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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‐tau181, which was in turn directly associated with CSF neurofilament light (NfL). Plasma glial fibrillary acidic protein (GFAP) mediated the relationship between CSF Aβ42/40 and Aβ‐PET, and CSF YKL‐40 partly explained the association between Aβ‐PET, p‐tau181, 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 Aβ42/40 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. [ABSTRACT FROM AUTHOR]

Background: Cognitively unimpaired (CU) adults with Alzheimer's disease (AD) pathologic change may be more vulnerable to developing neuropsychiatric symptoms. We reported an association of higher β‐amyloid (Aβ) and increased anxiety/depression during the COVID‐19 lockdown in CU adults (Akinci et al., 2022). Here, we investigated whether changes in Aβ1−42 predict post‐traumatic stress disorder (PTSD) symptomatology following COVID‐19 lockdown in CU adults at risk for AD. Method: We included 128 CU participants who underwent lumbar puncture 2.3±0.6 years before and 1.1±0.4 years after the lockdown. The outcome of interest was self‐reported PTSD symptomatology (Impact of Event Scale Revised) measured 1.7±0.1 years after the lockdown. The main predictor was annual rate of change in cerebrospinal fluid (CSF) Aβ1−42 measured with the NeuroToolKit panel of robust prototype assays (Roche Diagnostics International Ltd, Rotkreuz, Switzerland). Other predictors included sex, age, years of education, stressors during COVID‐19, and anxiety/depression (Hospital Anxiety and Depression Scale, HADS) and perceived stress (Perceived Stress Scale, PSS) measured during lockdown. We performed regression analyses to explore the association between annual rate of change in Aβ1‐42 with PTSD scores adjusting for demographic and stressor variables, and further adjusting for HADS and PSS scores. We then explored the mediating effect of HADS and PSS on the association between change in Aβ1‐42 and PTSD scores. Result: Participant age ranged from 53−72 and 59% were women (Table 1). Independent of demographic variables and stressors experienced during COVID‐19, the rate of annual change in Aβ1‐42 predicted PTSD scores (p =.008; Table 2). This association attenuated after introducing HADS and PSS scores into the model (p =.066). We found full mediation effects of HADS and PSS scores, explaining 46% and 40% of the effect of annual change in Aβ1‐42 on PTSD scores, respectively (Figure 1). Conclusion: CU older adults with longitudinal CSF Aβ1−42 increases are more vulnerable to developing PTSD symptomatology after a stressful event, such as the pandemic. Anxiety/depression is one plausible mechanism through which increases in Aβ might exacerbate PTSD symptomatology. The results suggest a window for stress regulation during stressful events to prevent further mental health worsening in people at risk for AD. [ABSTRACT FROM AUTHOR]

Background: Epidemiologic studies show that multiparity (≥3 children) is associated with a higher risk of clincal AD in cognitively unimpaired (CU) women. However, studies exploring the impact of parity on AD biomarkers are scarce. We explored the association between number of children and imaging and fluid AD biomarkers, and the related interaction with neurodegeneration and cognition. Method: We included 210 CU parous women from the ALFA+ cohort with 34 nulliparous women and 152 men with children as controls. The number of children was dichotomized as <3 children vs ≥3 children. All CSF biomarkers were measured using the Roche NeuroToolKit and Elecsys® immunoassays (both Roche Diagnostics International Ltd), except p‐tau231 and GAP‐43 (ELISA). All plasma biomarkers were measured using the Simoa HD‐X (Quanterix Corp) except sICAM1 (MSD). Jack's cortical thickness AD signature was used as a marker of neurodegeneration. Cognitive change (3‐year follow‐up) was measured with a PACC‐like composite as well as for individual cognitive domains. Biomarkers differences between parity groups were analyzed with ANCOVA adjusted by age. Independent linear models with biomarkers, AD signature and cognitive change as dependent variable were constructed. The number of children was set as predictor, and age, APOE‐ε4, and age at first birth as covariates in all models. Interaction terms between number of children and biomarkers were modeled. p‐values <0.05 were considered as significant. Result: Several biomarkers were significantly higher in grand multiparours women (Table 1). Linear regression results (Table 2, Fig. 1A) showed that multiparity was associated with higher CSF p‐tau181 levels. Moreover, multiparity interacted with CSF p‐tau181 to predict thinner cortical thickness in AD‐sensitive regions and a steeper decline in executive function (Table 2, Fig. 1B & 1C). No significant associations in men and nulliparous women were found. Conclusion: Having ≥3 children increases the risk of higher CSF p‐tau181 levels in CU middle‐aged women, with CSF p‐tau181 having a more deleterious effect on cortical thickness and change on executive function performance. These findings contribute to our understanding of the higher risk for AD observed in CU multiparous women, who show higher susceptibility and more adverse downstream consequences to tau pathology. [ABSTRACT FROM AUTHOR]

Background: Biochemical changes, which may precede morphological changes, could be of great relevance in profiling preclinical AD. We aimed to investigate metabolic changes using magnetic resonance spectroscopy (MRS) in three AD‐relevant regions: right hippocampus, right angular gyrus, and right precuneus, focusing on myoinositol due to its role in glial activity (osmoregulation‐neuroinflammation). Method: Three hundred sixty‐six participants from the ALFA+ cohort underwent three single‐voxel MRS (PRESS sequence, TR = 2000ms; TE = 100ms chosen to invert myoinositol peak for more precise quantitation; volume of interest (VOI): 20×20×20mm3 [25×20×16mm3 for hippocampus]). Figure 1 shows VOI location and MRS samples. Concentrations of N‐acetyl‐containing compounds (NAA) that is a neuronal marker, total creatine (Cr) related to brain energy, myoinositol (mI), choline‐containing compounds (Cho) related to cell proliferation, and glutamate/glutamine were calculated with LCModel in arbitrary units (using water reference) with the default settings and basis set adapted to the acquisition conditions. Concentrations were corrected for VOI CSF content. Remaining VOI gray matter percentage was used as a confounder in all analyses, jointly with age, sex, and APOE‐e4 status (carrier/non‐carrier). We investigated the correlation of MRS metabolite concentrations with CSF concentrations of Aβ42/40 and ptau‐181 as biomarkers for AD (Elecsys®; Roche Diagnostics). For completeness, we also checked the dependency of MRS metabolites on age. MRS not meeting QA criteria were discarded (Cramer‐Rao lower bounds >20 for any of the metabolites or imprecise VOI location). The statistical threshold was set to p<0.05 for all the analyses. Result: Table 1 shows characteristics of the subsamples with MRS in each location. Higher myoinositol levels in hippocampus and angular gyrus were associated with lower CSF Ab42/40, but not in the precuneus, where it was associated with higher Cr/Cho ratio. Higher Cr and NAA were positively associated with higher CSF p‐tau181 levels in the angular gyrus. NAA was negatively associated with age on cortical regions, as well as Cr on the angular gyrus. Table 2 summarizes the main results. Conclusion: MRS allowed determination of differential metabolite changes in AD‐related regions in preclinical AD. Further research is warranted to better characterize the nature of these metabolic changes and determine their impact on longitudinal outcomes of these participants. [ABSTRACT FROM AUTHOR]

Background: Intracranial cerebrospinal fluid (CSF) motion is driven by the wave pressure associated with arterial blood flow into the skull (Figure 1). Since one of the roles of CSF is the clearance of neural waste, it was investigated the relationship between blood and CSF flow parameters (as measured by magnetic resonance imaging [MRI]) and CSF Ab42/40 and ptau‐181 levels in the preclinical stages of Alzheimer's disease (AD). Method: Three hundred sixty‐five subjects from the ALFA+ cohort underwent two MRI phase‐encoded velocity sequences (30 frames per cardiac cycle) to measure (1) blood flow in carotids below carotid bifurcation and (2) CSF flow through foramen magnum. The scanner's Q‐flow tool was used to quantify stroke volume (volume per cardiac cycle), percent of vessel's area increase and flow velocity increase, as a proxy for vessel elasticity and flow pulsatility, respectively. Associations between flow parameters and age, CSF Ab42/40 and ptau‐181 concentrations were sought, correcting for sex, age and time between lumbar puncture and MRI (P<0.05). Result: One hundred thirty‐two subjects were excluded because the scanning session was not completed, showed missing or outlier values or did not pass quality control (artifacts or unbalanced outwards‐inwards CSF flow measures), resulting in a final sample size of 233 participants (mean age [SD]: 60.8±4.5 years; male: n = 73 [31.3%]). Figure 2 shows the plots with the most significant relationships between flow parameters, CSF biomarkers, CSF volume and age. It was observed that a higher stroke volume in CSF flow was associated with lower Ab42/40 and higher ptau‐181 concentrations in CSF. Conclusion: These results indicate that, despite the role of CSF in waste clearance, the accumulation of amyloid and tau in the brain might be neither caused nor enhanced by a global deficit in CSF circulation. We hypothesize that a higher volume of CSF associated with age and high ptau‐181 levels and/or the loss of parenchyma elasticity might reduce the global intracranial compressibility, resulting in an enhanced response to pressure increase due to blood flow into the skull, which could explain the observed increase in CSF flow associated with the early stages of AD. [ABSTRACT FROM AUTHOR]

Background: Neuroimaging‐derived brain‐age is a useful biomarker to study the brain's biological aging process. Brain‐age has shown cross‐sectional associations with cognitive function and modifiable risk factors for dementia. We aimed to study, in cognitively unimpaired (CU) individuals, the mediating role of brain‐age in the association between modifiable risk factors and cognitive changes, and the impact of AD pathology on this role. Method: We included 416 CU individuals from the ALFA+ study with available structural MRI, measurements of the global cognitive Preclinical Alzheimer's Cognitive Composite (PACC) (370 individuals had a follow‐up PACC assessment 3.28±0.27 years later), and lifestyle and cardiovascular risk factors assessments. We computed brain‐age delta as the difference between chronological and predicted brain‐age using a previously pre‐trained machine learning algorithm on structural MRI data. Partial Least Squares Path Modeling (PLS‐PM) was employed to investigate the mediation effect of brain‐age delta between a computed latent variable from modifiable risk factors (cardiovascular, mental health and mood, metabolic/endocrine disease history, and alcohol consumption factors; Table 1) and a latent variable from longitudinal PACC. Statistical bias adjustment was performed to control for the confounding effects of age and sex by using multiple linear regression. The analysis was performed on the whole sample (ALL) and after stratification by amyloid‐β (Aβ) status. Participants were classified as amyloid‐β positive (Aβ+) if CSF Aβ42/40<0.071 (Milà‐Alomà et al, 2020). Significance of mediation was examined by 95% confidence interval bootstrap. Result: The effect of risk factors (latent risk) on longitudinal cognition (latent cognition) was partially mediated by brain‐age delta only in Aβ+ individuals (57.286%) (Figure 1C). Higher latent risk was associated with older brain‐age delta (p = 0.003) and older brain‐age delta was associated with worse latent cognition (p = 0.007). Conversely, the indirect effect was not significant in ALL nor in Aβ‐ individuals, where brain‐age delta was not significantly associated with latent cognition (Figure 1A‐B). Still, higher latent risk was associated with older brain‐age delta (ALL: p<0.001; Aβ‐: p = 0.004) and associated with worse latent cognition (ALL: p = 0.012, Aβ‐: p = 0.001). Conclusion: In CU individuals in the AD continuum, biological brain aging mediates the association between modifiable risk factors and cognitive decline. [ABSTRACT FROM AUTHOR]

Background: Glial fibrillary acidic protein (GFAP) and chitinase‐3‐like protein 1 (YKL‐40) are biomarkers of different astrocyte phenotypes, both of which are elevated in the dementia phase of Alzheimer's disease (AD). However, the specific contribution of these astrocyte phenotypes early in the AD continuum is not fully understood. Here, we studied how these two astrocyte phenotypes mediate the early pathogenic cascade in the preclinical stage of AD. Method: We assessed 384 cognitively unimpaired individuals from the ALFA+ study with amyloid‐β (Aβ)42/40, phosphorylated tau (p‐tau181), neurofilament light (NfL) and YKL‐40 measured in cerebrospinal fluid (CSF) and GFAP measured in plasma, as well as [18F]flutemetamol positron emission tomography (PET) and neuropsychological testing (Annual change in the Preclinical Alzheimer's Cognitive Composite [PACC]). Path analysis using structural equation modelling was used to quantify the relationships between biomarkers of reactive astrogliosis and Amyloid‐Tau‐Neurodegeneration biomarkers, while incorporating age, sex, and apolipoprotein E (APOE) ε4 effects. Direct effects with FDR‐corrected p‐values below.05 were considered significant. Result: CSF Aβ42/40 was associated with Aβ aggregation as measured by PET and with CSF p‐tau181, respectively. The latter was associated with CSF NfL, but no associations were found between any biomarkers and PACC changes in this early sample (Figure 1; Table 1). Plasma GFAP mediated the association between CSF Aβ42/40 and Aβ‐PET. Additionally, CSF YKL‐40 mediated the association between Aβ‐PET and p‐tau181 and between p‐tau181 and NfL. APOE ε4 had a direct association with CSF Aβ42/40 only, whereas age had independent associations with CSF Aβ42/40, NfL, GFAP and YKL‐40. Male sex was associated with higher CSF NfL levels, independently of other variables tested. Conclusion: Our results suggest that astrocyte phenotypes that release GFAP into the blood influence the aggregation of soluble Aβ into fibrillary plaques. On the other hand, those releasing YKL‐40 into the CSF appear to play a role later in the pathological cascade, mediating downstream tau pathology and neuronal damage. These results indicate that different astrocyte phenotypes are specifically involved in distinct stages of the early pathological cascade in preclinical AD. Interventions targeting astrocyte dysfunction in preclinical stages may prevent or delay the onset of AD dementia. [ABSTRACT FROM AUTHOR]