Agustín Ibáñez, PhD | Interoceptive links of whole-body health and the exposome in brain health

Zoom Link: https://gwdg.zoom.us/j/82855697786?pwd=iABbntJ0GU4m6FLOGfq2iedOuDwfth.1

Meeting ID: 828 5569 7786

Passcode: 470724

Despite unprecedented advances in omics, neuroimaging, and data science, brain health

research remains deeply fragmented, limiting our capacity to predict, prevent, or modify

trajectories of brain aging and disease. In this keynote, I introduce the Brain Health

Synercome as a forward-looking scientific horizon rather than a finalized framework. The

Synercome calls for moving beyond isolated data layers toward synergistic modeling that

integrates genetic, molecular, neural, bodily, environmental, social, and cultural dimensions

of brain health. My research brings together whole-body health and interoception, exposomic factors, and

computational modeling to understand accelerated aging and dementia across global settings.

I examine how physical, social, and sociopolitical exposures interact with neurodegeneration,

cardiovascular integrity, and allostatic interoception to shape brain vulnerability and

resilience. To quantify these cross-level interactions, multimodal aging clocks spanning

neuroimaging, epigenetics, electrophysiology, language, behavior, and exposomic profiles,

can be combined with biophysical models of excitatory–inhibitory balance and neurovascular

dynamics. Across international cohorts (particularly in underrepresented populations) this

work demonstrates that exposomic adversity and systemic health exert measurable and

substantial effects on accelerated brain aging and dementia risk. I argue that the central

challenge we face is not data scarcity, but disconnection between omics and phenotypes,

between exposomes and lived experience, and between biological mechanisms and social

context. I will discuss how generative models, federated data infrastructures, and hybrid

theory-driven and data-driven approaches can help capture cross-level dependencies,

feedback loops, and emergent dynamics. The Synercome functions as a heuristic metamodel

designed to integrate multilevel global data into personalized predictions, fostering

population inclusion, multimodal integration, diagnostic precision, and equitable, context-

sensitive innovation.