# Lithium Effects on the Brain's Functional and Structural Connectome in the Treatment of Bipolar Disorder

> **NIH NIH R01** · CLEVELAND CLINIC LERNER COM-CWRU · 2020 · $731,216

## Abstract

ABSTRACT
Lithium is one of the most specific and effective treatments for bipolar disorder (BD) yet its mechanism
of action remains unclear. This has impeded methods to monitor its effects and the development of new
medications with similar efficacy and specificity. Clinical efficacy of lithium in bipolar disorder, and its
complex effects on multiple brain physiological functions, may be best deciphered using a network
properties-metric approach. This approach is critical because it provides insight into the function of
brain networks (e.g., resilience to disruption, central hubs), which is likely to be more closely linked to
behavioral outcomes. Furthermore, the relationship of the neuroimaging effects of lithium and its
molecular effects in humans has been studied even less. This proposal addresses these important
gaps in knowledge by measuring brain functional and structural connectomics before and after acute
and longer term treatment with lithium. We will study 90 medication free bipolar disorder depressed
(BDD) type II subjects at baseline and after 2, 8 and 26 weeks of lithium monotherapy. We will also
study 30 closely matched healthy controls who will be imaged at the same time points but will not
receive any treatment. BDD II subjects will undergo resting state functional magnetic resonance
imaging (fMRI) scans and diffusion weighted structural imaging scans. In addition to imaging, we will
also collect RNA samples from peripheral blood lymphocytes to explore lithium induced peripheral gene
expression changes. Functional and structural scans will be analyzed using graph theory metrics
(GTM) and Independent Component Analysis (ICA). Graph theory metrics move beyond simple
description of brain connectivity and provide insight into network function (e.g., resilience to disruption,
regional hubs). ICA analysis has identified consistent and well defined independent components in
resting state data e.g the default mode and salience networks. Preliminary data from our studies
indicates significant effect of lithium on GTM and ICA metrics and correlation of the changes in these
metrics to clinical improvement. In this proposal, we will acquire images on a state-of-the-art 7-T
scanner, conduct rigorous motion correction and apply cutting-edge GTM and ICA analytics. We will
correlate changes in GTA and ICA metrics to improvement in depression in the short term and mood
stability in the longer term in BDD II subjects. Furthermore, we will conduct an exploratory analysis
regarding association between changes in peripheral gene expression and improvement in
symptomatology and mood stability using the GTA metrics change as mediators and using ICA
multimodality fusion analysis. This will be an exploratory analysis to yield data for future more definitive
human and basic science studies of lithium effect. This study will therefore provide unique data
regarding imaging and molecular correlates of lithium monotherapy and its relationship to lithium
effica...

## Key facts

- **NIH application ID:** 9922362
- **Project number:** 5R01MH113256-04
- **Recipient organization:** CLEVELAND CLINIC LERNER COM-CWRU
- **Principal Investigator:** Amit Anand
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $731,216
- **Award type:** 5
- **Project period:** 2017-07-01 → 2021-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9922362

## Citation

> US National Institutes of Health, RePORTER application 9922362, Lithium Effects on the Brain's Functional and Structural Connectome in the Treatment of Bipolar Disorder (5R01MH113256-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9922362. Licensed CC0.

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