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      Are Phosphatidylcholine and Lysophosphatidylcholine Body Levels Potentially Reliable Biomarkers in Obesity? A Review of Human Studies

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          A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010

          The Lancet, 380(9859), 2224-2260
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            The Metabolic Phenotype in Obesity: Fat Mass, Body Fat Distribution, and Adipose Tissue Function

            The current obesity epidemic poses a major public health issue since obesity predisposes towards several chronic diseases. BMI and total adiposity are positively correlated with cardiometabolic disease risk at the population level. However, body fat distribution and an impaired adipose tissue function, rather than total fat mass, better predict insulin resistance and related complications at the individual level. Adipose tissue dysfunction is determined by an impaired adipose tissue expandability, adipocyte hypertrophy, altered lipid metabolism, and local inflammation. Recent human studies suggest that adipose tissue oxygenation may be a key factor herein. A subgroup of obese individuals - the ‘metabolically healthy obese' (MHO) - have a better adipose tissue function, less ectopic fat storage, and are more insulin sensitive than obese metabolically unhealthy persons, emphasizing the central role of adipose tissue function in metabolic health. However, controversy has surrounded the idea that metabolically healthy obesity may be considered really healthy since MHO individuals are at increased (cardio)metabolic disease risk and may have a lower quality of life than normal weight subjects due to other comorbidities. Detailed metabolic phenotyping of obese persons will be invaluable in understanding the pathophysiology of metabolic disturbances, and is needed to identify high-risk individuals or subgroups, thereby paving the way for optimization of prevention and treatment strategies to combat cardiometabolic diseases.
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              Identification of Serum Metabolites Associated With Risk of Type 2 Diabetes Using a Targeted Metabolomic Approach

              Metabolomic discovery of biomarkers of type 2 diabetes (T2D) risk may reveal etiological pathways and help to identify individuals at risk for disease. We prospectively investigated the association between serum metabolites measured by targeted metabolomics and risk of T2D in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam (27,548 adults) among all incident cases of T2D (n = 800, mean follow-up 7 years) and a randomly drawn subcohort (n = 2,282). Flow injection analysis tandem mass spectrometry was used to quantify 163 metabolites, including acylcarnitines, amino acids, hexose, and phospholipids, in baseline serum samples. Serum hexose; phenylalanine; and diacyl-phosphatidylcholines C32:1, C36:1, C38:3, and C40:5 were independently associated with increased risk of T2D and serum glycine; sphingomyelin C16:1; acyl-alkyl-phosphatidylcholines C34:3, C40:6, C42:5, C44:4, and C44:5; and lysophosphatidylcholine C18:2 with decreased risk. Variance of the metabolites was largely explained by two metabolite factors with opposing risk associations (factor 1 relative risk in extreme quintiles 0.31 [95% CI 0.21–0.44], factor 2 3.82 [2.64–5.52]). The metabolites significantly improved T2D prediction compared with established risk factors. They were further linked to insulin sensitivity and secretion in the Tübingen Family study and were partly replicated in the independent KORA (Cooperative Health Research in the Region of Augsburg) cohort. The data indicate that metabolic alterations, including sugar metabolites, amino acids, and choline-containing phospholipids, are associated early on with a higher risk of T2D.
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                Author and article information

                Contributors
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                Journal
                Molecular Nutrition & Food Research
                Molecular Nutrition Food Res
                Wiley
                1613-4125
                1613-4133
                April 2023
                February 09 2023
                April 2023
                : 67
                : 7
                Affiliations
                [1 ] Postgraduate Program in Nutrition Center for Health Sciences Federal University of Rio Grande do Norte Av. Senador Salgado Filho, 3000 – Lagoa Nova, 59078‐970 Natal Rio Grande do Norte Brazil
                [2 ] Department of Nutrition Federal University of Rio Grande do Norte Av. Senador Salgado Filho, 3000 – Lagoa Nova, 59078‐970 Natal Rio Grande do Norte Brazil
                [3 ] Department of Organic Chemistry Institute of Chemistry University of Campinas Campinas, Rua Josué de Castro s/n – Cidade Universitária Zeferino Vaz, 13083‐970, Campinas São Paulo‐SP Brazil
                [4 ] Department of Clinical, Toxicological and Bromatological Analysis Faculty of Pharmaceutical Sciences University of São Paulo Ribeirão Preto Campus, Av. do Café, s/n – Monte Alegre, 14040‐903, Ribeirão Preto São Paulo‐SP Brazil
                Article
                10.1002/mnfr.202200568
                36707969
                46581bda-e60f-4deb-8739-e53b90946f29
                © 2023

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