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O'Keeffe LM, Tilling K, Bell JA, Walsh PT, Lee MA, Lawlor DA, Davey Smith G, Kearney PM. Sex-specific trajectories of molecular cardiometabolic traits from childhood to young adulthood. Heart 2023; 109:674-685. [PMID: 36914250 PMCID: PMC10176380 DOI: 10.1136/heartjnl-2022-321347] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 11/15/2022] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND The changes which typically occur in molecular causal risk factors and predictive biomarkers for cardiometabolic diseases across early life are not well characterised. METHODS We quantified sex-specific trajectories of 148 metabolic trait concentrations including various lipoprotein subclasses from age 7 years to 25 years. Data were from 7065 to 7626 offspring (11 702 to14 797 repeated measures) of the Avon Longitudinal Study of Parents and Children birth cohort study. Outcomes were quantified using nuclear magnetic resonance spectroscopy at 7, 15, 18 and 25 years. Sex-specific trajectories of each trait were modelled using linear spline multilevel models. RESULTS Females had higher very-low-density lipoprotein (VLDL) particle concentrations at 7 years. VLDL particle concentrations decreased from 7 years to 25 years with larger decreases in females, leading to lower VLDL particle concentrations at 25 years in females. For example, females had a 0.25 SD (95% CI 0.20 to 0.31) higher small VLDL particle concentration at 7 years; mean levels decreased by 0.06 SDs (95% CI -0.01 to 0.13) in males and 0.85 SDs (95% CI 0.79 to 0.90) in females from 7 years to 25 years, leading to 0.42 SDs (95% CI 0.35 to 0.48) lower small VLDL particle concentrations in females at 25 years. Females had lower high-density lipoprotein (HDL) particle concentrations at 7 years. HDL particle concentrations increased from 7 years to 25 years with larger increases among females leading to higher HDL particle concentrations in females at 25 years. CONCLUSION Childhood and adolescence are important periods for the emergence of sex differences in atherogenic lipids and predictive biomarkers for cardiometabolic disease, mostly to the detriment of males.
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Affiliation(s)
- Linda M O'Keeffe
- School of Public Health, University College Cork, Cork, Ireland
- MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Kate Tilling
- MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Joshua A Bell
- MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Patrick T Walsh
- School of Public Health, University College Cork, Cork, Ireland
| | - Matthew A Lee
- MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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Qiu S, Cai Y, Yao H, Lin C, Xie Y, Tang S, Zhang A. Small molecule metabolites: discovery of biomarkers and therapeutic targets. Signal Transduct Target Ther 2023; 8:132. [PMID: 36941259 PMCID: PMC10026263 DOI: 10.1038/s41392-023-01399-3] [Citation(s) in RCA: 99] [Impact Index Per Article: 99.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 03/01/2023] [Accepted: 03/03/2023] [Indexed: 03/22/2023] Open
Abstract
Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.
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Affiliation(s)
- Shi Qiu
- International Advanced Functional Omics Platform, Scientific Experiment Center, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), College of Chinese Medicine, Hainan Medical University, Xueyuan Road 3, Haikou, 571199, China
| | - Ying Cai
- Graduate School, Heilongjiang University of Chinese Medicine, Harbin, 150040, China
| | - Hong Yao
- First Affiliated Hospital, Harbin Medical University, Harbin, 150081, China
| | - Chunsheng Lin
- Second Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, 150001, China
| | - Yiqiang Xie
- International Advanced Functional Omics Platform, Scientific Experiment Center, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), College of Chinese Medicine, Hainan Medical University, Xueyuan Road 3, Haikou, 571199, China.
| | - Songqi Tang
- International Advanced Functional Omics Platform, Scientific Experiment Center, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), College of Chinese Medicine, Hainan Medical University, Xueyuan Road 3, Haikou, 571199, China.
| | - Aihua Zhang
- International Advanced Functional Omics Platform, Scientific Experiment Center, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), College of Chinese Medicine, Hainan Medical University, Xueyuan Road 3, Haikou, 571199, China.
- Graduate School, Heilongjiang University of Chinese Medicine, Harbin, 150040, China.
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Su KJ, Chen XY, Gong R, Zhao Q, Hu SD, Feng MC, Li Y, Lin X, Zhang YH, Greenbaum J, Tian Q, Shen H, Xiao HM, Shen J, Deng HW. Systematic metabolomic studies identified adult adiposity biomarkers with acetylglycine associated with fat loss in vivo. Front Mol Biosci 2023; 10:1166333. [PMID: 37122566 PMCID: PMC10141311 DOI: 10.3389/fmolb.2023.1166333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 03/28/2023] [Indexed: 05/02/2023] Open
Abstract
Obesity is associated with various adverse health outcomes. Body fat (BF) distribution is recognized as an important factor of negative health consequences of obesity. Although metabolomics studies, mainly focused on body mass index (BMI) and waist circumference, have explored the biological mechanisms involved in the development of obesity, these proxy composite measures are not accurate and cannot reflect BF distribution, and thus may hinder accurate assessment of metabolic alterations and differential risk of metabolic disorders among individuals presenting adiposity differently throughout the body. Thus, the exact relations between metabolites and BF remain to be elucidated. Here, we aim to examine the associations of metabolites and metabolic pathways with BF traits which reflect BF distribution. We performed systematic untargeted serum metabolite profiling and dual-energy X-ray absorptiometry (DXA) whole body fat scan for 517 Chinese women. We jointly analyzed DXA-derived four BF phenotypes to detect cross-phenotype metabolite associations and to prioritize important metabolomic factors. Topology-based pathway analysis was used to identify important BF-related biological processes. Finally, we explored the relationships of the identified BF-related candidate metabolites with BF traits in different sex and ethnicity through two independent cohorts. Acetylglycine, the top distinguished finding, was validated for its obesity resistance effect through in vivo studies of various diet-induced obese (DIO) mice. Eighteen metabolites and fourteen pathways were discovered to be associated with BF phenotypes. Six of the metabolites were validated in varying sex and ethnicity. The obesity-resistant effects of acetylglycine were observed to be highly robust and generalizable in both human and DIO mice. These findings demonstrate the importance of metabolites associated with BF distribution patterns and several biological pathways that may contribute to obesity and obesity-related disease etiology, prevention, and intervention. Acetylglycine is highlighted as a potential therapeutic candidate for preventing excessive adiposity in future studies.
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Affiliation(s)
- Kuan-Jui Su
- Tulane Center for Biomedical Informatics and Genomics, School of Medicine, Tulane University, New Orleans, LA, United States
- Department of Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States
| | - Xing-Ying Chen
- Shunde Hospital of Southern Medical University (The First People’s Hospital of Shunde), Foshan, China
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China
| | - Rui Gong
- Tulane Center for Biomedical Informatics and Genomics, School of Medicine, Tulane University, New Orleans, LA, United States
- Shunde Hospital of Southern Medical University (The First People’s Hospital of Shunde), Foshan, China
- Department of Cadre Ward Endocrinology, Gansu Provincial Hospital, Lanzhou, China
| | - Qi Zhao
- Department of Preventive Medicine, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Shi-Di Hu
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China
| | - Mei-Chen Feng
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China
| | - Ye Li
- Shunde Hospital of Southern Medical University (The First People’s Hospital of Shunde), Foshan, China
| | - Xu Lin
- Tulane Center for Biomedical Informatics and Genomics, School of Medicine, Tulane University, New Orleans, LA, United States
- Shunde Hospital of Southern Medical University (The First People’s Hospital of Shunde), Foshan, China
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China
| | - Yin-Hua Zhang
- Shunde Hospital of Southern Medical University (The First People’s Hospital of Shunde), Foshan, China
| | - Jonathan Greenbaum
- Tulane Center for Biomedical Informatics and Genomics, School of Medicine, Tulane University, New Orleans, LA, United States
| | - Qing Tian
- Tulane Center for Biomedical Informatics and Genomics, School of Medicine, Tulane University, New Orleans, LA, United States
| | - Hui Shen
- Tulane Center for Biomedical Informatics and Genomics, School of Medicine, Tulane University, New Orleans, LA, United States
| | - Hong-Mei Xiao
- Center of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, Central South University, Changsha, China
| | - Jie Shen
- Shunde Hospital of Southern Medical University (The First People’s Hospital of Shunde), Foshan, China
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China
- *Correspondence: Hong-Wen Deng, ; Jie Shen,
| | - Hong-Wen Deng
- Tulane Center for Biomedical Informatics and Genomics, School of Medicine, Tulane University, New Orleans, LA, United States
- *Correspondence: Hong-Wen Deng, ; Jie Shen,
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Boulet N, Briot A, Galitzky J, Bouloumié A. The Sexual Dimorphism of Human Adipose Depots. Biomedicines 2022; 10:2615. [PMID: 36289874 PMCID: PMC9599294 DOI: 10.3390/biomedicines10102615] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 10/11/2022] [Accepted: 10/13/2022] [Indexed: 08/21/2023] Open
Abstract
The amount and the distribution of body fat exhibit trajectories that are sex- and human species-specific and both are determinants for health. The enhanced accumulation of fat in the truncal part of the body as a risk factor for cardiovascular and metabolic diseases is well supported by epidemiological studies. In addition, a possible independent protective role of the gluteofemoral fat compartment and of the brown adipose tissue is emerging. The present narrative review summarizes the current knowledge on sexual dimorphism in fat depot amount and repartition and consequences on cardiometabolic and reproductive health. The drivers of the sex differences and fat depot repartition, considered to be the results of complex interactions between sex determination pathways determined by the sex chromosome composition, genetic variability, sex hormones and the environment, are discussed. Finally, the inter- and intra-depot heterogeneity in adipocytes and progenitors, emphasized recently by unbiased large-scale approaches, is highlighted.
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Affiliation(s)
| | | | | | - Anne Bouloumié
- Inserm, Unité Mixte de Recherche (UMR) 1297, Team 1, Institut des Maladies Métaboliques et Cardiovasculaires (I2MC), Université de Toulouse, F-31432 Toulouse, France
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Bell JA, Richardson TG, Wang Q, Sanderson E, Palmer T, Walker V, O'Keeffe LM, Timpson NJ, Cichonska A, Julkunen H, Würtz P, Holmes MV, Davey Smith G. Effects of general and central adiposity on circulating lipoprotein, lipid, and metabolite levels in UK Biobank: A multivariable Mendelian randomization study. THE LANCET REGIONAL HEALTH. EUROPE 2022; 21:100457. [PMID: 35832062 PMCID: PMC9272390 DOI: 10.1016/j.lanepe.2022.100457] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
Background The direct effects of general adiposity (body mass index (BMI)) and central adiposity (waist-to-hip-ratio (WHR)) on circulating lipoproteins, lipids, and metabolites are unknown. Methods We used new metabolic data from UK Biobank (N=109,532, a five-fold higher N over previous studies). EDTA-plasma was used to quantify 249 traits with nuclear-magnetic-resonance spectroscopy including subclass-specific lipoprotein concentrations and lipid content, plus pre-glycemic and inflammatory metabolites. We used univariable and multivariable two-stage least-squares regression models with genetic risk scores for BMI and WHR as instruments to estimate total (unadjusted) and direct (mutually-adjusted) effects of BMI and WHR on metabolic traits; plus effects on statin use and interaction by sex, statin use, and age (proxy for medication use). Findings Higher BMI decreased apolipoprotein B and low-density lipoprotein cholesterol (LDL-C) before and after WHR-adjustment, whilst BMI increased triglycerides only before WHR-adjustment. These effects of WHR were larger and BMI-independent. Direct effects differed markedly by sex, e.g., triglycerides increased only with BMI among men, and only with WHR among women. Adiposity measures increased statin use and showed metabolic effects which differed by statin use and age. Among the youngest (38-53y, statins-5%), BMI and WHR (per-SD) increased LDL-C (total effects: 0.04-SD, 95%CI=-0.01,0.08 and 0.10-SD, 95%CI=0.02,0.17 respectively), but only WHR directly. Among the oldest (63-73y, statins-29%), BMI and WHR directly lowered LDL-C (-0.19-SD, 95%CI=-0.27,-0.11 and -0.05-SD, 95%CI=-0.16,0.06 respectively). Interpretation Excess adiposity likely raises atherogenic lipid and metabolite levels exclusively via adiposity stored centrally, particularly among women. Apparent effects of adiposity on lowering LDL-C are likely explained by an effect of adiposity on statin use. Funding UK Medical Research Council; British Heart Foundation; Novo Nordisk; National Institute for Health Research; Wellcome Trust; Cancer Research UK.
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Affiliation(s)
- Joshua A. Bell
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tom G. Richardson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Novo Nordisk Research Centre Oxford, Old Road Campus, Oxford, UK
| | - Qin Wang
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Eleanor Sanderson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tom Palmer
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Venexia Walker
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Linda M. O'Keeffe
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- School of Public Health, Western Gateway Building, University College Cork, Ireland
| | - Nicholas J. Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | | | | | | | - Michael V. Holmes
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit at the University of Oxford, Oxford, UK
- National Institute for Health Research, Oxford Biomedical Research Centre, Oxford University Hospital, Oxford, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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