Network Science Methodology for Assessing PTSD Risk

评估 PTSD 风险的网络科学方法

• 批准号: 7893201
• 负责人: GLENN N SAXE
• 金额: $ 1.27万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-15 至 2010-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7893201
• 关键词: Applications Grants; Area; Autistic Disorder; Behavioral; Bioinformatics; Biomedical Research; Burn injury; Cells; Child; Child Development; Coin; Communicable Diseases; Complex; Computational Biology; Data Set; Development; Disease; Dissociation; Emotional; Evaluation; Event; Exploratory/Developmental Grant; Exposure to; Failure; Family; Future; Gene Proteins; Genomics; Hippocampus (Brain); Hour; Human; Injury; Internet; Intervention; Knowledge; Lead; Link; Literature; Malignant Neoplasms; Medicine; Mental Health; Methodology; Modeling; Molecular; Nature; Outcome; Post-Traumatic Stress Disorders; Prevention; Problem behavior; Process; Property; Psychopathology; Refractory; Research; Research Methodology; Resistance; Risk; Risk Factors; Science; System; Time; Trauma; Work; aged; base; functional disability; high risk infant; infancy; medical schools; reconstruction; self organization; social; young adult

DESCRIPTION (provided by applicant): 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.

描述（由申请人提供）：本申请旨在将一种称为网络科学（NS）的相对较新的研究方法带入对PTSD复杂和多确定的心理病理学的风险因素的理解。网络科学已在科学追求的许多领域应用，以了解最大程度地促进复杂现象的出现和持久性的变量。 NS的方法可以确定一组变量是否形成所谓的“复杂自适应系统（CAS）”的属性。 CAS的基本特性包括自组织，自我维持和鲁棒性。 CAS可以从天然（例如细胞，疾病）或人为（例如互联网，经济）现象中出现。一旦出现CAS，这种复杂的变量系统就会对外部挑战具有高度抵抗力。这种观点影响了许多重要领域（例如癌症，传染病，自闭症）和“网络医学”一词的生物医学研究，以描述NS在生物医学研究中的应用。该应用程序汇集了一个具有不同专业知识领域的团队，非常适合将NS应用于PTSD的风险因素研究。这项拟议的研究中介绍了以下领域的专业知识：1）PTSD的生物行为危险因素，2）PTSD的基因组学，3）计算生物学和生物信息学，4）儿童发育和5）5）与PTSD相关的纵向研究方法。该团队将共同努力，以确定与PTSD相关的一组复杂的变量是否可能构成复杂的自适应系统；以及这种系统的鲁棒性能是否导致PTSD的治疗性质。网络科学方法将应用于1）对两个引人注目的纵向数据集的分析，这些数据集包含非常适合理解PTSD的系统性特性的信息； 2）基于有关PTSD（和相关疾病）之间关系的可用信息查询，创建了PTSD的分子网络重建；以及与这些疾病相关的基因和蛋白质。如果NS揭示了与创伤性暴露和PTSD相关的复杂自适应系统，则可以通过了解这种系统如何持续或失败来实质性地了解治疗PTSD的干预方法。该应用程序旨在将一种称为网络科学（NS）的相对较新的研究方法带入对PTSD复杂而多确定的心理病理学的风险因素的理解。网络科学已在科学追求的许多领域应用，以了解最大程度地促进复杂现象的出现和持久性的变量。 NS的方法可以确定一组变量是否形成所谓的“复杂自适应系统（CAS）”的属性。如果NS揭示了与创伤性暴露和PTSD相关的复杂自适应系统，则可以通过了解这种系统如何持续或失败来实质性地了解治疗PTSD的干预方法。