183 research outputs found

    Defective mitochondrial peroxiredoxin-3 results in sensitivity to oxidative stress in Fanconi anemia

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    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

    a report from the Children's Oncology Group and the Utah Population Database

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    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

    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

    Targeted Sequencing in Chromosome 17q Linkage Region Identifies Familial Glioma Candidates in the Gliogene Consortium

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    Glioma is a rare, but highly fatal, cancer that accounts for the majority of malignant primary brain tumors. Inherited predisposition to glioma has been consistently observed within non-syndromic families. Our previous studies, which involved non-parametric and parametric linkage analyses, both yielded significant linkage peaks on chromosome 17q. Here, we use data from next generation and Sanger sequencing to identify familial glioma candidate genes and variants on chromosome 17q for further investigation. We applied a filtering schema to narrow the original list of 4830 annotated variants down to 21 very rare (,0.1% frequency), non-synonymous variants. Our findings implicate the MYO19 and KIF18B genes and rare variants in SPAG9 and RUNDC1 as candidates worthy of further investigation. Burden testing and functional studies are planned

    MODEL PENGELOLAAN PASCA TANGKAP SEBAGAI UPAYA PENGENTASAN KEMISKINAN MASYARAKAT KAMPUNG NELAYAN DI PULAU ENGGANO

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    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 (&lt;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 &lt;30years of age

    A survey of informatics approaches to whole-exome and whole-genome clinical reporting in the electronic health record

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    Genome-scale clinical sequencing is being adopted more broadly in medical practice. The National Institutes of Health developed the Clinical Sequencing Exploratory Research (CSER) program to guide implementation and dissemination of best practices for the integration of sequencing into clinical care. This study describes and compares the state of the art of incorporating whole-exome and whole-genome sequencing results into the electronic health record, including approaches to decision support across the six current CSER sites

    Attitudes and Practices Among Internists Concerning Genetic Testing

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    Many questions remain concerning whether, when, and how physicians order genetic tests, and what factors are involved in their decisions. We surveyed 220 internists from two academic medical centers about their utilization of genetic testing. Rates of genetic utilizations varied widely by disease. Respondents were most likely to have ordered tests for Factor V Leiden (16.8 %), followed by Breast/Ovarian Cancer (15.0 %). In the past 6 months, 65 % had counseled patients on genetic issues, 44 % had ordered genetic tests, 38.5 % had referred patients to a genetic counselor or geneticist, and 27.5 % had received ads from commercial labs for genetic testing. Only 4.5 % had tried to hide or disguise genetic information, and <2 % have had patients report genetic discrimination. Only 53.4 % knew of a geneticist/genetic counselor to whom to refer patients. Most rated their knowledge as very/somewhat poor concerning genetics (73.7 %) and guidelines for genetic testing (87.1 %). Most felt needs for more training on when to order tests (79 %), and how to counsel patients (82 %), interpret results (77.3 %), and maintain privacy (80.6 %). Physicians were more likely to have ordered a genetic test if patients inquired about genetic testing (p  < .001), and if physicians had a geneticist/genetic counselor to whom to refer patients (p  < .002), had referred patients to a geneticist/genetic counselor in the past 6 months, had more comfort counseling patients about testing (p  < .019), counseled patients about genetics, larger practices (p  < .032), fewer African‐American patients (p  < .027), and patients who had reported genetic discrimination (p  < .044). In a multiple logistic regression, ordering a genetic test was associated with patients inquiring about testing, having referred patients to a geneticist/genetic counselor and knowing how to order tests. These data suggest that physicians recognize their knowledge deficits, and are interested in training. These findings have important implications for future medical practice, research, and education

    Performance of ACMG-AMP Variant-Interpretation Guidelines among Nine Laboratories in the Clinical Sequencing Exploratory Research Consortium

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    Evaluating the pathogenicity of a variant is challenging given the plethora of types of genetic evidence that laboratories consider. Deciding how to weigh each type of evidence is difficult, and standards have been needed. In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published guidelines for the assessment of variants in genes associated with Mendelian diseases. Nine molecular diagnostic laboratories involved in the Clinical Sequencing Exploratory Research (CSER) consortium piloted these guidelines on 99 variants spanning all categories (pathogenic, likely pathogenic, uncertain significance, likely benign, and benign). Nine variants were distributed to all laboratories, and the remaining 90 were evaluated by three laboratories. The laboratories classified each variant by using both the laboratory's own method and the ACMG-AMP criteria. The agreement between the two methods used within laboratories was high (K-alpha = 0.91) with 79% concordance. However, there was only 34% concordance for either classification system across laboratories. After consensus discussions and detailed review of the ACMG-AMP criteria, concordance increased to 71%. Causes of initial discordance in ACMG-AMP classifications were identified, and recommendations on clarification and increased specification of the ACMG-AMP criteria were made. In summary, although an initial pilot of the ACMG-AMP guidelines did not lead to increased concordance in variant interpretation, comparing variant interpretations to identify differences and having a common framework to facilitate resolution of those differences were beneficial for improving agreement, allowing iterative movement toward increased reporting consistency for variants in genes associated with monogenic disease
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