Competing influences on healthy food choices: Mindsetting versus contextual food cues.

Food choices are influenced by one's current mindset, suggesting that supporting health (vs. a palatability) mindsets could improve daily food choices. The question rises, however, to what extent internal mindsets still guide choices when people are exposed to external food-context stimuli in an obesogenic environment. To examine these two competing effects we induced health vs. palatability mindsets, and investigated the robustness of the mindset effect by presenting food-context stimuli during a Pavlovian-to-Instrumental-Transfer (PIT) task in two separate cohorts of 102 (76 females) Dutch and 120 (60 females) German participants. For the mindset induction, participants rated food items on visual analogue scales (VAS), based on healthiness and palatability, respectively. In each cohort, half of the participants received a health, the other half a palatability mindset induction. Additionally, we explored whether 'mindset triggers' could be used to further shape behavior. Triggers were established by placing unfamiliar logos at the extreme ends of the VASs used for the mindset inductions. Independent of the mindset, food-associated stimuli influenced food choices in accordance with the previously learned association in each test phase. Health mindset induction biased food choices towards healthier, palatability mindset towards unhealthier choices in the first cohort, but not in the second. The mindset triggers had a more robust effect. These induced healthier (triggers for healthy and not-palatable) and unhealthier (triggers for unhealthy and palatable) food choices in both cohorts alike. Interestingly, these effects did not tamper with the overall effect of Pavlovian cues and were thus true in the presence and absence of food-context stimuli. Therefore, we show that, in our experimental setting, food-associated mindset triggers can be used to bias food choices towards a healthy snack even in an obesogenic environment.

Are you laughing at me? Neural correlates of social intent attribution to auditory and visual laughter.

Laughter is a multifaceted signal, which can convey social acceptance facilitating social bonding as well as social rejection inflicting social pain. In the current study, we addressed the neural correlates of social intent attribution to auditory or visual laughter within an fMRI study to identify brain areas showing linear increases of activation with social intent ratings. Negative social intent attributions were associated with activation increases within the medial prefrontal cortex/anterior cingulate cortex (mPFC/ACC). Interestingly, negative social intent attributions of auditory laughter were represented more rostral than visual laughter within this area. Our findings corroborate the role of the mPFC/ACC as key node for processing "social pain" with distinct modality-specific subregions. Other brain areas that showed an increase of activation included bilateral inferior frontal gyrus and right superior/middle temporal gyrus (STG/MTG) for visually presented laughter and bilateral STG for auditory presented laughter with no overlap across modalities. Similarly, positive social intent attributions were linked to hemodynamic responses within the right inferior parietal lobe and right middle frontal gyrus, but there was no overlap of activity for visual and auditory laughter. Our findings demonstrate that social intent attribution to auditory and visual laughter is located in neighboring, but spatially distinct neural structures.

A longitudinal approach to biological psychiatric research: The PsyCourse study.

In current diagnostic systems, schizophrenia and bipolar disorder are still conceptualized as distinct categorical entities. Recently, both clinical and genomic evidence have challenged this Kraepelinian dichotomy. There are only few longitudinal studies addressing potential overlaps between these conditions. Here, we present design and first results of the PsyCourse study (N = 891 individuals at baseline), an ongoing transdiagnostic study of the affective-to-psychotic continuum that combines longitudinal deep phenotyping and dimensional assessment of psychopathology with an extensive collection of biomaterial. To provide an initial characterization of the PsyCourse study sample, we compare two broad diagnostic groups defined by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) classification system, that is, predominantly affective (n = 367 individuals) versus predominantly psychotic disorders (n = 524 individuals). Depressive, manic, and psychotic symptoms as well as global functioning over time were contrasted using linear mixed models. Furthermore, we explored the effects of polygenic risk scores for schizophrenia on diagnostic group membership and addressed their effects on nonparticipation in follow-up visits. While phenotypic results confirmed expected differences in current psychotic symptoms and global functioning, both manic and depressive symptoms did not vary between both groups after correction for multiple testing. Polygenic risk scores for schizophrenia significantly explained part of the variability of diagnostic group. The PsyCourse study presents a unique resource to research the complex relationships of psychopathology and biology in severe mental disorders not confined to traditional diagnostic boundaries and is open for collaborations.

Neural correlates of processing emotional prosody in unipolar depression.

Major depressive disorder (MDD) is characterized by a biased emotion perception. In the auditory domain, MDD patients have been shown to exhibit attenuated processing of positive emotions expressed by speech melody (prosody). So far, no neuroimaging studies examining the neural basis of altered processing of emotional prosody in MDD are available. In this study, we addressed this issue by examining the emotion bias in MDD during evaluation of happy, neutral, and angry prosodic stimuli on a five-point Likert scale during functional magnetic resonance imaging (fMRI). As expected, MDD patients rated happy prosody less intense than healthy controls (HC). At neural level, stronger activation in the middle superior temporal gyrus (STG) and the amygdala was found in all participants when processing emotional as compared to neutral prosody. MDD patients exhibited an increased activation of the amygdala during processing prosody irrespective of valence while no significant differences between groups were found for the STG, indicating that altered processing of prosodic emotions in MDD occurs rather within the amygdala than in auditory areas. Concurring with the valence-specific behavioral effect of attenuated evaluation of positive prosodic stimuli, activation within the left amygdala of MDD patients correlated with ratings of happy, but not neutral or angry prosody. Our study provides first insights in the neural basis of reduced experience of positive information and an abnormally increased amygdala activity during prosody processing.

Association of Polygenic Score and the involvement of Cholinergic and Glutamatergic Pathways with Lithium Treatment Response in Patients with Bipolar Disorder.

Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N=2,367) and replicated in the combined PsyCourse (N=89) and BipoLife (N=102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P<����������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������.

An Investigation of Psychosis Subgroups With Prognostic Validation and Exploration of Genetic Underpinnings: The PsyCourse Study.

Importance: Identifying psychosis subgroups could improve clinical and research precision. Research has focused on symptom subgroups, but there is a need to consider a broader clinical spectrum, disentangle illness trajectories, and investigate genetic associations. Objective: To detect psychosis subgroups using data-driven methods and examine their illness courses over 1.5 years and polygenic scores for schizophrenia, bipolar disorder, major depression disorder, and educational achievement. Design, Setting, and Participants: This ongoing multisite, naturalistic, longitudinal (6-month intervals) cohort study began in January 2012 across 18 sites. Data from a referred sample of 1223 individuals (765 in the discovery sample and 458 in the validation sample) with DSM-IV diagnoses of schizophrenia, bipolar affective disorder (I/II), schizoaffective disorder, schizophreniform disorder, and brief psychotic disorder were collected from secondary and tertiary care sites. Discovery data were extracted in September 2016 and analyzed from November 2016 to January 2018, and prospective validation data were extracted in October 2018 and analyzed from January to May 2019. Main Outcomes and Measures: A clinical battery of 188 variables measuring demographic characteristics, clinical history, symptoms, functioning, and cognition was decomposed using nonnegative matrix factorization clustering. Subtype-specific illness courses were compared with mixed models and polygenic scores with analysis of covariance. Supervised learning was used to replicate results in validation data with the most reliably discriminative 45 variables. Results: Of the 765 individuals in the discovery sample, 341 (44.6%) were women, and the mean (SD) age was 42.7 (12.9) years. Five subgroups were found and labeled as affective psychosis (n = 252), suicidal psychosis (n = 44), depressive psychosis (n = 131), high-functioning psychosis (n = 252), and severe psychosis (n = 86). Illness courses with significant quadratic interaction terms were found for psychosis symptoms (R2 = 0.41; 95% CI, 0.38-0.44), depression symptoms (R2 = 0.28; 95% CI, 0.25-0.32), global functioning (R2 = 0.16; 95% CI, 0.14-0.20), and quality of life (R2 = 0.20; 95% CI, 0.17-0.23). The depressive and severe psychosis subgroups exhibited the lowest functioning and quadratic illness courses with partial recovery followed by reoccurrence of severe illness. Differences were found for educational attainment polygenic scores (mean [SD] partial η2 = 0.014 [0.003]) but not for diagnostic polygenic risk. Results were largely replicated in the validation cohort. Conclusions and Relevance: Psychosis subgroups were detected with distinctive clinical signatures and illness courses and specificity for a nondiagnostic genetic marker. New data-driven clinical approaches are important for future psychosis taxonomies. The findings suggest a need to consider short-term to medium-term service provision to restore functioning in patients stratified into the depressive and severe psychosis subgroups.

CACNA1C risk variant affects microstructural connectivity of the amygdala.

Deficits in perception of emotional prosody have been described in patients with affective disorders at behavioral and neural level. In the current study, we use an imaging genetics approach to examine the impact of CACNA1C, one of the most promising genetic risk factors for psychiatric disorders, on prosody processing on a behavioral, functional and microstructural level. Using functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) we examined key areas involved in prosody processing, i.e. the amygdala and voice areas, in a healthy population. We found stronger activation to emotional than neutral prosody in the voice areas and the amygdala, but CACNA1C rs1006737 genotype had no influence on fMRI activity. However, significant microstructural differences (i.e. mean diffusivity) between CACNA1C rs1006737 risk allele carriers and non carriers were found in the amygdala, but not the voice areas. These modifications in brain architecture associated with CACNA1C might reflect a neurobiological marker predisposing to affective disorders and concomitant alterations in emotion perception.