An Exploration of Genetic Test Utilization, Genetic Counseling, and Consanguinity within the Inborn Errors of Metabolism Collaborative (IBEMC).

Citation data:

Journal of genetic counseling, ISSN: 1573-3599, Vol: 26, Issue: 6, Page: 1238-1243

Publication Year:
2017
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PMID:
28451876
DOI:
10.1007/s10897-017-0100-0
Author(s):
Stein, Quinn P, Vockley, Cate Walsh, Edick, Mathew J, Zhai, Shaohui, Hiner, Sally J, Loman, Rebecca S, Davis-Keppen, Laura, Zuck, Taylor A, Cameron, Cynthia A, Berry, Susan A, Inborn Errors of Metabolism Collaborative Show More Hide
Publisher(s):
Springer Nature
Tags:
Medicine
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article description
The Inborn Errors of Metabolism Collaborative (IBEMC) includes clinicians from 29 institutions collecting data to enhance understanding of metabolic conditions diagnosable by newborn screening. Data collected includes hospitalizations, test results, services, and long-term outcomes. Through evaluation of this data, we sought to determine how frequently genetic counseling had been provided, how often genetic testing was performed, and also determine the consanguinity rate in this population. A data query was performed with the following elements abstracted/analyzed: current age, metabolic condition, whether genetic counseling was provided (and by whom), whether genetic testing was performed, and consanguinity. Genetic counseling was provided to families 95.8% of the time and in 68.6% of cases by a genetic counselor. Genetic testing was performed on 68.0% of subjects, with usage highest for fatty-acid-oxidation disorders (85.1%). The rate of consanguinity was 2.38%. Within this large national collaborative there is a high frequency of genetic counseling, though in one-third of cases a genetic counselor has not been involved. Additionally, while metabolic conditions have historically been diagnosed biochemically, there is currently high utilization of molecular testing suggesting DNA testing is being incorporated into diagnostic assessments - especially for fatty-acid-oxidation disorders where the underlying genotype helps predict clinical presentation.

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