5′ Flanking Variants of Resistin Are Associated With Obesity

Approximately 80% of type 2 diabetic subjects are overweight or obese. The growing rate of obesity (1,2) is thought to directly impact the increasing prevalence of type 2 diabetes in North America (3). Recently, the hormone resistin (accession no. NM_020415) has been postulated to play a role at the nexus of these two complex traits (4). Resistin belongs to a family of secreted peptides (5,6) that shares a cysteine-rich COOH-terminus and forms disulfide-linked homodimers (7). Resistin was identified in the mouse by screening differentiated adipocytes for genes repressed by the antidiabetic drug rosiglitazone, a member of the class of insulin-sensitizing drugs known as thiazolidinediones (TZDs), which are thought to target peroxisome proliferator-activated receptor (PPAR)-γ (rev. in 8). Mouse resistin is expressed exclusively in adipocytes (4,9) and inhibits their differentiation in culture (9). Circulating levels of resistin are increased after high-carbohydrate meals (9) and in genetically and diet-induced obesity (4). In mice fed a high-fat diet, anti-resistin antibodies improve blood glucose and insulin action (4). Human resistin is expressed only at low levels in adipose tissue (10,11), and its contribution to these disease states is unclear.

Previous work demonstrated that the Pro12Ala variant of PPAR-γ affects susceptibility to diabetes (12 and refs. therein). Because PPAR-γ is thought to be a target for TZDs, we reasoned that polymorphisms in the resistin gene, whose expression appears to be regulated by TZDs in mice (4,13,14), might show a similar association with these related disorders. Therefore, we examined resistin for coding and noncoding variants. In the polymorphism discovery phase of this study, all exons, the exon-intron boundaries, and 472 bp of the 5′ flanking region of resistin were resequenced in 45 individuals from two study populations (15,16) representing a sample of diabetic, obese, and control individuals. In this phase of the study, seven variants were found: one substitution in the 3′ UTR (c.*62G>A), two single-nucleotide polymorphisms (SNPs) in intron 2 (IVS2 + 39C>T and IVS2 + 181G>A), two SNPs in intron 3 (IVS3 + 30C>T and IVS3-16C>G), and two SNPs in the 5′ flanking region (g.-537A>C and g.-420C>G) (Fig. 1). Two polymorphisms were previously described (c.*62G>A and IVS2 + 39C>T) (17), and one (g.-420C>G) had been identified by the SNP Consortium (GenBank reference SNP no. 1862513). Because the two promoter polymorphisms are in close proximity, we elected to genotype them by sequencing genomic DNA. Two more rare 5′ flanking SNPs were identified in subsequent samples (g.-638G>A and g.-358G>A) (Fig. 1). These two SNPs appear to be in perfect linkage disequilibrium (LD), with the minor alleles present in the same 11 heterozygotes among 590 Quebec individuals.

As no coding variants were found and promoter variants are likely to play an important role in complex traits, we elected to first study the promoter SNPs for a possible relationship with diabetes or BMI. An association study was initiated to examine the two more common 5′ flanking SNPs (g.-537A>C and g.-420C>G) in a type 2 diabetic case/control sample from the Saguenay-Lac-St-Jean (SLSJ) region of Quebec and a population sample of men from the Quebec City (QC) area. Genotype distributions for these two variants did not differ significantly from Hardy-Weinberg equilibrium in either the QC or SLSJ case/control sample. In addition, allelic frequencies in these two study samples were not significantly different. To assess the association of the g.-537A>C and g.-420C>G polymorphisms with type 2 diabetes, we compared allele frequencies of these variants in the case/control study sample of diabetic and nondiabetic subjects recruited from the SLSJ area. As shown in Table 1, no difference in allele frequencies was observed between type 2 diabetic and nondiabetic subects. In a logistic regression model that included age and sex, neither the resistin g.-537A>C polymorphism nor the g.-420C>G polymorphism were significant contributors to diabetes (data not shown).

In the QC sample, an increase in BMI (30.4 vs. 29.2 kg/m², P = 0.03) was associated with the presence of the g.-420 G allele compared with the C/C genotype (Fig. 2A). Similarly, we found an association with the presence of the g.-537 C allele compared with the A/A genotype for BMI (31.8 vs. 29.7 kg/m²), which was also significant (P = 0.03) (Fig. 2B), despite the low frequency (3.9%) of this allele. In addition, several indices of obesity were significantly associated with the G allele at g.-420: weight (92.8 vs. 87.9 kg, P = 0.006), body fat mass (27.8 vs. 25.4 kg, P = 0.03), and waist circumference (102.9 vs. 100.0 cm, P = 0.04) (Table 2). All of these same parameters were affected by the C allele at position g.-537. All differences remained statistically significant after adjustment for age (data not shown).

Because we observed an association of the g.-537 and c.-420 alleles with BMI in the QC sample, these alleles were analyzed in the SLSJ diabetic and nondiabetic subjects for their association with BMI. No association was observed between either of the polymorphisms and BMI in the whole study population (data not shown), but there was a statistically significant effect for carriers of the g.-537 C allele when only women were examined (P = 0.03) (Fig. 2B). Waist circumference was also significantly higher in these women (90.9 vs. 86.4 cm, P = 0.01). We also found a significantly higher BMI in carriers of the g.-537 C allele (P = 0.01), when only the nondiabetic subgroup of the SLSJ study population was examined (Fig. 2A). The most significant association of BMI and genotype was observed when combining all nondiabetic subjects from both studies, with both g.-420G and g.-537C significant at P = 0.017 and P = 0.001, respectively (Figs. 2A and B). All differences remained significant after adjustment for age (data not shown). In addition, in a family-based population sample from SLSJ that had some overlap with the case/control sample, a quantitative transmission disequilibrium test (QTDT) showed a significant contribution of the g.-537C allele to a higher BMI when age and sex were included in the model (P = 0.039). We note that as this family-based cohort contained some of the same individuals as the SLSJ case/control sample, this does not constitute an independent replication.

Using logistic regression analyses, we calculated odds ratios (ORs) for a BMI >30 kg/m². There was a strong agreement between the OR for the QC and the SLSJ study samples when only nondiabetic individuals were examined. For both of these groups, the OR was >1.5 for the g.-420G variant and >2.7 for the g.-537C variant (Table 3). Finally, for all nondiabetic subjects combined, the ORs for the G allele at g.-420C>G and the C allele at g.-537A>C are 1.58 (CI 1.06–2.35, P = 0.025) and 2.72 (1.28–5.81, P = 0.01), respectively, when age and sex are included in the model (Table 3).

The g.-420 G and the g.-537 C alleles are in significant LD with each other. In the 590 Quebec individuals studied thus far, the C allele at position g.-537 is present only in individuals bearing the G allele at position g.-420. We observed that the average BMI of those nondiabetic individuals possessing the C allele at position g.-537 (and thus possessing both variants) was higher than those possessing only the G allele at position g.-420 (P = 0.006).

It is possible that either of these 5′ polymorphisms may change a transcription factor binding site affecting resistin mRNA levels. A search for potential binding sites at positions g.-420 and g.-537 with MatInspector V2.2 (18) revealed several transcription factor motifs altered by these variant alleles (e.g., an AP1 site is destroyed by g.-537A>C). Although the precise mechanisms controlling resistin transcription remain to be elucidated, one report has implicated the β-adrenergic receptors and protein kinase A in decreased resistin expression (19).

We attempted to replicate our finding in Scandinavian study populations. There was no significant association between the two resistin promoter variants and obesity in these previously described (12) study populations, which included a diabetes case/control sample (Table 1), diabetic trios, and normal glucose tolerant trios (QTDT, data not shown). In the case of g.-537, this may be because the rare allele had a frequency of 0.02 in the Scandinavian case/control sample, significantly lower than the 0.04 observed in Quebec (P = 0.005, Fisher’s exact test) (Table 1). Three other alternatives may explain the lack of replication for the promoter variants: 1) interacting loci or environmental conditions differ between these two populations and influence the phenotypic expression of the variants; 2) resistin polymorphisms from Quebec are in LD with another functional variant in this or another gene, whereas the Scandinavian sample could be in linkage equilibrium with this other mutation; or 3) the finding in the Quebec populations is spurious.

At present, very little is known about the function of resistin in humans, and the expression level in human adipose tissue remains controversial (10,11,20,21). However, Savage et al. (11) detected resistin more often in the fat of the morbidly obese than in normal control subjects, and McTernan et al. (20) found an increase in resistin in abdominal fat compared with thigh. Our results demonstrate an increased risk for higher BMI for carriers of two resistin promoter polymorphisms among French Canadians in Quebec. Interestingly, the observed effect appears to be strongest in nondiabetic subjects. In nondiabetic subjects, a change in the level of resistin may contribute to obesity, possibly as a result of misregulated transcription that has other physiological consequences in diabetic subjects. Alternatively, the basal or activated transcription of resistin in diabetic subjects may be different. Measuring levels of resistin in individuals with these variants could contribute to the characterization of the resistin promoter. The increased risk for obesity conferred by the resistin variants in these populations warrants additional studies in larger population samples.