Autoimmune Diseases

Volume 2013 (2013), Article ID 761046, 11 pages

http://dx.doi.org/10.1155/2013/761046

Research Article

Genome-Wide Association Study of Antiphospholipid Antibodies

M. Ilyas Kamboh,¹ Xingbin Wang,¹ Amy H. Kao,² Michael M. Barmada,¹ Ann Clarke,³ Rosalind Ramsey-Goldman,⁴ Susan Manzi,² and F. Yesim Demirci¹

¹Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA

²Division of Rheumatology, Department of Medicine, West Penn Allegheny Health System, Pittsburgh, PA 15212, USA

³Divisions of Clinical Immunology/Allergy, and Clinical Epidemiology, Department of Medicine, McGill University, Montreal, QC, Canada, H3A 1A1

⁴Division of Rheumatology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA

Received 5 November 2012; Revised 10 January 2013; Accepted 10 January 2013

Academic Editor: Ricard Cervera

Copyright © 2013 M. Ilyas Kamboh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Background. The persistent presence of antiphospholipid antibodies (APA) may lead to the development of primary or secondary antiphospholipid syndrome. Although the genetic basis of APA has been suggested, the identity of the underlying genes is largely unknown. In this study, we have performed a genome-wide association study (GWAS) in an effort to identify susceptibility loci/genes for three main APA: anticardiolipin antibodies (ACL), lupus anticoagulant (LAC), and anti-β ₂ glycoprotein I antibodies (anti-β ₂GPI). Methods. DNA samples were genotyped using the Affymetrix 6.0 array containing 906,600 single-nucleotide polymorphisms (SNPs). Association of SNPs with the antibody status (positive/negative) was tested using logistic regression under the additive model. Results. We have identified a number of suggestive novel loci with . Although they do not meet the conservative threshold of genome-wide significance, many of the suggestive loci are potential candidates for the production of APA. We have replicated the previously reported associations of HLA genes and APOH with APA but these were not the top loci. Conclusions. We have identified a number of suggestive novel loci for APA that will stimulate follow-up studies in independent and larger samples to replicate our findings.

1. Introduction

Antiphospholipid antibodies (APA) are a heterogeneous group of antibodies that are detected in a variety of conditions, including primary antiphospholipid syndrome (APS) and systemic lupus erythematosus (SLE) [1]. The term antiphospholipid antibodies is a misnomer as APA present in autoimmune disease, like SLE, do not bind to phospholipids but recognize phospholipid-binding proteins [2]. Patients with persistent APA who develop pregnancy complications or thrombosis are considered to have primary APS and those who develop these complications in the presence of autoimmune disease are classified having secondary APS. Since the definition of APS is not limited to a single APA assay, it is required to measure more than one APA. Indeed, currently recognized laboratory criteria for APS include having one or more of three APA, including anticardiolipin antibodies (ACL), lupus anticoagulant (LAC), or anti-β ₂ glycoprotein I antibodies (anti-β ₂GPI) in conjunction with the presence of thrombosis or pregnancy loss [3].

Although the genetic basis of APA [4] and APS [5] has been suggested, the underlying genetic factors have not been clearly established. Understanding the genetic bases of various APA may help to delineate the mechanisms for APS. The objective of this study was to perform a genome-wide association study (GWAS) in an effort to identify loci/genes for the three main APA, namely, ACL, LAC, and anti-β ₂GPI.

2. Subjects and Methods

2.1. Subjects

A subset of individuals from our larger GWAS of SLE (unpublished data) that had the ACL (), LAC (), and anti-β ₂GPI () measurements available were used in this study. All individuals were women of European ancestry. The study participants included both SLE cases and controls and their characteristics are given in Table 1. Our controls were apparently healthy individuals that were recruited from blood bank. We measured APA in our controls but they were not characterized for primary APS due to our study design that is focused on identifying genes for SLE and APA. Furthermore, there were only 28 individuals with APS, and this small number was not considered to be appropriate for a GWAS analysis. All subjects provided written informed consent and the study was approved by the Institutional Review Board.

Table 1: Characteristics of study participants with three antiphospholipid antibodies in the GWAS dataset*.

ACL
LAC
Anti-GPI

Positive
Negative
Positive
Negative
Positive
Negative

()
()
()
()
()
()

Mean age ± SD

SLE cases (%)
58.5
58.1
70.8
56.3
71.3
51.9

Controls (%)
41.5
41.9
29.2
43.7
28.7
48.1

ACL: anticardiolipin antibodies; LAC: lupus anticoagulant; Anti-GPI: anti- glycoprotein I antibodies.

2.2. Antiphospholipid Antibodies

The presence of ACL (IgG > 15 GPL units, IgM > 10 MPL units, IncStar, Stillwater, MN, USA), LAC (partial thromboplastin time or Russell’s viper venon time with mix) and anti-β ₂GPI (QUANTA Lite β ₂GPI screen, INOVA Diagnostics, Inc. San Diego, CA, USA) was tested in sera or plasma obtained from the study subjects. The three APA (ACL, LAC, and anti-β ₂GPI) were classified into antibody-positive and antibody-negative groups based on manufacturer’s protocols.

2.3. Genotyping and Quality Control (QC)

DNA samples were genotyped using the Affymetrix Genome-Wide Human SNP Array 6.0 containing 906,600 SNPs at Expression Analysis, Durham, NC, USA. All samples used in this study passed strict quality control measurements in our larger GWAS. Exclusion criteria included samples with poor performance (<95% average call rate across the array), poorly performing markers (44,592 with <95% call rate across all samples genotyped), and markers with significant deviation from Hardy-Weinberg equilibrium () and with low minor allele frequency (MAF <0.01). Population stratification analysis was conducted using a multidimensional scaling method implemented in PLINK. SNPs falling within the genomic regions with abnormal linkage disequilibrium patterns and structural variations (hg18; chr2: 130–140 Mb, chr6: 24–36 Mb, chr8: 8–12 Mb, chr11: 42–58 Mb, and chr17: 40–43 Mb) were excluded from the principal component (PC) analysis but were included in subsequent association analysis. First 4 components were determined to be relevant for the determination of population origin based on visual examination of PC plots and were used as covariates in the association statistics.

2.4. Association Analysis

The three APA (ACL, LAC, and anti-β ₂GPI) were classified into antibody-positive and antibody-negative groups based on manufacturer’s protocols. Association of SNPs with the antibody status was tested using logistic regression under the additive model. Considering the effect of SNPs on the antibody status may be confounded by the disease status (SLE) and other demographic variables (age, BMI, smoking), we used the stepwise regression method to select the most parsimonious set of covariates for each dependent variable. The analysis for each antibody was adjusted for the disease status (SLE) and the first four principal components. In addition, the ACL and LAC analyses were adjusted for smoking and BMI, respectively. and/or PLINK statistical software programs were used for all analyses performed for this study.

3. Results

3.1. Quantile-Quantile Plots of the GWAS Data

The genome-wide association analysis was performed on 670 individuals with ACL, 708 individuals with LAC and 496 individuals with anti-β ₂GPI (Table 1) who were genotyped using the Affymetrix Genome-Wide Human SNP Array 6.0. Figure 1 shows the quantile-quantile plots for comparisons of observed and expected values distribution for ACL, LAC, and anti-β ₂GPI. For all three APA, the distribution of observed values conformed to the null distribution until the tail of the distribution where it deviated, indicating no evidence of significant population stratification but evidence of genetic association.

Figure 1: Quantile-quantile plots of the observed versus the expected values for ACL, LAC, and Anti-β ₂GPI.

3.2. Association with Anticardiolipin Antibodies (ACL)

Figure 2 shows the genome-wide values for ACL in a Manhattan plot and the top loci with are presented in Table 2. Three top SNPs with were observed. The most significant SNP, rs6889746 ), was located upstream of PELO (Pelota homolog) on chromosome 5q11.2. The next top SNP, rs6681460 (), was present in SGIP1 (SH3-domain GRB2-like-intercation protein1) on chromosome 1p31.3. There was a total of 28 SNPs in this region with . The next top SNP, rs12204683 (), resided downstream of LCA5 on chromosome 6q14.1.

Table 2: Genetic loci associated with the occurrence of ACL with *.

CHR
Gene
Lead SNP
BP
Total SNPs
MAF
OR

Negative
Positive

5
PELO
rs6889746
51742663
3
0.3534
0.5
1.776

1
SGIP1
rs6681460
66895645
28
0.3755
0.5168
1.827

6
LCA5
rs12204683
80212978
4
0.2378
0.3701
1.877

4
MIR4275
rs17642174
28160435
6
0.1355
0.2346
2.021

4
C4orf37
rs13134014
99323902
21
0.1517
0.2542
1.928

7
BZW2
rs6961256
16697717
3
0.01261
0.05587
5.214

2
FAM49A
rs6753768
16483918
11
0.2836
0.1648
0.5016

4
MAD2L1
rs10518344

3
0.05136
0.1178
2.696

11
KIRREL3
rs1793667

1
0.2789
0.3966
1.781

14
YLPM1
rs2241275
74321193
7
0.435
0.5587
1.754

14
PROX2
rs4899536
74386367
2
0.4331
0.5559
1.752

2
ATL2
rs6749177
38531205
11
0.4958
0.3659
0.576

17
PRPSAP1
rs11077813
71848140
1
0.2704
0.1564
0.5072

9
TTLL11
rs10985483

4
0.3703
0.25
0.5571

8
ZBTB10
rs406629
81620942
6
0.3795
0.2599
0.5501

21
LINC00317
rs2827107
22175926
3
0.2128
0.3156
1.847

7
NUPL2
rs10232205
23197079
1
0.09244
0.02793
0.2465

1
DUSP10
rs11118750

4
0.2174
0.3287
1.753

15
MCTP2
rs1863095
92917093
1
0.3224
0.4511
1.665

17
SHPK
rs222790
3478239
1
0.2051
0.3097
1.793

6
KHDRBS2
rs2752976
63486388
11
0.431
0.5447
1.688

5
GLRA1
rs154111

14
0.4569
0.3399
0.5875

9
MIR548AA1
rs4836873

4
0.3651
0.2514
0.5746

1
LOC100505918
rs16860501

1
0.09119
0.1648
2.116

19
OR7A10
rs4808564
14825095
1
0.05126
0.1117
2.449

9
C9orf46
rs4742085
5340548
2
0.3501
0.4678
1.696

9
PTPRD
rs2484741
10477877
7
0.2977
0.1983
0.5439

16
PDXDC1
rs3198697
15037441
1
0.3658
0.4859
1.646

CHR: chromosome; Gene: a plausible biological candidate gene in the locus or the nearest annotated gene to the lead SNP; Lead SNP: most significant SNP in the gene region; BP: base-pair position of the lead SNP; Total SNPs: total number of SNPs with in the gene region; MAF: minor allele frequencies in antibody-negative and antibody-positive groups; OR: odds ratio; : -values for the test.

Figure 2: Manhattan plot showing the genome-wide association values with anticardiolipin antibodies (ACL). Blue line indicates .

3.3. Association with Lupus Anticoagulant (LAC)

The Manhattan plot for LAC is shown in Figure 3 and the top hits with are given in Table 3. The most significant SNP, rs1978968, was observed in MICAL3 on chromosome 22q11.21 () and there were additional 7 significant SNPs in this region with . The next significant SNP was observed on chromosome 2p12 in FAM176A (rs17011455, ). However, no other SNP with was observed in this region. The third significant SNP, rs17791782, was observed in DSTN on chromosome 20p12.1 ().

Table 3: Genetic loci associated with the occurrence of lupus anticoagulant (LAC) with *.

CHR
Gene
Lead SNP
BP
Total SNPs
MAF
OR

Negative
Positive

22
MICAL3
rs1978968
16828113
8
0.2144
0.3553
2.235

2
FAM176A
rs17011455
75643997
1
0.01661
0.06967
5.211

20
DSTN
rs17791782
17514069
2
0.07867
0.1721
2.628

6
SUPT3H
rs9472374
44904278
1
0.01957
0.07083
4.77

3
LRIG1
rs4549225
66850149
10
0.3735
0.5246
1.867

1
SMYD3
rs7527610

2
0.005236
0.04098
10.19

14
PELI2
rs754314
55822350
8
0.04833
0.1167
3.111

20
BFSP1
rs16999416
17489830
1
0.08494
0.1777
2.412

16
NDRG4
rs11862356
57067820
1
0.05846
0.1393
2.745

17
CDRT15P1
rs7208809
13678048
2
0.06806
0.1516
2.573

22
FAM19A5
rs9615320
47219591
2
0.1065
0.2008
2.333

6
SNRNP48
rs17398435
7549105
1
0.06392
0.1446
2.589

14
OTX2
rs12897597
56314078
1
0.1531
0.2667
2.097

17
RBFOX3
rs16972153
74719776
1
0.04974
0.1148
2.925

16
MAF
rs9935211
78440577
5
0.05467
0.1311
2.692

5
YTHDC2
rs6865651

2
0.1848
0.3058
2.005

10
LDB3
rs4934256
88490345
2
0.05507
0.123
2.783

9
KLF4
rs1888617

1
0.2657
0.4009
1.935

10
TACC2
rs12773310

6
0.3536
0.219
0.4945

6
LY86
rs9328374
6536628
1
0.1875
0.307
1.989

9
ZCCHC7
rs7031314
37366122
3
0.2204
0.3375
1.924

3
SETD5
rs17050346
9456593
5
0.01926
0.06967
4.047

4
COL25A1
rs13104799

6
0.2245
0.1107
0.4106

7
C7orf58
rs12537243

1
0.09178
0.1736
2.289

4
RBM46
rs7687314

6
0.4474
0.5902
1.808

9
LOC100506710
rs10973184
37056617
1
0.09895
0.1885
2.252

3
EPHA6
rs4318565
97564200
1
0.03369
0.08607
3.32

11
LOC283143
rs1393275

3
0.05026
0.1261
2.595

18
MAPRE2
rs573269
30863716
1
0.3129
0.4385
1.816

13
FARP1
rs285031
97584032
1
0.1489
0.2438
2.092

10
ANXA2P3
rs10822492
66751936
15
0.3439
0.219
0.5075

6
TBCC
rs11759402
42831787
4
0.1658
0.2686
1.945

4
LNX1
rs6831173
54085908
4
0.1337
0.2377
1.962

4
SLC7A11
rs10440463

3
0.2073
0.3238
1.88

1
HHAT
rs1028383

1
0.2248
0.3475
1.882

11
WT1
rs2207549
32325033
2
0.4202
0.2833
0.5274

4
FAM198B
rs17036867

12
0.02747
0.08621
3.54

CHR: chromosome; Gene: a plausible biological candidate gene in the locus or the nearest annotated gene to the lead SNP; Lead SNP: most significant SNP in the gene region; BP: base-pair position of the lead SNP; Total SNPs: total number of SNPs with in the gene region; MAF: minor allele frequencies in antibody-negative and antibody-positive groups; OR: odds ratio; : -values for the test.

Figure 3: Manhattan plot showing the genome-wide association values with lupus anticoagulant (LAC). Blue line indicates .

3.4. Association with Anti-β ₂ Glycoprotein I Antibodies (Anti-β ₂GPI)

Five loci on four chromosomes were observed at for association with anti-β ₂GPI (Figure 4, Table 4). The top SNP (rs10492418) at was observed on chromosome 13q33.3 in MYO16. This chromosome also harbors another locus for anti-β ₂GPI at 13q14.11 (rs9315762, ), near a region expressing long intergenic nonprotein coding RNAs. The second most significant SNP, rs11975235, was observed in PDE1C on chromosome 7p14.3 (). The third most significant SNP was observed upstream of TANK on chromosome 2q24.2 (rs2357982, ) that also harbored 12 additional significant SNPs with .

Table 4: Genetic loci associated with the occurrence of anti-GPI antibodies with *.

CHR
Gene
Lead SNP
BP
Total SNPs
MAF
OR

Negative
Positive

13
MYO16
rs10492418
108178727
5
0.4292
0.6016
2.172

7
PDE1C
rs11975235
32156065
4
0.4843
0.311
0.4675

2
TANK
rs2357982
161594349
13
0.2359
0.3885
2.189

13
FLJ42392
rs9315762
39639907
2
0.1535
0.2901
2.255

20
MACROD2
rs6080100
15951406
7
0.2655
0.4275
2.086

17
CAMKK1
rs758642
3733656
1
0.3314
0.4837
2.038

14
ITPK1
rs8021497
92637371
6
0.2059
0.3508
2.101

2
SESTD1
rs10186547
179921914
2
0.3853
0.5391
2.009

10
CACNB2
rs12356676
18687510
6
0.2587
0.3943
2.134

18
LRRC30
rs9965173
7201755
4
0.07887
0.1718
2.647

3
PEX5L
rs9856007
181225431
3
0.2514
0.3817
1.976

11
TMEM45B
rs10894119
129081436
1
0.1835
0.293
2.168

10
SFTA1P
rs1000039
10597879
1
0.02254
0.08779
4.19

9
OR1J1
rs2778636
124270913
2
0.2641
0.3931
1.955

5
RAPGEF6
rs17671387
130911895
1
0.04507
0.1183
3.186

2
GMCL1
rs4241261
69917164
3
0.4761
0.3308
0.5278

14
C14orf101
rs7153196
56256660
2
0.362
0.229
0.4996

9
WNK2
rs10821084
94991443
1
0.07627
0.1718
2.425

10
SLC16A9
rs7082987
61007793
1
0.3663
0.2317
0.4886

4
GDEP
rs11730315
81020089
2
0.1648
0.2829
2.075

4
ARHGAP24
rs17010960
86938938
2
0.02254
0.07634
4.326

13
HTR2A
rs582385
46343995
4
0.1624
0.2824
2.02

15
FMN1
rs2444955
31199305
2
0.2211
0.355
1.974

5
CARTPT
rs16869487
70976850
1
0.02841
0.09542
3.602

2
NEU2
rs11695991
233608333
1
0.0169
0.0687
4.802

17
CA10
rs203076
47354484
7
0.2944
0.1603
0.4729

9
C9orf135
rs1389124
71669176
3
0.09943
0.1985
2.286

20
SMOX
rs1764996
4070805
2
0.02817
0.07634
4.014

CHR: chromosome; Gene: a plausible biological candidate gene in the locus or the nearest annotated gene to the lead SNP; Lead SNP: most significant SNP in the gene region; BP: base-pair position of the lead SNP; Total SNPs: total number of SNPs with in the gene region; MAF: minor allele frequencies in antibody-negative and antibody-positive groups; OR: odds ratio; : -values for the test.

Figure 4: Manhattan plot showing the genome-wide association values with anti-β ₂ glycoprotein I antibodies (Anti-β ₂GPI). Blue line indicates .

3.5. Association with Presence of Two or More Antibodies

In addition to the single-antibody analyses described above, we also performed an association analysis between individuals who were positive for two or more antibodies () versus individuals who were negative for all three antibodies (). Table 5 shows the results of top loci with . Interestingly, five of these loci (SESTD1, CACNB2, TANK, TMEM45B, and FMN1) overlapped with those observed in the anti-β ₂GPI analysis (see Table 4) and two (DSTN and BFSP1) overlapped with those observed in the LAC analysis (see Table 3). Although the most significant locus, DYNLRB2 (), was not among the top loci detected in any of the single-antibody analyses, the second most significant locus, SESTD1 (), also showed association with anti-β ₂GPI.

Table 5: Genetic loci associated with the occurrence of two or more antiphospholipid antibodies (ACL, LAC, or Anti-GPI) with *.

CHR
Gene
Lead SNP
BP
Total SNPs
MAF
OR

Negative
Positive

16
DYNLRB2
rs8060581
78750106
6
0.02466
0.1406
6.714

2
SESTD1
rs13403289
179924976
2
0.3857
0.5833
2.423

1
DNAH14
rs3913653
223603694
11
0.543
0.3421
0.43

10
CACNB2
rs10828616
18710023
6
0.2175
0.3698
2.538

18
EPB41L3
rs7238186
5469093
2
0.213
0.3854
2.327

1
MAGI3
rs11102625
113750976
5
0.4355
0.6146
2.298

2
TANK
rs13010671
161593338
5
0.07442
0.1882
3.437

7
CNTNAP2
rs12113442
145329124
1
0.1054
0.2188
2.938

18
ZNF519
rs8093228
13989380
4
0.2152
0.3646
2.326

3
FAM198A
rs7624799
43020807
3
0.1592
0.2969
2.466

20
DSTN
rs17791782
17514069
2
0.07883
0.1927
3.086

20
BFSP1
rs16999416
17489830
1
0.08371
0.2031
2.93

13
ANKRD20A9P
rs7319595
18392986
1
0.3484
0.5213
2.337

15
TLE3
rs10518889
68337482
4
0.2838
0.4427
2.231

22
CLTCL1
rs8135222
17672446
1
0.1749
0.3281
2.293

11
TMEM45B
rs10894119
129081436
1
0.1789
0.3158
2.432

1
GADD45A
rs787480
67868460
1
0.2207
0.08854
0.3088

20
SPTLC3
rs6105044
13065747
2
0.352
0.1979
0.4138

6
HIVEP1
rs6908010
12325985
2
0.4753
0.3073
0.4688

7
CUX1
rs427534
101673424
3
0.4439
0.2656
0.4569

10
MSMB
rs7094791
51229942
1
0.3857
0.2396
0.4081

8
TPD52
rs10090469
81396522
1
0.1099
0.2292
2.668

14
LOC100506433
rs698322
47597316
1
0.3914
0.2344
0.4277

6
MMS22L
rs1206164
97703068
1
0.2511
0.4219
2.212

12
CDK17
rs11108526
95379901
2
0.02691
0.08333
5.95

11
PDGFD
rs4754095
103278377
3
0.2851
0.1436
0.3771

15
FMN1
rs2444955
31199305
2
0.1951
0.3474
2.408

10
SORCS1
rs4918273
108715485
11
0.3597
0.5319
2.064

CHR: chromosome; Gene: a plausible biological candidate gene in the locus or the nearest annotated gene to the lead SNP; Lead SNP: most significant SNP in the gene region; BP: base-pair position of the lead SNP; Total SNPs: total number of SNPs with in the gene region; MAF: minor allele frequencies in antibody-negative (negative for ALC, ACL and anti-GPI) and antibody-positive (positive for at least two of ALC, ACL or anti-GPI) groups; OR: odds ratio; : -values for the test.

3.6. Association of Extended Major Histocompatibility Complex (xMHC) Region and Apolipoprotein H (APOH) with APA

Previously, several studies have reported genetic association of the human leukocyte antigen (HLA) genes located at the MHC locus on chromosome 6p21 with the presence of APA [6]. Likewise, since β ₂GPI is the main target antigen for APA, genetic variation in its gene, APOH, is expected to be associated with the occurrence of APA. Although no SNPs from either the HLA genes or APOH were among the top GWAS SNPs with (Tables 2–5), the xMHC region revealed 104, 191, and 108 significant SNPs () to be associated with ACL, LAC, and anti-β ₂GPI, respectively. Table 6 lists significant SNPs with in the MHC region for the three APA examined. Most significant SNPs were observed in or near HLA-DPB1, HLA-DPB2, HLA-DPA1, HLA-DQA1, HLA-DQA2, and HLA-DMA. Noteworthy, some SNPs were associated with more than one APA. For example, among the SNPs located upstream of HLA-DQA2, rs9275765 and rs9275772 were associated with LAC () and anti-β ₂GPI (), rs9275793 with LAC () and anti-β ₂GPI (), and rs9276298 with LAC () and anti-β ₂GPI (). Likewise, rs2395357 near HLA-DPB2 showed association with ACL () and LAC () and rs11539216 in HLA-DMA with ACL () and LAC (). Of the 21 QC-passed SNPs present in or near APOH, six revealed nominal associations with anti-β ₂GPI, and the Trp316Ser variant (rs1801690) was the most significant SNP () (Table 7). Two additional SNPs also showed nominal associations with LAC (, 0.027).

Table 6: Significant SNPs with in the MHC region on chromosome 6 for ACL, LAC, and Anti-GP1*.

Gene
SNP
P

ACL

HLA-DPB1
rs3128918
0.00028

HLA-DPB2
rs2395357
0.00043

HLA-DMA
rs11539216
0.00099

HLA-DQB2
rs10484564
0.00536

GNL1
rs9295888
0.00758

GNL1
rs9295873
0.00794

HLA-DOA
rs4713603
0.0081

RPP21
rs1548515
0.00842

GNL1
rs9461607
0.00863

GNL1
rs17411480
0.00863

RPP21
rs9261821
0.00863

RPP21
rs9261850
0.00863

RPP21
rs9261854
0.00863

RPP21
rs9261855
0.00863

RPP21
rs1548513
0.00863

RPP21
rs9261925
0.00863

RPP21
rs9261926
0.00863

BRD2
rs17840186
0.00939

RPP21
rs9261799
0.00955

LAC

TAP2
rs1044043
0.00029

HLA-DQA1
rs642093
0.00032

AIF1
rs2736177
0.00041

HLA-DQA2
rs9275765
0.00078

HLA-DQA2
rs9275772
0.00078

HLA-DQA2
rs9275793
0.00088

HLA-DQA1
rs9272346
0.00130

HLA-DQA2
rs9276298
0.00133

HLA-DQA1
rs9272219
0.00167

C6orf10
rs3129934
0.00168

HLA-DQA1
rs9272535
0.00179

HLA-DRB1
rs674313
0.00215

HLA-DRB1
rs502771
0.00227

HLA-DRB1
rs9270986
0.00250

AIF1
rs2857597
0.00257

HCG26
rs2516516
0.00282

HLA-DRB1
rs615672
0.00295

HLA-DRB1
rs502055
0.00300

HLA-DQA1
rs9272723
0.00329

LOC100294145
rs9276915
0.00352

C6orf10
rs2894254
0.00372

UBD
rs9368606
0.00403

C6orf10
rs3129900
0.00458

MCCD1
rs2734573
0.00553

PRRC2A
rs1046080
0.00618

C6orf10
rs7767325
0.00623

C6orf15
rs2517448
0.00627

C6orf10
rs3132928
0.00640

HLA-H
rs3132722
0.00675

HLA-DQB2
rs2857210
0.00685

HLA-DRA
rs3129868
0.00731

ATP6V1G2-DDX39B/DDX39B
rs933208
0.00740

NFKBIL1
rs2857605
0.00755

TRIM26
rs3132671
0.00757

HLA-DQB1
rs3129716
0.00770

MSH5/MSH5-C6orf26
rs3131379
0.00849

MSH5/MSH5-C6orf26
rs3130484
0.00901

PSMB9
rs9276832
0.00907

BTNL2
rs2213581
0.00922

HLA-DMA
rs11539216
0.00929

ATP6V1G2-DDX39B/DDX39B
rs3093978
0.00957

C6orf10
rs2143461
0.00986

TUBB
rs3095330
0.00990

LOC100294145
rs4959119
0.00992

TRIM26
rs2517611
0.00993

Anti-GPI

HLA-DPB2
rs9277916
0.00147

HLA-DQA2
rs9275793
0.00310

HLA-DQA2
rs9275765
0.00315

HLA-DQA2
rs9275772
0.00315

HLA-DPA1
rs3130182
0.00331

HLA-DQB1
rs9469220
0.00372

HLA-DPB2
rs4711314
0.00378

HLA-DQA2
rs2647089
0.00463

HLA-DQA2
rs9276298
0.00523

HLA-DQB1
rs9275356
0.00526

HLA-DQA2
rs17615250
0.00710

HLA-DQA2
rs9275618
0.00807

ACL: anticardiolipin antibodies; LAC: lupus anticoagulant; Anti-GPI: anti- glycoprotein I antibodies; Gene: a plausible biological candidate gene in the locus or the nearest annotated gene to the SNP; SNP: single-nucleotide polymorphism; : -values for the test.

Table 7: Odds ratios and -values for the association analysis of APOH SNPs on chromosome 17 with ACL, LAC, and anti-GPI*.

SNP
BP
ACL
LAC
Anti-GPI

OR

OR

OR

rs1801690
61638747
0.7655
0.4048
0.6444
0.2614
2.461
0.003122

rs17769836
61663751
0.8968
0.4457
1.004
0.9821
0.5978
0.004849

rs2873966
61642435
0.9519
0.7168
0.9858
0.9262
0.6224
0.005407

rs7215391
61662484
0.8932
0.4391
0.984
0.9227
0.6146
0.008069

rs8073418
61678134
0.9639
0.7759
0.8949
0.455
0.6661
0.01061

rs8064837
61673165
0.9833
0.8915
1.011
0.9388
1.404
0.02235

rs10491174
61685021
1.017
0.9335
0.765
0.2665
1.487
0.07256

rs2215413
61679959
0.9418
0.6397
0.842
0.2435
0.829
0.221

rs16958979
61654321
0.8586
0.5569
0.4332
0.02739
1.375
0.2253

rs8178822
61655991
0.8748
0.6127
0.407
0.0258
1.379
0.2345

rs12452959
61635526
0.8991
0.5748
1.196
0.3965
1.275
0.2541

rs4791079
61640002
1.128
0.3573
1.206
0.2028
1.181
0.2802

rs3176975
61641219
0.9723
0.8552
0.9923
0.9649
1.209
0.2858

rs8066294
61673500
1.094
0.5597
1.014
0.9365
1.162
0.3981

rs17763430
61635203
0.998
0.9904
0.8987
0.5811
0.8448
0.4051

rs17690171
61633319
0.9893
0.9435
1.172
0.3479
1.141
0.4528

rs16959003
61671199
1.105
0.6095
0.8378
0.4548
1.14
0.5639

rs735866
61670208
1.206
0.3459
0.8419
0.4765
1.117
0.642

rs7208089
61689374
1.091
0.5465
0.7956
0.1906
1.08
0.6476

rs7222710
61630703
1.089
0.5011
1.016
0.9143
0.942
0.6896

rs6933
61638692
1.126
0.3408
1.068
0.6431
1.02
0.8948

APOH: apolipoprotein H; SNP: single-nucleotide polymorphism; BP: base-pair position; OR: odds ratio; : -values. ACL: anticardiolipin antibodies; LAC: lupus anticoagulant; Anti-GPI: anti- glycoprotein I antibodies.

4. Discussion

The persistent presence of APA, such as ACL, LAC, or anti-β ₂GPI, may lead to the development of antiphospholipid syndrome (APS), which may occur alone (primary APS) or in the presence of an autoimmune disease (secondary APS). Although the genetic basis of APA and APS has been suggested [4, 5], the precise identity of the causative genes is largely unknown. Here we report the first GWAS focused on identifying the susceptibility loci/genes for the occurrence of three main APA, namely, ACL, LAC, and anti-β ₂GPI.

Initially, we performed separate genome-wide analyses for the three APA because the antigen specificity of APA is highly heterogeneous and each APA may have different genetic determinants. This seems to be confirmed in our GWAS results where none of the top loci for the three APA overlapped (see Tables 2–4). However, a single-antibody analysis may include individuals who are positive for more than one antibody in the antibody-positive group or may include individuals in the antibody-negative group who are positive for another antibody, which might have an effect on the genetic association outcome. In order to address this potential problem, we performed an additional genome-wide analysis on individuals who were positive for two or more APA as they presumably would have a higher genetic load of APA susceptibility genes and compared them with those who were negative for all three APA tested. Noteworthy, seven of the top loci observed in the latter analysis overlapped with the top loci observed in the individual analyses of anti-β ₂GPI and LAC (see Table 5). Although none of the observed top loci in any analysis met the strict criteria for genome-wide level of significance (), we have identified a number of suggestive genomic regions with that are worthy of follow-up studies in independent samples. They include loci harboring DYNLRB2 () and SESTD1 () for individuals positive for at least two APA; PELO (), SGIP1 (), and LCA5 () for ACL; MICAL3 (), FAM176A (), and DSTN () for LAC; and MYO16 (), PDE1C (), TANK (), FLJ42392 (), and MACROD2 () for anti-β ₂GPI.

While many of these loci are of unknown function in antibody production, some of them harbor candidate genes known to be involved in immune response and thus may be relevant to the production of APA. For example, DYNLRB2 is involved in immune signaling and genetic variation in this gene is associated with tuberculosis susceptibility [7]. SESTD1 binds several phospholipid species [8] and may thus serve as an autoantigen for APA. TANK (TRAF family member-associated NFKB activator) is believed to be important in type 1 interferon production [9] and has been suggested to play a role in hepatitis B and C infections [10, 11]. The MYO16 (myosin XVI) locus has recently been implicated in diabetic nephropathy [12–14]. Interestingly, the presence of APA or APS is a strong risk factor for nephropathy [15–17] and one study has suggested that anti-β ₂GPI may be protective against lupus nephritis and renal damage [18]. FAM176A (a.k.a TMEM166) has been implicated in autophagy and apoptosis [19], two mechanisms with suggested roles in autoimmunity [20, 21].

Before the GWAS era, the focus of genetic studies on APA was mainly on candidate genes, with a major emphasis on HLA genes located at the MHC locus and to some extent on APOH. Since none of our top hits included SNPs from either the HLA genes or APOH, we examined the extent of association signals in these genomic regions. Indeed, we found a number of promising significant SNPs near or in various HLA genes to be associated with ACL, LAC, and anti-β ₂GPI (see Table 6). Our findings are consistent with previous reports that also found multiple associations of HLA genes with these autoantibodies [6]. Previous findings regarding the association of APOH coding SNPs with APA have been inconsistent because of the conflicting reports [6, 22]. In our sample, we found six APOH SNPs to be associated with anti-β ₂GPI and the most significant SNP was rs1801690 (Trp316Ser) (see Table 7) that is located in the 5th domain of β ₂GPI affecting the phospholipid-binding site [23]. Another coding SNP in APOH, rs3176975 (Val247Leu), that has been reported to be associated with APS [22], showed only a modest trend for association in our sample (odds ratio 1.21; ). The replication of previously reported HLA and APOH findings with similar association signals serve as positive controls for our GWAS. On the other hand, it also indicates that HLA and APOH are not among the top loci for APA and thus our focus should be on the identification and characterization of other genes that are more relevant to the production of APA.

In conclusion, to the best of our knowledge, this is the first GWAS that has attempted to delineate the genetic basis of three main APA, namely, ACL, LAC, and anti-β ₂GPI. Although we did not identify loci meeting the conservative threshold of genome-wide significance, we have identified a number of suggestive novel loci for APA that will stimulate follow-up studies in independent and larger sample sets to replicate our findings. The main limitations of our study include relatively small sample size and lack of a replication sample; however, our top SNPs provide a select group of suggestive candidate loci/genes that can easily be tested for replication by other research groups, which would also enable a subsequent meta-analysis with increased power.

Conflict of Interests

The authors declare that they have no conflict of interests.

Acknowledgments

This study was supported by the US National Institutes of Health, Grants HL092397, HL088648, AR057028, AR046588, AR057338, HD066139, AR02318, AR30492, AR48098, AR30692, and RR025741, and by a Grant from the Lupus Foundation of America.

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