Automated Phenotyping of Patients with Non-Alcoholic Fatty Liver Disease Reveals Clinically Relevant Disease Subtypes

Details

• Personal Author:
  Branch A ; Dudley JT ; Jun T ; Li L ; Perumalswami P ; Vandromme M
• Description:
  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. [Description provided by NIOSH]
• Subjects:
  Cohort Studies Digestive System Digestive System Diseases Liver Occupational Health Risk Assessment Risk Factors Safety
• Keywords:
  Author Keywords: Clustering Cohort Studies Liver Disease Liver Disorders Liver Function NAFLD Risk Factors Statistical Analysis Subtypes Definition Survival Analysis Survival Rate

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• ISBN:
  9789811215629
• ISSN:
  2335-6928
• Publisher:
  World Scientific Publishing Co.
• Document Type:
  Text
• Funding:
  Cooperative Agreement
• Genre:
  Journal Article
• Place as Subject:
  Connecticut ; Hawaii ; New York ; OSHA Region 1 ; OSHA Region 2 ; OSHA Region 9
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  91-102
• Volume:
  25
• NIOSHTIC Number:
  nn:20059192
• Citation:
  Pac Symp Biocomput 2020 Jan; 25:91-102
• Contact Point Address:
  Andrea Branch, Division of Liver Diseases, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
• Email:
  li.li@mssm.edu
• Editor(s):
  Altman RB; Dunker AK; Hunter L; Ritchie MD; Murray T; Klein TE
• Federal Fiscal Year:
  2020
• Performing Organization:
  Icahn School of Medicine at Mount Sinai, New York
• Peer Reviewed:
  True
• Start Date:
  20170701
• Source Full Name:
  Pacific Symposium on Biocomputing 2020, January 3-7, 2020, Kohala Coast, Hawai
• End Date:
  20210630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:8c2b820b0d26209baca570a7e31f364fafaf504b083fa977969e93329fb74acab7693269f821dea9c5178e7169cb70d9bdcf31cc224f2666473a190d4c2582d5
• Download URL:
  https://stacks.cdc.gov/view/cdc/223486/cdc_223486_DS1.pdf
• File Type:
  [PDF - 2.20 MB ]