Literature DB >> 22887825

Multivariate patterns of brain-cognition associations relating to vulnerability and clinical outcome in the at-risk mental states for psychosis.

Nikolaos Koutsouleris1, Christian Gaser, Katja Patschurek-Kliche, Johanna Scheuerecker, Ronald Bottlender, Petra Decker, Gisela Schmitt, Maximilian Reiser, Hans-Jürgen Möller, Eva M Meisenzahl.   

Abstract

BACKGROUND: Neuropsychological deficits are a core feature of established psychosis and have been previously linked to fronto-temporo-limbic brain alterations. Both neurocognitive and neuroanatomical abnormalities characterize clinical at-risk mental states (ARMS) for psychosis. However, structure-cognition relationships in the ARMS have not been directly explored using multivariate neuroimaging techniques.
METHODS: Voxel-based morphometry and partial least squares were employed to study system-level covariance patterns between whole-brain morphological data and processing speed, working memory, verbal learning/IQ, and executive functions in 40 ARMS subjects and 30 healthy controls (HC). The detected structure-cognition covariance patterns were tested for significance and reliability using non-parametric permutation and bootstrap resampling.
RESULTS: We identified ARMS-specific covariance patterns that described a generalized association of neurocognitive measures with predominantly prefronto-temporo-limbic and subcortical structures as well as the interconnecting white matter. In the conversion group, this generalized profile particularly involved working memory and verbal IQ and was positively correlated with limbic, insular and subcortical volumes as well as negatively related to prefrontal, temporal, parietal, and occipital cortices. Conversely, the neurocognitive profiles in the HC group were confined to working memory, learning and IQ, which were diffusely associated with cortical and subcortical brain regions.
CONCLUSIONS: These findings suggest that the ARMS and prodromal phase of psychosis are characterized by a convergent mapping from multi-domain neurocognitive measures to a set of prefronto-temporo-limbic and subcortical structures. Furthermore, a neuroanatomical separation between positive and negative brain-cognition correlations may not only point to a biological process determining the clinical risk for disease transition, but also to possible compensatory or dysmaturational neural processes.
Copyright © 2011 Wiley Periodicals, Inc.

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Year:  2011        PMID: 22887825      PMCID: PMC6870479          DOI: 10.1002/hbm.21342

Source DB:  PubMed          Journal:  Hum Brain Mapp        ISSN: 1065-9471            Impact factor:   5.038


  104 in total

1.  Use of neuroanatomical pattern regression to predict the structural brain dynamics of vulnerability and transition to psychosis.

Authors:  Nikolaos Koutsouleris; Christian Gaser; Ronald Bottlender; Christos Davatzikos; Petra Decker; Markus Jäger; Gisela Schmitt; Maximilian Reiser; Hans-Jürgen Möller; Eva M Meisenzahl
Journal:  Schizophr Res       Date:  2010-09-17       Impact factor: 4.939

2.  White matter integrity and cognitive impairment in first-episode psychosis.

Authors:  Rocío Pérez-Iglesias; Diana Tordesillas-Gutiérrez; Philip K McGuire; Gareth J Barker; Roberto Roiz-Santiañez; Ignacio Mata; Enrique Marco de Lucas; Jose Manuel Rodríguez-Sánchez; Rosa Ayesa-Arriola; Jose L Vazquez-Barquero; Benedicto Crespo-Facorro
Journal:  Am J Psychiatry       Date:  2010-02-16       Impact factor: 18.112

3.  Neurodevelopmental trajectories of the human cerebral cortex.

Authors:  Philip Shaw; Noor J Kabani; Jason P Lerch; Kristen Eckstrand; Rhoshel Lenroot; Nitin Gogtay; Deanna Greenstein; Liv Clasen; Alan Evans; Judith L Rapoport; Jay N Giedd; Steve P Wise
Journal:  J Neurosci       Date:  2008-04-02       Impact factor: 6.167

Review 4.  The neural underpinnings of associative learning in health and psychosis: how can performance be preserved when brain responses are abnormal?

Authors:  Graham K Murray; Philip R Corlett; Paul C Fletcher
Journal:  Schizophr Bull       Date:  2010-02-12       Impact factor: 9.306

5.  Are schizophrenic men at higher risk for developmental deficits than schizophrenic women? Implications for adult neuropsychological functions.

Authors:  J M Goldstein; L J Seidman; S Santangelo; P H Knapp; M T Tsuang
Journal:  J Psychiatr Res       Date:  1994 Nov-Dec       Impact factor: 4.791

6.  Shape of caudate nucleus and its cognitive correlates in neuroleptic-naive schizotypal personality disorder.

Authors:  James J Levitt; Carl Fredrik Westin; Paul G Nestor; Raul S J Estepar; Chandlee C Dickey; Martina M Voglmaier; Larry J Seidman; Ron Kikinis; Ferenc A Jolesz; Robert W McCarley; Martha E Shenton
Journal:  Biol Psychiatry       Date:  2004-01-15       Impact factor: 13.382

Review 7.  Early detection and intervention in the initial prodromal phase of schizophrenia.

Authors:  S Ruhrmann; F Schultze-Lutter; J Klosterkötter
Journal:  Pharmacopsychiatry       Date:  2003-11       Impact factor: 5.788

8.  Sustained attention impairment correlates to gray matter decreases in first episode neuroleptic-naive schizophrenic patients.

Authors:  Pilar Salgado-Pineda; Immaculada Baeza; Mercedes Pérez-Gómez; Pere Vendrell; Carme Junqué; Nuria Bargalló; Miquel Bernardo
Journal:  Neuroimage       Date:  2003-06       Impact factor: 6.556

9.  Neurocognitive deficit in schizophrenia: a quantitative review of the evidence.

Authors:  R W Heinrichs; K K Zakzanis
Journal:  Neuropsychology       Date:  1998-07       Impact factor: 3.295

10.  Neurocognitive endophenotypes of obsessive-compulsive disorder.

Authors:  Lara Menzies; Sophie Achard; Samuel R Chamberlain; Naomi Fineberg; Chi-Hua Chen; Natalia del Campo; Barbara J Sahakian; Trevor W Robbins; Ed Bullmore
Journal:  Brain       Date:  2007-09-13       Impact factor: 13.501

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  13 in total

1.  Multisite Machine Learning Analysis Provides a Robust Structural Imaging Signature of Schizophrenia Detectable Across Diverse Patient Populations and Within Individuals.

Authors:  Martin Rozycki; Theodore D Satterthwaite; Nikolaos Koutsouleris; Guray Erus; Jimit Doshi; Daniel H Wolf; Yong Fan; Raquel E Gur; Ruben C Gur; Eva M Meisenzahl; Chuanjun Zhuo; Hong Yin; Hao Yan; Weihua Yue; Dai Zhang; Christos Davatzikos
Journal:  Schizophr Bull       Date:  2018-08-20       Impact factor: 9.306

2.  Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model.

Authors:  Laura Pina-Camacho; Juan Garcia-Prieto; Mara Parellada; Josefina Castro-Fornieles; Ana M Gonzalez-Pinto; Igor Bombin; Montserrat Graell; Beatriz Paya; Marta Rapado-Castro; Joost Janssen; Inmaculada Baeza; Francisco Del Pozo; Manuel Desco; Celso Arango
Journal:  Eur Child Adolesc Psychiatry       Date:  2014-08-11       Impact factor: 4.785

3.  A stratified model for psychosis prediction in clinical practice.

Authors:  Chantal Michel; Stephan Ruhrmann; Benno G Schimmelmann; Joachim Klosterkötter; Frauke Schultze-Lutter
Journal:  Schizophr Bull       Date:  2014-03-07       Impact factor: 9.306

4.  Lack of Evidence for Regional Brain Volume or Cortical Thickness Abnormalities in Youths at Clinical High Risk for Psychosis: Findings From the Longitudinal Youth at Risk Study.

Authors:  Paul Klauser; Juan Zhou; Joseph K W Lim; Joann S Poh; Hui Zheng; Han Ying Tng; Ranga Krishnan; Jimmy Lee; Richard S E Keefe; R Alison Adcock; Stephen J Wood; Alex Fornito; Michael W L Chee
Journal:  Schizophr Bull       Date:  2015-03-04       Impact factor: 9.306

Review 5.  Endophenotypes in Schizophrenia for the Perinatal Period: Criteria for Validation.

Authors:  Randal G Ross; Robert Freedman
Journal:  Schizophr Bull       Date:  2015-05-04       Impact factor: 9.306

6.  Predicting first episode psychosis in those at high risk for genetic or cognitive reasons.

Authors:  Stephen M Lawrie; Andrew Stanfield; Eve C Johnstone; Andrew M McIntosh
Journal:  Epidemiol Psychiatr Sci       Date:  2012-09-12       Impact factor: 6.892

7.  Multimodal predictive modeling of individual treatment outcome in cocaine dependence with combined neuroimaging and behavioral predictors.

Authors:  Sean X Luo; Diana Martinez; Kenneth M Carpenter; Mark Slifstein; Edward V Nunes
Journal:  Drug Alcohol Depend       Date:  2014-07-10       Impact factor: 4.492

8.  Detecting the psychosis prodrome across high-risk populations using neuroanatomical biomarkers.

Authors:  Nikolaos Koutsouleris; Anita Riecher-Rössler; Eva M Meisenzahl; Renata Smieskova; Erich Studerus; Lana Kambeitz-Ilankovic; Sebastian von Saldern; Carlos Cabral; Maximilian Reiser; Peter Falkai; Stefan Borgwardt
Journal:  Schizophr Bull       Date:  2014-06-09       Impact factor: 9.306

9.  Multivariate neuroanatomical classification of cognitive subtypes in schizophrenia: a support vector machine learning approach.

Authors:  Ian C Gould; Alana M Shepherd; Kristin R Laurens; Murray J Cairns; Vaughan J Carr; Melissa J Green
Journal:  Neuroimage Clin       Date:  2014-09-18       Impact factor: 4.881

10.  Progressive brain changes in schizophrenia related to antipsychotic treatment? A meta-analysis of longitudinal MRI studies.

Authors:  P Fusar-Poli; R Smieskova; M J Kempton; B C Ho; N C Andreasen; S Borgwardt
Journal:  Neurosci Biobehav Rev       Date:  2013-06-14       Impact factor: 8.989

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