Version 1
: Received: 14 January 2022 / Approved: 17 January 2022 / Online: 17 January 2022 (13:01:03 CET)
How to cite:
Polster, A. Rethinking Complex Diseases: A High-Dimensional Representation of Individual Disease Burden and Global Disease Landscape. Preprints2022, 2022010228. https://doi.org/10.20944/preprints202201.0228.v1
Polster, A. Rethinking Complex Diseases: A High-Dimensional Representation of Individual Disease Burden and Global Disease Landscape. Preprints 2022, 2022010228. https://doi.org/10.20944/preprints202201.0228.v1
Polster, A. Rethinking Complex Diseases: A High-Dimensional Representation of Individual Disease Burden and Global Disease Landscape. Preprints2022, 2022010228. https://doi.org/10.20944/preprints202201.0228.v1
APA Style
Polster, A. (2022). Rethinking Complex Diseases: A High-Dimensional Representation of Individual Disease Burden and Global Disease Landscape. Preprints. https://doi.org/10.20944/preprints202201.0228.v1
Chicago/Turabian Style
Polster, A. 2022 "Rethinking Complex Diseases: A High-Dimensional Representation of Individual Disease Burden and Global Disease Landscape" Preprints. https://doi.org/10.20944/preprints202201.0228.v1
Abstract
Complex diseases are prevalent medical conditions which are characterized by strong inter-patient differences in symptom profiles, disease trajectory and treatment response. The challenges in understanding and managing these diseases are due to their complex pathophysiology, comprising of a combination of genetic and environmental factors. The traditional model of disease assumes a clear distinction between health and disease, as well as between different diagnoses, but recent findings with regards to diseasomes and network pleiotrophy suggest that this dogma is not useful in understanding complex diseases. This paper presents a novel model, in which the individual disease burden is determined as a function of molecular, physiological and pathological factors simultaneously: disease(symptoms(traits(genes AND environment))). From this a high-dimensional space is defined which includes all individual disease burdens, ranging from healthy (i.e. low disease burden) to multi-morbidity (i.e. high disease burden), termed the disease landscape. This model provides a novel way to conceptualize human physiology and pathophysiology in the context of complex diseases and may present a useful concept to simultaneously address the strong interindividual heterogeneity of diagnose cohorts as well as the lack of clear distinction between diagnoses and health and disease, thus facilitating the progression towards personalized medicine.
Keywords
Complex diseases; Nosology; Systems Medicine
Subject
Medicine and Pharmacology, Medicine and Pharmacology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
