Section Corrected Panatzatos Identification and characterization of genomic factors involved in maintaining brain circuits and neurotransmitter systems associated with psychopathological behavior could identify new therapeutic targets and elucidate mechanisms of psychopathology. Using recently available human postmortem brain gene expression maps (Allen Brain Atlas) and methods to quantify large-scale in vivo functional connectivity (FC) from fMRI data, the proposed project will develop and validate new computational tools which relate functional network architecture to molecular neuroanatomy in order to identify and characterize genomic risk factors for major depressive disorder (MDD) and suicide. Our pilot data demonstrate correlations between gene expression and FC, suggesting sufficient inter-individual consistency in their spatial distributions to allow detection of genes whose expression predict FC. Separate streams of research have linked abnormalities in FC related to resting state and negative valence processing to MDD and suicidal behavior. Dysregulated genomic factors that are involved in these specific circuits are more likely to confer risk towards these disorders.
Aim 1 is to develop and validate computational approaches that identify genes whose expression predict FC associated with resting state and negative valence processing.
Aim 2 is to test whether these genes are also dysregulated in MDD and suicide using a distinct genomics dataset, which would suggest translational value for the approach developed in Aim 1. A Corollary Aim is to create publically available, open-source tools which can be applied to identify genomic factors related to other RDoC constructs using task and resting-state fMRI. It is anticipated this project will facilitate evidence-based identification of psychiatric biomarkers and hypothesis generation. Results would also elucidate the relationships of genes with neural circuits and psychopathology at the NIMH Research Domain Criteria (RDoC) level and further our understanding of the molecular biology of brain functional architecture, mood disorders and suicidal behavior. To carry out these aims and attain my career goal of becoming an expert in translational neuroinformatics, the PI has mapped out a course of further training in clinical and molecular neuroscience, computational genomics, computer science and informatics and advanced statistics. This training will complement and build upon the PI?s previous training in cellular physiology, cognitive neuroscience and computational neuroimaging.

Public Health Relevance

Section Depression is a disease with significant public health and economic burden, for which currently available treatments are not effective in the majority of patients. This proposal investigates the neurobiological mechanisms that determine antidepressant response and treatment-resistance, with a specific focus on molecular signaling pathways that regulate neuronal network activity in the hippocampal dentate gyrus, a key brain region involved in mood and cognition. This work will help to discover new targets for improved antidepressant treatments.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
1K01MH108721-01
Application #
9013842
Study Section
Adult Psychopathology and Disorders of Aging Study Section (APDA)
Program Officer
Van'T Veer, Ashlee V
Project Start
2016-04-01
Project End
2020-03-31
Budget Start
2016-04-01
Budget End
2017-03-31
Support Year
1
Fiscal Year
2016
Total Cost
Indirect Cost
Name
New York State Psychiatric Institute
Department
Type
DUNS #
167204994
City
New York
State
NY
Country
United States
Zip Code
10032
Zanderigo, Francesca; Pantazatos, Spiro; Rubin-Falcone, Harry et al. (2018) In vivo relationship between serotonin 1A receptor binding and gray matter volume in the healthy brain and in major depressive disorder. Brain Struct Funct 223:2609-2625
Ritchie, Jacob; Pantazatos, Spiro P; French, Leon (2018) Transcriptomic characterization of MRI contrast with focus on the T1-w/T2-w ratio in the cerebral cortex. Neuroimage 174:504-517
Zong, Xiaofen; Hu, Maolin; Pantazatos, Spiro P et al. (2018) A Dissociation in Effects of Risperidone Monotherapy on Functional and Anatomical Connectivity Within the Default Mode Network. Schizophr Bull :
Galgano, Jessica; Pantazatos, Spiro; Allen, Kachina et al. (2018) Functional connectivity of PAG with core limbic system and laryngeal cortico-motor structures during human phonation. Brain Res :
Milak, Matthew S; Pantazatos, Spiro; Rashid, Rain et al. (2018) Higher 5-HT1A autoreceptor binding as an endophenotype for major depressive disorder identified in high risk offspring - A pilot study. Psychiatry Res Neuroimaging 276:15-23
Pantazatos, Spiro P; Li, Xinyi (2017) Commentary: BRAIN NETWORKS. Correlated Gene Expression Supports Synchronous Activity in Brain Networks. Science 348, 1241-4. Front Neurosci 11:412
Pantazatos, S P; Huang, Y-Y; Rosoklija, G B et al. (2017) Whole-transcriptome brain expression and exon-usage profiling in major depression and suicide: evidence for altered glial, endothelial and ATPase activity. Mol Psychiatry 22:760-773
Yin, Honglei; Galfalvy, Hanga; Pantazatos, Spiro P et al. (2016) GLUCOCORTICOID RECEPTOR-RELATED GENES: GENOTYPE AND BRAIN GENE EXPRESSION RELATIONSHIPS TO SUICIDE AND MAJOR DEPRESSIVE DISORDER. Depress Anxiety 33:531-540
Hu, Mao-Lin; Zong, Xiao-Fen; Zheng, Jun-Jie et al. (2016) Short-term Effects of Risperidone Monotherapy on Spontaneous Brain Activity in First-episode Treatment-naïve Schizophrenia Patients: A Longitudinal fMRI Study. Sci Rep 6:34287
Hu, M; Zong, X; Zheng, J et al. (2016) Risperidone-induced topological alterations of anatomical brain network in first-episode drug-naive schizophrenia patients: a longitudinal diffusion tensor imaging study. Psychol Med 46:2549-60

Showing the most recent 10 out of 11 publications