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18 Jun | 2024

Irene Cumplido successfully defends the sixth doctoral thesis developed at the BBRC

Irene Cumplido, researcher in the Neuroimaging Research Group of the Barcelonaβeta Brain Research Center (BBRC), has defended her doctoral thesis, entitled “Biological brain-age prediction using Machine Learning on neuroimaging data: Links with pathophysiological mechanisms, dementia risk factors and “cognitive decline.”

The work, directed by Dr. Juan Domingo Gispert, has focused on the development and validation of a biomarker of brain aging based on neuroimaging techniques using a predictive artificial intelligence model. This new marker, called brain-age delta, has made possible to demonstrate that the presence of pathological alterations of Alzheimer's disease is associated with accelerated brain aging. Although the two phenomena had already been related, the thesis has for the first time compared these data with specific biological markers of the disease and risk factors linked to aging. In this sense, the estimate of accelerated brain aging has been associated with abnormal beta-amyloid deposits and the presence of the APOE-e4 genotype, among others. The research thus opens the door to the use of this marker in the development of lifestyle interventions to prevent cognitive decline.

Irene Cumplido joined the BBRC in 2020 and has developed her research activity in the study of healthy and pathological aging related to Alzheimer's, and its impact on cognition, through the combination of artificial intelligence and neuroimaging techniques.

We have spoken with her to find out about her thesis and her projects.

What are the main conclusions of your thesis?

In this thesis we demonstrate that we can develop a neuroimaging-based biomarker for the biological age of the brain (so-called brain-age), which is robust and generalizable between participants from different cohorts. Furthermore, we found that having an older-looking brain is associated with greater neuronal loss as measured by plasma neurofilament light (NfL), more advanced stages of amyloid and tau pathology, and carrying the APOE-ε4 allele, as well as older white matter hyperintensities. On the other hand, brain-age could show sex differences in brain aging. Finally, we show that brain-age captures the association between modifiable risk factors and longitudinal cognitive decline. Our findings also showed that greater TREM2-mediated microglial reactivity, measured with sTREM2 in cerebrospinal fluid (CSF), was associated with younger brain age.

What doors do these findings open for us in Alzheimer's disease research?

This thesis helps us understand the mechanisms underlying biological aging of the brain, cognitive decline and its relationship with Alzheimer's disease and with different brain physiological processes such as neurodegeneration, glia activation, and cerebrovascular diseases. This highlights the potential of brain-age for preventive interventions targeting cognitive decline and provides insight into mechanisms related to aging and Alzheimer's disease.

How do you face your new stage as a postdoctoral researcher? What lines of research would you like to delve into from now on?

From now on, I would like to go deeper into characterizing the heterogeneity of processes related to aging and neurodegenerative diseases. These types of studies can help us understand the biological mechanisms involved in these diseases, opening doors to the development of new treatments and possible prevention interventions.