Functional network dysconnectivity as a biomarker of treatment resistance in schizophrenia
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McNabb, C., Tait, R., McIlwain, M., Anderson, V., Suckling, J., Kydd, R., & Russell, B. (2017). Functional network dysconnectivity as a biomarker of treatment resistance in schizophrenia. Schizophrenia Research https://doi.org/10.1016/j.schres.2017.10.015
Schizophrenia may develop from disruptions in functional connectivity regulated by neurotransmitters such as dopamine and acetylcholine. The modulatory effects of these neurotransmitters might explain how antipsychotics attenuate symptoms of schizophrenia and account for the variable response to antipsychotics observed in clinical practice. Based on the putative mechanisms of antipsychotics and evidence of disrupted connectivity in schizophrenia, we hypothesised that functional network connectivity, as assessed using network-based statistics, would exhibit differences between treatment response subtypes of schizophrenia and healthy controls. Resting-state functional MRI data were obtained from 17 healthy controls as well as individuals with schizophrenia who responded well to first-line atypical antipsychotics (first-line responders; FLR, n=18), had failed at least two trials of antipsychotics but responded to clozapine (treatment-resistant schizophrenia; TRS, n=18), or failed at least two trials of antipsychotics and a trial of clozapine (ultra-treatment-resistant schizophrenia; UTRS, n=16). Data were pre-processed using the Advanced Normalisation Toolkit and BrainWavelet Toolbox. Network connectivity was assessed using the Network-Based Statistics toolbox in Matlab. ANOVA revealed a significant difference in functional connectivity between groups that extended between cerebellar and parietal regions to the frontal cortex (p<0.05). Post-hoc T-tests revealed weaker network connectivity in individuals with UTRS compared with healthy controls but no other differences between groups. Results demonstrated distinct differences in functional connectivity between individuals with UTRS and healthy controls. Future work must determine whether these changes occur prior to the onset of treatment and if they can be used to predict resistance to antipsychotics during first-episode psychosis.
schizophrenia, treatment resistance, treatment response, magnetic resonance imaging, network based statistics, clozapine
This work was supported by The University of Auckland Faculty Research and Development Fund Project number 3624739, with support from the New Zealand Pharmacy Education and Research Fund Grant number 263, the New Zealand Schizophrenia Research Group Donation and the Oakley Mental Health Research Foundation. Carolyn McNabb was supported by a Vernon Tews Education Trust scholarship. Meghan McIlwain was supported by a University of Auckland Doctoral Scholarship and a New Zealand Federation of Graduate Women Fellowship. Valerie Anderson was supported by an Edith C. Coan Research Fellowship from The Auckland Medical Research Foundation.
External DOI: https://doi.org/10.1016/j.schres.2017.10.015
This record's URL: https://www.repository.cam.ac.uk/handle/1810/271688
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