In a recent study published in The Lancet Journal, researchers used machine learning models to assess the physical and primarily mental performance of superagers compared to typical age-matched elderly.
Study: Brain structure and phenotypic profile of superagers compared with age-matched older adults: a longitudinal analysis from the Vallecas Project. Image Credit: GroundPicture/Shutterstock.com
The study found that people with the superager phenotype had significantly faster movement speed, agility, and balance than their peers.
Their brains were structurally different from typical adults, with reduced memory atrophy, improved cognitive ability, significantly reduced risk of dementia, and overall better mental health than normal elderly.
'Superagers' is a term sometimes applied to older adults who resist age-associated memory decline much better than normal people of the same age.
Their episodic memory function – remembering personal experiences – is comparable to adults 20 or even 30 years younger than themselves. Unfortunately, while superagers have been included in scientific studies in the past, hitherto, no characterization of the underlying mechanisms of the superager phenotype currently exists.
Research has previously explored the relationship between the superager phenotype and lifestyle factors, including satisfaction with social relationships.
Neuroimaging of superager brains has shown thicker anterior cingulate cortices, larger hippocampal volumes, and slower cortical atrophy than normal older adults.
However, these studies were cross-sectional and had small sample sizes, making long-standing comparisons between superagers and typical adults difficult.
About the study
In the present research, researchers employed a machine learning classifier to elucidate the phenotypic profile of superagers. They further analyzed grey matter volume differences in typical adult- and superager cohorts to reveal structural differences which may underly the physical and mental advantages of the latter group over the former.
Researchers began by formulating three key hypotheses – firstly, superagers belong to the typical aging spectrum, evaluated by Alzheimer's disease prevalence and neurodegeneration blood marker comparisons between normal and superager elderly.
Secondly, superagers would show structural differences in brain parts associated with cognition and memory retention, specifically grey matter in the medial temporal lobe. Thirdly, superagers would be more likely to partake in lifestyles that promote better cognitive performance, including socioeconomic status, education, and physical activity.
To test the above, researchers selected participants from the Vallecas Project, a cohort of White elderly devoid of neurological disorders, based in Madrid, Spain. Screening involved participants meeting all five study criteria – age above 79.5 years, MRI data availability, cognition, episodic memory function, and episodic memory stability.
One thousand two hunger and thirteen participants were screened, with 64 superagers (individuals performing at or better than 50-56-year-olds in free recall verbal memory tests) and 55 age-matched normal adults finally selected.
All participants were presented with cognitive performance tests, the 'Free and Cued Selective Reminding Test,' and underwent structural MRI neuroimaging. Episodic memory function was assessed at subsequent follow-ups during the study.
Superagers, on average, were found to have a significantly higher education duration than normal adults; however, no differences between sexes were noted. Of the 119 initially, mild-cognitive-impairment-free individuals included in the study, 6 developed the condition within a year of initial screening, all from the typical adult cohort.
In contrast to prior research, no differences were found in the apolipoprotein E (APOE) ε4 allele between cohorts. The ε4 allele has been linked to an increased risk of non-familial Alzheimer's disease and was thought to be underexpressed or downregulated in superagers, which these results disprove.
Researchers tested five neurodegeneration-associated blood markers and found similar results – no differences between superager and typical adult cohorts.
MRI scans over five consecutive years revealed that while both cohorts had similar grey matter volumes at age 75, superagers had larger volumes of grey matter than their typical age-matched counterparts by age 80.
Typical adults experience hastened rates of grey matter decline, especially in the thalamus, but surprisingly, not the anterior thalamic nucleus – the region most implicated in memory.
"Superagers had greater grey matter volume than did typical older adults in the bilateral thalamus, basal forebrain, angular gyrus, and regions within the medial temporal lobe, including bilateral effects on grey matter volume in the hippocampus, amygdala, entorhinal cortex, parahippocampal gyrus, and fusiform gyrus."
Adjusting for duration of education did not change observed results. Merging cognitive test results with neuroimaging suggests that while no statistically significant brain structural differences exist between cohorts, superagers displayed visible superiority in memory recollection even at 75 years old.
Machine learning random forest models identified 89 lifestyle, demographic, and clinical variables differentiating superagers from typical older adults. The timed up-and-go test was the most significant predictor of the superager phenotype.
When clubbed with the dominant hand finger-tapping test, this suggests that superagers outcompete their typical counterparts in physical traits as well. Notably, no differences in reported exercise frequency were found between cohorts.
Superager scored lower on the State-Trait Anxiety Inventory and the Geriatric Depression Scale than the typical cohort, supported by self-reports of better mental health, improved sleep duration, and a lower likelihood of hypertension.
"The proportion of separated or divorced individuals was higher in the superager group than in the typical older adults group, regardless of gender. Superagers had higher independence in activities of daily living and a higher score in the National Adult Reading Test."
In the present study, researchers utilized questionaries, MRI neuroimaging, and tests of cognition, memory retention, and physical attributes to elucidate the differences between individuals with the superager phenotype and those without.
Using one of the largest superager cohorts in the literature, researchers found marked differences in lifestyle, brain structure, and clinical features between superagers and typical adults above 80.
Machine learning models identified 89 variables predicting the superuser phenotype. Of the four most significant predictors, the timed up-and-go test, a physical test of mobility, balance, and agility, was found to have the highest predictive power.
The remaining three were all mental-health related, namely self-reported depression, self-reported anxiety, and the Geriatric Depression Scale.
Grey matter atrophy was faster in typical adults beyond 75 years, though both typical and superager cohorts had similar grey matter volumes at 75 years. APOE ε4 allele expression results suggest that genetic underpinnings for superager, if present, do not overlap with known non-familial Alzheimer's disease causes.
"…the connection between preserved memory performance and motor function in people older than 80 provides novel insights into how to promote resistance to age-related memory loss. Taken together, the identified factors associated with superageing can inform the design of intervention trials to promote healthy ageing of episodic memory."
Garo-Pascual M., Gaser C., Zhang L., Tohka J., Medina M., and Strange B. A. (2023) Brain structure and phenotypic profile of superagers compared with age-matched older adults: a longitudinal analysis from the Vallecas Project. The Lancet. doi: 10.1016/S2666-7568(23)00079-X. https://www.thelancet.com/journals/lanhl/article/PIIS2666-7568(23)00079-X/fulltext#%20
Posted in: Medical Science News | Medical Research News | Medical Condition News | Healthcare News
Tags: Aging, Allele, Alzheimer's Disease, Amygdala, Anxiety, Apolipoprotein, Blood, Brain, Cortex, Dementia, Depression, Education, Exercise, Frequency, Genetic, Grey Matter, Hippocampus, Machine Learning, Mental Health, Neurodegeneration, Neuroimaging, Phenotype, Physical Activity, Research, Sleep, Thalamus
Hugo Francisco de Souza
Hugo Francisco de Souza is a scientific writer based in Bangalore, Karnataka, India. His academic passions lie in biogeography, evolutionary biology, and herpetology. He is currently pursuing his Ph.D. from the Centre for Ecological Sciences, Indian Institute of Science, where he studies the origins, dispersal, and speciation of wetland-associated snakes. Hugo has received, amongst others, the DST-INSPIRE fellowship for his doctoral research and the Gold Medal from Pondicherry University for academic excellence during his Masters. His research has been published in high-impact peer-reviewed journals, including PLOS Neglected Tropical Diseases and Systematic Biology. When not working or writing, Hugo can be found consuming copious amounts of anime and manga, composing and making music with his bass guitar, shredding trails on his MTB, playing video games (he prefers the term ‘gaming’), or tinkering with all things tech.