Evidence map›Paper›PMID 37659996›Full record

ArticleCardiovascular diabetology2023

Causal associations between type 1 diabetes mellitus and cardiovascular diseases: a Mendelian randomization study.

Zirui Liu, Haocheng Wang, Zhengkai Yang, Yu Lu, Cao Zou

Open access · goldAbstract read
In one paragraph

Article in Cardiovascular diabetology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
22.5field-weighted citation impact, top 1% 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

43 citing papers in PubMed, 60 citations in OpenAlex.

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  16. Causal associations between 17 common autoimmune diseases and aortic diseases: a Mendelian randomization study.International journal of cardiology. Cardiovascular risk and prevention · 2025
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  19. Diabetes and atrial fibrillation: Causality is still a black-box.International journal of cardiology. Heart & vasculature · 2025
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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

5 authors at 2 institutions in 1 country.

Zirui LiuDepartment of Cardiology, First Affiliated Hospital of Soochow University, No.188 Shizi Street, Gusu District, Suzhou City, Jiangsu Province, China.
Haocheng WangDepartment of Cardiology, First Affiliated Hospital of Soochow University, No.188 Shizi Street, Gusu District, Suzhou City, Jiangsu Province, China.
Zhengkai YangDepartment of Cardiology, First Affiliated Hospital of Soochow University, No.188 Shizi Street, Gusu District, Suzhou City, Jiangsu Province, China.
Yu LuDepartment of Cardiology, First Affiliated Hospital of Soochow University, No.188 Shizi Street, Gusu District, Suzhou City, Jiangsu Province, China.
Cao ZouDepartment of Cardiology, First Affiliated Hospital of Soochow University, No.188 Shizi Street, Gusu District, Suzhou City, Jiangsu Province, China. nkzc75@suda.edu.cn.
Soochow University · CNFirst Affiliated Hospital of Soochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe presence of type 1 diabetes mellitus (T1DM) has been demonstrated to pose an increased risk for developing cardiovascular diseases (CVDs). However, the causal relationships between T1DM and CVDs remain unclear due to the uncontrolled confounding factors and reverse causation bias of the observational studies.

methodsSummary statistics of T1DM and seven CVDs from the largest available genome-wide association studies (GWAS) of European ancestry and FinnGen biobank were extracted for the primary MR analysis, and the analysis was replicated using UK biobank (UKBB) for validation. Three complementary methods: inverse variance weighted (IVW), weighted median, and MR-Egger were used for the MR estimates. The potential pleiotropic effects were assessed by MR-Egger intercept and MR-PRESSO global test. Additionally, multivariable MR (MVMR) analysis was performed to examine whether T1DM has independent effects on CVDs with adjustment of potential confounding factors. Moreover, a two-step MR approach was used to assess the potential mediating effects of these factors on the causal effects between T1DM and CVDs.

resultsCausal effects of T1DM on peripheral atherosclerosis (odds ratio [OR] = 1.06, 95% confidence interval [CI]: 1.02-1.10; p = 0.002)] and coronary atherosclerosis (OR = 1.03, 95% CI: 1.01-1.05; p = 0.001) were found. The results were less likely to be biased by the horizontal pleiotropic effects (both p values of MR-Egger intercept and MR-PRESSO Global test > 0.05). In the following MVMR analysis, we found the causal effects of T1DM on peripheral atherosclerosis and coronary atherosclerosis remain significant after adjusting for a series of potential confounding factors. Moreover, we found that hypertension partly mediated the causal effects of T1DM on peripheral atherosclerosis (proportion of mediation effect in total effect: 11.47%, 95% CI: 3.23-19.71%) and coronary atherosclerosis (16.84%, 95% CI: 5.35-28.33%). We didn't find significant causal relationships between T1DM and other CVDs, including heart failure (HF), coronary artery disease (CAD), atrial fibrillation (AF), myocardial infarction (MI) and stroke. For the reverse MR from CVD to T1DM, no significant causal relationships were identified.

conclusionThis MR study provided evidence supporting the causal effect of T1DM on peripheral atherosclerosis and coronary atherosclerosis, with hypertension partly mediating this effect.

Indexed as

AtherosclerosisCardiovascular DiseasesCoronary Artery DiseaseDiabetes Mellitus, Type 1HypertensionGenome-Wide Association StudyHumansMendelian Randomization AnalysisNonoxynolNonoxynolCardiovascular diseaseMendelian randomizationType 1 diabetes mellitus

Identifiers

PMID37659996
PMCPMC10475187
OpenAlexW4386387933

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.