Insulin resistance plays a major role in dyslipidemia, cardiovascular disease, and type 2 diabetes. TRB3, a mammalian tribbles homolog, whose chromosomal region 20p13-p12 has been linked to human type 2 diabetes, impairs insulin signaling through the inhibition of Akt phosphorylation and is overexpressed in murine models of insulin resistance. We here report that the prevalent TRB3 missense Q84R polymorphism is significantly (P < 0.05) associated with several insulin resistance–related abnormalities in two independent cohorts (n = 178 and n = 605) of nondiabetic individuals and with the presence of a cluster of insulin resistance–related cardiovascular risk factors in 716 type 2 diabetic patients (OR 3.1 [95% CI 1.2–8.2], P = 0.02). In 100 additional type 2 diabetic patients who suffered from myocardial ischemia, age at myocardial ischemia was progressively and significantly (P = 0.03) reduced from Q84Q to Q84R to R84R individuals. To test the functional role of TRB3 variants, either Q84 or R84 TRB3 full-length cDNAs were transfected in human HepG2 hepatoma cell lines. As compared with control HepG2 cells, insulin-induced Ser473-Akt phosphorylation was reduced by 22% in Q84- (P < 0.05 vs. control cells) and by 45% in R84-transfected cells (P < 0.05 vs. Q84 transfected and P < 0.01 vs. control cells). These data provide the first evidence that TRB3 gene plays a role in human insulin resistance and related clinical outcomes.

Insulin resistance is pathogenic for dyslipidemia, cardiovascular disease (CVD), and type 2 diabetes (1). Both environmental and genetic factors modulate insulin resistance, with the latter being mostly unknown (2). Akt, a serine/threonine protein kinase, is a key mediator of insulin signaling (3); impaired Akt activity is involved in human and animal models of insulin resistance (46). Thus, mediators of Akt activity are candidates for insulin resistance (7). The newly identified TRB3 gene (a mammalian tribbles homolog, also known as TRIB3/NIPK, gene ID 57761) has been reported by most (8,9), although not all (10), studies to affect insulin action by binding to and inhibiting Akt phosphorylation and to play a role in insulin resistance (8,9). TRB3 is located on the 20p13 human chromosome region that has been associated with type 2 diabetes (11,12). TRB3, therefore, is a candidate gene for insulin resistance (7).

By resequencing the coding region of TRB3, five missense and two synonymous variants were identified; four were novel and three already available from the National Center for Biotechnology Information (NCBI) database of single nucleotide polymorphisms (dbSNP). Two additional synonymous variants already available from the NCBI dbSNP were not found (Table 1). Haplotype block partitioning showed that the three polymorphisms with minor allele frequency (MAF) >5% (Q84R, Y111Y, and A323A) were not gathered together into a single block. Strong, although not complete, linkage disequilibrium was observed between Y111Y and A323A (D′ = 0.67; r2 = 0.4), leaving an unlinked missense Q84R variant. Because of either their extremely low MAF (four missense) or their unlikely biological significance (two synonymous), only the prevalent missense Q84R variant, which causes the substitution of a polar uncharged amino acid with a charged one, was further tested for association with insulin resistance phenotypes.

We genotyped Q84R polymorphism in 178 nondiabetic Caucasian unrelated offspring of type 2 diabetic patients residing in Rome or surrounding areas (Table 2). Insulin sensitivity, as measured by euglycemic-hyperinsulinemic clamp (13), was reduced from Q84Q to Q84R and R84R individuals. Significant changes were also observed in serum insulin, triglycerides, and HDL cholesterol across the three genotypes. Differences in serum insulin and HDL cholesterol were no longer significant when waist circumference (but not BMI) was added into the model, thus suggesting that adipose distribution may modulate TRB3 effects on some insulin resistance–related abnormalities. This is also indicated by the observed interaction between Q84R polymorphism and waist circumference in modulating lean glucose disposal rate. In fact, the expected negative correlation between the two variables was stronger in Q84R and R84R (r = −0.47 and −0.40, respectively) than in Q84Q (r = −0.13) individuals (P for interaction <0.05). We then genotyped Q84R polymorphism in 605 unrelated nondiabetic Caucasians from Gargano (Table 2). Serum insulin level, but not lipid profile, was significantly different across the three genotype groups and higher in R84R individuals, independently of BMI and waist circumference. Worth noting is that individuals from the first sample were offspring of type 2 diabetic patients and, therefore, highly predisposed to insulin resistance because of environmental and/or genetic factors (14). It can be hypothesized that with such a strong unfavorable background, a single copy of the R84 variant (as carried by Q84R heterozygous individuals) is also sufficient to determine insulin resistance. This does not seem to be the case in the second sample, which resembles the general population, where insulin resistance was observed only in homozygous R84R individuals. Insulin resistance may predispose to CVD, particularly among type 2 diabetic patients (15). Accordingly, we studied 716 type 2 diabetic patients (Table 3) from the Gargano area and subgrouped them according to presence of insulin resistance–related cardiovascular risk factors, namely abdominal obesity (waist circumference >88 and >102 cm for woman and men, respectively), dyslipidemia (total cholesterol ≥200 mg/dl and/or HDL cholesterol ≤40 mg/dl in men and 50 mg/dl in woman, and/or triglycerides ≥150 mg/dl or currently on lipid-lowering treatment), and hypertension (systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg or currently on antihypertensive treatment). A total of 356 patients showed the simultaneous presence of three risk factors (very-high-risk subgroup), while 360 patients did not (two or fewer risk factors). The proportion of R84R patients was higher in the very-high-risk group (14 of 356 [3.9%] vs. 7 of 360 [1.9%]; age- and sex-adjusted OR 3.1 [95% CI 1.2–8.2], P = 0.02). A second independent cohort of 100 consecutive type 2 diabetic patients who had suffered myocardial infarction (16) was also genotyped. The age at myocardial ischemia decreased from 58 ± 9 years in Q84Q (n = 79) to 55 ± 10 years in Q84R (n = 18) and to 47 ± 11 years in R84R (n = 3) individuals; P = 0.03 after adjusting for the following three clinical variables that were independently associated with age at myocardial ischemia: sex (P = 0.03), hypertension (P = 0.03), and dyslipidemia (P = 0.05). Insulin resistance may also predispose to type 2 diabetes (1). Accordingly, we compared the distribution of the TRB3 Q84R genotype in the above-described 716 type 2 diabetic patients with that in 330 unrelated nondiabetic control subjects (117 men and 213 women with fasting plasma glucose <6.1 mmol/l, no medications known to affect glucose and lipid metabolism, and absence of systemic diseases) within the same age range (35–76 years) who were recruited in the same region (Gargano and surrounding area) and were part of the previously described sample of 605 individuals. The Q84Q, Q84R, and R84R genotypes, respectively, were carried by 504 (70.4%), 191 (26.7%), and 21 (2.9%) diabetic patients and by 242 (73.4%), 80 (24.2%), and 8 (2.4%) control individuals. The observed tendency of an increased risk of type 2 diabetes for 84R carriers, although compatible with the above-reported association with insulin resistance–related phenotypes, is not significant in the present sample size (P = 0.61). To test the functional role of TRB3 variants on the S473Akt phosporylation, either Q84 or R84 TRB3 full-length cDNAs were transfected in human HepG2 hepatoma cell line. A progressive reduction of insulin-induced S473Akt phosphorylation was observed from untransfected control to Q84- and R84-HepG2 cells, with no change of Akt protein expression (Fig. 1A). Comparable expression levels of the two transfected TRB3 variants were ascertained in cell lysates by immunoprecipitation and blotting with anti-Myc antibody (Fig. 1). On average (n = 3 experiments), insulin effect was significantly (P < 0.05) reduced by 22% in Q84-HepG2 with respect to control cells (Fig. 1B). As compared with Q84-HepG2, a further 23% reduction of Akt phosphorylation was observed in R84-HepG2 cells (Fig. 1B) (P < 0.05 vs. Q84-HepG2 and P < 0.01 vs. control cells). In contrast, in these cell lines, no significant change was observed in the expression of both total Akt and anti-Myc immunoprecipitated TRB3 (P = 0.57 and P = 0.87 by one-way ANOVA, respectively; n = 3 experiments). We here describe for the first time that a functional missense variant of the TRB3 gene (i.e., R84) is associated with several insulin resistance–related abnormalities, including hyperinsulinemia, dyslipidemia, and CVD. This association has been confirmed in several independent samples, making the risk of a false-positive result very unlikely. At variance, at least with the present sample size, no significant association was found with type 2 diabetes. As compared with wild-type Q84, the R84 variant introduces a significant charge change. In addition, R84 variant has a stronger inhibitory activity on insulin-stimulated Akt phosphorylation, a finding that provides a convincing biological explanation for the observed association between the Q84R polymorphism and insulin resistance. Although a comprehensive survey of variations also in the regulatory regions of the gene is certainly needed to deeper understand its allelic structure and several large studies are necessary to better define the specific role of Q84R variant (and possibly other variants) of TRB3 gene, our preliminary findings strongly suggest that the R84 variant contributes to the complex genetic background of insulin resistance and may help identify individuals who are at risk for insulin resistance and related cardiovascular risk at whom preventive programs could be specifically targeted.

The study was approved by local ethical committees and performed according to the Helsinki Declaration. All subjects gave written informed consent and were examined between 8:00 and 9:00 a.m. after an overnight fast. BMI was calculated by dividing the weight (in kilograms) by the square of height (in meters). Waist circumference was measured at the level midway between the lowest rib margin and the iliac crest to the nearest 0.5 cm. Methods for plasma glucose, serum insulin, lipid profile, and euglycemic-hyperinsulinemic clamp have been previously described (13,17). The first study was carried out in 178 nondiabetic (fasting plasma glucose <110 mg/dl and normal oral glucose tolerance test) Caucasian unrelated offspring of type 2 diabetic patients (i.e., the eldest offspring of a family with only one parent affected by type 2 diabetes) residing in Rome. The second sample comprised 605 nondiabetic Caucasians (fasting plasma glucose <110 mg/dl, not taking medications known to interfere with glucose and lipid metabolism) residing in the Gargano region (the east coast of Italy). A cohort of 716 unrelated Caucasians with type 2 diabetes was recruited at the Scientific Institute CSS, according to the following criteria: diabetes diagnosed after 30 years, insulin treatment not required for at least 2 years after diabetes diagnosis, and absence of clinically evident autoimmune disease. Clinical features of patients are shown in Table 3. Anti-GAD antibodies were determined in 200 randomly selected patients; only 3 of 200 patients were anti-GAD positive (>0.9 units/ml). A second cohort of 100 type 2 diabetic Caucasians (68 men and 32 women, aged 65 ± 8 years, with a diabetes duration of 16 ± 10 years, BMI of 30 ± 4.5 kg/m2, and HbA1c of 8.5 ± 1.7%) who suffered myocardial ischemia (16) was also recruited.

Resequencing and linkage disequilibrium assessment.

Resequencing of the TRB3 coding region was performed in 50 nondiabetic and 50 type 2 diabetic individuals according to the genomic sequence NT-0011387 (NCBI GenBank) (details in the online appendix available at http://diabetes.diabetesjournals.org). Pairwise disequilibria measures (D′) were calculated among all polymorphisms with MAF >5% by the software programs PHASE v. 2.0 (18) and Haploview v. 3.0 (19). PHASE was also used to reconstruct individual haplotypes.

Genotyping.

Genotyping of the TRB3 R84 variant was performed by restriction fragment–length polymorphisms (online appendix).

Construction of the expression plasmid.

The TRB3 full-length cDNA was obtained by RT-PCR from total liver RNA (Stratagene) according to NCBI mRNA sequence NM-021158 (methods in online appendix) .

Transfection and Western blotting.

S473Akt phosporylation was evaluated by transient transfections of TRB3 full-length cDNAs in human HepG2 hepatoma cells (methods in online appendix). Cells were serum-starved 18 h before treatment with insulin. Lysates were immunoprecipitated with anti-Myc antibody (Clontech) or directly loaded on an SDS-PAGE. Samples were separated by 8% SDS-PAGE, transferred to nitrocellulose, and immunoblotted with an anti–Phospho-Ser473Akt or total Akt antibody (Cell Signaling) or anti–Myc-Tag antibody. Proteins were detected by enhanced chemiluminescence (Amersham) and band densities quantified by densitometry using a Fluor-S MultiImager (Bio-Rad).

Statistical analyses.

Data are means ± SD. Comparisons between groups were tested by unpaired student’s t test or Mann-Whitney and among groups by one-way ANOVA. Mean values, after adjusting for covariates, were evaluated by ANCOVA. The χ2 was used to test for associations between categorical variables and for Hardy-Weinberg equilibrium. To model the effect of the polymorphism on bivariate variables, multivariate logistic regression analysis was used, and ORs (95% CI) are shown. A P value <0.05 was considered significant. Analyses were performed by the statistical package SPSS v. 12 (Chicago, IL).

FIG. 1.

Insulin stimulation of S473 Akt phosphorylation in HepG2 cells transfected with TRB3 Q84 or R84 variant. A:Western blot analysis of Phospho (Ser473) Akt, total Akt, and TRB3 protein level in HepG2 cells transfected with Myc-Tagged TRB3 wild-type (Q84) and mutant (R84) vector. IP, immunoprecipitation; WB, Western blot. B: Mean ± SD (n = 3 experiments) of S473-Akt phosphorylation in the absence or presence of 100 nmol/l insulin in HepG2 cells. *P < 0.05 vs. control-HepG2 cells. †P < 0.01 vs. control-HepG2 cells. ‡P < 0.05 vs. Q84-HepG2 cells.

FIG. 1.

Insulin stimulation of S473 Akt phosphorylation in HepG2 cells transfected with TRB3 Q84 or R84 variant. A:Western blot analysis of Phospho (Ser473) Akt, total Akt, and TRB3 protein level in HepG2 cells transfected with Myc-Tagged TRB3 wild-type (Q84) and mutant (R84) vector. IP, immunoprecipitation; WB, Western blot. B: Mean ± SD (n = 3 experiments) of S473-Akt phosphorylation in the absence or presence of 100 nmol/l insulin in HepG2 cells. *P < 0.05 vs. control-HepG2 cells. †P < 0.01 vs. control-HepG2 cells. ‡P < 0.05 vs. Q84-HepG2 cells.

TABLE 1

Newly identified or verified variants in the coding region of TRB3 gene

DesignationdsSNP IDLocationTypeCodonMAF
A251G* rs2295490 Ex2 Missense Q84R 15% 
T333C rs6051637 Ex3 Synonymous Y111Y 35% 
G375A rs6084298 Ex3 Synonymous E125E Not found 
G437A new Ex3 Missense S146N 0.5% 
G458A new Ex3 Missense R153H 1% 
T533C new Ex3 Missense L178P 0.5% 
C541T new Ex3 Missense R181C 0.5% 
C969T rs6115830 Ex4 Synonymous A323A 33% 
G1026C rs6076497 Ex4 Synonymous L342L Not found 
DesignationdsSNP IDLocationTypeCodonMAF
A251G* rs2295490 Ex2 Missense Q84R 15% 
T333C rs6051637 Ex3 Synonymous Y111Y 35% 
G375A rs6084298 Ex3 Synonymous E125E Not found 
G437A new Ex3 Missense S146N 0.5% 
G458A new Ex3 Missense R153H 1% 
T533C new Ex3 Missense L178P 0.5% 
C541T new Ex3 Missense R181C 0.5% 
C969T rs6115830 Ex4 Synonymous A323A 33% 
G1026C rs6076497 Ex4 Synonymous L342L Not found 
*

Nucleotide positions are based on the NCBI TRB3 mRNA sequence NM-021158; +1 is referred to the ATG start site. Bold letters indicate minor alleles.

TABLE 2

Clinical and biochemical features of unrelated nondiabetic patients of two independent samples

Q84R genotype
First sample of 178 individuals from Rome and surrounding area
Second sample of 605 individuals from Gargano and surrounding area
QQQRRRQQQRRR
Men/women (n32/95 13/31 3/4 161/269 58/99 6/12 
Age (years) 37 ± 10 39 ± 10 42 ± 10 37 ± 12 36 ± 12 37 ± 14 
BMI (kg/m228.0 ± 6.9 30.4 ± 6.8 29.4 ± 4.2 25.6 ± 4.9 25.0 ± 4.1 26.4 ± 4.8 
Waist (cm) 87.2 ± 16.0 93 ± 13.0 97 ± 17.0 83.2 ± 13.0 81.8 ± 11.9 83.5 ± 12.7 
Fasting glucose (mg/dl) 89.1 ± 10.0 93.2 ± 11.0 93.1 ± 6.0 89.9 ± 9.4 89.4 ± 9.4 89.7 ± 9.3 
Fasting insulin (μU/ml)* 10.0 ± 7.0 12.1 ± 7.0 11.5 ± 7.0 7.8 ± 4.5 7.4 ± 3.6 10.4 ± 6.1 
HDL cholesterol (mg/dl)* 55.1 ± 14 49.0 ± 13 47.2 ± 8.0 53.0 ± 13 53.6 ± 14 54.3 ± 15 
Triglycerides (mg/dl)* 96.0 ± 46 120.1 ± 57 175.4 ± 106 91.7 ± 60 86.7 ± 51 92.4 ± 47 
Lean glucose disposal (mg · kg−1 FFM · min−1)* 12.7 ± 4.3 11.7 ± 4.1 9.0 ± 3.9 N.T. N.T. N.T. 
Q84R genotype
First sample of 178 individuals from Rome and surrounding area
Second sample of 605 individuals from Gargano and surrounding area
QQQRRRQQQRRR
Men/women (n32/95 13/31 3/4 161/269 58/99 6/12 
Age (years) 37 ± 10 39 ± 10 42 ± 10 37 ± 12 36 ± 12 37 ± 14 
BMI (kg/m228.0 ± 6.9 30.4 ± 6.8 29.4 ± 4.2 25.6 ± 4.9 25.0 ± 4.1 26.4 ± 4.8 
Waist (cm) 87.2 ± 16.0 93 ± 13.0 97 ± 17.0 83.2 ± 13.0 81.8 ± 11.9 83.5 ± 12.7 
Fasting glucose (mg/dl) 89.1 ± 10.0 93.2 ± 11.0 93.1 ± 6.0 89.9 ± 9.4 89.4 ± 9.4 89.7 ± 9.3 
Fasting insulin (μU/ml)* 10.0 ± 7.0 12.1 ± 7.0 11.5 ± 7.0 7.8 ± 4.5 7.4 ± 3.6 10.4 ± 6.1 
HDL cholesterol (mg/dl)* 55.1 ± 14 49.0 ± 13 47.2 ± 8.0 53.0 ± 13 53.6 ± 14 54.3 ± 15 
Triglycerides (mg/dl)* 96.0 ± 46 120.1 ± 57 175.4 ± 106 91.7 ± 60 86.7 ± 51 92.4 ± 47 
Lean glucose disposal (mg · kg−1 FFM · min−1)* 12.7 ± 4.3 11.7 ± 4.1 9.0 ± 3.9 N.T. N.T. N.T. 

Data are means ± SD. All genotyped samples obeyed Hardy-Weiberg equilibrium.

*

P < 0.05 after adjusting for age, sex, and BMI among the three groups of individuals from Rome.

P < 0.05 after adjusting for age, sex, and BMI among the three groups of individuals from Gargano. FFM, fat-free mass; NT, not tested.

TABLE 3

Clinical features of patients with type 2 diabetes

Diabetic patients (n = 716)
Present age (years) 60.1 ± 9 
Sex (M/F) 353/363 
BMI (kg/m230.9 ± 6 
Age at diagnosis of type 2 diabetes (years) 50 ± 10 
Duration of disease (years) 10.1 ± 9 
HbA1c (%) 8.6 ± 2 
Treatment  
    Diet alone 88 (12) 
    OHA 339 (47) 
    Insulin ± OHA 289 ± 41 
Dislipidemia 632 (88) 
Hypertension 593 (83) 
Diabetic patients (n = 716)
Present age (years) 60.1 ± 9 
Sex (M/F) 353/363 
BMI (kg/m230.9 ± 6 
Age at diagnosis of type 2 diabetes (years) 50 ± 10 
Duration of disease (years) 10.1 ± 9 
HbA1c (%) 8.6 ± 2 
Treatment  
    Diet alone 88 (12) 
    OHA 339 (47) 
    Insulin ± OHA 289 ± 41 
Dislipidemia 632 (88) 
Hypertension 593 (83) 

Data are means ± SD and n (%). OHA, oral hypoglycemic agent.

Additional information for this article can be found in an online appendix at http://diabetes.diabetesjournals.org.

This work was partly supported by the Italian Ministry of Health (R.C. 2004 and 2005 to S.P.) and the European Community’s FP6 EUGENE2 no. LSHM-CT-2004-512013 (to G.S.).

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Supplementary data