Personalized medicine in psychiatry

Personalised medicine: a healing application within comorbid PTSD and mTBI military patient sample with a particular focus on special operators

Personalised medicine is replacing prototypical medical care. Personalised medicine focuses on enhancing patients' functioning and preventing future negative impacts of both medical disease and psychological disorders, and unfolds uniquely for each individual. The military special forces community is a group at higher risk for physical trauma, for example, traumatic brain injuries, as well as psychosocial stressors and traumas associated with combat, high operational tempos and sleep deprivation. From a system's cost-benefit perspective and resonating with community norms of resiliency, personalised medicine offers unique innovative treatments for special operators. In this article, we outline the successful applications of personalised medicine via the multidisciplinary treatment of special operators with comorbid conditions (primarily mild traumatic brain injury and post-traumatic stress disorder).

Circadian markers as a predictor of response in the treatment of depression-A systematic review

Despite many available treatment options for depression, response rates remain suboptimal. To improve outcome, circadian markers may be suitable as markers of treatment response. This systematic review provides an overview of circadian markers that have been studied as predictors of response in treatment of depression. A search was performed (EMBASE, PUBMED, PSYCHINFO) for research studies or articles, randomized controlled trials and case report/series with no time boundaries on March 2, 2024 (PROSPERO: CRD42021252333). Other criteria were; an antidepressant treatment as intervention, treatment response measured by depression symptom severity and/or occurrence of a clinical diagnosis of depression and assessment of a circadian marker at baseline. 44 articles, encompassing 8,772 participants were included in the analysis. Although additional research is needed with less variation in types of markers and treatments to provide definitive recommendations, circadian markers, especially diurnal mood variation and chronotype, show potential to implement as response markers in the clinic.

The transition towards community-based mental health care in the European Union: Current realities and prospects

The shift of mental health care from mental institutions to community-based services has been implemented differentially throughout the EU. However, because a comprehensive overview of the current mental health provision in member states is lacking, it is challenging to compare services across nations. This study investigates the extent of implementation of community-based mental health services within the EU using data collected from the WHO Mental Health Atlas. Results show that, although great cross-country variation exists in the implementation of community-based services, mental hospitals remain the prominent model of care in most countries. A few countries endorsed a balanced care model, with the co-occurrence of community services and mental hospitals. However, missing data, low quality of data and different service definitions hamper the possibility of a thorough analysis of the status on deinstitutionalization. Although policies on the closing and downsizing of mental institutions have been endorsed by the EU, the strong presence of mental hospitals slows down the shift towards community-based mental health care. This study highlights the need for an international consensus on definitions and a harmonization of indicators on mental health services. Together with the commitment of member states to improve the quality of data reporting, leadership must emerge to ensure quality monitoring of mental health-related data, which will help advance research, policies and practices.

Personalized medicine in old age psychiatry and Alzheimer's disease

Elderly patients show us unfolded lives with unique individual characteristics. An increasing life span is associated with increasing physical and mental disease burden. Alzheimer's disease (AD) is an increasing challenge in old age. AD cannot be cured but it can be treated. The complexity of old age and AD offer targets for personalized medicine (PM). Targets for stratification of patients, detection of patients at risk for AD or for future targeted therapy are plentiful and can be found in several omic-levels.

Challenges in Identifying Individualized Brain Biomarkers of Late Life Depression

Research into neuroimaging biomarkers for Late Life Depression (LLD) has identified neural correlates of LLD including increased white matter hyperintensities and reduced hippocampal volume. However, studies into neuroimaging biomarkers for LLD largely fail to converge. This lack of replicability is potentially due to challenges linked to construct variability, etiological heterogeneity, and experimental rigor. We discuss suggestions to help address these challenges, including improved construct standardization, increased sample sizes, multimodal approaches to parse heterogeneity, and the use of individualized analytical models.

Early indicators of response to transdiagnostic treatment of pediatric anxiety and depression

BACKGROUND

Pediatric anxiety and depression are prevalent, impairing, and highly comorbid. Available evidence-based treatments have an average response rate of 60%. One path to increasing response may be to identify likely non-responders midway through treatment to adjust course prior to completing an episode of care. The aims of this study, thus, were to identify predictors of post-intervention response assessing (a) mid-treatment symptom severity, (b) session-by-session treatment process factors, and (c) a model optimizing the combination of these.

METHOD

Data were drawn from the treatment arm (N = 95, ages 8-16) of a randomized transdiagnostic intervention trial (Msessions  = 11.2). Mid-point measures of youth- and parent-reported anxiety and depression were collected, and therapists rated homework completion, youth and parent engagement, and youth therapeutic alliance at each session. Logistic regression was used to predict response on the Clinical Global Impression Improvement Scale (CGI-I ≤2) rated by independent evaluators masked to treatment condition.

RESULTS

Mid-point symptom measures were significant predictors of treatment response, as were therapist-ratings of youth and parent engagement, therapeutic alliance, and homework completion. Therapist ratings were significant when tested as mean ratings summing across the first eight sessions of treatment (all ps < .004) and at individual session points (all ps <0.05). A combined prediction model included youth-reported anxiety, parent-reported depression, youth engagement at Session 2, and parent engagement at Session 8. This model correctly classified 76.5% of youth as non-responders and 91.3% as responders at post-treatment (Nagelkerke R2  = .59, χ2 (4, 80) = 46.54, p < .001).

CONCLUSION

This study provides initial evidence that response to transdiagnostic intervention for pediatric anxiety and depression may be reliably predicted by mid-point. These data may serve as foundational evidence to develop adaptive treatment strategies to personalize intervention, correct treatment course, and optimize outcomes for youth with anxiety and depression.

Potential efficacy of dopaminergic antidepressants in treatment resistant anergic-anhedonic depression results of the chronic anergic-anhedonic depression open trial - CADOT

Introduction

Among treatment-resistant depression (TRD), we identified anergic-anhedonic clinical presentations (TRAD) as putatively responsive to pro-dopaminergic strategies. Based on the literature, non-selective monoamine oxidase inhibitors (MAOI) and dopamine D2 receptor agonists (D2RAG) were sequentially introduced, frequently under the coverage of a mood stabilizer. This two-step therapeutic strategy will be referred to as the Dopaminergic Antidepressant Therapy Algorithm (DATA). We describe the short and long-term outcomes of TRAD managed according to DATA guidelines.

Method

Out of 52 outpatients with TRAD treated with DATA in a single expert center, 48 were included in the analysis [severity - QIDS (Quick Inventory of Depressive Symptomatology) = 16 ± 3; episode duration = 4.1 ± 2.7 years; Thase and Rush resistance stage = 2.9 ± 0.6; functioning - GAF (Global Assessment of Functioning) = 41 ± 8]. These were followed-up for a median (1st - 3rd quartile) of 4 (1-9) months before being prescribed the first dopaminergic treatment and remitters were followed up 21 (11-33) months after remission.

Results

At the end of DATA step 1, 25 patients were in remission (QIDS <6; 52% [38-66%]). After DATA step 2, 37 patients were in remission (77% [65-89%]) to whom 5 patients with a QIDS score = 6 could be added (88% [78-97%]). Many of these patients felt subjectively remitted (GAF = 74 ± 10). There was a significant benefit to combining MAOI with D2RAG which was maintained for at least 18 months in 30 patients (79% [62-95%]).

Conclusion

These results support TRAD sensitivity to pro-dopaminergic interventions. However, some clinical heterogeneities remain in our sample and suggest some improvement in the description of dopamine-sensitive form(s).

The longitudinal trajectory of emotional cognition in subgroups of recently diagnosed patients with bipolar disorder

Although cross-sectional studies show heterogeneity in emotional cognition in bipolar disorder (BD), the temporal course within subgroups is unclear. In this prospective, longitudinal study we assessed the trajectories of emotional cognition subgroups within a 16-month follow-up period in recently diagnosed BD patients compared to healthy controls (HC). Recently diagnosed BD patients and HC underwent comprehensive emotional and non-emotional testing at baseline and again at follow-up. We employed hierarchical cluster analysis at baseline to identify homogenous emotional cognition subgroups of patients, and changes across the subgroups of BD and HC were assessed with linear mixed-model analyses. We found two emotional cognition subgroups: subgroup 1 (65%, n = 179), showing heightened negative emotional reactivity in neutral and negative social scenarios and faster recognition of emotional facial expressions than HC (ps<0.001, n = 190), and subgroup 2 (35%, n = 96) showing blunted reactivity in positive social scenarios, impaired emotion regulation, poorer recognition of positive and slower recognition of all facial expressions than HC (ps≤.03). Subgroup 1 exhibited normalization of the initial emotional cognition abnormalities in follow-up. In contrast, subgroup 2 showed a lack of improvement in reactivity positively-valenced emotional information. Patients in subgroup 2 presented more and longer mixed episodes during the follow-up time and were more often prescribed lithium. One third of patients display blunted emotional reactivity, impaired emotion regulation abilities and facial expression recognition difficulties also show persistent impairments and poorer course of illness. This subgroup may indicate a need for earlier and more targeted therapeutic interventions.

Toward Precision Medicine in ADHD

Attention-Deficit Hyperactivity Disorder (ADHD) is a complex and heterogeneous neurodevelopmental condition for which curative treatments are lacking. Whilst pharmacological treatments are generally effective and safe, there is considerable inter-individual variability among patients regarding treatment response, required dose, and tolerability. Many of the non-pharmacological treatments, which are preferred to drug-treatment by some patients, either lack efficacy for core symptoms or are associated with small effect sizes. No evidence-based decision tools are currently available to allocate pharmacological or psychosocial treatments based on the patient's clinical, environmental, cognitive, genetic, or biological characteristics. We systematically reviewed potential biomarkers that may help in diagnosing ADHD and/or stratifying ADHD into more homogeneous subgroups and/or predict clinical course, treatment response, and long-term outcome across the lifespan. Most work involved exploratory studies with cognitive, actigraphic and EEG diagnostic markers to predict ADHD, along with relatively few studies exploring markers to subtype ADHD and predict response to treatment. There is a critical need for multisite prospective carefully designed experimentally controlled or observational studies to identify biomarkers that index inter-individual variability and/or predict treatment response.

Psychosocial Profiles of Patients Admitted to Psychiatric Emergency Services: Results from the Signature Biobank Project

OBJECTIVES

Patients admitted to psychiatric emergency services (PES) are highly heterogenous. New tools based on a transdiagnosis approach could help attending psychiatrists in their evaluation process and treatment planning. The goals of this study were to: (1) identify profiles of symptoms based on self-reported, dimensional outcomes in psychiatric patients upon their admission to PES, (2) link these profiles to developmental variables, that is, history of childhood abuse (CA) and trajectories of externalizing behaviours (EB), and (3) test whether this link between developmental variables and profiles was moderated by sex.

METHODS

In total, 402 patients were randomly selected from the Signature Biobank, a database of measures collected from patients admitted to the emergency of a psychiatric hospital. A comparison group of 92 healthy participants was also recruited from the community. Symptoms of anxiety, depression, alcohol and drug abuse, impulsivity, and psychosis as well as CA and EB were assessed using self-reported questionnaires. Symptom profiles were identified using cluster analysis. Prediction of profile membership by sex, CA, and EB was tested using structural equation modelling.

RESULTS

Among patients, four profiles were identified: (1) low level of symptoms on all outcomes, (2) high psychotic symptoms, (3) high anxio-depressive symptoms, and (4) elevated substance abuse and high levels of symptoms on all scales. An indirect effect of CA was found through EB trajectories: patients who experienced the most severe form of CA were more likely to develop chronic EB from childhood to adulthood, which in turn predicted membership to the most severe psychopathology profile. This indirect effect was not moderated by sex.

CONCLUSION

Our results suggest that a transdiagnostic approach allows to highlight distinct clinical portraits of patients admitted to PES. Importantly, developmental factors were predictive of specific profiles. Such transdiagnostic approach is a first step towards precision medicine, which could lead to develop targeted interventions.

Hair cortisol change at COVID-19 pandemic onset predicts burnout among health personnel

BACKGROUND

The COVID-19 pandemic has put chronic pressure on worldwide healthcare systems. While the literature regarding the prevalence of psychological distress and associated risk factors among healthcare workers facing COVID-19 has exploded, biological variables have been mostly overlooked.

METHODS

467 healthcare workers from Quebec, Canada, answered an electronic survey covering various risk factors and mental health outcomes three months after the onset of the COVID-19 pandemic. Of them, 372 (80%) provided a hair sample, providing a history of cortisol secretion for the three months preceding and following the pandemic's start. We used multivariable regression models and a receiver operating characteristic curve to study hair cortisol as a predictor of burnout and psychological health, together with individual, occupational, social, and organizational factors.

RESULTS

As expected, hair cortisol levels increased after the start of the pandemic, with a median relative change of 29% (IQR = 3-59%, p < 0.0001). There was a significant association between burnout status and change in cortisol, with participants in the second quarter of change having lower odds of burnout. No association was found between cortisol change and post-traumatic stress disorder, anxiety, and depression symptoms. Adding cortisol to individual-occupational-socio-organizational factors noticeably enhanced our burnout logistic regression model's predictability.

CONCLUSION

Change in hair cortisol levels predicted burnout at three months in health personnel at the onset of the COVID-19 pandemic. This non-invasive biological marker of the stress response could be used in further clinical or research initiatives to screen high-risk individuals to prevent and control burnout in health personnel facing an important stressor.

Machine learning approaches for parsing comorbidity/heterogeneity in antisociality and substance use disorders: A primer

By some accounts, as many as 93% of individuals diagnosed with antisocial personality disorder (ASPD) or psychopathy also meet criteria for some form of substance use disorder (SUD). This high level of comorbidity, combined with an overlapping biopsychosocial profile, and potentially interacting features, has made it difficult to delineate the shared/unique characteristics of each disorder. Moreover, while rarely acknowledged, both SUD and antisociality exist as highly heterogeneous disorders in need of more targeted parcellation. While emerging data-driven nosology for psychiatric disorders (e.g., Research Domain Criteria (RDoC), Hierarchical Taxonomy of Psychopathology (HiTOP)) offers the opportunity for a more systematic delineation of the externalizing spectrum, the interrogation of large, complex neuroimaging-based datasets may require data-driven approaches that are not yet widely employed in psychiatric neuroscience. With this in mind, the proposed article sets out to provide an introduction into machine learning methods for neuroimaging that can help parse comorbid, heterogeneous externalizing samples. The modest machine learning work conducted to date within the externalizing domain demonstrates the potential utility of the approach but remains highly nascent. Within the paper, we make suggestions for how future work can make use of machine learning methods, in combination with emerging psychiatric nosology systems, to further diagnostic and etiological understandings of the externalizing spectrum. Finally, we briefly consider some challenges that will need to be overcome to encourage further progress in the field.

Oxidative Stress Biomarkers as a Predictor of Stage Illness and Clinical Course of Schizophrenia

Pro/antioxidant imbalance has been reported in schizophrenia (SZ). However, the results of studies are inconsistent and usually do not include other factors that are highly affected by oxidative stress (OS).This cross-sectional study aimed to determine the serum levels of OS markers and their potential connection with schizophrenia. The total sample comprised 147: 98 individuals with SZ -47 first-episode (FS) and 49 chronic patients (CS)-and 49 healthy individuals (HC) as a control group. The examination included clinical variables and serum levels of antioxidants and oxidative damage products. The significant changes were observed in concentrations of all examined markers, without any specific direction of the pro/antioxidant balance shift between SZ and HC. In the regression model adjusted for cofounders, catalase: OR = 0.81 (95%CI: 0.74-0.88); glutathione peroxidase: OR = 1.06 (95%CI: 1.02-1.10); total antioxidant capacity: OR = 0.85 (95%CI: 0.75-0.98); oxidative stress index: OR = 1.25 (95%CI: 1.03-1.52); ferric reducing ability of plasma: OR = 0.79 (95%CI: 0.69-0.89); advanced glycation end products: OR = 1.03 (95%CI: 1.01-1.04); and advanced oxidation protein products (AOPP): OR = 1.05 (95%CI: 1.03-1.07) turned out to be significant predictors of schizophrenia. In the multiple stepwise regression model, pro/antioxidant status and their interaction with the duration of illness-related factors affected schizophrenia symptoms: positive symptoms (FRAPxKYN), negative (DITYR, FRAP, CAT), general (KYN), and over-all psychopathology (KYNxNFK). The results confirm differences in serum levels of oxidative biomarkers between SZ patients and healthy individuals. The pro/antioxidant status could be considered a predictor of schizophrenia and the factor affects patients' symptom severity.

Predominant Polarity and Polarity Index of Maintenance Treatments for Bipolar Disorder: A Validation Study in a Large Naturalistic Sample in Italy

Background and Objectives: Predominant polarity (PP) may be a useful course specifier in at least a significant proportion of patients with Bipolar Disorder (BD), being associated with several clinically relevant correlates. Emerging evidence suggests that the concept of PP might influence the selection of maintenance treatments, based on a drug polarity index (PI) which measures the greater antidepressive vs. antimanic preventive efficacy of mood stabilizers over long-term maintenance treatment. In this study, we aimed to validate the PI in a large sample of Italian BD patients with accurate longitudinal characterization of the clinical course, which ensured a robust definition of the PP. Materials and Methods: Our sample is comprised of 653 patients with BD, divided into groups based on the predominant polarity (manic/hypomanic predominant polarity—MPP, depressive predominant polarity—DPP and no predominant polarity). Subsequently we calculated the mean total polarity index for each group, and we compared the groups. Results: When we examined the mean PI of treatments prescribed to individuals with DPP, MPP and no predominant polarity, calculated using two different methods, we failed to find significant differences, with the exception of the PI calculated with the Popovic method and using the less stringent criterion for predominant polarity (PP_50%). Conclusions: Future prospective studies are needed in order to determine whether the predominant polarity is indeed one clinical factor that might guide the clinician in choosing the right mood stabilizer for BD maintenance treatment.

Convergence between clinician-rated and patient-reported PTSD symptoms in a specialized outpatient service: The moderator role of gender

PURPOSE

Posttraumatic stress disorder (PTSD) includes different symptoms: re-experiencing, avoidance of reminders and numbing, and hyperarousal. Although questionnaires are widely used, clinician-administered interviews provide a more comprehensive exploration of symptoms. Few studies examined the convergence between clinician-rated and patient-reported general severity and symptoms, with mixed findings. We explored the association between clinician-rated and patient-reported general severity and symptoms and the moderator role of gender in PTSD patients referred to a specialized outpatient service.

DESIGN AND METHODS

The Clinician-Administered PTSD Scale and Davidson Trauma Scale were administered to 56 patients.

FINDINGS

Patients classified by clinicians as with higher avoidance/numbing symptoms and women classified with higher hyperarousal symptoms reported higher general severity.

PRACTICE IMPLICATIONS

The assessment of the patients reporting high severity should focus on hyperarousal, particularly for women.

Computational Models in Electroencephalography

Computational models lie at the intersection of basic neuroscience and healthcare applications because they allow researchers to test hypotheses in silico and predict the outcome of experiments and interactions that are very hard to test in reality. Yet, what is meant by “computational model” is understood in many different ways by researchers in different fields of neuroscience and psychology, hindering communication and collaboration. In this review, we point out the state of the art of computational modeling in Electroencephalography (EEG) and outline how these models can be used to integrate findings from electrophysiology, network-level models, and behavior. On the one hand, computational models serve to investigate the mechanisms that generate brain activity, for example measured with EEG, such as the transient emergence of oscillations at different frequency bands and/or with different spatial topographies. On the other hand, computational models serve to design experiments and test hypotheses in silico. The final purpose of computational models of EEG is to obtain a comprehensive understanding of the mechanisms that underlie the EEG signal. This is crucial for an accurate interpretation of EEG measurements that may ultimately serve in the development of novel clinical applications.

Personalized Healthcare: The Importance of Patients' Rights in Clinical Practice from the Perspective of Nursing Students in Poland, Spain and Slovakia-A Cross-Sectional Study

Background: This study aimed to define the role and importance of patients’ rights in personalized healthcare from the perspective of nursing students in Poland, Spain and Slovakia. Methods: The research was carried out by means of a diagnostic survey, using the survey technique, with the participation of 1002 nursing students attending a full-time undergraduate study program at three European countries. The “Patients’ rights” questionnaire was used as a research tool. The average age of students was 21.6 years (±3.4). The empirical material collected was subjected to a statistical analysis. Results: The study demonstrated that 72.1% of nursing students from Spain, 51.2% from Poland and 38.5% from Slovakia believe that patients’ rights are respected at a good level in their country. Significant intergroup differences (F = 67.43; p < 0.0001) were observed in the self-assessment of students’ knowledge of patients’ rights. The highest average values were obtained by students from Spain (3.54 ± 0.92), while 35.9% of students from Slovakia and 25.5% from Poland were quite critical and pointed to their low level of knowledge of patients’ rights in their self-assessment. When ranking patients’ rights related to respecting dignity, students from Spain obtained much higher average values (4.37 ± 0.92) than students from the other two countries. Conclusions: The level of students’ knowledge of patients’ rights and the respect for patients’ rights by medical personnel is, in the opinion of the respondents, quite diverse and requires in-depth educational activities among nursing students at the university level in respective countries.

Four Actionable Bottlenecks and Potential Solutions to Translating Psychiatric Genetics Research: An Expert Review

BACKGROUND

Psychiatric genetics has had limited success in translational efforts. A thorough understanding of the present state of translation in this field will be useful in the facilitation and assessment of future translational progress.

PURPOSE

A narrative literature review was conducted. Combinations of 3 groups of terms were searched in EBSCOhost, Google Scholar, and PubMed. The review occurred in multiple steps, including abstract collection, inclusion/exclusion criteria review, coding, and analysis of included papers.

RESULTS

One hundred and fourteen articles were analyzed for the narrative review. Across those, 4 bottlenecks were noted that, if addressed, may provide insights and help improve and increase translation in the field of psychiatric genetics. These 4 bottlenecks are emphasizing linear translational frameworks, relying on molecular genomic findings, prioritizing certain psychiatric disorders, and publishing more reviews than experiments.

CONCLUSIONS

These entwined bottlenecks are examined with one another. Awareness of these bottlenecks can inform stakeholders who work to translate and/or utilize psychiatric genetic information. Potential solutions include utilizing nonlinear translational frameworks as well as a wider array of psychiatric genetic information (e.g., family history and gene-environment interplay) in this area of research, expanding which psychiatric disorders are considered for translation, and when possible, conducting original research. Researchers are urged to consider how their research is translational in the context of the frameworks, genetic information, and psychiatric disorders discussed in this review. At a broader level, these efforts should be supported with translational efforts in funding and policy shifts.

The Discovery of Clinically Applicable Biomarkers for Bipolar Disorder: A Review of Candidate and Proteomic Approaches

Bipolar disorder (BD) is a severe psychiatric condition which affects innumerable people across the globe. The etiopathogenesis of BD is multi-faceted with genetic, environmental and psychosocial factors playing a role. Hitherto, the diagnosis and management of BD are purely on empirical grounds as we lack confirmed biomarkers for this condition. In this regard, hypothesis-driven investigations have been unable to identify clinically applicable biomarkers, steering the field towards newer technologies. Innovative, state-of-the-art techniques like multiplex immunoassays and mass spectrometry can potentially investigate the entire proteome. By detecting up or down regulated proteins, novel biomarkers are identified and new postulates about the etiopathogenesis of BD are specified. Hence, biological pathways are uncovered which are involved in the initiation and advancement of the disease and new therapeutic targets are identified. In this manuscript, the extant literature is thoroughly reviewed and the latest findings on candidate BD biomarkers are provided, followed by an overview of the proteomic approaches. It was found that due to the heterogeneous nature of BD no single biomarker is feasible, instead a panel of tests is more likely to be useful. With the application of latest technologies, it is expected that validated biomarkers will be discovered which will be useful as diagnostic tools and help in the delivery of individually tailored therapies to the patients.

Exploring Health Literacy in Individuals with Alcohol Addiction: A Mixed Methods Clinical Study

This mixed methods research paper explores health literacy (HL) in individuals with alcohol addiction by using the 47-item version of the European Health Literacy Survey Questionnaire (HLS-EU-Q47) and semi-structured interviews concerning health-related competencies (access, understand, appraise, and apply health information), and determines the limitations of the HLS-EU-Q47 when used under specific conditions of clinical practice. The questionnaire survey and the interviews were conducted with individuals of different health literacy levels who were undergoing inpatient alcohol addiction treatment. The findings indicate that individuals with alcohol addiction might require different types of health information according to their health literacy level in terms of quantity and quality of information to recover from alcohol addiction and improve their overall health. The implications for the clinical practice of addiction treatment as well as recommendations for national and regional policy are also discussed.

Can personalized treatment prediction improve the outcomes, compared with the group average approach, in a randomized trial? Developing and validating a multivariable prediction model in a pragmatic megatrial of acute treatment for major depression

BACKGROUND

Clinical trials have traditionally been analysed at the aggregate level, assuming that the group average would be applicable to all eligible and similar patients. We re-analyzed a mega-trial of antidepressant therapy for major depression to explore whether a multivariable prediction model may lead to different treatment recommendations for individual participants.

METHODS

The trial compared the second-line treatment strategies of continuing sertraline, combining it with mirtazapine or switching to mirtazapine after initial failure to remit on sertraline among 1,544 patients with major depression. The outcome was the Personal Health Questionnaire-9 (PHQ-9) at week 9: the original analyses showed that both combining and switching resulted in greater reduction in PHQ-9 by 1.0 point than continuing. We considered several models of penalized regression or machine learning.

RESULTS

Models using support vector machines (SVMs) provided the best performance. Using SVMs, continuing sertraline was predicted to be the best treatment for 123 patients, combining for 696 patients, and switching for 725 patients. In the last two subgroups, both combining and switching were equally superior to continuing by 1.2 to 1.4 points, resulting in the same treatment recommendations as with the original aggregate data level analyses; in the first subgroup, however, switching was substantively inferior to combining (-3.1, 95%CI: -5.4 to -0.5).

LIMITATIONS

Stronger predictors are needed to make more precise predictions.

CONCLUSIONS

The multivariable prediction models led to improved recommendations for a minority of participants than the group average approach in a megatrial.

Assessment of Population Well-Being With the Mental Health Quotient (MHQ): Development and Usability Study

BACKGROUND

Existing mental health assessment tools provide an incomplete picture of symptom experience and create ambiguity, bias, and inconsistency in mental health outcomes. Furthermore, by focusing on disorders and dysfunction, they do not allow a view of mental health and well-being across a general population.

OBJECTIVE

This study aims to demonstrate the outcomes and validity of a new web-based assessment tool called the Mental Health Quotient (MHQ), which is designed for the general population. The MHQ covers the complete breadth of clinical mental health symptoms and also captures healthy mental functioning to provide a complete profile of an individual's mental health from clinical to thriving.

METHODS

The MHQ was developed based on the coding of symptoms assessed in 126 existing Diagnostic and Statistical Manual of Mental Disorders (DSM)-based psychiatric assessment tools as well as neuroscientific criteria laid out by Research Domain Criteria to arrive at a comprehensive set of semantically distinct mental health symptoms and attributes. These were formulated into questions on a 9-point scale with both positive and negative dimensions and developed into a web-based tool that takes approximately 14 min to complete. As its output, the assessment provides overall MHQ scores as well as subscores for 6 categories of mental health that distinguish clinical and at-risk groups from healthy populations based on a nonlinear scoring algorithm. MHQ items were also mapped to the DSM fifth edition (DSM-5), and clinical diagnostic criteria for 10 disorders were applied to the MHQ outcomes to cross-validate scores labeled at-risk and clinical. Initial data were collected from 1665 adult respondents to test the tool.

RESULTS

Scores in the normal healthy range spanned from 0 to 200 for the overall MHQ, with an average score of approximately 100 (SD 45), and from 0 to 100 with average scores between 48 (SD 21) and 55 (SD 22) for subscores in each of the 6 mental health subcategories. Overall, 2.46% (41/1665) and 13.09% (218/1665) of respondents were classified as clinical and at-risk, respectively, with negative scores. Validation against DSM-5 diagnostic criteria showed that 95% (39/41) of those designated clinical were positive for at least one DSM-5-based disorder, whereas only 1.14% (16/1406) of those with a positive MHQ score met the diagnostic criteria for a mental health disorder.

CONCLUSIONS

The MHQ provides a fast, easy, and comprehensive way to assess population mental health and well-being; identify at-risk individuals and subgroups; and provide diagnosis-relevant information across 10 disorders.

Toward prevention of bipolar disorder in at-risk children: Potential strategies ahead of the data

BACKGROUND

Despite the well-documented negative impact of untreated bipolar illness, approaches to early intervention in childhood-onset bipolar and related disorders are not well delineated.

METHODS

We reviewed the extant treatment literature on children at high risk for bipolar disorder, with definitions based on family history, childhood adversity, and prodromal symptoms.

RESULTS

A panoply of approaches have been described, but most interventions are based on an inadequate database to support their routine implementation. We classify early stage interventions as a function of their safety and tolerability with the hope that these might generate more rigorous study and a stronger database.

LIMITATIONS

Critics may rightly argue that identifying viable treatment methods is premature given our lack of ability to reliably predict illness trajectory in very young children. However, many of the psychosocial and pharmacological interventions we present could have nonspecific positive effects across a variety of symptoms, syndromes, and diagnoses, further enhancing the rationale for more rigorous study.

CONCLUSIONS

Early stage interventions have the potential to improve functioning in prodromal illness and exert long-term positive effects on the course of illness. Many of the safest interventions deserve consideration for implementation and dissemination studies.

Current challenges and possible future developments in personalized psychiatry with an emphasis on psychotic disorders

A personalized medicine approach seems to be particularly applicable to psychiatry. Indeed, considering mental illness as deregulation, unique to each patient, of molecular pathways, governing the development and functioning of the brain, seems to be the most justified way to understand and treat disorders of this medical category. In order to extract correct information about the implicated molecular pathways, data can be drawn from sampling phenotypic and genetic biomarkers and then analyzed by a machine learning algorithm. This review describes current difficulties in the field of personalized psychiatry and gives several examples of possibly actionable biomarkers of psychotic and other psychiatric disorders, including several examples of genetic studies relevant to personalized psychiatry. Most of these biomarkers are not yet ready to be introduced in clinical practice. In a next step, a perspective on the path personalized psychiatry may take in the future is given, paying particular attention to machine learning algorithms that can be used with the goal of handling multidimensional datasets.

The Empathic Brain of Psychopaths: From Social Science to Neuroscience in Empathy

Empathy is a crucial human ability, because of its importance to prosocial behavior, and for moral development. A deficit in empathic abilities, especially affective empathy, is thought to play an important role in psychopathic personality. Empathic abilities have traditionally been studied within the social and behavioral sciences using behavioral methods, but recent work in neuroscience has begun to elucidate the neural underpinnings of empathic processing in relation to psychopathy. In this review, current knowledge in the social neuroscience of empathy is discussed and a comprehensive view of the neuronal mechanisms that underlie empathy in psychopathic personality is provided. Furthermore, it will be argued that using classification based on overt behavior, we risk failing to identify important mechanisms involved in the psychopathology of psychopathy. In the last decade, there is a growing attention in combining knowledge from (neuro)biological research areas with psychology and psychiatry, to form a new basis for categorizing individuals. Recently, a converging framework has been put forward that applies such approach to antisocial individuals, including psychopathy. In this bio-cognitive approach, it is suggested to use information from different levels, to form latent categories on which individuals are grouped, that may better reflect underlying (neurobiological) dysfunctions. Subsequently, these newly defined latent categories may be more effective in guiding interventions and treatment. In conclusion, in my view, the future understanding of the social brain of psychopaths lies in studying the complex networks in the brain in combination with the use of other levels of information (e.g., genetics and cognition). Based on that, profiles of individuals can be formed that can be used to guide neurophysiological informed personalized treatment interventions that ultimately reduce violent transgressions in individuals with psychopathic traits.

The Finnish psychiatric birth cohort consortium (PSYCOHORTS) - content, plans and perspectives

Background: Psychiatric disorders tend to be developmental, and longitudinal settings are required to examine predictors of psychiatric phenomena. Replicating and combining data and results from different birth cohorts, which are a source of reliable data, can make research even more valuable. The Finnish Psychiatric Birth Cohort Consortium (PSYCOHORTS) project combines birth cohorts in Finland. Aim: The aim of this paper is to introduce content, plans and perspectives of the PSYCOHORTS project that brings together researchers from Finland. In addition, we illustrate an example of data harmonization using available data on causes of death. Content: PSYCOHORTS includes eight Finnish birth cohorts. The project has several plans: to harmonize different data from birth cohorts, to incorporate biobanks into psychiatric birth cohort research, to apply multigenerational perspectives, to integrate longitudinal patterns of marginalization and inequality in mental health, and to utilize data in health economics research. Data on causes of death, originally obtained from Finnish Cause of Death register, were harmonized across the six birth cohorts using SAS macro facility. Results: Harmonization of the cause of death data resulted in a total of 21,993 observations from 1965 to 2015. For example, the percentage of deaths due to suicide and the sequelae of intentional self-harm was 14% and alcohol-related diseases, including accidental poisoning by alcohol, was 13%. Conclusions: PSYCOHORTS lays the foundation for complex examinations of psychiatric disorders that is based on compatible datasets, use of biobanks and multigenerational approach to risk factors, and extensive data on marginalization and inequality.

Analysis of Lithuanian CYP2D6 polymorphism and its relevance to psychiatric care of the local population

BACKGROUND

CYP450 system gene CYP2D6 polymorphisms have been associated with an altered response to psychotropic drugs. While there exists interindividual and interethnic differences of clinical significance, there is no data concerning the Lithuanian population.

AIMS

To determine the distribution of CYP2D6 alleles and predicted phenotype in the Lithuanian population, compare it to other Europeans and find the differences between patients with affective disorders and the healthy population.

METHODS

Our study sample consisted of 179 subjects that included 104 healthy volunteers and 75 patients with clinical diagnosis of affective disorders according to ICD-10AM classification, treated in hospital settings. DNA samples were taken from the blood and alleles of the CYP2D6 gene were determined for each participant. Frequencies were compared to other Europeans.

RESULTS

The frequency of the most common alleles *1 and *2 was 45.0% and 28.8% accordingly. Dysfunctional *5 (1 vs. 30, p < .002) allele was less frequent in Lithuania inhabitants than previously established in other Europeans. There were no polymorphisms of the CYP2D6 gene that could be associated with changes in drug metabolism in the patients. The functional CYP2D6 *2 allele was more prevalent in the control group, while the non functional CYP2D6 *4 allele was more prevalent in the patient group (p < .05 for both cases).

CONCLUSION

The genetic makeup of Lithuanians was generally comparable to other Europeans, but fewer Lithuanians had non-functional *5 allele. More patients had non-functional alleles. Study findings contradict previous results from other countries, where CYP2D6 gene polymorphism was associated with treatment outcomes.

Precision pharmacotherapy: psychiatry's future direction in preventing, diagnosing, and treating mental disorders

Mental disorders account for around one-third of disability worldwide and cause enormous personal and societal burden. Current pharmacotherapies and nonpharmacotherapies do help many patients, but there are still high rates of partial or no response, delayed effect, and unfavorable adverse effects. The current diagnostic taxonomy of mental disorders by the Diagnostic and Statistical Manual of Mental Disorders and the International Classification of Diseases relies on presenting signs and symptoms, but does not reflect evidence from neurobiological and behavioral systems. However, in the last decades, the understanding of biological mechanisms underlying mental disorders has grown and can be used for the development of precision medicine, that is, to deliver a patient-tailored individual treatment. Precision medicine may incorporate genetic variants contributing to the mental disorder and the response to pharmacotherapies, but also consider gene ¥ environment interactions, blood-based markers, neuropsychological tests, data from electronic health records, early life adversity, stressful life events, and very proximal factors such as lifestyle, nutrition, and sport. Methods such as artificial intelligence and the underlying machine learning and deep learning approaches provide the framework to stratify patients, initiate specific tailored treatments and thus increase response rates, reduce adverse effects and medical errors. In conclusion, precision medicine uses measurable health parameters to identify individuals at risk of a mental disorder, to improve the diagnostic process and to deliver a patient-tailored treatment.

Bifrontal active and sham rTMS in treatment-resistant unipolar major depression

BACKGROUND AND AIM

Prevention of the recurrence of major depression and its residual symptoms requires effective treatment. Our aim was to study the effects of bifrontal active rTMS controlled by sham rTMS in treatment-resistant unipolar major depressive disorder (MDD).

METHODS

Thirty-seven patients with treatment-resistant MDD were randomized into two groups. One group received a total of 30 sessions of active bifrontal rTMS (10 Hz rTMS on left dorsolateral prefrontal cortex (DLPFC) and 1 Hz rTMS on right DLPFC) and the other group received bilateral sham rTMS on five days a week for six weeks.

RESULTS

Depressive symptoms significantly improved in both the groups, but without a significant group difference. Furthermore, patients with psychotic depression improved similarly to those with moderate or severe depression.

CONCLUSIONS

The results of present study indicate a large sham effect of stimulation treatment. The intensive structured treatment protocol may explain the positive outcome in both the groups. It is important to recognize, appreciate, and utilize placebo effects as a significant means of rehabilitation in psychiatric care.

Does S100B have a potential role in affective disorders? A literature review

BACKGROUND

S100B is a calcium-binding protein located in glial cells; it is regarded as a potential biomarker in affective disorders.

AIM

To review the literature investigating the role of S100B in patients with affective disorders.

METHOD

A systematic review of original English language studies investigating S100B in serum, cerebrospinal fluid, plasma and lymphocytes, in patients with affective disorders, was conducted. The literature search was conducted within the PubMed database. Effect sizes were calculated to adjust for systematic measurement effects.

RESULTS

Twenty studies were included, with a total of 1292 participants. Of these, 398 patients had or have had depressive disorder, 301 patients had bipolar disorder and 593 were healthy controls. S100B levels in serum were consistently elevated in studies with statistically significant results which investigated acute affective episodes (comprising major depressive episode in major depressive disorder, and both manic and depressive episodes in patients with bipolar disorder), in comparison to healthy controls. There were few studies assessing S100B levels in cerebrospinal fluid, plasma or lymphocytes, and these had inconsistent results.

CONCLUSION

The results indicated that elevated S100B levels might be associated with mood episodes in affective disorders. However, the role of S100B, and its possible impact in affective disorders, requires further investigation and at the present S100B does not have a role as clinically biomarker in affective disorder. Future longitudinal multicentre studies with larger transdiagnostic real life patient cohorts are warranted.

Precision Psychiatry and Dual Disorders

OBJECTIVE

Addiction co-occurs with distinct pathological personality traits, other psychiatric disorders or symptoms and cognitive impairment, which are known as dual disorders or co-occurring disorders. This symptomatic high concurrency suggests that both conditions are in some ways causally linked. Research is ongoing to identify distinctive neurobehavioral mechanisms and endophenotypes that predispose individuals to compulsive drug use and other mental disorders. Research is also providing new revelations about the diverse effects of substances on individuals, including differences according to sex. Today we know that the same substance may give rise to different behavioral, affective, cognitive, and sensory effects across different individuals.

METHODS

This state-of the art review tends to address the concept of precision psychiatry and dual disorders. The PubMed database was searched for the last 15 years to identify those articles that reported neurobiological perspectives on dual disorders, addiction and other mental disorders, precision medicine, and precision psychiatry.

RESULTS

There has been considerable progress made in recent years in relation to the study of addiction and dual disorders. The concept of dual disorders attempts to capture not only the persistence of substance use and substance seeking but also the evident vulnerability of specific subpopulations to switch from controlled to compulsive drug use. Precision medicine is focused on identifying this individual vulnerability to illness as much as the individual response to treatment. Psychiatry is fully committed to this goal. Regarding addiction, essential precision medicine advances will be possible if concerted efforts are made in the discovery of biological variations and environmental factors that contribute to individual vulnerability to addictive disorders and dual disorders, together with the identification of moderators of treatment response.

CONCLUSIONS

Here we survey the discoveries, future research directions, and translational relevance of the concept of precision psychiatry for dual disorders. The review may offer new perspectives on this issue and highlight a new way to see and to think about dual disorders.

Can an Integrated Science Approach to Precision Medicine Research Improve Lithium Treatment in Bipolar Disorders?

Clinical practice guidelines identify lithium as a first line treatment for mood stabilization and reduction of suicidality in bipolar disorders (BD); however, most individuals show sub-optimal response. Identifying biomarkers for lithium response could enable personalization of treatment and refine criteria for stratification of BD cases into treatment-relevant subgroups. Existing systematic reviews identify potential biomarkers of lithium response, but none directly address the conceptual issues that need to be addressed to enhance translation of research into precision prescribing of lithium. For example, although clinical syndrome subtyping of BD has not led to customized individual treatments, we emphasize the importance of assessing clinical response phenotypes in biomarker research. Also, we highlight the need to give greater consideration to the quality of prospective longitudinal monitoring of illness activity and the differentiation of non-response from partial or non-adherence with medication. It is unlikely that there is a single biomarker for lithium response or tolerability, so this review argues that more research should be directed toward the exploration of biosignatures. Importantly, we emphasize that an integrative science approach may improve the likelihood of discovering the optimal combination of clinical factors and multimodal biomarkers (e.g., blood omics, neuroimaging, and actigraphy derived-markers). This strategy could uncover a valid lithium response phenotype and facilitate development of a composite prediction algorithm. Lastly, this narrative review discusses how these strategies could improve eligibility criteria for lithium treatment in BD, and highlights barriers to translation to clinical practice including the often-overlooked issue of the cost-effectiveness of introducing biomarker tests in psychiatry.

Objective and quantitative equilibriometric evaluation of individual locomotor behaviour in schizophrenia: Translational and clinical implications

Psychiatry is the only medical specialty that lacks clinically applicable biomarkers for objective evaluation of the existing pathology at a single-patient level. On the basis of an original translational equilibriometric method for evaluation of movement patterns, we have introduced in the everyday clinical practice of psychiatry an easy-to-perform computerized objective quantification of the individual locomotor behaviour during execution of the Unterberger stepping test. For the last 20 years, we have gradually collected a large database of more than 1000 schizophrenic patients, their relatives, and matched psychiatric, neurological, and healthy controls via cross-sectional and longitudinal investigations. Comparative analyses revealed transdiagnostic locomotor similarities among schizophrenic patients, high-risk schizotaxic individuals, and neurological patients with multiple sclerosis and cerebellar ataxia, thus suggesting common underlying brain mechanisms. In parallel, intradiagnostic dissimilarities were revealed, which allow to separate out subclinical locomotor subgroups within the diagnostic categories. Prototypical qualitative (dysmetric and ataxic) locomotor abnormalities in schizophrenic patients were differentiated from 2 atypical quantitative ones, manifested as either hypolocomotion or hyperlocomotion. Theoretical analyses suggested that these 3 subtypes of locomotor abnormalities could be conceived as objectively measurable biomarkers of 3 schizophrenic subgroups with dissimilar brain mechanisms, which require different treatment strategies. Analogies with the prominent role of locomotor measures in some well-known animal models of mental disorders advocate for a promising objective translational research in the so far over-subjective field of psychiatry. Distinctions among prototypical, atypical, and diagnostic biomarkers, as well as between neuromotor and psychomotor locomotor abnormalities, are discussed. Conclusions are drawn about the translational and clinical implications of the new approach and its future perspectives.

The functional variant rs334558 of GSK3B is associated with remission in patients with depressive disorders

Purpose

GSK3B and AKT1 genes have been implicated in the pathogenesis of a number of psychiatric and neurological disorders. Furthermore, their genetic variants are associated with response to antidepressant pharmacotherapy. As the evidence is still incomplete and inconsistent, continuing efforts to investigate the role of these two genes in the pathogenesis and treatment of brain disorders is necessary. The aim of our study was thus to evaluate the association of variants of these two genes with depressive disorders and drug treatment response.

Patients and methods

In the present study, 222 patients with a depressive disorder who underwent pharmacological antidepressant treatment were divided into remitters and non-remitters following a 28-day course of pharmacotherapy. The association of a depressive disorder and remission rates with polymorphisms rs334558 in the GSK3B gene and rs1130214 and rs3730358 in the AKT1 gene was evaluated with a chi-square test.

Results

Neither of the studied genetic variants was associated with a depressive disorder. Furthermore, frequencies of alleles and genotypes for rs1130214 and rs3730358 were not different in the groups of remitters and non-remitters. However, the activating allele T of the functional polymorphism rs334558 was significantly associated with remission, when all types of antidepressant drugs were included. This association continued as a trend when only patients taking selective serotonin reuptake inhibitors were considered.

Conclusion

The present study provides support that the functional polymorphism rs334558 of GSK3B may play a role as a useful genetic and pharmacogenetic biomarker in the framework of personalized medicine approach.

Post-GWAS in Psychiatric Genetics: A Developmental Perspective on the "Other" Next Steps

As psychiatric genetics enters an era where gene identification is finally yielding robust, replicable genetic associations and polygenic risk scores, it is important to consider next steps and delineate how that knowledge will be applied to ultimately ameliorate suffering associated with substance use and psychiatric disorders. Much of the post-genome-wide association study discussion has focused on the potential of genetic information to elucidate the underlying biology and use this information for the development of more effective pharmaceutical treatments. In this review we focus on additional areas of research that should follow gene identification. By taking genetic findings into longitudinal, developmental studies, we can map the pathways by which genetic risk manifests across development, elucidating the early behavioral manifestations of risk, and studying how various environments and interventions moderate that risk across developmental stages. The delineation of risk across development will advance our understanding of mechanism, sex differences and risk and resilience processes in different racial/ethnic groups. Here, we review how the extant twin study literature can be used to guide these efforts. Together, these new lines of research will enable us to develop more informed, tailored prevention and intervention efforts.

Association analysis of ANK3 variants with bipolar disorder in the Korean population

BACKGROUND

Bipolar disorder (BD) is a major psychiatric disorder characterized by alternating mood episodes, including major depressive, hypomanic, and manic episodes. Previous genetic studies of BD have reported several genes as potentially associated with BD. The ANK3 gene has been identified as a possible BD susceptibility gene in genome-wide association analyses.

AIMS

The goal of the present study was to evaluate the association of ANK3 variants with BD in the Korean population.

METHODS

Based on previous results, two single nucleotide polymorphisms (SNPs), rs1938526 and rs10994336, were selected in the ANK3 gene. The study included 287 BD patients and 340 healthy controls. Case-control association and case-control haplotype analyses of the two ANK3 variants were performed.

RESULTS

No significant association was found of either single SNP with BD by case-control association analysis. However, rs1938526 and rs10994336 showed a significant association (overall p = 3.6 × 10^-11; permutation p = 0) in a case-control haplotype analysis.

CONCLUSIONS

The haplotype analysis results suggest that ANK3 variants rs1938526 and rs10994336 may confer susceptibility for BD in the Korean population. Association analysis revealed a probable genetic difference between Korean and Caucasian populations in the degree of ANK3 involvement in BD pathogenesis.