The better question might be, “Are genetic data ready for doctors?”

The onslaught of clinical study results that now include potentially significant genetic biomarkers associated with a particular patient population, condition, or metabolic response is enough to make the head spin of even the most astute physician.

I learned rather quickly while working up a few writing samples for a potential client, that extracting clinically applicable information from the medical literature was going to be quite difficult.

Terminology is not fully standardized (yet) so results are categorized under a number of different terms, which makes searching for something like single nucleotide polymorphisms (SNPs) related to a particular condition challenging and time consuming.

The Drivers of Change

Change, however, is happening at a fast pace and some of the players getting involved as well as the modern business and technology approaches being used will certainly move genomics into the practice setting faster than historical discoveries.

For example, scanning through the past few editions of ClinicalOMICs I came across some interesting news, such as:

  • Google is entering the genetic space with Google Genomics – a publicly accessible database containing 85 billion annotations of genetic variants.
  • Standards committees are convening and releasing guidelines that recommend use of specific standard terminology and a process for classifying variants based on the type of evidence.
  • Crowdsourcing of alleles (The Allele Frequency Community, AFC) is being used in an initiative that began on March 2, compiling ethnically diverse genomic information to improve the interpretation of gene variants in personalized medicine.

The Challenges

And while genetic testing is becoming increasingly available, and affordable, for a wide range of human diseases, its use to transform medicine on a broad scale is met with certain limitations, including reliability, ability to capture the entire genome, and predictive capabilities.

Equally challenging is translating the economics of genomic medicine into actual health benefits for patients…the cost vs the value.

With the advent of personalized medicine and its associated explosive genomic knowledge base, also comes the need to train healthcare professionals.

Increasingly, healthcare providers will need to:

  • apply basic genomic concepts (including topics such as patterns of inheritance and gene-environment interactions),
  • demonstrate understanding of genetic testing and genomic-based interventions,
  • explain risks and benefits of genomics in health and disease in their practice, and
  • be knowledgeable of ethical, legal, and social issues related to genetic testing and information.

The Reward

The significance of the resulting application of genomics to medicine, however, will become increasingly apparent as physicians will know, for example, that:

  • A teenage European-American alcoholic with 5′-HTTLPR-LL and SLC6A4-LL/TT polymorphisms will respond to treatment with the drug ondansetron better than with sertraline.
  • Young healthy males with SNPs in the FADS1 (rs174537) gene are likely to require continued supplementation with omega-3 fatty acids, especially EPA, to maintain reductions in cardiometabolic markers.
  • In individuals, especially Koreans, found to carry the APOA5 -1131C variant that the replacement of refined rice with whole grains and legumes in a high-carbohydrate diet may need to be considered to prevent diabetic hypertriglyceridemia.


Clinical Omics accessed at on April 2, 2015.

Johnson BA, Seneviratne C, Wang XQ, Ait-Daoud N, Li MD. Determination of genotype combinations that can predict the outcome of the treatment of alcohol dependence using the 5-HT(3) antagonist ondansetron. Am J Psychiatry. 2013;170(9):1020-31. [PubMed]

Kang R, Kim M, Chae JS, Lee SH, Lee JH. Consumption of whole grains and legumes modulates the genetic effect of the APOA5 -1131C variant on changes in triglyceride and apolipoprotein A-V concentrations in patients with impaired fasting glucose or newly diagnosed type 2 diabetes. Trials. 2014;15:100. [PubMed]

Kenna GA, Zywiak WH, Swift RM, McGeary JE, Clifford JS, Shoaff JR, Vuittonet C, Fricchione S, Brickley M, Beaucage K, Haass-Koffler CL, Leggio L. Ondansetron reduces naturalistic drinking in nontreatment-seeking alcohol-dependent individuals with the LL 5′-HTTLPR genotype: a laboratory study. Alcohol Clin Exp Res. 2014;38(6):1567-74. [PubMed]

Roke K, Mutch DM. The role of FADS1/2 polymorphisms on cardiometabolic markers and fatty acid profiles in young adults consuming fish oil supplements. Nutrients. 2014;6(6):2290-304. [PubMed]

Centers for Disease Control and Prevention. National Office of Public Health Genomics. Genomics Competencies for the Public Health Workforce. Available at