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Investigating the potential anti-depressive mechanisms of statins: a transcriptomic and Mendelian randomization analysis
Observational studies and randomized controlled trials presented inconsistent findings on the effects of cholesterol-lowering statins on depression. It therefore remains unclear whether statins have any beneficial effects on depression, and if so, what the underlying molecular mechanisms are. Here,...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10073189/ https://www.ncbi.nlm.nih.gov/pubmed/37015906 http://dx.doi.org/10.1038/s41398-023-02403-8 |
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author | Jiang, Jiayue-Clara Hu, Chenwen McIntosh, Andrew M. Shah, Sonia |
author_facet | Jiang, Jiayue-Clara Hu, Chenwen McIntosh, Andrew M. Shah, Sonia |
author_sort | Jiang, Jiayue-Clara |
collection | PubMed |
description | Observational studies and randomized controlled trials presented inconsistent findings on the effects of cholesterol-lowering statins on depression. It therefore remains unclear whether statins have any beneficial effects on depression, and if so, what the underlying molecular mechanisms are. Here, we aimed to use genomic approaches to investigate this further. Using Connectivity Map (CMap), we first investigated whether statins and antidepressants shared pharmacological effects by interrogating gene expression responses to drug exposure in human cell lines. Second, using Mendelian randomization analysis, we investigated both on-target (through HMGCR inhibition) and potential off-target (through ITGAL and HDAC2 inhibition) causal effects of statins on depression risk and depressive symptoms, and traits related to the shared biological pathways identified from CMap analysis. Compounds inducing highly similar gene expression responses to statins in HA1E cells (indicated by an average connectivity score with statins > 90) were found to be enriched for antidepressants (12 out of 38 antidepressants; p = 9E-08). Genes perturbed in the same direction by both statins and antidepressants were significantly enriched for diverse cellular and metabolic pathways, and various immune activation, development and response processes. MR analysis did not identify any significant associations between statin exposure and depression risk or symptoms after multiple testing correction. However, genetically proxied HMGCR inhibition was strongly associated with alterations in platelets (a prominent serotonin reservoir) and monocyte percentage, which have previously been implicated in depression. Genetically proxied ITGAL inhibition was strongly associated with basophil, monocyte and neutrophil counts. We identified biological pathways that are commonly perturbed by both statins and antidepressants, and haematological biomarkers genetically associated with statin targets. Our findings warrant pre-clinical investigation of the causal role of these shared pathways in depression and potential as therapeutic targets, and investigation of whether blood biomarkers may be important considerations in clinical trials investigating effects of statins on depression. |
format | Online Article Text |
id | pubmed-10073189 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-100731892023-04-06 Investigating the potential anti-depressive mechanisms of statins: a transcriptomic and Mendelian randomization analysis Jiang, Jiayue-Clara Hu, Chenwen McIntosh, Andrew M. Shah, Sonia Transl Psychiatry Article Observational studies and randomized controlled trials presented inconsistent findings on the effects of cholesterol-lowering statins on depression. It therefore remains unclear whether statins have any beneficial effects on depression, and if so, what the underlying molecular mechanisms are. Here, we aimed to use genomic approaches to investigate this further. Using Connectivity Map (CMap), we first investigated whether statins and antidepressants shared pharmacological effects by interrogating gene expression responses to drug exposure in human cell lines. Second, using Mendelian randomization analysis, we investigated both on-target (through HMGCR inhibition) and potential off-target (through ITGAL and HDAC2 inhibition) causal effects of statins on depression risk and depressive symptoms, and traits related to the shared biological pathways identified from CMap analysis. Compounds inducing highly similar gene expression responses to statins in HA1E cells (indicated by an average connectivity score with statins > 90) were found to be enriched for antidepressants (12 out of 38 antidepressants; p = 9E-08). Genes perturbed in the same direction by both statins and antidepressants were significantly enriched for diverse cellular and metabolic pathways, and various immune activation, development and response processes. MR analysis did not identify any significant associations between statin exposure and depression risk or symptoms after multiple testing correction. However, genetically proxied HMGCR inhibition was strongly associated with alterations in platelets (a prominent serotonin reservoir) and monocyte percentage, which have previously been implicated in depression. Genetically proxied ITGAL inhibition was strongly associated with basophil, monocyte and neutrophil counts. We identified biological pathways that are commonly perturbed by both statins and antidepressants, and haematological biomarkers genetically associated with statin targets. Our findings warrant pre-clinical investigation of the causal role of these shared pathways in depression and potential as therapeutic targets, and investigation of whether blood biomarkers may be important considerations in clinical trials investigating effects of statins on depression. Nature Publishing Group UK 2023-04-04 /pmc/articles/PMC10073189/ /pubmed/37015906 http://dx.doi.org/10.1038/s41398-023-02403-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Jiang, Jiayue-Clara Hu, Chenwen McIntosh, Andrew M. Shah, Sonia Investigating the potential anti-depressive mechanisms of statins: a transcriptomic and Mendelian randomization analysis |
title | Investigating the potential anti-depressive mechanisms of statins: a transcriptomic and Mendelian randomization analysis |
title_full | Investigating the potential anti-depressive mechanisms of statins: a transcriptomic and Mendelian randomization analysis |
title_fullStr | Investigating the potential anti-depressive mechanisms of statins: a transcriptomic and Mendelian randomization analysis |
title_full_unstemmed | Investigating the potential anti-depressive mechanisms of statins: a transcriptomic and Mendelian randomization analysis |
title_short | Investigating the potential anti-depressive mechanisms of statins: a transcriptomic and Mendelian randomization analysis |
title_sort | investigating the potential anti-depressive mechanisms of statins: a transcriptomic and mendelian randomization analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10073189/ https://www.ncbi.nlm.nih.gov/pubmed/37015906 http://dx.doi.org/10.1038/s41398-023-02403-8 |
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