Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Androgen Receptor and ALDH1 Expression Among Internationally Diverse Patient Populations

PURPOSE: Population-based incidence rates of breast cancers that are negative for estrogen receptor (ER), progesterone receptor, and human epidermal growth factor receptor 2/ neu (triple-negative breast cancer [TNBC]) are higher among African American (AA) compared with white American (WA) women, and TNBC prevalence is elevated among selected populations of African patients. The extent to which TNBC risk is related to East African versus West African ancestry, and whether these associations extend to expression of other biomarkers, is uncertain. METHODS: We used immunohistochemistry to evaluate estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2/ neu, androgen receptor and aldehyde dehydrogenase 1 (ALDH1) expression among WA (n = 153), AA (n = 76), Ethiopian (Eth)/East African (n = 90), and Ghanaian (Gh)/West African (n = 286) patients with breast cancer through an institutional review board-approved international research program. RESULTS: Mean age at diagnosis was 43, 49, 60, and 57 years for the Eth, Gh, AA, and WA patients, respectively. TNBC frequency was higher for AA and Gh patients (41% and 54%, respectively) compared with WA and Eth patients (23% and 15%, respectively; P \u3c .001) Frequency of ALDH1 positivity was higher for AA and Gh patients (32% and 36%, respectively) compared with WA and Eth patients (23% and 17%, respectively; P = .007). Significant differences were observed for distribution of androgen receptor positivity: 71%, 55%, 42%, and 50% for the WA, AA, Gh, and Eth patients, respectively ( P = .008). CONCLUSION: Extent of African ancestry seems to be associated with particular breast cancer phenotypes. West African ancestry correlates with increased risk of TNBC and breast cancers that are positive for ALDH1

Blockchain-enabled immutable, distributed, and highly available clinical research activity logging system for federated COVID-19 data analysis from multiple institutions

ObjectiveWe aimed to develop a distributed, immutable, and highly available cross-cloud blockchain system to facilitate federated data analysis activities among multiple institutions.Materials and methodsWe preprocessed 9166 COVID-19 Structured Query Language (SQL) code, summary statistics, and user activity logs, from the GitHub repository of the Reliable Response Data Discovery for COVID-19 (R2D2) Consortium. The repository collected local summary statistics from participating institutions and aggregated the global result to a COVID-19-related clinical query, previously posted by clinicians on a website. We developed both on-chain and off-chain components to store/query these activity logs and their associated queries/results on a blockchain for immutability, transparency, and high availability of research communication. We measured run-time efficiency of contract deployment, network transactions, and confirmed the accuracy of recorded logs compared to a centralized baseline solution.ResultsThe smart contract deployment took 4.5 s on an average. The time to record an activity log on blockchain was slightly over 2 s, versus 5-9 s for baseline. For querying, each query took on an average less than 0.4 s on blockchain, versus around 2.1 s for baseline.DiscussionThe low deployment, recording, and querying times confirm the feasibility of our cross-cloud, blockchain-based federated data analysis system. We have yet to evaluate the system on a larger network with multiple nodes per cloud, to consider how to accommodate a surge in activities, and to investigate methods to lower querying time as the blockchain grows.ConclusionBlockchain technology can be used to support federated data analysis among multiple institutions