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The Journal of Clinical Endocrinology & Metabolism Vol. 87, No. 6 2520-2524
Copyright © 2002 by The Endocrine Society

The Impact of the Human Genome on Endocrinology: Original Articles

Human Resistin Gene: Molecular Scanning and Evaluation of Association with Insulin Sensitivity and Type 2 Diabetes in Caucasians

Hua Wang, Winston S. Chu, Chris Hemphill and Steven C. Elbein

Division of Endocrinology and Metabolism and Endocrinology Section, John L. McClellan Jr. Memorial Veterans Hospital and University of Arkansas for Medical Sciences, Little Rock, Arkansas 72205

Address all correspondence and requests for reprints to: Steven C. Elbein, M.D., Professor of Medicine, Endocrinology 111J/LR, John L. McClellan Jr. Memorial Veterans Hospital, 4300 West 7th Street, Little Rock, Arkansas 72205. E-mail: . ElbeinStevenC{at}uams.edu

Abstract

Insulin resistance is strongly associated with obesity, but even among obese subjects insulin sensitivity varies widely. Recently, a new adipocyte hormone, resistin, was identified, shown to reduce insulin-mediated glucose uptake, and shown to be increased in obese mice. We used the chromosome 19 draft sequence to determine the genomic structure of human resistin and to screen the exons, introns, and flanking sequences for variation. We screened 44 subjects with type 2 diabetes and 20 nondiabetic family members who were at the extremes of insulin sensitivity. We identified eight noncoding single nucleotide polymorphisms (SNPs) and one GAT microsatellite repeat. Three SNPs, which were in incomplete linkage disequilibrium with each other and had allelic frequencies exceeding 5%, were selected for further study. No SNP was associated with type 2 diabetes, but the SNP in the promoter region was a significant determinant of insulin sensitivity index (P = 0.04) among nondiabetic family members who had undergone iv glucose tolerance tests. The three common SNPs showed statistical significance as determinants of insulin sensitivity index (P < 0.01) in interaction with body mass index. Noncoding SNPs in the resistin gene may influence insulin sensitivity in interaction with obesity, but this finding will need to be confirmed in other populations.

TYPE 2 DIABETES (T2DM) is characterized by both insulin resistance, which precedes and predicts the onset of diabetes (1, 2), and, in 80–85% of subjects, obesity. Although insulin resistance correlates closely with obesity and measures of fat mass, the mechanisms by which elevated body fat causes reduced insulin sensitivity are unknown. Adipocytes secrete a number of factors that might modulate insulin sensitivity, including FFAs (3), TNF-{alpha} (4), IL-6 (5), adiponectin (6), and perhaps other factors. Recently, a novel, cysteine-rich, adipocyte-specific secretory factor was identified in mouse adipocytes and was detectable in serum (7). This factor, called resistin, had increased levels in both genetic and diet-induced obesity in mice (7). Furthermore, exogenous resistin altered glucose tolerance and reduced insulin action in normal mice (7). Finally, PPAR{gamma} agonists, which improve insulin sensitivity, decreased resistin levels in both ob/ob mice and Zucker diabetic fatty rats (7). This new hormone was proposed as an adipokine that is secreted in response to the nutritional state of animals (7, 8), although available published studies of resistin gene expression in human tissues have raised questions about the role of this gene in humans (9, 10).

Based on the data from mice, we hypothesized that genetic variation in the resistin gene might explain the previously observed heritability of insulin action (11, 12) in members of familial T2DM kindreds. In this study, we identified nine variants in and near the human resistin gene. We show a statistically significant influence of resistin variants on insulin sensitivity in nondiabetic members of familial T2DM kindreds in interaction with body mass index (BMI) as a measure of obesity.

Subjects and Methods

Experimental subjects

All studies were conducted on individuals of Northern European ancestry ascertained in Utah, as described in detail elsewhere (13). All subjects provided written informed consent under a protocol approved by the University of Utah Institutional Review Board. Insulin sensitivity was determined by tolbutamide-modified iv glucose tolerance tests with minimal model calculation of the insulin sensitivity index (SI), as described previously (12). Mutation detection was performed in 44 unrelated individuals with T2DM and 20 unrelated nondiabetic family members. The nondiabetic family members comprised the 10 unrelated individuals with the highest indices of SI [range, 21.25 x 10-5 min-1/(pmol/liter) to 71.13 x 10-5 min-1/(pmol/liter)] and the 10 unrelated individuals with the lowest values of SI [range, 0.48 x 10-5 min-1/(pmol/liter) to 1.85 x 10-5 min-1/(pmol/liter)]. Association studies with T2DM were conducted in 68 unrelated family members with T2DM, 61 unrelated individuals ascertained individually for T2DM and a family history of diabetes, and 118 nondiabetic control individuals, most ascertained as spouses of family members. The effect of resistin sequence variants on insulin sensitivity was tested in 119 nondiabetic members from 26 families for whom measurements of SI and resistin polymorphism typing were available.

Materials and methods

Molecular screening. Intron-exon structure was derived by comparison of the resistin cDNA sequence (7) and the chromosome 19 draft sequence (GenBank accession no. NT_011145). Exon 1 is untranslated. Intron 3 showed disagreement between the two draft sequences, and primers were designed to avoid the area of disagreement, which we did not resolve. We screened approximately 800 bp of 5' flanking sequence, including the untranslated exon, exons 2–4, all of introns 1 and 2, 220 bp of intron 3 (excluding the uncertain gap of 100–200 bp), and 160 bp of 3' flanking region (Fig. 1Go). Four sets of primers gave amplicons of 320–550 bp, which were subsequently digested to fragments of 100–280 bp before single-strand conformation polymorphism (SSCP) analysis under two conditions: 5% acrylamide with 10% glycerol, and 1x mutation detection enhancement gel (BioWhittaker Molecular Applications, Rockland, ME). PCR primers and oligonucleotide ligation assay primers and conditions are available from the authors. We have shown previously that these two conditions have nearly 100% sensitivity (14). Each SSCP variant was confirmed by direct, bidirectional sequencing (15) using M13 forward and reverse sequencing primer sequences appended to each forward and reverse PCR amplification primer. Amplification products were column purified (Qiaquick PCR purification kit; QIAGEN, Chatsworth, CA) before direct sequencing. PCR product was sequenced with fluorescent infrared dyes and detected on a Li-Cor GR4200 sequencer (Li-Cor, Inc., Lincoln, NE) using the Direct Cycle Sequencing Kit with 7-deaza-dGTP (Amersham Pharmacia Biotech, Inc., Piscataway, NJ).



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  		Figure 1. Map of resistin gene with sequence variation. The figure shows the layout of the resistin gene, including the first nontranslated exon. Exons are denoted as boxes, untranslated regions are shown in light gray, and coding regions are shown in black. SNPs are shown with arrows and correspond to Table 1Go. Horizontal arrows show the locations of the primers used for screening and sequence confirmation. Nucleotide locations are referenced to the beginning of the coding sequence in exon 2, as shown in Table 1Go.

 
Single nucleotide polymorphism (SNP) typing. Four sequence variants (SNPs) initially appeared sufficiently frequent (minor allele frequency >5%) on SSCP screening of the 64 individuals to type in the population association studies and metabolic panels (Table 1Go and Fig. 1Go). SNPs 3 and 6–8 and the GAT microsatellite (Table 1Go) were either in complete linkage disequilibrium (SNPs 2 and 3) or were seen in fewer than four individuals on initial screening. SNP1 (putative promoter region, -179 from transcription start) was typed with enzyme EarI (New England Biolabs, Inc., Beverly, MA), and SNP 5 was typed with enzyme BanI (New England Biolabs, Inc.). SNP2 and SNP4 were typed using an oligonucleotide ligation assay (16) in which the allele-specific primers were labeled with {gamma}-32P-ATP and the common primer was unlabeled. Radioactive images were collected on a Storm optical scanner (Molecular Dynamics, Inc., Sunnyvale, CA). Images were scored with the Scanalytics GeneImagR system (Scanalytics, Inc., Fairfax, VA) and exported into Excel spreadsheets, which in turn were converted to Access database files for analysis and further manipulation.


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  		Table 1. Summary of resistin sequence variation

 
Statistical analysis. Association of each resistin SNP with diabetes was tested using allelic frequencies and standard 2 x 2 contingency tables. Because SNP4 was rare on actual typing, it was not included in subsequent analyses. Association of each resistin SNP with altered insulin sensitivity used mixed effects regression models, as we have described previously (17). This method corrects for family relationships but allows entry of covariate and interaction terms (17). For each SNP, we tested SI as the dependent variable; BMI and age as covariates; gender, genotype, and diagnosis (impaired glucose tolerance vs. normal) as fixed factors; and pedigree membership as a random factor (18). All skewed variables (BMI, SI) were natural logarithmically transformed to normality before analysis. Because the three SNPs are in strong linkage disequilibrium, and similarly the analyses with and without interaction with BMI are correlated, we report all results without Bonferroni correction. All analyses were performed using SPSS for Windows (SPSS, Inc., Chicago, IL). Linkage disequilibrium was calculated after establishing haplotype frequencies using gene-counting and the expectation maximization algorithm (19) using the EH and 2LD computer programs (20).

Results

We identified eight SNPs and one trinucleotide (GATn) repeat among 64 individuals, as described above. The results are reported in Table 1Go and shown in Fig. 1Go. No variant altered the coding sequence, and only one variant was located in the 5' flanking region. SNPs 2 and 3 gave identical patterns in all sequenced individuals and, thus, appeared to be in complete linkage disequilibrium. Only SNP2 was investigated further. Minor allele frequencies of SNP6, SNP7, and SNP 8, along with the GAT repeat were too rare (<5% based on SSCP screening) to justify further typing. Because noncoding variants may alter transcription or translation of the resistin gene or be in linkage disequilibrium with an undetected variant that might alter resistin mRNA levels, we tested for an association with the four SNPs (SNPs 1, 2, 4, and 5; Table 1Go and Fig. 1Go), for which the minor allele frequency appeared to exceed 10% on initial screening. We first examined 129 unrelated diabetic individuals of Northern European descent (87 men and 42 women; mean BMI, 27.8 ± 8.1) and 118 unrelated nondiabetic control individuals (54 men and 64 women; mean BMI, 27.8 ± 6.2). SNP4 (nucleotide 282483) was rare on further typing (<1%); thus, we had insufficient power to determine an association. Allele frequencies were statistically equivalent among individuals with T2DM and nondiabetic control individuals for the three remaining SNPs, SNP1, SNP2, and SNP5 (Table 1Go).

We next examined 119 nondiabetic members from 26 families for whom we had both resistin SNP genotypes and insulin sensitivity as determined by frequently sampled iv glucose tolerance test and minimal model analysis (12, 21). No resistin gene variant had an effect on BMI (P > 0.16). We then used a mixed effect model to test for an effect of resistin gene polymorphisms on SI as the dependent variable, with the natural logarithm of BMI as a covariate, while controlling for family membership, gender, and glucose tolerance status. Only SNP1 in the 5' flanking region showed statistically significant effects on SI (P = 0.038), although a trend was also seen for SNP2 (P = 0.07). SNP5 had no effect on SI, and we had insufficient power to evaluate the role of SNP4 due to the low minor allele frequency.

Because resistin is hypothesized to be one link between obesity and insulin resistance (22), we repeated the mixed model analysis to include an interaction between resistin variants SNP1, SNP2, and SNP5 and logarithmically transformed BMI. Genotypes for all three variants showed statistically significant interaction with BMI to determine SI, with P values for the interaction of SNP1 and BMI of 0.011, SNP2 and BMI of 0.005, and SNP5 and BMI of 0.010. SNP1, SNP2, and SNP5 were in strong linkage disequilibrium (Table 2Go; P < 10-5 for all associations), as might be anticipated given the relatively close distance between SNPs (<1 kb).


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  		Table 2. Linkage disequilibrium among common resistin SNPs

 
To further explore the interaction of SNP1, SNP2, and SNP5 with obesity, we repeated the mixed model analysis but divided our subjects into four groups according to BMI: under 25.0, from 25.0–30.0, over 30.0–35.0, and over 35.0. Thus, BMI was converted to a fixed factor rather than a covariate. In this analysis, only SNP1 and SNP2 remained as statistically significant determinants of SI, and significance was reduced to P = 0.038 and P = 0.028, respectively. Examination of marginal means for SI by obesity class and by genotype shows that individuals who carry the rare allele for SNP1 (CG heterozygotes) have improved insulin sensitivity over individuals with the common (CC) genotype (Fig. 2Go); similarly, the common genotype for SNP2 reduced SI with increasing BMI (Fig. 3Go).



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  		Figure 2. Effects of SNP1 in interaction with obesity on insulin sensitivity. The figure shows the marginal means for SI from the mixed effect model, but with obesity coded in four classes, as shown beneath the figure and described in the text. The number of individuals in each group and genotype is shown beneath the figure. The dashed line and open square represent the common homozygous genotype, and the solid line and solid circle represent carriers of the rare allele. Horizontal lines represent 95% confidence intervals for the residual value of SI. In this model, both SNP1 and the interaction terms are significant at P = 0.001 and P = 0.035, respectively.

 


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  		Figure 3. Effects of SNP2 in interaction with obesity on insulin sensitivity. The figure shows the marginal means for SI from the mixed effect model, as in Fig. 1Go, but for SNP2. The number of individuals in each group and genotype is shown beneath the figure. The dashed line and open square represent the common homozygous genotype, and the solid line and solid circle represent carriers of the rare allele. Horizontal lines represent 95% confidence intervals for the residual value of SI. In this analysis with SI as the dependent variable, SNP2 was significant at P < 0.001, and the interaction of SNP2 and obesity class was significant at P = 0.028.

 
Discussion

Although reduced insulin sensitivity commonly accompanies obesity, the variation in insulin resistance even among obese individuals is considerable. Furthermore, multiple studies have demonstrated that insulin sensitivity is familial. Genetic variation in adipocyte genes that alter insulin sensitivity, thus, could explain the observed genetic predisposition to insulin resistance in combination with obesity. Resistin seems to be a good candidate for such variation. Resistin levels in the mouse were increased in insulin-resistant states and were decreased by the thiazolidinedione class of insulin sensitizers (7). Insulin sensitivity and glucose tolerance were improved when circulating resistin was neutralized with antibodies to the protein (7). Based on these data, resistin was hypothesized to be the signal to decrease insulin-stimulated glucose uptake (7). We screened the human resistin gene for sequence variants and identified a total of nine variants. None of the variants are expected to alter the coding sequence, and only three of these variants were sufficiently common to justify further analysis. Of these variants, none were associated with T2DM in a case control study. This finding is not surprising, because insulin resistance is only one component of the risk of T2DM and resistin alone might be unlikely to predispose to diabetes. Furthermore, our association study was not powered to detect a minor role in increasing diabetes risk. We estimated only 40–50% power to detect a 10% difference in minor allele frequencies between diabetic individuals and nondiabetic individuals for the frequency range of these three variants. Similarly, calpain-10 is associated with decreased glucose oxidation and increased postload glucose but not diabetes in Pima Indians (23) and in the families under study here (24).

In contrast to studies of diabetes, we do show an effect of resistin variants on insulin sensitivity among individuals at high risk for future diabetes. The effects of the three resistin sequence variants on SI are most striking when examined in the context of interaction with BMI, where all three variants show similar effect. In each case, the common homozygous genotype appears to reduce insulin sensitivity relative to the heterozygous genotype (see Figs. 2Go and 3Go). Similar findings have been reported for calpain-10 (23, 24). One might speculate that these noncoding variants alter mRNA levels or perhaps translation and, thus, circulating resistin levels. That alteration would be more pronounced in individuals with higher BMI and, thus, greater fat mass. Because the three variants are in strong linkage disequilibrium, the variant responsible cannot be determined from this study. Indeed, the functional variant could be in a region further upstream or in the small region of intron 3 that was not sequenced.

Because each hypothesis we tested was correlated, we reported the significance of our results without Bonferroni correction. Were that correction fully included for nine tests, only the effects of SNP2 in interaction with BMI would remain statistically significant. However, given the correlation between the SNPs, the correlation between tests, and the finding of significant (P < 0.05) association in four of six tests of the hypothesis that resistin alters insulin sensitivity, we believe this correction would be overly conservative. The number of individuals homozygous for the rare allele at each of these variants was small, and because the effect of these variants seems to be primarily in the most obese individuals, we had little power to detect a gene dosage effect. Ultimately, further study, including replication of these results in other populations that include more subjects with BMI over 30, will be required to confirm the importance of these variants in the relationship of obesity and insulin resistance and to determine the variant responsible.

Two recent published studies have raised questions about the role of resistin in humans (9, 10). These studies have questioned whether human resistin is indeed expressed in adipose or is instead an inflammatory marker. Furthermore, the homology between human and mouse resistin is incomplete, raising the possibility that human resistin is more closely related to other resistin-like molecules and may have different action than mouse resistin (25). Even the role of mouse resistin may be in doubt. Recent studies in mouse models of genetic obesity and insulin resistance suggested that resistin was suppressed rather than increased by obesity and was increased rather than decreased by thiazolidinediones (26). Although our data would support a functional role of resistin in human insulin sensitivity, further work is clearly needed to explore the role of resistin in insulin sensitivity and obesity.

In summary, our data suggest that noncoding sequence variation in the resistin gene may alter the interaction of BMI and SI. The mechanism of action of this variation remains to be determined. To our knowledge, this study is the first evidence that human resistin may play a role in insulin sensitivity. However, our data are based on members of only 26 families with a very strong propensity to T2DM. The hypotheses proposed by this study must be confirmed in other populations and other ethnic groups, and in vitro studies of these variants will be needed to identify the actual biological variant that presumably alters the interaction between resistin gene expression and obesity.

Acknowledgments

Footnotes

This work was supported in part by the Research and Development Office of the Department of Veterans Affairs, Central Arkansas Veterans Healthcare System, by NIH/NIDDK Grant DK39311, and by a grant to the University of Arkansas for Medical Sciences General Clinical Research Center (Grant M01RR14288 from NIH/NCRR). Subject ascertainment was supported in part by a grant from NIH/NCRR to the General Clinical Research Center of the University of Utah, and by a GENNID Family Center Acquisition grant from the American Diabetes Association.

Abbreviations: BMI, Body mass index; SI, insulin sensitivity index; SNP, single nucleotide polymorphism; SSCP, single-strand conformation polymorphism; T2DM, type 2 diabetes.

Received December 4, 2001.

Accepted February 15, 2002.

References

  1. Martin BC, Warram JH, Rosner B, Rich SS, Soeldner JS, Krolewski AS 1992 Familial clustering of insulin sensitivity. Diabetes 41:850–854[Abstract]
  2. Warram JH, Martin BC, Krolewski AS 1990 Slow glucose removal rate and hyperinsulinemia precede the development of type II diabetes in the offspring of diabetic parents. Ann Intern Med 113: 909–915
  3. Boden G 1997 Role of fatty acids in the pathogenesis of insulin resistance and NIDDM. Diabetes 46:3–10[Abstract]
  4. Moller DE 2000 Potential role of TNF-{alpha} in the pathogenesis of insulin resistance and type 2 diabetes. Trends Endocrinol Metab 11:212–217[CrossRef][Medline]
  5. Fernandez-Real JM, Broch M, Vendrell J, Gutierrez C, Casamitjana R, Pugeat M, Richart C, Ricart W 2000 Interleukin-6 gene polymorphism and insulin sensitivity. Diabetes 49:517–520[Abstract]
  6. Weyer C, Funahashi T, Tanaka S, Hotta K, Matsuzawa Y, Pratley RE, Tataranni PA 2001 Hypoadiponectinemia in obesity and type 2 diabetes: close association with insulin resistance and hyperinsulinemia. J Clin Endocrinol Metab 86:1930–1935[Abstract/Free Full Text]
  7. Steppan CM, Bailey ST, Bhat S, Brown EJ, Banerjee RR, Wright CM, Patel HR, Ahima RS, Lazar MA 2001 The hormone resistin links obesity to diabetes. Nature 409:307–312[CrossRef][Medline]
  8. Kim KH, Lee K, Moon YS, Sul HS 2001 A cysteine-rich adipose tissue-specific secretory factor inhibits adipocyte differentiation. J Biol Chem 276:11252–11256[Abstract/Free Full Text]
  9. Nagaev I, Smith U 2001 Insulin resistance and type 2 diabetes are not related to resistin expression in human fat cells or skeletal muscle. Biochem Biophys Res Commun 285:561–564[CrossRef][Medline]
  10. Savage DB, Sewter CP, Klenk ES, Segal DG, Vidal-Puig A, Considine RV, O’Rahilly S 2001 Resistin/fizz3 expression in relation to obesity and peroxisome proliferator-activated receptor-gamma action in humans. Diabetes 50:2199–2202[Abstract/Free Full Text]
  11. Schumacher MC, Hasstedt SJ, Hunt SC, Williams RR, Elbein SC 1992 Major gene effect for insulin levels in familial NIDDM pedigrees. Diabetes 41:416–423[Abstract]
  12. Elbein SC, Hasstedt SJ, Wegner K, Kahn SE 1999 Heritability of pancreatic ß-cell function among nondiabetic members of Caucasian familial type 2 diabetic kindreds. J Clin Endocrinol Metab 84:1398–1403[Abstract/Free Full Text]
  13. Elbein SC, Hoffman MD, Teng K, Leppert MF, Hasstedt SJ 1999 A genome-wide search for type 2 diabetes susceptibility genes in Utah Caucasians. Diabetes 48:1175–1182[Abstract]
  14. Elbein SC, Teng K, Eddings K, Hargrove D, Scroggin E 2000 Molecular scanning analysis of hepatocyte nuclear factor 1{alpha} (TCF1) gene in typical familial type 2 diabetes in African Americans. Metabolism 49:280–284[CrossRef][Medline]
  15. Shevchenko YO, Bale SJ, Compton JG 2000 Mutation screening using automated bidirectional dideoxy fingerprinting. BioTechniques 28:134–138[Medline]
  16. Delahunty C, Ankener W, Deng Q, Eng J, Nickerson DA 1996 Testing the feasibility of DNA typing for human identification by PCR and an oligonucleotide ligation assay. Am J Hum Genet 58:1239–1246[Medline]
  17. Elbein SC, Sun J, Scroggin E, Teng K, Hasstedt SJ 2001 Role of common sequence variants in insulin secretion in familial type 2 diabetic kindreds: the sulfonylurea receptor, glucokinase, and hepatocyte nuclear factor 1{alpha} genes. Diabetes Care 24:472–478[Abstract/Free Full Text]
  18. Allison DB, Heo M, Kaplan N, Martin ER 1999 Sibling-based tests of linkage and association for quantitative traits. Am J Hum Genet 64:1754–1763[CrossRef][Medline]
  19. Long JC, Williams RC, Unbanek M 1995 An E-M algorithm and testing strategy for multiple-locus haplotypes. Am J Hum Genet 56:799–810[Medline]
  20. Xie X, Ott J 1993 Testing linkage disequilibrium between a disease gene and marker loci. Am J Hum Genet 53:1107 (Abstract)[Medline]
  21. Bergman RN 1989 Toward physiological understanding of glucose tolerance: minimal model approach. Diabetes 39:1512–1527
  22. Berger A 2001 Resistin: a new hormone that links obesity with type 2 diabetes. BMJ 322:193[Free Full Text]
  23. Baier LJ, Permana PA, Yang X, Pratley RE, Hanson RL, Shen GQ, Mott D, Knowler WC, Cox NJ, Horikawa Y, Oda N, Bell GI, Bogardus C 2000 A calpain-10 gene polymorphism is associated with reduced muscle mRNA levels and insulin resistance. J Clin Invest 106:R69–R73
  24. Elbein SC, Chu W, Ren Q, Hemphill C, Schay J, Cox NJ, Hanis CL, Hasstedt SJ 2002 Role of calpain-10 gene variants in familial type 2 diabetes in Caucasians. J Clin Endocrinol Metab 87:650–654[Abstract/Free Full Text]
  25. Steppan CM, Brown EJ, Wright CM, Bhat S, Banerjee RR, Dai CY, Enders GH, Silberg DG, Wen X, Wu GD, Lazar MA 2001 A family of tissue-specific resistin-like molecules. Proc Natl Acad Sci USA 98:502–506[Abstract/Free Full Text]
  26. Way JM, Gorgun CZ, Tong Q, Uysal KT, Brown KK, Harrington WW, Oliver Jr WR, Willson TM, Kliewer SA, Hotamisligil GS 2001 Adipose tissue resistin expression is severely suppressed in obesity and stimulated by peroxisome proliferator-activated receptor {gamma} agonists. J Biol Chem 276:25651–25653[Abstract/Free Full Text]



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S. R. Smith, F. Bai, C. Charbonneau, L. Janderova, and G. Argyropoulos
A Promoter Genotype and Oxidative Stress Potentially Link Resistin to Human Insulin Resistance
Diabetes, July 1, 2003; 52(7): 1611 - 1618.
[Abstract] [Full Text] [PDF]

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M.-S. Tan, S.-Y. Chang, D.-M. Chang, J. C.-R. Tsai, and Y.-J. Lee
Association of Resistin Gene 3'-Untranslated Region +62G->A Polymorphism with Type 2 Diabetes and Hypertension in a Chinese Population
J. Clin. Endocrinol. Metab., March 1, 2003; 88(3): 1258 - 1263.
[Abstract] [Full Text] [PDF]

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L. Chen and B. L. G. Nyomba
Glucose Intolerance and Resistin Expression in Rat Offspring Exposed to Ethanol in Utero: Modulation by Postnatal High-Fat Diet
Endocrinology, February 1, 2003; 144(2): 500 - 508.
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