Genome-wide associate study identifies five new schizophrenia loci

We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yielded genome-wide significant associations with schizophrenia for seven loci, five of which are new (1p21.3, 2q32.3, 8p23.2, 8q21.3 and 10q24.32-q24.33) and two of which have been previously implicated (6p21.32-p22.1 and 18q21.2). The strongest new finding (P = 1.6 x 10(-11)) was with rs1625579 within an intron of a putative primary transcript for MIR137 (microRNA 137), a known regulator of neuronal development. Four other schizophrenia loci achieving genome-wide significance contain predicted targets of MIR137, suggesting MIR137-mediated dysregulation as a previously unknown etiologic mechanism in schizophrenia. In a joint analysis with a bipolar disorder sample (16,374 affected individuals and 14,044 controls), three loci reached genome-wide significance: CACNA1C (rs4765905, P = 7.0 x 10(-9)), ANK3 (rs10994359, P = 2.5 x 10(-8)) and the ITIH3-ITIH4 region (rs2239547, P = 7.8 x 10(-9))

Genome-wide association study identifies five new schizophrenia loci

We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yielded genome-wide significant associations with schizophrenia for seven loci, five of which are new (1p21.3, 2q32.3, 8p23.2, 8q21.3 and 10q24.32-q24.33) and two of which have been previously implicated (6p21.32-p22.1 and 18q21.2). The strongest new finding (P = 1.6 × 10−11) was with rs1625579 within an intron of a putative primary transcript for MIR137 (microRNA 137), a known regulator of neuronal development. Four other schizophrenia loci achieving genome-wide significance contain predicted targets of MIR137, suggesting MIR137-mediated dysregulation as a previously unknown etiologic mechanism in schizophrenia. In a joint analysis with a bipolar disorder sample (16,374 affected individuals and 14,044 controls), three loci reached genome-wide significance: CACNA1C (rs4765905, P = 7.0 × 10−9), ANK3 (rs10994359, P = 2.5 × 10−8) and the ITIH3-ITIH4 region (rs2239547, P = 7.8 × 10−9)

Common variants in FOXP1 are associated with generalized vitiligo

In a recent genome-wide association study of generalized vitiligo, we identified ten confirmed susceptibility loci. By testing additional loci that showed suggestive association in the genome-wide study, using two replication cohorts of European descent, we observed replicated association of generalized vitiligo with variants at 3p13 encompassing FOXP1 (rs17008723, combined P = 1.04 × 10−8) and with variants at 6q27 encompassing CCR6 (rs6902119, combined P = 3.94 × 10−7)

Rare coding SNP in DZIP1 gene associated with late-onset sporadic Parkinson's disease

We present the first application of the hypothesis-rich mathematical theory to genome-wide association data. The Hamza et al. late-onset sporadic Parkinson's disease genome-wide association study dataset was analyzed. We found a rare, coding, non-synonymous SNP variant in the gene DZIP1 that confers increased susceptibility to Parkinson's disease. The association of DZIP1 with Parkinson's disease is consistent with a Parkinson's disease stem-cell ageing theory.Comment: 14 page

Genome-wide gene-based association study

Genome-wide association studies, which analyzes hundreds of thousands of single-nucleotide polymorphisms to identify disease susceptibility genes, are challenging because the work involves intensive computation and complex modeling. We propose a two-stage genome-wide association scanning procedure, consisting of a single-locus association scan for the first stage and a gene-based association scan for the second stage. Marginal effects of single-nucleotide polymorphisms are examined by using the exact Armitage trend test or logistic regression, and gene effects are examined by using a p-value combination method. Compared with some existing single-locus and multilocus methods, the proposed method has the following merits: 1) convenient for definition of biologically meaningful regions, 2) powerful for detection of minor-effect genes, 3) helpful for alleviation of a multiple-testing problem, and 4) convenient for result interpretation. The method was applied to study Genetic Analysis Workshop 16 Problem 1 rheumatoid arthritis data, and strong association signals were found. The results show that the human major histocompatibility complex region is the most important genomic region associated with rheumatoid arthritis. Moreover, previously reported genes including PTPN22, C5, and IL2RB were confirmed; novel genes including HLA-DRA, BTNL2, C6orf10, NOTCH4, TAP2, and TNXB were identified by our analysis

Using Ontology Fingerprints to evaluate genome-wide association study results

We describe an approach to characterize genes or phenotypes via ontology fingerprints which are composed of Gene Ontology (GO) terms overrepresented among those PubMed abstracts linked to the genes or phenotypes. We then quantify the biological relevance between genes and phenotypes by comparing their ontology fingerprints to calculate a similarity score. We validated this approach by correctly identifying genes belong to their biological pathways with high accuracy, and applied this approach to evaluate GWA study by ranking genes associated with the lipid concentrations in plasma as well as to prioritize genes within linkage disequilibrium (LD) block. We found that the genes with highest scores were: ABCA1, LPL, and CETP for HDL; LDLR, APOE and APOB for LDL; and LPL, APOA1 and APOB for triglyceride. In addition, we identified some top ranked genes linking to lipid metabolism from the literature even in cases where such knowledge was not reflected in current annotation of these genes. These results demonstrate that ontology fingerprints can be used effectively to prioritize genes from GWA studies for experimental validation

Meta-Analysis of Genome-Wide Linkage Studies in Celiac Disease.

OBJECTIVE: A meta-analysis of genome-wide linkage studies allows us to summarize the extensive information available from family-based studies, as the field moves into genome-wide association studies. METHODS: Here we apply the genome scan meta-analysis (GSMA) method, a rank-based, model-free approach, to combine results across eight independent genome-wide linkages performed on celiac disease (CD), including 554 families with over 1,500 affected individuals. We also investigate the agreement between signals we identified from this meta-analysis of linkage studies and those identified from genome-wide association analysis using a hypergeometric distribution. RESULTS: Not surprisingly, the most significant result was obtained in the HLA region. Outside the HLA region, suggestive evidence for linkage was obtained at the telomeric region of chromosome 10 (10q26.12-qter; p = 0.00366), and on chromosome 8 (8q22.2-q24.21; p = 0.00491). Testing signals of association and linkage within bins showed no significant evidence for co-localization of results. CONCLUSION: This meta-analysis allowed us to pool the results from available genome-wide linkage studies and to identify novel regions potentially harboring predisposing genetic variation contributing to CD. This study also shows that linkage and association studies may identify different types of disease-predisposing variants