Dataset Information

Age- and sex-dependent changes in levels of circulating brain-enriched microRNAs during normal aging.

ABSTRACT: Aging is a major risk factor for many common and life-threatening pathologies. The development of reliable biomarkers of aging should lead to a better understanding of aging-associated processes and facilitate the development of therapeutic regimens that delay aging. Levels of 38 brain-enriched microRNAs (miRNA) circulating in plasma were measured by quantitative RT-PCR in two age groups: 26-35 and 56-65 years old. An miRNA-pair approach was used for data normalization and determination of effective miRNA biomarker ratios. Nineteen miRNAs, comprising miRNA pairs and pair combinations (classifiers) that effectively differentiated the age and sex (individual pairs: 74-95% and 68-95%, respectively; classifiers: up to 100% accuracy) groups, were selected for further analysis of plasma samples from 5 donor age groups: 26-35, 36-45, 46-55, 56-65 and 66-75 years old. Dynamic changes in the plasma concentrations of certain miRNAs occurred at different ages in females and males, with peaks in the 46-55-year-old and 56-65-year-old groups, respectively. This finding suggests that the changes in miRNA levels can reflect centrally regulated processes, including changes in hormone levels during menopause. Certain miRNAs and miRNA pairs correlated with age in the sex-stratified groups at different ages and should be investigated further as potentially promising biomarkers of brain aging.

SUBMITTER: Sheinerman K

PROVIDER: S-EPMC6224262 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Age- and sex-dependent changes in levels of circulating brain-enriched microRNAs during normal aging.

Sheinerman Kira K Tsivinsky Vladimir V Mathur Aabhas A Kessler Debra D Shaz Beth B Umansky Samuil S

Aging 20181001 10

Aging is a major risk factor for many common and life-threatening pathologies. The development of reliable biomarkers of aging should lead to a better understanding of aging-associated processes and facilitate the development of therapeutic regimens that delay aging. Levels of 38 brain-enriched microRNAs (miRNA) circulating in plasma were measured by quantitative RT-PCR in two age groups: 26-35 and 56-65 years old. An miRNA-pair approach was used for data normalization and determination of effec ...[more]

PMID: 30383539

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Project description:Background: Neuroscience lacks a reliable method of screening the early stages of dementia. Objective: To improve the diagnostics of age-related cognitive functions by developing insight into the proportionality of age-related changes in cognitive subdomains. Materials and Methods: We composed a battery of psychophysiological tests and collected an open-access psychophysiological outcomes of brain atrophy (POBA) dataset by testing individuals without dementia. To extend the utility of machine learning (ML) classification in cognitive studies, we proposed estimates of the disproportional changes in cognitive functions: an index of simple reaction time to decision-making time (ISD), ISD with the accuracy performance (ISDA), and an index of performance in simple and complex visual-motor reaction with account for accuracy (ISCA). Studying the distribution of the values of the indices over age allowed us to verify whether diverse cognitive functions decline equally throughout life or there is a divergence in age-related cognitive changes. Results: Unsupervised ML clustering shows that the optimal number of homogeneous age groups is four. The sample is segregated into the following age-groups: Adolescents ∈ [0, 20), Young adults ∈ [20, 40), Midlife adults ∈ [40, 60) and Older adults ≥60 year of age. For ISD, ISDA, and ISCA values, only the median of the Adolescents group is different from that of the other three age-groups sharing a similar distribution pattern (p > 0.01). After neurodevelopment and maturation, the indices preserve almost constant values with a slight trend toward functional decline. The reaction to a moving object (RMO) test results (RMO_mean) follow another tendency. The Midlife adults group's median significantly differs from the remaining three age subsamples (p < 0.01). No general trend in age-related changes of this dependent variable is observed. For all the data (ISD, ISDA, ISCA, and RMO_mean), Levene's test reveals no significant changes of the variances in age-groups (p > 0.05). Homoscedasticity also supports our assumption about a linear dependency between the observed features and age. Conclusion: In healthy brain aging, there are proportional age-related changes in the time estimates of information processing speed and inhibitory control in task switching. Future studies should test patients with dementia to determine whether the changes of the aforementioned indicators follow different patterns.

Project description:BACKGROUND:Minimally invasive specific biomarkers of neurodegenerative diseases (NDs) would facilitate patient selection and disease progression monitoring. We describe the assessment of circulating brain-enriched microRNAs as potential biomarkers for Alzheimer's disease (AD), frontotemporal dementia (FTD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). METHODS:In this case-control study, the plasma samples were collected from 250 research participants with a clinical diagnosis of AD, FTD, PD, and ALS, as well as from age- and sex-matched control subjects (n = 50 for each group), recruited from 2003 to 2015 at the University of Pennsylvania Health System, including the Alzheimer's Disease Center, the Parkinson's Disease and Movement Disorders Center, the Frontotemporal Degeneration Center, and the Amyotrophic Lateral Sclerosis Clinic. Each group was randomly divided into training and confirmation sets of equal size. To evaluate the potential of circulating microRNAs enriched in specific brain regions affected by NDs and present in synapses as biomarkers of NDs, the levels of 37 brain-enriched and inflammation-associated microRNAs in the plasma of all participants were measured using individual qRT-PCR. A "microRNA pair" approach was used for data normalization. RESULTS:MicroRNA pairs and their combinations (classifiers) capable of differentiating NDs from control and from each other were defined using independently and jointly analyzed training and confirmation datasets. AD, PD, FTD, and ALS are differentiated from control with accuracy of 0.89, 0.90, 0.88, and 0.83 (AUCs, 0.96, 0.96, 0.94, and 0.93), respectively; NDs are differentiated from each other with accuracy ranging from 0.77 (AUC, 0.87) for AD vs. FTD to 0.93 (AUC, 0.98) for AD vs. ALS. The data further indicate sex dependence of some microRNA markers. The average increase in accuracy in distinguishing ND from control for all and male/female groups is 0.06; the largest increase is for ALS, from 0.83 for all participants to 0.92/0.98 for male/female participants. CONCLUSIONS:The work presented here suggests the possibility of developing microRNA-based diagnostics for detection and differentiation of NDs. Larger multicenter clinical studies are needed to further evaluate circulating brain-enriched microRNAs as biomarkers for NDs and to investigate their association with other ND biomarkers in clinical trial settings.

Dataset Information

Age- and sex-dependent changes in levels of circulating brain-enriched microRNAs during normal aging.

Publications

Age- and sex-dependent changes in levels of circulating brain-enriched microRNAs during normal aging.

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