Biology subjects

Kushi, L. H.

Publications and source records attributed to Kushi, L. H..

4 recordsLinked to original sources

bioRxiv2020

Cross-Cancer Evaluation of Polygenic Risk Scores for 17 Cancer Types in Two Large Cohorts

Genetic factors that influence etiologic mechanisms shared across cancers could affect the risk of multiple cancer types. We investigated polygenic risk score (PRS)-specific pleiotropy across 17 cancers in two large population-based cohorts. The study population included European ancestry individuals from the Genetic Epidemiology Research on Adult Health and Aging cohort (16,012 cases, 50,552 controls) and the UK Biobank (48,969 cases, 359,802 controls). We selected known independent risk variants from published GWAS to construct a PRS for each cancer type. Within cohorts, each PRS was evaluated in multivariable logistic regression models with respect to the cancer for which it was developed and each other cancer type. Results were then meta-analyzed across cohorts. In the UK Biobank, each PRS was additionally evaluated relative to 20 cancer risk factors or biomarkers. All PRS replicated associations with their corresponding cancers (p<0.05). Eleven cross-cancer associations - ten positive and one inverse - were found after correction for multiple testing (p<0.05/17=0.0029). Two cancer pairs showed bidirectional associations; the melanoma PRS was positively associated with oral cavity/pharyngeal cancer and vice versa, whereas the lung cancer PRS was positively associated with oral cavity/pharyngeal cancer, and the oral cavity/pharyngeal cancer PRS was inversely associated with lung cancer. We identified 65 associations between a cancer PRS and non-cancer phenotype. In this study examining cross-cancer PRS associations in two cohorts unselected for phenotype, we validated known and uncovered novel patterns of pleiotropy. Our results have the potential to inform investigations of risk prediction, shared etiology, and precision cancer prevention strategies. STATEMENT OF SIGNIFICANCEBy examining cross-cancer polygenic risk score associations, we validated known and uncovered novel patterns of pleiotropy. Our results may inform investigations of risk prediction, shared etiology, and precision prevention strategies.

genetics↗

bioRxiv2019

Pan-Cancer Study Detects Novel Genetic Risk Variants and Shared Genetic Basis in Two Large Cohorts

Deciphering the shared genetic basis of distinct cancers has the potential to elucidate carcinogenic mechanisms and inform broadly applicable risk assessment efforts. However, no studies have investigated pan-cancer pleiotropy within single, well-defined populations unselected for phenotype. We undertook novel genome-wide association studies (GWAS) and comprehensive evaluations of heritability and pleiotropy across 18 cancer types in two large, population-based cohorts: the UK Biobank (413,870 European ancestry individuals; 48,961 cancer cases) and the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging cohorts (66,526 European ancestry individuals; 16,001 cancer cases). The GWAS detected 21 novel genome-wide significant risk variants. In addition, numerous cancer sites exhibited clear heritability. Investigations of pleiotropy identified 12 cancer pairs exhibiting either positive or negative genetic correlations and 43 pleiotropic loci. We identified 158 pleiotropic variants, many of which were enriched for regulatory elements and influenced cross-tissue gene expression. Our findings demonstrate widespread pleiotropy and offer further insight into the complex genetic architecture of cross-cancer susceptibility.

genetics↗

bioRxiv2019

A polygenic risk score for breast cancer in U.S. Latinas and Latin-American women

BackgroundOver 180 single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility have been identified; these SNPs can be combined into polygenic risk scores (PRS) to predict breast cancer risk. Since most SNPs were identified in predominantly European populations, little is known about the performance of PRS in non-Europeans. We tested the performance of a 180-SNP PRS in Latinas, a large ethnic group with variable levels of Indigenous American, European, and African ancestry.\n\nMethodsWe conducted a pooled case-control analysis of U.S. Latinas and Latin-American women (4,658 cases, 7,622 controls). We constructed a 180-SNP PRS consisting of SNPs associated with breast cancer risk (p < 5 x 10-8). We evaluated the association between the PRS and breast cancer risk using multivariable logistic regression and assessed discrimination using area under the receiver operating characteristic curve (AUROC). We also assessed PRS performance across quartiles of Indigenous American genetic ancestry.\n\nResultsOf 180 SNPs tested, 142 showed directionally consistent associations compared with European populations, and 39 were nominally significant (p < 0.05). The PRS was associated with breast cancer risk, with an odds ratio (OR) per standard deviation increment of 1.58 (95% CI 1.52 to 1.64) and AUCROC of 0.63 (95% CI 0.62 to 0.64). The discrimination of the PRS was similar between the top and bottom quartiles of Indigenous American ancestry.\n\nConclusionsThe 180-SNP PRS predicts breast cancer risk in Latinas, with similar performance as reported for Europeans. The performance of the PRS did not vary substantially according to Indigenous American ancestry.

epidemiology↗

bioRxiv2017

Identification of Novel Breast Tumor Expression Dimensions within the PAM50 and Discovery of a Breast Cancer Susceptibility Locus at 12q15

It is well-known that breast tumors exhibit different expression patterns that can be used to assign intrinsic subtypes - the PAM50 assay, for example, categorizes tumors into: Luminal A, Luminal B, HER2-enriched and Basal-like - yet tumors are often more complex than categorization can describe. We used 911 sporadic breast tumors to reparameterize expression from the PAM50 genes to five orthogonal tumor dimensions using principal components (PC). Three dimensions captured intrinsic subtype, two dimensions were novel, and all replicated in 945 TCGA tumors. By definition dimensions are independent, an important attribute for inclusion in downstream studies exploring effects of tumor diversity. One application where tumor subtyping has failed to provide impact is susceptibility genetics. Germline genetic heterogeneity reduces power for gene-finding. The identification of heritable tumor characteristics has potential to increase homogeneity. We compared 238 breast tumors from high-risk pedigrees not attributable to BRCA1 or BRCA2 to 911 sporadic breast tumors. Two PC dimensions were significantly enriched in the pedigrees (intrinsic subtypes were not). We performed proof-of-concept gene-mapping in one enriched pedigree and identified a 0.5 Mb genomewide significant region at 12q15 that segregated to the 8 breast cancer cases with the most extreme PC tumors through 32 meioses (p=2.6x10-8). In conclusion, our study: suggests a new approach to describe tumor diversity; supports the hypothesis that tumor characteristics are heritable providing new avenues for germline studies; and proposes a new breast cancer locus. Reparameterization of expression patterns may similarly inform other studies attempting to model the effects of tumor heterogeneity.

genetics↗