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UnknownGenome-wide association and transcriptome studies identify target genes and risk loci for breast cancer.
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...
S-EPMC6465407 | biostudies-literature
UnknownA case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers.
Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variant...
S-EPMC7890067 | biostudies-literature
UnknownTranscriptome-wide association study of breast cancer risk by estrogen-receptor status.
Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted...
S-EPMC7987299 | biostudies-literature
UnknownTrans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.
Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independ...
S-EPMC8148035 | biostudies-literature
UnknownGenome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses.
Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast ...
S-EPMC7808397 | biostudies-literature
UnknownFine-mapping of 150 breast cancer risk regions identifies 191 likely target genes.
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 ris...
S-EPMC6974400 | biostudies-literature
UnknownCharacterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants.
The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls...
S-EPMC10841479 | biostudies-literature
UnknownFunctional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus.
A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10(-20)), ER-nega...
S-EPMC5023955 | biostudies-literature
UnknownIdentification of six new susceptibility loci for invasive epithelial ovarian cancer.
Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associ...
S-EPMC4445140 | biostudies-literature
UnknownCorrection: Polygenic risk modeling for prediction of epithelial ovarian cancer risk.
Not available
S-EPMC9090804 | biostudies-literature
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