Clashing Diagnostic Approaches: DSM-ICD Versus RDoC

Novel genome-wide associations for effort valuation and psychopathology in children and adults

The Research Domain Criteria (RDoC) initiative was established by the US National Institute of Mental Health as a multilevel, disorder-agnostic framework for analysis of human psychopathology through designated domains and constructs, including the "Positive Valence Systems" domain focused on reward-related behavior. This study investigates the reward valuation subconstruct of "effort" and its association with genetic markers, functional neurobiological pathways, and polygenic risk scores for psychopathology in 1215 children aged 6-12 and their parents (n = 1044). All participants completed the effort expenditure for rewards task (EEfRT), which assesses "effort" according to two quantitative measures: hard-task choice and reward sensitivity. Genetic association analyses were undertaken in MAGMA, utilizing EEfRT outcome variables as genome-wide association studies phenotypes to compute SNP and gene-level associations. Genome-wide association analyses found two distinct genetic loci that were significantly associated with measures of reward sensitivity and a separate genetic locus associated with hard task choice. Gene-set enrichment analysis yielded significant associations between "effort" and multiple gene sets involved in reward processing-related pathways, including dopamine receptor signaling, limbic system and forebrain development, and biological response to cocaine. These results serve to establish "effort" as a relevant construct for understanding reward-related behavior at the genetic level and support the RDoC framework for assessing disorder-agnostic psychopathology.

Gut microbiota composition links to variation in functional domains across psychiatric disorders

OBJECTIVE

Changes in microbial composition are observed in various psychiatric disorders, but their specificity to certain symptoms or processes remains unclear. This study explores the associations between the gut microbiota composition and the Research Domain Criteria (RDoC) domains of functioning, representing symptom domains, specifically focusing on stress-related and neurodevelopmental disorders in patients with and without psychiatric comorbidity.

METHODS

The gut microbiota was analyzed in 369 participants, comprising 272 individuals diagnosed with a mood disorder, anxiety disorder, attention deficit/hyperactivity disorder, autism spectrum disorder, and/or substance use disorder, as well as 97 psychiatrically unaffected individuals. The RDoC domains were estimated using principal component analysis (PCA) with oblique rotation on a range of psychiatric, psychological, and personality measures. Associations between the gut microbiota and the functional domains were assessed using multiple linear regression and permanova, adjusted for age, sex, diet, smoking, medication use and comorbidity status.

RESULTS

Four functional domains, aligning with RDoC's negative valence, social processes, cognitive systems, and arousal/regulatory systems domains, were identified. Significant associations were found between these domains and eight microbial genera, including associations of negative valence with the abundance of the genera Sellimonas, CHKCI001, Clostridium sensu stricto 1, Oscillibacter, and Flavonifractor; social processes with Sellimonas; cognitive systems with Sporobacter and Hungatella; and arousal/regulatory systems with Ruminococcus torques (all pFDR < 0.05).

CONCLUSION

Our findings demonstrate associations between the gut microbiota and the domains of functioning across patients and unaffected individuals, potentially mediated by immune-related processes. These results open avenues for microbiota-focused personalized interventions, considering psychiatric comorbidity. However, further research is warranted to establish causality and elucidate mechanistic pathways.

A critical review of hot executive functioning in youth attention-deficit/hyperactivity disorder: Methodological limitations, conceptual considerations, and future directions

Hot executive functioning (EF) - EF under emotionally or motivationally salient conditions - is a putative etiology of attention-deficit/hyperactivity disorder (ADHD), disruptive behavior problems (DBPs), and their related impairments. Despite two decades of research, the present study is the first review of the construct in youth ADHD, with a particular focus on the role of task design, age, and DBPs, as well as relevant conceptual and methodological considerations. While certain hot EF tasks have been investigated extensively (e.g., choice impulsivity), substantial inconsistency in measurement of the broader construct remains, severely limiting conclusions. Future research should a) consider the extent to which various hot EF tasks relate to one another, a higher order factor, and other related constructs; b) further investigate task design, particularly the elicitation of emotion or motivation and its anticipated effect on EF; and c) incorporate multiple levels of analysis to validate similarities and differences among tasks with regard to the affective experiences and cognitive demands they elicit. With improved measurement and conceptual clarity, hot EF has potential to advance the literature on etiological pathways to ADHD, DBPs and associated impairments and, more broadly, may represent a useful tool for understanding the influence of emotion and motivation on cognition.

Longitudinal study of peer victimization, social support, and mental health during early adolescence

BACKGROUND

Peer victimization predicts the development of mental health symptoms in the transition to adolescence, but it is unclear whether and how parents and school environments can buffer this link.

METHODS

We analyzed two-year longitudinal data from the Adolescent Brain Cognitive Development (ABCD) study, involving a diverse sample of 11 844 children across the United States (average at baseline = 9.91 years; standard deviation = 0.63; range = 8.92-11.08; complete case sample = 8385). Longitudinal associations between peer victimization and two-year changes in mental health symptoms of major depression disorder (MDD), separation anxiety (SA), prodromal psychosis (PP), and attention-deficit/hyperactivity disorder (ADHD) were examined including a wide range of covariates. Mixed linear models were used to test for the moderating effects of parental warmth and prosocial school environment.

RESULTS

20% of children experienced peer victimization. Higher exposure to peer victimization was associated with increases in MDD, SA, and ADHD symptoms. Parental warmth was associated with decreases in MDD symptoms but did not robustly buffer the link between peer victimization and mental health symptoms. Prosocial school environment predicted decreases in PP symptoms and buffered the link between peer victimization and MDD symptoms but amplified the link between peer victimization and SA and ADHD symptoms.

CONCLUSIONS

Peer victimization is associated with increases in mental health symptoms during the transition to adolescence. Parental warmth and prosocial school environments might not be enough to counter the negative consequences of peer victimization on all mental health outcomes.

Precision psychiatry and Research Domain Criteria: Implications for clinical trials and future practice

Psychiatric disorders are associated with significant social and economic burdens, many of which are related to issues with current diagnosis and treatments. The coronavirus (COVID-19) pandemic is estimated to have increased the prevalence and burden of major depressive and anxiety disorders, indicating an urgent need to strengthen mental health systems globally. To date, current approaches adopted in drug discovery and development for psychiatric disorders have been relatively unsuccessful. Precision psychiatry aims to tailor healthcare more closely to the needs of individual patients and, when informed by neuroscience, can offer the opportunity to improve the accuracy of disease classification, treatment decisions, and prevention efforts. In this review, we highlight the growing global interest in precision psychiatry and the potential for the National Institute of Health-devised Research Domain Criteria (RDoC) to facilitate the implementation of transdiagnostic and improved treatment approaches. The need for current psychiatric nosology to evolve with recent scientific advancements and increase awareness in emerging investigators/clinicians of the value of this approach is essential. Finally, we examine current challenges and future opportunities of adopting the RDoC-associated translational and transdiagnostic approaches in clinical studies, acknowledging that the strength of RDoC is that they form a dynamic framework of guiding principles that is intended to evolve continuously with scientific developments into the future. A collaborative approach that recruits expertise from multiple disciplines, while also considering the patient perspective, is needed to pave the way for precision psychiatry that can improve the prognosis and quality of life of psychiatric patients.

Evaluation of a Nondepleted Plasma Multiprotein-Based Model for Discriminating Psychiatric Disorders Using Multiple Reaction Monitoring-Mass Spectrometry: Proof-of-Concept Study

Psychiatric evaluation relies on subjective symptoms and behavioral observation, which sometimes leads to misdiagnosis. Despite previous efforts to utilize plasma proteins as objective markers, the depletion method is time-consuming. Therefore, this study aimed to enhance previous quantification methods and construct objective discriminative models for major psychiatric disorders using nondepleted plasma. Multiple reaction monitoring-mass spectrometry (MRM-MS) assays for quantifying 453 peptides in nondepleted plasma from 132 individuals [35 major depressive disorder (MDD), 47 bipolar disorder (BD), 23 schizophrenia (SCZ) patients, and 27 healthy controls (HC)] were developed. Pairwise discriminative models for MDD, BD, and SCZ, and a discriminative model between patients and HC were constructed by machine learning approaches. In addition, the proteins from nondepleted plasma-based discriminative models were compared with previously developed depleted plasma-based discriminative models. Discriminative models for MDD versus BD, BD versus SCZ, MDD versus SCZ, and patients versus HC were constructed with 11 to 13 proteins and showed reasonable performances (AUROC = 0.890-0.955). Most of the shared proteins between nondepleted and depleted plasma models had consistent directions of expression levels and were associated with neural signaling, inflammatory, and lipid metabolism pathways. These results suggest that multiprotein markers from nondepleted plasma have a potential role in psychiatric evaluation.

Assessment of biomarker stability and assay performance parameters for medical diagnosis: a case study of diagnosis of major depressive disorder

Aim: Assessing the stability profiles and assay performance of 24 biomarker assays in 32 biomarker/body fluid combinations identified as relevant for prediction of major depressive disorder. Materials & methods: Combinations were tested for stability and assay performance with ELISA at different storage and freeze-thaw conditions in pooled samples of 40 patients. Results: Stability and assay performance issues were found in almost all cases except three biomarkers in urine and three in serum. Conclusion: This study shows that, to produce reliable measurement data, assessments of stability and assay performance are essential. In development, other quality assurance parameters might be implemented to increase the level of measurement reliability by increasing assay performance control.

The absurdity of the latent disease model in mental health: 10,130,814 ways to have a DSM-5-TR psychological disorder

BACKGROUND

Latent disease classification is currently the accepted approach to mental illness diagnosis. In the United States, this takes the form of the Diagnostic and Statistical Manual of Mental Disorders-5-Text Revision (DSM-5-TR). Latent disease classification has been criticized for reliability and validity problems, particularly regarding diagnostic heterogeneity. No authors have calculated the scope of the heterogeneity problem of the entire DSM-5-TR.

AIMS

We addressed this issue by calculating the unique diagnostic profiles that exist for every DSM-5-TR diagnosis.

METHODS

We did this by applying formulas previously used in smaller heterogeneity analyses to all diagnoses within the DSM-5-TR.

RESULTS

We found that there are 10,130,814 ways to be diagnosed with a mental illness using DSM-5-TR criteria. When specifiers are considered, this number balloons to over 161 septillion unique diagnostic presentations (driven mainly by bipolar II disorder). Additionally, there are 1,951,065 ways to present with psychiatric symptoms, yet not meet diagnostic criteria.

CONCLUSIONS

Latent disease classification leads to considerable heterogeneity in possible presentations. We provide examples of how latent disease classification harms research and treatment programs. We echo recommendations for the dismissal of latent disease classification as a mental illness diagnostic program.

The future of diagnosis in clinical neurosciences: Comparing multiple sclerosis and schizophrenia

The ongoing developments of psychiatric classification systems have largely improved reliability of diagnosis, including that of schizophrenia. However, with an unknown pathophysiology and lacking biomarkers, its validity still remains low, requiring further advancements. Research has helped establish multiple sclerosis (MS) as the central nervous system (CNS) disorder with an established pathophysiology, defined biomarkers and therefore good validity and significantly improved treatment options. Before proposing next steps in research that aim to improve the diagnostic process of schizophrenia, it is imperative to recognize its clinical heterogeneity. Indeed, individuals with schizophrenia show high interindividual variability in terms of symptomatic manifestation, response to treatment, course of illness and functional outcomes. There is also a multiplicity of risk factors that contribute to the development of schizophrenia. Moreover, accumulating evidence indicates that several dimensions of psychopathology and risk factors cross current diagnostic categorizations. Schizophrenia shares a number of similarities with MS, which is a demyelinating disease of the CNS. These similarities appear in the context of age of onset, geographical distribution, involvement of immune-inflammatory processes, neurocognitive impairment and various trajectories of illness course. This article provides a critical appraisal of diagnostic process in schizophrenia, taking into consideration advancements that have been made in the diagnosis and management of MS. Based on the comparison between the two disorders, key directions for studies that aim to improve diagnostic process in schizophrenia are formulated. All of them converge on the necessity to deconstruct the psychosis spectrum and adopt dimensional approaches with deep phenotyping to refine current diagnostic boundaries.

The Social Determinants of Mental Illness: A Rapid Review of Systematic Reviews

Previous research agendas have prioritised the role of biological determinants in mental illness aetiology. This is of particular concern, as endorsing biological determinants has been shown to promote negative attitudes towards people with mental illness. The aim of this review was to provide an overview of high-quality evidence of the social determinants of mental illness. A rapid review of systematic reviews was conducted. Five databases were searched: Embase, Medline, Academic Search Complete, CINAHL Plus, and PsycINFO. Systematic reviews or meta-analyses that described any social determinant of mental illness, were published in peer-review journals in English, and focussed on human participants were included. The Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines were applied for the selection procedure. Thirty-seven systematic reviews were deemed eligible for review and narrative synthesis. Determinants identified included conflict, violence and maltreatment, life events and experiences, racism and discrimination, culture and migration, social interaction and support, structural policies and inequality, financial factors, employment factors, housing and living conditions, and demographic factors. We recommend that mental health nurses ensure adequate support be provided to those affected by the evidenced social determinants of mental illness.

Evaluation of delay discounting as a transdiagnostic research domain criteria indicator in 1388 general community adults

BACKGROUND

The Research Domain Criteria (RDoC) approach proposes a novel psychiatric nosology using transdiagnostic dimensional mechanistic constructs. One candidate RDoC indicator is delay discounting (DD), a behavioral economic measure of impulsivity, based predominantly on studies examining DD and individual conditions. The current study sought to evaluate the transdiagnostic significance of DD in relation to several psychiatric conditions concurrently.

METHODS

Participants were 1388 community adults (18-65) who completed an in-person assessment, including measures of DD, substance use, depression, anxiety, posttraumatic stress disorder, and attention-deficit hyperactivity disorder (ADHD). Relations between DD and psychopathology were examined with three strategies: first, examining differences by individual condition using clinical cut-offs; second, examining DD in relation to latent psychopathology variables via principal components analysis (PCA); and third, examining DD and all psychopathology simultaneously via structural equation modeling (SEM).

RESULTS

Individual analyses revealed elevations in DD were present in participants screening positive for multiple substance use disorders (tobacco, cannabis, and drug use disorder), ADHD, major depressive disorder (MDD), and an anxiety disorder (ps < 0.05-0.001). The PCA produced two latent components (substance involvement v. the other mental health indicators) and DD was significantly associated with both (ps < 0.001). In the SEM, unique significant positive associations were observed between the DD latent variable and tobacco, cannabis, and MDD (ps < 0.05-0.001).

CONCLUSIONS

These results provide some support for DD as a transdiagnostic indicator, but also suggest that studies of individual syndromes may include confounding via comorbidities. Further systematic investigation of DD as an RDoC indicator is warranted.

Introducing a depression-like syndrome for translational neuropsychiatry: a plea for taxonomical validity and improved comparability between humans and mice

Depressive disorders are the most burdensome psychiatric disorders worldwide. Although huge efforts have been made to advance treatment, outcomes remain unsatisfactory. Many factors contribute to this gridlock including suboptimal animal models. Especially limited study comparability and replicability due to imprecise terminology concerning depressive-like states are major problems. To overcome these issues, new approaches are needed. Here, we introduce a taxonomical concept for modelling depression in laboratory mice, which we call depression-like syndrome (DLS). It hinges on growing evidence suggesting that mice possess advanced socioemotional abilities and can display non-random symptom patterns indicative of an evolutionary conserved disorder-like phenotype. The DLS approach uses a combined heuristic method based on clinical depression criteria and the Research Domain Criteria to provide a biobehavioural reference syndrome for preclinical rodent models of depression. The DLS criteria are based on available, species-specific evidence and are as follows: (I) minimum duration of phenotype, (II) significant sociofunctional impairment, (III) core biological features, (IV) necessary depressive-like symptoms. To assess DLS presence and severity, we have designed an algorithm to ensure statistical and biological relevance of findings. The algorithm uses a minimum combined threshold for statistical significance and effect size (p value ≤ 0.05 plus moderate effect size) for each DLS criterion. Taken together, the DLS is a novel, biologically founded, and species-specific minimum threshold approach. Its long-term objective is to gradually develop into an inter-model validation standard and microframework to improve phenotyping methodology in translational research.

Psychometric evaluation of the Swedish Multidimensional Psychological Flexibility Inventory (MPFI)

Psychiatric disorders are common, and reliable measures are crucial for research and clinical practice. A cross-diagnostic construct that can be used to index treatment outcomes as well as prevalence of psychological ill health is psychological flexibility. The aim of this study was to validate a Swedish version of the Multidimensional Psychological Flexibility Inventory (MPFI). The MPFI has 12 subscales, six of which measure flexibility, and six that measure inflexibility. Using confirmatory factor analysis in a community sample of 670 participants, we found that a model with two higher order factors had satisfactory fit (CFI = .933) and a 12-factor model had the best fit to the data (CFI = .955). All 12 subscales showed adequate reliability (CRs = .803-.933) and the factor structure was similar across age groups and gender. Findings suggest that the Swedish version of the MPFI is a reliable instrument that can be used to index psychological flexibility. Potential areas for improvement of the instrument are discussed.

Auditory brainstem response deficits in learning disorders and developmental language disorder: a systematic review and meta-analysis

Although learning disorders (LD) and developmental language disorder (DLD) can be linked to overlapping psychological and behavioral deficits, such as phonological, morphological, orthographic, semantic, and syntactic deficits, as well as academic (e.g., reading) difficulties, they are currently separate diagnoses in the DSM-5 with explicit phenotypic differences. At a neural level, it is yet to be determined to what extent they have overlapping or distinct signatures. The identification of such neural markers/endophenotypes could be important for the development of physiological diagnostic tools, as well as an understanding of disorders across different dimensions, as recommended by the Research Domain Criteria Initiative (RDoC). The current systematic review and meta-analysis examined whether the two disorders can be differentiated based on the auditory brainstem response (ABR). Even though both diagnoses require hearing problems to be ruled out, a number of articles have demonstrated associations of these disorders with the auditory brainstem response. We demonstrated that both LD and DLD are associated with longer latencies in ABR Waves III, V, and A, as well as reduced amplitude in Waves V and A. However, multilevel subgroup analyses revealed that LD and DLD do not significantly differ for any of these ABR waves. Results suggest that less efficient early auditory processing is a shared mechanism underlying both LD and DLD.

Testing intrusive thoughts as illness pathways between eating disorders and obsessive-compulsive disorder symptoms: a network analysis

Obsessive-compulsive disorder (OCD) and eating disorders (EDs) frequently co-occur. Intrusive thoughts are a mechanism that may maintain this comorbidity. This study used network analysis to identify central ED-related intrusive thoughts and tested which intrusive thoughts connected ED and OCD symptoms. Two cross-sectional graphical LASSO networks were computed using a sample of 353 non-clinical participants (mean age = 35.38, SD = 9.9, 40% female, 81.6% Caucasian) with elevated disordered eating symptoms. Model 1 included just ED-related intrusive thoughts, and Model 2 included ED-related intrusive thoughts, ED, and OCD symptoms. In Model 1, we found that thoughts about one's bodily appearance (i.e., looking horrible, getting fat, gaining weight) were most central. In Model 2, we found that desire to lose weight, eating in secret, and shape dissatisfaction were most central. We identified one illness pathway (i.e., difficulty concentrating due to thoughts of food/calories) connecting intrusive thoughts, ED symptoms, and OCD symptoms. However, intrusive thoughts did not bridge ED and OCD symptoms. Hence, we found some evidence that ED-related intrusive thoughts may contribute to ED and OCD symptoms based on thought content and frequency. However, other aspects of intrusive thoughts should be considered to ascertain whether they do in fact significantly contribute to ED and OCD comorbidity. Prevention efforts targeting ED-related intrusive thoughts may attenuate ED and OCD symptoms among subclinical individuals.

A call for renewed attention to construct validity and measurement in psychopathology research

Psychopathologists have failed to make significant progress toward understanding the causes of psychopathology. Despite the foundational importance of construct validity and measurement to our field, insufficient attention is paid to these concerns in the assessment of psychopathology vulnerabilities prior to their implementation in causal models. I review the current state of construct validity and measurement in psychopathology research, highlighting the lack of consensus regarding how we should define and measure vulnerability constructs. The limited capacity of open science practices to address these definitional and measurement challenges is discussed. Recommendations for progress are made, including the need for consensus agreement on (1) working definitions and (2) measures of vulnerability constructs. Other recommendations include (3) the need to incentivize 'pre-clinical' descriptive work focused on measurement development, (4) the formation of open-access databases designed to facilitate measurement evaluation and development, and (5) increased exploration of the use of novel technologies to facilitate the collection of high-quality measures of vulnerability.

Integrating cultural evolution and behavioral genetics

The 29 commentaries amplified our key arguments; offered extensions, implications, and applications of the framework; and pushed back and clarified. To help forge the path forward for cultural evolutionary behavioral genetics, we (1) focus on conceptual disagreements and misconceptions about the concepts of heritability and culture; (2) further discuss points raised about the intertwined relationship between culture and genes; and (3) address extensions to the proposed framework, particularly as it relates to cultural clusters, development, and power. These commentaries, and the deep engagement they represent, reinforce the importance of integrating cultural evolution and behavioral genetics.

Functional neuroimaging in psychiatry and the case for failing better

Psychiatric disorders encompass complex aberrations of cognition and affect and are among the most debilitating and poorly understood of any medical condition. Current treatments rely primarily on interventions that target brain function (drugs) or learning processes (psychotherapy). A mechanistic understanding of how these interventions mediate their therapeutic effects remains elusive. From the early 1990s, non-invasive functional neuroimaging, coupled with parallel developments in the cognitive neurosciences, seemed to signal a new era of neurobiologically grounded diagnosis and treatment in psychiatry. Yet, despite three decades of intense neuroimaging research, we still lack a neurobiological account for any psychiatric condition. Likewise, functional neuroimaging plays no role in clinical decision making. Here, we offer a critical commentary on this impasse and suggest how the field might fare better and deliver impactful neurobiological insights.

Klerman's "credo" reconsidered: neo-Kraepelinianism, Spitzer's views, and what we can learn from the past

In 1978, G. Klerman published an essay in which he named the then-nascent "neo-Kraepelinian" movement and formulated a "credo" of nine propositions expressing the movement's essential claims and aspirations. Klerman's essay appeared on the eve of the triumph of neo-Kraepelinian ideas in the DSM-III. However, this diagnostic system has subsequently come under attack, opening the way for competing proposals for the future of psychiatric nosology. To better understand what is at stake, in this paper I provide a close reading and consideration of Klerman's credo in light of the past forty years of research and reflection. The credo is placed in the context of two equally seminal publications in the same year, one by S. Guze, the leading neo-Kraepelinian theorist, and the other by R. Spitzer and J. Endicott, defining mental disorder. The divergences between Spitzer and standard neo-Kraepelinianism are highlighted and argued to be much more important than is generally realized. The analysis of Klerman's credo is also argued to have implications for how to satisfactorily resolve the current nosological ferment in psychiatry. In addition to issues such as creating descriptive syndromal diagnostic criteria, overthrowing psychoanalytic dominance of psychiatry, and making psychiatry more scientific, neo-Kraepelinians were deeply concerned with the conceptual issue of the nature of mental disorder and the defense of psychiatry's medical legitimacy in response to antipsychiatric criticisms. These issues cannot be ignored, and I argue that proposals currently on offer to replace the neo-Kraepelinian system, especially popular proposals to replace it with dimensional measures, fail to adequately address them.

Machine Learning Prediction of ADHD Severity: Association and Linkage to ADGRL3, DRD4, and SNAP25

OBJECTIVE

To investigate whether single nucleotide polymorphisms (SNPs) in the ADGRL3, DRD4, and SNAP25 genes are associated with and predict ADHD severity in families from a Caribbean community.

METHOD

ADHD severity was derived using latent class cluster analysis of DSM-IV symptomatology. Family-based association tests were conducted to detect associations between SNPs and ADHD severity latent phenotypes. Machine learning algorithms were used to build predictive models of ADHD severity based on demographic and genetic data.

RESULTS

Individuals with ADHD exhibited two seemingly independent latent class severity configurations. SNPs harbored in DRD4, SNAP25, and ADGRL3 showed evidence of linkage and association to symptoms severity and a potential pleiotropic effect on distinct domains of ADHD severity. Predictive models discriminate severe from non-severe ADHD in specific symptom domains.

CONCLUSION

This study supports the role of DRD4, SNAP25, and ADGRL3 genes in outlining ADHD severity, and a new prediction framework with potential clinical use.

Examining weekly relationships between obsessive-compulsive and eating disorder symptoms

BACKGROUND

Despite the severity and high rate of co-occurrence between eating disorders (ED) and obsessive-compulsive disorder (OCD), less is known regarding the longitudinal sequencing of their comorbidity and whether and how their symptoms may influence one another over time. The current study sought to answer these questions by testing if a bidirectional, longitudinal relationship exists between ED symptoms and OCD obsessions and compulsions.

METHODS

We examined the relationship between ED symptoms, obsessions and compulsions across five time points, each one week apart using auto-regressive cross-lagged panel modeling. The final sample consisted of 358 individuals from the community with moderate levels of ED and OCD symptoms, the majority of whom identified as White and male.

RESULTS

Bivariate correlations revealed that ED symptoms, obsessions and compulsions were associated with one another across the five weeks. Two cross-lagged panel models indicated that ED symptoms predicted OCD symptoms at numerous time points and vice versa. However, we found this significant longitudinal associations across only certain weeks. Notably, the models found that only ED symptoms and OCD obsessions predicted one another across different time points across the five weeks; ED symptoms and OCD compulsions did not predict one another.

LIMITATIONS

Due to the non-clinical nature of the sample, there is limited generalizability to clinical populations.

CONCLUSIONS

Our results provide preliminary evidence that there is a bidirectional, longitudinal relationship between ED symptoms and OCD symptoms among a community sample, particularly with respect to cognitive as opposed to behavioral symptoms.

Beyond Description and Deficits: How Computational Psychiatry Can Enhance an Understanding of Decision-Making in Anorexia Nervosa

PURPOSE OF REVIEW

Despite decades of research, knowledge of the mechanisms maintaining anorexia nervosa (AN) remains incomplete and clearly effective treatments elusive. Novel theoretical frameworks are needed to advance mechanistic and treatment research for this disorder. Here, we argue the utility of engaging a novel lens that differs from existing perspectives in psychiatry. Specifically, we argue the necessity of expanding beyond two historically common perspectives: (1) the descriptive perspective: the tendency to define mechanisms on the basis of surface characteristics and (2) the deficit perspective: the tendency to search for mechanisms associated with under-functioning of decision-making abilities and related circuity, rather than problems of over-functioning, in psychiatric disorders.

RECENT FINDINGS

Computational psychiatry can provide a novel framework for understanding AN because this approach emphasizes the role of computational misalignments (rather than absolute deficits or excesses) between decision-making strategies and environmental demands as the key factors promoting psychiatric illnesses. Informed by this approach, we argue that AN can be understood as a disorder of excess goal pursuit, maintained by over-engagement, rather than disengagement, of executive functioning strategies and circuits. Emerging evidence suggests that this same computational imbalance may constitute an under-investigated phenotype presenting transdiagnostically across psychiatric disorders. A variety of computational models can be used to further elucidate excess goal pursuit in AN. Most traditional psychiatric treatments do not target excess goal pursuit or associated neurocognitive mechanisms. Thus, targeting at the level of computational dysfunction may provide a new avenue for enhancing treatment for AN and related disorders.

Differential aberrant connectivity of precuneus and anterior insula may underpin the diagnosis of schizophrenia and mood disorders

BACKGROUND

Over the past decade, resting-state functional magnetic resonance imaging (rs-fMRI) has concentrated on brain networks such as the default mode network (DMN), the salience network (SN), and the central executive network (CEN), allowing for a better understanding of cognitive deficits observed in mental disorders, as well as other characteristic psychopathological phenomena such as thought and behavior disorganization.

AIM

To investigate differential patterns of effective connectivity across distributed brain networks involved in schizophrenia (SCH) and mood disorders.

METHODS

The sample comprised 58 patients with either paranoid syndrome in the context of SCH (n = 26) or depressive syndrome (Ds) (n = 32), in the context of major depressive disorder or bipolar disorder. The methods used include rs-fMRI and subsequent dynamic causal modeling to determine the direction and strength of connections to and from various nodes in the DMN, SN and CEN.

RESULTS

A significant excitatory connection from the dorsal anterior cingulate cortex to the anterior insula (aI) was observed in the SCH patient group, whereas inhibitory connections from the precuneus to the ventrolateral prefrontal cortex and from the aI to the precuneus were observed in the Ds group.

CONCLUSION

The results delineate specific patterns associated with SCH and Ds and offer a better explanation of the underlying mechanisms of these disorders, and inform differential diagnosis and precise treatment targeting.

Measuring the biological embedding of racial trauma among Black Americans utilizing the RDoC approach

The National Institute of Mental Health (NIMH) Research Domain Criteria (RDoC) initiative aims to understand the mechanisms influencing psychopathology through a dimensional approach. Limited research thus far has considered potential racial/ethnic differences in RDoC constructs that are influenced by developmental and contextual processes. A growing body of research has demonstrated that racial trauma is a pervasive chronic stressor that impacts the health of Black Americans across the life course. In this review article, we examine the ways that an RDOC framework could allow us to better understand the biological embedding of racial trauma among Black Americans. We also specifically examine the Negative Valence System domain of RDoC to explore how racial trauma is informed by and can help expand our understanding of this domain. We end the review by providing some additional research considerations and future research directives in the area of racial trauma that build on the RDoC initiative.

AI ethics in computational psychiatry: From the neuroscience of consciousness to the ethics of consciousness

Methods used in artificial intelligence (AI) overlap with methods used in computational psychiatry (CP). Hence, considerations from AI ethics are also relevant to ethical discussions of CP. Ethical issues include, among others, fairness and data ownership and protection. Apart from this, morally relevant issues also include potential transformative effects of applications of AI—for instance, with respect to how we conceive of autonomy and privacy. Similarly, successful applications of CP may have transformative effects on how we categorise and classify mental disorders and mental health. Since many mental disorders go along with disturbed conscious experiences, it is desirable that successful applications of CP improve our understanding of disorders involving disruptions in conscious experience. Here, we discuss prospects and pitfalls of transformative effects that CP may have on our understanding of mental disorders. In particular, we examine the concern that even successful applications of CP may fail to take all aspects of disordered conscious experiences into account.

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Considerations from AI ethics are also relevant to the ethics of computational psychiatry.

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Ethical issues include, among others, fairness and data ownership and protection.

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They also include potential transformative effects.

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Computational psychiatry may transform conceptions of mental disorders and health.

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Disordered conscious experiences may pose a particular challenge.

Stress Disorders and the Risk of Nonfatal Suicide Attempts in the Danish Population

Accurate documentation of the associations between stress disorders and suicide attempts provides important information about a high-risk population and target group for preventative interventions. In this case-cohort study, cases were all individuals born or residing in Denmark who made a nonfatal suicide attempt during 1995-2015 (n = 22,974). The comparison subcohort included a 5% random sample of the Danish population on January 1, 1995 (n = 265,183). Stress disorder diagnoses and suicide attempts were identified using ICD-10 codes from national medical registries. The presence of any stress disorder substantially increased the rate of suicide attempts versus the comparison subcohort, rate per 100,000 person-years (PYs) = 604 vs. 13. We observed associations between each type of stress disorder and suicide attempts, hazard ratios (HRs) = 10.1-37.6, even after adjustment for potential confounders, adjusted HRs = 1.8-8.3, with the strongest associations for adjustment disorder relative to other diagnoses. After adjusting for demographic and health variables, the rate of suicide attempts among individuals with any stress disorder diagnosis was nearly 13 times the suicide attempt rate in the comparison cohort. A bias analysis demonstrated that associations remained robust despite potential differential misclassification of suicide attempts. Study strengths included the use of individual-level data linked across administrative and medical registries in the setting of universal health care and the use of longitudinal analyses capturing data over 20 years. The study demonstrated associations between the full range of stress disorders and suicide attempts, extending research specific to posttraumatic stress disorder.

Depression, Deprivation, and Dysbiosis: Polyiatrogenesis in Multiple Chronic Illnesses

Biomedicine tends to treat "mental" illnesses as if they could be isolated from multiple social and somatic problems. Yet mental suffering is inseparable from complex somatosocial relations. Clinical fieldwork in a deprived area of the UK shows that nearly all the people treated for "depression" are chronically multimorbid, both in their bodies and in their social relations. Mental suffering is co-produced by poverty, trauma, and excessive medication use. Patients' guts are as imbalanced as their moods. Single vertical treatments make them worse rather than better. In the UK, patients in poorer neighbourhoods do not "lack access" to healthcare. If anything, they suffer from taking too many medications with too little integration. I conceptualize the bad effects of excessive interventions in patients with multiple chronic problems as polyiatrogenesis.

The Etiologic, Theory-Based, Ontogenetic Hierarchical Framework of Alcohol Use Disorder: A Translational Systematic Review of Reviews

Modern nosologies (e.g., ICD-11, DSM-5) for alcohol use disorder (AUD) and dependence prioritize reliability and clinical presentation over etiology, resulting in a diagnosis that is not always strongly grounded in basic theory and research. Within these nosologies, DSM-5 AUD is treated as a discrete, largely categorical, but graded, phenomenon, which results in additional challenges (e.g., significant phenotypic heterogeneity). Efforts to increase the compatibility between AUD diagnosis and modern conceptualizations of alcohol dependence, which describe it as dimensional and partially overlapping with other psychopathology (e.g., other substance use disorders) will inspire a stronger scientific framework and strengthen AUD's validity. We conducted a systematic review of 144 reviews to integrate addiction constructs and theories into a comprehensive framework with the aim of identifying fundamental mechanisms implicated in AUD. The product of this effort was the Etiologic, Theory-Based, Ontogenetic Hierarchical Framework (ETOH Framework) of AUD mechanisms, which outlines superdomains of cognitive control, reward, as well as negative valence and emotionality, each of which subsume narrower, hierarchically-organized components. We also outline opponent processes and self-awareness as key moderators of AUD mechanisms. In contrast with other frameworks, we recommend an increased conceptual role for negative valence and compulsion in AUD. The ETOH framework serves as a critical step towards conceptualizations of AUD as dimensional and heterogeneous. It has the potential to improve AUD assessment and aid in the development of evidence-based diagnostic measures that focus on key mechanisms in AUD, consequently facilitating treatment matching.

Structure, Function, and Pharmacology of Glutamate Receptor Ion Channels

Many physiologic effects of l-glutamate, the major excitatory neurotransmitter in the mammalian central nervous system, are mediated via signaling by ionotropic glutamate receptors (iGluRs). These ligand-gated ion channels are critical to brain function and are centrally implicated in numerous psychiatric and neurologic disorders. There are different classes of iGluRs with a variety of receptor subtypes in each class that play distinct roles in neuronal functions. The diversity in iGluR subtypes, with their unique functional properties and physiologic roles, has motivated a large number of studies. Our understanding of receptor subtypes has advanced considerably since the first iGluR subunit gene was cloned in 1989, and the research focus has expanded to encompass facets of biology that have been recently discovered and to exploit experimental paradigms made possible by technological advances. Here, we review insights from more than 3 decades of iGluR studies with an emphasis on the progress that has occurred in the past decade. We cover structure, function, pharmacology, roles in neurophysiology, and therapeutic implications for all classes of receptors assembled from the subunits encoded by the 18 ionotropic glutamate receptor genes. SIGNIFICANCE STATEMENT: Glutamate receptors play important roles in virtually all aspects of brain function and are either involved in mediating some clinical features of neurological disease or represent a therapeutic target for treatment. Therefore, understanding the structure, function, and pharmacology of this class of receptors will advance our understanding of many aspects of brain function at molecular, cellular, and system levels and provide new opportunities to treat patients.

The cultural equivalence of measurement in substance use research

Across a wide range of substance use outcomes, ethnic/racial minorities in the U.S. experience a disproportionately higher burden of negative health outcomes and/or lower levels of access to care (relative to non-Latinx White individuals). Various explanations for these substance use-related health disparities have been proposed. This narrative review will not focus on the theoretical content of these explanations but will instead focus on the underlying statistical frameworks that are used to test such theories. Here, we provide a narrative review of psychometric critiques of cross-cultural research, which collectively suggest that (a) research testing similarities and differences among ethnic/racial groups often miss or omit to test statistical assumptions of equal instrument functioning across the ethnic/racial groups being compared; (b) testing the assumptions of equal instrument functioning is feasible using established guidelines from modern measurement theories; and (c) substance use research may need to explicitly incorporate the tests of equal instrument functioning to prevent bias when making inferences across ethnic/racial groups. We provide recommendations for evaluating the cultural equivalence of measurement using structural equation modeling, and advocate that cross-cultural substance use research move toward statistical approaches that are better positioned to test for (and model) bias in measurement. Explicitly testing the cultural equivalence of measurement when making inferences across cultural groups (within a falsifiable psychometric framework) can advance our understanding of similarities and differences among ethnic/racial groups, and hence can provide a more socially just (and statistically robust) scientific base. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

[Psychiatry without mind?]

Philosophy of Mind is currently one of the most prolific fields of research in philosophy and has witnessed a progressive hybridization with cognitive science. It focuses on fundamental questions to neuroscience and psychiatry, such as the nature of mental states and cognitive processes, or the relationships between mental states and the world. Anticipating the accumulation of experimental data from neuroscience, it provides a framework for the generation of theories in cognitive science. Philosophy of mind has thus laid the foundations of the conceptual space within which cognitive sciences have spread: a large part of contemporary theories in cognitive science result from a hybridization of conceptions forged by philosophers of mind and data produced by neuroscientists. Yet contemporary psychiatry is still reluctant to feed on the philosophy of mind, other than through the fragments that emerge from neuroscience. In this paper, we describe the evolution of contemporary philosophy of mind, and we detail its contributions around three central themes for psychiatry: naturalization of mind, mental causality, and subjectivity of mental states. We show how philosophy of mind provide the conceptual framework to link different levels of explanation in psychiatry: from biological to functional, from neurophysiology to cognition, from matter to mind.

[Introduction to the hierarchical taxonomy of psychopathology]

INTRODUCTION

In clinical practice, the usefulness of diagnosis based on the Diagnostic or Statistical Manual of Mental Disorders (DSM) or the International Classification of Diseases, 11th edition, appears essential from a clinical, research, epidemiological, administrative, economic and political level. However, such diagnostic systems have shortcomings in terms of validity, little consideration of comorbidities and strong intra-class heterogeneity. On a structural level, the operationalization of its criteria is based on a reliability which has been defined a posteriori and which does not lead to improving the validity of the diagnosis but rather to the reification of the diagnostic categories.

METHODS

First published in its current form in 2017, the Hierarchical Taxonomy of Psychopathology (HiTOP) constitutes a nosological alternative based on statistics. It conceptualizes psychopathology as a set of hierarchical dimensions, i.e. in "transdiagnostic" continua. The HiTOP is structured according to super-spectra, spectra, sub-factors, syndromes, components and symptoms. This comes from the current dimensional psychology and quantitative nosology. This article describes the basic principles of the HiTOP project and its potential to integrate into clinical and psychiatric research based on its advantages and limitations.

RESULTS

Unlike the DSM, which is descriptive and categorical, the HiTOP is first a dimensional classification. This dimensionality describes psychiatric phenomena on continua, each dimension providing a diagnostic continuum to situate a clinical patient. This dimensionality avoids the reification of categories and it limits the dichotomy between normal and pathological. In addition, HiTOP shows a hierarchical structure: vertical refinement of dimensions allows to circumvent the problem of comorbidities, proposes a new conception of etiopathogenic mechanisms, and improves management of care.

DISCUSSION

Thus, we provide an illustration of the applications of a dimensional and hierarchical classification in current clinical practice and scientific research, compared to traditional nosology. The challenges of the HiTOP arise in terms of validity, i.e. in the relation of dimensions with physiopathological mechanisms, in clinical terms, i.e. in the potential contribution of dimensions in relation to categories. Moreover, methodological challenges will be important given the inherent limitations of the HiTOP.

CONCLUSION

The HiTOP allows to examine the conceptualization of psychiatric disorders, the search for explanatory mechanisms, and treatment from another perspective for psychiatry.

Towards a contemporary approach for understanding personality pathology in developmental context: An integrative model

Traditional categorical approaches to classifying personality disorders are limited in important ways, leading to a shift in the field to dimensional approaches to conceptualizing personality pathology. Different areas of psychology – personality, developmental, and psychopathology – can be leveraged to understand personality pathology by examining its structure, development, and underlying mechanisms. However, an integrative model that encompasses these distinct lines of inquiry has not yet been proposed. In order to address this gap, we review the latest evidence for dimensional classification of personality disorders based on structural models of maladaptive personality traits, provide an overview of developmental theories of pathological personality, and summarize the Research Domain Criteria (RDoC) initiative, which seeks to understand underlying mechanisms of psychopathology. We conclude by proposing an integrative model of personality pathology development that aims to elucidate the developmental pathways of personality pathology and its underlying mechanisms.

Neurophysiological Responses to Interpersonal Emotional Images: Associations with Symptoms of Depression and Social Anxiety

Affective neuroscience research using electrocortical event-related potentials has provided valuable insights on alterations in emotion processing in internalizing disorders. However, internalizing disorders are accompanied by additional impairments in social cognition and functioning, and most extant research examines neural responses to broad categories of emotional scenes or faces presented irrespective of context. Examining neural reactivity specifically to interpersonal emotional scenes may more precisely capture and disentangle processes involved in depression and social anxiety, two highly comorbid forms of psychopathology. The current study validated a novel set of positive and threatening interpersonal emotional stimuli in a sample of emerging adults (N = 114) who completed a modified emotional interrupt paradigm while electroencephalogram and behavioral data were recorded. Participant ratings of valence and arousal supported the validity of the emotional images. Consistent with prior research, sustained neurophysiological processing indexed by the late positive potential (LPP) was observed for interpersonal emotional images, especially positive, compared with neutral images. Elevated LPP reactivity to both positive and threatening interpersonal images moderated the effects of chronic interpersonal stress on social anxiety symptoms, such that enhanced LPP reactivity in conjunction with higher levels of chronic interpersonal stress was associated with elevated social anxiety symptoms. These results were unique to social anxiety symptoms and not symptoms of depression, suggesting sustained neural processing of interpersonal stimuli may differentiate social anxiety from depression. Future research on emotional reactivity specifically within the interpersonal domain is needed to inform our understanding of developmental pathways to internalizing psychopathology.

An Answer to "So What?" Implications of Network Theory for Research and Practice

Research and practice in psychiatry and clinical psychology have been guided by differing schools of thought over the years. Recently, the network theory of psychopathology has arisen as a framework for thinking about mental health. Network theory challenges three common assumptions: psychological problems are caused by disease entities that exist independently of their signs and symptoms, classification and diagnosis of psychological problems should follow a medical model, and psychological problems are caused by diseases or aberrations in the brain. Conversely, network theory embraces other assumptions that are well accepted in clinical practice (e.g., the interaction of thoughts, behaviors, and emotions, as posited in cognitive-behavioral therapies) and integrates those assumptions into a coherent framework for research and practice. In this article, the authors review developments in network theory by focusing on anxiety-related conditions, discuss future areas for change, and outline implications of network theory for research and clinical practice.

All for one and one for all: heterogeneity of genetic etiologies in neurodevelopmental psychiatric disorders

Alexandre Dumas' famous phrase All for One and One for All recapitulates our current understanding of the genomic architecture of neurodevelopmental psychiatric disorders (NPD), like autism Spectrum disorder, bipolar disorder, and schizophrenia. Many rare genomic variants of large effect size have been identified; all of them together can explain a significant proportion of NPD. In parallel, one rare genomic variant can cause all of the above NPD. Finally, common genomic variants of individually small effect size can be combined to further explain risk for NPD. How do we reconcile different genomic variants accounting for one clinical diagnosis, and different clinical diagnoses arising from a single genomic variant? Here, we discuss a framework to understand genetic and clinical heterogeneity in NPD.

The C Factor: Cognitive dysfunction as a transdiagnostic dimension in psychopathology

Research into cognitive functions across psychological disorders suggests that cognitive deficiencies may be present across multiple disorders, potentially pointing to a transdiagnostic phenomenon. More recently, a single dimension model of psychopathology, the p factor, has been proposed, in which cognitive deficits are thought to be an intrinsic construct, assumed to be transdiagnostic. However, no systematic investigation to date tested this hypothesis. The aim of the present study was to systematically review meta-analyses to assess the hypothesis that the C factor (cognitive dysfunction) is transdiagnostic in psychopathology and review potential moderators that may account for such a phenomenon. We conducted a systematic review of meta-analyses examining cognitive function across all disorders for which data were available. Included meta-analyses (n = 82), comprising 97 clinical samples, yielded 1,055 effect sizes. Twelve major disorders/categories (e.g., bipolar disorder, substance use disorders) were included, comprising 29 distinct clinical entities (e.g., euthymic bipolar disorder; alcohol use disorder). Results show that all disorders reviewed are associated with underperformance across cognitive domains, supporting the hypothesis that the C factor (or cognitive dysfunction) is a transdiagnostic factor related to p. To examine moderators that may explain or contribute to c, we first consider important interpretative limitations of neuropsychological data in psychopathology. More crucially, we review oft-neglected motivational and emotional transdiagnostic constructs of p, as prominent contributing constructs to the C factor. These constructs are offered as a roadmap for future research examining these constructs related to p, that contribute, and may account for cognitive dysfunctions in psychopathology.

Investigating the stress-related fluctuations of level of personality functioning: A critical review and agenda for future research

The Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and the International Classification of Diseases (ICD-11) proposed a dimensional approach to the assessment of personality disorders (PDs). Both models dictate that the clinician first determines PD severity before assessing maladaptive traits, invoking the level of personality functioning (LPF) construct. We consider LPF a promising dimensional construct for translational research because of its clinical importance and conceptual overlap with the Research Domain Criteria (RDoC) Social Processes. We aim to identify biomarkers that co-vary with fluctuations in LPF in adulthood, ultimately to predict persistent decrease in LPF, associated with suicidality and morbidity. However, a theoretical framework to investigate stress-related oscillations in LPF is currently missing. In this article, we aim to fill this hiatus with a critical review about stress and LPF. First, we discuss acute stress and LPF. We briefly present the basics of the neurophysiological stress response and review the literature on momentary and daily fluctuations in LPF, both at a subjective and physiological level. Second, we review the effects of chronic stress on brain function and social behaviour and recapitulate the main findings from prospective cohort studies. This review underlies our suggestions for multimethod assessment of stress-related oscillations in LPF and our theoretical framework for future longitudinal studies, in particular studies using the experience sampling method (ESM).

Genetic Testing in Neurodevelopmental Disorders

Neurodevelopmental disorders are the most prevalent chronic medical conditions encountered in pediatric primary care. In addition to identifying appropriate descriptive diagnoses and guiding families to evidence-based treatments and supports, comprehensive care for individuals with neurodevelopmental disorders includes a search for an underlying etiologic diagnosis, primarily through a genetic evaluation. Identification of an underlying genetic etiology can inform prognosis, clarify recurrence risk, shape clinical management, and direct patients and families to condition-specific resources and supports. Here we review the utility of genetic testing in patients with neurodevelopmental disorders and describe the three major testing modalities and their yields - chromosomal microarray, exome sequencing (with/without copy number variant calling), and FMR1 CGG repeat analysis for fragile X syndrome. Given the diagnostic yield of genetic testing and the potential for clinical and personal utility, there is consensus that genetic testing should be offered to all patients with global developmental delay, intellectual disability, and/or autism spectrum disorder. Despite this recommendation, data suggest that a minority of children with autism spectrum disorder and intellectual disability have undergone genetic testing. To address this gap in care, we describe a structured but flexible approach to facilitate integration of genetic testing into clinical practice across pediatric specialties and discuss future considerations for genetic testing in neurodevelopmental disorders to prepare pediatric providers to care for patients with such diagnoses today and tomorrow.

The Hierarchical Taxonomy of Psychopathology (HiTOP): A Quantitative Nosology Based on Consensus of Evidence

Traditional diagnostic systems went beyond empirical evidence on the structure of mental health. Consequently, these diagnoses do not depict psychopathology accurately, and their validity in research and utility in clinicalpractice are therefore limited. The Hierarchical Taxonomy of Psychopathology (HiTOP) consortium proposed a model based on structural evidence. It addresses problems of diagnostic heterogeneity, comorbidity, and unreliability. We review the HiTOP model, supporting evidence, and conceptualization of psychopathology in this hierarchical dimensional framework. The system is not yet comprehensive, and we describe the processes for improving and expanding it. We summarize data on the ability of HiTOP to predict and explain etiology (genetic, environmental, and neurobiological), risk factors, outcomes, and treatment response. We describe progress in the development of HiTOP-based measures and in clinical implementation of the system. Finally, we review outstanding challenges and the research agenda. HiTOP is of practical utility already, and its ongoing development will produce a transformative map of psychopathology.

Developmental Perspectives on the Study of Persons with Intellectual Disability

Developmental approaches provide inclusive, universal, and methodologically rigorous frameworks for studying persons with intellectual disability (ID). This is an exceptionally heterogeneous group with regard to etiology, genotype, and phenotype that simply shares the traditional diagnostic criteria, typically a score of two standard deviations below the population mean of 100 on standardized IQ tests and deficits in adaptive behavior. We trace the foundational, conceptual, and methodological roots of developmental approaches and highlight ways that these and more recent iterations continue to be central to advances in the increasingly nuanced study of persons with ID. This work is premised on the consideration of specific etiological groupings and subgroupings across and between different domains of functioning within the context of familial and complex environments throughout the life span. We highlight the potential contributions of advances in behavioral methodologies, genomics, and neuroscience when considered within universal and hierarchic frameworks based on development.

Measuring diagnostic heterogeneity using text-mining of the lived experiences of patients

BACKGROUND

The diagnostic system is fundamental to any health discipline, including mental health, as it defines mental illness and helps inform possible treatment and prognosis. Thus, the procedure to estimate the reliability of such a system is of utmost importance. The current ways of measuring the reliability of the diagnostic system have limitations. In this study, we propose an alternative approach for verifying and measuring the reliability of the existing system.

METHODS

We perform Jaccard's similarity index analysis between first person accounts of patients with the same disorder (in this case Major Depressive Disorder) and between those who received a diagnosis of a different disorder (in this case Bulimia Nervosa) to demonstrate that narratives, when suitably processed, are a rich source of data for this purpose. We then analyse 228 narratives of lived experiences from patients with mental disorders, using Python code script, to demonstrate that patients with the same diagnosis have very different illness experiences.

RESULTS

The results demonstrate that narratives are a statistically viable data resource which can distinguish between patients who receive different diagnostic labels. However, the similarity coefficients between 99.98% of narrative pairs, including for those with similar diagnoses, are low (< 0.3), indicating diagnostic Heterogeneity.

CONCLUSIONS

The current study proposes an alternative approach to measuring diagnostic Heterogeneity of the categorical taxonomic systems (e.g. the Diagnostic and Statistical Manual, DSM). In doing so, we demonstrate the high Heterogeneity and limited reliability of the existing system using patients' written narratives of their illness experiences as the only data source. Potential applications of these outputs are discussed in the context of healthcare management and mental health research.

Behavioral and molecular effects of the antipsychotic drug blonanserin in the chronic mild stress model

Psychiatric disorders represent a critical challenge to our society, given their high global prevalence, complex symptomatology, elusive etiology and the variable effectiveness of pharmacological therapies. Recently, there has been a shift in investigating and redefining these diseases by integrating behavioral observations and multilevel neurobiological measures. Accordingly, endophenotype-oriented studies are needed to develop new therapeutic strategies, with the idea of targeting shared symptoms instead of one defined disease. With these premises, here we investigated the therapeutic properties of chronic treatment with the second-generation antipsychotic blonanserin in counteracting the alterations caused by 7 weeks of Chronic Mild Stress (CMS) in the rat. CMS is a well-established preclinical model able to induce depressive and anxiety-like alterations, which are shared by different psychiatric disorders. Our results demonstrated that the antipsychotic treatment normalizes the CMS-induced emotionality deficits, an effect that may be due to its ability in modulating, within the prefrontal cortex, redox mechanisms, a molecular dysfunction associated with several psychiatric disorders. These evidences provide new insights into the therapeutic properties and potential use of blonanserin as well as in its mechanisms of action and provide further support for the role of oxidative stress in the pathophysiology of psychiatric disorders.

Präzisionspsychiatrie und der Beitrag von Brain Imaging und anderen Biomarkern

'Precision Psychiatry' as the psychiatric variant of 'Precision Medicine' aims to provide high-level diagnosis and treatment based on robust biomarkers and tailored to the individual clinical, neurobiological, and genetic constitution of the patient. The specific peculiarity of psychiatry, in which disease entities are normatively defined based on clinical experience and are also significantly influenced by contemporary history, society and philosophy, has so far made the search for valid and reliable psychobiological connections difficult. Nevertheless, considerable progress has now been made in all areas of psychiatric research, made possible above all by the critical review and renewal of previous concepts of disease and psychopathology, the increased orientation towards neurobiology and genetics, and in particular the use of machine learning methods. Notably, modern machine learning methods make it possible to integrate high-dimensional and multimodal data sets and generate models which provide new psychobiological insights and offer the possibility of individualized, biomarker-driven single-subject prediction of diagnosis, therapy response and prognosis. The aim of the present review is therefore to introduce the concept of 'Precision Psychiatry' to the interested reader, to concisely present modern, machine learning methods required for this, and to clearly present the current state and future of biomarker-based 'precision psychiatry'.