Alterations in Human Milk Adiponectin, Leptin, Resistin, and microRNAs in Mothers With Gestational Diabetes Mellitus Compared With Healthy Controls: A Systematic Review and Network-Based Analysis.

Gestational diabetes mellitus (GDM) is linked to poor infant metabolic outcomes, potentially via altered human milk (HM) hormones and microRNAs. Since their specific roles remain unclear, this study synthesizes current evidence on HM adipose tissue-derived hormones (particularly adiponectin, leptin, and resistin) and microRNA modifications during gestational diabetes. Firstly, a systematic review following PRISMA 2020 guidelines was conducted (PROSPERO: CRD42024612813). Searches in major databases identified studies comparing HM adiponectin, leptin, or resistin concentrations and/or miRNA profiles between GDM and normoglycemic mothers. Secondly, bioinformatics analysis using miRWalk 3.0, functional enrichment, and network topology mapping examined miRNA interactions with ADIPOQ, LEP, and RETN genes. Twelve studies were included. Adiponectin showed the most consistent GDM-associated reductions, though findings were context-dependent. Leptin was primarily associated with maternal adiposity rather than GDM status. Resistin evidence was insufficient. Three miRNA studies revealed stage-dependent dysregulation in GDM, with miR-148a, miR-30b, let-7a, and let-7d linked to infant growth outcomes during the first 6 months. Bioinformatics identified miR-148a-5p and miR-30b-3p as targeting all three adipokine genes, with enrichment in glucose homeostasis and insulin resistance pathways. Network analysis highlighted TCF7L2, INSR, GCK, and HNF1A as central nodes. GDM is associated with selective alterations in HM adipokines and miRNAs, with adiponectin and specific miRNAs showing the strongest signals. These findings support a conceptual model where GDM shapes HM's molecular composition through interacting endocrine and posttranscriptional mechanisms, potentially influencing infant metabolic programming. Larger longitudinal studies are needed to validate these observations and determine clinical relevance.