The San Diego Nathan Shock Center: tackling the heterogeneity of aging

Abstract

Understanding basic mechanisms of aging holds great promise for developing interventions that prevent or delay many age-related declines and diseases simultaneously to increase human healthspan. However, a major confounding factor in aging research is the heterogeneity of the aging process itself. At the organismal level, it is clear that chronological age does not always predict biological age or susceptibility to frailty or pathology. While genetics and environment are major factors driving variable rates of aging, additional complexity arises because different organs, tissues, and cell types are intrinsically heterogeneous and exhibit different aging trajectories normally or in response to the stresses of the aging process (e.g., damage accumulation). Tackling the heterogeneity of aging requires new and specialized tools (e.g., single-cell analyses, mass spectrometry-based approaches, and advanced imaging) to identify novel signatures of aging across scales. Cutting-edge computational approaches are then needed to integrate these disparate datasets and elucidate network interactions between known aging hallmarks. There is also a need for improved, human cell-based models of aging to ensure that basic research findings are relevant to human aging and healthspan interventions. The San Diego Nathan Shock Center (SD-NSC) provides access to cutting-edge scientific resources to facilitate the study of the heterogeneity of aging in general and to promote the use of novel human cell models of aging. The center also has a robust Research Development Core that funds pilot projects on the heterogeneity of aging and organizes innovative training activities, including workshops and a personalized mentoring program, to help investigators new to the aging field succeed. Finally, the SD-NSC participates in outreach activities to educate the general community about the importance of aging research and promote the need for basic biology of aging research in particular.

Keywords: Aging; Heterogeneity; Human cohort; Machine learning; Organoids; Single-cell analysis.

Fig. 1

The study of aging is complicated by the intrinsic heterogeneity of the process. This is manifest between individuals and within an organism across multiple scales down to the sub-cellular organelles and even at the molecular level

Fig. 2

Subject-specific fibroblasts and iPSCs will be generated from the SD-NSC clinical cohort that has been assessed for metrics of biological age and cellular bioenergetics. New cells lines will power models of aging through direct conversion and organoid technologies

Fig. 3

tSNE plot of single-cell data from pancreas (young—black dots, old—red dots). Clusters represent the different cell types captured by this approach