BCL9 and C9orf5 are associated with negative symptoms in schizophrenia: meta-analysis of two genome-wide association studies

Integrating Genetic and Transcriptomic Data to Identify Genes Underlying Obesity Risk Loci

Genome-wide association studies (GWAS) have identified numerous body mass index (BMI) loci. However, most underlying mechanisms from risk locus to BMI remain unknown. Leveraging omics data through integrative analyses could provide more comprehensive views of biological pathways on BMI. We analyzed genotype and blood gene expression data in up to 5,619 samples from the Framingham Heart Study (FHS). Using 3,992 single nucleotide polymorphisms (SNPs) at 97 BMI loci and 20,692 transcripts within 1 Mb, we performed separate association analyses of transcript with BMI and SNP with transcript (PBMI and PSNP, respectively) and then a correlated meta-analysis between the full summary data sets (PMETA). We identified transcripts that met Bonferroni-corrected significance for each omic, were more significant in the correlated meta-analysis than each omic, and were at least nominally associated with BMI in FHS data. Among 308 significant SNP-transcript-BMI associations, we identified seven genes (NT5C2, GSTM3, SNAPC3, SPNS1, TMEM245, YPEL3, and ZNF646) in five association regions. Using an independent sample of blood gene expression data, we validated results for SNAPC3 and YPEL3. We tested for generalization of these associations in hypothalamus, nucleus accumbens, and liver and observed significant (PMETA<0.05 & PMETA Collapse

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Grants

• R01 HL143885 NHLBI NIH HHS
• R01 HL142302 NHLBI NIH HHS
• R01 HL151152 NHLBI NIH HHS
• HHSN268201500001I NHLBI NIH HHS
• R01 DK139598 NIDDK NIH HHS
• N01HC25195 NHLBI NIH HHS
• R01 HG010297 NHGRI NIH HHS
• HHSN268201500001C NHLBI NIH HHS
• R01 HL163262 NHLBI NIH HHS
• R01 HL092577 NHLBI NIH HHS
• P20 MD000170 NIMHD NIH HHS
• 75N92019D00031 NHLBI NIH HHS
• R01 HD057194 NICHD NIH HHS
• UL1 TR000371 NCATS NIH HHS
• R01 DK122503 NIDDK NIH HHS

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Affiliation(s)

Hanfei Xu Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
Shreyash Gupta Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Ian Dinsmore Department of Genomic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Abbey Kollu Department of Psychology and Neuroscience, University of North Carolina, 235 E. Cameron Avenue, Chapel Hill, NC, 27599, USA
Anne Marie Cawley Marsico Lung Institute, University of North Carolina, 125 Mason Farm Rd, Chapel Hill, NC, 27599, USA
Mohammad Y. Anwar Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
Hung-Hsin Chen Institute of Biomedical Sciences, Academia Sinica, No. 128, Section 2, Academia Rd., Taipei, Nangang District, 115201, Taiwan Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
Lauren E. Petty Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
Sudha Seshadri Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA Department of Neurology, School of Medicine, Boston University, 85 East Concord Street, Boston, MA, 02118, USA Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, UT Health San Antonio, 8300 Floyd Curl Drive, San Antonio, TX, 78229, USA
Misa Graff Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
Piper Below Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
Jennifer A. Brody Department of Medicine, Cardiovascular Health Research Unit, University of Washington, 1730 Minor Ave, Seattle, WA, 98101, USA
Geetha Chittoor Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Susan P. Fisher-Hoch Department of Epidemiology, School of Public Health, UT Health Houston, Regional Academic Health Center, One West University Blvd, Brownsville, TX, 78520, USA
Nancy L. Heard-Costa Framingham Heart Study, 73 Mt Wayte Ave, Framingham, MA, 01702, USA Department of Neurology, Chobanian & Avedisian School of Medicine, Boston University, 72 E Concord St, Boston, MA, 02118, USA
Daniel Levy Population Sciences Branch, National Heart, Lung, and Blood Institute of the National Institutes of Health, 6701 Rockledge Drive, Bethesda, MD, 20892, USA
Honghuang Lin Department of Medicine, University of Massachusetts Chan Medical School, 55 N Lake Ave, Worcester, MA, 01655, USA
Ruth JF. Loos Charles Bronfman Institute for Personalized Medicine at Mount Sinai, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY, 10029, USA Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3A, 2200, Copenhagen, Denmark
Joseph B. Mccormick Department of Epidemiology, School of Public Health, UT Health Houston, Regional Academic Health Center, One West University Blvd, Brownsville, TX, 78520, USA
Jerome I. Rotter Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, 1124 West Carson Street, Torrance, CA, 90502, USA
Tooraj Mirshahi Department of Genomic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Christopher D. Still Center for Obesity and Metabolic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Anita Destefano Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA Department of Neurology, School of Medicine, Boston University, 85 East Concord Street, Boston, MA, 02118, USA
L. Adrienne Cupples Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
Karen L Mohlke Department of Genetics, School of Medicine, University of North Carolina, Chapel Hill, NC, 27599, USA
Kari E. North Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
Anne E. Justice Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Ching-Ti Liu Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA

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Exome sequencing identifies genes associated with sleep-related traits

Sleep is vital for human health and has a moderate heritability. Previous genome-wide association studies have limitations in capturing the role of rare genetic variants in sleep-related traits. Here we conducted a large-scale exome-wide association study of eight sleep-related traits (sleep duration, insomnia symptoms, chronotype, daytime sleepiness, daytime napping, ease of getting up in the morning, snoring and sleep apnoea) among 450,000 participants from UK Biobank. We identified 22 new genes associated with chronotype (ADGRL4, COL6A3, CLK4 and KRTAP3-3), daytime sleepiness (ST3GAL1 and ANKRD12), daytime napping (PLEKHM1, ANKRD12 and ZBTB21), snoring (WDR59) and sleep apnoea (13 genes). Notably, 20 of these genes were confirmed to be significantly associated with sleep disorders in the FinnGen cohort. Enrichment analysis revealed that these discovered genes were enriched in circadian rhythm and central nervous system neurons. Phenotypic association analysis showed that ANKRD12 was associated with cognition and inflammatory traits. Our results demonstrate the value of large-scale whole-exome analysis in understanding the genetic architecture of sleep-related traits and potential biological mechanisms.

Transcription Factor Regulation of Gene Expression Network by ZNF385D and HAND2 in Carotid Atherosclerosis

Carotid intima-media thickness (CIMT) is a surrogate indicator for atherosclerosis and has been shown to predict cardiovascular risk in multiple large studies. Identification of molecular markers for carotid atheroma plaque formation can be critical for early intervention and prevention of atherosclerosis. This study performed transcription factor (TF) network analysis of global gene expression data focusing on two TF genes, ZNF385D and HAND2, whose polymorphisms have been recently reported to show association with CIMT. Genome-wide gene expression data were measured from pieces of carotid endarterectomy collected from 34 hypertensive patients (atheroma plaque of stages IV and above according to the Stary classification) each paired with one sample of distant macroscopically intact tissue (stages I and II). Transcriptional regulation networks or the regulons were reconstructed for ZNF385D (5644 target genes) and HAND2 (781 target genes) using network inference. Their association with the progression of carotid atheroma was examined using gene-set enrichment analysis with extremely high statistical significance for regulons of both ZNF385D and HAND2 (p < 6.95 × 10-7) suggesting the involvement of expression quantitative loci (eQTL). Functional annotation of the regulon genes found heavy involvement in the immune system's response to inflammation and infection in the development of atherosclerosis. Detailed examination of the regulation and correlation patterns suggests that activities of the two TF genes could have high clinical and interventional impacts on impairing carotid atheroma plaque formation and preventing carotid atherosclerosis.

Genetic Variants Associated with Suicide Risk in the Mexican Population: A Systematic Literature Review

Suicide is defined as the action of harming oneself with the intention of dying. It is estimated that worldwide, one person dies by suicide every 40 s, making it a major health problem. Studies in families have suggested that suicide has a genetic component, so the search for genetic variants associated with suicidal behavior could be useful as potential biomarkers to identify people at risk of suicide. In Mexico, some studies of gene variants related to neurotransmission and other important pathways have been carried out and potential association of variants located in the following genes has been suggested: SLC6A4, SAT-1, TPH-2, ANKK1, GSHR, SCARA50, RGS10, STK33, COMT, and FKBP5. This systematic review shows the genetic studies conducted on the Mexican population. This article contributes by compiling the existing information on genetic variants and genes associated with suicidal behavior, in the future could be used as potential biomarkers to identify people at risk of suicide.

Identifying genetic loci and phenomic associations of substance use traits: A multi-trait analysis of GWAS (MTAG) study

BACKGROUND AND AIMS

Genome-wide association studies (GWAS) of opioid use disorder (OUD) and cannabis use disorder (CUD) have lagged behind those of alcohol use disorder (AUD) and smoking, where many more loci have been identified. We sought to identify novel loci for substance use traits (SUTs) in both African- (AFR) and European- (EUR) ancestry individuals to enhance our understanding of the traits' genetic architecture.

DESIGN

We used multi-trait analysis of GWAS (MTAG) to analyze four SUTs in EUR subjects (OUD, CUD, AUD and smoking initiation [SMKinitiation]), and three SUTs in AFR subjects (OUD, AUD and smoking trajectory [SMKtrajectory]). We conducted gene-set and protein-protein interaction analyses and calculated polygenic risk scores (PRS) in two independent samples.

SETTING

This study was conducted in the United States.

PARTICIPANTS

A total of 5692 EUR and 4918 AFR individuals in the Yale-Penn sample and 29 054 EUR and 10 265 AFR individuals in the Penn Medicine BioBank sample.

FINDINGS

MTAG identified genome-wide significant (GWS) single nucleotide polymorphisms (SNPs) for all four traits in EUR: 41 SNPs in 36 loci for OUD; 74 SNPs in 60 loci for CUD; 63 SNPs in 52 loci for AUD; and 183 SNPs in 144 loci for SMKinitiation. MTAG also identified GWS SNPs in AFR: 2 SNPs in 2 loci for OUD; 3 SNPs in 3 loci for AUD; and 1 SNP in 1 locus for SMKtrajectory. In the Yale-Penn sample, the MTAG-derived PRS consistently yielded more significant associations with both the corresponding substance use disorder diagnosis and multiple related phenotypes than the GWAS-derived PRS.

CONCLUSIONS

Multi-trait analysis of genome-wide association studies boosted the number of loci found for substance use traits, identifying genes not previously linked to any substance, and increased the power of polygenic risk scores. Multi-trait analysis of genome-wide association studies can be used to identify novel associations for substance use, especially those for which the samples are smaller than those for historically legal substances.

Genetic Predisposition to Schizophrenia and Depressive Disorder Comorbidity

Background: Patients with schizophrenia have an increased risk of depressive disorders compared to the general population. The comorbidity between schizophrenia and depression suggests a potential coincidence of the pathophysiology and/or genetic predictors of these mental disorders. The aim of this study was to review the potential genetic predictors of schizophrenia and depression comorbidity. Materials and Methods: We carried out research and analysis of publications in the databases PubMed, Springer, Wiley Online Library, Taylor & Francis Online, Science Direct, and eLIBRARY.RU using keywords and their combinations. The search depth was the last 10 years (2010–2020). Full-text original articles, reviews, meta-analyses, and clinical observations were analyzed. A total of 459 articles were found, of which 45 articles corresponding to the purpose of this study were analyzed in this topic review. Results: Overlap in the symptoms and genetic predictors between these disorders suggests that a common etiological mechanism may underlie the presentation of comorbid depression in schizophrenia. The molecular mechanisms linking schizophrenia and depression are polygenic. The most studied candidate genes are GRIN1, GPM6A, SEPTIN4, TPH1, TPH2, CACNA1C, CACNB2, and BCL9.Conclusion: Planning and conducting genome-wide and associative genetic studies of the comorbid conditions under consideration in psychiatry is important for the development of biological and clinical predictors and a personalized therapy strategy for schizophrenia. However, it should be recognized that the problems of predictive and personalized psychiatry in the diagnosis and treatment of schizophrenia and comorbid disorders are far from being resolved.

Integration of Transcriptome and Exome Genotyping Identifies Significant Variants with Autism Spectrum Disorder

Autism is a complex disease with genetic predisposition factors. Real factors for treatment and early diagnosis are yet to be defined. This study integrated transcriptome and exome genotyping for identifying functional variants associated with autism spectrum disorder and their impact on gene expression to find significant variations. More than 1800 patients were screened, and 70 (47 male/23 female) with an average age of 7.56 ± 3.68 years fulfilled the DSM-5 criteria for autism. Analysis revealed 682 SNPs of 589 genes significantly (p < 0.001) associated with autism among the putative functional exonic variants (n = 243,345) studied. Olfactory receptor genes on chromosome 6 were significant after Bonferroni correction (α = 0.05/243345 = 2.05 × 10−7) with a high degree of linkage disequilibrium on 6p22.1 (p = 6.71 × 10−9). The differentially expressed gene analysis of autistic patients compared to controls in whole RNA sequencing identified significantly upregulated (foldchange ≥ 0.8 and p-value ≤ 0.05; n = 125) and downregulated (foldchange ≤ −0.8 and p-value ≤ 0.05; n = 117) genes. The integration of significantly up- and downregulated genes and genes of significant SNPs identified regulatory variants (rs6657480, rs3130780, and rs1940475) associated with the up- (ITGB3BP) and downregulation (DDR1 and MMP8) of genes in autism spectrum disorder in people of Arab ancestries. The significant variants could be a biomarker of interest for identifying early autism among Arabs and helping to characterize the genes involved in the susceptibility mechanisms for autistic subjects.

The Latent Structure of Negative Symptoms in the General Population in Adolescence and Emerging Adulthood

Negative symptoms predict adverse outcomes within psychotic disorders, in individuals at high-risk for psychosis, and in young people in the community. There is considerable interest in the dimensional structure of negative symptoms in clinical samples, and accumulating evidence suggests a 5-factor structure. Little is known about the underlying structure of negative symptoms in young people despite the importance of this developmental stage for mental health. We used confirmatory factor analysis to test the structure of parent-reported negative symptoms at mean ages 16.32 (SD 0.68, N = 4974), 17.06 (SD 0.88, N = 1469) and 22.30 (SD 0.93, N = 5179) in a community sample. Given previously reported associations between total negative symptoms and genome-wide polygenic scores (GPS) for major depressive disorder (MDD) and schizophrenia in adolescence, we assessed associations between individual subdomains and these GPSs. A 5-factor model of flat affect, alogia, avolition, anhedonia, and asociality provided the best fit at each age and was invariant over time. The results of our linear regression analyses showed associations between MDD GPS with avolition, flat affect, anhedonia, and asociality, and between schizophrenia GPS with avolition and flat affect. We showed that a 5-factor structure of negative symptoms is present from ages 16 to 22 in the community. Avolition was most consistently associated with polygenic liability to MDD and schizophrenia, and alogia was least associated. These findings highlight the value of dissecting negative symptoms into psychometrically derived subdomains and may offer insights into early manifestation of genetic risk for MDD and schizophrenia.

Developments in Biological Mechanisms and Treatments for Negative Symptoms and Cognitive Dysfunction of Schizophrenia

The causal mechanisms and treatment for the negative symptoms and cognitive dysfunction in schizophrenia are the main issues attracting the attention of psychiatrists over the last decade. The first part of this review summarizes the pathogenesis of schizophrenia, especially the negative symptoms and cognitive dysfunction from the perspectives of genetics and epigenetics. The second part describes the novel medications and several advanced physical therapies (e.g., transcranial magnetic stimulation and transcranial direct current stimulation) for the negative symptoms and cognitive dysfunction that will optimize the therapeutic strategy for patients with schizophrenia in future.

Whole-exome sequencing identifies genes associated with Tourette's disorder in multiplex families

Tourette's Disorder (TD) is a neurodevelopmental disorder (NDD) that affects about 0.7% of the population and is one of the most heritable NDDs. Nevertheless, because of its polygenic nature and genetic heterogeneity, the genetic etiology of TD is not well understood. In this study, we combined the segregation information in 13 TD multiplex families with high-throughput sequencing and genotyping to identify genes associated with TD. Using whole-exome sequencing and genotyping array data, we identified both small and large genetic variants within the individuals. We then combined multiple types of evidence to prioritize candidate genes for TD, including variant segregation pattern, variant function prediction, candidate gene expression, protein-protein interaction network, candidate genes from previous studies, etc. From the 13 families, 71 strong candidate genes were identified, including both known genes for NDDs and novel genes, such as HtrA Serine Peptidase 3 (HTRA3), Cadherin-Related Family Member 1 (CDHR1), and Zinc Finger DHHC-Type Palmitoyltransferase 17 (ZDHHC17). The candidate genes are enriched in several Gene Ontology categories, such as dynein complex and synaptic membrane. Candidate genes and pathways identified in this study provide biological insight into TD etiology and potential targets for future studies.

Dissecting Molecular Genetic Mechanisms of 1q21.1 CNV in Neuropsychiatric Disorders

Pathogenic copy number variations (CNVs) contribute to the etiology of neurodevelopmental/neuropsychiatric disorders (NDs). Increased CNV burden has been found to be critically involved in NDs compared with controls in clinical studies. The 1q21.1 CNVs, rare and large chromosomal microduplications and microdeletions, are detected in many patients with NDs. Phenotypes of duplication and deletion appear at the two ends of the spectrum. Microdeletions are predominant in individuals with schizophrenia (SCZ) and microcephaly, whereas microduplications are predominant in individuals with autism spectrum disorder (ASD) and macrocephaly. However, its complexity hinders the discovery of molecular pathways and phenotypic networks. In this review, we summarize the recent genome-wide association studies (GWASs) that have identified candidate genes positively correlated with 1q21.1 CNVs, which are likely to contribute to abnormal phenotypes in carriers. We discuss the clinical data implicated in the 1q21.1 genetic structure that is strongly associated with neurodevelopmental dysfunctions like cognitive impairment and reduced synaptic plasticity. We further present variations reported in the phenotypic severity, genomic penetrance and inheritance.

Identification of critical genetic variants associated with metabolic phenotypes of the Japanese population

We performed a metabolome genome-wide association study for the Japanese population in the prospective cohort study of Tohoku Medical Megabank. By combining whole-genome sequencing and nontarget metabolome analyses, we identified a large number of novel associations between genetic variants and plasma metabolites. Of the identified metabolite-associated genes, approximately half have already been shown to be involved in various diseases. We identified metabolite-associated genes involved in the metabolism of xenobiotics, some of which are from intestinal microorganisms, indicating that the identified genetic variants also markedly influence the interaction between the host and symbiotic bacteria. We also identified five associations that appeared to be female-specific. A number of rare variants that influence metabolite levels were also found, and combinations of common and rare variants influenced the metabolite levels more profoundly. These results support our contention that metabolic phenotyping provides important insights into how genetic and environmental factors provoke human diseases.

A logical relationship for schizophrenia, bipolar, and major depressive disorder. Part 1: Evidence from chromosome 1 high density association screen

Familial clustering of schizophrenia (SCZ), bipolar disorder (BPD), and major depressive disorder (MDD) was investigated systematically (Aukes et al., Genetics in Medicine, 2012, 14, 338-341) and any two or even three of these disorders could coexist in some families. Furthermore, evidence from symptomatology and psychopharmacology also imply the existence of intrinsic connections between these three major psychiatric disorders. A total of 71,445 SNPs on chromosome 1 were genotyped on 119 SCZ, 253 BPD (type-I), 177 MDD cases and 1000 controls and further validated in 986 SCZ patients in the population of Shandong province of China. Outstanding psychosis genes are systematically revealed( ATP1A4, ELTD1, FAM5C, HHAT, KIF26B, LMX1A, NEGR1, NFIA, NR5A2, NTNG1, PAPPA2, PDE4B, PEX14, RYR2, SYT6, TGFBR3, TTLL7, and USH2A). Unexpectedly, flanking genes for up to 97.09% of the associated SNPs were also replicated in an enlarged cohort of 986 SCZ patients. From the perspective of etiological rather than clinical psychiatry, bipolar, and major depressive disorder could be subtypes of schizophrenia. Meanwhile, the varied clinical feature and prognosis might be the result of interaction of genetics and epigenetics, for example, irreversible or reversible shut down, and over or insufficient expression of certain genes, which may gives other aspects of these severe mental disorders.

BCL9 provides multi-cellular communication properties in colorectal cancer by interacting with paraspeckle proteins

Colorectal cancer (CRC) is the third most commonly diagnosed cancer, which despite recent advances in treatment, remains incurable due to molecular heterogeneity of tumor cells. The B-cell lymphoma 9 (BCL9) oncogene functions as a transcriptional co-activator of the Wnt/β-catenin pathway, which plays critical roles in CRC pathogenesis. Here we have identified a β-catenin-independent function of BCL9 in a poor-prognosis subtype of CRC tumors characterized by expression of stromal and neural associated genes. In response to spontaneous calcium transients or cellular stress, BCL9 is recruited adjacent to the interchromosomal regions, where it stabilizes the mRNA of calcium signaling and neural associated genes by interacting with paraspeckle proteins. BCL9 subsequently promotes tumor progression and remodeling of the tumor microenvironment (TME) by sustaining the calcium transients and neurotransmitter-dependent communication among CRC cells. These data provide additional insights into the role of BCL9 in tumor pathogenesis and point towards additional avenues for therapeutic intervention.

LncRNA ROR1‑AS1 high expression and its prognostic significance in liver cancer

Hepatocellular carcinoma (HCC) is a common disease of the digestive system with no curative treatments. Long noncoding RNA tyrosine protein kinase transmembrane receptor 1 antisense RNA 1 (lncRNA ROR1‑AS1) is an lncRNA whose functions have been predicted in human diseases; however, its important role in cancer has been probed only in mantle cell lymphoma, not in HCC. Therefore, the present study aimed to elucidate the prognostic significance of lncRNA ROR1‑AS1 in HCC. The Cancer Genome Atlas Liver Hepatocellular Carcinoma was used to analyze the expression of ROR1‑AS1 in liver cancer. χ2 tests were performed to evaluate associations between clinical characteristics and ROR1‑AS1 expression. The role of ROR1‑AS1 in HCC prognosis was assessed using Kaplan‑Meier curves and proportional hazards model (Cox) analysis. Gene set enrichment analysis was performed by using a Gene Expression Omnibus dataset. At the same time, Multi Experiment Matrix was used to predict genes that may be co‑expressed with ROR1‑AS1. The Database for Annotation, Visualization and Integrated Discovery and KO‑Based Annotation System were used to analyze the most closely associated cytological behaviors and pathways in HCC. Then, the genes in the three databases were integrated to screen mRNAs, microRNAs and lncRNAs that had co‑expression relationships with ROR1‑AS1. Cytoscape, Search Tool for the Retrieval of Interacting Genes/Proteins and Molecular Evolutionary Genetics Analysis were used to map potential regulatory networks and developmental relationships associated with ROR1‑AS1. Finally, 12 genes most closely associated with ROR1‑AS1 were identified, and their relationship was described using a Circos plot. The results showed that ROR1‑AS1 was upregulated in HCC, and its expression was related to clinical stage, T stage and N stage. Furthermore, Kaplan‑Meier curves and Cox analysis indicated that high expression of ROR1‑AS1 was associated with poor prognosis, and that ROR1‑AS1 was an independent risk factor for HCC. Co‑expression data suggested that there may be a large regulatory network of 45 genes with indirect associations with ROR1‑AS1, a small regulatory network of 15 genes with direct or indirect regulatory relationships, and a special regulatory network containing 12 genes directly associated with ROR1‑AS1. The present findings indicated that high expression of ROR1‑AS1 suggests poor prognosis in patients with HCC.

Worming into the Uncharacterized Human Proteome

Using neXtProt release 2019-01-11, we manually curated a list of 1837 functionally uncharacterized human proteins. Using OrthoList 2, we found that 270 of them have homologues in Caenorhabditis elegans, including 60 with a one-to-one orthology relationship. According to annotations extracted from WormBase, the vast majority of these 60 worm genes have RNAi experimental data or mutant alleles, but manual inspection shows that only 15% have phenotypes that could be interpreted in terms of a specific function. One third of the worm orthologs have protein-protein interaction data, and two of these interactions are conserved in humans. The combination of phenotypic, protein-protein interaction, and gene expression data provides functional hypotheses for 8 uncharacterized human proteins. Experimental validation in human or orthologs is necessary before they can be considered for annotation.

Gene-level genome-wide association analysis of suicide attempt, a preliminary study in a psychiatric Mexican population

Background

Evidence suggests that liability for suicide behavior is heritable; additionally, suicide has been partly related to other psychiatric disorders. Nevertheless, most of the information reported so far address Caucasian and Asian individuals. Hence, our aim was to conduct a gene‐level association study in Mexican psychiatric individuals diagnosed with suicide attempt.

Methods

We recruited 192 individuals from two clinical centers in Mexico. All participants were born in Mexico and had Mexican parents and grandparents. Direct genotyping was performed using the commercial platform Infinium PsychArray BeadChip. A p‐value lower than 1e‐05 was considered as gene‐level significant and a p‐value lower than 1e‐04 was considered as gene‐level nominal significant.

Results

Our analyses showed that SCARA5 was associated to suicide intent at a gene‐level with statistical significance (p‐value = 1.12e‐6). Other genes were nominally associated with suicide attempt: GHSR (p‐value = 0.0004), RGS10 (p‐value = 5.13e‐5), and STK33 (p‐value = 3.62e‐5). Regarding gene variant analyses, the SNPs with a statistical association (p > .05) were rs561361616, rs1537577, rs11198999 for RGS10, and rs11041981, rs11041993, rs11041994, rs11041995, rs11041997, rs10840083, rs10769918 for STK33. For these genes, previous studies have associated SCARA5 with depression, GHSR with alcohol dependence and depression, and RGS10 with schizophrenia and depression. To date, STK33 has not been associated with any psychiatric disorder.

Conclusion

Our outcomes revealed that SCARA5, GHSR, RGS10 and STK33 could be considered as risk biomarkers for suicide attempt behavior in our Mexican psychiatric sample. We recommend to perform larger scale analyses to have conclusive results.

Low lncRNA ZNF385D‑AS2 expression and its prognostic significance in liver cancer

Hepatocellular carcinoma (HCC) is a common digestive system disease with no curative treatment. Zinc finger protein 385D antisense RNA 2 (ZNF385D‑AS2) is a long non‑coding RNA (lncRNA) that has been predicted to function in human diseases, including several types of cancer. Yet, it has not been investigated in relation to liver cancer. Thus, the present study was designed with an aim to elucidate the prognostic significance of lncRNA ZNF385D‑AS2 in HCC. The Cancer Genome Atlas‑Liver Hepatocellular Carcinoma (TCGA‑LIHC) collection of data was utilized to analyze the expression of lncRNA ZNF385D‑AS2 in liver cancer. Then Chi‑square tests were used to evaluate the correlation between clinical characteristics and lncRNA ZNF385D‑AS2 expression. The significance of lncRNA ZNF385D‑AS2 in patient prognosis was evaluated using Kaplan‑Meier curves and Cox analysis. Concomitantly, Gene Set Enrichment Analysis (GSEA) was performed to analyze the most closely related cytological behavior. Finally, we used the Database for Annotation, Visualization and Integrated Discovery (DAVID) and KOBAS software and data from the Gene Expression Omnibus (GEO) database to analyze the possible competing endogenous RNA (ceRNA) network pattern as well as the co‑expression network in liver cancer. Based on the results, analysis of RNA‑Seq gene expression data for 303 patients with primary tumors revealed low expression of ZNF385D‑AS2 in liver cancer. Low expression of ZNF385D‑AS2 was found to be significantly associated with sex (P=0.050), T stage (P=0.049), M stage (P=0.040), N stage (P<0.001) and clinical stage (P=0.037). Patients with ZNF385D‑AS2 low‑expression liver cancers had a shorter median overall survival compared with the patients with ZNF385D‑AS2 high‑expression liver cancers (P=0.0079). Cox analysis identified ZNF385D‑AS2 low‑expression as an independent prognostic variable (AUC=0.594) for overall survival in liver cancer patients. Co‑expression and ceRNA predictive analysis data suggested that there may be a regulatory signaling axis between ZNF385D‑AS2 and miR‑96 and miR‑182. In conclusion, our results suggests that low expression of ZNF385D‑AS2 is predictive of a poor prognosis of liver cancer patients.

Robust Candidates for Language Development and Evolution Are Significantly Dysregulated in the Blood of People With Williams Syndrome

Williams syndrome (WS) is a clinical condition, involving cognitive deficits and an uneven language profile, which has been the object of intense inquiry over the last decades. Although WS results from the hemideletion of around two dozen genes in chromosome 7, no gene has yet been probed to account for, or contribute significantly to, the language problems exhibited by the affected people. In this paper we have relied on gene expression profiles in the peripheral blood of WS patients obtained by microarray analysis and show that several robust candidates for language disorders and/or for language evolution in the species, all of them located outside the hemideleted region, are up- or downregulated in the blood of subjects with WS. Most of these genes play a role in the development and function of brain areas involved in language processing, which exhibit structural and functional anomalies in people with this condition. Overall, these genes emerge as robust candidates for language dysfunction in WS.

Analysis of the promoter region of the human miR-32 gene in colorectal cancer

The pathogenesis of colorectal cancer (CRC) is poorly understood. MicroRNA (miR)-32 upregulation in CRC tissues was previously reported, where it increased the proliferation, migration and invasion, and reduced apoptosis of CRC cells by inhibiting the expression of phosphatase and tensin homolog (PTEN). However, the mechanism underlying miR-32 upregulation remains unknown. miR-32 is an intronic miRNA located within intron 14 of the transmembrane protein 245 gene (TMEM245). The present study aimed to elucidate the biological pathways underlying miR-32 regulation in CRC. A truncated promoter containing the 5′-flanking region of TMEM245/miR-32 gene was constructed. The promoter region was analyzed by dual luciferase reporter assay in CRC cells. DNA pull-down assay and mass spectrometry (MS) were used to identify proteins binding to the core promoter. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and transcription factor (TF) analyses were used to identify the binding proteins. The −320 to −1 bp fragment of the 5′-flanking region exhibited the highest luciferase activity. The regions spanning −606 to −320 bp exhibited a significant decrease in luciferase activity, compared with the −320 to −1 bp fragment. DNA pull-down assay and MS revealed 403 potential miR-32 promoter binding proteins. GO and KEGG pathway analysis indicated that these proteins were involved in numerous physiological and biochemical processes, including ‘structural molecule activity’, ‘RNA binding’, ‘small molecule metabolic process’ and ‘biogenesis’. Furthermore, TF analysis revealed 10 potential interacting TFs, including SMAD family member 1 (SMAD1), signal transducer and activator of transcription 1 (STAT1) and forkhead box K1 (Foxk1). These results suggested that the core promoter region may be located within-320 to −1 bp of the 5′-flanking region of TMEM245/miR-32 gene, while the region from −606 to −320 bp may harbor repressive regulatory elements. The TFs SMAD1, STAT1 and Foxk1 may be involved in the transcriptional regulation of miR-32.

Cross-species evidence from human and rat brain transcriptome for growth factor signaling pathway dysregulation in major depression

An enhanced understanding of the pathophysiology of depression would facilitate the discovery of new efficacious medications. To this end, we examined hippocampal transcriptional changes in rat models of disease and in humans to identify common disease signatures by using a new algorithm for signature-based clustering of expression profiles. The tool identified a transcriptomic signature comprising 70 probesets able to discriminate depression models from controls in both Flinders Sensitive Line and Learned Helplessness animals. To identify disease-relevant pathways, we constructed an expanded protein network based on signature gene products and performed functional annotation analysis. We applied the same workflow to transcriptomic profiles of depressed patients. Remarkably, a 171-probesets transcriptional signature which discriminated depressed from healthy subjects was identified. Rat and human signatures shared the SCARA5 gene, while the respective networks derived from protein-based significant interactions with signature genes contained 25 overlapping genes. The comparison between the most enriched pathways in the rat and human signature networks identified a highly significant overlap (p-value: 3.85 × 10-6) of 67 terms including ErbB, neurotrophin, FGF, IGF, and VEGF signaling, immune responses and insulin and leptin signaling. In conclusion, this study allowed the identification of a hippocampal transcriptional signature of resilient or susceptible responses in rat MDD models which overlapped with gene expression alterations observed in depressed patients. These findings are consistent with a loss of hippocampal neural plasticity mediated by altered levels of growth factors and increased inflammatory responses causing metabolic impairments as crucial factors in the pathophysiology of MDD.

Negative symptoms of psychosis: A life course approach and implications for prevention and treatment

AIM

Negative symptoms are a cause of enduring disability in serious mental illness. In spite of this, the development of effective treatments for negative symptoms has remained slow. The challenge of improving negative symptom outcomes is compounded by our limited understanding of their aetiology and longitudinal development.

METHODS

A literature search was conducted for life course approach of negative symptoms using PubMed. Further articles were included following manual checking of reference lists and other search strategies. The paper contains a theoretical synthesis of the literature, summarized using conceptual models.

RESULTS

Negative symptom definitions are compared and considered within a context of the life course. Previous studies suggest that several illness phases may contribute to negative symptoms, highlighting our uncertainty in relation to the origin of negative symptoms.

CONCLUSIONS

Similar to other aspects of schizophrenia, negative symptoms likely involve a complex interplay of several risk and protective factors at different life phases. Concepts suggested in this article, such as "negative symptom reserve" theory, require further research, which may inform future prevention and treatment strategies.

Narrowing the Genetic Causes of Language Dysfunction in the 1q21.1 Microduplication Syndrome

The chromosome 1q21.1 duplication syndrome (OMIM# 612475) is characterized by head anomalies, mild facial dysmorphisms, and cognitive problems, including autistic features, mental retardation, developmental delay, and learning disabilities. Speech and language development are sometimes impaired, but no detailed characterization of language problems in this condition has been provided to date. We report in detail on the cognitive and language phenotype of a child who presents with a duplication in 1q21.1 (arr[hg19] 1q21.1q21.2(145,764,455-147,824,207) × 3), and who exhibits cognitive delay and behavioral disturbances. Language is significantly perturbed, being the expressive domain the most impaired area (with significant dysphemic features in absence of pure motor speech deficits), although language comprehension and use (pragmatics) are also affected. Among the genes found duplicated in the child, CDH1L is upregulated in the blood of the proband. ROBO1, a candidate for dyslexia, is also highly upregulated, whereas, TLE3, a target of FOXP2, is significantly downregulated. These changes might explain language, and particularly speech dysfunction in the proband.

A novel relationship for schizophrenia, bipolar and major depressive disorder Part 3: Evidence from chromosome 3 high density association screen

Familial clustering of schizophrenia (SCZ), bipolar disorder (BPD), and major depressive disorder (MDD) was systematically reported (Aukes et al, Genet Med 2012, 14, 338-341) and convergent evidence from genetics, symptomatology, and psychopharmacology imply that there are intrinsic connections between these three major psychiatric disorders, for example, any two or even three of these disorders could co-exist in some families. A total of 60, 838 single-nucleotide polymorphisms (SNPs) on chromosome 3 were genotyped by Affymetrix Genome-Wide Human SNP array 6.0 on 119 SCZ, 253 BPD (type-I), 177 MDD patients and 1,000 controls. The population of Shandong province was formed in 14 century and believed that it belongs to homogenous population. Associated SNPs were systematically revealed and outstanding susceptibility genes (CADPS, GRM7,KALRN, LSAMP, NLGN1, PRICKLE2, ROBO2) were identified. Unexpectedly, flanking genes for the associated SNPs distinctive for BPD and/or MDD were replicated in an enlarged cohort of 986 SCZ patients. The evidence from this chromosome 3 analysis supports the notion that both of bipolar and MDD might be subtypes of schizophrenia rather than independent disease entity. Also, a similar finding was detected on chromosome 5, 6, 7, and 8 (Chen et al. Am J Transl Res 2017;9 (5):2473-2491; Curr Mol Med 2016;16(9):840-854; Behav Brain Res 2015;293:241-251; Mol Neurobiol 2016. doi: 10.1007/s12035-016-0102-1). Furthermore, PRICKLE2 play an important role in the pathogenesis of three major psychoses in this population.

Genome-wide association studies of placebo and duloxetine response in major depressive disorder

We investigated variants associated with treatment response in depressed patients treated with either the antidepressant duloxetine or placebo using a genome-wide approach. Our sample (N=391) included individuals aged 18-75 years, diagnosed with major depressive disorder and treated with either duloxetine or placebo for up to 8 weeks. We conducted genome-wide associations for treatment response as operationalized by percentage change in Montgomery-Åsberg Depression Rating Scale score from baseline, as well as mixed models analyses across five time points. In the placebo-treated subsample (N=205), we observed a genome-wide association with rs76767803 (β=0.69, P=1.25 × 10^-8) upstream of STAC1. STAC1 rs76767803 was also associated with response using mixed model analysis (χ²=3.95; P=0.001). In the duloxetine-treated subsample (N=186), we observed suggestive associations with ZNF385D (rs4261893; β=-0.46, P=1.55 × 10^-5), NCAM1 (rs2303377; β=0.45, P=1.76 × 10^-5) and MLL5 (rs117986340; β=0.91, P=3.04 × 10^-5). Our findings suggest that a variant upstream of STAC1 is associated with placebo response, which might have implications for treatment optimization, clinical trial design and drug development.

Genetic Basis of Positive and Negative Symptom Domains in Schizophrenia

Schizophrenia is a highly heritable disorder, the genetic etiology of which has been well established. Yet despite significant advances in genetics research, the pathophysiological mechanisms of this disorder largely remain unknown. This gap has been attributed to the complexity of the polygenic disorder, which has a heterogeneous clinical profile. Examining the genetic basis of schizophrenia subphenotypes, such as those based on particular symptoms, is thus a useful strategy for decoding the underlying mechanisms. This review of literature examines the recent advances (from 2011) in genetic exploration of positive and negative symptoms in schizophrenia. We searched electronic databases PubMed, Web of Science, and Cumulative Index to Nursing and Allied Health Literature using key words schizophrenia, symptoms, positive symptoms, negative symptoms, cognition, genetics, genes, genetic predisposition, and genotype in various combinations. We identified 115 articles, which are included in the review. Evidence from these studies, most of which are genetic association studies, identifies shared and unique gene associations for the symptom domains. Genes associated with neurotransmitter systems and neuronal development/maintenance primarily constitute the shared associations. Needed are studies that examine the genetic basis of specific symptoms within the broader domains in addition to functional mechanisms. Such investigations are critical to developing precision treatment and care for individuals afflicted with schizophrenia.

Bipolar disorder risk gene FOXO6 modulates negative symptoms in schizophrenia: a neuroimaging genetics study

BACKGROUND

Despite being diagnostically associated uniquely with schizophrenia, negative symptoms are also observed in bipolar disorder (BD). Genome-wide association studies (GWAS) have uncovered a number of shared risk genes between schizophrenia and BD. The objectives of this study were to examine whether previously identified risk genes for BD are associated with negative symptom severity within a first-episode schizophrenia (FES) cohort and to examine whether such genes influence brain morphology.

METHODS

Patients experiencing FES were genotyped for 21 previously identified BD risk genes; a series of univariate analyses of covariance examined the association between negative symptom severity, as measured using the Scale for the Assessment of Negative Symptoms (SANS), and genotype. A subset of participants underwent a structural 1.5 T MRI T₁ scan, analyzed for surface area and cortical thickness changes via the CIVET pipeline and LPBA40 atlas.

RESULTS

We included 133 patients with FES in our analysis; 61 of them underwent structural MRI. We observed a significant association between negative symptom severity and the BD risk gene FOXO6 (rs4660531). Individuals with the CC genotype presented significantly higher negative symptoms (Cohen d = 0.46, F = 5.854, p = 0.017) and significantly smaller surface area within the right middle orbitofrontal gyrus (Cohen d = 0.69, F = 7.289, p = 0.009) than carriers of allele A.

LIMITATIONS

Limitations of this study include its modest sample size and lack of a control sample.

CONCLUSION

Lacking the FOXO6 risk allele was associated with an increase in negative symptoms and surface area reduction in the right orbitofrontal gyrus - an area previously associated with negative symptoms - suggesting that presence of the FOXO6 risk allele confers resistance against negative symptoms and associated neuroanatomical changes in individuals with FES.

Gene expression profiling of the dorsolateral and medial orbitofrontal cortex in schizophrenia

Schizophrenia is a complex polygenic disorder of unknown etiology. Over 3,000 candidate genes associated with schizophrenia have been reported, most of which being mentioned only once. Alterations in cognitive processing - working memory, metacognition and mentalization - represent a core feature of schizophrenia, which indicates the involvement of the prefrontal cortex in the pathophysiology of this disorder. Hence we compared the gene expression in postmortem tissue from the left and right dorsolateral prefrontal cortex (DLPFC, Brodmann's area 46), and the medial part of the orbitofrontal cortex (MOFC, Brodmann's area 11/12), in six patients with schizophrenia and six control brains. Although in the past decade several studies performed transcriptome profiling in schizophrenia, this is the first study to investigate both hemispheres, providing new knowledge about possible brain asymmetry at the level of gene expression and its relation to schizophrenia. We found that in the left hemisphere, twelve genes from the DLPFC and eight genes from the MOFC were differentially expressed in patients with schizophrenia compared to controls. In the right hemisphere there was only one gene differentially expressed in the MOFC. We reproduce the involvement of previously reported genes TARDBP and HNRNPC in the pathogenesis of schizophrenia, and report seven novel genes: SART1, KAT7, C1D, NPM1, EVI2A, XGY2, and TTTY15. As the differentially expressed genes only partially overlap with previous studies that analyzed other brain regions, our findings indicate the importance of considering prefrontal cortical regions, especially those in the left hemisphere, for obtaining disease-relevant insights.

The role of the ITIH3 rs2535629 variant in antipsychotic response

INTRODUCTION

There is mounting evidence that schizophrenia risk variants influence response to antipsychotic medication. Common single nucleotide polymorphisms (SNPs) in or near the inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3) gene have been repeatedly associated with schizophrenia and related psychiatric disorders in genome-wide association studies. Here, we provide the first study to assess the relevance of the ITIH3 rs2535629 SNP in response to antipsychotic medication.

METHODS

The rs2535629 SNP was genotyped in N=256 patients receiving various antipsychotics for up to 26weeks. Treatment response was assessed using the Brief Psychiatric Rating Scale (BPRS) including its positive and negative subscales. Follow-up analyses were performed after stratifying for ethnicity and medication.

RESULTS

We found significant association of rs2535629 with improvement of negative symptoms in patients of European ancestry after six months of clozapine treatment (F1,87=8.8, pcorr=0.032). Patients homozygous for the minor A-allele showed the best improvement of negative BPRS scores. However, we observed no association between rs2535629 and changes in total BPRS score in the entire sample or the clozapine-treated subgroup.

DISCUSSION

Although there was no association of genotype with overall changes in BPRS scores, the greater improvement of negative symptoms in minor allele carriers indicates that rs2535629 may help to identify a subset of schizophrenia patients with better treatment response to clozapine. Therefore, our findings provide the first suggestive evidence that rs2535629 is relevant in antipsychotic response.

Currently recognized genes for schizophrenia: High-resolution chromosome ideogram representation

A large body of genetic data from schizophrenia-related research has identified an assortment of genes and disturbed pathways supporting involvement of complex genetic components for schizophrenia spectrum and other psychotic disorders. Advances in genetic technology and expanding studies with searchable genomic databases have led to multiple published reports, allowing us to compile a master list of known, clinically relevant, or susceptibility genes contributing to schizophrenia. We searched key words related to schizophrenia and genetics from peer-reviewed medical literature sources, authoritative public access psychiatric websites and genomic databases dedicated to gene discovery and characterization of schizophrenia. Our list of 560 genes were arranged in alphabetical order in tabular form with gene symbols placed on high-resolution human chromosome ideograms. Genome wide pathway analysis using GeneAnalytics was carried out on the resulting list of genes to assess the underlying genetic architecture for schizophrenia. Recognized genes of clinical relevance, susceptibility or causation impact a broad range of biological pathways and mechanisms including ion channels (e.g., CACNA1B, CACNA1C, CACNA1H), metabolism (e.g., CYP1A2, CYP2C19, CYP2D6), multiple targets of neurotransmitter pathways impacting dopamine, GABA, glutamate, and serotonin function, brain development (e.g., NRG1, RELN), signaling peptides (e.g., PIK3CA, PIK4CA) and immune function (e.g., HLA-DRB1, HLA-DQA1) and interleukins (e.g., IL1A, IL10, IL6). This summary will enable clinical and laboratory geneticists, genetic counselors, and other clinicians to access convenient pictorial images of the distribution and location of contributing genes to inform diagnosis and gene-based treatment as well as provide risk estimates for genetic counseling of families with affected relatives.

Gene expression profiling of the dorsolateral and medial orbitofrontal cortex in schizophrenia

Schizophrenia is a complex polygenic disorder of unknown etiology. Over 3,000 candidate genes associated with schizophrenia have been reported, most of which being mentioned only once. Alterations in cognitive processing - working memory, metacognition and mentalization - represent a core feature of schizophrenia, which indicates the involvement of the prefrontal cortex in the pathophysiology of this disorder. Hence we compared the gene expression in postmortem tissue from the left and right dorsolateral prefrontal cortex (DLPFC, Brodmann's area 46), and the medial part of the orbitofrontal cortex (MOFC, Brodmann's area 11/12), in six patients with schizophrenia and six control brains. Although in the past decade several studies performed transcriptome profiling in schizophrenia, this is the first study to investigate both hemispheres, providing new knowledge about possible brain asymmetry at the level of gene expression and its relation to schizophrenia. We found that in the left hemisphere, twelve genes from the DLPFC and eight genes from the MOFC were differentially expressed in patients with schizophrenia compared to controls. In the right hemisphere there was only one gene differentially expressed in the MOFC. We reproduce the involvement of previously reported genes TARDBP and HNRNPC in the pathogenesis of schizophrenia, and report seven novel genes: SART1, KAT7, C1D, NPM1, EVI2A, XGY2, and TTTY15. As the differentially expressed genes only partially overlap with previous studies that analyzed other brain regions, our findings indicate the importance of considering prefrontal cortical regions, especially those in the left hemisphere, for obtaining disease-relevant insights.

Association study of BCL9 gene polymorphism rs583583 with schizophrenia and negative symptoms in Japanese population

B-cell CLL/lymphoma 9 (BCL9) is located within the schizophrenia (SCZ) suspected locus chr1q21.1. A recent study reported that a single nucleotide polyphormism (SNP) within BCL9 (rs583583) is associated with negative symptoms of Schizophrenia, as measured by the Positive and Negative Syndrome Scale (PANSS), in the Caucasian population. We therefore investigated genetic association of rs583583, and its effect on negative symptoms in the Japanese patients. For association analysis, we used a Japanese sample set comprising 1089 SCZ and 950 controls (CON). Analysis of the effect of rs586586 on negative symptoms as examined by PANSS was investigated using 280 SCZ. Furthermore, for analysis of cognitive performance, we investigated 90 SCZ and 51 CON using the Continuous Performance Test (CPT-IP) and the Wisconsin Card Sorting Test (WCST) Keio version. We did not detect association between rs583583 and SCZ. Furthermore, rs583583 was not associated with PANSS negative scores or with CPT-IT or WCST cognitive tests. Considering the results of our previous study, combined with the results of the current study of rs583583, we argue that BCL9 most likely does not harbor a common genetic variant that can increase the risk for SCZ in the Japanese population.

Genome wide association study identifies variants in NBEA associated with migraine in bipolar disorder

BACKGROUND

Migraine is a common comorbidity among individuals with bipolar disorder, but the underlying mechanisms for this co-occurrence are poorly understood. The aim of this study was to investigate the genetic background of bipolar patients with and without migraine.

METHODS

We performed a genome-wide association analysis contrasting 460 bipolar migraneurs with 914 bipolar patients without migraine from the Bipolar Genome Study (BiGS).

RESULTS

We identified one genome-wide significant association between migraine in bipolar disorder patients and rs1160720, an intronic single nucleotide polymorphism (SNP) in the NBEA gene (P=2.97 × 10(-8), OR: 1.82, 95% CI: 1.47-2.25), although this was not replicated in a smaller sample of 289 migraine cases.

LIMITATIONS

Our study is based on self-reported migraine.

CONCLUSIONS

NBEA encodes neurobeachin, a scaffolding protein primarily expressed in the brain and involved in trafficking of vesicles containing neurotransmitter receptors. This locus has not previously been implicated in migraine per se. We found no evidence of association in data from the GWAS migraine meta-analysis consortium (n=118,710 participants) suggesting that the association might be specific to migraine co-morbid with bipolar disorder.

In vivo imaging of histone deacetylases (HDACs) in the central nervous system and major peripheral organs

Epigenetic enzymes are now targeted to treat the underlying gene expression dysregulation that contribute to disease pathogenesis. Histone deacetylases (HDACs) have shown broad potential in treatments against cancer and emerging data supports their targeting in the context of cardiovascular disease and central nervous system dysfunction. Development of a molecular agent for non-invasive imaging to elucidate the distribution and functional roles of HDACs in humans will accelerate medical research and drug discovery in this domain. Herein, we describe the synthesis and validation of an HDAC imaging agent, [¹¹C]6. Our imaging results demonstrate that this probe has high specificity, good selectivity, and appropriate kinetics and distribution for imaging HDACs in the brain, heart, kidney, pancreas, and spleen. Our findings support the translational potential for [¹¹C]6 for human epigenetic imaging.

Associations of genetic polymorphisms of Siglecs with human diseases

Genetic polymorphism studies in humans provide unique opportunities to understand human biology and the mechanisms of diseases. Correlations between polymorphisms in the genes encoding human Siglecs and various diseases have been reported. Leading examples, such as the CD33 polymorphism associated with late-onset Alzheimer's disease, are well supported by genetic replication and mechanistic studies, while some others (such as SIGLEC8 polymorphism associated with bronchial asthma and SIGLEC14 polymorphism associated with exacerbation of chronic obstructive pulmonary disease) may benefit reinforcement by independent genetic replication or mechanistic studies. In a few cases, such as MAG polymorphism associated with psychological disorder and CD22 polymorphism associated with autoimmune disease, the phenotype associated with a genetic polymorphism of a Siglec gene and that of an enzyme gene involved in the biosynthesis of Siglec ligand show some overlap, providing indirect support for the observed genotype-phenotype association. Although studies using engineered mutant mice have provided invaluable insights into the biological functions and mechanisms of diseases, it is not always possible to develop appropriate mouse model to replicate human situations because of significant species-to-species differences, which can be a major obstacle in understanding the biology of some of human CD33/Siglec-3-related Siglecs. Further studies in genetic polymorphisms of human Siglecs, combined with appropriate functional studies, may reveal unexpected biological roles of human Siglecs, and identify possible targets for prevention and/or treatment of certain diseases.

Genome-wide association study of shared components of reading disability and language impairment

Written and verbal languages are neurobehavioral traits vital to the development of communication skills. Unfortunately, disorders involving these traits-specifically reading disability (RD) and language impairment (LI)-are common and prevent affected individuals from developing adequate communication skills, leaving them at risk for adverse academic, socioeconomic and psychiatric outcomes. Both RD and LI are complex traits that frequently co-occur, leading us to hypothesize that these disorders share genetic etiologies. To test this, we performed a genome-wide association study on individuals affected with both RD and LI in the Avon Longitudinal Study of Parents and Children. The strongest associations were seen with markers in ZNF385D (OR = 1.81, P = 5.45 × 10(-7) ) and COL4A2 (OR = 1.71, P = 7.59 × 10(-7) ). Markers within NDST4 showed the strongest associations with LI individually (OR = 1.827, P = 1.40 × 10(-7) ). We replicated association of ZNF385D using receptive vocabulary measures in the Pediatric Imaging Neurocognitive Genetics study (P = 0.00245). We then used diffusion tensor imaging fiber tract volume data on 16 fiber tracts to examine the implications of replicated markers. ZNF385D was a predictor of overall fiber tract volumes in both hemispheres, as well as global brain volume. Here, we present evidence for ZNF385D as a candidate gene for RD and LI. The implication of transcription factor ZNF385D in RD and LI underscores the importance of transcriptional regulation in the development of higher order neurocognitive traits. Further study is necessary to discern target genes of ZNF385D and how it functions within neural development of fluent language.