Antonucci, Linda A. ORCID: 0000-0002-7919-7402, Penzel, Nora, Pergola, Giulio ORCID: 0000-0002-9193-1841, Kambeitz-Ilankovic, Lana, Dwyer, Dominic, Kambeitz, Joseph, Haas, Shalaila Siobhan, Passiatore, Roberta, Fazio, Leonardo, Caforio, Grazia, Falkai, Peter ORCID: 0000-0003-2873-8667, Blasi, Giuseppe, Bertolino, Alessandro and Koutsouleris, Nikolaos (2020). Multivariate classification of schizophrenia and its familial risk based on load-dependent attentional control brain functional connectivity. Neuropsychopharmacology, 45 (4). S. 613 - 622. LONDON: NATURE PUBLISHING GROUP. ISSN 1740-634X

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Abstract

Patients with schizophrenia (SCZ), as well as their unaffected siblings (SIB), show functional connectivity (FC) alterations during performance of tasks involving attention. As compared with SCZ, these alterations are present in SIB to a lesser extent and are more pronounced during high cognitive demand, thus possibly representing one of the pathways in which familial risk is translated into the SCZ phenotype. Our aim is to measure the separability of SCZ and SIB from healthy controls (HC) using attentional control-dependent FC patterns, and to test to which extent these patterns span a continuum of neurofunctional alterations between HC and SCZ. 65 SCZ with 65 age and gender-matched HC and 39 SIB with 39 matched HC underwent the Variable Attentional Control (VAC) task. Load-dependent connectivity matrices were generated according to correct responses in each VAC load. Classification performances of high, intermediate and low VAC load FC on HC-SCZ and HC-SIB cohorts were tested through machine learning techniques within a repeated nested cross-validation framework. HC-SCZ classification models were applied to the HC-SIB cohort, and vice-versa. A high load-related decreased FC pattern discriminated between HC and SCZ with 66.9% accuracy and with 57.7% accuracy between HC and SIB. A high load-related increased FC network separated SIB from HC (69.6% accuracy), but not SCZ from HC (48.5% accuracy). Our findings revealed signatures of attentional FC abnormalities shared by SCZ and SIB individuals. We also found evidence for potential, SIB-specific FC signature, which may point to compensatory neurofunctional mechanisms in persons at familial risk for schizophrenia.

Item Type: Journal Article
Creators:
CreatorsEmailORCIDORCID Put Code
Antonucci, Linda A.UNSPECIFIEDorcid.org/0000-0002-7919-7402UNSPECIFIED
Penzel, NoraUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Pergola, GiulioUNSPECIFIEDorcid.org/0000-0002-9193-1841UNSPECIFIED
Kambeitz-Ilankovic, LanaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Dwyer, DominicUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Kambeitz, JosephUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Haas, Shalaila SiobhanUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Passiatore, RobertaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Fazio, LeonardoUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Caforio, GraziaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Falkai, PeterUNSPECIFIEDorcid.org/0000-0003-2873-8667UNSPECIFIED
Blasi, GiuseppeUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Bertolino, AlessandroUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Koutsouleris, NikolaosUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
URN: urn:nbn:de:hbz:38-343634
DOI: 10.1038/s41386-019-0532-3
Journal or Publication Title: Neuropsychopharmacology
Volume: 45
Number: 4
Page Range: S. 613 - 622
Date: 2020
Publisher: NATURE PUBLISHING GROUP
Place of Publication: LONDON
ISSN: 1740-634X
Language: English
Faculty: Unspecified
Divisions: Unspecified
Subjects: no entry
Uncontrolled Keywords:
KeywordsLanguage
SUPPORT VECTOR MACHINE; RESTING-STATE FMRI; CLINICAL HIGH-RISK; PATTERN-CLASSIFICATION; PREFRONTAL CORTEX; NETWORK CONNECTIVITY; GENETIC LIABILITY; DEFAULT-MODE; PSYCHOSIS; SIBLINGSMultiple languages
Neurosciences; Pharmacology & Pharmacy; PsychiatryMultiple languages
URI: http://kups.ub.uni-koeln.de/id/eprint/34363

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