Methodological Issues in Malingering Research: The Use of Simulation Designs

The accurate determination of malingering relies on the use of validated and clinically relevant assessment measures. Simulation design is the most often-used research design to accomplish this. However, its external validity is sometimes questioned. The goal of the thesis was to systematically evaluate these major elements: situation, incentives, and coaching. The situation in simulation studies can vary from relevant (academic failure in a college population) to irrelevant (capital murder) for the samples being studied. Incentives refer to the external motivation given to improve simulators' performance and can be positive (extra credit and monetary reward) or negative (extra time and effort). Finally, coaching refers to whether the participant receives any information on detection strategies that are designed to identify feigners. Using a large undergraduate sample in a factorial design, results indicate that a scenario familiar to the participants generally improved the believability of their responses. Coaching also improved the ability to feign convincingly, while incentive type was not associated with any change in scores. The implications of these findings for future research designs and the connection to practice are discussed

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease

Denial of Risk: the Effects of Intentional Minimization on Risk Assessments for Psychopathic and Nonpsychopathic Offenders

Risk assessments for offenders often combine past records with current clinical findings from observations, interviews, and test data. Conclusions based on these risk assessments are highly consequential, sometimes resulting in increased criminal sentences or prolonged hospitalization. Offenders are therefore motivated to intentionally minimize their risk scores. Intentional minimization is especially likely to occur in offenders with high psychopathic traits because goal-directed deception is reflected in many of the core traits of the disorder, such as manipulativeness, glibness, and superficial charm. However, this connection appears to be based on the conceptual understanding of psychopathy, and it has rarely been examined empirically for either frequency or success. The current study examined the connection between psychopathic traits and the intentional minimization of risk factors using a sentenced jail sample. In general, offenders were able to effectively minimize risk on the HCR-20 and SAQ, while the PICTS, as a measure of cognitive styles, was more resistant to such minimization. Psychopathic traits, especially high interpersonal facet scores, led to greater minimization using a repeated measure, simulation design. Important differences in the willingness and ability to use deception were found based on (a) the content of subscales, and (b) the mode of administration (i.e., interview vs. self-report). The important implications of this research are discussed for risk assessment procedures regarding likely areas of deception and its detection. It also informs the growing literature on the connection between psychopathic traits and deception

Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease

Long non-coding RNA (lncRNA) genes have well-established and important impacts on molecular and cellular functions. However, among the thousands of lncRNA genes, it is still a major challenge to identify the subset with disease or trait relevance. To systematically characterize these lncRNA genes, we used Genotype Tissue Expression (GTEx) project v8 genetic and multi-tissue transcriptomic data to profile the expression, genetic regulation, cellular contexts, and trait associations of 14,100 lncRNA genes across 49 tissues for 101 distinct complex genetic traits. Using these approaches, we identified 1,432 lncRNA gene-trait associations, 800 of which were not explained by stronger effects of neighboring protein-coding genes. This included associations between lncRNA quantitative trait loci and inflammatory bowel disease, type 1 and type 2 diabetes, and coronary artery disease, as well as rare variant associations to body mass index.[Display omitted]•29% of lncRNA genes with eQTLs show tissue-specific genetic regulation•Co-expression networks and single-cell data provide annotations for 94% of lncRNAs•Rare variants near lncRNA expression outliers impact complex traits, like BMI•We identify 800 lncRNA-trait relationships not explained by protein-coding genesA systematic analysis of NIH Genotype Tissue Expression (GTEx) project data provides insights into lncRNA expression patterns and functions, explores the impact of genetic variation on lncRNAs, and connects lncRNAs to complex traits and human disease