Integrative Endocrinology in Focus: Multi-Scale Insights from Integrated Diagnostics and Biomarker Discovery in Endocrinology and Biomedical Sciences: Volume II

Kinam Park¹Mikyung Jin¹Yong-Min Kwon²Yena Park¹Soon-Yong Kwon³Youngmi Ji⁴Sajung Yun¹Sijung Yun^5,6*

• ¹Predictive AI Inc, Seongnam, Republic of Korea
• ²Youido St. Mary's Hospital, Seoul, Republic of Korea
• ³Seoul Bethesda Hospital, Seoul, Republic of Korea
• ⁴National Institute of Dental and Craniofacial Research, Bethesda, United States
• ⁵Predictiv Care, Inc., Mountain View, United States
• ⁶Johns Hopkins University, Baltimore, United States

*Correspondence: Sijung Yun, syun16@jhu.edu; Youngmi Ji, charmgene@gmail.comThe integration of multi-omics biological data, such as genomics, transcriptomics, proteomics, etc., is reshaping how we conceptualize and pursue biomarker discovery in endocrinology. Moving beyond reductionist paradigms, contemporary research now unites molecular, cellular, physiological, and population-level information to illuminate the complex regulatory architecture underlying endocrine health and disease. Integrated Diagnostics and Biomarker Discovery in Endocrinology and Biomedical Sciences: Volume II brings together nine original contributions that exemplify this transition toward a systems-oriented and data-driven discipline.Spanning the spectrum from ionic ratios and proteomic signaling to transcriptomic networks, genomic variation, and ecological microbiome interactions, these studies demonstrate how diagnostic precision emerges through the convergence of molecular and systemic perspectives. Collectively, they trace a coherent trajectoryfrom basal biochemistry and molecular communication to clinical integration and population-scale modeling -illustrating how multi-scale data synthesis from ionic ratios to networks can refine both mechanistic understanding and translational application.Taken together, this collection reflects the growing maturity of integrative endocrinology, a field where multi-omics analytics, causal inference, and real-world data harmonization converge to enable predictive and personalized approaches to endocrine disorders. By highlighting these multi-scale insights, Volume II underscores the central message of modern biomarker science: meaningful diagnostic innovation arises not from any single data layer, but from their integration into a unified systems framework that connects molecules to medicine. Lou et al. (2025) systematically validated the Glucose-Potassium Ratio (GPR) -a longrecognized broad clinical predictive marker 1 -as a prognostic biomarker for both shortand long-term all-cause mortality. They showed a strong association with mortality in both hospital and ICU settings. Mortality risk escalated sharply when GPR exceeded this threshold. Sensitivity analyses confirmed the robustness of these findings, positioning GPR as a valuable, non-invasive indicator for early identification and risk stratification of high-risk sepsis patients. This study opens the collection by illustrating that integrated diagnostics can arise not only from macromolecular data but from fundamental ionic interactions reflecting systemic metabolic homeostasis. Together, these nine contributions delineate a rapidly expanding frontier in integrated diagnostics, spanning the full continuum of biological organization-from ionic ratios and proteomic signatures to genomic databases and microbiome-derived ecological biomarkers. Collectively, they illustrate how endocrine science is evolving from isolated molecular characterization toward a fully systems-based discipline, in which the integration of multi-omics, clinical, and environmental data enhances both mechanistic insight and translational precision. This convergence reflects the maturation of data-informed endocrinology, where diagnostic and prognostic innovation emerges from the synthesis of diverse data modalities rather than from any single layer of observation. By harmonizing biochemical, genetic, immunologic, and ecological perspectives, these studies redefine biomarker discovery as a process of multi-scale inference and integration -one that connects molecular precision with population-level relevance and real-world applicability. In this new framework, integration is not merely a methodological approach but a scientific imperative -transforming endocrinology into a discipline that systematically bridges molecules to medicine, and data to diagnosis.