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.
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Acknowledgements
We are grateful to Dr. Paolo Taurisano, Dr. Tiziana Quarto, Dr. Barbara Gelao, Dr. Raffaella Romano, for making data acquisition possible, and to Johanna Weiske for the methodological help.
Funding and Disclosure
This work was supported by the EU-FP7-HEALTH grant for the project “PRONIA” (Personalized Prognostic Tools for Early Psychosis Management-agreement number: 602152) and from the Structural European Funding of the Italian Minister of Education (Attraction and International Mobility–AIM-action, grant agreement No 1859959). The AIM action also funds LAA's salary. NK has received honoraria for two lectures from Otsuka. AB is a stockholder of Hoffmann-La Roche Ltd. He has also received lecture fees from Otsuka, Jannssen, Lundbeck, and consultant fees from Biogen. GB has received lecture fees by Janssen and Lundbeck. GP’s position is funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 798181. The funding bodies had no role in study design, data collection, and analysis, decision to publish, or preparation of the paper. This paper reflects only the author's views and the European Union is not liable for any use that may be made of the information contained therein. The remaning authors declare no biomedical financial interests and no potential conflicts of interest.
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Antonucci, L.A., Penzel, N., Pergola, G. et al. Multivariate classification of schizophrenia and its familial risk based on load-dependent attentional control brain functional connectivity. Neuropsychopharmacol. 45, 613–621 (2020). https://doi.org/10.1038/s41386-019-0532-3
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DOI: https://doi.org/10.1038/s41386-019-0532-3
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