Khaberni - Researchers have revealed that it is now possible to determine the rate of body aging based on a single brain image, according to "Live Science".
A team of researchers who published the results of their new study in the journal "Nature Aging" developed a biological aging standard based on magnetic resonance imaging of the brain.
The researchers say this tool can predict an individual's future risks of cognitive impairment, dementia, chronic diseases such as heart disease, physical weakness, and premature death.
Single magnetic resonance imaging
The lead researcher, Ahmed El Hariri, a professor of psychology and neuroscience at Duke University, said: "The research paper presents a new way of measuring a person's aging speed at any given moment using the information available in a single brain MRI," adding that "aging faster increases the risk of many diseases, including diabetes, heart disease, stroke, and dementia."
Machine learning algorithm
The researchers analyzed magnetic resonance images of the brain taken from participants at the age of 45, and processed data related to brain structure - the volume and thickness of different brain regions and the ratio of white matter to gray matter - through a machine learning algorithm.
The processed brain data were compared with other data collected from the participants at the same time, such as tests of physical and cognitive decline and self-reported health conditions and signs of aging on the face, such as wrinkles.
Faster aging rate
The researchers confirmed that greater declines in these areas are associated with a generally faster pace of aging, then linked the characteristics of the brain data to those metrics. They named their resulting model "DunedinPACNI."
In the past, the team created a similar tool called "DunedinPACE" (Dunedin Pace of Aging Calculated from the Epigenome). This measure focused on methylation - chemical marks associated with DNA molecules - in blood samples to estimate people's aging pace. Methylation is a type of "epigenetic change", meaning it changes gene activity without altering the DNA's basic code.
Aging speed gauge
Hariri said: "DunedinPACE has been widely adopted in studies where epigenetic data were available," explaining that "DunedinPACNI" currently allows for conducting studies without epigenetic data but using brain imaging to measure accelerated aging."
The researchers directly compared "DunedinPACNI" with "DunedinPACE" and found that they arrived at similar results. To see if their new tool was useful outside the scope of Dunedin, the team used it to estimate the aging pace using MRI images in other datasets: 42,000 MRI images from the UK Biobank; more than 1,700 MRI images from the Alzheimer's Disease Neuroimaging Initiative "ADNI"; and 369 images from the "BrainLat" group, which includes data from five countries in South America.
Generalization a top priority
Ethan Whitman, a co-researcher and doctoral student at Duke University, stated, "Ensuring that our results are generalizable to data sets and demographic groups represents a top priority for brain imaging research."
They found that the Dunedin "PACNI" initiative could also estimate the aging rate in these other groups, and they did so with precision, better than previously used measures. Both the UK Biobank and the "ADNI" index also include measures for specific health effects of aging, including physical frailty tests, such as grip strength and walking speed, as well as rates of heart attacks, strokes, chronic obstructive pulmonary disease, and death from all causes within age groups.
By using these additional measures, the team was able to link faster aging rates, as determined using "DunedinPACNI," with increased risks of heart attacks, strokes, chronic obstructive pulmonary disease, and death. Hariri added that it is now about analyzing data and setting criteria that reflect "healthy" and "weak" aging."
Major win
Dr. Dan Henderson, a primary care physician at Brigham and Women's Hospital and professor of medicine at Harvard Medical School, who did not participate in the study, commented: "Their success with 'BrainLat' data represents a major win for the researchers as it supports the possibility of generalizing the model," adding that it is "still beneficial to study other data sets where genetic and other factors may differ significantly."
Henderson said he sees the potential for using the Dunedin database for clinical evaluations eventually instead of traditional health measures to enhance medical interventions for each patient individually. Whitman also sees wide-ranging effects on research. Assuming it is adopted for use by physicians, he believes it could help patients prepare for aging by anticipating health problems before they arise.
Diagnosis before symptoms appear
Whitman stated, "We were really amazed by our tool's ability to predict the risk of disease before symptoms appear," expressing his belief as "an excellent example of the importance of studying aging in general, and particularly in younger and healthier individuals. If studies are limited to after the onset of disease, much information is missed."
