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Background: CSF Aβ42 is thought to show AD‐related alterations earlier than amyloid‐β PET. Therefore, cognitively unimpaired (CU) individuals with abnormal CSF Aβ42 and normal amyloid‐β PET are believed to be in the earliest stages of the AD continuum. In this work, we sought to detect structural cerebral alterations in CU individuals with discordant status in these amyloid‐β biomarkers using Machine Learning techniques. Method: We included 498 CU individuals from the ALFA+ and ADNI studies with available MRI, amyloid‐β PET and CSF Aβ42 measurements, the latter measured with the exploratory Roche NeuroToolKit assays, a panel of automated robust prototype immunoassays. In addition, we calculated Centiloid (CL) values for the PET measurements. Individuals were categorized as CSF‐/PET‐, CSF+/PET‐ and CSF+/PET+ according to established cut‐offs (CSF Aβ42<1098pg/mL for ALFA+ and <880pg/mL for ADNI, and CL<17 for PET). We trained XGBoost classifiers to predict amyloid‐β positivity using as features age, sex, APOE‐ɛ4 status, brain volumes and cortical thicknesses, obtained with Freesurfer 6.0 and the Desikan‐Kiliany atlas. Relevant features for pairwise‐group classification were sought (CSF‐/PET‐ vs CSF+/PET‐; CSF+/PET‐ vs CSF+/PET+; CSF‐/PET‐ vs CSF+/PET+), calculating SHAP values to determine the most important features for prediction. Result: With respect the CSF‐/PET‐ group, the CSF+/PET‐ showed decreased gray matter volumes in the anterior and posterior cingulate/precuneus and increases in the lateral ventricles and bilateral parahippocampal gyri, among other regions (Figure 1A). Unexpectedly, the posterior cingulate/precuneus showed the opposite effect in cortical thickness measurements. These patterns were similar but more prominent in the comparison between the CSF‐/PET‐ vs CSF+/PET+ group (Figure 1B). Finally, CSF+/PET‐ group was characterized, with respect the CSF+/PET+ group by higher volume of the bilateral supramarginal gyri and lower cortical thickness in the posterior cingulate/precuneus (Figure 1C). Regarding the other variables in the model, APOE‐ɛ4 status was the most predictive variable in models with respect the CSF‐/PET‐ group and age in the CSF+/PET‐ vs CSF+/PET+ comparison. Conclusion: Our results show that model‐free machine learning techniques can detect complex brain morphological alterations in the earliest stages of the AD continuum. Interestingly, some regions showed increases in volume and/or cortical thickness which may reflect compensatory or inflammatory effects. [ABSTRACT FROM AUTHOR]

Background: Cerebral beta‐amyloid (Aβ) deposition disrupts functional resting‐state connectivity in cognitively unimpaired (CU) individuals. However, only a few studies have investigated these associations using Aβ cerebrospinal fluid (CSF) markers. Moreover, the reorganization of functional brain networks across the progressive stages of preclinical Alzheimer's disease (AD) remains poorly understood. Here, we aim to identify functional connectivity (FC) differences in middle‐aged CU individuals, grouped as a function of both CSF Aβ (A) and pathological tau (T). Method: We analyzed CSF and resting‐state functional magnetic resonance imaging (fMRI) data from 349 CU participants of the ALFA study (mean age=60.21 years). CSF Aβ42 and Aβ40 were assessed with the exploratory Roche NeuroToolKit robust prototype immunoassays, while p‐Tau181 was measured with the Elecsys® Phospho‐Tau (181P) CSF immunoassay (Roche Diagnostics International Ltd). Participants were grouped into three categories according to their biomarker status, resulting in three groups: A‐T‐, A+T‐, and A+T+. fMRI volumes were parceled into 218 regions, and correlations in the filtered fMRI signal among parcels were computed. We first assessed the impact of continuous CSFAβ42/40 concentration in the entire sample and subsequently assessed AT biomarker group differences in FC. A threshold of uncorrected p<0.005 using non‐parametric pair‐wise clustering was implemented. Result: A higher cerebral Aβ deposition, reflected by lower CSFAβ42/40, was associated with reduced FC within the default mode network (DMN), but increased FC between the visual network and the DMN, as well as the salience networks. Compared with A‐T‐, A+T‐ showed decreased within‐DMN connectivity (Fig. 1). Finally, compared with A+T‐, A+T+ individuals showed reduced FC within the temporo‐hippocampal (THN) and the executive control networks (ECN) (Fig. 2). Conclusion: This is the first study assessing FC in CU individuals adopting a staging of preclinical AD relying on multiple CSF biomarker classification. We report that CSFAβ42/40 disrupts the DMN but the co‐occurrence of Aβ and tau yields reduced connectivity in the THN and ECN, suggesting that Aβ and tau may interact in promoting a network reconfiguration extending beyond the DMN. Future studies shall clarify whether these differences reflect a correlate of pathology or rather a compensatory strategy to support cognitive performance in the face of AD pathology. [ABSTRACT FROM AUTHOR]

Introduction: We studied how biomarkers of reactive astrogliosis mediate the pathogenic cascade in the earliest Alzheimer's disease (AD) stages., Methods: We performed path analysis on data from 384 cognitively unimpaired individuals from the ALzheimer and FAmilies (ALFA)+ study using structural equation modeling to quantify the relationships between biomarkers of reactive astrogliosis and the AD pathological cascade., Results: Cerebrospinal fluid (CSF) amyloid beta (Aβ) 42/40 was associated with Aβ aggregation on positron emission tomography (PET) and with CSF p-tau 181 , which was in turn directly associated with CSF neurofilament light (NfL). Plasma glial fibrillary acidic protein (GFAP) mediated the relationship between CSF Aβ 42/40 and Aβ-PET, and CSF YKL-40 partly explained the association between Aβ-PET, p-tau 181 , and NfL., Discussion: Our results suggest that reactive astrogliosis, as indicated by different fluid biomarkers, influences the pathogenic cascade during the preclinical stage of AD. While plasma GFAP mediates the early association between soluble and insoluble Aβ, CSF YKL-40 mediates the latter association between Aβ and downstream Aβ-induced tau pathology and tau-induced neuronal injury., Highlights: Lower CSF Aβ 42/40 was directly linked to higher plasma GFAP concentrations. Plasma GFAP partially explained the relationship between soluble Aβ and insoluble Aβ. CSF YKL-40 mediated Aβ-induced tau phosphorylation and tau-induced neuronal injury., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Detection of Alzheimer's disease (AD) pathophysiology among cognitively unimpaired individuals and those experiencing subjective cognitive decline (SCD) remains challenging. Plasma p-tau217 is one of the most promising of the emerging biomarkers for AD. However, accessible methods are limited., Methods: We employed a novel p-tau217 immunoassay (UGOT p-tau217) in four independent cohorts (n=308) including a cerebrospinal fluid (CSF) biomarker-classified cohort (Discovery), two cohorts consisting mostly of cognitively unimpaired participants (MYHAT and Pittsburgh), and a population-based cohort of individuals with SCD (β-AARC)., Results: UGOT p-tau217 showed high accuracy (AUC= 0.80-0.91) identifying Aβ pathology, determined either by Aβ positron emission tomography or CSF Aβ42/40 ratio. In individuals experiencing SCD, UGOT p-tau217 showed high accuracy identifying those with a positive CSF Aβ42/40 ratio (AUC= 0.91)., Discussion: UGOT p-tau217 can be an easily accessible and efficient way to screen and monitor patients with suspected AD pathophysiology, even in the early stages of the continuum.