61 research outputs found
Hundreds of variants clustered in genomic loci and biological pathways affect human height
Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (Pâ<â0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.
Identification and reconstruction of low-energy electrons in the ProtoDUNE-SP detector
Measurements of electrons from interactions are crucial for the Deep
Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as
searches for physics beyond the standard model, supernova neutrino detection,
and solar neutrino measurements. This article describes the selection and
reconstruction of low-energy (Michel) electrons in the ProtoDUNE-SP detector.
ProtoDUNE-SP is one of the prototypes for the DUNE far detector, built and
operated at CERN as a charged particle test beam experiment. A sample of
low-energy electrons produced by the decay of cosmic muons is selected with a
purity of 95%. This sample is used to calibrate the low-energy electron energy
scale with two techniques. An electron energy calibration based on a cosmic ray
muon sample uses calibration constants derived from measured and simulated
cosmic ray muon events. Another calibration technique makes use of the
theoretically well-understood Michel electron energy spectrum to convert
reconstructed charge to electron energy. In addition, the effects of detector
response to low-energy electron energy scale and its resolution including
readout electronics threshold effects are quantified. Finally, the relation
between the theoretical and reconstructed low-energy electron energy spectrum
is derived and the energy resolution is characterized. The low-energy electron
selection presented here accounts for about 75% of the total electron deposited
energy. After the addition of lost energy using a Monte Carlo simulation, the
energy resolution improves from about 40% to 25% at 50~MeV. These results are
used to validate the expected capabilities of the DUNE far detector to
reconstruct low-energy electrons.Comment: 19 pages, 10 figure
Impact of cross-section uncertainties on supernova neutrino spectral parameter fitting in the Deep Underground Neutrino Experiment
A primary goal of the upcoming Deep Underground Neutrino Experiment (DUNE) is
to measure the MeV neutrinos produced by a Galactic
core-collapse supernova if one should occur during the lifetime of the
experiment. The liquid-argon-based detectors planned for DUNE are expected to
be uniquely sensitive to the component of the supernova flux, enabling
a wide variety of physics and astrophysics measurements. A key requirement for
a correct interpretation of these measurements is a good understanding of the
energy-dependent total cross section for charged-current
absorption on argon. In the context of a simulated extraction of
supernova spectral parameters from a toy analysis, we investigate the
impact of modeling uncertainties on DUNE's supernova neutrino
physics sensitivity for the first time. We find that the currently large
theoretical uncertainties on must be substantially reduced
before the flux parameters can be extracted reliably: in the absence of
external constraints, a measurement of the integrated neutrino luminosity with
less than 10\% bias with DUNE requires to be known to about 5%.
The neutrino spectral shape parameters can be known to better than 10% for a
20% uncertainty on the cross-section scale, although they will be sensitive to
uncertainties on the shape of . A direct measurement of
low-energy -argon scattering would be invaluable for improving the
theoretical precision to the needed level.Comment: 25 pages, 21 figure
Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas
Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (, , ) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types
Highly-parallelized simulation of a pixelated LArTPC on a GPU
The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype
The DUNE far detector vertical drift technology. Technical design report
DUNE is an international experiment dedicated to addressing some of the questions at the forefront of particle physics and astrophysics, including the mystifying preponderance of matter over antimatter in the early universe. The dual-site experiment will employ an intense neutrino beam focused on a near and a far detector as it aims to determine the neutrino mass hierarchy and to make high-precision measurements of the PMNS matrix parameters, including the CP-violating phase. It will also stand ready to observe supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector implements liquid argon time-projection chamber (LArTPC) technology, and combines the many tens-of-kiloton fiducial mass necessary for rare event searches with the sub-centimeter spatial resolution required to image those events with high precision. The addition of a photon detection system enhances physics capabilities for all DUNE physics drivers and opens prospects for further physics explorations. Given its size, the far detector will be implemented as a set of modules, with LArTPC designs that differ from one another as newer technologies arise. In the vertical drift LArTPC design, a horizontal cathode bisects the detector, creating two stacked drift volumes in which ionization charges drift towards anodes at either the top or bottom. The anodes are composed of perforated PCB layers with conductive strips, enabling reconstruction in 3D. Light-trap-style photon detection modules are placed both on the cryostat's side walls and on the central cathode where they are optically powered. This Technical Design Report describes in detail the technical implementations of each subsystem of this LArTPC that, together with the other far detector modules and the near detector, will enable DUNE to achieve its physics goals
Higher Serum Free Testosterone Concentration in Older Women Is Associated with Greater Bone Mineral Density, Lean Body Mass, and Total Fat Mass: The Cardiovascular Health Study
Higher serum testosterone is associated with higher bone mineral density, greater lean body mass, and greater total fat mass in women aged 65 and older
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