Utilising lipid and, arginine and proline metabolism in blood plasma to differentiate the biochemical expression in functional dyspepsia (FD) and irritable bowel syndrome (IBS)

Metabolomics(2022)

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摘要
Functional gastrointestinal disorders (FGID) such as functional dyspepsia (FD) and irritable bowel syndrome (IBS) are highly prevalent and debilitating attributed to altered gut function and gut-brain interactions. FGID can be reliably diagnosed based upon the symptom pattern; but in the clinical setting FD or IBS a frequent diagnoses of exclusion after relevant structural causes of symptoms have been ruled out by appropriate testing. Thus far, there is no established biomarker for FGIDs. To address this limitation, we utilised multi-omics and chemometrics integration to characterise the blood plasma biochemistry in patients with IBS, FD, an overlap of FD/IBS, and controls using liquid chromatography-mass spectrometry (LC-MS) techniques. Cholesterol metabolism products Cholest-5,24-dien-3β-ol, 3-O-β-D-glucopyranoside, energy pathway metabolites, immunoglobulin-γ2 and immunoglobulin-κ, and carbonic anhydrase-1 proteins were particularly elevated in IBS. Furthermore, arginine and proline metabolisms, thyroid hormone synthesis, ferroptosis and, complementary and coagulation cascades were particularly upregulated in patients with IBS. Cer(d18:1/26:1(17Z)) and PI(14:0/22:1(11Z)) lipids were elevated in FD and FD-IBS but were depleted in IBS. Markers of central carbon metabolism and lipidome profiles allowed better discrimination and model predictability than metaproteome profile in healthy and FGID conditions. Overall, the multi-omics integration allowed the discrimination of healthy controls and FGID patients. It also effectively differentiated the biochemistry of FGID subtypes including FD, IBS and FD-IBS co-occurrence. This study points towards the possibility of multi-omics integration for rapid and high throughput analysis of plasma samples to support clinicians screen and diagnose patients with suspected FGIDs.
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关键词
FGIDs, Multi-omics, Arginine-proline metabolism, Cholesterol metabolism, Biomarker panel
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