Michael J Friez

Greenwood Genetic Center, Greenwood, South Carolina, United States

Are you Michael J Friez?

Claim your profile

Publications (4)15.49 Total impact

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Positive control materials for clinical diagnostic molecular genetic testing are in critically short supply. High-quality DNA that closely resembles DNA isolated from patient specimens can be obtained from Epstein-Barr virus (EBV)-transformed peripheral blood lymphocyte cell lines. Here we report the development of a process to (a) recover residual blood samples with clinically important mutations detected during routine medical care, (b) select samples likely to provide viable lymphocytes for EBV transformation, (c) establish stable cell lines and confirm the reported mutation(s), and (d) validate the cell lines for use as positive controls in clinical molecular genetic testing applications. A network of 32 genetic testing laboratories was established to obtain anonymous, residual clinical samples for transformation and to validate resulting cell lines for use as positive controls. Three panel meetings with experts in molecular genetic testing were held to evaluate results and formulate a process that could function in the context of current common practices in molecular diagnostic testing. Thirteen laboratories submitted a total of 113 residual clinical blood samples with mutations for 14 genetic disorders. Forty-one EBV-transformed cell lines were established. Thirty-five individual point and deletion mutations were shown to be stable after 20 population doublings in culture. Thirty-three cell lines were characterized for specific mutations and validated for use as positive controls in clinical diagnostic applications. A process for producing and validating positive control cell lines from residual clinical blood samples has been developed. Sustainable implementation of the process could help alleviate the current shortage of positive control materials.
    Clinical Chemistry 12/2005; 51(11):2013-24. · 7.15 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We expect that the mutation panel currently recommended for preconception/prenatal CF carrier screening will be modified as new information is learned regarding the phenotype associated with specific mutations and allele frequencies in various populations. One such example is the I148T mutation, originally described as a severe CF mutation. After implementation of CF population-based carrier screening, we learned that I148T exists as a complex allele with 3199del6 in patients with clinical CF, whereas asymptomatic compound heterozygotes for I148T and a second severe CF mutation were negative for 3199del6. We performed reflex testing for 3199del6 on 663 unrelated specimens, including I148T heterozygotes, compound heterozygotes, and a homozygous individual. Less than 1% of I148T carriers were also positive for 3199del6. Excluding subjects tested because of a suspected or known CF diagnosis or positive family history, 0.6% of I148T-positive individuals were also positive for 3199del6. We identified 1 I148T homozygote and 6 unrelated compound heterozygous individuals with I148T and a second CF variant (2 of whom also carried 3199del6). In addition, one fetus with echogenic bowel and one infertile male were heterozygous for I148T (3199del6 negative). Reflex testing for 3199del6 should be considered whenever I148T is identified. Reflex testing is of particular importance for any symptomatic patient or whenever one member of a couple carries a deleterious CF mutation and the other member is an I148T heterozygote. Further population data are required to determine if I148T, in the absence of 3199del6, is associated with mild or atypical CF or male infertility.
    Genetics in Medicine 10/2004; 6(5):421-5. · 5.56 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Bioelectronic sensors, which combine microchip and biological components, are an emerging technology in clinical diagnostic testing. An electronic detection platform using DNA biochip technology (eSensor) is under development for molecular diagnostic applications. Owing to the novelty of these devices, demonstrations of their successful use in practical diagnostic applications are limited. To assess the performance of the eSensor bioelectronic method in the validation of 6 Epstein-Barr virus-transformed blood lymphocyte cell lines with clinically important mutations for use as sources of genetic material for positive controls in clinical molecular genetic testing. Two cell lines carry mutations in the CFTR gene (cystic fibrosis), and 4 carry mutations in the HFE gene (hereditary hemochromatosis). Samples from each cell line were sent for genotype determination to 6 different molecular genetic testing facilities, including the laboratory developing the DNA biochips. In addition to the bioelectronic method, at least 3 different molecular diagnostic methods were used in the analysis of each cell line. Detailed data were collected from the DNA biochip output, and the genetic results were compared with those obtained using the more established methods. We report the successful use of 2 applications of the bioelectronic platform, one for detection of CFTR mutations and the other for detection of HFE mutations. In all cases, the results obtained with the DNA biochip were in concordance with those reported for the other methods. Electronic signal output from the DNA biochips clearly differentiated between mutated and wild-type alleles. This is the first report of the use of the cystic fibrosis detection platform. Bioelectronic sensors for the detection of disease-causing mutations performed well when used in a "real-life" situation, in this case, a validation study of positive control blood lymphocyte cell lines with mutations of public health importance. This study illustrates the practical potential of emerging bioelectronic DNA detection technologies for use in current molecular diagnostic applications.
    Archives of pathology & laboratory medicine 01/2004; 127(12):1565-72. · 2.78 Impact Factor
  • Genetics in Medicine. 01/2002; 4(3):212.