CoChat
Sign Up
Cited by 90Adipokines, Inflammation, and Metabolic DiseasesCardiovascular Disease and AdiposityAdipose Tissue and Metabolism

The pathophysiology of abdominal adipose tissue depots in health and disease

Open access
Walker, Gillian E., Marzullo, Paolo, Ricotti, Roberta, Bona, Gianni, Prodam, Flavia·2014·Hormone Molecular Biology and Clinical Investigation
DOI 10.1515/hmbci-2014-0023
Open this paper in CoChat — free accountOpen PDF

Abstract

Obesity is currently the most important contributor to ill health and expenditure worldwide. More alarming is the fact that the pediatric population parallels adults, with obesity closely associated to type 2 diabetes mellitus (T2D), cardiovascular disease, hypertension, non-alcoholic fatty liver disease, vitamin D deficiency (VDD) and certain types of cancer. The observation in the early 1950s that android or truncal adipose tissue (AT) distribution compared to gynoid had a greater association with metabolic dysfunction, in particular T2D and cardiovascular disease risk, led to the hypothesis that obesity-associated complications are not associated with fat mass per se, but the pattern of fat distribution. This concept was further supported by groups of individuals with metabolic dysfunction despite a lean phenotype, and healthy obese people protected from metabolic dysfunction. It is now well recognized that an increase in visceral AT is an independent risk factor for the development of obesity-associated comorbidities with AT depot distribution, their anatomic, cellular and molecular features defining their role. The differences and the plasticity of subcutaneous, visceral and ectopic ATs to store and release fatty acids and to synthesize and secrete adipokines, defines the metabolic outcomes. The present review will examine the phenotypic and pathophysiological differences between the different AT depots, with a particular focus on the abdominal depots and their link to metabolic complications.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1515/hmbci-2014-0023

Cites

164 of 164 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 26

  1. [3]3. Levy-Marchal C, Arslanian S, Cutfield W, Sinaiko A, Druet C, Marcovecchio ML, Chiarelli F; ESPE-LWPES-ISPAD-APPESAPEG-SLEP-JSPE; Insulin Resistance in Children Consensus Conference Group. Insulin resistance in children: consensus, perspective, and future directions. J Clin Endocrinol Metab 2010;95:5189-98.
  2. [5]5. Giordano A, Smorlesi A, Frontini A, Barbatelli G, Cinti S. White, brown and pink adipocytes: the extraordinary plasticity of the adipose organ. Eur J Endocrinol 2014;170:R159-71.
  3. [14]14. Ruderman NB, Schneider SH, Berchtold P. The 'metabolicallyobese,' normal-weight individual. Am J Clin Nutr 1981;34:1617-21.
  4. [16]16. Kitahara CM, Flint AJ, Berrington de Gonzalez A, Bernstein L, Brotzman M, MacInnis RJ, Moore SC, Robien K, Rosenberg PS, Singh PN, Weiderpass E, Adami HO, Anton-Culver H, Ballard-Barbash R, Buring JE, Freedman DM, Fraser GE, Beane ­ Freeman LE, Gapstur SM, Gaziano JM, Giles GG, Håkansson N, Hoppin JA, Hu FB, Koenig K, Linet MS, Park Y, Patel AV, Purdue MP, Schairer C, Sesso HD, Visvanathan K, White E, Wolk A, Zeleniuch-Jacquotte A, Hartge P. Association between class III obesity (BMI of 40-59 kg/m 2 ) and mortality: a pooled analysis of 20 prospective studies. PLoS Med 2014;11:e1001673.
  5. [17]17. Britton KA, Fox CS. Ectopic fat depots and cardiovascular disease. Circulation 2011;124:e837-41.
  6. [24]24. Beechy L, Galpern J, Petrone A, Das SK. Assessment tools in obesity - psychological measures, diet, activity, and body composition. Physiol Behav 2012;107:154-71.
  7. [25]25. Shah NR, Braverman ER. Measuring adiposity in patients: the utility of body mass index (BMI), percent body fat, and leptin. PLoS One 2012;7:e33308.
  8. [29]29. Camhi SM, Bray GA, Bouchard C, Greenway FL, Johnson WD, Newton RL, Ravussin E, Ryan DH, Smith SR, Katzmarzyk PT. (The relationship of waist circumference and BMI to visceral, subcutaneous, and total body fat: sex and race differences. Obesity (Silver Spring) 2011;19:402-8.
  9. [30]30. Lim U, Turner SD, Franke AA, Cooney RV, Wilkens LR, Ernst T, Albright CL, Novotny R, Chang L, Kolonel LN, Murphy SP, Le Marchand L. Predicting total, abdominal, visceral and hepatic adiposity with circulating biomarkers in caucasian and japanese american women. PLoS One 2012;7:e43502.
  10. [34]34. Ross R, Janssen I. Computer tomography and magnetic resonance imaging. In: Heymsfield SB, Lohman TG, Wang Z, Going S, editors. Human Body Composition, 2nd ed. Champaign, IL: Human Kinetics Press, 2005:89-108.
  11. [36]36. Napolitano A, Miller SR, Murgatroyd PR, Coward WA, Wright A, Finer N, De Bruin TW, Bullmore ET, Nunez DJ. Validation of a quantitative magnetic resonance method for measuring human body composition. Obesity 2008;16:191-8.
  12. [44]44. Sepe A, Tchkonia T, Thomou T, Zamboni M, Kirkland JL. Aging and regional differences in fat cell progenitors - a mini-review. Gerontology 2011;57:66-75.
  13. [55]55. Spalding KL, Arner E, Westermark PO, Bernard S, Buchholz BA, Bergmann O, Blomqvist L, Hoffstedt J, Näslund E, Britton T, Concha H, Hassan M, Rydén M, Frisén J, Arner P.Dynamics of fat cell turnover in humans. Nature 2008;453:783-7.
  14. [56]56. Jo J, Gavrilova O, Pack S, Jou W, Mullen S, Sumner AE, ­ Cushman SW, Periwal V. Hypertrophy and/or hyperplasia: dynamics of adipose tissue growth. PLoS Comput Biol 2009;5:e1000324.
  15. [77]77. Wang WZ, Fang XH, Williams SJ. Analysis of apotosis and necrosis on adipocytes, stromal vascular fraction and adiposederived stem cells in human lipoaspirates after liposuction. Plast Reconstr Surg 2012;131:77e-85e.
  16. [96]96. Kuk JL, Saunders TJ, Davidson LE, Ross R. Age-related changes in total and regional fat distribution. Ageing Res Rev 2009;8:339-48.
  17. [105]105. Snijder MB, Visser M, Dekker JM, Goodpaster BH, Harris TB, Kritchevsky SB, De Rekeneire N, Kanaya AM, Newman AB, Tylavsky FA, Seidell JC; Health ABC Study. Low subcutaneous thigh fat is a risk factor for unfavourable glucose and lipid levels, independently of high abdominal fat. The Health ABC Study. Diabetologia 2005;48:301-8.
  18. [124]124. Strawford A, Antelo F, Christiansen M, Hellerstein MK. Adipose tissue triglyceride turnover, de novo lipogenesis, and cell proliferation in humans measured with 2H2O. Am J Physiol Endocrinol Metab 2004;286:E577-88.
  19. [133]133. Ruderman NB, Saha AK, Kraegen EW. Minireview: malonyl CoA, AMP-activated protein kinase, and adiposity. Endocrinology 2003;144:5166-71.
  20. [134]134. Garrido-Sánchez L, Vendrell J, Fernández-García D, ­ Ceperuelo-Mallafré V, Chacón MR, Ocaña-Wilhelmi L, Alcaide J, ­ Tinahones FJ, García-Fuentes E. De novo lipogenesis in adipose tissue is associated with course of morbid obesity after bariatric surgery. PLoS One 2012;7:e31280.
  21. [135]135. Gathercole LL, Morgan SA, Bujalska IJ, Hauton D, Stewart PM, Tomlinson JW. Regulation of lipogenesis by glucocorticoids and insulin in human adipose tissue. PLoS One 2011;6:e26223.
  22. [141]141. Halaas JL, Gajiwala KS, Maffei M, Cohen SL, Chait BT, ­ Rabinowitz D, Lallone RL, Burley SK, Friedman JM. Weightreducing effects of the plasma protein encoded by the obese gene. Science 1995;269:543-46.
  23. [150]150. He G, Pedersen SB, Bruun JM, Lihn AS, Jensen PF, Richelsen B. Differences in plasminogen activator inhibitor 1 in subcutaneous versus omental adipose tissue in non-obese and obese subjects. Horm Metab Res 2003;35:178-82.
  24. [166]166. Halvorsen YD, Wilkison WO, Briggs MR. Human adipocyte proteomics-a complementary way of looking at fat. Pharmacogenomics 2000;1:179-85.
  25. [178]178. Mariman EC, Wang P. Adipocyte extracellular matrix composition, dynamics and role in obesity. Cell Mol Life Sci 2010;67:1277-92.
  26. [181]181. Gehrke S, Brueckner B, Schepky A, Klein J, Iwen A, Bosch TC, Wenck H, Winnefeld M, Hagemann S. Epigenetic regulation of depot-specific gene expression in adipose tissue. PLoS One 2013;8:e82516.

Cited by

Sorted by citations

Related

Authors
Walker, G. E., Marzullo, P., Ricotti, R., Bona, G., & Prodam, F.
Affiliations
  • Università degli Studi del Piemonte Orientale “Amedeo Avogadro” (IT)
  • IRCCS Istituto Auxologico Italiano (IT)
Corresponding author
Walker, Gillian E.
ORCID
Venue
Hormone Molecular Biology and Clinical Investigation
Publisher
Walter de Gruyter GmbH
Published
2014-07-01
Volume
19
Issue
1
Pages
57-74
ISSN
  • 1868-1883 (ISSN-L)
  • 1868-1891
DOI
10.1515/hmbci-2014-0023
OpenAlex
W2067204155
Cited by
90
References
164
Citations by year
2026: 1 · 2025: 4 · 2024: 8 · 2023: 6 · 2022: 8 · 2021: 10 · 2020: 4 · 2019: 8 · 2018: 7 · 2017: 8 · 2016: 14 · 2015: 12
FWCI
1.51
Type
journal article
Language
en
Open access
Locations
  • Hormone Molecular Biology and Clinical Investigation (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Epidemiology › Adipokines, Inflammation, and Metabolic Diseases
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Disease and Adiposity
  • Health Sciences › Medicine › Physiology › Adipose Tissue and Metabolism
Keywords
abdominal fat, visceral adipose tissue, subcutaneous adipose tissue, ectopic fat, obesity, type 2 diabetes, adipokines, metabolic dysfunction, cardiovascular disease, non-alcoholic fatty liver disease, vitamin D deficiency
MeSH terms
Cardiovascular Diseases, Diabetes Mellitus, Type 2, Humans, Insulin Resistance, Obesity, Risk Factors, Abdominal Fat

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review