Genetics and genomics of psychiatric disease

Brain somatic mutations as RNA therapeutic targets in neurological disorders

Research into the genetic etiology of a neurological disorder can provide directions for genetic diagnosis and targeted therapy. In the past, germline mutations, which are transmitted from parents or newly arise from parental germ cells, were considered as major genetic causes of neurological disorders. However, recent evidence has shown that somatic mutations in the brain, which can arise from neural stem cells during development or over aging, account for a significant number of brain disorders, ranging from neurodevelopmental, neurodegenerative, and neuropsychiatric to neoplastic disease. Moreover, the identification of disease-causing somatic mutations or mutated genes has provided new insights into molecular pathogenesis and unveiled potential therapeutic targets for treating neurological disorders that have few, or no, therapeutic options. RNA therapeutics, including antisense oligonucleotide (ASO) and small interfering RNA (siRNA), are emerging as promising therapeutic tools for treating genetic neurological disorders. As the number of approved and investigational ASO and siRNA drugs for neurological disorders associated with germline mutations increases, they may also prove to be attractive modalities for treating neurologic disorders resulting from somatic mutations. In this perspective, we highlight several neurological diseases caused by brain somatic mutations and discuss the potential role of RNA therapeutics in these conditions.

Revealing the Impact of Mitochondrial Fitness During Early Neural Development Using Human Brain Organoids

Mitochondrial homeostasis -including function, morphology, and inter-organelle communication- provides guidance to the intrinsic developmental programs of corticogenesis, while also being responsive to environmental and intercellular signals. Two- and three-dimensional platforms have become useful tools to interrogate the capacity of cells to generate neuronal and glia progeny in a background of metabolic dysregulation, but the mechanistic underpinnings underlying the role of mitochondria during human neurogenesis remain unexplored. Here we provide a concise overview of cortical development and the use of pluripotent stem cell models that have contributed to our understanding of mitochondrial and metabolic regulation of early human brain development. We finally discuss the effects of mitochondrial fitness dysregulation seen under stress conditions such as metabolic dysregulation, absence of developmental apoptosis, and hypoxia; and the avenues of research that can be explored with the use of brain organoids.

Genomic modules and intramodular network concordance in susceptible and resilient male mice across models of stress

The multifactorial etiology of stress-related disorders necessitates a constant interrogation of the molecular convergences in preclinical models of stress that use disparate paradigms as stressors spanning from environmental challenges to genetic predisposition to hormonal signaling. Using RNA-sequencing, we investigated the genomic signatures in the ventral hippocampus common to mouse models of stress. Chronic oral corticosterone (CORT) induced increased anxiety- and depression-like behavior in wild-type male mice and male mice heterozygous for the gene coding for brain-derived neurotrophic factor Val66Met, a variant associated with genetic susceptibility to stress. In a separate set of male mice, chronic social defeat stress (CSDS) led to a susceptible or a resilient population, whose proportion was dependent on housing conditions, namely standard housing or enriched environment. Rank-rank-hypergeometric overlap (RRHO), a threshold-free approach that ranks genes by their p value and effect size direction, was used to identify genes from a continuous gradient of significancy that were concordant across groups. In mice treated with CORT and in standard-housed susceptible mice, differentially expressed genes (DEGs) were concordant for gene networks involved in neurotransmission, cytoskeleton function, and vascularization. Weighted gene co-expression analysis generated 54 gene hub modules and revealed two modules in which both CORT and CSDS-induced enrichment in DEGs, whose function was concordant with the RRHO predictions, and correlated with behavioral resilience or susceptibility. These data showed transcriptional concordance across models in which the stress coping depends upon hormonal, environmental, or genetic factors revealing common genomic drivers that embody the multifaceted nature of stress-related disorders.

Krüppel-like Transcription Factor 7 Is a Causal Gene in Autism Development

Background: Autism spectrum disorder (ASD) is a complex neurodevelopmental disease. To date, more than 1000 genes have been shown to be associated with ASD, and only a few of these genes account for more than 1% of autism cases. Klf7 is an important transcription factor of cell proliferation and differentiation in the nervous system, but whether klf7 is involved in autism is unclear. Methods: We first performed ChIP-seq analysis of klf7 in N2A cells, then performed behavioral tests and RNA-seq in klf7^+/− mice, and finally restored mice with adeno-associated virus (AAV)-mediated overexpression of klf7 in klf7^+/− mice. Results: Klf7 targeted genes are enriched with ASD genes, and 631 ASD risk genes are also differentially expressed in klf7^+/− mice which exhibited the core symptoms of ASD. When klf7 levels were increased in the central nervous system (CNS) in klf7^+/− adult mice, deficits in social interaction, repetitive behavior and majority of dysregulated ASD genes were rescued in the adults, suggesting transcriptional regulation. Moreover, knockdown of klf7 in human brain organoids caused dysregulation of 517 ASD risk genes, 344 of which were shared with klf7^+/− mice, including some high-confidence ASD genes. Conclusions: Our findings highlight a klf7 regulation of ASD genes and provide new insights into the pathogenesis of ASD and promising targets for further research on mechanisms and treatments.

Genetics and Brain Transcriptomics of Completed Suicide

OBJECTIVE

The authors sought to study the transcriptomic and genomic features of completed suicide by parsing the method chosen, to capture molecular correlates of the distinctive frame of mind of individuals who die by suicide, while reducing heterogeneity.

METHODS

The authors analyzed gene expression (RNA sequencing) from postmortem dorsolateral prefrontal cortex of patients who died by suicide with violent compared with nonviolent means, nonsuicide patients with the same psychiatric disorders, and a neurotypical group (total N=329). They then examined genomic risk scores (GRSs) for each psychiatric disorder included, and GRSs for cognition (IQ) and for suicide attempt, testing how they predict diagnosis or traits (total N=888).

RESULTS

Patients who died by suicide by violent means showed a transcriptomic pattern remarkably divergent from each of the other patient groups but less from the neurotypical group; consistently, their genomic profile of risk was relatively low for their diagnosed illness as well as for suicide attempt, and relatively high for IQ: they were more similar to the neurotypical group than to other patients. Differentially expressed genes (DEGs) associated with patients who died by suicide by violent means pointed to purinergic signaling in microglia, showing similarities to a genome-wide association study of Drosophila aggression. Weighted gene coexpression network analysis revealed that these DEGs were coexpressed in a context of mitochondrial metabolic activation unique to suicide by violent means.

CONCLUSIONS

These findings suggest that patients who die by suicide by violent means are in part biologically separable from other patients with the same diagnoses, and their behavioral outcome may be less dependent on genetic risk for conventional psychiatric disorders and be associated with an alteration of purinergic signaling and mitochondrial metabolism.

Identification of ultra-rare disruptive variants in voltage-gated calcium channel-encoding genes in Japanese samples of schizophrenia and autism spectrum disorder

Several large-scale whole-exome sequencing studies in patients with schizophrenia (SCZ) and autism spectrum disorder (ASD) have identified rare variants with modest or strong effect size as genetic risk factors. Dysregulation of cellular calcium homeostasis might be involved in SCZ/ASD pathogenesis, and genes encoding L-type voltage-gated calcium channel (VGCC) subunits Ca_v1.1 (CACNA1S), Ca_v1.2 (CACNA1C), Ca_v1.3 (CACNA1D), and T-type VGCC subunit Ca_v3.3 (CACNA1I) recently were identified as risk loci for psychiatric disorders. We performed a screening study, using the Ion Torrent Personal Genome Machine (PGM), of exon regions of these four candidate genes (CACNA1C, CACNA1D, CACNA1S, CACNA1I) in 370 Japanese patients with SCZ and 192 with ASD. Variant filtering was applied to identify biologically relevant mutations that were not registered in the dbSNP database or that have a minor allele frequency of less than 1% in East-Asian samples from databases; and are potentially disruptive, including nonsense, frameshift, canonical splicing site single nucleotide variants (SNVs), and non-synonymous SNVs predicted as damaging by five different in silico analyses. Each of these filtered mutations were confirmed by Sanger sequencing. If parental samples were available, segregation analysis was employed for measuring the inheritance pattern. Using our filter, we discovered one nonsense SNV (p.C1451* in CACNA1D), one de novo SNV (p.A36V in CACNA1C), one rare short deletion (p.E1675del in CACNA1D), and 14 NSstrict SNVs (non-synonymous SNV predicted as damaging by all of five in silico analyses). Neither p.A36V in CACNA1C nor p.C1451* in CACNA1D were found in 1871 SCZ cases, 380 ASD cases, or 1916 healthy controls in the independent sample set, suggesting that these SNVs might be ultra-rare SNVs in the Japanese population. The neuronal splicing isoform of Ca_v1.2 with the p.A36V mutation, discovered in the present study, showed reduced Ca²⁺-dependent inhibition, resulting in excessive Ca²⁺ entry through the mutant channel. These results suggested that this de novo SNV in CACNA1C might predispose to SCZ by affecting Ca²⁺ homeostasis. Thus, our analysis successfully identified several ultra-rare and potentially disruptive gene variants, lending partial support to the hypothesis that VGCC-encoding genes may contribute to the risk of SCZ/ASD.

The Current Progress of Psychiatric Genomics

Psychiatric disorders such as bipolar disorder and schizophrenia are highly heritable. While the genetic contribution to psychiatric disorders is quite sure, specific genetic factors contributing to particular conditions have long been a mystery. Empowered by the initial report of the Human Genome Project, the analysis of the comprehensive set of the human genome, called "genomics," became possible. Subsequent development of large-scale genomic technologies enabled us to elucidate various disease-related genetic information, accelerating our understanding of various diseases. Genomic research on psychiatric disorders is not an exception. In this Review, I introduce significant advancements in psychiatric genomics with a special focus on our investigation of bipolar disorder. International consortiums and advocacy groups accelerate psychiatric genomics, increasing the sample size and statistical power for robust findings. The genetic architecture of schizophrenia has been elucidated in both common and rare variant studies. The genetic architecture of autism spectrum disorder (ASD) has been elucidated mainly by rare variant analysis. As to bipolar disorder, common variant analysis precedes rare variant analysis, but we are struggling to elucidate relevant rare variants. While the genomic approach has explained specific genetic factors for particular disorders, overlapping risk genes or pleiotropy has been observed more than expected. The boundary in the current nosology of psychiatric disorders is more or less challenged. To understand the genotype-phenotype relation more deeply, an attempt to understand phenotypes based on genotypes, called the "genotype first" approach, has started. I discuss this new approach for better understanding and treatment of psychiatric disorders.

The Interplay of Environmental Exposures and Mental Health: Setting an Agenda

BACKGROUND

To date, health-effects research on environmental stressors has rarely focused on behavioral and mental health outcomes. That lack of research is beginning to change. Science and policy experts in the environmental and behavioral health sciences are coming together to explore converging evidence on the relationship-harmful or beneficial-between environmental factors and mental health.

OBJECTIVES

To organize evidence and catalyze new findings, the National Academy of Sciences, Engineering, and Medicine (NASEM) hosted a workshop 2-3 February 2021 on the interplay of environmental exposures and mental health outcomes.

METHODS

This commentary provides a nonsystematic, expert-guided conceptual review and interdisciplinary perspective on the convergence of environmental and mental health, drawing from hypotheses, findings, and research gaps presented and discussed at the workshop. Featured is an overview of what is known about the intersection of the environment and mental health, focusing on the effects of neurotoxic pollutants, threats related to climate change, and the importance of health promoting environments, such as urban green spaces.

DISCUSSION

We describe what can be gained by bridging environmental and psychological research disciplines and present a synthesis of what is needed to advance interdisciplinary investigations. We also consider the implications of the current evidence for a) foundational knowledge of the etiology of mental health and illness, b) toxicant policy and regulation, c) definitions of climate adaptation and community resilience, d) interventions targeting marginalized communities, and e) the future of research training and funding. We include a call to action for environmental and mental health researchers, focusing on the environmental contributions to mental health to unlock primary prevention strategies at the population level and open equitable paths for preventing mental disorders and achieving optimal mental health for all. https://doi.org/10.1289/EHP9889.

The impact of HTR1A and HTR1B methylation combined with stress/genotype on early antidepressant efficacy

AIMS

Antidepressants are effective in the treatment of major depressive disorder (MDD), while many patients fail to respond to antidepressants. Both 5-HT1A (HTR1A) and 5-HT1B (HTR1B) receptors play an important role in antidepressant activity. Meanwhile, DNA methylation is associated with MDD and antidepressant efficacy. In this study we investigate the influence of HTR1A and HTR1B methylation combined with stress/genotype on antidepressant efficacy.

METHODS

A total of 291 MDD patients and 100 healthy controls received the Life Events Scale (LES) and the Childhood Trauma Questionnaire (CTQ) as stress assessment. Eight single nucleotide polymorphisms (SNPs) of HTR1A and HTR1B involved in antidepressant mechanisms were tested. Methylation status in 181 cytosine-phosphate-guanine (CpG) sites of HTR1A and HTR1B were assessed. All MDD patients were divided into response (RES) and non-response (NRES) after 2 weeks of antidepressant treatment. Logistic regression was conducted for interactions between methylation, NLES/CTQ score and genotype.

RESULTS

Low HTR1A-2-143 methylation is connected with better antidepressant efficacy in subgroup. Low HTR1A-2-143 methylation combined with low CTQ score is related to better antidepressant efficacy. The interaction between high HTR1B methylation with the rs6298 AA/AG genotype affects better antidepressant efficacy.

CONCLUSIONS

HTR1A and HTR1B methylation combined with stress/genotype is associated with antidepressant efficacy.

Genome-wide DNA methylation profiling in anorexia nervosa discordant identical twins

Up until now, no study has looked specifically at epigenomic landscapes throughout twin samples, discordant for Anorexia nervosa (AN). Our goal was to find evidence to confirm the hypothesis that epigenetic variations play a key role in the aetiology of AN. In this study, we quantified genome-wide patterns of DNA methylation using the Infinium Human DNA Methylation EPIC BeadChip array ("850 K") in DNA samples isolated from whole blood collected from a group of 7 monozygotic twin pairs discordant for AN. Results were then validated performing a genome-wide DNA methylation profiling using DNA extracted from whole blood of a group of non-family-related AN patients and a group of healthy controls. Our first analysis using the twin sample revealed 9 CpGs associated to a gene. The validation analysis showed two statistically significant CpGs with the rank regression method related to two genes associated to metabolic traits, PPP2R2C and CHST1. When doing beta regression, 6 of them showed statistically significant differences, including 3 CpGs associated to genes JAM3, UBAP2L and SYNJ2. Finally, the overall pattern of results shows genetic links to phenotypes which the literature has constantly related to AN, including metabolic and psychological traits. The genes PPP2R2C and CHST1 have both been linked to the metabolic traits type 2 diabetes through GWAS studies. The genes UBAP2L and SYNJ2 have been related to other psychiatric comorbidity.

OUP accepted manuscript

Epilepsy is one of the most frequent neurological diseases, with focal epilepsy accounting for the largest number of cases. The genetic alterations involved in focal epilepsy are far from being fully elucidated.

Here, we show that defective lipid signalling caused by heterozygous ultra-rare variants in PIK3C2B, encoding for the class II phosphatidylinositol 3-kinase PI3K-C2β, underlie focal epilepsy in humans. We demonstrate that patients’ variants act as loss-of-function alleles, leading to impaired synthesis of the rare signalling lipid phosphatidylinositol 3,4-bisphosphate, resulting in mTORC1 hyperactivation. In vivo, mutant Pik3c2b alleles caused dose-dependent neuronal hyperexcitability and increased seizure susceptibility, indicating haploinsufficiency as a key driver of disease. Moreover, acute mTORC1 inhibition in mutant mice prevented experimentally induced seizures, providing a potential therapeutic option for a selective group of patients with focal epilepsy.

Our findings reveal an unexpected role for class II PI3K-mediated lipid signalling in regulating mTORC1-dependent neuronal excitability in mice and humans.

Mapping brain asymmetry in health and disease through the ENIGMA consortium

Left-right asymmetry of the human brain is one of its cardinal features, and also a complex, multivariate trait. Decades of research have suggested that brain asymmetry may be altered in psychiatric disorders. However, findings have been inconsistent and often based on small sample sizes. There are also open questions surrounding which structures are asymmetrical on average in the healthy population, and how variability in brain asymmetry relates to basic biological variables such as age and sex. Over the last 4 years, the ENIGMA-Laterality Working Group has published six studies of gray matter morphological asymmetry based on total sample sizes from roughly 3,500 to 17,000 individuals, which were between one and two orders of magnitude larger than those published in previous decades. A population-level mapping of average asymmetry was achieved, including an intriguing fronto-occipital gradient of cortical thickness asymmetry in healthy brains. ENIGMA's multi-dataset approach also supported an empirical illustration of reproducibility of hemispheric differences across datasets. Effect sizes were estimated for gray matter asymmetry based on large, international, samples in relation to age, sex, handedness, and brain volume, as well as for three psychiatric disorders: autism spectrum disorder was associated with subtly reduced asymmetry of cortical thickness at regions spread widely over the cortex; pediatric obsessive-compulsive disorder was associated with altered subcortical asymmetry; major depressive disorder was not significantly associated with changes of asymmetry. Ongoing studies are examining brain asymmetry in other disorders. Moreover, a groundwork has been laid for possibly identifying shared genetic contributions to brain asymmetry and disorders.

OGDHL Variant rs2293239: A Potential Genetic Driver of Chinese Familial Depressive Disorder

Depressive disorders are a severe psychiatric and social problem that affect more than 4% of the global population. Depressive disorders have explicit hereditary characteristics; however, the precise driving genetic force behind these disorders has not yet been clearly illustrated. In the present study, we recruited a three-generation Chinese pedigree in which 5 of 17 members had long-term depression. We conducted whole-exome sequencing to identify the genetic mutation profiles of the family, and a list of susceptible genetic variations that were highly associated with depression onset was revealed via multiple omics analysis. In particular, a non-synonymous single nucleotide variation in the oxoglutarate dehydrogenase-like (OGDHL) gene, rs2293239 (p.Asn725Ser), was identified as one of the major driving genetic forces for depression onset in the family. This variant causes an important conformational change in the transketolase domain of OGDHL, thus reducing its binding affinity with the cofactor thiamine pyrophosphate and eventually resulting in the abnormal accumulation of glutamate in the brain. Brain imaging analysis further linked the rs2293239 variant with an enlarged amygdala and cerebellum in depressive family members. In summary, the present study enhances the current genetic understanding of depressive disorders. It also provides new options for prioritizing better clinical therapeutic regimens, as well as identifying a new protein target for the design of highly specific drugs to treat depressive disorders.

Gene × environment interaction in major depressive disorder

Major depressive disorder (MDD) is a multifactorial disorder, where multiple susceptibility genes interact with environmental factors, predisposing individuals to the development of the illness. In this article, we reviewed different gene × environment interaction (G×E) studies shifting from a candidate gene to a genome-wide approach. Among environmental factors, childhood adversities and stressful life events have been suggested to exert crucial impacts on MDD. Importantly, the diathesis-stress conceptualization of G×E has been challenged by the differential susceptibility theory. Finally, we summarized several limitations of G×E studies and suggested how future G×E studies might reveal complex interactions between genes and environments in MDD.

'Omics' of suicidal behaviour: A path to personalised psychiatry

Psychiatric disorders, including suicide, are complex disorders that are affected by many different risk factors. It has been estimated that genetic factors contribute up to 50% to suicide risk. As the candidate gene approach has not identified a gene or set of genes that can be defined as biomarkers for suicidal behaviour, much is expected from cutting edge technological approaches that can interrogate several hundred, or even millions, of biomarkers at a time. These include the '-omic' approaches, such as genomics, transcriptomics, epigenomics, proteomics and metabolomics. Indeed, these have revealed new candidate biomarkers associated with suicidal behaviour. The most interesting of these have been implicated in inflammation and immune responses, which have been revealed through different study approaches, from genome-wide single nucleotide studies and the micro-RNA transcriptome, to the proteome and metabolome. However, the massive amounts of data that are generated by the '-omic' technologies demand the use of powerful computational analysis, and also specifically trained personnel. In this regard, machine learning approaches are beginning to pave the way towards personalized psychiatry.

PTEN mutations in autism spectrum disorder and congenital hydrocephalus: developmental pleiotropy and therapeutic targets

The lack of effective treatments for autism spectrum disorder (ASD) and congenital hydrocephalus (CH) reflects the limited understanding of the biology underlying these common neurodevelopmental disorders. Although ASD and CH have been extensively studied as independent entities, recent human genomic and preclinical animal studies have uncovered shared molecular pathophysiology. Here, we review and discuss phenotypic, genomic, and molecular similarities between ASD and CH, and identify the PTEN-PI3K-mTOR (phosphatase and tensin homolog-phosphoinositide 3-kinase-mammalian target of rapamycin) pathway as a common underlying mechanism that holds diagnostic, prognostic, and therapeutic promise for individuals with ASD and CH.

Can animals develop depression? An overview and assessment of ‘depression-like’ states

Describing certain animal behaviours as ‘depression-like’ or ‘depressive’ has become common across several fields of research. These typically involve unusually low activity or unresponsiveness and/or reduced interest in pleasure (anhedonia). While the term ‘depression-like’ carefully avoids directly claiming that animals are depressed, this narrative review asks whether stronger conclusions can be legitimate, with animals developing the clinical disorder as seen in humans (cf., DSM-V/ICD-10). Here, we examine evidence from animal models of depression (especially chronically stressed rats) and animals experiencing poor welfare in conventional captive conditions (e.g., laboratory mice and production pigs in barren environments). We find troubling evidence that animals are indeed capable of experiencing clinical depression, but demonstrate that a true diagnosis has yet to be confirmed in any case. We thus highlight the importance of investigating the co-occurrence of depressive criteria and discuss the potential welfare and ethical implications of animal depression.

Three decades of ASD genetics: building a foundation for neurobiological understanding and treatment

Methodological advances over the last three decades have led to a profound transformation in our understanding of the genetic origins of neuropsychiatric disorders. This is exemplified by the study of autism spectrum disorders (ASDs) for which microarrays, whole exome sequencing and whole genome sequencing have yielded over a hundred causal loci. Genome-wide association studies in ASD have also been fruitful, identifying 5 genome-wide significant loci thus far and demonstrating a substantial role for polygenic inherited risk. Approaches rooted in systems biology and functional genomics have increasingly placed genes implicated by risk variants into biological context. Genetic risk affects a finite group of cell-types and biological processes, converging primarily on early stages of brain development (though, the expression of many risk genes persists through childhood). Coupled with advances in stem cell-based human in vitro model systems, these findings provide a basis for developing mechanistic models of disease pathophysiology.

Rediscovering Psilocybin as an Antidepressive Treatment Strategy

There has recently been a renewal of interest in psychedelic research on the use of psilocybin in psychiatric treatment and, in particular, for the treatment of major depressive disorder (MDD). Several state-of-the-art studies have provided new insight into the mechanisms of action of psilocybin and its therapeutic potential. Nevertheless, many questions remain unanswered. With this review, we provide an overview of the current state of research on the potential mechanisms of psilocybin, its antidepressant potential, and the associated risks and adverse effects, to provide an update on a controversial topic discussed in psychopharmacology. A database search was conducted in Medline including articles on psilocybin over the period of the last 20 years. Despite the promising progress in understanding the mechanisms of psilocybin, the exact antidepressive mechanism and the role of the psychedelic experience remain elusive. The studies included in this review found high treatment effect sizes for psilocybin as an antidepressant. However, the results must be regarded as preliminary due to several limitations. Although the current studies observed no severe adverse events, several questions regarding safety and utility remain and must be subject of future research.

Coexpression network architecture reveals the brain-wide and multiregional basis of disease susceptibility

Gene networks have yielded numerous neurobiological insights, yet an integrated view across brain regions is lacking. We leverage RNA sequencing in 864 samples representing 12 brain regions to robustly identify 12 brain-wide, 50 cross-regional and 114 region-specific coexpression modules. Nearly 40% of genes fall into brain-wide modules, while 25% comprise region-specific modules reflecting regional biology, such as oxytocin signaling in the hypothalamus, or addiction pathways in the nucleus accumbens. Schizophrenia and autism genetic risk are enriched in brain-wide and multiregional modules, indicative of broad impact; these modules implicate neuronal proliferation and activity-dependent processes, including endocytosis and splicing, in disease pathophysiology. We find that cell-type-specific long noncoding RNA and gene isoforms contribute substantially to regional synaptic diversity and that constrained, mutation-intolerant genes are primarily enriched in neurons. We leverage these data using an omnigenic-inspired network framework to characterize how coexpression and gene regulatory networks reflect neuropsychiatric disease risk, supporting polygenic models.

Long-Lasting Changes in Glial Cells Isolated From Rats Subjected to the Valproic Acid Model of Autism Spectrum Disorder

Synaptic alterations concomitant with neuroinflammation have been described in patients and experimental models of autism spectrum disorder (ASD). However, the role of microglia and astroglia in relation to synaptic changes is poorly understood. Male Wistar rats prenatally exposed to valproic acid (VPA, 450 mg/kg, i.p.) or saline (control) at embryonic day 10.5 were used to study synapses, microglia, and astroglia in the prefrontal cortex (PFC) at postnatal days 3 and 35 (PND3 and PND35). Primary cultures of cortical neurons, microglia, and astroglia isolated from control and VPA animals were used to study each cell type individually, neuron-microglia and microglia-astroglia crosstalk. In the PFC of VPA rats, synaptic changes characterized by an increase in the number of excitatory synapses were evidenced at PND3 and persisted until PND35. At PND3, microglia and astroglia from VPA animals were morphologically similar to those of age-matched controls, whereas at PND35, reactive microgliosis and astrogliosis were observed in the PFC of VPA animals. Cortical neurons isolated from VPA rats mimicked in vitro the synaptic pattern seen in vivo. Cortical microglia and astroglia isolated from VPA animals exhibited reactive morphology, increased pro-inflammatory cytokines, and a compromised miRNA processing machinery. Microglia from VPA animals also showed resistance to a phagocytic challenge. In the presence of neurons from VPA animals, microglia isolated from VPA rats revealed a non-reactive morphology and promoted neurite outgrowth, while microglia from control animals displayed a reactive profile and promoted dendritic retraction. In microglia-astroglia co-cultures, microglia from VPA animals displayed a reactive profile and exacerbated astrocyte reactivity. Our study indicates that cortical microglia from VPA animals are insensitive or adapted to neuronal cues expressed by neurons from VPA animals. Further, long-term in vivo microgliosis could be the result of altered microglia-astroglia crosstalk in VPA animals. Thus, our study highlights cortical microglia-astroglia communication as a new mechanism implicated in neuroinflammation in ASD; consequently, we propose that this crosstalk is a potential target for interventions in this disorder.

How does genetic variation modify ND-CNV phenotypes?

Rare copy-number variants (CNVs) associated with neurodevelopmental disorders (NDDs), i.e., ND-CNVs, provide an insight into the neurobiology of NDDs and, potentially, a link between biology and clinical outcomes. However, ND-CNVs are characterised by incomplete penetrance resulting in heterogeneous carrier phenotypes, ranging from non-affected to multimorbid psychiatric, neurological, and physical phenotypes. Recent evidence indicates that other variants in the genome, or 'other hits', may partially explain the variable expressivity of ND-CNVs. These may be other rare variants or the aggregated effects of common variants that modify NDD risk. Here we discuss the recent findings, current questions, and future challenges relating to other hits research in the context of ND-CNVs and their potential for improved clinical diagnostics and therapeutics for ND-CNV carriers.

3D Brain Organoids: Studying Brain Development and Disease Outside the Embryo

Scientists have been fascinated by the human brain for centuries, yet knowledge of the cellular and molecular events that build the human brain during embryogenesis and of how abnormalities in this process lead to neurological disease remains very superficial. In particular, the lack of experimental models for a process that largely occurs during human in utero development, and is therefore poorly accessible for study, has hindered progress in mechanistic understanding. Advances in stem cell-derived models of human organogenesis, in the form of three-dimensional organoid cultures, and transformative new analytic technologies have opened new experimental pathways for investigation of aspects of development, evolution, and pathology of the human brain. Here, we consider the biology of brain organoids, compared and contrasted with the endogenous human brain, and highlight experimental strategies to use organoids to pioneer new understanding of human brain pathology.

Unveiling the Pathogenesis of Psychiatric Disorders Using Network Models

Psychiatric disorders are complex brain disorders with a high degree of genetic heterogeneity, affecting millions of people worldwide. Despite advances in psychiatric genetics, the underlying pathogenic mechanisms of psychiatric disorders are still largely elusive, which impedes the development of novel rational therapies. There has been accumulating evidence suggesting that the genetics of complex disorders can be viewed through an omnigenic lens, which involves contextualizing genes in highly interconnected networks. Thus, applying network-based multi-omics integration methods could cast new light on the pathophysiology of psychiatric disorders. In this review, we first provide an overview of the recent advances in psychiatric genetics and highlight gaps in translating molecular associations into mechanistic insights. We then present an overview of network methodologies and review previous applications of network methods in the study of psychiatric disorders. Lastly, we describe the potential of such methodologies within a multi-tissue, multi-omics approach, and summarize the future directions in adopting diverse network approaches.

Potential causal effect of posttraumatic stress disorder on alcohol use disorder and alcohol consumption in individuals of European descent: A Mendelian Randomization Study

BACKGROUND

Posttraumatic stress disorder (PTSD) often co-occurs with alcohol consumption (AC) and alcohol use disorder (AUD). However, it is unknown whether the same etiologic influences that underlie PTSD co-occurring with AUD are those that underlie PTSD and AC individually.

METHODS

This study used large-scale genome-wide association study (GWAS) data to test whether PTSD and drinks per week [DPW]/AUD are causally related to one another, and, if so, whether PTSD precedes DPW/AUD and/or vice versa. We used Mendelian Randomization methods to analyze European ancestry GWAS summary statistics from the Psychiatric Genomics Consortium (PGC; PTSD), GWAS & Sequencing Consortium of Alcohol and Nicotine Use (GSCAN; DPW), and the Million Veteran Program (MVP; AUD).

RESULTS

PTSD exerted a potentially causal effect on AUD (β = 0.039, SE = 0.014, p = 0.005), but not on DPW (β = 0.002, SE = 0.003, p = 0.414). Additionally, neither DPW (β = 0.019, SE = 0.041, p = 0.637) nor AUD (β = 8.87 × 10^-4 , SE = 0.001, p = 0.441) exerted a causal effect on PTSD.

CONCLUSIONS

These findings are consistent with the self-medication model, in which individuals misuse alcohol to cope with aversive trauma-related symptoms. These findings extend latent analysis and molecular findings of shared and correlated risk between PTSD and alcohol phenotypes. Given the health behaviors associated with these phenotypes, these findings are important in that they suggest groups to prioritize for prevention efforts. Further, they provide a rationale for future preclinical and clinical studies examining the biological mechanisms by which PTSD may impact AUD.

Genetic loci shared between major depression and intelligence with mixed directions of effect

Genome-wide association studies (GWAS) have identified several common genetic variants influencing major depression and general cognitive abilities, but little is known about whether the two share any of their genetic aetiology. Here we investigate shared genomic architectures between major depression (MD) and general intelligence (INT) with the MiXeR statistical tool and their overlapping susceptibility loci with conjunctional false discovery rate (conjFDR), which evaluate the level of overlap in genetic variants and improve the power for gene discovery between two phenotypes. We analysed GWAS data on MD (n = 480,359) and INT (n = 269,867) to characterize polygenic architecture and identify genetic loci shared between these phenotypes. Despite non-significant genetic correlation (r_g = -0.0148, P = 0.50), we observed large polygenic overlap and identified 92 loci shared between MD and INT at conjFDR < 0.05. Among the shared loci, 69 and 64 are new for MD and INT, respectively. Our study demonstrates polygenic overlap between these phenotypes with a balanced mixture of effect.

Genetic Influences on Hippocampal Subfields: An Emerging Area of Neuroscience Research

There is clear evidence that hippocampal subfield volumes have partly distinct genetic determinants associated with specific biological processes. The identification of genetic correlates of hippocampal subfield volumes may help to elucidate the mechanisms of neurologic diseases, as well as aging and neurodegenerative processes. However, despite the emerging interest in this area of research, the current knowledge of the genetic architecture of hippocampal subfields has not yet been consolidated. We aimed to provide a review of the current evidence from genetic studies of hippocampal subfields, highlighting current priorities and upcoming challenges. The limited number of studies investigating the influential genetic effects on hippocampal subfields, a lack of replicated results and longitudinal designs, and modest sample sizes combined with insufficient standardization of protocols are identified as the most pressing challenges in this emerging area of research.

Transcriptomic networks implicate neuronal energetic abnormalities in three mouse models harboring autism and schizophrenia-associated mutations

Genetic risk for psychiatric illness is complex, so identification of shared molecular pathways where distinct forms of genetic risk might coincide is of substantial interest. A growing body of genetic and genomic studies suggest that such shared molecular pathways exist across disorders with different clinical presentations, such as schizophrenia and autism spectrum disorder (ASD). But how this relates to specific genetic risk factors is unknown. Further, whether some of the molecular changes identified in brain relate to potentially confounding antemortem or postmortem factors are difficult to prove. We analyzed the transcriptome from the cortex and hippocampus of three mouse lines modeling human copy number variants (CNVs) associated with schizophrenia and ASD: Df(h15q13)/+, Df(h22q11)/+, and Df(h1q21)/+ which carry the 15q13.3 deletion, 22q11.2 deletion, and 1q21.1 deletion, respectively. Although we found very little overlap of differential expression at the level of individual genes, gene network analysis identified two cortical and two hippocampal modules of co-expressed genes that were dysregulated across all three mouse models. One cortical module was associated with neuronal energetics and firing rate, and overlapped with changes identified in postmortem human brain from SCZ and ASD patients. These data highlight aspects of convergent gene expression in mouse models harboring major risk alleles, and strengthen the connection between changes in neuronal energetics and neuropsychiatric disorders in humans.

Can Molecular Biology Propose Reliable Biomarkers for Diagnosing Major Depression?

BACKGROUND

Modern medicine has provided considerable knowledge of the pathophysiology of mental disorders at the body, systemic, organ and neurochemical levels of the biological organization of the body. Modern clinical diagnostics of depression have some problems, that is why psychiatric society makes use of diagnostics and taxonomy of different types of depression by implemention of modern molecular biomarkers in diagnostic procedures. But up to now, there are no reliable biomarkers of major depressive disorder (MDD) and other types of depression.

OBJECTIVE

The purpose of this review is to find fundamentals in pathological mechanisms of depression, which could be a basis for development of molecular and genetic biomarkers, being the most feasible for clinical use.

METHOD

This review summarizes the published data using PubMed, Science Direct, Google Scholar and Scopus.

RESULTS

In this review, we summarized and discussed findings in molecular biology, genetics, neuroplasticity, neurotransmitters, and neuroimaging that could increase our understanding of the biological foundations of depression and show new directions for the development of reliable biomarkers. We did not find any molecular and genetic biomarker approved for the clinic. But the Genome-Wide Association Study method promises some progress in the development of biomarkers based on SNP in the future. Epigenetic factors also are a promising target for biomarkers. We have found some differences in the etiology of different types of atypical and melancholic depression. This knowledge could be the basis for development of biomarkers for clinical practice in diagnosis, prognosis and selection of treatment.

CONCLUSION

Depression is not a monoetiological disease. Many pathological mechanisms are involved in depression, thus up to now, there is no approved and reliable biomarker for diagnosis, prognosis and correction of treatment of depression. The structural and functional complexity of the brain, the lack of invasive technology, poor correlations between genetic and clinical manifestation of depression, imperfect psychiatric classification and taxonomy of subtypes of disease are the main causes of this situation. One of the possible ways to come over this situation can be to pay attention to the trigger mechanism of disease and its subtypes. Researchers and clinicians should focus their efforts on searching the trigger mechanism of depression and different types of it . HPA axis can be a candidate for such trigger in depression caused by stress, because it influences the main branches of disease: neuroinflammation, activity of biogenic amines, oxidative and nitrosative stress, epigenetic factors, metabolomics, etc. But before we shall find any trigger mechanism, we need to create complex biomarkers reflecting genetic, epigenetic, metabolomics and other pathological changes in different types of depression. Recently the most encouraging results have been obtained from genetics and neuroimaging. Continuing research in these areas should be forced by using computational, statistical and systems biology approaches, which can allow to obtain more knowledge about the neurobiology of depression. In order to obtain clinically useful tests, search for biomarkers should use appropriate research methodologies with increasing samples and identifying more homogeneous groups of depressed patients.

Interneuron development and dysfunction

Understanding excitation and inhibition balance in the brain begins with the tale of two basic types of neurons, glutamatergic projection neurons and GABAergic interneurons. The diversity of cortical interneurons is contributed by multiple origins in the ventral forebrain, various tangential migration routes, and complicated regulations of intrinsic factors, extrinsic signals, and activities. Abnormalities of interneuron development lead to dysfunction of interneurons and inhibitory circuits, which are highly associated with neurodevelopmental disorders including schizophrenia, autism spectrum disorders, and intellectual disability. In this review, we mainly discuss recent findings on the development of cortical interneuron and on neurodevelopmental disorders related to interneuron dysfunction.

Psychiatric Neural Networks and Precision Therapeutics by Machine Learning

Learning and environmental adaptation increase the likelihood of survival and improve the quality of life. However, it is often difficult to judge optimal behaviors in real life due to highly complex social dynamics and environment. Consequentially, many different brain regions and neuronal circuits are involved in decision-making. Many neurobiological studies on decision-making show that behaviors are chosen through coordination among multiple neural network systems, each implementing a distinct set of computational algorithms. Although these processes are commonly abnormal in neurological and psychiatric disorders, the underlying causes remain incompletely elucidated. Machine learning approaches with multidimensional data sets have the potential to not only pathologically redefine mental illnesses but also better improve therapeutic outcomes than DSM/ICD diagnoses. Furthermore, measurable endophenotypes could allow for early disease detection, prognosis, and optimal treatment regime for individuals. In this review, decision-making in real life and psychiatric disorders and the applications of machine learning in brain imaging studies on psychiatric disorders are summarized, and considerations for the future clinical translation are outlined. This review also aims to introduce clinicians, scientists, and engineers to the opportunities and challenges in bringing artificial intelligence into psychiatric practice.

The "missing heritability"-Problem in psychiatry: Is the interaction of genetics, epigenetics and transposable elements a potential solution?

Psychiatric disorders exhibit an enormous burden on the health care systems worldwide accounting for around one-third of years lost due to disability among adults. Their etiology is largely unknown and diagnostic classification is based on symptomatology and course of illness and not on objective biomarkers. Most psychiatric disorders are moderately to highly heritable. However, it is still unknown what mechanisms may explain the discrepancy between heritability estimates and the present data from genetic analysis. In addition to genetic differences also epigenetic modifications are considered as potentially relevant in the transfer of susceptibility to psychiatric diseases. Though, whether or not epigenetic alterations can be inherited for many generations is highly controversial. In the present article, we will critically summarize both the genetic findings and the results from epigenetic analyses, including also those of noncoding RNAs. We will argue that one possible solution to the "missing heritability" problem in psychiatry is a potential role of retrotransposons, the exploration of which is presently only in its beginnings.

Experimental Therapeutics in Treatment-Resistant Major Depressive Disorder

Treatment-Resistant Depression (TRD) patients remain a challenging sub-division of patients with Major Depressive Disorder (MDD) in day to day clinical practice. As with any diagnostic condition, comprehensive evaluation, exclusion of other psychiatric conditions, assessment of co-morbid medical and psychiatric illnesses and psychosocial stressors are the keys to appropriate diagnosis and subsequent management. There are various management options available for the treatment of MDD, however, about 30% of the patients fail to achieve full remission of symptoms despite multiple trials and belong to this sub-category of MDD. This article brings forth discussion of other non-conventional medication and non-medication treatment alternatives that merit exploration of their efficacy in TRD. Many of the proposed novel medications and other treatment modalities such as Deep Brain Stimulation, exercise, yoga are already used for other medical and psychiatric disorders and have some evidence suggesting their potential benefits in TRD in conjunction with conventional medications or even as monotherapy. Nevertheless, more research is needed in this direction to establish effectiveness.

The emerging role of chromatin remodelers in neurodevelopmental disorders: a developmental perspective

Neurodevelopmental disorders (NDDs), including intellectual disability (ID) and autism spectrum disorders (ASD), are a large group of disorders in which early insults during brain development result in a wide and heterogeneous spectrum of clinical diagnoses. Mutations in genes coding for chromatin remodelers are overrepresented in NDD cohorts, pointing towards epigenetics as a convergent pathogenic pathway between these disorders. In this review we detail the role of NDD-associated chromatin remodelers during the developmental continuum of progenitor expansion, differentiation, cell-type specification, migration and maturation. We discuss how defects in chromatin remodelling during these early developmental time points compound over time and result in impaired brain circuit establishment. In particular, we focus on their role in the three largest cell populations: glutamatergic neurons, GABAergic neurons, and glia cells. An in-depth understanding of the spatiotemporal role of chromatin remodelers during neurodevelopment can contribute to the identification of molecular targets for treatment strategies.

Epigenetics in bipolar disorder: a critical review of the literature

INTRODUCTION

Bipolar disorder (BD) is a chronic, disabling disease characterised by alternate mood episodes, switching through depressive and manic/hypomanic phases. Mood stabilizers, in particular lithium salts, constitute the cornerstone of the treatment in the acute phase as well as for the prevention of recurrences. The pathophysiology of BD and the mechanisms of action of mood stabilizers remain largely unknown but several pieces of evidence point to gene x environment interactions. Epigenetics, defined as the regulation of gene expression without genetic changes, could be the molecular substrate of these interactions. In this literature review, we summarize the main epigenetic findings associated with BD and response to mood stabilizers.

METHODS

We searched PubMed, and Embase databases and classified the articles depending on the epigenetic mechanisms (DNA methylation, histone modifications and non-coding RNAs).

RESULTS

We present the different epigenetic modifications associated with BD or with mood-stabilizers. The major reported mechanisms were DNA methylation, histone methylation and acetylation, and non-coding RNAs. Overall, the assessments are poorly harmonized and the results are more limited than in other psychiatric disorders (e.g. schizophrenia). However, the nature of BD and its treatment offer excellent opportunities for epigenetic research: clear impact of environmental factors, clinical variation between manic or depressive episodes resulting in possible identification of state and traits biomarkers, documented impact of mood-stabilizers on the epigenome.

CONCLUSION

Epigenetic is a growing and promising field in BD that may shed light on its pathophysiology or be useful as biomarkers of response to mood-stabilizer.

Genomic Variation, Evolvability, and the Paradox of Mental Illness

Twentieth-century genetics was hard put to explain the irregular behavior of neuropsychiatric disorders. Autism and schizophrenia defy a principle of natural selection; they are highly heritable but associated with low reproductive success. Nevertheless, they persist. The genetic origins of such conditions are confounded by the problem of variable expression, that is, when a given genetic aberration can lead to any one of several distinct disorders. Also, autism and schizophrenia occur on a spectrum of severity, from mild and subclinical cases to the overt and disabling. Such irregularities reflect the problem of missing heritability; although hundreds of genes may be associated with autism or schizophrenia, together they account for only a small proportion of cases. Techniques for higher resolution, genomewide analysis have begun to illuminate the irregular and unpredictable behavior of the human genome. Thus, the origins of neuropsychiatric disorders in particular and complex disease in general have been illuminated. The human genome is characterized by a high degree of structural and behavioral variability: DNA content variation, epistasis, stochasticity in gene expression, and epigenetic changes. These elements have grown more complex as evolution scaled the phylogenetic tree. They are especially pertinent to brain development and function. Genomic variability is a window on the origins of complex disease, neuropsychiatric disorders, and neurodevelopmental disorders in particular. Genomic variability, as it happens, is also the fuel of evolvability. The genomic events that presided over the evolution of the primate and hominid lineages are over-represented in patients with autism and schizophrenia, as well as intellectual disability and epilepsy. That the special qualities of the human genome that drove evolution might, in some way, contribute to neuropsychiatric disorders is a matter of no little interest.

The Auditory Steady-State Response: Electrophysiological Index for Sensory Processing Dysfunction in Psychiatric Disorders

Sensory processing is disrupted in several psychiatric disorders, including schizophrenia, bipolar disorder, and autism spectrum disorder. In this review, we focus on the electrophysiological auditory steady-state response (ASSR) driven by high-frequency stimulus trains as an index for disease-associated sensory processing deficits. The ASSR amplitude is suppressed within the gamma band (≥30 Hz) among these patients, suggesting an imbalance between GABAergic and N-methyl-D-aspartate (NMDA) receptor-mediated neurotransmission. The reduced power and synchronization of the 40-Hz ASSR are robust in patients with schizophrenia. In recent years, similar ASSR deficits at gamma frequencies have also been reported in patients with bipolar disorder and autism spectrum disorder. We summarize ASSR abnormalities in each of these psychiatric disorders and suggest that the observed commonalities reflect shared pathophysiological mechanisms. We reviewed studies on phase resetting in which a salient sensory stimulus affects ASSR. Phase resetting induces the reduction of both the amplitude and phase of ASSR. Moreover, phase resetting is also affected by rare auditory stimulus patterns or superimposed stimuli of other modalities. Thus, sensory memory and multisensory integration can be investigated using phase resetting of ASSR. Here, we propose that ASSR amplitude, phase, and resetting responses are sensitive indices for investigating sensory processing dysfunction in psychiatric disorders.

Impaired expression of the COSMOC/MOCOS gene unit in ASD patient stem cells

Autism spectrum disorders (ASD) are complex neurodevelopmental disorders with a very large number of risk loci detected in the genome. However, at best, each of them explains rare cases, the majority being idiopathic. Genomic data on ASD derive mostly from post-mortem brain analyses or cell lines derived from blood or patient-specific induced pluripotent stem cells (iPSCS). Therefore, the transcriptional and regulatory architecture of the nervous system, particularly during early developmental periods, remains highly incomplete. To access the critical disturbances that may have occurred during pregnancy or early childhood, we recently isolated stem cells from the nasal cavity of anesthetized patients diagnosed for ASD and compared them to stem cells from gender-matched control individuals without neuropsychiatric disorders. This allowed us to discover MOCOS, a non-mutated molybdenum cofactor sulfurase-coding gene that was under-expressed in the stem cells of most ASD patients of our cohort, disturbing redox homeostasis and synaptogenesis. We now report that a divergent transcription upstream of MOCOS generates an antisense long noncoding RNA, to which we coined the name COSMOC. Surprisingly, COSMOC is strongly under-expressed in all ASD patients of our cohort with the exception of a patient affected by Asperger syndrome. Knockdown studies indicate that loss of COSMOC reduces MOCOS expression, destabilizes lipid and energy metabolisms of stem cells, but also affects neuronal maturation and splicing of synaptic genes. Impaired expression of the COSMOC/MOCOS bidirectional unit might shed new lights on the origins of ASD that could be of importance for future translational studies.

Metabolomic changes in animal models of depression: a systematic analysis

Extensive research has been carried out on the metabolomic changes in animal models of depression; however, there is no general agreement about which metabolites exhibit constant changes. Therefore, the aim of this study was to identify consistently altered metabolites in large-scale metabolomics studies of depression models. We performed vote counting analyses to identify consistently upregulated or downregulated metabolites in the brain, blood, and urine of animal models of depression based on 3743 differential metabolites from 241 animal metabolomics studies. We found that serotonin, dopamine, gamma-aminobutyric acid, norepinephrine, N-acetyl-L-aspartic acid, anandamide, and tryptophan were downregulated in the brain, while kynurenine, myo-inositol, hydroxykynurenine, and the kynurenine to tryptophan ratio were upregulated. Regarding blood metabolites, tryptophan, leucine, tyrosine, valine, trimethylamine N-oxide, proline, oleamide, pyruvic acid, and serotonin were downregulated, while N-acetyl glycoprotein, corticosterone, and glutamine were upregulated. Moreover, citric acid, oxoglutaric acid, proline, tryptophan, creatine, betaine, L-dopa, palmitic acid, and pimelic acid were downregulated, and hippuric acid was upregulated in urine. We also identified consistently altered metabolites in the hippocampus, prefrontal cortex, serum, and plasma. These findings suggested that metabolomic changes in depression models are characterized by decreased neurotransmitter and increased kynurenine metabolite levels in the brain, decreased amino acid and increased corticosterone levels in blood, and imbalanced energy metabolism and microbial metabolites in urine. This study contributes to existing knowledge of metabolomic changes in depression and revealed that the reproducibility of candidate metabolites was inadequate in previous studies.

Turning strains into strengths for understanding psychiatric disorders

There is a paucity in the development of new mechanistic insights and therapeutic approaches for treating psychiatric disease. One of the major challenges is reflected in the growing consensus that risk for these diseases is not determined by a single gene, but rather is polygenic, arising from the action and interaction of multiple genes. Canonically, experimental models in mice have been designed to ascertain the relative contribution of a single gene to a disease by systematic manipulation (e.g., mutation or deletion) of a known candidate gene. Because these studies have been largely carried out using inbred isogenic mouse strains, in which there is no (or very little) genetic diversity among subjects, it is difficult to identify unique allelic variants, gene modifiers, and epigenetic factors that strongly affect the nature and severity of these diseases. Here, we review various methods that take advantage of existing genetic diversity or that increase genetic variance in mouse models to (1) strengthen conclusions of single-gene function; (2) model diversity among human populations; and (3) dissect complex phenotypes that arise from the actions of multiple genes.

Functional genomics links genetic origins to pathophysiology in neurodegenerative and neuropsychiatric disease

Neurodegenerative and neuropsychiatric disorders are pervasive and debilitating conditions characterized by diverse clinical syndromes and comorbidities, whose origins are as complex and heterogeneous as their associated phenotypes. Risk for these disorders involves substantial genetic liability, which has fueled large-scale genetic studies that have led to a flood of discoveries. In turn, these discoveries have exposed substantial gaps in our knowledge with regards to the complicated genetic architecture of each disorder and the substantial amount of genetic overlap among disorders, which implies some degree of shared pathophysiology underlying these clinically distinct, multifactorial disorders. Understanding the role of specific genetic variants will involve resolving the connections between molecular pathways, heterogeneous cell types, specific circuits and disease pathogenesis at the tissue and patient level. We consider the current known genetic basis of these disorders and highlight the utility of molecular systems approaches that establish the function of genetic variation in the context of specific neurobiological networks, cell-types, and life stages. Beyond expanding our knowledge of disease mechanisms, understanding these relationships provides promise for early detection and potential therapeutic interventions.

Lowering costs for large-scale screening in psychosis: a systematic review and meta-analysis of performance and value of information for speech-based psychiatric evaluation

OBJECTIVE

Obstacles for computational tools in psychiatry include gathering robust evidence and keeping implementation costs reasonable. We report a systematic review of automated speech evaluation for the psychosis spectrum and analyze the value of information for a screening program in a healthcare system with a limited number of psychiatrists (Maputo, Mozambique).

METHODS

Original studies on speech analysis for forecasting of conversion in individuals at clinical high risk (CHR) for psychosis, diagnosis of manifested psychotic disorder, and first-episode psychosis (FEP) were included in this review. Studies addressing non-verbal components of speech (e.g., pitch, tone) were excluded.

RESULTS

Of 168 works identified, 28 original studies were included. Valuable speech features included direct measures (e.g., relative word counting) and mathematical embeddings (e.g.: word-to-vector, graphs). Accuracy estimates reported for schizophrenia diagnosis and CHR conversion ranged from 71 to 100% across studies. Studies used structured interviews, directed tasks, or prompted free speech. Directed-task protocols were faster while seemingly maintaining performance. The expected value of perfect information is USD 9.34 million. Imperfect tests would nevertheless yield high value.

CONCLUSION

Accuracy for screening and diagnosis was high. Larger studies are needed to enhance precision of classificatory estimates. Automated analysis presents itself as a feasible, low-cost method which should be especially useful for regions in which the physician pool is insufficient to meet demand.

Modeling brain development and diseases with human cerebral organoids

Understanding the mechanisms that underlie human brain development and neurological and neuropsychiatric disorders is one of the key topics of neurobiology. Because of the poor accessibility of human and non-human primate brain tissues, the current perception and understanding of human brain development have been mainly derived from studies of rodents. However, some human-specific features of neural development cannot be well characterized by these animal models. Thanks to the advances in stem cell technologies, brain organoids are being under rapid development, showing the promising applications in decoding the human brain development and uncovering the pathology of brain diseases. In this review, we mainly summarized the recent advances in the development of brain organoid technology and discussed the limitations, applications and future prospects of this promising field.

Face individual identity recognition: a potential endophenotype in autism

BACKGROUND

Face individual identity recognition skill is heritable and independent of intellectual ability. Difficulties in face individual identity recognition are present in autistic individuals and their family members and are possibly linked to oxytocin polymorphisms in families with an autistic child. While it is reported that developmental prosopagnosia (i.e., impaired face identity recognition) occurs in 2-3% of the general population, no prosopagnosia prevalence estimate is available for autism. Furthermore, an autism within-group approach has not been reported towards characterizing impaired face memory and to investigate its possible links to social and communication difficulties.

METHODS

The present study estimated the prevalence of prosopagnosia in 80 autistic adults with no intellectual disability, investigated its cognitive characteristics and links to autism symptoms' severity, personality traits, and mental state understanding from the eye region by using standardized tests and questionnaires.

RESULTS

More than one third of autistic participants showed prosopagnosia. Their face memory skill was not associated with their symptom's severity, empathy, alexithymia, or general intelligence. Face identity recognition was instead linked to mental state recognition from the eye region only in autistic individuals who had prosopagnosia, and this relationship did not depend on participants' basic face perception skills. Importantly, we found that autistic participants were not aware of their face memory skills.

LIMITATIONS

We did not test an epidemiological sample, and additional work is necessary to establish whether these results generalize to the entire autism spectrum.

CONCLUSIONS

Impaired face individual identity recognition meets the criteria to be a potential endophenotype in autism. In the future, testing for face memory could be used to stratify autistic individuals into genetically meaningful subgroups and be translatable to autism animal models.

Epigenetic mechanisms underlying stress-induced depression

Stressful life events are a major contributor to the development of major depressive disorder. Environmental perturbations like stress change gene expression in the brain, leading to altered behavior. Gene expression is ultimately regulated by chromatin structure and the epigenetic modifications of DNA and the histone proteins that make up chromatin. Studies over the past two decades have demonstrated that stress alters the epigenetic landscape in several brain regions relevant for depressive-like behavior in rodents. This chapter will discuss epigenetic mechanisms of brain histone acetylation, histone methylation, and DNA methylation that contribute to adult stress-induced depressive-like behavior in rodents. Several biological themes have emerged from the examination of the brain transcriptome after stress such as alterations in the neuroimmune response, neurotrophic factors, and synaptic structure. The epigenetic mechanisms regulating these processes will be highlighted. Finally, pharmacological and genetic manipulations of epigenetic enzymes in rodent models of depression will be discussed as these approaches have demonstrated the ability to reverse stress-induced depressive-like behaviors and provide proof-of-concept as novel avenues for the treatment of clinical depression.

Overlapping but Asymmetrical Relationships Between Schizophrenia and Autism Revealed by Brain Connectivity

Although the relationship between schizophrenia spectrum disorder (SSD) and autism spectrum disorder (ASD) has long been debated, it has not yet been fully elucidated. The authors quantified and visualized the relationship between ASD and SSD using dual classifiers that discriminate patients from healthy controls (HCs) based on resting-state functional connectivity magnetic resonance imaging. To develop a reliable SSD classifier, sophisticated machine-learning algorithms that automatically selected SSD-specific functional connections were applied to Japanese datasets from Kyoto University Hospital (N = 170) including patients with chronic-stage SSD. The generalizability of the SSD classifier was tested by 2 independent validation cohorts, and 1 cohort including first-episode schizophrenia. The specificity of the SSD classifier was tested by 2 Japanese cohorts of ASD and major depressive disorder. The weighted linear summation of the classifier's functional connections constituted the biological dimensions representing neural classification certainty for the disorders. Our previously developed ASD classifier was used as ASD dimension. Distributions of individuals with SSD, ASD, and HCs s were examined on the SSD and ASD biological dimensions. We found that the SSD and ASD populations exhibited overlapping but asymmetrical patterns in the 2 biological dimensions. That is, the SSD population showed increased classification certainty for the ASD dimension but not vice versa. Furthermore, the 2 dimensions were correlated within the ASD population but not the SSD population. In conclusion, using the 2 biological dimensions based on resting-state functional connectivity enabled us to discover the quantified relationships between SSD and ASD.