S944 former phenotypes having largely overlapping genetic architecture. Methods: LD-Score Regression (LDSC) was conducted to examine the relationship between schizophrenia (PGC2SczWGp, 2014, Nature, PMID: 25056061), and subsets of SNPs derived from GWAS for education (Okbay et al., 2016, Nature, PMID: 27225129) and cognition. GWAS summary statistics from Sniekers et al., 2017 (Nature Genetics, PMID: 28530673) and independent cohorts reported in Trampush et al., 2017 (Molecular Psychiatry, PMID: 28093568) were meta-analyzed resulting N = 107,207 individuals for cognition. SNPs related to either education or cognition, but were completely unrelated to the other phenotype were identified. Thus, SNPs nominally significantly (po.05) associated with education, but demonstrated no association to cognition (p4.50) were selected; there were 294,319 such SNPs. We also examined 386,664 SNPs nominally associated with cognition (po.05) but unrelated to education (p4.50). Follow-up pathway analysis was conducted to identify potential biological pathways underlying each set of markers. Results: We confirmed significant inverse genetic correlations between cognition and schizophrenia (rg= -.192, p= 2.85e-10) and positive correlations between education and schizophrenia (rg =.097, p= 3.91e-5). LDSC results for filtered markers demonstrated that the counter-intuitive positive correlation between education and schizophrenia was entirely driven by SNPs unrelated to cognition (rg[scz] = .55, p = 1.06e-7). Much of the inverse correlation between cognition and schizophrenia was accounted for by the cognition-specific SNPs (rg[scz] = -.11, p = 4.65e-2). By contrast, SNPs nominally significant (po.05) in both the education and cognition GWAS were unrelated to schizophrenia (rg[scz] = -.039, p= .73). The top enriched pathways for SNPs specific to cognition appeared to be ion transport and ion channel regulation, while those for education pointed to cell adhesion and neuronal developmental pathways. Discussion: While the genetic architecture between cognition and education is largely concordant; the discordant association with schizophrenia reveals a critical set of SNPs and pathways that differentiate the two. In schizophrenia, ion transport and ion channel regulation related pathways appear dysregulated, explaining the strong negative genetic correlations with cognition. However, it was a subset of pathways related to cell adhesion and neuronal development underlying education genetic architecture that appears to drive the counter-intuitive positive genetic correlation with schizophrenia. These findings suggest that a subset of the neurodevelopmental anomalies implicated in schizophrenia may be associated with educational success in the general population, perhaps providing a mechanism of balancing selection for these seemingly deleterious alleles.
Abstracts SU102. GENOME-WIDE ASSOCIATION OF TARDIVE DYSKINESIA n
Keane Lim ,1, Max Lam1, Jianjun Liu2, Jimmy Lee1 1 2
Institute of Mental Health Genome Institute of Singapore
Background: Tardive Dyskinesia (TD) is a persistent and potentially irreversible condition associated with long term exposure to antipsychotics. Commonly observed in schizophrenia, TD is a movement disorder characterised by involuntary movements of orofacial muscles, trunk and limbs. TD appears to represent a genetically complex phenotype, with candidate gene and genome-wide studies identifying a collection of genes. The pathophysiology of TD is still unclear and the genetic factors predisposing TD across ancestries remain relatively unexplored. Here, we performed a GWAS of TD in a sample of East Asians, European and African-American ancestries. Methods: Two available datasets were used: 780 schizophrenia patients of Chinese ethnicity from Singapore and 626 schizophrenia patients of European and African ancestry from the CATIE cohort. Dyskinesia was rated on the Abnormal Involuntary Movement Scale (AIMS) and TD case ascertainment followed the Schooler and Kane criteria. Standard GWAS QC procedures were carried out. Imputation was carried out on the Sanger imputation server; markers were phased via SHAPEIT and imputed via Minimac3 (MACH) to the 1000 Genomes Project Phase 3 reference panel (GRch37). To address complex ancestry effects, linear mixed model association was carried out via GEMMA. Fixed-effects meta-analysis was conducted via GWAMA. Results: Meta-analysis revealed one locus on chr16 (rs11639774), which met the GWAS significant threshold (Z= 5.551, p= 3.09e-8). Three other loci of interests were at subthreshold significance; these were found on chromosomes 1 (rs499646, p= 8.48e-8), 6 (rs6926250, p= 2.59e-7) and 12 (rs4237808, p= 1.1e-7) respectively. Further investigation revealed that these four loci harboured i) downstream gene variant (rs11639774) ii) intronic variants (rs499646, rs6926250) and iii) intergenic variant (rs4237808). Though MAGMA gene-set analysis did not reveal significant gene-based results, one of the top gene-sets appeared to implicate immunoglobulin production. Further gene prioritization of the top 200 associated genes revealed unique brain expression profiles. Notably, several pathways emerged that point to DNA damage and immune responses. Discussion: Here we report the largest TD GWAS study to date and evidence for a significant GWAS locus for TD and three other candidate loci of interest. This suggests an inherent vulnerability to TD, which might be brought about by long term antipsychotic exposure. Of interest, the role of immune system in the aetiopathogenesis of TD warrants further research. Disclosure: Nothing to disclose.
Disclosure: Nothing to disclose. http://dx.doi.org/10.1016/j.euroneuro.2017.08.291 http://dx.doi.org/10.1016/j.euroneuro.2017.08.290