bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2025.01.28.635128

Exploring sex-specific alterations in early Alzheimer's disease using network MRI analyses

Ben Abdallah, I.·Sourty, M.·Rame, M.·Degiorgis, L.·Isik, A.·Mathis, C.·Harsan, L.-A.
View original source ↗Export metadata ↓

Abstract

Alzheimers disease (AD) is characterized by the accumulation of amyloid-{beta} plaques and tau neurofibrillary tangles, leading to progressive cognitive decline. Subtle cognitive and neural adaptations mark the preclinical stage of AD, occurring years before mild cognitive impairment and AD diagnosis. Throughout the continuum of AD, women ([~]60% of AD cases) demonstrate faster rates of cognitive decline, greater hippocampal atrophy, and more extensive tau pathology compared to men. This is particularly evident in early AD phases. Therefore, investigating early sex-specific changes is crucial for identifying biomarkers and developing targeted interventions. In the present study, we conducted a longitudinal investigation on the AppNL-F/MAPT double knock-in (dKI) mouse model, to identify sex-specific resting-state functional connectivity (FC) patterns associated with early cognitive deficits. Male and female wild-type and dKI mice were tested for associative and long-term memory deficits, followed by resting-state functional magnetic resonance imaging to examine the default mode network (DMN) connectivity at 2 and 4 months of age. Female dKI mice exhibited earlier and more pronounced memory impairments, with deficits apparent at 2 months, while male deficits emerged at 4 months. FC analyses revealed distinct sex-specific alterations within DMN and between DMN hubs and memory processing nodes. Notably, female dKI mice showed hypersynchrony between the retrosplenial cortex (RSP) and key memory-related regions such as the entorhinal cortex (ENT) and hippocampus (HIP), but also towards subcortical regions overlapping thalamic nuclei, amygdala, and substantia nigra. Meanwhile, male dKI mice exhibited hypoconnectivity along RSP-HIP axis, RSP-reuniens nucleus, and RSP-sensorimotor cortex. Our data particularly highlight sexually dimorphic RSP-ENT and RSP-HIP connectivity. These results underscore the critical role of sex in shaping neural network reorganization and cognitive decline during preclinical AD. These findings position neural network connectivity as a sensitive biomarker of early memory dysfunction and highlight the need for sex-specific investigations and potentially tailored therapeutic strategies in AD.

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Ben Abdallah, I., Sourty, M., Rame, M., Degiorgis, L., Isik, A., Mathis, C., Harsan, L.-A.. 2025-01-28. Exploring sex-specific alterations in early Alzheimer's disease using network MRI analyses. https://doi.org/10.1101/2025.01.28.635128

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

KEEP EXPLORING

Related preprints

bioRxiv2026

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↗
bioRxiv2026

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↗
bioRxiv2026

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↗