Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders.

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.

The researcher's guide to selecting biomarkers in mental health studies.

Clinical mental health researchers may understandably struggle with how to incorporate biological assessments in clinical research. The options are numerous and are described in a vast and complex body of literature. Here we provide guidelines to assist mental health researchers seeking to include biological measures in their studies. Apart from a focus on behavioral outcomes as measured via interviews or questionnaires, we advocate for a focus on biological pathways in clinical trials and epidemiological studies that may help clarify pathophysiology and mechanisms of action, delineate biological subgroups of participants, mediate treatment effects, and inform personalized treatment strategies. With this paper we aim to bridge the gap between clinical and biological mental health research by (1) discussing the clinical relevance, measurement reliability, and feasibility of relevant peripheral biomarkers; (2) addressing five types of biological tissues, namely blood, saliva, urine, stool and hair; and (3) providing information on how to control sources of measurement variability.

High-throughput screening of glucocorticoid-induced enhancer activity reveals mechanisms of stress-related psychiatric disorders.

Exposure to stressful life events increases the risk for psychiatric disorders. Mechanistic insight into the genetic factors moderating the impact of stress can increase our understanding of disease processes. Here, we test 3,662 single nucleotide polymorphisms (SNPs) from preselected expression quantitative trait loci in massively parallel reporter assays to identify genetic variants that modulate the activity of regulatory elements sensitive to glucocorticoids, important mediators of the stress response. Of the tested SNP sequences, 547 were located in glucocorticoid-responsive regulatory elements of which 233 showed allele-dependent activity. Transcripts regulated by these functional variants were enriched for those differentially expressed in psychiatric disorders in the postmortem brain. Phenome-wide Mendelian randomization analysis in 4,439 phenotypes revealed potentially causal associations specifically in neurobehavioral traits, including major depression and other psychiatric disorders. Finally, a functional gene score derived from these variants was significantly associated with differences in the physiological stress response, suggesting that these variants may alter disease risk by moderating the individual set point of the stress response.

Meta-analysis of 46,000 germline de novo mutations linked to human inherited disease.

BACKGROUND: De novo mutations (DNMs) are variants that occur anew in the offspring of noncarrier parents. They are not inherited from either parent but rather result from endogenous mutational processes involving errors of DNA repair/replication. These spontaneous errors play a significant role in the causation of genetic disorders, and their importance in the context of molecular diagnostic medicine has become steadily more apparent as more DNMs have been reported in the literature. In this study, we examined 46,489 disease-associated DNMs annotated by the Human Gene Mutation Database (HGMD) to ascertain their distribution across gene and disease categories. RESULTS: Most disease-associated DNMs reported to date are found to be associated with developmental and psychiatric disorders, a reflection of the focus of sequencing efforts over the last decade. Of the 13,277 human genes in which DNMs have so far been found, the top-10 genes with the highest proportions of DNM relative to gene size were H3-3 A, DDX3X, CSNK2B, PURA, ZC4H2, STXBP1, SCN1A, SATB2, H3-3B and TUBA1A. The distribution of CADD and REVEL scores for both disease-associated DNMs and those mutations not reported to be de novo revealed a trend towards higher deleteriousness for DNMs, consistent with the likely lower selection pressure impacting them. This contrasts with the non-DNMs, which are presumed to have been subject to continuous negative selection over multiple generations. CONCLUSION: This meta-analysis provides important information on the occurrence and distribution of disease-associated DNMs in association with heritable disease and should make a significant contribution to our understanding of this major type of mutation.

Belief traps: Tackling the inertia of harmful beliefs.

Beliefs can be highly resilient in the sense that they are not easily abandoned in the face of counterevidence. This has the advantage of guiding consistent behavior and judgments but may also have destructive consequences for individuals, nature, and society. For instance, pathological beliefs can sustain psychiatric disorders, the belief that rhinoceros horn is an aphrodisiac may drive a species extinct, beliefs about gender or race may fuel discrimination, and belief in conspiracy theories can undermine democracy. Here, we present a unifying framework of how self-amplifying feedbacks shape the inertia of beliefs on levels ranging from neuronal networks to social systems. Sustained exposure to counterevidence can destabilize rigid beliefs but requires organized rational override as in cognitive behavioral therapy for pathological beliefs or institutional control of discrimination to reduce racial biases. Black-and-white thinking is a major risk factor for the formation of resilient beliefs associated with psychiatric disorders as well as prejudices and conspiracy thinking. Such dichotomous thinking is characteristic of a lack of cognitive resources, which may be exacerbated by stress. This could help explain why conspiracy thinking and psychiatric disorders tend to peak during crises. A corollary is that addressing social factors such as poverty, social cleavage, and lack of education may be the most effective way to prevent the emergence of rigid beliefs, and thus of problems ranging from psychiatric disorders to prejudices, conspiracy theories, and posttruth politics.

Disrupted Cacna1c gene expression perturbs spontaneous Ca2+ activity causing abnormal brain development and increased anxiety.

The L-type voltage-gated Ca2+ channel gene CACNA1C is a risk gene for various psychiatric conditions, including schizophrenia and bipolar disorder. However, the cellular mechanism by which CACNA1C contributes to psychiatric disorders has not been elucidated. Here, we report that the embryonic deletion of Cacna1c in neurons destined for the cerebral cortex using an Emx1-Cre strategy disturbs spontaneous Ca2+ activity and causes abnormal brain development and anxiety. By combining computational modeling with electrophysiological membrane potential manipulation, we found that neural network activity was driven by intrinsic spontaneous Ca2+ activity in distinct progenitor cells expressing marginally increased levels of voltage-gated Ca2+ channels. MRI examination of the Cacna1c knockout mouse brains revealed volumetric differences in the neocortex, hippocampus, and periaqueductal gray. These results suggest that Cacna1c acts as a molecular switch and that its disruption during embryogenesis can perturb Ca2+ handling and neural development, which may increase susceptibility to psychiatric disease.

Social processes and social environment during development.

Social behavior involves many processes including cognitive functions. Altered social behaviors associated with many psychiatric disorders might have alterations in the processes. Poor social environment affects development and maturation of cognitive functions that are important for social cognition, possibly introducing social stress as well as vulnerability to the stress into the developing brain. Adolescence and early adulthood have higher sensitivity to social stress, which may be linked to the onset of psychiatric disorders during this time period. Understanding social behavioral processes in detail will be crucial for elucidating mechanisms of emerging the social behavior phenotypes in psychiatric disorders and for devising therapeutic and preventive interventions to introduce the resilience for the onset of psychiatric disorders through modulation of social circuitries.

Exploring the potential of representation and transfer learning for anatomical neuroimaging: Application to psychiatry.

The perspective of personalized medicine for brain disorders requires efficient learning models for anatomical neuroimaging-based prediction of clinical conditions. There is now a consensus on the benefit of deep learning (DL) in addressing many medical imaging tasks, such as image segmentation. However, for single-subject prediction problems, recent studies yielded contradictory results when comparing DL with Standard Machine Learning (SML) on top of classical feature extraction. Most existing comparative studies were limited in predicting phenotypes of little clinical interest, such as sex and age, and using a single dataset. Moreover, they conducted a limited analysis of the employed image pre-processing and feature selection strategies. This paper extensively compares DL and SML prediction capacity on five multi-site problems, including three increasingly complex clinical applications in psychiatry namely schizophrenia, bipolar disorder, and Autism Spectrum Disorder (ASD) diagnosis. To compensate for the relative scarcity of neuroimaging data on these clinical datasets, we also evaluate three pre-training strategies for transfer learning from brain imaging of the general healthy population: self-supervised learning, generative modeling and supervised learning with age. Overall, we find similar performance between randomly initialized DL and SML for the three clinical tasks and a similar scaling trend for sex prediction. This was replicated on an external dataset. We also show highly correlated discriminative brain regions between DL and linear ML models in all problems. Nonetheless, we demonstrate that self-supervised pre-training on large-scale healthy population imaging datasets (N≈10k), along with Deep Ensemble, allows DL to learn robust and transferable representations to smaller-scale clinical datasets (N≤1k). It largely outperforms SML on 2 out of 3 clinical tasks both in internal and external test sets. These findings suggest that the improvement of DL over SML in anatomical neuroimaging mainly comes from its capacity to learn meaningful and useful abstract representations of the brain anatomy, and it sheds light on the potential of transfer learning for personalized medicine in psychiatry.

Central role of the habenulo-interpeduncular system in the neurodevelopmental basis of susceptibility and resilience to anxiety in mice.

Having experienced stress during sensitive periods of brain development strongly influences how individuals cope with later stress. Some are prone to develop anxiety or depression, while others appear resilient. The as-yet-unknown mechanisms underlying these differences may lie in how genes and environmental stress interact to shape the circuits that control emotions. Here, we investigated the role of the habenulo-interpeduncular system (HIPS), a critical node in reward circuits, in early stress-induced anxiety in mice. We found that habenular and IPN components characterized by the expression of Otx2 are synaptically connected and particularly sensitive to chronic stress (CS) during the peripubertal period. Stress-induced peripubertal activation of this HIPS subcircuit elicits both HIPS hypersensitivity to later stress and susceptibility to develop anxiety. We also show that HIPS silencing through conditional Otx2 knockout counteracts these effects of stress. Together, these results demonstrate that a genetic factor, Otx2, and stress interact during the peripubertal period to shape the stress sensitivity of the HIPS, which is shown to be a key modulator of susceptibility or resilience to develop anxiety.