Publications

9 Publications visible to you, out of a total of 9

Abstract (Expand)

Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes.

Authors: H. Kirsten, H. Al-Hasani, L. Holdt, A. Gross, F. Beutner, K. Krohn, K. Horn, P. Ahnert, R. Burkhardt, K. Reiche, J. Hackermuller, M. Loffler, D. Teupser, J. Thiery, M. Scholz

Date Published: 15th Aug 2015

Publication Type: Journal article

Abstract (Expand)

The Manchester scoring system (MSS) allows the calculation of the probability for the presence of mutations in BRCA1 or BRCA2 genes in families suspected of having hereditary breast and ovarian cancer. In 9,390 families, we determined the predictive performance of the MSS without (MSS-2004) and with (MSS-2009) consideration of pathology parameters. Moreover, we validated a recalibrated version of the MSS-2009 (MSS-recal). Families were included in the registry of the German Consortium for Hereditary Breast and Ovarian Cancer, using defined clinical criteria. Receiver operating characteristics (ROC) analysis was used to determine the predictive performance. The recalibrated model was developed using logistic regression analysis and tested using an independent random validation sample. The area under the ROC curves regarding a mutation in any of the two BRCA genes was 0.77 (95%CI 0.75-0.79) for MSS-2004, 0.80 (95%CI 0.78-0.82) for MSS-2009, and 0.82 (95%CI 0.80-0.83) for MSS-recal. Sensitivity at the 10% mutation probability cutoff was similar for all three models (MSS-2004 92.2%, MSS-2009 92.2%, and MSS-recal 90.3%), but specificity of MSS-recal (46.0%) was considerably higher than that of MSS-2004 (25.4%) and MSS-2009 (32.3%). In the MSS-recal model, almost all predictors of the original MSS were significantly predictive. However, the score values of some predictors, for example, high grade triple negative breast cancers, differed considerably from the originally proposed score values. The original MSS performed well in our sample of high risk families. The use of pathological parameters increased the predictive performance significantly. Recalibration improved the specificity considerably without losing much sensitivity.

Authors: K. Kast, R. K. Schmutzler, K. Rhiem, M. Kiechle, C. Fischer, D. Niederacher, N. Arnold, T. Grimm, D. Speiser, B. Schlegelberger, D. Varga, J. Horvath, M. Beer, S. Briest, A. Meindl, C. Engel

Date Published: 15th Nov 2014

Publication Type: Not specified

Human Diseases: breast cancer, ovarian cancer

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