Functional brain networks in treatment-resistant schizophrenia
Introduction
Schizophrenia is a severe and chronically debilitating psychiatric disorder, with a two to three-fold increase in early mortality compared with the general population (Saha et al., 2007). Although use of first and second generation antipsychotics has significantly improved treatment response and quality of life for many individuals with schizophrenia, symptoms persist for up to one third of affected individuals, despite trialing various types of antipsychotic medications. This population has been termed “treatment resistant” (i.e., TRS). Currently clozapine is the only evidence-based atypical antipsychotic that has been found effective in ameliorating psychotic symptoms in TRS (Asenjo Lobos et al., 2010). However, clozapine is effective in only a fraction of patients, as up to 70% of TRS individuals do not respond (Papetti et al., 2007). Consequently, TRS is one of the greatest therapeutic challenges, with patients often suffering a more severe and chronic form of the disorder than those who respond to antipsychotic treatment (Bolonna and Kerwin, 2005). Many clinicians have posited that TRS may in fact be more accurately understood as a distinct subtype of schizophrenia, as opposed to being a chronic illness phase (Farooq et al., 2013, Lee et al., 2015). This notion has been supported by recent findings of differences in dopamine concentrations in the limbic and associative striatal subdivisions and glutamate levels in the anterior cingulate cortex between treatment-responsive schizophrenia and TRS groups (Demjaha et al., 2014, Demjaha et al., 2012). The relation between striatal dopamine and disrupted functional connectivity remains unclear in schizophrenia, however elevated dopamine levels may worsen the signal-to-noise ratio of spontaneous brain activity in the striatum, leading to a reduction in functional connectivity between striatum and frontal regions (Sorg et al., 2013). Despite the clinical relevance of TRS, few neuroimaging studies have focused on this population.
The theory of ‘dysconnectivity’ between spatially separated brain systems is one of the most prominent and widely researched hypotheses in schizophrenia (Friston and Frith, 1995, Zalesky et al., 2011, Zalesky et al., 2015). Findings however are inconsistent, with reports of both increased resting-state functional connectivity (rs-FC) (Jafri et al., 2008, Lui et al., 2010, Sorg et al., 2013, Whitfield-Gabrieli et al., 2009) and decreased rs-FC (Bluhm et al., 2007, Bluhm et al., 2009, Camchong et al., 2011, Gavrilescu et al., 2010, Hoptman et al., 2010, Liang et al., 2006, Meda et al., 2012, Ongur et al., 2010, Rotarska-Jagiela et al., 2010, Vercammen et al., 2010, Zhou et al., 2007, Zhou et al., 2008). Few studies have used functional imaging to investigate rs-FC in individuals with TRS. Using independent component analysis, one study found that TRS individuals with auditory-verbal hallucinations (AVH) showed reduced rs-FC between the left temporo-parietal junction and right Broca's area and anterior cingulate cortex (Vercammen et al., 2010). A later study also investigated AVH in TRS and found an increase in connectivity between bilateral temporal regions and a decrease in connectivity within the cingulate cortex (Wolf et al., 2011). These studies however, had relatively small samples (n = 27, n = 10) and explored connectivity predominantly in the context of AVH (Vercammen et al., 2010, Wolf et al., 2011). The most recent study by White et al. (2016) found reduced FC between the ventral striatum and substantia nigra in TRS compared with non-TRS patients, indicating there may be fundamental differences in network properties (reduced FC) between treatment-responsive and TRS patients.
More recently, in conjunction with measures of FC strength, graph theoretical methods have been applied to functional magnetic resonance imaging (fMRI) data in an attempt to understand the topology of brain networks. Two such measures that address the question of functional network organization are global and local efficiency. The efficiency of a brain network is inversely related to the number of intermediate regions that must be traversed for a pair of brain regions to communicate with each other. A directly connected pair of regions can communicate most efficiently since they do not utilize any intermediate regions. However, many pairs of brain regions are not directly connected, and thus communication between such regions is via a path that traverses one or more intermediate regions. The greater the number of intermediate regions traversed, the less efficient communication becomes, due to increasing energy requirements and potential signal dispersion (Bullmore and Sporns, 2012, Fornito et al., 2016). A reduction in brain network efficiency in patients may indicate a bias in the trade-off between metabolic costs and topology (Rubinov and Sporns, 2010, Wang et al., 2010).
Here, we characterized the connectivity and efficiency of whole-brain functional networks inferred from rs-fMRI in a group of individuals with TRS, compared to healthy controls. We also investigated whether a relationship between network connectivity and topology and symptomatology/functioning is evident. In light of previous research and the chronicity of the present sample, we hypothesize that the TRS group will show widespread reduced rs-FC, predominantly between frontal-temporal regions and topological abnormalities in the form of reduced global efficiency compared with controls. We also hypothesize that these abnormalities will correlate with symptom severity and functioning in the TRS group.
Section snippets
Participants
Forty-two treatment resistant schizophrenia (TRS) individuals (mean age 41.3 ± 10.0, 30 males) were recruited from inpatient and outpatient clinics in Melbourne, Australia. TRS was defined as at least two unsuccessful trials of two or more different antipsychotic types and currently taking clozapine (Kane et al., 1988, Suzuki et al., 2012).
Inclusion criteria for the TRS group were a diagnosis of schizophrenia, currently prescribed and taking clozapine and aged 18–65 years. Forty-two healthy
Results
Demographic information is shown in Table 1.
Discussion
This study explored whole-brain resting-state functional connectivity (FC), and the efficiency of whole-brain networks in patients with schizophrenia who have not responded to antipsychotic treatment (treatment-resistant schizophrenia; TRS). We found widespread reductions in FC in the TRS group at the whole-brain level, particularly implicating temporal, occipital and frontal regions with follow-up analyses showing the subregions predominantly involved to be Heschl's gyri, cuneus and
Contributors
Author Zalesky designed the functional connectivity protocol and was imperative to the methodology and analysis of the neuroimaging data. Author Seguin assisted in the design and execution of the graph theory section. Author Pantelis, author Phassouliotis and author Everall were imperative to the design, recruitment and execution of the study. Author Whittle, author Bousman and author Bartholomeusz assisted in the statistical design of the study. Author Ganella performed all the neuroimaging
Funding body agreements and policies
The authors acknowledge the financial support of the Cooperative Research Centre (CRC) for Mental Health which is an Australian Government Initiative. EG was supported by the University of Melbourne Ronald John Gleghorn Bursary and CRC for Mental Health PhD top-up scholarship. CAB was supported by University of Melbourne Ronald Phillip Griffith Fellowship and Brain and Behavior Research Foundation (NARSAD) Young Investigator Award (20526). CP was supported by NHMRC Senior Principal Research
Conflict of interest
The authors declare they have no conflicts of interest.
Acknowledgements
We thank the research assistants Annabel Burnside and Courtney Purdie who recruited the participants for this study and Despina Ganella who assisted with the preparation and proof-reading of the manuscript. We would also like to thank Chester Kang for IT support.
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2022, Psychiatry Research - NeuroimagingCitation Excerpt :We believe that these abnormalities indicate the efficient information processing may be at the cost of lowering the local fault tolerance, which might account for the generation of delusion in SZ, as proposed by the hypothesis of jumping to the conclusion (Moritz and Woodward, 2005). Some fMRI researches also reported the opposite results, which showed lower global efficiency or increased local efficiency in schizophrenia (Ganella et al., 2017, Sun et al., 2019, Su et al., 2015). The conflicting results may come from differences in methodology, race, or illness state.
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2019, Neuroscience and Biobehavioral ReviewsCitation Excerpt :Within 16 TRS studies, 3 did not report a definition of TRS (Bourque et al., 2013; Orlov et al., 2018; Thomann et al., 2017). In the 13 remaining studies treatment resistance was defined as a lack of symptom reduction in response to more than one trial of antipsychotic treatment: 3 assessed the response in terms of reductions in overall positive symptoms (Vanes et al., 2018; Wang et al., 2015; White et al., 2016), 6 evaluated a specific positive symptom (medication-resistant AVH, mrAVH) (Alonso-Solís et al., 2015; Homan et al., 2012; Mondino et al., 2016; Vercammen et al., 2010; Wolf et al., 2012, 2011), and 4 studies did not report the symptom domain of response (Ganella et al., 2017; McNabb et al., 2018a, b; Potvin et al., 2015). A widespread pattern of brain activation and connectivity differences was identified in TRS with the main involvement of fronto—temporal networks, implicated in auditory perception (particularly, superior temporal gyrus, STG), social cognition (particularly, temporo-parietal junction, TPJ) and in self-related processing (particularly, default mode network, DMN); subcortical networks, with associative and limbic corticostriatal and striato-striatal networks; frontal lobe, with a role in cognitive and emotional processing; also, global topological network properties were affected.
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Joint last authorship.