Cong Wang1, Jun Yang1, Enliang Li1, Shuaiwu Luo1, Chi Sun1, Yuting Liao2, Min Li1, Jin Ge1, Jun Lei1, Fan Zhou3, Linquan Wu4, Wenjun Liao5. 1. Department of General Surgery, The Second Affiliated Hospital of Nanchang University, No. 1, Minde Road, Nanchang, 330006, China. 2. Department of Nursing, Gannan Medical College, No. 1, Medical Road, Ganzhou, 341000, China. 3. Department of General Surgery, The Second Affiliated Hospital of Nanchang University, No. 1, Minde Road, Nanchang, 330006, China. nczhoufan@126.com. 4. Department of General Surgery, The Second Affiliated Hospital of Nanchang University, No. 1, Minde Road, Nanchang, 330006, China. wulqnc@163.com. 5. Department of General Surgery, The Second Affiliated Hospital of Nanchang University, No. 1, Minde Road, Nanchang, 330006, China. liaowenjun120@163.com.
Abstract
BACKGROUND & AIMS: A metabolomic study of hepatolithiasis has yet to be performed. The purpose of the present study was to characterize the metabolite profile and identify potential biomarkers of hepatolithiasis using a metabolomic approach. METHODS: We comprehensively analyzed the serum metabolites from 30 patients with hepatolithiasis and 20 healthy individuals using ultra-high performance liquid chromatography-tandem mass spectrometry operated in negative and positive ionization modes. Statistical analyses were performed using univariate (Student's t-test) and multivariate (orthogonal partial least-squares discriminant analysis) statistics and R language. Receiver operator characteristic (ROC) curve analysis was performed to identify potential predictors of hepatolithiasis. RESULTS: We identified 277 metabolites that were significantly different between hepatolithiasis serum group and healthy control serum group. These metabolites were principally lipids and lipid-like molecules and amino acid metabolites. The steroid hormone biosynthesis pathway was enriched in hepatolithiasis serum group. In all specific metabolites, 75 metabolites were over-expressed in hepatolithiasis serum group. The AUC values for 60 metabolites exceeded 0.70, 4 metabolites including 18-β-Glycyrrhetinic acid, FMH, Rifampicin and PC (4:0/16:2) exceeded 0.90. CONCLUSIONS: We have identified serum metabolites that are associated with hepatolithiasis for the first time. 60 potential metabolic biomarkers were identified, 18-β-Glycyrrhetinic acid, FMH, Rifampicin and PC (4:0/16:2) may have the potential clinical utility in hepatolithiasis.
BACKGROUND & AIMS: A metabolomic study of hepatolithiasis has yet to be performed. The purpose of the present study was to characterize the metabolite profile and identify potential biomarkers of hepatolithiasis using a metabolomic approach. METHODS: We comprehensively analyzed the serum metabolites from 30 patients with hepatolithiasis and 20 healthy individuals using ultra-high performance liquid chromatography-tandem mass spectrometry operated in negative and positive ionization modes. Statistical analyses were performed using univariate (Student's t-test) and multivariate (orthogonal partial least-squares discriminant analysis) statistics and R language. Receiver operator characteristic (ROC) curve analysis was performed to identify potential predictors of hepatolithiasis. RESULTS: We identified 277 metabolites that were significantly different between hepatolithiasis serum group and healthy control serum group. These metabolites were principally lipids and lipid-like molecules and amino acid metabolites. The steroid hormone biosynthesis pathway was enriched in hepatolithiasis serum group. In all specific metabolites, 75 metabolites were over-expressed in hepatolithiasis serum group. The AUC values for 60 metabolites exceeded 0.70, 4 metabolites including 18-β-Glycyrrhetinic acid, FMH, Rifampicin and PC (4:0/16:2) exceeded 0.90. CONCLUSIONS: We have identified serum metabolites that are associated with hepatolithiasis for the first time. 60 potential metabolic biomarkers were identified, 18-β-Glycyrrhetinic acid, FMH, Rifampicin and PC (4:0/16:2) may have the potential clinical utility in hepatolithiasis.
Authors: Cristina Alonso; David Fernández-Ramos; Marta Varela-Rey; Ibon Martínez-Arranz; Nicolás Navasa; Sebastiaan M Van Liempd; José L Lavín Trueba; Rebeca Mayo; Concetta P Ilisso; Virginia G de Juan; Marta Iruarrizaga-Lejarreta; Laura delaCruz-Villar; Itziar Mincholé; Aaron Robinson; Javier Crespo; Antonio Martín-Duce; Manuel Romero-Gómez; Holger Sann; Julian Platon; Jennifer Van Eyk; Patricia Aspichueta; Mazen Noureddin; Juan M Falcón-Pérez; Juan Anguita; Ana M Aransay; María Luz Martínez-Chantar; Shelly C Lu; José M Mato Journal: Gastroenterology Date: 2017-01-26 Impact factor: 22.682
Authors: Jesus M Banales; Mercedes Iñarrairaegui; Ander Arbelaiz; Piotr Milkiewicz; Jordi Muntané; Luis Muñoz-Bellvis; Adelaida La Casta; Luis M Gonzalez; Enara Arretxe; Cristina Alonso; Ibon Martínez-Arranz; Ainhoa Lapitz; Alvaro Santos-Laso; Matias A Avila; Maria L Martínez-Chantar; Luis Bujanda; Jose J G Marin; Bruno Sangro; Rocio I R Macias Journal: Hepatology Date: 2019-02-14 Impact factor: 17.425