From Many to One to Many-the Search for Causes of Psychiatric Illness

Improving treatments for mental disorders using computational models

Progress in the treatment of psychopathology has slowed and much remains unknown about how treatments achieve their beneficial effects. We propose that computational models can be used to provide new insights into how treatments may work and how they may be improved. We argue that treatments can be understood as interventions on systems of interacting components, and that computational models are needed if we are to accurately and precisely determine the effect an intervention will have on this system. We demonstrate this approach by using a computational model of panic disorder to conduct an in silico dismantling study of cognitive behavioral therapy. This simulated trial allows us to: identify a common source of treatment failure; propose a revised treatment protocol that mitigates this source of failure; and demonstrate that, if the model is accurate, this revised protocol will lead to improved treatment outcomes for 10% of patients. We conclude with a discussion of the promise and challenges of using computational models for treatment research.

Randomized Double Blind Inpatient Study of a Gluten-Free Diet in Persons with Schizophrenia

Background

Schizophrenia and related disorders (SRD) are characterized by positive and negative symptoms, such as anhedonia and avolition. There are no current FDA approved treatments for negative symptoms, which is a critical gap in our treatment of people with SRDs, since they are a major determinant of functional impairment. An emerging literature suggests that SRDs have a relationship with immune function and inflammation. Recently an SRD subgroup with high inflammation and elevated levels of anti-gliadin antibodies (AGA) of immunoglobulin G type (IgG) has been characterized. Negative symptom improvement has been previously observed with gluten removal in this subgroup in two small clinical trials.

Methods

We conducted a 5-week confirmatory double-blind placebo-controlled trial of a gluten free diet (GFD) versus gluten-containing diet (GCD) for negative symptoms in people with SRD who have elevated AGA IgG (NCT03183609). Participants were between the ages of 18-64 years, had baseline negative symptoms and a diagnosis of schizophrenia or schizoaffective disorder. Those included were screened for an AGA IgG >20 U, no serologic evidence of celiac disease, and stable antipsychotic treatment and dose. All participants were inpatients, received a GFD and were randomized to 30 grams of gluten or rice flour daily delivered in protein shakes. The Clinical Assessment Interview for Negative Symptoms (CAINS) Motivation and Pleasure (MAP) scale was the primary outcome measure. We also examined the CAINS Expressivity (EXP) scale, the Scale for the Assessment of Negative Symptoms (SANS), the Brief Psychiatric Rating Scale (BPRS), the MATRICS Consensus Cognitive Battery (MCCB) and conducted regular side effect screening and laboratory measures for safety.

Findings

Between 2018 and 2024, we included 39 participants (N=21 GFD and N=18 GCD). There was a significant improvement over time in the CAINS MAP (treatment X time df=30.1, F=2.78, p=0.045) in the GFD compared to GCD, but no significant change in the CAINS EXP, the SANS, BPRS or MCCB. The diet was well tolerated; the most frequently occurring side effects were constipation (38.1% GFD, 33.3% GCD), sedation (33.3% GFD, 50% GCD), dry mouth (33.3% GFD, 33.3% GCD), headache (33.3% GFD, 27.8% GCD), and insomnia (33.3% GFD, 27.8% GCD).

Interpretation

This is the first large scale double-blind randomized clinical trial in SRD with AGA IgG+. This replication of smaller studies suggests that negative symptoms, particularly anhedonia and avolition may be improved. However, we did not replicate our previous finding of cognitive improvement and COVID-19 likely impacted the extent of improvement in negative symptoms due to quarantines and lockdowns. More work is needed to determine the mechanism of action of gluten removal in this subgroup with hopes of developing new treatment targets for motivational deficits of this illness.

Funding

This project was funded by NIMH R01 R01MH113617 (DL Kelly PI).

Reward-Related Brain Activity Mediates the Relationship Between Decision-Making Deficits and Pediatric Depression Symptom Severity

BACKGROUND

The mechanisms that link neural and behavioral indices of reduced reward sensitivity in depression, particularly in children, remain unclear. Reward positivity (RewP), a neural index of reward processing, has been consistently associated with depression. Separately, recent studies using the drift-diffusion model on behavioral data have delineated computational indices of reward sensitivity. Therefore, in the current study, we examined whether RewP is a neural mediator of drift-diffusion model-based indices of reward processing in predicting pediatric depression across varying levels of symptom severity.

METHODS

A community sample of 166 girls, ages 8 to 14 years, completed 2 tasks. The first was a reward guessing task from which RewP was computed using electroencephalography; the second was a probabilistic reward-based decision-making task. On this second task, drift-diffusion model analysis was applied to behavioral data to quantify the efficiency of accumulating reward-related evidence (drift rate) and potential baseline bias (starting point) toward the differently rewarded choices. Depression severity was measured using the self-report Children's Depression Inventory.

RESULTS

RewP was correlated with drift rate, but not starting point bias, toward the more rewarded choice. Furthermore, RewP completely mediated the association between a slower drift rate toward the more rewarded option and higher depression symptom severity.

CONCLUSIONS

Our findings suggest that reduced neural sensitivity to reward feedback may be a neural mechanism that underlies behavioral insensitivity to reward in children and adolescents with higher depression symptom severity, offering novel insights into the relationship between neural and computational indices of reward processing in this context.

Reducing maladaptive behavior in neuropsychiatric disorders using network modification

Neuropsychiatric disorders are caused by many factors and produce a wide range of symptomatic maladaptive behaviors in patients. Despite this great variance in causes and resulting behavior, we believe the maladaptive behaviors that characterize neuropsychiatric disorders are most proximally determined by networks of neurons and that this forms a common conceptual link between these disorders. Operating from this premise, it follows that treating neuropsychiatric disorders to reduce maladaptive behavior can be accomplished by modifying the patient's network of neurons. In this proof-of-concept computational psychiatry study, we tested this approach in a simple model organism that is controlled by a neural network and that exhibits aversion-resistant alcohol drinking - a key maladaptive behavior associated with alcohol use disorder. We demonstrated that it was possible to predict personalized network modifications that substantially reduced maladaptive behavior without inducing side effects. Furthermore, we found that it was possible to predict effective treatments with limited knowledge of the model and that information about neural activity during certain types of trials was more helpful in predicting treatment than information about model parameters. We hypothesize that this is a general feature of developing effective treatment strategies for networks of neurons. This computational study lays the groundwork for future studies utilizing more biologically realistic network models in conjunction with in vivo data.

Systems modelling and simulation to guide targeted investments to reduce youth suicide and mental health problems in a low-middle-income country

BACKGROUND

Despite suicide's public health significance and global mental health awareness, current suicide prevention efforts show limited impact, posing a challenge for low- and middle-income countries. This study aimed to develop a dynamic simulation model that could be used to examine the potential effectiveness of alternative interventions for reducing youth mental health problems and suicidal behavior in Bogotá, Colombia.

METHODS

A system dynamics model was designed using a participatory approach involving three workshops conducted in 2021 and 2022. These workshops engaged 78 stakeholders from various health and social sectors to map key mental health outcomes and influential factors affecting them. A model was subsequently developed, tested, and presented to the participants for interactive feedback, guided by a moderator. Simulation analyses were conducted to compare projected mental health outcomes for a range of intervention scenarios with projections for a reference scenario corresponding to business-as-usual.

RESULTS

A total of 6670 suicide attempts and 347 suicides are projected among 7 - 17-year-olds from January 1, 2023, to early 2031 under the business-as-usual scenario. Mental health issues among 12 - 17-year-olds are projected to increase from 18.9% (2023) to 27.8% (2031), and substance use issues from 2.29 to 2.49% over the same period. School-based suicide prevention and gatekeeper training are the most effective strategies, reducing total numbers of suicide attempts and suicides by more than 20% (i.e., compared to business-as-usual). However, discontinuous funding significantly hinders these effective suicide prevention efforts.

CONCLUSIONS

Systems modelling is an important tool for understanding where the best strategic financial and political investments lie for improving youth mental health in resource-constrained settings.

Intergenerational transmission of psychopathology across three generations: the role of social support

Psychopathology runs in families and affects functioning of individuals and their family members. This study assessed the intergenerational transmission of psychopathology risk across three generations, and the extent to which social support factors may protect against this transmission from parents to their offspring. This study was embedded in Generation R, a multi-ethnic population-based cohort from fetal life onwards. Lifetime psychiatric disorders of grandparents were assessed with the Family Informant Schedule Criteria- updated for DSM-IV. Parental psychopathology was repeatedly measured by the Brief Symptom Inventory. Offspring psychopathology (ages 10 and 14) was assessed with the Brief Problem Monitor. Maternal and child social factors were assessed using questionnaire measures and a computerized peer nomination assessment. Our results show that the estimated additive interaction effect for the risk transmission of grandparental and pre- and postnatal parental psychopathology to offspring psychopathology was 23% (95% CI 19; 27). The joint effect of grandparental and parental psychopathology combined with maternal and child social support factors was 13% (95% CI 08; 17)], suggesting that social support factors diminished the intergenerational transmission of psychopathology from (grand)parents (G1 and G2) to offspring (G3). Transmission of psychopathology risk may have long-lasting developmental effects across generations. Social support factors reduced the vulnerability to the effects of psychopathology risk, underscoring the importance of the identification of buffering factors associated with good mental health in adolescents who are at high familial risk.

The Development of Non-affective Psychotic Syndromes in the 19th Century: LeGrand du Saulle and His 1871 Monograph "Le Délire De Persécutions" (Persecutory Delusions)

While the origins of two of Kraepelin's three subtypes of dementia praecox (DP), catatonic and hebephrenic, are well understood, no similar clear narrative exists for his concepts of paranoia and paranoid DP, which require a consideration of both German and French sources. An important milestone in the French literature is the massive 524 page monograph entitled "Le Délire Des Persécutions" published in 1871 by Henri Legrand du Saulle which contained extensive, clinically detailed descriptions of a wide range of cases with prominent, organized persecutory delusions. Many of his cases reported auditory hallucinations (AH), and some bizarre, Schneiderian delusions. The delusional content could evolve to include prominent somatic and/or grandiose themes. Using a symptomatic diagnostic framework, Legrand du Saulle proposed that this syndrome represented an independent "species" of mental illness. He sought to give a voice to the affected individuals, including a chapter devoted entirely to their writings. He described several clinically fascinating features of such patients including how often they moved residence to unsuccessfully flee their persecutors and how delusional beliefs could be communicated to spouses and relatives. Unlike Kraepelin, he was little interested in their course of illness or rates of deterioration, except to note that recoveries occurred in 20% of cases. The clinical richness of this work substantially exceeded that in the contemporaneous German literature. Most of the cases described by du Saulle would fit easily into the two major non-affective delusional syndromes articulated 28 years later in Kraepelin's famous 6th edition of his textbook: paranoia and paranoid DP.

Common Cause Versus Dynamic Mutualism: An Empirical Comparison of Two Theories of Psychopathology in Two Large Longitudinal Cohorts

Mental disorders are among the leading causes of global disease burden. To respond effectively, a strong understanding of the structure of psychopathology is critical. We empirically compared two competing frameworks, dynamic-mutualism theory and common-cause theory, that vie to explain the development of psychopathology. We formalized these theories in statistical models and applied them to explain change in the general factor of psychopathology (p factor) from early to late adolescence (N = 1,482) and major depression in middle adulthood and old age (N = 6,443). Change in the p factor was better explained by mutualism according to model-fit indices. However, a core prediction of mutualism was not supported (i.e., predominantly positive causal interactions among distinct domains). The evidence for change in depression was more ambiguous. Our results support a multicausal approach to understanding psychopathology and showcase the value of translating theories into testable statistical models for understanding developmental processes in clinical sciences.

Reexamining "psychosocial clearance": A procedural framework for psychosocial evaluation in liver transplantation

Psychosocial and "nonmedical" phenomena are commonly encountered in liver transplantation (LT) evaluations. They are simultaneously crucial decision-making factors and some of the most difficult and controversial clinical matters clinicians confront. Epidemiology, societal trends, and the preponderance of psychological and behavioral factors underpinning common end-stage liver diseases ensure that LT teams will continue to encounter highly complex psychosocial patient presentations. Psychosocial policies, practices, and opinions vary widely among clinicians and LT centers. Liver clinicians already report insufficient psychosocial expertise, which creates a large gap between the stark need for psychosocial expansion, improvement, and innovation in LT and the lack of accompanying guidance on how to achieve it. While the clinical domains of an LT psychosocial evaluation have been well-described, few articles analyze the procedures by which teams determine candidates' "psychosocial clearance" and no conceptual frameworks exist. This article proposes a framework of core domains of psychosocial evaluation procedures, common pitfalls, and practical improvement strategies.

Transdiagnostic symptom of depression and anxiety associated with reduced gray matter volume in prefrontal cortex

Dimensional models of psychopathology may provide insight into mechanisms underlying comorbid depression and anxiety and improve specificity and sensitivity of neuroanatomical findings. The present study is the first to examine neural structure alterations using the empirically derived Tri-level Model. Depression and anxiety symptoms of 269 young adults were assessed using the Tri-level Model dimensions: General Distress (transdiagnostic depression and anxiety symptoms), Anhedonia-Apprehension (relatively specific depression symptoms), and Fears (specific anxiety symptoms). Using structural MRI, gray matter volumes were extracted for emotion generation (amygdala, nucleus accumbens) and regulation (orbitofrontal, ventrolateral, and dorsolateral prefrontal cortex) regions, often implicated in depression and anxiety. Each Tri-level symptom was regressed onto each region of interest, separately, adjusting for relevant covariates. General Distress was significantly associated with smaller gray matter volumes in bilateral orbitofrontal cortex and ventrolateral prefrontal cortex, independent of Anhedonia-Apprehension and Fears symptom dimensions. These results suggests that prefrontal alterations are associated with transdiagnostic dysphoric mood common across depression and anxiety, rather than unique symptoms of these disorders. Additionally, no regions of interest were associated with Anhedonia-Apprehension or Fears, highlighting the importance of studying transdiagnostic features of depression and anxiety. This has implications for understanding mechanisms of and interventions for depression and anxiety.

Neuromelanin-sensitive magnetic resonance imaging in the study of mental disorder: A systematic review

Dopamine and norepinephrine are implicated in the pathophysiology of mental disorders, but non-invasive study of their neuronal function remains challenging. Recent research suggests that neuromelanin-sensitive magnetic resonance imaging (NM-MRI) techniques may overcome this limitation by enabling the non-invasive imaging of the substantia nigra (SN)/ ventral tegmental area (VTA) dopaminergic and locus coeruleus (LC) noradrenergic systems. A review of 19 studies that met the criteria for NM-MRI application in mental disorders found that despite the use of heterogeneous sequence parameters and metrics, nearly all studies reported differences in contrast ratio (CNR) of LC or SN/VTA between patients with mental disorders and healthy controls. These findings suggest that NM-MRI is a valuable tool in psychiatry, but the differences in sequence parameters across studies hinder comparability, and a standardized analysis pipeline is needed to improve the reliability of results. Further research using standardized methods is needed to better understand the role of dopamine and norepinephrine in mental disorders.

Targeted Treatment of Schizophrenia Symptoms as They Manifest, or Continuous Treatment to Reduce the Risk of Psychosis Recurrence

Current pharmacological treatment of schizophrenia employs drugs that interfere with dopamine neurotransmission, aiming to suppress acute exacerbation of psychosis and maintenance treatment to reduce the risk of psychosis recurrence. According to this treatment scheme, available psychotropic drugs intended to treat negative symptoms, cognitive impairment, or anxiety are administered as add-ons to treatment with antipsychotics. However, an alternative treatment scheme proposes a targeted or intermittent treatment approach, by which antipsychotic drugs are administered upon psychosis exacerbation and discontinued upon remission or stabilization, while negative symptoms, cognitive impairment, or anxiety are treated with specific psychotropics as monotherapy. Along these lines, antipsychotics are renewed only in the event of recurrence of psychotic symptoms. This 50-year-old debate between targeted and continuous treatment schemes arises from disagreements about interpreting scientific evidence and discordant views regarding benefit/risk assessment. Among the debate's questions are: (1) what is the percentage of individuals who can maintain stability without antipsychotic maintenance treatment, and what is the percentage of those who exacerbate despite antipsychotic treatment? (2) how to interpret results of placebo-controlled 9- to 18-month-long maintenance trials in a life-long chronic disorder, and how to interpret results of the targeted trials, some of which are open label or not randomized; (3) how to weigh the decreased risk for psychotic recurrence vs the almost certainty of adverse effects on patient's quality of life. Patients' profiles, preferences, and circumstances of the care provision should be considered as the targeted vs continuous treatment options are considered.

The general psychopathology factor (p) from adolescence to adulthood: Exploring the developmental trajectories of p using a multi-method approach

Considerable attention has been directed towards studying co-occurring psychopathology through the lens of a general factor (p-factor). However, the developmental trajectory and stability of the p-factor have yet to be fully understood. The present study examined the explanatory power of dynamic mutualism theory - an alternative framework that suggests the p-factor is a product of lower-level symptom interactions that strengthen throughout development. Data were drawn from a population-based sample of girls (N = 2450) who reported on the severity of internalizing and externalizing problems each year from age 14 to age 21. Predictions of dynamic mutualism were tested using three distinct complementary statistical approaches including: longitudinal bifactor models, random-intercept cross-lagged panel models (RI-CLPMs), and network models. Across methods, study results document preliminary support for mutualistic processes in the development of co-occurring psychopathology (that is captured in p). Findings emphasize the importance of exploring alternative frameworks and methods for better understanding the p-factor and its development.

Irremediability in psychiatric euthanasia: examining the objective standard

BACKGROUND

Irremediability is a key requirement for euthanasia and assisted suicide for psychiatric disorders (psychiatric EAS). Countries like the Netherlands and Belgium ask clinicians to assess irremediability in light of the patient's diagnosis and prognosis and 'according to current medical understanding'. Clarifying the relevance of a default objective standard for irremediability when applied to psychiatric EAS is crucial for solid policymaking. Yet so far, a thorough examination of this standard is lacking.

METHODS

Using treatment-resistant depression (TRD) as a test case, through a scoping review in PubMed, we analyzed the state-of-the-art evidence for whether clinicians can accurately predict individual long-term outcome and single out irremediable cases, by examining the following questions: (1) What is the definition of TRD; (2) What are group-level long-term outcomes of TRD; and (3) Can clinicians make accurate individual outcome predictions in TRD?

RESULTS

A uniform definition of TRD is lacking, with over 150 existing definitions, mostly focused on psychopharmacological research. Available yet limited studies about long-term outcomes indicate that a majority of patients with long-term TRD show significant improvement over time. Finally, evidence about individual predictions in TRD using precision medicine is growing, but methodological shortcomings and varying predictive accuracies pose important challenges for its implementation in clinical practice.

CONCLUSION

Our findings support the claim that, as per available evidence, clinicians cannot accurately predict long-term chances of recovery in a particular patient with TRD. This means that the objective standard for irremediability cannot be met, with implications for policy and practice of psychiatric EAS.

Major depressive disorder

Major depressive disorder (MDD) is characterized by persistent depressed mood, loss of interest or pleasure in previously enjoyable activities, recurrent thoughts of death, and physical and cognitive symptoms. People with MDD can have reduced quality of life owing to the disorder itself as well as related medical comorbidities, social factors, and impaired functional outcomes. MDD is a complex disorder that cannot be fully explained by any one single established biological or environmental pathway. Instead, MDD seems to be caused by a combination of genetic, environmental, psychological and biological factors. Treatment for MDD commonly involves pharmacological therapy with antidepressant medications, psychotherapy or a combination of both. In people with severe and/or treatment-resistant MDD, other biological therapies, such as electroconvulsive therapy, may also be offered.

Transforming mental health systems globally: principles and policy recommendations

A burgeoning mental health crisis is emerging globally, regardless of each country's human resources or spending. We argue that effectively responding to this crisis is impeded by the dominant framing of mental ill health through the prism of diagnostic categories, leading to an excessive reliance on interventions that are delivered by specialists; a scarcity of widespread promotive, preventive, and recovery-oriented strategies; and failure to leverage diverse resources within communities. Drawing upon a series of syntheses, we identify five principles to transform current practices; namely, address harmful social environments across the life course, particularly in the early years; ensure that care is not contingent on a categorical diagnosis but aligned with the staging model of mental illness; empower diverse front-line providers to deliver psychosocial interventions; embrace a rights-based approach that seeks to provide alternatives to violence and coercion in care; and centre people with lived experience in all aspects of care. We recommend four policy actions which can transform these principles into reality: a whole of society approach to prevention and care; a redesign of the architecture of care delivery to provide a seamless continuum of care, tailored to the severity of the mental health condition; investing more in what works to enhance the impact and value of the investments; and ensuring accountability through monitoring and acting upon a set of mental health indicators. All these actions are achievable, relying-for the most part-on resources already available to every community and country. What they do require is the acceptance that business as usual will fail and the solutions to transforming mental health-care systems are already present within existing resources.

The genetic basis of major depressive disorder

The genetic dissection of major depressive disorder (MDD) ranks as one of the success stories of psychiatric genetics, with genome-wide association studies (GWAS) identifying 178 genetic risk loci and proposing more than 200 candidate genes. However, the GWAS results derive from the analysis of cohorts in which most cases are diagnosed by minimal phenotyping, a method that has low specificity. I review data indicating that there is a large genetic component unique to MDD that remains inaccessible to minimal phenotyping strategies and that the majority of genetic risk loci identified with minimal phenotyping approaches are unlikely to be MDD risk loci. I show that inventive uses of biobank data, novel imputation methods, combined with more interviewer diagnosed cases, can identify loci that contribute to the episodic severe shifts of mood, and neurovegetative and cognitive changes that are central to MDD. Furthermore, new theories about the nature and causes of MDD, drawing upon advances in neuroscience and psychology, can provide handles on how best to interpret and exploit genetic mapping results.

Genesis, modelling and methodological remedies to autism heterogeneity

Diagnostic criteria used in autism research have undergone a shift towards the inclusion of a larger population, paralleled by increasing, but variable, estimates of autism prevalence across clinical settings and continents. A categorical diagnosis of autism spectrum disorder is now consistent with large variations in language, intelligence, comorbidity, and severity, leading to a heterogeneous sample of individuals, increasingly distant from the initial prototypical descriptions. We review the history of autism diagnosis and subtyping, and the evidence of heterogeneity in autism at the cognitive, neurological, and genetic levels. We describe two strategies to address the problem of heterogeneity: clustering, and truncated-compartmentalized enrollment strategy based on prototype recognition. The advances made using clustering methods have been modest. We present an alternative, new strategy for dissecting autism heterogeneity, emphasizing incorporation of prototypical samples in research cohorts, comparison of subgroups defined by specific ranges of values for the clinical specifiers, and retesting the generality of neurobiological results considered to be acquired from the entire autism spectrum on prototypical cohorts defined by narrow specifiers values.

Diagnosis and management of bipolar disorders

Bipolar disorders (BDs) are recurrent and sometimes chronic disorders of mood that affect around 2% of the world's population and encompass a spectrum between severe elevated and excitable mood states (mania) to the dysphoria, low energy, and despondency of depressive episodes. The illness commonly starts in young adults and is a leading cause of disability and premature mortality. The clinical manifestations of bipolar disorder can be markedly varied between and within individuals across their lifespan. Early diagnosis is challenging and misdiagnoses are frequent, potentially resulting in missed early intervention and increasing the risk of iatrogenic harm. Over 15 approved treatments exist for the various phases of bipolar disorder, but outcomes are often suboptimal owing to insufficient efficacy, side effects, or lack of availability. Lithium, the first approved treatment for bipolar disorder, continues to be the most effective drug overall, although full remission is only seen in a subset of patients. Newer atypical antipsychotics are increasingly being found to be effective in the treatment of bipolar depression; however, their long term tolerability and safety are uncertain. For many with bipolar disorder, combination therapy and adjunctive psychotherapy might be necessary to treat symptoms across different phases of illness. Several classes of medications exist for treating bipolar disorder but predicting which medication is likely to be most effective or tolerable is not yet possible. As pathophysiological insights into the causes of bipolar disorders are revealed, a new era of targeted treatments aimed at causal mechanisms, be they pharmacological or psychosocial, will hopefully be developed. For the time being, however, clinical judgment, shared decision making, and empirical follow-up remain essential elements of clinical care. This review provides an overview of the clinical features, diagnostic subtypes, and major treatment modalities available to treat people with bipolar disorder, highlighting recent advances and ongoing therapeutic challenges.

Examining the shared etiology of psychopathology with genome-wide association studies

Genome-wide association studies (GWASs) have ushered in a new era of reproducible discovery in psychiatric genetics. The field has now identified hundreds of common genetic variants that are associated with mental disorders, and many of them influence more than one disorder. By advancing the understanding of causal biology underlying psychopathology, GWAS results are poised to inform the development of novel therapeutics, stratification of at-risk patients, and perhaps even the revision of top-down classification systems in psychiatry. Here, we provide a concise review of GWAS findings with an emphasis on findings that have elucidated the shared genetic etiology of psychopathology, summarizing insights at three levels of analysis: 1) genome-wide architecture; 2) networks, pathways, and gene sets; and 3) individual variants/genes. Three themes emerge from these efforts. First, all psychiatric phenotypes are heritable, highly polygenic, and influenced by many pleiotropic variants with incomplete penetrance. Second, GWAS results highlight the broad etiological roles of neuronal biology, system-wide effects over localized effects, and early neurodevelopment as a critical period. Third, many loci that are robustly associated with multiple forms of psychopathology harbor genes that are involved in synaptic structure and function. Finally, we conclude our review by discussing the implications that GWAS results hold for the field of psychiatry, as well as expected challenges and future directions in the next stage of psychiatric genetics.

Psychological and contextual risk factors for first-onset depression among adolescents and young people around the globe: A systematic review and meta-analysis

AIM

Identifying predictors for future onset of depression is crucial to effectively developing preventive interventions. We conducted a systematic review and meta-analysis to identify risk factors for first-onset depression among adolescents and young people.

METHODS

We searched MEDLINE (Ovid), PsycINFO, Cochrane Database, Web of Science, Lilacs, African Journals Online and Global Health (July 2009 to December 2020) for longitudinal studies assessing risk factors for first-onset depression among adolescents and young people aged 10-25 years. Meta-analyses generated summary odds ratio (OR) estimates.

REGISTRATION

PROSPERO CRD42018103973.

RESULTS

Nineteen studies representing 21 unique populations were included in the meta-analysis. Among studies reporting race/ethnicity, 79% of participants were of White/European descent. Seventeen studies were from high-income countries, with only two from an upper-middle-income country (China). Odds for first-onset depression were significantly greater for girls compared to boys (n = 13; OR = 1.78 [1.78, 2.28], p < 0.001) and for youth with other mental health problems at baseline (n = 4; OR = 3.20 [1.95, 5.23], p < 0.001). There were non-significant associations for negative family environment (n = 8; OR = 1.60 [0.82, 3.10], p = 0.16) and parental depression (n = 3; OR = 2.30 [0.73, 7.24], p = 0.16).

CONCLUSIONS

Most longitudinal studies do not report risk factors specifically for first-onset depression. Moreover, predictive data are limited to predominantly White populations in high-income countries. Future research must be more ethnically and geographically representative. Recommendations are provided for consistent and comprehensive reporting of study designs and analyses of risk factors for first-onset depression.

Mental health progress requires causal diagnostic nosology and scalable causal discovery

Nine hundred and seventy million individuals across the globe are estimated to carry the burden of a mental disorder. Limited progress has been achieved in alleviating this burden over decades of effort, compared to progress achieved for many other medical disorders. Progress on outcome improvement for all medical disorders, including mental disorders, requires research capable of discovering causality at sufficient scale and speed, and a diagnostic nosology capable of encoding the causal knowledge that is discovered. Accordingly, the field's guiding paradigm limits progress by maintaining: (a) a diagnostic nosology (DSM-5) with a profound lack of causality; (b) a misalignment between mental health etiologic research and nosology; (c) an over-reliance on clinical trials beyond their capabilities; and (d) a limited adoption of newer methods capable of discovering the complex etiology of mental disorders. We detail feasible directions forward, to achieve greater levels of progress on improving outcomes for mental disorders, by: (a) the discovery of knowledge on the complex etiology of mental disorders with application of Causal Data Science methods; and (b) the encoding of the etiological knowledge that is discovered within a causal diagnostic system for mental disorders.

Disentangling the impact of childhood abuse and neglect on depressive affect in adulthood: A machine learning approach in a general population sample

BACKGROUND

Different types of childhood maltreatment (CM) are key risk factors for psychopathology. Specifically, there is evidence for a unique role of emotional abuse in affective psychopathology in children and youth; however, its predictive power for depressive symptomatology in adulthood is still unknown. Additionally, emotional abuse encompasses several facets, but the strength of their individual contribution to depressive affect has not been examined.

METHOD

Here, we used a machine learning (ML) approach based on Random Forests to assess the performance of domain scores and individual items from the Childhood Trauma Questionnaire (CTQ) in predicting self-reported levels of depressive affect in an adult general population sample. Models were generated in a training sample (N = 769) and validated in an independent test sample (N = 466). Using state-of-the-art methods from interpretable ML, we identified the most predictive domains and facets of CM for adult depressive affect.

RESULTS

Models based on individual CM items explained more variance in the independent test sample than models based on CM domain scores (R² = 7.6 % vs. 6.4 %). Emotional abuse, particularly its more subjective components such as reactions to and appraisal of the abuse, emerged as the strongest predictors of adult depressive affect.

LIMITATIONS

Assessment of CM was retrospective and lacked information on timing and duration. Moreover, reported rates of CM and depressive affect were comparatively low.

CONCLUSIONS

Our findings corroborate the strong role of subjective experience in CM-related psychopathology across the lifespan that necessitates greater attention in research, policy, and clinical practice.

Youth depression and inflammation: Cross-sectional network analyses of C-Reactive protein, interleukin-6 and symptoms in a population-based sample

BACKGROUND

Inflammation-related proteins constitute a promising avenue in studying biological correlates of major depressive disorder (MDD). However, MDD is a heterogeneous condition - a crucial aspect to be considered in association studies. We examined whether inflammatory proteins are associated with categorical diagnosis, a dimensional total sum-score, and specific depressive symptoms among youths.

METHODS

We analyzed data from the 1993 Pelotas Birth Cohort, a population-based study in Brazil that followed individuals up to age 22 years. Categorical psychiatric diagnoses were derived using adapted modules of the Mini International Neuropsychiatric Interview (MINI). Dimensional symptomatology was assessed using the Brazilian Portuguese version of the Center for Epidemiological Studies-Depression Scale-Revised (CESD-R). We estimated network structures that included individual depressive symptoms as measured by CESD-R items, peripheral inflammatory markers (C-Reactive Protein [CRP] and Interleukin-6 [IL-6]), as well as relevant covariates.

RESULTS

We evaluated 2586 participants (mean age = 22.5[SD = 0.33]) There were no associations between concentrations of inflammatory proteins and categorical diagnosis of MDD or with CESD-R total sum-scores. In symptom-specific analysis, CRP and IL-6 were positively connected to somatic and cognitive items.

DISCUSSION

We found cross-sectional connections of two commonly studied inflammatory proteins and specific depressive symptoms. Conducting symptom-specific analyses in relation to biological markers might advance our understanding of the heterogeneity of MDD.

Expanding the system: A brief psychosocial complex systems model of internalising disorder

BACKGROUND

The aetiology of internalising disorders remains poorly understood. Recently, a bottom-up network perspective has suggested mental disorders are best conceptualised as emergent systems, and may be explained by mapping systems of symptoms embedded within a complex biopsychosocial environment. Under this framework, the complex system in which internalising disorders are embedded remains poorly understood. The present research outlines a brief psychosocial system of internalising disorders as a basis for future research.

METHODS

A Mixed Graphical Model was fitted on 15 psychosocial variables (including depression and anxiety) collected during the Christchurch Health and Development Study, a representative population birth cohort of 1265 people born in 1977 in Christchurch, New Zealand.

RESULTS

The model demonstrates that psychosocial risk factors for internalising disorders tend to be inter-related. The psychosocial system accounted for 19.9% of the variance in the diagnostic depression variable, and 5.0% of the variance in diagnostic anxiety. Most variables (10/13) were associated with depression and anxiety either directly or indirectly.

LIMITATIONS

First, the estimated model is undirected, so causal directions are unspecified except for longitudinal relationships. Second, binary diagnostic variables were used for depression and anxiety, meaning the model does include symptom-level complexity. Third, the model does not account for within-person effects.

CONCLUSIONS

This exploratory model may serve as a basis for the mapping of greater (bio) psychosocial complexity around internalising disorders. The model concisely demonstrates the need for researchers to "embrace complexity", but also underscores the conceptual scope that is required to do so on a broader (bio) psychosocial level.

Reconsidering Informed Consent for Trans-Identified Children, Adolescents, and Young Adults

In less than a decade, the western world has witnessed an unprecedented rise in the numbers of children and adolescents seeking gender transition. Despite the precedent of years of gender-affirmative care, the social, medical and surgical interventions are still based on very low-quality evidence. The many risks of these interventions, including medicalizing a temporary adolescent identity, have come into a clearer focus through an awareness of detransitioners. The risks of gender-affirmative care are ethically managed through a properly conducted informed consent process. Its elements-deliberate sharing of the hoped-for benefits, known risks and long-term outcomes, and alternative treatments-must be delivered in a manner that promotes comprehension. The process is limited by: erroneous professional assumptions; poor quality of the initial evaluations; and inaccurate and incomplete information shared with patients and their parents. We discuss data on suicide and present the limitations of the Dutch studies that have been the basis for interventions. Beliefs about gender-affirmative care need to be separated from the established facts. A proper informed consent process can both prepare parents and patients for the difficult choices that they must make and can ease professionals' ethical tensions. Even when properly accomplished, however, some clinical circumstances exist that remain quite uncertain.

Understanding Long Covid: Nosology, social attitudes and stigma

The debate around Long Covid has so far shown resistance to accept parallels between Long Covid and a set of existing conditions which have historically been subject to stigma. This resistance risks endorsing the stigma associated with such existing conditions, and as such, these dynamics of stigma ought to be dismantled in order to facilitate the development of effective clinical resources for all such implicated conditions. As well as affecting proceedings at the structural level, I discuss how the aforementioned problems also risk affecting patients at the personal level by motivating the reconfiguration and restriction of patient illness narratives. The problems I identify therefore risk affecting both collective and individual understanding of Long Covid.

Reflections on the Clinician's Role with Individuals Who Self-identify as Transgender

The fact that modern patterns of the treatment of trans individuals are not based on controlled or long-term comprehensive follow-up studies has allowed many ethical tensions to persist. These have been intensifying as the numbers of adolescent girls declare themselves to be trans, have gender dysphoria, or are "boys." This essay aims to assist clinicians in their initial approach to trans patients of any age. Gender identity is only one aspect of an individual's multifaceted identity. The contributions to the passionate positions in the trans culture debate are discussed along with the controversy over the official, not falsifiable, position that all gender identities are inherently normal. The essay posits that it is relevant and ethical to investigate the forces that may have propelled an individual to create and announce a new identity. Some of these biological, social, and psychological forces are enumerated. Using the adolescent patient as an example, a model for a comprehensive evaluation process and its goals are provided. The essay is framed within a developmental perspective.

Meaningful associations in the adolescent brain cognitive development study

The Adolescent Brain Cognitive Development (ABCD) Study is the largest single-cohort prospective longitudinal study of neurodevelopment and children's health in the United States. A cohort of n = 11,880 children aged 9-10 years (and their parents/guardians) were recruited across 22 sites and are being followed with in-person visits on an annual basis for at least 10 years. The study approximates the US population on several key sociodemographic variables, including sex, race, ethnicity, household income, and parental education. Data collected include assessments of health, mental health, substance use, culture and environment and neurocognition, as well as geocoded exposures, structural and functional magnetic resonance imaging (MRI), and whole-genome genotyping. Here, we describe the ABCD Study aims and design, as well as issues surrounding estimation of meaningful associations using its data, including population inferences, hypothesis testing, power and precision, control of covariates, interpretation of associations, and recommended best practices for reproducible research, analytical procedures and reporting of results.

Accounting for Confounding in Observational Studies

The goal of this review is to enable clinical psychology researchers to more rigorously test competing hypotheses when studying risk factors in observational studies. We argue that there is a critical need for researchers to leverage recent advances in epidemiology/biostatistics related to causal inference and to use innovative approaches to address a key limitation of observational research: the need to account for confounding. We first review theoretical issues related to the study of causation, how causal diagrams can facilitate the identification and testing of competing hypotheses, and the current limitations of observational research in the field. We then describe two broad approaches that help account for confounding: analytic approaches that account for measured traits and designs that account for unmeasured factors. We provide descriptions of several such approaches and highlight their strengths and limitations, particularly as they relate to the etiology and treatment of behavioral health problems.

Do DSM classifications help or hinder drug development?

Development and regulatory approval of psychotropic drugs targets individuals with syndromes described in the current Diagnostic and Statistical Manual of Mental Disorders (DSM). This helps drug developers and regulators to communicate with prescribers, and prescribers to match a specific psychotropic with the individual patient(s) most likely to benefit from it. However, this practice has been criticized on the grounds that DSM syndromes are too heterogenous biologically, and the effects of psychotropics are too nonspecific to allow for an effective match. This review considers the advantages and disadvantages of the current practice and the possible alternatives. It concludes that efforts should be made to explore psychotropic development transdiagnostically, free of the DSM boundaries. However, currently there exists no alternative diagnostic system that is clearly superior to the DSM in terms of communications between the stakeholders in drug development.


Linking RDoC and HiTOP: A new interface for advancing psychiatric nosology and neuroscience

The Research Domain Criteria (RDoC) and the Hierarchical Taxonomy of Psychopathology (HiTOP) represent major dimensional frameworks proposing two alternative approaches to accelerate progress in the way psychopathology is studied, classified, and treated. RDoC is a research framework rooted in neuroscience aiming to further the understanding of transdiagnostic biobehavioral systems underlying psychopathology and ultimately inform future classifications. HiTOP is a dimensional classification system, derived from the observed covariation among symptoms of psychopathology and maladaptive traits, which seeks to provide more informative research and treatment targets (i.e., dimensional constructs and clinical assessments) than traditional diagnostic categories. This article argues that the complementary strengths of RDoC and HiTOP can be leveraged in order to achieve their respective goals. RDoC's biobehavioral framework may help elucidate the underpinnings of the clinical dimensions included in HiTOP, whereas HiTOP may provide psychometrically robust clinical targets for RDoC-informed research. We present a comprehensive mapping between dimensions included in RDoC (constructs and subconstructs) and HiTOP (spectra and subfactors) based on narrative review of the empirical literature. The resulting RDoC-HiTOP interface sheds light on the biobehavioral correlates of clinical dimensions and provides a broad set of dimensional clinical targets for etiological and neuroscientific research. We conclude with future directions and practical recommendations for using this interface to advance clinical neuroscience and psychiatric nosology. Ultimately, we envision that this RDoC-HiTOP interface has the potential to inform the development of a unified, dimensional, and biobehaviorally-grounded psychiatric nosology.

Predictors of persistence of anxiety disorders across the lifespan: a systematic review

Despite the substantial disease burden of anxiety disorders, physicians have a poor understanding of factors that predict their typical persistent course. This systematic review of predictors of persistent anxiety disorders covered 48 studies with 29 690 patients diagnosed with an anxiety disorder that were published in PubMed, PsycINFO, and Web of Science between Jan 1, 1980 (introduction of DSM-III), and Dec 1, 2019. We also compared predictors between children, adolescents, adults, and older adults (ie, ≥55 years). A persistent course was primarily predicted by clinical and psychological characteristics, including having panic attacks, co-occurring personality disorders, treatment seeking, poor clinical status after treatment, higher severity and longer duration of avoidance behaviour, low extraversion, higher anxiety sensitivity, and higher behavioural inhibition. Unlike disorder onset, sociodemographic characteristics did not predict persistence. Our results outline a profile of patients with specific clinical and psychological characteristics who are particularly vulnerable to anxiety disorder persistence. Clinically, these patients probably deserve additional or more intensive treatment to prevent development of chronicity.

Editorial: The Developmental Science of Borderline Personality Disorder

In a seminal review article on borderline personality disorder (BPD) for the American Journal of Psychiatry, John Gunderson once made the allusion that "borderline personality disorder is to psychiatry what psychiatry is to medicine," suggesting that the condition is frequently neglected, even among mental health professionals and researchers.¹ For instance, BPD-related research received less than one-tenth of the US National Institutes of Health funding compared to bipolar disorder research, despite sharing similar rates of prevalence, impairment, and mortality.² Along those lines, one could argue that borderline personality features in adolescence share the same hierarchical relationship with their counterparts in adults, being even more stigmatized and overlooked, even in the child and adolescent psychiatry community. Accordingly, only 1 of 4 randomized trials with psychosocial interventions for BPD were conducted in youth.^3,4.

Multifactorial prediction of depression diagnosis and symptom dimensions

While depression is a leading cause of disability, prior investigations of depression have been limited by studying correlates in isolation. A data-driven approach was applied to identify out-of-sample predictors of current depression from adults (N = 217) sampled on a continuum of no depression to clinical levels. The current study used elastic net regularized regression and predictors from sociodemographic, self-report, polygenic scores, resting electroencephalography, pupillometry, actigraphy, and cognitive tasks to classify individuals into currently depressed (MDE), psychiatric control (PC), and no current psychopathology (NP) groups, as well as predicting symptom severity and lifetime MDE. Cross-validated models explained 20.6% of the out-of-fold deviance for the classification of MDEs versus PC, 33.2% of the deviance for MDE versus NP, but -0.6% of the deviance between PC and NP. Additionally, predictors accounted for 25.7% of the out-of-fold variance in anhedonia severity, 65.7% of the variance in depression severity, and 12.9% of the deviance in lifetime depression (yes/no). Self-referent processing, anhedonia, and psychosocial functioning emerged as important differentiators of MDE and PC groups. Findings highlight the advantages of using psychiatric control groups to isolate factors specific to depression.

Depressive and anxiety disorders in concert-A synthesis of findings on comorbidity in the NESDA study

BACKGROUND

Comorbidity of depressive and anxiety disorders is common and remains incompletely comprehended. This paper summarizes findings from the Netherlands Study of Depression and Anxiety (NESDA) regarding prevalence, temporal sequence, course and longitudinal patterns; sociodemographic, vulnerability and neurobiological indicators; and functional, somatic and mental health indicators of comorbidity.

METHODS

Narrative synthesis of earlier NESDA based papers on comorbidity (n=76).

RESULTS

Comorbidity was the rule in over three-quarter of subjects with depressive and/or anxiety disorders, most often preceded by an anxiety disorder. Higher severity and chronicity characterized a poorer comorbidity course. Over time, transitions between depressive and anxiety disorders were common. Consistent comorbidity risk indicators in subjects with depressive and anxiety disorders were childhood trauma, neuroticism and early age of onset. Psychological vulnerabilities, such as trait avoidance tendencies, were more pronounced in comorbid than in single disorders. In general, there were few differences in biological markers and neuroimaging findings between persons with comorbid versus single disorders. Most functional, somatic, and other mental health indicators, ranging from disability to cardiovascular and psychiatric multimorbidity, were highest in comorbid disorders.

LIMITATIONS

The observational design of NESDA limits causal inference. Attrition was higher in comorbid relative to single disorders.

CONCLUSIONS

As compared to single disorders, persons with comorbid depressive and anxiety disorders were characterized by more psychosocial risk determinants, more somatic and other psychiatric morbidities, more functional impairments, and poorer outcome. These results justify specific attention for comorbidity of depressive and anxiety disorders, particularly in treatment settings.

Parental risk constellations and future alcohol use disorder (AUD) in offspring: A combined HUNT survey and health registries study

OBJECTIVE

We examined the risk of developing a future alcohol use disorder (AUD) among offspring of families with different constellations of parental risk factors.

METHOD

We analyzed a sample of 8,774 offspring (50.2% male) from 6,696 two-parent families who participated in the Nord-Trøndelag Health Study in Norway when offspring were 13-19 years old in 1995-1997 or 2006-2008. Based on population registry information and parental Nord-Trøndelag Health Study self-reports, families were classified via Latent Profile Analysis into fiver risk constellations reflecting parents' education, drinking quantities and frequencies, and mental health. Information about AUD-related diagnoses, treatments, and prescriptions for all offspring in the period between 2008 and 2016 was obtained from 3 national health registries and pooled to reflect any AUD. The likelihood of AUD in offspring was examined with a set of nested logistic regression models.

RESULTS

Registry records yielded 186 AUD cases (2.1%). Compared with the lowest-risk constellation, offspring from two constellations were more likely to present with AUD in unadjusted analyses. After adjusting for all covariates, including offspring's alcohol consumption and witnessing parental intoxication during adolescence, AUD risk remained elevated and statistically significant (adjusted odds ratio = 2.34, 95% confidence interval = 1.14, 4.85) for offspring from the constellation characterized by at least weekly binge drinking, low education, and poor mental health in both parents.

CONCLUSION

Weekly binge drinking by both parents was associated with future AUD risk among community offspring in Norway when clustered with additional parental risks such as poor mental health and low educational attainment. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Editorial overview: Analytic and methodological innovations for suicide-focused research

This editorial overview provides an introduction to the Suicide and Life-Threatening Behaviors Special Issue: "Analytic and Methodological Innovations for Suicide-Focused Research." We outline several challenges faced by modern suicidologists, such as the need to integrate different analytical and methodological techniques from other fields with the unique data problems in suicide research. Therefore, the overall aim of this issue was to provide up-to-date methodological and analytical guidelines, recommendations, and considerations when conducting suicide-focused research. The articles herein present this information in an accessible way for researchers/clinicians and do not require a comprehensive background in quantitative methods. We introduce the topics covered in this special issue, which include how to conduct power analyses using simulations, work with large data sets, use experimental therapeutics, and choose covariates, as well as open science considerations, decision-making models, ordinal regression, machine learning, network analysis, and measurement considerations. Many of the topics covered in this issue provide step-by-step walkthroughs using worked examples with the accompanied code in free statistical programs (i.e., R). It is our hope that these articles provide suicidologists with valuable information and strategies that can help overcome some of the past limitations of suicide research, and improve the methodological rigor of our field.

Exemplar scoring identifies genetically separable phenotypes of lithium responsive bipolar disorder

Predicting lithium response (LiR) in bipolar disorder (BD) may inform treatment planning, but phenotypic heterogeneity complicates discovery of genomic markers. We hypothesized that patients with "exemplary phenotypes"-those whose clinical features are reliably associated with LiR and non-response (LiNR)-are more genetically separable than those with less exemplary phenotypes. Using clinical data collected from people with BD (n = 1266 across 7 centers; 34.7% responders), we computed a "clinical exemplar score," which measures the degree to which a subject's clinical phenotype is reliably predictive of LiR/LiNR. For patients whose genotypes were available (n = 321), we evaluated whether a subgroup of responders/non-responders with the top 25% of clinical exemplar scores (the "best clinical exemplars") were more accurately classified based on genetic data, compared to a subgroup with the lowest 25% of clinical exemplar scores (the "poor clinical exemplars"). On average, the best clinical exemplars of LiR had a later illness onset, completely episodic clinical course, absence of rapid cycling and psychosis, and few psychiatric comorbidities. The best clinical exemplars of LiR and LiNR were genetically separable with an area under the receiver operating characteristic curve of 0.88 (IQR [0.83, 0.98]), compared to 0.66 [0.61, 0.80] (p = 0.0032) among poor clinical exemplars. Variants in the Alzheimer's amyloid-secretase pathway, along with G-protein-coupled receptor, muscarinic acetylcholine, and histamine H1R signaling pathways were informative predictors. This study must be replicated on larger samples and extended to predict response to other mood stabilizers.

The Identifying Depression Early in Adolescence Risk Stratified Cohort (IDEA-RiSCo): Rationale, Methods, and Baseline Characteristics

Background: The characterization of adolescents at high risk for developing depression has traditionally relied on the presence or absence of single risk factors. More recently, the use of composite risk scores combining information from multiple variables has gained attention in prognostic research in the field of mental health. We previously developed a sociodemographic composite score to estimate the individual level probability of depression occurrence in adolescence, the Identifying Depression Early in Adolescence Risk Score (IDEA-RS). Objectives: In this report, we present the rationale, methods, and baseline characteristics of the Identifying Depression Early in Adolescence Risk Stratified Cohort (IDEA-RiSCo), a study designed for in-depth examination of multiple neurobiological, psychological, and environmental measures associated with the risk of developing and with the presence of depression in adolescence, with a focus on immune/inflammatory and neuroimaging markers. Methods: Using the IDEA-RS as a tool for risk stratification, we recruited a new sample of adolescents enriched for low (LR) and high (HR) depression risk, as well as a group of adolescents with a currently untreated major depressive episode (MDD). Methods for phenotypic, peripheral biological samples, and neuroimaging assessments are described, as well as baseline clinical characteristics of the IDEA-RiSCo sample. Results: A total of 7,720 adolescents aged 14-16 years were screened in public state schools in Porto Alegre, Brazil. We were able to identify individuals at low and high risk for developing depression in adolescence: in each group, 50 participants (25 boys, 25 girls) were included and successfully completed the detailed phenotypic assessment with ascertainment of risk/MDD status, blood and saliva collections, and magnetic resonance imaging (MRI) scans. Across a variety of measures of psychopathology and exposure to negative events, there was a clear pattern in which either the MDD group or both the HR and the MDD groups exhibited worse indicators in comparison to the LR group. Conclusion: The use of an empirically-derived composite score to stratify risk for developing depression represents a promising strategy to establish a risk-enriched cohort that will contribute to the understanding of the neurobiological correlates of risk and onset of depression in adolescence.

Serotonin Reuptake Inhibitors and the Gut Microbiome: Significance of the Gut Microbiome in Relation to Mechanism of Action, Treatment Response, Side Effects, and Tachyphylaxis

The monoamine hypothesis of psychopharmacology has been dominating the biological psychiatric research field for decades. Currently psychiatric research has increasingly appreciated psychiatric disorders and suicidal behavior as being highly complex and multi-etiological. In this pathway the gut microbiome and its interrelationship with the brain is gaining traction. The usage of selective serotonin reuptake inhibitors (SSRIs) is increasing in the general population. This is due to their effect on a broad range of psychiatric disorders, and their favorable side effect profile. Still, there are enigmatic aspects about SSRIs, such as the difficulty to predict effect in individual patients, inter-individual differences in side effect, tachyphylaxis (a sudden loss of response to a certain drug), and to date, uncertainties on how they exert their clinical effect. A majority of the serotonin in the human body is produced within the gut, and SSRIs affect enteric neurons. They also exhibit antimicrobial properties that comes with the potential of disrupting microbial hemostasis. We propose that the role of the gut-brain axis and the gut microbiome in relation to psychopharmacology should be more highlighted. With this article, together with similar articles, we would like to provide a hypothetical framework for future studies within this field. We believe that this would have the potential to provide a paradigm shift within the field of psychopharmacology, and result in findings that potentially could contribute to the development of a more personalized and tailored treatment.

Association of Recent Stressful Life Events With Mental and Physical Health in the Context of Genomic and Exposomic Liability for Schizophrenia

Importance

Both adulthood stressful life events (SLEs) and liability for schizophrenia have been associated with poor mental and physical health in the general population, but their interaction remains to be elucidated to improve population-based health outcomes.

Objective

To test whether recent SLEs interact with genetic and environmental liability for schizophrenia in models of mental and physical health.

Design, Setting, and Participants

The Netherlands Mental Health Survey and Incidence Study-2 is a population-based prospective cohort study designed to investigate the prevalence, incidence, course, and consequences of mental disorders in the Dutch general population. Participants were enrolled from November 5, 2007, to July 31, 2009, and followed up with 3 assessments during 9 years. Follow-up was completed on June 19, 2018, and data were analyzed from September 1 to November 1, 2019.

Exposures

Recent SLEs assessed at each wave and aggregate scores of genetic and environmental liability for schizophrenia: polygenic risk score for schizophrenia (PRS-SCZ) trained using the Psychiatric Genomics Consortium analysis results and exposome score for schizophrenia (ES-SCZ) trained using an independent data set.

Main Outcomes and Measures

Independent and interacting associations of SLEs with ES-SCZ and PRS-SCZ on mental and physical health assessed at each wave using regression coefficients.

Results

Of the 6646 participants included at baseline, the mean (SD) age was 44.26 (12.54) years, and 3672 (55.25%) were female. The SLEs were associated with poorer physical health (B = -3.22 [95% CI, -3.66 to -2.79]) and mental health (B = -3.68 [95% CI, -4.05 to -3.32]). Genetic and environmental liability for schizophrenia was associated with poorer mental health (ES-SCZ: B = -3.07 [95% CI, -3.35 to -2.79]; PRS-SCZ: B = -0.93 [95% CI, -1.31 to -0.54]). Environmental liability was also associated with poorer physical health (B = -3.19 [95% CI, -3.56 to -2.82]). The interaction model showed that ES-SCZ moderated the association of SLEs with mental (B = -1.08 [95% CI, -1.47 to -0.69]) and physical health (B = -0.64 [95% CI, -1.11 to -0.17]), whereas PRS-SCZ did not. Several sensitivity analyses confirmed these results.

Conclusions and Relevance

In this study, schizophrenia liability was associated with broad mental health outcomes at the population level. Consistent with the diathesis-stress model, exposure to SLEs, particularly in individuals with high environmental liability for schizophrenia, was associated with poorer health. These findings underline the importance of modifiable environmental factors during the life span for population-based mental health outcomes.