COVID-19 Knowledge Extractor (COKE): A Curated Repository of Drug-Target Associations Extracted from the CORD-19 Corpus of Scientific Publications on COVID-19.

The COVID-19 pandemic has catalyzed a widespread effort to identify drug candidates and biological targets of relevance to SARS-COV-2 infection, which resulted in large numbers of publications on this subject. We have built the COVID-19 Knowledge Extractor (COKE), a web application to extract, curate, and annotate essential drug-target relationships from the research literature on COVID-19. SciBiteAI ontological tagging of the COVID Open Research Data set (CORD-19), a repository of COVID-19 scientific publications, was employed to identify drug-target relationships. Entity identifiers were resolved through lookup routines using UniProt and DrugBank. A custom algorithm was used to identify co-occurrences of the target protein and drug terms, and confidence scores were calculated for each entity pair. COKE processing of the current CORD-19 database identified about 3000 drug-protein pairs, including 29 unique proteins and 500 investigational, experimental, and approved drugs. Some of these drugs are presently undergoing clinical trials for COVID-19. The COKE repository and web application can serve as a useful resource for drug repurposing against SARS-CoV-2. COKE is freely available at https://coke.mml.unc.edu/, and the code is available at https://github.com/DnlRKorn/CoKE.

COVID-19 Knowledge Extractor (COKE): A Tool and a Web Portal to Extract Drug - Target Protein Associations from the CORD-19 Corpus of Scientific Publications on COVID-19.

Objective: The COVID-19 pandemic has catalyzed a widespread effort to identify drug candidates and biological targets of relevance to SARS-COV-2 infection, which resulted in large numbers of publications on this subject. We have built the COVID-19 Knowledge Extractor (COKE), a web application to extract, curate, and annotate essential drug-target relationships from the research literature on COVID-19 to assist drug repurposing efforts. Materials and Methods: SciBiteAI ontological tagging of the COVID Open Research Dataset (CORD-19), a repository of COVID-19 scientific publications, was employed to identify drug-target relationships. Entity identifiers were resolved through lookup routines using UniProt and DrugBank. A custom algorithm was used to identify co-occurrences of protein and drug terms, and confidence scores were calculated for each entity pair. Results: COKE processing of the current CORD-19 database identified about 3,000 drug-protein pairs, including 29 unique proteins and 500 investigational, experimental, and approved drugs. Some of these drugs are presently undergoing clinical trials for COVID-19. Discussion: The rapidly evolving situation concerning the COVID-19 pandemic has resulted in a dramatic growth of publications on this subject in a short period. These circumstances call for methods that can condense the literature into the key concepts and relationships necessary for insights into SARS-CoV-2 drug repurposing. Conclusion: The COKE repository and web application deliver key drug - target protein relationships to researchers studying SARS-CoV-2. COKE portal may provide comprehensive and critical information on studies concerning drug repurposing against COVID-19. COKE is freely available at https://coke.mml.unc.edu/ and the code is available at https://github.com/DnlRKorn/CoKE.

Polygenic risk scores for cigarettes smoked per day do not generalize to a Native American population.

BACKGROUND: Recent studies have demonstrated the utility of polygenic risk scores (PRSs) for exploring the genetic etiology of psychiatric phenotypes and the genetic correlations between them. To date, these studies have been conducted almost exclusively using participants of European ancestry, and thus, there is a need for similar studies conducted in other ancestral populations. However, given that the predictive ability of PRSs are sensitive to differences in linkage disequilibrium (LD) patterns and minor allele frequencies across discovery and target samples, the applicability of PRSs developed in European ancestry samples to other ancestral populations has yet to be determined. Therefore, the current study derived PRSs for cigarettes per day (CPD) from predominantly European-ancestry samples and examined their ability to predict nicotine dependence (ND) in a Native American (NA) population sample. METHOD: Results from the Tobacco and Genetics Consortium's meta-analysis of genome-wide association studies of CPD were used to compute PRSs in a NA community sample (N=288). These scores were then used to predict ND diagnostic status. RESULTS: The PRS was not significantly associated with liability for ND in the full sample. However, a significant interaction between PRS and percent NA ancestry was observed. Risk scores were positively associated with liability for ND at higher levels of European ancestry, but no association was observed at higher levels of NA ancestry. CONCLUSION: These findings illustrate how differences in patterns of LD across discovery and target samples can reduce the predictive ability of PRSs for complex traits.

High Diagnostic Yield of Whole Exome Sequencing in Participants With Retinal Dystrophies in a Clinical Ophthalmology Setting.

PURPOSE: To assess the diagnostic yield and the practicality of implementing whole exome sequencing within a clinical ophthalmology setting. DESIGN: Evaluation of a diagnostic protocol. METHODS: setting: Patient participants were enrolled during clinical appointments in a university-based ophthalmic genetics clinic. PATIENT POPULATION: Twenty-six patients with a variety of presumed hereditary retinal dystrophies. INTERVENTION: Participants were offered whole exome sequencing in addition to clinically available sequencing gene panels between July 2012 and January 2013 to determine the molecular etiology of their retinal dystrophy. MAIN OUTCOME MEASURES: Diagnostic yield and acceptability of whole exome sequencing in patients with retinal disorders. RESULTS: Twenty-six of 29 eligible patients (∼90%) who were approached opted to undergo molecular testing. Each participant chose whole exome sequencing in addition to, or in lieu of, clinically available sequencing gene panels. Time to obtain informed consent was manageable in the clinical context. Whole exome sequencing successfully identified known pathogenic mutations or suspected deleterious variants in 57.7% of participants. Additionally, 1 participant had 2 autosomal dominant medically actionable incidental findings (unrelated to retinopathy) that were reported to enable the participant to take preventive action and reduce risk for future disease. CONCLUSIONS: In this study, we identified the molecular etiology for more than half of all participants. Additionally, we found that participants were widely accepting of whole exome sequencing and the possibility of being informed about medically actionable incidental findings.

Germline mutations in HOXB13 and prostate-cancer risk.

BACKGROUND: Family history is a significant risk factor for prostate cancer, although the molecular basis for this association is poorly understood. Linkage studies have implicated chromosome 17q21-22 as a possible location of a prostate-cancer susceptibility gene. METHODS: We screened more than 200 genes in the 17q21-22 region by sequencing germline DNA from 94 unrelated patients with prostate cancer from families selected for linkage to the candidate region. We tested family members, additional case subjects, and control subjects to characterize the frequency of the identified mutations. RESULTS: Probands from four families were discovered to have a rare but recurrent mutation (G84E) in HOXB13 (rs138213197), a homeobox transcription factor gene that is important in prostate development. All 18 men with prostate cancer and available DNA in these four families carried the mutation. The carrier rate of the G84E mutation was increased by a factor of approximately 20 in 5083 unrelated subjects of European descent who had prostate cancer, with the mutation found in 72 subjects (1.4%), as compared with 1 in 1401 control subjects (0.1%) (P=8.5x10(-7)). The mutation was significantly more common in men with early-onset, familial prostate cancer (3.1%) than in those with late-onset, nonfamilial prostate cancer (0.6%) (P=2.0x10(-6)). CONCLUSIONS: The novel HOXB13 G84E variant is associated with a significantly increased risk of hereditary prostate cancer. Although the variant accounts for a small fraction of all prostate cancers, this finding has implications for prostate-cancer risk assessment and may provide new mechanistic insights into this common cancer. (Funded by the National Institutes of Health and others.).