权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Genetic markers associated with brain structural abnormalities and drug use in human addiction

与人类成瘾中大脑结构异常和药物使用相关的遗传标记

基本信息

批准号：
9059066
负责人：
Scott J Moeller
金额：
$ 15.56万
依托单位：
ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-05-01 至 2020-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9059066
关键词：
Accounting Alleles Atlases Behavior Blood specimen Brain Brain imaging Brain region Candidate Disease Gene Clinical Cocaine Dependence Complex Corpus striatum structure Cues DNA Data Diagnosis Disease Dorsal Drug Addiction Drug usage Exhibits Functional disorder Future Gene Expression Gene Targeting Genes Genetic Genetic Markers Genetic Polymorphism Genetic Variation Goals Hand Health Human Image Individual Intervention Intervention Studies Knowledge Link Magnetic Resonance Imaging Maps Measures Methaqualone Modality Neurobiology Outcome Participant Pharmaceutical Preparations Pharmacogenetics Protocols documentation Psychotic Disorders Recruitment Activity Recurrent disease Relapse Research Resources Rewards Sampling Schizophrenia Self-control as a personality trait Single Nucleotide Polymorphism Structural defect Structure Sum Syndrome System Testing Time Transcript Urine addiction brain behavior brain morphology clinically relevant cocaine use complement C2a dopamine transporter drug relapse follow-up gene discovery genetic approach genetic information genetic variant genome wide association study gray matter imaging genetics innovation insight interest neuroimaging neuropsychiatric disorder novel predict clinical outcome primary outcome prospective response reward processing

项目摘要

DESCRIPTION (provided by applicant): Drug addiction is a chronically relapsing disease associated with deficits in brain function and structure in regions that underlie reward processing and self-control, manifesting as a pernicious syndrome of impaired response inhibition and salience attribution (iRISA). This syndrome is likely further modulated by select genetic variations that precede and/or exacerbate the addiction, evidenced by studies that have examined the influence of single nucleotide polymorphisms (SNPs) on brain and behavior. However, this approach is fundamentally limited insofar as individual SNPs (e.g., DAT1, MAOA) are likely to explain only a small portion of behavior in complex disorders such as addiction. To move the field forward, this proposal seeks to implement an innovative analysis pipeline to fundamentally expand upon the menu of genetic factors that may contribute to cocaine addiction (i.e., beyond traditional candidate genes) while simultaneously avoiding the potential pitfalls of genome-wide association (GWAS) studies (i.e., insufficient statistical power). The analysis pipeline proceeds according to the following steps, which will be applied to an already-collected sample (Sample 1) and a new, ongoing sample (Sample 2): (A) probing for group differences between individuals with cocaine use disorder (iCUD) and healthy controls (HC) in structural gray matter volume (GMV), a reliable and robust neuroimaging modality; (B) for those regions exhibiting between-group differences, using a freely-available brain Atlas to map and identify gene SNPs, coexpression networks, and region-specific transcripts; and (C) using DNA samples for empirical testing of these same select genes, SNPs, and networks in iCUD and HC for verification of influence. For Sample 2 specifically, an additional primary outcome of interest is the prospective prediction of future drug use in iCUD, assessed as part of 4 follow-up study sessions with multiple, valid objective and subjective drug use probes. In sum, this study uses a novel data-driven imaging genetics approach to identify previously uncharacterized genetic differences between iCUD and HC, which in turn will be used to correlate with brain morphology and predict drug-relevant outcomes in cocaine addiction.