Clinical features of metabolism-related fatty liver disease in the non-lean population

Clinical features of metabolism-related fatty liver disease in the non-lean population | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinical features of metabolism-related fatty liver disease in the non-lean population Minran Li, Jin-Zhong Li, Cun-chuan Wang, Rui-kun Yuan, Li-hong Ye, and 17 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2009818/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To assess the clinical and histological features of metabolic associated fatty liver disease (MAFLD) in non-lean population. Methods Current study enrolled consecutive non-lean (Body Mass Index (BMI) > 23 kg/m 2 ) patients with MAFLD and available liver biopsy results. Patients were stratified by BMI into two groups for the comparison of their clinical and histological variables, which included the overweight (BMI 23 ~ 1) were also analysed through the logistic regression model. Results Among 184 non-lean patients with MALFD enrolled, 65 and 119 were overweight and obese, respectively. Patients in the obesity group had a significantly lower level of gamma-Glutamyl transpeptidase (GGT), higher levels of platelet (PLT), Glucose (Glu), prothrombin time (PT), and more common of moderate to severe inflammatory activity when compared to those in the overweight group. However, a significant low frequency of moderate to severe fibrosis was found in the obesity group vs the overweight group (19.33% vs 40.00%, P = 0.002). Multivariate logistic regression analysis of fibrosis found that aspartate transaminase (AST), BMI, alanine transaminase (ALT) and cholesterol (CHOL) were independent predictors for moderate to severe fibrosis in non-lean patients with MAFLD. Compared with the traditional FIB-4 (AUC = 0.77) and APRI (AUC = 0.79) indexes, the combined index based on AST, BMI, ALT and CHOL was more accurated in predicting moderate to severe fibrosis in non-lean patients with MAFLD (AUC = 0.87). Conclusions Clinical and histological features differed between obesity and overweight patients with MAFLD. When compared to the traditional serum markers, the combination index including AST, BMI, ALT and CHOL provides a better model to predictor moderate to severe fibrosis in non-lean patients with MAFLD. metabolic associated fatty liver disease overweight obese fibrosis Figures Figure 1 Introduction With urbanization, modernization and westernization of dietary structure, non-alcoholic fatty liver disease (NAFLD) has become the world's largest chronic liver disease [1] . NAFLD is the manifestation of metabolic syndrome (MetS) in the liver, and the latest international consensus recommends that it be renamed as Metabolic associated fatty liver disease (MAFLD). According to the guidelines for the diagnosis and treatment of MAFLD issued by the Asia-Pacific Society of Hepatology in 2020 [2] , regardless of the presence or absence of metabolic syndrome, overweight and obese patients diagnosed with fatty liver by abdominal ultrasonography or liver biopsy pathology or other imaging methods can be clearly diagnosed MAFLD. Body Mass Index (BMI) is closely related to the occurrence and development of MAFLD. With the increase of BMI, the prevalence of MAFLD increases significantly, and increased BMI is a risk factor for MAFLD [3,4] . Increased BMI is not only a risk factor for MAFLD but also determine severity of MAFLD. Lean MAFLD patients have lower prevalence of insulin resistance and less hepatic fibrosis compared to non-lean (overweight/obese) MAFLD [5,6] . And data on clinical characteristics, metabolic profiles, and histopathological severity in non-lean patients have yet to be fully explored. Recent study analysis the clinical features between overweight and obese MAFLD, which shown BMI was associated with hepatic steatosis and fibrosis [7] . The above results hinted that weight control can improve MAFLD patient outcome, while most of these patients were not underwent with liver biopsy. Furthermore, validation of conventional non-invasive fibrosis scoring systems in MAFLD patients shown that aspartate aminotransferase to platelet ratio index (APRI) scores do not perform well in MAFLD, a new threshold of fibrosis-4 index (FIB-4) was needed, so novel non-invasive scoring systems for fibrosis are required for MAFLD [8] . With that in mind, we designed a cross-sectional study to compare the clinical presentation and pathological findings between overweight and obese patients with MAFLD. In addition, the study except to develop, validate and compare a non-invasive scoring system for moderate to severe fibrosis in non-lean MAFLD patients. Methods 1) Study population Patients who were pathologically diagnosed with MAFLD by liver biopsy from April 1, 2017 to May 31, 2022 in the Fifth Hospital of Shijiazhuang and the First Affiliated Hospital of Jinan University were selected. This study was approved by the Medical Ethics Committee of The Fifth Hospital of Shijiazhuang (approval number: LL2016003) and the Medical Ethics Committee of The First Affiliated Hospital of Jinan University (approval number: KY-2022-048) Inclusion criteria: (1) Liver biopsy histology showed fatty liver; (2) BMI>23 kg/m 2 with or without type 2 diabetes or metabolic dysfunction. Exclusion criteria: (1) patients with other viral liver diseases (hepatitis A, C, E) or HIV infection; (2) patients with alcoholic liver disease, autoimmune liver disease, drug-induced liver injury, hepatolenticular degeneration, total parenteral nutrition and toxic liver disease, etc.; (3) patients with liver cancer and other malignant tumors; (4) combined with other autoimmune diseases. 2) Data assessment and collection All study objectives underwent medical history collection and clinical check-up. A medical history of alcohol consumption, and details of personal medicine prescriptions, hypertension, diabetes, viral hepatitis and autoimmune hepatitis were collected before a general examination. Patients’ body mass and height were assessed, and the BMI (kg/m 2 ) was calculated as body mass divided by height squared. Blood pressure was also assessed, and hypertension was defined as a systolic blood pressure of ≥140 mmHg and/or a diastolic blood pressure of 90 mmHg, a self-reported history of hypertension, and/or the use of antihypertensive drugs. Diabetes was defined as having fasting plasma Glucose≥7.0mmol/L, a self-reported history of diabetes, and/or undergoing treatment of oral antidiabetic agents. Fasting venous blood samples were obtained within seven days before the biopsy, and used for measurements of the following parameters by conventional laboratory techniques: the complete blood cell counts, aspartate transaminase (AST), alanine transaminase (ALT), alkaline phosphatase (ALP), gamma-Glutamyl transpeptidase (GGT), total bilirubin (TB), direct bilirubin (DB), total protein, albumin(ALB), globulin (GLB), prealbumin (PA), cholinesterase (CHE), blood Glucose (Glu), total cholesterol (CHOL), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), triglycerides (TG), uric acid (UA), urea, creatinine, and prothrombin time (PT). FibroScan was measured 1 ～ 30 days before liver biopsy. FibroScan was used for the measure of liver stiffness measurement (LSM) and controlled attenuation parameter (CAP) via transient elastography by trained operators in accordance with the manufacturer’s instruction. Standard M probe was used in the first instance so that both LSM and CAP could be obtained. The XL probe was used in obese patients when the M probe failed. Ten successful acquisitions were performed in each patient. LSM and CAP values are expressed as the median of all valid measurements obtained. 3) Histological data Morbid obsess patients underwent intro-operative liver biopsies during bariatric surgery, while other patients undergoing liver puncture. The samples were fixed in formalin and embedded in paraffin, sections were cut and prepared by haematoxylin-eosin staining for morphological evaluation, Masson’s trichrome staining, and reticulin staining for fibrosis assessment. All MAFLD sections were scored by two liver pathologists using FLIP-SAF, who were blind to the study protocol and the pathology report should include the presence and extent of hepatocyte steatosis, ballooning, intralobular inflammation, and liver fibrosis [9] . MAFLD was pathologically diagnosed if the steatosis area was > 5%. Hepatic steatosis was assigned on a scale of 0 to 3 (S0: 67%), ballooning of hepatocytes and lobular inflammation was graded from 0 to 2 and fibrosis was assigned a score of 0, 1, 2, 3, or 4 (stage 0, no fibrosis; stage 1, perisinusoidal or periportal fibrosis; stage 2, perisinusoidal and portal/periportal fibrosis; stage 3, bridging fibrosis; and stage 4, cirrhosis). The grade of activity (from A0 to A4) was calculated by addition of grades of hepatocytes ballooning and lobular inflammation. “Moderate to severity activity/ fibrosis” was defined as activity/fibrosis score of more than 2. 4) Statistical Methods SPSS 24.0 statistical software was applied, measurement data conforming to normal distribution were expressed as x±s, and t test was used for comparison between groups; The measurement data that do not conform to the normal distribution are represented by the median M (P25, P75), and the rank sum test is used for comparison between groups; Enumeration data were expressed as the number of cases (percentage), and the comparison between groups was performed by c2 test. Multivariate logistic regression analysis was performed on the relevant factors with statistical significance at the test level of 0.05 in univariate analysis. Logistic regression analysis used the likelihood ratio advance method to screen variables, and the test level of the introduced variables was α=0.10. And the independent factors affecting the occurrence of the disease were analyzed by the multivariate adjusted OR value. The diagnostic efficacy was analyzed by receiver operating characteristic (ROC) curve. P<0.05 was considered to be statistically significant. Results 1. Clinical features of overweight and obese MAFLD Because of the obvious positive correlation between age and liver fibrosis, age adjustment was performed for the two groups of MAFLD patients. According to the above inclusion, exclusion criteria and age adjustment, 184 non-lean MAFLD patients were finally included, including 65 overweight (BMI 23~<28 kg/m 2 ) and 119 obese (BMI≥28 kg/m 2 ) MAFLD patients. Out of 184 non-lean MAFLD subjects, 80 were male, 104 were female. The median age was 36 years old. 28.8% non-lean MAFLD patients had diabetes or abnormal blood sugar, and 25.0% had hypertension. A small number non-lean MAFLD patients (9.8%) were with drinking history. There were more women in obese group than overweight group. There was no significantly difference between the two subgroups on the other mentioned items (Table 1). The levels of WBC and PLT in peripheral blood of obese MAFLD group were significantly higher than those of overweight MAFLD group, the difference was statistically significant, P<0.05. The levels of ALT, AST and GGT in the two groups were all higher than the upper limit of normal values, and the levels of ALT, AST and GGT in the overweight MAFLD group were significantly higher than those in the obese MAFLD group (P<0.05). The levels of TB, DB and ALB in the overweight MAFLD group were significantly higher than those in the obese MAFLD group, while the GLB and PT levels were lower, the differences were statistically significant (P<0.05), but they were all within the normal range. The levels of UA and Glu in the two groups were higher than normal levels, and the levels of UA and Glu in the obese MAFLD group were higher than those in the overweight MAFLD group (P 0.05), as shown in Table 2. Multivariate logistic regression analysis found that PLT, GGT, Glu and PT were independent predict factors for obese MAFLD in non-lean patients. Among them, the OR values of PLT, Glu and PT were 1.005 (0.999, 1.011), 1.392 (1.005, 1.926) and 4.265 (2.462, 7.388), respectively, which were all risk factors for the occurrence of obese MAFLD, see Table 3. After deducting the influence of the above four factors, there was no significant association between gender, ALT, AST and other factors and the occurrence of obese MAFLD. 2. Noninvasive indicators of steatosis and fibrosis in overweight and obese MAFLD The APRI and FIB-4 indexes of the overweight MAFLD patients were higher than those of the obese MAFLD group, and the difference was statistically significant (P0.05). (Table 4). 3. Histopathological characteristics of liver in overweight and obese MAFLD groups Compared with overweight MAFLD, the proportion of moderate to severe inflammatory activity (≥A2) in obese MAFLD patients was significantly higher, but the proportion of significant fibrosis (≥F2) in obese MAFLD patients was significantly lower (P<0.05). However, there was no statistically difference in the proportion of significant steatosis (≥S2) between the two groups, as shown in Table 5. 4. Logistic regression analysis of moderate to severe fibrosis in non-lean MAFLD Taking the moderate to severe of fibrosis (≥F2) in non-lean MAFLD as the dependent variable and the factors with statistical differences in univariate analysis as the independent variables, a multivariate logistic regression analysis was performed. The results showed that AST, BMI, ALT and CHOL were independent influencing factors of fibrosis in non-lean MAFLD. Among them, the OR value of AST was 1.057 (1.024, 1.090), which was a risk factor for fibrosis in non-lean MAFLD (see Table 6). 5. Diagnostic efficacy of various non-invasive methods for moderate to severe fibrosis in non-lean MAFLD Generate regression equations of AST, BMI, ALT and CHOL according to the logistic regression model：9.025 - 0.144 * BMI - 0.014 * ALT + 0.055 * AST - 1.476 * CHOL. The regression equation was used as four combined indicators to diagnose moderate to severe fibrosis in non-lean MAFLD patients. The results showed that compared with the traditional FIB-4 (AUC=0.770) and APRI (AUC=0.791) indices, the new combined index was more effective in diagnosing moderate to severe fibrosis in non-lean MAFLD patients, AUC=0.869, see Figure 1. Discussion MAFLD is a newly proposed diagnosis of fatty liver disease that is more applicable to clinical practice than before [10] . According to BMI, non-lean MAFLD patients were divided to overweight and obese subgroups. Logistic regression models revealed that obese MAFLD was associated with PLT, GGT, Glu and PT. Compared with overweight MAFLD patients, obese MAFLD patients had higher levels of peripheral blood PLT, PT and Glu, and a higher proportion of histologically moderate to severe inflammatory activity levels. However, GGT level in obese MAFLD group was lower than those in overweight MAFLD group. With the increase in BMI and CAP, the PLT showed a decreasing trend [11,12] , but some studies have also reached the opposite conclusion as we have [13] . Platelets participate in the inflammatory response of the liver and can promote leukocyte recruitment and activation of effector cells through hepatic sinuses. Moreover, the function and morphology of platelets will also change in patients with diabetes and metabolic syndrome [14] . Average platelet volume is directly related to the histological severity of live fibrosis [15] . GGT is a liver enzyme, which can help diagnose liver injury. Xing Y et al shown that there was a progressive increase in the prevalence of MAFLD with increasing tertiles of GGT/HDL [16] , which was not consistent with the study. Increased Glucose is considered an important component of metabolic syndrome. The association of the prevalence of MAFLD with impaired Glucose metabolism has been reported in both children and adult. The prevalence of NASH in obesity children was closely related to high BMI, gender, insulin resistance and hyperuricemia [17] . Fasting blood-Glucose was positively associated with BMI in adult patients with NAFLD [18] . Furthermore, Type 2 diabetes increases the risk of serious NASH and advanced fibrosis in NAFLD patients [19] . Liver hepatocytes are involved in the synthesis of most blood coagulation factors. In patients with NAFLD, FVIII, FIX, FXI and FXII activities are increased. The relationships between NAFLD and these coagulation factors are independent of age, gender and BMI, which suggest that NAFLD can contribute to the risk of thrombosis [20] . Although previous meta-analyses have confirmed that obese MAFLD patients have significantly higher metabolic-related serological markers than lean (BMI< 25 kg/m 2 ) patients [21] , a late-stage fibrosis relationship between non-obese and obese MAFLD persists dispute. A meta-analysis suggested that obesity may predict poor long-term prognosis in MAFLD patients, however, obesity may not be an independent factor for developing NASH or advanced fibrosis in MAFLD patients [22] . In the study, APRI and FIB-4 index levels were lower, and the proportion of histologically significant fibrosis was also lower in obese MAFLD compared to overweight MAFLD. We also found that the combined index composed of AST, BMI, ALT and CHOL is more effective in diagnosing significant fibrosis in non-lean MAFLD patients than traditional FIB-4 and APRI. Published studies suggested that blood cholesterol levels were relatively reduced in mice due to inflammation promoting abnormal accumulation of cholesterol from the blood to the liver [25,26] . Cheng-Maw Ho et al. also found that free cholesterol and oxidized low-density lipoprotein co-localize on the portal vein wall, and their accumulation in periportal and sinus fibrosis is associated with local stellate cell activation and chicken-wire fibrosis. The accumulation of free cholesterol (FC) is associated with the activation of Hematopoietic stem cells, and FC sensitizes cells to TGF-β through TLR4 up-regulation and down-regulation of the TGF-β pseudoreceptor, resulting in TGF-β-induced liver fibrosis [27,28] . Our study has several limitations. First, we did not assess the influence of body fat distribution (eg waist circumference, abdominal circumference, waist-to-hip ratio), and lifestyle factors. Second, there was patient selection bias, because patients with MAFLD who underwent liver biopsy were more likely to consider non-alcoholic steatohepatitis and were generally associated with elevated transaminases. Other morbidly obese MAFLD patients, mostly young women with low transaminase levels, were biopsied during bariatric surgery. Third, the main body of the study is non-lean MAFLD, and there is a lack of normal-weight controls. More data or studies are needed to clarify the differences between non-obese and overweight and obese MAFLD. In conclusion, overweight and obese MAFLD have different clinical features in terms of laboratory indicators and pathology, especially obese MAFLD manifests as low fibrosis level. AST, BMI, ALT and CHOL provides a better model to predictor is more effective in the diagnosis of fibrosis stage≥F2 in non-lean patients with MAFLD patients. Abbreviations ALT: alanine transaminase APRI: aspartate aminotransferase to platelet ratio AST: aspartate transaminase BMI: Body Mass Index CHOL: total cholesterol FIB-4: fibrosis-4 GGT: gamma-Glutamyl transpeptidase Glu: Glucose NAFLD: non-alcoholic fatty liver disease MAFLD: metabolic associated fatty liver disease MetS: metabolic syndrome PLT: platelet PT: prothrombin time Declarations Contributions Min-ran Li and Jin-zhong Li searched the literature and conceived of the study, Zhi-yong Dong, Er-hei Dai and Cun-chuan Wang designed the study, and Min-ran Li and Jin-zhong Li interpreted the results and drafted the report. Li-hong Ye, Hai-cong Hai and Zhi-quan Liu made pathological diagnoses of needle-biopsied liver tissue. Xue-dong Zhang performed laboratory test. Yun-yan Liu, Dong-yu Zeng, De-hua Wang, Liu Yang, Jie-ying Li, Yang Cao, Yun Pan and Xun-ge Lin collected the data. Min-ran Li, Jin-zhong Li, Rui-kun Yuan, Xu-jing Liang and Tao-yuan Li analyzed the data. Calvin Pan revised the manuscript and addressed the reviewers’ comments. Ethics declarations This study was approved by the Medical Ethics Committee of The Fifth Hospital of Shijiazhuang (approval number: LL2016003) and the Medical Ethics Committee of The First Affiliated Hospital of Jinan University (approval number: KY-2022-048) Funding and grant support Youth Program of the National Nature Science Foundation of China (grant number 82000556) References Huang TD, Behary J, Zekry A. Non-alcoholic fatty liver disease: a review of epidemiology, risk factors, diagnosis and management. Intern Med J. 2020;50(9):1038–47. Eslam M, Sarin SK, Wong VW, Fan JG, Kawaguchi T, Ahn SH, Zheng MH, Shiha G, Yilmaz Y, Gani R, Alam S, Dan YY, Kao JH, Hamid S, Cua IH, Chan WK, Payawal D, Tan SS, Tanwandee T, Adams LA, Kumar M, Omata M, George J. 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Tables Table 1 Comparison of general data between overweight and obese MAFLD group Group All patients (n=184) Overweight group（n=65） Obese group（n=119） Statistics *P value Gender(male/female) 80/104 36/29 44/75 χ2 =5.80 0.01 Age M (P25, P75) 36(29, 49) 40（28, 51） 34（30, 44） Z=-1.83 0.07 Diabetes or abnormal blood sugar（%） 28.8 21.5 32.8 χ2 =2.59 0.11 Hypertension（%） 25.0 16.9 29.4 χ2 =3.50 0.06 drinking history（%） 9.8 4.6 12.6 χ2 =1.04 0.08 *P value for overweight group vs. obese group Table 2 Comparison of laboratory parameters between overweight and obese MAFLD groups Project Overweight group （n = 65） Obese group （n=119） Statistics P value WBC[M（P25, P75）,×10 9 /L] 5.93±1.64 7.70±2.80 5.37 0.00 RBC[M（P25, P75）,×10 12 /L] 4.79±0.56 4.96±0.73 1.59 0.11 Hb（xˉ± s ,g/L） 144.39±18.65 139.84±20.43 -1.48 0.14 PLT（xˉ± s ,×10 9 /L） 226.03±74.97 274.19±84.60 3.81 0.00 ALT（U/L） 145.93(59.45, 172.30) 85.22(32.00, 113.05) -4.10 0.00 AST（U/L） 84.65(39.45, 94.15) 49.49(21.50, 57.10) -5.15 0.00 TB（μmol/L） 16.98(10.00, 19.00) 13.43(9.35, 15.10) -2.31 0.02 DB（μmol/L） 6.02(3.70, 6.73) 4.20(2.40, 4.90) -4.04 0.00 ALB（g/L） 47.33±4.56 43.23±4.01 -6.15 0.00 PA（g/L） 261.21±68.93 241.03±62.04 -1.81 0.07 GLB（g/L） 27.09±5.75 29.21±4.85 2.54 0.01 GGT（U/L） 128.23(43.98, 140.03) 65.52(27.00, 80.50) -4.16 0.00 ALP（U/L） 91.28±44.20 89.73±42.06 -0.22 0.83 UA（μmol/L） 365.08±97.79 422.71±120.91 2.95 0.00 GLU（mmol/L） 6.06±1.32 7.54±4.93 3.04 0.00 TG（mmol/L） 2.80(1.14, 2.50) 2.29(1.30, 2.32) -0.16 0.87 CHOL（x± s，mmol/L） 4.94±0.94 5.25±1.12 1.87 0.06 HDL-C（mmol/L） 1.08±0.23 1.11±0.60 0.35 0.73 LDL-C（x±s，mmol/L） 3.09±0.7 3.13±0.91 0.30 0.77 CHE 9625.69±2053.87 10224.81±2087.72 1.71 0.09 Urea 4.45±1.00 4.40±1.11 -0.25 0.80 Cr 62.87±13.21 60.95±15.30 -0.66 0.51 PT 11.15±0.78 12.56±1.26 8.97 0.00 INR 0.97±0.11 0.98±0.09 0.91 0.36 AFP 5.50(2.09, 4.37) 3.00(2.13, 3.67) -0.77 0.44 Table 3 Multivariate logistic regression analysis for prediction of obses MALFD in non-lean patients Influencing factors B OR P 95% CI PLT 0.005 1.005 0.105 0.999-1.011 GGT -0.007 0.993 0.045 0.986-1.000 GLU 0.330 1.392 0.046 1.005-1.926 PT 1.451 4.265 0.00 2.462-7.388 Table 4 Comparison of non-invasive indicators of steatosis and liver fibrosis between overweight and obese MAFLD groups Group APRI [M（ P 25 , P 75 ）] FIB-4 [M（ P 25 , P 75 ）] CAP （x±s, dB/m) LSM （x±s，kPa） Overweight group（n = 65） 1.18（0.27，1.46） 1.69（0.66，1.84） 283.50±31.63 13.36（8.05，17.00） Obese group（n=119） 0.67（0.23，0.72） 1.01（0.39，0.95） 306.71±43.59 12.38（4.85，15.98） Statistics -5.64 -4.67 -1.55 1.57 P value <0.001 <0.001 0.12 0.12 Table 5 Comparison of histopathology between overweight and obese MAFLD groups Group Steatosis Activity Fibrosis S0 ~ S1 S2 ~ S3 A0 ~ A1 A2 ~ A4 F0 ~ F1 F2 ~ F4 Overweight group（n = 65） 33 32 25 40 39 26 Obese group（n=119） 62 57 22 97 96 23 χ2 value 0.03 8.82 9.19 P value 0.86 0.003 0.002 Table 6 Multivariate logistic regression analysis of fibrosis stage≥F2 in non-lean MAFLD Influencing factors B OR P 95% CI AST 0.055 1.057 0.001 1.024-1.090 BMI -0.144 0.866 0.005 0.783-0.958 ALT -0.014 0.986 0.015 0.975-0.997 CHOL -1.476 0.228 0.001 0.097-0.541 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Pan","email":"","orcid":"","institution":"Capital Medical University Affiliated Beijing Ditan Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Calvin","middleName":"Q.","lastName":"Pan","suffix":""},{"id":134000211,"identity":"cfeafeae-897d-43d4-85fe-cfd7c3e99938","order_by":20,"name":"Er-hei Dai","email":"","orcid":"","institution":"Hebei Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Er-hei","middleName":"","lastName":"Dai","suffix":""},{"id":134000212,"identity":"48802ed5-6f43-4fd1-975d-33c25bf4ff22","order_by":21,"name":"Zhi-yong Dong","email":"","orcid":"","institution":"Jinan University First Affiliated Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhi-yong","middleName":"","lastName":"Dong","suffix":""}],"badges":[],"createdAt":"2022-08-29 12:11:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2009818/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2009818/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":26197380,"identity":"11f53f5e-2651-42c4-a755-ac76b114ab91","added_by":"auto","created_at":"2022-09-07 23:05:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":16567,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves of novel model, APRI and FIB-4 for predicting fibrosis≥F2 in non-lean patients\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-2009818/v1/737180f41abce256462d995c.png"},{"id":26592577,"identity":"4dbcc9ac-acd0-410e-bf98-5f9b7b6af55b","added_by":"auto","created_at":"2022-09-17 05:39:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":386095,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2009818/v1/3fc54b48-165a-444c-90a0-5c67b56d0843.pdf"}],"financialInterests":"","formattedTitle":"Clinical features of metabolism-related fatty liver disease in the non-lean population","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWith urbanization, modernization and westernization of dietary structure, non-alcoholic fatty liver disease (NAFLD) has become the world\u0026apos;s largest chronic liver disease \u003csup\u003e[1]\u003c/sup\u003e. NAFLD is the manifestation of metabolic syndrome (MetS) in the liver, and the latest international consensus recommends that it be renamed as Metabolic associated fatty liver disease (MAFLD). According to the guidelines for the diagnosis and treatment of MAFLD issued by the Asia-Pacific Society of Hepatology in 2020\u003csup\u003e[2]\u003c/sup\u003e, regardless of the presence or absence of metabolic syndrome, overweight and obese patients diagnosed with fatty liver by abdominal ultrasonography or liver biopsy pathology or other imaging methods can be clearly diagnosed MAFLD. Body Mass Index (BMI) is closely related to the occurrence and development of MAFLD. With the increase of BMI, the prevalence of MAFLD increases significantly, and increased BMI is a risk factor for MAFLD\u003csup\u003e\u0026nbsp;[3,4]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIncreased BMI is not only a risk factor for MAFLD but also determine severity of MAFLD. Lean MAFLD patients have lower prevalence of insulin resistance and less hepatic fibrosis compared to non-lean (overweight/obese) MAFLD \u003csup\u003e[5,6]\u003c/sup\u003e. And data on clinical characteristics, metabolic profiles, and histopathological severity in non-lean patients have yet to be fully explored. Recent study analysis the clinical features between overweight and obese MAFLD, which shown BMI was associated with hepatic steatosis and fibrosis \u003csup\u003e[7]\u003c/sup\u003e. The above results hinted that weight control can improve MAFLD patient outcome, while most of these patients were not underwent with liver biopsy. Furthermore, validation of conventional non-invasive fibrosis scoring systems in MAFLD patients shown that aspartate aminotransferase to platelet ratio index (APRI) scores do not perform well in MAFLD, a new threshold\u0026nbsp;of fibrosis-4 index (FIB-4) was needed, so novel non-invasive scoring systems for fibrosis are required for MAFLD\u003csup\u003e\u0026nbsp;[8]\u003c/sup\u003e. With that in mind, we designed a cross-sectional study to compare the clinical presentation and pathological findings between overweight and obese patients with MAFLD. In addition, the study except to develop, validate and compare a non-invasive scoring system for moderate to severe fibrosis in non-lean MAFLD patients.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e1) Study population\u0026nbsp;\u003c/strong\u003ePatients who were pathologically diagnosed with MAFLD by liver biopsy from April 1, 2017 to May 31, 2022 in the Fifth Hospital of Shijiazhuang and the First Affiliated Hospital of Jinan University were selected.\u0026nbsp;This study was approved by\u0026nbsp;the Medical Ethics Committee of The Fifth Hospital of Shijiazhuang\u0026nbsp;(approval number: LL2016003) and\u0026nbsp;the Medical Ethics Committee of\u0026nbsp;The First Affiliated Hospital of Jinan University\u0026nbsp;(approval number: KY-2022-048)\u003c/p\u003e\n\u003cp\u003eInclusion criteria: (1) Liver biopsy histology showed fatty liver; (2) BMI\u0026gt;23 kg/m\u003csup\u003e2\u003c/sup\u003e with or without type 2 diabetes or metabolic dysfunction. Exclusion criteria: (1) patients with other viral liver diseases (hepatitis A, C, E) or HIV infection; (2) patients with alcoholic liver disease, autoimmune liver disease, drug-induced liver injury, hepatolenticular degeneration, total parenteral nutrition and toxic liver disease, etc.; (3) patients with liver cancer and other malignant tumors; (4) combined with other autoimmune diseases.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2) Data assessment and collection\u0026nbsp;\u003c/strong\u003eAll study objectives underwent medical history collection and clinical check-up. A medical history of alcohol consumption, and details of personal medicine prescriptions, hypertension, diabetes, viral hepatitis and autoimmune hepatitis were collected before a general examination.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePatients\u0026rsquo; body mass and height were assessed, and the BMI (kg/m\u003csup\u003e2\u003c/sup\u003e) was calculated as body mass divided by height squared. Blood pressure was also assessed, and hypertension was defined as a systolic blood pressure of\u0026nbsp;\u0026ge;140 mmHg and/or a diastolic blood pressure of 90 mmHg, a self-reported history of hypertension, and/or the use of antihypertensive drugs. Diabetes was defined as having fasting plasma Glucose\u0026ge;7.0mmol/L, a self-reported history of diabetes, and/or undergoing treatment of oral antidiabetic agents. Fasting venous blood samples were obtained within seven days before the biopsy, and used for measurements of the following parameters by conventional laboratory techniques: the complete blood cell counts, aspartate transaminase (AST), alanine transaminase (ALT), alkaline phosphatase (ALP), gamma-Glutamyl transpeptidase (GGT), total bilirubin (TB), direct bilirubin (DB), total protein, albumin(ALB), globulin (GLB), prealbumin (PA), cholinesterase (CHE), blood Glucose (Glu), total cholesterol (CHOL), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), triglycerides (TG), uric acid (UA), urea, creatinine, and prothrombin time (PT).\u003c/p\u003e\n\u003cp\u003eFibroScan was measured 1\u003cstrong\u003e～\u003c/strong\u003e30 days before liver biopsy.\u0026nbsp;FibroScan was used for the measure of liver stiffness measurement (LSM) and\u0026nbsp;controlled attenuation parameter (CAP)\u0026nbsp;via transient elastography by trained operators in accordance with the manufacturer\u0026rsquo;s instruction. Standard M probe was used in the first instance so that both LSM and CAP could be obtained. The XL probe was used in obese patients when the M probe failed. Ten successful acquisitions were performed in each patient. LSM and CAP values are expressed as the median of all valid measurements obtained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3)\u003c/strong\u003e \u003cstrong\u003eHistological data\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMorbid obsess patients underwent intro-operative liver biopsies during bariatric surgery, while other patients undergoing liver puncture. The samples were fixed in formalin and embedded in paraffin, sections were cut and prepared by haematoxylin-eosin staining for morphological evaluation, Masson\u0026rsquo;s trichrome staining, and reticulin staining for fibrosis assessment. All MAFLD sections were scored by two liver pathologists using FLIP-SAF, who were blind to the study protocol and the pathology report should include the presence and extent of hepatocyte steatosis, ballooning, intralobular inflammation, and liver fibrosis \u003csup\u003e[9]\u003c/sup\u003e. MAFLD was pathologically diagnosed if the steatosis area was\u0026thinsp;\u0026gt;\u0026thinsp;5%.\u0026nbsp;Hepatic steatosis was assigned on a scale of 0 to 3 (S0: \u0026lt;5%; S1: 5%-33%, S2: 34%-66%, S3: \u0026gt;67%), ballooning of hepatocytes and lobular inflammation was graded from 0 to 2 and fibrosis was assigned a score of 0, 1, 2, 3, or 4 (stage 0, no fibrosis; stage 1, perisinusoidal or periportal fibrosis; stage 2, perisinusoidal and portal/periportal fibrosis; stage 3, bridging fibrosis; and stage 4, cirrhosis).\u0026nbsp;The grade of activity (from A0 to A4) was calculated by addition of grades of hepatocytes ballooning and lobular inflammation. \u0026ldquo;Moderate to severity\u0026nbsp;activity/ fibrosis\u0026rdquo; was defined as activity/fibrosis score of more than 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4) Statistical Methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSPSS 24.0 statistical software was applied, measurement data conforming to normal distribution were expressed as x\u0026plusmn;s, and t test was used for comparison between groups; The measurement data that do not conform to the normal distribution are represented by the median M (P25, P75), and the rank sum test is used for comparison between groups; Enumeration data were expressed as the number of cases (percentage), and the comparison between groups was performed by c2 test. Multivariate logistic regression analysis was performed on the relevant factors with statistical significance at the test level of 0.05 in univariate analysis. Logistic regression analysis used the likelihood ratio advance method to screen variables, and the test level of the introduced variables was \u0026alpha;=0.10. And the independent factors affecting the occurrence of the disease were analyzed by the multivariate adjusted OR value. The diagnostic efficacy was analyzed by receiver operating characteristic (ROC) curve. P\u0026lt;0.05 was considered to be statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e1. Clinical features of overweight and obese MAFLD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBecause of the obvious positive correlation between age and liver fibrosis, age adjustment was performed for the two groups of MAFLD patients. According to the above inclusion, exclusion criteria and age adjustment, 184 non-lean MAFLD patients were finally included, including 65 overweight (BMI 23~\u0026lt;28 kg/m\u003csup\u003e2\u003c/sup\u003e) and 119 obese (BMI\u0026ge;28 kg/m\u003csup\u003e2\u003c/sup\u003e) MAFLD patients. Out\u0026nbsp;of\u0026nbsp;184 non-lean MAFLD\u0026nbsp;subjects, 80 were male, 104 were female. The median age was 36 years old. 28.8%\u0026nbsp;non-lean MAFLD patients\u0026nbsp;had diabetes or abnormal blood sugar, and 25.0% had hypertension. A small number\u0026nbsp;non-lean MAFLD patients (9.8%) were with drinking history.\u0026nbsp;There were more women in obese group than overweight group. There was no significantly difference between the two subgroups on the other mentioned items (Table 1).\u003c/p\u003e\n\u003cp\u003eThe levels of WBC and PLT in peripheral blood of obese MAFLD group were significantly higher than those of overweight MAFLD group, the difference was statistically significant, P\u0026lt;0.05. The levels of ALT, AST and GGT in the two groups were all higher than the upper limit of normal values, and the levels of ALT, AST and GGT in the overweight MAFLD group were significantly higher than those in the obese MAFLD group (P\u0026lt;0.05). The levels of TB, DB and ALB in the overweight MAFLD group were significantly higher than those in the obese MAFLD group, while the GLB and PT levels were lower, the differences were statistically significant (P\u0026lt;0.05), but they were all within the normal range. The levels of UA and Glu in the two groups were higher than normal levels, and the levels of UA and Glu in the obese MAFLD group were higher than those in the overweight MAFLD group (P\u0026lt;0.05). However, there were no statistical significance in blood lipid, renal function and other indicators (P\u0026gt; 0.05), as shown in Table 2.\u003c/p\u003e\n\u003cp\u003eMultivariate logistic regression analysis found that PLT, GGT, Glu and PT were independent predict factors for obese MAFLD in non-lean patients. Among them, the OR values of PLT, Glu and PT were 1.005 (0.999, 1.011), 1.392 (1.005, 1.926) and 4.265 (2.462, 7.388), respectively, which were all risk factors for the occurrence of obese MAFLD, see Table 3. After deducting the influence of the above four factors, there was no significant association between gender, ALT, AST and other factors and the occurrence of obese MAFLD.\u003c/p\u003e\n\u003cp\u003e2.\u003cstrong\u003e\u0026nbsp;Noninvasive indicators of steatosis and fibrosis in overweight and obese MAFLD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe APRI and FIB-4 indexes of the overweight MAFLD patients were higher than those of the obese MAFLD group, and the difference was statistically significant (P\u0026lt;0.05). There was no significant difference in the CAP and LSM between the two groups (P\u0026gt;0.05). (Table 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. Histopathological characteristics of liver in overweight and obese MAFLD groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompared with overweight MAFLD, the proportion of moderate to severe inflammatory activity (\u0026ge;A2) in obese MAFLD patients was significantly higher, but the proportion of significant fibrosis (\u0026ge;F2) in obese MAFLD patients was significantly lower (P\u0026lt;0.05). However, there was no statistically difference in the proportion of significant steatosis (\u0026ge;S2) between the two groups, as shown in Table 5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4. Logistic regression analysis of moderate to severe fibrosis in non-lean MAFLD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTaking the moderate to severe of fibrosis (\u0026ge;F2) in non-lean MAFLD as the dependent variable and the factors with statistical differences in univariate analysis as the independent variables, a multivariate logistic regression analysis was performed. The results showed that AST, BMI, ALT and CHOL were independent influencing factors of fibrosis in non-lean MAFLD. Among them, the OR value of AST was 1.057 (1.024, 1.090), which was a risk factor for fibrosis in non-lean MAFLD (see Table 6).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5. Diagnostic efficacy of various non-invasive methods for moderate to severe fibrosis in non-lean MAFLD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGenerate regression equations of AST, BMI, ALT and CHOL according to the logistic regression model：9.025 - 0.144 * BMI - 0.014 * ALT + 0.055 * AST - 1.476 * CHOL. The regression equation was used as four combined indicators to diagnose moderate to severe fibrosis in non-lean MAFLD patients. The results showed that compared with the traditional FIB-4 (AUC=0.770) and APRI (AUC=0.791) indices, the new combined index was more effective in diagnosing moderate to severe fibrosis in non-lean MAFLD patients, AUC=0.869, see Figure 1.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMAFLD is a newly proposed diagnosis of fatty liver disease that is more applicable to clinical practice than before \u003csup\u003e[10]\u003c/sup\u003e. According to BMI, non-lean MAFLD patients were divided to overweight and obese subgroups. Logistic regression models revealed that obese MAFLD was associated with PLT, GGT, Glu and PT.\u0026nbsp;Compared with overweight MAFLD patients, obese MAFLD patients had higher levels of peripheral blood PLT, PT and Glu, and a higher proportion of histologically moderate to severe inflammatory activity levels. However, GGT level in obese MAFLD group was lower than those in overweight MAFLD group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWith the increase in BMI and CAP, the PLT showed a decreasing trend \u003csup\u003e[11,12]\u003c/sup\u003e, but some studies have also reached the opposite conclusion as we have \u003csup\u003e[13]\u003c/sup\u003e. Platelets participate in the inflammatory response of the liver and can promote leukocyte recruitment and activation of effector cells through hepatic sinuses. Moreover, the function and morphology of platelets will also change in patients with diabetes and metabolic syndrome \u003csup\u003e[14]\u003c/sup\u003e. Average platelet volume is directly related to the histological severity of live fibrosis \u003csup\u003e[15]\u003c/sup\u003e.\u0026nbsp;GGT is a liver enzyme, which can help diagnose liver injury. Xing Y et al shown that there was a progressive increase in the prevalence of MAFLD with increasing tertiles of GGT/HDL \u003csup\u003e[16]\u003c/sup\u003e, which was not consistent with the study. Increased Glucose is considered an important component of metabolic syndrome. The association of the prevalence of MAFLD with impaired Glucose metabolism has been reported in both children and adult. The prevalence of NASH in obesity children was closely related to high BMI, gender, insulin resistance and hyperuricemia \u003csup\u003e[17]\u003c/sup\u003e. Fasting blood-Glucose was positively associated with BMI in adult patients with NAFLD\u003csup\u003e\u0026nbsp;[18]\u003c/sup\u003e. Furthermore, Type 2 diabetes increases the risk of serious NASH and advanced fibrosis in NAFLD patients\u003csup\u003e\u0026nbsp;[19]\u003c/sup\u003e. Liver hepatocytes are involved in the synthesis of most blood coagulation factors. In patients with NAFLD, FVIII, FIX, FXI and FXII activities are increased. The relationships between NAFLD and these coagulation factors are independent of age, gender and BMI, which suggest that NAFLD can contribute to the risk of thrombosis\u003csup\u003e\u0026nbsp;[20]\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAlthough previous meta-analyses have confirmed that obese MAFLD patients have significantly higher metabolic-related serological markers than lean (BMI\u0026lt; 25 kg/m\u003csup\u003e2\u003c/sup\u003e) patients \u003csup\u003e[21]\u003c/sup\u003e, a late-stage fibrosis relationship between non-obese and obese MAFLD persists dispute. A meta-analysis suggested that obesity may predict poor long-term prognosis in MAFLD patients, however, obesity may not be an independent factor for developing NASH or advanced fibrosis in MAFLD patients \u003csup\u003e[22]\u003c/sup\u003e. In the study, APRI and FIB-4 index levels were lower, and the proportion of histologically significant fibrosis was also lower in obese MAFLD compared to overweight MAFLD. We also found that the combined index composed of AST, BMI, ALT and CHOL is more effective in diagnosing significant fibrosis in non-lean MAFLD patients than traditional FIB-4 and APRI. Published studies suggested that blood cholesterol levels were relatively reduced in mice due to inflammation promoting abnormal accumulation of cholesterol from the blood to the liver \u003csup\u003e[25,26]\u003c/sup\u003e. Cheng-Maw Ho et al. also found that free cholesterol and oxidized low-density lipoprotein co-localize on the portal vein wall, and their accumulation in periportal and sinus fibrosis is associated with local stellate cell activation and chicken-wire fibrosis. The accumulation of free cholesterol (FC) is associated with the activation of Hematopoietic stem cells, and FC sensitizes cells to TGF-\u0026beta; through TLR4 up-regulation and down-regulation of the TGF-\u0026beta; pseudoreceptor, resulting in TGF-\u0026beta;-induced liver fibrosis \u003csup\u003e[27,28]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eOur study has several limitations. First, we did not assess the influence of body fat distribution (eg waist circumference, abdominal circumference, waist-to-hip ratio), and lifestyle factors. Second, there was patient selection bias, because patients with MAFLD who underwent liver biopsy were more likely to consider non-alcoholic steatohepatitis and were generally associated with elevated transaminases. Other morbidly obese MAFLD patients, mostly young women with low transaminase levels, were biopsied during bariatric surgery. Third, the main body of the study is non-lean MAFLD, and there is a lack of normal-weight controls. More data or studies are needed to clarify the differences between non-obese and overweight and obese MAFLD.\u003c/p\u003e\n\u003cp\u003eIn conclusion, overweight and obese MAFLD have different clinical features in terms of laboratory indicators and pathology, especially obese MAFLD manifests as low fibrosis level. AST, BMI, ALT and CHOL provides a better model to predictor is more effective in the diagnosis of fibrosis stage\u0026ge;F2 in non-lean patients with MAFLD patients.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eALT: alanine transaminase\u003c/p\u003e\n\u003cp\u003eAPRI: aspartate aminotransferase to platelet ratio\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAST: aspartate transaminase\u003c/p\u003e\n\u003cp\u003eBMI: Body Mass Index\u003c/p\u003e\n\u003cp\u003eCHOL: total cholesterol\u003c/p\u003e\n\u003cp\u003eFIB-4: fibrosis-4\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGGT: gamma-Glutamyl transpeptidase\u003c/p\u003e\n\u003cp\u003eGlu: Glucose\u003c/p\u003e\n\u003cp\u003eNAFLD: non-alcoholic fatty liver disease\u003c/p\u003e\n\u003cp\u003eMAFLD:\u0026nbsp;metabolic associated fatty liver disease\u003c/p\u003e\n\u003cp\u003eMetS: metabolic syndrome\u003c/p\u003e\n\u003cp\u003ePLT: platelet\u003c/p\u003e\n\u003cp\u003ePT: prothrombin time\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMin-ran Li and Jin-zhong Li searched the literature and conceived of the study, Zhi-yong Dong, Er-hei Dai and Cun-chuan Wang designed the study, and Min-ran Li and Jin-zhong Li interpreted the results and drafted the report. Li-hong Ye, Hai-cong Hai and Zhi-quan Liu made pathological\u0026nbsp;diagnoses\u0026nbsp;of needle-biopsied liver tissue. Xue-dong Zhang performed laboratory test. Yun-yan Liu, Dong-yu Zeng, De-hua Wang, Liu Yang, Jie-ying Li, Yang Cao, Yun Pan and Xun-ge Lin collected the data. Min-ran Li, Jin-zhong Li, Rui-kun Yuan, Xu-jing Liang and Tao-yuan Li analyzed the data. Calvin Pan revised the manuscript and addressed the reviewers\u0026rsquo; comments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by\u0026nbsp;the Medical Ethics Committee of The Fifth Hospital of Shijiazhuang\u0026nbsp;(approval number: LL2016003) and\u0026nbsp;the Medical Ethics Committee of\u0026nbsp;The First Affiliated Hospital of Jinan University\u0026nbsp;(approval number: KY-2022-048)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding and grant support\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYouth Program of the National Nature Science Foundation of China (grant number 82000556)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHuang TD, Behary J, Zekry A. Non-alcoholic fatty liver disease: a review of epidemiology, risk factors, diagnosis and management. 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Am J Gastroenterol. 2019 Jun;114(6):916\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu YL, Kumar R, Wang MF, Singh M, Huang JF, Zhu YY, Lin S. Validation of conventional non-invasive fibrosis scoring systems in patients with metabolic associated fatty liver disease. World J Gastroenterol. 2021 Sep;14(34):5753\u0026ndash;63. 27(.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMu YP, Ogawa T, Kawada N. Reversibility of fibrosis, inflammation, and endoplasmic reticulum stress in the liver of rats fed a methionine-choline-deficient diet. Lab Invest. 2010;90(2):245\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Y. The Effect of Inflammatory Stress on Hepatic Cholesterol Accumulation and Hepatic Fibrosis in C57BL/6J Mice [D]. Chongqing Medical University; 2013.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnavi S, Eisenberg-Bord M, Hahn-Obercyger M, Genin O, Pines M, Tirosh O. The role of iNOS in cholesterol-induced liver fibrosis. Lab Invest. 2015;95(8):914\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTomita K, Teratani T, Suzuki T, et al. Acyl-CoA:cholesterol acyltransferase 1 mediates liver fibrosis by regulating free cholesterol accumulation in hepatic stellate cells. J Hepatol. 2014;61(1):98\u0026ndash;106.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 Comparison of general data between overweight and obese MAFLD group\u003c/p\u003e\n\u003ctable width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"227\"\u003e\n\u003cp\u003eGroup\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eAll patients\u003c/p\u003e\n\u003cp\u003e(n=184)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003eOverweight group（n=65）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003eObese group（n=119）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eStatistics\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e*P value\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"227\"\u003e\n\u003cp\u003eGender(male/female)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e80/104\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e36/29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e44/75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026chi;2 =5.80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e0.01\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"227\"\u003e\n\u003cp\u003eAge M (P25, P75)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e36(29, 49)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e40（28, 51）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e34（30, 44）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eZ=-1.83\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e0.07\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"227\"\u003e\n\u003cp\u003eDiabetes or abnormal blood sugar（%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e28.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e21.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e32.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026chi;2 =2.59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e0.11\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"227\"\u003e\n\u003cp\u003eHypertension（%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e25.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e16.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e29.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026chi;2 =3.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e0.06\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"227\"\u003e\n\u003cp\u003edrinking history（%）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e9.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e4.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e12.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026chi;2 =1.04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e0.08\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*P value for overweight group vs. obese group\u003c/p\u003e\n\u003cp\u003eTable 2 Comparison of laboratory parameters between overweight and obese MAFLD groups\u003c/p\u003e\n\u003ctable width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eProject\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eOverweight group\u003c/p\u003e\n\u003cp\u003e（n = 65）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eObese group\u003c/p\u003e\n\u003cp\u003e（n=119）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003eStatistics\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cem\u003eP \u003c/em\u003evalue\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eWBC[M（P25, P75）,\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e5.93\u0026plusmn;1.64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e7.70\u0026plusmn;2.80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e5.37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.00\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eRBC[M（P25, P75）,\u0026times;10\u003csup\u003e12\u003c/sup\u003e/L]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e4.79\u0026plusmn;0.56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e4.96\u0026plusmn;0.73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e1.59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0.11\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eHb（xˉ\u0026plusmn; s ,g/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e144.39\u0026plusmn;18.65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e139.84\u0026plusmn;20.43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e-1.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0.14\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003ePLT（xˉ\u0026plusmn; s ,\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e226.03\u0026plusmn;74.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e274.19\u0026plusmn;84.60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e3.81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.00\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eALT（U/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e145.93(59.45, 172.30)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e85.22(32.00, 113.05)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e-4.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.00\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eAST（U/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e84.65(39.45, 94.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e49.49(21.50, 57.10)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e-5.15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.00\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eTB（\u0026mu;mol/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e16.98(10.00, 19.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e13.43(9.35, 15.10)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e-2.31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eDB（\u0026mu;mol/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e6.02(3.70, 6.73)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e4.20(2.40, 4.90)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e-4.04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.00\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eALB（g/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e47.33\u0026plusmn;4.56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e43.23\u0026plusmn;4.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e-6.15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.00\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003ePA（g/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e261.21\u0026plusmn;68.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e241.03\u0026plusmn;62.04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e-1.81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0.07\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eGLB（g/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e27.09\u0026plusmn;5.75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e29.21\u0026plusmn;4.85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e2.54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eGGT（U/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e128.23(43.98, 140.03)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e65.52(27.00, 80.50)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e-4.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.00\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eALP（U/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e91.28\u0026plusmn;44.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e89.73\u0026plusmn;42.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e-0.22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0.83\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eUA（\u0026mu;mol/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e365.08\u0026plusmn;97.79\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e422.71\u0026plusmn;120.91\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e2.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.00\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eGLU（mmol/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e6.06\u0026plusmn;1.32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e7.54\u0026plusmn;4.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e3.04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.00\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eTG（mmol/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e2.80(1.14, 2.50)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e2.29(1.30, 2.32)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e-0.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0.87\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eCHOL（x\u0026plusmn; s，mmol/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e4.94\u0026plusmn;0.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e5.25\u0026plusmn;1.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e1.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0.06\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eHDL-C（mmol/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e1.08\u0026plusmn;0.23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e1.11\u0026plusmn;0.60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0.73\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eLDL-C（x\u0026plusmn;s，mmol/L）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e3.09\u0026plusmn;0.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e3.13\u0026plusmn;0.91\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0.77\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eCHE\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e9625.69\u0026plusmn;2053.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e10224.81\u0026plusmn;2087.72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e1.71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0.09\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eUrea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e4.45\u0026plusmn;1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e4.40\u0026plusmn;1.11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e-0.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0.80\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eCr\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e62.87\u0026plusmn;13.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e60.95\u0026plusmn;15.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e-0.66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0.51\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003ePT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e11.15\u0026plusmn;0.78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e12.56\u0026plusmn;1.26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e8.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.00\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eINR\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e0.97\u0026plusmn;0.11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e0.98\u0026plusmn;0.09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.91\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0.36\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"195\"\u003e\n\u003cp\u003eAFP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e5.50(2.09, 4.37)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e3.00(2.13, 3.67)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e-0.77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e0.44\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3 Multivariate logistic regression analysis for prediction of obses MALFD in non-lean patients\u003c/p\u003e\n\u003ctable\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"165\"\u003e\n\u003cp\u003eInfluencing factors\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003e95%\u0026nbsp;\u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"165\"\u003e\n\u003cp\u003ePLT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e1.005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e0.105\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003e0.999-1.011\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"165\"\u003e\n\u003cp\u003eGGT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e-0.007\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e0.993\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e0.045\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003e0.986-1.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"165\"\u003e\n\u003cp\u003eGLU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e0.330\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e1.392\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e0.046\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003e1.005-1.926\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"165\"\u003e\n\u003cp\u003ePT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e1.451\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e4.265\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003e2.462-7.388\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 4 Comparison of non-invasive indicators of steatosis and liver fibrosis between overweight and obese MAFLD groups\u003c/p\u003e\n\u003ctable width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"170\"\u003e\n\u003cp\u003eGroup\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003eAPRI\u003c/p\u003e\n\u003cp\u003e[M（\u003cem\u003eP\u003c/em\u003e\u003csub\u003e25 \u003c/sub\u003e\u003cem\u003e, P\u003c/em\u003e\u003csub\u003e75\u003c/sub\u003e）]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003eFIB-4\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;[M（\u003cem\u003eP\u003c/em\u003e\u003csub\u003e25 \u003c/sub\u003e\u003cem\u003e, P\u003c/em\u003e\u003csub\u003e75\u003c/sub\u003e）]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003eCAP\u003c/p\u003e\n\u003cp\u003e（x\u0026plusmn;s, dB/m)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eLSM\u003c/p\u003e\n\u003cp\u003e（x\u0026plusmn;s，kPa）\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"170\"\u003e\n\u003cp\u003eOverweight group（n = 65）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e1.18（0.27，1.46）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e1.69（0.66，1.84）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003e283.50\u0026plusmn;31.63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e13.36（8.05，17.00）\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"170\"\u003e\n\u003cp\u003eObese group（n=119）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e0.67（0.23，0.72）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e1.01（0.39，0.95）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003e306.71\u0026plusmn;43.59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e12.38（4.85，15.98）\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"170\"\u003e\n\u003cp\u003eStatistics\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e-5.64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e-4.67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003e-1.55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e1.57\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"170\"\u003e\n\u003cp\u003e\u003cem\u003eP \u003c/em\u003evalue\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003e0.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e0.12\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 5 Comparison of histopathology between overweight and obese MAFLD groups\u003c/p\u003e\n\u003ctable width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" width=\"196\"\u003e\n\u003cp\u003eGroup\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"125\"\u003e\n\u003cp\u003eSteatosis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"137\"\u003e\n\u003cp\u003eActivity\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"120\"\u003e\n\u003cp\u003eFibrosis\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003eS0 ~ S1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003eS2 ~ S3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eA0 ~ A1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003eA2 ~ A4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"60\"\u003e\n\u003cp\u003eF0 ~ F1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"60\"\u003e\n\u003cp\u003eF2 ~ F4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"196\"\u003e\n\u003cp\u003eOverweight group（n = 65）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"60\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"60\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"196\"\u003e\n\u003cp\u003eObese group（n=119）\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"60\"\u003e\n\u003cp\u003e96\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"60\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"196\"\u003e\n\u003cp\u003e\u0026chi;2 value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"125\"\u003e\n\u003cp\u003e0.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"137\"\u003e\n\u003cp\u003e8.82\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"120\"\u003e\n\u003cp\u003e9.19\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"196\"\u003e\n\u003cp\u003e\u003cem\u003eP \u003c/em\u003evalue\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"125\"\u003e\n\u003cp\u003e0.86\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"137\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"120\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Table 6 Multivariate logistic regression analysis of fibrosis stage\u0026ge;F2 in non-lean MAFLD\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003ctable\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"165\"\u003e\n\u003cp\u003eInfluencing factors\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003e95%\u0026nbsp;\u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"165\"\u003e\n\u003cp\u003eAST\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e0.055\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e1.057\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003e1.024-1.090\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"165\"\u003e\n\u003cp\u003eBMI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e-0.144\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e0.866\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003e0.783-0.958\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"165\"\u003e\n\u003cp\u003eALT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e-0.014\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e0.986\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e0.015\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003e0.975-0.997\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"165\"\u003e\n\u003cp\u003eCHOL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e-1.476\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e0.228\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"96\"\u003e\n\u003cp\u003e0.097-0.541\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"metabolic associated fatty liver disease, overweight, obese, fibrosis","lastPublishedDoi":"10.21203/rs.3.rs-2009818/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2009818/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo assess the clinical and histological features of metabolic associated fatty liver disease (MAFLD) in non-lean population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eCurrent study enrolled consecutive non-lean (Body Mass Index (BMI)\u0026thinsp;\u0026gt;\u0026thinsp;23 kg/m\u003csup\u003e2\u003c/sup\u003e) patients with MAFLD and available liver biopsy results. Patients were stratified by BMI into two groups for the comparison of their clinical and histological variables, which included the overweight (BMI 23\u0026thinsp;~\u0026thinsp;\u0026lt;\u0026thinsp;28 kg/m2) and the obese (BMI\u0026thinsp;\u0026ge;\u0026thinsp;28 kg/m2). Risk factors for moderate to severe fibrosis (stage\u0026thinsp;\u0026gt;\u0026thinsp;1) were also analysed through the logistic regression model.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 184 non-lean patients with MALFD enrolled, 65 and 119 were overweight and obese, respectively. Patients in the obesity group had a significantly lower level of gamma-Glutamyl transpeptidase (GGT), higher levels of platelet (PLT), Glucose (Glu), prothrombin time (PT), and more common of moderate to severe inflammatory activity when compared to those in the overweight group. However, a significant low frequency of moderate to severe fibrosis was found in the obesity group vs the overweight group (19.33% vs 40.00%, P\u0026thinsp;=\u0026thinsp;0.002). Multivariate logistic regression analysis of fibrosis found that aspartate transaminase (AST), BMI, alanine transaminase (ALT) and cholesterol (CHOL) were independent predictors for moderate to severe fibrosis in non-lean patients with MAFLD. Compared with the traditional FIB-4 (AUC\u0026thinsp;=\u0026thinsp;0.77) and APRI (AUC\u0026thinsp;=\u0026thinsp;0.79) indexes, the combined index based on AST, BMI, ALT and CHOL was more accurated in predicting moderate to severe fibrosis in non-lean patients with MAFLD (AUC\u0026thinsp;=\u0026thinsp;0.87).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eClinical and histological features differed between obesity and overweight patients with MAFLD. When compared to the traditional serum markers, the combination index including AST, BMI, ALT and CHOL provides a better model to predictor moderate to severe fibrosis in non-lean patients with MAFLD.\u003c/p\u003e","manuscriptTitle":"Clinical features of metabolism-related fatty liver disease in the non-lean population","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-09-07 23:05:56","doi":"10.21203/rs.3.rs-2009818/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"20e699d1-dbfa-4bc1-ba74-1baa1b41b33c","owner":[],"postedDate":"September 7th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-09-17T05:39:03+00:00","versionOfRecord":[],"versionCreatedAt":"2022-09-07 23:05:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2009818","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2009818","identity":"rs-2009818","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}