Mapping the multidimensional geometric landscape of graded phenotypic variation and progression in neurodegenerative syndromes

medRxiv (Cold Spring Harbor Laboratory)(2023)

引用 0|浏览14
暂无评分
摘要
Clinical variants of Alzheimer’s disease (AD) and frontotemporal lobar degeneration (FTLD) display a spectrum of cognitive-behavioural changes varying between individuals and over time. Understanding the landscape of these graded individual-/group-level longitudinal variations is critical for precise phenotyping; however, this remains challenging to model. Addressing this challenge, we leverage the National Alzheimer’s Coordinating Center database to derive a unified geometric framework of graded AD/FTLD longitudinal phenotypic variation. Using three time-point, cognitive-behavioural and clinical data from 390 typical, atypical and intermediate AD/FTLD variants, we apply advanced data-science approaches to derive low-dimensional geometric spaces capturing core features underpinning AD/FTLD clinical progression. Importantly, these geometries enable the assimilation and inter-relation of paradigmatic and mixed cases, capturing dynamic individual trajectories, and linking syndromic variability to neuropathology and key clinical end-points such as survival. This resultant mapping of dynamics underlying cognitive-behavioural evolution potentially holds paradigm-changing implications to predicting phenotypic diversification and phenotype-neurobiological mapping in AD/FTLD. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement D.A. is supported by UK Research and Innovation (UKRI) Medical Research Council (MRC) funding (MC-A0606-5PQ41), the James S. McDonnell Foundation Opportunity Award for Understanding Human Cognition and the Templeton World Charity Foundation, Inc. (funder DOI 501100011730) under the grant TWCF-2022-30510. S.K.H. is supported and funded by the Bill & Melinda Gates Foundation, Seattle, WA, and Gates Cambridge Trust (Grant Number: OPP1144). M.A.R is supported by the MRC (SUAG/096 G116768). J.B.R is supported by the MRC (MC\_UU\_00030/14; MR/T033371/1), NIHR Cambridge Biomedical Research Centre (BRC1215-20014, NIHR203312; the views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care) and the Cambridge Centre for Parkinson-plus. M.A.LR. is supported by an MRC programme grant (MR/R023883/1) and intramural funding (MC\_UU\_00005/18). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: As determined by the University of Washington Human Subjects Division, use of the National Alzheimers Coordinating Center (NACC) database itself is exempt from Institutional Review Board review. However, all contributing Alzheimer's Disease Research Centers are required to obtain informed consent from their participants and to maintain their own separate Institutional Review Board review and approval from their institution before submitting data to NACC. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes
更多
查看译文
关键词
multidimensional geometric landscape,phenotypic variation,mapping
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要