Characteristics of Age-Associated Changes in the Whole Transcriptome of Human Peripheral Blood Leukocytes and Establishment of an Aging Clock

In the post-pandemic era, there are limited methods for identifying accelerated aging through peripheral blood transcriptomics. Therefore, we conducted whole-transcriptome sequencing on 35 healthy individuals (22-88 years old). Analyzing mRNA, lncRNA, and miRNA expression, we constructed a ceRNA network and employed a random forest algorithm to develop an aging clock based on 10 genes, validated by pseudo-time analysis and RT-PCR. Utilizing the OEP001041 dataset (277 healthy individuals, aged 17-75) and datasets comprising patients with infectious diseases (n = 1558), we validated the aging clock's ability to categorize the aging rates among different individuals, uncovering associations between aging rates and infectious diseases. Further investigations revealed that infections accelerate aging by elevating inflammation and oxidative stress. Importantly, the aging clock demonstrated alterations post-infection, showcasing its potential in assessing the aging rate after patient recovery. This study uncovers potential factors contributing to accelerated aging and promotes the development of healthy aging.