“Begin at the beginning,” the King said, very gravely, “and go on till you come to the end.” Lewis Carroll
Exposome Perspectives Blog by Robert O. Wright, MD, MPH
A common criticism of exposomics is that it is “amorphous”, and “without boundaries”. How can we possibly measure everything, everywhere, all the time, all at once? There was a time when the same criticism was leveled at genomics—after all, measuring 4 billion base pairs was a tall order, but at least it was finite and didn’t change with time. Exposomics, however, is a very different bird—it includes diet, behavior, toxicology, social stress, emotions, neighborhood characteristics, work environment, etc. Furthermore, you have to measure it repeatedly. While it may seem to be a larger task, the exposome may not actually be bigger or harder to measure than the genome.
Should we even try and measure the entirety of the exposome?
Our daily exposome is much, much smaller than our genome and much, much smaller than our lifetime exposome. We don’t even have to measure every day, if we choose wisely, we can measure a subset (e.g. weekdays vs. weekends, multiple seasons, etc). Perhaps, the exposome only appears to be amorphous because we are not starting at the beginning. We are already very good at measuring all the social, chemical, physical, nutritional, infectious components of the exposome, but we do so in isolation. To promote collaboration, we need a repository that can accommodate different measurement types and has an informative structure for all of the exposome’s components. As we systematically measure and catalogue more and more of our environment, we will start to see its shape and connections.
Ultimately, our goal shouldn’t be to measure the “entirety of the exposome.” We should instead determine a set of reference exposomes that arise during important life stages and focus on those key parts. Once we know that information, we can model the rest. We know already that there are patterns—chemicals and nutrients travel together in consumer products and food. They have predictable metabolites. Social stress ebbs and flows with age or occupation and correlates with pollution levels (ask anyone living near a Superfund site whether pollution causes social stress). Like any other journey, we need to start with a map.
Science, Deus Ex Machina and Anagnorisis.
Deus Ex Machina is Latin for “God from the machine.” It is the name of the off-stage crane that raised and lowered the actors portraying Roman or Greek Gods in ancient plays. In literature it’s used to describe a contrived plot trick that resolves a conflict, i.e. divine intervention that relies too much on impossible odds being overcome. For example, James Bond escaping certain death from an otherwise brilliant villain who talks too much. Likewise, Batman’s utility belt seemed to overflow with just the right weapon to win his current fight, whether he needed glue, rope, shark repellent, or even kryptonite.
A Deus Ex Machina device will not solve the exposome puzzle. While understanding the exposome will be a very difficult lift, it will be a game changer and different type of plot device is needed. An exposome map is an ‘anagnorisis’ which is Greek for a “discovery”, representing a turning point in a story. Building an exposome map is the moment when Bruce Willis realizes he is actually dead in the ‘Sixth Sense’ or when Jon Snow realizes he is a Targaryen Prince. Maps will reveal the true identity of the exposome because maps are foundational to the exposome plot.
Everything, Everywhere, All the Time, All at Once.
If we are to bring order to chaos in our quest to study exposomics, we must define its boundaries while embracing its complexity. Maps are very good at defining boundaries, so let’s start there. What do we know about exposomics? We know that it varies geospatially with regards to air, water, culture, food, social stressors, and pollution. Because there is a geographical correlation of the exposome that ties to spatial characteristics (e.g. urbanicity plus mountains), we know that the air in Los Angeles will be more polluted than in Yellowstone Park. By mapping more and more of the characteristics of many places, we can predict what is happening in similar places around the world.
The exposome also varies with calendar date. Air pollution changes with the season and in some places air pollution has gotten better over the last 50 years, in other places it’s gotten worse. Air pollution is not unique in varying over time. Blood lead levels are decreasing over time, but Perfluoryl Alkyls blood levels are increasing with time. Our map can show the spatial and temporal patterns of the exposome. The exposome depends on behaviors including eating, drinking and exercise. Behavior correlates with age and life stage. Therefore, the exposome will correlate with life stage. Infancy, preschool children, school age children, adolescents, young adults, middle aged adults, and elderly adult life stages will all have different exposome patterns.
There will also be exposome patterns that correlate with cultural practices, social networks, diet and neighborhood. Race is a social construct and will correlate with our exposome because racism correlates with the exposome. We know that redlining divided the geography of where people live by race and that redlining correlates with higher levels of air pollution and poorer access to healthcare and education. Toxic waste sites are not randomly distributed but instead cluster in poor, minoritized neighborhoods. We should add all the known toxic waste sites to our map and what is in them as a starting point. Social class also has a spatial pattern that correlates with the exposome. Furthermore, all these mapping dimensions intersect: geography, time, life stage and social class/race/ethnicity. An exposome map will help us understand the root causes of health disparities that track with racism and how these environments change over time and affect us at different life stages. Most importantly an exposome map will point us toward solutions and will have far greater impact on health disparities than anything we have ever done before in science.
The best part of mapping is that you can map everything, everywhere, and all at once. If we know an address or global positioning system (GPS) coordinates, we can place the measurement inside a map. If we measure blood lead, air pollution, neighborhood crime, income, diseases, noise, light and wavelengths, presence of pets, number of televisions in a house etc., we can place that information in a map. We can map the origin of social media tweets, pesticide use, untargeted assays, disease rates etc. We can make maps that vary by calendar date and/or make them specific to life stage (i.e. map Perfluoryl Alkyl levels in people >65 living in Manhattan) to address these dimensions. Our map should not stop just at the exposome either. Diseases can be mapped and add another dimension.
Color codes can help us see patterns—we can map cancer rates and overlay Perfluoryl Alkyl levels then restrict it to people over 65 using color codes to see disease and exposure clusters. The exposome map will be a powerful means of discovery showing us the correlational structure of the exposome. If the correlation is strong enough, we may be able to a select a subset of exposures to conduct an exposome study. Just like how Genome Wide Association Studies use the correlational structure of the genome by measuring a subset of genetic variants (rather than sequencing the whole genome), we may be able to measure a subset of exposures to characterize the ambient exposome, the chemical exposure, the social exposome, etc.
At present that correlational structure is largely unknown, especially across the different domains of chemicals, social environment, age/life stage, etc. Perhaps as we build these maps, we should begin by thinking of each domain as its own exposome. There are no true experts in measuring all of the components of the exposome. Different sets of scientists have the skills to measure the chemical, physical, social, infectious, nutritional aspects. Each can work on their piece of the map simultaneously and as we get nearer and nearer to completion, we can begin to overlay them and understand where, how, in whom, and why they intersect over place and time.
The first map is time
The most important reason we must first map and then model the exposome is time—to map an existing person’s exposome, you need to go back in time. My personal exposome goes back to 1963 and covers two different continents and cultures, not to mention six different homes. Most of the exposures from my past cannot be directly measured, but a global exposome map may make modeling my past environment a possibility and help predict my future health.
This project is as important as the Human Genome Project—in fact without the exposome map, we will never fully understand how the genome works as genes always interact with environment across our lifespan, turning on and off due to signals from our diet, social life, physical environment, air, infections and well—everything around us—all the time. We need to start this map now. As Lewis Carroll once wrote: “I don’t see how he can ever finish, if he doesn’t begin.”