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Establishing a valid approach for estimating familial risk of cancer explained by common genetic variants.

ABSTRACT: We critically examined existing approaches for the estimation of the excess familial risk of cancer that can be attributed to identified common genetic risk variants and propose an alternative, more straightforward approach for calculating this proportion using well-established epidemiological methodology. We applied the underlying equations of the traditional approaches and the new epidemiological approach for colorectal cancer (CRC) in a large population-based case-control study in Germany with 4,447 cases and 3,480 controls, who were recruited from 2003 to 2016 and for whom interview, medical and genomic data were available. Having a family history of CRC (FH) was associated with a 1.77-fold risk increase in our study population (95% CI 1.52-2.07). Traditional approaches yielded estimates of the FH-associated risk explained by 97 common genetics variants from 9.6% to 23.1%, depending on various assumptions. Our alternative approach resulted in smaller and more consistent estimates of this proportion, ranging from 5.4% to 14.3%. Commonly employed methods may lead to strongly divergent and possibly exaggerated estimates of excess familial risk of cancer explained by associated known common genetic variants. Our results suggest that familial risk and risk associated with known common genetic variants might reflect two complementary major sources of risk.

SUBMITTER: Weigl K

PROVIDER: S-EPMC7121903 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Establishing a valid approach for estimating familial risk of cancer explained by common genetic variants.

Weigl Korbinian K Chang-Claude Jenny J Hsu Li L Hoffmeister Michael M Brenner Hermann H

International journal of cancer 20191016 1

We critically examined existing approaches for the estimation of the excess familial risk of cancer that can be attributed to identified common genetic risk variants and propose an alternative, more straightforward approach for calculating this proportion using well-established epidemiological methodology. We applied the underlying equations of the traditional approaches and the new epidemiological approach for colorectal cancer (CRC) in a large population-based case-control study in Germany wit ...[more]

PMID: 31483856

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Project description:Rationale: To identify functionally relevant common genetic risk variants associated with idiopathic pulmonary fibrosis (IPF), we performed expression quantitative trait loci (eQTL) and methylation quantitative trait loci (mQTL) mapping, followed by co-localization of eQTL and mQTL with genetic association signals as well as mediation analysis. Methods: Illumina MEGA genotyping arrays, mRNA sequencing, and Illumina 850k methylation arrays were performed on lung tissue of participants with IPF (234 RNA and 345 DNA samples) and non-diseased control (188 RNA and 202 DNA samples). Transcriptome and methylome datasets were normalized for unknown batch effects using Probabilistic Estimation of Expression Residuals (PEER). eQTL, cell type-interaction eQTL, and mQTL analyses were performed in FastQTL and co-localization analysis in eCAVIAR separately for cases and controls. Benjamini-Hochberg false discovery rate was used for adjustment for multiple comparisons. Results: After appropriate adjustment, we identified 4,745 genes with significant eQTLs in controls and 6,047 in cases (FDR-adjusted p<0.05). Focusing on genetic variants within 10 primary IPF-associated genetic loci, we identified 27 eQTLs in controls and 24 eQTLs in cases (FDR-adjusted p<0.05). Among these signals, we identified association of rs35705950 with expression of MUC5B (Chr11 locus) and rs2076295 with expression of DSP (Chr6 locus) in both cases and controls. To address cell specificity, we performed cell type-interaction eQTL analysis and identified an association of rs2076295 with expression of DSP in smooth muscle cells. mQTL analysis identified CpGs in gene bodies of MUC5B (cg17589883) and DSP (cg08964675) associated with the lead variants in these two loci. eCAVIAR demonstrated strong co-localization of eQTL/mQTL and genetic signal in MUC5B (rs35705950) and DSP (rs2076295) in both cases and controls. Mediation analysis demonstrated partial mediation of the effect of common variants in MUC5B and DSP loci on disease risk though MUC5B and DSP gene expression. Functional validation of the mQTL in MUC5B demonstrates that the CpG is within a putative internal repressor element that interacts through a 3D loop with the enhancer containing the rs35705950 genetic variant. Conclusions: Using lung eQTL/mQTL, co-localization, and mediation analyses, we have established the functional validation of the common IPF genetic risk variants for MUC5B (rs35705950) and DSP (rs2076295). These results provide additional evidence that both MUC5B and DSP are involved in the etiology of IPF.

Dataset Information

Establishing a valid approach for estimating familial risk of cancer explained by common genetic variants.

Publications

Establishing a valid approach for estimating familial risk of cancer explained by common genetic variants.

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