Affiliations: [a]
Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| [b] Eli Lilly and Company, Indianapolis, IN, USA
| [c]
Department of Radiology, Mayo Clinic, Rochester, MN, USA
| [d]
Department of Neurology, Mayo Clinic, Rochester, MN, USA
Correspondence:
[*]
Correspondence to: Michelle M. Mielke, PhD, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. Tel.: +1 507 293 1069; Fax: +1 507 284 1516; E-mail: Mielke.Michelle@mayo.edu.
Abstract: 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 groups Methods: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.
