SGLT2 inhibition, circulating metabolites, and atrial fibrillation: a Mendelian randomization study

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Abstract

Background

Sodium-glucose cotransporter 2 (SGLT2) inhibitors have shown promise in reducing the risk of atrial fibrillation (AF). However, the results are controversial and the underlying metabolic mechanism remains unclear. Emerging evidence implied that SGLT2 inhibitors have extra beneficial metabolic effects on circulating metabolites beyond glucose control, which might play a role in reducing the risk of AF. Hence, our study aimed to investigate the effect of circulating metabolites mediating SGLT2 inhibition in AF by Mendelian randomization (MR).

Methods

A two-sample and two-step MR study was conducted to evaluate the association of SGLT2 inhibition with AF and the mediation effects of circulating metabolites linking SGLT2 inhibition with AF. Genetic instruments for SGLT2 inhibition were identified as genetic variants, which were both associated with the expression of SLC5A2 gene and glycated hemoglobin level (HbA1c). Positive control analysis on type 2 diabetes mellitus (T2DM) was conducted to validate the selection of genetic instruments.

Results

Genetically predicted SGLT2 inhibition (per 1 SD decrement in HbA1c) was associated with reduced risk of T2DM (odds ratio [OR] = 0.63 [95% CI 0.45, 0.88], P = 0.006) and AF (0.51 [0.27, 0.97], P = 0.039). Among 168 circulating metabolites, two metabolites were both associated with SGLT2 inhibition and AF. The effect of SGLT2 inhibition on AF through the total concentration of lipoprotein particles (0.88 [0.81, 0.96], P = 0.004) and the concentration of HDL particles (0.89 [0.82, 0.97], P = 0.005), with a mediated proportion of 8.03% (95% CI [1.20%, 14.34%], P = 0.010) and 7.59% ([1.09%, 13.34%], P = 0.011) of the total effect, respectively.

Conclusions

This study supported the association of SGLT2 inhibition with a reduced risk of AF. The total concentration of lipoprotein particles and particularly the concentration of HDL particles might mediate this association. Further mechanistic and clinical studies research are needed to understand the mediation effects of circulating metabolites especially blood lipids in the association between SGLT2 inhibition and AF.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-023-02019-8.

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Most cited references 62

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Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression

Jack Bowden, George Davey Smith, Stephen Burgess (2016)

Background: The number of Mendelian randomization analyses including large numbers of genetic variants is rapidly increasing. This is due to the proliferation of genome-wide association studies, and the desire to obtain more precise estimates of causal effects. However, some genetic variants may not be valid instrumental variables, in particular due to them having more than one proximal phenotypic correlate (pleiotropy). Methods: We view Mendelian randomization with multiple instruments as a meta-analysis, and show that bias caused by pleiotropy can be regarded as analogous to small study bias. Causal estimates using each instrument can be displayed visually by a funnel plot to assess potential asymmetry. Egger regression, a tool to detect small study bias in meta-analysis, can be adapted to test for bias from pleiotropy, and the slope coefficient from Egger regression provides an estimate of the causal effect. Under the assumption that the association of each genetic variant with the exposure is independent of the pleiotropic effect of the variant (not via the exposure), Egger’s test gives a valid test of the null causal hypothesis and a consistent causal effect estimate even when all the genetic variants are invalid instrumental variables. Results: We illustrate the use of this approach by re-analysing two published Mendelian randomization studies of the causal effect of height on lung function, and the causal effect of blood pressure on coronary artery disease risk. The conservative nature of this approach is illustrated with these examples. Conclusions: An adaption of Egger regression (which we call MR-Egger) can detect some violations of the standard instrumental variable assumptions, and provide an effect estimate which is not subject to these violations. The approach provides a sensitivity analysis for the robustness of the findings from a Mendelian randomization investigation.

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Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator

Jack Bowden, George Davey Smith, Philip C. Haycock … (2017)

ABSTRACT Developments in genome‐wide association studies and the increasing availability of summary genetic association data have made application of Mendelian randomization relatively straightforward. However, obtaining reliable results from a Mendelian randomization investigation remains problematic, as the conventional inverse‐variance weighted method only gives consistent estimates if all of the genetic variants in the analysis are valid instrumental variables. We present a novel weighted median estimator for combining data on multiple genetic variants into a single causal estimate. This estimator is consistent even when up to 50% of the information comes from invalid instrumental variables. In a simulation analysis, it is shown to have better finite‐sample Type 1 error rates than the inverse‐variance weighted method, and is complementary to the recently proposed MR‐Egger (Mendelian randomization‐Egger) regression method. In analyses of the causal effects of low‐density lipoprotein cholesterol and high‐density lipoprotein cholesterol on coronary artery disease risk, the inverse‐variance weighted method suggests a causal effect of both lipid fractions, whereas the weighted median and MR‐Egger regression methods suggest a null effect of high‐density lipoprotein cholesterol that corresponds with the experimental evidence. Both median‐based and MR‐Egger regression methods should be considered as sensitivity analyses for Mendelian randomization investigations with multiple genetic variants.

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Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases

Marie Verbanck, Chia-Yen Chen, Benjamin M. Neale … (2018)

Horizontal pleiotropy occurs when the variant has an effect on disease outside of its effect on the exposure in Mendelian randomization (MR). Violation of the ‘no horizontal pleiotropy’ assumption can cause severe bias in MR. We developed the Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test to identify horizontal pleiotropic outliers in multi-instrument summary-level MR testing. We showed using simulations that MR-PRESSO is best suited when horizontal pleiotropy occurs in <50% of instruments. Next, we applied MR-PRESSO, along with several other MR tests to complex traits and diseases, and found that horizontal pleiotropy: (i) was detectable in over 48% of significant causal relationships in MR; (ii) introduced distortions in the causal estimates in MR that ranged on average from −131% to 201%; (iii) induced false positive causal relationships in up to 10% of relationships; and (iv) can be corrected in some but not all instances.

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Author and article information

Contributors

Yingli Lu: luyingli2008@126.com

Ningjian Wang: wnj486@126.com

Journal

Journal ID (nlm-ta): Cardiovasc Diabetol

Journal ID (iso-abbrev): Cardiovasc Diabetol

Title: Cardiovascular Diabetology

Publisher: BioMed Central (London )

ISSN (Electronic): 1475-2840

Publication date (Electronic): 17 October 2023

Publication date PMC-release: 17 October 2023

Publication date Collection: 2023

Volume: 22

Electronic Location Identifier: 278

Affiliations

[1 ]GRID grid.16821.3c, ISNI 0000 0004 0368 8293, Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People’s Hospital, , Shanghai Jiao Tong University School of Medicine, ; Shanghai, China

[2 ]School of Public Health, Zhejiang University, ( https://ror.org/00a2xv884) Hangzhou, China

[3 ]Department of Medical Sciences, Uppsala University, ( https://ror.org/048a87296) Uppsala, Sweden

Article

Publisher ID: 2019

DOI: 10.1186/s12933-023-02019-8

PMC ID: 10583416

PubMed ID: 37848934

SO-VID: aa166c71-6bf8-4c9b-b3ee-d6c0ab3e7990

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 30 August 2023

Date accepted : 9 October 2023

Funding

Funded by: Shanghai Municipal Health Commission

Award ID: 2022XD017

Funded by: Innovative Research Team of High-level Local Universities in Shanghai

Award ID: SHSMU-ZDCX20212501

Funded by: FundRef http://dx.doi.org/10.13039/501100009018, Shanghai Municipal Human Resources and Social Security Bureau;

Award ID: 2020074

Funded by: Clinical Research Plan of Shanghai Hospital Development Center

Award ID: SHDC2020CR4006

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ScienceOpen disciplines: Endocrinology & Diabetes

Keywords: atrial fibrillation,sodium-glucose cotransporter 2 inhibition,circulating metabolites,mendelian randomization

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ScienceOpen disciplines: Endocrinology & Diabetes

Keywords: atrial fibrillation, sodium-glucose cotransporter 2 inhibition, circulating metabolites, mendelian randomization

SGLT2 inhibition, circulating metabolites, and atrial fibrillation: a Mendelian randomization study

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Abstract

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Conclusions

Supplementary Information

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Journal of the ASEAN Federation of Endocrine Societies

Most cited references 62

Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression

Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator

Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases

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