Biomarkers in Psoriasis: The Future of Personalised Treatment

Abstract

Psoriasis is a chronic and complex immune-mediated papulosquamous disease affecting almost 2% of the world population. The interaction between a genetically predisposed individual and environmental triggers leads to a vicious cycle involving autoreactive T cells, dendritic cells, keratinocytes and dermal cells. Up to 40% of the psoriasis cases develop disabling psoriatic arthritis and an equal number of patients also tend to develop metabolic syndrome as well as cardiovascular comorbidities; hence, this is no more considered to be a disease limited to skin only. Being a systemic disease, there is an urgent need to develop potential biomarkers for the assessment of disease severity, prediction of outcome of the therapeutic intervention and association with various systemic comorbidities. Diverse genetic markers not only function as predictors of diseases pathogenesis, but also help to predict development of psoriasis and psoriatic arthritis. Personalised medicine is customising the therapeutic needs of a psoriasis patient and improving the outcome as per the hints we receive from the various biomarkers. This review deals with the list of potential biomarkers proposed to be useful in psoriasis, though there is limited data validating their routine use in clinical practice and the progress so far made in the field of precision medicine for psoriasis.

Introduction

Psoriasis is a common, chronic, multisystem inflammatory disease with a prevalence of 0.09% and 11.4% across various studies.[1,2] It is a disease of multifactorial origin, caused by a complex interaction between genetic predisposition, the immune system and various poorly identified environmental triggers.[3] Apart from the extent of cutaneous lesions, the risk of comorbidities like psoriatic arthropathy, cardiometabolic derangements and depression accounts for a significant impact on the patient’s psyche.[4]

The US National Institutes of Health (NIH) biomarkers and surrogate endpoint working group defines a biological biomarker as a characteristic that is objectively measured and evaluated as an indicator of normal physiological processes, pathogenic processes or pharmacological responses to therapeutic intervention.[5] The NIH working group classified biomarkers into three types: Type 0 markers are the ones that correlate longitudinally with the natural history of the disease, Type I markers are those that capture the effects of an intervention in accordance with the mechanism of action of the drug and Type II markers are surrogate endpoints for changes that predict clinical benefits. Biomarkers are important clinically as they help in quantitative evaluation of diagnosis, disease pathophysiology and severity as well as treatment response.[6] They can be represented by genetic, soluble, cellular or tissue-associated markers.

Biomarkers help the healthcare providers to assess the people who are at risk of a severe form of disease as well as who are likely to develop comorbidities. They also help to predict the response to various therapeutic interventions employed in the treatment of psoriasis, including biologics, and tailor-make the treatment approach.[7]

However, as of now, there are no approved biomarkers that are part of routine clinical management in psoriasis. Though improvements in various types of highly sensitive biological assays have resulted in an increase in biomarker discovery, they need to be chosen wisely and validated before implementation.[8]

Biomarker discovery and clinical implementation

Various omics technologies that help the development of candidate biomarkers of psoriasis include genomics, transcriptomics, proteomics, glycomics, lipidomics and metabolomics. Potential biomarkers are usually validated through established techniques such as enzyme-linked immunosorbent assay (ELISA), immunohistochemistry (IHC), lectin array, western blot (WB) and quantitative reverse transcription polymerase chain reaction with a large cohort of subjects and/or samples. The successfully validated ones are the candidate biomarkers which are utilised in various clinical applications related to diagnosis, prognosis, recurrence or relapse prediction and therapy of psoriasis.[9]

Classification of biomarkers in psoriasis

1. Genetic biomarkers

2. Tissue-associated biomarkers

3. Soluble biomarkers

4. Biomarkers for associated comorbidities

5. Biomarkers to predict a therapeutic response

6. Biomarkers related to various adverse events during therapy.

Genetic Biomarkers

Genetics plays a vital role in the predisposition and morphological manifestations of psoriasis. In a genetically predisposed individual, certain environmental triggers stimulate the immune system that leads to a cascade of inflammatory cytokines.

Psoriasis has a higher incidence among people who have affected relatives. Monozygotic twins have two to three times higher risk of developing psoriasis than dizygotic twins.[10] Nine chromosomal loci, from PSORS1 to PSORS9, have been confirmed in linkage analysis studies,[11] out of which PSORS1 is the major genetic determinant and encodes for human leucocyte antigen (HLA) CW6. PSORS1 is expressed in up to 60% of patients with early-onset psoriasis.[12] PSORS4 is another locus of susceptibility associated with terminal differentiation of keratinocytes. PSORS4 contains genes belonging to the late cornified envelope complex and S100 calcium-binding proteins produced by keratinocytes.

Single-nucleotide polymorphisms (SNPs), belonging to the Th1/Th17 pathway (Il23R, Il12B, Il23A genes) and the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kB) pathway (TNFAIP3), have been closely linked with psoriasis and psoriatic arthritis. Increased copy numbers of the genes encoding human beta defensin-2, human beta defensin-3 and human beta defensin-4 are associated with psoriasis.[13] 238G/A SNP, detected at the tumour necrosis factor (TNF)-α gene promoter, has been found to be associated with development of psoriasis. SNP involving 857C/T has been reported to be more closely associated with psoriatic arthritis.[14] Genetic susceptibility loci of psoriasis serve two important purposes by giving important insights into the pathogenesis of the disease as well as functioning as markers of risk of development of psoriasis and related comorbidities. Few important genetic biomarkers are given in Table 1.

Table 1.

Genetic biomarkers in psoriasis

Proposed biomarker	Name/function	Association
PSORS4 S100	S100 calcium-binding protein	Psoriasis
CNv DEFB4	Beta-defensin-2	Psoriasis
SNP Il23r	Proinflammatory cytokines	Psoriasis
SNP Il 12b		Psoriasis
SNP IL 23a		Psoriasis
SNPs TNF-alpha encoding		Pso/PsA

SNP=single-nucleotide polymorphism, TNF=tumour necrosis factor

Tissue-Associated Biomarkers

Tissue-associated biomarkers are presented in Table 2.

Table 2.

Tissue-level biomarkers in psoriasis

Biomarkers	Associated psoriasis type
K1, K6, K10, K16	PSO
VEGF	PSO
S100A8/A9	PSO
IL-6, IL-8, IL-18	PSO
TNF-alpha	PSO
IFN-gamma	PSO
IL-17	PSO
IL-22	PSO
TLR4	Guttate psoriasis
Oxidative stress markers (oxidised lipids)	PSO/PsA

IL=interleukin, INF=interferon, TNF=tumour necrosis factor, VEGF=vascular endothelial growth factor

Psoriasis area severity index (PASI) scoring is time-consuming and has interobserver variations and a low reproducibility. Skin biopsy with IHC is a semiquantitative way of measuring the severity of psoriasis and it bypasses the loopholes seen with the use of PASI.[15,16] Immunostaining with anti-K1, -K6, -K10 and -K16 antibodies reflects abnormal proliferation and differentiation of keratinocytes in the psoriatic epidermis.[17,18] K16 is overexpressed in the suprabasal layers of the interfollicular epidermis, and response to effective therapy can be monitored by using downregulation of K16[17] as an indicator. K16 is also a marker of relapsing psoriasis lesions.[18]

Non-lesional psoriatic epidermis shows increased K16 expression and is proposed as a marker of preclinical psoriasis.[19] K1 and K10 are downregulated in psoriatic lesions.[17]

Soluble Biomarkers

Soluble biomarkers are presented in Table 3.

Table 3.

Soluble biomarkers in psoriasis

Biomarkers	Associated with
hsCRP, ESR, fibrinogen	Severity of psoriasis
VEGF	Link between angiogenesis and inflammation in psoriasis
hBD-2	Psoriasis disease activity
	Proportionate to IL-17 activity
S100A8/A9	Psoriasis disease activity
IL-6, IL-8, IL-18, TNF-α, IFN-γ, IL-17, IL-22, TGF-β1	Psoriasis disease severity

ESR=erythrocyte sedimentation rate, IL=interleukin, INF=interferon, TGF=transforming growth factor, TNF=tumour necrosis factor, VEGF=vascular endothelial growth factor, hBD-2=human beta defensin 2

The most important serum biomarkers of inflammation associated with severity of psoriasis include high-sensitivity C-reactive protein, erythrocyte sedimentation rate and fibrinogen level.[20]

Human beta defensin-2 is overexpressed in psoriasis lesions.[21] Serum levels of human beta defensin-2 increase in patients with psoriasis compared to controls and also show changes proportionate to the PASI score. The high amount of the molecule, which is an antimicrobial peptide, in psoriatic skin in comparison to normal or atopic skin explains the lesser rate of infections seen in psoriasis cases.[22]

Serum levels of Human beta defensin 2 (hBD-2) serve a surrogate marker for interleukin (IL)-17A axis-related skin diseases.[23] Hence, hBD-2 can be a potential biomarker of psoriasis disease activity both in the circulation and in tissue.[24]

PSORS4 encodes for various S100 calcium-binding proteins like S100A7 (psoriasin), S100A8 (calgranulin A) and S100A9 (calgranulin B). These proteins have proinflammatory and chemotactic activity and are markedly upregulated in psoriatic plaques.[25] IL22 induces the expression of S100A7, S100A8 and S100A9 and leads to proliferation of keratinocytes and production of antimicrobial peptides.[26] Higher serum levels of S100A8 and S100A9 correlate positively with psoriasis activity.[27]

Vascular endothelial growth factor (VEGF) is a key cytokine in angiogenesis. VEGF activates monocytes and promotes chemotaxis, and hence, it serves as a missing link between angiogenesis and the inflammatory events in psoriasis. Higher serum levels of VEGF in psoriasis patients compared to controls make VEGF a potential biomarker for psoriasis. Bevacizumab, which is an autoantibody against VEGF, has been used in the treatment of psoriasis with favourable outcomes.[28]

Lipocalin-2

Lipocalin-2 (LCN2) is a proinflammatory protein which stimulates the production of IL-6, IL-8 and CXCL10, which are key players in the pathogenesis of psoriasis. LCN2 affects neutrophil chemotaxis and its role in the Th17 pathway. Psoriasis patients have higher levels of LCN2 in both serum and skin, compared to controls.[29] Severity of psoriasis as well as psoriatic arthritis corelates with serum LCN2 level.[30]

YKL-40

Expression of YKL-40 has been linked to the Th17 pathway[31] and is regulated by IL-6, IL-13, IL-17, interferon (IFN)-γ and vasopressin. In moderate to severe psoriasis patients treated with Narrow Band Ultraviolet B (NBUVB) phototherapy, serum YKL-40 level is correlated with that of IL-17 as well as the PASI score.[31] Higher YKL-40 levels in patients than in controls,[32] as found in a meta-analysis, suggest that YKL-40 is a potential biomarker for the assessment of psoriasis and its severity and progression.

Cytokines involved in various steps of psoriasis pathogenesis have also been proposed as soluble biomarkers. Serum concentrations of IL-6, IL-8, IL-17, IL-18, IFN-γ, p40 subunit of IL-12 and IL-23 are increased proportionate to psoriasis severity.[33]

Guttate psoriasis is triggered mostly after upper respiratory infections and is associated with increased expression of Toll-like receptor 4.[34]

All the proposed biomarkers in tissue and serum are associated with the various inflammatory pathways linked to the pathogenesis of psoriasis. Exploring a correlation between the proposed biomarkers and the PASI score will provide a comprehensive understanding of the molecular pathomechanisms of various types of psoriasis.

Biomarkers of Comorbidities

Though C-reactive protein is a reliable and validated biomarker of cardiovascular disease,[35] it is a non-specific indicator of inflammation. Hence, GlycA, which is a nuclear magnetic resonance signal originating from a subset of glycan N-acetylglucosamine residues, is proposed as an alternative to it. GlycA levels studied by nuclear magnetic resonance spectroscopy correlated significantly with hs-CRP and markers of cardiometabolic disease in 412 psoriasis patients and controls.[36]

Psoriasin belongs to the S100 family of small calcium-binding proteins. It is a keratinocyte-derived antimicrobial peptide and acts as a chemotactic factor for inflammatory cells.[37] Psoriasin also contributes to angiogenesis associated with psoriasis.[38] Serum levels of psoriasin corelate well with the intima–media thickness and PASI.[39]

T cells and natural killer cells release IFN-γ under the influence of IL-18.[40] Arican et al.[41] reported higher concentration of inflammatory cytokines like IL-6, IL-8, IL-12, IL-18, IFN-γ and TNF-α in psoriasis patients. IL-18 also plays a role in activating Th17 cells. It is one of the earliest biomarkers with the potential to predict the risk of cardiovascular comorbidities in psoriasis patients.[42]

Cardiac myocytes produce N-terminal pro-B-type natriuretic peptide (NT-proBNP) in response to stress. It is an inactivated peptide derived from the prohormone of Type B Natriuretic Peptide (BNP). Psoriasis patients have increased serum levels of NT-proBNP compared to controls.[43]

Plasma levels of asymmetric dimethylarginine and small dense low-density lipoprotein (LDL) reflect subclinical atherosclerosis in psoriatic arthritis patients.[44] Abdollahimajd et al.[45] reported higher concentration of angiotensin-converting enzyme (ACE) in psoriasis patients compared to controls and the association of ACE level with mean intima–media thickness of carotid arteries. Serum levels of TNF-α and IL-6 are elevated in obese psoriasis patients and can serve as surrogate biomarkers of psoriatic disease activity and the associated risk of comorbidities.[46] Serum level of IL-21 is significantly elevated in obese patients with or without psoriasis. Higher serum homocysteine is also correlated with a higher PASI score.[46]

Higher levels of serum markers of oxidative stress, like catalase, LDL antibody and higher neutrophil function, were seen in patients with psoriatic disease compared to controls.[47] Oxidative damage and lipid peroxidation also contribute to atherosclerosis in psoriasis.

Obesity is a commonly encountered comorbidity in psoriasis patients. Activated adipocytes in obese subjects secrete proinflammatory cytokines like TNF-α and leptin. Resistin secreted by peripheral blood mononuclear cells promotes insulin resistance and inflammation.[48] Serum resistin levels were found to corelate well with the disease severity i multiple studies.[49,50] Leptin concentration has been reported to change in proportion to the disease severity score across the moderate and severe variants of psoriasis.[51] More robust data on leptin and resistin will aid their use as potential predictive biomarkers of insulin resistance and atherosclerosis in psoriasis patients.

Renal disorder-related tests

Psoriasis is a multisystem inflammatory disorder, and the role of oxidative stress contributing to the inflammation is well established. There is a higher chance of occurrence of renal disease in psoriasis patients, as seen in some studies. In imiquimod-induced mice models, renal involvement was found to be proportionate to the severity of psoriasis and this also correlated with the upregulation of NADPH oxidases like NADPH Oxidase 2 (NOX-2), NADPH Oxidase 4 (NOX-4) and Inducible Nitric Oxide Synthase (iNOS).[52]

Serum levels of uric acid, adenosine deaminase, xanthine oxidase and 8-hydroxy-deoxy-guanosine were elevated in psoriasis patients proportionate to the PASI score. Serum levels of related purine derivatives were also correlated with various parameters of renal impairment. These experimental works suggest that severe psoriasis may be associated with renal diseases, and related purine derivatives might serve as the candidate biomarkers of renal disease progression.[53]

Biomarkers to identify risk of psoriatic arthritis (PsA)

IFN-γ induces production of an important chemokine CXCL10 by monocytes, endothelial cells and fibroblasts. IFN-γ signalling, denoted by serum CXCL10 level, is a key driver in the early stages of PsA, but normalises later once PsA establishes.[54] Other biomarkers associated with PsA are given in Table 4.

Table 4.

Other biomarkers tested in relation to PsA

Disease condition	Potential biomarkers
PsA activity	hs-CRP, IL-6, IL-12, IL-10 and IL-1 receptor antagonists[55]
Differentiating PsA from cutaneous psoriasis	Panel of hs-CRP, osteoprotegerin, MMP-3 and the CPII/C2C ratio[56] ITGB5, M2BP and CRP; IL-18, IL-20, MMP-3 and COMP[57]
Diagnosis of PsA	Autoantibodies to LL37 and ADAMTSL5 along with antibodies against the PsA peptide[58]
Differentiating PsA from osteoarthritis-	Panel of COMP, resistin, MCP-1 and NGF[59]
Prediction of response to therapy in PsA patients	hs-CRP, plasma C3, apolipoprotein C-III, S100A12, IL-16, MPO, VEGF, pyridinoline, MMP-3, carcinoembryonic antigen, intercellular adhesion molecule 1 and macrophage inflammatory protein 1a[60,61]
PsA disease activity	miR-221-3p, miR-130a-3p, miR-146a-5p, miR-151-5p, miR-26a-5p and miR-21-5p[62]

COMP=cartilage oligomeric matrix protein, IL=interleukin, MMP-3=matrix metalloproteinase 3, VEGF=vascular endothelial growth factor, MCP-1=monocyte chemoattractant protein 1, NGF=nerve growth factor, MPO=myeloperoxidase

Biomarkers of Clinical Response to Biological and Systemic Therapies

Biologics for the treatment of psoriasis include T-cell agents (e.g., alefacept and efalizumab), TNF-α inhibitors (e.g., etanercept, infliximab, adalimumab), anti-IL-17 agents like secukinumab, ixekizumab and brodalumab, and the anti-p40 agent ustekinumab.[63]

C-reactive protein is the most widely studied biomarker to gauge the clinical response to TNF-α inhibitors, and the serum level of this molecule declines with treatment both in cutaneous and systemic psoriasis.[64,65] In Phase III PHOENIX-1 study, patients treated with ustekinumab demonstrated a decline in the levels of C-reactive protein, reflecting amelioration of the disease.[66] HLA-C*06:02, the primary susceptibility allele in psoriasis, showed a consistent association with response to ustekinumab. This can be used as a stratification tool to select ustekinumab responders compared to TNF-α antagonists[67] before starting therapy.

Andres-Ejarque et al.[68] used a ‘hypothesis-free’ approach, which identified enhanced NF-kB signalling in type 2 dendritic cells as a biomarker of TNF-α inhibitor non-response.

Serum markers like C-reactive protein, VEGF and resistin were reduced proportionate to the reduction in PASI score in response to treatment in 42 patients with severe psoriasis treated with various systemic therapies like fumaric acid esters, cyclosporine A, methotrexate, etanercept, adalimumab or ustekinumab.[69]

Zaba et al.[70] reported downregulation of genes in the Th17 pathway in etanercept responders.

Micoarray analysis of peripheral blood mononuclear cells using 23 genes was done to predict the treatment response to alefacept in a series of 16 patients with moderate to severe psoriasis. These results paved the way for classifying alefacept responders a priori based on the baseline gene expression in Peripheral blood mononuclear cells (PBMCs).[71]

Whole-genome transcriptome profiling based on microarray data from 62 lesional skin samples was used to characterise the inflammatory and cytokine network in psoriatic plaques. Patients were stratified into strong, moderate and weak according to the inflammatory gene expression. They were further divided into two subgroups based on the expression of IL-13. Once this outcome is validated in larger studies, it will be useful in personalising psoriasis treatments.[72]

Recently, seven differentially expressed proteins (ANXA6, RPS27A, EZR, FN1, GPV, XRCC6 and STOM) associated with the NF-κB and Janus kinase-signal transducers and activators of transcription (JAK–STAT) pathways, neutrophil degranulation and platelet activation have been identified in Methotrexate (MTX) responders by Isobaric Tags for relative and absolute quantification (iTRAQ) technique. These proteins can serve as important biomarkers in predicting methotrexate response in psoriasis patients in the future.[73]

Th2 cells express thymus and activation regulated chemokine (TARC), which is a ligand of C–C chemokine receptor 4. Shibuya et al.[74] found that serum levels of TARC correlate inversely with PASI.[73] TARC levels also were higher in a group treated with secukinumab compared to Tumor Necrosis Factor Inhibitor (TNFi). Level of TARC was higher in patients with generalised pustular psoriasis[75] and it declined proportionately with effective Generalised Pustular Psoriasis (GPP) treatment.[75]

Platelet–lymphocyte complexes

Platelet–lymphocyte complexes (PLCs) have a high level of IL-17–secreting cells. They are also a marker of platelet activation. They remain high in untreated psoriasis cases and the levels show a proportionate decline in response to TNFi treatment. PLC is an important biomarker under consideration to identify TNFi responders.[76]

Neutrophil or platelet to lymphocyte ratio

Neutrophil lymphocyte ratio (NLR) and platelet lymphocyte ratio (PLR) are markers of systemic inflammation in psoriasis and psoriasis-associated atherosclerosis and metabolic syndrome. These two parameters have been investigated as surrogate markers of therapeutic response to TNFi in patients with psoriasis.[77]

Biomarkers to Monitor Adverse Effects of Specific Interventions

Liver fibrosis-associated tests

Liver function test has a sensitivity of 38% and a specificity of 83% for detection of liver fibrosis. The sensitivity and specificity values for other methods like Type III Procollagen Peptide (PIIINP) are 74% and 77%, respectively, for ultrasound are 55% and 49%, respectively, and for FibroScan VR are 60% and 80%, respectively.[78] PIIINP has limitations as a monitoring method for fibrosis because of false-positive results with other conditions like arthritis, post-myocardial infarction state and normal puberty state. It only detects ongoing hepatic fibrogenesis, but fails to diagnose established cirrhosis.

Enhanced liver fibrosis

Enhanced liver fibrosis (ELF) test measures serum levels of hyaluronic acid, Tissue Inhibitor of mettaloproteinases-1 (TIMP-1) and PIIINP by ELISA. This test has been found to be useful in monitoring hepatic fibrosis in psoriasis patients.[79] Ability of ELF test to detect liver fibrosis related to hepatitis C and B infection, nonalcoholic fatty liver disease, primary biliary cirrhosis and methotrexate-induced liver injury has also been evaluated.[79] ELF was found to outperform PIIINP measurements in diagnosing liver fibrosis in patients with rheumatoid arthritis, psoriasis and PsA. The ELF panel test has a sensitivity of 90% and a negative predictive value of 92% for diagnosis of hepatic fibrosis.[80]

Hepascore panel was anlaysed in patients with long-term use of methotrexate by Wang et al.[81] Hepascore is a composite score that predicts fibrosis using the serum levels of bilirubin, α2-macroglobulin, hyaluronic acid and c-glutamyl transpeptidase. It predicts the severity of liver fibrosis in alcoholic and non-alcoholic liver diseases and chronic hepatitis B. Higher baseline level of Hepascore is a predictor of higher risks for adverse liver-related outcomes as well as overall mortality. However, Chládek et al.[82] proposed that psoriasis disease activity itself affects the hyaluronic acid levels and Hepascore values. Hence, PIIINP and FibroTest were suggested as more stable biomarkers for assessing liver fibrosis in psoriasis patients receiving methotrexate when compared to Hepascore panel. Lynch et al.[83] proposed that transient elastography and FibroTest are future tools for the assessment of hepatic fibrosis in psoriasis patients on methotrexate therapy.

Conclusion

So far, not a single biomarker has been approved as a definitive marker for the diagnosis or monitoring of psoriasis or its associated comorbidities. The proposed list of candidate biomarkers includes a list of genetic, tissue and soluble markers. However, most of them are not a part of the standard practice. It makes more sense to rely on a thorough history taking and physical examination and various established clinical scoring systems to monitor disease status and therapeutic response till we have validated and approved biomarkers available with us.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.