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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).

ObjectiveDiagnosis is a cornerstone of clinical practice for mental health care providers, yet traditional diagnostic systems have well-known shortcomings, including inadequate reliability, high comorbidity, and marked within-diagnosis heterogeneity. The Hierarchical Taxonomy of Psychopathology (HiTOP) is a data-driven, hierarchically based alternative to traditional classifications that conceptualizes psychopathology as a set of dimensions organized into increasingly broad, transdiagnostic spectra. Prior work has shown that using a dimensional approach improves reliability and validity, but translating a model like HiTOP into a workable system that is useful for health care providers remains a major challenge.MethodThe present work outlines the HiTOP model and describes the core principles to guide its integration into clinical practice.ResultsPotential advantages and limitations of the HiTOP model for clinical utility are reviewed, including with respect to case conceptualization and treatment planning. A HiTOP approach to practice is illustrated and contrasted with an approach based on traditional nosology. Common barriers to using HiTOP in real-world health care settings and solutions to these barriers are discussed.ConclusionsHiTOP represents a viable alternative to classifying mental illness that can be integrated into practice today, although research is needed to further establish its utility. (PsycINFO Database Record (c) 2019 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.

Depression, conduct, and hyperactivity symptoms are chronic and frequently co-occur in adolescence. Common genetic and environmental vulnerability to these conditions have previously been demonstrated, however, the manner in which common versus disorder-specific etiological influences operate across development and maintain symptom co-occurrence is unclear. Thus, the current study investigated the role of common genetic and environmental influences in the comorbidity of depression, conduct, and hyperactivity across adolescence. Over 10,000 twins and their parents reported adolescents' symptoms at mean ages 11 and 16 years. Biometric independent pathway models were fitted to estimate genetic and environmental contributions to the continuity of symptom co-occurrence over time, as well as time‐ and symptom‐specific influences. Results found that a common stable genetic factor accounted for the concurrent and longitudinal co-occurrence of depression, conduct, and hyperactivity symptoms. New genetic influences common to these three symptom scales emerged at 16 years, and further contributed to symptom co-occurrence. Conversely, environmental influences largely contributed to the time-specific associations. The findings were generally consistent for self- and parent-reported symptoms. Overall, the results suggest that stable, overlapping genetic influences contribute to the co-occurrence of depression, conduct, and hyperactivity symptoms across adolescence. The results are in line with hierarchical causal models of psychopathology, which posit that much of the developmental co-occurrence between different symptoms is due to common liability. Specifically, current findings indicate that only genetic influences constitute common liability over time. Future studies should identify genetically influenced transdiagnostic risk and maintenance factors to inform prevention and treatment of comorbid internalizing and externalizing symptoms in adolescence. [ABSTRACT FROM AUTHOR]

Background: Personality is a major predictor of many mental and physical disorders, but its contributions to illness course are understudied.Purpose: The current study aimed to explore whether personality is associated with a course of psychiatric and medical illness over 10 years following trauma.Methods: World Trade Center (WTC) responders (N = 532) completed the personality inventory for DSM-5, which measures both broad domains and narrow facets. Responders' mental and physical health was assessed in the decade following the WTC disaster during annual monitoring visits at a WTC Health Program clinic. Multilevel modeling was used in an exploratory manner to chart the course of health and functioning, and examine associations of maladaptive personality domains and facets with intercepts (initial illness) and slopes (course) of illness trajectories.Results: Three maladaptive personality domains-negative affectivity, detachment and psychoticism-were uniquely associated with initial posttraumatic stress disorder (PTSD); detachment and psychoticism were also associated with initial functional impairment. Five facets-emotional lability, anhedonia, callousness, distractibility and perceptual dysregulation-were uniquely associated with initial mental and physical health and functional impairment. Anxiousness and depressivity facets were associated with worse initial levels of psychiatric outcomes only. With regard to illness trajectory, callousness and perceptual dysregulation were associated with the increase in PTSD symptoms. Anxiousness was associated with greater persistence of respiratory symptoms.Conclusions: Several personality domains and facets were associated with initial levels and long-term course of illness and functional impairment in a traumatized population. Results inform the role of maladaptive personality in the development and maintenance of chronic mental-physical comorbidity. Personality might constitute a transdiagnostic prognostic and treatment target. [ABSTRACT FROM AUTHOR]