Evidence map›Paper›PMID 25187168›Full record

SynthesisActa neuropathologica communications2014

Integrated multi-cohort transcriptional meta-analysis of neurodegenerative diseases.

Matthew D Li, Terry C Burns, Alexander A Morgan, Purvesh Khatri

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in Acta neuropathologica communications, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers, 10 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
68citing papers in PubMed, 10 pooled it
5.0field-weighted citation impact, top 5% 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

68 citing papers in PubMed, 10 syntheses or guidelines pooled it, 95 citations in OpenAlex.

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  18. In vivo validation of late-onset Alzheimer's disease genetic risk factors.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
    Article
  19. Review
  20. bioRxiv : the preprint server for biology · 2023
    Article

8 more citing papers are in PubMed but not listed here.

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 1 institution in 1 country.

Matthew D Li
Terry C Burns
Alexander A Morgan
Purvesh Khatri
Stanford University · US

Funding

Using a tonsil organoid system to probe conditions for the induction of protective antibody and T cell responses to influenza.U19AI057229 · NIAID · STANFORD UNIVERSITY · PI Mark Morris Davis · 2003 to 2026
$88.5M
Translational Incubator CoreU19AI109662 · NIAID · STANFORD UNIVERSITY · PI GLENN, JEFFREY S · 2014 to 2019
$28.6M
NIAID NIH HHS 1U19AI109662NIAID NIH HHS U19 AI057229NIAID NIH HHS U19 AI109662
6 · The paper itself

Abstract

introductionNeurodegenerative diseases share common pathologic features including neuroinflammation, mitochondrial dysfunction and protein aggregation, suggesting common underlying mechanisms of neurodegeneration. We undertook a meta-analysis of public gene expression data for neurodegenerative diseases to identify a common transcriptional signature of neurodegeneration.

resultsUsing 1,270 post-mortem central nervous system tissue samples from 13 patient cohorts covering four neurodegenerative diseases, we identified 243 differentially expressed genes, which were similarly dysregulated in 15 additional patient cohorts of 205 samples including seven neurodegenerative diseases. This gene signature correlated with histologic disease severity. Metallothioneins featured prominently among differentially expressed genes, and functional pathway analysis identified specific convergent themes of dysregulation. MetaCore network analyses revealed various novel candidate hub genes (e.g. STAU2). Genes associated with M1-polarized macrophages and reactive astrocytes were strongly enriched in the meta-analysis data. Evaluation of genes enriched in neurons revealed 70 down-regulated genes, over half not previously associated with neurodegeneration. Comparison with aging brain data (3 patient cohorts, 221 samples) revealed 53 of these to be unique to neurodegenerative disease, many of which are strong candidates to be important in neuropathogenesis (e.g. NDN, NAP1L2). ENCODE ChIP-seq analysis predicted common upstream transcriptional regulators not associated with normal aging (REST, RBBP5, SIN3A, SP2, YY1, ZNF143, IKZF1). Finally, we removed genes common to neurodegeneration from disease-specific gene signatures, revealing uniquely robust immune response and JAK-STAT signaling in amyotrophic lateral sclerosis.

conclusionsOur results implicate pervasive bioenergetic deficits, M1-type microglial activation and gliosis as unifying themes of neurodegeneration, and identify numerous novel genes associated with neurodegenerative processes.

Indexed as

Gene Expression RegulationCentral Nervous SystemCohort StudiesFemaleGene Expression ProfilingHumansMaleNeurodegenerative DiseasesOligonucleotide Array Sequence AnalysisTranscription FactorsTranscription Factors

Identifiers

PMID25187168
PMCPMC4167139
OpenAlexW2128873861

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.