Inflammatory Response & Treatment-Resistant Mental Disorders

Research Paper Title

Inflammatory Response and Treatment-Resistant Mental Disorders: Should Immunotherapy Be Added to Pharmacotherapy?

Abstract

Treatment resistance continues to challenge and frustrate mental health clinicians and provoke psychiatric researchers to seek additional explanatory theories for psychopathology.

Because the inflammatory process activates symptoms of depression, anxiety, and psychosis, it is a reasonable route to follow for primary and/or indirect contribution to mental disorders.

The current article reviews the research literature regarding the role the inflammatory process and immune system play in mental disorders as well as novel treatments under investigation for resistant depression, anxiety, substance use, and psychotic disorders.

Reference

Limandri, B.J. (2020) Inflammatory Response and Treatment-Resistant Mental Disorders: Should Immunotherapy Be Added to Pharmacotherapy? Journal of Psychosocial Nursing and Mental Health Services. 58(1), pp.11-16. doi: 10.3928/02793695-20191218-03.

What are the Comorbidity Rates of Depression & Anxiety in First Episode Psychosis?

Research Paper Title

Comorbidity rates of depression and anxiety in first episode psychosis: A systematic review and meta-analysis.

Background

Anxiety and depression symptoms are frequently experienced by individuals with psychosis, although prevalence rates have not been reviewed in first-episode psychosis (FEP).

The aim of this systematic review was to focus on the prevalence rates for both anxiety and depression, comparing the rates within the same study population.

Methods

A systematic review and meta-analysis was completed for all studies measuring both anxiety and depression in FEP at baseline.

The search identified 6040 citations, of which n = 10 met inclusion criteria.

These reported 1265 patients (age 28.3 ± 9.1, females: 39.9%) with diagnosed FEP.

Studies which used diagnosis to define comorbidity count were included in separate meta-analyses for anxiety and depression, although the heterogeneity was high limiting interpretation of separate prevalence rates.

A random-effects meta-analysis also compared the mean difference between anxiety and depression within the same studies.

Results

The researchers show that anxiety and depression co-occur at a similar rate within FEP, although the exact rates are not reliable due to the heterogeneity between the small number of studies.

Conclusions

Future research in FEP should consider routinely measuring anxiety and depression using continuous self-report measures of symptoms.

Clinically, the researchers recommend that both anxiety and depression are equally targeted during psychological intervention in FEP, together with the psychotic symptoms.

Reference

Wilson, R.S., Yung, A.R. & Morrison, A.P. (2019) Comorbidity rates of depression and anxiety in first episode psychosis: A systematic review and meta-analysis. Schizophrenia Research. pii: S0920-9964(19)30542-0. doi: 10.1016/j.schres.2019.11.035. [Epub ahead of print].

Can Brain Changes Reflected by Alterations in Functional Connectivity be a Useful for Outcome Prediction in the Prodromal Stage?

Research Paper Title

Brain functional connectivity data enhance prediction of clinical outcome in youth at risk for psychosis.

Background

The first episode of psychosis is typically preceded by a prodromal phase with subthreshold symptoms and functional decline.

Improved outcome prediction in this stage is needed to allow targeted early intervention.

This study assesses a combined clinical and resting-state fMRI prediction model in 137 adolescents and young adults at Clinical High Risk (CHR) for psychosis from the Shanghai At Risk for Psychosis (SHARP) programme.

Methods

Based on outcome at one-year follow-up, participants were separated into three outcome categories including:

  • Good outcome (symptom remission, N = 71);
  • Intermediate outcome (ongoing CHR symptoms, N = 30); and
  • Poor outcome (conversion to psychosis or treatment-refractory, N = 36).

Validated clinical predictors from the psychosis-risk calculator were combined with measures of resting-state functional connectivity.

Results

Using multinomial logistic regression analysis and leave-one-out cross-validation, a clinical-only prediction model did not achieve a significant level of outcome prediction (F1 = 0.32, p = .154).

An imaging-only model yielded a significant prediction model (F1 = 0.41, p = .016), but a combined model including both clinical and connectivity measures showed the best performance (F1 = 0.46, p < .001).

Influential predictors in this model included functional decline, verbal learning performance, a family history of psychosis, default-mode and frontoparietal within-network connectivity, and between-network connectivity among language, salience, dorsal attention, sensorimotor, and cerebellar networks.

Conclusions

These findings suggest that brain changes reflected by alterations in functional connectivity may be useful for outcome prediction in the prodromal stage.

Reference

Collin, G., Nieto-Castanon, A., Shenton, M.E., Pasternak, O., Kelly, S., Keshavan, M.S., Seidman, L.J., McCarley, R.W., Niznikiewicz, M.A., Li, H., Zhang, T., Tang, Y., Stone, W.S., Wang, J. & Whitfield-Gabrieli, S. (2019) Brain functional connectivity data enhance prediction of clinical outcome in youth at risk for psychosis. NeuroImage Clinical. doi: 10.1016/j.nicl.2019.102108. [Epub ahead of print].