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. 2022 Jul 26;12(1):297.
doi: 10.1038/s41398-022-02057-y.

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

Helen Baldwin  1   2 Joaquim Radua  3   4   5 Mathilde Antoniades  6 Shalaila S Haas  6 Sophia Frangou  6   7 Ingrid Agartz  8   9   10   11 Paul Allen  12   13 Ole A Andreassen  11   14 Kimberley Atkinson  15 Peter Bachman  16 Inmaculada Baeza  17 Cali F Bartholomeusz  18   19 Michael W L Chee  20 Tiziano Colibazzi  21   22 Rebecca E Cooper  23 Cheryl M Corcoran  6   24 Vanessa L Cropley  23   25 Bjørn H Ebdrup  26   27 Adriana Fortea  28 Louise Birkedal Glenthøj  29 Holly K Hamilton  30   31 Kristen M Haut  32 Rebecca A Hayes  16 Ying He  33 Karsten Heekeren  34   35 Michael Kaess  36   37 Kiyoto Kasai  38   39   40 Naoyuki Katagiri  41 Minah Kim  42   43 Jochen Kindler  37 Mallory J Klaunig  44 Shinsuke Koike  39   45 Alex Koppel  46 Tina D Kristensen  26   29 Yoo Bin Kwak  47   48 Jun Soo Kwon  42   43 Stephen M Lawrie  15 Irina Lebedeva  49 Jimmy Lee  48   50 Ashleigh Lin  51 Rachel L Loewy  30 Daniel H Mathalon  30   31 Chantal Michel  37 Romina Mizrahi  52   53 Paul Møller  54 Barnaby Nelson  18   19 Takahiro Nemoto  41 Dorte Nordholm  29 Maria A Omelchenko  55 Christos Pantelis  23   56 Jayachandra M Raghava  26   57   58 Jan I Røssberg  14 Wulf Rössler  35   59 Dean F Salisbury  16 Daiki Sasabayashi  60   61 Ulrich Schall  62   63 Lukasz Smigielski  35   64 Gisela Sugranyes  17 Michio Suzuki  60   61 Tsutomu Takahashi  60   61 Christian K Tamnes  8   14   65 Jinsong Tang  66   67 Anastasia Theodoridou  35 Sophia I Thomopoulos  68 Alexander S Tomyshev  49 Peter J Uhlhaas  69   70 Tor G Værnes  14   71 Therese A M J van Amelsvoort  72 Theo G M Van Erp  73   74 James A Waltz  75 Lars T Westlye  11   14   76 Stephen J Wood  18   19   77 Juan H Zhou  20   78 Philip McGuire  13 Paul M Thompson  68 Maria Jalbrzikowski  16   79   80 Dennis Hernaus  72 Paolo Fusar-Poli  3   81   82   83 ENIGMA Clinical High Risk for Psychosis Working Group
Collaborators, Affiliations

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

Helen Baldwin et al. Transl Psychiatry. .

Abstract

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.

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Conflict of interest statement

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.

Figures

Fig. 1
Fig. 1. Forest plot of the variability ratio (VR) of cortical surface area (SA) measures in CHR-P compared with healthy controls.
CHR-P clinical high risk for psychosis, STS superior temporal sulcus, VR variability ratio.
Fig. 2
Fig. 2. Forest plot of the variability ratio (VR) of cortical thickness (CT) measures in CHR-P compared with healthy controls.
CHR-P clinical high risk for psychosis, STS superior temporal sulcus, VR variability ratio.
Fig. 3
Fig. 3. Forest plot of the variability ratio (VR) of subcortical volume (SV) measures in CHR-P compared with healthy controls.
CHR-P clinical high risk for psychosis, VR variability ratio.
Fig. 4
Fig. 4. Violin plots comparing the distribution of PBSI scores between individuals at CHR-P and healthy controls, across surface area (PBSI_SA), cortical thickness (PBSI_CT), and subcortical volume (PBSI_SV); the mid-point indicates the group mean.
PBSI Person-Based Similarity Index, SA surface area, CT cortical thickness, SV subcortical volume. All three phenotypes demonstrate significantly lower similarity in PBSI profiles in the CHR-P group compared with healthy controls, across PBSI_SA (p < 0.01), PBSI_CT (p < 0.01), PBSI_SV (p < 0.01).
Fig. 5
Fig. 5. A bar chart representing the percentage of the CHR-P sample who demonstrate marked deviation from the ‘normative’ neuroanatomical profile.
CHR-P clinical high risk for psychosis, PBSI_SA_Z person-based similarity index surface area z-scores, PBSI_CT_Z person-based similarity index cortical thickness z-scores, PBSI_SV_Z person-based similarity index subcortical volume z-scores.

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