{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T10:07:34Z","timestamp":1780308454883,"version":"3.54.0"},"posted":{"date-parts":[[2026,5,28]]},"group-title":"Neuroscience","reference-count":58,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T00:00:00Z","timestamp":1779926400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.biorxiv.org\/about\/FAQ#license"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","award":["R01DK137899"],"award-info":[{"award-number":["R01DK137899"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","award":["R01MH133840"],"award-info":[{"award-number":["R01MH133840"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","award":["K01MH122774"],"award-info":[{"award-number":["K01MH122774"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000874","name":"Brain & Behavior Research Foundation","doi-asserted-by":"crossref","award":["NARSAD Young Investigator Award"],"award-info":[{"award-number":["NARSAD Young Investigator Award"]}],"id":[{"id":"10.13039\/100000874","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,5,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Importance<\/jats:title>\n                  <jats:p>Prenatal exposure to gestational diabetes mellitus (GDM) has been associated with adverse metabolic, neurodevelopmental, and psychiatric outcomes in offspring. However, whether GDM-exposed youth exhibit heterogeneous neuroanatomical patterns remains unclear.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>To identify distinct cortical thickness subtypes among GDM-exposed youth and examine their associations with anthropometric, neurocognitive, psychiatric\/behavioral and neuroimaging measures both cross-sectionally and longitudinally.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Design, Setting, and Participants<\/jats:title>\n                  <jats:p>This cohort study used the Adolescent Brain Cognitive Development (ABCD)\u00aedata, a multisite longitudinal population study. Subtype and Stage Inference (SuStaIn), an unsupervised machine learning framework, was applied to cross-sectional structural MRI data to identify cortical thickness patterns in 573 GDM-exposed youth and 2854 healthy controls. Posthoc longitudinal analyses included 1,853 observations from a subset of GDM-exposed youth with 1-, 2-, and 4-year follow-up visits to examine subtype differences in developmental trajectories over time.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Exposure(s)<\/jats:title>\n                  <jats:p>Prenatal exposure to GDM.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Main Outcome(s) and Measure(s)<\/jats:title>\n                  <jats:p>The primary outcomes included identification of cortical thickness subtypes and their inferred regional ordering patterns. Secondary outcomes included subtype-specific anthropometric, neurocognitive, psychiatric\/behavioral and neuroimaging measures.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>\n                    The GDM-exposed sample had a mean age of 119.02 \u00b1 7.34 months and was 47.5% female. Two cortical thickness subtypes were identified. Between subtypes, Subtype 1 (63.2%) was characterized by earlier inferred insula involvement and was associated with greater height (\n                    <jats:italic>d<\/jats:italic>\n                    = 0.36,\n                    <jats:italic>p<\/jats:italic>\n                    <jats:sub>\n                      <jats:italic>FDR<\/jats:italic>\n                    <\/jats:sub>\n                    &lt; 0.001) and weight (\n                    <jats:italic>d<\/jats:italic>\n                    = 0.26,\n                    <jats:italic>p<\/jats:italic>\n                    <jats:sub>\n                      <jats:italic>FDR<\/jats:italic>\n                    <\/jats:sub>\n                    = 0.007), whereas Subtype 2 exhibited earlier inferred frontal involvement and nominally higher Attention-Deficit\/Hyperactivity Disorder (ADHD) prevalence (\n                    <jats:italic>d<\/jats:italic>\n                    = 0.08,\n                    <jats:italic>p<\/jats:italic>\n                    = 0.036), steeper longitudinal cortical thinning across all six cortical regions of interest (\u03b2 range: \u22120.05 to \u22120.13, all\n                    <jats:italic>p<\/jats:italic>\n                    <jats:sub>\n                      <jats:italic>FDR<\/jats:italic>\n                    <\/jats:sub>\n                    &lt; 0.05), and a smaller decline in Obsessive-Compulsive Disorder (OCD) prevalence over time (\u03b2 = -1.02,\n                    <jats:italic>p<\/jats:italic>\n                    <jats:sub>\n                      <jats:italic>FDR<\/jats:italic>\n                    <\/jats:sub>\n                    = 0.049).\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusions and Relevance<\/jats:title>\n                  <jats:p>GDM exposure was associated with two distinct offspring cortical thickness subtypes, each showing different inferred regional ordering patterns and clinical associations. One subtype showed an insula-cingulate\u2013predominant pattern associated with anthropometric measures, whereas the other showed a frontal-predominant pattern associated with nominally higher psychiatric measures and faster cortical thinning over time.<\/jats:p>\n                <\/jats:sec>","DOI":"10.64898\/2026.05.25.727436","type":"posted-content","created":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T04:40:18Z","timestamp":1780029618000},"source":"Crossref","is-referenced-by-count":0,"title":["Identification of Heterogeneous Cortical Thickness Patterns Associated with Prenatal Gestational Diabetes Exposure: A SuStaIn-Based Subtyping Study"],"prefix":"10.64898","author":[{"given":"Yumeng","family":"Qi","sequence":"first","affiliation":[{"name":"Department of Bioengineering, University of Texas at Arlington, Arlington, Texas, United 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