TY - JOUR
T1 - Hepatic triglyceride content is intricately associated with numerous metabolites and biochemical pathways
AU - Faquih, Tariq O.
AU - van Klinken, Jan Bert
AU - Li-Gao, Ruifang
AU - Noordam, Raymond
AU - van Heemst, Diana
AU - Boone, Sebastiaan
AU - Sheridan, Patricia A.
AU - Michelotti, Gregory
AU - Lamb, Hildo
AU - de Mutsert, Renée
AU - Rosendaal, Frits R.
AU - van Hylckama Vlieg, Astrid
AU - van Dijk, Ko Willems
AU - Mook-Kanamori, Dennis O.
N1 - Funding Information: The NEO study is supported by the participating Departments, the Division, and the Board of Directors of the Leiden University Medical Centre, and by the Leiden University, Research Profile Area ‘Vascular and Regenerative Medicine’. The analyses of metabolites are funded by the VENI grant (ZonMW‐VENI Grant 916.14.023) of D.O.M.‐K., D.v.H. and R.N. were supported by a grant of the VELUX Stiftung [grant number 1156]. T.O.F. was supported by the King Abdullah Scholarship Program and King Faisal Specialist Hospital & Research Center [No. 1012879283]. Publisher Copyright: © 2023 The Authors. Liver International published by John Wiley & Sons Ltd.
PY - 2023/7
Y1 - 2023/7
N2 - Background and Aims: Non-alcoholic fatty liver disease (NAFLD) is characterized by the pathological accumulation of triglycerides in hepatocytes and is associated with insulin resistance, atherogenic dyslipidaemia and cardiometabolic diseases. Thus far, the extent of metabolic dysregulation associated with hepatic triglyceride accumulation has not been fully addressed. In this study, we aimed to identify metabolites associated with hepatic triglyceride content (HTGC) and map these associations using network analysis. Methods: To gain insight in the spectrum of metabolites associated with hepatic triglyceride accumulation, we performed a comprehensive plasma metabolomics screening of 1363 metabolites in apparently healthy middle aged (age 45–65) individuals (N = 496) in whom HTGC was measured by proton magnetic resonance spectroscopy. An atlas of metabolite–HTGC associations, based on univariate results, was created using correlation-based Gaussian graphical model (GGM) and genome scale metabolic model network analyses. Pathways associated with the clinical prognosis marker fibrosis 4 (FIB-4) index were tested using a closed global test. Results: Our analyses revealed that 118 metabolites were univariately associated with HTGC (p-value <6.59 × 10−5), including 106 endogenous, 1 xenobiotic and 11 partially characterized/uncharacterized metabolites. These associations were mapped to several biological pathways including branched amino acids (BCAA), diglycerols, sphingomyelin, glucosyl-ceramide and lactosyl-ceramide. We also identified a novel possible HTGC-related pathway connecting glutamate, metabolonic lactone sulphate and X-15245 using the GGM network. These pathways were confirmed to be associated with the FIB-4 index as well. The full interactive metabolite-HTGC atlas is provided online: https://tofaquih.github.io/AtlasLiver/. Conclusions: The combined network and pathway analyses indicated extensive associations between BCAA and the lipids pathways with HTGC and the FIB-4 index. Moreover, we report a novel pathway glutamate-metabolonic lactone sulphate-X-15245 with a potential strong association with HTGC. These findings can aid elucidating HTGC metabolomic profiles and provide insight into novel drug targets for fibrosis-related outcomes.
AB - Background and Aims: Non-alcoholic fatty liver disease (NAFLD) is characterized by the pathological accumulation of triglycerides in hepatocytes and is associated with insulin resistance, atherogenic dyslipidaemia and cardiometabolic diseases. Thus far, the extent of metabolic dysregulation associated with hepatic triglyceride accumulation has not been fully addressed. In this study, we aimed to identify metabolites associated with hepatic triglyceride content (HTGC) and map these associations using network analysis. Methods: To gain insight in the spectrum of metabolites associated with hepatic triglyceride accumulation, we performed a comprehensive plasma metabolomics screening of 1363 metabolites in apparently healthy middle aged (age 45–65) individuals (N = 496) in whom HTGC was measured by proton magnetic resonance spectroscopy. An atlas of metabolite–HTGC associations, based on univariate results, was created using correlation-based Gaussian graphical model (GGM) and genome scale metabolic model network analyses. Pathways associated with the clinical prognosis marker fibrosis 4 (FIB-4) index were tested using a closed global test. Results: Our analyses revealed that 118 metabolites were univariately associated with HTGC (p-value <6.59 × 10−5), including 106 endogenous, 1 xenobiotic and 11 partially characterized/uncharacterized metabolites. These associations were mapped to several biological pathways including branched amino acids (BCAA), diglycerols, sphingomyelin, glucosyl-ceramide and lactosyl-ceramide. We also identified a novel possible HTGC-related pathway connecting glutamate, metabolonic lactone sulphate and X-15245 using the GGM network. These pathways were confirmed to be associated with the FIB-4 index as well. The full interactive metabolite-HTGC atlas is provided online: https://tofaquih.github.io/AtlasLiver/. Conclusions: The combined network and pathway analyses indicated extensive associations between BCAA and the lipids pathways with HTGC and the FIB-4 index. Moreover, we report a novel pathway glutamate-metabolonic lactone sulphate-X-15245 with a potential strong association with HTGC. These findings can aid elucidating HTGC metabolomic profiles and provide insight into novel drug targets for fibrosis-related outcomes.
KW - dysregulation
KW - genetic targets
KW - liver triglyceride content
KW - metabolomics
KW - pathway analysis
UR - http://www.scopus.com/inward/record.url?scp=85151996081&partnerID=8YFLogxK
U2 - https://doi.org/10.1111/liv.15575
DO - https://doi.org/10.1111/liv.15575
M3 - Article
C2 - 37017544
SN - 1478-3223
VL - 43
SP - 1458
EP - 1472
JO - Liver international
JF - Liver international
IS - 7
ER -