Title: Metabolic Syndrome and Severity of Fibrosis in Nonalcoholic Fatty Liver Disease: An Age-Dependent Risk Profiling Study
AUTHORS: Salvatore Petta1, Mohammed Eslam2, Luca Valenti3, Elisabetta Bugianesi4, Marco Barbara1, Calogero Cammà1, Marianna Porzio3, Chiara Rosso4, Silvia Fargion3, Jacob George2, Antonio Craxì1.
INSTITUTONS: 1 Section of Gastroenterology, Di.Bi.M.I.S., University of Palermo,
Palermo, Italy; 2 Storr Liver Unit, Westmead Millennium Institute and Westmead Hospital, University of Sydney, Australia; 3 Department of Pathophysiology and Transplantation, Università degli Studi, Internal Medicine, Fondazione Ca' Granda IRCCS Ospedale
Maggiore Policlinico, Milano, Italy; 4Division of Gastro-Hepatology, Department of Medical Sciences, San Giovanni Battista Hospital, University of Torino, Torino, Italy;
SHORT TITLE: Metabolic Syndrome and NAFLD.
CORRESPONDING AUTHOR: Salvatore Petta, MD, PhD, Sezione di Gastroenterologia Di.Bi.M.I.S Università di Palermo, Piazza delle Cliniche, 2, 90127 Palermo, Italy. Phone: +39 091 655 2145. Fax +39 091 655 2156. E-mail: salvatore.petta@unipa.it;
petsa@inwind.it
ABBREVIATIONS: MS: metabolic syndrome; IR: insulin resistance; NAFLD: non-alcoholic fatty liver disease.
Word count: 2958
Tables/Figures: 2/2
Competing Interest: None to declare.
Author contributions: S. Petta, M. Eslam, L. Valenti, E. Bugianesi, M. Barbara, C. Cammà, C. Rosso, S. Fargion, J. George, A. Craxì had full control of the study design, data
analysis and interpretation, and preparation of article. All authors were involved in planning the analysis and drafting the article. The final draft article was approved by all the authors.
Grant support. This study was funded by grants from the PRIN 2010-2011 (Prot. N. 2010C4JJWB_001). ME and JG are supported by the Robert W. Storr Bequest to the Sydney Medical Foundation, University of Sydney; a National Health and Medical Research Council of Australia (NHMRC) Program Grant (1053206) and Project grants (APP1107178 and APP1108422). EB is supported by.Horizon2020 under grant agreement no.634413 for the project EPoS
CORRESPONDING AUTHOR: Salvatore Petta, MD, PhD, Sezione di Gastroenterologia ed Epatologia, Di.Bi.M.I.S Università di Palermo, Piazza delle Cliniche, 2, 90127 Palermo, Italy. Phone: +39 091 655 2145. Fax +39 091 655 2156. E-mail: salvatore.petta@unipa.it; petsa@inwind.it
Abstract
Background/Aims: Metabolic syndrome (MS) and its individual components are associated with nonalcoholic fatty liver disease (NAFLD) severity and progression. We sought to evaluate, in NAFLD patients discriminated by age, the effect of all components of the MS and of their combinations on the risk of severe hepatic fibrosis.
Methods: We considered 863 consecutive biopsy-proven NAFLD patients, fully evaluated for components of MS – visceral obesity, IFG/diabetes, HDL, triglycerides and arterial hypertension.
Results: At multivariate logistic regression analysis, severe fibrosis (F3-F4) was associated with visceral obesity (OR 20.5, 95%CI 2.29-235.9, p=0.01), IFG/diabetes (OR 2.66, 95%CI 1.76-4.04, p<0.001), and low HDL cholesterol (<40/<50 mg/dl; OR 1.73, 95%CI 1.17-2.56, p=0.006), but not triglycerides >150 or arterial hypertension. A significant interaction was found between age and visceral obesity (p=0.04). By stratifying patients for age, we confirmed the interaction between third tertile age (>54 years) and visceral obesity
(p=0.04). Consistently, in the lower (<41 years) and middle (41-54 years) age tertiles, the risk for F3-F4 fibrosis was mostly driven by visceral obesity and IFG/diabetes, and was higher in those with all three metabolic risk factors (29% and 36% in lower and middle age tertiles, respectively). Finally, among patients in the higher age tertile (>54 years), obesity did not affect fibrosis severity, and the risk of severe fibrosis was higher in those with low HDL and IFG/Diabetes with/without visceral obesity (from 52% to 54%).
Conclusions: In NAFLD, among all components of MS, IFG/diabetes, low HDL and visceral obesity are the most closely associated with severe fibrosis. Metabolic profiles at risk for severe fibrosis changed according to age, with low HDL, but mostly obesity and
IFG/Diabetes being dominant in patients in lower and middle age tertiles, and HDL and IFG/Diabetes but not visceral obesity in those in the highest age tertile.
Introduction
The metabolic syndrome (MS) is a cluster of metabolic alterations that includes visceral obesity, high blood glucose, arterial hypertension, high triglycerides and low HDL levels, able to predict the occurrence of cardiometabolic events [1]. Nonalcoholic fatty liver disease (NAFLD) can be considered the hepatic counterpart of MS, and consistent with this, it shares with MS and its individual components a common pathogenic trigger, namely insulin resistance (IR) [2].
As expected, NAFLD and MS have a strong bidirectional interplay, with NAFLD being able to increase the risk of occurrence of MS and its components, and these in turn increasing the risk of NAFLD and of its severity.
Growing evidence from cohort studies has reported that the presence of NAFLD at baseline is an independent predictor of the occurrence of diabetes, hypertension, dyslipidaemia and MS [3-5], even if in some studies the association was lost after
adjustment for IR [5]. On the other hand, in both Asiatic and Western large cohort studies, the presence of MS or of diabetes independently predicted the occurrence of fatty liver [6,7]. Consistent with all these data, while the prevalence of NAFLD in the general population is roughly 25%, it dramatically increases to over 50% in patients with MS or with its singular components [8].
When looking at the impact of MS and its components on the severity of fibrosis the strongest predictor of hepatic and extrahepatic prognosis in NAFLD [9,10 ]-, contrasting evidence is available. Several studies, not always taking into account all MS components, has shown that obesity and/or diabetes and/or dyslipidemia are associated with NAFLD severity/progression [12-15], reporting however the impact on fibrosis of metabolic risk factors considered singularly, but not in combination. On the other hand, other studies, evaluating the number but not the kind of metabolic alteration, found that MS - defined as the presence of at least three metabolic alterations- was associated with severe fibrosis
[8], and that the likelihood of a higher amount of liver fibrosis progressively increased according to the number of components of the MS [13]. Consistent with these data,
American guidelines on diagnosis and management of NAFLD suggests that the presence of metabolic syndrome may be used for identifying patients who are at risk for
steatohepatitis and advanced fibrosis [11].
Having this in mind, in a large cohort of biopsy-proven NAFLD patients fully characterized for all features of MS and discriminated by age, we assessed the weight of each
component of the MS and of their combinations on the risk of severe hepatic fibrosis.
Patients and Methods
Patients
We analyzed data from 863 prospectively recruited NAFLD patients. The study cohort included 298 patients from the Gastrointestinal & Liver Unit of the Palermo University Hospital in Italy, 221 patients from the Westmead Millenium Institute, Sydney in Australia, 204 patients from the Metabolic Liver Diseases outpatient service, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, - Italy, and 140 patients from the Gastro-hepatology Division of the University Hospital Torino, Italy. Other causes of liver disease were ruled out, including alcohol intake (>20 g/day) evaluated by a questionnaire, viral and autoimmune hepatitis, hereditary hemochromatosis, and alpha1-antitrypsin deficiency. Patients with advanced cirrhosis, hepatocellular carcinoma, and current use of steatosis inducing drugs were excluded.
The study was carried out in accordance with the principles of the Helsinki Declaration, and with local and national laws. Approval was obtained from the hospital Internal Review Boards and their Ethics Committees, and written informed consent for the study was obtained from all controls and patients.
Clinical and Laboratory Assessment
Clinical and anthropometric data were collected at the time of liver biopsy. Body mass index (BMI) was calculated on the basis of weight in kilograms and height in meters; patients were classified as obese when BMI ≥30. Waist circumference (WC) was measured at the midpoint between the lower border of the rib cage and the iliac crest. Visceral obesity was defined according to ATPIII criteria (WC was >102 cm in males and > 88 cm in females) [16]. A diagnosis of arterial hypertension was based on the following criteria: systolic blood pressure ≥135 mm Hg and/or diastolic blood pressure ≥85 mm Hg (measured three times in 30 minutes, in the sitting position and using a brachial
sphygmomanometer), or use of blood-pressure-lowering agents. A diagnosis of IFG/type 2 diabetes was based on the revised criteria of the American Diabetes Association, using a value of fasting blood glucose ≥100 for IFG and ≥126 mg/dL for diabetes on at least two occasions [17]. In patients with a previous diagnosis of type 2 diabetes, current therapy with insulin or oral hypoglycemic agents was documented. Metabolic syndrome was diagnosed according to ATPIII criteria [16].
Insulin resistance (IR) was determined according to the homeostasis model assessment (HOMA) method [18], as: Insulin resistance (HOMA-IR) = Fasting insulin (μU/mL) x Fasting glucose (mmol/L)/22.5.
Genetic Analyses
DNA was purified using the QIAmp blood Mini Kit (Qiagen, Mainz, Germany) and DNA samples were quantified using spectrophotometric determination. Genotyping for PNPLA3 (rs738409) was carried out using the TaqMan SNP genotyping allelic discrimination
The genotyping call was done with SDS software v.1.3.0 (ABI Prism 7500, Foster City, CA, USA). Genotyping was conducted in a blinded fashion relative to patient characteristics.
Assessment of Histology
Slides were coded and read at each clinical center by one expert pathologist, who was unaware of patients’ identity and history. The inter-observer agreement of pathologists between centers was acceptable [19] and similar to that reported in the literature [20]. A minimum 15mm-length of the biopsy specimen or the presence of at least 10 complete portal tracts was required [21]. Steatosis was assessed as the percentage of hepatocytes containing fat droplets (minimum 5%). The Kleiner classification [20] was used to compute steatosis, ballooning and lobular inflammation, and to stage fibrosis from 0 to 4. NASH was diagnosed in the presence of steatosis >5%, lobular inflammation and ballooning or fibrosis.
Statistical Analysis
Continuous variables were summarized as mean ± standard deviation, and categorical variables as frequency and percentage. Differences of baseline characteristics between age classes were tested for statistical significance by a one-way ANOVA for continuous variables and by a Pearson's chi-squared test for categorical ones. Variables related to all components of MS, together with age, sex, AST/ALT ratio, PLT, and enrolling center were included in a stepwise logistic regression procedure with best Akaike Information Criterion stopping rule to identify a set of factors independently associated with severe fibrosis (F3-F4 fibrosis); statistically significant first-order interactions between remaining variables were then included in the model, and a final check was made to ensure that none of the variables excluded on the first step could significantly improve the final model. Additional
models for F3-F4 fibrosis were performed by including as independent variables also PNPLA3 variant (additive model) or HOMA. Analyses were performed using “r” program.
Results
Patient Features
The baseline features of the entire population of 863 NAFLD patients overall and split according to age tertiles are shown in Table 1.Mean age was 47 years, and 2 patients in three were males. Metabolic syndrome was present in 39% of cases, and 2 patients in three were obese. Diabetes was present in 41% of patients and arterial hypertension in 36%. About 37% and 35% of patients had high triglycerides and low HDL levels,
respectively. Using the Kleiner criteria (39), one patient in five had fibrosis stage ≥ 3.
Effect of metabolic syndrome and its components on F3-F4 fibrosis
The prevalence of F3-F4 fibrosis progressively increased according to the number of metabolic alterations from 1.6% to 41.8% (Figure 1).Severe fibrosis was more prevalent in patients with IFG/diabetes (116/348, 33.3% vs 52/515, 10%; p<0.001), or visceral obesity (141/543, 25.9% vs 27/320, 8.4%; p<0.001), or HDL <40/50 mg/dl (80/301, 26.6% vs 88/562, 15.6%; p<0.001), or triglycerides >150 mg/dl, (75/322, 23.3% vs 93/541, 17.2%; p=0.02) or arterial hypertension (81/309, 26.2% vs 87/554, 15.8%; p<0.001) when compared with their counterparts.
When looking at the independent effect of each component of the MS on severe fibrosis, F3-F4 fibrosis remained significantly associated only with HDL mg/dl <40/50, visceral obesity and IFG/diabetes, together with older age, AST/ALT ratio and PLT values (Table 2
right). Conversely, female gender (OR 0.87, 95%CI 0.57-1.30, p=0.49), triglycerides >150 (OR 1.06, 95%CI 0.70-1.59, p=0.78) and arterial hypertension (OR 1.08, 95%CI 0.71-1.63, p=0.73) were not independently linked to F3-F4 fibrosis. Notably, we found a significant interaction between obesity and age (OR 0.95, 95%CI 0.91-0.99, p=0.04) (Table 2 right). To better explain this interaction, when we included in the model age stratified by tertiles instead of age as a continuous variable, we confirmed the independent link of visceral obesity (OR 3.54, 95%CI 1.35-11.1, p=0.01), IFG/diabetes (OR 2.78, 95%CI 1.83-4.26, p<0.001), and low HDL (OR 1.73, 95%CI 1.16-2.57, p=0.006) with F3-F4 fibrosis, but also observed a significant interaction of visceral obesity with the higher age tertile (OR 0.27, 95%CI 0.07-0.92, p=0.04) (Table 2 left).Consistent with these data, we generated different metabolic risk profiles for F3-F4 fibrosis based on low HDL cholesterol, IFG/diabetes and visceral obesity, stratified by age. Noteworthy, in patients in the lower age tertile (<41 years), the risk of F3-F4 fibrosis was negligible (<10%) in those without any of them or with one, low in those with two (from 11% to 19%) and moderate in those with all three
metabolic risk factors (29%), with a greater weight of obesity and IFG/diabetes compared with HDL in terms of fibrosis risk (Figure 2A). Similarly, in the second age tertile (41-54 years), the risk for F3-F4 fibrosis was low in those without metabolic risk factors or with only one of them (from 3% to 11%), moderate in those with low HDL and visceral obesity or IFG/diabetes (from 13% to 17%), and moderate-high in those with IFG/diabetes and obesity with/without HDL<40/50 (from 25% to 36%) (Figure 2B). Finally, among patients in the higher age tertile (>54 years), we observed that obesity did not impact on the likelihood of F3-F4 fibrosis. The risk of severe fibrosis was moderate in those without metabolic risk factors or with only obesity (from 19% to 21%), moderate-high in those with only
HDL<40/50 or IFG/Diabetes with/without obesity (from 29% to 42%), and very high in those with HDL<40/50 and IFG/Diabetes with/without obesity (from 52% to 55%) (Figure 2C). Bootstrap procedure showed no significant differences between the bootstrapped
coefficient estimates and the model coefficients (estimated model bias range : -0.100 – 0.088, corresponding to a range of bootstrap p-values range of 0.8908 to 0.9754 and 9997, see supplementary table 1); bootstrapped model p-values are substantially similar to the original p-value, the biggest difference being 0.022 , so that all significant variables in the model are also significant in the bootstrapped model. Corrected Somer's D index between predicted probability and observed responses is 0.593, which corresponds to an AUC of 0.797, showing a moderately good predictive performance of the model.
Due to the strong correlation of low HDL cholesterol, IFG/Diabetes and visceral obesity with insulin resistance, we also included in the model HOMA as an independent variable. As expected, we found that HOMA (OR 1.07, 95%CI 1.02-1.13, p=0.006) was independently associated with F3-F4 fibrosis, also confirming the independent association of this with obesity (OR 3.60, 95%CI 1.25-13.0, p=0.02), IFG/diabetes (OR 2.09, 95%CI 1.29-3.42, p=0.003), and low HDL cholesterol (OR 1.55, 95%CI 1.01-2.40, p=0.04), as well as the significant interaction between age >54 years and obesity (OR 0.20, 95%CI 0.04-0.80, p=0.02). However, neither the estimated effects size, nor the significance structure of the parameter was substantially altered. In addition, the predictive performance of the two models was nearly equal (AUC = 0.815 with HOMA vs AUC = 0.804 without, p=0.69).
Finally, in the subgroup of 724 patients with available PNPLA3 genotype, we further confirmed the independent association of F3-F4 fibrosis with visceral obesity (OR 2.80, 95%CI 1.01-9.10, p=0.04), IFG/diabetes (OR 2.46, 95%CI 1.54-3.99, p<0.001) and low HDL (OR 1.67, 95%CI 1.08-2.59, p=0.02), as well as the interaction between age and visceral obesity (OR 0.42, 95%CI 0.10-0.96, p=0.04), but not the association with PNPLA3 genotype (OR 1.52, 95%CI 0.88-2.57, p=0.12).
Discussion
In this study of 863 patients with a histological diagnosis of NAFLD, and characterized for all components of the MS, we found that IFG/diabetes, low HDL and visceral obesity, but not high triglycerides and arterial hypertension, were independent risk factors for severe liver fibrosis. When discriminating patients according to classes of age, the risk for severe fibrosis was driven by low HDL and mostly by IFG/Diabetes and obesity in patients in the lower and middle age tertiles, with the higher risk observed in patients with all three metabolic risk factors. Conversely, IFG/diabetes and low HDL, not visceral obesity, were the main predictors of severe fibrosis in patients in the older age tertile. Notably these results were further confirmed after correction for genetic, biochemical and metabolic-HOMA- risk factors for fibrosis.
Metabolic alterations share similar pathogenic triggers like IR, and as expected in the same individual, different metabolic disturbances can coexist, together contributing to liver damage. MS has been associated with severe fibrosis [8], and the higher the number MS components, the greater the severity of fibrosis [13]. Consistent with these data obesity, diabetes, dyslipidemia and hypertension have also been associated with NAFLD
severity/progression [12-15]. However, these studies took into account the number of metabolic risk factors or the effect of a singular risk factor but not the age-dependent quantitative and qualitative impact of their combinations.
In our study, we confirmed that the prevalence of severe fibrosis increased according to the number of metabolic features. However, a more critical analysis allowed us to confirm the association of only visceral obesity, IFG/diabetes and low HDL cholesterol with the severity of hepatic fibrosis. Notably, this feature was obtained by considering together all the components of the metabolic syndrome and after adjusting for age, gender and
genotype. In this manner we identified the independent weight of each metabolic alteration as a risk factor for severe fibrosis in NAFLD.
The most relevant finding of our study lies in the assessment of the impact of different metabolic profiles on the severity of fibrosis according to classes of age. Notably, we found that among patients in the lower and middle age tertiles, the risk for severe fibrosis was driven by low HDL and mostly by visceral obesity and IFG/diabetes, with the higher risk in patients with all three metabolic alterations. Conversely, among patients in the higher age tertile the risk was mainly driven by both HDL and IFG/Diabetes, with the higher risk in those with this association and without impact of obesity. Noteworthy, internal validation of these results make us confident on their robustness.
The lack of effect of obesity on the severity of fibrosis in older patients is difficult to explain even if some hypotheses can be entertained Obesity is a principal determinant of NAFLD and its progression [22]. However, it should be possible that in older patients the impact of obesity-related metabolic alterations like diabetes and atherogenic dyslipidemia
overcomes obesity per se. In addition, recent evidence assessing the impact of obesity on mortality and cardiovascular outcomes suggests that aging can attenuate the association between high BMI and poor outcomes [23,24]. Besides, the higher weight of low HDL on severe fibrosis in older patients could be the expression of a more severe diabetes and age-related atherogenic dyslipidemia phenotype.
In our study we did not find an independent association between arterial hypertension and severity of fibrosis, while a recent meta-analysis identified hypertension as a risk factor for fast fibrosis progression in NAFLD [25]. Differences in assessed outcomes (fibrosis
severity vs fibrosis progression), and the lack of individual patient data in the meta-analysis, could explain the discrepancies in the results.
The main limitation of this study is the cross-sectional design that makes us unable to definitively ascertain the temporal relationship between metabolic alterations and the
severity of fibrosis in NAFLD. A further methodological question is the potentially limited external validity of the results for different populations and settings. Our study included a cohort of Caucasian patients enrolled at tertiary care centers, who may be different in terms of both metabolic features and severity of liver disease, from the majority of prevalent cases of NAFLD in the general population. In spite of these limits, strengths of this study are internal validation and the large sample size, that allowed us to stratify patients according to metabolic profiles and classes of age.
From a clinical point of view our study suggests that in patients with NAFLD, while all components of MS should be assessed for the evaluation of cardiovascular risk, considering the assessment of liver damage, the presence of IFG/diabetes, visceral obesity and low HDL, considered alone and in combinations allows oneto identify age-dependent metabolic profiles at different risk for severe liver fibrosis. Notably, the ability of prediction by our model did not change when considering also HOMA, an expression of IR, suggesting that the assessment of a not widely available parameter like insulin does not add a significant advantage in the prediction of the risk of fibrosis when added to classical MS components. However, the lack of OGIS ─an expression of peripheral IR and
predicting severe fibrosis better than HOMA [26]─ could affect the interpretation of these results.
In conclusion, this study on a large cohort of patients with a histological diagnosis of NAFLD demonstrated that among all components of MS, IFG/diabetes, low HDL and visceral obesity are those mostly associated with the severity of fibrosis. Notably,
metabolic profiles at risk for severe fibrosis changed according to age, with low HDL and mostly both obesity and IFG/Diabetes being dominant in patients in the lower and middle age tertiles, while low HDL cholesterol and IFG/Diabetes but not visceral obesity in those in the higher age tertile.
Legends
Figure 1. Prevalence of F3-F4 fibrosis according to the number of metabolic alterations in the entire NAFLD cohort.
Figure 2. Prevalence of F3-F4 fibrosis according to the number of metabolic alterations in the NAFLD cohort according to tertiles of age. A. NAFLD patients in the lower quartile of age (<38 years); B. NAFLD patients in the middle quartiles of age (38-57 years); C.
NAFLD patients in the higher quartile of age (>57 years). I am confused different ages cuts to the rest of manuscript and also here it is qquartiles?????
References
[1]. Vanni E, Bugianesi E, Kotronen A, De Minicis S, Yki-Järvinen H, SvegliatiBaroni G. From the metabolic syndrome to NAFLD or vice versa? Dig Liver Dis 2010;42:320–330.
[2]. Marchesini G, Brizi M, Bianchi G, Tomassetti S, Bugianesi E, Lenzi M, et al. Nonalcoholic fatty liver disease: a feature of the metabolic syndrome. Diabetes 2001;50:1844–1850.
[3]. Adams LA, Lymp JF, St Sauver J, Sanderson SO, Lindor KD, Feldstein A, et al. The natural history of nonalcoholic fatty liver disease: a population-based cohort study.
Gastroenterology 2005;129:113–121.
[4]. Goessling W, Massaro JM, Vasan RS, D'Agostino RB Sr, Ellison RC, Fox CS. Aminotransferase levels and 20-year risk of metabolic syndrome, diabetes, and cardiovascular disease. Gastroenterology. 2008 Dec;135(6):1935-44, 1944.e1
[5]. Adams LA, Waters OR, Knuiman MW, Elliott RR, Olynyk JK. NAFLD as a risk factor for the development of diabetes and the metabolic syndrome: an eleven-year follow-up study. Am J Gastroenterol 2009;104:861–867.
[6]. Hamaguchi M, Kojima T, Takeda N, Nakagawa T, Taniguchi H, Fujii K, et al. The metabolic syndrome as a predictor of nonalcoholic fatty liver disease. Ann Intern Med 2005;143:722–728.
[7]. El Serag et al, Gastroenterology 2004
[8]. Marchesini G, Bugianesi E, Forlani G, Cerrelli F, Lenzi M, Manini R, et al. Nonalcoholic fatty liver, steatohepatitis, and the metabolic syndrome. Hepatology 2003;37:917–923.
[9]. Ekstedt M, Hagström H, Nasr P, Fredrikson M, Stål P, Kechagias S, et al. Fibrosis stage is the strongest predictor for disease-specific mortality in NAFLD after up to 33 years of follow-up. Hepatology. 2015 May;61(5):1547-54.
[10]. Angulo P, Kleiner DE, Dam-Larsen S, Adams LA, Bjornsson ES,
Charatcharoenwitthaya P, et al. Liver Fibrosis, but no Other Histologic Features,
Associates with Long-term Outcomes of Patients With Nonalcoholic Fatty Liver Disease. Gastroenterology. 2015 Apr 29. pii: S0016-5085(15)00599-5.
[11]. Chalasani N, Younossi Z, Lavine JE, Diehl AM, Brunt EM, Cusi K, et al. The diagnosis and management of non-alcoholic fatty liver disease: Practice Guideline by the American Association for the Study of Liver Diseases, American College of
Gastroenterology, and the American Gastroenterological Association. Hepatology 2012;55:2005–2023
[12]. Angulo P, Hui JM, Marchesini G, Bugianesi E, George J, Farrell GC, et al. The NAFLD fibrosis score: a noninvasive system that identifies liver fibrosis in patients with NAFLD. Hepatology 2007;45:846–854
[13]. Ryan MC, Wilson AM, Slavin J et al. Associations between liver histology and severity of the metabolic syndrome in subjects with nonalcoholic fatty liver disease. Diabetes Care 2005;28:1222-1224.
[14]. Adams LA, Sanderson S, Lindor KD, Angulo P. The histological course of
nonalcoholic fatty liver disease: a longitudinal study of 103 patients with sequential liver biopsies. J Hepatol. 2005 Jan;42(1):132-8.
[15]. Pais R, Charlotte F, Fedchuk L, Bedossa P, Lebray P, Poynard T, Ratziu V; LIDO Study Group. A systematic review of follow-up biopsies reveals disease progression in patients with non-alcoholic fatty liver. J Hepatol. 2013 Sep;59(3):550-6.
[16]. Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III). JAMA 2001;285:2486–97.
[17]. Standards of Medical Care in Diabetes-2014. Diabetes Care Volume 37, Supplement 1, January 2014, S14-S80.
[18]. Matthews DR, Hosker JP, Rudenski AS, et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin
concentrations in man. Diabetologia 1985;28:412-419.
[19]. Petta S, Valenti L, Marra F, Grimaudo S, Tripodo C, Bugianesi E, et al. MERTK rs4374383 polymorphism affects the severity of fibrosis in non-alcoholic fatty liver disease. J Hepatol 2016;64:682-90.
[20]. Kleiner DE, Brunt EM, Van Natta M, et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 2005;411:313-321.
[21]. Colloredo G, Guido M, Sonzogni A, et al. Impact of liver biopsy size on histological evaluation of chronic viral hepatitis: the smaller the sample, the milder the disease. J Hepatol 2003;39:239-244.
[22]. van der Poorten D, Milner KL, Hui J, Hodge A, Trenell MI, Kench JG, et al. Visceral fat: a key mediator of steatohepatitis in metabolic liver disease. Hepatology. 2008
Aug;48(2):449-57.
[23]. Adams KF, Schatzkin A, Harris TB, Kipnis V, Mouw T, BallardBarbash R, et al. Overweight, obesity, and mortality in a large prospective cohort of persons 50 to 71 years old. N Engl J Med. 2006;355:763–78.
[24]. Lainscak M, von Haehling S, Doehner W, Anker SD. The obesity paradox in chronic disease: facts and numbers. J Cachexia Sarcopenia Muscle. 2012 Mar;3(1):1-4.
[25]. Singh S, Allen AM, Wang Z, Prokop LJ, Murad MH, Loomba R. Fibrosis progression in nonalcoholic fatty liver vs nonalcoholic steatohepatitis: a systematic review and meta-analysis of paired-biopsy studies. Clin Gastroenterol Hepatol 2015;13:643-54.
[26]. Rosso C, Mezzabotta L, Gaggini M, Salomone F, Gambino R, Marengo A, et al. Peripheral insulin resistance predicts liver damage in nondiabetic subjects with
