Psychological Research Articles

The genetic landscape of neuro-related proteins in human plasma.

Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioural traits and the disease aetiology of neuropsychiatric disorders. Here the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,000 individuals for 184 neuro-related proteins in human plasma. The analysis identified 125 cis-regulatory protein quantitative trait loci (cis-pQTL) and 164 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. At the cis-pQTL, multiple proteins shared a genetic basis with human behavioural traits such as alcohol and food intake, smoking and educational attainment, as well as neurological conditions and psychiatric disorders such as pain, neuroticism and schizophrenia. Integrating with established drug information, the causal inference analysis validated 52 out of 66 matched combinations of protein targets and diseases or side effects with available drugs while suggesting hundreds of repurposing and new therapeutic targets.

A scalable adaptive quadratic kernel method for interpretable epistasis analysis in complex traits.

Our knowledge of the contribution of genetic interactions (epistasis) to variation in human complex traits remains limited, partly due to the lack of efficient, powerful, and interpretable algorithms to detect interactions. Recently proposed approaches for set-based association tests show promise in improving the power to detect epistasis by examining the aggregated effects of multiple variants. Nevertheless, these methods either do not scale to large Biobank data sets or lack interpretability. We propose QuadKAST, a scalable algorithm focused on testing pairwise interaction effects (quadratic effects) within small to medium-sized sets of genetic variants (window size ≤100) on a trait and provide quantified interpretation of these effects. Comprehensive simulations show that QuadKAST is well-calibrated. Additionally, QuadKAST is highly sensitive in detecting loci with epistatic signals and accurate in its estimation of quadratic effects. We applied QuadKAST to 52 quantitative phenotypes measured in ≈300,000 unrelated white British individuals in the UK Biobank to test for quadratic effects within each of 9515 protein-coding genes. We detect 32 trait-gene pairs across 17 traits and 29 genes that demonstrate statistically significant signals of quadratic effects (accounting for the number of genes and traits tested). Across these trait-gene pairs, the proportion of trait variance explained by quadratic effects is comparable to additive effects, with five pairs having a ratio >1. Our method enables the detailed investigation of epistasis on a large scale, offering new insights into its role and importance.

Nutrition, Other Environmental Influences, and Genetics in the Determination of Human Stature.

Linear growth during three distinct stages of life determines attained stature in adulthood: namely, in utero, early postnatal life, and puberty and the adolescent period. Individual host factors, genetics, and the environment, including nutrition, influence attained human stature. Each period of physical growth has its specific biological and environmental considerations. Recent epidemiologic investigations reveal a strong influence of prenatal factors on linear size at birth that in turn influence the postnatal growth trajectory. Although average population height changes have been documented in high-income regions, stature as a complex human trait is not well understood or easily modified. This review summarizes the biology of linear growth and its major drivers including nutrition from a life-course perspective, the genetics of programmed growth patterns or height, and gene-environment interactions that determine human stature in toto over the life span. Implications for public health interventions and knowledge gaps are discussed.

Human capital and black-white earnings gaps, 1966–2019

This paper estimates the contribution of human capital, measured using educational attainment and standardized test scores, to Black-white gaps in labor market outcomes in three separate samples of both men and women spanning the period from 1966 through 2019. There are three main findings. First, the magnitude of the reduction in the earnings gap that occurs after controlling for education and test scores has become much larger over time, suggesting a growing contribution of these traits to Black-white earnings disparities. Second, growth in the explanatory power of education and test scores has been primarily due to increases in the association between these traits and the likelihood of non-work, with no clear increases for hourly wages or other intensive earnings margins. Third, in most cases these trends are due to changes in the returns to the human capital traits, rather than changing racial gaps in the human capital traits themselves. These main findings apply qualitatively to both men and women. However, the magnitude of attenuation is much larger for women than for men, and conditional racial gaps in labor market outcome among women are often close to zero. Evidence suggests that this parity between Black and white women conditional on education and test scores is not primarily due to sample selection. Overall, the paper’s findings highlight how structural developments in the US labor market, such as increasing returns to skill and changing labor force participation rates by skill level and gender, have had disparate impacts across racial groups despite being race-neutral on their face.

Looking Back at Wasteland(s): A Historiographic Metafictional Reading of Kurt Vonnegut’s Slaughterhouse-Five

Some moments can never become memories; on the contrary, every breath taken, every word uttered, and every gesture performed are reminiscent of them. Much as the past is said to be past, it never dies. Memories of war belong to this group of the past never past, as in Kurt Vonnegut's Slaughterhouse-Five (1969). The novel centres on a traumatized survivor of the Dresden bombing of World War II with an untraditional, fragmented, surreal, and impressive narrative style and generic hybridity of science fiction and historiographic metafiction. Slaughterhouse-Five is an example of historiographic metafiction in that it presents the bombing as a historical fact combined with fictional characters and the author's self-references, experiences, and interpretation of the event. The novel is also a significant work with regard to trauma studies inasmuch as it portrays the effects of wars on human psychology, the traumatized protagonist of the novel, along with other characters, including the author himself. Vonnegut employs metafictional elements to display that people experiencing war trauma create figurative wastelands, their minds become confused and disorganized, and the line between reality and fiction blurs, and thereby, he challenges the conventional boundaries between fiction and history. In that regard, what follows is an attempt to demonstrate how wars turn landscapes and human beings into wastelands both literally and figuratively through not only the author’s but also the protagonist Billy Pilgrim’s experiences and, finally, how postmodernism could be a tool to demonstrate those traumas.

The Genetics of Human Sleep and Sleep Disorders.

Healthy sleep is vital for humans to achieve optimal health and longevity. Poor sleep and sleep disorders are strongly associated with increased morbidity and mortality. However, the importance of good sleep continues to be underrecognized. Mechanisms regulating sleep and its functions in humans remain mostly unclear even after decades of dedicated research. Advancements in gene sequencing techniques and computational methodologies have paved the way for various genetic analysis approaches, which have provided some insights into human sleep genetics. This review summarizes our current knowledge of the genetic basis underlying human sleep traits and sleep disorders. We also highlight the use of animal models to validate genetic findings from human sleep studies and discuss potential molecular mechanisms and signaling pathways involved in the regulation of human sleep.

Unraveling NEK4 as a Potential Drug Target in Schizophrenia and Bipolar I Disorder: A Proteomic and Genomic Approach.

Investigating the shared brain protein and genetic components of schizophrenia (SCZ) and bipolar I disorder (BD-I) presents a unique opportunity to understand the underlying pathophysiological processes and pinpoint potential drug targets. To identify overlapping susceptibility brain proteins in SCZ and BD-I, we carried out proteome-wide association studies (PWAS) and Mendelian Randomization (MR) by integrating human brain protein quantitative trait loci with large-scale genome-wide association studies for both disorders. We utilized transcriptome-wide association studies (TWAS) to determine the consistency of mRNA-protein dysregulation in both disorders. We applied pleiotropy-informed conditional false discovery rate (pleioFDR) analysis to identify common risk genetic loci for SCZ and BD-I. Additionally, we performed a cell-type-specific analysis in the human brain to detect risk genes notably enriched in distinct brain cell types. The impact of risk gene overexpression on dendritic arborization and axon length in neurons was also examined. Our PWAS identified 42 proteins associated with SCZ and 14 with BD-I, among which NEK4, HARS2, SUGP1, and DUS2 were common to both conditions. TWAS and MR analysis verified the significant risk gene NEK4 for both SCZ and BD-I. PleioFDR analysis further supported genetic risk loci associated with NEK4 for both conditions. The cell-type specificity analysis revealed that NEK4 is expressed on the surface of glutamatergic neurons, and its overexpression enhances dendritic arborization and axon length in cultured primary neurons. These findings underscore a shared genetic origin for SCZ and BD-I, offering novel insights for potential therapeutic target identification.

Fine-mapping across diverse ancestries drives the discovery of putative causal variants underlying human complex traits and diseases.

Genome-wide association studies (GWAS) of human complex traits or diseases often implicate genetic loci that span hundreds or thousands of genetic variants, many of which have similar statistical significance. While statistical fine-mapping in individuals of European ancestry has made important discoveries, cross-population fine-mapping has the potential to improve power and resolution by capitalizing on the genomic diversity across ancestries. Here we present SuSiEx, an accurate and computationally efficient method for cross-population fine-mapping. SuSiEx integrates data from an arbitrary number of ancestries, explicitly models population-specific allele frequencies and linkage disequilibrium patterns, accounts for multiple causal variants in a genomic region and can be applied to GWAS summary statistics. We comprehensively assessed the performance of SuSiEx using simulations. We further showed that SuSiEx improves the fine-mapping of a range of quantitative traits available in both the UK Biobank and Taiwan Biobank, and improves the fine-mapping of schizophrenia-associated loci by integrating GWAS across East Asian and European ancestries.

Should Doctor Robot possessmoralempathy?

Critics of clinical artificial intelligence (AI) suggest that the technology is ethically harmful because it may lead to the dehumanization of the doctor-patient relationship (DPR) by eliminating moral empathy, which is viewed as a distinctively human trait. The benefits of clinical empathy-that is, moral empathy applied in the clinical context-are widely praised, but this praise is often unquestioning and lacks context. In this article, I will argue that criticisms of clinical AI based on appeals to empathy are misplaced. As psychological and philosophical research has shown, empathy leads to certain types of biased reasoning and choices. These biases of empathy consistently impact the DPR. Empathy may lead to partial judgments and asymmetric DPRs, as well as disparities in the treatment of patients, undermining respect for patient autonomy and equality. Engineers should consider the flaws of empathy when designing affective artificial systems in the future. The nature of sympathy and compassion (i.e., displaying emotional concern while maintaining some balanced distance) has been defended by some ethicists as more beneficial than perspective-taking in the clinical context. However, these claims do not seem to have impacted the AI debate. Thus, this articlewill also argue that if machines are programmed for affective behavior, they should also be given some ethical scaffolding.

Public perceptions and acceptance of artificial intelligence humanoid bots/robots: Evidence from Turkey

The development of artificial intelligence (AI) humanoid bots/robots (AIHB/R), which integrate AI with robot technology to emulate human traits, has swiftly evolved and found applications in several sectors like healthcare, education, home support, industrial production, and entertainment. AIHB/R's decision-making process has become more complex due to incorporating AI, a fascinating element affecting public perceptions and attitudes towards these robots. This paper investigates this topic in the Turkish context based on data collected from 485 adults. A general finding is that participants have positive perceptions and attitudes towards (AIHB/R) and some concerns. We found significant gender differences between male and female participants regarding the use of AIHB/R in care and treatment services (CTS), administration and justice (AJ), and in the future (FC). No gender difference was found when using religious practice (RP). The educational level statistically correlated significantly with the total scale scores and the four sub-domains. CTS has a positive and moderately significant effect on accepting AIHB/R applications. The R2 value for this domain showed the highest explanatory power of the model with 0.829.

Viewing machines as humans but humans as machines? Social connectedness shapes the robot anthropomorphism-dehumanization link

Human interactions with social robots inevitably involve anthropomorphism. Concerns have arisen regarding whether robot anthropomorphism is accompanied by negative human relationships. In particular, limited empirical research suggests that the more humanness people attribute to nonhuman agents (e.g., social robots), the more they deny to humans, thus implying a positive association between robot anthropomorphism and dehumanization. From a motivational perspective, we examined whether social connectedness—the perception of closeness with others—may expand the scope of agents deserving to be treated as having humanness, thereby tempering the possible positive association between robot anthropomorphism and dehumanization. Across three studies (two preregistered) conducted with Chinese participants, we induced social connectedness and measured anthropomorphism of social robots and dehumanization of certain individuals. Robot anthropomorphism negatively predicted dehumanization on human nature traits and the mental capacity to feel among participants induced to feel social connectedness (but not social neutrality or disconnectedness). Although their generalizability across diverse cultures warrants further investigation, our findings offer novel theoretical insights into humanness attribution, and practical implications for promoting social cohesion in the era of intelligent machines.

Enhancing MBTI Personality Prediction from Text Data with Advance Word Embedding Technique.

Understanding human personality traits is crucial for various domains, including psychology, education, and human resources. The Myers-Briggs Type Indicator (MBTI) is a widely recognized psychological assessment tool, categorizing individuals into one of sixteen distinct personality types. The existing methodologies, which primarily relied on Word2Vec embeddings and traditional machine learning models, showed promise but left room for improvement. To address this problem, this research focused on enhancing Myers-Briggs Type Indicator (MBTI) personality prediction from text data through advanced word-embedding techniques, specifically GloVe and BERT. The research investigates the effectiveness of various Machine Learning Classifiers, including Random Forest, XGBoost, LinearSVC, SGD, Logistic Regression, and CatBoost, in predicting MBTI personality types. Additionally, the impact of preprocessing techniques such as text cleaning, tokenization, TF-IDF vectorization, GloVe, and BERT embeddings on classification performance is examined. Furthermore, the research explores strategies for addressing class imbalance through upsampling techniques. Results indicate high accuracy and performance across multiple classifiers, with XGBoost achieving the highest accuracy of 97.33%. The analysis of MBTI dimensions reveals nuanced insights into the classifiers' ability to capture specific personality traits.

Widespread natural selection on metabolite levels in humans.

Natural selection acts ubiquitously on complex human traits, predominantly constraining the occurrence of extreme phenotypes (stabilizing selection). These constraints propagate to DNA sequence variants associated with traits under selection. The genetic signatures of such evolutionary events can thus be detected via combining effect size estimates from genetic association studies and the corresponding allele frequencies. Although this approach has been successfully applied to high-level traits, the prevalence and mode of selection acting on molecular traits remain poorly understood. Here, we estimate the action of natural selection on genetic variants associated with metabolite levels, an important layer of molecular traits. By leveraging summary statistics of published genome-wide association studies with large sample sizes, we find strong evidence of stabilizing selection for 15 out of 97 plasma metabolites, with nonessential amino acids displaying especially strong selection signatures. Mendelian randomization analysis reveals that metabolites under stronger stabilizing selection display larger effects on a range of clinically relevant complex traits, suggesting that maintaining a disease-free profile may be an important source of selective constraints on the metabolome. Metabolites under strong stabilizing selection in humans are also more conserved in their concentrations among diverse mammalian species, suggesting shared selective forces across micro- and macroevolutionary timescales. Overall, this study demonstrates that variation in metabolite levels among humans is frequently shaped by natural selection and this may act through their causal impact on disease susceptibility.

A genome-wide investigation into the underlying genetic architecture of personality traits and overlap with psychopathology.

Personality is influenced by both genetic and environmental factors and is associated with other psychiatric traits such as anxiety and depression. The 'big five' personality traits, which include neuroticism, extraversion, agreeableness, conscientiousness and openness, are a widely accepted and influential framework for understanding and describing human personality. Of the big five personality traits, neuroticism has most often been the focus of genetic studies and is linked to various mental illnesses, including depression, anxiety and schizophrenia. Our knowledge of the genetic architecture of the other four personality traits is more limited. Here, utilizing the Million Veteran Program cohort, we conducted a genome-wide association study in individuals of European and African ancestry. Adding other published data, we performed genome-wide association study meta-analysis for each of the five personality traits with sample sizes ranging from 237,390 to 682,688. We identified 208, 14, 3, 2 and 7 independent genome-wide significant loci associated with neuroticism, extraversion, agreeableness, conscientiousness and openness, respectively. These findings represent 62 novel loci for neuroticism, as well as the first genome-wide significant loci discovered for agreeableness. Gene-based association testing revealed 254 genes showing significant association with at least one of the five personality traits. Transcriptome-wide and proteome-wide analysis identified altered expression of genes and proteins such as CRHR1, SLC12A5, MAPT and STX4. Pathway enrichment and drug perturbation analyses identified complex biology underlying human personality traits. We also studied the inter-relationship of personality traits with 1,437 other traits in a phenome-wide genetic correlation analysis, identifying new associations. Mendelian randomization showed positive bidirectional effects between neuroticism and depression and anxiety, while a negative bidirectional effect was observed for agreeableness and these psychiatric traits. This study improves our comprehensive understanding of the genetic architecture underlying personality traits and their relationship to other complex human traits.

A plasma proteomic signature links secretome of senescent monocytes to aging- and obesity-related clinical outcomes in humans.

Cellular senescence increases with age and contributes to age-related declines and pathologies. We identified circulating biomarkers of senescence associated with diverse clinical traits in humans to facilitate future non-invasive assessment of individual senescence burden and efficacy testing of novel senotherapeutics. Using a novel nanoparticle-based proteomic workflow, we profiled the senescence-associated secretory phenotype (SASP) in monocytes and examined these proteins in plasma samples (N = 1060) from the Baltimore Longitudinal Study of Aging (BLSA). Machine learning models trained on monocyte SASP associated with several age-related phenotypes in a test cohort, including body fat composition, blood lipids, inflammation, and mobility-related traits, among others. Notably, a subset of SASP-based predictions, including a 'high impact' SASP panel that predicts age- and obesity-related clinical traits, were validated in InCHIANTI, an independent aging cohort. These results demonstrate the clinical relevance of the circulating SASP and identify relevant biomarkers of senescence that could inform future clinical studies.

Tropomyosin 1 deficiency facilitates cell state transitions and enhances hemogenic endothelial cell specification during hematopoiesis

Tropomyosins coat actin filaments to impact actin-related signaling and cell morphogenesis. Genome-wide association studies have linked Tropomyosin 1 (TPM1) with human blood trait variation. TPM1 has been shown to regulate blood cell formation invitro, but it remains unclear how or when TPM1 affects hematopoiesis. Using gene-edited induced pluripotent stem cell (iPSC) model systems, we found that TPM1 knockout augmented developmental cell state transitions and key signaling pathways, including tumor necrosis factor alpha (TNF-α) signaling, to promote hemogenic endothelial (HE) cell specification and hematopoietic progenitor cell (HPC) production. Single-cell analyses revealed decreased TPM1 expression during human HE specification, suggesting that TPM1 regulated invivo hematopoiesis via similar mechanisms. Analyses of a TPM1 gene trap mouse model showed that TPM1 deficiency enhanced HE formation during embryogenesis, without increasing the number of hematopoietic stem cells. These findings illuminate novel effects of TPM1 on developmental hematopoiesis.

Genes with differential expression across ancestries are enriched in ancestry-specific disease effects likely due to gene-by-environment interactions

Multi-ancestry genome-wide association studies (GWASs) have highlighted the existence of variants with ancestry-specific effect sizes. Understanding where and why these ancestry-specific effects occur is fundamental to understanding the genetic basis of human diseases and complex traits. Here, we characterized genes differentially expressed across ancestries (ancDE genes) at the cell-type level by leveraging single-cell RNA-sequencing data in peripheral blood mononuclear cells for 21 individuals with East Asian (EAS) ancestry and 23 individuals with European (EUR) ancestry (172,385 cells); then, we tested whether variants surrounding those genes were enriched in disease variants with ancestry-specific effect sizes by leveraging ancestry-matched GWASs of 31 diseases and complex traits (average n ∼ 90,000 and ∼ 267,000 in EAS and EUR, respectively). We observed that ancDE genes tended to be cell-type specific and enriched in genes interacting with the environment and in variants with ancestry-specific disease effect sizes, which suggests cell-type-specific, gene-by-environment interactions shared between regulatory and disease architectures. Finally, we illustrated how different environments might have led to ancestry-specific myeloid cell leukemia 1 (MCL1) expression in B cells and ancestry-specific allele effect sizes in lymphocyte count GWASs for variants surrounding MCL1. Our results imply that large single-cell and GWAS datasets from diverse ancestries are required to improve our understanding of human diseases.

A Review of Research on Foreign Language Enjoyment in Second Language Learning

Positive psychology (pp) is a branch of human psychology that specialises in the study of methods to evoke positive psychological dispositions in people. It advocates a focus on mental health and emotional experience, and on the well-being of people's lives. Pp was introduced to the field of second language acquisition around 2012. The past decade has seen a surge in research and discussion surrounding the emotions experienced by English language learners. Two of the most prominent emotions are foreign language anxiety and foreign language enjoyment (FLE). This study employs a literature analysis to investigate the influence of FLE on second language acquisition. The findings indicate that the degree of FLE experienced by different research subjects varies and that these emotions are correlated with foreign language anxiety. Finally, this study demonstrates How positive emotions affect the acquisition of foreign language proficiency and performance. The primary focus of the study is the influence of FLE on students' SLA abilities. This is a significant area of research that offers valuable insights for educators seeking to create positive learning environments in the English classroom.

Constructs of the Stress–Appraisal–Coping Theory and Positive Human Traits as Predictors of Perceived Stress in People With Multiple Sclerosis: Implications for Rehabilitation Professions

People with multiple sclerosis (MS) often have to cope with high levels of stress. Lazarus and Folkman’s (1984) stress–appraisal–coping theory emphasizes the relationship between the individual and the environment, suggesting that a stress response is highly influenced by individual appraisal processes. This study aimed to evaluate constructs of Lazarus and Folkman’s stress–appraisal–coping theory and positive human traits as predictors of perceived stress in a sample of 477 adults with MS. Hierarchical regression analysis was used to determine the incremental variance in perceived stress accounted for by demographic covariates, functional disabilities, challenge appraisal, and positive human traits. Core self-evaluations, challenge appraisal, limitations in social/cognitive functioning, agency hope, and age were significant predictors in the final model, accounting for 68% of the variance in perceived stress scores (R2= .68,f2= 2.13; large effect size). Core self-evaluations and challenge appraisal were the strongest predictors of perceived stress. The findings from this study will help rehabilitation professionals develop empirically supported stress management and well-being interventions, enabling people with MS to cope effectively with stressors and challenges and improve their health and well-being.

Redefining Vygotsky’s early works as a theory of aesthetics

The paper critically examines Lev Vygotsky’s art-related texts from 1915 to 1924, challenging interpretations based in Psychology by asserting that his aesthetic framework transcends outdated objectivist references, offering a nuanced philosophical perspective. Situating this within post-1917 Revolutionary Russia, the study explores its alignment with the visions of a ‘Revolutionary’ theatre for the ‘new human being’ in the Russian Futurist movement. It underscores Vygotsky’s pursuit of empirical evidence for understanding theatre’s impact on individuals and society, highlighting Marxist dialectics as the backbone of his aesthetic thought. Moreover, it establishes a connection between Vygotsky’s thought and Formalism, rooted in their shared emphasis on art’s structural features and links his ideas with Futurism, exploring their shared belief in the transformative power of form as a crucial element in provoking social change. The paper defines Vygotsky’s aesthetics, focusing on integral aspects of artistic reception, particularly emotion and imagination. It traces the shifts in Vygotsky’s understanding of these terms from his early reliance on psychoanalysis to the incorporation of dialectic and, later, cultural-historical perspectives, thus integrating Vygotsky’s later theories on human psychology into his aesthetic theory. The paper concludes by exploring the resonance between Vygotsky’s redefined aesthetics and contemporary Cognitive Theatre Studies. It draws attention to methodological convergence and shared insights on the interplay between natural and cultural influences, such as image schemas and conceptual blending, emphasising the enduring relevance of Vygotsky’s perspective on artistic structure and theatre’s transformative socio-political impact.