Automating the analysis of facial emotion expression dynamics: A computational framework and application in psychotic disorders.

Facial emotion expressions play a central role in interpersonal interactions; these displays are used to predict and influence the behavior of others. Despite their importance, quantifying and analyzing the dynamics of brief facial emotion expressions remains an understudied methodological challenge. Here, we present a method that leverages machine learning and network modeling to assess the dynamics of facial expressions. Using video recordings of clinical interviews, we demonstrate the utility of this approach in a sample of 96 people diagnosed with psychotic disorders and 116 never-psychotic adults. Participants diagnosed with schizophrenia tended to move from neutral expressions to uncommon expressions (e.g., fear, surprise), whereas participants diagnosed with other psychoses (e.g., mood disorders with psychosis) moved toward expressions of sadness. This method has broad applications to the study of normal and altered expressions of emotion and can be integrated with telemedicine to improve psychiatric assessment and treatment.

Exploring the genetic etiology across the continuum of the general psychopathology factor: a Swedish population-based family and twin study.

Psychiatric comorbidity can be accounted for by a latent general psychopathology factor (p factor), which quantifies the variance that is shared to varying degrees by every dimension of psychopathology. It is unclear whether the entire continuum of the p factor shares the same genetic origin. We investigated whether mild, moderate, and extreme elevations on the p factor shared the same genetic etiology by, first, examining the linearity of the association between p factors across siblings (N = 580,891 pairs). Second, we estimated the group heritability in a twin sample (N = 17,170 pairs), which involves testing whether the same genetic variants influence both extreme and normal variations in the p factor. In both samples, the p factor was based on 10 register-based psychiatric diagnoses. Results showed that the association between siblings' p factors appeared linear, even into the extreme range. Likewise, the twin group heritabilities ranged from 0.42 to 0.45 (95% CI: 0.33-0.57) depending on the thresholds defining the probands (2-3.33 SD beyond the mean; >2 SD beyond the mean; >4.33 SD beyond the mean; and >5.33 SD beyond the mean), and these estimates were highly similar to the estimated individual differences heritability (0.41, 95% CI: 0.39-0.43), indicating that scores above and below these thresholds shared a common genetic origin. Together, these results suggest that the entire continuum of the p factor shares the same genetic origin, with common genetic variants likely playing an important role. This implies, first, genetic risk factors for the aspect that is shared between all forms of psychopathology (i.e., genetic risk factors for the p factor) might be generalizable between population-based cohorts with a higher prevalence of milder cases, and clinical samples with a preponderance of more severe cases. Second, prioritizing low-cost genome-wide association studies capable of identifying common genetic variants, rather than expensive whole genome sequencing that can identify rare variants, may increase the efficiency when studying the genetic architecture of the p factor.

Psychosis superspectrum II: neurobiology, treatment, and implications.

Alternatives to traditional categorical diagnoses have been proposed to improve the validity and utility of psychiatric nosology. This paper continues the companion review of an alternative model, the psychosis superspectrum of the Hierarchical Taxonomy of Psychopathology (HiTOP). The superspectrum model aims to describe psychosis-related psychopathology according to data on distributions and associations among signs and symptoms. The superspectrum includes psychoticism and detachment spectra as well as narrow subdimensions within them. Auxiliary domains of cognitive deficit and functional impairment complete the psychopathology profile. The current paper reviews evidence on this model from neurobiology, treatment response, clinical utility, and measure development. Neurobiology research suggests that psychopathology included in the superspectrum shows similar patterns of neural alterations. Treatment response often mirrors the hierarchy of the superspectrum with some treatments being efficacious for psychoticism, others for detachment, and others for a specific subdimension. Compared to traditional diagnostic systems, the quantitative nosology shows an approximately 2-fold increase in reliability, explanatory power, and prognostic accuracy. Clinicians consistently report that the quantitative nosology has more utility than traditional diagnoses, but studies of patients with frank psychosis are currently lacking. Validated measures are available to implement the superspectrum model in practice. The dimensional conceptualization of psychosis-related psychopathology has implications for research, clinical practice, and public health programs. For example, it encourages use of the cohort study design (rather than case-control), transdiagnostic treatment strategies, and selective prevention based on subclinical symptoms. These approaches are already used in the field, and the superspectrum provides further impetus and guidance for their implementation. Existing knowledge on this model is substantial, but significant gaps remain. We identify outstanding questions and propose testable hypotheses to guide further research. Overall, we predict that the more informative, reliable, and valid characterization of psychopathology offered by the superspectrum model will facilitate progress in research and clinical care.

Psychosis superspectrum I: Nosology, etiology, and lifespan development.

This review describes the Hierarchical Taxonomy of Psychopathology (HiTOP) model of psychosis-related psychopathology, the psychosis superspectrum. The HiTOP psychosis superspectrum was developed to address shortcomings of traditional diagnoses for psychotic disorders and related conditions including low reliability, arbitrary boundaries between psychopathology and normality, high symptom co-occurrence, and heterogeneity within diagnostic categories. The psychosis superspectrum is a transdiagnostic dimensional model comprising two spectra-psychoticism and detachment-which are in turn broken down into fourteen narrow components, and two auxiliary domains-cognition and functional impairment. The structure of the spectra and their components are shown to parallel the genetic structure of psychosis and related traits. Psychoticism and detachment have distinct patterns of association with urbanicity, migrant and ethnic minority status, childhood adversity, and cannabis use. The superspectrum also provides a useful model for describing the emergence and course of psychosis, as components of the superspectrum are relatively stable over time. Changes in psychoticism predict the onset of psychosis-related psychopathology, whereas changes in detachment and cognition define later course. Implications of the superspectrum for genetic, socio-environmental, and longitudinal research are discussed. A companion review focuses on neurobiology, treatment response, and clinical utility of the superspectrum, and future research directions.

Effects of Daily Posttraumatic Stress Disorder Symptoms on Heart Rate Variability.

OBJECTIVE: Posttraumatic stress disorder (PTSD) is common, debilitating, and associated with an increased risk of health problems, including cardiovascular disease. PTSD is related to poor autonomic function indicated by reduced heart rate variability (HRV). However, very little work has tested the timescale or direction of these effects, given that most evidence comes from cross-sectional studies. Documentation of when effects occur and in what direction can shed light on mechanisms of cardiovascular disease risk and inform treatment. The present study of 169 World Trade Center responders, oversampled for PTSD, tested how daily PTSD symptoms were associated with autonomic function as reflected through HRV. METHODS: Participants ( N = 169) completed surveys of PTSD symptoms three times a day at 5-hour intervals for 4 days while also wearing ambulatory monitors to record electrocardiograms to derive HRV (i.e., mean absolute value of successive differences between beat-to-beat intervals). RESULTS: HRV did not predict PTSD symptoms. However, PTSD symptoms during a 5-hour interval predicted reduced HRV at the next 5-hour interval ( ß = -0.09, 95% confidence interval = -0.16 to -0.02, p = .008). Results held adjusting for baseline age, current heart problems, and current PTSD diagnosis. CONCLUSIONS: Findings underscore growing awareness that PTSD symptoms are not static. Even their short-term fluctuations may affect cardiovascular functioning, which could have more severe impacts if disruption accumulates over time. Research is needed to determine if momentary interventions can halt increases in PTSD symptoms or mitigate their impact on cardiovascular health.

Developmental pathway for first onset of depressive disorders in females: from adolescence to emerging adulthood.

BACKGROUND: Although risk markers for depressive disorders (DD) are dynamic, especially during adolescence, few studies have examined how change in risk levels during adolescence predict DD onset during transition to adulthood. We compared two competing hypotheses of the dynamic effects of risk. The risk escalation hypothesis posits that worsening of risk predicts DD onset beyond risk level. The chronic risk hypothesis posits that persistently elevated risk level, rather than risk change, predicts DD onset. METHODS: Our sample included 393 girls (baseline age 13.5-15.5 years) from the adolescent development of emotions and personality traits project. Participants underwent five diagnostic interviews and assessments of risk markers for DD at 9-month intervals and were re-interviewed at a 6-year follow-up. We focused on 17 well-established risk markers. For each risk marker, we examined the prospective effects of risk level and change on first DD onset at wave six, estimated by growth curve modeling using data from the first five waves. RESULTS: For 13 of the 17 depression risk markers, elevated levels of risk during adolescence, but not change in risk, predicted first DD onset during transition to adulthood, supporting the chronic risk hypothesis. Minimal evidence was found for the risk escalation hypothesis. CONCLUSIONS: Participants who had a first DD onset during transition to adulthood have exhibited elevated levels of risk throughout adolescence. Researchers and practitioners should administer multiple assessments and focus on persistently elevated levels of risk to identify individuals who are most likely to develop DD and to provide targeted DD prevention.

Dimensional and transdiagnostic phenotypes in psychiatric genome-wide association studies.

Genome-wide association studies (GWAS) provide biological insights into disease onset and progression and have potential to produce clinically useful biomarkers. A growing body of GWAS focuses on quantitative and transdiagnostic phenotypic targets, such as symptom severity or biological markers, to enhance gene discovery and the translational utility of genetic findings. The current review discusses such phenotypic approaches in GWAS across major psychiatric disorders. We identify themes and recommendations that emerge from the literature to date, including issues of sample size, reliability, convergent validity, sources of phenotypic information, phenotypes based on biological and behavioral markers such as neuroimaging and chronotype, and longitudinal phenotypes. We also discuss insights from multi-trait methods such as genomic structural equation modelling. These provide insight into how hierarchical 'splitting' and 'lumping' approaches can be applied to both diagnostic and dimensional phenotypes to model clinical heterogeneity and comorbidity. Overall, dimensional and transdiagnostic phenotypes have enhanced gene discovery in many psychiatric conditions and promises to yield fruitful GWAS targets in the years to come.

Associations between polygenic risk scores for cardiometabolic phenotypes and adolescent depression and body dissatisfaction.

BACKGROUND: Adolescents with elevated body mass index (BMI) are at an increased risk for depression and body dissatisfaction. Type 2 diabetes (T2D) is an established risk factor for depression. However, shared genetic risk between cardiometabolic conditions and mental health outcomes remains understudied in youth. METHODS: The current study examined associations between polygenic risk scores (PRS) for BMI and T2D, and symptoms of depression and body dissatisfaction, in a sample of 827 community adolescents (Mage = 13.63, SDage = 1.01; 76% girls). BMI, depressive symptoms, and body dissatisfaction were assessed using validated self-report questionnaires. RESULTS: BMI-PRS was associated with phenotypic BMI (ß = 0.24, p < 0.001) and body dissatisfaction (ß = 0.17, p < 0.001), but not with depressive symptoms. The association between BMI-PRS and body dissatisfaction was significantly mediated by BMI (indirect effect = 0.10, CI [0.07-0.13]). T2D-PRS was not associated with depression or body dissatisfaction. CONCLUSIONS: The results suggest phenotypic BMI may largely explain the association between genetic risk for elevated BMI and body dissatisfaction in adolescents. Further research on age-specific genetic effects is needed, as summary statistics from adult discovery samples may have limited utility in youth. IMPACT: The association between genetic risk for elevated BMI and body dissatisfaction in adolescents may be largely explained by phenotypic BMI, indicating a potential pathway through which genetic predisposition influences body image perception. Furthermore, age-specific genetic research is needed to understand the unique influences on health outcomes during adolescence. By identifying BMI as a potential mediator in the association between genetic risk for elevated BMI and body dissatisfaction, the current findings offer insights that could inform interventions targeting body image concerns and mental health in this population.

Mismatch negativity and clinical trajectories in psychotic disorders: Five-year stability and predictive utility.

BACKGROUND: Mismatch negativity (MMN) amplitude is reduced in psychotic disorders and associated with symptoms and functioning. Due to these robust associations, it is often considered a biomarker for psychotic illness. The relationship between MMN and clinical outcomes has been examined well in early onset psychotic illness; however, its stability and predictive utility in chronic samples are not clear. METHOD: We examined the five-year stability of MMN amplitude over two timepoints in individuals with established psychotic disorders (cases; N = 132) and never-psychotic participants (NP; N = 170), as well as longitudinal associations with clinical symptoms and functioning. RESULTS: MMN amplitude exhibited good temporal stability (cases, r = 0.53; never-psychotic, r = 0.52). In cases, structural equation models revealed MMN amplitude to be a significant predictor of worsening auditory hallucinations (ß = 0.19), everyday functioning (ß = -0.13), and illness severity (ß = -0.12) at follow-up. Meanwhile, initial IQ (ß = -0.24), negative symptoms (ß = 0.23), and illness severity (ß = -0.16) were significant predictors of worsening MMN amplitude five years later. CONCLUSIONS: These results imply that MMN measures a neural deficit that is reasonably stable up to five years. Results support disordered cognition and negative symptoms as preceding reduced MMN, which then may operate as a mechanism driving reductions in everyday functioning and the worsening of auditory hallucinations in chronic psychotic disorders. This pattern may inform models of illness course, clarifying the relationships amongst biological mechanisms of predictive processing and clinical deficits in chronic psychosis and allowing us to better understand the mechanisms driving such impairments over time.

Dynamic risk for first onset of depressive disorders in adolescence: does change matter?

BACKGROUND: Risk factors for depressive disorders (DD) change substantially over time, but the prognostic value of these changes remains unclear. Two basic types of dynamic effects are possible. The 'Risk Escalation hypothesis' posits that worsening of risk levels predicts DD onset above average level of risk factors. Alternatively, the 'Chronic Risk hypothesis' posits that the average level rather than change predicts first-onset DD. METHODS: We utilized data from the ADEPT project, a cohort of 496 girls (baseline age 13.5-15.5 years) from the community followed for 3 years. Participants underwent five waves of assessments for risk factors and diagnostic interviews for DD. For illustration purposes, we selected 16 well-established dynamic risk factors for adolescent depression, such as depressive and anxiety symptoms, personality traits, clinical traits, and social risk factors. We conducted Cox regression analyses with time-varying covariates to predict first DD onset. RESULTS: Consistently elevated risk factors (i.e. the mean of multiple waves), but not recent escalation, predicted first-onset DD, consistent with the Chronic Risk hypothesis. This hypothesis was supported across all 16 risk factors. CONCLUSIONS: Across a range of risk factors, girls who had first-onset DD generally did not experience a sharp increase in risk level shortly before the onset of disorder; rather, for years before onset, they exhibited elevated levels of risk. Our findings suggest that chronicity of risk should be a particular focus in screening high-risk populations to prevent the onset of DDs. In particular, regular monitoring of risk factors in school settings is highly informative.

World Trade Center responders in their own words: predicting PTSD symptom trajectories with AI-based language analyses of interviews.

BACKGROUND: Oral histories from 9/11 responders to the World Trade Center (WTC) attacks provide rich narratives about distress and resilience. Artificial Intelligence (AI) models promise to detect psychopathology in natural language, but they have been evaluated primarily in non-clinical settings using social media. This study sought to test the ability of AI-based language assessments to predict PTSD symptom trajectories among responders. METHODS: Participants were 124 responders whose health was monitored at the Stony Brook WTC Health and Wellness Program who completed oral history interviews about their initial WTC experiences. PTSD symptom severity was measured longitudinally using the PTSD Checklist (PCL) for up to 7 years post-interview. AI-based indicators were computed for depression, anxiety, neuroticism, and extraversion along with dictionary-based measures of linguistic and interpersonal style. Linear regression and multilevel models estimated associations of AI indicators with concurrent and subsequent PTSD symptom severity (significance adjusted by false discovery rate). RESULTS: Cross-sectionally, greater depressive language (ß = 0.32; p = 0.049) and first-person singular usage (ß = 0.31; p = 0.049) were associated with increased symptom severity. Longitudinally, anxious language predicted future worsening in PCL scores (ß = 0.30; p = 0.049), whereas first-person plural usage (ß = -0.36; p = 0.014) and longer words usage (ß = -0.35; p = 0.014) predicted improvement. CONCLUSIONS: This is the first study to demonstrate the value of AI in understanding PTSD in a vulnerable population. Future studies should extend this application to other trauma exposures and to other demographic groups, especially under-represented minorities.

General v. specific vulnerabilities: polygenic risk scores and higher-order psychopathology dimensions in the Adolescent Brain Cognitive Development (ABCD) Study.

BACKGROUND: Polygenic risk scores (PRSs) capture genetic vulnerability to psychiatric conditions. However, PRSs are often associated with multiple mental health problems in children, complicating their use in research and clinical practice. The current study is the first to systematically test which PRSs associate broadly with all forms of childhood psychopathology, and which PRSs are more specific to one or a handful of forms of psychopathology. METHODS: The sample consisted of 4717 unrelated children (mean age = 9.92, s.d. = 0.62; 47.1% female; all European ancestry). Psychopathology was conceptualized hierarchically as empirically derived general factor (p-factor) and five specific factors: externalizing, internalizing, neurodevelopmental, somatoform, and detachment. Partial correlations explored associations between psychopathology factors and 22 psychopathology-related PRSs. Regressions tested which level of the psychopathology hierarchy was most strongly associated with each PRS. RESULTS: Thirteen PRSs were significantly associated with the general factor, most prominently Chronic Multisite Pain-PRS (r = 0.098), ADHD-PRS (r = 0.079), and Depression-PRS (r = 0.078). After adjusting for the general factor, Depression-PRS, Neuroticism-PRS, PTSD-PRS, Insomnia-PRS, Chronic Back Pain-PRS, and Autism-PRS were not associated with lower order factors. Conversely, several externalizing PRSs, including Adventurousness-PRS and Disinhibition-PRS, remained associated with the externalizing factor (|r| = 0.040-0.058). The ADHD-PRS remained uniquely associated with the neurodevelopmental factor (r = 062). CONCLUSIONS: PRSs developed to predict vulnerability to emotional difficulties and chronic pain generally captured genetic risk for all forms of childhood psychopathology. PRSs developed to predict vulnerability to externalizing difficulties, e.g. disinhibition, tended to be more specific in predicting behavioral problems. The results may inform translation of existing PRSs to pediatric research and future clinical practice.

Do general and specific factors of preschool psychopathology predict preadolescent outcomes? A transdiagnostic hierarchical approach.

BACKGROUND: Preschool psychiatric symptoms significantly increase the risk for long-term negative outcomes. Transdiagnostic hierarchical approaches that capture general ('p') and specific psychopathology dimensions are promising for understanding risk and predicting outcomes, but their predictive utility in young children is not well established. We delineated a hierarchical structure of preschool psychopathology dimensions and tested their ability to predict psychiatric disorders and functional impairment in preadolescence. METHODS: Data for 1253 preschool children (mean age = 4.17, s.d. = 0.81) were drawn from three longitudinal studies using a similar methodology (one community sample, two psychopathology-enriched samples) and followed up into preadolescence, yielding a large and diverse sample. Exploratory factor models derived a hierarchical structure of general and specific factors using symptoms from the Preschool Age Psychiatric Assessment interview. Longitudinal analyses examined the prospective associations of preschool p and specific factors with preadolescent psychiatric disorders and functional impairment. RESULTS: A hierarchical dimensional structure with a p factor at the top and up to six specific factors (distress, fear, separation anxiety, social anxiety, inattention-hyperactivity, oppositionality) emerged at preschool age. The p factor predicted all preadolescent disorders (ΔR2 = 0.04-0.15) and functional impairment (ΔR2 = 0.01-0.07) to a significantly greater extent than preschool psychiatric diagnoses and functioning. Specific dimensions provided additional predictive power for the majority of preadolescent outcomes (disorders: ΔR2 = 0.06-0.15; functional impairment: ΔR2 = 0.05-0.12). CONCLUSIONS: Both general and specific dimensions of preschool psychopathology are useful for predicting clinical and functional outcomes almost a decade later. These findings highlight the value of transdiagnostic dimensions for predicting prognosis and as potential targets for early intervention and prevention.

Daily Sleep-Stress Reactivity and Functional Impairment in World Trade Center Responders.

BACKGROUND: How sleep is impacted by stress ("sleep reactivity to stress") and how stress is impacted by sleep ("stress reactivity to sleep") are trait-like characteristics of individuals that predict depression, anxiety, and insomnia. However, pathways between reactivity and functional impairment (e.g., impairment in social relationships and interpersonal functioning) have not been explored, which may be a critical pathway in understanding the link between reactivity and the development of psychological disorders. PURPOSE: We examined associations between reactivity and changes in functional impairment among a cohort of 9/11 World Trade Center responders. METHODS: Data from 452 responders (Mage = 55.22 years; 89.4% male) were collected between 2014 and 2016. Four baseline sleep and stress reactivity indices (i.e., sleep duration and efficiency reactivity to stress; stress reactivity to sleep duration and efficiency) were calculated from 14 days of sleep and stress data using random slopes from multilevel models. Functional impairment was assessed approximately 1 year and 2 years after baseline via semi-structured interviews. Latent change score analyses examined associations between baseline reactivity indices and changes in functional impairment. RESULTS: Greater baseline sleep efficiency reactivity to stress was associated with decreases in functioning (ß = -0.05, p = .039). In addition, greater stress reactivity to sleep duration (ß = -0.08, p = .017) and sleep efficiency (ß = -0.22, p < .001) was associated with lower functioning at timepoint one. CONCLUSION: People who are more reactive to daily fluctuations in stress and sleep have poorer interpersonal relationships and social functioning. Identifying individuals with high reactivity who could benefit from preventative treatment may foster better social integration.

How sleep is impacted by stress ("sleep reactivity to stress") and how stress is impacted by sleep ("stress reactivity to sleep") are trait-like characteristics of individuals that may contribute to an individual's risk of developing of psychological disorders, such as depression, anxiety, and insomnia. It is possible that individuals with high sleep-stress reactivity are more likely to experience long-term functional impairment (e.g., impairment in social relationships and interpersonal functioning)­a predisposing factor for psychological disorders, yet this pathway has not been explored. Therefore, we examined associations between sleep-stress reactivity and changes in functional impairment across a 1-year period in a large sample of 9/11 World Trade Center responders. The study results suggest that 9/11 World Trade Center responders who are more reactive to daily fluctuations in stress and sleep have poorer interpersonal relationships and social functioning. Identifying individuals with high sleep-stress reactivity who could benefit from preventative treatment may foster better social integration.

Three-variable systems: An integrative moderation and mediation framework for developmental psychopathology.

In this article, we consider an often overlooked model that combines mediation and moderation to explain how a third variable can relate to a risk factor-psychopathology relationship. We refer to it as moderation and mediation in a three-variable system. We describe how this model is relevant to studying vulnerability factors and how it may advance developmental psychopathology research. To illustrate the value of this approach, we provide several examples where this model may be applicable, such as the relationships among parental externalizing pathology, harsh parenting, and offspring psychopathology as well as between neuroticism, stressful life events, and depression. We discuss possible reasons why this model has not gained traction and attempt to clarify and dispel those concerns. We provide guidance and recommendations for when to consider this model for a given data set and point toward existing resources for testing this model that have been developed by statisticians and other methodologists. Lastly, we describe important caveats, limitations, and considerations for making this approach most useful for developmental research. Overall, our goal in presenting this information to developmental psychopathology researchers is to encourage testing moderation and mediation in a three-variable system with the aim of advancing analytic strategies for studying vulnerability factors.

Dynamic interplay between life events and course of psychotic disorders: 10-year longitudinal study following first admission.

BACKGROUND: Life events (LEs) are a risk factor for first onset and relapse of psychotic disorders. However, the impact of LEs on specific symptoms - namely reality distortion, disorganization, negative symptoms, depression, and mania - remains unclear. Moreover, the differential effects of negative v. positive LEs are poorly understood. METHODS: The present study utilizes an epidemiologic cohort of patients (N = 428) ascertained at first-admission for psychosis and followed for a decade thereafter. Symptoms were assessed at 6-, 24-, 48-, and 120-month follow-ups. RESULTS: We examined symptom change within-person and found that negative events in the previous 6 months predicted an increase in reality distortion (ß = 0.07), disorganized (ß = 0.07), manic (ß = 0.08), and depressive symptoms (ß = 0.06), and a decrease in negative symptoms (ß = -0.08). Conversely, positive LEs predicted fewer reality distortion (ß = -0.04), disorganized (ß = -0.04), and negative (ß = -0.13) symptoms, and were unrelated to mood symptoms. A between-person approach to the same hypotheses confirmed that negative LEs predicted change in all symptoms, while positive LEs predicted change only in negative symptoms. In contrast, symptoms rarely predicted future LEs. CONCLUSIONS: These findings confirm that LEs have an effect on symptoms, and thus contribute to the burden of psychotic disorders. That LEs increase positive symptoms and decrease negative symptoms suggest at least two different mechanisms underlying the relationship between LEs and symptoms. Our findings underscore the need for increased symptom monitoring following negative LEs, as symptoms may worsen during that time.

The Hierarchical Taxonomy of Psychopathology (HiTOP) in psychiatric practice and research.

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.

Polygenic association of glomerular filtration rate decline in world trade center responders.

BACKGROUND: The factors associated with estimated glomerular filtrate rate (eGFR) decline in low risk adults remain relatively unknown. We hypothesized that a polygenic risk score (PRS) will be associated with eGFR decline. METHODS: We analyzed genetic data from 1,601 adult participants with European ancestry in the World Trade Center Health Program (baseline age 49.68 ± 8.79 years, 93% male, 23% hypertensive, 7% diabetic and 1% with cardiovascular disease) with ≥ three serial measures of serum creatinine. PRSs were calculated from an aggregation of single nucleotide polymorphisms (SNPs) from a recent, large-scale genome-wide association study (GWAS) of rapid eGFR decline. Generalized linear models were used to evaluate the association of PRS with renal outcomes: baseline eGFR and CKD stage, rate of change in eGFR, stable versus declining eGFR over a 3-5-year observation period. eGFR decline was defined in separate analyses as "clinical" (> -1.0 ml/min/1.73 m2/year) or "empirical" (lower most quartile of eGFR slopes). RESULTS: The mean baseline eGFR was ~ 86 ml/min/1.73 m2. Subjects with decline in eGFR were more likely to be diabetic. PRS was significantly associated with lower baseline eGFR (B = -0.96, p = 0.002), higher CKD stage (OR = 1.17, p = 0.010), decline in eGFR (OR = 1.14, p = 0.036) relative to stable eGFR, and the lower quartile of eGFR slopes (OR = 1.21, p = 0.008), after adjusting for established risk factors for CKD. CONCLUSION: Common genetic variants are associated with eGFR decline in middle-aged adults with relatively low comorbidity burdens.

Anxiety sensitivity and Pain Experience: a prospective investigation among World Trade Center Responders.

Chronic pain is a significant public health problem and is exacerbated by stress. The World Trade Center (WTC) Disaster represents a unique stressor, and responders to the WTC disaster are at increased risk for pain and other health complaints. Therefore, there is a significant need to identify vulnerability factors for exacerbated pain experience among this high-risk population. Anxiety sensitivity (AS), defined as fear of anxiety-related sensations, is one such vulnerability factor associated with pain intensity and disability. Yet, no work has tested the predictive effects of AS on pain, limiting conclusions regarding the predictive utility and direction of associations. Therefore, the current study examined the prospective associations of AS, pain intensity, and pain interference among 452 (Mage = 55.22, SD = 8.73, 89.4% male) responders to the WTC disaster completing a 2-week daily diary study. Using multi-level modeling, AS total score was positively associated with both pain intensity and pain interference, and that AS cognitive concerns, but not social or physical concerns, were associated with increased pain. These results highlight the importance of AS as a predictor of pain complaints among WTC responders and provide initial empirical evidence to support AS as a clinical target for treating pain complaints among WTC responders.

The distinction between symptoms and traits in the Hierarchical Taxonomy of Psychopathology (HiTOP).

The Hierarchical Taxonomy of Psychopathology (HiTOP) is an empirically and quantitatively derived dimensional classification system designed to describe the features of psychopathology and, ultimately, to replace categorical nosologies. Among the constructs that HiTOP organizes are "symptom components" and "maladaptive traits," but past HiTOP publications have not fully explicated the distinction between symptoms and traits. We propose working definitions of symptoms and traits and explore challenges, exceptions, and remaining questions. Specifically, we propose that the only systematic difference between symptoms and traits in HiTOP is one of time frame. Maladaptive traits are dispositional constructs that describe persistent tendencies to manifest features of psychopathology, whereas symptoms are features of psychopathology as they are manifest during any specific time period (from moments to days to months). This has the consequence that almost every HiTOP dimension, at any level of the hierarchy, can be assessed as either a trait or a symptom dimension, by adjusting the framing of the assessment. We discuss the implications of these definitions for causal models of the relations between symptoms and traits and for distinctions between psychopathology, normal personality variation, and dysfunction.