Biomarkers Associated with Physical Resilience After Hip Fracture.


Journal

The journals of gerontology. Series A, Biological sciences and medical sciences
ISSN: 1758-535X
Titre abrégé: J Gerontol A Biol Sci Med Sci
Pays: United States
ID NLM: 9502837

Informations de publication

Date de publication:
25 09 2020
Historique:
received: 19 11 2019
pubmed: 10 5 2020
medline: 17 2 2021
entrez: 10 5 2020
Statut: ppublish

Résumé

Clinically similar older adults demonstrate variable responses to health stressors, heterogeneity attributable to differences in physical resilience. However, molecular mechanisms underlying physical resilience are unknown. We previously derived a measure of physical resilience after hip fracture-the expected recovery differential (ERD)-that captures the difference between actual recovery and predicted recovery. Starting with biomarkers associated with physical performance, morbidity, mortality, and hip fracture, we evaluated associations with the ERD to identify biomarkers of physical resilience after hip fracture. In the Baltimore Hip Studies (N = 304) sera, we quantified biomarkers of inflammation (TNFR-I, TNFR-II, sVCAM-1, and IL-6), metabolic and mitochondrial function (non-esterified fatty acids, lactate, ketones, acylcarnitines, free amino acids, and IGF-1), and epigenetic dysregulation (circulating microRNAs). We used principal component analysis, canonical correlation, and least absolute shrinkage and selection operator regression (LASSO) to identify biomarker associations with better-than-expected recovery (greater ERD) after hip fracture. Participants with greater ERD were more likely to be women and less disabled at baseline. The complete biomarker set explained 37% of the variance in ERD (p < .001) by canonical correlation. LASSO regression identified a biomarker subset that accounted for 27% of the total variance in the ERD and included a metabolic factor (aspartate/asparagine, C22, C5:1, lactate, glutamate/mine), TNFR-I, miR-376a-3p, and miR-16-5p. We identified a set of biomarkers that explained 27% of the variance in ERD-a measure of physical resilience after hip fracture. These ERD-associated biomarkers may be useful in predicting physical resilience in older adults facing hip fracture and other acute health stressors.

Sections du résumé

BACKGROUND
Clinically similar older adults demonstrate variable responses to health stressors, heterogeneity attributable to differences in physical resilience. However, molecular mechanisms underlying physical resilience are unknown. We previously derived a measure of physical resilience after hip fracture-the expected recovery differential (ERD)-that captures the difference between actual recovery and predicted recovery. Starting with biomarkers associated with physical performance, morbidity, mortality, and hip fracture, we evaluated associations with the ERD to identify biomarkers of physical resilience after hip fracture.
METHODS
In the Baltimore Hip Studies (N = 304) sera, we quantified biomarkers of inflammation (TNFR-I, TNFR-II, sVCAM-1, and IL-6), metabolic and mitochondrial function (non-esterified fatty acids, lactate, ketones, acylcarnitines, free amino acids, and IGF-1), and epigenetic dysregulation (circulating microRNAs). We used principal component analysis, canonical correlation, and least absolute shrinkage and selection operator regression (LASSO) to identify biomarker associations with better-than-expected recovery (greater ERD) after hip fracture.
RESULTS
Participants with greater ERD were more likely to be women and less disabled at baseline. The complete biomarker set explained 37% of the variance in ERD (p < .001) by canonical correlation. LASSO regression identified a biomarker subset that accounted for 27% of the total variance in the ERD and included a metabolic factor (aspartate/asparagine, C22, C5:1, lactate, glutamate/mine), TNFR-I, miR-376a-3p, and miR-16-5p.
CONCLUSIONS
We identified a set of biomarkers that explained 27% of the variance in ERD-a measure of physical resilience after hip fracture. These ERD-associated biomarkers may be useful in predicting physical resilience in older adults facing hip fracture and other acute health stressors.

Identifiants

pubmed: 32386291
pii: 5835302
doi: 10.1093/gerona/glaa119
pmc: PMC7518564
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

e166-e172

Subventions

Organisme : NIA NIH HHS
ID : R01 AG029315
Pays : United States
Organisme : NIA NIH HHS
ID : P30 AG028747
Pays : United States
Organisme : NIA NIH HHS
ID : UH3 AG056925
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR002553
Pays : United States
Organisme : NIA NIH HHS
ID : P30 AG028716
Pays : United States
Organisme : NIA NIH HHS
ID : UH2 AG056925
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG018668
Pays : United States
Organisme : NIA NIH HHS
ID : R37 AG009901
Pays : United States
Organisme : NIA NIH HHS
ID : T32 AG000262
Pays : United States

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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Auteurs

Daniel C Parker (DC)

Division of Geriatrics, Duke University School of Medicine, Durham, North Carolina.
Center for the Study of Aging and Human Development, Duke University, Durham, North Carolina.

Cathleen Colόn-Emeric (C)

Division of Geriatrics, Duke University School of Medicine, Durham, North Carolina.
Center for the Study of Aging and Human Development, Duke University, Durham, North Carolina.

Janet L Huebner (JL)

Duke University School of Medicine, Duke Molecular Physiology Institute, Durham, North Carolina.

Ching-Heng Chou (CH)

Duke University School of Medicine, Duke Molecular Physiology Institute, Durham, North Carolina.

Virginia Byers Kraus (VB)

Center for the Study of Aging and Human Development, Duke University, Durham, North Carolina.
Division of Rheumatology, Duke University School of Medicine, Durham, North Carolina.
Department of Biostatistics, Duke University School of Medicine, Durham, North Carolina.

Carl F Pieper (CF)

Center for the Study of Aging and Human Development, Duke University, Durham, North Carolina.
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore.

Richard Sloane (R)

Center for the Study of Aging and Human Development, Duke University, Durham, North Carolina.

Heather E Whitson (HE)

Division of Geriatrics, Duke University School of Medicine, Durham, North Carolina.
Center for the Study of Aging and Human Development, Duke University, Durham, North Carolina.
Duke University School of Medicine, Duke Molecular Physiology Institute, Durham, North Carolina.

Denise Orwig (D)

Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore.

Donna M Crabtree (DM)

Duke Office of Clinical Research, Duke University Medical Center, Durham, North Carolina.

Jay Magaziner (J)

Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore.

James R Bain (JR)

Duke University School of Medicine, Duke Molecular Physiology Institute, Durham, North Carolina.

Michael Muehlbauer (M)

Duke University School of Medicine, Duke Molecular Physiology Institute, Durham, North Carolina.

Olga R Ilkayeva (OR)

Duke University School of Medicine, Duke Molecular Physiology Institute, Durham, North Carolina.

Kim M Huffman (KM)

Center for the Study of Aging and Human Development, Duke University, Durham, North Carolina.
Duke University School of Medicine, Duke Molecular Physiology Institute, Durham, North Carolina.
Division of Rheumatology, Duke University School of Medicine, Durham, North Carolina.

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