# Connectivity Biomarkers of Clinical Response in Treatment Resistant Schizophrenia

> **NIH NIH R01** · FEINSTEIN INSTITUTE FOR MEDICAL RESEARCH · 2020 · $692,366

## Abstract

Project Summary
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 antipsychot...

## Key facts

- **NIH application ID:** 9891084
- **Project number:** 5R01MH109508-04
- **Recipient organization:** FEINSTEIN INSTITUTE FOR MEDICAL RESEARCH
- **Principal Investigator:** Anil K Malhotra
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $692,366
- **Award type:** 5
- **Project period:** 2017-01-13 → 2021-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9891084

## Citation

> US National Institutes of Health, RePORTER application 9891084, Connectivity Biomarkers of Clinical Response in Treatment Resistant Schizophrenia (5R01MH109508-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9891084. Licensed CC0.

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