Adipose tissue and metabolic alterations: regional differences in fat cell size and number matter, but differently: a cross-sectional study.
Abstract
OBJECTIVE: White adipose tissue can expand by increasing the size and/or number of fat cells. Although increased sc and visceral fat cell size associates with an adverse metabolic profile, the relationship with fat cell number in either depot is unknown. We hypothesized that adipocyte number and size displayed different relationships with clinically relevant metabolic variables. METHODS: This was a cross-sectional study of 204 patients scheduled for gastric bypass surgery. Fat cell size and number were determined in visceral and abdominal sc adipose tissue and related to insulin sensitivity (by hyperinsulinemic euglycemic clamp), fasting plasma levels of insulin, triglycerides and high-density lipoprotein (HDL) cholesterol. RESULTS: Visceral and sc fat cell volumes were positively correlated with insulin and triglyceride levels and negatively with insulin sensitivity and HDL-cholesterol (P = .0020 or better). In contrast, although visceral fat cell number did not associate with any metabolic parameter, sc adipocyte number displayed a positive association with insulin sensitivity and HDL-cholesterol and a negative relationship with insulin and triglyceride levels (P = .0014 or better). All results were independent of body fat mass. CONCLUSIONS: Variations in fat cell size and number correlate differently with metabolic parameters in obesity. Increased fat cell size in visceral and sc depots associates with a pernicious metabolic profile, whereas increased sc, but not visceral, fat cell number correlates with a more beneficial phenotype. Whether determination of sc fat cell number, in addition to adipocyte size, may have a predictive value for the risk of type 2 diabetes needs to be demonstrated in prospective or mechanistic studies.
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Written from the paper’s full text.
TL;DR
In 204 patients undergoing gastric bypass, visceral and subcutaneous fat cell volume associated with a worse metabolic profile, while subcutaneous fat cell number associated with a more favorable insulin/lipid profile. These relationships were independent of total body fat mass, but the cross-sectional design cannot establish causality.
Key findings
- Visceral and subcutaneous fat cell volume correlated positively with plasma insulin and triglycerides and negatively with insulin sensitivity and HDL-cholesterol (P = .0020 or better). For example, visceral fat cell volume vs plasma insulin: r = 0.45, P < .0001; vs insulin sensitivity: r = −0.42, P < .0001.
- Visceral fat cell number did not associate with any studied metabolic parameter (e.g., plasma insulin r = −0.080, P = .28; insulin sensitivity r = −0.0038, P = .96).
- Subcutaneous fat cell number showed the opposite pattern from fat cell volume: positive with insulin sensitivity (r = 0.25, P = .0014) and HDL-cholesterol (r = 0.29, P < .0001), negative with plasma insulin (r = −0.26, P = .0003) and triglycerides (r = −0.35, P < .0001).
- In multiple linear regression corrected for total body fat, subcutaneous fat cell number remained associated with plasma insulin (Std β = −0.34, P < .0001), insulin sensitivity (Std β = 0.31, P = .0002), triglycerides (Std β = −0.38, P < .0001), and HDL-cholesterol (Std β = 0.35, P < .0001).
Methods
- Cross-sectional study of 204 patients referred for Roux-en-Y gastric bypass surgery (age 18–60 years; BMI >30 kg/m² with obesity-related complications or BMI >35 kg/m²); ESAT/EVAT values were obtainable from 188 subjects.
- Abdominal subcutaneous fat biopsy was obtained by needle aspiration, and visceral fat biopsy from the greater omentum during surgery. Fat cell size was determined by measuring 100 isolated adipocytes; fat cell number was estimated from depot weight divided by mean fat cell weight.
- Insulin sensitivity was measured by hyperinsulinemic-euglycemic clamp; fasting plasma insulin, triglycerides, and HDL-cholesterol were measured. DEXA with CoreScan estimated visceral and subcutaneous abdominal fat masses. Analyses used Spearman correlation, ANCOVA, and multiple linear regression, with Bonferroni correction.
Limitations
- The paper states that correlations ranged from −0.5 to +0.5, suggesting relatively large interindividual differences in adipocyte size/number are needed to observe metabolic differences; the cohort was rather homogeneous, predominantly women, and larger studies including normal-weight subjects and more men might yield different or stronger correlations.
- The paper states that fat cell number is calculated from two independent parameters (depot size and mean adipocyte weight), so determinations are only relevant for ESAT and EVAT; DEXA/CoreScan measures are indirect, and no visceral adipose tissue phantom was used for calibration.
- The paper states that only a limited set of metabolic phenotypes was studied, the cohort included T2DM and/or hypertension with gender imbalance, and predictive/causal relationships require prospective or mechanistic validation. Evident from the text: the cross-sectional design cannot establish causality, and the bariatric-surgery population may not represent obese individuals in the general population.
Model-written summary. Check it against the paper before relying on it.
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Claims the paper makes
0 of 37 cited sources checked · 0 supported · 0 flagged
- Findingown data
When corrected for gender, diabetes, or hypertension, the observed correlations remained statistically significant with nominal P values < .05.
“Nevertheless, when corrected for gender, diabetes, or hypertension, the observed correlations remained statistically significant with nominal P values Ͻ .05.”
Quote in the paperSubstantial claim - Findingown data
The same correlations remained significant if the Bonferroni correction was used (allowing P < .0042 to be significant).
“The same was true if the Bonferroni correction was used (allowing P Ͻ .0042 to be significant).”
Quote in the paperSubstantial claim - Findingown data
In subcutaneous adipose tissue of obese subjects, fat cell volume showed correlations with insulin sensitivity and plasma levels of insulin, triglycerides, and HDL-cholesterol that were similar to those of visceral fat cell volume.
“In sc adipose tissue, similar correlations were observed regarding fat cell volume as for visceral adipose tissue (Table 2 and Figure 2).”
Quote in the paperSubstantial claim - Findingown data
After Bonferroni correction of P values in Table 2 (16 comparisons allowing P < .0031 to be significant), all significant correlations remained.
“After Bonferroni correction of P values in Table 2 (16 comparisons allowing P Ͻ .0031 to be significant), all significant correlations remained.”
Quote in the paperSubstantial claim - Findingown data
All correlations between subcutaneous fat cell volume/number, visceral adipocyte volume, and metabolic variables remained statistically significant after correction for total body fat in kilograms.
“All correlations remained statistically significant after correction for total body fat expressed in kilograms (or as percentage of total body weight, values not shown).”
Quote in the paperSubstantial claim
- Findingown data
In visceral adipose tissue of obese subjects, fat cell number was not significantly correlated with insulin sensitivity or plasma levels of insulin, triglycerides, or HDL-cholesterol.
“In visceral adipose tissue, fat cell volume, but not number, correlated significantly with insulin sensitivity and plasma levels of insulin, triglycerides, or HDL-cholesterol.”
Quote in the paperSubstantial claim - Findingown data
In visceral adipose tissue of obese subjects, fat cell volume was significantly correlated with insulin sensitivity and plasma levels of insulin, triglycerides, and HDL-cholesterol.
“In visceral adipose tissue, fat cell volume, but not number, correlated significantly with insulin sensitivity and plasma levels of insulin, triglycerides, or HDL-cholesterol.”
Quote in the paperSubstantial claim - Premisecitation
It is well established that a phenotype characterized by large (hypertrophic) adipocytes is associated with hyperinsulinemia, insulin resistance, and dyslipidemia.
“It is well established that a phenotype characterized by large (hypertrophic) adipocytes, is associated with hyperinsulinemia, insulin resistance, and dyslipidemia (14 -18).”
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- Interpretationown data
Variations in fat cell size and number correlate differently with metabolic parameters in obesity.
“Variations in fat cell size and number correlate differently with metabolic parameters in obesity.”
Quote in the paperSubstantial claim - Interpretationown data
Fat cell size and number, independently of body fat mass, associate differently with metabolic parameters in obese subjects.
“In conclusion, this study shows that fat cell size and number, independently of body fat mass, associate differently with metabolic parameters in obese subjects.”
Quote in the paperSubstantial claim - Interpretationown data
Large fat cells in both subcutaneous and visceral adipose tissue are associated with a more pernicious metabolic phenotype.
“Large fat cells in both sc and visceral adipose tissue are associated with a more pernicious metabolic phenotype.”
Quote in the paperSubstantial claim - Interpretationown data
The size and number of fat cells in different adipose depots play different roles in obesity-associated metabolic complications.
“These relationships, which were independent of total body fat mass, suggest that the size and number of fat cells in different adipose depots play different roles in obesity-associated metabolic complications.”
Quote in the paperSubstantial claim - Interpretationreasoning
The determinations of adipose cellularity in this study are only relevant for estimated subcutaneous abdominal adipose tissue (ESAT) and estimated visceral adipose tissue (EVAT).
“that our determinations of adipose cellularity are only relevant for ESAT and EVAT”
Quote in the paperSubstantial claim - Interpretationreasoning
The number of fat cells is not a simple function of fat cell diameter.
“that the number of fat cells is not a simple function of fat cell diameter.”
Quote in the paperSubstantial claim - Premisecitation
When the size limit is reached, the tissue must generate more fat cells to be able to expand further.
“When this size limit is reached, the tissue must generate more fat cells to be able to expand further (13,32).”
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- Premisecitation
Determination of EVAT with this method shows a strong correlation (r2 ≥ 0.95) with measures using computed tomography (CT).
“Determination of EVAT with this method shows a strong correlation (r 2 Ն 0.95) with measures using computed tomography (CT) (21).”
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- Premisecitation
Fat cell volume in adult humans cannot become larger than approximately 1400 pL.
“As measured with the method adopted in the present study, fat cell volume in adult humans cannot become larger than ϳ1400 pL (33).”
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- Premisecitation
Total fat cell number is approximately doubled in obese compared with age- and gender-matched lean subjects.
“This is supported by the observation that total fat cell number is approximately doubled in obese compared with ageand gender-matched lean subjects (33).”
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- Interpretationreasoning
The subjects studied could therefore in theory not be representative for obese individuals in the general population.
“The subjects studied herein could therefore in theory not be representative for obese individuals in the general population.”
Quote in the paperNot a substantial claim - Premisecitation
Several studies have shown that the association between large adipocytes and metabolic abnormalities is independent of body fatness as measured by BMI.
“Several of these studies have shown that this association is independent of body fatness as measured by body mass index (BMI) (14,15,17,18).”
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- Premisecitation
Two prospective studies have confirmed that adipose hypertrophy is associated with increased risk for developing T2DM, independently of BMI.
“Two prospective studies have confirmed that adipose hypertrophy is associated with increased risk for developing T2DM, independently of BMI (19,20).”
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- Interpretationcitation
Visceral adipose expansion may primarily be determined by increased adipocyte number.
“suggesting that visceral adipose expansion may primarily be determined by increased adipocyte number.”
Quote in the paperSubstantial claim - Interpretationcitation
Taken together, these data strongly suggest that the amount or distribution of adipose tissue is not per se of major importance for the development of T2DM in obesity.
“Taken together, these data strongly suggest that the amount or distribution of adipose tissue is not per se of major importance for the development of T2DM in obesity.”
Quote in the paperSubstantial claim - Premisecitation
The precision of the CoreScan tool to measure visceral adipose tissue mass has been estimated and shown to have relatively low error in both phantoms and obese women.
“However, the precision of the CoreScan tool to measure visceral adipose tissue mass has recently been estimated and shown to have relatively low error in both phantoms and obese women (35).”
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- Premisecitation
The average fat cell volume is better approximated by using the formula (where is mean diameter and is SD) than by arithmetic mean of d3.
“As previously discussed (24,25), the diameter (d) is a normally distributed variable but its cube (d 3 ) is skewed and the arithmetic mean of d 3 can therefore not be used to calculate mean fat cell volume.The average fat cell volume is instead much better approximated by using the formula (where is the mean diameter and is the standard deviation of the diameter).”
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- Premisecitation
Counting 100 or 300 cells by microscopy is a reliable estimate of fat cell size comparable with manual or automated image analysis software.
“The diameters were distributed in a unimodal way, and it has been shown in several independent studies that counting 100 or 300 cells by microscopy is a reliable estimate of fat cell size that is comparable with results obtained using either manual or automated image analysis software (23).”
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- May combine two claims. 17
- Classified as probably not a substantial claim. 21
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Findingown dataIn subcutaneous adipose tissue of obese subjects, fat cell number was positively related to insulin sensitivity and HDL-cholesterol and negatively related to insulin and triglycerides.
“Thus, there was a positive relationship with insulin sensitivity and HDL-cholesterol and a negative relationship with insulin and triglycerides.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn subcutaneous adipose tissue of obese subjects, fat cell number was significantly correlated with all studied metabolic variables, but in the opposite direction to fat cell volume.
“In contrast, although sc fat cell number correlated significantly with all variables, it did so in an opposite way compared with cell volume (Table 2 and Figure 2).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataNumerically similar correlations and P values were obtained if insulin sensitivity was corrected for lean body mass.
“Furthermore, numerically similar and P values were obtained if insulin sensitivity was corrected for LBM (M/LBM, values not shown).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable). May combine two claims.
InterpretationreasoningThe present study suggests that classifying overweight/obese patients according to their fat cell size and number might be clinically useful to estimate the risk of T2DM and related metabolic complications and thereby determine treatment strategies, at least in specialized clinics.
“The present study suggest that classifying overweight/obese patients according to their fat cell size and number might be clinically useful to estimate the risk of T2DM and related metabolic complications and thereby determine treatment strategies, at least in specialized clinics.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataIncreased subcutaneous or visceral fat cell size correlates with an adverse insulin/lipid profile, whereas increased subcutaneous fat cell number is coupled to a less pernicious phenotype.
“Increased sc or visceral fat cell size correlates with an adverse insulin/lipid profile, whereas increased sc fat cell number is coupled to a less pernicious phenotype.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataIn abdominal subcutaneous fat, more adipocytes is related to a more favorable state, whereas fat cell number in the visceral depot does not correlate with any of the studied metabolic parameters.
“In abdominal sc fat, more adipocytes is related to a more favorable state, whereas fat cell number in the visceral depot does not correlate with any of the studied metabolic parameters.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAdipose inflammation has emerged as an important factor contributing to insulin resistance.
“Adipose inflammation has emerged as an important factor contributing to insulin resistance (27).”
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PremisecitationIt is relatively easy to measure fat cell size in small subcutaneous needle biopsies.
“It is relatively easy to measure fat cell size in small sc needle biopsies (40), and fat mass in different regions can be assessed by DEXA, with the use of recently developed software.”
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Premisenone givenFat mass in different regions can be assessed by DEXA with recently developed software.
“It is relatively easy to measure fat cell size in small sc needle biopsies (40), and fat mass in different regions can be assessed by DEXA, with the use of recently developed software.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenOne subject was examined using different DEXA equipment, and in one individual, DEXA measurements were missing.
“One subject was examined using different DEXA equipment, and in one individual, DEXA measurements were missing.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenA limitation of the study is that no visceral adipose tissue phantom was used for calibrations.
“Nevertheless, a limitation of our study is that no visceral adipose tissue phantom was used for calibrations.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductreasoningThe cohort included participants with non-insulin-dependent diabetes and/or hypertension, and there was a clear imbalance in gender.
“Moreover, our cohort included participants with non-insulin-dependent diabetes (T2DM) and/or hypertension, and there was a clear imbalance in gender.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationAdipocyte size correlates closely with the expression and secretion of the proinflammatory cytokine TNFα in lean healthy women and with insulin resistance/hyperlipidemia in morbidly obese women.
“Interestingly, adipocyte size correlates closely with the expression and secretion of the proinflammatory cytokine TNF␣ in lean healthy women (28) and insulin resistance/hyperlipidemia in morbidly obese women (14).”
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PremisecitationThe capacity of adipose tissue to store lipids is limited.
“A related possibility explaining the association between adipose cellularity and metabolic changes may be that the capacity of adipose tissue to store lipids is limited (32).”
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Study design and conductnone givenThe subjects were scanned using standard imaging and positioning protocols and the same scan mode (set for obese subjects) was used throughout the study.
“The subjects were scanned using standard imaging and positioning protocols and the same scan mode (set for obese subjects) was used throughout the study.”
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PremisecitationUp to one-third of overweight or obese subjects are metabolically healthy.
“Up to one-third of overweight or obese subjects are metabolically healthy (37).”
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Study design and conductown dataIn multiple regression analyses, normal distribution of residual error was determined using Shapiro-Wilk W test and constant variance checked.
“In the multiple regression analyses, normal distribution of the residual error was determined using the Shapiro-Wilk W test and the constant variance of the errors was further checked by rando/mLy distributed patterns in residual-by-predicted plots.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductcitationThe study validated the DEXA CoreScan method in an independent cohort of obese women and men, comparing the weight of the greater omentum with visceral adipose tissue mass estimated using DEXA and CT.
“We subsequently validated this in an independent cohort of obese women and men, comparing the weight of the greater omentum with visceral adipose tissue mass estimated using the presently used DEXA equipment/software and CT (22).”
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PremisecitationIt has been suggested that the classical categorization of body fat status based on BMI and adipose distribution is insufficient.
“It has been suggested that the classical categorization of body fat status based on BMI and adipose distribution is insufficient (36).”
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PremisecitationSurgical removal of large amounts of abdominal subcutaneous adipose tissue from obese patients does not improve insulin resistance or other metabolic abnormalities.
“Furthermore, surgical removal of large amounts of abdominal sc adipose tissue from obese patients does not improve insulin resistance or other metabolic abnormalities (7, 8).”
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Study design and conductnone givenThe Bonferroni test was used to correct for multiple comparison statistics in Tables 2 and 3.
“The Bonferroni test was used to correct for multiple comparison statistics in Tables 2 and 3.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenNo hardware or software changes were made during the course of the trial.
“No hardware or software changes were made during the course of the trial.”
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Study design and conductnone givenAutomatic calibration checks of the DEXA were performed daily, and thrice-weekly calibrations using a spine phantom were performed.
“Automatic calibration checks of the DEXA were performed daily throughout the study, and thrice-weekly calibrations using a spine phantom (for bone mineral density, provided by the manufacturer) were performed.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataIn total, 204 subjects were included in the study where ESAT/EVAT values from 188 subjects could be obtained.
“In total, 204 subjects were included in the study where ESAT/EVAT values from 188 subjects could be obtained.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataIn 14 patients, EVAT and ESAT values could not be measured because of severe obesity.
“In 14 patients, EVAT and ESAT values could not be measured because of the severe obesity.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationSubjects with many small subcutaneous fat cells displayed lower TNFα secretion and better insulin sensitivity.
“In these studies, subjects with many small sc fat cells displayed lower TNF␣ secretion and better insulin sensitivity, respectively.”
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PremisecitationWhen adipose expansion reaches a maximum, lipids are stored ectopically in skeletal muscle, liver, and pancreatic islets, which leads to lipotoxic effects including abnormal lipoprotein metabolism, insulin dysfunction, and altered insulin secretion.
“Consequently, when adipose expansion reaches a maximum, lipids are stored ectopically in skeletal muscle, liver, and pancreatic islets, which in turn leads to lipotoxic effects including abnormal lipoprotein metabolism, insulin dysfunction, and altered insulin secretion.”
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Study design and conductcitationFat cell volume and weight were determined using a standard method in the field.
“Fat cell volume and weight were determined using a standard method in the field that has been described in detail previously (14,22).”
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PremisecitationThe association between body fat distribution and insulin resistance/T2DM is controversial.
“Furthermore, the association between body fat distribution and insulin resistance/T2DM is controversial (38,39).”
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InterpretationreasoningBecause only total android fat mass and EVAT are used to determine ESAT and both are valid measures, the calculation of ESAT should be valid.
“Because only total android fat mass and EVAT are used to determine ESAT and both are valid measures, it follows that also the calculation of ESAT should be valid.”
Quote in the paperSubstantial claim
The paper relies on this without support.
The relationship between adipocyte number and insulin resistance and other metabolic variables associated with T2DM risk was unknown at the time of the study.
“However, the relationship between adipocyte number and insulin resistance as well as other metabolic variables associated with T2DM risk is unknown.”
The authors state this as an assumption.
Mean fat cell weight can be obtained by multiplying fat cell volume by 0.915, assuming fat cell density equals that of human adipose triglycerides.
“Assuming a mean density of fat cells equal to that of human adipose triglycerides, mean fat cell weight was obtained by multiplying the volume by 0.915 (ie, the density in grams per milliliter of triolein).”
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?
AT content and function differ markedly between obese and healthy lean people, regardless of localization.
“Regardless of its localization, AT content and function differ markedly between obese and healthy lean people”
From Effect of Exercise Training on Fat Loss—Energetic Perspectives and the Role of Improved Adipose Tissue Function and Body Fat Distribution (2021) · cites this paper as Rydén et al., 2014
The Abstract describes measurements of subcutaneous and visceral fat in obese subjects, but not a comparison with healthy lean people. The Discussion says that including normal-weight subjects might yield different results. I searched for lean and normal-weight comparators; the copy does not establish the claimed difference in adipose-tissue content and function regardless of location. (LLM, conf=0.76)
Experimental — accuracy not yet measured
Cites
Dynamics of fat cell turnover in humans
Spalding, K. L., Arner, E., Westermark, P. O., Bernard, S., Buchholz, B. A., Bergmann, O., Blomqvist, L., Hoffstedt, J., Näslund, E., Britton, T., et al. (2008) · Nature · doi:10.1038/nature06902 · Cited by 2,357 · see citing works
Self-citationBariatric Surgery versus Conventional Medical Therapy for Type 2 Diabetes
Mingrone, G., Panunzi, S., De Gaetano, A., Guidone, C., Iaconelli, A., Leccesi, L., Nanni, G., Pomp, A., Castagneto, M., Ghirlanda, G., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1200111 · Cited by 1,791 · see citing works
Krotkiewski, M., Björntorp, P. A., Sjöström, L., & Smith, U. (1983) · Journal of Clinical Investigation · doi:10.1172/jci111040 · Cited by 1,448 · see citing works
Gloy, V. L., Briel, M., Bhatt, D. L., Kashyap, S. R., Schauer, P. R., Mingrone, G., Bucher, H. C., & Nordmann, A. J. (2013) · BMJ · doi:10.1136/bmj.f5934 · Cited by 1,351 · see citing works
Adipose tissue expandability, lipotoxicity and the Metabolic Syndrome — An allostatic perspective
Virtue, S., & Vidal-Puig, A. (2010) · Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids · doi:10.1016/j.bbalip.2009.12.006 · Cited by 1,013 · see citing works
Absence of an Effect of Liposuction on Insulin Action and Risk Factors for Coronary Heart Disease
Klein, S., Fontana, L., Young, V. L., Coggan, A. R., Kilo, C., Patterson, B. W., & Mohammed, B. S. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa033179 · Cited by 909 · see citing works
Methods for the determination of adipose cell size in man and animals
Hirsch, J., & Gallian, E. (1968) · Journal of Lipid Research · doi:10.1016/s0022-2275(20)43151-7 · Cited by 894 · see citing works
Weyer, C., Foley, J. E., Bogardus, C., Tataranni, P. A., & Pratley, R. E. (2000) · Diabetologia · doi:10.1007/s001250051560 · Cited by 799 · see citing works
Bariatric surgery and prevention of type 2 diabetes in Swedish obese subjects
Carlsson, L. M. S., Peltonen, M., Ahlin, S., Anveden, Å., Bouchard, C., Carlsson, B., Jacobson, P., Lönroth, H., Maglio, C., Näslund, I., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1112082 · Cited by 794 · see citing works
Adipocyte Turnover: Relevance to Human Adipose Tissue Morphology
Arner, E., Westermark, P. O., Spalding, K. L., Britton, T., Rydén, M., Frisén, J., Bernard, S., & Arner, P. (2010) · Diabetes · doi:10.2337/db09-0942 · Cited by 645 · see citing works
Self-citationDiabetes and obesity: the twin epidemics
Smyth, S., & Heron, A. (2006) · Nature Medicine · doi:10.1038/nm0106-75 · Cited by 643 · see citing works
The distinction of metabolically ‘healthy’ from ‘unhealthy’ obese individuals
Blüher, M. (2010) · Current Opinion in Lipidology · doi:10.1097/mol.0b013e3283346ccc · Cited by 632 · see citing works
Dual‐Energy X‐Ray Absorptiometry for Quantification of Visceral Fat
Kaul, S., Rothney, M. P., Peters, D. M., Wacker, W. K., Davis, C. E., Shapiro, M. D., & Ergun, D. L. (2012) · Obesity · doi:10.1038/oby.2011.393 · Cited by 622 · see citing works
Salans, L. B., Knittle, J. L., & Hirsch, J. (1968) · Journal of Clinical Investigation · doi:10.1172/jci105705 · Cited by 581 · see citing works
Adipose tissue cellularity in human obesity
Hirsch, J., & Batchelor, B. R. (1976) · Clinics in Endocrinology and Metabolism · doi:10.1016/s0300-595x(76)80023-0 · Cited by 441 · see citing works
Arterburn, D. E., Bogart, A., Sherwood, N. E., Sidney, S., Coleman, K. J., Haneuse, S., O’Connor, P. J., Theis, M. K., Campos, G. M., McCulloch, D., et al. (2013) · Obesity Surgery · doi:10.1007/s11695-012-0802-1 · Cited by 426 · see citing works
The Health Risk of Obesity—Better Metrics Imperative
Ahima, R. S., & Lazar, M. A. (2013) · Science · doi:10.1126/science.1241244 · Cited by 384 · see citing works
Point: Visceral Adiposity Is Causally Related to Insulin Resistance
Lebovitz, H. E., & Banerji, M. A. (2005) · Diabetes Care · doi:10.2337/diacare.28.9.2322 · Cited by 328 · see citing works
Fat cell enlargement is an independent marker of insulin resistance and ‘hyperleptinaemia’
Lundgren, M., Svensson, M. K. E., Lindmark, S., Renström, F., Ruge, T., & Eriksson, J. W. (2007) · Diabetologia · doi:10.1007/s00125-006-0572-1 · Cited by 278 · see citing works
Regional impact of adipose tissue morphology on the metabolic profile in morbid obesity
Hoffstedt, J., Arner, E., Wahrenberg, H., Andersson, D. P., Qvisth, V., Löfgren, P., Rydén, M., Thörne, A., Wirén, M., Palmér, M., et al. (2010) · Diabetologia · doi:10.1007/s00125-010-1889-3 · Cited by 246 · see citing works
Self-citationMorphological changes in the adipocyte during fat deposition and mobilization
Goldrick, R. B. (1967) · American Journal of Physiology-Legacy Content · doi:10.1152/ajplegacy.1967.212.4.777 · Cited by 242 · see citing works
Obesity Affects the Liver – The Link between Adipocytes and Hepatocytes
Wree, A., Kahraman, A., Gerken, G., & Canbay, A. E. (2010) · Digestion · doi:10.1159/000318741 · Cited by 216 · see citing works
Fabbrini, E., Tamboli, R. A., Magkos, F., Marks–Shulman, P. A., Eckhauser, A. W., Richards, W. O., Klein, S., & Abumrad, N. N. (2010) · Gastroenterology · doi:10.1053/j.gastro.2010.04.056 · Cited by 207 · see citing works
Adipocyte size predicts incidence of type 2 diabetes in women
Lönn, M., Mehlig, K., Bengtsson, C., & Lissner, L. (2009) · The FASEB Journal · doi:10.1096/fj.09-133058 · Cited by 203 · see citing works
Park, Y.-W., Heymsfield, S., & Gallagher, D. (2002) · International Journal of Obesity · doi:10.1038/sj.ijo.0801982 · Cited by 196 · see citing works
Comparison of two methods for determining human adipose cell size
Smith, U., Sjöström, L., & Björntorp, P. A. (1972) · Journal of Lipid Research · doi:10.1016/s0022-2275(20)39356-1 · Cited by 188 · see citing works
Veilleux, A., Caron-Jobin, M., Noël, S., Laberge, P. Y., & Tchernof, A. (2011) · Diabetes · doi:10.2337/db10-1039 · Cited by 155 · see citing works
Rydén, M., & Arner, P. (2007) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2007.01854.x · Cited by 118 · see citing works
Self-citationA quick, reliable, and automated method for fat cell sizing
Tchoukalova, Y. D., Harteneck, D. A., Karwoski, R. A., Tarara, J. E., & Jensen, M. D. (2003) · Journal of Lipid Research · doi:10.1194/jlr.d300001-jlr200 · Cited by 109 · see citing works
Long-term Effects of Large-volume Liposuction on Metabolic Risk Factors for Coronary Heart Disease
Mohammed, B. S., Cohen, S., Reeds, D., Young, V. L., & Klein, S. (2008) · Obesity · doi:10.1038/oby.2008.418 · Cited by 108 · see citing works
Counterpoint: Visceral Adiposity Is Not Causally Related to Insulin Resistance
Miles, J. M., & Jensen, M. D. (2005) · Diabetes Care · doi:10.2337/diacare.28.9.2326 · Cited by 102 · see citing works
Variations in the Size of the Major Omentum Are Primarily Determined by Fat Cell Number
Arner, P., Andersson, D. P., Thörne, A., Wirén, M., Hoffstedt, J., Näslund, E. B., Thorell, A., & Rydén, M. (2013) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2012-4106 · Cited by 100 · see citing works
Self-citationDynamics of Fat Cell Turnover in Humans
Spalding, K. L., Arner, E., Westermark, P. O., Bernard, S., Buchholz, B. A., Bergmann, O., Blomqvist, L., Hoffstedt, J., Näslund, E. B., Britton, T., et al. (2008) · Obstetrical & Gynecological Survey · doi:10.1097/01.ogx.0000325910.81966.ac · Cited by 99 · see citing works
Self-citationEarly B Cell Factor 1 Regulates Adipocyte Morphology and Lipolysis in White Adipose Tissue
Gao, H., Mejhert, N., Fretz, J. A., Arner, E., Lorente‐Cebrián, S., Ehrlund, A., Dahlman‐Wright, K., Gong, X., Strömblad, S., Douagi, I., et al. (2014) · Cell Metabolism · doi:10.1016/j.cmet.2014.03.032 · Cited by 98 · see citing works
Self-citationRothney, M. P., Xia, Y., Wacker, W. K., Martin, F., Beaumont, M., Rezzi, S., Giusti, V., & Ergun, D. L. (2013) · Obesity · doi:10.1002/oby.20140 · Cited by 84 · see citing works
Herrera, M. F., Pantoja, J. P., Velázquez‐Fernández, D., Cabiedes, J., Aguilar-Salinas, C. A., García‐García, E., Rivas‐Delgado, A., Villeda, C., Hernández‐Ramírez, D. F., Dávila, A. P., et al. (2010) · Diabetes Care · doi:10.2337/dc09-1833 · Cited by 79 · see citing works
Mechanism of Metabolic Advantages After Bariatric Surgery
Knop, F. K., & Taylor, R. (2013) · Diabetes Care · doi:10.2337/dcs13-2032 · Cited by 77 · see citing works
Bariatric Surgery versus Conventional Medical Therapy for Type 2 Diabetes
Ness-Abramof, R. (2012) · Yearbook of Endocrinology · doi:10.1016/j.yend.2012.04.017 · Cited by 73 · see citing works
Tumor Necrosis Factor α and Regulation of Adipose Tissue
Arner, E., Rydén, M., & Arner, P. (2010) · New England Journal of Medicine · doi:10.1056/nejmc0910718 · Cited by 53 · see citing works
Self-citationOmentectomy added to Roux-en-Y gastric bypass surgery: a randomized, controlled trial
Dillard, T. H., Purnell, J. Q., Smith, M. D., Raum, W. J., Hong, D., Laut, J., & Patterson, E. J. (2011) · Surgery for Obesity and Related Diseases · doi:10.1016/j.soard.2011.09.027 · Cited by 50 · see citing works
Andersson, D. P., Thorell, A., Löfgren, P., Wirén, M., Toft, E., Qvisth, V., Risérus, U., Berglund, L., Näslund, E. B., Bringman, S., et al. (2014) · Clinical Nutrition · doi:10.1016/j.clnu.2014.01.004 · Cited by 45 · see citing works
Self-citationAdipokine expression in brown and white adipocytes in response to hypoxia.
Wree, A., Mayer, A., Westphal, S., Beilfuss, A., Canbay, A. E., Schick, R., Gerken, G., & Vaupel, P. W. (2012) · PubMed · doi:10.3275/7964 · Cited by 32 · see citing works
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Metabolically healthy obesity: facts and fantasies
Smith, G. I., Mittendorfer, B., & Klein, S. (2019) · Journal of Clinical Investigation · doi:10.1172/jci129186 · Cited by 655 · see citing works
Lotta, L. A., Gulati, P., Day, F. R., Payne, F., Ongen, H., van de Bunt, M., Gaulton, K. J., Eicher, J. D., Sharp, S. J., Luan, J., et al. (2016) · Nature Genetics · doi:10.1038/ng.3714 · Cited by 587 · see citing works
Impaired adipogenesis and dysfunctional adipose tissue in human hypertrophic obesity
Hammarstedt, A., Gogg, S., Hedjazifar, S., Nerstedt, A., & Smith, U. (2018) · Physiological Reviews · doi:10.1152/physrev.00034.2017 · Cited by 462 · see citing works
Obesity and the risk of cardiometabolic diseases
Valenzuela, P. L., Carrera-Bastos, P., Castillo-García, A., Lieberman, D. E., Santos-Lozano, A., & Lucia, A. (2023) · Nature Reviews Cardiology · doi:10.1038/s41569-023-00847-5 · Cited by 452 · see citing works
Adipose tissue fibrosis, hypertrophy, and hyperplasia: Correlations with diabetes in human obesity
Muir, L. A., Neeley, C. K., Meyer, K. A., Baker, N. A., Brosius, A. M., Washabaugh, A. R., Varban, O. A., Finks, J. F., Zamarron, B. F., Flesher, C. G., et al. (2016) · Obesity · doi:10.1002/oby.21377 · Cited by 367 · see citing works
Macrophage functions in lean and obese adipose tissue
Thomas, D. D., & Apovian, C. M. (2017) · Metabolism · doi:10.1016/j.metabol.2017.04.005 · Cited by 318 · see citing works
Adipose cell size: importance in health and disease
Stenkula, K. G., & Erlanson‐Albertsson, C. (2018) · American Journal of Physiology-Regulatory, Integrative and Comparative Physiology · doi:10.1152/ajpregu.00257.2017 · Cited by 248 · see citing works
Lotta, L. A., Wittemans, L. B. L., Zuber, V., Stewart, I. D., Sharp, S. J., Luan, J., Day, F. R., Li, C., Bowker, N., Cai, L., et al. (2018) · JAMA · doi:10.1001/jama.2018.19329 · Cited by 229 · see citing works
Acosta, J. R., Douagi, I., Andersson, D. P., Bäckdahl, J., Rydén, M., Arner, P., & Laurencikiene, J. (2015) · Diabetologia · doi:10.1007/s00125-015-3810-6 · Cited by 221 · see citing works
Self-citationAdipocyte size as a determinant of metabolic disease and adipose tissue dysfunction
Laforest, S., Labrecque, J., Michaud, A., Cianflone, K., & Tchernof, A. (2015) · Critical Reviews in Clinical Laboratory Sciences · doi:10.3109/10408363.2015.1041582 · Cited by 214 · see citing works
Shao, M., Vishvanath, L., Busbuso, N. C., Hepler, C., Shan, B., Sharma, A. X., Chen, S., Yu, X., An, Y., Zhu, Y. Z., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-03196-x · Cited by 163 · see citing works
Adipose tissue hyperplasia and hypertrophy in common and syndromic obesity-the case of BBS obesity
Horwitz, A., & Birk, R. (2023) · Nutrients · doi:10.3390/nu15153445 · Cited by 143 · see citing works
The pathophysiology of visceral adipose tissues in cardiometabolic diseases
Lee, M., & Kim, J. (2024) · Biochemical Pharmacology · doi:10.1016/j.bcp.2024.116116 · Cited by 137 · see citing works
Liu, F., He, J., Wang, H., Zhu, D., & Bi, Y. (2020) · Obesity Surgery · doi:10.1007/s11695-020-04983-6 · Cited by 115 · see citing works
Kolnes, K. J., Petersen, M. H., Lien-Iversen, T., Højlund, K., & Jensen, J. (2021) · Frontiers in Physiology · doi:10.3389/fphys.2021.737709 · Cited by 112 · see citing works
Ye, R. Z., Richard, G. M., Gévry, N. Y., Tchernof, A., & Carpentier, A. C. (2021) · Endocrine Reviews · doi:10.1210/endrev/bnab018 · Cited by 105 · see citing works
Almuraikhy, S., Kafienah, W., Bashah, M., Diboun, I., Jaganjac, M., Al‐Khelaifi, F., Abdesselem, H., Mazloum, N. A., Alsayrafi, M., Mohamed‐Ali, V., et al. (2016) · Diabetologia · doi:10.1007/s00125-016-4031-3 · Cited by 98 · see citing works
Camastra, S., Vitali, A., Anselmino, M., Gastaldelli, A., Bellini, R., Berta, R., Severi, I., Baldi, S., Astiarraga, B., Barbatelli, G., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-08444-6 · Cited by 93 · see citing works
Association of Epicardial, Visceral, and Subcutaneous Fat With Cardiometabolic Diseases
Sato, F., Maeda, N., Yamada, T., Namazui, H., Fukuda, S., Natsukawa, T., Nagao, H., Murai, J., Masuda, S., Tanaka, Y., et al. (2017) · Circulation Journal · doi:10.1253/circj.cj-17-0820 · Cited by 89 · see citing works
Regulatory mechanisms of the early phase of white adipocyte differentiation: an overview
Audano, M., Pedretti, S., Caruso, D., Crestani, M., Fabiani, E. D., & Mitro, N. (2022) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-022-04169-6 · Cited by 83 · see citing works
miR-30a Remodels Subcutaneous Adipose Tissue Inflammation to Improve Insulin Sensitivity in Obesity
Koh, E.-H., Chernis, N., Saha, P., Xiao, L., Bader, D. A., Zhu, B., Rajapakshe, K., Hamilton, M. P., Liu, X., Perera, D. N., et al. (2018) · Diabetes · doi:10.2337/db17-1378 · Cited by 73 · see citing works
Phenotypic Characterization of Insulin-Resistant and Insulin-Sensitive Obesity
Chen, D., Liess, C., Poljak, A., Xu, A., Zhang, J.-L., Thoma, C., Trenell, M. I., Milner, B., Jenkins, A. B., Chisholm, D. J., et al. (2015) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2015-2712 · Cited by 72 · see citing works
Mechanisms Underlying Type 2 Diabetes Remission After Metabolic Surgery
Pérez‐Pevida, B., Escalada, J., Miras, A. D., & Frühbeck, G. (2019) · Frontiers in Endocrinology · doi:10.3389/fendo.2019.00641 · Cited by 67 · see citing works
Porro, S., Genchi, V. A., Cignarelli, A., Natalicchio, A., Laviola, L., Giorgino, F., & Perrini, S. (2020) · Journal of Endocrinological Investigation · doi:10.1007/s40618-020-01446-8 · Cited by 63 · see citing works
Impaired atrial natriuretic peptide-mediated lipolysis in obesity
Rydén, M., Bäckdahl, J., Petrus, P., Thorell, A., Gao, H., Coué, M., Langin, D., Moro, C., & Arner, P. (2015) · International Journal of Obesity · doi:10.1038/ijo.2015.222 · Cited by 61 · see citing works
Self-citationBays, H. E., Jones, P. H., Jacobson, T. A., Cohen, D. E., Orringer, C. E., Kothari, S. N., Azagury, D. E., Morton, J. M., Nguyen, N. T., Westman, E. C., et al. (2015) · Journal of clinical lipidology · doi:10.1016/j.jacl.2015.12.002 · Cited by 57 · see citing works
White Adipose Tissue Dysfunction: Pathophysiology and Emergent Measurements
Santillana, N., Astudillo-Guerrero, C., D’Espessailles, A., & Cruz, G. (2023) · Nutrients · doi:10.3390/nu15071722 · Cited by 56 · see citing works
Malden, D. E., Lacey, B., Emberson, J., Karpe, F., Allen, N. E., Bennett, D., & Lewington, S. (2019) · Obesity · doi:10.1002/oby.22509 · Cited by 55 · see citing works
Key signaling networks are dysregulated in patients with the adipose tissue disorder, lipedema
Ishaq, M., Bandara, N., Morgan, S., Nowell, C. J., Mehdi, A. M., Lyu, R., McCarthy, D. J., Anderson, D., Creek, D. J., Achen, M. G., et al. (2021) · International Journal of Obesity · doi:10.1038/s41366-021-01002-1 · Cited by 54 · see citing works
Anti-obesity potential of natural methylxanthines
Carrageta, D. F., Dias, T. R., Alves, M. G., Oliveira, P. F., Monteiro, M. P., & Silva, B. M. (2018) · Journal of Functional Foods · doi:10.1016/j.jff.2018.02.001 · Cited by 52 · see citing works
Winkler, T. W., Günther, F., Höllerer, S., Zimmermann, M. E., Loos, R. J. F., Kutalik, Z., & Heid, I. M. (2018) · Nature Communications · doi:10.1038/s41467-018-04124-9 · Cited by 51 · see citing works
Importance of the Microenvironment and Mechanosensing in Adipose Tissue Biology
Lecoutre, S., Lambert, M., Drygalski, K., Dugail, I., Maqdasy, S., Hautefeuille, M., & Clément, K. (2022) · Cells · doi:10.3390/cells11152310 · Cited by 48 · see citing works
Current Knowledge on the Pathophysiology of Lean/Normal-Weight Type 2 Diabetes
Salvatore, T., Galiero, R., Caturano, A., Rinaldi, L., Criscuolo, L., Martino, A. D., Albanese, G., Vetrano, E., Catalini, C., Sardu, C., et al. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms24010658 · Cited by 48 · see citing works
Baldini, F., Fabbri, R., Eberhagen, C., Voci, A., Portincasa, P., Zischka, H., & Vergani, L. (2020) · Life Sciences · doi:10.1016/j.lfs.2020.118812 · Cited by 47 · see citing works
Revisiting the metabolic syndrome: the emerging role of aquaglyceroporins
da Silva, I. V., Rodrigues, J. S., Rebelo, I., Miranda, J., & Soveral, G. (2018) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-018-2781-4 · Cited by 42 · see citing works
Larrick, B., Kim, K., Donkin, S. S., & Teegarden, D. (2018) · Nutrition Research · doi:10.1016/j.nutres.2018.07.004 · Cited by 47 · see citing works
Enhancing adipose tissue plasticity: progenitor cell roles in metabolic health
Lecoutre, S., Rebière, C., Maqdasy, S., Lambert, M., Dussaud, S., Abatan, J. B., Dugail, I., Gautier, E. L., Clément, K., & Marcelin, G. (2025) · Nature Reviews Endocrinology · doi:10.1038/s41574-024-01071-y · Cited by 46 · see citing works
Heterogeneity in Obesity: Genetic Basis and Metabolic Consequences
Sulc, J., Winkler, T. W., Heid, I. M., & Kutalik, Z. (2020) · Current Diabetes Reports · doi:10.1007/s11892-020-1285-4 · Cited by 44 · see citing works
Fano, M. D., Bartolini, D., Tortoioli, C., Vermigli, C., Malara, M., Galli, F., & Murdolo, G. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23105511 · Cited by 44 · see citing works
Abdominal subcutaneous adipose tissue cellularity in men and women
Andersson, D. P., Arner, P., Hogling, D. E., Rydén, M., & Arner, P. (2017) · International Journal of Obesity · doi:10.1038/ijo.2017.148 · Cited by 41 · see citing works
Self-citationPark, J., Huh, J. Y., Oh, J., Kim, J. I., Han, S. M., Shin, K. C., Jeon, Y. G., Choe, S. S., Park, J., & Kim, J. B. (2019) · Genes & Development · doi:10.1101/gad.329557.119 · Cited by 41 · see citing works
Arner, P., Petrus, P., Estève, D., Boulomié, A., Näslund, E. B., Thorell, A., Gao, H., Dahlman, I. A., & Rydén, M. (2018) · International Journal of Obesity · doi:10.1038/s41366-018-0018-0 · Cited by 40 · see citing works
Self-citationIacobini, C., Vitale, M., Haxhi, J., Menini, S., & Pugliese, G. (2024) · Cells · doi:10.3390/cells13090763 · Cited by 38 · see citing works
Winkler, T. W., Günther, F., Höllerer, S., Zimmermann, M. E., Loos, R. J. F., Kutalik, Z., & Heid, I. M. (2018) · Nature Communications · doi:10.1038/s41467-018-05088-6 · Cited by 35 · see citing works
García-Rubio, J., León, J., Redruello-Romero, A., Pavón, E. J., Cozar, A., Tamayo, F., Molina, M. C., Salmerón, J., & Carazo, Á. (2018) · Scientific Reports · doi:10.1038/s41598-018-33488-7 · Cited by 35 · see citing works
Takahara, S., Ferdaoussi, M., Srnic, N., Maayah, Z. H., Soni, S., Migglautsch, A. K., Breinbauer, R., Kershaw, E. E., & Dyck, J. R. B. (2020) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.00737.2020 · Cited by 35 · see citing works
Menikdiwela, K. R., Guimarães, J. P. T., Ramalingam, L., Kalupahana, N. S., Dufour, J. M., Washburn, R. L., & Moustaïd‐Moussa, N. (2021) · Critical Reviews in Biochemistry and Molecular Biology · doi:10.1080/10409238.2021.1925219 · Cited by 35 · see citing works
Wiik, A., Andersson, D. P., Brismar, T. B., Chanpen, S., Dhejne, C., Ekström, T. J., Flanagan, J. N., Holmberg, M., Kere, J., Lilja, M. R., et al. (2018) · Contemporary Clinical Trials Communications · doi:10.1016/j.conctc.2018.04.005 · Cited by 34 · see citing works
Self-citationIL-1β promotes adipogenesis by directly targeting adipocyte precursors
Hofwimmer, K., Souza, J. D. P., Subramanian, N., Vujičić, M., Rachid, L., Méreau, H., Zhao, C., Dror, E., Barreby, E., Björkström, N. K., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-51938-x · Cited by 33 · see citing works
Wenderott, J. K., Flesher, C. G., Baker, N. A., Neeley, C. K., Varban, O. A., Lumeng, C. N.-K., Muhammad, L. N., Yeh, C., Green, P. F., & O’Rourke, R. W. (2020) · Scientific Reports · doi:10.1038/s41598-020-77498-w · Cited by 31 · see citing works
Adipose Tissue Plasticity: A Comprehensive Definition and Multidimensional Insight
Mo, Y.-Y., Han, Y., Xu, S., Jiang, H., Wu, H., Cai, J., Li, L., Bu, Y., Xiao, F., Liang, H., et al. (2024) · Biomolecules · doi:10.3390/biom14101223 · Cited by 28 · see citing works
Omentectomy in Addition to Bariatric Surgery—a 5-Year Follow-up
Andersson, D. P., Hogling, D. E., Bäckdahl, J., Thorell, A., Löfgren, P., Rydén, M., Arner, P., & Hoffstedt, J. (2017) · Obesity Surgery · doi:10.1007/s11695-017-2576-y · Cited by 28 · see citing works
Self-citationUsefulness of surrogate markers to determine insulin action in fat cells
Rydén, M., Andersson, D. P., & Arner, P. (2020) · International Journal of Obesity · doi:10.1038/s41366-020-0592-9 · Cited by 26 · see citing works
Self-citationWu, Y., Chu, N., Huang, Y.-H., Syu, J.-T., & Chang, J. (2015) · Obesity Research & Clinical Practice · doi:10.1016/j.orcp.2015.08.009 · Cited by 25 · see citing works
Camastra, S., & Ferrannini, E. (2022) · Reviews in Endocrine and Metabolic Disorders · doi:10.1007/s11154-021-09708-3 · Cited by 25 · see citing works
Recent developments in lipodystrophy
Melvin, A., Stears, A. J., & Savage, D. B. (2019) · Current Opinion in Lipidology · doi:10.1097/mol.0000000000000613 · Cited by 25 · see citing works
Adipose and Circulating CCL18 Levels Associate With Metabolic Risk Factors in Women
Hogling, D. E., Petrus, P., Gao, H., Bäckdahl, J., Dahlman, I. A., Laurencikiene, J., Acosta, J. R., Ehrlund, A., Näslund, E. B., Kulyté, A., et al. (2016) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2016-2390 · Cited by 24 · see citing works
Self-citationmiR-30a targets gene networks that promote browning of human and mouse adipocytes
Saha, P., Hamilton, M. P., Rajapakshe, K., Putluri, V., Felix, J. B., Masschelin, P. M., Cox, A. R., Bajaj, M., Putluri, N., Coarfa, C., et al. (2020) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.00045.2020 · Cited by 23 · see citing works
Gao, H., Zhong, Y., Ding, Z., Lin, S., Hou, X., Tang, W., Zhou, X., Zou, X., Shao, J., Yang, F., et al. (2021) · Diabetes · doi:10.2337/db21-0392 · Cited by 23 · see citing works
Dias, B. V., Gomes, S. V., Castro, M. L. D. C., Carvalho, L. C. F., Breguez, G. S., de Souza, D. M. S., Ramos, C. D. O., Sant’Ana, M. R., Nakandakari, S. C. B. R., Araújo, C. M., et al. (2022) · Prostaglandins & Other Lipid Mediators · doi:10.1016/j.prostaglandins.2022.106622 · Cited by 23 · see citing works
Bays, H. E., Jones, P. H., Jacobson, T. A., Cohen, D. E., Orringer, C. E., Kothari, S. N., Azagury, D. E., Morton, J. M., Nguyen, N. T., Westman, E. C., et al. (2015) · Journal of clinical lipidology · doi:10.1016/j.jacl.2015.12.003 · Cited by 23 · see citing works
Potential role of aryl hydrocarbon receptor signaling in childhood obesity
Shahin, N. N., Abd-Elwahab, G. T., Tawfiq, A. A., & Abdelgawad, H. M. (2020) · Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids · doi:10.1016/j.bbalip.2020.158714 · Cited by 22 · see citing works
Pereira, M. J., Vranic, M., Kamble, P. G., Jernow, H., Kristófi, R., Holbikova, E., Skrtic, S., Kullberg, J., Svensson, M. K. E., Hetty, S., et al. (2021) · Translational research · doi:10.1016/j.trsl.2021.12.003 · Cited by 20 · see citing works
Roerink, S. H. P. P., Wagenmakers, M. A. E. M., Langenhuijsen, J. F., Ballak, D. B., Rooijackers, H. M. M., d’Ancona, F. C. H., van Dielen, F. M. H., Smit, J. W. A., Plantinga, T. S., Netea-Maier, R. T., et al. (2017) · Obesity · doi:10.1002/oby.21887 · Cited by 20 · see citing works
Arriarán, S., Agnelli, S., Remesar, X., Fernández–Löpez, J., & Alemany, M. (2015) · PeerJ · doi:10.7717/peerj.1399 · Cited by 19 · see citing works
Chen, C. V., Liu, Y., Lee, S., Yang, H., & Chan, W. P. (2019) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.26956 · Cited by 18 · see citing works
Hübers, M., Geisler, C., Bosy‐Westphal, A., Braun, W., Pourhassan, M., Sørensen, T. I. A., & Müller, M. J. (2018) · European Journal of Clinical Nutrition · doi:10.1038/s41430-018-0150-x · Cited by 17 · see citing works
Moreno‐Navarrete, J. M., Rodrı́guez, A., Ortega, F. J., Becerril, S., Sabater, M., Latorre, J., Ricart, W., Frühbeck, G., & Fernández‐Real, J. M. (2017) · Scientific Reports · doi:10.1038/s41598-017-05597-2 · Cited by 16 · see citing works
Wongdokmai, R., Shantavasinkul, P. C., Chanprasertyothin, S., Panpunuan, P., Matchariyakul, D., Sritara, P., & Sirivarasai, J. (2021) · Diabetes Metabolic Syndrome and Obesity · doi:10.2147/dmso.s303146 · Cited by 15 · see citing works
Umbayev, B. A., Saliev, T. M., Safarova, Y., Yermekova, A., Olzhayev, F., Bulanin, D. S., Tsoy, A., & Askarova, S. (2023) · Nutrients · doi:10.3390/nu15234964 · Cited by 14 · see citing works
Angiotensin II directly impairs adipogenic differentiation of human preadipose cells
Palominos, M. M., Dünner, N. H., Wabitsch, M., & Rojas, C. (2015) · Molecular and Cellular Biochemistry · doi:10.1007/s11010-015-2487-y · Cited by 13 · see citing works
Reference Gene Optimization for Circadian Gene Expression Analysis in Human Adipose Tissue
White, J. M., Piron, M. J., Rangaraj, V. R., Hanlon, E. C., Cohen, R., & Brady, M. (2019) · Journal of Biological Rhythms · doi:10.1177/0748730419883043 · Cited by 13 · see citing works
Calderón-DuPont, D., Romero-Cordoba, S. L., Tello, J. K., Espinosa, A., Guerrero, B., Contreras, A. V., Morán‐Ramos, S., & Díaz‐Villaseñor, A. (2023) · Toxicology and Applied Pharmacology · doi:10.1016/j.taap.2023.116428 · Cited by 12 · see citing works
White adipose tissue in type 2 diabetes and the effect of antidiabetic drugs
Zhao, Y., & Yue, R. (2025) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-025-01678-9 · Cited by 12 · see citing works
Novel aspects on the role of white adipose tissue in type 2 diabetes
Mejhert, N., & Rydén, M. (2020) · Current Opinion in Pharmacology · doi:10.1016/j.coph.2020.09.008 · Cited by 12 · see citing works
Self-citationLipophagy: A New Perspective of Natural Products in Type 2 Diabetes Mellitus Treatment
Huang, M., Yang, X., Wang, Z., Long, J., Wang, A., Zhang, Y., & Yan, D. (2021) · Diabetes Metabolic Syndrome and Obesity · doi:10.2147/dmso.s310166 · Cited by 12 · see citing works
Walpot, J., Herck, P. V., Heyning, C. M. V. D., Bosmans, J. M., Massalha, S., Malbrain, M. L. N. G., Heidbüchel, H., & Inácio, J. R. (2023) · Anaesthesiology Intensive Therapy · doi:10.5114/ait.2023.130922 · Cited by 11 · see citing works
Chénard, T., Guénard, F., Vohl, M., Carpentier, A. C., Tchernof, A., & Najmanovich, R. (2017) · BMC Systems Biology · doi:10.1186/s12918-017-0438-9 · Cited by 11 · see citing works
Zhao, D., Zuo, J., Yu, N., Fang, X., Mo, F., Wu, R., Tian, T., Ma, R., Gao, Y., Zhang, D., et al. (2017) · Journal of Traditional Chinese Medical Sciences · doi:10.1016/j.jtcms.2017.07.003 · Cited by 11 · see citing works
Association of omental adipocyte hypertrophy and fibrosis with human obesity and type 2 diabetes
Liu, F., He, J., Liu, B., Zhang, P., Wang, H., Sun, X., Chu, X., Guan, W., Feng, W., Bi, Y., et al. (2021) · Obesity · doi:10.1002/oby.23155 · Cited by 9 · see citing works
Palomurto, S., Virtanen, K. A., Kärjä, V. J., Schwab, U., Kamińska, D., Käkelä, P., Pihlajamäki, J., & Männistö, V. (2025) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgaf346 · Cited by 9 · see citing works
Hwang, D.-J., Song, H., Kim, K., Jung, Y., Hwang, D., & Cho, J. Y. (2017) · Laboratory Animal Research · doi:10.5625/lar.2017.33.2.140 · Cited by 9 · see citing works
Zhao, L., Zhu, L., Su, Z., Li, W., Li, P., Liu, Y., Liu, S., & Zhu, S. (2018) · Gastroenterology report · doi:10.1093/gastro/goy024 · Cited by 8 · see citing works
Zhao, M., Chen, H., Zhang, Q., Zhao, T., Xu, C., Yin, B., Bu, Z., Xu, N., Liu, X., Zhao, H., et al. (2026) · International Journal of Surgery · doi:10.1097/js9.0000000000004912 · Cited by 7 · see citing works
Jeon, S., Lee, J., Shin, Y., & Yoon, M. (2023) · Canadian Journal of Physiology and Pharmacology · doi:10.1139/cjpp-2022-0339 · Cited by 7 · see citing works
Pourdashti, S., Faridi, N., Monem-Homaie, F., Yaghooti, S. H., Soroush, A., & Bathaie, S. Z. (2023) · Molecular Biology Reports · doi:10.1007/s11033-023-08460-y · Cited by 7 · see citing works
De la dysfonction du tissu adipeux blanc aux phénotypes anatomocliniques de l’obésité
Ziegler, O., Böhme, P., & Valet, P. (2017) · Obésité · doi:10.1007/s11690-017-0555-z · Cited by 7 · see citing works
Tumor Suppressor Par-4 Regulates Complement Factor C3 and Obesity
Araújo, N. V. P., Sledziona, J., Noothi, S. K., Burikhanov, R., Hebbar, N., Ganguly, S., Shrestha-Bhattarai, T., Zhu, B., Katz, W. S., Zhang, Y., et al. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.860446 · Cited by 6 · see citing works
Tremblay, È.-J., Tchernof, A., Pelletier, M., Chabot, N., Joanisse, D. R., & Mauriège, P. (2022) · Adipocyte · doi:10.1080/21623945.2022.2059902 · Cited by 6 · see citing works
Öztürk, G., Kahraman, A. N., Akpınar, P., Utangac, U., Karamanlıoğlu, D. Ş., Begoğlu, F. A., Özkan, F. Ü., Aktaş, İ., & Vural, A. (2025) · Phlebology The Journal of Venous Disease · doi:10.1177/02683555251357094 · Cited by 5 · see citing works
Jeon, Y., Lee, M., & Cheon, Y. (2015) · Development & Reproduction · doi:10.12717/dr.2015.19.4.235 · Cited by 5 · see citing works
Adiposity Is the Enemy: Body Composition and Insulin Sensitivity
Davis, S., Sherk, V. D., & HIGGINS, J. A. (2019) · Contemporary Endocrinology · doi:10.1007/978-3-030-25057-7_9 · Cited by 5 · see citing works
Tsuji, T., Yamaguchi, K., Kikuchi, R., Nakamura, H., Misaka, R., Nagai, A., & Aoshiba, K. (2017) · Prostaglandins & Other Lipid Mediators · doi:10.1016/j.prostaglandins.2017.03.001 · Cited by 4 · see citing works
Motor Capabilities and Body Composition in Health vs. Non-Health University Students: A Pilot Study
Živoder, I., Hodić, V., Degač, N. Z., Potočnjak, J., Arapović, M., Kuzmić, A., Jeleč, Ž., Knežević, G., Znika, M., & Meštrović, T. (2025) · Life · doi:10.3390/life15101504 · Cited by 3 · see citing works
Beneficial effects of long-chain n-3 fatty acids on insulin-resistance: basic and clinical aspects
Delarue, J. (2025) · Biochimie · doi:10.1016/j.biochi.2025.09.014 · Cited by 3 · see citing works
Tian, Z., Li, H., Wei, M., Ji, H., He, G., & Sun, J. (2026) · Aquaculture · doi:10.1016/j.aquaculture.2026.743618 · Cited by 2 · see citing works
Zhan, H., Qichun, C., Liu, T., Shi, Y., Pei, J., Zou, L., & Wang, L. (2024) · Diabetes Metabolic Syndrome and Obesity · doi:10.2147/dmso.s447847 · Cited by 2 · see citing works
Hu, J., Deng, X., Li, L., Liu, H., Tang, F., Ding, Z., Guo, B., Fan, Y., & Lu, L. (2024) · Annals of Surgical Oncology · doi:10.1245/s10434-024-15882-w · Cited by 2 · see citing works
Zinc finger protein 251 deficiency impairs glucose metabolism by inducing adipocyte hypertrophy
Kim, E., Ham, S. A., Hwang, J. S., Won, J. P., Lee, H. G., Hur, J., & Seo, H. G. (2022) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2022.111838 · Cited by 2 · see citing works
Tissue-specific insulin resistance in human obesity
van der Kolk (2018) · doi:10.26481/dis.20180503bk · Cited by 2 · see citing works
- Authors
- Rydén, M., Andersson, D. P., Bergström, I. B., & Arner, P.
- Affiliations
- Karolinska University Hospital (SE)
- Corresponding author
- Rydén, Mikael
- Venue
- The Journal of Clinical Endocrinology & Metabolism
- Publisher
- The Endocrine Society
- Published
- 2014-10
- Volume
- 99
- Issue
- 10
- Pages
- E1870-E1876
- ISSN
- 0021-972X (ISSN-L)
- 1945-7197
- OpenAlex
- W2114647414
- Semantic Scholar
- d4539851f822e7fab616919f43ad2e7b017805f4
- Cited by
- 124
- References
- 43
- Citations by year
- 2026: 7 · 2025: 8 · 2024: 10 · 2023: 10 · 2022: 11 · 2021: 10 · 2020: 10 · 2019: 9 · 2018: 18 · 2017: 12 · 2016: 4 · 2015: 15
- FWCI
- 7.81
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Journal of Clinical Endocrinology & Metabolism (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Eli Lilly and Company
- Karolinska Institutet
- Novo Nordisk
- Vetenskapsrådet
- European Association for the Study of Diabetes
- Novo Nordisk Fonden (NNF14OC0010187, NNF12OC1016371)
- U.S. Food and Drug Administration
- Topics
- Health Sciences › Medicine › Epidemiology › Adipokines, Inflammation, and Metabolic Diseases
- Health Sciences › Medicine › Physiology › Adipose Tissue and Metabolism
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Disease and Adiposity
- Keywords
- white adipose tissue, adipocyte size, adipocyte number, visceral adipose tissue, subcutaneous adipose tissue, insulin sensitivity, insulin resistance, type 2 diabetes risk, HDL cholesterol, triglycerides, obesity, gastric bypass, metabolic phenotypes
- MeSH terms
- Adolescent, Adult, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Female, Humans, Insulin, Insulin Resistance, Cholesterol, HDL, Male, Middle Aged, Obesity, Morbid, Omentum, Triglycerides, Glucose Clamp Technique, Adipocytes, Cell Size, Subcutaneous Fat, Intra-Abdominal Fat, Young Adult, Preoperative Period
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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.
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