Evidence map›Paper›PMID 39238070›Full record

ArticleJournal of cellular and molecular medicine2024

Genetic interactions and pleiotropy in metabolic diseases: Insights from a comprehensive GWAS analysis.

Jing Shen, Julong Pan, Gang Yu, Hui Cai, Hua Xu, Hanfei Yan, Yu Feng

Abstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 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

The trial behind it

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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
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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.

Jing ShenThe Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China.
Julong PanThe Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China.
Gang YuThe Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China.
Hui CaiThe Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China.
Hua XuThe Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China.
Hanfei YanThe Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China.
Yu FengThe Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China.ORCID 0009-0008-4746-1070

Funding

Science and Technology Program of Suzhou SKY2023101Wujiang District Science and Education Revitalization Health Project WWK202221
6 · The paper itself

Abstract

This study offers insights into the genetic and biological connections between nine common metabolic diseases using data from genome-wide association studies. Our goal is to unravel the genetic interactions and biological pathways of these complex diseases, enhancing our understanding of their genetic architecture. We employed a range of advanced analytical techniques to explore the genetic correlations and shared genetic variants of these diseases. These methods include Linked Disequilibrium Score Regression, High-Definition Likelihood (HDL), genetic analysis combining multiplicity and annotation (GPA), two-sample Mendelian randomization analyses, analysis under the multiplicity-complex null hypothesis (PLACO), and Functional mapping and annotation of genetic associations (FUMA). Additionally, Bayesian co-localization analyses were used to examine associations of specific loci across traits. Our study discovered significant genomic correlations and shared loci, indicating complex genetic interactions among these metabolic diseases. We found several shared single nucleotide variants and risk loci, notably highlighting the role of the immune system and endocrine pathways in these diseases. Particularly, rs2476601 and its associated gene PTPN22 appear to play a crucial role in the connection between type 2 diabetes mellitus, hypothyroidism/mucous oedema and hypoglycaemia. These findings enhance our understanding of the genetic underpinnings of these diseases and open new potential avenues for targeted therapeutic and preventive strategies. The results underscore the importance of considering pleiotropic effects in deciphering the genetic architecture of complex diseases, especially metabolic ones.

Indexed as

Genetic PleiotropyGenetic Predisposition to DiseaseGenome-Wide Association StudyLinkage DisequilibriumMetabolic DiseasesPolymorphism, Single NucleotideBayes TheoremDiabetes Mellitus, Type 2Epistasis, GeneticHumansMendelian Randomization Analysisgenome‐wide association studiesmetabolic diseasespleiotropyPTPN22single nucleotide variants

Identifiers

PMID39238070
PMCPMC11377178

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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.