SNPedia is a wiki-style index of genetic variants that have interesting phenotypic associations in human beings. The name comes from the acronym for “single nucleotide polymorphisms,” i.e., one-letter variations among different individuals’ genomes.
In honor of the new year, one of the proprietors has posted SNPedia’s Top 10 SNPs of the Year, based on an admittedly “subjective combination of medical importance, statistical believability, and overall general interest.” The variants that made the list are associated with a wide range of phenotypes, but they fall into a few categories:
- benefits of major drugs (e.g., effect of Plavix on heart disease risk);
- likelihood of drug side effects (e.g., myopathy in response to statins);
- risk for specific diseases (CVD, periodontitis, cancers)
The list, especially the items regarding drug efficacy and adverse reactions, got me thinking about anti-aging medicine.
Any hypothetical longevity-enhancing therapies will be more or less effective, and be subject to more or less severe side effects, as a function of individual genetic variation. One consequence of pharmacogenetic variability is that small or insufficiently diverse trial populations (in which specific genetic variants might be underrepresented) can result in misleading results about a therapy’s potential efficacy in the general population. And it’s hard to know, in advance of preliminary results, what the relevant variants might be.
This logic is general to a wide variety of therapies. Drugs are just molecules of varying shapes and sizes, and molecules of all shapes and sizes mediate cell-cell interactions, so it’s likely that pharmacogenetics will influence cellular therapies as well as more conventional pharmaceutical approaches. I suspect that cellular therapies might even be more vulnerable to genetic variation, since cell-cell interactions rely on proteins and other molecules produced by multiple genetic loci – e.g., not just a receptor or a ligand but both the receptor and the ligand acting together – and these pairwise interactions will be even more difficult to tease out than phenotypes that rely on a single locus.
It’s already going to be hard to determine over short intervals whether a given anti-aging therapeutic is effective, since we don’t (yet) have biomarkers that allow us to measure the rate of aging. Most of the best biomarkers are most convincing at the population level, and it’s hard to use them to compare the rate of physiological vs. chronological aging in a single individual. Therefore, proof of efficacy of longevity-enhancing treatments will rely on long studies and sizable populations of subjects – and the existence of unresponsive genotypes in the population will further confound that analysis.
Granted, we already know that building an anti-aging pharmacopeia will be challenging, and I’m not suggesting that this line of reasoning means we should pack up and go home. I mention it mostly because genetic variations will almost certainly play an important role in determining the efficacy of any given therapy, and we had best be prepared for that.