ArticleFrontiers in aging neuroscience2014
Gender-specific impact of personal health parameters on individual brain aging in cognitively unimpaired elderly subjects.
Article in Frontiers in aging neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 1 of them a synthesis that pooled it.
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Who cites it
53 citing papers in PubMed, 1 synthesis or guideline pooled it, 90 citations in OpenAlex.
- Factors associated with brain ageing - a systematic review.BMC neurology · 2021Pooled it
- Physical Activity and BrainAGE: Exploring the Impact on Brain Health and Plasticity in Older Adults.Human brain mapping · 2025Trial
- Trial
- Your brain doesn't look a day past 70! Cross-sectional associations with brain-predicted age in the cognitively-intact oldest-old.GeroScience · 2026Article
- Generalizable and explainable deep learning for brain MRI: a multi-cohort evaluation of 3D architectures for age and sex prediction.Brain informatics · 2026Article
- The Effect of Internet Use on Older Adults' Executive Function: The Chain Mediation Effect of Social Participation and Loneliness.Healthcare (Basel, Switzerland) · 2026Article
- A discovery protein panel for brain predicted age discordance using MRI in neurologically healthy individuals.Frontiers in cell and developmental biology · 2026Article
- Genome-wide analysis of brain age identifies 59 associated loci and unveils relationships with mental and physical health.Nature aging · 2025Article
- Gender Differences in the Effects of Exercise Interventions on Alzheimer's Disease.Brain sciences · 2025Review
- Metabolic Status Modulates Global and Local Brain Age Estimates in Overweight and Obese Adults.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2025Article
- A Case for estradiol: younger brains in women with earlier menarche and later menopause.GigaScience · 2025Article
- Prevalence and factors influencing disability and cognitive impairment among empty nesters and non-empty nesters in Guangdong, China: a cross-sectional study.Frontiers in public health · 2025Article
- The effect of weight loss on brain age in schizophrenia spectrum disorders.PLOS mental health · 2025Article
- Dissecting unique and common variance across body and brain health indicators using age prediction.Human brain mapping · 2024Article
- Investigating the impact of motion in the scanner on brain age predictions.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Ethnic differences in the effects of apolipoprotein E ɛ4 and vascular risk factors on accelerated brain aging.Brain communications · 2024Article
- Vimar/RAP1GDS1 promotes acceleration of brain aging after flies and mice reach middle age.Communications biology · 2023Article
- Comparison of Machine Learning Models for Brain Age Prediction Using Six Imaging Modalities on Middle-Aged and Older Adults.Sensors (Basel, Switzerland) · 2023Article
- Turning Back the Clock: A Retrospective Single-Blind Study on Brain Age Change in Response to Nutraceuticals Supplementation vs. Lifestyle Modifications.Brain sciences · 2023Article
- Diffusion Tensor Imaging in Amyotrophic Lateral Sclerosis: Machine Learning for Biomarker Development.International journal of molecular sciences · 2023Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
Aging alters brain structure and function. Personal health markers and modifiable lifestyle factors are related to individual brain aging as well as to the risk of developing Alzheimer's disease (AD). This study used a novel magnetic resonance imaging (MRI)-based biomarker to assess the effects of 17 health markers on individual brain aging in cognitively unimpaired elderly subjects. By employing kernel regression methods, the expression of normal brain-aging patterns forms the basis to estimate the brain age of a given new subject. If the estimated age is higher than the chronological age, a positive brain age gap estimation (BrainAGE) score indicates accelerated atrophy and is considered a risk factor for developing AD. Within this cross-sectional, multi-center study 228 cognitively unimpaired elderly subjects (118 males) completed an MRI at 1.5Tesla, physiological and blood parameter assessments. The multivariate regression model combining all measured parameters was capable of explaining 39% of BrainAGE variance in males (p < 0.001) and 32% in females (p < 0.01). Furthermore, markers of the metabolic syndrome as well as markers of liver and kidney functions were profoundly related to BrainAGE scores in males (p < 0.05). In females, markers of liver and kidney functions as well as supply of vitamin B12 were significantly related to BrainAGE (p < 0.05). In conclusion, in cognitively unimpaired elderly subjects several clinical markers of poor health were associated with subtle structural changes in the brain that reflect accelerated aging, whereas protective effects on brain aging were observed for markers of good health. Additionally, the relations between individual brain aging and miscellaneous health markers show gender-specific patterns. The BrainAGE approach may thus serve as a clinically relevant biomarker for the detection of subtly abnormal patterns of brain aging probably preceding cognitive decline and development of AD.
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