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[Preprint]. 2023 Jan 18:2023.01.17.523348.
doi: 10.1101/2023.01.17.523348.

Normative modeling of brain morphometry in Clinical High-Risk for Psychosis

Shalaila S Haas  1 Ruiyang Ge  2   3 Ingrid Agartz  4   5   6   7 G Paul Amminger  8   9 Ole A Andreassen  10   6 Peter Bachman  11 Inmaculada Baeza  12 Sunah Choi  13 Tiziano Colibazzi  14   15 Vanessa L Cropley  16 Camilo de la Fuente-Sandoval  17 Bjørn H Ebdrup  18   19 Adriana Fortea  20 Paolo Fusar-Poli  21   22 Birte Yding Glenthøj  18   19 Louise Birkedal Glenthøj  23 Kristen M Haut  24 Rebecca A Hayes  11 Karsten Heekeren  25   26 Christine I Hooker  24 Wu Jeong Hwang  13   27 Neda Jahanshad  28 Michael Kaess  29   30 Kiyoto Kasai  31   32   33 Naoyuki Katagiri  34 Minah Kim  35   36 Jochen Kindler  30 Shinsuke Koike  37   32 Tina D Kristensen  38 Jun Soo Kwon  35   36 Stephen M Lawrie  39 Jimmy Lee  40   41 Imke Lj Lemmers-Jansen  42   43 Ashleigh Lin  44 Xiaoqian Ma  45 Daniel H Mathalon  46   47 Philip McGuire  48 Chantal Michel  30 Romina Mizrahi  49   50 Masafumi Mizuno  51 Paul Møller  52 Ricardo Mora-Durán  53 Barnaby Nelson  8   9 Takahiro Nemoto  34 Merete Nordentoft  23 Dorte Nordholm  23 Maria A Omelchenko  54 Christos Pantelis  55   56 Jose C Pariente  57 Jayachandra M Raghava  18   58 Francisco Reyes-Madrigal  17 Jan I Røssberg  59 Wulf Rössler  60   61 Dean F Salisbury  62 Daiki Sasabayashi  63   64 Ulrich Schall  65   66 Lukasz Smigielski  67   26 Gisela Sugranyes  12 Michio Suzuki  63   64 Tsutomu Takahashi  63   64 Christian K Tamnes  4   7   68 Anastasia Theodoridou  26 Sophia I Thomopoulos  28 Paul M Thompson  28 Alexander S Tomyshev  69 Peter J Uhlhaas  70   71 Tor G Værnes  72   7 Therese Amj van Amelsvoort  73 Theo Gm van Erp  74   75 James A Waltz  76 Christina Wenneberg  23 Lars T Westlye  77   7   6 Stephen J Wood  8   9   78 Juan H Zhou  79   80 Dennis Hernaus  73 Maria Jalbrzikowski  11   81 René S Kahn  1 Cheryl M Corcoran  1   82 Sophia Frangou  1   2   3 ENIGMA Clinical High Risk for Psychosis Working Group
Affiliations

Normative modeling of brain morphometry in Clinical High-Risk for Psychosis

Shalaila S Haas et al. bioRxiv. .

Update in

  • Normative Modeling of Brain Morphometry in Clinical High Risk for Psychosis.
    ENIGMA Clinical High Risk for Psychosis Working Group; Haas SS, Ge R, Agartz I, Amminger GP, Andreassen OA, Bachman P, Baeza I, Choi S, Colibazzi T, Cropley VL, de la Fuente-Sandoval C, Ebdrup BH, Fortea A, Fusar-Poli P, Glenthøj BY, Glenthøj LB, Haut KM, Hayes RA, Heekeren K, Hooker CI, Hwang WJ, Jahanshad N, Kaess M, Kasai K, Katagiri N, Kim M, Kindler J, Koike S, Kristensen TD, Kwon JS, Lawrie SM, Lebedeva I, Lee J, Lemmers-Jansen ILJ, Lin A, Ma X, Mathalon DH, McGuire P, Michel C, Mizrahi R, Mizuno M, Møller P, Mora-Durán R, Nelson B, Nemoto T, Nordentoft M, Nordholm D, Omelchenko MA, Pantelis C, Pariente JC, Raghava JM, Reyes-Madrigal F, Røssberg JI, Rössler W, Salisbury DF, Sasabayashi D, Schall U, Smigielski L, Sugranyes G, Suzuki M, Takahashi T, Tamnes CK, Theodoridou A, Thomopoulos SI, Thompson PM, Tomyshev AS, Uhlhaas PJ, Værnes TG, van Amelsvoort TAMJ, van Erp TGM, Waltz JA, Wenneberg C, Westlye LT, Wood SJ, Zhou JH, Hernaus D, Jalbrzikowski M, Kahn RS, Corcoran CM, Frangou S. ENIGMA Clinical High Risk for Psychosis Working Group, et al. JAMA Psychiatry. 2024 Jan 1;81(1):77-88. doi: 10.1001/jamapsychiatry.2023.3850. JAMA Psychiatry. 2024. PMID: 37819650 Free PMC article.

Abstract

Importance: The lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in the majority of individuals at psychosis risk may be nested within the range observed in healthy individuals.

Objective: To quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high-risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder.

Design setting and participants: Clinical, IQ and FreeSurfer-derived regional measures of cortical thickness (CT), cortical surface area (SA), and subcortical volume (SV) from 1,340 CHR-P individuals [47.09% female; mean age: 20.75 (4.74) years] and 1,237 healthy individuals [44.70% female; mean age: 22.32 (4.95) years] from 29 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group.

Main outcomes and measures: For each regional morphometric measure, z-scores were computed that index the degree of deviation from the normative means of that measure in a healthy reference population (N=37,407). Average deviation scores (ADS) for CT, SA, SV, and globally across all measures (G) were generated by averaging the respective regional z-scores. Regression analyses were used to quantify the association of deviation scores with clinical severity and cognition and two-proportion z-tests to identify case-control differences in the proportion of individuals with infranormal (z<-1.96) or supranormal (z>1.96) scores.

Results: CHR-P and healthy individuals overlapped in the distributions of the observed values, regional z-scores, and all ADS vales. The proportion of CHR-P individuals with infranormal or supranormal values in any metric was low (<12%) and similar to that of healthy individuals. CHR-P individuals who converted to psychosis compared to those who did not convert had a higher percentage of infranormal values in temporal regions (5-7% vs 0.9-1.4%). In the CHR-P group, only the ADSSA showed significant but weak associations (|β|<0.09; PFDR<0.05) with positive symptoms and IQ.

Conclusions and relevance: The study findings challenge the usefulness of macroscale neuromorphometric measures as diagnostic biomarkers of psychosis risk and suggest that such measures do not provide an adequate explanation for psychosis risk.

Keywords: FreeSurfer; IQ; MRI; clinical high-risk; normative modeling; positive symptoms.

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Figures

Figure 1.
Figure 1.. Distribution of hippocampal subcortical volume normative z-scores in the study sample.
The figure presents the distribution of the left and right hippocampus regional normative z-scores in healthy individuals (HI), individuals at clinical high-risk for psychosis (CHR-P) and CHR-P that converted to full-blown psychosis (CHR-PC). The results for the remaining regional normative z-score are presented in the eVideo. The dotted lines represent the cutoffs for infranormal and supranormal values at z = |1.96|.
Figure 2.
Figure 2.. Percentage of subjects with infra- or supranormal regional normative z-scores.
The proportion of healthy individuals, clinical high-risk for psychosis (CHR-P), and cinical high-risk for psychosis converters with infranormal (left) and supranormal deviations (right) are presented for each hemisphere for cortical thickness, cortical surface area, and subcortical volume.
Figure 3.
Figure 3.. Distribution of the total number of regions with infra- or supranormal regional normative z-scores.
Bar plots show the distribution of the total number of regions per individual with infra-normal (top row) and supra-normal (bottom row) deviations from the normative model for A) cortical thickness, B) cortical surface area, and C) subcortical volume separately in healthy individuals, clinical high-risk for psychosis (CHR-P) individuals, and clinical high-risk for psychosis converters (CHR-PC).
Figure 4.
Figure 4.. Distributions of average deviation scores and percentage of subjects with infra- or supranormal regional normative z-scores.
A) Percentage of healthy, clinical high-risk for psychosis (CHR-P), and clinical high-risk for psychosis converters (CHR-PC) with supra- or infranormal global average deviation score (ADSG), the average deviation score for cortical thickness (ADSCT), average deviation score for cortical surface area (ADSSA), and average deviation score for subcortical volumes (ADSSV). B) The distributions of the average deviation scores in CHR-P (magenta color), CHR-PC (purple color), and healthy individuals (yellow color) for ADSG, ADSCT, ADSSA, and ADSSV. The dotted lines represent the cutoffs for infranormal and supranormal values at z = |1.96|.

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