A class of anti-inflammatory lipids decrease with aging in the central nervous system

Dan Tan, Srihari Konduri, Meric Erikci Ertunc, Pan Zhang, Justin Wang, Tina Chang, Antonio F.M. Pinto, Andrea Rocha, Cynthia J. Donaldson, Joan M. Vaughan, Raissa G. Ludwig, Elizabeth Willey, Manasi Iyer, Peter C. Gray, Pamela Maher, Nicola J. Allen, J. Bradley Zuchero, Andrew Dillin, Marcelo A. Mori, Steven G. KohamaDionicio Siegel, Alan Saghatelian

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Lipids contribute to the structure, development, and function of healthy brains. Dysregulated lipid metabolism is linked to aging and diseased brains. However, our understanding of lipid metabolism in aging brains remains limited. Here we examined the brain lipidome of mice across their lifespan using untargeted lipidomics. Co-expression network analysis highlighted a progressive decrease in 3-sulfogalactosyl diacylglycerols (SGDGs) and SGDG pathway members, including the potential degradation products lyso-SGDGs. SGDGs show an age-related decline specifically in the central nervous system and are associated with myelination. We also found that an SGDG dramatically suppresses LPS-induced gene expression and release of pro-inflammatory cytokines from macrophages and microglia by acting on the NF-κB pathway. The detection of SGDGs in human and macaque brains establishes their evolutionary conservation. This work enhances interest in SGDGs regarding their roles in aging and inflammatory diseases and highlights the complexity of the brain lipidome and potential biological functions in aging. [Figure not available: see fulltext.]

Original languageEnglish (US)
Pages (from-to)187-197
Number of pages11
JournalNature Chemical Biology
Volume19
Issue number2
DOIs
StatePublished - Feb 2023

ASJC Scopus subject areas

  • Molecular Biology
  • Cell Biology

Fingerprint

Dive into the research topics of 'A class of anti-inflammatory lipids decrease with aging in the central nervous system'. Together they form a unique fingerprint.

Cite this