Association of primary biliary cirrhosis with variants in the CLEC16A, SOCS1, SPIB and SIAE immunomodulatory genes

Abstract

We fine mapped two primary biliary cirrhosis (PBC) risk loci, CLEC16A (C-type lectin domain family 16 member A)-suppressor of cytokine signaling 1 (SOCS1) and Spi-B protein (SPIB) and sequenced a locus, sialic acid acetylesterase (SIAE), proposed to harbor autoimmunity-associated mutations. In all, 1450 PBC cases and 2957 healthy controls were genotyped for 84 single-nucleotide polymorphisms (SNPs) across the CLEC16A-SOCS1 and SPIB loci. All 10 exons of the SIAE gene were resequenced in 381 cases and point substitutions of unknown significance assayed for activity and secretion. Fine mapping identified 26 SNPs across the CLEC16A-SOCS1 and 11 SNPs across the SPIB locus with significant association to PBC, the strongest signals at the CLEC16A-SOCS1 locus emanating from a SOCS1 intergenic SNP (rs243325; P=9.91 × 10(-9)) and at the SPIB locus from a SPIB intronic SNP (rs34944112; P=3.65 × 10(-9)). Among the associated SNPs at the CLEC16A-SOCS1 locus, two within the CLEC16A gene as well as one SOCS1 SNP (rs243325) remained significant after conditional logistic regression and contributed independently to risk. Sequencing of the SIAE gene and functional assays of newly identified variants revealed six patients with functional non-synonymous SIAE mutations (Fisher's P=9 × 10(-4) vs controls) We demonstrate independent effects on risk of PBC for CLEC16A, SOCS1 and SPIB variants, while identifying functionally defective SIAE variants as potential factors in risk for PBC.

Figure 1

Association plots for the CLEC16A-SOCS1 locus. Strength of the associations and recombination rates estimated from HapMap data for genotyped SNPs are shown for the SOCS1 loci. Both current fine-mapping data (diamonds) and genome-wide association data from a prior study of a subset of this cohort (circles) are shown. The extent of linkage disequilibrium with the most significant polymorphisms is indicated by the size of each data point; larger data points indicate stronger linkage disequilibrium. Chromosomal positions for each gene region are indicated by the arrows, with the arrow direction representing the orientation of translation. Linkage disequilibrium was calculated using observed data in PLINK.

Figure 2

Association plots for the SPIB locus. Strength of the associations and recombination rates estimated from HapMap data for genotyped SNPs are shown for the SPIB locus. Both fine-mapping data from this study (diamonds) and genome-wide association data from a prior study of a subset of this cohort (circles) are shown. The extent of linkage disequilibrium with the most significant polymorphisms is indicated by the size of each data point; larger data points indicate stronger linkage disequilibrium. Gene positions for each gene region are indicated by the arrows, with the arrow direction representing the orientation of translation. Linkage disequilibrium was calculated using observed data in PLINK.

Figure 3

Functional analysis of newly identified SIAE variants. SIAE cDNAs encoding Flag-tagged versions of wild-type SIAE, a catalytically inert SIAE mutation (S127A) and three SIAE variants of unknown functional significance (F199C, P356L and Q382R) were expressed in 293 cells, the cell lysates and culture supernatants harvested 48 h later and immunoprecipitated with anti-Flag antibody (‘control’ refers to untransfected cells). Immunoprecipitates were split into two equivalent aliquots with one used in immunoblotting to quantitate SIAE levels and the second used to assay for esterase activity on a fluorogenic substrate. Anti-Flag antibody immunoblotting analysis of cell lysates and supernatants from 293 transfected cells is shown in the upper panel. Bottom left panel shows esterase activity of each SIAE species normalized for lysate SIAE protein levels and bottom right panel shows ratios of SIAE levels in culture supernatant relative to lysate. Each variant was tested three times and the data are shown as mean±s.e.m.