A systems biology approach to explain sex differences in aging

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ABSTRACT The risk of mortality is higher for human males than females at all ages and in almost every country, and this same pattern holds in most other mammalian species as well. In studies of genetic, environmental or pharmacological interventions designed to ameliorate the effects of aging, the responses are frequently sex- biased, and in some cases, benefits are limited to just one sex. Researchers have been encouraged by NIH’s “Sex As a Biological Variable” (SABV) initiative to consider the effect of sex in aging-related laboratory and clinical studies. However, the focus has been on sexual dimorphism due to dichotomous differences (e.g., XY versus XX sex chromosomes). This typological approach can successfully determine if sex affects outcome, but fails to address why these sex differences occur. This gap in existing approaches represents a critical unmet need in the field of aging research. Recent published studies and preliminary work from our lab show that the effects of sex on complex traits are far from dichotomous, falling along a continuum. In fruit flies, for example, both the magnitude and direction of difference between males and females in lifespan vary among genotypes. Preliminary data suggest the same is true for the sex-specific response to treatments designed to improve healthy aging in lab organisms. This shift from a dichotomous to continuous perspective on the effects of sex reflects an important conceptual innovation. Based on these findings, the central hypothesis tested here is that biological sex differences fall along a continuum shaped by sex interacting with the underlying genotype, and that the mechanisms contributing to this continuum are discoverable. The primary goal of this proposal is to use a systems biology approach with metabolomic profiling to discover the molecular mechanisms that underlie genotype-dependent effects of sex on aging and age-related traits. As in much of our prior work, we use the Drosophila Genome Reference Panel, a powerful model of natural genetic variation. We combine this genetic resource with profiles of the metabolome, which measures the small molecules that make up the structural and functional building blocks for all traits. To test our central hypothesis, we explore two questions. First, we use measures of metabolome profiles, including measures within each sex and the difference between sexes, to predict and explain genetic variation in sex differences for lifespan and stress resistance in Drosophila. Second, we test the ability of the metabolome to predict and explain sex differences in response to rapamycin, a drug found to extend healthy lifespan in diverse lab organisms. We employ proteomic and transgenic approaches to validate putative mechanisms for sex differences suggested by metabolomics. The long-term goal of this research is to lay the groundwork for improved sex-specific disease prediction, prognosis, diagnosis, treatment and prevention in human populations.