ACMG Statements and Guidelines
These online statements and guidelines are definitive and may be cited using the digital object identifier (DOI). These recommendations are designed primarily as an educational resource for medical geneticists and other healthcare providers to help them provide quality medical genetics services; they should not be considered inclusive of all proper procedures and tests or exclusive of other procedures and tests that are reasonably directed to obtaining the same results. Please refer to the leading disclaimer in each document for more information.
- Trio-based genetic analysis (typically involving a child and their biological parents) is an important tool in clinical diagnostic testing, as this type of analysis aids in developing an accurate understanding of the inheritance of variants observed in the proband.1-5 Understanding if a variant is inherited or is de novo can directly affect variant classification and result interpretation; consequently, misunderstanding the true biological relationship between analyzed samples can lead to erroneous clinical interpretations.
- Pathogenic variants in the CFTR gene are causative of classic cystic fibrosis (CF) as well as some nonclassic CF phenotypes. In 2001, CF became the first target of pan-ethnic universal carrier screening by molecular methods. The American College of Medical Genetics and Genomics (ACMG) recommended a core panel of 23 disease-causing variants as the minimal set to be included in pan-ethnic carrier screening of individuals with no family history of the disease, and these variants were usually assessed using targeted methods.
- Reductions in the cost of genomic analyses and the elimination of gene patents for clinical diagnostics have enabled clinical laboratories to provide increasingly comprehensive genetic testing using sequencing, microarrays, and other methods, resulting in the generation of a vast amount of data that then needs to be analyzed.1 A significant challenge for clinical laboratory geneticists is the provision of accurate and consistent variant classification. Variant classification has historically been hindered by a lagging recognition of gene–disease associations, as well as a lack of publicly available data (including reference data) from clinical laboratories and other sources.