Evidence map›Paper›PMID 36527260›Full record

SynthesisGlia2023

Integrating transcriptomic datasets across neurological disease identifies unique myeloid subpopulations driving disease-specific signatures.

Claire L Wishart, Alanna G Spiteri, Giuseppe Locatelli, Nicholas J C King

Open access · bronzeAbstract readMeta-Analysis
In one paragraph

Synthesis in Glia, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 24% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Regional Molecular Diversity in Chronic Spinal Cord Injury.Cellular and molecular neurobiology · 2026
    Article
  4. Metabolic Programming Drives Protective and Inflammatory Monocyte Fates in Viral Encephalitis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
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

4 authors at 2 institutions in 3 countries.

Claire L WishartInfection, Immunity, Inflammation Research Theme, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-4299-159X
Alanna G SpiteriInfection, Immunity, Inflammation Research Theme, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0001-6787-6195
Giuseppe LocatelliTheodor Kocher Institute, University of Bern, Bern, Switzerland.ORCID 0000-0002-2179-4407
Nicholas J C KingInfection, Immunity, Inflammation Research Theme, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-3877-9772
The University of Sydney · AUUniversity of Bern · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microglia and bone marrow-derived monocytes are key elements of central nervous system (CNS) inflammation, both capable of enhancing and dampening immune-mediated pathology. However, the study-specific focus on individual cell types, disease models or experimental approaches has limited our ability to infer common and disease-specific responses. This meta-analysis integrates bulk and single-cell transcriptomic datasets of microglia and monocytes from disease models of autoimmunity, neurodegeneration, sterile injury, and infection to build a comprehensive resource connecting myeloid responses across CNS disease. We demonstrate that the bulk microglial and monocyte program is highly contingent on the disease environment, challenging the notion of a universal microglial disease signature. Integration of six single-cell RNA-sequencing datasets revealed that these disease-specific signatures are likely driven by differing proportions of unique myeloid subpopulations that were individually expanded in different disease settings. These subsets were functionally-defined as neurodegeneration-associated, inflammatory, interferon-responsive, phagocytic, antigen-presenting, and lipopolysaccharide-responsive cellular states, revealing a core set of myeloid responses at the single-cell level that are conserved across CNS pathology. Showcasing the predictive and practical value of this resource, we performed differential expression analysis on microglia and monocytes across disease and identified Cd81 as a new neuroinflammatory-stable gene that accurately identified microglia and distinguished them from monocyte-derived cells across all experimental models at both the bulk and single-cell level. Together, this resource dissects the influence of disease environment on shared immune response programmes to build a unified perspective of myeloid behavior across CNS pathology.

Indexed as

Nervous System DiseasesTranscriptomeAnimalsCentral Nervous SystemMiceMice, Inbred C57BLMicrogliaMonocytescentral nervous system pathologyhigh parameter data integrationmicrogliamonocyte-derived cellssingle-cell RNA-sequencing

Identifiers

PMID36527260
PMCPMC10952672
OpenAlexW4311825762

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.