A systematic review and meta-analysis of serum resistin level and its relation to HOMA-IR score using meta-regression in nonalcoholic fatty liver disease patients

Abstract

BACKGROUND:

Non-alcoholic fatty liver disease (NAFLD) comorbidity with adipose tissue dysfunction is not new and studies have focused on how adipose tissue influences NAFLD pathophysiology.

OBJECTIVE:

Quantification of nature and magnitude of the association between serum resistin and also insulin resistance, by calculating pooled Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) score, with NAFLD pathophysiology was the objective of the current study.

METHODS:

Using systematic review and meta-analysis and standardized mean difference (SMD) as the effect size, the levels of resistin and HOMA-IR scores have been investigated in NAFLD subjects in comparison with controls in the case-control studies using random-effects models.

RESULTS:

This meta-analysis retrieved a total number of 665 and 522 cases and 671 and 555 control subjects until May 2020 for serum levels of resistin and HOMA-IR score until May 2020. The final analyses demonstrated that pooled SMD of resistin and HOMA-IR score was 0.687 (95% confidence interval, 0.070–1.304) and 1.368 (95% confidence interval, 1.080–1.655); respectively. Moreover, the p-value for the test of significance for each pooled SMD was examined by the z-test and calculated as 0.029 and 0.000 for resistin and HOMA-IR score (clearly considered as statistically significant).

CONCLUSION:

Based on the findings, the HOMA-IR score and the serum levels of resistin in NAFLD subjects are associated with disease pathogenesis.

Keywords

Resistin HOMA-IR NAFLD NASH simple steatosis

1 Background

Non-alcoholic fatty liver disease (NAFLD) is highly prevalent worldwide and manifests in pathological stages comprising a wide progressive spectrum of diseases ranging from simple steatosis (i.e., more than 5% of the liver weight is composed of fat) to non-alcoholic steatohepatitis (NASH), in which steatosis is combined with inflammation and fibrosis with a significant risk at later stages for the development of cirrhosis [1]. NAFLD is associated with significant adverse outcomes both through liver-specific complications which promotes both morbidity and mortality [2]. It is believed that NAFLD is closely related to obesity and insulin resistance (type 2 diabetes), and these conditions augment the progressiveness of the disease-associated complications toward more advanced stages [3]. NAFLD pathogenesis is considered multifactorial; however, the mechanisms that play role in hepatic steatosis and liver predisposition to inflammation, fibrosis and consequently cirrhosis are still not fully understood but reflect complex interactions among metabolic target tissues including hepatocytes, adipose, skeletal muscle, and immune system cells [4]. It is believed that NAFLD is a hepatic manifestation of metabolic syndrome. Factors like genetic predisposition, increased gut microbial-derived components, dietary intakes (e.g., high fat and fructose intake), inflammation, insulin resistance and lipotoxicity are presumed to contribute to the NAFLD development and progression [5 –7]. The adipose tissue, which is not only a lipid-storage organ but also an endocrine organ, closely interacts with liver by secreting polypeptides known as adipokines [8, 9]. A growing body of literature demonstrates that adipokines are involved in various processes, such as immunity, inflammation, insulin sensitivity, hepatic steatosis, and NASH [10]. Resistin, leptin and adiponectin are known as main adipokines playing role in NAFLD development [10]. In the current study, the serum levels of resistin, and the reported HOMA-IR scores in the included records were investigated in NAFLD pathogenesis using systematic review and meta-analysis.

2 Methods

2.1 Protocol of the systematic review and meta-analysis

The PRISMA Checklist 2009 was used to conduct this systematic review and meta-analysis [11]. This investigation was approved by the Ethics Committee of Ilam University of Medical Sciences (ethical code: IR.MEDILAM.REC.1398.183).

2.2 Information sources and search strategies

The literature sources of information for the systematic review were Pubmed, Pubmed Central, Medline, Google Scholar, Embase and SCOPUS specialized biomedical databases and independently carried out by two authors (A. M., A. A.) without the beginning date restriction until May 2020. The search key terms were framed along with three major categories: NAFLD pathological stages; resistin blood levels and study type. Publications using the MeSH and non-MeSH terms “non-alcoholic fatty liver disease”, “NAFLD”, “simple steatosis”, “steatohepatitis”, “cirrhosis” in combination with “resistin” with additional keywords such as “peripheral blood samples”, “circulatory” and “case-control study” were identified. Then, the search results were restricted to the English language and the review possesses were limited to case-control studies by two authors independently, which fulfilled our inclusion and exclusion criteria. Apart from the databases aforementioned, the harvested references from retrieved studies were also subjected to a manual search of references.

2.3 Eligibility criteria

Only original articles that had been published in peer-reviewed journals were pre-included. On the other hand, studies applying NAFLD reviews and theories and models, to discuss phases of NAFLD development and management, conference papers, non-English language articles were excluded. Studies were pre-included if they used standardized methods such as enzyme-linked immunosorbent assay (ELISA) and chemiluminescent methods for the detection of serum resistin levels. No limitation was applied to the subtypes of NAFLD, the severity of NAFLD, sex or race of the study participants. However, studies were excluded if they enrolled populations other than NAFLD as well as reports describing NAFLD interventional therapies. Moreover, only records reporting serum resistin levels and their corresponding HOMA-IR score were considered for effect size analyses in each study in the case and control groups.

2.4 Study selection

First, records excluded with no NAFLD data, records with no full text available (conference proceedings), studies that did not report original data (editorials or reviews), records that did not report the number of participants, and case reports. Publications were assessed based on their titles and then based on abstracts; to exclude studies that did not meet the inclusion and exclusion criteria. The full texts of the remaining papers were archived and read, and at this stage, studies that not fulfilling the inclusion criteria were rejected. Only the case-control studies providing enough information about their results in such a way to compute an estimate of the effect size (such as mean and standard deviation or standardized error of the mean, etc.) for serum resistin concentrations were included. The data must be reported in an exact numerical format and not extracted from the figures of the record by estimation and if the data not reported in such a way, the record was excluded. Due to the different protocol definition used for assessment of serum resistin levels, only studies which determined the levels of resistin in NAFLD in comparison with non-NAFLD subjects were considered to be included in the current meta-analysis.

2.5 Data collection process

The first author of the selected records, date of publication, the serum levels of resistin in NAFLD patients and non-NAFLD controls, evaluated criteria for the NAFLD and also the total number of cases and controls and other related information were extracted from the publications which have been provided from the systematic review for the meta-analytical process. Moreover, the HOMA-IR was also meta-analyzed for the selected studies, if the finally included records reported such information.

2.6 Summary measures and synthesis of results

Stata version 14.0 (Stata Corporation, College Station, TX, USA) was employed for data analyses of the systematic review and meta-analysis. Between-study heterogeneity was assessed using the χ² based Q-test and also I². The Q test and I² statistics were applied to evaluate the inconsistencies and heterogeneities among the records. A significant Q suggests the existence of heterogeneities and I² estimates the magnitude of the inconsistencies among the studies [12]. For analysis of the estimated total effect size, the random-effects model and SMD were used. Data were shown as the estimated SMD with a 95% confidence interval (CI) for each study. The significance of the total SMD was examined by the z-test and p < 0.05 was considered as statistically significant.

2.7 Risk of bias across studies

For the risk of bias across records, the records were scrutinized for method validation and data processing. For effect size estimation for each selected study, the funnel plot was developed. For interpretation of any publication bias among records, visual inspections of the generated funnel plot were employed to evaluate the plot symmetry. In this plot, the Y and X axes represent the standard error and standard difference in means, respectively. Besides, for the investigation of the HOMA-IR score and serum resistin relationship, the meta-regression (under random-effects model) was performed in such a way that the calculated SMD for HOMA-IR defined as a moderator variable and it was plotted against the SMD for resistin serum levels for the finally included studies.

3 Results

3.1 Study selection

A flowchart, representing the systematic review process for study selection, has been shown in Fig. 1. The initial search for serum resistin concentrations in NAFLD retrieved a total number of 5180 potentially eligible records and, then 543 studies removed being as duplicates. Then, 4600 studies were excluded after reading titles or abstracts as being obviously irrelevant to the goal of this meta-analysis. Moreover, because of insufficient data presented by the authors of such publications for calculation of the SMD and 95% CI and because of poor quality, 3 papers were excluded additionally for serum resistin levels in NAFLD. Finally, the records which fulfilled exclusion and inclusion criteria (14 studies, 18 including within study subgroups, which have been detailed in Table 1A and Table 1B cited in the references part of the current study as [13 –26]); were included in the meta-analytical process. The data for HOMA-IR calculation was extracted from the selected studies which have reported serum resistin levels as well in this systematic review and then subjected to meta-analysis (10 studies, 13 including within-study subgroups, which have been detailed in Table 2 and cited in the references part of the current study as [13–15 , 26]).

Fig. 1

Systematic review process. The flowchart represents the systematic review process for study selection according to the inclusion and exclusion criteria. The results have been shown for serum resistin concentrations and HOMA-IR scores in non-alcoholic fatty liver disease patients vs controls; respectively.

Table 1A

Demographic data for finally included studies reported serum resistin concentrations

Number	First author name	BMI (Mean±Standard deviation) in NAFLD subjects (kg/m²)	BMI (Mean±Standard in deviation) in Non-NAFLD controls (kg/m²)	Gender (Female/male) in NAFLD subjects	Gender (Female/male) in non-NAFLD controls	Age (Mean±Standard deviation, in years) in NAFLD	Age (Mean±Standard deviation in years) in non-NAFLD controls	Country
1.	Osama H. Al- jiffry (2017)	31.5±5.16	30.94±4.87	55/45 (n = 100)	57/43 (n = 100)	43.83±6.12	45.16±5.97	Saudi Arabia
2.	E. Senates (2012)	31±6	23±4	42/55 (n = 97)	33/33 (n = 66)	41±10	39±9	Turkey
3.	Sameh M.Abdel Monem (2018)	32.71±1.18	23.46±0.76	6/13 (n = 19)	8/11 (n = 19)	44.05±5.45	43.26±6.81	Egypt
4.	Mona Hegazy (2014)	34.77±3.76	33.588±2.1912	50/4 (n = 54)	6/2 (n = 8)	43.17±7.37	45.75±6.274	Egypt
5.	Engy Yousry Elsayed (2010)	28.2±5.2	25.2±2.6	25/15 (n = 40)	14/6 (n = 20)	42±13	40±12	Egypt
6.	Raika Jamali (2016)	31.58±3.94	29.28±3.89	5/13	5/13	34.50±8.85 (n = 18)	30.44±10.11 (n = 18)	Iran
7.	Chuan Shen (2014)a	28.2±1.9	22.0±1.8	11/19 (n = 30)	14/29 (n = 43)	42±9	45±14	China
8.	Chuan Shen (2014)b	26.6±2.6	22.0±1.8	9/19 (n = 28)	14/29 (n = 43)	44±12	45±14	China
9.	A Murad (2010)a	Not reported for males separately	Not reported for males separately	15/0 (n = 30)	16/0 (n = 30)	Not reported for males separately	Not reported for males separately	Egypt
10.	A Murad (2010)b	Not reported for females separately	Not reported for females separately	0/15 (n = 30)	0/14 (n = 30)	Not reported for females separately	Not reported for females separately	Egypt
11.	Claudio Pagano (2006)	27.3±3.17	26.9±5.74	2/26	3/30	45±10.58 (n = 28)	42±17.23 (n = 33)	Italy
12.	Mehmet Boyraz (2013)a	31.6±4.9	29.5±5.3	(n = 63)	(n = 85)	13.0±2.0	11.9±2.0	Turkey
13.	Mehmet Boyraz (2013)b	32.3±5.1	29.6±5.5	(n = 18)	(n = 26)	13.1±2.2	11.8±1.9	Turkey
14.	Gianluka Perseghin (2006)	27.1±3.9	26.8±3.0	4/28 (n = 28)	9/38 (n = 47)	35±8	36±8	Italy
15.	Ahmet Tarik Eminler (2014)	Not reported by authors	Not reported by authors	19/21 (n = 40)	22/18 (n = 40)	Not reported by authors	Not reported by authors	Turkey
16.	Ling-Ling Jiang (2008)	25.75±1.91	24.81±1.91	26/17 (n = 43)	26/17 (n = 43)	52.6±10.8	51.1±12.5	China
17.	Stergios A. Polyzos (2016)a	31.9±5.03	30.5±4.0	10/5 (n = 15)	20/5 (n = 25)	53.9±10.06	53.6±9.0	Greece
18.	Stergios A. Polyzos (2016)b	33.9±5.99	30.5±4.0	12/2 (n = 14)	20/5 (n = 25)	54.8±5.99	53.6±9.0	Greece

Table 1B

Data extracted from the finally included studies to calculate pooled standardized mean difference (SMD) for serum resistin concentrations

Number	Study name	Mean serum resistin in NAFLD (ng/ml)	Standard deviation serum resistin in NAFLD (ng/ml)	Sample size in NAFLD	Mean serum resistin in NAFLD (ng/ml)	Standard deviation serum resistin in NAFLD (ng/ml)	Sample size in non-NAFLD	NAFLD subtype (if reported authors)^*
1.	Osama H. Al-Jiffri (2017)	16.83	4.52	100	13.17	4.11	100	-
2.	E. Senates (2012)	32.1	10	97	26.57	13.6	66	-
3.	Sameh M. Abdel Monem (2018)	5.58	0.94	19	3.3	0.44	19	NASH
4.	Mona Hegazy (2014)	5.28	2.39	54	2.03	0.64	8	NASH
5.	Engy Yousry Elsayed (2010)	16.2	4	40	3.4	1.1	20	-
6.	Raika Jamali (2016)	2.06	1.1	18	2.66	1.17	18	-
7.	Chuan Shen (2014)a	6.3	1.54	30	3.14	1.22	43	NASH
8.	Chuan Shen (2014)b	5.9	1.54	28	3.14	1.12	43	SS
9.	A Murad (2010)a	5.5	1.57	15	3.2	0.99	16	-
10.	A Murad (2010)b	4.3	1.42	15	2.3	0.94	14	-
11.	Claudio Pagano (2006)	4.3	1.05	28	5.87	2.81	33	-
12.	Mehmet Boyraz (2013)a	8.5	3.2	63	15	3.9	85	-
13.	Mehmet Boyraz (2013)b	7.6	2.6	18	15.1	3.6	26	-
14.	Gianluka Perseghin (2006)	3.9	1	28	3.4	8	47	-
15.	Ahmet Tarik Eminler (2014)	0.55	0.25	40	0.41	0.126	40	-
16.	Ling-Ling Jiang (2008)	9.2	7.2	43	4.7	3.3	43	-
17.	Stergios A. Polyzos (2016)a	48.3	49.96	15	76.6	63	25	SS
18.	Stergios A. Polyzos (2016)b	44.6	39.28	14	72.6	63	25	NASH

^* -: NAFLD subtype not reported by authors, NASH: Nonalcoholic steatohepatitis, SS: simple steatosis.

Table 2

Data extracted from the finally included studies to calculate pooled standardized mean difference (SMD) for HOMA-IR score as reported by finally included records for serum resistin levels

Number	Study name	Mean HOMA-IR score in NAFLD	Standard deviation HOMA-IR score in NAFLD	Sample size in NAFLD	Mean HOMA-IR score in NAFLD	Standard deviation HOMA-IR score in NAFLD	Sample size in non-NAFLD	NAFLD subtype (if reported by authors)^*
1.	Osama H. Al-Jiffri (2017)	5.28	1.95	100	2.73	1.13	100	-
2.	E.Senates (2012)	3.7	2.6	97	1.5	0.8	66	-
3.	Sameh M.Abdel Monem (2018)	3.42	1.06	19	1.37	0.36	19	NASH
4.	Engy Yousry Elsayed (2010)	135.2	123	40	49.4	20.5	20	-
5.	Chuan Shen (2014)a	2.9	0.6	30	1.6	0.5	43	NASH
6.	Chuan Shen (2014)b	2.6	0.7	28	1.6	0.5	43	SS
7.	A Murad (2010)	3.46	1.04	30	1.92	0.45	30	-
8.	Claudio Pagano (2006)	2.77	2.53	28	1.78	1.14	33	-
9.	Mehmet Boyraz (2013)a	4.9	2.3	63	3.1	1.2	85	-
10.	Mehmet Boyraz (2013)b	5.3	2.5	18	3	0.9	26	-
11.	Ahmet Tarik Eminler (2014)	5.81	5.56	40	2.04	1.33	40	-
12.	Stergios A. Polyzos (2016)a	2.49	1.74	15	1.2	1.05	25	SS
13.	Stergios A. Polyzos (2016)b	4.48	3.51	14	1.2	1.05	25	NASH

^* -: NAFLD subtype not reported by authors, NASH: Nonalcoholic steatohepatitis, SS: simple steatosis.

3.2 Study characteristics

For each record, the demographic and disease characteristics data which have been reported by the authors were extracted. The number of NAFLD subjects, NAFLD pathological state, number of non-NAFLD controls, NAFLD subtype (if reported by authors), body mass index (BMI), mean age in control subjects and NAFLD patients have been presented in Table 1A. Actually, this meta-analysis retrieved a total number of 665 and 522 cases and 671 and 555 control subjects for serum levels of resistin and HOMA-IR score until May 2020.

3.3 Risk of bias within studies

The results showed that all of the selected studies were not homogenous and actually they were inconsistent in their corresponding results. The Q test was calculated as 417.428 (24.713) and 49.975 (14.860) for serum resistin and HOMA-IR score under the fixed-effect model (random-effects model); respectively. It is well accepted that the Q statistic test could be only applied for testing the heterogeneity existence among studies, but it is not suitable for calculation of the heterogeneity extent. Moreover, the I²% tests were calculated as 95.927 (31.211) and 75.988 (18.417) for resistin and HOMA-IR under the fixed-effect model (random-effects model); respectively. As the I² index and the between-studies variance, τ², are directly related: the higher the τ², the higher the I² index [12]. However, it has been proposed a tentative classification of I² values with the purpose to interpret heterogeneity magnitude. Thus, the percentages of nearly 25% (I² = 25), 50% (I² = 50), and 75% (I² = 75) would mean low, medium, and high heterogeneity, respectively [12]. Therefore, the random-effects model of the meta-analysis was applied for the presentation of the forest plots of the finally included studies for serum resistin levels as well as HOMA-IR score effect size calculation in NAFLD subjects as compared to controls.

3.4 Synthesis of results

The forest plots showed the weighted SMD and standard deviation including the corresponding confidence interval for each study and the overall SMD as well (Fig. 2). The final analyses demonstrated that mean pooled SMD for serum resistin level was 0.687 (95% confidence interval, 0.070–1.304). Moreover, the p-value for the test of significance for the pooled SMD was examined by the z-test and calculated as 0.029, demonstrating a statistically significant effect. The weighted pooled SMD for the association between serum resistin concentration with NAFLD pathogenesis was calculated for 14 studies (18 including within study subgroups, as presented in Fig. 2A). Moreover, the forest plot for the HOMA-IR score which has been reported by the included studies measuring serum resistin levels was developed. The analyses demonstrated that the weighted pooled SMD for the association between the HOMA-IR score and NAFLD pathogenesis was 1.368 (95% confidence interval, 1.080–1.655) applying the random-effects model for 10 studies (13 including within study subgroups) as presented in Fig. 2B. The p-value of the HOMA-IR score for the significance of the combined SMD calculated 0.000, as examined by the corresponding z-test.

Fig. 2

Forest plots. For serum resistin (2A), HOMA-IR score (2B), the final analyses demonstrated that standardized mean differences (SMDs) of serum resistin concentration and HOMA-IR score was 0.687 (95% confidence interval, 0.070–1.304) and 1.368 (95% confidence interval, 1.080–1.655); respectively. Moreover, the p-value for the test of significance for pooled SMD was examined by the z-test and calculated as 0.029 and 0.000 for resistin and HOMA-IR score, respectively (clearly considered as statistically significant).

3.5 Risk of bias across studies

Shapes of the funnel plots were considered to be moderately asymmetrical confirming that there was some publication bias in the related records in reporting serum resistin concentrations and HOMA-IR scores (Fig. 3A and Fig. 3B). For serum resistin (Fig. 3A) and HOMA-IR score (Fig. 3B), this bias mainly refers to the right part of each plot that has been mainly occupied by the publications reporting the higher SMD in NAFLD subjects in comparison with corresponding non-NAFLD controls. The meta-regression analysis showed that the SMD for serum resistin levels was directly proportional to the calculated HOMA-IR score (the moderator) using the random-effects model (Fig. 4).

Fig. 3

Funnel plots. For serum resistin (3A), HOMA-IR score (3B), the publication bias mainly refers to the right part of each plot that has been mainly occupied by the publications demonstrating the higher standardized mean difference (SMD) in NAFLD subjects in comparison with corresponding controls.

Fig. 4

Meta-regression for calculated HOMA-IR score and standardized mean difference (SMD) for serum resistin levels. As it is evident, the meta-regression analysis showed that SMD for serum resistin levels is directly proportional to the calculated HOMA-IR (the moderator) using the random-effects model and the meta-regression curve roughly showed a linear relationship i.e. higher SMD for serum resistin levels corresponds to higher HOMA-IR and thus more severe insulin resistance.

4 Discussion

NAFLD comorbidity with adipose tissue dysfunction is not new and studies have focused on how adipokines might be involved in the NAFLD pathophysiology. Quantification of nature and magnitude of the association between adipokines and also insulin resistance by calculating pooled HOMA-IR score and NAFLD pathophysiology was the objective of the current study. In this study, the serum levels of resistin and the reported HOMA-IR scores in the included records were investigated for their associated roles in NAFLD pathogenesis using a systematic review and meta-analysis. The records were collected by systematic review and then filtered according to inclusion and exclusion criteria. Actually, the number of filtered records for resistin and HOMA-IR was sufficient. According to recently published studies that have been included in the current investigation, the results demonstrated that serum levels of resistin and the calculated HOMA-IR score were clearly considered to be statistically significant. Interestingly, the highest mean weighted pooled SMD between serum level of resistin and the calculated HOMA-IR factors for the association between HOMA-IR and NAFLD pathogenesis was HOMA-IR score (mean pooled SMD = 1.368, 95% confidence interval, 1.080–1.655). Besides, the adipose-derived serum resistin levels were higher in NAFLD than healthy controls implying the adverse effects of this adipokine in NAFLD development. The results show the important role of resistin, even though, the role of other adipokines cannot be ruled out. Another factor we considered was HOMA-IR and the highest mean weighted pooled SMD for the association between HOMA-IR and NAFLD pathogenesis was HOMA-IR score (mean pooled SMD = 1.368). HOMA-IR score is calculated as follows: HOMA-IR score = (Fasting insulin)^*(Fasting glucose) / 405. The HOMA-IR is used to measure the severity of insulin resistance, though normal insulin resistance varies depending on the population. Common reference levels for HOMA-IR insulin resistance range from 0.7–2 [27]. As it is evident, the meta-regression analysis showed that SMD of serum resistin levels are directly proportional to the calculated HOMA-IRs (the moderator) using the random-effects model and is actually evident that the curve roughly showed a linear relationship i.e. higher SMD for serum resistin levels causes higher HOMA-IR score and thus more severe insulin resistance. Recent study showed that HOMA-IR is an independent predictor of advanced liver fibrosis [28]. Our data are in accordance with the narrative reviews discussing the relationships among NAFLD, resistin hormone levels, HOMA-IR score and insulin resistance development [29 –34]. To best our knowledge, this is the first meta-analysis that reports the serum levels of resistin and their corresponding HOMA-IR score in this regard. Although, the precise mechanisms by which resistin affects fatty liver pathogenesis are unclear, however, investigations are ongoing and some of them shed light on its mechanisms of action. Resent study shows that inflammation appears to play a pivotal role in determination of resistin circulating levels and it proposed resistin as a molecular link between body fat deposition and insulin resistance [35]. Moreover, intracellular signaling for resistin induces Nuclear factor kappa B (NF-κB) and mitogen-activated protein kinase (MAPK or MAP kinase) activations and also it causes increased oxidative stress [35]. Recently published data suggests that acute elevated resistin levels exacerbate mitochondrial damage and aggravates liver steatosis through 5’ AMP-activated protein kinase (AMPK)/Peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α) signaling pathway in male NAFLD mice [36]. Moreover, it has been proposed that MiR-34a regulates mitochondrial content and fat ectopic deposition induced by resistin through the AMPK/Peroxisome proliferator-activated receptor alpha (PPAR-α) pathway in HepG2 cells [37]. Future studies may focus on the mechanism of action of resistin and also other adipokines and their relationship with NAFLD in depth. In conclusion, the HOMA-IR score and the serum levels of resistin in NAFLD subjects are associated with disease pathogenesis and one of the implications of this study is that resistin may be considered as a useful diagnostic and prognostic tool in NAFLD.

Footnotes

Acknowledgments

None declared.

Funding

Not funded.

Conflict of interest

The authors do not have any disclosures to report.

Author contributions

A. N. performed the study, acquisition and analysis of data and writing the manuscript. A. M., A. A. and A. S-N performed literature database searching.

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