John Dolan on Aging and the Horrifying Conclusion of GWAS

Behold! The ideal reference human.

The eXile Guide to Aging

Look down at your hand. Flex the tendons, watch them ripple under the skin. What a nice design! So silent and quick. That’s what they never get in these cyborg movies: the fact that a really good design doesn’t whirr and clank. It’s silent and quick, like bodies are. Like yours. Yours, these sinews; and that long, stretchable leg, genital toy, brave shoulders, stubborn toes, a zoo of perfect forms and all yours for the price of admission.

There’s only one little flaw: you are trapped in the body of a dying animal…

There’s been a mistake. Someone screwed up the design, with malicious intent. Can you sue Darwin? Can you negotiate an exit from this dying animal? Apparently not. What are we, mere medieval peasants, serfs? Absolutely.

Read this. Digest it.

Now, consider the conclusion of “Clinical assessment incorporating a personal genome” [Lancet 2010; 375: 1525–35]

Important limitations remain in our ability to comprehensively integrate genetic information into clinical care. For example, a comprehensive database of rare mutations is needed. Since risk estimates change as studies are completed, a continually updated pipeline is necessary. There are imperfections in all human genomes published to date—false positive and false negative SNP calls, incomplete measurement of structural variation, and little direct haplotype data. Finally, gene-environment interactions are challenging to quantify and have been little studied.

Really? And what are these “important limitations?”

  • “database” not “comprehensive” “enough”
  • “imperfections” in “published” data
  • “challenging to quantify”

OK. Skip ahead two decades. We’ve done more studies, our models have improved, and our data is more complete.

Prediction: This same paper will be published in two decades with the following conclusions:

  • “database” not “comprehensive” “enough”
  • “imperfections” in “published” data
  • “challenging to quantify”

Why? For once in medicine, the disappointing conclusion is not because the clinical application was sloppy. This is excellent data analyzed by excellent people using excellent methods. The problem with this paper is the premise —first paragraph, first sentence:

the clinical translation of genetic risk estimates remains unclear

No! The clinical translation of genetic risk estimates remains clearly to be what we already know about human medicine:


The conclusion of GWAS is right there, in your face, cold and ugly. You’re an animal, animals die, and there’s nothing you can learn about yourself to change that.

There is no “silver bullet” in software, and there’s no silver bullet in medicine, because there is no particular feature you can correct or understand about the human body to achieve a clinical expectation of “perfect health” because that hypothesis is nonsensical.

Life is not the movie Avatar. The Nature Tree doesn’t love you, and you won’t live forever if you can always remember your yoga mat and buy fresh groceries at Whole Foods. Disease is not a human flaw, it is a human feature, and a disease-free human would not be human as we understand humans to be. It is an insane, desperate superstition to believe that if only we can “purge all unnatural toxins” or “fix all diseases” or “learn everything about our bodies” that we’ll live in “good health” forever. No, you won’t, and you’ll be dead before you can tell anybody that you didn’t.

All existing medical science from antiquity to present confirms this conclusion, and I am unaware of any credible counter example —which I consider to include a living adult human who is casually indistinguishable from middle age, but who is actually over 150 years old.

I’m not discouraging research or clinical application of genomics. I’m saying that the ideal human is not good enough if your premise includes an expectation of superhuman health.

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