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JPND: Early Detection of Alzheimer's Disease Subtypes

JPND: Early Detection of Alzheimer's Disease Subtypes
JPND:阿尔茨海默病亚型的早期检测
批准号:
MR/T046422/1
负责人:
Daniel Alexander
金额:
$56.94万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2020
资助国家:
英国
项目状态:
未结题
起止时间:
2020 至 --

项目摘要

项目成果

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中文摘要
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英文摘要
Alzheimer's disease (AD) is a global health and economic burden with currently about 47 million affected individuals worldwide. No provably disease-modifying treatments exist. Delaying disease onset in dementia patients by five years can reduce care costs by 36% about 88B euro per year across the EU. A key confound preventing successful outcomes in most treatment trials to date has been AD's high variation in onset, mechanism, and clinical expression. E-DADS aims to untangle this heterogeneity by defining data-driven subtypes of the clinical manifestation of AD based on brain imaging, cognitive markers, and fluid biomarkers that are robustly identifiable from predictive risk factors (genetics, co-morbidities, physiological and lifestyle factors) years before disease onset. To achieve this we develop a novel multi-view learning strategies that relates end-stage disease manifestations observable in clinical cohorts to features of early-stage or at-risk individuals in preclinical cohorts and the general pre-affected population from population or aging studies. This approach is only possible now due to the availability of large population data, richly phenotyped AD cohorts and advances in machine learning. E-DADS uniquely assembles the necessary data and expertise. The ability to identify AD subtypes and predict them years before onset will significantly advance AD research and clinical management via precision medicine. First, it identifies distinct homogeneous groups, shedding new light on that nature and variability of disease mechanisms ultimately pinpointing effective drug targets. Second, it enables enrichment of future clinical trials for specific groups of patients likely to benefit from a particular intervention. Third, it highlights potential lifestyle interventions that may affect or delay disease onset at very early stages. E-DADS delivers the underpinning technology to achieve this through machine learning and big-data analytics together with a prototype software tool enabling future translation and uptake.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
Alzheimer-like biomarker heterogeneity in a preclinical elderly birth cohort: Insight46
临床前老年出生队列中的阿尔茨海默样生物标志物异质性:Insight46
DOI: 10.1002/alz.067555
发表时间: 2022
期刊: Alzheimer's & Dementia
影响因子: --
作者: [Garcia M]
通讯作者: Garcia M
Transferability of Alzheimer's disease progression subtypes to an independent population cohort.
阿尔茨海默病进展亚型向独立人群队列的可转移性。
DOI: 10.1016/j.neuroimage.2023.120005
发表时间: 2023
期刊: NeuroImage
影响因子: 5.7
作者: [Chen H]
通讯作者: Chen H
DOI: 10.1093/brain/awad232
发表时间: 2023-12-01
期刊: Brain : a journal of neurology
影响因子: --
作者: []
通讯作者:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 - 26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings, Part VIII
医学图像计算和计算机辅助干预 - MICCAI 2023 - 第 26 届国际会议,加拿大不列颠哥伦比亚省温哥华,2023 年 10 月 8-12 日,会议记录,第八部分
DOI: 10.1007/978-3-031-43993-3_39
发表时间: 2023
期刊:
影响因子: --
作者: [Kirk T]
通讯作者: Kirk T
7
    Assessing Placental Structure and Function by Unified Fluid Mechanical Modelling and in-vivo MRI
    • 批准号:
      EP/V034537/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $143.22万
    • 财政年份:
      2022
    • 负责人:
      Daniel Alexander
    • 依托单位:
    JPND: Stratification of presymptomatic amyotrophic lateral sclerosis: the development of novel imaging biomarkers
    • 批准号:
      MR/T046473/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $50.47万
    • 财政年份:
      2020
    • 负责人:
      Daniel Alexander
    • 依托单位:
    Enabling Clinical Decisions From Low-power MRI In Developing Nations Through Image Quality Transfer
    • 批准号:
      EP/R014019/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $131.95万
    • 财政年份:
      2018
    • 负责人:
      Daniel Alexander
    • 依托单位:
    Learning MRI and histology image mappings for cancer diagnosis and prognosis
    • 批准号:
      EP/R006032/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $98.66万
    • 财政年份:
      2017
    • 负责人:
      Daniel Alexander
    • 依托单位:
    国内基金
    海外基金
    玉米Edk1(Early delayed kernel 1)基因的克隆及其在胚乳早期发育中的功能研究