Beyond Association: Predictive Modeling of Nicotine Dependance
Beyond Association: Predictive Modeling of Nicotine Dependance
批准号:
7617627
负责人:
GIL ALTEROVITZ
金额:
$17.5万
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-05-01 至 2013-04-30
关键词:
Artificial IntelligenceClinicalComplexComputing MethodologiesDataData SetDental SchoolsDependenceDependencyDiagnosisEconomicsEnrollmentFundingFunding AgencyGenesGeneticGenetic VariationGenomeGoalsHumanIndividualMeasuresMedicineModelingMolecularNational Institute of Drug AbuseNicotineNicotine DependencePharmacologic SubstancePhysiological ProcessesPopulationPositioning AttributePreventivePrincipal InvestigatorProcessResearchResearch PersonnelResourcesRiskSiteSmokerSmokingSocietiesSourceTechniquesTobacco useTranslatingValidationVariantbasecigarette smokingclinical practicecomputer based statistical methodscostgenetic variantgenome wide association studygenome-wideinnovationmortalitynovelpredictive modelingprognosticprogramssmoking cessationstatisticstooltrait
中文摘要
烟草使用,主要是吸烟,是世界上可预防死亡的最大来源,仅在美国就造成了超过1.6亿美元的健康相关经济损失。尼古丁依赖是吸烟者继续吸烟的主要原因,并且大多数无辅助戒烟尝试在一周内失败。众所周知,尼古丁依赖具有遗传成分,但它是一种复杂的性状,即,没有单一的基因是尼古丁依赖的原因。因此,研究人员和资助机构投入了相当大的努力和支持,通过全基因组扫描来确定该性状的遗传基础,使我们在确定尼古丁依赖的全球遗传预测因子方面处于独特的地位。本研究提出通过实现两个特定目标来实现NIDA资助的尼古丁依赖性协作遗传研究(COGEND)全基因组数据的承诺:(1)使用称为贝叶斯网络的尖端计算方法来识别尼古丁依赖复杂性状的遗传变异集,以及(2)在完全独立的人群中验证预后模型。这一提议代表了一个更广泛的研究计划的第一步,该计划旨在发现尼古丁依赖背后复杂的相互作用网络。该计划的最终结果将提供一种临床工具,该工具将准确评估依赖风险,允许个性化预防措施,阐明依赖的分子过程,并为尼古丁成瘾的药物治疗提名新的靶点。尼古丁依赖给个人和社会带来了巨大的负担。遗传因素至少是造成这种情况的一部分原因,NIDA已经资助了一项名为COGEND的研究,该研究检查了尼古丁依赖者和非尼古丁依赖者的40,000多个遗传变异。我们建议使用尖端技术来分析这个大型数据集,以确定尼古丁依赖的有效预测模型,这将有助于我们预测,诊断和治疗这种疾病。
英文摘要
DESCRIPTION (provided by applicant): Tobacco use, primarily cigarette smoking, is the greatest source of preventable mortality in the world and costs over $160 million in health-related economic losses in the U.S. alone. Nicotine dependence is the primary reason that smokers continue smoking and that most unassisted quit attempts fail within a single week. It is known that nicotine dependence has a genetic component, but that it is a complex trait, i.e., no single gene is responsible for nicotine dependence. Thus, researchers and funding agencies have devoted considerable effort and support to identifying the genetic underpinnings of the trait through whole genome scans, putting us in a unique position to identify global genetic predictors of nicotine dependence. This study proposes to realize the promise of the NIDA-funded Collaborative Genetic Study of Nicotine Dependence (COGEND) whole genome data through the accomplishment of two specific aims: (1) to identify the set of genetic variations underlying the complex trait of nicotine dependence using a cutting-edge computational method called Bayesian networks and (2) to validate the prognostic model in an entirely independent population. This proposal represents the very first step of a broader research program aimed at discovering the complex network of interactions underpinning nicotine dependence. The ultimate result of this program will provide a clinical tool, which will accurately assess the risk of dependency, allow for individualized preventive measures, elucidate the molecular processes of dependence and nominate novel targets for the pharmaceutical treatment of nicotine addiction. Nicotine dependence places an enormous burden on individuals and society. Genetic factors are responsible for at least some part of the condition, and the NIDA has already funded a study, called COGEND, that examined over 40,000 genetic variations in people who were nicotine dependent and who were not nicotine dependent. We propose to use cutting-edge techniques to analyze this large dataset to identify a valid predictive model of nicotine dependence that will help us predict, diagnose, and treat this condition.
期刊论文(7)
专著(0)
科研奖励(0)
会议论文
登录
查看更多内容
DOI:
10.1186/s12918-017-0403-7
发表时间:
2017-03-14
期刊:
BMC systems biology
影响因子:
--
作者:
[Zollanvari A, Alterovitz G]
通讯作者:
Alterovitz G
Automated synthesis and visualization of a chemotherapy treatment regimen network.
化疗治疗方案网络的自动合成和可视化。
DOI:
--
发表时间:
2013
期刊:
Studies in health technology and informatics
影响因子:
--
作者:
[Warner,Jeremy, Yang,Peter, Alterovitz,Gil]
通讯作者:
Alterovitz,Gil
A bayesian translational framework for knowledge propagation, discovery, and integration under specific contexts.
用于特定背景下知识传播、发现和集成的贝叶斯翻译框架。
DOI:
--
发表时间:
2012
期刊:
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
影响因子:
--
作者:
[Deng,Michelle, Zollanvari,Amin, Alterovitz,Gil]
通讯作者:
Alterovitz,Gil
Is the reduction of dimensionality to a small number of features always necessary in constructing predictive models for analysis of complex diseases or behaviours?
在构建用于分析复杂疾病或行为的预测模型时,是否始终需要将维度降低到少量特征?
DOI:
10.1109/iembs.2011.6090596
发表时间:
2011
期刊:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
影响因子:
--
作者:
[Zollanvari,Amin, Saccone,NancyL, Bierut,LauraJ, Ramoni,MarcoF, Alterovitz,Gil]
通讯作者:
Alterovitz,Gil
External phenome analysis enables a rational federated query strategy to detect changing rates of treatment-related complications associated with multiple myeloma.
外部表组分析使合理的联合查询策略能够检测与多发性骨髓瘤相关的治疗相关并发症的变化率。
DOI:
10.1136/amiajnl-2012-001355
发表时间:
2013
期刊:
Journal of the American Medical Informatics Association : JAMIA
影响因子:
--
作者:
[Warner,JeremyL, Alterovitz,Gil, Bodio,Kelly, Joyce,RobinM]
通讯作者:
Joyce,RobinM
共 6 条
Towards a generalizable drug discovery framework based on intrinsically disordered regions
-
批准号:10116778
-
项目类别:
-
资助金额:$36.99万
-
财政年份:2016
-
负责人:GIL ALTEROVITZ
-
依托单位:
NOT-GM-21-028:Towards a generalizable drug discovery framework based on intrinsically disordered regions
-
批准号:10393070
-
项目类别:
-
资助金额:$1.43万
-
财政年份:2016
-
负责人:GIL ALTEROVITZ
-
依托单位:
Automated Integration of Biomedical Knowledge
-
批准号:7945368
-
项目类别:
-
资助金额:$42.81万
-
财政年份:2009
-
负责人:GIL ALTEROVITZ
-
依托单位:
A Holistic Approach to Information Processing for Biomedical Networks
-
批准号:8324015
-
项目类别:
-
资助金额:$23.89万
-
财政年份:2008
-
负责人:GIL ALTEROVITZ
-
依托单位:
A Holistic Approach to Information Processing for Biomedical Networks
-
批准号:8123728
-
项目类别:
-
资助金额:$24.9万
-
财政年份:2008
-
负责人:GIL ALTEROVITZ
-
依托单位:
A Holistic Approach to Information Processing for Biomedical Networks
-
批准号:7690865
-
项目类别:
-
资助金额:$13.17万
-
财政年份:2008
-
负责人:GIL ALTEROVITZ
-
依托单位:
A Holistic Approach to Information Processing for Biomedical Networks
-
批准号:7590533
-
项目类别:
-
资助金额:$13.17万
-
财政年份:2008
-
负责人:GIL ALTEROVITZ
-
依托单位:
A Holistic Approach to Information Processing for Biomedical Networks
-
批准号:8139959
-
项目类别:
-
资助金额:$23.9万
-
财政年份:2008
-
负责人:GIL ALTEROVITZ
-
依托单位:
国内基金
海外基金
Molecular Interaction Reconstruction of Rheumatoid Arthritis Therapies Using Clinical Data
-
批准号:31070748
-
项目类别:面上项目
-
资助金额:34.0万元
-
批准年份:2010
-
负责人:Christine Nardini
-
依托单位: