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Cited by 575Diabetes, Cardiovascular Risks, and LipoproteinsAdipokines, Inflammation, and Metabolic DiseasesCardiovascular Disease and Adiposity

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Causes, Characteristics, and Consequences of Metabolically Unhealthy Normal Weight in Humans

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Stefan, Norbert, Schick, Fritz, Häring, Hans-Ulrich·2017·Cell Metabolism
DOI 10.1016/j.cmet.2017.07.008
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Abstract

A BMI in the normal range associates with a decreased risk of cardiometabolic disease and all-cause mortality. However, not all subjects in this BMI range have this low risk. Compared to people who are of normal weight and metabolically healthy, subjects who are of normal weight but metabolically unhealthy (∼20% of the normal weight adult population) have a greater than 3-fold higher risk of all-cause mortality and/or cardiovascular events. Here we address to what extent major risk phenotypes determine metabolic health in lean compared to overweight and obese people and provide support for the existence of a lipodystrophy-like phenotype in the general population. Furthermore, we highlight the molecular mechanisms that induce this phenotype. Finally, we propose strategies as to how this knowledge could be implemented in the prevention and treatment of cardiometabolic diseases in different stages of adiposity in routine clinical practice.

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Research works printed but not linked: 61

  1. Ahima, 2013, Physiology. The health risk of obesity--better metrics imperative, Science, 341, 856, 10.1126/science.1241244 · DOI
  2. Aleksandrova, 2013, Influence of obesity and related metabolic alterations on colorectal cancer risk, Curr. Nutr. Rep., 2, 1, 10.1007/s13668-012-0036-9 · DOI
  3. 2017, 5. Prevention or Delay of Type 2 Diabetes, Diabetes Care, 40, S44
  4. Blüher, 2014, Are metabolically healthy obese individuals really healthy?, Eur. J. Endocrinol., 171, R209, 10.1530/EJE-14-0540 · DOI
  5. Cao, 2008, Identification of a lipokine, a lipid hormone linking adipose tissue to systemic metabolism, Cell, 134, 933, 10.1016/j.cell.2008.07.048 · DOI
  6. Carr, 2004, No effect of rosiglitazone for treatment of HIV-1 lipoatrophy: randomised, double-blind, placebo-controlled trial, Lancet, 363, 429, 10.1016/S0140-6736(04)15489-5 · DOI
  7. Després, 2006, Abdominal obesity and metabolic syndrome, Nature, 444, 881, 10.1038/nature05488 · DOI · Paper page
  8. Eckel, 2015, Characterization of metabolically unhealthy normal-weight individuals: risk factors and their associations with type 2 diabetes, Metabolism, 64, 862, 10.1016/j.metabol.2015.03.009 · DOI
  9. Edgeworth, 2013, Thiazolidinediones in the treatment of HIV/HAART-associated lipodystrophy syndrome, AIDS Rev., 15, 171
  10. Flegal, 2013, Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis, JAMA, 309, 71, 10.1001/jama.2012.113905 · DOI · Paper page
  11. Gandotra, 2011, Perilipin deficiency and autosomal dominant partial lipodystrophy, N. Engl. J. Med., 364, 740, 10.1056/NEJMoa1007487 · DOI
  12. Garg, 2004, Acquired and inherited lipodystrophies, N. Engl. J. Med., 350, 1220, 10.1056/NEJMra025261 · DOI
  13. Garg, 2011, Clinical review#: Lipodystrophies: genetic and acquired body fat disorders, J. Clin. Endocrinol. Metab., 96, 3313, 10.1210/jc.2011-1159 · DOI
  14. Gavrila, 2005, Improvement in highly active antiretroviral therapy-induced metabolic syndrome by treatment with pioglitazone but not with fenofibrate: a 2 x 2 factorial, randomized, double-blinded, placebo-controlled trial, Clin. Infect. Dis., 40, 745, 10.1086/427697 · DOI
  15. Ginsberg, 2000, Insulin resistance and cardiovascular disease, J. Clin. Invest., 106, 453, 10.1172/JCI10762 · DOI
  16. Gujral, 2017, Cardiometabolic Abnormalities Among Normal-Weight Persons From Five Racial/Ethnic Groups in the United States: A Cross-sectional Analysis of Two Cohort Studies, Ann. Intern. Med., 166, 628, 10.7326/M16-1895 · DOI
  17. Hughes, 2013, The big fat truth, Nature, 497, 428
  18. Karelis, 2008, Inclusion of C-reactive protein in the identification of metabolically healthy but obese (MHO) individuals, Diabetes Metab., 34, 183, 10.1016/j.diabet.2007.11.004 · DOI
  19. Karelis, 2004, Metabolic and body composition factors in subgroups of obesity: what do we know?, J. Clin. Endocrinol. Metab., 89, 2569, 10.1210/jc.2004-0165 · DOI
  20. Karpe, 2015, Biology of upper-body and lower-body adipose tissue--link to whole-body phenotypes, Nat. Rev. Endocrinol., 11, 90, 10.1038/nrendo.2014.185 · DOI · Paper page
  21. Kramer, 2013, Are metabolically healthy overweight and obesity benign conditions?: A systematic review and meta-analysis, Ann. Intern. Med., 159, 758, 10.7326/0003-4819-159-11-201312030-00008 · DOI
  22. Kusminski, 2016, Targeting adipose tissue in the treatment of obesity-associated diabetes, Nat. Rev. Drug Discov., 15, 639, 10.1038/nrd.2016.75 · DOI · Paper page
  23. Laakso, 2014, Insulin resistance and hyperglycaemia in cardiovascular disease development, Nat. Rev. Endocrinol., 10, 293, 10.1038/nrendo.2014.29 · DOI
  24. Lotta, 2015, Definitions of Metabolic Health and Risk of Future Type 2 Diabetes in BMI Categories: A Systematic Review and Network Meta-analysis, Diabetes Care, 38, 2177, 10.2337/dc15-1218 · DOI
  25. Lotta, 2017, Integrative genomic analysis implicates limited peripheral adipose storage capacity in the pathogenesis of human insulin resistance, Nat. Genet., 49, 17, 10.1038/ng.3714 · DOI
  26. Marinou, 2014, Structural and functional properties of deep abdominal subcutaneous adipose tissue explain its association with insulin resistance and cardiovascular risk in men, Diabetes Care, 37, 821, 10.2337/dc13-1353 · DOI
  27. Mathew, 2016, Metabolic health and weight: Understanding metabolically unhealthy normal weight or metabolically healthy obese patients, Metabolism, 65, 73, 10.1016/j.metabol.2015.10.019 · DOI · Paper page
  28. McLaughlin, 2007, Heterogeneity in the prevalence of risk factors for cardiovascular disease and type 2 diabetes mellitus in obese individuals: effect of differences in insulin sensitivity, Arch. Intern. Med., 167, 642, 10.1001/archinte.167.7.642 · DOI
  29. Meigs, 2006, Body mass index, metabolic syndrome, and risk of type 2 diabetes or cardiovascular disease, J. Clin. Endocrinol. Metab., 91, 2906, 10.1210/jc.2006-0594 · DOI
  30. Mørkedal, 2014, Risk of myocardial infarction and heart failure among metabolically healthy but obese individuals: HUNT (Nord-Trøndelag Health Study), Norway, J. Am. Coll. Cardiol., 63, 1071, 10.1016/j.jacc.2013.11.035 · DOI
  31. Murphy, 2016, A Nested Case-Control Study of Metabolically Defined Body Size Phenotypes and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC), PLoS Med., 13, e1001988, 10.1371/journal.pmed.1001988 · DOI
  32. Nolan, 2015, Insulin resistance as a physiological defense against metabolic stress: implications for the management of subsets of type 2 diabetes, Diabetes, 64, 673, 10.2337/db14-0694 · DOI
  33. Nordestgaard, 2012, The effect of elevated body mass index on ischemic heart disease risk: causal estimates from a Mendelian randomisation approach, PLoS Med., 9, e1001212, 10.1371/journal.pmed.1001212 · DOI
  34. O’Rahilly, 2009, Human genetics illuminates the paths to metabolic disease, Nature, 462, 307, 10.1038/nature08532 · DOI
  35. Paruthi, 2013, Adipokines in the HIV/HAART-associated lipodystrophy syndrome, Metabolism, 62, 1199, 10.1016/j.metabol.2013.04.014 · DOI
  36. Patni, 2015, Congenital generalized lipodystrophies--new insights into metabolic dysfunction, Nat. Rev. Endocrinol., 11, 522, 10.1038/nrendo.2015.123 · DOI
  37. Phillips, 2017, Metabolically healthy obesity across the life course: epidemiology, determinants, and implications, Ann. N Y Acad. Sci., 1391, 85, 10.1111/nyas.13230 · DOI
  38. Pinnick, 2012, Gluteofemoral adipose tissue plays a major role in production of the lipokine palmitoleate in humans, Diabetes, 61, 1399, 10.2337/db11-1810 · DOI
  39. Pou, 2009, Patterns of abdominal fat distribution: the Framingham Heart Study, Diabetes Care, 32, 481, 10.2337/dc08-1359 · DOI
  40. Robbins, 2015, The genetics of lipid storage and human lipodystrophies, Trends Mol. Med., 21, 433, 10.1016/j.molmed.2015.04.004 · DOI
  41. Rosen, 2014, What we talk about when we talk about fat, Cell, 156, 20, 10.1016/j.cell.2013.12.012 · DOI · Paper page
  42. Ross, 2016, Importance of Assessing Cardiorespiratory Fitness in Clinical Practice: A Case for Fitness as a Clinical Vital Sign: A Scientific Statement From the American Heart Association, Circulation, 134, e653, 10.1161/CIR.0000000000000461 · DOI · Paper page
  43. Ruderman, 1981, The “metabolically-obese,” normal-weight individual, Am. J. Clin. Nutr., 34, 1617, 10.1093/ajcn/34.8.1617 · DOI · Paper page
  44. Ruderman, 1998, The metabolically obese, normal-weight individual revisited, Diabetes, 47, 699, 10.2337/diabetes.47.5.699 · DOI · Paper page
  45. Sahakyan, 2015, Normal-Weight Central Obesity: Implications for Total and Cardiovascular Mortality, Ann. Intern. Med., 163, 827, 10.7326/M14-2525 · DOI
  46. Samocha-Bonet, 2014, Metabolically healthy and unhealthy obese--the 2013 Stock Conference report, Obes. Rev., 15, 697, 10.1111/obr.12199 · DOI
  47. Scott, 2014, Common genetic variants highlight the role of insulin resistance and body fat distribution in type 2 diabetes, independent of obesity, Diabetes, 63, 4378, 10.2337/db14-0319 · DOI
  48. Semple, 2011, Genetic syndromes of severe insulin resistance, Endocr. Rev., 32, 498, 10.1210/er.2010-0020 · DOI
  49. Shimabukuro, 1997, Leptin- or troglitazone-induced lipopenia protects islets from interleukin 1beta cytotoxicity, J. Clin. Invest., 100, 1750, 10.1172/JCI119700 · DOI
  50. Smith, 2016, Adipose tissue regulates insulin sensitivity: role of adipogenesis, de novo lipogenesis and novel lipids, J. Intern. Med., 280, 465, 10.1111/joim.12540 · DOI
  51. Stefan, 2008, Identification and characterization of metabolically benign obesity in humans, Arch. Intern. Med., 168, 1609, 10.1001/archinte.168.15.1609 · DOI · Paper page
  52. Stefan, 2010, Circulating palmitoleate strongly and independently predicts insulin sensitivity in humans, Diabetes Care, 33, 405, 10.2337/dc09-0544 · DOI
  53. Stefan, 2014, Mechanisms explaining the relationship between metabolically healthy obesity and cardiovascular risk, J. Am. Coll. Cardiol., 63, 2748, 10.1016/j.jacc.2014.01.079 · DOI
  54. Stefan, 2016, Phenotypes of prediabetes and stratification of cardiometabolic risk, Lancet Diabetes Endocrinol., 4, 789, 10.1016/S2213-8587(16)00082-6 · DOI · Paper page
  55. Stern, 2016, Adiponectin, Leptin, and Fatty Acids in the Maintenance of Metabolic Homeostasis through Adipose Tissue Crosstalk, Cell Metab., 23, 770, 10.1016/j.cmet.2016.04.011 · DOI · Paper page
  56. Tan, 2008, Adipose tissue expandability: the metabolic problems of obesity may arise from the inability to become more obese, Biochem. Soc. Trans., 36, 935, 10.1042/BST0360935 · DOI
  57. Tchkonia, 2013, Mechanisms and metabolic implications of regional differences among fat depots, Cell Metab., 17, 644, 10.1016/j.cmet.2013.03.008 · DOI
  58. Wildman, 2008, The obese without cardiometabolic risk factor clustering and the normal weight with cardiometabolic risk factor clustering: prevalence and correlates of 2 phenotypes among the US population (NHANES 1999-2004), Arch. Intern. Med., 168, 1617, 10.1001/archinte.168.15.1617 · DOI · Paper page
  59. White, 2016, Differences in In Vivo Cellular Kinetics in Abdominal and Femoral Subcutaneous Adipose Tissue in Women, Diabetes, 65, 1642, 10.2337/db15-1617 · DOI
  60. Yaghootkar, 2014, Genetic evidence for a normal-weight “metabolically obese” phenotype linking insulin resistance, hypertension, coronary artery disease, and type 2 diabetes, Diabetes, 63, 4369, 10.2337/db14-0318 · DOI
  61. Yaghootkar, 2016, Genetic Evidence for a Link Between Favorable Adiposity and Lower Risk of Type 2 Diabetes, Hypertension, and Heart Disease, Diabetes, 65, 2448, 10.2337/db15-1671 · DOI

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Metadata

Authors
Stefan, N., Schick, F., & Häring, H.-U.
Affiliations
Helmholtz Munich (DE)
Corresponding author
  • Stefan, Norbert
  • Häring, Hans-Ulrich
ORCID
Venue
Cell Metabolism
Publisher
Elsevier BV
Published
2017-08
Volume
26
Issue
2
Pages
292-300
ISSN
1550-4131 (ISSN-L)
DOI
10.1016/j.cmet.2017.07.008
OpenAlex
W2741982109
Cited by
575
References
0
Citations by year
2026: 50 · 2025: 53 · 2024: 58 · 2023: 60 · 2022: 99 · 2021: 76 · 2020: 88 · 2019: 40 · 2018: 40 · 2017: 10
FWCI
7.10
Type
journal article
Language
en
Open access
Licence
Locations
  • Cell Metabolism (publishedVersion)
  • PubMed (publishedVersion)
  • Site cant be reached (submittedVersion)
  • PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion)
Funders
  • Deutsche Forschungsgemeinschaft (KFO 114, STE 1096/1-3)
  • Bundesministerium für Bildung und Forschung
Topics
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adipokines, Inflammation, and Metabolic Diseases
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Disease and Adiposity
Keywords
metabolically unhealthy normal weight, metabolic health, cardiometabolic disease, all-cause mortality, cardiovascular risk, adiposity, risk phenotypes, molecular mechanisms, disease prevention, treatment options
MeSH terms
Female, Heart Diseases, Humans, Male, Metabolic Diseases, Risk Factors, Body Mass Index, Adiposity

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