ethnicity</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Caucasians</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">0.106</td>
<td valign="top" align="center">0.941 (0.873&#x2013;1.013)</td>
<td valign="top" align="center">36.00%</td>
<td valign="top" align="center">0.337</td>
<td valign="top" align="center">0.951 (0.858&#x2013;1.054)</td>
<td valign="top" align="center">0.00%</td>
<td valign="top" align="center">0.066</td>
<td valign="top" align="center">0.869 (0.749&#x2013;1.009)</td>
<td valign="top" align="center">53.30%</td>
<td valign="top" align="center">0.078</td>
<td valign="top" align="center">0.866 (0.737&#x2013;1.016)</td>
<td valign="top" align="center">46.70%</td>
<td valign="top" align="center">0.674</td>
<td valign="top" align="center">0.977 (0.876&#x2013;1.089)</td>
<td valign="top" align="center">0.00%</td>
</tr>
<tr>
<td valign="top" align="left">Mixed</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">0.423</td>
<td valign="top" align="center">0.965 (0.885&#x2013;1.053)</td>
<td valign="top" align="center">0.00%</td>
<td valign="top" align="center">0.411</td>
<td valign="top" align="center">1.052 (0.932&#x2013;1.188)</td>
<td valign="top" align="center">0.00%</td>
<td valign="top" align="center">
<bold>0.006</bold>
</td>
<td valign="top" align="center">
<bold>0.785 (0.660&#x2013;0.934)</bold>
</td>
<td valign="top" align="center">0.00%</td>
<td valign="top" align="center">0.056</td>
<td valign="top" align="center">0.833 (0.690&#x2013;1.004)</td>
<td valign="top" align="center">0.00%</td>
<td valign="top" align="center">0.069</td>
<td valign="top" align="center">1.126 (0.991&#x2013;1.280)</td>
<td valign="top" align="center">12.20%</td>
</tr>
<tr>
<td valign="top" align="left">Asians</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">
<bold>0.000</bold>
</td>
<td valign="top" align="center">0.885 (0.830&#x2013;0.944)</td>
<td valign="top" align="center">59.80%</td>
<td valign="top" align="center">
<bold>0.000</bold>
</td>
<td valign="top" align="center">
<bold>0.862 (0.799&#x2013;0.931)</bold>
</td>
<td valign="top" align="center">36.00%</td>
<td valign="top" align="center">0.119</td>
<td valign="top" align="center">0.866 (0.722&#x2013;1.038)</td>
<td valign="top" align="center">54.10%</td>
<td valign="top" align="center">
<bold>0.039</bold>
</td>
<td valign="top" align="center">
<bold>0.824 (0.686&#x2013;0.990)</bold>
</td>
<td valign="top" align="center">60.40%</td>
<td valign="top" align="center">
<bold>0.000</bold>
</td>
<td valign="top" align="center">
<bold>0.868 (0.802&#x2013;0.939)</bold>
</td>
<td valign="top" align="center">0.00%</td>
</tr>
<tr>
<td valign="top" colspan="3" align="left">Cancer type</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">NHL</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">0.103</td>
<td valign="top" align="center">0.921 (0.835&#x2013;1.017)</td>
<td valign="top" align="center">48.70%</td>
<td valign="top" align="center">0.299</td>
<td valign="top" align="center">0.932 (0.817&#x2013;1.062)</td>
<td valign="top" align="center">0.00%</td>
<td valign="top" align="center">0.082</td>
<td valign="top" align="center">0.832 (0.676&#x2013;1.024)</td>
<td valign="top" align="center">69.40%</td>
<td valign="top" align="center">0.079</td>
<td valign="top" align="center">0.82 (0.658&#x2013;1.023)</td>
<td valign="top" align="center">66.90%</td>
<td valign="top" align="center">0.579</td>
<td valign="top" align="center">0.962 (0.837&#x2013;1.104)</td>
<td valign="top" align="center">0.00%</td>
</tr>
<tr>
<td valign="top" align="left">CRC</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">0.312</td>
<td valign="top" align="center">0.963 (0.896&#x2013;1.036)</td>
<td valign="top" align="center">0.00%</td>
<td valign="top" align="center">0.771</td>
<td valign="top" align="center">1.015 (0.921&#x2013;1.118)</td>
<td valign="top" align="center">0.00%</td>
<td valign="top" align="center">
<bold>0.010</bold>
</td>
<td valign="top" align="center">
<bold>0.816 (0.700&#x2013;0.952)</bold>
</td>
<td valign="top" align="center">35.00%</td>
<td valign="top" align="center">0.081</td>
<td valign="top" align="center">0.863 (0.732&#x2013;1.018)</td>
<td valign="top" align="center">0.00%</td>
<td valign="top" align="center">0.306</td>
<td valign="top" align="center">1.055 (0.952&#x2013;1.168)</td>
<td valign="top" align="center">8.20%</td>
</tr>
<tr>
<td valign="top" align="left">EC</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">
<bold>0.014</bold>
</td>
<td valign="top" align="center">
<bold>0.888 (0.808&#x2013;0.976)</bold>
</td>
<td valign="top" align="center">68.00%</td>
<td valign="top" align="center">
<bold>0.022</bold>
</td>
<td valign="top" align="center">
<bold>0.874 (0.779&#x2013;0.980)</bold>
</td>
<td valign="top" align="center">67.30%</td>
<td valign="top" align="center">0.113</td>
<td valign="top" align="center">0.813 (0.630&#x2013;1.050)</td>
<td valign="top" align="center">17.80%</td>
<td valign="top" align="center">0.100</td>
<td valign="top" align="center">0.801 (0.615&#x2013;1.043)</td>
<td valign="top" align="center">52.50%</td>
<td valign="top" align="center">
<bold>0.060</bold>
</td>
<td valign="top" align="center">
<bold>0.892 (0.791&#x2013;1.005)</bold>
</td>
<td valign="top" align="center">61.90%</td>
</tr>
<tr>
<td valign="top" align="left">PC</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">0.275</td>
<td valign="top" align="center">0.935 (0.828&#x2013;1.055)</td>
<td valign="top" align="center">29.70%</td>
<td valign="top" align="center">0.204</td>
<td valign="top" align="center">0.898 (0.760&#x2013;1.060)</td>
<td valign="top" align="center">43.90%</td>
<td valign="top" align="center">0.740</td>
<td valign="top" align="center">0.959 (0.752&#x2013;1.225)</td>
<td valign="top" align="center">0.00%</td>
<td valign="top" align="center">0.485</td>
<td valign="top" align="center">0.911 (0.702&#x2013;1.183)</td>
<td valign="top" align="center">0.00%</td>
<td valign="top" align="center">0.221</td>
<td valign="top" align="center">0.896 (0.752&#x2013;1.068)</td>
<td valign="top" align="center">38.20%</td>
</tr>
<tr>
<td valign="top" align="left">Others</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">
<bold>0.010</bold>
</td>
<td valign="top" align="center">
<bold>0.866 (0.777&#x2013;0.966)</bold>
</td>
<td valign="top" align="center">76.40%</td>
<td valign="top" align="center">
<bold>0.010</bold>
</td>
<td valign="top" align="center">
<bold>0.842 (0.739&#x2013;0.959)</bold>
</td>
<td valign="top" align="center">62.50%</td>
<td valign="top" align="center">0.247</td>
<td valign="top" align="center">0.837 (0.619&#x2013;1.132)</td>
<td valign="top" align="center">72.40%</td>
<td valign="top" align="center">0.132</td>
<td valign="top" align="center">0.791 (0.583&#x2013;1.073)</td>
<td valign="top" align="center">76.40%</td>
<td valign="top" align="center">
<bold>0.018</bold>
</td>
<td valign="top" align="center">
<bold>0.849 (0.742&#x2013;0.973)</bold>
</td>
<td valign="top" align="center">24.40%</td>
</tr>
<tr>
<td valign="top" align="left">System of cancer</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Hematopoietic<break/>malignancy</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">0.103</td>
<td valign="top" align="center">0.921 (0.835&#x2013;1.017)</td>
<td valign="top" align="center">48.70%</td>
<td valign="top" align="center">0.290</td>
<td valign="top" align="center">0.932 (0.817&#x2013;1.062)</td>
<td valign="top" align="center">0.00%</td>
<td valign="top" align="center">0.082</td>
<td valign="top" align="center">0.832 (0.676&#x2013;1.024)</td>
<td valign="top" align="center">69.40%</td>
<td valign="top" align="center">0.079</td>
<td valign="top" align="center">0.82 (0.658&#x2013;1.023)</td>
<td valign="top" align="center">66.90%</td>
<td valign="top" align="center">0.579</td>
<td valign="top" align="center">0.962 (0.837&#x2013;1.104)</td>
<td valign="top" align="center">0.00%</td>
</tr>
<tr>
<td valign="top" align="left">Digestive system</td>
<td valign="top" align="center">11</td>
<td valign="top" align="center">
<bold>0.016</bold>
</td>
<td valign="top" align="center">
<bold>0.937 (0.889&#x2013;0.988)</bold>
</td>
<td valign="top" align="center">44.90%</td>
<td valign="top" align="center">0.127</td>
<td valign="top" align="center">0.948 (0.886&#x2013;1.015)</td>
<td valign="top" align="center">43.20%</td>
<td valign="top" align="center">
<bold>0.005</bold>
</td>
<td valign="top" align="center">
<bold>0.838 (0.740&#x2013;0.949)</bold>
</td>
<td valign="top" align="center">44.50%</td>
<td valign="top" align="center">
<bold>0.028</bold>
</td>
<td valign="top" align="center">
<bold>0.863 (0.757&#x2013;0.984)</bold>
</td>
<td valign="top" align="center">41.40%</td>
<td valign="top" align="center">0.407</td>
<td valign="top" align="center">0.907 (0.904&#x2013;1.042)</td>
<td valign="top" align="center">44.70%</td>
</tr>
<tr>
<td valign="top" align="left">Urinary system</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">
<bold>0.022</bold>
</td>
<td valign="top" align="center">
<bold>0.881 (0.791&#x2013;0.982)</bold>
</td>
<td valign="top" align="center">65.50%</td>
<td valign="top" align="center">
<bold>0.019</bold>
</td>
<td valign="top" align="center">
<bold>0.842 (0.729&#x2013;0.973)</bold>
</td>
<td valign="top" align="center">50.70%</td>
<td valign="top" align="center">0.262</td>
<td valign="top" align="center">0.877 (0.698&#x2013;1.103)</td>
<td valign="top" align="center">51.80%</td>
<td valign="top" align="center">0.109</td>
<td valign="top" align="center">0.82 (0.643&#x2013;1.045)</td>
<td valign="top" align="center">61.20%</td>
<td valign="top" align="center">
<bold>0.043</bold>
</td>
<td valign="top" align="center">
<bold>0.855 (0.735&#x2013;0.995)</bold>
</td>
<td valign="top" align="center">25.00%</td>
</tr>
<tr>
<td valign="top" align="left">Others</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">0.090</td>
<td valign="top" align="center">0.808 (0.631&#x2013;1.034)</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">0.091</td>
<td valign="top" align="center">0.781 (0.586&#x2013;1.040)</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">0.465</td>
<td valign="top" align="center">0.758 (0.361&#x2013;1.594)</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">0.358</td>
<td valign="top" align="center">0.704 (0.333&#x2013;1.489)</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">0.121</td>
<td valign="top" align="center">0.79 (0.586&#x2013;1.064)</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>NO, number of study; NHL, non-Hodgkin lymphoma; CRC, colorectal cancer; EC, esophageal cancer; HWE, Hardy&#x2013;Weinberg equilibrium; _, no available.</p>
</fn>
<fn>
<p>The meaning of bold values is statistically significant (P&lt;0.05).</p>
<p>
<sup>a</sup>P value of Q test for heterogeneity test; <sup>b</sup>P value of Begg rank for testing publication bias; <sup>c</sup>P value of Egger rank for testing publication bias.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Forest plot of subgroup analysis of LEP G19A and cancer risk in the allele model (A vs. G) <bold>(A)</bold> LEP G19A polymorphism and overall cancer risk; <bold>(B)</bold> LEP G19A polymorphism and cancer risk on ethnicity; <bold>(C)</bold> LEP G19A polymorphism and risk of cancer type; <bold>(D)</bold> LEP G19A polymorphism and the risk of cancer system).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-754162-g002.tif"/>
</fig>
<p>In a subgroup analysis conducted by ethnicity, we obtained significant results in Asians in four models (allele comparison: OR = 0.885, <italic>p</italic> = 0.000; dominant comparison: OR = 0.862, <italic>p</italic> = 0.000; homozygote model: OR = 0.824, <italic>p</italic> = 0.039; and heterozygote comparison: OR = 0.868, <italic>p</italic> = 0.000); we also obtained significant results in the mixed recessive model: OR = 0.785, <italic>p</italic> = 0.1006. We obtained no significant results in the Caucasian population in five models (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref> and <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>).</p>
<p>In a subgroup analysis conducted by cancer type, we obtained significant results that the LEP G19A polymorphism decreased the risk of colorectal cancer in one model (recessive model: OR = 0.816, <italic>p</italic> = 0.010); decreased the risk of esophageal cancer in two models (allele model: OR = 0.888, <italic>p</italic> = 0.014; dominant comparison: OR = 0.874, <italic>p</italic> = 0.022); and decreased the risk of other types of cancer in three models (allele comparison: OR = 0.866, <italic>p</italic> = 0.010; dominant comparison: OR = 0.842, <italic>p</italic> = 0.010; heterozygote comparison: OR = 0.849, <italic>p</italic> = 0.018) (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref> and <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>).</p>
<p>In a subgroup analysis conducted by cancer system, we obtained significant results that the LEP G19A polymorphism decreased the risk of digestive system cancer in three models (allele comparison: OR = 0.937, <italic>p</italic> = 0.016; recessive comparison: OR = 0.838, <italic>p</italic> = 0.005; homozygote comparison: OR = 0.863, <italic>p</italic> = 0.028); we also obtained significant results that the LEP G19A polymorphism decreased the risk of urinary system cancer in three models (allele comparison: OR = 0.881, <italic>p</italic> = 0.022; dominant comparison: OR = 0.842, <italic>p</italic> = 0.019; heterozygote comparison: OR = 0.855, <italic>p</italic> = 0.043) (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref> and <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>).</p>
</sec>
<sec id="s3_3">
<title>Sensitivity Analysis and Publication Bias</title>
<p>We used Begg&#x2019;s and Egger&#x2019;s tests to evaluate publication bias in all models. All results of Begg&#x2019;s and Egger&#x2019;s tests were &gt;0.05 in all models and funnel plots, revealing that publication bias may not exist among our studies (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>, <xref ref-type="fig" rid="f3">
<bold>Figures&#xa0;3</bold>
</xref> and <xref ref-type="fig" rid="f4">
<bold>4</bold>
</xref>). We conducted a sensitivity analysis, and pooled ORs and the corresponding 95% CIs were computed. The results did not show a significant change even though one study was deleted each time, which suggested that the results were statistically stable (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5</bold>
</xref>).</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Funnel plot of publication bias on the relationship between LEP G19A polymorphism and the risk of digestion-related cancer in allele model (A vs. G).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-754162-g003.tif"/>
</fig>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Begg&#x2019;s funnel plot of meta&#x2013;analysis in the allele model (A vs. G).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-754162-g004.tif"/>
</fig>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Sensitivity analysis of the influence of A vs. G comparison.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-754162-g005.tif"/>
</fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>It has been confirmed that the occurrence of cancer is a complex, multistep, and multifactorial event that contains various genetic, environmental, and lifestyle factors, such as smoking, drinking, obesity, and genetic factor. Multiple studies have revealed that metabolic-related factors are associated with the risk of cancer (<xref ref-type="bibr" rid="B35">35</xref>&#x2013;<xref ref-type="bibr" rid="B37">37</xref>). The LEP, metabolic-related factors regulating balancing by regulating acquisition and energy consumption, was confirmed relevant to cancer (<xref ref-type="bibr" rid="B38">38</xref>&#x2013;<xref ref-type="bibr" rid="B40">40</xref>). The LEP G19A polymorphism may alter the transcription of mRNA and the level of LEP was confirmed to be associated with any kind of cancer (<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B24">24</xref>&#x2013;<xref ref-type="bibr" rid="B26">26</xref>). However, the conclusions of those studies were inconsistent. Two meta-analyses were researched by Liu et&#xa0;al. (<xref ref-type="bibr" rid="B41">41</xref>), including 10 studies, and Yang et&#xa0;al. (<xref ref-type="bibr" rid="B29">29</xref>), including 13 studies, generating conflicting results in subgroup analysis and lacking subgroup analysis of the cancer system. Meanwhile, an expanding body of literature on the relationship between LEP G19A polymorphism and cancer risk has been published. Therefore, we conducted this meta-analysis to address this relevance between the LEP G19A polymorphism and cancer risk.</p>
<p>Our current meta-analysis contained 19 studies of cancers containing 9,878 patients, and 14,251 controls were pooled, which contained more participants and cancer types than the previous meta-analysis. Overall, we found a significant correlation between the LEP G19A mutation and susceptibility to cancers under four models (allele model, dominant model, recessive model, and homozygote model), which means that this mutation may decrease the risk of overall cancer. This result was confirmed in a meta-analysis conducted by Liu et&#xa0;al. (<xref ref-type="bibr" rid="B41">41</xref>) and Yang et&#xa0;al. (<xref ref-type="bibr" rid="B29">29</xref>). Studies (<xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B43">43</xref>) confirmed that the LEP G19A mutation might reduce mRNA translation with a lower serum level of LEP, which may attenuate the cancer risk as a protective factor.</p>
<p>Obesity was defined as an imbalance between caloric consumption and energy expenditure. Meanwhile, the LEP is a metabolic-related factor regulating balancing by regulating acquisition and consumption of energy. So it seems that obesity has a positive correlation with LEP polymorphism. However, some studies showed that there was no association between LEP polymorphism and obesity (<xref ref-type="bibr" rid="B44">44</xref>, <xref ref-type="bibr" rid="B45">45</xref>). Mizuta et&#xa0;al. (<xref ref-type="bibr" rid="B46">46</xref>) study showed that LEP G19A was not associated with obesity. The study by Nesrine et&#xa0;al. (<xref ref-type="bibr" rid="B47">47</xref>) even showed that different polymorphisms of the LEP gene have distinct correlations with obesity. Our study showed that LEP G19A polymorphism decreases cancer risk, but the exact mechanism is unknown and mounting evidence indicates that obesity may greatly increase the risk of cancer (<xref ref-type="bibr" rid="B3">3</xref>&#x2013;<xref ref-type="bibr" rid="B5">5</xref>). This provides us with a hint that LEP G19A polymorphism may not lead to cancer by gaining weight. Further studies are needed to elucidate the mechanism of action of LEP G19A polymorphism and cancer.</p>
<p>When stratified by ethnicity, we found a significant correlation between this mutation and Asians and no significant in Caucasians, which means that this mutation may decrease the risk of Asian people not Caucasians. This difference might be caused by a discrepancy in the interplay between genes and the environment. Moreover, the frequency of the A allele in Caucasians (68%) and Asians (44%) might be the reason for contributing to the discrepancy in the non-significant results in Caucasians. When stratified by cancer type and cancer system, it was first to describe the association between LEP G19A mutation and the cancer system. We found a significant correlation between this mutation and colorectal cancer, esophageal cancer, digestive system cancer, and urinary system cancer, which means that this mutation may decrease the risk of colorectal cancer, esophageal cancer, digestive system cancer, and urinary system cancer, but we found no correlation between this mutation and the other cancer system; the reason for this difference in risk with different tumors is as yet unknown, possibly due to LEP and its receptors playing various roles in the mediation of physiological reactions and carcinogenesis in different pathological types of cancer.</p>
<p>Heterogeneity may exist in our meta-analysis of cancer in the overall analysis. Stratified analyses indicated that heterogeneity was significant in some subgroups (e.g., Asians, esophageal cancer, and urinary system cancer). These factors may cause heterogeneity in our study. We checked the stability of our pooled results by sensitivity analyses. The trend of relevance was not significantly changed in the sensitivity analyses, which meant that the pooled results in our meta-analysis were statistically stable. We used Begg&#x2019;s and Egger&#x2019;s tests to evaluate publication bias. Begg&#x2019;s and Egger&#x2019;s tests&#x2019; <italic>p</italic>-values &gt; 0.05 in all models, so that publication bias may exist in this meta-analysis.</p>
<p>The following limitations should be mentioned: (1) The number of studies focused on the relationship between LEP G19A and cancer was relatively small, so little information about stratified analyses of ethnicity, cancer type, and cancer system was available; therefore, further studies are required to determine the actual relationship in all populations. (2) Our study had no access to other potential factors influencing the results, such as other lifestyles, environments, and ages.</p>
</sec>
<sec id="s5">
<title>Conclusion</title>
<p>In conclusion, this meta-analysis suggests that the LEP G19A mutation may decrease the risk of overall cancer, colorectal cancer, esophageal cancer, digestive system cancer, and urinary system cancer. In the future, more comprehensive objects containing genetic environmental interaction are warranted to discover the correlation between LEP G19A mutation and the risk of cancer.</p>
</sec>
<sec id="s6" sec-type="data-availability">
<title>Data Availability Statement</title>
<p>The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s7" sec-type="author-contributions">
<title>Author Contributions</title>
<p>AZ, SW, FZ, WL, QL, and XL conceived the study. FZ, WL, and QL contributed to data acquisition, data interpretation, and statistical analysis. AZ, SW, and XL contributed to the study design, statistical analysis, writing, and revising of the manuscript critically. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec id="s8" sec-type="funding-information">
<title>Funding</title>
<p>This work was supported by the National Natural Science Funds of China (82171594) and Zhao Yi-Cheng Medical Science Foundation (ZYYFY2018031).</p>
</sec>
<sec id="s9" 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="s10" 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>
<ack>
<title>Acknowledgments</title>
<p>We thank all authors whose studies were included in our meta-analysis.</p>
</ack>
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