Methylation Defect in Imprinted Genes Detected in Patients with an Albright's Hereditary Osteodystrophy Like Phenotype and Platelet Gs Hypofunction

Pseudohypoparathyroidism (PHP) indicates a group of heterogeneous disorders whose common feature is represented by impaired signaling of hormones that activate Gsalpha, encoded by the imprinted GNAS gene. PHP-Ib patients have isolated Parathormone (PTH) resistance and GNAS epigenetic defects while PHP-Ia cases present with hormone resistance and characteristic features jointly termed as Albright's Hereditary Osteodystrophy (AHO) due to maternally inherited GNAS mutations or similar epigenetic defects as found for PHP-Ib. Pseudopseudohypoparathyroidism (PPHP) patients with an AHO phenotype and no hormone resistance and progressive osseous heteroplasia (POH) cases have inactivating paternally inherited GNAS mutations.We here describe 17 subjects with an AHO-like phenotype that could be compatible with having PPHP but none of them carried Gsalpha mutations. Functional platelet studies however showed an obvious Gs hypofunction in the 13 patients that were available for testing. Methylation for the three differentially methylated GNAS regions was quantified via the Sequenom EpiTYPER. Patients showed significant hypermethylation of the XL amplicon compared to controls (36 ± 3 vs. 29 ± 3%; p<0.001); a pattern that is reversed to XL hypomethylation found in PHPIb. Interestingly, XL hypermethylation was associated with reduced XLalphaS protein levels in the patients' platelets. Methylation for NESP and ExonA/B was significantly different for some but not all patients, though most patients have site-specific CpG methylation abnormalities in these amplicons. Since some AHO features are present in other imprinting disorders, the methylation of IGF2, H19, SNURF and GRB10 was quantified. Surprisingly, significant IGF2 hypermethylation (20 ± 10 vs. 14 ± 7%; p<0.05) and SNURF hypomethylation (23 ± 6 vs. 32 6%; p<0.001) was found in patients vs. controls, while H19 and GRB10 methylation was normal.In conclusion, this is the first report of methylation defects including GNAS in patients with an AHO-like phenotype without endocrinological abnormalities. Additional studies are still needed to correlate the methylation defect with the clinical phenotype

Quantification of the methylation at the GNAS locus identifies subtypes of sporadic pseudohypoparathyroidism type Ib

Particulate matter (PM) is a class of malicious environmental pollutants known to be detrimental to human health. Regulatory efforts aimed at curbing PM levels in different countries often require high resolution space–time maps that can identify red-flag regions exceeding statutory concentration limits. Continuous spatio-temporal Gaussian Process (GP) models can deliver maps depicting predicted PM levels and quantify predictive uncertainty. However, GP-based approaches are usually thwarted by computational challenges posed by large datasets. We construct a novel class of scalable Dynamic Nearest Neighbor Gaussian Process (DNNGP) models that can provide a sparse approximation to any spatio-temporal GP (e.g., with nonseparable covariance structures). The DNNGP we develop here can be used as a sparsity-inducing prior for spatio-temporal random effects in any Bayesian hierarchical model to deliver full posterior inference. Storage and memory requirements for a DNNGP model are linear in the size of the dataset, thereby delivering massive scalability without sacrificing inferential richness. Extensive numerical studies reveal that the DNNGP provides substantially superior approximations to the underlying process than low-rank approximations. Finally, we use the DNNGP to analyze a massive air quality dataset to substantially improve predictions of PM levels across Europe in conjunction with the LOTOS-EUROS chemistry transport models (CTMs). © Institute of Mathematical Statistics, 2016

Contribution of Chronic Myeloid Leukaemia (CML) as a Disease Model to Define and Study Clonal Heterogeneity

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