Affiliations: [a] Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany
| [b] German Centre for Neurodegenerative Diseases (DZNE), Rostock, Germany
| [c] Anatomy Research Group, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, Oldenburg, Germany
| [d] Research Centre for Neurosensory Science, Carl von Ossietzky University Oldenburg, Oldenburg, Germany
Correspondence:
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Correspondence to: Fatemah A. Sakr, MSc, PhD candidate, Marie-Curie Early-Stage Researcher under the ITN-ETN H2020 BBDiag; Clinical Dementia Research Department, University Medicine Rostock, Rostock, Germany; German Centre for Neuro-degenerative Diseases (DZNE), Gehlsheimer Str. 20, 18147 Rostock, Germany. Tel.: +49 381 494 9487; Fax: +49 381 494 9472; E-mails: [email protected]; [email protected].
Note: [1] Data used in the preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) data-base (http://adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and provided data but did not participate in the analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf
Abstract: 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/Aβ42 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/Aβ42 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.
