Evidence map›Paper›PMID 37860752›Full record

ReviewThe Japanese dental science review2023

Identification of disease-associate variants of aggressive periodontitis using genome-wide association studies.

Chiharu Fujihara, Osa Amila Hafiyyah, Shinya Murakami

Open access · goldAbstract readReview
In one paragraph

Review in The Japanese dental science review, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. 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

3 authors at 2 institutions in 2 countries.

Chiharu FujiharaDepartment of Periodontology and Regenerative Dentistry, Osaka University Graduate School of Dentistry, Osaka, Japan.
Osa Amila HafiyyahDepartment of Periodontology and Regenerative Dentistry, Osaka University Graduate School of Dentistry, Osaka, Japan.
Shinya MurakamiDepartment of Periodontology and Regenerative Dentistry, Osaka University Graduate School of Dentistry, Osaka, Japan.
Osaka University · JPUniversitas Gadjah Mada · ID

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aggressive periodontitis (AgP), Stage III or IV and Grade C according to the new periodontitis classification, is characterized by the rapid destruction of periodontal tissues in the systemically healthy population and often causes premature tooth loss. The presence of familial aggregation suggests the involvement of genetic factors in the pathogenesis. However, the genes associated with the onset and progression of the disease and details of its pathogenesis have not yet been fully identified. In recent years, the genome-wide approach (GWAS), a comprehensive genome analysis method using bioinformatics, has been used to search for disease-related genes, and the results have been applied in genomic medicine for various diseases, such as cancer. In this review, we discuss GWAS in the context of AgP. First, we introduce the relationship between single-nucleotide polymorphisms (SNPs) and susceptibility to diseases and how GWAS is useful for searching disease-related SNPs. Furthermore, we summarize the recent findings of disease-related genes using GWAS on AgP inside and outside Japan and a possible mechanism of the pathogenesis of AgP based on available literature and our research findings. These findings will lead to advancements in the prevention, prognosis, and treatment of AgP.

Indexed as

Aggressive periodontitis (AgP)Genome-wide association studies (GWAS)Single-nucleotide polymorphisms (SNPs)

Identifiers

PMID37860752
PMCPMC10582758
OpenAlexW4387631235

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.