Mapping Immune Aging: Metabolic Regulation, Systems Immunology, and AI-Driven Discovery

The field of immune aging investigates the complex and multifaceted changes to immune system function across the lifespan, with mounting interest in how metabolic and environmental factors modulate these processes. Rather than a predictable decline, immune aging displays remarkable heterogeneity, as individual genetic backgrounds, exposures, and metabolic states dynamically shape immune cell behavior, tissue environments, and, ultimately, disease risk. Recent research reveals the centrality of metabolism—conditions such as obesity, insulin resistance, and chronic nutrient surfeit modulate immune cell energetics, inflammatory responses, and have cascading effects on health and longevity. However, despite rapid technological advances, the mechanisms by which metabolic pathways influence immune system resilience or dysfunction, and the reasons behind variable aging trajectories, remain incompletely understood. The emergence of single-cell multi-omics, longitudinal population studies, and computational systems immunology, alongside artificial intelligence (AI), has revolutionized our ability to map immune dynamics, but open questions persist about translating knowledge into actionable interventions. This Research Topic aims to promote a systems-level understanding of immune aging by integrating metabolic regulation, systems immunology, and advanced computational and AI driven methodologies. The principal objective is to clarify the molecular and cellular underpinnings that connect metabolic states with the remodeling of the immune system, identifying pathways influencing susceptibility or resilience to age-associated diseases. Central questions include how different metabolic stresses modify immune aging, how immune landscapes adapt or malfunction with time, and which molecular markers best predict healthy versus maladaptive trajectories. The integration of experimental, clinical, and predictive analytic approaches is encouraged to generate comprehensive maps of immune aging and to accelerate discovery of therapeutic and preventive strategies. This Research Topic focuses on studies that delineate the connections between metabolism, immune system adaptation throughout life, and disease risk, using an interdisciplinary approach. Scope is limited to work that combines experimental, clinical, and data-driven strategies to map immune cell and system-level changes, particularly those leveraging novel technologies or computational tools. To gather further insights in this dynamic and evolving area, we welcome articles addressing, but not limited to, the following themes: • Metabolic regulation of immune cell function during aging • Novel immune-metabolism and immune-aging therapeutic targets • Immunometabolism in states of metabolic stress, such as obesity and metabolic syndrome • Longitudinal profiling of immune system trajectories in health and disease • Determinants of immune resilience versus susceptibility to chronic disease • Systems and computational immunology analyses integrating genomics, multi-omics, and clinical phenotyping • Artificial intelligence and machine learning strategies for modeling immune aging, predicting outcomes, and identifying new biomarkers • Application of single-cell, spatial, and multimodal profiling to track immune system dynamics We encourage submissions of original research articles, reviews, and perspectives that use integrative and predictive frameworks to better understand immune aging and its interaction with metabolic factors.Topic Editor Emanuele de Rinaldis is employed by Sanofi S.A. and declares ownership of shares in the company Topic editors: Emanuele De Rinaldis, Timothy Radstake, Jennifer Chia Source: https://www.frontiersin.org/research-topics/82981/mapping-immune-aging-metabolic-regulation-systems-immunology-and-ai-driven-discovery