Evidence map›Paper›PMID 28260899›Full record

ArticleNeuropsychiatric disease and treatment2017

Gene expression-based biological test for major depressive disorder: an advanced study.

Shin-Ya Watanabe, Shusuke Numata, Jun-Ichi Iga, Makoto Kinoshita, Hidehiro Umehara, Kazuo Ishii, Tetsuro Ohmori

Abstract read
In one paragraph

Article in Neuropsychiatric disease and treatment, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Association Study ofJournal of personalized medicine · 2023
    Article
  3. A Single-Nucleotide Polymorphism in the Promoter of PorcineFrontiers in cell and developmental biology · 2022
    Article
  4. Association between theNeuropsychiatric disease and treatment · 2019
    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

7 authors.

Shin-Ya WatanabeDepartment of Psychiatry, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima.
Shusuke NumataDepartment of Psychiatry, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima.
Jun-Ichi IgaDepartment of Neuropsychiatry, Molecules and Function, Ehime University Graduate School of Medicine, Ehime.
Makoto KinoshitaDepartment of Psychiatry, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima.
Hidehiro UmeharaDepartment of Psychiatry, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima.
Kazuo IshiiDepartment of Applied Biological Science, Faculty of Agriculture, Tokyo University of Agriculture and Technology, Tokyo, Japan.
Tetsuro OhmoriDepartment of Psychiatry, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeRecently, we could distinguished patients with major depressive disorder (MDD) from nonpsychiatric controls with high accuracy using a panel of five gene expression markers ( PATIENTS AND

methodsWe measured messenger ribonucleic acid expression levels of the aforementioned five genes in peripheral leukocytes in 17 patients with schizophrenia and 36 patients with bipolar disorder using quantitative real-time polymerase chain reaction (PCR), and we combined these expression data with our previous expression data of 25 patients with MDD and 25 controls. Subsequently, a linear discriminant function was developed for use in discriminating between patients with MDD and without MDD.

resultsThis expression panel was able to segregate patients with MDD from those without MDD with a sensitivity and specificity of 64% and 67.9%, respectively.

conclusionFurther research to identify MDD-specific markers is needed to improve the performance of this biological test.

Indexed as

biomarkerbipolar disorderdepressive disordergene expressionschizophrenia

Identifiers

PMID28260899
PMCPMC5328599

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