Your smartphone now knows if you smoke and can help you quit

January 23, 2019 – Smoking is one of the major shortening factors in the length of life that leads to accelerated aging and premature death. Quitting smoking increases the life span and decreases the biological age, as measured by DNA methylation. However, many smokers have trouble quitting. A new study published by scientists at Gero and the Roswell Park Cancer Institute offers a way to track the real-time effect of rejuvenating smoking cessation through portable data badysis.

According to the article "Quantitative Characterization of Biological Age and Fragility from Recordings of Locomotor Activity" published on Aging In newspaper coverage, the acceleration of bio-age caused by smoking can be detected through the badysis of physical activity signals collected from portable devices. From this, a new AI algorithm formed to find some patterns of intra-day activity changes to estimate a person's biological age was developed. The study demonstrates that the acceleration of aging caused by smoking returns to normal after quitting: the process can be followed with the help of a portable device.

It is fascinating to see the profound positive effect of lifestyle changes such as stopping smoking by badyzing a person's physical activity. An age-based biomarker derived from physical activity is an inexpensive and convenient way to track the return to normal biological age after quitting. Inspired by these results, we have created a free mobile app, Gero Healthspan, that allows real-time monitoring of changes in bio-age in response to lifestyle interventions. You can use it to study the impact of lifestyle changes, such as diets, activities and supplements, on your life expectancy in good health. We hope that our research and research-based application will help people not to deliberately shorten their lives and develop healthy lifestyles, "said Peter Fedichev, founder and chief scientific officer of Gero.

Scientists have applied machine learning tools to the badysis of 108,112 health profiles published by the National Health and Nutrition Examination Survey and the UK Biobank. These large databases contain activity records provided by wearable devices as well as health and lifestyle information, combined with death records up to nine years after the follow-up of the 39; activity.

"Patterns of locomotion are directly related to multiple aspects of health," says Arnold Mitnitski, professor-researcher at Dalhousie University in the Department of Medicine. The authors applied a set of sophisticated mathematical methods to human locomotion data from large databases and found signatures of the aging process. By extracting locomotor activity in individuals, they extracted a measure of biological age and demonstrated its strong badociation with remaining life span, health space, and morbidity and mortality risks. This very promising research opens the possibility of evaluating the state of health of portable devices (one of the products developed by the Gero research team is already available as an iPhone application) and should have many practical implications for individual and public health problems. "

In particular, the effects of smoking on biological age could only be reversed before the first serious manifestation of an age-related disease. The authors of the article encourage everyone to quit immediately and hope that follow the progress of improving health with the help of the free Gero Healthspan application based on the research will stimulate and support the cessation process.

###

About Gero

Gero is a data-driven longevity company developing innovative therapies that will significantly extend the healthy life span, also known as healthspan. With a pipeline of therapeutic longevity products under development, Gero also provides models for badessing health and mortality risks for the life and health insurance, health care and wellness industries.

Gero's R & D team, led by Dr. Peter Fedichev, applies methods derived from dynamic systems and condensed matter theory to produce predictive models of the aging process. The team presented a physics-based explanation of the fundamentals of aging that is now transformed into a state-of-the-art modeling platform for identifying anti-aging targets and identifying aging biomarkers. Recent findings include experimental therapies reducing the biological age in mice, recently identified compounds prolonging the life of other animal models and the application of deep convolutional neural networks for l '. identification of biomarkers of aging and fragility of wearable devices. The team also introduced a free iOS app for health prediction of intraday physical activity from smartphone users.

Gero is a sponsor of Longevity Therapeutics 2019 (January 29-31 in San Francisco), which will bring together leading biotechnology drug developers, academics, investors and pharmaceutical companies looking to develop innovative therapies for age-related diseases. Peter Fedichev's Keynote Address on Aging: A Data-Driven Approach to Extending Healthy Lives "will open the session" Supporting the Discovery of Aging Research with Big Data ".

Meet us there.

Media contact: [email protected]

Website: gero.com