30 research outputs found
Galectin-1 prevents pathological vascular remodeling in atherosclerosis and abdominal aortic aneurysm
Pathological vascular remodeling is the underlying cause of atherosclerosis and abdominal aortic aneurysm (AAA). Here, we analyzed the role of galectin-1 (Gal-1), a β-galactoside-binding protein, as a therapeutic target for atherosclerosis and AAA. Mice lacking Gal-1 (Lgals1 −/− ) developed severe atherosclerosis induced by pAAV/D377Y-mPCSK9 adenovirus and displayed higher lipid levels and lower expression of contractile markers of vascular smooth muscle cells (VSMCs) in plaques than wild-type mice. Proteomic analysis of Lgals1 −/− aortas showed changes in markers of VSMC phenotypic switch and altered composition of mitochondrial proteins. Mechanistically, Gal-1 silencing resulted in increased foam cell formation and mitochondrial dysfunction in VSMCs, while treatment with recombinant Gal-1 (rGal-1) prevented these effects. Furthermore, rGal-1 treatment attenuated atherosclerosis and elastase-induced AAA, leading to higher contractile VSMCs in aortic tissues. Gal-1 expression decreased in human atheroma and AAA compared to control tissue. Thus, Gal-1-driven circuits emerge as potential therapeutic strategies in atherosclerosis and AAA. Galectin-1 plays an essential role in prevention of atherosclerosis and abdominal aortic aneurysm
Energy Estimation of Cosmic Rays with the Engineering Radio Array of the Pierre Auger Observatory
The Auger Engineering Radio Array (AERA) is part of the Pierre Auger
Observatory and is used to detect the radio emission of cosmic-ray air showers.
These observations are compared to the data of the surface detector stations of
the Observatory, which provide well-calibrated information on the cosmic-ray
energies and arrival directions. The response of the radio stations in the 30
to 80 MHz regime has been thoroughly calibrated to enable the reconstruction of
the incoming electric field. For the latter, the energy deposit per area is
determined from the radio pulses at each observer position and is interpolated
using a two-dimensional function that takes into account signal asymmetries due
to interference between the geomagnetic and charge-excess emission components.
The spatial integral over the signal distribution gives a direct measurement of
the energy transferred from the primary cosmic ray into radio emission in the
AERA frequency range. We measure 15.8 MeV of radiation energy for a 1 EeV air
shower arriving perpendicularly to the geomagnetic field. This radiation energy
-- corrected for geometrical effects -- is used as a cosmic-ray energy
estimator. Performing an absolute energy calibration against the
surface-detector information, we observe that this radio-energy estimator
scales quadratically with the cosmic-ray energy as expected for coherent
emission. We find an energy resolution of the radio reconstruction of 22% for
the data set and 17% for a high-quality subset containing only events with at
least five radio stations with signal.Comment: Replaced with published version. Added journal reference and DO
Measurement of the Radiation Energy in the Radio Signal of Extensive Air Showers as a Universal Estimator of Cosmic-Ray Energy
We measure the energy emitted by extensive air showers in the form of radio
emission in the frequency range from 30 to 80 MHz. Exploiting the accurate
energy scale of the Pierre Auger Observatory, we obtain a radiation energy of
15.8 \pm 0.7 (stat) \pm 6.7 (sys) MeV for cosmic rays with an energy of 1 EeV
arriving perpendicularly to a geomagnetic field of 0.24 G, scaling
quadratically with the cosmic-ray energy. A comparison with predictions from
state-of-the-art first-principle calculations shows agreement with our
measurement. The radiation energy provides direct access to the calorimetric
energy in the electromagnetic cascade of extensive air showers. Comparison with
our result thus allows the direct calibration of any cosmic-ray radio detector
against the well-established energy scale of the Pierre Auger Observatory.Comment: Replaced with published version. Added journal reference and DOI.
Supplemental material in the ancillary file
Measurement of the cosmic ray spectrum above eV using inclined events detected with the Pierre Auger Observatory
A measurement of the cosmic-ray spectrum for energies exceeding
eV is presented, which is based on the analysis of showers
with zenith angles greater than detected with the Pierre Auger
Observatory between 1 January 2004 and 31 December 2013. The measured spectrum
confirms a flux suppression at the highest energies. Above
eV, the "ankle", the flux can be described by a power law with
index followed by
a smooth suppression region. For the energy () at which the
spectral flux has fallen to one-half of its extrapolated value in the absence
of suppression, we find
eV.Comment: Replaced with published version. Added journal reference and DO
Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees
Significance
Contributions of rare variants to common and complex traits such as type 2 diabetes (T2D) are difficult to measure. This paper describes our results from deep whole-genome analysis of large Mexican-American pedigrees to understand the role of rare-sequence variations in T2D and related traits through enriched allele counts in pedigrees. Our study design was well-powered to detect association of rare variants if rare variants with large effects collectively accounted for large portions of risk variability, but our results did not identify such variants in this sample. We further quantified the contributions of common and rare variants in gene expression profiles and concluded that rare expression quantitative trait loci explain a substantive, but minor, portion of expression heritability.</jats:p
A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data
Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants
Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps
We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci,135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency 2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).Peer reviewe