The ABCs of Viral Hepatitis That Define Biomarker Signatures of Acute Viral Hepatitis Darragh Duffy,1,2 Rasha Mamdouh,3 Melissa Laird,1,2 Charlotte Soneson,4 Lenaig Le Fouler,5 Ma€ı El-Daly,6,7 Armanda Casrouge,1,2 Jeremie Decalf,1,2 Amal Abbas,3 Noha Sharaf Eldin,3 Magnus Fontes,4 Mohamed Abdel-Hamid,6,8 Mostafa K. Mohamed,3,6 Mona Rafik,3 Arnaud Fontanet,5,9 and Matthew L. Albert1,2,10 Viral hepatitis is the leading cause of liver disease worldwide and can be caused by several agents, including hepatitis A (HAV), B (HBV), and C (HCV) virus. We employed multiplexed protein immune assays to identify biomarker signatures of viral hepatitis in order to define unique and common responses for three different acute viral infections of the liver. We performed multianalyte profiling, measuring the concentrations of 182 serum proteins obtained from acute HAV- (18), HBV- (18), and HCV-infected (28) individuals, recruited as part of a hospital-based surveillance program in Cairo, Egypt. Virus-specific biomarker signatures were identified and validation was performed using a unique patient population. A core signature of 46 plasma proteins was commonly modulated in all three infections, as compared to healthy controls. Principle component analysis (PCA) revealed a host response based upon 34 proteins, which could distinguish HCV patients from HAV- and HBV-infected individuals or healthy controls. When HAV and HBV groups were compared directly, 34 differentially expressed serum proteins allowed the separation of these two patient groups. A validation study was performed on an additional 111 patients, confirming the relevance of our initial findings, and defining the 17 analytes that reproducibly segregated the patient populations. Conclusions: This combined discovery and biomarker validation approach revealed a previously unrecognized virus-specific induction of host proteins. The identification of hepatitis virus specific signatures provides a foundation for functional studies and the identification of potential correlates of viral clearance. (HEPATOLOGY 2014;59:1273-1282)
T
he liver functions primarily as a metabolic organ and is in constant exposure to dietary and microbial antigens.1 This requires a state of relative immune tolerance, which evolutionarily has been exploited by pathogens such as hepatitis viruses, bacteria, and parasites.1 Three hepatotropic viruses, hepatitis
A, B, and C (HAV, HBV, and HCV, respectively) all directly infect hepatocytes, triggering similar acute disease in symptomatic patients despite displaying differing modalities of infection and levels of pathogenicity. HAV is a positive-strand RNA virus and a member of the Picornaviridae family, and infection results in a
Abbreviations: AHC, acute hepatitis C; a1-AT, alpha 1 antitrypsin; ALT, alanine aminotransferase; ANOVA, analysis of variance; Apo, apolipoprotein; BDNF, brain-derived neurotrophic factor; CLIA, chemiluminescent immunoassay; CMV, cytomegalovirus; EBV, Epstein-Barr virus; FDR, false discovery rate; HAV, hepatitis A virus; HBV, hepatitis B virus; HCV, hepatitis C virus; ICAM-1, intercellular adhesion molecule 1; IFN, interferon; IgM, immunoglobulin M; IL, interleukin; IP-10, IFN-g-inducible protein 10; LDD, lowest detectable dose; MAP, multianalyte profiling; MCP-4, monocyte chemotactic protein 4; M-CSF, macrophage colony-stimulating factor; MIP, macrophage-inflammatory protein; ORF, open reading frame; PARC, pulmonary and activation-regulated chemokine; PCA, principle component analysis; RT-PCR, reverse-transcriptase polymerase chain reaction; t1/2, half-life; TGF-a, transforming growth factor alpha; TNF, tumor necrosis factor; TTR, transthyretin; ULN, upper limit of normal. From the 1Laboratory of Dendritic Cells Immunobiology, Institut Pasteur, Paris, France; 2INSERM U818, Paris, France; 3Faculty of Medicine, Aim Shams University, Cairo, Egypt; 4Centre for Mathematical Sciences, Lund University, Lund, Sweden; 5Emerging Disease Epidemiology Unit, Institut Pasteur, Paris, France; 6Liver Disease Research Unit, National Hepatology and Tropical Medicine Research Institute, Cairo, Egypt; 7National Liver Institute, Menoufia University, e tiers, Paris, France; and Menoufia, Egypt; 8Department of Microbiology, Faculty of Medicine, Minia University, Egypt; 9Conservatoire National des Arts et M 10 Universite Paris Descartes, 75006 Paris, France. Received July 12, 2013; accepted October 11, 2013. This work was supported by ANRS grant 12199 (to M.L.A., A.F., and M.R.), the European Research Council Young Investigator Award (to M.L.A.), and the European FP7 project SPHINX (grant reference no.: 261365). 1273
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self-limiting acute disease with a considerable percentage of adult patients developing clinical symptoms of fever or jaundice.2,3 Partly as a result of a successful vaccine, relatively little is known about immune clearance of HAV, although recent studies in chimpanzees suggested a role for CD41 T cells.4 Earlier studies demonstrated that viral loads peak 2 weeks posttransmission, with a half-life (t1/2) of 9 days for viral populations in the liver, and are undetectable by weeks 6-8. Notably, clinical symptoms develop after week 4 and are coincident with the emergence of a humoral response to viral proteins.3,5 HBV is an enveloped circular DNA virus belonging to the Hepadnaviridae family. It directly enters the nucleus of infected hepatocytes to initiate its replication cycle,6 peak viral load occurs at 7-8 weeks posttransmission, and the reported t1/2 is 2-3 days.6,7 Similar to HAV, HBV elicits a limited type I interferon (IFN) response in the liver,8,9 and clearance is believed to be mediated by CD41 and CD81 T cells.10 Approximately 5%-10% of acutely infected adults will progress to chronic HBV infection. Although a prophylactic vaccine exists, HBV remains a leading worldwide public health problem, with 350 million chronically infected persons and >4 million acute clinical cases per year. HCV is an enveloped positive-strand RNA virus and is classified among the Flaviviridae family. In contrast to HAV and HBV, it results in chronic infection in >60% of cases, and no vaccine currently exists. HCV also has an early peak in viral load, however it is unique among the three viruses in its rapid turnover and induction of a strong type I IFN response in the liver.11,12 Studies in humans and chimpanzees have highlighted the importance of the adaptive immune response for achieving spontaneous clearance of the virus,13 although neither cellular nor humoral immunity is believed to be fully protective against secondary infection.14,15 A direct comparison of acute viral hepatitis infections in humans has not been previously performed from the perspective of the host response. This is, in part, a result of the limited incident of disease for HAV as well as the low percentage of symptomatic
HEPATOLOGY, April 2014
acute HCV patients in the United States and Europe. Beginning in 2002, we established a hospital-based surveillance program to monitor acute symptomatic viral hepatitis in Cairo, Egypt.16 This program was established to characterize the current localized HCV epidemic, which resulted from iatrogenic transmissions during the mass treatment parenteral antischistosomiasis (PAT) campaigns in the 1970s.17 In the context of this program, we identified patients monoinfected with either HAV, HBV, or HCV. To identify the inflammatory signatures that define the host response to these different infectious agents, we performed multianalyte profiling (MAP) using a panel of 182 chemiluminescent immunoassay (CLIA)-validated immunoassays. We report on a core signature profile that was common for acute infection of the liver by three different hepatotropic viruses, as well as serum protein biomarker signatures for each virus and host interaction. To identify patterns of virus-specific protein responses, we utilized principle component analysis (PCA), in combination with a novel statistical tool (the Projection Score),18 that aimed to determine the optimal subset of features for distinguishing patient groups. A collection of feature subsets were obtained by ranking all analytes according to their adjusted P values from an analysis of variance (ANOVA), contrasting hepatitis subtypes and successively eliminating the analytes that showed the highest adjusted P values. The projection score for such a subset is a measure of the information content captured by PCA, and the optimal subset of features is defined as the one that provides the most informative PCA representation of the samples in the data set. Thus, by comparing the information content of variable subsets resulting from different cut-off levels for the adjusted P value, the projection score provides an objective, statistically well-founded way to establish an optimal cutoff. Notably, projection score analysis may represent a general mechanism for enabling statistical analysis of biomarker information to optimize the variable subsets in the context of discovery-based research. Subsequent to the identification of host response signatures, our core set of biomarkers was validated using an independent patient population. These results will provide a solid
Address reprint requests to: Matthew L. Albert, M.D., Ph.D., Laboratory of Dendritic Cell Immunobiology and Inserm U818, Institut Pasteur, 25 rue de Dr. Roux, Paris 75724, France. E-mail: [email protected]; fax: 133 1 45 68 85 48. C 2014 by the American Association for the Study of Liver Diseases. Copyright V View this article online at wileyonlinelibrary.com. DOI 10.1002/hep.26901 Potential conflict of interest: Nothing to report. Additional Supporting Information may be found in the online version of this article.
HEPATOLOGY, Vol. 59, No. 4, 2014
foundation for mechanistic studies and may provide insights into different hepatotropic viral disease pathogenesis.
Patients and Methods Patient, Cohort, and Study Design. Study 1 included 18 patients with HAV, 18 with HBV, 28 with HCV, and 15 healthy controls (Supporting Table 1), and the validation population, study 2, included 20 patients with HAV, 20 with HBV, and 71 with HCV (Supporting Table 2). All patients were recruited from two “fever hospitals” specialized in infectious diseases in Cairo, Egypt.16 Inclusion criteria were characteristic clinical findings including fever or jaundice as well as an elevated alanine aminotransferase (ALT) 3 times the upper limit of normal (ULN; Supporting Tables 1 and 2). Acute HCV was identified by positive HCV-RNA (reverse-transcriptase polymerase chain reaction; RT-PCR) with either negative or positive anti-HCV antibody (Ab; Innotest HCV Ab IV; Innogenetics N.V., Ghent, Belgium). Patients with negative anti-HCV Ab and positive HCV-RNA were considered as acute hepatitis C (AHC) cases. Patients with positive anti-HCV Ab and positive HCV-RNA were considered AHC cases only if ALT values were >10 times ULN and there was a recent history of possible high-risk exposure to HCV (e.g., surgical procedure). Acute HBV was defined by a positive immunoglobulin M (IgM) antihepatitis B virus core (Corzyme M; ribosomal DNA; Abbott Laboratories, Abbott Park, IL) and circulating levels of hepatitis B surface antigen (Auszyme Monoclonal; third-generation enzyme immunoassay; Abbott Laboratories). Acute hepatitis A infection was defined as positive anti-HAV IgM Ab. Using RT-PCR for HEV-RNA (inhouse assay using open reading frame ORF1 and ORF2 primers) and serological testing, including anti–EpsteinBarr virus (EBV) IgM (ETI-EBV-M reverse P001605; Dia Sorin, Vercelle, Italy), anti-cytomegalovirus (CMV) IgM (AXSYM system-CMV-IgM; Abbott Laboratories, Wiesbaden, Delknheim, Germany), and anti-Toxoplasma IgM (AXSYM system-Toxo-IgM; Abbott Laboratories, Germany), EBV, CMV, toxoplasmosis, and hepatitis E infection were all used as exclusion criteria. Serum samples analyzed in this study were collected with a median of 7-10 days postsymptoms (Supporting Table 1 and 2). All patients were treatment na€ıve because this was their first recorded incidence of hepatitis. Healthy control serum from 15 anonymous donors was obtained from the local Cairo blood bank and confirmed to be negative for HAV, HBV, HCV, and human immunodeficiency virus. Protocols were reviewed and approved by local ethical committees
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Table 1. Protein Analytes That Distinguish HAV, HBV, and HCV Patients From Healthy Controls Analyte
ALT PARC HB-EGF Thrombomodulin Complement 3 a1-AT EGF M-CSF IP-10 TECK MCP-4 ICAM-1 VCAM-1 NrCAM Apo H IgM AXL IgA MIG E-selectin TTR TNF RII MIP-1a Apo D
P Value
Q Value 225
4.56 3 10 3.83 3 10221 9.8 3 10218 4.51 3 10217 1.07 3 10215 1.38 3 10215 2.1 3 10215 1.03 3 10213 2.32 3 10213 4.97 3 10213 7.56 3 10213 2.21 3 10212 3.49 3 10212 4.08 3 10211 4.82 3 10211 9.81 3 10211 7.28 3 10210 1.96 3 1029 2.49 3 1029 1.8 3 1028 1.8 3 1028 3.18 3 1028 4.54 3 1028 9.71 3 1028
Group 223
6.65 3 10 2.8 3 10219 4.77 3 10216 1.64 3 10215 3.12 3 10214 3.35 3 10214 4.38 3 10214 1.89 3 10212 3.77 3 10212 7.26 3 10212 1 3 10211 2.7 3 10211 3.92 3 10211 4.25 3 10210 4.69 3 10210 8.42 3 10210 5.9 3 1029 1.51 3 1028 1.82 3 1028 1.24 3 1027 1.24 3 1027 2.09 3 1027 2.84 3 1028 5.8 3 1028
ABC C AB AB C C ABC ABC ABC C AB C ABC ABC C ABC AB C ABC ABC ABC ABC AB C
The 24 most differential analytes are shown, indicating the P and Q values (ANOVA). Analytes were quantified using MAP and are listed in the order of statistical significance. Data shown are from the patients recruited as part of study 1. To identify the patient group(s) associated with the protein analyte, Dunn’s post-test was performed. Abbreviations: HB-EGF, heparin-binding EGF-like growth factor; EGF, epidermal growth factor; TECK, thymus-expressed chemokine; VCAM-1, vascular cell adhesion molecule 1; NrCAM, neuronal cell adhesion molecule; AXL, AXL receptor tyrosine kinase; MIG, monokine-induced by gamma interferon.
and patients provided informed consent. The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki. MAP. Sera were clarified by a high-speed centrifugation and analyzed using Luminex xMAP technology. Samples were measured by a diagnostic lab (Myriad Rules Based Medicine) for 182 molecules with all assays being CLIA certified (validated using guidelines set forth by the U.S. Clinical and Laboratory Standards Institute, Wayne, PA). Additional details on determining assay sensitivity are included in the Supporting Materials (Supporting Table 3). Statistical Analyses. PCA, agglomerative hierarchical clustering (based on mean linkage), and ANOVA testing were performed with Qlucore Omics Explorer (Qlucore, Lund, Sweden). The projection score was computed and used to quantify the information content for each of a collection of variable subsets obtained by ordering the analytes with respect to their false discovery rate (FDR)adjusted ANOVA P values and successively excluding the analytes with the highest adjusted P values. By selecting
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HEPATOLOGY, April 2014
Table 2. Protein Analytes That Distinguish HAV, HBV, and HCV Patients Study 1 Analyte
PARC HB-EGF Thrombomodulin a1-AT Complement 3 IgA IgM MCP-4 BDNF Apo H vWF Prolactin C-reactive protein AXL VEGF Apo B TGF-a Osteopontin THP Clusterin MIP-1a CD5L M-CSF HGF TNF RII Apo D Apo A-I ICAM-1 CD40 ligand IL-18 PPP Lipoprotein (a) TIMP-1 IL-6
P Value
Study 2 Q Value
24
7.55 3 104.03 3 10220 1.15 3 10213 1.74 3 10213 1.75 3 10213 5.14 3 10211 8.17 3 10211 1.28 3 10210 2.45 3 1029 1.71 3 1027 1.76 3 1027 5.8 3 1027 2.31 3 1028 2.35 3 1026 2.69 3 1026 2.72 3 1026 6.8 3 1026 1.06 3 1025 1.54 3 1025 1.61 3 1025 1.86 3 1025 2.46 3 1025 2.46 3 1025 3.9 3 1025 4.5 3 1025 5.7 3 1025 7.17 3 1025 7.8 3 1025 7.99 3 1025 9.13 3 1025 1.2 3 1024 4.5 3 1024 7.1 3 1024 1.3 3 1023
Group 221
1.05 3 10 2.8 3 10218 4.88 3 10212 4.88 3 10212 4.88 3 10212 1.19 3 1029 1.62 3 1029 2.23 3 1029 3.92 3 1028 2.23 3 1027 2.23 3 1026 6.72 3 1026 2.34 3 1027 2.34 3 1025 2.36 3 1025 2.36 3 1025 5.56 3 1025 8.18 3 1025 1.12 3 1024 1.12 3 1024 1.22 3 1024 1.49 3 1024 1.49 3 1024 2.2 3 1024 2.5 3 1024 2.7 3 1024 3.6 3 1024 3.8 3 1024 3.8 3 1024 4.2 3 1024 5.6 3 1024 1.9 3 1023 3.0 3 1023 5.4 3 1023
C C C C C C C C C C C C C B C C C C C C C B C C C C C C C C B C C C
Analyte
IgM Apo B M-CSF CD5L Complement 3 a1-AT Apo D PPP Apo H AXL BDNF Osteopontin THP vWF VEGF HGF TIMP-1 Apo AI Lipoprotein (a) Clusterin MCP-4 TNF RII Thrombomodulin Prolactin PARC MIP-1a ICAM-1 CD40 ligand IgA IL-18 C-reactive protein IL-6 HB-EGF TGF-a
P Value
Q Value 213
1.28 3 10 7.57 3 1028 1.83 3 1027 1.19 3 1025 3.2 3 1024 4.6 3 1023 5.05 3 1023 8.93 3 1023 9.6 3 1023 1.1 3 1022 1.46 3 1022 1.66 3 1022 2.57 3 1022 3.03 3 1022 4.2 3 1022 4.5 3 1022 5.0 3 1022 5.4 3 1022 7.7 3 1022 7.9 3 1022 9.1 3 1022 1.1 3 1021 1.6 3 1021 1.6 3 1021 1.9 3 1021 2.8 3 1021 3.8 3 1021 5.4 3 1021 5.6 3 1021 7.0 3 1021 7.5 3 1021 9.8 3 1021 — —
Group 212
1.45 3 10 6.44 3 1027 1.24 3 1026 6.75 3 1025 1.5 3 1023 1.9 3 1022 1.9 3 1022 2.9 3 1022 2.9 3 1022 3.3 3 1022 3.8 3 1022 4.03 3 1022 5.8 3 1022 6.45 3 1022 8.45 3 1022 8.5 3 1022 9.2 3 1022 9.2 3 1022 1.2 3 1021 1.2 3 1021 1.3 3 1021 1.6 3 1021 2.1 3 1021 2.1 3 1021 2.4 3 1021 3.4 3 1021 4.4 3 1021 6.1 3 1021 6.2 3 1021 7.4 3 1021 7.7 3 1021 9.8 3 1021 — —
C B C B C C C A C B C C C B — A C — — — — — — — — — — — — — — — — —
The 34 most differential analytes are shown, indicating the P and Q values (ANOVA). Analytes were quantified using MAP and are listed in the order of statistical significance, as determined from the analysis of data from the patients recruited as part of study 1. These same analytes were then examined in an independent cohort (study 2). To identify the patient group(s) associated with the protein analyte, Dunn’s post-test was performed. Abbreviations: HB-EGF, heparin-binding epidermal growth factor (EGF)-like growth factor; vWF, von Willebrand factor; AXL, AXL receptor tyrosine kinase; VEGF, vascular endothelial growth factor; THP, Tamm-Horsfall protein; HGF, hepatocyte growth factor; PPP, protein serine/threonine phosphatases; TIMP-1, tissue inhibitor metallopeptidase inhibitor 1.
the variable subset with the highest information content (i.e., with the highest projection score), we objectively established an optimally adjusted P value threshold to use as inclusion criterion for defined protein signatures.18 Kruskal-Wallis’ and Mann-Whitney’s unpaired tests and Spearman’s correlation calculations were performed using OmniViz (BioWisdom Ltd., Cambridge, UK) or Prism (GraphPad Software Inc., San Diego, CA). Data are reported as standard P values and FDR-adjusted P values (called Q values) to control for multiple testing.19
Results A Common Hepatic Viral Signature. To examine the signature of the host response to HAV, HBV, and
HCV infection, we performed Luminex xMAP on sera of patients, isolated at the time of acute, symptomatic infection. To clean the data set, we removed 43 analytes that had a median value across all samples (study 1) that was below the lowest detectable dose (LDD). For the remaining 139 analytes (Supporting Table 3), individual patients that had a value below the LDD were assigned a value half that of the lowest value detected in the data set. To identify a common hepatic viral signature, we compared HAV-, HBV-, and HCVinfected patients with healthy controls using two complementary strategies. First, we performed one-way ANOVA, contrasting healthy donors and the combined set of infected patients. This approach revealed 46 analytes that significantly distinguished patients
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Table 3. Protein Analytes That Distinguish HAV and HBV Patients Study 1 Analyte
IP-10 EGFR Betacellulin AXL PPP CD5L MIP-1b SAP IgM Tenascin C MIG SOD1 TNF RII MIF ANG-2 MIP-3a Haptoglobin IL-1b TBG TTR Ferritin ACE PLGF M-CSF Apo A-II b2 microglobulin Cancer antigen 19-9 Eotaxin-1 E-selectin Apo E VCAM-1 EGF Cystatin C IL-18
P Value 24
4.3 3 10 6.5 3 1024 5.13 3 1023 7.5 3 1023 1.14 3 1022 1.19 3 1022 1.51 3 1022 2.47 3 1022 3.26 3 1022 3.45 3 1022 3.71 3 1022 3.72 3 1022 4.57 3 1022 4.68 3 1022 5.5 3 1022 5.5 3 1022 6.2 3 1022 7.2 3 1022 7.8 3 1022 8.6 3 1022 8.7 3 1022 9.6 3 1022 1.0 3 1021 1.0 3 1021 1.1 3 1021 1.1 3 1021 1.1 3 1021 1.2 3 1021 1.2 3 1021 1.2 3 1021 1.2 3 1021 1.3 3 1021 1.3 3 1021 1.4 3 1021
Study 2
T
he liver functions primarily as a metabolic organ and is in constant exposure to dietary and microbial antigens.1 This requires a state of relative immune tolerance, which evolutionarily has been exploited by pathogens such as hepatitis viruses, bacteria, and parasites.1 Three hepatotropic viruses, hepatitis
A, B, and C (HAV, HBV, and HCV, respectively) all directly infect hepatocytes, triggering similar acute disease in symptomatic patients despite displaying differing modalities of infection and levels of pathogenicity. HAV is a positive-strand RNA virus and a member of the Picornaviridae family, and infection results in a
Abbreviations: AHC, acute hepatitis C; a1-AT, alpha 1 antitrypsin; ALT, alanine aminotransferase; ANOVA, analysis of variance; Apo, apolipoprotein; BDNF, brain-derived neurotrophic factor; CLIA, chemiluminescent immunoassay; CMV, cytomegalovirus; EBV, Epstein-Barr virus; FDR, false discovery rate; HAV, hepatitis A virus; HBV, hepatitis B virus; HCV, hepatitis C virus; ICAM-1, intercellular adhesion molecule 1; IFN, interferon; IgM, immunoglobulin M; IL, interleukin; IP-10, IFN-g-inducible protein 10; LDD, lowest detectable dose; MAP, multianalyte profiling; MCP-4, monocyte chemotactic protein 4; M-CSF, macrophage colony-stimulating factor; MIP, macrophage-inflammatory protein; ORF, open reading frame; PARC, pulmonary and activation-regulated chemokine; PCA, principle component analysis; RT-PCR, reverse-transcriptase polymerase chain reaction; t1/2, half-life; TGF-a, transforming growth factor alpha; TNF, tumor necrosis factor; TTR, transthyretin; ULN, upper limit of normal. From the 1Laboratory of Dendritic Cells Immunobiology, Institut Pasteur, Paris, France; 2INSERM U818, Paris, France; 3Faculty of Medicine, Aim Shams University, Cairo, Egypt; 4Centre for Mathematical Sciences, Lund University, Lund, Sweden; 5Emerging Disease Epidemiology Unit, Institut Pasteur, Paris, France; 6Liver Disease Research Unit, National Hepatology and Tropical Medicine Research Institute, Cairo, Egypt; 7National Liver Institute, Menoufia University, e tiers, Paris, France; and Menoufia, Egypt; 8Department of Microbiology, Faculty of Medicine, Minia University, Egypt; 9Conservatoire National des Arts et M 10 Universite Paris Descartes, 75006 Paris, France. Received July 12, 2013; accepted October 11, 2013. This work was supported by ANRS grant 12199 (to M.L.A., A.F., and M.R.), the European Research Council Young Investigator Award (to M.L.A.), and the European FP7 project SPHINX (grant reference no.: 261365). 1273
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self-limiting acute disease with a considerable percentage of adult patients developing clinical symptoms of fever or jaundice.2,3 Partly as a result of a successful vaccine, relatively little is known about immune clearance of HAV, although recent studies in chimpanzees suggested a role for CD41 T cells.4 Earlier studies demonstrated that viral loads peak 2 weeks posttransmission, with a half-life (t1/2) of 9 days for viral populations in the liver, and are undetectable by weeks 6-8. Notably, clinical symptoms develop after week 4 and are coincident with the emergence of a humoral response to viral proteins.3,5 HBV is an enveloped circular DNA virus belonging to the Hepadnaviridae family. It directly enters the nucleus of infected hepatocytes to initiate its replication cycle,6 peak viral load occurs at 7-8 weeks posttransmission, and the reported t1/2 is 2-3 days.6,7 Similar to HAV, HBV elicits a limited type I interferon (IFN) response in the liver,8,9 and clearance is believed to be mediated by CD41 and CD81 T cells.10 Approximately 5%-10% of acutely infected adults will progress to chronic HBV infection. Although a prophylactic vaccine exists, HBV remains a leading worldwide public health problem, with 350 million chronically infected persons and >4 million acute clinical cases per year. HCV is an enveloped positive-strand RNA virus and is classified among the Flaviviridae family. In contrast to HAV and HBV, it results in chronic infection in >60% of cases, and no vaccine currently exists. HCV also has an early peak in viral load, however it is unique among the three viruses in its rapid turnover and induction of a strong type I IFN response in the liver.11,12 Studies in humans and chimpanzees have highlighted the importance of the adaptive immune response for achieving spontaneous clearance of the virus,13 although neither cellular nor humoral immunity is believed to be fully protective against secondary infection.14,15 A direct comparison of acute viral hepatitis infections in humans has not been previously performed from the perspective of the host response. This is, in part, a result of the limited incident of disease for HAV as well as the low percentage of symptomatic
HEPATOLOGY, April 2014
acute HCV patients in the United States and Europe. Beginning in 2002, we established a hospital-based surveillance program to monitor acute symptomatic viral hepatitis in Cairo, Egypt.16 This program was established to characterize the current localized HCV epidemic, which resulted from iatrogenic transmissions during the mass treatment parenteral antischistosomiasis (PAT) campaigns in the 1970s.17 In the context of this program, we identified patients monoinfected with either HAV, HBV, or HCV. To identify the inflammatory signatures that define the host response to these different infectious agents, we performed multianalyte profiling (MAP) using a panel of 182 chemiluminescent immunoassay (CLIA)-validated immunoassays. We report on a core signature profile that was common for acute infection of the liver by three different hepatotropic viruses, as well as serum protein biomarker signatures for each virus and host interaction. To identify patterns of virus-specific protein responses, we utilized principle component analysis (PCA), in combination with a novel statistical tool (the Projection Score),18 that aimed to determine the optimal subset of features for distinguishing patient groups. A collection of feature subsets were obtained by ranking all analytes according to their adjusted P values from an analysis of variance (ANOVA), contrasting hepatitis subtypes and successively eliminating the analytes that showed the highest adjusted P values. The projection score for such a subset is a measure of the information content captured by PCA, and the optimal subset of features is defined as the one that provides the most informative PCA representation of the samples in the data set. Thus, by comparing the information content of variable subsets resulting from different cut-off levels for the adjusted P value, the projection score provides an objective, statistically well-founded way to establish an optimal cutoff. Notably, projection score analysis may represent a general mechanism for enabling statistical analysis of biomarker information to optimize the variable subsets in the context of discovery-based research. Subsequent to the identification of host response signatures, our core set of biomarkers was validated using an independent patient population. These results will provide a solid
Address reprint requests to: Matthew L. Albert, M.D., Ph.D., Laboratory of Dendritic Cell Immunobiology and Inserm U818, Institut Pasteur, 25 rue de Dr. Roux, Paris 75724, France. E-mail: [email protected]; fax: 133 1 45 68 85 48. C 2014 by the American Association for the Study of Liver Diseases. Copyright V View this article online at wileyonlinelibrary.com. DOI 10.1002/hep.26901 Potential conflict of interest: Nothing to report. Additional Supporting Information may be found in the online version of this article.
HEPATOLOGY, Vol. 59, No. 4, 2014
foundation for mechanistic studies and may provide insights into different hepatotropic viral disease pathogenesis.
Patients and Methods Patient, Cohort, and Study Design. Study 1 included 18 patients with HAV, 18 with HBV, 28 with HCV, and 15 healthy controls (Supporting Table 1), and the validation population, study 2, included 20 patients with HAV, 20 with HBV, and 71 with HCV (Supporting Table 2). All patients were recruited from two “fever hospitals” specialized in infectious diseases in Cairo, Egypt.16 Inclusion criteria were characteristic clinical findings including fever or jaundice as well as an elevated alanine aminotransferase (ALT) 3 times the upper limit of normal (ULN; Supporting Tables 1 and 2). Acute HCV was identified by positive HCV-RNA (reverse-transcriptase polymerase chain reaction; RT-PCR) with either negative or positive anti-HCV antibody (Ab; Innotest HCV Ab IV; Innogenetics N.V., Ghent, Belgium). Patients with negative anti-HCV Ab and positive HCV-RNA were considered as acute hepatitis C (AHC) cases. Patients with positive anti-HCV Ab and positive HCV-RNA were considered AHC cases only if ALT values were >10 times ULN and there was a recent history of possible high-risk exposure to HCV (e.g., surgical procedure). Acute HBV was defined by a positive immunoglobulin M (IgM) antihepatitis B virus core (Corzyme M; ribosomal DNA; Abbott Laboratories, Abbott Park, IL) and circulating levels of hepatitis B surface antigen (Auszyme Monoclonal; third-generation enzyme immunoassay; Abbott Laboratories). Acute hepatitis A infection was defined as positive anti-HAV IgM Ab. Using RT-PCR for HEV-RNA (inhouse assay using open reading frame ORF1 and ORF2 primers) and serological testing, including anti–EpsteinBarr virus (EBV) IgM (ETI-EBV-M reverse P001605; Dia Sorin, Vercelle, Italy), anti-cytomegalovirus (CMV) IgM (AXSYM system-CMV-IgM; Abbott Laboratories, Wiesbaden, Delknheim, Germany), and anti-Toxoplasma IgM (AXSYM system-Toxo-IgM; Abbott Laboratories, Germany), EBV, CMV, toxoplasmosis, and hepatitis E infection were all used as exclusion criteria. Serum samples analyzed in this study were collected with a median of 7-10 days postsymptoms (Supporting Table 1 and 2). All patients were treatment na€ıve because this was their first recorded incidence of hepatitis. Healthy control serum from 15 anonymous donors was obtained from the local Cairo blood bank and confirmed to be negative for HAV, HBV, HCV, and human immunodeficiency virus. Protocols were reviewed and approved by local ethical committees
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Table 1. Protein Analytes That Distinguish HAV, HBV, and HCV Patients From Healthy Controls Analyte
ALT PARC HB-EGF Thrombomodulin Complement 3 a1-AT EGF M-CSF IP-10 TECK MCP-4 ICAM-1 VCAM-1 NrCAM Apo H IgM AXL IgA MIG E-selectin TTR TNF RII MIP-1a Apo D
P Value
Q Value 225
4.56 3 10 3.83 3 10221 9.8 3 10218 4.51 3 10217 1.07 3 10215 1.38 3 10215 2.1 3 10215 1.03 3 10213 2.32 3 10213 4.97 3 10213 7.56 3 10213 2.21 3 10212 3.49 3 10212 4.08 3 10211 4.82 3 10211 9.81 3 10211 7.28 3 10210 1.96 3 1029 2.49 3 1029 1.8 3 1028 1.8 3 1028 3.18 3 1028 4.54 3 1028 9.71 3 1028
Group 223
6.65 3 10 2.8 3 10219 4.77 3 10216 1.64 3 10215 3.12 3 10214 3.35 3 10214 4.38 3 10214 1.89 3 10212 3.77 3 10212 7.26 3 10212 1 3 10211 2.7 3 10211 3.92 3 10211 4.25 3 10210 4.69 3 10210 8.42 3 10210 5.9 3 1029 1.51 3 1028 1.82 3 1028 1.24 3 1027 1.24 3 1027 2.09 3 1027 2.84 3 1028 5.8 3 1028
ABC C AB AB C C ABC ABC ABC C AB C ABC ABC C ABC AB C ABC ABC ABC ABC AB C
The 24 most differential analytes are shown, indicating the P and Q values (ANOVA). Analytes were quantified using MAP and are listed in the order of statistical significance. Data shown are from the patients recruited as part of study 1. To identify the patient group(s) associated with the protein analyte, Dunn’s post-test was performed. Abbreviations: HB-EGF, heparin-binding EGF-like growth factor; EGF, epidermal growth factor; TECK, thymus-expressed chemokine; VCAM-1, vascular cell adhesion molecule 1; NrCAM, neuronal cell adhesion molecule; AXL, AXL receptor tyrosine kinase; MIG, monokine-induced by gamma interferon.
and patients provided informed consent. The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki. MAP. Sera were clarified by a high-speed centrifugation and analyzed using Luminex xMAP technology. Samples were measured by a diagnostic lab (Myriad Rules Based Medicine) for 182 molecules with all assays being CLIA certified (validated using guidelines set forth by the U.S. Clinical and Laboratory Standards Institute, Wayne, PA). Additional details on determining assay sensitivity are included in the Supporting Materials (Supporting Table 3). Statistical Analyses. PCA, agglomerative hierarchical clustering (based on mean linkage), and ANOVA testing were performed with Qlucore Omics Explorer (Qlucore, Lund, Sweden). The projection score was computed and used to quantify the information content for each of a collection of variable subsets obtained by ordering the analytes with respect to their false discovery rate (FDR)adjusted ANOVA P values and successively excluding the analytes with the highest adjusted P values. By selecting
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Table 2. Protein Analytes That Distinguish HAV, HBV, and HCV Patients Study 1 Analyte
PARC HB-EGF Thrombomodulin a1-AT Complement 3 IgA IgM MCP-4 BDNF Apo H vWF Prolactin C-reactive protein AXL VEGF Apo B TGF-a Osteopontin THP Clusterin MIP-1a CD5L M-CSF HGF TNF RII Apo D Apo A-I ICAM-1 CD40 ligand IL-18 PPP Lipoprotein (a) TIMP-1 IL-6
P Value
Study 2 Q Value
24
7.55 3 104.03 3 10220 1.15 3 10213 1.74 3 10213 1.75 3 10213 5.14 3 10211 8.17 3 10211 1.28 3 10210 2.45 3 1029 1.71 3 1027 1.76 3 1027 5.8 3 1027 2.31 3 1028 2.35 3 1026 2.69 3 1026 2.72 3 1026 6.8 3 1026 1.06 3 1025 1.54 3 1025 1.61 3 1025 1.86 3 1025 2.46 3 1025 2.46 3 1025 3.9 3 1025 4.5 3 1025 5.7 3 1025 7.17 3 1025 7.8 3 1025 7.99 3 1025 9.13 3 1025 1.2 3 1024 4.5 3 1024 7.1 3 1024 1.3 3 1023
Group 221
1.05 3 10 2.8 3 10218 4.88 3 10212 4.88 3 10212 4.88 3 10212 1.19 3 1029 1.62 3 1029 2.23 3 1029 3.92 3 1028 2.23 3 1027 2.23 3 1026 6.72 3 1026 2.34 3 1027 2.34 3 1025 2.36 3 1025 2.36 3 1025 5.56 3 1025 8.18 3 1025 1.12 3 1024 1.12 3 1024 1.22 3 1024 1.49 3 1024 1.49 3 1024 2.2 3 1024 2.5 3 1024 2.7 3 1024 3.6 3 1024 3.8 3 1024 3.8 3 1024 4.2 3 1024 5.6 3 1024 1.9 3 1023 3.0 3 1023 5.4 3 1023
C C C C C C C C C C C C C B C C C C C C C B C C C C C C C C B C C C
Analyte
IgM Apo B M-CSF CD5L Complement 3 a1-AT Apo D PPP Apo H AXL BDNF Osteopontin THP vWF VEGF HGF TIMP-1 Apo AI Lipoprotein (a) Clusterin MCP-4 TNF RII Thrombomodulin Prolactin PARC MIP-1a ICAM-1 CD40 ligand IgA IL-18 C-reactive protein IL-6 HB-EGF TGF-a
P Value
Q Value 213
1.28 3 10 7.57 3 1028 1.83 3 1027 1.19 3 1025 3.2 3 1024 4.6 3 1023 5.05 3 1023 8.93 3 1023 9.6 3 1023 1.1 3 1022 1.46 3 1022 1.66 3 1022 2.57 3 1022 3.03 3 1022 4.2 3 1022 4.5 3 1022 5.0 3 1022 5.4 3 1022 7.7 3 1022 7.9 3 1022 9.1 3 1022 1.1 3 1021 1.6 3 1021 1.6 3 1021 1.9 3 1021 2.8 3 1021 3.8 3 1021 5.4 3 1021 5.6 3 1021 7.0 3 1021 7.5 3 1021 9.8 3 1021 — —
Group 212
1.45 3 10 6.44 3 1027 1.24 3 1026 6.75 3 1025 1.5 3 1023 1.9 3 1022 1.9 3 1022 2.9 3 1022 2.9 3 1022 3.3 3 1022 3.8 3 1022 4.03 3 1022 5.8 3 1022 6.45 3 1022 8.45 3 1022 8.5 3 1022 9.2 3 1022 9.2 3 1022 1.2 3 1021 1.2 3 1021 1.3 3 1021 1.6 3 1021 2.1 3 1021 2.1 3 1021 2.4 3 1021 3.4 3 1021 4.4 3 1021 6.1 3 1021 6.2 3 1021 7.4 3 1021 7.7 3 1021 9.8 3 1021 — —
C B C B C C C A C B C C C B — A C — — — — — — — — — — — — — — — — —
The 34 most differential analytes are shown, indicating the P and Q values (ANOVA). Analytes were quantified using MAP and are listed in the order of statistical significance, as determined from the analysis of data from the patients recruited as part of study 1. These same analytes were then examined in an independent cohort (study 2). To identify the patient group(s) associated with the protein analyte, Dunn’s post-test was performed. Abbreviations: HB-EGF, heparin-binding epidermal growth factor (EGF)-like growth factor; vWF, von Willebrand factor; AXL, AXL receptor tyrosine kinase; VEGF, vascular endothelial growth factor; THP, Tamm-Horsfall protein; HGF, hepatocyte growth factor; PPP, protein serine/threonine phosphatases; TIMP-1, tissue inhibitor metallopeptidase inhibitor 1.
the variable subset with the highest information content (i.e., with the highest projection score), we objectively established an optimally adjusted P value threshold to use as inclusion criterion for defined protein signatures.18 Kruskal-Wallis’ and Mann-Whitney’s unpaired tests and Spearman’s correlation calculations were performed using OmniViz (BioWisdom Ltd., Cambridge, UK) or Prism (GraphPad Software Inc., San Diego, CA). Data are reported as standard P values and FDR-adjusted P values (called Q values) to control for multiple testing.19
Results A Common Hepatic Viral Signature. To examine the signature of the host response to HAV, HBV, and
HCV infection, we performed Luminex xMAP on sera of patients, isolated at the time of acute, symptomatic infection. To clean the data set, we removed 43 analytes that had a median value across all samples (study 1) that was below the lowest detectable dose (LDD). For the remaining 139 analytes (Supporting Table 3), individual patients that had a value below the LDD were assigned a value half that of the lowest value detected in the data set. To identify a common hepatic viral signature, we compared HAV-, HBV-, and HCVinfected patients with healthy controls using two complementary strategies. First, we performed one-way ANOVA, contrasting healthy donors and the combined set of infected patients. This approach revealed 46 analytes that significantly distinguished patients
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Table 3. Protein Analytes That Distinguish HAV and HBV Patients Study 1 Analyte
IP-10 EGFR Betacellulin AXL PPP CD5L MIP-1b SAP IgM Tenascin C MIG SOD1 TNF RII MIF ANG-2 MIP-3a Haptoglobin IL-1b TBG TTR Ferritin ACE PLGF M-CSF Apo A-II b2 microglobulin Cancer antigen 19-9 Eotaxin-1 E-selectin Apo E VCAM-1 EGF Cystatin C IL-18
P Value 24
4.3 3 10 6.5 3 1024 5.13 3 1023 7.5 3 1023 1.14 3 1022 1.19 3 1022 1.51 3 1022 2.47 3 1022 3.26 3 1022 3.45 3 1022 3.71 3 1022 3.72 3 1022 4.57 3 1022 4.68 3 1022 5.5 3 1022 5.5 3 1022 6.2 3 1022 7.2 3 1022 7.8 3 1022 8.6 3 1022 8.7 3 1022 9.6 3 1022 1.0 3 1021 1.0 3 1021 1.1 3 1021 1.1 3 1021 1.1 3 1021 1.2 3 1021 1.2 3 1021 1.2 3 1021 1.2 3 1021 1.3 3 1021 1.3 3 1021 1.4 3 1021
Study 2
