Plasma proteomics-based organ-specific aging for all-cause mortality and cause-specific mortality: a prospective cohort study.

Abstract

Individual's aging rates vary across organs. However, there are few methods for assessing aging at organ levels and whether they contribute differently to mortalities remains unknown. We analyzed data from 45,821 adults in the UK Biobank, using plasma proteomics and machine learning to estimate biological ages for 12 major organs. The differences between biological age and chronological age, referred to as "age gaps," were calculated for each organ. Partial correlation analyses were used to assess the association between age gaps and modifiable factors. Adjusted multivariable Cox regression models were applied to examine the association of age gaps with all-cause mortality, cause-specific mortalities, and cancer-specific mortalities. We reveal a complex network of varied associations between multi-organ aging and modifiable factors. All age gaps increase the risk of all-cause mortality by 6-60%. The risk of death varied from 5.54 to 29.18 times depending on the number of aging organs. Cause-specific mortalities are associated with certain organs' aging. For mental diseases mortality, and nervous system mortality, only brain aging exhibited a significant increased risk of HR 2.38 (per SD, 95% CI: 2.06-2.74) and 1.99 (per SD, 95% CI: 1.84-2.16), respectively. Age gaps of stomach were also a specific indicator for gastric cancer. Eventually, we find that an organ's biological age selectively influences the aging of other organ systems. Our study demonstrates that accelerated aging in specific organs increases the risk of mortality from various causes. This provides a potential tool for early identification of at-risk populations, offering a relatively objective method for precision medicine.