TY - JOUR
T1 - An epidemiological human disease network derived from disease Co-occurrence in Taiwan
AU - Jiang, Yefei
AU - Ma, Shuangge
AU - Shia, Ben Chang
AU - Lee, Tian Shyug
N1 - Funding Information:
We thank the reviewers for their careful review and insightful comments, which have led to a significant improvement of the article. We would like to acknowledge Mingchih Chen and Ariana Chang for their support, and thoughtful comments on the manuscript. This research was supported by Fu Jen Catholic University of Taiwan under the Grant No. 300394 and the Ministry of Science and Technology under Grant Nos MOST106-2221-E030-011-MY2, MOST106-2221-E030-012 and MOST106-3011-F038-004.
Publisher Copyright:
© 2018 The Author(s).
PY - 2018/12/1
Y1 - 2018/12/1
N2 - In "classic" biomedical research, diseases have usually been studied individually. The pioneering human disease network (HDN) studies jointly consider a large number of diseases, analyse their interconnections, and provide a more comprehensive description of diseases. However, most of the existing HDN studies are based on molecular information and can only partially describe disease interconnections. Building on the unique Taiwan National Health Insurance Research Database (NHIRD), in this study, we construct the epidemiological HDN (eHDN), where two diseases are concluded as interconnected if their observed probability of co-occurrence deviating that expected under independence. Advancing from the existing HDN, the eHDN can also accommodate non-molecular connections and have more important practical implications. Building on the network construction, we examine important network properties such as connectivity, module, hub, and others and describe their temporal patterns. This study is among the first to systematically construct the eHDN and can have important implications for human disease research and health care and management.
AB - In "classic" biomedical research, diseases have usually been studied individually. The pioneering human disease network (HDN) studies jointly consider a large number of diseases, analyse their interconnections, and provide a more comprehensive description of diseases. However, most of the existing HDN studies are based on molecular information and can only partially describe disease interconnections. Building on the unique Taiwan National Health Insurance Research Database (NHIRD), in this study, we construct the epidemiological HDN (eHDN), where two diseases are concluded as interconnected if their observed probability of co-occurrence deviating that expected under independence. Advancing from the existing HDN, the eHDN can also accommodate non-molecular connections and have more important practical implications. Building on the network construction, we examine important network properties such as connectivity, module, hub, and others and describe their temporal patterns. This study is among the first to systematically construct the eHDN and can have important implications for human disease research and health care and management.
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U2 - 10.1038/s41598-018-21779-y
DO - 10.1038/s41598-018-21779-y
M3 - Article
AN - SCOPUS:85044237030
SN - 2045-2322
VL - 8
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 4557
ER -