Autoimmune Diseases

Autoimmune Diseases / 2013 / Article

Research Article | Open Access

Volume 2013 |Article ID 761046 | 11 pages | https://doi.org/10.1155/2013/761046

Genome-Wide Association Study of Antiphospholipid Antibodies

Academic Editor: Ricard Cervera
Received05 Nov 2012
Revised10 Jan 2013
Accepted10 Jan 2013
Published24 Feb 2013

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-β2 glycoprotein I antibodies (anti-β2GPI). 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-β2 glycoprotein I antibodies (anti-β2GPI) 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-β2GPI.

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-β2GPI ( ) 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.


ACLLACAnti- GPI
PositiveNegativePositiveNegativePositiveNegative
( )( )( )( )( )( )

Mean age ± SD
SLE cases (%)58.558.170.856.371.351.9
Controls (%)41.541.929.243.728.748.1

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-β2GPI (QUANTA Lite β2GPI 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-β2GPI) 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-β2GPI) 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-β2GPI (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-β2GPI. 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.

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.


CHRGeneLead SNPBPTotal SNPsMAFOR
NegativePositive

5PELO rs68897465174266330.35340.51.776
1SGIP1 rs668146066895645280.37550.51681.827
6LCA5 rs122046838021297840.23780.37011.877
4MIR4275 rs176421742816043560.13550.23462.021
4C4orf37 rs1313401499323902210.15170.25421.928
7BZW2 rs69612561669771730.012610.055875.214
2FAM49A rs675376816483918110.28360.16480.5016
4MAD2L1 rs10518344 30.051360.11782.696
11KIRREL3 rs1793667 10.27890.39661.781
14YLPM1 rs22412757432119370.4350.55871.754
14PROX2 rs48995367438636720.43310.55591.752
2ATL2 rs674917738531205110.49580.36590.576
17PRPSAP1 rs110778137184814010.27040.15640.5072
9TTLL11 rs10985483 40.37030.250.5571
8ZBTB10 rs4066298162094260.37950.25990.5501
21LINC00317 rs28271072217592630.21280.31561.847
7NUPL2 rs102322052319707910.092440.027930.2465
1DUSP10 rs11118750 40.21740.32871.753
15MCTP2 rs18630959291709310.32240.45111.665
17SHPK rs222790347823910.20510.30971.793
6KHDRBS2 rs275297663486388110.4310.54471.688
5GLRA1 rs154111 140.45690.33990.5875
9MIR548AA1 rs4836873 40.36510.25140.5746
1LOC100505918 rs16860501 10.091190.16482.116
19OR7A10 rs48085641482509510.051260.11172.449
9C9orf46 rs4742085534054820.35010.46781.696
9PTPRD rs24847411047787770.29770.19830.5439
16PDXDC1 rs31986971503744110.36580.48591.646

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.
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 ( ).


CHRGeneLead SNPBPTotal SNPsMAFOR
NegativePositive

22MICAL3 rs19789681682811380.21440.35532.235
2FAM176A rs170114557564399710.016610.069675.211
20DSTN rs177917821751406920.078670.17212.628
6SUPT3H rs94723744490427810.019570.070834.77
3LRIG1 rs454922566850149100.37350.52461.867
1SMYD3 rs7527610 20.0052360.0409810.19
14PELI2 rs7543145582235080.048330.11673.111
20BFSP1 rs169994161748983010.084940.17772.412
16NDRG4 rs118623565706782010.058460.13932.745
17CDRT15P1 rs72088091367804820.068060.15162.573
22FAM19A5 rs96153204721959120.10650.20082.333
6SNRNP48 rs17398435754910510.063920.14462.589
14OTX2 rs128975975631407810.15310.26672.097
17RBFOX3 rs169721537471977610.049740.11482.925
16MAF rs99352117844057750.054670.13112.692
5YTHDC2 rs6865651 20.18480.30582.005
10LDB3 rs49342568849034520.055070.1232.783
9KLF4 rs1888617 10.26570.40091.935
10TACC2 rs12773310 60.35360.2190.4945
6LY86 rs9328374653662810.18750.3071.989
9ZCCHC7 rs70313143736612230.22040.33751.924
3SETD5 rs17050346945659350.019260.069674.047
4COL25A1 rs13104799 60.22450.11070.4106
7C7orf58 rs12537243 10.091780.17362.289
4RBM46 rs7687314 60.44740.59021.808
9LOC100506710 rs109731843705661710.098950.18852.252
3EPHA6 rs43185659756420010.033690.086073.32
11LOC283143 rs1393275 30.050260.12612.595
18MAPRE2 rs5732693086371610.31290.43851.816
13FARP1 rs2850319758403210.14890.24382.092
10ANXA2P3 rs1082249266751936150.34390.2190.5075
6TBCC rs117594024283178740.16580.26861.945
4LNX1 rs68311735408590840.13370.23771.962
4SLC7A11 rs10440463 30.20730.32381.88
1HHAT rs1028383 10.22480.34751.882
11WT1 rs22075493232503320.42020.28330.5274
4FAM198B rs17036867 120.027470.086213.54

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.
3.4. Association with Anti-β2 Glycoprotein I Antibodies (Anti-β2GPI)

Five loci on four chromosomes were observed at for association with anti-β2GPI (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-β2GPI 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 .


CHRGeneLead SNPBPTotal SNPsMAFOR
NegativePositive

13MYO16 rs1049241810817872750.42920.60162.172
7PDE1C rs119752353215606540.48430.3110.4675
2TANK rs2357982161594349130.23590.38852.189
13FLJ42392 rs93157623963990720.15350.29012.255
20MACROD2 rs60801001595140670.26550.42752.086
17CAMKK1 rs758642373365610.33140.48372.038
14ITPK1 rs80214979263737160.20590.35082.101
2SESTD1 rs1018654717992191420.38530.53912.009
10CACNB2 rs123566761868751060.25870.39432.134
18LRRC30 rs9965173720175540.078870.17182.647
3PEX5L rs985600718122543130.25140.38171.976
11TMEM45B rs1089411912908143610.18350.2932.168
10SFTA1P rs10000391059787910.022540.087794.19
9OR1J1 rs277863612427091320.26410.39311.955
5RAPGEF6 rs1767138713091189510.045070.11833.186
2GMCL1 rs42412616991716430.47610.33080.5278
14C14orf101 rs71531965625666020.3620.2290.4996
9WNK2 rs108210849499144310.076270.17182.425
10SLC16A9 rs70829876100779310.36630.23170.4886
4GDEP rs117303158102008920.16480.28292.075
4ARHGAP24 rs170109608693893820.022540.076344.326
13HTR2A rs5823854634399540.16240.28242.02
15FMN1 rs24449553119930520.22110.3551.974
5CARTPT rs168694877097685010.028410.095423.602
2NEU2 rs1169599123360833310.01690.06874.802
17CA10 rs2030764735448470.29440.16030.4729
9C9orf135 rs13891247166917630.099430.19852.286
20SMOX rs1764996407080520.028170.076344.014

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.
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-β2GPI 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-β2GPI.


CHRGeneLead SNPBPTotal SNPsMAFOR
NegativePositive

16DYNLRB2 rs80605817875010660.024660.14066.714
2SESTD1 rs1340328917992497620.38570.58332.423
1DNAH14 rs3913653223603694110.5430.34210.43
10CACNB2 rs108286161871002360.21750.36982.538
18EPB41L3 rs7238186546909320.2130.38542.327
1MAGI3 rs1110262511375097650.43550.61462.298
2TANK rs1301067116159333850.074420.18823.437
7CNTNAP2 rs1211344214532912410.10540.21882.938
18ZNF519 rs80932281398938040.21520.36462.326
3FAM198A rs76247994302080730.15920.29692.466
20DSTN rs177917821751406920.078830.19273.086
20BFSP1 rs169994161748983010.083710.20312.93
13ANKRD20A9P rs73195951839298610.34840.52132.337
15TLE3 rs105188896833748240.28380.44272.231
22CLTCL1 rs81352221767244610.17490.32812.293
11TMEM45B rs1089411912908143610.17890.31582.432
1GADD45A rs7874806786846010.22070.088540.3088
20SPTLC3 rs61050441306574720.3520.19790.4138
6HIVEP1 rs69080101232598520.47530.30730.4688
7CUX1 rs42753410167342430.44390.26560.4569
10MSMB rs70947915122994210.38570.23960.4081
8TPD52 rs100904698139652210.10990.22922.668
14LOC100506433 rs6983224759731610.39140.23440.4277
6MMS22L rs12061649770306810.25110.42192.212
12CDK17 rs111085269537990120.026910.083335.95
11PDGFD rs475409510327837730.28510.14360.3771
15FMN1 rs24449553119930520.19510.34742.408
10SORCS1 rs4918273108715485110.35970.53192.064

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 β2GPI 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 25), the xMHC region revealed 104, 191, and 108 significant SNPs ( ) to be associated with ACL, LAC, and anti-β2GPI, 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-β2GPI ( ), rs9275793 with LAC ( ) and anti-β2GPI ( ), and rs9276298 with LAC ( ) and anti-β2GPI ( ). 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-β2GPI, and the Trp316Ser variant (rs1801690) was the most significant SNP ( ) (Table 7). Two additional SNPs also showed nominal associations with LAC ( , 0.027).


GeneSNPP

ACL

HLA-DPB1 rs31289180.00028
HLA-DPB2 rs23953570.00043
HLA-DMA rs115392160.00099
HLA-DQB2 rs104845640.00536
GNL1 rs92958880.00758
GNL1 rs92958730.00794
HLA-DOA rs47136030.0081
RPP21 rs15485150.00842
GNL1 rs94616070.00863
GNL1 rs174114800.00863
RPP21 rs92618210.00863
RPP21 rs92618500.00863
RPP21 rs92618540.00863
RPP21 rs92618550.00863
RPP21 rs15485130.00863
RPP21 rs92619250.00863
RPP21 rs92619260.00863
BRD2 rs178401860.00939
RPP21 rs92617990.00955

LAC

TAP2 rs10440430.00029
HLA-DQA1 rs6420930.00032
AIF1 rs27361770.00041
HLA-DQA2 rs92757650.00078
HLA-DQA2 rs92757720.00078
HLA-DQA2 rs92757930.00088
HLA-DQA1 rs92723460.00130
HLA-DQA2 rs92762980.00133
HLA-DQA1 rs92722190.00167
C6orf10 rs31299340.00168
HLA-DQA1 rs92725350.00179
HLA-DRB1 rs6743130.00215
HLA-DRB1 rs5027710.00227
HLA-DRB1 rs92709860.00250
AIF1 rs28575970.00257
HCG26 rs25165160.00282
HLA-DRB1 rs6156720.00295
HLA-DRB1 rs5020550.00300
HLA-DQA1 rs92727230.00329
LOC100294145 rs92769150.00352
C6orf10 rs28942540.00372
UBD rs93686060.00403
C6orf10 rs31299000.00458
MCCD1 rs27345730.00553
PRRC2A rs10460800.00618
C6orf10 rs77673250.00623
C6orf15 rs25174480.00627
C6orf10 rs31329280.00640
HLA-H rs31327220.00675
HLA-DQB2 rs28572100.00685
HLA-DRA rs31298680.00731
ATP6V1G2-DDX39B/DDX39B rs9332080.00740
NFKBIL1 rs28576050.00755
TRIM26 rs31326710.00757
HLA-DQB1 rs31297160.00770
MSH5/MSH5-C6orf26 rs31313790.00849
MSH5/MSH5-C6orf26 rs31304840.00901
PSMB9 rs92768320.00907
BTNL2 rs22135810.00922
HLA-DMA rs115392160.00929
ATP6V1G2-DDX39B/DDX39B rs30939780.00957
C6orf10 rs21434610.00986
TUBB rs30953300.00990
LOC100294145 rs49591190.00992
TRIM26 rs25176110.00993

Anti- GPI

HLA-DPB2 rs92779160.00147
HLA-DQA2 rs92757930.00310
HLA-DQA2 rs92757650.00315
HLA-DQA2 rs92757720.00315
HLA-DPA1 rs31301820.00331
HLA-DQB1 rs94692200.00372
HLA-DPB2 rs47113140.00378
HLA-DQA2 rs26470890.00463
HLA-DQA2 rs92762980.00523
HLA-DQB1 rs92753560.00526
HLA-DQA2 rs176152500.00710
HLA-DQA2 rs92756180.00807

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.

SNPBPACLLACAnti- GPI
OR OR OR

rs1801690616387470.76550.40480.64440.26142.4610.003122
rs17769836616637510.89680.44571.0040.98210.59780.004849
rs2873966616424350.95190.71680.98580.92620.62240.005407
rs7215391616624840.89320.43910.9840.92270.61460.008069
rs8073418616781340.96390.77590.89490.4550.66610.01061
rs8064837616731650.98330.89151.0110.93881.4040.02235
rs10491174616850211.0170.93350.7650.26651.4870.07256
rs2215413616799590.94180.63970.8420.24350.8290.221
rs16958979616543210.85860.55690.43320.027391.3750.2253
rs8178822616559910.87480.61270.4070.02581.3790.2345
rs12452959616355260.89910.57481.1960.39651.2750.2541
rs4791079616400021.1280.35731.2060.20281.1810.2802
rs3176975616412190.97230.85520.99230.96491.2090.2858
rs8066294616735001.0940.55971.0140.93651.1620.3981
rs17763430616352030.9980.99040.89870.58110.84480.4051
rs17690171616333190.98930.94351.1720.34791.1410.4528
rs16959003616711991.1050.60950.83780.45481.140.5639
rs735866616702081.2060.34590.84190.47651.1170.642
rs7208089616893741.0910.54650.79560.19061.080.6476
rs7222710616307031.0890.50111.0160.91430.9420.6896
rs6933616386921.1260.34081.0680.64311.020.8948

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-β2GPI, 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-β2GPI.

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 24). 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-β2GPI 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-β2GPI.

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 [1214]. Interestingly, the presence of APA or APS is a strong risk factor for nephropathy [1517] and one study has suggested that anti-β2GPI 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-β2GPI (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-β2GPI and the most significant SNP was rs1801690 (Trp316Ser) (see Table 7) that is located in the 5th domain of β2GPI 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-β2GPI. 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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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.

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