Dimitri Monos

A genome-wide association study identifies KIAA0350 as a type 1 diabetes gene.

Type 1 diabetes (T1D) in children results from autoimmune destruction of pancreatic beta cells, leading to insufficient production of insulin. A number of genetic determinants of T1D have already been established through candidate gene studies, primarily within the major histocompatibility complex but also within other loci. To identify new genetic factors that increase the risk of T1D, we performed a genome-wide association study in a large paediatric cohort of European descent. In addition to confirming previously identified loci, we found that T1D was significantly associated with variation within a 233-kb linkage disequilibrium block on chromosome 16p13. This region contains KIAA0350, the gene product of which is predicted to be a sugar-binding, C-type lectin. Three common non-coding variants of the gene (rs2903692, rs725613 and rs17673553) in strong linkage disequilibrium reached genome-wide significance for association with T1D. A subsequent transmission disequilibrium test replication study in an independent cohort confirmed the association. These results indicate that KIAA0350 might be involved in the pathogenesis of T1D and demonstrate the utility of the genome-wide association approach in the identification of previously unsuspected genetic determinants of complex traits.

Common variants at five new loci associated with early-onset inflammatory bowel disease

The inflammatory bowel diseases (IBD) Crohns disease and ulcerative colitis are common causes of morbidity in children and young adults in the western world. Here we report the results of a genome-wide association study in early-onset IBD involving 3,426 affected individuals and 11,963 genetically matched controls recruited through international collaborations in Europe and North America, thereby extending the results from a previous study of 1,011 individuals with early-onset IBD. We have identified five new regions associated with early-onset IBD susceptibility, including 16p11 near the cytokine gene IL27 (rs8049439, P = 2.41 × 10−9), 22q12 (rs2412973, P = 1.55 × 10−9), 10q22 (rs1250550, P = 5.63 × 10−9), 2q37 (rs4676410, P = 3.64 × 10−8) and 19q13.11 (rs10500264, P = 4.26 × 10−10). Our scan also detected associations at 23 of 32 loci previously implicated in adult-onset Crohns disease and at 8 of 17 loci implicated in adult-onset ulcerative colitis, highlighting the close pathogenetic relationship between early- and adult-onset IBD.

Loci on 20q13 and 21q22 are associated with pediatric-onset inflammatory bowel disease

Inflammatory bowel disease (IBD) is a common inflammatory disorder with complex etiology that involves both genetic and environmental triggers, including but not limited to defects in bacterial clearance, defective mucosal barrier and persistent dysregulation of the immune response to commensal intestinal bacteria. IBD is characterized by two distinct phenotypes: Crohns disease (CD) and ulcerative colitis (UC). Previously reported GWA studies have identified genetic variation accounting for a small portion of the overall genetic susceptibility to CD and an even smaller contribution to UC pathogenesis. We hypothesized that stratification of IBD by age of onset might identify additional genes associated with IBD. To that end, we carried out a GWA analysis in a cohort of 1,011 individuals with pediatric-onset IBD and 4,250 matched controls. We identified and replicated significantly associated, previously unreported loci on chromosomes 20q13 (rs2315008[T] and rs4809330[A]; P = 6.30 × 10−8 and 6.95 × 10−8, respectively; odds ratio (OR) = 0.74 for both) and 21q22 (rs2836878[A]; P = 6.01 × 10−8; OR = 0.73), located close to the TNFRSF6B and PSMG1 genes, respectively.

HLA-DRB1*1101: A Significant Risk Factor for Sarcoidosis in Blacks and Whites

Sarcoidosis is a granulomatous disorder of unknown etiology, associated with an accumulation of CD4+ T cells and a TH1 immune response. Since previous studies of HLA associations with sarcoidosis were limited by serologic or low-resolution molecular identification, we performed high-resolution typing for the HLA-DPB1, HLA-DQB1, HLA-DRB1, and HLA-DRB3 loci and the presence of the DRB4 or DRB5 locus, to define HLA class II associations with sarcoidosis. A Case Control Etiologic Study of Sarcoidosis (ACCESS) enrolled biopsy-confirmed cases (736 total) from 10 centers in the United States. Seven hundred six (706) controls were case matched for age, race, sex, and geographic area. We studied the first 474 ACCESS patients and case-matched controls. The HLA-DRB1 alleles were differentially distributed between cases and controls (P<.0001). The HLA-DRB1*1101 allele was associated (P<.01) with sarcoidosis in blacks and whites and had a population attributable risk of 16% in blacks and 9% in whites. HLA-DRB1-F(47) was the amino acid residue most associated with sarcoidosis and independently associated with sarcoidosis in whites. The HLA-DPB1 locus also contributed to susceptibility for sarcoidosis and, in contrast to chronic beryllium disease, a non-E(69)-containing allele, HLA-DPB1*0101, conveyed most of the risk. Although significant differences were observed in the distribution of HLA class II alleles between blacks and whites, only HLA-DRB1*1501 was differentially associated with sarcoidosis (P<.003). In addition to being susceptibility markers, HLA class II alleles may be markers for different phenotypes of sarcoidosis (DRB1*0401 for eye in blacks and whites, DRB3 for bone marrow in blacks, and DPB1*0101 for hypercalcemia in whites). These studies confirm a genetic predisposition for sarcoidosis and present evidence for the allelic variation at the HLA-DRB1 locus as a major contributor.

From Disease Association to Risk Assessment: An Optimistic View from Genome-Wide Association Studies on Type 1 Diabetes

Genome-wide association studies (GWAS) have been fruitful in identifying disease susceptibility loci for common and complex diseases. A remaining question is whether we can quantify individual disease risk based on genotype data, in order to facilitate personalized prevention and treatment for complex diseases. Previous studies have typically failed to achieve satisfactory performance, primarily due to the use of only a limited number of confirmed susceptibility loci. Here we propose that sophisticated machine-learning approaches with a large ensemble of markers may improve the performance of disease risk assessment. We applied a Support Vector Machine (SVM) algorithm on a GWAS dataset generated on the Affymetrix genotyping platform for type 1 diabetes (T1D) and optimized a risk assessment model with hundreds of markers. We subsequently tested this model on an independent Illumina-genotyped dataset with imputed genotypes (1,008 cases and 1,000 controls), as well as a separate Affymetrix-genotyped dataset (1,529 cases and 1,458 controls), resulting in area under ROC curve (AUC) of ∼0.84 in both datasets. In contrast, poor performance was achieved when limited to dozens of known susceptibility loci in the SVM model or logistic regression model. Our study suggests that improved disease risk assessment can be achieved by using algorithms that take into account interactions between a large ensemble of markers. We are optimistic that genotype-based disease risk assessment may be feasible for diseases where a notable proportion of the risk has already been captured by SNP arrays.

A Novel Susceptibility Locus for Type 1 Diabetes on Chr12q13 Identified by a Genome-Wide Association Study

OBJECTIVE—In stage 1 of our genome-wide association (GWA) study for type 1 diabetes, one locus at 16p13 was detected (P = 1.03 × 10−10) and confirmed in two additional cohorts. Here we describe the results of testing, in these additional cohorts, 23 loci that were next in rank of statistical significance. RESEARCH DESIGN AND METHODS—Two independent cohorts were studied. The Type 1 Diabetes Genetics Consortium replication cohort consisted of 549 families with at least one child diagnosed with diabetes (946 total affected) and DNA from both parents. The Canadian replication cohort consisted of 364 nuclear family trios with one type 1 diabetes–affected offspring and two parents (1,092 individuals). RESULTS—One locus at 12q13, with the highest statistical significance among the 23, was confirmed. It involves type 1 diabetes association with the minor allele of rs1701704 (P = 9.13 × 10−10, OR 1.25 [95% CI 1.12–1.40]). CONCLUSIONS—We have discovered a type 1 diabetes locus at 12q13 that is replicated in an independent cohort of type 1 diabetic patients and confers a type 1 diabetes risk comparable with that of the 16p13 locus we recently reported. These two loci are identical to two loci identified by the whole-genome association study of the Wellcome Trust Case-Control Consortium, a parallel independent discovery that adds further support to the validity of the GWA approach.

Comparative genetic analysis of inflammatory bowel disease and type 1 diabetes implicates multiple loci with opposite effects

Inflammatory bowel disease, including Crohns disease (CD) and ulcerative colitis (UC), and type 1 diabetes (T1D) are autoimmune diseases that may share common susceptibility pathways. We examined known susceptibility loci for these diseases in a cohort of 1689 CD cases, 777 UC cases, 989 T1D cases and 6197 shared control subjects of European ancestry, who were genotyped by the Illumina HumanHap550 SNP arrays. We identified multiple previously unreported or unconfirmed disease associations, including known CD loci (ICOSLG and TNFSF15) and T1D loci (TNFAIP3) that confer UC risk, known UC loci (HERC2 and IL26) that confer T1D risk and known UC loci (IL10 and CCNY) that confer CD risk. Additionally, we show that T1D risk alleles residing at the PTPN22, IL27, IL18RAP and IL10 loci protect against CD. Furthermore, the strongest risk alleles for T1D within the major histocompatibility complex (MHC) confer strong protection against CD and UC; however, given the multi-allelic nature of the MHC haplotypes, sequencing of the MHC locus will be required to interpret this observation. These results extend our current knowledge on genetic variants that predispose to autoimmunity, and suggest that many loci involved in autoimmunity may be under a balancing selection due to antagonistic pleiotropic effect. Our analysis implies that variants with opposite effects on different diseases may facilitate the maintenance of common susceptibility alleles in human populations, making autoimmune diseases especially amenable to genetic dissection by genome-wide association studies.

Next-generation sequencing: the solution for high-resolution, unambiguous human leukocyte antigen typing

Human leukocyte antigen (HLA) typing has been a challenge for more than 50 years. Current methods (Sanger sequencing, sequence-specific primers [SSP], sequence-specific oligonucleotide probes [SSOP]) continue to generate ambiguities that are time-consuming and expensive to resolve. However, next-generation sequencing (NGS) overcomes ambiguity through the combination of clonal amplification, which provides on-phase sequence and a high level of parallelism, whereby millions of sequencing reads are produced enabling an expansion of the HLA regions sequenced. We explored HLA typing using NGS through a three-step process. First, HLA-A, -B, -C, -DRB1, and -DQB1 were amplified with long-range PCR. Subsequently, amplicons were sequenced using the 454 GS-FLX platform. Finally, sequencing data were analyzed with Assign-NG software. In a single experiment, four individual samples and two mixtures were sequenced producing >75 Mb of sequence from >300,000 individual sequence reads (average length, 244 b). The reads were aligned and covered 100% of the regions amplified. Allele assignment was 100% concordant with the known HLA alleles of our samples. Our results suggest this method can be a useful tool for complete genomic characterization of new HLA alleles and for completion of sequence for existing, partially sequenced alleles. NGS can provide complete, unambiguous, high-resolution HLA typing; however, further evaluation is needed to explore the feasibility of its routine use.

Follow-up analysis of genome-wide association data identifies novel loci for type 1 diabetes.

OBJECTIVE—Two recent genome-wide association (GWA) studies have revealed novel loci for type 1 diabetes, a common multifactorial disease with a strong genetic component. To fully utilize the GWA data that we had obtained by genotyping 563 type 1 diabetes probands and 1,146 control subjects, as well as 483 case subject–parent trios, using the Illumina HumanHap550 BeadChip, we designed a full stage 2 study to capture other possible association signals. RESEARCH DESIGN AND METHODS—From our existing datasets, we selected 982 markers with P < 0.05 in both GWA cohorts. Genotyping these in an independent set of 636 nuclear families with 974 affected offspring revealed 75 markers that also had P < 0.05 in this third cohort. Among these, six single nucleotide polymorphisms in five novel loci also had P < 0.05 in the Wellcome Trust Case-Control Consortium dataset and were further tested in 1,303 type 1 diabetes probands from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) plus 1,673 control subjects. RESULTS—Two markers (rs9976767 and rs3757247) remained significant after adjusting for the number of tests in this last cohort; they reside in UBASH3A (OR 1.16; combined P = 2.33 × 10−8) and BACH2 (1.13; combined P = 1.25 × 10−6). CONCLUSIONS—Evaluation of a large number of statistical GWA candidates in several independent cohorts has revealed additional loci that are associated with type 1 diabetes. The two genes at these respective loci, UBASH3A and BACH2, are both biologically relevant to autoimmunity.

A multi-site study using high-resolution HLA genotyping by next generation sequencing

The high degree of polymorphism at human leukocyte antigen (HLA) class I and class II loci makes high-resolution HLA typing challenging. Current typing methods, including Sanger sequencing, yield ambiguous typing results because of incomplete genomic coverage and inability to set phase for HLA allele determination. The 454 Life Sciences Genome Sequencer (GS FLX) next generation sequencing system coupled with conexio atf software can provide very high-resolution HLA genotyping. High-throughput genotyping can be achieved by use of primers with multiplex identifier (MID) tags to allow pooling of the amplicons generated from different individuals prior to sequencing. We have conducted a double-blind study in which eight laboratory sites performed amplicon sequencing using GS FLX standard chemistry and genotyped the same 20 samples for HLA-A, -B, -C, DPB1, DQA1, DQB1, DRB1, DRB3, DRB4, and DRB5 (DRB3/4/5) in a single sequencing run. The average sequence read length was 250 base pairs and the average number of sequence reads per amplicon was 672, providing confidence in the allele assignments. Of the 1280 genotypes considered, assignment was possible in 95% of the cases. Failure to assign genotypes was the result of researcher procedural error or the presence of a novel allele rather than a failure of sequencing technology. Concordance with known genotypes, in cases where assignment was possible, ranged from 95.3% to 99.4% for the eight sites, with overall concordance of 97.2%. We conclude that clonal pyrosequencing using the GS FLX platform and CONEXIO ATF software allows reliable identification of HLA genotypes at high resolution.