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Williams, R. G.

Publications and source records attributed to Williams, R. G..

2 recordsLinked to original sources

A multi-omic atlas in the African turquoise killifish reveals increased glucocorticoid signaling as a hallmark of brain aging

Aging is the leading risk factor for cognitive impairment and neurodegeneration, yet molecular changes that unfold in the brain over time, and how they drive this vulnerability, remain unclear. The naturally short-lived African turquoise killifish (Nothobranchius furzeri) offers a powerful model to understand brain aging on an accelerated timescale and test the impact of potential interventions. Here, we present a multi-omic atlas of brain aging of female and male African turquoise killifish from 2 independent genetic strains of different captive lifespans, encompassing single-nuclei RNA-seq, single nuclei ATAC-seq, and bulk ATAC-seq to capture transcriptional and regulatory changes. Interestingly, our atlas indicates that aging leads to a significant expansion of microglia numbers, regardless of sex or strain, which we independently validate using in-situ hybridization. In addition, we identify robust and conserved gene regulation changes, that are consistent with activation of glucocorticoid signalling as a hallmark (and potential driver) of vertebrate brain aging. Furthermore, pharmacological inhibition of glucocorticoid receptor activity starting at middle-age led to significant rescue of key molecular and cellular aging phenotypes. Thus, our study provides a powerful resource and framework to leverage the African turquoise killifish and rapidly uncover actionable pathways driving brain aging.

neuroscience↗

Systematic characterization of the ovarian landscape across mouse menopause models

Menopause affects not only fertility but also systemic health. Yet mechanisms underlying this coupling are still poorly understood, partly due to the absence of robust, age-relevant preclinical models with comprehensive molecular and phenotypic characterization. To address this, we systematically compared three candidate mouse models of menopause: (1) intact aging, (2) chemical ovarian follicle depletion using 4-vinylcyclohexene diepoxide (VCD) administered at multiple ages, and (3) Foxl2 haploinsufficiency, a genetic model based on a gene linked to human premature ovarian failure. Through histology, serum hormone profiling, single-cell transcriptomics and machine-learning approaches, we identify both shared and model-specific features of follicle loss, endocrine disruption, and transcriptional remodeling. Our comparative framework enables informed selection of context-appropriate preclinical rodent models to study menopause and the broader physiological consequences of ovarian aging. TeaserThis systematic characterization of mouse menopause models lays the groundwork for future preclinical work on the systemic impacts of menopause.

genomics↗