{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["13"],"submitter":["Du R"],"pubmed_abstract":["<h4>Objective</h4>The objective of this study was to reveal the potential crosstalk between immune infiltration and N<sup>6</sup>- methyladenosine (m<sup>6</sup>A) modification in the placentas of patients with gestational diabetes mellitus (GDM), and to construct a model for the diagnosis of GDM.<h4>Methods</h4>We analyzed imbalanced immune infiltration and differentially expressed m<sup>6</sup>A-related genes (DMRGs) in the placentas of patients with GDM, based on the GSE70493 dataset. An immune-related DMRG signature, with significant classifying power and diagnostic value, was identified using a least absolute shrinkage and selection operator (LASSO) regression. Based on the selected DMRGs, we developed and validated a nomogram model using GSE70493 and GSE92772 as the training and vali"],"journal":["Frontiers in endocrinology"],"pagination":["853857"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8971567"],"repository":["biostudies-literature"],"pubmed_title":["N6-Methyladenosine-Related Gene Signature Associated With Monocyte Infiltration Is Clinically Significant in Gestational Diabetes Mellitus."],"pmcid":["PMC8971567"],"pubmed_authors":["Du R","Wang Y","Li L"],"additional_accession":[]},"is_claimable":false,"name":"N6-Methyladenosine-Related Gene Signature Associated With Monocyte Infiltration Is Clinically Significant in Gestational Diabetes Mellitus.","description":"<h4>Objective</h4>The objective of this study was to reveal the potential crosstalk between immune infiltration and N<sup>6</sup>- methyladenosine (m<sup>6</sup>A) modification in the placentas of patients with gestational diabetes mellitus (GDM), and to construct a model for the diagnosis of GDM.<h4>Methods</h4>We analyzed imbalanced immune infiltration and differentially expressed m<sup>6</sup>A-related genes (DMRGs) in the placentas of patients with GDM, based on the GSE70493 dataset. An immune-related DMRG signature, with significant classifying power and diagnostic value, was identified using a least absolute shrinkage and selection operator (LASSO) regression. Based on the selected DMRGs, we developed and validated a nomogram model using GSE70493 and GSE92772 as the training and vali","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022","modification":"2025-04-19T12:55:59.605Z","creation":"2025-04-19T12:55:59.605Z"},"accession":"S-EPMC8971567","cross_references":{"pubmed":["35370940"],"doi":["10.3389/fendo.2022.853857"]}}