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1.  Common variants at five new loci associated with early-onset inflammatory bowel disease 
Nature Genetics  2009;41(12):1335-1340.
The inflammatory bowel diseases (IBD) Crohn’s 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 IBD1. 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 Crohn’s disease and at 8 of 17 loci implicated in adult-onset ulcerative colitis, highlighting the close pathogenetic relationship between early- and adult-onset IBD.
PMCID: PMC3267927  PMID: 19915574
2.  A Genome-Wide Meta-Analysis of Six Type 1 Diabetes Cohorts Identifies Multiple Associated Loci 
PLoS Genetics  2011;7(9):e1002293.
Diabetes impacts approximately 200 million people worldwide, of whom approximately 10% are affected by type 1 diabetes (T1D). The application of genome-wide association studies (GWAS) has robustly revealed dozens of genetic contributors to the pathogenesis of T1D, with the most recent meta-analysis identifying in excess of 40 loci. To identify additional genetic loci for T1D susceptibility, we examined associations in the largest meta-analysis to date between the disease and ∼2.54 million SNPs in a combined cohort of 9,934 cases and 16,956 controls. Targeted follow-up of 53 SNPs in 1,120 affected trios uncovered three new loci associated with T1D that reached genome-wide significance. The most significantly associated SNP (rs539514, P = 5.66×10−11) resides in an intronic region of the LMO7 (LIM domain only 7) gene on 13q22. The second most significantly associated SNP (rs478222, P = 3.50×10−9) resides in an intronic region of the EFR3B (protein EFR3 homolog B) gene on 2p23; however, the region of linkage disequilibrium is approximately 800 kb and harbors additional multiple genes, including NCOA1, C2orf79, CENPO, ADCY3, DNAJC27, POMC, and DNMT3A. The third most significantly associated SNP (rs924043, P = 8.06×10−9) lies in an intergenic region on 6q27, where the region of association is approximately 900 kb and harbors multiple genes including WDR27, C6orf120, PHF10, TCTE3, C6orf208, LOC154449, DLL1, FAM120B, PSMB1, TBP, and PCD2. These latest associated regions add to the growing repertoire of gene networks predisposing to T1D.
Author Summary
Despite the fact that there is clearly a large genetic component to type 1 diabetes (T1D), uncovering the genes contributing to this disease has proven challenging. However, in the past three years there has been relatively major progress in this regard, with advances in genetic screening technologies allowing investigators to scan the genome for variants conferring risk for disease without prior hypotheses. Such genome-wide association studies have revealed multiple regions of the genome to be robustly and consistently associated with T1D. More recent findings have been a consequence of combining of multiple datasets from independent investigators in meta-analyses, which have more power to pick up additional variants contributing to the trait. In the current study, we describe the largest meta-analysis of T1D genome-wide genotyped datasets to date, which combines six large studies. As a consequence, we have uncovered three new signals residing at the chromosomal locations 13q22, 2p23, and 6q27, which went on to be replicated in independent sample sets. These latest associated regions add to the growing repertoire of gene networks predisposing to T1D.
PMCID: PMC3183083  PMID: 21980299
3.  Comparative genetic analysis of inflammatory bowel disease and type 1 diabetes implicates multiple loci with opposite effects 
Human Molecular Genetics  2010;19(10):2059-2067.
Inflammatory bowel disease, including Crohn's 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.
PMCID: PMC2860894  PMID: 20176734
4.  Microtubule Actin Crosslinking Factor 1 Regulates the Balbiani Body and Animal-Vegetal Polarity of the Zebrafish Oocyte 
PLoS Genetics  2010;6(8):e1001073.
Although of fundamental importance in developmental biology, the genetic basis for the symmetry breaking events that polarize the vertebrate oocyte and egg are largely unknown. In vertebrates, the first morphological asymmetry in the oocyte is the Balbiani body, a highly conserved, transient structure found in vertebrates and invertebrates including Drosophila, Xenopus, human, and mouse. We report the identification of the zebrafish magellan (mgn) mutant, which exhibits a novel enlarged Balbiani body phenotype and a disruption of oocyte polarity. To determine the molecular identity of the mgn gene, we positionally cloned the gene, employing a novel DNA capture method to target region-specific genomic DNA of 600 kb for massively parallel sequencing. Using this technique, we were able to enrich for the genomic region linked to our mutation within one week and then identify the mutation in mgn using massively parallel sequencing. This is one of the first successful uses of genomic DNA enrichment combined with massively parallel sequencing to determine the molecular identity of a gene associated with a mutant phenotype. We anticipate that the combination of these technologies will have wide applicability for the efficient identification of mutant genes in all organisms. We identified the mutation in mgn as a deletion in the coding sequence of the zebrafish microtubule actin crosslinking factor 1 (macf1) gene. macf1 is a member of the highly conserved spectraplakin family of cytoskeletal linker proteins, which play diverse roles in polarized cells such as neurons, muscle cells, and epithelial cells. In mgn mutants, the oocyte nucleus is mislocalized; and the Balbiani body, localized mRNAs, and organelles are absent from the periphery of the oocyte, consistent with a function for macf1 in nuclear anchoring and cortical localization. These data provide the first evidence for a role for spectraplakins in polarization of the vertebrate oocyte and egg.
Author Summary
How the axes of the embryo are established is an important question in developmental biology. In many organisms, the axes of the embryo are established during oogenesis through the generation of a polarized egg. Very little is known regarding the mechanisms of polarity establishment and maintenance in vertebrate oocytes and eggs. We have identified a zebrafish mutant called magellan, which displays a defect in egg polarity. The gene disrupted in the magellan mutant encodes the cytoskeletal linker protein microtubule actin crosslinking factor 1 (macf1). In vertebrates, it can take years to identify the molecular nature of a mutation. We used a new technique to identify the magellan mutation, which allowed us to rapidly isolate genomic DNA linked to the mutation and sequence it. Our results describe an important new function for macf1 in polarizing the oocyte and egg and demonstrate the feasibility of this new technique for the efficient identification of mutations.
PMCID: PMC2924321  PMID: 20808893
6.  Follow-Up Analysis of Genome-Wide Association Data Identifies Novel Loci for Type 1 Diabetes 
Diabetes  2009;58(1):290-295.
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.
PMCID: PMC2606889  PMID: 18840781
7.  Loci on 20q13 and 21q22 are associated with pediatric-onset inflammatory bowel disease 
Nature genetics  2008;40(10):1211-1215.
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: Crohn’s 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.
PMCID: PMC2770437  PMID: 18758464
8.  From Disease Association to Risk Assessment: An Optimistic View from Genome-Wide Association Studies on Type 1 Diabetes 
PLoS Genetics  2009;5(10):e1000678.
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.
Author Summary
An often touted utility of genome-wide association studies (GWAS) is that the resulting discoveries can facilitate implementation of personalized medicine, in which preventive and therapeutic interventions for complex diseases can be tailored to individual genetic profiles. However, recent studies using whole-genome SNP genotype data for disease risk assessment have generally failed to achieve satisfactory results, leading to a pessimistic view of the utility of genotype data for such purposes. Here we propose that sophisticated machine-learning approaches on a large ensemble of markers, which contain both confirmed and as yet unconfirmed disease susceptibility variants, may improve the performance of disease risk assessment. We tested an algorithm called Support Vector Machine (SVM) on three large-scale datasets for type 1 diabetes and demonstrated that risk assessment can be highly accurate for the disease. Our results suggest that individualized disease risk assessment using whole-genome data may be more successful for some diseases (such as T1D) than other diseases. However, the predictive accuracy will be dependent on the heritability of the disease under study, the proportion of the genetic risk that is known, and that the right set of markers and right algorithms are being used.
PMCID: PMC2748686  PMID: 19816555
9.  SNP-specific extraction of haplotype-resolved targeted genomic regions 
Nucleic Acids Research  2008;36(15):e94.
The availability of genotyping platforms for comprehensive genetic analysis of complex traits has resulted in a plethora of studies reporting the association of specific single-nucleotide polymorphisms (SNPs) with common diseases or drug responses. However, detailed genetic analysis of these associated regions that would correlate particular polymorphisms to phenotypes has lagged. This is primarily due to the lack of technologies that provide additional sequence information about genomic regions surrounding specific SNPs, preferably in haploid form. Enrichment methods for resequencing should have the specificity to provide DNA linked to SNPs of interest with sufficient quality to be used in a cost-effective and high-throughput manner. We describe a simple, automated method of targeting specific sequences of genomic DNA that can directly be used in downstream applications. The method isolates haploid chromosomal regions flanking targeted SNPs by hybridizing and enzymatically elongating oligonucleotides with biotinylated nucleotides based on their selective binding to unique sequence elements that differentiate one allele from any other differing sequence. The targeted genomic region is captured by streptavidin-coated magnetic particles and analyzed by standard genotyping, sequencing or microarray analysis. We applied this technology to determine contiguous molecular haplotypes across a ∼150 kb genomic region of the major histocompatibility complex.
PMCID: PMC2528194  PMID: 18611953

Results 1-9 (9)