Summary: Nutrient intake, brain structure and cognitive function jointly contribute to brain health in older adults, a new study finds. Research has found that blood markers of certain fatty acids are linked to better memory and larger brain structures in certain areas, suggesting the value of a holistic approach to food and nutrition to support a healthy aging.
Source: University of Illinois
In a new study, scientists explored the links between three measures known to independently predict healthy aging: nutrient intake, brain structure and cognitive function. Their analysis adds to the evidence that these factors jointly contribute to brain health in older adults.
Reported in the Nutrition reviewthe study found that blood markers of two saturated fatty acids, as well as certain omega-6, -7 and -9 fatty acids, were correlated with better scores on memory tests and with larger brain structures in the regions frontal, temporal, parietal and insular. cortex.
While other studies have found individual associations between individual nutrients or nutrient classes and specific brain regions or functions, very little research thoroughly examines brain health, cognition, and general dietary patterns. said Aron Barbey, professor of psychology, bioengineering and neuroscience at the University of Illinois Urbana-Champaign who led the study with postdoctoral researcher Tanveer Talukdar and psychology researcher Chris Zwilling.
The three co-authors are all affiliated with the Beckman Institute for Advanced Science and Technology at U. of I.
“Our results reveal that we can use nutrient biomarkers, cognitive testing and MRI measures of brain structure to explain much of the variation in healthy aging,” Barbey said. “It allows us to better understand how nutrition contributes to health, aging and disease,”
The researchers collected data from 111 healthy elderly people with MRI structural scans, blood biomarkers of 52 dietary nutrients, and cognitive performance on memory and intelligence tests. By combining these measures using a data fusion approach, the team found associations between dozens of characteristics that appear to work in tandem to promote brain and cognitive health in older adults.
Data fusion allows researchers to look at multiple datasets to map traits or characteristics that have common patterns of variability, said Talukdar, who adapted the method to incorporate volumetric data on nutrition, cognition and the brain.
“We are looking at the relationships between all of these elements together,” he said. “It allows us to identify certain features that cluster together.”
This overcomes some of the limitations of individual factor analysis, Barbey said.
“If we just look at nutrition as it relates to brain structures and we don’t study cognition, or if we look at nutrition as it relates to cognition and we don’t study the brain, then we are missing out. makes some really important pieces of information.”
The most obvious features that clustered in the new analysis were the size of gray matter volumes in the frontal, temporal, and parietal cortices; performance on tests of auditory memory and short-term and long-term memory; and blood markers related to the consumption of monounsaturated and polyunsaturated fatty acids.
Study participants who scored higher on memory tests tended to have larger gray matter volumes and higher levels of omega-6, -7, and -9 fatty acid markers in their body. blood. Those who performed better on cognitive tests also had smaller gray matter volumes in those brain regions and lower levels of these dietary markers, the analysis found.
Although the study only reveals associations between these factors and does not prove that eating habits directly promote brain health, it does add to the evidence that nutrition is a key player in healthy aging, the researchers said. .
“Our work motivates a more complete picture of healthy aging,” Zwilling said. This provides insight into the importance of food and nutrition and the value of data fusion methods for studying their contributions to adult development and the neuroscience of aging.
Funding: This work was supported by a grant from Abbott Nutrition through the Center for Nutrition, Learning and Memory at the U. of I.
About this brain aging and nutrition research news
Author: Diana Yates
Source: University of Illinois
Contact: Diana Yates – University of Illinois
Picture: Image is in public domain
Original research: Free access.
“Integration of biomarkers of nutrients, cognitive functions and structural MRI data to construct multivariate phenotypes of healthy aging” by Aron Barbey et al. Nutrition review
Integration of biomarkers of nutrients, cognitive functions and structural MRI data to create multivariate phenotypes of healthy aging
Research in the emerging field of nutritional cognitive neuroscience demonstrates that many aspects of nutrition, from whole-food diets to specific nutrients, affect cognitive performance and brain health.
Although previous research has primarily examined the bivariate relationship between nutrition and cognition or nutrition and brain health, this study aimed to investigate the joint relationship between these essential and interacting elements of human health.
We applied a state-of-the-art data fusion method, coupled matrix tensor factorization, to characterize the joint association between measures of nutrition (52 nutrient biomarkers), cognition (Wechsler Abbreviated Test of Intelligence and Wechsler Memory Scale ) and brain health (high-resolution MRI measures of structural brain volume) in a cross-sectional sample of 111 healthy elderly people, with a mean age of 69.1 years, 62% being female, and a mean body mass index 26.0 kg/m2.
The data fusion revealed latent factors that capture the joint association between specific nutrient profiles, cognitive measures, and cortical volumes, demonstrating how closely these domains of health are coupled.
Hierarchical cluster analysis further revealed systematic differences between a subset of variables contributing to the underlying latent factors, providing evidence for multivariate phenotypes that represent high and low levels of performance across several health domains.
The main characteristics that distinguish each phenotype were: 1) nutrient biomarkers for monounsaturated and polyunsaturated fatty acids; 2) cognitive measures of immediate, auditory and delayed memory; And 3) brain volumes in the frontal, temporal and parietal cortices.
By incorporating innovations in nutritional epidemiology (nutrient biomarker analysis), cognitive neuroscience (high-resolution structural brain imaging), and statistics (data fusion), this study provides an interdisciplinary synthesis of methods that explain how nutrition, cognition and brain health are integrated. through lifestyle choices that affect healthy aging.