24 research outputs found

    Integrative Analysis Reveals a Molecular Stratification of Systemic Autoimmune Diseases

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    Objective Clinical heterogeneity, a hallmark of systemic autoimmune diseases, impedes early diagnosis and effective treatment, issues that may be addressed if patients could be classified into groups defined by molecular pattern. This study was undertaken to identify molecular clusters for reclassifying systemic autoimmune diseases independently of clinical diagnosis. Methods Unsupervised clustering of integrated whole blood transcriptome and methylome cross-sectional data on 955 patients with 7 systemic autoimmune diseases and 267 healthy controls was undertaken. In addition, an inception cohort was prospectively followed up for 6 or 14 months to validate the results and analyze whether or not cluster assignment changed over time. Results Four clusters were identified and validated. Three were pathologic, representing “inflammatory,” “lymphoid,” and “interferon” patterns. Each included all diagnoses and was defined by genetic, clinical, serologic, and cellular features. A fourth cluster with no specific molecular pattern was associated with low disease activity and included healthy controls. A longitudinal and independent inception cohort showed a relapse–remission pattern, where patients remained in their pathologic cluster, moving only to the healthy one, thus showing that the molecular clusters remained stable over time and that single pathogenic molecular signatures characterized each individual patient. Conclusion Patients with systemic autoimmune diseases can be jointly stratified into 3 stable disease clusters with specific molecular patterns differentiating different molecular disease mechanisms. These results have important implications for future clinical trials and the study of nonresponse to therapy, marking a paradigm shift in our view of systemic autoimmune diseases

    Integration of new biological and physical retrospective dosimetry methods into EU emergency response plans : joint RENEB and EURADOS inter-laboratory comparisons

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    Purpose: RENEB, 'Realising the European Network of Biodosimetry and Physical Retrospective Dosimetry,' is a network for research and emergency response mutual assistance in biodosimetry within the EU. Within this extremely active network, a number of new dosimetry methods have recently been proposed or developed. There is a requirement to test and/or validate these candidate techniques and inter-comparison exercises are a well-established method for such validation. Materials and methods: The authors present details of inter-comparisons of four such new methods: dicentric chromosome analysis including telomere and centromere staining; the gene expression assay carried out in whole blood; Raman spectroscopy on blood lymphocytes, and detection of radiation induced thermoluminescent signals in glass screens taken from mobile phones. Results: In general the results show good agreement between the laboratories and methods within the expected levels of uncertainty, and thus demonstrate that there is a lot of potential for each of the candidate techniques. Conclusions: Further work is required before the new methods can be included within the suite of reliable dosimetry methods for use by RENEB partners and others in routine and emergency response scenarios

    A Roadmap for HEP Software and Computing R&D for the 2020s

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    Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware, either to build new facilities and experiments, or to upgrade existing ones. Similarly, it requires commensurate investment in the R&D of software to acquire, manage, process, and analyse the shear amounts of data to be recorded. In planning for the HL-LHC in particular, it is critical that all of the collaborating stakeholders agree on the software goals and priorities, and that the efforts complement each other. In this spirit, this white paper describes the R&D activities required to prepare for this software upgrade.Peer reviewe

    O31 Integrative analysis reveals a molecular stratification of systemic autoimmune diseases

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    Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations

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    Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10−9, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies. Delineation of the genetic architecture of hematological traits in a multi-ethnic dataset allows identification of rare variants with strong effects specific to non-European populations and improved fine mapping of GWAS variants using the trans-ethnic approach

    Microbial fuel cell using activated sludge as the substrate

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    A microbial fuel cell utilizes the natural metabolic activities of microorganisms in the production of electrical power. The objectives of this project were (1) to determine the feasibility of using activated sludge as the microbe for a microbial fuel cell, (2) to determine the optimal setup to yield the most electrical power, and (3) to evaluate the scale up of our microbial fuel cell. The results of this project indicate that activated sludge is capable of generating electrical power, the simplified cell being the best setup, and the scale up of the model could potentially power a wastewater treatment plant

    Validating genetic markers of response to recombinant human growth hormone (r-hGH) in children with growth hormone deficiency (GHD) and Turner Syndrome (TS): The PREDICT Validation study

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    OBJECTIVE: Single-nucleotide polymorphisms (SNPs) associated with the response to recombinant human growth hormone (r-hGH) have previously been identified in growth hormone deficiency (GHD) and Turner syndrome (TS) children in the PREDICT long-term follow-up (LTFU) study (Nbib699855). Here, we describe the PREDICT validation (VAL) study (Nbib1419249), which aimed to confirm these genetic associations. DESIGN AND METHODS: Children with GHD (n = 293) or TS (n = 132) were recruited retrospectively from 29 sites in nine countries. All children had completed 1 year of r-hGH therapy. 48 SNPs previously identified as associated with first year growth response to r-hGH were genotyped. Regression analysis was used to assess the association between genotype and growth response using clinical/auxological variables as covariates. Further analysis was undertaken using random forest classification. RESULTS: The children were younger, and the growth response was higher in VAL study. Direct genotype analysis did not replicate what was found in the LTFU study. However, using exploratory regression models with covariates, a consistent relationship with growth response in both VAL and LTFU was shown for four genes – SOS1 and INPPL1 in GHD and ESR1 and PTPN1 in TS. The random forest analysis demonstrated that only clinical covariates were important in the prediction of growth response in mild GHD (>4 to <10 μg/L on GH stimulation test), however, in severe GHD (≤4 μg/L) several SNPs contributed (in IGF2, GRB10, FOS, IGFBP3 and GHRHR). CONCLUSIONS: The PREDICT validation study supports, in an independent cohort, the association of four of 48 genetic markers with growth response to r-hGH treatment in both pre-pubertal GHD and TS children after controlling for clinical/auxological covariates. However, the contribution of these SNPs in a prediction model of first-year response is not sufficient for routine clinical use

    Near infrared overtone (v(OH)=2 <- 0) spectroscopy of Ne-H2O clusters

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    Vibrationally state selective overtone spectroscopy and dynamics of weakly bound Ne-H2O complexes (D0(para) = 31.67 cm-1, D0(ortho) = 34.66 cm-1) are reported for the first time, based on near infrared excitation of van der Waals cluster bands correlating with vOH = 2 ← 0 overtone transitions (|02-⟩←|00+⟩ and |02+⟩←|00+⟩) out of the ortho (101) and para (000) internal rotor states of the H2O moiety. Quantum theoretical calculations for nuclear motion on a high level ab initio potential energy surface (CCSD(T)/VnZ-f12 (n = 3,4), corrected for basis set superposition error and extrapolated to the complete basis set limit) are employed for assignment of Σ←Σ,Π←Σ, and Σ←Π infrared bands in the overtone spectra, where Σ(K = 0) and Π (K = 1) represent approximate projections (K) of the body angular momentum along the Ne-H2O internuclear axis. End-over-end tumbling of the ortho Ne-H2O cluster is evident via rotational band contours observed, with band origins and rotational progressions in excellent agreement with ab initio frequency and intensity predictions. A clear Q branch in the corresponding |02+⟩fΠ(111)←eΣ(000) para Ne-H2O spectrum provides evidence for a novel e/f parity-dependent metastability in these weakly bound clusters, in agreement with ab initio bound state calculations and attributable to the symmetry blocking of an energetically allowed channel for internal rotor predissociation. Finally, Boltzmann analysis of the rotational spectra reveals anomalously low jet temperatures (Trot ≈ 4(1) K), which are attributed to "evaporative cooling" of weakly bound Ne-H2O clusters and provide support for similar cooling dynamics in rare gas-tagging studies.status: publishe

    GH deficiency status combined with GH receptor polymorphism affects response to GH in children.

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    Meta-analysis has shown a modest improvement in first-year growth response to recombinant human GH (r-hGH) for carriers of the exon 3-deleted GH receptor (GHRd3) polymorphism but with significant interstudy variability. The associations between GHRd3 and growth response to r-hGH over 3 years in relation to severity of GH deficiency (GHD) were investigated in patients from 14 countries. Treatment-naïve pre-pubertal children with GHD were enrolled from the PREDICT studies (NCT00256126 and NCT00699855), categorized by peak GH level (peak GH) during provocation test: ≤4 μg/l (severe GHD; n=45) and >4 to <10 μg/l mild GHD; n=49) and genotyped for the GHRd3 polymorphism (full length (fl/fl, fl/d3, d3/d3). Gene expression (GE) profiles were characterized at baseline. Changes in growth (height (cm) and SDS) over 3 years were measured. There was a dichotomous influence of GHRd3 polymorphism on response to r-hGH, dependent on peak GH level. GH peak level (higher vs lower) and GHRd3 (fl/fl vs d3 carriers) combined status was associated with height change over 3 years (P<0.05). GHRd3 carriers with lower peak GH had lower growth than subjects with fl/fl (median difference after 3 years -3.3 cm; -0.3 SDS). Conversely, GHRd3 carriers with higher peak GH had better growth (+2.7 cm; +0.2 SDS). Similar patterns were observed for GH-dependent biomarkers. GE profiles were significantly different between the groups, indicating that the interaction between GH status and GHRd3 carriage can be identified at a transcriptomic level. This study demonstrates that responses to r-hGH depend on the interaction between GHD severity and GHRd3 carriage
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