This application seeks to bring a relatively new research methodology called Network Science (NS) to the understanding of risk factors for the complex and multi-determined psychopathology of PTSD. Network Science has been applied, in many areas of scientific pursuit, to understand the variables that most contribute to the emergence and persistence of complex phenomena. The methodology of NS enables the determination of whether a given set of variables develops the properties of what has been termed a 'Complex Adaptive System (CAS)'. The essential properties of a CAS include self-organization, self- sustenance, and robustness. A CAS can emerge from natural (e.g. a cell, a disease) or human-made (e.g. the internet, an economy) phenomena. Once a CAS emerges, this complex system of variables becomes highly resistant to external challenge. This perspective has influenced biomedical research in a number of important areas (e.g. cancer, infectious disease, autism) and the term 'Network Medicine'has been coined to describe the application of NS to biomedical research. This application brings together a team with diverse areas of expertise ideally suited to the application of NS to risk factor research for PTSD. Expertise in the following areas is featured in this proposed research: 1) bio-behavioral risk factors for PTSD, 2) genomics of PTSD, 3) computational biology and bioinformatics, 4) child development, and 5) longitudinal research methodology related to PTSD. This team will work together to determine if a complex set of variables related to PTSD may constitute a Complex Adaptive System;and whether the robust properties of such a system lead to the treatment refractory nature of PTSD. Network Science methodology will be applied to 1) the analysis of two compelling longitudinal datasets that contain information ideally suited to understanding the systemic properties of PTSD;and 2) the creation of a Molecular Network Reconstruction of PTSD based on queries of available information on the relationship between PTSD (and related disorders);and the genes and proteins associated with these disorders. If NS reveals a Complex Adaptive System related to traumatic exposure and PTSD, intervention approaches to treat PTSD can be substantially informed by understanding how such a system persists or fails. This application seeks to bring a relatively new research methodology called Network Science (NS) to the understanding of risk factors for the complex and multi-determined psychopathology of PTSD. Network Science has been applied, in many areas of scientific pursuit, to understand the variables that most contribute to the emergence and persistence of complex phenomena. The methodology of NS enables the determination of whether a given set of variables develops the properties of what has been termed a 'Complex Adaptive System (CAS)'. If NS reveals a Complex Adaptive System related to traumatic exposure and PTSD, intervention approaches to treat PTSD can be substantially informed by understanding how such a system persists or fails.

Public Health Relevance

This application seeks to bring a relatively new research methodology called Network Science (NS) to the understanding of risk factors for the complex and multi-determined psychopathology of PTSD. Network Science has been applied, in many areas of scientific pursuit, to understand the variables that most contribute to the emergence and persistence of complex phenomena. The methodology of NS enables the determination of whether a given set of variables develops the properties of what has been termed a 'Complex Adaptive System (CAS)'. If NS reveals a Complex Adaptive System related to traumatic exposure and PTSD, intervention approaches to treat PTSD can be substantially informed by understanding how such a system persists or fails.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21MH086309-01
Application #
7680858
Study Section
Special Emphasis Panel (ZMH1-ERB-N (04))
Program Officer
Tuma, Farris K
Project Start
2009-07-15
Project End
2011-06-30
Budget Start
2009-07-15
Budget End
2010-06-30
Support Year
1
Fiscal Year
2009
Total Cost
$229,736
Indirect Cost
Name
Children's Hospital Boston
Department
Type
DUNS #
076593722
City
Boston
State
MA
Country
United States
Zip Code
02115
Saxe, Glenn N; Ma, Sisi; Ren, Jiwen et al. (2017) Machine learning methods to predict child posttraumatic stress: a proof of concept study. BMC Psychiatry 17:223
Zhu, Qisha; Wang, Jiawei; Shen, Chanchan et al. (2017) Inhibitory brainstem reflexes under external emotional-stimuli in bipolar I and II disorders. BMC Psychiatry 17:224
Saxe, Glenn N; Statnikov, Alexander; Fenyo, David et al. (2016) A Complex Systems Approach to Causal Discovery in Psychiatry. PLoS One 11:e0151174
Roberts, Andrea L; Glymour, M Maria; Koenen, Karestan C (2013) Does maltreatment in childhood affect sexual orientation in adulthood? Arch Sex Behav 42:161-71
Amstadter, Ananda B; Nugent, Nicole R; Yang, Bao-Zhu et al. (2011) Corticotrophin-releasing hormone type 1 receptor gene (CRHR1) variants predict posttraumatic stress disorder onset and course in pediatric injury patients. Dis Markers 30:89-99
Roberts, Andrea L; McLaughlin, Katie A; Conron, Kerith J et al. (2011) Adulthood stressors, history of childhood adversity, and risk of perpetration of intimate partner violence. Am J Prev Med 40:128-38