Novel IL2RG Mutation Causes Leaky TLOWB+NK+ SCID With Nodular Regenerative Hyperplasia and Normal IL-15 STAT5 Phosphorylation

X-linked severe combined immunodeficiency disease (SCID) is caused by mutations in the interleukin (IL)-2 receptor γ (IL2RG) gene and patients usually present with a TBNK SCID phenotype. Nevertheless, a minority of these patients present with a TBNK phenotype, similar to the IL-7R-deficient patients. We report a patient with a novel missense p.Glu297Gly mutation in the IL2RG gene presenting with a leaky TBNK SCID with delayed onset, moderate susceptibility to infections, and nodular regenerative hyperplasia. He presents with preserved STAT5 tyrosine phosphorylation in response to IL-15 stimulation but not in response to IL-2 and IL-7, resulting in the NK phenotype.info:eu-repo/semantics/publishedVersio

Inference of disease associations with unmeasured genetic variants by combining results from genome-wide association studies with linkage disequilibrium patterns in a reference data set

Results from whole-genome association studies of many common diseases are now available. Increasingly, these are being incorporated into meta-analyses to increase the power to detect weak associations with measured single-nucleotide polymorphisms (SNPs). Imputation of genotypes at unmeasured loci has been widely applied using patterns of linkage disequilibrium (LD) observed in the HapMap panels, but there is a need for alternative methods that can utilize the pooled effect estimates from meta-analyses and explore possible associations with SNPs and haplotypes that are not included in HapMap

Reevaluation of SNP heritability in complex human traits

SNP heritability, the proportion of phenotypic variance explained by SNPs, has been reported for many hundreds of traits. Its estimation requires strong prior assumptions about the distribution of heritability across the genome, but current assumptions have not been thoroughly tested. By analyzing imputed data for a large number of human traits, we empirically derive a model that more accurately describes how heritability varies with minor allele frequency (MAF), linkage disequilibrium (LD) and genotype certainty. Across 19 traits, our improved model leads to estimates of common SNP heritability on average 43% (s.d. 3%) higher than those obtained from the widely used software GCTA and 25% (s.d. 2%) higher than those from the recently proposed extension GCTA-LDMS. Previously, DNase I hypersensitivity sites were reported to explain 79% of SNP heritability; using our improved heritability model, their estimated contribution is only 24%

Evaluation of the association between the common E469K polymorphism in the ICAM-1 gene and diabetic nephropathy among type 1 diabetic patients in GoKinD population

<p>Abstract</p> <p>Background</p> <p>The ICAM-1 gene is a strong positional and biological candidate for susceptibility to the development of T1D and DN. We have recently demonstrated that SNP rs5498(E469K) confers susceptibility to the development of T1D and might be associated with DN in Swedish Caucasians. The present study aimed to further evaluate the association between the ICAM-1 genetic polymorphisms and DN.</p> <p>Methods</p> <p>Two common non-synonymous SNPs, including rs5498(E469K) and rs1799969(R241G), in the ICAM-1 gene were genotyped in 662 (312 female/350 male) T1D patients with DN and 620 (369/251) without DN. All patients were selected from the GoKinD study.</p> <p>Results</p> <p>Genotype distributions of both SNPs were in Hardy-Weinberg equilibrium but SNP rs5498(E469K) had high heterozygous index. In this SNP, the heterozygosity and positivity for the allele G were found to be significantly associated with DN in female T1D patients (P = 0.010, OR = 0.633, CI 95% 0.447–0.895 and P = 0.026, OR = 0.692, CI 95% 0.500–0.958). Furthermore, the female patients without DN carrying three genotypes A/A, A/G and G/G had different cystatin levels (0.79 ± 0.17, 0.81 ± 0.14 and 0.75 ± 0.12 mg/L, P = 0.021). No significant association of SNP rs1799969 (R241G) with DN was found.</p> <p>Conclusion</p> <p>The present study provides further evidence that SNP rs5498(E469K) in the ICAM-1 gene presents a high heterozygous index and the allele G of this polymorphism may confers the decreased risk susceptibility to the development of DN in female T1D patients among the GoKinD population.</p

Microevolution of extensively drug-resistant tuberculosis in Russia.

Extensively drug-resistant (XDR) tuberculosis (TB), which is resistant to both first- and second-line antibiotics, is an escalating problem, particularly in the Russian Federation. Molecular fingerprinting of 2348 Mycobacterium tuberculosis isolates collected in Samara Oblast, Russia, revealed that 72%belonged to the Beijing lineage, a genotype associated with enhanced acquisition of drug resistance and increased virulence. Whole-genome sequencing of 34 Samaran isolates, plus 25 isolates representing global M. tuberculosis complex diversity, revealed that Beijing isolates originating in Eastern Europe formed a monophyletic group. Homoplasic polymorphisms within this clade were almost invariably associated with antibiotic resistance, indicating that the evolution of this population is primarily driven by drug therapy. Resistance genotypes showed a strong correlation with drug susceptibility phenotypes. A novel homoplasic mutation in rpoC, found only in isolates carrying a common rpoB rifampicin-resistance mutation, may play a role in fitness compensation. Most multidrug-resistant (MDR) isolates also had mutations in the promoter of a virulence gene, eis, which increase its expression and confer kanamycin resistance. Kanamycin therapy may thus select for mutants with increased virulence, helping preserve bacterial fitness and promoting transmission of drug-resistant TB strains. The East European clade was dominated by two MDR clusters, each disseminated across Samara. Polymorphisms conferring fluoroquinolone resistance were independently acquired multiple times within each cluster, indicating that XDR TB is currently not widely transmitted. © 2012 by Cold Spring Harbor Laboratory Press

A Classifier-based approach to identify genetic similarities between diseases

Motivation: Genome-wide association studies are commonly used to identify possible associations between genetic variations and diseases. These studies mainly focus on identifying individual single nucleotide polymorphisms (SNPs) potentially linked with one disease of interest. In this work, we introduce a novel methodology that identifies similarities between diseases using information from a large number of SNPs. We separate the diseases for which we have individual genotype data into one reference disease and several query diseases. We train a classifier that distinguishes between individuals that have the reference disease and a set of control individuals. This classifier is then used to classify the individuals that have the query diseases. We can then rank query diseases according to the average classification of the individuals in each disease set, and identify which of the query diseases are more similar to the reference disease. We repeat these classification and comparison steps so that each disease is used once as reference disease

Biallelic JAK1 mutations in immunodeficient patient with mycobacterial infection

Mutations in genes encoding components of the immune system cause primary immunodeficiencies. Here, we study a patient with recurrent atypical mycobacterial infection and early-onset metastatic bladder carcinoma. Exome sequencing identified two homozygous missense germline mutations, P733L and P832S, in the JAK1 protein that mediates signalling from multiple cytokine receptors. Cells from this patient exhibit reduced JAK1 and STAT phosphorylation following cytokine stimulations, reduced induction of expression of interferon-regulated genes and dysregulated cytokine production; which are indicative of signalling defects in multiple immune response pathways including Interferon-γ production. Reconstitution experiments in the JAK1-deficient cells demonstrate that the impaired JAK1 function is mainly attributable to the effect of the P733L mutation. Further analyses of the mutant protein reveal a phosphorylation-independent role of JAK1 in signal transduction. These findings clarify JAK1 signalling mechanisms and demonstrate a critical function of JAK1 in protection against mycobacterial infection and possibly the immunological surveillance of cancer.Wellcome Trust (095198/Z/10/Z and 090233/Z/09/Z); Higher Education Funding Council for England; Great Ormond Street Hospital Children’s Charity; National Institute for Health Research (NIHR); Great Ormond Street Hospital Biomedical Research Centre; NIHR Cambridge Biomedical Research Centre; Alfonso Martin Escudero Foundatio

Digging into the extremes: a useful approach for the analysis of rare variants with continuous traits?

The common disease/rare variant hypothesis predicts that rare variants with large effects will have a strong impact on corresponding phenotypes. Therefore it is assumed that rare functional variants are enriched in the extremes of the phenotype distribution. In this analysis of the Genetic Analysis Workshop 17 data set, my aim is to detect genes with rare variants that are associated with quantitative traits using two general approaches: analyzing the association with the complete distribution of values by means of linear regression and using statistical tests based on the tails of the distribution (bottom 10% of values versus top 10%). Three methods are used for this extreme phenotype approach: Fisher’s exact test, weighted-sum method, and beta method. Rare variants were collapsed on the gene level. Linear regression including all values provided the highest power to detect rare variants. Of the three methods used in the extreme phenotype approach, the beta method performed best. Furthermore, the sample size was enriched in this approach by adding additional samples with extreme phenotype values. Doubling the sample size using this approach, which corresponds to only 40% of sample size of the original continuous trait, yielded a comparable or even higher power than linear regression. If samples are selected primarily for sequencing, enriching the analysis by gathering a greater proportion of individuals with extreme values in the phenotype of interest rather than in the general population leads to a higher power to detect rare variants compared to analyzing a population-based sample with equivalent sample size