Cost-effective epigenetic age profiling in shallow methylation sequencing data

There is a critical need for robust, high-throughput assays of biological aging trajectories. Among various approaches, epigenetic aging clocks emerged as reliable molecular trackers of the aging process. However, current methods for epigenetic age profiling are inherently costly and lack throughput. Here, we leverage the scAge framework for accurate prediction of biological age from very few bisulfite sequencing reads in bulk samples, thereby enabling drastic (100-1,000-fold) reduction in sequencing costs per sample. Our approach permits age assessment based on distinct assortments of CpG sites in different samples, without the need for targeted site enrichment or specialized reagents. We demonstrate the efficacy of this method to quantify the age of mouse blood samples across independent cohorts, identify the effect of calorie restriction as an attenuator of the aging process, and discern rejuvenation upon cellular reprogramming. We propose that this framework may be used for epigenetic age prediction in extremely high-throughput applications, enabling robust, large-scale and inexpensive interventions testing and age profiling.