Cargando…
DNA methylation regulator-mediated modification patterns and risk of intracranial aneurysm: a multi-omics and epigenome-wide association study integrating machine learning, Mendelian randomization, eQTL and mQTL data
BACKGROUND: Intracranial aneurysms (IAs) pose a significant and intricate challenge. Elucidating the interplay between DNA methylation and IA pathogenesis is paramount to identify potential biomarkers and therapeutic interventions. METHODS: We employed a comprehensive bioinformatics investigation of...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10518114/ https://www.ncbi.nlm.nih.gov/pubmed/37742034 http://dx.doi.org/10.1186/s12967-023-04512-w |
_version_ | 1785109442958721024 |
---|---|
author | Maimaiti, Aierpati Turhon, Mirzat Abulaiti, Aimitaji Dilixiati, Yilidanna Zhang, Fujunhui Axieer, Aximujiang Kadeer, Kaheerman Zhang, Yisen Maimaitili, Aisha Yang, Xinjian |
author_facet | Maimaiti, Aierpati Turhon, Mirzat Abulaiti, Aimitaji Dilixiati, Yilidanna Zhang, Fujunhui Axieer, Aximujiang Kadeer, Kaheerman Zhang, Yisen Maimaitili, Aisha Yang, Xinjian |
author_sort | Maimaiti, Aierpati |
collection | PubMed |
description | BACKGROUND: Intracranial aneurysms (IAs) pose a significant and intricate challenge. Elucidating the interplay between DNA methylation and IA pathogenesis is paramount to identify potential biomarkers and therapeutic interventions. METHODS: We employed a comprehensive bioinformatics investigation of DNA methylation in IA, utilizing a transcriptomics-based methodology that encompassed 100 machine learning algorithms, genome-wide association studies (GWAS), Mendelian randomization (MR), and summary-data-based Mendelian randomization (SMR). Our sophisticated analytical strategy allowed for a systematic assessment of differentially methylated genes and their implications on the onset, progression, and rupture of IA. RESULTS: We identified DNA methylation-related genes (MRGs) and associated molecular pathways, and the MR and SMR analyses provided evidence for potential causal links between the observed DNA methylation events and IA predisposition. CONCLUSION: These insights not only augment our understanding of the molecular underpinnings of IA but also underscore potential novel biomarkers and therapeutic avenues. Although our study faces inherent limitations and hurdles, it represents a groundbreaking initiative in deciphering the intricate relationship between genetic, epigenetic, and environmental factors implicated in IA pathogenesis. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-04512-w. |
format | Online Article Text |
id | pubmed-10518114 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-105181142023-09-25 DNA methylation regulator-mediated modification patterns and risk of intracranial aneurysm: a multi-omics and epigenome-wide association study integrating machine learning, Mendelian randomization, eQTL and mQTL data Maimaiti, Aierpati Turhon, Mirzat Abulaiti, Aimitaji Dilixiati, Yilidanna Zhang, Fujunhui Axieer, Aximujiang Kadeer, Kaheerman Zhang, Yisen Maimaitili, Aisha Yang, Xinjian J Transl Med Research BACKGROUND: Intracranial aneurysms (IAs) pose a significant and intricate challenge. Elucidating the interplay between DNA methylation and IA pathogenesis is paramount to identify potential biomarkers and therapeutic interventions. METHODS: We employed a comprehensive bioinformatics investigation of DNA methylation in IA, utilizing a transcriptomics-based methodology that encompassed 100 machine learning algorithms, genome-wide association studies (GWAS), Mendelian randomization (MR), and summary-data-based Mendelian randomization (SMR). Our sophisticated analytical strategy allowed for a systematic assessment of differentially methylated genes and their implications on the onset, progression, and rupture of IA. RESULTS: We identified DNA methylation-related genes (MRGs) and associated molecular pathways, and the MR and SMR analyses provided evidence for potential causal links between the observed DNA methylation events and IA predisposition. CONCLUSION: These insights not only augment our understanding of the molecular underpinnings of IA but also underscore potential novel biomarkers and therapeutic avenues. Although our study faces inherent limitations and hurdles, it represents a groundbreaking initiative in deciphering the intricate relationship between genetic, epigenetic, and environmental factors implicated in IA pathogenesis. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-04512-w. BioMed Central 2023-09-23 /pmc/articles/PMC10518114/ /pubmed/37742034 http://dx.doi.org/10.1186/s12967-023-04512-w 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 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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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. |
spellingShingle | Research Maimaiti, Aierpati Turhon, Mirzat Abulaiti, Aimitaji Dilixiati, Yilidanna Zhang, Fujunhui Axieer, Aximujiang Kadeer, Kaheerman Zhang, Yisen Maimaitili, Aisha Yang, Xinjian DNA methylation regulator-mediated modification patterns and risk of intracranial aneurysm: a multi-omics and epigenome-wide association study integrating machine learning, Mendelian randomization, eQTL and mQTL data |
title | DNA methylation regulator-mediated modification patterns and risk of intracranial aneurysm: a multi-omics and epigenome-wide association study integrating machine learning, Mendelian randomization, eQTL and mQTL data |
title_full | DNA methylation regulator-mediated modification patterns and risk of intracranial aneurysm: a multi-omics and epigenome-wide association study integrating machine learning, Mendelian randomization, eQTL and mQTL data |
title_fullStr | DNA methylation regulator-mediated modification patterns and risk of intracranial aneurysm: a multi-omics and epigenome-wide association study integrating machine learning, Mendelian randomization, eQTL and mQTL data |
title_full_unstemmed | DNA methylation regulator-mediated modification patterns and risk of intracranial aneurysm: a multi-omics and epigenome-wide association study integrating machine learning, Mendelian randomization, eQTL and mQTL data |
title_short | DNA methylation regulator-mediated modification patterns and risk of intracranial aneurysm: a multi-omics and epigenome-wide association study integrating machine learning, Mendelian randomization, eQTL and mQTL data |
title_sort | dna methylation regulator-mediated modification patterns and risk of intracranial aneurysm: a multi-omics and epigenome-wide association study integrating machine learning, mendelian randomization, eqtl and mqtl data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10518114/ https://www.ncbi.nlm.nih.gov/pubmed/37742034 http://dx.doi.org/10.1186/s12967-023-04512-w |
work_keys_str_mv | AT maimaitiaierpati dnamethylationregulatormediatedmodificationpatternsandriskofintracranialaneurysmamultiomicsandepigenomewideassociationstudyintegratingmachinelearningmendelianrandomizationeqtlandmqtldata AT turhonmirzat dnamethylationregulatormediatedmodificationpatternsandriskofintracranialaneurysmamultiomicsandepigenomewideassociationstudyintegratingmachinelearningmendelianrandomizationeqtlandmqtldata AT abulaitiaimitaji dnamethylationregulatormediatedmodificationpatternsandriskofintracranialaneurysmamultiomicsandepigenomewideassociationstudyintegratingmachinelearningmendelianrandomizationeqtlandmqtldata AT dilixiatiyilidanna dnamethylationregulatormediatedmodificationpatternsandriskofintracranialaneurysmamultiomicsandepigenomewideassociationstudyintegratingmachinelearningmendelianrandomizationeqtlandmqtldata AT zhangfujunhui dnamethylationregulatormediatedmodificationpatternsandriskofintracranialaneurysmamultiomicsandepigenomewideassociationstudyintegratingmachinelearningmendelianrandomizationeqtlandmqtldata AT axieeraximujiang dnamethylationregulatormediatedmodificationpatternsandriskofintracranialaneurysmamultiomicsandepigenomewideassociationstudyintegratingmachinelearningmendelianrandomizationeqtlandmqtldata AT kadeerkaheerman dnamethylationregulatormediatedmodificationpatternsandriskofintracranialaneurysmamultiomicsandepigenomewideassociationstudyintegratingmachinelearningmendelianrandomizationeqtlandmqtldata AT zhangyisen dnamethylationregulatormediatedmodificationpatternsandriskofintracranialaneurysmamultiomicsandepigenomewideassociationstudyintegratingmachinelearningmendelianrandomizationeqtlandmqtldata AT maimaitiliaisha dnamethylationregulatormediatedmodificationpatternsandriskofintracranialaneurysmamultiomicsandepigenomewideassociationstudyintegratingmachinelearningmendelianrandomizationeqtlandmqtldata AT yangxinjian dnamethylationregulatormediatedmodificationpatternsandriskofintracranialaneurysmamultiomicsandepigenomewideassociationstudyintegratingmachinelearningmendelianrandomizationeqtlandmqtldata |