XXII October 12-16, 2014 Copenhagen, Denmark Pathways to Therapy and Prevention
Short Description
Download XXII October 12-16, 2014 Copenhagen, Denmark Pathways to Therapy and Prevention...
Description
XXII
ND World Congress of Psychiatric Genetics
October 12-16, 2014 Copenhagen, Denmark ORAL PRESENTATION ABSTRACTS
Pathways to Therapy and Prevention
Monday, October 13, 2014 11:00 AM - 12:00 PM Concurrent Oral Sessions OVERALL SESSION: THE GENOMICS OF AFFECTIVE DISORDERS & ADHD THE RELATIONSHIP BETWEEN COMMON AND RARE GENETIC VARIANTS IN ATTENTION DEFICIT HYPERACTIVITY DISORDER Joanna Martin1, Michael C. O'Donovan1, Anita Thapar1, Kate Langley1, Nigel Williams1 1 MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University Background Attention deficit hyperactivity disorder (ADHD) is highly heritable. Genome-wide molecular studies show an increased burden of large, rare copy number variants (CNVs) in children with ADHD compared with controls. Recent polygenic score analyses have also shown that common variants can be used in mass to differentiate ADHD cases from controls. The relationship between these common and rare variants has yet to be explored. Methods In this study, we tested whether children with ADHD with a large (>500kb), rare (C on chromosome 9p24 (p-value=9*10-04, MAF=1%, effect=2.47) in the gene RCL1 associated with the HADS scale. All carriers (N=34) connected within 6 generations. This variant is highly conserved (phastcons = 1) and predicted to be damaging (polyphen=0.68). A rare T>G damaging (polyPhen=1) missense variant in the gene BTNL9 on chromosome 5q35 was suggestively associated (pvalue=1.5*10-05, MAF=1%, effect=3.44) with the HADS depression scale. All carriers (N=35) were connected to each other in four generations of which, 15 were treated for either major or mild depression. Discussion Using exome-sequencing and various gene-mapping techniques in a large family from a genetically isolated population, we have identified several rare genetic variants that segregate and confer large effects on depression/depressive symptoms. While RCL1 is a novel candidate, TMEM151A lies in the candidate region discovered in the major depression genome-wide association study by the psychiatric genetics consortium. Further, TMEM151A is predominantly expressed in brain (primarily subthalamicnucleus: AUC = 1.00, p-value=3*10-09) and predicted to be involved in dopamine and serotonin release cycle (p-value=2.7*10-11). BTNL9 is expressed in brain and fat tissues and known to be involved in triglyceride homeostasis. All discovered variants are relatively rare in 1000 genomes and other populations and usually not well-imputed thus limiting the scope for replication. Most variants are also not present on the Illumina exome array. We, therefore, plan to perform functional analyses. PATHWAY-BASED ENRICHMENT ANALYSIS (INRICH) IN 9,474 PATIENTS WITH BIPOLAR DISORDER AND 14,278 CONTROLS SUGGESTS AN INVOLVEMENT OF NCAM SIGNALING IN DISEASE ETIOLOGY Sven Cichon1, Thomas W. Mühleisen2, Andreas Forstner3, Markus Leber4, Thomas G. Schulze5, Jana Strohmaier6, Franziska Degenhardt3, Stefan Herms1, Manuel Mattheisen7, Per Hoffmann1, Additional Members of the MooDS Bipolar Disorder Working Group MooDS BD, Peter Propping8, Tim Becker4, Marcella Rietschel6, Markus M. Nöthen3 1 University of Basel, 2Institute of Human Genetics, Life & Brain Center, University of Bonn, Germany; Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, 3Institute of Human Genetics,
Life & Brain Center, University of Bonn, Germany, 4DZNE Bonn, Germany; Institute of Medical Biometry, Informatics and Epidemiology (IMBIE), University of Bonn, 5University of Göttingen, 6 Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, 7Aarhus University, 8Institute of Human Genetics, University of Bonn Background Genome-wide association studies (GWAS) have identified the first common risk variants for bipolar disorder (BD), in particular ANK3, CACNA1C, NCAN, ODZ4, ADCY2, MIR2113-POU3F2. The majority of genetic variants influencing BD, however, remains unknown. These variants are expected to have small effect-sizes and are difficult to detect individually at high statistical stringency by GWAS using the currently available sample sizes. Pathway-based approaches have been developed, which use prior biological knowledge on gene function to facilitate a more powerful analysis of GWAS data sets and get more comprehensive insights into the biology of complex diseases. We employed this strategy in a large GWAS data set of BD. Methods For the pathway-based analysis, we used a sample of 9,747 patients with BD and 14,278 controls, comprised of a large cohort of European/Australian descent and the samples of the published BD-GWAS by the Psychiatric Genomics Consortium. Analysis was performed with INRICH, a software that tests if association signals in predefined gene sets (pathways) are enriched across independent gene loci (non-overlapping intervals). Results Test intervals were constructed in two steps. First, GWAS results on 2.3 million autosomal SNPs were filtered for strong to moderate signals (P1,200 breakpoints. By international expansion we will extend this at least 10-fold to reach a proposed first goal of ~10,000 breakpoints. Unlike other large scale genomic efforts, all countries including undeveloped and developing countries can participate. We expect that the breakpoint-map will identify and confirm numerous genotypephenotype associations, a majority of which will involve disorders of the brain.
PSYCHCHIP: DESIGN, QUALITY CONTROL AND PERFORMANCE Stephan Ripke1, PGC PsychChip Group 1 Massachusetts General Hospital Background The Psychiatric Genomics Consortium (PGC) is an international group of researchers whose major aim is to maximize the utility of psychiatric genome-wide association studies (GWAS) through mega-analysis. In recent years, these studies have successfully identified many novel genetic associations for psychiatric disorders by integrating data from >170,000 subjects. To continue these efforts, the PGC has developed a custom genotyping array, the PsychChip, and is coordinating genotyping of over 100,000 samples at the Stanley Center of the Broad Institute and the Mount Sinai School of Medicine. Methods The PsychChip consists of three components: a GWAS backbone of ~256k SNPs, ~236k rare and low-frequency exome variants, and ~50k custom markers tailored to psychiatric disorders. We used previous psychiatric genetic studies to select markers with the following goals in mind. First, we ensured any variants showing modest association (P2.9) were further examined by performing associations of SNPs underneath. Results The insula-mPFC grey matter SBM component derived from GOBS was very similar to the one
derived from the case-control sample (Cota et al., In Review): Dice coefficient: 0.42, Pearson r = 0.58. The overall grey matter density across this component was highly heritable, as indicated by the polygenic model of the weights (h2 = 0.59; p = 1.78*10-15). A QTL was identified on chromosome 12 at 12q24.22-12q24.23, with a highly significant LOD = 3.76. There were 397 common SNPs under the linkage peak, the strongest association of which was for rs7133582 (p = 7.71*10-4) in a transcription factor binding site of KSR2, at the 12q24.23 end of the peak, which is in agreement with the maximum LOD score in this locus. Discussion There is compelling evidence that gray matter density in the insula and mPFC is reduced in patients with schizophrenia, and their unaffected relatives. Our findings indicate that genetic variation in 12q24 influences grey matter density in these brain regions. Our QTL has previously been linked to schizophrenia (Bulayeva at al., 2007) and bipolar disorder (Berettini et al., 2001). Our top SNP under the peak is located 90% of subjects were switched from genetically discordant to genetically concordant medications and showed improved clinical outcomes relative to their blinded, TAU counterparts (p = 0.005). Discussion Continued from results: In the retrospective healthcare utilization study, subjects on
discordant medications had 69% more total healthcare visits (p = 0.01), 3-fold more medical absence days (p = 0.04), 4-fold more disability claims (p = 0.003), resulting in an estimated $5,188 higher medical costs relative to subjects on genetically concordant medications. In the prospective pharmacy claims pilot, GeneSight-guided patients saved a mean $1,035.60 in annual medication costs compared to unguided TAU patients (p < 0.0001). Within the GeneSight arm, patients who remained on genetically concordant medications saved $587.77 more annually relative to patients who remained on genetically discordant medications (p = 0.007). Conclusions - GeneSight has shown clinical validity by predicting patient treatment responses. - GeneSight clinical utility is evidenced by a 2.3-fold greater odds of response. GeneSight is estimated to reduce healthcare costs by over $3,000 annually. OVERALL SESSION: FUNCTIONAL GENOMICS & ENDOPHENOTYPES THE ANTIPSYCHOTIC OLANZAPINE INTERACTS WITH THE GUT MICROBIOME TO CAUSE WEIGHT GAIN IN MOUSE James Crowley1, Andrew Morgan1, Randal Nonneman1, Corey Quackenbush1, Cheryl Miller1, Allison Ryan1, Molly Bogue2, Sur Paredes1, Scott Yourstone1, Ian Carroll1, Thomas Kawula1, Maureen Bower1, Balfour Sartor1, Patrick Sullivan1 1 University of North Carolina at Chapel Hill, 2Jackson Laboratory Background The second-generation antipsychotic olanzapine is effective in reducing psychotic symptoms but is associated with considerable weight gain. Given the known involvement of the gut microbiome in obesity, we used a mouse model to evaluate the role of the gut microbiome in olanzapineinduced weight gain. Methods C57BL/6J mice were randomized to receive either olanzapine (50 mg/kg diet) or placebo while consuming a high-fat diet ad libitum beginning at 8 weeks of age and body weight was measured weekly. Results First, we established that oral delivery of olanzapine to C57BL6/J mice on a high fat diet resulted in considerable weight gain compared to placebo (p = 1.1 × 10-5). Second, we found that mice raised in germ-free conditions had no significant weight gain while consuming olanzapine (p = 0.48) but that the same mice had significant weight gain following introduction of gut flora (p = 4.9 × 10-3). Third, we used a randomized controlled crossover design to survey the fecal microbiome before, during, and after olanzapine treatment by sequencing bacterial 16S ribosomal DNA. Olanzapine potentiated a shift towards an “obesogenic” microbiota and this shift was correlated with weight gain. Finally, we demonstrated that olanzapine has antimicrobial activity in vitro against two commensal enteric bacterial strains. Discussion Taken together, these results provide strong evidence for a mechanism underlying olanzapine- induced weight gain in mouse. Olanzapine is a subtle antimicrobial, and shifts the gut microbiome to an obesogenic pattern. This work suggests a hypothesis for clinical translation in human patients. We note that the effects of olanzapine are analogous to low-dose antibiotic regimens used to promote growth in livestock. CARRIERS OF A GENOME-WIDE SIGNIFICANT BIPOLAR DISORDER RISK ALLELE SHOW DECREASED TRANK1 EXPRESSION IN NEURAL PROGENITOR CELLS THAT IS RESCUED BY SODIUM VALPROATE Xueying Jiang1, Sevilla Detera-Wadleigh 1, Nirmala Akula1, Francis McMahon1 1 National Institute of Mental Health Background Genome-wide association studies (GWAS) have identified several risk variants for bipolar disorder (BD), but the functional consequences of most variants remain undefined. A common variant (rs9834970) located ~15 kb 3’ of the gene TRANK1 on chromosome 3p22 has shown genome-wide significant association with BD in several studies [1-4] and nearby markers have been associated with
schizophrenia [5]. Previously, we showed that valproic acid (VPA), an effective treatment for BD, increased TRANK1 expression in commercial cell lines [1]. In this study, we aimed to confirm the effect of VPA treatment on TRANK1 expression in induced pluripotent stem cells (iPSc) and in iPSC-derived neural progenitor cells (NPCs), and to test the effect of the rs9834970 risk allele (G) on TRANK1 expression in both iPSc and NPC cultures. Methods iPSC lines were generated by lentiviral reprogramming of adult human fibroblast cells from 7 individuals with known genotypes at rs9834970. All 7 iPSC lines were further differentiated into NPCs with Gibco PSC neural induction medium (Life technology, CA). iPScs and NPCs were validated by standard immunochemical analysis. RNA was extracted at baseline and after 72h of treatment with VPA (0.5mM or 1mM) from 4 iPSC and 7 NPC lines. TRANK1 gene expression levels were measured by quantitative real-time polymerase chain reaction (qRT-PCR), with 3 technical replicates for each treatment condition. All samples were genotyped on the Illumina Infinium Human OmniExpress Exome bead array. Statistical significance of gene expression differences was determined by two-way ANOVA. Results VPA treatment substantially increased TRANK1 expression in both iPSc and NPC lines. Foldchange vs. baseline ranged from 2.76 (0.5mM VPA) to 6.18 (1mM VPA) in iPSc (P22,000 controls, genotyped on the CoreExome Chip. Samples derive from eight different populations; care has been taken to ensure that cases and controls are ancestrally matched. The CoreExome Chip enables us to study both common and lowfrequency variants simultaneously; our study is the first to examine the role played by low-frequency and rare variants in AN. Results Analysis is currently complete across three of the eight contributing populations: Norway, with 87 cases and 100 controls; Finland, 163 cases, 5,300 controls; and the UK, 181 cases and 10,034 controls. We have performed a meta-analysis across these three populations and thus far have identified four genome-wide significant signals: exm370124, exm462797, exm464785, exm2116552. These four variants are all low frequency, mis-sense variants. We looked at the frequency of these SNPs in both cases and controls. All SNPs were extremely low frequency in the control populations, with highest MAF between 0.005 and 0.01. SNPs were also low frequency in the cases, with highest MAF between 0.01 and 0.10. Effect sizes for each SNP were high, and the same direction of effect was noted for every SNP in at least 2/3 populations. Maximum effect sizes for each SNP were between 6.6 and 74.5. Discussion One of these associated variants (exm464785) lies in RASGRF2, a gene that has previously
been associated with eating disorders (Wade et al 2013), albeit not at a genome-wide significant level. This is the first genome-wide significant variant that has been associated with AN. We hope that this will enable further studies into the functional mechanisms underlying AN, and perhaps be a first step towards establishing effective medications and treatment. Further, all four hits that have been identified are very low frequency and could not possibly have been identified in previous GWAS studies. This may be a good indication that low-frequency, Core-Exome chip type studies have potential to reveal new associated variants across a range of psychiatric disorders. MEGA-ANALYSIS OF AGE AT ONSET OF BIPOLAR DISORDER, MAJOR DEPRESSIVE DISORDER AND SCHIZOPHRENIA IN THE PSYCHIATRIC GENOMICS CONSORTIUM T. Bernard Bigdeli1, Stephan Ripke2, Silviu-Alin Bacanu3, Richard L. Amdur4, Aiden Corvin5, Cathryn M. Lewis6, Robert A. Power7, Andrew McQuillin8, S. Hong Lee9, Naomi R. Wray9, Kenneth S. Kendler3, PGC Cross-disorder Group, PGC MDD Workgroup, PGC Bipolar Disorder Workgroup, PGC Schizophrenia Workgroup, Ayman H. Fanous4 1 VIPBG, 2Analytic and Translational Genetics Unit, Massachusetts General Hospital, 3Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University School of Medicine, 4Mental Health Service Line, Washington VA Medical Center, 5Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, 6Medical Research Council's Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, 7 MRC Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, 8 Molecular Psychiatry Laboratory, Windeyer Institute of Medical Sciences, Research Department of Mental Health Sciences, University College London, 9The Queensland Brain Institute, The University of Queensland Background Age at onset (AAO) of adult psychiatric disorders is an important clinical indicator of illness course and outcome, with earlier AAO often associated with disease severity and response to treatment. Whether onset at very early or relatively advanced ages suggests distinct disease entities remains unclear, as does the relative importance of familial and environmental factors. Methods Single-nucleotide polymorphism (SNP) and AAO data were available for 8803 bipolar disorder (BIP), 9380 major depressive disorder (MDD), and 9354 schizophrenia (SCZ) cases from respective workgroups of the Psychiatric Genomics Consortium. We performed genome-wide association studies (GWAS) of AAO within each disorder (case-only), combining these results in cross-disorder meta- analyses of BIP and MDD (N=18183) and BIP and SCZ (N=18157), and culminating in a metaanalysis of all three disorders (N=27537). We obtained estimates of the proportion of variability in AAO explained by genome-wide SNPs using the Genome-wide Complex Traits Analysis (GCTA) tool. Results While no single SNP attained genome-wide significance (P
View more...
Comments