Search

Since the publication of this article, the authors have found that the numbers of patients and controls were reversed. This study included 412 MS patients and 419 controls. This correction applies to the Abstract, the final paragraph of the Introduction, and the first paragraph of the Materials and Methods. This was entirely a reporting error and does not impact the Results or Conclusions.

We investigated association between HLA class I and class II alleles and haplotypes, and KIR loci and their HLA class I ligands, with multiple sclerosis (MS) in 412 European American MS patients and 419 ethnically matched controls, using next-generation sequencing. The DRB1*15:01~DQB1*06:02 haplotype was highly predisposing (odds ratio (OR) = 3.98; 95% confidence interval (CI) = 3-5.31; p-value (p) = 2.22E-16), as was DRB1*03:01~DQB1*02:01 (OR = 1.63; CI = 1.19-2.24; p = 1.41E-03). Hardy-Weinberg (HW) analysis in MS patients revealed a significant DRB1*03:01~DQB1*02:01 homozyote excess (15 observed; 8.6 expected; p = 0.016). The OR for this genotype (5.27; CI = 1.47-28.52; p = 0.0036) suggests a recessive MS risk model. Controls displayed no HW deviations. The C*03:04~B*40:01 haplotype (OR = 0.27; CI = 0.14-0.51; p = 6.76E-06) was highly protective for MS, especially in haplotypes with A*02:01 (OR = 0.15; CI = 0.04-0.45; p = 6.51E-05). By itself, A*02:01 is moderately protective, (OR = 0.69; CI = 0.54-0.87; p = 1.46E-03), and haplotypes of A*02:01 with the HLA-B Thr80 Bw4 variant (Bw4T) more so (OR = 0.53; CI = 0.35-0.78; p = 7.55E-04). Protective associations with the Bw4 KIR ligand resulted from linkage disequilibrium (LD) with DRB1*15:01, but the Bw4T variant was protective (OR = 0.64; CI = 0.49-0.82; p = 3.37-04) independent of LD with DRB1*15:01. The Bw4I variant was not associated with MS. Overall, we find specific class I HLA polymorphisms to be protective for MS, independent of the strong predisposition conferred by DRB1*15:01.

Objective: Genetic risk scores (GRS) have been developed that differentiate individuals with type 1 diabetes from those with other forms of diabetes and are starting to be used for population screening; however, most studies were conducted in European-ancestry populations. This study identifies novel genetic variants associated with type 1 diabetes risk in African-ancestry participants and develops an African-specific GRS., Research Design and Methods: We generated single nucleotide polymorphism (SNP) data with the ImmunoChip on 1,021 African-ancestry participants with type 1 diabetes and 2,928 control participants. HLA class I and class II alleles were imputed using SNP2HLA. Logistic regression models were used to identify genome-wide significant ( P < 5.0 × 10 -8 ) SNPs associated with type 1 diabetes in the African-ancestry samples and validate SNPs associated with risk in known European-ancestry loci ( P < 2.79 × 10 -5 )., Results: African-specific (HLA- DQA1 *03:01-HLA- DQB1 *02:01) and known European-ancestry HLA haplotypes (HLA- DRB1 *03:01-HLA- DQA1 *05:01-HLA- DQB1 *02:01, HLA- DRB1 *04:01-HLA- DQA1 *03:01-HLA- DQB1 *03:02) were significantly associated with type 1 diabetes risk. Among European-ancestry defined non-HLA risk loci, six risk loci were significantly associated with type 1 diabetes in subjects of African ancestry. An African-specific GRS provided strong prediction of type 1 diabetes risk (area under the curve 0.871), performing significantly better than a European-based GRS and two polygenic risk scores in independent discovery and validation cohorts., Conclusions: Genetic risk of type 1 diabetes includes ancestry-specific, disease-associated variants. The GRS developed here provides improved prediction of type 1 diabetes in African-ancestry subjects and a means to identify groups of individuals who would benefit from immune monitoring for early detection of islet autoimmunity., (© 2019 by the American Diabetes Association.)

The authors wish to make the following change to their paper [1][...].

The application of next generation sequencing (NGS) for the analysis of mitochondrial (mt) DNA, short tandem repeats (STRs), and single nucleotide polymorphism (SNPs) has demonstrated great promise for challenging forensic specimens, such as degraded, limited, and mixed samples. Target enrichment using probe capture rather than PCR amplification offers advantages for analysis of degraded DNA since two intact PCR primer sites in the template DNA molecule are not required. Furthermore, NGS software programs can help remove PCR duplicates to determine initial template copy numbers of a shotgun library. Moreover, the same shotgun library prepared from a limited DNA source can be enriched for mtDNA as well as nuclear markers by hybrid capture with the relevant probe panels. Here, we demonstrate the use of this strategy in the analysis of limited and mock degraded samples using our custom probe capture panels for massively parallel sequencing of the whole mtgenome and 426 SNP markers. We also applied the mtgenome capture panel in a mixed sample and analyzed using both phylogenetic and variant frequency based bioinformatics tools to resolve the minor and major contributors. Finally, the results obtained on individual telogen hairs demonstrate the potential of probe capture NGS analysis for both mtDNA and nuclear SNPs for challenging forensic specimens., Competing Interests: The authors declare no conflict of interest.

Massively parallel (next-generation) sequencing provides a powerful method to analyze DNA from many different sources, including degraded and trace samples. A common challenge, however, is that many forensic samples are often known or suspected mixtures of DNA from multiple individuals. Haploid lineage markers, such as mitochondrial (mt) DNA, are useful for analysis of mixtures because, unlike nuclear genetic markers, each individual contributes a single sequence to the mixture. Deconvolution of these mixtures into the constituent mitochondrial haplotypes is challenging as typical sequence read lengths are too short to reconstruct the distinct haplotypes completely. We present a powerful computational approach for determining the constituent haplotypes in massively parallel sequencing data from potentially mixed samples. At the heart of our approach is an expectation maximization based algorithm that co-estimates the overall mixture proportions and the source haplogroup for each read individually. This approach, implemented in the software package mixemt, correctly identifies haplogroups from mixed samples across a range of mixture proportions. Furthermore, our method can separate fragments in a mixed sample by the most likely originating contributor and generate reconstructions of the constituent haplotypes based on known patterns of mtDNA diversity., (Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.)

Compared to Sanger sequencing, next-generation sequencing offers advantages for high resolution HLA genotyping including increased throughput, lower cost, and reduced genotype ambiguity. Here we describe an enhancement of the Roche 454 GS GType HLA genotyping assay to provide very high resolution (VHR) typing, by the addition of 8 primer pairs to the original 14, to genotype 11 HLA loci. These additional amplicons help resolve common and well-documented alleles and exclude commonly found null alleles in genotype ambiguity strings. Simplification of workflow to reduce the initial preparation effort using early pooling of amplicons or the Fluidigm Access Array™ is also described. Performance of the VHR assay was evaluated on 28 well characterized cell lines using Conexio Assign MPS software which uses genomic, rather than cDNA, reference sequence. Concordance was 98.4%; 1.6% had no genotype assignment. Of concordant calls, 53% were unambiguous. To further assess the assay, 59 clinical samples were genotyped and results compared to unambiguous allele assignments obtained by prior sequence-based typing supplemented with SSO and/or SSP. Concordance was 98.7% with 58.2% as unambiguous calls; 1.3% could not be assigned. Our results show that the amplicon-based VHR assay is robust and can replace current Sanger methodology. Together with software enhancements, it has the potential to provide even higher resolution HLA typing., (Copyright © 2015. Published by Elsevier Inc.)

Background: The cobas HPV Test ("cobas"; Roche Molecular Systems) detects HPV16 and HPV18 individually, and a pool of 12 other high-risk (HR) HPV types. The test is approved for (i) atypical squamous cells of undetermined significance (ASC-US) triage to determine need for colposcopy, (ii) combined screening with cytology ("cotesting"), and (iii) primary HPV screening., Methods: To assess the possible value of HPV16/18 typing, >17,000 specimens from a longitudinal cohort study of initially HPV-positive women (HC2, Qiagen) were retested with cobas. To study accuracy, cobas genotyping results were compared with those of an established method, the Linear Array HPV Genotyping Test (LA, Roche Molecular Systems). Clinical value of the typing strategy was evaluated by linking the cobas results (supplemented by other available typing results) to 3-year cumulative risks of CIN3+., Results: Grouped hierarchically (HPV16, else HPV18, else other HR types, else negative), the κ statistic for agreement between cobas and LA was 0.86 [95% confidence interval (CI), 0.86-0.87]. In all three scenarios, HPV16-positive women were at much higher 3-year risk of CIN3+ than HPV16-negative women: women ages 21 and older with ASC-US (14.5%; 95% CI, 13.5%-15.5% vs. 3.5%; 95% CI, 3.3-3.6); women ages 30 years and older that were HPV-positive cytology-negative (10.3%; 95% CI, 9.6-11.1 vs. 2.3%; 95% CI, 2.2-2.4); and all women 25 years and older that were HPV-positive (18.5%; 95% CI, 17.8-19.2 vs. 4.3%; 95% CI, 4.2-4.4)., Conclusion: The cobas and LA results show excellent agreement. The data support HPV16 typing., Impact: HPV16 typing is useful in the management of HPV-positive/cytology-negative women in cotesting, of all HPV-positive women in primary HPV testing, and perhaps in the management of HPV-positive women with ASC-US. Cancer Epidemiol Biomarkers Prev; 24(9); 1304-10., (©2015 American Association for Cancer Research.)

Aim: To apply massively parallel and clonal sequencing (next generation sequencing or NGS) to the analysis of forensic mixed samples., Methods: A duplex polymerase chain reaction (PCR) assay targeting the mitochondrial DNA (mtDNA) hypervariable regions I/II (HVI/HVII) was developed for NGS analysis on the Roche 454 GS Junior instrument. Eight sets of multiplex identifier-tagged 454 fusion primers were used in a combinatorial approach for amplification and deep sequencing of up to 64 samples in parallel., Results: This assay was shown to be highly sensitive for sequencing limited DNA amounts (~100 mtDNA copies) and analyzing contrived and biological mixtures with low level variants (~1%) as well as "complex" mixtures (≥3 contributors). PCR artifact "hybrid" sequences generated by jumping PCR or template switching were observed at a low level (<2%) in the analysis of mixed samples but could be eliminated by reducing the PCR cycle number., Conclusion: This study demonstrates the power of NGS technologies targeting the mtDNA HVI/HVII regions for analysis of challenging forensic samples, such as mixtures and specimens with limited DNA.

NK cells are innate immune cells known for their cytolytic activities toward tumors and infections. They are capable of expressing diverse killer Ig-like receptors (KIRs), and KIRs are implicated in susceptibility to Crohn's disease (CD), a chronic intestinal inflammatory disease. However, the cellular mechanism of this genetic contribution is unknown. In this study, we show that the "licensing" of NK cells, determined by the presence of KIR2DL3 and homozygous HLA-C1 in host genome, results in their cytokine reprogramming, which permits them to promote CD4(+) T cell activation and Th17 differentiation ex vivo. Microfluidic analysis of thousands of NK single cells and bulk secretions established that licensed NK cells are more polarized to proinflammatory cytokine production than unlicensed NK cells, including production of IFN-γ, TNF-α, CCL-5, and MIP-1β. Cytokines produced by licensed NK augmented CD4(+) T cell proliferation and IL-17A/IL-22 production. Ab blocking indicated a primary role for IFN-γ, TNF-α, and IL-6 in the augmented T cell-proliferative response. In conclusion, NK licensing mediated by KIR2DL2/3 and HLA-C1 elicits a novel NK cytokine program that activates and induces proinflammatory CD4(+) T cells, thereby providing a potential biologic mechanism for KIR-associated susceptibility to CD and other chronic inflammatory diseases., (Copyright © 2014 by The American Association of Immunologists, Inc.)

The high-resolution human leukocyte antigen (HLA) genotyping assay that we developed using 454 sequencing and Conexio software uses generic polymerase chain reaction (PCR) primers for DRB exon 2. Occasionally, we observed low abundance DRB amplicon sequences that resulted from in vitro PCR 'crossing over' between DRB1 and DRB3/4/5. These hybrid sequences, revealed by the clonal sequencing property of the 454 system, were generally observed at a read depth of 5%-10% of the true alleles. They usually contained at least one mismatch with the IMGT/HLA database, and consequently, were easily recognizable and did not cause a problem for HLA genotyping. Sometimes, however, these artifactual sequences matched a rare allele and the automatic genotype assignment was incorrect. These observations raised two issues: (1) could PCR conditions be modified to reduce such artifacts? and (2) could some of the rare alleles listed in the IMGT/HLA database be artifacts rather than true alleles? Because PCR crossing over occurs during late cycles of PCR, we compared DRB genotypes resulting from 28 and (our standard) 35 cycles of PCR. For all 21 cell line DNAs amplified for 35 cycles, crossover products were detected. In 33% of the cases, these hybrid sequences corresponded to named alleles. With amplification for only 28 cycles, these artifactual sequences were not detectable. To investigate whether some rare alleles in the IMGT/HLA database might be due to PCR artifacts, we analyzed four samples obtained from the investigators who submitted the sequences. In three cases, the sequences were generated from true alleles. In one case, our 454 sequencing revealed an error in the previously submitted sequence., (© 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Objective: This study assessed the ability to distinguish between type 1 diabetes-affected individuals and their unaffected relatives using HLA and single nucleotide polymorphism (SNP) genotypes., Research Design and Methods: Eight models, ranging from only the high-risk DR3/DR4 genotype to all significantly associated HLA genotypes and two SNPs mapping to the cytotoxic T-cell-associated antigen-4 gene (CTLA4) and insulin (INS) genes, were fitted to high-resolution class I and class II HLA genotyping data for patients from the Type 1 Diabetes Genetics Consortium collection. Pairs of affected individuals and their unaffected siblings were divided into a "discovery" (n = 1,015 pairs) and a "validation" set (n = 318 pairs). The discriminating performance of various combinations of genetic information was estimated using receiver operating characteristic (ROC) curve analysis., Results: The use of only the presence or absence of the high-risk DR3/DR4 genotype achieved very modest discriminating ability, yielding an area under the curve (AUC) of 0.62 in the discovery set and 0.59 in the validation set. The full model-which included HLA information from the class II loci DPB1, DRB1, and DQB1; selected alleles from HLA class I loci A and B; and SNPs from the CTLA4 and INS genes-increased the AUC to 0.74 in the discovery set and to 0.71 in the validation set. A cost-effective alternative is proposed, using genotype information equivalent to typing four SNPs (DR3, DR4-DQB1*03:02, CTLA-4, and INS), which achieved an AUC of 0.72 in the discovery set and 0.69 in the validation set., Conclusions: Genotyping data sufficient to tag DR3, DR4-DQB1*03:02, CTLA4, and INS were shown to distinguish between subjects with type 1 diabetes and their unaffected siblings adequately to achieve clinically utility to identify children in multiplex families to be considered for early intervention.

The primary associations of the HLA class II genes, HLA-DRB1 and HLA-DQB1, and the class I genes, HLA-A and HLA-B, with type 1 diabetes (T1D) are well established. However, the role of polymorphism at the HLA-DRB3, HLA-DRB4, and HLA-DRB5 loci remains unclear. In two separate studies, one of 500 subjects and 500 control subjects and one of 366 DRB1*03:01-positive samples from selected multiplex T1D families, we used Roche 454 sequencing with Conexio Genomics ASSIGN ATF 454 HLA genotyping software analysis to analyze sequence variation at these three HLA-DRB loci. Association analyses were performed on the two HLA-DRB loci haplotypes (DRB1-DRB3, -DRB4, or -DRB5). Three common HLA-DRB3 alleles (*01:01, *02:02, *03:01) were observed. DRB1*03:01 haplotypes carrying DRB3*02:02 conferred a higher T1D risk than did DRB1*03:01 haplotypes carrying DRB3*01:01 in DRB1*03:01/*03:01 homozygotes with two DRB3*01:01 alleles (odds ratio [OR] 3.4 [95% CI 1.46-8.09]), compared with those carrying one or two DRB3*02:02 alleles (OR 25.5 [3.43-189.2]) (P = 0.033). For DRB1*03:01/*04:01 heterozygotes, however, the HLA-DRB3 allele did not significantly modify the T1D risk of the DRB1*03:01 haplotype (OR 7.7 for *02:02; 6.8 for *01:01). These observations were confirmed by sequence analysis of HLA-DRB3 exon 2 in a targeted replication study of 281 informative T1D family members and 86 affected family-based association control (AFBAC) haplotypes. The frequency of DRB3*02:02 was 42.9% in the DRB1*03:01/*03:01 patients and 27.6% in the DRB1*03:01/*04 (P = 0.005) compared with 22.6% in AFBAC DRB1*03:01 chromosomes (P = 0.001). Analysis of T1D-associated alleles at other HLA loci (HLA-A, HLA-B, and HLA-DPB1) on DRB1*03:01 haplotypes suggests that DRB3*02:02 on the DRB1*03:01 haplotype can contribute to T1D risk.

The human leukocyte antigen (HLA) class I and class II loci are the most polymorphic genes in the human genome; distinguishing the thousands of HLA alleles is challenging. Next generation sequencing of exonic amplicons with the 454 genome sequence (GS) FLX System and Conexio Assign ATF 454 software provides high resolution, high throughput HLA genotyping for eight class I and class II loci. HLA typing of potential donors for unrelated bone marrow donor registries typically uses a subset of these loci at high sample throughput and low cost per sample. The Fluidigm Access Array System enables the incorporation of 48 different multiplex identifiers (MIDs) corresponding to 48 genomic DNA samples with up to 48 different primer pairs in a microfluidic device generating 2304 parallel polymerase chain reactions (PCRs). Minimal volumes of reagents are used. During genomic PCR, in this 4-primer system, the outer set of primers containing the MID and the 454 adaptor sequences are incorporated into an amplicon generated by the inner HLA target-specific primers each containing a common sequence tag at the 5' end of the forward and reverse primers. Pools of the resulting amplicons are used for emulsion PCR and clonal sequencing on the 454 Life Sciences GS FLX System, followed by genotyping with Conexio software. We have genotyped 192 samples with 100% concordance to known genotypes using 8 primer pairs (covering exons 2 and 3 of HLA-A, B and C, and exon 2 of DRB1, 3/4/5 and DQB1) and 96 MIDs in a single GS FLX run. An average of 166 reads per amplicon was obtained. We have also genotyped 96 samples at high resolution (14 primer pairs covering exons 2, 3, and 4 of the class I loci and exons 2 of DRB1, 3/4/5, DQA1, DQB1, DPB1, and exon 3 of DQB1), recovering an average of 173 sequence reads per amplicon., (© 2013 John Wiley & Sons A/S.)

Human leucocyte antigen (HLA) genes play an important role in the success of organ transplantation and are associated with autoimmune and infectious diseases. Current DNA-based genotyping methods, including Sanger sequence-based typing (SSBT), have identified a high degree of polymorphism. This level of polymorphism makes high-resolution HLA genotyping challenging, resulting in ambiguous typing results due to an inability to resolve phase and/or defining polymorphisms lying outside the region amplified. Next-generation sequencing (NGS) may resolve the issue through the combination of clonal amplification, which provides phase information, and the ability to sequence larger regions of genes, including introns, without the additional effort or cost associated with current methods. The NGS HLA sequencing project of the 16IHIW aimed to discuss the different approaches to (i) template preparation including short- and long-range PCR amplicons, exome capture and whole genome; (ii) sequencing platforms, including GS 454 FLX, Ion Torrent PGM, Illumina MiSeq/HiSeq and Pacific Biosciences SMRT; (iii) data analysis, specifically allele-calling software. The pilot studies presented at the workshop demonstrated that although individual sequencers have very different performance characteristics, all produced sequence data suitable for the resolution of HLA genotyping ambiguities. The developments presented at this workshop clearly highlight the potential benefits of NGS in the HLA laboratory., (© 2012 Blackwell Publishing Ltd.)

Balancing selection has maintained human leukocyte antigen (HLA) allele diversity, but it is unclear whether this selection is symmetric (all heterozygotes are comparable and all homozygotes are comparable in terms of fitness) or asymmetric (distinct heterozygote genotypes display greater fitness than others). We tested the hypothesis that HLA is under asymmetric balancing selection in populations by estimating allelic branch lengths from genetic sequence data encoding peptide-binding domains. Significant deviations indicated changes in the ratio of terminal to internal branch lengths. Such deviations could arise even if no individual alleles present a strikingly altered branch length (e.g. if there is an overall distortion, with all or many terminal branches being longer than expected). DQ and DP loci were also analyzed as haplotypes. Using allele frequencies for 419 distinct populations in 10 geographical regions, we examined population differentiation in alleles within and between regions, and the relationship between allelic branch length and frequency. The strongest evidence for asymmetrical balancing selection was observed for HLA-DRB1, HLA-B and HLA-DPA1, with significant deviation (P ≤ 1.1 × 10(-4)) in about half of the populations. There were significant results at all loci except HLA-DQB1/DQA1. We observed moderate genetic variation within and between geographic regions, similar to the rest of the genome. Branch length was not correlated with allele frequency. In conclusion, sequence data suggest that balancing selection in HLA is asymmetric (some heterozygotes enjoy greater fitness than others). Because HLA polymorphism is crucial for pathogen resistance, this may manifest as a frequency-dependent selection with fluctuation in the fitness of specific heterozygotes over time.

The common genetic loci that independently influence the risk of type 1 diabetes have largely been determined. Their interactions with age-at-diagnosis of type 1 diabetes, sex, or the major susceptibility locus, HLA class II, remain mostly unexplored. A large collection of more than 14,866 type 1 diabetes samples (6,750 British diabetic individuals and 8,116 affected family samples of European descent) were genotyped at 38 confirmed type 1 diabetes-associated non-HLA regions and used to test for interaction of association with age-at-diagnosis, sex, and HLA class II genotypes using regression models. The alleles that confer susceptibility to type 1 diabetes at interleukin-2 (IL-2), IL2/4q27 (rs2069763) and renalase, FAD-dependent amine oxidase (RNLS)/10q23.31 (rs10509540), were associated with a lower age-at-diagnosis (P = 4.6 × 10⁻⁶ and 2.5 × 10⁻⁵, respectively). For both loci, individuals carrying the susceptible homozygous genotype were, on average, 7.2 months younger at diagnosis than those carrying the protective homozygous genotypes. In addition to protein tyrosine phosphatase nonreceptor type 22 (PTPN22), evidence of statistical interaction between HLA class II genotypes and rs3087243 at cytotoxic T-lymphocyte antigen 4 (CTLA4)/2q33.2 was obtained (P = 7.90 × 10⁻⁵). No evidence of differential risk by sex was obtained at any loci (P ≥ 0.01). Statistical interaction effects can be detected in type 1 diabetes although they provide a relatively small contribution to our understanding of the familial clustering of the disease.

The human leukocyte antigen (HLA) genes are candidate genetic susceptibility loci for childhood acute lymphoblastic leukemia (ALL). We examined the effect of HLA-DP genetic variation on risk and evaluated its potential interaction with 4 proxies for early immune modulation, including measures of infectious exposures in infancy (presence of older siblings, daycare attendance, ear infections) and breastfeeding. A total of 585 ALL cases and 848 controls were genotyped at the HLA-DPA1 and DPB1 loci. Because of potential heterogeneity in effect by race/ethnicity, we included only non-Hispanic white (47%) and Hispanic (53%) children and considered these 2 groups separately in the analysis. Logistic regression analyses showed an increased risk of ALL associated with HLA-DPB1*01:01 (odds ratio [OR] = 1.43, 95% CI, 1.01-2.04) with no heterogeneity by Hispanic ethnicity (P = .969). Analyses of DPB1 supertypes showed a marked childhood ALL association with DP1, particularly for high-hyperdiploid ALL (OR = 1.83; 95% CI, 1.20-2.78). Evidence of interaction was found between DP1 and older sibling (P = .036), and between DP1 and breastfeeding (P = .094), with both showing statistically significant DP1 associations within the lower exposure categories only. These findings support an immune mechanism in the etiology of childhood ALL involving the HLA-DPB1 gene in the context of an insufficiently modulated immune system.

Aims/hypothesis: The study aimed to assess, in multiple populations, the role of HLA alleles on early and late age at onset of type 1 diabetes., Methods: Stepwise linear regression models were used to determine which HLA class I and class II risk alleles to include. High-resolution genotyping data for patients from the Type 1 Diabetes Genetics Consortium (T1DGC) collection (n = 2,278) and four independent cohorts from Denmark, Sardinia and the USA (Human Biological Data Interchange [HBDI] and Joslin Diabetes Center) (n = 1,324) (total n = 3,602) were used to assess the role of HLA variation on age of onset and predict early onset (age ≤ 5 years) and late onset (age ≥ 15 years) of type 1 diabetes., Results: In addition to carriage of HLA class I alleles A*24:02, B*39:06, B*44:03 and B*18:01, HLA class II DRB1-DQB1 loci significantly contributed to age at onset, explaining 3.4% of its variance in the combined data. HLA genotypes, together with sex, were able to predict late onset in all cohorts studied, with AUC values ranging from 0.58 to 0.63. Similar AUC values (0.59-0.70) were obtained for early onset for most cohorts, except in the Sardinian study, in which none of the models tested had significant predictive power., Conclusions/interpretation: HLA associations with age of onset are consistent across most white populations and HLA information can predict some of the risk of early and late onset of type 1 diabetes. Considerable heterogeneity was observed between Sardinian and other populations, particularly with regard to early age of onset.

Follicular lymphoma (FL) is an indolent, sometimes, fatal disease characterized by recurrence at progressively shorter intervals and is frequently refractive to therapy. Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) in the human leukocyte antigen (HLA) region on chromosome 6p21.32-33 that are statistically significantly associated with FL risk. Low to medium resolution typing of single or multiple HLA genes has provided an incomplete picture of the total genetic risk imparted by this highly variable region. To gain further insight into the role of HLA alleles in lymphomagenesis and to investigate the independence of validated SNPs and HLA alleles with FL risk, high-resolution HLA typing was conducted using next-generation sequencing in 222 non-Hispanic White FL cases and 220 matched controls from a larger San Francisco Bay Area population-based case-control study of lymphoma. A novel protective association was found between the DPB1*03:01 allele and FL risk [odds ratio (OR) = 0.39, 95% confidence interval (CI) = 0.21-0.68]. Extended haplotypes DRB1*01:01-DQA1*01:01-DQB1*05:01 (OR = 2.01, 95% CI = 1.22-3.38) and DRB1*15-DQA1*01-DQB1*06 (OR = 0.55, 95% CI = 0.36-0.82) also influenced FL risk. Moreover, DRB1*15-DQA1*01-DQB1*06 was highly correlated with an established FL risk locus, rs2647012. These results provide further insight into the critical roles of HLA alleles and SNPs in FL pathogenesis that involve multi-locus effects across the HLA region., (© 2012 John Wiley & Sons A/S.)

Aims/hypothesis: Over 50 regions of the genome have been associated with type 1 diabetes risk, mainly using large case/control collections. In a recent genome-wide association (GWA) study, 18 novel susceptibility loci were identified and replicated, including replication evidence from 2,319 families. Here, we, the Type 1 Diabetes Genetics Consortium (T1DGC), aimed to exclude the possibility that any of the 18 loci were false-positives due to population stratification by significantly increasing the statistical power of our family study., Methods: We genotyped the most disease-predicting single-nucleotide polymorphisms at the 18 susceptibility loci in 3,108 families and used existing genotype data for 2,319 families from the original study, providing 7,013 parent-child trios for analysis. We tested for association using the transmission disequilibrium test., Results: Seventeen of the 18 susceptibility loci reached nominal levels of significance (p < 0.05) in the expanded family collection, with 14q24.1 just falling short (p = 0.055). When we allowed for multiple testing, ten of the 17 nominally significant loci reached the required level of significance (p < 2.8 × 10(-3)). All susceptibility loci had consistent direction of effects with the original study., Conclusions/interpretation: The results for the novel GWA study-identified loci are genuine and not due to population stratification. The next step, namely correlation of the most disease-associated genotypes with phenotypes, such as RNA and protein expression analyses for the candidate genes within or near each of the susceptibility regions, can now proceed.

Genetic susceptibility to type 1 diabetes (T1D) has been a subject of intensive study for nearly four decades. This article will present the history of these studies, beginning with observations of the Human Leukocyte Antigen (HLA) association in the 1970s, through the advent of DNA-based genotyping methodologies, through recent large, international collaborations and genome-wide association studies. More than 40 genetic loci have been associated with T1D in multiple studies; however, the HLA region, with its multiple genes and extreme polymorphism at those loci, remains by far the greatest contributor to the genetic susceptibility to T1D. Even after decades of study, the complete story has yet to unfold, and exact mechanisms by which HLA and other associated loci confer T1D susceptibility remain elusive.

We have conducted a pathway-based analysis of genome-wide single-nucleotide polymorphism (SNP) data in order to identify genetic susceptibility factors for cervical cancer in situ. Genotypes derived from Affymetrix 500k or 5.0 arrays for 1076 cases and 1426 controls were analyzed for association, and pathways with enriched signals were identified using the SNP ratio test. The most strongly associated KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways were Asthma (empirical P=0.03), Folate biosynthesis (empirical P=0.04) and Graft-versus-host disease (empirical P=0.05). Among the 11 top-ranking pathways were 6 related to the immune response with the common denominator being genes in the major histocompatibility complex (MHC) region on chromosome 6. Further investigation of the MHC revealed a clear effect of HLA-DPB1 polymorphism on disease susceptibility. At a functional level, DPB1 alleles associated with risk and protection differ in key amino-acid residues affecting peptide-binding motifs in the extracellular domains. The results illustrate the value of pathway-based analysis to mine genome-wide data, and point to the importance of the MHC region and specifically the HLA-DPB1 locus for susceptibility to cervical cancer.

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., (© 2011 John Wiley & Sons A/S.)

Objective: The aim of this study was to quantitate risk and to examine heterogeneity for HLA at high resolution in patients with the most common subtypes of juvenile idiopathic arthritis (JIA), IgM rheumatoid factor-negative polyarticular JIA and oligoarticular JIA. Use of 4-digit comprehensive HLA typing enabled great precision, and a large cohort allowed for consideration of both age at disease onset and disease subtype., Methods: Polymerase chain reaction-based high-resolution HLA typing for class I and class II loci was accomplished for 820 patients with JIA and 273 control subjects. Specific HLA epitopes, potential interactions of alleles at specific loci and between loci (accounting for linkage disequilibrium and haplotypic associations), and an assessment of the current International League of Associations for Rheumatology classification criteria were considered., Results: An HLA-DRB1/DQB1 effect was shown to be exclusively attributable to DRB1 and was similar between patients with oligoarticular JIA and a younger subgroup of patients with polyarticular JIA. Furthermore, patients with polyarticular JIA showed age-specific related effects, with disease susceptibility in the group older than age 6 years limited to an effect of the HLA-DRB1*08 haplotype, which is markedly different from the additional susceptibility haplotypes, HLA-DRB1*1103/1104, found in the group with oligoarticular JIA and the group of younger patients with polyarticular JIA. Also in contrast to findings for oligoarticular JIA, patients with polyarticular arthritis had no evidence of an HLA class I effect. Markers associated with a reduced risk of disease included DRB1*1501, DRB1*0401, and DRB1*0701. DRB1*1501 was shown to reduce risk across the whole cohort, whereas DRB1*0401 and DRB1*0701 were protective for selected JIA subtypes. Surprisingly, the disease predisposition mediated by DPB1*0201 in individuals without any disease-predisposing DRB1 alleles was great enough to overcome even the very strong protective effect observed for DRB1*1501., Conclusion: Inherited HLA factors in JIA show similarities overall as well as differences between JIA subtypes.

The WHO Nomenclature Committee for Factors of the HLA System met during the 15th International Histocompatibility and Immunogenetics Workshop in Buzios, Brazil in September 2008. This update is an extract of the main report that documents the additions and revisions to the nomenclature of human leukocyte antigen (HLA) specificities following the principles established in previous reports.

Background: Although human leukocyte antigen (HLA) DQ and DR loci appear to confer the strongest genetic risk for type 1 diabetes, more detailed information is required for other loci within the HLA region to understand causality and stratify additional risk factors. The Type 1 Diabetes Genetics Consortium (T1DGC) study design included high-resolution genotyping of HLA-A, B, C, DRB1, DQ, and DP loci in all affected sibling pair and trio families, and cases and controls, recruited from four networks worldwide, for analysis with clinical phenotypes and immunological markers., Purpose: In this article, we present the operational strategy of training, classification, reporting, and quality control of HLA genotyping in four laboratories on three continents over nearly 5 years., Methods: Methods to standardize HLA genotyping at eight loci included: central training and initial certification testing; the use of uniform reagents, protocols, instrumentation, and software versions; an automated data transfer; and the use of standardized nomenclature and allele databases. We implemented a rigorous and consistent quality control process, reinforced by repeated workshops, yearly meetings, and telephone conferences., Results: A total of 15,246 samples have been HLA genotyped at eight loci to four-digit resolution; an additional 6797 samples have been HLA genotyped at two loci. The genotyping repeat rate decreased significantly over time, with an estimated unresolved Mendelian inconsistency rate of 0.21%. Annual quality control exercises tested 2192 genotypes (4384 alleles) and achieved 99.82% intra-laboratory and 99.68% inter-laboratory concordances., Limitations: The chosen genotyping platform was unable to distinguish many allele combinations, which would require further multiple stepwise testing to resolve. For these combinations, a standard allele assignment was agreed upon, allowing further analysis if required., Conclusions: High-resolution HLA genotyping can be performed in multiple laboratories using standard equipment, reagents, protocols, software, and communication to produce consistent and reproducible data with minimal systematic error. Many of the strategies used in this study are generally applicable to other large multi-center studies.

Introduction: This study investigated five confirmed rheumatoid arthritis (RA) susceptibility genes/loci (HLA-DRB1, PTPN22, STAT4, OLIG3/TNFAIP3 and TRAF1/C5) for association with susceptibility and severity in an inception cohort., Methods: The magnitude of association for each genotype was assessed in 1,046 RA subjects from the Yorkshire Early RA cohort and in 5,968 healthy UK controls. Additional exploratory subanalyses were undertaken in subgroups defined by autoantibody status (rheumatoid factor and anti-cyclic citrullinated peptide) or disease severity (baseline articular erosions, Health Assessment Questionnaire (HAQ) score and swollen joint count (SJC))., Results: In the total RA inception cohort, the HLA-DRB1 shared epitope (per-allele odds ratio (OR) = 2.1, trend P < 0.0001), PTPN22 (per-allele OR = 1.5, trend P < 0.0001), OLIG3/TNFAIP3 locus (per-allele OR = 1.2, trend P = 0.009) and TRAF1/C5 locus (per-allele OR = 1.1, trend P = 0.04) were associated with RA. The magnitude of association for these loci was increased in those patients who were autoantibody-positive. PTPN22 was associated with autoantibody-negative RA (per-allele OR = 1.3, trend P = 0.04). There was no evidence of association between these five genetic loci and baseline erosions or SJC in the total RA cohort, after adjustment for symptom duration. TRAF1/C5 was significantly associated with baseline HAQ, however, following adjustment for symptom duration (P trend = 0.03)., Conclusions: These findings support the mounting evidence that different genetic loci are associated with autoantibody-positive and autoantibody-negative RA, possibly suggesting that many of the genes identified to date are associated with autoantibody production. Additional studies with a specific focus on autoantibody-negative RA will be needed to identify the genes predisposing to this RA subgroup. The TRAF1/C5 locus in particular warrants further investigation in RA as a potential disease severity locus.

Several studies suggest that the peroxisome proliferator-activated receptor gamma (PPARγ) is involved in atherogenesis. The Pro12Ala polymorphism in the gene encoding PPARγ (PPARγ2 gene) influences the risk for type 2 diabetes. Two population-based studies have shown that the Ala allele is associated with reduced carotid intimal-medial thickness (IMT). However, studies focusing on acute clinical events have yielded conflicting results. Our aim was to evaluate the role of the Pro12Ala PPARγ2 polymorphism on the risk of coronary artery disease (CAD) in an Italian population with a case-controlled genetic association study in which 478 CAD patients and 218 controls were genotyped for the Pro12Ala polymorphism. CAD was diagnosed by angiography. We found that homozygotes for the Ala12 allele had a significantly reduced risk of CAD after adjusting for diabetes, sex, age, body mass index (BMI), smoking, lipids and hypertension (OR =0.007; 95% C.I. = 0.00-0.32 p< 0.011). In this case-control study, homozygosity for the Ala allele at codon 12 of the PPARγ2 gene resulted in reduced risk of CAD. This is consistent with reports from previous studies focusing on atherosclerosis and myocardial infarction.

The immune response HLA class II DRB1 gene provides the major genetic contribution to Juvenile Idiopathic Arthritis (JIA), with a hierarchy of predisposing through intermediate to protective effects. With JIA, and the many other HLA associated diseases, it is difficult to identify the combinations of biologically relevant amino acid (AA) residues directly involved in disease due to the high level of HLA polymorphism, the pattern of AA variability, including varying degrees of linkage disequilibrium (LD), and the fact that most HLA variation occurs at functionally important sites. In a subset of JIA patients with the clinical phenotype oligoarticular-persistent (OP), we have applied a recently developed novel approach to genetic association analyses with genes/proteins sub-divided into biologically relevant smaller sequence features (SFs), and their "alleles" which are called variant types (VTs). With SFVT analysis, association tests are performed on variation at biologically relevant SFs based on structural (e.g., beta-strand 1) and functional (e.g., peptide binding site) features of the protein. We have extended the SFVT analysis pipeline to additionally include pairwise comparisons of DRB1 alleles within serogroup classes, our extension of the Salamon Unique Combinations algorithm, and LD patterns of AA variability to evaluate the SFVT results; all of which contributed additional complementary information. With JIA-OP, we identified a set of single AA SFs, and SFs in which they occur, particularly pockets of the peptide binding site, that account for the major disease risk attributable to HLA DRB1. These are (in numeric order): AAs 13 (pockets 4 and 6), 37 and 57 (both pocket 9), 67 (pocket 7), 74 (pocket 4), and 86 (pocket 1), and to a lesser extent 30 (pockets 6 and 7) and 71 (pockets 4, 5, and 7).

The Type I Diabetes Genetics Consortium (T1DGC) has collected thousands of multiplex and simplex families with type I diabetes (T1D) with the goal of identifying genes involved in T1D susceptibility. These families have been genotyped for the HLA class I and class II loci and, recently, for a genome-wide panel of single-nucleotide polymorphisms (SNPs). In addition, multiple SNPs in specific candidate genes have been genotyped in these families in an attempt to evaluate previously reported T1D associations, including the C883A (Pro-Thr) polymorphism in exon 2 of TCF7, a T-cell transcription factor. The TCF7 883A allele was associated with T1D in subjects with T1D not carrying the high-risk HLA genotype DR3/DR4. A panel of 11 SNPs in TCF7 was genotyped in 2092 families from 9 cohorts of the T1DGC. SNPs at two positions in TCF7 were associated with T1D. One associated SNP, C883A (rs5742913), was reported earlier to have a T1D association. A second SNP, rs17653687, represents a novel T1D susceptibility allele in TCF7. After stratification on the high T1D risk DR3/DR4 genotype, the variant (A) allele of C883A was significantly associated with T1D among non-DR3/DR4 cases (transmission=55.8%, P=0.004; OR=1.26) but was not significantly associated in the DR3/DR4 patient subgroup, replicating the earlier report. The reference A allele of intronic SNP rs17653687 was modestly associated with T1D in both DR3/DR4 strata (transmission=54.4% in DR3/DR4; P=0.03; transmission=52.9% in non-DR3/DR4; P=0.03). These results support the previously reported association of the non-synonymous Pro-Thr SNP in TCF7 with T1D, and suggest that other alleles at this locus may also confer risk.

The Type I Diabetes Genetics Consortium (T1DGC) has collected thousands of multiplex and simplex families with type I diabetes (T1D) with the goal of identifying genes involved in T1D susceptibility. These families have all been genotyped for the HLA class I and class II loci and a subset of samples has been typed for an major histocompatibility complex (MHC) single-nucleotide polymorphism (SNP) panel. In addition, the T1DGC has genotyped SNPs in candidate genes to evaluate earlier reported T1D associations. Individual SNPs and SNP haplotypes in IL4R, which encodes the alpha-chain of the IL4 and IL13 receptors, have been associated with T1D in some reports, but not in others. In this study, 38 SNPs in IL4R were genotyped using the Sequenom iPLEX Gold MassARRAY technology in 2042 multiplex families from nine cohorts. Association analyses (transmission-disequilibrium test and parental-disequilibrium test) were performed on individual SNPs and on three-SNP haplotypes. Analyses were also stratified on the high-risk HLA DR3/DR4-DQB1*0302 genotype. A modest T1D association in HBDI families (n=282) was confirmed in this larger collection of HBDI families (n=424). The variant alleles at the non-synonymous SNPs (rs1805011 (E400A), rs1805012 (C431R), and rs1801275 (Q576R)), which are in strong linkage disequilibrium, were negatively associated with T1D risk. These SNPs were more associated with T1D among non-DR3/DR4-DQB1*0302 genotypes than DR3/DR4-DQB1*0302 genotypes. This association was stronger, both in terms of odds ratio and P-values, than the initial report of the smaller collection of HBDI families. However, the IL4R SNPs and the three-SNP haplotype containing the variant alleles were not associated with T1D in the total data. Thus, in the overall families, these results do not show evidence for an association of SNPs in IL4R with T1D.

The human leukocyte antigen (HLA) class I and class II loci are the most polymorphic genes in the human genome. Hematopoietic stem cell transplantation requires allele-level HLA typing at multiple loci to select the best matched unrelated donors for recipient patients. In current methods for HLA typing, both alleles of a heterozygote are amplified and typed or sequenced simultaneously, often making it difficult to unambiguously determine the sequence of the two alleles. Next-generation sequencing methods clonally propagate in parallel millions of single DNA molecules, which are then also sequenced in parallel. Recently, the read lengths obtainable by one such next-generation sequencing method (454 Life Sciences, Inc.) have increased to >250 nucleotides. These clonal read lengths make possible setting the phase of the linked polymorphisms within an exon and thus the unambiguous determination of the sequence of each HLA allele. Here we demonstrate this capacity as well as show that the throughput of the system is sufficiently high to enable a complete, 7-locus HLA class I and II typing for 24 or 48 individual DNAs in a single GS FLX sequencing run. Highly multiplexed amplicon sequencing is facilitated by the use of sample-specific internal sequence tags (multiplex identification tags or MIDs) in the primers that allow pooling of samples yet maintain the ability to assign sequences to specific individuals. We have incorporated an HLA typing software application developed by Conexio Genomics (Freemantle, Australia) that assigns HLA genotypes for these 7 loci (HLA-A, -B, -C, DRB1, DQA1, DQB1, DPB1), as well as for DRB3, DRB4, and DRB5 from 454 sequence data. The potential of this HLA sequencing system to analyze chimeric mixtures is demonstrated here by the detection of a rare HLA-B allele in a mixture of two homozygous cell lines (1/100), as well as by the detection of the rare nontransmitted maternal allele present in the blood of a severe combined immunodeficiency disease syndrome (SCIDS) patient.

In the present study, we investigated the relationship between the KIR loci and the genes encoding their HLA ligands and genetic susceptibility to Crohn's disease (CD). Analyses of the interactions between KIR3DL1, KIR2DL1, KIR2DL2, and KIR2DL3 with their respective HLA ligands indicate that there is a protective effect for KIR2DL2 in the absence of its HLA ligand C1. Given that KIR2DL2 and KIR2DL3 segregate as alleles, we compared their genotypic distributions to expectations under Hardy-Weinberg Equilibrium (HWE) with regard to the HLA ligand C1 status. While all the genotypic distributions conform to expectations under HWE in controls, in C2 ligand homozygous cases there is significant deviation from HWE, with a reduction of KIR2DL2, KIR2DL3 heterozygotes. KIR2DL2, KIR2DL3 heterozygosity is the only genotypic combination that confers protection from CD. In addition to the protective effect (OR = 0.44, CI = 0.22-0.87; p = 0.018) observed in C2 ligand homozygotes, the KIR2DL2, KIR2DL3 genotype is predisposing (OR = 1.34, CI = 1.03-4.53; p = 0.031) in the presence of C1 ligand. A test for trend of HLA class I C ligand group genotypes with KIR2DL2, KIR2DL3 heterozygosity in cases and controls indicates that C1, C2 ligand group heterozygotes have an intermediate effect on predisposition. These results show for the first time that disease susceptibility may be related to heterozygosity at a specific KIR locus, and that HLA ligand genotype influences the relative effect of the KIR genotype.

The analysis of families collected by the T1DGC and typed at high resolution for the HLA class I and class II loci provided an opportunity for identifying new alleles and rare recombination events. In one American Caucasian family, a novel allele (HLA-DPB1*1302), detected as an unusual pattern of probe binding, was identified in the mother and in one child. Amplicons from both individuals were sequenced and a new variant of DPB1*1301 with an A->T mutation [TAC to TTC in codon 64, (amino acid 35); Y to F] was confirmed. In another American Caucasian family, one child inherited an unusual haplotype, DRB1*1501-DQA1*0102-DQB1*0609-DPA1*0103-DPB1*0601 resulting from a recombination between the DRB1 loci on the maternal chromosomes DRB1*1501-DQA1*0102-DQB1*0602-DPA1*0103-DPB1*0401 and DRB1*1302-DQA1*0102-DQB1*0609-DPA1*0103-DPB1*0601.

The availability of both HLA data and genotypes for thousands of SNPs across the major histocompatibility complex (MHC) in 1240 complete families of the Type 1 Diabetes Genetics Consortium allowed us to analyze the occurrence and extent of megabase contiguous identity for founder chromosomes from unrelated individuals. We identified 82 HLA-defined haplotype groups, and within these groups, megabase regions of SNP identity were readily apparent. The conserved chromosomes within the 82 haplotype groups comprise approximately one third of the founder chromosomes. It is currently unknown whether such frequent conservation for groups of unrelated individuals is specific to the MHC, or if initial binning by highly polymorphic HLA alleles facilitated detection of a more general phenomenon within the MHC. Such common identity, specifically across the MHC, impacts type 1 diabetes susceptibility and may impact transplantation between unrelated individuals.

Type 1 diabetes (T1D) is a common autoimmune disorder that arises from the action of multiple genetic and environmental risk factors. We report the findings of a genome-wide association study of T1D, combined in a meta-analysis with two previously published studies. The total sample set included 7,514 cases and 9,045 reference samples. Forty-one distinct genomic locations provided evidence for association with T1D in the meta-analysis (P < 10(-6)). After excluding previously reported associations, we further tested 27 regions in an independent set of 4,267 cases, 4,463 controls and 2,319 affected sib-pair (ASP) families. Of these, 18 regions were replicated (P < 0.01; overall P < 5 × 10(-8)) and 4 additional regions provided nominal evidence of replication (P < 0.05). The many new candidate genes suggested by these results include IL10, IL19, IL20, GLIS3, CD69 and IL27.

Objective: Type 1 diabetes arises from the actions of multiple genetic and environmental risk factors. Considerable success at identifying common genetic variants that contribute to type 1 diabetes risk has come from genetic association (primarily case-control) studies. However, such studies have limited power to detect genes containing multiple rare variants that contribute significantly to disease risk., Research Design and Methods: The Type 1 Diabetes Genetics Consortium (T1DGC) has assembled a collection of 2,496 multiplex type 1 diabetic families from nine geographical regions containing 2,658 affected sib-pairs (ASPs). We describe the results of a genome-wide scan for linkage to type 1 diabetes in the T1DGC family collection., Results: Significant evidence of linkage to type 1 diabetes was confirmed at the HLA region on chromosome 6p21.3 (logarithm of odds [LOD] = 213.2). There was further evidence of linkage to type 1 diabetes on 6q that could not be accounted for by the major linkage signal at the HLA class II loci on chromosome 6p21. Suggestive evidence of linkage (LOD > or =2.2) was observed near CTLA4 on chromosome 2q32.3 (LOD = 3.28) and near INS (LOD = 3.16) on chromosome 11p15.5. Some evidence for linkage was also detected at two regions on chromosome 19 (LOD = 2.84 and 2.54)., Conclusions: Five non-HLA chromosome regions showed some evidence of linkage to type 1 diabetes. A number of previously proposed type 1 diabetes susceptibility loci, based on smaller ASP numbers, showed limited or no evidence of linkage to disease. Low-frequency susceptibility variants or clusters of loci with common alleles could contribute to the linkage signals observed.

Aim: The goal of this study was to develop and implement methodology that would aid in the analysis of extended high-density single nucleotide polymorphism (SNP) major histocompatibility complex (MHC) haplotypes combined with human leucocyte antigen (HLA) alleles in relation to type 1 diabetes risk., Methods: High-density SNP genotype data (2918 SNPs) across the MHC from the Type 1 Diabetes Genetics Consortium (1240 families), in addition to HLA data, were processed into haplotypes using PedCheck and Merlin, and extended DR3 haplotypes were analysed., Results: With this large dense set of SNPs, the conservation of DR3-B8-A1 (8.1) haplotypes spanned the MHC (>/=99% SNP identity). Forty-seven individuals homozygous for the 8.1 haplotype also shared the same homozygous genotype at four 'sentinel' SNPs (rs2157678 'T', rs3130380 'A', rs3094628 'C' and rs3130352 'T'). Conservation extended from HLA-DQB1 to the telomeric end of the SNP panels (3.4 Mb total). In addition, we found that the 8.1 haplotype is associated with lower risk than other DR3 haplotypes by both haplotypic and genotypic analyses [haplotype: p = 0.009, odds ratio (OR) = 0.65; genotype: p = 6.3 x 10(-5), OR = 0.27]. The 8.1 haplotype (from genotypic analyses) is associated with lower risk than the high-risk DR3-B18-A30 haplotype (p = 0.01, OR = 0.23), but the DR3-B18-A30 haplotype did not differ from other non-8.1 DR3 haplotypes relative to diabetes association., Conclusion: The 8.1 haplotype demonstrates extreme conservation (>3.4 Mb) and is associated with significantly lower risk for type 1 diabetes than other DR3 haplotypes.

Objective: The Type 1 Diabetes Genetics Consortium (T1DGC) has assembled and genotyped a large collection of multiplex families for the purpose of mapping genomic regions linked to type 1 diabetes. In the current study, we tested for evidence of loci associated with type 1 diabetes utilizing genome-wide linkage scan data and family-based association methods., Research Design and Methods: A total of 2,496 multiplex families with type 1 diabetes were genotyped with a panel of 6,090 single nucleotide polymorphisms (SNPs). Evidence of association to disease was evaluated by the pedigree disequilibrium test. Significant results were followed up by genotyping and analyses in two independent sets of samples: 2,214 parent-affected child trio families and a panel of 7,721 case and 9,679 control subjects. RESULTS- Three of the SNPs most strongly associated with type 1 diabetes localized to previously identified type 1 diabetes risk loci: INS, IFIH1, and KIAA0350. A fourth strongly associated SNP, rs876498 (P = 1.0 x 10(-4)), occurred in the sixth intron of the UBASH3A locus at chromosome 21q22.3. Support for this disease association was obtained in two additional independent sample sets: families with type 1 diabetes (odds ratio [OR] 1.06 [95% CI 1.00-1.11]; P = 0.023) and case and control subjects (1.14 [1.09-1.19]; P = 7.5 x 10(-8))., Conclusions: The T1DGC 6K SNP scan and follow-up studies reported here confirm previously reported type 1 diabetes associations at INS, IFIH1, and KIAA0350 and identify an additional disease association on chromosome 21q22.3 in the UBASH3A locus (OR 1.10 [95% CI 1.07-1.13]; P = 4.4 x 10(-12)). This gene and its flanking regions are now validated targets for further resequencing, genotyping, and functional studies in type 1 diabetes.

Cervical cancer has been associated with specific human leukocyte antigen (HLA) haplotypes/alleles and with polymorphisms at the nearby non-HLA loci TNF, LTA, TAP1 and TAP2. Distinguishing effects of individual loci in the major histocompatibility complex (MHC) region are difficult due to the complex linkage disequilibrium (LD) pattern characterized by high LD, punctuated by recombination hot spots. We have evaluated the association of polymorphism at HLA class II DQB1 and the TNF, LTA, TAP1 and TAP2 genes with cervical cancer risk, using 1306 familial cases and 288 controls. DQB1 was strongly associated; alleles *0301, *0402 and (*)0602 increased cancer susceptibility, whereas *0501 and *0603 decreased susceptibility. Among the non-HLA loci, association was only detected for the TAP2 665 polymorphism, and interallelic disequilibrium analysis indicated that this could be due to LD with DQB1. As the TAP2 665 association was seen predominantly in non-carriers of DQB1 susceptibility alleles, we hypothesized that TAP2 665 may have an effect not attributable to LD with DQB1. However, a logistic regression analysis suggested that TAP2 665 was strongly influenced by LD with DQB1. Our results emphasize the importance of large sample sizes and underscore the necessity of examining both HLA and non-HLA loci in the MHC to assign association to the correct locus.

Candidate osteoporosis gene variants were examined for associations with fracture risk and bone mineral density (BMD). A total of 9,704 white women were recruited at four U.S. clinical centers and enrolled into the Study of Osteoporotic Fractures, a longitudinal cohort study. Genotyping of 31 polymorphisms from 18 candidate osteoporosis genes was performed in 6,752 women. Incident radiographic fractures were identified at the third and eighth examinations compared with the baseline examination. BMD was measured at the total hip by dual-energy X-ray absorptiometry. Analyses were adjusted for age, clinic site, and self-reported ethnicity. During a mean follow-up of 14.5 years, a total of 849 hip, 658 vertebral, and 2,496 nonhip/nonvertebral fractures occurred in 6,752 women. Women carrying the ALOX15&#95;G48924T T/T genotype had a higher rate of hip fracture (hazard ratio [HR] = 1.33;95% confidence interval [95% CI] = 1.00-1.77) compared with the G/G genotype. Compared with those carrying the PRL&#95;T228C T/T genotype, women with either the C/C (HR = 0.80; 95% CI = 0.67-0.95) or C/T (HR = 0.81; 95% CI = 0.68-0.97) genotype had a lower rate of nonvertebral/nonhip fractures. Women carrying the BMP2&#95;A125611G G/G genotype had a higher rate of vertebral fracture (odds ratio [OR] = 1.51; 95% CI = 1.03-2.23) compared with the A/A genotype. Women with the ESR1&#95;C1335G G/G genotype had a higher rate of vertebral fracture (OR = 1.64; 95% CI = 1.07-2.50) compared with the C/C genotype. Compared with those with the MMP2&#95;C595T C/C genotype, women with the C/T (OR = 0.79; 95% CI = 0.65-0.96) or T/T (OR = 0.44; 95% CI = 0.27-0.72) genotype had a lower rate of vertebral fracture. In conclusion, polymorphisms in several candidate genes were associated with hip, vertebral, and nonhip/nonvertebral fractures but not with total hip BMD in this large population based cohort study.

Patients with high-risk human leukocyte antigen (HLA)-DR-DQ genotypes for type 1 diabetes (T1D) were compared with HLA-matched controls to evaluate T1D risk for other HLA loci, including HLA-A, -B, -Cw, and DPB1. Patients (n = 133) with high-risk genotypes (DR3/DR3, DR3/DR4, DR4/DR4) were selected from the Lazio (Rome) region of Italy. Screening of more than 9000 patients from the Lazio region and northern Italy yielded 162 controls with high-T1D-risk haplotypes. Although the overall distributions did not differ significantly, allele frequency differences were discovered between the controls from Lazio and controls from northern Italy for some alleles previously determined to affect T1D risk, such as A*3002, DPB1*0301, and DPB1*0402. Therefore, Lazio patient data were compared both with the Lazio subset of controls (n = 53) and with the entire group of controls for association analyses. Significant allele frequency differences between patients and DR-DQ-matched controls existed for specific alleles at all loci. Data for the DR3/DR3 subset of patients and controls demonstrated an increase of Cw*0702 in patients. Compared with controls, reduced patient frequencies were seen for several alleles, including A*0101, B*0801, and Cw*0701, all on the highly conserved, extended DR3 haplotype known as 8.1 in DR3/DR3, but not DR3/DR4, subgroup. DPB1*0101, often reported on 8.1 haplotypes, was also less frequent in DR3/DR3 patients than controls. Analysis of family-based data from the HBDI repository was consistent with the observed results from the Italian patients, indicating the presence of a T1D-protective locus at or near A*0101 and a second T1D-protective locus at or near DPB1*0101. These data indicate that T1D risk conferred by the 8.1 haplotype is genotype dependent.

Objective: HLA-DRB1*03-DQB1*0201/DRB1*04-DQB1*0302 (DR3/4-DQ8) siblings who share both major histocompatibility complex (MHC) haplotypes identical-by-descent with their proband siblings have a higher risk for type 1A diabetes than DR3/4-DQ8 siblings who do not share both MHC haplotypes identical-by-descent. Our goal was to search for non-DR/DQ MHC genetic determinants that cause the additional risk in the DR3/4-DQ8 siblings who share both MHC haplotypes., Research Design and Methods: We completed an extensive single nucleotide polymorphism (SNP) analysis of the extended MHC in 237 families with type 1A diabetes from the U.S. and 1,240 families from the Type 1 Diabetes Genetics Consortium., Results: We found evidence for an association with type 1A diabetes (rs1233478, P = 1.6 x 10(-23), allelic odds ratio 2.0) in the UBD/MAS1L region, telomeric of the classic MHC. We also observed over 99% conservation for up to 9 million nucleotides between chromosomes containing a common haplotype with the HLA-DRB1*03, HLA-B*08, and HLA-A*01 alleles, termed the "8.1 haplotype." The diabetes association in the UBD/MAS1L region remained significant both after chromosomes with the 8.1 haplotype were removed (rs1233478, P = 1.4 x 10(-12)) and after adjustment for known HLA risk factors HLA-DRB1, HLA-DQB1, HLA-B, and HLA-A (P = 0.01)., Conclusions: Polymorphisms in the region of the UBD/MAS1L genes are associated with type 1A diabetes independent of HLA class II and I alleles.