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ORIGINAL RESEARCH article
Front. Neurosci.
Sec. Neuroendocrine Science
Volume 19 - 2025 | doi: 10.3389/fnins.2025.1547010
Relations between neurometabolism and clinical biomarkers in patients with metabolic disease
Provisionally accepted- Sun Yat-sen Memorial Hospital, Guangzhou, China
The global prevalence of metabolic diseases, including hypertension, type 2 diabetes mellitus (T2DM), gout, and obesity, has significantly increased over the past two decades. The brain plays a central role in regulating both human behavior and metabolism. Understanding the potential connections among these metabolic diseases and the involvement of the brain in their progression presents an intriguing and critical area of research.In this study, we analyzed PET-CT images and clinical biomarkers from 112 cases of hypertension, 56 cases of T2DM, 11 cases of obesity, and 14 cases of gout. Standardized uptake value ratios (SUVRs) were extracted from various brain regions using the Spatial-Normalization-of-Brain-PET-Images (SNBPI) software. The SUVRs were calculated using the standard methodology, where the mean standardized uptake value (SUV) of each region of interest (ROI) was divided by the mean SUV of the reference region, that is the whole cerebellum. The SNBPI tool was employed for intensity normalization. Partial correlation analysis was conducted to examine the relationships between SUVRs in different brain regions and clinical biomarkers, adjusting for sex, age, and BMI. Brain network metabolic connectivity was assessed using Permutation_IHEP software and visualized with BrainNet Viewer.Our results indicate that SUVRs in most brain regions were decreased in patients with hypertension or T2DM but increased in patients with obesity or gout. Specifically, SUVRs in brain regions associated with blood pressure were correlated with blood uric acid, creatinine, potassium, and apolipoprotein B. SUVRs in brain regions related to blood glucose were associated with blood triglycerides and cholinesterase. SUVRs in BMI-related brain regions correlated with blood urea nitrogen, aspartate aminotransferase, and alkaline phosphatase. SUVRs in brain regions associated with gout were correlated with fasting blood glucose, glutamic oxalacetic transaminase, total bilirubin, and alkaline phosphatase. Furthermore, brain network metabolic connectivity was reduced in patients with hypertension, T2DM, or obesity but increased in patients with gout. In conclusion, our study highlights potential relationships among metabolic diseases and suggests the possible regulatory roles of specific brain regions in the progression of these conditions. These insights could pave the way for novel therapeutic strategies targeting brain metabolism in the management of metabolic diseases.
Keywords: PET-CT, Hypertension, T2DM, Obesity, Gout, clinical biomarkers
Received: 17 Dec 2024; Accepted: 31 Mar 2025.
Copyright: © 2025 Lee, Chen, Tan, Yin and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Ying Lee, Sun Yat-sen Memorial Hospital, Guangzhou, China
Jian-Ming Li, Sun Yat-sen Memorial Hospital, Guangzhou, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.