{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T16:17:30Z","timestamp":1783959450222,"version":"3.55.0"},"reference-count":238,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"5","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["Circ: Genomic and Precision Medicine"],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:sec>\n                    <jats:title>BACKGROUND:<\/jats:title>\n                    <jats:p>Congenital heart disease (CHD) is the most common heterogeneous birth defect, with prevalence varying across populations. A comprehensive meta-analysis could refine the genetic risk estimates and enhance our understanding of CHD susceptibility.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS:<\/jats:title>\n                    <jats:p>We conducted a meta-analysis of 175 case-control studies investigating 107 genetic variants across 72 gene regions. Pooled odds ratios were calculated using 6 genetic models, with subgroup analyses by ethnicity and CHD subtype. Gene Ontology and network analyses elucidated the functional significance of implicated genes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS:<\/jats:title>\n                    <jats:p>\n                      Thirty-six variants were significantly associated with CHD (\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt;0.05), including 7 missense mutations in\n                      <jats:italic toggle=\"yes\">NRP1<\/jats:italic>\n                      ,\n                      <jats:italic toggle=\"yes\">MTHFR<\/jats:italic>\n                      ,\n                      <jats:italic toggle=\"yes\">MTRR<\/jats:italic>\n                      ,\n                      <jats:italic toggle=\"yes\">NOS3<\/jats:italic>\n                      , and\n                      <jats:italic toggle=\"yes\">DNMT1<\/jats:italic>\n                      . Ten variants, including rs1531070 in\n                      <jats:italic toggle=\"yes\">MAML3<\/jats:italic>\n                      (odds ratio, 1.52;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =5.9\u00d710\n                      <jats:sup>\u221215<\/jats:sup>\n                      ), surpassed genome-wide significance. Ethnicity-specific analyses identified 13 significant variants, including\n                      <jats:italic toggle=\"yes\">MTHFR<\/jats:italic>\n                      -rs1801131 in Chinese (\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =1.71\u00d710\n                      <jats:sup>\u221210<\/jats:sup>\n                      ),\n                      <jats:italic toggle=\"yes\">STX18-AS1<\/jats:italic>\n                      -rs870142 in Europeans (\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =7.13\u00d710\n                      <jats:sup>\u221216<\/jats:sup>\n                      ), and\n                      <jats:italic toggle=\"yes\">MTRR<\/jats:italic>\n                      -rs1801394 in Middle Eastern populations (\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =9.8\u00d710\n                      <jats:sup>\u22128<\/jats:sup>\n                      ). Subtype analyses revealed 25 variants associated with specific CHD subtypes, such as\n                      <jats:italic toggle=\"yes\">STX18-AS1<\/jats:italic>\n                      -rs16835979 with atrial septal defect (\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =2.1\u00d710\n                      <jats:sup>\u221216<\/jats:sup>\n                      ) and variants in\n                      <jats:italic toggle=\"yes\">MTHFR<\/jats:italic>\n                      ,\n                      <jats:italic toggle=\"yes\">NRP1<\/jats:italic>\n                      , and\n                      <jats:italic toggle=\"yes\">PTPN11<\/jats:italic>\n                      with tetralogy of Fallot (\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =3.0\u00d710\n                      <jats:sup>\u221217<\/jats:sup>\n                      \u20132.33\u00d710\n                      <jats:sup>\u221210<\/jats:sup>\n                      ). The rs1801133 variant was linked to double-outlet right ventricle (\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =3.0\u00d710\n                      <jats:sup>\u221211<\/jats:sup>\n                      ) and patent ductus arteriosus (\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =6.5\u00d710\n                      <jats:sup>\u22129<\/jats:sup>\n                      ). Gene Ontology and network analyses highlighted genes involved in cardiac development and folate metabolism in CHD pathogenesis.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSIONS:<\/jats:title>\n                    <jats:p>This meta-analysis refines CHD risk estimates across diverse ancestries and subtypes, underscoring the complex genetic architecture of the disease. Variants involved in cardiac development and metabolic pathways represent promising targets for precision medicine in CHD.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1161\/circgen.124.005039","type":"journal-article","created":{"date-parts":[[2025,8,27]],"date-time":"2025-08-27T09:00:15Z","timestamp":1756285215000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":2,"title":["Genetic Variants Associated With Congenital Heart Disease: A Meta-Analysis of Ethnicity and Subtype-Specific Susceptibility"],"prefix":"10.1161","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-8604-5989","authenticated-orcid":true,"given":"Hae Sung","family":"Chon","sequence":"first","affiliation":[{"name":"Department of Medical Genetics, Hallym University College of Medicine, Chuncheon, Gangwon, Republic of Korea."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0840-1696","authenticated-orcid":true,"given":"Ji Wan","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Medical Genetics, Hallym University College of Medicine, Chuncheon, Gangwon, Republic of Korea."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2020.11.010"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1093\/ije\/dyz009"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1515\/CCLM.2003.043"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.4238\/2011.October.25.7"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.kjms.2017.05.016"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12864-024-10172-x"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1172\/JCI141837"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0010855"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1089\/gtmb.2011.0249"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.0001-6349.2005.00611.x"},{"key":"e_1_3_3_12_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.b2700"},{"key":"e_1_3_3_13_2","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/29.1.308"},{"key":"e_1_3_3_14_2","volume-title":"The Newcastle\u2013Ottawa Scale (NOS) for Assessing the Quality of Non-Randomized Studies in Meta-Analysis","author":"Wells G","year":"2000","unstructured":"Wells G, Shea B, O\u2019Connell D, Peterson j, Welch V, Losos M, Tugwell P. 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