Evidence map›Paper›PMID 34527023›Full record

ArticleFrontiers in genetics2021

No Casual Relationship Between T2DM and the Risk of Infectious Diseases: A Two-Sample Mendelian Randomization Study.

Huachen Wang, Zheng Guo, Yulu Zheng, Chunyan Yu, Haifeng Hou, Bing Chen

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 17% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

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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

6 authors at 4 institutions in 2 countries.

Huachen WangIntensive Care Unit, The Second Hospital of Tianjin Medical University, Tianjin, China.
Zheng GuoCentre for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.
Yulu ZhengCentre for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.
Chunyan YuMedical Imaging Department, Longgang District Central Hospital of Shenzhen, Shenzhen, China.
Haifeng HouShandong First Medical University & Shandong Academy of Medical Sciences, Taian, China.
Bing ChenIntensive Care Unit, The Second Hospital of Tianjin Medical University, Tianjin, China.
Edith Cowan University · AUTianjin Medical University · CNLonggang Central Hospital · CNShandong First Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn epidemiological studies, it has been proven that the occurrence of type 2 diabetes mellitus (T2DM) is related to an increased risk of infectious diseases. However, it is still unclear whether the relationship is casual.

methodsWe employed a two-sample Mendelian randomization (MR) to clarify the causal effect of T2DM on high-frequency infectious diseases: sepsis, skin and soft tissue infections (SSTIs), urinary tract infections (UTIs), pneumonia, and genito-urinary infection (GUI) in pregnancy. And then, we analyzed the genome-wide association study (GWAS) meta-analysis of European-descent individuals and conducted T2DM-related single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) that were associated with genome-wide significance (

resultsThe UK Biobank (UKB) cohort (

conclusionT2DM would not be causally associated with high-frequency infectious diseases (including sepsis, SSTI, UTI, pneumonia, and GUI in pregnancy).

Indexed as

infectionsinstrumental variableMendelian randomization studysepsissingle-nucleotide polymorphismsT2DM

Identifiers

PMID34527023
PMCPMC8435717
OpenAlexW3198130249

What OpenQuestion holds

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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.