Dissecting the molecular aetiology of complex traits using high dimensional omic data
使用高维组学数据剖析复杂性状的分子病因学
基本信息
- 批准号:MR/S003886/1
- 负责人:
- 金额:$ 39.03万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Fellowship
- 财政年份:2018
- 资助国家:英国
- 起止时间:2018 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The discovery of genetic variants associated with complex traits is increasing at an exponential rate. It is now of vital importance to develop our understanding of the molecular mechanisms which can help explain these findings, in order to improve our capability to prevent and treat disease. Advancements in high-throughput sequencing technologies present an unprecedented opportunity to address this challenge and ascertain the biological and clinical relevance of results from genome-wide association studies (GWAS). However, there is an increasing abundance of data being generated on diverse types of molecular "omic" traits, accompanied by the rapid development of partially overlapping and often untested methodologies. To overcome this challenge, there needs to be focused research into the most appropriate and efficient manner to harness large-scale 'omic data to elucidate the molecular determinants of complex disease.The research outlined in this fellowship proposal can be delineated into five categories, with the overall aim of harnessing large-scale data to improve patient healthcare in-line with the UK's industrial strategy. The opportunity presented by HDR-UK will allow me to address some of the most crucial limitations in molecular aetiology. Specifically, there needs to be extensive research into tissue-specificity for 'omic traits, systematic frameworks to appropriately appraise molecular mediation and methods to improve causal inference in this paradigm. I also intend on applying novel, state-of-art-methods to available 'omic data to elucidate findings which have translational value for therapeutic evaluation. Finally, I will build publicly accessible computational tools to automate fundamental analyses in this paradigm and resources to disseminate the findings of this fellowship. Using health informatics to harness large-scale, high throughput data to develop our understanding of the causal pathway from genetic variation to complex disease is the overarching theme of this research project. This research will lead to several high impact publications to improve our understanding of the molecular determinants of disease, as well as web tools that should help disseminate the product of this project and also assist colleagues with their endeavors in this field. As such, this work most closely aligns with the HDR-UK priorities concerning health informatics and accelerating medicines discovery.
与复杂性状相关的遗传变异的发现正以指数速度增加。现在至关重要的是发展我们对分子机制的理解,这可以帮助解释这些发现,以提高我们预防和治疗疾病的能力。高通量测序技术的进步为解决这一挑战和确定全基因组关联研究(GWAS)结果的生物学和临床相关性提供了前所未有的机会。然而,有越来越丰富的数据正在产生的不同类型的分子“组学”性状,伴随着部分重叠,往往未经测试的方法的快速发展。为了克服这一挑战,需要集中研究最合适和最有效的方式来利用大规模的“组学数据,以阐明复杂疾病的分子决定因素。本奖学金提案中概述的研究可以分为五类,总体目标是利用大规模数据,以改善患者的医疗保健符合英国的产业战略。联合王国人类发展报告提供的机会将使我能够解决分子病因学中一些最关键的局限性。具体而言,需要对组学性状的组织特异性进行广泛的研究,适当评估分子介导的系统框架和改进这种范式中因果推理的方法。我还打算将新的、最先进的方法应用于现有的组学数据,以阐明对治疗评价具有转化价值的发现。最后,我将建立公共可访问的计算工具,以自动化基本分析在这个范例和资源,以传播这个奖学金的结果。利用健康信息学来利用大规模,高通量数据来发展我们对从遗传变异到复杂疾病的因果途径的理解是本研究项目的首要主题。这项研究将导致几个高影响力的出版物,以提高我们对疾病的分子决定因素的理解,以及网络工具,应该有助于传播这个项目的产品,也有助于同事们在这一领域的努力。因此,这项工作与联合王国人类发展报告关于卫生信息学和加速药物发现的优先事项最为一致。
项目成果
期刊论文数量(9)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Leveraging brain cortex-derived molecular data to elucidate epigenetic and transcriptomic drivers of neurological function and disease
利用大脑皮层衍生的分子数据来阐明神经功能和疾病的表观遗传和转录组驱动因素
- DOI:10.1101/429134
- 发表时间:2018
- 期刊:
- 影响因子:0
- 作者:Hatcher C
- 通讯作者:Hatcher C
Combined effect of PNPLA3, TM6SF2, and HSD17B13 variants on risk of cirrhosis and hepatocellular carcinoma in the general population
PNPLA3、TM6SF2 和 HSD17B13 变异对普通人群肝硬化和肝细胞癌风险的综合影响
- DOI:10.1016/j.atherosclerosis.2021.06.120
- 发表时间:2021
- 期刊:
- 影响因子:5.3
- 作者:Gellert-Kristensen H
- 通讯作者:Gellert-Kristensen H
Identifying drug targets for neurological and psychiatric disease via genetics and the brain transcriptome.
- DOI:10.1371/journal.pgen.1009224
- 发表时间:2021-01
- 期刊:
- 影响因子:4.5
- 作者:Baird DA;Liu JZ;Zheng J;Sieberts SK;Perumal T;Elsworth B;Richardson TG;Chen CY;Carrasquillo MM;Allen M;Reddy JS;De Jager PL;Ertekin-Taner N;Mangravite LM;Logsdon B;Estrada K;Haycock PC;Hemani G;Runz H;Smith GD;Gaunt TR;AMP-AD eQTL working group
- 通讯作者:AMP-AD eQTL working group
Separating the genetics of childhood and adult obesity: a validation study of genetic scores for body mass index in adolescence and adulthood in the HUNT Study.
- DOI:10.1093/hmg/ddaa256
- 发表时间:2021-02-25
- 期刊:
- 影响因子:3.5
- 作者:Brandkvist M;Bjørngaard JH;Ødegård RA;Åsvold BO;Smith GD;Brumpton B;Hveem K;Richardson TG;Vie GÅ
- 通讯作者:Vie GÅ
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Thomas Richardson其他文献
Left-handed fighters are overrepresented and more successful in combat sports
左撇子拳击手在格斗运动中所占比例较高且更为成功
- DOI:
10.17605/osf.io/x3unr - 发表时间:
2019 - 期刊:
- 影响因子:0
- 作者:
Thomas Richardson - 通讯作者:
Thomas Richardson
Young, formidable men show greater sensitivity to facial cues of dominance
年轻而强大的男性对面部主导地位的暗示更加敏感
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:5.1
- 作者:
Thomas Richardson;M. Waddington;R. Tucker Gilman - 通讯作者:
R. Tucker Gilman
Does Childhood Trauma Predict Impulsive Spending in Later Life? An Analysis of the Mediating Roles of Impulsivity and Emotion Regulation
童年创伤是否预示着晚年的冲动消费?
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Thomas Richardson;Annelise Egglishaw;Monica Sood - 通讯作者:
Monica Sood
Generalizing minimum safe operating altitudes for fixed‐wing UAVs in real‐time
实时概括固定翼无人机的最低安全操作高度
- DOI:
10.1002/rob.22331 - 发表时间:
2024 - 期刊:
- 影响因子:8.3
- 作者:
Ashford Milne;Alex McConville;Thomas Richardson;Matt Watson;Ben Schellenberg - 通讯作者:
Ben Schellenberg
The effect of SiC additives on the cycling performance of CaCOsub3/sub when used as a high-temperature thermal battery
碳化硅添加剂对碳酸钙作为高温热电池时循环性能的影响
- DOI:
10.1016/j.jallcom.2022.167844 - 发表时间:
2023-02-10 - 期刊:
- 影响因子:6.300
- 作者:
Thomas Richardson;Rajani K. Vijayaraghavan;Patrick J. McNally;M. Veronica Sofianos - 通讯作者:
M. Veronica Sofianos
Thomas Richardson的其他文献
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{{ truncateString('Thomas Richardson', 18)}}的其他基金
Autonomous Drones for Nature Conservation Missions
用于自然保护任务的自主无人机
- 批准号:
EP/X029077/1 - 财政年份:2023
- 资助金额:
$ 39.03万 - 项目类别:
Research Grant
Collaborative Research: Graphical and Algebraic Models for Multivariate Categorical Data
协作研究:多元分类数据的图形和代数模型
- 批准号:
0505865 - 财政年份:2005
- 资助金额:
$ 39.03万 - 项目类别:
Standard Grant
Graphical Markov Models with Interpretable Structure
具有可解释结构的图形马尔可夫模型
- 批准号:
9972008 - 财政年份:1999
- 资助金额:
$ 39.03万 - 项目类别:
Continuing Grant
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