Abstract
Context: Fetuin-A inhibits the insulin receptor in vitro. Higher serum fetuin-A concentrations are associated with type 2 diabetes longitudinally and greater adiposity in cross-sectional analyses. Whether higher fetuin-A concentrations are associated with accumulation of adiposity over time is unknown.
Objective: To determine the association of fetuin-A levels with changes in body composition over 5 yr.
Study Design: Observational cohort study nested in the Health Aging and Body Composition Study.
Predictor: Serum fetuin-A levels.
Outcomes: Visceral adipose tissue (VAT), abdominal sc adipose tissue, and thigh muscle area by computed tomography, and waist circumference and body mass index were measured at baseline and again after 5 yr. Percent change and extreme change (>1.5 sds) in each measure were calculated.
Results: Over 5 yr, subjects lost body mass in each measure, including 6% decline in VAT. Yet each sd (0.42 g/liter) higher fetuin-A concentration was associated with a 5.5% increase in VAT over 5 yr (95% confidence interval 1.9–9.2%; P = 0.003) in models adjusted for age, sex, race, clinical site, diabetes, physical activity, triglycerides, kidney function, and the baseline VAT score. Similarly, higher fetuin-A concentrations were associated with extreme VAT gain (relative risk 1.70, 95% confidence interval 1.12–2.60, P = 0.01). Fetuin-A concentrations were not statistically significant associated with change in any other measures of body composition (P > 0.20).
Conclusions: Higher fetuin-A concentrations are associated with the accumulation of VAT in well-functioning, community-living older persons. The mechanisms linking fetuin-A, VAT, and insulin resistance remain to be determined.
Higher serum fetuin-A levels are associated with accumulation of visceral adipose tissue over time in community-living older adults.
The prevalence of obesity has increased dramatically, currently affecting one in three Americans by conventional definitions (1,2). Obesity prevalence has grown particularly rapidly in older persons (1), a concerning trend because older persons are at highest risk of obesity-related diseases such as cardiovascular disease, malignancy, and kidney disease on the basis of advancing age alone. In addition, with age, fat tends to redistribute centrally, a distribution that is more strongly associated with adverse outcomes compared with noncentripetal fat distributions (3,4). Little is known about mechanisms responsible for age-related changes in body composition, although hypothalamic stress (5), activation of the renin-angiotensin-aldosterone axis (6), and alterations in corticosteroid and sex hormones may be involved.
Fetuin-A is a hepatic secretory protein that may, in part, mediate these changes (7). Fetuin-A binds and inhibits the insulin receptor tyrosine kinase on adipocytes and skeletal muscle cells, thereby inhibiting insulin signal transduction and inducing insulin resistance in vitro (7,8,9). In humans, higher fetuin-A concentrations are associated with insulin resistance and type 2 diabetes in middle-aged and older persons (10,11,12,13). Fetuin-A may also exert proadipogenic properties (14). In vitro, fetuin-A stimulates fibroblast and smooth muscle cell uptake of triglycerides and their incorporation into fatty acids (15). Whether similar effects occur with adipocytes in vitro is unknown; however, fetuin-A knockout mice are characterized by decreased adiposity compared with wild-type controls despite similar caloric intake (7), an effect that is preserved in aged (80 wk old) mice (16). In cross-sectional studies, we previously demonstrated that higher fetuin-A concentrations are associated with higher body mass index, waist circumference, and visceral adipose tissue (VAT) (10,11). However, the cross-sectional designs of these studies precluded evaluation of the temporality of associations.
To our knowledge, the association of fetuin-A concentrations with changes in body composition have not previously been evaluated. To that end, we determined the relation of serum fetuin-A concentrations with longitudinal changes in body composition among well-functioning older persons who participated in the Health Aging and Body Composition (Health ABC) Study. Because the association of fetuin-A with VAT was particularly strong in cross-sectional analysis, we hypothesized that higher fetuin-A concentrations would be more strongly associated with increases in VAT compared with other fat depots.
Subjects and Methods
Study sample
At the baseline study visit (April 1997 to June 1998), Health ABC enrolled 3075 well-functioning men and women aged 70–79 yr. Subjects were recruited from a sample of Medicare beneficiaries at two clinical sites (Pittsburgh, PA, and Memphis, TN). Participation required black or white race, and no reported difficulty in walking a quarter mile, climbing 10 steps, or performing basic activities of daily living. Venous blood samples were obtained after overnight (8 h) fasts, and stored at −70 C. Participants underwent a day-long evaluation that included medical history, physical activity assessment, medication inventory, physical examination, and radiographical tests including abdominal and thigh computed tomography (CT) scans for evaluation of regional adipose and muscle area. After the fasting blood draw, a 75-g oral glucose challenge was administered, and venous blood specimens were obtained again after 2 h. Participants returned to study visits annually for 5 yr. At the sixth study visit (5 yr after baseline), participants underwent repeat CT scans using identical protocols to that used at baseline, allowing for evaluation of longitudinal change in body composition. All participants provided written informed consent, and the study was approved by the Institutional Review Boards at the University of Pittsburgh and the University of Tennessee Health Sciences Center (Memphis, TN). In addition, this study was approved by the Human Research Protection Program at the University of California, San Diego.
A random sample of 508 participants was chosen from the Health ABC Study to participate in the present study, stratified equally in four sex and race strata. Random numbers were generated on a continuous standard uniform distribution U (0, 1) and were assigned to each participant within each of the four race/sex strata. The participants were then sorted in ascending order by the assigned random number. One hundred twenty-seven participants were chosen in order from each stratum until we reached the total sample size of 508. Frozen blood specimens among these participants were thawed and measured for fetuin-A.
Measurements
Fetuin-A
Fetuin-A concentrations were measured using a human ELISA kit (Epitope Diagnostics, San Diego, CA). The assay uses a two-site sandwich technique with polyclonal antibodies that bind to different epitopes on human fetuin-A. Measurements were performed at the Laboratory for Clinical Biochemistry Research at the University of Vermont (Burlington, VT). Fetuin-A was measured twice on each sample and results were averaged. The intra- and interassay coefficients of variation were less than 5%. Among a 5% blind duplicate assessment at the Laboratory for Clinical Biochemistry Research, the intraindividual coefficients of variation were 13.5 and 20%, respectively.
Body composition
Waist circumference was measured at the maximal circumference between the lower rib and iliac crest using a metal tape. Participants were asked to stand with their weight equally distributed on both feet and arms at their sides. Measurements were made over bare skin at the end of normal expiration to the nearest 0.2 cm. Measurements were made twice, and if the difference between measurements was greater than 1 cm, third and fourth measurements were obtained. The average of the two or four measurements was used as the recorded value. Height was measured by a stadiometer to the nearest 0.1 cm.
Regional adiposity was measured by CT scans as previously described (17). In brief, a GE 9800 Advantage (Milwaukee, WI) was used at the Pittsburgh center, and a Somatom Plus Pcker PQ2000S (Siemens, Melvern, PA) was used at the Memphis center. One-centimeter CT images were obtained during suspended respiration between the fourth and fifth lumbar vertebrae. Images were read centrally at the University of Colorado Health Sciences Center (Denver, CO). VAT was manually distinguished from sc adipose tissue (SAT) using the internal abdominal wall fascial plane. All pixels within the fascial plain with a Hounsfield unit consistent with fat were considered as VAT. Thigh CT scans were taken at the midpoint between the greater trochanter and intercondyloid fossa. Thigh muscle was manually distinguished from fat by drawing a line around the deep facial plane surrounding the thigh muscle.
CT scans and body composition measurements were repeated using the identical protocols when participants returned for their sixth annual clinic visit (5 yr after baseline).
Other measurements
Age, sex, and race were determined by self-report. Participants were categorized as having prevalent diabetes if they had any of the following: a self-report of diabetes diagnosis, use of hypoglycemic medications, fasting glucose level 126 mg/dl or greater, or 2-h postchallenge plasma glucose level 200 mg/dl or greater. Physical activity was assessed using self-report of walking and exercise and assigning kilocalories per week to activities. Seated systolic and diastolic blood pressures were measured using manual sphygmomanometers by trained study personnel. Total and high-density lipoprotein cholesterol and triglyceride concentrations were measured using a Vitros 950 analyzer (Johnson & Johnson, New Brunswick, NJ). Low-density lipoprotein cholesterol was calculated by the Friedewald equation (18). High-sensitivity C-reactive protein was measured by ELISA (Calbiochem, San Diego, CA) and was standardized to the World Health Organization’s first international reference standard. Serum creatinine was measured by colorimetry (Johnson & Johnson) and estimated glomerular filtration rate (eGFR) was calculated by the four-variable modification of diet in renal disease study equation (19). Among the subset of participants without diabetes at baseline, fasting serum insulin levels were measured by RIA (Pharmacia, Uppsala, Sweden) as previously described (20). Insulin resistance was calculated using the homeostasis model assessment (HOMA): fasting glucose × fasting insulin/22.5 (21).
Statistical analysis
Among the 508 participants, we included all subjects who provided repeat CT scan measurements at the follow-up visit 5 yr later. To evaluate potential bias introduced by participant censored before the 5-yr follow-up examination, we began by comparing baseline mean fetuin-A concentrations, the distribution of age, sex, and race, and mean body composition measures among participants with and without follow-up CT data using the Student t test and the χ2 test.
For each measure of body composition, intraindividual percent change was calculated by subtracting the baseline value from the yr 5 follow-up value and dividing by the baseline value. Graphical methods evaluated the distribution of each change score, and all were observed to closely approximate a normal distribution. The association of fetuin-A with change in body composition at each site was evaluated using multivariable linear regression with fetuin-A modeled as per sd increase. Sequential models were evaluated: 1) unadjusted; 2) adjusted for age, sex, race, and study site; and 3) with the addition of other variables associated with fetuin-A in bivariate analysis with a threshold of P < 0.20 (diabetes, physical activity, triglycerides, eGFR). We explored whether additional adjustment for baseline measurement of each body composition measure affected results. For all cases the results were similar, so all results are presented with adjustment for the baseline value. To explore the functional form of fetuin-A concentrations with each outcome, we used generalized additive models with a smoother to fit cubic B-spline functions to the change score data.
Because persons with extremes of gain or loss of body composition may be clinically informative, we defined extreme gain and extreme loss for each measure of body composition. In subjects with change greater than or less than 1.5 sd of the mean values of the study sample defined extreme gain and extreme loss for each measure. The remaining subjects within the 1.5 sd of the mean served as the reference category. The associations of fetuin-A with extreme gain or loss were evaluated simultaneously using multinomial logistic regression. This model does not assume that the outcome is ordinal and uses a multinomial link function, which provides estimate of the relative risks rather than odds ratios. We explored relationships stratified by sex, but in all cases, results were similar and all tests of interaction were nonsignificant (P > 0.30).
Two-tailed P < 0.05 was considered statistically significant. Analyses were performed with SAS version 9.1 (SAS Institute, Cary, NC) and SPlus version 6.1 (Insightful Corp., Seattle, WA).
Results
Among the 508 randomly selected participants, 284 (57%) provided repeat CT scans for VAT, SAT, and thigh muscle area measurements at the fifth annual study visit. Among participants with only baseline CT measurements (n = 224), the majority had died before the follow-up [n = 144 (64%)]. Compared with participants with follow-up CT scans, those with missing follow-up scan data had similar baseline mean fetuin-A concentrations and body composition measurements at each anatomic site; however, they were more likely to be black, were less physically active, and had higher C-reactive protein levels (Table 1). Among participants with follow-up scans, the mean age at baseline was 74 yr, and approximately half were black and female, reflecting our stratified sampling design. Twenty percent had diabetes, and the mean body mass index was 27 ± 4 kg/m2. The mean fetuin-A concentration was 0.95 ± 0.42 g/liter, and the distribution was approximately normal (Fig. 1). Fetuin-A concentrations were similar in men and women (P = 0.48) and blacks and whites (P = 0.19).
Table 1.
Baseline characteristics among participants with and without follow-up CT scans
| Characteristic | Participants with follow-up CT (n = 284) | Participants without follow-up CT (n = 224) | P value |
|---|---|---|---|
| Fetuin-A (g/liter) ± sd | 0.95 ± 0.42 | 0.92 ± 0.43 | 0.43 |
| Demographics | |||
| Age (yr) ± sd | 73 ± 3 | 74 ± 3 | 0.08 |
| Black race, n (%) | 127 (45) | 126 (56) | 0.01 |
| Female, n (%) | 145 (51) | 106 (47) | 0.40 |
| Diabetes, n (%) | 56 (20) | 46 (21) | 0.82 |
| Measurements | |||
| Physical activity score (kcal/wk)a | 575 (153, 1535) | 364 (62, 1096) | <0.01 |
| Systolic blood pressure (mm Hg) ± sd | 134 ± 20 | 135 ± 24 | 0.44 |
| Diastolic blood pressure (mm Hg) ± sd | 72 ± 13 | 71 ± 13 | 0.83 |
| Total cholesterol (mg/dl) ± sd | 206 ± 38 | 202 ± 36 | 0.30 |
| LDL cholesterol (mg/dl) ± sd | 125 ± 33 | 122 ± 35 | 0.42 |
| HDL cholesterol (mg/dl) ± sd | 55 ± 18 | 55 ± 17 | 0.88 |
| Triglycerides (mg/dl)a | 122 (86, 168) | 113 (84, 152) | 0.19 |
| C-reactive protein (mg/dl)a | 1.5 (1.0, 2.6) | 1.7 (1.1, 3.4) | 0.05 |
| eGFR (ml/min per 1.73 m2) ± sd | 75 ± 14 | 73 ± 19 | 0.21 |
| Baseline body composition | |||
| Body mass index (kg/m2) ± sd | 27 ± 4 | 28 ± 5 | 0.31 |
| VAT (cm2) ± sd | 134 ± 59 | 137 ± 61 | 0.66 |
| SAT (cm2) ± sd | 284 ± 121 | 291 ± 128 | 0.50 |
| Thigh muscle area (cm2) ± sd | 113 ± 28 | 112 ± 28 | 0.65 |
| Waist circumference (cm) ± sd | 99 ± 12 | 100 ± 13 | 0.39 |
| Height (cm) ± sd | 166 ± 9 | 166 ± 10 | 0.93 |
HDL, High-density lipoprotein; LDL, low-density lipoprotein.
Median (interquartile range); P values by Wilcoxon test.
Figure 1.
Distribution of fetuin-A levels among study participants (n = 284).
Over 5 yr of follow-up, the mean change in VAT was −8 ± 40 cm2, change in SAT was −21 ± 50 cm2, change in thigh muscle area was −6 ± 10 cm2, change in waist circumference was −1 ± 10 cm, change in height was −0.2 ± 2 cm, change in body mass index was −0.21 ± 1.98 kg/m2, and change in body weight was −1.7 ± 5.4 kg. Thus, on average, participants lost body mass at each measurement site over the observation period, yet this varied substantially across individuals.
Baseline fetuin-A concentrations were strongly associated with change in VAT in unadjusted analysis, a relationship that was only minimally altered in multivariable models (Table 2). In the final model, each sd (0.42 g/liter) higher fetuin-A was associated with a 5% increase in VAT over 5 yr. Results were similar when the association of fetuin-A with VAT was further adjusted for change in thigh muscle area (data not shown). Fetuin-A in isolation accounted for 3% of the variance in change in VAT, whereas the final multivariable model accounted for 11%. Spline functions demonstrated that this relationship was fairly linear across the spectrum of fetuin-A measurements (Fig. 2). In contrast, fetuin-A concentrations were not significantly associated with change in any other body composition measure over the observation period. All associations were similar in men and women (all interaction P > 0.30) and African Americans and Caucasians (all interaction P > 0.10).
Table 2.
Association of fetuin-A (per sd increase) with percent change in body composition over 5 yr in older persons
| Percent changea | 95% CI | P value | |
|---|---|---|---|
| VAT | |||
| Unadjusted | 4.94 | 1.32–8.55 | 0.008 |
| Age, sex, race, and field center site adjusted | 5.62 | 2.03–9.22 | 0.002 |
| Fully adjustedb | 5.54 | 1.87–9.20 | 0.003 |
| Abdominal SAT | |||
| Unadjusted | 0.33 | −1.98 to 2.64 | 0.78 |
| Age, sex, race, and field center site adjusted | 0.92 | −1.32 to 3.20 | 0.43 |
| Fully adjustedb | 1.11 | −1.22 to 3.43 | 0.35 |
| Thigh muscle area | |||
| Unadjusted | 0.27 | −0.70 to 1.24 | 0.58 |
| Age, sex, race, and field center site djusted | 0.12 | −0.81 to 1.06 | 0.80 |
| Fully adjustedb | 0.21 | −0.73 to 1.15 | 0.66 |
| Waist circumference | |||
| Unadjusted | 0.13 | −1.07 to 1.33 | 0.83 |
| Age, sex, race, and field center site adjusted | 0.49 | −0.64 to 1.62 | 0.39 |
| Fully adjustedb | 0.66 | −0.43 to 1.75 | 0.24 |
| Body mass index | |||
| Unadjusted | 0.39 | −0.43 to 1.20 | 0.35 |
| Age, sex, race, and field center site adjusted | 0.41 | −0.41 to 1.23 | 0.33 |
| Fully adjustedb | 0.46 | −0.37 to 1.30 | 0.28 |
CI, Confidence interval.
(Year 5 value − yr 1 value)/yr 1 value at each measurement site.
Adjusted for age, sex, race, clinical site, diabetes, physical activity, triglycerides, eGFR, and baseline measurement of body composition at each body site.
Figure 2.
Adjusted association of fetuin-A levels and 5-yr percent change in VAT. CI, Confidence interval.
We preliminarily evaluated the relative strength of association of fetuin-A with VAT compared with that of insulin resistance evaluated by HOMA with VAT. HOMA measurement was available in 217 subjects without type 2 diabetes mellitus at inception. In this subset, each sd greater natural log transformed HOMA (0.61 change) was associated with a 0.3% (−4.7% to 5.2%) increase in VAT over 5 yr in the final multivariable model (adjustment for age, sex, race, field center site, physical activity, triglycerides, eGFR, and baseline VAT score). In comparison, each sd increase in fetuin-A was associated with a 3.6% (95% confidence interval −0.9 to 8.9%) increase in VAT over 5 yr within the subset. Further adjustment for HOMA did not materially alter the association of fetuin-A with VAT (β = 3.6%; 95% confidence interval −0.8 to 8.1%).
Including all 284 study participants, results were similar in companion analyses evaluating extreme gain or loss of body mass, wherein each sd higher fetuin-A level was associated with approximately 70% greater risk of extreme VAT gain but not with extreme gain in any of the other measures of body composition (Table 3). Persons with higher fetuin-A concentrations were less likely to experience extreme VAT loss, although this association failed to reach statistical significance.
Table 3.
Adjusted association of fetuin-A (per sd increase) with extreme gain or loss in body composition over 5 yr in older personsa,b
| RR | 95% CI | P value | |
|---|---|---|---|
| VAT | |||
| Extreme gain | 1.70 | (1.12, 2.60) | 0.013 |
| Extreme Loss | 0.50 | (0.20, 1.21) | 0.12 |
| Abdominal SAT | |||
| Extreme gain | 1.31 | (0.76, 2.25) | 0.33 |
| Extreme loss | 0.92 | (0.47, 1.80) | 0.81 |
| Thigh muscle area | |||
| Extreme gain | 1.44 | (0.77, 2.67) | 0.25 |
| Extreme loss | 1.16 | (0.74, 1.82) | 0.51 |
| Waist circumference | |||
| Extreme gain | 0.92 | (0.54, 1.58) | 0.77 |
| Extreme loss | 0.66 | (0.36, 1.23) | 0.19 |
| Body mass index | |||
| Extreme gain | 0.85 | (0.48, 1.48) | 0.56 |
| Extreme loss | 0.77 | (0.49, 1.20) | 0.24 |
RR, Relative risk; CI, confidence interval.
Evaluated by multinomial logistic regression. Compared to the distribution of change of each body composition measure, extreme gain was defined by individuals who gained greater than 1.5 sd of the distribution, and extreme lost was defined by individuals who lost more than 1.5 sd below the distribution.
Adjusted for age, sex, race, clinical site, diabetes, physical activity, triglycerides, eGFR, and baseline measurement of body composition at each body site.
Discussion
Higher serum fetuin-A concentrations are associated with accumulation of VAT over time in community-living older persons. The association was similar in men and women and stronger than the association of fetuin-A with change in SAT, thigh muscle area, waist circumference, or body mass index. In prior studies, VAT was more strongly linked to insulin resistance, proinflammatory cytokines, lower adiponectin levels, and risk of type 2 diabetes and cardiovascular disease, compared with other fat depots (22). If the association of fetuin-A with longitudinal accumulation of VAT is confirmed, research designed to elucidate the underlying mechanisms may provide novel insights to the pathogenesis of visceral adiposity and, by extension, type 2 diabetes and cardiovascular disease.
We recently demonstrated that higher fetuin-A concentrations were associated with incident type 2 diabetes mellitus (11). Approximately 30% of this association was attenuated when models were adjusted for baseline VAT, but despite its inclusion, the association of fetuin-A with diabetes remained statistically significant. Fetuin-A is known to have direct inhibitory effects on the insulin receptor (8,23,24) and may also alter adipocytokine and inflammatory cytokine levels (14). These actions may be responsible for the residual association of fetuin-A with type 2 diabetes, independent of its association with VAT. Less is known about the relation of fetuin-A with cardiovascular disease (25,26). Future studies evaluating this association should account for VAT to determine whether the associations are independent or whether they may be partially mediated through differences in regional fat distribution. In addition, where fat loss may be advantageous in middle-aged individuals, it is a well-known marker of occult disease in the elderly. Whereas we hypothesize that the association of fetuin-A with accumulation of VAT in this older cohort may contribute to insulin resistance and adverse health outcomes, it remains possible that accumulation of VAT may be a marker of better health in this age-group. The association of higher fetuin-A with incident diabetes has been reported, both in middle and older age groups (12,27). However, less is known about its association with other clinical outcomes, which should be a high priority for future research.
Whereas, increasingly, studies are demostrating associations of fetuin-A concentrations and disease outcomes, little is known about factors that regulate serum fetuin-A. Intensive short-term diet and exercise programs and thiazolidinedione therapy have recently been reported to decrease fetuin-A concentrations in humans (13,28). It remains unknown whether these findings reflect an overall improvement in metabolic profile or whether fetuin-A may be a causal intermediary in the pathway to enhanced insulin sensitivity. Additional studies are required to evaluate these and other strategies to alter fetuin-A concentrations to determine whether any such changes result in measurable improvements in health. These studies may help to identify novel therapeutic targets for diabetes and obesity globally and VAT specifically.
Strengths of this study include the evaluation of a well-characterized community-living population, availability of repeated CT scans over time, and measurements of a wide range of demographic and clinical variables in all subjects. The study also has important limitations. First, implicit in evaluating change in body composition over time is the requirement for multiple measures within individuals, and therefore persons with only baseline CT measurements were excluded by necessity. This design feature lends the results susceptible to survival bias. Fortunately, fetuin-A levels and baseline body composition measures at each body site were similar among persons with or without follow-up CT data. The study sample was relatively small, yet change in each body composition measure was evaluated on a continuous scale, which improved statistical power. Nonetheless, null associations reported here may have been due to chance and should be interpreted within the confines of the 95% confidence intervals. Lastly, the study participants were all older, well functioning at baseline, and of black or white race. Results may differ in middle-aged and younger populations and persons of other races or ethnicities.
In conclusion, higher fetuin-A concentrations are associated with longitudinal accumulation of VAT in older community-living persons. If confirmed, investigation of the mechanisms responsible for this association might ultimately lead to the identification of novel therapies to limit VAT accumulation and may provide new insights to mechanisms leading to type 2 diabetes mellitus.
Footnotes
This study was supported by an American Diabetes Association (ADA) – Association of Subspecialty Professors (ASP) Young Investigator Innovation Award in Geriatric Endocrinology sponsored by the Atlantic Philanthropies, ADA, the John A. Hartford Foundation, and ASP, an American Heart Association Fellow to Faculty Transition Award (J.H.I.). The Health ABC study was supported by contracts N01-AG-6-2101, N01-AG-6-2103, and N01-AG-6-2106 and by the Intramural Research Program of the National Institutes of Health, National Institute on Aging (NIA). The funding sources played no role in the design and conduct of the study; collection, management, analysis, or interpretation of the data, nor in the preparation of the manuscript. The NIA reviewed and approved this manuscript prior to submission.
Disclosure Summary: The authors have nothing to disclose.
First Published Online October 9, 2009
Abbreviations: CT, Computed tomography; eGFR, estimated glomerular filtration rate; Health ABC, Health Aging and Body Composition Study; HOMA, homeostasis model assessment; SAT, sc adipose tissue; VAT, visceral adipose tissue.
References
- Flegal KM, Carroll MD, Ogden CL, Johnson CL 2002 Prevalence and trends in obesity among U.S. adults, 1999–2000. JAMA 288:1723–1727 [DOI] [PubMed] [Google Scholar]
- Howard BV, Rodriguez BL, Bennett PH, Harris MI, Hamman R, Kuller LH, Pearson TA, Wylie-Rosett J 2002 Prevention Conference VI: diabetes and cardiovascular disease: Writing Group I: epidemiology. Circulation 105:e132–e137 [DOI] [PubMed] [Google Scholar]
- Borkan GA, Hults DE, Gerzof SG, Robbins AH 1985 Comparison of body composition in middle-aged and elderly males using computed tomography. Am J Phys Anthropol 66:289–295 [DOI] [PubMed] [Google Scholar]
- Gallagher D, Ruts E, Visser M, Heshka S, Baumgartner RN, Wang J, Pierson RN, Pi-Sunyer FX, Heymsfield SB 2000 Weight stability masks sarcopenia in elderly men and women. Am J Physiol Endocrinol Metab 279:E366–E375 [DOI] [PubMed] [Google Scholar]
- Hochberg Z, Friedberg M, Yaniv L, Bader T, Tiosano D 2004 Hypothalamic regulation of adiposity: the role of 11β-hydroxysteroid dehydrogenase type 1. Horm Metab Res 36:365–369 [DOI] [PubMed] [Google Scholar]
- Cassis LA, Police SB, Yiannikouris F, Thatcher SE 2008 Local adipose tissue renin-angiotensin system. Curr Hypertens Rep 10:93–98 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mathews ST, Singh GP, Ranalletta M, Cintron VJ, Qiang X, Goustin AS, Jen KL, Charron MJ, Jahnen-Dechent W, Grunberger G 2002 Improved insulin sensitivity and resistance to weight gain in mice null for the Ahsg gene. Diabetes 51:2450–2458 [DOI] [PubMed] [Google Scholar]
- Auberger P, Falquerho L, Contreres JO, Pages G, Le Cam G, Rossi B, Le Cam A 1989 Characterization of a natural inhibitor of the insulin receptor tyrosine kinase: cDNA cloning, purification, and anti-mitogenic activity. Cell 58:631–640 [DOI] [PubMed] [Google Scholar]
- Rauth G, Pöschke O, Fink E, Eulitz M, Tippmer S, Kellerer M, Häring HU, Nawratil P, Haasemann M, Jahnen-Dechent W 1992 The nucleotide and partial amino acid sequences of rat fetuin. Identity with the natural tyrosine kinase inhibitor of the rat insulin receptor. Eur J Biochem 204:523–529 [DOI] [PubMed] [Google Scholar]
- Ix JH, Shlipak MG, Brandenburg VM, Ali S, Ketteler M, Whooley MA 2006 Association between human fetuin-A and the metabolic syndrome: data from the Heart and Soul Study. Circulation 113:1760–1767 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ix JH, Wassel CL, Kanaya AM, Vittinghoff E, Johnson KC, Koster A, Cauley JA, Harris TB, Cummings SR, Shlipak MG 2008 Fetuin-A and incident diabetes mellitus in older persons. JAMA 300:182–188 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Stefan N, Fritsche A, Weikert C, Boeing H, Joost HG, Haring HU, Schulze MB 2008 Plasma fetuin-A levels and the risk of type 2 diabetes. Diabetes 57:2762–2767 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Stefan N, Hennige AM, Staiger H, Machann J, Schick F, Kröber SM, Machicao F, Fritsche A, Häring HU 2006 α2-Heremans-Schmid glycoprotein/fetuin-A is associated with insulin resistance and fat accumulation in the liver in humans. Diabetes Care 29:853–857 [DOI] [PubMed] [Google Scholar]
- Hennige AM, Staiger H, Wicke C, Machicao F, Fritsche A, Häring HU, Stefan N 2008 Fetuin-A induces cytokine expression and suppresses adiponectin production. PLoS ONE 3:e1765 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Cayatte AJ, Kumbla L, Subbiah MT 1990 Marked acceleration of exogenous fatty acid incorporation into cellular triglycerides by fetuin. J Biol Chem 265:5883–5888 [PubMed] [Google Scholar]
- Mathews ST, Rakhade S, Zhou X, Parker GC, Coscina DV, Grunberger G 2006 Fetuin-null mice are protected against obesity and insulin resistance associated with aging. Biochem Biophys Res Commun 350:437–443 [DOI] [PubMed] [Google Scholar]
- Kanaya AM, Harris T, Goodpaster BH, Tylavsky F, Cummings SR 2004 Adipocytokines attenuate the association between visceral adiposity and diabetes in older adults. Diabetes Care 27:1375–1380 [DOI] [PubMed] [Google Scholar]
- Friedewald WT, Levy RI, Fredrickson DS 1972 Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 18:499–502 [PubMed] [Google Scholar]
- Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D 1999 A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 130:461–470 [DOI] [PubMed] [Google Scholar]
- Kanaya AM, Wassel Fyr C, Vittinghoff E, Harris TB, Park SW, Goodpaster BH, Tylavsky F, Cummings SR 2006 Adipocytokines and incident diabetes mellitus in older adults: the independent effect of plasminogen activator inhibitor 1. Arch Intern Med 166:350–356 [DOI] [PubMed] [Google Scholar]
- Wallace TM, Levy JC, Matthews DR 2004 Use and abuse of HOMA modeling. Diabetes Care 27:1487–1495 [DOI] [PubMed] [Google Scholar]
- Hamdy O, Porramatikul S, Al-Ozairi E 2006 Metabolic obesity: the paradox between visceral and subcutaneous fat. Curr Diabetes Rev 2:367–373 [DOI] [PubMed] [Google Scholar]
- Haasemann M, Nawratil P, Muller-Esterl W 1991 Rat tyrosine kinase inhibitor shows sequence similarity to human alpha 2-HS glycoprotein and bovine fetuin. Biochem J 274(Pt 3):899–902 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kalabay L, Chavin K, Lebreton JP, Robinson KA, Buse MG, Arnaud P 1998 Human recombinant α2-HS glycoprotein is produced in insect cells as a full length inhibitor of the insulin receptor tyrosine kinase. Horm Metab Res 30:1–6 [DOI] [PubMed] [Google Scholar]
- Lim P, Collet JP, Moutereau S, Guigui N, Mitchell-Heggs L, Loric S, Bernard M, Benhamed S, Montalescot G, Randé JL, Guéret P 2007 Fetuin-A is an independent predictor of death after ST-elevation myocardial infarction. Clin Chem 53:1835–1840 [DOI] [PubMed] [Google Scholar]
- Weikert C, Stefan N, Schulze MB, Pischon T, Berger K, Joost HG, Häring HU, Boeing H, Fritsche A 2008 Plasma fetuin-A levels and the risk of myocardial infarction and ischemic stroke. Circulation 118:2555–2562 [DOI] [PubMed] [Google Scholar]
- Ix JH, Wassel CL, Kanaya AM, Vittinghoff E, Johnson KC, Koster A, Cauley JA, Harris TB, Cummings SR, Shlipak MG 2008 Fetuin-A and incident diabetes mellitus in older persons. JAMA 300:182–188 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mori K, Emoto M, Araki T, Yokoyama H, Lee E, Teramura M, Koyama H, Shoji T, Inaba M, Nishizawa Y 2008 Effects of pioglitazone on serum fetuin-A levels in patients with type 2 diabetes mellitus. Metabolism 57:1248–1252 [DOI] [PubMed] [Google Scholar]