bluuebunny/crossref_metadata_2025_split huggingface dataset:
Skin testing and drug provocation in the diagnosis of nonimmediate reactions to aminopenicillins in children
Authors: Blanca‐López N. , Zapatero L. , Alonso E. , Torres M. J. , Fuentes V. , Martínez‐Molero M. I. , Blanca M. 
Published: January 2009

Background:  Nonimmediate allergic reactions (NIR) to aminopenicillin include several entities, the most common of which are urticaria‐like and maculopapular exanthemas.Aims of the study:  To evaluate a group of children who developed one or more episodes of skin reactions suggestive of NIR after aminopenicillin administration.Methods:  The inclusion criteria required negative immediate skin tests and absence of specific IgE antibodies to different penicillins. Intradermal and patch tests were carried out with delayed readings and, if negative, a drug‐provocation test including a full therapeutic course of the drug was given. Two different groups were compared: A) children with positive skin testing or a positive drug‐provocation test and B) children with negative skin testing and good tolerance after a drug‐provocation test.Results:  Group A was composed of 20 patients. Positive intradermal/patch tests were found in one patient and in the remaining 19, a positive response to a drug‐provocation test confirmed the diagnosis. Group B (the control group) consisted of 19 patients with similar symptoms after aminopenicillin intake but good tolerance. No differences in age, dose or number of previous treatments were observed between the groups. The clinical entities were also similar in both groups.Conclusions:  Reproducible nonimmediate skin reactions to aminopenicillins may occur in children in spite of negative skin testing. The value of this diagnostic procedure seems to be limited in this type of reaction, with drug‐provocation tests (DPT) being a reasonable and safe alternative if the diagnosis has to be confirmed.
Fruit fly liquid larval diet technology transfer and update
Authors: Chang C. L. 
Published: January 2009

AbstractSince October 2006, the US Department of Agriculture–Agricultural Research Service (USDA–ARS) has been implementing a fruit fly liquid larval diet technology transfer, which has proceeded according to the following steps: (1) recruitment of interested groups through request; (2) establishment of the Material Transfer Agreement with agricultural research service; (3) fruit fly liquid larval diet starter kit sent to the requestor for preliminary evaluation; (4) problem‐solving through email or onsite demonstration; (5) assessment on feedback from the participants to decide whether to continue the project. Up to date, the project has involved 35 participants from 29 countries and 26 species of fruit flies. Fourteen participants have concluded their evaluation of the process, and 11 of these 14, have deemed it to be successful. One participant has decided to implement the project on a larger scale.The 14 participants were, Argentina (Ceratitis capitata and Anastrepha fraterculus), Bangladesh (Bactrocera cucurbitae, C. capitata, and Bactrocera dorsalis), China (Fujia province) (B. dorsalis), Italy (C. capitata), Fiji (Bactrocera passiflorae), Kenya (Bactrocera invadens, Ceratitis cosyra), Mauritius (Bactrocera zonata and B. cucurbitae), Mexico (Anastrepha species), Philippines (Bactrocera philippinese), Thailand (Bactrocera correcta), Austria (C. capitata, Vienna 8 and A. fraterculus), Israel (Dacus ciliatus and C. capitata), South Africa (C. capitata, Vienna 8) and Australia (C. capitata).The Stellenbosch medfly mass‐rearing facility in South Africa and the CDFA in Hawaii were two mass‐scale rearing facilities that allowed us to demonstrate onsite rearing in a larger scale. Demonstrations were performed in CDFA in 2007, and in Stellenbosch, South Africa in 2008; both were found to be successful. The Stellenbosch medfly mass‐rearing facility in South Africa decided to adopt the technology and is currently evaluating the quality control of the flies that were reared as larvae on a liquid diet.
Hierarchical models facilitate spatial analysis of large data sets: a case study on invasive plant species in the northeastern United States
Authors: Latimer A. M. , Banerjee S. , Sang Jr H. , Mosher E. S. , Silander Jr J. A. 
Published: January 2009

AbstractMany critical ecological issues require the analysis of large spatial point data sets – for example, modelling species distributions, abundance and spread from survey data. But modelling spatial relationships, especially in large point data sets, presents major computational challenges. We use a novel Bayesian hierarchical statistical approach, ‘spatial predictive process’ modelling, to predict the distribution of a major invasive plant species,Celastrus orbiculatus, in the northeastern USA. The model runs orders of magnitude faster than traditional geostatistical models on a large data set ofc. 4000 points, and performs better than generalized linear models, generalized additive models and geographically weighted regression in cross‐validation. We also use this approach to model simultaneously the distributions of a set of four major invasive species in a spatially explicit multivariate model. This multispecies analysis demonstrates that some pairs of species exhibit negative residual spatial covariation, suggesting potential competitive interaction or divergent responses to unmeasured factors.
Community genetics: resource addition has opposing effects on genetic and species diversity in a 150‐year experiment
Authors: Silvertown Jonathan , Biss Pamela M. , Freeland Joanna 
Published: January 2009

AbstractWe used the Park Grass Experiment, begun in 1856, to test alternative hypotheses about the relationship between genetic diversity and plant species diversity. The niche variation hypothesis predicts that populations with few interspecific competitors and hence broader niches are expected to contain greater genetic diversity. The coexistence hypothesis predicts that genetic diversity within species favours coexistence among species and therefore species and genetic diversity should be positively correlated. Amplified Fragment Length Polymorphism (AFLP) markers were used to measure the genetic diversity of populations of Anthoxanthum odoratum growing in 10 plots of differing species richness that lie along resource and soil pH gradients. Genetic diversity in A. odoratum was positively correlated with the number of resources added to a plot, but not correlated with species richness. However, separate analyses have shown a negative correlation between resource addition and species richness at Park Grass and elsewhere, so genetic and species diversity appear to respond in opposite directions.
Overview of the MHC fine mapping data
Authors: Brown W. M. , Pierce J. , Hilner J. E. , Perdue L. H. , Lohman K. , Li L. , Venkatesh R. B. , Hunt S. , Mychaleckyj J. C. , Deloukas P. ,   Diabetes Genetics Consortium
Published: January 2009

Aim:  The aim of this study was to perform quality control (QC) and initial family‐based association analyses on the major histocompatibility complex (MHC) single nucleotide polymorphism (SNP) and microsatellite marker data for the MHC Fine Mapping Workshop through the Type 1 Diabetes Genetics Consortium (T1DGC).Methods:  A random sample of blind duplicates was sent for analysis of QC. DNA samples collected from participants were shipped to the genotyping laboratory from several T1DGC DNA Repository sites. Quality checks including examination of plate‐panel yield, marker yield, Hardy–Weinberg equilibrium, mismatch error rate, Mendelian error rate and allele distribution across plates were performed.Results:  Genotypes from 2325 families within nine cohorts were obtained and subjected to QC procedures. The MHC project consisted of three marker panels – two 1536 SNP sets (Illumina Golden Gate platform performed at the Wellcome Trust Sanger Institute, Cambridge, UK) and one 66 microsatellite marker panel (performed at deCODE). In the raw SNP data, the overall concordance rate was 99.1% (±0.02).Conclusions:  The T1DGC MHC Fine Mapping project resulted in a 2300 family, 9992 genotyped individuals database comprising of two 1536 SNP panels and a 66 microsatellite panel to densely cover the 4 Mb MHC core region for use in statistical genetic analyses.
Haplotype‐based search for SNPs associated with differential type 1 diabetes risk among chromosomes carrying a specific HLA DRB1–DQA1–DQB1 haplotype
Authors: McGinnis R. , McLaren W. , Ranganath V. , Whittaker P. , Hunt S. , Deloukas P. ,   Diabetes Genetics Consortium
Published: January 2009

Aim:  The aim of this study was to test chromosomes carrying the same DRB1–DQA1–DQB1 haplotype for single nucleotide polymorphisms (SNPs) in the major histocompatibility complex (MHC) that might mark subgroups of the haplotype with different risks for type 1 diabetes (T1D).Methods:  Chromosomes from T1D children, their parents and non‐diabetic siblings in families of the Type 1 Diabetes Genetics Consortium (T1DGC) were analysed by two haplotype‐based methods: (i) logistic regression analysis restricted to phased chromosomes carrying the same DRB1–DQA1–DQB1 haplotype but differentiated by the two alleles at MHC SNPs, which were individually tested for association with T1D and (ii) homozygous parent transmission disequilibrium test (TDT) for biased transmission of a SNP allele to diabetic children from parents who are heterozygous at the SNP but homozygous for the specific DRB1–DQA1–DQB1 haplotype being evaluated.Results:  A number of SNPs gave nominally significant (p < 0.05) evidence of marking two subsets of the 301–501–201 haplotype that might differ with respect to their diabetogenic potency. However, none of the SNPs achieved experiment‐wide significance and hence may be false‐positive associations.Conclusions:  We discuss limitations and possible deficiencies of our study suggesting further work that might yield more robust SNP associations marking two subgroups of a DRB1–DQA1–DQB1 haplotype with different T1D risks.
The frequent and conserved DR3‐B8‐A1 extended haplotype confers less diabetes risk than other DR3 haplotypes
Authors: Baschal E. E. , Aly T. A. , Jasinski J. M. , Steck A. K. , Johnson K. N. , Noble J. A. , Erlich H. A. , Eisenbarth G. S. ,   Diabetes Genetics Consortium
Published: January 2009

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 × 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.
Confirmation of HLA class II independent type 1 diabetes associations in the major histocompatibility complex including HLA‐B and HLA‐A
Authors: Howson J. M. M. , Walker N. M. , Clayton D. , Todd J. A. ,   Diabetes Genetics Consortium
Published: January 2009

Aim:  Until recently, human leucocyte antigen (HLA) class II‐independent associations with type 1 diabetes (T1D) in the Major Histocompatibility Complex (MHC) region were not adequately characterized owing to insufficient map coverage, inadequate statistical approaches and strong linkage disequilibrium spanning the entire MHC. Here we test for HLA class II‐independent associations in the MHC using fine mapping data generated by the Type 1 Diabetes Genetics Consortium (T1DGC).Methods:  We have applied recursive partitioning to the modelling of the class II loci and used stepwise conditional logistic regression to test ∼1534 loci between 29 and 34 Mb on chromosome 6p21, typed in 2240 affected sibpair (ASP) families.Results:  Preliminary analyses confirm that HLA‐B (at 31.4 Mb), HLA‐A (at 30.0 Mb) are associated with T1D independently of the class II genes HLA‐DRB1 and HLA‐DQB1 (P = 6.0 × 10−17 and 8.8 × 10−13, respectively). In addition, a second class II region of association containing the single‐nucleotide polymorphism (SNP), rs439121, and the class II locus HLA‐DPB1, was identified as a T1D susceptibility effect which is independent of HLA‐DRB1, HLA‐DQB1 and HLA‐B (P = 9.2 × 10−8). A younger age‐at‐diagnosis of T1D was found for HLA‐B*39 (P = 7.6 × 10−6), and HLA‐B*38 was protective for T1D.Conclusions:  These analyses in the T1DGC families replicate our results obtained previously in ∼2000 cases and controls and 850 families. Taking both studies together, there is evidence for four T1D‐associated regions at 30.0 Mb (HLA‐A), 31.4 Mb (HLA‐B), 32.5 Mb (rs9268831/HLA‐DRA) and 33.2 Mb (rs439121/HLA‐DPB1) that are independent of HLA‐DRB1/HLA‐DQB1. Neither study found evidence of independent associations at HLA‐C, HLA‐DQA1 loci nor in the UBD/MAS1L or ITPR3 gene regions. These studies show that to find true class II‐independent effects, large, well‐powered sample collections are required and be genotyped with a dense map of markers. In addition, a robust statistical methodology that fully models the class II effects is necessary. Recursive partitioning is a useful tool for modelling these multiallelic systems.
Identification of T1D susceptibility genes within the MHC region by combining protein interaction networks and SNP genotyping data
Authors: Brorsson C. , Hansen N. T. , Lage K. , Bergholdt R. , Brunak S. , Pociot F. ,   Diabetes Genetics Consortium
Published: January 2009

Aim:  To develop novel methods for identifying new genes that contribute to the risk of developing type 1 diabetes within the Major Histocompatibility Complex (MHC) region on chromosome 6, independently of the known linkage disequilibrium (LD) between human leucocyte antigen (HLA)‐DRB1, ‐DQA1, ‐DQB1 genes.Methods:  We have developed a novel method that combines single nucleotide polymorphism (SNP) genotyping data with protein–protein interaction (ppi) networks to identify disease‐associated network modules enriched for proteins encoded from the MHC region. Approximately 2500 SNPs located in the 4 Mb MHC region were analysed in 1000 affected offspring trios generated by the Type 1 Diabetes Genetics Consortium (T1DGC). The most associated SNP in each gene was chosen and genes were mapped to ppi networks for identification of interaction partners. The association testing and resulting interacting protein modules were statistically evaluated using permutation.Results:  A total of 151 genes could be mapped to nodes within the protein interaction network and their interaction partners were identified. Five protein interaction modules reached statistical significance using this approach. The identified proteins are well known in the pathogenesis of T1D, but the modules also contain additional candidates that have been implicated in β‐cell development and diabetic complications.Conclusions:  The extensive LD within the MHC region makes it important to develop new methods for analysing genotyping data for identification of additional risk genes for T1D. Combining genetic data with knowledge about functional pathways provides new insight into mechanisms underlying T1D.
Effect of linkage status of affected sib‐pairs on the search for novel type 1 diabetes susceptibility genes in the HLA complex
Authors: Morahan G. , Mehta M. , McKinnon E. , James I. ,   Diabetes Genetics Consortium
Published: January 2009

Aim:  Type 1 diabetes susceptibility is influenced by a number of genes, of which those with the strongest effects map to the human leucocyte antigen (HLA) complex. Evidence for linkage of non‐HLA genes in several affected sib‐pair analyses was increased if the HLA or gender status of the sibs was considered independently. We investigated whether linkage status at the HLA complex differentially affected transmission of alleles to sibs depending on their HLA or gender linkage status.Methods:  Genotypes of 2437 markers typed on 11 279 individuals from 2363 families, stratified according to HLA and gender, were examined using the transmission disequilibrium test.Results:  Several significant single nucleotide polymorphisms (SNPs) loci were found near the class II genes; no significant SNPs were found by these analyses near the class I or class II genes. Other significant effects were found when the gender of the sibs or the parents was considered. There was not a significant difference in HLA‐DRB genotypes between the stratified sets.Conclusions:  These results suggest the presence of novel recessive susceptibility gene(s) within the HLA complex.
Mating in parents of type 1 diabetes families as a function of the HLA DR‐DQ haplotype
Authors: Kahles H. , Kordonouri O. , Ramos Lopez E. , Walter M. , Rosinger S. , Boehm B. O. , Badenhoop K. , Seidl C. , Ziegler A. ,   Diabetes Genetics Consortium
Published: January 2009

Aim:  The Major Histocompatibility Complex (MHC) region on chromosome 6p21 (IDDM1) contributes about half of the familial clustering of type 1 diabetes (T1D). Several studies have revealed that highly polymorphic genes within the MHC may associate with the mating choice. Our study should determine whether a specific mating effect is detectable in T1D families as a function of human leucocyte antigen (HLA) DR‐DQ, which could contribute to disease susceptibility.Methods:  We analysed the parental HLA‐DR genotypes in 829 diabetic families. The families derive from the Type 1 Diabetes Genetics Consortium (T1DGC) in addition to those of our own centre and the original UK, US and SCAND diabetic families.Results:  A total of 307 of 829 parental couples (37.0%) were matched for at least one known T1D risk haplotype (DR3 or DR4), which is significantly less than the expected 374.9 (45.2%), derived from population genotype frequencies (p < 0.0009). Parents share less susceptibility haplotypes and rather complement each other as both carry one different risk haplotype (DR3 or DR4). The number of such parental couples was significantly higher than expected (293 vs. 223.4; p < 0.0003). All non‐transmitted DR haplotype pairs were also analysed. More often than expected, both parents did not transmit DR1 (94 vs. 59.1; p < 0.003) and DRy (y: not DR1, not DR3, not DR4; 63 vs. 30.3; p < 0.0005). In contrast, the parental non‐transmitted pair of haplotypes DR1‐DRy was observed to a far lesser extent than expected (26 vs. 84.7; p < 10‐8). These observations were only made in multiplex families, whereas in simplex families, no deviation from the expected frequencies was observed.Conclusions:  Our data are consistent with the conclusion that genes in the HLA region may influence the mating choice in parents of T1D patients, thus contributing to familial clustering of T1D in multiplex families. This may indicate a different parental background of multiplex compared with simplex T1D families.
Missingness in the T1DGC MHC fine‐mapping SNP data: association with HLA genotype and potential influence on genetic association studies
Authors: James I. , McKinnon E. , Gaudieri S. , Morahan G. ,   Diabetes Genetics Consortium
Published: January 2009

Aim:  The absence or ‘missingness’ of single nucleotide polymorphism (SNP) assay values because of genotype or related factors of interest may bias association and other studies. Missingness was determined for the Type 1 Diabetes Genetics Consortium (T1DGC) Major Histocompatibility Complex (MHC) data and was found to vary across the region, ranging up to 11.1% of the non‐null proband SNPs, with a median of 0.3%. We consider factors related to missingness in the T1DGC data and briefly assess its possible influence on association studies.Methods:  We assessed associations of missingness in the SNP assay data with human leucocyte antigen (HLA) genotype of the individual and with SNP genotypes of the parents. Within‐cohort analyses were combined (over all cohorts) using (i) Mantel–Haenszel tests for two‐by‐two tables or (ii) by combining test statistics for larger tables and regression models. Mixed effect regression models were used to assess association of the SNP genotypes with affected status of the offspring after adjustment for parental SNP genotypes, cohort membership and HLA genotypes. Log‐linear models were used to assess association of missingness in the unaffected sib assays with SNP genotypes of the probands.Results:  Missingness of SNP values near the HLA class I (A, B and C) and class II (DR, DQ and DP) loci is strongly associated with carriage of corresponding HLA genotypes within these groups. Similar associations pertain to missing values among the microsatellite data. In at least some of these cases, regions of missingness coincided with known deletion regions corresponding to the associated HLA haplotype. We conjecture that other regions of associated missingness may point to similar haplotypic deletions. Analysis of association patterns of SNP genotypes with affected status of offspring does not indicate strong informative missingness. However, association of missingness in proband data with parental SNP genotypes may impact transmission disequilibrium test (TDT)‐type analyses. Comparisons of affected and unaffected siblings point to possible susceptibility regions additional to the classical HLA‐DR3/4 alleles near BAT4‐LY6G5B‐BAT5 and NOTCH4.Conclusions:  Potentially informative missingness in SNP assay values in the MHC region may impact on association and related analyses based on the T1DGC data. These results suggest that it would be prudent to assess the degree to which missingness may abrogate assessed SNP disease markers in such studies. Initial analyses based on comparison of affected and unaffected status in offspring suggest that at least these may be little affected.