Identity-by-descent filtering as a tool for the identification of disease alleles in exome sequence data from distant relatives

Large-scale, deep resequencing may be the next logical step in the genetic investigation of common complex diseases. Because each individual is likely to carry many thousands of variants, the identification of causal alleles requires an efficient strategy to reduce the number of candidate variants. Under many genetic models, causal alleles can be expected to reside within identity-by-descent (IBD) regions shared by affected relatives. In distant relatives, IBD regions constitute a small portion of the genome and can thus greatly reduce the search space for causal alleles. However, the effectiveness of this strategy is unknown. We test the simulated mini-exome data set in extended pedigrees provided by Genetic Analysis Workshop 17. At the fourth- and fifth-degree level of relatedness, case-case pairs shared between 1% and 9% of the genome identical by descent. As expected, no genes were shared identical by descent by all case subjects, but 43 genes were shared by many case subjects across at least 50 replicates. We filtered variants in these genes based on population frequency, function, informativeness, and evidence of association using the family-based association test. This analysis highlighted five genes previously implicated in triglyceride, lipid, and cholesterol metabolism. Comparison with the list of true risk alleles revealed that strict IBD filtering followed by association testing of the rarest alleles was the most sensitive strategy. IBD filtering may be a useful strategy for narrowing down the list of candidate variants in exome data, but the optimal degree of relatedness of affected pairs will depend on the genetic architecture of the disease under study

Observation of an Excited Bc+ State

Using pp collision data corresponding to an integrated luminosity of 8.5 fb-1 recorded by the LHCb experiment at center-of-mass energies of s=7, 8, and 13 TeV, the observation of an excited Bc+ state in the Bc+π+π- invariant-mass spectrum is reported. The observed peak has a mass of 6841.2±0.6(stat)±0.1(syst)±0.8(Bc+) MeV/c2, where the last uncertainty is due to the limited knowledge of the Bc+ mass. It is consistent with expectations of the Bc∗(2S31)+ state reconstructed without the low-energy photon from the Bc∗(1S31)+→Bc+γ decay following Bc∗(2S31)+→Bc∗(1S31)+π+π-. A second state is seen with a global (local) statistical significance of 2.2σ (3.2σ) and a mass of 6872.1±1.3(stat)±0.1(syst)±0.8(Bc+) MeV/c2, and is consistent with the Bc(2S10)+ state. These mass measurements are the most precise to date

MCAM: Multiple Clustering Analysis Methodology for Deriving Hypotheses and Insights from High-Throughput Proteomic Datasets

Advances in proteomic technologies continue to substantially accelerate capability for generating experimental data on protein levels, states, and activities in biological samples. For example, studies on receptor tyrosine kinase signaling networks can now capture the phosphorylation state of hundreds to thousands of proteins across multiple conditions. However, little is known about the function of many of these protein modifications, or the enzymes responsible for modifying them. To address this challenge, we have developed an approach that enhances the power of clustering techniques to infer functional and regulatory meaning of protein states in cell signaling networks. We have created a new computational framework for applying clustering to biological data in order to overcome the typical dependence on specific a priori assumptions and expert knowledge concerning the technical aspects of clustering. Multiple clustering analysis methodology (‘MCAM’) employs an array of diverse data transformations, distance metrics, set sizes, and clustering algorithms, in a combinatorial fashion, to create a suite of clustering sets. These sets are then evaluated based on their ability to produce biological insights through statistical enrichment of metadata relating to knowledge concerning protein functions, kinase substrates, and sequence motifs. We applied MCAM to a set of dynamic phosphorylation measurements of the ERRB network to explore the relationships between algorithmic parameters and the biological meaning that could be inferred and report on interesting biological predictions. Further, we applied MCAM to multiple phosphoproteomic datasets for the ERBB network, which allowed us to compare independent and incomplete overlapping measurements of phosphorylation sites in the network. We report specific and global differences of the ERBB network stimulated with different ligands and with changes in HER2 expression. Overall, we offer MCAM as a broadly-applicable approach for analysis of proteomic data which may help increase the current understanding of molecular networks in a variety of biological problems.National Institutes of Health (U.S.) (NIH-U54-CA112967 )National Institutes of Health (U.S.) (NIH-R01-CA096504

Epithelial reticulon 4B (Nogo-B) is an endogenous regulator of Th2-driven lung inflammation

The reticulon protein Nogo-B is highly expressed in the lungs, and its loss augments lung inflammation in part as a result of decreased expression of the antiinflammatory protein PLUNC

An evolutionary approach to a combined mixed integer programming model of seaside operations as arise in container ports

This paper puts forward an integrated optimisation model that combines three distinct problems, namely berth allocation, quay crane assignment, and quay crane scheduling that arise in container ports. Each one of these problems is difficult to solve in its own right. However, solving them individually leads almost surely to sub-optimal solutions. Hence, it is desirable to solve them in a combined form. The model is of the mixed-integer programming type with the objective being to minimize the tardiness of vessels and reduce the cost of berthing. Experimental results show that relatively small instances of the proposed model can be solved exactly using CPLEX. Large scale instances, however, can only be solved in reasonable times using heuristics. Here, an implementation of the genetic algorithm is considered. The effectiveness of this implementation is tested against CPLEX on small to medium size instances of the combined model. Larger size instances were also solved with the genetic algorithm, showing that this approach is capable of finding the optimal or near optimal solutions in realistic times

Threat of allergenic airborne grass pollen in Szczecin, NW Poland: the dynamics of pollen seasons, effect of meteorological variables and air pollution

The dynamics of Poaceae pollen season, in particularly that of the Secale genus, in Szczecin (western Poland) 2004–2008 was analysed to establish a relationship between the meteorological variables, air pollution and the pollen count of the taxa studied. Consecutive phases during the pollen season were defined for each taxon (1, 2.5, 5, 25, 50, 75, 95, 97.5, 99% of annual total), and duration of the season was determined using the 98% method. On the basis of this analysis, the temporary differences in the dynamics of the seasons were most evident for Secale in 2005 and 2006 with the longest main pollen season (90% total pollen). The pollen season of Poaceae started the earliest in 2007, when thermal conditions were the most favourable. Correlation analysis with meteorological factors demonstrated that the relative humidity, mean and maximum air temperature, and rainfall were the factors influencing the average daily pollen concentrations in the atmosphere; also, the presence of air pollutants such as ozone, PM10 and SO2 was statistically related to the pollen count in the air. However, multiple regression models explained little part of the total variance. Atmospheric pollution induces aggravation of symptoms of grass pollen allergy

Caveolin-1 Influences Vascular Protease Activity and Is a Potential Stabilizing Factor in Human Atherosclerotic Disease

Caveolin-1 (Cav-1) is a regulatory protein of the arterial wall, but its role in human atherosclerosis remains unknown. We have studied the relationships between Cav-1 abundance, atherosclerotic plaque characteristics and clinical manisfestations of atherosclerotic disease.We determined Cav-1 expression by western blotting in atherosclerotic plaques harvested from 378 subjects that underwent carotid endarterectomy. Cav-1 levels were significantly lower in carotid plaques than non-atherosclerotic vascular specimens. Low Cav-1 expression was associated with features of plaque instability such as large lipid core, thrombus formation, macrophage infiltration, high IL-6, IL-8 levels and elevated MMP-9 activity. Clinically, a down-regulation of Cav-1 was observed in plaques obtained from men, patients with a history of myocardial infarction and restenotic lesions. Cav-1 levels above the median were associated with absence of new vascular events within 30 days after surgery [0% vs. 4%] and a trend towards lower incidence of new cardiovascular events during longer follow-up. Consistent with these clinical data, Cav-1 null mice revealed elevated intimal hyperplasia response following arterial injury that was significantly attenuated after MMP inhibition. Recombinant peptides mimicking Cav-1 scaffolding domain (Cavtratin) reduced gelatinase activity in cultured porcine arteries and impaired MMP-9 activity and COX-2 in LPS-challenged macrophages. Administration of Cavtratin strongly impaired flow-induced expansive remodeling in mice.This is the first study that identifies Cav-1 as a novel potential stabilizing factor in human atherosclerosis. Our findings support the hypothesis that local down-regulation of Cav-1 in atherosclerotic lesions contributes to plaque formation and/or instability accelerating the occurrence of adverse clinical outcomes. Therefore, given the large number of patients studied, we believe that Cav-1 may be considered as a novel target in the prevention of human atherosclerotic disease and the loss of Cav-1 may be a novel biomarker of vulnerable plaque with prognostic value

Studies of η\eta and η′\eta' production in pppp and ppPb collisions

The production of $\eta$ and $\eta'$ mesons is studied in proton-proton and proton-lead collisions collected with the LHCb detector. Proton-proton collisions are studied at center-of-mass energies of $5.02$ and $13~{\rm TeV}$, and proton-lead collisions are studied at a center-of-mass energy per nucleon of $8.16~{\rm TeV}$. The studies are performed in center-of-mass rapidity regions $2.5<y_{\rm c.m.}<3.5$ (forward rapidity) and $-4.0<y_{\rm c.m.}<-3.0$ (backward rapidity) defined relative to the proton beam direction. The $\eta$ and $\eta'$ production cross sections are measured differentially as a function of transverse momentum for $1.5<p_{\rm T}<10~{\rm GeV}$ and $3<p_{\rm T}<10~{\rm GeV}$, respectively. The differential cross sections are used to calculate nuclear modification factors. The nuclear modification factors for $\eta$ and $\eta'$ mesons agree at both forward and backward rapidity, showing no significant evidence of mass dependence. The differential cross sections of $\eta$ mesons are also used to calculate $\eta/\pi^0$ cross section ratios, which show evidence of a deviation from the world average. These studies offer new constraints on mass-dependent nuclear effects in heavy-ion collisions, as well as $\eta$ and $\eta'$ meson fragmentation.Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://lhcbproject.web.cern.ch/Publications/p/LHCb-PAPER-2023-030.html (LHCb public pages

Measurement of antiproton production from antihyperon decays in pHe collisions at √sNN=110GeV

The interpretation of cosmic antiproton flux measurements from space-borne experiments is currently limited by the knowledge of the antiproton production cross-section in collisions between primary cosmic rays and the interstellar medium. Using collisions of protons with an energy of 6.5 TeV incident on helium nuclei at rest in the proximity of the interaction region of the LHCb experiment, the ratio of antiprotons originating from antihyperon decays to prompt production is measured for antiproton momenta between 12 and 110GeV\!/c . The dominant antihyperon contribution, namely Λ¯ → p¯ π+ decays from promptly produced Λ¯ particles, is also exclusively measured. The results complement the measurement of prompt antiproton production obtained from the same data sample. At the energy scale of this measurement, the antihyperon contributions to antiproton production are observed to be significantly larger than predictions of commonly used hadronic production models