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Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC

Title: Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC
Authors: Rootes-Murdy, K; Panta, S; Kelly, R; Romero, J; Quidé, Y; Cairns, MJ; Loughland, C; Carr, VJ; Catts, SV; Jablensky, A; Green, MJ; Henskens, F; Kiltschewskij, D; Michie, PT; Mowry, B; Pantelis, C; Rasser, PE; Reay, WR; Schall, U; Scott, RJ; Watkeys, OJ; Roberts, G; Mitchell, PB; Fullerton, JM; Overs, BJ; Kikuchi, M; Hashimoto, R; Matsumoto, J; Fukunaga, M; Sachdev, PS; Brodaty, H; Wen, W; Jiang, J; Fani, N; Ely, TD; Lorio, A; Stevens, JS; Ressler, K; Jovanovic, T; van Rooij, SJH; Federmann, LM; Jockwitz, C; Teumer, A; Forstner, AJ; Caspers, S; Cichon, S; Plis, SM; Sarwate, AD; Calhoun, VD; Quide, Yann
Source: urn:ISSN:2666-3899 ; Patterns, 5, 7, 100987-100987
Publisher Information: Elsevier
Publication Year: 2024
Collection: UNSW Sydney (The University of New South Wales): UNSWorks
Subject Terms: 46 Information and Computing Sciences; 4905 Statistics; 49 Mathematical Sciences; 4603 Computer Vision and Multimedia Computation; 4611 Machine Learning; Serious Mental Illness; Depression; Mental Illness; Mental Health; Brain Disorders; Autism; Neurosciences; Schizophrenia; Intellectual and Developmental Disabilities (IDD); 2.1 Biological and endogenous factors; 3 Good Health and Well Being; COINSTAC; PTSD; decentralized; federated analysis; gray matter; mild cognitive impairment; mood disorders; psychiatric disorders; regression; transdiagnostic; anzsrc-for: 46 Information and Computing Sciences; anzsrc-for: 4905 Statistics; anzsrc-for: 49 Mathematical Sciences; anzsrc-for: 4603 Computer Vision and Multimedia Computation
Description: Structural neuroimaging studies have identified a combination of shared and disorder-specific patterns of gray matter (GM) deficits across psychiatric disorders. Pooling large data allows for examination of a possible common neuroanatomical basis that may identify a certain vulnerability for mental illness. Large-scale collaborative research is already facilitated by data repositories, institutionally supported databases, and data archives. However, these data-sharing methodologies can suffer from significant barriers. Federated approaches augment these approaches by enabling access or more sophisticated, shareable and scaled-up analyses of large-scale data. We examined GM alterations using Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation, an open-source, decentralized analysis application. Through federated analysis of eight sites, we identified significant overlap in the GM patterns (n = 4,102) of individuals with schizophrenia, major depressive disorder, and autism spectrum disorder. These results show cortical and subcortical regions that may indicate a shared vulnerability to psychiatric disorders.
Document Type: article in journal/newspaper
File Description: application/pdf
Language: unknown
Relation: https://hdl.handle.net/1959.4/102077; https://doi.org/10.1016/j.patter.2024.100987
DOI: 10.1016/j.patter.2024.100987
Availability: https://hdl.handle.net/1959.4/102077; https://unsworks.unsw.edu.au/bitstreams/8a982c6a-e4b9-4cfa-af37-83ca9e06ea4b/download; https://doi.org/10.1016/j.patter.2024.100987
Rights: open access ; https://purl.org/coar/access_right/c_abf2 ; CC-BY-NC-ND ; https://creativecommons.org/licenses/by-nc-nd/4.0/ ; CC BY-NC-ND ; free_to_read
Accession Number: edsbas.F91F8B4C
Database: BASE