associated medications. However, under the current
knowledge base and clinical reporting guidelines, only
a fraction of these people will receive actionable disease
The American College of Medical Genetics and
Genomics (ACMG) published a secondary findings
minimum list that includes 59 medically actionable
genes recommended for return in clinical genomic
sequencing. 6 The goal of this list is to identify selected
disorders that have established interventions which
can significantly reduce morbidity and mortality. As
our knowledge of gene-disease associations increases
along with emerging therapies, this list will continue to
We’ve already discussed how having PGx results
linked with the medical record increases its usefulness.
Applying genomic screening results within the clinical
context along with the capability to perform reinterpretation will be a crucial step in achieving precision
medicine’s full potential. New genetic insights will
require periodic re-analysis of genomic data. An individual with a genetic change in a disease-causing gene
that, once originally classified as a “variant of uncertain
significance,” might be re-classified as a “pathogenic”
variant with the discovery of several affected individuals with the same variant, consequently leading to a
disease prevention plan for that person.
Genetic Risk Scores
Genetic risk scores (GRSs) are a set of predetermined genetic markers (or risk alleles) that may increase
or decrease the risk of a condition. A recent study7
developed a GRS for colorectal cancer based on a set of
27 validated common risk alleles. This GRS classified
patients into high-, medium-, or low-risk groups, which
refined the recommended starting ages for colonoscopy
screening ( 42 years of age in the high-risk group vs.
52 years in the low-risk group). Linking this information to the medical record could generate an alert to a
provider if a patient has not received a colonoscopy by
the recommended age, thus giving high priority to those
with high risk. Similar studies are emerging that may
improve decision-making on mammographic screening
and elevated cholesterol treatment.
Genomic analysis capabilities will continue to
increase, and an ever-growing number of people will
undergo genetic testing. The best way to leverage this
genomic data is by weaving it into the clinical context
and developing the resources to perform automated
reinterpretation. Only then will we be able to achieve
the goals of precision medicine.
1. Z.D. Stephens, S. Y. Lee, F. Faghri, et al. 2015. Big Data: Astronomical or Genomical? PLOS Biology, 13( 7): e1002195.
2. National Human Genome Research Institute. 2017. Human
Genome Project Fact Sheet. Accessed May 23, 2017 at report.
3. National Center for Biotechnology Information. 2017. GTR:
Genetic Testing Registry. Accessed May 23, 2017 at ncbi.nlm.
4. E.J. Berm, et al. 2016. Economic Evaluations of Pharmacogenetic and Pharmacogenomic Screening Tests: A Systematic Review. Second Update of the Literature. PLOS One.
January 11, 2016; 11( 1):e0146262. Accessed May 23, 2017
5. M.D. Linderman, D.E. Nielsen, and R.C. Green. 2016.
Personal Genome Sequencing in Ostensibly Healthy Individuals and the PeopleSeq Consortium. Journal of Personalized
Medicine, 6( 2): pii:E14.
6. S.S. Kalia, et al. 2017. Recommendations for Reporting of
Secondary Findings in Clinical Exome and Genome Sequencing, 2016 Update (ACMG SF v2.0): A Policy Statement of the
American College of Medical Genetics and Genomics. February 2017. Genetics in Medicine, 19( 2): 249–255.
7. L. Hsu, et al. 2015. Colorectal Transdisciplinary (CORECT)
Study: Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO): A Model to Determine Colorectal Cancer
Risk Using Common Genetic Susceptibility Loci.
Gastroenter-ology, 148( 7): e14.1330–1339.
Ahmed Ghouri, M.D., is founder and CEO at Inter-preta, a provider of a real-time healthcare analytics
that continuously updates, interprets, and synchronizes
clinical and genomics data, creating a personalized
roadmap and enabling the orchestration of timely care.