{"title":"转录组学和代谢组学:骨关节炎肥胖症研究面临的挑战","authors":"Jason S. Rockel , Pratibha Potla , Mohit Kapoor","doi":"10.1016/j.ocarto.2024.100479","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><p>Obesity is a leading risk factor for both the incidence and progression of osteoarthritis (OA). Omic technologies, including transcriptomics and metabolomics are capable of identifying RNA and metabolite profiles in tissues and biofluids of OA patients. The objective of this review is to highlight studies using transcriptomics and metabolomics that contribute to our understanding of OA pathology in relation to obesity.</p></div><div><h3>Design</h3><p>We conducted a targeted search of PUBMED for articles, and GEO for datasets, published up to February 13, 2024, screening for those using high-throughput transcriptomic and metabolomic techniques to study human or pre-clinical animal model tissues or biofluids related to obesity-associated OA. We describe relevant studies and discuss challenges studying obesity as a disease-related factor in OA.</p></div><div><h3>Results</h3><p>Of the 107 publications identified by our search criteria, only 15 specifically used transcriptomics or metabolomics to study joint tissues or biofluids in obesity-related OA. Specific transcriptomic and metabolomic signatures associated with obesity-related OA have been defined in select local joint tissues, biofluids and other biological material. However, considerable challenges exist in understanding contributions of obesity-associated modifications of transcriptomes and metabolomes related to OA, including sociodemographic, anthropometric, dietary and molecular redundancy-related factors.</p></div><div><h3>Conclusions</h3><p>A number of additional transcriptomic and metabolomic studies are needed to comprehensively understand how obesity affects OA incidence, progression and outcomes. Integration of transcriptome and metabolome signatures from multiple tissues and biofluids, using network-based approaches will likely help to better define putative therapeutic targets that could enable precision medicine approaches to obese OA patients.</p></div>","PeriodicalId":74377,"journal":{"name":"Osteoarthritis and cartilage open","volume":"6 3","pages":"Article 100479"},"PeriodicalIF":0.0000,"publicationDate":"2024-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2665913124000463/pdfft?md5=326e73331c908327403707c783256b9f&pid=1-s2.0-S2665913124000463-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Transcriptomics and metabolomics: Challenges of studying obesity in osteoarthritis\",\"authors\":\"Jason S. Rockel , Pratibha Potla , Mohit Kapoor\",\"doi\":\"10.1016/j.ocarto.2024.100479\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><p>Obesity is a leading risk factor for both the incidence and progression of osteoarthritis (OA). Omic technologies, including transcriptomics and metabolomics are capable of identifying RNA and metabolite profiles in tissues and biofluids of OA patients. The objective of this review is to highlight studies using transcriptomics and metabolomics that contribute to our understanding of OA pathology in relation to obesity.</p></div><div><h3>Design</h3><p>We conducted a targeted search of PUBMED for articles, and GEO for datasets, published up to February 13, 2024, screening for those using high-throughput transcriptomic and metabolomic techniques to study human or pre-clinical animal model tissues or biofluids related to obesity-associated OA. We describe relevant studies and discuss challenges studying obesity as a disease-related factor in OA.</p></div><div><h3>Results</h3><p>Of the 107 publications identified by our search criteria, only 15 specifically used transcriptomics or metabolomics to study joint tissues or biofluids in obesity-related OA. Specific transcriptomic and metabolomic signatures associated with obesity-related OA have been defined in select local joint tissues, biofluids and other biological material. However, considerable challenges exist in understanding contributions of obesity-associated modifications of transcriptomes and metabolomes related to OA, including sociodemographic, anthropometric, dietary and molecular redundancy-related factors.</p></div><div><h3>Conclusions</h3><p>A number of additional transcriptomic and metabolomic studies are needed to comprehensively understand how obesity affects OA incidence, progression and outcomes. Integration of transcriptome and metabolome signatures from multiple tissues and biofluids, using network-based approaches will likely help to better define putative therapeutic targets that could enable precision medicine approaches to obese OA patients.</p></div>\",\"PeriodicalId\":74377,\"journal\":{\"name\":\"Osteoarthritis and cartilage open\",\"volume\":\"6 3\",\"pages\":\"Article 100479\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2665913124000463/pdfft?md5=326e73331c908327403707c783256b9f&pid=1-s2.0-S2665913124000463-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Osteoarthritis and cartilage open\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2665913124000463\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Osteoarthritis and cartilage open","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2665913124000463","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
目标肥胖是骨关节炎(OA)发病和恶化的主要风险因素。包括转录组学和代谢组学在内的 Omic 技术能够识别 OA 患者组织和生物流体中的 RNA 和代谢物特征。本综述旨在重点介绍利用转录组学和代谢组学进行的研究,这些研究有助于我们了解与肥胖有关的OA病理学。设计我们在PUBMED和GEO上有针对性地搜索了截至2024年2月13日发表的文章和数据集,筛选出那些利用高通量转录组学和代谢组学技术研究与肥胖相关OA的人体或临床前动物模型组织或生物流体的文章。我们描述了相关研究,并讨论了将肥胖作为 OA 中一种疾病相关因素进行研究所面临的挑战。结果在根据我们的搜索标准确定的 107 篇出版物中,只有 15 篇专门使用转录组学或代谢组学研究肥胖相关 OA 中的关节组织或生物流体。与肥胖相关的 OA 的特定转录组学和代谢组学特征已在选定的局部关节组织、生物流体和其他生物材料中确定。然而,要了解肥胖相关的转录组和代谢组的改变对 OA 的贡献,包括社会人口、人体测量、饮食和分子冗余相关因素,还存在相当大的挑战。利用基于网络的方法整合来自多个组织和生物流体的转录组和代谢组特征,将有助于更好地确定可能的治疗靶点,从而为肥胖 OA 患者提供精准医疗方法。
Transcriptomics and metabolomics: Challenges of studying obesity in osteoarthritis
Objective
Obesity is a leading risk factor for both the incidence and progression of osteoarthritis (OA). Omic technologies, including transcriptomics and metabolomics are capable of identifying RNA and metabolite profiles in tissues and biofluids of OA patients. The objective of this review is to highlight studies using transcriptomics and metabolomics that contribute to our understanding of OA pathology in relation to obesity.
Design
We conducted a targeted search of PUBMED for articles, and GEO for datasets, published up to February 13, 2024, screening for those using high-throughput transcriptomic and metabolomic techniques to study human or pre-clinical animal model tissues or biofluids related to obesity-associated OA. We describe relevant studies and discuss challenges studying obesity as a disease-related factor in OA.
Results
Of the 107 publications identified by our search criteria, only 15 specifically used transcriptomics or metabolomics to study joint tissues or biofluids in obesity-related OA. Specific transcriptomic and metabolomic signatures associated with obesity-related OA have been defined in select local joint tissues, biofluids and other biological material. However, considerable challenges exist in understanding contributions of obesity-associated modifications of transcriptomes and metabolomes related to OA, including sociodemographic, anthropometric, dietary and molecular redundancy-related factors.
Conclusions
A number of additional transcriptomic and metabolomic studies are needed to comprehensively understand how obesity affects OA incidence, progression and outcomes. Integration of transcriptome and metabolome signatures from multiple tissues and biofluids, using network-based approaches will likely help to better define putative therapeutic targets that could enable precision medicine approaches to obese OA patients.