Metabolic Profiling
of Neocortical Tissue Discriminates
Alzheimer’s Disease from Mild Cognitive Impairment, High Pathology
Controls, and Normal Controls
posted on 2021-08-06, 14:36authored byPaniz Jasbi, Xiaojian Shi, Ping Chu, Natalie Elliott, Haley Hudson, Douglas Jones, Geidy Serrano, Brandon Chow, Thomas G. Beach, Li Liu, Garilyn Jentarra, Haiwei Gu
Alzheimer’s disease
(AD) is the most common cause of dementia, accounting for an estimated
60–80% of cases, and is the sixth-leading cause of death in
the United States. While considerable advancements have been made
in the clinical care of AD, it remains a complicated disorder that
can be difficult to identify definitively in its earliest stages.
Recently, mass spectrometry (MS)-based metabolomics has shown significant
potential for elucidation of disease mechanisms and identification
of therapeutic targets as well diagnostic and prognostic markers that
may be useful in resolving some of the difficulties affecting clinical
AD studies, such as effective stratification. In this study, complementary
gas chromatography- and liquid chromatography-MS platforms were used
to detect and monitor 2080 metabolites and features in 48 postmortem
tissue samples harvested from the superior frontal gyrus of male and
female subjects. Samples were taken from four groups: 12 normal control
(NC) patients, 12 cognitively normal subjects characterized as high
pathology controls (HPC), 12 subjects with nonspecific mild cognitive
impairment (MCI), and 12 subjects with AD. Multivariate statistics
informed the construction and cross-validation (p < 0.01) of partial least squares-discriminant analysis (PLS-DA)
models defined by a nine-metabolite panel of disease markers (lauric
acid, stearic acid, myristic acid, palmitic acid, palmitoleic acid,
and four unidentified mass spectral features). Receiver operating
characteristic analysis showed high predictive accuracy of the resulting
PLS-DA models for discrimination of NC (97%), HPC (92%), MCI (∼96%),
and AD (∼96%) groups. Pathway analysis revealed significant
disturbances in lysine degradation, fatty acid metabolism, and the
degradation of branched-chain amino acids. Network analysis showed
significant enrichment of 11 enzymes, predominantly within the mitochondria.
The results expand basic knowledge of the metabolome related to AD
and reveal pathways that can be targeted therapeutically. This study
also provides a promising basis for the development of larger multisite
projects to validate these candidate markers in readily available
biospecimens such as blood to enable the effective screening, rapid
diagnosis, accurate surveillance, and therapeutic monitoring of AD.
All raw mass spectrometry data have been deposited to MassIVE (data
set identifier MSV000087165).