Literature DB >> 34813621

Assessment of non-alcoholic fatty liver disease (NAFLD) severity with novel serum-based markers: A pilot study.

Atul Goyale1, Anjly Jain1, Colette Smith2, Margarita Papatheodoridi3, Marta Guerrero Misas3, Davide Roccarina3, Laura Iogna Prat3, Dimitri P Mikhailidis1, Devaki Nair1, Emmanuel Tsochatzis3.   

Abstract

BACKGROUND/AIMS: Non-alcoholic fatty liver disease (NAFLD) represents a significant public health issue. Identifying patients with simple steatosis from those with non-alcoholic steatohepatitis (NASH) is crucial since NASH is correlated with increased morbidity and mortality. Serum-based markers, including adipokines and cytokines, are important in the pathogenesis and progression of NAFLD. Here we assessed the usefulness of such markers in patients with NAFLD.
METHODS: This prospective, cross-sectional study included 105 adult patients with varying severity of NAFLD. Twelve serum-based markers were measured by 3 biochip platforms and 2 enzyme-linked immunosorbent assay (ELISA) methods. We also developed a NAFLD individual fibrosis index (NIFI) using the serum-based markers mostly correlated with fibrosis severity.
RESULTS: Sixty-one out of 105 patients were male (58.1%) with mean age was 53.5 years. Higher Interleukin-6 (IL-6) increased (p = 0.0321) and lower Matrix Metalloproteinase-9 (MMP-9) serum levels (p = 0.0031) were associated with higher fibrosis as measured by Fibroscan® in multivariable regression analysis. Using receiver-operating characteristic (ROC) curve analysis for the NIFI, area under the curve for predicting Fibroscan values ≥ 7.2 kPa was 0.77 (95%CI: 0.67, 0.88, p<0.001), with sensitivity of 89.3%, specificity of 57.9% and a positive likelihood ratio of 2.8.
CONCLUSIONS: Increasing fibrosis severity in NAFLD is associated with differential expression of IL-6 and MMP-9. NIFI could be valuable for the prediction of advanced NAFLD fibrosis and potentially help avoid unnecessary interventions such as liver biopsy in low-risk patients.

Entities:  

Mesh：

Substances：

Year:  2021        PMID： 34813621      PMCID： PMC8610238          DOI： 10.1371/journal.pone.0260313

Source DB:  PubMed          Journal:  PLoS One        ISSN： 1932-6203            Impact factor:   3.240


Introduction

Non-alcoholic fatty liver disease (NAFLD) is an increasing health issue with a world-wide prevalence of around 25% [1]. In NAFLD, there is accumulation of fat in the liver (>5%) in the absence of other liver disease (e.g. viral and auto-immune hepatitis), significant alcohol consumption, use of steatogenic medication (e.g. amiodarone, methotrexate or isoniazid), and hereditary disorders [2].

NAFLD pathogenesis

The “multiple hit” hypothesis of NAFLD pathogenesis [3] suggests that energy imbalances attributable to excess calorie intake and insufficient exercise lead to increased insulin resistance which serves as a ‘key hit’ on genetically predisposed subjects to induce NAFLD. Further ‘hits’ consist of a combination of hormones secreted from adipose tissue, nutritional factors, gut microbiota in-addition to genetic and epigenetic factors that then contributed to oxidative stress and inflammation aiding the progression of steatosis to non-alcoholic steatohepatitis (NASH) [4]. An estimated 5% of the United Kingdom (UK) population are affected by NASH [5]. Persistent inflammation results in scar tissue formation and progression to fibrosis, which then may progress further to liver cirrhosis, with end-stage liver disease and hepatocellular carcinoma being possible outcomes [6]. Most patients may not progress beyond simple steatosis when picked up early and managed appropriately [5]. Differentiating simple steatosis from NASH is essential in the clinical setting, as simple steatosis has a benign course whereas NASH, in sharp distinction, is associated with reduced life expectancy [7]. Besides, there is increased cardiovascular (CV) risk [8] with myocardial infarction and cerebral vascular accident being the leading causes of morbidity and mortality in the NAFLD population [1].

NAFLD diagnosis and assessment of disease severity

Several diagnostic panels based on a combination of liver tests and clinical parameters such as the NAFLD fibrosis score (age, body mass index (BMI), diabetes status, with aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratio, platelet count and albumin) and FIB-4 score (age, BMI, AST/ALT ratio and platelet count) have been developed to facilitate the non-invasive assessment of NAFLD severity [9]. The Enhanced Liver Fibrosis (ELF) test is an algorithm that combines quantitative serum concentration measurements of three extracellular matrix fibrosis markers (tissue inhibitor of metalloproteinases-1, amino-terminal pro-peptide of type III procollagen and hyaluronic acid) [10] that has shown good correlation with fibrosis stages in chronic liver disease in general and NAFLD specifically [11]. FIB-4 score and the ELF test are used as decision tools in primary care to determine which patients with suspected NAFLD are referred to secondary care, with the latter being utilised when result of the former is equivocal [12]. Although these scoring systems have a greater utility in the detection of advanced fibrosis than liver tests alone, in practice they rarely negate the need for a liver biopsy, which despite its invasive nature and limitations, remains the gold standard [13]. Liver biopsy limitations include the cost as well as the expertise required in obtaining and interpreting a liver biopsy. Additionally, as fibrosis is not evenly distributed throughout the liver, biopsy sampling issues can potentially give rise to incorrect disease severity categorisation. Other considerations include patient acceptance of an invasive procedure and potential complications such pain and bleeding [13]. FibroScan is an accurate and accepted non-invasive tool that employs sound wave technology to measure liver tissue elasticity. It is used in secondary care to evaluate liver steatosis and fibrosis in patients with NAFLD and has shown concordance with liver biopsy results [14]. In practice, NAFLD disease severity is assessed by a combination of the non-invasive clinical, biochemical and sonographic parameters mentioned above with liver biopsy being reserved for patients with suspected progressive or advanced disease.

Role of adipokines and cytokines in NAFLD

The ‘multi-hit’ hypothesis of NAFLD pathogenesis raises the possibility that several potentially quantifiable biochemical imbalances may be present and could be useful clinically. Adipose tissue, now accepted as a metabolically active endocrine organ [15], releases a variety of bioactive cytokines, termed adipokines into the blood stream [7]. These adipokines, central to the communication between adipose tissue and other organs, play a role in the initiation of NAFLD. Adipokines produced by adipose tissue including adiponectin, leptin and resistin play an important role in energy homeostasis [15]. Pro-inflammatory cytokines such as tumour necrosis factor alpha (TNFα) and interleukin-6 (IL-6) are produced by adipocytes, hepatic stellate cells and Kupffer cells as a result of hepatic fat accumulation [16]. These cytokines have immune-modelling functions utilizing signalling pathways involving nuclear receptors such as peroxisome proliferators-activated receptors (PPARs) and play a role in the evolution of NAFLD [16]. Several further related markers [soluble TNF-alpha receptor-1 (sTNFR1), soluble TNF-alpha receptor-2 (sTNFR2), soluble IL-6 receptor (sIL-6R), ghrelin, plasminogen activator inhibitor-1 (PAI-1), cytokeratin-18 fragments, and matrix metalloproteinase-9 (MMP-9)] could play a significant role in NAFLD pathogenesis. These metabolic markers have been the subject of research, often with conflicting results [9,17-28]. These markers were evaluated in the present study. The aim of the present study was to assess the serum levels of 12 metabolic markers [adiponectin, leptin, ghrelin, TNFα, IL-6, PAI-1, cytokeratin-18 fragments, resistin, sIL-6R, sTNFR1, sTNFR2 and MMP-9] in patients with NAFLD and to investigate the potential association of these markers with the severity of fibrosis. A secondary aim was to generate a predictive NAFLD individual fibrosis index (NIFI) based on the markers that showed strongest correlation (positive or negative) with NAFLD severity. Such an index could be used as a predicator of disease severity and possibly help negate the need for liver biopsy in patients with low scores. The NIFI may also help predict progression of NAFLD and any effect of treatment.

Materials and methods

The present prospective, cross-sectional study was performed at The Royal Free London NHS Foundation Trust, a large teaching hospital with a specialist hepatology service. The study, part of a wider study of non-invasive assessment and determinants of liver fibrosis in NAFLD was approved by the University College Hospital: Royal Free Hospital Ethics committee (Reference number: NC2014.006, project as part of the UCL-RFH Biobank Research Tissue Bank, REC reference: 16/WA/0289, Wales Research Ethics Committee 4). Written consent was obtained from all participants. All patients were provided with written information regarding the aims and objective of the study. Blood samples for the measurement of the 12 serum-based markers were collected on enrolment, as part of the study protocol.

Population

Patients (n = 105) with NAFLD attending the Specialist Multidisciplinary NAFLD Liver clinic were enrolled. The diagnosis of NAFLD was based on the presence of fatty liver on ultrasound in patients, who had no history of alcohol misuse (defined as >14 units/week in females or >21 units/week in males) and in whom other causes of liver disease (viral, auto-immune, hereditary haemochromatosis, Wilson’s disease and alcoholic hepatitis) had been excluded with a comprehensive work up. Patients with liver conditions other than NALFD were not included in the present study. Patients with concomitant systemic inflammatory conditions, including rheumatoid arthritis, psoriasis and inflammatory bowel disease were excluded from the study as were patients on immunosuppressive therapy. All included patients were in a stable clinical condition. Data collected included height, weight, renal, liver, bone and lipid profiles as well as a full blood count. Demographic data and co-morbidities (history of conditions such as diabetes mellitus, hypertension, hyperlipidaemia or a history of CV disease) were recorded for all patients. Patients also underwent a liver ultrasound and a fibroscan. Severity of NAFLD was characterized by a combination of clinical, laboratory, radiological and fibroscan findings. Where indicated, patients proceeded to liver biopsy for a histological diagnosis.

Anthropometry assessment

BMI was calculated as weight (in kg)/height (in m2) [29].

General investigations

Liver enzymes and lipids were analysed using standard methods on a Roche Modular P® analyser and Roche® reagents (Roche Diagnostics, GmbH, D-68298 Mannheim, Germany). Platelets were analysed using standard methods on one of 4 Sysmex XN-9000™ analysers (Sysmex America, Illinois, U.S.A). FIB-4 was calculated using the formula [9].

Fibroscan®

Fibroscan® (Echosens, Paris, France) was carried out by experienced examiners (DR and LIP) following a standard protocol in all patients. The median liver stiffness of 10 successful measurements was noted in (kPa). Fibroscan measurements of ≥7.2 kPa were used do define the likely presence of significant fibrosis [30]. The M or XL probe were used as recommended by the device, according to the patient’s anthropometric characteristics, in order to obtain the most optimal measurements. Moreover, controlled attenuated parameter (CAP) has been measured as a marker of steatosis and the cut-off above 302 dB/m has been used to predict steatosis >S1 [31].

Measurement of serum concentrations of serum-based markers

In the present study, blood samples for metabolic marker measurements were collected from consented patients in addition to the blood tests taken as part of their clinic review. Patients were provided information pertaining to the study verbally and in writing, through a detailed patient information leaflet. All blood samples were measured in the morning following an overnight fast. Plasma and serum were separated by centrifugation for 10 min at 3000 revolutions/min (rpm) and then stored at -70°C until the time of analysis. All samples were given a unique non-patient identifiable barcode, ensuring blinding of the researcher.

Biochip assay

Three separate biochip technology systems employing the Randox Investigator™ were used in this study to measure 10 of the metabolic markers in patients’ stored serum samples. The Metabolic Syndrome Array I (leptin, resistin, TNFα, IL-6 and PAI-1), Metabolic Syndrome Array II (adiponectin) and Cytokine Array IV (sIL-6R, sTNFR1, sTNFR2 and MMP-9).

Ghrelin assay

Ghrelin concentrations were measured by competitive solid-phase sandwich enzyme-linked immunosorbent assay (ELISA) tests as per the instructions of the manufacturer (RayBiotech, Norcross, USA) in patients’ stored serum samples.

Keratin-18 assay

Keratin-18 concentrations were measured by quantitative solid-phase sandwich enzyme immunoassay assay (ELISA) tests for the M30 antibody, according to the instructions of the manufacturer (PEVIVA, AB, Sweden) in patients’ stored serum samples. We preferred the M30 to the M65 antibody as the former is specific for apoptotic fragments of keratin-18.

Power calculation

A power calculation for sample size (n) using the formula n = 2σ2 (z1-α/2 + z1-β)2/(μ1 –μ2)2 was performed. Based on confidence level of 95% corresponding to a z1-α/2 value of 2.87 for a p of 0.004. The z1-α/2 value and the p value we selected were adjusted for 12 separate serum-based markers. A sample size calculation with a power of 80%, giving a value for z1-β of 0.84 revealed that an initial sample of 90 patients could be sufficient to achieve statistically significant when comparing the relationship between biomarker concentrations and NAFLD severity. The sample size calculation was based work by Kumar et al. who found higher IL-6 concentrations in patients with more advanced stages of fibrosis; stage III fibrosis compared with stage I fibrosis (560 [523-575] compared with 206 [181-413] pg/ml, respectively [32].

Statistical analysis

Analyses were performed using SAS Version 9.3 (SAS Institute Inc, Cary, NC). The data was checked for normality by Shapiro Wilk test in addition to visual inspection of the distribution of the data. Where required the data was logged and further analysis was performed. Normally distributed numerical data are expressed as mean (standard deviation). For describing the levels of the serum markers across different groups, geometric means (95% confidence intervals, CI) were used. Geometric means are calculated by raising the product of a series of values of the variable to the inverse of the total length of the series. Data that where not normally distributed are reported as median and interquartile range (IQR). Categorical data are presented as number and percentages of patients. Pearson’s chi square test was used for categorical data. Spearman rank test was used for correlations; a two-sided p-value of <0.05 was considered significant. A receiver-operating characteristic (ROC) curve was generated for NIFI against Fibroscan measurements of ≥7.2 kPa in order to generate optimal sensitivity and specificity cut-offs for NIFI.

Results

Demographics and clinical characteristics

Patients (n = 105) with a clinical diagnosis of NAFLD were included in this study. Baseline demographic data and clinical characteristics are shown in Table 1. The mean age was 53.5 ± 13.4 years; 61 patients were male (58.1%). The mean BMI was 32.4 ± 6.1 kg/m2. The rates of pre-existing co-morbidities were as follows: 31 (29.5%) patients had diabetes mellitus, 52 (49.5%) patients had hyperlipidaemia (defined as total cholesterol > 5mmol/L or low-density lipoprotein (LDL) > 3mmol/L) and 50 (47.6%) had hypertension. There was a history of CV disease in 10 (9.5%) patients.
Table 1

Demographic and clinical characteristics of all study patients.

CharacteristicsAll patients, N = 105
Male gender, n (%) 61 (58.1%)
Age, years 53.5 ±13.4
 Age <50 years, n (%)43 (41.0%)
BMI, kg/m 2 32.4 ± 6.1
 BMI <30 kg/m2, n (%)45 (42.9%)
Diabetes mellitus type II, n (%) 31 (29.5%)
Hyperlipidaemia, n (%) 52 (49.5%)
Hypertension, n (%) 50 (47.6%)
History of CVD, n (%) 10 (9.5%)
AST:ALT ratio > 1.00, n (%) 16 (15.2%)
NAFLD Fibrosis Score > -1.455, n (%) 45 (42.9%)
FIB-4 score >1.3, n (%) 42 (47.7%)
Liver stiffness by Fibroscan ≥7.2 kPa, n (%) 47 (44.8%)
CAP measurements >302 dB/m, n (%) 38 (71.7%)

Quantitative variables are presented as Mean ± Standard deviation, and categorical variables as count, n (%).

BMI, Body Mass Index; CVD, cardiovascular disease; AST, aspartate aminotransferase; ALT, alanine aminotransferase; NAFLD, non-alcoholic liver disease; kPa, kilopascal.

Quantitative variables are presented as Mean ± Standard deviation, and categorical variables as count, n (%). BMI, Body Mass Index; CVD, cardiovascular disease; AST, aspartate aminotransferase; ALT, alanine aminotransferase; NAFLD, non-alcoholic liver disease; kPa, kilopascal.

Metabolic markers and demographic characteristics

Adiponectin geometric mean was higher in those aged ≥50 and females. Leptin concentrations were higher in females. IL-6 was higher in persons aged ≥ 50. Resistin, TNFα, PAI-1, sIL-6R, sTNFR1, sTNFR2, MMP9, keratin-18 and ghrelin concentrations did not display any differences with age, BMI or gender (S1 Table).

Correlations of serum-based markers with ALT, AST and Fib-4 score

Although ALT and AST abnormalities are not associated with the presence and severity of NAFLD, a quantitative correlation might still be of value as it can expose trends and associations for further investigation. Adiponectin and leptin did not significantly correlate with ALT, AST or FIB-4 score. Concentrations of resistin, TNFα, IL-6 and ghrelin positively correlated with FIB-4 scores (r = 0.240 [p = 0.030], 0.225 [p = 0.042], 0.276 [p = 0.012] and 0.285 [p = 0.0075]), respectively. However, there was no correlation between these 4 metabolic markers with the ALT or AST activities, from which FIB-4 is generated. The relationship between the 12 metabolic markers and ALT, AST and FIB-4 is displayed in Table 2. Significant negative correlation was found between sIL-6R and AST concentrations (r = -0.243, [p = 0.029]). TNF-alpha receptors 1 and 2 showed significant negative correlation ALT (r = -0.337 [p = 0.0019] and r = -0.348 [p = 0.0013, respectively]). MMP-9 showed significant negative correlations with ALT, AST and FIB-4 (r = -0.288 [p = 0.0087], -0354 [p = 0.001] and -0.327 [p = 0.0027], respectively). PAI-1 showed positive correlation with ALT (r = 0.224 [p = 0.0433]) and negative correlation with Fib-4 (r = -0.326 [p = 0.0028]). Keratin-18 displayed strong positive correlation with ALT (r = 0.462 [p < 0.0001]) and AST (r = 0.448 [p < 0.0001]).
Table 2

Correlations between aspartate aminotransferase (AST), alanine aminotransferase (ALT) serum levels and FIB-4 score with various metabolic markers in 105 study patients.

Spearman correlation coefficients (p-value) are presented for each marker and significant p- values are shown in BOLD font.

ALT (U/L)AST (U/L)FIB-4 score
Median (IQR) 48 (30, 74)33 (28, 46)1.19 (0.77, 1.73)
Correlation coefficients with metabolic markers
Adiponectin (μg/ml) -0.187 (0.096)-0.038 (0.740)0.108 (0.340)
Leptin (ng/ml) -0.015 (0.900)0.071 (0.530)0.034 (0.770)
Resistin (ng/ml) -0.125 (0.260)0.054 (0.630)0.240 (0.030)
TNFα (pg/ml) 0.090 (0.400)0.215 (0.054)0.225 (0.042)
IL-6 (pg/ml) -0.151 (0.180)0.049 (0.660)0.276 (0.012)
PAI-1 (ng/ml) 0.224 (0.043)0.088 (0.434)-0.326 (0.003)
sIL-6R (ng/ml) -0.197 (0.077)-0.243 (0.029)-0.174 (0.120)
sTNFR1 (ng/ml) -0.337 (0.002)-0.213 (0.056)0.020 (0.860)
sTNFR2 (ng/ml) -0.348 (0.001)-0.128 (0.260)0.180 (0.110)
MMP-9 (ng/ml) -0.288 (0.009)-0.354 (0.001)-0.327 (0.003)
Keratin-18 (U/L) 0.462 (<0.001)0.448 (<0.001)0.100 (0.370)
Ghrelin (ng/ml) 0.052 (0.630)0.137 (0.210)0.285 (0.008)

TNFα, Tumour Necrosis Factor alpha; IL-6, Interleukin-6; PAI-1, Plasminogen Activator Inhibitor-1; sIL-6R, Interleukin-6 receptor; sTNFR1, soluble TNFα receptor 1; sTNFR2, soluble TNFα receptor 2; MMP-9, Matrix Metalloproteinase-9.

Correlations between aspartate aminotransferase (AST), alanine aminotransferase (ALT) serum levels and FIB-4 score with various metabolic markers in 105 study patients.

Spearman correlation coefficients (p-value) are presented for each marker and significant p- values are shown in BOLD font. TNFα, Tumour Necrosis Factor alpha; IL-6, Interleukin-6; PAI-1, Plasminogen Activator Inhibitor-1; sIL-6R, Interleukin-6 receptor; sTNFR1, soluble TNFα receptor 1; sTNFR2, soluble TNFα receptor 2; MMP-9, Matrix Metalloproteinase-9.

Serum-based markers and Fibroscan result

Fibroscan results ≥7.2 kPa were significantly associated with increased geometric means of ghrelin, TNFα and IL-6 (p = 0.018, 0.022 and 0.008, respectively). The relationship between the 12 serum-based markers and Fibroscan results is shown in (S2a Table). Lower concentrations of MMP9 were significantly associated with elevated Fibroscan readings (p = 0.005). No significant association was found between Fibroscan results and concentrations of adiponectin, leptin, keratin-18, resistin or any of the 3 soluble receptors (sIL-6R, sTNFR1, and sTNFR2). Moreover, the levels of the 12 serum-based markers were examined in relation to the CAP values; while MMP-9 levels were significantly lower, keratin-18 and ghrelin levels were significantly higher in patients with steatosis >S1 (CAP ≥302dB/m) than those without (S2b Table).

Fibroscan result and demographic characteristics

Multi-variable analysis revealed that age ≥50 years and diabetes were associated with Fibroscan results of ≥7.2 kPa (p = 0.013 and 0.042, respectively). Gender, BMI and history of hyperlipidaemia, hypertension and CV disease did not meet significance in their association with Fibroscan in multivariate analysis, see Table 3a.
Table 3

a. Factors associated with Fibroscan result ≥7.2 kPa. Logistic regression analysis in all study patients (n = 105). b. Multi-variable analysis of factors associated with Fibroscan result ≥7.2 kPa.

Univariable analysisMultivariable analysisUnivariableMultivariable
FactorsOR (95% CI)pOR (95% CI)pOR95% CIpOR95% CIp
Sex Male vs Female 0.67 (0.30, 1.49)0.3231.34 (0.47, 3.80)0.5790.670.30, 1.490.323
Age (years) <50 vs ≥50 0.20 (0.08, 0.50)<0.001 0.24 (0.08, 0.74) 0.013 0.20 0.08, 0.50 0.0006 0.26 0.07, 0.74 0.014
BMI (kg/m 2 ) <30 vs ≥30 0.81 (0.23, 3.21)0.8320.79 (0.18, 3.69)0.7131.070.48, 2.400.870
Diabetes Yes vs No 4.40 (1.79, 10.83)0.001 2.98 (0.95, 9.38) 0.022 4.40 1.79, 10.83 0.001 4.57 1.20, 17.39 0.026
Hyperlipidaemia Yes vs No 2.07 (0.92, 4.70)0.0801.09 (0.38, 3.10)0.874 2.07 0.92, 4.70 0.080 0.660.20, 2.220.502
Hypertension Yes vs No 2.71 (1.19, 6.20)0.0181.29 (0.44, 3.79)0.638 2.71 1.19, 6.20 0.018 1.120.32, 3.930.857
History of CVD Yes vs No 1.66 (0.39, 7.05)0.4940.45 (0.08, 2.65)0.3801.660.39, 7.050.494
Ghrelin Per 1-log higher 1.63 1.07, 2.50 0.024 1.130.63, 2.020.682
TNFα Per 1-log higher 4.50 1.27, 15.93 0.019 2.200.49, 9.860.302
IL-6 Per 1-log higher 2.34 1.25, 4.36 0.008 2.13 1.07, 4.25 0.032
MMP-9 Per 1-log higher 0.34 0.15, 0.76 0.008 0.19 0.06, 0.57 0.003

OR, odds ratio; CI, confidence interval; BMI, Body Mass Index; CVD, cardiovascular disease.

kg, kilograms; m, metre; CVD, cardiovascular disease; TNFα, Tumour Necrosis Factor alpha; IL-6, Interleukin-6; MMP-9, Matrix Metalloproteinase-9.

a. Factors associated with Fibroscan result ≥7.2 kPa. Logistic regression analysis in all study patients (n = 105). b. Multi-variable analysis of factors associated with Fibroscan result ≥7.2 kPa. OR, odds ratio; CI, confidence interval; BMI, Body Mass Index; CVD, cardiovascular disease. kg, kilograms; m, metre; CVD, cardiovascular disease; TNFα, Tumour Necrosis Factor alpha; IL-6, Interleukin-6; MMP-9, Matrix Metalloproteinase-9.

Results from logistic regression model: Multi-variable analysis of Fibroscan, metabolic markers and demographic characteristics

Multi-variable analysis of the relationship between Fibroscan results of ≥7.2 kPa, demographic data and metabolic markers is shown in Table 3b. In order to optimise the multivariate model, only variables with a p <0.10 in univariate analysis were processed in the multivariate model. Age and history of diabetes were associated with Fibroscan results of ≥7.2 kPa (see Table 3a) in the multivariate model that only included demographic characteristics. Age, diabetes, IL-6 and MMP-9 were significantly associated with a stiffness of ≥7.2 kPa in the multivariate model that included both demographic factors and serum-based markers (ghrelin, IL-6, TNFα and MMP-9) (Table 3b). We assessed the association of these 4 metabolic markers (ghrelin, IL-6, TNFα and MMP-9) and their direct association with demographic factors in the multivariable model (S3a–S3d Table) the only significant association found was with IL-6 concentration and increasing age (p = 0.009). The results show that following multivariate analysis, Fibroscan results of ≥7.2 kPa remained significantly associated with increased IL-6 concentrations (p = 0.032) and lower concentrations of MMP-9 (p = 0.003). We also examined whether these factors were associated with Fibroscan results ≥9.6 kPa, indicating advanced fibrosis (S4a and S4b Table). From the multivariable analysis examining only demographic characteristics associated with Fibroscan values ≥9.6 kPa, only age was significantly associated with advanced fibrosis (p = 0.026) (S4a Table), while when serum markers were also added to the model (S4b Table), both age and TNFa were significantly associated with Fibroscan results ≥9.6 kPa (p = 0.026 and p = 0.028, respectively) (S4b Table).

Derivation of NIFI score

IL-6 and MMP-9 were combined to generate the NIFI. This index was derived in a similar way to the homeostatic model assessment for insulin resistance (HOMA-IR), which is based on multiplying the glucose concentration by the insulin concentration and then dividing by a factor (product of mean glucose and insulin values), which normalises to 1.0 [33]. In the current study, as Fibroscan results of ≥7.2 kPa were associated with increased IL-6 concentrations and decreased MMP-9 concentrations, NIFI was calculated by deriving the mean of the reference ranges of IL-6 and MMP-9 [34,35]. The quotient of these two numbers 0.026 (rounded to 2 significant figures), which formed the basis for the divisor to derive a ‘NIFI’, defined as the quotient of IL-6 and MMP-9 divided by 0.026. Using ROC analysis for NIFI, the cuff-off that gave optimal sensitivity and specificity for significant fibrosis was 1.45, with a likelihood ratio of 2.8. At this cut off, sensitivity and specificity were 89.3% and 57.9%, respectively (Fig 1). With ROC curve analysis we can establish a rule-in 90% specificity NIFI cut-off of 3.79 and a rule-out 90% sensitivity NIFI cut-off of 1.41. Of the total 105 patients in the current study, the NIFI of 26 patients (24.8%) was between these two cut-offs, while the proportion of patients with indeterminate results for FIB-4 and NFS were 35 (32.7%) and 24 (22.4%), respectively.
Fig 1

Receiver-operating characteristic (ROC) curves showing area under the curve (AUC) for 105 patients.

The outcome of NAFLD severity (defined by Fibroscan score ≥7.2 kPa) is tested against NAFLD fibrosis index (NIFI), NAFLD fibrosis score (NFS) and FIB-4 score.

Receiver-operating characteristic (ROC) curves showing area under the curve (AUC) for 105 patients.

The outcome of NAFLD severity (defined by Fibroscan score ≥7.2 kPa) is tested against NAFLD fibrosis index (NIFI), NAFLD fibrosis score (NFS) and FIB-4 score. Finally, we examined the diagnostic accuracy of the NIFI cut-offs for significant fibrosis, in comparison to the recommended FIB-4 and NFS dual cut-offs (<1.3/ >2.67 and <-1.455/>0.675, respectively). Of note, FIB-4 cut-offs <1.3 and >2.67 had 66% rule-out sensitivity and 100% rule-in specificity, respectively, as did the NFS dual cut-offs <1.455 and >0.675 for the prediction of significant fibrosis ≥ 7.2kPa.

Discussion

Metabolic markers and NAFLD severity as defined by Fibroscan ≥7.2 kPa

This study investigates a panel of 12 markers in adult NAFLD patients using 3 separate multianalyte platforms as well as 2 ELISA kits. Differences were found in concentrations for a number of metabolic markers in NAFLD patients with more significant disease when compared with those with less severe disease based on fibroscan findings. IL-6 is a pro-inflammatory cytokine adipocyte derived pro-inflammatory cytokine produced by adipocytes and hepatocytes. IL-6 impairs insulin signalling in hepatocytes, increases gluconeogenesis resulting in compensatory hyperinsulinaemia [4]. IL-6 is thought to increase insulin resistance through its inhibition of cytokine signalling [36]. In the present study we found increased IL-6 concentrations in patients with significant fibrosis as evidenced by fibroscan scores which supports the results of previous studies that found higher IL-6 concentrations in NAFLD patients with advanced histological disease [32] as well as showing that sustained exposure to IL-6 sensitises the liver to injury and promotes apoptosis [37]. IL-6 concentrations are raised in a number of systemic inflammatory conditions including rheumatoid arthritis (RA). However, the magnitude of elevation in IL-6 concentrations is many fold higher in these inflammatory conditions than in our NAFLD population [38]. This could reflect that our population group were relatively well and the fact that we had excluded patients with any systemic inflammatory conditions. Despite a relatively healthy patient cohort, we detected a significant difference in IL-6 concentrations between patients with varying NAFLD severity in our study. Elevated IL-6 concentrations are also associated with CV risk. IL-6 has a number of properties that foster development of CV disease, including endothelial cell activation and smooth muscle proliferation [39]. It is possible that our findings simply reflect the increasing CV risk patients with more advanced fibrosis, rather than IL-6 playing a causative role in NAFLD pathogenesis. We did find an association in the multivariable analysis between age and IL-6 concentrations (S3b Table) which could offer another explanation for our findings. Further studies will be needed to elucidate our findings. We did not detect an association between IL-6 concentrations and patients with established CV disease in our NAFLD population, however this was because only 9.5% (Table 1) of our patient group had established CV disease. A number of novel pharmacotherapy agents against NAFLD are in the pipeline such as obeticholic acid (farnesoid X receptor agonist) [40]. IL-6 blockade may offer another potential therapeutic channel for NAFLD treatment. In fact, blockade of IL-6 is the mechanism of action of drugs such as tocilizumab, which is a recombinant humanised anti-human IL-6 receptor monoclonal antibody used in the treatment of rheumatoid arthritis [38]. MMP-9 is a member of a family of zinc-dependent neutral proteases that degrade the extracellular matrix and basement membrane and has been implicated in sinusoidal injury in liver failure, liver remodelling and necrosis [23]. Previously, there have been no direct studies in NAFLD patients assessing the role of MMP-9 which is involved in liver injury and remodeling [23]. The present study shows a decrease in MMP-9 with more advanced fibrosis, these findings are consistent with a previous study that revealed lower concentrations of MMP-9 in hepatitis C patients with advanced fibrosis [41]. A similar pathophysiological involvement of this protease in the fibrogenesis underlying the progression of NAFLD may be an explanation. IL-6 and MMP-9 results in this study may reflect the two important pathological processes underlying NAFLD, inflammation and fibrosis, respectively. Thus, combining the 2 markers to generate the NIFI may give superior predictive outcomes for disease severity than a single marker alone. There is a need to prospectively evaluate this index. Whether this index is superior to the currently employed FIB-4 and ELF score needs to be determined. Where such an index would fit into the diagnostic and management pathway for NAFLD would also need to be assessed. The NIFI marker may potentially enable assessment of patients with NAFLD at more frequent intervals than is possible with serial liver biopsies due to the invasive nature of the procedure as well as the logistical and financial considerations involved in obtaining and interpreting a liver biopsy. It may also overcome the sampling issues associated with liver biopsy where there is a potential of misclassification due to the fact that fibrosis is not evenly distributed throughout the liver. Ghrelin and TNFα concentrations in this study were positively associated with more advance fibrosis as evidenced by Fibroscan values. These findings are in agreement with previous studies but were not significant after multivariate analysis. In fact, by multivariate analysis, only IL-6 and MMP9 were independently associated with fibrosis. An explanation for this may be the population size in the present study. This study did not find significantly different concentrations of adiponectin, leptin, resistin or PAI-1 in patients with varying stages of NAFLD as evidenced by fibroscan scores. These metabolic markers have previously been shown to play a role in NAFLD, but our study findings are not unique as other researchers have also failed to find an association [21,26-28]. Again, this may be a due to the size of the present study. In the present study, no significant difference was found between keratin-18 concentration and increased fibroscan values. This is contrary to previous studies [25,42,43] and a recent systematic review [44] exploring the role of keratin-18 for fibrosis in NAFLD. The reason for this is not clear but could be due to a type 2 error and our sample size or how the data was categorised in the current study. Keratin-18 serum levels were indeed higher in the patients with fibroscan value ≥7.2 kPa but did not reach statistical significance. Comparing the continuous serum-based markers data with categorised Fibroscan results rather than continuous fibroscan scores could be an explanation for not detecting an association with keratin-18 and indeed some of the other markers that did not reach statistical significance. This study did not find significantly different concentrations of sIL-6R, sTNFR1 or sTNFR2 with fibroscan ≥7.2 kPa. Although a previous study found increased concentrations the sIL-6R and sTNFR1 in NAFLD patients compared with healthy volunteers [45], this is the first study investigating these 3 receptors in different stages of NAFLD. The correlation found in the current study with these receptors and liver aminotransferases (Table 2) is consistent with the findings the pervious study mentioned above [45].

Study limitations

The limitations of the current study included a lack of patients who had a liver biopsy; hence a lack of a gold standard to which the NIFI can be compared. We also had relatively few patients with established cardiovascular disease which is the leading cause for mortality in the NAFLD population, and this may be the reason why we did not find an association between the serum-based markers and history of cardiovascular disease. The current study serum-based markers were not measured and compared to matched healthy population.

Conclusions

IL-6 and MMP-9 are differentially expressed with increasing severity of NAFLD. Although further validation studies are needed, the NIFI, in combination with Fibroscan, could potentially serve as a marker for NAFLD severity and could prove to be a more acceptable and cost-effective alternative to liver biopsy. Given the role played in cardiovascular disease by the constituent markers of the NIFI, it could also potentially, serve as a predictor of vascular risk.

Geometric mean (95% CI) levels of serum-based markers, according to demographic factors.

(DOCX) Click here for additional data file. a. Geometric Mean (95% CI) levels of serum-based markers, according to Fibroscan result. p-values calculated using unpaired t-test (of log values)–no formal correction made for multiple testing. b. Geometric Mean (95% CI) levels of serum-based markers, according to CAP result. p-values calculated using unpaired t-test (of log values)–no formal correction made for multiple testing. (DOCX) Click here for additional data file. a. Demographic factors associated with ghrelin concentrations in multivariable model. Results from linear regression model (log scale). Fit of model determined by examination of Pearson residual plots. b. Demographic factors associated with interleukin-6 (IL-6) concentrations in multivariable model. Results from linear regression model (log scale). Fit of model determined by examination of Pearson residual plots. c. Demographic factors associated with tumor necrosis factor a (TNFa) concentrations in multivariable model. Results from linear regression model (log scale). Fit of model determined by examination of Pearson residual plots. d. Demographic factors associated with metalloproteinase 9 (MMP9) concentrations in multivariable model. Results from linear regression model (log scale). Fit of model determined by examination of Pearson residual plots. (DOCX) Click here for additional data file. a. Factors associated with Fibroscan result ≥9.6 kPa. Logistic regression analysis in all study patients. b. Multi-variable analysis of factors associated with Fibroscan result ≥9.6 kPa in all study patients. (DOCX) Click here for additional data file. (DOCX) Click here for additional data file.

Dataset table.

(XLSX) Click here for additional data file. 18 Aug 2021 PONE-D-21-17417 Assessment of Non-alcoholic Fatty Liver Disease (NAFLD) severity with novel metabolic markers: A Pilot Study PLOS ONE Dear Dr. Papatheodoridi, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. While both reviewers evaluated your work as potentially interesting, they also described several important issues that need to be addressed. Please submit your revised manuscript by Sep 23 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Pavel Strnad Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2.  Thank you for submitting the above manuscript to PLOS ONE. During our internal evaluation of the manuscript, we found significant text overlap between your submission and the following previously published works. - https://linkinghub.elsevier.com/retrieve/pii/S002191501830491X - https://journals.sagepub.com/doi/full/10.1177/0004563214523739 We would like to make you aware that copying extracts from previous publications, especially outside the methods section, word-for-word is unacceptable, even for works which you authored. In addition, the reproduction of text from published reports has implications for the copyright that may apply to the publications. Please revise the manuscript to rephrase the duplicated text, cite your sources, and provide details as to how the current manuscript advances on previous work. Please note that further consideration is dependent on the submission of a manuscript that addresses these concerns about the overlap in text with published work. We will carefully review your manuscript upon resubmission, so please ensure that your revision is thorough. 3. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For more information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. In your revised cover letter, please address the following prompts: a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially sensitive information, data are owned by a third-party organization, etc.) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent. b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories. We will update your Data Availability statement on your behalf to reflect the information you provide. 4. Please note that in order to use the direct billing option the corresponding author must be affiliated with the chosen institute. Please either amend your manuscript to change the affiliation or corresponding author, or email us at plosone@plos.org with a request to remove this option. 5. Please include a copy of Table 4A which you refer to in your text on page 17. 6. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Partly ********** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ********** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ********** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ********** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: Goyale et al. analysed 12 different adipokines and cytokines as biomarker in a cohort of 105 clinically diagnosed NAFLD patients. The manuscript is well written. The method section includes a detailed description of the statistical analysis including a power analysis for this study. IL-6 significantly increased and MMP9 significantly decreased with increasing fibrosis severity as determined by Fibroscan. A newly generated NAFLD individual fibrosis index (NIFI) showed a good sensitivity, but a mediocre specificity for fibrosis severity. No validation data are available for NIFI. Results of IL-6 and MMP9 are of interest for better understanding of disease progression. Please find my comments below: Major comments: - in Table 1 NFS is depicted, but no data for FIB-4. How many patients had a FIB-4 >1.3? - Are there also data for CAP measurements available in this cohort? - Univariate and multivariate analysis were performed for factors associated with Fibroscan > 7.2kPa. Was univariate and multivariate analysis also performed for further Fibroscan levels, e.g. Fibroscan> 9.6kPa for advanced disease? - In this study no significant associations between adiponectin, leptin, resistin or PAI-1 and liver fibrosis was found. Were these metabolic markers also analysed with “metabolic” disease feature, e.g. CAP values? - Figure 1: Only ROC of NIFI is depicted. Further ROCs for FIB-4 and NFS in the analysed cohort should be added. - Higher IL-6 leves were significantly associated to Fibroscan > 7.2kPa. Are there any data for other inflammatory markers available? e.g. hsCRP as another inflammatory marker that is associated with CVD events? - Follow-up data for this patient cohort would be interesting to see the development of NIFI over time. - Further validation cohort for NIFI were desirable. Minor comments: - In the Method section inclusion and exclusion criteria were described, but in line 115 only patients on TNF a inhibitor therapy were mentioned as excluded. How about other patients with immunosuppressive treatment? Were they also excluded? - line 366: Elafibranor has failed the phase 3 study. Please update this sentence - line317: calculated… Reviewer #2: In the present study the authors investigated 12 blood markers in patients with non-biopsy-proven NAFLD (n=105). They found that IL-6 and MMP-9 blood levels were associated with higher VCTE values (≥ 7.2 kPa). Based on this finding they established an index (NIFI) which predicted VCTE ≥ 7.2 kPa with moderate AUC (0.77). To improve the clinical relevance of the study, the following points should be addressed: 1) The marker panel represents not only metabolic parameters but also markers of inflammation, cell death and fibrosis. The term “metabolic markers” is therefore not correct and should be replaced. 2) The authors should provide information whether they used serum or plasma for the analyses of the different markers. 3) The term “geometric mean” should be explained. 4) It remains unclear which keratin-18 assay (M30 or M65 ELISA) was used. The authors should also provide information about the role of K18 biomarkers in NAFLD and explain why, e.g., the M30 was preferred over the M65 biomarker. The term cytokeratin-18 is no longer used and should be replaced with keratin-18. 5) For VCTE, cut-off values of 8 kPa and 12 kPa are recommended for risk stratification, i.e. rule out or rule in advanced fibrosis, in NAFLD (EASL Clinical Practice Guidelines on non-invasive tests for evaluation of liver disease severity and prognosis – 2021 update; J Hepatol 2021). The authors should therefore use these cut-off values for their analyses. It would be interesting to analyze how the markers correlate with advanced NAFLD. In this respect the different markers should be compared with VCTE values above and below 8 kPa or 12 kPa. 6) Since FIB-4 or NFS are recommended for risk stratification of NAFLD in primary care, the evaluated markers should also be compared with FIB-4 values above and below 1.3 or 2.67 and NFS values above and below -1.455 or 0.675. 7) If histological data obtained from a liver biopsy closely performed to the measurement of the blood markers are available, a sub-analysis comparing the different markers with the diagnosis NASH versus NAFL as well as with the NAFLD activity and the single NAS components and fibrosis stages would be interesting. 8) Aminotransferase levels are not suitable for the detection of disease activity in NAFLD, e.g. a significant proportion of NASH patients reveal normal aminotransferase levels despite progressed NAFLD. A correlation of the markers with aminotransferases is therefore less informative which should be considered and discussed. 9) The authors stated that VCTE ≥7.2 kPa was significantly associated with increased IL-6 concentrations and lower MMP-9 concentrations. However, in table 3b, it is indicated that similarly to IL-6, MMP-9 levels per 1-log “higher” were significantly associated with VCTE ≥ 7.2 kPa, which should be clarified. 10) Since more than 50% of patients reveal a BMI of > 30, more information about the success rate and quality criteria are required for VCTE measurements with the M probe in this patient cohort. It should be mentioned whether XL-probe was available or not. 11) More information about the calculation of the NIFI index is required. HOMA-IR calculation was firstly described 1985 by Matthews D.R. et al. in Diabetologia. The authors should refer to this publication with respect to the citation of HOMA-IR calculation. In addition to sensitivity and specificity, information about the PPV and NPV should be provided. The specificity of this index is rather low and the AUC remains below 0.8. Moreover, ~25% of patients remain between the 2 selected cut-offs. To further evaluate the diagnostic performance of the NIFI index, it should be compared to FIB-4 and NFS. Information about the number of NAFLD patients with intermediate results for FIB-4 or NFS should be provided. 12) In the abstract (results), information about the outcome prediction by ROC, i.e. VCTE ≥ 7.2 kPa, is missing. 13) The markers evaluated in this study should be simultaneously compared in matched healthy individuals. 14) Further corrections required: page 19, lane 317: NIFI was calculated by…. Page 22, lane 394, page 23, lane 404 and 408: fibroscan values (instead of scores). Reference 25: Feldstein et al. Page 24: The current study metabolic markers were not measured (in the current study…). Some reference numbers are in bold. ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. 11 Oct 2021 Manuscript Ref. PONE-D-21-17417 Dear Dr Strnad, We would like to thank you for giving us the opportunity to submit a revised version of our manuscript entitled “Assessment of non-alcoholic fatty liver disease (NAFLD) severity with novel serum based markers: A Pilot Study” for consideration for publication in Plos One journal. We appreciate the time and effort that you and the reviewers dedicated to providing feedback on our manuscript and are grateful for the insightful comments and valuable improvements to our paper. We believe that after completion of the suggested edits, the revised manuscript has benefitted from an improvement in overall presentation and clarity. To this end, we have incorporated the suggestions made by the reviewers to the best extent possible. Those changes are underlined within the main manuscript as well as supplementary material. In addition, we have now provided our dataset as a separate supplementary file, as requested and we would like to have our data availability status updated. In our revised main manuscript and supplementary material, you will find all the changes/new additions in red font. Below you will find, in blue, a point-by-point response to the reviewers’ comments and concerns. All page numbers refer to the revised manuscript files. Journal Requirements When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf We would like to thank you for your comment. We have now updated our manuscript format according to the journal’s requirements. 2. Thank you for submitting the above manuscript to PLOS ONE. During our internal evaluation of the manuscript, we found significant text overlap between your submission and the following previously published works. - https://linkinghub.elsevier.com/retrieve/pii/S002191501830491X - https://journals.sagepub.com/doi/full/10.1177/0004563214523739 We would like to make you aware that copying extracts from previous publications, especially outside the methods section, word-for-word is unacceptable, even for works which you authored. In addition, the reproduction of text from published reports has implications for the copyright that may apply to the publications. Please revise the manuscript to rephrase the duplicated text, cite your sources, and provide details as to how the current manuscript advances on previous work. Please note that further consideration is dependent on the submission of a manuscript that addresses these concerns about the overlap in text with published work. We will carefully review your manuscript upon resubmission, so please ensure that your revision is thorough. Thank you for this comment. The first linked publication refers to an abstract presented by us in an international congress showing the results of the work that is fully described in this manuscript. Therefore, we do not consider that this may constitute plagiarism. If you still consider we should rephrase our abstract, we can happily make the necessary changes. With regards to the second linked file, this is on an entirely different topic. We read through the manuscript but we could not detect any similarities. We would be grateful if you could point these out. 3. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For more information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. In your revised cover letter, please address the following prompts: a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially sensitive information, data are owned by a third-party organization, etc.) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent. b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories. We will update your Data Availability statement on your behalf to reflect the information you provide. Thank you for the opportunity to share our data. We have now uploaded our dataset as Supporting information and we would like to have our data availability status updated. 4. Please note that in order to use the direct billing option the corresponding author must be affiliated with the chosen institute. Please either amend your manuscript to change the affiliation or corresponding author or email us at plosone@plos.org with a request to remove this option. The corresponding author, Prof. E. Tsochatzis, is affiliated to UCL. Please let us know if you require further information. 5. Please include a copy of Table 4A which you refer to in your text on page 17. Thank you for pinpointing this typo. The table referred to at this point is Table 3a and there is no Table 4a for this manuscript. We have now changed this in our main manuscript, page 15. 6. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information. Thank you for this comment. We have now amended the issues with in-text citations and reference style, while you may find the captions for the Supporting information at the end of our main manuscript. Reviewers’ Comments to the Author Reviewer #1: Goyale et al. analysed 12 different adipokines and cytokines as biomarker in a cohort of 105 clinically diagnosed NAFLD patients. The manuscript is well written. The method section includes a detailed description of the statistical analysis including a power analysis for this study. IL-6 significantly increased and MMP9 significantly decreased with increasing fibrosis severity as determined by Fibroscan. A newly generated NAFLD individual fibrosis index (NIFI) showed a good sensitivity, but a mediocre specificity for fibrosis severity. No validation data are available for NIFI. Results of IL-6 and MMP9 are of interest for better understanding of disease progression. Please find my comments below: Major comments: - in Table 1 NFS is depicted, but no data for FIB-4. How many patients had a FIB-4 >1.3? Thank you for your comment. Number of patients (%) who had FIB-4 > 1.3 has been now added in Table 1 (page 11-12). - Are there also data for CAP measurements available in this cohort? Thank for raising this point. Yes, there are data for CAP measurements in this cohort. Number of patients (%) who had CAP >302 dB/m has been now added in Table 1 (page 12), as this cut-off has been considered to predict S1 steatosis and it is explained in Methods section (ref 31) (page 8). - Univariate and multivariate analysis were performed for factors associated with Fibroscan > 7.2kPa. Was univariate and multivariate analysis also performed for further Fibroscan levels, e.g. Fibroscan> 9.6kPa for advanced disease? Thank for this comment. We have now performed univariate and multivariate analysis for factors associated with Fibroscan> 9.6kPa for advanced fibrosis and this is now presented in S4a and S4b Tables. Moreover, we discussed the findings of this analysis on page 16 of our main manuscript. - In this study no significant associations between adiponectin, leptin, resistin or PAI-1 and liver fibrosis was found. Were these metabolic markers also analysed with “metabolic” disease feature, e.g. CAP values? We would like to thank for this comment. We have now analysed all the metabolic and other serum markers in relation to CAP values and this analysis can be now found in Table S2b and page 14 of the main manuscript. - Figure 1: Only ROC of NIFI is depicted. Further ROCs for FIB-4 and NFS in the analysed cohort should be added. Thank you for this comment. This is now added in the updated Figure 1, pages 17-18 of the main manuscript. - Higher IL-6 levels were significantly associated to Fibroscan > 7.2kPa. Are there any data for other inflammatory markers available? e.g. hsCRP as another inflammatory marker that is associated with CVD events? We understand that examining more inflammatory markers would be optimal, however we do not have enough available data regarding other inflammatory markers, such as hsCRP, in our dataset. - Follow-up data for this patient cohort would be interesting to see the development of NIFI over time. We agree with the reviewer that follow-up data would be needed to assess the development of NIFI over time. This is this is a prospective cohort, however no clinical events have been developed to date. We have not performed repeat measurements of the biomarkers to date but we will certainly do in the future. - Further validation cohort for NIFI were desirable. We agree with the reviewer at this point and we have already mentioned this issue as a limitation in our discussion section. Minor comments: - In the Method section inclusion and exclusion criteria were described, but in line 115 only patients on TNFa inhibitor therapy were mentioned as excluded. How about other patients with immunosuppressive treatment? Were they also excluded? Thank you for giving us the opportunity to clarify this. All patients on immunosuppressive therapy were excluded. This is now updated on page 7 of the main manuscript. - line 366: Elafibranor has failed the phase 3 study. Please update this sentence. Thank you for pinpointing this out. This has been now removed from the sentence on page 20 of the main manuscript. - line317: calculated… Thank you for pinpointing this mistake. We have now corrected the typo on page 27. Reviewer #2: In the present study the authors investigated 12 blood markers in patients with non-biopsy-proven NAFLD (n=105). They found that IL-6 and MMP-9 blood levels were associated with higher VCTE values (≥ 7.2 kPa). Based on this finding they established an index (NIFI) which predicted VCTE ≥ 7.2 kPa with moderate AUC (0.77). To improve the clinical relevance of the study, the following points should be addressed: 1) The marker panel represents not only metabolic parameters but also markers of inflammation, cell death and fibrosis. The term “metabolic markers” is therefore not correct and should be replaced. Thank you for this comment. We have now updated the term “metabolic markers” with serum-based markers, which can better reflect the wide spectrum of the different markers assessed in our study. This has been changed throughout the main manuscript and supporting information. 2) The authors should provide information whether they used serum or plasma for the analyses of the different markers. Serum samples were used for the analysis of these markers and this is now clarified in page 9 of the main manuscript. 3) The term “geometric mean” should be explained. Thank you for this comment. The term “geometric mean” is now described on page 10 of the main manuscript. 4) It remains unclear which keratin-18 assay (M30 or M65 ELISA) was used. The authors should also provide information about the role of K18 biomarkers in NAFLD and explain why, e.g., the M30 was preferred over the M65 biomarker. The term cytokeratin-18 is no longer used and should be replaced with keratin-18. Thank you for this comment. We used the M30 assay and this is now clarified in the methods section in page 11. The term cytokeratin-18 has been replaced by the term keratin-18 as requested. The M30 antibody identifies a fragmented form of keratin 18, which is an apoptosis-specific neo-epitope at the keratin aspartic acid residue 396, generated by caspase-6, caspase-3 and caspase-7 cleavage. The M65 antibody allows for measurement of all keratin 18 fragments because of loss of cell membrane integrity from necrosis and/or apoptosis. The relevant mechanism of injury in NAFLD is apoptosis, therefore we used the M30 assay also in line with several other studies on the topic. 5) For VCTE, cut-off values of 8 kPa and 12 kPa are recommended for risk stratification, i.e. rule out or rule in advanced fibrosis, in NAFLD (EASL Clinical Practice Guidelines on non-invasive tests for evaluation of liver disease severity and prognosis – 2021 update; J Hepatol 2021). The authors should therefore use these cut-off values for their analyses. It would be interesting to analyze how the markers correlate with advanced NAFLD. In this respect the different markers should be compared with VCTE values above and below 8 kPa or 12 kPa. Thank you for this comment. We were looking for significant rather than advanced fibrosis and therefore used the 7.2 KPa cut-off. We have now analysed the 9.6 cut-off for advanced fibrosis as requested by reviewer 1, and this is included in the S4a and S4b Tables while it is discussed on page 20 of the main manuscript. We used a single TE cut-off (with maximum combined se and sp) based in published literature rather than the rule-in and rule-out cut-offs that we recently described in a publication. 6) Since FIB-4 or NFS are recommended for risk stratification of NAFLD in primary care, the evaluated markers should also be compared with FIB-4 values above and below 1.3 or 2.67 and NFS values above and below -1.455 or 0.675. We would like to thank you for this comment. This is a secondary care cohort and most patients already had FIB4 >1.3 before referral from primary care. Moreover, our newly developed NIFI index aims to predict significant rather than advanced fibrosis. Taking into account these caveats, we did perform an analysis which shows that the sensitivity levels to rule-out significant fibrosis are much lower (66%) than NIFI for both FIB-4 and NFS, while the rule-in specificity reaches 100%. This sounds reasonable, as these cut-offs were initially optimised for predicting advanced but not significant fibrosis. This is now discussed in Results section, page 18. 7) If histological data obtained from a liver biopsy closely performed to the measurement of the blood markers are available, a sub-analysis comparing the different markers with the diagnosis NASH versus NAFL as well as with the NAFLD activity and the single NAS components and fibrosis stages would be interesting. We agree with the reviewer that this would be an interesting sub-analysis. However, unfortunately we do not have enough histological data for such analysis. 8) Aminotransferase levels are not suitable for the detection of disease activity in NAFLD, e.g. a significant proportion of NASH patients reveal normal aminotransferase levels despite progressed NAFLD. A correlation of the markers with aminotransferases is therefore less informative which should be considered and discussed. We certainly agree with this comment – it is also possible that the normal levels in NAFLD are lower than what is commonly accepted. However, we use the transaminases as continuous variables and we do think that these correlations are of relative value. We briefly discuss this on page 12 of the main manuscript. 9) The authors stated that VCTE ≥7.2 kPa was significantly associated with increased IL-6 concentrations and lower MMP-9 concentrations. However, in table 3b, it is indicated that similarly to IL-6, MMP-9 levels per 1-log “higher” were significantly associated with VCTE ≥ 7.2 kPa, which should be clarified. As presented in table 3b, higher levels of log10 IL-6 were significantly and positively associated with VCTE ≥ 7.2 kPa (OR:2.34, p=0.008), while higher levels of log10 MMP-9 were significantly but inversely associated with VCTE ≥7.2 kPa (OR 0.34, p=0.008). 10) Since more than 50% of patients reveal a BMI of > 30, more information about the success rate and quality criteria are required for VCTE measurements with the M probe in this patient cohort. It should be mentioned whether XL-probe was available or not. XL probe was available and performed as recommended by the device. This is now clarified in methods section, page 8. 11) More information about the calculation of the NIFI index is required. HOMA-IR calculation was firstly described 1985 by Matthews D.R. et al. in Diabetologia. The authors should refer to this publication with respect to the citation of HOMA-IR calculation. In addition to sensitivity and specificity, information about the PPV and NPV should be provided. The specificity of this index is rather low and the AUC remains below 0.8. Moreover, ~25% of patients remain between the 2 selected cut-offs. To further evaluate the diagnostic performance of the NIFI index, it should be compared to FIB-4 and NFS. Information about the number of NAFLD patients with intermediate results for FIB-4 or NFS should be provided. Thank you for this comment. This is now presented in the updated Figure 1 (page 17-18), which includes the ROC curves for FIB-4 and NFS, as requested by the reviewer 1 as well. As it is shown, FIB-4 and NFS have a lower AUC than NIFI. Number of patients with intermediate results for both FIB-4 and NFS are now provided in results section page 17. 12) In the abstract (results), information about the outcome prediction by ROC, i.e. VCTE ≥ 7.2 kPa, is missing. Thank you for this comment. We have now added the relevant findings (page 2). 13) The markers evaluated in this study should be simultaneously compared in matched healthy individuals. We agree that it would be interesting to compare the levels of these markers between NAFLD and healthy individuals. However, we have not included any healthy individuals in this cohort. 14) Further corrections required: page 19, lane 317: NIFI was calculated by…. Page 22, lane 394, page 23, lane 404 and 408: fibroscan values (instead of scores). Reference 25: Feldstein et al. Page 24: The current study metabolic markers were not measured (in the current study…). Some reference numbers are in bold. Thank you for pinpointing these mistakes. We have now made all necessary corrections in our revised manuscript. Submitted filename: Response to Reviewers 22092021.docx Click here for additional data file. 3 Nov 2021 PONE-D-21-17417R1Assessment of Non-alcoholic Fatty Liver Disease (NAFLD) severity with novel serum-based markers: A Pilot StudyPLOS ONE Dear Dr. Papatheodoridi, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. As you can see, both reviewers were satisfied with the improvements that you made and only minor changes are required at this stage. Please submit your revised manuscript by Dec 18 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript:If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Pavel Strnad Academic Editor PLOS ONE Journal Requirements: Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: (No Response) Reviewer #2: (No Response) ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ********** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: The authors addressed the majority of the raised comments in their revision and performed the suggested additional analyses. The manuscript has improved by this revision. Reviewer #2: The comments of the reviewers have been mainly addressed; however, some minor corrections are still required: 1. Discussion page 22: "a recent systemic review...." replace reference 41 with reference 42. 2. Discussion page 22: "This is contrary to previous studies and a recent systemic review exploring the role keratin-18 in NAFLD". This sentence should be corrected since the mentioned study (not studies) or review article did not evaluate or discuss an association of keratin-18 with fibroscan values but of keratin-18 fragments with histological fibrosis. It would be better to write “the role of keratin-18 for fibrosis in NAFLD”. Further studies indicating a correlation of keratin-18 fragments with fibrosis progression in NAFLD might be considered (Tamimi T et al., J Hepatol 2011; 54:1224-29; Diab DL et al., Clinical Gastroenterol Hepatol 2008; 6(11):1249-54). 3. S1 and S2aTables: Replace Cytokeratin-18 with Keratin-18. ********** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. 4 Nov 2021 RESPONSE TO REVIEWERS Manuscript Ref. PONE-D-21-17417 Dear Dr Strnad, We would like to thank you for your consideration of our manuscript entitled “Assessment of non-alcoholic fatty liver disease (NAFLD) severity with novel serum based markers: A Pilot Study” with minor revisions. We have tried to address all comments from the reviewers and we are looking forward to your final decision regarding the publication of our study. Below you will find, in blue, a point-by-point response to the reviewers’ comments and concerns. All page numbers refer to the revised manuscript files. In our revised main manuscript and supplementary material, you will find all the changes/new additions in red font. Journal Requirements Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. We have reviewed our reference list carefully and we have not found any retracted article. We have now revised the order of the citations, following the addition of 2 more references, according to Reviewer’s comment no 2, as you will see in the revised manuscript. Reviewers’ Comments to the Author Reviewer #1: The authors addressed the majority of the raised comments in their revision and performed the suggested additional analyses. The manuscript has improved by this revision. Reviewer #2: The comments of the reviewers have been mainly addressed; however, some minor corrections are still required: 1. Discussion page 22: "a recent systemic review...." replace reference 41 with reference 42. Thank you for your comment. We have now corrected this to cite the correct study, which is no 44 in the updated reference list, after the additions mentioned in the next comment. 2. Discussion page 22: "This is contrary to previous studies and a recent systemic review exploring the role keratin-18 in NAFLD". This sentence should be corrected since the mentioned study (not studies) or review article did not evaluate or discuss an association of keratin-18 with fibroscan values but of keratin-18 fragments with histological fibrosis. It would be better to write “the role of keratin-18 for fibrosis in NAFLD”. Further studies indicating a correlation of keratin-18 fragments with fibrosis progression in NAFLD might be considered (Tamimi T et al., J Hepatol 2011; 54:1224-29; Diab DL et al., Clinical Gastroenterol Hepatol 2008; 6(11):1249-54). Thank you for this comment. We have now updated this part of our discussion and we have added the suggested references as requested, (ref no 42, 43). 3. S1 and S2aTables: Replace Cytokeratin-18 with Keratin-18. Thank you for this comment. We have now amended the typo in the updated Suppl. Material. Submitted filename: Response to reviewers.docx Click here for additional data file. 8 Nov 2021 Assessment of Non-alcoholic Fatty Liver Disease (NAFLD) severity with novel serum-based markers: A Pilot Study PONE-D-21-17417R2 Dear Dr. Papatheodoridi, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Pavel Strnad Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: 15 Nov 2021 PONE-D-21-17417R2 Assessment of Non-alcoholic Fatty Liver Disease (NAFLD) severity with novel serum-based markers: A Pilot Study Dear Dr. Papatheodoridi: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Pavel Strnad Academic Editor PLOS ONE
  42 in total

1.  Prospective evaluation of a primary care referral pathway for patients with non-alcoholic fatty liver disease.

Authors:  Ankur Srivastava; Ruth Gailer; Sudeep Tanwar; Paul Trembling; Julie Parkes; Alison Rodger; Deepak Suri; Douglas Thorburn; Karen Sennett; Sarah Morgan; Emmanuel A Tsochatzis; William Rosenberg
Journal:  J Hepatol       Date:  2019-04-06       Impact factor: 25.083

Review 2.  Adipokines and proinflammatory cytokines, the key mediators in the pathogenesis of nonalcoholic fatty liver disease.

Authors:  Sanja Stojsavljević; Marija Gomerčić Palčić; Lucija Virović Jukić; Lea Smirčić Duvnjak; Marko Duvnjak
Journal:  World J Gastroenterol       Date:  2014-12-28       Impact factor: 5.742

Review 3.  The use of statins alone, or in combination with pioglitazone and other drugs, for the treatment of non-alcoholic fatty liver disease/non-alcoholic steatohepatitis and related cardiovascular risk. An Expert Panel Statement.

Authors:  Vasilios G Athyros; Theodore K Alexandrides; Helen Bilianou; Evangelos Cholongitas; Michael Doumas; Emmanuel S Ganotakis; John Goudevenos; Moses S Elisaf; Georgios Germanidis; Olga Giouleme; Asterios Karagiannis; Charalambos Karvounis; Niki Katsiki; Vasilios Kotsis; Jannis Kountouras; Evangelos Liberopoulos; Christos Pitsavos; Stergios Polyzos; Loukianos S Rallidis; Dimitrios Richter; Apostolos G Tsapas; Alexandros D Tselepis; Konstantinos Tsioufis; Konstantinos Tziomalos; Themistoklis Tzotzas; Themistoklis G Vasiliadis; Charalambos Vlachopoulos; Dimitri P Mikhailidis; Christos Mantzoros
Journal:  Metabolism       Date:  2017-03-04       Impact factor: 8.694

Review 4.  Adiponectin: a key player in obesity related disorders.

Authors:  Yuji Matsuzawa
Journal:  Curr Pharm Des       Date:  2010-06       Impact factor: 3.116

5.  Metabolic and adipokine profile of Chinese patients with nonalcoholic fatty liver disease.

Authors:  Vincent Wai-Sun Wong; Alex Yui Hui; Steven Woon-Choy Tsang; Joyce Lai-Yee Chan; Ada Mei-Ling Tse; Kui-Fat Chan; Wing-Yee So; Angela Yuen-Shan Cheng; Wing-Fung Ng; Grace Lai-Hung Wong; Joseph Jao-Yiu Sung; Henry Lik-Yuen Chan
Journal:  Clin Gastroenterol Hepatol       Date:  2006-08-14       Impact factor: 11.382

6.  Assessment of hepatic steatosis by controlled attenuation parameter using the M and XL probes: an individual patient data meta-analysis.

Authors:  David Petroff; Valentin Blank; Philip N Newsome; Cosmin Sebastian Voican; Maja Thiele; Victor de Lédinghen; Stephan Baumeler; Wah Kheong Chan; Gabriel Perlemuter; Ana-Carolina Cardoso; Sandeep Aggarwal; Magali Sasso; Peter J Eddowes; Michael Allison; Emmanuel Tsochatzis; Quentin M Anstee; David Sheridan; Jeremy F Cobbold; Sylvie Naveau; Monica Lupsor-Platon; Sebastian Mueller; Aleksander Krag; Marie Irles-Depe; David Semela; Grace Lai-Hung Wong; Vincent Wai-Sun Wong; Cristiane A Villela-Nogueira; Harshit Garg; Olivier Chazouillères; Johannes Wiegand; Thomas Karlas
Journal:  Lancet Gastroenterol Hepatol       Date:  2021-01-15

7.  Plasminogen activator inhibitor-1 is independently associated with non-alcoholic fatty liver disease whereas leptin and adiponectin vary between genders.

Authors:  Ming-Ling Chang; Chen-Ming Hsu; Jeng-Hwei Tseng; Yung-Kuan Tsou; Shu-Chun Chen; Shuen-Shian Shiau; Chau-Ting Yeh; Cheng-Tang Chiu
Journal:  J Gastroenterol Hepatol       Date:  2015-02       Impact factor: 4.029

8.  Noninvasive markers of fibrosis in nonalcoholic fatty liver disease: Validating the European Liver Fibrosis Panel and exploring simple markers.

Authors:  Indra Neil Guha; Julie Parkes; Paul Roderick; Dipanker Chattopadhyay; Richard Cross; Scott Harris; Philip Kaye; Alastair D Burt; Steve D Ryder; Guruprasad P Aithal; Christopher P Day; William M Rosenberg
Journal:  Hepatology       Date:  2008-02       Impact factor: 17.425

9.  Cytokeratin-18 fragment levels as noninvasive biomarkers for nonalcoholic steatohepatitis: a multicenter validation study.

Authors:  Ariel E Feldstein; Anna Wieckowska; A Rocio Lopez; Yao-Chang Liu; Nizar N Zein; Arthur J McCullough
Journal:  Hepatology       Date:  2009-10       Impact factor: 17.425

10.  Serum leptin levels correlate with body mass index but not with histologic disease severity in Indian patients with non-alcoholic steatohepatitis: a pilot study.

Authors:  Deepak Kumar Singh; Puja Sakhuja; Archana Rastogi; Anubha Singh; Ranjana Gondal; Shiv Kumar Sarin
Journal:  Indian J Med Res       Date:  2013-05       Impact factor: 2.375
View more
  1 in total

1.  Key Genes Associated With Non-Alcoholic Fatty Liver Disease and Polycystic Ovary Syndrome.

Authors:  Yong Chen; Leikai Ma; Zhouling Ge; Yizhao Pan; Lubin Xie
Journal:  Front Mol Biosci       Date:  2022-05-25
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.