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The Hierarchical Taxonomy of Psychopathology (HiTOP) has emerged out of the quantitative approach to psychiatric nosology. This approach identifies psychopathology constructs based on patterns of co-variation among signs and symptoms. The initial HiTOP model, which was published in 2017, is based on a large literature that spans decades of research. HiTOP is a living model that undergoes revision as new data become available. Here we discuss advantages and practical considerations of using this system in psychiatric practice and research. We especially highlight limitations of HiTOP and ongoing efforts to address them. We describe differences and similarities between HiTOP and existing diagnostic systems. Next, we review the types of evidence that informed development of HiTOP, including populations in which it has been studied and data on its validity. The paper also describes how HiTOP can facilitate research on genetic and environmental causes of psychopathology as well as the search for neurobiologic mechanisms and novel treatments. Furthermore, we consider implications for public health programs and prevention of mental disorders. We also review data on clinical utility and illustrate clinical application of HiTOP. Importantly, the model is based on measures and practices that are already used widely in clinical settings. HiTOP offers a way to organize and formalize these techniques. This model already can contribute to progress in psychiatry and complement traditional nosologies. Moreover, HiTOP seeks to facilitate research on linkages between phenotypes and biological processes, which may enable construction of a system that encompasses both biomarkers and precise clinical description.

BackgroundSuicide rates are high in borderline personality disorder (BPD) where interpersonal problems trigger intense affective dysregulation and impulses to act on suicidal thoughts. To date, however, no study has examined how interpersonal stressors contribute to momentary within-person links among affect and impulsivity with suicidal ideation (SI), and how those links vary over time in people's daily lives.MethodsA total of 153 individuals diagnosed with BPD and 52 healthy controls completed a 21-day ecological momentary assessment protocol. Of these 153 individuals with BPD, 105 had a history of suicide attempts. Multilevel structural equation modeling was used to examine dynamic links among interpersonal perceptions, affect, state impulsivity, and suicidal intent.ResultsAggregated across interactions, lower perceived warmth in others was associated with SI. This direct relationship, however, did not extend to momentary within-person associations. Instead, interpersonal conflicts were linked to SI indirectly via greater negative affect and lower positive affect. While a robust within-person link between interpersonal perceptions and impulsivity emerged, impulsivity did not account for the relationship between interpersonal perceptions and SI.ConclusionThis intensive longitudinal study illustrates momentary interpersonal signatures of an emerging suicidal crisis. Among people with BPD at high risk for suicide, interpersonal triggers initiate a cascade of affective dysregulation, which in turn gives rise to SI.

BackgroundAn ongoing challenge in understanding and treating personality disorders (PDs) is a significant heterogeneity in disorder expression, stemming from variability in underlying dynamic processes. These processes are commonly discussed in clinical settings, but are rarely empirically studied due to their personalized, temporal nature. The goal of the current study was to combine intensive longitudinal data collection with person-specific temporal network models to produce individualized symptom-level structures of personality pathology. These structures were then linked to traditional PD diagnoses and stress (to index daily functioning).MethodsUsing about 100 daily assessments of internalizing and externalizing domains underlying PDs (i.e. negative affect, detachment, impulsivity, hostility), a temporal network mapping approach (i.e. group iterative multiple model estimation) was used to create person-specific networks of the temporal relations among domains for 91 individuals (62.6% female) with a PD. Network characteristics were then associated with traditional PD symptomatology (controlling for mean domain levels) and with daily variation in clinically-relevant phenomena (i.e. stress).ResultsFeatures of the person-specific networks predicted paranoid, borderline, narcissistic, and obsessive-PD symptom counts above average levels of the domains, in ways that align with clinical conceptualizations. They also predicted between-person variation in stress across days.ConclusionsRelations among behavioral domains thought to underlie heterogeneity in PDs were indeed associated with traditional diagnostic constructs and with daily functioning (i.e. stress) in person-specific networks. Findings highlight the importance of leveraging data and models that capture person-specific, dynamic processes, and suggest that person-specific networks may have implications for precision medicine.

Psychiatric comorbidity is extensive in the general population (Kessler et al., 1994 Kessler et al., 2005), and in clinical samples poly-diagnosis is the rule rather than the exception (Zimmerman & Mattia, 1999). This complicates clinical communication, treatment selection, and frustrates efforts to uncover the pathophysiology, etiology, and maintenance mechanisms of mental illness (Hyman, 2010). One promising approach for resolving these issues involves using formal statistical modeling to clarify the natural structure of mental disorders (Krueger & Markon, 2006; Wright & Zimmermann, 2015). This approach has been profitably applied to both child(Achenbach, 1966; Lahey et al., 2008) and adult (Kotov et al., 2011; Krueger, 1999; Markon & Krueger, 2006) disorders. In adult psychopathology, a well-replicated structure has emerged based on the clustering of disorders and their symptoms into internalizing (e.g., unipolar mood disorders, anxiety disorders), externalizing (e.g., substance use, antisocial behavior), and thought disorder/psychosis (e.g., psychotic disorders, schizotypal personality disorder) spectra (Kotov et al., 2010; Markon, 2010; Wolf et al., 1988; Wright et al., 2013). This structure has demonstrated strong empirical and statistical evidence for its validity; importantly the resulting spectra or domains appear to predict treatment response and match genetic models of these disorders (Kendler et al., 2003; Kendler et al., 2011). Recently developed quantitative models of psychopathology have expanded the basic internalizing, externalizing, and thought disorder/psychosis structure by incorporating additional diagnoses, most notably personality disorders (PDs), and have begun to uncover additional spectra. To date only four published studies have explored the structure of psychopathology using a broad suite of clinical syndromes and personality disorders (Blanco et al., 2013; Kotov et al., 2011; Markon, 2010; Roysamb et al., 2011).1 Although each resultant model is necessarily unique given differences in the precise admixture of disorders (e.g., some do not include indicators of psychosis), sampling strategy (e.g., clinical vs. epidemiological), and other features (e.g., disorder-level vs. symptom-level analyses), two additional domains appear reasonably replicable across studies. First, Markon (2010) and Roysamb and colleagues (2011) each identified a new spectrum they respectively termed pathological or anhedonic introversion. In both cases, avoidant and dependent PDs were strong markers of the factor, although Roysamb et al. also found that schizoid and depressive PDs loaded strongly on the factor, which accounts for the slight difference in conceptualization. Blanco and colleagues (2013) also found evidence for a factor with the strongest loadings from avoidant and dependent PDs and social phobia. Second, in three studies (Blanco et al., 2013; Kotov et al., 2011; Roysamb et al., 2011), a domain related to antagonism, as labeled by Kotov and colleagues, has emerged. Again, slight differences emerge in the makeup of this domain across studies, although narcissistic and histrionic PDs consistently exhibit the strongest loadings. Additional markers for this domain, but varying slightly across studies, include obsessive-compulsive, borderline, paranoid, and (to a lesser extent) antisocial PDs. What these disorders share to varying degrees is an antagonistic interpersonal style that puts afflicted individuals at odds with others. Notably, introversion and antagonism, which emerge with the addition of PDs, each deal with maladaptive social/interpersonal functioning, consistent with the view that the PDs reflect the interpersonal disorders (Benjamin, 1996; Hill, Pilkonis, Bear, 2011; Hopwood et al., 2013; Meyer & Pilkonis, 2005; Pincus, 2005). Therefore, based on this initial accumulation of studies that have included PDs in structural models of psychopathology and a strong theoretical rationale, the domains of introversion and antagonism appear to be good candidates to include alongside internalizing, externalizing, and thought disorder/psychosis as broad, replicable domains of psychopathology. Taken together, these domains bear a remarkable conceptual resemblance to the pathological personality trait domains included in DSM-5 Section III system of PDs (American Psychiatric Association, 2013). The five domains outlined in this system include Negative Affectivity, Antagonism, Detachment, Disinhibition, and Psychoticism, and were empirically derived from quantitative modeling of more specific PD features (i.e., clinical specifiers) outlined by the DSM-5 Personality and PD workgroup (Krueger et al., 2011; 2012). Compared to this PD trait framework, the psychopathology spectra of internalizing, antagonism, anhedonic/pathological introversion, externalizing, and thought disorder, respectively, reflect strong conceptual matches. However, although intuitively compelling, these putative matches between psychopathology spectra and personality domains have not been empirically demonstrated. Notably, an empirical demonstration that the major spectra underlying psychiatric comorbidity in common clinical syndromes and PDs align with the domains of pathological personality trait models would represent a major advance in clarifying the phenotypic structure of psychopathology. A model such as this would provide the foundation for a comprehensive bridge between mental disorders and elementary domains of individual differences in basic functioning. For example, the DSM-5 pathological trait model has been linked empirically to a large scientific literature on structural models of normal personality and temperament (De Fruyt et al., 2013; Gore & Widiger, 2013; Thomas et al., 2013; Watson et al., 2013; Wright et al., 2012; Wright & Simms, 2014), which builds on a larger literature linking pathological and basic personality traits (e.g., Markon et al., 2005). Adding to the strength of our proposal, that the structures underlying traits and much of psychopathology align, basic trait domains demonstrate strong associations to clinical syndromes (Kotov et al., 2010) and PDs (Samuel & Widiger, 2008; Saulsman & Page, 2004) in meta-analyses. Based on these accumulated findings, some have suggested that there is potential to organize both basic domains of individual differences and psychopathology using a finite number of functional domains or spectra rooted in basic psychological and physiological systems (e.g., Harkness, Reynolds, & Lilienfeld, 2013; Siever & Davis, 1991). This parallels efforts in the broader DSM-5 development process aimed at developing crosscutting dimensions of pathology (Narrow et al., 2012) and in the National Institute of Mental Health's Research Domain Criteria (RDoC; Insel et al., 2010; Sanislow et al., 2010). Further, an empirically based dimensional structure increases the potential to link with biological correlates, genetic liabilities, and leads to more replicable and accurate etiological research (Orfat & Krueger, 2012; Plomin et al., 2009) The potential for an organizing metastructure that encompasses basic and pathological functioning would go a long way towards linking disparate scientific literatures and in so doing provide an organizing scheme for refining the study of psychopathology. In the current study, we tested whether such a model was viable by examining the joint structure of mental disorders and the DSM-5 pathological personality traits. We hypothesized that a factor analysis of interview-diagnosed major clinical syndromes and PDs and patient-reported pathological trait scales in a large general psychiatric outpatient sample would result in five easily interpretable dimensions that closely resemble the aforementioned internalizing, externalizing/disinhibition, thought disorder/psychoticism, antagonism, and introversion/detachment domains. Specifically, we use exploratory structural equation modeling (ESEM; Asparouhov & Muthen, 2009; see also Marsh et al. 2010 for an applied example) to examine the joint structure of DSM-5 pathological personality traits, clinical syndromes, and personality disorders, while accounting for method variance across instruments. We hypothesize that disorders that mark the internalizing spectrum (e.g., mood, anxiety disorders) will load on the same factor as traits that indicate Negative Affectivity (e.g., Emotional Lability, Separation Insecurity), and that markers of Externalizing (e.g., alcohol use, antisocial PD) and Disinhibition (e.g., Risk Taking, Implusivity), antagonism (e.g., narcissistic PD and histrionic PD) and trait Antagonism (e.g., callousness, manipulativeness), pathological introversion (e.g., avoidant PD, schizoid PD) and Detachment (e.g., Withdrawal, Restricted Affectivity), and Thought Disorder (e.g., psychotic symptoms, schizotypal PD) and Psychoticism (e.g., Unusual Beliefs, Perceptual Dysregulation) will load together on the same factors, respectively.