1,720,998 research outputs found
Pharmacogenomics polygenic risk score: Ready or not for prime time?
Get PDFPharmacogenomic Polygenic Risk Scores (PRS) have emerged as a tool to address the polygenic nature of pharmacogenetic phenotypes, increasing the potential to predict drug response. Most pharmacogenomic PRS have been extrapolated from disease-associated variants identified by genome wide association studies (GWAS), although some have begun to utilize genetic variants from pharmacogenomic GWAS. As pharmacogenomic PRS hold the promise of enabling precision medicine, including stratified treatment approaches, it is important to assess the opportunities and challenges presented by the current data. This assessment will help determine how pharmacogenomic PRS can be advanced and transitioned into clinical use. In this review, we present a summary of recent evidence, evaluate the current status, and identify several challenges that have impeded the progress of pharmacogenomic PRS. These challenges include the reliance on extrapolations from disease genetics and limitations inherent to pharmacogenomics research such as low sample sizes, phenotyping inconsistencies, among others. We finally propose recommendations to overcome the challenges and facilitate the clinical implementation. These recommendations include standardizing methodologies for phenotyping, enhancing collaborative efforts, developing new statistical methods to capitalize on drug-specific genetic associations for PRS construction. Additional recommendations include enhancing the infrastructure that can integrate genomic data with clinical predictors, along with implementing user-friendly clinical decision tools, and patient education. Ethical and regulatory considerations should address issues related to patient privacy, informed consent and safe use of PRS. Despite these challenges, ongoing research and large-scale collaboration is likely to advance the field and realize the potential of pharmacogenomic PRS
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Recommended from our members
Increasing Inclusion of Participants, Leveraging Gut Microbiomes, and Optimizing Machine Learning Models to Advance Warfarin Precision Medicine
No full textPrecision medicine, one of the promises of the future of clinical medicine, will not be realized without challenges. Here, focusing on an individual pharmaceutical therapeutic, warfarin, we demonstrate idealistic benefits, realistic caveats, and paths to improving the benefits and equity of precision medicine through rigorous research. Anticoagulation therapy with the popular vitamin K antagonist, warfarin, can be challenging due to large interpatient dose variability and a narrow therapeutic window. Warfarin genotype-guided dose prediction models currently can account for approximately 50% of the total variability seen across patients, however, this number can also be as low as 20% in diverse populations. This lack of equity and overall dismal performance of genotype-guided dosing has reasonably slowed the clinical implementation of warfarin dose predictions models and is a driving force of the research projects presented here. The paths that we suggest for improving future benefits of precision medicine research: 1) consciously include everyone, 2) survey the environment, regardless of temporal stability, and 3) validate the generalizations we make. In this thesis we briefly introduce the fields of pharmacogenetics, pharmacomicrobiomics, and statistical modeling to provide evidence for each of the previous suggestions demonstrated by the attached appendices. Finally, we make predictions regarding the future of warfarin precision medicine
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Recommended from our members
Warfarin Pharmacogenomics in a Hispanic Population: A Candidate SNP Study
No full textBackground: Warfarin remains one of the most widely prescribed anticoagulants but is also a leading cause of adverse drug reactions. Genotype-guided warfarin dosing algorithms enable accurate dose estimation, potentially leading to improved safety and efficacy. However, genotype-guided dosing algorithms were developed primarily in populations of European descent and limited data are available regarding single nucleotide polymorphisms (SNPs) that significantly influence warfarin dose in Hispanic populations.
Research Aim: The objective of this study was to determine whether clinical factors and SNPs previously associated with stable warfarin dose variability in populations of European and Hispanic descent accurately predicted warfarin stable dose in a Hispanic population.
Study Design: Self-reported Hispanic and Latino patients on stable warfarin dose (defined as the same dose for at least two clinic visits separated by at least two weeks) were recruited.
Methods: Candidate SNPs, including CYP2C9*2/*3, VKORC1-1639G>A, CYP4F2*3, and NQO1*2, were genotyped and clinical data were collected using a survey and the electronic medical record. Stepwise linear regression was performed to determine variables that significantly predicted square root of weekly warfarin dose.
Results: A total of 76 patients of primarily Mexican American ancestry participated. All SNPs were within Hardy-Weinberg Equilibrium. The final stepwise regression model incorporated six variables, which explained 71% of the variability in warfarin weekly dose requirements. Significant predictors included weight (R2=0.287, p<0.0001), age (R2=0.143, p<0.0001), amiodarone use (R2=0.067, p=0.0005), and prior stroke (R2=0.025, p=0.02). Significant SNPs included VKORC1-1639A (R2=0.152, p<0.0001), and CYP2C9*2/*3 (R2=0.032, p=0.02). CYP4F2*3 and NQO1*2 did not significantly impact warfarin dose requirements despite previously published associations in Hispanic populations.
Conclusion: These findings suggest that clinical and genetic predictors of warfarin weekly dose requirements are similar among populations of European descent and Hispanic populations with Mexican American ancestry. These results require replication and validation in independent cohorts with similar ethnicity, but advance our understanding of influences on warfarin dose variability among different race/ethnic groups
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
- …
