Background: Neuroimaging 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.

Objective: To 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.

Methods: A 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.

Results: The 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.

Conclusion: The 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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2809036PMC
http://dx.doi.org/10.1212/WNL.0b013e3181cb3e25DOI Listing

Publication Analysis

Top Keywords

subjects mci
24
subjects
15
alzheimer's disease
12
mci subjects
12
cognitively normal
12
mci
10
disease neuroimaging
8
neuroimaging initiative
8
mild cognitive
8
cognitive impairment
8

Similar Publications

The novel amyloid-beta, p-Tau, and neurofilament light chain (ATN) classification scheme has become a promising system for clinically detecting and diagnosing Alzheimer's disease (AD). In addition to its utility in Alzheimer's diagnosis and treatment, the ATN framework may also have clinical relevance in identifying non-Alzheimer's pathologies. In this study conducted at Broadlawns Geriatric and Memory Center, 92 amyloid-negative profiles out of 182 patients with an ATN framework were categorized into subjective cognitive impairment (SCI), non-amnestic mild cognitive impairment (non-amnestic MCI), amnestic MCI, Alzheimer's dementia, vascular dementia, mixed dementia, unspecified dementia, or other memory changes based on diagnoses written in the chart.

View Article and Find Full Text PDF

APOE4 impact on soluble and insoluble tau pathology is mostly influenced by amyloid-beta.

Brain

January 2025

Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, 22184 Lund, Sweden.

The APOE4 allele is the strongest genetic risk factor for sporadic Alzheimer's disease (AD). While APOE4 is strongly associated with amyloid-beta (Aβ), its relationship with tau accumulation is less understood. Studies evaluating the role of APOE4 on tau accumulation showed conflicting results, particularly regarding the independence of these associations from Aβ load.

View Article and Find Full Text PDF

Improved deep canonical correlation fusion approach for detection of early mild cognitive impairment.

Med Biol Eng Comput

January 2025

Non-Invasive Imaging and Diagnostic Laboratory, Department of Applied Mechanics and Biomedical Engineering, Indian Institute of Technology Madras, Chennai, India.

Detection of early mild cognitive impairment (EMCI) is clinically challenging as it involves subtle alterations in multiple brain sub-anatomic regions. Among different brain regions, the corpus callosum and lateral ventricles are primarily affected due to EMCI. In this study, an improved deep canonical correlation analysis (CCA) based framework is proposed to fuse magnetic resonance (MR) image features from lateral ventricular and corpus callosal structures for the detection of EMCI condition.

View Article and Find Full Text PDF

A comprehensive genome-wide association study (GWAS) has validated the identification of the Plexin-A 4 (PLXNA4) gene as a novel susceptibility factor for Alzheimer's disease (AD). Nonetheless, the precise role of PLXNA4 gene polymorphisms in the pathophysiology of AD remains to be established. Consequently, this study is aimed at exploring the relationship between PLXNA4 gene polymorphisms and neuroimaging phenotypes intimately linked to AD.

View Article and Find Full Text PDF

Optimal time-frequency localized wavelet filters for identification of Alzheimer's disease from EEG signals.

Cogn Neurodyn

December 2025

Department of Electrical and Electronics Engineering, Jazan, 45142 Jazan Saudi Arabia.

Alzheimer's disease (AD) is a chronic disability that occurs due to the loss of neurons. The traditional methods to detect AD involve questionnaires and expensive neuro-imaging tests, which are time-consuming, subjective, and inconvenient to the target population. To overcome these limitations, Electroencephalogram (EEG) based methods have been developed to classify AD patients from normal controlled (NC) and mild cognitive impairment (MCI) subjects.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!