Rxivist logo

Plasma lipid and liporotein biomarkers in LBC1936: Do they predict general cognitive ability and brain structure?

By Sarah E Harris, Stuart J. Ritchie, Gonçalo D S Correia, Beatriz Jiménez, Chloe Fawns-Ritchie, Alison Pattie, Janie Corley, Susana Munoz-Maniega, Maria Valdés Hernández, John M. Starr, Derek Hill, Paul Wren, Mark Bastin, Matthew R Lewis, Joanna M. Wardlaw, Ian J Deary

Posted 10 Jul 2020
bioRxiv DOI: 10.1101/2020.07.09.194688

Identifying predictors of cognitive ability and brain structure in later life is an important step towards understanding the mechanisms leading to cognitive decline and dementia. This study used ultra-performance liquid chromatography mass spectrometry (UPLC-MS) and nuclear magnetic resonance (NMR) to measure targeted and untargeted metabolites, mainly lipids and lipoproteins, in ~600 members of the Lothian Birth Cohort 1936 (LBC1936) at aged ~73 years. Penalized regression models (LASSO) were then used to identify sets of metabolites that predict variation in general cognitive ability and structural brain variables. UPLC-MS-POS measured lipids, together predicted 19% of the variance in total brain volume and 17% of the variance in both grey matter and normal appearing white matter volumes. Multiple subclasses of lipids were included in the predictor, but the best performing lipid was the sphingomyelin SM(d18:2/14:0) which occurred in 100% of iterations of all three significant models. No metabolite set predicted cognitive ability, or white matter hyperintensities or connectivity. Future studies should concentrate on identifying specific lipids as potential cognitive and brain-structural biomarkers in older individuals. ### Competing Interest Statement The authors have declared no competing interest.

Download data

  • Downloaded 214 times
  • Download rankings, all-time:
    • Site-wide: 128,924
    • In neuroscience: 19,364
  • Year to date:
    • Site-wide: 79,420
  • Since beginning of last month:
    • Site-wide: 53,486

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide