Castro Cecilia, Harshfield Eric L, Butterworth Adam S, Wood Angela M, Koulman Albert, Griffin Julian L
Rowett Institute, University of Aberdeen, Foresterhill, Aberdeen, AB25 2ZD, UK.
Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK.
Data Brief. 2024 Sep 12;57:110925. doi: 10.1016/j.dib.2024.110925. eCollection 2024 Dec.
Understanding the cause of coronary heart diseases relies on the analysis of data from a range of techniques on an epidemiological scale. Lipidomics, the identification and quantification of lipid species in a system, is an omic approach increasingly used in epidemiology. The altered concentration of lipids in plasma is one of the recognised risk factors for these diseases. An important first step in the analysis is to profile lipids in healthy volunteers at an epidemiological level to understand how the geneome influences risk factors; for this reason we made use of the control samples within a bigger case-control sample collection in Pakistan from patients with first acute myocardial infarctions. After extraction, the samples were infused into a Thermo Exactive Orbitrap, without any up-front chromatographic separation. The use of direct infusion allowed fast experiment, facilitating the analysis of large sets of samples. The raw data were processed and analysed using scripts within R, to extract all the meaningful information. The data set originated from this study is a valuable resource to both increase our knowledge in lipid metabolism associated with myocardial infarction, and test new methods and strategy in analysing big lipidomic data sets.
了解冠心病的病因依赖于对一系列流行病学规模技术的数据进行分析。脂质组学,即对系统中脂质种类进行鉴定和定量,是一种在流行病学中越来越常用的组学方法。血浆中脂质浓度的改变是这些疾病公认的危险因素之一。分析的重要第一步是在流行病学层面描绘健康志愿者的脂质特征,以了解基因组如何影响危险因素;出于这个原因,我们利用了巴基斯坦一个更大的病例对照样本收集项目中的对照样本,这些样本来自首次急性心肌梗死患者。提取后,样本直接注入赛默飞世尔Exactive Orbitrap质谱仪,无需任何前期色谱分离。直接进样的方式使实验快速进行,便于对大量样本进行分析。使用R语言中的脚本对原始数据进行处理和分析,以提取所有有意义的信息。本研究产生的数据集是一个宝贵的资源,既能增加我们对与心肌梗死相关的脂质代谢的认识,又能测试分析大型脂质组学数据集的新方法和策略。