Defining the Genetic, Genomic, Cellular, and Diagnostic Architectures of Psychiatric Disorders

A phenome-wide association and Mendelian Randomisation study of polygenic risk for depression in UK Biobank

Depression is a leading cause of worldwide disability but there remains considerable uncertainty regarding its neural and behavioural associations. Here, using non-overlapping Psychiatric Genomics Consortium (PGC) datasets as a reference, we estimate polygenic risk scores for depression (depression-PRS) in a discovery (N = 10,674) and replication (N = 11,214) imaging sample from UK Biobank. We report 77 traits that are significantly associated with depression-PRS, in both discovery and replication analyses. Mendelian Randomisation analysis supports a potential causal effect of liability to depression on brain white matter microstructure (β: 0.125 to 0.868, p_FDR < 0.043). Several behavioural traits are also associated with depression-PRS (β: 0.014 to 0.180, p_FDR: 0.049 to 1.28 × 10⁻¹⁴) and we find a significant and positive interaction between depression-PRS and adverse environmental exposures on mental health outcomes. This study reveals replicable associations between depression-PRS and white matter microstructure. Our results indicate that white matter microstructure differences may be a causal consequence of liability to depression.

Depression is correlated with many brain-related traits. Here, Shen et al. perform phenome-wide association studies of a depression polygenic risk score (PRS) and find associations with 51 behavioural and 26 neuroimaging traits which are further followed up on using Mendelian randomization and mediation analyses.

Insufficient Evidence for "Autism-Specific" Genes

Despite evidence that deleterious variants in the same genes are implicated across multiple neurodevelopmental and neuropsychiatric disorders, there has been considerable interest in identifying genes that, when mutated, confer risk that is largely specific for autism spectrum disorder (ASD). Here, we review the findings and limitations of recent efforts to identify relatively “autism-specific” genes, efforts which focus on rare variants of large effect size that are thought to account for the observed phenotypes. We present a divergent interpretation of published evidence; discuss practical and theoretical issues related to studying the relationships between rare, large-effect deleterious variants and neurodevelopmental phenotypes; and describe potential future directions of this research. We argue that there is currently insufficient evidence to establish meaningful ASD specificity of any genes based on large-effect rare-variant data.

Current challenges and possible future developments in personalized psychiatry with an emphasis on psychotic disorders

A personalized medicine approach seems to be particularly applicable to psychiatry. Indeed, considering mental illness as deregulation, unique to each patient, of molecular pathways, governing the development and functioning of the brain, seems to be the most justified way to understand and treat disorders of this medical category. In order to extract correct information about the implicated molecular pathways, data can be drawn from sampling phenotypic and genetic biomarkers and then analyzed by a machine learning algorithm. This review describes current difficulties in the field of personalized psychiatry and gives several examples of possibly actionable biomarkers of psychotic and other psychiatric disorders, including several examples of genetic studies relevant to personalized psychiatry. Most of these biomarkers are not yet ready to be introduced in clinical practice. In a next step, a perspective on the path personalized psychiatry may take in the future is given, paying particular attention to machine learning algorithms that can be used with the goal of handling multidimensional datasets.

Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson's disease

Genome-wide association studies have discovered hundreds of loci associated with complex brain disorders, but it remains unclear in which cell types these loci are active. Here we integrate genome-wide association study results with single-cell transcriptomic data from the entire mouse nervous system to systematically identify cell types underlying brain complex traits. We show that psychiatric disorders are predominantly associated with projecting excitatory and inhibitory neurons. Neurological diseases were associated with different cell types, which is consistent with other lines of evidence. Notably, Parkinson's disease was genetically associated not only with cholinergic and monoaminergic neurons (which include dopaminergic neurons) but also with enteric neurons and oligodendrocytes. Using post-mortem brain transcriptomic data, we confirmed alterations in these cells, even at the earliest stages of disease progression. Our study provides an important framework for understanding the cellular basis of complex brain maladies, and reveals an unexpected role of oligodendrocytes in Parkinson's disease.

Translating insights from neuropsychiatric genetics and genomics for precision psychiatry

The primary aim of precision medicine is to tailor healthcare more closely to the needs of individual patients. This requires progress in two areas: the development of more precise treatments and the ability to identify patients or groups of patients in the clinic for whom such treatments are likely to be the most effective. There is widespread optimism that advances in genomics will facilitate both of these endeavors. It can be argued that of all medical specialties psychiatry has most to gain in these respects, given its current reliance on syndromic diagnoses, the minimal foundation of existing mechanistic knowledge, and the substantial heritability of psychiatric phenotypes. Here, we review recent advances in psychiatric genomics and assess the likely impact of these findings on attempts to develop precision psychiatry. Emerging findings indicate a high degree of polygenicity and that genetic risk maps poorly onto the diagnostic categories used in the clinic. The highly polygenic and pleiotropic nature of psychiatric genetics will impact attempts to use genomic data for prediction and risk stratification, and also poses substantial challenges for conventional approaches to gaining biological insights from genetic findings. While there are many challenges to overcome, genomics is building an empirical platform upon which psychiatry can now progress towards better understanding of disease mechanisms, better treatments, and better ways of targeting treatments to the patients most likely to benefit, thus paving the way for precision psychiatry.

Increased burden of ultra-rare structural variants localizing to boundaries of topologically associated domains in schizophrenia

Despite considerable progress in schizophrenia genetics, most findings have been for large rare structural variants and common variants in well-imputed regions with few genes implicated from exome sequencing. Whole genome sequencing (WGS) can potentially provide a more complete enumeration of etiological genetic variation apart from the exome and regions of high linkage disequilibrium. We analyze high-coverage WGS data from 1162 Swedish schizophrenia cases and 936 ancestry-matched population controls. Our main objective is to evaluate the contribution to schizophrenia etiology from a variety of genetic variants accessible to WGS but not by previous technologies. Our results suggest that ultra-rare structural variants that affect the boundaries of topologically associated domains (TADs) increase risk for schizophrenia. Alterations in TAD boundaries may lead to dysregulation of gene expression. Future mechanistic studies will be needed to determine the precise functional effects of these variants on biology.

Modeling the complex genetic architectures of brain disease

The genetic architecture of each individual comprises common and rare variants that, acting alone and in combination, confer risk of disease. The cell-type-specific and/or context-dependent functional consequences of the risk variants linked to brain disease must be resolved. Coupling human induced pluripotent stem cell (hiPSC)-based technology with CRISPR-based genome engineering facilitates precise isogenic comparisons of variants across genetic backgrounds. Although functional-validation studies are typically performed on one variant in isolation and in one cell type at a time, complex genetic diseases require multiplexed gene perturbations to interrogate combinations of genes and resolve physiologically relevant disease biology. Our aim is to discuss advances at the intersection of genomics, hiPSCs and CRISPR. A better understanding of the molecular mechanisms underlying disease risk will improve genetic diagnosis, drive phenotypic drug discovery and pave the way toward precision medicine.

Identification of relevant hub genes for early intervention at gene coexpression modules with altered predicted expression in schizophrenia

Genetic risk for schizophrenia is due to the joint effect of multiple genes acting mainly at two different processes, prenatal/perinatal neurodevelopment and adolescence/early adulthood synapse maturation. Identification of important genes at the second process is of relevance for early intervention. The aim of this work was to identify gene co-expression modules with altered expression in schizophrenia during adolescence/early adulthood. To this goal, we predicted frontal cortex gene expression in one discovery sample, the largest GWAS of schizophrenia from the Psychiatric Genomics Consortium, using S-prediXcan, and in one target sample, consisting of 625 schizophrenic patients and 819 controls from Spain, using prediXcan. Prediction models were trained on GTEx frontal cortex expression dataset. In parallel, we identified brain co-expression modules from BrainSpan using WGCNA. Then, we estimated polygenic risk scores based on predicted expression (PE-PRS) for each co-expression module in the target sample, based on PE-PRS model from the discovery sample. This analysis led to the identification of a module with mainly adolescence/adulthood expression whose PE-PRS was significantly associated with schizophrenia. The module was significantly enriched in synaptic processes. Several hub genes at this module are drugabble, according to the drug-gene interaction database, and/or involved in synaptic transmission, such as the voltage-gated ion channels SCN2B and KCNAB2, the calcium calmodulin kinases CAMK2A and CAMK1G, or genes involved in synaptic vesicle cycle, such as DNM1, or SYNGR1. Therefore, identification of this module may be the first step in patient stratification based on biology, as well as in drug design and drug repurposing efforts.

Structural variation in the sequencing era

Identifying structural variation (SV) is essential for genome interpretation but has been historically difficult due to limitations inherent to available genome technologies. Detection methods that use ensemble algorithms and emerging sequencing technologies have enabled the discovery of thousands of SVs, uncovering information about their ubiquity, relationship to disease and possible effects on biological mechanisms. Given the variability in SV type and size, along with unique detection biases of emerging genomic platforms, multiplatform discovery is necessary to resolve the full spectrum of variation. Here, we review modern approaches for investigating SVs and proffer that, moving forwards, studies integrating biological information with detection will be necessary to comprehensively understand the impact of SV in the human genome.

One Single Nucleotide Polymorphism of the TRPM2 Channel Gene Identified as a Risk Factor in Bipolar Disorder Associates with Autism Spectrum Disorder in a Japanese Population

The transient receptor potential melastatin 2 (TRPM2) is a non-specific cation channel, resulting in Ca2+ influx at warm temperatures from 34 °C to 47 °C, thus including the body temperature range in mammals. TRPM2 channels are activated by β-NAD+, ADP-ribose (ADPR), cyclic ADPR, and 2'-deoxyadenosine 5'-diphosphoribose. It has been shown that TRPM2 cation channels and CD38, a type II or type III transmembrane protein with ADP-ribosyl cyclase activity, simultaneously play a role in heat-sensitive and NAD+ metabolite-dependent intracellular free Ca2+ concentration increases in hypothalamic oxytocinergic neurons. Subsequently, oxytocin (OT) is released to the brain. Impairment of OT release may induce social amnesia, one of the core symptoms of autism spectrum disorder (ASD). The risk of single nucleotide polymorphisms (SNPs) and variants of TRPM2 have been reported in bipolar disorder, but not in ASD. Therefore, it is reasonable to examine whether SNPs or haplotypes in TRPM2 are associated with ASD. Here, we report a case-control study with 147 ASD patients and 150 unselected volunteers at Kanazawa University Hospital in Japan. The sequence-specific primer-polymerase chain reaction method together with fluorescence correlation spectroscopy was applied. Of 14 SNPs examined, one SNP (rs933151) displayed a significant p-value (OR = 0.1798, 95% CI = 0.039, 0.83; Fisher's exact test; p = 0.0196). The present research data suggest that rs93315, identified as a risk factor for bipolar disorder, is a possible association factor for ASD.

Association of Genetic Risks With Autism Spectrum Disorder and Early Neurodevelopmental Delays Among Children Without Intellectual Disability

Importance

Autism spectrum disorder (ASD) is highly heritable, and modest contributions of common genetic variants to ASD have been reported. However, the association of genetic risks derived from common risk variants with ASD traits in children from the general population is not clear, and the association of these genetic risks with neurodevelopment in infants has not been well understood.

Objective

To test whether a polygenic risk score (PRS) for ASD is associated with neurodevelopmental progress at age 18 months and ASD traits at age 6 years among children from the general population.

Design, Setting, and Participants

In this cohort study, 876 children in the Hamamatsu Birth Cohort for Mothers and Children in Hamamatsu, Japan, underwent testing for the association of an ASD PRS with neurodevelopmental progress and ASD traits. Data collection began in December 2007 and is ongoing. Data analysis was conducted from April to December 2019.

Main Outcomes and Measures

Summary data from the largest genome-wide association study were used to generate ASD PRSs, and significance of thresholds was calculated for each outcome. The Autism Diagnostic Observation Schedule 2 was used to measure ASD traits at age 6 years, and the Mullen Scales of Early Learning was used to measure neurodevelopmental progress at age 18 months.

Results

Of 876 participants (mean [SD] gestational age at birth, 38.9 [1.6] weeks; 438 [50.0%] boys; 868 [99.1%] Japanese), 734 were analyzed. The ASD PRS was associated with ASD traits (R2 = 0.024; β, 0.71; SE, 0.24; P = .03). The association of ASD PRS with infant neurodevelopment was most pronounced in gross motor (R2 = 0.015; β, -1.25; SE, 0.39; P = .01) and receptive language (R2 = 0.014; β, -1.19; SE, 0.39; P = .02) scores on the Mullen Scales of Early Learning. Gene set enrichment analyses found that several pathways, such as cell maturation (R2 = 0.057; β, -5.28; SE, 1.40; P < .001) and adenylyl cyclase activity and cyclic adenosine monophosphate concentration (R2 = 0.064; β, -5.30; SE 1.30; P < .001), were associated with ASD traits. Gene sets associated with inflammation were commonly enriched with ASD traits and gross motor skills (eg, chemokine motif ligand 2 production: R2 = 0.051; β, -6.04; SE, 1.75; P = .001; regulation of monocyte differentiation: R2 = 0.052; β, -6.63; SE, 1.90; P = .001; and B-cell differentiation: R2 = 0.051; β, 7.37; SE, 2.15; P = .001); glutamatergic signaling-associated gene sets were commonly enriched with ASD traits and receptive language skills (eg, regulation of glutamate secretion: R2 = 0.052; β, -5.82; SE, 1.68; P = .001; ionotropic glutamate receptor signaling pathway: R2 = 0.047; β, 3.54; SE, 1.09; P = .001; and negative regulation of glutamate secretion: R2 = 0.045; β, -5.38; SE, 1.74; P = .002).

Conclusions and Relevance

In this study, the ASD PRS was associated with ASD traits among children from the general population. Genetic risks for ASD might be associated with delays in some neurodevelopmental domains, such as gross motor and receptive language skills.

Focus on Causality in ESC/iPSC-Based Modeling of Psychiatric Disorders

Genome-wide association studies (GWAS) have identified an increasing number of genetic variants that significantly associate with psychiatric disorders. Despite this wealth of information, our knowledge of which variants causally contribute to disease, how they interact, and even more so of the functions they regulate, is still poor. The availability of embryonic stem cells (ESCs) and the advent of patient-specific induced pluripotent stem cells (iPSCs) has opened new opportunities to investigate genetic risk variants in living disease-relevant cells. Here, we analyze how this progress has contributed to the analysis of causal relationships between genetic risk variants and neuronal phenotypes, especially in schizophrenia (SCZ) and bipolar disorder (BD). Studies on rare, highly penetrant risk variants have originally led the field, until more recently when the development of (epi-) genetic editing techniques spurred studies on cause-effect relationships between common low risk variants and their associated neuronal phenotypes. This reorientation not only offers new insights, but also raises issues on interpretability. Concluding, we consider potential caveats and upcoming developments in the field of ESC/iPSC-based modeling of causality in psychiatric disorders.

Novel Approaches for Identifying the Molecular Background of Schizophrenia

Recent advances in psychiatric genetics have led to the discovery of dozens of genomic loci associated with schizophrenia. However, a gap exists between the detection of genetic associations and understanding the underlying molecular mechanisms. This review describes the basic approaches used in the so-called post-GWAS studies to generate biological interpretation of the existing population genetic data, including both molecular (creation and analysis of knockout animals, exploration of the transcriptional effects of common variants in human brain cells) and computational (fine-mapping of causal variability, gene set enrichment analysis, partitioned heritability analysis) methods. The results of the crucial studies, in which these approaches were used to uncover the molecular and neurobiological basis of the disease, are also reported.

Playing the genome card

In the 1990s, prominent biologists and journalists predicted that by 2020 each of us would carry a genome card, which would allow physicians to access our entire genome sequence and routinely use this information to diagnose and treat common and debilitating conditions. This is not yet the case. Why not? Common and debilitating diseases are rarely caused by single-gene mutations, and this was recognized before these genome card predictions had been made. Debilitating conditions, including common psychiatric disorders, are typically caused either by rare mutations or by complex interactions of many genes, each having a small effect, and epigenetic, environmental, and microbial factors. In such cases, having a complete genome sequence may have limited utility in diagnosis and treatment. Genome sequencing technologies have transformed biological research in many ways, but had a much smaller effect than expected on treatments of common diseases. Thus, early proponents of genome sequencing effectively "mis-promised" its benefits. One reason may be that there are incentives for both biologists and journalists to tell simple stories, including the idea of relatively simple genetic causation of common, debilitating diseases. These incentives may have led to misleading predictions, which to some extent continue today. Although the Human Genome Project has facilitated biological research generally, the mis-promising of medical benefits, at least for treating common and debilitating disorders, could undermine support for scientific research over the long term.

Testing single/combined clinical categories on 5110 Italian patients with developmental phenotypes to improve array-based detection rate

Background

Chromosomal microarray analysis (CMA) is nowadays widely used in the diagnostic path of patients with clinical phenotypes. However, there is no ascertained evidence to date on how to assemble single/combined clinical categories of developmental phenotypic findings to improve the array‐based detection rate.

Methods

The Italian Society of Human Genetics coordinated a retrospective study which included CMA results of 5,110 Italian patients referred to 17 genetics laboratories for variable combined clinical phenotypes.

Results

Non‐polymorphic copy number variants (CNVs) were identified in 1512 patients (30%) and 615 (32%) present in 552 patients (11%) were classified as pathogenic. CNVs were analysed according to type, size, inheritance pattern, distribution among chromosomes, and association to known syndromes. In addition, the evaluation of the detection rate of clinical subgroups of patients allowed to associate dysmorphisms and/or congenital malformations combined with any other single clinical sign to an increased detection rate, whereas non‐syndromic neurodevelopmental signs and non‐syndromic congenital malformations to a decreased detection rate.

Conclusions

Our retrospective study resulted in confirming the high detection rate of CMA and indicated new clinical markers useful to optimize their inclusion in the diagnostic and rehabilitative path of patients with developmental phenotypes.

Investigating genetic links between grapheme-colour synaesthesia and neuropsychiatric traits

Synaesthesia is a neurological phenomenon affecting perception, where triggering stimuli (e.g. letters and numbers) elicit unusual secondary sensory experiences (e.g. colours). Family-based studies point to a role for genetic factors in the development of this trait. However, the contributions of common genomic variation to synaesthesia have not yet been investigated. Here, we present the SynGenes cohort, the largest genotyped collection of unrelated people with grapheme-colour synaesthesia (n = 723). Synaesthesia has been associated with a range of other neuropsychological traits, including enhanced memory and mental imagery, as well as greater sensory sensitivity. Motivated by the prior literature on putative trait overlaps, we investigated polygenic scores derived from published genome-wide scans of schizophrenia and autism spectrum disorder (ASD), comparing our SynGenes cohort to 2181 non-synaesthetic controls. We found a very slight association between schizophrenia polygenic scores and synaesthesia (Nagelkerke's R2 = 0.0047, empirical p = 0.0027) and no significant association for scores related to ASD (Nagelkerke's R2 = 0.00092, empirical p = 0.54) or body mass index (R2 = 0.00058, empirical p = 0.60), included as a negative control. As sample sizes for studying common genomic variation continue to increase, genetic investigations of the kind reported here may yield novel insights into the shared biology between synaesthesia and other traits, to complement findings from neuropsychology and brain imaging. This article is part of a discussion meeting issue 'Bridging senses: novel insights from synaesthesia'.

Progress in iPSC-Based Modeling of Psychiatric Disorders

Progress in iPSC-based cellular systems provides new insights into human brain development and early neurodevelopmental deviations in psychiatric disorders. Among these, studies on schizophrenia (SCZ) take a prominent role owing to its high heritability and multifarious evidence that it evolves from a genetically induced vulnerability in brain development. Recent iPSC studies on patients with SCZ indicate that functional impairments of neural progenitor cells (NPCs) in monolayer culture extend to brain organoids by disrupting neocorticogenesis in an in vitro model. In addition, the formation of hippocampal circuit-like structures in vitro is impaired in patients with SCZ as is the case for glia development. Intriguingly, chimeric-mice experiments show altered oligodendrocyte and astrocyte development in vivo that highlights the importance of cell-cell interactions in the pathogenesis of early-onset SCZ. Likewise, cortical imbalances in excitatory-inhibitory signaling may result from a cell-autonomous defect in cortical interneuron (cIN) development. Overall, these findings indicate that genetic risk in SCZ impacts neocorticogenesis, hippocampal circuit formation, and the development of distinct glial and neuronal subtypes. In light of this remarkable progress, we discuss current limitations and further steps necessary to harvest the full potential of iPSC-based investigations on psychiatric disorders.

Probing disrupted neurodevelopment in autism using human stem cell-derived neurons and organoids: An outlook into future diagnostics and drug development

Autism spectrum disorders (ASDs) represent a spectrum of neurodevelopmental disorders characterized by impaired social interaction, repetitive or restrictive behaviors, and problems with speech. According to a recent report by the Centers for Disease Control and Prevention, one in 68 children in the US is diagnosed with ASDs. Although ASD-related diagnostics and the knowledge of ASD-associated genetic abnormalities have improved in recent years, our understanding of the cellular and molecular pathways disrupted in ASD remains very limited. As a result, no specific therapies or medications are available for individuals with ASDs. In this review, we describe the neurodevelopmental processes that are likely affected in the brains of individuals with ASDs and discuss how patient-specific stem cell-derived neurons and organoids can be used for investigating these processes at the cellular and molecular levels. Finally, we propose a discovery pipeline to be used in the future for identifying the cellular and molecular deficits and developing novel personalized therapies for individuals with idiopathic ASDs.

Toward a Pathway-Driven Clinical-Molecular Framework for Classifying Autism Spectrum Disorders

BACKGROUND

The current classification system of neurodevelopmental disorders is based on clinical criteria; however, this method alone fails to incorporate what is now known about genomic similarities and differences between closely related clinical neurodevelopmental disorders. Here we present an alternative clinical molecular classification system of neurodevelopmental disorders based on shared molecular and cellular pathways, using syndromes with autistic features as examples.

METHODS

Using the Online Mendelian Inheritance in Man database, we identified 83 syndromes that had "autism" as a feature of disease, which in combination were associated with 69 autism disease-causing genes. Using annotation terms generated from the DAVID annotation tool, we grouped each gene and its associated autism syndrome into three biological pathways: ion transport, cellular synaptic function, and transcriptional regulation.

RESULTS

The majority of the autism syndromes we analyzed (54 of 83) enriched for processes related to transcriptional regulation and were associated with more non-neurologic symptoms and co-morbid psychiatric disease when compared with the other two pathways studied. Disorders with disrupted cellular synaptic function had significantly more motor-related symptoms when compared with the other groups of disorders.

CONCLUSION

Our pathway-based classification system identified unique clinical characteristics within each group that may help guide clinical diagnosis, prognosis, and treatment. These results suggest that shifting current clinical classification of autism disorders toward molecularly driven, pathway-related diagnostic groups such as this may more precisely guide clinical decision making and may be informative for future clinical trial and drug development approaches.

New insights into the development of the human cerebral cortex

The cerebral cortex constitutes more than half the volume of the human brain and is presumed to be responsible for the neuronal computations underlying complex phenomena, such as perception, thought, language, attention, episodic memory and voluntary movement. Rodent models are extremely valuable for the investigation of brain development, but cannot provide insight into aspects that are unique or highly derived in humans. Many human psychiatric and neurological conditions have developmental origins but cannot be studied adequately in animal models. The human cerebral cortex has some unique genetic, molecular, cellular and anatomical features, which need to be further explored. The Anatomical Society devoted its summer meeting to the topic of Human Brain Development in June 2018 to tackle these important issues. The meeting was organized by Gavin Clowry (Newcastle University) and Zoltán Molnár (University of Oxford), and held at St John's College, Oxford. The participants provided a broad overview of the structure of the human brain in the context of scaling relationships across the brains of mammals, conserved principles and recent changes in the human lineage. Speakers considered how neuronal progenitors diversified in human to generate an increasing variety of cortical neurons. The formation of the earliest cortical circuits of the earliest generated neurons in the subplate was discussed together with their involvement in neurodevelopmental pathologies. Gene expression networks and susceptibility genes associated to neurodevelopmental diseases were discussed and compared with the networks that can be identified in organoids developed from induced pluripotent stem cells that recapitulate some aspects of in vivo development. New views were discussed on the specification of glutamatergic pyramidal and γ-aminobutyric acid (GABA)ergic interneurons. With the advancement of various in vivo imaging methods, the histopathological observations can be now linked to in vivo normal conditions and to various diseases. Our review gives a general evaluation of the exciting new developments in these areas. The human cortex has a much enlarged association cortex with greater interconnectivity of cortical areas with each other and with an expanded thalamus. The human cortex has relative enlargement of the upper layers, enhanced diversity and function of inhibitory interneurons and a highly expanded transient subplate layer during development. Here we highlight recent studies that address how these differences emerge during development focusing on diverse facets of our evolution.

Associations between autistic-like traits and polymorphisms in NFKBIL1

OBJECTIVE

The immune system has been suggested to be associated with neuropsychiatric disorders; for example, elevated levels of cytokines and the inflammation-related transcription factor nuclear factor kappa-B (NF-κB) have been reported in individuals with autism spectrum disorder (ASD). The aim of this study was to investigate possible associations between autistic-like traits (ALTs) and single nucleotide polymorphisms (SNPs) in NFKB1 (encoding a subunit of the NF-κB protein complex) and NF-κB inhibitor-like protein 1 (NFKBIL1).

METHODS

The study was conducted in a cohort from the general population: The Child and Adolescent Twin Study in Sweden (CATSS, n = 12 319, 9-12 years old). The subjects were assessed by the Autism-Tics, ADHD, and Other Comorbidities Inventory. Five SNPs within the two genes were genotyped (NFKBIL1: rs2857605, rs2239707, rs2230365 and rs2071592; NFKB1: rs4648022).

RESULTS

We found significant associations for two SNPs in NFKBIL1: rs2239707 showed a significant distribution of genotype frequencies in the case-control analysis both for all individuals combined and in boys only, and rs2230365 was significantly associated with the ALTs-module language impairment in boys only. Furthermore, we found nominal association in the case-control study for rs2230365, replicating earlier association between this SNP and ASD in an independent genome-wide association study.

CONCLUSION

The shown associations between polymorphisms in NFKBIL1 and ALTs are supporting an influence of the immune system on neuropsychiatric symptoms.

Chromatin Remodeling Complex NuRD in Neurodevelopment and Neurodevelopmental Disorders

The nucleosome remodeling and deacetylase (NuRD) complex presents one of the major chromatin remodeling complexes in mammalian cells. Here, we discuss current evidence for NuRD's role as an important epigenetic regulator of gene expression in neural stem cell (NSC) and neural progenitor cell (NPC) fate decisions in brain development. With the formation of the cerebellar and cerebral cortex, NuRD facilitates experience-dependent cerebellar plasticity and regulates additionally cerebral subtype specification and connectivity in postmitotic neurons. Consistent with these properties, genetic variation in NuRD's subunits emerges as important risk factor in common polygenic forms of neurodevelopmental disorders (NDDs) and neurodevelopment-related psychiatric disorders such as schizophrenia (SCZ) and bipolar disorder (BD). Overall, these findings highlight the critical role of NuRD in chromatin regulation in brain development and in mental health and disease.

Disentangling chromatin architecture to gain insights into the etiology of brain disorders

Chromatin organization, together with DNA and histone modifications, is directly linked to the spatiotemporal control of gene expression that specifies and maintains cell type-specific functions. This is particularly important in the brain where hundreds of cell types with distinct functions reside. Recent advances in molecular and computational technologies have enabled the query of chromatin architecture at unprecedented resolution and detail. Here, we review recent studies on the emerging importance of chromatin architecture in the pathogenesis of brain disorders, with emphasis on schizophrenia, autism spectrum disorders (ASD), and unstable repeat expansion disorders. These studies provide molecular insights into how these brain disorders arise at the level of chromatin architecture and implicate new therapeutic directions.

Uncovering the Genetic Architecture of Major Depression

There have been several recent studies addressing the genetic architecture of depression. This review serves to take stock of what is known now about the genetics of depression, how it has increased our knowledge and understanding of its mechanisms, and how the information and knowledge can be leveraged to improve the care of people affected. We identify four priorities for how the field of MD genetics research may move forward in future years, namely by increasing the sample sizes available for genome-wide association studies (GWASs), greater inclusion of diverse ancestries and low-income countries, the closer integration of psychiatric genetics with electronic medical records, and the development of the neuroscience toolkit for polygenic disorders.

A single-nucleotide polymorphism influences brain morphology in drug-naïve patients with major depressive disorder

OBJECTIVE

Recently, a genome-wide association study successfully identified genetic variants associated with major depressive disorder (MDD). The study identified 17 independent single-nucleotide polymorphisms (SNPs) significantly associated with diagnosis of MDD. These SNPs were predicted to be enriched in genes that are expressed in the central nervous system and function in transcriptional regulation associated with neurodevelopment. The study aimed to investigate associations between 17 SNPs and brain morphometry using magnetic resonance imaging (MRI) in drug-naïve patients with MDD and healthy controls (HCs).

METHODS

Forty-seven patients with MDD and 42 HCs were included. All participants underwent T1-weighted structural MRI and genotyping. The genotype-diagnosis interactions associated with regional cortical thicknesses were evaluated using voxel-based morphometry for the 17 SNPs.

RESULTS

Regarding rs301806, an SNP in the RERE genomic regions, we found a significant difference in a genotype effect in the right-lateral orbitofrontal and postcentral lobes between diagnosis groups. After testing every possible diagnostic comparison, the genotype-diagnosis interaction in these areas revealed that the cortical thickness reductions in the MDD group relative to those in the HC group were significantly larger in T/T individuals than in C-carrier ones. For the other SNPs, no brain area was noted where a genotype effect significantly differed between the two groups.

CONCLUSIONS

We found that a RERE gene SNP was associated with cortical thickness reductions in the right-lateral orbitofrontal and postcentral lobes in drug-naïve patients with MDD. The effects of RERE gene polymorphism and gene-environment interactions may exist in brain structures of patients with MDD.