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Plasma proteomic signature of human longevity.
Thursday,2024-04-04 11:27 America/Los_Angeles — ecterry
| Title | Plasma proteomic signature of human longevity. |
| Publication Type | Journal Article |
| Year of Publication | 2024 |
| Authors | Liu, X, Axelsson, GThor, Newman, AB, Psaty, BM, Boudreau, RM, Wu, C, Arnold, AM, Aspelund, T, Austin, TR, Gardin, JM, Siggeirsdottir, K, Tracy, RP, Gerszten, RE, Launer, LJ, Jennings, LL, Gudnason, V, Sanders, JL, Odden, MC |
| Journal | Aging Cell |
| Pagination | e14136 |
| Date Published | 2024 Mar 05 |
| ISSN | 1474-9726 |
| Abstract | <p>The identification of protein targets that exhibit anti-aging clinical potential could inform interventions to lengthen the human health span. Most previous proteomics research has been focused on chronological age instead of longevity. We leveraged two large population-based prospective cohorts with long follow-ups to evaluate the proteomic signature of longevity defined by survival to 90 years of age. Plasma proteomics was measured using a SOMAscan assay in 3067 participants from the Cardiovascular Health Study (discovery cohort) and 4690 participants from the Age Gene/Environment Susceptibility-Reykjavik Study (replication cohort). Logistic regression identified 211 significant proteins in the CHS cohort using a Bonferroni-adjusted threshold, of which 168 were available in the replication cohort and 105 were replicated (corrected p value <0.05). The most significant proteins were GDF-15 and N-terminal pro-BNP in both cohorts. A parsimonious protein-based prediction model was built using 33 proteins selected by LASSO with 10-fold cross-validation and validated using 27 available proteins in the validation cohort. This protein model outperformed a basic model using traditional factors (demographics, height, weight, and smoking) by improving the AUC from 0.658 to 0.748 in the discovery cohort and from 0.755 to 0.802 in the validation cohort. We also found that the associations of 169 out of 211 proteins were partially mediated by physical and/or cognitive function. These findings could contribute to the identification of biomarkers and pathways of aging and potential therapeutic targets to delay aging and age-related diseases.</p> |
| DOI | 10.1111/acel.14136 |
| Alternate Journal | Aging Cell |
| PubMed ID | 38440820 |
| Grant List | HHSN268201200036C / HL / NHLBI NIH HHS / United States HHSN268200800007C / HL / NHLBI NIH HHS / United States HHSN268201800001C / HL / NHLBI NIH HHS / United States N01HC55222 / HL / NHLBI NIH HHS / United States N01HC85079 / HL / NHLBI NIH HHS / United States N01HC85080 / HL / NHLBI NIH HHS / United States N01HC85081 / HL / NHLBI NIH HHS / United States N01HC85082 / HL / NHLBI NIH HHS / United States N01HC85083 / HL / NHLBI NIH HHS / United States N01HC85086 / HL / NHLBI NIH HHS / United States 75N92021D00006 / HL / NHLBI NIH HHS / United States U01HL080295 / HL / NHLBI NIH HHS / United States R01HL144483 / HL / NHLBI NIH HHS / United States U01HL130114 / HL / NHLBI NIH HHS / United States R01AG023629 / AG / NIA NIH HHS / United States N01AG12100 / AG / NIA NIH HHS / United States HHSN271201200022C / DA / NIDA NIH HHS / United States |
ePub date:
24/03