Neuroanatomical heterogeneity and homogeneity in individuals at clinical high risk for psychosis

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  • Helen Baldwin
  • Joaquim Radua
  • Mathilde Antoniades
  • Shalaila S. Haas
  • Sophia Frangou
  • Ingrid Agartz
  • Paul Allen
  • Ole A. Andreassen
  • Kimberley Atkinson
  • Peter Bachman
  • Inmaculada Baeza
  • Cali F. Bartholomeusz
  • Michael W.L. Chee
  • Tiziano Colibazzi
  • Rebecca E. Cooper
  • Cheryl M. Corcoran
  • Vanessa L. Cropley
  • Ebdrup, Bjørn
  • Adriana Fortea
  • Glenthøj, Louise Birkedal
  • Holly K. Hamilton
  • Kristen M. Haut
  • Rebecca A. Hayes
  • Ying He
  • Karsten Heekeren
  • Michael Kaess
  • Kiyoto Kasai
  • Naoyuki Katagiri
  • Minah Kim
  • Jochen Kindler
  • Mallory J. Klaunig
  • Shinsuke Koike
  • Alex Koppel
  • Tina D. Kristensen
  • Yoo Bin Kwak
  • Jun Soo Kwon
  • Stephen M. Lawrie
  • Irina Lebedeva
  • Jimmy Lee
  • Ashleigh Lin
  • Rachel L. Loewy
  • Daniel H. Mathalon
  • Chantal Michel
  • Romina Mizrahi
  • Nordholm, Dorte
  • Christos Pantelis
  • Glenthøj, Birte Yding
  • Nordentoft, Merete
  • Mikkel E. Sørensen
  • Christina Wenneberg
  • the ENIGMA Clinical High Risk for Psychosis Working Group

Individuals at Clinical High Risk for Psychosis (CHR-P) demonstrate heterogeneity in clinical profiles and outcome features. However, the extent of neuroanatomical heterogeneity in the CHR-P state is largely undetermined. We aimed to quantify the neuroanatomical heterogeneity in structural magnetic resonance imaging measures of cortical surface area (SA), cortical thickness (CT), subcortical volume (SV), and intracranial volume (ICV) in CHR-P individuals compared with healthy controls (HC), and in relation to subsequent transition to a first episode of psychosis. The ENIGMA CHR-P consortium applied a harmonised analysis to neuroimaging data across 29 international sites, including 1579 CHR-P individuals and 1243 HC, offering the largest pooled CHR-P neuroimaging dataset to date. Regional heterogeneity was indexed with the Variability Ratio (VR) and Coefficient of Variation (CV) ratio applied at the group level. Personalised estimates of heterogeneity of SA, CT and SV brain profiles were indexed with the novel Person-Based Similarity Index (PBSI), with two complementary applications. First, to assess the extent of within-diagnosis similarity or divergence of neuroanatomical profiles between individuals. Second, using a normative modelling approach, to assess the ‘normativeness’ of neuroanatomical profiles in individuals at CHR-P. CHR-P individuals demonstrated no greater regional heterogeneity after applying FDR corrections. However, PBSI scores indicated significantly greater neuroanatomical divergence in global SA, CT and SV profiles in CHR-P individuals compared with HC. Normative PBSI analysis identified 11 CHR-P individuals (0.70%) with marked deviation (>1.5 SD) in SA, 118 (7.47%) in CT and 161 (10.20%) in SV. Psychosis transition was not significantly associated with any measure of heterogeneity. Overall, our examination of neuroanatomical heterogeneity within the CHR-P state indicated greater divergence in neuroanatomical profiles at an individual level, irrespective of psychosis conversion. Further large-scale investigations are required of those who demonstrate marked deviation.

OriginalsprogEngelsk
Artikelnummer297
TidsskriftTranslational Psychiatry
Vol/bind12
Udgave nummer1
ISSN2158-3188
DOI
StatusUdgivet - 2022

Bibliografisk note

Funding Information:
HB is funded by a National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre doctoral studentship. SF is supported by the National Institute of Mental Health under grant R01MH113619. CMC is supported by R01MH107558 and R01MH115332. BN is supported by a National Health and Medical Research Council (NHMRC) Senior Research Fellowship (1137687). AL is supported by a National Health and Medical Research Council (NHMRC) Senior Research Fellowship (#1148793). CKT is supported by the Research Council of Norway (223273, 288083, 323951) and the South-Eastern Norway Regional Health Authority (2019069, 2021070, 500189). PMT is supported by NIH grants R01MH116147, P41EB015922, and R01AG058854. VC is supported by a National Health and Medical Research Council (NHMRC) Investigator Grant (1177370). LTW is supported by the European Research Council under the European Union’s Horizon 2020 research and Innovation program (ERC StG, Grant 802998). GS is supported by the Fundació Clínic Recerca Biomèdica, the Brain and Behavior Research Foundation (NARSAD Young Investigator Award 2017, grant ID: 26731), the Alicia Koplowitz Foundation and the Spanish Ministry of Health, Instituto de Salud Carlos III “Health Research Fund” (PI15/0444; PI18/0242; PI18/00976). CF-S was supported by grants 182279 and 261895 from the Consejo Nacional de Ciencia y Tecnología, grants from CONACYT’s Sistema Nacional de Investigadores, and grant R21 MH117434 from the National Institutes of Health. CP was supported by a National Health and Medical Research Council (NHMRC) Senior Principal Research Fellowship (1105825), an NHMRC L3 Investigator Grant (1196508), and NHMRC Program Grant (ID: 1150083). Core funding for ENIGMA was provided by the NIH Big Data to Knowledge (BD2K) program under consortium grant U54 EB020403 to PMT.

Funding Information:
PMT receives partial research support from Biogen, Inc., for research unrelated to this manuscript. OAA is a consultant to HealthLytix. CP has received honoraria for talks at educational meetings and has served on an advisory board for Lundbeck, Australia Pty Ltd. BHE has received lecture fees Otsuka Pharma Scandinavia AB, Boehringer Ingelheim, and Lundbeck Pharma A/S.

Publisher Copyright:
© 2022, The Author(s).

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