Herpesvirus infections and Alzheimer’s disease: a Mendelian randomization study

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Abstract

Background

Observational studies have suggested that herpesvirus infection increased the risk of Alzheimer’s disease (AD), but it is unclear whether the association is causal. The aim of the present study is to evaluate the causal relationship between four herpesvirus infections and AD.

Methods

We performed a two-sample Mendelian randomization analysis to investigate association of four active herpesvirus infections with AD using summary statistics from genome-wide association studies. The four herpesvirus infections (i.e., chickenpox, shingles, cold sores, mononucleosis) are caused by varicella-zoster virus, herpes simplex virus type 1, and Epstein-Barr virus (EBV), respectively. A large summary statistics data from International Genomics of Alzheimer’s Project was used in primary analysis, including 21,982 AD cases and 41,944 controls. Validation was further performed using family history of AD data from UK Biobank (27,696 cases of maternal AD, 14,338 cases of paternal AD and 272,244 controls).

Results

We found evidence of a significant association between mononucleosis (caused by EBV) and risk of AD after false discovery rates (FDR) correction (odds ratio [OR] = 1.634, 95% confidence interval [CI] = 1.092–2.446, P = 0.017, FDR-corrected P = 0.034). It has been verified in validation analysis that mononucleosis is also associated with family history of AD (OR [95% CI] = 1.392 [1.061, 1.826], P = 0.017). Genetically predicted shingles were associated with AD risk (OR [95% CI] = 0.867 [0.784, 0.958], P = 0.005, FDR-corrected P = 0.020), while genetically predicted chickenpox was suggestively associated with increased family history of AD (OR [95% CI] = 1.147 [1.007, 1.307], P = 0.039).

Conclusions

Our findings provided evidence supporting a positive relationship between mononucleosis and AD, indicating a causal link between EBV infection and AD. Further elucidations of this association and underlying mechanisms are likely to identify feasible interventions to promote AD prevention.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-021-00905-5.

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Most cited references 41

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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

Jin-Tai Yu:

ORCID: http://orcid.org/0000-0002-7686-0547

jintai_yu@fudan.edu.cn

Journal

Journal ID (nlm-ta): Alzheimers Res Ther

Journal ID (iso-abbrev): Alzheimers Res Ther

Title: Alzheimer's Research & Therapy

Publisher: BioMed Central (London )

ISSN (Electronic): 1758-9193

Publication date (Electronic): 24 September 2021

Publication date PMC-release: 24 September 2021

Publication date Collection: 2021

Volume: 13

Electronic Location Identifier: 158

Affiliations

[1 ]GRID grid.11841.3d, ISNI 0000 0004 0619 8943, Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, , Shanghai Medical College, Fudan University, ; 12th Wulumuqi Zhong Road, Shanghai, 200040 China

[2 ]GRID grid.415468.a, ISNI 0000 0004 1761 4893, Department of Neurology, , Qingdao Municipal Hospital, Qingdao University, ; 266071 Qingdao, China

Author information

Jin-Tai Yu http://orcid.org/0000-0002-7686-0547

Article

Publisher ID: 905

DOI: 10.1186/s13195-021-00905-5

PMC ID: 8464096

PubMed ID: 34560893

SO-VID: c29a6f79-ea69-46bd-9bfe-84417e71227b

License:

Open AccessThis 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 March 2021

Date accepted : 15 September 2021

Funding

Funded by: National Natural Science Foundation of China

Award ID: 91849126

Award Recipient : Jin-Tai Yu

Funded by: the National Key R&D Program of China

Award ID: 2018YFC1314702

Award Recipient : Jin-Tai Yu

Funded by: Shanghai Municipal Science and Technology Major Project

Award ID: 2018SHZDZX01

Award Recipient : Jin-Tai Yu

Funded by: ZHANGJIANG LAB

Funded by: Tianqiao and Chrissy Chen Institute

Funded by: the State Key Laboratory of Neurobiology and Frontiers Center for Brain Science of Ministry of Education, Fudan University

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ScienceOpen disciplines: Neurology

Keywords: herpesvirus,infection,alzheimer’s disease,mendelian randomization

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ScienceOpen disciplines: Neurology

Keywords: herpesvirus, infection, alzheimer’s disease, mendelian randomization

Herpesvirus infections and Alzheimer’s disease: a Mendelian randomization study

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Karger: Neurology and Neuroscience

Most cited references 41

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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