Project description:The development of precision medicine strategies requires prior knowledge of the genetic background of the target population. However, despite the availability of data from admixed Americans within large reference population databases, we cannot use these data as a surrogate for that of the Brazilian population. This lack of transferability is mainly due to differences between ancestry proportions of Brazilian and other admixed American populations. To address the issue, a coalition of research centres created the Brazilian Initiative on Precision Medicine (BIPMed), an initiative of five Research Innovation and Dissemination Centers (RIDCs) supported by FAPESP.
Project description:Anorexia nervosa (AN), bulimia nervosa (BN), and obsessive-compulsive disorder (OCD) are complex psychiatric disorders with shared obsessive features, thought to arise from the interaction of multiple genes of small effect with environmental factors. Potential candidate genes for AN, BN, and OCD have been identified through clinical association and neuroimaging studies; however, recent genome-wide association studies of eating disorders (ED) so far have failed to report significant findings. Additionally, few if any studies have interrogated postmortem brain tissue for evidence of eQTLs associated with candidate genes, which has particular promise as an approach to elucidating molecular mechanisms of association. We therefore selected single nucleotide polymorphisms (SNPs) based on candidate gene studies for AN, BN, and OCD from the literature, and examined the association of these SNPs with gene expression across the lifespan in prefrontal cortex of a non-psychiatric control cohort (N=268). Several risk-predisposing SNPs were significantly associated with gene expression among control subjects. We then measured gene expression in the prefrontal cortex of cases previously diagnosed with obsessive psychiatric disorders, e.g., eating disorders (ED; N=15), and obsessive-compulsive disorder/obsessive-compulsive personality disorder or tics (OCD/OCPD/Tic; N=16), and non-psychiatric controls (N=102) and identified 6 and 286 genes that were differentially expressed between ED compared to controls and OCD cases compared to controls, respectively (FDR < 5%). However, none of the clinical risk SNPs were among the eQTLs and none were significantly associated with gene expression within the broad obsessive cohort, suggesting larger sample sizes or other brain regions may be required to identify candidate molecular mechanisms of clinical association in postmortem brain datasets. Gene expression data from the dorsolateral prefrontal cortex (DLPFC) from postmortem tissue on 133 subjects - 15 eating disorder (ED) patients, 16 obessive compulsive disorder (OCD) patients, and 102 non-psychiatric controls - run on the Illumina HumanHT-12 v3 microarray
Project description:Genome-wide association studies have been tremendously successful in identifying genetic variants associated with complex diseases. The majority of association signals are intergenic and evidence is accumulating that a high proportion of signals lie in enhancer regions.We use Capture Hi-C to investigate, for the first time, the interactions between associated variants for four autoimmune diseases and their functional targets in B- and T-cell lines. Here we report numerous looping interactions and provide evidence that only a minority of interactions are common to both B- and T-cell lines, suggesting interactions may be highly cell-type specific; some disease-associated SNPs do not interact with the nearest gene but with more compelling candidate genes (for example, FOXO1, AZI2) often situated several megabases away; and finally, regions associated with different autoimmune diseases interact with each other and the same promoter suggesting common autoimmune gene targets (for example, PTPRC, DEXI and ZFP36L1).
Project description:Anorexia nervosa (AN), bulimia nervosa (BN), and obsessive-compulsive disorder (OCD) are complex psychiatric disorders with shared obsessive features, thought to arise from the interaction of multiple genes of small effect with environmental factors. Potential candidate genes for AN, BN, and OCD have been identified through clinical association and neuroimaging studies; however, recent genome-wide association studies of eating disorders (ED) so far have failed to report significant findings. Additionally, few if any studies have interrogated postmortem brain tissue for evidence of eQTLs associated with candidate genes, which has particular promise as an approach to elucidating molecular mechanisms of association. We therefore selected single nucleotide polymorphisms (SNPs) based on candidate gene studies for AN, BN, and OCD from the literature, and examined the association of these SNPs with gene expression across the lifespan in prefrontal cortex of a non-psychiatric control cohort (N=268). Several risk-predisposing SNPs were significantly associated with gene expression among control subjects. We then measured gene expression in the prefrontal cortex of cases previously diagnosed with obsessive psychiatric disorders, e.g., eating disorders (ED; N=15), and obsessive-compulsive disorder/obsessive-compulsive personality disorder or tics (OCD/OCPD/Tic; N=16), and non-psychiatric controls (N=102) and identified 6 and 286 genes that were differentially expressed between ED compared to controls and OCD cases compared to controls, respectively (FDR < 5%). However, none of the clinical risk SNPs were among the eQTLs and none were significantly associated with gene expression within the broad obsessive cohort, suggesting larger sample sizes or other brain regions may be required to identify candidate molecular mechanisms of clinical association in postmortem brain datasets.
Project description:The identification of multiple signals at individual loci could explain additional phenotypic variance ('missing heritability') of common traits, and help identify causal genes. We examined gene expression levels as a model trait because of the large number of strong genetic effects acting in cis. Using expression profiles from 613 individuals, we performed genome-wide single nucleotide polymorphism (SNP) analyses to identify cis-expression quantitative trait loci (eQTLs), and conditional analysis to identify second signals. We examined patterns of association when accounting for multiple SNPs at a locus and when including additional SNPs from the 1000 Genomes Project. We identified 1298 cis-eQTLs at an approximate false discovery rate 0.01, of which 118 (9%) showed evidence of a second independent signal. For this subset of 118 traits, accounting for two signals resulted in an average 31% increase in phenotypic variance explained (Wilcoxon P< 0.0001). The association of SNPs with cis gene expression could increase, stay similar or decrease in significance when accounting for linkage disequilibrium with second signals at the same locus. Pairs of SNPs increasing in significance tended to have gene expression increasing alleles on opposite haplotypes, whereas pairs of SNPs decreasing in significance tended to have gene expression increasing alleles on the same haplotypes. Adding data from the 1000 Genomes Project showed that apparently independent signals could be potentially explained by a single association signal. Our results show that accounting for multiple variants at a locus will increase the variance explained in a substantial fraction of loci, but that allelic heterogeneity will be difficult to define without resequencing loci and functional work. Gene expression data was determined of peripheral blood samples (n=705) from InChianti cohort.
Project description:The identification of multiple signals at individual loci could explain additional phenotypic variance ('missing heritability') of common traits, and help identify causal genes. We examined gene expression levels as a model trait because of the large number of strong genetic effects acting in cis. Using expression profiles from 613 individuals, we performed genome-wide single nucleotide polymorphism (SNP) analyses to identify cis-expression quantitative trait loci (eQTLs), and conditional analysis to identify second signals. We examined patterns of association when accounting for multiple SNPs at a locus and when including additional SNPs from the 1000 Genomes Project. We identified 1298 cis-eQTLs at an approximate false discovery rate 0.01, of which 118 (9%) showed evidence of a second independent signal. For this subset of 118 traits, accounting for two signals resulted in an average 31% increase in phenotypic variance explained (Wilcoxon P< 0.0001). The association of SNPs with cis gene expression could increase, stay similar or decrease in significance when accounting for linkage disequilibrium with second signals at the same locus. Pairs of SNPs increasing in significance tended to have gene expression increasing alleles on opposite haplotypes, whereas pairs of SNPs decreasing in significance tended to have gene expression increasing alleles on the same haplotypes. Adding data from the 1000 Genomes Project showed that apparently independent signals could be potentially explained by a single association signal. Our results show that accounting for multiple variants at a locus will increase the variance explained in a substantial fraction of loci, but that allelic heterogeneity will be difficult to define without resequencing loci and functional work.