Envisioning health equity for American Indian/Alaska Natives: a unique HIT opportunity

The Indian Health Service provides care to remote and under-resourced communities in the United States. American Indian/Alaska Native patients have some of the highest morbidity and mortality among any ethnic group in the United States. Starting in the 1980s, the IHS implemented the Resource and Patient Management System health information technology (HIT) platform to improve efficiency and quality to address these disparities. The IHS is currently assessing the Resource and Patient Management System to ensure that changing health information needs are met. HIT assessments have traditionally focused on cost, reimbursement opportunities, infrastructure, required or desired functionality, and the ability to meet provider needs. Little information exists on frameworks that assess HIT legacy systems to determine solutions for an integrated rural healthcare system whose end goal is health equity. This search for a next-generation HIT solution for a historically underserved population presents a unique opportunity to envision and redefine HIT that supports health equity as its core mission

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