A lipidomic dataset for epidemiological studies of acute myocardial infarction

IF 1 Q3 MULTIDISCIPLINARY SCIENCES Data in Brief Pub Date : 2024-09-12 DOI:10.1016/j.dib.2024.110925

Cecilia Castro , Eric L. Harshfield , Adam S. Butterworth , Angela M. Wood , Albert Koulman , Julian L. Griffin

{"title":"A lipidomic dataset for epidemiological studies of acute myocardial infarction","authors":"Cecilia Castro , Eric L. Harshfield , Adam S. Butterworth , Angela M. Wood , Albert Koulman , Julian L. Griffin","doi":"10.1016/j.dib.2024.110925","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data in Brief","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352340924008886","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}

引用次数: 0

Abstract

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.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

用于急性心肌梗死流行病学研究的脂质组数据集

了解冠心病的病因有赖于在流行病学范围内对一系列技术数据进行分析。脂质组学是对一个系统中的脂质种类进行识别和量化的方法，是一种在流行病学中应用日益广泛的 omic 方法。血浆中脂质浓度的改变是导致这些疾病的公认风险因素之一。分析中重要的第一步是在流行病学水平上对健康志愿者的血脂进行分析，以了解基因组如何影响风险因素；为此，我们在巴基斯坦收集了大量首次急性心肌梗塞患者的病例对照样本。样本提取后，直接注入 Thermo Exactive Orbitrap 仪器，无需任何前期色谱分离。采用直接注入法可以快速进行实验，便于分析大量样本。原始数据使用 R 脚本进行处理和分析，以提取所有有意义的信息。这项研究产生的数据集是一个宝贵的资源，既能增加我们对心肌梗死相关脂质代谢的了解，又能测试分析脂质组学大数据集的新方法和策略。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.