De Novo Gene Variants and Familial Bipolar Disorder

Progress and Implications from Genetic Studies of Bipolar Disorder

With the advancements in gene sequencing technologies, including genome-wide association studies, polygenetic risk scores, and high-throughput sequencing, there has been a tremendous advantage in mapping a detailed blueprint for the genetic model of bipolar disorder (BD). To date, intriguing genetic clues have been identified to explain the development of BD, as well as the genetic association that might be applied for the development of susceptibility prediction and pharmacogenetic intervention. Risk genes of BD, such as CACNA1C, ANK3, TRANK1, and CLOCK, have been found to be involved in various pathophysiological processes correlated with BD. Although the specific roles of these genes have yet to be determined, genetic research on BD will help improve the prevention, therapeutics, and prognosis in clinical practice. The latest preclinical and clinical studies, and reviews of the genetics of BD, are analyzed in this review, aiming to summarize the progress in this intriguing field and to provide perspectives for individualized, precise, and effective clinical practice.

Adrenal Abcg1 Controls Cholesterol Flux and Steroidogenesis

Cholesterol is the precursor of all steroids, but how cholesterol flux is controlled in steroidogenic tissues is poorly understood. The cholesterol exporter ABCG1 is an essential component of the reverse cholesterol pathway and its global inactivation results in neutral lipid redistribution to tissue macrophages. The function of ABCG1 in steroidogenic tissues, however, has not been explored. To model this, we inactivated Abcg1 in the mouse adrenal cortex, which led to an adrenal-specific increase in transcripts involved in cholesterol uptake and de novo synthesis. Abcg1 inactivation did not affect adrenal cholesterol content, zonation, or serum lipid profile. Instead, we observed a moderate increase in corticosterone production that was not recapitulated by the inactivation of the functionally similar cholesterol exporter Abca1. Altogether, our data imply that Abcg1 controls cholesterol uptake and biosynthesis and regulates glucocorticoid production in the adrenal cortex, introducing the possibility that ABCG1 variants may account for physiological or subclinical variation in stress response.

Gene expression alterations in the postmortem hippocampus from older patients with bipolar disorder - A hypothesis generating study

Bipolar disorder (BD) presents with a progressive course in a subset of patients. However, our knowledge of molecular changes in older BD is limited. In this study, we examined gene expression changes in the hippocampus of BD from the Biobank of Aging Studies to identify genes of interest that warrant further exploration. RNA was extracted from the hippocampus from 11 subjects with BD and 11 age and sex-matched controls. Gene expression data was generated using the SurePrint G3 Human Gene Expression v3 microarray. Rank feature selection was performed to identify a subset of features that can optimally differentiate BD and controls. Genes ranked in the top 0.1% with log₂ fold change >1.2 were identified as genes of interest. Average age of the subjects was 64 years old; duration of disease was 21 years and 82% were female. Twenty-five genes were identified, of which all but one was downregulated in BD. Of these, CNTNAP4, MAP4, SLC4A1, COBL, and NEURL4 had been associated with BD and other psychiatric conditions in previous studies. We believe our findings have identified promising targets to inform future studies aiming to understand the pathophysiology of BD in later life.

Neurite outgrowth deficits caused by rare PLXNB1 mutation in pediatric bipolar disorder

Pediatric bipolar disorder (PBD) is a severe mood dysregulation condition that affects 0.5-1% of children and teens in the United States. It is associated with recurrent episodes of mania and depression and an increased risk of suicidality. However, the genetics and neuropathology of PBD are largely unknown. Here, we used a combinatorial family-based approach to characterize cellular, molecular, genetic, and network-level deficits associated with PBD. We recruited a PBD patient and three unaffected family members from a family with a history of psychiatric illnesses. Using resting-state functional magnetic resonance imaging (rs-fMRI), we detected altered resting-state functional connectivity in the patient as compared to an unaffected sibling. Using transcriptomic profiling of patient and control induced pluripotent stem cell (iPSC)-derived telencephalic organoids, we found aberrant signaling in the molecular pathways related to neurite outgrowth. We corroborated the presence of neurite outgrowth deficits in patient iPSC-derived cortical neurons and identified a rare homozygous loss-of-function PLXNB1 variant (c.1360C>C; p.Ser454Arg) responsible for the deficits in the patient. Expression of wild-type PLXNB1, but not the variant, rescued neurite outgrowth in patient neurons, and expression of the variant caused the neurite outgrowth deficits in cortical neurons from PlxnB1 knockout mice. These results indicate that dysregulated PLXNB1 signaling may contribute to an increased risk of PBD and other mood dysregulation-related disorders by disrupting neurite outgrowth and functional brain connectivity. Overall, this study established and validated a novel family-based combinatorial approach for studying cellular and molecular deficits in psychiatric disorders and identified dysfunctional PLXNB1 signaling and neurite outgrowth as potential risk factors for PBD.

Heterozygosity for neuronal ceroid lipofuscinosis predisposes to bipolar disorder

OBJECTIVE

Bipolar disorder is a heritable chronic mental disorder that causes psychosocial impairment through depressive/manic episodes. Familial transmission of bipolar disorder does not follow simple Mendelian patterns of inheritance. The aim of this study was to describe a large family with 12 members affected by bipolar disorder. Whole-exome sequencing was performed for eight members, three of whom were diagnosed with bipolar disorder, and another reported as "borderline."

METHODS

Whole-exome sequencing data allowed us to select variants that the affected members had in common, including and excluding the "borderline" individual with moderate anxiety and obsessive-compulsive traits.

RESULTS

The results favored designating certain genes as predispositional to bipolar disorder: a heterozygous missense variant in CLN6 resulted in a "borderline" phenotype that, if combined with a heterozygous missense variant in ZNF92, is responsible for the more severe bipolar disorder phenotype. Both rare missense changes are predicted to disrupt protein function.

CONCLUSIONS

Loss of both alleles in CLN6 causes neuronal ceroid lipofuscinosis, a severe progressive childhood neurological disorder. Our results indicate that heterozygous CLN6 carriers, previously reported as healthy, may be susceptible to bipolar disorder later in life if associated with additional variants in ZNF92.

Prevalence and Penetrance of Rare Pathogenic Variants in Neurodevelopmental Psychiatric Genes in a Health Care System Population

OBJECTIVE

Autism, schizophrenia, and other clinically distinct neurodevelopmental psychiatric disorders (NPDs) have shared genetic etiologies, including single-gene and multigenic copy number variants (CNVs). Because rare variants are primarily investigated in clinical cohorts, population-based estimates of their prevalence and penetrance are lacking. The authors determined the prevalence, penetrance, and NPD risk of pathogenic single-gene variants in a large health care system population.

METHODS

The authors analyzed linked genomic and electronic health record (EHR) data in a subset of 90,595 participants from Geisinger's MyCode Community Health Initiative, known as the DiscovEHR cohort. Loss-of-function pathogenic variants in 94 high-confidence NPD genes were identified through exome sequencing, and NPD penetrance was calculated using preselected EHR diagnosis codes. NPD risk was estimated using a case-control comparison of DiscovEHR participants with and without NPD diagnoses. Results from single-gene variant analyses were also compared with those from 31 previously reported pathogenic NPD CNVs.

RESULTS

Pathogenic variants were identified in 0.34% of the DiscovEHR cohort and demonstrated a 34.3% penetrance for NPDs. Similar to CNVs, sequence variants collectively conferred a substantial risk for several NPD diagnoses, including autism, schizophrenia, and bipolar disorder. Significant NPD risk remained after participants with intellectual disability were excluded from the analysis, confirming the association with major psychiatric disorders in individuals without severe cognitive deficits.

CONCLUSIONS

Collectively, rare single-gene variants and CNVs were found in >1% of individuals in a large health care system population and play an important contributory role in mental health disorders. Diagnostic genetic testing for pathogenic variants among symptomatic individuals with NPDs could improve clinical outcomes through early intervention and anticipatory therapeutic support.

A rigorous in silico genomic interrogation at 1p13.3 reveals 16 autosomal dominant candidate genes in syndromic neurodevelopmental disorders

Genome-wide chromosomal microarray is extensively used to detect copy number variations (CNVs), which can diagnose microdeletion and microduplication syndromes. These small unbalanced chromosomal structural rearrangements ranging from 1 kb to 10 Mb comprise up to 15% of human mutations leading to monogenic or contiguous genomic disorders. Albeit rare, CNVs at 1p13.3 cause a variety of neurodevelopmental disorders (NDDs) including development delay (DD), intellectual disability (ID), autism, epilepsy, and craniofacial anomalies (CFA). Most of the 1p13.3 CNV cases reported in the pre-microarray era encompassed a large number of genes and lacked the demarcating genomic coordinates, hampering the discovery of positional candidate genes within the boundaries. In this study, we present four subjects with 1p13.3 microdeletions displaying DD, ID, autism, epilepsy, and CFA. In silico comparative genomic mapping with three previously reported subjects with CNVs and 22 unreported DECIPHER CNV cases has resulted in the identification of four different sub-genomic loci harboring five positional candidate genes for DD, ID, and CFA at 1p13.3. Most of these genes have pathogenic variants reported, and their interacting genes are involved in NDDs. RT-qPCR in various human tissues revealed a high expression pattern in the brain and fetal brain, supporting their functional roles in NDDs. Interrogation of variant databases and interacting protein partners led to the identification of another set of 11 potential candidate genes, which might have been dysregulated by the position effect of these CNVs at 1p13.3. Our studies define 1p13.3 as a genomic region harboring 16 NDD candidate genes and underscore the critical roles of small CNVs in in silico comparative genomic mapping for disease gene discovery. Our candidate genes will help accelerate the isolation of pathogenic heterozygous variants from exome/genome sequencing (ES/GS) databases.

Epigenetic signatures relating to disease-associated genotypic burden in familial risk of bipolar disorder

Environmental factors contribute to risk of bipolar disorder (BD), but how environmental factors impact the development of psychopathology within the context of elevated genetic risk is unknown. We herein sought to identify epigenetic signatures operating in the context of polygenic risk for BD in young people at high familial risk (HR) of BD. Peripheral blood-derived DNA was assayed using Illumina PsychArray, and Methylation-450K or -EPIC BeadChips. Polygenic risk scores (PRS) were calculated using summary statistics from recent genome-wide association studies for BD, major depressive disorder (MDD) and cross-disorder (meta-analysis of eight psychiatric disorders). Unrelated HR participants of European ancestry (n = 103) were stratified based on their BD-PRS score within the HR-population distribution, and the top two quintiles (High-BD-PRS; n = 41) compared against the bottom two quintiles (Low-BD-PRS; n = 41). The High-BD-PRS stratum also had higher mean cross-disorder-PRS and MDD-PRS (ANCOVA p = 0.035 and p = 0.024, respectively). We evaluated DNA methylation differences between High-BD-PRS and Low-BD-PRS strata using linear models. One differentially methylated probe (DMP) (cg00933603; p = 3.54 × 10^-7) in VARS2, a mitochondrial aminoacyl-tRNA synthetase, remained significantly hypomethylated after multiple-testing correction. Overall, BD-PRS appeared to broadly impact epigenetic processes, with 1,183 genes mapped to nominal DMPs (p < 0.05); these displayed convergence with genes previously associated with BD, schizophrenia, chronotype, and risk taking. We tested poly-methylomic epigenetic profiles derived from nominal DMPs in two independent samples (n = 54 and n = 82, respectively), and conducted an exploratory evaluation of the effects of family environment, indexing cohesion and flexibility. This study highlights an important interplay between heritable risk and epigenetic factors, which warrant further exploration.

dbBIP: a comprehensive bipolar disorder database for genetic research

Bipolar disorder (BIP) is one of the most common hereditary psychiatric disorders worldwide. Elucidating the genetic basis of BIP will play a pivotal role in mechanistic delineation. Genome-wide association studies (GWAS) have successfully reported multiple susceptibility loci conferring BIP risk, thus providing insight into the effects of its underlying pathobiology. However, difficulties remain in the extrication of important and biologically relevant data from genetic discoveries related to psychiatric disorders such as BIP. There is an urgent need for an integrated and comprehensive online database with unified access to genetic and multi-omics data for in-depth data mining. Here, we developed the dbBIP, a database for BIP genetic research based on published data. The dbBIP consists of several modules, i.e.: (i) single nucleotide polymorphism (SNP) module, containing large-scale GWAS genetic summary statistics and functional annotation information relevant to risk variants; (ii) gene module, containing BIP-related candidate risk genes from various sources and (iii) analysis module, providing a simple and user-friendly interface to analyze one’s own data. We also conducted extensive analyses, including functional SNP annotation, integration (including summary-data-based Mendelian randomization and transcriptome-wide association studies), co-expression, gene expression, tissue expression, protein–protein interaction and brain expression quantitative trait loci analyses, thus shedding light on the genetic causes of BIP. Finally, we developed a graphical browser with powerful search tools to facilitate data navigation and access. The dbBIP provides a comprehensive resource for BIP genetic research as well as an integrated analysis platform for researchers and can be accessed online at http://dbbip.xialab.info.

Database URL:  http://dbbip.xialab.info

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.

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.

Protein phosphatase 2A - structure, function and role in neurodevelopmental disorders

Neurodevelopmental disorders (NDDs), including intellectual disability (ID), autism and schizophrenia, have high socioeconomic impact, yet poorly understood etiologies. A recent surge of large-scale genome or exome sequencing studies has identified a multitude of mostly de novo mutations in subunits of the protein phosphatase 2A (PP2A) holoenzyme that are strongly associated with NDDs. PP2A is responsible for at least 50% of total Ser/Thr dephosphorylation in most cell types and is predominantly found as trimeric holoenzymes composed of catalytic (C), scaffolding (A) and variable regulatory (B) subunits. PP2A can exist in nearly 100 different subunit combinations in mammalian cells, dictating distinct localizations, substrates and regulatory mechanisms. PP2A is well established as a regulator of cell division, growth, and differentiation, and the roles of PP2A in cancer and various neurodegenerative disorders, such as Alzheimer's disease, have been reviewed in detail. This Review summarizes and discusses recent reports on NDDs associated with mutations of PP2A subunits and PP2A-associated proteins. We also discuss the potential impact of these mutations on the structure and function of the PP2A holoenzymes and the etiology of NDDs.

Systematic analysis of exonic germline and postzygotic de novo mutations in bipolar disorder

Bipolar disorder is a severe mental illness characterized by recurrent manic and depressive episodes. To better understand its genetic architecture, we analyze ultra-rare de novo mutations in 354 trios with bipolar disorder. For germline de novo mutations, we find significant enrichment of loss-of-function mutations in constrained genes (corrected-P = 0.0410) and deleterious mutations in presynaptic active zone genes (FDR = 0.0415). An analysis integrating single-cell RNA-sequencing data identifies a subset of excitatory neurons preferentially expressing the genes hit by deleterious mutations, which are also characterized by high expression of developmental disorder genes. In the analysis of postzygotic mutations, we observe significant enrichment of deleterious ones in developmental disorder genes (P = 0.00135), including the SRCAP gene mutated in two unrelated probands. These data collectively indicate the contributions of both germline and postzygotic mutations to the risk of bipolar disorder, supporting the hypothesis that postzygotic mutations of developmental disorder genes may contribute to bipolar disorder.

The significance of rare and de novo variants in bipolar disorder is not well understood. Here, the authors have analyzed whole exome/genome data from trios to identify deleterious de novo variants associated with bipolar disorder.