47 research outputs found

    Evaluating the Clinical Validity of Gene-Disease Associations: An Evidence-Based Framework Developed by the Clinical Genome Resource

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    Supplemental Data Supplemental Data include 65 figures and can be found with this article online at http://dx.doi.org/10.1016/j.ajhg.2017.04.015. Supplemental Data Document S1. Figures S1–S65 Download Document S2. Article plus Supplemental Data Download Web Resources ClinGen, https://www.clinicalgenome.org/ ClinGen Gene Curation, https://www.clinicalgenome.org/working-groups/gene-curation/ ClinGen Gene Curation SOP, https://www.clinicalgenome.org/working-groups/gene-curation/projects-initiatives/gene-disease-clinical-validity-sop/ ClinGen Knowledge Base, https://search.clinicalgenome.org/kb/agents/sign_up OMIM, http://www.omim.org/ Orphanet, http://www.orpha.net/consor/cgi-bin/index.php With advances in genomic sequencing technology, the number of reported gene-disease relationships has rapidly expanded. However, the evidence supporting these claims varies widely, confounding accurate evaluation of genomic variation in a clinical setting. Despite the critical need to differentiate clinically valid relationships from less well-substantiated relationships, standard guidelines for such evaluation do not currently exist. The NIH-funded Clinical Genome Resource (ClinGen) has developed a framework to define and evaluate the clinical validity of gene-disease pairs across a variety of Mendelian disorders. In this manuscript we describe a proposed framework to evaluate relevant genetic and experimental evidence supporting or contradicting a gene-disease relationship and the subsequent validation of this framework using a set of representative gene-disease pairs. The framework provides a semiquantitative measurement for the strength of evidence of a gene-disease relationship that correlates to a qualitative classification: “Definitive,” “Strong,” “Moderate,” “Limited,” “No Reported Evidence,” or “Conflicting Evidence.” Within the ClinGen structure, classifications derived with this framework are reviewed and confirmed or adjusted based on clinical expertise of appropriate disease experts. Detailed guidance for utilizing this framework and access to the curation interface is available on our website. This evidence-based, systematic method to assess the strength of gene-disease relationships will facilitate more knowledgeable utilization of genomic variants in clinical and research settings

    Effect of genetic testing for risk of type 2 diabetes mellitus on health behaviors and outcomes: study rationale, development and design

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    <p>Abstract</p> <p>Background</p> <p>Type 2 diabetes is a prevalent chronic condition globally that results in extensive morbidity, decreased quality of life, and increased health services utilization. Lifestyle changes can prevent the development of diabetes, but require patient engagement. Genetic risk testing might represent a new tool to increase patients' motivation for lifestyle changes. Here we describe the rationale, development, and design of a randomized controlled trial (RCT) assessing the clinical and personal utility of incorporating type 2 diabetes genetic risk testing into comprehensive diabetes risk assessments performed in a primary care setting.</p> <p>Methods/Design</p> <p>Patients are recruited in the laboratory waiting areas of two primary care clinics and enrolled into one of three study arms. Those interested in genetic risk testing are randomized to receive <it>either </it>a standard risk assessment (SRA) for type 2 diabetes incorporating conventional risk factors plus upfront disclosure of the results of genetic risk testing ("SRA+G" arm), <it>or </it>the SRA alone ("SRA" arm). Participants not interested in genetic risk testing will not receive the test, but will receive SRA (forming a third, "no-test" arm). Risk counseling is provided by clinic staff (not study staff external to the clinic). Fasting plasma glucose, insulin levels, body mass index (BMI), and waist circumference are measured at baseline and 12 months, as are patients' self-reported behavioral and emotional responses to diabetes risk information. Primary outcomes are changes in insulin resistance and BMI after 12 months; secondary outcomes include changes in diet patterns, physical activity, waist circumference, and perceived risk of developing diabetes.</p> <p>Discussion</p> <p>The utility, feasibility, and efficacy of providing patients with genetic risk information for common chronic diseases in primary care remain unknown. The study described here will help to establish whether providing type 2 diabetes genetic risk information in a primary care setting can help improve patients' clinical outcomes, risk perceptions, and/or their engagement in healthy behavior change. In addition, study design features such as the use of existing clinic personnel for risk counseling could inform the future development and implementation of care models for the use of individual genetic risk information in primary care.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00849563">NCT00849563</a></p

    Question prompt lists and caregiver question asking in pediatric specialty appointments: A randomized controlled trial

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    Objective: Question prompt lists (QPLs) have been effective at increasing patient involvement and question asking in medical appointments, which is critical for shared decision making. We investigated whether pre-visit preparation (PVP), including a QPL, would increase question asking among caregivers of pediatric patients with undiagnosed, suspected genetic conditions. Methods: Caregivers were randomized to receive the PVP before their appointment (n = 59) or not (control, n = 53). Appointments were audio-recorded. Transcripts were analyzed to determine questions asked. Results: Caregivers in the PVP group asked more questions (MeanPVP = 4.36, SDPVP = 4.66 vs. Meancontrol = 2.83, SDcontrol = 3.03, p = 0.045), including QPL questions (MeanPVP = 1.05, SDPVP = 1.39 vs. Meancontrol = 0.36, SDcontrol = 0.81, p = 0.002). Caregivers whose child had insurance other than Medicaid in the PVP group asked more total and QPL questions than their counterparts in the control group (ps = 0.005 and 0.002); there was no intervention effect among caregivers of children with Medicaid or no insurance (ps = 0.775 and 0.166). Conclusion: The PVP increased question asking but worked less effectively among traditionally underserved groups. Additional interventions, including provider-focused efforts, may be needed to promote engagement of underserved patients. Practice implications: Patient/family-focused interventions may not be beneficial for all populations. Providers should be aware of potential implicit and explicit biases and encourage question asking to promote patient/family engagement

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