From Sample to Insight: Technologies Driving the Future of Precision Oncology Assays
answer is that billions of dollars of investment in sequencing the human genome and then devel- oping tools for mass screening our populations have fallen far short of the hope and promise that all diseases would be better understood once we had the genomic blueprint of life. The stark reality is that genomics alone only explains a small part of overall health and the most common disorders. This becomes clear when we confront a simple fact —if we sequence a newborn baby’s genome, how well can we predict their life long health journey? In most cases, we can’t predict much at all. Missing the Environmental Picture At the population level, few diseases are predomi- nantly genetic. A better view is that our life’s health trajectory is determined by an interplay between our genes and environment. Over the past 20 years, epigenomic and other studies have confirmed how environmental influences can even shape gene expression–this only further enforces that we cannot partition our genes from our environment the way we have been doing in most genomics scientific research to date. Still, the current biomarker landscape remains deeply rooted in genomic sequencing. This is like going to a gallery and only looking at the frames, ignoring the masterpieces that lie within. The time has come to truly embrace environmental data, not to supplant genomics but rather to augment it. Understanding environmental influ- ences has tremendous potential to clarify—and synergize with—existing genomic information.
This is particularly true for neurological condi- tions. The brain remains a (mostly) black box, and so far, sequencing has provided little illumi- nation. We see this in twin studies of many brain disorders, including those that arise in child- hood, such as autism spectrum disorder (ASD) or at other life stages, e.g., schizophrenia in adults to ALS in older adults. If a person’s genomic inheritance were truly their destiny, there would be no variations between identical twins. Yet, there are many examples of twins’ neurological health diverging. Environmental factors influence their development even prenatally. This shouldn’t be surprising–many identical twins are not born with the same birth weight. Why? Their genes are identical, and so is their household, same mother, same father, same diet, etc. The reason identical newborns can differ in their body weight is that their internal environment–think of it like their metabolism–is different, even prenatally. Genetics, therefore, has almost no ability to explain some- thing as simple as why two identical newborns don’t weigh the same. Integrating Environmental Data While scientists have known for many years that the environment directly impacts our health and influences gene expression, it’s only relatively recently that we’ve had the technology to develop biomarkers that can deal with the complexity of environmental exposures and our body’s response to those exposures. First, we are now awash in environmental data. Air pollution sensors, satellites, and other instruments
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