<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Parker DA</submitter><funding>U.S. Department of Health &amp; Human Services | NIH | National Institute of Mental Health (NIMH)</funding><funding>NCATS NIH HHS</funding><funding>U.S. Department of Health &amp; Human Services | NIH | National Center for Advancing Translational Sciences (NCATS)</funding><funding>NIMH NIH HHS</funding><pagination>281</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12354876</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>15(1)</volume><pubmed_abstract>Idiopathic psychosis shows considerable biological heterogeneity across cases. The Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) used psychosis-relevant biomarkers to identify psychosis Biotypes, which will aid etiological and targeted treatment investigations. Here, our previous approach (Clementz et al. 2022) is updated, which supports the development of an efficient psychosis Biotype diagnostic procedure called ADEPT. Psychosis probands (n = 1907), their first-degree biological relatives (n = 705), and healthy participants (n = 895) completed a biomarker battery composed of cognitive performance, saccades, and auditory EEG/ERP measurements. EEG and ERP quantifications were modified from previous Biotypes iterations. Multivariate integration using multiple approaches</pubmed_abstract><journal>Translational psychiatry</journal><pubmed_title>Differentiating biomarker features and familial characteristics of B-SNIP psychosis Biotypes.</pubmed_title><pmcid>PMC12354876</pmcid><funding_grant_id>R01 MH078113</funding_grant_id><funding_grant_id>MH127174</funding_grant_id><funding_grant_id>MH077945</funding_grant_id><funding_grant_id>TL1TR002382</funding_grant_id><funding_grant_id>UL1 TR002378</funding_grant_id><funding_grant_id>MH096942</funding_grant_id><funding_grant_id>UL1TR002378</funding_grant_id><funding_grant_id>MH096900</funding_grant_id><funding_grant_id>MH103368</funding_grant_id><funding_grant_id>MH127179</funding_grant_id><funding_grant_id>MH127158</funding_grant_id><funding_grant_id>MH103366</funding_grant_id><funding_grant_id>R01 MH096900</funding_grant_id><funding_grant_id>TL1 TR002382</funding_grant_id><funding_grant_id>MH124813</funding_grant_id><funding_grant_id>R01 MH096942</funding_grant_id><funding_grant_id>R01 MH124813</funding_grant_id><funding_grant_id>MH077851</funding_grant_id><funding_grant_id>R01 MH077945</funding_grant_id><funding_grant_id>MH127162</funding_grant_id><funding_grant_id>R01 MH124807</funding_grant_id><funding_grant_id>R01 MH077851</funding_grant_id><funding_grant_id>R01 MH124806</funding_grant_id><funding_grant_id>R01 MH124803</funding_grant_id><funding_grant_id>R01 MH124804</funding_grant_id><funding_grant_id>R21 MH126398</funding_grant_id><funding_grant_id>R01 MH127162</funding_grant_id><funding_grant_id>MH096913</funding_grant_id><funding_grant_id>MH096957</funding_grant_id><funding_grant_id>MH126398</funding_grant_id><funding_grant_id>R01 MH127158</funding_grant_id><funding_grant_id>R01 MH127179</funding_grant_id><funding_grant_id>MH124803</funding_grant_id><funding_grant_id>R01 MH096913</funding_grant_id><funding_grant_id>R01 MH103368</funding_grant_id><funding_grant_id>MH124802</funding_grant_id><funding_grant_id>R01 MH096957</funding_grant_id><funding_grant_id>MH124804</funding_grant_id><funding_grant_id>MH124807</funding_grant_id><funding_grant_id>MH124806</funding_grant_id><funding_grant_id>R01 MH127174</funding_grant_id><funding_grant_id>MH078113</funding_grant_id><funding_grant_id>R01 MH124802</funding_grant_id><funding_grant_id>R01 MH103366</funding_grant_id><pubmed_authors>Pearlson GD</pubmed_authors><pubmed_authors>Clementz BA</pubmed_authors><pubmed_authors>Keshavan MS</pubmed_authors><pubmed_authors>Hill SK</pubmed_authors><pubmed_authors>Keedy SK</pubmed_authors><pubmed_authors>Ivleva EI</pubmed_authors><pubmed_authors>McDowell JE</pubmed_authors><pubmed_authors>Tamminga CA</pubmed_authors><pubmed_authors>Trotti RL</pubmed_authors><pubmed_authors>Gershon ES</pubmed_authors><pubmed_authors>Huang LY</pubmed_authors><pubmed_authors>Parker DA</pubmed_authors><pubmed_authors>Sauer K</pubmed_authors><pubmed_authors>Sweeney JA</pubmed_authors></additional><is_claimable>false</is_claimable><name>Differentiating biomarker features and familial characteristics of B-SNIP psychosis Biotypes.</name><description>Idiopathic psychosis shows considerable biological heterogeneity across cases. The Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) used psychosis-relevant biomarkers to identify psychosis Biotypes, which will aid etiological and targeted treatment investigations. Here, our previous approach (Clementz et al. 2022) is updated, which supports the development of an efficient psychosis Biotype diagnostic procedure called ADEPT. Psychosis probands (n = 1907), their first-degree biological relatives (n = 705), and healthy participants (n = 895) completed a biomarker battery composed of cognitive performance, saccades, and auditory EEG/ERP measurements. EEG and ERP quantifications were modified from previous Biotypes iterations. Multivariate integration using multiple approaches</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Aug</publication><modification>2026-04-16T15:08:57.891Z</modification><creation>2026-04-07T14:12:22.702Z</creation></dates><accession>S-EPMC12354876</accession><cross_references><pubmed>40813865</pubmed><doi>10.1038/s41398-025-03501-5</doi></cross_references></HashMap>