- Email: [email protected]
How will insights from genetics translate to clinical practice in inflammatory bowel disease?
Accepted Manuscript How will insights from genetics translate to clinical practice in inflammatory bowel disease? E.A.M. Festen , Dr. R.K. Weersma , MD, PhD, Prof. Dr. PII:
S1521-6918(14)00046-8
DOI:
10.1016/j.bpg.2014.04.002
Reference:
YBEGA 1247
To appear in:
Best Practice & Research Clinical Gastroenterology
Received Date: 28 February 2014 Revised Date:
5 April 2014
Accepted Date: 13 April 2014
Please cite this article as: Festen EAM, Weersma RK, How will insights from genetics translate to clinical practice in inflammatory bowel disease?, Best Practice & Research Clinical Gastroenterology (2014), doi: 10.1016/j.bpg.2014.04.002. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
How will insights from genetics translate to clinical practice in inflammatory bowel disease?
1
University of Groningen, University Medical Centre Groningen, Department of Gastroenterology and Hepatology, the Netherlands
University of Groningen, University Medical Centre Groningen, Department of
SC
2
RI PT
Dr. E.A.M. Festen 1,2 , Prof. Dr. R.K. Weersma 1
Genetics, the Netherlands
M AN U
Correspondence to: R.K. Weersma MD, PhD, Department of Gastroenterology and Hepatology, University of Groningen and University Medical Centre Groningen, P.O. Box 30001, 9700 RB Groningen, the Netherlands. Email: [email protected]
Abstract
TE D
Tel: +31503610426 Fax: +31503619306
AC C
EP
Inflammatory bowel disease, consisting of Crohn’s disease and ulcerative colitis, is a chronic inflammatory disease of the gut, which arises through an excessive immune response to the normal gut flora in a genetically susceptible host. The disease affects predominantly young adults and due to its chronic and relapsing nature gives rise to a high disease burden both financially, physically and psychologically. Current therapy still cannot prevent the need for surgical intervention in more than half of IBD patients. Consequently, advances in IBD therapy are of high importance. Recently, several new forms of targeted therapy have been introduced, which should improve surgery-free prognosis of IBD patients. Recent identification of genetic risk variants for IBD has led to new insights into the biological mechanisms of the disease, which will, in the future, lead to new targeted therapy. In the meantime repositioning of drugs from biologically similar diseases towards IBD might lead to new IBD therapies. Keywords: Inflammatory bowel disease; Crohn's disease; Ulcerative colitis; Genetics; Personalised medicine; Pharmacogenetics; Thiopurines; Anti-TNF therapy; Drug repositioning
ACCEPTED MANUSCRIPT
Introduction Ever since the first human genome was sequenced in 2003 the clinical world has been waiting for translation of this genetic knowledge into therapies for disease or
RI PT
personalized care for individual patients[1][2]. This article is mainly focused on the implications of genetics for Inflammatory Bowel Disease (IBD), consisting of Crohn’s disease (CD) and ulcerative colitis (UC), both chronic inflammatory diseases of the
gastrointestinal tract. In the last few years the knowledge on the genetic background
SC
of IBD has been growing fast: 163 genetic risk loci have been identified for IBD,
making it the most successfully studied complex disease[3]. The promise genetics hold for clinical practice is three-fold (table 1): 1. better understanding of disease
M AN U
mechanisms allowing for the development of targeted therapies; 2. prediction of disease in the general population allowing for preventative measures; 3. adapting medical therapy to the genetic profile of the individual patient. The last two items together constitute the concept of ‘personalized medicine’. Personalized medicine will help us determine which patients will benefit from specific therapies and which
TE D
patients will not respond to therapy or even develop side effects. Since IBD are chronic disorders with an unpredictable disease course that need intensive and expensive treatment, and have potentially severe disease outcomes, the potential of personalized medicine is especially promising for this group of diseases. It is
EP
important for clinicians to identify those patients with a potentially severe disease course, since they might benefit from early intervention and a more aggressive treatment. Alternatively, patients with a favorable prognosis can be spared the side
AC C
effects of unnecessary treatment. This is an important issue since, in the treatment of IBD patients, the so-called “top-down” approach, in which biological therapies are administered early in the disease course, is increasingly being adopted[4]. This in contrast to the “step-up” approach, in which treatment is started with milder therapy and escalated if this therapy proves to be insufficient, which in patients with severe disease can lead to months of insufficient therapy. However, at the moment, the “top-down” approach may well lead to the over-zealous treatment of many patients, whereas a better selection of patients, based on genetic biomarkers, could
ACCEPTED MANUSCRIPT
very well prevent this. From the clinical perspective, genetics have not yet had much additional value to current therapy of IBD. However several steps have already been made: i) genetic knowledge can already contribute to new targeted therapies for IBD: ii) research is being done into whether genetic risk models can predict IBD in
RI PT
the general population and iii) genetic predictors for disease course and
therapeutic response are being investigated. We will review the current knowledge on these aspects of genetics in relation to the clinical care of IBD patients.
SC
1. Translating knowledge on genetic background of a disease to therapy
M AN U
Potentially many of the currently known 163 IBD genetic risk variants can be targets for disease. There are however several caveats. First of all some genetic risk variants are not clearly linked to a gene. Several hundreds of genes reside within the 163 IBD loci and for many of these loci the truly associated gene is not known yet[5]. For a genetic variant to be a suitable target for therapy it has to be clearly linked to a gene, preferably influencing the expression or function of the protein encoded by
TE D
the gene. Moreover, the function of the gene and the biological pathways in which it exerts its function must be well understood. Finally the protein encoded by the gene must be modifiable with a drug, and such modification should not result in known adverse events[6]. Another key issue to consider is that the observed risk-effects of
EP
genetic variants on complex disease are generally very small, while the effect of a drug aimed at this genetic target still might have large effects on the disease
AC C
phenotype. An intriguing example is the case with HMG-CoA reductase inhibitors (statins), which have a large effect on serum LDL-cholesterol levels, whereas genetic variants in the gene encoding HMG-CoA reductase only have a modest effect on LDLcholesterol levels in the general population[7,8]. In our endeavors to develop targeted therapy based on genetic knowledge we should be cautious not to underestimate the complexity of the relationship between genetic variants and disease pathogenesis. In short, targeting single genes for disease therapy can be beneficial but identifying these targets is a complex process. Another possible approach, currently the most commonly used, is to use the genetic
ACCEPTED MANUSCRIPT
knowledge on the background of a disease to uncover biological pathways that are important for this disease, and target these pathways instead of single genes[6,9].
RI PT
1.2 Therapies based on novel biological knowledge from genetics
Multiple therapies currently available for the treatment of IBD target biological
pathways that have been identified or reinforced as IBD disease mechanisms by
SC
genetic research. It has to be mentioned that most of the therapies described below were developed independently from genetic studies. Some of these therapies were
similar pathophysiology.
M AN U
developed for other inflammatory diseases and repositioned in IBD, based on
We will here describe those therapies that are currently available or are being studied that are backed by the results of (unbiased) genetic research. Targeting IL12/IL23: An important inflammatory pathway in IBD identified through genetic research is the IL-23/Th17 pathway: major units of this pathway are
TE D
encoded by IL23R and IL12B, which are both known risk genes for IBD[3,10]. IL-23 is a pro-inflammatory cytokine essential for the maintenance of the Th17 lymphocyte population, a subtype of T lymphocyte implicated in chronic
EP
inflammatory/autoimmune mediated diseases. Ustekinumab (Janssen-Cilag) is a human anti-interleukin-12/-23 monoclonal antibody targeting the common p40 subunit of IL-12 and IL-23, leading to diminished production of pro-inflammatory
AC C
cytokines, such as IFN-gamma and IL-17[11]. Ustekinumab was first licensed for the treatment of plaque psoriasis and psoriatric arthritis. Two placebo-controlled trials showed clinical efficacy in patients with moderate to severe CD [12,13]. Ustekinumab showed higher response rates than placebo in patients with moderate to severe Crohn’s disease and individuals previously unresponsive to anti-TNF therapy, however it showed no significant effect on the endpoint clinical remission. This might indicate that the drug is not as effective as hoped, on the other hand it might also reflect the severity of the inflammation in the patients admitted to the
ACCEPTED MANUSCRIPT
trial and the strict criteria for the definition of remission[13]. However, since Infliximab and Adalumimab have shown significant effect on clinical remission in trials, anti-TNF agents will remain first-line biological therapies.
RI PT
Targeting JAK: Secondary signaling in the IL23/Th17 pathway runs through januskinase 2 (JAK2), tyrosine kinase 2 (TYK2) and signal transducer and activator of
transcription 3 (STAT3), which provide intracellular signaling after the activation of the IL23 receptor leading to the expression of pro-inflammatory cytokines by Th17
SC
lymphocytes. The JAK2/STAT3 axis is crucial for signalling by many inflammatory cytokines such as IL-2, IL-6 and G-CSF. The genes coding for these proteins, JAK2,
TYK2 and STAT3, are all associated to IBD. A selective inhibitor of the JAK family of
M AN U
kinases, Tofacitinib (Pfizer), has a beneficial effect on induction and maintenance of remission in UC in a phase II trial[14] but limited effect in Crohn’s disease[15]. A phase III trial is currently being conducted for both UC and CD (www.clinicaltrials.gov). Because Tofacitinib inhibits a broad range of JAK, not only
monotherapy[14].
TE D
JAK2, it has a strong immunosuppressant effect and is therefore most suitable for
Leucocyte homing to the gut: Another important pathway for the inflammation that leads to IBD is the rapid homing and adhesion of leukocytes to the mucosa of the
EP
gut[16]. Again this pathogenetic mechanism is backed by genetic evidence: first of all IBD genetic risk loci contain CCR6 and CXCR5 that encode chemokine receptors that play a role in this leukocyte homing system[3]. An important molecule in this
AC C
pathway, MADCAM-1 (Mucosal Addressin Cellular Adhesion Molecule 1), has been shown to be overexpressed in inflamed mucosa in CD and UC[17,18]. Also a recent study shows that many genetic risk variants are expression quantitative trait loci (eQTL) for neutrophils (unpublished data). This means that the IBD genetic risk variants cause differential expression of genes in neutrophils and neutrophil homing[19]. This leukocyte homing pathway is targeted by Vedolizumab (Millenium Pharmaceuticals, Inc); a humanized monoclonal antibody that specifically prevents migration of leukocytes to the gut mucosa by blocking the interaction between α4β7
ACCEPTED MANUSCRIPT
integrin on lymphocytes and the endothelial MADCAM-1[20]. In phase III trials Vedolizumab was shown to be effective for induction and short-term maintenance of remission of disease in UC patients and CD patients with prior failure on anti-TNF therapy[21,22]. Another antibody that targets the same pathway, Natalizumab
RI PT
(Biogen Idec), works in a less specific manner, only blocking the α4-subunit of the
integrin heterodimer. Natalizumab has been shown to be effective for the treatment of CD, but has shown serious side effects in the form of infections of the central
licensed for the treatment of CD[23,24].
SC
nervous system through its lack of specificity. Therefore, only Vedoluzimab will be
Autophagy: Autophagy is a biological pathway that was only identified as an
M AN U
important disease mechanism for CD through genetic studies; NOD2, IRGM and ATG16L1 are CD-specific risk genes encoding proteins involved in autophagy. Autophagy is the process of intracellular degradation of dysfunctional cellular components or pathogens. This process appears to be impaired in CD leading to a breach in the innate immune system. Agents that upregulate autophagy, mammalian
TE D
target of rapamycin (mTOR) inhibitors, have thus been tested in the treatment of CD. A case report of the effect of such an mTOR inhibitor, Sirolimus (Pfizer), on CD seemed promising[25]. However, a randomized controlled trial with everolimus (Novartis), another mTOR inhibitor, was terminated before enrollment was
EP
completed due to the lack of efficacy[26]. It could be speculated that in the future one might consider repeating trials like these, including only patients carrying the
AC C
genetic risk variants for impaired autophagy. Recently a genetic meta-analysis was performed identifying 40 new risk loci for rheumatoid arthritis (RA)[27]. The authors prioritized candidate genes within these risk loci for their functional impact on the disease by scoring them for i.e. missense variants, genes whose expression was changed by the risk variant, and genes known to play a role in RA related phenotypes. The list of risk genes resulting from this selection process was then compared to a list of drug target genes corresponding to approved drugs for human diseases[27]. This analysis showed that many known RA
ACCEPTED MANUSCRIPT
therapies are overlapping with known RA risk genes. Moreover, this process identified several approved drugs that are registered for other phenotypes but
RI PT
might be effective in the treatment of RA[27].
1.3 Drug repositioning based on novel biological knowledge from genetics
The knowledge from the genetic background of diseases derived through genome-
SC
wide association studies can be used to develop new therapies targeted at single risk genes or disease pathways as described above. However, this genetic knowledge can be also be used to identify alternative or refined indications for
M AN U
already existing drugs approved for other indications. This process, known as drug repositioning, compares risk genes, their associated biological pathways and other factors, such as i.e. gene or protein expression, between multiple diseases to identify overlapping pathomechanisms[28–30]. Drugs in the areas where the pathomechanisms of the diseases overlap are then selected for repositioning from
TE D
one disease towards the other[28–30]. Currently, this strategy for drug development is still in its infancy, but it is likely to become one of the most important junctions in this process. There is a vast amount of knowledge on the genetic background of IBD and hence identification of drugs developed for different
EP
diseases targeted at IBD risk genes could be very profitable. An early example of drug-repositioning in IBD is the repositioning of topiramate (an anti-convulsive
AC C
drug) towards the treatment of IBD[31]. Topiramate was identified as a candidate drug for IBD by integrating a gene expression library of IBD with a small molecule drug compound library. This early example shows a possible limitation of drug repositioning; topiramate did in fact not reduce flares in IBD[32]. A current promising candidate for drug repositioning is Denosumab (Amgen/GlaxoSmithKline). Denosumab targets TNFSF11. TNFSF11 was previously identified as a CD risk locus and is also associated with bone mineral density[33,34]. Denosumab is a marketed drug for the treatment of postmenopausal women at high risk of fracture with osteoporosis. TNFSF11 is part of a pathway involved in both
ACCEPTED MANUSCRIPT
bone homeostasis and regulating T cell - dendritic cell communications, dendritic cell survival and lymph node organogenesis[35]. The latter pathway is crucial in IBD pathogenesis and Denosumab could be a good candidate for testing as a therapy in IBD. Another therapy targeted at an IBD risk gene, developed for another disease is
(www.clinicaltrials.gov)[3].
M AN U
1.4 Future progress in therapy development for IBD
SC
ICOSLG) and currently in a phase 1 trial for SLE treatment,
RI PT
AMG-557 . AMG-557 (Amgen.inc) is a monoclonal antibody directed at B7RP1 (alias
IBD are complex diseases that arise through a combination of genetic factors, environmental factors, lifestyle and diet, and commensal bacteria of the gut. In order to develop a therapy for such a disease requires in-depth knowledge on the effect of each of these factors on the disease and their interaction. In the last few years, tremendous progress has been made in unraveling the genetic background of IBD.
TE D
There is virtually no other complex, immune-mediated disease that has such a vast body of knowledge on the genetic architecture of the disease and the biological pathways involved. Despite these enormous advances, there has been limited progress in getting a grasp on the other factors involved in IBD pathogenesis. The
EP
main reason for this is the lack of multi-level integration of genomic data with uniform, validated phenotype data. To move the field forward it is essential to
AC C
combine molecular data with prospective clinical data, including important parameters like drug responses or toxicity. Currently efforts are being made to build biobanks of IBD patients with uniform and extensive phenotype data and biological materials that is being prospectively collected and followed [www.string-ofpearls.org].
2. Screening individuals for IBD development
Using the current knowledge on genetic background of IBD could theoretically be
ACCEPTED MANUSCRIPT
used for screening individuals at increased risk to develop IBD. Unfortunately, screening at risk individuals for genetic risk for IBD will not be very effective to predict whether individuals will eventually develop IBD. Firstly, the role of genetic factors in the development of IBD is moderate, which becomes
RI PT
evident in the moderate concordance rates of the disease in monozygotic twins (~20% in UC and 40-50% in CD) where the genetic risk is identical[36]. The
currently known risk variants predict less than 14% of disease risk: most risk
variants are common in the general population and have a very small effect on
SC
disease risk. Hence the currently known risk variants do not differentiate
adequately between healthy individuals and IBD patients (see Figure 1)[37,38].
M AN U
Secondly, many of these variants are associated to other inflammatory diseases, rendering a predictive test neither very sensitive, nor very specific[3]. Moreover, there are as yet no preventative measures for the development of IBD. In conclusion,
3. Predicting outcome
TE D
a clinically useful genetic screening test for IBD is not (yet) feasible.
One of the major problems in the treatment of IBD patients is the heterogeneity of
EP
the behavior of the disease between patients: some will have mild disease, while others will develop severe disease, requiring intensive drug therapy, surgical
AC C
treatment and frequent follow-up. Aggressive treatment from the moment of diagnosis will ameliorate outcome for patients with severe disease but will cause unnecessary disease burden, in the form of side effects and costs, for patients with mild disease. Whereas the currently known risk variants are not suitable for predicting IBD risk in healthy individuals, they might be useful in predicting disease course in newly diagnosed IBD patients. Subsequently, treatment could be adjusted accordingly. The first genetic risk variants identified for CD in the NOD2 gene, are known to be associated to early age of onset, ileal disease, fibrostenotic disease behavior and the need for early surgery[37,39–46]. The genetic risk variants in
ACCEPTED MANUSCRIPT
NOD2 are however relatively low-frequent and only play a significant role in 8 to 17% of CD patients and as such are not suitable for risk prediction in the clinic by itself[42,47]. Genetic risk variants for CD in the ATG16L1 gene, a gene encoding a protein involved in autophagy, have been reported to be associated to ileal and
RI PT
fibrostenosic disease, although this has not been widely replicated and hence these variants can not be readily incorporated in a genetic prediction model[46,48–50].
Recently a variant in FOXO3, a gene encoding a transcription factor, was found to be associated with an indolent disease course in CD and RA [51]. Interestingly, the gene
SC
is not associated with disease development, but does seem to be associated with disease behaviour. This finding stresses the need for accurate prospective
M AN U
phenotyping of study cohorts to identify disease modifying genetic variants.
Genetic variants in the HLA region have frequently been reported to be associated to both CD and UC. This association has so far only been consistently replicated in UC[3]. The heterogeneity of the association signal from the HLA might be due to association to specific subphenotypes of IBD, which would make these variants
TE D
exceedingly useful in a predictive model. Association of genetic HLA variants to IBD subphenotypes is currently being investigated by the International Inflammatory Bowel Disease Genetics Consortium[52]. HLA variants appear to be associated to extensive disease and need for surgery in UC patients.
EP
Several studies have shown that carrying a higher number of genetic risk variants leads to a higher risk for IBD and a higher risk for surgical intervention in
AC C
CD[37,44,53]. An effective test predicting the course of IBD from the point of diagnosis might be constructed using a combination of known genetic risk variants, their expression profiles in affected tissue, biomarkers such as serum antiSaccharomyces cerevisiae antibodies (ASCA), and environmental factors such as smoking. Several relatively small-scale studies have already been performed trying to construct such risk prediction models. Due to small sample sizes or incomplete phenotype information these studies have been underpowered and unable to construct a clinically useful prediction test[37,44,53–56]. In the near future it should be possible to develop a comprehensive prediction test for the prognosis of IBD. In
ACCEPTED MANUSCRIPT
order to attain this goal a large prospective study cohort is needed with thorough genotype, phenotype and follow-up data and an extensive array of biomaterials, such as serum and feces. One could use all known genetic risk variants and their known interactions as a part of the prediction model and acquire an accurate
RI PT
estimation of the power of the prediction test through a recently proposed
method[57]. Environmental factors that are known to have an effect on IBD risk and prognosis such as appendectomy, smoking, and a diet containing low-fibre, highsugar and high-animal-fat can then be added to the model[58–62]. Genetic
SC
expression in blood and affected tissue, both messenger-RNA and micro-RNA, can be tested for association to IBD prognosis and incorporated in the predictive
M AN U
model[28,55,63–65]. Finally, it has been described that IBD patients have altered resident gut microbiota compared to healthy individuals [66,67], whether this alteration is a cause of the inflammation or consequence is as yet unclear[68,69]. However, one could still use information on the gut microbiota of the individuals in a predictive model. Currently such a prospective cohort is being collected in the
4. Pharmacogenetics
TE D
Netherlands to achieve the goals described above (http://www.string-of-pearls.org).
EP
Genetic variants can have large effects on drug metabolism and can lead to dramatic side-effects. Genome wide association scans in relatively small affected cohorts ,
AC C
supported by the International Serious Adverse Events Consortium (iSAEC), have been recently able to identify single genetic variants responsible for rare side effects. For example a genetic variant in HLA-B, HLA-B*5701 was discovered that leads to serious drug-induced liver injury by Flucloxacilin[70] and another serious drug side-effect with an important genetic risk factor is statin myotoxicity: several studies have shown strong associations between genetic variants in the SLCO1B1 gene[71–73]. [74]. Similarly there are currently several ongoing studies within the International IBD Genetics Consortium to identify genetic variants predictive of serious side-effects caused by frequently used IBD therapies. This study, driven by
ACCEPTED MANUSCRIPT
the UK IBD genetics consortium, is focusing on genetic variants predicting nephrotoxicity caused by 5ASA, pancreatitis and myelotoxicity by thiopurines, and demyelination caused by anti-TNF therapy (http://www.ibdresearch.co.uk/).
RI PT
4.1 Thiopurines
Currently the only clinical application of pharmaco-genomics based prescription in IBD patients is testing for TPMT mutations before starting treatment with
thiopurines. Patients carrying mutations in this gene, leading to thiopurine S-
SC
methyltransferase (TPMT) deficiency, are at high risk for developing severe
myelotoxicity when treated with thiopurines[75]. In some medical centers testing
M AN U
for TPMT deficiency is standard procedure, however a lack of this deficiency does not predict other adverse effects of thiopurines such as hepatotoxicity, pancreatitis, flu-like symptoms or gastrointestinal complaints. Hence, most guidelines recommend regular blood tests for myelo- and hepatotoxicity, instead of a genetic TPMT test, when starting thiopurines[76]. Recent studies have identified new genetic variants associated with thiopurine side-effects such as those in the ITPA,
TE D
GST-P1, GST-T, GST-M1 and GSTA2 genes[77,78]. The associations of these genetic variants with thiopurine side-effects have not yet been robustly replicated, rendering them unfit for use in pharmaco-genomics based prescription. Because of the many serious side-effects of thiopurines, being able to predict
EP
response of disease to this drug would be very useful in the clinic. Thiopurines are administered as pro-drugs and are degraded into 6-thioguanine (6-TGN) and 6-
AC C
methylmercaptopurine (6-MMP). Both are toxic in high levels, but the effect of thiopurines is probably due to 6-TGN. Xanthine oxidase (XO) and aldehyde oxidase (AO) are enzymes involved in the catabolisation of thiopurines towards the active metabolites. Genetic variants in the genes coding for these enzymes have been reported to be associated to thiopurine response and side-effects, but this association has not yet been replicated and can hence not yet be used in the clinic[79–81]. 4.2 Anti-TNF therapy
ACCEPTED MANUSCRIPT
Anti-TNF therapy is at present the most effective, but also the most costly therapy for IBD. The most frequently used anti-TNF therapies, infliximab and adalumimab, have a sustained response rate of between 21 and 48%[82,83]. Because of the extremely high costs of these drugs a test that could predict their effectiveness
RI PT
would be highly lucrative. Several studies have been performed to identify genetic variants that could provide such a test and several genetic variants have been implicated in response to anti-TNF therapy. So far, a TNFRSF1A variant and a
TNFRSF1B are the only genetic variants reported to decrease biological response to
SC
infliximab, however these findings were not unequivocally replicated in subsequent studies[84–86]. At present prospective trials are being conducted trying to identify
M AN U
reliable predictive factors for anti-TNF response. 5. Conclusion
In this chapter we have outlined the role of genetic knowledge of IBD in current IBD therapy and in the development of new IBD therapy. We further discussed the influence of this genetic knowledge on the prediction of IBD disease course and
TE D
finally we discussed the role of IBD genetics in predicting response to therapy. Many currently used IBD therapies are now found to target putative IBD risk genes, but these therapies were developed before this genetic knowledge was available.
EP
Developing new drugs based on our current knowledge of the genetic background of IBD only is not yet achievable, because it requires a thorough knowledge of which
AC C
genes are causal for IBD risk within these risk loci. Furthermore, it requires extensive understanding of the biological pathways through which these genes act in IBD pathogenesis. Understanding of these biological pathways is an avenue we have only just begun to explore. On the other hand, we can already reposition drugs registered for other phenotypes towards IBD, hence increasing our possibilities for IBD treatment. This we can do by comparing our current knowledge on putative IBD risk genes and their biological pathways with those of other disease phenotypes and identifying drugs that act on overlapping biological pathways. Subsequently, we can test drugs that could be effective in both diseases, in IBD or IBD model systems.
ACCEPTED MANUSCRIPT
Predicting IBD disease course is currently the most promising utilization of genetic knowledge on IBD risk, because this could have a large effect on treatment paradigms. However, since many of the disease modifying variants were discovered in cohorts with incomplete phenotyping and no follow-up, studies are still on their
RI PT
way to identify genetic variants that influence disease course and response to
therapy. It is expected that these studies with well-phenotyped and prospectively
followed subjects will shortly reveal genetic risk factors for e.g. serious side-effects of IBD treatment, rendering these potentially life-threatening events preventable.
SC
Also, in the near future these studies should lead to a prediction model for IBD
disease course, directing the form of treatment. Such a prediction model will include
M AN U
genetic risk variants, but also environmental factors and additional biomarkers, which will need to be carefully and uniformly recorded and collected. Practice Points:
•
TE D
•
The inflammatory bowel diseases (IBD), Crohn’s disease and ulcerative colitis, are chronic inflammatory diseases occurring through an excessive reaction of the immune system to the commensal flora of the gut in genetically susceptible individuals Recently a large number of genetic risk variants for IBD have been identified, providing new insight into the biological mechanisms behind the disease These newly identified biological mechanisms in IBD are suitable targets for drug therapy and several new drugs are emerging targeting these mechanisms
Research agenda
Knowledge on the genetics, proteomics and microbiomics of IBD should be integrated with clinical data in order to gain better understanding of the biological background of this heterogeneous disease More complete understanding of the biological mechanisms behind IBD will enable us to develop new targeted drug therapies for the disease This complete understanding of the biological background of IBD will take several years to acquire, in the meantime repositioning drugs from biologically similar diseases towards IBD might lead to new IBD therapies
AC C
•
EP
•
• •
Conflict of interest: none declared.
ACCEPTED MANUSCRIPT
Acknowledgement: RKW is supported by a VIDI grant (016.136.308) from the Netherlands Organization for Scientific Research (NWO), EAMF is supported by a Mandema grant (20111107-1102) from the University of Groningen, University
SC
RI PT
Medical Center Groningen.
M AN U
References
Finishing the euchromatic sequence of the human genome. Nature 2004;431:931–45.
[2]
Evans WE, Relling M V. Moving towards individualized medicine with pharmacogenomics. Nature 2004;429:464–8.
[3]
Jostins L, Ripke S, Weersma RK, Duerr RH, McGovern DP, Hui KY, et al. Hostmicrobe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 2012;491:119–24.
[4]
D’Haens G, Baert F, van Assche G, Caenepeel P, Vergauwe P, Tuynman H, et al. Early combined immunosuppression or conventional management in patients with newly diagnosed Crohn’s disease: an open randomised trial. Lancet 2008;371:660–7.
[5]
Fransen K, Mitrovic M, van Diemen CC, Weersma RK. The quest for genetic risk factors for Crohn’s disease in the post-GWAS era. Genome Med 2011;3:13.
AC C
EP
TE D
[1]
[6]
Plenge RM, Scolnick EM, Altshuler D. Validating therapeutic targets through human genetics. Nat Rev Drug Discov 2013;12:581–94.
[7]
Kathiresan S, Melander O, Guiducci C, Surti A, Burtt NP, Rieder MJ, et al. Six new loci associated with blood low-density lipoprotein cholesterol, highdensity lipoprotein cholesterol or triglycerides in humans. Nat Genet 2008;40:189–97.
[8]
Therapeutic response to lovastatin (mevinolin) in nonfamilial hypercholesterolemia. A multicenter study. The Lovastatin Study Group II. JAMA 1986;256:2829–34.
ACCEPTED MANUSCRIPT
[9]
Rossin EJ, Lage K, Raychaudhuri S, Xavier RJ, Tatar D, Benita Y, et al. Proteins encoded in genomic regions associated with immune-mediated disease physically interact and suggest underlying biology. PLoS Genet 2011;7:e1001273.
RI PT
[10] Duerr RH, Taylor KD, Brant SR, Rioux JD, Silverberg MS, Daly MJ, et al. A genome-wide association study identifies IL23R as an inflammatory bowel disease gene. Science 2006;314:1461–3.
SC
[11] Reddy M, Davis C, Wong J, Marsters P, Pendley C, Prabhakar U. Modulation of CLA, IL-12R, CD40L, and IL-2Ralpha expression and inhibition of IL-12- and IL-23-induced cytokine secretion by CNTO 1275. Cell Immunol 2007;247:1– 11.
M AN U
[12] Sandborn WJ, Feagan BG, Fedorak RN, Scherl E, Fleisher MR, Katz S, et al. A randomized trial of Ustekinumab, a human interleukin-12/23 monoclonal antibody, in patients with moderate-to-severe Crohn’s disease. Gastroenterology 2008;135:1130–41. [13] Sandborn WJ, Gasink C, Gao L-L, Blank MA, Johanns J, Guzzo C, et al. Ustekinumab induction and maintenance therapy in refractory Crohn’s disease. N Engl J Med 2012;367:1519–28.
TE D
[14] Sandborn WJ, Ghosh S, Panes J, Vranic I, Su C, Rousell S, et al. Tofacitinib, an oral Janus kinase inhibitor, in active ulcerative colitis. N Engl J Med 2012;367:616–24.
EP
[15] Sandborn WJ, Ghosh S, Panes J, Vranic I, Wang W, Niezychowski W. A Phase 2 Study of Tofacitinib, an Oral Janus Kinase Inhibitor, in Patients with Crohn’s Disease. Clin Gastroenterol Hepatol 2014.
AC C
[16] Thomas S, Baumgart DC. Targeting leukocyte migration and adhesion in Crohn’s disease and ulcerative colitis. Inflammopharmacology 2012;20:1–18. [17] Souza HS, Elia CC, Spencer J, MacDonald TT. Expression of lymphocyteendothelial receptor-ligand pairs, alpha4beta7/MAdCAM-1 and OX40/OX40 ligand in the colon and jejunum of patients with inflammatory bowel disease. Gut 1999;45:856–63. [18] Arihiro S, Ohtani H, Suzuki M, Murata M, Ejima C, Oki M, et al. Differential expression of mucosal addressin cell adhesion molecule-1 (MAdCAM-1) in ulcerative colitis and Crohn’s disease. Pathol Int n.d.;52:367–74. [19] Westra H-J, Arends D, Esko T, Peters MJ, Schurmann C, Schramm K, et al. Cell specific eQTL analysis without sorting cells. Cold Spring Harbor Labs Journals; 2014.
ACCEPTED MANUSCRIPT
[20] Feagan BG, Greenberg GR, Wild G, Fedorak RN, Paré P, McDonald JWD, et al. Treatment of active Crohn’s disease with MLN0002, a humanized antibody to the alpha4beta7 integrin. Clin Gastroenterol Hepatol 2008;6:1370–7.
RI PT
[21] Feagan BG, Rutgeerts P, Sands BE, Hanauer S, Colombel J-F, Sandborn WJ, et al. Vedolizumab as induction and maintenance therapy for ulcerative colitis. N Engl J Med 2013;369:699–710. [22] Sandborn WJ, Feagan BG, Rutgeerts P, Hanauer S, Colombel J-F, Sands BE, et al. Vedolizumab as induction and maintenance therapy for Crohn’s disease. N Engl J Med 2013;369:711–21.
M AN U
SC
[23] Sakuraba A, Annunziata ML, Cohen RD, Hanauer SB, Rubin DT. Mucosal healing is associated with improved long-term outcome of maintenance therapy with natalizumab in Crohn’s disease. Inflamm Bowel Dis 2013;19:2577–83.
[24] Govani SM, Waljee AK, Higgins PDR. Anti-adhesion therapies and the rule of 3 for rare events. Am J Gastroenterol 2013;108:1831–2. [25] Massey DCO, Bredin F, Parkes M. Use of sirolimus (rapamycin) to treat refractory Crohn’s disease. Gut 2008;57:1294–6.
TE D
[26] Reinisch W, Panés J, Lémann M, Schreiber S, Feagan B, Schmidt S, et al. A multicenter, randomized, double-blind trial of everolimus versus azathioprine and placebo to maintain steroid-induced remission in patients with moderate-to-severe active Crohn’s disease. Am J Gastroenterol 2008;103:2284–92.
EP
[27] Okada Y, Wu D, Trynka G, Raj T, Terao C, Ikari K, et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature 2013.
AC C
[28] Clark PM, Dawany N, Dampier W, Byers SW, Pestell RG, Tozeren A. Bioinformatics analysis reveals transcriptome and microRNA signatures and drug repositioning targets for IBD and other autoimmune diseases. Inflamm Bowel Dis 2012;18:2315–33. [29] Fukuoka Y, Takei D, Ogawa H. A two-step drug repositioning method based on a protein-protein interaction network of genes shared by two diseases and the similarity of drugs. Bioinformation 2013;9:89–93. [30] Sanseau P, Agarwal P, Barnes MR, Pastinen T, Richards JB, Cardon LR, et al. Use of genome-wide association studies for drug repositioning. Nat Biotechnol 2012;30:317–20.
ACCEPTED MANUSCRIPT
[31] Dudley JT, Sirota M, Shenoy M, Pai RK, Roedder S, Chiang AP, et al. Computational repositioning of the anticonvulsant topiramate for inflammatory bowel disease. Sci Transl Med 2011;3:96ra76.
RI PT
[32] Crockett SD, Schectman R, Stürmer T, Kappelman MD. Topiramate Use Does Not Reduce Flares of Inflammatory Bowel Disease. Dig Dis Sci 2014. [33] Franke A, McGovern DPB, Barrett JC, Wang K, Radford-Smith GL, Ahmad T, et al. Genome-wide meta-analysis increases to 71 the number of confirmed Crohn’s disease susceptibility loci. Nat Genet 2010;42:1118–25.
SC
[34] Häusler KD, Horwood NJ, Chuman Y, Fisher JL, Ellis J, Martin TJ, et al. Secreted frizzled-related protein-1 inhibits RANKL-dependent osteoclast formation. J Bone Miner Res 2004;19:1873–81.
M AN U
[35] Tilg H, Moschen AR, Kaser A, Pines A, Dotan I. Gut, inflammation and osteoporosis: basic and clinical concepts. Gut 2008;57:684–94. [36] Tysk C, Lindberg E, Järnerot G, Flodérus-Myrhed B. Ulcerative colitis and Crohn’s disease in an unselected population of monozygotic and dizygotic twins. A study of heritability and the influence of smoking. Gut 1988;29:990– 6.
TE D
[37] Weersma RK, Stokkers PCF, van Bodegraven AA, van Hogezand RA, Verspaget HW, de Jong DJ, et al. Molecular prediction of disease risk and severity in a large Dutch Crohn’s disease cohort. Gut 2009;58:388–95.
EP
[38] Festen EAM, Stokkers PCF, van Diemen CC, van Bodegraven AA, Boezen HM, Crusius BJA, et al. Genetic analysis in a Dutch study sample identifies more ulcerative colitis susceptibility loci and shows their additive role in disease risk. Am J Gastroenterol 2010;105:395–402.
AC C
[39] Tyler AD, Milgrom R, Stempak JM, Xu W, Brumell JH, Muise AM, et al. The NOD2insC polymorphism is associated with worse outcome following ileal pouch-anal anastomosis for ulcerative colitis. Gut 2013;62:1433–9. [40] Abreu MT, Taylor KD, Lin Y-C, Hang T, Gaiennie J, Landers CJ, et al. Mutations in NOD2 are associated with fibrostenosing disease in patients with Crohn’s disease. Gastroenterology 2002;123:679–88. [41] Hampe J, Grebe J, Nikolaus S, Solberg C, Croucher PJP, Mascheretti S, et al. Association of NOD2 (CARD 15) genotype with clinical course of Crohn’s disease: a cohort study. Lancet 2002;359:1661–5.
ACCEPTED MANUSCRIPT
[42] Cuthbert AP, Fisher SA, Mirza MM, King K, Hampe J, Croucher PJP, et al. The contribution of NOD2 gene mutations to the risk and site of disease in inflammatory bowel disease. Gastroenterology 2002;122:867–74.
RI PT
[43] Ahmad T, Armuzzi A, Bunce M, Mulcahy-Hawes K, Marshall SE, Orchard TR, et al. The molecular classification of the clinical manifestations of Crohn’s disease. Gastroenterology 2002;122:854–66. [44] Henckaerts L, Van Steen K, Verstreken I, Cleynen I, Franke A, Schreiber S, et al. Genetic risk profiling and prediction of disease course in Crohn’s disease patients. Clin Gastroenterol Hepatol 2009;7:972–980.e2.
M AN U
SC
[45] Seiderer J, Brand S, Herrmann KA, Schnitzler F, Hatz R, Crispin A, et al. Predictive value of the CARD15 variant 1007fs for the diagnosis of intestinal stenoses and the need for surgery in Crohn’s disease in clinical practice: results of a prospective study. Inflamm Bowel Dis 2006;12:1114–21. [46] Cleynen I, González JR, Figueroa C, Franke A, McGovern D, Bortlík M, et al. Genetic factors conferring an increased susceptibility to develop Crohn’s disease also influence disease phenotype: results from the IBDchip European Project. Gut 2013;62:1556–65.
TE D
[47] Cavanaugh JA, Adams KE, Quak EJ, Bryce ME, O’Callaghan NJ, Rodgers HJ, et al. CARD15/NOD2 risk alleles in the development of Crohn’s disease in the Australian population. Ann Hum Genet 2003;67:35–41. [48] Prescott NJ, Fisher SA, Franke A, Hampe J, Onnie CM, Soars D, et al. A nonsynonymous SNP in ATG16L1 predisposes to ileal Crohn’s disease and is independent of CARD15 and IBD5. Gastroenterology 2007;132:1665–71.
AC C
EP
[49] Glas J, Konrad A, Schmechel S, Dambacher J, Seiderer J, Schroff F, et al. The ATG16L1 gene variants rs2241879 and rs2241880 (T300A) are strongly associated with susceptibility to Crohn’s disease in the German population. Am J Gastroenterol 2008;103:682–91. [50] Roberts RL, Gearry RB, Hollis-Moffatt JE, Miller AL, Reid J, Abkevich V, et al. IL23R R381Q and ATG16L1 T300A are strongly associated with Crohn’s disease in a study of New Zealand Caucasians with inflammatory bowel disease. Am J Gastroenterol 2007;102:2754–61. [51] Lee JC, Espéli M, Anderson CA, Linterman MA, Pocock JM, Williams NJ, et al. Human SNP links differential outcomes in inflammatory and infectious disease to a FOXO3-regulated pathway. Cell 2013;155:57–69.
ACCEPTED MANUSCRIPT
[52] McGovern DP. Characterization of the Approximately 40,000 Patient Cohort of the International Inflammatory Bowel Disease (IBD) Genetics Consortium (IIBDGC). Gastroenterology 2013;144:S–177.
RI PT
[53] Hoefkens E, Nys K, John JM, Van Steen K, Arijs I, Van der Goten J, et al. Genetic association and functional role of Crohn disease risk alleles involved in microbial sensing, autophagy, and endoplasmic reticulum (ER) stress. Autophagy 2013;9:2046–55.
SC
[54] Ryan JD, Silverberg MS, Xu W, Graff LA, Targownik LE, Walker JR, et al. Predicting complicated Crohn’s disease and surgery: phenotypes, genetics, serology and psychological characteristics of a population-based cohort. Aliment Pharmacol Ther 2013;38:274–83.
M AN U
[55] Montero-Meléndez T, Llor X, García-Planella E, Perretti M, Suárez A. Identification of novel predictor classifiers for inflammatory bowel disease by gene expression profiling. PLoS One 2013;8:e76235. [56] Wei Z, Wang W, Bradfield J, Li J, Cardinale C, Frackelton E, et al. Large sample size, wide variant spectrum, and advanced machine-learning technique boost risk prediction for inflammatory bowel disease. Am J Hum Genet 2013;92:1008–12.
TE D
[57] Lee SH, Goddard ME, Wray NR, Visscher PM. A better coefficient of determination for genetic profile analysis. Genet Epidemiol 2012;36:214–24. [58] Hou JK, Abraham B, El-Serag H. Dietary intake and risk of developing inflammatory bowel disease: a systematic review of the literature. Am J Gastroenterol 2011;106:563–73.
EP
[59] Hou JK, Lee D, Lewis J. Diet and Inflammatory Bowel Disease: Review of Patient-Targeted Recommendations. Clin Gastroenterol Hepatol 2013.
AC C
[60] Andersen V, Olsen A, Carbonnel F, Tjønneland A, Vogel U. Diet and risk of inflammatory bowel disease. Dig Liver Dis 2012;44:185–94. [61] Lakatos PL. Environmental factors affecting inflammatory bowel disease: have we made progress? Dig Dis 2009;27:215–25. [62] Mahid SS, Minor KS, Soto RE, Hornung CA, Galandiuk S. Smoking and inflammatory bowel disease: a meta-analysis. Mayo Clin Proc 2006;81:1462– 71. [63] Koukos G, Polytarchou C, Kaplan JL, Morley-Fletcher A, Gras-Miralles B, Kokkotou E, et al. MicroRNA-124 regulates STAT3 expression and is down-
ACCEPTED MANUSCRIPT
regulated in colon tissues of pediatric patients with ulcerative colitis. Gastroenterology 2013;145:842–52.e2. [64] Barabási A-L, Gulbahce N, Loscalzo J. Network medicine: a network-based approach to human disease. Nat Rev Genet 2011;12:56–68.
RI PT
[65] Nguyen HTT, Dalmasso G, Müller S, Carrière J, Seibold F, Darfeuille-Michaud A. Crohn’s Disease-Associated Adherent Invasive Escherichia coli Modulate Levels of microRNAs in Intestinal Epithelial Cells to Reduce Autophagy. Gastroenterology 2014;146:508–19.
SC
[66] Greenblum S, Turnbaugh PJ, Borenstein E. Metagenomic systems biology of the human gut microbiome reveals topological shifts associated with obesity and inflammatory bowel disease. Proc Natl Acad Sci U S A 2012;109:594–9.
M AN U
[67] Morgan XC, Tickle TL, Sokol H, Gevers D, Devaney KL, Ward D V, et al. Dysfunction of the intestinal microbiome in inflammatory bowel disease and treatment. Genome Biol 2012;13:R79. [68] Jansson J, Willing B, Lucio M, Fekete A, Dicksved J, Halfvarson J, et al. Metabolomics reveals metabolic biomarkers of Crohn’s disease. PLoS One 2009;4:e6386.
TE D
[69] Willing BP, Dicksved J, Halfvarson J, Andersson AF, Lucio M, Zheng Z, et al. A pyrosequencing study in twins shows that gastrointestinal microbial profiles vary with inflammatory bowel disease phenotypes. Gastroenterology 2010;139:1844–1854.e1.
EP
[70] Daly AK, Donaldson PT, Bhatnagar P, Shen Y, Pe’er I, Floratos A, et al. HLAB*5701 genotype is a major determinant of drug-induced liver injury due to flucloxacillin. Nat Genet 2009;41:816–9.
AC C
[71] Link E, Parish S, Armitage J, Bowman L, Heath S, Matsuda F, et al. SLCO1B1 variants and statin-induced myopathy--a genomewide study. N Engl J Med 2008;359:789–99. [72] Pasanen MK, Fredrikson H, Neuvonen PJ, Niemi M. Different effects of SLCO1B1 polymorphism on the pharmacokinetics of atorvastatin and rosuvastatin. Clin Pharmacol Ther 2007;82:726–33. [73] Voora D, Shah SH, Spasojevic I, Ali S, Reed CR, Salisbury BA, et al. The SLCO1B1*5 genetic variant is associated with statin-induced side effects. J Am Coll Cardiol 2009;54:1609–16. [74] Becquemont L, Alfirevic A, Amstutz U, Brauch H, Jacqz-Aigrain E, Laurent-Puig P, et al. Practical recommendations for pharmacogenomics-based
ACCEPTED MANUSCRIPT
prescription: 2010 ESF-UB Conference on Pharmacogenetics and Pharmacogenomics. Pharmacogenomics 2011;12:113–24.
RI PT
[75] Colombel JF, Ferrari N, Debuysere H, Marteau P, Gendre JP, Bonaz B, et al. Genotypic analysis of thiopurine S-methyltransferase in patients with Crohn’s disease and severe myelosuppression during azathioprine therapy. Gastroenterology 2000;118:1025–30. [76] Chisick L, Oleschuk C, Bernstein CN. The utility of thiopurine methyltransferase enzyme testing in inflammatory bowel disease. Can J Gastroenterol 2013;27:39–43.
M AN U
SC
[77] Van Dieren JM, Hansen BE, Kuipers EJ, Nieuwenhuis EES, Van der Woude CJ. Meta-analysis: Inosine triphosphate pyrophosphatase polymorphisms and thiopurine toxicity in the treatment of inflammatory bowel disease. Aliment Pharmacol Ther 2007;26:643–52.
[78] Stocco G, Martelossi S, Barabino A, Decorti G, Bartoli F, Montico M, et al. Glutathione-S-transferase genotypes and the adverse effects of azathioprine in young patients with inflammatory bowel disease. Inflamm Bowel Dis 2007;13:57–64.
TE D
[79] Wong DR, Derijks LJJ, den Dulk MO, Gemmeke EHKM, Hooymans PM. The role of xanthine oxidase in thiopurine metabolism: a case report. Ther Drug Monit 2007;29:845–8. [80] Kudo M, Moteki T, Sasaki T, Konno Y, Ujiie S, Onose A, et al. Functional characterization of human xanthine oxidase allelic variants. Pharmacogenet Genomics 2008;18:243–51.
AC C
EP
[81] Smith MA, Marinaki AM, Arenas M, Shobowale-Bakre M, Lewis CM, Ansari A, et al. Novel pharmacogenetic markers for treatment outcome in azathioprinetreated inflammatory bowel disease. Aliment Pharmacol Ther 2009;30:375– 84. [82] Peyrin-Biroulet L, Deltenre P, de Suray N, Branche J, Sandborn WJ, Colombel JF. Efficacy and safety of tumor necrosis factor antagonists in Crohn’s disease: meta-analysis of placebo-controlled trials. Clin Gastroenterol Hepatol 2008;6:644–53. [83] Sandborn WJ, Hanauer SB, Rutgeerts P, Fedorak RN, Lukas M, MacIntosh DG, et al. Adalimumab for maintenance treatment of Crohn’s disease: results of the CLASSIC II trial. Gut 2007;56:1232–9. [84] Pierik M, Vermeire S, Steen K V, Joossens S, Claessens G, Vlietinck R, et al. Tumour necrosis factor-alpha receptor 1 and 2 polymorphisms in
ACCEPTED MANUSCRIPT
inflammatory bowel disease and their association with response to infliximab. Aliment Pharmacol Ther 2004;20:303–10.
RI PT
[85] Medrano LM, Taxonera C, Márquez A, Barreiro-de Acosta M, Gómez-García M, González-Artacho C, et al. Role of TNFRSF1B polymorphisms in the response of Crohn’s disease patients to infliximab. Hum Immunol 2014;75:71–5.
SC
[86] Steenholdt C, Enevold C, Ainsworth MA, Brynskov J, Thomsen OØ, Bendtzen K. Genetic polymorphisms of tumour necrosis factor receptor superfamily 1b and fas ligand are associated with clinical efficacy and/or acute severe infusion reactions to infliximab in Crohn’s disease. Aliment Pharmacol Ther 2012;36:650–9.
M AN U
Table 1.
TE D
Knowledge of genetic risk variants for disease Specific risk variants for disease subphenotypes
EP
"Personalized medicine"
AC C
Prediction of disease in general population
Adapting medical therapy to the individual patient
Understanding of biological pathways of disease
Development of targeted therapies
Table 1: The promise of genetic knowledge on complex disease for clinical practice falls into two main groups: genetic knowledge of association to (sub)phenotypes and biological understanding of disease pathways. The former, genetic knowledge, leads the way for “personalized medicine”: predicting disease in healthy individuals
ACCEPTED MANUSCRIPT
and adapting therapy to the individual patient. The latter, understanding of underlying biological pathways, allows for the development of targeted therapies.
RI PT
Figure legend.
Figure 1: Graph showing the distribution of the number of risk alleles per individual for controls (blue bars) and cases (red bars). Both in cases and controls, the number
SC
of risk alleles per individual follows a normal distribution, but in cases this normal distribution is shifted to the right. In spite of this shift, it is impossible to
variants and individual carries.
M AN U
differentiate between cases and controls based on the number of genetic risk
This figure is based on a cohort of Dutch IBD cases and healthy controls genotyped on the ImmunoChip. 151 risk SNPs were adequately genotyped and could be
AC C
EP
TE D
included in this graph.
AC C
EP
Figure 1.
TE D
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
ACCEPTED MANUSCRIPT
M AN U
"Personalized medicine"
Understanding of biological pathways of disease
SC
Specific risk variants for disease subphenotypes
RI PT
Knowledge of genetic risk variants for disease
Adapting medical therapy to the individual patient
AC C
EP
TE D
Prediction of disease in general population
Development of targeted therapies
S1521-6918(14)00046-8
DOI:
10.1016/j.bpg.2014.04.002
Reference:
YBEGA 1247
To appear in:
Best Practice & Research Clinical Gastroenterology
Received Date: 28 February 2014 Revised Date:
5 April 2014
Accepted Date: 13 April 2014
Please cite this article as: Festen EAM, Weersma RK, How will insights from genetics translate to clinical practice in inflammatory bowel disease?, Best Practice & Research Clinical Gastroenterology (2014), doi: 10.1016/j.bpg.2014.04.002. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
How will insights from genetics translate to clinical practice in inflammatory bowel disease?
1
University of Groningen, University Medical Centre Groningen, Department of Gastroenterology and Hepatology, the Netherlands
University of Groningen, University Medical Centre Groningen, Department of
SC
2
RI PT
Dr. E.A.M. Festen 1,2 , Prof. Dr. R.K. Weersma 1
Genetics, the Netherlands
M AN U
Correspondence to: R.K. Weersma MD, PhD, Department of Gastroenterology and Hepatology, University of Groningen and University Medical Centre Groningen, P.O. Box 30001, 9700 RB Groningen, the Netherlands. Email: [email protected]
Abstract
TE D
Tel: +31503610426 Fax: +31503619306
AC C
EP
Inflammatory bowel disease, consisting of Crohn’s disease and ulcerative colitis, is a chronic inflammatory disease of the gut, which arises through an excessive immune response to the normal gut flora in a genetically susceptible host. The disease affects predominantly young adults and due to its chronic and relapsing nature gives rise to a high disease burden both financially, physically and psychologically. Current therapy still cannot prevent the need for surgical intervention in more than half of IBD patients. Consequently, advances in IBD therapy are of high importance. Recently, several new forms of targeted therapy have been introduced, which should improve surgery-free prognosis of IBD patients. Recent identification of genetic risk variants for IBD has led to new insights into the biological mechanisms of the disease, which will, in the future, lead to new targeted therapy. In the meantime repositioning of drugs from biologically similar diseases towards IBD might lead to new IBD therapies. Keywords: Inflammatory bowel disease; Crohn's disease; Ulcerative colitis; Genetics; Personalised medicine; Pharmacogenetics; Thiopurines; Anti-TNF therapy; Drug repositioning
ACCEPTED MANUSCRIPT
Introduction Ever since the first human genome was sequenced in 2003 the clinical world has been waiting for translation of this genetic knowledge into therapies for disease or
RI PT
personalized care for individual patients[1][2]. This article is mainly focused on the implications of genetics for Inflammatory Bowel Disease (IBD), consisting of Crohn’s disease (CD) and ulcerative colitis (UC), both chronic inflammatory diseases of the
gastrointestinal tract. In the last few years the knowledge on the genetic background
SC
of IBD has been growing fast: 163 genetic risk loci have been identified for IBD,
making it the most successfully studied complex disease[3]. The promise genetics hold for clinical practice is three-fold (table 1): 1. better understanding of disease
M AN U
mechanisms allowing for the development of targeted therapies; 2. prediction of disease in the general population allowing for preventative measures; 3. adapting medical therapy to the genetic profile of the individual patient. The last two items together constitute the concept of ‘personalized medicine’. Personalized medicine will help us determine which patients will benefit from specific therapies and which
TE D
patients will not respond to therapy or even develop side effects. Since IBD are chronic disorders with an unpredictable disease course that need intensive and expensive treatment, and have potentially severe disease outcomes, the potential of personalized medicine is especially promising for this group of diseases. It is
EP
important for clinicians to identify those patients with a potentially severe disease course, since they might benefit from early intervention and a more aggressive treatment. Alternatively, patients with a favorable prognosis can be spared the side
AC C
effects of unnecessary treatment. This is an important issue since, in the treatment of IBD patients, the so-called “top-down” approach, in which biological therapies are administered early in the disease course, is increasingly being adopted[4]. This in contrast to the “step-up” approach, in which treatment is started with milder therapy and escalated if this therapy proves to be insufficient, which in patients with severe disease can lead to months of insufficient therapy. However, at the moment, the “top-down” approach may well lead to the over-zealous treatment of many patients, whereas a better selection of patients, based on genetic biomarkers, could
ACCEPTED MANUSCRIPT
very well prevent this. From the clinical perspective, genetics have not yet had much additional value to current therapy of IBD. However several steps have already been made: i) genetic knowledge can already contribute to new targeted therapies for IBD: ii) research is being done into whether genetic risk models can predict IBD in
RI PT
the general population and iii) genetic predictors for disease course and
therapeutic response are being investigated. We will review the current knowledge on these aspects of genetics in relation to the clinical care of IBD patients.
SC
1. Translating knowledge on genetic background of a disease to therapy
M AN U
Potentially many of the currently known 163 IBD genetic risk variants can be targets for disease. There are however several caveats. First of all some genetic risk variants are not clearly linked to a gene. Several hundreds of genes reside within the 163 IBD loci and for many of these loci the truly associated gene is not known yet[5]. For a genetic variant to be a suitable target for therapy it has to be clearly linked to a gene, preferably influencing the expression or function of the protein encoded by
TE D
the gene. Moreover, the function of the gene and the biological pathways in which it exerts its function must be well understood. Finally the protein encoded by the gene must be modifiable with a drug, and such modification should not result in known adverse events[6]. Another key issue to consider is that the observed risk-effects of
EP
genetic variants on complex disease are generally very small, while the effect of a drug aimed at this genetic target still might have large effects on the disease
AC C
phenotype. An intriguing example is the case with HMG-CoA reductase inhibitors (statins), which have a large effect on serum LDL-cholesterol levels, whereas genetic variants in the gene encoding HMG-CoA reductase only have a modest effect on LDLcholesterol levels in the general population[7,8]. In our endeavors to develop targeted therapy based on genetic knowledge we should be cautious not to underestimate the complexity of the relationship between genetic variants and disease pathogenesis. In short, targeting single genes for disease therapy can be beneficial but identifying these targets is a complex process. Another possible approach, currently the most commonly used, is to use the genetic
ACCEPTED MANUSCRIPT
knowledge on the background of a disease to uncover biological pathways that are important for this disease, and target these pathways instead of single genes[6,9].
RI PT
1.2 Therapies based on novel biological knowledge from genetics
Multiple therapies currently available for the treatment of IBD target biological
pathways that have been identified or reinforced as IBD disease mechanisms by
SC
genetic research. It has to be mentioned that most of the therapies described below were developed independently from genetic studies. Some of these therapies were
similar pathophysiology.
M AN U
developed for other inflammatory diseases and repositioned in IBD, based on
We will here describe those therapies that are currently available or are being studied that are backed by the results of (unbiased) genetic research. Targeting IL12/IL23: An important inflammatory pathway in IBD identified through genetic research is the IL-23/Th17 pathway: major units of this pathway are
TE D
encoded by IL23R and IL12B, which are both known risk genes for IBD[3,10]. IL-23 is a pro-inflammatory cytokine essential for the maintenance of the Th17 lymphocyte population, a subtype of T lymphocyte implicated in chronic
EP
inflammatory/autoimmune mediated diseases. Ustekinumab (Janssen-Cilag) is a human anti-interleukin-12/-23 monoclonal antibody targeting the common p40 subunit of IL-12 and IL-23, leading to diminished production of pro-inflammatory
AC C
cytokines, such as IFN-gamma and IL-17[11]. Ustekinumab was first licensed for the treatment of plaque psoriasis and psoriatric arthritis. Two placebo-controlled trials showed clinical efficacy in patients with moderate to severe CD [12,13]. Ustekinumab showed higher response rates than placebo in patients with moderate to severe Crohn’s disease and individuals previously unresponsive to anti-TNF therapy, however it showed no significant effect on the endpoint clinical remission. This might indicate that the drug is not as effective as hoped, on the other hand it might also reflect the severity of the inflammation in the patients admitted to the
ACCEPTED MANUSCRIPT
trial and the strict criteria for the definition of remission[13]. However, since Infliximab and Adalumimab have shown significant effect on clinical remission in trials, anti-TNF agents will remain first-line biological therapies.
RI PT
Targeting JAK: Secondary signaling in the IL23/Th17 pathway runs through januskinase 2 (JAK2), tyrosine kinase 2 (TYK2) and signal transducer and activator of
transcription 3 (STAT3), which provide intracellular signaling after the activation of the IL23 receptor leading to the expression of pro-inflammatory cytokines by Th17
SC
lymphocytes. The JAK2/STAT3 axis is crucial for signalling by many inflammatory cytokines such as IL-2, IL-6 and G-CSF. The genes coding for these proteins, JAK2,
TYK2 and STAT3, are all associated to IBD. A selective inhibitor of the JAK family of
M AN U
kinases, Tofacitinib (Pfizer), has a beneficial effect on induction and maintenance of remission in UC in a phase II trial[14] but limited effect in Crohn’s disease[15]. A phase III trial is currently being conducted for both UC and CD (www.clinicaltrials.gov). Because Tofacitinib inhibits a broad range of JAK, not only
monotherapy[14].
TE D
JAK2, it has a strong immunosuppressant effect and is therefore most suitable for
Leucocyte homing to the gut: Another important pathway for the inflammation that leads to IBD is the rapid homing and adhesion of leukocytes to the mucosa of the
EP
gut[16]. Again this pathogenetic mechanism is backed by genetic evidence: first of all IBD genetic risk loci contain CCR6 and CXCR5 that encode chemokine receptors that play a role in this leukocyte homing system[3]. An important molecule in this
AC C
pathway, MADCAM-1 (Mucosal Addressin Cellular Adhesion Molecule 1), has been shown to be overexpressed in inflamed mucosa in CD and UC[17,18]. Also a recent study shows that many genetic risk variants are expression quantitative trait loci (eQTL) for neutrophils (unpublished data). This means that the IBD genetic risk variants cause differential expression of genes in neutrophils and neutrophil homing[19]. This leukocyte homing pathway is targeted by Vedolizumab (Millenium Pharmaceuticals, Inc); a humanized monoclonal antibody that specifically prevents migration of leukocytes to the gut mucosa by blocking the interaction between α4β7
ACCEPTED MANUSCRIPT
integrin on lymphocytes and the endothelial MADCAM-1[20]. In phase III trials Vedolizumab was shown to be effective for induction and short-term maintenance of remission of disease in UC patients and CD patients with prior failure on anti-TNF therapy[21,22]. Another antibody that targets the same pathway, Natalizumab
RI PT
(Biogen Idec), works in a less specific manner, only blocking the α4-subunit of the
integrin heterodimer. Natalizumab has been shown to be effective for the treatment of CD, but has shown serious side effects in the form of infections of the central
licensed for the treatment of CD[23,24].
SC
nervous system through its lack of specificity. Therefore, only Vedoluzimab will be
Autophagy: Autophagy is a biological pathway that was only identified as an
M AN U
important disease mechanism for CD through genetic studies; NOD2, IRGM and ATG16L1 are CD-specific risk genes encoding proteins involved in autophagy. Autophagy is the process of intracellular degradation of dysfunctional cellular components or pathogens. This process appears to be impaired in CD leading to a breach in the innate immune system. Agents that upregulate autophagy, mammalian
TE D
target of rapamycin (mTOR) inhibitors, have thus been tested in the treatment of CD. A case report of the effect of such an mTOR inhibitor, Sirolimus (Pfizer), on CD seemed promising[25]. However, a randomized controlled trial with everolimus (Novartis), another mTOR inhibitor, was terminated before enrollment was
EP
completed due to the lack of efficacy[26]. It could be speculated that in the future one might consider repeating trials like these, including only patients carrying the
AC C
genetic risk variants for impaired autophagy. Recently a genetic meta-analysis was performed identifying 40 new risk loci for rheumatoid arthritis (RA)[27]. The authors prioritized candidate genes within these risk loci for their functional impact on the disease by scoring them for i.e. missense variants, genes whose expression was changed by the risk variant, and genes known to play a role in RA related phenotypes. The list of risk genes resulting from this selection process was then compared to a list of drug target genes corresponding to approved drugs for human diseases[27]. This analysis showed that many known RA
ACCEPTED MANUSCRIPT
therapies are overlapping with known RA risk genes. Moreover, this process identified several approved drugs that are registered for other phenotypes but
RI PT
might be effective in the treatment of RA[27].
1.3 Drug repositioning based on novel biological knowledge from genetics
The knowledge from the genetic background of diseases derived through genome-
SC
wide association studies can be used to develop new therapies targeted at single risk genes or disease pathways as described above. However, this genetic knowledge can be also be used to identify alternative or refined indications for
M AN U
already existing drugs approved for other indications. This process, known as drug repositioning, compares risk genes, their associated biological pathways and other factors, such as i.e. gene or protein expression, between multiple diseases to identify overlapping pathomechanisms[28–30]. Drugs in the areas where the pathomechanisms of the diseases overlap are then selected for repositioning from
TE D
one disease towards the other[28–30]. Currently, this strategy for drug development is still in its infancy, but it is likely to become one of the most important junctions in this process. There is a vast amount of knowledge on the genetic background of IBD and hence identification of drugs developed for different
EP
diseases targeted at IBD risk genes could be very profitable. An early example of drug-repositioning in IBD is the repositioning of topiramate (an anti-convulsive
AC C
drug) towards the treatment of IBD[31]. Topiramate was identified as a candidate drug for IBD by integrating a gene expression library of IBD with a small molecule drug compound library. This early example shows a possible limitation of drug repositioning; topiramate did in fact not reduce flares in IBD[32]. A current promising candidate for drug repositioning is Denosumab (Amgen/GlaxoSmithKline). Denosumab targets TNFSF11. TNFSF11 was previously identified as a CD risk locus and is also associated with bone mineral density[33,34]. Denosumab is a marketed drug for the treatment of postmenopausal women at high risk of fracture with osteoporosis. TNFSF11 is part of a pathway involved in both
ACCEPTED MANUSCRIPT
bone homeostasis and regulating T cell - dendritic cell communications, dendritic cell survival and lymph node organogenesis[35]. The latter pathway is crucial in IBD pathogenesis and Denosumab could be a good candidate for testing as a therapy in IBD. Another therapy targeted at an IBD risk gene, developed for another disease is
(www.clinicaltrials.gov)[3].
M AN U
1.4 Future progress in therapy development for IBD
SC
ICOSLG) and currently in a phase 1 trial for SLE treatment,
RI PT
AMG-557 . AMG-557 (Amgen.inc) is a monoclonal antibody directed at B7RP1 (alias
IBD are complex diseases that arise through a combination of genetic factors, environmental factors, lifestyle and diet, and commensal bacteria of the gut. In order to develop a therapy for such a disease requires in-depth knowledge on the effect of each of these factors on the disease and their interaction. In the last few years, tremendous progress has been made in unraveling the genetic background of IBD.
TE D
There is virtually no other complex, immune-mediated disease that has such a vast body of knowledge on the genetic architecture of the disease and the biological pathways involved. Despite these enormous advances, there has been limited progress in getting a grasp on the other factors involved in IBD pathogenesis. The
EP
main reason for this is the lack of multi-level integration of genomic data with uniform, validated phenotype data. To move the field forward it is essential to
AC C
combine molecular data with prospective clinical data, including important parameters like drug responses or toxicity. Currently efforts are being made to build biobanks of IBD patients with uniform and extensive phenotype data and biological materials that is being prospectively collected and followed [www.string-ofpearls.org].
2. Screening individuals for IBD development
Using the current knowledge on genetic background of IBD could theoretically be
ACCEPTED MANUSCRIPT
used for screening individuals at increased risk to develop IBD. Unfortunately, screening at risk individuals for genetic risk for IBD will not be very effective to predict whether individuals will eventually develop IBD. Firstly, the role of genetic factors in the development of IBD is moderate, which becomes
RI PT
evident in the moderate concordance rates of the disease in monozygotic twins (~20% in UC and 40-50% in CD) where the genetic risk is identical[36]. The
currently known risk variants predict less than 14% of disease risk: most risk
variants are common in the general population and have a very small effect on
SC
disease risk. Hence the currently known risk variants do not differentiate
adequately between healthy individuals and IBD patients (see Figure 1)[37,38].
M AN U
Secondly, many of these variants are associated to other inflammatory diseases, rendering a predictive test neither very sensitive, nor very specific[3]. Moreover, there are as yet no preventative measures for the development of IBD. In conclusion,
3. Predicting outcome
TE D
a clinically useful genetic screening test for IBD is not (yet) feasible.
One of the major problems in the treatment of IBD patients is the heterogeneity of
EP
the behavior of the disease between patients: some will have mild disease, while others will develop severe disease, requiring intensive drug therapy, surgical
AC C
treatment and frequent follow-up. Aggressive treatment from the moment of diagnosis will ameliorate outcome for patients with severe disease but will cause unnecessary disease burden, in the form of side effects and costs, for patients with mild disease. Whereas the currently known risk variants are not suitable for predicting IBD risk in healthy individuals, they might be useful in predicting disease course in newly diagnosed IBD patients. Subsequently, treatment could be adjusted accordingly. The first genetic risk variants identified for CD in the NOD2 gene, are known to be associated to early age of onset, ileal disease, fibrostenotic disease behavior and the need for early surgery[37,39–46]. The genetic risk variants in
ACCEPTED MANUSCRIPT
NOD2 are however relatively low-frequent and only play a significant role in 8 to 17% of CD patients and as such are not suitable for risk prediction in the clinic by itself[42,47]. Genetic risk variants for CD in the ATG16L1 gene, a gene encoding a protein involved in autophagy, have been reported to be associated to ileal and
RI PT
fibrostenosic disease, although this has not been widely replicated and hence these variants can not be readily incorporated in a genetic prediction model[46,48–50].
Recently a variant in FOXO3, a gene encoding a transcription factor, was found to be associated with an indolent disease course in CD and RA [51]. Interestingly, the gene
SC
is not associated with disease development, but does seem to be associated with disease behaviour. This finding stresses the need for accurate prospective
M AN U
phenotyping of study cohorts to identify disease modifying genetic variants.
Genetic variants in the HLA region have frequently been reported to be associated to both CD and UC. This association has so far only been consistently replicated in UC[3]. The heterogeneity of the association signal from the HLA might be due to association to specific subphenotypes of IBD, which would make these variants
TE D
exceedingly useful in a predictive model. Association of genetic HLA variants to IBD subphenotypes is currently being investigated by the International Inflammatory Bowel Disease Genetics Consortium[52]. HLA variants appear to be associated to extensive disease and need for surgery in UC patients.
EP
Several studies have shown that carrying a higher number of genetic risk variants leads to a higher risk for IBD and a higher risk for surgical intervention in
AC C
CD[37,44,53]. An effective test predicting the course of IBD from the point of diagnosis might be constructed using a combination of known genetic risk variants, their expression profiles in affected tissue, biomarkers such as serum antiSaccharomyces cerevisiae antibodies (ASCA), and environmental factors such as smoking. Several relatively small-scale studies have already been performed trying to construct such risk prediction models. Due to small sample sizes or incomplete phenotype information these studies have been underpowered and unable to construct a clinically useful prediction test[37,44,53–56]. In the near future it should be possible to develop a comprehensive prediction test for the prognosis of IBD. In
ACCEPTED MANUSCRIPT
order to attain this goal a large prospective study cohort is needed with thorough genotype, phenotype and follow-up data and an extensive array of biomaterials, such as serum and feces. One could use all known genetic risk variants and their known interactions as a part of the prediction model and acquire an accurate
RI PT
estimation of the power of the prediction test through a recently proposed
method[57]. Environmental factors that are known to have an effect on IBD risk and prognosis such as appendectomy, smoking, and a diet containing low-fibre, highsugar and high-animal-fat can then be added to the model[58–62]. Genetic
SC
expression in blood and affected tissue, both messenger-RNA and micro-RNA, can be tested for association to IBD prognosis and incorporated in the predictive
M AN U
model[28,55,63–65]. Finally, it has been described that IBD patients have altered resident gut microbiota compared to healthy individuals [66,67], whether this alteration is a cause of the inflammation or consequence is as yet unclear[68,69]. However, one could still use information on the gut microbiota of the individuals in a predictive model. Currently such a prospective cohort is being collected in the
4. Pharmacogenetics
TE D
Netherlands to achieve the goals described above (http://www.string-of-pearls.org).
EP
Genetic variants can have large effects on drug metabolism and can lead to dramatic side-effects. Genome wide association scans in relatively small affected cohorts ,
AC C
supported by the International Serious Adverse Events Consortium (iSAEC), have been recently able to identify single genetic variants responsible for rare side effects. For example a genetic variant in HLA-B, HLA-B*5701 was discovered that leads to serious drug-induced liver injury by Flucloxacilin[70] and another serious drug side-effect with an important genetic risk factor is statin myotoxicity: several studies have shown strong associations between genetic variants in the SLCO1B1 gene[71–73]. [74]. Similarly there are currently several ongoing studies within the International IBD Genetics Consortium to identify genetic variants predictive of serious side-effects caused by frequently used IBD therapies. This study, driven by
ACCEPTED MANUSCRIPT
the UK IBD genetics consortium, is focusing on genetic variants predicting nephrotoxicity caused by 5ASA, pancreatitis and myelotoxicity by thiopurines, and demyelination caused by anti-TNF therapy (http://www.ibdresearch.co.uk/).
RI PT
4.1 Thiopurines
Currently the only clinical application of pharmaco-genomics based prescription in IBD patients is testing for TPMT mutations before starting treatment with
thiopurines. Patients carrying mutations in this gene, leading to thiopurine S-
SC
methyltransferase (TPMT) deficiency, are at high risk for developing severe
myelotoxicity when treated with thiopurines[75]. In some medical centers testing
M AN U
for TPMT deficiency is standard procedure, however a lack of this deficiency does not predict other adverse effects of thiopurines such as hepatotoxicity, pancreatitis, flu-like symptoms or gastrointestinal complaints. Hence, most guidelines recommend regular blood tests for myelo- and hepatotoxicity, instead of a genetic TPMT test, when starting thiopurines[76]. Recent studies have identified new genetic variants associated with thiopurine side-effects such as those in the ITPA,
TE D
GST-P1, GST-T, GST-M1 and GSTA2 genes[77,78]. The associations of these genetic variants with thiopurine side-effects have not yet been robustly replicated, rendering them unfit for use in pharmaco-genomics based prescription. Because of the many serious side-effects of thiopurines, being able to predict
EP
response of disease to this drug would be very useful in the clinic. Thiopurines are administered as pro-drugs and are degraded into 6-thioguanine (6-TGN) and 6-
AC C
methylmercaptopurine (6-MMP). Both are toxic in high levels, but the effect of thiopurines is probably due to 6-TGN. Xanthine oxidase (XO) and aldehyde oxidase (AO) are enzymes involved in the catabolisation of thiopurines towards the active metabolites. Genetic variants in the genes coding for these enzymes have been reported to be associated to thiopurine response and side-effects, but this association has not yet been replicated and can hence not yet be used in the clinic[79–81]. 4.2 Anti-TNF therapy
ACCEPTED MANUSCRIPT
Anti-TNF therapy is at present the most effective, but also the most costly therapy for IBD. The most frequently used anti-TNF therapies, infliximab and adalumimab, have a sustained response rate of between 21 and 48%[82,83]. Because of the extremely high costs of these drugs a test that could predict their effectiveness
RI PT
would be highly lucrative. Several studies have been performed to identify genetic variants that could provide such a test and several genetic variants have been implicated in response to anti-TNF therapy. So far, a TNFRSF1A variant and a
TNFRSF1B are the only genetic variants reported to decrease biological response to
SC
infliximab, however these findings were not unequivocally replicated in subsequent studies[84–86]. At present prospective trials are being conducted trying to identify
M AN U
reliable predictive factors for anti-TNF response. 5. Conclusion
In this chapter we have outlined the role of genetic knowledge of IBD in current IBD therapy and in the development of new IBD therapy. We further discussed the influence of this genetic knowledge on the prediction of IBD disease course and
TE D
finally we discussed the role of IBD genetics in predicting response to therapy. Many currently used IBD therapies are now found to target putative IBD risk genes, but these therapies were developed before this genetic knowledge was available.
EP
Developing new drugs based on our current knowledge of the genetic background of IBD only is not yet achievable, because it requires a thorough knowledge of which
AC C
genes are causal for IBD risk within these risk loci. Furthermore, it requires extensive understanding of the biological pathways through which these genes act in IBD pathogenesis. Understanding of these biological pathways is an avenue we have only just begun to explore. On the other hand, we can already reposition drugs registered for other phenotypes towards IBD, hence increasing our possibilities for IBD treatment. This we can do by comparing our current knowledge on putative IBD risk genes and their biological pathways with those of other disease phenotypes and identifying drugs that act on overlapping biological pathways. Subsequently, we can test drugs that could be effective in both diseases, in IBD or IBD model systems.
ACCEPTED MANUSCRIPT
Predicting IBD disease course is currently the most promising utilization of genetic knowledge on IBD risk, because this could have a large effect on treatment paradigms. However, since many of the disease modifying variants were discovered in cohorts with incomplete phenotyping and no follow-up, studies are still on their
RI PT
way to identify genetic variants that influence disease course and response to
therapy. It is expected that these studies with well-phenotyped and prospectively
followed subjects will shortly reveal genetic risk factors for e.g. serious side-effects of IBD treatment, rendering these potentially life-threatening events preventable.
SC
Also, in the near future these studies should lead to a prediction model for IBD
disease course, directing the form of treatment. Such a prediction model will include
M AN U
genetic risk variants, but also environmental factors and additional biomarkers, which will need to be carefully and uniformly recorded and collected. Practice Points:
•
TE D
•
The inflammatory bowel diseases (IBD), Crohn’s disease and ulcerative colitis, are chronic inflammatory diseases occurring through an excessive reaction of the immune system to the commensal flora of the gut in genetically susceptible individuals Recently a large number of genetic risk variants for IBD have been identified, providing new insight into the biological mechanisms behind the disease These newly identified biological mechanisms in IBD are suitable targets for drug therapy and several new drugs are emerging targeting these mechanisms
Research agenda
Knowledge on the genetics, proteomics and microbiomics of IBD should be integrated with clinical data in order to gain better understanding of the biological background of this heterogeneous disease More complete understanding of the biological mechanisms behind IBD will enable us to develop new targeted drug therapies for the disease This complete understanding of the biological background of IBD will take several years to acquire, in the meantime repositioning drugs from biologically similar diseases towards IBD might lead to new IBD therapies
AC C
•
EP
•
• •
Conflict of interest: none declared.
ACCEPTED MANUSCRIPT
Acknowledgement: RKW is supported by a VIDI grant (016.136.308) from the Netherlands Organization for Scientific Research (NWO), EAMF is supported by a Mandema grant (20111107-1102) from the University of Groningen, University
SC
RI PT
Medical Center Groningen.
M AN U
References
Finishing the euchromatic sequence of the human genome. Nature 2004;431:931–45.
[2]
Evans WE, Relling M V. Moving towards individualized medicine with pharmacogenomics. Nature 2004;429:464–8.
[3]
Jostins L, Ripke S, Weersma RK, Duerr RH, McGovern DP, Hui KY, et al. Hostmicrobe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 2012;491:119–24.
[4]
D’Haens G, Baert F, van Assche G, Caenepeel P, Vergauwe P, Tuynman H, et al. Early combined immunosuppression or conventional management in patients with newly diagnosed Crohn’s disease: an open randomised trial. Lancet 2008;371:660–7.
[5]
Fransen K, Mitrovic M, van Diemen CC, Weersma RK. The quest for genetic risk factors for Crohn’s disease in the post-GWAS era. Genome Med 2011;3:13.
AC C
EP
TE D
[1]
[6]
Plenge RM, Scolnick EM, Altshuler D. Validating therapeutic targets through human genetics. Nat Rev Drug Discov 2013;12:581–94.
[7]
Kathiresan S, Melander O, Guiducci C, Surti A, Burtt NP, Rieder MJ, et al. Six new loci associated with blood low-density lipoprotein cholesterol, highdensity lipoprotein cholesterol or triglycerides in humans. Nat Genet 2008;40:189–97.
[8]
Therapeutic response to lovastatin (mevinolin) in nonfamilial hypercholesterolemia. A multicenter study. The Lovastatin Study Group II. JAMA 1986;256:2829–34.
ACCEPTED MANUSCRIPT
[9]
Rossin EJ, Lage K, Raychaudhuri S, Xavier RJ, Tatar D, Benita Y, et al. Proteins encoded in genomic regions associated with immune-mediated disease physically interact and suggest underlying biology. PLoS Genet 2011;7:e1001273.
RI PT
[10] Duerr RH, Taylor KD, Brant SR, Rioux JD, Silverberg MS, Daly MJ, et al. A genome-wide association study identifies IL23R as an inflammatory bowel disease gene. Science 2006;314:1461–3.
SC
[11] Reddy M, Davis C, Wong J, Marsters P, Pendley C, Prabhakar U. Modulation of CLA, IL-12R, CD40L, and IL-2Ralpha expression and inhibition of IL-12- and IL-23-induced cytokine secretion by CNTO 1275. Cell Immunol 2007;247:1– 11.
M AN U
[12] Sandborn WJ, Feagan BG, Fedorak RN, Scherl E, Fleisher MR, Katz S, et al. A randomized trial of Ustekinumab, a human interleukin-12/23 monoclonal antibody, in patients with moderate-to-severe Crohn’s disease. Gastroenterology 2008;135:1130–41. [13] Sandborn WJ, Gasink C, Gao L-L, Blank MA, Johanns J, Guzzo C, et al. Ustekinumab induction and maintenance therapy in refractory Crohn’s disease. N Engl J Med 2012;367:1519–28.
TE D
[14] Sandborn WJ, Ghosh S, Panes J, Vranic I, Su C, Rousell S, et al. Tofacitinib, an oral Janus kinase inhibitor, in active ulcerative colitis. N Engl J Med 2012;367:616–24.
EP
[15] Sandborn WJ, Ghosh S, Panes J, Vranic I, Wang W, Niezychowski W. A Phase 2 Study of Tofacitinib, an Oral Janus Kinase Inhibitor, in Patients with Crohn’s Disease. Clin Gastroenterol Hepatol 2014.
AC C
[16] Thomas S, Baumgart DC. Targeting leukocyte migration and adhesion in Crohn’s disease and ulcerative colitis. Inflammopharmacology 2012;20:1–18. [17] Souza HS, Elia CC, Spencer J, MacDonald TT. Expression of lymphocyteendothelial receptor-ligand pairs, alpha4beta7/MAdCAM-1 and OX40/OX40 ligand in the colon and jejunum of patients with inflammatory bowel disease. Gut 1999;45:856–63. [18] Arihiro S, Ohtani H, Suzuki M, Murata M, Ejima C, Oki M, et al. Differential expression of mucosal addressin cell adhesion molecule-1 (MAdCAM-1) in ulcerative colitis and Crohn’s disease. Pathol Int n.d.;52:367–74. [19] Westra H-J, Arends D, Esko T, Peters MJ, Schurmann C, Schramm K, et al. Cell specific eQTL analysis without sorting cells. Cold Spring Harbor Labs Journals; 2014.
ACCEPTED MANUSCRIPT
[20] Feagan BG, Greenberg GR, Wild G, Fedorak RN, Paré P, McDonald JWD, et al. Treatment of active Crohn’s disease with MLN0002, a humanized antibody to the alpha4beta7 integrin. Clin Gastroenterol Hepatol 2008;6:1370–7.
RI PT
[21] Feagan BG, Rutgeerts P, Sands BE, Hanauer S, Colombel J-F, Sandborn WJ, et al. Vedolizumab as induction and maintenance therapy for ulcerative colitis. N Engl J Med 2013;369:699–710. [22] Sandborn WJ, Feagan BG, Rutgeerts P, Hanauer S, Colombel J-F, Sands BE, et al. Vedolizumab as induction and maintenance therapy for Crohn’s disease. N Engl J Med 2013;369:711–21.
M AN U
SC
[23] Sakuraba A, Annunziata ML, Cohen RD, Hanauer SB, Rubin DT. Mucosal healing is associated with improved long-term outcome of maintenance therapy with natalizumab in Crohn’s disease. Inflamm Bowel Dis 2013;19:2577–83.
[24] Govani SM, Waljee AK, Higgins PDR. Anti-adhesion therapies and the rule of 3 for rare events. Am J Gastroenterol 2013;108:1831–2. [25] Massey DCO, Bredin F, Parkes M. Use of sirolimus (rapamycin) to treat refractory Crohn’s disease. Gut 2008;57:1294–6.
TE D
[26] Reinisch W, Panés J, Lémann M, Schreiber S, Feagan B, Schmidt S, et al. A multicenter, randomized, double-blind trial of everolimus versus azathioprine and placebo to maintain steroid-induced remission in patients with moderate-to-severe active Crohn’s disease. Am J Gastroenterol 2008;103:2284–92.
EP
[27] Okada Y, Wu D, Trynka G, Raj T, Terao C, Ikari K, et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature 2013.
AC C
[28] Clark PM, Dawany N, Dampier W, Byers SW, Pestell RG, Tozeren A. Bioinformatics analysis reveals transcriptome and microRNA signatures and drug repositioning targets for IBD and other autoimmune diseases. Inflamm Bowel Dis 2012;18:2315–33. [29] Fukuoka Y, Takei D, Ogawa H. A two-step drug repositioning method based on a protein-protein interaction network of genes shared by two diseases and the similarity of drugs. Bioinformation 2013;9:89–93. [30] Sanseau P, Agarwal P, Barnes MR, Pastinen T, Richards JB, Cardon LR, et al. Use of genome-wide association studies for drug repositioning. Nat Biotechnol 2012;30:317–20.
ACCEPTED MANUSCRIPT
[31] Dudley JT, Sirota M, Shenoy M, Pai RK, Roedder S, Chiang AP, et al. Computational repositioning of the anticonvulsant topiramate for inflammatory bowel disease. Sci Transl Med 2011;3:96ra76.
RI PT
[32] Crockett SD, Schectman R, Stürmer T, Kappelman MD. Topiramate Use Does Not Reduce Flares of Inflammatory Bowel Disease. Dig Dis Sci 2014. [33] Franke A, McGovern DPB, Barrett JC, Wang K, Radford-Smith GL, Ahmad T, et al. Genome-wide meta-analysis increases to 71 the number of confirmed Crohn’s disease susceptibility loci. Nat Genet 2010;42:1118–25.
SC
[34] Häusler KD, Horwood NJ, Chuman Y, Fisher JL, Ellis J, Martin TJ, et al. Secreted frizzled-related protein-1 inhibits RANKL-dependent osteoclast formation. J Bone Miner Res 2004;19:1873–81.
M AN U
[35] Tilg H, Moschen AR, Kaser A, Pines A, Dotan I. Gut, inflammation and osteoporosis: basic and clinical concepts. Gut 2008;57:684–94. [36] Tysk C, Lindberg E, Järnerot G, Flodérus-Myrhed B. Ulcerative colitis and Crohn’s disease in an unselected population of monozygotic and dizygotic twins. A study of heritability and the influence of smoking. Gut 1988;29:990– 6.
TE D
[37] Weersma RK, Stokkers PCF, van Bodegraven AA, van Hogezand RA, Verspaget HW, de Jong DJ, et al. Molecular prediction of disease risk and severity in a large Dutch Crohn’s disease cohort. Gut 2009;58:388–95.
EP
[38] Festen EAM, Stokkers PCF, van Diemen CC, van Bodegraven AA, Boezen HM, Crusius BJA, et al. Genetic analysis in a Dutch study sample identifies more ulcerative colitis susceptibility loci and shows their additive role in disease risk. Am J Gastroenterol 2010;105:395–402.
AC C
[39] Tyler AD, Milgrom R, Stempak JM, Xu W, Brumell JH, Muise AM, et al. The NOD2insC polymorphism is associated with worse outcome following ileal pouch-anal anastomosis for ulcerative colitis. Gut 2013;62:1433–9. [40] Abreu MT, Taylor KD, Lin Y-C, Hang T, Gaiennie J, Landers CJ, et al. Mutations in NOD2 are associated with fibrostenosing disease in patients with Crohn’s disease. Gastroenterology 2002;123:679–88. [41] Hampe J, Grebe J, Nikolaus S, Solberg C, Croucher PJP, Mascheretti S, et al. Association of NOD2 (CARD 15) genotype with clinical course of Crohn’s disease: a cohort study. Lancet 2002;359:1661–5.
ACCEPTED MANUSCRIPT
[42] Cuthbert AP, Fisher SA, Mirza MM, King K, Hampe J, Croucher PJP, et al. The contribution of NOD2 gene mutations to the risk and site of disease in inflammatory bowel disease. Gastroenterology 2002;122:867–74.
RI PT
[43] Ahmad T, Armuzzi A, Bunce M, Mulcahy-Hawes K, Marshall SE, Orchard TR, et al. The molecular classification of the clinical manifestations of Crohn’s disease. Gastroenterology 2002;122:854–66. [44] Henckaerts L, Van Steen K, Verstreken I, Cleynen I, Franke A, Schreiber S, et al. Genetic risk profiling and prediction of disease course in Crohn’s disease patients. Clin Gastroenterol Hepatol 2009;7:972–980.e2.
M AN U
SC
[45] Seiderer J, Brand S, Herrmann KA, Schnitzler F, Hatz R, Crispin A, et al. Predictive value of the CARD15 variant 1007fs for the diagnosis of intestinal stenoses and the need for surgery in Crohn’s disease in clinical practice: results of a prospective study. Inflamm Bowel Dis 2006;12:1114–21. [46] Cleynen I, González JR, Figueroa C, Franke A, McGovern D, Bortlík M, et al. Genetic factors conferring an increased susceptibility to develop Crohn’s disease also influence disease phenotype: results from the IBDchip European Project. Gut 2013;62:1556–65.
TE D
[47] Cavanaugh JA, Adams KE, Quak EJ, Bryce ME, O’Callaghan NJ, Rodgers HJ, et al. CARD15/NOD2 risk alleles in the development of Crohn’s disease in the Australian population. Ann Hum Genet 2003;67:35–41. [48] Prescott NJ, Fisher SA, Franke A, Hampe J, Onnie CM, Soars D, et al. A nonsynonymous SNP in ATG16L1 predisposes to ileal Crohn’s disease and is independent of CARD15 and IBD5. Gastroenterology 2007;132:1665–71.
AC C
EP
[49] Glas J, Konrad A, Schmechel S, Dambacher J, Seiderer J, Schroff F, et al. The ATG16L1 gene variants rs2241879 and rs2241880 (T300A) are strongly associated with susceptibility to Crohn’s disease in the German population. Am J Gastroenterol 2008;103:682–91. [50] Roberts RL, Gearry RB, Hollis-Moffatt JE, Miller AL, Reid J, Abkevich V, et al. IL23R R381Q and ATG16L1 T300A are strongly associated with Crohn’s disease in a study of New Zealand Caucasians with inflammatory bowel disease. Am J Gastroenterol 2007;102:2754–61. [51] Lee JC, Espéli M, Anderson CA, Linterman MA, Pocock JM, Williams NJ, et al. Human SNP links differential outcomes in inflammatory and infectious disease to a FOXO3-regulated pathway. Cell 2013;155:57–69.
ACCEPTED MANUSCRIPT
[52] McGovern DP. Characterization of the Approximately 40,000 Patient Cohort of the International Inflammatory Bowel Disease (IBD) Genetics Consortium (IIBDGC). Gastroenterology 2013;144:S–177.
RI PT
[53] Hoefkens E, Nys K, John JM, Van Steen K, Arijs I, Van der Goten J, et al. Genetic association and functional role of Crohn disease risk alleles involved in microbial sensing, autophagy, and endoplasmic reticulum (ER) stress. Autophagy 2013;9:2046–55.
SC
[54] Ryan JD, Silverberg MS, Xu W, Graff LA, Targownik LE, Walker JR, et al. Predicting complicated Crohn’s disease and surgery: phenotypes, genetics, serology and psychological characteristics of a population-based cohort. Aliment Pharmacol Ther 2013;38:274–83.
M AN U
[55] Montero-Meléndez T, Llor X, García-Planella E, Perretti M, Suárez A. Identification of novel predictor classifiers for inflammatory bowel disease by gene expression profiling. PLoS One 2013;8:e76235. [56] Wei Z, Wang W, Bradfield J, Li J, Cardinale C, Frackelton E, et al. Large sample size, wide variant spectrum, and advanced machine-learning technique boost risk prediction for inflammatory bowel disease. Am J Hum Genet 2013;92:1008–12.
TE D
[57] Lee SH, Goddard ME, Wray NR, Visscher PM. A better coefficient of determination for genetic profile analysis. Genet Epidemiol 2012;36:214–24. [58] Hou JK, Abraham B, El-Serag H. Dietary intake and risk of developing inflammatory bowel disease: a systematic review of the literature. Am J Gastroenterol 2011;106:563–73.
EP
[59] Hou JK, Lee D, Lewis J. Diet and Inflammatory Bowel Disease: Review of Patient-Targeted Recommendations. Clin Gastroenterol Hepatol 2013.
AC C
[60] Andersen V, Olsen A, Carbonnel F, Tjønneland A, Vogel U. Diet and risk of inflammatory bowel disease. Dig Liver Dis 2012;44:185–94. [61] Lakatos PL. Environmental factors affecting inflammatory bowel disease: have we made progress? Dig Dis 2009;27:215–25. [62] Mahid SS, Minor KS, Soto RE, Hornung CA, Galandiuk S. Smoking and inflammatory bowel disease: a meta-analysis. Mayo Clin Proc 2006;81:1462– 71. [63] Koukos G, Polytarchou C, Kaplan JL, Morley-Fletcher A, Gras-Miralles B, Kokkotou E, et al. MicroRNA-124 regulates STAT3 expression and is down-
ACCEPTED MANUSCRIPT
regulated in colon tissues of pediatric patients with ulcerative colitis. Gastroenterology 2013;145:842–52.e2. [64] Barabási A-L, Gulbahce N, Loscalzo J. Network medicine: a network-based approach to human disease. Nat Rev Genet 2011;12:56–68.
RI PT
[65] Nguyen HTT, Dalmasso G, Müller S, Carrière J, Seibold F, Darfeuille-Michaud A. Crohn’s Disease-Associated Adherent Invasive Escherichia coli Modulate Levels of microRNAs in Intestinal Epithelial Cells to Reduce Autophagy. Gastroenterology 2014;146:508–19.
SC
[66] Greenblum S, Turnbaugh PJ, Borenstein E. Metagenomic systems biology of the human gut microbiome reveals topological shifts associated with obesity and inflammatory bowel disease. Proc Natl Acad Sci U S A 2012;109:594–9.
M AN U
[67] Morgan XC, Tickle TL, Sokol H, Gevers D, Devaney KL, Ward D V, et al. Dysfunction of the intestinal microbiome in inflammatory bowel disease and treatment. Genome Biol 2012;13:R79. [68] Jansson J, Willing B, Lucio M, Fekete A, Dicksved J, Halfvarson J, et al. Metabolomics reveals metabolic biomarkers of Crohn’s disease. PLoS One 2009;4:e6386.
TE D
[69] Willing BP, Dicksved J, Halfvarson J, Andersson AF, Lucio M, Zheng Z, et al. A pyrosequencing study in twins shows that gastrointestinal microbial profiles vary with inflammatory bowel disease phenotypes. Gastroenterology 2010;139:1844–1854.e1.
EP
[70] Daly AK, Donaldson PT, Bhatnagar P, Shen Y, Pe’er I, Floratos A, et al. HLAB*5701 genotype is a major determinant of drug-induced liver injury due to flucloxacillin. Nat Genet 2009;41:816–9.
AC C
[71] Link E, Parish S, Armitage J, Bowman L, Heath S, Matsuda F, et al. SLCO1B1 variants and statin-induced myopathy--a genomewide study. N Engl J Med 2008;359:789–99. [72] Pasanen MK, Fredrikson H, Neuvonen PJ, Niemi M. Different effects of SLCO1B1 polymorphism on the pharmacokinetics of atorvastatin and rosuvastatin. Clin Pharmacol Ther 2007;82:726–33. [73] Voora D, Shah SH, Spasojevic I, Ali S, Reed CR, Salisbury BA, et al. The SLCO1B1*5 genetic variant is associated with statin-induced side effects. J Am Coll Cardiol 2009;54:1609–16. [74] Becquemont L, Alfirevic A, Amstutz U, Brauch H, Jacqz-Aigrain E, Laurent-Puig P, et al. Practical recommendations for pharmacogenomics-based
ACCEPTED MANUSCRIPT
prescription: 2010 ESF-UB Conference on Pharmacogenetics and Pharmacogenomics. Pharmacogenomics 2011;12:113–24.
RI PT
[75] Colombel JF, Ferrari N, Debuysere H, Marteau P, Gendre JP, Bonaz B, et al. Genotypic analysis of thiopurine S-methyltransferase in patients with Crohn’s disease and severe myelosuppression during azathioprine therapy. Gastroenterology 2000;118:1025–30. [76] Chisick L, Oleschuk C, Bernstein CN. The utility of thiopurine methyltransferase enzyme testing in inflammatory bowel disease. Can J Gastroenterol 2013;27:39–43.
M AN U
SC
[77] Van Dieren JM, Hansen BE, Kuipers EJ, Nieuwenhuis EES, Van der Woude CJ. Meta-analysis: Inosine triphosphate pyrophosphatase polymorphisms and thiopurine toxicity in the treatment of inflammatory bowel disease. Aliment Pharmacol Ther 2007;26:643–52.
[78] Stocco G, Martelossi S, Barabino A, Decorti G, Bartoli F, Montico M, et al. Glutathione-S-transferase genotypes and the adverse effects of azathioprine in young patients with inflammatory bowel disease. Inflamm Bowel Dis 2007;13:57–64.
TE D
[79] Wong DR, Derijks LJJ, den Dulk MO, Gemmeke EHKM, Hooymans PM. The role of xanthine oxidase in thiopurine metabolism: a case report. Ther Drug Monit 2007;29:845–8. [80] Kudo M, Moteki T, Sasaki T, Konno Y, Ujiie S, Onose A, et al. Functional characterization of human xanthine oxidase allelic variants. Pharmacogenet Genomics 2008;18:243–51.
AC C
EP
[81] Smith MA, Marinaki AM, Arenas M, Shobowale-Bakre M, Lewis CM, Ansari A, et al. Novel pharmacogenetic markers for treatment outcome in azathioprinetreated inflammatory bowel disease. Aliment Pharmacol Ther 2009;30:375– 84. [82] Peyrin-Biroulet L, Deltenre P, de Suray N, Branche J, Sandborn WJ, Colombel JF. Efficacy and safety of tumor necrosis factor antagonists in Crohn’s disease: meta-analysis of placebo-controlled trials. Clin Gastroenterol Hepatol 2008;6:644–53. [83] Sandborn WJ, Hanauer SB, Rutgeerts P, Fedorak RN, Lukas M, MacIntosh DG, et al. Adalimumab for maintenance treatment of Crohn’s disease: results of the CLASSIC II trial. Gut 2007;56:1232–9. [84] Pierik M, Vermeire S, Steen K V, Joossens S, Claessens G, Vlietinck R, et al. Tumour necrosis factor-alpha receptor 1 and 2 polymorphisms in
ACCEPTED MANUSCRIPT
inflammatory bowel disease and their association with response to infliximab. Aliment Pharmacol Ther 2004;20:303–10.
RI PT
[85] Medrano LM, Taxonera C, Márquez A, Barreiro-de Acosta M, Gómez-García M, González-Artacho C, et al. Role of TNFRSF1B polymorphisms in the response of Crohn’s disease patients to infliximab. Hum Immunol 2014;75:71–5.
SC
[86] Steenholdt C, Enevold C, Ainsworth MA, Brynskov J, Thomsen OØ, Bendtzen K. Genetic polymorphisms of tumour necrosis factor receptor superfamily 1b and fas ligand are associated with clinical efficacy and/or acute severe infusion reactions to infliximab in Crohn’s disease. Aliment Pharmacol Ther 2012;36:650–9.
M AN U
Table 1.
TE D
Knowledge of genetic risk variants for disease Specific risk variants for disease subphenotypes
EP
"Personalized medicine"
AC C
Prediction of disease in general population
Adapting medical therapy to the individual patient
Understanding of biological pathways of disease
Development of targeted therapies
Table 1: The promise of genetic knowledge on complex disease for clinical practice falls into two main groups: genetic knowledge of association to (sub)phenotypes and biological understanding of disease pathways. The former, genetic knowledge, leads the way for “personalized medicine”: predicting disease in healthy individuals
ACCEPTED MANUSCRIPT
and adapting therapy to the individual patient. The latter, understanding of underlying biological pathways, allows for the development of targeted therapies.
RI PT
Figure legend.
Figure 1: Graph showing the distribution of the number of risk alleles per individual for controls (blue bars) and cases (red bars). Both in cases and controls, the number
SC
of risk alleles per individual follows a normal distribution, but in cases this normal distribution is shifted to the right. In spite of this shift, it is impossible to
variants and individual carries.
M AN U
differentiate between cases and controls based on the number of genetic risk
This figure is based on a cohort of Dutch IBD cases and healthy controls genotyped on the ImmunoChip. 151 risk SNPs were adequately genotyped and could be
AC C
EP
TE D
included in this graph.
AC C
EP
Figure 1.
TE D
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
ACCEPTED MANUSCRIPT
M AN U
"Personalized medicine"
Understanding of biological pathways of disease
SC
Specific risk variants for disease subphenotypes
RI PT
Knowledge of genetic risk variants for disease
Adapting medical therapy to the individual patient
AC C
EP
TE D
Prediction of disease in general population
Development of targeted therapies