Evidence map›Paper›PMID 38460073›Full record

ArticleEndocrine2024

Shared genetic architecture between periodontal disease and type 2 diabetes: a large scale genome-wide cross-trait analysis.

Kevin Chun Hei Wu, Lin Liu, Aimin Xu, Yap Hang Chan, Bernard Man Yung Cheung

Abstract read
In one paragraph

Article in Endocrine, 2024. 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

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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. Review
  2. Article
  3. Review
  4. Genetic Predisposition to Prediabetes in the Kazakh Population.Current issues in molecular biology · 2024
    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

5 authors.

Kevin Chun Hei WuDepartment of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
Lin LiuDepartment of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
Aimin XuDepartment of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
Yap Hang ChanDivision of Cardiology, Queen Mary Hospital, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
Bernard Man Yung CheungDepartment of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China. mycheung@hku.hk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo investigate the relationship between abnormal glucose metabolism, type 2 diabetes (T2D), and periodontal disease (PER) independent of Body Mass Index (BMI), we employed a genome-wide cross-trait approach to clarify the association.

methodsOur study utilized the most extensive genome-wide association studies conducted for populations of European ancestry, including PER, T2D, fasting glucose, fasting insulin, 2-hour glucose after an oral glucose challenge, HOMA-β, HOMA-IR (unadjusted or adjusted for BMI) and HbA1c.

resultsWith this approach, we were able to identify pleiotropic loci, establish expression-trait associations, and quantify global and local genetic correlations. There was a significant positive global genetic correlation between T2D (r

conclusionOur research has revealed a genetic link between T2D, glycemic traits, and PER that is influenced by biological pleiotropy. Notably, some of these links are not related to BMI. Our research highlights an underlying link between patients with T2D and PER, regardless of their BMI.

Indexed as

Diabetes Mellitus, Type 2Genome-Wide Association StudyPeriodontal DiseasesBlood GlucoseBody Mass IndexFemaleGenetic Predisposition to DiseaseGlycated HemoglobinHumansInsulin ResistanceMaleMiddle AgedPolymorphism, Single NucleotideBlood GlucoseGlycated HemoglobinGenome Wide Association AnalysisGlycemic ControlInsulin ResistancePeriodontal DiseasesType 2 Diabetes

Identifiers

PMID38460073
PMCPMC11291565

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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.