| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
Department of Internal Medicine (C.L.A.), Endocrinology-Hypertension Division, Brigham and Women’s Hospital, Boston, Massachusetts 02115; Divisions of Endocrinology and Metabolism (C.L.A., A.G., C.S.M.) and Infectious Diseases (S.T., A.W.K.), Department of Internal Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts 02215; and Merck Research Laboratories (K.B.), Blue Bell, Pennsylvania 19422
Address all correspondence and requests for reprints to: Christos S. Mantzoros, M.D., Division of Endocrinology and Metabolism, Beth Israel Deaconess Medical Center, 99 Brookline Avenue, RN 325A, Boston, Massachusetts 02215. E-mail: cmantzor{at}caregroup.harvard.edu.
 |
Abstract |
|---|
 Top Abstract IntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
Mean adiponectin levels were higher in patients with no fat redistribution (FR) vs. FR (4.8 ± 5.0 vs. 2.2 ± 2.7 µg/ml, P < 0.01), but no significant differences in adiponectin levels were observed between FR subgroups. The difference in adiponectin levels between subjects with and without FR remained significant after adjusting for age, gender, leptin, HIV medication use, and CD4 count using logistic regression (odds ratio, 0.54, P = 0.008). Adiponectin was significantly correlated with triglycerides (r = -0.40), abdominal visceral fat (r = -0.35), extremity fat (r = 0.37), insulin resistance (HOMA-IR) (r = -0.28), nucleoside reverse transcriptase inhibitor (NRTI) use (r = -0.32), and high-density lipoprotein (HDL) (r = 0.41) using bivariate analysis (all P < 0.01). The association with HDL weakened but remained significant on multivariate analysis (standard ß = 0.29, P = 0.01). However, the association of adiponectin with HOMA-IR became nonsignificant after adjusting for NRTI use (standard ß = -0.15, P = 0.12), suggesting that changes in adiponectin levels may underlie the effect of NRTI use on insulin resistance. The associations of adiponectin with triglycerides and HOMA-IR were also slightly weakened after adjusting for visceral and extremity fat, indicating that adiponectin may, in part, mediate the effect of FR on triglycerides and insulin resistance.
This study indicates that adiponectin is inversely correlated with abdominal visceral fat mass, serum triglycerides, and insulin resistance and is directly correlated with HDL and extremity fat in a sample of HIV-infected patients treated with HAART. The results also indicate that NRTI use may worsen insulin resistance by decreasing adiponectin levels. Thus, adiponectin replacement may be a potential treatment option to ameliorate the metabolic changes observed in this patient population.
|
Introduction |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
Adipocytes are metabolically and hormonally active, secreting proteins such as plasminogen activator inhibitor type 1, TNF
, IL-6, and leptin (4, 5, 6, 7, 8, 9). An excess or deficiency of these adipocytokines in the setting of obesity or lipoatrophy is thought to play an important role in the development of insulin resistance, positive energy balance, endothelial dysfunction, and abnormal fibrinolysis. These pathophysiological processes are commonly observed in the metabolic syndrome, which is characterized by hyperinsulinemia, type 2 diabetes mellitus, hypertension, hyperlipidemia, and coronary heart disease (CHD) (10, 11).
A new adipocytokine, adiponectin (acrp30, adipoQ), was discovered through cDNA cloning techniques by four different groups in the mid-1990s (12, 13, 14, 15). Adiponectin is the protein product of the apM1 gene, which is expressed exclusively in adipocytes. In vitro and animal studies and cross-sectional studies in humans have shown that adiponectin is inversely correlated with features of the metabolic syndrome including obesity, insulin resistance, type 2 diabetes, CHD, and congenital and acquired lipodystrophies in non-HIV infected subjects (16, 17, 18, 19). The association of adiponectin with the metabolic syndrome is strengthened further, given that this syndrome has recently been linked to a quantitative trait locus on chromosome 3q27, the location of the apM1 gene (20). Most recently, Yamauchi et al. (18) reported decreased serum adiponectin and leptin levels in a murine model of lipoatrophy. Administration of either adiponectin or leptin alone could only partially correct the insulin resistance in these mice. However, the administration of adiponectin and leptin together was able to fully correct the associated insulin resistance in this murine model of lipoatrophic diabetes.
It remains unknown, however, whether adiponectin is associated with metabolic abnormalities in patients with HIV-lipodystrophy. To study the association of adiponectin with metabolic and anthropometric changes observed in a sample of patients with lipodystrophy caused by HAART, we performed a cross-sectional analysis of 112 consecutively enrolled HIV-infected patients recruited through the Infectious Diseases Clinic of the Beth Israel Deaconess Medical Center (BIDMC), Boston, Massachusetts, from August 2000 through March 2001.
|
Subjects and Methods |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
Subjects were 112 consecutively enrolled patients recruited from two ambulatory HIV clinics at Beth Israel Deaconess Medical Center (Boston, MA) from August 2000 through March 2001. Recruitment occurred by means of contacting patients’ primary care physicians and through the posting of study fliers in clinics. Eligibility for study enrollment included: age 16 yr or older, laboratory documentation of HIV infection, and ability to give informed consent. The study consisted of one outpatient visit to the General Clinical Research Center at BIDMC.
Materials and methods
Two study investigators obtained a detailed medical history for each subject using a standardized questionnaire and interview. Information provided by subjects was later confirmed by a review of available inpatient and outpatient medical records. Note was made of medical conditions or medications that were known to affect glucose or lipid metabolism and body composition. Information pertaining to alcohol use (current or past use and number/quantity of alcoholic beverages per week) and exercise habits (type of activity, such as aerobic training or resistance training, and frequency/duration of exercise sessions) was obtained by means of a questionnaire and interview. All previous and ongoing antiretroviral therapies were noted, and exposure to each medication was recorded based on cumulative months of therapy.
Each subject received a complete physical examination with emphasis given to body FR. A clinical diagnosis of FR was either evident to the investigator during the physical examination or suggested based on comparison to prior physical examination findings noted in the subject’s medical record or through changes noted by the subjects themselves. Standardized digital photographs of each body region were obtained to document FR and used by the Fat Redistribution Adjudication Committee (described below) to support the classification of study subjects.
Anthropometric evaluation of subjects involved skinfold thickness (triceps and subscapular), upper arm circumference, waist circumference, and waist to hip ratio (WHR). Three measurements were obtained at each site and recorded as the mean of the three values. Whole body fat and lean masses and extremity fat mass were measured using dual-energy x-ray absorptiometry (DEXA) scans obtained with a QDR-2000 densitometer operating in an array mode (software version 5.73A; Hologic, Inc., Waltham, MA) (21, 22). A single-slice computed tomography (CT) scan at the level of L4 was performed for each subject to assess abdominal visceral and abdominal sc adipose tissue (23, 24, 25, 26).
Assessment of body FR classification for each subject was conducted independently by the Fat Redistribution Adjudication Committee. This committee consisted of three clinical investigators who were not involved with subject interviews, data collection, or analysis or in the clinical care of the study subjects. Committee members made a preliminary classification of each subject according to signs and symptoms noted in individual medical charts, study questionnaires, and study interviews. Subjects were then secondarily classified according to documented physical examination findings and digital photographs based on the criteria specified in Table 1
. Final classification of each subject was verified according to the diagnostic test criteria specified in Table 1. Each subject was classified as having no FR or the presence of FR, which included fat accumulation (FA), fat wasting (FW), or mixed FR (FA and FW). All committee members were provided with identical information on which to base their decisions, and classifications were based on supportive documentation and good clinical judgment. The final classification of each subject required the unanimous agreement of the committee. Subjects whose classification was not unanimously agreed on (n = 4) were not included in the analysis.
|
Statistical analysis
SPSS version 8.0 for Windows software (SPSS, Inc., Chicago, IL) was used for data analysis. Descriptive statistics are represented as mean ± SD, and graphical displays of data are shown as mean ± SE. Independent sample t test was used to compare normally distributed continuous variables between groups with or without FR, and Wilcoxon rank sum was used to compare variables that were not normally distributed. A 
2 test was used to compare categorical variables between groups with or without FR. Associations among adiponectin, leptin, anthropometric variables, metabolic variables, cumulative HIV medication use, and disease severity, as measured by CD4 count and HIV RNA, were determined using Spearman correlation coefficients. Multivariate linear regression analyses were conducted to investigate predictors of insulin resistance and lipids, and adjustments were made for potential confounders including age, gender, alcohol use, exercise, adiponectin, leptin, CD4 count, HIV RNA, HIV medication use, fat mass, presence or absence of FR, and WHR. A logistic regression analysis was performed to examine the association of adiponectin with FR while adjusting for age, gender, leptin, CD4 count, HIV RNA, and HIV medication use. Data were normalized via logarithmic or natural log transformation where appropriate. A P value of 0.05 was used to test for statistical significance, and all statistical tests were two tailed.
|
Results |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
Because the FR group included subjects with FA, mixed FR, and FW and was therefore heterogeneous, comparisons were made between these subgroups and the non-FR group using one-way ANOVA with Bonferroni correction (Table 2). Body mass index (BMI), sc abdominal fat, extremity fat, and HDL were increased in the FA vs. mixed FR and FW groups (P < 0.05), and abdominal visceral fat was significantly lower in the FW, compared with the FA and mixed groups (P < 0.05). The comparison of adiponectin levels between the FR subgroups showed apparent differences: no FR (4.8 ± 5.0 µg/ml), fat accumulation (3.2 ± 2.3 µg/ml), mixed FR (1.7 ± 2.8 µg/ml), and FW (2.0 ± 2.6 µg/ml). However, these differences were significant only between the no FR and mixed FR groups (P < 0.05) and the no FR and FW groups (P < 0.05). Differences in triglycerides (FA, compared with mixed FR, P = 0.06), fasting glucose (FA, compared with FW, P = 0.06), fasting insulin, and HOMA-IR among the three different FR subgroups were noted, but these differences did not reach statistical significance at the conventional level (P < 0.05) except between non-FR and FR subgroups (Fig. 1). Lack of significance may be due to small sample sizes (type II error) in each of the FR subgroups (n = 16 for FA, n = 27 for mixed, and n = 20 for FW), although similarities in the underlying pathophysiology among subgroups cannot be ruled out. Subgroup analyses were repeated after DM patients were excluded and resulted in no change in the results presented in Fig. 1.
|
|
). Adiponectin was significantly (P < 0.01) and inversely correlated with WHR, abdominal visceral fat, triglycerides, fasting insulin, HOMA-IR, and cumulative NRTI exposure. Additionally, adiponectin showed significant direct correlation with abdominal sc fat (r = 0.24), extremity fat (r = 0.37), and HDL cholesterol (r = 0.41). Importantly, the correlation of adiponectin with triglycerides, HOMA-IR, and abdominal visceral fat showed a significant negative curvilinear relationship, but no significant association with total fat mass was observed (r = 0.15, P = 0.12) (Fig. 2). Because of these apparent nonlinear relationships, additional models were run to better characterize the nature of these associations (data not shown). An exponential model showed that adiponectin explained nearly twice the variability of triglycerides in comparison with a linear model. Additionally, a logarithmic model showed that adiponectin explained nearly twice the variability of HOMA-IR in comparison with a linear model. These models suggest that Spearman correlation coefficients underestimate the association of adiponectin with both of these variables. Repeat correlation analyses after DM patients were excluded resulted in weakening of the correlation of adiponectin with insulin resistance (r = -0.25 vs. r = -0.28, P = 0.01 vs. P < 0.01), strengthening of the correlations of adiponectin with abdominal sc fat (r = 0.31 vs. r = 0.24, P < 0.01 vs. P = 0.01) and extremity fat (r = 0.40 vs. r = 0.37, both P < 0.01), but no change in the association of adiponectin with triglycerides, HDL, glucose, or fasting insulin.
|
|
). Regression models were run to adjust for each HAART medication class separately. Adjustments for cumulative PI or NNRTI use alone did not result in any significant improvement in the fit of the models and are therefore not reported. We presented the model that adjusted for cumulative NRTI use because this resulted in the model that best fit the data. Because the mixed FR subgroup was significantly older that the non-FR group and there was a significant correlation of age and abdominal visceral fat (r = 0.26, P < 0.01), all models were adjusted for age. We presented visceral adipose tissue (VAT) in all models as a correlate of central adiposity and extremity fat as a marker of peripheral fat wasting. We also ran similar models substituting WHR or waist circumference for VAT and models that substituted hip circumference or abdominal sc fat for extremity fat. The strong inverse correlation between adiponectin and serum triglycerides was essentially unaltered after adjusting for potential confounders such as age, gender, leptin, cumulative NRTI use, cumulative use of all HIV medications, CD4 count, or viral load (P = 0.01) (Table 4). The significance of this correlation was slightly decreased but remained statistically significant when the model was further adjusted for HOMA-IR (data not shown, P = 0.01). The association between serum triglycerides and adiponectin was slightly weakened but remained significant when the model was further adjusted for VAT (P = 0.03) and extremity fat (P = 0.04), indicating that the association between adiponectin and triglycerides is in part influenced by FR. A strong direct correlation was noted between adiponectin and HDL cholesterol, and this correlation remained significant when the model was adjusted for potential confounders (ß = 0.29, P = 0.007) (Table 4). In addition, adiponectin was inversely correlated with HOMA-IR after adjusting for age, gender, and leptin (ß = -0.21, P = 0.03) (Table 4). This correlation was weakened significantly after adjusting for cumulative NRTI but not other HIV medication use (P = 0.12) (Table 4). The association of adiponectin with insulin resistance was further weakened when the model was adjusted for CD4 count and HIV viral load (P = 0.20), suggesting that disease severity and NRTI use may modulate insulin resistance by altering adiponectin levels. The association between adiponectin and insulin resistance was further weakened when the model was adjusted for VAT and extremity fat (P = 0.40), suggesting that FR may modulate insulin resistance through changes in adiponectin (Table 4).
|
The exclusion of DM cases from the analyses (data not shown) showed weakening of the association of adiponectin with triglycerides (ß7 = -0.17, P = 0.16) and a weakened but still significant direct association with HDL (ß = 0.24, P = 0.02). The association of adiponectin with insulin resistance became of borderline significance after adjusting for potential confounders (ß2 = -0.18, P = 0.08).
We performed a multiple logistic regression analysis to examine the relationship of adiponectin with FR (Table 5). We observed adiponectin to be inversely associated with FR even when adjusting for age, gender, leptin, CD4 count, HIV RNA, and HIV medication use (odds ratio, 0.54, P = 0.008). Repeat analyses adjusting for duration of HIV infection and after excluding subjects with DM resulted in no change in this association.
|
Given recent data demonstrating that adiponectin administered to lipodystrophic mice led to improvement in metabolic parameters and insulin sensitivity, we explored the bivariate association between adiponectin and insulin resistance, metabolic outcomes, and anthropometric variables by means of Spearman correlation in the FW subgroup only (n = 20, data not shown). Significant associations were noted between adiponectin and HDL (r = 0.61, P = 0.005), abdominal visceral fat (r = -0.69, P = 0.007), total body fat mass on CT (r = -0.51, P = 0.02), and body weight (r = -0.46, P = 0.04). Adiponectin showed nonsignificant correlation with triglycerides (r = -0.30, P = 0.20) and HOMA-IR (r = -0.17, P = 0.48). The lack of significance of these correlations may be due to small sample size (n = 20) or the fact that the relationships between adiponectin and both triglycerides and HOMA-IR are not linear (as shown in Fig. 2
for the entire cohort). Thus, we repeated our analyses using nonlinear models and found that in the FW subgroup, an exponential model explained more than twice the variability of that explained by a linear model in describing the association of adiponectin with triglycerides. Similarly, a logarithmic model explained nearly twice as much of the variability of that explained by a linear model in the association of HOMA-IR and adiponectin. These models suggest that use of linear models underestimates the correlation because of a nonlinear relationship with adiponectin and both of these variables.
|
Discussion |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
. The difference in adiponectin levels between subjects with and without FR remained essentially unchanged after adjusting for age, gender, leptin, HIV medications, and disease severity using logistic regression analysis. Because of the significant association of adiponectin with both abdominal visceral fat and extremity fat, the distinct possibility exists that increased visceral adiposity coupled with peripheral FW best explains the decreased adiponectin levels in patients with mixed FR, especially in those with increased central, compared with peripheral, fat distribution. Because the possibility exists that visceral fat may also influence, in part, the relationship between adiponectin and metabolic factors, we examined whether adiponectin was related to several components of the metabolic syndrome and whether such associations were mediated by body fat distribution as well as disease severity or medication use. Our results demonstrate that adiponectin is significantly correlated with IR, triglycerides, and HDL in HIV-infected patients treated with HAART. The strong direct correlation of adiponectin with HDL was most pronounced in the entire study group and was even significant in the FW group, despite the small number of subjects in this subgroup. The associations of adiponectin with IR, HDL, and triglycerides persisted on multivariate analyses when adjusting for age, gender, leptin, DM, alcohol use, and exercise. Adjusting for central obesity, expressed as VAT, and extremity fat weakened the association of adiponectin with insulin resistance and slightly weakened its association with serum triglycerides, indicating that body FR may, in part, underlie the association between adiponectin and IR and serum triglycerides. The inverse association of adiponectin with HOMA-IR was also weakened significantly with adjustment for cumulative NRTI use, CD4 count, and HIV viral load, indicating that disease severity and HIV medication use may play a role in mediating the effect of adiponectin on IR. However, the association of adiponectin with HDL weakened but remained significant despite adjustments for potential confounders, including central obesity. Importantly, in our study adiponectin was inversely associated with abdominal visceral fat and positively associated with sc fat, which is consistent with the role of visceral adiposity in the development of IR and lipid abnormalities associated with the metabolic syndrome (32, 33, 34).
Features of the metabolic syndrome such as obesity and IR have been associated with increased levels of TNF. An in vitro study demonstrated that TNF decreased the expression of the apM1 gene and the secretion of its gene product, adiponectin, from 3T3-L1-adipocytes (35). The effect of HAART on TNF remains largely unknown. Although one study has suggested that circulating TNF levels decrease, but do not normalize, in patients receiving HAART, another study has suggested that HAART may be partly responsible for increased synthesis of TNF by T cells (36, 37). We found that adiponectin was inversely associated with cumulative months of NRTI use but not other classes of antiretroviral therapies, including PI use. The lack of association with the latter is potentially a type II error and may be explained by the fact that the vast majority of the study subjects had used PI therapy for some time period during their treatment for HIV infection. The strong association between adiponectin and IR on multivariate linear regression analysis became statistically insignificant when the model was adjusted for cumulative NRTI use. These observations support the hypothesis that adiponectin secretion may be down-regulated with use of medications such as NRTIs. Whether this effect is mediated by NRTI-induced changes in TNF levels or it is due to a direct effect of NRTIs to decrease adipocyte differentiation and thus decrease adiponectin secretion remains to be shown. Carr et al. (38) proposed that antiretroviral medications may directly decrease adipocyte differentiation by inhibiting the activation of the retinoid X receptor-peroxisome proliferator-activator receptor (PPAR)-
heterodimer, a nuclear receptor involved in adipocyte differentiation. Agonists of PPAR- have been associated with improvement in insulin sensitivity and increased adipocyte differentiation and have been shown in in vitro, animal, and human models to increase adiponectin secretion (18, 39, 40). Most recently, Bastard et al. (41) showed that a decrease in sterol-regulatory-element-binding-protein-1c was associated with decreased expression of PPAR- and decreased adipocyte differentiation in a sample of patients with HAART-induced lipoatrophy. TNF was found to be increased and leptin was found to be decreased in these patients as would be expected in the setting of abnormal adipocyte differentiation. Although adiponectin was not measured specifically, one could hypothesize that based on increased TNF and decreased adipocyte differentiation, adiponectin levels would be decreased as seen in our study.
The results from our study highlight a significant inverse association of adiponectin with IR and serum triglyceride levels as well as a strong direct correlation of adiponectin with HDL cholesterol. Our findings are in keeping with prior association studies in humans with type 2 DM, obesity, CHD, and congenital and acquired lipodystrophies in non-HIV infected subjects/populations and mirror those from a prospective longitudinal study that reported declining adiponectin levels in parallel with the development of obesity and type 2 DM in Rhesus monkeys (14, 16, 17, 19, 42, 43).
This is the first study to show that hypoadiponectinemia is associated with HIV-induced lipodystrophy. Although our entire study was adequately powered, our subgroup analysis was limited by relatively small numbers of subjects in each of the three FR subgroups. The factors contributing to these differences in body fat distribution in HAART-induced lipodystrophy are currently unknown but may include the effects of specific antiretroviral medications on the sterol-regulatory-element-binding-protein-1c and adipocyte differentiation (44). In all likelihood, the etiology of this disorder is multifactorial and influenced by genetics, diet, race, gender, and viral factors. Future studies are needed to better characterize the potential differences among subgroups with regard to the underlying pathophysiology of FR and the associated metabolic consequences such as hypoadiponectinemia, hyperlipidemia, and IR.
In a murine model of lipoatrophic diabetes mellitus and hypoadiponectinemia, administration of adiponectin decreased IR (18). Adiponectin increases free fatty acid transport, oxidation, and dissipation in skeletal muscle; reduces the levels of intramyocellular lipids; and thus improves insulin signaling (45, 46). In addition, adiponectin suppresses hepatic glucose output and increases the sensitivity of hepatocytes to insulin either through a direct action or indirectly by lowering circulating lipids because of its action in muscle (18, 45, 46, 47). Taken together, these data suggest that administration of adiponectin results in improved insulin sensitivity and glucose tolerance and decreased hyperglycemia.
Oral et al. (48) recently demonstrated partial but significant improvement in insulin sensitivity and a decline in serum triglycerides after leptin administration in patients with leptin-deficient lipodystrophy. Interestingly, leptin or adiponectin administration alone can only partially restore insulin sensitivity in lipoatrophic mice, whereas the coadministration of both leptin and adiponectin can fully normalize insulin sensitivity (18). It remains to be seen whether leptin and/or adiponectin replacement in patients with HIV-lipodystrophy would lead to similar metabolic improvements.
|
Acknowledgments |
|---|
|
Footnotes |
|---|
Abbreviations: BMI, Body mass index; CHD, coronary heart disease; CT, computed tomography; DEXA, dual-energy x-ray absorptiometry; DM, diabetes mellitus; FA, fat accumulation; FR, fat redistribution; FW, fat wasting; HAART, highly active antiretroviral therapy; HDL, high-density lipoprotein; HOMA, homeostasis model; IR, insulin resistance; NRTI, nucleoside reverse transcriptase inhibitor; PI, protease inhibitor; PPAR, peroxisome proliferator-activator receptor; VAT, visceral adipose tissue; WHR, waist to hip ratio.
Received May 23, 2002.
Accepted November 4, 2002.
|
References |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
: a key component of the obesity-diabetes link. Diabetes 43:1271–1278[Abstract]
inhibits signaling from the insulin receptor. Proc Natl Acad Sci USA 91:4854–4858 ligands increase expression and plasma concentrations of adiponectin, an adipose-derived protein. Diabetes 50:2094–2099 agonist, rosiglitazone, increases plasma levels of adiponectin in type 2 diabetic patients. Diabetes Care 25:376–380This article has been cited by other articles:
 |
|
 |
|
  M. Kratz, J. Q. Purnell, P. A. Breen, K. K. Thomas, K. M. Utzschneider, D. B. Carr, S. E. Kahn, J. P. Hughes, E. A. Rutledge, B. Van Yserloo, et al. Reduced Adipogenic Gene Expression in Thigh Adipose Tissue Precedes Human Immunodeficiency Virus-Associated Lipoatrophy J. Clin. Endocrinol. Metab., March 1, 2008; 93(3): 959 - 966. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
L. A. Kosmiski, P. Bacchetti, D. P. Kotler, S. B. Heymsfield, C. E. Lewis, M. G. Shlipak, R. Scherzer, and C. Grunfeld Relationship of Fat Distribution with Adipokines in Human Immunodeficiency Virus Infection J. Clin. Endocrinol. Metab., January 1, 2008; 93(1): 216 - 224. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 E. H. Koh, J.-Y. Park, H.-S. Park, M. J. Jeon, J. W. Ryu, M. Kim, S. Y. Kim, M.-S. Kim, S.-W. Kim, I. S. Park, et al. Essential Role of Mitochondrial Function in Adiponectin Synthesis in Adipocytes Diabetes, December 1, 2007; 56(12): 2973 - 2981. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. H. Lee, J. L. Chan, E. Sourlas, V. Raptopoulos, and C. S. Mantzoros Recombinant Methionyl Human Leptin Therapy in Replacement Doses Improves Insulin Resistance and Metabolic Profile in Patients with Lipoatrophy and Metabolic Syndrome Induced by the Highly Active Antiretroviral Therapy J. Clin. Endocrinol. Metab., July 1, 2006; 91(7): 2605 - 2611. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. Hadigan, D. Kamin, J. Liebau, S. Mazza, S. Barrow, M. Torriani, R. Rubin, S. Weise, A. Fischman, and S. Grinspoon Depot-specific regulation of glucose uptake and insulin sensitivity in HIV-lipodystrophy Am J Physiol Endocrinol Metab, February 1, 2006; 290(2): E289 - E298. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
D. Barb, S. G. Wadhwa, J. Kratzsch, A. Gavrila, J. L. Chan, C. J. Williams, A. W. Karchmer, and C. S. Mantzoros Circulating Resistin Levels Are Not Associated with Fat Redistribution, Insulin Resistance, or Metabolic Profile in Patients with the Highly Active Antiretroviral Therapy-Induced Metabolic Syndrome J. Clin. Endocrinol. Metab., September 1, 2005; 90(9): 5324 - 5328. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. S. Mantzoros, T. Li, J. E. Manson, J. B. Meigs, and F. B. Hu Circulating Adiponectin Levels Are Associated with Better Glycemic Control, More Favorable Lipid Profile, and Reduced Inflammation in Women with Type 2 Diabetes J. Clin. Endocrinol. Metab., August 1, 2005; 90(8): 4542 - 4548. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. B. Schulze, I. Shai, E. B. Rimm, T. Li, N. Rifai, and F. B. Hu Adiponectin and Future Coronary Heart Disease Events Among Men With Type 2 Diabetes Diabetes, February 1, 2005; 54(2): 534 - 539. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
F. Conus, D. B. Allison, R. Rabasa-Lhoret, M. St-Onge, D. H. St-Pierre, A. Tremblay-Lebeau, and E. T. Poehlman Metabolic and Behavioral Characteristics of Metabolically Obese but Normal-Weight Women J. Clin. Endocrinol. Metab., October 1, 2004; 89(10): 5013 - 5020. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 H. Yki-Jarvinen Thiazolidinediones N. Engl. J. Med., September 9, 2004; 351(11): 1106 - 1118. [Full Text] [PDF]
|
|
|
|
 |
|
 M. B. Schulze, E. B. Rimm, I. Shai, N. Rifai, and F. B. Hu Relationship Between Adiponectin and Glycemic Control, Blood Lipids, and Inflammatory Markers in Men With Type 2 Diabetes Diabetes Care, July 1, 2004; 27(7): 1680 - 1687. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 G. H. Wynn, M. J. Zapor, B. H. Smith, G. Wortmann, J. R. Oesterheld, S. C. Armstrong, and K. L. Cozza Antiretrovirals, Part 1: Overview, History, and Focus on Protease Inhibitors Psychosomatics, June 1, 2004; 45(3): 262 - 270. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. D. Karelis, D. H. St-Pierre, F. Conus, R. Rabasa-Lhoret, and E. T. Poehlman Metabolic and Body Composition Factors in Subgroups of Obesity: What Do We Know? J. Clin. Endocrinol. Metab., June 1, 2004; 89(6): 2569 - 2575. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. Hadigan, S. Yawetz, A. Thomas, F. Havers, P. E. Sax, and S. Grinspoon Metabolic Effects of Rosiglitazone in HIV Lipodystrophy: A Randomized, Controlled Trial Ann Intern Med, May 18, 2004; 140(10): 786 - 794. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 W. B. Kinlaw and B. Marsh Adiponectin and HIV-Lipodystrophy: Taking HAART Endocrinology, February 1, 2004; 145(2): 484 - 486. |
0.02 for comparison adiponectin between group 0 and groups 2 and 3. b, P = 0.001 for comparison of triglycerides between group 0 and group 2. c, P < 0.001 for comparison of abdominal visceral fat area between group 0 and groups 1 and 2 and between groups 1 and 2 and group 3. d, P < 0.03 for comparison of IR between group 0 and groups 1, 2, and 3.