Health octo tool matches personalized health with rate of aging
Abstract Medical practice mainly addresses single diseases, neglecting multimorbidity as a heterogeneous health decline across organ systems. Aging is a multidimensional process and cannot be captured by a single metric. Therefore, we assessed global health in longitudinal studies, BLSA (n = 907), I...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-58819-x |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849312987522793472 |
|---|---|
| author | Sh Salimi A. Vehtari M. Salive M. Kaeberlein D. Raftery L. Ferrucci |
| author_facet | Sh Salimi A. Vehtari M. Salive M. Kaeberlein D. Raftery L. Ferrucci |
| author_sort | Sh Salimi |
| collection | DOAJ |
| description | Abstract Medical practice mainly addresses single diseases, neglecting multimorbidity as a heterogeneous health decline across organ systems. Aging is a multidimensional process and cannot be captured by a single metric. Therefore, we assessed global health in longitudinal studies, BLSA (n = 907), InCHIANTI (n = 986), and NHANES (n = 40,790), by examining disease severities in 13 bodily systems, generating the Body Organ Disease Number (BODN), reflecting progressive system morbidities. We used Bayesian ordinal models, regressing BODN over organ specific and all organs disease severities to obtain Body System-Specific Clocks and the Body Clock, respectively. The Body Clock is BODN weighted by the posterior coefficient of diseases for each individual. It supersedes the frailty index, predicting disability, geriatric syndrome, SPPB, and mortality with ≥90% accuracy. The Health Octo Tool, derived from Bodily System-Specific Clocks, the Body Clock and Clocks that incorporate walking speed and disability and their aging rates, captures multidimensional aging heterogeneity across organs and individuals. |
| format | Article |
| id | doaj-art-db5c09fcd779444f9bd08f3b24218273 |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-db5c09fcd779444f9bd08f3b242182732025-08-20T03:52:53ZengNature PortfolioNature Communications2041-17232025-05-0116111610.1038/s41467-025-58819-xHealth octo tool matches personalized health with rate of agingSh Salimi0A. Vehtari1M. Salive2M. Kaeberlein3D. Raftery4L. Ferrucci5Department of Anesthesiology and Pain Medicine, University of WashingtonDepartment of Computer Science, Aalto UniversityDivision of Geriatrics and Clinical Gerontology, National Institute on AgingOptispan IncDepartment of Anesthesiology and Pain Medicine, University of Washington, Northwest Metabolomics Research CenterIntramural Research Program, National Institute on AgingAbstract Medical practice mainly addresses single diseases, neglecting multimorbidity as a heterogeneous health decline across organ systems. Aging is a multidimensional process and cannot be captured by a single metric. Therefore, we assessed global health in longitudinal studies, BLSA (n = 907), InCHIANTI (n = 986), and NHANES (n = 40,790), by examining disease severities in 13 bodily systems, generating the Body Organ Disease Number (BODN), reflecting progressive system morbidities. We used Bayesian ordinal models, regressing BODN over organ specific and all organs disease severities to obtain Body System-Specific Clocks and the Body Clock, respectively. The Body Clock is BODN weighted by the posterior coefficient of diseases for each individual. It supersedes the frailty index, predicting disability, geriatric syndrome, SPPB, and mortality with ≥90% accuracy. The Health Octo Tool, derived from Bodily System-Specific Clocks, the Body Clock and Clocks that incorporate walking speed and disability and their aging rates, captures multidimensional aging heterogeneity across organs and individuals.https://doi.org/10.1038/s41467-025-58819-x |
| spellingShingle | Sh Salimi A. Vehtari M. Salive M. Kaeberlein D. Raftery L. Ferrucci Health octo tool matches personalized health with rate of aging Nature Communications |
| title | Health octo tool matches personalized health with rate of aging |
| title_full | Health octo tool matches personalized health with rate of aging |
| title_fullStr | Health octo tool matches personalized health with rate of aging |
| title_full_unstemmed | Health octo tool matches personalized health with rate of aging |
| title_short | Health octo tool matches personalized health with rate of aging |
| title_sort | health octo tool matches personalized health with rate of aging |
| url | https://doi.org/10.1038/s41467-025-58819-x |
| work_keys_str_mv | AT shsalimi healthoctotoolmatchespersonalizedhealthwithrateofaging AT avehtari healthoctotoolmatchespersonalizedhealthwithrateofaging AT msalive healthoctotoolmatchespersonalizedhealthwithrateofaging AT mkaeberlein healthoctotoolmatchespersonalizedhealthwithrateofaging AT draftery healthoctotoolmatchespersonalizedhealthwithrateofaging AT lferrucci healthoctotoolmatchespersonalizedhealthwithrateofaging |