{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T09:21:46Z","timestamp":1771924906750,"version":"3.50.1"},"reference-count":53,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T00:00:00Z","timestamp":1769558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>\n                      Maternal obesity (pregravid body mass index &amp;gt;30 kg\/m\n                      <jats:sup>2<\/jats:sup>\n                      ), which has reached epidemic levels in the US, increases the incidence of cardiovascular disease and all cause premature death in the offspring. The placenta modulates fetal access to lipids and other nutrients and is considered a key player in fetal growth and maturation. However, the complex interplay between dysregulated metabolism in mothers with obesity and placental pathways mediating impacts on fetal development that predispose offspring to morbidities later in life, is poorly understood.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We used unbiased\n                      <jats:italic>Whole Genome Correlation Network Analysis<\/jats:italic>\n                      (WGCNA) in 39 full-term unlabored placentas from mothers affected by obesity to explore relationships between coding and non-coding placental transcripts with maternal and fetal metabolic variables.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      We identified positive correlations between members of the Rho network, a key inflammation regulator, with maternal leptin and cord blood free fatty acids (cbFFA). Furthermore, we identified negative correlations between epigenetic regulators and the lipid metabolism drivers\n                      <jats:italic>SMUG1<\/jats:italic>\n                      and\n                      <jats:italic>CDS1<\/jats:italic>\n                      , with cbFFA. A set of placental miRNAs showed positive correlations with cbFFA. Using mirTarRnaSeq, an R\/Bioconductor package, we predicted interactions between placental coding genes and miRNA, which correlated negatively and positively with cbFFA, respectively. Several FFA-associated miRNAs (miR-23b cluster, -168, -138, -6825, -6845) have been previously associated with obesity in animal models and human cohorts.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>Further studies are required to investigate the role that the Rho network plays in placental inflammation and the link between miRNAs and the predisposition towards cardiovascular diseases in the offspring of obese mothers.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2025.1736033","type":"journal-article","created":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T05:21:57Z","timestamp":1769577717000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Placental mRNA and miRNA dynamics associated with lipid metabolism pathways in pregnancies affected by obesity"],"prefix":"10.3389","volume":"16","author":[{"given":"Ruggero","family":"Spadafora","sequence":"first","affiliation":[{"name":"Woman, Mother + Baby Research Institute, Tufts Medical Center","place":["Boston, MA, United States"]},{"name":"Department of Pediatrics, Division of Neonatology Tufts Medical Center","place":["Boston, MA, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiayi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Data Analytics, Tufts University","place":["Boston, MA, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"N. 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