The discovery (and approval) of anti-aging pharmaceuticals is hindered by at least one major practical impediment: Measurement of the simplest biological endpoint of interest — length of lifespan — takes a long time. This is true even if one focuses first on shorter-lived model organisms: a normal healthy mouse can live for several years in a laboratory environment, and if this mouse is taking an effective longevity drug then (by assumption) one will take longer than that to observe the increase in lifespan.

Consequently, much attention has been paid to the idea of aging biomarkers, i.e., phenotypes that can be measured throughout the lifespan and that reflect the percent of lifespan that has elapsed. In the simplest case, if I’m aging half as fast at you, but we’re the same chronological age, then my reading for biomarker X should be 50% of yours. Useful biomarkers might include bone density, parameters of hair structure, aspects of blood count…essentially, anything quantifiable that correlates biological age with chronological age is fair game.

Spindler and Mote describe studies in which a biomarker approach is applied to the development of longevity drugs. The authors attempted to find compounds that result in gene expression changes that mimic the ones observed when animals are subjected to calorie restriction (CR):

Screening Candidate Longevity Therapeutics Using Gene-Expression Arrays

We review studies showing that CR acts rapidly, even in late adulthood, to extend health- and lifespan in mice. These rapid physiological effects are closely linked to patterns of gene expression in liver and heart. Non-human primate and human studies suggest that the signal transduction pathways responsible for the lifespan and health effects of caloric restriction (CR) may also be involved in human longevity. Thus, pharmaceuticals capable of mimicking the effects of CR (and other methods of lifespan extension) may have application to human health. Objective: We show that lifespan studies are an inefficient and theoretically problematic way of screening for longevity therapeutics. We review studies suggesting that rapid changes in patterns of gene expression can be used to identify pharmaceuticals capable of mimicking some positive effects of caloric restriction. Results: We present a traditional study of the effects of melatonin, melatonin and pregnenolone, aminoguanidine, aminoguanidine and alpha-lipoic acid, aminoguanidine, alpha-lipoic acid, pregnenolone, and coenzyme-Q10 on the lifespan of mice. No treatment extended lifespan. However, because the mice die mostly of cancer, only chemopreventives active against specific cancers can be identified by such studies. The studies were also time-consuming and expensive. We discuss high-density microarray studies of the effectiveness of glucoregulatory drugs and putative cancer chemopreventatives at reproducing the hepatic gene-expression profiles of long-term and short-term CR. We describe the identification of one compound, metformin, which reproduces a subset of the gene-expression and physiological effects of CR. Conclusion: Taken together, our results suggest that gene-expression biomarkers may be superior to lifespan studies for initial screening of candidate longevity therapeutics.

Gene expression measurements are excellent biomarkers: they are both quantitative (“I am expressing three times as much of gene A at age 2 than I was at age 1”), and also robust — because one can measure all of the genes in the genome simultaneously, using microarrays or similar approaches, small perturbations in the levels of single transcripts don’t obscure the overall picture. This might not be the case for biomarkers that focus on single phenotypes like bone density, since individual genetic variation might mask the aging signal in the data.

One major advantage of using gene expression biomarkers to monitor the effect of candidate longevity drugs is that one doesn’t have to wait a human lifetime (or even a mouse lifetime) in order to observe clues that a drug have anti-aging activity. Granted, one would still have to eventually verify an effect on human lifespan (as well as safety) for the drug to be approved…unless, of course, the drug has already been approved for another purpose; the burden for off-label use of a previously vetted molecule is much lower than for a completely new one. (On a related note: the compound that Spindler and Mote found to match the gene expression biomarkers of CR most closely, metformin, is one of the most widely used anti-diabetic drugs currently in use.)