“A PATH, A PATH, A PATH!” The Knights who say ‘Knee’”
(Monty Python and the Holy Grail)
Exposome Perspectives Blog by Robert O. Wright, MD, MPH
I grew up in the American Midwest where road signs are decent, honest, and hard-working. So when I moved to New England in 1993, it was a shock to learn that New England road signs were lazy, ill-mannered, and untruthful. Worse, they only lied on occasion; I would have preferred if they lied all the time, as that would have made it easier to get around.
I’ll begin with the exit to my old house in Sharon, Massachusetts—exit 10 off I-95. The sign told drivers to turn right to get to Sharon, but since I lived in Sharon, I knew that Sharon was to the left. A right turn would take you to Walpole, Massachusetts. If you were a visitor unfamiliar with the local tradition of posting useless signage, you would soon become hopelessly lost. In New England the phrase “you can’t get there from here” would sometimes be expressed with a mix of pity and schadenfreude, particularly at the local Dunkin Donuts, where, confused and frustrated, you inevitably asked for directions.
But roadmaps and getting lost are not just for cars; they are also used in science to similar ends. In previous blog posts, I have written about geospatial maps. This post is about biological and metabolic maps and the pathways that biochemical reactions take in response to our exposome. It’s also meant as a plug for an older science—physiology—and how that field aligns with the exposome. Just like our road system can be visualized as a complex interconnected map of highways, roads, and bridges, human biochemical pathways, such as KEGG pathways, display biological reactions like a map, in which proteins, nutrients, and chemicals are processed, turned into energy, bio-transformed, excreted, or stored in our cells.
Over the years, science has evolved to favor molecular biology as the key to understanding health. Physiology, which studies how our body functions at the macro level, is much less emphasized. In the age of single-cell analysis, physiology often takes a back seat to molecular processes. KEGG Pathway Maps are a research tool that visually illustrates molecular interactions, reactions, and networks. Their maps are useful tools to understand biological connections but they are two-dimensional. Travel and biology are actually four-dimensional processes. We drive up hills and down valleys. The speed limit changes; traffic patterns vary with time, and travel between any two points of equal distance can, therefore, take different amounts of time. Maps have difficulty conveying all these components without becoming so complex that they are unreadable. KEGG pathways also tell us little about how reactions may affect cells in other tissues over the course of many years. This means they tell us little about physiology, i.e., how all the reactions work together to produce functions. Mechanisms can occur across tissues and can evolve across time. I would argue that today’s science has a “molecular pathway bias” that I call “linear” thinking as shorthand. Mechanisms can occur at the macro level too. For example, perhaps I believe I have heart disease due to lead exposure. I may have been exposed to lead in my 20s while working in construction. Is it enough to look at cardiac molecular reactions that arise from lead exposure, or is toxicity more than just the molecular reactions arising from lead exposure to the heart?
To bring us back to roadmaps, the shortest distance between two points is a straight line, but the shortest distance is not necessarily the most scenic, or it may have too much traffic and may actually take longer than alternative paths. Think of your life as a long trip with many stops that can take different amounts of time and distance. You can take a trip to a disease destination through many different paths. Likewise, to drive to Los Angeles from New York you can drive through a number of different and interesting cities along the way, such as Chicago, St. Louis, or Denver. The path to one city can involve other cities. Similarly, the path to one disease can involve another disease.
First, let’s return to the example of how lead poisoning might cause heart attacks. What may be the mechanism? How does lead impact the cardiac myocytes (heart muscle cells)? Perhaps, lead affects calcium channels in the heart, impacting the electrophysiology of the heart. But is there another road you can take from lead exposure to heart attacks? Maybe there’s a road from hypertension, i.e., another disease that leaves the town of lead and connects to heart disease? We know that lead damages the kidneys’ proximal tubules and can cause interstitial nephritis. Damaged kidneys lead to hypertension. If I had been exposed to lead in my 20s from my workplace, I may have developed subclinical hypertension. Hypertension, especially when chronic, is an insidious risk factor for heart attacks that may have no symptoms. So in this example, lead poisoning could cause heart attacks by first damaging the kidneys to cause hypertension. There could even be no direct effect of lead exposure on the heart in this scenario. Looking just at a cardiac molecular pathway would miss the pathway from lead exposure to cardiac disease because the map doesn’t have the stop at kidney town. You could argue that molecular reactions in the kidney mattered in my example, but even so, without factoring in the bridge from the kidney to the heart created by physiology, we would have missed the bigger picture.
Like scientific thinking, fiction is also famously linear. Characters have arcs of development. Plotlines show us their motivations, fears, and desires. Against this dogma, some authors have rebelled against the linearity of storytelling. Julio Cortázar is considered a giant of Latin American literature, although he is less famous than Gabriel García Márquez. I first discovered him through a short story called “The Continuity of Parks,” which is only a five-minute read—but a blockbuster five minutes that blurs the boundaries of storytelling. I won’t spoil it beyond that. Cortázar was fascinated with the structure of storytelling and experimented with non-linear fiction. Cortázar believed that if fiction were to mimic life, it should not be linear, because life is never linear. People grow in some areas and regress in others. I believe if Ebenezer Scrooge had been invented by Julio Cortázar, he may have adopted Tiny Tim but still fired Bob Cratchit for using too much coal in the office furnace.
His most famous novel is called “Hopscotch” and has 155 chapters, but Cortázar describes the last 99 as “expendable.” These chapters fill in gaps about characters, their motivations, and backgrounds, even though they are written as brief non-sequiturs—metaphors for our day-to-day experience. Perhaps this is an intentional misdirection, as life has many seemingly “expendable” moments that upon reflection, are actually very telling. Cortázar first suggests readers tackle Hopscotch in two ways: either linearly from chapters 1 to 56 (the 99 expendable chapters are at the end) or by randomly selecting an order through the entire set of 155 chapters. He even provides a suggested road map of his favorite order that, if followed, sends the reader into a loop “hopscotching” back and forth in time. Cortázar believed that stories are nothing more than snapshots of episodic memory, smoothed out by the storyteller, and by definition, always incomplete in their capacity to capture reality.
Likewise, in research we have only snapshots of our exposome, transcriptome, epigenome, and proteome. We then use statistics to smooth out the missing pieces—just as great writers smooth out their stories. “Hopscotch” was an attempt to give readers a nonlinear option of creating a unique story path of their own with near-infinite beginnings, middles, and endings. Perhaps Cortázar understood something very fundamental that we can apply to our research—that our scientific tools can only ever capture incomplete pictures of health and disease. While we cannot “make up” random research stories by determining the order of stops in the biological pathways, because we are always constrained by our data, but we should have the humility to recognize that we are never measuring everything that is happening. We are instead smoothing out many, many missing pieces of the puzzle—whether we know it or not.
As we interpret exposomic data, we should consider the potential flaw of linear thinking in our pathway analyses and the role of physiology. A molecular mechanism is not the only possible story. Everything is connected, and the exposome rarely will act uniformly on all our cells and can’t predict how these disproportionate effects will carry forward to distant tissues. Time makes an effect that arises when we are young evolve to a completely different effect when we are old. Our ability to perceive how the exposome operates on our health may be limited but it is attainable if we remember that we are just hopscotching through snapshots of data, taken at oblique angles and across time. We shouldn’t get trapped into thinking linearly all the time or that seeing the bigger picture is easy- or if there is only 1 bigger picture rather than multiple possibilities. If we can ever do that, one day we can correctly patch the chapters of health and disease together in an order that reflects life.