Constraints on Charon's Orbital Elements from the Double Stellar Occultation of 2008 June 22

The original publication is available at http://iopscience.iop.org/1538-3881/International audiencePluto and its main satellite, Charon, occulted the same star on 2008 June 22. This event was observed from Australia and La Réunion Island, providing the east and north Charon Plutocentric offset in the sky plane (J2000): X= + 12,070.5 ± 4 km (+ 546.2 ± 0.2 mas), Y= + 4,576.3 ± 24 km (+ 207.1 ± 1.1 mas) at 19:20:33.82 UT on Earth, corresponding to JD 2454640.129964 at Pluto. This yields Charon's true longitude L= 153.483 ± 0fdg071 in the satellite orbital plane (counted from the ascending node on J2000 mean equator) and orbital radius r= 19,564 ± 14 km at that time. We compare this position to that predicted by (1) the orbital solution of Tholen & Buie (the "TB97" solution), (2) the PLU017 Charon ephemeris, and (3) the solution of Tholen et al. (the "T08" solution). We conclude that (1) our result rules out solution TB97, (2) our position agrees with PLU017, with differences of ΔL= + 0.073 ± 0fdg071 in longitude, and Δr= + 0.6 ± 14 km in radius, and (3) while the difference with the T08 ephemeris amounts to only ΔL= 0.033 ± 0fdg071 in longitude, it exhibits a significant radial discrepancy of Δr= 61.3 ± 14 km. We discuss this difference in terms of a possible image scale relative error of 3.35 × 10-3in the 2002-2003 Hubble Space Telescope images upon which the T08 solution is mostly based. Rescaling the T08 Charon semi-major axis, a = 19, 570.45 km, to the TB97 value, a = 19636 km, all other orbital elements remaining the same ("T08/TB97" solution), we reconcile our position with the re-scaled solution by better than 12 km (or 0.55 mas) for Charon's position in its orbital plane, thus making T08/TB97 our preferred solution

Evidence of causal effect of major depression on alcohol dependence: findings from the psychiatric genomics consortium

BACKGROUND Despite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC. METHODS Linkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals). RESULTS Positive genetic correlation was observed between MD and AD (rgMD−AD = + 0.47, P = 6.6 × 10−10). AC-quantity showed positive genetic correlation with both AD (rgAD−AC quantity = + 0.75, P = 1.8 × 10−14) and MD (rgMD−AC quantity = + 0.14, P = 2.9 × 10−7), while there was negative correlation of AC-frequency with MD (rgMD−AC frequency = −0.17, P = 1.5 × 10−10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10−6). There was no evidence for reverse causation. CONCLUSION This study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts

Genetic variants linked to education predict longevity

Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members’ polygenic profile score for education to predict their parents’ longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total ndeaths = 79,702) and ∼2.4% lower risk for fathers (total ndeaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity.</p