By MIKE MAGEE
In its final summary of the landmark paper in Nature this past month, the authors led with this statement: “This study underscores the highly personalized nature of thymic health and emphasizes the previously unrecognized possible critical role of maintaining thymic health to preserve an agile, adaptive immune response that will accommodate long-term well-being and longevity.”
The articles clinical significance was rapidly rebroadcast by a range of popular science publications like Scientific American. Its March 18th headline read “This overlooked organ may be more vital for longevity than scientists realized.” Mass General publications trumpeted, “Long Dismissed in Adult Health, the Thymus May Be Critical for Longevity and Cancer Treatment.” And global outlets went a step further with “Once dismissed as biologically obsolete after adolescence, the thymus is now being reclassified as a central regulator of immune aging, with new evidence linking its health to survival, cancer resistance, and how the human body ages itself.”
In their own Abstract, the authors of the Nature publication were somewhat more reserved, and yet the message is still remarkably consequential. They write, “These findings reposition the thymus as a central regulator of immune-mediated ageing and disease susceptibility in adulthood, highlighting its potential as a target for preventive and regenerative strategies to promote healthy ageing and longevity.”
But what intrigued me in the case above was barely mentioned by reviewers so excited by the primary clinical findings. My question was, “How did they measure thymic functionality?” The short answer is, they measured it with the help of an AI deep learning system.
As the authors explained, “In this study, we investigated the impact of thymic functionality, here called thymic health, in adults… For quantification of thymic health, we developed a deep learning system using an independent dataset of 5,674 individuals to determine compositional radiographic characteristics of the thymus as a proxy for its functionality. The system takes a CT scan as input and provides the automatic continuous thymic health estimate as output….We applied the system to prospectively collected data from a total of 27,612 individuals from two cohorts, including 2,581 participants in the FHS and 25,031 participants in the NLST… For outcome analyses, participants were categorized as low, average or high thymic health based on the bottom 25%, middle 50% and top 25% of the population.”
This new methodology to demonstrate different levels of thymic functionality turned out to be groundbreaking when cross-referenced with decades long longitudinal databases. Association with cardiovascular disease and lung cancer; history of smoking, obesity, and high HDL levels; disabilities, morbidity and mortality; sex and age all reinforced that prolonged functionality of the thymus correlated with both health and longevity.
For example they stated, “As expected thymic health was higher in female than male participants and significantly declined with age.” But more than that, the authors dug deep into associations “between metabolic and thymic health,” and concluded that “these findings suggest a profound impact of actionable lifestyle choices on thymic health and may further clarify why healthy behaviour improves well-being and lifespan.”
Finally, their calculations using multiple chemical markers for inflammation, suggested that “lower thymic health was indeed associated with pro-inflammatory modifications of blood plasma protein levels, consistent with the presence of chronic inflammation. The pro-inflammatory pattern included increased levels of cytokines IL-6, IL-18 and OSM, as well as several CXCL chemokines, all of known relevance in systemic inflammatory diseases such as atherosclerosis, age-associated diseases such as arthritis, and cancer.”
In its final summary, the authors reach for the golden ring stating, “this study underscores the highly personalized nature of thymic health and emphasizes the previously unrecognized possible critical role of maintaining thymic health to preserve an agile, adaptive immune response that will accommodate long-term well-being and longevity.”
And it is understandable that they would end on such a “good news” clinical note. But we should take care not to bury the lead here: Generative AI, in assisting researchers in creating a methodology to measure more accurately what previously had been unmeasurable, has reset what is “possible” in pursuing health and longevity. But more importantly, this paper suggests that other uses of “deep learning systems” to extend the measurement of functionality beyond what we see, or feel, or have always believed to be true, may accelerate discovery at a pace previously unimaginable.
Mike Magee MD is a Medical Historian and regular contributor to THCB. He is the author of CODE BLUE: Inside America’s Medical Industrial Complex. (Grove/2020)
