Investigation of manic and euthymic episodes identifies state- and trait-specific gene expression and STAB1 as a new candidate gene for bipolar disorder

Bipolar disorder (BD) is a highly heritable psychiatric disease characterized by recurrent episodes of mania and depression. To identify new BD genes and pathways, the present study employed a three-step approach. First, gene-expression profiles of BD patients were assessed during both a manic and an euthymic phase. These profiles were compared intra-individually and with the gene-expression profiles of controls. Second, those differentially expressed genes that were considered potential trait markers of BD were validated using data from the Psychiatric Genomics Consortiums'' genome-wide association study (GWAS) of BD. Third, the implicated molecular mechanisms were investigated using pathway analytical methods. In the present patients, this novel approach identified: (i) sets of differentially expressed genes specific to mania and euthymia; and (ii) a set of differentially expressed genes that were common to both mood states. In the GWAS data integration analysis, one gene (STAB1) remained significant (P=1.9 × 10⁻⁴) after adjustment for multiple testing. STAB1 is located in close proximity to PBMR1 and the NEK4-ITIH1-ITIH3-ITIH4 region, which are the top findings from GWAS meta-analyses of mood disorder, and a combined BD and schizophrenia data set. Pathway analyses in the mania versus control comparison revealed three distinct clusters of pathways tagging molecular mechanisms implicated in BD, for example, energy metabolism, inflammation and the ubiquitin proteasome system. The present findings suggest that STAB1 is a new and highly promising candidate gene in this region. The combining of gene expression and GWAS data may provide valuable insights into the biological mechanisms of BD.     

Genome-Wide Association Study of the Relationship Between Matrix Metalloproteinases and Intracranial Aneurysms

Background and PurposeMatrix metalloproteinases (MMPs) are expected to play an important role in extracellular matrix (ECM) remodeling in response to hemodynamic stress. We investigated the association between MMPs and intracranial aneurysms (IAs) via a genome-wide association study (GWAS) of IAs.MethodsA GWAS data set of 250 IAs and 294 controls was used to analyze the genetic link between MMPs and IAs via single-nucleotide polymorphisms (SNPs), MMP gene families, and in silico functional analyses of gene ontology (GO) enrichment and protein–protein interaction (PPI).ResultsForty-eight SNPs and 1 indel out of 342 markers of MMP genes were related to IAs. The rs2425024 SNP located on MMP24 was the most strongly associated with IAs (OR=0.43, CI=0.30–0.61, p=2.4×10^-6), suggesting a protective effect. The 16938619 SNP of MMP26 significantly increased the risk of an IA (OR=3.12, 95% CI=1.76–5.50, p=8.85×10^-5). Five MMP genes (MMP24, MMP13, MMP2, MMP17, and MMP1) increased the susceptibility to an IA. MMP24 was the gene most closely related to IAs (p=7.96×10^-7). GO analysis showed that collagen catabolism was the most-enhanced biological process. Further, metalloendopeptidase activity and ECM were predominantly detected in the cellular component and molecular function, respectively. PPI provided evidence that MMP2, TIMP2 (tissue inhibitor of metalloproteinase 2), and TIMP3 genes constitute a network for predicting IA formation.ConclusionsThe present results provide comprehensive insight into the occurrence of IAs associated with MMPs.     

Multi-locus genome-wide association analysis supports the role of glutamatergic synaptic transmission in the etiology of major depressive disorder

Major depressive disorder (MDD) is a common psychiatric illness characterized by low mood and loss of interest in pleasurable activities. Despite years of effort, recent genome-wide association studies (GWAS) have identified few susceptibility variants or genes that are robustly associated with MDD. Standard single-SNP (single nucleotide polymorphism)-based GWAS analysis typically has limited power to deal with the extensive heterogeneity and substantial polygenic contribution of individually weak genetic effects underlying the pathogenesis of MDD. Here, we report an alternative, gene-set-based association analysis of MDD in an effort to identify groups of biologically related genetic variants that are involved in the same molecular function or cellular processes and exhibit a significant level of aggregated association with MDD. In particular, we used a text-mining-based data analysis to prioritize candidate gene sets implicated in MDD and conducted a multi-locus association analysis to look for enriched signals of nominally associated MDD susceptibility loci within each of the gene sets. Our primary analysis is based on the meta-analysis of three large MDD GWAS data sets (total N=4346 cases and 4430 controls). After correction for multiple testing, we found that genes involved in glutamatergic synaptic neurotransmission were significantly associated with MDD (set-based association P=6.9 × 10⁻⁴). This result is consistent with previous studies that support a role of the glutamatergic system in synaptic plasticity and MDD and support the potential utility of targeting glutamatergic neurotransmission in the treatment of MDD.     

Genome-wide significant association between a ‘negative mood delusions' dimension in bipolar disorder and genetic variation on chromosome 3q26.1

Research suggests that clinical symptom dimensions may be more useful in delineating the genetics of bipolar disorder (BD) than standard diagnostic models. To date, no study has applied this concept to data from genome-wide association studies (GWAS). We performed a GWAS of factor dimensions in 927 clinically well-characterized BD patients of German ancestry. Rs9875793, which is located in an intergenic region of 3q26.1 and in the vicinity of the solute carrier family 2 (facilitated glucose transporter), member 2 gene (SLC2A2), was significantly associated with the factor analysis-derived dimension ‘negative mood delusions'' (n=927; P=4.65 × 10⁻⁸, odds ratio (OR)=2.66). This dimension was comprised of the symptoms delusions of poverty, delusions of guilt and nihilistic delusions. In case–control analyses, significant association with the G allele of rs9875793 was only observed in the subgroup of BD patients who displayed symptoms of ‘negative mood delusions'' (allelic χ² model: P_G=0.0001, OR=1.92; item present, n=89). Further support for the hypothesis that rs9875793 is associated with BD in patients displaying ‘negative mood delusions'' symptom, such as delusions of guilt, was obtained from an European American sample (GAIN/TGEN), which included 1247 BD patients and 1434 controls (P_EA=0.028, OR=1.27).     

Meta-analysis of genome-wide association studies for panic disorder in the Japanese population

Panic disorder (PD) is a moderately heritable anxiety disorder whose pathogenesis is not well understood. Due to the lack of power in previous association studies, genes that are truly associated with PD might not be detected. In this study, we conducted a genome-wide association study (GWAS) in two independent data sets using the Affymetrix Mapping 500K Array or Genome-Wide Human SNP Array 6.0. We obtained imputed genotypes for each GWAS and performed a meta-analysis of two GWAS data sets (718 cases and 1717 controls). For follow-up, 12 single-nucleotide polymorphisms (SNPs) were tested in 329 cases and 861 controls. Gene ontology enrichment and candidate gene analyses were conducted using the GWAS or meta-analysis results. We also applied the polygenic score analysis to our two GWAS samples to test the hypothesis of polygenic components contributing to PD. Although genome-wide significant SNPs were not detected in either of the GWAS nor the meta-analysis, suggestive associations were observed in several loci such as BDKRB2 (P=1.3 × 10⁻⁵, odds ratio=1.31). Among previous candidate genes, supportive evidence for association of NPY5R with PD was obtained (gene-wise corrected P=6.4 × 10⁻⁴). Polygenic scores calculated from weakly associated SNPs (P<0.3 and 0.4) in the discovery sample were significantly associated with PD status in the target sample in both directions (sample I to sample II and vice versa) (P<0.05). Our findings suggest that large sets of common variants of small effects collectively account for risk of PD.     

Working memory brain activity and capacity link MAOA polymorphism to aggressive behavior during development

A developmental increase in working memory capacity is an important part of cognitive development, and low working memory (WM) capacity is a risk factor for developing psychopathology. Brain activity represents a promising endophenotype for linking genes to behavior and for improving our understanding of the neurobiology of WM development. We investigated gene–brain–behavior relationships by focusing on 18 single-nucleotide polymorphisms (SNPs) located in six dopaminergic candidate genes (COMT, SLC6A3/DAT1, DBH, DRD4, DRD5, MAOA). Visuospatial WM (VSWM) brain activity, measured with functional magnetic resonance imaging, and VSWM capacity were assessed in a longitudinal study of typically developing children and adolescents. Behavioral problems were evaluated using the Child Behavior Checklist (CBCL). One SNP (rs6609257), located ∼6.6 kb downstream of the monoamine oxidase A gene (MAOA) on human chromosome X, significantly affected brain activity in a network of frontal, parietal and occipital regions. Increased activity in this network, but not in caudate nucleus or anterior prefrontal regions, was correlated with VSWM capacity, which in turn predicted externalizing (aggressive/oppositional) symptoms, with higher WM capacity associated with fewer externalizing symptoms. There were no direct significant correlations between rs6609257 and behavioral symptoms. These results suggest a mediating role of WM brain activity and capacity in linking the MAOA gene to aggressive behavior during development.     

A genome-wide association study of suicide severity scores in bipolar disorder

BackgroundSuicide claims one million lives worldwide annually, making it a serious public health concern. The risk for suicidal behaviour can be partly explained by genetic factors, as suggested by twin and family studies (reviewed in (Zai et al. 2012)). Recently, genome-wide association studies (GWASs) of suicide attempt on large samples of bipolar disorder (BD) patients from multiple sites have identified a number of novel candidate genes. GWASs of suicide behaviour severity, from suicidal ideation to serious suicide attempt, have not been reported for BD.MethodsWe conducted a GWAS of suicide behaviour severity in three independent BD samples:212 small nuclear families with BD probands from Toronto, Canada, 428 BD cases from Toronto, and 483 BD cases from the UK. We carried out imputation with 1000 Genome Project data as reference using IMPUTE2. Quality control and data analysis was conducted using PLINK and R. We conducted the quantitative analyses of suicide behaviour severity in the three samples separately, and derived an overall significance by a meta-analysis using the METAL software.ResultsWe did not find genome-wide significant association of any tested markers in any of the BD samples, but we found a number of suggestive associations, including regions on chromosomes 8 and 10 (p < 1e-5).ConclusionsOur GWAS findings suggest that likely many gene variants of small effects contribute collectively to the risk for suicidal behaviour severity in BD. Larger independent replications are required to strengthen the findings from the GWAS presented here.     

Genome-wide association study of Alzheimer's disease

In addition to apolipoprotein E (APOE), recent large genome-wide association studies (GWASs) have identified nine other genes/loci (CR1, BIN1, CLU, PICALM, MS4A4/MS4A6E, CD2AP, CD33, EPHA1 and ABCA7) for late-onset Alzheimer''s disease (LOAD). However, the genetic effect attributable to known loci is about 50%, indicating that additional risk genes for LOAD remain to be identified. In this study, we have used a new GWAS data set from the University of Pittsburgh (1291 cases and 938 controls) to examine in detail the recently implicated nine new regions with Alzheimer''s disease (AD) risk, and also performed a meta-analysis utilizing the top 1% GWAS single-nucleotide polymorphisms (SNPs) with P<0.01 along with four independent data sets (2727 cases and 3336 controls) for these SNPs in an effort to identify new AD loci. The new GWAS data were generated on the Illumina Omni1-Quad chip and imputed at ∼2.5 million markers. As expected, several markers in the APOE regions showed genome-wide significant associations in the Pittsburg sample. While we observed nominal significant associations (P<0.05) either within or adjacent to five genes (PICALM, BIN1, ABCA7, MS4A4/MS4A6E and EPHA1), significant signals were observed 69–180 kb outside of the remaining four genes (CD33, CLU, CD2AP and CR1). Meta-analysis on the top 1% SNPs revealed a suggestive novel association in the PPP1R3B gene (top SNP rs3848140 with P=3.05E–07). The association of this SNP with AD risk was consistent in all five samples with a meta-analysis odds ratio of 2.43. This is a potential candidate gene for AD as this is expressed in the brain and is involved in lipid metabolism. These findings need to be confirmed in additional samples.     

Genome-wide analysis implicates microRNAs and their target genes in the development of bipolar disorder

Bipolar disorder (BD) is a severe and highly heritable neuropsychiatric disorder with a lifetime prevalence of 1%. Molecular genetic studies have identified the first BD susceptibility genes. However, the disease pathways remain largely unknown. Accumulating evidence suggests that microRNAs, a class of small noncoding RNAs, contribute to basic mechanisms underlying brain development and plasticity, suggesting their possible involvement in the pathogenesis of several psychiatric disorders, including BD. In the present study, gene-based analyses were performed for all known autosomal microRNAs using the largest genome-wide association data set of BD to date (9747 patients and 14 278 controls). Associated and brain-expressed microRNAs were then investigated in target gene and pathway analyses. Functional analyses of miR-499 and miR-708 were performed in rat hippocampal neurons. Ninety-eight of the six hundred nine investigated microRNAs showed nominally significant P-values, suggesting that BD-associated microRNAs might be enriched within known microRNA loci. After correction for multiple testing, nine microRNAs showed a significant association with BD. The most promising were miR-499, miR-708 and miR-1908. Target gene and pathway analyses revealed 18 significant canonical pathways, including brain development and neuron projection. For miR-499, four Bonferroni-corrected significant target genes were identified, including the genome-wide risk gene for psychiatric disorder CACNB2. First results of functional analyses in rat hippocampal neurons neither revealed nor excluded a major contribution of miR-499 or miR-708 to dendritic spine morphogenesis. The present results suggest that research is warranted to elucidate the precise involvement of microRNAs and their downstream pathways in BD.     

Power and Pitfalls of the Genome-Wide Association Study Approach to Identify Genes for Alzheimer’s Disease

Until recently, the search for genes contributing to Alzheimer’s disease (AD) had been slow and disappointing, with the notable exception of the APOE ε4 allele, which increases risk and reduces the age at onset of AD in a dose-dependent fashion. Findings from genome-wide association studies (GWAS) made up of fewer than several thousand cases and controls each have not been replicated. Efforts of several consortia—each assembling much larger datasets with sufficient power to detect loci conferring small changes in AD risk—have resulted in robust associations with many novel genes involved in multiple biological pathways. Complex data mining strategies are being used to identify additional members of these pathways and gene–gene interactions contributing to AD risk. Guided by GWAS results, next-generation sequencing and functional studies are under way with the hope of helping us better understand AD pathology and providing new drug targets.     

Complex gene–gene interactions in multiple sclerosis: a multifactorial approach reveals associations with inflammatory genes

The complex inheritance involved in multiple sclerosis (MS) risk has been extensively investigated, but our understanding of MS genetics remains rudimentary. In this study, we explore 51 single nucleotide polymorphisms (SNPs) in 36 candidate genes from the inflammatory pathway and test for gene–gene interactions using complementary case–control, discordant sibling pair, and trio family study designs. We used a sample of 421 carefully diagnosed MS cases and 96 unrelated, healthy controls; discordant sibling pairs from 146 multiplex families; and 275 trio families. We used multifactor dimensionality reduction to explore gene–gene interactions. Based on our analyses, we have identified several statistically significant models including both main effect models and two-locus, three-locus, and four-locus epistasis models that predict MS disease risk with between ∼61% and 85% accuracy. These results suggest that significant epistasis, or gene–gene interactions, may exist even in the absence of statistically significant individual main effects.Alison A. Motsinger and David Brassat contributed equally to this work.     

Genetic association of impulsivity in young adults: a multivariate study

Impulsivity is a heritable, multifaceted construct with clinically relevant links to multiple psychopathologies. We assessed impulsivity in young adult (N~2100) participants in a longitudinal study, using self-report questionnaires and computer-based behavioral tasks. Analysis was restricted to the subset (N=426) who underwent genotyping. Multivariate association between impulsivity measures and single-nucleotide polymorphism data was implemented using parallel independent component analysis (Para-ICA). Pathways associated with multiple genes in components that correlated significantly with impulsivity phenotypes were then identified using a pathway enrichment analysis. Para-ICA revealed two significantly correlated genotype–phenotype component pairs. One impulsivity component included the reward responsiveness subscale and behavioral inhibition scale of the Behavioral-Inhibition System/Behavioral-Activation System scale, and the second impulsivity component included the non-planning subscale of the Barratt Impulsiveness Scale and the Experiential Discounting Task. Pathway analysis identified processes related to neurogenesis, nervous system signal generation/amplification, neurotransmission and immune response. We identified various genes and gene regulatory pathways associated with empirically derived impulsivity components. Our study suggests that gene networks implicated previously in brain development, neurotransmission and immune response are related to impulsive tendencies and behaviors.     

Bipolar disorder risk alleles in children with ADHD

Bipolar disorder (BD) and attention deficit/hyperactivity disorder (ADHD) may share common genetic risk factors as indicated by the high co-morbidity of BD and ADHD, their phenotypic overlap especially in pediatric populations, the high heritability of both disorders, and the co-occurrence in families. We therefore examined whether known polygenic BD risk alleles are associated with ADHD. We chose the eight best SNPs of the recent genome-wide association study (GWAS) of BD patients of German ancestry and the nine SNPs from international GWAS meeting a ‘genome-wide significance’ level of α = 5 × 10^?8. A GWAS was performed in 495 ADHD children and 1,300 population-based controls using HumanHap550v3 and Human660 W-Quadv1 BeadArrays. We found no significant association of childhood ADHD with single BD risk alleles surviving adjustment for multiple testing. Yet, risk alleles for BD and ADHD were directionally consistent at eight of nine loci with the strongest support for three SNPs in or near NCAN, BRE, and LMAN2L. The polygene analysis for the BP risk alleles at all 14 loci indicated a higher probability of being a BD risk allele carrier in the ADHD cases as compared to the controls. At a moderate power to detect association with ADHD, if true effects were close to estimates from GWAS for BD, our results suggest that the possible contribution of BD risk variants to childhood ADHD risk is considerably lower than for BD. Yet, our findings should encourage researchers to search for common genetic risk factors in BD and childhood ADHD in future studies.     

Meta-analysis of Positive and Negative Symptoms Reveals Schizophrenia Modifier Genes

Background: Evidence suggests that genetic factors may influence both schizophrenia (Scz) and its clinical presentation. In recent years, genome-wide association studies (GWAS) have demonstrated considerable success in identifying risk loci. Detection of “modifier loci” has the potential to further elucidate underlying disease processes. Methods: We performed GWAS of empirically derived positive and negative symptom scales in Irish cases from multiply affected pedigrees and a larger, independent case–control sample, subsequently combining these into a large Irish meta-analysis. In addition to single-SNP associations, we considered gene-based and pathway analyses to better capture convergent genetic effects, and to facilitate biological interpretation of these findings. Replication and testing of aggregate genetic effects was conducted using an independent European-American sample. Results: Though no single marker met the genome-wide significance threshold, genes and ontologies/pathways were significantly associated with negative and positive symptoms; notably, NKAIN2 and NRG1, respectively. We observed limited overlap in ontologies/pathways associated with different symptom profiles, with immune-related categories over-represented for negative symptoms, and addiction-related categories for positive symptoms. Replication analyses suggested that genes associated with clinical presentation are generalizable to non-Irish samples. Conclusions: These findings strongly support the hypothesis that modifier loci contribute to the etiology of distinct Scz symptom profiles. The finding that previously implicated “risk loci” actually influence particular symptom dimensions has the potential to better delineate the roles of these genes in Scz etiology. Furthermore, the over-representation of distinct gene ontologies/pathways across symptom profiles suggests that the clinical heterogeneity of Scz is due in part to complex and diverse genetic factors.Key words: schizophrenia, meta-analysis, clinical heterogeneity, modifier genes, negative symptoms, positive symptoms     

The influence of polygenic risk for bipolar disorder on neural activation assessed using fMRI

Genome-wide association studies (GWAS) have demonstrated a significant polygenic contribution to bipolar disorder (BD) where disease risk is determined by the summation of many alleles of small individual magnitude. Modelling polygenic risk scores may be a powerful way of identifying disrupted brain regions whose genetic architecture is related to that of BD. We determined the extent to which common genetic variation underlying risk to BD affected neural activation during an executive processing/language task in individuals at familial risk of BD and healthy controls. Polygenic risk scores were calculated for each individual based on GWAS data from the Psychiatric GWAS Consortium Bipolar Disorder Working Group (PGC-BD) of over 16 000 subjects. The familial group had a significantly higher polygene score than the control group (P=0.04). There were no significant group by polygene interaction effects in terms of association with brain activation. However, we did find that an increasing polygenic risk allele load for BD was associated with increased activation in limbic regions previously implicated in BD, including the anterior cingulate cortex and amygdala, across both groups. The findings suggest that this novel polygenic approach to examine brain-imaging data may be a useful means of identifying genetically mediated traits mechanistically linked to the aetiology of BD.     

Variants in the inflammatory IL6 and MPO genes modulate stroke susceptibility through main effects and gene–gene interactions

There is substantial evidence that inflammation within the central nervous system contributes to stroke risk and recovery. Inflammatory conditions increase stroke risk, and the inflammatory response is of major importance in recovery and healing processes after stroke. We investigated the role of inflammatory genes IL1B, IL6, MPO, and TNF in stroke susceptibility and recovery in a population sample of 672 patients and 530 controls, adjusting for demographic, clinical and lifestyle risk factors, and stroke severity parameters. We also considered the likely complexity of inflammatory mechanisms in stroke, by assessing the combined effects of multiple genes. Two interleukin 6 (IL6) and one myeloperoxidase (MPO) single-nucleotide polymorphisms were significantly associated with stroke risk (0.022<_correctedP<0.042), highlighting gene variants of low to moderate effect in stroke risk. An epistatic interaction between the IL6 and MPO genes was also identified in association with stroke susceptibility (P=0.031 after 1,000 permutations). In a subset of 546 patients, one IL6 haplotype was associated with stroke outcome at 3 months (_correctedP=0.024), an intriguing finding warranting further validation. Our findings support the association of the IL6 gene and present novel evidence for the involvement of MPO in stroke susceptibility, suggesting a modulation of stroke risk by main gene effects, clinical and lifestyle factors, and gene–gene interactions.