Genetic Determinants of Financial Risk Taking

Individuals vary in their willingness to take financial risks. Here we show that variants of two genes that regulate dopamine and serotonin neurotransmission and have been previously linked to emotional behavior, anxiety and addiction (5-HTTLPR and DRD4) are significant determinants of risk taking in investment decisions. We find that the 5-HTTLPR s/s allele carriers take 28% less risk than those carrying the s/l or l/l alleles of the gene. DRD4 7-repeat allele carriers take 25% more risk than individuals without the 7-repeat allele. These findings contribute to the emerging literature on the genetic determinants of economic behavior

Estimation and testing for the effect of a genetic pathway on a disease outcome using logistic kernel machine regression via logistic mixed models

<p>Abstract</p> <p>Background</p> <p>Growing interest on biological pathways has called for new statistical methods for modeling and testing a genetic pathway effect on a health outcome. The fact that genes within a pathway tend to interact with each other and relate to the outcome in a complicated way makes nonparametric methods more desirable. The kernel machine method provides a convenient, powerful and unified method for multi-dimensional parametric and nonparametric modeling of the pathway effect.</p> <p>Results</p> <p>In this paper we propose a logistic kernel machine regression model for binary outcomes. This model relates the disease risk to covariates parametrically, and to genes within a genetic pathway parametrically or nonparametrically using kernel machines. The nonparametric genetic pathway effect allows for possible interactions among the genes within the same pathway and a complicated relationship of the genetic pathway and the outcome. We show that kernel machine estimation of the model components can be formulated using a logistic mixed model. Estimation hence can proceed within a mixed model framework using standard statistical software. A score test based on a Gaussian process approximation is developed to test for the genetic pathway effect. The methods are illustrated using a prostate cancer data set and evaluated using simulations. An extension to continuous and discrete outcomes using generalized kernel machine models and its connection with generalized linear mixed models is discussed.</p> <p>Conclusion</p> <p>Logistic kernel machine regression and its extension generalized kernel machine regression provide a novel and flexible statistical tool for modeling pathway effects on discrete and continuous outcomes. Their close connection to mixed models and attractive performance make them have promising wide applications in bioinformatics and other biomedical areas.</p

Mutational Biases and Selective Forces Shaping the Structure of Arabidopsis Genes

Recently features of gene expression profiles have been associated with structural parameters of gene sequences in organisms representing a diverse set of taxa. The emerging picture indicates that natural selection, mediated by gene expression profiles, has a significant role in determining genic structures. However the current situation is less clear in plants as the available data indicates that the effect of natural selection mediated by gene expression is very weak. Moreover, the direction of the patterns in plants appears to contradict those observed in animal genomes. In the present work we analized expression data for >18000 Arabidopsis genes retrieved from public datasets obtained with different technologies (MPSS and high density chip arrays) and compared them with gene parameters. Our results show that the impact of natural selection mediated by expression on genes sequences is significant and distinguishable from the effects of regional mutational biases. In addition, we provide evidence that the level and the breadth of gene expression are related in opposite ways to many structural parameters of gene sequences. Higher levels of expression abundance are associated with smaller transcripts, consistent with the need to reduce costs of both transcription and translation. Expression breadth, however, shows a contrasting pattern, i.e. longer genes have higher breadth of expression, possibly to ensure those structural features associated with gene plasticity. Based on these results, we propose that the specific balance between these two selective forces play a significant role in shaping the structure of Arabidopsis genes

Radically open-dialectical behavior therapy for adult anorexia nervosa: feasibility and outcomes from an inpatient program

Background Anorexia Nervosa (AN) is a highly life-threatening disorder that is extremely difficult to treat. There is evidence that family-based therapies are effective for adolescent AN, but no treatment has been proven to be clearly effective for adult AN. The methodological challenges associated with studying the disorder have resulted in recommendations that new treatments undergo preliminary testing prior to being evaluated in a randomized clinical trial. The aim of this study was to provide preliminary evidence on the effectiveness of a treatment program based on a novel adaptation of Dialectical Behavior Therapy (DBT) for adult Anorexia Nervosa (Radically Open-DBT; RO-DBT) that conceptualizes AN as a disorder of overcontrol. Methods Forty-seven individuals diagnosed with Anorexia Nervosa-restrictive type (AN-R; mean admission body mass index = 14.43) received the adapted DBT inpatient program (mean length of treatment = 21.7 weeks). Results Seventy-two percent completed the treatment program demonstrating substantial increases in body mass index (BMI; mean change in BMI = 3.57) corresponding to a large effect size (d = 1.91). Thirty-five percent of treatment completers were in full remission, and an additional 55% were in partial remission resulting in an overall response rate of 90%. These same individuals demonstrated significant and large improvements in eating-disorder related psychopathology symptoms (d = 1.17), eating disorder-related quality of life (d = 1.03), and reductions in psychological distress (d = 1.34). Conclusions RO-DBT was associated with significant improvements in weight gain, reductions in eating disorder symptoms, decreases in eating-disorder related psychopathology and increases in eating disorder-related quality of life in a severely underweight sample. These findings provide preliminary support for RO-DBT in treating AN-R suggesting the importance of further evaluation examining long-term outcomes using randomized controlled trial methodology

Angular and Current-Target Correlations in Deep Inelastic Scattering at HERA

Correlations between charged particles in deep inelastic ep scattering have been studied in the Breit frame with the ZEUS detector at HERA using an integrated luminosity of 6.4 pb-1. Short-range correlations are analysed in terms of the angular separation between current-region particles within a cone centred around the virtual photon axis. Long-range correlations between the current and target regions have also been measured. The data support predictions for the scaling behaviour of the angular correlations at high Q2 and for anti-correlations between the current and target regions over a large range in Q2 and in the Bjorken scaling variable x. Analytic QCD calculations and Monte Carlo models correctly describe the trends of the data at high Q2, but show quantitative discrepancies. The data show differences between the correlations in deep inelastic scattering and e+e- annihilation.Comment: 26 pages including 10 figures (submitted to Eur. J. Phys. C

Subwavelength anti-diffracting beams propagating over more than 1,000 Rayleigh lengths

Propagating light beams with widths down to and below the optical wavelength require bulky large-aperture lenses and remain focused only for micrometric distances. Here, we report the observation of light beams that violate this localization/depth- of-focus law by shrinking as they propagate, allowing resolution to be maintained and increased over macroscopic propagation lengths. In nanodisordered ferroelectrics we observe a non-paraxial propagation of a sub-micrometre-sized beam for over 1,000 diffraction lengths, the narrowest visible beam reported to date. This unprecedented effect is caused by the nonlinear response of a dipolar glass, which transforms the leading opticalwave equation into a Klein-Gordon-type equation that describes a massive particle field. Our findings open the way to high-resolution optics over large depths of focus, and a route to merging bulk optics into nanodevices

Plastisol Foaming Process. Decomposition of the Foaming Agent, Polymer Behavior in the Corresponding Temperature Range and Resulting Foam Properties

The decomposition of azodicarbonamide, used as foaming agent in PVC - plasticizer (1/1) plastisols was studied by DSC. Nineteen different plasticizers, all belonging to the ester family, two being polymeric (polyadipates), were compared. The temperature of maximum decomposition rate (in anisothermal regime at 5 K min-1 scanning rate), ranges between 434 and 452 K. The heat of decomposition ranges between 8.7 and 12.5 J g -1. Some trends of variation of these parameters appear significant and are discussed in terms of solvent (matrix) and viscosity effects on the decomposition reactions. The shear modulus at 1 Hz frequency was determined at the temperature of maximum rate of foaming agent decomposition, and differs significantly from a sample to another. The foam density was determined at ambient temperature and the volume fraction of bubbles was used as criterion to judge the efficiency of the foaming process. The results reveal the existence of an optimal shear modulus of the order of 2 kPa that corresponds roughly to plasticizer molar masses of the order of 450 ± 50 g mol-1. Heavier plasticizers, especially polymeric ones are too difficult to deform. Lighter plasticizers such as diethyl phthalate (DEP) deform too easily and presumably facilitate bubble collapse

Transcriptome-Wide Assessment of Human Brain and Lymphocyte Senescence

Identifying biological pathways that vary across the age spectrum can provide insight into fundamental mechanisms that impact disease and frailty in the elderly. Few methodological approaches offer the means to explore this question on as broad a scale as gene expression profiling. Here, we have evaluated mRNA expression profiles as a function of age in two populations; one consisting of 191 individuals with ages-at-death ranging from 65-100 years and with post-mortem brain mRNA measurements of 13,216 genes and a second with 1240 individuals ages 15-94 and lymphocyte mRNA estimates for 18,519 genes.Among negatively correlated transcripts, an enrichment of mitochondrial genes was evident in both populations, providing a replication of previous studies indicating this as a common signature of aging. Sample differences were prominent, the most significant being a decrease in expression of genes involved in translation in lymphocytes and an increase in genes involved in transcription in brain, suggesting that apart from energy metabolism other basic cell processes are affected by age but in a tissue-specific manner. In assessing genomic architecture, intron/exon sequence length ratios were larger among negatively regulated genes in both samples, suggesting that a decrease in the expression of non-compact genes may also be a general effect of aging. Variance in gene expression itself has been theorized to change with age due to accumulation of somatic mutations and/or increasingly heterogeneous environmental exposures, but we found no evidence for such a trend here.Results affirm that deteriorating mitochondrial gene expression is a common theme in senescence, but also highlight novel pathways and features of gene architecture that may be important for understanding the molecular consequences of aging

A four-gene LincRNA expression signature predicts risk in multiple cohorts of acute myeloid leukemia patients.

Prognostic gene expression signatures have been proposed as clinical tools to clarify therapeutic options in acute myeloid leukemia (AML). However, these signatures rely on measuring large numbers of genes and often perform poorly when applied to independent cohorts or those with older patients. Long intergenic non-coding RNAs (lincRNAs) are emerging as important regulators of cell identity and oncogenesis, but knowledge of their utility as prognostic markers in AML is limited. Here we analyze transcriptomic data from multiple cohorts of clinically annotated AML patients and report that (i) microarrays designed for coding gene expression can be repurposed to yield robust lincRNA expression data, (ii) some lincRNA genes are located in close proximity to hematopoietic coding genes and show strong expression correlations in AML, (iii) lincRNA gene expression patterns distinguish cytogenetic and molecular subtypes of AML, (iv) lincRNA signatures composed of three or four genes are independent predictors of clinical outcome and further dichotomize survival in European Leukemia Net (ELN) risk groups and (v) an analytical tool based on logistic regression analysis of quantitative PCR measurement of four lincRNA genes (LINC4) can be used to determine risk in AML