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1.
  • Jiang, Xia, et al. (författare)
  • Shared heritability and functional enrichment across six solid cancers
  • 2019
  • Ingår i: Nature Communications. - 2041-1723. ; 10
  • Tidskriftsartikel (refereegranskat)abstract
    • Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg = 0.57, p = 4.6 × 10−8), breast and ovarian cancer (rg = 0.24, p = 7 × 10−5), breast and lung cancer (rg = 0.18, p =1.5 × 10−6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 10−4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis. © 2019, The Author(s).
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  • Mavaddat, Nasim, et al. (författare)
  • Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes
  • 2019
  • Ingår i: American journal of human genetics. - 1537-6605. ; 104:1, s. 21-34
  • Tidskriftsartikel (refereegranskat)abstract
    • Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57–1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628–0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs. © 2018 The Authors
4.
  • Fachal, Laura, et al. (författare)
  • Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes
  • 2020
  • Ingår i: Nature genetics. - 1546-1718. ; 52:1, s. 56-73
  • Tidskriftsartikel (refereegranskat)abstract
    • Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.
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  • Ferreira, Manuel A., et al. (författare)
  • Genome-wide association and transcriptome studies identify target genes and risk loci for breast cancer
  • 2019
  • Ingår i: Nature communications. - 2041-1723. ; 10:1, s. 1741
  • Tidskriftsartikel (refereegranskat)abstract
    • Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer. © 2019, The Author(s).
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8.
  • Haiman, Christopher A., et al. (författare)
  • A common variant at the TERT-CLPTM1L locus is associated with estrogen receptor-negative breast cancer
  • 2011
  • Ingår i: Nature Genetics. - Nature Publishing Group. - 1546-1718. ; 43:12, s. 61-1210
  • Tidskriftsartikel (refereegranskat)abstract
    • Estrogen receptor (ER)-negative breast cancer shows a higher incidence in women of African ancestry compared to women of European ancestry. In search of common risk alleles for ER-negative breast cancer, we combined genome-wide association study (GWAS) data from women of African ancestry (1,004 ER-negative cases and 2,745 controls) and European ancestry (1,718 ER-negative cases and 3,670 controls), with replication testing conducted in an additional 2,292 ER-negative cases and 16,901 controls of European ancestry. We identified a common risk variant for ER-negative breast cancer at the TERT-CLPTM1L locus on chromosome 5p15 (rs10069690: per-allele odds ratio (OR) = 1.18 per allele, P = 1.0 x 10(-10)). The variant was also significantly associated with triple-negative (ER-negative, progesterone receptor (PR)-negative and human epidermal growth factor-2 (HER2)-negative) breast cancer (OR = 1.25, P = 1.1 x 10(-9)), particularly in younger women (<50 years of age) (OR = 1.48, P = 1.9 x 10(-9)). Our results identify a genetic locus associated with estrogen receptor negative breast cancer subtypes in multiple populations.
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10.
  • Jiang, Xia, et al. (författare)
  • Shared heritability and functional enrichment across six solid cancers
  • 2019
  • Ingår i: Nature Communications. - Nature Publishing Group. - 2041-1723 .- 2041-1723. ; 10
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (<em>r</em><em>g</em> = 0.57, <em>p</em> = 4.6 × 10−8), breast and ovarian cancer (<em>r</em><em>g</em> = 0.24, <em>p</em> = 7 × 10−5), breast and lung cancer (<em>r</em><em>g</em> = 0.18, <em>p </em>=1.5 × 10−6) and breast and colorectal cancer (<em>r</em><em>g</em> = 0.15, <em>p</em> = 1.1 × 10−4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.</p>
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