Psoriatic arthritis: a complex

disease

– analyses on genetic and serological

biomarkers and of comorbidity

Kristina Juneblad

Department or Public Health and Clinical Medicine, Rheumatology

Umeå 2018

Responsible publisher under Swedish law: the Dean of the Medical Faculty This work is protected by the Swedish Copyright Legislation (Act 1960:729) Dissertation for PhD ISBN: 978-91-7601-910-8 ISSN: 0364-6612 New series no: 1968 Electronic version available at: http://umu.diva-portal.org/ Printed by: UmU Print Service, Umeå University Umeå, Sweden 2018 Figure 1 Reproduction, based on Fig 1 in (McGonagle and McDermott, 2006)

To my family

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Table of Contents

Abstract ............................................................................................ iii

Abbreviations .................................................................................... v

List of papers .................................................................................. vii

Sammanfattning på svenska .......................................................... viii

Background ........................................................................................ 1 Psoriatic Arthritis ............................................................................................................. 1 Classification and diagnostic criteria ............................................................................... 1 Disease expression ............................................................................................................ 1 Treatment.......................................................................................................................... 5

Pharmacological treatment; ..................................................................................... 5 Treatment goals ........................................................................................................ 6

Epidemiology .................................................................................................................... 7 Aetiology .......................................................................................................................... 8

The immune system ................................................................................................... 8 Soluble biomarkers .................................................................................................. 13 Genetics of Pso and PsA ........................................................................................... 15

Prognosis ........................................................................................................................ 20 Co-morbidity .................................................................................................................. 20

Aims ................................................................................................ 23

Patients and Methods ...................................................................... 24 Patients and controls ..................................................................................................... 24 Clinical characteristics .................................................................................................... 27 Laboratory tests ............................................................................................................. 29

Genotyping .............................................................................................................. 29 Measurement of serologic biomarkers .................................................................. 30

Statistical analysis.......................................................................................................... 30

Study design .................................................................................... 32 Paper I ............................................................................................................................ 32 Paper II........................................................................................................................... 32 Paper III ......................................................................................................................... 32 Paper IV ......................................................................................................................... 33

Results and discussion .................................................................... 34 Genetic analyses (Papers I and II) ................................................................................ 34 Analysis of biomarkers (Paper III) ............................................................................... 39

Variables reflecting disease activity at clinical examination ............................... 40 Serological biomarkers in relation to disease phenotypes ................................... 43

Investigation of mortality, cause of death and incidence of acute cardiovascular disease

in patients with PsA compared with the general population (Paper IV) ..................... 45 Mortality and cause of death .................................................................................. 45 Factors associated with death in PsA patients ...................................................... 46 Cardiovascular Events ............................................................................................ 48

ii

Factors associated with CVE among PsA patients ............................................... 48 Concluding remarks ....................................................................................................... 51

Conclusions ..................................................................................... 53

Future perspectives ......................................................................... 54

Acknowledgements ......................................................................... 56

References ...................................................................................... 58

iii

Abstract

Psoriatic Arthritis (PsA) is a heterogonous inflammatory arthritis associated with

psoriasis. The disease leads to inflammation of peripheral joints, axial skeleton

and/or enthesites, and can result in severe destruction of affected joints. In

contrast to rheumatoid arthritis (RA), most individuals with PsA are sero-

negative for rheumatoid factor (RF) and/or anti-citrullinated protein/peptide

antibodies (ACPA) and the distal interphalangeal (DIP) joints are often involved.

Dactylitis, a diffuse swelling of an entire digit (finger or toe), is also common.

Traditional markers of systemic inflammation, such as erythrocyte sedimentation

rate (ESR) and/or C-reactive protein (CRP) are elevated in only 50% of the

individuals with PsA. Underlying genetic factors are considered important for

the aetiology, disease expression and prognosis of PsA. To date no specific

biomarker for PsA disease or disease activity/severity is available and there is a

need for diagnostic and prognostic tools to meet the challenge of early diagnosis

and assessment of disease severity.

An increased risk of co-morbidity, particularly cardiovascular disease (CVD), has

been demonstrated in patients suffering from different rheumatic diseases, e.g.

systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA).

Corresponding data for patients with PsA are more limited, but evidence exists

for an increased risk of mortality and cardiovascular morbidity. However,

published results are conflicting and heterogeneity among studies makes

interpretation of data difficult.

The aim of this study was to investigate genetic and serological biomarkers, and

also mortality and cardiovascular comorbidity, in different phenotypes of PsA

and in comparison with healthy controls.

Patients with PsA were included between 1995 and 2015, the majority from the

county of Västerbotten, except for two cohorts from Örnsköldsvik (n=55) and

Östersund (n=98).

The genetic polymorphism PTPN22+1858C/T, previously found to be associated

with several autoimmune diseases, was also found associated with PsA, the

results were later confirmed in a genome wide association study (GWAS).

Additionally, among PsA patients, the minor allele, T, was associated with the

number of deformed joints and dactylitis (Paper I).

Genetic polymorphisms in genes related to the inflammasome were also

investigated, both in comparison with healthy controls and in relation to different

phenotypes of PsA (Paper II). An association was identified between patients with

iv

PsA and the polymorphism CARD8-C10X in comparison with controls. In

addition, associations between various inflammasome polymorphisms and

different clinical phenotypes of PsA were detected.

To investigate the relation of serological biomarkers and PsA, individuals with

blood samples collected in conjunction with clinical investigation were selected

(Paper III). Associations with different biomarkers and different clinical

phenotypes of PsA were identified In addition, associations were found with

different biomarkers and patients with moderate/high disease activity at clinical

investigation, confirming the inflammatory nature of the disease.

Mortality and incidence of acute cardiovascular disease were investigated with

standardized mortality rate-ratio (SMR) and standardized incidence ratio (SIR)

compared with the general population of Västerbotten (Paper IV). An increased

SMR for diseases of the circulatory system in PsA compared with controls was

found. Among PsA patients, death was associated with a composite disease

activity index (DAI) and with a disease phenotype including both axial- and

peripheral joint involvement.

In conclusion, associations were found with different clinical phenotypes of PsA,

both with genetic polymorphisms and serological biomarkers that confirm the

inflammatory nature of the disease and illustrate the disease heterogeneity. As in

many other inflammatory diseases, an increased cardiovascular mortality was

found that highlights the importance of considering cardiovascular risk factors in

patients with PsA.

v

Abbreviations

ACPA Anti-citrullinated protein/peptide antibodies ACR American Collage of Rheumatology AIM Absent in melanoma APC Antigen presenting cell AS Ankylosing spondylitis ASC Apoptosis-associated speck-like protein containing a C-terminal

caspase recruitment domain B-cell B-lymphocyte BcR B-cell receptor bDMARD Biologic disease modifying anti-rheumatic drug bFGF Basic fibroblast growth factor BMI Body mass index CARD8 caspase recruitment domain-containing protein 8 CASPAR Classification criteria for psoriatic arthritis CCL Chemokine of CC family CD Cluster of differentiation CI Confidence interval CLP Common lymphoid progenitor cell COMP Cartilage oligomeric matrix protein CPII:C2C C-propeptide of Type II collagen (CPII): collagen fragment

neoepitopes Col2-3/4(long mono) (C2C) CRP C-reactive protein csDMARD Conventional synthetic disease modifying anti-rheumatic drugs CTL Cytotoxic T-cell CVD Cardiovascular disease CVE Cardiovascular event CXCL Chemokine of CXC family DAI Disease activity index DAMP Danger-associated molecular pattern DIP joint Distal interphalangeal joint DMARD Disease modifying anti-rheumatic drug EGF Epidermal growth factor ESR Erythrocyte sedimentation rate ET-1 Endotelin-1 EULAR European league against rheumatism FCAS Familial cold-induced auto-inflammatory syndrome FGF Fibroblast growth factor Flt-1 Fms-like tyrosine kinase 1 G-CSF Granulocyte-colony stimulating factor GM-CSF Granulocyte macrophage-colony stimulating factor GRAPPA Group for research and assessment of psoriasis and psoriatic arthritis GWAS Genome wide association study HAQ Health assessment questionnaire HLA Human leukocyte antigen HT Hypertension IBD Inflammatory bowel disease ICAM Intercellular adhesion molecule ICD International classification of diseases IFN Interferon IL Interleukin IL-1ra Interleukin 1 receptor antagonist

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ILC Innate lymphoid cells IP-10 Interferon gamma-induced protein 10 (CXCL10) ITGβ5 Integrin-β5 M2BP Mac-2-binding protein MCP joint Metacarpophalangeal joint MDA Minimal disease activity MHC Major histocompatibility complex MIP Macrophage inflammatory protein MMP Metalloproteinase MRI Magnetic resonance investigation MTP joint Metatarsophalangeal joint MWS Muckle-Wells syndrome NK-cell Natural killer cell NLR NOD-like receptor NLRP1 NOD-like receptor family, pyrin domain containing 1 NLRP3 NOD-like receptor family, pyrin domain containing 3 NSAID Non-steroidal anti-inflammatory drug OPLS-DA Orthogonal partial least squares discriminant analysis OR Odds ratio PAMP Pathogen-associated molecular pattern PASI Psoriasis area and severity index PIGF Placental growth factor PIP joint Proximal interphalangeal joint PPP Pustulosis palmoplantaris PROM Patient related outcome measure PsA Psoriatic arthritis Pso Psoriasis of the skin PTPN22 protein tyrosine phosphatase non-receptor 22 RA Rheumatoid arthritis RANKL Receptor activator of nuclear factor kappa-Β ligand RF Rheumatoid factor SAA Serum amyloid A SAPHO Synovitis acne pustulosis hyperostosis syndrome SI-joint Sacro-iliaca joint sICAM Soluble intercellular adhesion molecule SIR Standardized incidence rate ratio SLE Systemic lupus erythematosus SMR Standardized mortality rate ratio SNP Single nucleotide polymorphism SpA Spondylarthropathy STAT Signal transducer and activator of transcription SwePsA Swedish Early Psoriatic Arthritis Register T1D Type-1-diabetes T-cell T-lymphocyte TcR T-cell receptor TH T helper cell Tie-2 Tyrosine kinase 2 TNF Tumour necrosis factor TREG Regulatory T-cell tsDMARD Targeted synthetic disease modifying anti-rheumatic drug uSpA Undifferentiated spondylarthropathy VCAM Vascular cell adhesion molecule VEGF Vascular endothelial growth factor χ2 Chi-square

vii

List of papers

The thesis is based on the following papers that will be referred to by their roman

numerals:

I. Kristina Juneblad, Martin Johansson, Solbritt Rantapää-Dahlqvist

and Gerd-Marie Alenius. Association between the PTPN22+1858 C/T

polymorphism and psoriatic arthritis. Arthritis Res Ther 2011;13:R45

II. Kristina Juneblad, Linda Johansson, Solbritt Rantapää-Dahlqvist and

Gerd-Marie Alenius. Association between inflammasome-related

polymorphisms and Psoriatic arthritis. Manuscript

III. Kristina Juneblad, Solbritt Ranstapää-Dahlqvist and Gerd-Marie

Alenius. Expression of biomarkers in relation to disease manifestations

of Psoriatic Arthritis. Submitted

IV. Kristina Juneblad, Solbritt Ranstapää-Dahlqvist and Gerd-Marie

Alenius. Disease activity and increased risk of cardiovascular death

among patients with Psoriatic Arthritis. J Rheumatol 2016;43:2155-61.

Papers I and IV are reprinted with the kind permission of the publishers.

viii

Sammanfattning på svenska

Psoriasisartrit (PsA) är en inflammatorisk ledsjukdom associerad med

hudsjukdomen psoriasis (Pso). PsA har en mångfacetterad sjukdomsbild med

inflammation i leder, rygg och/eller entesit (inflammation där ligament, senor

och ledkapslar fäster i benet) och kan leda till destruktion av drabbade leder med

påverkan på funktion och livskvalitet. Till skillnad från reumatoid artrit (RA) är

reumatoid faktorn (RF) samt antikroppar mot citrullinerade proteiner (ACPA)

vanligen negativa och det är vanligt att de yttersta lederna i fingrar och tår (DIP-

lederna) drabbas. Vanligt förekommande är också inflammation i ett helt finger

eller tå, s.k. daktylit. Traditionella markörer för sjukdomsaktiviteten mätt med

sänka (SR) och CRP är endast förhöjda hos ca 50 % av individer med PsA.

Bakomliggande genetiska faktorer som reglerar immunologiska och möjligen

också vaskulära uttryck anses vara av betydelse för etiologi, sjukdomsuttryck och

prognos vid Pso och PsA, med en betydande riskökning (ca 40 gånger ökad risk)

att insjukna i PsA om man har en förstagradssläkting med sjukdomen. I nuläget

finns inga tillgängliga biomarkörer för att mäta sjukdomsaktivitet och förutse

sjukdomsförlopp, varken genetiska eller serologiska, och det finns ett stort behov

av diagnostiska och prognostiska faktorer för att ställa tidig diagnos och bedöma

sjukdomens svårighetsgrad.

Under senare år har studier visat på en ökad risk för samsjuklighet, särskilt vad

gäller kardiovaskulär sjukdom, hos patienter med reumatologiska sjukdomar,

som t ex systemisk lupus erytematosus (SLE) och RA. Det finns färre studier

avseende PsA, men det finns stöd för att patienter med Pso och PsA har en ökad

samsjuklighet med engagemang av andra organsystem än hud och leder och en

översjuklighet och överdödlighet i kardiovaskulära sjukdomar. Resultaten är

dock inte entydiga och det finns en stor skillnad mellan olika studier och

studieupplägg som försvårar tolkningen av data.

Syftet med denna avhandling var att studera genetiska och serologiska markörer

samt dödlighet och kardiovaskulär samsjuklighet hos patienter med PsA, både i

jämförelse med friska kontroller och vid olika sjukdomsuttryck av PsA.

I studierna ingår totalt 856 individer med PsA som inkluderats mellan 1995-2015.

De flesta individerna är från Västerbotten, men två delpopulationer från

Östersund (n=98) och Örnsköldsvik (n=55) ingår i studie II.

Studie I och II innehåller den genetiska delen av studien. I delarbete I

undersöktes den genetiska polymorfin, PTPN22+1858C/T som tidigare visat

association med olika autoimmuna sjukdomar. Resultaten visade en association

ix

mellan PTPN22+1858 C/T och PsA i jämförelse med kontroller och bland

patienterna med PsA syntes en association med daktylit och antal deformerade

leder, vilket skulle kunna tyda på en koppling till en svårare sjukdomsbild.

Associationen mellan PTPN22+1858C/T och PsA har senare bekräftats i en stor

genome wide association study (GWAS). I studie II undersöktes olika genetiska

polymorfier i gener relaterade till det interleukin 1β-reglerande

proteinkomplexet, inflammasomen som under senare år har visat intressanta

kopplingar till olika inflammatoriska sjukdomar, t ex RA och Pso. Resultaten

visade association mellan en av polymorfierna, CARD8-C10X och PsA i

jämförelse med kontroller och resultaten visade också association mellan

polymorfier i andra inflammasomgener och olika sjukdomsmanifestationer av

PsA.

För att undersöka serologiska biomarkörer valdes de individer ut som hade

lämnat blodprover i samband med klinisk undersökning (Studie III). Trettionio

olika serologiska biomarkörer analyserades och jämfördes med olika

sjukdomsuttryck hos PsA patienterna och också i jämförelse med friska

kontroller. Resultaten visade association mellan olika biomarkörer och olika

sjukdomsmanifestationer, t ex PsA som involverar ryggen (axial sjukdom), PsA

som engagerar många leder (polyartrit) och PsA patienter som förskrivits

biologiskt läkemedel. Resultaten visade också association för några biomarkörer

och måttlig till hög sjukdomsaktivitet, vilket bekräftar PsA sjukdomens

inflammatoriska natur.

I studie IV undersöktes dödlighet, dödsorsaker och incidensen av akut hjärt-

/kärlsjukdom (akut hjärtinfarkt och stroke) i jämförelse med

normalbefolkningen i Västerbotten. Resultaten visade en ökad dödlighet (SMR) i

cirkulationsorganens sjukdomar (ICD kod; I00-I99) hos patienter med PsA

jämfört med kontroller. Hos PsA patienterna var sjukdomsaktiviteten mätt med

ett kompositindex, DAI, associerat med ökad dödlighet och resultaten visade

också association till en sjukdom med engagemang av både rygg och perifera

leder, som möjligen indikerar en ökad sjukdomsbörda.

Sammanfattningsvis visar resultaten av studierna i denna avhandling på

intressanta associationer till olika kliniska sjukdomsuttryck hos PsA patienter,

både för genetiska polymorfier och serologiska biomarkörer. Resultaten

bekräftar den inflammatoriska naturen hos PsA och illustrerar sjukdomens

heterogenitet och komplexitet. Som vid andra inflammatoriska sjukdomar

noterades ökad dödlighet i cirkulationsorganens sjukdomar, vilket stärker

behovet av att beakta och behandla kardiovaskulära riskfaktorer hos individer

med PsA.

x

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Background

Psoriatic Arthritis

Psoriatic arthritis (PsA) is a chronic inflammatory musculoskeletal disease

associated with cutaneous psoriasis (Pso) (Boehncke and Schon 2015). The

disease was probably first described in 1818 by Alibert (Moll and Wright 1973),

but it was not until 1964 that PsA was recognized as a separate disease by the

American Rheumatism Association (now the American College of Rheumatology)

(ACR) (Coates and Helliwell 2017).

Classification and diagnostic criteria

Due to similarities among the diseases, PsA is classified among the sero-negative

spondylarthropathies (SpA) including ankylosing spondylitis (AS), reactive

arthritis, arthritis and spondylitis associated with inflammatory bowel disease

(IBD) and undifferentiated spondylarthropathy (uSpA) (Dougados, van der

Linden et al. 1991). Due to the heterogeneity of the PsA disease and overlap in

disease pattern between other inflammatory arthropathies, disease classification

and diagnostic criteria have been a topic of debate. The initial criteria proposed

by Moll and Wright in 1973, defined PsA as an inflammatory arthritis in the

presence of psoriasis with usually an absence of rheumatoid factor (Moll and

Wright 1973). In the Moll and Wright criteria, PsA is divided into five sub-groups

defined by disease characteristics (Table 1). In most cases of PsA, psoriasis skin

disease (Pso) precedes the onset of joint disease, but in approximately 10-15%

skin disease develops after the onset of musculoskeletal symptoms (Coates and

Helliwell 2017) and in these cases the Moll and Wright criteria does not apply.

Additionally, PsA can present with polyenthesitis without arthritis, and neither

in these cases, the Moll and Wright criteria apply. Therefore, new consensus

criteria have been developed, e.g. the Classification Criteria for Psoriatic Arthritis

(CASPAR), and these criteria are now being applied in most clinical studies

(Taylor, Gladman et al. 2006) (Table 2).

Disease expression

Psoriatic arthritis is a heterogeneous inflammatory arthritis, with a varied disease

pattern, not only between patients, but also within an individual patient over

time. Disease expression can vary from a mild mono-/oligoarthritis to severe

erosive polyarthritis comparable with rheumatoid arthritis (RA), with or without

involvement of the axial joints and/or manifestations such as enthesitis and

2

dactylitis (Moll and Wright 1973, Dougados, van der Linden et al. 1991, Helliwell

2009). Contrary to RA, PsA disease often include DIP-joint arthritis. Also in

contrast with RA, most individuals with PsA are sero-negative for rheumatoid

factor (RF) and anti-citrullinated protein/peptide antibodies (ACPA) (Alenius,

Berglin et al. 2006, Taylor, Gladman et al. 2006).

Table 1. The Moll and Wright criteria for PsA

Main criteria; Presence of skin psoriasis in combination with

inflammatory articular disease affecting peripheral

joint and/or spine. Rheumatoid factor (RF) usually

negative.

Sub-classes according to

Moll & Wright

- DIP joint disease Exclusive DIP-joint involvement

- Axial disease Predominantly axial disease

- Mono-/oligoarthritis Involvement of ≤ 4 joints when clinically active PsA

disease

- Polyarthritis Involvement of ≥ 5 joints when clinically active PsA

disease

- Arthritis mutilans Severe, erosive, mutilating disease phenotype

Table 2. The Classification criteria for Psoriatic Arthritis (CASPAR) criteria

(Taylor, Gladman et al. 2006)

Main criteria: Documented inflammatory articular disease (joint, spine or entheseal).

+ ≥ 3 points of the following additional criteria

Active skin psoriasis (2p), own history of psoriasis (1p) or a first- or second degree relative with psoriasis (1p)

Typical psoriatic nail changes, including onycholysis, pitting or hyperkeratosis (1p)

Negative test for rheumatoid factor (RF), latex not included. (1p)

Either current dactylitis, defined as swelling of an entire digit, or a history of dactylitis recorded by a rheumatologist (1p)

Radiographic evidence of juxta-articular new bone formation, appearing as ill-defined ossification near joint margins (but excluding osteophyte formation) on plain radiographs of the hand or foot (1p)

3

Since PsA does not always present with increased inflammatory parameters,

erythrocyte sedimentation rate (ESR) and/or C-reactive protein (CRP) is elevated

in only approximately 50% of cases (Gladman, Shuckett et al. 1987, Coates and

Helliwell 2017) and no serological markers for disease are known, it is difficult in

early stages of disease to predict the severity of disease or its progress.

Psoriasis skin disease is also highly variable. Five types of skin psoriasis have been

described; the most common being plaque psoriasis (psoriasis vulgaris) (90% of

Pso); the others being guttate psoriasis; invers psoriasis (intertriginous or

flexural), occurring in skin folds; pustular psoriasis, either pustulosis palmo-

plantaris (PPP) or generalised pustular psoriasis; and erythrodermic psoriasis, a

rare but serious condition (Boehncke and Schon 2015).

Although, among patients with Pso, a more severe skin disease is a risk factor for

developing PsA (Scarpa, Oriente et al. 1984, Gelfand, Gladman et al. 2005,

Wilson, Icen et al. 2009), most patients with PsA have a mild or moderate skin

disease (Cohen, Reda et al. 1999). In addition, approximately 10-15% develop

arthritis prior to Pso and given the heterogeneity in disease expression, differing

PsA from other arthropathies, e.g. RA can be difficult in those cases. Extensive

clinical examination of the skin is essential to discover Pso in hidden places such

as the scalp, peri-umbilical area and natal cleft. Psoriatic nail disease, e.g. pitting,

onycholysis and hyperkeratosis is also common in PsA (Coates and Helliwell

2017). Interestingly, scalp lesions, nail dystrophy and intergluteal/perianal

lesions have been found most likely to be associated with the development of PsA

among patients with Pso (Wilson, Icen et al. 2009). Another challenge in the

diagnosis of PsA, especially among patients with Pso, is to differentiate between

an inflammatory arthritis and osteoarthritis/mechanical pain and between

polyenthesitis in PsA and fibromyalgia (Mease 2011, Eder, Polachek et al. 2017,

Marchesoni, De Marco et al. 2018). Moreover, early diagnosis is important,

especially in the case of destructive disease phenotype, to prevent the structural

damage that can occur early in the disease (Theander, Husmark et al. 2014,

Haroon, Gallagher et al. 2015).

Radiological findings in PsA are different from those associated with RA, and are

a consequence of a combination of bone resorption/erosions, similar to RA, but

also new-bone formation. Typical changes include; whittling of phalanges distal

bone ends, cupping of the proximal bone ends resulting in the typical pencil-in-

cup appearance on radiographs, erosion of terminal phalangeal tufts (acro-

osteolysis), sacroiliitis and spondylitis. Also typical are the lack of symmetry,

predilection for DIP- and PIP joints over MCP/MTP joints and severe destruction

of isolated small joints (Moll and Wright 1973). To detect the early signs of active

inflammation, especially in the spine and sacro-iliaca (SI) joints, Magnetic

Resonance Investigation (MRI) is used.

4

Dactylitis, a diffuse swelling of an entire digit (finger or toe), is a characteristic

feature of PsA with a high specificity for spondylarthropathies, is considered a

marker of disease severity (Brockbank, Stein et al. 2005, Geijer, Lindqvist et al.

2015, Mease, Karki et al. 2017). Dactylitis occurs in approximately 32-48% of

patients with PsA (Liu, Yeh et al. 2014). Imaging with ultrasound and MRI have

shown involvement of soft tissue thickening, tenosynovitis, enthesitis, synovitis

and the palmar/plantar plate in dactylitis (Sakkas, Alexiou et al. 2013,

Ostergaard, Eder et al. 2016) and in the DIP-joints, MRI has visualized

inflammation extending to the nail bed suggesting an association between

enthesitis, dactylitis and the nail (Ostergaard, Eder et al. 2016). Both dactylitis

and psoriatic nail disease are disease phenotypes included in the CASPAR criteria

(Table 2).

It has been hypothesized that the primary inflammatory site of PsA and other

SpAs are the enthesites, the site where tendons, ligaments and joint capsules

attach to bones (McGonagle, Gibbon et al. 1998). Evidence for the hypothesis

comes from radiological and MRI examinations with signs of inflammation, new

bone formation and erosions at entheseal sites, both early and late in the disease

process (McGonagle, Gibbon et al. 1998, Braun, Khan et al. 2000). Enthesitis is

common in patients with PsA with a prevalence of approximately 35% (Gladman

and Chandran 2011, Polachek, Li et al. 2017) and PsA patients with enthesitis

shows greater disease activity, poorer functional status (measured by Health

Assessment questionnaire (HAQ)), greater pain, fatigue and activity impairment

compared with patients without enthesitis (Mease, Karki et al. 2017).

Non-specific musculoskeletal symptoms and pain are common in patients with

Pso and PsA. Patients can present with tender joints and diffuse pain on and

around enthesites, both peripheral and axial, with no objective signs of active

inflammation, such as swelling, redness, heat or signs of active inflammation on

ultrasound or MR-scan of axial skeleton. These symptom occur both in patients

with and without established joint disease. The mechanism for this is unclear.

Recently, among patients with Pso, non-specific musculoskeletal symptoms were

evaluated to assess whether they could predict development of PsA. Joint pain in

women, fatigue and duration of morning joint stiffness and the gradual

worsening of symptoms predicted the development of PsA, but the authors stress

the clinical challenge in separating pain from osteoarthritis and mechanical pain

(Eder, Polachek et al. 2017). Pain is a common symptom in inflammatory arthritis

and has been considered to be mainly of peripheral nociceptive origin (Schaible,

von Banchet et al. 2010). Although in some cases, patients develop pain

hypersensitivity and chronic pain that persists after the inflammation has been

treated (Woolf 2011, Rifbjerg-Madsen, Christensen et al. 2017). In a recent

Danish study, pain was investigated in patients with RA, PsA and SpA, both with

traditional visual analogue scale (VAS) and an index specific for pain with

5

neuropathic features (Rifbjerg-Madsen, Christensen et al. 2017). They found that

50% of the patients had significant pain despite no objective signs of

inflammation and 20% had indications of neuropathic pain and patients with PsA

had a higher frequency of pain with neuropathic features compared with RA

(Rifbjerg-Madsen, Christensen et al. 2017).

Treatment

The complexity and heterogeneity of PsA can lead to challenges in the selection

of treatment. Both the skin and joint disease needs consideration, as does the

associated diseases, such as uveitis and inflammatory bowel disease. Also

important is to consider are the different associated comorbidities, such as

cardiovascular disease (CVD) and metabolic syndrome (Coates, Kavanaugh et al.

2016). Thus, several medical specialties are often involved in the management of

PsA. In addition, physical activity to preserve function and prevent comorbidities

are essential aspect of the basic treatment of PsA and therefore the involvement

of physiotherapists and occupational therapists in the early stages of disease is of

importance.

Pharmacological treatment;

The different disease pattern and severity determines the treatment strategy for

patients with PsA and a step up strategy is usually applied. Recently, new

recommendations from both the European League Against Rheumatism

(EULAR) and the Group for Research and Assessment of Psoriasis and Psoriatic

Arthritis (GRAPPA) have been updated (Coates, Kavanaugh et al. 2016, Gossec,

Smolen et al. 2016, Coates and Helliwell 2017). The overarching principles of the

two publications are similar, but the task forces behind were somewhat different

in composition. The EULAR group consisted almost exclusively of

rheumatologists whilst many members of the GRAPPA task force were

dermatologists resulting in specifically also considering dermatological aspects

such as skin and nail disease while the EULAR task force focused mainly on

musculoskeletal aspects (Gossec, Coates et al. 2016). Thus, the EULAR

recommendations focus on the treatment of the musculoskeletal aspects and

recommend consulting a dermatologist in PsA patients with predominantly skin

disease.

For the musculoskeletal aspects of PsA, the basic treatment, if no

contraindications are evident, is non-steroidal anti-inflammatory drugs

(NSAIDs), used for pain, stiffness and mild cases of inflammation, in initial stages

often combined with intra-articular corticosteroid injections. Oral steroids

should be used with caution due to possible worsening of skin-disease upon

6

cessation. In mild cases of PsA with mono-/oligoarthritic disease pattern the

combination of NSAID and intra-articular injections can be sufficient to control

the disease. If not, or if negative prognostic factors are evident at diagnosis (e.g.

polyarthritic disease, radiographic damage, elevated acute phase reactants,

dactylitis) conventional synthetic disease modifying anti-rheumatic drugs

(csDMARDs) are added to control the disease. Methotrexate is usually the first

choice of csDMARD unless contraindicated. Other used csDMARDs, either as

single treatment or in combinations are sulfasalazine, leflunomide and

cyclosporine, and less commonly intramuscular myocrisin and plaquenil. If

predominantly axial disease, treatment with csDMARDs is not included in either

the EULAR or the GRAPPA recommendation, but in individual cases, csDMARDs

can be beneficial.

If csDMARDs are insufficient or not tolerated, the next treatment step involves

different biological agents (bDMARDs) or a targeted synthetic DMARD

(tsDMARD). The term “biological” referring to the protocol for the production in

different cell types. The most commonly used bDMARDs are different drugs

targeting tumour necrosis factor (TNF), e.g. adalimumab, certolizumab

etanercept, golimumab and infliximab. In recent years, new biological drugs

targeting other molecules have been approved for treatment of PsA.

Ustekinumab, an inhibitor of interleukin (IL)-12/IL-23, originally approved for

Pso, has a good effect on skin disease but is generally considered less effective

than TNF- inhibitors in PsA (Coates and Helliwell 2017) and are thus considered

a second line of biological therapy. Also, based on the presumable importance of

(T helper cell) (TH)17-pathway in PsA-disease several drugs targeting IL-17 have

been developed, e.g. secukinumab and ixekinumab, both being monoclonal

antibodies against IL-17A with effect both on skin and joint disease. Recently, for

the first time in many years, a new oral drug, aprimelast, has been developed. It

is the first tsDMARD developed for PsA, generally considered having lower effect

compared with biological agents, but has a more favourable safety profile (Coates

and Helliwell 2017). Very recently, also another oral drug, a januskinase inhibitor

(tofacitinib), previously approved for RA, was approved for treatment of PsA.

Treatment goals

Treatment of PsA, as in RA, should aim at minimizing disease activity and avoid

long term complications secondary to disease and/or treatment. Recently, an

index to define minimal disease activity (MDA), considering the multiple disease

domains in PsA has been suggested as a treatment target (Coates, Fransen et al.

2010). In MDA, 7 domains are evaluated (tender joint count ≤ 1, swollen joint

count ≤ 1, enthesitis count ≤ 1, Psoriasis Area and Severity Index (PASI) ≤ 1 or

Body Surface Area (BSA) ≤ 3%, Health Assessment Questionnaire (HAQ) ≤ 0.5,

7

patients global VAS (0-100) ≤ 20 and patients pain VAS (0-100) ≤ 15). To achieve

MDA a patient should meet 5/7 criteria and for a patient to be in very low disease

activity an MDA score of 7/7 has been suggested (Coates and Helliwell 2016).

Additionally, in recent years, patient related outcome measures (PROMs), e.g.

fatigue, emotional well-being, sleep, health related quality of life etc have gained

a wider focus (Orbai, de Wit et al. 2017).

Epidemiology

Psoriatic arthritis affects men and women equally (Gladman 1994) with the exact

prevalence of PsA being unknown. Psoriasis of the skin has as a prevalence of 0.6-

4.8 % and varies between populations (Setty and Choi 2007) and of patients with

Pso, 10-45% also has PsA (Moll and Wright 1973, Alenius, Stenberg et al. 2002).

In a previous study (Alenius, Stenberg et al. 2002) the prevalence of PsA among

patients with Pso was investigated. In that study 33% among Pso patients were

diagnosed by a rheumatologist as having peripheral and/or axial arthritis, of

these 45% had not previously been diagnosed (Alenius, Stenberg et al. 2002). In

a very recent meta-analysis, the prevalence of PsA among Pso was investigated

and a pooled prevalence of 19.7% was detected with a higher prevalence of 24.6%

in patients with moderate-to-severe skin disease (Alinaghi, Calov et al. 2018).

The cumulative incidence of PsA among patients with Pso have also been

investigated, where Wilson et al reported a cumulative incidence of 5.1% per 20

years (1970-1999) and Eder et al reported a yearly incidence of 2.8% (2006-

2014). Factors predicting PsA among Pso in the two studies were psoriatic nail

dystrophy, scalp lesions, intergluteal/perianal psoriasis, severe Pso, nail pitting,

uveitis and lower level of education (Wilson, Icen et al. 2009, Eder, Haddad et al.

2016).

A systematic review of articles published until 2006 shows population prevalence

of PsA varying from of 0.02%-0.42% in Europe/America and 0.001% in Japan.

Data on the PsA incidence were fewer and the same study showed incidence rates

ranging from from 0.1/100000 in Japan to 23.1/100000 in Finland (Alamanos,

Voulgari et al. 2008).

In a recent population based study from Denmark, the yearly incidence of PsA

from 1997 to 2011 was investigated (Egeberg, Kristensen et al. 2017). The

incidence increased over time from 7.3/100000 in 1997 to a maximum of

27.3/100000 in 2010, according to the authors, possible explanations to the

increase being greater attention by patients and physicians, availability of

classification criteria and increased awareness of the need for early treatment. In

8

their study, the prevalence in individuals ≥18 years and diagnosed by

rheumatologists was 0.20% (Egeberg, Kristensen et al. 2017).

Aetiology

The precise aetiology of PsA is unknown. Environmental factors such as

streptococcal pharyngitis, medical drugs, stressful life events and physical trauma

are known environmental triggers for Pso. The Köbner phenomenon is a known

factor to develop psoriatic lesions at a site of skin injury and a connection with

physical trauma, reflecting a deep Köbner phenomenon, has been suggested to be

a risk factor for developing inflammatory arthritis in PsA (Pattison, Harrison et

al. 2008).

Synovia from patients with PsA show distinct features compared with those from

patients RA, at both microscopic level, with increased vascularity and fibrosis and

with respect to the cellular infiltrates, and expression of different cytokines

(Espinoza, Vasey et al. 1982, Reece, Canete et al. 1999, Fearon, Griosios et al.

2003). However, biopsies have shown comparable levels of pro-inflammatory

cytokines as in RA (van Kuijk, Reinders-Blankert et al. 2006).

Underlying genetic factors that regulate immunological and possibly also

vascular expression are considered important for aetiology, disease expression

and prognosis in Pso and PsA. A previous population study on the Icelandic

population has shown a significantly increased risk (39 times) of developing PsA,

if a first degree relative has the disease (Karason, Love et al. 2009), which can be

compared with the corresponding risk of developing psoriasis (8 times increased

risk) and RA (3 times increased risk) (Bluett and Barton 2012). Thus, evidence

exists for a strong genetic impact in PsA, making studies in the area of interest.

The immune system

The purpose of our immune system is to protect us from disease, e.g. harmful

pathogens and tumours. The immune system can be sub-divided into the

developmentally more ancient, innate immune system and the evolutionarily

younger adaptive immune system (Hedrich 2016). They are usually described as

two separate systems but a substantial communication between them is essential

for optimal function.

Inflammatory mediators

Cell to cell communication is important for the immune system and an important

role in this communication is mediated by cytokines and chemokines. Cytokines

9

are small proteins that are produced by one cell and affect other cells by binding

to specific receptors on the cell surface. Chemokines are also small proteins with

chemoattractant properties that stimulate migration and activation of different

cell types.

Innate immunity

The innate immune system is first line of defence against pathogens. It is non-

specific, lacks immunological memory but reacts quickly in response to outside

threats. In addition to physical (e.g. skin and mucosa) and chemical barriers (e.g.

anti-microbial substances from epithelia), it includes both cellular and humoral

components involved in detection and elimination of danger signals. Targets can

be of microbial origin and are recognized as pathogen-associated molecular

patterns (PAMPs), but also host molecules, danger-associated molecular patterns

(DAMPs). Cellular components of the innate immune system include monocytes

and macrophages, neutrophilic granulocytes, dendritic cells, natural killer cells

(NK-cells) and the recently discovered innate lymphoid cells (ILCs) (Hedrich

2016, Xiong and Turner 2018).

Innate lymphoid cells

Like antigen-receptor bearing T- and B-cells (described below), ILCs are derived

from common lymphoid progenitor cells (CLP), but they are devoid of any

antigen receptors. The first of these cells to be discovered were the NK-cells that

complements the cytotoxic, Cluster of differentiation (CD)8+ T-cells, in killing

infected, stressed or transformed cells (Eberl, Colonna et al. 2015). Apart from

NK-cells, ILCs are divided in three classes of non-cytotoxic, helper-like ILCs,

differentiated by their cytokine production and the transcription factors that

regulate their development and function. ILC1 cells produce mainly interferon

(IFN)-γ and tumour necrosis factor (TNF) and have been implicated in defence

against intra-cellular bacteria and parasites, ILC2 cells produce TH2-related

cytokines and are implicated in anti-helminth immunity, allergic inflammation

and tissue repair. ILC3 cells produce, depending on the stimulus, interleukin

(IL)-17A, IL17F, IL22, granulocyte macrophage-colony stimulating factor (GM-

CSF) and TNF and can promote anti-bacterial immunity, chronic inflammation

or tissue repair (Artis and Spits 2015). Thus, the different classes of ICLs largely

resembles the different classes of helper T-cells (TH) in the adaptive immune

system (TH1, TH2, TH17) (see below), but lacks corresponding antigen specific

receptors.

10

Adaptive immunity

If the innate immune system fails to clear an invading pathogen, the adaptive

immune system is activated. In contrast to the innate immune system, the

adaptive immune system matures during life, is highly specific, and can provide

long-lasting immunological memory. In addition, the adaptive immune system is

capable of separating self from non-self that, under normal circumstances, leads

to an immune response only to foreign antigens. Cells involved in the adaptive

immune system are T-lymphocytes (T-cells) and B-lymphocytes (B-cells).

B-cells

B-cells develop and mature in the bone marrow. B-cells interact with their

environment through a surface immunoglobulin, the B-cell receptor (BcR). When

naïve B-cells are activated by binding of their specific antigen to the BcR, they

differentiate into antibody producing cells, e.g. plasma cells and memory B-cells.

The main effector function of B-cells is the production of specific antibodies, but

B-cells are also important as cytokine secreting and antigen presenting cells.

T-cells

Like B-cells, T-cells develop in the bone marrow, but unlike B-cells differentiate

and mature in the thymus. All T-cells express the antigen recognizing T-cell

receptor (TcR). Most T-cells in humans express a TcR consisting of a heterodimer

of an α and β-receptor (αβ T-cells), but a smaller proportion consists of the highly

specialized γδ T-cells that is considered a part of the innate immune system

(Attaf, Legut et al. 2015). To be activated, T-cells require two signals, First, the

recognition of a specific foreign antigen presented together with the major

histocompatibility complex (MHC) on an antigen presenting cell (APC) and

secondly interaction of its co-receptor, CD28 (CTLA-4), with co-stimulatory

molecules (e.g. CD80/CD86) on the APC (Harris and Ronchese 1999).

T-cell subtypes

T-cells are sub-divided according to the expression of the co-receptors CD4 and

CD8.

When a CD8+ T-cell binds to and antigen presented on an MHC class I molecule

on an APS, the cell is activated and differentiate to a cytotoxic T-cells (CTL).

CD4+ T-cells recognize antigens presented together with MHC class II molecules

and upon activation differentiate to different T-helper sub-sets depending on the

type of cytokine produced and their immune regulatory function (Mosmann and

11

Coffman 1989, Harrington, Hatton et al. 2005). The TH1 cells mainly produce

IFN-γ and are involved in cell-mediated immunity. TH2 cells mainly produce IL-

4, IL-5, IL-13 and are involved in humoral immunity and allergic responses while

the more recently discovered TH17 cells mainly secrete IL-17A, IL-17F, IL-21 and

IL-22. The differentiation into the different TH sub-sets is mediated by several key

transcription factors (T-bet, signal transducer and activator of transcription

(STAT)-4 for TH1, GATA-3, STAT6 for TH2, and RORC for TH17) (Harrington,

Hatton et al. 2005). TH17 cells have been implicated to have an important role as

a driving force of autoimmune inflammation. The primary cytokine produced by

TH17 cells is IL-17A, a potent pro-inflammatory cytokine that stimulates the

production of IL-1 and TNF from human macrophages, induces secretion of IL-6

and IL-8 in synovial fibroblasts, induces up-regulation of receptor activator of

nuclear factor kappa-Β ligand (RANKL) and also promotes cartilage degradation

by inducing metalloproteinases (MMPs) and proteoglycan depletion (Leipe,

Grunke et al. 2010).

Recently a sub-type of T-cells, the TH9-cells, defined by the production of IL-9

have been described. They develop from naïve T-cells in the presence of TGF-β,

IL-4 and thymal stromal lymphopoitin. These cells have been implicated in

several inflammatory disorders, e.g. atopic diseases, helminth infections and

inflammatory bowel diseases. (Ciccia, Guggino et al. 2016).

Regulatory T-cells (TREG), previously known as T suppressor cells, have an

important role as regulators of the immune system and in immune tolerance.

TREGs are CD4+ T-cells that also express CD25 (IL-2 receptor alfa) (Sakaguchi,

Sakaguchi et al. 1995) and are also defined by the expression of transcription

factor FoxP3 (Fontenot, Gavin et al. 2003).

Auto-inflammation and autoimmunity

The role of the immune system is to protect from diseases or other threats.

Disturbances in the delicate control of this system can instead cause disease.

Autoimmune diseases are mediated by disturbances in the adaptive immune

system, involving autoreactive antibodies or T-lymphocytes. On the other end of

the spectrum of immunological diseases lies the monogenic auto-inflammatory

diseases, involving innate immunity. Most immunological diseases are

considered polygenic, multifactorial diseases and cannot be classified, purely as

being one or the other. In 2006 McGonagle and McDermott proposed a model

for classification of the immunological diseases where diseases are placed in a

continuum with the rare monogenic autoimmune and auto-inflammatory disease

at both ends and the more complex, polygenic diseases in between (McGonagle

and McDermott 2006) (Figur 1). In this model PsA is placed in the middle, and

12

thus considered as a mixed pattern disease involving both innate and adaptive

immunity.

Figure 1. The Immunological Disease Continuum. Published with courtesy of

professor McGonagle.

McGonagle, D., and M. F. McDermott. 2006. 'A proposed classification of the immunological diseases', PLoS Med. 2006 Aug;3(8):e297. doi: 10.1371/journal.pmed.0030297

The immune system in Pso and PsA

Cells from both the innate and adaptive immune system are involved in Pso and

PsA (Diani, Altomare et al. 2015, Coates, FitzGerald et al. 2016). According to

13

current knowledge of the natural history of Pso two phases of disease are

identified; an initiation phase, involving plasmocytoid and myeloid dendritic cells

(DCs) and a maintenance phase, also involving TH-cell of different subsets,

mainly TH1 and TH17 (Lowes, Suarez-Farinas et al. 2014, Diani, Altomare et al.

2015). The first phase is considered initiated by triggering events, e.g.

streptococcal infections, trauma and medication. In the second phase, autocrine

loops involving different T-cells, keratinocytes and the production inflammatory

cytokines result in chronic inflammation. Also in PsA, different T-cells subsets

are involved, but also macrophages are important (Coates, FitzGerald et al. 2016).

Other cells likely important are γδ T-cells and CD8+T-cells, both cell types

reported as sources of IL-17 in the skin and in synovial fluid (Menon, Gullick et

al. 2014, Diani, Altomare et al. 2015). Recently, cells from the innate immune

system, the ILCs, have been investigated in sera from PsA patients. The study

showed skewed ILC-homeostasis and higher numbers of ILC3, a potent producer

of IL-17/IL-22,that also correlated with PsA disease activity (Soare, Weber et al.

2018), highlighting the role of innate immunity in PsA.

Soluble biomarkers

Cytokines and chemokines in PsA

The PsA synovium, like psoriatic skin, is characterized by overexpression of

cytokines, e.g. TNF, INF-γ, IL-1β, IL-6, IL-10, IL-15 and IL-18 (de Vlam, Gottlieb

et al. 2014).

Serological cytokines have been investigated in PsA, and increased levels of IL-6,

IL-1 receptor antagonist (IL-1ra), soluble IL-2 receptor-alpha (IL-2sRα), INFα,

Pentraxin-3, MMP-3, CXCL10 (IP-10), IL-10, IL-13, CCL3 (MIP-1α), CCL4 (MIP-

1β), CCL11 (Eotaxin), epidermal growth factor (EGF), vascular endothelial growth

factor (VEGF) and fibroblast growth factor (FGF) have been reported (Spadaro,

Taccari et al. 1996, Elkayam, Yaron et al. 2000, Szodoray, Alex et al. 2007,

Alenius, Eriksson et al. 2009, Ramonda, Modesti et al. 2013, Abji, Pollock et al.

2016).

Soluble biomarkers are attractive as diagnostic tools due to their easy accessibility

in patients’ peripheral blood and there are some recent studies in PsA indicating

different biomarkers of relevance. However, for a biomarker to be relevant in

clinical practice it must correlate with disease activity and/or relate to disease

severity, be sensitive to changes in disease activity and/or relevant as a tool in

differentiating from closely related diseases. So far, several biomarkers have been

suggested in PsA, but as yet, none have reached clinical practice (Villanova, Di

Meglio et al. 2013).

14

Serological biomarkers as diagnostic tool and as markers for disease activity

In a Norwegian study by Szodoray et al., 23 soluble cytokines were investigated

in 43 PsA patients with polyarthritic phenotype and 25 healthy controls. In their

study significantly increased serum levels of INF-α, IL-10, IL-13, CCL3 (MIP-1α),

CCL4 (MIP-1β), CCL11 (Eotaxin), EGF, VEGF and FGF was detected in PsA and

G-CSF was decreased. Patients were also sub-grouped according to disease

activity, defined by the number of swollen joints at investigation and IFNα, IL-15

and IL-2 were able to discriminate between the three groups. They also

investigated combinations of cytokines and their differences between PsA and

controls and among PsA with different disease activity. With their model, the

factors best discriminating PsA from controls were IL-2, IL-12p40, IL-15, TNF-α,

MIP-1β, MIP-1α, IFN-α, FGF and Eotaxin and by using a discriminant function

analysis, EGF, INF-α, VEGF, MIP-1α and IL-12p40 discriminated between

controls and sub-sets of PsA with different disease activity (Szodoray, Alex et al.

2007). Also, in a small study by Fink et al. significantly higher concentration of

VEGF was detected in PsA with active disease (defined as ≥ 3 swollen and tender

joints) in comparison with inactive PsA and in healthy controls (Fink, Cauza et al.

2007).

In a study of Hansson and collegues, levels of S-Calprotectin (S-Cal) and CRP

were associated with PsA compared with controls in both mono-oligo arthritis

pattern and polyarthritic disease, with higher levels in PsA with a polyarthritic

disease pattern. In contrast, no associations were found for PsA with the other

cytokines and chemokines investigated (IL12, IL15, IL-16, IL17A, IL-18, IL22, IL-

33, CCL20, CXCL10 (IP-10) and CXCL12), but IL-12, IL-15, IL17A, IL-22, IL-33

correlated with number of tender joints (Hansson, Eriksson et al. 2014). Also, in

a study on clinically active PsA patients, S-calprotectin better related to

radiographic changes than ESR or CRP and also associated with moderate/high

disease activity (physicians’ global assessment and ≥3 swollen joints), but not

better than ESR or CRP (Madland, Larsen et al. 2007).

In two recent studies of Przepiera-Bedzak and co-workers different soluble

biomarkers (Il-18, soluble intercellular adhesion molecule-1 (sICAM-1), fetuin-A,

endotelin-1 (ET-1), IL-6, IL-23, VEGF and EGF have been investigated in patients

with different spondylarthropathies. In the first study, serum-levels of patients

were compared with those in healthy controls and associations were found for

levels of IL-18 and ankylosing spondylitis (AS), PsA, and synovitis acne pustulosis

hyperostosis syndrome (SAPHO) and also correlated with the levels of CRP,

VEGF and total cholesterol. In the second study, extra-articular manifestations

(acute anterior uveitis, IBD, skin psoriasis (Pso), psoriatic onycholysis and PPP)

was investigated, and their conclusion was that SpA-patients with increased

serum IL-18 and decreased ET-1 had an increased risk of extra-articular

15

symptoms (Przepiera-Bedzak, Fischer et al. 2016, Przepiera-Bedzak, Fischer et

al. 2016).

Different biomarkers in relation to treatment response in PsA have also been

studied. For example, in a study on 43 PsA-patients eligible for treatment with

TNF-inhibitors, baseline serum levels of MMP-3, VEGF and CRP were

significantly higher compared with healthy controls and the levels were reduced

after treatment with etanercept (Ramonda, Modesti et al. 2013). Also, in a study

by Chandran et al., levels of MMP-3 correlated with the response to treatment

with TNF-inhibitors and treatment response also correlated with a decrease in

MMP-3 and cartilage oligomeric matrix protein (COMP) after treatment

(Chandran, Shen et al. 2013).

Biomarkers to predict PsA in Pso

In a previous study, where patients with Pso with and without inflammatory joint

disease were compared, the levels of IL-6 was significantly higher in patients with

inflammatory joint disease, irrespective of elevated ESR and/or CRP (Alenius,

Eriksson et al. 2009). In addition, IL-6 levels were associated with polyarthritic

disease and dactylitis. CXCL10 (IP-10) has also been investigated as a potential

marker for PsA among patients with Pso (Abji, Pollock et al. 2016) and was found

in a higher serum concentration at baseline in Pso patients that later developed

PsA. In addition, in a pilot study from Chandran et al, serum levels of CRP,

osteoprotegerin, MMP-3 and C-propeptide of Type II collagen : collagen

fragment neoepitopes Col2-3/4(long mono) (CPII:C2C) ratio were markers for

PsA in patients with Pso (Chandran, Cook et al. 2010).

Thus, to date, the relevance of several biomarkers is indicated, but so far, studies

are few and often with few PsA cases included and further investigations in the

area is important.

Genetics of Pso and PsA

In recent years, genome-wide association studies (GWASs) have profoundly

expanded knowledge among genetic association in both Pso and PsA. Many loci

are common for both diseases, not surprisingly, since most patients with PsA also

have skin disease. However, the substantial difference in degree of heritage

makes it plausible that genetic loci exist that adds a risk of developing joint

disease.

The area most studied is the MHC region on chromosome 6, in which, through

linkage- and association studies, strong association with human leukocyte

16

antigen (HLA)-Cw6 and HLA-B alleles has been found, most of which are

associated with both Pso and PsA, whilst some seems to have a stronger

association with PsA (HLA-B27 and HLA-B7) (Chandran 2013). In addition, an

association with PsA in comparison with healthy controls was detected for the

TNF-B locus within the HLA-region (Alenius, Friberg et al. 2004). Associations

with genes outside the MHC region with both Pso and PsA have also been

identified, e.g. variants of IL12B and IL23R (Filer, Ho et al. 2008). In recent

years, several GWASs have been made, of which so far four on PsA (Cargill,

Schrodi et al. 2007, Liu, Helms et al. 2008, Huffmeier, Uebe et al. 2010, Stuart,

Nair et al. 2015). These studies confirmed previously known associations with

HLA-C and IL12B locus, and in one of these studies a previously unknown

association with TRAFAIP2 was found. This study was performed as a European

collaboration in which parts of the PsA-population included in this study was

included (Huffmeier, Uebe et al. 2010). A later study within the same project has

also shown significant association to another polymorphism in RUNX3 locus

(Apel, Uebe et al. 2013).

PTPN22

The protein tyrosine phosphatase non-receptor 22 (PTPN22) belongs to a family

of protein phosphatases (PTPs), that functions as regulators of tyrosine

phosphorylation-based cell signal transduction. The PTPN22 gene, located on

chromosome 1p13, codes for a non-receptor PTP only expressed by hematopoietic

cells (Stanford and Bottini 2014). PTPN22 is an intra-cellular protein with three

domains, an N-terminal PTP catalytic domain, an inter domain region and a C-

terminal domain with four proline-rich regions that function in interaction with

other proteins (Stanford and Bottini 2014).

PTPN22 is considered as having different roles in immune signalling. In the

adaptive immune system, T-cell receptor signalling is inhibited by

dephosphorylation of key mediators. The function of PTPN22 in B-cells is less

clear, but different roles in B-cell signalling have been suggested. By contrast, in

innate immunity, PTPN22 promotes myeloid-cell type-1 IFN production by

enhancing signalling downstream the pattern recognition receptors (Rhee and

Veillette 2012, Wang, Shaked et al. 2013, Bottini and Peterson 2014, Stanford and

Bottini 2014).

The single nucleotide polymorphism (SNP) rs2476601 (+1858C/T), located in

exon 14 of the PTPN22 gene encodes an arginine to tryptophan substitution at

amino acid 620. In 2004 this polymorphism was found associated with an

increased risk of type-1-diabetes (T1D), RA and systemic lupus erythematosus

(SLE) (Begovich, Carlton et al. 2004, Bottini, Musumeci et al. 2004, Kyogoku,

Langefeld et al. 2004) and the polymorphism is today considered a major risk

17

factor for autoimmunity affecting many, but not all, connective tissue

autoimmune diseases (Stanford and Bottini 2014). So far, PTPN22+1858C/T has

strongest associations with autoimmune diseases where autoantibodies have a

role in pathogenesis, e.g. ACPA-seropositive RA (Begovich, Carlton et al. 2004,

Kokkonen, Johansson et al. 2007) and the combination of PTPN22+1858T and

ACPA-positivity was highly specific for the development of RA in pre-patient sera

(Johansson, Arlestig et al. 2006).

The PTPN22+1858C/T has been suggested to be a gain-of-function variant with

increased dephosphorylating capacity (Vang, Congia et al. 2005), but at the

molecular level results are conflicting. The +1858C/T leads to a substitution of

Arginine (Arg) to Tryptophan (Trp) in position 620 in the first proline-rich

domain of the C-terminus that, in T-cells, is involved in the binding of PTPN22

to the intracellular tyrosine kinase Csk. (Bottini, Musumeci et al. 2004). The

substitution has been shown to inhibit the binding to Csk, leading to increased

phosphatase activity with increased suppression of T-cell receptor signalling

(Vang, Congia et al. 2005, Bottini, Vang et al. 2006). At the cellular level the

mechanisms are under investigation (Stanford and Bottini 2014).

The frequency of variant allele PTPN22+1858T varies considerably among

different populations, e.g. in Europe, the allele is found in 2-3 % in Italy and

Sardinia and the frequency increases in the north/east parts to as much as 15% in

Finland. Interestingly, the allele is almost absent in Asian and African

populations, e.g. Begovich et al showed that PTPN22+1858T was not detected in

100 Han Chinese or 21 Africans and the results have been confirmed in other

studies (Begovich, Carlton et al. 2004, Gregersen, Lee et al. 2006).

PTPN22 in Pso and PsA

Compared with RA, few studies have investigated PTPN22 and PsA. Initial

studies on the PTPN22+1858C/T polymorphism and susceptibility to PsA,

showed conflicting results. (Hinks, Barton et al. 2005, Butt, Peddle et al. 2006,

Huffmeier, Reis et al. 2006). In a UK population (Hinks, Barton et al. 2005) no

association was found with PsA and in a German cohort (Huffmeier, Reis et al.

2006) an association with male PsA-patients, but not females, was detected. Also,

in a study on two populations from Canada (Butt, Peddle et al. 2006) an

association with PTPN22+1858C/T was seen in the cohort from Toronto, but not

in the cohort from Newfoundland. Recently, a GWAS confirmed association

between PTPN22 +1858C/T and PsA. (Bowes, Loehr et al. 2015). Interestingly no

association was found with Pso. Thus the PTPN22+1858C/T polymorphism could

partly explain the higher heritage of PsA compared with Pso (Karason, Love et al.

2009, Bluett and Barton 2012).

18

Inflammasomes

In recent years, research on the IL-1β–regulating protein complexes, called the

inflammasomes, have shown interesting associations with various inflammatory

diseases.

Inflammasomes are a group of protein complexes involved in host defence

against microbes and other forms of stress and damage signals, and also has an

important role in inflammation and tissue repair (Strowig, Henao-Mejia et al.

2012). They consist of protein complexes of a NOD-like receptor (NLR) or an

absent in melanoma (AIM)-like receptor, the adaptor molecule apoptosis-

associated speck-like protein that contains a caspase recruitment domain (ASC)

and the effector protein, caspase-1. The NLR/AIM recognize different

inflammation-inducing stimuli, e.g. conserved PAMPs or DAMPs that leads to

assembly of the protein complex and activation of caspase-1 and subsequent

proteolytic cleavage of inactive forms of pro-IL-1β and pro-IL-18 to the active pro-

inflammatory cytokines, IL-1β and IL-18 (Strowig, Henao-Mejia et al. 2012).

Two of the most studied inflammasomes are the NOD-like receptor family, pyrin

domain containing 1, (NLRP1) and NOD-like receptor family pyrin domain

containing 3 (NLRP3). In mice, the NLRP3 inflammasome is composed of the

NLRP3 protein, the adaptor molecule ASC and caspase-1. In human, the NLRP3-

inflammasome also contain an additional molecule, CARDINAL (also named

caspase recruitment domain-containing protein 8 (CARD8) or TUCAN) (Wilson

and Cassel 2010).

Different mutations in genes of NLRP3 are causally associated with rare auto-

inflammatory conditions characterized by fever and excessive IL-1 production,

e.g. Muckle-Wells syndrome (MWS) and familial cold-induced auto-

inflammatory syndrome (FCAS), diseases that respond favourably to the anti-IL-

1 receptor antagonist, Anakinra (Hoffman, Mueller et al. 2001, Hawkins,

Lachmann et al. 2003, Goldbach-Mansky, Dailey et al. 2006). These diseases

represent prototypes of monogenic auto-inflammatory diseases. However, in

recent years, genetic polymorphisms of NLRP3 have been reported to be

associated with autoimmune diseases, e.g. rheumatoid arthritis (RA) (Kastbom,

Verma et al. 2008).

The NLRP1 inflammasomes have also been implicated in human disease, the first

implicated association was for SNPs in NLRP1 with vitiligo related autoimmune

diseases (Jin, Mailloux et al. 2007).

Several single nucleotide polymorphisms in NLRP1 and NLRP3 have been

examined in multiple inflammatory diseases. Of these, the functional mutations

19

CARD8-C10X and NLRP3-Q705K have been studied in several diseases, both

separately and in combination. For example, the combination of the genetic

polymorphisms NLRP3-Q705K and CARD8-C10X showed association with RA

compared with healthy controls (Kastbom, Verma et al. 2008) and the

combination were also found associated with Crohn’s disease in two studies

(Schoultz, Verma et al. 2009, Roberts, Topless et al. 2010). The NLRP3-Q705K

and CARD8-C10X have also shown individual association with several disease,

e.g. Alzheimer’s disease, Celiac disease, Ankylosing spondylitis and

Cardiovascular disease (CVD) (Paramel, Sirsjo et al. 2015). Recently, an

association with stroke was found with the CARD8-C10X polymorphism in a

recessive model (Bai, Nie et al. 2014). In addition, an association was found with

the variant allele of NLRP3-Q705K and stroke in patients with RA (Kastbom,

Arlestig et al. 2015).

The NLRP3-Q705K is a “gain of function” variant leading to excessive IL-1β and

IL-18 production (Verma, Sarndahl et al. 2012). The CARD8-C10X

polymorphism is a nonsense mutation leading to a truncated CARD8 protein.

Functional investigation of CARD8 is complicated by the fact that it is absent in

rodents. Also, a series of isoforms exists that can possibly affect the consequences

of the C10X polymorphism (Bagnall, Roberts et al. 2008) and patients

homozygous for the C10X might therefore have a functional CARD8 protein due

to different isoforms (Paramel, Sirsjo et al. 2015).

Genetic polymorphisms in inflammasome genes of diseases related to PsA

In a study on families with psoriasis, possible associations between CARD8-C10X

and three polymorphisms in the gene for NALP3 (including NLRP3-Q705K) and

psoriasis were examined. In this study, an association with CARD8-C10X in

comparison with controls was detected, and for one of polymorphisms in NLRP3

gene, the rs10733113G allele was significantly over-transmitted to a sub-group of

Pso with a more widespread skin disease (Carlstrom, Ekman et al. 2012).

Recently, also SNPs in the NLRP1-inflammasome have shown increased

transmission to patients with Pso in transmission disequilibrium test in families

with Pso (Ekman, Verma et al. 2014). In a study of patients with ankylosing

spondylitis (AS), an association with the polymorphism CARD8-C10X in

comparison to healthy controls was discovered, whereas no associations were

found with the three examined polymorphisms in the NLRP3 gene and AS

(Kastbom, Klingberg et al. 2013).

To date, only one study has been published in which genetic polymorphisms in

inflammasome genes have been investigated in patients with PsA (Loft, Skov et

al. 2018). In that study no significant associations were found with PsA (Loft,

Skov et al. 2018).

20

Prognosis

PsA disease expression is highly variable, both in disease expression and in

severity (Moll and Wright 1973, Gladman, Shuckett et al. 1987). As opposed to

the initial view of PsA to be relatively benign, studies have shown that PsA is a

destructive and progressive disease that in almost 20% of cases leads to severe

joint destruction and/or deformities (Gladman, Shuckett et al. 1987, Gladman

1994). Indicated negative prognostic factors for a poor outcome are polyarthritic

disease phenotype, increased levels of inflammatory parameters (ESR, CRP),

smoking and a delay in diagnosis (Gladman, Farewell et al. 1995, Alenius, Jidell

et al. 2002, Tillett, Jadon et al. 2013, Theander, Husmark et al. 2014, Haroon,

Gallagher et al. 2015).

A substantial impact of quality of life has also been shown in PsA (Sokoll and

Helliwell 2001, Husni, Merola et al. 2017). In the Swedish Early Psoriatic Arthritis

Register (SwePsA) patients with early PsA (<2 years symptom duration) have

been followed. At the 5-year follow-up prognostic factors were investigated.

Factors with a positive impact on disease course after 5 years were early

diagnosis, preserved function and male gender (Theander et al. 2014). Risk

factors for radiological progression at 5 years were dactylitis and the presence of

radiological damage at baseline and risk factors for early radiographic damage

was male sex (Geijer, Lindqvist et al. 2015).

Co-morbidity

In PsA, like other diseases in the group of SpAs, extra-articular manifestations

occur, e.g. uveitis, IBD, urogenital inflammation. Previous studies have also

shown renal involvement (Alenius, Stegmayr et al. 2001) and increased risk of

migraine (Egeberg, Mallbris et al. 2015) in patients with PsA. Additionally, in

patients with Pso, increased frequency of a number of co-morbidities have been

reported, particularly in patients with a more severe disease, e.g. CVD, diabetes,

obesity, metabolic syndrome , gastrointestinal diseases, kidney disease,

malignancy, infections and mood disorders (Coates, Kavanaugh et al. 2016,

Takeshita, Grewal et al. 2017, Gisondi, Fostini et al. 2018). In a recent study, the

frequency of extra-articular manifestations and their relation to different PsA

manifestations were investigated; 16.3% had bowel involvement, 12.7% had

urogenital involvement and 5.7% had uveitis (Peluso, Iervolino et al. 2015). Both

bowel involvement and ocular involvement were more common in PsA with axial

disease and urogenital involvement more common in males (Peluso, Iervolino et

al. 2015).

21

In addition to an increased frequency of IBD, sub-clinical inflammation has been

detected in the gastrointestinal tract of patients with PsA (Schatteman, Mielants

et al. 1995, Scarpa, Manguso et al. 2000, Lindqvist, Kristjansson et al. 2006).

Recently, an interesting link between the gut and joint was suggested (Ciccia,

Guggino et al. 2016). In their study an increased number of the recently

discovered TH9-cells and increased levels of IL-9 were detected in the gut of PsA

patients and IL-9 was also overexpressed in synovial tissue from patients with

PsA (Ciccia, Guggino et al. 2016).

Cardiovascular disease is the main cause of death in the general population of the

Western world. The major cause of cardiovascular events is atherosclerosis.

Atherosclerosis is a chronic process in the vessel wall that ultimately leads to

plaque formation and CVD. Atherosclerosis has been widely accepted to be

strongly linked to low-grade vascular inflammation (Hansson, Robertson et al.

2006). In the general population, a number of risk factors have been linked to

development of CVD, e.g. hypertension (HT), hyperlipidaemia, increased body

mass index (BMI), diabetes mellitus and smoking (Wilson, D'Agostino et al. 1998,

Yusuf, Reddy et al. 2001).

Among individuals suffering from different rheumatic diseases, e.g. SLE and RA,

both increased mortality and increased risk of cardiovascular comorbidity have

been demonstrated (Wallberg-Jonsson, Ohman et al. 1997, Wallberg-Jonsson,

Johansson et al. 1999, Bengtsson, Ohman et al. 2012). In RA, a meta-analysis

from 2012 shows increased risk of 48% for incident CVD compared with the

general population (Avina-Zubieta, Thomas et al. 2012) that have led to

recommendations of modifying clinical cardiovascular risk scores in individuals

with RA by multiplying the annual risk calculated by SCORE with a factor 1.5

(Peters, Symmons et al. 2010).

Corresponding data on PsA and CVD are more limited, but several studies

indicate that patients with Pso and PsA have increased morbidity and mortality

due to CVD (Gladman, Ang et al. 2009, Tobin, Veale et al. 2010, Ahlehoff,

Gislason et al. 2011, Horreau, Pouplard et al. 2013, Jamnitski, Symmons et al.

2013, Miller, Ellervik et al. 2013, Polachek, Touma et al. 2017).

Considering the link between inflammation and atherosclerosis (Libby, Ridker et

al. 2009), the increased inflammatory burden in rheumatic diseases has been

implicated in the increased risk of CVD. In Pso and PsA, also a high prevalence of

traditional risk factors, e.g. HT, hyperlipidaemia, increased BMI and diabetes

mellitus have been detected (Jamnitski, Symmons et al. 2013, Miller, Ellervik et

al. 2013). The concept of the “psoriatic march” has been suggested. In this model,

psoriatic disease causes systemic inflammation that causes insulin resistance and

endothelial dysfunction leading to atherosclerosis and ultimately risk of

22

cardiovascular events (CVE) (Boehncke and Boehncke 2012). Moreover, an

association with a more severe PsA disease was found among patients with

metabolic syndrome and insulin resistance (Haroon, Gallagher et al. 2014). The

high frequency of traditional risk factors complicates analysis of the role

inflammation due to disease. In a recent study of PsA patients, CVE were

associated with traditional risk factors (hypertension, diabetes) and disease

activity (ESR in women and dactylitis) (Eder, Wu et al. 2016).

An overall increased mortality in patients with PsA has been shown, particularly

in those patients with signs of a severe disease, high ESR values and early signs

of radiological changes (Wong, Gladman et al. 1997, Gladman, Farewell et al.

1998, Gladman 2008, Ahlehoff, Gislason et al. 2011). However, these findings

have not been confirmed in other studies (Coulton, Thomson et al. 1989, Shbeeb,

Uramoto et al. 2000, Gladman 2008, Ogdie, Haynes et al. 2014). Few studies

have examined causes of death in PsA, in these studies leading causes of death

have been circulatory/cardiovascular, respiratory and malignant neoplasms

(Wong, Gladman et al. 1997, Buckley, Cavill et al. 2010, Ogdie, Maliha et al. 2017).

In a study by Haque et al, frequencies of co-morbidities in PsA were compared

with other SpAs and increased risk of malignancy, hypertension, coronary artery

disease, diabetes, hyperlipidaemia and metabolic syndrome was detected in

patients with PsA compared with the other SpAs (Haque, Lories et al. 2016).

Thus, evidence exists for increased risk of mortality and cardiovascular morbidity

in patients with PsA. However, results are conflicting and heterogeneity among

studies makes interpretation of data difficult (Miller, Ellervik et al. 2013,

Polachek, Touma et al. 2017) and further studies are indicated.

23

Aims

Psoriatic Arthritis (PsA) is a complex disease with a heterogeneous disease

expression. In this study different aspects of PsA is explored and the following

aspects are highlighted:

Is there an association with genetic markers that control the

inflammatory process, and can they be linked to disease expression

and/or inflammatory activity in PsA?

Is the presence and/or levels of various biomarkers related to disease

expression/severity of PsA?

Is there an increased risk for comorbidity in PsA, in particular

cardiovascular disease, and if so, is there an association with disease

expression and/or inflammatory activity?

24

Patients and Methods

Patients and controls

Since PsA is a relatively rare disease, the patients were collected over time (1995-

2015). All of the patients were diagnosed with PsA at the Department of

Rheumatology, Västerbotten, gave their written, informed consent, and were

either examined according to a study protocol or by careful reading of patients’

medical record to validate the diagnosis and classify disease. Since data collection

was performed consecutively over time, various sub-populations are included in

different studies depending on when the study was conducted. During 2009-2010

patients who had been diagnosed with PsA at two nearby hospitals in northern

Sweden (Örnsköldsvik and Östersund), were also asked to participate in the

study. These patients were examined and diagnosed with PsA by rheumatologists

at their local clinic. During 2009-2010, those patients’ records were examined to

validate the diagnosis of PsA and blood samples were collected.

A total of 856 patients with PsA is included in Paper I-IV (Table 3). The study

population by year of inclusion is illustrated in Figure 2a and the representation

of the different cohorts in Paper I-IV is illustrated in Figure 2b and Figure 3.

Table 3. Patients with PsA in different studies by year of inclusion.

Paper I Paper II Paper III Paper IV

Population Year of

inclusion

n

1 1995-96 45 41 41 21 40

2 1999-2000 124 120 121 84 121

3 2007-2008 132 130 130 113 101

4 (Örnsköldsvik) 2009 55 0 55 0 0

5 (Östersund) 2010 98 0 98 0 0

6 2010-2011 203 0 80 11 202

7 2015 199 0 199 45 0

Tot, n 856 291 724 274 464

All patients were either examined, or their medical records evaluated using

standardized study protocols and underwent further tests and/or responded to

questionnaires depending on the aim of the specific study. For a majority of study

participants blood samples have been collected. Blood samples were stored at -

80°C.

25

Figure 2. Illustration of the whole study population divided according to a; year

of inclusion, b; Paper I-IV

a.

b.

26

Figure 3. Representation of the different study populations in Paper I-IV.

The control populations were also varied in the different studies. In Paper I

(n=724) and Paper II (n=586), controls were from the Medical Biobank of

Northern Sweden. In Paper III a proportion of healthy, population controls from

Västerbotten (n=30) that had been included in a previous study was used

(Alenius, Berglin et al. 2006). In Paper IV, no control population was included,

instead comparison was made with the statistics on the general population of

Västerbotten available in the National Causes of Death Register in Sweden and

the National Inpatient Care Register in Sweden (www.socialstyrelsen.se).

In Table 4 the age and gender of patients with PsA and controls in the different

studies are illustrated.

27

Table 4. Age and gender of PsA patients and controls in the different studies.

Paper I Paper II Paper III Paper IV

Pat Co Pat Co Pat Co Pat Co

Number, n 291 725 724 586 274 30 464 NA

Female

/male, n

146/145 460/265 387/337 153/434 136/138 15/15 230/234 NA

Mean age,

y±SD

52.2

±13.1

55.6

±12.4

59.4

±12.4

63.4

±9.7

53.6

±12.9

52.4

±17.4

59.5

±13.5

NA

PsA duration,

y±SD

15.2

±11.7

NA NA NA 14.0

±10.4

NA 20.4

±11.1

NA

Pso duration,

y±SD

NA NA NA NA 24.2

±14.8

NA 31.1

±16.4

NA

Pat=PsA patients, Co=controls, NA=not analysed

Clinical characteristics

Since the patient population was included consecutively and the studies differ

significantly in design and purpose, not all clinical data were available for all

individuals. Thus, some variables are unique to some of the studies while others

are available for all patients. Most definitions that are used and in which of the

studies they were applied are listed in Table 5.

Paper IV is based on investigation of patients’ medical records and

questionnaires. The questionnaires for this study included questions about family

history, medical history, current medication, body weight, body height and

smoking status. Unfortunately, many variables were missing from the patients’

medical records and the use of standardized activity indices for PsA and/or SpA

could not be applied. Instead a composite index, DAI, previously used for RA

(Baecklund, Sundstrom et al. 2003), was used (Table 6). The DAI reflects both

clinical activity for peripheral disease and laboratory activity, and also accounts

for this activity over time. A high DAI possibly reflects a more aggressive disease

or lack of effective treatment.

28

Table 5. Definition of different disease characteristics and in which studies they are used

Disease characteristic Applied

in Paper

Definition

Destructive/deforming disease II-IV Either typical, radiological changes, e.g., erosions, juxta-

articular new bone formation and/or irreversible deformations

(e.g., ankylosis, subluxations and/or loss of function or

reduced mobility).

Measurable inflammation

when clinically active PsA

disease

II-III Defined as either elevated levels of CRP (≥10 mg/L) and/or

ESR (≥20 mm/h when clinically active PsA disease according

to the investigating clinician.

Dactylitis I-IV Diffuse swelling of an entire digit, finger or toe.

Axial involvement I-IV Defined based on radiological findings in the sacroiliac joints

(SI-joints) according to the New York criteria (≥ 2) and/or

syndesmophytes, ligamentous ossification, vertebral squaring

and shining corners of the spine and/or positive MRI-findings

of the SI-joints or spine.

Arthritic joints I Number of swollen and tender joint at clinical investigation.

Deformed joints I Number of deformed joints at clinical investigation.

Nail psoriasis I-III Diagnosed by dermatologist or rheumatologist. Onycholysis

and/or pitting.

Psoriasis type I I-III Onset of skin psoriasis before 40 years of age.

Type of psoriasis II Psoriasis vulgaris, inverse psoriasis, guttate psoriasis,

pustulosis palmo-plantaris (PPP), erythrodermia

Enthesitis I-IV Swelling and tenderness over the insertion of achilles tendon

and/or plantar fascia. Criterion in CASPAR criteria.

DMARD II-IV Disease modifying anti-rheumatic drug.

csDMARD II-IV Conventional synthetic DMARD; cyclosporine,

hydroxychlorokine, leflunomide, methotrexate, myocrisin or

sulfasalazine

bDMARD II-IV Biological DMARD; abatacept, adalimumab, certolizumab,

etanercept, golimumab, infliximab or ustekinumab

Smoking status II, IV Never, current or previous.

PsA disease activity at clinical

investigation

III According investigating clinician, including; axial- and

peripheral joint involvements, enthesitis, dactylitis and

laboratory activity, as none, low, moderate, high or maximal.

PsA disease expression (Moll

& Wright)

- DIP joint disease I-IV Exclusive DIP-joint involvement.

- Axial disease I-IV Predominantly axial disease.

- Mono-

/oligoarthritis

I-IV Involvement of ≤ 4 joints when clinically active PsA disease.

- Polyarthritis I-IV Involvement of ≥ 5 joints when clinically active PsA disease.

- Arthritis mutilans I-IV Severe, erosive, mutilating disease phenotype.

PsA disease involvement

- Peripheral disease

only

I-IV No documented axial involvement (see definition above).

- Axial disease only I-IV No peripheral arthritis documented (see definition above).

- Peripheral and

axial disease

I-IV The combination of peripheral arthritis and axial involvement

according to definition above.

Disease Activity index (DAI) IV Table 6

29

Table 6. Disease activity index (DAI)*

Score 1 2 3 ESR 1-20 20-60 >60 Number of swollen and tender joints 0-3 4-6 ≥7 Physicians global assessment of disease activity

none-low Moderate high

*=As described in Baecklund et al. (Baecklund, Sundstrom et al. 2003) for RA, with modification of lowering ESR for score 2 from 30 to 20 mm/h. Values for score was extracted from patients’ medical

record every two years during the whole period of PsA disease (from diagnosis to the end of the

study). The final score was calculated as a mean, range 3-9. For missing data, the method of last observation value carried forward was used.

Laboratory tests

For patients who underwent clinical investigation at inclusion, blood samples

were collected at the time of investigation. When patients medical records were

used to verify diagnosis and disease characteristics, laboratory data were

extracted from medical records. In all papers, erythrocyte sedimentation rate

(ESR, mm/h) and C-reactive protein (CRP, mg/L) were determined using routine

methods. Rheumatoid factor (RF) and anti-citrullinated protein/peptide

antibodies (ACPA) were generally extracted from patients medical record, except

for in study I were RF and ACPA were analysed with ELISA (ORG522 M

Rheumatoid Factor IgM ELISA kit (Orgentic Diagnostika GmbH, Mainz,

Germany) and DIASTAT Anti-CCP ELISA kit FCCP200 from Axis-Shield

Diagnostics Limited (Technology Park, Dundee, Scotland, UK)). In study II, III

and IV, RF was used if analysed according to standardized method, excluding

latex beads.

All patients included in studies I, II and III and the majority of patients in study

IV donated blood. All blood samples were separated into plasma/serum and buffy

coat cells by centrifugation at 4400 x g for 15 min and stored at -80°C. For

individuals who donated blood at the time of investigation (Paper III) sera were

used for analysis of biomarkers (V-plex and ELISA, see below). Genomic DNA

was extracted from EDTA-treated whole blood using the “salting out” method, for

patients included before 2011 (n=445) and for the remaining with the Flexigene

DNA kit (250) (QIAGEN, Germany).

Genotyping

The PTPN22+1858C/T polymorphism (rs2476601) was determined by the

TaqMan® assay using an ABI PRISM 7900HT Sequence Detection System and

30

the SDS 2.1 software (Applied Biosystems, Foster City, CA, USA) according to the

manufacturer’s instructions.

The SNPs in study II, NLRP3 ( rs35829419 (Q705K) , rs10733113, CARD8 (rs

2043211 (C10X)) and NLRP1 (rs8079034, rs878329) was determined with

TaqMan® SNP Genotyping Assay supplied by Applied Biosystems (Foster City,

CA, USA) according to the manufacturer’s instructions. The samples were

analysed on a 7900 HT Fast Real-Time PCR System (Applied Biosystem) by

TaqMan® Allelic Discrimination (Applied Biosystem, Foster City, CA, USA).

Measurement of serologic biomarkers

Sera from patients with PsA and controls were stored in aliquots at -80°C and

analysed by V-plex, 40-plex panel (Meso Scale Discovery (MSD), Meso Scale

Diagnostic, LCC, Rockville, USA) according to the manufacturer’s instructions.

The biomarkers included in V-plex, 40-plex are listed in Table 7. IL-18 and

calprotectin was analysed with ELISA (Invitrogen™ IL-18 Human Platinum

ELISA kit, Thermo Fisher Scientific, Bender MedSystems GmbH, Vienna, Austria

and IDK®Calprotectin Serum/Plasma ELISA, Immundiagnostik AG, Bensheim,

Germany) according to the manufacturer’s instructions.

Table 7. Biomarkers included in the MSD®, V-plex, 40-plex kit®

Panel

Biomarkers included

Vascular injury

panel 2 (human)

Serum amyloid A (SAA), C-reactive protein (CRP), Vascular Cell Adhesion

Molecule-1 (VCAM-1), Intercellular Adhesion Molecule-1 (ICAM-1)

Angiogenesis

panel 1 (human)

Vascular endothelial growth factor-A (VEGF-A)*, Vascular endothelial

growth facto-C (VEGF-C), Vascular endothelial growth factor-D (VEGF-D), Tyrosine kinase-2 (Tie-2), Fms-like tyrosine kinase 1 (Flt-1), Placental

Growth Factor (PIGF)*, Basic Fibroblast Growth Factor (bFGF)

Chemokine panel

1 (human)

Eotaxin (CCL11), MIP-1β (CCL4), Eotaxin-3 (CCL26), TARC (CCL17), IP-10

(CXCL10), MIP-1α (CCL3), IL-8 (CXCL8)**, MCP-1 (CCL2), MDC (CCL22),

MCP-4 (CCL13)

Pro-inflammatory

panel 1 (human)

Interferon (IFN)-γ, Interleukin (IL)-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-

12p70, IL-13, Tumour necrosis factor (TNF)-α

Cytokine panel 1

(human)

Granulocyte-macrophage colony stimulating factor (GM-CSF), IL-1α, IL-5,

IL-7, IL-12/IL-23p40, IL-15, IL-16, IL-17A, TNF-β, VEGF

*=Due to problems at the manufacturer PIGF and VEGF-A were not included in the analysis.

**=quantitates high levels of IL-8 and was not used in the present analysis

Statistical analysis

Common for all studies: Student’s t-test was used to test for difference in

continuous data. For comparison of categorical data between groups, the Chi-

31

square (χ2) tests was used and for multivariate analysis, logistic regression

analysis were used. Odds ratios (ORs) were caluculated with 95% confidence

interval (CI). For all analysis, p-values were two-sided and a significance level of

≤0.05 was considered significant. Unless otherwise specified, statistical

calculations were performed using PASW Statistics program (SPSS Inc., Chicago,

IL, USA), either version 18.0 (Paper I and IV) or version 24.0 (Paper II and III).

The specific statistical methods used in the individual studies are described in

Table 8.

Table 8. Statistical methods specific for Paper I-IV

Paper I Power calculation was performed using EpiInfo.

Paper II In addition to SPSS 24.0, OpenEpi 3.01 was used. Paper III Orthogonal partial least squares discriminant analysis (OPLS-

DA) was performed using SIMCA-P+ software (version 12.0;

Umetrics AB, Umea, Sweden) to compare PsA with controls and

among PsA between disease phenotypes. In this study, t-tests

were performed with Microsoft Exel 2016, with p-values

adjusted by multiple test correction (pc) according to Benjamini-

Hochberg. Mann-Whitney U tests were analysed by SPSS 24.0.

Paper IV For calculation of standardized incidence ratio (SIR) and

standardized mortality rate ratio (SMR), the expected risk of

death/CVE in the general population in Västerbotten County was

used, stratified for age groups.

32

Study design

Paper I

The first study included in this thesis is a case-control study investigating the

frequency of the PTPN22+1858C/T single nucleotide polymorphism (SNP) in

patients with psoriatic arthritis (PsA) compared with population controls. The

polymorphism had previously been found associated with several autoimmune

diseases, but earlier studies in PsA had shown various results.

In this study, DNA from 291 PsA (146 female, 145 male) from the county of

Västerbotten and 725 population controls were genotyped for the

PTPN22+1858C/T polymorphism and allelic frequencies were compared. Among

PsA allelic frequencies were also examined in relation to different PsA disease

phenotypes.

Paper II

In this case-control study, polymorphisms in different genes related to the

inflammasome were investigated. Five different SNPs were analysed in 724 PsA

patients and allelic frequencies were compared with 587 population controls.

Selection of SNPs was based on previous research on related diseases, e.g.

rheumatoid arthritis (RA) and psoriasis (Pso). Among patients with PsA,

differences in allelic frequencies in different disease phenotypes were also

investigated.

Paper III

The aim of this cross-sectional study was to investigate different serological

biomarkers in relation to different clinical phenotypes of PsA. The study design

was based on the heterogeneity of PsA and lack of serological biomarkers to

predict disease severity. Biomarkers were selected based upon previous findings

in PsA and related diseases.

Two-hundred and seventy-four PsA patients who donated blood in conjunction

with clinical investigation between 1995 and 2015 were included. The study also

included a small number of healthy controls for comparison (n=30). Different

biomarkers were analysed in relation to both PsA disease activity at time of

investigation and to overall PsA disease phenotypes, including whether or not the

patient were treated with anti-rheumatic drugs.

33

Paper IV

In this cohort study, mortality, causes of death and the incidence of acute

cardiovascular events (CVE) in PsA patients were investigated in comparison

with the general population. The background to the study was the previous

findings of increased risk of co-morbidity, in particular CVD, found in several

rheumatic disease, e.g. RA and SLE. Although previous data indicate an

increased risk of CVD in PsA, data is limited and results conflicting.

In the study 464 patients with PsA with established disease were included

between 1995-2005. All patients were diagnosed at the Department of

Rheumatology, Västerbotten, and patients’ medical records were carefully

evaluated according to standardized protocols to verify the diagnosis, and to

record disease activity and disease phenotypes before, during and at the end of

the study and the use of anti-rheumatic drugs.

To investigate mortality and causes of death data was extracted from the National

Causes of Death Register in Sweden until the end of 2011 and to investigate

incidence of CVE (stroke, acute myocardial infarction, and unstable angina

pectoris), data were extracted from the National Inpatient Care Register until the

end of 2010. Standardized mortality rate ratio (SMR) and standardized incidence

rate ratio (SIR) were calculated in comparison with the general population of

Västerbotten.

To investigate the effect of inflammatory activity among PsA patients, a

composite disease activity index (DAI) was used (Table 6). The impact of different

anti-rheumatic treatments and different PsA disease phenotypes on the risk of

death and acute cardiovascular event were also investigated.

34

Results and discussion

The great heterogeneity and complexity of PsA disease is a challenge both in

research studies and in clinical practice. In some aspects, the more we know, the

more complex the picture seems to become. This thesis is the summary of four

studies on well-characterized patients with PsA in a relatively large cohort from

Northern Sweden. In this study, different aspects of PsA have been investigated

and some interesting results generated, but as often happens in research, new

questions arise as others are answered.

Genetic analyses (Papers I and II)

A strong genetic impact is suggested for PsA with an approximately 40-times

increased risk if a first degree relative with the disease (Karason, Love et al.

2009), making genetic studies of interest. Therefore, we wanted to study PsA in

comparison with healthy controls and among different phenotypes of PsA

disease. Studies of different SNPs were chosen based on previous research on

related diseases. Since allelic frequencies often differ between different

geographic areas, we used population controls from the same geographic area as

the patients.

In Paper I an association with the PTPN22+1858C/T polymorphism and PsA

was found, with both an increased carriage of risk allele PTPN22+1858T (CT+TT)

(χ2=6.56, p=0.010, odds ratio (OR) 1.49 (95%CI 1.10-2.02) and an increased

frequency of the T-allele in patients with PsA compared with controls (0.160 vs

0.119, p=0.013). Earlier studies of this polymorphism had shown conflicting

results (Hinks, Barton et al. 2005, Butt, Peddle et al. 2006, Huffmeier, Reis et al.

2006), but recently the association between PTPN22+1858C/T and PsA was

confirmed in a GWAS (Bowes, Loehr et al. 2015). Interestingly, no association

was found with Pso.

Since PTPN22 +1858 C/T had previously been associated with RA, it was decided

to investigate whether patients with PsA who were positive for RF and/or ACPA

contributed to the association. Instead, when RF or ACPA sero-positive patients

were excluded an even stronger association was found (χ2=8.56, p=0.003, OR

1.61 (95%CI 1.17-2.21) and (χ2=6.63, p=0.010, OR 1.51 (95%CI 1.10-2.07)

respectively) (Table 9). In addition, carriage of PTPN22+1858T was similar

among PsA patients with both mono-/oligoarthritic and polyarthritic disease

phenotypes (Table 10). Thus, the association with PTPN22+1858T was not

attributed to PsA with a more RA-like phenotype.

35

Table 9. Comparison of PTPN22+1858C/T genotypes in PsA patients stratified

according to anti-citrullinated protein/peptide antibodies (ACPA) and

rheumatoid factor (RF) with all controls.

CT+TT CC Cases versus controls

n (%) n (%) χ2 P-value OR (95% CI)

All PsA 87 (29.9) 204 (70.1) 6.56 0.010 1.49 (1.10-2.02)

ACPA neg 80 (30.3) 184 (69.7) 6.63 0.010 1.51(1.10-2.08)

ACPA pos 6 (28.6) 15 (71.4) 0.45 0.50 1.39 (0.53-3.64)

RF neg 79 (31.6) 171 (68.4) 8.56 0.003 1.61 (1.17-2.21)

RF pos 8 (23.5) 26 (76.5) 0.26 0.87 1.07 (0.48-2.41)

When patients with different phenotypes of PsA disease were compared, an

association was found between patients with PsA that anytime had been

diagnosed with dactylitis and carriage of PTPN22+1858T (χ2=10.56, p=0.001, OR

2.58 (95% CI 1.44-4.62). Additionally, carriers of PTPN22+1858T had

significantly more deformed joints at examination compared with non-carriers

(mean number of joints ± SEM; 5.9 ±1.2 vs 2.8 ±0.5; p=0.005) (Table 10). The

association with dactylitis and deformed joints indicate an association of

PTPN22+1858T with a more aggressive PsA disease.

In Paper II different SNPs in genes related to inflammasomes were investigated.

We found a significant association with the genotype AA (vs AT+TT) of CARD8-

C10X (rs2043211) for PsA patients compared with controls (χ2=5.77, OR (95%CI);

1.32 (1.05-1.65), p=0.016), with the strongest association compared with controls

in patients with peripheral joint disease without axial involvement (χ2=6.6, OR

(95%CI); 1.36 (1.08-1.72), p=0.010). These results are in agreement with previous

studies on patients with AS (Kastbom, Klingberg et al. 2013) and Pso (Carlstrom,

Ekman et al. 2012). In a previous study on early RA, an association with CARD8-

C10X and inflammatory activity was found (Kastbom, Johansson et al. 2010). In

this study, PsA patients with both short- and longstanding disease were included

and most patients had established disease. Thus, it was not possible to investigate

this polymorphism in relation to PsA disease activity early in disease and among

PsA patients there was no association with a disease phenotype with measurable

inflammation in active disease.

36

Table 10. Comparison of carriage of PTPN22+1858T in different PsA disease

phenotypes and among males and females

CC CT+TT p-value

Arthritic joints (n±SEM) 3.01 (±0.28) 3.18 (±0.41) 0.73 Deformed joints (n±SEM) 2.84 (±0.46) 5.89 (±1.24) 0.005 n (%) n (%) χ2 OR (95% CI)

Females 103 (71) 42 (29) Males 100 (69) 45 (31) 0.15 0.80 0.91 (0.55-1.50)

Axial disease 46 (77) 14 (23 No axial disease 156 (68) 72 (32) 1.54 0.27 0.66 (0.34-1.28)

Dactylitis 34 (53) 30 (47) No dactylitis 155 (74) 53 (26) 10.6 0.002 2.58 (1.44-4.62)

Nail psoriasis 85 (71) 35 (29) No nail psoriasis 113 (69) 50 (31) 0.075 0.80 0.93 (0.56-1.56)

Deformed joints 89 (64) 49 (36) Not deformed joints 112 (75) 38 (25) 3.53 0.06 1.62 (0.98-2.69)

Psoriasis type 1 154 (70) 66 (30) Not psoriasis type 1 47 (69) 21 (31) 0.019 0.88 0.96 (0.53-1.73)

Mono-/oligoarthritis 84 (72) 33 (28) Polyarthritis 94 (71) 38 (29) 0.01 0.92 1.03 (0.59-1.79)

Five SNPs, in three different inflammasome genes, were investigated in Paper II,

two in NLRP1 (rs878329G/C, rs8079034C/T), two in NLRP3 (rs10733113 G/A,

rs35829419 C/A) and one in CARD8 (rs2043211A/T). All polymorphisms were

analysed for association with different clinical phenotypes of PsA, e.g. skin

psoriasis type1 (onset <40 years), axial disease with- or without peripheral

arthritis, mono-/oligoarthritic or polyarthritic disease phenotype, nail psoriasis,

destructive-/deforming disease phenotype (x-ray and/or clinical), measurable

inflammation (ESR >20 mm/h and/or CRP >10 mg/L) in active disease,

bDMARD ever, csDMARD ever, as defined in Table 5. Significant associations

were found with four different PsA disease phenotypes with four different SNPs

(Table 11);

The C-allele and the genotype CC (vs CG+GG) of NLRP1 rs878329 were

significantly associated with PsA patients with axial involvement of

disease, with or without peripheral joint involvement (χ2=4.45, OR

(95%CI); 1.37 (1.02-1.84), p=0.035 and χ2=5.82, OR (95%CI); 1.84 (1.12-

3.04), p=0.016 respectively) (Table 11). In a previous family study on

patients with Pso, an increased transmission of rs878329C to affected

37

family members was seen and homozygosity was associated with a

younger age of onset (Ekman, Verma et al. 2014). In this study, no

association was detected for this polymorphism with Pso type 1 (onset <

40 years).

Instead, an association with Pso type1 and the G-allele of NLRP3

rs10733113 (χ2=9.59, OR (95%CI); 1.76 (1.23-2.53), P=0.0020) was

found (Table 11). This polymorphism had previously been found over-

transmitted to individuals with a more widespread Pso in a family-based

study (Carlstrom, Ekman et al. 2012). Pso type1 is considered a specific

entity with higher degree of heritability and is generally considered to be

associated with a more severe Pso (Henseler and Christophers 1985,

Boehncke and Schon 2015). Thus, the results of this study strengthen the

putative role of this polymorphism for the severity of psoriasis skin

disease.

An association was identified between the major, C-allele of NLRP3-

Q705K rs35829419 (χ2=4.72, OR (95% CI); 1.63 (1.04-2.55), p=0.030)

and PsA patients with a destructive-/deforming disease phenotype that

could indicate a role in disease severity (Table 11).

The association with carriage of the T-allele of NLRP1 rs8079034 and

patients who, at any time, had been prescribed a csDMARD (χ2=9.59, OR

(95%CI); 1.76 (1.23-2.53), P=0.0020) (Table 11) is interesting. A similar

trend, although not reaching significance was seen for patients

prescribed a bDMARD (χ2=3.24, OR (95%CI); 1.48 (0.96-2.28),

P=0.072) (data not shown). Prescription of a DMARD can be considered

a surrogate marker for a more aggressive disease. Thus, the data from

this study could indicate an association with a more severe PsA disease

phenotype and this polymorphism.

So far, only one study has been published in which SNPs in genes related to the

inflammasome have been investigated in patients with PsA (Loft, Skov et al.

2018). In their study, two of the SNPs investigated in this study were analysed,

rs2043211 in CARD8 and rs878329 in NLRP1 and no significant associations with

PsA in comparison with population controls were detected. Thus, this study is the

first in which an association of polymorphisms in inflammasome genes and PsA

have been shown.

38

Table 11. Distribution of frequencies of genotypes and alleles of NLRP1

(rs878329 and rs8079034) and NLRP3 (rs35829419 and rs10733113) in different

phenotypes of PsA. All data presented as n (%). Only SNPs and phenotypes with

significant associations are shown.

Axial disease

Peripheral disease

OR (95%CI) χ2 p-value

NLRP1 rs878329

N=107 N=539

CC 26 (24) 80 (15) Ref. GC 51 (48) 275 (51) 0.57 (0.33-0.97) 4.31 0.038 GG 30 (28) 184 (34) 0.50 (0.28-

0.90) 5.41 0.020

CC (vs GC+GG) 26 (24) 80 (15) 1.84 (1.12-3.04) 5.82 0.016

C carriage 77 (72) 355 (66) 1.33 (0.84-2.10) 1.50 0.22 C allele 103 (48) 435(41) 1.37 (1.02-1.84) 4.45 0.035 csDMARD2

ever never csDMARD

NLRP1 rs8079034

N=499 N=216

TT 19 (4) 5 (2) Ref. CT 160 (32) 47 (22) 0.90 (0.32-2.53) 0.043 0.84

CC 320 (64) 164 (76) 0.51 (0.19-1.40) 1.75 0.19

CC (vs. CT+TT) 320 (64) 164 (76) 0.57 (0.39-0.81) 9.59 0.0020

T carriage 179 (36) 52 (24) 1.76 (1.23-2.53) 9.59 0.0020 T allele 198 (20) 57 (13) 1.63 (1.18-2.24) 9.09 0.0026 Pso-type 11 Not Pso-type 1 NLRP3 rs10733113

N=439 N=210

AA 5 (1) 8 (4) Ref. GA 87 (20) 53 (25) 2.63 (0.82-8.45) 2.78 0.095

GG 347 (79) 149 (71) 3.73 (1.20-11.58) 5.89 0.015 GG (vs. GA+AA) 347 (79) 149 (71) 1.54 (1.06- 2.25) 5.16 0.023 G carriage 434 (99) 202 (96) 3.44 (1.11-10.64) 5.16 0.023

G allele 781(89) 351(84) 1.58 (1.13-2.21) 7.38 0.007 Destructive

disease Non-destructive disease

NLRP3-Q705K rs35829419

N=314 N=360

AA 0 (0) 2 (0.3) - CA 32 (10) 54 (15) Ref. CC 282 (90) 304 (84) 1.56 (0.98-2.50) 3.59 0.058

CC (vs. CA+AA) 282 (90) 304 (84) 1.62 (1.02-2.58 4.25 0.039

C allele 596 (95) 662 (92) 1.63 (1.04-2.55) 4.72 0.030 1skin psoriasis with onset before 40 years 2csDMARDS= conventional synthetic disease modifying anti-rheumatic drug

39

In two recent publications from Spalinger et al., an interesting link between

PTPN22 and the NLRP3 inflammasome have been discovered. In their first study,

they discovered that NLRP3 activation is negatively regulated by tyrosine

phosphorylation and that PTPN22 is the phosphatase responsible for the

dephosphorylation and subsequent activation of NLRP3 (Spalinger, Kasper et al.

2016). In their second publication they present data indicating an involvement of

autophagosomes, where phosphorylated but not non-phosphorylated NLRP3

were found in autophagosomes (Spalinger, Lang et al. 2017). Thus, the

dephosphorylation of NLRP3 by PTPN22 protects the NLRP3 from

autophagosomes and lead to increased inflammasome activity, with a subsequent

increase in inflammatory mediators such as IL-1β and IL-18.

The PTPN22+1858T variant is thought to be a gain-of –function mutation, but

published data are conflicting (Vang, Congia et al. 2005). Considering the results

from Spalinger et al., an increased dephosphorylating activity of the mutated

PTPN22 (with a tryptophan in position 620) could lead to a higher NLRP3

inflammasome activity and increased inflammation. In conclusion, the data

linking PTPN22 and inflammasomes illustrate the great complexity in the

regulation of immune response and autoimmunity and strengthens the need for

further studies in the area.

Analysis of biomarkers (Paper III)

In this study, we decided to investigate biomarker expression in PsA in relation

to disease activity, disease phenotypes and in comparison with healthy controls.

A total of 39 biomarkers were analysed, IL-18, calprotectin (analysed with ELISA)

and 37 from the MSD®, V-plex, 40-plex kit® (Table 7). In addition to standard

statistical methods, OPLS-DA was used. OPLS is a modification of the partial

least squares method that has been used in chemometrics analysis, with similar

capacity as the original, but improved model interpretation (Trygg and Wold

2002, Eriksson, Rosen et al. 2012). With OPLS-DA it is possible to calculate

which variables contribute most to the difference between groups.

With OPLS-DA it was not possible to discriminate PsA from controls (Figure 4)

and no significant difference in individual biomarkers between patients and

controls was found using t-test. However, the relatively small number of controls

could lower the sensitivity and the results, therefore, should be interpreted with

caution.

40

Figure 4. Comparison of PsA patients and controls with OPLS-DA

In addition, with OPLS-DA no complete separation was visualised between PsA

disease phenotypes, but a visual trend was obvious, with individual biomarkers

differing significantly between the different phenotypes in t-tests (Figure 5,

Figure 6 and Table 12).

Variables reflecting disease activity at clinical examination

Significant associations with higher levels of CRP (pc=0.0008), IL-6 (pc =0.001),

IL-16 (pc =0.007), calprotectin (pc =0.014), IL-12/IL-23p40 (pc =0.02) and

ICAM-1 (pc =0.045) was detected in PsA patients, who, at clinical examination

and blood sample collection, presented with a moderate to high PsA disease

activity according to the investigating clinician (Figure 5, Table 12). These

associations indicate a linkage between these markers and disease activity.

Biomarkers in relation to PsA disease activity have previously been investigated

(Fink, Cauza et al. 2007, Madland, Larsen et al. 2007, Szodoray, Alex et al. 2007).

In the study by Szodoray et al. EGF, INF-α, VEGF, MIP-1α and IL-12p40

discriminated between both controls and subsets of PsA with different levels of

disease activity. Madland et al. found association between PsA disease activity

and calprotectin (Madland, Larsen et al. 2007) and in a small study by Fink et al.

higher levels of VEGF were associated with active PsA (Fink, Cauza et al. 2007).

Thus, our results confirm previously detected associations with calprotectin

(Madland, Larsen et al. 2007) and IL-12p40 (Szodoray, Alex et al. 2007), but did

41

not reveal any significant association with EGF, VEGF or MIP-1α. These

variations could be due to differences in study design, e.g., in the study by

Szodoray et al. PsA patients with a polyarthritic disease pattern were selected, the

ratio between PsA and controls differ and a different statistical method was used.

The study by Fink et al. is small and defines active PsA by the number of arthritic

joints. Consequently, direct comparison between the studies is difficult.

Figure 5. PsA patients with ≥ moderate disease activity compared with ≤ low

disease activity at clinical examination and collection of blood

Figure 1: Orthogonal partial least square analysis (OPLS) of PsA patients sub-grouped according to ≥

moderate disease activity and ≤ low disease activity. (a) Score scatter plot. (b) VIP (Variable

Importance for the Projection) plot showing degree of importance of the different biomarkers to the

model. Whiskers show the confidence interval of the importance value

42

Table 12. Biomarkers associated with different PsA disease characteristics.

Disease characteristic, n (%) Biomarker Concentration, mean (pg/ml) Pc-value

Variables at clinical examination

≥moderate ≤low

≥moderate disease activity1, 87 (32)

CRP 16.5 x 106 6.76 x 106 0.0008

vs. ≤low disease activity1, 185 (68) IL-6 2.35 1.24 0.001 IL-16 240 204 0.007 calprotectin 1.24 x 106 0.86 x 106 0.014 IL-12/IL-

23p40 157 121 0.02

ICAM-1 5.72 x 105 5.09 x 105 0.045 Overall disease characteristics

Polyarthritis Mono-/oligo arthritis

Polyarthritic disease pattern, 130 (52)

IL-6 2.13 1.02 0.0006

vs. mono-/oligo arthritis disease pattern, 123 (49)

SAA 13.0 x 106 5.41 x 106 0.009

CRP 13.1 x 106 5.62 x 106 0.012 IL-8 16.8 10.1 0.04 Axial Peripheral Axial disease with or without peripheral disease, 45 (17)

IL-6 2.20 1.44 0.044

vs. peripheral disease only, 220 (83)

IL-16 245 209 0.044

MIP-1β 108 95 0.039 Measurable

inflammation Not measurable inflammation

Measurable inflammation when clinically active PsA disease 126 (52)

CRP 15.5 x 106 4.16 x 106 0.0001

vs. not measurable inflammation when clinically active PsA disease 117 (48)

SAA 13.9 x 106 5.20 x 106 0.003

IL-6 2.10 1.12 0.003 VCAM 7.85 x 105 6.91 x 105 0.017 calprotectin 1.15 x 106 0.80 x 106 0.020 IL-17A 4.02 3.11 0.022 TNF-β 0.534 0.307 0.022 IL-16 225 198 0.025 IL-12/IL-

23p40 139 114 0.040

bDMARD ever Never bDMARD bDMARD2, ever 42 (16) vs. never bDMARD 221 (84)

TNF-β 0.864 0.338 0.0001

TNF-α 14.5 2.91 0.0003 calprotectin 1.76 x 106 0.885 x 106 0.0009 CRP 21.5 x 106 8.39 x 106 0.016 Tie-2 (lower

level) 3290 3530 0.027

1 upon clinical investigation and collection of blood. 2 etanercept, adalimumab, infliximab,

certolizumab, golilumab, abatacept, ustekinumab or infliximab

43

Dactylitis was also recorded, but only a few individuals (n=16) presented with

active dactylitis at investigation. In t-test analysis, patients with active dactylitis

at investigated had significantly higher levels of TNF-α (pc =0.012), but there was

no difference with Mann-Whitney U test. Of the 16 individuals, two individuals

had very high levels, contributing to the significance in t-test. Ongoing dactylitis

is a marker of a more severe disease phenotype associated with radiographic

progression and worse clinical outcome (Brockbank, Stein et al. 2005, Geijer,

Lindqvist et al. 2015, Mease, Karki et al. 2017), but due to small numbers, it is not

possible to draw conclusions from the current study. To investigate this further

a prospective study, preferably on patients with early PsA, is suggested.

Serological biomarkers in relation to disease phenotypes

We found significant associations with different clinical PsA disease phenotypes

and different serological biomarkers, e.g. mono-/oligoarthritic disease

phenotype compared with polyarthritis, PsA with or without axial disease, PsA

disease with measurable inflammation when clinically active PsA disease and PsA

with past or present treatment with bDMARD (Table 12 and Figure 6). No

association was found with a destructive/deforming disease phenotype.

In the sub-group of PsA patients who had, at any time, been prescribed bDMARD,

in the majority of cases TNF-inhibitors, increased levels of TNF-β (pc=0.0001),

TNF-α (pc=0.0003) calprotectin (pc=0.0009) and CRP (pc=0.016) were found.

Patients prescribed this treatment likely represents a more aggressive disease

phenotype. Most patients started with bDMARD after serum sampling (n=27),

only nine individuals were currently receiving bDMARD at the time of collection

of blood samples and in these cases, the concentration of TNF-α is dependent of

the relation to the last dose. Unfortunately, the relation between blood sampling

and the last dose was unknown. However, since TNF-inhibitors, would, most

likely reduce the concentration of TNF-α, the significant difference would not be

reduced. Thus, the higher levels of TNF-α, TFN-β, calprotectin and CRP, possibly

reflect a more aggressive disease phenotype with a need for biological treatment.

44

Figure 6. PsA patients with mono-/oligoarthritis compared with polyarthritis.

Figure 1: Orthogonal partial least square analysis (OPLS) of PsA patients sub-grouped according to ≥

moderate disease activity and ≤ low disease activity. (a) Score scatter plot. (b) VIP (Variable

Importance for the Projection) plot showing degree of importance of the different biomarkers to the

model. Whiskers show the confidence interval of the importance value.

In conclusion, in this study on well-characterized patients with PsA, interesting

associations with clinical disease phenotypes of PsA and biomarkers were

detected. The study highlights the heterogeneity of PsA disease, with different

biomarkers associated with different disease phenotypes and the association of

some biomarkers with PsA disease activity confirms the inflammatory nature of

PsA. The study confirms previous findings of PsA being a complex disease leading

to difficulties in setting diagnosis (Mease 2011, Coates and Helliwell 2017,

45

Marchesoni, De Marco et al. 2018), as none of the biomarkers analysed could,

neither by itself, nor in combination, separate PsA patients from healthy controls.

Perhaps different/new approaches for finding new and specific biomarkers for

PsA are needed. Recently, an interesting approach to find novel biomarkers to

differentiate PsA from Pso was used by Cretu and colleagues (Cretu, Gao et al.

2018), when novel protein markers previously found by a method using mass

spectrometry in synovial fluid and psoriasis plaque was used (Cretu, Prassas et

al. 2014, Cretu, Liang et al. 2015). In the study, serum samples from cases with

PsA, Pso and healthy controls were investigated. In their study CD5-like protein

(CD5L, also known as Apoptosis Inhibitor expressed by Macrophages, Integrin-

β5 (ITGβ5), Mac-2-binding protein (M2BP), Myeloperoxidase (MPO), MMP‐3,

and CRP levels were markers for PsA and the combination of ITGβ5, M2BP, and

CRP level differentiated PsA from cutaneous Pso, better than CRP level alone

(Cretu, Gao et al. 2018).

Biomarkers for RA and PsA with a focus on predictors for early joint damage were

reviewed recently by Mc Ardle (Mc Ardle, Flatley et al. 2015), and include a list of

candidate biomarkers for joint damage in RA and PsA. Considerably more

candidates were suggested for RA, but the list includes calprotectin, SAA, IL-1

and VEGF investigated in this thesis. In this study association with disease

activity and calprotectin was detected; SAA was associated with a polyarthritic

disease phenotype and measurable inflammatory activity when clinically active

PsA disease. In the review IL-6, IL-16 and CRP were suggested as being

candidates for joint damage in RA. In this study IL-6 and CRP were associated

with disease activity, polyarthritic disease phenotype and CRP with prescription

of bDMARD, IL-16 was associated with axial involvement and with measurable

inflammation when clinically active PsA disease.

Investigation of mortality, cause of death and incidence of

acute cardiovascular disease in patients with PsA compared

with the general population (Paper IV)

Mortality and cause of death

In this study, patients with PsA were compared with the general population of

Västerbotten County. An increased SMR was found in patients with PsA for death

due to disease(s) of the circulatory system (ICD 10; I00–I99) (SMR (95%CI); 1.64

(1.02-2.52), whilst no difference in SMR for overall mortality was seen (SMR

(95%CI); 1.22 (0.89-1.63). Causes of death are presented in Table 13 and Figure

7.

46

Table 13. Causes of death

Cause of death ICD codes

Female n (%)

Male n (%)

Female+Male n (%)

Overall 19 25 44

Circulatory system I00-I99 9 (47) 12 (48) 21 (48)

Malignant

neoplasms

C00-C97 6 (32) 8 (32) 14 (32)

Respiratory

system

J00-J99 0 1 (4) 1 (2)

Other causes 4 (21) 4 (16) 8 (18)

Figure 7. Causes of death in male and female PsA patients during the study

Factors associated with death in PsA patients

When traditional risk factors and putative PsA related risk factors were evaluated

in relation to death, patients who died were older, had a longer duration of skin

disease and had a higher mean disease activity index (DAI). In addition, a

significantly higher fraction of patients who died had used oral corticosteroids,

while a significantly reduced number had used NSAIDs. Also, among patients

who died a higher proportion had destructive-/deforming disease and a

significantly higher proportion had axial involvement (Table 14).

When all significant variables associated with death were included in a multiple

logistic regression model with backward elimination, predictors for death

47

remaining significant were DAI (OR 95% CI; 1.88 (1.30–2.72)) and axial

involvement (OR 95% CI 0.33 (0.15–0.74)), adjusted for age.

Table 14. Comparison of disease characteristics at the end of the study between

patients who died and those who were alive at the end of the study. Data are

presented as n (%) unless otherwise indicated.

Alive Dead p-value OR(95% CI)

Age, years ±SD (n) 58.4 ±13.0 (420) 70.4 ±13.7 (44) <0.001 1.08(1.05-1.11)

Duration PsA, years ±SD (n) 20.3 ±10.9 (419) 21.4 ±13.7 (44) 0.566 1.01(0.98-1.04)

Duration Pso, years ±SD (n) 29.9 ±14.9 (399) 37.9 ±19.3 (39) 0.002 1.03(1.01-1.05)

BMI kg/m2 ±SD (n) 27.7 ±5.2 (370) 27.2 ±4.7 (30) 0.636 0.98(0.91-1.06)

DAI mean ±SD (n) 3.87 ±0.82 (411) 4.49 ±1.13 (43) <0.001 1.94(1.43-2.64)

Male gender, n (%) 209 (50) 25 (57) 0.373 0.75(0.40-1.41)

Smoking (ever), n (%) 224 (54) 24 (60) 0.505 1.25(0.65-2.43)

Hypertension, n (%) 181 (43) 24 (55) 0.157 1.56(0.84-2.92)

Hyperlipidaemia, n (%) 66 (16) 5 (11) 0.435 0.68(0.26-1.79)

Diabetes, n (%) 49 (12) 9 (20) 0.099 1.93(0.87-4.25)

Destructive/deforming

disease, n (%)

204 (49) 29 (67) 0.021 2.16(1.11-4.21)

bDMARD (ever), n (%) 55 (13) 2 (4.5) 0.098 0.31(0.74-1.34)

csDMARD (ever), n (%) 285 (68) 27 (61) 0.383 0.75(0.40-1.43)

NSAID (ever), n (%) 303 (72) 24 (54) 0.014 0.46(0.24-0.86)

Oral corticosteroid

treatment (ever), n (%)

123 (29) 20 (46) 0.028 2.00(1.07-3.76)

Fulfilling Caspar-criteria,

n (%)

378 (90) 40 (91) 0.882 1.08(0.37-3.18)

Polyarthritis (according to

Moll and Wright), n (%)

173 (41) 24 (54) 0.088 1.71(0.92-3.20)

Dactylitis (ever), n (%) 119 (41) 10 (33) 0.421 0.72(0.33-1.60)

Nail-involvement (ever),

n (%)

162 (53) 16 (48) 0.640 0.84(0.41-1.73)

Axial involvement, n (%) 65 (15) 14 (32) 0.006 2.54(1.28-5.05)

Axial and peripheral joint

involvement, n (%)

35 (8.3) 11 (24) <0.001 3.65(1.70-7.86)

PsA=psoriatic arthritis, Pso=psoriasis, BMI=body mass index, DAI=disease activity index,

DMARD=disease modifying anti-rheumatic drug, NSAID=non steroidal anti inflammatory drug

Patients with axial involvement of disease were further sub-divided in axial

disease with- or without peripheral disease. In the cohort with both axial and

peripheral involvement a higher proportion died (27%) compared with patients

with only peripheral involvement of disease (7.2%) (OR (95%CI); 4.02 (1.84–

8.84), p < 0.001). No significant difference was seen when patients with axial

disease only were compared with patients with only peripheral disease (9.1% vs

7.2%, OR 1.28, 95% CI 0.37–4.48) (Figure 8). Thus, the association was

significant only in patients with involvement of both spine and joints possibly

indicating a higher disease burden and increased risk of death in these patients

that would be interesting to evaluate in future studies.

48

Figure 8. Proportion of PsA patients who died according to disease phenotype

Since age is an obvious cause of death, patients were also stratified into different

age groups. With stratification into three age groups (< 40 yrs, 40–74 yrs, and >

75 yrs), the impact of higher DAI on death remained in the age group 40-74 years

(n=352, p=0.001) and with stratification in four age groups (<40, 40-54, 55-69,

>70), in the group 55-69 years (n=190, p=0.005). In the group of patients < 40

years (n=36), only one death occurred, thus statistical calculation in this sub-

group was inapposite.

Cardiovascular Events

The incidence of acute cardiovascular events (CVE), defined as myocardial

infarction (MI) or ischemic stroke, was also investigated in relation to the general

population of Västerbotten. Unfortunately, it was not possible to use a diagnosis

of instable angina pectoris in the calculation of SIR due to a less specific definition

being used in the statistics for the general population. Twenty-nine patients with

PsA suffered an MI or stroke, with the MI being fatal in three cases. The SIR

(95%CI) for an MI or stroke was 0.60 (0.40-0.86). The association was only

shown to be significant in male patients.

Factors associated with CVE among PsA patients

Traditional risk factors together with any likely PsA related risk factors in relation

with a CVE (stroke, MI or unstable angina pectoris) were also investigated.

Patients with PsA who experienced an acute CVE, were significantly older, but

Different disease manifestations compared with peripheral disease

only

0

20

40

60

80

100

120

peripheral disease only

(n=359)

axial and perpheral

disease (n=46)

axial disease only

(n=33)

%

not dead (%)

dead (%)

*** ns

49

had a shorter PsA disease duration. In addition, significantly fewer had been

treated with NSAIDs and a significantly higher proportion of patients with an

event had hypertension, hyperlipidaemia and/or diabetes (Table 15).

When all variables significantly associated with a CVE, and gender, were analysed

in a multiple logistic regression model with backward elimination, predictors for

a CVE remaining significant were shorter PsA disease duration and less NSAID

treatment adjusted for age.

Table 15. Comparison of disease characteristics at the end of the study between

patients with or without event during the study. Data are presented as n (%)

unless otherwise indicated.

No Event Event p-value OR(95% CI)

Age, y± SD (n) 57.6 ±13.3 (430) 70.7 ±12.1(34) <0.001 1.08(1.05-1.11)

Duration PsA, y±SD (n) 19.9±10.9 (430) 14.0±13.5 (33) 0.004 0.94(0.90-0.98)

Duration Pso, y±SD (n) 29.5±15.0 (407) 31.2±21.5 (31) 0.565 1.01(0.98-1.03)

BMI, kg/m2±SD(n) 27.7±5.2 (273) 27.8±4.5 (27) 0.872 1.01(0.93-1.08)

DAI, mean ±SD (n) 3.90±0.85 (420) 4.24±1.02 (34) 0.030 1.47(1.04-2.08)

Male gender, n (%) 215 (50) 19 (56) 0.51 0.79(0.39-1.59)

Smoking (ever), n (%) 226 (54) 22 (67) 0.16 1.70(0.08-3.59)

Hypertension, n (%) 179 (42) 26 (76) <0.001 4.5(1.99-10.2)

Hyperlipidaemia n (%) 61 (14) 10 (29) 0.019 2.5(1.14-5.49)

Diabetes n (%) 49 (12) 9 (27) 0.008 2.89(1.27-6.58)

Destructive/deforming

disease, n (%)

216 (51) 17 (50) 0.94 0.97(0.48-1.96)

bDMARD (ever), n (%) 56 (13) 1 (2.9) 0.083 0.20(0.03-1.5)

csDMARD (ever), n (%) 288 (67) 24 (71) 0.67 1.18(0.55-2.54)

NSAID (ever), n (%) 314 (73) 13 (38) <0.001 0.23(0.11-0.47)

Oral corticosteroids

(ever), n (%)

128 (30) 15 (44) 0.083 1.86(0.91-3.77)

Fulfilling Caspar-criteria,

n (%)

387 (90) 31 (91) 0.86 1.12(0.33-3.83)

Polyarthritis (according

to Moll and Wright), n

(%)

180 (42) 17 (50) 0.36 1.39(0.69-2.79)

Dactylitis (ever), n (%) 119 (40) 10 (38) 0.85 0.92(0.41-2.11)

Nail-involvement (ever),

n (%)

168 (53) 10 (40) 0.20 0.58(0.25-1.34)

Axial involvement, n (%) 74 (17) 5 (15) 0.70 0.83(0.31-2.21)

Axial and peripheral joint

involvement, n (%)

41 (9.6) 5 (15) 0.33 1.63(0.60-4.44)

PsA=psoriatic arthritis, Pso=psoriasis, BMI=body mass index, DAI=disease activity index,

DMARD=disease modifying anti-rheumatic drug, NSAID=non steroidal anti inflammatory drug

50

In conclusion, our data showed increased mortality rates due to cardiovascular

diseases compared with the general population and among PsA patients, also an

association between death and disease activity that indicate an involvement of

inflammation.

Considering previous data, indicating a high prevalence of traditional risk factors

in Pso and PsA (e.g. hypertension, hyperlipidaemia, increased body mass index

and diabetes mellitus) and the indicated increased frequency of indirect markers

for CVD, such as sub-clinical atherosclerosis, increased arterial stiffness, an

increased risk of mortality and acute cardiovascular events compared with the

general population would be expected. However, data on mortality and

cardiovascular comorbidity are still conflicting;

In a recent population study from the UK, mortality and causes of death in RA

and PsA was investigated. In contrast with RA patients, where increased overall-

and cardiovascular mortality was found, neither overall- nor cardiovascular

mortality was increased in PsA patients (Ogdie, Maliha et al. 2017).

Our study indicate a small, but significant, increase in deaths due to diseases of

the circulatory system and death was associated with disease activity, indicating

an involvement of inflammation. Indeed, recent data support increased risk of

CVD in patients with PsA. For example, in a meta-analysis from 2017 (Polachek,

Touma et al. 2017), increased risk of CVD (including cardiovascular- and

cerebrovascular events and heart failure) with a pooled OR of 1.44 (1.22-1.96).

One of the studies included in the meta-analysis was a Swedish study published

2017, in which an increased risk of acute coronary syndrome, stroke and venous

thromboembolism was detected in patients with PsA (Bengtsson, Forsblad-d'Elia

et al. 2017). Also, in a Danish nation-wide population study a small, but

significant, increased risk for myocardial infarction in patients with PsA was

found that disappeared after age-stratification (Egeberg, Thyssen et al. 2017).

In the present study, no increase in CVE was detected in PsA patients. It is

possible that differences in study populations and methods of analysis result in

different findings. The highly heterogeneous pattern of PsA disease could also

contribute to the differences (Miller, Ellervik et al. 2013). If a whole population is

investigated, e.g. with registries, it is not possible to differentiate between

different disease phenotypes and the whole spectra of PsA disease from mild to

severe is included. If instead hospital based databases are used or cohorts from

rheumatology specialist clinics, studies more likely reflect PsA patients with a

more severe disease. It is also possible that in cohort studies, older patients and

patients with co-morbidities are not included.

51

Concluding remarks

The heterogeneity and complexity of PsA disease remains a challenge. In the

studies included in this thesis, different aspects on PsA disease have been

investigated. PsA patients have been compared with population controls and

different clinical disease phenotypes of PsA disease have been compared among

the PsA patients included. The majority of the disease characteristics were used

in all four studies, except for some variables (Table 5). In summary, some of the

different clinical features show association in more than one of the studies while

others do not (Table 16);

A destructive-/deforming disease phenotype was associated the major,

C-allele, of NLRP3-Q705K (rs35829419). A different definition was used

in Study I where the number of deformed joints was associated with

carriage of PTPN22+1858T.

Axial disease (with or without peripheral disease) was associated with the

C-allele and the CC genotype of NLRP1 rs878329 and with higher levels

of IL-6, IL-16 and MIP-1β. Axial disease was also associated with patients

who died in Study IV. In this study, this association was seen in the

combined phenotype with axial and peripheral disease (Figure 7).

A polyarthritic disease phenotype in comparison with mono-oligoartritic

disease phenotype was associated with higher levels of IL-6, SAA, CRP

and IL-8 in study II. In the other three studies no associations with these

phenotypes were detected.

Prescription of csDMARD was associated with NLRP1 rs8079034T in

Study II and in patients prescribed a bDMARD, higher levels of TNF-α,

TNF-β, calprotectin and CRP was detected. Patients prescribed a

csDMARD and/or bDMARD were not examined in Study I and no

associations were detected in Study IV.

Early onset of skin psoriasis (Pso type I) was investigated in Study I -III,

and an association was found with the G-allele of NLRP3 rs10733113,

while no associations were detected with PTPN22+1858C/T or any of the

biomarkers investigated in Study III.

Nail-disease was analysed in Study I-IV and no association with this

phenotype was detected in any of the studies.

52

Dactylitis (ever) was associated with PTPN22+1858T in study I, but no

significant association were detected with this phenotype in study II-IV.

Table 16. Summary of significant associations in study I-IV in relation to

different PsA phenotypes

Disease phenotype/s

Paper I Paper II Paper III Paper IV

Destructive-

/deforming disease

(II-IV) or number of deformed joints (I)

PTPN22+1858T

(carriage)

NLRP3-

Q705K

(rs35829419)

No associations No

associations

Measurable

inflammation when

clinically active PsA

disease (II-III) or disease activity index

(DAI) (IV)

Not analyzed No

associations

CRP, SAA, IL-6,

VCAM,

Calprotectin, IL-

17A, TNF-β, IL-16,

IL12IL23p40

Death

Dactylitis (ever) PTPN22+1858T

(carriage)

No

associations

No associations No

associations

Psoriasis type I No association NLRP3 rs10733113

(G-allele)

No associations Not analyzed

csDMARD (ever) Not analyzed NLRP1

rs8079034T

No associations No

associations

bDMARD (ever) Not analyzed No

associations

TNF-β,TNF-α,

Calprotectin, CRP,

Tie-2 (lower

level)

No

associations

PsA disease activity at clinical

investigation (III)

Not analyzed Not analyzed CRP, IL-6, IL-16, Calprotectin, IL-

12IL23p40,

ICAM-1

Not analyzed

Polyarthritis vs

mono-oligoarthritis (I-IV)

No associations No

associations

IL-6, SAA, CRP,

IL-8

No

associations

Axial involvement vs

peripheral disease

only (I-IV)

No associations NLRP1

rs878329 (C-

allele)

IL-6, IL-16,

MIP-1β

Death

Peripheral and axial disease vs peripheral

disease only (I-IV)

Not analyzed No associations

No associations Death

In comparison with controls from the general population, the PTPN22+1858T

and CARD8-C10X were associated with PsA patients and an increased SMR for

deaths in diseases of the circulatory system was detected for PsA patients. No

significant differences were found for any of the 39 biomarkers investigated in

study III for PsA patients compared with controls, although this result must be

interpreted with caution due to relatively few control subjects.

53

Conclusions

The main conclusions from this study on patients with psoriatic arthritis in a

population from northern Sweden can be summarized as follows:

The PTPN22+1858 C/T polymorphism was significantly associated with

PsA in comparison with controls. Among PsA patients, carriage of

PTPN22+1858T was associated with dactylitis and the number of

deformed joints.

The AA genotype of the inflammasome-related polymorphism CARD8-

C10X, was significantly associated with PsA patients compared with

controls, with the strongest association in patients with peripheral

disease without axial involvement.

Among PsA patients, different inflammasome related polymorphisms

were significantly associated with different PsA disease phenotypes; e.g.

the C-allele of NLRP1 rs878329 with axial involvement of disease, the G-

allele of NLRP3 rs10733113 with Pso type 1, the C-allele of NLRP3-Q705K

rs35829419 with a destructive-/deforming disease phenotype and the T-

allele of NLRP1 rs8079034 with patients prescribed a csDMARD.

A significant association with higher levels of CRP, IL-6, IL-16,

calprotectin, IL-12/IL-23p40 and ICAM-1 was detected among PsA

patients presenting with a moderate/high disease activity compared with

PsA patients with low /none disease activity.

Among PsA patients, different serological biomarkers were significantly

associated with different PsA disease phenotypes, e.g. IL-6, SAA, CRP

and IL-8 were associated with a polyarthritic disease phenotype; IL-6,

IL-16 and MIP-1β with axial disease with- or without peripheral disease;

CRP, SAA, IL-6, VCAM, Calprotectin, IL-17A, TNF-β , IL-16 and IL-

12/IL-23p40 with measurable inflammation when clinically active PsA

disease; TNF-β, TNF-α, calprotectin, CRP and Tie-2 with PsA patients

prescribed a bDMARD.

An increased SMR for death in diseases of the circulatory system was

detected in PsA patients in comparison with the general population.

Among PsA patients, significant predictors for death were disease activity

(DAI) and axial involvement.

54

Future perspectives

A correct, early diagnosis and prediction of disease severity in early stages of

disease are highly prioritised in the research agenda in PsA. As discussed, the

complexity and heterogeneity of PsA disease is substantial, e.g. in comparison

with RA. For example, an easy set of biomarkers as diagnostic aid and to monitor

disease activity would be of great value. In RA, although not positive in all cases,

RF and the highly specific ACPA are included in the diagnostic criteria. Recently,

a commercial blood test has been developed to monitor disease activity in RA with

a score calculated from concentrations of 12 serum biomarkers (VCAM-1, EGF,

IL-6, TNF-receptor type 1, MMP-1, MMP-3, cartilage glycoprotein 39 (YKL-40,

leptin, resistin, SAA, VEGF-A and CRP) (Eastman, Manning et al. 2012).

In the more heterogeneous PsA perhaps new strategies might be required? As

suggested by previous research and the results presented in this thesis, PsA

patients possibly need to be sub-categorized to develop diagnostic and prognostic

tools. The different phenotypes of skin disease possibly also needs consideration.

Thus, in the future, it would be highly beneficial if studies of patients with PsA

include all types of PsA, but that patients also are sub-grouped according to

different phenotypes, both for the skin and joint disease.

The associations with different inflammasome genes and PsA suggest a role of

inflammasomes in the disease. Different mutations of NLRP3 are causally

associated with rare auto-inflammatory conditions characterized by fever and

excessive IL-1 production. In this study an association was found between the

major, C-allele of NLRP3-Q705K and PsA patients with a destructive-/deforming

disease phenotype. The functional polymorphism at this site corresponds to a

transition from a glutamine (Q) to a lysine (K). This transition results in a “gain

of function” of the NLRP3-inflammasome leading to excessive IL-1β and IL-18

production (Verma, Sarndahl et al. 2012). Thus, the association with a

destructive-/deforming disease phenotype detected in this study is not to the

minor allele causing excessive IL-1β and IL-18 production.

In clinical practice, I have met patients with PsA describing fever as an associated

feature in conjunction with other signs of active PsA disease. Interestingly, a case

report on an HLA-B27 positive male patient presenting with fewer, arthritis of

large joints and elevated CRP-levels showed that the patient was heterozygous for

both NLRP3-Q705K and CARD8-C10X. The patient had elevated IL-1β levels and

responded well to the IL-1 blocking agent Anakinra (Verma, Lerm et al. 2008).

PsA patients are generally considered unresponsive to treatment with IL-1

blockers, but elevated levels of IL-1β has been found in psoriatic lesions (Buerger,

Richter et al. 2012). Considering the heterogeneity of PsA patients, it is possible

55

that the sub-group presenting with fever could respond to this treatment? It

would be interesting to analyse both the combination of CARD8-C10X and

NLRP3-Q705K polymophisms and the levels of IL-1β and IL-18 in this sub-group

of PsA patients in early/active disease.

In this study, a relatively large cohort of patients with PsA is included, but the

patients have been included over a long period and in different studies with a

specified focus. In the future, it would be interesting to investigate PsA patients

in both early and established disease, and in addition to the disease phenotypes

investigated in this thesis, also sub-categorize patients according to other joint

and skin phenotypes and to include anamnestic symptoms of fever and

gastrointestinal symptoms. It would also be interesting to analyse biomarkers in

blood samples, synovial fluid and synovial biopsies in both early/active disease

and after treatment, when the patients are in remission. Also important to

consider in future studies are the patient related outcomes such as pain, fatigue,

sleep and emotional well-being.

The studies presented in this thesis confirm the substantial heterogeneity of PsA

disease. In this thesis, no obvious pattern for any of the investigated disease

phenotypes was detected, but the results confirm the inflammatory nature of PsA

disease and some risk factors for a destructive disease phenotype were detected.

The results from these studies can be used as a ground for future studies in PsA.

56

Acknowledgements

So many people have contributed in different ways to make the production of this

thesis possible. In particular I want to thank;

Gerd-Marie Alenius, my supervisor, for endless patience and support! Thank you

for giving me the opportunity to work at the clinic and to be your PhD-student in

this interesting project! Without you this book would not have existed.

My co-supervisor, Solbritt Rantapää-Dahlqvist for always giving helpful

comments and advice. Your knowledge and expertise have been invaluable!

Martin Johansson, co-author, for help with the genetic analysis and statistical

calculations in Paper I.

Linda Johansson, co-author, for performing genetic analysis of controls and for

critical evaluation of Paper II.

Alf Kastbom and Peter Söderqvist for valuable advice in the planning of study II

and for genetic analysis of the patients in the same study.

Joakim Bygdell, NBIS (National Bioinformatics Infrastructure Sweden), for

performing the OPLS-DA and t-test analysis in Paper III.

Marie-Louise Öhman, for performing statistical analyses in Paper IV and Simon

Vallin for statistical advice in the same study.

Solveig Linghult, Maria Lindberg, Kristina Eriksson, Inger Bucht, Sonja Odeblom

and Viktoria von Zweigbergk for technical support.

Brian Ellis for valuable language checking and comments on my papers and

thesis.

The whole research group at Rheumatology for fruitful scientific discussions, for

example at journal club in the library. A special thanks to Mikael Brink for help

with construction of the new database and to Lisbeth Ärlestig who I have called

when things have been unclear, you know the answers!

All my dear colleagues and co-workers at the Department of Rheumatology for

your patience with my ups and downs during this project. Thank you for being

there and making me laugh, in both success and difficulties and for taking care of

my patients when I was away. You make our clinic a great place to work at!

57

All patients with Psoriatic Arthritis, who kindly participated in the studies,

donated blood and answered questionnaires.

My family, Peter, Alexander, André, Julia and Jacob for love and support. You are

the lights of my life! And thank you Peter, for your everlasting patience, for taking

care of all “ground service” during the production of this thesis and for letting me

leave piles of papers all over our apartment.

My parents, Ingrid and Gunnar, who taught me early in life to appreciate the joy

of learning, for always being supportive and believing in me and for your help

with the children when they were young and I wanted to work and study.

All my friends who I have neglected even though you mean so much to me. I hope

you have not forgotten me!

58

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