Li-Gao Ruifang, de Mutsert Renée, Rensen Patrick C N, van Klinken Jan Bert, Prehn Cornelia, Adamski Jerzy, van Hylckama Vlieg Astrid, den Heijer Martin, le Cessie Saskia, Rosendaal Frits R, Willems van Dijk Ko, Mook-Kanamori Dennis O
Department of Clinical Epidemiology, Leiden University Medical Center, P. O. Box 9600, 2300 RC, Leiden, The Netherlands.
Division of Endocrinology, Department of Medicine, Leiden University Medical Center, Leiden, The Netherlands.
Metabolomics. 2018;14(1):13. doi: 10.1007/s11306-017-1307-7. Epub 2017 Dec 12.
Fasting metabolite profiles have been shown to distinguish type 2 diabetes (T2D) patients from normal glucose tolerance (NGT) individuals.
We investigated whether, besides fasting metabolite profiles, postprandial metabolite profiles associated with T2D can stratify individuals with impaired fasting glucose (IFG) by their similarities to T2D.
Three groups of individuals (age 45-65 years) without any history of IFG or T2D were selected from the Netherlands Epidemiology of Obesity study and stratified by baseline fasting glucose concentrations (NGT (n = 176), IFG (n = 186), T2D (n = 171)). 163 metabolites were measured under fasting and postprandial states (150 min after a meal challenge). Metabolite profiles specific for a high risk of T2D were identified by LASSO regression for fasting and postprandial states. The selected profiles were utilised to stratify IFG group into high (T2D probability ≥ 0.7) and low (T2D probability ≤ 0.5) risk subgroups. The stratification performances were compared with clinically relevant metabolic traits.
Two metabolite profiles specific for T2D (n = 12 metabolites, n = 4 metabolites) were identified, with all four postprandial metabolites also being identified in the fasting state. Stratified by the postprandial profile, the high-risk subgroup of IFG individuals (n = 72) showed similar glucose concentrations to the low-risk subgroup (n = 57), yet a higher BMI (difference: 3.3 kg/m (95% CI 1.7-5.0)) and postprandial insulin concentrations (21.5 mU/L (95% CI 1.8-41.2)).
Postprandial metabolites identified T2D patients as good as fasting metabolites and exhibited enhanced signals for IFG stratification, which offers a proof of concept that metabolomics research should not focus on the fasting state alone.
空腹代谢物谱已被证明可区分2型糖尿病(T2D)患者与正常糖耐量(NGT)个体。
我们研究了除空腹代谢物谱外,与T2D相关的餐后代谢物谱是否能根据与T2D的相似性对空腹血糖受损(IFG)个体进行分层。
从荷兰肥胖流行病学研究中选取三组无IFG或T2D病史的个体(年龄45 - 65岁),并根据基线空腹血糖浓度进行分层(NGT(n = 176),IFG(n = 186),T2D(n = 171))。在空腹和餐后状态(餐后挑战150分钟后)测量163种代谢物。通过LASSO回归确定空腹和餐后状态下T2D高风险特异性代谢物谱。所选谱用于将IFG组分为高风险(T2D概率≥0.7)和低风险(T2D概率≤0.5)亚组。将分层性能与临床相关代谢特征进行比较。
确定了两种T2D特异性代谢物谱(n = 12种代谢物,n = 4种代谢物),所有四种餐后代谢物在空腹状态下也被识别出来。根据餐后谱分层,IFG个体的高风险亚组(n = 72)与低风险亚组(n = 57)血糖浓度相似,但BMI更高(差异:3.3 kg/m²(95% CI 1.7 - 5.0))和餐后胰岛素浓度更高(21.5 mU/L(95% CI 1.8 - 41.2))。
餐后代谢物识别T2D患者的能力与空腹代谢物相当,且在IFG分层中显示出更强的信号,这为代谢组学研究不应仅关注空腹状态提供了概念验证。