Faculty Bibliography

Recent work has shown that much of the missing heritability of complex traits can be resolved by estimates of heritability explained by all genotyped SNPs. However, it is currently unknown how much heritability is missing due to poor tagging or additional causal variants at known GWAS loci. Here, we use variance components to quantify the heritability explained by all SNPs at known GWAS loci in nine diseases from WTCCC1 and WTCCC2. After accounting for expectation, we observed all SNPs at known GWAS loci to explain 1.29 x more heritability than GWAS-associated SNPs on average (P=3.3 x 10(-)(5)). For some diseases, this increase was individually significant: 2.07 x for Multiple Sclerosis (MS) (P=6.5 x 10(-)(9)) and 1.48 x for Crohn's Disease (CD) (P = 1.3 x 10(-)(3)); all analyses of autoimmune diseases excluded the well-studied MHC region. Additionally, we found that GWAS loci from other related traits also explained significant heritability. The union of all autoimmune disease loci explained 7.15 x more MS heritability than known MS SNPs (P < 1.0 x 10(-)(1)(6) and 2.20 x more CD heritability than known CD SNPs (P = 6.1 x 10(-)(9)), with an analogous increase for all autoimmune diseases analyzed. We also observed significant increases in an analysis of > 20,000 Rheumatoid Arthritis (RA) samples typed on ImmunoChip, with 2.37 x more heritability from all SNPs at GWAS loci (P = 2.3 x 10(-)(6)) and 5.33 x more heritability from all autoimmune disease loci (P < 1 x 10(-)(1)(6) compared to known RA SNPs (including those identified in this cohort). Our methods adjust for LD between SNPs, which can bias standard estimates of heritability from SNPs even if all causal variants are typed. By comparing adjusted estimates, we hypothesize that the genome-wide distribution of causal variants is enriched for low-frequency alleles, but that causal variants at known GWAS loci are skewed towards common alleles. These findings have important ramifications for fine-mapping study design and our understanding of complex disease architecture.

We previously reported that the G allele of rs3853839 at 3'untranslated region (UTR) of Toll-like receptor 7 (TLR7) was associated with elevated transcript expression and increased risk for systemic lupus erythematosus (SLE) in 9,274 Eastern Asians [P = 6.5x10(-10), odds ratio (OR) (95%CI) = 1.27 (1.17-1.36)]. Here, we conducted trans-ancestral fine-mapping in 13,339 subjects including European Americans, African Americans, and Amerindian/Hispanics and confirmed rs3853839 as the only variant within the TLR7-TLR8 region exhibiting consistent and independent association with SLE (Pmeta = 7.5x10(-11), OR = 1.24 [1.18-1.34]). The risk G allele was associated with significantly increased levels of TLR7 mRNA and protein in peripheral blood mononuclear cells (PBMCs) and elevated luciferase activity of reporter gene in transfected cells. TLR7 3'UTR sequence bearing the non-risk C allele of rs3853839 matches a predicted binding site of microRNA-3148 (miR-3148), suggesting that this microRNA may regulate TLR7 expression. Indeed, miR-3148 levels were inversely correlated with TLR7 transcript levels in PBMCs from SLE patients and controls (R(2) = 0.255, P = 0.001). Overexpression of miR-3148 in HEK-293 cells led to significant dose-dependent decrease in luciferase activity for construct driven by TLR7 3'UTR segment bearing the C allele (P = 0.0003). Compared with the G-allele construct, the C-allele construct showed greater than two-fold reduction of luciferase activity in the presence of miR-3148. Reduced modulation by miR-3148 conferred slower degradation of the risk G-allele containing TLR7 transcripts, resulting in elevated levels of gene products. These data establish rs3853839 of TLR7 as a shared risk variant of SLE in 22,613 subjects of Asian, EA, AA, and Amerindian/Hispanic ancestries (Pmeta = 2.0x10(-19), OR = 1.25 [1.20-1.32]), which confers allelic effect on transcript turnover via differential binding to the epigenetic factor miR-3148.

To further characterize the genetic basis of primary biliary cirrhosis (PBC), we genotyped 2426 PBC patients and 5731 unaffected controls from three independent cohorts using a single nucleotide polymorphism (SNP) array (Immunochip) enriched for autoimmune disease risk loci. Meta-analysis of the genotype data sets identified a novel disease-associated locus near the TNFSF11 gene at 13q14, provided evidence for association at six additional immune-related loci not previously implicated in PBC and confirmed associations at 19 of 22 established risk loci. Results of conditional analyses also provided evidence for multiple independent association signals at four risk loci, with haplotype analyses suggesting independent SNP effects at the 2q32 and 16p13 loci, but complex haplotype driven effects at the 3q25 and 6p21 loci. By imputing classical HLA alleles from this data set, four class II alleles independently contributing to the association signal from this region were identified. Imputation of genotypes at the non-HLA loci also provided additional associations, but none with stronger effects than the genotyped variants. An epistatic interaction between the IL12RB2 risk locus at 1p31and the IRF5 risk locus at 7q32 was also identified and suggests a complementary effect of these loci in predisposing to disease. These data expand the repertoire of genes with potential roles in PBC pathogenesis that need to be explored by follow-up biological studies.

Using the Immunochip custom SNP array, which was designed for dense genotyping of 186 loci identified through genome-wide association studies (GWAS), we analyzed 11,475 individuals with rheumatoid arthritis (cases) of European ancestry and 15,870 controls for 129,464 markers. We combined these data in a meta-analysis with GWAS data from additional independent cases (n = 2,363) and controls (n = 17,872). We identified 14 new susceptibility loci, 9 of which were associated with rheumatoid arthritis overall and five of which were specifically associated with disease that was positive for anticitrullinated peptide antibodies, bringing the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci. Bioinformatic analyses generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations.

OBJECTIVE: The objective of this study is to comprehensively define the genetic basis of early onset myasthenia gravis (EOMG). METHODS: We have carried out a 2-stage genome-wide association study on a total of 649 North European EOMG patients. Cases were matched 1:4 with controls of European ancestry. We performed imputation and conditional analyses across the major histocompatibility complex, as well as in the top regions of association outside the human leukocyte antigen (HLA) region. RESULTS: We observed the strongest association in the HLA class I region at rs7750641 (p = 1.2 x 10(-92) ; odds ratio [OR], 6.25). By imputation and conditional analyses, HLA-B*08 proves to be the major associated allele (p = 2.87 x 10(-113) ; OR, 6.41). In addition to the expected association with PTPN22 (rs2476601; OR, 1.71; p = 8.2 x 10(-10) ), an imputed coding variant (rs2233290) at position 151 (Pro-->Ala) in the TNFAIP3-interacting protein 1, TNIP1, confers even stronger risk than PTPN22 (OR, 1.91; p = 3.2 x 10(-10) ). INTERPRETATION: The association at TNIP1 in EOMG implies disease mechanisms involving ubiquitin-dependent dysregulation of NF-kappaB signaling. The localization of the major HLA signal to the HLA-B*08 allele suggests that CD8(+) T cells may play a key role in disease initiation or pathogenesis.

We have performed a meta-analysis of the major-histocompatibility-complex (MHC) region in systemic lupus erythematosus (SLE) to determine the association with both SNPs and classical human-leukocyte-antigen (HLA) alleles. More specifically, we combined results from six studies and well-known out-of-study control data sets, providing us with 3,701 independent SLE cases and 12,110 independent controls of European ancestry. This study used genotypes for 7,199 SNPs within the MHC region and for classical HLA alleles (typed and imputed). Our results from conditional analysis and model choice with the use of the Bayesian information criterion show that the best model for SLE association includes both classical loci (HLA-DRB1( *)03:01, HLA-DRB1( *)08:01, and HLA-DQA1( *)01:02) and two SNPs, rs8192591 (in class III and upstream of NOTCH4) and rs2246618 (MICB in class I). Our approach was to perform a stepwise search from multiple baseline models deduced from a priori evidence on HLA-DRB1 lupus-associated alleles, a stepwise regression on SNPs alone, and a stepwise regression on HLA alleles. With this approach, we were able to identify a model that was an overwhelmingly better fit to the data than one identified by simple stepwise regression either on SNPs alone (Bayes factor [BF] > 50) or on classical HLA alleles alone (BF > 1,000).

The c-Src tyrosine kinase, Csk, physically interacts with the intracellular phosphatase Lyp (encoded by PTPN22) and can modify the activation state of downstream Src kinases, such as Lyn, in lymphocytes. We identified an association of CSK with systemic lupus erythematosus (SLE) and refined its location to the intronic polymorphism rs34933034 (odds ratio (OR) = 1.32; P = 1.04 x 10(-9)). The risk allele at this SNP is associated with increased CSK expression and augments inhibitory phosphorylation of Lyn. In carriers of the risk allele, there is increased B-cell receptor (BCR)-mediated activation of mature B cells, as well as higher concentrations of plasma immunoglobulin M (IgM), relative to individuals with the non-risk haplotype. Moreover, the fraction of transitional B cells is doubled in the cord blood of carriers of the risk allele, due to an expansion of late transitional cells in a stage targeted by selection mechanisms. This suggests that the Lyp-Csk complex increases susceptibility to lupus at multiple maturation and activation points in B cells.

OBJECTIVE: To examine the relationship of Porphyromonas gingivalis to the presence of autoantibodies in individuals at risk of rheumatoid arthritis (RA). METHODS: Study participants included the following: 1) a cohort enriched in subjects with HLA-DR4 and 2) subjects at risk of RA by virtue of having a first-degree relative with RA. None of the study subjects satisfied the American College of Rheumatology 1987 classification criteria for RA. Autoantibodies measured included anti-citrullinated protein antibody (ACPA; by second-generation anti-cyclic citrullinated peptide antibody enzyme-linked immunosorbent assay [ELISA]) and rheumatoid factor (RF; by nephelometry or ELISA for IgA, IgM, or IgG isotype). Individuals were considered autoantibody positive (n = 113) if they had >/=1 RA-related autoantibody; individuals were further categorized as high risk (n = 38) if they had ACPA or positive findings >/=2 assays for RF. Autoantibody-negative individuals (n = 171) served as a comparator group. Antibody to P gingivalis, P intermedia, and F nucleatum were measured. Associations of bacterial antibodies with group status were examined using logistic regression. RESULTS: Anti-P gingivalis concentrations were higher in high-risk (P = 0.011) and autoantibody positive group (P = 0.010) than in the autoantibody negative group. There were no group differences in anti-P intermedia or anti-F nucleatum concentrations. After multivariable adjustment, anti-P gingivalis concentrations (but not anti-P intermedia or anti-F nucleatum) were significantly associated with autoantibody-positive and high-risk status (P < 0.05). CONCLUSION: Immunity to P gingivalis, but not P intermedia or F nucleatum, is significantly associated with the presence of RA-related autoantibodies in individuals at risk of RA. These results support the hypothesis that infection with P gingivalis may play a central role in the early loss of tolerance to self antigens that occurs in the pathogenesis of RA.

OBJECTIVE: African Americans, East Asians, and Hispanics with systemic lupus erythematosus (SLE) are more likely to develop renal disease than are SLE patients of European descent. This study was undertaken to investigate whether European genetic ancestry protects against the development of lupus nephritis, with the aim of exploring the genetic and socioeconomic factors that might explain this effect. METHODS: This was a cross-sectional study of SLE patients from a multiethnic case collection. Participants were genotyped for 126 single-nucleotide polymorphisms (SNPs) informative for ancestry. A subset of participants was also genotyped for 80 SNPs in 14 candidate genes for renal disease in SLE. Logistic regression was used to test the association between European ancestry and renal disease. Analyses were adjusted for continental ancestries, socioeconomic status (SES), and candidate genes. RESULTS: Participants (n = 1,906) had, on average, 62.4% European, 15.8% African, 11.5% East Asian, 6.5% Amerindian, and 3.8% South Asian ancestry. Among the participants, 656 (34%) had renal disease. A 10% increase in the proportion of European ancestry estimated in each participant was associated with a 15% reduction in the odds of having renal disease, after adjustment for disease duration and sex (odds ratio 0.85, 95% confidence interval 0.82-0.87; P = 1.9 x 10(-30) ). Adjustment for other genetic ancestries, measures of SES, or SNPs in the genes most associated with renal disease (IRF5 [rs4728142], BLK [rs2736340], STAT4 [rs3024912], and HLA-DRB1*0301 and DRB1*1501) did not substantively alter this relationship. CONCLUSION: European ancestry is protective against the development of renal disease in SLE, an effect that is independent of other genetic ancestries, candidate risk alleles, and socioeconomic factors.

Genome wide association studies in human autoimmune disorders have provided a long list of alleles with rather modest degrees of risk. A large fraction of these associations are probably owing to either quantitative differences in gene expression or amino acid changes that regulate quantitative aspects of the immune response. While functional studies are still lacking for most of these associations, we present examples of autoimmune disease risk alleles that influence quantitative changes in lymphocyte activation, cytokine signaling and dendritic cell function. The analysis of immune quantitative traits associated with autoimmune loci is clearly going to be an important component of understanding the pathogenesis of autoimmunity. This will require both new and more efficient ways of characterizing the normal immune system, as well as large population resources in which genotype-phenotype correlations can be convincingly demonstrated. Future development of new therapies will depend on understanding the mechanistic underpinnings of immune regulation by these new risk loci.