PMID- 30528960
OWN - NLM
STAT- MEDLINE
DCOM- 20191211
LR  - 20210116
IS  - 2213-1582 (Electronic)
IS  - 2213-1582 (Linking)
VI  - 21
DP  - 2019
TI  - Neurocognitive and neuroanatomical maturation in the clinical high-risk states 
      for psychosis: A pattern recognition study.
PG  - 101624
LID - S2213-1582(18)30372-3 [pii]
LID - 10.1016/j.nicl.2018.101624 [doi]
LID - 101624
AB  - BACKGROUND: Findings from neurodevelopmental studies indicate that adolescents 
      with psychosis spectrum disorders have delayed neurocognitive performance 
      relative to the maturational state of their healthy peers. Using machine 
      learning, we generated a model of neurocognitive age in healthy adults and 
      investigated whether individuals in clinical high risk (CHR) for psychosis showed 
      systematic neurocognitive age deviations that were accompanied by specific 
      structural brain alterations. METHODS: First, a Support Vector Regression-based 
      age prediction model was trained and cross-validated on the neurocognitive data 
      of 36 healthy controls (HC). This produced Cognitive Age Gap Estimates (CogAGE) 
      that measured each participant's deviation from the normal cognitive maturation 
      as the difference between estimated neurocognitive and chronological age. Second, 
      we employed voxel-based morphometry to explore the neuroanatomical gray and white 
      matter correlates of CogAGE in HC, in CHR individuals with early (CHR-E) and late 
      (CHR-L) high risk states. RESULTS: The age prediction model estimated age in HC 
      subjects with a mean absolute error of +/-2.2 years (SD = 3.3; R(2) = 0.33, 
      P < .001). Mean (SD) CogAGE measured +4.3 (8.1) years in CHR individuals compared 
      to HC (-0.1 (5.5) years, P = .006). CHR-L individuals differed significantly from 
      HC subjects while this was not the case for the CHR-E group. CogAGE was 
      associated with a distributed bilateral pattern of increased GM volume in the 
      temporal and frontal areas and diffuse pattern of WM reductions. CONCLUSION: 
      Although the generalizability of our findings might be limited due to the 
      relatively small number of participants, CHR individuals exhibit a disturbed 
      neurocognitive development as compared to healthy peers, which may be independent 
      of conversion to psychosis and paralleled by an altered structural maturation 
      process.
CI  - Copyright (c) 2018 The Authors. Published by Elsevier Inc. All rights reserved.
FAU - Kambeitz-Ilankovic, Lana
AU  - Kambeitz-Ilankovic L
AD  - Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, 
      Germany. Electronic address: lana.kambeitz-ilankovic@med.uni-muenchen.de.
FAU - Haas, Shalaila S
AU  - Haas SS
AD  - Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, 
      Germany; International Max Planck Research School for Translational Psychiatry 
      (IMPRS-TP), Munich, Germany.
FAU - Meisenzahl, Eva
AU  - Meisenzahl E
AD  - Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, 
      Germany; LVR-Klinikum Dusseldorf, Kliniken der Heinrich-Heine-Universitat 
      Dusseldorf, Germany.
FAU - Dwyer, Dominic B
AU  - Dwyer DB
AD  - Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, 
      Germany.
FAU - Weiske, Johanna
AU  - Weiske J
AD  - Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, 
      Germany.
FAU - Peters, Henning
AU  - Peters H
AD  - Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, 
      Germany.
FAU - Moller, Hans-Jurgen
AU  - Moller HJ
AD  - Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, 
      Germany.
FAU - Falkai, Peter
AU  - Falkai P
AD  - Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, 
      Germany.
FAU - Koutsouleris, Nikolaos
AU  - Koutsouleris N
AD  - Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, 
      Germany.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20181203
PL  - Netherlands
TA  - Neuroimage Clin
JT  - NeuroImage. Clinical
JID - 101597070
SB  - IM
MH  - Adult
MH  - Age Factors
MH  - Brain/diagnostic imaging/*growth & development/*pathology
MH  - Brain Mapping/methods
MH  - Female
MH  - Humans
MH  - Male
MH  - Models, Neurological
MH  - Neuropsychological Tests
MH  - Psychotic Disorders/diagnostic imaging/*pathology/*psychology
MH  - Risk Factors
MH  - Support Vector Machine
MH  - Young Adult
PMC - PMC6413470
EDAT- 2018/12/12 06:00
MHDA- 2019/12/18 06:00
PMCR- 2018/12/03
CRDT- 2018/12/12 06:00
PHST- 2018/07/17 00:00 [received]
PHST- 2018/11/14 00:00 [revised]
PHST- 2018/12/01 00:00 [accepted]
PHST- 2018/12/12 06:00 [pubmed]
PHST- 2019/12/18 06:00 [medline]
PHST- 2018/12/12 06:00 [entrez]
PHST- 2018/12/03 00:00 [pmc-release]
AID - S2213-1582(18)30372-3 [pii]
AID - 101624 [pii]
AID - 10.1016/j.nicl.2018.101624 [doi]
PST - ppublish
SO  - Neuroimage Clin. 2019;21:101624. doi: 10.1016/j.nicl.2018.101624. Epub 2018 Dec 
      3.