Genetics and Genomics: Color at ACMG, 2019
For the first time, the American College of Medical Genetics and Genomics (ACMG) Annual Clinical Genetics Meeting took place in Seattle, Washington, from April 2–6 as thousands of medical and clinical geneticists, genetic counselors, and researchers gathered to learn about the latest research, therapies, and practical implementation of genetics and genomics.
This year, Color representatives from our Genetic Counseling, Data Science, Scientific Affairs, and Variant Science teams spoke and presented five posters. Our posters focused on two key thematic areas: 1) cancer genetics and therapeutics and 2) clinical genetics and therapeutics.
Two of our posters highlighted results from novel collaborations with Northshore University HealthSystem and The FH Foundation, and Color Data Scientist Julian Homburger’s poster was awarded a ribbon by the ACMG abstract reviewers. Here is a recap of the exciting work:
Implementation of hereditary cancer genetic testing in the primary care setting, a poster presentation
Historically, genetic testing for hereditary cancer has been restricted to high-risk individuals, putting potentially life-saving information out of reach for many individuals. To increase access to hereditary cancer testing and advance population health, Northshore University HealthSystem partnered with Color on a pilot to offer 1000 patients genetic testing through their primary care physician, regardless of personal or family history. 39% of patients who received information about the pilot elected to undergo genetic testing. Furthermore, 48% of patients with a positive result would not have met current recommendations for genetic testing. This suggests that health systems can proactively engage patients interested in genetic testing and further identify those with high-risk. See our poster here.
A complex rearrangement in the LDLR gene in a patient with familial hypercholesterolemia and severe coronary artery disease, a poster presentation
Familial hypercholesterolemia (FH) is a common, inherited disorder that causes high cholesterol. If left untreated, FH leads to coronary artery disease. Genetic testing for the three currently known genes that cause FH can confirm a diagnosis and be a powerful tool in the care of FH. In collaboration with The FH Foundation, Color is providing free genetic testing and counseling to individuals with FH who are participating in the PAGENT Study. Color Variant Scientist Serra Kim presented an interesting case study from PAGENT: a complex rearrangement in LDLR was identified by next generation sequencing (NGS) in a Caucasian individual who was diagnosed with FH following an emergency quadruple bypass surgery at the age of 32. Importantly, this variant is unlikely to have been detected by certain other sequencing methods. See her poster here.
Polygenic risk is independent from the risk conferred by pathogenic variants in 12 known breast cancer genes, a poster presentation
Breast cancer is the most common cancer among women, accounting for nearly 30% of newly diagnosed cancers in women in the United States during 2017. A woman’s risk for breast cancer can be estimated based on monogenic or polygenic risk. Monogenic risk is a single change in a gene associated with breast cancer, such as BRCA1 or BRCA2, and polygenic risk is many changes in many different genes. Color Data Scientist Julian Homburger investigated the relationship between monogenic and polygenic risk for breast cancer. He found that monogenic and polygenic risk are independent, meaning that they each confer their own risk and someone could have low monogenic risk and high polygenic risk or vice versa. Furthermore, the effects are additive so if someone has high monogenic and polygenic risk, the risk would be even higher. See his top rated post here.
Mind the gaps: Novel loss of function CYP2C19 variants in 48,657 Individuals, a poster presentation
Traditional pharmacogenomics (PGx) testing uses genotyping arrays, which provide DNA sequence information for only some parts of the genome. These arrays often miss new or rare genetic changes and tend to be European-centric, which means they could miss important PGx alleles in individuals of non-European ancestry. Color derives PGx-relevant diplotypes from NGS data and only reports on the established variants from PharmVar. Color Product Scientist Danny DeSloover explored the data beyond those known diplotypes to characterize the additional variation that is present, specifically in CYP2C19. His work suggests that NGS is a comparable tool for clinically reporting PGx diplotypes and can be used to reduce the ethnic disparities in PGx testing. See his poster here.
Phenotypic and genotypic spectrum identified in a cohort of germline TP53 carriers, a poster presentation
Li-Fraumeni syndrome (LFS) is a rare, inherited disorder that leads to a high risk of developing certain cancers. Traditionally, genetic testing for LFS was only done in individuals meeting classic clinical criteria and involved only sequencing the one gene associated with LFS, TP53. Recently, genetic testing has moved from single-gene to multi-gene panel tests, and TP53 pathogenic variants are now being identified in individuals who do not meet the classic clinical criteria for LFS. Color Genetic Counselor Carmelina Heydrich examined the clinical features of 34 individuals who had received multi-gene panel testing for hereditary cancer and had a TP53 pathogenic variant. She found that these individuals had a wide range of cancers and ages at onset and that approximately 50% would not have met current recommendations for TP53 genetic testing. See her poster here.
Leveraging NGS technologies beyond monogenic applications, an exhibit talk
NGS has had a tremendous impact on the clinical diagnosis and management of genetic diseases such as hereditary cancer, hereditary heart conditions, and metabolic disorders. Indeed, NGS is more sensitive and efficient than traditional genetic testing approaches and is increasingly more affordable. Color’s VP of Research and Scientific Affairs Alicia Zhou shared how Color is now using NGS for applications of statistical genetics such as genome-wide polygenic scores (GPSs), on which Color has been advised by experts in the field including Sek Kathiresan and Amit Khera from the Broad Institute. GPSs are an important emerging method to identify individuals with risk for common diseases and can help stratify their clinical management and treatment. Using NGS to determine GPSs will help drive the development and validation of GPSs in diverse populations, which can play an important role in closing the health equity gap.
Color is committed to advancing genetics research and increasing access to genetic information. To learn more about the innovative studies Color participates in and find out how to add Color genetic testing to your research study, you can find us at color.com/research.