# A translational approach for novel mechanisms of epigenetic regulation in treatment responses: toward a precision medicine model

> **NIH NIH R01** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2022 · $753,554

## Abstract

PROJECT SUMMARY/ABSTRACT
Treatment resistant depression (TRD) is a leading cause of illness and disability worldwide; there is a dearth of new mechanistic models for the development of better therapeutic strategies. Studies to date showed that administration of LAC, a pivotal mitochondrial metabolite, leads to a rapid and persistent antidepressant-like response by increasing histone acetyltransferases (HATs) activity and the related expression of a key inhibitor of glutamate release mGlu2 receptor in circuits implicated in TRD. Furthermore, LAC levels are decreased in clinical phenotypes of TRD. The objective of this application is to understand the role of central and peripheral LAC-related mitochondrial metabolism in the regulation of TMS responses in phenotypes of TRD. We will also use computational algorithm and statistical clustering to ascertain the role of the novel biomarkers of TMS responses in the trajectories of functional connectivity, and how these pathways are modified by sex. This contribution will advance our understanding of cellular and molecular mechanisms of mitochondrial metabolism for TMS responses in phenotypes of TRD, and identify sex-differences in these mechanisms.

## Key facts

- **NIH application ID:** 10344520
- **Project number:** 1R01MH128311-01
- **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- **Principal Investigator:** Carla Nasca
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $753,554
- **Award type:** 1
- **Project period:** 2022-02-08 → 2026-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10344520

## Citation

> US National Institutes of Health, RePORTER application 10344520, A translational approach for novel mechanisms of epigenetic regulation in treatment responses: toward a precision medicine model (1R01MH128311-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10344520. Licensed CC0.

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