Suicide ideation of individuals in online social networks

Suicide explains the largest number of death tolls among Japanese adolescents in their twenties and thirties. Suicide is also a major cause of death for adolescents in many other countries. Although social isolation has been implicated to influence the tendency to suicidal behavior, the impact of social isolation on suicide in the context of explicit social networks of individuals is scarcely explored. To address this question, we examined a large data set obtained from a social networking service dominant in Japan. The social network is composed of a set of friendship ties between pairs of users created by mutual endorsement. We carried out the logistic regression to identify users' characteristics, both related and unrelated to social networks, which contribute to suicide ideation. We defined suicide ideation of a user as the membership to at least one active user-defined community related to suicide. We found that the number of communities to which a user belongs to, the intransitivity (i.e., paucity of triangles including the user), and the fraction of suicidal neighbors in the social network, contributed the most to suicide ideation in this order. Other characteristics including the age and gender contributed little to suicide ideation. We also found qualitatively the same results for depressive symptoms.Comment: 4 figures, 9 table

<Book Reviews> Ingemar Fagerlind and Lawrence J Saha Education and National Development : A Comparative Perspective

textabstractVarious modeling methods have been proposed to estimate the potential predictive ability of polygenic risk variants that predispose to various common diseases. However, it is unknown whether differences between them affect their conclusions on predictive ability. We reviewed input parameters, assumptions and output of the five most common methods and compared their estimates of the area under the receiver operating characteristic (ROC) curve (AUC) using hypothetical data representing effect sizes and frequencies of genetic variants, population disease risk and number of variants. To assess the accuracy of the estimated AUCs, we aimed to reproduce the AUCs of published empirical studies. All methods assumed that the combined effect of genetic variants on disease risk followed a multiplicative risk model of independent genetic effects, but they either assumed per allele, per genotype or dominant/recessive effects for the genetic variants. Modeling strategy and input parameters differed. Methods used simulation analysis or analytical formulas with effect sizes quantified by odds ratios (ORs) or relative risks. Estimated AUC values were similar for lower ORs (0.7) due to variants with strong effects, differences in estimated AUCs between methods increased. The simulation methods accurately reproduced the AUC values of empirical studies, but the analytical methods did not. We conclude that despite differences in input parameters, the modeling methods estimate similar AUC for realistic values of the ORs. When one or more variants have stronger effects and AUC values are higher, the simulation methods tend to be more accurate

Risk factors for methamphetamine use in youth: a systematic review

<p>Abstract</p> <p>Background</p> <p>Methamphetamine (MA) is a potent stimulant that is readily available. Its effects are similar to cocaine, but the drug has a profile associated with increased acute and chronic toxicities. The objective of this systematic review was to identify and synthesize literature on risk factors that are associated with MA use among youth.</p> <p>More than 40 electronic databases, websites, and key journals/meeting abstracts were searched. We included studies that compared children and adolescents (≤ 18 years) who used MA to those who did not. One reviewer extracted the data and a second checked for completeness and accuracy. For discrete risk factors, odds ratios (OR) were calculated and when appropriate, a pooled OR with 95% confidence intervals (95% CI) was calculated. For continuous risk factors, mean difference and 95% CI were calculated and when appropriate, a weighted mean difference (WMD) and 95% CI was calculated. Results were presented separately by comparison group: low-risk (no previous drug abuse) and high-risk children (reported previous drug abuse or were recruited from a juvenile detention center).</p> <p>Results</p> <p>Twelve studies were included. Among low-risk youth, factors associated with MA use were: history of heroin/opiate use (OR = 29.3; 95% CI: 9.8–87.8), family history of drug use (OR = 4.7; 95% CI: 2.8–7.9), risky sexual behavior (OR = 2.79; 95% CI: 2.25, 3.46) and some psychiatric disorders. History of alcohol use and smoking were also significantly associated with MA use. Among high-risk youth, factors associated with MA use were: family history of crime (OR = 2.0; 95% CI: 1.2–3.3), family history of drug use (OR = 4.7; 95% CI: 2.8–7.9), family history of alcohol abuse (OR = 3.2; 95% CI: 1.8–5.6), and psychiatric treatment (OR = 6.8; 95% CI: 3.6–12.9). Female sex was also significantly associated with MA use.</p> <p>Conclusion</p> <p>Among low-risk youth, a history of engaging in a variety of risky behaviors was significantly associated with MA use. A history of a psychiatric disorder was a risk factor for MA for both low- and high-risk youth. Family environment was also associated with MA use. Many of the included studies were cross-sectional making it difficult to assess causation. Future research should utilize prospective study designs so that temporal relationships between risk factors and MA use can be established.</p

Genetics affects choice of academic subjects as well as achievement.

We have previously shown that individual differences in educational achievement are highly heritable throughout compulsory education. After completing compulsory education at age 16, students in England can choose to continue to study for two years (A-levels) in preparation for applying to university and they can freely choose which subjects to study. Here, for the first time, we show that choosing to do A-levels and the choice of subjects show substantial genetic influence, as does performance after two years studying the chosen subjects. Using a UK-representative sample of 6584 twin pairs, heritability estimates were 44% for choosing to do A-levels and 52–80% for choice of subject. Achievement after two years was also highly heritable (35–76%). The findings that DNA differences substantially affect differences in appetites as well as aptitudes suggest a genetic way of thinking about education in which individuals actively create their own educational experiences in part based on their genetic propensities

Alzheimer’s disease: diagnostics, prognostics and the road to prevention

Alzheimer’s disease (AD) presents one of the leading healthcare challenges of the 21st century, with a projected worldwide prevalence of >107 million cases by 2025. While biomarkers have been identified, which may correlate with disease progression or subtype for the purpose of disease monitoring or differential diagnosis, a biomarker for reliable prediction of late onset disease risk has not been available until now. This deficiency in reliable predictive biomarkers, coupled with the devastating nature of the disease, places AD at a high priority for focus by predictive, preventive and personalized medicine. Recent data, discovered using phylogenetic analysis, suggest that a variable length poly-T sequence polymorphism in the TOMM40 gene, adjacent to the APOE gene, is predictive of risk of AD age-of-onset when coupled with a subject’s current age. This finding offers hope for reliable assignment of disease risk within a 5-7 year window, and is expected to guide enrichment of clinical trials in order to speed development of preventative medicines

Following the genes: a framework for animal modeling of psychiatric disorders

The number of individual cases of psychiatric disorders that can be ascribed to identified, rare, single mutations is increasing with great rapidity. Such mutations can be recapitulated in mice to generate animal models with direct etiological validity. Defining the underlying pathogenic mechanisms will require an experimental and theoretical framework to make the links from mutation to altered behavior in an animal or psychopathology in a human. Here, we discuss key elements of such a framework, including cell type-based phenotyping, developmental trajectories, linking circuit properties at micro and macro scales and definition of neurobiological phenotypes that are directly translatable to humans

The Genetic Signatures of Noncoding RNAs

The majority of the genome in animals and plants is transcribed in a developmentally regulated manner to produce large numbers of non–protein-coding RNAs (ncRNAs), whose incidence increases with developmental complexity. There is growing evidence that these transcripts are functional, particularly in the regulation of epigenetic processes, leading to the suggestion that they compose a hitherto hidden layer of genomic programming in humans and other complex organisms. However, to date, very few have been identified in genetic screens. Here I show that this is explicable by an historic emphasis, both phenotypically and technically, on mutations in protein-coding sequences, and by presumptions about the nature of regulatory mutations. Most variations in regulatory sequences produce relatively subtle phenotypic changes, in contrast to mutations in protein-coding sequences that frequently cause catastrophic component failure. Until recently, most mapping projects have focused on protein-coding sequences, and the limited number of identified regulatory mutations have been interpreted as affecting conventional cis-acting promoter and enhancer elements, although these regions are often themselves transcribed. Moreover, ncRNA-directed regulatory circuits underpin most, if not all, complex genetic phenomena in eukaryotes, including RNA interference-related processes such as transcriptional and post-transcriptional gene silencing, position effect variegation, hybrid dysgenesis, chromosome dosage compensation, parental imprinting and allelic exclusion, paramutation, and possibly transvection and transinduction. The next frontier is the identification and functional characterization of the myriad sequence variations that influence quantitative traits, disease susceptibility, and other complex characteristics, which are being shown by genome-wide association studies to lie mostly in noncoding, presumably regulatory, regions. There is every possibility that many of these variations will alter the interactions between regulatory RNAs and their targets, a prospect that should be borne in mind in future functional analyses

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

Emergence of Leadership within a Homogeneous Group

All the authors thank Byron Crouch for his work on performing exploratory simulations of the model. Some of the computing for this project was performed at the OU Supercomputing Center for Education & Research (OSCER) at the University of Oklahoma.Large scale coordination without dominant, consistent leadership is frequent in nature. How individuals emerge from within the group as leaders, however transitory this position may be, has become an increasingly common question asked. This question is further complicated by the fact that in many of these aggregations, differences between individuals are minor and the group is largely considered to be homogeneous. In the simulations presented here, we investigate the emergence of leadership in the extreme situation in which all individuals are initially identical. Using a mathematical model developed using observations of natural systems, we show that the addition of a simple concept of leadership tendencies which is inspired by observations of natural systems and is affected by experience can produce distinct leaders and followers using a nonlinear feedback loop. Most importantly, our results show that small differences in experience can promote the rapid emergence of stable roles for leaders and followers. Our findings have implications for our understanding of adaptive behaviors in initially homogeneous groups, the role experience can play in shaping leadership tendencies, and the use of self-assessment in adapting behavior and, ultimately, self-role-assignment.Yeshttp://www.plosone.org/static/editorial#pee

B0 meson decays to rho0 K*0, f0 K*0, and rho-K*+, including higher K* resonances

We present branching fraction measurements for the decays B0 -> rho0 K*0, B0 -> f0 K*0, and B0 -> rho- K*+, where K* is an S-wave (K pi)_0* or a K*(892) meson; we also measure B0 -> f0 K_2*(1430)^0. For the K*(892) channels, we report measurements of longitudinal polarization fractions (for rho final states) and direct CP-violation asymmetries. These results are obtained from a sample of (471.0 +/- 2.8) x 10^6 BBbar pairs collected with the BaBar detector at the PEP-II asymmetric-energy e+ e- collider at the SLAC National Accelerator Laboratory. We observe rho0 K*(892)^0, rho0 (K pi)_0^{*0}, f0 K*(892)^0, and rho- K*(892)+ with greater than 5 sigma significance, including systematics. We report first evidence for f0 (K pi)_0^{*0} and f0 K_2*(1430)^0, and place an upper limit on rho- (K pi)_0^{*+}. Our results in the K*(892) channels are consistent with no direct CP-violation.Comment: 17 pages, 6 postscript figures, submitted to Phys. Rev.