| Title |
Age-related frailty and its association with biological markers of ageing
|
|---|---|
| Published in |
BMC Medicine, July 2015
|
| DOI | 10.1186/s12916-015-0400-x |
| Pubmed ID | |
| Authors |
Arnold Mitnitski, Joanna Collerton, Carmen Martin-Ruiz, Carol Jagger, Thomas von Zglinicki, Kenneth Rockwood, Thomas B. L. Kirkwood |
| Abstract |
The relationship between age-related frailty and the underlying processes that drive changes in health is currently unclear. Considered individually, most blood biomarkers show only weak relationships with frailty and ageing. Here, we examined whether a biomarker-based frailty index (FI-B) allowed examination of their collective effect in predicting mortality compared with individual biomarkers, a clinical deficits frailty index (FI-CD), and the Fried frailty phenotype. We analyzed baseline data and up to 7-year mortality in the Newcastle 85+ Study (n = 845; mean age 85.5). The FI-B combined 40 biomarkers of cellular ageing, inflammation, haematology, and immunosenescence. The Kaplan-Meier estimator was used to stratify participants into FI-B risk strata. Stability of the risk estimates for the FI-B was assessed using iterative, random subsampling of the 40 FI-B items. Predictive validity was tested using Cox proportional hazards analysis and discriminative ability by the area under receiver operating characteristic (ROC) curves. The mean FI-B was 0.35 (SD, 0.08), higher than the mean FI-CD (0.22; SD, 0.12); no participant had an FI-B score <0.12. Higher values of each FI were associated with higher mortality risk. In a sex-adjusted model, each one percent increase in the FI-B increased the hazard ratio by 5.4 % (HR, 1.05; CI, 1.04-1.06). The FI-B was more powerful for mortality prediction than any individual biomarker and was robust to biomarker substitution. The ROC analysis showed moderate discriminative ability for 7-year mortality (AUC for FI-CD = 0.71 and AUC for FI-B = 0.66). No individual biomarker's AUC exceeded 0.61. The AUC for combined FI-CD/FI-B was 0.75. Many biological processes are implicated in ageing. The systemic effects of these processes can be elucidated using the frailty index approach, which showed here that subclinical deficits increased the risk of death. In the future, blood biomarkers may indicate the nature of the underlying causal deficits leading to age-related frailty, thereby helping to expose targets for early preventative interventions. |
X Demographics
The data shown below were collected from the profiles of 28 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 14% |
| Canada | 4 | 14% |
| Australia | 3 | 11% |
| United States | 3 | 11% |
| Spain | 3 | 11% |
| India | 1 | 4% |
| Brazil | 1 | 4% |
| Unknown | 9 | 32% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 18 | 64% |
| Practitioners (doctors, other healthcare professionals) | 8 | 29% |
| Scientists | 2 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 244 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | <1% |
| Unknown | 243 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 40 | 16% |
| Student > Ph. D. Student | 39 | 16% |
| Student > Bachelor | 26 | 11% |
| Other | 21 | 9% |
| Student > Doctoral Student | 19 | 8% |
| Other | 45 | 18% |
| Unknown | 54 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 65 | 27% |
| Biochemistry, Genetics and Molecular Biology | 20 | 8% |
| Nursing and Health Professions | 16 | 7% |
| Agricultural and Biological Sciences | 14 | 6% |
| Immunology and Microbiology | 8 | 3% |
| Other | 43 | 18% |
| Unknown | 78 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 31. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 May 2021.
All research outputs
#1,305,529
of 25,743,152 outputs
Outputs from BMC Medicine
#904
of 4,083 outputs
Outputs of similar age
#15,692
of 276,789 outputs
Outputs of similar age from BMC Medicine
#19
of 75 outputs
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