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      COVID-19 and Parkinson’s disease: a single-center study and Mendelian randomization study

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          Abstract

          To investigate the association between COVID-19 and Parkinson’s disease (PD) via a single-center study and a Mendelian randomization (MR) study. A questionnaire-based survey was conducted among PD patients at a single center from December 7, 2022, to March 10, 2023. Logistic regression analysis was performed to identify the infection-related risk factors. Subsequently, bidirectional two-sample Mendelian randomization was employed to explore the association between COVID-19 and PD. In the cross-sectional analysis, it was found that the prevalence of COVID-19 infection in PD patients was 65.7%. Forty-eight (35.3%) PD patients experienced exacerbation of motor symptoms following COVID-19 infection. Long PD disease duration (≥ 10 years) (OR: 3.327, P = 0.045) and long time since last vaccination (> 12 m) (OR: 4.916, P = 0.035) were identified as significant risk factors related to infection. The MR analysis results supported that PD increases the COVID-19 susceptibility (β = 0.081, OR = 1.084, P = 0.006). However, the MR analysis showed that PD did not increases the COVID-19 severity and hospitalization, and no significant association of COVID-19 on PD was observed. The findings from this cross-sectional study suggest that individuals with PD may experience worsened motor symptoms following COVID-19 infection. Long disease duration (≥10 years) and long time since last vaccination (> 12 m) are identified as important risk factors for infection in these patients. Furthermore, our MR study provides evidence supporting an association between PD and COVID-19 susceptibility.

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          Most cited references23

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

          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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            The MR-Base platform supports systematic causal inference across the human phenome

            Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly and GWAS results are often insufficiently curated, undermining efficient implementation of the approach. We therefore developed MR-Base (http://www.mrbase.org): a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR. The software includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions. The database currently comprises 11 billion single nucleotide polymorphism-trait associations from 1673 GWAS and is updated on a regular basis. Integrating data with software ensures more rigorous application of hypothesis-driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome-wide association studies.
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              Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

              Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease.
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                Author and article information

                Contributors
                z1990zhengqian@126.com
                h9450203@126.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                17 July 2024
                17 July 2024
                2024
                : 14
                : 16517
                Affiliations
                [1 ]Department of Neurology, The Affiliated Hospital of Guizhou Medical University, ( https://ror.org/02kstas42) Guiyang, 550001 China
                [2 ]Department of Neurosurgery, The Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, ( https://ror.org/01gb3y148) Guiyang, China
                Article
                66197
                10.1038/s41598-024-66197-5
                11255217
                39020020
                9adff0a8-8193-47ba-86e0-4cb296416207
                © The Author(s) 2024

                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/.

                History
                : 19 January 2024
                : 28 June 2024
                Funding
                Funded by: Cultivate Project 2021 of the National Natural Science Foundation of China, Affiliated Hospital of Guizhou Medical University
                Award ID: gyfynsfc-2021-14
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 82360266
                Award Recipient :
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                parkinson’s disease,covid-19,covid-19 susceptibility,motor symptoms,mendelian randomization,neuroscience,diseases,neurology

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