Data Generated from HapMap and 1000 Genomes Samples Identifies Cause for Genetic Misdiagnoses


A recent study published in the New England Journal of Medicine examined publicly accessible exome data from several sources, including the 1000 Genomes Project and the HapMap project, published medical literature, and health records of patients tested for the heart condition hypertrophic cardiomyopathy.

Cardiomyopathy is a disease that causes heart muscle to become too thick, making it harder for the heart to pump blood. This can lead to shortness of breath, chest pain, or life-threatening abnormal heart rhythms. The goal of the study was to analyze gene changes thought to cause hypertrophic cardiomyopathy that have since been classified as benign. Hypertrophic cardiomyopathy has been linked to sudden death in young athletes, and an incorrect diagnosis of the condition can have serious consequences.

The study identified variants earlier thought to cause hypertrophic cardiomyopathy that are overrepresented in the general population. Many patients with African ancestry received positive reports, which incorrectly led them to believe they had a greater risk of encountering the disease. Misdiagnosis could have been prevented had more data from healthy people of African ancestry been available when the genetic tests were performed. Misclassification of benign variants as harmful shows the significance of sequencing the genomes of people from many different populations.

The deep genetic data provided by the International HapMap and 1000 Genomes Projects makes it possible for genetic diagnostic laboratories around the world to accurately classify variants found in patients with inherited disorders.

Full details of the study can be found in the New England Journal of Medicine publication: Manrai, A., et al. "Genetic Misdiagnoses and the Potential for Health Disparities." N Engl JMed 375.7, 655-65 (2016) or in the Medscape article linked below.

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