Author Correction: Obsessive–compulsive disorder
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Emotions and individual differences shape human foraging under threat
A common behavior in natural environments is foraging for rewards. However, this is often in the presence of predators. Therefore, one of the most fundamental decisions for humans, as for other animals, is how to apportion time between reward-motivated pursuit behavior and threat-motivated checking behavior. To understand what affects how people strike this balance, we developed an ecologically inspired task and looked at both within-participant dynamics (moods) and between-participant individual differences (questionnaires about real-life behaviors) in two large internet samples (n = 374 and n = 702) in a cross-sectional design. For the within-participant dynamics, we found that people regulate task-evoked stress homeostatically by changing behavior (increasing foraging and hiding). Individual differences, even in superficially related traits (apathy–anhedonia and anxiety–compulsive checking) reliably mapped onto unique behaviors. Worse task performance, due to maladaptive checking, was linked to gender (women checked excessively) and specific anxiety-related traits: somatic anxiety (reduced self-reported checking due to worry) and compulsivity (self-reported disorganized checking). While anhedonia decreased self-reported task engagement, apathy, strikingly, improved overall task performance by reducing excessive checking. In summary, we provide a multifaceted paradigm for assessment of checking for threat in a naturalistic task that is sensitive to both moods as they change throughout the task and clinical dimensions. Thus, it could serve as an objective measurement tool for future clinical studies interested in threat, vigilance or behavior–emotion interactions in contexts requiring both reward seeking and threat avoidance.
Associations between common genetic variants and income provide insights about the socio-economic health gradient
We conducted a genome-wide association study on income among individuals of European descent (N = 668,288) to investigate the relationship between socio-economic status and health disparities. We identified 162 genomic loci associated with a common genetic factor underlying various income measures, all with small effect sizes (the Income Factor). Our polygenic index captures 1–5% of income variance, with only one fourth due to direct genetic effects. A phenome-wide association study using this index showed reduced risks for diseases including hypertension, obesity, type 2 diabetes, depression, asthma and back pain. The Income Factor had a substantial genetic correlation (0.92, s.e. = 0.006) with educational attainment. Accounting for the genetic overlap of educational attainment with income revealed that the remaining genetic signal was linked to better mental health but reduced physical health and increased risky behaviours such as drinking and smoking. These findings highlight the complex genetic influences on income and health.
ARID2-related disorder: further delineation of the clinical phenotype of 27 novel individuals and description of an epigenetic signature
Rare genetic variants in ARID2 are responsible for a recently described neurodevelopmental condition called ARID2-related disorder (ARID2-RD). ARID2 belongs to PBAF, a unit of the SWI/SNF complex, which is a chromatin remodeling complex. This work aims to further delineate the phenotypic spectrum of ARID2-RD, providing clinicians with additional data for better care and aid in the future diagnosis of this condition. We obtained the genotypes and phenotypes of 27 previously unreported individuals with ARID2-RD and compared this series with findings in the literature. We also assessed peripheral blood DNA methylation profiles in individuals with ARID2-RD compared to episignatures of controls, unresolved cases, and other neurodevelopmental disorders. The main clinical features of ARID2-RD are developmental delay, speech disorders, intellectual disability (ID), behavior problems, short stature, and various dysmorphic and ectodermal features. Genome-wide differential methylation analysis revealed a global hypermethylated profile in ARID2-RD that could aid in reclassifying variants of uncertain significance. Our study doubles the number of reported individuals with ARID2 pathogenic variants to 53. It confirms loss-of-function as a pathomechanism and shows the absence of a clear genotype-phenotype correlation. We provide evidence for a unique DNA methylation episignature for ARID2-RD and further delineate the ARID2-associated phenotype.
Understanding learning through uncertainty and bias
Learning allows humans and other animals to make predictions about the environment that facilitate adaptive behavior. Casting learning as predictive inference can shed light on normative cognitive mechanisms that improve predictions under uncertainty. Drawing on normative learning models, we illustrate how learning should be adjusted to different sources of uncertainty, including perceptual uncertainty, risk, and uncertainty due to environmental changes. Such models explain many hallmarks of human learning in terms of specific statistical considerations that come into play when updating predictions under uncertainty. However, humans also display systematic learning biases that deviate from normative models, as studied in computational psychiatry. Some biases can be explained as normative inference conditioned on inaccurate prior assumptions about the environment, while others reflect approximations to Bayesian inference aimed at reducing cognitive demands. These biases offer insights into cognitive mechanisms underlying learning and how they might go awry in psychiatric illness.
Circular RNAs in neurological conditions – computational identification, functional validation, and potential clinical applications
Non-coding RNAs (ncRNAs) have gained significant attention in recent years due to advancements in biotechnology, particularly high-throughput total RNA sequencing. These developments have led to new understandings of non-coding biology, revealing that approximately 80% of non-coding regions in the genome possesses biochemical functionality. Among ncRNAs, circular RNAs (circRNAs), first identified in 1976, have emerged as a prominent research field. CircRNAs are abundant in most human cell types, evolutionary conserved, highly stable, and formed by back-splicing events which generate covalently closed ends. Notably, circRNAs exhibit high expression levels in neural tissue and perform diverse biochemical functions, including acting as molecular sponges for microRNAs, interacting with RNA-binding proteins to regulate their availability and activity, modulating transcription and splicing, and even translating into functional peptides in some cases. Recent advancements in computational and experimental methods have enhanced our ability to identify and validate circRNAs, providing valuable insights into their biological roles. This review focuses on recent developments in circRNA research as they related to neuropsychiatric and neurodegenerative conditions. We also explore their potential applications in clinical diagnostics, therapeutics, and future research directions. CircRNAs remain a relatively underexplored area of non-coding biology, particularly in the context of neurological disorders. However, emerging evidence supports their role as critical players in the etiology and molecular mechanisms of conditions such as schizophrenia, bipolar disorder, major depressive disorder, Alzheimer’s disease, and Parkinson’s disease. These findings suggest that circRNAs may provide a novel framework contributing to the molecular dysfunctions underpinning these complex neurological conditions.
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