Dataset Information

Relationship between telomere shortening and age in Korean individuals with mild cognitive impairment and Alzheimer's disease compared to that in healthy controls.

ABSTRACT: Although telomere length (TL) is highly variable, a shorter TL indicate increased biological age. This multicenter study was conducted to identify the overall correlation between age and TL in Koreans and investigate the associations between age and TL in healthy individuals and patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). TL was measured in peripheral leukocyte DNA. MCI and AD were diagnosed based on clinical examinations and amyloid deposition on positron emission tomography. This study enrolled 437 individuals. Multivariable linear analysis showed an overall approximate TL decrease of 37 bp per 1-year increase in age in all individuals (B=-0.037; P=0.002). There was no significant difference in the mean TL between healthy individuals and individuals with AD. Multivariable linear regression analysis showed that the mean rate of telomere shortening was 60 bp per year in individuals with AD (B=-0.060; P=0.006). There was a negative association between age and TL in our study. Our study results showed more significant telomere shortening per year in women than that in men. In addition, individuals with AD had greater telomere shortening every year than healthy individuals and individuals with MCI.

SUBMITTER: Lee EH

PROVIDER: S-EPMC7880372 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Relationship between telomere shortening and age in Korean individuals with mild cognitive impairment and Alzheimer's disease compared to that in healthy controls.

Lee Eun-Hye EH Han Myung-Hoon MH Ha Jungsoon J Park Hyun-Hee HH Koh Seong-Ho SH Choi Seong Hye SH Lee Jae-Hong JH

Aging 20201215 2

Although telomere length (TL) is highly variable, a shorter TL indicate increased biological age. This multicenter study was conducted to identify the overall correlation between age and TL in Koreans and investigate the associations between age and TL in healthy individuals and patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). TL was measured in peripheral leukocyte DNA. MCI and AD were diagnosed based on clinical examinations and amyloid deposition on positron emissio ...[more]

PMID: 33323554

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Project description:ObjectivesAlzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Certain genes have been identified as important clinical risk factors for AD, and technological advances in genomic research, such as genome-wide association studies (GWAS), allow for analysis of polymorphisms and have been widely applied to studies of AD. However, shortcomings of GWAS include sensitivity to sample size and hereditary deletions, which result in low classification and predictive accuracy. Therefore, this paper proposes a novel deep-learning genomics approach and applies it to multitasking classification of AD progression, with the goal of identifying novel genetic biomarkers overlooked by traditional GWAS analysis.MethodsIn this study, we selected genotype data from 1461 subjects enrolled in the Alzheimer's Disease Neuroimaging Initiative, including 622 AD, 473 mild cognitive impairment (MCI), and 366 healthy control (HC) subjects. The proposed deep-learning genomics (DLG) approach consists of three steps: quality control, coding of single-nucleotide polymorphisms, and classification. The ResNet framework was used for the DLG model, and the results were compared with classifications by simple convolutional neural network structure. All data were randomly assigned to one training/validation group and one test group at a ratio of 9 : 1. And fivefold cross-validation was used.ResultsWe compared classification results from the DLG model to those from traditional GWAS analysis among the three groups. For the AD and HC groups, the accuracy, sensitivity, and specificity of classification were, respectively, 98.78 ± 1.50%, 98.39% ± 2.50%, and 99.44% ± 1.11% using the DLG model, while 71.38% ± 0.63%, 63.13% ± 2.87%, and 85.59% ± 6.66% using traditional GWAS. Similar results were obtained from the other two intergroup classifications.ConclusionThe DLG model can achieve higher accuracy and sensitivity when applied to progression of AD. More importantly, we discovered several novel genetic biomarkers of AD progression, including rs6311 and rs6313 in HTR2A, rs1354269 in NAV2, and rs690705 in RFC3. The roles of these novel loci in AD should be explored in future research.

Dataset Information

Relationship between telomere shortening and age in Korean individuals with mild cognitive impairment and Alzheimer's disease compared to that in healthy controls.

Publications

Relationship between telomere shortening and age in Korean individuals with mild cognitive impairment and Alzheimer's disease compared to that in healthy controls.

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