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INTRODUCTION: Fast and minimally invasive approaches for early diagnosis of Alzheimer's disease (AD) are highly anticipated. Evidence of adaptive immune cells responding to cerebral ß-amyloidosis has raised the question of whether immune markers could be used as proxies for ß-amyloid accumulation in the brain. METHODS: Here, we apply multidimensional mass-cytometry combined with unbiased machine-learning techniques to immunophenotype peripheral blood mononuclear cells from a total of 251 participants in cross-sectional and longitudinal studies. RESULTS: We show that increases in antigen-experienced adaptive immune cells in the blood, particularly CD45RA-reactivated T effector memory (TEMRA) cells, are associated with early accumulation of brain ß-amyloid and with changes in plasma AD biomarkers in still cognitively healthy subjects. DISCUSSION: Our results suggest that preclinical AD pathology is linked to systemic alterations of the adaptive immune system. These immunophenotype changes may help identify and develop novel diagnostic tools for early AD assessment and better understand clinical outcomes.
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Enfermedad de Alzheimer , Proteínas tau , Humanos , Estudios Transversales , Leucocitos Mononucleares/metabolismo , Leucocitos Mononucleares/patología , Linfocitos T/metabolismo , Linfocitos T/patología , Péptidos beta-Amiloides/metabolismo , Enfermedad de Alzheimer/patología , Encéfalo/patología , BiomarcadoresRESUMEN
We discuss the experiences and results of the AppStatUZH team's participation in the comprehensive and unbiased comparison of different spatial approximations conducted in the Competition for Spatial Statistics for Large Datasets. In each of the different sub-competitions, we estimated parameters of the covariance model based on a likelihood function and predicted missing observations with simple kriging. We approximated the covariance model either with covariance tapering or a compactly supported Wendland covariance function.
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BACKGROUND: Cystic and alveolar echinococcosis (CE and AE) are neglected tropical diseases caused by Echinococcus granulosus sensu lato and E. multilocularis, and are emerging zoonoses in Kyrgyzstan. In this country, the spatial distribution of CE and AE surgical incidence in 2014-2016 showed marked heterogeneity across communities, suggesting the presence of ecological determinants underlying CE and AE distributions. METHODOLOGY/PRINCIPAL FINDINGS: For this reason, in this study we assessed potential associations between community-level confirmed primary CE (no.=2359) or AE (no.=546) cases in 2014-2016 in Kyrgyzstan and environmental and climatic variables derived from satellite-remote sensing datasets using conditional autoregressive models. We also mapped CE and AE relative risk. The number of AE cases was negatively associated with 10-year lag mean annual temperature. Although this time lag should not be considered as an exact measurement but with associated uncertainty, it is consistent with the estimated 10-15-year latency following AE infection. No associations were detected for CE. We also identified several communities at risk for CE or AE where no disease cases were reported in the study period. CONCLUSIONS/SIGNIFICANCE: Our findings support the hypothesis that CE is linked to an anthropogenic cycle and is less affected by environmental risk factors compared to AE, which is believed to result from spillover from a wild life cycle. As CE was not affected by factors we investigated, hence control should not have a geographical focus. In contrast, AE risk areas identified in this study without reported AE cases should be targeted for active disease surveillance in humans. This active surveillance would confirm or exclude AE transmission which might not be reported with the present passive surveillance system. These areas should also be targeted for ecological investigations in the animal hosts.