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Evaluation and classification of severity for 176 genes on an expanded carrier screening panel |
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| Authors: | Aishwarya Arjunan Holly Bellerose Raul Torres Rotem Ben-Shachar Jodi D Hoffman Brad Angle Robert Nathan Slotnick Brittany N Simpson Andrea M Lewis Pilar L Magoulas Kelly Bontempo Jeanine Schulze Jennifer Tarpinian Jessica A Bucher Richard Dineen Allison Goetsch Gabriel A Lazarin Katherine Johansen Taber |
| Institution: | 1. Division of Medical Affairs, Myriad Women's Health, South San Francisco, CA, USA;2. Department of Pediatric Genetics, Boston University School of Medicine, Boston, MA, USA;3. Division of Genetics, Advocate Children's Hospital, Park Ridge, IL, USA;4. Department of Internal Medicine, Renown Health Cancer Institute, Reno, NV, USA;5. Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA;6. Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
Department of Molecular and Human Genetics, Texas Children's Hospital, Houston, TX, USA;7. Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA;8. Individualized Medical Genetics Center, Children's Hospital of Philadelphia, Philadelphia, PA, USA;9. Department of Clinical Genetics and Genomics, Rush University Medical Center, Chicago, IL, USA;10. Division of Genetics, Birth Defects & Metabolism, Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA Department of Pediatrics, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA;11. Division of Medical Affairs, Myriad Women's Health, South San Francisco, CA, USA GAL and KJT contributed equally. |
| Abstract: | BackgroundDisease severity is important when considering genes for inclusion on reproductive expanded carrier screening (ECS) panels. We applied a validated and previously published algorithm that classifies diseases into four severity categories (mild, moderate, severe, and profound) to 176 genes screened by ECS. Disease traits defining severity categories in the algorithm were then mapped to four severity-related ECS panel design criteria cited by the American College of Obstetricians and Gynecologists (ACOG).MethodsEight genetic counselors (GCs) and four medical geneticists (MDs) applied the severity algorithm to subsets of 176 genes. MDs and GCs then determined by group consensus how each of these disease traits mapped to ACOG severity criteria, enabling determination of the number of ACOG severity criteria met by each gene.ResultsUpon consensus GC and MD application of the severity algorithm, 68 (39%) genes were classified as profound, 71 (40%) as severe, 36 (20%) as moderate, and one (1%) as mild. After mapping of disease traits to ACOG severity criteria, 170 out of 176 genes (96.6%) were found to meet at least one of the four criteria, 129 genes (73.3%) met at least two, 73 genes (41.5%) met at least three, and 17 genes (9.7%) met all four.ConclusionThis study classified the severity of a large set of Mendelian genes by collaborative clinical expert application of a trait-based algorithm. Further, it operationalized difficult to interpret ACOG severity criteria via mapping of disease traits, thereby promoting consistency of ACOG criteria interpretation. |
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