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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Genet.</journal-id>
<journal-title>Frontiers in Genetics</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Genet.</abbrev-journal-title>
<issn pub-type="epub">1664-8021</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">889530</article-id>
<article-id pub-id-type="doi">10.3389/fgene.2022.889530</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Genetics</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Impact of Long Noncoding RNA LINC00673 Genetic Variants on Susceptibility to Diabetic Retinopathy</article-title>
<alt-title alt-title-type="left-running-head">Chuang et al.</alt-title>
<alt-title alt-title-type="right-running-head">LINC00673 Polymorphism and DR</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Chuang</surname>
<given-names>Chih-Chun</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>Yang</surname>
<given-names>Yi-Sun</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Kornelius</surname>
<given-names>Edy</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Huang</surname>
<given-names>Chien-Ning</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1319325/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Hsu</surname>
<given-names>Min-Yen</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1438141/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lee</surname>
<given-names>Chia-Yi</given-names>
</name>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Yang</surname>
<given-names>Shun-Fa</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/693905/overview"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Institute of Medicine</institution>, <institution>Chung Shan Medical University</institution>, <addr-line>Taichung</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Ophthalmology</institution>, <institution>Changhua Christian Hospital</institution>, <addr-line>Changhua</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>School of Medicine</institution>, <institution>Chung Shan Medical University</institution>, <addr-line>Taichung</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Department of Internal Medicine</institution>, <institution>Division of Endocrinology and Metabolism</institution>, <institution>Chung Shan Medical University Hospital</institution>, <addr-line>Taichung</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff5">
<sup>5</sup>
<institution>Department of Ophthalmology</institution>, <institution>Chung Shan Medical University Hospital</institution>, <addr-line>Taichung</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff6">
<sup>6</sup>
<institution>Department of Ophthalmology</institution>, <institution>Nobel Eye Institute</institution>, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff7">
<sup>7</sup>
<institution>Department of Medical Research</institution>, <institution>Chung Shan Medical University Hospital</institution>, <addr-line>Taichung</addr-line>, <country>Taiwan</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/579325/overview">Yen-Wei Chu</ext-link>, National Chung Hsing University, Taiwan</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1064518/overview">Leyi Wei</ext-link>, Shandong University, China</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1311420/overview">Xing-Hua Liao</ext-link>, Wuhan University of Science and Technology, China</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Shun-Fa Yang, <email>ysf@csmu.edu.tw</email>
</corresp>
<fn fn-type="other">
<p>This article was submitted to Computational Genomics, a section of the journal Frontiers in Genetics</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>25</day>
<month>04</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>13</volume>
<elocation-id>889530</elocation-id>
<history>
<date date-type="received">
<day>04</day>
<month>03</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>24</day>
<month>03</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2022 Chuang, Yang, Kornelius, Huang, Hsu, Lee and Yang.</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Chuang, Yang, Kornelius, Huang, Hsu, Lee and Yang</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>
<p>Long noncoding RNAs (lncRNAs) have been proven to play critical roles in diabetic retinopathy (DR). This study investigated whether the single nucleotide polymorphism (SNP) of long intergenic noncoding RNA 00673 (<italic>LINC00673</italic>) affects the clinical characteristics of diabetic retinopathy (DR). A total of three loci of <italic>LINC00673</italic> SNPs (rs6501551, rs9914618, and rs11655237) were genotyped using TaqMan allelic discrimination in 276 and 454 individuals with and without DR, respectively. Our results revealed that <italic>LINC00673</italic> SNP rs11655237 CT genotype (AOR: 1.592, 95% CI: 1.059&#x2013;2.395, <italic>p</italic> &#x3d; 0.026), CT &#x2b; TT genotype (AOR: 1.255, 95% CI: 1.029&#x2013;1.531, <italic>p</italic> &#x3d; 0.025), and allele T (AOR: 1.185, 95% CI: 1.004&#x2013;1.397, <italic>p</italic> &#x3d; 0.044) yielded higher ratios in the non-proliferative diabetic retinopathy (NPDR) subgroup than in the non-DR group. Furthermore, the interval of diabetes mellitus (DM) was significantly shorter in the <italic>LINC00673</italic> SNP rs11655237 CT &#x2b; TT variant than that in the <italic>LINC00673</italic> SNP rs11655237 wild type (10.44 &#xb1; 7.10 vs. 12.98 &#xb1; 8.34, <italic>p</italic> &#x3d; 0.009). In conclusion, the <italic>LINC00673</italic> SNP rs11655237&#xa0;T allele is associated with a higher probability of NPDR development. Patients with the <italic>LINC00673</italic> SNP rs11655237 CT &#x2b; TT variant exhibited a short DM interval.</p>
</abstract>
<kwd-group>
<kwd>long intergenic noncoding RNA 00673</kwd>
<kwd>polymorphism</kwd>
<kwd>diabetic retinopathy</kwd>
<kwd>diabetes mellitus</kwd>
<kwd>disease duration</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Introduction</title>
<p>Diabetes mellitus (DM) affects more than 9% of individuals worldwide and can lead to various vascular disorders (<xref ref-type="bibr" rid="B44">Zheng et al., 2018</xref>). Diabetic retinopathy (DR) is a complication of DM that is characterized by vascular damage and fluid leakage in the retina. DR can be further divided into non-proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR), according to the presence of retinal neovascularization (<xref ref-type="bibr" rid="B1">Antonetti et al., 2012</xref>). Advanced PDR can cause other ocular diseases, including tractional retinal detachment, vitreous hemorrhage, and neovascular glaucoma (<xref ref-type="bibr" rid="B5">Cheung et al., 2010</xref>; <xref ref-type="bibr" rid="B29">Sabanayagam et al., 2019</xref>). A previous study estimated that nearly 2.5 and 1.4% of the global cases of blindness and moderate-to-severe visual impairment, respectively, resulted from DR (<xref ref-type="bibr" rid="B9">Flaxman et al., 2017</xref>).</p>
<p>The etiology of DR development is multifactorial (<xref ref-type="bibr" rid="B5">Cheung et al., 2010</xref>; <xref ref-type="bibr" rid="B1">Antonetti et al., 2012</xref>). Apart from DM duration and the condition of blood sugar control (defined as the concentration of glycated hemoglobin [HbA1c] (<xref ref-type="bibr" rid="B29">Sabanayagam et al., 2019</xref>; <xref ref-type="bibr" rid="B10">Ghamdi, 2020</xref>), biomarkers can also influence the occurrence of DR (<xref ref-type="bibr" rid="B17">Jenkins et al., 2015</xref>). Inflammatory cytokines such as interleukins are involved in the development of DR and diabetic macular edema (<xref ref-type="bibr" rid="B2">Capit&#xe3;o and Soares, 2016</xref>). Another prominent component in the development of DR is vascular endothelial growth factor (VEGF) (<xref ref-type="bibr" rid="B41">Zhang et al., 2009</xref>), which is secreted by the retina during DR progression (<xref ref-type="bibr" rid="B25">Pe&#x2019;er et al., 1996</xref>). In addition, some genes and their variants can influence DR occurrence, including the single nucleotide polymorphisms (SNPs) of VEGF and aquaporin-4 (<xref ref-type="bibr" rid="B19">Khan et al., 2020</xref>; <xref ref-type="bibr" rid="B45">Zhou et al., 2021</xref>).</p>
<p>Long noncoding RNAs (lncRNAs) are a group of RNAs that could contribute to angiogenesis and cell proliferation in tumor cells (<xref ref-type="bibr" rid="B31">Su S.-C. et al., 2018</xref>; <xref ref-type="bibr" rid="B43">Zhao et al., 2020</xref>; <xref ref-type="bibr" rid="B34">Su et al., 2021b</xref>; <xref ref-type="bibr" rid="B8">Ding et al., 2021</xref>). Among this group, long intergenic noncoding RNA 00673 (LINC00673) is associated with several malignancies (<xref ref-type="bibr" rid="B46">Zhu K. et al., 2021</xref>; <xref ref-type="bibr" rid="B47">Zhu Y. et al., 2021</xref>). In addition, <italic>LINC00673</italic> SNPs can influence the expression of cancers such as oral cancer and gastric cancer (<xref ref-type="bibr" rid="B42">Zhao et al., 2019</xref>; <xref ref-type="bibr" rid="B33">Su et al., 2021a</xref>). Nevertheless, research on the relationship between the SNPs of <italic>LINC00673</italic> and DR development is rare. Because LINC00673 is downregulated in patients with DR (<xref ref-type="bibr" rid="B4">Cheng et al., 2021</xref>), the SNPs of <italic>LINC00673</italic> may also affect the clinical features of DR.</p>
<p>The purpose of this study was to assess the possible correlation between <italic>LINC00673</italic> SNPs (rs6501551, rs9914618, and rs11655237) and the clinical characteristics of DR, including NPDR and PDR. The different phenotypes of <italic>LINC00673</italic> SNP rs11655237 were also separately analyzed.</p>
</sec>
<sec sec-type="materials|methods" id="s2">
<title>Materials and Methods</title>
<sec id="s2-1">
<title>Ethical Declarations</title>
<p>This study, conducted in accordance with the 1964 Declaration of Helsinki and its later amendments, was approved by the Institutional Review Board of Chung Shan Medical University Hospital (project identification code: CS1-20048, approval date: 27 April 2020). Written informed consent was signed by the participants.</p>
</sec>
<sec id="s2-2">
<title>Patient Selection</title>
<p>Our case&#x2013;control study was conducted at Chung Shan Medical University Hospital. A total of 730 patients diagnosed as having DM were included. Among these, 454 patients were categorized as the non-DR group and the other 276 patients were categorized as the DR group, according to fundus examination records in the ophthalmic department. The development of DR was regarded as any of the following fundus findings: dot- and flame-shaped hemorrhage, cotton-wool spot, hard exudate, venous beading, microaneurysm, or intraretinal microvascular abnormality. In the DR group, 111 patients were classified as the PDR group according to any of the following ophthalmological findings: neovascularization of the retina or optic disc, tractional retinal detachment, vitreous hemorrhage, or neovascular glaucoma. The remaining 165 patients constituted the NPDR group.</p>
</sec>
<sec id="s2-3">
<title>Data and Sample Collection</title>
<p>We reviewed the medical records of patients with DM in Chung Shan Medical University Hospital and collected basic data, including age, body mass index, sex, blood sugar level expressed as HbA1c, DM duration, blood pressure, lipid profiles, renal function, and insulin treatment regimen. To analyze <italic>LINC00673</italic> polymorphisms, we used the methods described in our previous study (<xref ref-type="bibr" rid="B13">Hsieh et al., 2021</xref>). First, venous blood was drawn from each patient, and the collected blood samples were stored in separate ethylenediaminetetraacetic acid&#x2013;containing tubes (<xref ref-type="bibr" rid="B12">Hsiao et al., 2010</xref>). Next, the blood samples were centrifuged promptly and stored in a laboratory refrigerator at approximately &#x2212;80&#xb0;C. Patients were excluded from the study if the genomes in their blood samples had been degraded prior to any analysis.</p>
</sec>
<sec id="s2-4">
<title>DNA Extraction and Determination of <italic>LINC00673</italic> SNP Using Real-Time PCR</title>
<p>A total of three <italic>LINC00673</italic> SNPs, namely, rs6501551 (A/G), rs9914618 (G/A), and rs11655237 (C/T), were selected for phenotype analyses because the minor allele frequencies of these SNPs were higher than 5% and our preceding research indicated the effect of these SNPs on other cancers (<xref ref-type="bibr" rid="B33">Su et al., 2021a</xref>). The procedures for DNA extraction and phenotype analyses in this study were in accordance with those of our previous study (<xref ref-type="bibr" rid="B32">Su S. C. et al., 2018</xref>). First, DNA was extracted from leukocytes by using QIAamp DNA kits (QIAGEN, Valencia, CA, United States), according to the manufacturer&#x2019;s instruction for DNA isolation (<xref ref-type="bibr" rid="B6">Chung et al., 2011</xref>). Next, the DNA was preserved at approximately &#x2212;20&#xb0;C. Genetic polymorphisms of the <italic>LINC00673</italic> SNPs, namely, rs6501551 (A/G) (ID: C_29084653_10), rs9914618 (G/A) (ID: C_29971800_10), and rs11655237 (C/T) (ID: C_345893_20), were then determined using the ABI StepOne Real-Time PCR System (Applied Biosystems, Foster City, CA, United States). The final results of the <italic>LINC00673</italic> genetic polymorphisms were analyzed using SDS version 3.0 software (Applied Biosystems).</p>
</sec>
<sec id="s2-5">
<title>Statistical Analysis</title>
<p>We used SAS version 9.4 (SAS Institute Inc., Cary, NC, United States) for all statistical analyses. Descriptive statistics such as mean, standard deviation, and percentage were used to compare demography, blood sugar status, and other laboratory data between the DR and non-DR groups. An independent <italic>t-</italic>test was used to evaluate the difference of these data between both groups. Next, multiple logistic regression models were applied to evaluate adjusted odds ratios (AORs) and 95% confidence intervals (CIs) of the <italic>LINC00673</italic> SNP distribution and the allele distribution between the two groups. The multiple logistic regressions were adjusted for age, DM duration, insulin treatment, HbA1c, glomerular filtration rate, serum creatinine levels, and HDL cholesterol levels. The same multiple logistic regression models were used in the subgroup analyses for SNP distributions between the non-DR group and each of the NPDR and PDR subgroups. Furthermore, differences in clinicopathological characteristics for each SNP rs11655237 phenotype (i.e., CC and CT &#x2b; TT) in the DR group were again analyzed using the independent <italic>t-</italic>test. A <italic>p</italic>-value less than 0.05 was considered statistically significant.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<sec id="s3-1">
<title>Characteristics Between the Non-DR and DR Groups</title>
<p>The mean age of the DR group was 62.61 &#xb1; 10.72&#xa0;years, which was significantly higher than that of the non-DR group (60.22 &#xb1; 11.22, <italic>p</italic> &#x3d; 0.005). Parameters related to DM, including DM duration, HbA1c level, and ratio of insulin treatment, were all higher in the DR group (all <italic>p</italic> &#x3c; 0.001). Serum creatinine was also higher in the DR group (<italic>p</italic> &#x3c; 0.001), although the glomerular filtration rate (<italic>p</italic> &#x3c; 0.001) and HDL cholesterol (<italic>p</italic> &#x3d; 0.017) were lower than those of the non-DR group. The remaining parameters were not significantly different between both groups (all <italic>p</italic> &#x3e; 0.05) (<xref ref-type="table" rid="T1">Table 1</xref>).</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Clinical and laboratory characteristics of patients with diabetic retinopathy and no diabetic retinopathy.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Variable</th>
<th align="center">Non-DR group (<italic>N</italic> &#x3d; 454)</th>
<th align="center">DR group (<italic>N</italic> &#x3d; 276)</th>
<th align="center">
<italic>p</italic>-value</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Age (years)</td>
<td align="center">60.22 &#xb1; 11.22</td>
<td align="center">62.61 &#xb1; 10.72</td>
<td align="char" char=".">0.005<xref ref-type="table-fn" rid="Tfn1">
<sup>a</sup>
</xref>
</td>
</tr>
<tr>
<td align="left">Male gender [n (%)]</td>
<td align="center">240 (52.9%)</td>
<td align="center">152 (55.1%)</td>
<td align="char" char=".">0.562</td>
</tr>
<tr>
<td align="left">Duration of DM (years)</td>
<td align="center">9.38 &#xb1; 7.03</td>
<td align="center">11.98 &#xb1; 7.96</td>
<td align="char" char=".">&#x3c;0.001<xref ref-type="table-fn" rid="Tfn1">
<sup>a</sup>
</xref>
</td>
</tr>
<tr>
<td align="left">HbA1c [% (mmol/mol)]</td>
<td align="center">6.96 &#xb1; 0.99</td>
<td align="center">7.59 &#xb1; 1.42</td>
<td align="char" char=".">&#x3c;0.001<xref ref-type="table-fn" rid="Tfn1">
<sup>a</sup>
</xref>
</td>
</tr>
<tr>
<td align="left">Insulin treatment [n (%)]</td>
<td align="center">105 (23.1%)</td>
<td align="center">129 (46.7%)</td>
<td align="char" char=".">&#x3c;0.001<xref ref-type="table-fn" rid="Tfn1">
<sup>a</sup>
</xref>
</td>
</tr>
<tr>
<td align="left">Body mass index [kg/m<sup>2</sup>]</td>
<td align="center">26.15 &#xb1; 4.32</td>
<td align="center">25.99 &#xb1; 4.29</td>
<td align="char" char=".">0.631</td>
</tr>
<tr>
<td align="left">Systolic blood pressure [mm Hg]</td>
<td align="center">135.44 &#xb1; 15.32</td>
<td align="center">137.34 &#xb1; 17.37</td>
<td align="char" char=".">0.123</td>
</tr>
<tr>
<td align="left">Diastolic blood pressure [mm Hg]</td>
<td align="center">76.44 &#xb1; 11.27</td>
<td align="center">75.74 &#xb1; 11.58</td>
<td align="char" char=".">0.419</td>
</tr>
<tr>
<td align="left">Serum creatinine [mg/dL]</td>
<td align="center">0.89 &#xb1; 0.35</td>
<td align="center">1.55 &#xb1; 1.84</td>
<td align="char" char=".">&#x3c;0.001<xref ref-type="table-fn" rid="Tfn1">
<sup>a</sup>
</xref>
</td>
</tr>
<tr>
<td align="left">Glomerular filtration rate [ml/min]</td>
<td align="center">78.44 &#xb1; 27.69</td>
<td align="center">62.88 &#xb1; 34.15</td>
<td align="char" char=".">&#x3c;0.001<xref ref-type="table-fn" rid="Tfn1">
<sup>a</sup>
</xref>
</td>
</tr>
<tr>
<td align="left">Total cholesterol [mmol/L]</td>
<td align="center">160.52 &#xb1; 43.04</td>
<td align="center">165.27 &#xb1; 47.61</td>
<td align="char" char=".">0.172</td>
</tr>
<tr>
<td align="left">HDL cholesterol [&#x3bc;mol/L]</td>
<td align="center">46.29 &#xb1; 12.64</td>
<td align="center">43.87 &#xb1; 13.58</td>
<td align="char" char=".">0.017<xref ref-type="table-fn" rid="Tfn1">
<sup>a</sup>
</xref>
</td>
</tr>
<tr>
<td align="left">LDL cholesterol [&#x3bc;mol/L]</td>
<td align="center">86.60 &#xb1; 28.22</td>
<td align="center">86.35 &#xb1; 32.86</td>
<td align="char" char=".">0.918</td>
</tr>
<tr>
<td align="left">Triglycerides, [&#x3bc;mol/L]</td>
<td align="left">140.19 &#xb1; 164.95</td>
<td align="left">156.80 &#xb1; 117.95</td>
<td align="char" char=".">0.154</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>N, number; DR, diabetic retinopathy; DM, diabetes mellitus; HbA1c, glycated hemoglobin.</p>
</fn>
<fn id="Tfn1">
<label>a</label>
<p>denotes significant difference between the two groups.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3-2">
<title>
<italic>LINC00673</italic> SNP Distribution Among Different DR Groups</title>
<p>The genotyping frequencies of each <italic>LINC00673</italic> SNP between the DR and non-DR groups are shown in <xref ref-type="table" rid="T2">Table 2</xref>. No significant differences were observed regarding the distribution of the <italic>LINC00673</italic> SNPs and their alleles between both groups (all <italic>p</italic> &#x3e; 0.05) (<xref ref-type="table" rid="T2">Table 2</xref>). In the subgroup analyses, the <italic>LINC00673</italic> SNP rs11655237 CT genotype (AOR: 1.592, 95% CI: 1.059&#x2013;2.395, <italic>p</italic> &#x3d; 0.026), <italic>LINC00673</italic> SNP rs11655237 CT &#x2b; TT genotype (AOR: 1.255, 95% CI: 1.029&#x2013;1.531, <italic>p</italic> &#x3d; 0.025), and <italic>LINC00673</italic> SNP rs11655237 allele T (AOR: 1.185, 95% CI: 1.004&#x2013;1.397, <italic>p</italic> &#x3d; 0.044) exhibited higher ratios in the NPDR subgroup than in the non-DR group (<xref ref-type="table" rid="T3">Table 3</xref>). However, no significant differences in genotype frequencies were observed between the PDR subgroup and the non-DR group (all <italic>p</italic> &#x3e; 0.05; <xref ref-type="table" rid="T4">Table 4</xref>).</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Adjusted odds ratio and 95% confidence intervals of diabetic retinopathy associated with <italic>LINC00673</italic> genotypic frequencies.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Variable</th>
<th align="center">Non-DR group (<italic>N</italic> &#x3d; 454)</th>
<th align="center">DR group (<italic>N</italic> &#x3d; 276)</th>
<th align="center">AOR (95% CI)</th>
<th align="center">
<italic>p</italic>-value</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td colspan="5" align="left">rs6501551</td>
</tr>
<tr>
<td align="left">&#x2003;AA</td>
<td align="center">334 (73.6%)</td>
<td align="center">200 (72.5%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;AG</td>
<td align="center">113 (24.9%)</td>
<td align="center">70 (25.4%)</td>
<td align="center">1.032 (0.699&#x2013;1.525)</td>
<td align="center">0.874</td>
</tr>
<tr>
<td align="left">&#x2003;GG</td>
<td align="center">7 (1.5%)</td>
<td align="center">6 (2.1%)</td>
<td align="center">1.836 (0.567&#x2013;5.945)</td>
<td align="center">0.311</td>
</tr>
<tr>
<td align="left">&#x2003;AG &#x2b; GG</td>
<td align="center">120 (26.4%)</td>
<td align="center">76 (27.5%)</td>
<td align="center">1.038 (0.859&#x2013;1.254)</td>
<td align="center">0.699</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-A</td>
<td align="center">781 (86.0%)</td>
<td align="center">470 (85.1%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-G</td>
<td align="center">127 (14.0%)</td>
<td align="center">82 (14.9%)</td>
<td align="center">1.055 (0.892&#x2013;1.247)</td>
<td align="center">0.533</td>
</tr>
<tr>
<td colspan="5" align="left">rs9914618</td>
</tr>
<tr>
<td align="left">&#x2003;GG</td>
<td align="center">302 (66.5%)</td>
<td align="center">173 (62.7%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;GA</td>
<td align="center">134 (29.5%)</td>
<td align="center">90 (32.6%)</td>
<td align="center">1.065 (0.734&#x2013;1.544)</td>
<td align="center">0.740</td>
</tr>
<tr>
<td align="left">&#x2003;AA</td>
<td align="center">18 (4.0%)</td>
<td align="center">13 (4.7%)</td>
<td align="center">0.932 (0.408&#x2013;2.131)</td>
<td align="center">0.868</td>
</tr>
<tr>
<td align="left">&#x2003;GA &#x2b; AA</td>
<td align="center">152 (33.5%)</td>
<td align="center">103 (37.3%)</td>
<td align="center">1.023 (0.857&#x2013;1.222)</td>
<td align="center">0.801</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-G</td>
<td align="center">738 (81.3%)</td>
<td align="center">436 (79.0%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-A</td>
<td align="center">170 (18.7%)</td>
<td align="center">116 (21.0%)</td>
<td align="center">1.010 (0.869&#x2013;1.174)</td>
<td align="center">0.894</td>
</tr>
<tr>
<td colspan="5" align="left">rs11655237</td>
</tr>
<tr>
<td align="left">&#x2003;CC</td>
<td align="center">301 (66.3%)</td>
<td align="center">167 (60.5%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;CT</td>
<td align="center">138 (30.4%)</td>
<td align="center">97 (35.1%)</td>
<td align="center">1.296 (0.899&#x2013;1.869)</td>
<td align="center">0.164</td>
</tr>
<tr>
<td align="left">&#x2003;TT</td>
<td align="center">15 (3.3%)</td>
<td align="center">12 (4.4%)</td>
<td align="center">1.655 (0.691&#x2013;3.967)</td>
<td align="center">0.258</td>
</tr>
<tr>
<td align="left">&#x2003;CT &#x2b; TT</td>
<td align="center">153 (33.7%)</td>
<td align="center">109 (39.5%)</td>
<td align="center">1.153 (0.967&#x2013;1.376)</td>
<td align="center">0.112</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-C</td>
<td align="center">740 (81.5%)</td>
<td align="center">431 (78.1%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-T</td>
<td align="center">168 (18.5%)</td>
<td align="center">121 (21.9%)</td>
<td align="center">1.134 (0.978&#x2013;1.315)</td>
<td align="center">0.096</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>N, number; DR, diabetic retinopathy; AOR, adjusted odds ratio, estimated by multiple logistic regression models after controlling for age, the duration of DM, HbA1c, insulin treatment, serum creatinine levels, glomerular filtration rate, and HDL cholesterol levels; CI, confidence interval.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T3" position="float">
<label>TABLE 3</label>
<caption>
<p>Adjusted odds ratio and 95% confidence intervals of non-proliferative diabetic retinopathy associated with <italic>LINC00673</italic> genotypic frequencies.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Variable</th>
<th align="center">Non-DR group (<italic>N</italic> &#x3d; 454)</th>
<th align="center">NPDR subgroup (<italic>N</italic> &#x3d; 165)</th>
<th align="center">AOR (95% CI)</th>
<th align="center">
<italic>p</italic>-value</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td colspan="5" align="left">rs6501551</td>
</tr>
<tr>
<td align="left">&#x2003;AA</td>
<td align="center">334 (73.6%)</td>
<td align="center">114 (69.1%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;AG</td>
<td align="center">113 (24.9%)</td>
<td align="center">45 (27.3%)</td>
<td align="center">1.139 (0.731&#x2013;1.773)</td>
<td align="center">0.565</td>
</tr>
<tr>
<td align="left">&#x2003;GG</td>
<td align="center">7 (1.5%)</td>
<td align="center">6 (3.6%)</td>
<td align="center">2.890 (0.903&#x2013;9.251)</td>
<td align="center">0.074</td>
</tr>
<tr>
<td align="left">&#x2003;AG &#x2b; GG</td>
<td align="center">120 (26.4%)</td>
<td align="center">51 (30.9%)</td>
<td align="center">1.114 (0.901&#x2013;1.377)</td>
<td align="center">0.320</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-A</td>
<td align="center">781 (86.0%)</td>
<td align="center">273 (82.7%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-G</td>
<td align="center">127 (14.0%)</td>
<td align="center">57 (17.3%)</td>
<td align="center">1.141 (0.949&#x2013;1.372)</td>
<td align="center">0.161</td>
</tr>
<tr>
<td colspan="5" align="left">rs9914618</td>
</tr>
<tr>
<td align="left">&#x2003;GG</td>
<td align="center">302 (66.5%)</td>
<td align="center">107 (64.8%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;GA</td>
<td align="center">134 (29.5%)</td>
<td align="center">48 (29.1%)</td>
<td align="center">0.928 (0.600&#x2013;1.436)</td>
<td align="center">0.738</td>
</tr>
<tr>
<td align="left">&#x2003;AA</td>
<td align="center">18 (4.0%)</td>
<td align="center">10 (6.1%)</td>
<td align="center">1.257 (0.527&#x2013;2.998)</td>
<td align="center">0.607</td>
</tr>
<tr>
<td align="left">&#x2003;GA &#x2b; AA</td>
<td align="center">152 (33.5%)</td>
<td align="center">58 (35.2%)</td>
<td align="center">0.986 (0.803&#x2013;1.211)</td>
<td align="center">0.895</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-G</td>
<td align="center">738 (81.3%)</td>
<td align="center">262 (79.4%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-A</td>
<td align="center">170 (18.7%)</td>
<td align="center">68 (20.6%)</td>
<td align="center">1.010 (0.850&#x2013;1.200)</td>
<td align="center">0.912</td>
</tr>
<tr>
<td colspan="5" align="left">rs11655237</td>
</tr>
<tr>
<td align="left">&#x2003;CC</td>
<td align="center">301 (66.3%)</td>
<td align="center">91 (55.2%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;CT</td>
<td align="center">138 (30.4%)</td>
<td align="center">68 (41.2%)</td>
<td align="center">1.592 (1.059&#x2013;2.395)</td>
<td align="center">0.026<xref ref-type="table-fn" rid="Tfn2">
<sup>a</sup>
</xref>
</td>
</tr>
<tr>
<td align="left">&#x2003;TT</td>
<td align="center">15 (3.3%)</td>
<td align="center">6 (3.6%)</td>
<td align="center">1.414 (0.492&#x2013;4.070)</td>
<td align="center">0.520</td>
</tr>
<tr>
<td align="left">&#x2003;CT &#x2b; TT</td>
<td align="center">153 (33.7%)</td>
<td align="center">74 (44.8%)</td>
<td align="center">1.255 (1.029&#x2013;1.531)</td>
<td align="center">0.025<xref ref-type="table-fn" rid="Tfn2">
<sup>a</sup>
</xref>
</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-C</td>
<td align="center">740 (81.5%)</td>
<td align="center">250 (75.8%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-T</td>
<td align="center">168 (18.5%)</td>
<td align="center">80 (24.2%)</td>
<td align="center">1.185 (1.004&#x2013;1.397)</td>
<td align="center">0.044<xref ref-type="table-fn" rid="Tfn2">
<sup>a</sup>
</xref>
</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>N, number; DR, diabetic retinopathy; NPDR, non-proliferative diabetic retinopathy; AOR, adjusted odds ratio, estimated by multiple logistic regression models after controlling for age, the duration of DM, HbA1c, insulin treatment, serum creatinine levels, glomerular filtration rate, and HDL cholesterol levels; CI: confidence interval.</p>
</fn>
<fn id="Tfn2">
<label>a</label>
<p>denotes significant difference about the distribution of polymorphism between the two groups.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T4" position="float">
<label>TABLE 4</label>
<caption>
<p>Adjusted odds ratio and 95% confidence intervals of proliferative diabetic retinopathy associated with <italic>LINC00673</italic> genotypic frequencies.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Variable</th>
<th align="center">Non-DR group (<italic>N</italic> &#x3d; 454)</th>
<th align="center">PDR subgroup (<italic>N</italic> &#x3d; 111)</th>
<th align="center">AOR (95% CI)</th>
<th align="center">
<italic>p</italic>-value</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td colspan="5" align="left">rs6501551</td>
</tr>
<tr>
<td align="left">&#x2003;AA</td>
<td align="center">334 (73.6%)</td>
<td align="center">86 (77.5%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;AG</td>
<td align="center">113 (24.9%)</td>
<td align="center">25 (22.5%)</td>
<td align="center">0.784 (0.433&#x2013;1.418)</td>
<td align="center">0.421</td>
</tr>
<tr>
<td align="left">&#x2003;GG</td>
<td align="center">7 (1.5%)</td>
<td align="center">0 (0.0%)</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;AG &#x2b; GG</td>
<td align="center">120 (26.4%)</td>
<td align="center">25 (22.5%)</td>
<td align="center">0.857 (0.637&#x2013;1.151)</td>
<td align="center">0.304</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-A</td>
<td align="center">781 (86.0%)</td>
<td align="center">197 (88.7%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-G</td>
<td align="center">127 (14.0%)</td>
<td align="center">25 (11.3%)</td>
<td align="center">0.844 (0.643&#x2013;1.108)</td>
<td align="center">0.223</td>
</tr>
<tr>
<td colspan="5" align="left">rs9914618</td>
</tr>
<tr>
<td align="left">&#x2003;GG</td>
<td align="center">302 (66.5%)</td>
<td align="center">66 (59.5%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;GA</td>
<td align="center">134 (29.5%)</td>
<td align="center">42 (37.8%)</td>
<td align="center">1.499 (0.885&#x2013;2.539)</td>
<td align="center">0.132</td>
</tr>
<tr>
<td align="left">&#x2003;AA</td>
<td align="center">18 (4.0%)</td>
<td align="center">3 (2.7%)</td>
<td align="center">0.594 (0.133&#x2013;2.653)</td>
<td align="center">0.495</td>
</tr>
<tr>
<td align="left">&#x2003;GA &#x2b; AA</td>
<td align="center">152 (33.5%)</td>
<td align="center">45 (40.5%)</td>
<td align="center">1.171 (0.906&#x2013;1.514)</td>
<td align="center">0.227</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-G</td>
<td align="center">738 (81.3%)</td>
<td align="center">174 (78.4%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-A</td>
<td align="center">170 (18.7%)</td>
<td align="center">48 (21.6%)</td>
<td align="center">1.082 (0.871&#x2013;1.343)</td>
<td align="center">0.478</td>
</tr>
<tr>
<td colspan="5" align="left">rs11655237</td>
</tr>
<tr>
<td align="left">&#x2003;CC</td>
<td align="center">301 (66.3%)</td>
<td align="center">76 (68.5%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;CT</td>
<td align="center">138 (30.4%)</td>
<td align="center">29 (26.1%)</td>
<td align="center">0.756 (0.420&#x2013;1.360)</td>
<td align="center">0.350</td>
</tr>
<tr>
<td align="left">&#x2003;TT</td>
<td align="center">15 (3.3%)</td>
<td align="center">6 (5.4%)</td>
<td align="center">2.295 (0.749&#x2013;7.033)</td>
<td align="center">0.146</td>
</tr>
<tr>
<td align="left">&#x2003;CT &#x2b; TT</td>
<td align="center">153 (33.7%)</td>
<td align="center">35 (31.5%)</td>
<td align="center">0.944 (0.720&#x2013;1.238)</td>
<td align="center">0.677</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-C</td>
<td align="center">740 (81.5%)</td>
<td align="center">181 (81.5%)</td>
<td align="center">1.000 (references)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;Allele-T</td>
<td align="center">168 (18.5%)</td>
<td align="center">41 (18.5%)</td>
<td align="center">1.026 (0.818&#x2013;1.287)</td>
<td align="center">0.824</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>N, number; DR, diabetic retinopathy; PDR: proliferative diabetic retinopathy; AOR, adjusted odds ratio, estimated by multiple logistic regression models after controlling for age, the duration of DM, HbA1c, insulin treatment, serum creatinine levels, glomerular filtration rate, and HDL cholesterol levels; CI: confidence interval.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3-3">
<title>Clinical Characteristics and Distribution of <italic>LINC00673</italic> SNP rs11655237 in the DR Group</title>
<p>In the DR group, DM duration was significantly shorter in the <italic>LINC00673</italic> SNP rs11655237 CT &#x2b; TT variant than in the <italic>LINC00673</italic> SNP rs11655237 wild type (10.44 &#xb1; 7.10 versus 12.98 &#xb1; 8.34, <italic>p</italic> &#x3d; 0.009). Other factors, including HbA1c, renal function, and lipid profile, produced similar values between the <italic>LINC00673</italic> SNP rs11655237 wild type and the <italic>LINC00673</italic> SNP rs11655237 CT &#x2b; TT variant (all <italic>p</italic> &#x3e; 0.05; <xref ref-type="table" rid="T5">Table 5</xref>).</p>
<table-wrap id="T5" position="float">
<label>TABLE 5</label>
<caption>
<p>Clinical characteristics of diabetic retinopathy individuals according to <italic>LINC00673</italic> rs11655237 genotypes.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="2" align="left">Variable</th>
<th colspan="3" align="center">
<italic>LINC00673</italic> rs11655237</th>
</tr>
<tr>
<th align="center">CC (<italic>N</italic> &#x3d; 167)</th>
<th align="center">CT &#x2b; TT (<italic>N</italic> &#x3d; 109)</th>
<th align="center">
<italic>p</italic>-value</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Duration of DM (years)</td>
<td align="char" char="plusmn">12.98 &#xb1; 8.34</td>
<td align="char" char="plusmn">10.44 &#xb1; 7.10</td>
<td align="char" char=".">0.009<xref ref-type="table-fn" rid="Tfn3">
<sup>a</sup>
</xref>
</td>
</tr>
<tr>
<td align="left">HbA1c [% (mmol/mol)]</td>
<td align="char" char="plusmn">7.64 &#xb1; 1.39</td>
<td align="char" char="plusmn">7.51 &#xb1; 1.46</td>
<td align="char" char=".">0.482</td>
</tr>
<tr>
<td align="left">Serum creatinine [mg/dL]</td>
<td align="char" char="plusmn">1.45 &#xb1; 1.40</td>
<td align="char" char="plusmn">1.68 &#xb1; 2.36</td>
<td align="char" char=".">0.318</td>
</tr>
<tr>
<td align="left">Glomerular filtration rate [ml/min]</td>
<td align="char" char="plusmn">61.73 &#xb1; 32.96</td>
<td align="char" char="plusmn">64.63 &#xb1; 35.99</td>
<td align="char" char=".">0.497</td>
</tr>
<tr>
<td align="left">Total cholesterol [mmol/L]</td>
<td align="char" char="plusmn">161.43 &#xb1; 47.95</td>
<td align="char" char="plusmn">171.13 &#xb1; 46.72</td>
<td align="char" char=".">0.108</td>
</tr>
<tr>
<td align="left">HDL cholesterol [&#x3bc;mol/L]</td>
<td align="char" char="plusmn">42.88 &#xb1; 13.06</td>
<td align="char" char="plusmn">45.37 &#xb1; 14.27</td>
<td align="char" char=".">0.148</td>
</tr>
<tr>
<td align="left">LDL cholesterol [&#x3bc;mol/L]</td>
<td align="char" char="plusmn">85.24 &#xb1; 34.07</td>
<td align="char" char="plusmn">88.05 &#xb1; 31.00</td>
<td align="char" char=".">0.502</td>
</tr>
<tr>
<td align="left">Triglycerides, [&#x3bc;mol/L]</td>
<td align="char" char="plusmn">153.08 &#xb1; 109.31</td>
<td align="char" char="plusmn">162.46 &#xb1; 130.37</td>
<td align="char" char=".">0.532</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>LINC00673, long intergenic noncoding RNA 00673; N, number; DM, diabetes mellitus; HbA1c, glycated hemoglobin.</p>
</fn>
<fn id="Tfn3">
<label>a</label>
<p>denotes significant difference between the two groups.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>In this study, the <italic>LINC00673</italic> SNP rs11655237 CT and CT &#x2b; TT phenotypes and the <italic>LINC00673</italic> SNP rs11655237 T allele were more common in patients with NPDR than in the non-DR population. In addition, <italic>LINC00673</italic> SNP rs11655237 CT &#x2b; TT variants were associated with a shorter DM interval in the DR group. However, the distribution of the <italic>LINC00673</italic> SNP rs11655237 variant was similar between the PDR and non-DR groups.</p>
<p>Several biochemical pathways are correlated with the occurrence of NPDR and PDR (<xref ref-type="bibr" rid="B17">Jenkins et al., 2015</xref>), in which inflammatory growth, and angiogenic molecules play major roles (<xref ref-type="bibr" rid="B17">Jenkins et al., 2015</xref>). In the development of DR, hypoxic and ischemic retinas secrete inflammatory cytokines such as interleukin-6 and monocyte chemotactic protein, resulting in a prominent inflammatory reaction and leading to vascular damage and retinal ganglion cell death (<xref ref-type="bibr" rid="B36">Wang and Lo, 2018</xref>). VEGF concentration is also elevated in such conditions (<xref ref-type="bibr" rid="B14">Huang et al., 2015</xref>). If DR progresses, the retinal concentration of VEGF further increases, and retinal neovascularization eventually develops (<xref ref-type="bibr" rid="B24">Osaadon et al., 2014</xref>). Anti-VEGF is the main treatment for PDR and its related complications such as vitreous hemorrhage and neovascular glaucoma (<xref ref-type="bibr" rid="B36">Wang and Lo, 2018</xref>). Intraocular steroid injection can also retard the progression of PDR (<xref ref-type="bibr" rid="B16">Iglicki et al., 2018</xref>). Regarding genetic polymorphisms, VEGF polymorphism influences the development of DR (<xref ref-type="bibr" rid="B19">Khan et al., 2020</xref>). In previous studies, VEGF SNP-634G &#x3e; C was associated with a higher rate of DR (<xref ref-type="bibr" rid="B28">Qiu et al., 2013</xref>), and VEGF SNP rs2146323 was related to DR severity (<xref ref-type="bibr" rid="B7">Churchill et al., 2008</xref>). SNP rs11567245 of inflammatory cytokine interleukin-10 could also promote DR development (<xref ref-type="bibr" rid="B30">Shi et al., 2019</xref>).</p>
<p>SNPs of lncRNAs have been proposed to influence certain types of malignancies and angiogenic diseases (<xref ref-type="bibr" rid="B26">Peng et al., 2017</xref>; <xref ref-type="bibr" rid="B40">Yuan et al., 2019</xref>; <xref ref-type="bibr" rid="B38">Weng et al., 2020</xref>; <xref ref-type="bibr" rid="B8">Ding et al., 2021</xref>; <xref ref-type="bibr" rid="B37">Wang et al., 2021</xref>). In previous studies, lncRNA <italic>CCAT1</italic> SNP rs67085638 was correlated with the development of gastric cancer (<xref ref-type="bibr" rid="B23">Olesi&#x144;ski et al., 2021</xref>), and lncRNA <italic>PCAT1</italic> and its SNP rs2632159 were associated with a higher rate of colon cancer, which involves an angiogenesis process (<xref ref-type="bibr" rid="B39">Yang et al., 2019</xref>). LINC00673, a member of the lncRNA family, can enhance the development of certain neoplasms because of its chromatin modulation and transcriptional regulation functions (<xref ref-type="bibr" rid="B21">Lu et al., 2017</xref>; <xref ref-type="bibr" rid="B27">Qiao et al., 2019</xref>; <xref ref-type="bibr" rid="B13">Hsieh et al., 2021</xref>; <xref ref-type="bibr" rid="B15">Huang et al., 2021</xref>). <italic>LINC00673</italic> SNP rs11655237 could alter the development of several cancers, including hepatocellular carcinoma, pancreatic cancer, and oral cancer (<xref ref-type="bibr" rid="B20">Li et al., 2020</xref>). Because <italic>LINC00673</italic> SNP is related to cellular proliferation and lncRNA SNP is correlated with angiogenesis, <italic>LINC00673</italic> SNP may also lead to DR development, which is characterized by both cell proliferation and angiogenesis. This hypothesis is aided by our study&#x2019;s results.</p>
<p>Studies that have discussed the possible correlation between <italic>LINC00673</italic> SNP and DR development are rare; only one study has evaluated the relationship between LINC00673 expression and DR (<xref ref-type="bibr" rid="B4">Cheng et al., 2021</xref>). In our study, the frequency of <italic>LINC00673</italic> SNPs (i.e., rs6501551, rs9914618, and rs11655237) was not significantly different between the non-DR and DR groups. In the subgroup analyses that divided the DR group into the NPDR and PDR subgroups, the <italic>LINC00673</italic> SNP rs11655237 CT and CT &#x2b; TT variants were correlated with NPDR development, with a higher AOR. This result may support the relationship between <italic>LINC00673</italic> SNP rs11655237 and NPDR. Conversely, the <italic>LINC00673</italic> SNP rs11655237 TT variant was not significantly correlated with NPDR development. A total of fifteen patients had the <italic>LINC00673</italic> SNP rs11655237&#xa0;TT phenotype, of which six patients were in each of the non-DR group and NPDR subgroup, accounting for approximately 3% in each group. Such a few number of cases may lead to statistical bias. The analysis of the T allele effect on <italic>LINC00673</italic> SNP rs11655237 revealed a significantly higher <italic>LINC00673</italic> SNP rs11655237 T-allele distribution in the NPDR subgroup. Consequently, we speculated that the existence of the T allele in <italic>LINC00673</italic> SNP rs11655237, whether in the homogenous or heterogeneous form, is crucial for the development of NPDR. On the contrary, the distribution of the three <italic>LINC00673</italic> SNPs was not significantly different between the non-DR group and the PDR population. It may be possible that the effect of a single SNP is not adequate to trigger the angiogenesis process that contributes to PDR development. Whether the development of PDR is influenced by the LINC00673 SNP in combination with VEGF SNP or other biomarkers requires additional investigation.</p>
<p>Concerning clinicopathological characteristics, our study demonstrated that individuals who had DR with the <italic>LINC00673</italic> SNP rs11655237 CT and TT variants exhibited a significantly shorter DM duration than that with the <italic>LINC00673</italic> SNP rs11655237 CC phenotype. We believe this is preliminary evidence that genetic polymorphisms of <italic>LINC00673</italic> may affect the course of DR development in patients with DM. The DM duration in patients with the <italic>LINC00673</italic> SNP rs11655237 CT and TT variants was nearly 2.5&#xa0;years shorter than that of patients with the <italic>LINC00673</italic> SNP rs11655237 wild type and also shorter than the mean DM duration in a previous study (<xref ref-type="bibr" rid="B11">Gverovi&#x107; Antunica et al., 2019</xref>). Although the exact mechanism underlying this finding is unknown, we speculate that the <italic>LINC00673</italic> SNP rs11655237 CT and TT variants might make the retina more vulnerable to hyperglycemic conditions, even with numerically lower HbA1c levels. This finding, along with the higher genotype frequency of <italic>LINC00673</italic> SNP rs11655237 variants in the NPDR subgroup, may explain the prominent effect of the <italic>LINC00673</italic> SNP rs11655237 variant on NPDR development.</p>
<p>Regarding demographic data and laboratory findings, patients with DR were significantly older than those without DR. Because age is an established risk factor for DR occurrence (<xref ref-type="bibr" rid="B1">Antonetti et al., 2012</xref>), our findings agree with those of previous studies (<xref ref-type="bibr" rid="B1">Antonetti et al., 2012</xref>). In addition, longer DM duration, higher serum HbA1c concentration, and higher ratio of insulin treatment were observed in the DR group, which could indicate that inadequate blood sugar control is a prominent risk factor for DR (<xref ref-type="bibr" rid="B5">Cheung et al., 2010</xref>). Renal function was significantly worse in the DR group. In previous studies, poorly controlled DM was associated with a higher rate of chronic kidney disease (<xref ref-type="bibr" rid="B35">Tziomalos and Athyros, 2015</xref>). Chronic kidney disease would in turn contribute to retinal diseases such as retinal microangiopathy and central serous chorioretinopathy (<xref ref-type="bibr" rid="B3">Chang et al., 2019</xref>; <xref ref-type="bibr" rid="B18">Kasumovic et al., 2020</xref>). It is therefore reasonable that kidney impairment and DR developed concurrently in our study. Higher HDL cholesterol levels in the DR group may have not been clinically significant because both values belonged to the low-HDL status (<xref ref-type="bibr" rid="B22">M&#xe4;rz et al., 2017</xref>).</p>
<p>Our study had several limitations. First, because our study used a case&#x2013;control design, rather than a cohort design, we could not evaluate the possible causal relationship between the <italic>LINC00673</italic> SNP and the clinical course of DR. Second, some patients may have received DR-related treatment elsewhere, which may have modified their clinical course toward NPDR and could have caused a wrong estimation of the effect of <italic>LINC00673</italic> SNP on PDR development. Additionally, the interval between the internal medicine department visit and the ophthalmic department visit was uneven among the participants.</p>
</sec>
<sec sec-type="conclusion" id="s5">
<title>Conclusion</title>
<p>In conclusion, the existence of the <italic>LINC00673</italic> SNP rs11655237 T allele is associated with a higher probability of NPDR development. The <italic>LINC00673</italic> SNP rs11655237 variant is correlated with a shorter DM interval in patients with DR; consequently, genetic screening might be suggested for patients with DM. Patients with this genetic polymorphism should observe stricter blood sugar control. Further large-scale prospective studies to examine whether the <italic>LINC00673</italic> polymorphism would interact with the VEGF polymorphism in DR are warranted.</p>
</sec>
</body>
<back>
<sec id="s6">
<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">
<title>Ethics Statement</title>
<p>The studies involving human subjects were reviewed and approved by the Institutional Review Board of Chung Shan Medical University Hospital. The patients/participants provided their written informed consent to participate in this study.</p>
</sec>
<sec id="s8">
<title>Author Contributions</title>
<p>C-CC and S-FY proposed the study concept and study design. Y-SY, EK, C-NH, M-YH, and S-FY participated in sample and data collection. C-CC, C-YL, and S-FY participated in statistical analyses. C-CC, C-YL, and S-FY wrote and edited the manuscript. All authors agree to be accountable for all aspects of the work.</p>
</sec>
<sec sec-type="COI-statement" id="s9">
<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 sec-type="disclaimer" id="s10">
<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>
<ack>
<p>We would like to thank the Human Biobank of Chung Shan Medical University Hospital for providing the biological specimen and related clinical data for our research.</p>
</ack>
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