MassIVE MSV000081035

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MetaboLights MTBLS72 - GNPS Plasma Lipidomics for the Identification of Anticedent Memory Impairment

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Description

This data set was downloaded from MetaboLights (http://www.ebi.ac.uk/metabolights/) accession number MTBLS72 Abstract:Alzheimer’s disease causes a progressive dementia that currently affects over 35 million individuals worldwide and is expected to affect 115 million by 2050. There are no cures or disease-modifying therapies, and this may be due to our inability to detect the disease before it has progressed to produce evident memory loss and functional decline. Biomarkers of preclinical disease will be critical to the development of disease-modifying or even preventative therapies. Unfortunately, current biomarkers for early disease, including cerebrospinal fluid tau and amyloid-beta levels, structural and functional magnetic resonance imaging and the recent use of brain amyloid imaging or inflammaging, are limited because they are either invasive, time-consuming or expensive. Blood-based biomarkers may be a more attractive option, but none can currently detect preclinical Alzheimer's disease with the required sensitivity and specificity.

Herein, we describe our lipidomic approach to detecting preclinical Alzheimer’s disease in a group of cognitively normal older adults. We discovered and validated a set of ten lipids from peripheral blood that predicted phenoconversion to either amnestic mild cognitive impairment or Alzheimer’s disease within a 2–3 year timeframe with over 90% accuracy. This biomarker panel, reflecting cell membrane integrity, may be sensitive to early neurodegeneration of preclinical Alzheimer's disease.

In this study, a combination of targeted and untargeted metabolomics/lipidomics approach was used in conjunction with statistical analysis for identification of a bio-signature of pre-clinical Alzheimer’s disease. [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Homo sapiens

Contact

Principal Investigators:
(in alphabetical order) 		Federoff, Georgetown University, us
Submitting User: rsilva
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