Deep Learning, Predictive Analytics Helps Identify Chronic Diseases

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By using deep learning and predictive analytics, researchers have determined who could develop age-related chronic disease based on immune system health.

Researchers from the Buck Institute and Stanford University have created an inflammatory clock for aging (iAge) that uses deep learning and predictive analytics to determine immunological health and chronic diseases associated with aging. By utilizing artificial intelligence technology, researchers studied the blood immunome of 1001 people.

The team of researchers also discovered a modifiable chemokine associated with cardiac aging. This chemokine can be used for early detection of age-related pathology and can help provide targets for interventions.

“Standard immune metrics which can be used to identify individuals most at risk for developing single or even multiple chronic diseases of aging have been sorely lacking,” David Furman, PhD, Buck Institute Associate Professor, Director of the 1001 Immunomes Project at Stanford University School of Medicine and senior author of the study said in a press release.

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“Bringing biology to our completely unbiased approach allowed us to identify a number of metrics, including a small immune protein which is involved in age-related systemic chronic inflammation and cardiac aging. We now have means of detecting dysfunction and a pathway to intervention before full-blown pathology occurs,” Furman continued.

According to first author Nazish Sayed, MD, PhD, Assistant Professor of Vascular Surgery at Stanford Medicine, the study highlights the soluble chemokine CXCL9 as the major contributor to iAge. Furman describes CXCL0 as a small immune protein typically called to action to attract lymphocytes to infection sites.

“But in this case we showed that CXCL9 upregulates multiple genes implicated in inflammation and is involved in cellular senescence, vascular aging and adverse cardiac remodeling,” Furman stated then added that silencing CXCL9 reversed the loss of function in aging endothelial cells in humans and mice.

According to Furman, the age of one’s immune system provides important information regarding health and longevity.

“On average, centenarians have an immune age that is 40 years younger than what is considered ‘normal’ and we have one outlier, a super-healthy 105 year-old man (who lives in Italy) who has the immune system of a 25 year old,” he said.

 Results for the initial analysis and the cardiac health study were able to be validated. Additionally, Furman said that the researchers found a correlation between CXCL9 and the results from the pulse wave velocity testing.

“These people are all healthy according to all available lab tests and clinical assessments, but by using iAge we were able to predict who is likely to suffer from left ventricular hypertrophy (an enlargement and thickening of the walls of the heart’s main pumping chamber) and vascular dysfunction,” Furman said.

These artificial intelligence tools can be used to track a patient’s risk of developing multiple chronic diseases by assessing the total physiological damage done to their immune system.

Predictive analytics of age-related frailty can be determined by comparing biological immune metrics to information about how long it takes an individual to perform a task, such as standing up from a chair or walking a certain distance.

“Using iAge it’s possible to predict seven years in advance who is going to become frail,” Furman said. “That leaves us lots of room for interventions.”

In 2013, a group of researchers conducted a study on aging and identified nine “hallmarks” in the process. Age-related immune system dysfunction was not one of them.

“It’s becoming clear that we have to pay more attention to the immune system with age, given that almost every age-related malady has inflammation as part of its etiology,” said Furman.

“If you’re chronically inflamed, you will have genomic instability as well as mitochondrial dysfunction and issues with protein stability. Systemic chronic inflammation triggers telomere attrition, as well as epigenetic alterations. It’s clear that all of these nine hallmarks are, by and large, triggered by having systemic chronic inflammation in your body. I think of inflammation as the 10th hallmark,” Furman concluded.

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