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If we can accurately understand each patient’s risk for disease, we can create more nuanced preventive care plans and better invest our resources.
In the 2015 State of the Union address, President Barack Obama talked about funding a National Precision Medicine Initiative, catapulting a new term into the limelight.
Precision medicine began picking up speed as a result of a report from the National Research Council back in November of 2013. Fortune 500 companies like General Electric have started using the term liberally, and medical centers like Weill Cornell and New York Presbyterian have since announced a new institute for precision medicine.
While definitions of precision medicine vary, one thing is generally agreed upon: precision medicine is about being able to classify people precisely based on their genome, lifestyle and medical susceptibilities to diseases, drugs and various foods. As the National Research Council has explained, “preventive or therapeutic interventions can then be concentrated on those who will benefit...” Precision medicine is about how personalized data can maximize the effect of disease treatment and prevention for each patient.
Read more: Exploring precision medicine's value: plans, providers are rolling out initiatives; government pledges new support.
What healthcare executives therefore need to understand about precision medicine is its incredible power to reduce risk and improve the overall health of populations who are susceptible to chronic disease. However, precision medicine is predicated upon the ability to manipulate a wide swath of personalized data that most providers and practitioners do not currently have at their disposal.
One of the most interesting use cases of precision medicine is its application for Type 2 diabetes. The disease we call “Type 2 diabetes” is arguably an amalgamation of a large number of specific conditions that together make up a much larger cohort called “diabetes sufferers.” Twenty nine million people in the U.S. suffer from Type 2 diabetes. Eighty million more Americans have prediabetes, meaning they are susceptible to developing the disease. Diabetes is therefore a continuum-your diabetes is not my diabetes. As such, the disease is the ideal proving ground for precision medicine.
It would be a big mistake to equate precision medicine solely with genomics data. Genomic precision is only one part of a more holistic view of a disease such as Type 2 diabetes and how it is interacting with an individual. The trick is being able to correlate genomic insights with environmental, behavioral, and medical factors. Your genes do not alone determine whether and when you get a disease, such as Type 2 diabetes, or how acutely you experience it. It is rather the unique combination of your genotype data and your phenotype data that we as providers and practitioners must account for. And so, any sufficient precision medicine initiative is only as precise as the data it collects.
We recently did a study in collaboration with a prominent cardiology center in San Jose, Calif., during which we took 99 randomly selected patients from the center to undergo a disease prediction test. Each patient’s lifestyle, biometrics, laboratory results, and family history data were collected. Without knowing how many of these patients had already been diagnosed with Type 2 diabetes, their holistic data was processed through the BaseHealth disease assessment engine and their Type 2 diabetes risk was measured.
We found a significant association between those who had a high risk of developing diabetes (based on the assessment) and those who had been already diagnosed with the disease by their physicians.
The interesting part of the study is actually in the methodology. We first processed the risk factors of each participant individually and then later processed the data collectively (lifestyle, biometrics, family history and laboratory results). The association between the Type 2 diabetes risk assessment and the comprehensiveness of the data was most significant when all the personalized data for each individual was processed together.
We’ve known that Type 2 diabetes is largely affected by lifestyle factors-not just our genome. But what this study showed us is that having comprehensive data about a patient’s total risk factors could contribute to a more accurate risk assessment for Type 2 diabetes.
Many have argued that the trend of preventive medicine is really just healthcare’s way of making money off of small levels of risk that will more than likely never become full blown issues. And in many ways, the critics are right. The one-size-fits-all approach in medicine does not work anymore.
With all the health data being generated on a daily basis, precision medicine brings just that-precision and accuracy. If we can accurately understand each patient’s risk for the disease, we can create more nuanced preventive care plans and invest our resources in a way that is commensurate with the individual level of risk.
Precision medicine on chronic disease is about action-actions that can improve health, such as reducing the risk of diabetes. If you pair molecular profiling along with dietary changes, environmental shifts, and other lifestyle-related interventions, you can start to envision what precision medicine can accomplish.
It’s a powerful vision for the future of healthcare, one that is predicated by accurate data collection and analysis, and the understanding that an individual’s genome is just one piece of the puzzle.
Dr. Fakhrai-Rad is the founder and chief scientific officer ofBaseHealth, a platform enabler that adds genomic precision to modern health and well-being offerings.