Antipsychotic drugs are the mainstay for treatment of psychosis, yet they are associated with substantial heterogeneity in their therapeutic efficacy. Non-response to treatment contributes to poor quality of life for patients, and a large economic impact on healthcare systems. Treatment algorithms for these illnesses are devoid of prognostic measures, and clinicians generally must rely on trial-and-error. At the same time, neural mechanisms underlying response to treatment remain unclear, resulting in a lack of potential targets for novel treatment development. Surprisingly, given the urgent public health and scientific needs, very little work has utilized modern neuroimaging techniques to understand the mechanisms of antipsychotic response. We have recently demonstrated that resting state functional connectivity (RSFC) may be a valuable assay for biomarker development, both as pre-treatment predictors of treatment response, as well as dynamic markers of antipsychotic efficacy over the course of treatment. For example, our group developed an index of striatal connectivity that predicted response to second-generation antipsychotics (SGAs) with high sensitivity and specificity in first-episode schizophrenia patients, and generalized to a cohort of chronic patients with psychosis. Moreover, we found that changes in the functional interactions of the striatum with the cingulate, hippocampus, thalamus, and cortex tracked improvements in psychosis after 12 weeks of SGA treatment. To date, this approach has not been applied to treatment-resistant schizophrenia (TRS) populations, nor have treatment strategies that do not primarily target the striatum been extensively studied. In this project, we propose to assess RSFC in two groups of TRS patients undergoing treatment with effective intervention strategies that significantly differ from traditional D2 receptor antagonists.
In Aim 1, we will assess psychotic patients undergoing a 24-week treatment trial with clozapine, which remains unique amongst antipsychotic drugs for its superior efficacy in TRS.
In Aim 2, we will assess patients whose psychotic symptoms remain refractory even to CLZ, whom we refer to as ultra-treatment-resistant (uTRS). We will scan uTRS patients undergoing an 8-week treatment trial of CLZ combined with adjunctive electro-convulsive therapy (CLZ+ECT), a treatment strategy recently demonstrated to have remarkable efficacy in severely ill uTRS patients. For both aims, we will use a longitudinal design with MRI scans collected before and after controlled treatment, with symptoms assessed with structured rating scales. RSFC will be assessed using a seed-based strategy based upon our recent work, but expanded to include relevant subcortical structures beyond the striatum. Results from this project may provide: 1) biomarkers for use in ?precision medicine? strategies for patients with psychotic illnesses; and 2) biomarkers of striatal- and nonstriatally-mediated antipsychotic efficacy for use in novel antipsychotic drug development. Such biomarkers are urgently needed, given the lack of a sufficient evidence base to guide clinical practice, and the lack of a research base to guide treatment development.

Public Health Relevance

This project will utilize modern neuroimaging techniques that assess the connections between brain regions to understand the efficacy of intervention strategies for treatment-resistant patients with psychosis. These treatment strategies include clozapine, and the augmentation of clozapine with electroconvulsive therapy. Results from this project will provide biomarkers to help identify good responders to treatment, as well as biomarkers for use in new treatment development.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
1R01MH109508-01A1
Application #
9239186
Study Section
Special Emphasis Panel (ZMH1-ERB-D (08))
Program Officer
Hillefors, MI
Project Start
2017-01-13
Project End
2021-12-31
Budget Start
2017-01-13
Budget End
2017-12-31
Support Year
1
Fiscal Year
2017
Total Cost
$728,807
Indirect Cost
$287,106
Name
Feinstein Institute for Medical Research
Department
Type
Research Institutes
DUNS #
110565913
City
Manhasset
State
NY
Country
United States
Zip Code
11030