Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Diabetologia. 2018 Jun;61(6):1315-1324. doi: 10.1007/s00125-018-4599-x. Epub 2018 Apr 6.
AIMS/HYPOTHESIS: Identifying the metabolite profile of individuals with normal fasting glucose (NFG [<5.55 mmol/l]) who progressed to type 2 diabetes may give novel insights into early type 2 diabetes disease interception and detection.
We conducted a population-based prospective study among 1150 Framingham Heart Study Offspring cohort participants, age 40-65 years, with NFG. Plasma metabolites were profiled by LC-MS/MS. Penalised regression models were used to select measured metabolites for type 2 diabetes incidence classification (training dataset) and to internally validate the discriminatory capability of selected metabolites beyond conventional type 2 diabetes risk factors (testing dataset).
Over a follow-up period of 20 years, 95 individuals with NFG developed type 2 diabetes. Nineteen metabolites were selected repeatedly in the training dataset for type 2 diabetes incidence classification and were found to improve type 2 diabetes risk prediction beyond conventional type 2 diabetes risk factors (AUC was 0.81 for risk factors vs 0.90 for risk factors + metabolites, p = 1.1 × 10). Using pathway enrichment analysis, the nitrogen metabolism pathway, which includes three prioritised metabolites (glycine, taurine and phenylalanine), was significantly enriched for association with type 2 diabetes risk at the false discovery rate of 5% (p = 0.047). In adjusted Cox proportional hazard models, the type 2 diabetes risk per 1 SD increase in glycine, taurine and phenylalanine was 0.65 (95% CI 0.54, 0.78), 0.73 (95% CI 0.59, 0.9) and 1.35 (95% CI 1.11, 1.65), respectively. Mendelian randomisation demonstrated a similar relationship for type 2 diabetes risk per 1 SD genetically increased glycine (OR 0.89 [95% CI 0.8, 0.99]) and phenylalanine (OR 1.6 [95% CI 1.08, 2.4]).
CONCLUSIONS/INTERPRETATION: In individuals with NFG, information from a discrete set of 19 metabolites improved prediction of type 2 diabetes beyond conventional risk factors. In addition, the nitrogen metabolism pathway and its components emerged as a potential effector of earliest stages of type 2 diabetes pathophysiology.
目的/假设：鉴定空腹血糖正常（NFG [<5.55 mmol/l]）但发展为 2 型糖尿病的个体的代谢物谱，可能为早期 2 型糖尿病疾病干预和检测提供新的见解。
我们对 1150 名弗莱明翰心脏研究后代队列参与者进行了一项基于人群的前瞻性研究，年龄在 40-65 岁之间，空腹血糖正常。通过 LC-MS/MS 对血浆代谢物进行了分析。惩罚回归模型用于选择用于 2 型糖尿病发病率分类的测量代谢物（训练数据集），并在常规 2 型糖尿病危险因素之外内部验证所选代谢物的区分能力（测试数据集）。
在 20 年的随访期间，95 名 NFG 个体发展为 2 型糖尿病。在训练数据集中，19 种代谢物被反复选择用于 2 型糖尿病发病分类，并且发现它们可以改善常规 2 型糖尿病危险因素之外的 2 型糖尿病风险预测（危险因素的 AUC 为 0.81，危险因素+代谢物的 AUC 为 0.90，p=1.1×10）。使用途径富集分析，氮代谢途径，包括三种优先代谢物（甘氨酸、牛磺酸和苯丙氨酸），在假发现率为 5%时与 2 型糖尿病风险显著相关（p=0.047）。在调整后的 Cox 比例风险模型中，甘氨酸、牛磺酸和苯丙氨酸每增加 1 SD，2 型糖尿病的风险分别为 0.65（95%CI 0.54，0.78）、0.73（95%CI 0.59，0.9）和 1.35（95%CI 1.11，1.65）。孟德尔随机化研究表明，2 型糖尿病风险每增加 1 SD 的遗传甘氨酸（OR 0.89 [95%CI 0.8，0.99]）和苯丙氨酸（OR 1.6 [95%CI 1.08，2.4]）也存在类似的关系。
结论/解释：在 NFG 个体中，来自离散的 19 种代谢物的信息可改善常规危险因素以外的 2 型糖尿病预测。此外，氮代谢途径及其成分似乎是 2 型糖尿病病理生理学早期阶段的潜在效应因子。
