Search

Objectives This study aimed to characterize the systemic lipid profile of patients with asymptomatic hyperuricemia (HUA) and gout using lipidomics, and to find potential underlying pathological mechanisms therefrom. Methods Sera were collected from Affiliated Hospital of Nanjing University of Chinese Medicine as centre 1 (discovery and internal validation sets) and Suzhou Hospital of Traditional Chinese Medicine as centre 2 (external validation set), including 88 normal subjects, 157 HUA and 183 gout patients. Lipidomics was performed by ultra high performance liquid chromatography plus Q-Exactive mass spectrometry (UHPLC-Q Exactive MS). Differential metabolites were identifed by both variable importance in the projection ≥1 in orthogonal partial least-squares discriminant analysis mode and false discovery rate adjusted P ≤ 0.05. Biomarkers were found by logistic regression and receiver operating characteristic (ROC) analysis. Results In the discovery set, a total of 245 and 150 metabolites, respectively, were found for normal subjects vs HUA and normal subjects vs gout. The disturbed metabolites included diacylglycerol, triacylglycerol (TAG), phosphatidylcholine, phosphatidylethanolamine, phosphatidylinositol, etc. We also found 116 differential metabolites for HUA vs gout. Among them, the biomarker panel of TAG 18:1-20:0-22:1 and TAG 14:0-16:0-16:1 could differentiate well between HUA and gout. The area under the receiver operating characteristic ROC curve was 0.8288, the sensitivity was 82% and the specificity was 78%, at a 95% CI 0.747, 0.9106. In the internal validation set, the predictive accuracy of TAG 18:1-20:0-22:1 and TAG 14:0-16:0-16:1 panel for differentiation of HUA and gout reached 74.38%, while it was 84.03% in external validation set. Conclusion We identified serum biomarkers panel that have the potential to predict and diagnose HUA and gout patients. [ABSTRACT FROM AUTHOR]

Metabolomics offers a noninvasive methodology to identify metabolic markers for pathogenesis and diagnosis of diseases. This work aimed to characterize circulating metabolic signatures of benign thyroid nodule (BTN) and papillary thyroid carcinoma (PTC) via serum‐plasma matched metabolomics. A cohort of 1,540 serum‐plasma matched samples and 114 tissues were obtained from healthy volunteers, BTN and PTC patients enrolled from 6 independent centers. Untargeted metabolomics was determined by liquid chromatography‐quadrupole time‐of‐flight mass spectrometric and multivariate statistical analyses. The use of serum‐plasma matched samples afforded a broad‐scope detection of 1,570 metabolic features. Metabolic phenotypes revealed significant pattern differences for healthy versus BTN and healthy versus PTC. Perturbed metabolic pathways related mainly to amino acid and lipid metabolism. It is worth noting that, BTN and PTC showed no significant differences but rather overlap in circulating metabolic signatures, and this observation was replicated in all study centers. For differential diagnosis of healthy versus thyroid nodules (BTN + PTC), a panel of 6 metabolic markers, namely myo‐inositol, α‐N‐phenylacetyl‐L‐glutamine, proline betaine, L‐glutamic acid, LysoPC(18:0) and LysoPC(18:1) provided area under the curve of 97.68% in the discovery phase and predictive accuracies of 84.78–98.18% in the 4 validation centers. Taken together, serum‐plasma matched metabolomics showed significant differences in circulating metabolites for healthy versus nodules but not for BTN versus PTC. Our results highlight the true metabolic nature of thyroid nodules, and potentially decrease overtreatment that exposes patients to unnecessary risks. What's new? When thyroid nodules are classified "indeterminate," is it better to wait and see, or take out the thyroid? Usually, doctors remove the thyroid, resulting in a lifetime of levothyroxine replacement, yet most often the nodules are not cancerous. Here, the authors investigated whether metabolic profile could give a more accurate prediction of whether a thyroid nodule is cancerous. They tested healthy patients, those with benign nodules, and those with papillary thyroid carcinoma. Healthy patients showed distinct differences from those with benign nodules and those with carcinomas, while significant overlap was observed between circulating metabolites from BTN and PTC patients. [ABSTRACT FROM AUTHOR]