A version of this originally appeared in the Timmerman Report.
When President Obama announced the Precision Medicine Initiative (PMI) back in 2015, it was a moment not unlike when a pop star drops a new album. We know she’s working on something, but details are scarce until that midnight announcement on iTunes. Then Boom!
This was Precision Medicine’s coming out party, the moment when a sensible, but somewhat obscure biomedical research concept went mainstream. And it’s exciting! As someone who’s been on the Precision Medicine bandwagon for a while now, I’m glad to see the concept getting more attention.
And yet, I’ve found myself worrying that we haven’t learned from the past and once again we’re riding a hype rocket destined to crash and burn like the first (and the second, third, and fourth) attempt at getting that SpaceX booster stage to land on a platform in the Pacific. While we’ve learned an amazing amount about human genetics over the past few decades, there’s much more we still don’t know and understand. While genetics races ahead, we are often still stuck in neutral when it comes to our understanding, much less predicting, the effect of the environment on genes’ effects on phenotype. It’s not easy.
Think, for a second about autoimmune diseases like type 1 diabetes, celiac, or rheumatoid arthritis. We don’t know what causes most of them, or causes them to flare up, but evidence is pointing toward the complex interplay of genes responding to environment. Consider the research on autoimmunity in Finland, compared with that across the border in Russia’s Karelia territory. As Moises Velasquez-Manoff has described, despite having quite homogeneous populations, and a similar geographic environment, the Finnish side sees much higher incidences of autoimmunity and allergies. Finnish scientists are increasingly pointing to genetic variations that have allowed Russians in a less-hygienic environment to avoid some of the autoimmune conditions that have emerged in Finland.
Or consider some provocative cohort studies from Florida, which characterize the timing of diagnosis for inflammatory bowel disease (IBD) in Cuban immigrants. Over time the duration between arrival in the US and diagnosis for IBD has been decreasing. Immigrants who arrived before 1980 had an average time to IBD diagnosis of 31.77 years, whereas immigrant who arrived after 1995 had an average time to diagnosis of 8.30 years. Given that the genetic background of immigrants is expected to be similar over time, the evidence suggests environmental factors.
Changes to the environment, including subtle ones that might seem trivial, sometimes matter.
Basic research often has a hard time justifying its existence in a world that wants immediate payoffs, but this is where it helps to look to basic research for guidance. In specific, we can learn from plants in space. There’s something here for everyone who studies eukaryotes.
I used to work on Arabidopsis thaliana – a genetically complex plant model organism that non-scientists would call a roadside weed. My ears perk up whenever I hear a story about Arabidopsis in the news. A few years back, researchers sent seeds up into space and grew Arabidopsis in microgravity. According to this report, while plant morphology was generally the same, the secondary branches and seed pods grew out perpendicular to the stem. On Earth, branches and pods normally point upwards, making an acute angle with the stem.
Who knew? But more to the point, who would have predicted this? I suspect no one would have guessed. Studies like this in space may help us actually figure out ahead of time, eventually, what effect microgravity will have on the growth pattern of seed pods, not to mention the many other things going on that weren’t or couldn’t be measured. It might also help us confidently predict the phenotypes that wouldn’t be affected. But this will take a lot of time and much better predictive models for gene regulation and phenotypic expression.
Arabidopsis had its genome sequenced back in 2000. It has been the subject of much basic and applied plant biology research—at this point, it’s probably the best studied plant on the planet (sorry maize—you had a good run). Scientists took advantage of the relatively easy transformation methods of Agrobacterium-mediated gene disruption and the ability to do blanket mutagenesis screens to define dozens of developmental and metabolic pathways. Many of those findings were used to improve numerous crop species (something to consider, for those in the US Congress who scoff at spending on basic research). But even after all this investment and research, I don’t think any scientist would suggest we’ve solved Arabidopsis to the point where we can predict everything about how it would grow, develop and otherwise behave when introduced to a new environment. But it’s a simpler model and easier place to start than human biology.
Parenthetically, speaking of unexpected things that happen to organisms in space, I’d suggest you check out this great piece on sex in space by Maggie Koerth-Baker and how the birds and the bees (and the rats) don’t (ahem) function the same in space either.
The heart of Precision Medicine is giving patients tailored treatments based on the molecular fingerprint of their diseases or conditions. There will be better efficacy and fewer side effects of new drugs because the treatment will be more specific. It’s no mystery why the current forefront of Precision Medicine is in cancer, where the strong causal connection between genetics and phenotype means therapeutics tailored for specific mutations in specific oncogenes or other biological processes provide a clear, straightforward path to Precision Medicine. If you have mutation X in gene Y, then take drug Z, which was developed to target that precise pathway.
This simple path works best, however, if the genetic penetrance is nearly complete and is not affected by environmental factors. Outside of cancer there aren’t as many examples of common genetic risk factors that have strong causality, even in combination. When you don’t have that kind of tight causal relationship, Precision Medicine is harder to pull off. The recent Omnigenic model proposed by Evan Boyle, Yang Li, and Jonathan Pritchard, which suggests most genes in a given tissue influence disease susceptibility, and the resulting debate about the applicability and value of GWAS moving forward shows the ongoing evolution in how genomicists and clinicians look at the interplay between our genes and phenotypes. The implication of a model like this is that even when looking only at the genetic side of things, strong causality driven by a small, testable number of variants for many diseases may just not be how biology works.
Adding to this, the plants in space example suggests to me that even as we learn more about genetic contributions and subsequent gene-by-environment interactions, some of that knowledge has an expiration date because of how our environment is changing.
Look at China. Thanks to decades of coal-burning for energy needs, China is currently experiencing a frightening air pollution challenge in some of its larger cities. How is that environmental phenomenon affecting gene expression and penetrance of variants? How will it affect development and gene expression and development of chronic diseases in the future? The airborne irritants and continual exposure might have no effect at all. Or they may have dramatic effects that will render some potential therapeutic pathways more or less effective in that population five, 20, 50 years from now. If, let’s say in a crazy hypothetical situation, which our government is assuring us will never happen, the global temperature was on track to increase by an average of 2 degrees Celsius or more over the next century, with all the cascading environmental changes that would cause, how would our genes respond?
I guess this just reduces down to a call for some circumspection. The very fact that Precision Medicine has entered the common lexicon is a reason for biomedical researchers to be cautious. Overpromising has already happened, but it could get a lot worse. At a time when funding for science is under siege, we don’t need examples at which naysayers can point as instances where scientists promised they’d cure cancer, but didn’t.
The science is already amazing. There are terrific things coming down the biopharma pipelines. And I think we’ll get a handle on gene-by-environment interactions—enough, at least, to meet the goal of creating specific health solutions based in part on each person’s genome for some diseases (although if the late Susan Lindquist’s HSP90 hypothesis turns out to be correct, many bets are off). But health and environment are moving targets. If we want Precision Medicine to be like the successful SpaceX launches, we need to keep an eye on things outside the controlled environments of our labs and clinical trials and do everything we can to embrace and understand the conversation our genes are having with the world outside.