Dataset Information

Adapting Blood DNA Methylation Aging Clocks for Use in Saliva Samples With Cell-type Deconvolution.

ABSTRACT: DeepMAge is a deep-learning DNA methylation aging clock that measures the organismal pace of aging with the information from human epigenetic profiles. In blood samples, DeepMAge can predict chronological age within a 2.8 years error margin, but in saliva samples, its performance is drastically reduced since aging clocks are restricted by the training set domain. However, saliva is an attractive fluid for genomic studies due to its availability, compared to other tissues, including blood. In this article, we display how cell type deconvolution and elastic net can be used to expand the domain of deep aging clocks to other tissues. Using our approach, DeepMAge's error in saliva samples was reduced from 20.9 to 4.7 years with no retraining.

SUBMITTER: Galkin F

PROVIDER: S-EPMC9261380 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Adapting Blood DNA Methylation Aging Clocks for Use in Saliva Samples With Cell-type Deconvolution.

Galkin Fedor F Kochetov Kirill K Mamoshina Polina P Zhavoronkov Alex A

Frontiers in aging 20210729

DeepMAge is a deep-learning DNA methylation aging clock that measures the organismal pace of aging with the information from human epigenetic profiles. In blood samples, DeepMAge can predict chronological age within a 2.8 years error margin, but in saliva samples, its performance is drastically reduced since aging clocks are restricted by the training set domain. However, saliva is an attractive fluid for genomic studies due to its availability, compared to other tissues, including blood. In thi ...[more]

PMID: 35822029

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Project description:BACKGROUND: The increasing trend for incorporation of biological sample collection within clinical trials requires sample collection procedures which are convenient and acceptable for both patients and clinicians. This study investigated the feasibility of using saliva-extracted DNA in comparison to blood-derived DNA, across two genotyping platforms: Applied Biosystems Taqman™ and Illumina Beadchip™ genome-wide arrays. METHOD: Patients were recruited from the Pharmacogenetics of Breast Cancer Chemotherapy (PGSNPS) study. Paired blood and saliva samples were collected from 79 study participants. The Oragene DNA Self-Collection kit (DNAgenotek®) was used to collect and extract DNA from saliva. DNA from EDTA blood samples (median volume 8 ml) was extracted by Gen-Probe, Livingstone, UK. DNA yields, standard measures of DNA quality, genotype call rates and genotype concordance between paired, duplicated samples were assessed. RESULTS: Total DNA yields were lower from saliva (mean 24 ?g, range 0.2-52 ?g) than from blood (mean 210 ?g, range 58-577 ?g) and a 2-fold difference remained after adjusting for the volume of biological material collected. Protein contamination and DNA fragmentation measures were greater in saliva DNA. 78/79 saliva samples yielded sufficient DNA for use on Illumina Beadchip arrays and using Taqman assays. Four samples were randomly selected for genotyping in duplicate on the Illumina Beadchip arrays. All samples were genotyped using Taqman assays. DNA quality, as assessed by genotype call rates and genotype concordance between matched pairs of DNA was high (>97%) for each measure in both blood and saliva-derived DNA. CONCLUSION: We conclude that DNA from saliva and blood samples is comparable when genotyping using either Taqman assays or genome-wide chip arrays. Saliva sampling has the potential to increase participant recruitment within clinical trials, as well as reducing the resources and organisation required for multicentre sample collection.

Dataset Information

Adapting Blood DNA Methylation Aging Clocks for Use in Saliva Samples With Cell-type Deconvolution.

Publications

Adapting Blood DNA Methylation Aging Clocks for Use in Saliva Samples With Cell-type Deconvolution.

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