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Hacking the aging code: Big data for saving human lives

#artificialintelligence

Aging is the most important single factor behind chronic diseases and death. As «silver tsunami» approaches, healthcare, and social protection systems face the looming crisis. By 2050, the global population of older persons is projected to more than double its size in 2015. The new article published in Frontiers in Genetics by MIPT scientist Dr. P. Fedichev describes a strategy for the systematic development of novel anti-aging therapeutics and biomarkers of aging using the data from medical studies and large biobanks. The mortality rate in humans increases exponentially with age and doubles approximately every eight years.


Deep biomarkers of human aging: Application of deep neural networks to biomarker development - AGING Journal

#artificialintelligence

One of the major impediments in human aging research is the absence of a comprehensive and actionable set of biomarkers that may be targeted and measured to track the effectiveness of therapeutic interventions. In this study, we designed a modular ensemble of 21 deep neural networks (DNNs) of varying depth, structure and optimization to predict human chronological age using a basic blood test. To train the DNNs, we used over 60,000 samples from common blood biochemistry and cell count tests from routine health exams performed by a single laboratory and linked to chronological age and sex. The best performing DNN in the ensemble demonstrated 81.5 % epsilon-accuracy r 0.90 with R2 0.80 and MAE 6.07 years in predicting chronological age within a 10 year frame, while the entire ensemble achieved 83.5% epsilon-accuracy r 0.91 with R2 0.82 and MAE 5.55 years. The ensemble also identified the 5 most important markers for predicting human chronological age: albumin, glucose, alkaline phosphatase, urea and erythrocytes.


4 Things You Probably Didn't Know Machine Learning and AI was used for

@machinelearnbot

Recently, Google's CEO, Sundar Pichai, likened the impact of artificial intelligence to the discovery of fire. In the same way our distant ancestors' world was transformed by an invention that literally turned night into day, the foundations of how our society operates is about to undergo a similar shift. But will artificial intelligence really live up to the hype? That all depends on you and what you decide to do with it. Fire was meaningless until creative cavemen figured out exactly what to do with it.


Hacking the aging code: Big data to the rescue

#artificialintelligence

Aging is the most important single factor behind chronic diseases and death. As «silver tsunami» approaches, healthcare and social protection systems face the looming crisis. By 2050, the global population of older persons is projected to more than double its size in 2015. New article published in Frontiers in Genetics by MIPT scientist Peter Fedichev describes a strategy for systematic development of novel anti-aging therapeutics and biomarkers of aging using the data from medical studies and large biobanks. The mortality rate in humans increases exponentially with age and doubles approximately every eight years.


Is Horvath's Clock the Smoking Gun of Biological Aging?

#artificialintelligence

When Steve Horvath first saw the correlation between DNA methylation levels and his test subjects' actual chronological age, he about fell out of his chair. Horvath had begun studying DNA cytosine methylation at specific genetic locations -- the addition of methyl groups to cytosine in the DNA to turn genes on, off, or somewhere in between -- as part of a research group that wanted to see if methylation had anything to do with sexual preference. "Of course it didn't," Horvath, a professor of human genetics and biostatistics at UCLA, says. What he did find was the basis for what's become known as the "Horvath Clock," a measure of the methylation in some 353 locations in human DNA called CpGs, where a cytosine nucleotide is followed by a guanine nucleotide. Using a weighted average of DNA methylation, the Horvath clock can return an incredibly accurate reading of chronological age.