Evidence map›Paper›PMID 35980567›Full record

ArticleMolecular neurobiology2024

Single-Cell Transcriptional Profiling and Gene Regulatory Network Modeling in Tg2576 Mice Reveal Gender-Dependent Molecular Features Preceding Alzheimer-Like Pathologies.

Muhammad Ali, Oihane Uriarte Huarte, Tony Heurtaux, Pierre Garcia, Beatriz Pardo Rodriguez, Kamil Grzyb, Rashi Halder, Alexander Skupin, Manuel Buttini, Enrico Glaab

Open access · hybridAbstract read
In one paragraph

Article in Molecular neurobiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 16 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 4 countries.

Muhammad AliLuxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7 avenue des Hauts Fourneaux, L-4362, Esch-sur-Alzette, Luxembourg.
Oihane Uriarte HuarteLuxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7 avenue des Hauts Fourneaux, L-4362, Esch-sur-Alzette, Luxembourg.
Tony HeurtauxLuxembourg Center of Neuropathology (LCNP), L-3555, Dudelange, Luxembourg.
Pierre GarciaLuxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7 avenue des Hauts Fourneaux, L-4362, Esch-sur-Alzette, Luxembourg.
Beatriz Pardo RodriguezLuxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7 avenue des Hauts Fourneaux, L-4362, Esch-sur-Alzette, Luxembourg.
Kamil GrzybLuxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7 avenue des Hauts Fourneaux, L-4362, Esch-sur-Alzette, Luxembourg.
Rashi HalderLuxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7 avenue des Hauts Fourneaux, L-4362, Esch-sur-Alzette, Luxembourg.
Alexander SkupinLuxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7 avenue des Hauts Fourneaux, L-4362, Esch-sur-Alzette, Luxembourg.
Manuel ButtiniLuxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7 avenue des Hauts Fourneaux, L-4362, Esch-sur-Alzette, Luxembourg.
Enrico GlaabLuxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7 avenue des Hauts Fourneaux, L-4362, Esch-sur-Alzette, Luxembourg. enrico.glaab@uni.lu.ORCID http://orcid.org/0000-0003-3977-7469
University of Luxembourg · LUUniversity of the Basque Country · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease (AD) onset and progression is influenced by a complex interplay of several environmental and genetic factors, one of them gender. Pronounced gender differences have been observed both in the relative risk of developing AD and in clinical disease manifestations. A molecular level understanding of these gender disparities is still missing, but could provide important clues on cellular mechanisms modulating the disease and reveal new targets for gender-oriented disease-modifying precision therapies. We therefore present here a comprehensive single-cell analysis of disease-associated molecular gender differences in transcriptomics data from the neocortex, one of the brain regions most susceptible to AD, in one of the most widely used AD mouse models, the Tg2576 model. Cortical areas are also most commonly used in studies of post-mortem AD brains. To identify disease-linked molecular processes that occur before the onset of detectable neuropathology, we focused our analyses on an age with no detectable plaques and microgliosis. Cell-type specific alterations were investigated at the level of individual genes, pathways, and gene regulatory networks. The number of differentially expressed genes (DEGs) was not large enough to build context-specific gene regulatory networks for each individual cell type, and thus, we focused on the study of cell types with dominant changes and included analyses of changes across the combination of cell types. We observed significant disease-associated gender differences in cellular processes related to synapse organization and reactive oxygen species metabolism, and identified a limited set of transcription factors, including Egr1 and Klf6, as key regulators of many of the disease-associated and gender-dependent gene expression changes in the model. Overall, our analyses revealed significant cell-type specific gene expression changes in individual genes, pathways and sub-networks, including gender-specific and gender-dimorphic changes in both upstream transcription factors and their downstream targets, in the Tg2576 AD model before the onset of overt disease. This opens a window into molecular events that could determine gender-susceptibility to AD, and uncovers tractable target candidates for potential gender-specific precision medicine for AD.

Indexed as

Alzheimer DiseaseAnimalsBrainGene Expression ProfilingGene Regulatory NetworksMiceTranscription FactorsTranscription FactorsAlzheimer’s diseaseBioinformaticsGender differencesMeta-analysisNetwork analysisPathway analysisSex differencesSingle-cell transcriptomicsTg2576

Identifiers

PMID35980567
PMCPMC10861719
OpenAlexW4293066958

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.