Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/87978
Title: Health and disease phenotyping in old age using a cluster network analysis
Authors: Valenzuela, Jesus Felix
Monterola, Christopher
Tong, Victor Joo Chuan
Ng, Tze Pin
Larbi, Anis
Keywords: Disease
DRNTU::Science::Biological sciences
Network Analysis
Issue Date: 2017
Source: Valenzuela, J. F., Monterola, C., Tong, V. J. C., Ng, T. P., & Larbi, A. (2017). Health and disease phenotyping in old age using a cluster network analysis. Scientific Reports, 7(1), 15608-.
Series/Report no.: Scientific Reports
Abstract: Human ageing is a complex trait that involves the synergistic action of numerous biological processes that interact to form a complex network. Here we performed a network analysis to examine the interrelationships between physiological and psychological functions, disease, disability, quality of life, lifestyle and behavioural risk factors for ageing in a cohort of 3,270 subjects aged ≥55 years. We considered associations between numerical and categorical descriptors using effect-size measures for each variable pair and identified clusters of variables from the resulting pairwise effect-size network and minimum spanning tree. We show, by way of a correspondence analysis between the two sets of clusters, that they correspond to coarse-grained and fine-grained structure of the network relationships. The clusters obtained from the minimum spanning tree mapped to various conceptual domains and corresponded to physiological and syndromic states. Hierarchical ordering of these clusters identified six common themes based on interactions with physiological systems and common underlying substrates of age-associated morbidity and disease chronicity, functional disability, and quality of life. These findings provide a starting point for indepth analyses of ageing that incorporate immunologic, metabolomic and proteomic biomarkers, and ultimately offer low-level-based typologies of healthy and unhealthy ageing.
URI: https://hdl.handle.net/10356/87978
http://hdl.handle.net/10220/45584
ISSN: 2045-2322
DOI: 10.1038/s41598-017-15753-3
Rights: © 2017 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SBS Journal Articles

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