Mid Sweden University

BackgroundAnxiety and depression are the most prevalent mental health disorders. The first-line treatment is antidepressants, such as serotonin reuptake inhibitors, but benzodiazepines and antihistamines are also used to treat anxiety. Only one-third of patients achieve remission with first-line treatment. Identifying responders and nonresponders to monotherapy prior to treatment could increase remission rates and reduce dropout. The aim of the current study was to predict response to antidepressants, benzodiazepines, and antihistamines from polygenic risk scores (PRSs) in individuals with anxiety and/or depression symptoms.MethodsWe identified 2515 individuals in a genotyped cohort in the Swedish Twin Registry who had been prescribed drugs for anxiety and/or depression. Of these individuals, 1037 received monotherapy (555 with antidepressants, 169 with benzodiazepines, and 313 with antihistamines). The remaining 1478 individuals switched or added more drugs during the assessment period (2005–2018). The accuracy of 42 PRSs for psychiatric diagnoses as well as for nonclinical phenotypes in predicting mono- versus multitherapy was assessed using logistic regression.ResultsMonotherapy with benzodiazepines was predicted by a PRS for depressive symptoms indexed by the Patient Health Questionnaire (odds ratio [OR] = 1.29), while monotherapy with antihistamines was predicted by a PRS for lifetime anxiety disorder (OR = 1.25) and a PRS for schizophrenia (OR = 1.24). None of the investigated PRSs significantly predicted monotherapy with antidepressants.ConclusionsReal-world data suggest that monotherapy with benzodiazepines or antihistamines can be predicted from PRSs related to anxiety, depression, and schizophrenia.

Background: Although many epidemiological studies show an association of cigarette smoking with suicide the path to the latter is not well understood. Objective: Using causal inference methodology with observational data, to examine if smoking leads indirectly to suicide through mental health hospitalization. Design: The study used 11 waves of a cross-sectional national health survey that was linked with hospitalization and death registers. Methods: The data came from Canadian Community Health Survey respondents (n = 723 665) between the years 2000 and 2014. These respondents agreed to link their data with hospitalization and death registers and were followed for an average of 9.18 (SD: 4.42; range: 3 to 17) years. Mediation models, one each for men and women, were created in which lifetime daily smoking was the exposure, mental health hospitalization was the mediator, and death by suicide was the outcome, adjusting for 11 covariates reported at survey participation. Results: In both men and women, the direct effect of daily smoking was larger than the indirect effect through hospitalization for mental conditions. The direct effect of smoking was 1.76 (95% CI: 1.47-2.10) for men and 2.60 (95% CI: 1.90-3.57) for women. The indirect effect through mental health hospitalization was 1.07 (95% CI: 1.05-1.09) for men and 1.04 (95% CI: 0.99-1.09) for women. Conclusion: A relatively smaller proportion of the daily smoking-suicide association is transmitted indirectly through mental health hospitalizations compared to a direct effect. Suicide interventions focusing on people hospitalized for mental disorders may miss many suicidal people, so primary prevention and secondary prevention of smoking are crucial.

Anxiety and depression commonly occur together resulting in worse health outcomes than when they occur in isolation. We aimed to determine whether the genetic liability for comorbid anxiety and depression was greater than when anxiety or depression occurred alone. Data from 12,792 genotyped twins (ages 38–85) were analysed, including 1,986 complete monozygotic and 1,594 complete dizygotic pairs. Outcomes were prescription of antidepressant and anxiolytic drugs, as defined by the World Health Organization Anatomical Therapeutic Chemical Classification System (ATC) convention, for comorbid anxiety and depression (n = 1028), anxiety only (n = 718), and depression only (n = 484). Heritability of each outcome was estimated using twin modelling, and the influence of common genetic variation was assessed from polygenic scores (PGS) for depressive symptoms, anxiety, and 40 other traits. Heritability of comorbid anxiety and depression was 79% compared with 41% for anxiety and 50% for depression alone. The PGS for depressive symptoms likewise predicted more variation in comorbid anxiety and depression (adjusted odds ratio per SD PGS = 1.53, 95% CI = 1.43–1.63; ΔR2 = 0.031, ΔAUC = 0.044) than the other outcomes, with nearly identical results when comorbid anxiety and depression was defined by International Classification of Diseases (ICD) diagnoses (adjusted odds ratio per SD PGS = 1.70, 95% CI = 1.53–1.90; ΔR2 = 0.036, ΔAUC = 0.051). Individuals in the highest decile of PGS for depressive symptoms had over 5 times higher odds of being prescribed medication for comorbid anxiety and depression compared to those in the lowest decile. While results on a predominant role of depressive symptoms may have been biased by the size and heterogeneity of available data bases, they are consistent with the conclusion that genetic factors explain substantially more variation in comorbid anxiety and depression than anxiety or depression alone.

Pavlovian fear conditioning is a fundamental process in both health and disease. We investigate its neural correlates and sources of variability using harmonized functional magnetic resonance imaging data from 2199 individuals across nine countries, including 1888 healthy individuals and 311 with anxiety-related or depressive disorders. Using mega-analysis and normative modeling, we show that fear conditioning consistently engages brain regions within the "central autonomic-interoceptive" or "salience" network. Several task variables strongly modulate activity in these regions, contributing to variability in neural responses. Additionally, brain activation patterns differ between healthy individuals and those with anxiety-related or depressive disorders, with distinct profiles characterizing specific disorders such as post-traumatic stress disorder and obsessive-compulsive disorder. While the neural correlates of fear conditioning are highly generalizable at the population level, variability arises from differences in task design and clinical status, highlighting the importance of methodological diversity in capturing fear learning mechanisms.

Background Stress-induced Exhaustion Disorder (ED) is associated with work absenteeism and adverse health outcomes. Currently, little is known regarding how the symptoms of ED are interrelated and whether the patterns of symptoms influence treatment outcomes. To this end, the current study applied network analyses on ED patients participating in a multimodal intervention.Methods The first aim of the study was to explore the internal relationships between exhaustion symptoms and identify symptoms that were more closely related than others. A second aim was to examine whether the baseline symptom network of non-responders to treatment was more closely connected than the baseline symptom networks of responders, by comparing the sum of all absolute partial correlations in the respective groups' symptom network. This comparison was made based on the hypothesis that a more closely connected symptom network before treatment could indicate poorer treatment outcomes. Network models were constructed based on self-rated ED symptoms in a large sample of patients (n = 915) participating in a 24-week multimodal treatment program with a 12-month follow-up.Results The internal relations between self-rated exhaustion symptoms were stable over time despite markedly decreased symptom levels throughout participation in treatment. Symptoms of limited mental stamina and negative emotional reactions to demands were consistently found to be the most closely related to other ED symptoms. Meanwhile, sleep quality and irritability were weakly related to other exhaustion symptoms. The symptom network for the full sample became significantly more closely connected from baseline to the end of treatment and 12-month follow-up. The symptom network of non-responders to treatment was not found to be more closely connected than the symptom network of responders at baseline.Conclusions The results of the current study suggest symptoms of limited mental stamina and negative emotional reactions to demands are central ED symptoms throughout treatment, while symptoms of irritability and sleep quality seem to have a weak relation to other symptoms of ED. The implications of these findings are discussed in relation to the conceptualization, assessment, and treatment of ED.Trial registration The clinical trial was registered on Clinicaltrials.gov 2017-12-02 (Identifier: NCT03360136).

Neuroanatomical findings on youth anxiety disorders are notoriously difficult to replicate, small in effect size and have limited clinical relevance. These concerns have prompted a paradigm shift toward highly powered (that is, big data) individual-level inferences, which are data driven, transdiagnostic and neurobiologically informed. Here we built and validated supervised neuroanatomical machine learning models for individual-level inferences, using a case–control design and the largest known neuroimaging database on youth anxiety disorders: the ENIGMA-Anxiety Consortium (N = 3,343; age = 10–25 years; global sites = 32). Modest, yet robust, brain-based classifications were achieved for specific anxiety disorders (panic disorder), but also transdiagnostically for all anxiety disorders when patients were subgrouped according to their sex, medication status and symptom severity (area under the receiver operating characteristic curve, 0.59–0.63). Classifications were driven by neuroanatomical features (cortical thickness, cortical surface area and subcortical volumes) in fronto-striato-limbic and temporoparietal regions. This benchmark study within a large, heterogeneous and multisite sample of youth with anxiety disorders reveals that only modest classification performances can be realistically achieved with machine learning using neuroanatomical data.

Childhood maltreatment (CM) is thought to be associated with altered responses to social stimuli and interpersonal signals. However, limited evidence exists that CM is linked to larger comfortable interpersonal distance (CID) – the physical distance humans prefer towards others during social interactions. However, no previous study has investigated this association in a comprehensive sample, yielding sufficient statistical power. Moreover, preliminary findings are limited to the European region. Finally, it is unclear how CM affects CID towards different interaction partners, and whether CID is linked to social functioning and attachment. To address these outstanding issues, adults (N = 2986) from diverse cultures and socio-economic strata completed a reaction time task measuring CID towards an approaching stranger and friend. Higher CM was linked to a larger CID towards both friends and strangers. Moreover, insecure attachment and less social support were associated with larger CID. These findings demonstrate for the first time that CM affects CID across countries and cultures, highlighting the robustness of this association.

Objective: Specific phobia is a common anxiety disorder, but the literature on associated brain structure alterations exhibits substantial gaps. The ENIGMA Anxiety Working Group examined brain structure differences between individuals with specific phobias and healthy control subjects as well as between the animal and blood-injection-injury (BII) subtypes of specific phobia. Additionally, the authors investigated associations of brain structure with symptom severity and age (youths vs. adults). Methods: Data sets from 31 original studies were combined to create a final sample with 1,452 participants with phobia and 2,991 healthy participants (62.7% female; ages 5-90). Imaging processing and quality control were performed using established ENIGMA protocols. Subcortical volumes as well as cortical surface area and thickness were examined in a preregistered analysis. Results: Compared with the healthy control group, the phobia group showed mostly smaller subcortical volumes, mixed surface differences, and larger cortical thickness across a substantial number of regions. The phobia subgroups also showed differences, including, as hypothesized, larger medial orbitofrontal cortex thickness in BII phobia (N=182) compared with animal phobia (N=739). All findings were driven by adult participants; no significant results were observed in children and adolescents. Conclusions: Brain alterations associated with specific phobia exceeded those of other anxiety disorders in comparable analyses in extent and effect size and were not limited to reductions in brain structure. Moreover, phenomenological differences between phobia subgroups were reflected in diverging neural underpinnings, including brain areas related to fear processing and higher cognitive processes. The findings implicate brain structure alterations in specific phobia, although subcortical alterations in particular may also relate to broader internalizing psychopathology.

Detecting and responding to threat engages several neural nodes including the amygdala, hippocampus, insular cortex, and medial prefrontal cortices. Recent propositions call for the integration of more distributed neural nodes that process sensory and cognitive facets related to threat. Integrative, sensitive, and reproducible distributed neural decoders for the detection and response to threat and safety have yet to be established. We combine functional MRI data across varying threat conditioning and negative affect paradigms from 1465 participants with multivariate pattern analysis to investigate distributed neural representations of threat and safety. The trained decoders sensitively and specifically distinguish between threat and safety cues across multiple datasets. We further show that many neural nodes dynamically shift representations between threat and safety. Our results establish reproducible decoders that integrate neural circuits, merging the well-characterized ‘threat circuit’ with sensory and cognitive nodes, discriminating threat from safety regardless of experimental designs or data acquisition parameters. 

The Sussex-Oxford Compassion Scales (SOCS) are recently developed measures of compassion, which have showed support for a five-factor structure for both other-compassion (SOCS-O) and self-compassion (SOCS-S). The study aimed to validate the Swedish translations of both the SOCS-O and the SOCS-S. A sample of adult participants was randomly split into either an exploratory sample (N = 403) or a replication sample (N = 402). The exploratory sample was used for both exploratory factor analysis and confirmatory factor analysis. In the replication sample, we (1) used CFA to validate results from the exploratory sample, (2) assessed measurement invariance for different groups (gender, nationality, age), and (3) evaluated psychometric properties using local fit. Results from both sub-samples support the presence of five-factor models for both SOCS-O (using 19 items) and SOCS-S (using 20 items). For both scales, measurement invariance is supported for all grouping variables, and local psychometric properties indicate good internal consistency with fairly good discriminant and convergent validity. This study supports the five-factor model of both other-compassion and self-compassion, respectively, and shows that the Swedish versions of both SOCS-O and SOCS-S are reliable and valid instruments that can be used to index compassion with general adult populations in Sweden and Finland.