Transdiagnostic biomarker approaches to mental health disorders: Consideration of symptom complexity, comorbidity and context

Acceptability, User Satisfaction, and Feasibility of an App-Based Support Service During the COVID-19 Pandemic in a Psychiatric Outpatient Setting: Prospective Longitudinal Observational Study

BACKGROUND

Patients with mental disorders often have difficulties maintaining a daily routine, which can lead to exacerbated symptoms. It is known that apps can help manage mental health in a low-threshold way and can be used in therapeutic settings to complement existing therapies.

OBJECTIVE

The aim of this study was to evaluate the acceptability, usability, and feasibility of an app-based support service specifically developed for outpatients with severe mental disorders in addition to regular face-to-face therapy during the COVID-19 pandemic.

METHODS

Patients in a psychiatric outpatient department at a German university hospital were invited to use an app-based support service designed transdiagnostically for mental disorders for 4 weeks. The app included 7 relaxation modules, consisting of video, audio, and psychoeducational text; ecological momentary assessment-like questionnaires on daily mood answered via a visual smiley-face scale; and an activity button to record and encourage daily activities. Standardized questionnaires at baseline (T0; preintervention time point) and after 4 weeks (T2; postintervention time point) were analyzed. Feedback via the smiley-face scale was provided after using the app components (T1; during the intervention). Measures included depressive symptoms, quality of life, treatment credibility and expectancy, and satisfaction. Furthermore, participation rates, use of app modules and the activity button, and daily mood and the provided feedback were analyzed (T2).

RESULTS

In total, 57 patients participated in the study, and the data of 38 (67%) were analyzed; 17 (30%) dropped out. Satisfaction with the app was high, with 53% (30/57) of the participants stating being rather satisfied or satisfied. Furthermore, 79% (30/38) of completers stated they would be more likely or were definitely likely to use an app-based support service again and recommend it. Feasibility and acceptability were high, with nearly half (18/38, 47%) of the completers trying relaxation modules and 71% (27/38) regularly responding to the ecological momentary assessment-like questionnaire between 15 and 28 times (mean 19.91, SD 7.57 times). The activity button was used on average 12 (SD 15.72) times per completer, and 58% (22/38) felt "definitely" or "rather" encouraged to perform the corresponding activities. Depressive symptomatology improved significantly at the postintervention time point (P=.02). Quality of life showed a nonsignificant increase in the physical, psychological, and social domains (P=.59, P=.06, and P=.42, respectively) and a significant improvement in the environment domain (P=.004). Treatment credibility and expectancy scores were moderate and significantly decreased at T2 (P=.02 and P<.001, respectively). Posttreatment expectancy scores were negatively associated with posttreatment depressive symptomatology (r=-0.36; P=.03).

CONCLUSIONS

App-based programs seem to be an accessible tool for stabilizing patients with severe mental disorders, supporting them in maintaining a daily routine, complementing existing face-to-face treatments, and overall helping respond to challenging situations such as the COVID-19 pandemic.

Sex differences in the inflammation-depression link: A systematic review and meta-analysis

Major Depressive Disorder (MDD) is a heterogeneous disorder that affects twice as many women than men. Precluding advances in more tailored and efficacious treatments for depression is the lack of reliable biomarkers. While depression is linked to elevations in inflammatory immune system functioning, this relationship is not evident among all individuals with depression and may vary based on symptom subtypes and/or sex. This systematic review and meta-analysis examined whether inflammatory immune peripheral markers of depression are sex-specific. PRISMA guidelines were followed for the systematic review, and a comprehensive search strategy that identified studies from PubMed and PsycInfo was applied. Studies were included if they reported C-reactive protein (CRP), interleukin (IL)-6, tumor necrosis factor (TNF)-α and/or IL-1β for males and/or females among depressed and healthy adults. We identified 23 studies that satisfied these inclusion criteria. Random-effects meta-analysis models were fit, and measures of association were summarized between levels of circulating markers of inflammation in depressed and healthy males and females. Sex-based analyses revealed elevated levels of CRP among females with depression (Cohen's d = 0.19) relative to their healthy counterparts (p = 0.02), an effect not apparent among males (Cohen's d = -0.01). Similarly, levels of IL-6 were increased among females with depression compared to healthy controls (Cohen's d = 0.51; p = 0.04), but once again this was not found among males (Cohen's d = 0.16). While TNF-α levels were elevated among individuals with depression compared to controls (p = 0.01), no statistically significant sex differences were found. The meta-analysis for IL-1β resulted in only three articles, and thus, results are presented in the supplemental section. This meta-analysis advances our understanding of the unique involvement of inflammatory biomarkers in depression among men and women, which may help inform more tailored sex-specific treatment approaches in the future.

Inflammation as an aetiological trigger for depressive symptoms in a prospective cohort of patients with inflammatory bowel disease

OBJECTIVE

Inflammatory bowel disease (IBD) is often comorbid with mood disorders and depressive symptoms. The aetiology of depressive symptoms in IBD, however, remains largely unknown. Consistent with the inflammatory hypothesis of depression, the aim of this study was to explore the prospective associations between inflammatory biomarkers and depressive symptoms in a cohort of IBD patients with and without a previous clinical diagnosis of mood disorder.

METHOD

IBD clinical activity was determined using the Harvey-Bradshaw Index for CD and the Partial Mayo score for UC; serum C-reactive protein (CRP) and faecal calprotectin (fCAL) were used as biomarkers of systemic and intestinal inflammation, respectively. Participants were administered the Hospital Anxiety and Depression Scale-depression (HADS-D) at baseline and 1-year follow-up.

RESULTS

Eighty-four participants (50 ± 16 years; 75% UC and 25% CD) were included in the main analyses. Longitudinal moderated regression models showed that baseline CRP significantly predicted follow-up HADS-D scores among individuals with a previous mood disorder diagnosis (β = 0.843, p < .001), but not among individuals without (β = -0.013, p = .896), after controlling for baseline HADS-D scores, body mass index, IBD phenotype, sex, and perceived stress. Likely due to lower power, results on FCAL (n = 31) were not statistically significant.

CONCLUSION

This study suggests that IBD patients with previous diagnosis of mood disorder may be at higher risk of inflammation-related depressive symptoms.

Biomarker-Guided Tailored Therapy in Major Depression

This chapter provides a comprehensive examination of a broad range of biomarkers used for the diagnosis and prediction of treatment outcomes in major depressive disorder (MDD). Genetic, epigenetic, serum, cerebrospinal fluid (CSF), and neuroimaging biomarkers are analyzed in depth, as well as the integration of new technologies such as digital phenotyping and machine learning. The intricate interplay between biological and psychological elements is emphasized as essential for tailoring MDD management strategies. In addition, the evolving link between psychotherapy and biomarkers is explored to uncover potential associations that shed light on treatment response. This analysis underscores the importance of individualized approaches in the treatment of MDD that integrate advanced biological insights into clinical practice to improve patient outcomes.

Does the current state of biomarker discovery in autism reflect the limits of reductionism in precision medicine? Suggestions for an integrative approach that considers dynamic mechanisms between brain, body, and the social environment

Over the past decade, precision medicine has become one of the most influential approaches in biomedical research to improve early detection, diagnosis, and prognosis of clinical conditions and develop mechanism-based therapies tailored to individual characteristics using biomarkers. This perspective article first reviews the origins and concept of precision medicine approaches to autism and summarises recent findings from the first "generation" of biomarker studies. Multi-disciplinary research initiatives created substantially larger, comprehensively characterised cohorts, shifted the focus from group-comparisons to individual variability and subgroups, increased methodological rigour and advanced analytic innovations. However, although several candidate markers with probabilistic value have been identified, separate efforts to divide autism by molecular, brain structural/functional or cognitive markers have not identified a validated diagnostic subgroup. Conversely, studies of specific monogenic subgroups revealed substantial variability in biology and behaviour. The second part discusses both conceptual and methodological factors in these findings. It is argued that the predominant reductionist approach, which seeks to parse complex issues into simpler, more tractable units, let us to neglect the interactions between brain and body, and divorce individuals from their social environment. The third part draws on insights from systems biology, developmental psychology and neurodiversity approaches to outline an integrative approach that considers the dynamic interaction between biological (brain, body) and social mechanisms (stress, stigma) to understanding the origins of autistic features in particular conditions and contexts. This requires 1) closer collaboration with autistic people to increase face validity of concepts and methodologies; (2) development of measures/technologies that enable repeat assessment of social and biological factors in different (naturalistic) conditions and contexts, (3) new analytic methods to study (simulate) these interactions (including emergent properties), and (4) cross-condition designs to understand which mechanisms are transdiagnostic or specific for particular autistic sub-populations. Tailored support may entail both creating more favourable conditions in the social environment and interventions for some autistic people to increase well-being.

Striatal reactivity during emotion and reward relates to approach-avoidance conflict behaviour and is altered in adults with anxiety or depression

BACKGROUND

We have previously reported activation in reward, salience and executive control regions during functional MRI (fMRI) using an approach-avoidance conflict (AAC) decision-making task with healthy adults. Further investigations into how anxiety and depressive disorders relate to differences in neural responses during AAC can inform their understanding and treatment. We tested the hypothesis that people with anxiety or depression have altered neural activation during AAC.

METHODS

We compared 118 treatment-seeking adults with anxiety or depression and 58 healthy adults using linear mixed-effects models to examine group-level differences in neural activation (fMRI) during AAC decision-making. Correlational analyses examined relationships between behavioural and neural measures.

RESULTS

Adults with anxiety or depression had greater striatal engagement when reacting to affective stimuli (p = 0.008, d = 0.31) regardless of valence, and weaker striatal engagement during reward feedback (p = 0.046, d = -0.27) regardless of the presence of monetary reward. They also had blunted amygdala activity during decision-making (p = 0.023, d = -0.32) regardless of the presence of conflict. Across groups, approach behaviour during conflict decision-making was inversely correlated with striatal activation during affective stimuli (p < 0.001, r = -0.28) and positively related to striatal activation during reward feedback (p < 0.001, r = 0.27).

LIMITATIONS

Our transdiagnostic approach did not allow for comparisons between specific anxiety disorders, and our cross-sectional approach did not allow for causal inference.

CONCLUSION

Anxiety and depression were associated with altered neural responses to AAC. Findings were consistent with the role of the striatum in action selection and reward responsivity, and they point toward striatal reactivity as a future treatment target. Blunting of amygdala activity in anxiety or depression may indicate a compensatory response to inhibit affective salience and maintain approach.

High depression symptomatology and mental pain characterize suicidal psychiatric patients

BACKGROUND

Symptoms of depression are transdiagnostic heterogenous features frequently assessed in psychiatric disorders, that impact the response to first-line treatment and are associated with higher suicide risk. This study assessed whether severe mental pain could characterize a specific phenotype of severely depressed high-risk psychiatric patients. We also aimed to analyze differences in treatments administered.

METHODS

2,297 adult patients (1,404 females and 893 males; mean age = 43.25 years, SD = 15.15) treated in several Italian psychiatric departments. Patients were assessed for psychiatric diagnoses, mental pain, symptoms of depression, hopelessness, and suicide risk.

RESULTS

More than 23% of the patients reported high depression symptomatology and high mental pain (HI DEP/HI PAIN). Compared to patients with lower symptoms of depression, HI DEP/HI PAIN is more frequent among females admitted to an inpatient department and is associated with higher hopelessness and suicide risk. In addition, HI DEP/HI PAIN (compared to both patients with lower symptoms of depression and patients with higher symptoms of depression but lower mental pain) were more frequently diagnosed in patients with personality disorders and had different treatments.

CONCLUSIONS

Patients reporting severe symptoms of depression and high mental pain presented a mixture of particular dangerousness (high trait hopelessness and the presence of suicide ideation with more frequency and less controllability and previous suicide behaviors). The presence of severe mental pain may act synergically in expressing a clinical phenotype that is likewise treated with a more complex therapeutic regime than that administered to those experiencing symptoms of depression without mental pain.

A Novel Adaptive Affective Cognition Analysis Model for College Students Using a Deep Convolution Neural Network and Deep Features

Currently, under the impact of the COVID-19, college students are facing increasingly elevated employment pressure and higher education pressure. This can easily cause a huge psychological burden on them, causing affective cognition problems such as anxiety and depression. In the long run, this is not conducive to students’ physical and mental health, nor is it conducive to the healthy development of the school and even the whole society. Therefore, it is imperative to build a novel adaptive affective cognition analysis model for college students. In particular, in the context of smart cities and smart China, many universities have opened the smart campus mode, which provides a huge data resource for our research. Due to problems of the low real-time evaluation and single data source in traditional questionnaire evaluation methods, evaluation errors are prone to occur, which in turn interferes with subsequent treatment. Therefore, for the purpose of alleviating the above deficiencies and improving the efficiency and accuracy of the affective cognition analysis model of college students, this paper studies the adaptive affective cognition analysis method of college students on basis of deep learning. First, because students’ psychological problems are often not sudden, on the contrary, most of these abnormalities will leave traces in their daily activities. Therefore, this paper constructs a multisource dataset with the access control data, network data, and learning data collected from the smart campus platform to describe the affective cognition status of students. Second, the multisource dataset is divided into two categories: image and text, and the CNN model is introduced to mine the psychological characteristics of college students, so as to provide a reference for the subsequent affective cognition state assessment. Finally, simulation tests are developed to confirm the viability of the technique suggested in this research. The experiments demonstrate that the accuracy of the assessment model is significantly increased because it can fully reflect the heterogeneity and comprehensiveness of the data. This also highlights that the new method has a wide range of potential applications in the modern campus setting and is also helpful in fostering the accuracy and depth of college students’ work on their affective cognition.

Visual-stress-related cortical excitability as a prospective marker for symptoms of depression and anxiety in young people

Visual stress is thought to reflect cortical excitability and has been associated with many neurological, neuropsychiatric, and neurodevelopmental conditions. However, its relationships with symptoms of depression and anxiety have not yet been elucidated. We conducted two separate studies to first examine visual stress in a longitudinal community sample of 104 participants (aged 12-24) in association with prospective symptoms of depression, anxiety, and distress after 3 months, and subsequently in a cross-sectional epidemiological sample of 530 participants (aged 15-24) to validate its associations with current mood and distress symptoms. The Pattern Glare Test was used to examine visual stress to three grating patterns with the spatial frequencies (SF) of 0.3, 2.3, and 9.4 cycles per degree (cpd). Other known factors of mental health, including functioning, as well as resilience, hopelessness, and loneliness, were also assessed at baseline. In both studies, we showed that perceptual distortions were highest toward the pattern with mid-SF (2.3 cpd). Multiple linear regression analyses revealed that greater visual stress was significantly associated with not only baseline but also 3-month symptom outcomes, even when accounting for age, years of education, days of no functioning, resilience, hopelessness, and loneliness. Our findings suggest the importance of visual stress in understanding and predicting poor mental health outcomes. As mental health can lead to far-reaching consequences that extend to adulthood, our findings may inform state-of-the-art innovative strategies for the prediction of poor mental health outcomes and suggest visual stress as a potential marker for early risk detection among young people.

Developing symptom clusters: linking inflammatory biomarkers to depressive symptom profiles

Considering the burden of depression and the lack of efficacy of available treatments, there is a need for biomarkers to predict tailored or personalized treatments. However, identifying reliable biomarkers for depression has been challenging, likely owing to the vast symptom heterogeneity and high rates of comorbidity that exists. Examining biomarkers that map onto dimensions of depression as well as shared symptoms/constructs that cut across disorders could be most effective for informing personalized treatment approaches. With a sample of 539 young adults, we conducted a principal component analysis (PCA) followed by hierarchical cluster analysis to develop transdiagnostic clusters of depression and anxiety symptoms. We collected blood to assess whether neuroendocrine (cortisol) and inflammatory profiles (C-reactive protein (CRP), Interleukin (IL)-6, and tumor necrosis factor (TNF) - α) could be used to differentiate symptom clusters. Six distinct clusters were identified that differed significantly on symptom dimensions including somatic anxiety, general anxiety, anhedonia, and neurovegetative depression. Moreover, the neurovegetative depression cluster displayed significantly elevated CRP levels compared to other clusters. In fact, inflammation was not strongly associated with overall depression scores or severity, but rather related to specific features of depression marked by eating, appetite, and tiredness. This study emphasizes the importance of characterizing the biological underpinnings of symptom dimensions and subtypes to better understand the etiology of complex mental health disorders such as depression.

Narcissistic Personality and Its Relationship with Post-Traumatic Symptoms and Emotional Factors: Results of a Mediational Analysis Aimed at Personalizing Mental Health Treatment

Background: Narcissism is characterized by entitlement, grandiose fantasies and the need for admiration. This personality trait has been associated with both traumatic experiences and emotional problems. Most studies have only focused on narcissism in the context of childhood trauma and negative emotional factors. However, dimensions of grandiose narcissism such as authority have been linked to adaptive outcomes. Furthermore, narcissism might not be linked only to negative childhood experiences; it may also be associated with the presence of post-traumatic symptoms. Therefore, the present study aimed to assess the associations between narcissism and the frequency and severity of post-traumatic symptoms and emotional factors (resilience capacity, emotional regulation, positive and negative affect, intolerance of uncertainty and perceived stress), as well as the possible mediational role of the latter in the relationship between narcissism and post-traumatic symptoms. Method: A total of 115 healthy young psychology undergraduates and their relatives, aged from 18 to 40 years, were asked to complete a set of questionnaires to evaluate the aforementioned variables. Results: The results showed that most of the grandiose narcissism dimensions were positively related to emotional adaptive outcomes, except exploitativeness and entitlement. The negative associations observed between the frequency and severity of post-traumatic symptoms and narcissism (self-sufficiency) were mediated by affect and resilience, which were in turn positively associated with the majority of the narcissism dimensions. Both positive affect and resilience were important factors mediating the association between grandiose narcissism and post-traumatic symptoms. Conclusions: Our findings reaffirm the need to assess not only desirable personality traits, but also ones that are not initially desirable, before pathologizing them. This consideration may be essential to achieve a personalized approach to the prevention of mental health problems, and promotion of positive emotions, in the general population.

Editorial commentary on the special issue emerging psychoneuroimmunology research: Future leaders in focus

The theme of this BBI-Health special issue is to promote the research, creativity and forward-thinking of future key opinion leaders in the field of psychoneuroimmunology (PNI). We asked contributing researchers to identify new ideas and spaces for innovation to map out the future trajectory of our discipline. This special issue provides global and diverse views from early career investigators focused on science, society, and/or policy, with an emphasis on diversity in all its aspects. The common thread weaving through the articles contained in this special issue is that all authors were invited to consider the future of PNI while they were experiencing the global COVID-19 lockdowns that slowed down or even prevented them from access to their "hands-on" research. The contributors vary from Master level to assistant professors, and all have already significantly contributed to the field of PNI. Each contributor has provided a photograph and short biography alongside their written perspectives. We hope that you will enjoy learning about their visions for the future of PNI and will join us with enthusiasm as we watch our field grow through the advancement of their scientific careers.