Gene coexpression patterns predict opiate-induced brain-state transitions

Proceedings of the National Academy of Sciences, vol. 117, pp. 19556–19565

Abstract

Opioid addiction is a chronic, relapsing disorder associated with persistent changes in brain plasticity. Reconfiguration of neuronal connectivity may explain heightened abuse liability in individuals with a history of chronic drug exposure. To characterize network-level changes in neuronal activity induced by chronic opiate exposure, we compared FOS expression in mice that are morphine-naïve, morphine-dependent, or have undergone 4 wk of withdrawal from chronic morphine exposure, relative to saline-exposed controls. Pairwise interregional correlations in FOS expression data were used to construct network models that reveal a persistent reduction in connectivity strength following opiate dependence. Further, we demonstrate that basal gene expression patterns are predictive of changes in FOS correlation networks in the morphine-dependent state. Finally, we determine that regions of the hippocampus, striatum, and midbrain are most influential in driving transitions between opiate-naïve and opiate-dependent brain states using a control theoretic approach. This study provides a framework for predicting the influence of specific therapeutic interventions on the state of the opiate-dependent brain.

Authors 7

1. Julia K. Brynildsen

   University of Pennsylvania

   Affiliation as printed

   Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104;

2. Kyla D. Mace

   University of Pennsylvania

   Affiliation as printed

   Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104;

3. Eli J. Cornblath

   University of Pennsylvania

   Affiliation as printed

   Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104;

   Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104;

   Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104;

   Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA 19104;

   Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104;

4. Carmen Weidler Aachen Department of Psychiatry, Psychotherapy and Psychosomatics Faculty of Medicine

   RWTH Aachen University

   Affiliation as printed

   Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, Germany;

5. Fabio Pasqualetti

   University of California, Riverside

   Affiliation as printed

   Department of Mechanical Engineering, University of California, Riverside, CA 92521;

6. Danielle S. Bassett

   University of Pennsylvania

   Affiliation as printed

   Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104;

   Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104;

   Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104;

   Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA 19104;

   Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104;

7. Julie A. Blendy

   University of Pennsylvania

   Affiliation as printed

   Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104;