The Aging Imageomics Study: rationale, design and baseline characteristics of the study population

Josep Puig, Carles Biarnes, Salvador Pedraza, Joan C. Vilanova, Reinald Pamplona, José Manuel Fernández-Real, Ramon Brugada, Rafel Ramos, Gabriel Coll-de-Tuero, Laia Calvo-Perxas, Joaquin Serena, Lluís Ramió-Torrentà, Jordi Gich, Lluis Gallart, Manel Portero-Otin, Angel Alberich-Bayarri, Ana Jimenez-Pastor, Eduardo Camacho-Ramos, Jordi Mayneris-Perxachs, Victor PinedaRaquel Font, Anna Prats-Puig, Mariano Luis Gacto, Gustavo Deco, Anira Escrichs, Bonaventura Clotet, Roger Paredes, Eugenia Negredo, Bruno Triaire, Manuel Rodríguez, Alberto Heredia-Escámez, Rafael Coronado, Wolter de Graaf, Valentin Prevost, Anca Mitulescu, Pepus Daunis-i-Estadella, Santiago Thió-Henestrosa, Felip Miralles, Vicent Ribas-Ripoll, Manel Puig-Domingo, Marco Essig, Chase R. Figley, Teresa D. Figley, Benedict Albensi, Ahmed Ashraf, Johan H.C. Reiber, Giovanni Schifitto, Uddin Md Nasir, Carlos Leiva-Salinas, Max Wintermark, Kambiz Nael, Joan Vilalta-Franch, Jordi Barretina, Josep Garre-Olmo

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


Biomarkers of aging are urgently needed to identify individuals at high risk of developing age-associated disease or disability. Growing evidence from population-based studies points to whole-body magnetic resonance imaging's (MRI) enormous potential for quantifying subclinical disease burden and for assessing changes that occur with aging in all organ systems. The Aging Imageomics Study aims to identify biomarkers of human aging by analyzing imaging, biopsychosocial, cardiovascular, metabolomic, lipidomic, and microbiome variables. This study recruited 1030 participants aged ≥50 years (mean 67, range 50–96 years) that underwent structural and functional MRI to evaluate the brain, large blood vessels, heart, abdominal organs, fat, spine, musculoskeletal system and ultrasonography to assess carotid intima-media thickness and plaques. Patients were notified of incidental findings detected by a certified radiologist when necessary. Extensive data were also collected on anthropometrics, demographics, health history, neuropsychology, employment, income, family status, exposure to air pollution and cardiovascular status. In addition, several types of samples were gathered to allow for microbiome, metabolomic and lipidomic profiling. Using big data techniques to analyze all the data points from biological phenotyping together with health records and lifestyle measures, we aim to cultivate a deeper understanding about various biological factors (and combinations thereof) that underlie healthy and unhealthy aging.

Original languageEnglish (US)
Article number111257
JournalMechanisms of Ageing and Development
StatePublished - Jul 2020


  • aging
  • big data analyses
  • biomarkers
  • population-based study
  • radiomics
  • whole-body magnetic resonance imaging

ASJC Scopus subject areas

  • Aging
  • Developmental Biology


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