156 research outputs found
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Experiences and Attitudes of Genome Investigators Regarding Return of Individual Genetic Test Results
Purpose Whether and how to return individual genetic results to study participants is among the most contentious policy issues in contemporary genomic research. Methods: We surveyed corresponding authors of genome-wide association studies (GWAS), identified through the National Human Genome Research Institute's Catalog of Published GWAS, to describe the experiences and attitudes of these stakeholders. Results: Of 357 corresponding authors, 200 (56%) responded. One hundred twenty-six (63%) had been responsible for primary data and sample collection, whereas 74 (37%) had performed secondary analyses. Only 7 (4%) had returned individual results within their index GWAS. Most (69%) believed that return of results to individual participants was warranted under at least some circumstances. Most respondents identified a desire to benefit participants's health (63%) and respect for participants's; desires for information (57%) as major motivations for returning results. Most also identified uncertain clinical utility (76%), the possibility that participants will misunderstand results (74%), the potential for emotional harm (61%), the need to ensure access to trained clinicians (59%), and the potential for loss of confidentiality (51%) as major barriers to return. Conclusion: Investigators have limited experience returning individual results from genome-scale research, yet most are motivated to do so in at least some circumstances
Pediatric Cancer Genetics Research and an Evolving Preventive Ethics Approach for Return of Results after Death of the Subject
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/115941/1/jlme12295.pd
Defective mitochondrial peroxiredoxin-3 results in sensitivity to oxidative stress in Fanconi anemia
Cells from patients with Fanconi anemia (FA), an inherited disorder that includes bone marrow failure and cancer predisposition, have increased sensitivity to oxidative stress through an unknown mechanism. We demonstrate that the FA group G (FANCG) protein is found in mitochondria. Wild-type but not G546R mutant FANCG physically interacts with the mitochondrial peroxidase peroxiredoxin-3 (PRDX3). PRDX3 is deregulated in FA cells, including cleavage by a calpainlike cysteine protease and mislocalization. FA-G cells demonstrate distorted mitochondrial structures, and mitochondrial extracts have a sevenfold decrease in thioredoxin-dependent peroxidase activity. Transient overexpression of PRDX3 suppresses the sensitivity of FA-G cells to H2O2, and decreased PRDX3 expression increases sensitivity to mitomycin C. Cells from the FA-A and -C subtypes also have PRDX3 cleavage and decreased peroxidase activity. This study demonstrates a role for the FA proteins in mitochondria witsh sensitivity to oxidative stress resulting from diminished peroxidase activity. These defects may lead to apoptosis and the accumulation of oxidative DNA damage in bone marrow precursors
Identifying gene disruptions in novel balanced de novo constitutional translocations in childhood cancer patients by whole-genome sequencing
PurposeWe applied whole genome sequencing to children diagnosed with neoplasms and found to carry apparently balanced constitutional translocations, to discover novel genic disruptions.MethodsWe applied SV calling programs CREST, Break Dancer, SV-STAT and CGAP-CNV, and developed an annotative filtering strategy to achieve nucleotide resolution at the translocations.ResultsWe identified the breakpoints for t(6;12) (p21.1;q24.31) disrupting HNF1A in a patient diagnosed with hepatic adenomas and Maturity Onset Diabetes of the Young (MODY). Translocation as the disruptive event of HNF1A, a gene known to be involved in MODY3, has not been previously reported. In a subject with Hodgkin’s lymphoma and subsequent low-grade glioma, we identified t(5;18) (q35.1;q21.2), disrupting both SLIT3 and DCC, genes previously implicated in both glioma and lymphoma.ConclusionsThese examples suggest that implementing clinical whole genome sequencing in the diagnostic work-up of patients with novel but apparently balanced translocations may reveal unanticipated disruption of disease-associated genes and aid in prediction of the clinical phenotype
a report from the Children's Oncology Group and the Utah Population Database
Relatively little is known about the epidemiology and factors underlying
susceptibility to childhood rhabdomyosarcoma (RMS). To better characterize
genetic susceptibility to childhood RMS, we evaluated the role of family
history of cancer using data from the largest case–control study of RMS and
the Utah Population Database (UPDB). RMS cases (n = 322) were obtained from
the Children's Oncology Group (COG). Population-based controls (n = 322) were
pair-matched to cases on race, sex, and age. Conditional logistic regression
was used to evaluate the association between family history of cancer and
childhood RMS. The results were validated using the UPDB, from which 130 RMS
cases were identified and matched to controls (n = 1300) on sex and year of
birth. The results were combined to generate summary odds ratios (ORs) and 95%
confidence intervals (CI). Having a first-degree relative with a cancer
history was more common in RMS cases than controls (ORs = 1.39, 95% CI:
0.97–1.98). Notably, this association was stronger among those with embryonal
RMS (ORs = 2.44, 95% CI: 1.54–3.86). Moreover, having a first-degree relative
who was younger at diagnosis of cancer (<30 years) was associated with a
greater risk of RMS (ORs = 2.37, 95% CI: 1.34–4.18). In the largest analysis
of its kind, we found that most children diagnosed with RMS did not have a
family history of cancer. However, our results indicate an increased risk of
RMS (particularly embryonal RMS) in children who have a first-degree relative
with cancer, and among those whose relatives were diagnosed with cancer at <30
years of age
ClinGen Pathogenicity Calculator: a configurable system for assessing pathogenicity of genetic variants
Abstract Background The success of the clinical use of sequencing based tests (from single gene to genomes) depends on the accuracy and consistency of variant interpretation. Aiming to improve the interpretation process through practice guidelines, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) have published standards and guidelines for the interpretation of sequence variants. However, manual application of the guidelines is tedious and prone to human error. Web-based tools and software systems may not only address this problem but also document reasoning and supporting evidence, thus enabling transparency of evidence-based reasoning and resolution of discordant interpretations. Results In this report, we describe the design, implementation, and initial testing of the Clinical Genome Resource (ClinGen) Pathogenicity Calculator, a configurable system and web service for the assessment of pathogenicity of Mendelian germline sequence variants. The system allows users to enter the applicable ACMG/AMP-style evidence tags for a specific allele with links to supporting data for each tag and generate guideline-based pathogenicity assessment for the allele. Through automation and comprehensive documentation of evidence codes, the system facilitates more accurate application of the ACMG/AMP guidelines, improves standardization in variant classification, and facilitates collaborative resolution of discordances. The rules of reasoning are configurable with gene-specific or disease-specific guideline variations (e.g. cardiomyopathy-specific frequency thresholds and functional assays). The software is modular, equipped with robust application program interfaces (APIs), and available under a free open source license and as a cloud-hosted web service, thus facilitating both stand-alone use and integration with existing variant curation and interpretation systems. The Pathogenicity Calculator is accessible at http://calculator.clinicalgenome.org. Conclusions By enabling evidence-based reasoning about the pathogenicity of genetic variants and by documenting supporting evidence, the Calculator contributes toward the creation of a knowledge commons and more accurate interpretation of sequence variants in research and clinical care
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Clinical Genetics Lacks Standard Definitions and Protocols for the Collection and Use of Diversity Measures
Genetics researchers and clinical professionals rely on diversity measures such as race, ethnicity, and ancestry (REA) to stratify study participants and patients for a variety of applications in research and precision medicine. However, there are no comprehensive, widely accepted standards or guidelines for collecting and using such data in clinical genetics practice. Two NIH-funded research consortia, the Clinical Genome Resource (ClinGen) and Clinical Sequencing Evidence-generating Research (CSER), have partnered to address this issue and report how REA are currently collected, conceptualized, and used. Surveying clinical genetics professionals and researchers (n = 448), we found heterogeneity in the way REA are perceived, defined, and measured, with variation in the perceived importance of REA in both clinical and research settings. The majority of respondents (>55%) felt that REA are at least somewhat important for clinical variant interpretation, ordering genetic tests, and communicating results to patients. However, there was no consensus on the relevance of REA, including how each of these measures should be used in different scenarios and what information they can convey in the context of human genetics. A lack of common definitions and applications of REA across the precision medicine pipeline may contribute to inconsistencies in data collection, missing or inaccurate classifications, and misleading or inconclusive results. Thus, our findings support the need for standardization and harmonization of REA data collection and use in clinical genetics and precision health research
Evaluating the Clinical Validity of Gene-Disease Associations: An Evidence-Based Framework Developed by the Clinical Genome Resource
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
MODEL PENGELOLAAN PASCA TANGKAP SEBAGAI UPAYA PENGENTASAN KEMISKINAN MASYARAKAT KAMPUNG NELAYAN DI PULAU ENGGANO
Relatively little is known about the epidemiology and factors underlying susceptibility to childhood rhabdomyosarcoma (RMS). To better characterize genetic susceptibility to childhood RMS, we evaluated the role of family history of cancer using data from the largest case-control study of RMS and the Utah Population Database (UPDB). RMS cases (n=322) were obtained from the Children's Oncology Group (COG). Population-based controls (n=322) were pair-matched to cases on race, sex, and age. Conditional logistic regression was used to evaluate the association between family history of cancer and childhood RMS. The results were validated using the UPDB, from which 130 RMS cases were identified and matched to controls (n=1300) on sex and year of birth. The results were combined to generate summary odds ratios (ORs) and 95% confidence intervals (CI). Having a first-degree relative with a cancer history was more common in RMS cases than controls (ORs=1.39, 95% CI: 0.97-1.98). Notably, this association was stronger among those with embryonal RMS (ORs=2.44, 95% CI: 1.54-3.86). Moreover, having a first-degree relative who was younger at diagnosis of cancer (<30years) was associated with a greater risk of RMS (ORs=2.37, 95% CI: 1.34-4.18). In the largest analysis of its kind, we found that most children diagnosed with RMS did not have a family history of cancer. However, our results indicate an increased risk of RMS (particularly embryonal RMS) in children who have a first-degree relative with cancer, and among those whose relatives were diagnosed with cancer at <30years of age
Gene-specific ACMG/AMP classification criteria for germline APC variants: recommendations from the ClinGen InSIGHT Hereditary Colorectal Cancer/Polyposis Variant Curation Expert Panel
Purpose
The Hereditary Colorectal Cancer/Polyposis Variant Curation Expert Panel (VCEP) was established by the International Society for Gastrointestinal Hereditary Tumours and the Clinical Genome Resource, who set out to develop recommendations for the interpretation of germline APC variants underlying Familial Adenomatous Polyposis, the most frequent hereditary polyposis syndrome.
Methods
Through a rigorous process of database analysis, literature review, and expert elicitation, the APC VCEP derived gene-specific modifications to the ACMG/AMP (American College of Medical Genetics and Genomics and Association for Molecular Pathology) variant classification guidelines and validated such criteria through the pilot classification of 58 variants.
Results
The APC-specific criteria represented gene- and disease-informed specifications, including a quantitative approach to allele frequency thresholds, a stepwise decision tool for truncating variants, and semiquantitative evaluations of experimental and clinical data. Using the APC-specific criteria, 47% (27/58) of pilot variants were reclassified including 14 previous variants of uncertain significance (VUS).
Conclusion
The APC-specific ACMG/AMP criteria preserved the classification of well-characterized variants on ClinVar while substantially reducing the number of VUS by 56% (14/25). Moving forward, the APC VCEP will continue to interpret prioritized lists of VUS, the results of which will represent the most authoritative variant classification for widespread clinical use
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