Multi-omics network analysis reveals distinct stages in the human aging progression in epidermal tissue
Open accessAbstract
human skin tissue. For this we generated transcriptome and methylome profiling data from suction blister lesions of female subjects between 21 and 76 years, which were integrated using a network fusion approach. Unsupervised cluster analysis on the combined network identified four distinct subgroupings exhibiting a significant age-association. As indicated by DNAm age analysis and Hallmark of Aging enrichment signals, the stages captured the biological aging state more clearly than a mere grouping by chronological age and could further be recovered in a longitudinal validation cohort with high stability. Characterization of the biological processes driving the phases using machine learning enabled a data-driven reconstruction of the order of Hallmark of Aging manifestation. Finally, we investigated non-linearities in the mid-life aging progression captured by the aging phases and identified a far-reaching non-linear increase in transcriptional noise in the pathway landscape in the transition from mid- to late-life.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Epigenetic and other molecular features in blood cells or skin change in distinct undulating patterns across the lifespan.
“similarly, epigenetic and other molecular features in blood cells177 or skin178 change in distinct undulating patterns across the lifespan.”
From Measuring biological age using omics data (2022) · cites this paper as [178]
A longitudinal study of the transcriptome and DNA methylation state of skin in 121 humans between 21 and 76 years of age revealed 4 distinct 'phases of aging' highlighted by the activity of different biological processes.
“Likewise, a longitudinal study of the transcriptome and DNA methylation state of skin in 121 humans between 21 and 76 years of age revealed 4 distinct “phases of aging” highlighted by the activity of different biological processes.37”
From Asynchronous, contagious and digital aging (2021) · cites this paper as [37]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 49 · Cited by 40
Research works printed but not linked: 4
- [32]National Cancer Institute (NCI). SEER Cancer Statistics Review (CSR) 1975–2014. 2018.
- [33]Fitzpatrick TB. Soleil et peau. Journal de Médecine Esthétique. 1975; 2: 4.
- [48]Bischl B, Lang M, Kotthoff L, Schiffner J, Richter J, Studerus E, Casalicchio G, Jones ZM, Casalicchio G, Gallo M, Schratz P. mlr: Machine Learning in R. Journal of Machine Learning Research. 2016; 17: 1– 5.
- [57]Xiao N. ggsci: Scientific Journal and Sci-Fi Themed Color Palettes for “ggplot2.” 2018.
- Authors
- Holzscheck, N., Söhle, J., Kristof, B., Grönniger, E., Gallinat, S., Wenck, H., Winnefeld, M., Falckenhayn, C., & Kaderali, L.
- Affiliations
- Beiersdorf (Germany) (DE)
- Universitätsmedizin Greifswald (DE)
- Corresponding author
- Holzscheck, Nicholas
- ORCID
- Venue
- Aging
- Publisher
- Impact Journals, LLC
- Published
- 2020-06-18
- Volume
- 12
- Issue
- 12
- Pages
- 12393-12409
- ISSN
- 1945-4589 (ISSN-L)
- PMC
- PMC7343460
- OpenAlex
- W3036524281
- Cited by
- 40
- References
- 49
- Citations by year
- 2026: 6 · 2025: 6 · 2024: 8 · 2023: 5 · 2022: 4 · 2021: 9 · 2020: 2
- FWCI
- 1.62
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- cc-by
- Locations
- Aging (publishedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- epidermis, transcriptome, DNA methylation, hallmarks of aging, transcriptional noise, longitudinal cohort
- MeSH terms
- Machine Learning, Adult, Aged, Epidermis, Female, Humans, Middle Aged, Models, Genetic, Skin Aging, Cluster Analysis, Logistic Models, DNA Methylation, Gene Expression Profiling, Young Adult, Epigenomics, Transcriptome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
