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Structural covariance network topology in individuals at clinical high risk for psychosis: the ENIGMA-CHR Study

Title: Structural covariance network topology in individuals at clinical high risk for psychosis: the ENIGMA-CHR Study
Authors: Liu, S; Agartz, I; Allen, P; Amminger, GP; Andreassen, OA; Bachman, P; Baeza, I; Baldwin, H; Bartholomeusz, CF; Borgwardt, S; Catalano, S; Chen, X; Cho, KIK; Choi, S; Colibazzi, T; Cooper, RE; Corcoran, CM; Cropley, VL; de Haan, L; de la Fuente-Sandoval, C; Dolz, M; Ebdrup, BH; Fortea, A; Fusar-Poli, P; Glenthøj, LB; Glenthøj, BY; Haas, SS; Hamilton, HK; Haut, KM; Hayes, RA; He, Y; Heekeren, K; Hegelstad, WTV; Hooker, CI; Horton, LE; Hubl, D; Hwang, WJ; Kaess, M; Kasai, K; Katagiri, N; Kim, M; Kindler, J; Klaunig, MJ; Koike, S; Kristensen, TD; Kwak, YB; Kwon, JS; Lawrie, SM; Lebedeva, I; Lemmers-Jansen, IL; León-Ortiz, P; Lin, A; Loewy, RL; Ma, X; Mathalon, DH; McGorry, P; McGuire, P; Michel, C; Mizrahi, R; Mizuno, M; Møller, P; Mora-Durán, R; Muñoz-Samons, D; Nelson, B; Nemoto, T; Nordentoft, M; Nordholm, D; Omelchenko, MA; Ouyang, L; Pantelis, C; Pariente, JC; Raghava, JM; Rasser, PE; Resch, F; Reyes-Madrigal, F; Rivera-Chávez, LF; Røssberg, JI; Rössler, W; Salisbury, DF; Sasabayashi, D; Schall, U; Schiffman, J; Schmidt, A; Smigielski, L; Sørensen, ME; Sugranyes, G; Suzuki, M; Takahashi, T; Tamnes, CK; Tang, J; Theodoridou, A; Thomopoulos, SI; Tomyshev, AS; Tor, J; Uhlhaas, PJ; Værnes, TG; van Amelsvoort, TA; Velakoulis, D; Via, E; Vinogradov, S; Waltz, JA; Wenneberg, C; Westlye, LT; Wood, SJ; Yamasue, H; Yuan, L; Yung, AR; Chee, MW; Thompson, PM; Hernaus, D; Jalbrzikowski, M; Lee, J; Zhou, JH; ENIGMA Clinical High Risk for Psychosis Working Group
Publisher Information: Springer Nature [academic journals on nature.com]
Publication Year: 2025
Collection: Oxford University Research Archive (ORA)
Description: Brain network architecture is anticipated to influence future grey matter loss in individuals at Clinical High Risk (CHR) for psychosis. However, existing studies on grey matter structural network properties in CHR are scarce and constrained by small sample sizes. Here, we examined network topology differences comparing a) CHR versus healthy controls (HC); b) CHR who transitioned to psychosis (CHR-T) versus those who did not (CHR-NT); and c) different subsyndromes. We included structural scans from 1842 CHR individuals and 1417 HC individuals from 31 sites within the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium. At the global level, CHR individuals exhibited lower structural covariance (q < 0.001; Cohen's d = 0.164) and less optimal structural network configuration than HC (lower global efficiency and clustering coefficient, d = 0.100,0.087, qs
Document Type: article in journal/newspaper
Language: English
DOI: 10.1038/s41380-025-03304-6
Availability: https://doi.org/10.1038/s41380-025-03304-6; https://ora.ox.ac.uk/objects/uuid:2d0974bc-e8a1-42b7-8f85-559ca4d098b1
Rights: info:eu-repo/semantics/openAccess ; CC Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND)
Accession Number: edsbas.DC6D1022
Database: BASE