Interaction between polygenic risk for cigarette use and environmental exposures in the Detroit neighborhood health study

Cigarette smoking is influenced both by genetic and environmental factors. Until this year, all large-scale gene identification studies on smoking were conducted in populations of European ancestry. Consequently, the genetic architecture of smoking is not well described in other populations. Further, despite a rich epidemiologic literature focused on the social determinants of smoking, few studies have examined the moderation of genetic influences (for example, gene-environment interactions) on smoking in African Americans. In the Detroit Neighborhood Health Study (DNHS), a sample of randomly selected majority African American residents of Detroit, we constructed a genetic risk score (GRS), in which we combined top (P-value <5 × 10-7) genetic variants from a recent meta-analysis conducted in a large sample of African Americans. Using regression (effective n=399), we first tested for association between the GRS and cigarettes per day, attempting to replicate the findings from the meta-analysis. Second, we examined interactions with three social contexts that may moderate the genetic association with smoking: traumatic events, neighborhood social cohesion and neighborhood physical disorder. Among individuals who had ever smoked cigarettes, the GRS significantly predicted the number of cigarettes smoked per day and accounted for ∼3% of the overall variance in the trait. Significant interactions were observed between the GRS and number of traumatic events experienced, as well as between the GRS and average neighborhood social cohesion; the association between genetic risk and smoking was greater among individuals who had experienced an increased number of traumatic events in their lifetimes, and diminished among individuals who lived in a neighborhood characterized by greater social cohesion. This study provides support for the utility of the GRS as an alternative approach to replication of common polygenic variation, and in gene-environment interaction, for smoking behaviors. In addition, this study indicates that environmental determinants have the potential to both exacerbate (traumatic events) and diminish (neighborhood social cohesion) genetic influences on smoking behaviors. © 2013 Macmillan Publishers Limited. All rights reserved

Aldehyde dehydrogenase-1a1 induces oncogene suppressor genes in B cell populations

AbstractThe deregulation of B cell differentiation has been shown to contribute to autoimmune disorders, hematological cancers, and aging. We provide evidence that the retinoic acid-producing enzyme aldehyde dehydrogenase 1a1 (Aldh1a1) is an oncogene suppressor in specific splenic IgG1+/CD19− and IgG1+/CD19+ B cell populations. Aldh1a1 regulated transcription factors during B cell differentiation in a sequential manner: 1) retinoic acid receptor alpha (Rara) in IgG1+/CD19− and 2) zinc finger protein Zfp423 and peroxisome proliferator-activated receptor gamma (Pparg) in IgG1+/CD19+ splenocytes. In Aldh1a1−/− mice, splenic IgG1+/CD19− and IgG1+/CD19+ B cells acquired expression of proto-oncogenic genes c-Fos, c-Jun, and Hoxa10 that resulted in splenomegaly. Human multiple myeloma B cell lines also lack Aldh1a1 expression; however, ectopic Aldh1a1 expression rescued Rara and Znf423 expressions in these cells. Our data highlight a mechanism by which an enzyme involved in vitamin A metabolism can improve B cell resistance to oncogenesis

Genomic differentiation during speciation-with-gene-flow: Comparing geographic and host-related variation in divergent life history adaptation in rhagoletis pomonella

A major goal of evolutionary biology is to understand how variation within populations gets partitioned into differences between reproductively isolated species. Here, we examine the degree to which diapause life history timing, a critical adaptation promoting population divergence, explains geographic and host-related genetic variation in ancestral hawthorn and recently derived apple-infesting races of Rhagoletis pomonella. Our strategy involved combining experiments on two different aspects of diapause (initial diapause intensity and adult eclosion time) with a geographic survey of genomic variation across four sites where apple and hawthorn flies co-occur from north to south in the Midwestern USA. The results demonstrated that the majority of the genome showing significant geographic and host-related variation can be accounted for by initial diapause intensity and eclosion time. Local genomic differences between sympatric apple and hawthorn flies were subsumed within broader geographic clines; allele frequency differences within the races across the Midwest were two to three-fold greater than those between the races in sympatry. As a result, sympatric apple and hawthorn populations displayed more limited genomic clustering compared to geographic populations within the races. The findings suggest that with reduced gene flow and increased selection on diapause equivalent to that seen between geographic sites, the host races may be recognized as different genotypic entities in sympatry, and perhaps species, a hypothesis requiring future genomic analysis of related sibling species to R. pomonella to test. Our findings concerning the way selection and geography interplay could be of broad significance for many cases of earlier stages of divergence-with-gene flow, including (1) where only modest increases in geographic isolation and the strength of selection may greatly impact genetic coupling and (2) the dynamics of how spatial and temporal standing variation is extracted by selection to generate differences between new and discrete units of biodiversity

High strain-rate material model validation for laser peening simulation

Finite element modeling can be a powerful tool for predicting residual stresses induced by laser peening; however the sign and magnitude of the stress predictions depend strongly on how the material model captures the high strain rate response. Although a Johnson-Cook formulation is often employed, its suitability for modeling phenomena at very high strain rates has not been rigorously evaluated. In this paper, we address the effectiveness of the Johnson-Cook model, with parameters developed from lower strain rate material data (∼10^3 s^–1), to capture the higher strain rate response (∼10^5–10^6 s^–1) encountered during the laser peening process. Published Johnson-Cook parameters extracted from split Hopkinson bar testing were used to predict the shock response of aluminum samples during high-impact flyer plate tests. Additional quasi-static and split Hopkinson bar tests were also conducted to study the model response in the lower strain rate regime. The overall objective of the research was to ascertain whether a material model based on conventional test data (quasi-static compression testing and split Hopkinson bar measurements) can credibly be used in FE simulations to predict laser peen-induced stresses

Standing geographic variation in eclosion time and the genomics of host race formation in Rhagoletis pomonella fruit flies.

Taxa harboring high levels of standing variation may be more likely to adapt to rapid environmental shifts and experience ecological speciation. Here, we characterize geographic and host-related differentiation for 10,241 single nucleotide polymorphisms in Rhagoletis pomonella fruit flies to infer whether standing genetic variation in adult eclosion time in the ancestral hawthorn (Crataegus spp.)-infesting host race, as opposed to new mutations, contributed substantially to its recent shift to earlier fruiting apple (Malus domestica). Allele frequency differences associated with early vs. late eclosion time within each host race were significantly related to geographic genetic variation and host race differentiation across four sites, arrayed from north to south along a 430-km transect, where the host races co-occur in sympatry in the Midwest United States. Host fruiting phenology is clinal, with both apple and hawthorn trees fruiting earlier in the North and later in the South. Thus, we expected alleles associated with earlier eclosion to be at higher frequencies in northern populations. This pattern was observed in the hawthorn race across all four populations; however, allele frequency patterns in the apple race were more complex. Despite the generally earlier eclosion timing of apple flies and corresponding apple fruiting phenology, alleles on chromosomes 2 and 3 associated with earlier emergence were paradoxically at lower frequency in the apple than hawthorn host race across all four sympatric sites. However, loci on chromosome 1 did show higher frequencies of early eclosion-associated alleles in the apple than hawthorn host race at the two southern sites, potentially accounting for their earlier eclosion phenotype. Thus, although extensive clinal genetic variation in the ancestral hawthorn race exists and contributed to the host shift to apple, further study is needed to resolve details of how this standing variation was selected to generate earlier eclosing apple fly populations in the North

First Observation of Coherent π0\pi^0 Production in Neutrino Nucleus Interactions with Eν<E_{\nu}< 2 GeV

The MiniBooNE experiment at Fermilab has amassed the largest sample to date of $\pi^0$s produced in neutral current (NC) neutrino-nucleus interactions at low energy. This paper reports a measurement of the momentum distribution of $\pi^0$s produced in mineral oil (CH$_2$) and the first observation of coherent $\pi^0$ production below 2 GeV. In the forward direction, the yield of events observed above the expectation for resonant production is attributed primarily to coherent production off carbon, but may also include a small contribution from diffractive production on hydrogen. Integrated over the MiniBooNE neutrino flux, the sum of the NC coherent and diffractive modes is found to be (19.5 $\pm$1.1 (stat) $\pm$2.5 (sys))% of all exclusive NC $\pi^0$ production at MiniBooNE. These measurements are of immediate utility because they quantify an important background to MiniBooNE's search for $\nu_{\mu} \to \nu_e$ oscillations.Comment: Submitted to Phys. Lett.

Astroparticle Physics with a Customized Low-Background Broad Energy Germanium Detector

The MAJORANA Collaboration is building the MAJORANA DEMONSTRATOR, a 60 kg array of high purity germanium detectors housed in an ultra-low background shield at the Sanford Underground Laboratory in Lead, SD. The MAJORANA DEMONSTRATOR will search for neutrinoless double-beta decay of 76Ge while demonstrating the feasibility of a tonne-scale experiment. It may also carry out a dark matter search in the 1-10 GeV/c^2 mass range. We have found that customized Broad Energy Germanium (BEGe) detectors produced by Canberra have several desirable features for a neutrinoless double-beta decay experiment, including low electronic noise, excellent pulse shape analysis capabilities, and simple fabrication. We have deployed a customized BEGe, the MAJORANA Low-Background BEGe at Kimballton (MALBEK), in a low-background cryostat and shield at the Kimballton Underground Research Facility in Virginia. This paper will focus on the detector characteristics and measurements that can be performed with such a radiation detector in a low-background environment.Comment: Submitted to NIMA Proceedings, SORMA XII. 9 pages, 4 figure

Large‐scale collaboration in ENIGMA‐EEG: A perspective on the meta‐analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity.

Background and purpose The ENIGMA-EEG working group was established to enable large-scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functional brain activity may be crucial for understanding how neurological and psychiatric liability genes affect the brain. Methods We summarize how we have performed our currently largest genome-wide association study of oscillatory brain activity in EEG recordings by meta-analyzing the results across five participating cohorts, resulting in the first genome-wide significant hits for oscillatory brain function located in/near genes that were previously associated with psychiatric disorders. We describe how we have tackled methodological issues surrounding genetic meta-analysis of EEG features. We discuss the importance of harmonizing EEG signal processing, cleaning, and feature extraction. Finally, we explain our selection of EEG features currently being investigated, including the temporal dynamics of oscillations and the connectivity network based on synchronization of oscillations. Results We present data that show how to perform systematic quality control and evaluate how choices in reference electrode and montage affect individual differences in EEG parameters. Conclusion The long list of potential challenges to our large-scale meta-analytic approach requires extensive effort and organization between participating cohorts; however, our perspective shows that these challenges are surmountable. Our perspective argues that elucidating the genetic of EEG oscillatory activity is a worthwhile effort in order to elucidate the pathway from gene to disease liability