Will COVID-19 Power a New Era of Precision Medicine?

COVID-19 Precision Medicine Future

As the cases of COVID-19 mount worldwide and scientists struggle to understand the new pathogenic foe, one thing has become clear: the enemy SARS-CoV-2, is getting personal and its victims are not responding equally.

Is there a reason why this disease seems to hit men harder than women, or some ethnic populations more severely than others? If so, why? Does their genetic makeup play a role? Do variations in key genes make some individuals less likely to mount an effective counter attack?

The answers to all of these questions may very well be yes.

The SARS-CoV-2 virus accesses host cells via the enzyme angiotensin-converting enzyme 2 (ACE2). Its receptor, hACE2, is on the X chromosome, meaning men have a single copy and women have two. Men seem to be experiencing more severe symptoms of the disease in some contries, at a ratio of almost 2:1. Scientists have also hypothesized that mutations (single nucleotide polymorphisms, or SNPs) in the hACE2 protein’s binding site could have an effect of severity of infection. An estimated 1-3% of the population have these mutations, which seems to correlate with the median death rate of COVID-19 in several countries. These mutations also occur in higher frequency in some populations, such as those of Mediterranean and African descent, which are also experiencing higher COVID-19 related fatalities.

Scientists are exploring several of these avenues while trying to understand the biology of the pathogen and host responses.

With nearly every case, it is becoming increasingly clear that there is a genetic code to COVID-19 that will be crucial to unlock if we are to develop effective diagnostics, treatments and prevention measures.

Could this also be the ideal opportunity to move precision medicine beyond oncology and into infectious disease?

Precision, or personalized, medicine is built on the concept that we all harbor unique biological variables that influence our response to disease, and then leverages these differences for improved diagnostics and therapeutics tailored specifically to the individual.

Infectious disease seems a strong candidate for a precision medicine approach, due to the high variability between patients. Being able to link genetic profiles to clinical outcomes would be extremely useful when developing diagnostics and formulating treatment plans. By stratifying patients based on genetic information, healthcare providers and government decision-makers could adopt more rational and effective surveillance, containment, and treatment  strategies.

Advances in genetic sequencing are enabling much of this research to rapidly occur. Unprecedented global collaboration is also helping to accelerate the work we need to do in order to control this virus and its aftermath.

Building a Precision Medicine Hub

Building a Precision Medicine Hub

Our understanding of human disease is progressing and so is the arc of precision medicine. Originally focused on genomics, thanks to the Human Genome Project, precision medicine is unfolding to include other -omics data and patient-level data such as clinical, environmental and behavioral data. And while no one ever claimed precision medicine would be easy, we’re learning just how hard it is to combine multiple, disparate data types for the purpose of improving human health. 

Indeed, the idea of precision medicine used to be more simple. In the beginning, there was only clinical data and expression data. Today, precision medicine is moving beyond single modalities and looking at how to assign treatment to patients based on multiple -omics data and other data types.

Adding more complexity is the way we now understand disease. Take cancer, for example. We used to think it was just one disease. But based on the seminal work of Charles Perou, who used expression analysis to subphenotype breast cancer, we now know that it’s many different diseases. Stratifying phenotype and genotype to distinguish disease based on various characteristics is what we must continue to do to develop effective therapies for patients. 

How we view our obligations is evolving as well. The U.S., after years of investing in precision medicine initiatives and realizing that its outcomes aren’t significantly better than nations with no investments, is revising the mantra of precision medicine. The “We must learn from every patient,” has shifted to “We must learn from every patient and translate what we learn to larger populations.” Doing otherwise simply isn’t scalable or cost-effective for our healthcare systems.

But we have made significant progress, and that is perhaps why precision medicine now poses the challenges it does. Advances in the -omics fields–transcriptomics, epigenomics, etc.–are continuing. We can begin to take a holistic approach to precision medicine, rather than the reductionist view we have been taking. Systems biology used to be a dirty word, but luckily it has become popular again.

And a new paradigm is emerging — that of population-based precision medicine initiatives, such as UK Biobank and All of Us. These initiatives examine genomics data alongside phenotypic data, but reveal just how sorely we need platforms to standardize, manage, and analyze multiple data types. The platforms must be able to transact multi-omics data along with electronic health records data. They must promote provenance, auditability, scalability, and security. And most of all, these platforms must be accessible to scientists and clinicians from multiple disciplines to transform data into information that helps us translate what we learn from patients to larger populations. 

To accommodate these complex needs, DNAnexus has partnered with industry leaders to build DNAnexus Apollo.

For more information, watch the video below.

1. Liu MC, Pitcher BN, Mardis ER, et al. PAM50 gene signatures and breast cancer prognosis with adjuvant anthracycline- and taxane-based chemotherapy: correlative analysis of C9741 (Alliance). Nature News. https://www.nature.com/articles/npjbcancer201523. Published January 6, 2016. Accessed October 4, 2019.