Staging of biliary atresia at diagnosis by molecular profiling of the liver
© Moyer et al.; licensee BioMed Central Ltd. 2010
Received: 19 January 2010
Accepted: 13 May 2010
Published: 13 May 2010
Young age at portoenterostomy has been linked to improved outcome in biliary atresia, but pre-existing biological factors may influence the rate of disease progression. In this study, we aimed to determine whether molecular profiling of the liver identifies stages of disease at diagnosis.
We examined liver biopsies from 47 infants with biliary atresia enrolled in a prospective observational study. Biopsies were scored for inflammation and fibrosis, used for gene expression profiles, and tested for association with indicators of disease severity, response to surgery, and survival at 2 years.
Fourteen of 47 livers displayed predominant histological features of inflammation (N = 9) or fibrosis (N = 5), with the remainder showing similar levels of both simultaneously. By differential profiling of gene expression, the 14 livers had a unique molecular signature containing 150 gene probes. Applying prediction analysis models, the probes classified 29 of the remaining 33 livers into inflammation or fibrosis. Molecular classification into the two groups was validated by the findings of increased hepatic population of lymphocyte subsets or tissue accumulation of matrix substrates. The groups had no association with traditional markers of liver injury or function, response to surgery, or complications of cirrhosis. However, infants with an inflammation signature were younger, while those with a fibrosis signature had decreased transplant-free survival.
Molecular profiling at diagnosis of biliary atresia uncovers a signature of inflammation or fibrosis in most livers. This signature may relate to staging of disease at diagnosis and has implications to clinical outcomes.
Biliary atresia results from a severe cholangiopathy that obstructs extrahepatic bile ducts, disrupts bile flow, and progresses to end-stage cirrhosis in most patients. Without knowledge of etiology and pathogenic mechanisms of disease, all patients are subjected to the same surgical and medical treatments despite the coexistence of different clinical forms. Thus, new strategies to phenotype the liver disease at diagnosis will aid the design of new clinical protocols that take into account the patient's biological makeup and facilitate studies of pathogenesis of disease. Among several proposed pathogenic mechanisms of disease [1, 2], there is increasing evidence for an inflammatory response in promoting bile duct injury. For example, analysis of affected livers uncovered a prominent expression of proinflammatory genes and evidence of oligoclonal expansion of T lymphocytes at diagnosis [3–5]. The biological relevance of these findings was supported by mechanistic experiments demonstrating the roles of CD8+ lymphocytes or interferon-gamma in bile duct injury in a mouse model of biliary atresia [6–8]. In this mouse model, infection of newborn mice within the first 2 days of birth results in an inflammatory obstruction of extrahepatic bile ducts within 1 week and atresia by 12 to 14 days [9, 10]. However, the extent to which individual cell types and molecular circuits relate to disease presentation and clinical course in humans is not well established.
Potential factors affecting the clinical course of children with biliary atresia include the center experience, age at portoenterostomy, and coexistence of embryonic malformations [11–17]. These factors notwithstanding, the progression of liver disease in most patients is the rule even after the surgical removal of atretic bile ducts and restoration of bile drainage, suggesting that biological factors operative at the time of portoenterostomy might influence the outcome of liver disease. Using histological approaches, previous studies linked the presence of inflammation  and fibrosis [19–21] with poor clinical outcome. Here, we aimed to determine whether molecular profiling of the liver identifies stages of disease at diagnosis. Analysis of liver biopsies uncovered a gene expression signature of inflammation or fibrosis that was associated with age at diagnosis and with differences in transplant-free survival.
Study population, covariates and outcomes
Tissue and clinical data were obtained from subjects enrolled into a prospective study of patients with biliary atresia evaluated at Cincinnati Children's Hospital Medical Center or into a multi-center prospective observational study carried out by the Biliary Atresia Research Consortium, with informed consent obtained from all infants' legal guardians. The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki and was approved by the human research committees of all participating institutions. Subjects were enrolled if diagnosed with biliary atresia and treated with portoenterostomy before 6 months of age. The diagnosis was defined by an abnormal intraoperative cholangiogram and histological demonstration of obstruction of extrahepatic bile ducts. Clinical and laboratory data were obtained at surgery and at 3- to 6-month intervals for the first 2 years of life (Additional file 1).
Microarray and quantitative PCR
Genome-wide liver expression datasets were generated for individual subjects using pools of biotinylated cRNAs synthesized from 400 ng of total RNA isolated from 10 to 20 mg of frozen liver samples. cRNA pools were hybridized to oligonucleotide-based human HG-U133 Plus 2.0 Array (Affymetrix, Santa Clara, CA, USA) containing 54,681 probe sets, scanned, and monitored for specific signals with GeneChip® Operating Software as described previously [3, 22, 23]. Affymetrix CEL files were imported into GeneSpring v7.3 (Agilent Technologies, Santa Clara, CA, USA) and subjected to Robust Multichip Average normalization. Detailed information on handling of liver biopsy samples, protocols for RNA labeling, chip hybridization and signals, internal controls, normalization procedures, and analysis of gene expression were deposited in Gene Expression Omnibus [GEO:GSE15235]. Quantitative PCR was done in a real-time Mx3000P thermocycler employing specific primers (Additional file 2) and established protocols [3, 22, 23].
Using the GeneSpring platform, we performed standard 'per-gene' median normalization for the entire gene expression dataset. Using 14 samples that were grouped as either inflammation or fibrosis based on the differences in histological scores being ≥2, the levels of expression for individual probes were filtered based on fold change >2 between the two groups. This yielded 304 probesets, which were then subjected to a Welch's t-test, with a significance cutoff of 0.05 and Benjamini and Hochberg false discovery rate (FDR) multiple testing correction (5% FDR), generating a list of 150 probesets.
To evaluate the predictive ability of the 150-probeset signatures to identify inflammation or fibrosis, we applied the supervised method of prediction analysis of microarrays (PAM) [24–26]. In this approach, all genes are reassessed according to their ability to separate individual types; those genes that are less useful in discriminating between these types are eliminated. Classification accuracy was assessed by a method of ten-times ten-fold cross-validation using the R-Project and Bioconductor package MCRestimate [24–26]. Briefly, the training set is subdivided into ten equal parts. Nine parts are used for training, then employed to make class predictions on the tenth part, which is used as the test set. After each portion has been used as the test set once, the division into 10 parts is done again and the 10-fold cross-validation is repeated 10 times for a total of 100 runs (that is, class predictions are made on each sample exactly 10 times). We applied this approach to the remaining 33 unclassified samples and assigned them into groups of inflammation or fibrosis. The accuracy of this classification method was determined by finding a percent of samples correctly classified in at least six out of ten predictions made on the same sample as described previously [24–26].
Functional analysis of genes
The genes highly expressed in the groups of inflammation or fibrosis were analyzed separately for functional themes using the Ingenuity Pathway Analysis 7.1 (Ingenuity Systems, Inc., Redwood City, CA, USA), using a right-tailed Fisher's exact test (with Benjamini-Hochberg/FDR correction) to evaluate for over-representation and displaying as -log(P-value); -log values exceeding 1.30 were significant (P < 0.05). Gene groups were also evaluated for biological relationship by searching for shared transcription factor binding sites (TFBSs) within 1 kb upstream of the transcription start sites of individual genes using Genomatix Gems Launcher , with a level of significance that includes FDR correction.
Statistical testing of molecular signatures with clinical data
Testing for association between molecular signatures or histological groups with categorical variables (clinical form, cholangitis, ascites, transplant/death by 2 years of age) used Fisher's exact test. For quantitative dependent variables (age at diagnosis, level of bilirubin or alanine aminotransferase, weight Z score), means or medians were tested using Kruskal-Wallis one-way ANOVA on Ranks or two-sample Wilcoxon rank sum test (with continuity correction for age) when appropriate (two-sided P-values). The relationship of molecular signature or histological groups and age was assessed by the Gaussian Kernel method, while the relationship to outcome was examined by censored Kaplan-Meier. The R-package was used for all statistical analysis .
A total of 47 subjects were included in the study based on the availability of clinical data and tissue for analysis. Liver biopsies for individual subjects were examined for inflammation and the extent of fibrosis at diagnosis. For inflammation, we focused on the population of inflammatory cells within the portal space because it contains the primary site of biliary pathology and to avoid variables related to extra-medullary hematopoiesis that is commonly present in the hepatic lobule. We found that 34 of 47 (72.3%) of the biopsies had scores ≥1 for both inflammation and fibrosis (Additional file 3). Thus, we calculated the differences in scores within individual samples and identified biopsies displaying predominant features of either inflammation or fibrosis based on a differential score ≥2. Fourteen of 47 (30%) samples fell into this category, of which 9 had prominent inflammation and 5 had advanced fibrosis, while the remaining 70% had mixed histological features (differential scores <2). Next, we examined whether these 14 samples could be differentiated at the molecular level, and whether the signatures could identify other liver biopsies displaying molecular profiles for inflammation or fibrosis even when they were not evident by histology.
Grouping by molecular signature
Testing of biological plausibility
Testing for clinical relevance
Relationship between clinical and biochemical characteristics and molecular groups of inflammation and fibrosis in infants with biliary atresia
Inflammation group, N = 15
Fibrosis group, N = 26
Total, N = 41a
Sex, N (%)
Race, N (%)
Ethnicity, N (%)
Age in days, median (25-75%)
BASM N (%)
Perinatal N (%)
Mean CB at diagnosisc
4.9 ± 2.1
5.8 ± 2.4
5.5 ± 2.3
Mean ALT at diagnosisc
125 ± 83
154 ± 74
144 ± 78
Mean CB at 3 months after HPEc
1.7 ± 2.6
3.5 ± 5.3
2.8 ± 4.5
Weight Z-score at 6 months after HPEc
-1.3 ± 1.1
-1.7 ± 1.2
-1.5 ± 1.2
Presence of cholangitis, N (%)
Presence of ascites, N (%)
Relationship between clinical and biochemical characteristics and histological groups in infants with biliary atresia
Inflammatory subtype, N = 14
Fibrosing subtype, N = 17
Total, N = 31a
Sex, N (%)
Race, N (%)
Ethnicity, N (%)
Age in days, median (25-75%)
BASM N (%)
Perinatal N (%)
Mean CB at diagnosisc
5.1 ± 1.6
5.8 ± 2.5
5.6 ± 2.2
Mean ALT at diagnosisc
196 ± 150
192 ± 120
194 ± 136
Mean CB at 3 months after HPEc
2.3 ± 3.7
3.0 ± 3.5
2.6 ± 3.6
Weight Z-score at 6 months after HPEc
-1.1 ± 0.9
-1.8 ± 1.9
-1.4 ± 1.4
Presence of cholangitis, N (%)
Presence of ascites, N (%)
We found that most livers of infants with biliary atresia display some elements of inflammation and fibrosis at diagnosis, with a subset (30% of the biopsies) containing more predominant histological features of either inflammation or fibrosis based on a greater differential score for the phenotypes. Using a gene expression signature highly specific for this subset of livers, we were able to group 91% of the biopsies into molecular inflammation or fibrosis and found significant association with age at portoenterostomy and transplant-free survival. These findings suggest that molecular profiling at diagnosis may stage the liver disease by the identification of biological pathways that may not be easily distinguishable by standard histological approaches to quantify inflammation or fibrosis. This may be due to intrinsic limitations of morphological methods (that is, hematoxylin/eosin or trichrome staining) or to a sampling artifact caused by a non-uniform tissue injury that varies between anatomical lobes and, perhaps more importantly, among neighboring lobules and portal tracts. Both obstacles may be overcome by the molecular profiling described herein. First, it uses RNA isolated from a fragment of tissue that, although small, contains a much larger representation of lobules/portal tracts than individual histological sections. Second, it is based on a molecular signature that contains the collective expression behavior of gene groups, without a priori bias related to their biological affiliations.
In experiments to validate the grouping of liver biopsies based on molecular signatures, we found that some gene groups are functionally related to the population of portal tracts by inflammatory cells and to molecular circuits previously implicated in pathogenesis of disease. For example, livers with a molecular signature of inflammation had an increase in the number of T and NK lymphocytes, overexpressed genes related to the immune system, and contained a cluster of genes with NFκB transcription sites. The activation of NFκB was also reported in this mouse model [29, 30], but the enrichment of bindings sites for NFAT and other transcription factors in the list of genes that are differentially expressed suggests that molecular networks regulated by these factors may be important for the pathogenesis of disease. Despite the activation of these molecular pathways within the inflammation signature, we recognize that there might be distinctions between wedge and core liver biopsies. We were unable to make a direct comparison between these two types of biopsies due to the unavailability of tissues. Further, the isolation of RNA from a liver biopsy fragment may limit the potential implication of the findings with regards to disease pathogenesis because the biopsy includes several cell types and different regions of the liver lobule. This type of study will benefit from the use of laser-capture microdissection, which enables the analysis of specific cell types or anatomical regions (that is, portal tract versus lobule).
Gene expression profiling increases the number of available methods to quantify prominent biological processes in biliary atresia. A previous study used histological staining methods and reported that a high degree of syncytial giant cells, focal and bridging necrosis, and inflammation were associated with poor clinical outcome [18, 19]. These findings differ from the improved outcome of our subjects assigned to the inflammation group, but we recognize that our findings will require validation in a larger population. Other studies have investigated the association of hepatic fibrosis and clinical course after portoenterostomy, with poor outcome reported for children with advanced fibrosis, either quantified by standard methods or aided by computerized morphometry [18–21]. This association was reproduced in our study in the children assigned to the group of molecular fibrosis.
The temporal differences in age at diagnosis for the molecular groups raise the possibility that the gene expression signatures reflect two distinct but inter-related stages of disease. The first stage, represented by younger patients with an inflammatory signature (most often but not exclusively at younger age), is placed biologically earlier in pathogenesis of disease, while the other patients may have transitioned to a more advanced stage of fibrosis. Such a continuum in the pathogenesis of disease has been demonstrated in the rotavirus-induced mouse model of biliary atresia [7, 8, 34], which begins with prominent inflammation of the liver and extrahepatic bile ducts and progresses to less inflammation and persistent duct obstruction; however, in humans, the stages appear not to obey a strict temporal organization. The presence of fibrosis in a subset of younger infants suggests that age alone cannot stage the disease. In these patients, the liver injury may have started at an earlier age, or it may have undergone rapid progression to fibrosis. The possibility of a rapid progression to fibrosis is supported by a previous report showing greater fibrogenesis in the livers of neonatal rats when compared to adults in a model of cholestasis induced by bile duct ligation .
Molecular profiling of liver biopsies at the time of diagnosis has been shown to differentiate the embryonic and perinatal forms of biliary atresia and identified genes with potential roles in pathogenesis of the embryonic form of disease . For example, among the genes with unique expression patterns were five imprinted genes (Igf2, Peg3, Peg10, Meg3, and IPW) in infants with the embryonic form, suggesting that a failure to down-regulate embryonic gene programs may be involved in the non-hepatic malformations that are typical of this group of patients . In a separate study, molecular profiling also revealed the activation of an interferon-gamma-rich proinflammatory circuit . The biological relationship between this circuit and biliary injury was demonstrated in mechanistic studies showing that the in vivo depletion of interferon-gamma in mice prevented the obstruction of extrahepatic bile ducts . Despite the informative data produced by these two studies, we recognize that the approach described here to stage the disease using molecular profiles needs future studies to evaluate its relevance in clinical practice and in potential therapies. This can be pursued by prospective validation in a new group of patients adequately powered for statistical analysis to look at clinical correlates and at responses to clinical intervention. For example, will the 150-probe set be reproduced if the same statistical method is applied to new livers with histological scores ≥2 for inflammation or fibrosis? Will infants with an inflammation signature do better if treated with anti-inflammatory drugs (for example, corticosteroids)? Formal answers to these questions will ultimately reveal the clinical impact of staging of liver disease and open opportunities for new trials that take into account the patient's biological makeup.
Gene expression profiling of the liver at the time of diagnosis of biliary atresia identifies prominent signatures of inflammation or fibrosis in most patients. These signatures cannot be foreseen by traditional histological methods or by serum markers of liver injury or function. The segregation of inflammation with younger age at diagnosis and of fibrosis with decreased survival is in keeping with the ability of molecular profiling to stage the liver disease at diagnosis.
false discovery rate
nuclear factor of activated T-cells
prediction analysis of microarray
transcription factor binding site.
This work was funded by the following grants from the National Institutes of Health: DK083781 and DK062497 (to JAB) and DK078392 (Gene Expression and Sequencing Core and Bioinformatics Core, Digestive Disease Research Core Center in Cincinnati). We thank Dr William Balistreri for insightful review of the manuscript. We also thank the Witzigreuter Family for support of liver research, the Data Coordinating Center of the NIDDK-funded Biliary Atresia Research Consortium (BARC) and the Principal Investigators and Clinical Research Coordinators of individual BARC Centers for patient recruitment and acquisition of tissue and data. The contents of the article do not necessarily reflect the opinions or views of the NIDDK, BARC, or BARC investigators.
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