Metabolome-Defined Obesity and the Risk of Future Type 2 Diabetes and Mortality

Author:

Ottosson Filip12ORCID,Smith Einar1ORCID,Ericson Ulrika1,Brunkwall Louise1,Orho-Melander Marju1,Di Somma Salvatore34,Antonini Paola4,Nilsson Peter M.1,Fernandez Céline1ORCID,Melander Olle1

Affiliation:

1. Department of Clinical Sciences, Lund University, Malmö, Sweden

2. Section for Clinical Mass Spectrometry, Danish Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark

3. Department of Medical-Surgery Sciences and Translational Medicine, University of Rome Sapienza, Rome, Italy

4. GREAT Health Sciences, Rome, Italy

Abstract

OBJECTIVE Obesity is a key risk factor for type 2 diabetes; however, up to 20% of patients are normal weight. Our aim was to identify metabolite patterns reproducibly predictive of BMI and subsequently to test whether lean individuals who carry an obese metabolome are at hidden high risk of obesity-related diseases, such as type 2 diabetes. RESEARCH DESIGN AND METHODS Levels of 108 metabolites were measured in plasma samples of 7,663 individuals from two Swedish and one Italian population-based cohort. Ridge regression was used to predict BMI using the metabolites. Individuals with a predicted BMI either >5 kg/m2 higher (overestimated) or lower (underestimated) than their actual BMI were characterized as outliers and further investigated for obesity-related risk factors and future risk of type 2 diabetes and mortality. RESULTS The metabolome could predict BMI in all cohorts (r2 = 0.48, 0.26, and 0.19). The overestimated group had a BMI similar to individuals correctly predicted as normal weight, had a similar waist circumference, were not more likely to change weight over time, but had a two times higher risk of future type 2 diabetes and an 80% increased risk of all-cause mortality. These associations remained after adjustments for obesity-related risk factors and lifestyle parameters. CONCLUSIONS We found that lean individuals with an obesity-related metabolome have an increased risk for type 2 diabetes and all-cause mortality compared with lean individuals with a healthy metabolome. Metabolomics may be used to identify hidden high-risk individuals to initiate lifestyle and pharmacological interventions.

Publisher

American Diabetes Association

Subject

Advanced and Specialized Nursing,Endocrinology, Diabetes and Metabolism,Internal Medicine

Reference34 articles.

1. World Health Organization . Obesity. Accessed 30 August 2021. Available from https://www.who.int/news-room/facts-in-pictures/detail/6- facts-on-obesity

2. Association of weight status with mortality in adults with incident diabetes;Carnethon;JAMA,2012

3. Cardiovascular and metabolic heterogeneity of obesity: clinical challenges and implications for management;Neeland;Circulation,2018

4. Metabolically healthy obesity: definitions, determinants and clinical implications;Phillips;Rev Endocr Metab Disord,2013

5. Innovation: metabolomics: the apogee of the omics trilogy;Patti;Nat Rev Mol Cell Biol,2012

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3