A Genetic Association Study of Chromosome 11q22-24 in Two Different Samples Implicates the FXYD6 Gene, Encoding Phosphohippolin, in Susceptibility to Schizophrenia

Previous linkage analyses of families with multiple cases of schizophrenia by us and others have confirmed the involvement of the chromosome 11q22-24 region in the etiology of schizophrenia, with LOD scores of 3.4 and 3.1. We now report fine mapping of a susceptibility gene in the 11q22-24 region, determined on the basis of a University College London (UCL) sample of 496 cases and 488 supernormal controls. Confirmation was then performed by the study of an Aberdeen sample consisting of 858 cases and 591 controls (for a total of 2,433 individuals: 1,354 with schizophrenia and 1,079 controls). Seven microsatellite or single-nucleotide polymorphism (SNP) markers localized within or near the FXYD6 gene showed empirically significant allelic associations with schizophrenia in the UCL sample (for D11S1998, P=.021; for rs3168238, P=.009; for TTTC20.2, P=.048; for rs1815774, P=.049; for rs4938445, P=.010; for rs4938446, P=.025; for rs497768, P=.023). Several haplotypes were also found to be associated with schizophrenia; for example, haplotype Hap-F21 comprising markers rs10790212-rs4938445-rs497768 was found to be associated with schizophrenia, by a global permutation test (P=.002). Positive markers in the UCL sample were then genotyped in the Aberdeen sample. Two of these SNPs were found to be associated with schizophrenia in the Scottish sample (for rs4938445, P=.044; for rs497768, P=.037). The Hap-F21 haplotype also showed significant association with schizophrenia in the Aberdeen sample, with the same alleles being associated (P=.013). The FXYD6 gene encodes a protein called “phosphohippolin” that is highly expressed in regions of the brain thought to be involved in schizophrenia. The protein functions by modulating the kinetic properties of Na,K-ATPase to the specific physiological requirements of the tissue. Etiological base-pair changes in FXYD6 or in associated promoter/control regions are likely to cause abnormal function or expression of phosphohippolin and to increase genetic susceptibility to schizophrenia

New data and an old puzzle: the negative association between schizophrenia and rheumatoid arthritis

BackgroundA long-standing epidemiological puzzle is the reduced rate of rheumatoid arthritis (RA) in those with schizophrenia (SZ) and vice versa. Traditional epidemiological approaches to determine if this negative association is underpinned by genetic factors would test for reduced rates of one disorder in relatives of the other, but sufficiently powered data sets are difficult to achieve. The genomics era presents an alternative paradigm for investigating the genetic relationship between two uncommon disorders.MethodsWe use genome-wide common single nucleotide polymorphism (SNP) data from independently collected SZ and RA case-control cohorts to estimate the SNP correlation between the disorders. We test a genotype X environment (GxE) hypothesis for SZ with environment defined as winter- vs summer-born.ResultsWe estimate a small but significant negative SNP-genetic correlation between SZ and RA (-0.046, s.e. 0.026, P = 0.036). The negative correlation was stronger for the SNP set attributed to coding or regulatory regions (-0.174, s.e. 0.071, P = 0.0075). Our analyses led us to hypothesize a gene-environment interaction for SZ in the form of immune challenge. We used month of birth as a proxy for environmental immune challenge and estimated the genetic correlation between winter-born and non-winter born SZ to be significantly less than 1 for coding/regulatory region SNPs (0.56, s.e. 0.14, P = 0.00090).ConclusionsOur results are consistent with epidemiological observations of a negative relationship between SZ and RA reflecting, at least in part, genetic factors. Results of the month of birth analysis are consistent with pleiotropic effects of genetic variants dependent on environmental context

Identifying relationships among genomic disease regions: predicting= pathogenic SNP associations and rare deletions

Translating a set of disease regions into insight about pathogenic mechanisms requires not only the ability to identify the key disease genes within them, but also the biological relationships among those key genes. Here we describe a statistical method, Gene Relationships Among Implicated Loci (GRAIL), that takes a list of disease regions and automatically assesses the degree of relatedness of implicated genes using 250,000 PubMed abstracts. We first evaluated GRAIL by assessing its ability to identify subsets of highly related genes in common pathways from validated lipid and height SNP associations from recent genome-wide studies. We then tested GRAIL, by assessing its ability to separate true disease regions from many false positive disease regions in two separate practical applications in human genetics. First, we took 74 nominally associated Crohn's disease SNPs and applied GRAIL to identify a subset of 13 SNPs with highly related genes. Of these, ten convincingly validated in follow-up genotyping; genotyping results for the remaining three were inconclusive. Next, we applied GRAIL to 165 rare deletion events seen in schizophrenia cases (less than one-third of which are contributing to disease risk). We demonstrate that GRAIL is able to identify a subset of 16 deletions containing highly related genes; many of these genes are expressed in the central nervous system and play a role in neuronal synapses. GRAIL offers a statistically robust approach to identifying functionally related genes from across multiple disease regions—that likely represent key disease pathways. An online version of this method is available for public use (http://www.broad.mit.edu/mpg/grail/)

Common polygenic variation contributes to risk of schizophrenia and bipolar disorder

Schizophrenia is a severe mental disorder with a lifetime risk of about 1%, characterized by hallucinations, delusions and cognitive deficits, with heritability estimated at up to 80%1, 2. We performed a genome-wide association study of 3,322 European individuals with schizophrenia and 3,587 controls. Here we show, using two analytic approaches, the extent to which common genetic variation underlies the risk of schizophrenia. First, we implicate the major histocompatibility complex. Second, we provide molecular genetic evidence for a substantial polygenic component to the risk of schizophrenia involving thousands of common alleles of very small effect. We show that this component also contributes to the risk of bipolar disorder, but not to several non-psychiatric diseases