Biology subjects

Gruber, S. B.

Publications and source records attributed to Gruber, S. B..

5 recordsLinked to original sources

bioRxiv2020

A combined proteomics and Mendelian randomization approach to investigate the effects of aspirin-targeted proteins on colorectal cancer

BackgroundEvidence for aspirins chemopreventative properties on colorectal cancer (CRC) is substantial, but its mechanism of action is not well-understood. We combined a proteomic approach with Mendelian randomization (MR) to identify possible new aspirin targets that decrease CRC risk. MethodsHuman colorectal adenoma cells (RG/C2) were treated with aspirin (24 hours) and a stable isotope labelling with amino acids in cell culture (SILAC) based proteomics approach identified altered protein expression. Protein quantitative trait loci (pQTLs) from INTERVAL (N=3,301) and expression QTLs (eQTLs) from the eQTLGen Consortium (N=31,684) were used as genetic proxies for protein and mRNA expression levels. Two-sample MR of mRNA/protein expression on CRC risk was performed using eQTL/pQTL data combined with CRC genetic summary data from the Colon Cancer Family Registry (CCFR), Colorectal Transdisciplinary (CORECT), Genetics and Epidemiology of Colorectal Cancer (GECCO) consortia and UK Biobank (55,168 cases and 65,160 controls). ResultsAltered expression was detected for 125/5886 proteins. Of these, aspirin decreased MCM6, RRM2 and ARFIP2 expression and MR analysis showed that a standard deviation increase in mRNA/protein expression was associated with increased CRC risk (OR:1.08, 95% CI:1.03-1.13, OR:3.33, 95% CI:2.46-4.50 and OR:1.15, 95% CI:1.02-1.29, respectively). ConclusionMCM6 and RRM2 are involved in DNA repair whereby reduced expression may lead to increased DNA aberrations and ultimately cancer cell death, whereas ARFIP2 is involved in actin cytoskeletal regulation indicating a possible role in aspirins reduction of metastasis. ImpactOur approach has shown how laboratory experiments and population-based approaches can combine to identify aspirin-targeted proteins possibly affecting CRC risk.

cancer biology↗

bioRxiv2019

Physical activity and risks of breast and colorectal cancer: A Mendelian randomization analysis

Physical activity has been associated with lower risks of breast and colorectal cancer in epidemiological studies; however, it is unknown if these associations are causal or confounded. In two-sample Mendelian randomization analyses, using summary genetic data from the UK Biobank and GWA consortia, we found that a one standard deviation increment in average acceleration was associated with lower risks of breast cancer (odds ratio [OR]: 0.59, 95% confidence interval [CI]: 0.42 to 0.84, P-value=0.003) and colorectal cancer (OR: 0.66, 95% CI: 0.53 to 0.82, P-value=2*E-4). We found similar magnitude inverse associations by breast cancer subtype and by colorectal cancer anatomical site. Our results support a potentially causal relationship between higher physical activity levels and lower risks of breast cancer and colorectal cancer. Based on these data, the promotion of physical activity is probably an effective strategy in the primary prevention of these commonly diagnosed cancers.\n\nDisclaimerWhere authors are identified as personnel of the International Agency for Research on Cancer / World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer / World Health Organization.

genetics↗

bioRxiv2019

Assessment of Polygenic Architecture and Risk Prediction based on Common Variants Across Fourteen Cancers

We analyzed summary-level data from genome-wide association studies (GWAS) of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) contributing to risk, as well as the distribution of their associated effect sizes. All cancers evaluated showed polygenicity, involving at a minimum thousands of independent susceptibility variants. For some malignancies, particularly chronic lymphoid leukemia (CLL) and testicular cancer, there are a larger proportion of variants with larger effect sizes than those for other cancers. In contrast, most variants for lung and breast cancers have very small associated effect sizes. For different cancer sites, we estimate a wide range of GWAS sample sizes, required to explain 80% of GWAS heritability, varying from 60,000 cases for CLL to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores, compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that polygenic risk scores have substantial potential for risk stratification for relatively common cancers such as breast, prostate and colon, but limited potential for other cancer sites because of modest heritability and lower disease incidence.

genetics↗

bioRxiv2018

Exploring Various Polygenic Risk Scores for Basal Cell Carcinoma, Cutaneous Squamous Cell Carcinoma and Melanoma in the Phenomes of the Michigan Genomics Initiative and the UK Biobank

Polygenic risk scores (PRS) are designed to serve as a single summary measure, condensing information from a large number of genetic variants associated with a disease. They have been used for stratification and prediction of disease risk. The construction of a PRS often depends on the purpose of the study, the available data/summary estimates, and the underlying genetic architecture of a disease. In this paper, we consider several choices for constructing a PRS using summary data obtained from various publicly-available sources including the UK Biobank and evaluate their abilities to predict outcomes derived from electronic health records (EHR). Weexamine the three most common skin cancer subtypes in the USA: basal cellcarcinoma, cutaneous squamous cell carcinoma, and melanoma. The genetic risk profiles of subtypes may consist of both shared and unique elements and we construct PRS to understand the common versus distinct etiology. This study is conducted using data from 30,702 unrelated, genotyped patients of recent European descent from the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort within Michigan Medicine. Using these PRS for various skin cancer subtypes, we conduct a phenome-wide association study (PheWAS) within the MGI data to evaluate their association with secondary traits. PheWAS results are then replicated using population-based UK Biobank data. We develop an accompanying visual catalog called PRSweb that provides detailed PheWAS results and allows users to directly compare different PRS construction methods. The results of this study can provide guidance regarding PRS construction in future PRS-PheWAS studies using EHR data involving disease subtypes.\n\nAuthor summaryIn the study of genetically complex diseases, polygenic risk scores synthesize information from multiple genetic risk factors to provide insight into a patients risk of developing a disease based on his/her genetic profile. These risk scores can be explored in conjunction with health and disease information available in the electronic medical records. They may be associated with diseases that may be related to or precursors of the underlying disease of interest. Limited work is available guiding risk score construction when the goal is to identify associations across the medical phenome. In this paper, we compare different polygenic risk score construction methods in terms of their relationships with the medical phenome. We further propose methods for using these risk scores to decouple the shared and unique genetic profiles of related diseases and to explore related diseases shared and unique secondary associations. Leveraging and harnessing the rich data resources of the Michigan Genomics Initiative, a biorepository effort at Michigan Medicine, and the larger population-based UK Biobank study, we investigated the performance of genetic risk profiling methods for the three most common types of skin cancer: melanoma, basal cell carcinoma and squamous cell carcinoma.

genetics↗

bioRxiv2017

Association of Polygenic Risk Scores for Multiple Cancers in a Phenome-wide Study: Results from The Michigan Genomics Initiative

Health systems are stewards of patient electronic health record (EHR) data with extraordinarily rich depth and breadth, reflecting thousands of diagnoses and exposures. Measures of genomic variation integrated with EHRs offer a potential strategy to accurately stratify patients for risk profiling and discover new relationships between diagnoses and genomes. The objective of this study was to evaluate whether Polygenic Risk Scores (PRS) for common cancers are associated with multiple phenotypes in a Phenome-wide Association Study (PheWAS) conducted in 28,260 unrelated, genotyped patients of recent European ancestry who consented to participate in the Michigan Genomics Initiative, a longitudinal biorepository effort within Michigan Medicine. PRS for 12 cancer traits were calculated using summary statistics from the NHGRI-EBI catalog. A total of 1,711 synthetic case-control studies was used for PheWAS analyses. There were 13,490 (47.7%) patients with at least one cancer diagnosis in this study sample. PRSs exhibited strong association for several cancer traits they were designed for including female breast cancer, prostate cancer, melanoma, basal cell carcinoma, squamous cell carcinoma and thyroid cancer. Phenome-wide significant associations were observed between PRS and many non-cancer diagnoses. To differentiate PRS associations driven by the primary trait from associations arising through shared genetic risk profiles, the idea of \"exclusion PRS PheWAS\" was introduced. This approach led to phenome-wide significant associations between a lower risk for hypothyroidism in patients with high thyroid cancer PRS and a higher risk for actinic keratosis in patients with high squamous cell carcinoma PRS after removing all cases of the primary cancer trait. Further analysis of temporal order of the diagnoses improved our understanding of these secondary associations. This is the first comprehensive PheWAS study using PRS instead of a single variant.

genetics↗