The Boeing 737 Max and Evolutionary Medicine

The Boeing 737 Max and Evolutionary Medicine

The recent Boeing 737 Max crashes provide a tragic illustration of how the core principle of evolutionary medicine can be useful for understanding failures of machines as well as bodies.

On October 29, 2019 Lion Air flight 610 crashed into the Java Sea 13 minutes after takeoff, killing all 189 aboard. Initials explanations focused on what was different about that individual plane and its pilots. This is a mechanic’s approach, much like most medical research. It asks what part of the mechanism failed in this individual instance.

On March 10, 2019 Ethiopian Airlines flight 302, another Boeing 737 Max, crashed six minutes after take-off. The similarities to the previous crash turned attention to shared traits of Boeing 737 Max planes. This is an engineer’s approach. It poses the question asked by evolutionary medicine: why did the forces that shaped the design leave it vulnerable to failure?

The course of events that led to the tragedy began a decade ago when airplane manufacturers were in a desperate competition to reduce fuel costs and increase range. Airbus had the advantage. The competition created strong pressure on Boeing to create a new model fast, in much the same way that pathogens can induce strong selection pressures.

Planes, like bodies, have path dependent designs that make starting from scratch nearly impossible.  So, Boeing decided to adapt an older 737 model.

Longer-range and better fuel efficiency required larger engines that could not be mounted on the older 737 models, so the wings were shifted forward on the fuselage to accommodate the larger engines. The trade-off gave fuel cost and range benefits that increased linearly with larger engine size, but risks that increased exponentially, especially stalling during the climb after take-off. A cliff-edged fitness function resulted.

In recognition of the risks, engineers added a defense system to monitor angle and airspeed and automatically push the nose down when a stall is imminent. As is the case for bodily defenses, dire risks were manifest only in unusual circumstances. Sensor failure activated the automatic stall prevention mechanism and pushed the nose down even as the plane plummeted.

Engineers who recognized the risk suggested adding redundant sensors and controls, but the changes were rejected because they would add cost and delay.  If a sensor failed, pilots could turn off the automated system.

However, the rapid change in design was not fully coordinated with pilot training so some did not know about the automatic stall prevention system and how to turn it off. Catastrophic failure required failure of only one component combined with inability of the pilot to respond quickly and accurately in an emergency situation.

Test pilots reported related problems two years ago, but their experiences were never analyzed in a way that revealed the inherent vulnerability of the Boeing 737 Max.  Today’s news suggests that their concerns may have been concealed to avoid costly delays in production.

Could the principles of evolutionary medicine have helped to prevent the tragedy of Flights 610 and 302?  We can’t know, but system failures, whether bodily or mechanical, make more sense in light of careful attention to the forces shaping the design, the historical sequence and path dependent constraints, trade offs, fitness functions, and the vulnerabilities imposed by defense systems.

Articles in The Economist, The Atlantic and other media sources provided background for this essay; it is intended to be illustrative, not definitive.

Why NIH needs evolution expertise–The amyloid beta case study

Why NIH needs evolution expertise–The amyloid beta case study

Sharon Begley has written a lovely article on Tanzi and Moir’s research on the antimicrobial properties of amyloid beta and the outrageous difficulty they have had getting NIH to fund their work. They noted that study after study has found no benefit from treatments that disrupt amyloid synthesis, and that there must be some reason why amyloid beta exists.

The crucial paragraphs are in italics below

“For years in the 1990s, Moir, too, researched beta-amyloid, especially its penchant for gunking up into plaques and “a whole bunch of things all viewed as abnormal and causing disease,” he said. “The traditional view is that amyloid-beta is a freak, that it has a propensity to form fibrils that are toxic to the brain — that it’s irredeemably bad. In the 1980s, that was a reasonable assumption.”

But something had long bothered him about the “evil amyloid” dogma. The peptide is made by all vertebrates, including frogs and lizards and snakes and fish. In most species, it’s identical to humans’, suggesting that beta-amyloid evolved at least 400 million years ago. “Anything so extensively conserved over that immense span of time must play an important physiological role,” Moir said.  What, he wondered, could that be?

Their subsequent work has demonstrated beyond doubt that amyloid beta is a powerful antimicrobial [1] and has strongly suggested a role for herpes viruses[2]. But despite these findings, they still are having difficulty getting their work published and getting NIH funding. I predict this will lead to a Nobel prize, and go into the history books as an especially egregious example of how pure reductionism obstructs progress.  Evolutionary thinking about the reasons why we are vulnerable to Alzheimer’s disease adds the missing perspective. We can hope that it will also inspire new approaches to prevention and treatment.

  1.  Kumar, D. K. V., Choi, S. H., Washicosky, K. J., Eimer, W. A., Tucker, S., Ghofrani, J., … others. (2016). Amyloid-β peptide protects against microbial infection in mouse and worm models of Alzheimer’s disease. Science Translational Medicine, 8(340), 340ra72–340ra72
  2. Eimer, W. A., Vijaya Kumar, D. K., Navalpur Shanmugam, N. K., Rodriguez, A. S., Mitchell, T., Washicosky, K. J., … Moir, R. D. (2018). Alzheimer’s Disease-Associated β-Amyloid Is Rapidly Seeded by Herpesviridae to Protect against Brain Infection. Neuron, 99(1), 56-63.e3. https://doi.org/10.1016/j.neuron.2018.06.030

Photo credit: Creator:Jon ChaseInformation extracted from IPTC Photo Metadata

How EvMed Misled Me—The ASA saga

How EvMed Misled Me—The ASA saga

The history of medicine is replete with examples of the disasters that result when clinical practice is guided by theory alone. For instance, in the early 20th century sudden infant death was attributed to suffocation caused by an enlarged thymus.1 Thousands of infants received radiation treatment that created an epidemic of thyroid cancer, with new cases still emerging 45 years after exposure.2 

Such examples make most of us in evolutionary medicine extremely wary of basing clinical advice on theory. However, recommending aspirin to prevent strokes and heart attacks seemed like a sure thing. In modern environments, bleeding is less of a risk, and clots in coronary or cerebral arteries are a much more of a risk, than in ancestral environments. Taking a baby aspirin every day should adjust the tradeoffs to help our ancient bodies cope better with modern environments.  Also, studies showing that a baby aspirin a day reduced heart attacks by more than 25% led medical organizations to endorse aspirin for prevention.3

The data supported the evolutionary theory, so I started taking a daily aspirin, and I recommended that my patients over 50 years old do the same. Millions of people took an aspirin every day for years. But it is becoming clear that even solid theory and supporting data are not enough.

The first warnings came from new studies showing that even small doses of aspirin caused more gastrointestinal bleeds than expected. Then, late in 2017, the results of a double-blind long-term study were published. The ARRIVE trial enrolled over 12,000 subjects averaging 55-60 years of age with an average risk for a heart attack; half got aspirin half got placebo. At the end of five years, cardiovascular death, myocardial infarction, unstable angina, stroke, or transient ischemic attack had occurred in 4.29% of the aspirin group, and 4.48% of the placebo group.4 The rate of gastrointestinal bleeding was twice as high for the aspirin group. I stopped taking aspirin and decided to write this article.

This will not be the last word on the issue; compliance was inconsistent, and the results may not generalize to people with higher risk. Patients who have had a cardiac event should not stop their aspirin. But the trial offers yet more evidence that there is no substitute for a controlled trial with random assignment…and that clinical recommendations based on apparently solid evolutionary thinking may not be justified, even when apparently supported by data.

  1. Symmers D. The Cause of Sudden Death in Status Lymphaticus. Am J Dis Child. 1917 Dec 1;14(6):463–9.
  2. Adams (Michael) Jacob, Shore RE, Dozier A, Lipshultz SE, Schwartz RG, Constine LS, et al. Thyroid Cancer Risk 40+ Years after Irradiation for an Enlarged Thymus: An Update of the Hempelmann Cohort. Radiat Res. 2010 Dec;174(6):753–62.
  3. Patrono C, García Rodríguez LA, Landolfi R, Baigent C. Low-Dose Aspirin for the Prevention of Atherothrombosis. N Engl J Med. 2005 Dec 1;353(22):2373–83.
  4. Gaziano JM, Brotons C, Coppolecchia R, Cricelli C, Darius H, Gorelick PB, et al. Use of aspirin to reduce risk of initial vascular events in patients at moderate risk of cardiovascular disease (ARRIVE): a randomised, double-blind, placebo-controlled trial. The Lancet. 2018 Sep 22;392(10152):1036–46.
After 60 years, the seminal Williams paper on aging is aging well

After 60 years, the seminal Williams paper on aging is aging well

The paper George Williams published in 1957 about senescence has inspired much of the field of evolutionary medicine.  I never heard about it in medical school, but the evolutionary biologists I was talking with at the University of Michigan in the 1980’s said I should get a copy. Reading it changed my life. If aging has an evolutionary explanation, what about everything else in medicine?  I spent a summer in the library finding and analyzing data on survival curves for animals in the wild.  They showed that senescence greatly decreases fitness for many species in the wild, contradicting the the mutation accumulation theory, and supporting Williams’ idea of antagonistic pleiotropy. That led to publications and a wonderful collaboration with George for the next two decades. 
Now 60 years after its publication, Williams’ article remains fresh. In a new article in Evolution, Laillard and Lemaître offer a review of the paper, and the status of the hypotheses it proposed. I hope it inspires many people to read the original paper that inspired much of the progress in evolutionary medicine. 
Gaillard, J.-M., & Lemaître, J.-F. (2017). The Williams’ legacy: A critical reappraisal of his nine predictions about the evolution of senescence. Evolution. https://doi.org/10.1111/evo.13379
 
 
Abstract:  Williams’ evolutionary theory of senescence based on antagonistic pleiotropy has become a landmark in evolutionary biology, and more recently in biogerontology and evolutionary medicine. In his original article, Williams launched a set of nine “testable deductions” from his theory. Although some of these predictions have been repeatedly discussed, most have been overlooked and no systematic evaluation of the whole set of Williams’ original predictions has been performed. For the sixtieth anniversary of the publication of the Williams’ article, we provide an updated evaluation of all these predictions. We present the pros and cons of each prediction based on recent accumulation of both theoretical and empirical studies performed in the laboratory and in the wild. From our viewpoint, six predictions are mostly supported by our current knowledge at least under some conditions (although Williams’ theory cannot thoroughly explain why for some of them). Three predictions, all involving the timing of senescence, are not supported. Our critical review of Williams’ predictions highlights the importance of William’s contribution and clearly demonstrates that, 60 years after its publication, his article does not show any sign of senescence.
Human Evolution Continues!…Or more exactly: Only two loci in the whole genome influence longevity

Human Evolution Continues!…Or more exactly: Only two loci in the whole genome influence longevity

 Enormous interest is being generated by a new open access article in PLoS Biology: Identifying genetic variants that affect viability in large cohorts, by Mostafavi, H., Berisa, T., Day, F. R., Perry, J. R. B., Przeworski, M., & Pickrell, J. K.  The press release from Columbia was titled “Large-scale Study of Genetic Data Shows Humans Still Evolving.” New Scientist covered it as “Our genomes reveal modern-day evolution.” At The Atlantic the headline was “Huge DNA Databases Reveal the Recent Evolution of Humans.”  What does the article really show?  

Author summary:  Our global understanding of adaptation in humans is limited to indirect statistical inferences from patterns of genetic variation, which are sensitive to past selection pressures. We introduced a method that allowed us to directly observe ongoing selection in humans by identifying genetic variants that affect survival to a given age (i.e., viability selection). We applied our approach to the GERA cohort and parents of the UK Biobank participants. We found viability effects of variants near the APOE and CHRNA3 genes, which are associated with the risk of Alzheimer disease and smoking behavior, respectively. We also tested for the joint effect of sets of genetic variants that influence quantitative traits. We uncovered an association between longer life span and genetic variants that delay puberty timing and age at first birth. We also detected detrimental effects of higher genetically predicted cholesterol levels, body mass index, risk of coronary artery disease (CAD), and risk of asthma on survival. Some of the observed effects differ between males and females, most notably those at the CHRNA3 gene and variants associated with risk of CAD and cholesterol levels. Beyond this application, our analysis shows how large biomedical data sets can be used to study natural selection in humans.

The method is creative.The authors looked at genetic data from more than 60,000+ people in the Kaiser Permanente  system and 150,000+ people in  the U.K. Biobank and asked if certain genetic variations were less common in older people, implying that people with those variations died young. The astounding result is that only two variations popped out. One is APOE ε4, long recognized as a cause of heart disease and Alzheimer’s disease in modern populations.  The other is a variation in CHRNA3 that is associated in higher smoking rates in smokers. 

  • We know that about 25% of the variation in human lifespan results from genetic variations (Brooks-Wilson, 2013) so there should be genetic variations to be found. Why didn’t they show up?
  • Despite having hundreds of thousands of subjects, the study was able to detect only effects from variations present in over 10% of the population. To achieve genome wide significance requires a p<10−8   Perhaps  many more alleles are waiting to be identified;the authors understandably would now like to look at samples of many hundreds of thousands of people. 
  • Both identified alleles may qualify as “genetic quirks” that may cause harm only when interacting with modern environments.  
  • The authors suggest that perhaps all other common variations have been purged by natural selection, perhaps via benefits to kin from long-lived post-reproductive adults. Kin selection is powerful, but is is plausible that it would eliminate all but two common alleles that reduce fitness up at age 75? This is a better starting point than assuming that genetic drift accounts for most disease, however, it seems unlikely. 
  • Environments are so vastly different now from those of our ancestors that many previously neutral variations should now influence age at death. 
  • Mention was made about antagonistic pleiotropy and its role in aging however  genes that are not polymorphic would not have any variation to find. 
Brooks-Wilson, A. R. (2013). Genetics of healthy aging and longevity. Human Genetics, 132(12), 1323–1338. https://doi.org/10.1007/s00439-013-1342-z