Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): III. Emotional dysfunction superspectrum

The Hierarchical Taxonomy of Psychopathology (HiTOP) is a quantitative nosological system that addresses shortcomings of traditional mental disorder diagnoses, including arbitrary boundaries between psychopathology and normality, frequent disorder co‐occurrence, substantial heterogeneity within disorders, and diagnostic unreliability over time and across clinicians. This paper reviews evidence on the validity and utility of the internalizing and somatoform spectra of HiTOP, which together provide support for an emotional dysfunction superspectrum. These spectra are composed of homogeneous symptom and maladaptive trait dimensions currently subsumed within multiple diagnostic classes, including depressive, anxiety, trauma‐related, eating, bipolar, and somatic symptom disorders, as well as sexual dysfunction and aspects of personality disorders. Dimensions falling within the emotional dysfunction superspectrum are broadly linked to individual differences in negative affect/neuroticism. Extensive evidence establishes that dimensions falling within the superspectrum share genetic diatheses, environmental risk factors, cognitive and affective difficulties, neural substrates and biomarkers, childhood temperamental antecedents, and treatment response. The structure of these validators mirrors the quantitative structure of the superspectrum, with some correlates more specific to internalizing or somatoform conditions, and others common to both, thereby underlining the hierarchical structure of the domain. Compared to traditional diagnoses, the internalizing and somatoform spectra demonstrated substantially improved utility: greater reliability, larger explanatory and predictive power, and greater clinical applicability. Validated measures are currently available to implement the HiTOP system in practice, which can make diagnostic classification more useful, both in research and in the clinic.     

Testing structural models of psychopathology at the genomic level

Genome‐wide association studies (GWAS) have revealed hundreds of genetic loci associated with the vulnerability to major psychiatric disorders, and post‐GWAS analyses have shown substantial genetic correlations among these disorders. This evidence supports the existence of a higher‐order structure of psychopathology at both the genetic and phenotypic levels. Despite recent efforts by collaborative consortia such as the Hierarchical Taxonomy of Psychopathology (HiTOP), this structure remains unclear. In this study, we tested multiple alternative structural models of psychopathology at the genomic level, using the genetic correlations among fourteen psychiatric disorders and related psychological traits estimated from GWAS summary statistics. The best‐fitting model included four correlated higher‐order factors – externalizing, internalizing, thought problems, and neurodevelopmental disorders – which showed distinct patterns of genetic correlations with external validity variables and accounted for substantial genetic variance in their constituent disorders. A bifactor model including a general factor of psychopathology as well as the four specific factors fit worse than the above model. Several model modifications were tested to explore the placement of some disorders – such as bipolar disorder, obsessive‐compulsive disorder, and eating disorders – within the broader psychopathology structure. The best‐fitting model indicated that eating disorders and obsessive‐compulsive disorder, on the one hand, and bipolar disorder and schizophrenia, on the other, load together on the same thought problems factor. These findings provide support for several of the HiTOP higher‐order dimensions and suggest a similar structure of psychopathology at the genomic and phenotypic levels.     

Transdiagnostic dimensions of psychosis in the Bipolar‐Schizophrenia Network on Intermediate Phenotypes (B‐SNIP)

The validity of the classification of non‐affective and affective psychoses as distinct entities has been disputed, but, despite calls for alternative approaches to defining psychosis syndromes, there is a dearth of empirical efforts to identify transdiagnostic phenotypes of psychosis. We aimed to investigate the validity and utility of general and specific symptom dimensions of psychosis cutting across schizophrenia, schizoaffective disorder and bipolar I disorder with psychosis. Multidimensional item‐response modeling was conducted on symptom ratings of the Positive and Negative Syndrome Scale, Young Mania Rating Scale, and Montgomery‐Åsberg Depression Rating Scale in the multicentre Bipolar‐Schizophrenia Network on Intermediate Phenotypes (B‐SNIP) consortium, which included 933 patients with a diagnosis of schizophrenia (N=397), schizoaffective disorder (N=224), or bipolar I disorder with psychosis (N=312). A bifactor model with one general symptom dimension, two distinct dimensions of non‐affective and affective psychosis, and five specific symptom dimensions of positive, negative, disorganized, manic and depressive symptoms provided the best model fit. There was further evidence on the utility of symptom dimensions for predicting B‐SNIP psychosis biotypes with greater accuracy than categorical DSM diagnoses. General, positive, negative and disorganized symptom dimension scores were higher in African American vs. Caucasian patients. Symptom dimensions accurately classified patients into categorical DSM diagnoses. This study provides evidence on the validity and utility of transdiagnostic symptom dimensions of psychosis that transcend traditional diagnostic boundaries of psychotic disorders. Findings further show promising avenues for research at the interface of dimensional psychopathological phenotypes and basic neurobiological dimensions of psychopathology.     

Association of preceding psychosis risk states and non‐psychotic mental disorders with incidence of clinical psychosis in the general population: a prospective study in the NEMESIS‐2 cohort

The validity and clinical utility of the concept of “clinical high risk” (CHR) for psychosis have so far been investigated only in risk‐enriched samples in clinical settings. In this population‐based prospective study, we aimed – for the first time – to assess the incidence rate of clinical psychosis and es­timate the population attributable fraction (PAF) of that incidence for preceding psychosis risk states and DSM‐IV diagnoses of non‐psychotic mental disorders (mood disorders, anxiety disorders, alcohol use disorders, and drug use disorders). All analyses were adjusted for age, gender and education. The incidence rate of clinical psychosis was 63.0 per 100,000 person‐years. The mutually‐adjusted Cox proportional hazards model indicated that preceding diagnoses of mood disorders (hazard ratio, HR=10.67, 95% CI: 3.12‐36.49), psychosis high‐risk state (HR=7.86, 95% CI: 2.76‐22.42) and drug use disorders (HR=5.33, 95% CI: 1.61‐17.64) were associated with an increased risk for clinical psychosis incidence. Of the clinical psychosis incidence in the population, 85.5% (95% CI: 64.6‐94.1) was attributable to prior psychopathology, with mood disorders (PAF=66.2, 95% CI: 33.4‐82.9), psychosis high‐risk state (PAF=36.9, 95% CI: 11.3‐55.1), and drug use disorders (PAF=18.7, 95% CI: –0.9 to 34.6) as the most important factors. Although the psychosis high‐risk state displayed a high relative risk for clinical psychosis outcome even after adjusting for other psychopathology, the PAF was comparatively low, given the low prevalence of psychosis high‐risk states in the population. These findings provide empirical evidence for the “prevention paradox” of targeted CHR early intervention. A comprehensive prevention strategy with a focus on broader psychopathology may be more effective than the current psychosis‐focused approach for achieving population‐based improvements in prevention of psychotic disorders.     

Progress in achieving quantitative classification of psychopathology

Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad “spectrum level” dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the “problem of comorbidity” by explicitly modeling patterns of co‐occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach.     

Psychopathology in 7‐year‐old children with familial high risk of developing schizophrenia spectrum psychosis or bipolar disorder – The Danish High Risk and Resilience Study ‐ VIA 7, a population‐based cohort study

This study aimed to compare the psychopathological profiles of children at familial high risk of schizophrenia spectrum psychosis (FHR‐SZ) or bipolar disorder (FHR‐BP) with population‐based controls. We used Danish nationwide registers to retrieve a cohort of 522 seven‐year‐old children of parents with schizophrenia spectrum psychosis (N=202), bipolar disorder (N=120) or none of these disorders (N=200). Psychopathology was assessed by reports from multiple informants, including children, parents and teachers. Lifetime DSM‐IV diagnoses were ascertained by blinded raters through the Schedule for Affective Disorders and Schizophrenia for School‐Age Children. The dimensional assessment of psychopathology was performed by the Child Behavior Checklist, the Teacher's Report Form, a modified version of the ADHD‐Rating Scale, the Test Observation Form, and the State‐Trait Anxiety Inventory for Children. Current level of functioning was evaluated using the Children's Global Assessment Scale (CGAS). The prevalence of lifetime psychiatric diagnoses was significantly higher in both FHR‐SZ children (38.7%, odds ratio, OR=3.5, 95% confidence interval, CI: 2.2‐5.7, p < 0.001) and FHR‐BP children (35.6%, OR=3.1, 95% CI: 1.8‐5.3, p < 0.001) compared with controls (15.2%). FHR‐SZ children displayed significantly more dimensional psychopathology on all scales and subscales compared with controls except for the Anxious subscale of the Test Observation Form. FHR‐BP children showed higher levels of dimensional psychopathology on several scales and subscales compared with controls, but lower levels compared with FHR‐SZ children. Level of functioning was lower in both FHR‐SZ children (CGAS mean score = 68.2; 95% CI: 66.3‐70.2, p < 0.0001) and FHR‐BP children (73.7; 95% CI: 71.2‐76.3, p < 0.05) compared with controls (77.9; 95% CI: 75.9‐79.9). In conclusion, already at the age of seven, FHR‐SZ and FHR‐BP children show a higher prevalence of a broad spectrum of categorical and dimensional psychopathology compared with controls. These results emphasize the need for developing early intervention strategies towards this vulnerable group of children.     

The effectiveness of psychodynamic psychotherapies: An update

This paper provides a comprehensive review of outcome studies and meta‐analyses of effectiveness studies of psychodynamic therapy (PDT) for the major categories of mental disorders. Comparisons with inactive controls (waitlist, treatment as usual and placebo) generally but by no means invariably show PDT to be effective for depression, some anxiety disorders, eating disorders and somatic disorders. There is little evidence to support its implementation for post‐traumatic stress disorder, obsessive‐compulsive disorder, bulimia nervosa, cocaine dependence or psychosis. The strongest current evidence base supports relatively long‐term psychodynamic treatment of some personality disorders, particularly borderline personality disorder. Comparisons with active treatments rarely identify PDT as superior to control interventions and studies are generally not appropriately designed to provide tests of statistical equivalence. Studies that demonstrate inferiority of PDT to alternatives exist, but are small in number and often questionable in design. Reviews of the field appear to be subject to allegiance effects. The present review recommends abandoning the inherently conservative strategy of comparing heterogeneous “families” of therapies for heterogeneous diagnostic groups. Instead, it advocates using the opportunities provided by bioscience and computational psychiatry to creatively explore and assess the value of protocol‐directed combinations of specific treatment components to address the key problems of individual patients.     

An empirically derived approach to the classification and diagnosis of mood disorders

This article describes a system for diagnosing mood disorders that is empirically derived and designed for its clinical utility in everyday practice. A ran-dom national sample of psychiatrists and clinical psychologists described a randomly selected current patient with a measure designed for clinically ex-perienced informants, the Mood Disorder Diagnostic Questionnaire (MDDQ), and completed additional research forms. We applied factor analysis to the MDDQ to identify naturally occurring diagnostic groupings within the patient sample. The analysis yielded three clinically distinct mood disorder dimen-sions or spectra, consistent with the major mood disturbances included in the DSM and ICD over successive editions (major depression, dysthymia, and mania), along with a suicide risk index. Diagnostic criteria were determined strictly empirically. Initial data using diagnostic efficiency statistics sup-ported the accuracy of the dimensions in discriminating DSM-IV diagnoses; regression analyses supported the discriminant validity of the MDDQ scales; and correlational analysis demonstrated coherent patterns of association with family history of mood disorders and functional outcomes, supporting va-lidity. Perhaps most importantly, the MDDQ diagnostic scales demonstrated incremental validity in predicting adaptive functioning and psychiatric his-tory over and above DSM-IV diagnosis. The empirically derived syndromes can be used to diagnose mood syndromes dimensionally without complex di-agnostic algorithms or can be combined into diagnostic prototypes that eliminate the need for ever-expanding categories of mood disorders that are clini-cally unwieldy.     

Childhood adversities and psychosis: evidence,challenges, implications

There is a substantial body of research reporting evidence of associations between various forms of childhood adversity and psychosis, across the spectrum from experiences to disorder. This has been extended, more recently, to include studies of cumulative effects, of interactions with other factors, of specific effects, and of putative biological and psychological mechanisms. In this paper we evaluate this research and highlight the remaining methodological issues and gaps that temper, but do not dismiss, conclusions about the causal role of childhood adversity. We also consider the emerging work on cumulative, synergistic, and specific effects and on mechanisms; and discuss the broader implications of this line of research for our understanding of psychosis. We conclude that the current balance of evidence is that childhood adversities – particularly exposure to multiple adversities involving hostility and threat – do, in some people, contribute to the onset of psychotic experiences and psychotic disorders.     

Disorders related to sexuality and gender identity in the ICD‐11: revising the ICD‐10 classification based on current scientific evidence,best clinical practices,and human rights considerations

In the World Health Organization's forthcoming eleventh revision of the International Classification of Diseases and Related Health Problems (ICD‐11), substantial changes have been proposed to the ICD‐10 classification of mental and behavioural disorders related to sexuality and gender identity. These concern the following ICD‐10 disorder groupings: F52 Sexual dysfunctions, not caused by organic disorder or disease; F64 Gender identity disorders; F65 Disorders of sexual preference; and F66 Psychological and behavioural disorders associated with sexual development and orientation. Changes have been proposed based on advances in research and clinical practice, and major shifts in social attitudes and in relevant policies, laws, and human rights standards. This paper describes the main recommended changes, the rationale and evidence considered, and important differences from the DSM‐5. An integrated classification of sexual dysfunctions has been proposed for a new chapter on Conditions Related to Sexual Health, overcoming the mind/body separation that is inherent in ICD‐10. Gender identity disorders in ICD‐10 have been reconceptualized as Gender incongruence, and also proposed to be moved to the new chapter on sexual health. The proposed classification of Paraphilic disorders distinguishes between conditions that are relevant to public health and clinical psychopathology and those that merely reflect private behaviour. ICD‐10 categories related to sexual orientation have been recommended for deletion from the ICD‐11.     

Diagnosis and classification of disorders specifically associated with stress: proposals for ICD‐11

The diagnostic concepts of post‐traumatic stress disorder (PTSD) and other disorders specifically associated with stress have been intensively discussed among neuro‐ and social scientists, clinicians, epidemiologists, public health planners and humanitarian aid workers around the world. PTSD and adjustment disorder are among the most widely used diagnoses in mental health care worldwide. This paper describes proposals that aim to maximize clinical utility for the classification and grouping of disorders specifically associated with stress in the forthcoming 11th revision of the International Classification of Diseases (ICD‐11). Proposals include a narrower concept for PTSD that does not allow the diagnosis to be made based entirely on non‐specific symptoms; a new complex PTSD category that comprises three clusters of intra‐ and interpersonal symptoms in addition to core PTSD symptoms; a new diagnosis of prolonged grief disorder, used to describe patients that undergo an intensely painful, disabling, and abnormally persistent response to bereavement; a major revision of “adjustment disorder” involving increased specification of symptoms; and a conceptualization of “acute stress reaction” as a normal phenomenon that still may require clinical intervention. These proposals were developed with specific considerations given to clinical utility and global applicability in both low‐ and high‐income countries.     

A meta‐review of “lifestyle psychiatry”: the role of exercise,smoking, diet and sleep in the prevention and treatment of mental disorders

There is increasing academic and clinical interest in how “lifestyle factors” traditionally associated with physical health may also relate to mental health and psychological well‐being. In response, international and national health bodies are producing guidelines to address health behaviors in the prevention and treatment of mental illness. However, the current evidence for the causal role of lifestyle factors in the onset and prognosis of mental disorders is unclear. We performed a systematic meta‐review of the top‐tier evidence examining how physical activity, sleep, dietary patterns and tobacco smoking impact on the risk and treatment outcomes across a range of mental disorders. Results from 29 meta‐analyses of prospective/cohort studies, 12 Mendelian randomization studies, two meta‐reviews, and two meta‐analyses of randomized controlled trials were synthesized to generate overviews of the evidence for targeting each of the specific lifestyle factors in the prevention and treatment of depression, anxiety and stress‐related disorders, schizophrenia, bipolar disorder, and attention‐deficit/hyperactivity disorder. Standout findings include: a) convergent evidence indicating the use of physical activity in primary prevention and clinical treatment across a spectrum of mental disorders; b) emerging evidence implicating tobacco smoking as a causal factor in onset of both common and severe mental illness; c) the need to clearly establish causal relations between dietary patterns and risk of mental illness, and how diet should be best addressed within mental health care; and d) poor sleep as a risk factor for mental illness, although with further research required to understand the complex, bidirectional relations and the benefits of non‐pharmacological sleep‐focused interventions. The potentially shared neurobiological pathways between multiple lifestyle factors and mental health are discussed, along with directions for future research, and recommendations for the implementation of these findings at public health and clinical service levels.     

The ICD‐11 developmental field study of reliability of diagnoses of high‐burden mental disorders: results among adult patients in mental health settings of 13 countries

Reliable, clinically useful, and globally applicable diagnostic classification of mental disorders is an essential foundation for global mental health. The World Health Organization (WHO) is nearing completion of the 11th revision of the International Classification of Diseases and Related Health Problems (ICD‐11). The present study assessed inter‐diagnostician reliability of mental disorders accounting for the greatest proportion of global disease burden and the highest levels of service utilization – schizophrenia and other primary psychotic disorders, mood disorders, anxiety and fear‐related disorders, and disorders specifically associated with stress – among adult patients presenting for treatment at 28 participating centers in 13 countries. A concurrent joint‐rater design was used, focusing specifically on whether two clinicians, relying on the same clinical information, agreed on the diagnosis when separately applying the ICD‐11 diagnostic guidelines. A total of 1,806 patients were assessed by 339 clinicians in the local language. Intraclass kappa coefficients for diagnoses weighted by site and study prevalence ranged from 0.45 (dysthymic disorder) to 0.88 (social anxiety disorder) and would be considered moderate to almost perfect for all diagnoses. Overall, the reliability of the ICD‐11 diagnostic guidelines was superior to that previously reported for equivalent ICD‐10 guidelines. These data provide support for the suitability of the ICD‐11 diagnostic guidelines for implementation at a global level. The findings will inform further revision of the ICD‐11 diagnostic guidelines prior to their publication and the development of programs to support professional training and implementation of the ICD‐11 by WHO member states.     

Etiology in psychiatry: embracing the reality of poly‐gene‐environmental causation of mental illness

Intriguing findings on genetic and environmental causation suggest a need to reframe the etiology of mental disorders. Molecular genetics shows that thousands of common and rare genetic variants contribute to mental illness. Epidemiological studies have identified dozens of environmental exposures that are associated with psychopathology. The effect of environment is likely conditional on genetic factors, resulting in gene‐environment interactions. The impact of environmental factors also depends on previous exposures, resulting in environment‐environment interactions. Most known genetic and environmental factors are shared across multiple mental disorders. Schizophrenia, bipolar disorder and major depressive disorder, in particular, are closely causally linked. Synthesis of findings from twin studies, molecular genetics and epidemiological research suggests that joint consideration of multiple genetic and environmental factors has much greater explanatory power than separate studies of genetic or environmental causation. Multi‐factorial gene‐environment interactions are likely to be a generic mechanism involved in the majority of cases of mental illness, which is only partially tapped by existing gene‐environment studies. Future research may cut across psychiatric disorders and address poly‐causation by considering multiple genetic and environmental measures across the life course with a specific focus on the first two decades of life. Integrative analyses of poly‐causation including gene‐environment and environment‐environment interactions can realize the potential for discovering causal types and mechanisms that are likely to generate new preventive and therapeutic tools.     

A critique of the “ultra‐high risk” and “transition” paradigm

The transdiagnostic expression of psychotic experiences in common mental disorder (anxiety/depression/substance use disorder) is associated with a poorer prognosis, and a small minority of people may indeed develop a clinical picture that meets criteria for schizophrenia. However, it appears neither useful nor valid to observe early states of multidimensional psychopathology in young people through the “schizo”‐prism, and apply misleadingly simple, unnecessary and inefficient binary concepts of “risk” and “transition”. A review of the “ultra‐high risk” (UHR) or “clinical high risk” (CHR) literature indicates that UHR/CHR samples are highly heterogeneous and represent individuals diagnosed with common mental disorder (anxiety/depression/substance use disorder) and a degree of psychotic experiences. Epidemiological research has shown that psychotic experiences are a (possibly non‐causal) marker of the severity of multidimensional psychopathology, driving poor outcome, yet notions of “risk” and “transition” in UHR/CHR research are restrictively defined on the basis of positive psychotic phenomena alone, ignoring how baseline differences in multidimensional psychopathology may differentially impact course and outcome. The concepts of “risk” and “transition” in UHR/CHR research are measured on the same dimensional scale, yet are used to produce artificial diagnostic shifts. In fact, “transition” in UHR/CHR research occurs mainly as a function of variable sample enrichment strategies rather than the UHR/CHR “criteria” themselves. Furthermore, transition rates in UHR/CHR research are inflated as they do not exclude false positives associated with the natural fluctuation of dimensional expression of psychosis. Biological associations with “transition” thus likely represent false positive findings, as was the initial claim of strong effects of omega‐3 polyunsatured fatty acids in UHR samples. A large body of UHR/CHR intervention research has focused on the questionable outcome of “transition”, which shows lack of correlation with functional outcome. It may be more productive to consider the full range of person‐specific psychopathology in all young individuals who seek help for mental health problems, instead of “policing” youngsters for the transdiagnostic dimension of psychosis. Instead of the relatively inefficient medical high‐risk approach, a public health perspective, focusing on improved access to a low‐stigma, high‐hope, small scale and youth‐specific environment with acceptable language and interventions may represent a more useful and efficient strategy.     

A network theory of mental disorders

In recent years, the network approach to psychopathology has been advanced as an alternative way of conceptualizing mental disorders. In this approach, mental disorders arise from direct interactions between symptoms. Although the network approach has led to many novel methodologies and substantive applications, it has not yet been fully articulated as a scientific theory of mental disorders. The present paper aims to develop such a theory, by postulating a limited set of theoretical principles regarding the structure and dynamics of symptom networks. At the heart of the theory lies the notion that symptoms of psychopathology are causally connected through myriads of biological, psychological and societal mechanisms. If these causal relations are sufficiently strong, symptoms can generate a level of feedback that renders them self‐sustaining. In this case, the network can get stuck in a disorder state. The network theory holds that this is a general feature of mental disorders, which can therefore be understood as alternative stable states of strongly connected symptom networks. This idea naturally leads to a comprehensive model of psychopathology, encompassing a common explanatory model for mental disorders, as well as novel definitions of associated concepts such as mental health, resilience, vulnerability and liability. In addition, the network theory has direct implications for how to understand diagnosis and treatment, and suggests a clear agenda for future research in psychiatry and associated disciplines.     

Advantages and limitations of Internet‐based interventions for common mental disorders

Several Internet interventions have been developed and tested for common mental disorders, and the evidence to date shows that these treatments often result in similar outcomes as in face‐to‐face psychotherapy and that they are cost‐effective. In this paper, we first review the pros and cons of how participants in Internet treatment trials have been recruited. We then comment on the assessment procedures often involved in Internet interventions and conclude that, while online questionnaires yield robust results, diagnoses cannot be determined without any contact with the patient. We then review the role of the therapist and conclude that, although treatments including guidance seem to lead to better outcomes than unguided treatments, this guidance can be mainly practical and supportive rather than explicitly therapeutic in orientation. Then we briefly describe the advantages and disadvantages of treatments for mood and anxiety disorders and comment on ways to handle comorbidity often associated with these disorders. Finally we discuss challenges when disseminating Internet interventions. In conclusion, there is now a large body of evidence suggesting that Internet interventions work. Several research questions remain open, including how Internet interventions can be blended with traditional forms of care.     

Using the tools of genetic epidemiology to understand sex differences in neuropsychiatric disorders

Many neuropsychiatric disorders exhibit differences in prevalence, age of onset, symptoms or course of illness between males and females. For the most part, the origins of these differences are not well understood. In this article, we provide an overview of sex differences in psychiatric disorders including autism spectrum disorder (ASD), attention deficit/hyperactivity disorder (ADHD), anxiety, depression, alcohol and substance abuse, schizophrenia, eating disorders and risk of suicide. We discuss both genetic and nongenetic mechanisms that have been hypothesized to underlie these differences, including ascertainment bias, environmental stressors, X‐ or Y‐linked risk loci, and differential liability thresholds in males and females. We then review the use of twin, family and genome‐wide association approaches to study potential genetic mechanisms of sex differences and the extent to which these designs have been employed in studies of psychiatric disorders. We describe the utility of genetic epidemiologic study designs, including classical twin and family studies, large‐scale studies of population registries, derived recurrence risks, and molecular genetic analyses of genome‐wide variation that may enhance our understanding sex differences in neuropsychiatric disorders.     

Beyond the “at risk mental state” concept: transitioning to transdiagnostic psychiatry

The “at risk mental state” for psychosis approach has been a catalytic, highly productive research paradigm over the last 25 years. In this paper we review that paradigm and summarize its key lessons, which include the valence of this phenotype for future psychosis outcomes, but also for comorbid, persistent or incident non‐psychotic disorders; and the evidence that onset of psychotic disorder can at least be delayed in ultra high risk (UHR) patients, and that some full‐threshold psychotic disorder may emerge from risk states not captured by UHR criteria. The paradigm has also illuminated risk factors and mechanisms involved in psychosis onset. However, findings from this and related paradigms indicate the need to develop new identification and diagnostic strategies. These findings include the high prevalence and impact of mental disorders in young people, the limitations of current diagnostic systems and risk identification approaches, the diffuse and unstable symptom patterns in early stages, and their pluripotent, transdiagnostic trajectories. The approach we have recently adopted has been guided by the clinical staging model and adapts the original “at risk mental state” approach to encompass a broader range of inputs and output target syndromes. This approach is supported by a number of novel modelling and prediction strategies that acknowledge and reflect the dynamic nature of psychopathology, such as dynamical systems theory, network theory, and joint modelling. Importantly, a broader transdiagnostic approach and enhancing specific prediction (profiling or increasing precision) can be achieved concurrently. A holistic strategy can be developed that applies these new prediction approaches, as well as machine learning and iterative probabilistic multimodal models, to a blend of subjective psychological data, physical disturbances (e.g., EEG measures) and biomarkers (e.g., neuroinflammation, neural network abnormalities) acquired through fine‐grained sequential or longitudinal assessments. This strategy could ultimately enhance our understanding and ability to predict the onset, early course and evolution of mental ill health, further opening pathways for preventive interventions.