Evidence map›Paper›PMID 30165727›Full record

SynthesisMolecular genetics & genomic medicine2018

Association between COMT gene rs165599 SNP and schizophrenia: A meta-analysis of case-control studies.

Harika Gozde Gozukara Bag

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Molecular genetics & genomic medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact, top 90% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. 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 at 1 institution in 1 country.

Harika Gozde Gozukara BagFaculty of Medicine, Department of Biostatistics & Medical Informatics, Inonu University, Malatya, Turkey.ORCID 0000-0003-1208-4072
Inonu University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere are many studies with different results that examine the association between Catechol-O-MethylTransferase (COMT) gene single-nucleotide polymorphisms (SNPs) and schizophrenia. In this study, the aim was to conduct a meta-analysis to achieve a pooled effect size of the association between COMT gene rs165599 SNP and schizophrenia.

methodsOdds ratio (OR) was used as an effect size to determine the association between schizophrenia and the SNP. The pooled ORs were achieved under four different genetic models. When the heterogeneity among studies was high the DerSimonian-Laird random-effects model, otherwise the Mantel-Haenszel fixed-effects model was used. Publication bias was evaluated by Egger's test.

resultsUnder different genetic models no statistically significant association was found between rs165599 SNP and schizophrenia by meta-analyses consist of 20 independent studies. There was high heterogeneity among studies, for the possible reason the population differences, although the subgroup analyzes reduced the heterogeneity, no association was obtained. However, the sex-specific estimation of the females showed that to be a G allele carrier is a risk factor for schizophrenia (OR = 1.366 [95% confidence interval = 1.094-1.706]) compared to AA homozygous.

conclusionThe COMT gene rs165599 SNP does not appear to be a single-risk factor for schizophrenia.

Indexed as

Polymorphism, Single NucleotideCase-Control StudiesCatechol O-MethyltransferaseFemaleHumansMaleRisk FactorsSchizophreniaCatechol O-MethyltransferaseCOMT protein, humanCOMTmeta-analysisodds ratioschizophreniaSNP

Identifiers

PMID30165727
PMCPMC6160701
OpenAlexW2889189775

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.