Biology subjects

De Bastiani, M. A.

Publications and source records attributed to De Bastiani, M. A..

3 recordsLinked to original sources

bioRxiv2026

Metabolic brain network reorganization precedes clinical conversion in Alzheimer's disease

Structured AbstractO_ST_ABSIntroductionC_ST_ABSBrain glucose hypometabolism is a hallmark of Alzheimers disease (AD), yet conventional [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) analyses have limited sensitivity in preclinical stages. Metabolic brain network approaches may better capture early vulnerability preceding clinical conversion. MethodsCognitively unimpaired individuals (n = 127) from the ADNI cohort with baseline FDG-PET and amyloid (A) and tau (T) status were classified as clinically stable or converters over an average longitudinal follow-up of 5.8 years. Baseline brain FDG uptake patterns were analyzed at the regional, voxel, and network levels across AT profiles. Network density was quantified globally and within functional networks. AD biomarkers and cognitive performance were also examined. ResultsConventional FDG-PET SUVr analyses failed to distinguish cognitively stable individuals from clinical converters at baseline, either at the regional or voxel levels. AT(N) biomarkers and neuropsychological performance likewise did not differ significantly between groups. In contrast, clinical converters exhibited hyperconnected metabolic networks at baseline, including within the default-mode network. These effects were consistent across A-T-, A+T-, and A+T+ groups, with network density higher in clinical converters than in cognitively stable individuals. Conversely, network density among stable individuals declined with AT progression, pointing to divergent network trajectories. DiscussionMetabolic network organization analysis revealed early AD-related vulnerability beyond regional hypometabolism, even before detectable amyloid positivity, and may reflect divergent trajectories of resilience and pathological propagation preceding clinical conversion. By leveraging existing FDG-PET datasets, this framework offers a valuable opportunity to identify individuals at risk of clinical progression at scale.

neuroscience↗

bioRxiv2022

Hippocampal GFAP-positive astrocyte responses to amyloid and tau pathologies

IntroductionIn Alzheimers disease clinical research, glial fibrillary acidic protein (GFAP) released into the cerebrospinal fluid and blood is widely measured and perceived as a biomarker of reactive astrogliosis. However, it was demonstrated that GFAP levels differ in individuals presenting with amyloid-{beta} (A{beta}) or tau pathology. The molecular underpinnings behind this specificity are unexplored. Here we investigated biomarker and transcriptomic associations of GFAP-positive astrocytes with A{beta} and tau pathologies in humans and mouse models. MethodsWe studied 90 individuals with plasma GFAP, A{beta}- and Tau-PET to investigate the association between biomarkers. Then, transcriptomic analysis in hippocampal GFAP-positive astrocytes isolated from mouse models presenting A{beta} (PS2APP) or tau (P301S) pathologies was applied to explore differentially expressed genes (DEGs), Gene Ontology processes, and protein-protein interaction networks associated with each phenotype. ResultsIn humans, we found that plasma GFAP associates with A{beta} but not tau pathology. Unveiling the unique nature of GFAP-positive astrocytic responses to A{beta} or tau pathology, mouse transcriptomics showed scarce overlap of DEGs between the A{beta} and tau mouse models, While A{beta} GFAP-positive astrocytes were overrepresented with genes associated with proteostasis and exocytosis-related processes, tau hippocampal GFAP-positive astrocytes presented greater abnormalities in functions related to DNA/RNA processing and cytoskeleton dynamics. ConclusionOur results offer insights into A{beta}- and tau-driven specific signatures in GFAP-positive astrocytes. Characterizing how different underlying pathologies distinctly influence astrocyte responses is critical for the biological interpretation of astrocyte-related biomarker and suggests the need to develop context-specific astrocyte targets to study AD. FundingThis study was supported by Instituto Serrapilheira, Alzheimers Association, CAPES, CNPq and FAPERGS.

neuroscience↗

bioRxiv2021

Transcriptomic similarities and differences between mouse models and human Alzheimer's Disease

Alzheimers disease (AD) is a multifactorial pathology, with most cases having a sporadic origin. Recently, knock-in (KI) models have been developed with the promise of resembling better sporadic human AD, such as the novel hA{beta}-KI mouse. Here, we compared hippocampal publicly available transcriptomic profiles of transgenic (5xFAD and APP/PS1) and KI (hA{beta}-KI) mouse models with early- (EOAD) and late- (LOAD) onset AD patients. Experimental validation of consistently dysregulated genes revealed four altered in mice (SLC11A1, S100A6, CD14, CD33, C1QB) and three in humans (S100A6, SLC11A1, KCNK). Additionally, the three mouse models presented more Gene Ontology biological processes terms and enriched signaling pathways in common with LOAD than with EOAD individuals. Finally, we identified 17 transcription factors potentially acting as master regulators of AD. Our cross-species analyses revealed that the three mouse models presented a remarkable similarity to LOAD, with the hA{beta}-KI being the more specific one.

neuroscience↗