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The Hierarchical Taxonomy of Psychopathology (HiTOP) is an empirical structural model of psychological symptoms formulated to improve the reliability and validity of clinical assessment. Neurobiology can inform assessments of early risk and intervention strategies, and the HiTOP model has greater potential to interface with neurobiological measures than traditional categorical diagnoses given its enhanced reliability. However, one complication is that observed biological correlates of clinical symptoms can reflect various factors, ranging from dispositional risk to consequences of psychopathology. In this paper, we argue that the HiTOP model provides an optimized framework for conducting research on the biological correlates of psychopathology from an ontogenetic perspective that distinguishes among indicators of liability, current symptoms, and consequences of illness. Through this approach, neurobiological research can contribute more effectively to identifying individuals at high dispositional risk, indexing treatment-related gains, and monitoring the consequences of mental illness, consistent with the aims of the HiTOP framework.
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Genetic discovery in psychiatry and clinical psychology is hindered by suboptimal phenotypic definitions. We argue that the hierarchical, dimensional, and data-driven classification system proposed by the Hierarchical Taxonomy of Psychopathology (HiTOP) consortium provides a more effective approach to identifying genes that underlie mental disorders, and to studying psychiatric etiology, than current diagnostic categories. Specifically, genes are expected to operate at different levels of the HiTOP hierarchy, with some highly pleiotropic genes influencing higher order psychopathology (e.g., the general factor), whereas other genes conferring more specific risk for individual spectra (e.g., internalizing), subfactors (e.g., fear disorders), or narrow symptoms (e.g., mood instability). We propose that the HiTOP model aligns well with the current understanding of the higher order genetic structure of psychopathology that has emerged from a large body of family and twin studies. We also discuss the convergence between the HiTOP model and findings from recent molecular studies of psychopathology indicating broad genetic pleiotropy, such as cross-disorder SNP-based shared genetic covariance and polygenic risk scores, and we highlight molecular genetic studies that have successfully redefined phenotypes to enhance precision and statistical power. Finally, we suggest how to integrate a HiTOP approach into future molecular genetic research, including quantitative and hierarchical assessment tools for future data-collection and recommendations concerning phenotypic analyses. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

For more than a century, research on psychopathology has focused on categorical diagnoses. Although this work has produced major discoveries, growing evidence points to the superiority of a dimensional approach to the science of mental illness. Here we outline one such dimensional system-the Hierarchical Taxonomy of Psychopathology (HiTOP)-that is based on empirical patterns of co-occurrence among psychological symptoms. We highlight key ways in which this framework can advance mental-health research, and we provide some heuristics for using HiTOP to test theories of psychopathology. We then review emerging evidence that supports the value of a hierarchical, dimensional model of mental illness across diverse research areas in psychological science. These new data suggest that the HiTOP system has the potential to accelerate and improve research on mental-health problems as well as efforts to more effectively assess, prevent, and treat mental illness.

Some people are more willing to make immediate, risky, or costly reward-focused choices than others, which has been hypothesized to be associated with individual differences in dopamine (DA) function. In two studies using PET imaging, one empirical (Study 1: N = 144 males and females across 3 samples) and one meta-analytic (Study 2: N = 307 across 12 samples), we sought to characterize associations between individual differences in DA and time, probability, and physical effort discounting in human adults. Study 1 demonstrated that individual differences in DA D2-like receptors were not associated with time or probability discounting of monetary rewards in healthy humans, and associations with physical effort discounting were inconsistent across adults of different ages. Meta-analytic results for temporal discounting corroborated our empirical finding for minimal effect of DA measures on discounting in healthy individuals but suggested that associations between individual differences in DA and reward discounting depend on clinical features. Addictions were characterized by negative correlations between DA and discounting, but other clinical conditions, such as Parkinson's disease, obesity, and attention-deficit/hyperactivity disorder, were characterized by positive correlations between DA and discounting. Together, the results suggest that trait differences in discounting in healthy adults do not appear to be strongly associated with individual differences in D2-like receptors. The difference in meta-analytic correlation effects between healthy controls and individuals with psychopathology suggests that individual difference findings related to DA and reward discounting in clinical samples may not be reliably generalized to healthy controls, and vice versa.SIGNIFICANCE STATEMENT Decisions to forgo large rewards for smaller ones due to increasing time delays, uncertainty, or physical effort have been linked to differences in dopamine (DA) function, which is disrupted in some forms of psychopathology. It remains unclear whether alterations in DA function associated with psychopathology also extend to explaining associations between DA function and decision making in healthy individuals. We show that individual differences in DA D2 receptor availability are not consistently related to monetary discounting of time, probability, or physical effort in healthy individuals across a broad age range. By contrast, we suggest that psychopathology accounts for observed inconsistencies in the relationship between measures of DA function and reward discounting behavior.

The latent structure of schizotypy and psychosis-spectrum symptoms remains poorly understood. Furthermore, molecular genetic substrates are poorly defined, largely due to the substantial resources required to collect rich phenotypic data across diverse populations. Sample sizes of phenotypic studies are often insufficient for advanced structural equation modeling approaches. In the last 50 years, efforts in both psychiatry and psychological science have moved toward (1) a dimensional model of psychopathology (eg, the current Hierarchical Taxonomy of Psychopathology [HiTOP] initiative), (2) an integration of methods and measures across traits and units of analysis (eg, the RDoC initiative), and (3) powerful, impactful study designs maximizing sample size to detect subtle genomic variation relating to complex traits (the Psychiatric Genomics Consortium [PGC]). These movements are important to the future study of the psychosis spectrum, and to resolving heterogeneity with respect to instrument and population. The International Consortium of Schizotypy Research is composed of over 40 laboratories in 12 countries, and to date, members have compiled a body of schizotypy- and psychosis-related phenotype data from more than 30000 individuals. It has become apparent that compiling data into a protected, relational database and crowdsourcing analytic and data science expertise will result in significant enhancement of current research on the structure and biological substrates of the psychosis spectrum. The authors present a data-sharing infrastructure similar to that of the PGC, and a resource-sharing infrastructure similar to that of HiTOP. This report details the rationale and benefits of the phenotypic data collective and presents an open invitation for participation.

Every day, humans make countless decisions that require the integration of information about potential benefits (i.e. rewards) with other decision features (i.e. effort required, probability of an outcome or time delays). Here, we examine the overlap and dissociation of behavioral preferences and neural representations of subjective value in the context of three different decision features (physical effort, probability and time delays) in a healthy adult life span sample. While undergoing functional neuroimaging, participants (N = 75) made incentive compatible choices between a smaller monetary reward with lower physical effort, higher probability, or a shorter time delay versus a larger monetary reward with higher physical effort, lower probability, or a longer time delay. Behavioral preferences were estimated from observed choices, and subjective values were computed using individual hyperbolic discount functions. We found that discount rates were uncorrelated across tasks. Despite this apparent behavioral dissociation between preferences, we found overlapping subjective value-related activity in the medial prefrontal cortex across all three tasks. We found no consistent evidence for age differences in either preferences or the neural representations of subjective value across adulthood. These results suggest that while the tolerance of decision features is behaviorally dissociable, subjective value signals share a common representation across adulthood.

Although research on aging and decision making continues to grow, the majority of studies examine decisions made to maximize monetary earnings or points. It is not clear whether these results generalize to other types of rewards. To investigate this, we examined adult age differences in 92 healthy participants aged 22 to 83. Participants completed 9 hypothetical discounting tasks, which included 3 types of discounting factors (time, probability, effort) across 3 reward domains (monetary, social, health). Participants made choices between a smaller magnitude reward with a shorter time delay/higher probability/lower level of physical effort required and a larger magnitude reward with a longer time delay/lower probability/higher level of physical effort required. Older compared with younger individuals were more likely to choose options that involved shorter time delays or higher probabilities of experiencing an interaction with a close social partner or receiving health benefits from a hypothetical drug. These findings suggest that older adults may be more motivated than young adults to obtain social and health rewards immediately and with certainty. (PsycINFO Database Record

Rate of delivery of psychostimulants has been associated with their positive euphoric effects and potential addiction liability. However, information on individual differences in onset of d-amphetamine's effects remains scarce. We examined individual differences in the time to peak subjective and physiological effects and the pharmacokinetics/pharmacodynamics of oral d-amphetamine. We considered two independent studies that used different dosing regimens where subjects completed the drug effects questionnaire at multiple time points post d-amphetamine. Based on the observation of distinct individual differences in time course of drug effects questionnaire "feel", "high", and "like" ratings (DEQH+L+F) in Study 1, subjects in both studies were categorized as early peak responders (peak within 60 minutes), late peak responders (peak > 60 minutes) or nonresponders; 20-25% of participants were categorized as early peak responders, 50-55% as late peak responders and 20-30% as nonresponders. Physiological (both studies) and plasma d-amphetamine (Study 1) were compared among these groups. Early peak responders exhibited an earlier rise in plasma d-amphetamine levels and more sustained elevation in heart rate compared to late peak responders. The present data illustrate the presence of significant individual differences in the temporal pattern of responses to oral d-amphetamine, which may contribute to heightened abuse potential.

Developmental literature suggests that susceptibility to social conformity pressure peaks in adolescence and disappears with maturity into early adulthood. Predictions about these behaviors are less clear for middle-aged and older adults. On the one hand, while age-related increases in prioritization of socioemotional goals might predict greater susceptibility to social conformity pressures, aging is also associated with enhanced emotion regulation that could support resistance to conformity pressures. In this exploratory research study, we used mobile experience sampling surveys to naturalistically track how 157 healthy adults between the ages of 18 and 80 practice self-control over spontaneous desires in daily life. Many of these desires were experienced in the presence of others enacting that desire. Results showed that middle-aged and older adults were better at controlling their desires than younger adults when desires were experienced in the presence of others enacting that desire. Consistent with the literature on improved emotion regulation with age, these results provide evidence that the ability to resist social conformity pressure is enhanced across the adult life span. Public Significance Statement: People regularly experience and resist temptations in daily life. Successful resistance of desires can be especially difficult when others are around enacting those desires. The present study demonstrates that compared to younger adults, middle-aged and older adults are less susceptible to conformity pressures from others enacting a desire when practicing self-control in daily life. [ABSTRACT FROM AUTHOR]