{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T23:29:04Z","timestamp":1785281344703,"version":"3.55.0"},"reference-count":55,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,1,12]],"date-time":"2025-01-12T00:00:00Z","timestamp":1736640000000},"content-version":"vor","delay-in-days":11,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Diabetes Metabolism Res"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>To synthesise the evidence from clinical trials and observational studies using omics techniques to investigate the impact of diet and lifestyle factors on metabolite profile in pregnancy, and in the prevention and management of gestational diabetes mellitus (GDM).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods<\/jats:title>\n                    <jats:p>A systematic literature search was performed using PubMed, Ovid, CINAHL, and Web of Science databases in October 2023 and updated in September 2024. Inclusion criteria were randomised controlled trials (RCT) or non\u2010RCTs in pregnant women with or without GDM, that measured diet and lifestyle factors, and which applied post\u2010transcriptional omics approaches. Risk of bias was assessed using the ROBINS\u2010I for non\u2010RCTs and ROB\u20102 tool for RCTs. The results of all studies are narratively synthesised.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Of 6293 studies identified, eight observational studies and three RCTs comprising 2639 pregnant women were included. Three studies reported on changes in diet\u2010related metabolic phenotypes during pregnancy; however, the impact of certain foods on the metabolome and risk for GDM was less clear. Compared with women without GDM, women with GDM had a worse deterioration in metabolites, including saturated fatty acids, branched chain amino acids and purine degradation metabolites. There is limited evidence that conventional dietary treatment for GDM may modify the metabolome in women with GDM.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Metabolome profiles in pregnancy may be altered by certain dietary choices; however, it is inconclusive whether improved diet related metabolite profiles have a beneficial impact in the prevention or management of GDM. High quality studies with larger sample sizes are needed to better understand the role that maternal nutrition plays in modulating the maternal metabolome, not only for a healthy pregnancy but also for the prevention and management of GDM.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/dmrr.70026","type":"journal-article","created":{"date-parts":[[2025,1,12]],"date-time":"2025-01-12T23:24:52Z","timestamp":1736724292000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["The Use of Omics in Untangling the Effect of Lifestyle Factors in Pregnancy and Gestational Diabetes: A Systematic Review"],"prefix":"10.1002","volume":"41","author":[{"given":"Kai","family":"Liu","sequence":"first","affiliation":[{"name":"Faculty of Health and Medical Sciences Adelaide Medical School The University of Adelaide  Adelaide Australia"},{"name":"Robinson Research Institute The University of Adelaide  Adelaide 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