the second affiliated hospital of chongqing...prof. paul j. gaglio new york, usa ping gu new york,...

Prof. Hong RenGeneral Editor-in-Chief

The Second Affiliated Hospital of Chongqing Medical University, China

Dr. Harry Hua-Xiang XiaEditor-in-Chief

Novartis Pharmaceuticals Corporation, USA

Prof. George Y. WuComprehensive Editor-in-Chief

University of Connecticut Heath Center, USA

Editors-in-Chief

Managing Editors

Dr. Huaidong HuThe Second Affiliated Hospital of Chongqing

Medical University, China

Dr. Zhi PengThe Second Affiliated Hospital of Chongqing

Medical University, China

Associate Editors

Dr. Timothy BilliarF-1281 Presbyterian University Hospital Pittsburgh, USA

Dr. John BirkUniversity of ConnecticutFarmington, USA

Prof. Limin ChenPeking Union Medical College Chengdu, China

Prof. Chengwei ChenNanjing Military Command Shanghai, China

Prof. Aziz A. ChentoufiMedicine King Fahad Medical College Riyadh, Saudi Arabia

Prof. Xiaoguang DouShengjing Hospital of China Medical UniversityShengyang, China

Prof. Zhongping DuanAffiliated Beijing You'an Hospital of Capital Medical UniversityBeijing, China

Dr. Jean-François DufourUniversity of Bern Bern, Switzerland

Prof. Marko DuvnjakClinical Hospital Centre “Sestre milosrdnice”Zagreb, Croatia

Prof. Faripour ForouharUniversity of ConnecticutFarmington, USA

Dr. Johannes HaybaeckMedical University GrazGraz, Austria

Prof. Jinlin HouNanfang Hospital of Southern Medical UniversityGuangzhou, China

Prof. Keqin HuUniversity of CaliforniaOrange, USA

Prof. Ailong HuangChongqing Medical UniversityChongqing, China

Dr. Hitoshi IkedaThe University of TokyoTokyo, Japan

Prof. Jidong JiaCapital Medical UniversityBeijing, China

Prof. Yong LiaoThe Second Hospital Affiliated Chongqing Medical UniversityChongqing, China

Dr. Joseph LimYale UniversityNew Haven, USA

Prof. Lungen LuShanghai Jiaotong University School of MedicineShanghai, China

Dr. John LukJohnson & Johnson Medical Ltd.Shanghai, China

Prof. Yen-Hsuan NiNational Taiwan UniversityTaipei, Taiwan

Prof. Kannika PhornphutkulChiang Mai UniversityChiangmai, Thailand

Dr. Kittichai PromratAlpert Medical School of Brown UniversityProvidence, USA

Prof. Cheng QianThird Military Medical University Southwest HospitalChongqing, China

Dr. Arielle RosenbergUniversity Paris DescartesParis, France

Prof. Naoya SakamotoHokkaido UniversitySapporo, Japan

Dr. Michael SchilskyYale UniversityNew Haven, USA

Dr. Tawesak TanwandeeSiriraj Hospital, Mahidol UniversityBangkok, Thailand

Prof. Lai WeiPeking University People’s HospitalBeijing, China

Dr. Xuefeng XiaThe Methodist Hospital Research InstituteHouston, USA

Dr. Kecheng XuFuda Cancer HospitalGuangzhou, China

Prof. Man-Fung YuenThe University of Hong Kong Queen Mary HospitalHong Kong, China

Dr. Jinxiang ZhangTongji Medical CollegeHuazhong University of Science and TechnologyWuhan, China

Prof. Dazhi ZhangThe Second Affiliated Hospital of Chongqing Medical UniversityChongqing, China

Dr. Lanjing ZhangUniversity Medical Center of Princeton Plainsboro, USA

OWNED BY THE SECOND AFFILIATED HOSPITAL OF CHONGQING MEDICAL UNIVERSITY

Editorial Board

Dr.Subrat Kumar AcharyaNew Delhi, India Dr. Piero Luigi AlmasioPalermo, ItalyDr. Costica AlomanNew York, USAProf. Gianfranco D. AlpiniBryan, USADr. Masahiro AraiTokyo, JapanDr. Gyorgy BaffyBoston, USADr. Savino BrunoMilan, ItalyDr. Chalermrat BunchorntavakulBangkok, ThailandDr. Wendy CaoNew York, USAProf. Mark J. CzajaNew York, USADr. Andres CardenasBarcelona, SpainProf. Flair José Carrilho São Paulo, BrazilDr. Phunchai CharatcharoenwitthayaBangkok, Thailand Prof. Zhi ChenHangzhou, ChinaDr. Silvia Degli-EspostiProvidence, USAProf. Lei DongXi’an, ChinaDr. Yu-Chen FanJinan, ChinaDr. Peter FerenciHeidelberg, AustriaProf. Eduardo Fernández-MartínezHidalgo, MexicoDr. Heather L. FrancisBryan, USADr. James Y.Y. FungHong Kong, ChinaProf. Paul J. GaglioNew York, USAPing GuNew York, USAProf. Ahmet GurakarBaltimore, USAProf. Steven-Huy Bui HanLos Angeles, USAProf. Tao HanTianjin, ChinaProf. Ying HanXi'an, ChinaProf. Saeed HamidKarachi, ParkistanDr. Kazuhiko HayashiNagoya, Japan

Dr. Wasim JafriAga Khan, ParkistanDr. Di JiaBoston, USADr. Wei JiaKunming, ChinaDr. Jiaji JiangFuzhou, ChinaDr. Jianning JiangNanning, ChinaProf. Xiang-Jun JiangQingdao, ChinaDr. Anastasios KoulaouzidisEdinburgh, United KingdomDr. Ashish KumarNew Delhi, IndiaProf. Laurentius A. LesmanaJakarta, IndonesiaDr. Bing LiuGuangzhou, ChinaDr. Rohit LoombaSan Diego, USAProf. Eduardo MartinezHidalgo, MexicoProf. Jane McKeatingBirmingham, United KingdomProf. Albert D. MinSan Diego, USAProf. Ming KuangGuangzhou, ChinaDr. Mohamed OthmanEl Paso, USAProf. Jin-Jiang PangShanghai, ChinaProf. Piero PortincasaBari, ItalyDr. Farzin RoohvandTehran, IranDr. Regina SantellaNew York, USADr. Ke-Qing ShiWenzhou, ChinaProf. Gamal ShihaMansoura, EgyptDr. Robert SmolicOsijek, CroatiaDr. Martina SmolicOsijek, CroatiaDr. Qingfeng SunWenzhou, ChinaProf. Gloria TalianiRoma, ItalyProf. Hong TangChengdu, ChinaDr. Claudio TiribelliTrieste, ItalyProf. Zhengkun TuChangchun, China

Dr. Adriana VinceZagreb, CroatiaDr. Farzin RoohvandParis, France/IranDr. Fusheng WangBeijing, ChinaProf. Genshu WangGuangzhou, ChinaDr. Leyi WangColumbus, USAProf. Benjamin WongHong Kong, ChinaProf. Catherine Y. WuFarmington, USADr. Yongning XinQingdao, ChinaProf. Huiping YanBeijing, ChinaProf. Ming YanShangdong, ChinaProf. Eric M. YoshidaVancouver, CanadaDr. Hong YouBeijing, ChinaProf. Yu-Feng YuanWuhan, ChinProf. Cihan YurdaydinAnkara, TurkeyProf. Mikio ZeniyaTokyo, JapanProf. Xinxin ZhangShanghai, ChinaDr. Yuanyuan ZhangChengdu, ChinaProf. Yuexin ZhangXinjiang, ChinaProf. Jingmin ZhaoBeijing, ChinaDr. Minghua ZhengWenzhou, ChinaDr. Senlin ZhuGuangzhou, China

Telephone

Fax

E-mail

Address

+86 23 63727251

+86 23 63701383

[email protected]

74 Linjiang Road, Yuzhong District, Chongqing, P. R. China, 400010

JCTH

Contact information

JOURNAL OF CLINICAL ANDTRANSLATIONAL HEPATOLOGY

Call for papers

JCTH is a new, comprehensive specialist journal focusing on the recent progress in clinical and basic

research with direct applications to clinical management of liver diseases. The studies published in JCTH

will represent the most current trends in the field of hepatology, highlighting the topically relevant

subjects of nations worldwide. Publications in JCTH will be presented in formats that emphasize clarity

of the study’s objectives and implications of its findings, using high quality visual aids to enhance the

manuscript’s esthetic appeal as well as its impact. For our upcoming issue, we encourage you and your

group to submit original articles that showcase your work in hepatology and topically relevant reviews to

promote our readers’ understanding of the field.

CONTENTS 2015 3(1):1–84

Original Articles

Secondary Structural Elements of the HCV X-region Involved in Viral ReplicationNidhi Gupta, Catherine H. Wu and George Y. Wu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Diabetes Mellitus Predicts Occurrence of Cirrhosis and Hepatocellular Cancer in Alcoholic Liverand Non-alcoholic Fatty Liver DiseasesEvan J. Raff, Donny Kakati, Joseph R. Bloomer, Mohamed Shoreibah, Khalid Rasheedand and

Ashwani K. Singal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Review Articles

Acute Hepatic PorphyriaD. Montgomery Bissell and Bruce Wang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Sofosbuvir, a Significant Paradigm Change in HCV TreatmentThomas McQuaid, Carolyn Savini and Star Seyedkazemi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Chronic Hepatitis C Infection in Children: Current Treatment and New TherapiesAndrew Lee, Jeremy Rajanayagam and Mona Abdel-Hady . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Update on Autoimmune HepatitisRodrigo Liberal, Diego Vergani and Giorgina Mieli-Vergani . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Animal Models for Fibrotic Liver Diseases: What We Have, What We Need, and What Is underDevelopmentBénédicte Delire, Peter Stärkel and Isabelle Leclercq . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

An Update to Hepatobiliary StentsBrian T. Moy and John W. Birk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Nonalcoholic Fatty Liver Disease: Dyslipidemia, Risk for Cardiovascular Complications, andTreatment StrategyQing-Qing Zhang and Lun-Gen Lu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

Secondary Structural Elements of the HCV X-region Involvedin Viral Replication

Nidhi Gupta, Catherine H. Wu and George Y. Wu*

Department of Medicine, Division of Gastroenterology-Hepatology, University of Connecticut Health Center, Farmington, CT, USA

Abstract

Background and Aims: The noncoding regions in the 39-untranslated region (UTR) of the hepatitis C virus (HCV)genome contain secondary structures that are important forreplication. The aim of this study was to identify detailedconformational elements of the X-region involved in HCVreplication. Methods: Ribonucleic acid (RNA) structuralanalogs X94, X12, and X12c were constructed to haveidentical conformation but 94%, 12%, and 0% sequenceidentity, respectively, to the X region of HCV genotype 2a.Effects of structural analogs on replication of HCV genotypes1b and 2a HCV RNA were studied by quantitative reversetranscriptase polymerase chain reaction. Results: In repliconBB7 cells, a constitutive replication model, HCV RNA levelsdecreased to 55%, 52%, 53%, and 54% after transfectionwith expression plasmids generating RNA structural analogs5B-46, X-94, X-12, and X-12c, respectively (p,0.001 for all).In an HCV genotype 2a infection model, RNA analogs 5B-46,X-94, and X-12 in hepatic cells inhibited replication to 11%,9%, and 12%, respectively. Because the X-12 analog wasonly 12% identical to the corresponding sequence of HCVgenotype 2a, the sequence per se, or antisense effects wereunlikely to be involved. Conclusions: The data suggest thatconformation of secondary structures in 39-UTR of HCV RNAgenome is required for HCV replication. Stable expression ofRNA analogs predicted to have identical stem-loop structuresmight inhibit HCV infection of hepatocytes in liver and mayrepresent a novel approach to design anti-HCV agents.

E 2015 The Second Affiliated Hospital of Chongqing MedicalUniversity. Published by XIA & HE Publishing Ltd. All rightsreserved.

Introduction

Hepatitis C virus (HCV) is a ribonucleic acid (RNA) virus thatcauses chronic hepatitis and liver failure, worldwide.1,2 Itconsists of six different genotypes that are differentiallydistributed geographically.3,4 Success of treatment variesgreatly depending on the genotype.4,5 The genome containscis-acting replication elements (CREs) that are critical forHCV RNA replication and translation.6,7 RNA structural ele-ments present in 59- and 39-untranslated regions (39UTR) ofthe HCV genome interact with viral and cellular proteinsto initiate and facilitate the replication and translationprocesses.8–11 In our previous studies, we showed that RNAsecondary structure of the nonstructural (NS)5B codingregion of the HCV genome was required for HCV RNAreplication, and hence viral particle production.12–15 It hasbeen shown that the X region in the 39-UTR of the HCV RNAgenome contains a highly conserved sequence.16 The latterhave also been found to form stable secondary stem-loopstructures that require physical contact between its RNA-dependent RNA polymerase for HCV replication.17–19 Wehypothesized that RNA structural analogs resembling sec-ondary stem-loop structure of the X region could be createdthat can compete with natural HCV genomic structure forbinding to proteins and inhibit HCV replication. The aim of thisstudy was to introduce RNA structural analogs resemblingthese CREs into human liver cells and to identify secondarystructural elements of the HCV X-region involved in HCVreplication and infection.

Materials and methods

Cell culture

In order to identify important secondary structural elements,the effects of HCV structural analogs on HCV replication intwo model cell lines were studied: a constitutive replicationmodel and an infection model. In addition, to evaluatewhether differences in viral genotype could affect the possibleinteractions of structural analogs, viruses representing twodifferent genotypes 1 and 2, were studied.

A genotype 1b BB7 constitutive replication system

Replicon cells, BB7, a cell culture system containing the HCVgenotype 1b genome, were obtained from Apath (St. Louis,USA).20,21 Cells were maintained in Dulbecco’s Modified EagleMedium (DMEM) supplemented with antibiotic/antimycoticsolution (Invitrogen, USA), 10% fetal bovine serum (FBS)and 0.5 mg/mL G418.

Keywords: HCV RNA genome; HCV X-region; Hepatitis C virus; Infection;Japanese Fulminant Hepatitis Virus; RNA secondary structure.Abbreviations: 39UTR, 39-untranslated regions; cDNA, complementary deoxyr-ibonucleic acid; CREs, cis-acting replication elements; CMV, cytomegalovirus;DMEM, Dulbecco’s Modified Eagle Medium; FBS, fetal bovine serum; HCV,hepatitis C virus; JFH-1, Japanese Fulminant Hepatitis Virus-1; LDHA, lactatedehydrogenase A; MTT, 3-(4,5-dimethylthiazol-2-Yl)-2,5-diphenyltetrazoliumbromide; NS, nonstructural; nt, nucleotide; PBS, phosphate buffered saline;qRT-PCR, quantitative reverse transcriptase polymerase chain reaction; RNA,ribonucleic acid; UTR, untranslated region.Received: 02 February 2015; Revised: 26 February 2015; Accepted: 01March 2015

*Correspondence to: George Y. Wu, Department of Medicine, Division ofGastroenterology-Hepatology, University of Connecticut Health Center, 263Farmington Ave, Farmington, CT 06030-1845, USA. Tel: +1-800-535-6232; +1-860-679-7692, Fax: +1-860-679-3159, E-mail: [email protected]

qDOI: 10.14218/JCTH.2015.00003.

Original Article

Journal of Clinical and Translational Hepatology 2015 vol. 3 | 1–8

A Japanese Fulminant Hepatitis Virus-1 (JFH-1) HCVinfection system

For JFH-1 HCV genotype 2a studies, Huh7.5 cells (humanhepatoma cell line) (obtained from Dr. Charles Rice,Rockefeller University, NY, USA) were maintained in DMEMsupplemented with antibiotic/antimycotic solution and 10%FBS. JFH-1 complementary deoxyribonucleic acid (cDNA), anHCV genotype 2a strain, from Dr. Takaji Wakita (NationalInstitute of Infectious Diseases, Tokyo, Japan)22–24 was usedto produce infectious HCV viral particles in Huh7.5.25,26 Tomake JFH-1 HCV stocks for infection, Huh 7.5 cells wereinfected with JFH-1 HCV. Media were collected 5 days post-infection and centrifuged at 10006g for 20 min to removedebris. JFH-1 HCV in media was concentrated with acentrifugal device (100K NMWL, Amicon ultra, Millipore,USA). Stocks were frozen at 280 C̊ until further use.Infectivity levels of viral stocks were checked by quantitationof JFH-1 HCV RNA in media 48 h post-infection of Huh7.5cells with HCV genotype 2a specific primers (Table 1) usingreal time reverse transcriptase polymerase chain reaction(RT-PCR). The PCR conditions were: one cycle of 2 min at 50

˚C and 10 min at 95 C̊ followed by 40 cycles of 15 sec at95 C̊ and 1 min at 60 C̊. Specificity of all designed primerswas determined with PCR amplification and sequencing ofamplified product (data not shown). Melt curve analysiswas performed following each RT-PCR to identify the pre-sence of primer dimers and analyze the specificity of thereaction.

RNA structural analogs

RNA structural analog X-94 was designed to be 100%identical to the (+) strand of X-region (9508-9605 nucleotides(nt)) on the 39-end of the HCV genotype 1b (94% identical togenotype 2a) genome (Fig. 1A). To determine whether stem-loop structures versus specific sequences of HCV of RNAwere most important in HCV replication, base pair changes,described below, were made in stems (analog X-12) andloops (analog X-12c) of analog X-94 (Fig. 1B and 1D). Severalsoftware products are available for prediction of secondarystructures of RNA based on thermodynamic parameters.Because of its high reliability and reproducibility, Mfold ver3.2 was used in the current study.27–29 RNA structuralanalogs X-12 and X-12c were predicted to adopt stem-loopstructure identical to analog X-94 (Fig. 1B and 1D). Table 3shows the percent identity of the various RNA structuralanalogs with HCV genotypes 1b and 2a. To determine the

minimal structure of the X-region that could inhibit HCV RNAreplication, shorter RNA structural analogs X-12a and X-12b(Fig. 1C) were designed that were predicted to retainindividual stem-loop structures of analog X-94.27–29 Allanalogs were named based on HCV genome region studiedand sequence homology of the analogues relative to theJFH-1 HCV genotype 2a genome.

Cloning and expression

For expression studies, the X-94 sequence was subcloned intoa pSilencer 4.1 cytomegalovirus (CMV) puro plasmid (Ambion,USA), as previously described.12 pSilencer 4.1 CMV puroplasmid enables high level expression of cloned hairpin shortRNA templates. Expression vectors for RNA structural analogsX-12 and X-12c were constructed from a plasmid expressingthe RNA analog X-94 using a QuikChange II Site-DirectedMutagenesis Kit (Agilent Technologies, Inc. USA) according tomanufacturer’s instructions. Fig. 1B shows nucleotide repla-cements made in stems of analog X-94 resulting in analog X-12, and Fig. 1D illustrates nucleotide replacements made inloops of analog X-12 to construct analog X-12c. Shorter RNAstructural analogs X-12a and X-12b (Fig. 1C) were con-structed from a plasmid expressing RNA analog X-12 using aQuikChange II Site-Directed Mutagenesis Kit. Thesesequences were selected as non-overlapping fragments of X-12 that were individually predicted by Mfold to retain all thestructural elements present in the parent X-12 analog. 5B-74RNA analog, which was previously shown to inhibit viralgenome replication12 was used as a positive control forinhibition of viral replication, and a plasmid expressing anunrelated sequence, HB, from hepatitis B virus was used asnegative control. An RNA structural analog 5B-46 waspredicted to adopt stem-loop structures identical to analog5B-74 as determined by Mfold, and was constructed using aplasmid expressing RNA analog 5B-74 with QuikChange IISite-Directed Mutagenesis Kit. Sequences of each analog inpSilencer 4.1 CMV puro plasmid (Ambion) were verified withCMV puro primers (Table 1) as recommended by the manu-facturer.

For BB7HCV genotype 1b replicon studies, cells were platedin 6-well plates 2 days before transfection. Seventy-fivepercent confluent cells were transfected with various amountsof each plasmid to generate RNA structural analogs individu-ally or in combinations using lipofectamine (Life Technologies)according to manufacturer’s instructions. In brief, lipofecta-mine and plasmid DNA were separately diluted in Opti-MEM Imedium (Invitrogen) without serum. After 15 min incubation,

Table 1. Sequences of primers used for quantification

Primers Sequences

LDHA FW 59 TAATGAAGGACTTGGCAGATGAACT 39

LDHA RV 59 ACGGCTTTCTCCCTCTTGCT 39

HCV1b FW 59 CTGTCTTCACGCAGAAAGCG 39

HCV1b RV 59 CACTCGCAAGCACCCTATCA 39

CMV puro FW 59 AGGCGATTAAGTTGGGTA 39

CMV puro RV 59 CGGTAGGCGTGTACGGTG 39

JFH1 HCV FW 59 TAGGAGGGCCCATGTTCAAC 39

JFH1 HCV RV 59 CCCCTGGCTTTCTGAGATGAC 39

CMV, cytomegalovirus; FW, forward; HCV, hepatitis C virus; JFH-1, Japanese Fulminant Hepatitis Virus-1; LDHA, lactate dehydrogenase A; RV, reverse.

Gupta N. et al: RNA structures involved in viral replication

2 Journal of Clinical and Translational Hepatology 2015 vol. 3 | 1–8

they were combined, incubated for 20 min at room tempera-ture, and added to cells in varying concentrations. Cells wereharvested 48 h post-transfection with Trizol (Invitrogen), andHCV RNA levels quantitated in the cell lysates.

For HCV genotype 2a infection studies, two models wereused: transfection into cells with a pre-existing infection andtransfection into cells before infection. For pre-existing JFH-1HCV infection studies, 75% confluent Huh7.5 cells wereinfected with JFH-1 HCV for 8 h and then transfected withplasmids expressing RNA structural analogs with lipofecta-mine, as described above. In brief, cells were washed withphosphate buffered saline (PBS). Lipofectamine and plasmid

DNA were separately diluted in Opti-MEM I medium withoutserum. After a 15 min incubation, they were combined, andincubated for 20 min at room temperature before beingadded to cells. Culture medium, 200 mL, was collected forquantification of JFH-1 HCV levels, and replaced with fresh200 mL of cell culture medium at 0, 4, 8, 12, 24, 36, 48, and72 h of transfection.

For before infection studies, 75% confluent Huh7.5 cells in6-well plates were transfected with 16 mg of each plasmidexpressing RNA structural analogs, as described above. Cellswere then infected with JFH-1 HCV 48 h post-transfection.After 8 h of infection, cells were washed twice with PBS to

Fig. 1. A, a diagram of the Mfold ver3.2 computed secondary structure of analog X-94; B, a diagram of nt replacementsmade in the stems of analog X-94 toconstruct analog X-12 (secondary structure of X-12 was predicted identical to X-94); C, a diagram of analogs X-12a and X-12b, non-overlappingfragments of analog X-12; D, a diagram of nucleotide replacementsmade in loops of analog X-12 to construct analog X-12c (secondary structure of X-12cwas predicted to be identical to X-94).


Journal of Clinical and Translational Hepatology 2015 vol. 3 | 1–8 3

remove input JFH-1 HCV. Culture medium, 200 mL, wascollected for quantification of JFH-1 HCV levels and replacedwith fresh 200 mL of cell culture medium at 0, 4, 8, 12, 24, 36,48, and 72 h of infection.

Quantitative RT-PCR (qRT-PCR)

For BB7 HCV genotype 1b studies, whole cell RNA wasisolated from replicon cell lysates with an RNeasy kit(Qiagen, Germany) according to manufacturer’s instructionsand treated with RNase free DNase (Invitrogen). cDNA wassynthesized using 4 mg DNase treated RNA with SuperScriptIII First-Strand kit (Invitrogen) and quantified by real timeRT-PCR with Power SYBR Green PCR Master Mix (AppliedBiosystems, USA) using HCV genotype 1b specific primers(Table 1) according to manufacturer’s instructions. Humanlactate dehydrogenase A (LDHA) mRNA levels were quanti-fied in each sample to normalize HCV RNA levels using humanLDHA specific primers (Table 1). Assays were done inquadruplicate, and results expressed as mean ± standarderror of HCV RNA levels in cells transfected with analogscompared to untreated controls.

For JFH-1 HCV infection studies, viral RNA was extractedfrom 200 mL media collected from infected cells with aQIAamp Viral RNA kit (Qiagen, Germany) according tomanufacturer’s instructions. cDNA was synthesized using4 mg RNA with SuperScript III First-Strand kit (Invitrogen),and quantified by real-time RT-PCR with Power SYBR GreenPCR Master Mix (Applied Biosystems) using JFH-1 HCV RNAspecific primers (Table 1) according to manufacturer’sinstructions. Assays were repeated with three independentreplicates, and results are expressed as means ± standarderror of JFH-1 HCV RNA levels in media from infected cellstransfected with analogs before or after infection compared tountreated controls.

Results

Table 2 shows the sequence of all RNA structural analogs.Analogs X-94 and X-12 were 100% and 59% identical to HCVgenotype 1b, respectively, but were only 94% and 12%identical to the JFH-1 HCV genome, respectively. Analog

X-12c was 50% identical to HCV genotype 1b, and 0%identical to the JFH-1 HCV genome.

To determine whether short RNA sequences predicted tofold into secondary structural analogs of the X region of HCVRNA genome could inhibit HCV replication, plasmids expres-sing RNA analogs X-94, X-12, and X-12c were transfected inreplicon cells. Fig. 2 shows that the effects of transfection ofplasmids expressing RNA structural analogs were dose-dependent and most effective at 16 mg of plasmid. Higherdoses did not increase effects beyond those at 16 mg, andbased on this information, 16 mg of each plasmid was used fortransfection for subsequent experiments. 3-(4,5-dimethy-lthiazol-2-Yl)-2,5-diphenyltetrazolium bromide (MTT) assaysshowed no significant toxic effects due to DNA transfection(data not shown).

Fig. 3 shows that transfection of plasmids generatingRNA analogs affected HCV RNA levels in replicon cells.After transfection of 5B-74, 5B-46, X-94, X-12, and X-12cat 16 mg, HCV RNA levels were decreased to 42%, 55%, 52%,53%, and 54%, respectively, compared to levels of untreatedcontrols. These differences were significant (p,0.001 for all).An unrelated control plasmid (HB) generating an HBVsequence had no significant effect under identical conditions.Furthermore, combinations of 5B-74 plus X-94 and 5B-46plus X-12 administered at the same total dose, and underidentical conditions, decreased HCV RNA levels to 21% and30%, (p,0.001), respectively, compared to untreated con-trols (Fig. 3). These levels of inhibition for the combinationswere greater than that for any individual analog alone.

The X-region analog is 98 nt long. We wondered whethersmaller structural elements could be produced that retainedinhibitory effects. To test this hypothesis, two smalleranalogs, X-12a and X-12b, were created that correspondedto nt 1-55 and nt 56-95 regions, respectively, of analog X-12(Fig. 1C). Transfection with X-12a decreased HCV RNA to58%, about the same as intact X-12 (p,0.001). However, theother fragment, X-12b, was much less effective, resultingin a level of only 78% and not significantly different fromuntreated control. A combination of X-12a plus X-12binhibited levels to 60% of untreated controls, which wassimilar to the effects of X-12a alone (Fig. 4). The datasuggested that the X-12a region was the portion of the Xanalog that was responsible for the majority of the inhibitory

Table 2. Sequences of RNA structural analogs

RNA analog Sequences

X94 GGUGGCUCCAUCUUAGCCCUAGUCACGGCUAGCUGUGAAAGGUCCGUGAGCCGCUUGACUGCAGAGAGU-GCUGAUACUGGCCUCUCUGCAGAUCAAGU

X12 GCGCCGACCAUCUUAGGCCUAGUGUGUGCUAGCGCACAAAGCUCCGUGUCGGCGUUCACACGUCUCAGU-GGUGAUACUGCCCUGAGACGUGAUGAAGU

X12a GCGCCGACCAUCUUAGGCCUAGUGUGUGCUAGCGCACAAAGCUCCGUGUCGGCGU

X12b UCACACGUCUCAGUGGUGAUACUGCCCUGAGACGUGAUGA

X12c GCGCCGACCAUCAAAGGCCAAGUGUGUGCAUGCGCACAAAGCUCCGUGUCGGCGUUCACACGUCUCAGU-GGUGUAUCAGCCCUGAGACGUGAUGAAGU

HB CAAAUUCUUUAUAAGGGUCAAUGUCCAUGCCCCAAAGCCACCCAAGGCACAGCUUGGAGGCUUGAACAGU-GGGACAUGUACAAGAGAUGAUUAGGCAGAGGUG

5B-74 CCGGCUGCGUCCCAGUUGGAUUUAUCCAGCUGGUUCGUUGCUGGUUACAGCGGGGGAGACAUAUAUCA-CAGCCUGUCUCGUGCCCGACCCCGCUG

5B-46 CGGCGGGGCGCGGGCUUCGAUUUAUCGAGGUCCGCGCCUCGCCGUUACGCGCCCGGCCGGAUAUAUCA-CAGCCUCCGGCGUGCCCGACGGGCGCG



activity. The X-12b region appeared to contribute little to Xanalog activity.

To determine whether RNA structural analogs were alsoeffective in an infection model and against a different HCVgenotype, a JFH-1 infection model was studied. Fig. 5 showsthat the levels in untreated controls increased progressively,and by 12 h, exceeded the level of input HCV RNA levels by 6-fold (extreme left bars) at 72 h. In contrast, Huh7.5 cellstransfected with analogs 5B-74, 5B-46, X-94, and X-12 andinfected with JFH-1 48 h later, inhibited HCV RNA levels to5.9%, 6.2%, 6.6%, and 1.8%, respectively, compared tountreated controls (p,0.001). Even after 72 h, no cellstreated with analogs had HCV RNA levels that exceeded morethan 30% of input levels.

To determine whether RNA structural analogs could inhibita pre-existing HCV infection, cells were infected with JFH-1HCV for 8 h and then transfected with analogs HB, 5B-74, 5B-46, X-94, and X-12. Medium was tested for JFH-1 HCV RNApost-transfection at various time points. Fig. 6 shows thatthere was a progressive increase in JFH-1 HCV RNA levelswith time in the media compared to uninfected controls. HCVRNA levels exceeded those of input virus at 12 h post-transfection and were four-fold higher by 72 h. However,72 h after transfection with analogs 5B-74, 5B-46, X-94, andX-12; HCV RNA levels were 8.8%, 10.5%, 9.0%, and 11.6%,respectively, compared to untreated controls.

Discussion

Many previous studies, including our own, have shown thatspecific domains of the genomes of some RNA viruses arecritical for viral translation and replication.30–32 The NS5B

coding region of the HCV genome adopts a stem-loopstructure that is involved in the replication of HCV.Expression of RNA structural analogs predicted to mimic thestem-loop structure identical to the NS5B region of the HCVgenome was able to inhibit replication of HCV genotype 2a.12

The current study confirms previous reports that RNAsecondary structure is important for HCV RNA replication.16,33

Conserved genomic RNA sequences have been shown tofold to adopt stem-loopmotifs that interact with other RNAmotifsand/or proteins required for translation and replication.10,31,34–37

Identification of such RNA sequences and determination ofsecondary structure formed by these sequences are challengingbecause structural motifs depend on various parameters, includ-ing host cellular microenvironments and the presence of otherhost and viral interacting molecules.29,38–40 Several types ofsoftware have been developed to predict the stable structuresformed byRNA sequences based on thermodynamic parameters.The current data generated by Mfold software confirm ourprevious findings that structures predicted using these two-dimensionalmodels dohave substantial inhibitoryactivity againstHCV replication. It is also clear that the actual molecules exist notin a two-dimensional but a three-dimensional state, and it is thelatter that causes the inhibitory activity. Such structures cannotbe predicted by the current software. Nevertheless, the datasupport the notion that two-dimensional structures are related toand can predict the activity of analogs in three-dimensions.

We intentionally studied models of two different HCVgenotypes. The structural analogs were effective in modelsof both genotype 1 and 2 viruses, suggesting that because thedesign of the molecules was based on secondary rather thanprimary structure, the effects are more likely to be multi-genotypic. This may be clinically relevant as it has already

Fig. 2. HCV RNA levels in replicon cells 48 h post-transfection withstructural analogs. Replicon cells were transfected with various concentrationsof plasmids expressing HB, 5B-74, X-94, and X-12. HCV RNA levels werequantified in cell lysates by qRT-PCR 48 h post-transfection. The values representHCV1b RNA levels in transfected cells compared to untreated controls (n54),*p,0.001.

Fig. 3. HCV RNA levels in replicon cells 48 h post-transfection withstructural analogs. Replicon cells were transfected with HB, 5B-74, X-94, X-12,X-12c, 5B-74 plus X-94, and 5B-46 plus X-12, and HCV RNA levels were quantifiedin cell lysates by qRT-PCR 48 h post-transfection. The figure represents HCV 1bRNA levels in transfected cells compared to untreated controls (n54), *p,0.001.

Table 3. Percent identity of RNA structural analogs with HCV genotypes 1b and 2a (dG: free energy)

Analog HCV1b HCV 2a

X-94(dG5246.70 kcal/mol)

100% 94%

X-12(dG5247.40 kcal/mol)

59% 12%

X-12c(dG5247.50 kcal/mol)

50% No significant identity



been demonstrated that some current direct acting antiviralagents vary in efficacy against HCV genotypes41,42 and evensubtypes.43 Design of novel anti-HCV agents based on second-ary structural considerations may offer a strategy to developnew agents that are independent of viral genotype or subtype.

For HCV genotype 1b studies, a replicon cell model with anintegrated HCV genome was used to constitutively generatesubgenomic HCV1b replicons in Huh7.5 cells.20 This systemhas been used extensively to determine the effects of variousdrugs and proteins on viral replication and infection.44,45

However, because HCV RNA replication in this model isconstitutive, it is not a simulation of HCV infection. For thisreason, we examined here the effects of structural analogs onJFH1, to provide a more realistic HCV infection modelsystem.24,46,47 The results from the JFH-1 infection model

systems offered insight into the differences in efficacy amongstructural analogs depending on whether they were intro-duced before or after viral infection. The JFH-1 HCV infectionsystem has been used to determine the anti-HCV activity ofseveral proteins and inhibitors (example: Raloxifene, NSCcompounds) before or after infection of hepatic cells.48,49

Introduction of RNA structural analogs after viral infectionresembles treatment strategies for hepatocytes alreadyinfected with HCV, while exposure of cells before viralinfection represents a potential prophylactic approach.

Expression of the stem-loop structure of X-region in the39-UTR of HCV genome (using RNA analogs X-94, X-12, andX-12c) was found to be effective against HCV replication,regardless of the sequence of RNA. Furthermore, we haveidentified a small portion, one of the stem-loop structures ofthe X-region, X-12a, as the smallest identified portion of the X-region analog that retains inhibitory activity. The other stem-loop structure, X-12b of approximately the same length; whichalso possesses natural HCV sequences, was virtually ineffec-tive. These data confirmed that a specific structure, the stem-loop conformation, was involved, and that the observedinhibitory effects were not due a nonspecific interaction ofHCV sequences. The studies on nucleotide base substitution inthe X-region showing reduction in the identity to the naturalHCV sequence to less than 50%, while retaining secondarystructure, indicated that the observed inhibitory effects did notlikely involve anti-sense mechanisms. These results areconsistent with previous studies.12,50

Conclusions

The data indicate that conformation of secondary structuresin 39-UTR of HCV RNA genome is required for HCV replication.Stable expression of RNA analogs predicted to have identical

Fig. 4. HCV RNA levels in replicon cells 48 h post-transfection withstructural analogs. Replicon cells were transfected with HB, 5B-74, X-12a, X-12b, and X-12a plus X-12b, and HCV RNA levels were quantified in cell lysates byqRT-PCR 48 h post-transfection. The figure represents HCV 1b RNA levels intransfected cells compared to untreated controls (n54), *p,0.001.

Fig. 5. JFH-1 HCV RNA levels inmedia fromHuh7.5 cells at various time points post-infection. Huh7.5 cells were transfected with analogs HB, 5B-74, 5B-46, X-94,and X-12 and then infected with JFH-1 HCV 48 h post-transfection. HCV RNA levels in media were quantified by qRT-PCR at various time points post-infection. The valuesrepresent JFH-1 HCV RNA levels in media from cells transfected with analogs 48 h before infection compared to untreated controls at various time points (n53), *p,0.001.



stem-loop structures, but sequences vastly different fromHCV genomic RNA, might inhibit HCV infection of hepatocytesin liver, and may represent a novel approach to design anti-HCV agents.

Acknowledgments

We thank Dr. Charles Rice (Rockefeller University, NY, USA)for providing Huh7.5 cells, Dr. Takaji Wakita (NationalInstitute of Infectious Diseases, Tokyo, Japan) for generousdonation of HCV JFH-1 cDNA, and Amy Pallotti and AnniliseLarosa for their secretarial assistance.

Conflict of interest

George Y. Wu serves on medical advisory boards for Gilead,Janssen, and Bristol-Myers Squibb.

Author contributions

Conceiving the study and contributing interpretation of data(GYW), designing and performing the research, as well aswriting the manuscript (NG), contributing technical adviceand review of manuscript (CHW).

References

[1] Alter MJ. Epidemiology of hepatitis C virus infection. World J Gastroenterol2007;13:2436–2441. doi: 10.3748/wjg.v13.i17.2436.

[2] Lauer GM, Walker BD. Hepatitis C virus infection. N Engl J Med 2001;345:41–52. doi: 10.1056/NEJM200107053450107.

[3] Chakravarti A, Dogra G, Verma V, Srivastava AP. Distribution pattern of HCVgenotypes & its association with viral load. Indian J Med Res 2011;133:326–331.

[4] Hnatyszyn HJ. Chronic hepatitis C and genotyping: the clinical significance ofdetermining HCV genotypes. Antivir Ther 2005;10:1–11.

[5] Pang PS, Planet PJ, Glenn JS. The evolution of the major hepatitis Cgenotypes correlates with clinical response to interferon therapy. PLoS One2009;4:e6579. doi: 10.1371/journal.pone.0006579.

[6] You S, Stump DD, Branch AD, Rice CM. A cis-acting replication element in thesequence encoding the NS5B RNA-dependent RNA polymerase is required forhepatitis C virus RNA replication. J Virol 2004;78:1352–1366. doi: 10.1128/JVI.78.3.1352-1366.2004.

[7] Piñeiro D, Martinez-Salas E. RNA structural elements of hepatitis C viruscontrolling viral RNA translation and the implications for viral pathogenesis.Viruses 2012;4:2233–2250. doi: 10.3390/v4102233.

[8] Ray PS, Das S. Inhibition of hepatitis C virus IRES-mediated translation bysmall RNAs analogous to stem-loop structures of the 59-untranslated region.Nucleic Acids Res 2004;32:1678–1687. doi: 10.1093/nar/gkh328.

[9] Kolykhalov AA, Mihalik K, Feinstone SM, Rice CM. Hepatitis C virus-encodedenzymatic activities and conserved RNA elements in the 39 nontranslatedregion are essential for virus replication in vivo. J Virol 2000;74:2046–2051.doi: 10.1128/JVI.74.4.2046-2051.2000.

[10] Luo G, Xin S, Cai Z. Role of the 59-proximal stem-loop structure of the 59untranslated region in replication and translation of hepatitis C virus RNA.J Virol 2003;77:3312–3318. doi: 10.1128/JVI.77.5.3312-3318.2003.

[11] Dutkiewicz M, Swiatkowska A, Figlerowicz M, Ciesiołka J. Structural domainsof the 39-terminal sequence of the hepatitis C virus replicative strand.Biochemistry 2008;47:12197–12207. doi: 10.1021/bi800348g.

[12] Smolic R, Smolic M, Andorfer JH, Wu CH, Smith RM, Wu GY. Inhibition ofhepatitis C virus replication by single-stranded RNA structural mimics. WorldJ Gastroenterol 2010;16:2100–2108. doi: 10.3748/wjg.v16.i17.2100.

[13] Smith RM, Wu GY. Structure-based design of hepatitis C virus inhibitors.J Viral Hepat 2003;10:405–412. doi: 10.1046/j.1365-2893.2003.00443.x.

[14] Smith RM, Walton CM, Wu CH, Wu GY. Secondary structure and hybridizationaccessibility of hepatitis C virus 39-terminal sequences. J Virol 2002;76:9563–9574. doi: 10.1128/JVI.76.19.9563-9574.2002.

[15] Zhang J, Yamada O, Sakamoto T, Yoshida H, Araki H, Murata T, et al.Inhibition of hepatitis C virus replication by pol III-directed overexpression ofRNA decoys corresponding to stem-loop structures in the NS5B codingregion. Virology 2005;342:276–285. doi: 10.1016/j.virol.2005.08.003.

Fig. 6. JFH-1 HCV RNA levels in media fromHuh7.5 cells at various time points post-transfection. Huh7.5 cells infected with JFH-1 HCV, and then transfected withanalogs HB, 5B-74, 5B-46, X-94 and X-12 8 h post-infection. HCV RNA levels in media from infected cells were quantified by qRT-PCR at various time points post-transfection. The figure represents JFH-1 HCV RNA levels in media from infected cells transfected with analogs 8 h post-infection compared to untreated controls at varioustime points (n53), *p,0.001.



[16] Kolykhalov AA, Feinstone SM, Rice CM. Identification of a highly conservedsequence element at the 39 terminus of hepatitis C virus genome RNA. J Virol1996;70:3363–3371.

[17] Blight KJ, Rice CM. Secondary structure determination of the conserved 98-base sequence at the 39 terminus of hepatitis C virus genome RNA. J Virol1997;71:7345–7352.

[18] Ito T, Lai MM. Determination of the secondary structure of and cellular proteinbinding to the 39-untranslated region of the hepatitis C virus RNA genome.J Virol 1997;71:8698–8706.

[19] Huang L, Hwang J, Sharma SD, Hargittai MR, Chen Y, Arnold JJ, et al.Hepatitis C virus nonstructural protein 5A (NS5A) is an RNA-binding protein.J Biol Chem 2005;280:36417–36428. doi: 10.1074/jbc.M508175200.

[20] Lohmann V, Hoffmann S, Herian U, Penin F, Bartenschlager R. Viral andcellular determinants of hepatitis C virus RNA replication in cell culture.J Virol 2003;77:3007–3019. doi: 10.1128/JVI.77.5.3007-3019.2003.

[21] Lohmann V, Körner F, Koch J, Herian U, Theilmann L, Bartenschlager R.Replication of subgenomic hepatitis C virus RNAs in a hepatoma cell line.Science 1999;285:110–113. doi: 10.1126/science.285.5424.110.

[22] Kato T, Date T, Miyamoto M, Furusaka A, Tokushige K, Mizokami M, et al.Efficient replication of the genotype 2a hepatitis C virus subgenomic replicon.Gastroenterology 2003;125:1808–1817. doi: 10.1053/j.gastro.2003.09.023.

[23] Wakita T, Pietschmann T, Kato T, Date T, Miyamoto M, Zhao Z, et al.Production of infectious hepatitis C virus in tissue culture from a cloned viralgenome. Nat Med 2005;11:791–796. doi: 10.1038/nm1268.

[24] Kato T, Date T, Murayama A, Morikawa K, Akazawa D, Wakita T. Cell cultureand infection system for hepatitis C virus. Nat Protoc 2006;1:2334–2339.doi: 10.1038/nprot.2006.395.

[25] Blight KJ, McKeating JA, Rice CM. Highly permissive cell lines for subgenomicand genomic hepatitis C virus RNA replication. J Virol 2002;76:13001–13014. doi: 10.1128/JVI.76.24.13001-13014.2002.

[26] Suzuki T, Aizaki H, Murakami K, Shoji I, Wakita T. Molecular biology ofhepatitis C virus. J Gastroenterol 2007;42:411–423. doi: 10.1007/s00535-007-2030-3.

[27] Zuker M. Mfold web server for nucleic acid folding and hybridizationprediction. Nucleic Acids Res 2003;31:3406–3415. doi: 10.1093/nar/gkg595.

[28] Doshi KJ, Cannone JJ, Cobaugh CW, Gutell RR. Evaluation of the suitability offree-energy minimization using nearest-neighbor energy parameters forRNA secondary structure prediction. BMC Bioinformatics 2004;5:105. doi:10.1186/1471-2105-5-105.

[29] Mathews DH, Sabina J, Zuker M, Turner DH. Expanded sequence dependenceof thermodynamic parameters improves prediction of RNA secondarystructure. J Mol Biol 1999;288:911–940. doi: 10.1006/jmbi.1999.2700.

[30] Hofacker IL, Stadler PF, Stocsits RR. Conserved RNA secondary structures inviral genomes: a survey. Bioinformatics 2004;20:1495–1499. doi: 10.1093/bioinformatics/bth108.

[31] Kieft JS. Viral IRES RNA structures and ribosome interactions. TrendsBiochem Sci 2008;33:274–283. doi: 10.1016/j.tibs.2008.04.007.

[32] Gamarnik AV, Andino R. Switch from translation to RNA replication in apositive-stranded RNA virus. Genes Dev. 1998;12:2293–2304. doi:10.1101/gad.12.15.2293.

[33] Han JH, Shyamala V, Richman KH, Brauer MJ, Irvine B, Urdea MS, et al.Characterization of the Terminal Regions of Hepatitis C Viral RNA:Identification of Conserved Sequences in the 59 Untranslated Region andPoly(a) Tails at the 39 End. Proc Natl Acad Sci USA 1991;88:1711–1715. doi:10.1073/pnas.88.5.1711.

[34] Blackham SL, McGarvey MJ. A host cell RNA-binding protein, Staufen1, has arole in hepatitis C virus replication before virus assembly. J Gen Virol 2013;94:2429–2436. doi: 10.1099/vir.0.051383-0.

[35] Wang L, Jeng KS, Lai MM. Poly(C)-Binding Protein 2 Interacts with SequencesRequired for Viral Replication in the Hepatitis C Virus (HCV) 59 UntranslatedRegion and Directs HCV RNA Replication through Circularizing the ViralGenome. J Virol 2011;85:7954–7964. doi: 10.1128/JVI.00339-11.

[36] Ito T, Lai MM. An internal polypyrimidine-tract-binding protein-binding site inthe hepatitis C virus RNA attenuates translation, which is relieved by the 39-untranslated sequence. Virology 1999;254:288–296. doi: 10.1006/viro.1998.9541.

[37] Anjum S, Ali S, Ahmad T, Afzal MS, Waheed Y, Shafi T, et al. Sequence andstructural analysis of 39 untranslated region of hepatitis C virus, genotype 3a,from pakistani isolates. Hepat Mon 2013;13:e8390. doi: 10.5812/hepatmon.8390.

[38] Fontana W, Konings DA, Stadler PF, Schuster P. Statistics of Rna SecondaryStructures. Biopolymers 1993;33:1389–1404. doi: 10.1002/bip.360330909.

[39] Fontana W, Griesmacher T, Schnabl W, Stadler PF, Schuster P. Statistics ofLandscapes Based on Free-Energies, Replication and Degradation RateConstants of Rna Secondary Structures. Monatsh Chem 1991;122:795–819. doi: 10.1007/BF00815919.

[40] Butcher SE, Pyle AM. The Molecular Interactions That Stabilize RNA TertiaryStructure: RNA Motifs, Patterns, and Networks. Acc Chem Res 2011;44:1302–1311. doi: 10.1021/ar200098t.

[41] Kamal SM. Pharmacogenetics of hepatitis C: transition from interferon-basedtherapies to direct-acting antiviral agents. Hepat Med 2014;6:61–77. doi:10.2147/HMER.S41127.

[42] Bartels DJ, Sullivan JC, Zhang EZ, Tigges AM, Dorrian JL, De Meyer S, et al.Hepatitis C virus variants with decreased sensitivity to direct-acting antivirals(DAAs) were rarely observed in DAA-naive patients prior to treatment. J Virol2013;87:1544–1553. doi: 10.1128/JVI.02294-12.

[43] Wyles DL, Gutierrez JA. Importance of HCV genotype 1 subtypes for drugresistance and response to therapy. J Viral Hepat 2014;21:229–240. doi:10.1111/jvh.12230.

[44] Ludmerer SW, Graham DJ, Boots E, Murray EM, Simcoe A, Markel EJ, et al.Replication fitness and NS5B drug sensitivity of diverse hepatitis C virusisolates characterized by using a transient replication assay. AntimicrobAgents Chemother 2005;49:2059–2069. doi: 10.1128/AAC.49.5.2059-2069.2005.

[45] Gu B, Gates AT, Isken O, Behrens SE, Sarisky RT. Replication studies usinggenotype 1a subgenomic hepatitis C virus replicons. J Virol 2003;77:5352–5359. doi: 10.1128/JVI.77.9.5352-5359.2003.

[46] Zhong J, Gastaminza P, Cheng G, Kapadia S, Kato T, Burton DR, et al. Robusthepatitis C virus infection in vitro. Proc Natl Acad Sci USA 2005;102:9294–9299. doi: 10.1073/pnas.0503596102.

[47] Date T, Miyamoto M, Kato T, Morikawa K, Murayama A, Akazawa D, et al. Aninfectious and selectable full-length replicon system with hepatitis C virusJFH-1 strain. Hepatol Res 2007;37:433–443. doi: 10.1111/j.1872-034X.2007.00056.x.

[48] Takeda M, Ikeda M, Mori K, Yano M, Ariumi Y, Dansako H, et al. Raloxifeneinhibits hepatitis C virus infection and replication. FEBS Open Bio 2012;2:279–283. doi: 10.1016/j.fob.2012.08.003.

[49] Yu X, Sainz B Jr, Petukhov PA, Uprichard SL. Identification of hepatitis C virusinhibitors targeting different aspects of infection using a cell-based assay.Antimicrob Agents Chemother 2012;56:6109–6120. doi: 10.1128/AAC.01413-12.

[50] Tuplin A, Evans DJ, Simmonds P. Detailed mapping of RNA secondarystructures in core and NS5B-encoding region sequences of hepatitis C virusby RNase cleavage and novel bioinformatic prediction methods. J Gen Virol2004;85:3037–3047. doi: 10.1099/vir.0.80141-0.



Diabetes Mellitus Predicts Occurrence of Cirrhosis andHepatocellular Cancer in Alcoholic Liver and Non-alcoholic

Fatty Liver Diseases

Evan J. Raff1, Donny Kakati1, Joseph R. Bloomer2, Mohamed Shoreibah2, Khalid Rasheed3

and Ashwani K. Singal*2

1Department of Internal Medicine, UAB, Birmingham, AL, USA; 2Division of Gastroenterology and Hepatology, UAB, Birmingham,AL, USA; 3Department of Internal Medicine, UAB Montgomery Program, Huntsville, AL, USA

Abstract

Background and Aims: Alcohol abuse and nonalcoholic fattyliver disease (NAFLD) are common causes of liver disease.Diabetes mellitus (DM) is a common comorbidity amongNAFLD patients. We performed this study with the specificaim to examine the impact of DM on progression of alcoholicliver disease (ALD) liver and NAFLD. Methods: Medical chartsof 480 patients with ALD or NAFLD (2004–2011)managed at atertiary center were retrospectively reviewed. NAFLD wasdiagnosed based on exclusion of other causes of liver diseaseand alcohol use of ,10 g/d. ALD was diagnosed based onalcohol use of .40 g/d in women or .60 g/d in men for .5years. Results: Of 480 patients (307 NAFLD), 200 diabeticsdiffered from nondiabetics for: age (52±11 vs. 49±11 years;p50.004); male gender (48% vs. 57%; p50.03); metabolicsyndrome (49% vs. 30%; p50.0002); NAFLD (80% vs. 56%;p,0.0001); cirrhosis (70% vs. 59%; p50.005); and hepato-cellular carcinoma (HCC; 8% vs. 3%; p50.009). Over a 3 yearmedian follow-up period, diabetics relative to nondiabetics hada higher probability to develop cirrhosis (60% vs. 41%;p50.022) and HCC (27% vs. 10%; p50.045). There was atrend for increased development of hepatic encephalopathy indiabetics compared to nondiabetics (55% vs. 39%; p50.053),and therewas no difference between the two groups in survivalor other liver disease complications. Conclusions: DMincreased risk for cirrhosis and HCC among patients with ALDand NAFLD. Prospective studies with longer follow-up periodsare needed to examine the impact of DM on survival and therole of aggressive HCC screening in diabetic cirrhotics.

E 2015 The Second Affiliated Hospital of Chongqing MedicalUniversity. Published by XIA & HE Publishing Ltd. All rightsreserved.

Introduction

Alcohol abuse and nonalcoholic fatty liver disease (NAFLD)are the most common causes of liver cirrhosis and indicationsfor liver transplantation in the US, following chronic hepatitisC virus infection.1 Although alcoholic liver disease (ALD) andNAFLD exhibit different phenotypes and risk factors, theyshare similar pathogenic mechanisms and histological find-ings of steatohepatitis.2 The histological spectrum may rangefrom simple steatosis to more advanced disease, includingsteatohepatitis, fibrosis, cirrhosis, or hepatocellular carci-noma (HCC).

There is an epidemic of obesity in the US, and thefrequency of liver disease and liver transplantation due tosteatohepatitis in NAFLD (NASH) has been increasing overthe last two decades. Prevalence of NASH is currentlyreported to be as high as 17% among patients withNAFLD.3–5 It is estimated that 8% of the US population hasdiabetes mellitus (DM), and it is the seventh leading causeof death in the US.6 Furthermore, the prevalence of DM isreported to be higher among patients with liver diseasesecondary to NAFLD relative to other etiologies of liverdisease.7,8

Many studies have reported DM to be a risk factor inpatients with ALD and NAFLD for the development of fibrosis,accelerated fibrosis progression, and liver disease relatedmortality.9–16 Multiple cohort and case-control studies havealso shown an association between diabetes and HCC.17–23

However, data remain relatively scant on the link betweendiabetes and progression to cirrhosis and development ofassociated complications. Here, we explored this associationin a cohort of patients with ALD and NAFLD.

Material and methods

Study population

Patients evaluated at a single tertiary referral center betweenJanuary 2004 and December 2011 diagnosed with ALD (ICD-09 codes 571.0 and 571.3), alcoholic cirrhosis of the liver(571.2), cirrhosis of the liver without alcohol (571.5), or otherchronic NAFLD including steatosis (571.8) formed the studypopulation. Patients were excluded from the analysis if detailsregarding alcohol use were unavailable or if alcohol consump-tion was .10 g/d in patients diagnosed with NALFD (Fig. 1).

Keywords: Diabetes mellitus; Steatohepatitis; Nonalcoholic steatohepatitis;Alcoholic cirrhosis.Abbreviations: ALD, alcoholic liver disease; ALT, alanine aminotransferase; AST,aspartate aminotransferase; BMI, body mass index; CCI, charlson comorbidityindex; CI, confidence interval; CT, computed tomography; DM, diabetes mellitus;HCC, hepatocellular carcinoma; MELD, model for end-stage liver disease; MRI,magnetic resonance imaging; NAFLD, non-alcoholic fatty liver disease; NASH,nonalcoholic steatohepatitis; OR, odds ratio.Received: 05 January 2015; Revised: 19 February 2015; Accepted: 22 February2015qDOI: 10.14218/JCTH.2015.00001.*Correspondence to: Ashwani K Singal, University of Alabama at Birmingham,1808 7th Ave South, BDB 351, Birmingham, AL 35294, USA. Tel: +1-205-975-3515, Fax: +1-205-975-9777, E-mail: [email protected]

Original Article

Journal of Clinical and Translational Hepatology 2015 vol. 3 | 9–16

Definitions

ALD

Defined based on the following criteria: 1) presence of liverdisease as determined by clinical evaluation along withlaboratory work-up, imaging assessment, or liver biopsyfindings; 2) exclusion of other causes of liver disease; and3) a history of excessive alcohol use (.40 g/d in women or.60 g/d in men for .5 years).

NAFLD

Defined based on the following criteria: 1) demonstration ofhepatic steatosis by imaging or biopsy; 2) exclusion ofsignificant alcohol consumption (.10 g/d); and 3) exclusionof other causes of hepatic steatosis. There was considerablevariation across different studies for the amount of alcoholconsumption used to define NAFLD, and some studies did nottake into account gender differences in alcohol use.3

Therefore, we used the safest and lowest amount of alcoholuse (,10 g/d) to define NAFLD in our study cohort.

Steatohepatitis

This is a histological diagnosis based on thepresence of steatosisand inflammation (lobular inflammation and hepatocyte

ballooning). NAFLD activity score (NAS) was determined oneach biopsy as the underweighted sum of the scores forsteatosis: grades 0–3 as proportion of hepatocytes containingfat vacuoles with ,5%, 5–33%, 33–66%, and .66% hepato-cytes, respectively; lobular inflammation: grades 0–3 asinflammation foci per 2006 field with absent, ,2 foci, 2–4 foci,and .4 foci, respectively; and cytological ballooning: grades0–2 qualitatively as number of ballooned cells with none, few,and many cells, respectively.24 Due to the lack of a scoringsystem to grade steatohepatitis in ALD patients and in order tokeep homogeneity for diagnosis of steatohepatitis, we used thesame definition of NAS, four or more to define steatohepatitis inthe ALD group. Diagnosis of steatohepatitis was made onbiopsies in ALD and NAFLD patients with an NAS of 3 or more.

Alcohol use

Grams per day derived from the average number of drinksconsumed per day. One drink was equal to 12 ounces of beer,5 ounces of wine, or 1.25 ounces of hard liquor, eachrepresenting 15 g of pure alcohol.

Diabetes

Based on the following criteria: 1) formal diagnosis listed inthe medical chart; and/or 2) receiving specific antidiabetic

Fig. 1. Study population

Evan J.R. et al: Diabetes and steatohepatitis


medications; and/or 3) documented hemoglobin A1c of 6.5%or above.25

Metabolic syndrome

Defined as the presence of three or more of the following:hyperglycemia (taking medications for previously diagnosedtype 2 diabetes or fasting blood sugar level §100 mg/dL),hypertension (taking medications for previously diagnosedhypertension or blood pressure §130/85 mmHg), obesity(body mass index (BMI) §30), reduced high density lipopro-tein level (,50 mg/dL in females and ,40 mg/dL in males),and/or elevated triglyceride level (§150 mg/dL).26–28

Cirrhosis

Diagnosed by clinical/imaging criteria and/or biopsy whenavailable.

HCC

Diagnosed based on American Association for Study of LiverDiseases guidelines and criteria incorporating computedtomography (CT) and magnetic resonance imaging (MRI)scans and/or biopsy when available.29

Data collection

Our center utilized a searchable electronic medical recordthat collects information on patient demographic, clinic notes,notes from hospitalizations (history and physicals, progressnotes, and discharge summaries), vital signs, reports fromradiologic imaging studies, laboratory data, and pathologyreports. The referral center had utilized this system to storeinformation since 2000.

Using the medical record number as a unique identifier,patient charts were reviewed for data collection on patientdemographics (age, gender and race); BMI; dates of onset ofsymptoms and of diagnosis; components ofmetabolic syndrome(diabetes, hypertension, dyslipidemia, and obesity); alcoholintake in g/d; and presentation with cirrhosis and/or associatedcomplications (ascites, variceal bleeding, hepatic encephalopa-thy, and HCC). Results of laboratory, imaging, upper gastro-intestinal endoscopy, and liver biopsy details were also recorded.Charlson comorbidity index (CCI) was obtained for each patientusing the information on defined comorbidities.30,31 For patientswith available liver biopsy information, data were collected forsteatosis, lobular inflammation, and hepatocyte ballooning. Datawere also collected for fibrosis stage: 0–4 as no fibrosis, portalfibrosis, periportal fibrosis, bridging fibrosis, and cirrhosis,respectively.32,33

Data on prospective follow-up of patients from the time oftheir first contact at our center was collected retrospectively.Development of cirrhosis was evaluated among patientswithout diagnosis of cirrhosis at or within the first 6 monthsof presentation. Development of liver disease complications(ascites, hepatic encephalopathy, variceal hemorrhage, andHCC) was assessed among cirrhotics who did not have thesecomplications at or within 1 month of their presentation.Patient survival status was recorded from the chart reviewand confirmed with the National Death Registry. Time todevelopment of cirrhosis, liver disease complications, anddeath was calculated from dates of event occurrence anddisease onset. Patients lost to follow-up and those without the

event at the time of their last follow-up were censored.Medical charts of these patients were reviewed to identifypatients meeting criteria for diagnosis of ALD and NAFLD, aspreviously detailed in the section on definitions.

Statistical analyses

Patients with and without DM were compared for demo-graphics; components of metabolic syndrome; CCI; presenta-tion with cirrhosis and/or associated complications; laboratorydata; and findings on endoscopy, imaging, and liver biopsy.Chi-square and student’s t tests were utilized for categoricaland continuous variables, respectively. Logistic regressionmodels were built to examine predictors of cirrhosis and HCCdevelopment. Variables different between the two groups andother clinically relevant ones were entered into the model.Results are reported as odds ratio (OR) with 95% confidenceinterval (CI). Kaplan Meier curves were generated to comparediabetics and nondiabetics for development of cirrhosis,complications of liver disease, and patient survival. Log ranktest was used for statistical significance. All statistical analyseswere performed using the Statistical Analyses Software (SASInstitute, USA), and p,0.05 was considered statisticallysignificant. The study was approved by the InstitutionalReview Board at our center.

Results

Study population

Of 607 patients in the database (401 with diagnosed NAFLD),108 were excluded from analysis (67 NAFLD) because detailswere missing regarding alcohol use. A total of 19 NAFLDpatients were excluded due to reported alcohol use of .10 g/dand did not meet our criteria for NAFLD diagnosis. Of theremaining 480 patients (315 NAFLD), 200 (160 NAFLD) metthe criteria for diagnosis of diabetes (Fig. 1).

Baseline characteristics

Diabetics relative to nondiabetics were older in age, pre-dominantly female in gender, had metabolic syndrome, andhad NAFLD as the underlying etiology (Table 1). About 90%of patients were Caucasian, consistent with the patientpopulation at our center. Diabetics had a higher BMI (35±8vs. 31±10; p,0.0001) and were more likely to havehypertension (69% vs. 48%; p,0.0001) than nondiabetics.Triglyceride levels were similar and lower density lipoproteinlevels were lower among diabetics than nondiabetics(153±136 vs. 139±111 mg/dL; p50.3 and 98±36 vs.111±53 mg/dL; p50.02, respectively). Diabetics had ahigher CCI, after excluding the impact of liver disease anddiabetes, than nondiabetics (Table 1). In total, 305 (64%)patients had cirrhosis on initial evaluation, and this percen-tage was higher in diabetics (Table 1). A total of 128, 40, and33 patients had ascites, encephalopathy, and variceal bleed-ing, respectively, at presentation, and there were no differ-ences between diabetics and nondiabetics. Twenty-fourpatients had HCC at presentation, with a higher proportionin diabetic patients (Table 1). There was over a 3-fold risk forcirrhosis and/or HCC in diabetics at the time of clinicalpresentation (Table 2). Other significant predictors of cirrho-sis and HCC were age, male gender, and the ratio of aspartateaminotransferase (AST) to alanine aminotransferase (ALT)



levels (Table 2). Other variables included in the model wererace/ethnicity, CCI, and etiology of liver disease (NAFLD orALD).

Diabetics compared to nondiabetics had lower alanine ALTand aspartate AST levels (Table 1). However, the AST/ALT

ratio was similar (1.4±1.1 vs. 1.5±0.9; p50.23) betweenthe two groups. About 15% of patients were positive forautoimmune markers, and there was no difference betweenthose with and without diabetes (16% vs. 15%; p50.45).Serum albumin levels were similar between the two groups as

Table 1. Demographic and clinical characteristics of patients with alcoholic and non-alcoholic fatty liver diseases comparing patients with and withoutdiabetes

VariableNo diabetes mellitus

(n5280) Diabetes mellitus (n5200) p-value

Demographics

Age (years) 49±11 52±11 0.004

Male (%) 57 48 0.03

Caucasians (%) 89 87 0.97

Comorbidities

MS (%) 30 49 0.0002

CCI 1.6±2 2.7±2.2 ,0.0001

Liver disease status at presentation

NAFLD (%) 56 80 ,0.0001

Cirrhosis (%) 59 70 0.005

HCC (%) 3 8 0.009

Ascites (%) 30 22 0.052

PSE (%) 7 7 0.37

Variceal bleed (%) 9 7 0.93

Laboratory values

ALT (IU/L) 55±56 46±43 0.03

AST (IU/L) 67±68 53±48 0.004

MELD score 11±8 9±8 0.03

Endoscopic findings

EV Absent 35 35 0.44

Small 32 27

Moderate-to-large 33 38

PHG Absent 56 60 0.07

Mild-to-moderate 40 34

Severe 4 6

ALT, alanine aminotransferase; AST, aspartate aminotransferase; CCI, charlson comorbidity index; EV, esophageal varices; HCC, hepatocellular carcinoma; MELD, Model forEnd-Stage Liver Disease; MS, metabolic syndrome; NAFLD, nonalcoholic fatty liver disease; PHG, portal hypertensive gastropathy; PSE, portal systemic encephalopathy.

Table 2. Predictors of cirrhosis and HCC in alcoholic and non-alcoholic fatty liver diseases

Predictors of cirrhosis p Predictors of HCC p

Variable OR 95% CI OR 95% CI

Diabetes 3.9 2.3–6.4 ,0.0001 3.0 1.3–6.9 ,0.0001

Age increase by 5 years 1.30 1.17–1.44 ,0.0001 1.17 1.02–1.53 0.047

Male gender 2.1 1.3–3.4 0.002 2.8 1.3–9.2 0.001

ALD vs. NAFLD 14.7 7.6–28.3 ,0.0001 11.2 5.2–17.2 ,0.0001

Cirrhosis 8.9 1.4–75 ,0.0001

ALD, alcoholic liver disease; ALT, alanine aminotransferase; AST, aspartate aminotransferase; CI, confidence interval; HCC, hepatocellular carcinoma; NAFLD, nonalcoholicfatty liver disease; OR, odds ratio.



well (3.4±7 vs. 3.5±2; p50.61). However, diabetics had alower model for end-stage liver disease (MELD) scorecompared to nondiabetics (Table 1). On upper gastrointest-inal endoscopy, there were no differences in the presence andseverity of portal hypertensive gastropathy or esophagealvarices between diabetics and non-diabetics (Table 1).

Histological findings

Liver biopsy details on histological findings were available in162 patients (80 with DM; Fig. 2). When comparing diabeticsand nondiabetics, there were no differences in steatosis in

.33% of hepatocytes (49% vs. 49%; p50.99), lobularinflammation (72% vs. 70%; p50.78), and hepatocyteballooning (52% vs 45%; p50.34). NAFLD activity scorewas also similar between the two groups (3.6±1.7 vs.3.4±1.5; p50.61). Steatohepatitis (NAFLD activity score of4 or more) was present in 44 (27%) cases, and 20 of thesewere diabetic and only two had ALD. About 55% patients hadbridging fibrosis or cirrhosis, and there were no differencesbetween those with or without DM (60% vs. 51%; p50.26).ALD patients were more likely than NAFLD patients to havecirrhosis at the time of first contact (46% vs. 12%,p,0.0001). Among NAFLD patients with diabetes, there was

Fig. 2. Histologic findings in liver biopsies among patients with alcoholic liver disease (ALD) or nonalcoholic fatty liver disease (NAFLD) and with orwithout diabetes.

Fig. 3. Cumulative probability of developing cirrhosis in diabetics and nondiabetics in patients with alcoholic liver or non-alcoholic fatty liver diseases. Theprobability of developing cirrhosis is higher among diabetics.



an increased tendency to have cirrhosis, as determined bybiopsy, than nondiabetics (5 of 56 vs. 1 of 49, p50.21). Thefrequency of cirrhosis at first contact based on clinical and/orhistological diagnosis of cirrhosis was also higher in diabeticsthan nondiabetics (51 of 160 vs. 24 of 155, p50.009).

Impact of diabetes on progression of liver disease

Development of cirrhosis and HCC

Over a median follow-up period of 6 months among 156patients (55 with DM) without cirrhosis, a higher proportion ofdiabetics relative to nondiabetics developed cirrhosis (43%vs. 27%, respectively), with a higher cumulative probabilityof developing cirrhosis (60% vs. 41%, respectively; log rankp50.022, Fig. 3). Similarly, over a median follow-up of 3years among 359 patients with cirrhosis at or during follow-up, a higher proportion of diabetics compared to nondiabeticsdeveloped HCC (22% vs. 5%, respectively) with a highercumulative probability of developing HCC (27% vs. 10%; logrank p50.045, Fig. 4). Etiology specific analyses were alsoperformed. Among ALD patients, the cumulative develop-ment of cirrhosis and HCC for diabetics and nondiabetics was97% vs. 87%, p50.023 and 13% vs. 6%, p50.08. Similarfigures were found for NAFLD patients, 64% vs. 36%,p,0.0001 and 4.5% vs. 1.5%, p50.38 respectively.

Development of liver disease complications

Over a median follow-up period of 3 years among patientswithout liver disease complications at or within 30 days ofdisease onset, diabetics relative to nondiabetics tended to

develop more frequently hepatic encephalopathy (30% vs.9%, respectively) with a higher cumulative probability (39%vs. 55%, respectively; log rank p50.053). However, prob-abilities of developing ascites and variceal bleeding weresimilar between diabetics and nondiabetics (52% vs. 42%;p50.3 and 23% vs. 16%, p50.47, respectively). Etiologyspecific analyses for cumulative development of hepaticencephalopathy was higher among diabetics with NAFLDthan nondiabetics (35% vs. 15%, p50.0006). There was atrend suggesting diabetics with ALD were at greater risk thannondiabetics for developing hepatic encephalopathy (35%vs. 28%, p50.43).

Overall survival

In total, 31 of 480 (6%) patients in the study population died,and 17 of these were nondiabetics. There was no difference inprobability of survival between patients with and withoutDM over a median follow-up period of 3.2 and 4 years,respectively (85% vs. 83%, respectively; p50.81).

Discussion

Our analysis of patients with steatohepatitis-related liverdisease revealed: a) different baseline characteristics andsimilar histological findings of patients with or without DM; b)diabetes is a risk factor for the development of cirrhosis andHCC; and c) diabetics relative to nondiabetics are more likelyto develop cirrhosis and HCC.

Baseline differences between diabetics and nondiabeticswere likely due to a higher proportion of NAFLD patients in thediabetic group. Many studies have reported NAFLD patients to

Fig. 4. Cumulative probability of developing hepatocellular carcinoma (HCC) in diabetics and nondiabetics in patients with alcoholic liver or non-alcoholicfatty liver diseases. Results show that the probability of developing HCC is higher among diabetics.



be older females with a higher likelihood of exhibitingcomponents of metabolic syndrome.4,5,34 Histological find-ings on liver biopsy were similar between diabetics andnondiabetics. Furthermore, the proportion of patients withadvanced fibrosis or cirrhosis on liver biopsy was similarlystratified for DM. These results were likely due to selectionbias due to the performance of liver biopsy, as the proportionof patients with cirrhosis at first contact and follow-upremained higher among diabetics relative to nondia-betics.35,36 In one study of 46 NAFLD patients (17 with type2 diabetes), markers of insulin resistance correlated inde-pendently with the degree of hepatic inflammation andfibrosis.37 In another study on NASH patients; older age,obesity and DM predicted severe liver fibrosis on biopsy. Ahigher proportion of NAFLD patients in the diabetes groupthan the nondiabetes group and the selection bias forperforming liver biopsy may explain the differences betweenthese two patient groups found in our retrospective analysis.

Many studies have shown that type DM is a predictor offibrosis, accelerated fibrosis progression, and increased liver-related mortality.9–14 Similarly, studies have observed DM tobe a risk factor for the development of HCC in patients withcirrhosis.20,38–40 Our study findings are consistent with thesereports and demonstrated that DM is a predictor for cirrhosisand/or HCC irrespective of the etiology of steatohepatitis-related liver disease. In one study, the synergistic effects ofalcohol abuse and DM on the development of HCC was shown,suggesting that heavy alcohol consumption may exacerbatethe effect of DM on the development of cirrhosis and HCC.39

The mechanisms underlying DM mediated acceleration ofliver disease progression in patients with steatohepatitis remainunclear. It has been speculated that release of free fatty acidsfrom adipose tissue due to insulin resistance in DM accumulatewithin hepatocytes. Insulin resistance also mediates release ofcytokines, such as leptin and tumor necrosis factor-alpha,which in turn mediate activation of inflammatory pathways41

and mitochondrial oxidative stress within the hepatocytes.42

Furthermore, adiponectin, an anti-inflammatory cytokine pro-duced by adipose tissue, is decreased in states of insulinresistance.43,44 Local inflammation and circulating adipokinesstimulate stellate cells to produce collagen, connective tissuegrowth factor, and extracellular matrix, ultimately resulting infibrosis.45 Risk of HCC has been shown to be modulated byantidiabetic medications. Insulin use was associated withincreased risk and use of oral drugs, including metformin andthiazolidinediones, was linked with decreased risk.46,47 In thecurrent study, the lack of details on diabetic medications limitedanalysis on the impact antidiabeticmedications have on the riskof cirrhosis and HCC.

We found that diabetics with ALD or NAFLD related liverdisease had an increased likelihood of developing encephalo-pathy without an increase in risk for ascites or varicealbleeding. Similar findings were reported in another study onpatients with decompensated cirrhosis. In this study, dia-betics relative to nondiabetics had a higher prevalence andseverity of hepatic encephalopathy. There were no significantdifferences between the two groups, however, in terms ofChild-Pugh class, MELD scores, or the presence of ascitesand esophageal varices.48 In the future, mechanistic studiesshould be performed to identify pathways mediating thiseffect of diabetes on the development of hepatic encephalo-pathy among patients with cirrhosis. Interestingly, in spite ofthe increased risk for developing cirrhosis and HCC indiabetics, the overall survival was similar to nondiabetics. In

another study that evaluated patients with compensated livercirrhosis, diabetes was associated with a significant increasein mortality.49 This discrepancy with our data may be due tothe relatively short follow-up period (median around 3 years)in our study.

The advantages of the current study include its largecohort and the well-characterized study population of stea-tohepatitis-related liver disease patients. Limitations includeits retrospective design, patient population from a singlecenter, and lack of details on alcohol use, control of NAFLDrisk factors (including diabetes and weight), and antidiabeticmedications. Prospective studies with a larger sample sizeand longer follow-up period are suggested in order toexamine: 1) the role of antidiabetic medications on thedevelopment of cirrhosis and its complications in patientswith steatohepatitis-related liver disease; 2) the effect ofdiabetes on clinical end points, including overall survival andtransplantation, and 3) the benefit of more aggressive HCCscreening in diabetics with steatohepatitis-related liverdisease.

Conclusions

Diabetes is a risk factor for the development of cirrhosis andHCC in the natural history of ALD and NAFLD. Our studyfindings are of clinical relevance and demonstrate the needfor a) better management and control of diabetes and b)more rigorous screening and surveillance of HCC amongpatients with steatohepatitis-related liver disease.

Conflict of interest

None

Author contributions

Performing data collection (EJR, DK, MS, KR), conceptualizingand designing the study as well as performing data analysis(AKS), reviewing the manuscript (AKS, JRB).

References

[1] Singal AK, Anand BS. Recent trends in the epidemiology of alcoholic liverdisease. Clin Liver Dis 2013;2:53–56. doi: 10.1002/cld.168.

[2] Völzke H. Multicausality in fatty liver disease: is there a rationale todistinguish between alcoholic and non-alcoholic origin? World JGastroenterol 2012;18:3492–3501. doi: 10.3748/wjg.v18.i27.3492.

[3] Chalasani N, Younossi Z, Lavine JE, Diehl AM, Brunt EM, Cusi K, et al. Thediagnosis and management of non-alcoholic fatty liver disease: practiceguideline by the American Gastroenterological Association, AmericanAssociation for the Study of Liver Diseases, and American College ofGastroenterology. Gastroenterology 2012;142:1592–1609. doi: 10.1053/j.gastro.2012.04.001.

[4] Charlton MR, Burns JM, Pedersen RA, Watt KD, Heimbach JK, Dierkhising RA.Frequency and outcomes of liver transplantation for nonalcoholic steatohe-patitis in the United States. Gastroenterology 2011;141:1249–1253. doi:10.1053/j.gastro.2011.06.061.

[5] Singal AK, Guturu P, Hmoud B, Kuo YF, Salameh H, Wiesner RH. EvolvingFrequency and Outcomes of Liver Transplantation Based on Etiology ofLiver Disease. Transplantation 2013;95:755–760. doi: 10.1097/TP.0b013e31827afb3a.

[6] http://www.cdc.gov/diabetes/data/statistics/2014statisticsreport.html,accessed October 24, 2014.

[7] Palmeira CM, Rolo AP, Berthiaume J, Bjork JA, Wallace KB. Hyperglycemiadecreases mitochondrial function: The regulatory role of mitochondrialbiogenesis. Toxicol Appl Pharmacol 2007;225:214–220. doi: 10.1016/j.taap.2007.07.015.



[8] Williamson RM, Price JF, Glancy S, Perry E, Nee LD, Hayes PC, et al.Prevalence of and risk factors for hepatic steatosis and nonalcoholic Fattyliver disease in people with type 2 diabetes: the Edinburgh Type 2 DiabetesStudy. Diabetes Care 2011;34:1139–1144. doi: 10.2337/dc10-2229.

[9] Wanless IR, Lentz JS. Fatty Liver Hepatitis (Steatohepatitis) and Obesity - AnAutopsy Study with Analysis of Risk Factors. Hepatology 1990;12:1106–1110. doi: 10.1002/hep.1840120505.

[10] Younossi ZM, Gramlich T, Matteoni CA, Boparai N, McCullough AJ.Nonalcoholic Fatty Liver Disease in Patients With Type 2 Diabetes. ClinGastroenterol Hepatol 2004;2:262–265. doi: 10.1016/S1542-3565(04)00014-X.

[11] Adams LA, Sanderson S, Lindor KD, Angulo P. The histological course ofnonalcoholic fatty liver disease: a longitudinal study of 103 patients withsequential liver biopsies. J Hepatol 2005;42:132–138. doi: 10.1016/j.jhep.2004.09.012.

[12] Adams LA, Lymp JF, St Sauver J, Sanderson SO, Lindor KD, Feldstein A, et al.The natural history of nonalcoholic fatty liver disease: A population-basedcohort study. Gastroenterology 2005;129:113–121. doi: 10.1053/j.gastro.2005.04.014.

[13] de Ledinghen V, Ratziu V, Causse X, Le Bail B, Capron D, Renou C, et al.Diagnostic and predictive factors of significant liver fibrosis and minimallesions in patients with persistent unexplained elevated transaminases. Aprospective multicenter study. J Hepatol 2006;45:592–599. doi: 10.1016/j.jhep.2006.05.008.

[14] Angulo P, Keach JC, Batts KP, Lindor KD. Independent predictors of liverfibrosis in patients with nonalcoholic steatohepatitis. Hepatology 1999;30:1356–1362. doi: 10.1002/hep.510300604.

[15] Raynard B, Balian A, Fallik D, Capron F, Bedossa P, Chaput JC, et al. Riskfactors of fibrosis in alcohol-induced liver disease. Hepatology 2002;35:635–638. doi: 10.1053/jhep.2002.31782.

[16] Hessheimer AJ, Forner A, Varela M, Bruix J. Metabolic risk factors are a majorcomorbidity in patients with cirrhosis independent of the presence ofhepatocellular carcinoma. Eur J Gastroenterol Hepatol 2010;22:1239–1244. doi: 10.1097/MEG.0b013e32833aa19b.

[17] Chen CL, Yang HI, Yang WS, Liu CJ, Chen PJ, You SL, et al. Metabolic factorsand risk of hepatocellular carcinoma by chronic hepatitis B/C infection: Afollow-up study in Taiwan. Gastroenterology 2008;135:111–121. doi:10.1053/j.gastro.2008.03.073.

[18] Lai MS, Hsieh MS, Chiu YH, Chen TH. Type 2 diabetes and hepatocellularcarcinoma: A cohort study in high prevalence area of hepatitis virus infection.Hepatology 2006;43:1295–1302. doi: 10.1002/hep.21208.

[19] Adami HO, Ekbom A, Chow WH, Nyren O, Wolk A, Berne C, et al. Excess riskof primary liver cancer in patients with diabetes mellitus - Response. J NatlCancer Inst 1997;89:327–328. doi: 10.1093/jnci/89.4.327.

[20] Wideroff L, Gridley G, Mellemkjaer L, Chow WH, Linet M, Keehn S, et al.Cancer incidence in a population-based cohort of patients hospitalized withdiabetes mellitus in Denmark. J Natl Cancer Inst 1997;89:1360–1365. doi:10.1093/jnci/89.18.1360.

[21] Hassan MM, Hwang LY, Hatten CJ, Swaim M, Li D, Abbruzzese JL, et al. Riskfactors for hepatocellular carcinoma: Synergism of alcohol with viralhepatitis and diabetes mellitus. Hepatology 2002;36:1206–1213. doi:10.1053/jhep.2002.36780.

[22] Davila JA, Morgan RO, Shaib Y, McGlynn KA, El-Serag HB. Diabetes increasesthe risk of hepatocellular carcinoma in the United States: a population basedcase control study. Gut 2005;54:533–539. doi: 10.1136/gut.2004.052167.

[23] Hassan MM, Curley SA, Li DH, Kaseb A, Davila M, Abdalla EK, et al.Association of Diabetes Duration and Diabetes Treatment With the Riskof Hepatocellular Carcinoma. Cancer 2010;116:1938–1946. doi: 10.1002/cncr.24982.

[24] Kleiner DE, Brunt EM, Van Natta M, Behling C, Contos MJ, Cummings OW,et al. Design and validation of a histological scoring system for nonalcoholicfatty liver disease. Hepatology 2005;41:1313–1321. doi: 10.1002/hep.20701.

[25] Association Diabetes Association. Diagnosis and classification of diabetesmellitus. Diabetes Care 2014;37(Suppl 1):S81–S90. doi: 10.2337/dc14-S081.

[26] Alberti KG, Zimmet P, Shaw J. Metabolic syndrome - a new world-widedefinition. A Consensus Statement from the International DiabetesFederation. Diabetic Medicine 2006;23:469–480. doi: 10.1111/j.1464-5491.2006.01858.x.

[27] Stone NJ, Bilek S, Rosenbaum S. Recent National Cholesterol EducationProgram Adult Treatment Panel III update: adjustments and options.Am J Cardiol 2005;96:53E–59E. doi: 10.1016/j.amjcard.2005.06.006.

[28] Aronow WS. Updated National Cholesterol Education Program III guidelines.J Am Med Dir Assoc 2005;6:160–161. doi: 10.1016/j.jamda.2004.12.022.

[29] Bruix J, Sherman M, American Association for the Study of Liver Diseases.Management of hepatocellular carcinoma: an update. Hepatology 2011;53:1020–1022. doi: 10.1002/hep.24199.

[30] D’Hoore W, Sicotte C, Tilquin C. Risk adjustment in outcome assessment: theCharlson comorbidity index. Methods Inf Med 1993;32:382–387.

[31] Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifyingprognostic comorbidity in longitudinal studies: development and validation.J Chronic Dis 1987;40:373–383. doi: 10.1016/0021-9681(87)90171-8.

[32] Brunt

the second affiliated hospital of chongqing...prof. paul j. gaglio new york, usa ping gu new york,...

Documents