NEW YORK – New research has unearthed organ-specific aging markers from within blood plasma that can highlight individuals with faster-than-usual aging in one or more organs.
"Our study introduces a framework for modeling organ health and biological aging using plasma proteomics," senior and corresponding author Tony Wyss-Coray, a neurology and neurological sciences researcher at Stanford University and director of the Phil and Penny Knight Initiative for Brain Resilience, and his colleagues wrote in Nature on Wednesday. "The resulting organ aging models can predict mortality, organ-specific functional decline, disease risk and progression, and aging heterogeneity between tissues."
Starting with RNA sequencing profiles found in Genotype-Tissue Expression (GTEx) project data, the investigators focused in on 4,979 proteins for subsequent testing in blood samples from 1,398 healthy control participants from the Knight Alzheimer's Disease Research Center study. With SomaLogic's DNA aptamer-based SomaScan assay, they found that 893 of those proteins appeared to have higher-than-usual expression in specific organs.
From there, they turned to machine learning models to estimate overall biological aging and aging across 11 organs in 5,676 individuals enrolled in five prior studies, putting together a set of software tools dubbed "organage" to assess organ age based on SomaScan assay-based plasma proteome profiles.
The proteomics-based approach "allows us to estimate the biological age of all major organs in living people," Wyss-Coray explained in an email.
"Because we measure known proteins, we can find out what their function is in the aging of organs," he added, "and potentially develop new drugs that slow the aging of specific organs to prevent organ-specific disease."
Consistent with past findings in animal models, the researchers found that different organs within the same individual sometimes showed distinct aging rates, potentially reflecting genetic, environmental, and lifestyle interactions with organ-specific impacts.
In particular, the authors saw accelerated organ aging in more than 18 percent of participants profiled. But only 1.7 percent of individuals showed signs of faster-than-usual aging in two or more organs, suggesting "organ age gaps may capture unique aging information, which may have implications for organ-specific biological aging and diseases of aging."
When the team then analyzed available disease diagnostic data for two of the cohorts considered, it found that cases of accelerated organ aging appeared to coincide with the prevalence of disease in related organs.
For example, in individuals who appeared to have accelerated kidney aging, the investigators saw higher-than-usual rates of diabetes, hypertension, hypercholesterolemia, and obesity. Likewise, they noted that markers linked to kidney aging tended to include proteins expressed in cell types previously implicated in kidney biology or kidney features.
Meanwhile, "heart agers," who had altered blood levels of age-related proteins expressed mainly in cardiomyocyte cells, were more prone to heart attack and atrial fibrillation. Accelerated muscle aging features tended to turn up in individuals with gait issues.
Brain aging was linked to cognitive decline and faster aging of both the brain and vascular system and appeared to predict Alzheimer's disease, the team explained, though mortality was broadly affected by increased organ aging rates: Accelerated aging in 10 of the organs profiled was linked to a 20 percent to 50 percent boost in all-cause mortality in a longitudinal study known as LonGenity that began at the Albert Einstein College of Medicine in 2008.
If and when the protein marker approach is validated in much larger cohort studies, Wyss-Coray noted organ aging measurements may offer views of organ health and responses to everything from different treatment approaches to lifestyle interventions such as exercise, while pointing to potential drug targets that have been overlooked in the past.
In addition, the authors noted that the "rapidly growing number of human gene expression maps at single-cell resolution will help further refine organ and cell-type specific aging models and allow for a comprehensive understanding of organismal physiology based on the plasma proteome."