Age-related effects on the potency of human adipose-derived stem cells: creation and evaluation of superlots and implications for musculoskeletal tissue engineering applications.

Human adipose-derived stem cells (hASC) are now a prevalent source of adult stem cells for studies in tissue engineering and regenerative medicine. However, researchers utilizing hASC in their investigations often encounter high levels of donor-to-donor variability in hASC differentiation potential. Because of this, conducting studies with this primary cell type can require extensive resources to generate statistically significant data. We present a method to generate pooled donor cell populations, termed "superlots," containing cell populations derived from four to five age-clustered donors. The goal of generating these superlots was to 1) increase experimental throughput, 2) to utilize assay resources more efficiently, and 3) to begin to establish global hASC differentiation behaviors that may be associated with donor age. With our superlot approach, we have validated that pooled donor cell populations exhibit proliferative activity representing the combined behavior of each individual donor cell line. Further, the superlots also exhibit differentiation levels roughly approximating the average combined differentiation levels of each individual donor cell line. We established that high donor-to-donor variability exists between the pre-, peri-, and postmenopausal age groupings and that proliferation and differentiation characteristics can vary widely, independent of age. Interestingly, we did observe that cell lines derived from postmenopausal donors demonstrated a relatively high proclivity for osteogenic differentiation and a relatively lowered proclivity for adipogenic differentiation as compared with cells derived from pre- and perimenopausal donors. In general, superlots effectively represented the average differentiation behavior of each of their contributing cell populations and could provide a powerful tool for increasing experimental throughput to more efficiently utilize resources when studying hASC differentiation.