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Bertran L, Capellades J, Abelló S, Aguilar C, Auguet T, Richart C. Untargeted lipidomics analysis in women with morbid obesity and type 2 diabetes mellitus: A comprehensive study. PLoS One 2024; 19:e0303569. [PMID: 38743756 PMCID: PMC11093320 DOI: 10.1371/journal.pone.0303569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Accepted: 04/26/2024] [Indexed: 05/16/2024] Open
Abstract
There is a phenotype of obese individuals termed metabolically healthy obese that present a reduced cardiometabolic risk. This phenotype offers a valuable model for investigating the mechanisms connecting obesity and metabolic alterations such as Type 2 Diabetes Mellitus (T2DM). Previously, in an untargeted metabolomics analysis in a cohort of morbidly obese women, we observed a different lipid metabolite pattern between metabolically healthy morbid obese individuals and those with associated T2DM. To validate these findings, we have performed a complementary study of lipidomics. In this study, we assessed a liquid chromatography coupled to a mass spectrometer untargeted lipidomic analysis on serum samples from 209 women, 73 normal-weight women (control group) and 136 morbid obese women. From those, 65 metabolically healthy morbid obese and 71 with associated T2DM. In this work, we find elevated levels of ceramides, sphingomyelins, diacyl and triacylglycerols, fatty acids, and phosphoethanolamines in morbid obese vs normal weight. Conversely, decreased levels of acylcarnitines, bile acids, lyso-phosphatidylcholines, phosphatidylcholines (PC), phosphatidylinositols, and phosphoethanolamine PE (O-38:4) were noted. Furthermore, comparing morbid obese women with T2DM vs metabolically healthy MO, a distinct lipid profile emerged, featuring increased levels of metabolites: deoxycholic acid, diacylglycerol DG (36:2), triacylglycerols, phosphatidylcholines, phosphoethanolamines, phosphatidylinositols, and lyso-phosphatidylinositol LPI (16:0). To conclude, analysing both comparatives, we observed decreased levels of deoxycholic acid, PC (34:3), and PE (O-38:4) in morbid obese women vs normal-weight. Conversely, we found elevated levels of these lipids in morbid obese women with T2DM vs metabolically healthy MO. These profiles of metabolites could be explored for the research as potential markers of metabolic risk of T2DM in morbid obese women.
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Affiliation(s)
- Laia Bertran
- Department of Medicine and Surgery, Study Group on Metabolic Diseases Associated with Insulin-Resistance (GEMMAIR), Rovira i Virgili University, Hospital Universitari de Tarragona Joan XXIII, IISPV, Tarragona, Spain
| | - Jordi Capellades
- Department of Electronic, Electric and Automatic Engineering, Higher Technical School of Engineering, Rovira i Virgili University, IISPV, Tarragona, Spain
| | - Sonia Abelló
- Scientific and Technical Service, Rovira i Virgili University, Tarragona, Spain
| | - Carmen Aguilar
- Department of Medicine and Surgery, Study Group on Metabolic Diseases Associated with Insulin-Resistance (GEMMAIR), Rovira i Virgili University, Hospital Universitari de Tarragona Joan XXIII, IISPV, Tarragona, Spain
| | - Teresa Auguet
- Department of Medicine and Surgery, Study Group on Metabolic Diseases Associated with Insulin-Resistance (GEMMAIR), Rovira i Virgili University, Hospital Universitari de Tarragona Joan XXIII, IISPV, Tarragona, Spain
| | - Cristóbal Richart
- Department of Medicine and Surgery, Study Group on Metabolic Diseases Associated with Insulin-Resistance (GEMMAIR), Rovira i Virgili University, Hospital Universitari de Tarragona Joan XXIII, IISPV, Tarragona, Spain
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Lu S, Wang Q, Lu H, Kuang M, Zhang M, Sheng G, Zou Y, Peng X. Lipids as potential mediators linking body mass index to diabetes: evidence from a mediation analysis based on the NAGALA cohort. BMC Endocr Disord 2024; 24:66. [PMID: 38730299 PMCID: PMC11083816 DOI: 10.1186/s12902-024-01594-5] [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: 03/06/2024] [Accepted: 04/30/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND Body mass index (BMI) and lipid disorders are both known to be strongly associated with the development of diabetes, however, the indirect effect of lipid parameters in the BMI-related diabetes risk is currently unknown. This study aimed to investigate the mediating role of lipid parameters in the association of BMI with diabetes risk. METHODS We assessed the association of diabetes risk with BMI, as well as lipid parameters including high-density lipoprotein cholesterol(HDL-C), low-density lipoprotein cholesterol(LDL-CF and LDL-CS), triglycerides(TG), total cholesterol(TC), remnant cholesterol(RC), non-HDL-C, and combined indices of lipid parameters with HDL-C (RC/HDL-C ratio, TG/HDL-C ratio, TC/HDL-C ratio, non-HDL/HDL-C ratio, LDL/HDL-C ratio) using data from 15,453 subjects in the NAGALA project. Mediation models were used to explore the mediating role of lipid parameters in the association of BMI with diabetes risk, and mediation percentages were calculated for quantifying the strength of the indirect effects. Finally, receiver operating characteristic curve (ROC) analysis was used to compare the accuracy of BMI and BMI combined with lipid parameters in predicting incident diabetes. RESULTS Multivariate regression models, adjusted for confounding factors, demonstrated robust associations of lipid parameters, BMI, with diabetes risk, with the exception of TC, LDL-CF, LDL-CS, and non-HDL-C. Mediation analysis showed that lipid parameters except TC, LDL-CF, LDL-CS, and Non-HDL-C were involved in and mediated the association of BMI with diabetes risk, with the largest mediation percentage being the RC/HDL-C ratio, which was as high as 40%; it is worth mentioning that HDL-C and HDL-C-related lipid ratio parameters also play an important mediating role in the association between BMI and diabetes, with the mediator proportion being greater than 30%. Finally, based on the ROC results, we found that the prediction performance of all lipid parameters in the current study except TC was significantly improved when combined with BMI. CONCLUSION Our fresh findings suggested that lipid parameters partially mediated the association of BMI with diabetes risk; this result indicated that in the context of diabetes risk screening and disease management, it is important to not only monitor BMI but also pay attention to lipid parameters, particularly HDL-C and HDL-C-related lipid ratio parameters.
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Affiliation(s)
- Song Lu
- Department of Cardiology, The First Affiliated Hospital of Nanchang University, Jiangxi Medical College, Nanchang University, Nanchang, 330006, China
| | - Qun Wang
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, 330006, China
| | - Hengcheng Lu
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, 330006, China
| | - Maobin Kuang
- Department of Cardiology, The First Affiliated Hospital of Nanchang University, Jiangxi Medical College, Nanchang University, Nanchang, 330006, China
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, 330006, China
| | - Min Zhang
- Department of Cardiology, The First Affiliated Hospital of Nanchang University, Jiangxi Medical College, Nanchang University, Nanchang, 330006, China
- Jiangxi Hypertension Research Institute, Nanchang, 330006, China
| | - Guotai Sheng
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, 330006, China
| | - Yang Zou
- Jiangxi Cardiovascular Research Institute, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, 330006, China.
| | - Xiaoping Peng
- Department of Cardiology, The First Affiliated Hospital of Nanchang University, Jiangxi Medical College, Nanchang University, Nanchang, 330006, China.
- Jiangxi Hypertension Research Institute, Nanchang, 330006, China.
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Tian CY, Yang QH, Lv HZ, Yue F, Zhou FF. Combined untargeted and targeted lipidomics approaches reveal potential biomarkers in type 2 diabetes mellitus cynomolgus monkeys. J Med Primatol 2024; 53:e12688. [PMID: 38083989 DOI: 10.1111/jmp.12688] [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] [Received: 09/24/2023] [Revised: 11/14/2023] [Accepted: 12/01/2023] [Indexed: 02/13/2024]
Abstract
BACKGROUND The significantly increasing incidence of type 2 diabetes mellitus (T2DM) over the last few decades triggers the demands of T2DM animal models to explore the pathogenesis, prevention, and therapy of the disease. The altered lipid metabolism may play an important role in the pathogenesis and progression of T2DM. However, the characterization of molecular lipid species in fasting serum related to T2DM cynomolgus monkeys is still underrecognized. METHODS Untargeted and targeted LC-mass spectrometry (MS)/MS-based lipidomics approaches were applied to characterize and compare the fasting serum lipidomic profiles of T2DM cynomolgus monkeys and the healthy controls. RESULTS Multivariate analysis revealed that 196 and 64 lipid molecules differentially expressed in serum samples using untargeted and targeted lipidomics as the comparison between the disease group and healthy group, respectively. Furthermore, the comparative analysis of differential serum lipid metabolites obtained by untargeted and targeted lipidomics approaches, four common serum lipid species (phosphatidylcholine [18:0_22:4], lysophosphatidylcholine [14:0], phosphatidylethanolamine [PE] [16:1_18:2], and PE [18:0_22:4]) were identified as potential biomarkers and all of which were found to be downregulated. By analyzing the metabolic pathway, glycerophospholipid metabolism was associated with the pathogenesis of T2DM cynomolgus monkeys. CONCLUSION The study found that four downregulated serum lipid species could serve as novel potential biomarkers of T2DM cynomolgus monkeys. Glycerophospholipid metabolism was filtered out as the potential therapeutic target pathway of T2DM progression. Our results showed that the identified biomarkers may offer a novel tool for tracking disease progression and response to therapeutic interventions.
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Affiliation(s)
- Chao-Yang Tian
- Sanya Research Institute of Hainan University, School of Biomedical Engineering, Hainan University, Sanya, China
- Key Laboratory of Biomedical Engineering of Hainan Province, One Health Institute, Hainan University, Haikou, China
| | | | - Hai-Zhou Lv
- Hainan Jingang Biotech Co., Ltd, Haikou, China
| | - Feng Yue
- Sanya Research Institute of Hainan University, School of Biomedical Engineering, Hainan University, Sanya, China
- Key Laboratory of Biomedical Engineering of Hainan Province, One Health Institute, Hainan University, Haikou, China
| | - Fei-Fan Zhou
- Sanya Research Institute of Hainan University, School of Biomedical Engineering, Hainan University, Sanya, China
- Key Laboratory of Biomedical Engineering of Hainan Province, One Health Institute, Hainan University, Haikou, China
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Yuan L, Verhoeven A, Blomberg N, van Eyk HJ, Bizino MB, Rensen PCN, Jazet IM, Lamb HJ, Rabelink TJ, Giera M, van den Berg BM. Ethnic Disparities in Lipid Metabolism and Clinical Outcomes between Dutch South Asians and Dutch White Caucasians with Type 2 Diabetes Mellitus. Metabolites 2024; 14:33. [PMID: 38248836 PMCID: PMC10819672 DOI: 10.3390/metabo14010033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 12/26/2023] [Accepted: 12/30/2023] [Indexed: 01/23/2024] Open
Abstract
Type 2 diabetes mellitus (T2DM) poses a higher risk for complications in South Asian individuals compared to other ethnic groups. To shed light on potential mediating factors, we investigated lipidomic changes in plasma of Dutch South Asians (DSA) and Dutch white Caucasians (DwC) with and without T2DM and explore their associations with clinical features. Using a targeted quantitative lipidomics platform, monitoring over 1000 lipids across 17 classes, along with 1H NMR based lipoprotein analysis, we studied 51 healthy participants (21 DSA, 30 DwC) and 92 T2DM patients (47 DSA, 45 DwC) from the MAGNetic resonance Assessment of VICTOza efficacy in the Regression of cardiovascular dysfunction in type 2 dIAbetes mellitus (MAGNA VICTORIA) study. This comprehensive mapping of the circulating lipidome allowed us to identify relevant lipid modules through unbiased weighted correlation network analysis, as well as disease and ethnicity related key mediatory lipids. Significant differences in lipidomic profiles, encompassing various lipid classes and species, were observed between T2DM patients and healthy controls in both the DSA and DwC populations. Our analyses revealed that healthy DSA, but not DwC, controls already exhibited a lipid profile prone to develop T2DM. Particularly, in DSA-T2DM patients, specific lipid changes correlated with clinical features, particularly diacylglycerols (DGs), showing significant associations with glycemic control and renal function. Our findings highlight an ethnic distinction in lipid modules influencing clinical outcomes in renal health. We discover distinctive ethnic disparities of the circulating lipidome and identify ethnicity-specific lipid markers. Jointly, our discoveries show great potential as personalized biomarkers for the assessment of glycemic control and renal function in DSA-T2DM individuals.
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Affiliation(s)
- Lushun Yuan
- Einthoven Laboratory for Vascular and Regenerative Medicine, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (L.Y.); (P.C.N.R.); (T.J.R.)
- Department of Internal Medicine, Division of Nephrology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
| | - Aswin Verhoeven
- Center for Proteomics and Metabolomics, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (A.V.); (N.B.); (M.G.)
| | - Niek Blomberg
- Center for Proteomics and Metabolomics, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (A.V.); (N.B.); (M.G.)
| | - Huub J. van Eyk
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (H.J.v.E.); (I.M.J.)
| | - Maurice B. Bizino
- Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (M.B.B.); (H.J.L.)
| | - Patrick C. N. Rensen
- Einthoven Laboratory for Vascular and Regenerative Medicine, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (L.Y.); (P.C.N.R.); (T.J.R.)
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (H.J.v.E.); (I.M.J.)
| | - Ingrid M. Jazet
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (H.J.v.E.); (I.M.J.)
| | - Hildo J. Lamb
- Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (M.B.B.); (H.J.L.)
| | - Ton J. Rabelink
- Einthoven Laboratory for Vascular and Regenerative Medicine, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (L.Y.); (P.C.N.R.); (T.J.R.)
- Department of Internal Medicine, Division of Nephrology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
| | - Martin Giera
- Center for Proteomics and Metabolomics, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (A.V.); (N.B.); (M.G.)
| | - Bernard M. van den Berg
- Einthoven Laboratory for Vascular and Regenerative Medicine, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (L.Y.); (P.C.N.R.); (T.J.R.)
- Department of Internal Medicine, Division of Nephrology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
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Soares NP, Magalhaes GC, Mayrink PH, Verano-Braga T. Omics to Unveil Diabetes Mellitus Pathogenesis and Biomarkers: Focus on Proteomics, Lipidomics, and Metabolomics. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1443:211-220. [PMID: 38409423 DOI: 10.1007/978-3-031-50624-6_11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
Diabetes mellitus (DM) is a chronic metabolic disorder characterized by elevated blood sugar levels, resulting from either body's inability to produce or effectively utilize insulin. There are several types of DM, but the most common are type 1 diabetes (T1D), type 2 diabetes (T2D), and gestational diabetes mellitus (GDM). DM is a complex disease and a global health concern, and the current clinical markers, such as fasting glucose, are helpful in the diagnosis of DM, but are not specific and sensitive, especially when measured on the beginning of the pathogenesis. Therefore, there is a pressing need to discover new early biomarkers that can provide an early diagnosis. Omics is an important field for the discovery of potential new biomarkers, especially proteomics, metabolomics, and lipidomics, where techniques such as liquid chromatography, mass spectrometry, and nuclear magnetic resonance are utilized to identify novel DM biomarkers and their pathways. In this review, we report papers that applied omics in the context of DM to identify new markers and their relationship with this disease, with the aim of elucidating new diagnostic techniques for the main types of DM.
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Affiliation(s)
- Nícia Pedreira Soares
- National Institute of Science and Technology in Nanobiopharmaceutics (INCT-Nanobiofar), Department of Physiology and Biophysics, Federal University of Minas Gerais, Belo Horizonte, Brazil
- Proteomics Group (NPF), Department of Physiology and Biophysics, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Gabriela Castro Magalhaes
- National Institute of Science and Technology in Nanobiopharmaceutics (INCT-Nanobiofar), Department of Physiology and Biophysics, Federal University of Minas Gerais, Belo Horizonte, Brazil
- Proteomics Group (NPF), Department of Physiology and Biophysics, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Pedro Henrique Mayrink
- National Institute of Science and Technology in Nanobiopharmaceutics (INCT-Nanobiofar), Department of Physiology and Biophysics, Federal University of Minas Gerais, Belo Horizonte, Brazil
- Proteomics Group (NPF), Department of Physiology and Biophysics, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Thiago Verano-Braga
- National Institute of Science and Technology in Nanobiopharmaceutics (INCT-Nanobiofar), Department of Physiology and Biophysics, Federal University of Minas Gerais, Belo Horizonte, Brazil.
- Proteomics Group (NPF), Department of Physiology and Biophysics, Federal University of Minas Gerais, Belo Horizonte, Brazil.
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Anderson BJ, Curtis AM, Jen A, Thomson JA, Clegg DO, Jiang P, Coon JJ, Overmyer KA, Toh H. Plasma metabolomics supports non-fasted sampling for metabolic profiling across a spectrum of glucose tolerance in the Nile rat model for type 2 diabetes. Lab Anim (NY) 2023; 52:269-277. [PMID: 37857753 PMCID: PMC10611569 DOI: 10.1038/s41684-023-01268-0] [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] [Received: 01/18/2023] [Accepted: 09/12/2023] [Indexed: 10/21/2023]
Abstract
Type 2 diabetes is a challenge in modern healthcare, and animal models are necessary to identify underlying mechanisms. The Nile rat (Arvicanthis niloticus) develops diet-induced diabetes rapidly on a conventional rodent chow diet without genetic or chemical manipulation. Unlike common laboratory models, the outbred Nile rat model is diurnal and has a wide range of overt diabetes onset and diabetes progression patterns in both sexes, better mimicking the heterogeneous diabetic phenotype in humans. While fasted blood glucose has historically been used to monitor diabetic progression, postprandial blood glucose is more sensitive to the initial stages of diabetes. However, there is a long-held assumption that ad libitum feeding in rodent models leads to increased variance, thus masking diabetes-related metabolic changes in the plasma. Here we compared repeatability within triplicates of non-fasted or fasted plasma samples and assessed metabolic changes relevant to glucose tolerance in fasted and non-fasted plasma of 8-10-week-old male Nile rats. We used liquid chromatography-mass spectrometry lipidomics and polar metabolomics to measure relative metabolite abundances in the plasma samples. We found that, compared to fasted metabolites, non-fasted plasma metabolites are not only more strongly associated with glucose tolerance on the basis of unsupervised clustering and elastic net regression model, but also have a lower replicate variance. Between the two sampling groups, we detected 66 non-fasted metabolites and 32 fasted metabolites that were associated with glucose tolerance using a combined approach with multivariable elastic net and individual metabolite linear models. Further, to test if metabolite replicate variance is affected by age and sex, we measured non-fasted replicate variance in a cohort of mature 30-week-old male and female Nile rats. Our results support using non-fasted plasma metabolomics to study glucose tolerance in Nile rats across the progression of diabetes.
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Affiliation(s)
- Benton J Anderson
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Anne M Curtis
- Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA, USA
- Neuroscience Research Institute, University of California, Santa Barbara, CA, USA
| | - Annie Jen
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - James A Thomson
- Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA, USA
- Neuroscience Research Institute, University of California, Santa Barbara, CA, USA
- Morgridge Institute for Research, Madison, WI, USA
| | - Dennis O Clegg
- Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA, USA
- Neuroscience Research Institute, University of California, Santa Barbara, CA, USA
| | - Peng Jiang
- Department of Biological, Geological and Environmental Sciences, Cleveland State University, Cleveland, OH, USA
- Center for Gene Regulation in Health and Disease, Cleveland State University, Cleveland, OH, USA
- Center for RNA Science and Therapeutics, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Joshua J Coon
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI, USA
- Morgridge Institute for Research, Madison, WI, USA
| | - Katherine A Overmyer
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI, USA.
- Morgridge Institute for Research, Madison, WI, USA.
| | - Huishi Toh
- Neuroscience Research Institute, University of California, Santa Barbara, CA, USA.
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Wu HC, Hsieh YR, Wang W, Chang CW, Chang IW, Chen CL, Chang CC, Chang CH, Kao WY, Huang SY. Potential Hepatic Lipid Markers Associated with Nonalcoholic Steatohepatitis and Fibrosis in Morbid Obesity Patients. J Clin Med 2023; 12:jcm12113730. [PMID: 37297926 DOI: 10.3390/jcm12113730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 05/23/2023] [Accepted: 05/25/2023] [Indexed: 06/12/2023] Open
Abstract
This study investigated differences in lipidomic profile features in nonalcoholic steatohepatitis (NASH) between mild and significant liver fibrosis cases among patients with morbid obesity. Wedge liver biopsy was performed during sleeve gastrectomy and significant liver fibrosis was defined as a fibrosis score ≥ 2. We selected patients with NASH with non/mild fibrosis (stage F0-F1; n = 30) and NASH with significant fibrosis (stage F2-F4; n = 30). The results of the liver tissue lipidomic analysis revealed that the fold changes of triglyceride (TG) (52:6); cholesterol ester (CE) (20:1); phosphatidylcholine (PC) (38:0) and (50:8); phosphatidic acid (PA) (40:4); phosphatidylinositol (PI) (49:4); phosphatidylglycerol (PG) (40:2); and sphingomyelin (SM) (35:0) and (37:0) were significantly lower in patients with NASH with F2-F4 than those with NASH with F0-F1 (p < 0.05). However, the fold changes of PC (42:4) were relatively higher in patients with NASH with stage 2-4 fibrosis (p < 0.05). Moreover, predictive models incorporating serum markers levels, ultrasonographic studies, and levels of specific lipid components [PC (42:4) and PG (40:2)] yielded the highest area under receiver operating curve (0.941), suggesting a potential correlation between NASH fibrosis stages and liver lipid accumulation among specific lipid species subclasses. This study demonstrated that the concentrations of particular lipid species in the liver correlate with NASH fibrosis stages and may indicate hepatic steatosis regression or progression in patients with morbid obesity.
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Affiliation(s)
- Hua-Chien Wu
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan
| | - Yin-Ru Hsieh
- School of Nutrition and Health Sciences, Taipei Medical University, Taipei 110, Taiwan
| | - Weu Wang
- Division of Digestive Surgery, Department of Surgery, Taipei Medical University Hospital, Taipei 110, Taiwan
- Department of Surgery, School of Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan
- TMU Research Center for Digestive Medicine, Taipei Medical University, Taipei 110, Taiwan
- Graduate Institute of Metabolism and Obesity Sciences, Taipei Medical University, Taipei 110, Taiwan
| | - Ching-Wen Chang
- Graduate Institute of Metabolism and Obesity Sciences, Taipei Medical University, Taipei 110, Taiwan
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD 247202, USA
| | - I-Wei Chang
- Department of Pathology, Taipei Medical University Hospital, Taipei 110, Taiwan
- Department of Pathology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan
- Department of Clinical Pathology, Wan Fang Hospital, Taipei Medical University, Taipei 110, Taiwan
- Department of Pathology, Shuang Ho Hospital, Taipei Medical University, Taipei 110, Taiwan
| | - Chi-Long Chen
- Department of Pathology, Taipei Medical University Hospital, Taipei 110, Taiwan
- Department of Pathology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan
| | - Chun-Chao Chang
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan
- TMU Research Center for Digestive Medicine, Taipei Medical University, Taipei 110, Taiwan
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei 110, Taiwan
| | - Chia-Hsuan Chang
- School of Nutrition and Health Sciences, Taipei Medical University, Taipei 110, Taiwan
| | - Wei-Yu Kao
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan
- TMU Research Center for Digestive Medicine, Taipei Medical University, Taipei 110, Taiwan
- Graduate Institute of Metabolism and Obesity Sciences, Taipei Medical University, Taipei 110, Taiwan
- Department of Pathology, Shuang Ho Hospital, Taipei Medical University, Taipei 110, Taiwan
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei 110, Taiwan
- Taipei Cancer Center, Taipei Medical University, Taipei 110, Taiwan
| | - Shih-Yi Huang
- School of Nutrition and Health Sciences, Taipei Medical University, Taipei 110, Taiwan
- TMU Research Center for Digestive Medicine, Taipei Medical University, Taipei 110, Taiwan
- Graduate Institute of Metabolism and Obesity Sciences, Taipei Medical University, Taipei 110, Taiwan
- Nutrition Research Center, Taipei Medical University Hospital, Taipei 110, Taiwan
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Qian L, Qian B, Xu J, Yang J, Wu G, Zhao Y, Liu Q, Yuan Z, Fan Y, Li H. Clinical relevance of serum lipids in the carcinogenesis of oral squamous cell carcinoma. BMC Oral Health 2023; 23:200. [PMID: 37013557 PMCID: PMC10071612 DOI: 10.1186/s12903-023-02859-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 03/06/2023] [Indexed: 04/05/2023] Open
Abstract
BACKGROUND Dyslipidaemia is associated with cancers. However, the specific expression of serum lipids in oral potentially malignant disorders (OPMD) and oral squamous cell carcinoma (OSCC) remains unclear, and it remains unknown whether serum lipids are associated with the development of OPMD and OSCC. This study investigated the serum lipid profiles of OPMD and OSCC patients, and the association of serum lipids with the occurrence of OPMD and OSCC. METHODS A total of 532 patients were recruited from the Affiliated Hospital of Stomatology, Nanjing Medical University. Serum lipid parameters including total cholesterol (TC), triglycerides (TGs), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A (Apo-A), apolipoprotein B (Apo-B), and lipoprotein (a) (Lpa) were analysed, and clinicopathological data were collected for further analysis. Furthermore, a regression model was used to evaluate the relationship between serum lipids and the occurrence of OSCC and OPMD. RESULTS After adjusting for age and sex, no significant differences were observed in serum lipid or body mass index (BMI) between OSCC patients and controls (P > 0.05). HDL-C, Apo-A, and Apo-B levels were lower in OSCC patients than in OPMD patients (P < 0.05); HDL-C and Apo-A levels were higher in OPMD patients than in controls (P < 0.05). Furthermore, female OSCC patients had higher Apo-A and BMI values than males. The HDL-C level was lower in patients under 60 years of age than in elders (P < 0.05); and age was related to a higher risk of developing OSCC. Female patients with OPMD had higher TC, HDL-C, and Apo-A levels than males (P < 0.05); OPMD patients over 60 years of age had higher HDL-C than youngers (P < 0.05), whereas the LDL-C level was lower in elders (P < 0.05). The HDL-C and BMI values of the patients with oral leukoplakia (OLK) with dysplasia were more elevated than those of the oral lichen planus group, and the LDL-C, and Apo-A levels in patients with OLK with dysplasia were decreased (P < 0.05). Sex, high HDL-C and Apo-A values were associated with the development of OPMD. CONCLUSION Serum lipids exhibited certain differences according to the occurrence and development of OSCC; high levels of HDL-C and Apo-A might be markers for predicting OPMD.
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Affiliation(s)
- Ling Qian
- Department of Oral Mucosal Diseases, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing, China
- Jiangsu Province Key Laboratory of Oral Diseases, Nanjing Medical University, Nanjing, China
- Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing, China
| | - Bo Qian
- Department of Cardiothoracic Surgery, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Juanyong Xu
- Department of Oral Mucosal Diseases, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing, China
- Jiangsu Province Key Laboratory of Oral Diseases, Nanjing Medical University, Nanjing, China
- Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing, China
| | - Jingjing Yang
- Department of Oral Mucosal Diseases, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing, China
- Jiangsu Province Key Laboratory of Oral Diseases, Nanjing Medical University, Nanjing, China
- Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing, China
| | - Guoying Wu
- Department of Oral Mucosal Diseases, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing, China
- Jiangsu Province Key Laboratory of Oral Diseases, Nanjing Medical University, Nanjing, China
- Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing, China
| | - Yuping Zhao
- Department of Oral Mucosal Diseases, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing, China
- Jiangsu Province Key Laboratory of Oral Diseases, Nanjing Medical University, Nanjing, China
- Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing, China
| | - Qinglan Liu
- Department of Oral Mucosal Diseases, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing, China
- Jiangsu Province Key Laboratory of Oral Diseases, Nanjing Medical University, Nanjing, China
- Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing, China
| | - Zhiran Yuan
- The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing, China
| | - Yuan Fan
- Department of Oral Mucosal Diseases, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing, China.
- Jiangsu Province Key Laboratory of Oral Diseases, Nanjing Medical University, Nanjing, China.
- Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing, China.
| | - Huaiqi Li
- Jiangsu Province Key Laboratory of Oral Diseases, Nanjing Medical University, Nanjing, China.
- Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing, China.
- Department of Oral and Maxillofacial Surgery, The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing, China.
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