Association of Lipidomics Signatures in Blood with Clinical Progression in Preclinical and Prodromal Alzheimer's Disease

Background: Lipidomics may provide insight into biochemical processes driving Alzheimer's disease (AD) pathogenesis and ensuing clinical trajectories. Objective: To identify a peripheral lipidomics signature associated with AD pathology and investigate its potential to predict clinical progression. Methods: We used Bayesian elastic net regression to select plasma lipid classes associated with the CSF pTau/A beta(42) ratio as a biomarker of AD pathology in preclinical and prodromal AD cases from the ADNI cohort. Consensus clustering of the selected lipid classes was used to identify lipidomic endophenotypes and study their association with clinical progression. Results: In the APOE4-adjusted model, ether-glycerophospholipids, lyso-glycerophospholipids, free-fatty acids, cholesterol esters, and complex sphingolipids were found to be associated with the CSF pTau/A beta(42) ratio. We found an optimal number of five lipidomic endophenotypes in the prodromal and preclinical cases, respectively. In the prodromal cases, these clusters differed with respect to the risk of clinical progression as measured by clinical dementia rating score conversion. Conclusion: Lipid alterations can be captured at the earliest phases of AD. A lipidomic signature in blood may provide a dynamic overview of an individual's metabolic status and may support identifying different risks of clinical progression.

Automated summary

This study found that lipid alterations can be observed in the early stages of Alzheimer's disease and that a specific lipidomic signature in blood may provide insights into an individual's metabolic status and predict the risk of clinical progression.