Evidence map›Paper›PMID 36161993›Full record

SynthesisDiabetes care2022

SGLT2 Inhibition, Choline Metabolites, and Cardiometabolic Diseases: A Mediation Mendelian Randomization Study.

Min Xu, Jie Zheng, Tianzhichao Hou, Hong Lin, Tiange Wang, Shuangyuan Wang, Jieli Lu, Zhiyun Zhao, Mian Li, Yu Xu and 3 more

Open access · bronzeAbstract readMeta-Analysis
In one paragraph

Synthesis in Diabetes care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 1 pooled it
12.6field-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

52 citing papers in PubMed, 1 synthesis or guideline pooled it, 86 citations in OpenAlex.

  1. Pooled it
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  14. Gut Microbiota-Derived Metabolites Orchestrate Metabolic Reprogramming in Diabetic Cardiomyopathy: Mechanisms and Therapeutic Frontiers.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025
    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

13 authors at 1 institution in 2 countries.

Min XuDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID 0000-0003-3930-8718
Jie ZhengDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Tianzhichao HouDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Hong LinDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Tiange WangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shuangyuan WangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jieli LuDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zhiyun ZhaoDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Mian LiDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yu XuDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Guang NingDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID 0000-0002-5754-7635
Yufang BiDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID 0000-0002-4829-5915
Weiqing WangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID 0000-0001-6027-3084
Shanghai Jiao Tong University · CN

Funding

British Heart FoundationMedical Research Council MC_PC_17228Medical Research Council MC_QA137853
6 · The paper itself

Abstract

objectiveTo investigate the causal role of choline metabolites mediating sodium-glucose cotransporter 2 (SGLT2) inhibition in coronary artery disease (CAD) and type 2 diabetes (T2D) using Mendelian randomization (MR). RESEARCH DESIGN AND

methodsA two-sample two-step MR was used to determine 1) causal effects of SGLT2 inhibition on CAD and T2D; 2) causal effects of three choline metabolites, total choline, phosphatidylcholine, and glycine, on CAD and T2D; and 3) mediation effects of these metabolites. Genetic proxies for SGLT2 inhibition were identified as variants in the SLC5A2 gene that were associated with both levels of gene expression and hemoglobin A1c. Summary statistics for metabolites were from UK Biobank, CAD from CARDIoGRAMplusC4D (Coronary ARtery DIsease Genome wide Replication and Meta-analysis [CARDIoGRAM] plus The Coronary Artery Disease [C4D] Genetics) consortium, and T2D from DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) and the FinnGen study.

resultsSGLT2 inhibition (per 1 SD, 6.75 mmol/mol [1.09%] lowering of HbA1c) was associated with lower risk of T2D and CAD (odds ratio [OR] 0.25 [95% CI 0.12, 0.54], and 0.51 [0.28, 0.94], respectively) and positively with total choline (β 0.39 [95% CI 0.06, 0.72]), phosphatidylcholine (0.40 [0.13, 0.67]), and glycine (0.34 [0.05, 0.63]). Total choline (OR 0.78 [95% CI 0.68, 0.89]) and phosphatidylcholine (OR 0.81 [0.72, 0.91]) were associated with T2D but not with CAD, while glycine was associated with CAD (0.94 [0.91, 0.98]) but not with T2D. Mediation analysis showed evidence of indirect effect of SGLT2 inhibition on T2D through total choline (0.91 [0.83, 0.99]) and phosphatidylcholine (0.93 [0.87, 0.99]) with a mediated proportion of 8% and 5% of the total effect, respectively, and on CAD through glycine (0.98 [0.96, 1.00]) with a mediated proportion of 2%. The results were well validated in at least one independent data set.

conclusionsOur study identified the causal roles of SGLT2 inhibition in choline metabolites. SGLT2 inhibition may influence T2D and CAD through different choline metabolites.

Indexed as

Coronary Artery DiseaseDiabetes Mellitus, Type 2Sodium-Glucose Transporter 2 InhibitorsCholineGenome-Wide Association StudyGlycineHumansMendelian Randomization AnalysisPhosphatidylcholinesPolymorphism, Single NucleotideRisk FactorsCholineGlycinePhosphatidylcholinesSodium-Glucose Transporter 2 Inhibitors

Identifiers

PMID36161993
PMCPMC9862376
OpenAlexW4297094094

What OpenQuestion holds

Textmetadata
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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 OpenQuestion graph.