The effect of weight loss following 18 months of lifestyle intervention on brain age assessed with resting-state functional connectivity
- Ben-Gurion University of the Negev, Israel
- University of Leipzig, Germany
- Soroka Medical Center, Israel
Abstract
Background: Obesity negatively impacts multiple bodily systems, including the central nervous system. Retrospective studies that estimated chronological age from neuroimaging have found accelerated brain aging in obesity, but it is unclear how this estimation would be affected by weight loss following a lifestyle intervention.
Methods: In a sub-study of 102 participants of the DIRECT-PLUS (dietary-intervention-randomized-controlled-trial polyphenol-unprocessed) trial, we tested the effect of weight loss following 18 months of lifestyle intervention on predicted brain age based on MRI-assessed resting-state functional connectivity (RSFC). We further examined how dynamics in multiple health factors, including anthropometric measurements, blood biomarkers, and fat deposition, can account for changes in brain age.
Results: To establish our method, we first demonstrated that our model could successfully predict chronological age from RSFC in three cohorts (n=291;358;102). We then found that among the DIRECT-PLUS participants, 1% of body weight loss resulted in an 8.9 months attenuation of brain age. Attenuation of brain age was significantly associated with improved liver biomarkers, decreased liver fat, and visceral and deep subcutaneous adipose tissues after 18m of intervention. Finally, we showed that lower consumption of processed food, sweets, and beverages were associated with attenuated brain age.
Conclusions: Successful weight loss following lifestyle intervention might have a beneficial effect on the trajectory of brain aging.
Funding: The German Research Foundation (DFG), German Research Foundation - project number 209933838 - SFB 1052; B11), Israel Ministry of Health grant 87472511 (to I Shai); Israel Ministry of Science and Technology grant 3-13604 (to I Shai); and the California Walnuts Commission (to I Shai).
Clinical Trial: This trial was registered at clinicaltrials.gov as NCT03020186.
Data availability
The code for the brain age prediction model and the calculation of brain age attenuation is openly available online at https://github.com/GidLev/functional_brain_aging. The unprocessed data used for the model training and validation is openly available online at http://fcon_1000.projects.nitrc.org/indi/enhanced/neurodata.html for the eNKI dataset and available upon online access request https://camcan-archive.mrc-cbu.cam.ac.uk/dataaccess/ for the CamCAN dataset. Data from the DIRECT-PLUS trial is not publicly available since it contains information that could compromise the privacy of research participants. However, de-identified data could be shared upon request, subject to approval from the Soroka Medical Center Medical Ethics Board. A processed version of the data that includes participants' demographics, predicted and observed age and weight values for T0 and T18 is available as supplementary information.
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The Cambridge Centre for Ageing and NeuroscienceStructural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample.
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The NKI-Rockland sampleWide array of physiological and psychological assessments, genetic information, and advanced neuroimaging.
Article and author information
Author details
Funding
The German Research Foundation (209933838 SFB 1052; B11)
- Iris Shai
Israel Ministry of Health (grant 87472511)
- Iris Shai
Israel Ministry of Science and Technology (3-13604)
- Iris Shai
California Walnuts Commission
- Iris Shai
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: This work was based on a sub-study of the DIREC-PLUS trial (clinicaltrials.gov ID: NCT03020186). The Soroka Medical Center Medical Ethics Board and Institutional Review Board provided ethics approval. All participants provided written consent and received no financial compensation.
Copyright
© 2023, Levakov et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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The effect of weight loss following 18 months of lifestyle intervention on brain age assessed with resting-state functional connectivity
eLife 12:e83604.
https://doi.org/10.7554/eLife.83604
Further reading
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Background:
The role of circulating metabolites on child development is understudied. We investigated associations between children’s serum metabolome and early childhood development (ECD).
Methods:
Untargeted metabolomics was performed on serum samples of 5004 children aged 6–59 months, a subset of participants from the Brazilian National Survey on Child Nutrition (ENANI-2019). ECD was assessed using the Survey of Well-being of Young Children’s milestones questionnaire. The graded response model was used to estimate developmental age. Developmental quotient (DQ) was calculated as the developmental age divided by chronological age. Partial least square regression selected metabolites with a variable importance projection ≥1. The interaction between significant metabolites and the child’s age was tested.
Results:
Twenty-eight top-ranked metabolites were included in linear regression models adjusted for the child’s nutritional status, diet quality, and infant age. Cresol sulfate (β=–0.07; adjusted-p <0.001), hippuric acid (β=–0.06; adjusted-p <0.001), phenylacetylglutamine (β=–0.06; adjusted-p <0.001), and trimethylamine-N-oxide (β=–0.05; adjusted-p=0.002) showed inverse associations with DQ. We observed opposite directions in the association of DQ for creatinine (for children aged –1 SD: β=–0.05; pP=0.01;+1 SD: β=0.05; p=0.02) and methylhistidine (–1 SD: β = - 0.04; p=0.04;+1 SD: β=0.04; p=0.03).
Conclusions:
Serum biomarkers, including dietary and microbial-derived metabolites involved in the gut-brain axis, may potentially be used to track children at risk for developmental delays.
Funding:
Supported by the Brazilian Ministry of Health and the Brazilian National Research Council.
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- Epidemiology and Global Health
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