A Cell Metamodel Uncovers Mechanistic Drivers of Disease Phenotypes Across Molecular, Cellular, and Tissue Scales

Understanding how molecular and cellular dynamics regulate tissue function remains a central challenge in biology. Here, we develop a graph-based metamodeling framework for modeling of complex biological systems and apply it to construct a comprehensive metamodel of the $\beta$ -cell. The metamodel integrates 115 input models that describe various aspects of $\beta$ -cell physiology across molecular, cellular, and multicellular spatial scales, spanning ten orders of magnitude in timescales. Validated against a broad range of experimental data, including fluorescence imaging, the metamodel uncovers how the interplay between gap junction coupling and $K^{+}$ channel-mediated signaling regulates islet function. Moreover, the metamodel identifies and characterizes two types of hub cells, each deterministically driving islet activity and synchronization via unique ion channel properties. Perturbing channel conductance and hub cell activity recapitulates distinct diabetic phenotypes, highlighting them as mechanistic drivers of diabetes and potential therapeutic targets. Our metamodeling framework is broadly applicable to modeling other complex biological systems.