Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

Abstract The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared to information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known non-pathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification. This article is protected by copyright. All rights reserved.Peer reviewe

An Evaluation Of Luria's Theory Of Verbal Control Of Motor Actions With Regard To A Dual Response To One Stimulus.

PhDExperimentsPsychologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/186885/2/7204988.pd

Awareness of symptoms and risk factors of ovarian cancer in a population of women and healthcare providers

Background: Awareness of ovarian cancer among women and healthcare providers is understudied. An early awareness of ovarian cancer may lead to early detection and treatment of ovarian cancer. Objectives: The purpose of this study was to determine the level of that awareness among a sample of women and providers. Methods: Written surveys were developed by the authors based on available literature and were administered to women (n = 857) and healthcare providers (n = 188) attending or volunteering at a community health fair. Chi-square tests for independence and z tests were used for analysis. Findings: Healthcare providers were significantly more likely to identify the symptoms and risk factors for ovarian cancer. Forty percent of women reported being at least slightly familiar with the symptoms of ovarian cancer. Women who were familiar with symptoms were significantly more likely to identify symptoms and risk factors correctly and to report symptoms immediately to a provider. Identification of symptoms among healthcare providers ranged from 59%–93%. Identification of ovarian cancer symptoms and risk factors is poor among women, and knowledge deficits are present in providers. Increasing familiarity and awareness could lead to improvements in early diagnosis

License Analysis of e-Journal Perpetual Access

In this paper we investigate the definitions of perpetual access and examine current studies on the attitudes and concerns towards perpetual access from both libraries and publishers separately. We then conduct a content analysis of 72 e-journal licenses to explore whether perpetual access clauses vary among commercial publishers and non-commercial publishers, whether clauses change over time, and whether differences exist between consortium and site licenses. Results suggest that different perpetual access clauses may be at different stages of institutionalization. Perpetual access clauses that are more institutionalized include: addressing perpetual access in license, providing perpetual access upon expiry of subscription, and specifying a location for perpetual access