Evidence map›Paper›PMID 26733279›Full record

ReviewCurrent neuropharmacology2016

Systems Genomics Support for Immune and Inflammation Hypothesis of Depression.

Abhay Sharma

Abstract readReview
In one paragraph

Review in Current neuropharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

13 citing papers in PubMed.

  1. Trial
  2. Review
  3. Review
  4. Integrated Single-Cell RNA-seq and ATAC-seq Reveals Heterogeneous Differentiation of CD4Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Erythropoietin Pathway: A Potential Target for the Treatment of Depression.International journal of molecular sciences · 2016
    Review
  13. 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

1 author.

Abhay SharmaCSIR-Institute of Genomics and Integrative Biology, Council of Scientific and Industrial Research, Sukhdev Vihar, Mathura Road, New Delhi 110025, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundImmune system plays an important role in brain development and function. With the discovery of increased circulating inflammatory cytokine levels in depression over two decades ago, evidence implicating immune system alterations in the disease has increasingly accumulated.

objectiveTo assess the underlying etiology and pathophysiology, a brief overview of the hypothesis free genomic, transcriptomic and proteomic studies in depression is presented here in order to specifically examine if the immune and inflammation hypothesis of depression is supported.

resultsIt is observed that genes identified in genome-wide association studies, and genes showing differential expression in transcriptomic studies in human depression do separately overrepresent processes related to both development as well as functioning of the immune system, and inflammatory response. These processes are also enriched in differentially expressed genes reported in animal models of antidepressant treatment. It is further noted that some of the genes identified in genome sequencing and proteomic analyses in human depression, and transcriptomic studies in chronic social defeat stress, an established animal model of depression, relate to immune and inflammatory pathways.

conclusionIn conclusion, integrative genomics evidence supports the immune and inflammation hypothesis of depression.

Indexed as

AnimalsDepressive DisorderGenomeGenomicsHumansInflammationProteomicsTranscriptome

Identifiers

PMID26733279
PMCPMC5050401

What OpenQuestion holds

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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.