Simple blood test may reveal who is likely to live longer

A Duke Health and University of Minnesota study reported that levels of small RNAs called piRNAs in blood predicted two‑year survival among adults aged 71 and older, with a six‑piRNA signature reaching about 86% accuracy and validation in an independent group.

Researchers led by Duke Health and the University of Minnesota measured small RNAs called piRNAs in blood samples from adults aged 71 and older and reported that specific piRNA patterns were linked to short‑term survival. The work, published in the journal Aging Cell, used advanced causal artificial intelligence and machine‑learning to analyze 187 clinical factors and 828 small RNAs across more than 1,200 samples. The team compared piRNA results with many familiar health measures and reported that a small set of piRNAs was the strongest predictor of two‑year survival in their analysis. The researchers say the findings were validated in a second, independent group of older adults. Key findings: - A group of six piRNAs predicted two‑year survival with reported accuracy up to about 86% in the study cohort. - Lower levels of certain piRNAs were consistently associated with longer survival among participants aged 71 and older. - The study analyzed over 1,200 blood samples and compared piRNA signals to 187 clinical measures and lifestyle factors. - Results were validated in an independent set of older adults and survival outcomes were confirmed using national mortality records. - Researchers used causal AI and machine‑learning methods to identify the piRNA signature reported in the paper. Summary: The study reports that a simple blood measurement of specific piRNAs may identify short‑term survival risk in older adults and that these piRNAs outperformed many standard clinical and lifestyle measures in predicting two‑year survival. The research team plans further work to see whether lifestyle changes, medications (including classes mentioned in the paper), or comparisons with tissue piRNA levels affect these signals, and to better understand how the molecules function.