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Multiomics analysis to explore blood metabolite biomarkers in an Alzheimer's Disease Neuroimaging Initiative cohort.

Publication ,  Journal Article
Oka, T; Matsuzawa, Y; Tsuneyoshi, M; Nakamura, Y; Aoshima, K; Tsugawa, H; Alzheimer’s Disease Metabolomics Consortium
Published in: Sci Rep
April 2, 2024

Alzheimer's disease (AD) is a neurodegenerative disease that commonly causes dementia. Identifying biomarkers for the early detection of AD is an emerging need, as brain dysfunction begins two decades before the onset of clinical symptoms. To this end, we reanalyzed untargeted metabolomic mass spectrometry data from 905 patients enrolled in the AD Neuroimaging Initiative (ADNI) cohort using MS-DIAL, with 1,304,633 spectra of 39,108 unique biomolecules. Metabolic profiles of 93 hydrophilic metabolites were determined. Additionally, we integrated targeted lipidomic data (4873 samples from 1524 patients) to explore candidate biomarkers for predicting progressive mild cognitive impairment (pMCI) in patients diagnosed with AD within two years using the baseline metabolome. Patients with lower ergothioneine levels had a 12% higher rate of AD progression with the significance of P = 0.012 (Wald test). Furthermore, an increase in ganglioside (GM3) and decrease in plasmalogen lipids, many of which are associated with apolipoprotein E polymorphism, were confirmed in AD patients, and the higher levels of lysophosphatidylcholine (18:1) and GM3 d18:1/20:0 showed 19% and 17% higher rates of AD progression, respectively (Wald test: P = 3.9 × 10-8 and 4.3 × 10-7). Palmitoleamide, oleamide, diacylglycerols, and ether lipids were also identified as significantly altered metabolites at baseline in patients with pMCI. The integrated analysis of metabolites and genomics data showed that combining information on metabolites and genotypes enhances the predictive performance of AD progression, suggesting that metabolomics is essential to complement genomic data. In conclusion, the reanalysis of multiomics data provides new insights to detect early development of AD pathology and to partially understand metabolic changes in age-related onset of AD.

Duke Scholars

Published In

Sci Rep

DOI

EISSN

2045-2322

Publication Date

April 2, 2024

Volume

14

Issue

1

Start / End Page

6797

Location

England

Related Subject Headings

  • Neuroimaging
  • Neurodegenerative Diseases
  • Multiomics
  • Lipids
  • Humans
  • Disease Progression
  • Cognitive Dysfunction
  • Biomarkers
  • Alzheimer Disease
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Oka, T., Matsuzawa, Y., Tsuneyoshi, M., Nakamura, Y., Aoshima, K., Tsugawa, H., & Alzheimer’s Disease Metabolomics Consortium. (2024). Multiomics analysis to explore blood metabolite biomarkers in an Alzheimer's Disease Neuroimaging Initiative cohort. Sci Rep, 14(1), 6797. https://doi.org/10.1038/s41598-024-56837-1
Oka, Takaki, Yuki Matsuzawa, Momoka Tsuneyoshi, Yoshitaka Nakamura, Ken Aoshima, Hiroshi Tsugawa, and Alzheimer’s Disease Metabolomics Consortium. “Multiomics analysis to explore blood metabolite biomarkers in an Alzheimer's Disease Neuroimaging Initiative cohort.Sci Rep 14, no. 1 (April 2, 2024): 6797. https://doi.org/10.1038/s41598-024-56837-1.
Oka T, Matsuzawa Y, Tsuneyoshi M, Nakamura Y, Aoshima K, Tsugawa H, et al. Multiomics analysis to explore blood metabolite biomarkers in an Alzheimer's Disease Neuroimaging Initiative cohort. Sci Rep. 2024 Apr 2;14(1):6797.
Oka, Takaki, et al. “Multiomics analysis to explore blood metabolite biomarkers in an Alzheimer's Disease Neuroimaging Initiative cohort.Sci Rep, vol. 14, no. 1, Apr. 2024, p. 6797. Pubmed, doi:10.1038/s41598-024-56837-1.
Oka T, Matsuzawa Y, Tsuneyoshi M, Nakamura Y, Aoshima K, Tsugawa H, Alzheimer’s Disease Metabolomics Consortium. Multiomics analysis to explore blood metabolite biomarkers in an Alzheimer's Disease Neuroimaging Initiative cohort. Sci Rep. 2024 Apr 2;14(1):6797.

Published In

Sci Rep

DOI

EISSN

2045-2322

Publication Date

April 2, 2024

Volume

14

Issue

1

Start / End Page

6797

Location

England

Related Subject Headings

  • Neuroimaging
  • Neurodegenerative Diseases
  • Multiomics
  • Lipids
  • Humans
  • Disease Progression
  • Cognitive Dysfunction
  • Biomarkers
  • Alzheimer Disease