Modeling the enigma of complex disease etiology

Journal of Translational Medicine

Research

Cynthia Bearer¹  Richard Lichenstein²  Carol Greene²  Katharine Bisordi²  J. Allen Baron³  Lynn M. Schriml³ 

[1] Case Western Reserve University, Cleveland, OH, USA;University of Maryland School of Medicine, Baltimore, MD, USA;University of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA;

关键词: Disease etiology;    Diabetes;    Asthma;    Fetal alcohol syndrome;    Pathophysiology;    Environmental drivers;    Genetics;   

DOI  :  10.1186/s12967-023-03987-x

 received in 2022-09-12, accepted in 2023-02-14,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundComplex diseases often present as a diagnosis riddle, further complicated by the combination of multiple phenotypes and diseases as features of other diseases. With the aim of enhancing the determination of key etiological factors, we developed and tested a complex disease model that encompasses diverse factors that in combination result in complex diseases. This model was developed to address the challenges of classifying complex diseases given the evolving nature of understanding of disease and interaction and contributions of genetic, environmental, and social factors.MethodsHere we present a new approach for modeling complex diseases that integrates the multiple contributing genetic, epigenetic, environmental, host and social pathogenic effects causing disease. The model was developed to provide a guide for capturing diverse mechanisms of complex diseases. Assessment of disease drivers for asthma, diabetes and fetal alcohol syndrome tested the model.ResultsWe provide a detailed rationale for a model representing the classification of complex disease using three test conditions of asthma, diabetes and fetal alcohol syndrome. Model assessment resulted in the reassessment of the three complex disease classifications and identified driving factors, thus improving the model. The model is robust and flexible to capture new information as the understanding of complex disease improves.ConclusionsThe Human Disease Ontology’s Complex Disease model offers a mechanism for defining more accurate disease classification as a tool for more precise clinical diagnosis. This broader representation of complex disease, therefore, has implications for clinicians and researchers who are tasked with creating evidence-based and consensus-based recommendations and for public health tracking of complex disease. The new model facilitates the comparison of etiological factors between complex, common and rare diseases and is available at the Human Disease Ontology website.

【 授权许可】

CC BY   
© The Author(s) 2023

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