1
|
Georgiopoulos G, Athanasopoulos S, Mavraganis G, Konstantaki C, Papaioannou M, Delialis D, Angelidakis L, Sachse M, Papoutsis D, Cavlan B, Tual-Chalot S, Zervas G, Sopova K, Mitrakou A, Stellos K, Stamatelopoulos K. Incremental Value of Blood-Based Markers of Liver Fibrosis in Cardiovascular Risk Stratification. J Clin Endocrinol Metab 2025; 110:1115-1127. [PMID: 39257198 PMCID: PMC11913098 DOI: 10.1210/clinem/dgae619] [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: 06/08/2024] [Revised: 08/23/2024] [Accepted: 09/10/2024] [Indexed: 09/12/2024]
Abstract
CONTEXT Nonalcoholic fatty liver disease (NAFLD) with advanced liver fibrosis is associated with cardiovascular disease (CVD). OBJECTIVE This work aimed to examine if markers of vascular injury mediate the link between liver fibrosis noninvasive tests (LFNITs) and CVD events, and to compare the incremental predictive value of LFNITs over established CVD risk scores. METHODS Consecutively recruited individuals (n = 1692) with or without clinically overt coronary artery disease (CAD) from the Athens Cardiometabolic Cohort, were analyzed. Fibrosis-4 index (FIB-4), NAFLD Fibrosis score (NFS), and BARD score were evaluated for direct and indirect associations with indices of subclinical arterial injury including carotid maximal wall thickness (maxWT) and pulse wave velocity (PWV) and with a composite of major adverse cardiovascular events (MACE) that consisted of cardiac death, acute myocardial infarction, or coronary revascularization (39-month median follow-up). RESULTS FIB-4 was the only LFNIT that was consistently associated with multiple markers of vascular injury, irrespective of CAD presence and after controlling for traditional risk factors, surrogates of insulin resistance, or obesity (adjusted P < .05 for all). FIB-4 was also independently associated with CAD presence (adjusted odds ratio [OR] 6.55; 3.48-12.3; P < .001). Increased FIB-4 greater than 2.67 was incrementally associated with an increased risk for MACE (OR [95% CI] 2.00 [1.12-3.55], ΔAUC [95% CI] 0.014 [0.002-0.026]). These associations were mediated by maxWT rather than PWV. Only FIB-4 (>3.25) was independently and incrementally associated with all-cause mortality (adjusted P < 0.05). CONCLUSION In a cardiometabolically diverse population, the incremental associations of LFNITs with CVD outcomes were mediated by atherosclerotic burden rather than arterial stiffening. FIB-4 consistently demonstrated associations with all study end points. These findings provide mechanistic insights and support the clinical applicability of FIB-4 in CVD prevention.
Collapse
Affiliation(s)
- Georgios Georgiopoulos
- Department of Clinical Therapeutics, Alexandra Hospital, National and Kapodistrian University of Athens Medical School, 11528 Athens, Greece
| | - Stavros Athanasopoulos
- Department of Clinical Therapeutics, Alexandra Hospital, National and Kapodistrian University of Athens Medical School, 11528 Athens, Greece
| | - Georgios Mavraganis
- Department of Clinical Therapeutics, Alexandra Hospital, National and Kapodistrian University of Athens Medical School, 11528 Athens, Greece
| | - Christina Konstantaki
- Department of Clinical Therapeutics, Alexandra Hospital, National and Kapodistrian University of Athens Medical School, 11528 Athens, Greece
| | - Maria Papaioannou
- Department of Clinical Therapeutics, Alexandra Hospital, National and Kapodistrian University of Athens Medical School, 11528 Athens, Greece
| | - Dimitrios Delialis
- Department of Clinical Therapeutics, Alexandra Hospital, National and Kapodistrian University of Athens Medical School, 11528 Athens, Greece
| | - Lasthenis Angelidakis
- Department of Clinical Therapeutics, Alexandra Hospital, National and Kapodistrian University of Athens Medical School, 11528 Athens, Greece
| | - Marco Sachse
- Department of Cardiovascular Research, European Center for Angioscience, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany
| | - Dimitrios Papoutsis
- Department of Clinical Therapeutics, Alexandra Hospital, National and Kapodistrian University of Athens Medical School, 11528 Athens, Greece
| | - Beyza Cavlan
- Department of Cardiovascular Research, European Center for Angioscience, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany
| | - Simon Tual-Chalot
- Biosciences Institute, Vascular Biology and Medicine Theme, Faculty of Medical Sciences, Newcastle University, NE1 7RU Newcastle Upon Tyne, UK
| | - Georgios Zervas
- Department of Clinical Therapeutics, Alexandra Hospital, National and Kapodistrian University of Athens Medical School, 11528 Athens, Greece
| | - Kateryna Sopova
- Department of Cardiovascular Research, European Center for Angioscience, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany
- Department of Cardiology, University Hospital Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Heidelberg/Mannheim, 68167 Mannheim, Germany
| | - Asimina Mitrakou
- Department of Clinical Therapeutics, Alexandra Hospital, National and Kapodistrian University of Athens Medical School, 11528 Athens, Greece
| | - Konstantinos Stellos
- Department of Cardiovascular Research, European Center for Angioscience, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany
- Biosciences Institute, Vascular Biology and Medicine Theme, Faculty of Medical Sciences, Newcastle University, NE1 7RU Newcastle Upon Tyne, UK
- Department of Cardiology, University Hospital Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Heidelberg/Mannheim, 68167 Mannheim, Germany
| | - Kimon Stamatelopoulos
- Department of Clinical Therapeutics, Alexandra Hospital, National and Kapodistrian University of Athens Medical School, 11528 Athens, Greece
- Translational and Clinical Research Institute, Vascular Biology and Medicine Theme, Faculty of Medical Sciences, Newcastle University, NE1 7RU Newcastle Upon Tyne, UK
| |
Collapse
|
2
|
Foster C, Gagnon CA, Ashraf AP. Altered lipid metabolism and the development of metabolic-associated fatty liver disease. Curr Opin Lipidol 2024; 35:200-207. [PMID: 38484227 DOI: 10.1097/mol.0000000000000933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
PURPOSE OF REVIEW An increasing amount of research has underscored the significant role of lipoproteins in the pathogenesis of metabolic-associated fatty liver disease (MAFLD). This comprehensive review examines the intricate relationship between lipoprotein abnormalities and the development of MAFLD. RECENT FINDINGS Atherogenic dyslipidemia seen in insulin resistance states play a significant role in initiating and exacerbating hepatic lipid accumulation. There are also specific genetic factors ( PNPLA3 , TM6SF2 , MBOAT7 , HSD17B13 , GCKR- P446L) and transcription factors (SREBP-2, FXR, and LXR9) that increase susceptibility to both lipoprotein disorders and MAFLD. Most monogenic primary lipid disorders do not cause hepatic steatosis unless accompanied by metabolic stress. Hepatic steatosis occurs in the presence of secondary systemic metabolic stress in conjunction with predisposing environmental factors that lead to insulin resistance. Identifying specific aberrant lipoprotein metabolic factors promoting hepatic fat accumulation and subsequently exacerbating steatohepatitis will shed light on potential targets for therapeutic interventions. SUMMARY The clinical implications of interconnection between genetic factors and an insulin resistant environment that predisposes MAFLD is many fold. Potential therapeutic strategies in preventing or mitigating MAFLD progression include lifestyle modifications, pharmacological interventions, and emerging therapies targeting aberrant lipoprotein metabolism.
Collapse
Affiliation(s)
- Christy Foster
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, University of Alabama at Birmingham
| | - Charles A Gagnon
- University of Alabama at Birmingham Marnix E. Heersink School of Medicine, Birmingham, Alabama, USA
| | - Ambika P Ashraf
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, University of Alabama at Birmingham
| |
Collapse
|
3
|
Soto A, Spongberg C, Martinino A, Giovinazzo F. Exploring the Multifaceted Landscape of MASLD: A Comprehensive Synthesis of Recent Studies, from Pathophysiology to Organoids and Beyond. Biomedicines 2024; 12:397. [PMID: 38397999 PMCID: PMC10886580 DOI: 10.3390/biomedicines12020397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 02/04/2024] [Accepted: 02/05/2024] [Indexed: 02/25/2024] Open
Abstract
Non-alcoholic fatty liver disease (NAFLD) is a widespread contributor to chronic liver disease globally. A recent consensus on renaming liver disease was established, and metabolic dysfunction-associated steatotic liver disease, MASLD, was chosen as the replacement for NAFLD. The disease's range extends from the less severe MASLD, previously known as non-alcoholic fatty liver (NAFL), to the more intense metabolic dysfunction-associated steatohepatitis (MASH), previously known as non-alcoholic steatohepatitis (NASH), characterized by inflammation and apoptosis. This research project endeavors to comprehensively synthesize the most recent studies on MASLD, encompassing a wide spectrum of topics such as pathophysiology, risk factors, dietary influences, lifestyle management, genetics, epigenetics, therapeutic approaches, and the prospective trajectory of MASLD, particularly exploring its connection with organoids.
Collapse
Affiliation(s)
- Allison Soto
- Department of Surgery, University of Illinois College of Medicine, Chicago, IL 60607, USA;
| | - Colby Spongberg
- Touro College of Osteopathic Medicine, Great Falls, MT 59405, USA
| | | | - Francesco Giovinazzo
- General Surgery and Liver Transplant Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy
| |
Collapse
|
4
|
Han S, Wu X, Zhu L, Lu H, Ling X, Luo Y, Hu Z, Zhou Y, Tang Y, Luo F. Whole grain germinated brown rice intake modulates the gut microbiota and alleviates hypertriglyceridemia and hypercholesterolemia in high fat diet-fed mice. Food Funct 2024; 15:265-283. [PMID: 38059679 DOI: 10.1039/d3fo03288d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/08/2023]
Abstract
Hyperlipidemia is a common clinical disorder of lipid metabolism in modern society and is considered to be one of the major risk factors leading to cardiovascular-related diseases. Germinated brown rice (GBR) is a typical whole grain food. The lipid-lowering effect of GBR has received increasing attention, but its mechanism of action is not fully understood. The gut microbiota has been proposed as a novel target for the treatment of hyperlipidemia. The aim of this study was to investigate the effects of GBR on the gut microbiota and lipid metabolism in high-fat diet (HFD)-fed C57BL/6J mice. The effect of GBR on hyperlipidemia was evaluated by measuring blood lipid levels and by pathological examination. The gut microbiota was detected by 16S rRNA sequencing, and the protein and mRNA expression levels involved in cholesterol metabolism were detected by western blotting and RT-qPCR to find potential correlations. The results showed that GBR supplementation could effectively reduce the levels of TC, TG, LDL-C and HDL-C in the serum and alleviate the excessive accumulation of fat droplets caused by HFD. Moreover, GBR intervention improved HFD-fed gut microbiota disorder via increasing the diversity of the gut microbiota, reducing the Firmicutes/Bacteroidetes ratio, and improving gut barrier damage. In addition, GBR could inhibit endogenous cholesterol synthesis and promote cholesterol transport and excretion. These findings suggest that GBR may be a competitive candidate for the development of functional foods to prevent abnormal lipid metabolism.
Collapse
Affiliation(s)
- Shuai Han
- Laboratory of Molecular Nutrition, College of Food Science and Engineering, Central South University of Forestry and Technology, 498 Southern Shaoshan Road, Changsha, Hunan 410004, P. R. China.
| | - Xiuxiu Wu
- Laboratory of Molecular Nutrition, College of Food Science and Engineering, Central South University of Forestry and Technology, 498 Southern Shaoshan Road, Changsha, Hunan 410004, P. R. China.
| | - Lingfeng Zhu
- Laboratory of Molecular Nutrition, College of Food Science and Engineering, Central South University of Forestry and Technology, 498 Southern Shaoshan Road, Changsha, Hunan 410004, P. R. China.
| | - Han Lu
- Laboratory of Molecular Nutrition, College of Food Science and Engineering, Central South University of Forestry and Technology, 498 Southern Shaoshan Road, Changsha, Hunan 410004, P. R. China.
| | - Xuke Ling
- Laboratory of Molecular Nutrition, College of Food Science and Engineering, Central South University of Forestry and Technology, 498 Southern Shaoshan Road, Changsha, Hunan 410004, P. R. China.
| | - Yi Luo
- Department of Clinic Medicine, Xiangya School of Medicine, Central South University, Changsha, Hunan, 410008, China
| | - Zuomin Hu
- Laboratory of Molecular Nutrition, College of Food Science and Engineering, Central South University of Forestry and Technology, 498 Southern Shaoshan Road, Changsha, Hunan 410004, P. R. China.
| | - Yaping Zhou
- Laboratory of Molecular Nutrition, College of Food Science and Engineering, Central South University of Forestry and Technology, 498 Southern Shaoshan Road, Changsha, Hunan 410004, P. R. China.
| | - Yiping Tang
- National Engineering Research Center of Rice and Byproduct Deep Processing, 498 South Shaoshan Road, Changsha, Hunan 410004, P. R. China
| | - Feijun Luo
- Laboratory of Molecular Nutrition, College of Food Science and Engineering, Central South University of Forestry and Technology, 498 Southern Shaoshan Road, Changsha, Hunan 410004, P. R. China.
- National Engineering Research Center of Rice and Byproduct Deep Processing, 498 South Shaoshan Road, Changsha, Hunan 410004, P. R. China
| |
Collapse
|
5
|
Deng Y, Ma Y, Fu J, Wang X, Yu C, Lv J, Man S, Wang B, Li L. Combinatorial Use of Machine Learning and Logistic Regression for Predicting Carotid Plaque Risk Among 5.4 Million Adults With Fatty Liver Disease Receiving Health Check-Ups: Population-Based Cross-Sectional Study. JMIR Public Health Surveill 2023; 9:e47095. [PMID: 37676713 PMCID: PMC10514774 DOI: 10.2196/47095] [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: 03/07/2023] [Revised: 04/28/2023] [Accepted: 07/25/2023] [Indexed: 09/08/2023] Open
Abstract
BACKGROUND Carotid plaque can progress into stroke, myocardial infarction, etc, which are major global causes of death. Evidence shows a significant increase in carotid plaque incidence among patients with fatty liver disease. However, unlike the high detection rate of fatty liver disease, screening for carotid plaque in the asymptomatic population is not yet prevalent due to cost-effectiveness reasons, resulting in a large number of patients with undetected carotid plaques, especially among those with fatty liver disease. OBJECTIVE This study aimed to combine the advantages of machine learning (ML) and logistic regression to develop a straightforward prediction model among the population with fatty liver disease to identify individuals at risk of carotid plaque. METHODS Our study included 5,420,640 participants with fatty liver from Meinian Health Care Center. We used random forest, elastic net (EN), and extreme gradient boosting ML algorithms to select important features from potential predictors. Features acknowledged by all 3 models were enrolled in logistic regression analysis to develop a carotid plaque prediction model. Model performance was evaluated based on the area under the receiver operating characteristic curve, calibration curve, Brier score, and decision curve analysis both in a randomly split internal validation data set, and an external validation data set comprising 32,682 participants from MJ Health Check-up Center. Risk cutoff points for carotid plaque were determined based on the Youden index, predicted probability distribution, and prevalence rate of the internal validation data set to classify participants into high-, intermediate-, and low-risk groups. This risk classification was further validated in the external validation data set. RESULTS Among the participants, 26.23% (1,421,970/5,420,640) were diagnosed with carotid plaque in the development data set, and 21.64% (7074/32,682) were diagnosed in the external validation data set. A total of 6 features, including age, systolic blood pressure, low-density lipoprotein cholesterol (LDL-C), total cholesterol, fasting blood glucose, and hepatic steatosis index (HSI) were collectively selected by all 3 ML models out of 27 predictors. After eliminating the issue of collinearity between features, the logistic regression model established with the 5 independent predictors reached an area under the curve of 0.831 in the internal validation data set and 0.801 in the external validation data set, and showed good calibration capability graphically. Its predictive performance was comprehensively competitive compared with the single use of either logistic regression or ML algorithms. Optimal predicted probability cutoff points of 25% and 65% were determined for classifying individuals into low-, intermediate-, and high-risk categories for carotid plaque. CONCLUSIONS The combination of ML and logistic regression yielded a practical carotid plaque prediction model, and was of great public health implications in the early identification and risk assessment of carotid plaque among individuals with fatty liver.
Collapse
Affiliation(s)
- Yuhan Deng
- Chongqing Research Institute of Big Data, Peking University, Chongqing, China
- Meinian Institute of Health, Beijing, China
| | - Yuan Ma
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Jingzhu Fu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Health Science Center Meinian Public Health Institute, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | | | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Health Science Center Meinian Public Health Institute, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Health Science Center Meinian Public Health Institute, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Sailimai Man
- Meinian Institute of Health, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Health Science Center Meinian Public Health Institute, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Bo Wang
- Meinian Institute of Health, Beijing, China
- Peking University Health Science Center Meinian Public Health Institute, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Health Science Center Meinian Public Health Institute, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| |
Collapse
|
6
|
Zhou Y, Duan S, Wang R, Chen J, Yao S. Nonlinear correlation between fatty liver index and carotid intima media thickness among individuals undergoing health examination. Front Endocrinol (Lausanne) 2023; 14:1120581. [PMID: 37056670 PMCID: PMC10086365 DOI: 10.3389/fendo.2023.1120581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Accepted: 03/01/2023] [Indexed: 03/30/2023] Open
Abstract
BACKGROUND Fatty liver index (FLI) is a predictor of non-alcohol fatty liver disease (NAFLD). This study aimed to assess the association between FLI and carotid intima media thickness (CIMT). METHODS In this cross-sectional study, we enrolled 277 individuals for health examination from the China-Japan Friendship Hospital. Blood sampling and ultrasound examinations were conducted. Multivariate logistic regression and restricted cubic spline analyses were performed to evaluate the association between FLI and CIMT. RESULTS Overall, 175 (63.2%) and 105 (37.9%) individuals had NAFLD and CIMT, respectively. The multivariate logistic regression analyses results showed that high FLI was independently associated with a high risk of increased CIMT, T2 vs. T1 (odds ratio [OR], 95% confidence interval [CI]): 2.41, 1.10-5.25, p = 0.027; T3 vs. T1 (OR, 95% CI): 1.58, 0.68-3.64, p = 0.285. The association between FLI and increased CIMT exhibited a J-shaped curve (nonlinear, p = 0.019). In the threshold analysis, the OR for developing increased CIMT was 1.031 (95% CI: 1.011-1.051, p = 0.0023) in participants with FLI < 64.247. CONCLUSION The relationship between FLI and increased CIMT in the health examination population is J-shaped, with an inflection point of 64.247.
Collapse
Affiliation(s)
- Yuanchen Zhou
- Peking University China-Japan Friendship School of Clinical Medicine, Peking University, Beijing, China
- Department of Gastroenterology, China-Japan Friendship Hospital, Beijing, China
| | - Shaojie Duan
- Department of Gastroenterology, China-Japan Friendship Hospital, Beijing, China
- Graduate School of Beijing University of Chinese Medicine, Beijing, China
| | - Rongrui Wang
- Graduate School of Beijing University of Chinese Medicine, Beijing, China
| | - Jialiang Chen
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Shukun Yao
- Peking University China-Japan Friendship School of Clinical Medicine, Peking University, Beijing, China
- Department of Gastroenterology, China-Japan Friendship Hospital, Beijing, China
| |
Collapse
|