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Utility of Continuous Disease Subtyping Systems for Improved Evaluation of Etiologic Heterogeneity.

Authors :
Li, Ruitong
Ugai, Tomotaka
Xu, Lantian
Zucker, David
Ogino, Shuji
Wang, Molin
Source :
Cancers; Apr2022, Vol. 14 Issue 7, p1811, 10p
Publication Year :
2022

Abstract

Simple Summary: This paper presents an extended version of the Cox regression model to examine heterogeneous effects of risk factors on disease subtypes defined by a continuous biomarker. This approach can be easily applied to cancer studies and is accessible to researchers via user-friendly R scripts. Molecular pathologic diagnosis is important in clinical (oncology) practice. Integration of molecular pathology into epidemiological methods (i.e., molecular pathological epidemiology) allows for investigating the distinct etiology of disease subtypes based on biomarker analyses, thereby contributing to precision medicine and prevention. However, existing approaches for investigating etiological heterogeneity deal with categorical subtypes. We aimed to fully leverage continuous measures available in most biomarker readouts (gene/protein expression levels, signaling pathway activation, immune cell counts, microbiome/microbial abundance in tumor microenvironment, etc.). We present a cause-specific Cox proportional hazards regression model for evaluating how the exposure–disease subtype association changes across continuous subtyping biomarker levels. Utilizing two longitudinal observational prospective cohort studies, we investigated how the association of alcohol intake (a risk factor) with colorectal cancer incidence differed across the continuous values of tumor epigenetic DNA methylation at long interspersed nucleotide element-1 (LINE-1). The heterogeneous alcohol effect was modeled using different functions of the LINE-1 marker to demonstrate the method's flexibility. This real-world proof-of-principle computational application demonstrates how the new method enables visualizing the trend of the exposure effect over continuous marker levels. The utilization of continuous biomarker data without categorization for investigating etiological heterogeneity can advance our understanding of biological and pathogenic mechanisms. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20726694
Volume :
14
Issue :
7
Database :
Complementary Index
Journal :
Cancers
Publication Type :
Academic Journal
Accession number :
156276607
Full Text :
https://doi.org/10.3390/cancers14071811