Biology subjects

Rosa-Neto, P.

Publications and source records attributed to Rosa-Neto, P..

18 recordsLinked to original sources

bioRxiv2026

HIPPOCAMPAL TAU RELATED SIGNAL INDEXES HYPEREXCITABILITY AND NREM SLEEP MEMORY DYSFUNCTION IN TEMPORAL LOBE EPILEPSY

Background Sleep and memory disturbances are common in temporal lobe epilepsy (TLE), yet their relationship with tau-targeted neuroimaging measures remains unclear. We investigated whether in-vivo temporal 18F-MK6240 tracer retention relates to seizure burden, non-rapid eye movement (NREM) sleep microstructure, and memory performance in TLE. Methods This cross-sectional study was conducted from 2019 to 2024 at the Montreal Neurological Institute-Hospital. Eligible patients had unilateral TLE diagnosed according to International League Against Epilepsy criteria and underwent overnight electroencephalography (EEG) recordings, research-protocol 3T magnetic resonance imaging, and 18F-MK6240 positron emission tomography. Regional 18F-MK6240 standardized uptake value ratios (SUVRs), using the cerebellum as the reference region, were quantified in the ipsilateral hippocampus (defined a priori as the primary region of interest), as well as in peri-hippocampal and lateral temporal regions. Electroclinical and neuropsychological measures, including seizure burden (high vs low), N2 interictal epileptiform discharge frequency (frequent vs non-frequent), and memory performance (impaired vs intact), were classified according to predefined clinical criteria. N2 spindle rate and N3 slow-wave rate were quantified from overnight EEG recordings. Findings Of 70 eligible patients, 25 were included (eight [32%] females; mean age 35.2 years [SD 12.1]). Higher ipsilateral hippocampal 18F-MK6240 uptake was observed in participants with greater focal seizure burden (median [IQR] 0.70 [0.67-0.78] vs 0.64 [0.58-0.65], rank-biserial correlation=-0.58, 95% CI -0.82 to -0.19; p=0.02), was associated with lower N2 spindle rate (r=-0.42, 95% CI -0.70 to -0.03; p=0.04) and higher N3 slow-wave rate (r=0.47; 95% CI 0.09 to 0.73; p=0.02), and was also higher in participants with impaired than intact memory performance (n=21; mean [SD] 0.80 [0.12] vs 0.68 [0.10], Cohen's d=1.15, 95% CI 0.07 to 2.21; p=0.04). Associations outside the hippocampus were generally less consistent and less precise, with the largest non-hippocampal estimate observed in peri-hippocampal regions. Interpretation Higher hippocampal 18F-MK6240 uptake was associated with greater focal seizure burden, altered NREM sleep microstructure, and impaired memory performance in TLE. These findings suggest that hippocampal 18F-MK6240 uptake may represent a candidate marker of circuit vulnerability associated with NREM sleep-memory dysfunction in TLE, warranting validation in larger longitudinal studies.

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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.

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bioRxiv2025

Amyloid-β 42-carrying extracellular vesicles are associated with neurodegeneration and neuroinflammation in Alzheimer's disease

Alzheimers disease (AD) is the most common form of dementia, characterized by progressive amyloid-{beta} (A{beta}) accumulation and neurodegeneration. Extracellular vesicles (EVs) have been implicated in AD pathology, but their relationship to disease progression and the cerebrospinal fluid (CSF) proteome remains poorly understood. In this study, we analysed plasma-derived A{beta}42-containing EVs from participants of the Alzheimers Disease Neuroimaging Initiative (ADNI) and calculated the ratio between the percentage of A{beta}42-positive peripheral EVs and CSF A{beta}42 (rA{beta}42). This ratio was elevated in AD and positively correlated with amyloid pathology as measured by PET. Longitudinal analyses revealed that higher rA{beta}42 values predicted accelerated hippocampal atrophy and cognitive decline, independent of CSF A{beta}42 concentrations. Proteomic profiling of CSF using the SomaScan platform showed that rA{beta}42 was associated with an inflammatory signature characterized by myeloid activation and type II interferon-related signalling pathways. Together, these findings indicate that A{beta}42-carrying EVs reflect an active and inflammatory component of AD pathology and may represent a novel class of biomarkers for disease progression. Understanding the mechanisms that link A{beta}42-positive EVs to neuroinflammatory signalling could open new avenues for pathway-specific diagnostics and therapeutic strategies in AD.

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bioRxiv2025

Molecular and neuropathological determinants of neuronal dysfunction in Alzheimer's disease

The biological basis of neuronal excitatory/inhibitory (E/I) imbalance in Alzheimers disease (AD) remains unclear. Using a comprehensive cohort with ante-mortem functional neuroimaging and post-mortem molecular data from the same participants, we mapped individual, whole-brain E/I imbalances through biophysical modeling. E/I ratios in regions supporting higher-order cognitive functions were significantly associated with cognitive performance and decline, with mediation by global neuropathological burden. We also observed a significant inverted U-shaped relationship between E/I ratios and neurofibrillary tangle severity, peaking at the limbic stage (Braak III-IV) in 14 brain areas, including the bilateral hippocampus and superior frontal gyrus. In addition, we identified 89 genes and 101 proteins that predict regional E/I ratios, with pathways related to synaptic signaling and immune response overrepresented. The generalizability of these molecular predictors was confirmed in two independent cohorts, achieving good classification performance for neuropathology severity and AD dementia. Lastly, the estimated E/I imbalances in AD aligned with whole-brain distributions of microglia and oligodendrocyte precursor cells, suggesting that spatial cellular organization contributes to vulnerability to neuronal dysfunction. Overall, this study provides critical insights into the cellular, molecular, and neuropathological signatures of circuit-level dysfunction in AD.

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bioRxiv2025

Inter-individual variability of neurotransmitter receptor and transporter density in the human brain

Neurotransmitter receptors guide the propagation of signals between brain regions. Mapping receptor distributions in the brain is therefore necessary for understanding how neurotransmitter systems mediate the link between brain structure and function. Normative receptor density can be estimated using group averages from Positron Emission Tomography (PET) imaging. However, the generalizability and reliability of group-average receptor maps depends on the inter-individual variability of receptor density, which is currently unknown. Here we collect group standard deviation brain maps of PET-estimated protein abundance for 12 different neurotransmitter receptors and transporters across 7 neurotransmitter systems, including dopamine, serotonin, acetylcholine, glutamate, GABA, cannabinoid, and opioid. We illustrate how cortical and subcortical inter-individual variability of receptor and transporter density varies across brain regions and across neurotransmitter systems. We complement inter-individual variability with inter-regional variability, and show that receptors that vary more across brain regions than across individuals also demonstrate greater out-of-sample spatial consistency. Altogether, this work quantifies how receptor systems vary in healthy individuals, and provides a means of assessing the generalizability of PET-derived receptor density quantification.

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bioRxiv2025

Translating the Post-Mortem Brain Multi-Omics Molecular Taxonomy of Alzheimer's Dementia to Living Humans

Alzheimers disease (AD) dementia is characterized by significant molecular and phenotypic heterogeneity, which confounds its mechanistic understanding, diagnosis, and effective treatment. In this study, we harness the most comprehensive dataset of paired ante-mortem blood omics, clinical, psychological, and post-mortem brain multi-omics data and neuroimaging to extensively characterize and translate the molecular taxonomy of AD dementia to living individuals. First, utilizing a comprehensive integration of eight complementary molecular layers from brain multi-omics data (N = 1,189), we identified three distinct molecular AD dementia subtypes exhibiting strong associations with cognitive decline, sex, psychological traits, brain morphology, and characterized by specific cellular and molecular drivers involving immune, vascular, and oligodendrocyte precursor cells. Next, in a significant translational effort, we developed predictive models to convert these advanced brain-derived molecular profiles (AD dementia pseudotimes and subtypes) into blood-, MRI- and psychological traits-based markers. The translation results underscore both the promise of these models and the opportunities for further enhancement. Our findings enhance the understanding of AD heterogeneity, underscore the value of multi-scale molecular approaches for elucidating causal mechanisms, and lay the groundwork for the development of novel therapies in living persons that target multi-level brain molecular subtypes of AD dementia.

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bioRxiv2023

Transcriptomic signatures of Abeta- and tau-induced neuronal dysfunction reveal inflammatory processes at the core of Alzheimer's disease pathophysiology

Molecular mechanisms enabling pathology-induced neuronal dysfunction in Alzheimers disease (AD) remain elusive. Here, we use mechanistic computational models to infer the combined influence of PET-measured A{beta} and tau burdens on fMRI-derived neuronal activity and to subsequently identify the transcriptomic spatial correlates of AD pathophysiology. Our results reveal overrepresented genes and biological processes that participate in synaptic degeneration and interact with A{beta} and tau deposits. Furthermore, we confirmed the central role of the immune system and neuroinflammatory pathways within AD pathogenesis; microglia were significantly enriched in the gene set associated with A{beta} and tau synergistic influences on neuronal activity. Lastly, our computational approach unveiled drug candidates with the potential to halt or reduce the observed pathological effects on neuronal activity, including existing medication for cancer, immune disorders, and cardiovascular diseases, many currently under clinical evaluation in AD. Overall, these findings support the notion that the AD brain experiences functional changes intricately associated with a diverse spectrum of molecular processes.

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bioRxiv2023

Revealing the combined roles of Abeta and tau in Alzheimer's disease via a pathophysiological activity decoder

Neuronal dysfunction and cognitive deterioration in Alzheimers disease (AD) are likely caused by multiple pathophysiological factors. However, evidence in humans remains scarce, necessitating improved non-invasive techniques and integrative mechanistic models. Here, we introduce personalized brain activity models incorporating functional MRI, amyloid-{beta} (A{beta}) and tau-PET from AD-related participants (N=132). Within the model assumptions, electrophysiological activity is mediated by toxic protein deposition. Our integrative subject-specific approach uncovers key patho-mechanistic interactions, including synergistic A{beta} and tau effects on cognitive impairment and neuronal excitability increases with disease progression. The data-derived neuronal excitability values strongly predict clinically relevant AD plasma biomarker concentrations (p-tau217, p-tau231, p-tau181, GFAP). Furthermore, our results reproduce hallmark AD electrophysiological alterations (theta band activity enhancement and alpha reductions) which occur with A{beta}-positivity and after limbic tau involvement. Microglial activation influences on neuronal activity are less definitive, potentially due to neuroimaging limitations in mapping neuroprotective vs detrimental phenotypes. Mechanistic brain activity models can further clarify intricate neurodegenerative processes and accelerate preventive/treatment interventions.

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bioRxiv2022

Normative values of neuromelanin-sensitive MRI signal in older adults obtained using a standard protocol for acquisition and analysis

BackgroundThe integrity and function of catecholamine neurotransmitter systems can be assessed using MRI sequences often referred to as neuromelanin-sensitive MRI (NM-MRI). The relevance of this method to neurodegenerative and psychiatric disorders is becoming increasingly evident, and it has potential as a clinical biomarker. To support such future applications, we report here the normative range of NM-MRI signal and volume metrics in cognitively normal older adults. Methods3 Tesla NM-MRI images and demographic and cognitive data were available from 152 cognitively normal older adults aged 53-86 years old at baseline; a subsample of 68 participants also had follow-up NM-MRI data collected around one-year later. NM-MRI images were processed to yield summary measures of volume and signal (contrast-to-noise ratio, CNR) for the substantia nigra (SN) and locus coeruleus (LC) using a recently developed software employing a fully automated algorithm. The extent of annual change in these metrics was quantified and tested for significance using 1-sample t-tests. ResultsBaseline SN signal (CNR) was 10.02% (left SN) and 10.28% (right) and baseline LC signal was 24.71% (left) and 20.42% (right). The only NM-MRI metric to show a significant annual change was a decrease in left SN volume. ConclusionWe report normative values for NM-MRI signal and volume in the SN and LC of cognitively normal older adults and normative values for their change over time. These values may help future efforts to use NM-MRI as a clinical biomarker for adults in this age range by facilitating identification of patients with extreme NM-MRI values.

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bioRxiv2022

Stage dependent differential influence of metabolic and structural networks on memory across Alzheimer's disease continuum

BackgroundLarge-scale neuronal network breakdown underlies memory impairment in Alzheimers disease (AD). However, the differential trajectories of the relationships between network organization and memory across pathology and cognitive stages in AD remain elusive. We determined whether and how the influences of individual-level structural and metabolic covariance network integrity on memory varied with amyloid pathology across clinical stages without assuming a constant relationship. Methods708 participants from the Alzheimers Disease Neuroimaging Initiative were studied. Individual-level structural and metabolic covariance scores in higher-level cognitive and hippocampal networks were derived from magnetic resonance imaging and [18F]fluorodeoxyglucose positron emission tomography using seed-based partial least square analyses. The non-linear associations between network scores and memory across cognitive stages in each pathology group were examined using sparse varying coefficient modelling. ResultsWe showed that the associations of memory with structural and metabolic networks in the hippocampal and default mode regions exhibited pathology-dependent differential trajectories across cognitive stages using sparse varying coefficient modelling. In amyloid pathology group, there was an early influence of hippocampal structural network deterioration on memory impairment in the preclinical stage, and a biphasic influence of the angular gyrus-seeded default mode network metabolism on memory in both preclinical and dementia stages. In non-amyloid pathology groups, in contrast, the trajectory of the hippocampus-memory association was opposite and weaker overall, while no metabolism covariance networks were related to memory. Key findings were replicated in a larger cohort of 1280 participants. ConclusionsOur findings highlight potential windows of early intervention targeting network breakdown at the preclinical AD stage.

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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.

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bioRxiv2021

Mapping neurotransmitter systems to the structural and functional organization of the human neocortex

Neurotransmitter receptors support the propagation of signals in the human brain. How receptor systems are situated within macroscale neuroanatomy and how they shape emergent function remains poorly understood, and there exists no comprehensive atlas of receptors. Here we collate positron emission tomography data from >1 200 healthy individuals to construct a whole-brain 3-D normative atlas of 19 receptors and transporters across 9 different neurotransmitter systems. We find that receptor profiles align with structural connectivity and mediate function, including neurophysiological oscillatory dynamics and resting state hemodynamic functional connectivity. Using the Neurosynth cognitive atlas, we uncover a topographic gradient of overlapping receptor distributions that separates extrinsic and intrinsic psychological processes. Finally, we find both expected and novel associations between receptor distributions and cortical thinning patterns across 13 disorders. We replicate all findings in an independently collected autoradiography dataset. This work demonstrates how chemoarchitecture shapes brain structure and function, providing a new direction for studying multi-scale brain organization.

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bioRxiv2021

The calcium sensor synaptotagmin-1 is critical for phasic axonal dopamine release in the striatum and mesencephalon, but is dispensable for basic motor behaviors in mice

In Parkinsons disease (PD), motor dysfunctions only become apparent after extensive loss of DA innervation. This resilience has been hypothesized to be due to the ability of many motor behaviors to be sustained through a diffuse basal tone of DA; but experimental evidence for this is limited. Here we show that conditional deletion of the calcium sensor synaptotagmin-1 (Syt1) in DA neurons (Syt1 cKODA mice) abrogates most activity-dependent axonal DA release in the striatum and mesencephalon, leaving somatodendritic (STD) DA release intact. Strikingly, Syt1 cKODA mice showed intact performance in multiple unconditioned DA-dependent motor tasks and even in a task evaluating conditioned motivation for food. Considering that basal extracellular DA levels in the striatum were unchanged, our findings suggest that activity-dependent DA release is dispensable for such tasks and that they can be sustained by a basal tone of extracellular DA. Taken together, our findings reveal the striking resilience of DA-dependent motor functions in the context of a near-abolition of phasic DA release, shedding new light on why extensive loss of DA innervation is required to reveal motor dysfunctions in PD.

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bioRxiv2021

Social isolation is linked to classical risk factors of Alzheimer's disease-related dementias

Alzheimers disease and related dementias is a major public health burden - compounding over upcoming years due to longevity. Recently, clinical evidence hinted at the experience of social isolation in expediting dementia onset. In 502,506 UK Biobank participants and 30,097 participants from the Canadian Longitudinal Study of Aging, we revisited traditional risk factors for developing dementia in the context of loneliness and lacking social support. Across these measures of subjective and objective social deprivation, we have identified strong links between individuals social capital and various indicators of Alzheimers disease and related dementias risk, which replicated across both population cohorts. The quality and quantity of daily social encounters had deep connections with key aetiopathological factors, which represent 1) personal habits and lifestyle factors, 2) physical health, 3) mental health, and 4) societal and external factors. Our population-scale assessment suggest that social lifestyle determinants are linked to most neurodegeneration risk factors, highlighting them promising targets for preventive clinical action.

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bioRxiv2021

Stable brain PET metabolic networks using a multiple sampling scheme

The human brains interregional communication is vital for its proper functioning. A promising direction for investigating how these regions communicate relies on the assumption that the brain is a complex network. In this context, images derived from positron emission tomography (PET) have been proposed as a potential source for understanding brain networks. However, such networks are often assembled via direct computation of inter-subject correlations, neglecting variabilities between subjects and jeopardizing the construction of group representative networks. Here, we used [18F]FDG-PET data from 1027 individuals at different syndromal stages (352 CU, 621 MCI and 234 AD) to develop a novel method for constructing stable (i.e. resilient to spurious data points) metabolic brain networks. Our multiple sampling (MS) scheme generates brain networks with higher stability when compared to the conventional approach. In addition, the proposed method is robust to imbalanced datasets and requires 50% fewer subjects to achieve stability than the conventional approach. Our method has the potential to considerably boost PET data reutilization and advance our understating of human brain network patterns in health and disease.

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bioRxiv2020

Creation of an Open Science Dataset from PREVENT-AD, a Longitudinal Cohort Study of Pre-symptomatic Alzheimer's Disease.

To move Alzheimer Disease (AD) research forward it is essential to collect data from large cohorts, but also make such data available to the global research community. We describe the creation of an open science dataset from the PREVENT-AD (PResymptomatic EValuation of Experimental or Novel Treatments for AD) cohort, composed of cognitively unimpaired older individuals with a parental or multiple-sibling history of AD. From 2011 to 2017, 386 participants were enrolled (mean age 63 years old {+/-} 5) for sustained investigation among whom 349 have retrospectively agreed to share their data openly. Repositories are findable through the unified interface of the Canadian Open Neuroscience Platform (https://portal.conp.ca/) and contain up to five years of longitudinal imaging data, cerebral fluid biochemistry, neurosensory capacities, cognitive, genetic, and medical information. Imaging data can be accessed openly at https://openpreventad.loris.ca while most of the other information, sensitive by nature, is accessible by qualified researchers at https://registeredpreventad.loris.ca. In addition to being a living resource for continued data acquisition, PREVENT-AD offers opportunities to facilitate understanding of AD pathogenesis.

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bioRxiv2019

Distinct changes in morphometric networks in aging versus Alzheimer’s disease dementia

Brain gray matter (GM) morphometric changes are prevalent in both aging and Alzheimers disease (AD), though disentangling these two processes has proved challenging. Using independent component analysis, we derived morphometric networks from a large, multi-cohort dataset, and investigated how GM volume within these networks differs in young adulthood, old adulthood, and AD. Aging and AD contributed additive effects on GM loss in nearly all networks, except frontal lobe networks, where GM reductions were more specific to aging. While no networks show GM loss highly specific to AD, a higher degree of variability in the whole-brain pattern of GM volume characterized AD only. Preservation of the whole-brain GM pattern in cognitively normal older adults was related to better cognition and lower risk of developing cognitive impairment. These results suggest both aging and AD involve widespread atrophy, but that cognitive impairment is uniquely associated with disruption of morphometric organization.

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bioRxiv2017

Subtypes of functional brain connectivity as early markers of neurodegeneration in Alzheimer’s disease

HighlightsO_LIReliable functional brain network subtypes accompany cognitive impairment in AD\nC_LIO_LISymptom-related subtypes exist in the default-mode, limbic and salience networks\nC_LIO_LIA limbic subtype is associated with a familial risk of AD in healthy older adults\nC_LIO_LILimbic subtypes also associate with beta amyloid deposition and ApoE4\nC_LI\n\nIn BriefWe found reliable subtypes of functional brain connectivity networks in older adults, associated with AD-related clinical symptoms in patients as well as several AD risk factors/biomarkers in asymptomatic individuals.\n\nSummaryThe heterogeneity of brain degeneration has not been investigated yet for functional brain network connectivity, a promising biomarker of Alzheimers disease. We coupled cluster analysis with resting-state functional magnetic resonance imaging to discover connectivity subtypes in healthy older adults and patients with cognitive disorders related to Alzheimers disease, noting associations between subtypes and cognitive symptoms in the default-mode, limbic and salience networks. In an independent asymptomatic cohort with a family history of Alzheimers dementia, the connectivity subtypes had good test-retest reliability across all tested networks. We found that a limbic subtype was overrepresented in these individuals, which was previously associated with symptoms. Other limbic subtypes showed associations with cerebrospinal fluid A{beta}1-42 levels and ApoE4 genotype. Our results demonstrate the existence of reliable subtypes of functional brain networks in older adults and support future investigations in limbic connectivity subtypes as early biomarkers of Alzheimers degeneration.

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