Lipidomic Network of Mild Cognitive Impairment from the Mayo Clinic Study of Aging.
Aging
Alzheimer’s disease
amyloid
lipid
lipidomics
mild cognitive impairment
network analysis
systems biology
Journal
Journal of Alzheimer's disease : JAD
ISSN: 1875-8908
Titre abrégé: J Alzheimers Dis
Pays: Netherlands
ID NLM: 9814863
Informations de publication
Date de publication:
2021
2021
Historique:
pubmed:
6
4
2021
medline:
7
9
2021
entrez:
5
4
2021
Statut:
ppublish
Résumé
Lipid alterations contribute to Alzheimer's disease (AD) pathogenesis. Lipidomics studies could help systematically characterize such alterations and identify potential biomarkers. To identify lipids associated with mild cognitive impairment and amyloid-β deposition, and to examine lipid correlation patterns within phenotype groupsMethods:Eighty plasma lipids were measured using mass spectrometry for 1,255 non-demented participants enrolled in the Mayo Clinic Study of Aging. Individual lipids associated with mild cognitive impairment (MCI) were first identified. Correlation network analysis was then performed to identify lipid species with stable correlations across conditions. Finally, differential correlation network analysis was used to determine lipids with altered correlations between phenotype groups, specifically cognitively unimpaired versus MCI, and with elevated brain amyloid versus without. Seven lipids were associated with MCI after adjustment for age, sex, and APOE4. Lipid correlation network analysis revealed that lipids from a few species correlated well with each other, demonstrated by subnetworks of these lipids. 177 lipid pairs differently correlated between cognitively unimpaired and MCI patients, whereas 337 pairs of lipids exhibited altered correlation between patients with and without elevated brain amyloid. In particular, 51 lipid pairs showed correlation alterations by both cognitive status and brain amyloid. Interestingly, the lipids central to the network of these 51 lipid pairs were not significantly associated with either MCI or amyloid, suggesting network-based approaches could provide biological insights complementary to traditional association analyses. Our attempt to characterize the alterations of lipids at network-level provides additional insights beyond individual lipids, as shown by differential correlations in our study.
Sections du résumé
BACKGROUND
Lipid alterations contribute to Alzheimer's disease (AD) pathogenesis. Lipidomics studies could help systematically characterize such alterations and identify potential biomarkers.
OBJECTIVE
To identify lipids associated with mild cognitive impairment and amyloid-β deposition, and to examine lipid correlation patterns within phenotype groupsMethods:Eighty plasma lipids were measured using mass spectrometry for 1,255 non-demented participants enrolled in the Mayo Clinic Study of Aging. Individual lipids associated with mild cognitive impairment (MCI) were first identified. Correlation network analysis was then performed to identify lipid species with stable correlations across conditions. Finally, differential correlation network analysis was used to determine lipids with altered correlations between phenotype groups, specifically cognitively unimpaired versus MCI, and with elevated brain amyloid versus without.
RESULTS
Seven lipids were associated with MCI after adjustment for age, sex, and APOE4. Lipid correlation network analysis revealed that lipids from a few species correlated well with each other, demonstrated by subnetworks of these lipids. 177 lipid pairs differently correlated between cognitively unimpaired and MCI patients, whereas 337 pairs of lipids exhibited altered correlation between patients with and without elevated brain amyloid. In particular, 51 lipid pairs showed correlation alterations by both cognitive status and brain amyloid. Interestingly, the lipids central to the network of these 51 lipid pairs were not significantly associated with either MCI or amyloid, suggesting network-based approaches could provide biological insights complementary to traditional association analyses.
CONCLUSION
Our attempt to characterize the alterations of lipids at network-level provides additional insights beyond individual lipids, as shown by differential correlations in our study.
Identifiants
pubmed: 33814434
pii: JAD201347
doi: 10.3233/JAD-201347
pmc: PMC8154710
mid: NIHMS1696054
doi:
Substances chimiques
Amyloid beta-Peptides
0
Biomarkers
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
533-543Subventions
Organisme : NIA NIH HHS
ID : R01 AG034676
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG011378
Pays : United States
Organisme : NIA NIH HHS
ID : R33 AG058738
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG049704
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG006786
Pays : United States
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