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Psychiatric disorders are the leading cause of disability worldwide while the pathogenesis remains unclear. Genome-wide association studies (GWASs) have made great achievements in detecting disease-related genetic variants. However, functional information on the underlying biological processes is often lacking. Current reports propose the use of metabolic traits as functional intermediate phenotypes (the so-called genetically determined metabotypes or GDMs) to reveal the biological mechanisms of genetics in human diseases. Here we conducted a two-sample Mendelian randomization analysis that uses GDMs to assess the causal effects of 486 human serum metabolites on 5 major psychiatric disorders, which respectively were schizophrenia (SCZ), major depression (MDD), bipolar disorder (BIP), autism spectrum disorder (ASD), and attention-deficit/hyperactivity disorder (ADHD). Using genetic variants as proxies, our study has identified 137 metabolites linked to the risk of psychiatric disorders, including 2-methoxyacetaminophen sulfate, which affects SCZ (P = 1.7 × 10–5) and 1-docosahexaenoylglycerophosphocholine, which affects ADHD (P = 5.6 × 10–5). Fourteen significant metabolic pathways involved in the 5 psychiatric disorders assessed were also detected, such as glycine, serine, and threonine metabolism for SCZ (P = .0238), Aminoacyl-tRNA biosynthesis for both MDD (P = .0144) and ADHD (P = .0029). Our study provided novel insights into integrating metabolomics with genomics in order to understand the mechanisms underlying the pathogenesis of human diseases.

Bipolar disorder (BD) is a common and highly heritable mental illness and genome-wide association studies (GWAS) have robustly identified the first common genetic variants involved in disease aetiology. The data also provide strong evidence for the presence of multiple additional risk loci, each contributing a relatively small effect to BD susceptibility. Large samples are necessary to detect these risk loci. Here we present results from the largest BD GWAS to date by investigating 2.3 million single-nucleotide polymorphisms (SNPs) in a sample of 24,025 patients and controls. We detect 56 genome-wide significant SNPs in five chromosomal regions including previously reported risk loci ANK3 , ODZ4 and TRANK1, as well as the risk locus ADCY2 (5p15.31) and a region between MIR2113 and POU3F2 (6q16.1). ADCY2 is a key enzyme in cAMP signalling and our finding provides new insights into the biological mechanisms involved in the development of BD. Bipolar disorder (BD) is a severe mood disorder, which has been shown to have a large genetic component. Here the authors identify two previously unreported BD risk loci and provide further insights into the biological mechanisms underlying BD development.

Major mood disorders, which primarily include bipolar disorder and major depressive disorder, are the leading cause of disability worldwide and pose a major challenge in identifying robust risk genes. Here, we present data from independent large-scale clinical data sets (including 29 557 cases and 32 056 controls) revealing brain expressed protocadherin 17 (PCDH17) as a susceptibility gene for major mood disorders. Single-nucleotide polymorphisms (SNPs) spanning the PCDH17 region are significantly associated with major mood disorders; subjects carrying the risk allele showed impaired cognitive abilities, increased vulnerable personality features, decreased amygdala volume and altered amygdala function as compared with non-carriers. The risk allele predicted higher transcriptional levels of PCDH17 mRNA in postmortem brain samples, which is consistent with increased gene expression in patients with bipolar disorder compared with healthy subjects. Further, overexpression of PCDH17 in primary cortical neurons revealed significantly decreased spine density and abnormal dendritic morphology compared with control groups, which again is consistent with the clinical observations of reduced numbers of dendritic spines in the brains of patients with major mood disorders. Given that synaptic spines are dynamic structures which regulate neuronal plasticity and have crucial roles in myriad brain functions, this study reveals a potential underlying biological mechanism of a novel risk gene for major mood disorders involved in synaptic function and related intermediate phenotypes.

Background Major depressive disease (MDD), schizophrenia (SCZ), and bipolar disorder (BD) are common psychiatric disorders, and their relationship with thyroid cancer has been of great interest. This study aimed to investigate the potential causal effects of MDD, SCZ, BD, and thyroid cancer. Methods We used publicly available summary statistics from large-scale genome-wide association studies to select genetic variant loci associated with MDD, SCZ, BD, and thyroid cancer as instrumental variables (IVs), which were quality controlled and clustered. Additionally, we used three Mendelian randomization (MR) methods, inverse variance weighted (IVW), MR–Egger regression and weighted median estimator (WME) methods, to estimate the bidirectional causal relationship between psychiatric disorders and thyroid cancer. In addition, we performed heterogeneity and multivariate tests to verify the validity of the IVs. Results We used two-sample bidirectional MR analysis to determine whether there was a positive causal association between MDD and thyroid cancer risk. The results of the IVW analysis (OR = 3.956 95% CI = 1.177–13.299; P  = 0.026) and the WME method (OR = 5.563 95% CI = 0.998–31.008; P  = 0.050) confirmed that MDD may increase the risk of thyroid cancer. Additionally, our study revealed a correlation between genetic susceptibility to SCZ and thyroid cancer (OR = 1.532 95% CI = 1.123–2.088; P  = 0.007). The results of the WME method analysis based on the median estimate (OR = 1.599 95% CI = 1.014–2.521; P  = 0.043) also suggested that SCZ may increase the risk of thyroid cancer. Furthermore, our study did not find a causal relationship between BD and thyroid cancer incidence. In addition, the results of reverse MR analysis showed no significant causal relationships between thyroid cancer and MDD, SCZ, or BD ( P  > 0.05), ruling out the possibility of reverse causality. Conclusions This MR method analysis provides new evidence that MDD and SCZ may be positively associated with thyroid cancer risk while also revealing a correlation between BD and thyroid cancer. These results may have important implications for public health policy and clinical practice. Future studies will help elucidate the biological mechanisms of these associations and potential confounders.

To assess the role of lithium treatment in the relationship between bipolar disorder (BD) and leukocyte telomere length (LTL). We compared LTL between 131 patients with BD, with or without a history of lithium treatment, and 336 controls. We tested the association between genetically determined LTL and BD in two large genome-wide association datasets. Patients with BD with a history lithium treatment showed longer LTL compared with never-treated patients (p = 0.015), and similar LTL compared with controls. Patients never treated with lithium showed shorter LTL compared with controls (p = 0.029). Mendelian randomization analysis showed no association between BD and genetically determined LTL. Our data support previous findings showing that long-term lithium treatment might protect against telomere shortening.

Education and intelligence are highly correlated and inversely associated with schizophrenia. Counterintuitively, education genetically associates with an increased risk for the disease. To investigate why, this study applies a multivariable Mendelian randomization of intelligence and education. For those without college degrees, older age of finishing school associates with a decreased likelihood of schizophrenia—independent of intelligence—and, hence, may be entangled with the health inequalities reflecting differences in education. A different picture is observed for schooling years inclusive of college: more years of schooling increases the likelihood of schizophrenia, whereas higher intelligence distinctly and independently decreases it. This implies the pleiotropy between years of schooling and schizophrenia is horizontal and likely confounded by a third trait influencing education. A multivariable Mendelian randomization of schooling years and bipolar disorder reveals that the increased risk of schizophrenia conferred by more schooling years is an artefact of bipolar disorder – not education.

Background Given that psychopharmacological approaches routinely used to treat mood-related problems may result in adverse outcomes in mood dysregulated adolescents at familial risk for bipolar disorder (BD), Mindfulness-Based Cognitive Therapy for Children (MBCT-C) provides an alternative effective and safe option. However, little is known about the brain mechanisms of beneficial outcomes from this intervention. Herein, we aimed to investigate the network-level neurofunctional effects of MBCT-C in mood dysregulated adolescents. Methods Ten mood dysregulated adolescents at familial risk for BD underwent a 12-week MBCT-C intervention. Resting-state functional magnetic resonance imaging (fMRI) was performed prior to and following MBCT-C. Topological metrics of three intrinsic functional networks (default mode network (DMN), fronto-parietal network (FPN) and cingulo-opercular network (CON)) were investigated respectively using graph theory analysis. Results Following MBCT-C, mood dysregulated adolescents showed increased global efficiency and decreased characteristic path length within both CON and FPN. Enhanced functional connectivity strength of frontal and limbic areas were identified within the DMN and CON. Moreover, change in characteristic path length within the CON was suggested to be significantly related to change in the Emotion Regulation Checklist score. Conclusions 12-week MBCT-C treatment in mood dysregulated adolescents at familial risk for BD yield network-level neurofunctional effects within the FPN and CON, suggesting enhanced functional integration of the dual-network. Decreased characteristic path length of the CON may be associated with the improvement of emotion regulation following mindfulness training. However, current findings derived from small sample size should be interpreted with caution. Future randomized controlled trials including larger samples are critical to validate our findings.

Bipolar disorder (BD) has been associated with premature cellular aging with shortened telomere length (TL) as compared to the general population. We recently identified a subgroup of young individuals with prematurely shortened TL. The aims of the present study were to replicate this observation in a larger sample and analyze the expression levels of genes associated with age or TL in a subsample of these individuals. TL was measured on peripheral blood DNA using quantitative polymerase chain reaction in a sample of 542 individuals with BD and clustering analyses were performed. Gene expression level of 29 genes, associated with aging or with telomere maintenance, was analyzed in RNA samples from a subsample of 129 individuals. Clustering analyses identified a group of young individuals (mean age 29.64 years), with shorter TL. None of the tested clinical variables were significantly associated with this subgroup. Gene expression level analyses showed significant downregulation of MYC, POT1, and CD27 in the prematurely aged young individuals compared to the young individuals with longer TL. After adjustment only POT1 remained significantly differentially expressed between the two groups of young individuals. This study confirms the existence of a subgroup of young individuals with BD with shortened TL. The observed decrease of POT1 expression level suggests a newly described cellular mechanism in individuals with BD, that may contribute to telomere shortening.

Genetic essentialism suggests that beliefs in genetic causes of mental illness will inflate a desire for social distance from affected individuals, regardless of specific disorder. However, genetic contingency theory predicts that genetic attributions will lead to an increased desire for social distance only from persons with disorders who are perceived as dangerous. Purpose To assess the interactive effect of diagnosis and attribution on social distance and actual helping decisions across disorders. Methods Undergraduate students ( n  = 149) were randomly assigned to read one of the six vignettes depicting a person affected by one of the three disorders (i.e., schizophrenia, bipolar disorder, or major depression) with either a genetic or environmental causal attribution for disorder. Participants completed measures of perceived dangerousness, social distance, empathic concern, familiarity with mental illness, and actual helping decisions. Results When provided with genetic attributions, participants’ desire for social distance was greater for targets with schizophrenia relative to targets with depression or bipolar disorder. This effect was mediated by perceived dangerousness. The indirect effect of diagnosis on helping decisions, through social distance, was significant within the genetic attribution condition. Conclusion Consistent with genetic contingency theory, genetic attributions for schizophrenia, but not affective disorders, lead to greater desire for social distance via greater perceived dangerousness. Further, results suggest that genetic attributions decrease the likelihood of helping people with schizophrenia, but have no effect on the likelihood of helping people with affective disorders. These effects are partially accounted for by desired social distance from people with schizophrenia.

We explored the effect of the Brain-derived neurotrophic factor ( BDNF ) Val66Met polymorphism (rs6265) on correlation between changes in plasma BDNF levels with cognitive function and quality of life (QoL) after 12 weeks of treatment in bipolar disorder (BD). Symptom severity and plasma BDNF levels were assessed upon recruitment and during weeks 1, 2, 4, 8 and 12. QoL, the Wisconsin Card Sorting Test (WCST), and the Conners’ Continuous Performance Test (CPT) were assessed at baseline and endpoint. The BDNF Val66Met polymorphism was genotyped. Changes in cognitive function and QoL over 12 weeks were reduced using factor analysis for the evaluation of their correlations with changes in plasma BDNF. Five hundred forty-one BD patients were recruited and 65.6% of them completed the 12-week follow-up. Changes in plasma BDNF levels with factor 1 (WCST) were significantly negatively correlated ( r  = −0.25, p  = 0.00037). After stratification of BD subtypes and BDNF genotypes, this correlation was significant only in BP-I and the Val/Met genotype ( r  = −0.54, p  = 0.008). We concluded that changes in plasma BDNF levels significantly correlated with changes in WCST scores in BD and is moderated by the BDNF Val66Met polymorphism and the subtype of BD.