A novel brain-based “aging” clock can accurately and reliably estimate how quickly an individual is biologically aging from a single MRI scan, offering a potential tool to help clinicians predict the risk for dementia, mild cognitive impairment, and other chronic diseases, a new study showed.
Investigators developed the Dunedin Pace of Aging Calculated from NeuroImaging (DunedinPACNI) to estimate an individual’s pace of aging based on brain MRI features such as cortical thickness, surface area, gray matter volume, gray-to-white matter contrast, subcortical volumes, and ventricular sizes.
In a series of studies with more than 50,000 brain MRI scans from people aged 22-98 years across multiple datasets, those whose biological age outpaced their chronological age not only had poorer cognition, faster hippocampal atrophy, and greater dementia risk but also worse general health, including greater frailty, poorer self-reported health, and greater risk for chronic disease and premature death.
While more research on the new tool is needed, investigators said they expect it will be ready for use in clinical practice in a few years.
“Perhaps our boldest expectation is for DunedinPACNI to become part of routine clinical care across the lifespan as an index of faster aging that can help physicians identify patients at risk for later poor health well before symptoms appear and when prevention efforts can be most effective,” Ahmad R. Hariri, PhD, professor of psychology and neuroscience and director, Laboratory of Neurogenetics, Duke University, Durham, North Carolina, told Medscape Medical News.
The study was published online on July 1 in Nature Aging.
Blood-Based Epigenetic Clock
The DunedinPACE-NI tool builds on earlier research from a long-term study that has followed more than 1000 individuals born in Dunedin, New Zealand, in 1972-1973.
The researchers initially used data from this study to develop DunedinPACE, a blood-based epigenetic clock that uses DNA methylation to estimate the rate of aging. While DunedinPACE has shown strong associations with morbidity, brain aging, and more. Itsy, its application is limited to studies where blood samples are available, the researchers noted.
To overcome this limitation, they developed DunedinPACNI, which uses data from a single standard T1-weighted MRI scan to estimate an individual’s longitudinal pace of aging — a composite index reflecting physiological decline across cardiovascular, metabolic, immune, renal, and other systems.
The researchers trained DunedinPACNI on MRI data from 860 participants in the Dunedin Study, all scanned at age 45. The model incorporated 315 structural brain features. The algorithm for DunedinPACNI is publicly available to the research community.
Applying this measure to the Alzheimer’s Disease Neuroimaging Initiative (ADNI), UK Biobank and BrainLat datasets showed that faster DunedinPACNI scores predicted cognitive impairment, accelerated brain atrophy, and conversion to diagnosed mild cognitive impairment (MCI) or dementia.
For example, in the ADNI sample, individuals deemed to be aging the fastest (top 10%) when they joined the study had a 61% higher risk of progressing to MCI or dementia in the years that followed than average agers. The fast agers also started to have memory problems sooner than those who were found to be aging slower based on DunedinPACNI scores.
In the UK Biobank sample, healthy participants with faster DunedinPACNI at baseline were 14% more likely to be diagnosed with chronic age-related diseases later on.
The fastest agers had an 18% higher risk of being diagnosed with a chronic age-related disease than average agers. Fast aging was also associated with worse cognitive performance, higher frailty, and poorer self-rated health.
Over an average of nearly 10 years of follow-up, those with the fastest DunedinPACNI scores were 41% more likely to die than those who were aging more slowly.
DunedinPACNI also reflects social gradients of health inequities. Faster aging scores were observed in individuals with fewer years of formal education or lower income.
The measure also had similar predictive power for dementia risk and cognitive impairment among Latin American adults in the BrainLat cohort.
“It seems to be capturing something that is reflected in all brains,” Hariri said in a press release.
From Bench to Bedside
“Right now, DunedinPACNI can only tell us if a person is aging faster or slower than others within any given dataset or sample,” Hariri told Medscape Medical News. “That is, DunedinPACNI is currently a relative measure. It doesn’t yet tell us if a person is aging faster or slower than would be expected for any person anywhere in the world who is of the same chronological age. But that is changing quickly.”
Investigators need to develop normative reference charts for DunedinPACNI, similar to what they have done for such measures as height, weight, and BMI, Hariri noted.
“It will take time to analyze the tens of thousands of scans collected across the lifespan necessary to develop these norms, but we’ve already begun to do this. We are confident that reference norms for DunedinPACNI will be ready within the next year and, subsequently, DunedinPACNI can be adopted in clinical practice within a few years,” Hariri said.
Immediate applications of DunedinPACNI in the research setting include using it as an outcome measure in randomized clinical trials of interventions to slow down aging and as a biomarker of accelerated aging that can help predict the chances that an older person will convert from normal cognitive functioning to MCI or from MCI to dementia, Hariri explained.
DunedinPACNI could also be used in clinical trials of AD interventions. This could be as a surrogate outcome measure in younger people decades before they might develop dementia by showing that an intervention slows down aging, which is itself a major risk factor for dementia, Hariri said.
“In older people, DunedinPACNI may be useful as a screening tool to either reduce heterogeneity in the sample by enrolling people all aging at about the same rate or excluding people for are aging faster than others and who may be at increased risk for unintended side effects of treatment including amyloid related imaging abnormalities (ARIAs),” Hariri added.
The authors have filed a patent application for the tool. This research was supported by the US National Institute on Aging, the UK Medical Research Council, and the New Zealand Health Research Council.