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

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

Haas, Shalaila S;Ge, Ruiyang;Agartz, Ingrid;Amminger, G Paul;Andreassen, Ole A;Bachman, Peter;Baeza, Inmaculada;Choi, Sunah;Colibazzi, Tiziano;Cropley, Vanessa L;de la Fuente-Sandoval, Camilo;Ebdrup, Bjørn H;Fortea, Adriana;Fusar-Poli, Paolo;Glenthøj, Birte Yding;Glenthøj, Louise Birkedal;Haut, Kristen M;Hayes, Rebecca A;Heekeren, Karsten;Hooker, Christine I;Hwang, Wu Jeong;Jahanshad, Neda;Kaess, Michael;Kasai, Kiyoto;Katagiri, Naoyuki;Kim, Minah;Kindler, Jochen;Koike, Shinsuke;Kristensen, Tina D;Kwon, Jun Soo;Lawrie, Stephen M;Lee, Jimmy;Lemmers-Jansen, Imke Lj;Lin, Ashleigh;Ma, Xiaoqian;Mathalon, Daniel H;McGuire, Philip;Michel, Chantal;Mizrahi, Romina;Mizuno, Masafumi;Møller, Paul;Mora-Durán, Ricardo;Nelson, Barnaby;Nemoto, Takahiro;Nordentoft, Merete;Nordholm, Dorte;Omelchenko, Maria A;Pantelis, Christos;Pariente, Jose C;Raghava, Jayachandra M;Reyes-Madrigal, Francisco;Røssberg, Jan I;Rössler, Wulf;Salisbury, Dean F;Sasabayashi, Daiki;Schall, Ulrich;Smigielski, Lukasz;Sugranyes, Gisela;Suzuki, Michio;Takahashi, Tsutomu;Tamnes, Christian K;Theodoridou, Anastasia;Thomopoulos, Sophia I;Thompson, Paul M;Tomyshev, Alexander S;Uhlhaas, Peter J;Værnes, Tor G;van Amelsvoort, Therese Amj;van Erp, Theo Gm;Waltz, James A;Wenneberg, Christina;Westlye, Lars T;Wood, Stephen J;Zhou, Juan H;Hernaus, Dennis;Jalbrzikowski, Maria;Kahn, René S;Corcoran, Cheryl M;Frangou, Sophia;, ;
bioRxiv : the preprint server for biology 2023
88
haas2023normativebiorxiv

Abstract

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.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.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.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.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 ADS showed significant but weak associations (|β|<0.09; P <0.05) with positive symptoms and IQ.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. Is the risk of psychosis associated with brain morphometric changes that deviate significantly from healthy variation? In this study of 1340 individuals high-risk for psychosis (CHR-P) and 1237 healthy participants, individual-level variation in macroscale neuromorphometric measures of the CHR-P group was largely nested within healthy variation and was not associated with the severity of positive psychotic symptoms or conversion to a psychotic disorder. The findings suggest the macroscale neuromorphometric measures have limited utility as diagnostic biomarkers of psychosis risk.

Citation

ID: 277120
Ref Key: haas2023normativebiorxiv
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
277120
Unique Identifier:
2023.01.17.523348
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet