Project description:Via a GWA study, several SNPs have been identified as markers capable of predicting prognosis of lung cancer patients receiving TKIs therapy as first-line treatment. In order to get insights into how these genetic variants are linked to traits of interest, we conducted a genome-wide eQTL study by integrated analyses of SNP genotyping array data and gene expression array data of 115 subjects of lung adenocarcinoma. Our study successfully identified several SNPs as eQTLs, whose genotype were significantly associated with expression levels of several already known genes related to lung cancer.
Project description:Genome-wide association studies (GWAS) have boosted our knowledge of genetic risk variants in autoimmune diseases (AIDs). Most of the risk variants are located within or near genes with immunological functions, and the majority is found to be non-coding, pointing towards a regulatory role. We have performed a cis expression quantitative trait locus (eQTL) screen to investigate whether single nucleotide polymorphisms (SNPs) associated with AIDs influence gene expression in thymus. Genotyping was performed using the Immunochip and 353 AID associated SNPs were tested against expression of surrounding genes (+/- 1 Mb) from human thymic tissue (N=42). We identified eight genes where the expression was associated with AID risk SNPs at a study-wide level of significance (P < 2.57x10-5). Five genes (FCRL3, RNASET2, C2orf74, SIRPG and SYS1) displayed cis eQTL signals also in other tissues, while for two loci (NPIPB8 and LOC388814), the eQTL signal appear to be thymus-specific. Since many AID risk variants from GWAS have been subsequently fine-mapped in recent Immunochip projects, we explored the overlap between these novel AID risk variants and the thymic eQTL regions. Moreover, we examined the functional annotation of the seven expression altering SNPs (eSNPs). Our study reveals autoimmune risk variants that act as eQTLs in thymus. We have highlighted functional variants within these genetic regions that potentially can represent causal autoimmune risk variants. Total RNA from 42 human thymic samples were obtained from children undergoing cardiac surgery.
Project description:This experiment was carried out in the context of a pharmacogenetic study of long-term (4-year follow-up) response to Interferon-beta treatment in two cohorts of Italian Multiple Sclerosis patients, to identify genetic variants (SNPs) that may influence response to IFN-beta. We integrated results from meta-analysis of the two cohorts with gene expression profiling of IFNβ stimulated PBMCs from 20 healthy controls and eQTL analyses, to look at possible enrichment of IFN-beta induced genes with genes mapped by top-ranking meta-analyzed SNPs.
Project description:Genome-wide association study (GWAS) was performed in 120 patient-parents trio samples from Japanese schizophrenia pedigrees ABSTRACT: Schizophrenia is a devastating neuropsychiatric disorder with genetically complex traits. Genetic variants should explain a considerable portion of the risk for schizophrenia, and genome-wide association study (GWAS) is a potentially powerful tool for identifying the risk variants that underlie the disease. Here, we report the results of a three-stage analysis of three independent cohorts consisting of a total of 2,535 samples from Japanese and Chinese populations for searching schizophrenia susceptibility genes using a GWAS approach. Firstly, we examined 115,770 single nucleotide polymorphisms (SNPs) in 120 patient-parents trio samples from Japanese schizophrenia pedigrees. In stage II, we evaluated 1,632 SNPs (1,159 SNPs of p < 0.01 and 473 SNPs of p < 0.05 that located in previously reported linkage regions). The second sample consisted of 1,012 case-control samples of Japanese origin. The most significant p value was obtained for the SNP in the ELAVL2 [(embryonic lethal, abnormal vision, Drosophila)-like 2] gene located on 9p21.3 (p = 0.00087). In stage III, we scrutinized the ELAVL2 gene by genotyping gene-centric tagSNPs in the third sample set of 293 family samples (1,163 individuals) of Chinese descent and the SNP in the gene showed a nominal association with schizophrenia in Chinese population (p = 0.026). The current data in Asian population would be helpful for deciphering ethnic diversity of schizophrenia etiology.
Project description:Background: Expression quantitative trait loci (eQTL) studies are a valuable approach for identifying genetic variants correlated with gene expression. However, identifying the causal variants is challenging due to linkage disequilibrium amongst variants in the same haplotype block. In this study, we aim to identify functional SNPs in key regulatory regions that alter transcriptional regulation and thus, potentially impact cellular function. The majority of disease-associated single-nucleotide polymorphisms (SNPs) are located in regulatory regions, which can result in allele-specific binding (ASB) of transcription factors and differential expression of the target gene alleles. Here, we present regSNPs-ASB, a generalized linear model-based approach to accurately identify regulatory SNPs that are located in transcription factor binding sites from ATAC-seq data. Results: Using regSNPs-ASB, we identified 53 regulatory SNPs in human MCF-7 breast cancer cells and 125 regulatory SNPs in human mesenchymal stem cells (MSC). By integrating the regSNPs-ASB output with RNA-seq experimental data and publicly available chromatin interaction data from MCF-7 cells, we found that these 53 regulatory SNPs were associated with 74 potential target genes and that 32 (43%) of these genes showed significant allele-specific expression (ASE). By comparing all of the MCF-7 and MSC regulatory SNPs to the eQTLs in the Genome-Tissue Expression (GTEx) Project database, we found that 30% (16/53) of the regulatory SNPs in MCF-7 and 43% (52/122) of the regulatory SNPs in MSC were also eQTLs. The enrichment of regulatory SNPs in eQTLs indicated that many of them are likely responsible for allelic differences in gene expression (chi-square test, p-value < 0.01). In sum, we conclude that regSNPs-ASB is a useful tool for identifying causal variants from ATAC-seq data. This new computational tool will enable efficient prioritization of genetic variants identified as eQTL for further studies to validate their causal regulatory function. Ultimately, identifying causal genetic variants will further our understanding of the underlying molecular mechanisms of disease and the eventual development of potential therapeutic targets.
Project description:Genome-wide association studies (GWAS) have highlighted a large number of genetic variants with potential disease association, but functional analysis and validation remains a challenge. Here we describe an approach to functionally validate these variants through the differentiation of induced pluripotent stem cells (iPSCs) to study cellular pathophysiology. We collected peripheral blood cells from Framingham Heart Study participants and reprogrammed them to iPSCs. We then differentiated 68 iPSC lines into hepatocytes and adipocytes to investigate the effect of the 1p13 rs12740374 variant on cardiometabolic disease phenotypes via transcriptomics and metabolomic signatures. We observed a clear association between rs12740374 and lipid accumulation and gene expression changes in differentiated hepatocytes, in particular expression of SORT1, CELSR2 and PSRC1, consistent with previous analysis of this variant using other approaches. Initial investigation of additional SNPs also highlighted correlations with gene expression. Thus, iPSC-based population studies seem promising for further development as a tool for the functional validation of GWAS variants.
Project description:Background: Current reports suggest that a certain minimum plasma concentration of (Z)-endoxifen is required for breast cancer patient to benefit from tamoxifen therapy. A reliable prediction of which patients are at risk for insufficient exposure to (Z)-endoxifen would be relevant for optimizing treatment, e.g. by adjusting the dose, from the very beginning. The objective of this study was to search for new DNA variants that could be helpful in the preemptive prediction of impaired tamoxifen to endoxifen metabolism. Methods: The molecular ratio (MR) was defined as (Z)-endoxifen plasma concentration divided by the sum of concentrations of tamoxifen and other measured metabolites. The MR of 0.0146, previously delineated as corresponding to (Z)-endoxifen 6 ng/ml efficacy threshold level, was adopted as a cut-off value in a genome-wide association study (GWAS) comprising 287 breast cancer patients receiving tamoxifen 20 mg daily. Multivariate binary logistic regression was used for the pre-selection of variables that showed independent impact on MR and to develop models predictive for MR value below the threshold. Results: In total, 13 GWAS-selected single nucleotide polymorphisms (SNPs) located outside the CYP2D6 gene and two known CYP2D6 variants were significantly associated with the MR value below 0.0146. The strongest association was observed for rs8138080 in WBP2NL (p = 1.78 x 10-15). The minor allele of six SNPs was associated with a decreased risk of impaired tamoxifen metabolism. CYP2D6 genotype was found by Nagelkerke pseudo-R2 to explain 42.7% of a total variation observed in MR, while rs8138080 alone explained 33.7% of this variability. Two alternative models for MR prediction have been developed. The prediction accuracy of Model 1, including rs7245, rs6950784 and rs1320308 in addition to CYP2D6 genotype, was considerably higher than predictive performance of CYP2D6 genotype alone (AUC increase from 0.758 to 0.879). The AUC of 0.830 achieved for the Model 2, developed with the same three SNPs as in Model 1 and rs8138080 instead of CYP2D6 genotype, makes it an interesting, simplified alternative to the costly and time-consuming testing of full CYP2D6 genotype. Conclusions: The four novel SNPs, tested alone or in addition to CYP2D6 genotype, improved the prediction of impaired tamoxifen to endoxifen metabolism, allowing for adjustments in dosing regimen before the treatment begins.
Project description:We adapted the self-transcribing active regulatory region sequencing (Starr-seq) strategy to systematically identify the SNPs that affect gene expression by modulating activities of regulatory elements. Among 10,673 SNPs linked with 996 GWAS-identified cancer-risk SNPs, we found 70 regulatory variants for which the two alleles conferred different regulatory activities. We analyzed one of them in-depth and confirmed its target by CRIPSR-Cas9 technology. Our results will help the interpretation of GWAS results and better cancer risk assessment.
Project description:Precise identification of causal variants within credible intervals of eQTL associations is needed to identify regulatory GWAS variants. We show that CROPseq, namely multiplex CRISPR-Cas9 genome editing combined with single cell RNAseq, is a viable strategy for fine mapping regulatory SNPs. Mutations were induced nearby 67 SNPs in three genes, two of which, rs2251039 and rs17523802, significantly altered CISD1 and PARK7 expression, respectively, and overlap with chromatin accessibility peaks.
Project description:The common genetic variants associated with complex traits typically lie in non-coding DNA and may alter gene regulation in a cell-type specific manner. Consequently, the choice of tissue or cell model in the dissection of disease associations is important. We carried out an eQTL study of primary human osteoblasts (HOb) derived from unrelated donors of Swedish origin, each represented by two independently derived primary lines to provide biological replication. We combined our data with publicly available information from a genome-wide association study (GWAS) of bone mineral density (BMD). The top BMD-associated SNPs were tested for cis-association of gene expression in HObs and in lymphoblastoid cell lines (LCLs) using publicly available data and showed that HObs have a significantly greater enrichment of converging cis-eQTLs as compared to LCLs. The top BMD loci with SNPs showing strong cis-effects on gene expression in HObs were selected for further validation using a staged design in two cohorts of Caucasian male subjects. All variants were tested in the Swedish MrOs Cohort (n=3014), providing evidence for two novel BMD loci. These variants were then tested in the Rotterdam Study (n=2100), yielding converging evidence for BMD association at one locus. The cis-regulatory effect was further fine-mapped to the proximal promoter of the gene. Our results suggest that primary cells relevant to disease phenotypes complement traditional approaches for prioritization and validation of GWAS hits for follow-up studies.