Multidimensional informatic deconvolution defines gender-specific roles of hypothalamic GIT2 in aging trajectories. (December 2019) - van Gastel, Jaana; Cai, Huan; Cong, Wei-Na; Chadwick, Wayne; Daimon, Caitlin; Leysen, Hanne; Hendrickx, Jhana O.; De Schepper, Robin; Vangenechten, Laura; Van Turnhout, Jens; Verswyvel, Jasper; Becker, Kevin G.; et al.
Highlights: Across multiple species and diverse human cultures females demonstrate a longevity advantage. GIT2 represents a keystone factor that controls somatic aging. Genomic GIT2 heterozygosity induces a significant hypothalamic transcriptomic response. Female GIT2 heterozygous mice demonstrate a stronger anti-aging response compared to males. Abstract: In most species, females live longer than males. An understanding of this female longevity advantage will likely uncover novel anti-aging therapeutic targets. Here we investigated the transcriptomic responses in the hypothalamus – a key organ for somatic aging control – to the introduction of a simple aging-related molecular perturbation, i.e . GIT2 heterozygosity. Our previous work has demonstrated that GIT2 acts as a network controller of aging. A similar number of both total (1079-female, 1006-male) and gender-unique (577-female, 527-male) transcripts were significantly altered in response to GIT2 heterozygosity in early life-stage (2 month-old) mice. Despite a similar volume of transcriptomic disruption in females and males, a considerably stronger dataset coherency and functional annotation representation was observed for females. It was also evident that female mice possessed a greater resilience to pro-aging signaling pathways compared to males. Using a highly data-dependent natural language processing informatics pipeline, we identified novel functional data clusters that were connected by a coherent group of multifunctional transcripts. From these it was clear that females prioritized metabolic activity preservation compared to males to mitigate this pro-aging perturbation. These findings were corroborated by somatic metabolism analyses of living animals, demonstrating the efficacy of our new informatics pipeline.