基于二维液相色谱质谱技术的深度覆盖脂质组学新方法建立及在糖尿病研究中的应用

Fatty acids (FFAs) are pivotal components of lipids and are relevant to numerous biological processes and development of diseases. Comprehensive analysis of lipids including FFAs, acyl-CoAs, acyl-carnitines, phospholipids, glycerolipids etc. is particularly necessary for disease prevention. However, there is no method being reported for the comprehensive analysis. The main constraints are the large in the number of lipids, the extreme differences in chemical properties and concentrations, and the poor stability of acyl-CoAs. This project intends to investigate a stable sample pretreatment method through the strategy that samples are extracted and ground simultaneously at an ultra-low temperature to avoid the degradation of acyl-CoA. Then, a new two-dimensional liquid chromatography (2DLC) system which can simultaneously cover all FFA-related lipids within one method is developed based on the strategy that the first dimensional pre-separation is combined with the second dimensional parallel columns analysis, and that solvent replacement, as well as post-column mobile phase modifier, are simultaneously introduced. Based on the established method and model mice with type 2 diabetes, we will study the overall response of FFA metabolism from insulin target organs including liver, skeletal muscle, and adipose tissue, to long-term aerobic exercise. The implement of the project will provide a new strategy for high-coverage and high-throughput metabolomics studies and indicate potential targets for effective intervention and prevention of diabetes.

脂肪酸（FFA）是机体脂质的核心组份，与诸多重大疾病密切相关。系统研究FFA代谢谱（含FFA、酰基肉碱、酰基辅酶A（acyl-CoA）、磷脂、甘油酯等）有助于全面理解FFA在生理病理过程中的作用。但国内外尚无高效的全覆盖分析方法，主要制约因素为：脂质种类繁多、理化性质复杂、acyl-CoA稳定性差。对此，本项目拟发展快速稳定的样本前处理方案，采用超低温研磨同时提取的方式解决acyl-CoA稳定性差的问题；设计新型二维液相色谱（2DLC）分离系统，结合馏分预分离和平行柱交替分离，并引入在线溶剂置换和柱后流动相改性剂补充，首次实现一个方法对FFA代谢谱的“全景”分析；利用该方法，系统研究长期有氧运动对2型糖尿病小鼠肝脏、骨骼肌、脂肪等胰岛素靶器官FFA代谢特征的影响，阐述缓解机制。本项目的实施可为高通量、深度覆盖脂质组学研究提供新思路，并为发现2型糖尿病新的干预靶点提供重要科学数据。

本项目发展了高通量样本前处理方案，建立了2DLC-HRMS分离系统，实现了FFA代谢谱深度覆盖分析，设计并建立多平台代谢组学检测体系，实现代谢组和脂质组组份的高通量、深度覆盖检测；将方法用于血清、肝脏组织、回肠组织等不同类型样本分离分析，证明所建立体系的普适性。设计大规模队列研究，并开展深度FFA代谢谱和代谢组检测，系统研究循环代谢物水平与2型糖尿病发生风险的关系和紊乱特征，为发现2型糖尿病新的干预靶点提供重要的科学数据。.首次在前瞻性中国人群中系统、全面研究采用非靶向代谢组学的检测手段，分析998种代谢物和156 种代谢产物与反应物的比值与胰腺癌的关系，解析胰腺癌诊断前的系统代谢紊乱特征，发现氨基酸、类固醇激素等与胰腺癌显著相关，筛选并验证新型代谢物组合（天冬氨酸/丙氨酸、雄烯二醇单硫酸酯和甘氨酰缬氨酸）对早期胰腺癌的诊断价值。率先开展迄今为止最大、最全面的人群脂质组学研究，全面系统评价2型糖尿病患者在糖耐量正常阶段的脂质代谢谱，阐明T2DM发病前脂质通路共调节的改变，为早期调控血脂异常对预防T2DM的潜在益处提供了重要的科学数据。首次基于大样本、前瞻性、多中心中国人群研究队列，发现糖尿病患者糖耐量正常阶段氨基酸和肠道菌群相关代谢物紊乱特征，强调氨基酸和肠道菌群相关代谢物在糖尿病发病机制中的重要性，解析循环代谢物水平与2型糖尿病发生风险的关系；首次报道了天冬酰胺与2型糖尿病发生风险的正相关关系。值得注意的是，本研究纳入受试者在基线和随访时的糖代谢状态均基于OGTT精准评估。本研究探讨了临床危险因素与代谢物-糖尿病的介导关系，为2型糖尿病的诊断以及新的治疗靶点提供新的数据支持。.该项目研究所建立的2DLC-HRMS分离分析体系，具有高通量深度覆盖和重复性好等优点，为性质高度复杂的脂质组和代谢组的全面分析提供技术手段，从而为系统探索2型糖尿病等疾病的代谢紊乱特征提供重要的科学数据，对于筛选新的具有针对性的治疗途径和干预靶点提供新思路，具有重要的意义。