bioRxiv Science⌕ Search

bioRxiv · 10.1101/2022.02.04.479130

Theta band-power shapes amyloid-driven longitudinal EEG changes in pre-clinical Alzheimer's Disease

Abstract

Alzheimers Disease (AD) includes progressive symptoms spread along a continuum of pre-clinical (pre-AD) and clinical stages. Pre-AD refers to cognitively healthy individuals with presence of positive pathophysiological biomarkers of AD (i.e., markers of amyloidopathy and tauopathy). Although numerous studies uncovered the neuro-cognitive changes of AD, very little is known on the natural history of brain lesions and modifications of brain networks of pre-AD. To address this issue, we analysed resting-state EEG data of 318 cognitively healthy individuals with subjective memory complains from the INSIGHT-preAD cohort at the time of their first visit (M0) and two-years later (M24). Using 18F-florbetapir PET-scanner, subjects were stratified between amyloid positive (A-; n=230) and amyloid negative (A+; n=88) groups. Differences between A+ and A- individuals were estimated at source level in each band of the EEG power spectrum. At M0, we found an increase of theta-band power in the mid-frontal cortex in A+ compared to A-. No significant association was found between mid-frontal theta power and the individuals cognitive performance. While the very same effect was not replicated at M24, theta-band power increased in A+ relative to A- individuals in the posterior cingulate cortex and the pre-cuneus. Furthermore, alpha band revealed a peculiar decremental trend in posterior brain regions in the A+ relative to the A- group only at M24. These results provide the first source-level longitudinal evidence on the impact of brain amyloidosis on the EEG dynamics of a large-scale, monocentric cohort of pre-AD. Theta-band power increase over the mid-frontal and mid-posterior cortices suggests an hypoactivation of the default-mode network in individuals at-risk of AD and a non-linear longitudinal progression of the AD-spectrum.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Spinelli, G., Bakardjian, H., Schwartz, D., Potier, M.-C., Habert, M.-O., Dubois, B., George, N.. 2022-02-07. Theta band-power shapes amyloid-driven longitudinal EEG changes in pre-clinical Alzheimer's Disease. https://doi.org/10.1101/2022.02.04.479130

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗