Evidence map›Paper›PMID 37095539›Full record

ArticleDiabetology & metabolic syndrome2023

Leveraging IgG N-glycosylation to infer the causality between T2D and hypertension.

Haotian Wang, Yuan Li, Weijie Cao, Jie Zhang, Mingyang Cao, Xiaoni Meng, Di Liu, Youxin Wang

Open access · goldAbstract read
In one paragraph

Article in Diabetology & metabolic syndrome, 2023. 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
0.8field-weighted citation impact, top 28% 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

4 citing papers in PubMed, 5 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

8 authors at 4 institutions in 2 countries.

Haotian Wang *Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Xitoutiao, Beijing, 100069, China.
Yuan Li *Lianyungang Maternal and Child Health Hospital, Lianyungang, 222062, Jiangsu, China.
Weijie CaoCentre for Precision Medicine, Edith Cowan University, Perth, 60127, Australia.
Jie ZhangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Xitoutiao, Beijing, 100069, China.
Mingyang CaoBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Xitoutiao, Beijing, 100069, China.
Xiaoni MengBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Xitoutiao, Beijing, 100069, China.
Di LiuCentre for Biomedical Information Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, University Town, Nanshan District, Shenzhen, 518055, Guangdong, China. di.liu@siat.ac.cn.
Youxin WangBeijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, 10 Xitoutiao, Beijing, 100069, China. wangy@ccmu.edu.cn.ORCID http://orcid.org/0000-0002-6574-6706
Capital Medical University · CNEdith Cowan University · AULianyungang Maternal and Children’s Hospital · CNShenzhen Institutes of Advanced Technology · CN

Funding

National Natural Science Foundation of China 81872682
6 · The paper itself

Abstract

backgroundObservational studies demonstrated a bidirectional association between type 2 diabetes (T2D) and hypertension, whereas Mendelian randomization (MR) analyses supported the causality from T2D to hypertension but not causal from hypertension to T2D. We previously found that IgG N-glycosylation is associated with both T2D and hypertension, and thus IgG N-glycosylation might link the causality between them.

methodsWe carried out a genome-wide association study (GWAS) to identify IgG N-glycosylation-quantitative-trait loci (QTLs) integrating GWAS for T2D and hypertension and then performed bidirectional univariable and multivariable MR analyses to infer the causal association among them. The inverse-variance-weighted (IVW) analysis was performed as the primary analysis, followed by some sensitivity analyses to explore the stability of the results.

resultsSix putatively causal IgG N-glycans for T2D and four for hypertension were identified in the IVW method. Genetically predicted T2D increased the risk of hypertension (odds ratio [OR] = 1.177, 95% confidence interval (95% CI) = 1.037-1.338, P = 0.012) and vice versa (OR = 1.391, 95% CI = 1.081-1.790, P = 0.010). Multivariable MR showed that T2D remained at risk effect with hypertension ([OR] = 1.229, 95% CI = 1.140-1.325, P = 7.817 × 10

conclusionOur study validated the mutual causality between T2D and hypertension from the perspective of IgG N-glycosylation, further validating the "common soil" hypothesis underlying the pathogenesis of T2D and hypertension.

Indexed as

Bidirectional Mendelian randomizationGlycosylationHypertensionIgG N-glycosylation quantitative trait lociType 2 diabetes

Identifiers

PMID37095539
PMCPMC10127371
OpenAlexW4366989758

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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.