1,721,006 research outputs found
Pharmacogenomics polygenic risk score: Ready or not for prime time?
Full text linkPharmacogenomic 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
Full text linkThe 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
Defining clinical applications of a polygenic score for height in the pediatric setting
No full textPolygenic scores (PGS) aim to capture a person’s genetic predisposition to a disease or trait. There is substantial interest in applying PGS to clinical settings to identify patients at elevated risk for disease. Given its high heritability, height is a particularly promising trait for the study of clinical applications of PGS. We first performed a cross-ancestry validation of a recently developed height PGS in adult (N=61,701) and pediatric (N=9,088) cohorts. We show that variance explained by the PGS decreases when applied in non-European compared to European ancestries. Variance explained also decreases when applied in children compared to adults, particularly during onset of the pubertal growth spurt. We then show that the PGS associates with having short stature and clinical utilization related to short stature, including ICD codes for short stature and referrals to endocrinology. We then curated a cohort of pediatric patients evaluated by endocrinology for short stature. This cohort included 225 patients with short stature secondary to pathology and 114 patients without an explanation for their short stature (i.e., idiopathic short stature) even after extensive testing. We show that a lower height PGS is associated with idiopathic short stature, while the current standard for height prediction, mid-parental height, is not. We show that a PGS improves discrimination between idiopathic and pathologic short stature when added to a baseline model. In summary, a PGS associates with height and short stature-related clinical outcomes and discriminates idiopathic from pathologic short stature. However, portability between ancestries remains a barrier to implementation
Variations on the Author
Full text link“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
The impact of benign genetic variation on clinical misclassification and overtreatment in biomarker-driven care
No full textDiagnostic biomarkers such as laboratory tests guide clinician decision-making, but interpretation relies on reference intervals and clinical decision thresholds derived from populations that may be either unrepresentative or under sample the populations to which the thresholds are applied. Traditional approaches can adjust for measurable sources of variability, such as age and sex, but a growing body of evidence indicates that individuals possess stable biomarker "set points" that are genetically influenced and not accounted for in current practice. Misalignment of clinical decision thresholds to these set points can lead to misclassification, unnecessary procedures, and extensive diagnostic uncertainty. We hypothesize that benign genetic variation underlies many unnecessary diagnostic odysseys and can be used as a risk stratification tool to reduce unnecessary testing and interventions. In the first application, we demonstrate that a benign genetic predisposition to higher prostate-specific antigen (PSA) increases the risk of urology referrals for false-positive PSA elevations. In patients undergoing prostate biopsy, genetically elevated PSA was associated with a lower likelihood of prostate cancer. In evaluations for underlying pathology in children with unexplained short stature, polygenic scores for height effectively distinguish between benign polygenic short stature and pathologic growth disorders, particularly among patients whose average parental heights do not accurately reflect their genetic predisposition. Finally, we observe that polygenic variation underlying neutrophil counts further increases the risk of benign neutropenia in patients with the Duffy null genotype. This genotype, present in two-thirds of patients of African ancestry, causes a benign form of neutropenia that can predispose patients to unnecessary bone marrow biopsies and chemotherapy modifications due to provider concerns for a low neutrophil count. Using a polygenic score, we create genotype-adjusted reference ranges for neutrophil counts, demonstrating a proactive approach to preventing inappropriate referrals. Together, these findings demonstrate the value of genetic personalization in biomarker interpretation, reducing diagnostic uncertainty and unnecessary diagnostic odysseys and interventions
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe 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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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
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