Multidimensional predictors of antidepressant responses: Integrating mitochondrial, genetic, metabolic and environmental factors with clinical outcomes

Carla Nasca; Olivia Barnhill; Paolo DeAngelis; Kathleen Watson; Jue Lin; James Beasley; Sarah P Young; Alison Myoraku; Josh Dobbin; Benedetta Bigio; Bruce McEwen; Natalie Rasgon

doi:10.1016/j.ynstr.2021.100407

Multidimensional predictors of antidepressant responses: Integrating mitochondrial, genetic, metabolic and environmental factors with clinical outcomes

Neurobiol Stress. 2021 Oct 9:15:100407. doi: 10.1016/j.ynstr.2021.100407. eCollection 2021 Nov.

Authors

Carla Nasca^{1

2

3}, Olivia Barnhill¹, Paolo DeAngelis¹, Kathleen Watson⁴, Jue Lin^{5

6}, James Beasley⁷, Sarah P Young^{7

8}, Alison Myoraku⁴, Josh Dobbin¹, Benedetta Bigio^{1

9}, Bruce McEwen¹, Natalie Rasgon⁴

Affiliations

¹ Harold and Margaret Milliken Hatch Laboratory of Neuroendocrinology, Rockefeller University, New York, USA.
² Department of Psychiatry, New York University, Grossman School of Medicine, New York, NY, USA.
³ Department of Neuroscience and Physiology, New York University Neuroscience Institute, New York University, New York, NY, USA.
⁴ Center for Neuroscience in Women's Health, Stanford University, Palo Alto, USA.
⁵ Department of Psychiatry, University of California, San Francisco, San Francisco, USA.
⁶ Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, USA.
⁷ Division of Medical Genetics, Department of Pediatrics, Duke University School of Medicine, Durham, NC, USA.
⁸ Biochemical Genetics Laboratory, Duke University Health System, Durham, USA.
⁹ Biostatistics and Experimental Research Design, Center for Clinical and Translational Science, Rockefeller University, New York, USA.

Abstract

Major depressive disorder (MDD) is a primary psychiatric illness worldwide; there is a dearth of new mechanistic models for the development of better therapeutic strategies. Although we continue to discover individual biological factors, a major challenge is the identification of integrated, multidimensional traits underlying the complex heterogeneity of depression and treatment outcomes. Here, we set out to ascertain the emergence of the novel mitochondrial mediator of epigenetic function acetyl-L-carnitine (LAC) in relation to previously described individual predictors of antidepressant responses to the insulin-sensitizing agent pioglitazone. Herein, we report that i) subjects with MDD and shorter leukocyte telomere length (LTL) show decreased levels of LAC, increased BMI, and a history of specific types of childhood trauma; and that ii) these multidimensional factors spanning mitochondrial metabolism, cellular aging, metabolic function, and childhood trauma provide more detailed signatures to predict longitudinal changes in depression severity in response to pioglitazone than individual factors. The findings of multidimensional signatures involved in the pathophysiology of depression and their role in predicting treatment outcomes provide a starting point for the development of a mechanistic framework linking biological networks and environmental factors to clinical outcomes in pursuit of personalized medicine strategies to effectively treat MDD.

Keywords: Acetylcarnitine; Metabolism; Stress.