Population-based research in obesity – An overview of neuroimaging studies using big data approach. (April 2022)

• Record Type: Journal Article
• Authors: Morys, Filip; Shishikura, Mari; Dagher, Alain
• Is Part Of: Current opinion in endocrine and metabolic research. Volume 23(2022)
• Publication Date: 2022-04
• Subjects: Obesity -- Big data -- Population-based research -- White matter -- Grey matter -- Resting-state fMRI; Endocrine glands -- Diseases -- Periodicals; Metabolism -- Disorders -- Periodicals; Endocrine System Diseases; Metabolic Diseases; Endocrine glands -- Diseases; Metabolism -- Disorders; Periodical; Electronic journals; Periodicals; Electronic journals; 616.4
• DOI: 10.1016/j.coemr.2022.100323
• Languages: English
• ISSNs: 2451-9650

Abstract

Abstract: In this review, we present research on neuroanatomical correlates of obesity using big data. This approach utilizes large sample sizes from population-based cohorts and is especially important for brain imaging research given the current replication crisis. Recent studies show that large sample sizes are needed to detect replicable associations between brain phenotypes and behavioral or anthropometric features, but previous brain imaging research on excess weight was often performed on samples including fewer than 100 participants. While smaller studies are crucial to investigate mechanistically fine-grained and more novel research questions, big data can be a tool to test some of the results generated by this research. Here, we present studies on adiposity-related brain changes, but also discuss genetic and environmental factors related to the excess weight development. We provide a summary of grey and white matter changes in obesity and conclude with recommendations for future studies investigating neurocognitive profiles of obesity.