PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of diabetesSubscribeSearchDiabetes JournalAmerican Diabetes Association
 
Diabetes. May 2010; 59(5): 1276–1282.
Published online Feb 25, 2010. doi:  10.2337/db09-1700
PMCID: PMC2857909
Variants in ASK1 Are Associated With Skeletal Muscle ASK1 Expression, In Vivo Insulin Resistance, and Type 2 Diabetes in Pima Indians
Li Bian, Robert L. Hanson, Victoria Ossowski, Kim Wiedrich, Clinton C. Mason, Michael Traurig, Yunhua L. Muller, Sayuko Kobes, William C. Knowler, Leslie J. Baier, and Clifton Bogardus
From the Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Department of Health and Human Services, Phoenix, Arizona.
Corresponding author: Clifton Bogardus, cbogardus/at/phx.niddk.nih.gov.
Received November 17, 2009; Accepted February 7, 2010.
OBJECTIVE
Prior genome-wide association and exon array expression studies both provided suggestive evidence that apoptosis signal regulating kinase 1 (ASK1) may influence in vivo insulin action in Pima Indians. Genetic variants in or near ASK1 were analyzed to assess the role of this gene in insulin action and type 2 diabetes.
RESEARCH DESIGN AND METHODS
Genotypic data from 31 variants were used to determine the linkage disequilibrium pattern across ASK1 in Pima Indians. Eight tag SNPs were initially genotyped in 3,501 full-heritage Pima Indians. Replication for association with diabetes was assessed in a second population-based sample of 3,723 Native Americans and the published DIAGRAM study. Quantitative traits were analyzed in 536 nondiabetic Native Americans, and ASK1 expression was examined in skeletal muscle of 153 nondiabetic Native Americans.
RESULTS
Three tag SNPs were associated with type 2 diabetes (rs35898099, P = 0.003, odds ratio [95% CI] 1.27 [1.08–1.47]; rs1570056, P = 0.007, 1.19 [1.05–1.36]; rs7775356, P = 0.04, 1.14 [1.01–1.28]) in the full-heritage Pima Indians. The association with rs35898099 was replicated in a second sample of Native Americans (P = 0.04, 1.22 [1.01–1.47]), while that for rs1570056 was replicated in the DIAGRAM study of Caucasians (Z statistic based P = 0.026; fixed-effect model, 1.06 [1.00–1.12]). The diabetes risk allele for rs1570056 was associated with reduced insulin action as assessed by either HOMA-IR in 2,549 nondiabetic full-heritage Pima Indians (P = 0.027) or a hyperinsulinemic-euglycemic clamp among 536 nondiabetic Native Americans (P = 0.02). Real-time PCR identified a positive correlation between ASK1 expression in skeletal muscle biopsies and in vivo insulin action (P = 0.02, r = 0.23), and the risk allele for rs1570056 was associated with lower ASK1 expression (P = 0.003, r = −0.22).
CONCLUSIONS
ASK1 variants may increase susceptibility to type 2 diabetes by decreasing insulin sensitivity via reduced ASK1 expression.
The Pima Indians of Arizona have an extremely high prevalence of type 2 diabetes (1). Their diabetes is characterized by obesity, decreased insulin action (insulin resistance), impaired insulin secretion, as well as increased endogenous glucose production (2), and the first three characteristics are predictive of type 2 diabetes and heritable in this population (3,4). To identify genetic variants that affect the metabolic risk factors for diabetes, we previously completed a genome-wide association study (GWAS) in 536 metabolically phenotyped nondiabetic Native Americans using the Affymetrix 100K Mapping Array (Bogardus et al., unpublished data) and also examined gene expression profiles in skeletal muscle biopsies from nondiabetic Native Americans using an Affymetrix GeneChip Exon 1.0 ST Array (Bogardus et al., unpublished data). The three traits that predict type 2 diabetes, namely obesity, measures of in vivo insulin action, and acute insulin secretion, were investigated for association in these two preliminary studies. Genes associated with the same metabolic trait in both of the two genome-wide studies (<20 genes for each of the three traits) were prioritized for further investigation. One such prioritized gene is apoptosis signal regulating kinase 1 (ASK1). Preliminary evidence from the GWAS suggested that one intronic single nucleotide polymorphism (SNP) in ASK1 (rs10484491) was associated with in vivo insulin action, as determined by the hyperinsulinemic-euglycemic clamp, and evidence from the exon array study suggested that ASK1 expression levels were also correlated with in vivo insulin action. Therefore, ASK1 was directly analyzed as a candidate gene for type 2 diabetes in Pima Indians.
All subjects were part of our ongoing longitudinal study of the etiology of type 2 diabetes among the Gila River Indian Community in Arizona (1). Association with type 2 diabetes was initially assessed in a population-based sample of 3,501 full-heritage Pima Indians. Among these individuals, 1,561 had been diagnosed with type 2 diabetes and 1,940 were nondiabetic at the time of their last exam. Replication for association with type 2 diabetes was assessed in a second population-based sample of 3,723 subjects, most of whom were of mixed-heritage (on average, their reported heritage was one-half Pima and three-quarters American Indian). Among this replication sample, 750 subjects had been diagnosed with type 2 diabetes and 2,973 individuals were nondiabetic at their last exam. Homeostasis model assessment of insulin resistance (HOMA-IR) was analyzed among 2,549 subjects of the full-heritage Pima Indian sample who had available fasting plasma glucose and insulin data measured from the last nondiabetic exam at age ≥15 years. Additionally, more precise measures of diabetes-related quantitative traits were analyzed in 536 nondiabetic Native Americans who had also participated in our 100K GWAS of pre-diabetic traits. ASK1 mRNA level was assessed using real-time PCR in skeletal muscle biopsies provided by 153 nondiabetic Native Americans involved in the exon array study, among whom 116 subjects had undergone a hyperinsulinemic-euglycemic clamp to determine their whole-body insulin sensitivity during the same period for which the biopsy was ascertained. Detailed characteristics of these sample sets are given in Table 1. All studies were approved by the tribal council of the Gila River Indian Community and the institutional review board of the National Institute of Diabetes and Digestive and Kidney Diseases.
TABLE 1
TABLE 1
Characteristics of the sample sets used in this study
Metabolic phenotyping.
A 75-g oral glucose tolerance test was used to determine diabetes as defined by the criteria of the World Health Organization (5). HOMA-IR was calculated as fasting plasma glucose (mmol/l) × fasting plasma insulin (μU/ml)/22.5. Among subjects studied as inpatients, body composition was estimated by underwater weighing or by total-body dual-energy X-ray absorptiometry (DPX-1; Lunar Radiation) (6). The hyperinsulinemic-euglycemic clamp technique was used to determine insulin-stimulated glucose disposal rate (7). Rates of endogenous glucose production basally and during the clamp were measured using tritiated glucose as previously described (7). The acute insulin response to a 25-g glucose bolus infusion was calculated as previously described (7). Plasma free fatty acid concentrations were measured using a colorimetric assay (Wako Chemicals).
Analysis of ASK1 expression levels in skeletal muscle.
Percutaneous needle biopsies were carried out on the vastus lateralis muscle under local anesthesia with 1% lidocaine after a 12-h overnight fast, and the biopsy specimens were immediately frozen in liquid nitrogen (8). Total RNA was extracted using TRIzol reagent (Invitrogen, Carlsbad, CA) and was further purified using a RNeasy Micro Kit (Qiagen, Valencia, CA). cDNA was synthesized using a RETROscript Kit (Ambion, Austin, TX). ASK1 expression levels were quantified using TaqMan real-time PCR with an ABI PRISM 7700 system (Applied Biosystems, Foster City, CA) using the specific probe and primers for ASK1 (assay ID: Hs00178726_m1; Applied Biosystems). Each sample was run in triplicate and the ASK1 expression level was normalized to the mRNA level of cyclophilin A (assay ID: Hs99999904_m1; Applied Biosystems). The relative ASK1 expression level was determined by the ΔΔCt method according to the manufacturer's protocol (Applied Biosystems).
Sequencing and genotyping.
Genotyping and quality-control methods for the 100K GWAS for pre-diabetic traits were the same as previously described for the 100K GWAS for type 2 diabetes (9). To identify novel variants in ASK1, all exons, exon-intron boundaries, and 1.2 kb of the putative promoter region were sequenced in 30 nondiabetic Pima Indians who were part of the prior genome-wide exon array study. Sequencing was performed using the Big Dye Terminator (Applied Biosystems) on an automated DNA capillary sequencer (model 3730XL; Applied Biosystems). In addition to six variants identified by sequencing and the SNP providing suggestive evidence for association with insulin action in the prior GWAS, 24 additional database SNPs were directly selected from NCBI dbSNP (Build 36) to provide a denser coverage of the unsequenced intronic regions. The 24 dbSNPs spanned the entire ASK1 locus with an inter-marker distance of 10 ± 7 kb (mean ± SD) and had an average reported heterozygosity >10%. All these 31 SNPs were genotyped in 1,500 Pima Indians to determine the linkage disequilibrium (LD) pattern across ASK1 and select tag SNPs. Genotyping was performed by SNPlex (Applied Biosystems) after the manufacturer's protocol.
Statistical analysis.
Statistical analyses were performed using SAS software version 9.1 (SAS Institute, Cary, NC). The association of traits with genotype was assessed with an additive model by assigning a numeric variable (0, 1, or 2) to the genotype based on the number of a given allele for each individual. Logistic regression was used to assess the association of genotype with type 2 diabetes, whereas linear regression was used for analysis of continuous variables. Both logistic and linear models were fit with the generalized estimating equation procedure to account for family membership and other potential confounding variables (10). In the replication group, which included many individuals of mixed heritage, the individual estimate of European admixture was also used as a covariate; these estimates were derived by the method of Hanis et al. (11) from 39 markers with large difference in allele frequency between populations (12). A combined test of association with type 2 diabetes for the full-heritage and replication groups was conducted by the inverse variance method (13). The LD pattern was evaluated by Haploview (version 3.32). Tag SNPs were selected using the Tagger algorithm (14) among those with a minor allele frequency >0.05 with a pairwise r2 ≥0.80 taken as indicative of redundancy.
Sequencing of the exons, exon-intron boundaries, and promoter region of ASK1 in 30 nondiabetic Pima Indians identified six SNPs, none of which were novel (supplementary Table 1, available in an online appendix at http://diabetes.diabetesjournals.org/cgi/content/full/db09-1700/DC1). A total of 31 variants (six identified by sequencing, 1 from the prior GWAS, and 24 selected from dbSNP; supplementary Table 1) were genotyped in 1,500 Pima Indians to determine the LD structure across ASK1. All of these SNPs were in the Hardy-Weinberg equilibrium, and eight tag SNPs were then selected to capture all the common variants (minor allele frequency >0.05) with a pairwise r2 ≥0.8 (Fig. 1).
FIG. 1.
FIG. 1.
Relative position and LD pattern of the 31 variants across the ASK1 locus in Pima Indians. LD is shown as r2 and the eight tag SNPs (no. 1, 5, 7, 8, 9, 10, 20, and 31) were selected by Tagger algorithm (r2 ≥0.8, minor allele frequency >0.05). (more ...)
The eight tag SNPs were initially genotyped in a population-based sample of 3,501 full-heritage Pima Indians to determine their association with type 2 diabetes (Table 2; quality-control information provided in supplementary Table 2). Three of the tag SNPs were significantly associated with type 2 diabetes (rs35898099, P = 0.003, odds ratio [95% CI] 1.27 [1.08–1.47]; rs1570056, P = 0.007, 1.19 [1.05–1.36]; rs7775356, P = 0.04, 1.14 [1.01–1.28)]; adjusted for age, sex, and birth year; Table 2). These three SNPs were further genotyped in a second population-based sample of Native Americans (n = 3,723). rs35898099 was also nominally associated with type 2 diabetes in this second sample (P = 0.04, 1.22 [1.01–1.47], adjusted for age, sex, birth year, and Pima heritage; Table 2). Analyzing the combined samples (n = 7,224) provided significant associations with type 2 diabetes (adjusted P = 0.0004–0.04, odds ratio 1.11–1.24; Table 2) for all three SNPs. To determine if variants in this gene associate with type 2 diabetes in other ethnic groups, SNPs across ASK1 that were analyzed in the DIAGRAM meta-analysis of Caucasians (15) were examined. rs1570056 also showed nominal association with type 2 diabetes in the DIAGRAM meta-analysis (Z statistic based, P = 0.027) and the risk allele is consistent with the Pimas' risk allele (fixed-effect model, P = 0.06, odds ratio [95% CI] 1.06 [1.00–1.12] per copy of the C allele; Table 2). When the DIAGRAM results for rs1570056 are combined with those from the Pima studies, the summary odds ratio is 1.07 per copy of the C allele (95% CI 1.02–1.13, P = 0.008). rs35898099, which was associated with type 2 diabetes in both Native American samples, was not included in the DIAGRAM study or HapMap CEU database. By sequencing 90 Caucasian subjects, we find that rs35898099 is also common in Caucasians (minor allele A frequency = 0.31); however, its association with diabetes in this population remains to be determined. We also performed a conditional analysis for rs1570056 and rs35898099 to assess the possible relevance between their associations with type 2 diabetes in Pima studies. In the full-heritage Pima study, both of the SNPs still showed significant associations with type 2 diabetes conditional on the effect of each other (P = 0.037 and 0.02, for rs1570056 and rs35898099, respectively), indicating their effects on type 2 diabetes may be somewhat independent in the full-heritage Pima population. However, when the Native American sample was combined with the full-heritage Pima sample, rs35898099 but not rs1570056 was significantly associated with type 2 diabetes conditional on the effect of the other SNP (P = 0.001 for rs35898099 conditional on rs1570056; P = 0.268 for rs1570056 conditional on rs35898099).
TABLE 2
TABLE 2
Association of ASK1 tag SNPs with type 2 diabetes in the Pima studies (full-heritage Pima Indian, Native American, and combined samples), the DIAGRAM study, and the combined analysis of full-heritage Pimas, Native Americans, and DIAGRAM Caucasians (meta-analysis) (more ...)
We further investigated whether the diabetes-associated SNPs were associated with quantitative traits that predict this disease. Among the full-heritage Pima Indians who had available HOMA-IR information when they were nondiabetic (n = 2,549), rs1570056 was associated with HOMA-IR, where individuals carrying the diabetes-risk allele (C) were more insulin resistant (P = 0.027, adjusted for age, sex, and BMI; data not shown). The relationship with insulin resistance was investigated further by analyzing 536 nondiabetic Native Americans who had undergone the hyperinsulinemic-euglycemic clamp, where subjects carrying the diabetes risk allele (C) had decreased rates of insulin-stimulated glucose disposal (P = 0.02, adjusted for age, sex, percent body fat, family membership, and Pima heritage; Table 3). The association with insulin resistance was also reflected by the increased plasma insulin levels (adjusted P = 0.04 for both fasting and 2-h insulin) during an oral glucose tolerance test. In contrast, no significant difference in percent body fat or measure of acute insulin secretion, by genotype of rs1570056, was observed (Table 3). Similarly, no significant association with rates of endogenous glucose production basally or during the clamp was observed for rs1570056 (Table 3); this suggests that ASK1 has no specific effect on hepatic insulin resistance. Measures of fasting plasma free fatty acid concentration were available on a small number (n = 204) of individuals, and the mean levels were comparable among the different genotype groups for rs1570056 (P = 0.91, data not shown).
TABLE 3
TABLE 3
Associations of rs1570056 (C/T) with diabetes-related traits in the nondiabetic Native Americans who had been metabolically phenotyped
To determine the potential mechanism whereby SNPs within ASK1 influence insulin resistance and type 2 diabetes, ASK1 expression levels were determined by quantitative real-time PCR in muscle cDNA isolated from 153 nondiabetic Native Americans. Adjusted for age, sex, percent body fat, and Pima heritage, the diabetic risk allele (C) of rs1570056 was significantly associated with reduced ASK1 expression (P = 0.003, r = −0.22, n = 153; Fig. 2). Furthermore, among 116 of these nondiabetic subjects who had undergone the hyperinsulinemic clamp at the time of their biopsy, ASK1 expression levels were positively correlated with in vivo insulin action (P = 0.02, r = 0.23, adjusted for age, sex, percent body fat, and Pima heritage; Fig. 3).
FIG. 2.
FIG. 2.
Association of rs1570056 with ASK1 expression in skeletal muscle from 153 nondiabetic Native Americans. Data were raw means ± SE. P value was calculated under an additive model and adjusted for age, sex, percent body fat, and Pima heritage. Before (more ...)
FIG. 3.
FIG. 3.
Positive correlation between ASK1 expression in skeletal muscle and in vivo insulin action (insulin-stimulated glucose disposal). Before the analysis, both in vivo insulin action (insulin-stimulated glucose disposal) and the relative ASK1 expression levels (more ...)
Although insulin resistance is a predominant clinical feature of type 2 diabetes, most of the type 2 diabetes risk loci identified in prior GWASs appear to affect insulin secretion, but not insulin sensitivity (16). A key finding of the present study is that variations in ASK1 (tagged by rs1570056 in Pima Indians) increase risk for both in vivo insulin resistance and type 2 diabetes, where the risk alleles are further associated with reduced ASK1 expression in skeletal muscle and lower ASK1 expression levels are correlated with reduced insulin sensitivity in vivo. It remains unclear why rs1570056 was associated with type 2 diabetes in the initial population-based sample of full-heritage Pima Indians and the DIAGRAM Caucasians but not the second population-based sample of Native Americans that included mixed-heritage individuals. However, the summary estimate of the odds ratio from both Pima groups and from DIAGRAM was 1.07, and the power of the second population sample is modest for effects of this magnitude, even with 3,700 individuals genotyped. We estimate the power of this second sample to detect an odds ratio of 1.07 given the allele frequency of 0.32 is ~20% at P < 0.05 (17). The association for type 2 diabetes did not reach genome-wide significance (P < 5 × 10−8) even in the combined analysis; however, the associations with measures of insulin action and with expression levels suggest that these genetic effects are biologically meaningful, despite the lack of genome-wide significance. The role of rs35898099, which was associated with type 2 diabetes in both the full-heritage Pima Indian and Native American samples, but was not associated with ASK1 expression, deserves further investigation in other ethnic groups.
Our expression study in skeletal muscle showed the insulin resistance risk allele of rs1570056 was associated with reduced ASK1 expression and the lower expression level of ASK1 predicted decreased in vivo insulin action. This finding is consistent with Yang et al. (18), who found that ASK1 (also known as MAP3K5) expression in human subcutaneous adipose tissue was positively correlated with in vivo glucose disposal rate. Moreover, they also found the ASK1 expression was inversely associated with adipose cell mass. Our expression study in skeletal muscle did show a negative correlation of the ASK1 expression with BMI and percent body fat (adjusted P = 0.004 and 0.006, r = −0.23 and −0.22, for BMI and percent body fat, respectively; supplementary Fig. 1). Furthermore, we performed real-time PCR for ASK1 in subcutaneous adipocytes isolated from 77 nondiabetic Pima Indians and confirmed the negative correlation between BMI or percent body fat and ASK1 expression (adjusted P = 3.6 × 10−6 and 3.3 × 10−7, r = −0.50 and −0.54, for BMI and percent body fat, respectively; supplementary Fig. 2). Because the correlation between ASK1 expression and in vivo insulin action persisted despite control for adiposity, this suggests obesity may not fully account for the insulin resistance caused by lower ASK1 expression.
Skeletal muscle and adipose tissues are two major insulin-responsive tissues, where insulin increases glucose uptake not only through stimulating GLUT4 translocation to the cell surface but also by increasing the intrinsic activity of GLUT4 (19). As the highest module of MAP kinase cascade, ASK1 may influence both translocation and activation of GLUT4 by activating its downstream MAP2K4/MAP2K7-JNK and MAP2K3/MAP2K6-p38 pathways (20). GLUT4 translocation is regulated by the IRS1-PI3K-Akt signaling pathway (21). JNK activation has been suggested to impair insulin signaling by decreasing insulin-stimulated tyrosine phosphorylation of IRS1 (22). Imoto et al. (23) reported that over-activation of ASK1 in human hepatoma cells impaired insulin signaling and partly mediated tumor necrosis factor (TNF)-α–induced insulin resistance by activating JNK. In this case, reduced ASK1 expression seems likely to promote GLUT4 translocation and improve insulin sensitivity. This hypothesis is not supported by our findings. However, the report by Imoto et al. was based on a hepatoma cell study and thus may not represent what happens in muscle or fat cells in vivo. On the other hand, although GLUT4 translocation is a prerequisite for insulin action in muscle and fat tissue (24,25), evidence suggests that insulin-stimulated glucose transport still needs the activation of GLUT4 (2628). The activation of p38 MAPK is thought to be involved in the insulin-induced enhancement of intrinsic GLUT4 activity (2832). For instance, inhibition of p38 by diverse inhibitors suppresses glucose transport but not GLUT4 translocation in both mouse adipocytes and myotubes (2831). In contrast, activation of p38 by a specific activator stimulates p38 phosphorylation and increases glucose transport in skeletal muscle cells (32). In this aspect, reduced ASK1 expression may decrease the phosphorylation and inhibit the activation of p38, which may diminish GLUT4 activity at least on skeletal muscle cell surface. This hypothesis is in agreement with the positive correlation between ASK1 expression and insulin action observed in our study, suggesting ASK1 may influence insulin action in skeletal muscle mainly through the effect on the p38 MAP kinase pathway rather than on the JNK pathway.
The region of LD tagged by rs1570056 is large and spans the ASK1 promoter through intron 5, making it is difficult to determine the causative variant(s) underlying these associations. Based on sequence inspection, one potential causative variant was rs5880308, a short tandem repeat variant in the core promoter region of ASK1 that was predicted to affect a TFIIB binding site (MapInspector at www.genomatix.de). However, we conducted a luciferase assay that did not show any significant difference in reporter gene activity between the two constructs carrying different alleles (data not shown), suggesting that this variant is not functional. These results are consistent with the study of Arning et al. (33). Thus, additional functional studies are required to determine the true causative variant that affects the ASK1 expression.
ACKNOWLEDGMENTS
This study was supported by the intramural research program of the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health. L.B. was supported by a grant from the American Diabetes Association.
No potential conflicts of interest relevant to this article were reported.
We thank all the participants from the Gila River Indian Community for their cooperation.
Parts of this article were presented in abstract form at the 69th Scientific Sessions of the American Diabetes Association, New Orleans, LA, 5–9 June 2009.
Footnotes
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
1. Knowler WC, Bennett PH, Hamman RF, Miller M. Diabetes incidence and prevalence in Pima Indians: a 19-fold greater incidence than in Rochester, Minnesota. Am J Epidemiol 1978;108:497–505. [PubMed]
2. Bogardus C. Metabolic abnormalities in the development of non-insulin dependent mellitus. In Diabetes Mellitus: A Fundamental and Clinical Text. LeRoith D, Taylor SI, Olefsky JM, editors. Eds. Philadelphia, Lippincott Williams & Wilkins, 1996, p. 459–467.
3. Ravussin E, Bogardus C. Energy expenditure in the obese: is there a thrifty gene? Infusionstherapie 1990;17:108–112. [PubMed]
4. Sakul H, Pratley R, Cardon L, Ravussin E, Mott D, Bogardus C. Familiality of physical and metabolic characteristics that predict the development of non-insulin-dependent diabetes mellitus in Pima Indians. Am J Hum Genet 1997;60:651–656. [PubMed]
5. World Health Organization. Report of a WHO Study Group: Diabetes Mellitus Geneva, World Health Org., 1985. (Tech. Rep. Ser., no. 727)
6. Norman RA, Tataranni PA, Pratley R, Thompson DB, Hanson RL, Prochazka M, Baier L, Ehm MG, Sakul H, Foroud T, Garvey WT, Burns D, Knowler WC, Bennett PH, Bogardus C, Ravussin E. Autosomal genomic scan for loci linked to obesity and energy metabolism in Pima Indians. Am J Hum Genet 1998;62:659–668. [PubMed]
7. Lillioja S, Mott DM, Spraul M, Ferraro R, Foley JE, Ravussin E, Knowler WC, Bennett PH, Bogardus C. Insulin resistance and insulin secretory dysfunction as precursors of non-insulin-dependent diabetes mellitus: prospective studies of Pima Indians. N Engl J Med 1993;329:1988–1992. [PubMed]
8. Majer M, Mott DM, Mochizuki H, Rowles JC, Pedersen O, Knowler WC, Bogardus C, Prochazka M. Association of the glycogen synthase locus on 19q13 with NIDDM in Pima Indians. Diabetologia 1996;39:314–321. [PubMed]
9. Hanson RL, Bogardus C, Duggan D, Kobes S, Knowlton M, Infante AM, Marovich L, Benitez D, Baier LJ, Knowler WC. A search for variants associated with young-onset type 2 diabetes in American Indians in a 100K genotyping array. Diabetes 2007;56:3045–3052. [PubMed]
10. Zeger SL, Liang KY. Longitudinal data analysis for discrete and continuous outcomes. Biometrics 1986;42:121–130. [PubMed]
11. Hanis CL, Chakraborty R, Ferrell RE, Schull WJ. Individual admixture estimates: disease associations and individual risk of diabetes and gallbladder disease in Mexican-Americans in Starr County, Texas. Am J Phys Anthropol 1986;70:433–441. [PubMed]
12. Tian C, Hinds DA, Shigeta R, Adler SG, Lee A, Pahl MV, Silva G, Belmont JW, Hanson RL, Knowler WC, Gregersen PK, Ballinger DG, Seldin MF. A genome-wide single nucleotide polymorphism panel for Mexican American admixture mapping. Am J Hum Genet 2007;80:1014–1023. [PubMed]
13. Petitti DB. Statistical methods in meta-analysis. In Meta-Analysis, Decision Analysis and Cost-Effectiveness Analysis: Methods for Quantitative Synthesis in Medicine. Petitti DB, editor. Ed. Oxford, Oxford University Press, 2000, p. 94–118.
14. de Bakker PI, Yelensky R, Pe'er I, Gabriel SB, Daly MJ, Altshuler D. Efficiency and power in genetic association studies. Nat Genet 2005;37:1217–1223. [PubMed]
15. Zeggini E, Scott LJ, Saxena R, Voight BF, Marchini JL, Hu T, de Bakker PI, Abecasis GR, Almgren P, Andersen G, Ardlie K, Boström KB, Bergman RN, Bonnycastle LL, Borch-Johnsen K, Burtt NP, Chen H, Chines PS, Daly MJ, Deodhar P, Ding CJ, Doney AS, Duren WL, Elliott KS, Erdos MR, Frayling TM, Freathy RM, Gianniny L, Grallert H, Grarup N, Groves CJ, Guiducci C, Hansen T, Herder C, Hitman GA, Hughes TE, Isomaa B, Jackson AU, Jørgensen T, Kong A, Kubalanza K, Kuruvilla FG, Kuusisto J, Langenberg C, Lango H, Lauritzen T, Li Y, Lindgren CM, Lyssenko V, Marvelle AF, Meisinger C, Midthjell K, Mohlke KL, Morken MA, Morris AD, Narisu N, Nilsson P, Owen KR, Palmer CN, Payne F, Perry JR, Pettersen E, Platou C, Prokopenko I, Qi L, Qin L, Rayner NW, Rees M, Roix JJ, Sandbaek A, Shields B, Sjögren M, Steinthorsdottir V, Stringham HM, Swift AJ, Thorleifsson G, Thorsteinsdottir U, Timpson NJ, Tuomi T, Tuomilehto J, Walker M, Watanabe RM, Weedon MN, Willer CJ, Wellcome Trust Case Control Consortium. Illig T, Hveem K, Hu FB, Laakso M, Stefansson K, Pedersen O, Wareham NJ, Barroso I, Hattersley AT, Collins FS, Groop L, McCarthy MI, Boehnke M, Altshuler D. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat Genet 2008;40:638–645. [PMC free article] [PubMed]
16. Florez JC. Newly identified loci highlight beta cell dysfunction as a key cause of type 2 diabetes: where are the insulin resistance genes? Diabetologia 2008;51:1100–1110. [PubMed]
17. Hanson RL, Looker HC, Ma L, Muller YL, Baier LJ, Knowler WC. Design and analysis of genetic association studies to finely map a locus identified by linkage analysis: sample size and power calculations. Ann Intern Med 2006;70:332–349. [PubMed]
18. Yang X, Enerbäck S, Smith U. Reduced expression of FOXC2 and brown adipogenic genes in human subjects with insulin resistance. Obes Res 2003;11:1182–1191. [PubMed]
19. Michelle Furtado L, Poon V, Klip A. GLUT4 activation: thoughts on possible mechanisms. Acta Physiol Scand 2003;178:287–296. [PubMed]
20. Ichijo H, Nishida E, Irie K, ten Dijke P, Saitoh M, Moriguchi T, Takagi M, Matsumoto K, Miyazono K, Gotoh Y. Induction of apoptosis by ASK1, a mammalian MAPKKK that activates SAPK/JNK and p38 signaling pathways. Science 1997;275:90–94. [PubMed]
21. Shepherd PR, Kahn BB. Glucose transporters and insulin action: implications for insulin resistance and diabetes mellitus. N Engl J Med 1999;341:248–257. [PubMed]
22. Aguirre V, Uchida T, Yenush L, Davis R, White MF. The c-Jun NH(2)-terminal kinase promotes insulin resistance during association with insulin receptor substrate-1 and phosphorylation of Ser(307). J Biol Chem 2000;275:9047–9054. [PubMed]
23. Imoto K, Kukidome D, Nishikawa T, Matsuhisa T, Sonoda K, Fujisawa K, Yano M, Motoshima H, Taguchi T, Tsuruzoe K, Matsumura T, Ichijo H, Araki E. Impact of mitochondrial reactive oxygen species and apoptosis signal-regulating kinase 1 on insulin signaling. Diabetes 2006;55:1197–1204. [PubMed]
24. Kahn BB. Lilly lecture 1995: glucose transport: pivotal step in insulin action. Diabetes 1996;45:1644–1654. [PubMed]
25. Klip A, Marette A. Acute and chronic signals controlling glucose transport in skeletal muscle. J Cell Biochem 1992;48:51–60. [PubMed]
26. Clark AE, Holman GD, Kozka IJ. Determination of the rates of appearance and loss of glucose transporters at the cell surface of rat adipose cells. Biochem J 1991;278:235–241. [PubMed]
27. Zierler K. Does insulin-induced increase in the amount of plasma membrane GLUTs quantitatively account for insulin-induced increase in glucose uptake? Diabetologia 1998;41:724–730. [PubMed]
28. Somwar R, Kim DY, Sweeney G, Huang C, Niu W, Lador C, Ramlal T, Klip A. GLUT4 translocation precedes the stimulation of glucose uptake by insulin in muscle cells: potential activation of GLUT4 via p38 mitogen-activated protein kinase. Biochem J 2001;359:639–649. [PubMed]
29. Sweeney G, Somwar R, Ramlal T, Volchuk A, Ueyama A, Klip A. An inhibitor of p38 mitogen-activated protein kinase prevents insulin-stimulated glucose transport but not glucose transporter translocation in 3T3–L1 adipocytes and L6 myotubes. J Biol Chem 1999;274:10071–10078. [PubMed]
30. Somwar R, Koterski S, Sweeney G, Sciotti R, Djuric S, Berg C, Trevillyan J, Scherer PE, Rondinone CM, Klip A. A dominant-negative p38 MAPK mutant and novel selective inhibitors of p38 MAPK reduce insulin-stimulated glucose uptake in 3T3–L1 adipocytes without affecting GLUT4 translocation. J Biol Chem 2002;277:50386–50395. [PubMed]
31. Niu W, Huang C, Nawaz Z, Levy M, Somwar R, Li D, Bilan PJ, Klip A. Maturation of the regulation of GLUT4 activity by p38 MAPK during L6 cell myogenesis. J Biol Chem 2003;278:17953–17962. [PubMed]
32. Geiger PC, Wright DC, Han DH, Holloszy JO. Activation of p38 MAP kinase enhances sensitivity of muscle glucose transport to insulin. Am J Physiol Endocrinol Metab 2005;288:E782–E788. [PubMed]
33. Arning L, Monté D, Hansen W, Wieczorek S, Jagiello P, Akkad DA, Andrich J, Kraus PH, Saft C, Epplen JT. ASK1 and MAP2K6 as modifiers of age at onset in Huntington's disease. J Mol Med 2008;86:485–490. [PubMed]
Articles from Diabetes are provided here courtesy of
American Diabetes Association