Many studies have demonstrated that biological age (BA) varies significantly among individuals of similar chronological age. A recent study by Ahadi et al. used longitudinal and deep multi-omic profiling to identify individuals with distinct BA phenotypes or 'ageotypes'. These ageotypes open new avenues to creating diagnostic and treatment strategies that may slow the aging process based on the unique biochemistry of each individual.