Associating Biomarkers of Healthy Aging with Longevity Finds Only Small Effects

The past decade of genetic research into natural variations in human longevity have made it pretty clear that there are no large effects. Where genes influence longevity, they do so in later life, when individuals are damaged and health is failing, and individual effects per gene are both small and vary widely between study populations. This has long suggested to me that comparative genetics, examining long-lived and short-lived people, is not the place to find any sort of meaningful basis for a therapy to extend healthy life. The open access research linked below reinforces this point in a well-studied human population by associating longevity with genetic variants related to a number of biomarkers thought to reflect better health in old age. The individual associations found can be shown to explain only a small fraction of the observed variation in longevity:

Genetic studies have thus far identified a limited number of loci associated with human longevity by applying age at death or survival up to advanced ages as phenotype. As an alternative approach, one could first try to identify biomarkers of healthy ageing and the genetic variants associated with these traits and subsequently determine the association of these variants with human longevity. In the present study, we used this approach by testing whether the 35 baseline serum parameters measured in the Leiden Longevity Study (LLS) meet the proposed criteria for a biomarker of healthy ageing. We have previously proposed four criteria for a quantitative parameter that, we think, need to be fulfilled before being considered a biomarker of healthy ageing. In short, a biomarker of healthy ageing should show an association with (1) chronological age, (2) familial propensity for longevity, (3) known health parameters, and (4) morbidity and/or mortality. Thus far, biomarker research has identified several potential biomarkers of healthy ageing, such as glucose and free triiodothyronine (fT3) serum levels, CDKN2A (p16) gene expression, leukocyte telomere length (LTL), and gait speed.

By testing the four previously proposed criteria for biomarkers of healthy ageing in individuals from the LLS, we identified parameters involved in carbohydrate (glucose and insulin) and lipid metabolism (triglycerides) as biomarkers of healthy ageing. In addition, we showed that a relatively high proportion of the genetic variants previously associated with these parameters are also nominal significant in the largest genome-wide association study (GWAS) for human longevity to date. However, even in the largest GWAS for these parameters to date the explained variance is only 4.8% (glucose), 1.2% (insulin) and 2.1% (triglycerides), indicating that there is still a lot to discover. Nonetheless, we were able to find an enrichment of significant genetic variants, previously indicated to be involved in glucose, insulin and triglycerides regulation, in the longevity GWAS dataset. This indicates that the genetic component underlying these traits may also contribute to human longevity.



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