Biology subjects

Haiman, C.

Publications and source records attributed to Haiman, C..

3 recordsLinked to original sources

bioRxiv2018

Large-scale transcriptome-wide association study identifies new prostate cancer risk regions

Although genome-wide association studies (GWAS) for prostate cancer (PrCa) have identified more than 100 risk regions, most of the risk genes at these regions remain largely unknown. Here, we integrate the largest PrCa GWAS (N=142,392) with gene expression measured in 45 tissues (N=4,458), including normal and tumor prostate, to perform a multi-tissue transcriptomewide association study (TWAS) for PrCa. We identify 235 genes at 87 independent 1Mb regions associated with PrCa risk, 9 of which are regions with no genome-wide significant SNP within 2Mb. 24 genes are significant in TWAS only for alternative splicing models in prostate tumor thus supporting the hypothesis of splicing driving risk for continued oncogenesis. Finally, we use a Bayesian probabilistic approach to estimate credible sets of genes containing the causal gene at pre-defined level; this reduced the list of 235 associations to 120 genes in the 90% credible set. Overall, our findings highlight the power of integrating expression with PrCa GWAS to identify novel risk loci and prioritize putative causal genes at known risk loci.

genetics↗

bioRxiv2018

Identification of Novel Common Breast Cancer Risk Variants in Latinas at the 6q25 Locus

Background: Breast cancer is a partially heritable trait and over 180 common genetic variants have been associated with breast cancer in genome wide association studies (GWAS). We have previously performed breast cancer GWAS in Latinas and identified a strongly protective single nucleotide polymorphism (SNP) at 6q25 with the protective minor allele originating from Indigenous American ancestry. Here we report on additional GWAS and replication in Latinas.\n\nMethods: We performed GWAS in 2385 cases and 7342 controls who were either U.S. Latinas or Mexican women. We replicated 2412 cases and 1620 controls of U.S Latina, Mexican, and Colombian women. In addition, we replicated the top novel variants in study of African American and African women and in one study of Chinese women. In each dataset we used logistic regression models to test the association between SNPs and breast cancer risk and corrected for genetic ancestry using either principal components or genetic ancestry inferred from ancestry informative markers using a model based approach.\n\nResults: We identified 3 SNPs (p=1.9x10-8 - 2.8x10-8) at 6q25 locus not in linkage disequilibrium (LD) with variants previously reported at this locus. These SNPs were in high LD with each other, with the top SNP, rs3778609, associated with breast cancer with an odds ratio (OR) and 95% confidence interval (95% CI) of 0.75 (0.68-0.83). In a replication in women of Latin American origin, we also observed a consistent effect (OR: 0.88; 95% CI: 0.78-0.99; p=0.037). Since the minor allele was common in East Asians and African American but not European ancestry populations, we replicated in a meta-analysis of those populations and also observed a consistent effect (OR 0.94; 95% CI: 0.91 - 0.97; p=0.013).\n\nConclusion: The effect size of this variant is relatively large compared to other common variants associated with breast cancer and adds to evidence about the importance of the 6q25 locus for breast cancer susceptibility. Our finding also highlights the utility of performing additional searches for genetic variants for breast cancer in non-European populations.

genetics↗

bioRxiv2017

Exome chip meta-analysis elucidates the genetic architecture of rare coding variants in smoking and drinking behavior

BackgroundSmoking and alcohol use behaviors in humans have been associated with common genetic variants within multiple genomic loci. Investigation of rare variation within these loci holds promise for identifying causal variants impacting biological mechanisms in the etiology of disordered behavior. Microarrays have been designed to genotype rare nonsynonymous and putative loss of function variants. Such variants are expected to have greater deleterious consequences on gene function than other variants, and significantly contribute to disease risk.\n\nMethodsIn the present study, we analyzed [~]250,000 rare variants from 17 independent studies. Each variant was tested for association with five addiction-related phenotypes: cigarettes per day, pack years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted single variant tests of all variants, and gene-based burden tests of nonsynonymous or putative loss of function variants with minor allele frequency less than 1%.\n\nResultsMeta-analytic sample sizes ranged from 70,847 to 164,142 individuals, depending on the phenotype. Known loci tagged by common variants replicated, but there was no robust evidence for individually associated rare variants, either in gene based or single variant tests. Using a modified method-of-moment approach, we found that all low frequency coding variants, in aggregate, contributed 1.7% to 3.6% of the phenotypic variation for the five traits (p<.05).\n\nConclusionsThe findings indicate that rare coding variants contribute to phenotypic variation, but that much larger samples and/or denser genotyping of rare variants will be required to successfully identify associations with these phenotypes, whether individual variants or gene- based associations.

genetics↗