Psychological and Genetic Predictors of Pain Tolerance

Previous studies have shown associations between genetic polymorphisms and pain tolerance, but psychological evaluations are seldom measured. The objective of this study was to determine the independent effects of demographic, psychological, and genetic predictors of cold noxious pain tolerance. Healthy subjects (n = 89) completed the Pain Catastrophizing Scale (PCS) and Fear of Pain Questionnaire (FPQ-III), underwent genotyping for candidate single nucleotide polymorphisms (SNPs), and completed a cold-pressor test in a 1-2 degrees C water bath for a maximum of 3 minutes. The primary outcome measure was pain tolerance, defined as the maximum duration of time subjects left their nondominant hand in the cold-water bath. Cox proportional hazards regression indicated that female sex, Asian race, and increasing PCS and FPQ-III scores were associated with lower pain tolerance. No candidate SNP was significantly associated with pain tolerance. Future genetic studies should include demographic and psychological variables as confounders in experimental pain models.Open access journal.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Comparison of family health history in surveys vs electronic health record data mapped to the observational medical outcomes partnership data model in the All of Us Research Program

OBJECTIVE: Family health history is important to clinical care and precision medicine. Prior studies show gaps in data collected from patient surveys and electronic health records (EHRs). The All of Us Research Program collects family history from participants via surveys and EHRs. This Demonstration Project aims to evaluate availability of family health history information within the publicly available data from All of Us and to characterize the data from both sources. MATERIALS AND METHODS: Surveys were completed by participants on an electronic portal. EHR data was mapped to the Observational Medical Outcomes Partnership data model. We used descriptive statistics to perform exploratory analysis of the data, including evaluating a list of medically actionable genetic disorders. We performed a subanalysis on participants who had both survey and EHR data. RESULTS: There were 54 872 participants with family history data. Of those, 26% had EHR data only, 63% had survey only, and 10.5% had data from both sources. There were 35 217 participants with reported family history of a medically actionable genetic disorder (9% from EHR only, 89% from surveys, and 2% from both). In the subanalysis, we found inconsistencies between the surveys and EHRs. More details came from surveys. When both mentioned a similar disease, the source of truth was unclear. CONCLUSIONS: Compiling data from both surveys and EHR can provide a more comprehensive source for family health history, but informatics challenges and opportunities exist. Access to more complete understanding of a person\u27s family health history may provide opportunities for precision medicine

From Big Data to Precision Medicine.

For over a decade the term "Big data" has been used to describe the rapid increase in volume, variety and velocity of information available, not just in medical research but in almost every aspect of our lives. As scientists, we now have the capacity to rapidly generate, store and analyse data that, only a few years ago, would have taken many years to compile. However, "Big data" no longer means what it once did. The term has expanded and now refers not to just large data volume, but to our increasing ability to analyse and interpret those data. Tautologies such as "data analytics" and "data science" have emerged to describe approaches to the volume of available information as it grows ever larger. New methods dedicated to improving data collection, storage, cleaning, processing and interpretation continue to be developed, although not always by, or for, medical researchers. Exploiting new tools to extract meaning from large volume information has the potential to drive real change in clinical practice, from personalized therapy and intelligent drug design to population screening and electronic health record mining. As ever, where new technology promises "Big Advances," significant challenges remain. Here we discuss both the opportunities and challenges posed to biomedical research by our increasing ability to tackle large datasets. Important challenges include the need for standardization of data content, format, and clinical definitions, a heightened need for collaborative networks with sharing of both data and expertise and, perhaps most importantly, a need to reconsider how and when analytic methodology is taught to medical researchers. We also set "Big data" analytics in context: recent advances may appear to promise a revolution, sweeping away conventional approaches to medical science. However, their real promise lies in their synergy with, not replacement of, classical hypothesis-driven methods. The generation of novel, data-driven hypotheses based on interpretable models will always require stringent validation and experimental testing. Thus, hypothesis-generating research founded on large datasets adds to, rather than replaces, traditional hypothesis driven science. Each can benefit from the other and it is through using both that we can improve clinical practice.Wellcome Trus

The Frequency of Pathogenic Variation in the All of Us Cohort Reveals Ancestry-Driven Disparities

Disparities in data underlying clinical genomic interpretation is an acknowledged problem, but there is a paucity of data demonstrating it. The All of Us Research Program is collecting data including whole-genome sequences, health records, and surveys for at least a million participants with diverse ancestry and access to healthcare, representing one of the largest biomedical research repositories of its kind. Here, we examine pathogenic and likely pathogenic variants that were identified in the All of Us cohort. The European ancestry subgroup showed the highest overall rate of pathogenic variation, with 2.26% of participants having a pathogenic variant. Other ancestry groups had lower rates of pathogenic variation, including 1.62% for the African ancestry group and 1.32% in the Latino/Admixed American ancestry group. Pathogenic variants were most frequently observed in genes related to Breast/Ovarian Cancer or Hypercholesterolemia. Variant frequencies in many genes were consistent with the data from the public gnomAD database, with some notable exceptions resolved using gnomAD subsets. Differences in pathogenic variant frequency observed between ancestral groups generally indicate biases of ascertainment of knowledge about those variants, but some deviations may be indicative of differences in disease prevalence. This work will allow targeted precision medicine efforts at revealed disparities

PRN OPINION PAPER: Application of precision medicine across pharmacy specialty areas

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149551/1/jac51107_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149551/2/jac51107.pd

Role of Primary Tumor Resection Among Chemotherapy-Treated Patients with Synchronous Stage IV Colorectal Cancer: A Survival Analysis

INTRODUCTION: The benefit of an operation to remove the primary tumor among patients with synchronous stage IV colorectal cancer is controversial. This study analyzed the survival benefits associated with primary tumor resection among chemotherapy-treated stage IV colorectal cancer patients. METHODS: The study analyzed 11,716 chemotherapy-treated stage IV colorectal cancer patients in the California Cancer Registry between 1996 and 2007, with follow-up through 2009. Patients were stratified into operation and non-operation groups. Estimates of median overall and colorectal cancer-specific survival were generated. RESULTS: Patients undergoing operation compared to those who are not had higher median overall and colorectal cancer-specific survival, 21 versus 10 months (p <0.0001) and 22 versus 12 months (p <0.0001), respectively. Patients who were offered surgery but refused had decreased median overall and colorectal cancer-specific survival when compared to patients who underwent resection, 8 versus 21 months (p <0.001) and 7 versus 22 months (p <0.001), respectively. In multivariate regression models, patients who underwent resection of primary tumor had improved overall (hazard ratio (HR), 0.42; 95 % confidence interval (CI) 0.40–0.44, p <0.0001) and colorectal cancer-specific survival (HR, 0.43; 95 % CI, 0.41–0.45; p <0.0001). CONCLUSION: Primary tumor resection is associated with improved survival among stage IV chemotherapy-treated colorectal cancer patients

Pharmacogenetics to prevent heparin-induced thrombocytopenia: what do we know?

Heparin-induced thrombocytopenia (HIT) is a life-threatening, immune-mediated adverse reaction to heparin anticoagulants. The inability to predict HIT represents a considerable liability associated with heparin administration. Genetic studies of HIT are challenging due to the scarcity of true HIT cases, potential for misclassification, and many environmental risk factors. Genetic studies have not consistently identified risk alleles for HIT, the production of platelet factor 4/heparin antibodies or the thromboembolic complications of HIT. Genes implicated in HIT and platelet factor 4/heparin antibody levels include FCGR2A, TDAG8, HLA-DR and others. Compelling evidence also suggests that the FCGR2A H131R polymorphism is associated with HIT-related thrombosis. There is a need for well-powered, multiethnic studies with laboratory confirmation of HIT, detailed patient- and drug-specific data, and inclusion of both serologic and thromboembolic outcomes. Genomic biomarkers identified from such studies offer the possibility of shifting current clinical practice paradigms from early detection and treatment to prevention.American Heart Association [16SDG29090005]; American College of Clinical Pharmacy Research Institute (Futures Grant)12 month embargo; published online: 6 November 2018This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Differential drug response in pulmonary arterial hypertension: The potential for precision medicine

Abstract Pulmonary arterial hypertension (PAH) is a rare, complex, and deadly cardiopulmonary disease. It is characterized by changes in endothelial cell function and smooth muscle cell proliferation in the pulmonary arteries, causing persistent vasoconstriction, resulting in right heart hypertrophy and failure. There are multiple drug classes specific to PAH treatment, but variation between patients may impact treatment response. A small subset of patients is responsive to pulmonary vasodilators and can be treated with calcium channel blockers, which would be deleterious if prescribed to a typical PAH patient. Little is known about the underlying cause of this important difference in vasoresponsive PAH patients. Sex, race/ethnicity, and pharmacogenomics may also factor into efficacy and safety of PAH‐specific drugs. Research has indicated that endothelin receptor antagonists may be more effective in women and there have been some minor differences found in certain races and ethnicities, but these findings are muddled by the impact of socioeconomic factors and a lack of representation of non‐White patients in clinical trials. Genetic variants in genes such as CYP3A5, CYP2C9, PTGIS, PTGIR, GNG2, CHST3, and CHST13 may influence the efficacy and safety of certain PAH‐specific drugs. PAH research faces many challenges, but there is potential for new methodologies to glean new insights into PAH development and treatment