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Cis -eQTL-based trans-ethnic meta-analysis reveals novel genes associated with breast cancer risk

View Article: PubMed Central - PubMed

ABSTRACT

Breast cancer is the most common solid organ malignancy and the most frequent cause of cancer death among women worldwide. Previous research has yielded insights into its genetic etiology, but there remains a gap in the understanding of genetic factors that contribute to risk, and particularly in the biological mechanisms by which genetic variation modulates risk. The National Cancer Institute’s “Up for a Challenge” (U4C) competition provided an opportunity to further elucidate the genetic basis of the disease. Our group leveraged the seven datasets made available by the U4C organizers and data from the publicly available UK Biobank cohort to examine associations between imputed gene expression and breast cancer risk. In particular, we used reference datasets describing the breast tissue and whole blood transcriptomes to impute expression levels in breast cancer cases and controls. In trans-ethnic meta-analyses of U4C and UK Biobank data, we found significant associations between breast cancer risk and the expression of RCCD1 (joint p-value: 3.6x10-06) and DHODH (p-value: 7.1x10-06) in breast tissue, as well as a suggestive association for ANKLE1 (p-value: 9.3x10-05). Expression of RCCD1 in whole blood was also suggestively associated with disease risk (p-value: 1.2x10-05), as were expression of ACAP1 (p-value: 1.9x10-05) and LRRC25 (p-value: 5.2x10-05). While genome-wide association studies (GWAS) have implicated RCCD1 and ANKLE1 in breast cancer risk, they have not identified the remaining three genes. Among the genetic variants that contributed to the predicted expression of the five genes, we found 23 nominally (p-value < 0.05) associated with breast cancer risk, among which 15 are not in high linkage disequilibrium with risk variants previously identified by GWAS. In summary, we used a transcriptome-based approach to investigate the genetic underpinnings of breast carcinogenesis. This approach provided an avenue for deciphering the functional relevance of genes and genetic variants involved in breast cancer.

No MeSH data available.


Related in: MedlinePlus

LocusZoom plots of SNPs contributing to the whole blood expression of (A) RCCD1 at 15q26.1, (B) ACAP1 at 17p13.1, and (C) LRRC25 at 19p13.11. The x-axis displays the location of the modeled eQTL SNPs relative to the genes of interest discovered in analyses of whole blood expression. The y-axis indicates the strength of association between the SNPs and breast cancer risk. Each point is sized based on the relative contribution of the variant to gene expression.
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pgen.1006690.g002: LocusZoom plots of SNPs contributing to the whole blood expression of (A) RCCD1 at 15q26.1, (B) ACAP1 at 17p13.1, and (C) LRRC25 at 19p13.11. The x-axis displays the location of the modeled eQTL SNPs relative to the genes of interest discovered in analyses of whole blood expression. The y-axis indicates the strength of association between the SNPs and breast cancer risk. Each point is sized based on the relative contribution of the variant to gene expression.

Mentions: Fig 2 depicts the genes for which whole blood expression levels were associated with breast cancer risk. Among the 20 RCCD1 eQTL SNPs, rs3826033 (p-value: 4.1x10-03) and rs2290202 (p-value: 5.3x10-03) contributed the most weight to prediction (33% and 29% respectively) and were the most strongly associated with breast cancer risk. The other SNPs showing evidence of an association were rs7180016 (p-value: 7.3x10-03), rs11073961 (p-value: 9.9x10-03), rs11207 (p-value: 0.016), rs2285937 (p-value: 0.023), and rs3809583 (p-value: 0.035). rs3826033, rs2290202, and rs11207 were included in the both the breast tissue and the whole blood prediction models for RCCD1 expression. Only rs11073961 and rs3809583 have not been previously implicated in breast cancer GWAS.


Cis -eQTL-based trans-ethnic meta-analysis reveals novel genes associated with breast cancer risk
LocusZoom plots of SNPs contributing to the whole blood expression of (A) RCCD1 at 15q26.1, (B) ACAP1 at 17p13.1, and (C) LRRC25 at 19p13.11. The x-axis displays the location of the modeled eQTL SNPs relative to the genes of interest discovered in analyses of whole blood expression. The y-axis indicates the strength of association between the SNPs and breast cancer risk. Each point is sized based on the relative contribution of the variant to gene expression.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5391966&req=5

pgen.1006690.g002: LocusZoom plots of SNPs contributing to the whole blood expression of (A) RCCD1 at 15q26.1, (B) ACAP1 at 17p13.1, and (C) LRRC25 at 19p13.11. The x-axis displays the location of the modeled eQTL SNPs relative to the genes of interest discovered in analyses of whole blood expression. The y-axis indicates the strength of association between the SNPs and breast cancer risk. Each point is sized based on the relative contribution of the variant to gene expression.
Mentions: Fig 2 depicts the genes for which whole blood expression levels were associated with breast cancer risk. Among the 20 RCCD1 eQTL SNPs, rs3826033 (p-value: 4.1x10-03) and rs2290202 (p-value: 5.3x10-03) contributed the most weight to prediction (33% and 29% respectively) and were the most strongly associated with breast cancer risk. The other SNPs showing evidence of an association were rs7180016 (p-value: 7.3x10-03), rs11073961 (p-value: 9.9x10-03), rs11207 (p-value: 0.016), rs2285937 (p-value: 0.023), and rs3809583 (p-value: 0.035). rs3826033, rs2290202, and rs11207 were included in the both the breast tissue and the whole blood prediction models for RCCD1 expression. Only rs11073961 and rs3809583 have not been previously implicated in breast cancer GWAS.

View Article: PubMed Central - PubMed

ABSTRACT

Breast cancer is the most common solid organ malignancy and the most frequent cause of cancer death among women worldwide. Previous research has yielded insights into its genetic etiology, but there remains a gap in the understanding of genetic factors that contribute to risk, and particularly in the biological mechanisms by which genetic variation modulates risk. The National Cancer Institute’s “Up for a Challenge” (U4C) competition provided an opportunity to further elucidate the genetic basis of the disease. Our group leveraged the seven datasets made available by the U4C organizers and data from the publicly available UK Biobank cohort to examine associations between imputed gene expression and breast cancer risk. In particular, we used reference datasets describing the breast tissue and whole blood transcriptomes to impute expression levels in breast cancer cases and controls. In trans-ethnic meta-analyses of U4C and UK Biobank data, we found significant associations between breast cancer risk and the expression of RCCD1 (joint p-value: 3.6x10-06) and DHODH (p-value: 7.1x10-06) in breast tissue, as well as a suggestive association for ANKLE1 (p-value: 9.3x10-05). Expression of RCCD1 in whole blood was also suggestively associated with disease risk (p-value: 1.2x10-05), as were expression of ACAP1 (p-value: 1.9x10-05) and LRRC25 (p-value: 5.2x10-05). While genome-wide association studies (GWAS) have implicated RCCD1 and ANKLE1 in breast cancer risk, they have not identified the remaining three genes. Among the genetic variants that contributed to the predicted expression of the five genes, we found 23 nominally (p-value < 0.05) associated with breast cancer risk, among which 15 are not in high linkage disequilibrium with risk variants previously identified by GWAS. In summary, we used a transcriptome-based approach to investigate the genetic underpinnings of breast carcinogenesis. This approach provided an avenue for deciphering the functional relevance of genes and genetic variants involved in breast cancer.

No MeSH data available.


Related in: MedlinePlus