OPINION: Understanding Genetic Testing: Towards Precision Medicine

The human genome project, completed in 2003, cost $100 million. Today, anybody can get their DNA tested for $99 by 23andMe. More thorough genetic testing costs around $3000. Genomic sequencing technology has improved exponentially, and soon these tests will become standard in clinical practice. But how reliable are these test results, and do we know what they mean?

Genetic testing is largely used to assess the risk of a person developing a particular disease. But this risk assessment is given in terms of a probability, never a certainty.

Angelina Jolie made headlines when she got a double mastectomy after testing for increased risk of breast cancer. Was this a rational decision? One of the genes responsible for breast cancer is BRCA1. Studies show BRCA1 mutation carriers have a 57% risk of developing breast cancer by age 70. It is worth remembering that the risk estimates are low and unstable for developing cancer at age 30 or younger. The individual and the family need to know what all this means.

Understanding the risk isn’t as simple as a number out of one hundred. Your risk for a disease also depends on your genetic and environmental background. For Hypertrophic Cardiomyopathy (HCM), expected prevalence is 1 in 500 people, yet a much higher proportion of African Americans test positive for disease-causing genetic mutations. Most of these individuals are healthy. The discrepancy is a result of common benign variants misclassified exclusively for African Americans. That is, harmless genetic mutations are said to be disease causing, simply because the data used to make decisions did not cover the population as a whole and instead oversampled certain groups. Knowing your background and matching to a relevant study with the appropriate sample population is crucial.

Physicians and genetic counselors must be able to interpret the probabilistic risks. This includes risk analysis and understanding that genetic screening for hundreds or thousands of variants will likely reveal incidental findings simply due to multiple testing, incorrect algorithmic calling, missing data, and so on. And a mutated gene may not even be a negative finding.

As Dr. Isaac Kohane of Harvard Medical School said last month, physician education is the first thing that needs to happen in order to move forward in the genomic age. With well-informed physicians, we can have better information sharing with patients.

Additionally, we need more data sharing. Whether it be making data public or simply sharing your new knowledge with your family, the more information we have, the more educated everybody is, and the more we can progress towards true and effective individualized medicine.

The Personal Genome Project understands the importance of patient and public education. The initiative collects genomic and biomedical data from participants and makes it all public on the Internet. But, through a required pamphlet reading and test, they make sure each and every participant understands what they are providing and what analyses may or may not mean.

Such education should be required of all who undergo genetic testing. This includes the patient and any immediate family who may be affected. In the case of fetal genetic testing, parents should be fully knowledgeable of the meaning and risks of any unusual finding. Only with complete knowledge and clinical help can patients and family make appropriate decisions for their own lives.

The science and technology are arriving fast, but policy and education have to keep up if we are to truly herald in an era of Precision Medicine.

April Lo, CSN Staff


Image found here.


  1. Nice article, it is remarkable to say that genomic sequencing is individually practical now, and continues to follow a Moore’s law, exponential trend. I like that you point out knowing a sequence is only as useful as your knowledge about the sequence. The BRCA breast cancer gene is a classic example, since it is so decisive and well understood. But most genes are so interdependent and variable that our genetic prediction models are ambiguous and subject dependent. Even with futuristic quantum computers, or even omniscience, I think one-size-fits-all determinstic applications are never going to be possible. But personal healthcare is exciting!

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