Sodium valproate rescues expression of TRANK1 in iPSC-derived neural cells that carry a genetic variant associated with serious mental illness

Fine-mapping genomic loci refines bipolar disorder risk genes

Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 17 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of genes involved in neurotransmission and neurodevelopment including SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, CRTC3, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, DPH1, GSDMB, MED24 and THRA in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance of BD polygenic risk scores across diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).

Epigenetic insights into GABAergic development in Dravet Syndrome iPSC and therapeutic implications

Dravet syndrome (DS) is a devastating early-onset refractory epilepsy syndrome caused by variants in the SCN1A gene. A disturbed GABAergic interneuron function is implicated in the progression to DS but the underlying developmental and pathophysiological mechanisms remain elusive, in particularly at the chromatin level. Induced pluripotent stem cells (iPSCs) derived from DS cases and healthy donors were used to model disease-associated epigenetic abnormalities of GABAergic development. Chromatin accessibility was assessed at multiple time points (Day 0, Day 19, Day 35, and Day 65) of GABAergic differentiation. Additionally, the effects of the commonly used anti-seizure drug valproic acid (VPA) on chromatin accessibility were elucidated in GABAergic cells. The distinct dynamics in the chromatin profile of DS iPSC predicted accelerated early GABAergic development, evident at D19, and diverged further from the pattern in control iPSC with continued differentiation, indicating a disrupted GABAergic maturation. Exposure to VPA at D65 reshaped the chromatin landscape at a variable extent in different iPSC-lines and rescued the observed dysfunctional development of some DS iPSC-GABA. The comprehensive investigation on the chromatin landscape of GABAergic differentiation in DS-patient iPSC offers valuable insights into the epigenetic dysregulations associated with interneuronal dysfunction in DS. Moreover, the detailed analysis of the chromatin changes induced by VPA in iPSC-GABA holds the potential to improve the development of personalized and targeted anti-epileptic therapies.

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.

The antiseizure medication valproate increases hemichannel activity found in brain cells, which could worsen disease outcomes

Glial cells play relevant roles in neuroinflammation caused by epilepsy. Elevated hemichannel (HC) activity formed by connexins (Cxs) or pannexin1 (Panx1) largely explains brain dysfunctions commonly caused by neuroinflammation. Glia express HCs formed by Cxs 43, 30, or 26, while glia and neurons both express HCs formed by Panx1. Cx43 HCs allow for the influx of Ca2+, which promotes glial reactivity, enabling the release of the gliotransmitters that contribute to neuronal over-stimulation. Valproate (VPA), an antiseizure medication, has pleiotropic actions on neuronal molecular targets, and their action on glial cell HCs remains elusive. We used HeLa cells transfected with Cx43, Cx30, Cx26, or Panx1 to determine the effect of VPA on HC activity in the brain. VPA slightly increased HC activity under basal conditions, but significantly enhanced it in cells pre-exposed to conditions that promoted HC activity. Furthermore, VPA increased ATP release through Cx43 HCs. The increased HC activity caused by VPA was resistant to washout, being consistent with in silico studies, which predicted the binding site for VPA and Cx43, as well as for Panx1 HCs on the intracellular side, suggesting that VPA first enters through HCs, after which their activity increases.

Dental and medical management of the patient with bipolar disorder

OBJECTIVE

The objective of this literature review is to understand the appropriate medical management of patients with bipolar disorder (BD) which subsequently can translate into the effective dental management of patients suffering with this illness METHODS: This study was completed using three databases which included PubMed, Google Scholar and Cochrane library. Additionally, relevant dental and medical textbooks were also used to summarize more complex topics regarding BD. Descriptors used to find relevant articles included "Bipolar Disorder", "Adverse drug effects of bipolar medications", and "Orofacial findings with patients with bipolar disorder". A total of 49 relevant articles and textbooks were found which were included in this literature review.

RESULTS

BD is a mental illness which affects millions worldwide. It is characterized by alternating episodes of mania and depression. During the manic phase there is an abnormal elevation in mood whereas the depressive episodes consist of the opposite. The medical management of BD involves pharmacotherapy and psychotherapy. Common dental findings in patients with BD include caries, periodontal disease, xerostomia and adverse oral effects from the medications used to manage this illness.

CONCLUSION

BD has a significant burden on society and to effectively manage their medical and dental needs, the clinician must be well versed in their illness.

A resource of induced pluripotent stem cell (iPSC) lines including clinical, genomic, and cellular data from genetically isolated families with mood and psychotic disorders

Genome-wide (GWAS) and copy number variant (CNV) association studies have reproducibly identified numerous risk alleles associated with bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ), but biological characterization of these alleles lags gene discovery, owing to the inaccessibility of live human brain cells and inadequate animal models for human psychiatric conditions. Human-derived induced pluripotent stem cells (iPSCs) provide a renewable cellular reagent that can be differentiated into living, disease-relevant cells and 3D brain organoids carrying the full complement of genetic variants present in the donor germline. Experimental studies of iPSC-derived cells allow functional characterization of risk alleles, establishment of causal relationships between genes and neurobiology, and screening for novel therapeutics. Here we report the creation and availability of an iPSC resource comprising clinical, genomic, and cellular data obtained from genetically isolated families with BD and related conditions. Results from the first 324 study participants, 61 of whom have validated pluripotent clones, show enrichment of rare single nucleotide variants and CNVs overlapping many known risk genes and pathogenic CNVs. This growing iPSC resource is available to scientists pursuing functional genomic studies of BD and related conditions.

A characteristic cerebellar biosignature for bipolar disorder, identified with fully automatic machine learning

Background

Transcriptomic profile differences between patients with bipolar disorder and healthy controls can be identified using machine learning and can provide information about the potential role of the cerebellum in the pathogenesis of bipolar disorder.With this aim, user-friendly, fully automated machine learning algorithms can achieve extremely high classification scores and disease-related predictive biosignature identification, in short time frames and scaled down to small datasets.

Method

A fully automated machine learning platform, based on the most suitable algorithm selection and relevant set of hyper-parameter values, was applied on a preprocessed transcriptomics dataset, in order to produce a model for biosignature selection and to classify subjects into groups of patients and controls. The parent GEO datasets were originally produced from the cerebellar and parietal lobe tissue of deceased bipolar patients and healthy controls, using Affymetrix Human Gene 1.0 ST Array.

Results

Patients and controls were classified into two separate groups, with no close-to-the-boundary cases, and this classification was based on the cerebellar transcriptomic biosignature of 25 features (genes), with Area Under Curve 0.929 and Average Precision 0.955. The biosignature includes both genes connected before to bipolar disorder, depression, psychosis or epilepsy, as well as genes not linked before with any psychiatric disease. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed participation of 4 identified features in 6 pathways which have also been associated with bipolar disorder.

Conclusion

Automated machine learning (AutoML) managed to identify accurately 25 genes that can jointly - in a multivariate-fashion - separate bipolar patients from healthy controls with high predictive power. The discovered features lead to new biological insights. Machine Learning (ML) analysis considers the features in combination (in contrast to standard differential expression analysis), removing both irrelevant as well as redundant markers, and thus, focusing to biological interpretation.

Sleep Disorder Kleine-Levin Syndrome (KLS) Joins the List of Polygenic Brain Disorders Associated with Obstetric Complications

Kleine-Levin Syndrome is a rare neurological disorder with onset typically during adolescence that is characterized by recurrent episodes of hypersomnia, behavioral changes, and cognitive abnormalities, in the absence of structural changes in neuroimaging. As for many functional brain disorders, the exact disease mechanism in Kleine-Levin Syndrome is presently unknown, preventing the development of specific treatment approaches or protective measures. Here we review the pathophysiology and genetics of this functional brain disorder and then present a specific working hypothesis. A neurodevelopmental mechanism has been suspected based on associations with obstetric complications. Recent studies have focused on genetic factors whereby the first genome-wide association study (GWAS) in Kleine-Levin Syndrome has defined a linkage at the TRANK1 locus. A Gene x Environment interaction model involving obstetric complications was proposed based on concepts developed for other functional brain disorders. To stimulate future research, we here performed annotations of the genes under consideration for Kleine-Levin Syndrome in relation to factors expected to be associated with obstetric complications. Annotations used data-mining of gene/protein lists related to for hypoxia, ischemia, and vascular factors and targeted literature searches. Tentative links for TRANK1, four additional genes in the TRANK1 locus, and LMOD3-LMO2 are described. Protein interaction data for TRANK1 indicate links to CBX2, CBX4, and KDM3A, that in turn can be tied to hypoxia. Taken together, the neurological sleep disorder, Kleine-Levin Syndrome, shows genetic and mechanistic overlap with well analyzed brain disorders such as schizophrenia, autism spectrum disorder and ADHD in which polygenic predisposition interacts with external events during brain development, including obstetric complications.

Genetic Insights of Schizophrenia via Single Cell RNA-Sequencing Analyses

BACKGROUND

Schizophrenia is a complex and heterogeneous disorder involving multiple regions and types of cells in the brain. Despite rapid progress made by genome-wide association studies (GWAS) of schizophrenia, the mechanisms of the illness underlying the GWAS significant loci remain less clear.

STUDY DESIGN

We investigated schizophrenia risk genes using summary-data-based Mendelian randomization based on single-cell sequencing data, and explored the types of brain cells involved in schizophrenia through the expression weighted cell-type enrichment analysis.

RESULTS

We identified 54 schizophrenia risk genes (two-thirds of these genes were not identified using sequencing data of bulk tissues) using single-cell RNA-sequencing data. Further cell type enrichment analysis showed that schizophrenia risk genes were highly expressed in excitatory neurons and caudal ganglionic eminence interneurons, suggesting putative roles of these cells in the pathogenesis of schizophrenia. We also found that these risk genes identified using single-cell sequencing results could form a large protein-protein interaction network with genes affected by disease-causing rare variants.

CONCLUSIONS

Through integrative analyses using expression data at single-cell levels, we identified 54 risk genes associated with schizophrenia. Notably, many of these genes were only identified using single-cell RNA-sequencing data, and their altered expression levels in particular types of cells, rather than in the bulk tissues, were related to the increased risk of schizophrenia. Our results provide novel insight into the biological mechanisms of schizophrenia, and future single-cell studies are necessary to further facilitate the understanding of the disorder.

Multi-ancestry meta-analysis and fine-mapping in Alzheimer's disease

Genome-wide association studies (GWAS) of Alzheimer's disease are predominantly carried out in European ancestry individuals despite the known variation in genetic architecture and disease prevalence across global populations. We leveraged published GWAS summary statistics from European, East Asian, and African American populations, and an additional GWAS from a Caribbean Hispanic population using previously reported genotype data to perform the largest multi-ancestry GWAS meta-analysis of Alzheimer's disease and related dementias to date. This method allowed us to identify two independent novel disease-associated loci on chromosome 3. We also leveraged diverse haplotype structures to fine-map nine loci with a posterior probability >0.8 and globally assessed the heterogeneity of known risk factors across populations. Additionally, we compared the generalizability of multi-ancestry- and single-ancestry-derived polygenic risk scores in a three-way admixed Colombian population. Our findings highlight the importance of multi-ancestry representation in uncovering and understanding putative factors that contribute to risk of Alzheimer's disease and related dementias.

Advances in the pathophysiology of bipolar disorder

PURPOSE OF REVIEW

Due to bipolar disorder clinical heterogeneity, a plethora of studies have provided new genetic, epigenetic, molecular, and cellular findings associated with its pathophysiology.

RECENT FINDINGS

Genome-wide association studies and epigenetic evidence points to genotype-phenotype interactions associated with inflammation, oxidative stress, abnormalities in signaling pathways, hypothalamic-pituitary-adrenal axis, and circadian rhythm linked to mitochondrial dysfunction in bipolar disorder. Although the literature is constantly increasing, most of the genetic variants proposed as biomarkers remain to be validated by independent groups and use bigger samples and longitudinal approaches to enhance their power and predictive ability.

SUMMARY

Regardless of which of the mechanisms described here plays a primary or secondary role in the pathophysiology of bipolar disorder, all of these interact to worsen clinical outcomes for patients. Identifying new biomarkers for early detection, prognosis, and response to treatment might provide novel targets to prevent progression and promote general well being.

A Systematic Review of Genetic Polymorphisms Associated with Bipolar Disorder Comorbid to Substance Abuse

It is currently unknown which genetic polymorphisms are involved in substance use disorder (SUD) comorbid with bipolar disorder (BD). The research on polymorphisms in BD comorbid with SUD (BD + SUD) is summarized in this systematic review. We looked for case-control studies that genetically compared adults and adolescents with BD and SUD, healthy controls, and BD without SUD. PRISMA was used to create our protocol, which is PROSPERO-registered (identification: CRD4221270818). The following bibliographic databases were searched indefinitely until December 2021 to identify potentially relevant articles: PubMed, PsycINFO, Scopus, and Web of Science. This systematic review, after the qualitative analysis of the study selection, included 17 eligible articles. In the selected studies, 66 polymorphisms in 29 genes were investigated. The present work delivers a group of potentially valuable genetic polymorphisms associated with BD + SUD: rs11600996 (ARNTL), rs228642/rs228682/rs2640909 (PER3), PONQ192R (PON1), rs945032 (BDKRB2), rs1131339 (NR4A3), and rs6971 (TSPO). It is important to note that none of those findings have been confirmed by two or more studies; thus, we believe that all the polymorphisms identified in this review require additional evidence to be confirmed.

Putting Genetics to Work in the Psychiatric Clinic

The rapid progress in psychiatric genetics over the past 10 years, while exciting from a research perspective, has not yet had an impact on clinical practice. How will we really be able to put genetics to work in the psychiatric clinic? This overview will attempt to answer this question. A survey of widely used methods and major study designs highlights key findings that have emerged so far. These findings inform a broad conceptual model of how genetic risk may act to influence dimensions of psychopathology and clinical presentations. The overview concludes with highlights of some of the most clinically relevant findings to date and their implications for psychiatric practice in the near future.

Kleine-Levin syndrome is associated with birth difficulties and genetic variants in the TRANK1 gene loci

Kleine-Levin syndrome (KLS) is a rare disorder characterized by severe episodic hypersomnia, with cognitive impairment accompanied by apathy or disinhibition. Pathophysiology is unknown, although imaging studies indicate decreased activity in hypothalamic/thalamic areas during episodes. Familial occurrence is increased, and risk is associated with reports of a difficult birth. We conducted a worldwide case-control genome-wide association study in 673 KLS cases collected over 14 y, and ethnically matched 15,341 control individuals. We found a strong genome-wide significant association (rs71947865, Odds Ratio [OR] = 1.48, P = 8.6 × 10^-9) within the 3'region of TRANK1 gene locus, previously associated with bipolar disorder and schizophrenia. Strikingly, KLS cases with rs71947865 variant had significantly increased reports of a difficult birth. As perinatal outcomes have dramatically improved over the last 40 y, we further stratified our sample by birth years and found that recent cases had a significantly reduced rs71947865 association. While the rs71947865 association did not replicate in the entire follow-up sample of 171 KLS cases, rs71947865 was significantly associated with KLS in the subset follow-up sample of 59 KLS cases who reported birth difficulties (OR = 1.54, P = 0.01). Genetic liability of KLS as explained by polygenic risk scores was increased (pseudo R ² = 0.15; P < 2.0 × 10^-22 at P = 0.5 threshold) in the follow-up sample. Pathway analysis of genetic associations identified enrichment of circadian regulation pathway genes in KLS cases. Our results suggest links between KLS, circadian regulation, and bipolar disorder, and indicate that the TRANK1 polymorphisms in conjunction with reported birth difficulties may predispose to KLS.

Mood Stabilizers in Psychiatric Disorders and Mechanisms Learnt from In Vitro Model Systems

Bipolar disorder (BD) and schizophrenia are psychiatric disorders that manifest unusual mental, behavioral, and emotional patterns leading to suffering and disability. These disorders span heterogeneous conditions with variable heredity and elusive pathophysiology. Mood stabilizers such as lithium and valproic acid (VPA) have been shown to be effective in BD and, to some extent in schizophrenia. This review highlights the efficacy of lithium and VPA treatment in several randomized, controlled human trials conducted in patients suffering from BD and schizophrenia. Furthermore, we also address the importance of using induced pluripotent stem cells (iPSCs) as a disease model for mirroring the disease's phenotypes. In BD, iPSC-derived neurons enabled finding an endophenotype of hyperexcitability with increased hyperpolarizations. Some of the disease phenotypes were significantly alleviated by lithium treatment. VPA studies have also reported rescuing the Wnt/β-catenin pathway and reducing activity. Another significant contribution of iPSC models can be attributed to studying the molecular etiologies of schizophrenia such as abnormal differentiation of patient-derived neural stem cells, decreased neuronal connectivity and neurite number, impaired synaptic function, and altered gene expression patterns. Overall, despite significant advances using these novel models, much more work remains to fully understand the mechanisms by which these disorders affect the patients' brains.

Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.

Independent replications and integrative analyses confirm TRANK1 as a susceptibility gene for bipolar disorder

Genetic analyses for bipolar disorder (BD) have achieved prominent success in Europeans in recent years, whereas its genetic basis in other populations remains relatively less understood. We herein report that the leading risk locus for BD in European genome-wide association studies (GWAS), the single-nucleotide polymorphism (SNP) rs9834970 near TRANK1 at 3p22 region, is also genome-wide significantly associated with BD in a meta-analysis of four independent East Asian samples including 5748 cases and 65,361 controls (p = 2.27 × 10^-8, odds ratio = 1.136). Expression quantitative trait loci (eQTL) analyses and summary data-based Mendelian randomization (SMR) analyses in multiple human brain samples suggest that lower TRANK1 mRNA expression is a principal BD risk factor explaining its genetic risk signals at 3p22. We also identified another SNP rs4789 in the 3' untranslated region (3'UTR) of TRANK1 showing stronger eQTL associations as well as genome-wide significant association with BD. Despite the relatively unclear neuronal function of TRANK1, our mRNA expression analyses in the human brains and in rat primary cortical neurons reveal that genes highly correlated with TRANK1 are significantly enriched in the biological processes related to dendritic spine, synaptic plasticity, axon guidance and circadian entrainment, and are also more likely to exhibit strong associations in psychiatric GWAS (e.g., the CACNA1C gene). Overall, our results support that TRANK1 is a potential BD risk gene. Further studies elucidating its roles in this illness are needed.

Muscle transcriptional networks linked to resistance exercise training hypertrophic response heterogeneity

The skeletal muscle hypertrophic response to resistance exercise training (RT) is highly variable across individuals. The molecular underpinnings of this heterogeneity are unclear. This study investigated transcriptional networks linked to RT-induced muscle hypertrophy, classified as 1) predictive of hypertrophy, 2) responsive to RT independent of muscle hypertrophy, or 3) plastic with hypertrophy. Older adults (n = 31, 18 F/13 M, 70 ± 4 yr) underwent 14-wk RT (3 days/wk, alternating high-low-high intensity). Muscle hypertrophy was assessed by pre- to post-RT change in mid-thigh muscle cross-sectional area (CSA) [computed tomography (CT), primary outcome] and thigh lean mass [dual-energy X-ray absorptiometry (DXA), secondary outcome]. Transcriptome-wide poly-A RNA-seq was performed on vastus lateralis tissue collected pre- (n = 31) and post-RT (n = 22). Prediction networks (using only baseline RNA-seq) were identified by weighted gene correlation network analysis (WGCNA). To identify Plasticity networks, WGCNA change indices for paired samples were calculated and correlated to changes in muscle size outcomes. Pathway-level information extractor (PLIER) was applied to identify Response networks and link genes to biological annotation. Prediction networks (n = 6) confirmed transcripts previously connected to resistance/aerobic training adaptations in the MetaMEx database while revealing novel member genes that should fuel future research to understand the influence of baseline muscle gene expression on hypertrophy. Response networks (n = 6) indicated RT-induced increase in aerobic metabolism and reduced expression of genes associated with spliceosome biology and type-I myofibers. A single exploratory Plasticity network was identified. Findings support that interindividual differences in baseline gene expression may contribute more than RT-induced changes in gene networks to muscle hypertrophic response heterogeneity. Code/Data: https://github.com/kallavin/MASTERS_manuscript/tree/master.

Novel Alzheimer Disease Risk Loci and Pathways in African American Individuals Using the African Genome Resources Panel: A Meta-analysis

Importance

Compared with non-Hispanic White individuals, African American individuals from the same community are approximately twice as likely to develop Alzheimer disease. Despite this disparity, the largest Alzheimer disease genome-wide association studies to date have been conducted in non-Hispanic White individuals. In the largest association analyses of Alzheimer disease in African American individuals, ABCA7, TREM2, and an intergenic locus at 5q35 were previously implicated.

Objective

To identify additional risk loci in African American individuals by increasing the sample size and using the African Genome Resource panel.

Design, Setting, and Participants

This genome-wide association meta-analysis used case-control and family-based data sets from the Alzheimer Disease Genetics Consortium. There were multiple recruitment sites throughout the United States that included individuals with Alzheimer disease and controls of African American ancestry. Analysis began October 2018 and ended September 2019.

Main Outcomes and Measures

Diagnosis of Alzheimer disease.

Results

A total of 2784 individuals with Alzheimer disease (1944 female [69.8%]) and 5222 controls (3743 female [71.7%]) were analyzed (mean [SD] age at last evaluation, 74.2 [13.6] years). Associations with 4 novel common loci centered near the intracellular glycoprotein trafficking gene EDEM1 (3p26; P = 8.9 × 10-7), near the immune response gene ALCAM (3q13; P = 9.3 × 10-7), within GPC6 (13q31; P = 4.1 × 10-7), a gene critical for recruitment of glutamatergic receptors to the neuronal membrane, and within VRK3 (19q13.33; P = 3.5 × 10-7), a gene involved in glutamate neurotoxicity, were identified. In addition, several loci associated with rare variants, including a genome-wide significant intergenic locus near IGF1R at 15q26 (P = 1.7 × 10-9) and 6 additional loci with suggestive significance (P ≤ 5 × 10-7) such as API5 at 11p12 (P = 8.8 × 10-8) and RBFOX1 at 16p13 (P = 5.4 × 10-7) were identified. Gene expression data from brain tissue demonstrate association of ALCAM, ARAP1, GPC6, and RBFOX1 with brain β-amyloid load. Of 25 known loci associated with Alzheimer disease in non-Hispanic White individuals, only APOE, ABCA7, TREM2, BIN1, CD2AP, FERMT2, and WWOX were implicated at a nominal significance level or stronger in African American individuals. Pathway analyses strongly support the notion that immunity, lipid processing, and intracellular trafficking pathways underlying Alzheimer disease in African American individuals overlap with those observed in non-Hispanic White individuals. A new pathway emerging from these analyses is the kidney system, suggesting a novel mechanism for Alzheimer disease that needs further exploration.

Conclusions and Relevance

While the major pathways involved in Alzheimer disease etiology in African American individuals are similar to those in non-Hispanic White individuals, the disease-associated loci within these pathways differ.

Integrative analyses prioritize GNL3 as a risk gene for bipolar disorder

Genome-wide association studies (GWASs) have identified numerous single nucleotide polymorphisms (SNPs) associated with bipolar disorder (BD), but what the causal variants are and how they contribute to BD is largely unknown. In this study, we used FUMA, a GWAS annotation tool, to pinpoint potential causal variants and genes from the latest BD GWAS findings, and performed integrative analyses, including brain expression quantitative trait loci (eQTL), gene coexpression network, differential gene expression, protein-protein interaction, and brain intermediate phenotype association analysis to identify the functions of a prioritized gene and its connection to BD. Convergent lines of evidence prioritized protein-coding gene G Protein Nucleolar 3 (GNL3) as a BD risk gene, with integrative analyses revealing GNL3's roles in cell proliferation, neuronal functions, and brain phenotypes. We experimentally revealed that BD-related eQTL SNPs rs10865973, rs12635140, and rs4687644 regulate GNL3 expression using dual luciferase reporter assay and CRISPR interference experiment in human neural progenitor cells. We further identified that GNL3 knockdown and overexpression led to aberrant neuronal proliferation and differentiation, using two-dimensional human neural cell cultures and three-dimensional forebrain organoid model. This study gathers evidence that BD-related genetic variants regulate GNL3 expression which subsequently affects neuronal proliferation and differentiation.

From Anti-EBV Immune Responses to the EBV Diseasome via Cross-reactivity

Sequence analyses highlight a massive peptide sharing between immunoreactive Epstein-Barr virus (EBV) epitopes and human proteins that—when mutated, deficient or improperly functioning—associate with tumorigenesis, diabetes, lupus, multiple sclerosis, rheumatoid arthritis, and immunodeficiencies, among others. Peptide commonality appears to be the molecular platform capable of linking EBV infection to the vast EBV-associated diseasome via cross-reactivity and questions the hypothesis of the “negative selection” of self-reactive lymphocytes. Of utmost importance, this study warns that using entire antigens in anti-EBV immunotherapies can associate with autoimmune manifestations and further supports the concept of peptide uniqueness for designing safe and effective anti-EBV immunotherapies.

Exome sequencing identification of susceptibility genes in Chinese patients with keratoconus

PURPOSE

Keratoconus (KC) is a corneal ectasia disease with complex genetic heterogeneity. The present study aimed to identify susceptibility genes in Chinese patients with KC.

METHODS

Exome sequencing (ES) was performed in 28 Chinese KC patients to search for susceptibility genes of the disease. The candidate variants were filtered out by multi-step bioinformatics analysis and validated by Sanger sequencing. Another 100 individuals with KC were also recruited to verify those variants by Sanger sequencing.

RESULTS

By filtering out nonsynonymous variants located in exon, selecting variants which were presented in two or more samples and applying public databases to remove common variants, along with the inclusion of missense SNVs located in differential expressed genes and protein damaging variants (stop gain/stop loss SNVs and InDels), we have identified 6 SNVs (4 missense SNVs: c.1168 T > C in TRANK1, c.341A>T in ERMP1, c.4346 T > C in SDK2, c.1730A>C in COL6A1; 2 stop gain SNVs: c.1138 C > T in CNBD1, c.241 C > T in KRT82) and 2 InDels (c.193_195del in NSUN5, c.1690_1698del in COL9A3) as candidate variants for KC. The verifying results showed that c.341A>T in ERMP1 and c.193_195del in NSUN5 was found in one and two samples, respectively.

CONCLUSIONS

Our study suggested that a total of six SNVs in six genes and two InDels in two genes might be considered as candidate variants in Chinese patients with KC.

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.

The genetics of bipolar disorder

Bipolar disorder (BD) is one of the most heritable mental illnesses, but the elucidation of its genetic basis has proven to be a very challenging endeavor. Genome-Wide Association Studies (GWAS) have transformed our understanding of BD, providing the first reproducible evidence of specific genetic markers and a highly polygenic architecture that overlaps with that of schizophrenia, major depression, and other disorders. Individual GWAS markers appear to confer little risk, but common variants together account for about 25% of the heritability of BD. A few higher-risk associations have also been identified, such as a rare copy number variant on chromosome 16p11.2. Large scale next-generation sequencing studies are actively searching for other alleles that confer substantial risk. As our understanding of the genetics of BD improves, there is growing optimism that some clear biological pathways will emerge, providing a basis for future studies aimed at molecular diagnosis and novel therapeutics.

From Schizophrenia Genetics to Disease Biology: Harnessing New Concepts and Technologies

Schizophrenia (SZ) is a severe mental disorder afflicting around 1% of the population. It is highly heritable but with complex genetics. Recent research has unraveled a plethora of risk loci for SZ. Accordingly, our conceptual understanding of SZ genetics has been rapidly evolving, from oligogenic models towards polygenic or even omnigenic models. A pressing challenge to the field, however, is the translation of the many genetic findings of SZ into disease biology insights leading to more effective treatments. Bridging this gap requires the integration of genetic findings and functional genomics using appropriate cellular models. Harnessing new technologies, such as the development of human induced pluripotent stem cells (hiPSC) and the CRISPR/Cas-based genome/epigenome editing approach are expected to change our understanding of SZ disease biology to a fundamentally higher level. Here, we discuss some new developments.

Genetic Overlap Between Alzheimer's Disease and Bipolar Disorder Implicates the MARK2 and VAC14 Genes

Background: Alzheimer's disease (AD) and bipolar disorder (BIP) are complex traits influenced by numerous common genetic variants, most of which remain to be detected. Clinical and epidemiological evidence suggest that AD and BIP are related. However, it is not established if this relation is of genetic origin. Here, we applied statistical methods based on the conditional false discovery rate (FDR) framework to detect genetic overlap between AD and BIP and utilized this overlap to increase the power to identify common genetic variants associated with either or both traits. Methods: We obtained genome wide association studies data from the International Genomics of Alzheimer's Project part 1 (17,008 AD cases and 37,154 controls) and the Psychiatric Genetic Consortium Bipolar Disorder Working Group (20,352 BIP cases and 31,358 controls). We used conditional QQ-plots to assess overlap in common genetic variants between AD and BIP. We exploited the genetic overlap to re-rank test-statistics for AD and BIP and improve detection of genetic variants using the conditional FDR framework. Results: Conditional QQ-plots demonstrated a polygenic overlap between AD and BIP. Using conditional FDR, we identified one novel genomic locus associated with AD, and nine novel loci associated with BIP. Further, we identified two novel loci jointly associated with AD and BIP implicating the MARK2 gene (lead SNP rs10792421, conjunctional FDR = 0.030, same direction of effect) and the VAC14 gene (lead SNP rs11649476, conjunctional FDR = 0.022, opposite direction of effect). Conclusion: We found polygenic overlap between AD and BIP and identified novel loci for each trait and two jointly associated loci. Further studies should examine if the shared loci implicating the MARK2 and VAC14 genes could explain parts of the shared and distinct features of AD and BIP.

Crosstalk of Genetic Variants, Allele-Specific DNA Methylation, and Environmental Factors for Complex Disease Risk

Over the past decades, genome-wide association studies (GWAS) have identified thousands of phenotype-associated DNA sequence variants for potential explanations of inter-individual phenotypic differences and disease susceptibility. However, it remains a challenge for translating the associations into causative mechanisms for complex diseases, partially due to the involved variants in the noncoding regions and the inconvenience of functional studies in human population samples. So far, accumulating evidence has suggested a complex crosstalk among genetic variants, allele-specific binding of transcription factors (ABTF), and allele-specific DNA methylation patterns (ASM), as well as environmental factors for disease risk. This review aims to summarize the current studies regarding the interactions of the aforementioned factors with a focus on epigenetic insights. We present two scenarios of single nucleotide polymorphisms (SNPs) in coding regions and non-coding regions for disease risk, via potentially impacting epigenetic patterns. While a SNP in a coding region may confer disease risk via altering protein functions, a SNP in non-coding region may cause diseases, via SNP-altering ABTF, ASM, and allele-specific gene expression (ASE). The allelic increases or decreases of gene expression are key for disease risk during development. Such ASE can be achieved via either a "SNP-introduced ABTF to ASM" or a "SNP-introduced ASM to ABTF." Together with our additional in-depth review on insulator CTCF, we are convinced to propose a working model that the small effect of a SNP acts through altered ABTF and/or ASM, for ASE and eventual disease outcome (named as a "SNP intensifier" model). In summary, the significance of complex crosstalk among genetic factors, epigenetic patterns, and environmental factors requires further investigations for disease susceptibility.