{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T10:18:25Z","timestamp":1779099505458,"version":"3.51.4"},"reference-count":60,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T00:00:00Z","timestamp":1758844800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T00:00:00Z","timestamp":1758844800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["X01HD100698"],"award-info":[{"award-number":["X01HD100698"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["X01HD110998"],"award-info":[{"award-number":["X01HD110998"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["HD114132"],"award-info":[{"award-number":["HD114132"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["P01HD104436"],"award-info":[{"award-number":["P01HD104436"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U54OD030187"],"award-info":[{"award-number":["U54OD030187"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100013114","name":"Broad Institute","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100013114","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000011","name":"Howard Hughes Medical Institute","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000011","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Birth Defects Research"],"published-print":{"date-parts":[[2025,10]]},"abstract":"ABSTRACT<\/jats:title>\n \n Background<\/jats:title>\n \n Spina bifida (\n SB<\/jats:styled-content>\n ), a common neural tube defects (\n NTDs<\/jats:styled-content>\n ), has a complex genetic architecture that remains incompletely understood. Although prior studies have identified rare, deleterious single nucleotide variants (\n SNVs<\/jats:styled-content>\n ) in\n SB<\/jats:styled-content>\n , broader contributions to risk remain unclear. Here, we investigated shared genetic risk among 256\n SB<\/jats:styled-content>\n probands compared with 395 ancestry\u2010matched controls using an unbiased sequencing approach.\n <\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n We performed an exome\u2010wide association study (\n ExWAS<\/jats:styled-content>\n ) of 46,887\n SNVs<\/jats:styled-content>\n with minor allele frequencies (\n MAF<\/jats:styled-content>\n ) >\u20090.001 to identify single\u2010variant associations, followed by gene\u2010based burden tests to assess the cumulative effect of\n SNVs<\/jats:styled-content>\n within genes, using all variants and then restricting to rare variants (\n MAF<\/jats:styled-content>\n <\u20090.05). Both burden tests were repeated in 510 unaffected parents to evaluate excess mutational burden relative to controls.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Across all analyses, 16 genes were associated with\n SB<\/jats:styled-content>\n :\n \n SRCIN1<\/jats:italic>\n <\/jats:styled-content>\n ,\n \n PDE4DIP<\/jats:italic>\n <\/jats:styled-content>\n ,\n \n XCL2<\/jats:italic>\n <\/jats:styled-content>\n ,\n \n CTAGE10P<\/jats:italic>\n <\/jats:styled-content>\n ,\n \n GLB1L3<\/jats:italic>\n <\/jats:styled-content>\n ,\n \n PMS2P4<\/jats:italic>\n <\/jats:styled-content>\n ,\n \n HSPA4<\/jats:italic>\n <\/jats:styled-content>\n ,\n \n GLB1L2<\/jats:italic>\n <\/jats:styled-content>\n ,\n \n FAM90A1<\/jats:italic>\n <\/jats:styled-content>\n ,\n \n PLA1A<\/jats:italic>\n <\/jats:styled-content>\n ,\n \n HLA<\/jats:styled-content>\n \u2010A\n <\/jats:italic>\n ,\n \n SPIRE2<\/jats:italic>\n <\/jats:styled-content>\n ,\n \n TVP23B<\/jats:italic>\n <\/jats:styled-content>\n ,\n \n CHD5<\/jats:italic>\n <\/jats:styled-content>\n ,\n \n FOXA2<\/jats:italic>\n <\/jats:styled-content>\n , and\n \n PIF1<\/jats:italic>\n <\/jats:styled-content>\n .\n ExWAS<\/jats:styled-content>\n identified 11 significant\n SNVs<\/jats:styled-content>\n , nine of which were common (\n MAF<\/jats:styled-content>\n >\u20090.05). The unrestricted burden test identified seven genes; four remained significant when restricted to rare variants, and two additional genes emerged only in that subset. Five burden\u2010associated genes were not detected in the\n ExWAS<\/jats:styled-content>\n , suggesting cumulative variant effects. Four burden\u2010associated genes also showed enrichment in parents, supporting inherited risk. Three of these showed suggestive transmission disequilibrium (\n p<\/jats:italic>\n values \u2264\u20090.10) and one was attributed to multiple\n SNVs.<\/jats:styled-content>\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n \n These results provide new insight into the multifactorial genetic landscape of\n SB<\/jats:styled-content>\n and highlight the importance of unbiased approaches in constructing genetic models of\n NTD<\/jats:styled-content>\n .\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1002\/bdr2.2533","type":"journal-article","created":{"date-parts":[[2025,9,27]],"date-time":"2025-09-27T05:59:06Z","timestamp":1758952746000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Sequencing Analysis Demonstrates That a Complex Genetic Architecture Contributes to Risk for Spina Bifida"],"prefix":"10.1002","volume":"117","author":[{"given":"Madison","family":"Strain","sequence":"first","affiliation":[{"name":"Duke Molecular Physiology Institute Duke University Medical Center Durham North Carolina USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Melanie E.","family":"Garrett","sequence":"additional","affiliation":[{"name":"Duke Molecular Physiology Institute Duke University Medical Center Durham North Carolina USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Max","family":"Bucklan","sequence":"additional","affiliation":[{"name":"Duke Molecular Physiology Institute Duke University Medical Center Durham North Carolina USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joan M.","family":"Jasien","sequence":"additional","affiliation":[{"name":"Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics Duke University Medical Center Durham North Carolina USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gordon","family":"Worley","sequence":"additional","affiliation":[{"name":"Division of Pediatric Neurology and Developmental Medicine, Department of Pediatrics Duke University Medical Center Durham North Carolina USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joseph G.","family":"Gleeson","sequence":"additional","affiliation":[{"name":"Rady Children's Institute for Genomic Medicine San Diego California USA"},{"name":"Department of Neurosciences and Pediatrics University of California San Diego California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5409-9155","authenticated-orcid":false,"given":"Allison E.","family":"Ashley\u2010Koch","sequence":"additional","affiliation":[{"name":"Duke Molecular Physiology Institute Duke University Medical Center Durham North Carolina USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,9,26]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnmol.2017.00212"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1101\/gr.277908.123"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598\u2010021\u201083058\u20107"},{"key":"e_1_2_9_5_1","volume-title":"Genomics in the Cloud: Using Docker, GATK, and WDL in Terra","author":"Auwera G. v. 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