孟德尔随机化研究:为代谢性疾病和慢性肾脏病的研究打开一扇新窗。

Ning Liang, Xiaoqi Ma, Yang Cao, Ting Liu, Jing-Ai Fang, Xiaodong Zhang
{"title":"孟德尔随机化研究:为代谢性疾病和慢性肾脏病的研究打开一扇新窗。","authors":"Ning Liang, Xiaoqi Ma, Yang Cao, Ting Liu, Jing-Ai Fang, Xiaodong Zhang","doi":"10.2174/0118715303288685240808073238","DOIUrl":null,"url":null,"abstract":"<p><p>It is widely recognized that a strong correlation exists between metabolic diseases and chronic kidney disease (CKD). Based on bibliometric statistics, the overall number of Mendelian randomization (MR) analysis in relation to metabolic diseases and CKD has increased since 2005. In recent years, this topic has emerged as a significant area of research interest. In clinical studies, RCTs are often limited due to the intricate causal interplay between metabolic diseases and CKD, which makes it difficult to ascertain the precise etiology of these conditions definitively. In MR studies, genetic variation is incorporated as an instrumental variable (IV). They elucidate the possible causal relationships between associated risk factors and disease risks by including individual innate genetic markers. It is widely believed that MR avoids confounding and can reverse effects to the greatest extent possible. As an increasingly popular technology in the medical field, MR studies have become a popular technology in causal relationships investigation, particularly in epidemiological etiology studies. At present, MR has been widely used for the investigation of medical etiologies, drug development, and decision-making in public health. The article aims to offer insights into the causal relationship between metabolic diseases and CKD, as well as strategies for prevention and treatment, through a summary of MR-related research on these conditions.</p>","PeriodicalId":94316,"journal":{"name":"Endocrine, metabolic & immune disorders drug targets","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mendelian Randomization Studies: Opening a New Window in the Study of Metabolic Diseases and Chronic Kidney Disease.\",\"authors\":\"Ning Liang, Xiaoqi Ma, Yang Cao, Ting Liu, Jing-Ai Fang, Xiaodong Zhang\",\"doi\":\"10.2174/0118715303288685240808073238\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>It is widely recognized that a strong correlation exists between metabolic diseases and chronic kidney disease (CKD). Based on bibliometric statistics, the overall number of Mendelian randomization (MR) analysis in relation to metabolic diseases and CKD has increased since 2005. In recent years, this topic has emerged as a significant area of research interest. In clinical studies, RCTs are often limited due to the intricate causal interplay between metabolic diseases and CKD, which makes it difficult to ascertain the precise etiology of these conditions definitively. In MR studies, genetic variation is incorporated as an instrumental variable (IV). They elucidate the possible causal relationships between associated risk factors and disease risks by including individual innate genetic markers. It is widely believed that MR avoids confounding and can reverse effects to the greatest extent possible. As an increasingly popular technology in the medical field, MR studies have become a popular technology in causal relationships investigation, particularly in epidemiological etiology studies. At present, MR has been widely used for the investigation of medical etiologies, drug development, and decision-making in public health. The article aims to offer insights into the causal relationship between metabolic diseases and CKD, as well as strategies for prevention and treatment, through a summary of MR-related research on these conditions.</p>\",\"PeriodicalId\":94316,\"journal\":{\"name\":\"Endocrine, metabolic & immune disorders drug targets\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Endocrine, metabolic & immune disorders drug targets\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2174/0118715303288685240808073238\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Endocrine, metabolic & immune disorders drug targets","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/0118715303288685240808073238","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

人们普遍认为,代谢性疾病与慢性肾脏病(CKD)之间存在密切的相关性。根据文献计量学统计,自 2005 年以来,与代谢性疾病和慢性肾脏病有关的孟德尔随机化(MR)分析的总体数量有所增加。近年来,该主题已成为一个备受关注的研究领域。在临床研究中,由于代谢性疾病和慢性肾脏病之间错综复杂的因果关系,RCT 通常受到限制,很难明确确定这些疾病的确切病因。在磁共振研究中,遗传变异作为工具变量(IV)被纳入其中。它们通过纳入个体先天遗传标记,阐明相关风险因素与疾病风险之间可能存在的因果关系。人们普遍认为,MR 可以避免混淆,并能最大程度地逆转效应。作为医学领域日益普及的技术,磁共振研究已成为因果关系调查,尤其是流行病学病因学研究中的热门技术。目前,磁共振已广泛应用于医学病因学调查、药物开发和公共卫生决策。本文旨在通过对代谢性疾病和慢性肾脏病相关研究的总结,深入探讨代谢性疾病和慢性肾脏病之间的因果关系以及预防和治疗策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Mendelian Randomization Studies: Opening a New Window in the Study of Metabolic Diseases and Chronic Kidney Disease.

It is widely recognized that a strong correlation exists between metabolic diseases and chronic kidney disease (CKD). Based on bibliometric statistics, the overall number of Mendelian randomization (MR) analysis in relation to metabolic diseases and CKD has increased since 2005. In recent years, this topic has emerged as a significant area of research interest. In clinical studies, RCTs are often limited due to the intricate causal interplay between metabolic diseases and CKD, which makes it difficult to ascertain the precise etiology of these conditions definitively. In MR studies, genetic variation is incorporated as an instrumental variable (IV). They elucidate the possible causal relationships between associated risk factors and disease risks by including individual innate genetic markers. It is widely believed that MR avoids confounding and can reverse effects to the greatest extent possible. As an increasingly popular technology in the medical field, MR studies have become a popular technology in causal relationships investigation, particularly in epidemiological etiology studies. At present, MR has been widely used for the investigation of medical etiologies, drug development, and decision-making in public health. The article aims to offer insights into the causal relationship between metabolic diseases and CKD, as well as strategies for prevention and treatment, through a summary of MR-related research on these conditions.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Safety Profile of Statins for Post-Marketing Adverse Cardiovascular Events: A Real-World Pharmacovigilance Analysis. Tanshinone IIA Regulates NRF2/NLRP3 Signal Pathway to Restrain Oxidative Stress and Inflammation in Uric Acid-Induced HK-2 Fibrotic Models. Ketogenic Diet and Endocrine and Metabolic Diseases: A Bibliometric Study and Visualization Analysis. Effects of ethanol extract from senna leaf (EESL) on inflammation and oxidative stress in mice: A non-targeted metabolomic study. Revealing Fibrosis Genes as Biomarkers of Ulcerative Colitis: A Bioinformatics Study Based on ScRNA and Bulk RNA Datasets.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1