Evidence map›Paper›PMID 23705665›Full record

ArticleGenome medicine2013

Genes and pathways underlying regional and cell type changes in Alzheimer's disease.

Jeremy A Miller, Randall L Woltjer, Jeff M Goodenbour, Steve Horvath, Daniel H Geschwind

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 173 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
173citing papers in PubMed, 8 pooled it
8.3field-weighted citation impact, top 2% 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

173 citing papers in PubMed, 8 syntheses or guidelines pooled it, 285 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. A Meta-Analysis of Alzheimer's Disease Brain Transcriptomic Data.Journal of Alzheimer's disease : JAD · 2019
    Pooled it
  6. Pooled it
  7. Pooled it
  8. Pooled it
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Decoding Alzheimer's Disease One Cell Class at a Time.Cellular and molecular neurobiology · 2026
    Review
  17. Article
  18. Article
  19. Article
  20. Article

113 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

5 authors at 2 institutions in 1 country.

Jeremy A MillerInterdepartmental Program for Neuroscience and Human Genetics Department, UCLA, 2309 Gonda Bldg, 695 Charles E Young Dr. South, Los Angeles, CA 90095-1761, USA.
Randall L WoltjerDepartment of Pathology, Oregon Health & Science University, Department of Pathology L113, Portland, OR 97239, USA.
Jeff M GoodenbourHuman Genetics Department, UCLA, 2309 Gonda Bldg, 695 Charles E Young Dr. South, Los Angeles, CA 90095-1761, USA.
Steve HorvathHuman Genetics Department and Biostatistics Department, UCLA, 4357A Gonda Bldg, 695 Charles E Young Dr. South, Los Angeles, CA 90095-1761, USA.
Daniel H GeschwindHuman Genetics Department and Neurology Department, UCLA, 2309 Gonda Bldg, 695 Charles E Young Dr. South, Los Angeles, CA 90095-1761, USA.
Charles R. Drew University of Medicine and Science · USOregon Health & Science University · US

Funding

Outreach, Recruitment and Education CoreP30AG008017 · NIA · OREGON HEALTH & SCIENCE UNIVERSITY · PI DODGE, HIROKO HAYAMA · 1990 to 2019
$27.7M
6 · The paper itself

Abstract

backgroundTranscriptional studies suggest Alzheimer's disease (AD) involves dysfunction of many cellular pathways, including synaptic transmission, cytoskeletal dynamics, energetics, and apoptosis. Despite known progression of AD pathologies, it is unclear how such striking regional vulnerability occurs, or which genes play causative roles in disease progression.

methodsTo address these issues, we performed a large-scale transcriptional analysis in the CA1 and relatively less vulnerable CA3 brain regions of individuals with advanced AD and nondemented controls. In our study, we assessed differential gene expression across region and disease status, compared our results to previous studies of similar design, and performed an unbiased co-expression analysis using weighted gene co-expression network analysis (WGCNA). Several disease genes were identified and validated using qRT-PCR.

resultsWe find disease signatures consistent with several previous microarray studies, then extend these results to show a relationship between disease status and brain region. Specifically, genes showing decreased expression with AD progression tend to show enrichment in CA3 (and vice versa), suggesting transcription levels may reflect a region's vulnerability to disease. Additionally, we find several candidate vulnerability (ABCA1, MT1H, PDK4, RHOBTB3) and protection (FAM13A1, LINGO2, UNC13C) genes based on expression patterns. Finally, we use a systems-biology approach based on WGCNA to uncover disease-relevant expression patterns for major cell types, including pathways consistent with a key role for early microglial activation in AD.

conclusionsThese results paint a picture of AD as a multifaceted disease involving slight transcriptional changes in many genes between regions, coupled with a systemic immune response, gliosis, and neurodegeneration. Despite this complexity, we find that a consistent picture of gene expression in AD is emerging.

Identifiers

PMID23705665
PMCPMC3706780
OpenAlexW2158198121

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.