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Barbehenn A, Zhao SD. Nonparametric empirical Bayes biomarker imputation and estimation. Stat Med 2024; 43:3742-3758. [PMID: 38897921 DOI: 10.1002/sim.10150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 03/31/2024] [Accepted: 06/06/2024] [Indexed: 06/21/2024]
Abstract
Biomarkers are often measured in bulk to diagnose patients, monitor patient conditions, and research novel drug pathways. The measurement of these biomarkers often suffers from detection limits that result in missing and untrustworthy measurements. Frequently, missing biomarkers are imputed so that down-stream analysis can be conducted with modern statistical methods that cannot normally handle data subject to informative censoring. This work develops an empirical Bayesg $$ g $$ -modeling method for imputing and denoising biomarker measurements. We establish superior estimation properties compared to popular methods in simulations and with real data, providing the useful biomarker measurement estimations for down-stream analysis.
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Affiliation(s)
- Alton Barbehenn
- Department of Medicine, Division of HIV, Infectious Diseases & Global Medicine, University of California, San Francisco, California, USA
- Department of Statistics, University of Illinois, Urbana-Champaign, Illinois, USA
| | - Sihai Dave Zhao
- Department of Statistics, University of Illinois, Urbana-Champaign, Illinois, USA
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2
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Steenackers N, Eksteen G, Wauters L, Augustijns P, Van der Schueren B, Vanuytsel T, Matthys C. Understanding the gastrointestinal tract in obesity: From gut motility patterns to enzyme secretion. Neurogastroenterol Motil 2024; 36:e14758. [PMID: 38342973 DOI: 10.1111/nmo.14758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 01/15/2024] [Accepted: 01/25/2024] [Indexed: 02/13/2024]
Abstract
BACKGROUND AND PURPOSE The pathophysiology of obesity has been the product of extensive research, revealing multiple interconnected mechanisms contributing to body weight regulation. The regulation of energy balance involves an intricate network, including the gut-neuroendocrine interplay. As a consequence, research on the gut-brain-microbiota axis in obesity has grown extensively. The physiology of the gastrointestinal tract, far from being underexplored, has significant implications for the development of specific complications in people living with obesity across the fields of gastroenterology, nutrition, and pharmacology. Clinical research indicates higher fasting bile acids serum levels, and blunted postprandial increases in bilious secretions in people living with obesity. Findings are less straightforward for the impact of obesity on gastric emptying with various studies reporting accelerated, normal, or delayed gastric emptying rates. Conversely, the effect of obesity on gastrointestinal pH, gastrointestinal transit, and gastric and pancreatic enzyme secretion is largely unknown. In this review, we explore the current evidence on the gastrointestinal physiology of obesity.
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Affiliation(s)
- Nele Steenackers
- Clinical and Experimental Endocrinology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium
| | - Gabriel Eksteen
- Clinical and Experimental Endocrinology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium
| | - Lucas Wauters
- Translational Research Center for Gastrointestinal Disorders, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium
- Department of Gastroenterology and Hepatology, University Hospitals Leuven, Leuven, Belgium
| | - Patrick Augustijns
- Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
| | - Bart Van der Schueren
- Clinical and Experimental Endocrinology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium
- Department of Endocrinology, University Hospitals Leuven, Leuven, Belgium
| | - Tim Vanuytsel
- Translational Research Center for Gastrointestinal Disorders, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium
- Department of Gastroenterology and Hepatology, University Hospitals Leuven, Leuven, Belgium
| | - Christophe Matthys
- Clinical and Experimental Endocrinology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium
- Department of Endocrinology, University Hospitals Leuven, Leuven, Belgium
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3
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Qi L, Ye Z, Lin H. Identification of Differential Metabolites Between
Type 2 Diabetes and Postchronic Pancreatitis Diabetes (Type 3c) Based on an Untargeted Metabolomics Approach. Lab Med 2023; 54:562-573. [PMID: 36864551 DOI: 10.1093/labmed/lmad004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/04/2023] Open
Abstract
OBJECTIVE A nontargeted metabolomics approach was established to characterize serum metabolic profile in type 3c diabetes mellitus (T3cDM) secondary to chronic pancreatitis and compare with T2DM. METHODS Forty patients were recruited for metabolite analysis based on liquid chromatography-mass spectrometry. Cluster heatmap and KEGG metabolic pathway enrichment analysis were used to analyze the specific and differential metabolites. The receiver operating characteristics (ROCs) were generated and correlation analysis with clinical data was conducted. RESULTS Metabolites including sphingosine, lipids, carnitine, bile acid, and hippuric acid were found to be different between T2DM and T3cDM, mainly enriched in bile acid biosynthesis, fatty acid biosynthesis, and sphingolipid metabolic pathways. The ROCs were generated with an area under the curve of 0.907 (95% confidence interval, 0.726-1) for the model with 15 metabolites. CONCLUSION T3cDM is characterized by increased sphingosine, carnitine, bile acid, and most lipids, providing novel biomarkers for clinical diagnosis and a future direction in research on pathophysiological mechanisms.
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Affiliation(s)
- Liang Qi
- Department of Endocrinology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Zheng Ye
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
| | - Hao Lin
- Department of Clinical Science and Research, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
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Beabout K, Ehrenworth Breedon AM, Blum SM, Miklos AE, Lux MW, Chávez JL, Goodson MS. Detection of Bile Acids in Complex Matrices Using a Transcription Factor-Based Biosensor. ACS Biomater Sci Eng 2023; 9:5151-5162. [PMID: 36475595 DOI: 10.1021/acsbiomaterials.2c01006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Bile acids play an important role in digestion and human health, are found throughout the gastrointestinal tract, and are excreted in feces. Therefore, bile acids are promising biomarkers for monitoring health and detecting fecal contamination in water sources. Here, we engineered a bile acid sensor by expressing the transcription factor BreR, a TetR-like repressor from Vibrio cholorae, in Escherichia coli. The sensor was further optimized by screening a promoter library. To further characterize the BreR sensor and increase its utility, we moved expression to a cell-free expression (CFE) system, resulting in an approximately 3 orders of magnitude increase in deoxycholic acid sensitivity. We next optimized this sensor to detect bile acids in fecal water, wastewater, and serum and transferred the CFE sensor to a paper-based assay to enhance fieldability.
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Affiliation(s)
- Kathryn Beabout
- 711th Human Performance Wing, Air Force Research Laboratory, Wright-Patterson Air Force Base, Ohio 45433, United States
- UES, Inc., Dayton, Ohio 45432, United States
| | - Amy M Ehrenworth Breedon
- 711th Human Performance Wing, Air Force Research Laboratory, Wright-Patterson Air Force Base, Ohio 45433, United States
- UES, Inc., Dayton, Ohio 45432, United States
| | - Steven M Blum
- U.S. Army Combat Capabilities Development Command Chemical Biological Center, Aberdeen Proving Ground, Maryland 21010, United States
| | - Aleksandr E Miklos
- U.S. Army Combat Capabilities Development Command Chemical Biological Center, Aberdeen Proving Ground, Maryland 21010, United States
| | - Matthew W Lux
- U.S. Army Combat Capabilities Development Command Chemical Biological Center, Aberdeen Proving Ground, Maryland 21010, United States
| | - Jorge L Chávez
- 711th Human Performance Wing, Air Force Research Laboratory, Wright-Patterson Air Force Base, Ohio 45433, United States
| | - Michael S Goodson
- 711th Human Performance Wing, Air Force Research Laboratory, Wright-Patterson Air Force Base, Ohio 45433, United States
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5
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Feng S, Guo L, Wang S, Chen L, Chang H, Hang B, Mao J, Snijders AM, Lu Y, Ding D. Association of Serum Bile Acid and Unsaturated Fatty Acid Profiles with the Risk of Diabetic Retinopathy in Type 2 Diabetic Patients. Diabetes Metab Syndr Obes 2023; 16:2117-2128. [PMID: 37465650 PMCID: PMC10351529 DOI: 10.2147/dmso.s411522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 06/10/2023] [Indexed: 07/20/2023] Open
Abstract
Aim We aimed to identify the ability of serum bile acids (BAs) and unsaturated fatty acids (UFAs) profiles to predict the development of diabetic retinopathy (DR) in type 2 diabetes mellitus (T2DM) patients. Methods We first used univariate and multivariate analysis to compare 15 serum BA and 11 UFA levels in healthy control (HC) group (n = 82), T2DM patients with DR (n = 58) and T2DM patients without DR (n = 60). Forty T2DM patients were considered for validation. Then, the receiver operating characteristic curve (ROC) and decision curve analysis were used to assess the diagnostic value and clinical benefit of serum biomarkers alone, clinical variables alone or in combination, and the area under the curve (AUC), integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were used to further assess whether the addition of biomarkers significantly improved the predictive ability of the model. Results Orthogonal partial least squares-discriminant analysis (OPLS-DA) of serum BAs and UFAs separated the three cohorts including HC, T2DM patients with or without DR. The difference in serum BA and UFA profiles of T2DM patients with or without DR was mainly manifested in the three metabolites of taurolithocholic acid (TLCA), tauroursodeoxycholic acid (TUDCA) and arachidonic acid (AA). Together, they had an AUC of 0.785 (0.918 for validation cohort) for predicting DR in T2DM patients. After adjusting for numerous confounding factors, TLCA, TUDCA, and AA were independent predictors that differentiated T2DM with or without DR. The results of AUC, IDI, and NRI demonstrated that adding these three biomarkers to a model with clinical variables statistically increased their predictive value and were replicated in our independent validation cohort. Conclusion These findings highlight the association of three metabolites, TLCA, TUDCA and AA, with DR and may indicate their potential value in the pathogenesis of DR.
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Affiliation(s)
- Susu Feng
- Department of Endocrinology, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, People’s Republic of China
| | - Lin Guo
- Department of Endocrinology, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, People’s Republic of China
| | - Sijing Wang
- Department of Endocrinology, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, People’s Republic of China
| | - Lijuan Chen
- Department of Endocrinology, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, People’s Republic of China
| | - Hang Chang
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Bo Hang
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Department of Biomaterials, Berkeley-Nanjing Research Center, Nanjing, People's Republic of China
| | - Jianhua Mao
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Antoine M Snijders
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Yibing Lu
- Department of Endocrinology, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, People’s Republic of China
| | - Dafa Ding
- Department of Endocrinology, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, People’s Republic of China
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Bai Z, Huang X, Wu G, Zhang Y, Xu H, Chen Y, Yang H, Nie S. Polysaccharides from small black soybean alleviating type 2 diabetes via modulation of gut microbiota and serum metabolism. Food Hydrocoll 2023. [DOI: 10.1016/j.foodhyd.2023.108670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2023]
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Cai J, Rimal B, Jiang C, Chiang JYL, Patterson AD. Bile acid metabolism and signaling, the microbiota, and metabolic disease. Pharmacol Ther 2022; 237:108238. [PMID: 35792223 DOI: 10.1016/j.pharmthera.2022.108238] [Citation(s) in RCA: 104] [Impact Index Per Article: 52.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 06/13/2022] [Accepted: 06/27/2022] [Indexed: 11/24/2022]
Abstract
The diversity, composition, and function of the bacterial community inhabiting the human gastrointestinal tract contributes to host health through its role in producing energy or signaling molecules that regulate metabolic and immunologic functions. Bile acids are potent metabolic and immune signaling molecules synthesized from cholesterol in the liver and then transported to the intestine where they can undergo metabolism by gut bacteria. The combination of host- and microbiota-derived enzymatic activities contribute to the composition of the bile acid pool and thus there can be great diversity in bile acid composition that depends in part on the differences in the gut bacteria species. Bile acids can profoundly impact host metabolic and immunological functions by activating different bile acid receptors to regulate signaling pathways that control a broad range of complex symbiotic metabolic networks, including glucose, lipid, steroid and xenobiotic metabolism, and modulation of energy homeostasis. Disruption of bile acid signaling due to perturbation of the gut microbiota or dysregulation of the gut microbiota-host interaction is associated with the pathogenesis and progression of metabolic disorders. The metabolic and immunological roles of bile acids in human health have led to novel therapeutic approaches to manipulate the bile acid pool size, composition, and function by targeting one or multiple components of the microbiota-bile acid-bile acid receptor axis.
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Affiliation(s)
- Jingwei Cai
- Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, PA, USA
| | - Bipin Rimal
- Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, PA, USA
| | - Changtao Jiang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Peking University, and the Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Beijing, PR China
| | - John Y L Chiang
- Department of Integrative Medical Sciences, College of Medicine, Northeast Ohio Medical University, Rootstown, OH, USA
| | - Andrew D Patterson
- Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, PA, USA.
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Liu X, Cheng F, Bai X, Zhao T, Zhao L, Wang L, Li M, Wu X, Chen X, Tang P, Wang M, Jiang L, Yan C, Pei F, Gao X, Ma N, Yang B, Zhang Y. MiR-203 is an anti-obese miRNA by targeting ASBT. iScience 2022; 25:104708. [PMID: 35856025 PMCID: PMC9287609 DOI: 10.1016/j.isci.2022.104708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 05/29/2022] [Accepted: 06/28/2022] [Indexed: 12/01/2022] Open
Abstract
Obesity is characterized by excessive fat deposition within the body. Bile acids (BA) are important regulators for controlling the absorption of lipid. Here we show that miR-203 exerts weight-loss and lipid-lowering effects by increasing total BA excretion in obese rodents. miR-203 overexpression transgenic mice are resistant to high-fat diet (HFD)-induced obesity and dyslipidemia. Moreover, the knockdown of miR-203 deteriorates metabolic disorders. ASBT plays important role in regulating BA homeostasis and is a direct target of miR-203. In human intestinal epithelial cells, overexpression of miR-203 decreases the cellular uptake of BA by inhibiting ASBT. Furthermore, TCF7L2 is downregulated in obese mice and acts as a transcription factor of miR-203. The ASBT mRNA level was positively correlated with the body mass index (BMI) of population, while the miR-203 level was negatively associated with BMI. Taken together, these data suggest miR-203 could be a new therapeutic BA regulator for obesity and dyslipidemia. miR-203 is downregulated in obese rodents and overweight/obese population ASBT is a direct target of miR-203 in obesity TCF7L2 acts as an upstream activator of miR-203 in obesity miR-203 ameliorates obesity and dyslipidemia by increasing TBAs and lipids excretion
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Heianza Y, Zhou T, He H, Rood J, Clish CB, Bray GA, Sacks FM, Qi L. Changes in bile acid subtypes and long-term successful weight-loss in response to weight-loss diets: The POUNDS lost trial. Liver Int 2022; 42:363-373. [PMID: 34748263 DOI: 10.1111/liv.15098] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 10/27/2021] [Accepted: 11/04/2021] [Indexed: 12/31/2022]
Abstract
BACKGROUND AND AIMS Primary bile acids (BAs) are synthesized in the liver and secondary BAs result from intestinal microbial activity. Different subtypes of BAs may be involved in regulating adiposity and energy homeostasis. We examined how changes in circulating BA subtypes induced by weight-loss diets were associated with improvements in adiposity, regional fat deposition and energy metabolism among overweight and obese adults. METHODS The study included 551 subjects who participated in a 2-year weight-loss diet intervention trial. Circulating 14 BA subtypes (primary and secondary unconjugated BAs and their taurine-/glycine-conjugates) were measured at baseline and 6 months. Associations of changes in BAs with changes in weight, waist circumference, resting energy expenditure (REE), body fat composition and fat distribution were evaluated. RESULTS Greater decreases in primary BAs (cholate and chenodeoxycholate) and secondary BAs (deoxycholate and lithocholate) and their conjugates (except for glycolithocholate) were associated with more decreases in weight and waist circumference at 6 months (P-after-false-discovery-rate-correction [PFDR ] < .05). We found that changes in glycocholate and glycoursodeoxycholate were consistently associated with reductions of general and central adiposity, REE, whole-body fat and visceral adipose tissue (PFDR < .05). Further, the initial (6-month) changes in BA subtypes were differently predictive of successful weight loss over 2 years. CONCLUSIONS The decreases in primary and secondary BA subtypes after eating low-calorie weight-loss diets were significantly associated with improving adiposity, fat accumulation and energy metabolism, suggesting that specific BA subtypes would be predictive of long-term successful weight loss and individuals' response to the treatment of weight-loss diets.
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Affiliation(s)
- Yoriko Heianza
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana, USA
| | - Tao Zhou
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana, USA
| | - Hua He
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana, USA
| | - Jennifer Rood
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, Louisiana, USA
| | - Clary B Clish
- Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - George A Bray
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, Louisiana, USA
| | - Frank M Sacks
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana, USA.,Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
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10
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Metabolomics prospect of obesity and metabolic syndrome; a systematic review. J Diabetes Metab Disord 2021; 21:889-917. [DOI: 10.1007/s40200-021-00917-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 10/06/2021] [Indexed: 02/06/2023]
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Improved fatty acid profile reduces body fat and arterial stiffness in obese adolescents upon combinatorial intervention with exercise and dietary restriction. J Exerc Sci Fit 2021; 19:234-240. [PMID: 34552635 PMCID: PMC8429968 DOI: 10.1016/j.jesf.2021.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 08/13/2021] [Accepted: 08/20/2021] [Indexed: 11/22/2022] Open
Abstract
Objective In order to examine the effect of 4-week combinatorial intervention with exercise training and dietary restriction on serum fatty acids, and to explore the correlation of intervention-induced improvement of serum fatty acid profile with the reduction of body fat and arterial stiffness. Methods Thirty-three obese adolescents were randomized into the intervention (n = 19) and control (n = 14) groups. The participants from the intervention group were subjected to 4-week combinatorial intervention with exercise training and dietary restriction while the participants from the control group maintained regular activities and diet habits. Anthropometry, serum fatty acids and arterial stiffness were measured before and after 4-week intervention. Results The participants upon combinatorial intervention revealed the improved body compositions and serum fatty acid profile, and reduced arterial stiffness when compared with their basal levels and the control participants (p < 0.05). Moreover, the decrease in myristic acid, stearic acid, arachidic acid, behenic acid, palmitoleic acid, and dihomo-γ-linolenic acid, was associated with the reduction in body fat. A positive correlation between arachidonic acid and left brachial ankle pulse velocity was observed, and the increase in docosahexaenoic acid was associated with the reduction of left brachial ankle pulse wave velocity and the enhancement of right ankle brachial index. Conclusion The 4-week combinatorial intervention is a useful strategy to improve serum fatty acid profile along with the reduction of body fat and arterial stiffness in obese adolescents.
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Zheng X, Chen T, Jiang R, Zhao A, Wu Q, Kuang J, Sun D, Ren Z, Li M, Zhao M, Wang S, Bao Y, Li H, Hu C, Dong B, Li D, Wu J, Xia J, Wang X, Lan K, Rajani C, Xie G, Lu A, Jia W, Jiang C, Jia W. Hyocholic acid species improve glucose homeostasis through a distinct TGR5 and FXR signaling mechanism. Cell Metab 2021; 33:791-803.e7. [PMID: 33338411 DOI: 10.1016/j.cmet.2020.11.017] [Citation(s) in RCA: 180] [Impact Index Per Article: 60.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2020] [Revised: 07/31/2020] [Accepted: 11/20/2020] [Indexed: 02/08/2023]
Abstract
Hyocholic acid (HCA) and its derivatives are found in trace amounts in human blood but constitute approximately 76% of the bile acid (BA) pool in pigs, a species known for its exceptional resistance to type 2 diabetes. Here, we show that BA depletion in pigs suppressed secretion of glucagon-like peptide-1 (GLP-1) and increased blood glucose levels. HCA administration in diabetic mouse models improved serum fasting GLP-1 secretion and glucose homeostasis to a greater extent than tauroursodeoxycholic acid. HCA upregulated GLP-1 production and secretion in enteroendocrine cells via simultaneously activating G-protein-coupled BA receptor, TGR5, and inhibiting farnesoid X receptor (FXR), a unique mechanism that is not found in other BA species. We verified the findings in TGR5 knockout, intestinal FXR activation, and GLP-1 receptor inhibition mouse models. Finally, we confirmed in a clinical cohort, that lower serum concentrations of HCA species were associated with diabetes and closely related to glycemic markers.
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Affiliation(s)
- Xiaojiao Zheng
- Center for Translational Medicine, Shanghai Key Laboratory of Diabetes Mellitus and Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Tianlu Chen
- Center for Translational Medicine, Shanghai Key Laboratory of Diabetes Mellitus and Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Runqiu Jiang
- Department of Hepatobiliary Surgery, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing 210093, China
| | - Aihua Zhao
- Center for Translational Medicine, Shanghai Key Laboratory of Diabetes Mellitus and Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Qing Wu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Peking University, and the Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Beijing 100191, China
| | - Junliang Kuang
- Center for Translational Medicine, Shanghai Key Laboratory of Diabetes Mellitus and Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Dongnan Sun
- Center for Translational Medicine, Shanghai Key Laboratory of Diabetes Mellitus and Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Zhenxing Ren
- Center for Translational Medicine, Shanghai Key Laboratory of Diabetes Mellitus and Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Mengci Li
- Center for Translational Medicine, Shanghai Key Laboratory of Diabetes Mellitus and Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Mingliang Zhao
- Center for Translational Medicine, Shanghai Key Laboratory of Diabetes Mellitus and Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Shouli Wang
- Center for Translational Medicine, Shanghai Key Laboratory of Diabetes Mellitus and Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Yuqian Bao
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Diabetes Institute, Shanghai 200233, China
| | - Huating Li
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Diabetes Institute, Shanghai 200233, China
| | - Cheng Hu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Diabetes Institute, Shanghai 200233, China
| | - Bing Dong
- National Key Laboratory of Animal Nutrition, China Agricultural University, Beijing 100193, China
| | - Defa Li
- National Key Laboratory of Animal Nutrition, China Agricultural University, Beijing 100193, China
| | - Jiayu Wu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Peking University, and the Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Beijing 100191, China
| | - Jialin Xia
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Peking University, and the Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Beijing 100191, China
| | - Xuemei Wang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Peking University, and the Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Beijing 100191, China
| | - Ke Lan
- Key Laboratory of Drug Targeting and Drug Delivery System, Ministry of Education, West China School of Pharmacy, Sichuan University, Chengdu 610041, China
| | - Cynthia Rajani
- University of Hawaii Cancer Center, Honolulu, HI 96813, USA
| | - Guoxiang Xie
- University of Hawaii Cancer Center, Honolulu, HI 96813, USA
| | - Aiping Lu
- School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China
| | - Weiping Jia
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Diabetes Institute, Shanghai 200233, China.
| | - Changtao Jiang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Peking University, and the Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Beijing 100191, China.
| | - Wei Jia
- Center for Translational Medicine, Shanghai Key Laboratory of Diabetes Mellitus and Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China; University of Hawaii Cancer Center, Honolulu, HI 96813, USA; School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China.
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Asano T, Taki K, Kitamori K, Naito H, Nakajima T, Tsuchihashi H, Ishii A, Zaitsu K. One-Pot Extraction and Quantification Method for Bile Acids in the Rat Liver by Capillary Liquid Chromatography Tandem Mass Spectrometry. ACS OMEGA 2021; 6:8588-8597. [PMID: 33817519 PMCID: PMC8015121 DOI: 10.1021/acsomega.1c00403] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 03/05/2021] [Indexed: 06/12/2023]
Abstract
We developed a highly sensitive method for quantifying 21 bile acids (BAs) in the rat liver by capillary liquid chromatography tandem mass spectrometry (cLC/MS/MS) with one-pot extraction. High recovery rates were obtained for the one-pot methods with either methanol (MeOH) extraction or MeOH/acetonitrile (ACN) (1:1, v/v) mixture extraction; the results obtained for the MeOH/ACN mixture solution were better than the results obtained for MeOH. Thus, we determined that the one-pot method with MeOH/ACN was the most suitable method for the efficient extraction of BAs in the liver. Targeted BAs were well separated by cLC with gradient elution using ammonium acetate (NH4OAc)-MeOH mobile phases. Method validation proved that the intra-day and inter-day accuracies and precisions were primarily less than ±20 and 20% relative standard deviation, respectively. Also, the limit of detection (LOD) and the limit of quantitation (LOQ) were 0.9-10 and 2.3-27 ng/g liver, which proves the high sensitivity of the method. Finally, we quantitated 21 BA concentrations in the liver samples of normal and nonalcoholic steatohepatitis (NASH) rats, both of which were derived from stroke-prone spontaneously hypertensive five (SHRSP5) /Dmcr rat. The hepatic BA profiles were found to be substantially different between the normal and NASH groups; the two groups were clearly separated along the first component axis in the score plots of the principal component analysis. In particular, 10 BAs (β-muricholic acid (MCA), glyco (G-) cholic acid (CA), G-chenodeoxycholic acid (CDCA), tauro (T-) CA, T-CDCA, T-ursodeoxycholic acid (UDCA), T-lithocholic acid (LCA), T-hiodeoxycholic acid (HDCA), T-α-MCA, and T-β-MCA) were significantly different between the two groups using Welch's t-test with the false discovery rate correction method, demonstrating BA disruption in the NASH model rat. In conclusion, this method was able to quantify 21 BAs in the rat liver and will evaluate the hepatic BA pathophysiology of rat disease models.
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Affiliation(s)
- Tomomi Asano
- Department
of Human Life and Environment, Kinjo Gakuin
University, 2-1723 Omori, Moriyama-ku, Nagoya 463-8521, Japan
- Department
of Legal Medicine & Bioethics, Nagoya
University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Kentaro Taki
- Department
of Legal Medicine & Bioethics, Nagoya
University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Kazuya Kitamori
- Department
of Human Life and Environment, Kinjo Gakuin
University, 2-1723 Omori, Moriyama-ku, Nagoya 463-8521, Japan
| | - Hisao Naito
- Department
of Human Life and Environment, Kinjo Gakuin
University, 2-1723 Omori, Moriyama-ku, Nagoya 463-8521, Japan
| | - Tamie Nakajima
- College
of Life and Health Sciences, Chubu University, 1200 Matsumoto-cho, Kasugai, Aichi 487-8501, Japan
| | - Hitoshi Tsuchihashi
- Department
of Legal Medicine & Bioethics, Nagoya
University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Akira Ishii
- Department
of Legal Medicine & Bioethics, Nagoya
University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Kei Zaitsu
- Department
of Legal Medicine & Bioethics, Nagoya
University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
- In
Vivo Real-time Omics Laboratory, Institute for Advanced Research, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan
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14
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Lv XC, Chen M, Huang ZR, Guo WL, Ai LZ, Bai WD, Yu XD, Liu YL, Rao PF, Ni L. Potential mechanisms underlying the ameliorative effect of Lactobacillus paracasei FZU103 on the lipid metabolism in hyperlipidemic mice fed a high-fat diet. Food Res Int 2021; 139:109956. [DOI: 10.1016/j.foodres.2020.109956] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 11/26/2020] [Accepted: 11/27/2020] [Indexed: 12/12/2022]
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15
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Guo WL, Guo JB, Liu BY, Lu JQ, Chen M, Liu B, Bai WD, Rao PF, Ni L, Lv XC. Ganoderic acid A from Ganoderma lucidum ameliorates lipid metabolism and alters gut microbiota composition in hyperlipidemic mice fed a high-fat diet. Food Funct 2020; 11:6818-6833. [PMID: 32686808 DOI: 10.1039/d0fo00436g] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Ganoderic acid A (GA) is one of the most abundant triterpenoids in Ganoderma lucidum, and has been proved to possess a wide range of beneficial health effects. The aim of the current study is to investigate the amelioration effects and mechanism of GA on improving hyperlipidemia in mice fed a high-fat diet (HFD). The results showed that GA intervention significantly inhibited the abnormal growth of body weight and epididymal white adipose tissue (eWAT), prevented the hypertrophy of epididymal adipocytes, and ameliorated the biochemical parameters of serum and liver related to lipid metabolism in HFD-fed mice. Histological analysis also showed that the excessive accumulation of lipid droplets in the liver induced by HFD-feeding was greatly alleviated by GA intervention. In addition, GA intervention also increased the level of short chain fatty acids (SCFAs) in the intestine and promoted the excretion of bile acids (BAs) through feces. High-throughput sequencing of bacterial full-length 16S rDNA revealed that daily supplementation with GA made significant structural changes in the gut microbial population of mice fed with HFD, in particular modulating the relative abundance of some function related microbial phylotypes. The relationships between lipid metabolic parameters and gut microbial phylotypes were also revealed by correlation analysis based on a heatmap and network. The result showed that 46 key gut microbial phylotypes (OTUs) were markedly correlated with at least one lipid metabolic parameter. Moreover, UPLC-QTOF/MS-based liver metabolomics showed that 111 biomarkers (47 up-regulated metabolites and 64 down-regulated metabolites) were significantly changed after high-dose GA intervention (75 mg kg-1 day-1), compared with the HFD-fed hyperlipidemic mice. Metabolic pathway enrichment analysis of the differential hepatic metabolites demonstrated that GA intervention had significant regulatory effects on primary bile acid biosynthesis, fatty acid biosynthesis, amino sugar and nucleotide sugar metabolism, inositol phosphate metabolism, and so on. In addition, GA intervention regulated the mRNA levels of hepatic genes involved in fatty acid metabolism and bile acid homeostasis. These findings present new evidence supporting that GA from G. lucidum has the potential to alleviate lipid metabolic disorders and ameliorate the imbalance of gut microflora in a positive way.
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Affiliation(s)
- Wei-Ling Guo
- Institute of Food Science and Technology, College of Biological Science and Technology, Fuzhou University, Fuzhou, Fujian 350108, P. R. China.
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16
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So SSY, Yeung CHC, Schooling CM, El-Nezami H. Targeting bile acid metabolism in obesity reduction: A systematic review and meta-analysis. Obes Rev 2020; 21:e13017. [PMID: 32187830 DOI: 10.1111/obr.13017] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Revised: 02/16/2020] [Accepted: 02/20/2020] [Indexed: 02/06/2023]
Abstract
A systematic review and meta-analysis was conducted of studies that address the association of bile acid (BA) with obesity and of studies on the effects of treatment in patients with obesity on BA metabolism, assessed from systemic BA, fibroblast growth factor 19 (FGF19), 7α-hydroxy-4-cholesten-3-one (C4) level, and faecal BA. We searched PubMed, Embase, and the Cochrane Library from inception to 1 August 2019 using the keywords obesity, obese, body mass index, and overweight with bile acid, FGF19, FXR, and TGR5. Two reviewers independently searched, selected, and assessed the quality of studies. Data were analysed using either fixed or random effect models with inverse variance weighting. Of 3771 articles, 33 papers were relevant for the association of BA with obesity of which 22 were included in the meta-analysis, and 50 papers were relevant for the effect of obesity interventions on BA of which 20 were included in the meta-analysis. Circulating fasting total BA was not associated with obesity. FGF19 was inversely and faecal BA excretion was positively associated with obesity. Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) modulated BA metabolism, ie, increased BA and FGF19. Our results indicate that BA metabolism is altered in obesity. Certain bariatric surgeries including RYGB and SG modulate BA, whether these underlie the beneficial effect of the treatment should be investigated.
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Affiliation(s)
- Stephanie Sik Yu So
- School of Biological Sciences, Faculty of Science, Kadoorie Biological Sciences Building, The University of Hong Kong, Pokfulam, Hong Kong
| | - Chris Ho Ching Yeung
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong
| | - C Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong.,Graduate School of Public Health and Health Policy, City University of New York, New York, United States
| | - Hani El-Nezami
- School of Biological Sciences, Faculty of Science, Kadoorie Biological Sciences Building, The University of Hong Kong, Pokfulam, Hong Kong.,Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
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17
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Xu S, Chen Y, Ma Y, Liu T, Zhao M, Wang Z, Zhao L. Lipidomic Profiling Reveals Disruption of Lipid Metabolism in Valproic Acid-Induced Hepatotoxicity. Front Pharmacol 2019; 10:819. [PMID: 31379584 PMCID: PMC6659130 DOI: 10.3389/fphar.2019.00819] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 06/24/2019] [Indexed: 12/13/2022] Open
Abstract
Valproic acid (VPA) is one of the most widely prescribed antiepileptic drugs, as VPA-induced hepatotoxicity is one of the most severe adverse reaction that can lead to death. The objective of this study was to gain an understanding of dysregulated lipid metabolism in mechanism of hepatotoxicity. Nontargeted lipidomics analysis with liquid chromatography-quadrupole-time-of-flight mass spectrometry (LC-Q-TOF/MS) was performed to explore differential lipids from the patient serum and L02 cells. Lipidomics data interpretation was augmented by gene expression analyses for the key enzymes in lipid metabolism pathways. From patient serum lipidomics, pronouncedly changed lipid species between abnormal liver function (ALF) patients and normal liver function (NLF) patients were identified. Among these lipid species, LPCs, Cers, and SMs were markedly reduced in the ALF group and showed negative relationships with liver injury severity [alanine aminotransferase (ALT) levels], while significantly increased triacylglycerols (TAG) with higher summed carbon numbers demonstrated a positive relationship with ALT levels. Regarding lipidomics in hepatic L02 cells, TAG was markedly elevated after VPA exposure, especially in TAGs with more than 53 summed carbons. Besides, gene expression analysis revealed dysregulated lipid metabolism in VPA-treated L02 cells. Peroxime proliferators-activated receptor (PPARγ) pathway played an important role in VPA-induced lipid disruption through inducing long-chain fatty acid uptake and TAG synthesis, which was also regulated by Akt pathway. Our findings present that VPA-induced lipid metabolism disruption might lead to lipotoxicity in the liver. This approach is expected to be applicable for other drug-induced toxicity assessments.
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Affiliation(s)
- Shansen Xu
- Department of Pharmacy, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yanan Chen
- Department of Pharmacy, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yiyi Ma
- Department of Pharmacy, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ting Liu
- Shanghai AB Sciex Analytical Instrument Trading Co. Ltd., Shanghai, China
| | - Mingming Zhao
- Department of Pharmacy, Shengjing Hospital of China Medical University, Shenyang, China
| | - Zhanyou Wang
- Institute of Health Sciences, Key Laboratory of Medical Cell Biology of Ministry of Education, China Medical University, Shenyang, China
| | - Limei Zhao
- Department of Pharmacy, Shengjing Hospital of China Medical University, Shenyang, China
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18
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Li Y, Zheng X, Liang D, Zhao A, Jia W, Chen T. MCEE 2.0: more options and enhanced performance. Anal Bioanal Chem 2019; 411:5089-5098. [DOI: 10.1007/s00216-019-01874-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2019] [Revised: 03/24/2019] [Accepted: 04/16/2019] [Indexed: 12/14/2022]
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19
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Skill NJ, Elliott CM, Ceballos B, Saxena R, Pepin R, Bettcher L, Ellensberg M, Raftery D, Malucio MA, Ekser B, Mangus RS, Kubal CA. Metabolomic Characterization of Human Model of Liver Rejection Identifies Aberrancies Linked to Cyclooxygenase (COX) and Nitric Oxide Synthase (NOS). Ann Transplant 2019; 24:341-349. [PMID: 31182705 PMCID: PMC6582681 DOI: 10.12659/aot.913800] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Acute liver rejection (ALR), a significant complication of liver transplantation, burdens patients, healthcare payers, and the healthcare providers due to an increase in morbidity, cost, and resources. Despite clinical resolution, ALR is associated with an increased risk of graft loss. A unique protocol of delayed immunosuppression used in our institute provided a model to characterize metabolomic profiles in human ALR. MATERIAL AND METHODS Twenty liver allograft biopsies obtained 48 hours after liver transplantation in the absence of immunosuppression were studied. Hepatic metabolites were quantitated in these biopsies by liquid chromatography and mass spectroscopy (LC/MS). Metabolite profiles were compared among: 1) biopsies with reperfusion injury but no histological evidence of rejection (n=7), 2) biopsies with histological evidence of moderate or severe rejection (n=5), and 3) biopsies with histological evidence of mild rejection (n=8). RESULTS There were 133 metabolites consistently detected by LC/MS and these were prioritized using variable importance to projection (VIP) analysis, comparing moderate or severe rejection vs. no rejection or mild rejection using partial least squares discriminant statistical analysis (PLS-DA). Twenty metabolites were identified as progressively different. Further PLS-DA using these metabolites identified 3 metabolites (linoleic acid, γ-linolenic acid, and citrulline) which are associated with either cyclooxygenase or nitric oxide synthase functionality. CONCLUSIONS Hepatic metabolic aberrancies associated with cyclooxygenase and nitric oxide synthase function occur contemporaneous with ALR. Additional studies are required to better characterize the role of these metabolic pathways to enhance utility of the metabolomics approach in diagnosis and outcomes of ALR.
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Affiliation(s)
- Nicholas J Skill
- Department of Surgery, Indiana University Medical School, Indianapolis, IN, USA
| | - Campbell M Elliott
- Department of Surgery, Indiana University Medical School, Indianapolis, IN, USA
| | - Brian Ceballos
- Department of Surgery, Indiana University Medical School, Indianapolis, IN, USA
| | - Romil Saxena
- Department of Pathology, Indiana University Medical School, Indianapolis, IN, USA
| | - Robert Pepin
- Department of Anesthesiology and Pain Medicine, Northwest Metabolomics Research Center, University of Washington, Seattle, WA, USA
| | - Lisa Bettcher
- Department of Anesthesiology and Pain Medicine, Northwest Metabolomics Research Center, University of Washington, Seattle, WA, USA
| | - Matthew Ellensberg
- Department of Anesthesiology and Pain Medicine, Northwest Metabolomics Research Center, University of Washington, Seattle, WA, USA
| | - Daniel Raftery
- Department of Anesthesiology and Pain Medicine, Northwest Metabolomics Research Center, University of Washington, Seattle, WA, USA
| | - Mary A Malucio
- Department of Surgery, Indiana University Medical School, Indianapolis, IN, USA
| | - Burcin Ekser
- Department of Surgery, Indiana University Medical School, Indianapolis, IN, USA
| | - Richard S Mangus
- Department of Surgery, Indiana University Medical School, Indianapolis, IN, USA
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20
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Effects of glaucocalyxin A on human liver cancer cells as revealed by GC/MS- and LC/MS-based metabolic profiling. Anal Bioanal Chem 2018; 410:3325-3335. [DOI: 10.1007/s00216-018-0996-8] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Revised: 02/17/2018] [Accepted: 03/05/2018] [Indexed: 11/26/2022]
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21
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Wei R, Wang J, Jia E, Chen T, Ni Y, Jia W. GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies. PLoS Comput Biol 2018; 14:e1005973. [PMID: 29385130 PMCID: PMC5809088 DOI: 10.1371/journal.pcbi.1005973] [Citation(s) in RCA: 78] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Revised: 02/12/2018] [Accepted: 01/12/2018] [Indexed: 01/12/2023] Open
Abstract
Left-censored missing values commonly exist in targeted metabolomics datasets and can be considered as missing not at random (MNAR). Improper data processing procedures for missing values will cause adverse impacts on subsequent statistical analyses. However, few imputation methods have been developed and applied to the situation of MNAR in the field of metabolomics. Thus, a practical left-censored missing value imputation method is urgently needed. We developed an iterative Gibbs sampler based left-censored missing value imputation approach (GSimp). We compared GSimp with other three imputation methods on two real-world targeted metabolomics datasets and one simulation dataset using our imputation evaluation pipeline. The results show that GSimp outperforms other imputation methods in terms of imputation accuracy, observation distribution, univariate and multivariate analyses, and statistical sensitivity. Additionally, a parallel version of GSimp was developed for dealing with large scale metabolomics datasets. The R code for GSimp, evaluation pipeline, tutorial, real-world and simulated targeted metabolomics datasets are available at: https://github.com/WandeRum/GSimp. Missing values caused by the limit of detection/quantification (LOD/LOQ) were widely observed in mass spectrometry (MS)-based targeted metabolomics studies and could be recognized as missing not at random (MNAR). MNAR leads to biased parameter estimations and jeopardizes following statistical analyses in different aspects, such as distorting sample distribution, impairing statistical power, etc. Although a wide range of missing value imputation methods was developed for–omics studies, a limited number of methods was designed appropriately for the situation of MNAR currently. To alleviate problems caused by MNAR and to facilitate targeted metabolomics studies, we developed a Gibbs sampler based missing value imputation approach, called GSimp, which is public-accessible on GitHub. And we compared our method with existing approaches using an imputation evaluation pipeline on both of the real-world and simulated metabolomics datasets to demonstrate the superiority of our method from different perspectives.
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Affiliation(s)
- Runmin Wei
- Metabolomics Shared Resource, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America
- Department of Molecular Biosciences and Bioengineering, University of Hawaii at Manoa, Honolulu, Hawaii, United States of America
| | - Jingye Wang
- Metabolomics Shared Resource, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America
- * E-mail:
| | - Erik Jia
- High School, Punahou School, Honolulu, Hawaii, United States of America
| | - Tianlu Chen
- Shanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China
| | - Yan Ni
- Metabolomics Shared Resource, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America
| | - Wei Jia
- Metabolomics Shared Resource, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America
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22
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Wei R, Wang J, Su M, Jia E, Chen S, Chen T, Ni Y. Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data. Sci Rep 2018; 8:663. [PMID: 29330539 PMCID: PMC5766532 DOI: 10.1038/s41598-017-19120-0] [Citation(s) in RCA: 311] [Impact Index Per Article: 51.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Accepted: 12/20/2017] [Indexed: 12/28/2022] Open
Abstract
Missing values exist widely in mass-spectrometry (MS) based metabolomics data. Various methods have been applied for handling missing values, but the selection can significantly affect following data analyses. Typically, there are three types of missing values, missing not at random (MNAR), missing at random (MAR), and missing completely at random (MCAR). Our study comprehensively compared eight imputation methods (zero, half minimum (HM), mean, median, random forest (RF), singular value decomposition (SVD), k-nearest neighbors (kNN), and quantile regression imputation of left-censored data (QRILC)) for different types of missing values using four metabolomics datasets. Normalized root mean squared error (NRMSE) and NRMSE-based sum of ranks (SOR) were applied to evaluate imputation accuracy. Principal component analysis (PCA)/partial least squares (PLS)-Procrustes analysis were used to evaluate the overall sample distribution. Student's t-test followed by correlation analysis was conducted to evaluate the effects on univariate statistics. Our findings demonstrated that RF performed the best for MCAR/MAR and QRILC was the favored one for left-censored MNAR. Finally, we proposed a comprehensive strategy and developed a public-accessible web-tool for the application of missing value imputation in metabolomics ( https://metabolomics.cc.hawaii.edu/software/MetImp/ ).
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Affiliation(s)
- Runmin Wei
- University of Hawaii Cancer Center, Honolulu, HI, 96813, USA.,Department of Molecular Biosciences and Bioengineering, University of Hawaii at Manoa, Honolulu, HI, 96822, USA
| | - Jingye Wang
- University of Hawaii Cancer Center, Honolulu, HI, 96813, USA
| | - Mingming Su
- University of Hawaii Cancer Center, Honolulu, HI, 96813, USA.,Metabo-Profile Biotechnology (Shanghai) Co., Ltd, Shanghai, 201203, P. R. China
| | - Erik Jia
- Punahou School, Honolulu, HI, 96822, USA
| | - Shaoqiu Chen
- University of Hawaii Cancer Center, Honolulu, HI, 96813, USA.,Department of Molecular Biosciences and Bioengineering, University of Hawaii at Manoa, Honolulu, HI, 96822, USA
| | - Tianlu Chen
- Shanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200233, China
| | - Yan Ni
- University of Hawaii Cancer Center, Honolulu, HI, 96813, USA.
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23
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Wei R, Wang J, Su M, Jia E, Chen S, Chen T, Ni Y. Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data. Sci Rep 2018. [PMID: 29330539 DOI: 10.1038/s41598-017-19120-19120] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/28/2023] Open
Abstract
Missing values exist widely in mass-spectrometry (MS) based metabolomics data. Various methods have been applied for handling missing values, but the selection can significantly affect following data analyses. Typically, there are three types of missing values, missing not at random (MNAR), missing at random (MAR), and missing completely at random (MCAR). Our study comprehensively compared eight imputation methods (zero, half minimum (HM), mean, median, random forest (RF), singular value decomposition (SVD), k-nearest neighbors (kNN), and quantile regression imputation of left-censored data (QRILC)) for different types of missing values using four metabolomics datasets. Normalized root mean squared error (NRMSE) and NRMSE-based sum of ranks (SOR) were applied to evaluate imputation accuracy. Principal component analysis (PCA)/partial least squares (PLS)-Procrustes analysis were used to evaluate the overall sample distribution. Student's t-test followed by correlation analysis was conducted to evaluate the effects on univariate statistics. Our findings demonstrated that RF performed the best for MCAR/MAR and QRILC was the favored one for left-censored MNAR. Finally, we proposed a comprehensive strategy and developed a public-accessible web-tool for the application of missing value imputation in metabolomics ( https://metabolomics.cc.hawaii.edu/software/MetImp/ ).
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Affiliation(s)
- Runmin Wei
- University of Hawaii Cancer Center, Honolulu, HI, 96813, USA
- Department of Molecular Biosciences and Bioengineering, University of Hawaii at Manoa, Honolulu, HI, 96822, USA
| | - Jingye Wang
- University of Hawaii Cancer Center, Honolulu, HI, 96813, USA
| | - Mingming Su
- University of Hawaii Cancer Center, Honolulu, HI, 96813, USA
- Metabo-Profile Biotechnology (Shanghai) Co., Ltd, Shanghai, 201203, P. R. China
| | - Erik Jia
- Punahou School, Honolulu, HI, 96822, USA
| | - Shaoqiu Chen
- University of Hawaii Cancer Center, Honolulu, HI, 96813, USA
- Department of Molecular Biosciences and Bioengineering, University of Hawaii at Manoa, Honolulu, HI, 96822, USA
| | - Tianlu Chen
- Shanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200233, China
| | - Yan Ni
- University of Hawaii Cancer Center, Honolulu, HI, 96813, USA.
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