The evolving science around longevity, and its unknowns
Longevity research is becoming more precise, but its answers remain incomplete
Bharatmorningnews.com – Ageing is no longer viewed solely as the number of years a person has lived. Scientists are increasingly trying to measure how quickly different parts of the body are changing, revealing that the heart, brain, lungs and other organs may not all age at the same pace.
Over roughly the past 20 years, research has identified 12 biological processes linked to ageing. These include DNA damage, misplaced chemical markers on genes, declining performance in the cellular structures that produce energy, and senescent cells that remain in the body while driving inflammation in nearby tissue.
Blood-based tests have added another layer to this work. Because certain proteins largely originate in particular organs, researchers can use them to estimate the apparent biological age of individual organs. A study involving nearly 5,700 adults found that close to one in five participants had one organ ageing substantially faster than the rest of their body. The organ showing accelerated ageing was associated with later health risks: a rapidly ageing heart, for example, was linked with heart failure, while an older-appearing brain was linked with Alzheimer’s disease.
Drug targets emerge, but proof remains limited
Once researchers can identify and measure a biological pathway, it becomes a possible target for medicines. Several widely discussed longevity interventions focus on different parts of the ageing process.
Rapamycin, originally used in transplant medicine, affects a cellular signalling system that helps cells decide whether to grow or conserve resources in response to food availability. Semaglutide, a GLP-1 medicine used for diabetes and weight management, can reduce inflammation and visceral abdominal fat. Rentosertib is designed to suppress the activity of senescent cells. NMN, sold as a supplement, is intended to increase a molecule involved in converting food into cellular energy, levels of which decline with age.
Three of these four interventions were created for conditions other than ageing. None has yet demonstrated, through a large clinical trial, that it can slow ageing itself.
Why ageing clocks do not always agree
A September 2026 study of rentosertib illustrates the difficulty of interpreting longevity research. The trial included 42 people with a fibrotic lung disease, the illness for which the medicine was developed. Participants receiving the highest daily dose saw their predicted age drop by around three years after four weeks.
That result came from ageing clocks: computer models trained on blood samples from thousands of people. But a clock’s output depends greatly on the outcome it was designed to predict.
Some clocks are trained to estimate chronological age. When those models return a lower figure, they indicate that a person’s blood resembles that of someone younger. Other clocks are built around illness and premature mortality. They draw on long-term follow-up data to identify blood patterns associated with remaining healthier for longer. A lower result on these models suggests reduced resemblance to people who later became ill or died earlier.
In the rentosertib study, four clocks focused on age suggested an average improvement of about three years. Two clocks built to assess disease and mortality risk did not show a meaningful shift. The participants’ blood appeared younger by one measure, but not less vulnerable by another. The researchers also noted that they could not determine whether the change reflected slower overall ageing or improvement in the lung disease being treated.
A Yale review published in August 2026 examined 16 clocks across 51 studies of interventions intended to affect ageing. It found that risk-focused clocks responded consistently to genuine physical changes, while chronological-age clocks did not move in a clear or uniform pattern.
“The clocks are misleading unless they are deployed in the context of a specific physiological condition. If all clocks show different time, then the clocks are wrong, not the time,” says Deepak Kumar Saini, a professor at the Indian Institute of Science who coordinates BHARAT, an Indian study of how people age.
Saini’s point is central to the field: an ageing measurement is most useful when it is connected to a specific organ, disease process or biological condition rather than treated as a definitive score for the whole person.
Established measures still have the strongest evidence
The interventions with the clearest trial evidence are neither new nor especially expensive. Studies lasting two to three years in healthy older adults have found that shingles vaccination, omega-3 combined with vitamin D, exercise and a daily multivitamin can slow some clock readings. The changes were measured in months rather than years, but they reinforce the importance of interventions already familiar to many patients and clinicians.
Newer approaches may also involve meaningful risks. Rapamycin is used to dampen immune activity so that a transplant recipient’s body does not reject a donated organ. Using it off label in a healthy person for longevity could weaken immune defences and make infections easier to acquire.
That concern has particular relevance in India, where tuberculosis and other infectious diseases circulate more widely than in many Western countries where interest in rapamycin for longevity has grown. Suppressing a healthy person’s immune system could carry a higher infection risk in such settings.
A practical role for longevity science
For now, one of the most valuable contributions of ageing research may be better identification of vulnerability. If testing suggests that one organ is ageing more rapidly than others, it may provide a reason for closer medical attention using the established screening, monitoring and diagnostic tools already available for that organ’s diseases.
The science is advancing from a single age number toward a more detailed map of the body. Yet that map is not a diagnosis, and a lower biological-age score is not automatically evidence of better health or a longer life. The challenge ahead is to show which measurements truly predict meaningful outcomes, which treatments change those outcomes, and which apparent improvements are simply reflections of a disease already being treated.
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