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Common variants at PVT1, ATG13–AMBRA1, AHI1 and CLEC16A are associated with selective IgA deficiency

Nature Genetics volume 48, pages 1425–1429 (2016)Cite this article

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Abstract

Selective immunoglobulin A deficiency (IgAD) is the most common primary immunodeficiency in Europeans. Our genome-wide association study (GWAS) meta-analysis of 1,635 patients with IgAD and 4,852 controls identified four new significant (P < 5 × 10−8) loci and association with a rare IFIH1 variant (p.Ile923Val). Peak new variants (PVT1, P = 4.3 × 10−11; ATG13–AMBRA1, P = 6.7 × 10−10; AHI1, P = 8.4 × 10−10; CLEC16A, P = 1.4 × 10−9) overlapped with autoimmune markers (3/4) and correlated with 21 putative regulatory variants, including expression quantitative trait loci (eQTLs) for AHI1 and DEXI and DNase hypersensitivity sites in FOXP3+ regulatory T cells. Pathway analysis of the meta-analysis results showed striking association with the KEGG pathway for IgA production (pathway P < 0.0001), with 22 of the 30 annotated pathway genes containing at least one variant with P ≤ 0.05 in the IgAD meta-analysis. These data suggest that a complex network of genetic effects, including genes known to influence the biology of IgA production, contributes to IgAD.

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Figure 1: Genome-wide significant loci in the IgAD meta-analysis.
Figure 2: KEGG pathway for IgA production associated with IgAD.

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Acknowledgements

We thank the individuals who participated in this study as case and control study subjects. We thank B. Yaspan, J. Kim, J. Sitrin and T. Hung for insightful discussion, J. Tom and O. Mayba for helpful feedback on a manuscript draft, and A. Bruce for sharing her graphical expertise. Genentech funded the current GWAS. A. Lee and P. Gregersen performed sample genotyping at the Laboratory of Genomics and Human Genetics at the Feinstein Institute for Medical Research. These studies were supported by the US National Institutes of Health (U19AI067152 and AR043274), the Swedish Research Council, the European Research Council (242551-ImmunoSwitch), EURO-PADnet grant 201549, CETOCOEN PLUS and the Fondazione C. Golgi, Brescia, Italy. Financial support was also provided through the regional agreement on medical training and clinical research (ALF) between the Stockholm County Council and Karolinska Institutet. Population allele and genotype frequencies were obtained from a data source funded by the Nordic Center of Excellence in Disease Genetics based on regional samples from Finland and Sweden. The Helsinki 4 study was supported by the Yale Center for Human Genetics and Genomics and the Yale Program on Neurogenetics and by US National Institutes of Health grants R01NS057756 and U24NS051869.

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Authors and Affiliations

  1. Department of Human Genetics, Genentech, Inc., South San Francisco, California, USA

    Paola G Bronson, Diana Chang, Ward Ortmann, Robert R Graham & Timothy W Behrens

  2. Department of Bioinformatics and Computational Biology, Genentech, Inc., South San Francisco, California, USA

    Tushar Bhangale

  3. Department of Biochemistry, School of Medicine, University of California, Davis, Davis, California, USA

    Michael F Seldin

  4. Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research, Cambridge, UK

    Ricardo C Ferreira

  5. Department of Immunology, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, IdISSC, Madrid, Spain

    Elena Urcelay

  6. Department of Immunology, Hospital San Pedro de Alcántara, Cáceres, Spain

    Luis Fernández Pereira

  7. Instituto de Parasitología y Biomedicina López-Neyra, CSIC, Granada, Spain

    Javier Martin

  8. Department of Clinical and Experimental Sciences, Pediatrics Clinic, University of Brescia, Spedali Civili di Brescia, Brescia, Italy

    Alessandro Plebani & Vassilios Lougaris

  9. Department of Clinical and Experimental Sciences, Institute for Molecular Medicine, A. Nocivelli, University of Brescia, Spedali Civili di Brescia, Brescia, Italy

    Alessandro Plebani & Vassilios Lougaris

  10. Department of Infectious Diseases, University of Gothenburg, Gothenburg, Sweden

    Vanda Friman

  11. Molecular Genetics Laboratory, Centre for Cardiovascular Surgery and Transplantation, Brno, Czech Republic

    Tomáš Freiberger

  12. Central European Institute of Technology, Masaryk University, Brno, Czech Republic

    Tomáš Freiberger

  13. Department of Clinical Immunology and Allergy, Faculty of Medicine, Masaryk University, St. Anne's University Hospital, Brno, Czech Republic

    Jiri Litzman & Vojtech Thon

  14. Research Centre for Toxic Compounds in the Environment, Faculty of Science, Masaryk University, Brno, Czech Republic

    Vojtech Thon

  15. Division of Clinical Immunology and Transfusion Medicine, Karolinska Institutet, Stockholm, Sweden

    Qiang Pan-Hammarström & Lennart Hammarström

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  1. Paola G Bronson
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Contributions

P.G.B. and D.C. carried out the analyses for this study. P.G.B., L.H., T.W.B., R.R.G. and T.B. conceived and directed this study. L.H., Q.P.-H., A.P., V.L., T.F., J.L., E.U., L.F.P., V.F. and V.T. performed subject diagnosis, coordinated the enrollment of subjects and provided access to genotyping data sets. M.F.S. and J.M. provided access to genotypes for healthy controls. M.F.S. provided guidance for addressing population structure due to ancestry. M.F.S., Q.P.-H., R.C.F., T.B., R.R.G. and W.O. contributed to data access and analysis. P.G.B., T.W.B., L.H. and R.R.G. wrote the manuscript with collaboration from coauthors. All authors discussed the results and commented on the manuscript.

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Correspondence to Paola G Bronson or Lennart Hammarström.

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Integrated supplementary information

Supplementary Figure 1 Association plot for the significant (P < 5 × 10−8) IgAD GWAS locus at HLA-DQ.

rs116041786 hg19 has been renamed as rs9272226 in newer builds. The regional association plot displays P values from a genome-wide meta-analysis of ~9.5 million variants in 1,635 patients with IgAD and 4,852 controls. Each dot represents a P value for a genotyped or imputed SNP, where the highest dot has the smallest P value and is labeled with the SNP name; the color of the other dots represents the level of linkage disequilibrium (r2) with the peak SNP. The lines at the top of the plot represent the location and number of directly genotyped SNPs in each cohort.

Supplementary Figure 2 Association plot for the significant (P < 5 × 10−8) IgAD GWAS locus at IFIH1.

The regional association plot displays P values from a genome-wide meta-analysis of ~9.5 million variants in 1,635 patients with IgAD and 4,852 controls. Each dot represents a P value for a genotyped or imputed SNP, where the highest dot has the smallest P value and is labeled with the SNP name; the color of the other dots represents the level of linkage disequilibrium (r2) with the peak SNP. The lines at the top of the plot represent the location and number of directly genotyped SNPs in each cohort.

Supplementary Figure 3 Association plot for the significant (P < 5 × 10−8) IgAD GWAS locus at PVT1.

The regional association plot displays P values from a genome-wide meta-analysis of ~9.5 million variants in 1,635 patients with IgAD and 4,852 controls. Each dot represents a P value for a genotyped or imputed SNP, where the highest dot has the smallest P value and is labeled with the SNP name; the color of the other dots represents the level of linkage disequilibrium (r2) with the peak SNP. The lines at the top of the plot represent the location and number of directly genotyped SNPs in each cohort.

Supplementary Figure 4 Association plot for the significant (P < 5 × 10−8) IgAD GWAS locus at ATG13–AMBRA1.

The regional association plot displays P values from a genome-wide meta-analysis of ~9.5 million variants in 1,635 patients with IgAD and 4,852 controls. Each dot represents a P value for a genotyped or imputed SNP, where the highest dot has the smallest P value and is labeled with the SNP name; the color of the other dots represents the level of linkage disequilibrium (r2) with the peak SNP. The lines at the top of the plot represent the location and number of directly genotyped SNPs in each cohort.

Supplementary Figure 5 Association plots for the significant (P < 5 × 10−8) IgAD GWAS locus at AHI1.

The regional association plot displays P values from a genome-wide meta-analysis of ~9.5 million variants in 1,635 patients with IgAD and 4,852 controls. Each dot represents a P value for a genotyped or imputed SNP, where the highest dot has the smallest P value and is labeled with the SNP name; the color of the other dots represents the level of linkage disequilibrium (r2) with the peak SNP. The lines at the top of the plot represent the location and number of directly genotyped SNPs in each cohort.

Supplementary Figure 6 Association plot for the significant (P < 5 × 10−8) IgAD GWAS locus at CLEC16A.

The regional association plot displays P values from a genome-wide meta-analysis of ~9.5 million variants in 1,635 patients with IgAD and 4,852 controls. Each dot represents a P value for a genotyped or imputed SNP, where the highest dot has the smallest P value and is labeled with the SNP name; the color of the other dots represents the level of linkage disequilibrium (r2) with the peak SNP. The lines at the top of the plot represent the location and number of directly genotyped SNPs in each cohort.

Supplementary Figure 7 Association plot for additional IgAD GWAS loci with P < 1 × 10−5.

The Manhattan association plot displays P values from a genome-wide meta-analysis of ~9.5 million variants in 1,635 patients with IgAD and 4,852 controls. Each dot represents a P value for a genotyped or imputed SNP, where the highest dot has the smallest P value. Loci with P values that did not reach genome-wide significance but had P < 1 × 10−5 are labeled.

Supplementary Figure 8 GTEx box plot of AHI1 gene expression for the cis-eQTL rs2179781 in esophagus mucosa (n = 241).

The box plot displays gene expression levels for the novel IgAD locus AHI1 stratified by genotype at the rs2179781 cis-eQTL in esophagus mucosa, based on GTEx analysis release v6 (http://gtexportal.org/). The reference allele is A and was associated with reduced risk for IgAD (P = 8.8 × 10−10) and reduced AHI1 expression (P = 3 × 10−12). This eQTL had the strongest log Bayes factor (LBF) score (6.83) in the Bayesian statistical framework Sherlock. “Homo Ref” refers to the homozygous reference allele genotype, AA; “Het” refers to the heterozygous genotype, AC; and “Homo Alt” refers to the homozygous alternate allele genotype, CC.

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Bronson, P., Chang, D., Bhangale, T. et al. Common variants at PVT1, ATG13–AMBRA1, AHI1 and CLEC16A are associated with selective IgA deficiency. Nat Genet 48, 1425–1429 (2016). https://doi.org/10.1038/ng.3675

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