Dataset Information

MicroRNA predicts cognitive performance in healthy older adults.

ABSTRACT: The expression of microRNA (miRNA) is influenced by ongoing biological processes, including aging, and has begun to play a role in the measurement of neurodegenerative processes in central nervous system. The purpose of this study is to utilize machine learning approaches to determine whether miRNA can be utilized as a blood-based biomarker of cognitive aging. A random forest regression combining miRNA with biological (brain volume), clinical (comorbid conditions), and demographic variables in 115 typically aging older adults explained the greatest level of variance in cognitive performance compared to the other machine learning models explored. Three miRNA (miR-140-5p, miR-197-3p, and miR-501-3p) were top-ranked predictors of multiple cognitive outcomes (Fluid, Crystallized, and Overall Cognition) and past studies of these miRNA link them to cellular senescence, inflammatory signals for atherosclerotic formation, and potential development of neurodegenerative disorders (e.g., Alzheimer's disease). Several novel miRNAs were also linked to age and multiple cognitive functions, findings which together warrant further exploration linking these miRNAs to brain-derived metrics of neurodegeneration in typically aging older adults.

SUBMITTER: Gullett JM

PROVIDER: S-EPMC7606424 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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MicroRNA predicts cognitive performance in healthy older adults.

Gullett Joseph M JM Chen Zhaoyi Z O'Shea Andrew A Akbar Maisha M Bian Jiang J Rani Asha A Porges Eric C EC Foster Thomas C TC Woods Adam J AJ Modave Francois F Cohen Ronald A RA

Neurobiology of aging 20200803

The expression of microRNA (miRNA) is influenced by ongoing biological processes, including aging, and has begun to play a role in the measurement of neurodegenerative processes in central nervous system. The purpose of this study is to utilize machine learning approaches to determine whether miRNA can be utilized as a blood-based biomarker of cognitive aging. A random forest regression combining miRNA with biological (brain volume), clinical (comorbid conditions), and demographic variables in 1 ...[more]

PMID: 32846274

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Project description:BackgroundHere, we address a pivotal factor in Alzheimer's prevention-identifying those at risk early, when dementia can still be avoided. Recent research highlights an accelerated forgetting phenotype as a risk factor for Alzheimer's disease. We hypothesized that delayed recall over 4 weeks would predict cognitive decline over 1 year better than 30-min delayed recall, the current gold standard for detecting episodic memory problems which could be an early clinical manifestation of incipient Alzheimer's disease. We also expected hippocampal subfield volumes to improve predictive accuracy.MethodsForty-six cognitively healthy older people (mean age 70.7 ± 7.97, 21/46 female), recruited from databases such as Join Dementia Research, or a local database of volunteers, performed 3 memory tasks on which delayed recall was tested after 30 min and 4 weeks, as well as Addenbrooke's Cognitive Examination III (ACE-III) and CANTAB Paired Associates Learning. Medial temporal lobe subregion volumes were automatically measured using high-resolution 3T MRI. The ACE-III was repeated after 12 months to assess the change in cognitive ability. We used univariate linear regressions and ROC curves to assess the ability of tests of delayed recall to predict cognitive decline on ACE-III over the 12 months.ResultsFifteen of the 46 participants declined over the year (≥ 3 points lost on ACE-III). Four-week verbal memory predicted cognitive decline in healthy older people better than clinical gold standard memory tests and hippocampal MRI. The best single-test predictor of cognitive decline was the 4-week delayed recall on the world list (R2 = .123, p = .018, β = .418). Combined with hippocampal subfield volumetry, 4-week verbal recall identifies those at risk of cognitive decline with 93% sensitivity and 86% specificity (AUC = .918, p < .0001).ConclusionsWe show that a test of accelerated long-term forgetting over 4 weeks can predict cognitive decline in healthy older people where traditional tests of delayed recall cannot. Accelerated long-term forgetting is a sensitive, easy-to-test predictor of cognitive decline in healthy older people. Used alone or with hippocampal MRI, accelerated forgetting probes functionally relevant Alzheimer's-related change. Accelerated forgetting will identify early-stage impairment, helping to target more invasive and expensive molecular biomarker testing.

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MicroRNA predicts cognitive performance in healthy older adults.

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MicroRNA predicts cognitive performance in healthy older adults.

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