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There is increasing evidence of the relationship between sleep and neurodegeneration, but this knowledge is not incorporated into clinical practice yet. We aimed to test whether a basic sleep parameter, as total sleep estimated by actigraphy for 1 week, was a valid predictor of CSF Alzheimer’s Disease core biomarkers (amyloid-β-42 and –40, phosphorylated-tau-181, and total-tau) in elderly individuals, considering possible confounders and effect modifiers, particularly the APOE ε4 allele. One hundred and twenty-seven cognitively unimpaired volunteers enrolled in the Valdecilla Study for Memory and Brain Aging participated in this study. Seventy percent of the participants were women with a mean age of 65.5 years. After adjustment for covariates, reduced sleep time significantly predicted higher t-tau and p-tau. This association was mainly due to the APOE ε4 carriers. Our findings suggest that total sleep time, estimated by an actigraphy watch, is an early biomarker of tau pathology and that APOE modulates this relationship. The main limitation of this study is the limited validation of the actigraphy technology used. Sleep monitoring with wearables may be a useful and inexpensive screening test to detect early neurodegenerative changes.

Oculomotor behavior can provide insight into the integrity of widespread cortical networks, which may contribute to the differential diagnosis between Alzheimer's disease and frontotemporal dementia. Three groups of patients with Alzheimer's disease, behavioral variant of frontotemporal dementia (bvFTD) and semantic variant of primary progressive aphasia (svPPA) and a sample of cognitively unimpaired elders underwent an eye-tracking evaluation. All participants in the discovery sample, including controls, had a biomarker-supported diagnosis. Oculomotor correlates of neuropsychology and brain metabolism evaluated with 18F-FDG PET were explored. Machine-learning classification algorithms were trained for the differentiation between Alzheimer's disease, bvFTD and controls. A total of 93 subjects (33 Alzheimer's disease, 24 bvFTD, seven svPPA, and 29 controls) were included in the study. Alzheimer's disease was the most impaired group in all tests and displayed specific abnormalities in some visually-guided saccade parameters, as pursuit error and horizontal prosaccade latency, which are theoretically closely linked to posterior brain regions. BvFTD patients showed deficits especially in the most cognitively demanding tasks, the antisaccade and memory saccade tests, which require a fine control from frontal lobe regions. SvPPA patients performed similarly to controls in most parameters except for a lower number of correct memory saccades. Pursuit error was significantly correlated with cognitive measures of constructional praxis and executive function and metabolism in right posterior middle temporal gyrus. The classification algorithms yielded an area under the curve of 97.5% for the differentiation of Alzheimer's disease vs. controls, 96.7% for bvFTD vs. controls, and 92.5% for Alzheimer's disease vs. bvFTD. In conclusion, patients with Alzheimer's disease, bvFTD and svPPA exhibit differentiating oculomotor patterns which reflect the characteristic neuroanatomical distribution of pathology of each disease, and therefore its assessment can be useful in their diagnostic work-up. Machine learning approaches can facilitate the applicability of eye-tracking in clinical practice.