{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["14(1)"],"submitter":["Karaglani M"],"pubmed_abstract":["Schizophrenia (SCZ) is a chronic, severe, and complex psychiatric disorder that affects all aspects of personal functioning. While SCZ has a very strong biological component, there are still no objective diagnostic tests. Lately, special attention has been given to epigenetic biomarkers in SCZ. In this study, we introduce a three-step, automated machine learning (AutoML)-based, data-driven, biomarker discovery pipeline approach, using genome-wide DNA methylation datasets and laboratory validation, to deliver a highly performing, blood-based epigenetic biosignature of diagnostic clinical value in SCZ. Publicly available blood methylomes from SCZ patients and healthy individuals were analyzed via AutoML, to identify SCZ-specific biomarkers. The methylation of the identified genes was then an"],"journal":["Translational psychiatry"],"pagination":["257"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11183091"],"repository":["biostudies-literature"],"pubmed_title":["A novel blood-based epigenetic biosignature in first-episode schizophrenia patients through automated machine learning."],"pmcid":["PMC11183091"],"pubmed_authors":["Chatzaki E","Theodosiou T","Bozikas VP","Karaglani M","Panagopoulou M","Bitsios P","Tzitzikou K","Agorastos A","Parlapani E","Athanasis P","Iliopoulos I"],"additional_accession":[]},"is_claimable":false,"name":"A novel blood-based epigenetic biosignature in first-episode schizophrenia patients through automated machine learning.","description":"Schizophrenia (SCZ) is a chronic, severe, and complex psychiatric disorder that affects all aspects of personal functioning. While SCZ has a very strong biological component, there are still no objective diagnostic tests. Lately, special attention has been given to epigenetic biomarkers in SCZ. In this study, we introduce a three-step, automated machine learning (AutoML)-based, data-driven, biomarker discovery pipeline approach, using genome-wide DNA methylation datasets and laboratory validation, to deliver a highly performing, blood-based epigenetic biosignature of diagnostic clinical value in SCZ. Publicly available blood methylomes from SCZ patients and healthy individuals were analyzed via AutoML, to identify SCZ-specific biomarkers. The methylation of the identified genes was then an","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Jun","modification":"2026-07-15T10:27:02.426Z","creation":"2026-07-04T03:12:19.372Z"},"accession":"S-EPMC11183091","cross_references":{"pubmed":["38886359"],"doi":["10.1038/s41398-024-02946-4"]}}