Applying dimensional psychopathology: transdiagnostic prediction of executive cognition using brain connectivity and inflammatory biomarkers

Characterizing the distinct imaging phenotypes, clinical behavior, and genetic vulnerability of brain maturational subtypes in mood disorders

BACKGROUND

Mood disorders are characterized by great heterogeneity in clinical manifestation. Uncovering such heterogeneity using neuroimaging-based individual biomarkers, clinical behaviors, and genetic risks, might contribute to elucidating the etiology of these diseases and support precision medicine.

METHODS

We recruited 174 drug-naïve and drug-free patients with major depressive disorder and bipolar disorder, as well as 404 healthy controls. T1 MRI imaging data, clinical symptoms, and neurocognitive assessments, and genetics were obtained and analyzed. We applied regional gray matter volumes (GMV) and quantile normative modeling to create maturation curves, and then calculated individual deviations to identify subtypes within the patients using hierarchical clustering. We compared the between-subtype differences in GMV deviations, clinical behaviors, cell-specific transcriptomic associations, and polygenic risk scores. We also validated the GMV deviations based subtyping analysis in a replication cohort.

RESULTS

Two subtypes emerged: subtype 1, characterized by increased GMV deviations in the frontal cortex, cognitive impairment, a higher genetic risk for Alzheimer's disease, and transcriptionally associated with Alzheimer's disease pathways, oligodendrocytes, and endothelial cells; and subtype 2, displaying globally decreased GMV deviations, more severe depressive symptoms, increased genetic vulnerability to major depressive disorder and transcriptionally related to microglia and inhibitory neurons. The distinct patterns of GMV deviations in the frontal, cingulate, and primary motor cortices between subtypes were shown to be replicable.

CONCLUSIONS

Our current results provide vital links between MRI-derived phenotypes, spatial transcriptome, genetic vulnerability, and clinical manifestation, and uncover the heterogeneity of mood disorders in biological and behavioral terms.

Unmasking the mental health scars of COVID-19: A longitudinal investigation of children and adolescents in post-lockdown China

The long-term mental health consequences of COVID-19 in children and adolescents remain unclear. We investigated the impact of COVID-19 infection on mental health after China's zero-COVID policy relaxation, focusing on symptom-specific and social-family risk factors for mental health issues in children and adolescents. In a longitudinal study, 8348 youths (aged 10-18) were assessed twice (T1: September to October 2022 and T2: April to May 2023). Mental health changes (Δ=T1-T2) were compared between COVID-19-infected (COVID+, n = 4108) and non-infected (COVID-, n = 4240). After balancing social-family confounding factors at T1 with propensity score-based inverse probability weights, multivariable logistic regression was employed to assess associations between COVID-19 infection and the onset/worsening of mental health symptoms. Multivariable logistic regression was conducted to explore specific acute COVID-19 symptoms and social-family risk factors associated with the onset/worsening of mental health symptoms in COVID + group. Compared to COVID- group, COVID + group exhibited lower overall mental health improvement (Δ). COVID + group was associated with increased risks of depression worsening (OR 1.20, 95 % CI 1.04-1.39), anxiety worsening (OR 1.30, 95 % CI 1.15-1.47), stress worsening (OR 1.23, 95 % CI 1.03-1.46), insomnia worsening (OR 1.21, 95 % CI 1.05-1.39), and emotional symptoms worsening (OR 1.72, 95 % CI 1.27-2.33). Moderate-to-severe difficulty thinking, breathlessness, and gastrointestinal symptoms were specific COVID-19 symptoms associated with worsening of various mental health outcomes. Furthermore, academic difficulties, economic disadvantages, family conflicts, food addiction, and alcohol consumption were identified as social-family risk factors for worsening mental health symptoms in COVID + youths. COVID-19 infection leaves lasting mental health scars in youths, extending beyond the acute phase. Specific symptoms, particularly cognitive dysfunction and respiratory/gastrointestinal distress play a significant role in this vulnerability. Social-family factors further modulate these effects, highlighting the need for comprehensive interventions that address both biological and psychosocial aspects. This study provides valuable insights for tailoring mental health support to youths navigating the consequences of the COVID-19 pandemic.

Transdiagnostic dimensions of symptoms and experiences associated with immune proteins in the continuity of psychosis

BACKGROUND

There is limited evidence as to whether the immune protein profile is associated with a particular symptomatology pattern across the psychosis continuum.

METHODS

We estimated two bifactor models of general and specific dimensions of psychotic experiences in unaffected siblings of patients (n = 52) and community controls (n = 200), and of psychotic symptoms in first-episode psychosis (FEP) patients (n = 110). We evaluated associations between these transdiagnostic dimensions and trait (TNF-α, IFN-γ), state (IL-6, IL-1β), and regulatory (TGF-β, IL-10, IL-4) cytokines. We explored whether schizophrenia genetic liability (schizophrenia polygenic risk score; SZ-PRS) modified the associations.

RESULTS

High levels of trait marker IFN-γ were associated with the severity of general psychosis dimension in the unaffected siblings and community controls, expanding to the depressive dimension in siblings and to the manic dimension in FEP. High TNF-α levels were associated with more positive psychotic experiences in unaffected siblings and manic symptoms in FEP. Low levels of state markers IL-6 and IL-1β were observed in unaffected siblings presenting more depressive experiences. Still, high levels of IL-6 and IL-1β were associated with the severity of the depressive and negative symptom dimensions at FEP. The severity of transdiagnostic dimension scores across the three groups was associated with lower regulatory cytokines. Exploratory analysis suggested that a high SZ-PRS contributed mostly to associations with psychotic dimensions.

CONCLUSIONS

IFN-γ mapped onto the multidimensional expression of psychosis, reinforcing the trait concept. State markers IL-6 and IL-1β may fluctuate along the spectrum. Dysfunction in the regulatory arm may disinhibit the inflammatory system. Associations with psychotic dimensions may be more prone to SZ-PRS susceptibility.

Neurocognitive Artificial Neural Network Models Are Superior to Linear Models at Accounting for Dimensional Psychopathology

In recent years, there has been debate about the optimal conceptualisation of psychopathology. Structural models of psychopathology have been developed to counter issues, including comorbidity and poor diagnostic stability prevalent within the traditional nosological approach. Regardless of the conceptualisation of psychological dysfunction, deficits in neurocognitive abilities have been claimed to be an aetiological feature of psychopathology. Explorations of the association between neurocognition and psychopathology have typically taken a linear approach, overlooking the potential interactive dynamics of neurocognitive abilities. Previously, we proposed a multidimensional hypothesis, where within-person interactions between neurocognitive domains are fundamental to understanding the role of neurocognition within psychopathology. In this study, we used previously collected psychopathology data for 400 participants on psychopathological symptoms, substance use, and performance on eight neurocognitive tasks and compared the predictive accuracy of linear models to artificial neural network models. The artificial neural network models were significantly more accurate than the traditional linear models at predicting actual (a) lower-level and (b) high-level dimensional psychopathology. These results provide support for the multidimensional hypothesis: that the study of non-linear interactions and compensatory neurocognitive profiles are integral to understanding the functional associations between neurocognition and of psychopathology.

Clinical Value of Inflammatory and Neurotrophic Biomarkers in Bipolar Disorder: A Systematic Review and Meta-Analysis

Bipolar disorder (BD) is a multifactorial chronic psychiatric disease highly defined by genetic, clinical, environmental and social risk factors. The present systematic review and meta-analysis aimed to examine the relationship between inflammatory and neurotrophic factors and clinical, social and environmental factors involved in the development and the characterization of BD. Web of Science, PubMed, PsycINFO, Scopus and Science Direct were searched by two independent reviewers. The systematic review was registered in PROSPERO (CRD42020180626). A total of 51 studies with 4547 patients with a diagnosis of BD were selected for systematic review. Among them, 18 articles were included for meta-analysis. The study found some evidence of associations between BDNF and/or inflammatory factors and different stressors and functional and cognitive impairment, but limitations prevented firm conclusions. The main finding of the meta-analysis was a negative correlation between circulating levels of BDNF and depression severity score (standardized mean difference = −0.22, Confidence Interval 95% = −0.38, −0.05, p = 0.01). Evidence indicates that BDNF has a role in the depressive component of BD. However, the poor consistency found for other inflammatory mediators clearly indicates that highly controlled studies are needed to identity precise biomarkers of this disorder.