SEARCH

SEARCH BY CITATION

Keywords:

  • autoantibodies;
  • congenital heart block;
  • HLA-DRB1*04;
  • MHC ;
  • neonatal lupus erythematosus

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. Author contributions
  10. References
  11. Supporting Information

Objective

The main aim of this study was to identify foetal susceptibility genes on chromosome six for Ro/SSA autoantibody-mediated congenital heart block.

Subjects and Design

Single nucleotide polymorphism (SNP) genotyping of individuals in the Swedish Congenital Heart Block (CHB) study population was performed. Low-resolution HLA-A, -Cw and -DRB1 allele typing was carried out in 86 families comprising 339 individuals (86 Ro/SSA autoantibody-positive mothers, 71 fathers, 87 CHB index cases and 95 unaffected siblings).

Results

A case–control comparison between index cases and population-based out-of-study controls (n = 1710) revealed association of CHB with 15 SNPs in the 6p21.3 MHC locus at a chromosome-wide significance of < 2.59 × 10−6 (OR 2.21–3.12). In a family-based analysis of association of SNP markers as well as distinct MHC class I and II alleles with CHB, HLA-DRB1*04 and HLA-Cw*05 variants were significantly more frequently transmitted to affected individuals (< 0.03 and < 0.05, respectively), whilst HLA-DRB1*13 and HLA-Cw*06 variants were significantly less often transmitted to affected children (< 0.04 and < 0.03). We further observed marked association of increased paternal (but not maternal) HLA-DRB1*04 transmission to affected offspring (P < 0.02).

Conclusions

HLA-DRB1*04 and HLA-Cw*05 were identified as novel foetal HLA allele variants that confer susceptibility to CHB in response to Ro/SSA autoantibody exposure, whilst DRB1*13 and Cw*06 emerged as protective alleles. Additionally, we demonstrated a paternal contribution to foetal susceptibility to CHB for the first time.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. Author contributions
  10. References
  11. Supporting Information

Increased risk of complications and foetal death during pregnancy in women with autoimmune diseases is clearly documented [1]. In women carrying autoantibodies to Ro/SSA and La/SSB autoantigens, the foetus may develop congenital heart block (CHB) [2, 3]. These mothers are often diagnosed with systemic lupus erythematosus or Sjögren's syndrome, but may also be asymptomatic [4-6]. The foetal atrioventricular (AV) block frequently develops during gestational weeks 18–24 after placental transfer of maternal autoantibodies, which affect the foetal heart by initiating a series of events leading to cardiac inflammation, fibrosis and calcification, and eventual blockage of signal conduction at the AV node [7, 8]. The association between CHB and maternal Ro/SSA autoantibodies is well established, with recent studies indicating that the risk for foetal heart block may be higher in women with antibody reactivity towards Ro52 and its specific epitopes, rather than the Ro60 component of the Ro/SSA antigen [9-12]. However, the current assays used to detect anti-Ro60 autoantibodies often fail to reproduce all relevant epitopes, and the number of Ro60 autoantibody-positive women may therefore be underestimated.

The risk for CHB in Ro/SSA antibody-positive pregnancies is 1–2% [13], with a recurrence rate of 12–20%, despite persisting maternal autoantibodies [6, 14-17], indicating that factors other than maternal autoantibodies are additionally critical for development of CHB in response to Ro/SSA antibody exposure.

Foetal susceptibility factors are suggested to determine outcomes in Ro/SSA-positive pregnancies [18], and in most autoimmune disorders, the MHC locus is the dominant genetic contributor to disease development. We recently demonstrated that maternal MHC restricts and regulates the generation of pathogenic Ro52 autoantibodies. Furthermore, foetal MHC alleles appear to determine susceptibility to CHB development under exposure to pathogenic Ro52 autoantibodies in the rat model [19]. In view of these observations and the major influence of the HLA locus in human autoimmune disease, we examined the hypothesis that foetal HLA alleles affect the risk of developing Ro/SSA autoantibody-mediated CHB. To this effect, we genotyped single nucleotide polymorphisms (SNPs) on chromosome six and determined HLA-A, -Cw and -DRB1 alleles in a population-based cohort of families with Ro/SSA-positive mothers and at least one case of CHB. HLA-DRB1*04 and HLA-Cw*05 were identified as novel foetal genetic variants that confer susceptibility to CHB, whilst DRB1*13 and Cw*06 emerged as protective alleles. Moreover, our experiments revealed a significant paternal genetic influence on foetal susceptibility to CHB for the first time.

Materials and methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. Author contributions
  10. References
  11. Supporting Information

Study population

Patients and their families were selected from a population-based cohort with complete third-degree CHB [17, 20, 21]. Identification and characterization of patients and their families have been described in previous reports [17, 20, 21]. We included 86 families (mothers, fathers, index CHB cases and siblings) with available maternal serum samples and testing positive for Ro52 and/or Ro60 and La in the present study [17, 20, 21]. Amongst the 86 mothers, 47 had rheumatic diagnosis (systemic lupus erythematosus [22], n = 27; Sjögren's syndrome [23], n = 14; rheumatoid arthritis [24], n = 4; undifferentiated connective tissue disease, n = 2); 18 were asymptomatic and/or did not fulfil diagnostic criteria for rheumatic diseases; and information was not available for 21 patients.

The study was approved by the Regional Ethical Committee, Stockholm, Karolinska Institute, and all participants (parents in cases where the individual was <18 years of age) provided informed written consent.

DNA preparation

Erythrocytes were lysed in EDTA blood samples by adding Red Blood Cell Lysis Buffer (160 mmol L−1 NH4Cl, 10 mmol L−1 KHCO3, 50 mmol L−1 EDTA), and leucocytes collected by centrifugation at 1200 × g for 20 min at 4 °C. Leucocytes were solubilized with 0.75% (w/v) SDS/ddH2O, and proteolytic digestion performed by adding 10 mg mL−1 Proteinase K (Invitrogen, Stockholm, Sweden) followed by overnight incubation at 37 °C. Saturated NaCl (6M at a 1:3 ratio) was added, and precipitated proteins and lipid fractions spun down at 6000 × g for 10 min at room temperature. DNA was precipitated with 99% ethanol and dissolved in 1× Tris-EDTA buffer at 37 °C. Photometric analysis of DNA concentration and purity was performed. DNA working solutions were diluted to a final concentration of 50 μg mL−1 and stored at −80 °C.

Single nucleotide polymorphism genotyping and statistical analysis

Genotyping of individuals from the Swedish Congenital Heart Block study population was performed on the Illumina 660W-Quad Beadchip. The consistency of reported genotype calls and strand determination was maintained using the Illumina ‘TOP/BOT’ strand and ‘A/B’ allele designations (http://www.illumina.com/documents/products/technotes/technote_topbot.pdf). Quality control (QC) of genotyping revealed an average genotype call rate per individual of 99.87% and average SNP call rate of 99.86%. In total, 13 samples (3.34%) were genotyped in duplicate, with a genotype call reproducibility of 99.99%.

Genotyping data from population-based controls for case–control analysis were obtained from a) EIRA [25], a population-based study of incident cases of rheumatoid arthritis and matched controls, and b) PROCARDIS [26], a family-based multicentre study of coronary heart disease and controls. Genotyping of out-of-study control samples has been described in earlier reports [26, 27]. After QC, 19,341 SNP markers on chromosome six overlapping across the three data sets and displaying MAF >0.01, Hardy–Weinberg equilibrium (HWE) >0.0001 (controls) and SNP genotype call rate >95% were included in the analysis. QC for population stratification in the case–control data set was performed using structured analysis within homogeneous clusters defined by identity-by-state (IBS) similarity for SNPs across the genome (PLINK, http://pngu.mgh.harvard.edu/~purcell/plink/). Overall, 87 homogeneous clusters were obtained and 42 control samples failed QC, resulting in their removal from downstream analysis. The Cochran–Mantel–Haenszel (CMH) [28] statistical test across 87 strata was used to examine SNP associations with CHB. Genomic control inflation factor was 1.01, indicating minimal background stratification. A P-value of 2.59 × 10−6 was defined as chromosome-wide significance (after Bonferroni correction) in this SNP association analysis.

For family-based analysis, samples with an individual genotype call rate >95%, Mendelian errors per family <2%, SNP genotype call rate >95%, SNP-based Mendelian error <4%, minor allele frequency (MAF) >0.01 and HWE P > 1 × 10−8 were included. After QC, 36,636 SNPs on chromosome six comprising genotype information from 244 individuals (87 cases and 157 parents) were retained for analysis. SNP genotypes from unaffected siblings were used in cases where parental information was missing. Transmission disequilibrium in families was analysed with the pedigree disequilibrium test (PDT) using Unphased (Version 3.0.13.) [29]. PDT analysis was further applied to calculate the association of 2311 SNP markers within the extended MHC region (6:25.7–33.7 Mb) [30] with HLA-A,-Cw and DRB1 alleles. We additionally estimated odds ratios (OR), confidence intervals (CI) and global linkage disequilibrium (LD) using the full model analysis, calculation of individual haplotypes and the specific test haplotype option in the Unphased program. P-values denote deviation from 50% transmission, whilst OR and CI calculations are based on risk allele frequencies in relation to all other allele frequencies as a reference and rely on the Unphased output of estimated counts of the risk haplotype transmitted to cases and estimated number of risk haplotypes amongst controls and nontransmitted haplotypes to affected individuals, which are used in a standard two-by-two table analysis. For allele frequencies ≤0.008, Haldane's corrections were used to calculate OR [31]. All reference genome assemblies refer to the NCBI 36.3 build.

HLA allele genotyping and statistical analysis

Low-resolution HLA allele typing was carried out using sequence-specific primers for PCR-based amplification of HLA-A,-Cw and -DRB1 genes [32]. Amplified products were analysed after size separation on a 2% agarose gel, and specific HLA genotypes determined according to the manufacturer's instructions (Olerup SSP AB, Stockholm, Sweden). After QC for Mendelian rules of inheritance, 339 individuals (86 Ro/SSA autoantibody-positive mothers, 71 fathers, 87 CHB index cases and 95 unaffected siblings) were included for further analyses. HLA genotyping data from out-of-study controls were obtained from the previously described Swedish Multiple Sclerosis cohort [33, 34]. Differences amongst HLA allele carrier frequencies were calculated using Yates′s correction for continuity (Yates's chi-squared test) in Microsoft Excel (2007). For expected numbers of carriers ≤5, the Fisher exact test was applied. Transmission frequency, OR and CI calculations for CHB-associated alleles were performed in Unphased using full model analysis, calculation of individual haplotypes and the specific test haplotype option, including only heterozygous parents. OR and CI calculations in HLA family-based analysis are based on risk allele frequencies in relation to all other allele frequencies as a reference, whilst P-values denote deviation from 50% transmission. Parental transmission frequencies of associated HLA alleles to siblings with and without CHB were calculated using the parent-of-origin tool in PLINK.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. Author contributions
  10. References
  11. Supporting Information

SNP association study of chromosome six reveals significant associations of HLA class I and II gene loci with congenital heart block

We recently demonstrated that foetal MHC genes add to the risk of CHB development after exposure to maternal Ro/SSA autoantibodies in an experimental animal model of CHB [35]. To identify the human foetal susceptibility genes in Ro/SSA autoantibody-mediated CHB, we performed an association study of 19 341 SNP markers on chromosome six comprising SNP data from index cases (n = 87) and population-based healthy controls (n = 1710). Fifteen SNPs in the 6p21.3 extended MHC locus were associated with CHB at a chromosome-wide significance level (P < 2.59 × 10−6; Fig. 1 and Table S1).

image

Figure 1. The strongest SNP associations with congenital heart block across chromosome six are found within the MHC region. Association plot shows the significance of association [−log10 (p)] of the Cochran–Mantel–Haenszel test of 19 341 SNPs after correction by λ and population strata versus chromosomal position (mega bases, Mb) across chromosome six (NCBI build 36.3). The analysis included 87 CHB cases and 1710 population controls. PGWAS values are plotted for all SNPs. The horizontal line represents the chromosome-wide significance level (2.59 × 10−6) after Bonferroni correction.

Download figure to PowerPoint

Single nucleotide polymorphism associations within the MHC locus were subsequently analysed using a family-based approach. In view of the known strong HLA-DRB1*03 allele association with SLE, Sjögren's syndrome and production of Ro/SSA autoantibodies [36], we attempted to discriminate CHB-related SNP marker associations from those reflecting the inherited maternal autoimmune disease traits. Pedigree disequilibrium test (PDT) of 2311 SNP markers within the 6p21.3 extended MHC locus [30], including 87 CHB index cases and 157 parents, 86 mothers and 71 fathers, disclosed seven SNP marker associations ( 0.01) as CHB-specific disease traits (Fig. 2 and Table S2). LD analysis between the associated SNP markers and HLA-A,-Cw and -DRB1 revealed LD of rs7356880, rs805272, rs2858870 and rs926239 with HLA-Cw and/or -DRB1, respectively (D’ values >0.65) (Table S3). Given the strong LD in this genomic region, we additionally performed conditional analysis to ascertain the independent signals for CHB associations amongst the significant candidate SNPs. Our results revealed independent associations of rs7356880 and rs2858870 with CHB (data not shown).

image

Figure 2. Polymorphisms associated with congenital heart block across the extended MHC region in a family-based analysis. Association plot shows significance of association [−log10 (p)] using the pedigree disequilibrium test (PDT) of 2311 SNPs versus chromosomal position (Mb) across the extended MHC region (chromosome six: 25.7–33.7 Mb) in 87 cases, 86 mothers and 71 fathers (NCBI build 36.3). PDT values are plotted for all SNPs. SNPs above the horizontal line reached P-values <0.01.

Download figure to PowerPoint

HLA-DRB1*04 and HLA-Cw*05 alleles are significantly associated with susceptibility to congenital heart block

To determine whether specific HLA alleles encoded by HLA-A, -Cw and -DRB1 gene loci influence disease outcomes in Ro/SSA autoantibody-exposed individuals, we performed HLA-A, -Cw and -DRB1 genotyping in families with CHB index cases.

As expected, mothers who were carriers of Ro/SSA autoantibodies and often diagnosed with Sjögren′s syndrome or SLE had significantly higher frequencies of HLA-A*01 (52%; < 2 × 10-6), HLA-Cw*07 (84%; < 4 × 10-6) and class II HLA-DRB1*03 (79%; < 2 × 10-29) and HLA-DRB1*11 (14%; < 9 × 10-9) alleles, compared to distribution amongst the general population (Table 1), consistent with previous reports [37-39]. HLA-DRB1*04 alleles were significantly lower in mothers of CHB index cases than healthy controls. For the majority of paternal HLA alleles, no significant differences in the percentage of carrier frequencies were observed, compared to carrier frequencies in the general population (Table 1).

Table 1. HLA-A, HLA-Cw and HLA-DRB1 carrier frequencies in parents to CHB index cases, compared to the general populationa
 General populationMothersFathers
n (Carrier)% (C.freq.)% (A.freq.)n (Carrier)% (C.freq.)P-value% (A.freq.)n (Carrier)% (C.freq.)P-value
  1. a

    Yates chi-squared test of allele distribution amongst mothers (n = 86) or fathers (n = 71) of CHB index cases, compared to the general population [n (HLA-A) = 2281; n (HLA-Cw) = 1133; n (HLA-DRB1) = 2275] was performed. Corrected Yates P-values are depicted. For expected numbers of carriers ≤5, the Fisher exact test was applied. All tested HLA-A, HLA-Cw and HLA-DRB1 alleles, number of carriers [n (carrier)] and percentage of carrier frequencies [% (C.freq.)] are listed. For mothers and fathers of CHB index cases, the percentages of allele frequencies [% (A.freq.)] are denoted. A P-value of 6 × 10−4 was considered significant after Bonferroni correction for multiple comparisons.

HLA-A
*0159727.0027.064451.761 × 10-613.571927.141.00
*02125856.9027.064249.410.2134.293955.711.00
*0367430.4814.122428.240.7518.572535.710.44
*112209.954.7178.240.755.00710.001.00
*23512.310.5911.180.750.7111.431.00
*2435616.104.7189.410.135.71811.430.37
*25823.711.1822.350.750.0000.000.19
*261094.933.5367.060.532.1434.291.00
*29602.710.0000.000.242.1434.290.65
*30361.630.5911.181.002.1434.290.22
*311426.422.3544.710.654.2968.570.65
*321587.152.9455.880.752.1434.290.48
*33221.000.0000.000.750.7111.430.75
*682079.368.821315.290.105.71811.430.75
*7420.092.3544.712 × 10-52.1434.291 × 10-9
HLA-Cw
*01958.953.5367.060.652.8245.630.48
*0212111.394.7178.240.482.1134.230.09
*0339337.0113.532225.880.0524.653143.660.32
*0418417.336.471112.940.379.151216.901.00
*0517116.104.7189.410.146.34912.680.53
*0614914.034.7189.410.296.34912.681.00
*0761157.5354.127183.534 × 10-635.924056.341.00
*08302.822.3533.531.002.1134.230.75
*12716.691.7633.530.371.4122.820.29
*14232.171.7633.530.651.4122.821.00
*15545.081.1822.350.404.2368.450.34
*16323.010.5911.180.531.4122.820.75
*1780.750.5911.181.002.1134.230.03
HLA-DRB1
*0145920.832.9155.811 × 10-48.451216.900.53
*0353124.0941.286879.072 × 10-2916.902230.990.24
*0476534.718.141416.286 × 10-416.202129.580.44
*0734015.433.4966.980.059.861419.720.40
*082119.575.811011.630.6510.561419.720.01
*09622.810.0000.000.221.4122.820.75
*10391.770.5811.161.000.0000.000.53
*111034.676.981213.959 × 10-43.5257.040.53
*12904.081.7433.491.002.1134.230.75
*1358126.3610.471618.600.149.861318.310.17
*141135.130.5811.160.163.5257.040.65
*1564829.4016.862933.720.4817.612230.991.00
*16291.321.1622.330.750.0000.000.65

Four alleles were significantly associated with CHB in a family-based analysis: HLA-Cw*05 [< 0.05, OR = 3 (0.97–9.30)], HLA-Cw*06 (< 0.03, OR = 0.22 (0.05–1.03)], HLA-DRB1*04 (< 0.03, OR = 2.37 (1.06–5.32)] and HLA-DRB1*13 [< 0.04, OR = 0.41 (0.17–0.99)] (Table 2 and Table S4 for allele frequencies in CHB index cases). Notably, odds ratio calculations with the Unphased software are based on risk allele frequencies in relation to all other allele frequencies as a reference, whilst P-values represent deviation from 50% transmission. None of the HLA-A alleles were significantly associated with CHB. HLA-DRB1*04 had the highest level of significance amongst the associated alleles. The robustness of association was further supported by a relatively high-risk allele frequency (0.269) in the study population.

Table 2. HLA-A, HLA-Cw and HLA-DRB1 associations with CHB in a family-based analysisa
HLA-AP-valueOR, 95% CIHLA-CwP-valueRAF (cases)OR, 95% CIHLA-DRB1P-valueRAF (cases)OR, 95% CI
  1. a

    HLA-A, HLA-Cw and HLA-DRB1 allele associations were calculated with the pedigree disequilibrium test (PDT), including 87 cases and 146 heterozygous parents. HLA alleles and P-values are listed for all tested alleles. Odds ratio calculations with the Unphased software are based on risk allele frequencies in relation to all other allele frequencies for HLA-A,-Cw and –DR B1, respectively.

  2. Alleles with < 0.05 are depicted in bold, and information on RAF (risk allele frequency) amongst cases, OR (odds ratio), and 95% CI (confidence interval) is included.

*010.89 *010.32  *010.23  
*020.45 *020.25  *030.55  
*030.25 *031.00   *04 0.03 0.159 2.37 (1.06–5.32)
*110.59 *040.09  *070.09  
*230.16  *05 0.05 0.094 3.00 (0.97–9.30) *080.65  
*240.64  *06 0.03 0.022 0.22 (0.05–1.03) *090.16  
*250.32 *070.81  *100.32  
*260.71 *081.00  *110.59  
*290.08 *120.26  *120.41  
*300.32 *141.00   *13 0.04 0.073 0.41 (0.17–0.99)
*310.71 *150.76  *140.74  
*320.71 *160.56  *150.88  
*360.32 *171.00  *161.00  
*680.80         
*741.00         
           

As expected, given these associations, allele transmission of HLA-DRB1*04, -DRB1*13, -Cw*05 and -Cw*06 alleles to CHB-affected individuals showed skewed frequencies, in comparison with the normal allele transmission frequency of 50% (Fig. 3). The transmission frequencies of HLA-Cw*05 (72%) and HLA-DRB1*04 (71%) were increased, whilst those of HLA-Cw*06 and DRB1*13 were decreased relative to index cases than suggested by normal transmission frequencies. Allele transmission frequency of the four CHB-associated HLA alleles was not significantly skewed in healthy siblings (Fig. 3 and Table S5).

image

Figure 3. Allele transmission frequencies of CHB-associated HLA alleles to siblings with and without CHB. Allele transmission frequencies were calculated from heterozygous parents. Percentages of allele transmission frequencies were plotted for CHB-associated HLA alleles to siblings with and without CHB. Dashed lines indicate the percentage of normal allele transmission frequency of 50%.

Download figure to PowerPoint

Interestingly, we observed a marked increase in paternal transmission of DRB1*04 (77% of alleles were transmitted, = 0.018) (Table 3) to CHB index cases, but not maternal DRB1*04 transmission (60% of alleles were transmitted, nonsignificant), suggesting a paternally regulated effect in addition to transmission of the DRB1*04 allele. Based on these results, we conclude that transmission of paternal HLA-DRB1*04 alleles to the offspring is a dominant factor in conferring susceptibility to CHB development. Moreover, our data suggest susceptibility to CHB development in the presence of HLA-Cw*05, whilst transmission of HLA-Cw*06 or DRB1*13 appears to have a protective effect.

Table 3. Parent-of-origin analysis of CHB-associated HLA-allelesa
HLASiblings with CHBSiblings without CHB
Paternal transmission frequencyP-valueMaternal transmissionP-valuePaternal transmission frequencyP-valueMaternal transmission frequencyP-value
  1. a

    Parental transmission frequencies of CHB-associated HLA alleles to siblings with and without CHB were calculated using the parent-of-origin analysis in PLINK, including 87 mothers, 71 fathers, 88 cases and 95 unaffected siblings. Associated HLA alleles, paternal and maternal transmission frequencies and P-values are listed. Significant P-values < 0.05 are highlighted in bold.

DRB1*040.77 0.018 0.600.5270.410.5290.550.739
DRB1*130.250.0830.330.2480.390.4220.79 0.043
Cw50.800.0570.620.4790.501.0000.360.363
Cw60.310.2880.100.0731.000.3130.00 0.025

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. Author contributions
  10. References
  11. Supporting Information

Maternal Ro/SSA autoantibodies have been identified as the major risk factor for CHB to date [40]. However, the recurrence risk for CHB in a following pregnancy is only 12–20%, despite persisting maternal autoantibodies [17], suggesting the existence of additional risk factors that determine foetal susceptibility for CHB. The MHC locus has a significant impact on autoimmune diseases [41]. Accordingly, we addressed whether foetal MHC genes contribute to susceptibility in Ro/SSA autoantibody-mediated CHB.

In a case–control set-up, we initially identified 15 SNP markers within the MHC region that were significantly associated with CHB. Seven of these markers (rs558702, rs3131379, rs2187668, rs3117582, rs7775397, rs3130544, rs3134942) have been shown to associate with CHB in a case–control analysis [42], supporting the hypothesis that the MHC locus plays a significant role in CHB. However, both these case–control studies were limited in that they did not distinguish between CHB-specific disease traits within the MHC region and inherited maternal traits. Thus, the results may reflect the maternal autoimmune disease MHC associations, rather than true foetal CHB associations. With the aid of a family-based association analysis of our cohort containing mothers, fathers and unaffected siblings, we successfully segregated the two disease traits. Investigation of genetic polymorphisms in the MHC locus led to the identification of several SNP markers in this region associated with CHB. Amongst the SNP markers, we observed LD with HLA-Cw and -DRB1 gene loci. HLA typing of our cohort to identify specific HLA alleles revealed a significant and robust association of HLA-DRB1*04 and HLA-DRB1*13 with CHB. We additionally observed significant associations of HLA-Cw*05 and -Cw*06 with CHB. The discrepancy between the level of significance and confidence intervals for the latter associations is influenced by the fact that they are based on different calculation methods built in to the analysis software. Amongst the associated alleles, HLA-DRB1*04 and HLA-Cw*05 mediated susceptibility, whilst HLA-DRB1*13 and HLA-Cw*06 appeared protective.

Several case reports in the literature have investigated the HLA allele constitution of CHB-affected individuals [13, 43-46]. However, these studies most frequently fail to achieve statistical significance of association owing to small sample size, which is attributed to the rarity of CHB. One study on a Finnish cohort of 24 children with CHB and their mothers showed increased transmission of HLA-Cw*03 to CHB-affected individuals [47]. Consistent with the findings of Sirén et al.[47], we showed that the HLA-Cw gene locus is associated with CHB, whilst two different HLA-Cw alleles conveyed susceptibility in the two cohorts. The differences in HLA alleles and susceptibility to disease may be explained by the structural characteristics of certain HLA alleles that result in presentation of similar peptide antigens, thus eliciting the same immune activation mechanism. Alternative explanations for the different results include the relatively low numbers of individuals or differences in LD between populations, assuming that the true susceptibility gene is not HLA-Cw but a gene in LD with this gene.

Imbalance of the foetal immune system drives the inflammatory process in the developing heart after maternal autoantibody exposure, with macrophages being the major cell type involved [48]. Although not fully mature, the foetal immune system is capable of response, and there is significant evidence that foetuses possess a broad set-up of functional immune cells able to mount innate as well as adaptive immune responses [49]. In this context, our findings that two HLA class II alleles are associated with CHB are of interest, supporting the idea that complex immune alterations in the monocytic compartment, possibly including peptide presentation by class II molecules, play a role in CHB pathogenesis. Initial binding of anti-Ro antibodies to a heart muscle epitope and tissue damage may lead to a disease-promoting effect of DRB1*04 mechanistically related to preferential presentation of certain critical peptides of the heart muscle, triggering a T-cell-mediated inflammatory reaction with consequences of innate immunity reactions and fibrosis.

Interestingly, Liu et al. [39] demonstrated that MHC class II molecules are not limited to antigen presentation and adaptive immune responses, but also promote Toll-like receptor (TLR)-mediated innate immune responses. Together with data from Buyon et al.[50] showing that TLR signalling in macrophages is crucial for fibrosis and subsequent conduction impairment in the foetal heart, we speculate that HLA-DRB1*04 and TLRs interact to induce the fibrotic cascade, leading to calcification and conductive tissue disruption. We previously reported an association between the season of birth and CHB and demonstrated increased risk of giving birth to a child with CHB if the risk period during gestational week 18–24 falls in January–March, coinciding with low vitamin D levels [51]. At this time, the risk for seasonal infections is high. Taking the role of vitamin D in the immune response into account, one can speculate that carriers of specific HLA alleles cope differently with infections and that this may influence the risk of CHB during periods with low vitamin D levels. Interestingly, HLA-DRB1*04 has been shown to determine chronicity of inflammatory responses after infectious disease [52]. As a further explanation of CHB association with the HLA locus, association with DRB1*04 may not be related to the molecule itself, but to other immune-related genes in LD, such as TNF-alpha and components of the complement cascade, which are implicated in the pathogenesis of CHB [53, 54].

The most significantly associated susceptibility allele, HLA-DRB1*04, has been consistently reported for other autoimmune diseases, including rheumatoid arthritis [55-57]. Interestingly, in autoimmune mothers of children with CHB, there is a well-known strong association with HLA, but to different alleles, predominantly HLA-DRB1*03 [45, 58-60]. This expected association was also observed in our study. The frequency of maternal HLA-DRB1*11 was additionally increased in our Swedish cohort, compared to the general population. This allele was previously reported to be more frequent in mothers of CHB individuals in a Japanese cohort [38]. Thus, common shared maternal susceptibility alleles in the Caucasian population as well as a susceptibility allele shared across ethnic barriers may determine the foetal outcomes of CHB. Notably, however, transmission of these alleles is not associated with foetal disease outcome.

Only a few sporadic HLA types for fathers of children with CHB have been reported to date [45, 47, 61]. In the present study, we analysed the potential paternal genetic contribution to CHB for the first time. Our data showed that HLA allele frequencies of fathers are essentially similar to the general population, but, importantly, revealed a parent-of-origin effect on the foetal HLA-DRB1*04 association with CHB, as significantly increased paternal transmission of DRB1*04 was associated with CHB. Parent-of-origin influence has previously been demonstrated in the context of Type 1 diabetes [62], where paternal transmission of associated MHC alleles influences the risk of disease development. Based on these collective findings, we hypothesize that in addition to the presence of the DRB1*04 allele, potentially epigenetic mechanisms enhance the risk of CHB. Additionally, our observations are consistent with recent findings with an animal model, whereby CHB was associated with specific but distinct MHC alleles in mother and offspring and further influenced by epigenetic regulation [63].

Our results should facilitate the identification of couples at risk of giving birth to offspring with CHB and genotyping to identify risk genes of value in prioritizing mothers for monitoring during pregnancy. Limitations of our study include the relatively small number of individuals and families and lack of a replication cohort, which may be explained by the rarity of the condition.

In summary, HLA-DRB1*04 and HLA-DRB1*13 have been identified as novel foetal susceptibility alleles robustly associated with CHB. We further demonstrate a parent-of-origin effect with increased paternal transmission of the DRB1*04 susceptibility allele, providing preliminary evidence of paternal HLA influence on CHB outcomes.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. Author contributions
  10. References
  11. Supporting Information

We thank Ms Åse Elfving for excellent technical assistance. Grant support for this study was obtained from the Swedish Research Council, Torsten and Ragnar Söderberg Foundation, Göran Gustafsson Foundation, King Gustaf the V the 80-year foundation, Goljes Memory Foundation, Lars Hiertas Memory Foundation, Swedish Foundation for Strategic Research, Stockholm County Council, Heart-Lung Foundation, Karolinska Institute and the Swedish Rheumatism Association.

Author contributions

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. Author contributions
  10. References
  11. Supporting Information

TÖ, SS and MWH designed the study. SS, HE, AM, LA, LK, AH, TO, LP, FG, AJ, SES, IK and MWH characterized patients and contributed to patient material and/or data. TÖ and SM performed the experiments. SM, TÖ, BD, IK and MWH analysed experimental data. SM, IK and MWH wrote the manuscript.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. Author contributions
  10. References
  11. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Conflict of interest statement
  9. Author contributions
  10. References
  11. Supporting Information
FilenameFormatSizeDescription
joim12179-sup-0001-Tables.docWord document200K

Table S1. SNP markers on chromosome six which reach chromosome-wide significance level for associated with congenital heart block in case-control analysisd.

Table S2. SNP markers in the extended MHC region most significantly associated with congenital heart block in family-based analysise.

Table S3. Linkage disequilibrium analysis between the most significantly associated SNP markers and HLA-A, HLA-Cw and HLA-DRB1 gene locig.

Table S4. HLA-A, HLA-Cw and HLA-DRB1 carrier frequencies among CHB index cases in comparison to the general populationh.

Table S5. HLA-A, HLA-Cw and HLA-DRB1 carrier frequencies among healthy siblings of CHB index cases in comparison to the general populationi.

Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.