A Systematic Review of Biomarkers and Risk of Incident Type 2 Diabetes: An Overview of Epidemiological, Prediction and Aetiological Research Literature.
A Systematic Review of Biomarkers and Risk of Incident Type 2 Diabetes: An Overview of Epidemiological, Prediction and Aetiological Research Literature.
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DOI：
10.1371/journal.pone.0163721
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Wareham NJ
中科院分区：
文献类型：
--
作者：
Abbasi A;Sahlqvist AS;Lotta L;Brosnan JM;Vollenweider P;Giabbanelli P;Nunez DJ;Waterworth D;Scott RA;Langenberg C;Wareham NJ
基于血液或尿液的生物标志物可能在量化2型糖尿病（T2D）的未来风险和了解疾病的可能病因学途径方面发挥作用。然而，尚未进行系统性综述，以确定并概述T2D事件的可用生物标志物。我们的目的是系统地回顾生物标志物与发展T2D的风险之间的关系，并强调现有文献中关于这些生物标志物的预测和病因学价值的证据差距，并指导该领域的未来研究。我们根据2009年PRISMA指南，系统检索了PubMed MEDLINE（2000年1月至2015年3月）和Embase（至2016年1月）数据库中的生物标志物和T2D事件的观察性研究。我们还检索了荟萃分析的可用性，孟德尔随机化和预测研究所确定的生物标志物。我们回顾了3910篇标题（705篇摘要）和164篇全文，并纳入了来自69项队列研究的139篇论文，这些研究描述了167种血液或尿液生物标志物与T2D事件之间的前瞻性关系。在超过1000例T2D病例的大规模研究中仅报告了35种生物标志物，因此大多数生物标志物的相关性证据不确定。使用孟德尔随机化方法研究了14种生物标志物。只有一种生物标志物存在强有力的相关性观察证据和来自遗传相关性研究的证据，与潜在的因果关系相一致。在对T2D预测的额外搜索中，我们发现只有一半的生物标志物被检查，其中少数生物标志物具有预测价值的正式证据。大多数生物标志物并没有增强预测的强度，但预测的最有力证据是用于量化血液病指标的生物标志物。本研究对文献的现状进行了广泛的综述，以告知未来对现有和新描述的T2D生物标志物进行询问的策略。据报道，许多生物标志物与发生T2D的风险相关。到目前为止，它们在增加对疾病因果途径的理解方面的价值的证据非常有限。大多数生物标志物在临床预测中的效用在很大程度上仍然未知。未来的研究应该集中在为孟德尔随机化中可能的生物标志物提供跨财团的良好遗传工具，在大规模队列研究中优先考虑生物标志物的测量，并检查生物标志物在给定背景下的预测效用。
Blood-based or urinary biomarkers may play a role in quantifying the future risk of type 2 diabetes (T2D) and in understanding possible aetiological pathways to disease. However, no systematic review has been conducted that has identified and provided an overview of available biomarkers for incident T2D. We aimed to systematically review the associations of biomarkers with risk of developing T2D and to highlight evidence gaps in the existing literature regarding the predictive and aetiological value of these biomarkers and to direct future research in this field. We systematically searched PubMed MEDLINE (January 2000 until March 2015) and Embase (until January 2016) databases for observational studies of biomarkers and incident T2D according to the 2009 PRISMA guidelines. We also searched availability of meta-analyses, Mendelian randomisation and prediction research for the identified biomarkers. We reviewed 3910 titles (705 abstracts) and 164 full papers and included 139 papers from 69 cohort studies that described the prospective relationships between 167 blood-based or urinary biomarkers and incident T2D. Only 35 biomarkers were reported in large scale studies with more than 1000 T2D cases, and thus the evidence for association was inconclusive for the majority of biomarkers. Fourteen biomarkers have been investigated using Mendelian randomisation approaches. Only for one biomarker was there strong observational evidence of association and evidence from genetic association studies that was compatible with an underlying causal association. In additional search for T2D prediction, we found only half of biomarkers were examined with formal evidence of predictive value for a minority of these biomarkers. Most biomarkers did not enhance the strength of prediction, but the strongest evidence for prediction was for biomarkers that quantify measures of glycaemia. This study presents an extensive review of the current state of the literature to inform the strategy for future interrogation of existing and newly described biomarkers for T2D. Many biomarkers have been reported to be associated with the risk of developing T2D. The evidence of their value in adding to understanding of causal pathways to disease is very limited so far. The utility of most biomarkers remains largely unknown in clinical prediction. Future research should focus on providing good genetic instruments across consortia for possible biomarkers in Mendelian randomisation, prioritising biomarkers for measurement in large-scale cohort studies and examining predictive utility of biomarkers for a given context.
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影响因子：
158.5
作者：
Knowler, WC;Barrett-Connor, E;Nathan, DM
通讯作者：
Nathan, DM
影响因子：
16.2
作者：
Herder C;Brunner EJ;Rathmann W;Strassburger K;Tabák AG;Schloot NC;Witte DR
通讯作者：
Witte DR
影响因子：
5.5
作者：
Buijsse B;Simmons RK;Griffin SJ;Schulze MB
通讯作者：
Schulze MB
影响因子：
16.2
作者：
Fraser A;Harris R;Sattar N;Ebrahim S;Davey Smith G;Lawlor DA
通讯作者：
Lawlor DA
影响因子：
13.6
作者：
Buijsse, Brian;Boeing, Heiner;Kaaks, Rudolf
通讯作者：
Kaaks, Rudolf