Anhedonia as a potential transdiagnostic phenotype with immune-related changes in recent onset mental health disorders.

BACKGROUND: Chronic low-grade inflammation is observed across mental disorders and is associated with difficult-to-treat-symptoms of anhedonia and functional brain changes - reflecting a potential transdiagnostic dimension. Previous investigations have focused on distinct illness categories in those with enduring illness, with few exploring inflammatory changes. We sought to identify an inflammatory signal and associated brain function underlying anhedonia among young people with recent onset psychosis (ROP) and recent onset depression (ROD). METHOD: Resting-state functional magnetic resonance imaging, inflammatory markers, and anhedonia symptoms were collected from N=108 (M age=26.2[SD 6.2]years; Female =50) participants with ROP (n=53) and ROD (n=55) from the EU-FP7-funded PRONIA study. Time-series were extracted using the Schaefer atlas, defining 100 cortical regions of interest. Using advanced multimodal machine learning, an inflammatory marker model and functional connectivity model were developed to classify an anhedonic group, compared to a normal hedonic group. RESULTS: A repeated nested cross-validation model using inflammatory markers classified normal hedonic and anhedonic ROP/ROD groups with a balanced accuracy (BAC) of 63.9%, and an area under the curve (AUC) of 0.61. The functional connectivity model produced a BAC of 55.2% and an AUC of 0.57. Anhedonic group assignment was driven by higher levels of Interleukin-6, S100B, and Interleukin-1 receptor antagonist, and lower levels of Interferon gamma, in addition to connectivity within the precuneus and posterior cingulate. CONCLUSION: We identified a potential transdiagnostic anhedonic subtype that was accounted for by an inflammatory profile and functional connectivity. Results have implications for anhedonia as an emerging transdiagnostic target across emerging mental disorders.

Trait related aberrant connectivity in clinically stable patients with schizophrenia: A seed based resting state fMRI study.

Aberrant resting-state connectivity within and between the Default Mode Network, the Executive Control Network, and the Salience Network is well-established in schizophrenia. Meta-analyses have identified that bilateral lingual gyrus is as the only region showing hyperactivity in schizophrenia and there are reports of increased connectivity between the lingual gyrus and other brain regions in schizophrenia. It is not clear whether these abnormalities represent state or trait markers of the illness, i.e., if they are only present during the acute phase of the illness (state) or if they reflect a predisposition to schizophrenia (trait). In this study, we used a seed-based functional connectivity analysis to investigate brain networks in schizophrenia patients who are in the stable phase of their illness and assess functional connectivity using seeds in the lingual gyrus, the posterior cingulate, the right dorsolateral prefrontal cortex (dlPFC), the right anterior insula (rAI) and the right orbital frontoinsula. Twenty patients with schizophrenia in a stable phase of their illness (as defined by the course of illness and Signs and Symptoms of Psychotic Illness (SSPI) scores) and 20 age and sex-matched healthy controls underwent resting-state functional Magnetic Resonance Imaging (rs-fMRI). Data was analysed using the Data Processing Assistant for Resting-State fMRI Advanced Edition (DPARSFA) V3.1 ( http://rfmri.org/DPARSF ) and the statistical parametric mapping software 8 (SPM8). Compared with healthy controls, patients with schizophrenia showed increased connectivity between the left lingual gyrus and the middle frontal gyrus, and the cingulate cortex. Lingual gyrus hyper-connectivity may be a stable trait neuroimaging marker for schizophrenia. Our findings suggest that aberrant connectivity in major resting-state networks may not be present after the acute illness has stabilised.