Reflections on an emerging new science of mental disorders

Depression, Anxiety, Emotional Eating, and Body Mass Index among Self-Reported Vegetarians and Non-Vegetarians: A Cross-Sectional Study in Peruvian Adults

Background: Vegetarianism is commonly associated with various health benefits. However, the association between this dietary regimen and aspects of mental health remains ambiguous. This study compared the symptoms of depression and anxiety, emotional eating (EmE), and body mass index (BMI) in Peruvian vegetarian and non-vegetarian adults. Methods: A cross-sectional study was conducted on 768 Peruvian adults, of whom 284 (37%) were vegetarians and 484 (63%) were non-vegetarians. The Depression Patient Health Questionnaire-2 (PHQ-2), Generalized Anxiety Disorder Scale-2 (GAD-2), and an EmE questionnaire were applied; additionally, the BMI was calculated. Simple and multiple linear regression and Poisson regression models with robust variance were used to evaluate the association between depression, anxiety, EmE, and BMI with dietary patterns. Results: The vegetarians (Adjusted Prevalence Ratio [PR] = 0.24, 95% CI 0.16-0.31; p < 0.001) reported more depressive symptoms than the non-vegetarians. This trend persisted for anxiety, with an adjusted PR of 0.17 (95% CI: 0.01-0.29; p = 0.012). However, the vegetarians (adjusted PR = -0.38, 95% CI: -0.61--0.14; p < 0.001) reported lower EmE scores compared to the non-vegetarians. Likewise, the vegetarians had a lower mean BMI than the non-vegetarians (B = -0.16, 95% CI: -0.21--0.08; p < 0.001). Conclusions: Vegetarian diets are associated with increased symptoms of depression and anxiety, as well as lower EmE and BMI scores. Further longitudinal studies are needed to elucidate these associations and determine causality and the underlying mechanisms involved.

Network analysis of anxiety and depressive symptoms during the COVID-19 pandemic in older adults in the United Kingdom

The health crisis caused by COVID-19 in the United Kingdom and the confinement measures that were subsequently implemented had unprecedented effects on the mental health of older adults, leading to the emergence and exacerbation of different comorbid symptoms including depression and anxiety. This study examined and compared depression and anxiety symptom networks in two specific quarantine periods (June-July and November-December) in the older adult population in the United Kingdom. We used the database of the English Longitudinal Study of Aging COVID-19 Substudy, consisting of 5797 participants in the first stage (54% women) and 6512 participants in the second stage (56% women), all over 50 years of age. The symptoms with the highest centrality in both times were: "Nervousness (A1)" and "Inability to relax (A4)" in expected influence and predictability, and "depressed mood (D1"; bridging expected influence). The latter measure along with "Irritability (A6)" overlapped in both depression and anxiety clusters in both networks. In addition, a the cross-lagged panel network model was examined in which a more significant influence on the direction of the symptom "Nervousness (A1)" by the depressive symptoms of "Anhedonia (D6)", "Hopelessness (D7)", and "Sleep problems (D3)" was observed; the latter measure has the highest predictive capability of the network. The results report which symptoms had a higher degree of centrality and transdiagnostic overlap in the cross-sectional networks (invariants) and the cross-lagged panel network model of anxious and depressive symptomatology.

The genetic basis of major depressive disorder

The genetic dissection of major depressive disorder (MDD) ranks as one of the success stories of psychiatric genetics, with genome-wide association studies (GWAS) identifying 178 genetic risk loci and proposing more than 200 candidate genes. However, the GWAS results derive from the analysis of cohorts in which most cases are diagnosed by minimal phenotyping, a method that has low specificity. I review data indicating that there is a large genetic component unique to MDD that remains inaccessible to minimal phenotyping strategies and that the majority of genetic risk loci identified with minimal phenotyping approaches are unlikely to be MDD risk loci. I show that inventive uses of biobank data, novel imputation methods, combined with more interviewer diagnosed cases, can identify loci that contribute to the episodic severe shifts of mood, and neurovegetative and cognitive changes that are central to MDD. Furthermore, new theories about the nature and causes of MDD, drawing upon advances in neuroscience and psychology, can provide handles on how best to interpret and exploit genetic mapping results.

A network analysis of anxiety, depressive, and psychotic symptoms and functioning in children and adolescents at clinical high risk for psychosis

Objective

Youths at clinical high risk for psychosis (CHR-P) are characterized by a high prevalence of anxiety and depressive disorders. The present study aimed at developing and analyzing a network structure of CHR-P symptom domains (i.e., positive, negative, disorganization, and general subclinical psychotic symptoms), depressive and anxiety symptoms, and general functioning.

Methods

Network analysis was applied to data on 111 CHR-P children and adolescents (M age = 14.1), who were assessed using the Structured Interview for Prodromal Syndromes, the Children's Depression Inventory, the Children's Global Assessment Scale, and the Multidimensional Anxiety Scale for Children.

Results

In the network, negative and disorganization symptoms showed the strongest association (r = 0.71), and depressive and anxiety symptoms showed dense within-domain connections, with a main bridging role played by physical symptoms of anxiety. The positive symptom cluster was not associated with any other node. The network stability coefficient (CS) was slightly below 0.25, and observed correlations observed ranged from 0.35 to 0.71.

Conclusion

The lack of association between subclinical positive symptoms and other network variables confirmed the independent nature of subclinical positive symptoms from comorbid symptoms, which were found to play a central role in the analyzed network. Complex interventions should be developed to target positive and comorbid symptoms, prioritizing those with the most significant impact on functioning and the most relevance for the young individual, through a shared decision-making process. Importantly, the results suggest that negative and disorganization symptoms, as well as depressive and anxiety symptoms, may be targeted simultaneously.