Search bioRxivSearch

bioRxiv · 10.1101/491902

Novel Alzheimer risk genes determine the microglia response to amyloid-β but not to TAU pathology

Abstract

BackgroundThousands of SNPs associated with risk of Alzheimers disease (AD) in genome-wide association studies (GWAS) do not reach genome-wide significance. When combined, they contribute however to a highly predictive polygenic risk score. The relevance of these subthreshold risk genes to disease, and how their combined predictive power translates into functionally relevant disease pathways, is unknown. We investigate here at the genome-wide level and in an unbiased way to what extent AD risk genes show altered gene expression in the context of increasing A{beta} or Tau pathology in mouse models of AD.\n\nMethodsWe used an existing GWAS data set to generate lists of candidate AD genes at different levels of significance. We performed transcriptomic analysis on wild-type and transgenic APP/PS1 (APPtg) and Thy-TAU22 (TAUtg) mouse models at early and late stage of disease. We used unbiased weighted gene co-expression network analysis (WGCNA) to identify clusters of co-regulated genes responsive to A{beta} or TAU pathology. Gene set enrichment was used to identify clusters that were enriched for AD risk genes.\n\nFindingsConsistent and significant enrichment of AD risk genes was found in only one out of 63 coexpression modules. This module is highly responsive to A{beta} but not to TAU pathology. We identify in this module 18 AD risk genes (p-value=6{middle dot}5e-11) including 11 new ones, GPC2, TREML2, SYK, GRN, SLC2A5, SAMSN1, PYDC1, HEXB, RRBP1, LYN and BLNK. All are expressed in microglia, have a binding site for the transcription factor SPI1 (PU.1), and become significantly upregulated when exposed to A{beta}. A subset regulates FC-gamma receptor mediated phagocytosis.\n\nInterpretationGenetic risk of AD is functionally translated into a microglia pathway responsive to A{beta} pathology. This insight integrates aspects of the amyloid hypothesis with genetic risk associated to sporadic AD.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sierksma, A., Lu, A., Salta, E., Mancuso, R., Zoco, J., Blum, D., Buee, L., De Strooper, B., Fiers, M.. 2018-12-11. Novel Alzheimer risk genes determine the microglia response to amyloid-β but not to TAU pathology. https://doi.org/10.1101/491902

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