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A framework enabling the genomic analysis of psychiatric traits across admixed populations.

A framework enabling the genomic analysis of psychiatric traits across admixed populations.
一个能够对混合人群的精神特征进行基因组分析的框架。
批准号:
10470343
负责人:
Elizabeth Grace Atkinson
金额:
$17.38万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-23 至 2023-09-10

项目摘要

项目成果

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中文摘要
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英文摘要
PROJECT SUMMARY/ABSTRACT Globally, neuropsychiatric disorders are the leading cause of disability. Despite recent advances in mental health genetics in Eurasian groups, major limitations remain in the understanding of psychiatric disorders in minority populations, in particular “admixed” groups of mixed ancestry. Due to the paucity of methodological approaches that account for their additional genomic complexity, admixed populations are systematically excluded from psychiatric genomic studies. Admixed populations, including African American and Latino individuals, make up more than a third of the US populace and have higher rates of some anxiety disorders including PTSD, yet these groups face severe disparities in mental health research and treatment due to being so sorely underrepresented in psychiatric genomics. To reap full and equitable benefits from efforts including All of Us, NeuroGAP, and the PGC, there is a pressing unmet need for the development of tools permitting the study of psychiatric traits in admixed peoples. The candidate proposes to address this issue by developing a suite of statistical methods, software packages, and analytical resources. Dr. Atkinson will: 1a) build a tool to allow for the integration of admixed individuals into psychiatric GWAS; 1b) aggregate a significantly expanded Native American reference panel to improve genomic inference in admixed American populations; 2a) characterize the genetic basis of traits relevant to psychiatric disorders in diverse populations of the largest biobank dataset; 2b) leverage the linkage disequilibrium in admixed individuals to improve fine-mapping; and 3) develop a statistical method that generates reliable genetic risk scores for psychiatric traits in admixed subjects. These efforts fill a major gap in existing resources and will improve our understanding of psychiatric diseases in diverse groups whom medical genomics has so far failed. These efforts are in direct line with the strategic mission of the NIMH, highlighting the crucial and timely nature of the proposed project. The proposed research and training plan were carefully designed to confer expertise in three domains: 1) phenotypes and genetic architectures of psychiatric disorders, 2) statistical methods development, and 3) professional development. These skills are fundamental to the candidate’s goal of becoming a leading investigator who develops and applies statistical genomics to understand psychiatric disorders across diverse populations. In addition to research training, Dr. Atkinson will take coursework, participate in regular seminars, attend workshops and conferences, and gain mentorship and teaching experience locally and in Africa. All research will be conducted in the Analytic and Translational Genetics Unit at Massachusetts General Hospital, the Broad Institute, and the Harvard TH Chan School of Public Health with mentorship from renowned scientists Drs. Mark Daly and Karestan Koenen. Additional guidance from leading experts Drs. Ben Neale, Alkes Price, and Jordan Smoller will ensure exceptional guidance and support. Overall, the training environment is outstanding, the mentors and advisors are world-class, the proposed studies address an urgent unmet need, and the additional skills gained in this award will poise Dr. Atkinson to establish independent leadership in population, statistical, and psychiatric genomics.
期刊论文(5)
专著(0)
科研奖励(0)
会议论文
Estimation of cross-ancestry genetic correlations within ancestry tracts of admixed samples.
混合样本祖先区域内跨祖先遗传相关性的估计。
DOI: 10.1038/s41588-023-01325-x
发表时间: 2023
期刊: Nature genetics
影响因子: 30.8
作者: [Atkinson,ElizabethG]
通讯作者: Atkinson,ElizabethG
Reply to: On powerful GWAS in admixed populations.
回复:关于混合人群中强大的 GWAS。
DOI: 10.1038/s41588-021-00975-z
发表时间: 2021
期刊: Nature genetics
影响因子: 30.8
作者: [Atkinson,ElizabethG, Bloemendal,Alex, Maihofer,AdamX, Nievergelt,CarolineM, Daly,MarkJ, Neale,BenjaminM]
通讯作者: Neale,BenjaminM
DOI: 10.1146/annurev-biodatasci-020722-014310
发表时间: 2023
期刊: Annual review of biomedical data science
影响因子: --
作者: [Tan,Taotao, Atkinson,ElizabethG]
通讯作者: Atkinson,ElizabethG
Machine Learning and Health Care: Potential Benefits and Issues.
机器学习和医疗保健:潜在的好处和问题。
DOI: 10.1097/jac.0000000000000453
发表时间: 2023
期刊: The Journal of ambulatory care management
影响因子: --
作者: [Atkinson,JGraham, Atkinson,ElizabethG]
通讯作者: Atkinson,ElizabethG
Empowering gene discovery and accelerating clinical translation for diverse admixed populations
  • 批准号:
    10584936
  • 项目类别:
  • 资助金额:
    $78.2万
  • 财政年份:
    2023
  • 负责人:
    Elizabeth Grace Atkinson
  • 依托单位:
A framework enabling the genomic analysis of psychiatric traits across admixed populations.
  • 批准号:
    10405367
  • 项目类别:
  • 资助金额:
    $17.44万
  • 财政年份:
    2019
  • 负责人:
    Elizabeth Grace Atkinson
  • 依托单位:
A framework enabling the genomic analysis of psychiatric traits across admixed populations.
  • 批准号:
    10022335
  • 项目类别:
  • 资助金额:
    $18.52万
  • 财政年份:
    2019
  • 负责人:
    Elizabeth Grace Atkinson
  • 依托单位:
海外基金