PXD028281 is an
original dataset announced via ProteomeXchange.
Dataset Summary
Title | Age prediction from human blood plasma using proteomic and small RNA data: a comparative analysis |
Description | Aging clocks, built from comprehensive molecular data, have emerged as promising tools in medicine, forensics, and ecological research. However, few studies have compared the suitability of different molecular data types to predict age in the same cohort and whether combining them would improve predictions. Here, we explored this at the level of proteins and small RNAs in 103 human blood plasma samples. First, we used a two-step mass spectrometry approach measuring 612 proteins to select and quantify 21 proteins that changed in abundance with age. Notably, proteins increasing with age were enriched for components of the complement system. Next, we used small RNA sequencing to select and quantify a set of 315 small RNAs that changed in abundance with age. Most of these were microRNAs (miRNAs), downregulated with age, and predicted to target genes related to growth, cancer, and senescence. Finally, we used the collected data to build age-predictive models. Among the different types of molecules, proteins yielded the most accurate model (R² = 0.59 ± 0.02), followed by miRNAs as the best-performing class of small RNAs (R² = 0.54 ± 0.02). Interestingly, the use of protein and miRNA data together improved predictions (R2 = 0.70 ± 0.01). Future work using larger sample sizes and a validation dataset will be necessary to confirm these results. Nevertheless, our study suggests that combining proteomic and miRNA data yields superior age predictions, possibly by capturing a broader range of age-related physiological changes. It will be interesting to determine if combining different molecular data types works as a general strategy to improve future aging clocks. |
HostingRepository | PRIDE |
AnnounceDate | 2023-11-14 |
AnnouncementXML | Submission_2023-11-14_09:02:01.489.xml |
DigitalObjectIdentifier | |
ReviewLevel | Peer-reviewed dataset |
DatasetOrigin | Original dataset |
RepositorySupport | Unsupported dataset by repository |
PrimarySubmitter | Jerome Salignon |
SpeciesList | scientific name: Homo sapiens (Human); NCBI TaxID: 9606; |
ModificationList | No PTMs are included in the dataset |
Instrument | Q Exactive HF |
Dataset History
Revision | Datetime | Status | ChangeLog Entry |
0 | 2021-09-09 08:10:27 | ID requested | |
1 | 2023-07-03 06:02:54 | announced | |
⏵ 2 | 2023-11-14 09:02:07 | announced | 2023-11-14: Updated project metadata. |
Publication List
Salignon J, Faridani OR, Miliotis T, Janssens GE, Chen P, Zarrouki B, Sandberg R, Davidsson P, Riedel CG, Age prediction from human blood plasma using proteomic and small RNA data: a comparative analysis. Aging (Albany NY), 15(12):5240-5265(2023) [pubmed] |
Keyword List
submitter keyword: Human, plasma, HRM-MS |
Contact List
Christian Riedel |
contact affiliation | Biosciences and Nutrition, Riedel Lab, Karolinska Institute, Sweden |
contact email | christian.riedel@ki.se |
lab head | |
Jerome Salignon |
contact affiliation | Karolinska Institute |
contact email | jerome.salignon@ki.se |
dataset submitter | |
Full Dataset Link List
Dataset FTP location
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PRIDE project URI |
Repository Record List
[ + ]
[ - ]
- PRIDE
- PXD028281
- Label: PRIDE project
- Name: Age prediction from human blood plasma using proteomic and small RNA data: a comparative analysis