Mule deer (Odocoileus hemionus) populations throughout the west appear to be declining, whereas white-tailed deer (Odocoileus virginianus) populations are increasing. We compared abundance, number of ...fetuses per female (maternity rate), recruitment, and cause-specific adult (
1 year old) mortality rate for sympatric mule deer and white-tailed deer in south-central British Columbia to assess population growth for each species. White-tailed deer were three times more abundant (908 ± 152) than mule deer (336 ± 122) (mean ± 1 SE). Fetal rates of white-tailed deer (1.83) were similar to those of mule deer (1.78). There was no statistically significant difference in recruitment of white-tailed deer (56 fawns : 100 does) and mule deer (38 fawns : 100 does). The annual survival rate for adult white-tailed deer (S
WT
= 0.81) was significantly higher than that for mule deer (S
MD
= 0.72). The main cause of mortality in both populations was cougar predation. The lower mule deer survival rate could be directly linked to a higher predation rate (0.17) than for white-tailed deer (0.09). The finite growth rate ( λ) was 0.88 for mule deer and 1.02 for white-tailed deer. The disparate survival and predation rates are consistent with the apparent-competition hypothesis.
Several proteins have been linked to neurodegenerative disorders (NDDs), but their molecular function is not completely understood. Here, we used quantitative interaction proteomics to identify ...binding partners of Amyloid beta precursor protein (APP) and Presenilin-1 (PSEN1) for Alzheimer’s disease (AD), Huntingtin (HTT) for Huntington’s disease, Parkin (PARK2) for Parkinson’s disease, and Ataxin-1 (ATXN1) for spinocerebellar ataxia type 1. Our network reveals common signatures of protein degradation and misfolding and recapitulates known biology. Toxicity modifier screens and comparison to genome-wide association studies show that interaction partners are significantly linked to disease phenotypes in vivo. Direct comparison of wild-type proteins and disease-associated variants identified binders involved in pathogenesis, highlighting the value of differential interactome mapping. Finally, we show that the mitochondrial protein LRPPRC interacts preferentially with an early-onset AD variant of APP. This interaction appears to induce mitochondrial dysfunction, which is an early phenotype of AD.
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•Quantitative interactomics of proteins involved in four neurodegenerative diseases•Differential interaction mapping of wild-type and disease-associated proteins•Interaction partners are significantly linked to disease phenotypes in vivo•Interaction of APP and LRPPRC appears to induce mitochondrial dysfunction in AD
Hosp et al. show that quantitative interaction proteomics of neurodegenerative disease proteins captures interactions relevant to pathogenesis. Differential interactome mapping reveals preferential binding of the mitochondrial protein LRPPRC with an early-onset Alzheimer’s disease (AD) variant of APP, potentially contributing to mitochondrial dysfunction observed in AD.
Objective
Genome‐wide association studies (GWAS) have identified over 30 susceptibility loci associated with Alzheimer's disease (AD). Using AD GWAS data from the International Genomics of ...Alzheimer's Project (IGAP), Polygenic Risk Score (PRS) was successfully applied to predict life time risk of AD development. A recently introduced Polygenic Hazard Score (PHS) is able to quantify individuals with age‐specific genetic risk for AD. The aim of this study was to quantify the age‐specific genetic risk for AD with PRS and compare the results generated by PRS with those from PHS.
Methods
Quantification of individual differences in age‐specific genetic risk for AD identified by the PRS, was performed with Cox Regression on 9903 (2626 cases and 7277 controls) individuals from the Genetic and Environmental Risk in Alzheimer's Disease consortium (GERAD). Polygenic Hazard Scores were generated for the same individuals. The age‐specific genetic risk for AD identified by the PRS was compared with that generated by the PHS. This was repeated using varying SNPs P‐value thresholds for disease association.
Results
Polygenic Risk Score significantly predicted the risk associated with age at AD onset when SNPs were preselected for association to AD at P ≤ 0.001. The strongest effect (B = 0.28, SE = 0.04, P = 2.5 × 10−12) was observed for PRS based upon genome‐wide significant SNPs (P ≤ 5 × 10−8). The strength of association was weaker with less stringent SNP selection thresholds.
Interpretation
Both PRS and PHS can be used to predict an age‐specific risk for developing AD. The PHS approach uses SNP effect sizes derived with the Cox Proportional Hazard Regression model. When SNPs were selected based upon AD GWAS case/control P ≤ 10−3, we found no advantage of using SNP effects sizes calculated with the Cox Proportional Hazard Regression model in our study. When SNPs are selected for association with AD risk at P > 10−3, the age‐specific risk prediction results are not significant for either PRS or PHS. However PHS could be more advantageous than PRS of age specific AD risk predictions when SNPs are prioritized for association with AD age at onset (i.e., powerful Cox Regression GWAS study).
The genetic aetiology of osteoarthritis has not yet been elucidated. To enable a well-powered genome-wide association study (GWAS) for osteoarthritis, the authors have formed the arcOGEN Consortium, ...a UK-wide collaborative effort aiming to scan genome-wide over 7500 osteoarthritis cases in a two-stage genome-wide association scan. Here the authors report the findings of the stage 1 interim analysis.
The authors have performed a genome-wide association scan for knee and hip osteoarthritis in 3177 cases and 4894 population-based controls from the UK. Replication of promising signals was carried out in silico in five further scans (44,449 individuals), and de novo in 14 534 independent samples, all of European descent.
None of the association signals the authors identified reach genome-wide levels of statistical significance, therefore stressing the need for corroboration in sample sets of a larger size. Application of analytical approaches to examine the allelic architecture of disease to the stage 1 genome-wide association scan data suggests that osteoarthritis is a highly polygenic disease with multiple risk variants conferring small effects.
Identifying loci conferring susceptibility to osteoarthritis will require large-scale sample sizes and well-defined phenotypes to minimise heterogeneity.
The scattering of dark matter (DM) particles with sub-GeV masses off nuclei is difficult to detect using liquid xenon-based DM search instruments because the energy transfer during nuclear recoils is ...smaller than the typical detector threshold. However, the tree-level DM-nucleus scattering diagram can be accompanied by simultaneous emission of a Bremsstrahlung photon or a so-called "Migdal" electron. These provide an electron recoil component to the experimental signature at higher energies than the corresponding nuclear recoil. The presence of this signature allows liquid xenon detectors to use both the scintillation and the ionization signals in the analysis where the nuclear recoil signal would not be otherwise visible. In this work, we report constraints on spin-independent DM-nucleon scattering for DM particles with masses of 0.4-5 GeV/c$^2$ using 1.4$\times10^4$ kg$\cdot$day of search exposure from the 2013 data from the Large Underground Xenon (LUX) experiment for four different classes of mediators. Finally, this analysis extends the reach of liquid xenon-based DM search instruments to lower DM masses than has been achieved previously.
High fluence (>10
17
H/cm
2) ion implantation of H in GaAs is suitable for the ion cut process, and produces H bubbles under the surface which may cause blistering. By comparing the destructive depth ...profiling of these implants by secondary ion mass spectrometry (SIMS) with non-destructive profiling by elastic recoil detection analysis (ERD), we demonstrate that SIMS underestimates total H content by up to a factor of 2 due to undetected H escaping from bubbles during analysis. We also show that the depth of the maximum H concentration from SIMS can be in error by 20% due to large variations in the sputter rate through the profile.
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