Metabolomics Unit, College of Veterinary Medicine, Lincoln Memorial University, 6965 Cumberland Gap Pkwy, Harrogate, TN 37752, USA.
Metabolomics Unit, College of Veterinary Medicine, Lincoln Memorial University, 6965 Cumberland Gap Pkwy, Harrogate, TN 37752, USA; Department of Medicine, DeBusk College of Osteopathic Medicine, Lincoln Memorial University, 6965 Cumberland Gap Pkwy, Harrogate, TN 37752, USA.
Biochem Biophys Res Commun. 2018 Oct 7;504(3):569-575. doi: 10.1016/j.bbrc.2018.03.188. Epub 2018 Mar 27.
Lipidomics is an ever-expanding subfield of metabolomics that surveys 3000 to 5000 individual lipids across more than 56 lipid subclasses, including lipid peroxidation products. Unfortunately, there exists a large number of publications with poor quality data obtained with unit mass resolution leading to many lipid misidentifications. This is further complicated by poor scientific oversight with regard to recognition of isobar issues, sample collection, and sample storage issues that inexplicably requires more detailed attention. Inadvertent or intentional obfuscation of relative quantification data represented as absolute quantification is a subtle but profound difference that may readers outside of the field may not realize, therefore, instigating disservice and unnecessary distrust in the scientific community. These issues need to be addressed aggressively as high quality data are essential for the translation of biomarker research to clinical practice.
脂质组学是代谢组学不断扩展的一个分支领域,它可以检测超过 56 个脂质亚类的 3000 到 5000 种个体脂质,包括脂质过氧化产物。不幸的是,存在大量数据质量较差的出版物,这些出版物使用单位质量分辨率获得数据,导致许多脂质误识别。此外,由于对同量异位问题、样本采集和样本存储问题的科学监督不力,情况变得更加复杂,这些问题需要格外关注。将相对定量数据表示为绝对定量的无意或有意混淆是一个微妙但深远的差异,可能会使领域外的读者无法意识到,因此会对科学界造成损害和不必要的不信任。这些问题需要积极解决,因为高质量的数据对于将生物标志物研究转化为临床实践至关重要。