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Am J Physiol Gastrointest Liver Physiol 292: G298-G304, 2007. First published September 7, 2006; doi:10.1152/ajpgi.00321.2006 Free Article
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INFLAMMATION/IMMUNITY/MEDIATORS

Clinical phenotype and gene expression profile in Crohn's disease

Claudio Csillag,1 Ole Haagen Nielsen,1 Rehannah Borup,2 Finn Cilius Nielsen,2 and Jørgen Olsen3

1Department of Gastroenterology C, Herlev Hospital; 2Department of Clinical Biochemistry, Core Unit for Microarray Analyses, Rigshospitalet; and 3Department of Medical Biochemistry and Genetics, University of Copenhagen, Copenhagen, Denmark

Submitted 19 July 2006 ; accepted in final form 1 September 2006


   ABSTRACT
TOP
 ABSTRACT
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
The clinical course varies significantly among patients with Crohn's disease (CD). This study investigated whether gene expression profiles generated by DNA microarray technology might predict disease progression. Biopsies from the descending colon were obtained colonoscopically from 40 CD patients. Gene profiling analyses were performed using a Human Genome U133 Plus 2.0 GeneChip Array, and summarization into a single expression measure for each probe set was performed using the robust multiple array procedure. Principal component analysis demonstrated that three components explain two-thirds of the total variation. The most important parameters for the determination of the colonic gene expression patterns were the presence of disease (CD) and presence of inflammation. Superimposition of clinical phenotype data revealed a grouping of the samples from patients with stenosis toward negative values on the axis of the second principal component. The functional annotation analysis suggested that the expression of genes involved in intracellular transport and cytoskeletal organization might influence the development of stenosis. In conclusion, even though most variation in the colonic gene expression patterns is due to presence or absence of CD and inflammation status, the development of stenosis is a parameter that affects colonic gene expression to some extent.

clinical presentation; inflammatory bowel disease; microarray

CROHN'S DISEASE (CD), a chronic inflammatory bowel disease (IBD), could represent a group of heterogeneous diseases. CD results from an abnormal immune response, which is believed to be due to the interaction between genetic susceptibility (20) and environmental triggers, herein bacterial factors from luminal microflora (10, 21, 29, 30, 37, 38, 40).

Several approaches have been made to define clinical subgroups (based on location, extent, behavior, and surgical history) (15, 35, 39). In addition, molecular and genetic classification proposals have been made (2, 4, 5). Markers from peripheral blood [anti-neutrophil cytoplasm antibodies (ANCA) and anti-Saccharomyces cerevisiae antibodies (ASCA)] (28) and genetic polymorphism, most notably, the caspase activation recruitment domain 15 (CARD15) gene at chromosome 16 (IBD1), have been intensively investigated (1, 13). The discovery and confirmation of the role of CARD15 variations related to the risk of developing CD and in disease behavior resulted in an increased emphasis on genetic studies (9, 25, 26). One copy of the risk alleles in these polymorphic regions is involved in a 2.4-fold increased risk for CD, and two copies of the risk alleles increases the risk 17-fold (3, 34, 42a). CARD15 mutations have also been implicated with ileal involvement (2, 9, 19, 41), fibrostenosis (1), and early onset of the disease (25). Besides IBD1, several other loci have been shown to be involved in the pathogenesis of CD (16).

It is our hypothesis that factors that determine the clinical phenotypes of CD also affect the gene expression pattern in the colonic mucosa represented by biopsies from the sigmoid colon. Such an association might be used to predict the clinical course based on the gene expression pattern.

DNA array (microarrays, GeneChips) technology allows a wide survey of gene expression. It is based on standard hybridization techniques, though scaled up to promote simultaneous hybridization of thousands of genes or expressed sequence tags (ESTs) fixed on a single solid matrix with mRNA from single tissue sample. DNA arrays rely on known nucleotide sequences (i.e., probes) fixed on a matrix that complementary binds to unknown nucleotide sequences (i.e., targets) expressed on sample tissues. Since microarrays facilitate the measurement of RNA levels for the complete set of transcripts of an organism, microarray experiments based on specimens from the intestinal mucosa might give us new insight into the patterns of local cellular processes involved in CD.

Since it is believed that there are several loci involved in the pathogenesis of CD, the hypothesized association between the clinical phenotype and the gene expression in the colonic mucosa of CD patients is likely to be represented by a combinatorial expression pattern of different genes. Such relationships are best uncovered using multivariate statistical procedures. Principal component analysis (PCA) and partial least-squares regression (17, 24, 42) are well-known multivariate techniques suitable for uncovering patterns in a wide variety of data.

PCA is a method that projects the image of a multidimensional object into fewer dimensions (42). PCA is therefore much like taking a two-dimensional picture of a three-dimensional object. If the picture is taken at the right angle (i.e., projection), then the features of the three-dimensional object can easily be recognized on the picture. In our case, our objects are patient samples represented in a multidimensional space where each gene measured is a dimension. PCA projects this multidimensional gene expression pattern into a space with fewer dimensions, which are referred to as the principal components.

In the human colon, physiological variations account for >1,000 differentially expressed genes (12, 18). It is therefore necessary to choose one intestinal segment to avoid intersegmental variations in gene expression. In this study, the descending colon was chosen because biopsies can be obtained both by colonoscopy and sigmoideoscopy and because it allows future comparisons with the samples from the same segment from patients with ulcerative colitis. In addition, the prevalence of colonic disease among Danish CD patients is relatively high (30% colonic only and 33% ileocolonic) (27).

The aim of this study was to investigate the hypothesis that microarray gene expression profiles from biopsies from the descending colon might correlate to categories of patients classified according to four clinical criteria, namely, the age of onset, presence of extraintestinal manifestations, fistulizing disease, and stenotic disease. We chose to approach this problem using PCA and functional annotation analysis using gene ontology terms.


   MATERIALS AND METHODS
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 ABSTRACT
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Patients. Forty CD patients (median age: 32 yr, range 18–60 yr; 16 male and 24 female patients) were enrolled prospectively (Table 1). Twenty-seven biopsies were taken from areas without inflammation, and thirteen biopsies were taken from inflamed areas.


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  		Table 1. Patient and sample data

 
All biopsies were taken from the descending colon. Specimens from healthy controls were also obtained and were solely used with the purpose of normalization of absolute values of mRNA expression

Patients were subject to sigmoidoscopy or colonoscopy either for histological confirmation of CD or for routine control of their disease, diagnosed according to well-established criteria (32).

Treatments at the day of examination and lengths of treatment are shown together with patients' demographic data in Table 1. Therapeutic regimes included mesalazine (1.6–3.2 g/day); budesonide (9 mg/day); azathioprine/6-mercaptopurine (referred as azathioprine, 150–200 mg/day); either glucocorticoids alone (30–40 mg/day) or in combination with azathioprine (dosage as mentioned above); a combination of drugs that included infliximab (5 mg/kg of body wt); or a combination of drugs that included weekly methotrexate (15 mg/wk). Fourteen CD patients did not receive medication for IBD.

Disease location was defined according to well-established criteria (15).

Exclusion criteria were an age over 75 yr or below 18 yr, clinical or laboratorial evidence of an active infectious condition, pregnancy, and severe mental illness.

Several studies have correlated early onset, ileal involvement, stricturing disease, and higher frequency of surgery to CARD15 mutations (2, 6, 25, 33). In this work, the age of 25 yr or younger was chosen as a criterion to designate early onset. Age of onset was defined as the age of onset of symptoms that eventually led to diagnosis.

Information about fistulizing and stenotic disease was obtained both by a questionnaire, which was applied by an interviewer prior to sigmoidoscopy or colonoscopy and retrospectively from their medical records. These data were discarded if the information given by the patient and that obtained from medical records were discordant. Likewise, if the patient was newly diagnosed (<4 mo), it was not attempted to classify the disease as fistulizing or stenotic, unless clinical data (e.g., radiological exams) suggested the presence of these manifestations.

In our sample, 5 patients had fistulizing disease, 31 did not, and 4 could not be classified according to this criterion due to a short (<4 mo) observation period; 8 patients had stenotic disease, 24 did not, and 8 could not be classified.

Data about extraintestinal manifestations were obtained both by a questionnaire and from medical records. Twenty-two patients did not have extraintestinal manifestations, fourteen had manifestations in the joints, two had ocular manifestations, and two had primary sclerosing cholangitis.

Tissue samples. Specimens from the descending colon were obtained from all included persons. Specimens obtained at colonoscopy or sigmoidoscopy (~10–20 mg each) were immediately stabilized in RNA-later (Ambion, Austin, TX). Each glass contained two specimens sampled from the same area with no more than 2 cm between them. Additional biopsies from the same colonic areas were obtained for histopathological evaluation after samples had been fixed in formalin and embedded in paraffin. The histopathological evaluation was conducted in an unblinded fashion by staff pathologists, according to well-established criteria (11), and focused on confirming the diagnosis and assessing the degree of inflammation. Only biopsies taken from areas with both macroscopic and histological signs of inflammation were categorized as "inflamed;" in the same manner, only those considered without macroscopic and microscopic signs of inflammation were categorized as "noninflamed." Biopsies obtained from areas with conflicting assessment of inflammation were not used in the microarray analyses.

Sample preparation, hybridization, and detection and quantification of signals. After 48 h storage at 4°C, the remaining intestinal specimens were kept at –20°C until total RNA isolation was initiated. RNA was extracted with TRIzol (Invitrogen, Carlsbad, CA) and chloroform and precipitated with isopropanol (7). Further purification was obtained with a RNeasy Mini Kit (Qiagen, Valencia, CA). The integrity and purity were verified with an Agilent Bioanalyzer (Palo Alto, CA). Double-stranded cDNA was synthesized from total RNA. An in vitro transcription reaction was then performed to produce biotin-labeled cRNA from the cDNA. The cRNA was fragmented and a hybridization cocktail was prepared, which included the fragmented target, probe array controls, BSA, and herring sperm DNA.

In this experiment, Affymetrix GeneChip Human Genome U133 Plus 2.0 (Santa Clara, CA) was applied. The hybridized probe array was subsequently stained and scanned by a GeneArray Scanner at an excitation wavelength of 488 nm with detection of the amount of light emitted at 570 nm, which is proportional to the bound target at each location on the probe array. Data were stored as image files for further analysis.

The complete data set of this study has been submitted to the European Bioinformatics Institute ArrayExpress repository (Accession No. E-TABM-118) (13a).

Data analysis based on multivariate modeling. Summarization of probe level data into a single expression measure for each probe set on the Affymetrix HGU133A 2.0 plus GeneChip was performed using the robust multiple array procedure (24) using the Affymetrix library for the R statistical language. Probe sets where the lower quartile of the expression measures fell below a log2 value of 5 were removed. The filtered data set consisted of 14.378 probe sets. The data were analyzed using the Simca-P 11 program (Umetrics) for multivariate modeling. A PCA was conducted. Eight principal components were necessary to obtain the best representation of the original data.

To functionally interpret the PCA, the 250 probe sets with the highest positive or highest negative loading values were extracted for the first four principal components. The two lists with positive or negative loading values, respectively, for each principal component were loaded into the program GoSurfer to conduct a functional annotation analysis (43). Biological processes represented by at least 10 genes in the gene lists and that were significantly (P < 0.01) overrepresented in one of the gene lists (with positive or negative loading values, respectively) were reported.

Ethics. The project was approved by the Scientific Ethics Committee of the Copenhagen County. Patient participation in the project was made on a voluntary basis after oral and written information and consent according to the Helsinki V Declaration (42a).


   RESULTS
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 GRANTS
 REFERENCES
 
Multivariate modeling of colonic gene expression data. PCA carried out on the gene expression data revealed that the first eight components explained 64% of the variation. Adding additional components did not improve the model markedly. Two-thirds of the variation explained by the model resulted from the first three components.

A two-dimensional score plot using these first three components as axes demonstrated a different distribution of the samples (Fig. 1). As expected, samples with inflammation deviated the most and were scattered mainly in the negative direction on the axis for the first principal component and in the positive direction on the axis for the third principal component (Fig. 1A). In contrast, samples from control subjects were scattered mainly toward negative values on the axes of both the second and third components (Fig. 1, A and B).


Figure 1
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  		Fig. 1. Two-dimensional score plot from the principal component analysis (PCA). The gene expression data from the HGU133A plus 2.0 GeneChip were analyzed by PCA. Eight principal components were extracted, and the samples were plotted in two-dimensional score plots using either the first and third principal components (A) or the first and second principal component axes (B). The thick arrows indicate the positioning of the indicated samples relative to the axes. Samples from the inflamed mucosa from Crohn's disease (CD) patients are positioned toward negative values on the axis of the first principal component and toward positive values on the axis for the third principal component. The thin arrows indicate the positive direction of the principal component axes. Gene ontology terms for biological processes, which are overrepresented in the functional annotation of the genes defining the positive or negative directions of each axis, are written along the thin arrows and positioned in a way that indicates whether the terms are overrepresented in genes defining the positive or negative direction of each axis.

 
Superimposing the clinical phenotype (age of onset, history of stenosis, localization of disease, history of fistula, and extra intestinal manifestations) revealed a grouping of the samples from patients with stenosis toward negative values on the axis of the second principal component (Fig. 2A). Moreover, this relationship was further enhanced by projecting the samples on the second and fourth principal component axes. This projection placed the CD samples from patients with a history of stenosis toward the top left quadrant of the plot (Fig. 2B).


Figure 2
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  		Fig. 2. Two-dimensional score plot from the PCA. The score plot used first and second principal component scores (A) or the second and fourth principal component scores (B) from the PCA model. The samples from CD patients with episodes of stenosis is mainly dispersed towards the left half in A and the top left quadrant in B. The thin arrows indicate the positive direction of the principal component axes. Gene ontology terms for biological processes, which are overrepresented in the functional annotation of the genes defining the positive or negative directions of each axis, are written along the thin arrows and positioned in a way that indicates whether the terms are overrepresented in genes defining the positive or negative direction of each axis.

 
Functional annotation analysis of principal components. The genes that contributed the most in generating the calculated principal components could be identified using the information about the calculated principal component loading values from the PCA procedure. For each principal component, the genes with the 250 highest or lowest loading values, respectively, were extracted. Positive loadings contributed to the axis in the positive direction and vice versa. For the first principal component axis (Fig. 1), the gene ontology term "generation of precursor metabolites and energy" was more frequently encountered among the genes defining positive values of the first principal component, whereas the gene ontology terms "response to stress," "DNA metabolism," and "immune response" were more frequently encountered among the genes defining negative values of the first principal component axis. For the second principal component axis (Fig. 1B), biological processes related to intracellular transport, protein localization, cellular localization, mRNA processing, and RNA metabolism were overrepresented among the genes defining the negative direction of the axis. For the third principal component (Fig. 1A), processes related to defense response, response to wounding, immune response, apoptosis, regulation of transcription, and regulation of metabolism were overrepresented among the genes defining positive values of the axis. The biological process "electron transport" was overrepresented among the genes defining the negative direction of the third principal component. Finally, terms related to protein transport, protein folding, microtubule-based processes, and ribosome biogenesis were overrepresented in the functional annotation of the genes defining the positive direction of the fourth principal component (Fig. 2A).


   DISCUSSION
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
GRANTS
 REFERENCES
 
Our findings suggest that the variation in colonic gene expression patterns is very complex and governed by many different factors. The fact that the first three components explain one-third of the total variance, however, suggests that some parameters might be discernible by superimposing information of clinical phenotype onto score plots of the first three principal components.

Our multivariate modeling of the gene expression data show that the most important parameters for the determination of the colonic gene expression patterns are the presence of disease (CD) and presence of inflammation.

It is important to note that no grouping of the noninflamed CD samples was found when information about disease localization was used to mark the samples. Differences in colonic gene expression patterns between the noninflamed mucosa from CD patients and control subjects were, however, detected (Fig. 1), which shows that CD affects the gene expression in the descending colon of patients that are known to have ileal disease only.

Negative values on the axis for the first principal component and positive values on the axis of the third principal component were both related to inflammation. Neither control samples nor noninflamed samples had the combination of positive scores on the third principal component axis and negative scores on the first principal component axis. Control samples were widely distributed along the first principal component axis; thus, some of these samples shared characteristics with inflamed samples.

Taking the functional annotation analysis into account, a reasonable interpretation is that the first principal component is related to variations in proliferation and unspecific stress response in the mucosa. Few control samples were distributed with high positive scores on the axis of the third principal component. Thus, this axis is likely to reflect the specific immune system activation seen in active inflammation; this conclusion is also supported by the findings that the genes involved in immune and defense responses defined the positive direction of the third principal component axis.

The second principal component did not seem to depend on the inflammation status of the sample. Noninflamed samples from CD patients were, to some degree, centered toward more positive values on the second principal component axis than samples from control subjects. This is compatible with previous results in which a different form of data analysis showed upregulation of two genes in noninflamed samples from CD patients compared with control subjects (8).

Interestingly, CD samples from patients with a history of stenosis seemed to be distributed toward negative values on the axis of the second principal component and positive values of the fourth principal component. Thus, these two components reflect variation that is seen in both CD and control samples and that appears to be related to a history of stenosis for CD patients. The functional annotation analysis suggests that the expression of genes involved in intracellular transport, cytoskeletal organization, protein folding, and ribosome biogenesis might be important for the development of stenosis. Our analysis shows that it is possible to focus on the individual parameters by projecting the gene expression data onto the right principal component axis. Projections that avoided the third PCA component removed most information related to the active inflammation and the projections onto the second and fourth principal component axes focused on the presence of stenotic disease.

The remaining phenotypic criteria (age of onset, ileal/colonic disease, extraintestinal manifestations, and fistulizing disease) did not result in a discernible grouping of patients. Several factors might explain this negative finding. Thus, it cannot be excluded that variations in intestinal microflora composition to some degree might have affected our results, since it has previously been shown that microflora have a clear influence on colonic mucosal gene expression (14, 31, 36).

Another possible explanation for this negative finding is the nature of the biopsy material, which contain several cell types, including leucocytes and fibroblasts, as documented by histological assessment (not shown). However, isolation and quantification of the different cell populations were not possible in the assay applied, and genetic variations in cellular subpopulations might thus have affected the results.

In conclusion, our results indicate that most variation in the colonic gene expression patterns is due to the following parameters: presence or absence of CD and presence or absence of inflammation. Stenosis development is a parameter that affects the colonic gene expression to a minor extent.


   GRANTS
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 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
REFERENCES
 
This study was supported by grants from the Danish Research Agency; the Augustinus Foundation; the Director Emil C. Hertz and spouse Inger Hertz Foundation, the Research Foundation of Greater Copenhagen, Faroe Islands, and Greenland; the Foundation of Graduate Engineer Frode V. Nyegaard and spouse; and the Foundation of Kathrine and Vigo Skovgaard.


   FOOTNOTES
 

Address for reprint requests and other correspondence: C. Csillag, Dept. of Gastroenterology C, Herlev Hospital, Univ. of Copenhagen, Herlev Ringvej, Herlev DK-2730, Denmark (e-mail: claudio{at}dadlnet.dk)

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


   REFERENCES
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 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
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 REFERENCES
 

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