Computational whole-body-exposome models for global precision brain health

Agustín Ibáñez; Claudia Duran-Aniotz; Joaquín Migeot; Sandra Báez; Sol Fittipaldi; Carlos Coronel-Oliveros; Harris A. Eyre; Chinedu Udeh-Momoh; Henrik Zetterberg; Suvarna Alladi; Carmen Sandi; Ian H. Robertson; Sanne Franzen; Temitope Farombi; Janitza L. Montalvo Ortiz; Sudha Seshadri; Felipe Court; Pedro Valdes-Sosa; Jiayuan Xu; Chunshui Yu; Lea Grinberg; Brian Lawlor; Perminder S. Sachdev; Kristine Yaffe; Vladimir Hachinski; Karl Friston; Enzo Tagliazucchi; Hernando Santamaría-García

doi:10.1038/s41467-025-67448-3

Computational whole-body-exposome models for global precision brain health

Agustín Ibáñez
, Claudia Duran-Aniotz
, Joaquín Migeot
, Sandra Báez
, Sol Fittipaldi
, Carlos Coronel-Oliveros
, Harris A. Eyre
, Chinedu Udeh-Momoh
, Henrik Zetterberg
, Suvarna Alladi
, Carmen Sandi
, Ian H. Robertson
, Sanne Franzen
, Temitope Farombi
, Janitza L. Montalvo Ortiz
, Sudha Seshadri
, Felipe Court
, Pedro Valdes-Sosa
, Jiayuan Xu
, Chunshui Yu

Lea Grinberg, Brian Lawlor, Perminder S. Sachdev, Kristine Yaffe, Vladimir Hachinski, Karl Friston, Enzo Tagliazucchi, Hernando Santamaría-García

Universidad Adolfo Ibáñez
Trinity College Dublin
Istanbul Medipol University
Pasqual Maragall Foundation
Universidad de San Andrés
Universidad de los Andes Colombia
Rice University
University of California at San Francisco
Euro-Mediterranean Economists Association
Wake Forest University School of Medicine
Aga Khan University
University of Gothenburg
University College London
Hong Kong Center for Neurodegenerative Diseases
University of Wisconsin-Madison
National Institute of Mental Health and Neurosciences
Swiss Federal Institute of Technology Lausanne
University of Texas at Dallas
Erasmus University Rotterdam
University College Hospital, Ibadan
Yale University
University of Texas Health Science Center at San Antonio
Universidad Mayor
Geroscience Center for Brain Health and Metabolism (GERO)
Buck Institute for Age Research
Fundación Ciencia & Vida
University of Electronic Science and Technology of China
Cuban Neuroscience Center
Tianjin Medical University
Universidade de São Paulo
Mayo Clinic Jacksonville, FL
University of New South Wales
Western University
Universidad de Buenos Aires

Research output: Contribution to journal › Review article › peer-review

5 Scopus citations

Abstract

The worldwide rise of neurological and psychiatric conditions poses major challenges. However, current global research remains fragmented, dominated by limited cohorts and poorly integrated datasets that disconnect whole-body health, exposome, and brain health. Theories rarely unify brain measures with extracerebral factors or capture heterogeneity in individual trajectories. We introduce multimodal diversity, a non-linear, non-simplistic causal and ecological construct integrating data representation, whole-body and exposomic factors, and computational modeling to address this situated, embedded, and embodied complexity. This heuristic metamodel integrates global, multilevel data into personalized predictions fostering population inclusion, multimodal integration, diagnostic precision, and equitable, context-sensitive advances in brain health.

Original language	English
Article number	11078
Journal	Nature Communications
Volume	16
Issue number	1
DOIs	https://doi.org/10.1038/s41467-025-67448-3
State	Published - 11 Dec 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Precision Medicine/methods
Models, Biopsychosocial
Mental Disorders/etiology
Humans
Brain/physiology
Nervous System Diseases/etiology
Mental Health
Exposome

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10.1038/s41467-025-67448-3

Cite this

Ibáñez, A., Duran-Aniotz, C., Migeot, J., Báez, S., Fittipaldi, S., Coronel-Oliveros, C., Eyre, H. A., Udeh-Momoh, C., Zetterberg, H., Alladi, S., Sandi, C., Robertson, I. H., Franzen, S., Farombi, T., Montalvo Ortiz, J. L., Seshadri, S., Court, F., Valdes-Sosa, P., Xu, J., ... Santamaría-García, H. (2025). Computational whole-body-exposome models for global precision brain health. Nature Communications, 16(1), Article 11078. https://doi.org/10.1038/s41467-025-67448-3

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title = "Computational whole-body-exposome models for global precision brain health",

abstract = "The worldwide rise of neurological and psychiatric conditions poses major challenges. However, current global research remains fragmented, dominated by limited cohorts and poorly integrated datasets that disconnect whole-body health, exposome, and brain health. Theories rarely unify brain measures with extracerebral factors or capture heterogeneity in individual trajectories. We introduce multimodal diversity, a non-linear, non-simplistic causal and ecological construct integrating data representation, whole-body and exposomic factors, and computational modeling to address this situated, embedded, and embodied complexity. This heuristic metamodel integrates global, multilevel data into personalized predictions fostering population inclusion, multimodal integration, diagnostic precision, and equitable, context-sensitive advances in brain health.",

keywords = "Precision Medicine/methods, Models, Biopsychosocial, Mental Disorders/etiology, Humans, Brain/physiology, Nervous System Diseases/etiology, Mental Health, Exposome",

author = "Agust{\'i}n Ib{\'a}{\~n}ez and Claudia Duran-Aniotz and Joaqu{\'i}n Migeot and Sandra B{\'a}ez and Sol Fittipaldi and Carlos Coronel-Oliveros and Eyre, \{Harris A.\} and Chinedu Udeh-Momoh and Henrik Zetterberg and Suvarna Alladi and Carmen Sandi and Robertson, \{Ian H.\} and Sanne Franzen and Temitope Farombi and \{Montalvo Ortiz\}, \{Janitza L.\} and Sudha Seshadri and Felipe Court and Pedro Valdes-Sosa and Jiayuan Xu and Chunshui Yu and Lea Grinberg and Brian Lawlor and Sachdev, \{Perminder S.\} and Kristine Yaffe and Vladimir Hachinski and Karl Friston and Enzo Tagliazucchi and Hernando Santamar{\'i}a-Garc{\'i}a",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2025.",

year = "2025",

month = dec,

day = "11",

doi = "10.1038/s41467-025-67448-3",

language = "English",

volume = "16",

journal = "Nature Communications",

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Ibáñez, A, Duran-Aniotz, C, Migeot, J, Báez, S, Fittipaldi, S, Coronel-Oliveros, C, Eyre, HA, Udeh-Momoh, C, Zetterberg, H, Alladi, S, Sandi, C, Robertson, IH, Franzen, S, Farombi, T, Montalvo Ortiz, JL, Seshadri, S, Court, F, Valdes-Sosa, P, Xu, J, Yu, C, Grinberg, L, Lawlor, B, Sachdev, PS, Yaffe, K, Hachinski, V, Friston, K, Tagliazucchi, E & Santamaría-García, H 2025, 'Computational whole-body-exposome models for global precision brain health', Nature Communications, vol. 16, no. 1, 11078. https://doi.org/10.1038/s41467-025-67448-3

TY - JOUR

T1 - Computational whole-body-exposome models for global precision brain health

AU - Ibáñez, Agustín

AU - Duran-Aniotz, Claudia

AU - Migeot, Joaquín

AU - Báez, Sandra

AU - Fittipaldi, Sol

AU - Coronel-Oliveros, Carlos

AU - Eyre, Harris A.

AU - Udeh-Momoh, Chinedu

AU - Zetterberg, Henrik

AU - Alladi, Suvarna

AU - Sandi, Carmen

AU - Robertson, Ian H.

AU - Franzen, Sanne

AU - Farombi, Temitope

AU - Montalvo Ortiz, Janitza L.

AU - Seshadri, Sudha

AU - Court, Felipe

AU - Valdes-Sosa, Pedro

AU - Xu, Jiayuan

AU - Yu, Chunshui

AU - Grinberg, Lea

AU - Lawlor, Brian

AU - Sachdev, Perminder S.

AU - Yaffe, Kristine

AU - Hachinski, Vladimir

AU - Friston, Karl

AU - Tagliazucchi, Enzo

AU - Santamaría-García, Hernando

PY - 2025/12/11

Y1 - 2025/12/11

N2 - The worldwide rise of neurological and psychiatric conditions poses major challenges. However, current global research remains fragmented, dominated by limited cohorts and poorly integrated datasets that disconnect whole-body health, exposome, and brain health. Theories rarely unify brain measures with extracerebral factors or capture heterogeneity in individual trajectories. We introduce multimodal diversity, a non-linear, non-simplistic causal and ecological construct integrating data representation, whole-body and exposomic factors, and computational modeling to address this situated, embedded, and embodied complexity. This heuristic metamodel integrates global, multilevel data into personalized predictions fostering population inclusion, multimodal integration, diagnostic precision, and equitable, context-sensitive advances in brain health.

AB - The worldwide rise of neurological and psychiatric conditions poses major challenges. However, current global research remains fragmented, dominated by limited cohorts and poorly integrated datasets that disconnect whole-body health, exposome, and brain health. Theories rarely unify brain measures with extracerebral factors or capture heterogeneity in individual trajectories. We introduce multimodal diversity, a non-linear, non-simplistic causal and ecological construct integrating data representation, whole-body and exposomic factors, and computational modeling to address this situated, embedded, and embodied complexity. This heuristic metamodel integrates global, multilevel data into personalized predictions fostering population inclusion, multimodal integration, diagnostic precision, and equitable, context-sensitive advances in brain health.

KW - Precision Medicine/methods

KW - Models, Biopsychosocial

KW - Mental Disorders/etiology

KW - Humans

KW - Brain/physiology

KW - Nervous System Diseases/etiology

KW - Mental Health

KW - Exposome

UR - https://www.scopus.com/pages/publications/105024809948

UR - https://www.mendeley.com/catalogue/973b71a4-2d7f-39c3-b5f6-58c2e61056c6/

U2 - 10.1038/s41467-025-67448-3

DO - 10.1038/s41467-025-67448-3

M3 - Review article

C2 - 41372244

AN - SCOPUS:105024809948

SN - 2041-1723

VL - 16

JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - 11078

ER -

Computational whole-body-exposome models for global precision brain health

Abstract

UN SDGs

Keywords

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