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Identification and Analysis of Sex-Biased MicroRNAs in Human Diseases
It is well known that significant differences exist between males and females in both physiology and disease. Thus, it is important to identify and analyze sex-biased miRNAs. However, previous studies investigating sex differences in miRNA expression have predominantly focused on healthy individuals...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10531062/ https://www.ncbi.nlm.nih.gov/pubmed/37761827 http://dx.doi.org/10.3390/genes14091688 |
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author | Zhong, Bitao Cui, Chunmei Cui, Qinghua |
author_facet | Zhong, Bitao Cui, Chunmei Cui, Qinghua |
author_sort | Zhong, Bitao |
collection | PubMed |
description | It is well known that significant differences exist between males and females in both physiology and disease. Thus, it is important to identify and analyze sex-biased miRNAs. However, previous studies investigating sex differences in miRNA expression have predominantly focused on healthy individuals or restricted their analysis to a single disease. Therefore, it is necessary to comprehensively identify and analyze the sex-biased miRNAs in diseases. For this purpose, in this study, we first identified the miRNAs showing sex-biased expression between males and females in diseases based on a number of miRNA expression datasets. Then, we performed a bioinformatics analysis for these sex-biased miRNAs. Notably, our findings revealed that women exhibit a greater number of conserved miRNAs that are highly expressed compared to men, and these miRNAs are implicated in a broader spectrum of diseases. Additionally, we explored the enriched transcription factors, functions, and diseases associated with these sex-biased miRNAs using the miRNA set enrichment analysis tool TAM 2.0. The insights gained from this study could carry implications for endeavors such as precision medicine and possibly pave the way for more targeted and tailored approaches to disease management. |
format | Online Article Text |
id | pubmed-10531062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105310622023-09-28 Identification and Analysis of Sex-Biased MicroRNAs in Human Diseases Zhong, Bitao Cui, Chunmei Cui, Qinghua Genes (Basel) Article It is well known that significant differences exist between males and females in both physiology and disease. Thus, it is important to identify and analyze sex-biased miRNAs. However, previous studies investigating sex differences in miRNA expression have predominantly focused on healthy individuals or restricted their analysis to a single disease. Therefore, it is necessary to comprehensively identify and analyze the sex-biased miRNAs in diseases. For this purpose, in this study, we first identified the miRNAs showing sex-biased expression between males and females in diseases based on a number of miRNA expression datasets. Then, we performed a bioinformatics analysis for these sex-biased miRNAs. Notably, our findings revealed that women exhibit a greater number of conserved miRNAs that are highly expressed compared to men, and these miRNAs are implicated in a broader spectrum of diseases. Additionally, we explored the enriched transcription factors, functions, and diseases associated with these sex-biased miRNAs using the miRNA set enrichment analysis tool TAM 2.0. The insights gained from this study could carry implications for endeavors such as precision medicine and possibly pave the way for more targeted and tailored approaches to disease management. MDPI 2023-08-25 /pmc/articles/PMC10531062/ /pubmed/37761827 http://dx.doi.org/10.3390/genes14091688 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhong, Bitao Cui, Chunmei Cui, Qinghua Identification and Analysis of Sex-Biased MicroRNAs in Human Diseases |
title | Identification and Analysis of Sex-Biased MicroRNAs in Human Diseases |
title_full | Identification and Analysis of Sex-Biased MicroRNAs in Human Diseases |
title_fullStr | Identification and Analysis of Sex-Biased MicroRNAs in Human Diseases |
title_full_unstemmed | Identification and Analysis of Sex-Biased MicroRNAs in Human Diseases |
title_short | Identification and Analysis of Sex-Biased MicroRNAs in Human Diseases |
title_sort | identification and analysis of sex-biased micrornas in human diseases |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10531062/ https://www.ncbi.nlm.nih.gov/pubmed/37761827 http://dx.doi.org/10.3390/genes14091688 |
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