Topic Editors

Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Fukuoka 8078555, Japan
Department of Psychiatry, Teikyo University School of Medicine, Tokyo 173-8605, Japan
Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
Dr. Naomichi Okamoto
Department of Psychiatry, University of Occupational and Environmental Health, Iseigaoka, Yahatanishi-ku, Kitakyushu 8078555, Fukuoka, Japan

"Metabolites" as Metabolomics for Neuropsychiatric Diseases

Abstract submission deadline
closed (25 September 2023)
Manuscript submission deadline
closed (25 November 2023)
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5417

Topic Information

Dear Colleagues,

The diagnosis of psychiatric disorders is based solely on symptoms, and a lack of understanding of the molecular pathogenesis is a major challenge that must be overcome in the future. Furthermore, drug treatment guidelines use a one-size-fits-all approach to treat each disorder, despite the known heterogeneity of clinical symptoms and prognosis of psychiatric disorders. The limited effectiveness of treatment emphasizes the need for precision medicine in psychiatry and is referred to as precision psychiatry. To practice precision psychiatry, it is essential to research and develop multiple omics-based biomarkers to accurately determine phenotypes. Metabolomics, the endpoint of the omics cascade, detects changes in metabolites at the systems level of biological pathways, thereby providing insight into the mechanisms underlying various physiological states and pathological conditions. Metabolomics is a promising tool for precision psychiatry and holds great promise for both biomarker discovery and the elucidation of molecular mechanisms underlying psychiatric disorders.

Prof. Dr. Reiji Yoshimura
Prof. Dr. Hiroshi Kunugi
Dr. Takahiro Kato
Dr. Naomichi Okamoto
Topic Editors

Keywords

  • metabolomics
  • neuropsychiatric diseases
  • biomarkers
  • precision medicine
  • molecular pathogenesis

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
BioChem
biochem
- - 2021 24.1 Days CHF 1000
Biology
biology
3.6 5.7 2012 16.1 Days CHF 2700
Biomolecules
biomolecules
4.8 9.4 2011 16.3 Days CHF 2700
Journal of Developmental Biology
jdb
2.2 4.1 2013 19.6 Days CHF 1800
Metabolites
metabolites
3.4 5.7 2011 13.9 Days CHF 2700

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Published Papers (1 paper)

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14 pages, 1833 KiB  
Article
Metabolically Healthy Obesity Is a Misnomer: Components of the Metabolic Syndrome Linearly Increase with BMI as a Function of Age and Gender
by Yonit Marcus, Elad Segev, Gabi Shefer, David Eilam, Galina Shenkerman, Assaf Buch, Shani Shenhar-Tsarfaty, David Zeltser, Itzhak Shapira, Shlomo Berliner and Ori Rogowski
Biology 2023, 12(5), 719; https://doi.org/10.3390/biology12050719 - 15 May 2023
Cited by 6 | Viewed by 4327
Abstract
Objectives: We aimed to examine the relationships between body mass index (BMI) and metabolic syndrome (MS) components as a function of age and gender across weight categories. Methods: This cross-sectional study included 19,328 subjects who participated in a health-screening program. We analyzed 14,093 [...] Read more.
Objectives: We aimed to examine the relationships between body mass index (BMI) and metabolic syndrome (MS) components as a function of age and gender across weight categories. Methods: This cross-sectional study included 19,328 subjects who participated in a health-screening program. We analyzed 14,093 apparently healthy subjects with a BMI ≥ 18.5 kg/m2 (ranging from 18.5 to 46 kg/m2). Results: At a BMI of 18.5 kg/m2, 16% of subjects had one or more MS components (MS ≥ 1). The number of MS components increased linearly with BMI. The most prevalent components for MS1-4 were hypertension (in men) and increased waist circumference (in women). Among 6391 non-obese subjects with MS = 0, there was a linear increase in blood pressure, glucose, and triglycerides, as well as a decline in high-density lipoprotein cholesterol, as BMI increased. In 2087 subjects with a BMI ≥ 30 kg/m2, a true normometabolic state (MS = 0) was observed in only 7.5%, declining to less than 1% at a BMI ≥ 36 kg/m2 (ATP criteria). Women were metabolically protected relative to men between the ages of 30 and 50 years. Conclusions: (A) MS components increase linearly with BMI from the lowest normal BMI and continue to increase with age and BMI; (B) metabolically healthy obesity is rare in subjects with a high BMI and declines with age; (C) hypertension is the most common component in men; and (D) in women, MS components are seen at older ages than in men for the same BMI. Metabolic health declines with age and BMI in nearly all subjects with obesity. Full article
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