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Review Article
Adrenal Gland
Recent Updates on the Management of Adrenal Incidentalomas
Seung Shin Park, Jung Hee Kim
Endocrinol Metab. 2023;38(4):373-380.   Published online August 16, 2023
DOI: https://doi.org/10.3803/EnM.2023.1779
  • 7,230 View
  • 1,447 Download
AbstractAbstract PDFPubReader   ePub   
Adrenal incidentalomas represent an increasingly common clinical conundrum with significant implications for patients. The revised 2023 European Society of Endocrinology (ESE) guideline incorporates cutting-edge evidence for managing adrenal incidentalomas. This paper provides a concise review of the updated contents of the revised guideline. In the 2023 guideline, in patients without signs and symptoms of overt Cushing’s syndrome, a post-dexamethasone cortisol level above 50 nmol/L (>1.8 μg/dL) should be considered as mild autonomous cortisol secretion. Regarding the criteria of benign adrenal adenomas, a homogeneous adrenal mass with ≤10 Hounsfield units on non-contrast computed tomography requires no further follow-up, irrespective of its size. The updated guideline also discusses steroid metabolomics using tandem mass spectrometry to discriminate malignancy. It underscores the importance of high-volume surgeons performing adrenalectomy and emphasizes the pivotal role of a multidisciplinary team approach in deciding the treatment plan for indeterminate adrenal masses. The guideline advocates for more proactive surgical treatment for indeterminate adrenal masses in young patients (<40 years) and pregnant women. This review of the 2023 ESE guideline underscores the ongoing evolution of the adrenal incidentaloma management landscape, emphasizing the need for further research and adaptation of diagnostic and therapeutic strategies.
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Original Article
Thyroid
Metabolite Changes during the Transition from Hyperthyroidism to Euthyroidism in Patients with Graves’ Disease
Ho Yeop Lee, Byeong Chang Sim, Ha Thi Nga, Ji Sun Moon, Jingwen Tian, Nguyen Thi Linh, Sang Hyeon Ju, Dong Wook Choi, Daiki Setoyama, Hyon-Seung Yi
Endocrinol Metab. 2022;37(6):891-900.   Published online December 26, 2022
DOI: https://doi.org/10.3803/EnM.2022.1590
  • 2,498 View
  • 255 Download
  • 1 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
An excess of thyroid hormones in Graves’ disease (GD) has profound effects on systemic energy metabolism that are currently partially understood. In this study, we aimed to provide a comprehensive understanding of the metabolite changes that occur when patients with GD transition from hyperthyroidism to euthyroidism with methimazole treatment.
Methods
Eighteen patients (mean age, 38.6±14.7 years; 66.7% female) with newly diagnosed or relapsed GD attending the endocrinology outpatient clinics in a single institution were recruited between January 2019 and July 2020. All subjects were treated with methimazole to achieve euthyroidism. We explored metabolomics by performing liquid chromatography-mass spectrometry analysis of plasma samples of these patients and then performed multivariate statistical analysis of the metabolomics data.
Results
Two hundred metabolites were measured before and after 12 weeks of methimazole treatment in patients with GD. The levels of 61 metabolites, including palmitic acid (C16:0) and oleic acid (C18:1), were elevated in methimazole-naïve patients with GD, and these levels were decreased by methimazole treatment. The levels of another 15 metabolites, including glycine and creatinine, were increased after recovery of euthyroidism upon methimazole treatment in patients with GD. Pathway analysis of metabolomics data showed that hyperthyroidism was closely related to aminoacyl-transfer ribonucleic acid biosynthesis and branched-chain amino acid biosynthesis pathways.
Conclusion
In this study, significant variations of plasma metabolomic patterns that occur during the transition from hyperthyroidism to euthyroidism were detected in patients with GD via untargeted metabolomics analysis.

Citations

Citations to this article as recorded by  
  • Associations of serum keratin 1 with thyroid function and immunity in Graves’ disease
    Chao-Wen Cheng, Wen-Fang Fang, Jiunn-Diann Lin, Appuwawadu Mestri Nipun Lakshitha de Silva
    PLOS ONE.2023; 18(11): e0289345.     CrossRef
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Review Article
Obesity and Metabolism
Understanding Metabolomics in Biomedical Research
Su Jung Kim, Su Hee Kim, Ji Hyun Kim, Shin Hwang, Hyun Ju Yoo
Endocrinol Metab. 2016;31(1):7-16.   Published online March 16, 2016
DOI: https://doi.org/10.3803/EnM.2016.31.1.7
  • 6,940 View
  • 127 Download
  • 45 Web of Science
  • 42 Crossref
AbstractAbstract PDFPubReader   

The term "omics" refers to any type of specific study that provides collective information on a biological system. Representative omics includes genomics, proteomics, and metabolomics, and new omics is constantly being added, such as lipidomics or glycomics. Each omics technique is crucial to the understanding of various biological systems and complements the information provided by the other approaches. The main strengths of metabolomics are that metabolites are closely related to the phenotypes of living organisms and provide information on biochemical activities by reflecting the substrates and products of cellular metabolism. The transcriptome does not always correlate with the proteome, and the translated proteome might not be functionally active. Therefore, their changes do not always result in phenotypic alterations. Unlike the genome or proteome, the metabolome is often called the molecular phenotype of living organisms and is easily translated into biological conditions and disease states. Here, we review the general strategies of mass spectrometry-based metabolomics. Targeted metabolome or lipidome analysis is discussed, as well as nontargeted approaches, with a brief explanation of the advantages and disadvantages of each platform. Biomedical applications that use mass spectrometry-based metabolomics are briefly introduced.

Citations

Citations to this article as recorded by  
  • Urine metabolomic biomarkers for prediction of isolated fetal congenital heart defect
    Perry Friedman, Ali Yilmaz, Zafer Ugur, Faryal Jafar, Amy Whitten, Ilyas Ustun, Onur Turkoglu, Stewart Graham, Ray Bahado Singh
    The Journal of Maternal-Fetal & Neonatal Medicine.2024; 35(25): 6380.     CrossRef
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    Environmental Research.2023; 216: 114570.     CrossRef
  • UPLC-Q-Exactive-based rats serum metabolomics for characterization of traditional Chinese medicine Natures and Flavors
    Hong Wang, Ruofang Gao, Jing Liu, Shuang Zhang, Yunli Zhao, Zhiguo Yu
    Journal of Ethnopharmacology.2023; 302: 115931.     CrossRef
  • Artificial Neural Networks Coupled with MALDI-TOF MS Serum Fingerprinting To Classify and Diagnose Pathological Pain Subtypes in Preclinical Models
    Meritxell Deulofeu, Eladia M. Peña-Méndez, Petr Vaňhara, Josef Havel, Lukáš Moráň, Lukáš Pečinka, Anna Bagó-Mas, Enrique Verdú, Victoria Salvadó, Pere Boadas-Vaello
    ACS Chemical Neuroscience.2023; 14(2): 300.     CrossRef
  • Metabolic signature of HepaRG cells exposed to ethanol and tumor necrosis factor alpha to study alcoholic steatohepatitis by LC–MS-based untargeted metabolomics
    Elias Iturrospe, Rani Robeyns, Katyeny Manuela da Silva, Maria van de Lavoir, Joost Boeckmans, Tamara Vanhaecke, Alexander L. N. van Nuijs, Adrian Covaci
    Archives of Toxicology.2023; 97(5): 1335.     CrossRef
  • Integrating metabolomics and network pharmacology to assess the effects of quercetin on lung inflammatory injury induced by human respiratory syncytial virus
    Ya-Lei Sun, Pei-Pei Zhao, Cheng-Bi Zhu, Ming-Chen Jiang, Xin-Min Li, Jia-Lei Tao, Chan-Chan Hu, Bin Yuan
    Scientific Reports.2023;[Epub]     CrossRef
  • Comparison of Plasma Metabolites From Patients With Non-Small Cell Lung Cancer by Erlotinib Treatment and Skin Rash
    Won Kil Lee, Jisoo Myong, Eunbin Kwag, Younmin Shin, Ji Woong Son, Byong Chul Yoo, Byoung-Soo Kim, Hwa-Seung Yoo, Jeong June Choi
    Integrative Cancer Therapies.2023;[Epub]     CrossRef
  • Metabolomic Signatures of Exposure to Nitrate and Trihalomethanes in Drinking Water and Colorectal Cancer Risk in a Spanish Multicentric Study (MCC-Spain)
    Jose A. Alcolea, Carolina Donat-Vargas, Anastasia Chrysovalantou Chatziioannou, Pekka Keski-Rahkonen, Nivonirina Robinot, Antonio José Molina, Pilar Amiano, Inés Gómez-Acebo, Gemma Castaño-Vinyals, Lea Maitre, Marc Chadeau-Hyam, Sonia Dagnino, Sibo Lucas
    Environmental Science & Technology.2023; 57(48): 19316.     CrossRef
  • Metabolic Signature of Ethanol-Induced Hepatotoxicity in HepaRG Cells by Liquid Chromatography–Mass Spectrometry-Based Untargeted Metabolomics
    Elias Iturrospe, Katyeny Manuela da Silva, Rani Robeyns, Maria van de Lavoir, Joost Boeckmans, Tamara Vanhaecke, Alexander L.N. van Nuijs, Adrian Covaci
    Journal of Proteome Research.2022; 21(4): 1153.     CrossRef
  • Current State and Challenges of the Global Outcomes of Dental Caries Research in the Meta-Omics Era
    Dina G. Moussa, Paras Ahmad, Tamer A. Mansour, Walter L. Siqueira
    Frontiers in Cellular and Infection Microbiology.2022;[Epub]     CrossRef
  • Current Knowledge in Skin Metabolomics: Updates from Literature Review
    Alessia Paganelli, Valeria Righi, Elisabetta Tarentini, Cristina Magnoni
    International Journal of Molecular Sciences.2022; 23(15): 8776.     CrossRef
  • Metabolome-wide association study of the relationship between chlorpyrifos exposure and first trimester serum metabolite levels in pregnant Thai farmworkers
    Donghai Liang, Jonathan Batross, Nancy Fiedler, Tippawan Prapamontol, Panrapee Suttiwan, Parinya Panuwet, Warangkana Naksen, Brittney O. Baumert, Volha Yakimavets, Youran Tan, Priya D'Souza, Ampica Mangklabruks, Supattra Sittiwang, Kristsanachai Kaewthit,
    Environmental Research.2022; 215: 114319.     CrossRef
  • Differential Plasma Metabolites between High- and Low-Grade Meningioma Cases
    Gabriel A. Kurokawa, Pedro T. Hamamoto Filho, Jeany Delafiori, Aline F. Galvani, Arthur N. de Oliveira, Flávia L. Dias-Audibert, Rodrigo R. Catharino, Maria Inês M. C. Pardini, Marco A. Zanini, Estela de O. Lima, Adriana C. Ferrasi
    International Journal of Molecular Sciences.2022; 24(1): 394.     CrossRef
  • Plasma metabolites associated with exposure to perfluoroalkyl substances and risk of type 2 diabetes – A nested case-control study
    Tessa Schillemans, Lin Shi, Carolina Donat-Vargas, Kati Hanhineva, Andreas Tornevi, Ingegerd Johansson, Jani Koponen, Hannu Kiviranta, Olov Rolandsson, Ingvar A. Bergdahl, Rikard Landberg, Agneta Åkesson, Carl Brunius
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  • Methionine transsulfuration pathway is upregulated in long-lived humans
    Natàlia Mota-Martorell, Mariona Jové, Consuelo Borrás, Rebeca Berdún, Èlia Obis, Joaquim Sol, Rosanna Cabré, Irene Pradas, José Daniel Galo-Licona, Josep Puig, José Viña, Reinald Pamplona
    Free Radical Biology and Medicine.2021; 162: 38.     CrossRef
  • Investigating metabolism by mass spectrometry: From steady state to dynamic view
    Matteo Audano, Silvia Pedretti, Simona Ligorio, Flavio Giavarini, Donatella Caruso, Nico Mitro
    Journal of Mass Spectrometry.2021;[Epub]     CrossRef
  • The Efficacy of Pilates on Urinary Incontinence in Korean Women: A Metabolomics Approach
    Gyumin Kang, Haelim Lee, Malsoon Shin, Jaekwan Kim, Sungki Lee, Youngja Park
    Metabolites.2021; 11(2): 118.     CrossRef
  • Broad Metabolome Alterations Associated with the Intake of Oral Contraceptives Are Mediated by Cortisol in Premenopausal Women
    Clara Eick, Johanna Klinger-König, Stephanie Zylla, Anke Hannemann, Kathrin Budde, Ann Kristin Henning, Maik Pietzner, Matthias Nauck, Henry Völzke, Hans J. Grabe, Johannes Hertel
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  • Nutritional Metabolomics and the Classification of Dietary Biomarker Candidates: A Critical Review
    Talha Rafiq, Sandi M Azab, Koon K Teo, Lehana Thabane, Sonia S Anand, Katherine M Morrison, Russell J de Souza, Philip Britz-McKibbin
    Advances in Nutrition.2021; 12(6): 2333.     CrossRef
  • MSCAT: A Machine Learning Assisted Catalog of Metabolomics Software Tools
    Jonathan Dekermanjian, Wladimir Labeikovsky, Debashis Ghosh, Katerina Kechris
    Metabolites.2021; 11(10): 678.     CrossRef
  • Defining NASH from a Multi-Omics Systems Biology Perspective
    Lili Niu, Karolina Sulek, Catherine G. Vasilopoulou, Alberto Santos, Nicolai J. Wewer Albrechtsen, Simon Rasmussen, Florian Meier, Matthias Mann
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Endocrinol Metab : Endocrinology and Metabolism