The Longitudinal Effect of Diabetes-Associated Variation in TCF7L2 on Islet Function in Humans

Type 2 diabetes arises from an interaction between incompletely understood environmental factors and multiple common genetic variants with moderate to weak effects on disease predisposition (1). Of these variants, the single nucleotide polymorphism at rs7903146 in the TCF7L2 locus arguably confers the greatest effect on disease predisposition (2). Multiple studies have shown that people with one or two copies of the diabetes-associated (T) allele have decreased insulin secretion compared with those with the diabetes-protective allele (3). However, we showed that in subjects without type 2 diabetes, the TT genotype at rs7903146 is also associated with higher glucagon concentrations (4,5) in addition to the previously described impaired β-cell function.

This observation implies that α-cell dysfunction can occur in, and contribute to, the pathogenesis of prediabetes earlier than previously thought. There is also evidence that α-cell dysfunction can occur without defects in insulin secretion (6) and, at least in the fasting state, is secreted independently (7). In a small cohort of subjects followed over an average of 7 years, elevated fasting glucagon concentrations independently predicted a decline in glucose tolerance (8). The responsivity of the α-cell to glucose also seems to regulate the set point for fasting glucose independently of β-cell function (9).

These data reinforce the notion that diabetes is a bihormonal disease, even early in its pathogenesis. However, they do not provide information on the temporal relationship (or the primacy) of changes in β-cell and α-cell function that lead to type 2 diabetes. We posited that genetic variation in TCF7L2 could help answer these questions and hypothesized that impaired glucagon suppression after an oral challenge decreases over time in people with the diabetes-associated allele at rs7903146.

We used an established biobank, as before (4), to recruit matched cohorts of subjects homozygous for the diabetes-protective allele (CC at rs7903146) with subjects homozygous for the diabetes-associated allele (TT at rs7903146) in TCF7L2. Although Florez et al. (3) clearly showed an additive effect of each diabetes-associated allele in the Diabetes Prevention Program, we used this strategy to maximize genotype-attributable differences. Islet function was studied at baseline using a glucose challenge and repeated 3 years later. We report that in this cohort, β-cell responsivity to glucose (Φ) did not change over time, but there was a small, but significant decline in α-cell suppression after an oral glucose challenge in subjects with the TT genotype that accompanied increasing postchallenge glucose concentrations.

After approval from the Mayo Clinic institutional review board, we used the Mayo Clinic Biobank to genotype 6,000 individuals at the rs7903146 polymorphism (separate from our previous cohort [4]). The individuals genotyped were randomly selected from the biobank cohort and were aged 25–70 years (thereby minimizing the potential confounding effects of age extremes on glucose tolerance and insulin secretion), had no history of diabetes, and resided within a 100-mile radius of the Mayo Clinic in Rochester, Minnesota. Individuals with the CC or TT genotype who had expressed interest in participating in research were contacted and invited in writing to participate in the study. Eligible subjects (as determined by a phone interview to ascertain the absence of active disease and medications that could alter glucose metabolism [e.g., glucocorticoids, diabetes]) were invited to the Clinical Research and Trials Unit (CRTU) for a screening visit. After providing written informed consent, subjects underwent a history and physical examination with relevant laboratory testing. Body composition was measured at the time of screening using DXA (Lunar; GE HealthCare, Madison, WI). Care was taken to ensure that age, sex, body weight, and fasting glucose were matched between the two cohorts. Subject characteristics are reported in Table 1. A repeat examination and measurement of body composition was undertaken prior to the second study.

All subjects underwent two studies, 3 years apart. The two studies were otherwise identical. After an overnight fast (cessation of oral intake other than water at 2000 h), subjects were admitted to the CRTU at 0530 h on the day of the study. A dorsal hand vein was cannulated at 0600 h and placed in a heated Plexiglas box maintained at 55°C to allow sampling of arterialized venous blood. At 0900 h (0 min), subjects ingested Jell-O containing 75 g of glucose. Blood was collected to allow measurement of glucose and hormone concentrations. At the end of the study (1530 h, 360 min), cannulae were removed, and subjects consumed a late lunch before leaving the CRTU.

All subjects were contacted by a member of the study team at 6-month intervals (by phone or e-mail) to review medical history and medications and ensure continued health and the absence of confounding medical illnesses or therapy. Subjects who developed a severe intercurrent illness (one was diagnosed with multiple sclerosis, and another underwent kidney transplant), developed overt type 2 diabetes, or started therapy with a medication known to alter glucose metabolism (four subjects) did not complete the second oral challenge performed 36 months after the first study.

All blood was immediately placed on ice after collection, centrifuged at 4°C, separated, and stored at −80°C until assay. Plasma glucose concentrations were measured using a Yellow Springs glucose analyzer. Plasma insulin concentrations were measured using a chemiluminescence assay (Access Assay; Beckman Coulter, Chaska, MN). Plasma C-peptide was measured using a two-site immunenzymatic sandwich assay (Roche Diagnostics, Indianapolis, IN). Glucagon was measured using a two-site ELISA (Mercodia, Winston-Salem, NC) in accordance with the manufacturer’s instructions.

Net insulin action (S_i) and β-cell responsivity (Ф) were estimated using the oral glucose and the oral C-peptide minimal model, respectively (10), incorporating age-associated changes in C-peptide kinetics (11). These models derive their respective indices from the integrated relationship of insulin and glucose concentrations (S_i) and from the relationship of insulin secretion rate (obtained by deconvolution from C-peptide concentrations) and glucose (Ф). The disposition index (DI) for each subject was subsequently calculated by multiplying Ф by S_i. The glucagon secretion rate (GSR) was calculated from glucagon concentrations using nonparametric deconvolution and the population model of glucagon kinetics (12). Based on previous observations of glucagon concentrations (12), we estimated that a sample size of 65 subjects in a genotype group would provide 80% power to detect a 35% within-group difference in nadir glucagon concentrations. Based on the experimental data and the sample size remaining at the end of the 3-year period, the study was powered to detect a similar within-group difference in the TT group.

All continuous data are summarized as mean ± SEM. Area under the curve (AUC) and area above basal (AAB) were calculated using the trapezoidal rule. Within-group differences (baseline vs. 3-year visit) were assessed using a two-tailed Student paired t test (parametric) or Wilcoxon matched-pairs signed rank test (nonparametric). To assess between-group differences, we used a two-tailed Student unpaired t test (parametric) or a Wilcoxon test (nonparametric). In addition, to compare changes over time across groups, we calculated the symmetric percent change (13) as 100 × Log_e (3-year visit/baseline visit). BlueSky Statistics software version 7.10 (BlueSky Statistics LLC, Chicago, IL) and GraphPad Prism 5 (GraphPad Software, San Diego, CA) were used for the statistical analysis. P < 0.05 was considered statistically significant.

The data sets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. No applicable resources were generated or analyzed during the current study.

A total of 67 subjects with the TT genotype and 61 with the CC genotype completed the initial study. However, only 55 (TT) and 41 (CC) completed the second study (Table 1). The results shown here report the paired data of subjects who completed both studies. The anthropometric and demographic characteristics of the group completing the study did not differ from the initial group presenting for baseline studies. Anthropometric characteristics did not differ between genotypes at baseline. More importantly, the net change in weight and body composition during the study did not differ between genotypes.

In subjects with the TT genotype, peak and integrated glucose concentrations (AAB) in response to the test meal increased compared with baseline (Fig. 1A). In contrast, fasting and postchallenge glucose concentrations did not change significantly in the CC genotype (Fig. 1B). The symmetric percent change of AAB glucose concentrations differed significantly between genotype groups during the study (Fig. 1C).

Integrated insulin concentrations (AAB) increased slightly but significantly in both the TT (Fig. 1D) and CC (Fig. 1E) genotype groups (see also Table 2). However, the symmetric percent change of AAB insulin concentrations did not differ between genotype groups during the study (Fig. 1F).

Fasting, peak, and integrated (AAB) C-peptide concentrations increased in the TT group over the study period (Fig. 1G). In contrast, in the CC genotype group, there was a slight, but significant increase in fasting C-peptide concentrations (Fig. 1H). The symmetric percent change of AAB C-peptide differed significantly between groups during the study (Fig. 1I).

Fasting glucagon concentrations did not change in both the TT (Fig. 1J) and CC (Fig. 1K) genotype groups. However, nadir and AUC glucagon concentrations over the first 120 min postchallenge increased in the TT group but decreased in the CC group. The symmetric percent change of AUC glucagon concentrations reflected this between-group difference (Fig. 1L). In keeping with the hormone data, fasting GSR did not change over time, while nadir GSR increased in the TT group but not the CC group during the study (Table 2).

In subjects with the TT genotype, insulin action in response to the test meal decreased over the duration of the study (Fig. 2A). In contrast, this parameter did not change in subjects with the CC genotype (Fig. 2B). The symmetric percent change (Fig. 2C) did not differ between genotype groups (Table 2).

Total β-cell responsivity to glucose (Φ) did not change over the duration of the study in both genotype groups (Fig. 2D and E, respectively). The symmetric percent change (Fig. 2F) did not differ significantly between genotype groups during the study (Table 2).

The DI decreased over the 3 years of the study in subjects with the TT genotype (Fig. 2G). No change in DI was observed in the CC genotype (Fig. 2H). The symmetric percent change (Fig. 2I) did not differ significantly between genotype groups during the study (Table 2).

In this longitudinal study, the TT genotype at rs7903146 was associated with a decline in glucose tolerance over a 3-year period of observation. This could not be explained by an impaired β-cell response to glucose, as Φ was unchanged. In contrast, despite the rise in glucose concentrations in response to the oral glucose challenge, nadir glucagon concentrations increased inappropriately. These changes were not observed in subjects with the CC (diabetes-protective) genotype and suggest that α-cell dysfunction attributable to genetic variation in TCF7L2 is the first manifestation of islet dysfunction in the development of glucose intolerance. The mechanism by which this occurs is uncertain. The gene’s product was first characterized as the transcription factor necessary for proglucagon expression in the gut (14). However, the diabetes-associated variant does not alter circulating concentrations of proglucagon-derived gut peptides (15). Whether it affects the intraislet fate of proglucagon remains to be ascertained (16).

Previously, we (17) and others (18) have shown that the T-allele does not alter hepatic and peripheral insulin action when glucagon and insulin concentrations are matched. Therefore, a decline in insulin action associated with this genotype would be unexpected. A possible explanation for this observation is that the minimal model estimates insulin action from the relationship between insulin and glucose concentrations without accounting for glucagon’s actions on glucose. Given the rise in postchallenge glucose and insulin concentrations we observed in the TT group, accompanied by impaired glucagon suppression, this is a plausible scenario.

A decrease in DI implies that β-cell function is inappropriate for the prevailing insulin action and may suggest that the β-cell fails to compensate for the decline in insulin action in the group with the TT genotype. However, β-cell responsivity to glucose was unchanged, implying an appropriate secretory response to the higher postchallenge glucose concentrations observed. This is also in keeping with the (appropriate) increase in postchallenge concentrations of insulin and C-peptide we observed in this group. Taken together with the longitudinal changes in glucagon concentrations, this would suggest the primacy of α-cell dysfunction in driving early hyperglycemia in this cohort.

This study has some limitations. There was a significantly greater number of subjects with the CC genotype who did not return for a follow-up visit. The reasons for this are unclear. However, the baseline characteristics of subjects who returned for the follow-up visit did not differ from those who did not, suggesting that this is an unlikely confounder. Another difficulty associated with longitudinal studies of glucose metabolism is the possibility that changes in anthropometric characteristics might confound or contribute to changes in islet function. However, in this case, there were no significant between-group differences in BMI and lean and total body mass over time. By design, the two genotype groups were matched for fasting glucose. Genetic variation in TCF7L2 has been associated with increased fasting as well as postchallenge glucose (19). This may have obscured even greater differences in α-cell function given its importance in regulating fasting glucose (9). In conclusion, this longitudinal study shows that the T allele at rs7903146 is associated with the development of glucose intolerance accompanied by decreased α-cell suppression postchallenge and an appropriate β-cell response to glucose.

Acknowledgments. The authors acknowledge the excellent editorial assistance of M.M. Davis, Endocrine Research Unit, Mayo Clinic.

Funding. This study was supported by National Institute of Diabetes and Digestive and Kidney Diseases grant DK TR000135 to the Mayo Clinic General Clinical Research Center. A.V. is supported by National Institute of Diabetes and Digestive and Kidney Diseases grants DK78646, DK116231, and DK126206. C.D.M. was supported by the Italian Ministry of Education under the initiative “Departments of Excellence” (Law 232/2016).

Duality of Interest. A.V. is the recipient of an investigator-initiated grant from Novo Nordisk and has consulted for Hanmi, Crinetics, and Rezolute. No other potential conflicts of interest relevant to this article were reported.

Author Contributions. M.Z. researched data and ran the studies. M.C.L. undertook mathematical modeling of insulin and glucagon secretion. A.M.E. researched data and ran the studies. K.M., A.R., and E.V. assisted with data management and organization as well as with the initial data analysis. K.R.B. supervised the statistical analyses. C.C. and C.D.M. supervised the mathematical modeling, contributed to the discussion, and reviewed and edited manuscript. A.V. designed the study, oversaw its conduct, researched data, and wrote the first draft of the manuscript. A.V. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Prior Presentation. Parts of this study were presented in poster form at the 83rd Scientific Sessions of the American Diabetes Association, San Diego, CA, 23–26 June 2023.