241 research outputs found

    Structure and Stress: Trajectories of Depressive Symptoms across Adolescence and Young Adulthood

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    Previous research into the social distribution of early life depression has yielded inconsistent results regarding subgroup differences in depression levels and in the etiology of these differences. Using latent curve models and data from the National Longitudinal Study of Adolescent Health, this study investigates gender and racial/ethnic disparities in early life depressive symptoms and the explanatory roles of stress and socioeconomic status (SES). Results show that females and minorities experience higher levels of depressive symptoms across early life compared to males and Whites. Further, childhood SES and stressful life events (SLEs) explain much of the disparity for Blacks and Hispanics. Finally, Blacks, Hispanics, and females show greater sensitivity to the effects of low childhood SES and, in the case of females, SLEs. Overall, this study provides new insight into gender and racial/ethnic differences in the course of early life depression and in the role of the stress process during this important developmental stage

    The influence of five monoamine genes on trajectories of depressive symptoms across adolescence and young adulthood

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    The influence of five monoamine candidate genes on depressive symptom trajectories in adolescence and young adulthood were examined in the Add Health genetic sample. Results indicated that, for all respondents, carriers of the DRD4 5-repeat allele were characterized by distinct depressive symptom trajectories across adolescence and early adulthood. Similarly, for males, individuals with the MAOA 3.5-repeat allele exhibited unique depressive symptom trajectories. Specifically, the trajectories of those with the DRD4 5-repeat allele were characterized by rising levels in the transition to adulthood, while their peers were experiencing a normative drop in depressive symptom frequency. Conversely, males with the MAOA 3.5-repeat allele were shown to experience increased distress in late adolescence. An empirical method for examining a wide array of allelic combinations was employed, and false discovery rate methods were used to control the risk of false positives due to multiple testing. Special attention was given to thoroughly interrogate the robustness of the putative genetic effects. These results demonstrate the value of combining dynamic developmental perspectives with statistical genetic methods to optimize the search for genetic influences on psychopathology across the life course

    X-Ray Flaring on the dMe Star, Ross 154

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    We present results from two Chandra imaging observations of Ross 154, a nearby flaring M dwarf star. During a 61-ks ACIS-S exposure, a very large flare occurred (the equivalent of a solar X3400 event, with L_X = 1.8x10^30 ergs/s) in which the count rate increased by a factor of over 100. The early phase of the flare shows evidence for the Neupert effect, followed by a further rise and then a two-component exponential decay. A large flare was also observed at the end of a later 48-ks HRC-I observation. Emission from the non-flaring phases of both observations was analyzed for evidence of low level flaring. From these temporal studies we find that microflaring probably accounts for most of the `quiescent' emission, and that, unlike for the Sun and the handful of other stars that have been studied, the distribution of flare intensities does not appear to follow a power-law with a single index. Analysis of the ACIS spectra, which was complicated by exclusion of the heavily piled-up source core, suggests that the quiescent Ne/O abundance ratio is enhanced by a factor of ~2.5 compared to the commonly adopted solar abundance ratio, and that the Ne/O ratio and overall coronal metallicity during the flare appear to be enhanced relative to quiescent abundances. Based on the temperatures and emission measures derived from the spectral fits, we estimate the length scales and plasma densities in the flaring volume and also track the evolution of the flare in color-intensity space. Lastly, we searched for a stellar-wind charge-exchange X-ray halo around the star but without success; because of the relationship between mass-loss rate and the halo surface brightness, not even an upper limit on the stellar mass-loss rate can be determined.Comment: 20 pages, 12 figures (4 color), accepted by ApJ, expected publication April 1, 200

    Behavioral metabolomics analysis identifies novel neurochemical signatures in methamphetamine sensitization: Methamphetamine sensitization metabolomics

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    Behavioral sensitization has been widely studied in animal models and is theorized to reflect neural modifications associated with human psychostimulant addiction. While the mesolimbic dopaminergic pathway is known to play a role, the neurochemical mechanisms underlying behavioral sensitization remain incompletely understood. In the present study, we conducted the first metabolomics analysis to globally characterize neurochemical differences associated with behavioral sensitization. Methamphetamine-induced sensitization measures were generated by statistically modeling longitudinal activity data for eight inbred strains of mice. Subsequent to behavioral testing, nontargeted liquid and gas chromatography-mass spectrometry profiling was performed on 48 brain samples, yielding 301 metabolite levels per sample after quality control. Association testing between metabolite levels and three primary dimensions of behavioral sensitization (total distance, stereotypy and margin time) showed four robust, significant associations at a stringent metabolome-wide significance threshold (false discovery rate < 0.05). Results implicated homocarnosine, a dipeptide of GABA and histidine, in total distance sensitization, GABA metabolite 4-guanidinobutanoate and pantothenate in stereotypy sensitization, and myo-inositol in margin time sensitization. Secondary analyses indicated that these associations were independent of concurrent methamphetamine levels and, with the exception of the myo-inositol association, suggest a mechanism whereby strain-based genetic variation produces specific baseline neurochemical differences that substantially influence the magnitude of MA-induced sensitization. These findings demonstrate the utility of mouse metabolomics for identifying novel biomarkers, and developing more comprehensive neurochemical models, of psychostimulant sensitization

    Rotation and X-ray emission from protostars

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    The ASCA satellite has recently detected variable hard X-ray emission from two Class I protostars in the rho Oph cloud, YLW15 (IRS43) and WL6, with a characteristic time scale ~20h. In YLW15, the X-ray emission is in the form of quasi-periodic energetic flares, which we explain in terms of strong magnetic shearing and reconnection between the central star and the accretion disk. In WL6, X-ray flaring is rotationally modulated, and appears to be more like the solar-type magnetic activity ubiquitous on T Tauri stars. We find that YLW15 is a fast rotator (near break-up), while WL6 rotates with a significantly longer period. We derive a mass M_\star ~ 2 M_\odot and \simlt 0.4 M_\odot for the central stars of YLW15 and WL6 respectively. On the long term, the interactions between the star and the disk results in magnetic braking and angular momentum loss of the star. On time scales t_{br} ~ a few 10^5 yrs, i.e., of the same order as the estimated duration of the Class~I protostar stage. Close to the birthline there must be a mass-rotation relation, t_{br} \simpropto M_\star, such that stars with M_\star \simgt 1-2 M_\odot are fast rotators, while their lower-mass counterparts have had the time to spin down. The rapid rotation and strong star-disk magnetic interactions of YLW15 also naturally explain the observation of X-ray ``superflares''. In the case of YLW15, and perhaps also of other protostars, a hot coronal wind (T~10^6 K) may be responsible for the VLA thermal radio emission. This paper thus proposes the first clues to the rotation status and evolution of protostars.Comment: 13 pages with 6 figures. To be published in ApJ (April 10, 2000 Part 1 issue

    An XMM-Newton Study of the Coronae of σ2\sigma^2 Coronae Borealis

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    (Abridged) We present results of XMM-Newton observations of the RS CVn binary σ2\sigma^2 Coronae Borealis. The RGS and EPIC MOS2 spectra were simultaneously fitted with collisional ionization equilibrium plasma models to determine coronal abundances of various elements. Contrary to the solar first ionization potential (FIP) effect in which elements with a low FIP are overabundant in the corona compared to the solar photosphere, and contrary to the ``inverse'' FIP effect observed in several active RS CVn binaries, coronal abundance ratios in σ2\sigma^2 CrB show a complex pattern as supported by similar findings in the Chandra HETGS analysis of σ2\sigma^2 CrB with a different methodology (Osten et al. 2003). Low-FIP elements (<10<10 eV) have their abundance ratios relative to Fe consistent with the solar photospheric ratios, whereas high-FIP elements have their abundance ratios increase with increasing FIP. We find that the coronal Fe abundance is consistent with the stellar photospheric value, indicating that there is no metal depletion in σ2\sigma^2 CrB. However, we obtain a higher Fe absolute abundance than in Osten et al. (2003). Except for Ar and S, our absolute abundances are about 1.5 times larger than those reported by Osten et al. (2003). However, a comparison of their model with our XMM-Newton data (and vice versa) shows that both models work adequately in general. We find, therefore, no preference for one methodology over the other to derive coronal abundances. Despite the systematic discrepancy in absolute abundances, our abundance ratios are very close to those obtained by Osten et al. (2003). Finally, we confirm the measurement of a low density in \ion{O}{7} (<4×1010< 4 \times 10^{10} cm−3^{-3}), but could not confirm the higher densities measured in spectral lines formed at higher temperatures.Comment: To appear in Astrophysical Journal (ApJ 10 September 2005, v630 2 issue

    Genome-wide pharmacogenomic analysis of response to treatment with antipsychotics

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    Schizophrenia is an often devastating neuropsychiatric illness. Understanding the genetic variation affecting response to antipsychotics is important to develop novel diagnostic tests to match individual schizophrenic patients to the most effective and safe medication. Here we use a genomewide approach to detect genetic variation underlying individual differences in response to treatment with the antipsychotics olanzapine, quetiapine, risperidone, ziprasidone and perphenazine. Our sample consisted of 738 subjects with DSM-IV schizophrenia who took part in the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE). Subjects were genotyped using the Affymetrix 500K genotyping platform plus a custom 164K chip to improve genomewide coverage. Treatment outcome was measured using the Positive and Negative Syndrome Scale (PANSS). Our criterion for genomewide significance was a pre-specified threshold that ensures, on average, only 10% of the significant findings are false discoveries. The top statistical result reached significance at our pre-specified threshold and involved a SNP in an intergenic region on chromosome 4p15. In addition, SNPs in ANKS1B and CNTNAP5 that mediated the effects of olanzapine and risperidone on Negative symptoms were very close to our threshold for declaring significance. The most significant SNP in CNTNAP5 is nonsynonymous, giving rise to an amino acid substitution. In addition to highlighting our top results, we provide all p-values for download as a resource for investigators with the requisite samples to carry out replication. This study demonstrates the potential of GWAS to discover novel genes that mediate effects of antipsychotics, which eventually could help to tailor drug treatment to schizophrenic patients

    Genotype-Based Ancestral Background Consistently Predicts Efficacy and Side Effects across Treatments in CATIE and STAR*D

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    Only a subset of patients will typically respond to any given prescribed drug. The time it takes clinicians to declare a treatment ineffective leaves the patient in an impaired state and at unnecessary risk for adverse drug effects. Thus, diagnostic tests robustly predicting the most effective and safe medication for each patient prior to starting pharmacotherapy would have tremendous clinical value. In this article, we evaluated the use of genetic markers to estimate ancestry as a predictive component of such diagnostic tests. We first estimated each patient’s unique mosaic of ancestral backgrounds using genome-wide SNP data collected in the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) (n = 765) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) (n = 1892). Next, we performed multiple regression analyses to estimate the predictive power of these ancestral dimensions. For 136/89 treatment-outcome combinations tested in CATIE/STAR*D, results indicated 1.67/1.84 times higher median test statistics than expected under the null hypothesis assuming no predictive power (p<0.01, both samples). Thus, ancestry showed robust and pervasive correlations with drug efficacy and side effects in both CATIE and STAR*D. Comparison of the marginal predictive power of MDS ancestral dimensions and self-reported race indicated significant improvements to model fit with the inclusion of MDS dimensions, but mixed evidence for self-reported race. Knowledge of each patient’s unique mosaic of ancestral backgrounds provides a potent immediate starting point for developing algorithms identifying the most effective and safe medication for a wide variety of drug-treatment response combinations. As relatively few new psychiatric drugs are currently under development, such personalized medicine offers a promising approach toward optimizing pharmacotherapy for psychiatric conditions

    Some Like it Hot: The X-Ray Emission of The Giant Star YY Mensae

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    (Abridged abstract) We present an analysis of the X-ray emission of the rapidly rotating giant star YY Mensae observed by Chandra HETGS and XMM-Newton. Although no obvious flare was detected, the X-ray luminosity changed by a factor of two between the XMM-Newton and Chandra observations taken 4 months apart. The coronal abundances and the emission measure distribution have been derived from three different methods using optically thin collisional ionization equilibrium models. The abundances show an inverse first ionization potential (FIP) effect. We further find a high N abundance which we interpret as a signature of material processed in the CNO cycle. The corona is dominated by a very high temperature (20-40 MK) plasma, which places YY Men among the magnetically active stars with the hottest coronae. Lower temperature plasma also coexists, albeit with much lower emission measure. Line broadening is reported, which we interpret as Doppler thermal broadening, although rotational broadening due to X-ray emitting material high above the surface could be present as well. We use two different formalisms to discuss the shape of the emission measure distribution. The first one infers the properties of coronal loops, whereas the second formalism uses flares as a statistical ensemble. We find that most of the loops in the corona of YY Men have their maximum temperature equal to or slightly larger than about 30 MK. We also find that small flares could contribute significantly to the coronal heating in YY Men. Although there is no evidence of flare variability in the X-ray light curves, we argue that YY Men's distance and X-ray brightness does not allow us to detect flares with peak luminosities Lx <= 10^{31} erg/s with current detectors.Comment: Accepted paper to appear in Astrophysical Journal, issue Nov 10, 2004 (v615). This a revised version. Small typos are corrected. Figure 7 and its caption and some related text in Sct 7.2 are changed, without incidence for the conclusion
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