glp-1receptoragonisteffectsonlipidandliverprofilesin

Review ArticleGLP-1 Receptor Agonist Effects on Lipid and Liver Profiles inPatients withNonalcoholic Fatty LiverDisease Systematic Reviewand Meta-Analysis

Shahla Rezaei123 Reza Tabrizi4 Peyman Nowrouzi-Sohrabi15 Mohammad Jalali13

Stephen L Atkin6 Khalid Al-Rasadi7 Tannaz Jamialahmadi8

and Amirhossein Sahebkar 91011

1Student Research Committee Shiraz University of Medical Sciences Shiraz Iran2Department of Clinical Nutrition School of Health amp Nutrition Shiraz University of Medical Sciences Shiraz Iran3Nutrition Research Center School of Nutrition and Food Sciences Shiraz University of Medical Sciences Shiraz Iran4Noncommunicable Diseases Research Center Fasa University of Medical Sciences Fasa Iran5Department of Biochemistry School of Medicine Shiraz University of Medical Sciences Shiraz Iran6Weill Cornell Medicine Qatar Doha Qatar7Medical Research Centre Sultan Qaboos University Muscat Oman8Department of Nutrition Faculty of Medicine Mashhad University of Medical Sciences Mashhad Iran9Applied Biomedical Research Center Mashhad University of Medical Sciences Mashhad Iran10Biotechnology Research Center Pharmaceutical Technology Institute Mashhad University of Medical Sciences Mashhad Iran11School of Pharmacy Mashhad University of Medical Sciences Mashhad Iran

Correspondence should be addressed to Amirhossein Sahebkar amir_saheb2000yahoocom

Received 5 August 2021 Revised 4 October 2021 Accepted 25 October 2021 Published 12 November 2021

Academic Editor Manoj K Sharma

Copyright copy 2021 Shahla Rezaei et al is is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Aims is meta-analysis of randomized placebo-controlled clinical trials assessed the effect of glucose-like peptide-1-receptoragonists (GLP-1RA) on the lipid profile and liver enzymes in patients with nonalcoholic fatty liver disease (NAFLD) Materialsand Methods Randomized placebo-controlled trials investigating GLP-1RA on the lipid profile and liver enzymes in patients withNAFLD were searched in PubMed-Medline Scopus Web of Science and Google Scholar databases (from inception to January2020) A random-effects model and a generic inverse variance method were used for quantitative data synthesis Sensitivityanalysis was conducted Weighted random-effects meta-regression was performed on potential confounders on lipid profile andliver enzyme concentrations Results 12 studies were identified (12 GLP-1RA arms 677 subjects) that showed treatment with GLP-1RA reduced alanine transaminase (ALT) concentrations (WMD minus 1014 95CI [minus 1584 minus 044] Plt 0001) gamma-glutamyltransferase (GGT) (WMD minus 1153 95CI [minus 1521minus 785] Plt 0001) and alaline phosphatase (ALP) (WMD minus 829 95CI

[minus 1134 minus 524] Plt 0001) Aspartate aminotransferase (AST) (WMD minus 295 95 CI [minus 726 137] P 018) was unchangedGLP-1 therapy did not alter triglycerides (TC) (WMD minus 707 95CI [minus 1751 337] P 018) total cholesterol (TC)(WMD minus 117 (minus 525 291) P 057) high-density lipoprotein (HDL-C) (WMD 097 95CI [minus 163 358] P 046) orlow-density lipoprotein (LDL-C) (WMD minus 167 95CI [minus 1008 674] P 069) in comparison with controls Conclusion eresults of this meta-analysis suggest that GLP-1RA treatment significantly reduces liver enzymes in patients with NAFLD but thelipid profile is unaffected

HindawiCanadian Journal of Gastroenterology and HepatologyVolume 2021 Article ID 8936865 11 pageshttpsdoiorg10115520218936865

1 Introduction

Nonalcoholic fatty liver disease (NAFLD) is an increasingglobal public health problem with a worldwide prevalence ofNAFLD estimated at approximately 25 [1] and a commoncause of chronic liver disease [2] and it is predicted todevelop in more than 30 of the US adult population [3]NAFLD is diagnosed when there is hepatic steatosis in theabsence of other causes of hepatic fat [4] In NAFLD there isan accumulation of fat in the liver through increased freefatty acid delivery to the liver increasing triglyceride syn-thesis decreasing triglyceride export and reducing beta-oxidation [5] Coexisting insulin resistance (IR) in NAFLDenhances lipolysis from the adipose tissue [5] Currentlythere are no approved drug treatments for NAFLD andNASH [6]

Glucagon-like peptide-1 receptor agonists (GLP-1RA)are a newly introduced class of antidiabetic drugs thatimprove glycemic control via several molecular pathways[7 8] ese pharmacologic agents reduce blood glucose viaglucose-dependent insulin secretion and by glucagon sup-pression [8] In addition GLP-1RAs have other beneficialeffects [9ndash16] and decrease energy intake and body weight byprolonging gastric emptying and inducing satiety [17]ereis an association between NAFLD and metabolic syndromethat causes DM dyslipidemia and obesity suggesting thatbreaking this cycle by GLP-1 agonists may have therapeuticpotential [18] particularly as they may have anti-inflam-mation activity [19] e administration of the GLP-1RAliraglutide was suggested to directly reduce liver fibrosis andsteatosis in an in vivo study [17] and reduces markers offibrosis in man [20] erefore GLP-1 receptor analoguetherapy may have the potential for the treatment of NAFLDand NASH patients however it is unclear from the studiesthat have been done whether GLP-1 agonists improve thehepatic enzyme and lipid profiles in subjects with NAFLDtherefore this systematic review and meta-analysis wereundertaken

2 Methods

21 Search Strategy is meta-analysis was conductedaccording to PRISMA instruction of systematic reviews andmeta-analysis [21] e scientific web-portals such as

PubMed Scopus Cochrane Web of Science Embase andScholar were carefully surveyed to extract all relevant lit-erature on the effects of GLP-1 receptor agonists on lipidprofile and liver enzymes in patients with nonalcoholicfatty liver disease published until January 2020 e keyterms that were applied to finalize the first step of the searchstrategy to gather target data are shown in AppendixAdditionally manual searches were performed to findarticles that were not indexed in target databases Onlyhuman-based studies were selected from the search strat-egy and language restriction was not considered Twoauthors (ShR and PN) independently surveyed the titleand abstracts of the classified papers extracted relevantdata and applied quality assessments of eligible studies Athird author (RT) checked the data and resolved alldisagreements

22 Study Selection e following strategy was utilized toselect target papers randomized clinical trials (parallel orcross-over) that investigated the effect of GLP-1 receptoragonists on the lipid profile and liver enzymes in patientswith nonalcoholic fatty liver disease individuals treated withGLP-1 receptor agonists that were compared with placebo-control or other pharmaceutical agents at least 12 weeksrsquoadministration of GLP-1 receptor agonists papers thatcontained data for standard deviation (SD) standard error(SE) and confidence interval (CI) parameters in the be-ginning and the end of each study for both the interventionand control groups

23 Data Extraction Relevant RCT data were extracted byrechecking the name of first author country the number ofindividuals in the intervention and control groups the typeand doses of GLP-1 receptor agonists duration of the studytype of the study and related data for analysis (Table 1) Foreach study the values of the mean and SD for lipid profileand liver enzymes were recorded at the beginning and theend of each study using the calculation of the differencebetween the values before and after the intervention efollowing formula was used to calculate the mean differenceof SDs

SD square root (SD baseline)2 +(SD end of study)2

minus (2r times SD baseline times SD end of study)1113960 1113961 (1)

A correlation coefficient of 05 was used for r esti-mated between 0 and 1 values [22] e formula SD

SE timesn

radic(n the number of individuals in each group) was

used to measure SD in each article that reported SE insteadof SD

24 Quality Assessment e quality assessment of the in-cluded papers in this meta-analysis was conducted based onCochrane criteria [23] Accordingly any source of bias

including selection bias performance bias detection biasattrition bias and reporting bias was judged for all in-cluded studies (Figure 1)

25 Statistical Analysis A random-effects model was per-formed using Stata v13 (StataCorp 2021 Stata StatisticalSoftware release 17 College Station TX StataCorp LLC) toobtain weighted mean difference (WMD) and corre-sponding 95 CIs Interstudy heterogeneity was

2 Canadian Journal of Gastroenterology and Hepatology

Tabl

e1

Characteristicsof

includ

edstud

ies

Firstauthor

Publication

year

Cou

ntry

Popu

latio

nAge

(con

trol

vs

interventio

n)

Samplesiz

e(con

trol

vs

interventio

n)Ty

peof

stud

yTy

peof

interventio

nCon

trol

grou

pDuration

Fanet

al

2013

China

NAFL

D+T2

DM

+ob

esity

5468plusmn1214

5102plusmn1010

6849

RCT

Exenatide

Metform

in12

weeks

Shao

etal

2014

China

NAFL

D+T2

DM

42plusmn32

43plusmn41

3030

RCT

Exenatide+

insulin

glargine

Insulin

aspart+insulin

glargine

12weeks

Arm

strong

etal

2016

UK

NASH

with

with

out

T2DM

18ndash7

077

Dou

ble-blind

rand

omized

placebo-controlled

trial

Liraglutide

Placebo

12weeks

Arm

strong

etal

2016

UK

NASH

with

with

out

T2DM

50plusmn125

0plusmn11

2223

Multicentredo

uble-

blinded

rand

omized

placebo-controlled

phase2trial

Liraglutide

Placebo

48weeks

Kho

oet

al

2017

Sing

apore

NAFL

D+ob

esity

437plusmn104

390plusmn81

1212

Pilotr

ando

mized

trial

Liraglutide

Diet+

exercise

26weeks

Wanget

al

2017

China

NAFL

D+T2

DM

40ndash7

841ndash7

54949

RCT

Exenatide+

metform

inMetform

in12

weeks

Feng

etal

2017

China

NAFL

D+T2

DM

4807plusmn1259

4679plusmn968

29145

Sing

le-centerop

en-

labelprospective

andrand

omized

trial

with

paralleld

esign

Liraglutide

Gliclazide

24weeks

Feng

etal

2017

China

NAFL

D+T2

DM

4631plusmn1232

4679plusmn968

29145

Sing

le-centerop

en-

labelprospective

andrand

omized

trial

with

paralleld

esign

Liraglutide

Metform

in24

weeks

Tian

etal

2018

China

NAFL

D+T2

DM

564plusmn84

585plusmn76

7552

RCT

Liraglutide

Metform

in12

weeks

Yanet

al

2019

China

NAFL

D+T2

DM

457plusmn92

431plusmn97

2712

Rand

omizedo

pen-

labelactiv

e-controlled

parallel-

grou

pmulticenter

trial

Liraglutide

Sitagliptin

26weeks

Yanet

al

2019

China

NAFL

D+T2

DM

456plusmn76

431plusmn97

2412

Rand

omizedo

pen-

labelactiv

e-controlled

parallel-

grou

pmulticenter

trial

Liraglutide

Insulin

glargine

+metform

in26

weeks

Kho

oet

al

2019

Sing

apore

NAFL

D436plusmn99

386plusmn82

1515

Prospective

rand

omized

pilot

stud

yLiraglutide

Diet+

exercise

26weeks

Canadian Journal of Gastroenterology and Hepatology 3

investigated by checking Cochranersquos Q test (I2 gt 50Plt 01) [24] In cases with a high amount of statisticalheterogeneity a random-effects meta-regression was ap-plied to find its potential source by confounders such as ageintervention duration baseline body weight and bodymass index (BMI) Subgroup calculation was conductedaccording to the age (ge50 years lt50 years) study duration(le12 weeks vs gt12 weeks) BMI (gt30 lt30) body weight(gt85 kg lt85 kg) and type of intervention (GLP-1 vs GLP-1 plus other treatment) to detect the source of heteroge-neity Overall sensitivity analysis was performed to assessthe dependence of pooled results by discarding each studyin turn

Estimation of the value of a correlation coefficient (r) ineach outcome was imputed from studies that reported theSD of change for each intervention group in the currentmeta-analysis e following formula was used to determinethe SD of change calculation among studies that did notprovide sufficient information [24]

R R SD2

pre + SD2post minus SD2

Change1113872 1113873

2 times SDpre times SDpost

⎡⎢⎣ ⎤⎥⎦ (2)

where R was for TC 081 TG 045 HDL-c 050 LDL-C068 AST 064 Alt 062 GGT 060 and ALP 050 We alsoconducted a sensitivity analysis for outcomes (TG AST andALT) with different values of r TG (026 and 063) AST(020 and 077) and ALT (040 and 082) to evaluate if thepooled results are sensitive to these levels

267eGradeProfile e overall evaluation of the evidencerelating to the outcomes was conducted by the Grading ofRecommendations Assessment Development and Evalua-tion (GRADE) approach (Table 2) [25]

3 Results

31 Search Results and Study Selection e flowchartexplaining the method of selection and references obtainedin the databases is shown in Figure 1 In total 2906 articleswere identified in the first phase of the literature searchAfter removal of duplicate studies (n 1013) irrelevantstudies according to the title and abstracts (n 1865)different type of intervention (n 4) conference abstracts(n 10) and Chinese language (n 1) thirteen potentially

Scre

enin

gIn

clude

dEl

igib

ility

Iden

tific

atio

n

Records identified through databasesearching (n = 2906)

PubMed (153) Scopus (1581) Wob ofScience (318) Embase (267) Cochrane

Library (87) Scholar (500)

Records after duplicates removed(n = 1893)

Records screened(n = 1893)

Full-text articles assessedfor eligibility

(n = 28)

Studies included inqualitative synthesis

(n = 13)

Studies included inquantitative synthesis

(meta-analysis)(n = 10)

Full-text articles excludedwith reasons

(n = 3)

Non clinical trial (n = 2)Not enough data for

extraction (n = 1)


(n = 15)

Conference abstract (n = 10)Chinese language (n = 1)

Non RCT (n = 4)

Records excluded bytitleabstract (n = 1865)

Figure 1 Flowchart of study selection method


eligible studies were considered for full-text review Sub-sequently three articles were excluded for the followingreasons type of study and insufficient data reportingoutcomes Ultimately ten studies were entered in thecurrent meta-analysis

32 Data Charachteristics e main characteristics of theincluded trials are shown in Table 1 All of the RCTs werepublished between 2013 and 2019 were conducted in China[26ndash31] Singapore [32 33] and UK [34 35] and lasted 12 to48 weeks A total of 677 participants were aged between 18 to70 years Seven studies used Liraglutide as an intervention[28 30ndash35] and two others [26 27 29] used exenatide plusother treatments e details of the quality assessment areshown in Figure 2

33 7e Effects of GLP-1 Receptor Agonists on Lipid Profilee results of the meta-analysis regarding the influence ofGLP-1 receptor agonists are shown in Figure 3 Pooled effectsizes indicated that receiving GLP-1 receptor agonists didnot cause a statistically significant change in serum TG(WMD minus 707 95 CI [minus 1751 337] P 018) TC(WMD minus 117 95 CI [minus 525 291] P 057) HDL-C(WMD 097 95 CI [minus 163 358] P 046) and LDL-C(WMD minus 167 95 CI [minus 1008 674] P 069) incomparison with controls

In addition based on Cochranersquos Q test low degree ofbetween-study heterogeneity was observed in TG (I2 00P 06) TC (I2 272 P 02) and HDL-C (I2 459Plt 01) Conversely LDL-C (I2 682 Plt 01) had a highamount of statistical heterogeneity

34 7e Effects of GLP-1 Receptor Agonists on Liver EnzymesFigure 4 presents the results of meta-analysis for liver en-zymes Treatment with GLP-1 receptor agonists lead to theamelioration of ALT serum concentration (WMD minus 101495 CI [minus 1584 minus 444] Plt 0001) GGT (WMD minus 115395 CI [minus 1521 minus 785] Plt 0001) and ALP(WMD minus 829 95 CI [minus 1134 minus 524] Plt 0001)However serum AST level (WMD minus 295 95 CI [minus 726137] P 018) was not significantly affected followingintervention

Regarding between-study heterogeneity Cochranersquos Qtest showed the following results ALT (I2 806 Plt 01)AST (I2 882 Plt 01) ALP (I2 392 P 019) andGGT (I2 536 Plt 01)

35 Subgroup Analysis As shown in Table 3 lipid profileswere not changed based on subgroup analysis ConverselyASTand ALTwere significantly affected when we conducteda subanalysis on duration (le12 weeks) However serumALTwas significantly changed when subjects received GLP-1agonists alone and serum AST was reduced when they

Table 2 Summary of findings

Absolute effectWMD (95 CI)

No ofstudies

Studydesign

Risk ofbias Inconsistency Indirectness Imprecision Publication

biasEffectsize

GRADEquality

Effects of GLP-1 on lipid profileTGminus 707 [minus 1751337] 9 RCT minus 1 minus 1yen 0 minus 2dagger 0 +1 ++ndashndash

(Low)TCminus 117 [minus 525291] 9 RCT minus 1lowast 0 0 minus 1 0 0 ++ndashndash

(Low)HDL-c097 [minus 163358] 8 RCT minus 1 0 0 minus 1para 0 0 ++ndashndash

(Low)LDL-cminus 167 [minus 1008674] 8 RCT minus 1 0 0 minus 2 0 0 ++ndashndash

(Low)

Effects of GLP-1 on liver enzymesASTminus 295 [minus 726137] 12 RCT minus 1 0 0 minus 2 0 0 ++ndashndash

(Low)(low)

ALTminus 1014 [minus 1584minus 444] 12 RCT minus 1 0 0 minus 1 0 +1Dagger +++ndash

(Moderate)(moderate)

e symbols ++ndashndash show the quality of evidence Abbreviations WMD weighted mean difference CI confidence interval RCT randomized controlled trialTG triglycerides TC total cholesterol HDL-c high-density lipoprotein-cholesterol LDL-c low-density lipoprotein-cholesterol AST aspartate amino-transfrase ALT alanine aminotransfrase lowastDowngraded one level as the moderate risk of bias paraDowngraded one level as the confidence interval wasmoderate daggerDowngraded two levels as the number of studies was lt5 and imprecision was considerable DaggerUpgraded one level due to considerable effect sizeyenDowngraded one level as the statistical heterogeneity was gt50


received another treatment along with GLP-1 agonists Inaddition the AST level was altered in older participants (ge50years)

36 Sensitivity Analysis and Publication Bias e sensitivityanalysis was applied using ldquoone-study-removedrdquo strategy toinvestigate the influence of each study on the effect size e

Overall (I-squared = 272 p = 0202)

Yan (a) (2019)

Armstrong (2) (2016)

Feng (1) (a) (2017)

Yan (b) (2019)

ID

Tian (2018)


Fan (2013)

Shao (2014)

Feng (1) (b) (2017)

-117 (-525 291)

271 (-1913 2455)

539 (-1208 2286)

888 (-580 2356)

-1544 (-3981 893)

WMD (95 CI)

-116 (-1137 905)

-2702 (-4649 -754)

-116 (-1178 946)

-154 (-827 519)

348 (-1042 1738)

China

UK

China

China

Country

China

UK

China

China

China

0-465 465

(a)


Fan (2013)


Tian (2018)

ID


Yan (b) (2019)

Feng (1) (a) (2017)

Yan (a) (2019)

Shao (2014)

Feng (1) (b) (2017)

-707 (-1751 337)

177 (-4030 4384)

-1768 (-7070 3534)

177 (-3885 4239)

WMD (95 CI)

-3538 (-9138 2062)

-6195 (-16025 3635)

176 (-7456 7808)

2653 (-5747 11053)

-531 (-1748 686)

-6637 (-14323 1049)

China

UK

China

Country

UK

China

China

China

China

China

0-160 160

(b)

NOTE Weights are from random effects analysis


Fan (2013)

Yan (a) (2019)

Feng (1) (b) (2017)

Feng (1) (a) (2017)



ID

Tian (2018)

Yan (b) (2019)

097 (-163 358)

000 (-778 778)

348 (-552 1248)

039 (-569 647)

039 (-554 632)

424 (059 789)

386 (-011 783)

WMD (95 CI)

-038 (-786 710)

-424 (-802 -046)

China

China

China

China

UK

UK

China

China

Country

0-125 125

(c)




Fan (2013)

Feng (1) (b) (2017)

Yan (a) (2019)


Yan (b) (2019)

ID

Feng (1) (a) (2017)

Tian (2018)

-167 (-1008 674)

-2895 (-4301 -1489)

-116 (-1058 826)

1274 (-074 2622)

348 (-1312 2008)

000 (-1824 1824)

-810 (-2509 889)

WMD (95 CI)

966 (-528 2460)

-116 (-1023 791)

UK

China

China

China

UK

China

Country

China

China

0-43 43

(d)

Figure 3 Meta-analysis of weighted mean differences estimates for lipid profiles including (a) total cholesterol (b) triglycerides (c) HDL-cholesterol and (d) LDL-cholesterol in intervention and placebo groups (CI 95)

Random sequence generation (selection bias)

Allocation concealment (selection bias)

Blinding of participants and personnel (performance bias)

Blinding of outcome assessment (detection bias)

Incomplete outcome data (attrition bias)

Selective reporting (reporting bias)

Other sources of bias (eg bias of study design trialstoppedearly extreme baseline imbalance and fraudulent trial)

Yan

et al

(201

9)

Wan

g et

al (2

017)

Tian

et al

(201

8)

Shao

et al

(201

4)

Kho

o et

al (2

019)

Kho

o et

al (2

017)

Feng

et al

(201

7)

Fan

et al

(201

3)

Arm

stron

g 2

et al

(201

6)

Arm

stron

g 1

et al

(201

6)

++

+++

++

+ +

++

++

++

+

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

ndash ndash

ndash

Figure 2 Details of quality assessment of the included papers


results of sensitivity analysis displayed that the pooled resultsof interested outcomes were not sensitive to each studyAdditionaly we checked triglycerides aspartate amino-transferase alanine aminotransferase (TG AST and ALT)with different values of r e significance of the results ofTG (r 026 I2 00 P 022 r 063 I2 00P 013) AST (r 020 I2 837 P 018 r 077I2 994 P 005) and ALT (r 040 I2 763Plt 0001 r 082 I2 865 P 0001) was independent ofdifferent values of r Due to the minimum number of studiesrequired for the assessment of publication bias by funnel plotbeing 10 and for Eggerrsquos test being 20 these tools for de-tection of publication bias would not be meaningful with sofew studies and therefore were not performed

4 Discussion

is meta-analysis showed that the combined availablestudies including liraglutide and exenatide showed animprovement in the liver enzymes of patients with NAFLDbut that the lipid profile was unchanged is suggests thatGLP-1 agonists may have utility in the treatment of NAFLDor at least prevention of further progression Similarlyhepatic histological features in patients with nonalcoholicsteatohepatitis (NAFLD with additional inflammation) wereimproved in the liraglutide group compared to placebo

(hepatocyte ballooning (61 vs 32) and steatosis (83 vs45) [34] Moreover in a recent meta-analysis of fourclinical trials histological improvement was demonstrated[36] e mechanism by which liraglutide may improveNAFLD could be through inhibiting the NLRP3 inflam-masome and pyroptosis activation through mitophagy [37]Currently there is no recognized therapeutic agent for thetreatment of NAFLD [38] however whilst the studies withthese GLP-1 agonists may be encouraging they are of tooshort a study duration to know if their effects are maintainedor that they have continued clinical therapeutic utility

Liraglutide is reported to have a cholesterol-loweringeffect though the mechanism is unclear [39] and others haveshown an improvement in lipids in nondiabetic subjects[20 40] In this meta-analysis there was no effect of GLP-1agonists on any of the lipid parameters including TG TCHDL-C (where the heterogeneity between studies was low)and LDL-C (where the heterogeneity between studies washigh) is suggests that GLP-1 agonists do not have a directeffect on lipid metabolism in NAFLD and that the lipidchanges reported in the literature may have been indirectlydue to associated weight loss through the satiety effects of theGLP-1 agonists such as liraglutide [17]

e strength of this study was that it focused on ran-domized clinical trials that would increase its power ismeta-analysis has a number of limitations Firstly the effects



Khoo (2019)


Feng (1) (b) (2017)

Yan (b) (2019)

Khoo (2017)

ID

Shao (2014)

Tian (2018)

Yan (a) (2019)

Fan (2013)


Feng (1) (a) (2017)

Wang (2017)

-295 (-726 137)

800 (-590 2190)

-3600 (-6109 -1091)

425 (-307 1157)

110 (-964 1184)

500 (-1101 2101)

WMD (95 CI)

-1394 (-2019 -769)

-091 (-334 152)

690 (-205 1585)

-278 (-554 -002)

-720 (-2201 761)

-247 (-932 438)

-1040 (-1182 -898)

Singapore

UK

China

China

Singapore

Country

China

China

China

China

UK

China

China

0-611 611

(a)

NOTE Weights are from random effectsanalysis


Yan (a) (2019)

Tian (2018)

Shao (2014)

Khoo (2019)

Fan (2013)

ID

Khoo (2017)

Wang (2017)

Yan (b) (2019)


Feng (1) (b) (2017)


Feng (1) (a) (2017)

-1014 (-1584 -444)

600 (-600 1800)

-1147 (-1651 -643)

-3047 (-3875 -2219)

1300 (-1134 3734)

-1447 (-1969 -925)

WMD (95 CI)

800 (-2218 3818)

-707 (-873 -541)

-440 (-1455 575)

-5000 (-7849 -2151)

026 (-1539 1591)

-1640 (-3693 413)

-1068 (-2616 480)

China

China

China

Singapore

China

Country

Singapore

China

China

UK

China

UK

China

0-785 785

(b)



Fan (2013)

ID

Shao (2014)


Wang (2017)


-1153 (-1521 -785)

-1622 (-2212 -1032)

WMD (95 CI)

-980 (-1365 -595)

-2500 (-5620 620)

-903 (-1080 -726)

-2650 (-4751 -549)

China

Country

China

UK

China

UK

-562 0 562

(c)


Wang (2017)

ID



-829 (-1134 -524)

-968 (-1309 -627)

WMD (95 CI)

-390 (-1320 540)

-150 (-1143 843)

China

Country

UK

UK

0-132 132

(d)

Figure 4 Meta-analysis of weighted mean differences estimates for liver enzymes including (a) aspartate aminotransferase (b) alanineaminotransferase (c) gamma-glutamyltransferase and (d) alkaline phosphatase in intervention and placebo groups (CI 95)


Table 3 e results of subgroup analysis for serum TC TG HDL-C LDL-C AST and ALT

Subgroup Study WMD(95 CI)

P

valueHeterogeneity

(I2)Meta-

regressionTest of group

differences PgtQ_bTG

Age ge50 years old 3 minus 276(minus 2835 2283) 083 00 mdash 0718

lt50 years old 6 minus 793 (minus 1936 35) 017 37

Durationle12 weeks 4 minus 547

(minus 1648 555) 033 00mdash 0373

gt12 weeks 5 minus 2110(minus 1751 337) 020 00

Baseline BMIgt30 4 minus 731

(minus 1872 410) 021 00mdash 0920

lt30 4 minus 586(minus 3157 1985) 065 00

Baseline bodyweight

gt85 kg 4 minus 731(minus 1872 410) 021 00

mdash 0920lt85 kg 4 minus 586

(minus 3157 1985) 065 00

Interventiontype

GLP-1 agonists 8 minus 1196(minus 3224 832) 024 00

mdash 0582GLP-1 agonists + othertreatment 1 minus 531

(minus 1748 686) 039 mdash

TC

Age ge50minus years old 3 minus 017 (minus 695 661) 096 00 mdash 0719lt50 years old 6 minus 173 (minus 684 337) 050 519

Duration le12 weeks 4 minus 293 (minus 774 188) 023 521 mdash 0175gt12 weeks 5 335 (minus 434 1105) 039 00

Baseline BMI gt30 4 minus 339 (minus 900 221) 023 510 mdash 0256lt30 4 133 (minus 461 728) 065 00Baseline bodyweight

gt85 kg 4 minus 339 (minus 900 221) 023 510 mdash 0256lt85 kg 4 133 (minus 461 728) 065 00

Interventiontype

GLP-1 agonists 8 minus 095 (minus 608 418) 071 362mdash 0891GLP-1 agonists + other

treatment 1 minus 154 (minus 827 519) mdash mdash

HDL-C

Age ge50 years old 3 284 (minus 018 586) 006 00 mdash 0307lt50 years old 5 040 (minus 318 398) 082 558

Duration le12 weeks 3 243 (minus 076 563) 013 00 mdash 0460gt12 weeks 5 056 (minus 321 435) 076 618

Baseline BMI gt30 4 161 (minus 303 626) 049 761 mdash 0619lt30 4 016 (minus 317 350) 092 00Baseline bodyweight

gt85 kg 4 161 (minus 303 626) 049 761 mdash 0619lt85 kg 4 016 (minus 317 350) 092 00LDL-C

Agege50 years old 3 minus 102 (minus 717 512) 074 00 045 (minus 187

278) 0890lt50 years old 5 minus 222(minus 1806 1360) 078 818

Duration le12 weeks 3 minus 948(minus 2470 574) 022 838 036 (minus 037

140) 0097gt12 weeks 5 479 (minus 248 1207) 019 58

Baseline BMI gt30 4 minus 896(minus 2442 650) 025 719 minus 343 (minus 710

022) 0155lt30 4 326 (minus 346 1000) 034 303

Baseline bodyweight

gt85 kg 4 minus 896(minus 2442 650) 025 719 minus 059 (minus 136

018)lt85 kg 4 326 (minus 346 1000) 034 303AST

Age ge50 years old 4 minus 504(minus 1124 115) 011 952 minus 031 (minus 122

058) 0663lt50 years old 8 minus 160 (minus 897 577) 067 804


of GLP-1 therapy on liver enzymes and the lipid profile inNAFLD were not the primary aim of the clinical trials andthe studies were not powered for this Secondly there wereonly 12 trials with relatively few subjects available to beanalyzed giving a modest though robust number of subjectsto undertake the analysis e meta-analysis was also limitedin that only two studies were with exenatide and the re-mainder was with liraglutide and no studies were availablefor the newer GLP-1 agonists such as semaglutide SinceGLP-1 agonists have differing structures and potencies theireffects on liver enzymes are also likely to be different [41]

5 Conclusion

e results of this meta-analysis suggest that GLP-1 agonisttreatment significantly reduces the liver enzymes ALT GGTand ALP though AST was no different in patients withNAFLD however the lipid profile is unaffected

Appendix

Search String Employed for theSystematic Review

(INDEXTERMS (ldquoGLP-1 analogrdquo OR ldquoglucagon-likepeptide-1 analogrdquo OR ldquoGLP-1 receptor agonistrdquo ORldquoglucagon-like peptide-1 receptor agonistrdquo OR ldquoglp-1 re-ceptor agonistsrdquo OR ldquoglp1 receptor agonistrdquo OR ldquogluca-gon-likerdquo OR exenatide OR lixisenatide OR eperzan ORtanzeum OR albiglutide OR dulaglutide OR liraglutide ORsemaglutide OR taspoglutide OR tanzeum OR trulicity ORbyetta OR bydureon OR victoza OR adlyxin OR ozemoicOR saxenda OR bydureon OR ldquoITCA 650rdquo OR ldquoExendin-4rdquo OR ldquoExendin 4rdquo OR byetta OR adlyxin OR lyxumia ORldquorGLP-1 proteinrdquo OR ozempic) OR TITLE-ABS-KEY(ldquoGLP-1 analogrdquo OR ldquoglucagon-like peptide-1 analogrdquo ORldquoGLP-1 receptor agonistrdquo OR ldquoglucagon-like peptide-1

receptor agonistrdquo OR ldquoglp-1 receptor agonistsrdquo OR ldquoglp1receptor agonistrdquo OR ldquoglucagon-likerdquo OR exenatide ORlixisenatide OR eperzan OR tanzeum OR albiglutide ORdulaglutide OR liraglutide OR semaglutide OR taspoglu-tide OR tanzeum OR trulicity OR byetta OR bydureon ORvictoza OR adlyxin OR ozemoic OR saxenda OR bydureonOR ldquoITCA 650rdquo OR ldquoExendin-4rdquo OR ldquoExendin 4rdquo ORbyetta OR adlyxin OR lyxumia OR ldquorGLP-1 proteinrdquo ORozempic)) AND (INDEXTERMS (NASH OR Liver ORldquoFatty Liverrdquo OR steatohepatitis OR ldquoSteatosis of LiverrdquoOR ldquoVisceral Steatosisrdquo OR steatosis OR ldquoLiver SteatosisrdquoOR ldquoNon-alcoholic Fatty Liver Diseaserdquo OR ldquoNon alco-holic Fatty Liver Diseaserdquo OR ldquoNAFLDrdquo OR ldquoNonalcoholicFatty Liver Diseaserdquo OR nonalcoholic OR ldquoNon alcoholicrdquoOR ldquoNonalcoholic Fattyrdquo OR ldquoNon-alcoholic Fattyrdquo ORldquoNonalcoholic Fatty Liverrdquo OR ldquoNonalcoholic FattyLiversrdquo OR ldquoNonalcoholic Steatohepatitisrdquo OR steatohe-patitis OR steatotic) OR TITLE-ABS-KEY (NASH ORLiver OR ldquoFatty Liverrdquo OR steatohepatitis OR ldquoSteatosis ofLiverrdquo OR ldquoVisceral Steatosisrdquo OR steatosis OR ldquoLiverSteatosisrdquo OR ldquoNon-alcoholic Fatty Liver Diseaserdquo ORldquoNon alcoholic Fatty Liver Diseaserdquo OR ldquoNAFLDrdquo ORldquoNonalcoholic Fatty Liver Diseaserdquo OR nonalcoholic ORldquoNon alcoholicrdquo OR ldquoNonalcoholic Fattyrdquo OR ldquoNon-al-coholic Fattyrdquo OR ldquoNonalcoholic Fatty Liverrdquo OR ldquoNon-alcoholic Fatty Liversrdquo OR ldquoNonalcoholic SteatohepatitisrdquoOR steatohepatitis OR steatotic)) AND (INDEXTERMS(ldquorandomized clinical trialrdquo OR ldquoRandomized controlledtrialrdquo OR ldquorandom allocationrdquo OR randomized ORldquoclinical trialrdquo OR randomlowast OR trial OR blind OR ldquocon-trolled trialrdquo OR ldquocontrolled studyrdquo OR ldquorandomized trialrdquoOR ldquoclinical studyrdquo) OR TITLE-ABS-KEY (ldquorandomizedclinical trialrdquo OR ldquoRandomized controlled trialrdquo ORldquorandom allocationrdquo OR randomized OR ldquoclinical trialrdquoOR randomlowast OR trial OR blind OR ldquocontrolled trialrdquo ORldquocontrolled studyrdquo OR ldquorandomized trialrdquo OR ldquoclinicalstudyrdquo))

Table 3 Continued


P

valueHeterogeneity

(I2)Meta-


differences PgtQ_b

Duration le12 weeks 5 minus 807 (minus 1386minus 229) 0006 944 036 (minus 022

095) 0031gt12 weeks 7 184 (minus 159 528) 029 02

Interventiontype


treatment 2 minus 1081 (minus 1303minus 859) lt0001 147

ALT

Agege50 years old 4 minus 1071

(minus 1532 minus 611) lt0001 711minus 030 (minus 186

126) 0997lt50 years old 8 minus 847

(minus 2218 524) 022 881

Duration le12 weeks 5 minus 1812(minus 2734 minus 891) lt0001 942 053 (minus 041

148) 0003gt12 weeks 7 minus 205 (minus 843 431) 052 207

Interventiontype

GLP-1 agonists 10 minus 769(minus 1420 minus 118) 002 647


(minus 4132 452) 011 966


Data Availability

ere are no raw data associated with this review article

Conflicts of Interest

e authors declare that there are no conflicts of interest

References

[1] A R Araujo N Rosso G Bedogni C Tiribelli andS Bellentani ldquoGlobal epidemiology of nonalcoholic fatty liverdiseasenonalcoholic steatohepatitis what we need in thefuturerdquo Liver International vol 38 pp 47ndash51 2018

[2] H Hagstrom P Nasr M Ekstedt et al ldquoRisk for developmentof severe liver disease in lean patients with nonalcoholic fattyliver disease a long-term follow-up studyrdquo Hepatologycommunications vol 2 no 1 pp 48ndash57 2018

[3] J Wise ldquoPioglitazone seems safe and effective for patientswith fatty liver disease and diabetesrdquo BMJ vol 353 p i34352016

[4] V W-S Wong W-K Chan S Chitturi et al ldquoAsia-pacificworking party on non-alcoholic fatty liver disease guidelines2017-part 1 definition risk factors and assessmentrdquo Journalof Gastroenterology and Hepatology vol 33 no 1 pp 70ndash852018

[5] K J P Schwenger Nonalcoholic Fatty Liver Disease Inves-tigating the Impact of Bariatric Care and the Role of ImmuneFunction University of Toronto Toronto Canada 2018

[6] Z M Younossi R Loomba M E Rinella et al ldquoCurrent andfuture therapeutic regimens for nonalcoholic fatty liver dis-ease and nonalcoholic steatohepatitisrdquo Hepatology vol 68no 1 pp 361ndash371 2018

[7] H Yaribeygi T Sathyapalan and A Sahebkar ldquoMolecularmechanisms by which GLP-1 RA and DPP-4i induce insulinsensitivityrdquo Life Sciences vol 234 Article ID 116776 2019

[8] H Yaribeygi M Maleki T Sathyapalan T Jamialahmadiand A Sahebkar ldquoAnti-inflammatory potentials of incretin-based therapies used in the management of diabetesrdquo LifeSciences vol 241 Article ID 117152 2020

[9] H Yaribeygi M Ashrafizadeh N C Henney T SathyapalanT Jamialahmadi and A Sahebkar ldquoNeuromodulatory effectsof anti-diabetes medications a mechanistic reviewrdquo Phar-macological Research vol 152 pp 1096ndash1186 2020

[10] S Radbakhsh S L Atkin L E Simental-Mendia andA Sahebkar ldquoe role of incretins and incretin-based drugs inautoimmune diseasesrdquo International Immunopharmacologyvol 98 Article ID 107845 2021

[11] H Yaribeygi S L Atkin F Montecucco T Jamialahmadiand A Sahebkar ldquoRenoprotective effects of incretin-basedtherapy in diabetes mellitusrdquo BioMed Research Internationalvol 2021 Article ID 8163153 7 pages 2021

[12] H Yaribeygi F R Farrokhi M A Abdalla et al ldquoe effectsof glucagon-like peptide-1 receptor agonists and dipepty-dilpeptidase-4 inhibitors on blood pressure and cardiovas-cular complications in diabetesrdquo Journal of Diabetes Researchvol 2021 Article ID 6518221 10 pages 2021

[13] H Yaribeygi N Katsiki A E Butler and A SahebkarldquoEffects of antidiabetic drugs on NLRP3 inflammasome ac-tivity with a focus on diabetic kidneysrdquo Drug DiscoveryToday vol 24 no 1 pp 256ndash262 2019

[14] H Yaribeygi A Rashidy-Pour S L Atkin T Jamialahmadi andA Sahebkar ldquoGLP-1 mimetics and cognitionrdquo Life Sciencesvol 264 p 118645 2021

[15] H Yaribeygi M Maleki T Sathyapalan T Jamialahmadiand A Sahebkar ldquoAntioxidative potentials of incretin-basedmedications a review of molecular mechanismsrdquo OxidativeMedicine and Cellular Longevity vol 2021 Article ID9959320 9 pages 2021

[16] G Ranjbar D P Mikhailidis and A Sahebkar ldquoEffects ofnewer antidiabetic drugs on nonalcoholic fatty liver andsteatohepatitis think out of the boxrdquo Metabolism vol 101p 154001 2019

[17] T Ohki A Isogawa M Iwamoto et al ldquoe effectiveness ofliraglutide in nonalcoholic fatty liver disease patients withtype 2 diabetes mellitus compared to sitagliptin and piogli-tazonerdquo 7e ScientificWorld Journal vol 2012 Article ID496453 8 pages 2012

[18] F Angelico M Del Ben R Conti et al ldquoInsulin resistance themetabolic syndrome and nonalcoholic fatty liver diseaserdquoJournal of Clinical Endocrinology ampMetabolism vol 90 no 3pp 1578ndash1582 2005

[19] W Zhu P-P Feng K He S-W Li and J-P Gong ldquoLir-aglutide protects non-alcoholic fatty liver disease via inhib-iting NLRP3 inflammasome activation in a mouse modelinduced by high-fat dietrdquo Biochemical and Biophysical Re-search Communications vol 505 no 2 pp 523ndash529 2018

[20] H Kahal G Abouda A S Rigby A M CoadyE S Kilpatrick and S L Atkin ldquoGlucagon-like peptide-1analogue liraglutide improves liver fibrosis markers in obesewomen with polycystic ovary syndrome and nonalcoholicfatty liver diseaserdquo Clinical Endocrinology vol 81 no 4pp 523ndash528 2014

[21] D Moher A Liberati J Tetzlaff and D G J A AltmanldquoPreferred reporting items for systematic reviews and meta-analysesrdquo7ePRISMA Statement vol 151 no 4 pp 264ndash2692009

[22] M Borenstein L V Hedges J P Higgins andH R Rothstein Introduction to Meta-Analysis John Wiley ampSons Hoboken NJ USA 2011

[23] J P T Higgins D G Altman P C Gotzsche et al ldquoeCochrane collaborationrsquos tool for assessing risk of bias inrandomised trialsrdquo BMJ vol 343 p d5928 2011

[24] J Higgins J omas J Chandler et al Cochrane Handbookfor Systematic Reviews of Interventions Cochrane HandbookLondon UK 2019

[25] G H Guyatt A D Oxman G E Vist et al ldquoGRADE anemerging consensus on rating quality of evidence andstrength of recommendationsrdquo BMJ vol 336 no 7650pp 924ndash926 2008

[26] H Fan Q Pan Y Xu and X Yang ldquoExenatide improves type2 diabetes concomitant with non-alcoholic fatty liver diseaserdquoArquivos Brasileiros de Endocrinologia ampMetabologia vol 57no 9 pp 702ndash708 2013

[27] N Shao H Y Kuang M Hao X Y Gao W J Lin andW Zou ldquoBenefits of exenatide on obesity and non-alcoholicfatty liver disease with elevated liver enzymes in patients withtype 2 diabetesrdquo Diabetes vol 30 no 6 pp 521ndash529 2014

[28] W Feng C Gao Y Bi et al ldquoRandomized trial comparing theeffects of gliclazide liraglutide and metformin on diabeteswith non-alcoholic fatty liver diseaserdquo Journal of Diabetesvol 9 no 8 pp 800ndash809 2017

[29] D J J M U Wang ldquoEffect of exenatide combined withmetformin therapy on insulin resistance liver function andinflammatory response in patients with type 2 diabetesmellitus combined with NAFLDrdquo Journal of Hainan MedicalUniversity vol 23 no 18 pp 44ndash47 2017


[30] F Tian Z Zheng D Zhang S He and J Shen ldquoEfficacy ofliraglutide in treating type 2 diabetes mellitus complicatedwith non-alcoholic fatty liver diseaserdquo Bioscience Reportsvol 38 2018

[31] J Yan B Yao H Kuang et al ldquoLiraglutide sitagliptin andinsulin glargine added tometformin the effect on body weightand intrahepatic lipid in patients with type 2 diabetes mellitusand nonalcoholic fatty liver diseaserdquo Hepatology vol 69no 6 pp 2414ndash2426 2019

[32] J Khoo J Hsiang R Taneja N M Law and T L AngldquoComparative effects of liraglutide 3mg vs structured lifestylemodification on body weight liver fat and liver function inobese patients with non-alcoholic fatty liver disease a pilotrandomized trialrdquo Diabetes Obesity and Metabolism vol 19no 12 pp 1814ndash1817 2017

[33] J Khoo M Ho S Kam et al ldquoComparing effects of lir-aglutide-induced weight loss versus lifestyle modification onliver fat content and plasma acylcarnitine levels in obeseadults with nonalcoholic fatty liver diseaserdquo Obesity Factsvol 12 p 61 2019

[34] M J Armstrong P Gaunt G P Aithal et al ldquoLiraglutidesafety and efficacy in patients with non-alcoholic steatohe-patitis (LEAN) a multicentre double-blind randomisedplacebo-controlled phase 2 studyrdquo 7e Lancet vol 387no 10019 pp 679ndash690 2016

[35] M J Armstrong D Hull K Guo et al ldquoGlucagon-likepeptide 1 decreases lipotoxicity in non-alcoholic steatohe-patitisrdquo Journal of Hepatology vol 64 no 2 pp 399ndash4082016

[36] X Lv Y Dong L Hu F Lu C Zhou and S Qin ldquoGlucagon-like peptide-1 receptor agonists (GLP-1 RAs) for the man-agement of nonalcoholic fatty liver disease (NAFLD) a sys-tematic reviewrdquo Endocrinology Diabetes ampMetabolism vol 3no 3 Article ID e00163 2020

[37] X Yu M Hao Y Liu et al ldquoLiraglutide ameliorates non-alcoholic steatohepatitis by inhibiting NLRP3 inflammasomeand pyroptosis activation via mitophagyrdquo European Journal ofPharmacology vol 864 Article ID 172715 2019

[38] Y Sumida M Yoneda K Tokushige et al ldquoAntidiabetictherapy in the treatment of nonalcoholic steatohepatitisrdquoInternational Journal of Molecular Sciences vol 21 no 62020

[39] K Aoki H Kamiyama M Takihata et al ldquoEffect of liraglutideon lipids in patients with type 2 diabetes a pilot studyrdquoEndocrine Journal vol 67 no 9 pp 957ndash962 2020

[40] H Kahal A Aburima T Ungvari et al ldquoe effects oftreatment with liraglutide on atherothrombotic risk in obeseyoung women with polycystic ovary syndrome and controlsrdquoBMC Endocrine Disorders vol 15 no 1 p 14 2015

[41] M S Capehorn A-M Catarig J K Furberg et al ldquoEfficacyand safety of once-weekly semaglutide 10mg vs once-dailyliraglutide 12mg as add-on to 1ndash3 oral antidiabetic drugs insubjects with type 2 diabetes (SUSTAIN 10)rdquo Diabetes ampMetabolism vol 46 no 2 pp 100ndash109 2020


1 Introduction

Nonalcoholic fatty liver disease (NAFLD) is an increasingglobal public health problem with a worldwide prevalence ofNAFLD estimated at approximately 25 [1] and a commoncause of chronic liver disease [2] and it is predicted todevelop in more than 30 of the US adult population [3]NAFLD is diagnosed when there is hepatic steatosis in theabsence of other causes of hepatic fat [4] In NAFLD there isan accumulation of fat in the liver through increased freefatty acid delivery to the liver increasing triglyceride syn-thesis decreasing triglyceride export and reducing beta-oxidation [5] Coexisting insulin resistance (IR) in NAFLDenhances lipolysis from the adipose tissue [5] Currentlythere are no approved drug treatments for NAFLD andNASH [6]

Glucagon-like peptide-1 receptor agonists (GLP-1RA)are a newly introduced class of antidiabetic drugs thatimprove glycemic control via several molecular pathways[7 8] ese pharmacologic agents reduce blood glucose viaglucose-dependent insulin secretion and by glucagon sup-pression [8] In addition GLP-1RAs have other beneficialeffects [9ndash16] and decrease energy intake and body weight byprolonging gastric emptying and inducing satiety [17]ereis an association between NAFLD and metabolic syndromethat causes DM dyslipidemia and obesity suggesting thatbreaking this cycle by GLP-1 agonists may have therapeuticpotential [18] particularly as they may have anti-inflam-mation activity [19] e administration of the GLP-1RAliraglutide was suggested to directly reduce liver fibrosis andsteatosis in an in vivo study [17] and reduces markers offibrosis in man [20] erefore GLP-1 receptor analoguetherapy may have the potential for the treatment of NAFLDand NASH patients however it is unclear from the studiesthat have been done whether GLP-1 agonists improve thehepatic enzyme and lipid profiles in subjects with NAFLDtherefore this systematic review and meta-analysis wereundertaken

2 Methods

21 Search Strategy is meta-analysis was conductedaccording to PRISMA instruction of systematic reviews andmeta-analysis [21] e scientific web-portals such as

PubMed Scopus Cochrane Web of Science Embase andScholar were carefully surveyed to extract all relevant lit-erature on the effects of GLP-1 receptor agonists on lipidprofile and liver enzymes in patients with nonalcoholicfatty liver disease published until January 2020 e keyterms that were applied to finalize the first step of the searchstrategy to gather target data are shown in AppendixAdditionally manual searches were performed to findarticles that were not indexed in target databases Onlyhuman-based studies were selected from the search strat-egy and language restriction was not considered Twoauthors (ShR and PN) independently surveyed the titleand abstracts of the classified papers extracted relevantdata and applied quality assessments of eligible studies Athird author (RT) checked the data and resolved alldisagreements

22 Study Selection e following strategy was utilized toselect target papers randomized clinical trials (parallel orcross-over) that investigated the effect of GLP-1 receptoragonists on the lipid profile and liver enzymes in patientswith nonalcoholic fatty liver disease individuals treated withGLP-1 receptor agonists that were compared with placebo-control or other pharmaceutical agents at least 12 weeksrsquoadministration of GLP-1 receptor agonists papers thatcontained data for standard deviation (SD) standard error(SE) and confidence interval (CI) parameters in the be-ginning and the end of each study for both the interventionand control groups

23 Data Extraction Relevant RCT data were extracted byrechecking the name of first author country the number ofindividuals in the intervention and control groups the typeand doses of GLP-1 receptor agonists duration of the studytype of the study and related data for analysis (Table 1) Foreach study the values of the mean and SD for lipid profileand liver enzymes were recorded at the beginning and theend of each study using the calculation of the differencebetween the values before and after the intervention efollowing formula was used to calculate the mean differenceof SDs

SD square root (SD baseline)2 +(SD end of study)2

minus (2r times SD baseline times SD end of study)1113960 1113961 (1)

A correlation coefficient of 05 was used for r esti-mated between 0 and 1 values [22] e formula SD

SE timesn

radic(n the number of individuals in each group) was

used to measure SD in each article that reported SE insteadof SD

24 Quality Assessment e quality assessment of the in-cluded papers in this meta-analysis was conducted based onCochrane criteria [23] Accordingly any source of bias

including selection bias performance bias detection biasattrition bias and reporting bias was judged for all in-cluded studies (Figure 1)

25 Statistical Analysis A random-effects model was per-formed using Stata v13 (StataCorp 2021 Stata StatisticalSoftware release 17 College Station TX StataCorp LLC) toobtain weighted mean difference (WMD) and corre-sponding 95 CIs Interstudy heterogeneity was


Tabl

e1

Characteristicsof

includ

edstud

ies

Firstauthor

Publication

year

Cou

ntry

Popu

latio

nAge

(con

trol

vs

interventio

n)

Samplesiz

e(con

trol

vs

interventio

n)Ty

peof

stud

yTy

peof

interventio

nCon

trol

grou

pDuration

Fanet

al

2013

China

NAFL

D+T2

DM

+ob

esity

5468plusmn1214

5102plusmn1010

6849

RCT

Exenatide

Metform

in12

weeks

Shao

etal

2014

China

NAFL

D+T2

DM

42plusmn32

43plusmn41

3030

RCT

Exenatide+

insulin

glargine

Insulin

aspart+insulin

glargine

12weeks

Arm

strong

etal

2016

UK

NASH

with

with

out

T2DM

18ndash7

077

Dou

ble-blind

rand

omized

placebo-controlled

trial

Liraglutide

Placebo

12weeks

Arm

strong

etal

2016

UK

NASH

with

with

out

T2DM

50plusmn125

0plusmn11

2223

Multicentredo

uble-

blinded

rand

omized

placebo-controlled

phase2trial

Liraglutide

Placebo

48weeks

Kho

oet

al

2017

Sing

apore

NAFL

D+ob

esity

437plusmn104

390plusmn81

1212

Pilotr

ando

mized

trial

Liraglutide

Diet+

exercise

26weeks

Wanget

al

2017

China

NAFL

D+T2

DM

40ndash7

841ndash7

54949

RCT

Exenatide+

metform

inMetform

in12

weeks

Feng

etal

2017

China

NAFL

D+T2

DM

4807plusmn1259

4679plusmn968

29145

Sing

le-centerop

en-

labelprospective

andrand

omized

trial

with

paralleld

esign

Liraglutide

Gliclazide

24weeks

Feng

etal

2017

China

NAFL

D+T2

DM

4631plusmn1232

4679plusmn968

29145

Sing

le-centerop

en-

labelprospective

andrand

omized

trial

with

paralleld

esign

Liraglutide

Metform

in24

weeks

Tian

etal

2018

China

NAFL

D+T2

DM

564plusmn84

585plusmn76

7552

RCT

Liraglutide

Metform

in12

weeks

Yanet

al

2019

China

NAFL

D+T2

DM

457plusmn92

431plusmn97

2712

Rand

omizedo

pen-

labelactiv

e-controlled

parallel-

grou

pmulticenter

trial

Liraglutide

Sitagliptin

26weeks

Yanet

al

2019

China

NAFL

D+T2

DM

456plusmn76

431plusmn97

2412

Rand

omizedo

pen-

labelactiv

e-controlled

parallel-

grou

pmulticenter

trial

Liraglutide

Insulin

glargine

+metform

in26

weeks

Kho

oet

al

2019

Sing

apore

NAFL

D436plusmn99

386plusmn82

1515

Prospective

rand

omized

pilot

stud

yLiraglutide

Diet+

exercise

26weeks




R R SD2


Change1113872 1113873


⎡⎢⎣ ⎤⎥⎦ (2)



3 Results


Scre

enin

gIn

clude

dEl

igib

ility

Iden

tific

atio

n







(n = 28)


(n = 13)




(n = 3)


extraction (n = 1)


(n = 15)


Non RCT (n = 4)













No ofstudies

Studydesign


biasEffectsize

GRADEquality





(Low)


(Low)(low)








Yan (a) (2019)


Feng (1) (a) (2017)

Yan (b) (2019)

ID

Tian (2018)


Fan (2013)

Shao (2014)

Feng (1) (b) (2017)

-117 (-525 291)

271 (-1913 2455)

539 (-1208 2286)

888 (-580 2356)

-1544 (-3981 893)

WMD (95 CI)

-116 (-1137 905)

-2702 (-4649 -754)

-116 (-1178 946)

-154 (-827 519)

348 (-1042 1738)

China

UK

China

China

Country

China

UK

China

China

China

0-465 465

(a)


Fan (2013)


Tian (2018)

ID


Yan (b) (2019)

Feng (1) (a) (2017)

Yan (a) (2019)

Shao (2014)

Feng (1) (b) (2017)

-707 (-1751 337)

177 (-4030 4384)

-1768 (-7070 3534)

177 (-3885 4239)

WMD (95 CI)

-3538 (-9138 2062)

-6195 (-16025 3635)

176 (-7456 7808)

2653 (-5747 11053)

-531 (-1748 686)

-6637 (-14323 1049)

China

UK

China

Country

UK

China

China

China

China

China

0-160 160

(b)



Fan (2013)

Yan (a) (2019)

Feng (1) (b) (2017)

Feng (1) (a) (2017)



ID

Tian (2018)

Yan (b) (2019)

097 (-163 358)

000 (-778 778)

348 (-552 1248)

039 (-569 647)

039 (-554 632)

424 (059 789)

386 (-011 783)

WMD (95 CI)

-038 (-786 710)

-424 (-802 -046)

China

China

China

China

UK

UK

China

China

Country

0-125 125

(c)




Fan (2013)

Feng (1) (b) (2017)

Yan (a) (2019)


Yan (b) (2019)

ID

Feng (1) (a) (2017)

Tian (2018)

-167 (-1008 674)

-2895 (-4301 -1489)

-116 (-1058 826)

1274 (-074 2622)

348 (-1312 2008)

000 (-1824 1824)

-810 (-2509 889)

WMD (95 CI)

966 (-528 2460)

-116 (-1023 791)

UK

China

China

China

UK

China

Country

China

China

0-43 43

(d)









Yan

et al

(201

9)

Wan

g et

al (2

017)

Tian

et al

(201

8)

Shao

et al

(201

4)

Kho

o et

al (2

019)

Kho

o et

al (2

017)

Feng

et al

(201

7)

Fan

et al

(201

3)

Arm

stron

g 2

et al

(201

6)

Arm

stron

g 1

et al

(201

6)

++

+++

++

+ +

++

++

++

+

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

ndash ndash

ndash




4 Discussion







Khoo (2019)


Feng (1) (b) (2017)

Yan (b) (2019)

Khoo (2017)

ID

Shao (2014)

Tian (2018)

Yan (a) (2019)

Fan (2013)


Feng (1) (a) (2017)

Wang (2017)

-295 (-726 137)

800 (-590 2190)

-3600 (-6109 -1091)

425 (-307 1157)

110 (-964 1184)

500 (-1101 2101)

WMD (95 CI)

-1394 (-2019 -769)

-091 (-334 152)

690 (-205 1585)

-278 (-554 -002)

-720 (-2201 761)

-247 (-932 438)

-1040 (-1182 -898)

Singapore

UK

China

China

Singapore

Country

China

China

China

China

UK

China

China

0-611 611

(a)



Yan (a) (2019)

Tian (2018)

Shao (2014)

Khoo (2019)

Fan (2013)

ID

Khoo (2017)

Wang (2017)

Yan (b) (2019)


Feng (1) (b) (2017)


Feng (1) (a) (2017)

-1014 (-1584 -444)

600 (-600 1800)

-1147 (-1651 -643)

-3047 (-3875 -2219)

1300 (-1134 3734)

-1447 (-1969 -925)

WMD (95 CI)

800 (-2218 3818)

-707 (-873 -541)

-440 (-1455 575)

-5000 (-7849 -2151)

026 (-1539 1591)

-1640 (-3693 413)

-1068 (-2616 480)

China

China

China

Singapore

China

Country

Singapore

China

China

UK

China

UK

China

0-785 785

(b)



Fan (2013)

ID

Shao (2014)


Wang (2017)


-1153 (-1521 -785)

-1622 (-2212 -1032)

WMD (95 CI)

-980 (-1365 -595)

-2500 (-5620 620)

-903 (-1080 -726)

-2650 (-4751 -549)

China

Country

China

UK

China

UK

-562 0 562

(c)


Wang (2017)

ID



-829 (-1134 -524)

-968 (-1309 -627)

WMD (95 CI)

-390 (-1320 540)

-150 (-1143 843)

China

Country

UK

UK

0-132 132

(d)





P

valueHeterogeneity

(I2)Meta-






(minus 1648 555) 033 00mdash 0373



(minus 1872 410) 021 00mdash 0920

lt30 4 minus 586(minus 3157 1985) 065 00

Baseline bodyweight

gt85 kg 4 minus 731(minus 1872 410) 021 00


(minus 3157 1985) 065 00

Interventiontype



(minus 1748 686) 039 mdash

TC





Interventiontype



HDL-C








140) 0097gt12 weeks 5 479 (minus 248 1207) 019 58


022) 0155lt30 4 326 (minus 346 1000) 034 303

Baseline bodyweight


018)lt85 kg 4 326 (minus 346 1000) 034 303AST





5 Conclusion


Appendix




Table 3 Continued


P

valueHeterogeneity

(I2)Meta-


differences PgtQ_b


095) 0031gt12 weeks 7 184 (minus 159 528) 029 02

Interventiontype



ALT




(minus 2218 524) 022 881



Interventiontype



(minus 4132 452) 011 966


Data Availability




References












































Tabl

e1

Characteristicsof

includ

edstud

ies

Firstauthor

Publication

year

Cou

ntry

Popu

latio

nAge

(con

trol

vs

interventio

n)

Samplesiz

e(con

trol

vs

interventio

n)Ty

peof

stud

yTy

peof

interventio

nCon

trol

grou

pDuration

Fanet

al

2013

China

NAFL

D+T2

DM

+ob

esity

5468plusmn1214

5102plusmn1010

6849

RCT

Exenatide

Metform

in12

weeks

Shao

etal

2014

China

NAFL

D+T2

DM

42plusmn32

43plusmn41

3030

RCT

Exenatide+

insulin

glargine

Insulin

aspart+insulin

glargine

12weeks

Arm

strong

etal

2016

UK

NASH

with

with

out

T2DM

18ndash7

077

Dou

ble-blind

rand

omized

placebo-controlled

trial

Liraglutide

Placebo

12weeks

Arm

strong

etal

2016

UK

NASH

with

with

out

T2DM

50plusmn125

0plusmn11

2223

Multicentredo

uble-

blinded

rand

omized

placebo-controlled

phase2trial

Liraglutide

Placebo

48weeks

Kho

oet

al

2017

Sing

apore

NAFL

D+ob

esity

437plusmn104

390plusmn81

1212

Pilotr

ando

mized

trial

Liraglutide

Diet+

exercise

26weeks

Wanget

al

2017

China

NAFL

D+T2

DM

40ndash7

841ndash7

54949

RCT

Exenatide+

metform

inMetform

in12

weeks

Feng

etal

2017

China

NAFL

D+T2

DM

4807plusmn1259

4679plusmn968

29145

Sing

le-centerop

en-

labelprospective

andrand

omized

trial

with

paralleld

esign

Liraglutide

Gliclazide

24weeks

Feng

etal

2017

China

NAFL

D+T2

DM

4631plusmn1232

4679plusmn968

29145

Sing

le-centerop

en-

labelprospective

andrand

omized

trial

with

paralleld

esign

Liraglutide

Metform

in24

weeks

Tian

etal

2018

China

NAFL

D+T2

DM

564plusmn84

585plusmn76

7552

RCT

Liraglutide

Metform

in12

weeks

Yanet

al

2019

China

NAFL

D+T2

DM

457plusmn92

431plusmn97

2712

Rand

omizedo

pen-

labelactiv

e-controlled

parallel-

grou

pmulticenter

trial

Liraglutide

Sitagliptin

26weeks

Yanet

al

2019

China

NAFL

D+T2

DM

456plusmn76

431plusmn97

2412

Rand

omizedo

pen-

labelactiv

e-controlled

parallel-

grou

pmulticenter

trial

Liraglutide

Insulin

glargine

+metform

in26

weeks

Kho

oet

al

2019

Sing

apore

NAFL

D436plusmn99

386plusmn82

1515

Prospective

rand

omized

pilot

stud

yLiraglutide

Diet+

exercise

26weeks




R R SD2


Change1113872 1113873


⎡⎢⎣ ⎤⎥⎦ (2)



3 Results


Scre

enin

gIn

clude

dEl

igib

ility

Iden

tific

atio

n







(n = 28)


(n = 13)




(n = 3)


extraction (n = 1)


(n = 15)


Non RCT (n = 4)













No ofstudies

Studydesign


biasEffectsize

GRADEquality





(Low)


(Low)(low)








Yan (a) (2019)


Feng (1) (a) (2017)

Yan (b) (2019)

ID

Tian (2018)


Fan (2013)

Shao (2014)

Feng (1) (b) (2017)

-117 (-525 291)

271 (-1913 2455)

539 (-1208 2286)

888 (-580 2356)

-1544 (-3981 893)

WMD (95 CI)

-116 (-1137 905)

-2702 (-4649 -754)

-116 (-1178 946)

-154 (-827 519)

348 (-1042 1738)

China

UK

China

China

Country

China

UK

China

China

China

0-465 465

(a)


Fan (2013)


Tian (2018)

ID


Yan (b) (2019)

Feng (1) (a) (2017)

Yan (a) (2019)

Shao (2014)

Feng (1) (b) (2017)

-707 (-1751 337)

177 (-4030 4384)

-1768 (-7070 3534)

177 (-3885 4239)

WMD (95 CI)

-3538 (-9138 2062)

-6195 (-16025 3635)

176 (-7456 7808)

2653 (-5747 11053)

-531 (-1748 686)

-6637 (-14323 1049)

China

UK

China

Country

UK

China

China

China

China

China

0-160 160

(b)



Fan (2013)

Yan (a) (2019)

Feng (1) (b) (2017)

Feng (1) (a) (2017)



ID

Tian (2018)

Yan (b) (2019)

097 (-163 358)

000 (-778 778)

348 (-552 1248)

039 (-569 647)

039 (-554 632)

424 (059 789)

386 (-011 783)

WMD (95 CI)

-038 (-786 710)

-424 (-802 -046)

China

China

China

China

UK

UK

China

China

Country

0-125 125

(c)




Fan (2013)

Feng (1) (b) (2017)

Yan (a) (2019)


Yan (b) (2019)

ID

Feng (1) (a) (2017)

Tian (2018)

-167 (-1008 674)

-2895 (-4301 -1489)

-116 (-1058 826)

1274 (-074 2622)

348 (-1312 2008)

000 (-1824 1824)

-810 (-2509 889)

WMD (95 CI)

966 (-528 2460)

-116 (-1023 791)

UK

China

China

China

UK

China

Country

China

China

0-43 43

(d)









Yan

et al

(201

9)

Wan

g et

al (2

017)

Tian

et al

(201

8)

Shao

et al

(201

4)

Kho

o et

al (2

019)

Kho

o et

al (2

017)

Feng

et al

(201

7)

Fan

et al

(201

3)

Arm

stron

g 2

et al

(201

6)

Arm

stron

g 1

et al

(201

6)

++

+++

++

+ +

++

++

++

+

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

ndash ndash

ndash




4 Discussion







Khoo (2019)


Feng (1) (b) (2017)

Yan (b) (2019)

Khoo (2017)

ID

Shao (2014)

Tian (2018)

Yan (a) (2019)

Fan (2013)


Feng (1) (a) (2017)

Wang (2017)

-295 (-726 137)

800 (-590 2190)

-3600 (-6109 -1091)

425 (-307 1157)

110 (-964 1184)

500 (-1101 2101)

WMD (95 CI)

-1394 (-2019 -769)

-091 (-334 152)

690 (-205 1585)

-278 (-554 -002)

-720 (-2201 761)

-247 (-932 438)

-1040 (-1182 -898)

Singapore

UK

China

China

Singapore

Country

China

China

China

China

UK

China

China

0-611 611

(a)



Yan (a) (2019)

Tian (2018)

Shao (2014)

Khoo (2019)

Fan (2013)

ID

Khoo (2017)

Wang (2017)

Yan (b) (2019)


Feng (1) (b) (2017)


Feng (1) (a) (2017)

-1014 (-1584 -444)

600 (-600 1800)

-1147 (-1651 -643)

-3047 (-3875 -2219)

1300 (-1134 3734)

-1447 (-1969 -925)

WMD (95 CI)

800 (-2218 3818)

-707 (-873 -541)

-440 (-1455 575)

-5000 (-7849 -2151)

026 (-1539 1591)

-1640 (-3693 413)

-1068 (-2616 480)

China

China

China

Singapore

China

Country

Singapore

China

China

UK

China

UK

China

0-785 785

(b)



Fan (2013)

ID

Shao (2014)


Wang (2017)


-1153 (-1521 -785)

-1622 (-2212 -1032)

WMD (95 CI)

-980 (-1365 -595)

-2500 (-5620 620)

-903 (-1080 -726)

-2650 (-4751 -549)

China

Country

China

UK

China

UK

-562 0 562

(c)


Wang (2017)

ID



-829 (-1134 -524)

-968 (-1309 -627)

WMD (95 CI)

-390 (-1320 540)

-150 (-1143 843)

China

Country

UK

UK

0-132 132

(d)





P

valueHeterogeneity

(I2)Meta-






(minus 1648 555) 033 00mdash 0373



(minus 1872 410) 021 00mdash 0920

lt30 4 minus 586(minus 3157 1985) 065 00

Baseline bodyweight

gt85 kg 4 minus 731(minus 1872 410) 021 00


(minus 3157 1985) 065 00

Interventiontype



(minus 1748 686) 039 mdash

TC





Interventiontype



HDL-C








140) 0097gt12 weeks 5 479 (minus 248 1207) 019 58


022) 0155lt30 4 326 (minus 346 1000) 034 303

Baseline bodyweight


018)lt85 kg 4 326 (minus 346 1000) 034 303AST





5 Conclusion


Appendix




Table 3 Continued


P

valueHeterogeneity

(I2)Meta-


differences PgtQ_b


095) 0031gt12 weeks 7 184 (minus 159 528) 029 02

Interventiontype



ALT




(minus 2218 524) 022 881



Interventiontype



(minus 4132 452) 011 966


Data Availability




References














































R R SD2


Change1113872 1113873


⎡⎢⎣ ⎤⎥⎦ (2)



3 Results


Scre

enin

gIn

clude

dEl

igib

ility

Iden

tific

atio

n







(n = 28)


(n = 13)




(n = 3)


extraction (n = 1)


(n = 15)


Non RCT (n = 4)













No ofstudies

Studydesign


biasEffectsize

GRADEquality





(Low)


(Low)(low)








Yan (a) (2019)


Feng (1) (a) (2017)

Yan (b) (2019)

ID

Tian (2018)


Fan (2013)

Shao (2014)

Feng (1) (b) (2017)

-117 (-525 291)

271 (-1913 2455)

539 (-1208 2286)

888 (-580 2356)

-1544 (-3981 893)

WMD (95 CI)

-116 (-1137 905)

-2702 (-4649 -754)

-116 (-1178 946)

-154 (-827 519)

348 (-1042 1738)

China

UK

China

China

Country

China

UK

China

China

China

0-465 465

(a)


Fan (2013)


Tian (2018)

ID


Yan (b) (2019)

Feng (1) (a) (2017)

Yan (a) (2019)

Shao (2014)

Feng (1) (b) (2017)

-707 (-1751 337)

177 (-4030 4384)

-1768 (-7070 3534)

177 (-3885 4239)

WMD (95 CI)

-3538 (-9138 2062)

-6195 (-16025 3635)

176 (-7456 7808)

2653 (-5747 11053)

-531 (-1748 686)

-6637 (-14323 1049)

China

UK

China

Country

UK

China

China

China

China

China

0-160 160

(b)



Fan (2013)

Yan (a) (2019)

Feng (1) (b) (2017)

Feng (1) (a) (2017)



ID

Tian (2018)

Yan (b) (2019)

097 (-163 358)

000 (-778 778)

348 (-552 1248)

039 (-569 647)

039 (-554 632)

424 (059 789)

386 (-011 783)

WMD (95 CI)

-038 (-786 710)

-424 (-802 -046)

China

China

China

China

UK

UK

China

China

Country

0-125 125

(c)




Fan (2013)

Feng (1) (b) (2017)

Yan (a) (2019)


Yan (b) (2019)

ID

Feng (1) (a) (2017)

Tian (2018)

-167 (-1008 674)

-2895 (-4301 -1489)

-116 (-1058 826)

1274 (-074 2622)

348 (-1312 2008)

000 (-1824 1824)

-810 (-2509 889)

WMD (95 CI)

966 (-528 2460)

-116 (-1023 791)

UK

China

China

China

UK

China

Country

China

China

0-43 43

(d)









Yan

et al

(201

9)

Wan

g et

al (2

017)

Tian

et al

(201

8)

Shao

et al

(201

4)

Kho

o et

al (2

019)

Kho

o et

al (2

017)

Feng

et al

(201

7)

Fan

et al

(201

3)

Arm

stron

g 2

et al

(201

6)

Arm

stron

g 1

et al

(201

6)

++

+++

++

+ +

++

++

++

+

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

ndash ndash

ndash




4 Discussion







Khoo (2019)


Feng (1) (b) (2017)

Yan (b) (2019)

Khoo (2017)

ID

Shao (2014)

Tian (2018)

Yan (a) (2019)

Fan (2013)


Feng (1) (a) (2017)

Wang (2017)

-295 (-726 137)

800 (-590 2190)

-3600 (-6109 -1091)

425 (-307 1157)

110 (-964 1184)

500 (-1101 2101)

WMD (95 CI)

-1394 (-2019 -769)

-091 (-334 152)

690 (-205 1585)

-278 (-554 -002)

-720 (-2201 761)

-247 (-932 438)

-1040 (-1182 -898)

Singapore

UK

China

China

Singapore

Country

China

China

China

China

UK

China

China

0-611 611

(a)



Yan (a) (2019)

Tian (2018)

Shao (2014)

Khoo (2019)

Fan (2013)

ID

Khoo (2017)

Wang (2017)

Yan (b) (2019)


Feng (1) (b) (2017)


Feng (1) (a) (2017)

-1014 (-1584 -444)

600 (-600 1800)

-1147 (-1651 -643)

-3047 (-3875 -2219)

1300 (-1134 3734)

-1447 (-1969 -925)

WMD (95 CI)

800 (-2218 3818)

-707 (-873 -541)

-440 (-1455 575)

-5000 (-7849 -2151)

026 (-1539 1591)

-1640 (-3693 413)

-1068 (-2616 480)

China

China

China

Singapore

China

Country

Singapore

China

China

UK

China

UK

China

0-785 785

(b)



Fan (2013)

ID

Shao (2014)


Wang (2017)


-1153 (-1521 -785)

-1622 (-2212 -1032)

WMD (95 CI)

-980 (-1365 -595)

-2500 (-5620 620)

-903 (-1080 -726)

-2650 (-4751 -549)

China

Country

China

UK

China

UK

-562 0 562

(c)


Wang (2017)

ID



-829 (-1134 -524)

-968 (-1309 -627)

WMD (95 CI)

-390 (-1320 540)

-150 (-1143 843)

China

Country

UK

UK

0-132 132

(d)





P

valueHeterogeneity

(I2)Meta-






(minus 1648 555) 033 00mdash 0373



(minus 1872 410) 021 00mdash 0920

lt30 4 minus 586(minus 3157 1985) 065 00

Baseline bodyweight

gt85 kg 4 minus 731(minus 1872 410) 021 00


(minus 3157 1985) 065 00

Interventiontype



(minus 1748 686) 039 mdash

TC





Interventiontype



HDL-C








140) 0097gt12 weeks 5 479 (minus 248 1207) 019 58


022) 0155lt30 4 326 (minus 346 1000) 034 303

Baseline bodyweight


018)lt85 kg 4 326 (minus 346 1000) 034 303AST





5 Conclusion


Appendix




Table 3 Continued


P

valueHeterogeneity

(I2)Meta-


differences PgtQ_b


095) 0031gt12 weeks 7 184 (minus 159 528) 029 02

Interventiontype



ALT




(minus 2218 524) 022 881



Interventiontype



(minus 4132 452) 011 966


Data Availability




References





















































No ofstudies

Studydesign


biasEffectsize

GRADEquality





(Low)


(Low)(low)








Yan (a) (2019)


Feng (1) (a) (2017)

Yan (b) (2019)

ID

Tian (2018)


Fan (2013)

Shao (2014)

Feng (1) (b) (2017)

-117 (-525 291)

271 (-1913 2455)

539 (-1208 2286)

888 (-580 2356)

-1544 (-3981 893)

WMD (95 CI)

-116 (-1137 905)

-2702 (-4649 -754)

-116 (-1178 946)

-154 (-827 519)

348 (-1042 1738)

China

UK

China

China

Country

China

UK

China

China

China

0-465 465

(a)


Fan (2013)


Tian (2018)

ID


Yan (b) (2019)

Feng (1) (a) (2017)

Yan (a) (2019)

Shao (2014)

Feng (1) (b) (2017)

-707 (-1751 337)

177 (-4030 4384)

-1768 (-7070 3534)

177 (-3885 4239)

WMD (95 CI)

-3538 (-9138 2062)

-6195 (-16025 3635)

176 (-7456 7808)

2653 (-5747 11053)

-531 (-1748 686)

-6637 (-14323 1049)

China

UK

China

Country

UK

China

China

China

China

China

0-160 160

(b)



Fan (2013)

Yan (a) (2019)

Feng (1) (b) (2017)

Feng (1) (a) (2017)



ID

Tian (2018)

Yan (b) (2019)

097 (-163 358)

000 (-778 778)

348 (-552 1248)

039 (-569 647)

039 (-554 632)

424 (059 789)

386 (-011 783)

WMD (95 CI)

-038 (-786 710)

-424 (-802 -046)

China

China

China

China

UK

UK

China

China

Country

0-125 125

(c)




Fan (2013)

Feng (1) (b) (2017)

Yan (a) (2019)


Yan (b) (2019)

ID

Feng (1) (a) (2017)

Tian (2018)

-167 (-1008 674)

-2895 (-4301 -1489)

-116 (-1058 826)

1274 (-074 2622)

348 (-1312 2008)

000 (-1824 1824)

-810 (-2509 889)

WMD (95 CI)

966 (-528 2460)

-116 (-1023 791)

UK

China

China

China

UK

China

Country

China

China

0-43 43

(d)









Yan

et al

(201

9)

Wan

g et

al (2

017)

Tian

et al

(201

8)

Shao

et al

(201

4)

Kho

o et

al (2

019)

Kho

o et

al (2

017)

Feng

et al

(201

7)

Fan

et al

(201

3)

Arm

stron

g 2

et al

(201

6)

Arm

stron

g 1

et al

(201

6)

++

+++

++

+ +

++

++

++

+

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

ndash ndash

ndash




4 Discussion







Khoo (2019)


Feng (1) (b) (2017)

Yan (b) (2019)

Khoo (2017)

ID

Shao (2014)

Tian (2018)

Yan (a) (2019)

Fan (2013)


Feng (1) (a) (2017)

Wang (2017)

-295 (-726 137)

800 (-590 2190)

-3600 (-6109 -1091)

425 (-307 1157)

110 (-964 1184)

500 (-1101 2101)

WMD (95 CI)

-1394 (-2019 -769)

-091 (-334 152)

690 (-205 1585)

-278 (-554 -002)

-720 (-2201 761)

-247 (-932 438)

-1040 (-1182 -898)

Singapore

UK

China

China

Singapore

Country

China

China

China

China

UK

China

China

0-611 611

(a)



Yan (a) (2019)

Tian (2018)

Shao (2014)

Khoo (2019)

Fan (2013)

ID

Khoo (2017)

Wang (2017)

Yan (b) (2019)


Feng (1) (b) (2017)


Feng (1) (a) (2017)

-1014 (-1584 -444)

600 (-600 1800)

-1147 (-1651 -643)

-3047 (-3875 -2219)

1300 (-1134 3734)

-1447 (-1969 -925)

WMD (95 CI)

800 (-2218 3818)

-707 (-873 -541)

-440 (-1455 575)

-5000 (-7849 -2151)

026 (-1539 1591)

-1640 (-3693 413)

-1068 (-2616 480)

China

China

China

Singapore

China

Country

Singapore

China

China

UK

China

UK

China

0-785 785

(b)



Fan (2013)

ID

Shao (2014)


Wang (2017)


-1153 (-1521 -785)

-1622 (-2212 -1032)

WMD (95 CI)

-980 (-1365 -595)

-2500 (-5620 620)

-903 (-1080 -726)

-2650 (-4751 -549)

China

Country

China

UK

China

UK

-562 0 562

(c)


Wang (2017)

ID



-829 (-1134 -524)

-968 (-1309 -627)

WMD (95 CI)

-390 (-1320 540)

-150 (-1143 843)

China

Country

UK

UK

0-132 132

(d)





P

valueHeterogeneity

(I2)Meta-






(minus 1648 555) 033 00mdash 0373



(minus 1872 410) 021 00mdash 0920

lt30 4 minus 586(minus 3157 1985) 065 00

Baseline bodyweight

gt85 kg 4 minus 731(minus 1872 410) 021 00


(minus 3157 1985) 065 00

Interventiontype



(minus 1748 686) 039 mdash

TC





Interventiontype



HDL-C








140) 0097gt12 weeks 5 479 (minus 248 1207) 019 58


022) 0155lt30 4 326 (minus 346 1000) 034 303

Baseline bodyweight


018)lt85 kg 4 326 (minus 346 1000) 034 303AST





5 Conclusion


Appendix




Table 3 Continued


P

valueHeterogeneity

(I2)Meta-


differences PgtQ_b


095) 0031gt12 weeks 7 184 (minus 159 528) 029 02

Interventiontype



ALT




(minus 2218 524) 022 881



Interventiontype



(minus 4132 452) 011 966


Data Availability




References















































Yan (a) (2019)


Feng (1) (a) (2017)

Yan (b) (2019)

ID

Tian (2018)


Fan (2013)

Shao (2014)

Feng (1) (b) (2017)

-117 (-525 291)

271 (-1913 2455)

539 (-1208 2286)

888 (-580 2356)

-1544 (-3981 893)

WMD (95 CI)

-116 (-1137 905)

-2702 (-4649 -754)

-116 (-1178 946)

-154 (-827 519)

348 (-1042 1738)

China

UK

China

China

Country

China

UK

China

China

China

0-465 465

(a)


Fan (2013)


Tian (2018)

ID


Yan (b) (2019)

Feng (1) (a) (2017)

Yan (a) (2019)

Shao (2014)

Feng (1) (b) (2017)

-707 (-1751 337)

177 (-4030 4384)

-1768 (-7070 3534)

177 (-3885 4239)

WMD (95 CI)

-3538 (-9138 2062)

-6195 (-16025 3635)

176 (-7456 7808)

2653 (-5747 11053)

-531 (-1748 686)

-6637 (-14323 1049)

China

UK

China

Country

UK

China

China

China

China

China

0-160 160

(b)



Fan (2013)

Yan (a) (2019)

Feng (1) (b) (2017)

Feng (1) (a) (2017)



ID

Tian (2018)

Yan (b) (2019)

097 (-163 358)

000 (-778 778)

348 (-552 1248)

039 (-569 647)

039 (-554 632)

424 (059 789)

386 (-011 783)

WMD (95 CI)

-038 (-786 710)

-424 (-802 -046)

China

China

China

China

UK

UK

China

China

Country

0-125 125

(c)




Fan (2013)

Feng (1) (b) (2017)

Yan (a) (2019)


Yan (b) (2019)

ID

Feng (1) (a) (2017)

Tian (2018)

-167 (-1008 674)

-2895 (-4301 -1489)

-116 (-1058 826)

1274 (-074 2622)

348 (-1312 2008)

000 (-1824 1824)

-810 (-2509 889)

WMD (95 CI)

966 (-528 2460)

-116 (-1023 791)

UK

China

China

China

UK

China

Country

China

China

0-43 43

(d)









Yan

et al

(201

9)

Wan

g et

al (2

017)

Tian

et al

(201

8)

Shao

et al

(201

4)

Kho

o et

al (2

019)

Kho

o et

al (2

017)

Feng

et al

(201

7)

Fan

et al

(201

3)

Arm

stron

g 2

et al

(201

6)

Arm

stron

g 1

et al

(201

6)

++

+++

++

+ +

++

++

++

+

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

++

+

ndash ndash

ndash




4 Discussion







Khoo (2019)


Feng (1) (b) (2017)

Yan (b) (2019)

Khoo (2017)

ID

Shao (2014)

Tian (2018)

Yan (a) (2019)

Fan (2013)


Feng (1) (a) (2017)

Wang (2017)

-295 (-726 137)

800 (-590 2190)

-3600 (-6109 -1091)

425 (-307 1157)

110 (-964 1184)

500 (-1101 2101)

WMD (95 CI)

-1394 (-2019 -769)

-091 (-334 152)

690 (-205 1585)

-278 (-554 -002)

-720 (-2201 761)

-247 (-932 438)

-1040 (-1182 -898)

Singapore

UK

China

China

Singapore

Country

China

China

China

China

UK

China

China

0-611 611

(a)



Yan (a) (2019)

Tian (2018)

Shao (2014)

Khoo (2019)

Fan (2013)

ID

Khoo (2017)

Wang (2017)

Yan (b) (2019)


Feng (1) (b) (2017)


Feng (1) (a) (2017)

-1014 (-1584 -444)

600 (-600 1800)

-1147 (-1651 -643)

-3047 (-3875 -2219)

1300 (-1134 3734)

-1447 (-1969 -925)

WMD (95 CI)

800 (-2218 3818)

-707 (-873 -541)

-440 (-1455 575)

-5000 (-7849 -2151)

026 (-1539 1591)

-1640 (-3693 413)

-1068 (-2616 480)

China

China

China

Singapore

China

Country

Singapore

China

China

UK

China

UK

China

0-785 785

(b)



Fan (2013)

ID

Shao (2014)


Wang (2017)


-1153 (-1521 -785)

-1622 (-2212 -1032)

WMD (95 CI)

-980 (-1365 -595)

-2500 (-5620 620)

-903 (-1080 -726)

-2650 (-4751 -549)

China

Country

China

UK

China

UK

-562 0 562

(c)


Wang (2017)

ID



-829 (-1134 -524)

-968 (-1309 -627)

WMD (95 CI)

-390 (-1320 540)

-150 (-1143 843)

China

Country

UK

UK

0-132 132

(d)





P

valueHeterogeneity

(I2)Meta-






(minus 1648 555) 033 00mdash 0373



(minus 1872 410) 021 00mdash 0920

lt30 4 minus 586(minus 3157 1985) 065 00

Baseline bodyweight

gt85 kg 4 minus 731(minus 1872 410) 021 00


(minus 3157 1985) 065 00

Interventiontype



(minus 1748 686) 039 mdash

TC





Interventiontype



HDL-C








140) 0097gt12 weeks 5 479 (minus 248 1207) 019 58


022) 0155lt30 4 326 (minus 346 1000) 034 303

Baseline bodyweight


018)lt85 kg 4 326 (minus 346 1000) 034 303AST





5 Conclusion


Appendix




Table 3 Continued


P

valueHeterogeneity

(I2)Meta-


differences PgtQ_b


095) 0031gt12 weeks 7 184 (minus 159 528) 029 02

Interventiontype



ALT




(minus 2218 524) 022 881



Interventiontype



(minus 4132 452) 011 966


Data Availability




References













































4 Discussion







Khoo (2019)


Feng (1) (b) (2017)

Yan (b) (2019)

Khoo (2017)

ID

Shao (2014)

Tian (2018)

Yan (a) (2019)

Fan (2013)


Feng (1) (a) (2017)

Wang (2017)

-295 (-726 137)

800 (-590 2190)

-3600 (-6109 -1091)

425 (-307 1157)

110 (-964 1184)

500 (-1101 2101)

WMD (95 CI)

-1394 (-2019 -769)

-091 (-334 152)

690 (-205 1585)

-278 (-554 -002)

-720 (-2201 761)

-247 (-932 438)

-1040 (-1182 -898)

Singapore

UK

China

China

Singapore

Country

China

China

China

China

UK

China

China

0-611 611

(a)



Yan (a) (2019)

Tian (2018)

Shao (2014)

Khoo (2019)

Fan (2013)

ID

Khoo (2017)

Wang (2017)

Yan (b) (2019)


Feng (1) (b) (2017)


Feng (1) (a) (2017)

-1014 (-1584 -444)

600 (-600 1800)

-1147 (-1651 -643)

-3047 (-3875 -2219)

1300 (-1134 3734)

-1447 (-1969 -925)

WMD (95 CI)

800 (-2218 3818)

-707 (-873 -541)

-440 (-1455 575)

-5000 (-7849 -2151)

026 (-1539 1591)

-1640 (-3693 413)

-1068 (-2616 480)

China

China

China

Singapore

China

Country

Singapore

China

China

UK

China

UK

China

0-785 785

(b)



Fan (2013)

ID

Shao (2014)


Wang (2017)


-1153 (-1521 -785)

-1622 (-2212 -1032)

WMD (95 CI)

-980 (-1365 -595)

-2500 (-5620 620)

-903 (-1080 -726)

-2650 (-4751 -549)

China

Country

China

UK

China

UK

-562 0 562

(c)


Wang (2017)

ID



-829 (-1134 -524)

-968 (-1309 -627)

WMD (95 CI)

-390 (-1320 540)

-150 (-1143 843)

China

Country

UK

UK

0-132 132

(d)





P

valueHeterogeneity

(I2)Meta-






(minus 1648 555) 033 00mdash 0373



(minus 1872 410) 021 00mdash 0920

lt30 4 minus 586(minus 3157 1985) 065 00

Baseline bodyweight

gt85 kg 4 minus 731(minus 1872 410) 021 00


(minus 3157 1985) 065 00

Interventiontype



(minus 1748 686) 039 mdash

TC





Interventiontype



HDL-C








140) 0097gt12 weeks 5 479 (minus 248 1207) 019 58


022) 0155lt30 4 326 (minus 346 1000) 034 303

Baseline bodyweight


018)lt85 kg 4 326 (minus 346 1000) 034 303AST





5 Conclusion


Appendix




Table 3 Continued


P

valueHeterogeneity

(I2)Meta-


differences PgtQ_b


095) 0031gt12 weeks 7 184 (minus 159 528) 029 02

Interventiontype



ALT




(minus 2218 524) 022 881



Interventiontype



(minus 4132 452) 011 966


Data Availability




References














































P

valueHeterogeneity

(I2)Meta-






(minus 1648 555) 033 00mdash 0373



(minus 1872 410) 021 00mdash 0920

lt30 4 minus 586(minus 3157 1985) 065 00

Baseline bodyweight

gt85 kg 4 minus 731(minus 1872 410) 021 00


(minus 3157 1985) 065 00

Interventiontype



(minus 1748 686) 039 mdash

TC





Interventiontype



HDL-C








140) 0097gt12 weeks 5 479 (minus 248 1207) 019 58


022) 0155lt30 4 326 (minus 346 1000) 034 303

Baseline bodyweight


018)lt85 kg 4 326 (minus 346 1000) 034 303AST





5 Conclusion


Appendix




Table 3 Continued


P

valueHeterogeneity

(I2)Meta-


differences PgtQ_b


095) 0031gt12 weeks 7 184 (minus 159 528) 029 02

Interventiontype



ALT




(minus 2218 524) 022 881



Interventiontype



(minus 4132 452) 011 966


Data Availability




References













































5 Conclusion


Appendix




Table 3 Continued


P

valueHeterogeneity

(I2)Meta-


differences PgtQ_b


095) 0031gt12 weeks 7 184 (minus 159 528) 029 02

Interventiontype



ALT




(minus 2218 524) 022 881



Interventiontype



(minus 4132 452) 011 966


Data Availability




References












































Data Availability




References












































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