Comorbidity Networks: Mapping and Interpreting Interactions Across Organ Systems

Comorbid diseases rarely arise in isolation. Rather, they emerge from interacting organ systems, shared physiological pathways, and common environmental, behavioral, and genetic risk factors, giving rise to complex and structured patterns of disease co-occurrence. Understanding these structured patterns of interactions from the sub-cellular constituents to the organism level is essential to uncover the processes through which disease comorbidity emerges.

This Research Topic invites contributions that conceptualize comorbidity as a systems-level phenomenon, leveraging interdisciplinary data science approaches to uncover the complex pattern of disease–disease and systems-disease relationships.

We particularly welcome studies that apply concepts and tools from network physiology, network science, and computational modeling to link comorbidity networks with interactions among cardiovascular, metabolic, immune, neural, and other organ systems. Contributions may draw on clinical, electronic health record, population-level, or longitudinal data, and may integrate physiological signals, biomarkers, imaging, or multi-omics information.

Topics of interest include, but are not limited to:
• Construction, analysis, and interpretation of comorbidity networks across populations, life stages, or disease domains.
• Novel methods for inferring, validating, or characterizing disease–disease interactions.
• Integration of physiological dynamics, molecular data, or environmental exposures with comorbidity patterns.
• Multiscale models connecting organ-system interactions to clinical multimorbidity.
• Translation of network-based insights into improved risk stratification, prognosis, prevention, or management of multimorbidity.

Studies with clear implications for clinical decision-making, personalized medicine, or health system planning are welcomed. Methodological contributions introducing new statistical, machine learning, or network-based frameworks are especially encouraged. Rigorous studies reporting null or unexpected findings that challenge existing assumptions about comorbidity structure are also welcome.

By bringing together perspectives from medicine, biology, physics, statistics, and data science, this Research Topic aims to advance a unified, quantitative understanding of comorbidity and its implications for health and disease.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: Network Physiology, Comorbidity, Multimorbidity, Complex Networks, Network Medicine, Electronic Health Records, Medical Claims Data, Disease Trajectory, Digital Medicine

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.