| Literature DB >> 28007987 |
Nicolas A Crossley1,2, Tiago Reis Marques1,3, Heather Taylor4, Chris Chaddock4, Flavio Dell'Acqua5, Antje A T S Reinders4, Valeria Mondelli6, Marta DiForti4, Andrew Simmons5, Anthony S David4, Shitij Kapur4, Carmine M Pariante6, Robin M Murray4, Paola Dazzan4,7.
Abstract
Connectomic approaches using diffusion tensor imaging have contributed to our understanding of brain changes in psychosis, and could provide further insights into the neural mechanisms underlying response to antipsychotic treatment. We here studied the brain network organization in patients at their first episode of psychosis, evaluating whether connectome-based descriptions of brain networks predict response to treatment, and whether they change after treatment. Seventy-six patients with a first episode of psychosis and 74 healthy controls were included. Thirty-three patients were classified as responders after 12 weeks of antipsychotic treatment. Baseline brain structural networks were built using whole-brain diffusion tensor imaging tractography, and analysed using graph analysis and network-based statistics to explore baseline characteristics of patients who subsequently responded to treatment. A subgroup of 43 patients was rescanned at the 12-week follow-up, to study connectomic changes over time in relation to treatment response. At baseline, those subjects who subsequently responded to treatment, compared to those that did not, showed higher global efficiency in their structural connectomes, a network configuration that theoretically facilitates the flow of information. We did not find specific connectomic changes related to treatment response after 12 weeks of treatment. Our data suggest that patients who have an efficiently-wired connectome at first onset of psychosis show a better subsequent response to antipsychotics. However, response is not accompanied by specific structural changes over time detectable with this method.Entities:
Keywords: DTI; antipsychotics; connectome; first-episode psychosis; schizophrenia
Mesh:
Substances:
Year: 2016 PMID: 28007987 PMCID: PMC5841056 DOI: 10.1093/brain/aww297
Source DB: PubMed Journal: Brain ISSN: 0006-8950 Impact factor: 13.501