The Astounding Breadth of Health Disparity: Phenome-Wide Effects of Race on Disease Risk.

OBJECTIVE: We conducted a phenotype-wide association study (PheWAS) to compare diagnoses among Blacks with those of Whites in one health center in Tennessee using data from 1,883,369 patients. METHODS: We used our deidentified EHR, the Synthetic Derivative, to assess risk of diagnoses associated with Black as compared with White race using Firth logistic regression with covariates including age, sex, and density of clinical encounters. RESULTS: There were anchoring associations in both directions, including the highest increased risk for Blacks of having sickle cell anemia, and strongest decreased risk of basal cell carcinoma. Results included established areas of disparity and many novel associations. CONCLUSIONS: PheWAS is a viable tool for calculating risk associated with any biomarker. The current analysis provide a new approach to generating hypotheses and understanding the breadth of health disparities. Future analyses will further explore causality, risk factors, and potential confounders not accounted for here.

Repurposing of a Thromboxane Receptor Inhibitor Based on a Novel Role in Metastasis Identified by Phenome-Wide Association Study.

Although new drug discoveries are revolutionizing cancer treatments, repurposing existing drugs would accelerate the timeline and lower the cost for bringing treatments to cancer patients. Our goal was to repurpose CPI211, a potent and selective antagonist of the thromboxane A2-prostanoid receptor (TPr), a G-protein-coupled receptor that regulates coagulation, blood pressure, and cardiovascular homeostasis. To identify potential new clinical indications for CPI211, we performed a phenome-wide association study (PheWAS) of the gene encoding TPr, TBXA2R, using robust deidentified health records and matched genomic data from more than 29,000 patients. Specifically, PheWAS was used to identify clinical manifestations correlating with a TBXA2R single-nucleotide polymorphism (rs200445019), which generates a T399A substitution within TPr that enhances TPr signaling. Previous studies have correlated 200445019 with chronic venous hypertension, which was recapitulated by this PheWAS analysis. Unexpectedly, PheWAS uncovered an rs200445019 correlation with cancer metastasis across several cancer types. When tested in several mouse models of metastasis, TPr inhibition using CPI211 potently blocked spontaneous metastasis from primary tumors, without affecting tumor cell proliferation, motility, or tumor growth. Further, metastasis following intravenous tumor cell delivery was blocked in mice treated with CPI211. Interestingly, TPr signaling in vascular endothelial cells induced VE-cadherin internalization, diminished endothelial barrier function, and enhanced transendothelial migration by tumor cells, phenotypes that were decreased by CPI211. These studies provide evidence that TPr signaling promotes cancer metastasis, supporting the study of TPr inhibitors as antimetastatic agents and highlighting the use of PheWAS as an approach to accelerate drug repurposing.

COMPASS: A Pilot Trial of an Early Palliative Care Intervention for Patients With End-Stage Liver Disease.

CONTEXT: Palliative care interventions have shown promise in improving quality of life and reducing health-care utilization among patients with chronic organ failure. OBJECTIVES: To evaluate the effect of a palliative care intervention for adults with end-stage liver disease. METHODS: A randomized controlled trial of patients with end-stage liver disease admitted to the hepatology service at a tertiary referral center whose attending hepatologist indicated they would not be surprised if the patient died in the following year on a standardized questionnaire was performed. Control group patients received usual care. Intervention group patients received inpatient specialist palliative care consultations and outpatient phone follow-up by a palliative care nurse. The primary outcome was time until first readmission. Secondary outcomes included days alive outside the hospital, referral to hospice care, death, readmissions, patient quality of life, depression, anxiety, and quality of end-of-life care over 6 months. RESULTS: The trial stopped early because of difficulties in accruing patients. Of 293 eligible patients, only 63 patients were enrolled, 31 in the intervention group and 32 in the control group. This pace of enrollment was only 25% of what the study had planned, and so it was deemed infeasible to complete. Despite stopping early, intervention group patients had a lower hazard of readmission (hazard ratio: 0.36, 95% confidence interval: 0.16-0.83, P = 0.017) and greater odds of having more days alive outside the hospital than control group patients (odds ratio: 3.97, 95% confidence interval: 1.14-13.84, P = 0.030). No other statistically significant differences were observed. CONCLUSION: Logistical obstacles hindered completion of the trial as originally designed. Nevertheless, a preemptive palliative care intervention resulted in increased time to first readmission and more days alive outside the hospital in the first six months after study entry.

Motivation for Launching a Cancer Metastasis Inhibition (CMI) Program.

Metastatic cancers impose significant burdens on patients, affecting quality of life, morbidity, and mortality. Even during remission, microscopic metastases can lurk, but few therapies directly target tumor cell metastasis. Agents that interfere with this process would represent a new paradigm in cancer management, changing the 'waiting game' into a time of active prevention. These therapies could take multiple forms based on the pathways involved in the metastatic process. For example, a phenome-wide association study showed that a single nucleotide polymorphism in the gene TBXA2R is associated with increased metastasis in multiple primary cancers (P = 0.003), suggesting clinical applicability of TBXA2R antagonists. Emerging data related to the role of platelets in metastasis are concordant with our sense that these pathways present significant opportunities for therapeutic development. However, before real progress can be made toward clinical targeting of the metastatic process, foundational work is needed to define informative measures of critical elements such as circulating tumor cells and tumor DNA, and circulatory vs. lymphatic spread. These challenges require an expansion of team science and composition to obtain competitive funding. At our academic medical center, we have implemented a Cancer Metastasis Inhibition (CMI) program investigating this approach across multiple cancers.

Assessment of a pharmacogenomic marker panel in a polypharmacy population identified from electronic medical records.

BACKGROUND: The ADME Core Panel assays 184 variants across 34 pharmacogenes, many of which are difficult to accurately genotype with standard multiplexing methods. METHODS: We genotyped 326 frequently medicated individuals of European descent in Vanderbilt's biorepository linked to de-identified electronic medical records, BioVU, on the ADME Core Panel to assess quality and performance of the assay. We compared quality control metrics and determined the extent of direct and indirect marker overlap between the ADME Core Panel and the Illumina Omni1-Quad. RESULTS: We found the quality of the ADME Core Panel data to be high, with exceptions in select copy number variants and markers in certain genes (notably CYP2D6). Most of the common variants on the ADME panel are genotyped by the Omni1, but absent rare variants and copy number variants could not be accurately tagged by single markers. CONCLUSION: Our frequently medicated study population did not convincingly differ in allele frequency from reference populations, suggesting that heterogeneous clinical samples (with respect to medications) have similar allele frequency distributions in pharmacogenetics genes compared with reference populations.

Robust replication of genotype-phenotype associations across multiple diseases in an electronic medical record.

Large-scale DNA databanks linked to electronic medical record (EMR) systems have been proposed as an approach for rapidly generating large, diverse cohorts for discovery and replication of genotype-phenotype associations. However, the extent to which such resources are capable of delivering on this promise is unknown. We studied whether an EMR-linked DNA biorepository can be used to detect known genotype-phenotype associations for five diseases. Twenty-one SNPs previously implicated as common variants predisposing to atrial fibrillation, Crohn disease, multiple sclerosis, rheumatoid arthritis, or type 2 diabetes were successfully genotyped in 9483 samples accrued over 4 mo into BioVU, the Vanderbilt University Medical Center DNA biobank. Previously reported odds ratios (OR(PR)) ranged from 1.14 to 2.36. For each phenotype, natural language processing techniques and billing-code queries were used to identify cases (n = 70-698) and controls (n = 808-3818) from deidentified health records. Each of the 21 tests of association yielded point estimates in the expected direction. Previous genotype-phenotype associations were replicated (p < 0.05) in 8/14 cases when the OR(PR) was > 1.25, and in 0/7 with lower OR(PR). Statistically significant associations were detected in all analyses that were adequately powered. In each of the five diseases studied, at least one previously reported association was replicated. These data demonstrate that phenotypes representing clinical diagnoses can be extracted from EMR systems, and they support the use of DNA resources coupled to EMR systems as tools for rapid generation of large data sets required for replication of associations found in research cohorts and for discovery in genome science.

PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations.

MOTIVATION: Emergence of genetic data coupled to longitudinal electronic medical records (EMRs) offers the possibility of phenome-wide association scans (PheWAS) for disease-gene associations. We propose a novel method to scan phenomic data for genetic associations using International Classification of Disease (ICD9) billing codes, which are available in most EMR systems. We have developed a code translation table to automatically define 776 different disease populations and their controls using prevalent ICD9 codes derived from EMR data. As a proof of concept of this algorithm, we genotyped the first 6005 European-Americans accrued into BioVU, Vanderbilt's DNA biobank, at five single nucleotide polymorphisms (SNPs) with previously reported disease associations: atrial fibrillation, Crohn's disease, carotid artery stenosis, coronary artery disease, multiple sclerosis, systemic lupus erythematosus and rheumatoid arthritis. The PheWAS software generated cases and control populations across all ICD9 code groups for each of these five SNPs, and disease-SNP associations were analyzed. The primary outcome of this study was replication of seven previously known SNP-disease associations for these SNPs. RESULTS: Four of seven known SNP-disease associations using the PheWAS algorithm were replicated with P-values between 2.8 x 10(-6) and 0.011. The PheWAS algorithm also identified 19 previously unknown statistical associations between these SNPs and diseases at P < 0.01. This study indicates that PheWAS analysis is a feasible method to investigate SNP-disease associations. Further evaluation is needed to determine the validity of these associations and the appropriate statistical thresholds for clinical significance. AVAILABILITY: The PheWAS software and code translation table are freely available at http://knowledgemap.mc.vanderbilt.edu/research.