Performance of random forests and logic regression methods using mini-exome sequence data

Machine learning approaches are an attractive option for analyzing large-scale data to detect genetic variants that contribute to variation of a quantitative trait, without requiring specific distributional assumptions. We evaluate two machine learning methods, random forests and logic regression, and compare them to standard simple univariate linear regression, using the Genetic Analysis Workshop 17 mini-exome data. We also apply these methods after collapsing multiple rare variants within genes and within gene pathways. Linear regression and the random forest method performed better when rare variants were collapsed based on genes or gene pathways than when each variant was analyzed separately. Logic regression performed better when rare variants were collapsed based on genes rather than on pathways

Comparison of results from tests of association in unrelated individuals with uncollapsed and collapsed sequence variants using tiled regression

Tiled regression is an approach designed to determine the set of independent genetic variants that contribute to the variation of a quantitative trait in the presence of many highly correlated variants. In this study, we evaluate the statistical properties of the tiled regression method using the Genetic Analysis Workshop 17 data in unrelated individuals for traits Q1, Q2, and Q4. To increase the power to detect rare variants, we use two methods to collapse rare variants and compare the results with those from the uncollapsed data. In addition, we compare the tiled regression method to traditional tests of association with and without collapsed rare variants. The results show that collapsing rare variants generally improves the power to detect associations regardless of method, although only variants with the largest allelic effects could be detected. However, for traditional simple linear regression, the average estimated type I error is dependent on the trait and varies by about three orders of magnitude. The estimated type I error rate is stable for tiled regression across traits

Chromosomes 4 and 8 implicated in a genome wide SNP linkage scan of 762 prostate cancer families collected by the ICPCG

BACKGROUND In spite of intensive efforts, understanding of the genetic aspects of familial prostate cancer (PC) remains largely incomplete. In a previous microsatellite‐based linkage scan of 1,233 PC families, we identified suggestive evidence for linkage (i.e., LOD ≥ 1.86) at 5q12, 15q11, 17q21, 22q12, and two loci on 8p, with additional regions implicated in subsets of families defined by age at diagnosis, disease aggressiveness, or number of affected members. METHODS In an attempt to replicate these findings and increase linkage resolution, we used the Illumina 6000 SNP linkage panel to perform a genome‐wide linkage scan of an independent set of 762 multiplex PC families, collected by 11 International Consortium for Prostate Cancer Genetics (ICPCG) groups. RESULTS Of the regions identified previously, modest evidence of replication was observed only on the short arm of chromosome 8, where HLOD scores of 1.63 and 3.60 were observed in the complete set of families and families with young average age at diagnosis, respectively. The most significant linkage signals found in the complete set of families were observed across a broad, 37 cM interval on 4q13–25, with LOD scores ranging from 2.02 to 2.62, increasing to 4.50 in families with older average age at diagnosis. In families with multiple cases presenting with more aggressive disease, LOD scores over 3.0 were observed at 8q24 in the vicinity of previously identified common PC risk variants, as well as MYC , an important gene in PC biology. CONCLUSIONS These results will be useful in prioritizing future susceptibility gene discovery efforts in this common cancer. Prostate 72:410–426, 2012. © 2011 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90245/1/21443_ftp.pd

Analysis of Xq27-28 linkage in the international consortium for prostate cancer genetics (ICPCG) families.

BACKGROUND: Genetic variants are likely to contribute to a portion of prostate cancer risk. Full elucidation of the genetic etiology of prostate cancer is difficult because of incomplete penetrance and genetic and phenotypic heterogeneity. Current evidence suggests that genetic linkage to prostate cancer has been found on several chromosomes including the X; however, identification of causative genes has been elusive. METHODS: Parametric and non-parametric linkage analyses were performed using 26 microsatellite markers in each of 11 groups of multiple-case prostate cancer families from the International Consortium for Prostate Cancer Genetics (ICPCG). Meta-analyses of the resultant family-specific linkage statistics across the entire 1,323 families and in several predefined subsets were then performed. RESULTS: Meta-analyses of linkage statistics resulted in a maximum parametric heterogeneity lod score (HLOD) of 1.28, and an allele-sharing lod score (LOD) of 2.0 in favor of linkage to Xq27-q28 at 138 cM. In subset analyses, families with average age at onset less than 65 years exhibited a maximum HLOD of 1.8 (at 138 cM) versus a maximum regional HLOD of only 0.32 in families with average age at onset of 65 years or older. Surprisingly, the subset of families with only 2-3 affected men and some evidence of male-to-male transmission of prostate cancer gave the strongest evidence of linkage to the region (HLOD = 3.24, 134 cM). For this subset, the HLOD was slightly increased (HLOD = 3.47 at 134 cM) when families used in the original published report of linkage to Xq27-28 were excluded. CONCLUSIONS: Although there was not strong support for linkage to the Xq27-28 region in the complete set of families, the subset of families with earlier age at onset exhibited more evidence of linkage than families with later onset of disease. A subset of families with 2-3 affected individuals and with some evidence of male to male disease transmission showed stronger linkage signals. Our results suggest that the genetic basis for prostate cancer in our families is much more complex than a single susceptibility locus on the X chromosome, and that future explorations of the Xq27-28 region should focus on the subset of families identified here with the strongest evidence of linkage to this region.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Pharmacy Student Perceptions of a Virtual Pharmacogenomics Activity

Pharmacogenomics (PGx) utilizes a patient’s genome to guide drug treatment and dosing. The Accreditation Council for Pharmacy Education (ACPE) included PGx as a critical content area. Pharmacists are increasingly involved in providing this service, which necessitates training. Second-year pharmacy students at Samford University McWhorter School of Pharmacy have didactic training in the principles of PGx and managing drug therapy using PGx data. A clinical skills lab activity was developed to reinforce these principles and allow students to navigate resources to develop and communicate recommendations for drug therapy. The activity was initially planned as synchronous, but transitioned to asynchronous when students began remote learning in the spring of 2020 due to the COVID-19 pandemic. The investigators sought students’ perceptions of the PGx lab activity and the delivery of its content via a virtual format. This study gathered data from an anonymous, voluntary student survey through Samford University’s course management system, Canvas, in the spring of 2020 soon after completion of the virtual PGx learning activity. The investigators’ goal is to obtain the information and insights obtained from the students who participated in the PGx lab activity to provide guidance for the improvement of their PGx lab activity and for other schools of pharmacy to deliver a PGx lab activities using nontraditional teaching methodologies

Interprofessional Pharmacokinetics Simulation: Pharmacy and Nursing Students’ Perceptions

Interprofessional practice between pharmacists and nurses can involve pharmacokinetic dosing of medications in a hospital setting. This study describes student perceptions of an interprofessional collaboration pharmacokinetics simulation on the Interprofessional Education Collaborative (IPEC) 2016 Core Competencies. The investigators developed a simulation activity for senior undergraduate nursing and second-year pharmacy students. Nursing and pharmacy students (n = 54, 91 respectively) participated in the simulation using medium-fidelity manikins. Each case represented a pharmacokinetic dosing consult (vancomycin, tobramycin, phenytoin, theophylline, or lidocaine). Nursing students completed head-to-toe assessment and pharmacy students gathered necessary information and calculated empiric and adjusted doses. Students communicated using SBAR (Situation, Background, Assessment, and Recommendation). Students participated in debrief sessions and completed an IRB-approved online survey. Themes from survey responses revealed meaningful perceptions in all IPEC competencies as well as themes of safety, advocacy, appreciation, and areas for improvement. Students reported learning effectively from the simulation experience. Few studies relate to this type of interprofessional education experience and this study begins to explore student perceptions of interprofessional education (IPE) in a health sciences clinical context through simulation. This real-world application of nursing and pharmacy interprofessional collaboration can positively affect patient-centered outcomes and safety

Prevalence of the UGT1A1*28 Promoter Polymorphism and Breast Cancer Risk Among African American Women in Memphis, TN

Inherited variations in UDP-glucuronosyltransferase 1A1 (UGT1A1) are associated with an increased breast cancer risk in women of African ancestry.  The UGT1A1*28 promoter polymorphism is characterized by the presence of 7 TA repeats in the TATA box sequence and results in reduced UGT1A1 gene expression and enzymatic activity. In this study, we investigated associations between the UGT1A1*28 polymorphism and breast cancer risk among African American (AA) women in Memphis, Tennessee, a city with increased breast cancer mortality rates among AA women.  Saliva was collected from 352 AA women, including breast cancer cases (n=82) and controls (n=270) between June 2016 to June 2017. DNA was isolated and sequenced for the UGT1A1*28 polymorphism. The odds ratio for cases with the low UGT1A1 activity alleles (TA)7/8 repeat genotypes versus 5/5, 5/6, and 6/6 genotypes was 1.46 [95% CI, 0.65-3.31; P = 0.36] in premenopausal women and 1.10 (95% CI, 0.52-2.38; P = 0.79) in postmenopausal women.  Further analysis of TCGA RNA-seq data showed that UGT1A1 mRNA was significantly lower among estrogen receptor (ER)-negative breast cancers from AA as compared to non-Hispanic white women with ER-negative breast cancer.  Larger epidemiological studies are needed to determine the functional consequence of the UGT1A1*28 polymorphism on breast cancer risk in AA women