Omic-Scale High-Throughput Quantitative LC–MS/MS Approach for Circulatory Lipid Phenotyping in Clinical Research

Lipid analysis at the molecular species level represents a valuable opportunity for clinical applications due to the essential roles that lipids play in metabolic health. However, a comprehensive and high-throughput lipid profiling remains challenging given the lipid structural complexity and exceptional diversity. Herein, we present an ‘omic-scale targeted LC–MS/MS approach for the straightforward and high-throughput quantification of a broad panel of complex lipid species across 26 lipid (sub)classes. The workflow involves an automated single-step extraction with 2-propanol, followed by lipid analysis using hydrophilic interaction liquid chromatography in a dual-column setup coupled to tandem mass spectrometry with data acquisition in the timed-selective reaction monitoring mode (12 min total run time). The analysis pipeline consists of an initial screen of 1903 lipid species, followed by high-throughput quantification of robustly detected species. Lipid quantification is achieved by a single-point calibration with 75 isotopically labeled standards representative of different lipid classes, covering lipid species with diverse acyl/alkyl chain lengths and unsaturation degrees. When applied to human plasma, 795 lipid species were measured with median intra- and inter-day precisions of 8.5 and 10.9%, respectively, evaluated within a single and across multiple batches. The concentration ranges measured in NIST plasma were in accordance with the consensus intervals determined in previous ring-trials. Finally, to benchmark our workflow, we characterized NIST plasma materials with different clinical and ethnic backgrounds and analyzed a sub-set of sera (n = 81) from a clinically healthy elderly population. Our quantitative lipidomic platform allowed for a clear distinction between different NIST materials and revealed the sex-specificity of the serum lipidome, highlighting numerous statistically significant sex differences.鉴于脂质在代谢健康中发挥的关键作用，开展脂质分子物种水平的分析为临床应用提供了极具价值的研究契机。然而，由于脂质结构复杂且多样性极高，实现全面且高通量的脂质谱分析仍颇具挑战。在此，我们提出一种组学规模的靶向LC–MS/MS（液相色谱-串联质谱，Liquid Chromatography-Tandem Mass Spectrometry）方法，可便捷、高通量地定量分析覆盖26个脂质（亚）类的多种复杂脂质物种。该分析流程采用自动化单步异丙醇萃取，随后使用双柱构型的亲水相互作用液相色谱（hydrophilic interaction liquid chromatography, HILIC）联用串联质谱，并以定时选择性反应监测模式采集数据，总运行时长为12分钟。本分析管线首先对1903种脂质物种进行初筛，随后对稳定检出的物种开展高通量定量。脂质定量采用75种代表不同脂质类别的同位素标记内标进行单点校准，可覆盖具有不同酰基/烷基链长与不饱和度的脂质物种。将该方法应用于人体血浆样本时，可检出795种脂质物种，其日内、日间精密度的中位数分别为8.5%与10.9%，该性能评估覆盖单批次与多批次实验场景。在NIST（美国国家标准与技术研究院，National Institute of Standards and Technology）血浆样本中测得的浓度范围，与既往室间比对试验确定的共识区间一致。最后，为验证本分析流程的性能基准，我们对具有不同临床与种族背景的NIST血浆样本进行了脂质组表征，并分析了来自临床健康老年人群的81份血清子集样本。我们的定量脂质组学平台可清晰区分不同批次的NIST血浆样本，并揭示了血清脂质组的性别特异性，凸显出多项具有统计学意义的性别差异。