The problems with genomic prediction. Need it be stated again?

We often write about the challenges to prediction of phenotypes, especially disease, from DNA data.  If the trait is clearly due to variation at a single gene, then prediction can be useful.  If most instances are due to variation at a single gene, but not always the same gene, DNA data can be useful as well.  Of course if the variation is in regulatory or other DNA, rather than protein coding parts (genes proper), unless the whole genome is sequenced (not just the 'exomes'), things may be much more unclear.

Most common disease or behavioral traits aren't like that, however.  As we have piles of data to show, traits like cancer, stroke, dementia, and heart disease are typically due to very many but individually minor, contributing parts of the genome, plus, oh yes!, maybe some Environmental factors that, if we're geneticists, we don't really want to have to think much about)  But the big E is the key to trouble, in ways reflected by two stories in yesterday's NY Times Sunday Review section.

The cancer example
One story suggests what is presented as a surprise, that cancer (despite the 40-year 'war' against it by NIH) is rising in lifetime risk, not falling, or at least is going to affect more rather than fewer people in the future.  But, despite the fact that the 'war' on cancer was a bad way to waste a lot of money (good proposals would have been funded without the attraction of a poorly disciplined pot of gold), even if cancer treatments are better (sometimes true, at least), more victims will fall to cancer.  This seems counter-intuitive, so why?

The answer is something well-known to those who know, but poorly explained to the public.   We've written about it before here on MT.  It's called 'competing causes'. As long as we all have to die of something, and the older we are the more damage our various cells sustain, if you remove one cause, those who are spared that then stay alive to be vulnerable to the remaining causes.  Heart diseases can strike relatively early, but cancer, which in many if not most instances is due to mutational and other cellular damage, is a risk that keeps on growing as cells continue to be exposed to mutagens and the like.

This is no new discovery or surprise and the public and all geneticists should by now be well aware of it.  Also, earlier treatment that is developed for other diseases will have similar negative consequences (though of course to those who were saved from earlier death).  The overall health care cost burden is likely the result of research that is successful against earlier-age killers.

Other diseases are part of the Environment of cells unaffected by those diseases. Spared of those, you are exposed to continued mutagens throughout your life.  Yet these changes cannot be predicted, and as a result, genotype-based risk estimates (that aspect of 'personalized genomic medicine') are a fantasy: they may or may not be right and are of unknown--and unknowable--accuracy.

Socioeconomic advances
The other Times article yesterday that caught our attention was about the increased risk of various diseases to those who work their way out of the lower socioeconomic strata in our society.  As they rise in education, wealth and so on, and perhaps because of the stress required to dig oneself out of poverty, people suffer risks of various diseases that are higher than they would have experienced or of their peers in their newly achieved SES group.

Again this is the mixed blessing of changing lifestyles.  It is the again-unpredictable effect of Environmental change.  It's unpredictable even if we knew the specifics of a given sample of cases, because they are always retrospectively analyzed, after things have already happened to that sample, but we can't know how things will change in regard to SES-specific risks or in SES-mobility patterns in the future, the future of those who want to know their risks.  You cannot tell these things from the person's genotype, of course, and social science is even farther behind genomics when it comes to having a crystal ball for the future.  Indeed, all the Big Data resources in the world will have this problem, and to that extent will be a huge waste of public health funding.

These are not new major discoveries of new principles.  They just happened to be in the paper and to reflect the issues.  They just sound the warning bells that should be being heard, and heeded, in the labs and offices of NIH and medical schools, and the companies who have been giving what is essentially misleading (and inconsistent) DNA-based health advice, the whole community making rather careless promises of genome or other 'omic' based miracles.  These are facts of life, so to speak, that in themselves should be the subject of investigation. But that's a real, legitimate challenge, unlike the weak challenge of proposing to collect more and more data without being obligated to deliver on promises made to justify that or to address the real problems in an effective way.