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Neves TMG, Simoes E, Otaduy MCG, Calfat ELDB, Bertolazzi P, da Costa NA, Duran FLDS, Correia-Lima J, Martin MDGM, Seelander MCL, Otani VHO, Otani TZDS, Vasques DAC, Filho GB, Kochi C, Uchida RR. Inverse Association Between Hypothalamic N-Acetyl Aspartate/Creatine Ratio and Indices of Body Mass in Adolescents with Obesity. J Nutr 2021; 152:663-670. [PMID: 34888674 PMCID: PMC8891176 DOI: 10.1093/jn/nxab415] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 10/06/2021] [Accepted: 12/03/2021] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Approximately 10% of adolescents worldwide are overweight or obese, hence the urgent and universal need to elucidate possible mechanisms that lead to obesity in the adolescent population. OBJECTIVES We examined the hypothalamic metabolism and its relationship with physical development in obese and eutrophic adolescents. METHODS We performed a case-control study with 115 adolescents between 11 and 18 years of age, to compare obese (BMI z-score ≥ 2) and nonobese individuals (eutrophic controls; BMI z-score ≤ 1). The following hypothalamic metabolite ratios were examined as primary outcomes: glutamate/creatine (Cr), the sum of glutamate and glutamine/Cr, N-acetylaspartate (NAA)/Cr, myoinositol/Cr, and total choline/Cr (glycerophosphocholine + phosphocholine/Cr), quantified by magnetic resonance spectroscopy. BMI z-scores, pubertal status, and scores on the Yale Food Addiction Scale, the Binge Eating Scale, and the Child Depression Inventory were assessed as secondary outcomes. Pearson coefficients (r) or nonparametric Spearman correlation (rho) analyses were performed between hypothalamic metabolite ratios and other parameters, such as BMI z-scores, physical development, food habits, depression symptoms, and serum protein concentrations (cytokines, hormones, and neuropeptides). RESULTS Adolescents with obesity showed a lower hypothalamic NAA/Cr ratio (0.70 ± 0.19) compared to their eutrophic counterparts (0.84 ± 0.20; P = 0.004). The NAA/Cr ratio was negatively correlated with BMI z-scores (r = -0.25; P = 0.03) and serum insulin (rho = -0.27; P = 0.04), C-peptide (rho = -0.26; P = 0.04), amylin (r = -0.27; P = 0.04), ghrelin (rho = -0.30; P = 0.02), and neuropeptide Y (r = -0.27; P = 0.04). Also, the NAA/Cr ratio was positively correlated with circulating IL-8 levels (rho = 0.26; P = 0.04). CONCLUSIONS High BMI z-scores are associated with lower hypothalamic NAA/Cr ratios. The negative correlations found between the NAA/Cr ratio and serum cytokines, hormones, and neuropeptides suggest a broad cross-talk linking hormonal imbalances, neurohumoral alterations, and hypothalamic functions in adolescents with obesity.
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Affiliation(s)
| | | | | | | | - Pâmela Bertolazzi
- Mental Health Department, Santa Casa de Sao Paulo School of Medical Sciences, São Paulo, Brazil
| | - Naomi Antunes da Costa
- Neuroimaging Laboratory (LIM-21), Institute Psychiatry, University of São Paulo, São Paulo, Brazil
| | | | - Joanna Correia-Lima
- Cancer Metabolism Research Group, University of São Paulo, São Paulo, Brazil
| | | | - Marília Cerqueira Leite Seelander
- Cancer Metabolism Research Group, University of São Paulo, São Paulo, Brazil,Department of Surgery and LIM 26, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | | | | | | | - Geraldo Busatto Filho
- Neuroimaging Laboratory (LIM-21), Institute Psychiatry, University of São Paulo, São Paulo, Brazil
| | - Cristiane Kochi
- Pediatrics Department, Santa Casa de Sao Paulo School of Medical Sciences, São Paulo, Brazil
| | - Ricardo Riyoiti Uchida
- Mental Health Department, Santa Casa de Sao Paulo School of Medical Sciences, São Paulo, Brazil
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Magnetic Resonance Spectroscopy as a Non-invasive Method to Quantify Muscle Carnosine in Humans: a Comprehensive Validity Assessment. Sci Rep 2020; 10:4908. [PMID: 32184463 PMCID: PMC7078313 DOI: 10.1038/s41598-020-61587-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 02/28/2020] [Indexed: 11/08/2022] Open
Abstract
Carnosine is a dipeptide abundantly found in human skeletal muscle, cardiac muscle and neuronal cells having numerous properties that confers performance enhancing effects, as well as a wide-range of potential therapeutic applications. A reliable and valid method for tissue carnosine quantification is crucial for advancing the knowledge on biological processes involved with carnosine metabolism. In this regard, proton magnetic resonance spectroscopy (1H-MRS) has been used as a non-invasive alternative to quantify carnosine in human skeletal muscle. However, carnosine quantification by 1H-MRS has some potential limitations that warrant a thorough experimental examination of its validity. The present investigation examined the reliability, accuracy and sensitivity for the determination of muscle carnosine in humans using in vitro and in vivo experiments and comparing it to reference method for carnosine quantification (high-performance liquid chromatography - HPLC). We used in vitro 1H-MRS to verify signal linearity and possible noise sources. Carnosine was determined in the m. gastrocnemius by 1H-MRS and HPLC to compare signal quality and convergent validity. 1H-MRS showed adequate discriminant validity, but limited reliability and poor agreement with a reference method. Low signal amplitude, low signal-to-noise ratio, and voxel repositioning are major sources of error.
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Yang Y, Qian J, Mei J, Zhong K, Niu C. In vivo detection of metabolic changes in the striatum of proteasomal inhibition-induced Parkinson’s disease in rats using proton MR spectroscopy at 9.4 T. Int J Neurosci 2019; 130:153-160. [PMID: 31516042 DOI: 10.1080/00207454.2019.1667783] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Affiliation(s)
- Yanyan Yang
- Department of Neurosurgery, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, Anhui, P.R. China
| | - Junchao Qian
- High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, P.R. China
- Hefei Cancer Hospital, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, P.R.China
| | - Jiaming Mei
- Department of Neurosurgery, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, Anhui, P.R. China
| | - Kai Zhong
- High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, P.R. China
| | - Chaoshi Niu
- Department of Neurosurgery, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, Anhui, P.R. China
- Anhui Provincial Key Laboratory of Brain Function and Brain Disease, Hefei, Anhui, P.R. China
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Gazdzinski SP, Gaździńska AP, Orzeł J, Redlisz-Redlicki G, Pietruszka M, Mojkowska A, Pacho RA, Wylezol M. Intragastric balloon therapy leads to normalization of brain magnetic resonance spectroscopic markers of diabetes in morbidly obese patients. NMR IN BIOMEDICINE 2018; 31:e3957. [PMID: 30011110 DOI: 10.1002/nbm.3957] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Revised: 05/11/2018] [Accepted: 05/16/2018] [Indexed: 06/08/2023]
Abstract
Elevated brain myo-inositol (m-Ins) concentration (a putative marker of neuroinflammation) has been reported in patients suffering from type 2 diabetes mellitus (T2DM). Obesity alone and T2DM have been found to be associated with a lower concentration of N-acetyloaspartate and N-acetylaspartylglutamate (tNAA, a marker of neuronal integrity, reflecting neuronal loss or metabolic derangement). It is not clear if these changes reverse with weight loss. The intra-gastric balloon (IGB) is an endoscopic bariatric therapy that leads to massive weight loss and improvement of glycemic control. In this study we evaluated if tNAA/tCr and m-Ins/tCr metabolite ratios are affected by weight loss, where tCr is the signal of creatine containing compounds. Twenty-three morbidly obese patients, 12 of them with T2DM (OD) and 11 without T2DM (OB), as well as 11 healthy controls of normal weight (CON), underwent single voxel spectroscopy at 3 T. Spectra were obtained within a region in the left parietal white matter one month before IGB insertion, three months after IGB insertion, and one month after IGB removal. Before IGB insertion, m-Ins/tCr was 15% higher in OD than in OB (p = 0.005) and 12% higher in OD than in CON (p = 0.03). m-Ins/tCr decreased significantly by 8% over the first three months after IGB insertion (p = 0.01) and remained normal after IGB removal. tNAA/tCr was normal in all groups throughout the study, pointing to normal brain metabolism. Normalization of m-Ins/tCr is consistent with remission of neuroinflammation in patients with T2DM. An evaluation of long-term effects of IGB treatment is necessary.
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Affiliation(s)
| | - Agata P Gaździńska
- Department of Nutrition and Obesity, Military Institute of Aviation Medicine, Warsaw, Poland
| | - Jarosław Orzeł
- Department of Radioelectronics, Warsaw University of Technology, Warsaw, Poland
| | | | - Maciej Pietruszka
- Department of Surgery, Military Institute of Aviation Medicine, Warsaw, Poland
| | | | - Ryszard A Pacho
- Department of Radiology, Military Institute of Aviation Medicine, Warsaw, Poland
| | - Mariusz Wylezol
- Department of Surgery, Military Institute of Aviation Medicine, Warsaw, Poland
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Zhu H, Wang N, Yao L, Chen Q, Zhang R, Qian J, Hou Y, Guo W, Fan S, Liu S, Zhao Q, Du F, Zuo X, Guo Y, Xu Y, Li J, Xue T, Zhong K, Song X, Huang G, Xiong W. Moderate UV Exposure Enhances Learning and Memory by Promoting a Novel Glutamate Biosynthetic Pathway in the Brain. Cell 2018; 173:1716-1727.e17. [PMID: 29779945 DOI: 10.1016/j.cell.2018.04.014] [Citation(s) in RCA: 96] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2017] [Revised: 02/21/2018] [Accepted: 04/12/2018] [Indexed: 02/07/2023]
Abstract
Sunlight exposure is known to affect mood, learning, and cognition. However, the molecular and cellular mechanisms remain elusive. Here, we show that moderate UV exposure elevated blood urocanic acid (UCA), which then crossed the blood-brain barrier. Single-cell mass spectrometry and isotopic labeling revealed a novel intra-neuronal metabolic pathway converting UCA to glutamate (GLU) after UV exposure. This UV-triggered GLU synthesis promoted its packaging into synaptic vesicles and its release at glutamatergic terminals in the motor cortex and hippocampus. Related behaviors, like rotarod learning and object recognition memory, were enhanced after UV exposure. All UV-induced metabolic, electrophysiological, and behavioral effects could be reproduced by the intravenous injection of UCA and diminished by the application of inhibitor or short hairpin RNA (shRNA) against urocanase, an enzyme critical for the conversion of UCA to GLU. These findings reveal a new GLU biosynthetic pathway, which could contribute to some of the sunlight-induced neurobehavioral changes.
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Affiliation(s)
- Hongying Zhu
- Hefei National Laboratory for Physical Sciences at the Microscale, Neurodegenerative Disorder Research Center, School of Life Sciences, University of Science and Technology of China, 230026 Hefei, China; Hefei National Laboratory for Physical Sciences at the Microscale, School of Chemistry and Materials Science, University of Science and Technology of China, 230026 Hefei, China
| | - Ning Wang
- Hefei National Laboratory for Physical Sciences at the Microscale, Neurodegenerative Disorder Research Center, School of Life Sciences, University of Science and Technology of China, 230026 Hefei, China
| | - Lei Yao
- Hefei National Laboratory for Physical Sciences at the Microscale, Neurodegenerative Disorder Research Center, School of Life Sciences, University of Science and Technology of China, 230026 Hefei, China
| | - Qi Chen
- Hefei National Laboratory for Physical Sciences at the Microscale, Neurodegenerative Disorder Research Center, School of Life Sciences, University of Science and Technology of China, 230026 Hefei, China
| | - Ran Zhang
- Hefei National Laboratory for Physical Sciences at the Microscale, Neurodegenerative Disorder Research Center, School of Life Sciences, University of Science and Technology of China, 230026 Hefei, China
| | - Junchao Qian
- High Magnetic Field Laboratory, Chinese Academy of Sciences, 230031 Hefei, China
| | - Yiwen Hou
- Hefei National Laboratory for Physical Sciences at the Microscale, Neurodegenerative Disorder Research Center, School of Life Sciences, University of Science and Technology of China, 230026 Hefei, China
| | - Weiwei Guo
- Hefei National Laboratory for Physical Sciences at the Microscale, Neurodegenerative Disorder Research Center, School of Life Sciences, University of Science and Technology of China, 230026 Hefei, China
| | - Sijia Fan
- Hefei National Laboratory for Physical Sciences at the Microscale, Neurodegenerative Disorder Research Center, School of Life Sciences, University of Science and Technology of China, 230026 Hefei, China
| | - Siling Liu
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, 650223 Kunming, China
| | - Qiaoyun Zhao
- Hefei National Laboratory for Physical Sciences at the Microscale, Neurodegenerative Disorder Research Center, School of Life Sciences, University of Science and Technology of China, 230026 Hefei, China
| | - Feng Du
- Hefei National Laboratory for Physical Sciences at the Microscale, Neurodegenerative Disorder Research Center, School of Life Sciences, University of Science and Technology of China, 230026 Hefei, China
| | - Xin Zuo
- Hefei National Laboratory for Physical Sciences at the Microscale, Neurodegenerative Disorder Research Center, School of Life Sciences, University of Science and Technology of China, 230026 Hefei, China
| | - Yujun Guo
- Hefei National Laboratory for Physical Sciences at the Microscale, Neurodegenerative Disorder Research Center, School of Life Sciences, University of Science and Technology of China, 230026 Hefei, China
| | - Yan Xu
- Hefei National Laboratory for Physical Sciences at the Microscale, Neurodegenerative Disorder Research Center, School of Life Sciences, University of Science and Technology of China, 230026 Hefei, China
| | - Jiali Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, 650223 Kunming, China
| | - Tian Xue
- Hefei National Laboratory for Physical Sciences at the Microscale, Neurodegenerative Disorder Research Center, School of Life Sciences, University of Science and Technology of China, 230026 Hefei, China; Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, 200031 Shanghai, China
| | - Kai Zhong
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, 200031 Shanghai, China; High Magnetic Field Laboratory, Chinese Academy of Sciences, 230031 Hefei, China
| | - Xiaoyuan Song
- Hefei National Laboratory for Physical Sciences at the Microscale, Neurodegenerative Disorder Research Center, School of Life Sciences, University of Science and Technology of China, 230026 Hefei, China
| | - Guangming Huang
- Hefei National Laboratory for Physical Sciences at the Microscale, School of Chemistry and Materials Science, University of Science and Technology of China, 230026 Hefei, China.
| | - Wei Xiong
- Hefei National Laboratory for Physical Sciences at the Microscale, Neurodegenerative Disorder Research Center, School of Life Sciences, University of Science and Technology of China, 230026 Hefei, China; Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, 200031 Shanghai, China.
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6
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Birdsill AC, Oleson S, Kaur S, Pasha E, Ireton A, Tanaka H, Haley A. Abdominal obesity and white matter microstructure in midlife. Hum Brain Mapp 2017; 38:3337-3344. [PMID: 28390146 DOI: 10.1002/hbm.23576] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2016] [Revised: 03/08/2017] [Accepted: 03/09/2017] [Indexed: 12/12/2022] Open
Abstract
The aging U.S. population and the recent rise in the prevalence of obesity are two phenomena of great importance to public health. In addition, research suggests that midlife body mass index (BMI) is a risk factor for dementia, a particularly costly disease, in later life. BMI could influence brain health by adversely impacting cerebral white matter. Recently, greater BMI has been associated with lower white matter fractional anisotropy (FA), an index of tissue microstructure, as measured by diffusion-tensor imaging in midlife. The aim of this study was to investigate the role of abdominal obesity, the most metabolically active adipose tissue compartment, and white matter microstructure in midlife. Community dwelling participants (N = 168) between the ages of 40-62 underwent MRI scanning at 3T and a general health assessment. Inferences were made on whole brain white matter tracts using full-tensor, high-dimension normalization, and tract-based spatial statistics. Higher waist circumference was associated with higher FA, indicating more directional diffusion in several white matter tracts controlling for age, sex, triglycerides, systolic blood pressure, fasting glucose, and HDL-cholesterol. Post hoc analysis revealed that greater waist circumference was associated with lower axial diffusivity, indicating lower parallel diffusion; lower radial diffusivity, indicating lower perpendicular diffusion; and lower mean diffusivity, indicating restricted diffusion. This is the first study to report a positive relationship between obesity and FA, indicating a more complicated view of this relationship in the aging brain. Hum Brain Mapp 38:3337-3344, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Alex Cole Birdsill
- Department of Psychology, The University of Texas at Austin, Austin, Texas
| | - Stephanie Oleson
- Department of Psychology, The University of Texas at Austin, Austin, Texas
| | - Sonya Kaur
- Department of Psychology, The University of Texas at Austin, Austin, Texas
| | - Evan Pasha
- Department of Kinesiology & Health Education, The University of Texas at Austin, Austin, Texas
| | - Adele Ireton
- Department of Psychology, The University of Texas at Austin, Austin, Texas
| | - Hirofumi Tanaka
- Department of Kinesiology & Health Education, The University of Texas at Austin, Austin, Texas
| | - Andreana Haley
- Department of Psychology, The University of Texas at Austin, Austin, Texas
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Kyathanahally SP, Fichtner ND, Adalid V, Kreis R. Does superficial fat affect metabolite concentrations determined by MR spectroscopy with water referencing? NMR IN BIOMEDICINE 2015; 28:1543-1549. [PMID: 26423456 DOI: 10.1002/nbm.3419] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2015] [Revised: 08/26/2015] [Accepted: 08/29/2015] [Indexed: 06/05/2023]
Abstract
It has recently been reported in this journal that local fat depots produce a sizable frequency-dependent signal attenuation in magnetic resonance spectroscopy (MRS) of the brain. If of a general nature, this effect would question the use of internal reference signals for quantification of MRS and the quantitative use of MRS as a whole. Here, it was attempted to verify this effect and pinpoint the potential causes by acquiring data with various acquisition settings, including two field strengths, two MR scanners from different vendors, different water suppression sequences, RF coils, localization sequences, echo times, and lipid/metabolite phantoms. With all settings tested, the reported effect could not be reproduced, and it is concluded that water referencing and quantitative MRS per se remain valid tools under common acquisition conditions.
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Affiliation(s)
- S P Kyathanahally
- Department of Clinical Research and Institute of Diagnostic, Interventional and Pediatric Radiology, University of Bern, Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
| | - N D Fichtner
- Department of Clinical Research and Institute of Diagnostic, Interventional and Pediatric Radiology, University of Bern, Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - V Adalid
- Department of Clinical Research and Institute of Diagnostic, Interventional and Pediatric Radiology, University of Bern, Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
| | - R Kreis
- Department of Clinical Research and Institute of Diagnostic, Interventional and Pediatric Radiology, University of Bern, Bern, Switzerland
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Fat may affect magnetic resonance signal intensity and brain tissue volumes. Obes Res Clin Pract 2015; 10:211-5. [PMID: 26259685 DOI: 10.1016/j.orcp.2015.07.009] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2015] [Revised: 05/28/2015] [Accepted: 07/18/2015] [Indexed: 11/20/2022]
Abstract
Obesity/overweight is reported to affect MR-measured brain tissue volume and white matter (WM) signal intensity. This study investigated possible effects of fat on these measures, using pig fat on three participants at a 4T magnet. Grey matter volumes in the presence of fat were lower than baseline measures. Total WM volumes in the presence of fat were higher than baseline measures. WM hypo-intensities on T1-weighted images were higher in the presence of fat than baseline measures. Therefore physical effects of head fat of obese/overweight individual may at least, partly contribute to the association of obesity/overweight with MR structural measures.
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