The promise of “personalized medicine” guided by an understanding of each individual’s genome has been fostered by increasingly powerful and economical methods to acquire clinically relevant features. We describe operational implementation of prospective genotyping linked to an advanced clinical decision support system to guide individualized healthcare in a large academic health center. This approach to personalized medicine includes patient and healthcare provider engagement, identifying relevant genetic variation for implementation, assay reliability, point-of-care decision support, and necessary institutional investments. In one year, approximately 3,000 patients, most scheduled for cardiac catheterization, were genotyped on a multiplexed platform including CYP2C19 variants that modulate response to the widely-used antiplatelet drug clopidogrel. These data are deposited into the Electronic Medical Record and point-of-care decision support is deployed when clopidogrel is prescribed for those with variant genotypes. The establishment of programs such as this is a first step toward implementing and evaluating strategies for personalized medicine.
BackgroundThe rapid development of effective medical countermeasures against potential biological threat agents is vital. Repurposing existing drugs that may have unanticipated activities as potential countermeasures is one way to meet this important goal, since currently approved drugs already have well-established safety and pharmacokinetic profiles in patients, as well as manufacturing and distribution networks. Therefore, approved drugs could rapidly be made available for a new indication in an emergency.Methodology/Principal FindingsA large systematic effort to determine whether existing drugs can be used against high containment bacterial and viral pathogens is described. We assembled and screened 1012 FDA-approved drugs for off-label broad-spectrum efficacy against Bacillus anthracis; Francisella tularensis; Coxiella burnetii; and Ebola, Marburg, and Lassa fever viruses using in vitro cell culture assays. We found a variety of hits against two or more of these biological threat pathogens, which were validated in secondary assays. As expected, antibiotic compounds were highly active against bacterial agents, but we did not identify any non-antibiotic compounds with broad-spectrum antibacterial activity. Lomefloxacin and erythromycin were found to be the most potent compounds in vivo protecting mice against Bacillus anthracis challenge. While multiple virus-specific inhibitors were identified, the most noteworthy antiviral compound identified was chloroquine, which disrupted entry and replication of two or more viruses in vitro and protected mice against Ebola virus challenge in vivo.Conclusions/SignificanceThe feasibility of repurposing existing drugs to face novel threats is demonstrated and this represents the first effort to apply this approach to high containment bacteria and viruses.
Genome-wide association studies (GWASs) primarily performed in European-ancestry (EA) populations have identified numerous loci associated with body mass index (BMI). However, it is still unclear whether these GWAS loci can be generalized to other ethnic groups, such as African Americans (AAs). Furthermore, the putative functional variant or variants in these loci mostly remain under investigation. The overall lower linkage disequilibrium in AA compared to EA populations provides the opportunity to narrow in or fine-map these BMI-related loci. Therefore, we used the Metabochip to densely genotype and evaluate 21 BMI GWAS loci identified in EA studies in 29,151 AAs from the Population Architecture using Genomics and Epidemiology (PAGE) study. Eight of the 21 loci (SEC16B, TMEM18, ETV5, GNPDA2, TFAP2B, BDNF, FTO, and MC4R) were found to be associated with BMI in AAs at 5.8 × 10(-5). Within seven out of these eight loci, we found that, on average, a substantially smaller number of variants was correlated (r(2) > 0.5) with the most significant SNP in AA than in EA populations (16 versus 55). Conditional analyses revealed GNPDA2 harboring a potential additional independent signal. Moreover, Metabochip-wide discovery analyses revealed two BMI-related loci, BRE (rs116612809, p = 3.6 × 10(-8)) and DHX34 (rs4802349, p = 1.2 × 10(-7)), which were significant when adjustment was made for the total number of SNPs tested across the chip. These results demonstrate that fine mapping in AAs is a powerful approach for both narrowing in on the underlying causal variants in known loci and discovering BMI-related loci.
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