Accurate neuroimaging biomarkers to predict body mass index in adolescents: a longitudinal study
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ORIGINAL RESEARCH
Accurate neuroimaging biomarkers to predict body mass index in adolescents: a longitudinal study Bo-yong Park 1,2 & Chin-Sang Chung 3 & Mi Ji Lee 3 & Hyunjin Park 2,4
# Springer Science+Business Media, LLC, part of Springer Nature 2019
Abstract Obesity is often associated with cardiovascular complications. Adolescent obesity is a risk factor for cardiovascular disease in adulthood; thus, intensive management is warranted in adolescence. The brain state contributes to the development of obesity in addition to metabolic conditions, and hence neuroimaging is an important tool for accurately assessing an individual’s risk of developing obesity. Here, we aimed to predict body mass index (BMI) progression in adolescents with neuroimaging features using machine learning approaches. From an open database, we adopted 76 resting-state functional magnetic resonance imaging (rs-fMRI) datasets from adolescents with longitudinal BMI scores. Functional connectivity analyses were performed on cortical surfaces and subcortical volumes. We identified baseline functional connectivity features in the prefrontal-, posterior cingulate-, sensorimotor-, and inferior parietal-cortices as significant determinants of BMI changes. A BMI prediction model based on the identified fMRI biomarkers exhibited a high accuracy (intra-class correlation = 0.98) in predicting BMI at the second visit (1~2 years later). The identified brain regions were significantly correlated with the eating disorder-, anxiety-, and depressionrelated scores. Based on these results, we concluded that these functional connectivity features in brain regions related to eating disorders and emotional processing could be important neuroimaging biomarkers for predicting BMI progression. Keywords BMI prediction . Neuroimaging biomarkers . Resting-state functional MRI . Connectivity analysis . Cortical surface
Introduction Obesity is a serious medical condition highly associated with serious cardiovascular morbidity and mortality (Luppino et al.
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11682-019-00101-y) contains supplementary material, which is available to authorized users. * Mi Ji Lee [email protected] * Hyunjin Park [email protected] 1
Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, South Korea
2
Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon 16419, South Korea
3
Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, South Korea
4
School of Electronic and Electrical Engineering, Sungkyunkwan University, Suwon 16419, South Korea
2010; Malik et al. 2013). Obesity in adolescence is especially important, as obesity at a young age usually persists into adulthood (Guo et al. 2002; Laitinen et al. 2001). Studies have shown that childhood and adolescent obesity is a risk factor for the development of cardiovascular disease in adulthood, which might lead to cardiovascular mort
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