Using the Alzheimer's Disease Neuroimaging Initiative to improve early detection, diagnosis, and treatment of Alzheimer's disease.
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ABSTRACT: Introduction
The Alzheimer's Disease Neuroimaging Initiative (ADNI) has accumulated 15 years of clinical, neuroimaging, cognitive, biofluid biomarker and genetic data, and biofluid samples available to researchers, resulting in more than 3500 publications. This review covers studies from 2018 to 2020.Methods
We identified 1442 publications using ADNI data by conventional search methods and selected impactful studies for inclusion.Results
Disease progression studies supported pivotal roles for regional amyloid beta (Aβ) and tau deposition, and identified underlying genetic contributions to Alzheimer's disease (AD). Vascular disease, immune response, inflammation, resilience, and sex modulated disease course. Biologically coherent subgroups were identified at all clinical stages. Practical algorithms and methodological changes improved determination of Aβ status. Plasma Aβ, phosphorylated tau181, and neurofilament light were promising noninvasive biomarkers. Prognostic and diagnostic models were externally validated in ADNI but studies are limited by lack of ethnocultural cohort diversity.Discussion
ADNI has had a profound impact in improving clinical trials for AD.
SUBMITTER: Veitch DP
PROVIDER: S-EPMC9158456 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:With increasing life expectancy in developed countries, the incidence of Alzheimer's disease (AD) and its socioeconomic impact are growing. Increasing knowledge of the mechanisms of AD facilitates the development of treatment strategies aimed at slowing down or preventing neuronal death. AD treatment trials using clinical outcome measures require long observation times and large patient samples. There is increasing evidence that neuroimaging and cerebrospinal fluid and blood biomarkers may provide information that may reduce sample sizes and observation periods. The Alzheimer's Disease Neuroimaging Initiative will help identify clinical, neuroimaging, and biomarker outcome measures that provide the highest power for measurement of longitudinal changes and for prediction of transitions.
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Project description:BackgroundNeuroimaging measures and chemical biomarkers may be important indices of clinical progression in normal aging and mild cognitive impairment (MCI) and need to be evaluated longitudinally.ObjectiveTo characterize cross-sectionally and longitudinally clinical measures in normal controls, subjects with MCI, and subjects with mild Alzheimer disease (AD) to enable the assessment of the utility of neuroimaging and chemical biomarker measures.MethodsA total of 819 subjects (229 cognitively normal, 398 with MCI, and 192 with AD) were enrolled at baseline and followed for 12 months using standard cognitive and functional measures typical of clinical trials.ResultsThe subjects with MCI were more memory impaired than the cognitively normal subjects but not as impaired as the subjects with AD. Nonmemory cognitive measures were only minimally impaired in the subjects with MCI. The subjects with MCI progressed to dementia in 12 months at a rate of 16.5% per year. Approximately 50% of the subjects with MCI were on antidementia therapies. There was minimal movement on the Alzheimer's Disease Assessment Scale-Cognitive Subscale for the normal control subjects, slight movement for the subjects with MCI of 1.1, and a modest change for the subjects with AD of 4.3. Baseline CSF measures of Abeta-42 separated the 3 groups as expected and successfully predicted the 12-month change in cognitive measures.ConclusionThe Alzheimer's Disease Neuroimaging Initiative has successfully recruited cohorts of cognitively normal subjects, subjects with mild cognitive impairment (MCI), and subjects with Alzheimer disease with anticipated baseline characteristics. The 12-month progression rate of MCI was as predicted, and the CSF measures heralded progression of clinical measures over 12 months.
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Project description:INTRODUCTION:The low mild cognitive impairment (MCI) to cognitively normal (CN) reversion rate in the Alzheimer's Disease Neuroimaging Initiative (2-3%) suggests the need to examine reversion by other means. We applied comprehensive neuropsychological criteria (NP criteria) to determine the resulting MCI to CN reversion rate. METHODS:Participants with CN (n = 641) or MCI (n = 569) were classified at baseline and year 1 using NP criteria. Demographic, neuropsychological, and Alzheimer's disease biomarker variables as well as progression to dementia were examined across stable CN, reversion, and stable MCI groups. RESULTS:NP criteria produced a one-year reversion rate of 15.8%. Reverters had demographics, Alzheimer's disease biomarkers, and risk-of-progression most similar to the stable CN group and showed the most improvement on neuropsychological measures from baseline to year 1. DISCUSSION:NP criteria produced a reversion rate that is consistent with, albeit modestly improved from, reversion rates in meta-analyses. Reverters' biomarker profiles and progression rates suggest that NP criteria accurately tracked with underlying pathophysiologic status.
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Project description:BackgroundCross-sectional studies suggest self-reported cancer history is associated with decreased risk of Alzheimer's disease (AD). However, little is known about how self-reported cancer affects longitudinal AD progression, the primary outcome in clinical trials and observational studies.ObjectiveTo determine self-reported cancer history's effect on longitudinal AD progression in an observational study.MethodsWe utilized data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to evaluate progression to AD by self-reported all-cancer, breast, prostate, colorectal, or non-melanoma skin cancer history. Linear mixed effects models were used to examine baseline differences and rates of progression on the Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) by self-reported cancer history. Age at AD onset was examined using consensus clinical diagnoses with Cox proportional hazards regression.ResultsAmong 1,271 participants, models revealed no significant differences in progression over time but did reveal significantly lower baseline ADAS-Cog score, indicating better cognition at a given age in those with self-reported cancer history. Cox models indicated those with self-reported cancer history had significantly later age of AD onset (HR: 0.67, 95% CI: 0.53-0.85) after adjustment for covariates.ConclusionParticipants with self-reported cancer history entered ADNI with better cognition and later age of AD onset, but progressed similarly to participants without such history, indicating differences in AD between those with and without self-reported cancer history emerge early in the disease course. Such differences in longitudinal progression by self-reported cancer history could affect AD trials and observational studies, given the current focus on early disease course. Further investigation is warranted with detailed longitudinal assessment of cancer and AD.
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Project description:IntroductionThe objective of this study was to determine the factors including neuropsychological test performances and cerebrospinal fluid (CSF) biomarkers which can predict disease progression of early Alzheimer's disease (AD) in a Japanese population.MethodsThe group classification on early AD population in both Japanese Alzheimer's Disease Neuroimaging Initiative (J-ADNI) and North American ADNI (NA-ADNI) was performed using the inclusion criteria including brain amyloid positivity on positron emission tomography or CSF. Participants with early AD from each cohort were stratified into two groups based on a cutoff 1.0 of Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) change at month 24 (m24): participants in "progress group" have CDR-SB change ≥ 1.0 and participants in "stable group" have CDR-SB change < 1.0. Then, we performed identification of prognostic factors from baseline items including neuropsychological scores (Assessment Scale-Cognitive Subscale[ADAS-cog 13], Mini-Mental State Examination (MMSE), CDR, FAQ, and Geriatric Depression Scale ), CSF markers (t-tau, p-tau, and beta-amyloid 1-42), vital signs (body weight, pulse rate, etc.,), by using two statistical approaches, Welch's t-test and simple linear regression by ordinary least squares. Comparisons between participants with J-ADNI and participants with NA-ADNI were also performed.ResultsTrends of CDR-SB changes were very similar between J-ADNI and NA-ADNI early AD population enrolled in this study. Baseline levels of CSF t-tau, p-tau, Mini-Mental State Examination, FAQ, and ADAS-cog13 were identified as prognostic factors in both J-ADNI and NA-ADNI. Based on a detailed subscale analysis on ADAS-cog13, four subscales (Q1: word recall, Q3: construction, Q4: delayed word recall, and Q8: word recognition) were identified as prognostic factors in both J-ADNI and NA-ADNI.DiscussionCharacterizing population with early AD can provide benefits for promoting efficiency in conducting AD clinical trials for disease-modifying treatments. Thus, implementing these prognostic factors into clinical trials may be potentially a good method to enrich participants with early AD who are suitable for evaluating treatment effects.
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Project description:The Clinical Core of the Alzheimer's Disease Neuroimaging Initiative (ADNI) has provided clinical, operational, and data management support to ADNI since its inception. This article reviews the activities and accomplishments of the core in support of ADNI aims. These include the enrollment and follow-up of more than 800 subjects in the three original cohorts: healthy controls, amnestic mild cognitive impairment (now referred to as late MCI, or LMCI), and mild Alzheimer's disease (AD) in the first phase of ADNI (ADNI 1), with baseline longitudinal, clinical, and cognitive assessments. These data, when combined with genetic, neuroimaging, and cerebrospinal fluid measures, have provided important insights into the neurobiology of the AD spectrum. Furthermore, these data have facilitated the development of novel clinical trial designs. ADNI has recently been extended with funding from an NIH Grand Opportunities (GO) award, and the new ADNI GO phase has been launched; this includes the enrollment of a new cohort, called early MCI, with milder episodic memory impairment than the LMCI group. An application for a further 5 years of ADNI funding (ADNI 2) was recently submitted. This funding would support ongoing follow-up of the original ADNI 1 and ADNI GO cohorts, as well as additional recruitment into all categories. The resulting data would provide valuable data on the earliest stages of AD, and support the development of interventions in these critically important populations.
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