S94. MUTATION-INTOLERANT GENES AND MONOGENIC DISEASE GENES IN 145 LOCI OF SCHIZOPHRENIA (SCZ) GWAS ARE LINKED TO THE ISCHEMIA-HYPOXIA RESPONSE. (9th April 2019) - Schmidt-Kastner, Rainald; Guloksuz, Sinan; Kietzmann, Thomas; Os, Jim van; Rutten, Bart P F
Abstract: Background: We previously hypothesized that candidate genes for schizophrenia (SCZ) respond to ischemia-hypoxia as part of obstetric complications. Hypoxia may alter gene expression levels depending on genetic variants which in turn affect neurodevelopment (Schmidt-Kastner et al., 2012). The challenge is to examine a putative role for ischemia-hypoxia response (IHR) genes in genome-wide studies. It was recently reported that common SCZ alleles in GWAS are enriched for mutation-intolerant genes (Pardinas et al., 2018). If IHR genes are essential for protecting against ischemic-hypoxic challenges, they should be enriched in datasets of mutation-intolerant genes. Accordingly, we tested for an overlap between SCZ genes from GWAS, mutation-intolerant genes, and IHR genes. In addition, we annotated the SCZ genes from GWAS for known monogenic disorders of the nervous system. Methods: We analyzed n=458 genes from 145 loci of the recent GWAS dataset in SCZ (Pardinas et al., 2018). The database of Loss-of-function (LoF; Lek et al., 2016) was used to define mutation-intolerant genes (n=3, 230). Annotation for monogenic disorders of the nervous system was based on OMIM™, DDD-database, DisGeNET and abstract searches, including neurodevelopmental disorders (intellectual disability), neurological diseases, and disorders of the eye and ear. IHR genes (n=1, 629) were defined experimentally by changes in brain mRNA expression (Schmidt-Kastner, 2015). HypoxiaDB (HDB, n=2, 289), a database related to proteomic findings for hypoxia across various organs (Khurana et al., 2013) was used as second source. Additional genes involved in the hypoxia response were compiled from information available for HIF-targets and HIF-regulators in multiple databases and the literature. Statistical analysis used chi-square tests (p<0.017). Results: When the LoF database was compared with the IHR gene database, enrichment was found (n=452; chi-square p=0.0001). HDB showed also significant enrichment for LoF (n=634, p=0.0002). The SCZ GWAS dataset was enriched with N=112 LoF genes (p=0.0001). N=51 IHR genes were in the SCZ GWAS dataset, whereby n=25 IHR genes were among the n=112 LoF, indicating enrichment (p=0.0002). N=48 HDB genes were in the SCZ GWAS dataset, with n=23 overlapping LoF (p=0.0005). For the selection of HIF1-related genes in the SCZ GWAS dataset (n=37), n=16 overlapped with LoF (p=0.012). In addition, n=96 genes of the SCZ GWAS dataset (21%) could be linked to a monogenic disorder of the nervous system whereby IHR genes were enriched (n=19, p=0.008). Discussion: Mutation-intolerant genes (LoF) were overrepresented among IHR genes, suggesting an essential role of the ischemia-hypoxia response. Genes from SCZ GWAS were enriched for mutation-intolerant genes (Pardinas et al., 2018) which in turn were strongly enriched for IHR genes. A second database (HypoxiaDB) supported enrichment in LoFs in general and SCZ in specific which was independent of brain expression. An additional analysis showed that one fifth of genes from SCZ GWAS relate to monogenic disorders of the nervous system which were also enriched for IHR genes; this suggests an interaction in the brain itself. Variants of SCZ genes interacting with ischemia-hypoxia (e.g. during obstetric complications) may affect the same biological processes as potential or known mutations, providing a specific starting point for functional and experimental studies.