The Role Of Micrornas In The Course Of Severe Mental Disorders

The Role Of Micrornas In The Course Of Severe Mental Disorders

S456 Abstracts of the XXIV World Congress of Psychiatric Genetics (WCPG) 2016 T38. PRELIMINARY MODEL FOR THE GENETIC PREDICTION OF CLOZAPINE RESPONS...

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S456

Abstracts of the XXIV World Congress of Psychiatric Genetics (WCPG) 2016

T38. PRELIMINARY MODEL FOR THE GENETIC PREDICTION OF CLOZAPINE RESPONSE

James L. Kennedy1, Eric Huang1, Arun K. Tiwari1, Clement Zai1, Vanessa Gonçalves1, Steve Potkin2, Jeffrey Lieberman3, Herbert Meltzer4 1

Centre for Addiction and Mental Health Brain Imaging Center, University of Irvine 3 New York State Psychiatric Institute/Columbia University 4 Northwestern University

has lower expression in the hippocampus of SCZ patients compared to healthy controls. It mediates cognitive function, anxiety, and positive symptom improvement in animal models of SCZ. The model does not appear to generalize to other antipsychotics. For CLZ response prediction per se, replication in independent studies of CLZ response in SCZ is required to confirm the validity of these findings.

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Disclosure Nothing to Disclose. http://dx.doi.org/10.1016/j.euroneuro.2016.09.526

Background: Despite its clinical utility, the antipsychotic clozapine (CLZ) has not yet had a promising pharmacogenetic test developed for prediction of response. In the past 20 years, multiple genetic variants (e.g. dopamine, serotonin) have been suggested to be associated with CLZ response. Arranz et al (2000) proposed a model to predict response, but it was not replicated in independent samples. Since then, no other studies have sought to create a genetic panel predicting response to CLZ. Thus, we reinitiated the effort to develop a genetic model for CLZ response incorporating the most promising findings from our group’s repository of CLZ response studies. Methods: Our sample consisted of 151 Caucasian subjects with schizophrenia (SCZ) (DSM-III) treated with CLZ for six months. Response was assessed using the Brief Psychiatric Rating Scale (BPRS), and evaluated using absolute score change and binary response (Kane et al. 1988 criteria), with baseline score as a covariate. A total of 99 polymorphisms were tested from a range of candidate genes. Variants showing at least a nominal statistical trend (po0.1) were included in the model. An unweighted risk score was calculated for each SNP and assessed for association with response. Five-fold cross validation was performed in an attempt to limit model overfitting. The model was then tested in an independent sample of antipsychotic-treated SCZ patients of European ancestry (CATIE subsample, N= 390) to examine generalizability of findings to other antipsychotics. Results: Four markers from genes encoding for dopamine D2 receptor (DRD2), serotonin-6 receptor (5-HT6), brainderived neurotrophic factor (BDNF), and neurexin-1 (NRXN1) were included in the model. We observed a statistically significant association between genetic risk score with BPRS score change (p = 0.000039, Adjusted R̂ 2= 0.565) and binary response (p =0.004, Nagelkerke R̂ 2= 0.097) assuming a linear increase in response for each additional risk allele. The model had an accuracy of 62%, a sensitivity of 70%, and a specificity of 47%. The model was not significantly associated with response in the independent CATIE European Caucasian subsample treated with other antipsychotics (p = 0.10). Discussion: We have developed a preliminary genetic model for CLZ response that includes genes with strong rationale for involvement. NRXN1 is a synaptic membrane cell-adhesion protein that has been suggested to modulate NMDA receptor activity, which is indirectly regulated by CLZ. The 5-HT6 receptor is involved in neurite growth and

T39. THE ROLE OF MICRORNAS IN THE COURSE OF SEVERE MENTAL DISORDERS

Urs Heilbronner1, Gaurav Jain2, Lalit Kaurani2, Ivan Kondofersky3, Monika Budde1, Katrin Gade1, Janos Kalman1, Kristina Adorjan1, Fanny Aldinger1, Heike Anderson-Schmidt4, Nikola Mueller3, Fabian J. Theis3, Peter Falkai5, André Fischer2, Thomas G. Schulze1 1

Institute of Psychiatric Phenomics and Genomics, Medical Center of the University of Munich, Germany 2 German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany 3 Institute of Computational Biology, Helmholtz Zentrum München, Munich, Germany 4 Department of Psychiatry and Psychotherapy, University Medical Center, Georg-August-University, Göttingen, Germany 5 Department of Psychiatry and Psychotherapy, Medical Center of the University of Munich, Germany Background: Illnesses from the schizophrenia-to-bipolar spectrum have a highly variable course. Determinants of these different individual trajectories have been of particular interest to scholars during the past century. Beyond rudimentary understanding, however, different course types have been difficult to delineate in categorical disease phenotypes. We have therefore embarked upon a project in which we seek to delineate different course types in a large longitudinal sample of deeply phenotyped patients suffering from disorders of the schizophrenia-to-bipolar continuum. With respect to biology, a dysregulation of microRNAs, small non-coding RNA molecules that flexibly influence transcription, in mental disorders is increasingly recognized. To combine both of these novel approaches, we plan investigate the role of microRNAs in different course types identified using longitudinal cluster analysis. Methods Longitudinal clustering: Participants were selected from an ongoing longitudinal, multi-site study (www.kfo241.de, www.PsyCourse.de). Patients with a

Abstracts of the XXIV World Congress of Psychiatric Genetics (WCPG) 2016 DSM-IV diagnosis of the schizophrenia-to-bipolar spectrum were comprehensively phenotyped at four time-points over a period of 18 months. A set of longitudinally measured variables on current psychopathology, medication adherence, substance use, cognitive performance, level of psychosocial functioning and various questionnaires was analyzed using factor analysis for mixed data followed by longitudinal cluster analyses. This resulted in the identification of distinct subpopulations of patients, each being heterogeneous in terms of diagnostic composition. MicroRNA sequencing So far, we have compared four different methods to isolate blood borne small non-coding RNAs for RNAsequencing. By this we were able to establish SOPs for the reliable analysis of circulating small non-coding RNAs in longitudinal cohorts. Results: We will present results of our research project at the meeting. Discussion: We will discuss our research project at the meeting.

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Results: Three markers namely rs2064430 (p=0.04, OR= 1.14, CI=1.01-1.3, AHI), rs6932590 (p=0.05, OR= 0.85, CI=0.73-1.00, intergenic), rs6916921 (p=0.05,OR=1.19, CI=1.00-1.43, NFKBIL1) showed modest association to DSM IV schizophrenia diagnosis under allelic test of association while rs3130615 and rs6916394 showed genotypic (p=0.04, p=0.02) and recessive association (p=0.01, 0.05) but none withstood Bonferroni correction. The most significant 2 marker haplotype using PLINK sliding window came from four regions: 1) intergenic region -rs6932590|rs3800318 (TA, p=0.02) 2) HLADQA1 region- rs377763|rs9273012 (GA, p=0.04) and 3) TNF regionrs1800610|rs986475 (CC, p=0.03) 4) MICB region- rs3130615| rs2516489 (CG, p=0.04). Significant association was observed among cases for rs377763 (p = 1.54*10-6) with ‘Sensorimotor functioning’ domain of the battery. Discussion: The present study, although reaffirms association of a few chromosome 6 markers to schizophrenia in this ethnically distinct North Indian population; was of far lower magnitude than p= 10-8 seen in initial GWAS findings.

Disclosure Disclosure Nothing to Disclose. Nothing to Disclose.

http://dx.doi.org/10.1016/j.euroneuro.2016.09.528

http://dx.doi.org/10.1016/j.euroneuro.2016.09.527

T40. REPLICATION STUDY OF GWAS AND OTHER STRONGLY ASSOCIATED MARKERS FROM CHROMOSOME 6 IN NORTH INDIAN POPULATION

Smita Deshpande1, Suman Prasad2, Prachi Semwal2, Triptish Bhatia1, Vishwajit Nimgaonkar3, BK Thelma4 1

PGIMER, Dr.R.M.L.Hospital Delhi University South Campus 3 University of Pittsburgh 4 Department of Genetics, University of Delhi South Campus 2

Background: Schizophrenia is a polygenic neuropsychiatric disorder wherein specific molecular or phenotypic markers have not been reported, with several promising findings but inconsistent replication. Nevertheless, different markers from chromosome 6, discussed repeatedly and reinforced by GWAS findings, remain the most promising leads. The present study was carried out to replicate the important GWAS findings (po or = 10-8) in a modestly sized case and control sample from a North Indian population Methods: Schizophrenia cases (n = 1035) and matched healthy controls (n = 1035) were recruited at PGIMER-Dr.R. M.L. hospital. Controls included age and gender matched psychiatrically healthy adults and cord blood samples. Using Sequenome platform, 26 markers were evaluated. In a subset of the samples (n=173 cases; n=87 controls), 8 different cognitive domains were evaluated using the UPenn Computerized Neuropsychological Battery, for the markers.

T41. DISSECTING RELIGIOUS DELUSIONS IN SCHIZOPHRENIA: THE INTERPLAY OF RELIGIOUS ACTIVITY AND POLYGENIC BURDEN

Heike Anderson-Schmidt1, Katrin Gade2, Dörthe Malzahn3, Sergi Papiol4, Monika Budde4, Janos Kalman4, Fanny Aldinger4, Kristina Adorjan4, Urs Heilbronner4, Laura Flatau5, Peter Falkai6, Franziska Degenhardt7, Andreas J. Forstner8, Thomas G. Schulze9 1

University Medical Centre Goettingen LMU Munich, Dep. of Psychiatry 3 Dept. of Genetic Epidemiology, University Medical Center, Georg-August-University Göttingen 4 Institute of Psychiatric Phenomics and Genomics (IPPG), Medical Center of the University of Munich, Germany 5 University of Munich 6 Molecular and Behavioral Neurobiology, Department of Psychiatry, Ludwig Maximillian University, Munich, Germany 7 Institute of Human Genetics, University of Bonn, Bonn, Germany; Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany 8 University of Bonn 9 Institute of Psychiatric Phenomics and Genomics, Ludwig-Maximilians-University Munich, Germany; Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Mannheim, Germany 2