Genetics of Alcohol Dependence in American Populations

美国人酒精依赖的遗传学

基本信息

  • 批准号:
    7657224
  • 负责人:
  • 金额:
    $ 64.02万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2009
  • 资助国家:
    美国
  • 起止时间:
    2009-03-01 至 2014-02-28
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Genetic factors contribute to the development of alcohol dependence (AD). Substantial progress has been made in identifying specific risk genes, but currently known well-supported loci still account for only a small proportion of the overall disease risk. In the last iteration of this project, we recruited and rigorously assessed ~2000 AD subjects and relatives, with oversampling of African Americans (AAs); we also contributed to the understanding of AD risk though candidate gene studies of AD and related phenotypes, and gene-by-environment interaction involving AD risk (with mapping by admixture linkage disequilibrium studies currently in progress). It is widely appreciated that whole genome association studies (WGAS) have the potential to reveal more risk loci. The quality of such studies is always limited by the quality of the available phenotypic assessments; our investment in state-of-the-art phenotypic characterization has resulted in a sample that should be an outstanding one to probe for novel risk loci by this method. In the present application, we propose to recruit an additional 1250 AD subjects (primarily AAs and EAs); and to conduct a WGAS study of 2000 European American AD subjects and 4000 controls in two waves of 1000 affecteds and 2000 controls; and follow-up studies of implicated loci (in an expanded sample of already-collected AD subjects and a large sample of German AD affecteds and controls) via SNP genotyping and deep sequencing. Additionally, we will study high resolution copy number variation (CNV) in a subsample of AD subjects. When both waves of the study have been completed, we will be able to study subphenotypes within the sample (e.g., family history positive vs. negative, AD with or without other substance dependence comorbidity), both in case-only comparisons and in comparison to control subjects. A companion WGAS application with already-collected AA samples has been contingently-approved by CIDR for genotyping. The current project could provide the opportunity for instructive comparison of risk loci between AA and EA populations, with the potential to isolate associated regions. This project has the potential to contribute substantially to our growing knowledge of genetic risk factors for AD and related traits. PUBLIC HEALTH RELEVANCE: Alcohol dependence is genetically influenced. The main purpose of this project is to use a new and powerful technique, genomewide association analysis, to identify genes that influence risk for alcohol dependence. Successful completion of this research would be expected to increase our understanding of alcohol dependence, and potentially to lead to early identification of susceptible individuals, and to new treatments.
描述(申请人提供):遗传因素导致酒精依赖(AD)的发展。在识别特定的风险基因方面已经取得了实质性的进展,但目前已知的得到良好支持的基因座仍然只占总体疾病风险的一小部分。在这个项目的最后一次迭代中,我们招募了大约2000名AD受试者和亲属,并对非裔美国人(AAs)进行了过度抽样;我们还通过AD及其相关表型的候选基因研究,以及涉及AD风险的基因与环境的相互作用(目前正在进行的混合连锁不平衡研究),对AD风险的理解做出了贡献。人们普遍认为,全基因组关联研究(WGA)有可能揭示更多的风险基因座。这类研究的质量总是受到可用表型评估的质量的限制;我们对最先进的表型特征的投资已经产生了一个应该是通过这种方法探索新风险基因的优秀样本。在目前的应用中,我们建议额外招募1250名AD受试者(主要是AAs和EAs);并对2000名欧美AD受试者和4000名对照进行WGA研究,分两波进行1000名受试者和2000名对照;通过SNP基因分型和深度测序对相关基因座进行后续研究(在已收集的AD受试者和德国AD受试者和对照的扩大样本中)。此外,我们还将研究AD受试者的高分辨率拷贝数变异(CNV)。当两波研究完成后,我们将能够研究样本中的亚型(例如,家族史阳性与阴性,AD合并或不合并其他物质依赖),无论是在病例比较中还是在与对照对象的比较中。已收集的AA样本的配套WGA应用程序已被CIDR紧急批准用于基因分型。目前的项目可能提供机会对AA和EA人群之间的风险基因进行有启发性的比较,并有可能分离相关区域。这个项目有可能对我们不断增长的AD遗传风险因素和相关特征的知识做出实质性的贡献。与公共健康相关:酒精依赖受基因影响。这个项目的主要目的是使用一种新的、功能强大的技术-全基因组关联分析-来识别影响酒精依赖风险的基因。这项研究的成功完成将有望增加我们对酒精依赖的了解,并有可能导致早期识别易感人群,并找到新的治疗方法。

项目成果

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JOEL GELERNTER其他文献

JOEL GELERNTER的其他文献

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{{ truncateString('JOEL GELERNTER', 18)}}的其他基金

The Robert T. Malison Yale-Chulalongkorn Stress, Alcohol Use and Psychopathology Training Program
罗伯特·T·马利森耶鲁-朱拉隆功压力、酒精使用和精神病理学培训计划
  • 批准号:
    10665205
  • 财政年份:
    2023
  • 资助金额:
    $ 64.02万
  • 项目类别:
Genomics of PTSD and Related Traits
PTSD 和相关特征的基因组学
  • 批准号:
    10292943
  • 财政年份:
    2019
  • 资助金额:
    $ 64.02万
  • 项目类别:
Genetics of Alcohol Dependence in African Americans: Recruitment
非裔美国人酒精依赖的遗传学:招募
  • 批准号:
    10474310
  • 财政年份:
    2018
  • 资助金额:
    $ 64.02万
  • 项目类别:
Genetics of Alcohol Dependence in African Americans: Recruitment
非裔美国人酒精依赖的遗传学:招募
  • 批准号:
    9769607
  • 财政年份:
    2018
  • 资助金额:
    $ 64.02万
  • 项目类别:
Identifying Methamphetamine Risk Variants by Extreme Phenotype Exome Sequencing
通过极端表型外显子组测序识别甲基苯丙胺风险变异体
  • 批准号:
    9086352
  • 财政年份:
    2015
  • 资助金额:
    $ 64.02万
  • 项目类别:
Identifying Methamphetamine Risk Variants by Extreme Phenotype Exome Sequencing
通过极端表型外显子组测序识别甲基苯丙胺风险变异体
  • 批准号:
    9280890
  • 财政年份:
    2015
  • 资助金额:
    $ 64.02万
  • 项目类别:
Identifying Methamphetamine Risk Variants by Extreme Phenotype Exome Sequencing
通过极端表型外显子组测序识别甲基苯丙胺风险变异体
  • 批准号:
    9920116
  • 财政年份:
    2015
  • 资助金额:
    $ 64.02万
  • 项目类别:
Methamphetamine and Other Substance Use Disorder Genetics in Thailand
泰国的甲基苯丙胺和其他药物使用障碍遗传学
  • 批准号:
    10585560
  • 财政年份:
    2015
  • 资助金额:
    $ 64.02万
  • 项目类别:
Identifying Methamphetamine Risk Variants by Extreme Phenotype Exome Sequencing
通过极端表型外显子组测序识别甲基苯丙胺风险变异体
  • 批准号:
    9456704
  • 财政年份:
    2015
  • 资助金额:
    $ 64.02万
  • 项目类别:
Genetics of Anxiety Disorders
焦虑症的遗传学
  • 批准号:
    8542156
  • 财政年份:
    2013
  • 资助金额:
    $ 64.02万
  • 项目类别:

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Genetic & Social Determinants of Health: Center for Admixture Science and Technology
遗传
  • 批准号:
    10818088
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非裔美国人冠心病和相关代谢组标记物的混合图谱
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    10590405
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NSF Postdoctoral Fellowship in Biology: Coalescent Modeling of Sex Chromosome Evolution with Gene Flow and Analysis of Sexed-versus-Gendered Effects in Human Admixture
NSF 生物学博士后奖学金:性染色体进化与基因流的合并模型以及人类混合中性别与性别效应的分析
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Admixture mapping of mosaic copy number alterations for identification of cancer drivers
用于识别癌症驱动因素的马赛克拷贝数改变的混合图谱
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Leveraging the Microbiome, Local Admixture, and Machine Learning to Optimize Anticoagulant Pharmacogenomics in Medically Underserved Patients
利用微生物组、局部混合物和机器学习来优化医疗服务不足的患者的抗凝药物基因组学
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    2022
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