The DOI matches its Crossref record; 81 of the 81 references it cites were found in a registry or an index.
Multi-omic rejuvenation and lifespan extension on exposure to youthful circulation
Open accessPublished version of a preprint
Abstract
Heterochronic parabiosis (HPB) is known for its functional rejuvenation effects across several mouse tissues. However, its impact on biological age and long-term health is unknown. Here we performed extended (3-month) HPB, followed by a 2-month detachment period of anastomosed pairs. Old detached mice exhibited improved physiological parameters and lived longer than control isochronic mice. HPB drastically reduced the epigenetic age of blood and liver based on several clock models using two independent platforms. Remarkably, this rejuvenation effect persisted even after 2 months of detachment. Transcriptomic and epigenomic profiles of anastomosed mice showed an intermediate phenotype between old and young, suggesting a global multi-omic rejuvenation effect. In addition, old HPB mice showed gene expression changes opposite to aging but akin to several life span-extending interventions. Altogether, we reveal that long-term HPB results in lasting epigenetic and transcriptome remodeling, culminating in the extension of life span and health span.
Overview
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
Verification
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?
In the citing paper
“young blood prolongs the BA of aged recipients via epigenetic remodelling447 and rejuvenates various organs, including the brain.379,448”
From Antiageing strategy for neurodegenerative diseases: from mechanisms to clinical advances (2025) · cites this paper as [447]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
Robinson, M. D., McCarthy, D. J., & Smyth, G. K. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp616 · Cited by 41,364
featureCounts: an efficient general purpose program for assigning sequence reads to genomic features
Liao, Y., Smyth, G. K., & Shi, W. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btt656 · Cited by 27,219
Differential expression analysis for sequence count data
Anders, S., & Huber, W. (2010) · Genome Biology · doi:10.1186/gb-2010-11-10-r106 · Cited by 15,581
López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M., & Kroemer, G. (2013) · Cell · doi:10.1016/j.cell.2013.05.039 · Cited by 14,982
The Molecular Signatures Database Hallmark Gene Set Collection
Liberzon, A., Birger, C., Thorvaldsdóttir, H., Ghandi, M., Mesirov, J. P., & Tamayo, P. (2015) · Cell Systems · doi:10.1016/j.cels.2015.12.004 · Cited by 13,807
DNA methylation age of human tissues and cell types
Horvath, S. (2013) · Genome Biology · doi:10.1186/gb-2013-14-10-r115 · Cited by 7,075
Self-citation
Cited by
Sorted by citations
Items 101–147 of 147
Zhang, L., Ren, Y., Su, D., Jiang, Q., Peng, H., Cheng, F., Zhang, H., Bai, X. L., Wei, X., Yang, W., et al. (2025) · MedComm · doi:10.1002/mco2.70339
Natural accelerated proteomic ageing in the red-tailed phascogale mirrors human ageing trajectoriesPreprint
Tayebi, M., & David, M. A. (2025) · Research Square · doi:10.21203/rs.3.rs-7742962/v1
Transfer of Aging: Implications for Pediatric Solid Organ Transplantation
Gudenberg, R. W. V., Eckholt, L. S. J., Moosburner, S., Greve, D., Boerger, L., Walter, K. A., Wert, L., Geiger, D., Penkalla, A., Schmitto, J. D., et al. (2025) · Pediatric Transplantation · doi:10.1111/petr.70226
Song, J., Zhao, W., Zhang, J., Hu, K., Ma, B., Wang, S., Zhao, Y., & Pu, J. (2025) · STAR Protocols · doi:10.1016/j.xpro.2025.104268
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739624
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739621
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739645
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739603
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739615
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739636
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26113160
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739606
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739618
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739633
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739639
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739612
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739609
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739642
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739648
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739654
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739651
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739627
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26739630
Liu, Y., Lu, S., Yang, J., Yang, Y., Jiao, L., Hu, J., Li, Y., Yang, F., Pang, Y., Zhao, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26113065
Moldakozhayev, A., Tyshkovskiy, A., Nigro, P., Zhang, Z., Tskhay, A., de Magalhães, C. G., Yadav, S., Ying, K., Eames, A., Poganik, J. R., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.28.696721
Self-citationThe Aging Blood: Cellular Origins, Circulating Drivers, and Therapeutic Potential
He, H., & Wang, J. (2026) · Aging and Cancer · doi:10.1002/aac2.70016
Cai, J., Zhang, J., Ning, Y., Zhang, J., Xu, T., Liu, M., Wang, K., & Chen, H. (2026) · Aging Cell · doi:10.1111/acel.70400
Transplanting ANXA1⁻ CD8⁺ Naïve T cells Delay Aging Through SenolysisPreprint
Wu, Y., Guo, S. Z., Zhang, F., Lou, F., Li, Y. Y., Sun, Y., Shen, Q., Zhao, L., Cai, X., Wang, Z., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.21.707223
Regulation of Aging by the Epigenome
Oyabu, M., & Kamei, Y. (2025) · KAGAKU TO SEIBUTSU · doi:10.1271/kagakutoseibutsu.63.123
Cervantes, A. F. A. (2026) · Preprints.org · doi:10.20944/preprints202603.0713.v1
Liu, W., Yang, Z., Chen, C., Yu, F., Wu, M., Yao, Z., Fan, Y., Xie, T., Wan, L., Chou, T., et al. (2026) · Cell Discovery · doi:10.1038/s41421-026-00877-6
Longer-Term Interventions: Senolytics, Epigenetics, Telomeres
Cramer, J. G. (2026) · Copernicus books · doi:10.1007/978-3-032-17741-4_7
Li, X. D., Ma, G., Wang, F., Ding, Z., Chen, Y., Cheng, S., Pang, W., Chen, L., & Cao, H. (2026) · Molecular Therapy · doi:10.1016/j.ymthe.2026.05.015
Liu, J. T., Li, D. Y., Wu, S., & Liu, N. (2026) · Stem Cell Reviews and Reports · doi:10.1007/s12015-026-11157-x
Reversing mesenchymal drift in organismal decline: A new mandate for partial reprogramming
Zhang, Y., Chen, Q., Li, F., & Liang, C. (2026) · The Innovation Medicine · doi:10.59717/j.xinn-med.2026.100241
The microbiome in human skin aging
Arana, M. H., Wiegand, C., Omrani, O., & Fabri, M. (2026) · FEBS Letters · doi:10.1002/1873-3468.70435
Gulej, R., Kristóf, R., Patai, R., Chandragiri, S. S., Ekambaram, S., Nagykaldi, M., Brunner, E., Mukli, P., Nyúl‐Tóth, Á., Nagy, D., et al. (2026) · GeroScience · doi:10.1007/s11357-026-02424-3
Extracellular vesicles in longEVity medicines
Ding, S., Lei, Q., & Chrzanowski, W. (2026) · Biomedical Materials Science · doi:10.1186/s44495-026-00006-1
Naz, H., Lu, N., Escoubas, C. C., Sager, L., Xiong, J., Pálovics, R., Yamada, S., Molofsky, A. V., Wyss‐Coray, T., Li, Q., et al. (2026) · Cell Reports · doi:10.1016/j.celrep.2026.117919
Aging vs. biological age: Conceptual considerations for age reversal claims
Poganik, J. R., Moldakozhayev, A., Justice, J. N., Kaeberlein, M. R., Adams, P. D., Rockwood, K. J., Ferrucci, L., & Gladyshev, V. N. (2026) · Cell Metabolism · doi:10.1016/j.cmet.2026.06.015
Self-citationA positively selected microRNA controls a reversible aging program in striated musclePreprint
Boldridge, M. A., Xu, L., Wang, X., Stirm, M., Bonilla, G. M., Zhu, C., Lee, J. Y., Stark, R. L., Villivalam, S. D., Løvendorf, M. B., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.09.03.749250
Strengthening muscle for healthy ageing: innovative treatments for sarcopenia
Ancel, S., Moal, E. L., Wang, Y. X., & Blau, H. M. (2026) · Nature Reviews Drug Discovery · doi:10.1038/s41573-026-01514-3
Chenhao, J., Lu, H., Liu, Y., Jianhao, Z., Chen, H., Xinyun, W., Chi, X., Fan, L., Li, T., Shi, S., et al. (2026) · Journal of Hepatology · doi:10.1016/j.jhep.2026.08.036
Rodrigues, G. D. S., Neto, I. V. D. S., Kawamura, T., Carolino, R. O. G., Pinto, A. P., dos Santos, J. D. M., Cintra, D. E., Ropelle, E. R., Pauli, J. R., de Freitas, E. C., et al. (2026) · Physiological Genomics · doi:10.1152/physiolgenomics.00089.2026
Old hearts age backwards: transplanted organs adjust to host’s biological age
Simms, C. (2026) · Nature · doi:10.1038/d41586-026-03043-w
Systemic control and inter-organ communication of ovarian agingPreprint
Iqbal, S., Tyshkovskiy, A., Zhang, B., Zhang, S., Molière, A., Ying, K., Bai, Y., Steven, H., Goeminne, L., Alba‐Linares, J. J., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.10.11.758357
Self-citationEpigenetics in development, disease, and therapy: from mechanisms to clinical interventions
Ren, Y., Yang, L., Fei, B., Guo, R., Huang, J., Xu, Z., Wang, R., Zhang, P., Cao, D., Chen, P., et al. (2026) · Science China Life Sciences · doi:10.1007/s11427-025-3356-1
Metadata
- Authors
- Zhang, B., Lee, D. E., Trapp, A., Tyshkovskiy, A., Lu, A. T., Bareja, A., Kerepesi, C., McKay, L. K., Shindyapina, A. V., Dmitriev, S. E., Baht, G. S., Horvath, S., Gladyshev, V. N., & White, J. P.
- Affiliations
- Brigham and Women's Hospital (US)
- Duke University (US)
- University of California, Los Angeles (US)
- University of North Carolina at Chapel Hill (US)
- Lomonosov Moscow State University (RU)
- Corresponding author
- Gladyshev, Vadim N.
- White, James P.
- ORCID
- Venue
- Nature Aging
- Published
- 2023-07-27
- Volume
- 3
- Issue
- 8
- Pages
- 948-964
- ISSN
- 2662-8465 (ISSN-L)
- PMC
- PMC11095548
- OpenAlex
- W4385302610
- Cited by
- 134
- References
- 81
- Citations by year
- 2026: 31 · 2025: 41 · 2024: 48 · 2023: 13
- FWCI
- 9.76
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nature Aging (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- SZTAKI Publication Repository (Hungarian Academy of Sciences) (submittedVersion)
- Funders
- National Institutes of Health
- National Institute on Aging (K01AG056664, R01AG067782, R21AG065943, R01AG065403, P01AG047200)
- National Heart, Lung, and Blood Institute (T32HL007057)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Telomeres, Telomerase, and Senescence
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Keywords
- heterochronic parabiosis, rejuvenation, lifespan extension, healthspan, epigenetic aging, transcriptomic remodeling, age-related diseases, multi-omics profiling
- MeSH terms
- Multiomics, Aging, Animals, Longevity, Rejuvenation, Mice
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