Association between leptin and NAFLD: a two-sample Mendelian randomization study

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Abstract

Background

The etiology of nonalcoholic fatty liver disease (NAFLD) involves a complex interaction of genetic and environmental factors. Previous observational studies have revealed that higher leptin levels are related to a lower risk of developing NAFLD, but the causative association remains unknown. We intended to study the causal effect between leptin and NAFLD using the Mendelian randomization (MR) study.

Methods

We performed a two-sample Mendelian randomization (TSMR) analysis using summary GWAS data from leptin (up to 50,321 individuals) and NAFLD (8,434 cases and 770,180 controls) in a European population. Instrumental variables (IVs) that satisfied the three core assumptions of Mendelian randomization were selected. The TSMR analysis was conducted using the inverse variance weighted (IVW) method, MR-Egger regression method, and weighted median (WM) method. To ensure the accuracy and stability of the study results, heterogeneity tests, multiple validity tests, and sensitivity analyses were conducted.

Results

The findings of the TSMR correlation analysis between NAFLD and leptin were as follows: IVW method (odds ratio (OR) 0.6729; 95% confidence interval (95% CI) 0.4907–0.9235; P = 0.0142), WM method (OR 0.6549; 95% CI 0.4373–0.9806; P = 0.0399), and MR-Egger regression method ( P = 0.6920). Additionally, the findings of the TSMR correlation analysis between NAFLD and circulating leptin levels adjusted for body mass index (BMI) were as follows: IVW method (OR 0.5876; 95% CI 0.3781–0.9134; P = 0.0181), WM method (OR 0.6074; 95% CI 0.4231–0.8721; P = 0.0069), and MR-Egger regression method ( P = 0.8870). It has also been shown that higher levels of leptin are causally linked to a lower risk of developing NAFLD, suggesting that leptin may serve as a protective factor for NAFLD.

Conclusions

Using TSMR analysis and the GWAS database, we investigated the genetic relationship between elevated leptin levels and lowered risk of NAFLD in this study. However, further research is required to understand the underlying mechanisms.

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Most cited references 70

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

Jack Bowden, George Davey Smith, Stephen Burgess (2017)

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 … (2018)

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

Ziwei Guo: guoziweigzw0612@163.com

Hongbo Du: uhongbo@bucm.edu.cn

Yi Guo: guoyitxdy@sina.com

Qian Jin: jinqianqian0920@163.com

Ruijia Liu: ruijialiu520@163.com

Zhangjun Yun: yunzj1219@163.com

Jiaxin Zhang: happyjiaxin@bucm.edu.cn

Xiaoke Li: lixiaoke@vip.163.com

Yong’an Ye: yeyongan@vip.163.com

Journal

Journal ID (nlm-ta): Eur J Med Res

Journal ID (iso-abbrev): Eur J Med Res

Title: European Journal of Medical Research

Publisher: BioMed Central (London )

ISSN (Print): 0949-2321

ISSN (Electronic): 2047-783X

Publication date (Electronic): 3 July 2023

Publication date PMC-release: 3 July 2023

Publication date Collection: 2023

Volume: 28

Electronic Location Identifier: 215

Affiliations

[1 ]GRID grid.24695.3c, ISNI 0000 0001 1431 9176, Dongzhimen Hospital, , Beijing University of Chinese Medicine, ; Beijing, 100700 China

[2 ]GRID grid.24695.3c, ISNI 0000 0001 1431 9176, Beijing University of Chinese Medicine, ; Beijing, 100102 China

[3 ]GRID grid.24695.3c, ISNI 0000 0001 1431 9176, Institute of Liver Diseases, , Beijing University of Chinese Medicine, ; Beijing, China

Article

Publisher ID: 1147

DOI: 10.1186/s40001-023-01147-x

PMC ID: 10316638

PubMed ID: 37400922

SO-VID: 5f2def21-5fee-4cbb-95ac-c508c2aaad61

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 : 11 January 2023

Date accepted : 24 May 2023

Funding

Funded by: Xiaoke Li

Award ID: 82174341

Award Recipient : Xiaoke Li

Custom metadata

ScienceOpen disciplines: Medicine

Keywords: nonalcoholic fatty liver disease,leptin,causal effect,two-sample mendelian randomization

Data availability:

ScienceOpen disciplines: Medicine

Keywords: nonalcoholic fatty liver disease, leptin, causal effect, two-sample mendelian randomization