Combined Inflammation and Metabolism Biomarker Indices of Robust and Impaired Physical Function in Older Adults.

Abstract

To determine whether combinations of inflammatory markers are related to physical function.secondary analysis of baseline of three observational studies of community-dwelling older adults MEASUREMENTS: The baseline data from 3 cohorts of older adults with different health and disease status were employed. Twenty markers of inflammation and metabolism were individually assessed for correlation with usual gait speed and were separated into robust and impairment quartiles. For the robustness and impairment indices, individual markers were selected using step-wise regression over bootstrapping iterations, and regression coefficients were estimated for the markers individually and collectively as an additive score.We developed a robustness index involving 6 markers and an impairment index involving 8 markers corresponding positively and negatively with gait speed. Two markers, glycine and tumor necrosis factor receptor 1 (TNFR1), appeared only in the robustness index, and TNFR2; regulated on activation, normal T-cell expressed and secreted; the amino acid factor; and matrix metallopeptidase 3; appeared only in the impairment index.Indices of biomarkers were associated with robust and impaired physical performance but differ, in composition suggesting potential biological differences that may contribute to robustness and impairment.

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Citation

Published Version (Please cite this version)

10.1111/jgs.15393

Publication Info

Zuo, Xintong, Alison Luciano, Carl F Pieper, James R Bain, Virginia B Kraus, William E Kraus, Miriam C Morey, Harvey J Cohen, et al. (2018). Combined Inflammation and Metabolism Biomarker Indices of Robust and Impaired Physical Function in Older Adults. Journal of the American Geriatrics Society. 10.1111/jgs.15393 Retrieved from https://hdl.handle.net/10161/17282.

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Scholars@Duke

Pieper

Carl F. Pieper

Professor of Biostatistics & Bioinformatics

Analytic Interests.

1) Issues in the Design of Medical Experiments: I explore the use of reliability/generalizability models in experimental design. In addition to incorporation of reliability, I study powering longitudinal trials with multiple outcomes and substantial missing data using Mixed models.

2) Issues in the Analysis of Repeated Measures Designs & Longitudinal Data: Use of Hierarchical Linear Models (HLM) or Mixed Models in modeling trajectories of multiple variables over time (e.g., physical and cognitive functioning and Blood Pressure). My current work involves methodologies in simultaneous estimation of trajectories for multiple variables within and between domains, modeling co-occuring change.

Areas of Substantive interest: (1) Experimental design and analysis in gerontology and geriatrics, and psychiatry,
(2) Multivariate repeated measures designs,


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