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Major histocompatibility complex associations of ankylosing spondylitis are complex and involve further epistasis with ERAP1

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Ankylosing spondylitis (AS) is a common, highly heritable, inflammatory arthritis for which HLA-B*27 is the major genetic risk factor, although its role in the aetiology of AS remains elusive. To better understand the genetic basis of the MHC susceptibility loci, we genotyped 7,264 MHC SNPs in 22,647 AS cases and controls of European descent. We impute SNPs, classical HLA alleles and amino-acid residues within HLA proteins, and tested these for association to AS status. Here we show that in addition to effects due to HLA-B*27 alleles, several other HLA-B alleles also affect susceptibility. After controlling for the associated haplotypes in HLA-B, we observe independent associations with variants in the HLA-A, HLA-DPB1 and HLA-DRB1 loci. We also demonstrate that the ERAP1 SNP rs30187 association is not restricted only to carriers of HLA-B*27 but also found in HLA-B*40:01 carriers independently of HLA-B*27 genotype.
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ARTICLE
Received 8 Feb 2015 |Accepted 7 Apr 2015 |Published 21 May 2015
Major histocompatibility complex associations
of ankylosing spondylitis are complex and involve
further epistasis with ERAP1
Adrian Cortes1,SaraL.Pulit
2,PaulJ.Leo
1, Jenny J. Pointon3, Philip C. Robinson1, Michael H. Weisman4,MichaelWard
5,
Lianne S. Gensler6, Xiaodong Zhou7, Henri-Jean Garchon8,9, Gilles Chiocchia8, Johannes Nossent10,11,BenedicteA.Lie
12,13,
Øystein Førre14, Jaakko Tuomilehto15,16,17, Kari Laiho18, Linda A. Bradbury1, Dirk Elewaut19,20, Ruben Burgos-Vargas21,
Simon Stebbings22, Louise Appleton3,ClaireFarrah
3, Jonathan Lau3,NigilHaroon
23, Juan Mulero24, Francisco J. Blanco25,
Miguel A. Gonzalez-Gay26,C.Lopez-Larrea
27,28,PaulBowness
3, Karl Gaffney29, Hill Gaston30,DafnaD.Gladman
31,32,33,
Proton Rahman34, Walter P. Maksymowych35,J.BartA.Crusius
36, Irene E. van der Horst-Bruinsma37, Raphael Valle-On
˜ate38,
Consuelo Romero-Sa
´nchez38, Inger Myrnes Hansen39, Fernando M. Pimentel-Santos40, Robert D. Inman23,JavierMartin
41,
Maxime Breban8,42,BryanPaulWordsworth
3, John D. Reveille7, David M. Evans1,43,44,PaulI.W.deBakker
2,45
& Matthew A. Brown1
Ankylosing spondylitis (AS) is a common, highly heritable, inflammatory arthritis for which
HLA-B*27 is the major genetic risk factor, although its role in the aetiology of AS remains elusive.
To better understand the genetic basis of the MHC susceptibility loci, we genotyped 7,264
MHC SNPs in 22,647 AS cases and controls of European descent. We impute SNPs, classical
HLA alleles and amino-acid residues within HLA proteins, and tested these for association to AS
status. Here we show that in addition to effects due to HLA-B*27 alleles, several other HLA-B
alleles also affect susceptibility. After controlling for the associated haplotypes in HLA-B,we
observe independent associations with variants in the HLA-A,HLA-DPB1 and HLA-DRB1 loci. We
also demonstrate that the ERAP1 SNP rs30187 association is not restricted only to carriers of
HLA-B*27 but also found in HLA-B*40:01 carriers independently of HLA-B*27 genotype.
DOI: 10.1038/ncomms8146 OPEN
1University of Queensland Diamantina Institute, Princess Alexandra Hospital, Brisbane 4102, Australia. 2Department of Medical Genetics, Center for Molecular Medicine, University
Medical Center Utrecht, Utrecht 3584, The Netherlands. 3NIHR Oxford Musculoskeletal Biomedical Research Unit, Nuffield Orthopaedic Centre, Headington, Oxford OX3 7LD, UK.
4Department of Medicine/Rheumatology, Cedars-Sinai Medical Center, Los Angeles, California 90048, USA. 5Intramural Research Program, National Institute of Arthritis and
Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, Maryland 20892-1468, USA. 6Department of Medicine/Rheumatology, University of California, San
Francisco, California 94143, USA. 7Department of Rheumatology and Clinical Immunogenetics, University of Texas Health Science Center at Houston, Houston, Texas 77030, USA.
8INSERM UMR 1173, Universite
´de Versailles Saint Quentin en Yvelines, Laboratoire d’excellence Inflamex, Saint-Quentn-En-Yvelines 78180, France. 9Genetics Division, Ho
ˆpital
Ambroise Pare
´, AP-HP, and Universite
´de Versailles Saint Quentin en Yvelines, Boulogne-Billancourt 78180, France. 10 School of Medicine, University of Western Australia, Perth, WA
6009, Australia. 11Department of Rheumatology, Sir Charles Gairdner Hospital, Perth, WA 6009, Australia. 12Department of Medical Genetics, University of Oslo and Oslo University
Hospital, Oslo 0310, Norway. 13 Department of Immunology, Oslo University Hospital, Oslo 0310, Norway. 14 Department of Rheumatology, Oslo University Hospital, and University of
Oslo, Oslo 0310, Norway. 15 Department of Chronic Disease Prevention, National Institute for Health and Welfare, 00271 Helsinki, Finland. 16 Centre for Vascular Prevention, Danube-
University Krems, 3500 Krems, Austria. 17 Diabetes Research Group, King Abdulaziz University, 21589 Jeddah, Saudi Arabia. 18 Department of Medicine, Paijat-Hame Central Hospital,
Lahti, Finland. 19Department of Rheumatology, Gent University Hospital, Gent 9052, Belgium. 20 VIB Inflammation Research Center, Ghent University, Gent 9052, Belgium.
21 Department of Rheumatology, Hospital General de Mexico and Universidad Nacional Autonoma de Mexico, Mexico City 06726, Mexico. 22 Department of Medicine, Dunedin
School of Medicine, University of Otago, Dunedin 9016, New Zealand. 23 Division of Rheumatology, Toronto Western Hospital, University of Toronto, Toronto M5T2S8, Canada.
24 Department of Rheumatology, Hospital Puerta de Hierro, Madrid 28222, Spain. 25 Department of Rheumatology, Complejo Hospitalario La Corun
˜a, INIBIC, La Corun
˜a 15006, Spain.
26 Department of Rheumatology, Hospital Marques de Valcecillas, IFIMAV, Santander 39008, Spain. 27 Department of Immunology, Hospital Universitario Central de Asturias, Oviedo
33011, Spain. 28Fundacio
´n Renal ‘In
˜igo A
´lvarez de Toledo’, Madrid 33011, Spain. 29 Department of Rheumatology, Norfolk and Norwich University Hospital, Norwich NR4 7UY, UK.
30 Department of Medicine, University of Cambridge, Addenbrookes Hospital, Cambridge CB2 0SP, UK. 31Division of Rheumatology, University of Toronto, Toronto, ON M4N 3M5,
Canada. 32 Toronto Western Research Institute, Toronto ON M4N 3M5, Canada. 33 Psoriatic Arthritis Program, University Health Network, Toronto ON M4N 3M5, Canada.
34 Memorial University of Newfoundland, Newfoundland NL A1B 3X9, Canada. 35 Department of Medicine, University of Alberta, Alberta T6G 2R7, Canada. 36 Department of Medical
Microbiology and Infection Control, Laboratory of Immunogenetics, VU University Medical Center, Amsterdam 1081 BT, The Netherlands. 37 Department of Rheumatology, VU
University Medical Centre, Amsterdam 1081 BT, Netherlands. 38Spondyloarthropaty Group-Division of Rheumatology, Hospital Militar Central/Universidad de La Sabana, Transversal
3 # 49-00, Bogota
´, NA, Colombia. 39 Helgelandssykehuset, 8613 Mo i Rana, Norway. 40 Chronic Diseases Research Centre (CEDOC), Faculdade de Cie
ˆncias Me
´dicas, Universidade
Nova de Lisboa, Lisboa 1169-056, Portugal. 41 Instituto de Parasitologı
´
a y Biomedicina Lo
´pez-Neyra, Consejo Superior de Investigaciones–Cientı
´
ficas, Granada 18100, Spain. 42 Division
of Rheumatology, Ho
ˆpital Ambroise Pare
´, AP-HP, and Universite
´de Versailles Saint Quentin en Yvelines, Boulogne-Billancourt 92100, France. 43 MRC Integrative Epidemiology Unit,
University of Bristol, Bristol, UK. 44 School of Social and Community Medicine, University of Bristol, Bristol, UK. 45 Department of Epidemiology, Julius Center for Health Sciences and
Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands. Correspondence and requests for materials should be addressed to M.B. (email: matt.brown@uq.edu.au).
NATURE COMMUNICATIONS | 6:7146 | DOI: 10.1038/ncomms8146 | www.nature.com/naturecommunications 1
&2015 Macmillan Publishers Limited. All rights reserved.
Ankylosing spondylitis (AS) is a common, highly heritable1,
inflammatory arthritis for which HLA-B*27 is the major
genetic risk factor. To better understand the genetic basis
of the major histocompatibility complex (MHC) susceptibility
loci, we genotyped 7,264 MHC single-nucleotide polymorphisms
(SNPs) in 9,069 AS cases and 13,578 population controls of
European descent using the Illumina Immunochip microarray. In
addition to extremely strong effects due to HLA-B*27:02 and
B*27:05, several other HLA-B alleles (B*07:02,B*13:02,B*40:01,
B*40:02, B*47:01,B*51:01 and B*57:01) also affect susceptibility to
AS. HLA-B-independent associations were demonstrated with
variants in the HLA-A,HLA-DPB1 and HLA-DRB1 loci. We also
demonstrate that the ERAP1 SNP rs30187 association is not
restricted only to carriers of HLA-B*27 but also found in HLA-
B*40:01 carriers independently of the HLA-B*27 genotype. The
presence of associations in both HLA class I and II loci might
reflect effects on antigen presentation to both CD4 þand CD8 þ
T lymphocytes in the pathogenesis of AS.
While the classical HLA-B*27 allele is found in over 85% of AS
patients2–4, it is clearly not sufficient alone to cause disease, with
only 1–5% of HLA-B*27 carriers developing the disease. From
epidemiological data, it is evident that susceptibility to AS is
affected by other genes within and outside the MHC1. Indeed, 26
risk loci outside the MHC have now been identified by genome-
wide association studies5–8.
The biological mechanism(s) by which HLA-B27 confers risk of
disease remains elusive. The main hypotheses regarding this
mechanism can be divided into canonical mechanisms based on
the known function of HLA-B27 within the adaptive immune
system, and non-canonical mechanisms related to unusual
properties of HLA-B27, notably its propensity to dimerise or
misfold. Suggested canonical mechanisms propose either that
HLA-B27 is uniquely capable of presenting particular peptide(s)
found at sites of inflammation in AS to cytotoxic T lymphocytes
(the arthritogenic peptide hypothesis)9or that HLA-B27 is
associated with reduced gut mucosal immunity, leading to
migration of enteric bacteria across the intestinal mucosa,
driving the production of the pro-inflammatory cytokine
interleukin (IL)-23 and development of AS (the mucosal
immunodeficiency hypothesis)10,11. Both these theories place
antigenic peptide presentation and handling as critical steps in
the pathogenesis of AS. One of the first non-MHC susceptibility
loci to be identified in AS was endoplasmic reticulum
aminopeptidase 1 (ERAP1)5, the main function of which is to
trim peptides in the endoplasmic reticulum (ER) to optimal length
for binding to MHC class I molecules on antigen-presenting cells
for subsequent interaction with CD8þT cells12,13. Moreover, this
association is so far uniquely found in HLA-B*27-positive disease7.
HLA-B27 has an unusual property of forming homodimers
through disulphide bonding of the unpaired cysteine residue at
position 67 (ref. 14). It has been proposed that these homodimers
may cause AS through abnormal presentation of peptides or by
facilitating ‘abnormal’ interaction with natural killer cells15. Apart
from HLA-B*27, the subtypes of the alleles HLA-B*14,HLA-B*15,
HLA-B*38,HLA-B*39 and HLA-B*75 encode a cysteine residue at
position 67 but of these there is only evidence that HLA-B*14 may
be AS associated16,17. It is also unclear if these other non-HLA-
B27 Cys67 variants can form homodimers. In addition, Cys67 is
found on all HLA-B27 subtypes, including the subtypes HLA-
B*27:06 and HLA-B*27:09, which are not AS associated18,19.A
further hypothesis suggests that abnormal folding of the HLA-
B27 molecule during assembly results in ER stress and activation
of the unfolded protein response20,21. ER stress is evident in the
HLA-B*27-transgenic rat model of AS and correlates with
production of IL-23 (ref. 21), but has not been demonstrated in
HLA-B*27-positive patients22–24.
While non-B27 HLA associations have been reported, notably
with HLA-B40 (refs 25–27) and HLA-A*02 (ref. 8), most have not
been definitive or replicated in independent studies. In this study,
we analyse the associations of AS across the MHC aiming to
identify functional and potentially causal variants using a large,
previously reported, panel of cases and controls of European
ancestry8. Here we extend on our primary analysis of this cohort
by fine mapping the MHC region with imputation of SNPs, MHC
class I and II classical alleles, and amino-acid residues within the
classical HLA proteins28. In addition to HLA-B27, we identify
further HLA-B and other HLA class I and II alleles associated
with AS, and demonstrate that HLA-B40 in addition to HLA-B27
interacts with ERAP1 to cause disease. This implicates both CD4
and CD8 lymphocytes in AS pathogenesis and suggests that
HLA-B40 and HLA-B27 operate by similar mechanisms to induce
the disease.
Results
HLA-B susceptibility alleles. At the HLA-B locus, 38 classical
alleles at four-digit resolution were imputed. All SNP, HLA and
amino-acid association P-values were determined by logistic
regression. As expected, the two common HLA-B*27 alleles
in the European population, B*27:02 (odds ratio (OR) ¼43;
P¼1.07 10 122) and B*27:05 (OR ¼62; Po10321), were the
most significantly associated with disease risk (Fig. 1a–b;
Tables 1 and 2). Controlling for the effect of the two B*27 alleles,
we identified the protective alleles HLA-B*07:02 (OR ¼0.82;
P¼5.04 10 6)andHLA-B*57:01 (OR ¼0.75; P¼5.13 10 4;
Table 2). Moderate association was also observed, sequentially,
with the risk alleles HLA-B*51:01 (OR ¼1.33; P¼2.14 10 3),
HLA-B*47:01 (OR ¼2.35; P¼2.25 103), HLA-B*40:02
(OR ¼1.59; P¼4.65 103), HLA-B*13:02 (OR ¼1.43; P¼
4.29 103)andHLA-B*40:01 (OR¼1.22; P¼4.93 10 3).
No evidence of further susceptibility alleles was observed after
controlling for the risk and protective alleles identified above
(P40.05; Fig. 1d). The HLA-B associations were similar in both
HLA-B*27-positive and HLA-B*27-negative restricted analyses
(Supplementary Tables 1–6).
Non-HLA-B susceptibility loci in the MHC. To assess whether
other MHC loci affect disease susceptibility independently from
the HLA-B locus, we performed additional conditional analyses.
Adjusting for the HLA-B susceptibility alleles identified, we
observed an association signal with SNPs in the HLA-A locus
(rs2975033; OR ¼1.22; P¼6.16 10 10) and with the classical
allele HLA-A*02:01 (OR ¼1.22; P¼1.41 10 9; Fig. 1c–d).
The risk allele ‘A’ of rs2975033 was in near perfect linkage
disequilibrium with the risk allele HLA-A*02:01 (r2¼0.97).
Further controlling for the effect of the susceptibility SNP
rs2975033 in HLA-A revealed an independent signal with SNPs
(rs1126513; OR ¼1.21; P¼2.46 10 7) in the class II locus
HLA-DPB1 (Fig. 1e); no association of similar strength to those
seen with SNPs (P410 5) were observed with classical HLA-
DPB1 alleles (Fig. 1f). After controlling for the effect of the SNP
rs1126513 in HLA-DPB1, we observed an association with the
SNP rs17885388 (OR ¼1.16; P¼1.27 10 5) in the HLA-DRB1
locus, and a similar level of significance was also observed with
the class II allele HLA-DRB1*01:03 (P¼3.78 10 5). No further
associations were observed after controlling for all identified
effects (P4510 5; Fig. 1i–j).
Association signals and amino-acid positions in HLA proteins.
We observed disease-associated alleles at MHC class I and II loci.
Classical alleles at these loci determine the amino-acid sequence
of the respective HLA proteins, which could in turn influence the
ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/ncomms8146
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&2015 Macmillan Publishers Limited. All rights reserved.
specificity of the peptides presented to CD8 þand CD4 þ
T lymphocytes. We, therefore, analysed the polymorphic amino-
acid residues at these proteins to assess their effect in disease
susceptibility. In this analysis, the strongest association was
observed for amino-acid position 97 in HLA-B (omnibus
Po10 3221; Table 1; Fig. 1a–b). In addition, through conditional
analysis, we found that the association at the HLA-B*27 allele,
and other HLA-B*27-associated polymorphisms, was explained
by position 97 while the reverse was not true (Supplementary
Table 7). This polymorphic position carries as many as six
different amino-acid residues in the population (Fig. 2),
each conferring a different degree of risk (or protection) to
disease, consistent with the analysis of HLA-B alleles mentioned
above (Table 2). Position 97 lies in the floor of the HLA-B
peptide-binding groove (Fig. 3), located in the C/F pocket,
also referred as the C-terminal pocket, which anchors the side
chain of the C-terminal peptide residue29. Asparagine at position
97 is uniquely observed in HLA-B*27 alleles. Threonine at
position 97 (predominantly found in HLA-B*51 alleles) was also
found to increase disease risk (OR ¼1.12; P¼4.50 10 3);
serine (found in HLA-B*07 and *08 alleles) decreased risk of
disease (OR ¼0.86; P¼5.2 10 8); and valine (found in
HLA-B*57 alleles) was also protective (OR ¼0.68;
P¼1.4 10 8; Table 3).
Strong associations were also observed with the amino-acid
positions 70, 114, 77 and 67 of HLA-B but these signals were
strongly attenuated after conditioning on amino-acid position 97.
In contrast, none of these positions could explain the association
at position 97. In particular, there was little evidence of
association at position 67 (that is, the position where disulphide
bonding of unlinked cysteine residues might occur) after
conditioning on position 97 (P-value ¼0.04; Supplementary
Table 8).
The most strongly associated amino acid of the HLA-A
molecule, after conditioning on associated HLA-B alleles,
was amino acid valine at position 95 (P¼3.70 10 9).
HLA-A HLA-C HLA-B
HLA-DRB1
Chromosome 6 posiition (Mb)
HLA-DQA1
HLA-DQB1
HLA-DPB1
HLA-DPA1 HLA-A
HLA-C
HLA-B
HLA-DRB1
HLA-DQA1
HLA-DQB1
HLA-DPA1
HLA-DPB1
3,000
2,500
2,000
1,500
1,000
500
0
10
8
6
6
4
4
2
2
0
0
1
3
5
4
4
2
2
0
0
29.5 30 30.5 31 31.5 32 32.5 33
1
3
5
7
3,000
–log10(p)
–log10(p)
–log10(p)–log10(p)–log10(p)
2,500
2,000
1,500
1,000
500
0
10
8
6
6
4
4
2
2
0
0
HLA-DRB1*01: 03
HLA-A*02:01
HLA-C*02
HLA-C*01
HLA-C*07
HLA-C*0202
HLA-C*0102
HLA-B*2705
HLA-A*2702
HLA-B*27
0
r2
1
HLA-A*02
1
3
5
4
4
2
2
0
0
1
3
5
7
–log10(p)–log10(p)–log10(p)–log10(p)
–log10(p)
Figure 1 | Association results with ankylosing spondylitis susceptibility in the MHC. Omnibus SNP and amino-acid association tests are shown in a,c,e,
gand i, and classical allele association tests with two- and four-digit resolution in b,d,f,hand j. The strongest association was found with positions in the
polymorphic nucleotide rs41558317 and in the polymorphic amino acid 97 of HLA-B (a), and with the HLA-B*27 allele (b). Controlling for the effect of
HLA-B susceptibility alleles, an independent association was observed with SNPs and amino-acid position in the HLA-A locus (c) corresponding to the
HLA-A*02:01 allele (d). Further conditioning on HLA-A and HLA-B loci an independent association with SNPs and amino-acid positions in the HLA-DPB1
locus was evident (e); no HLA-DPB1 classical allele was significant at the same magnitude as the SNPs and amino-acid positions (f). Further controlling for
the effect of variation in the HLA-DPB1 locus association was observed with SNPs in the HLA-DRB1 locus (g,h). SNP association tests are shown in
blue circles, colour coded by linkage disequilibrium from the SNP with the strongest association. Amino-acid position tests are shown as red triangles.
Classical allele tests are shown as bars for two- and four-digit imputation resolution.
NATURE COMMUNICATIONS | DOI: 10.1038/ncomms8146 ARTICLE
NATURE COMMUNICATIONS | 6:7146 | DOI: 10.1038/ncomms8146 | www.nature.com/naturecommunications 3
&2015 Macmillan Publishers Limited. All rights reserved.
The association with this amino acid was statistically equivalent
with that observed with the SNP rs2975033 and with the classical
allele HLA-A*02:01. This amino acid is positioned within the
binding site of HLA-A (Fig. 3).
Independent associations were observed at the two class II loci
HLA-DPB1 and HLA-DRB1, and these were highly correlated
with polymorphic amino acids in the peptide-binding site
of these molecules (Fig. 3). At the HLA-DPB1 locus, rs1126513
showed the strongest association and the risk allele for rs1126513
was perfectly correlated with the presence of leucine at position
11 of the HLA-DPB1 molecule (position 11; OR ¼1.21;
P-value ¼2.46 10 7). At the HLA-DRB1 locus, the strongest
association with an amino acid was observed with aspartic acid at
position 70 (OR ¼1.16; P-value ¼3.44 10 5); due to linkage
disequilibrium this association was statistical equivalent to the
one observed with the SNP rs17885388.
Gene–gene interactions and susceptibility loci. We have
previously observed that the association with the variant rs30187
in the ERAP1 locus is restricted to HLA-B*27-positive subjects,
consistent with an epistatic interaction between these two loci7.
Here we investigated the possibility of interaction between the
other HLA-B susceptibility alleles and the variant rs30187. When
testing for interaction with the HLA-B*40 alleles, we found that
rs30187-T increased the risk of disease in the strata where
HLA-B*27 was present, as previously shown, or when
HLA-B*40:01 was present in the absence of HLA-B*27
(OR ¼1.41; P¼5.81 10 3); rs30187 had no effect on disease
susceptibility when both HLA-B*27 and HLA-B*40 alleles were
absent or in the non-HLA-B*27/HLA-B*40:02 stratum (Fig. 4). No
evidence of interaction was observed between rs30187 and the
other HLA-B susceptibility alleles. This suggests that the rs30187
variant interacts with the HLA-B*40:01 allele; although no
evidence to support an interaction was observed with
HLA-B*40:02, the study had low power to detect such an effect.
There was no evidence of interaction between either of the
HLA-B*40 alleles and any of the other independently associated
Table 1 | Most significant polymorphic positions (omnibus test) and imputed classical alleles associated with ankylosing
spondylitis susceptibility (P-valueo110 2000).
Position rs AA position Classical allele v2DF P-value
31,432,180 97 14,857 5 o10 3,221
31,432,180 rs1071652 14,841 3 o10 3,221
31,430,829 rs41558317 14,823 1 o10 3,221
31,432,179 rs1140412 14,823 2 o10 3,219
——HLA-B*27 14,820 1 o10 3,221
31,432,506 70 14,812 3 o10 3,215
31,432,129 114 14,402 2 o103,128
31,432,130 rs709055 14,401 2 o10 3,128
31,432,131 rs1050628 14,389 1 o10 3,127
——HLA-B*27:05 14,220 1 o10 3,090
31,430,834 rs3819282 13,798 1 o10 2,999
31,430,345 rs3819299 13,757 1 o10 2,990
31,430,346 rs3819299 13,757 1 o10 2,990
31,451,646 rs4463302 12,898 1 o102,803
31,432,485 77 12,871 2 o10 2,795
31,432,486 rs1131217 12,849 1 o10 2,793
31,377,108 rs2394967 11,613 1 o10 2,524
31,381,125 rs6905036 11,552 1 o10 2,511
31,432,208 rs41556113 10,929 1 o10 2,376
31,432,843 rs41553720 10,299 2 o10 2,237
31,432,515 67 9,741 4 o10 2,112
31,432,515 rs1071816 9,725 3 o102,110
31,518,387 rs2844510 9,525 1 o10 2,071
AA, amino acid; DF, degrees of freedom.
Table 2 | Evidence for association of HLA-B alleles with
susceptibility to ankylosing spondylitis. Effect sizes and
levels of significance were estimated in stepwise conditional
procedure, where for rounds 2 and onwards the test
conditioned on the previous alleles.
Round HLA-B allele OR (95% CI) P-value
127:05 62.41 (56.90–68.45) o10 321
227:02 43.41 (29.80–63.23) 1.07 10 122
307:02 0.82 (0.74–0.91) 5.04 10 6
457:01 0.75 (0.61–0.92) 5.13 10 4
551:01 1.33 (1.14–1.56) 2.14 10 3
647:01 2.35 (1.43–3.86) 2.25 10 3
740:02 1.59 (1.19–2.14) 4.65 10 3
813:02 1.43 (1.14–1.80) 4.2910 3
940:01 1.22 (1.06–1.40) 4.93 10 3
All other alleles 40.05
CI, confidence interval; OR, odds ratio;
HLA-B
97 11
HLA-A
0.8 Control
Case
0.6
0.4
0.2
0.0
Ser
Arg
Thr
Trp
Asn
Val
Ile
Val
Leu
Gly
Leu
95
HLA-DPβ1
Figure 2 | Amino-acid residue frequencies in 13,578 controls
and 9,069 cases within associated amino-acid positions within HLA
proteins.
ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/ncomms8146
4NATURE COMMUNICATIONS | 6:7146 | DOI: 10.1038/ncomms8146 | www.nature.com/naturecommunications
&2015 Macmillan Publishers Limited. All rights reserved.
Table 3 | Haplotype analysis of SNPs encoding the amino acid 97 of HLA-B.
HLA-B codon 97 position
12 3
SNP rs41558317 rs1140412 rs1071652 rs41556417 Amino-acid
residue
Position (HG18) 31,430,829 31,432,179 31,432,180 31,432,181
Reference allele or
amino acid in HG18
A G C T Serine (S)
Alternate allele(s) G C/A G/A/T A/C
Allele frequency in
controls (ref/alt(s))
0.95/0.05 0.29
0.67/0.05
0.82
0.10/0.04/
0.05
0.92
0.04/0.04
Single locus
univariate P-value
o10 3221 o10 3219 o10 3221 2.10 10 65 Multivariate OR
(95% CI)
Unadjusted
haplotype
frequency
P HLA-B Allele
Risk allele
univariate OR
(95% CI)
60.36
(55.47–
65.74)
59.99
(55.13–
65.33)
59.99
(55.14–
65.34)
2.03 (1.86–
2.21)
Controls Cases
Haplotype G/A A T T Asparagine
(N)
16.51 (15.43–17.69) 0.045 0.449 o10 300 *27:02
*27:04
*27:05
G/A C G T Threonine
(T)
1.12 (1.03–1.21) 0.097 0.065 4.50 10 3*13:02 *39:06
*40:06
*51:01 *51:08
*52:01 *55:01
*56:01
G/A C C T Arginine
(R)
1.00 (Reference) 0.493 0.297 1 *15:01 *15:03
*15:10
*15:16 *15:17
*15:18
*18:01 *35:01
*35:02
*35:03
*35:08 *35:12
*37:01
*38:01 *38:02
*39:01
*39:10 *40:01
*41:01
*44:02
*44:03
*44:04
*44:05
*45:01 *47:01
*49:01 *50:01
*53:01 *58:01
G/A C C A Tryptophan
(W)
1.00 (0.89–1.12) 0.042 0.025 0.95 *14:01 *14:02
G/A G C T Serine (S) 0.86 (0.81–0.91) 0.286 0.148 4.81 10 8*07:02
*07:05
*08:01 *15:07
*27:07
*40:02
*41:02 *48:01
A C A C Valine (V) 0.68 (0.59–0.78) 0.038 0.016 1.41 10 8*57:01 *57:03
CI, confidence interval; OR, odds ratio.
67
70 77
97
9
114
142
145
95
107 127
11
HLA-B HLA-A HLA-DPβ1
Figure 3 | Three-dimensional models for the HLA-B, HLA-A and HLA-DPb1 proteins. Three-dimensional models for the (a) HLA-B, (b) HLA-A and (c)
HLA-DPB1 proteins. These structures are based on Protein Data Bank entries 3LV3, 3UTQ and 3LQZ, respectively, with a direct view to the peptide-binding
groove.
NATURE COMMUNICATIONS | DOI: 10.1038/ncomms8146 ARTICLE
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susceptibility SNPs in the loci encoding the aminopeptidases
ERAP1,ERAP2 and NPEPPS (P40.1).
We then examined whether our data supported a model where
the HLA-B*27 and HLA-B*40 alleles increased disease suscept-
ibility beyond their inferred independent effects, as previously
reported30. No support for an interaction between these alleles
was observed in this data set (Supplementary Table 1).
Discussion
Independently of the expected HLA-B associations, this study
demonstrates that both HLA-B*40:01 and -B*40:02 are disease
associated alleles, and identified three further HLA-B risk alleles,
HLA-B*51:01,B*47:01 and B*13:02. The allele HLA-B*51:01 is
also the major genetic risk factor for Behc¸et’s disease31,
a seronegative disease complicated by sacroiliitis resembling
AS in up to 10% of cases32. In addition to the seven HLA-B
risk alleles, we identified two protective alleles at this locus,
HLA-B*07:02 and HLA-B*57:01. Interestingly, in the HLA-B*27-
transgenic rat model of AS, the HLA-B*27-negative control
carries the HLA-B*07 allele, and does not develop disease,
consistent with the protective effect of this allele in humans33.
It has recently been shown in HLA-B7/B27 co-expressing
mice that there is partial negative selection of HLA-B27 þ
T cells in the course of defining the immunodominant response
to influenza infection34. Further, in Erap-deficient, influenza-
infected HLA-B27-positive mice, there was a marked reduction in
presentation of the HLA-B27 immunodominant epitope, and
T-cell immunity to that epitope, presumed to be because the
HLA-B27-related immunodominant flu epitope requires cleavage
by Erap to be presented by HLA-B27. In contrast, in HLA-B7-
transgenic mice, Erap deficiency had no effect on presentation of
the HLA-B7 immunodominant epitope or the corresponding
T-cell response to it, suggesting that it does not require Erap
cleavage for presentation35. This provides a potential mechanism
to explain the genetic effects observed in humans with AS, with
ERAP1 loss of function protecting against HLA-B27-associated
AS, but having no effect in HLA-B7 carriers, where an HLA-B7
protective association is observed.
Outside the HLA-B locus, we identified three independent
significant signals associated with AS; one was in the HLA class I
locus HLA-A, and one each in the HLA class II loci HLA-DPB1
and HLA-DRB1. The association in the HLA-A locus corre-
sponded to the classical allele HLA-A*02:01, which has also been
implicated in multiple sclerosis36; however, while this allele is
protective in multiple sclerosis, it increases the risk of AS.
Previous studies have hinted at HLA-DPB1 associations with AS,
which we have confirmed here. HLA-DPB1, in conjunction with
HLA-DPA1, forms the HLA-DP heterodimer, which typically
plays a role in the presentation of exogenously derived peptides,
such as microbial peptides, to CD4 þT lymphocytes. The
strongest association was found with an amino-acid position
located in the base of the peptide-binding groove of HLA-DP,
suggesting that this polymorphism might impact on the peptide
repertoire presented by HLA-DP.
Previous findings that ERAP1 variants influence risk of disease
in HLA-B*27 positive, but not negative individuals, strongly
support the notion that both these molecules act in the same
biological pathway to affect disease susceptibility7. We have now
shown that HLA-B*40:01 interacts with ERAP1 variants in the
same manner. Similar genetic interactions involving ERAP1 have
been observed in two other immune-mediated disorders—
psoriasis with HLA-Cw6 (ref. 37) and Behc¸et’s syndrome with
HLA-B*51 (ref. 38), two disorders that are already known to share
genetic susceptibility factors with AS. It is likely that the similar
molecular mechanisms are involved in these disorders, and that
these include the pathways of MHC class I antigen presentation.
To our knowledge, there is no evidence that HLA-B40, HLA-B51
or HLA-Cw6 have non-canonical disease-related properties such
as those by which HLA-B27 is proposed to function in the
pathogenesis of AS.
Analysis of polymorphic amino-acid positions in these AS-
associated HLA molecules showed that the SNPs with the
strongest evidence of association at each of these three loci were
highly associated with amino-acid positions located in the
peptide-binding groove of these proteins. From these results, we
infer that antigen presentation to both CD4 þand CD8 þT
lymphocytes is likely to be important in the pathogenesis of AS
and/or its tissue specificity, although other mechanisms under-
lying the associations cannot formally be excluded.
MHC class I molecules contain six specificity pockets in the
peptide-binding groove, alphabetically named A to F, which serve
to anchor particular side chains of the bound peptide39. Position
97 of HLA-B is located in the C/F pocket, also referred to as the
C-terminal pocket, which anchors the side chain of the
C-terminal peptide residue29. Experimental evidence suggests
that this position is important for protein function and shaping
the peptide repertoire presented by HLA-B. Mutagenesis
experiments have shown that Asn97 is important for HLA-
B*27:04 surface expression; mutating this residue from Asn97 to
Asp97 results in reduced surface expression and increased
accumulation of unfolded protein in the ER, as well as reduced
homodimers formation40; thus, Asn97 relative to Asp97 reduces
ER stress and B27 homodimer formation, yet is associated with
AS risk. Moreover, work in the mouse homologue has shown that
changing residue 97 (W97R) results in altered peptide specificity
and affinity for b
2
-microglobulin41, and previous crystallographic
studies of viral peptides bound to HLA-B27 have shown that this
position influences the location of the peptide in the binding
groove of the molecule42. Last, this position was also found to be
associated with HIV-1 viral control, where Val97 was found to
provide the strongest protective effect to progression to AIDS,
hypothesized to be through a mechanism of peptide
presentation43. Asp97 is not shared by the AS-associated
subtype HLA-B*27:07, where it is substituted by serine. Serine
is also a polar amino acid and the substitution would be expected
to have only minor effects on the protein structure. While AS is
HLA-B*27
2.5
2.0
1.5
1.0
0.5
+
rs30187 OR (95% CI)
HLA-B*40:01
(1,395/149)
HLA-B*40:02
(249/51)
Non-HLA-B*40
(10,743/1,098)
HLA-B*40:01
(76/701)
HLA-B*40:02
(21/103)
Non-HLA-B*40
(1,093/6,951)
Figure 4 | Interaction between ERAP1 and HLA-B susceptibility alleles.
For each stratified group, effect size for the ERAP1 variant rs30187 is given.
Error bars represent 95% confidence intervals. Number of samples in each
group (controls/cases) is given below the HLA-B*40 genotype.
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&2015 Macmillan Publishers Limited. All rights reserved.
known to occur in individuals carrying HLA-B*27:07, its relative
strength of association compared with other AS-associated HLA-
B*27 subtypes is unknown.
In summary, with high-density genotyping of the MHC, we
have demonstrated independent association signals located in
HLA class I and II loci. Imputation of amino-acid residues in the
classical HLA class I and II proteins resolved the peak of
association at each of these loci to an amino-acid residue located
in the peptide-binding groove of these proteins. Refining this
analysis by imputation of classical HLA alleles showed that there
are multiple risk and protective haplotypes in the HLA-B locus.
Further, epistatic interaction was demonstrated between ERAP1
and the HLA class I alleles HLA-B*27 and HLA-B*40:01.
Methods
Sample collection.All cases met the modified New York classification criteria for
AS44. Nine thousand sixty-nine cases and 13,578 controls were recruited through a
multi-center study coordinated by the International Genetics of Ankylosing
Spondylitis Consortium8, and all samples were unrelated and met European
ancestry criteria as detailed therein. All subjects provided written informed consent
and the study was approved by the Princess Alexandra Hospital Research Ethics
Committee (reference HREC/05/QPAH/221) and University of Queensland
Research Ethics Committee (Project Clearance No: 2006000102). All samples were
genotyped with the Illumina (San Diego, CA, USA) Infinium platform
Immunochip45, and the current study was restricted to 7,264 markers in the MHC
(chromosome 6, bps 29,602,876–33,268,403, NCBI Build 36 human genome
coordinates).
Imputation.We imputed SNPs across the MHC, and classical HLA class I and II
alleles (HLA-A,HLA-C,HLA-B,HLA-DRBI,HLA-DQA1,HLA-DQB1,HLA-DPA1
and HLA-DPB1) and their corresponding amino acids determinants with
SNP2HLA28. Samples with cumulative dosage above 2.5, across all four-digit alleles
for any one of the HLA loci, were removed from the analysis. SNPs, alleles or
amino-acid residues were excluded from the analysis if the r2imputation quality
score was below 0.2.
Classical allele imputation at the HLA-B locus resulted in high-quality data,
with a median sensitivity and specificity for imputed HLA-B alleles of 0.958 and
0.998, respectively (Supplementary Fig. 1). With our imputation strategy, similar
imputation performance has previously been shown for the other HLA class I and
II loci (HLA-A,HLA-C,HLA-DRB1,HLA-DQA1,HLA-DQB1,HLA-DPA1 and
HLA-DPB1), suggesting that imputation performance for these loci was also
accurate in our study28,43,46,47.
Statistical framework for association analysis.Associations of SNPs, HLA
protein amino-acid positions and non-HLA-B alleles across the MHC locus were
assessed with logistic regression, assuming an additive risk effect on the log-odds
scale. To account for population stratification, we included as covariates 10 prin-
cipal components for each individual, computed with 16,145 unlinked autosomal,
non-MHC, SNPs with the tool shellfish (http://www.stats.ox.ac.uk/Bdavison/
software/shellfish/shellfish.php). The omnibus association test compares, via like-
lihood ratio test, the null model H
0
, where there is no risk effect at the position
tested, against the alternative model H
1
, where the risk effect at the position is
included in the model as a fixed effect:
H0:logit yi
ðÞ¼yþX
10
k¼1
pkpi;kð1Þ
H1:logit yi
ðÞ¼yþX
m1
a¼1
baga;iþX
10
k¼1
pkpi;k;ð2Þ
where y
i
denotes the binary phenotype code for individual i(0 ¼control and
1¼case). The p
k
parameter is the effect associated with each of the principal
components and p
i,k
is the value of the kth principal component for individual i.
The yparameter represents the sampling fraction (that is, the logistic regression
intercept). In the alternative model, aindicates the specific allele being tested and
g
a,i
is the dosage (imputed or genotyped) of allele ain individual i. The b
a
para-
meter represents the effect on the log odds of disease per allele. For testing a multi-
allelic locus, nucleic or amino-acid positions, with mpossible alleles we included
m-1 bparameters, one for each allele, where the most common allele was selected
as the reference allele. The likelihood ratio test that compares model H
0
with H
1
results in a test statistic that is w2distributed with m-1 degrees of freedom.
When testing for association with imputed classical HLA alleles, we defined a
series of binary markers coding the presence or absence of the allele being tested,
and each different allele was tested as a biallelic position as described above.
To identify independent effects. we performed conditional logistic regression by
including the most strongly associated position/polymorphism as a fixed effect in
both the null model H
0
and the alternative model H
1
. We then analysed all
positions as described above. Conditional analysis was repeated in an iterative
fashion by sequentially adding the most significant positions as fixed effects until
no significant position or polymorphism was observed. Allelic associations were
deemed significant with Po10 5, this statistical significance threshold accounted
for 5,000 independent tests using Bonferroni correction. Two tests were considered
independent if the two SNPs had a pairwise correlation (r2)o0.90, which resulted
in 3,252 SNPs independent tests. For the special case of HLA-B alleles where we
had a higher prior probability of association, we defined significance as Po10 3as
only 38 alleles were tested.
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Acknowledgements
We thank all participating subjects with AS and healthy individuals who provided the
DNA and clinical information necessary for this study. This work was in part funded by
grants from Arthritis Research UK (19536 and 18797), the NIHR Oxford comprehensive
Biomedical Research Centre (immunity and inflammation theme A93081) and NIHR
Thames Valley collaborative research network and National Ankylosing Spondylitis
Society (UK). SPARCC was established through the support of the Arthritis Society of
Canada. Support was received from National Institutes of Health/National Institute of
Allergy and Infectious Diseases grant 1U01AI09090-01. This work was supported in part
by grant PI12/02587 (Inst. Carlos III, Spain) and by European Union ‘Fondos FEDER’.
Support was received from Agence Nationale de la Recherche (grant ANR 2010 GEMISA
and Investissements d’Avenir programme ANR-11-IDEX-0005-02), the Socie
´te
´
Franc¸aise de Rhumatologie (SFR) and the Arthritis Foundation. M.W. is funded by the
Intramural Research Program, National Institute of Arthritis and Musculoskeletal and
Skin Diseases, National Institutes of Health. M.A.B. is funded by a National Health and
Medical Research Council (Australia) Senior Principal Research Fellowship. D.M.E. is
funded by an Australian Research Council Future Fellowship (FT130101709). P.I.W.d.B.
is funded in part by the Netherlands Organization for Scientific Research (VIDI
Vernieuwingsimpuls project 016.126.354) and by the National Institutes of Health
(1R01AR062886-1).
Author contributions
All authors contributed to the manuscript preparation and approved the final manu-
script. Case and control recruitment was performed by P.L.C., M.H.H., M.W., L.S.G.,
J.H., O.F., J.T., K.L., L.A.B., D.E., R.B-V., S.S., C.F., N.H., J.M., F.J.B., M.A.G-G., C.L-L,
P.B., K.G., H.G., D.D.G., P.R., W.P.M., I.V.H-B., R.V-O., C.R-S., I.M.H., F.M.P-S., R.D.I.,
M.B., B.P.W., J.D.R. and M.A.B. Study design was contributed by A.C., P.J.L., R.D.I.,
M.B., B.P.W., J.D.R., D.M.E., P.I.W.d.B. and M.A.B. DNA preparation and genotyping
were performed by J.J.P., X.Z., H-J.G., G.C., B.A.L., L.A., J.L., J.B.A.C., F.M.P-S. and
M.A.B.. Analysis and interpretation were performed by A.C., S.L.P., P.J.L., P.C.R.,
D.M.E., P.I.W.d.B. and M.A.B. The manuscript preparation was performed by A.C.,
P.J.L., D.M.E., P.I.W.d.B. and M.A.B.
Additional information
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How to cite this article: Cortes, A. et al. Major histocompatibility complex associations
of ankylosing spondylitis are complex and involve further epistasis with ERAP1.
Nat. Commun. 6:7146 doi: 10.1038/ncomms8146 (2015).
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8NATURE COMMUNICATIONS | 6:7146 | DOI: 10.1038/ncomms8146 | www.nature.com/naturecommunications
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... Multiple genes may be involved in the development of AS, based on the heterogeneity of the disease's progression. Several genes and genomic areas have been linked to AS susceptibility and severity in genome-wide association studies (GWAS), demonstrating that both MHC and non-MHC genes have a role in the illness process [4][5][6][7][8]. Despite breakthroughs in recent years, the genetic and pathophysiology processes of AS remain poorly known. ...
... As a result, effective ERAP1 function is required for optimal antigen presentation and health maintenance. ERAP1 is a non-MHC gene on chromosome 5q15, and genetic studies have shown that epistasis between ERAP1 SNVs and HLA-B27 is highly linked to AS vulnerability in different ethnic groups [6,14]. The biological functions of ERAP1 allelic variants on the other hand, are largely unexplored. ...
... With longer epitopes, the promiscuous sub-peptidome binding property of HLA-B51 indicates a genetic effect on dysregulated CD8+ T response and aberrant NK cell activation, leading to the development of BD [43]. Other HLA-B alleles have been involved in AS development in European populations [6], therefore ERAP1 epistasis may not be limited to HLA-B27. HLA-B40 increased susceptibility to AS in HLA-B27 − AS patients in Taiwanese [44], but not in Caucasian [45]. ...
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Epistasis of ERAP1 single nucleotide variations (SNVs) and HLA-B27 has been linked to ankylosing spondylitis susceptibility (AS). The current study examined how prevalent ERAP1 allelic variants (SNV haplotypes) in Taiwan affect ERAP1 functions and AS susceptibility in the presence or absence of HLA-B27. Sanger sequencing was used to discover all ERAP1 coding SNVs and common allelic variants in Taiwanese full-length cDNAs from 45 human patients. For the genetic association investigation, TaqMan genotyping assays were utilized to establish the genotypes of ERAP1 SNVs in 863 AS patients and 1438 healthy controls. Ex vivo biological analysis of peripheral blood mononuclear cells from homozygous donors of two common-risk ERAP1 allelic variants was performed. Two common-risk ERAP1 allelic variants were also cloned and functionally studied. In Taiwanese, eleven frequent ERAP1 SNVs and six major ERAP1 allelic variants were discovered. We discovered that in Taiwanese, the most prevalent ERAP1-001 variant with 56E, 127R, 276I, 349M, 528K, 575D, 725R, and 730Q interacting with HLA-B27 significantly contributed to the development of AS. In HLA-B27 negative group, however, the second most prevalent ERAP1-002 variant with 56E, 127P, 276M, 349M, 528R, 575D, 725R, and 730E was substantially related with an increased risk of AS. Ex vivo and in vitro research demonstrated that ERAP1 allelic variants have a significant impact on ERAP1 functions, suggesting that ERAP1 plays a role in the development of AS. In an HLA-B27-dependent manner, common ERAP1 allelic variants are related with AS susceptibility.
... Genetic identification of HLA-B*27 has good specificity and sensitivity, and it is also relatively inexpensive compared to MRI for the diagnosis of SpA, but the positive rate of HLA-B*27 in healthy individuals is relatively high, up to 10%. 1, 3 In addition to HLA-B*27, there is an association of other genes in HLA class I with SpA, including various subtypes of HLA-A and HLA-C, but despite this the level of this correlation has not been clearly reported. [4][5][6] Determining the HLA alleles involved in the disease activity of SpA is important because different alleles affect the 3D structure, biochemical activity, and peptide-binding groove of HLA proteins. [7][8][9] Based on the clinical experience of 15 years of observations, there are an increasing number of SpA patients and severe clinical manifestations in the outpatient clinic at Dr. Soetomo Hospital, Indonesia. ...
... 24 Despite HLA-B*2704 and -B*2705 being the most commonly reported HLA alleles associated with SpA, the patients of Dr. Soetomo General Hospital with HLA-B*2704 and -B*2705 tended to show less severe disease when compared to patients with HLA-C and HLA-K. Cortes et al. 5 found no correlation between radiographic severity and HLA-B*27, this is supported by the study from Arévalo et al. 25 that revealed the HLA-B*27 negative patients had higher BASFI scores (higher severity). The study by Ruiz et al. 26 also revealed that there was no association between the Schober score, which indicates low lumbar spine mobility, and the presence of HLA-B*27. ...
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Background: Spondyloarthritis (SpA) is a chronic inflammatory disease characterized by enthesitis, sacroiliitis, and axial joint involvement. Although the association of HLA with SpA has been widely reported, there have been no studies of HLA type in the Indonesian population within the last 20 years. This study aims to identify the HLA type in SpA patients at Dr. Soetomo General Hospital, Indonesia. Methods: This study used a cross-sectional analytical design with samples that met the criteria for SpA according to the 2009 ASAS. The clinical scores used in this study were mSASSS, BASFI, ASDAS, and Schober. Genetic identification using PCR was performed followed by sanger sequencing to determine the HLA type in the patient. DNA sequences were aligned with BLAST, and a phylogenetic tree was created using MEGA 11. Descriptive and comparative analyzes were performed using GraphPad Prism 9.
... In a special case, a woman with endometriosis was diagnosed with 13 co-morbidities, including SLE and AS (7). She was found homozygous for rs2476601 SNP of the PTPN22 gene, and heterozygous for both rs27434 and rs30187 SNPs of the ERAP1 gene, which have been proven to be related to AS (8)(9)(10). Secondly, both endometriosis and AS are involved in inflammatory responses induced by inflammatory mediators (11)(12)(13). ...
... Secondly, both endometriosis and AS are involved in inflammatory responses induced by inflammatory mediators (11)(12)(13). For endometriosis, the vigorous inflammatory response will cause endometrial cells to release more chemokines, namely, IL-1b, IL-6, IL-8, TNF-a, and IL-17 (10,11). Also, increased levels of IL-6, TNF-a, IL-1b, and IL-17 could be detected in AS patients (12,14,15). ...
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Objectives Previous research has shown a possible relationship between endometriosis and autoimmune diseases. However, the relationship between endometriosis and ankylosing spondylitis (AS) is lacking. Therefore, we intended to find possible associations between endometriosis and AS using ICD-9 coding data in a population-based retrospective cohort study in Taiwan.Method Data for this retrospective cohort study were collected from the Taiwan National Health Insurance Research Database (NHIRD) between 2000–2012. We collected 13,145 patients with endometriosis and a 78,870 non-endometriosis comparison cohort. Diagnoses of endometriosis and AS were defined by the International Classification of Diseases-9 (ICD-9-CM) code for at least 3 outpatients or 1 hospitalization. Propensity score matching by comorbidities, corticosteroids, and non-steroidal anti-inflammatory drugs (NSAIDs) usage were done for baseline comparability. Cox proportional hazard models were used to evaluate crude and adjusted hazard ratios.ResultsThe cumulative incidence of AS was higher in patients with endometriosis compared to the non-endometriosis comparison cohort (log-rank test, p = 0.015). The adjusted hazard ratio (aHR) of incidental AS in patients with endometriosis was 1.61 (95% CI = 1.11 to 2.35) in comparison to the non-endometriosis comparison cohort. An increased risk of AS was also observed in subjects with major depressive disorder (aHR = 5.05, 95% CI = 1.85 to 13.78). Stratified analyses of age subgroups showed consistent results. NSAID users had a lower risk of AS than NSAID non-users (aHR 4.57 vs 1.35, p for interaction = 0.031).Conclusions In this retrospective population-based cohort study, we found a higher risk of AS in patients with endometriosis. We suggest that clinicians should pay attention to the occurrence of AS in patients with endometriosis.
... Genome Wide Association Studies (GWAS), authors have identified in the coding and non-coding regions, Single Nucleotide Polymorphisms (SNPs) associated with Ankylosing Spondylitis (AS), Behcȩt's disease (BD), Psoriasis (Ps), Inflammatory Bowel Disease (IBD), Juvenile Idiopathic Arthritis (JIA), Birdshot chorioretinopathy (BSCR), Type I Diabetes (T1D) and Multiple Sclerosis (MS) (8,9). In particular, SNPs rs30187 (K528R) and rs27044 (Q730E) have been found to be associated with AS (10,11). The K528R amino acid substitution appears to determine, both in vitro and in vivo, a defect in the catalytic cycle with an alteration of the peptide cleavage activity, while the Q730E substitution seems to have an effect both in the specificity of the trimming as well as in the length preference of the peptide (12)(13)(14). ...
Article
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The Endoplasmic Reticulum Aminopeptidase 1 and 2 (ERAP1 and ERAP2) and Insulin Regulated Aminopeptidase (IRAP) are three M1 zinc metalloproteases whose role in antigen processing is the refining of peptidome either in the Endoplasmic reticulum (ERAP1 and ERAP2), or in the endosomes (IRAP). However, other novel and distinct functions are emerging. Here, we focus specifically on ERAP2. This gene has a peculiar evolutionary history, being absent in rodents and undergoing in humans to a balanced selection of two haplotypes, one of which not expressing the full length ERAP2. These observations suggest that its role in antigen presentation is not essential. An additional, less investigated role is in the regulation of the Renin Angiotensin System (RAS). ERAP1 and ERAP2 cleave Angiotensin II (Ang II) into Ang III and IV, which counteract the action of Ang II whereas IRAP is itself the receptor for Ang IV. We have recently reported that macrophages, independently from the haplotype, express and release a N-terminus ERAP2 “short” form which directly binds IRAP and the two molecules are co-expressed in the endosomes and on the cell membrane. This new evidence suggests that the maintenance of the ERAP2 gene in humans could be due to its activity in the regulation of the RAS system, possibly as an Ang IV agonist. Its role in the immune-mediated diseases as well as in disorders more specifically related to an imbalance of the RAS system, including hypertension, pre-eclampsia but also viral infections such as COVID-19, is discussed here.
... Endoplasmic reticulum aminopeptidase 1 (ERAP1), in conjunction with the HLA-B allele, has also been reported to associate with a higher risk of developing AS. The gene's major mutation (rs30187, K528R) interacts with the HLA-B27 allele only, while ERAP1 interacts with the HLA-B40 allele in patients who are HLA-B27 negative [20]. In males, a low copy number of the TLR7 gene was found to be a predictor of vulnerability to AS, whereas in females, it was found to be a protective factor [21]. ...
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The relation between vitamin D receptor (VDR) gene polymorphisms and ankylosing spondylitis (AS) remains unclear. A systematic review and meta-analysis were conducted using six databases, including PubMed, Web of Science, EMBASE, CNKI, Wanfang and Cochrane Library. The selection of each study was based on inclusion and exclusion criteria. The Newcastle–Ottawa Scale was applied to assess the quality of the included studies, while the strength was evaluated by odds ratios and 95% confidence intervals. The following contrasts were used: allele contrast (H vs h), homozygous contrast (HH vs hh), heterozygous contrast (Hh vs hh), dominant contrast (HH + Hh vs hh) and recessive contrast (HH vs Hh + hh). For the BsmI-rs1544410 polymorphism, three studies were included of 782 cases and 863 controls. The data showed a significant relationship under allele contrast H vs h (OR = 1.66, 95% CI 1.20–2.30 (P = 0.002)). For the TaqI-rs731236 polymorphism, 675 cases and 697 controls were included in two studies. The data showed a significant relationship under allele contrast H vs h (OR = 1.57, 95% CI 1.11–2.21 (P < 0.05)), homozygous contrast Hh vs hh (OR = 1.65, 95% CI 1.12–2.43 (P < 0.05)), and recessive contrast HH + Hh vs hh (OR = 1.66, 95% CI 1.13–2.43 (P < 0.05)). There were significant relationships between VDR gene BsmI-rs1544410 and TaqI-rs731236 polymorphisms and AS, while no associations were found between FokI-rs2228570 and ApaI-rs7975232 polymorphisms and AS. In the future, additional studies with larger case numbers are need.
... It is increasingly clear that complex traits are exceedingly polygenic, with influences from many complex regulatory and molecular pathways, and even chromosomal three-dimensional structure [11][12][13] . While there has been debate over whether non-additive genetic variance is a major contributor to heritability 6,14-18 , such complexity makes gene interactions likely to exist and these interactions have been demonstrated using several systems and model organisms [7][8][9]19,20 . Identifying genegene interactions and the pathways and networks in which they occur will provide a critical context for understanding the biology of complex traits 7,10 . ...
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It remains unknown to what extent gene-gene interactions contribute to complex traits. Here, we introduce a new approach using predicted gene expression to perform exhaustive transcriptome-wide interaction studies (TWISs) for multiple traits across all pairs of genes expressed in several tissue types. Using imputed transcriptomes, we simultaneously reduce the computational challenge and improve interpretability and statistical power. We discover and replicate several interaction associations, and find several hub genes with numerous interactions. We also demonstrate that TWIS can identify novel associated genes because genes with many or strong interactions have smaller single-locus model effect sizes. Finally, we develop a method to test gene set enrichment of TWIS associations (E-TWIS), finding numerous pathways and networks enriched in interaction associations. Epistasis is likely widespread, and our procedure represents a tractable framework for beginning to explore gene interactions and identify novel genomic targets.
... Ankylosing spondylitis (AS) occurs worldwide; its prevalence in northern Europe approaches 0.5%, [1][2][3][4][5][6][7][8] and 85%-95% of these patients possess HLA-B27 versus approximately 8% of the general population. [9][10][11] Twin studies have shown concordance rates of 25%-75% in monozygotic versus 4%-15% in dizygotic twins. 12 13 The reported recurrence rate (RR) for the first-degree relatives (FDR) of patients with AS has ranged between 4% and 11%. ...
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Objective The lifetime recurrence rate (RR) of axial spondyloarthritis (axSpA) among first-degree relatives (FDR) and the effect of proband’s gender, HLA-B27 and radiographic status is unclear. Our 35-year-follow-up family study has enabled these issues to be addressed. Methods In 1985, 363 ankylosing spondylitis (AS) probands (members of the Swiss AS Patient Society) and 806 FDR recruited into the study, completed questionnaires regarding axSpA manifestations, underwent a physical examination and most also underwent pelvic radiography and HLA-B27 typing. At follow-up in 2018–2019, of the former participants whose current addresses could be retrieved, 162 had died and 485 (125 patients with AS plus 360 FDR) completed a postal questionnaire. Results At follow-up, 48 of 177 HLA-B27(+) FDR had developed axSpA, an RR of 27.1% (95% CI 20.6% to 33.7%). 27/148 (18.2%) children of AS probands (modified New York (mNY) criteria) were affected versus 2/50 (4.0%) children of non-radiographic axSpA probands (p=0.0138, OR=5.36; 95% CI 1.23 to 23.40). Children of female probands were more often affected (12/22; 54.5%) than of male probands (15/78; 19.2%) (p=0.0003; OR=4.89; 95% CI 1.96 to 12.23). This increased risk applies equally to sons and daughters. Conclusion The lifetime RR of axSpA for HLA-B27(+) FDR is substantial (27.1%), and disease severity (as defined by radiographic sacroiliitis by the mNY criteria) is an additional risk factor. Affected mothers pass on the disease significantly more often to their offspring than do affected fathers. These findings may lead to better assessment of lifetime risk for axSpA in the offspring. Moreover, investigation of this gender effect may uncover additional putative disease susceptibility factors.
Linear or nonlinear interactions of multiple single-nucleotide polymorphisms (SNPs) play an important role in understanding the genetic basis of complex human diseases. However, combinatorial analytics in high-dimensional space makes it extremely challenging to detect multiorder SNP interactions. Most classic approaches can only perform one task (for detecting k-order SNP interactions) in each run. Since prior knowledge of a complex disease is usually not available, it is difficult to determine the value of k for detecting k-order SNP interactions. A novel multitasking ant colony optimization algorithm (named MTACO-DMSI) is proposed to detect multiorder SNP interactions, and it is divided into two stages: searching and testing. In the searching stage, multiple multiorder SNP interaction detection tasks (from 2nd-order to kth-order) are executed in parallel, and two subpopulations that separately adopt the Bayesian network-based K2-score and Jensen–Shannon divergence (JS-score) as evaluation criteria are generated for each task to improve the global search capability and the discrimination ability for various disease models. In the testing stage, the G test statistical test is adopted to further verify the authenticity of candidate solutions to reduce the error rate. Three multiorder simulated disease models with different interaction effects and three real age-related macular degeneration (AMD), rheumatoid arthritis (RA) and type 1 diabetes (T1D) datasets were used to investigate the performance of the proposed MTACO-DMSI. The experimental results show that the MTACO-DMSI has a faster search speed and higher discriminatory power for diverse simulation disease models than traditional single-task algorithms. The results on real AMD data and RA and T1D datasets indicate that MTACO-DMSI has the ability to detect multiorder SNP interactions at a genome-wide scale. Availability and implementation: https://github.com/shouhengtuo/MTACO-DMSI/
Article
Introduction: Interleukin 23 (IL-23) is a pro-inflammatory cytokine that plays a protective role against bacterial and fungal infections. However, the dysregulation of the IL-23/IL-17 axis provides a solid substrate for the development of various inflammatory diseases, such as psoriatic arthritis (PsA) and ankylosing spondylitis (AS). Areas covered: In different clinical trials, several drugs against IL-23 have shown efficacy and safety towards PsA, with excellent results on skin and joint scores. However, the same drugs did not show the same efficacy in AS, suggesting that IL-23 may not be a relevant driver of the pathobiology and clinical symptoms of active axial spondyloarthritis (axSpA). Expert opinion: These drugs have shown an excellent efficacy and a good safety profile towards PsA, while in AS the efficacy of the IL-23 blockade is lacking for reasons not yet known. Several hypotheses have been reported, but further studies will be needed for a greater understanding. This suggests the involvement of pathways or mechanisms for the development of SpA that remain unknown. In order to allow a wide use of IL-23 inhibitors, further clinical trials and long-term prospective studies are necessary.
Article
Inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), is clinically closely associated with arthritis. Three major arthritis clinical subtypes have been described, peripheral arthritis type 1 (PeA1), peripheral arthritis type 2 (PeA2), and axial spondyloarthritis (axSpA). While genetic overlaps between IBD and arthritis have been defined, detailed pathophysiology for these three major subtypes of arthritis in patients with IBD has only recently begun to be established. The genetic and molecular mechanisms distinguishing axial and peripheral arthropathies in patients with UC and CD need to be better described. Understanding the pathophysiology for PeA1, PeA2, and axSpA in the settings of both UC and CD is necessary to provide the fundamental biology underlying the clinical phenotypes in IBD arthritis. This has been attempted for CD-associated spondyloarthritis, differentiating this from both CD and axSpA, while observing unique peripheral blood mononuclear cells linking gut inflammation to joint disease. We should know more about the processes by which immune cells are perturbed in these disorders, how they translocate to joints, how they are activated, what other molecules and mediators are involved, and how gut microbes and microbial products damage joints. Information from such studies are needed to elucidate whether distinctions between IBD-related peripheral and axSpA are clinically meaningful. IBD-related peripheral and axSpA studies are needed to elucidate whether distinctions between peripheral and axSpA are clinically meaningful, to better understand immunopathogenesis, and to develop novel targeted therapies.
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The mechanism by which human leukocyte antigen B27 (HLA-B27) contributes to ankylosing spondylitis (AS) remains unclear. Genetic studies demonstrate that association with and interaction between polymorphisms of endoplasmic reticulum aminopeptidase 1 (ERAP1) and HLA-B27 influence the risk of AS. It has been hypothesised that ERAP1-mediated HLA-B27 misfolding increases endoplasmic reticulum (ER) stress, driving an interleukin (IL) 23-dependent, pro-inflammatory immune response. We tested the hypothesis that AS-risk ERAP1 variants increase ER-stress and concomitant pro-inflammatory cytokine production in HLA-B27(+) but not HLA-B27(-) AS patients or controls. Forty-nine AS cases and 22 healthy controls were grouped according to HLA-B27 status and AS-associated ERAP1 rs30187 genotypes: HLA-B27(+)ERAP1(risk), HLA-B27(+)ERAP1(protective), HLA-B27(-)ERAP1(risk) and HLA-B27(-)ERAP1(protective). Expression levels of ER-stress markers GRP78 (8 kDa glucose-regulated protein), CHOP (C/EBP-homologous protein) and inflammatory cytokines were determined in peripheral blood mononuclear cell and ileal biopsies. We found no differences in ER-stress gene expression between HLA-B27(+) and HLA-B27(-) cases or healthy controls, or between cases or controls stratified by carriage of ERAP1 risk or protective alleles in the presence or absence of HLA-B27. No differences were observed between expression of IL17A or TNF (tumour necrosis factor) in HLA-B27(+)ERAP1(risk), HLA-B27(+)ERAP1(protective) and HLA-B27(-)ERAP1(protective) cases. These data demonstrate that aberrant ERAP1 activity and HLA-B27 carriage does not alter ER-stress levels in AS, suggesting that ERAP1 and HLA-B27 may influence disease susceptibility through other mechanisms.Genes and Immunity advance online publication, 6 November 2014; doi:10.1038/gene.2014.62.
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Endoplasmic reticulum-associated aminopeptidase-1 (ERAP1) plays a critical role in the processing of peptides prior to binding to MHC class I molecules. In this article, we show for the first time, to our knowledge, that the HLA-B27 immunodominant influenza nucleoprotein (NP) 383-391 epitope is made as an N-terminally extended 14-mer before it is trimmed by ERAP. In the absence of ERAP, there is a significant reduction in the CTL response to the B27/NP383-391 epitope in influenza A (flu)-infected B27/ERAP(-/-) mice. With the use of tetramer staining, the number of naive CD8(+) T cells expressing TCR Vβ8.1 in B27/ERAP(-/-) transgenic mice is significantly lower than that seen in B27/ERAP(+/+) mice. HLA-B27 surface expression in naive and flu-infected B27/ERAP(-/-) mice is also lower than the expression seen for the same allele in naive and flu-infected B27/ERAP(+/+) mice. In contrast, surface expression of HLA-B7 was unaffected by the absence of ERAP in B7/ERAP(-/-) transgenic mice. The B7-restricted NP418-426 CTL response in flu-infected B7/ERAP(-/-) and B7/ERAP(+/+) mice was also similar. These results provide, to our knowledge, the first in vivo demonstration of ERAP functionally influencing host immune response in an HLA allele-specific manner. This principle has relevance to diseases such as ankylosing spondylitis, in which HLA-B27 and ERAP jointly contribute to disease predisposition.
Article
To identify new susceptibility loci for psoriasis, we undertook a genome-wide association study of 594,224 SNPs in 2,622 individuals with psoriasis and 5,667 controls. We identified associations at eight previously unreported genomic loci. Seven loci harbored genes with recognized immune functions (IL28RA, REL, IFIH1, ERAP1, TRAF3IP2, NFKBIA and TYK2). These associations were replicated in 9,079 European samples (six loci with a combined P < 5 x 10(-8) and two loci with a combined P < 5 x 10(-7)). We also report compelling evidence for an interaction between the HLA-C and ERAP1 loci (combined P = 6.95 x 10(-6)). ERAP1 plays an important role in MHC class I peptide processing. ERAP1 variants only influenced psoriasis susceptibility in individuals carrying the HLA-C risk allele. Our findings implicate pathways that integrate epidermal barrier dysfunction with innate and adaptive immune dysregulation in psoriasis pathogenesis.
Article
Ankylosing spondylitis is a model immunogenetic disease with major common and rare genetic risk factors, likely environmental contributors to its pathogenesis and, to date, no treatment that has been shown to induce disease remission in long-term studies. The discovery of the association of HLA-B27 with the disease in the early 1970s triggered extensive efforts to elucidate the mechanism of this association. However, the precise role of HLA-B27 in ankylosing spondylitis pathogenesis remains unclear. In recent years, rapid progress made in the discovery of non-MHC genes involved in susceptibility to ankylosing spondylitis has combined with increasing ability to investigate the immune system to make rapid progress in unraveling the etiopathogenesis of the condition.
Article
It is recognized that host response following viral infection is characterized by immunodominance, but deciphering the different factors contributing to immunodominance has proved a challenge due to concurrent expression of multiple MHC class I alleles. To address this, we generated H2-K(-/-) /D(-/-) (DKO) transgenic mice expressing either one or two human MHC-I alleles. We hypothesized that co-expression of different allele combinations figures critically in immunodominance and examined this in influenza-infected, double Tg MHC-I mice. In A2/B7 or A2/B27 mice, using ELISpot assays with the A2-restricted M1.58-66, the B7-restricted NP418-426 or the B27-restricted NP383-391 flu epitopes we observed the expected recognition of both peptides for both alleles. In contrast, in flu-infected B7/B27 mice a significantly reduced level of B27/NP383-restricted CTL response was detected while there was no change in the B7/NP418-restricted CTL response. Flu-specific tetramer studies revealed a partial deletion of Vβ8.1(+) NP383/B27-restricted CD8(+) T cells, and a diminished Vβ12(+) CD8(+) T-cell expansion in B7/B27 Tg mice. Using HLA Tg chimeric mice we confirmed these findings. These findings shed light on the immune consequences of co-dominant expression of MHC-I alleles for host immune response to pathogens. This article is protected by copyright. All rights reserved.
Article
The spondyloarthropathies represent highly enigmatic conditions and although their clinical features, anatomical distribution of disease and genetic predisposing factors have been known for some time, a unified concept of the basic pathobiology underlying these illnesses has remained undefined. Recently progress has been made because numerous independent studies have converged upon IL-23 as a central cytokine in spondyloarthropathy and the mechanism and sites of action of this cytokine have now become much clearer. These findings enable the rational design of therapeutic strategies which it is hoped will profoundly modify the progression of these diseases. We will review the anatomical sites affected and the evidence for the importance of IL-23 in these conditions, before drawing these lines of investigation together to propose a model for the unified understanding of spondyloarthropathy.