I am delighted that Wang and colleagues have done such a detailed analysis of the epigenome in LOAD. The results, especially the evidence of particularly marked epigenetic drifts in PS1 and APOE, are of great interest. The authors wisely point out, however, that there is an underlying methodological problem—variable shifts in subpopulation heterogeneity—and point out the need for follow-up studies using such methods as laser-assisted microdissection and single cell analysis.
While these results are likely to reflect, at least in part, variable environmental impacts, I am increasingly impressed with the potential role of stochastic events that can lead to epigenetic drifts in gene expression. There is enormous intra-specific variability in longevity within model organisms for which both genotype and environment appear to have been well controlled. This leads me to conclude that, while nature, nurture, and chance all play roles in modulating the rates of aging and the rates at which late-life disorders emerge, for the case of variations within a species, the "800-pound gorilla" may well be chance, including varying patterns of epigenetic drift. This is in striking contrast to the dominating role of the constitutional genome in the modulation of lifespan and late-life disorders between species. A question of great interest is the implications that one might derive from evidence that random variations in gene expression have deep evolutionary roots (e.g., in bacteria). Given unpredictable environments, it might be adaptive for a population to have not only genetic heterogeneity but also epigenetic heterogeneity. Perhaps LOAD is an antagonistic pleiotropic byproduct of a class of gene action that has beneficial effects on younger, reproducing populations; the price we pay may be unlucky members of our aging population who have had their epigenetic changes drift in the wrong directions. I hope to live long enough to test my more general quasi-group-selectionist hypothesis!
Comments
University of Washington
I am delighted that Wang and colleagues have done such a detailed analysis of the epigenome in LOAD. The results, especially the evidence of particularly marked epigenetic drifts in PS1 and APOE, are of great interest. The authors wisely point out, however, that there is an underlying methodological problem—variable shifts in subpopulation heterogeneity—and point out the need for follow-up studies using such methods as laser-assisted microdissection and single cell analysis.
While these results are likely to reflect, at least in part, variable environmental impacts, I am increasingly impressed with the potential role of stochastic events that can lead to epigenetic drifts in gene expression. There is enormous intra-specific variability in longevity within model organisms for which both genotype and environment appear to have been well controlled. This leads me to conclude that, while nature, nurture, and chance all play roles in modulating the rates of aging and the rates at which late-life disorders emerge, for the case of variations within a species, the "800-pound gorilla" may well be chance, including varying patterns of epigenetic drift. This is in striking contrast to the dominating role of the constitutional genome in the modulation of lifespan and late-life disorders between species. A question of great interest is the implications that one might derive from evidence that random variations in gene expression have deep evolutionary roots (e.g., in bacteria). Given unpredictable environments, it might be adaptive for a population to have not only genetic heterogeneity but also epigenetic heterogeneity. Perhaps LOAD is an antagonistic pleiotropic byproduct of a class of gene action that has beneficial effects on younger, reproducing populations; the price we pay may be unlucky members of our aging population who have had their epigenetic changes drift in the wrong directions. I hope to live long enough to test my more general quasi-group-selectionist hypothesis!
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