Biology subjects

Bellaver, B.

Publications and source records attributed to Bellaver, B..

5 recordsLinked to original sources

bioRxiv2026

Evaluation of harmonization methods to mitigate assay and cohort effects in plasma p-tau217

INTRODUCTIONThe growing number of assay platforms measuring blood-based biomarkers (BBMs) for Alzheimers disease (AD) has introduced challenges in interpretability and comparability across assays. Differences across studies also limit comparability of data. To address these challenges, a systematic evaluation of harmonization methods is needed to support BBM data integration within or across studies. METHODSTwo multisite studies, Alzheimers Disease Neuroimaging Initiative (ADNI, n = 219) and Human Connectome Project (HCP, n = 111), were used to evaluate harmonization methods for mitigating assay and cohort effects in plasma p-tau217 measurements. Methods includes various normalization, regression, and standardization approaches, including the recently developed CentiMarker. Assay effects were evaluated using repeated-measures data across assay platforms within each cohort, whereas cohort effects were assessed using pooled ADNI and HCP data. Harmonization performance was evaluated using distributional statistics and downstream modeling of p-tau217. RESULTSQuantile normalization and quantile mapping methods were most effective for mitigating assay effects, whereas conditional quantile mapping performed best for pooled multi-cohort data. These methods also preserved biological variability. In contrast, simple means adjustment and reference-based z-score standardization were least effective for mitigating assay effects, while simple means adjustment, z-score standardization, and quantile normalization were least effective for mitigating cohort effects. CentiMarker had minimal impact on assay or cohort effects. DISCUSSIONBased on our evaluation, we recommend (conditional) quantile mapping for p-tau217 studies integrating data across multiple assays or cohorts. In contrast, we caution against using CentiMarker and z-score-based methods, as they limit comparability and do not effectively mitigate technical variability.

neuroscience↗

bioRxiv2024

Impact of cardiometabolic factors and blood beta-amyloid on the volume of white matter hyperintensities in dementia-free subjects with cognitive complaints

IntroductionWhite matter hyperintensities (WMH) in Alzheimers disease (AD) have traditionally been associated with cerebrovascular diseases. Amyloid {beta} (A{beta}) deposition reportedly contributes to WMHs; however, this relationship remains unclear in dementia-free subjects with cognitive complaints (CC). Here, we explored the relationship between WMHs and cardiometabolic and A{beta} blood biomarkers in a community-based cohort of Latin American CC participants. MethodsWe recruited 112 individuals with CC (69 - 92 YO, 90 females) with available plasma A{beta} biomarkers and cardiometabolic markers (systolic - diastolic blood pressure and glycaemia). WMHs were quantified using a lesion segmentation tool based on SPM12 and segmented using the John Hopkins University (JHU) Atlas and ALVIN segmentation for periventricular and subcortical white matter. Linear multiple regression models were fitted to assess total WMH lesions and the segmented tract, using demographics, cardiometabolic, and A{beta} blood biomarker measures as independent variables. ResultsAfter multiple comparison corrections, diastolic blood pressure was associated with WMHs, specifically in the right anterior thalamic radiation, left cingulum, minor forceps, and subcortical ALVIN segmentation. Glycaemia was associated with WMH volume in forceps major, forceps minor, and right fronto-occipital fasciculi. Conversely, A{beta} blood biomarkers and systolic blood pressure showed no association with WMH overall or in specific tracts. ConclusionOur findings suggest that, in dementia-free CC individuals, WMH volume was more related to cardiometabolic factors, whereas A{beta} blood biomarkers might be of less relevance. Dementia prevention strategies in individuals might be a useful focus for managing high peripheral vessel resistance and endothelial damage due to hypertension and hyperglycaemia.

neuroscience↗

bioRxiv2023

Short-term consumption of ultra-processed semi-synthetic diets impairs the sense of smell and brain metabolism in mice

The prevalence of highly-palatable, ultra-processed food in our modern diet has exacerbated obesity rates and contributed to a global health crisis. While accumulating evidence suggests that chronic consumption of ultra-processed semi-synthetic food is detrimental to sensory and neural physiology, it is unclear whether its short-term intake has adverse effects. Here, we assessed how short-term consumption (<2 months) of three ultra-processed diets (one grain-based diet, and two semi-synthetic) influence olfaction and brain metabolism in mice. Our results demonstrate that short-term consumption of semi-synthetic diets, regardless of macronutrient composition, adversely affect odor-guided behaviors, physiological responses to odorants, transcriptional profiles in the olfactory mucosa and brain regions, and brain glucose metabolism and mitochondrial respiration. These findings reveal that even short periods of ultra-processed semi-synthetic food consumption are sufficient to cause early olfactory and brain abnormalities, which has the potential to alter food choices and influence the risk of developing metabolic disease.

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↗