
==== Front
Medicine (Baltimore)
Medicine (Baltimore)
MD
Medicine
0025-7974
1536-5964
Lippincott Williams & Wilkins Hagerstown, MD

MD-D-24-02412
00072
10.1097/MD.0000000000039613
3
4500
Research Article
Systematic Review and Meta-Analysis
Association of circulating visfatin level and metabolic fatty liver disease: An updated meta-analysis and systematic review
Chen Shuaihang MD zjhzcsh@zcmu.edu.cn
a
Wu Kaihan MD Coco328@126.com
b
Ke Yani MD 201512201503019@zcmu.edu.cn
a
Chen Shanshan MD 202012211506006@zcmu.edu.cn
b
He Ran MD HeranZJTCM@126.com
b
Zhang Qin MD 201912210902025@zcmu.edu.cn
b
Shen Chenlu MD Shencl1101@126.com
b
Li Qicong MD lllqcong@126.com
b
Ruan Yuting MD ruanyuting0617@126.com
b
Zhu Yuqing MD 873786231@qq.com
b
Du Keying MD 1047778095@qq.com
b
Hu Jie MD muhudie1106@163.com
c
Liu Shan MD d*
a The Second Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, China
b The First Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, China
c Department of Infectious Diseases, The First Affiliated Hospital of Zhejiang Chinese Medical University, Zhejiang Provincial Hospital of Chinese Medicine, Hangzhou, China
d Center of Clinical Evaluation, The First Affiliated Hospital of Zhejiang Chinese Medical University, Zhejiang Provincial Hospital of Chinese Medicine, Hangzhou, China.
* Correspondence: Shan Liu, Center of Clinical Evaluation, The First Affiliated Hospital of Zhejiang Chinese Medical University, Zhejiang Provincial Hospital of Chinese Medicine, No. 54, Hangzhou, Zhejiang Province 310006, China (e-mail: graystar92@163.com).
13 9 2024
13 9 2024
103 37 e3961306 3 2024
16 6 2024
16 8 2024
Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.

Background:

The rate of incidence of metabolic dysfunction-related fatty liver disease (MAFLD) has rapidly increased globally in recent years, but early diagnosis is still a challenge. The purpose of this systematic review and meta-analysis is to identify visfatin for early diagnosis of MAFLD.

Methods:

We strictly adhered to the relevant requirements of Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The systematic search was conducted in 7 sources (PubMed, Embase, Cochrane Library, CNKI, Wanfang, CBM, and ClinicalTrials.gov) until February 2024. The meta-analysis was performed using Stata 12. Outcomes were expressed in the form of standardized mean difference (SMD) and 95% confidence interval and were analyzed using meta-analysis.

Results:

The results showed that there was no significant difference in circulating visfatin levels between patients with MAFLD and controls (SMD = 0.13 [−0.34, 0.60]). However, the outcomes indicated that the level of circulating visfatin was significantly higher in MAFLD patients in the Middle Eastern subgroup (SMD = 0.45 [0.05, 0.85]) and in the obese patient subgroup (SMD = 1.05 [0.18, 1.92]). No publication bias was detected, and sensitivity analysis confirmed the stability of the outcomes.

Conclusion:

The serum visfatin levels of MAFLD patients did not differ significantly from those of controls. However, visfatin concentrations in serum were statistically higher within Middle Eastern or obese MAFLD patients compared to controls. There is a need for further research to investigate visfatin’s potential as a biomarker for MAFLD.

meta-analysis
metabolic dysfunction-related disease of fatty liver
non-alcoholic disease of fatty liver
visfatin
Natural Science Foundation of Zhejiang Province 10.13039/501100004731 LQ19H290001 Jie Huthe research project of Zhejiang Chinese Medicine University2021JKZKTS042B Shan LiuScience and Technology Program of Zhejiang Province 10.13039/501100017599 2022KY921 Shan LiuOPEN-ACCESSTRUE
SDCT
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pmc1. Introduction

Nonalcoholic fatty liver disease (NAFLD) is typified by pronounced hepatic steatosis, insulin resistance, and a strong genetic correlation with liver damage.[1] In recent years, the prevalence of NAFLD has surged, making it the most prevalent liver disorder globally.[2] To underscore the impact of metabolism on NAFLD, a 2020 expert panel agreed to recommend the term metabolic dysfunction-related fatty liver disease (MAFLD) to replace NAFLD.[3] Research indicates that the worldwide incidence rate of MAFLD is 38.77%.[4] MAFLD may contribute to the development of liver cirrhosis and ultimately lead to liver cancer.[5,6] MAFLD represents a hepatic manifestation of metabolic syndrome,[7] and patients with MAFLD are more prone to developing diabetes,[8] cardiovascular disease (CVD),[9] and chronic kidney disease.[10] At present, early screening methods for MAFLD in clinical settings are scarce, and no specific medications exist to treat this condition.[11] Hence, identifying MAFLD biomarkers may assist in discovering early screening indicators and therapeutic targets.

Visfatin, previously recognized as pre-B-cell colony enhancing factor and nicotinamide phosphoribosyltransferase (NAMPT), is a protein with a molecular weight of 52 kDa. The protein is encoded by a messenger RNA of approximately 2.4 kilobases.[12] Research has shown that visfatin is extensively secreted by the visceral adipose tissue and may be linked to the pathogenesis of various metabolic diseases, such as diabetes,[13] obesity,[14] and polycystic ovary syndrome.[15]

In recent years, numerous studies have investigated the connection between visfatin and MAFLD, albeit with inconsistent outcomes. Akbal[16] discovered elevated levels of visfatin in MAFLD patients compared to the general population, while Gaddipati[17] maintained a contrary viewpoint. A prior meta-analysis by Ismaiel[18] indicated that visfatin levels were not correlated with MAFLD. Nevertheless, due to database limitations, some crucial articles were not included in their search. We performed a comprehensive, up-to-date meta-analysis to examine the relationship involving visfatin as well as MAFLD.

2. Materials and methods

2.1. Strategy for study

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines[19] were strictly followed in the research conducted for this study. Additionally, the protocol has been registered with PROSPERO (registration ID: CRD42022300131) prior to commencement of the study and can be found in Supplemental File 1, http://links.lww.com/MD/N515. Two researchers conducted this systematic review independently. We conducted a comprehensive search of 7 sources (PubMed, Embase, Cochrane Library, CNKI, Wanfang, CBM, and ClinicalTrials.gov) for relevant literature as of February 5, 2024, using a specific retrieval scheme that is presented in Supplemental File 2, http://links.lww.com/MD/N516. To avoid omissions, we carefully examined the references of the retrieved literature to identify papers that met the inclusion criteria. For articles with incomplete data, we contacted the authors via email and other methods to obtain complete data. There were no language restrictions for inclusion in this review.

2.2. Study selection

Two independent researchers (S.H.C. and K.H.W.) conducted the article screening process with no communication between them. In cases where their outcomes differed, a third researcher (S.L.) was consulted to facilitate discussion and negotiation. Contact was made with the authors via email for any crucial information that could have affected the evaluation outcomes but was not reflected in the article.

The following inclusion criteria were used: participants were adults aged over 18 years; the disease cohort included patients with confirmed MAFLD or NAFLD; control group included healthy individuals without any metabolic diseases; visfatin levels were reported; and a case-control study and a cohort study were included in the study.

Studies were excluded based on the following criteria: the case group did not consist of patients diagnosed with MAFLD or NAFLD, but instead consisted of patients with viral or alcoholic disease of fatty liver; the study did not report circulating visfatin levels, or the data were incomplete and could not be obtained through contact with the corresponding author; the study had no control group or the control group consisted of an unhealthy population; the study was not a case-control or cohort study (e.g., review, animal experiments, or case report); and the study was a duplicate publication.

2.3. Quality assessment and data extraction

Two researchers (S.H.C. and K.H.W.) independently evaluated the literature based on the Newcastle-Ottawa Scale criteria for selection, comparability, and exposure.[20] In cases of inconsistencies, a third party (S.L.) was consulted for resolution. Study certainty was assessed using the Grading of Recommendation, Assessment, Development, and Evaluation scale (https://gdt.gradepro.org).

Data extraction was performed by S.H.C. and K.H.W. independently and included the following: basic study information (first author name, publication year, and country); MAFLD diagnostic criteria; visfatin detection method; group characteristics (sex and age); the following biochemical indices were measured: visfatin, adiponectin, apelin, aspartate aminotransferase, alanine aminotransferase, retinol-binding protein 4, C-reactive protein, and fasting serum insulin. In addition, indicators of insulin resistance, body mass index (BMI), and the homeostasis model assessment were also employed.

2.4. Statistical analysis

For this study, we performed all data analyses using Stata 12 (Stata Company, College Station). We presented all outcomes as standardized mean differences (SMD). Data that were presented as median and quartile was converted to mean ± standard deviation using Shi et al’s method.[21–23] Throughout the article, we presented data as mean ± standard deviation. We evaluated the heterogeneity of the included studies using the I2 test, Cochran test, and Galbraith test. If I2 increased beyond 50% or P decreased below .05, indicating a significant degree of heterogeneity, a random-effects model was used. If I2 was less than or equal to 50% or P was >.05, indicating low heterogeneity, we used a fixed-effects model.[24] To intuitively reflect any changing trends in circulating visfatin levels in MAFLD patients with an increase in the number of studies, we conducted a cumulative meta-analysis based on the year of publication of the study.[25] To explore the source of heterogeneity, the age, body mass index, and other indicators were used to conduct subgroup analyses. We conducted a sensitivity analysis to assess the reliability of the outcomes. Additionally, for the assessment of publication bias, Egger test, Begg test, and funnel plots were used.[26]

3. Results

3.1. Selection of research

In this study, literature selection is detailed in Figure 1. The 2 investigators retrieved 7 databases simultaneously, yielding 878 articles. After excluding 275 duplicates, the remaining 603 articles were read, and 33 articles were included (2304 patients and 1800 controls).[16,17,27–57] These studies were conducted in 10 countries, with 22 articles published in Chinese[28,30,31,33–35,39–44,46–48,50–54,56,57] and 11 articles published in English.[16,17,27,29,32,36–38,45,49,55] All included studies were case-control studies and examined visfatin levels using enzyme-linked immunosorbent assays. In the case groups, the proportion of men ranged from 43% to 100%, with an average age of 31.29 to 62.6 years, as well as a mean body mass index of 23.26 to 34.76 kg/m2. In the control groups, the proportion of men ranged from 33% to 100%, with an average age of 33.19 to 61.3 years and a mean BMI of 19.95 to 30.44 kg/m2. Table 1 provides more specific information.

Table 1 Baseline characteristics of the studies included in the meta-analysis.

No.	First author	Year	Country	Type of cases	Numbers	Sex (male %)	Age (yr)	BMI (kg/m2)	Visfatin	
Cases	Controls	Cases	Controls	Cases	Controls	Cases	Controls	Cases	Controls	Unit of visfatin	Detection method of visfatin	
1	Soardo G[27]	2006	Italy	\	21	20	\	\	\	\	\	\	20.6 ± 1.6	15.2 ± 1.2	ng/mL	ELISA	
2	Pan F[28]	2008	China	\	58	58	54%	\	49.2	\	\	\	25.64 ± 4.52	19.17 ± 3.23	mg/L	ELISA	
3	Younossi[29]	2008	American	Total	37	32	\	\	\	39.3 ± 9.8	\	\	31.2 ± 45.68†	25.8 ± 18	pg/mL	ELISA	
SS	15	\	37.4 ± 8.3	\	52.5 ± 67	
NASH	22	\	42.5 ± 10.4	\	16.7 ± 6.3	
4	Han J[30]	2009	China	Total	68	30	54%	47%		53.03 ± 12.41		24.1 ± 2.6	35.16 ± 7.05†	15.82 ± 1.73	\	ELISA	
NAFLD	32	53%	53.41 ± 10.53	25.58 ± 2.75	31.45 ± 3.51	
NAFLD + T2DM	36	56%	53.81 ± 10.71	25.52 ± 3.01	38.46 ± 7.77	
5	Gaddipati[17]	2010	India	Total	77	38	\	\	\	\	\	\	68.53 ± 65.34†	210.38 ± 93.16	ng/mg protein	ELISA	
Simple steatosis	35	\	48.94 ± 13.12	\	87.25 ± 75.22	
Moderate steatosis	30	\	46.2 ± 12.22	\	61.36 ± 56.46	
NASH	12	\	49 ± 13.19	\	31.83 ± 29.43	
6	Shen L[31]	2010	China	\	55	29	58%	59%	49.09 ± 14.48	50.72 ± 15.03	26.1 ± 3.91	22.6 ± 3.66	31.07 ± 10.14	14.82 ± 5.25	μg/mL	ELISA	
7	Dahl[32]	2010	Norway	Total	58	27	\	\	\	\	\	\	8.19 ± 5.23†	15.35 ± 4.03	ng/mL	ELISA	
SS	26	\	\	\	8 ± 6.17	
NASH	32	\	\	\	8.35 ± 4.43	
8	Pan JQ[33]	2011	China	Total	78	30	45%	53%	\	43 ± 8	\	22.8 ± 0.9	33.70 ± 16.80†	10.98 ± 3.41	ng/mL	ELISA	
NAFLD	30	43%	40 ± 9	24.8 ± 2.5	34.18 ± 16.11	
NAFLD + T2DM	48	46%	45 ± 11	27.3 ± 3.7	33.4 ± 17.38	
9	Tian Z[34]	2011	China	\	30	30	57%	60%	42.43 ± 4.45	41.23 ± 6.15	25.51 ± 1.74	19.95 ± 1.33	30.47 ± 4.1	22.93 ± 5.44	\	ELISA	
10	Zhu CH[35]	2011	China	Total	31	23	\	\	\	\	\	24.38 ± 4.01	59.72 ± 20.18†	73.98 ± 20.86	ng/mL	ELISA	
SS	11	\	\	25.25 ± 3.28	70.82 ± 19.68	
NASH	20	\	\	25.45 ± 3.34	53.61 ± 18.13	
11	Akbal E[16]	2012	Turkey	\	30	27	52%	45%	41.1 ± 9.1	43.6 ± 10.2	30.5 ± 5.4	25.2 ± 3.6	14.7 ± 8.1	9.4 ± 1.6	ng/mL	ELISA	
12	Auguet T[36]	2013	Spain	\	69	19	\	\	46.79 ± 10.3	44.1 ± 10.7	\	\	3.6 ± 2.7	2.2 ± 1.5	ng/mL	ELISA	
13	Genc H[37]	2013	Turkey	Total	114	60	100%	100%	32.35 ± 18.77*	31.12 ± 16.71*	29.47 ± 12.01*	23.72 ± 7.75*	13.66 ± 2.35†	13.33 ± 2.73	ng/mL	ELISA	
SS	31	33.00 ± 18.65*	30.25 ± 9.33*	\	
Borderline NASH	35	31.29 ± 17.01*	29.81 ± 12.37*	\	
NASH	48	31.71 ± 16.81*	28.06 ± 7.64*	\	
14	Polyzos[38]	2013	Greece	Total	52	44	58%	55%	\	56.35 ± 6.90*	\	30.21 ± 2.36*	5.63 ± 2.36†	5.94 ± 2.84	ng/mL	ELISA	
NAFL	25	60%	52.85 ± 12.58*	32.12 ± 5.42*	5.37 ± 1.89	
NASH	27	56%	55.79 ± 10.17*	34.76 ± 7.91*	5.88 ± 2.74	
15	Chen HY[39]	2013	China	\	60	60	53%	48%	48.61 ± 13.51	48.49 ± 16.75	\	\	25.31 ± 3.41	17.57 ± 3.37	μg/L	ELISA	
16	Shen L[40]	2013	China	Total	60	50	50%	50%	48.77 ± 10.48	50.02 ± 13.31	\	\	29.36 ± 9.96†	20.44 ± 8.74	μg/mL	ELISA	
NAFL	35	\	\	\	26.05 ± 10.03	
NASH	25	\	\	\	33.99 ± 7.94	
17	Sun X[41]	2013	China	Total	48	25	60%	60%	\	41 ± 7	\	22.65 ± 5.69	38.63 ± 14.52†	35.42 ± 13.45	ng/mL	ELISA	
NAFLD	22	64%	42 ± 8	28.01 ± 2.72	38.16 ± 15.46	
NAFLD + T2DM	26	58%	45 ± 11	25.17 ± 5.65	39.03 ± 13.98	
18	Cai HY[42]	2014	China	Total	110	60	69%	58%	\	47 ± 13	\	23.3 ± 2.9	52.16 ± 23.37†	17.33 ± 3.22	μg/L	ELISA	
Mild	40	60%	49 ± 11	26.3 ± 3.1	41.51 ± 20.05	
Moderate	40	75%	49 ± 14	28.5 ± 2.4	57.71 ± 23.2	
Severe	30	73%	43 ± 13	28.6 ± 3.2	58.96 ± 23.27	
19	Wei J[43]	2014	China	\	83	30	60%	\	47 ± 14	\	26.89 ± 2.28	24.38 ± 1.02	12.56 ± 6.23	28.59 ± 22.46	ng/mL	ELISA	
20	Wang HH[44]	2015	China	Total	80	30	\	\	\	42 ± 9	\	22.5 ± 0.5	34.01 ± 17.97†	10.48 ± 6.13†	ng/mL	ELISA	
NAFLD	30	\	\	39 ± 11	24.6 ± 1.5	34.95 ± 18.46	
NAFLD + T2DM	50	\	\	46 ± 10	27.2 ± 3.6	33.45 ± 17.83	
21	Jamali R[45]	2016	Iran	\	54	54	65%	41%	37.02 ± 9.82	33.24 ± 12.02	30.55 ± 3.97	30.44 ± 3.64	19.96 ± 17.5	12.68 ± 13.21	ng/mL	ELISA	
22	Chen L[46]	2016	China	\	100	150	47%	52%	44.27 ± 15.79	46.05 ± 16.97	23.66 ± 2.16	21.2 ± 1.79	45.06 ± 18.35	39.65 ± 19.03	μg/L	ELISA	
23	Zhou ZP[47]	2017	China	Total	172	50	\	\	\	\		22.68 ± 1.34	23.31 ± 4.90†	17.39 ± 3.58	μg/L	ELISA	
Mild	58	\	\	\	\	25.22 ± 1.96	21.26 ± 3.74	
Moderate	67	\	\	\	\	26.94 ± 2.74	25.62 ± 3.49	
Severe	47	\	\	\	\	31.9 ± 3.58	29.85 ± 3.56	
24	Ge LP[48]	2018	China	Total	59	25	0.51	48%	39.96 ± 1.67	38.4 ± 1.61	27.42 ± 0.39	22.55 ± 0.58	3.65 ± 0.24	6.83 ± 0.82	ng/mL	ELISA	
NAFL	28	\	\	26.68 ± 0.54	\	
NASH	31	\	\	28.1 ± 0.56	\	
25	Qiu Y[49]	2019	China	\	100	111	86%	82%	33.09 ± 5.57	33.25 ± 6.66	26.37 ± 2.89	22.63 ± 2.55	27.84 ± 7.39	31.4 ± 10.06	ng/mL	ELISA	
26	Qin HC[50]	2019	China	\	45	32	53%	50%	49.41 ± 8.70	50.16 ± 7.83	26.14 ± 2.29	22.49 ± 1.69	27.35 ± 3.05	39.1 ± 3.58	\	ELISA	
27	Yang L[51]	2019	China	\	66	66	61%	55%	62.6 ± 9.8	61.3 ± 10.5	26.3 ± 2.0	22.6 ± 1.8	0.78 ± 0.3	1.39 ± 0.52	mg/L	ELISA	
28	Fang JM[52]	2020	China	\	51	51	61%	63%	45.1 ± 6.2	44.2 ± 5.5	26.3 ± 1.2	23.5 ± 2.1	31.1 ± 8.4	15.9 ± 2.6	μg/mL	ELISA	
29	Guo YL[53]	2020	China	\	120	120	49%	51%	41.72 ± 8.29	40.48 ± 8.22	26.51 ± 1.72	24.71 ± 2.14	28.01 ± 3.43	31.33 ± 4.41	ng/mL	ELISA	
30	Hong WZ[54]	2020	China	\	50	50	58%	54%	41.65 ± 3.52	41.58 ± 3.46	23.26 ± 0.82	23.01 ± 0.64	3.75 ± 0.32	6.64 ± 0.45	mg/L	ELISA	
31	Ismaiel A[55]	2021	Romania	\	40	40	45%	45%	53.77 ± 7.88*	33.19 ± 11.53*	31.22 ± 5.07*	22.46 ± 3.63*	18.22 ± 8.44	16 ± 8.97	ng/L	ELISA	
32	Ren SP[56]	2021	China	\	90	60	49%	52%	54.74 ± 13.89	52.42 ± 13.57	\	\	0.23 ± 0.04	0.18 ± 0.04	ng/mL	ELISA	
33	Zheng SJ[57]	2023	China	\	138	269	65%	33%	53.48 ± 5.76	51.6 ± 5.63	26.88 ± 2.49	24.26 ± 2.49	107.43 ± 27.36*	100.54 ± 13.69*	pg/L	ELISA	
BMI = body mass index, ELISA = enzyme-linked immunosorbent assay, NAFL = simple nonalcoholic fatty liver, NAFLD = nonalcoholic fatty liver disease, NASH = nonalcoholic steatohepatitis, SS = simple steatosis, T2DM = type 2 diabetes mellitus.

* The data are converted from the median (quartile).

† The data are calculated based on the mean ± standard deviation of each group

Figure 1. PRISMA diagram describing the process of study selection. MAFLD=metabolic dysfunction-related fatty liver disease, NAFLD=nonalcoholic fatty liver disease.

3.2. Quality evaluation

All included studies were evaluated based on the Newcastle-Ottawa Scale, as reported in Supplemental File 3, http://links.lww.com/MD/N517. The average score for 32 articles, excluding one for which the full text was unavailable, was 6.69. Younossi,[29] Zhu,[35] and Auguet[36] received scores of 2, 4, and 5, respectively, due to unrepresentative control group selection and confounding factor issues. All other articles scored 6 or higher, and the experimental design of the included studies was generally reasonable. As all studies were observational, as per the Grading of Recommendation, Assessment, Development, and Evaluation scale (https://gdt.gradepro.org), all of the studies conducted were observational, and the degree of certainty of the evidence can only be considered very low, as noted in Supplemental File 4, http://links.lww.com/MD/N518. Furthermore, there was significant heterogeneity among the studies, which resulted in a risk of bias that was further complicated by differing confounding factors. As a result, the reliability of the findings is reduced.

3.3. Association between circulating visfatin levels and MAFLD

A meta-analysis was conducted using 33 datasets from 33 studies to investigate the relationship between circulating visfatin levels and MAFLD. As a result of high heterogeneity among studies, a random-effects model was adopted (I2 = 97.7%, P < .001) (Fig. 2A). There is no significant difference between MAFLD patients and their normal counterparts in terms of the level of circulating visfatin. (SMD = 0.13 [−0.34, 0.60]). A cumulative meta-analysis revealed that between 2013 and 2018, the circulating visfatin levels among MAFLD patients were significantly higher compared to the control group. However, after 2019, the differences in the visfatin levels between the 2 groups were no longer significant, as seen in Figure 2B. It is important to note that the Galbraith test indicated a high degree of heterogeneity, as illustrated in Figure 3. As a result, subgroup and meta-regression assessments were conducted to explain the source of heterogeneity.

Figure 2. (A) Forest plot of circulating visfatin levels between MAFLD and the healthy control group (random-effects model, SMD). (B) Cumulative meta-analysis forest plot of circulating visfatin levels between MAFLD and the healthy control group (random-effects model, SMD). CI=confidence interval, MAFLD=metabolic dysfunction-related fatty liver disease, SMD=standardized mean difference.

Figure 3. Galbraith test result of circulating visfatin levels between nonalcoholic fatty liver disease and the healthy control group.

3.4. Subgroup analyses

Subgroup analyses were conducted based on race, BMI, age, and severity to determine the source of heterogeneity.

3.4.1. Race-based subgroup analysis

Figure 4A displays the outcomes of subgroup assessment regarding race. Due to high heterogeneity (Asian: I2 = 98.2%, P < .001; Middle Eastern: I2 = 66.1%, P = .052; European: I2 = 95.5%, P < .001), an analysis of random effects was conducted. Between MAFLD patients and controls, there were no significant differences in circulating visfatin levels among Asians and Europeans (Asian: SMD = −0.01 [−0.61, 0.59]; European: SMD = 0.52 [−0.57, 1.62]). However, among Middle Eastern patients, patients with MAFLD had significantly higher levels of circulating visfatin than controls (Middle Eastern: SMD = 0.45 [0.05, 0.85]). Moreover, Figure 4A shows that the variation between study outcomes decreased among Middle Easterners, and there was no high heterogeneity.

Figure 4. Forest plot for subgroup analysis of circulating visfatin levels between MAFLD and healthy control group (random-effects model, SMD). (A) subgroup analysis by race, (B) subgroup analysis by BMI, (C) subgroup analysis by age, and (D) subgroup analysis by severity. BMI=body mass index, CI=confidence interval, MAFLD=metabolic dysfunction-related fatty liver disease, NAFL=nonalcoholic fatty liver, NASH=nonalcoholic steatohepatitis, SMD=standardized mean difference.

3.4.2. BMI-based subgroup assessment

The outcomes of subgroup assessment on BMI are presented in Figure 4B. As over half of the articles included were from Asia, an obese person was defined as having a BMI of 27.5 kg/m2 based on the expert consultation of the World Health Organization.[58] Due to high heterogeneity, a random-effects model was used. In subjects with a BMI ≥ 27.5 kg/m2, as compared to the control group, the MAFLD cohort had significantly higher levels of circulating visfatin (SMD = 1.05 [0.18, 1.92]). However, in subjects with a BMI < 27.5 kg/m2, circulating visfatin levels in the MAFLD group did not differ significantly from those in controls (SMD = −0.02 [−0.69, 0.65]). There was high heterogeneity in both subgroups (BMI < 27.5 kg/m2: I2 = 98.1%, P < .001; BMI ≥ 27.5 kg/m2: I2 = 96.3%, P < .001).

3.4.3. Age-based subgroup assessment

In Figure 4C, we present the results of the subgroup analysis based on age. The study participants were divided into 2 age groups: those aged < 50 and those aged ≥ 50 years. The high heterogeneity indicated by the I2 test for both groups led us to use a random-effects model. MAFLD and control groups did not have significantly different levels of circulating visfatin in either age group (age < 50: SMD = −0.23 [−0.88, 0.41]; age ≥ 50: SMD = 0.57 [−0.36, 1.50]).

3.4.4. Severity-based subgroup analysis

In Figure 4D, we present the outcomes of subgroup analysis concerning severity. The levels of circulating visfatin in nonalcoholic fatty liver (NAFL) and nonalcoholic steatohepatitis (NASH) groups were not statistically significant in comparison with the control group (NAFL: SMD = −0.86 [−1.77, 0.04]; NASH: SMD = −0.66 [−1.77, 0.45]). Subgrouping based on severity did not explain the high heterogeneity (NAFL: I2 = 95.3%; NASH: I2 = 97.1%).

3.5. Meta-regression

Table 2 presents the outcome of the univariate meta-regression analysis, which suggests the absence of any statistically significant variables.

Table 2 Meta-regression of MAFLD and circulating visfatin levels

Covariates	No. of studies	Coefficient	Standard error	t	P	95% CI	
Univariate meta-regression analysis	
 NOS score	32	−0.356	0.312	−1.14	0.263	(−0.992, 0.281)	
  Race	32	0.337	0.570	0.56	0.556	(−0.828, 1.502)	
  BMI	28	0.234	0.213	1.10	0.282	(−0.204, 0.671)	
  Age	27	0.036	0.067	0.54	0.592	(−0.102, 0.175)	
  AST	29	−0.021	0.028	−0.75	0.461	(−0.079, 0.037)	
  ALT	29	−0.020	0.015	−1.30	0.205	(−0.051, 0.011)	
 HOMA-IR	24	−0.190	0.182	−1.04	0.310	(−0.569, 0.189)	
Insulin/FINS	13	−0.036	0.088	−0.41	0.688	(−0.231, 0.158)	
ALT = alanine transaminase, AST = aspartate aminotransferase, BMI = body mass index, CI = confidence interval, FINS = fasting insulin, HOMA-IR = Homeostatic Model Assessment of Insulin Resistance.

3.6. Sensitivity analysis and publication bias

The overall outcomes were assessed by removing each study individually (Fig. 5). The outcomes remained relatively stable, as there was no significant impact on the outcomes regardless of which article was excluded. The funnel plot indicated a low possibility of publication bias, as there was no significant asymmetry observed (Fig. 6). The Egger and Begg tests also supported this finding, with the possibility of publication bias being low (P = .68 > .05) as illustrated in Figure 7A and 7B.

Figure 5. Sensitivity analysis plot of circulating visfatin levels between metabolic dysfunction-related fatty liver disease and the healthy control group. CI=confidence interval.

Figure 6. Funnel plot of circulating visfatin levels between metabolic dysfunction-related fatty liver disease and the healthy control group. SMD=standardized mean difference.

Figure 7. (A) Egger publication bias plot and (B) Begg publication bias plot. SMD=standardized mean difference.

4. Discussion

MAFLD is a metabolic liver disease that can be diagnosed if the following conditions are present in an individual: overweight or obesity, type 2 diabetes mellitus (T2DM), or a metabolic disorder showing evidence of liver steatosis.[59] In patients with MAFLD, there is an increased risk of the development of diabetes, chronic kidney disease, and CVD.[60] A median 5-year follow-up study has revealed that MAFLD increases the risk of developing T2DM and metabolic syndrome.[61] It is considered an early manifestation of various metabolic disorders, and early diagnosis and intervention are crucial in managing MAFLD.

Visfatin is a protein found in both intracellular (iNAMPT) and extracellular (eNAMPT) forms.[62] It is secreted in adipose tissue and can be found in liver, muscle, immune cells, and other areas.[12] The iNAMPT is a critical enzyme in nicotinamide adenine dinucleotide biosynthesis, and it regulates intracellular oxidized nicotinamide adenine dinucleotide levels, thereby affecting cellular energetics. The eNAMPT is seen as a secreted form of iNAMPT, and its role is currently undefined.[63] In rodent studies, scholars found that with the progress of obesity and natural aging, the content of iNAMPT in fat decreased.[64] The decrease of iNAMPT leads to the decrease of eNAMPT concentration, which induces the expression of cellular senescence phenotype.[65] Conversely, high levels of eNAMPT may be associated with prolonged life span in mice.[66] In humans, many diseases, such as insulin resistance, CVD, and kidney disease, are related to visfatin.[67] A clinical study by Hajianfar et al[68] showed higher visfatin levels in diabetic patients than in healthy individuals. However, while many studies have indicated that visfatin is related to the pathogenesis of gestational diabetes mellitus, a meta-assessment by Jiang et al[69] suggested that visfatin levels were independent of gestational diabetes mellitus. Zheng et al[70] evaluated visfatin levels in 97 patients and discovered that patients with atherosclerotic plaques had higher serum visfatin levels. Similarly, Chang et al[71] found increased levels of visfatin in patients with metabolic syndrome compared with those in normal subjects. This indicates that visfatin is closely related to metabolism. Garten et al[72] suggested that visfatin might affect pathogenesis via regulation of oxidative stress and apoptosis, lipid metabolism and glucose metabolism, inflammation, as well as insulin resistance.

Regrettably, the outcomes of this meta-analysis indicate no apparent distinctions in serum visfatin levels among individuals with MAFLD and controls, thus reaffirming the previous findings of Ismaiel et al.[18] Our study, in contrast to that of Ismaiel et al,[18] employed more stringent inclusion criteria for the affected group, excluded pediatric MAFLD cases, used more in-depth clinical data, and conducted searches in other databases such as CNKI, Wanfang, and CBM, besides searching PubMed, Embase, and the Cochrane Library. Concerning subgroup analysis, Ismaiel et al reported that there was no correlation between serum visfatin levels and severity of NASH or liver fibrosis; furthermore, our study also investigated whether visfatin levels were influenced by race, age, and obesity status.

A review was conducted on 33 papers from 10 different countries, which included a total of 2304 cases and 1800 controls. The findings from this review indicated that patients with MAFLD and controls did not differ significantly in serum visfatin levels. The sensitivity analysis confirmed the stability of the results, and no individual study altered the final results. Furthermore, neither the Egger test nor the funnel plot indicated any significant publication bias. However, a high degree of heterogeneity was observed in the qualitative synthesis, which could have influenced the outcomes. Therefore, it is crucial to conduct subgroup analysis. Among the subgroups stratified by race, the Middle Eastern subgroup showed a significant reduction in heterogeneity, whereas other subgroups categorized by BMI, age, and disease severity exhibited higher levels of heterogeneity.

In the analysis of subgroups by race, serum visfatin levels were found to be similar between MAFLD and control subjects in Asian and European populations. However, in the case of Middle Eastern populations, individuals with MAFLD had higher visfatin levels than controls, and this difference was found to be significant. This finding reduces the heterogeneity of the study. Previous studies have found that under the same BMI, the body fat content and fat distribution of different races are different, and the incidence of metabolic diseases such as MAFLD, obesity, and diabetes induced by them is also different. This may be influenced by special dietary habits and genetic factors.[73–75] Although we have not found any direct studies on racial differences in serum visfatin levels, considering that visfatin is mainly secreted by adipose tissue and closely related to the metabolic diseases mentioned above, we speculate that lipoprotein levels may be influenced by racial differences. As only 3 studies have been conducted among Middle Eastern populations, additional studies are needed to confirm this relationship.

According to research, BMI was found to have an impact on visfatin levels. There was a significant increase in visfatin levels among patients with a body mass index of 27.5 kg/m2 or higher compared to the control group. Despite this, there was no significant difference regarding visfatin levels between patients having a BMI lower than 27.5 kg/m2 and the control group. Obesity and MAFLD are 2 diseases that are highly correlated and result from metabolic disorders. A meta-analysis conducted in 2011 indicated that overweight/obese, metabolic syndrome, T2DM, and CVD patients have higher levels of plasma visfatin than normal subjects.[76] Abdalla[67] considered that a small elevation in visfatin levels among obese patients can aid in stabilizing blood glucose levels. However, if the concentration of visfatin surpasses a certain limit, it can trigger inflammation, causing insulin resistance. This, in turn, promotes the advancement of MAFLD.[77] In brief, visfatin is significantly associated with metabolic disorders, including obesity and MAFLD. As such, it has the potential to be a useful tool for monitoring the progression of MAFLD in overweight patients. However, further investigation is necessary to fully understand the underlying mechanism of action.

Our study has certain clinical significance. First, this meta-analysis examined the relationship between visfatin and MAFLD from different angles, making the relationship more clear. Second, we found that the visfatin level in obese MAFLD patients was higher than that in the control group, which may provide direction for future research. However, there were some limitations to this study. First, 23 of the 32 studies were conducted in China, and as such, the conclusions may reflect regional tendencies. As the attention on MAFLD is increasing globally, it is suggested that more studies from other regions be included in an updated meta-analysis in the future. Second, different manufacturers’ kits were used in the various studies, and the units for visfatin differed. The standardization of units in studies needs to be considered in future research. Although nanograms per milliliter are generally used, Gaddipati group used nanograms per milligram protein,[17] and some articles did not specify the unit used.[30,34,50] Throughout the analysis, we employed random-effects models. Additionally, we observed significant heterogeneity in the meta-analysis, which could have influenced the final outcomes. Through subgroup analysis, we determined that race might contribute to some heterogeneity, but the outcomes of the meta-regress were negative.

5. Conclusion

To summarize, there was no notable disparity in serum visfatin levels between individuals with MAFLD and the control group. However, serum visfatin level in patients with MAFLD who were either from the Middle East or had obesity exhibited significantly elevated compared to controls. Additional investigation is needed to ascertain the utility of visfatin as a viable biomarker for MAFLD.

Acknowledgments

The authors would like to thank Xin Mou in Hangzhou Red Cross Hospital for his encouragement and support.

Author contributions

Data curation: Shuaihang Chen, Kaihan Wu, Yani Ke, Shanshan Chen.

Formal analysis: Shuaihang Chen, Yani Ke, Shanshan Chen, Ran He.

Methodology: Shuaihang Chen, Yani Ke, Shan Liu.

Visualization: Shuaihang Chen, Shanshan Chen.

Writing – original draft: Shuaihang Chen.

Writing – review & editing: Shuaihang Chen, Shan Liu.

Supervision: Qin Zhang, Chenlu Shen.

Validation: Qin Zhang, Chenlu Shen, Qicong Li, Yuting Ruan, Yuqing Zhu, Keying Du.

Conceptualization: Jie Hu, Shan Liu.

Funding acquisition: Jie Hu, Shan Liu.

Supplementary Material

Abbreviations:

BMI body mass index,

CVD cardiovascular disease

eNAMPT extracellular NAMPT

iNAMPT intracellular NAMPT

MAFLD metabolic dysfunction-related fatty liver disease

NAFL nonalcoholic fatty liver

NAFLD nonalcoholic fatty liver disease

NASH nonalcoholic steatohepatitis

NAMPT nicotinamide phosphoribosyltransferase

SMD standardized mean difference,

T2DM type 2 diabetes mellitus

This study was supported by The Natural Science Foundation of Zhejiang Province, China (LQ19H290001), the research project of Zhejiang Chinese Medicine University (2021JKZKTS042B), and the Health Science and Technology Project of Zhejiang Province (2022KY921).

This study did not involve human subjects, human tissue, or animal subjects, and thus, no ethical approval was required.

The authors have no conflicts of interest to disclose.

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Supplemental Digital Content is available for this article.

How to cite this article: Chen S, Wu K, Ke Y, Chen S, He R, Zhang Q, Shen C, Li Q, Ruan Y, Zhu Y, Du K, Hu J, Liu S. Association of circulating visfatin level and metabolic fatty liver disease: An updated meta-analysis and systematic review. Medicine 2024;103:37(e39613).
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