Predicting age from the transcriptome of human dermal fibroblasts
Fleischer JG, Schulte R, Tsai HH, Tyagi S, Ibarra A, Shokhirev MN, Huang L, Hetzer M, Navlakha S. 2018. Predicting age from the transcriptome of human dermal fibroblasts. Genome Biology. 19, 221.
Download (ext.)
Journal Article
| Published
| English
Scopus indexed
Author
Fleischer, Jason G.;
Schulte, Roberta;
Tsai, Hsiao H.;
Tyagi, Swati;
Ibarra, Arkaitz;
Shokhirev, Maxim N.;
Huang, Ling;
Hetzer, MartinISTA 
;
Navlakha, Saket
;
Navlakha, SaketAbstract
Biomarkers of aging can be used to assess the health of individuals and to study aging and age-related diseases. We generate a large dataset of genome-wide RNA-seq profiles of human dermal fibroblasts from 133 people aged 1 to 94 years old to test whether signatures of aging are encoded within the transcriptome. We develop an ensemble machine learning method that predicts age to a median error of 4 years, outperforming previous methods used to predict age. The ensemble was further validated by testing it on ten progeria patients, and our method is the only one that predicts accelerated aging in these patients.
Publishing Year
Date Published
2018-12-20
Journal Title
Genome Biology
Publisher
BioMed Central
Volume
19
Article Number
221
ISSN
IST-REx-ID
Cite this
Fleischer JG, Schulte R, Tsai HH, et al. Predicting age from the transcriptome of human dermal fibroblasts. Genome Biology. 2018;19. doi:10.1186/s13059-018-1599-6
Fleischer, J. G., Schulte, R., Tsai, H. H., Tyagi, S., Ibarra, A., Shokhirev, M. N., … Navlakha, S. (2018). Predicting age from the transcriptome of human dermal fibroblasts. Genome Biology. BioMed Central. https://doi.org/10.1186/s13059-018-1599-6
Fleischer, Jason G., Roberta Schulte, Hsiao H. Tsai, Swati Tyagi, Arkaitz Ibarra, Maxim N. Shokhirev, Ling Huang, Martin Hetzer, and Saket Navlakha. “Predicting Age from the Transcriptome of Human Dermal Fibroblasts.” Genome Biology. BioMed Central, 2018. https://doi.org/10.1186/s13059-018-1599-6.
J. G. Fleischer et al., “Predicting age from the transcriptome of human dermal fibroblasts,” Genome Biology, vol. 19. BioMed Central, 2018.
Fleischer JG, Schulte R, Tsai HH, Tyagi S, Ibarra A, Shokhirev MN, Huang L, Hetzer M, Navlakha S. 2018. Predicting age from the transcriptome of human dermal fibroblasts. Genome Biology. 19, 221.
Fleischer, Jason G., et al. “Predicting Age from the Transcriptome of Human Dermal Fibroblasts.” Genome Biology, vol. 19, 221, BioMed Central, 2018, doi:10.1186/s13059-018-1599-6.
All files available under the following license(s):
Copyright Statement:
This Item is protected by copyright and/or related rights. [...]
Link(s) to Main File(s)
Access Level
Open Access
Export
Marked PublicationsOpen Data ISTA Research Explorer
Sources
PMID: 30567591
PubMed | Europe PMC
Google Scholar