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Merging genetic risk, neurological phenotypes, and clinical presentation is a primary goal for psychiatry. Pursuing this goal, we tested association between phenotypes and overall and pathway-specific polygenic risk in patients with early-stage psychosis. Subjects included 206 demographically diverse cases with a psychotic disorder and 115 matched controls with comprehensive psychiatric and neurological phenotyping. DNA was extracted from blood and genotyped. We calculated polygenic scores (PGSs) for schizophrenia (SZ) and bipolar disorder (BP) using Psychiatric Genomics Consortium GWAS summary statistics. To dissect convergent mechanisms of symptoms, we calculated pathway PGSs (pPGSs) for SZ risk affecting each of four major neurotransmitter systems: glutamate, GABA, dopamine, and serotonin. Psychosis subjects had elevated SZ and BP PGS versus controls; cases with SZ or BP diagnoses had stronger SZ or BP risk, respectively. There was no significant association between individual symptom measures and overall PGS. However, neurotransmitter-specific pPGSs were significantly associated with specific symptoms; most notably, increased glutamatergic pPGS was associated with deficits in cognitive control and altered cortical activation during cognitive control task-based fMRI. Finally, unbiased symptom-driven clustering identified three diagnostically mixed case groups with distinct symptom profiles that separated on primary deficits of positive symptoms, negative symptoms, global functioning, and cognitive control. These clusters had specific genetic risk profiles and differential response to treatment, and outperformed diagnosis in predicting glutamate and GABA pPGS. Our findings suggest pathway-based PGS analysis may be a powerful path forward for identifying convergent mechanisms driving psychotic disorders and linking genetic risk with endophenotypes.

A strong body of evidence supports a role for immune dysregulation across many psychiatric disorders including depression, the leading cause of global disability. Recent progress in the search for genetic variants associated with depression provides the opportunity to strengthen our current understanding of etiological factors contributing to depression and generate novel hypotheses. Here, we provide an overview of the literature demonstrating a role for immune dysregulation in depression, followed by a detailed discussion of the immune-related genes identified by the most recent genome-wide meta-analysis of depression. These genes represent strong evidence-based targets for future basic and translational research which aims to understand the role of the immune system in depression pathology and identify novel points for therapeutic intervention., Highlights • Dysregulated immune function has been strongly linked to depression. • Recent genome-wide association studies support this relationship. • These genes represent strong candidates for etiological and translational research.

Indirect parental genetic effects may be defined as the influence of parental genotypes on offspring phenotypes over and above that which results from the transmission of genes from parents to children. However, given the relative paucity of large-scale family-based cohorts around the world, it is difficult to demonstrate parental genetic effects on human traits, particularly at individual loci. In this manuscript, we illustrate how parental genetic effects on offspring phenotypes, including late onset diseases, can be estimated at individual loci in principle using large-scale genome-wide association study (GWAS) data, even in the absence of parental genotypes. Our strategy involves creating “virtual” mothers and fathers by estimating the genotypic dosages of parental genotypes using physically genotyped data from relative pairs. We then utilize the expected dosages of the parents, and the actual genotypes of the offspring relative pairs, to perform conditional genetic association analyses to obtain asymptotically unbiased estimates of maternal, paternal and offspring genetic effects. We develop a freely available web application that quantifies the power of our approach using closed form asymptotic solutions. We implement our methods in a user-friendly software package IMPISH (IMputing Parental genotypes In Siblings and Half-Siblings) which allows users to quickly and efficiently impute parental genotypes across the genome in large genome-wide datasets, and then use these estimated dosages in downstream linear mixed model association analyses. We conclude that imputing parental genotypes from relative pairs may provide a useful adjunct to existing large-scale genetic studies of parents and their offspring.

OBJECTIVE: To explore the relations between trauma exposure and anxiety and depression among college students, and to determine whether trait mindfulness may moderate these relations. PARTICIPANTS: Self-report survey data from 2,336 college sophomores was drawn from a larger university-wide study (“Spit for Science”). METHODS: We constructed multiple linear regression models using past-year trauma exposure, trait mindfulness, and their multiplicative interaction to predict current anxiety and depressive symptom severity, while controlling for covariates. RESULTS: Mindfulness was associated with lower levels of depression and anxiety symptom severity. Trauma was a significant predictor of anxiety, but not depression, and high levels of mindfulness attenuated the association between trauma exposure and higher anxiety symptom severity. CONCLUSIONS: These results have implications for the treatment and prevention of anxiety among trauma-exposed college students and provides a basis for further research into the mechanisms through which mindfulness may facilitate positive mental health.