Distinct changes in serum metabolites and lipid species in the onset and progression of NAFLD in Obese Chinese

Abstracts: Introduction: Metabolic disturbances are major contributors to the onset and progression of non-alcoholic fatty liver disease (NAFLD), which includes a histological spectrum ranging from single steatosis (SS) to non-alcoholic steatohepatitis (NASH). This study aimed to identify serum metabolites and lipids enriched in different histological stages of NAFLD and to explore metabolites/lipids as non-invasive biomarkers in risk prediction of NAFLD and NASH in obese Chinese. Methods: Serum samples and liver biopsies were obtained from 250 NAFLD subjects. Untargeted metabolomic and lipidomic profiling were performed using Liquid Chromatography-Mass Spectrometry. Significantly altered metabolites and lipids were identified by MaAsLin2. Pathway enrichment was conducted with MetaboAnalyst and LIPEA. WGCNA was implemented to construct the co-expression network. Logistic regression models were developed to classify different histological stages of NAFLD. Results: A total of 263 metabolites and 550 lipid species were detected in serum samples. Differential analysis and pathway enrichment analysis revealed the progressive patterns in metabolic mechanisms during the transition from normal liver to SS and to NASH, including N-palmitoyltaurine, tridecylic acid, and branched-chain amino acid signaling pathways. The co-expression network showed a distinct correlation between different triglyceride and phosphatidylcholine species with disease severity. Multiple models classifying NAFLD versus normal liver and NASH versus SS identified important metabolic features associated with significant improvement in disease prediction compared to conventional clinical parameters. Conclusion: Different histological stages of NAFLD are enriched with distinct sets of metabolites, lipids, and metabolic pathways. Integrated algorithms highlight the important metabolic and lipidomic features for diagnosis and staging of NAFLD in obese individuals. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Jiarui Chen [verfasserIn] Ronald Siyi Lu [verfasserIn] Candela Diaz-Canestro [verfasserIn] Erfei Song [verfasserIn] Xi Jia [verfasserIn] Yan Liu [verfasserIn] Cunchuan Wang [verfasserIn] Cynthia K.Y. Cheung [verfasserIn] Gianni Panagiotou [verfasserIn] Aimin Xu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Schlagwörter:	Non-alcoholic fatty liver disease Simple steatosis Nonalcoholic steatohepatitis Metabolomics Lipidomics Biomarkers

Übergeordnetes Werk:	In: Computational and Structural Biotechnology Journal - Elsevier, 2013, 23(2024), Seite 791-800
Übergeordnetes Werk:	volume:23 ; year:2024 ; pages:791-800

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1016/j.csbj.2024.01.007

Katalog-ID:	DOAJ096249269

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520			\|a Abstracts: Introduction: Metabolic disturbances are major contributors to the onset and progression of non-alcoholic fatty liver disease (NAFLD), which includes a histological spectrum ranging from single steatosis (SS) to non-alcoholic steatohepatitis (NASH). This study aimed to identify serum metabolites and lipids enriched in different histological stages of NAFLD and to explore metabolites/lipids as non-invasive biomarkers in risk prediction of NAFLD and NASH in obese Chinese. Methods: Serum samples and liver biopsies were obtained from 250 NAFLD subjects. Untargeted metabolomic and lipidomic profiling were performed using Liquid Chromatography-Mass Spectrometry. Significantly altered metabolites and lipids were identified by MaAsLin2. Pathway enrichment was conducted with MetaboAnalyst and LIPEA. WGCNA was implemented to construct the co-expression network. Logistic regression models were developed to classify different histological stages of NAFLD. Results: A total of 263 metabolites and 550 lipid species were detected in serum samples. Differential analysis and pathway enrichment analysis revealed the progressive patterns in metabolic mechanisms during the transition from normal liver to SS and to NASH, including N-palmitoyltaurine, tridecylic acid, and branched-chain amino acid signaling pathways. The co-expression network showed a distinct correlation between different triglyceride and phosphatidylcholine species with disease severity. Multiple models classifying NAFLD versus normal liver and NASH versus SS identified important metabolic features associated with significant improvement in disease prediction compared to conventional clinical parameters. Conclusion: Different histological stages of NAFLD are enriched with distinct sets of metabolites, lipids, and metabolic pathways. Integrated algorithms highlight the important metabolic and lipidomic features for diagnosis and staging of NAFLD in obese individuals.
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700	0		\|a Gianni Panagiotou \|e verfasserin \|4 aut
700	0		\|a Aimin Xu \|e verfasserin \|4 aut
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allfields	10.1016/j.csbj.2024.01.007 doi (DE-627)DOAJ096249269 (DE-599)DOAJ8daa620be9e24b74a5135fab902f6fe4 DE-627 ger DE-627 rakwb eng TP248.13-248.65 Jiarui Chen verfasserin aut Distinct changes in serum metabolites and lipid species in the onset and progression of NAFLD in Obese Chinese 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstracts: Introduction: Metabolic disturbances are major contributors to the onset and progression of non-alcoholic fatty liver disease (NAFLD), which includes a histological spectrum ranging from single steatosis (SS) to non-alcoholic steatohepatitis (NASH). This study aimed to identify serum metabolites and lipids enriched in different histological stages of NAFLD and to explore metabolites/lipids as non-invasive biomarkers in risk prediction of NAFLD and NASH in obese Chinese. Methods: Serum samples and liver biopsies were obtained from 250 NAFLD subjects. Untargeted metabolomic and lipidomic profiling were performed using Liquid Chromatography-Mass Spectrometry. Significantly altered metabolites and lipids were identified by MaAsLin2. Pathway enrichment was conducted with MetaboAnalyst and LIPEA. WGCNA was implemented to construct the co-expression network. Logistic regression models were developed to classify different histological stages of NAFLD. Results: A total of 263 metabolites and 550 lipid species were detected in serum samples. Differential analysis and pathway enrichment analysis revealed the progressive patterns in metabolic mechanisms during the transition from normal liver to SS and to NASH, including N-palmitoyltaurine, tridecylic acid, and branched-chain amino acid signaling pathways. The co-expression network showed a distinct correlation between different triglyceride and phosphatidylcholine species with disease severity. Multiple models classifying NAFLD versus normal liver and NASH versus SS identified important metabolic features associated with significant improvement in disease prediction compared to conventional clinical parameters. Conclusion: Different histological stages of NAFLD are enriched with distinct sets of metabolites, lipids, and metabolic pathways. Integrated algorithms highlight the important metabolic and lipidomic features for diagnosis and staging of NAFLD in obese individuals. Non-alcoholic fatty liver disease Simple steatosis Nonalcoholic steatohepatitis Metabolomics Lipidomics Biomarkers Biotechnology Ronald Siyi Lu verfasserin aut Candela Diaz-Canestro verfasserin aut Erfei Song verfasserin aut Xi Jia verfasserin aut Yan Liu verfasserin aut Cunchuan Wang verfasserin aut Cynthia K.Y. Cheung verfasserin aut Gianni Panagiotou verfasserin aut Aimin Xu verfasserin aut In Computational and Structural Biotechnology Journal Elsevier, 2013 23(2024), Seite 791-800 (DE-627)731890086 (DE-600)2694435-2 20010370 nnns volume:23 year:2024 pages:791-800 https://doi.org/10.1016/j.csbj.2024.01.007 kostenfrei https://doaj.org/article/8daa620be9e24b74a5135fab902f6fe4 kostenfrei http://www.sciencedirect.com/science/article/pii/S2001037024000072 kostenfrei https://doaj.org/toc/2001-0370 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2024 791-800
spelling	10.1016/j.csbj.2024.01.007 doi (DE-627)DOAJ096249269 (DE-599)DOAJ8daa620be9e24b74a5135fab902f6fe4 DE-627 ger DE-627 rakwb eng TP248.13-248.65 Jiarui Chen verfasserin aut Distinct changes in serum metabolites and lipid species in the onset and progression of NAFLD in Obese Chinese 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstracts: Introduction: Metabolic disturbances are major contributors to the onset and progression of non-alcoholic fatty liver disease (NAFLD), which includes a histological spectrum ranging from single steatosis (SS) to non-alcoholic steatohepatitis (NASH). This study aimed to identify serum metabolites and lipids enriched in different histological stages of NAFLD and to explore metabolites/lipids as non-invasive biomarkers in risk prediction of NAFLD and NASH in obese Chinese. Methods: Serum samples and liver biopsies were obtained from 250 NAFLD subjects. Untargeted metabolomic and lipidomic profiling were performed using Liquid Chromatography-Mass Spectrometry. Significantly altered metabolites and lipids were identified by MaAsLin2. Pathway enrichment was conducted with MetaboAnalyst and LIPEA. WGCNA was implemented to construct the co-expression network. Logistic regression models were developed to classify different histological stages of NAFLD. Results: A total of 263 metabolites and 550 lipid species were detected in serum samples. Differential analysis and pathway enrichment analysis revealed the progressive patterns in metabolic mechanisms during the transition from normal liver to SS and to NASH, including N-palmitoyltaurine, tridecylic acid, and branched-chain amino acid signaling pathways. The co-expression network showed a distinct correlation between different triglyceride and phosphatidylcholine species with disease severity. Multiple models classifying NAFLD versus normal liver and NASH versus SS identified important metabolic features associated with significant improvement in disease prediction compared to conventional clinical parameters. Conclusion: Different histological stages of NAFLD are enriched with distinct sets of metabolites, lipids, and metabolic pathways. Integrated algorithms highlight the important metabolic and lipidomic features for diagnosis and staging of NAFLD in obese individuals. Non-alcoholic fatty liver disease Simple steatosis Nonalcoholic steatohepatitis Metabolomics Lipidomics Biomarkers Biotechnology Ronald Siyi Lu verfasserin aut Candela Diaz-Canestro verfasserin aut Erfei Song verfasserin aut Xi Jia verfasserin aut Yan Liu verfasserin aut Cunchuan Wang verfasserin aut Cynthia K.Y. Cheung verfasserin aut Gianni Panagiotou verfasserin aut Aimin Xu verfasserin aut In Computational and Structural Biotechnology Journal Elsevier, 2013 23(2024), Seite 791-800 (DE-627)731890086 (DE-600)2694435-2 20010370 nnns volume:23 year:2024 pages:791-800 https://doi.org/10.1016/j.csbj.2024.01.007 kostenfrei https://doaj.org/article/8daa620be9e24b74a5135fab902f6fe4 kostenfrei http://www.sciencedirect.com/science/article/pii/S2001037024000072 kostenfrei https://doaj.org/toc/2001-0370 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2024 791-800
allfields_unstemmed	10.1016/j.csbj.2024.01.007 doi (DE-627)DOAJ096249269 (DE-599)DOAJ8daa620be9e24b74a5135fab902f6fe4 DE-627 ger DE-627 rakwb eng TP248.13-248.65 Jiarui Chen verfasserin aut Distinct changes in serum metabolites and lipid species in the onset and progression of NAFLD in Obese Chinese 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstracts: Introduction: Metabolic disturbances are major contributors to the onset and progression of non-alcoholic fatty liver disease (NAFLD), which includes a histological spectrum ranging from single steatosis (SS) to non-alcoholic steatohepatitis (NASH). This study aimed to identify serum metabolites and lipids enriched in different histological stages of NAFLD and to explore metabolites/lipids as non-invasive biomarkers in risk prediction of NAFLD and NASH in obese Chinese. Methods: Serum samples and liver biopsies were obtained from 250 NAFLD subjects. Untargeted metabolomic and lipidomic profiling were performed using Liquid Chromatography-Mass Spectrometry. Significantly altered metabolites and lipids were identified by MaAsLin2. Pathway enrichment was conducted with MetaboAnalyst and LIPEA. WGCNA was implemented to construct the co-expression network. Logistic regression models were developed to classify different histological stages of NAFLD. Results: A total of 263 metabolites and 550 lipid species were detected in serum samples. Differential analysis and pathway enrichment analysis revealed the progressive patterns in metabolic mechanisms during the transition from normal liver to SS and to NASH, including N-palmitoyltaurine, tridecylic acid, and branched-chain amino acid signaling pathways. The co-expression network showed a distinct correlation between different triglyceride and phosphatidylcholine species with disease severity. Multiple models classifying NAFLD versus normal liver and NASH versus SS identified important metabolic features associated with significant improvement in disease prediction compared to conventional clinical parameters. Conclusion: Different histological stages of NAFLD are enriched with distinct sets of metabolites, lipids, and metabolic pathways. Integrated algorithms highlight the important metabolic and lipidomic features for diagnosis and staging of NAFLD in obese individuals. Non-alcoholic fatty liver disease Simple steatosis Nonalcoholic steatohepatitis Metabolomics Lipidomics Biomarkers Biotechnology Ronald Siyi Lu verfasserin aut Candela Diaz-Canestro verfasserin aut Erfei Song verfasserin aut Xi Jia verfasserin aut Yan Liu verfasserin aut Cunchuan Wang verfasserin aut Cynthia K.Y. Cheung verfasserin aut Gianni Panagiotou verfasserin aut Aimin Xu verfasserin aut In Computational and Structural Biotechnology Journal Elsevier, 2013 23(2024), Seite 791-800 (DE-627)731890086 (DE-600)2694435-2 20010370 nnns volume:23 year:2024 pages:791-800 https://doi.org/10.1016/j.csbj.2024.01.007 kostenfrei https://doaj.org/article/8daa620be9e24b74a5135fab902f6fe4 kostenfrei http://www.sciencedirect.com/science/article/pii/S2001037024000072 kostenfrei https://doaj.org/toc/2001-0370 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2024 791-800
allfieldsGer	10.1016/j.csbj.2024.01.007 doi (DE-627)DOAJ096249269 (DE-599)DOAJ8daa620be9e24b74a5135fab902f6fe4 DE-627 ger DE-627 rakwb eng TP248.13-248.65 Jiarui Chen verfasserin aut Distinct changes in serum metabolites and lipid species in the onset and progression of NAFLD in Obese Chinese 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstracts: Introduction: Metabolic disturbances are major contributors to the onset and progression of non-alcoholic fatty liver disease (NAFLD), which includes a histological spectrum ranging from single steatosis (SS) to non-alcoholic steatohepatitis (NASH). This study aimed to identify serum metabolites and lipids enriched in different histological stages of NAFLD and to explore metabolites/lipids as non-invasive biomarkers in risk prediction of NAFLD and NASH in obese Chinese. Methods: Serum samples and liver biopsies were obtained from 250 NAFLD subjects. Untargeted metabolomic and lipidomic profiling were performed using Liquid Chromatography-Mass Spectrometry. Significantly altered metabolites and lipids were identified by MaAsLin2. Pathway enrichment was conducted with MetaboAnalyst and LIPEA. WGCNA was implemented to construct the co-expression network. Logistic regression models were developed to classify different histological stages of NAFLD. Results: A total of 263 metabolites and 550 lipid species were detected in serum samples. Differential analysis and pathway enrichment analysis revealed the progressive patterns in metabolic mechanisms during the transition from normal liver to SS and to NASH, including N-palmitoyltaurine, tridecylic acid, and branched-chain amino acid signaling pathways. The co-expression network showed a distinct correlation between different triglyceride and phosphatidylcholine species with disease severity. Multiple models classifying NAFLD versus normal liver and NASH versus SS identified important metabolic features associated with significant improvement in disease prediction compared to conventional clinical parameters. Conclusion: Different histological stages of NAFLD are enriched with distinct sets of metabolites, lipids, and metabolic pathways. Integrated algorithms highlight the important metabolic and lipidomic features for diagnosis and staging of NAFLD in obese individuals. Non-alcoholic fatty liver disease Simple steatosis Nonalcoholic steatohepatitis Metabolomics Lipidomics Biomarkers Biotechnology Ronald Siyi Lu verfasserin aut Candela Diaz-Canestro verfasserin aut Erfei Song verfasserin aut Xi Jia verfasserin aut Yan Liu verfasserin aut Cunchuan Wang verfasserin aut Cynthia K.Y. Cheung verfasserin aut Gianni Panagiotou verfasserin aut Aimin Xu verfasserin aut In Computational and Structural Biotechnology Journal Elsevier, 2013 23(2024), Seite 791-800 (DE-627)731890086 (DE-600)2694435-2 20010370 nnns volume:23 year:2024 pages:791-800 https://doi.org/10.1016/j.csbj.2024.01.007 kostenfrei https://doaj.org/article/8daa620be9e24b74a5135fab902f6fe4 kostenfrei http://www.sciencedirect.com/science/article/pii/S2001037024000072 kostenfrei https://doaj.org/toc/2001-0370 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2024 791-800
allfieldsSound	10.1016/j.csbj.2024.01.007 doi (DE-627)DOAJ096249269 (DE-599)DOAJ8daa620be9e24b74a5135fab902f6fe4 DE-627 ger DE-627 rakwb eng TP248.13-248.65 Jiarui Chen verfasserin aut Distinct changes in serum metabolites and lipid species in the onset and progression of NAFLD in Obese Chinese 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstracts: Introduction: Metabolic disturbances are major contributors to the onset and progression of non-alcoholic fatty liver disease (NAFLD), which includes a histological spectrum ranging from single steatosis (SS) to non-alcoholic steatohepatitis (NASH). This study aimed to identify serum metabolites and lipids enriched in different histological stages of NAFLD and to explore metabolites/lipids as non-invasive biomarkers in risk prediction of NAFLD and NASH in obese Chinese. Methods: Serum samples and liver biopsies were obtained from 250 NAFLD subjects. Untargeted metabolomic and lipidomic profiling were performed using Liquid Chromatography-Mass Spectrometry. Significantly altered metabolites and lipids were identified by MaAsLin2. Pathway enrichment was conducted with MetaboAnalyst and LIPEA. WGCNA was implemented to construct the co-expression network. Logistic regression models were developed to classify different histological stages of NAFLD. Results: A total of 263 metabolites and 550 lipid species were detected in serum samples. Differential analysis and pathway enrichment analysis revealed the progressive patterns in metabolic mechanisms during the transition from normal liver to SS and to NASH, including N-palmitoyltaurine, tridecylic acid, and branched-chain amino acid signaling pathways. The co-expression network showed a distinct correlation between different triglyceride and phosphatidylcholine species with disease severity. Multiple models classifying NAFLD versus normal liver and NASH versus SS identified important metabolic features associated with significant improvement in disease prediction compared to conventional clinical parameters. Conclusion: Different histological stages of NAFLD are enriched with distinct sets of metabolites, lipids, and metabolic pathways. Integrated algorithms highlight the important metabolic and lipidomic features for diagnosis and staging of NAFLD in obese individuals. Non-alcoholic fatty liver disease Simple steatosis Nonalcoholic steatohepatitis Metabolomics Lipidomics Biomarkers Biotechnology Ronald Siyi Lu verfasserin aut Candela Diaz-Canestro verfasserin aut Erfei Song verfasserin aut Xi Jia verfasserin aut Yan Liu verfasserin aut Cunchuan Wang verfasserin aut Cynthia K.Y. Cheung verfasserin aut Gianni Panagiotou verfasserin aut Aimin Xu verfasserin aut In Computational and Structural Biotechnology Journal Elsevier, 2013 23(2024), Seite 791-800 (DE-627)731890086 (DE-600)2694435-2 20010370 nnns volume:23 year:2024 pages:791-800 https://doi.org/10.1016/j.csbj.2024.01.007 kostenfrei https://doaj.org/article/8daa620be9e24b74a5135fab902f6fe4 kostenfrei http://www.sciencedirect.com/science/article/pii/S2001037024000072 kostenfrei https://doaj.org/toc/2001-0370 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2024 791-800
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source	In Computational and Structural Biotechnology Journal 23(2024), Seite 791-800 volume:23 year:2024 pages:791-800
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author	Jiarui Chen
spellingShingle	Jiarui Chen misc TP248.13-248.65 misc Non-alcoholic fatty liver disease misc Simple steatosis misc Nonalcoholic steatohepatitis misc Metabolomics misc Lipidomics misc Biomarkers misc Biotechnology Distinct changes in serum metabolites and lipid species in the onset and progression of NAFLD in Obese Chinese
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topic_title	TP248.13-248.65 Distinct changes in serum metabolites and lipid species in the onset and progression of NAFLD in Obese Chinese Non-alcoholic fatty liver disease Simple steatosis Nonalcoholic steatohepatitis Metabolomics Lipidomics Biomarkers
topic	misc TP248.13-248.65 misc Non-alcoholic fatty liver disease misc Simple steatosis misc Nonalcoholic steatohepatitis misc Metabolomics misc Lipidomics misc Biomarkers misc Biotechnology
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title	Distinct changes in serum metabolites and lipid species in the onset and progression of NAFLD in Obese Chinese
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title_full	Distinct changes in serum metabolites and lipid species in the onset and progression of NAFLD in Obese Chinese
author_sort	Jiarui Chen
journal	Computational and Structural Biotechnology Journal
journalStr	Computational and Structural Biotechnology Journal
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author_browse	Jiarui Chen Ronald Siyi Lu Candela Diaz-Canestro Erfei Song Xi Jia Yan Liu Cunchuan Wang Cynthia K.Y. Cheung Gianni Panagiotou Aimin Xu
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author-letter	Jiarui Chen
doi_str_mv	10.1016/j.csbj.2024.01.007
author2-role	verfasserin
title_sort	distinct changes in serum metabolites and lipid species in the onset and progression of nafld in obese chinese
callnumber	TP248.13-248.65
title_auth	Distinct changes in serum metabolites and lipid species in the onset and progression of NAFLD in Obese Chinese
abstract	Abstracts: Introduction: Metabolic disturbances are major contributors to the onset and progression of non-alcoholic fatty liver disease (NAFLD), which includes a histological spectrum ranging from single steatosis (SS) to non-alcoholic steatohepatitis (NASH). This study aimed to identify serum metabolites and lipids enriched in different histological stages of NAFLD and to explore metabolites/lipids as non-invasive biomarkers in risk prediction of NAFLD and NASH in obese Chinese. Methods: Serum samples and liver biopsies were obtained from 250 NAFLD subjects. Untargeted metabolomic and lipidomic profiling were performed using Liquid Chromatography-Mass Spectrometry. Significantly altered metabolites and lipids were identified by MaAsLin2. Pathway enrichment was conducted with MetaboAnalyst and LIPEA. WGCNA was implemented to construct the co-expression network. Logistic regression models were developed to classify different histological stages of NAFLD. Results: A total of 263 metabolites and 550 lipid species were detected in serum samples. Differential analysis and pathway enrichment analysis revealed the progressive patterns in metabolic mechanisms during the transition from normal liver to SS and to NASH, including N-palmitoyltaurine, tridecylic acid, and branched-chain amino acid signaling pathways. The co-expression network showed a distinct correlation between different triglyceride and phosphatidylcholine species with disease severity. Multiple models classifying NAFLD versus normal liver and NASH versus SS identified important metabolic features associated with significant improvement in disease prediction compared to conventional clinical parameters. Conclusion: Different histological stages of NAFLD are enriched with distinct sets of metabolites, lipids, and metabolic pathways. Integrated algorithms highlight the important metabolic and lipidomic features for diagnosis and staging of NAFLD in obese individuals.
abstractGer	Abstracts: Introduction: Metabolic disturbances are major contributors to the onset and progression of non-alcoholic fatty liver disease (NAFLD), which includes a histological spectrum ranging from single steatosis (SS) to non-alcoholic steatohepatitis (NASH). This study aimed to identify serum metabolites and lipids enriched in different histological stages of NAFLD and to explore metabolites/lipids as non-invasive biomarkers in risk prediction of NAFLD and NASH in obese Chinese. Methods: Serum samples and liver biopsies were obtained from 250 NAFLD subjects. Untargeted metabolomic and lipidomic profiling were performed using Liquid Chromatography-Mass Spectrometry. Significantly altered metabolites and lipids were identified by MaAsLin2. Pathway enrichment was conducted with MetaboAnalyst and LIPEA. WGCNA was implemented to construct the co-expression network. Logistic regression models were developed to classify different histological stages of NAFLD. Results: A total of 263 metabolites and 550 lipid species were detected in serum samples. Differential analysis and pathway enrichment analysis revealed the progressive patterns in metabolic mechanisms during the transition from normal liver to SS and to NASH, including N-palmitoyltaurine, tridecylic acid, and branched-chain amino acid signaling pathways. The co-expression network showed a distinct correlation between different triglyceride and phosphatidylcholine species with disease severity. Multiple models classifying NAFLD versus normal liver and NASH versus SS identified important metabolic features associated with significant improvement in disease prediction compared to conventional clinical parameters. Conclusion: Different histological stages of NAFLD are enriched with distinct sets of metabolites, lipids, and metabolic pathways. Integrated algorithms highlight the important metabolic and lipidomic features for diagnosis and staging of NAFLD in obese individuals.
abstract_unstemmed	Abstracts: Introduction: Metabolic disturbances are major contributors to the onset and progression of non-alcoholic fatty liver disease (NAFLD), which includes a histological spectrum ranging from single steatosis (SS) to non-alcoholic steatohepatitis (NASH). This study aimed to identify serum metabolites and lipids enriched in different histological stages of NAFLD and to explore metabolites/lipids as non-invasive biomarkers in risk prediction of NAFLD and NASH in obese Chinese. Methods: Serum samples and liver biopsies were obtained from 250 NAFLD subjects. Untargeted metabolomic and lipidomic profiling were performed using Liquid Chromatography-Mass Spectrometry. Significantly altered metabolites and lipids were identified by MaAsLin2. Pathway enrichment was conducted with MetaboAnalyst and LIPEA. WGCNA was implemented to construct the co-expression network. Logistic regression models were developed to classify different histological stages of NAFLD. Results: A total of 263 metabolites and 550 lipid species were detected in serum samples. Differential analysis and pathway enrichment analysis revealed the progressive patterns in metabolic mechanisms during the transition from normal liver to SS and to NASH, including N-palmitoyltaurine, tridecylic acid, and branched-chain amino acid signaling pathways. The co-expression network showed a distinct correlation between different triglyceride and phosphatidylcholine species with disease severity. Multiple models classifying NAFLD versus normal liver and NASH versus SS identified important metabolic features associated with significant improvement in disease prediction compared to conventional clinical parameters. Conclusion: Different histological stages of NAFLD are enriched with distinct sets of metabolites, lipids, and metabolic pathways. Integrated algorithms highlight the important metabolic and lipidomic features for diagnosis and staging of NAFLD in obese individuals.
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title_short	Distinct changes in serum metabolites and lipid species in the onset and progression of NAFLD in Obese Chinese
url	https://doi.org/10.1016/j.csbj.2024.01.007 https://doaj.org/article/8daa620be9e24b74a5135fab902f6fe4 http://www.sciencedirect.com/science/article/pii/S2001037024000072 https://doaj.org/toc/2001-0370
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author2	Ronald Siyi Lu Candela Diaz-Canestro Erfei Song Xi Jia Yan Liu Cunchuan Wang Cynthia K.Y. Cheung Gianni Panagiotou Aimin Xu
author2Str	Ronald Siyi Lu Candela Diaz-Canestro Erfei Song Xi Jia Yan Liu Cunchuan Wang Cynthia K.Y. Cheung Gianni Panagiotou Aimin Xu
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doi_str	10.1016/j.csbj.2024.01.007
callnumber-a	TP248.13-248.65
up_date	2024-07-03T19:06:31.846Z
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Distinct changes in serum metabolites and lipid species in the onset and progression of NAFLD in Obese Chinese

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