Genetic polymorphisms in folate and adenosine pathway and MTX transporters associated with MTX treatment outcome in patients with psoriasis or psoriatic arthritis.
Abstract
Psoriasis is a chronic systemic, immune-mediated disorder of unknown aetiology, usually presenting with typical inflammatory skin lesions and/or joint manifestations, but systemic inflammation that may lead to the development of co-morbidities may also be present. First-line therapy encompasses local cutaneous treatment and phototherapy, but with more severe symptoms or systemic course, systemic treatment with methotrexate (MTX), immunosuppressant cyclosporine, retinoid acitretin or biologicals may be used. Treatment response varies between patients in terms of efficacy and/or toxicity, which could, among other reasons, be due to genetic differences between patients. Approximately 10–30% of patients experience adverse drug reactions with MTX treatment, leading to discontinuation of MTX mostly due to hepatotoxicity. Around 15% of patients experience adverse events when treated with biologicals; however, the most frequent reason for discontinuation is inefficacy or loss of the initially favourable response over time. Inefficacy or occurrence of adverse drug reactions cannot be predicted, so genetic biomarkers of drug response in combination with clinical data could be helpful in treatment planning. Several polymorphic genes have already been associated with treatment outcome, most of them involved in drug metabolism, transport and target pathways. Genetic biomarkers could be helpful in personalized care of psoriasis patients in order to prevent adverse events or predict inefficacy of a certain drug.
Keywords
- psoriasis
- pharmacogenetics
- genetic polymorphisms
- personalized medicine
- methotrexate
- biologic agents
1. Introduction
Psoriasis is a chronic systemic immune-mediated disorder of which etiopathogenesis is not yet fully understood, though there is evidence of genetic, immunologic and environmental factors playing a role in the development and the severity of the disease. The most common symptoms involve typical inflammatory skin lesions, but systemic inflammation may also be present [1, 2]. Psoriatic arthritis (PsA) is the most frequent systemic manifestation that can accompany the skin lesions and occurs in up to 40% of patients [3]. Systemic inflammation is also one of the reasons for the occurrence of many other comorbidities in patients with psoriasis, such as metabolic syndrome which includes obesity, type 2 diabetes, hypertension and dyslipidaemia, cardiovascular diseases, chronic inflammatory bowel disease and also cancer in some cases [4]. Furthermore, lower quality of life and psychological disorders are also more frequent among psoriasis patients as compared to general population [5, 6]. It is proven that lifestyle, including diet, smoking and alcohol consumption, influences the occurrence and the course of psoriasis and the comorbidities [7]. Elevated body mass index and visceral fat can also increase the probability of more progressive course of the disease [7].
The severity of the disease is evaluated by the Psoriasis Area and Severity Index (PASI) score that takes into account the area of the affected skin, the thickness of skin plaques and the severity of inflammation. PASI score is calculated before the treatment strategy is chosen and is also used to monitor the treatment response. The response to treatment is considered to be good when PASI has decreased for at least 75% from the baseline score in 3–6 months after the first dose was administered (PASI75) [8]. The minimum treatment goal is usually set at PASI decreasing for at least 50% from the baseline score (PASI50). If PASI50 is not met, the treatment plan is usually changed [9]. However, PASI only evaluates the dermatological manifestations of the disease and neglects the psychological aspect. Therefore, Dermatology Life Quality Index (DLQI) is also assessed with a questionnaire to evaluate the impact of psoriasis on a patient’s physical, psychological and social well-being. The treatment goal is to achieve DLQI of zero to one after 2–4 months of treatment, but if this cannot be achieved, at least DLQI below five should be aimed for [9].
The patient’s response to systemic psoriasis treatment cannot be predicted. Furthermore, the interindividual variability in the treatment response is quite extensive and adverse events occur frequently [6]. A study conducted 3 years ago discovered that approximately 75% of traditional systemic drugs are discontinued after 143 days of treatment (
1.1. Genetic factors are associated with treatment response
Our genetic characteristics are encoded in our genome [13]. Interindividual differences between people are due to differences in less than 1% of genomic DNA sequence between unrelated individuals. Different variants of the same gene or genetic locus are called alleles. A variant is called a polymorphism when there are at least two alleles present in the population and the frequency of the less prevalent allele is more than 1%. A great majority of variants are due to single nucleotide polymorphisms (SNPs), which means that alleles differ only in one nucleotide. In addition to SNPs, deletions, insertions, duplications of nucleotides or longer sequences, microsatellites, changes in variable number of tandem nucleotide repeats (VNTR) and others may account for genetic polymorphism. Genetic polymorphisms may influence the process of transcription, translation and/or function of proteins. If variants change the binding site for different regulatory proteins, transcription may be altered. Amino acids are encoded as a sequence of three nucleotides, called codons. If a polymorphism changes a codon, another amino acid can be incorporated into a protein, which can change the characteristics and function of a protein. Insertion of only one nucleotide causes frame shift, which results in a premature stop codon and non-functional protein. The same happens after a stop codon is formed in the middle of an exon or when SNPs alter mRNA splicing. Gene deletions may cause depletion of proteins while, on the other hand, gene duplications lead to excess of the encoded protein [14].
Genetic polymorphisms may also influence expression and function of proteins involved in drug metabolism and transport as well as drug targets and their effector pathways. Because of that, genetic polymorphisms may influence patients’ response to drugs and the occurrence of adverse effects. Pharmacogenetics studies the associations between genetic polymorphisms and the course of disease and response to treatment. The aim of this chapter is to summarize the current knowledge on pharmacogenetic polymorphisms that may influence the response to systemic treatment in patients diagnosed with psoriasis. Such polymorphisms have been investigated as predictive biomarkers of treatment response that would support personalized treatment approaches in patients with psoriasis.
2. Pharmacogenetics of systemic psoriasis treatment
2.1. Low-dose methotrexate
Methotrexate (MTX) is an immunomodulatory drug that is widely used in the treatment of psoriasis and PsA and is frequently the first-line systemic treatment for these two indications. It is usually orally administered once per week in doses of 7.5–30 mg [9]. Good response to treatment is achieved in approximately 50% of cases [8]. On the other hand, from 10 to 30% of patients have to discontinue the treatment because of adverse drug reactions. These include nausea, malaise, gastrointestinal ulcers, depression, infections, nephrotoxicity and most importantly hepatotoxicity and bone marrow suppression [9]. Adverse events are usually mild and can be eliminated by dose reduction. However, some adverse events may be severe or even life-threatening and cannot be predicted. This is the reason why patients treated with MTX are monitored very closely, and liver and kidney functions and blood status have to be checked regularly [8]. With the low doses used for psoriasis treatment, MTX plasma concentrations are too low to be measured, so drug monitoring cannot be used to predict the occurrence of adverse events. It has been therefore proposed that genetic polymorphisms should be investigated as predictors of response to treatment, either efficacy or toxicity [15–17].
MTX is a folate analogue and as such inhibits folic acid metabolism. Folic acid is a donor of methyl group in the process of deoxythymidylate synthesis that is required for DNA synthesis and cell proliferation as well as donor of methyl groups for methionine synthesis that directs the methyl group towards methylation reactions [18].
MTX enters the cell through the reduced folate carrier SLC19A1 and is activated by folylpoly- glutamate synthase that adds glutamate moieties to the molecule. MTX polyglutamate primarily inhibits dihydrofolate reductase (DHFR), thus inhibiting also thymidylate synthase (TYMS) reaction, which results in inhibition of DNA synthesis. Indirectly it inhibits also other enzymes of folate metabolic pathway and methylation reactions, such as methylentetrahydrofolate dehydrogenase (MTHFD1), methylentetrahydrofolate reductase (MTHFR), methionine synthase (MS) and methionine-synthase reductase (MSR) (Figure 1) [19].
MTX is also adenosine pathway inhibitor. It inhibits the enzyme 5-aminoimidazole-4- carboxamide ribonucleotide (AICAR) transformylase (ATIC), which results in elevated levels of AICAR. AICAR inhibits adenosine deaminase (ADA) and this consequently leads to higher intercellular concentrations of adenosine. Adenosine is released into circulation, and its binding to adenosine receptors on the target cells contributes significantly to the anti-inflammatory effects of MTX (Figure 1) [18].
Cells are protected from toxic effects of MTX by transmembrane transporters ABC (ATP-binding cassette), especially ABCB1, ABCC2 and ABCG2. They are ATP dependent, and they actively pump MTX out of the cell. On the other hand, solute carriers (SLC), such as SLC19A1 and SLCO1B1, facilitate MTX transport in the direction of the concentration gradient (Figure 1) [19].
Most of the genes coding for the enzymes in folate and adenosine pathway as well as for folate and MTX transporters are polymorphic. As genetic polymorphisms may lead to differences in expression and activity of enzymes, polymorphisms in the genes coding for the above mentioned proteins (transporters and enzymes) contribute to interindividual variability in therapeutic response and toxicity profile of drugs among patients. Several of the above mentioned polymorphic genes were already studied in relation to MTX treatment response in rheumatoid arthritis (RA) and cancer, but studies regarding psoriasis are scarce. Studies pointing out positive associations between polymorphisms and response to MTX in psoriasis and PsA are listed in Table 1.
Genes | Variants | Predicted effect | Reference | |
---|---|---|---|---|
rs34743033 28-bp repeat | 0.048 | Carriers of the 3R allele susceptible to poor response to MTX | [20] | |
rs35592 c.1219-176T>C | 0.008 | Homozygotes for the major allele respond better to MTX | [25] | |
rs2238476 c.3391-1960G>A | 0.02 | |||
rs28364006 c.4009A>G | 0.02 | |||
rs13120400 c.1194+928A>G | 0.03 | Minor allele associated with better response to MTX | [25] | |
rs17731538 c.204-1592C>T | 0.007 | Major allele associated with better response to MTX | ||
DHFR | rs1232027 g.80619201G>A | 0.02 | Minor allele associated with better response to MTX | [15] |
rs1051266 c.80A>G | 0.025 | A allele associated with occurrence of adverse events | [20] | |
0.03 | A allele associated with toxicity | [25] | ||
rs1801131 c.1298A>C Glu429Ala | 0.042 | C allele associated with lower risk of hepatotoxicity | [20] | |
rs1801133 c.677C>T Ala222Val | 0.04 | Homozygotes for the minor allele more susceptible to liver toxicity | [15] | |
rs34489327 nt.1494del6 | 0.015 | Polymorphism increases the risk for hepatotoxicity | [20] | |
rs34743033 28-bp repeat | 0.0025 | 3R allele increased risk for adverse events in patients without folic acid supplementation | ||
rs2372536 c.347C>G | 0.038 | G allele associated with increased risk for MTX discontinuation due to adverse events | [20] | |
0.01 | Homozygotes for the major allele more susceptible to MTX toxicity | [22] | ||
rs4672768 c.1660-135G>A | 0.02 | Homozygotes for the major allele more susceptible to MTX toxicity | [22] | |
rs2238476 c.3391-1960G>A | 0.01 | Homozygotes for the major allele more susceptible to toxicity | [25] | |
rs3784864 c.616-1641G>A | 0.03 | Carriers of at least one major allele more susceptible to toxicity | ||
rs246240 c.616-7942A>G | 0.0006 | Homozygotes for the major allele more susceptible to toxicity | ||
rs3784862 c.615+413G>A | 0.002 | Homozygotes for the major allele more susceptible to toxicity | ||
rs1967120 c.489+409G>A | 0.01 | Carriers of at least one major allele more susceptible to toxicity | ||
rs11075291 c.49-3198G>A | 0.008 | Carriers of at least one major allele more susceptible to toxicity | ||
rs5760410 g.24815406G>A | 0.03 | Homozygotes for the major allele more susceptible to toxicity | [25] |
2.1.1. Genetic variability in folate pathway and MTX treatment
The direct target of MTX within folate pathway is DHFR that converts dihydrofolic acid into tetrahydrofolic acid (Figure 1). It is therefore surprising that the impact of
TYMS is one of the key enzymes providing deoxythymidylate for DNA synthesis, thus enabling cell proliferation. Two common functional polymorphisms in
MTHFR is the central enzyme in folate pathway as it is responsible for the conversion of 5,10-methylentetrahydrofolate, which is a substrate for TYMS, to 5-methyltetrahydrofolate, which is a substrate for homocysteine remethylation (Figure 1). The most studied polymorphisms in
Polymorphisms in
2.1.2. Genetic variability in adenosine pathway and MTX treatment
MTX directly inhibits ATIC, the key enzyme in the adenosine pathway (Figure 1). The consequent accumulation of AICAR indirectly leads to accumulation of adenosine in circulation, which acts as an anti-inflammatory factor. The most studied genetic polymorphism in
ADA is the enzyme inhibited because of accumulation of AICAR following MTX treatment. A functional polymorphism
No other polymorphic genes in adenosine metabolic pathway were investigated in psoriasis patients. However, in Slovenian patients with RA, several other genes in adenosine pathway were studied.
The anti-inflammatory effect of adenosine is directly related to its binding to the adenosine receptors (ADORA). Only one pharmacogenetic study investigated adenosine receptors so far and included 374 patients with chronic plaque psoriasis, who had been treated with MTX for at least 3 months. No significant association was detected between polymorphisms in
2.1.3. Genetic variability in folate and MTX transport and MTX treatment
Polymorphisms in transporters may influence intracellular MTX levels and, thus, also influence therapeutic effect. SLC19A1 (RFC1) is a reduced folate carrier, which facilitates the MTX transport into the cell. Many studies investigated the most common functional polymorphism in
On the other hand, polymorphisms in genes coding for the efflux ABC transporters showed association with efficacy as well as toxicity. In the study by Warren et al., two polymorphic transporter genes were investigated in psoriasis patients:
2.2. Cyclosporine
Cyclosporine is an orally administered systemic immunosuppressive drug that may be used to treat the most resistant forms of psoriasis, especially the plaque-type diseases [9]. It inhibits the first phase of T-lymphocyte activation, thus decreasing the levels of inflammatory cytokines, among them interleukin-2 (IL2) and interferon- gamma (IFNG) [26]. It is usually administered in doses of 2.5–5 mg/kg of body weight/day [9]. The current knowledge on cyclosporine pharmacogenetics comes from studies in recipients of solid organ transplants. Bioavailability and clearance of the drug are influenced by polymorphic P-glycoprotein (ABCB1) in gastrointestinal tract and CYP3A4 and CYP3A5 in the liver, suggesting that these polymorphisms could also influence the response to cyclosporine treatment in psoriatic patients [27, 28]. There was only one pharmacogenetic study performed on psoriasis patients treated with cyclosporine, and it focused only on
Genes | Variants | Predicted effect | Reference | |
---|---|---|---|---|
ABCB1 | rs1045642 c.3435C>T p.Ile1145= | 0.0075 | Minor T allele associated with poor response to cyclosporine | [29] |
2.3. Acitretin
Acitretin is a vitamin A derivative that belongs to the second-generation retinoids [30]. It reduces proliferation of epidermal keratinocytes and promotes their differentiation. It is also used as an anti-inflammatory agent. It is administered orally in doses of 0.5–0.8 mg/kg daily. Usually, it is used in combination with topical treatment as well as phototherapy [9]. Studies pointing out positive associations between polymorphisms and response to acitretin in psoriasis are listed in Table 3. The most widely studied polymorphisms lie in the gene coding for vascular epidermal growth factor (
Genes | Variants | Predicted effect | Reference | |
---|---|---|---|---|
rs833061 c.-958C>T | 0.04 | TT genotype increased the risk of poor response to acitretin | [31] | |
0.01 | TC genotype increased the chance of favourable response to acitretin | |||
14 bp DEL | 0.008 | DEL allele associated with better response to acitretin | [34] | |
0.05 | DEL/DEL genotype is associated with better response to acitretin |
Another study performed on a group of Italian patients found an association between the
2.4. Biologic drugs
Biologic drugs specifically bind to their target, usually inflammation mediators or their receptors, and inhibit their action, which results in anti-inflammatory effect. Biologics used in treatment of psoriasis mainly inhibit tumour necrosis factor alpha (TNFα) and several interleukins (IL)—IL17, IL12 and IL23. Among the biologics used for psoriasis treatment, infliximab, adalimumab, etanercept are TNFα inhibitors, while ustekinumab is an IL12/23 inhibitor and secukinumab is IL17 inhibitor [36, 37].
Biologic drugs are relatively safe and well tolerated. Adverse events occur only in appro- ximately 15% of patients, but the symptoms are usually not severe and are not the reason for discontinuation [38]. The most common adverse events are injection-site reaction (pain, erythema, itching and haemorrhage) and different infections, mostly of upper respiratory tract [9]. However, according to a study performed by Levin et al., 48% of patients discontinue treatment due to reasons not related to toxicity [8].
A study conducted in 2015 that included 4309 patients treated with different biologics for 12 months showed that patients experienced dose escalations and discontinuations, restarting the same biologic or switching to a different one. Approximately one-third of patients had their doses increased until month 6 and 39% until month 12 of treatment. On the other hand, half of these patients also discontinued the biologic drug or reduced the dose [6]. This indicates that many patients do not achieve sufficient response or lose an initially favourable response over time. Pharmacogenetic studies have investigated several polymorphisms in genes coding for the targets of biologic drugs and their signalling pathways regarding their contribution to interpatient and intrapatient variability in treatment response to biologics in patients with RA, PsA, Chron’s disease and spondyloarthritis (SA). However, such studies have been rarely performed exclusively in psoriasis patients [39].
2.4.1. Pharmacogenetics of anti-TNFα treatment
The most widely used biologic drugs for systemic psoriasis treatment are TNFα blockers. It is therefore not surprising that the majority of pharmacogenetic studies focused on polymorphisms in the gene coding for TNFα (
Genes | Variants | Predicted effect | Reference | |
---|---|---|---|---|
rs1799724 c.-857C>T | 0.002 | C allele associated with better response to etanercept | [49] | |
0.004 | Patients with CT/TT genotypes showed greater improvements in PASI score | [47] | ||
rs361525 c.-238A>G | 0.049 | Patients with GG genotype achieved PASI75 more frequently after 6 months of anti-TNFα therapy | [47] | |
0.03 | G allele associated with better response to etanercept | [48] | ||
rs1799964 c.-1031T>C | 0.041 | Patients with TT genotype demonstrated superior improvements in PASI after 6 months of therapy | [47] | |
rs80267959 c.186+123G>A | 0.0136 | G allele favours better response to etanercept in PsA patients | [63] | |
rs1800629 c.-308G>A | 0.001 | GG genotype associated with better response to etanercept | [48] | |
rs1061622 c.676T>G p.Met196Arg | 0.001 | T allele associated with better response to etanercept | [49] | |
0.05 | G allele associated with poor response | [52] | ||
rs610604 c.987-152G>T | 0.05 | G allele associated with better response to anti-TNFα therapy | [53] | |
0.007 | T allele associated with better response to etanercept | [54] | ||
rs20575 c.626G>C p.Arg209Thr | 0.048 | CC genotype associated with better response to infliximab in PsA | [66] | |
rs767455 c.36A>G p.Pro12= | 0.04 | AA genotype associated with better response to infliximab in PsA | ||
rs11209026 c.1142G>A p.Arg381Gln | 0.006 | Patients with GG genotype achieved more frequently PASI 90 at 6 months | [47] | |
rs1800795 c.-237C>G | <0.05 | Carriers of t C allele respond better to therapy | [55] | |
rs763780 c.482T>C p.His161Arg | 0.0044 | TC genotype associated with no response to adalimumab at 6 months | [56] | |
0.023 | TC genotype associated with better response to infliximab at 3 months | |||
0.020 | TC genotype associated with better response to infliximab at 6 months | |||
rs4819554 c.-947G>A | 0.03 | AA genotype associated with better response at12 weeks | [67] | |
rs10484554 g.2609009C>T | 0.007 | C allele associated with better response to adalimumab | [54] | |
rs13190932 c.220C>T p.Arg74Trp | 0.041 | G allele associated with better response to infliximab | ||
rs9260313 g.1428637T>C | 0.05 | TT genotype associated with better response to adalimumab | ||
rs1801274 c.497A>G p.His131Arg | 0.03 | Patients homozygous for high-affinity allele had a higher chance of achieving PASI75 after 3 months of therapy | [57] | |
0.034 | PsA patients with high-affinity genotype respond better to anti-TNFα drugs (etanercept) after 6 months of therapy | [64] | ||
rs396991 c.841T>C p.Val158Phe | 0.02 | Patients homozygous for high-affinity allele had a higher chance of achieving PASI75 after 3 months of therapy | [57] | |
0.018 | T allele associated with better response to etanercept | [58] | ||
rs3794271 c.50+1078G>A | 0.0031 | AA genotype associated with better response to etanercept | [59] | |
0.00034 | A gender-specific (males) association between G allele and poor response found in PsA patients | [65] | ||
rs6427528 c.*1738A>G | 0.025 | GA genotype associated with better response to etanercept | [60] | |
rs6701290 c.84-10630G>A | <0.05 | Associated with anti-TNFα drug response in a GWAS | [62] | |
rs3784240 c.475+782C>T | ||||
rs2390256 c.*2687G>A | ||||
rs2219538 c.77+2269G>A | ||||
rs10515637 c.2507-1067T>C | ||||
rs10823825 c.2290-538T>C | ||||
rs1927159 c.704-13438A>C | ||||
rs7820834 g.129238197T>C | ||||
rs553668 c.450+33966C>T | ||||
rs4867965 c.88+96839A>C | ||||
rs11209026 c.1142G>A p.Arg381Gln | 0.005 | AG genotype associated with development of paradoxical psoriasiform reactions | [61] | |
rs10782001 c.1361+720G>A | 0.028 | GG genotype associated with development of paradoxical psoriasiform reactions | ||
rs3087243 c.*1421G>A | 0.012 | AG/GG genotype associated with development of paradoxical psoriasiform reactions | ||
rs651630 c.1706-272C>T | 0.011 | TT genotype associated with development of paradoxical psoriasiform reactions | ||
rs1800453 c.1307A>G | 0.018 | AG genotype associated with development of paradoxical psoriasiform reactions |
The most frequently investigated candidate gene is
Other
Researchers expanded their interests also to polymorphisms in other genes in TNFα pathways. A study performed on 80 Greek patients with psoriasis investigated polymorphisms in
Polymorphisms within gene coding for tumour necrosis factor alpha-induced protein 3 (
Furthermore, polymorphisms in genes encoding several interleukins and their receptors were investigated in psoriasis patients treated with anti-TNFα drugs. A study that included 109 psoriasis patients investigated polymorphisms in
Genes for Fc gamma receptors were also investigated for their association with response of psoriasis patients to anti-TNFα drugs. Patients homozygous for high-affinity alleles of two variants
A study performed by Cabaleiro et al. revealed an association between certain polymorphisms and occurrence of paradoxical psoriasiform reactions after treatment with anti-TNFα therapy. Polymorphisms in five genes:
Another approach to identify novel loci and SNPs associated with response to anti-TNFα drugs included genome-wide association study (GWAS) approach. A small GWAS study was recently performed that included 65 psoriasis patients prospectively followed for 12 weeks. This study identified 10 SNPs in 10 different genes that could be associated with drug response: cadherin-related 23 (
Several studies have also investigated association of genetic polymorphisms with anti-TNFα treatment outcome in PsA cohorts. A study investigating the association of an intronic polymorphism at the position c.+489 of
2.4.2. IL12/23 inhibitors
Ustekinumab is a human monoclonal antibody directed against interleukins IL12 and IL23. Studies of polymorphisms affecting patients’ response to these inhibitors are scarce, but some of them, listed in Table 5, pointed out positive associations. A cohort of 51 patients with psoriasis treated with ustekinumab was tested for three polymorphisms, including the
Genes | Variants | Predicted effect | Reference | |
---|---|---|---|---|
rs763780 c.482T>C p.His161Arg | 0.022 | TC genotype associated with no response at 3 months | [56] | |
0.016 | TC genotype associated with no response at 6 months | |||
rs3213094 c.89-432G>A | 0.017 | CT genotype associated with favourable response | [60] | |
rs610604 c.987-152G>T | 0.031 | GG genotype associated with poor response | ||
Cw6POS/NEG | 0.008 | Cw6POS patients respond better and faster | [68] | |
0.035 | Cw6POS patients respond better | [69] | ||
rs1061622 c.676T>G p.Met196Arg | 0.05 | G allele associated with poor response | [52] | |
rs151823 c.-454-1169A>C | 0.026 | CC genotype associated with better response | [54] | |
rs26653 c.380G>C p.Arg127Pro | 0.016 | GG genotype associated with better response |
Another study found association between the
3. Future perspectives
Large heterogeneity in patients’ response to therapy calls for new molecular predictors of treatment response. We have searched the current literature to compile a comprehensive review of today’s knowledge on genetic variants that may influence the outcome of psoriasis systemic treatment. A rather small number of studies were performed so far, and, although some of the results are encouraging, even larger number of studies shows inconsistent or even conflicting results. The investigated patient cohorts were with a few exceptions rather small and the number of evaluated polymorphisms limited. The future studies should expand the range of polymorphisms investigated by either looking into other pathways besides the ones directly involved in drug mechanisms, such as metabolism and transport, though they certainly are important in treatment response. Great interindividual variability in treatment outcome among patients could also be associated with heterogeneous pathology. Not all of the patients have the same pathogenesis, although they present with similar symptoms. Genetic defects in various pathways could be causative of the disease or support disease occurrence, and these defects in so-called susceptibility genes should also be checked regarding their influence on treatment outcome. The heterogeneity in pathogenesis could also be the reason for inconsistency in pharmacogenetic studies conducted so far. The hypothesis-free approach of the GWAS studies could help to overcome these obstacles and help to elucidate genetic factors associated with both disease pathways and treatment responses; however, such studies should include large number of well-characterized patients. Furthermore, the identified predictors of the course of the disease and of the treatment response should be validated in independent patient samples.
Such validated pharmacogenetic biomarkers would enable us to characterize patients with psoriasis by their genetic characteristics and not just their phenotype and would allow for a more targeted approach to pharmacotherapy. The patients could be stratified according to their genetic defects affecting the molecular mechanisms of the disease in combination with genetic defects in pathways of drug metabolism and transport as well as in drug targets and effector pathways. Pharmacogenetic factors should also be combined with clinical data to find the most suitable way of stratifying patients into groups eligible for certain treatment strategies. If a physician would be able to predict patient’s response based on pharmacogenetic polymorphisms, problems of inefficacy and toxicity could be overcome by choosing the right drug and dose for a particular patient. This would also help to lower the cost of the treatment and, what is more important, relieve some of the patient’s psychological burden, which is often overlooked in psoriasis. Methods for genotyping are fast, reliable, relatively cheap and suitable for use in diagnostic laboratories. Despite the costs that would be spent on implementation of new genetic analysis methods into everyday clinical practice, pharmacogenetics-based personalized treatment approach would probably lower the expenses of psoriasis treatment due to more rational pharmacotherapy.
4. Conclusions
Personalized medicine is emerging as the innovative approach also in psoriasis treatment. A general belief that every drug can help every patient is getting obsolete. However, to be able to properly tailor the patient’s treatment, consistent biomarkers of the treatment outcome must be identified and validated. In psoriasis treatment, the search for such biomarkers is still in its beginnings. In this chapter, we summarized the current knowledge on genetic predictors of response to MTX, cyclosporine, acitretin and biologic drugs. Several studies have already identified some of the genetic variants associated with response to a particular drug, but none of the genetic polymorphisms within these genes were recognized as specific enough to be used in clinical practice so far. However, some promising candidates for predictors of treatment response were identified that could be used in personalized treatment of psoriasis patients if validated in further studies.
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