TY - JOUR
T1 - Automated phenotyping of patients with non-Alcoholic fatty liver disease reveals clinically relevant disease subtypes
AU - Vandromme, Maxence
AU - Jun, Tomi
AU - Perumalswami, Ponni
AU - Dudley, Joel T.
AU - Branch, Andrea
AU - Li, Li
N1 - Publisher Copyright:
© 2019 The Authors.
PY - 2020
Y1 - 2020
N2 - Non-Alcoholic fatty liver disease (NAFLD) is a complex heterogeneous disease which affects more than 20% of the population worldwide. Some subtypes of NAFLD have been clinically identified using hypothesis-driven methods. In this study, we used data mining techniques to search for subtypes in an unbiased fashion. Using electronic signatures of the disease, we identified a cohort of 13,290 patients with NAFLD from a hospital database. We gathered clinical data from multiple sources and applied unsupervised clustering to identify five subtypes among this cohort. Descriptive statistics and survival analysis showed that the subtypes were clinically distinct and were associated with different rates of death, cirrhosis, hepatocellular carcinoma, chronic kidney disease, cardiovascular disease, and myocardial infarction. Novel disease subtypes identified in this manner could be used to risk-stratify patients and guide management.
AB - Non-Alcoholic fatty liver disease (NAFLD) is a complex heterogeneous disease which affects more than 20% of the population worldwide. Some subtypes of NAFLD have been clinically identified using hypothesis-driven methods. In this study, we used data mining techniques to search for subtypes in an unbiased fashion. Using electronic signatures of the disease, we identified a cohort of 13,290 patients with NAFLD from a hospital database. We gathered clinical data from multiple sources and applied unsupervised clustering to identify five subtypes among this cohort. Descriptive statistics and survival analysis showed that the subtypes were clinically distinct and were associated with different rates of death, cirrhosis, hepatocellular carcinoma, chronic kidney disease, cardiovascular disease, and myocardial infarction. Novel disease subtypes identified in this manner could be used to risk-stratify patients and guide management.
KW - Clustering
KW - NAFLD
KW - Subtypes definition
KW - Survival analysis
UR - http://www.scopus.com/inward/record.url?scp=85076007716&partnerID=8YFLogxK
M3 - Conference article
C2 - 31797589
AN - SCOPUS:85076007716
SN - 2335-6936
VL - 25
SP - 91
EP - 102
JO - Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
JF - Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
IS - 2020
T2 - 25th Pacific Symposium on Biocomputing, PSB 2020
Y2 - 3 January 2020 through 7 January 2020
ER -