UPLC–QTOF-MS-Based Plasma Lipidomic Profiling Reveals Biomarkers for Inflammatory Bowel Disease Diagnosis

Abstract

Identification of new biomarkers may help in the early diagnosis of inflammatory bowel disease (IBD). In this study, ultrahigh-performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry (UPLC−QTOF-MS) was used to analyze the untargeted lipidomics and compare plasma lipid profiles between IBD patients and control subjects. The principal component analysis and partial least-squares-discriminant analysis were carried out to distinguish IBD patients from control subjects. Using univariate and multivariate analysis, 55 significantly different metabolites from five lipid classes, fatty acyls (n = 19), glycerophospholipids (n = 5), prenol lipids (n = 10), sphingolipids (n = 2), and sterol lipids (n = 19) were identified. Forty-four of the 55 metabolites were analyzed by receiver operating characteristic (ROC) curve and area under curve (AUC) of >0.80. After validation in an independent cohort, IBD patients were differentiated from the control subjects by significantly altered plasma level of palmitic acid, 7alpha, 25-dihydroxycholesterol, 20-hydroxyeicosatetraenoic (HETE)-d6, (+/−)5,6-epoxyeicosatrienoic acid (EpETrE), docosahexaenoic acid (DHA), 9-heptadecylenic acid, lactucaxanthin, α-carotene, traumatic acid, and neoquassin with both sensitivity and specificity above 80%. Pathway analysis suggested that IBD dysregulation was related to the biosynthesis of primary bile acid, the metabolism of arachidonic acid, the metabolism of sphingolipid, fatty acid elongation, and glycerophospholipid metabolism. Our results suggest that the lipidomic profiling of patients plasma could be a potential method for IBD diagnosis.

Systematic Review of Recent Lipidomics Approaches Toward Inflammatory Bowel Disease

“…Certain studies focused specifically on the involvement of SLs in IBD. The roles of ceramide (Cer), ceramide-1-phosphate (C1P), sphingomyelin (SM; Sph), and sphingoid-1-phosphate (S1P) in IBD development were examined (Guan et al, 2020 PC 10:0/26:2, PC 12:0/22:2, PC 12:0/24:2, PC 14:1/22:4, PC 16:1/16:0, PC 14:0/14:0, PC 14:0/16:0, PC 16:0/18:1, PC 18:1/18:0 Another study focusing on UC proposed that SLs may serve as key immunomodulators. However, this report was excluded from our review as the analyses therein were conducted on mice rather than humans.…”

“…For all reports except one, patients were categorized as CD or UC based on clinical and histological criteria. In the other study, the experimental group comprised all patients with CD and UC and they were collectively compared against healthy controls ( Guan et al ., 2020 ). In eight studies, CD and UC patients were individually compared with healthy controls.…”

The current issues and future perspective of artificial intelligence for developing new treatment strategy in non-small cell lung cancer: harmonization of molecular cancer biology and artificial intelligence

“…Logistic regression analysis, ANOVA statistics, and an ensemble approach with random sub-sampling have been widely used to select important features [ 37 – 39 ]. Another way to reduce the dimension of potential features is using unsupervised-machine learning, such as least absolute shrinkage and selection operator (LASSO) regression or principal component analysis (PCA) [ 40 ]. LASSO regression, one approach of regression analysis, has the feature of part of the coefficient being set to zero, reducing that dimension of the feature.…”

“…Meanwhile, PCA weighs and integrates many features to create a relatively small number of new features that represent the overall variability. Guan et al performed PCA to distinguish patients with inflammatory bowel disease (IBD) from control subjects using 55 lipid species [ 40 ]. They defined two new features of principal component 1(PC1) and principal component 2 (PC2), which were able to distinguish between patients with IBD and the control subjects.…”

Fecal metabolomics based on mass spectrometry to investigate the mechanism of qishen granules against isoproterenol‐induced chronic heart failure in rats

“…Metabolomics is a comprehensive study of the types, quantities, and changes of endogenous metabolites under the influence of internal and external factors (such as pathological stimuli and drug intervention) on organisms [10]. Nontargeted metabolomics is the unbiased detection of the dynamic changes of all small molecule metabolites in biological samples, screening for potential biomarkers, and explaining molecular mechanisms [11]. More and more studies have shown that the gut microbiota and its metabolites are closely related to chronic heart failure [12].…”