Journal of Clinical Endocrinology & Metabolism
, doi:10.1210/jc.2008-0546
The Journal of Clinical Endocrinology & Metabolism Vol. 93, No. 9 3644-3649
Copyright © 2008 by The Endocrine Society
Association Analysis of Krüppel-Like Factor 11 Variants with Type 2 Diabetes in Pima Indians
Lijun Ma,
Robert L. Hanson,
Lorem N. Que,
Janel L. Mack,
Paul W. Franks,
Aniello M. Infante,
Sayuko Kobes,
Clifton Bogardus and
Leslie J. Baier
Diabetes Molecular Genetics Section (L.M., R.L.H., L.N.Q., J.L.M., P.W.F., A.M.I., S.K., C.B., L.J.B.), Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes, Digestive and Kidney Diseases, National Institutes of Health, Department of Health and Human Services, Phoenix, Arizona 85004; and Genetic Epidemiology and Clinical Research Group (P.W.F.), Department of Public Health and Clinical Medicine, Division of Medicine, Umeå University Hospital, SE-901 87 Umeå, Sweden
Address all correspondence and requests for reprints to: Leslie J. Baier, Ph.D., Diabetes Molecular Genetics Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes, Digestive and Kidney Diseases, National Institutes of Health, 445 North Fifth Street, Suite 210, Phoenix, Arizona 85004. E-mail: lbaier{at}phx.niddk.nih.gov.
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Abstract
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Context: Krüppel-like factor 11 (KLF11) is a transcription factor of the zinc finger domain family that has been shown to regulate expression of the insulin gene. An initial study reported that a KLF11 variant predicting a Q62R was associated with type 2 diabetes (T2D) in French Caucasians; however, subsequent studies have failed to identify an association between this variant and T2D in subjects from a similar Northern-European ancestry.
Objective: We sought to determine whether the Q62R or other variants within KLF11 were associated with T2D in Pima Indians, a population with an extremely high prevalence of this disease.
Design, Setting, and Subjects: KLF11 was sequenced in 24 Pima Indians to identify potentially novel variants. There were 18 variants genotyped in a family-based sample of 1337 Pima Indians to analyze the linkage disequilibrium pattern of this gene and identify representative variants. Four representative variants were further genotyped in a population-based sample of 3501 full-heritage Pima Indians for association analyses. Among these subjects, 413 had undergone metabolic studies when they were nondiabetic to measure traits that predict T2D.
Results: Neither the Q62R nor any other common variant in KLF11 was associated with T2D in the Pima population. In addition, no variant was associated with insulin secretion or insulin-stimulated glucose disposal rate.
Conclusions: Common variation in KLF11 variation does not appear to influence the population-based risk for developing T2D among full-heritage Pima Indians. Thus, KLF11 is unlikely to play a major role in the etiology of T2D among this Native American population.
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Introduction
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The transcription factor Krüppel-like factor 11 (KLF11) is a member of the zinc finger domain family that mediates TGF-β-induced growth inhibition in untransformed epithelial cells (1, 2). KLF11 is a negative regulator of pancreatic cell growth (3, 4). Mice transgenic for KLF11 develop a significantly smaller exocrine pancreas than control mice due to reduced cellular proliferation and enhanced apoptosis (5), whereas KLF11–/– mice display normal development (6). In β-cell lines, it has been reported that high-glucose conditions stimulate KLF11 mRNA expression, and cotransfection of human KLF11 can activate the human proinsulin promoter (7). Conversely, it has also been reported that high glucose reduces endogenous KLF mRNA levels in β-cell lines (8). Although the exact role of KLF in glucose homeostasis remains controversial, the function of this transcription factor in pancreatic β-cell development makes it an intriguing candidate gene in the etiology of type 2 diabetes (T2D). The role of KLF11 in T2D was initially studied in French Caucasians, in whom a potentially functional Q62R was reported to be associated with this disease (7). However, in a subsequent study of 8676 subjects from Northern-European descent, including both case/control and family-based subjects, no association was detected between the Q62R and T2D or several insulin-related quantitative traits (9). In an attempt to replicate this study in Pima Indians who have an extremely high prevalence of T2D (10), we determined the linkage disequilibrium (LD) pattern across KLF11 in a group of family-based Pima subjects (n = 1337) and genotyped four representative variants in a population-based sample of 3501 full-heritage Pima Indians.
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Subjects and Methods
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Subjects and clinical characteristics
All subjects are Pima Indians who are participants in our ongoing longitudinal study of T2D among members of the Gila River Indian Community (11). Initially, a family-based sample was genotyped to determine the haplotype structure of KLF11 in this population, and representative variants were subsequently genotyped in a population-based sample for association analyses. The family-based sample consisted of 1337 subjects from 332 nuclear families in 112 pedigrees. The population-based sample consisted of 3501 full-heritage Pima Indians for whom there was DNA available and information on diabetes status and body mass index (BMI). Among the 3501 subjects, 1561 were diagnosed with T2D [male/female = 580/981; (mean ± SD) BMI = 38 ± 8 kg/m2, age of onset = 37 ± 12 yr], and 1940 were nondiabetic [male/female = 902/1038; (mean ± SD) BMI = 36 ± 8 kg/m2, age = 31 ± 14 yr], as defined by a 2-h oral glucose tolerance test (OGTT). A subset of these subjects (n = 413) had additionally undergone metabolic phenotyping in our clinical research center when they were nondiabetic. For these detailed metabolic tests, nondiabetic subjects between the ages of 18 and 45 yr were admitted to our clinical research ward for 7–10 d. Only individuals found to be healthy by medical history, physical examination, and routine laboratory tests and who are not taking medications are studied. Oral glucose tolerance is measured after 2–3 d on a weight-maintaining diet of mixed composition. Blood for plasma glucose and insulin measurements is drawn before ingesting 75 g glucose, and at 30, 60, 120, and 180 min thereafter. Subjects also receive a 25-g iv injection of glucose over 3 min to measure the acute insulin response. Blood samples were collected before infusion, and at 3, 4, 5, 6, 8, and 10 min after infusion for determination of plasma glucose and insulin concentrations. The acute insulin response was calculated as the mean increment in plasma insulin concentrations from 3–5 min (12). The hyperinsulinemic-euglycemic clamp technique was used to determine basal glucose appearance and insulin-stimulated glucose disappearance (uptake) rates and was described elsewhere. Body composition was estimated by underwater weighing or dual-energy x-ray absorptiometry (DPX-1; Lunar Radiation, Madison, WI). All studies were approved by the review board of the National Institute of Diabetes and Digestive and Kidney Diseases. All subjects provided signed informed consent before participation.
Single nucleotide polymorphism (SNP) identification and genotyping
To identify novel, potentially functional sequence variants, all exons, exon-intron boundaries, 5' and 3' untranslated regions, and 2.5 kilobases of the putative promoter regions of KLF11 were sequenced in DNA from 24 Pima Indians (12 had T2D with an age of onset of < 25 yr, and 12 were nondiabetic and > 45 yr of age) Sequencing was performed using the Big Dye Terminator (Applied Biosystems, Foster City, CA) on an automated DNA capillary sequencer (model 3730xl; Applied Biosystems). SNPs were either identified by sequencing or were selected from the National Center for Biotechnology Information public database (Build 35.1) from regions that were not sequenced, such as introns. All database SNPs were selected that had a minor allele frequency more than 0.20 in Caucasians. SNPs were genotyped by the method of SNPlex according to the manufacturer’s instructions (Applied Biosystems). All genotypical data were in Hardy-Weinberg equilibrium.
Statistical analysis
Statistical analyses were performed using the software of SAS Institute Inc. (version 8; Cary, NC). The association of genotypes with diabetes was assessed by analysis of contingency tables. For continuous variables, the general estimating equation procedure was used to adjust for the covariates, including sibship, because some subjects were siblings. A logistical regression was used to adjust for age, gender, birth date, and sibship to test the association with T2D in the population-based sample. To control for potential population stratification, the association with diabetes was also analyzed with a within-family association test using the method of Abecasis et al. (13). Plasma insulin concentrations, insulin-stimulated glucose disposal rates, and acute insulin responses were log transformed before analyses to approximate a normal distribution. For the additive model, homozygotes for the major allele (MM), heterozygotes (Mm) and homozygotes for the minor allele (mm) were coded to a continuous numeric variable for genotype (as 2, 1, 0). In each case the major allele was defined as the risk allele. The dominant model was defined as contrasting genotypic groups MM+Mm vs mm, and the recessive model was defined as contrasting genotypic groups MM vs. Mm+mm. To examine pair-wise LD, haplotype frequencies were estimated with the EH program (Xiaoli Xie and Jurg Ott, Rockefeller University, New York, NY) (http://linkage.rockefeller.edu/ott/), and these haplotype frequencies were used to calculate D' and 
2. P values less than 0.05 were considered to be of statistical significance.
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Results and Discussion
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The sequencing of KLF11 in 24 Pima Indian subjects (none was related by first degree) identified 10 variants, including a nonsynonymous Q62R (rs35927125) and a previously reported ATG-1659 (7), which were in complete genotypical concordance. The previously identified rare nonsynonymous SNPs that predict an A347S (7), T220M (rs34336420), S378F (rs35476458), and R402Q (rs34762805) were not detected in these Pima Indian samples. A total of 18 SNPs, identified either by sequencing or selected from public databases that are positioned within regions that were not sequenced, was genotyped in a family-based sample of 1337 Pima subjects to determine the LD pattern across this region in Pima Indians (Fig. 1
). Four representative SNPs, which captured more than 90% of genetic information, were selected for genotyping in the population-based sample of 3501 full-heritage Pima Indians. None of the SNPs was associated with T2D using either a general or a within-family analysis (Table 1). In addition, haplotype analysis did not uncover a more significant association than any single SNP analysis (Table 2).
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FIG. 1. Variants near/within KLF11 selected for analysis. A, Variants identified by direct sequencing (darker arrows) or selected from the National Center for Biotechnology Information public database (Build 35.1) (lighter arrows) are indicated. BC009884 is a 5' distant expressed sequence tag. B, LD pattern of variants is shown as D' (upper left portion of matrix) and r2 (lower right portion of matrix). D' is defined as a measure of allelic association and r2 as a measure of genotype concordance. Representative SNPs genotyped in the population-based sample are denoted by " ." kb, Kilobase; MAF, minor allele frequency in Pima Indians; UTR, untranslated region.
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TABLE 2. KLF11 haplotype association analysis with T2D in a population-based sample of 3501 full-heritage Pima Indians
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In a previous study of French Caucasians, Neve et al. (7) reported that the Q62R was significantly associated with T2D among 1696 cases and 1776 normal glycemic controls [odds ratio (OR) = 1.29; P = 0.0003]. The frequency of Q62R in the French Caucasians is 10%, whereas in Pima Indians it is 5%. Assuming a T2D prevalence of 45% in adult Pima Indians, with a risk allele frequency of 5%, and the previously reported OR range of 1.13–1.54 (7), our population-based sample of Pima Indians had approximately 97% power to detect an association (P = 0.05) with T2D.
Florez et al. (9) also reported a lack of association between Q62R and T2D in their study of both family-based and case-control samples from Northern-European ancestry (total subjects = 8676). This group also found no association with rs4444493, which is in high genotypical concordance with Q62R (D' = 0.98–1.0; r2 = 0.94–1.0) among four Caucasian groups (7, 9). These two SNPs are in perfect LD (D' = 1; r2 = 1) in Pima Indians (Fig. 1
). Owing to the similar ethnic background of the cohorts examined in the studies by Neve (7) and Florez (9) et al., it is unlikely that the disparate findings are due to different genomic substructures of the populations, which may be the case when comparing the results from Pima Indians and other ethnic groups. Alternative explanations for the differences between studies could include different population sampling strategies, and gene-gene or gene-environmental interactions. Although in Neve et al.’s (7) original study the association of Q62R with diabetes in the smaller family-based sample was highly statistically significant [P = 0.00023; OR = 1.85 (95% confidence interval (CI) 1.33–2.57)], the effect was much more modest in their larger replication sample [P = 0.034; OR = 1.18 (95% CI 1.01–1.38)]. Thus, it is possible that the effect of Q62R (or the variant it tags) may be dependent on certain genetic or environmental factors that are specific to certain families.
It is also noteworthy that in genome-wide association studies performed on the Affymetrix 500 K SNP chip (Affymetrix, Inc., Santa Clara, CA), seven SNPs, including rs4444493, described previously, were captured across the KLF11 region in a United Kingdom Caucasian sample [Wellcome Trust Case/Control Consortium (14)] (http://www.wtccc.org.uk/info/summary_stats.shtml) and a Scandinavian cohort (15) (http://www.broad.mit.edu/diabetes/). None of these SNPs was associated with T2D in these Caucasian samples. In a recent study of a Japanese population, the Q62R appeared to be monomorphic, but additional SNPs across KLF11 were not associated with T2D (16).
Impaired insulin secretion is a trait that predicts T2D, and the study in French Caucasians also reported that the Q62R affected insulin secretion in their study of 70 normal glycemic subjects. Therefore, we also analyzed both the acute insulin response to a 25-g iv bolus of glucose as well as the early (30 min) plasma insulin concentration after a 75-g OGTT in 297 normal glucose tolerant full-heritage Pima Indians. No association was found with either the Q62R or the other three representative SNPs and acute/early insulin response (Table 3). We were also unable to detect an association between these SNPs and other measures of plasma insulin during an OGTT, or insulin sensitivity as assessed by the insulin-stimulated glucose disposal rate during hyperinsulinemic-euglycemic clamp among 413 nondiabetic Pima Indians. A nominal association was observed between rs4073397 and percentage of body fat among the nondiabetic subjects who had been metabolically phenotyped (adjusted P = 0.04; Table 3); however, this SNP was not associated with BMI among the 3501 population-based subjects (P = 0.19 adjusted for age, sex, birth year, and family relationship). In addition, rs3885668 and rs6432053 were nominally associated with fasting plasma glucose among the metabolically phenotyped subjects (P = 0.03 and P = 0.01, respectively, Table 3), but the significance of these associations remains unclear.
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TABLE 3. Association between SNPs in KLF11 and diabetes-related traits among nondiabetic full-heritage Pima Indians
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In summary, our data do not support a major role for KLF11 in influencing the population-based risk for T2D among full-heritage Pima Indians.
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Acknowledgments
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We thank Dr. Bernadette Neve for valuable communication during the process of this project and Dr. Yunhua L. Muller for critical reading of this manuscript.
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Footnotes
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This study was also supported by the intramural research program of National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health.
Disclosure Statement: The authors have nothing to declare.
First Published Online July 1, 2008
Abbreviations: BMI, Body mass index; CI, confidence interval; KLF11, Krüppel-like factor 11; LD, linkage disequilibrium; OGTT, oral glucose tolerance test; OR, odds ratio; SNP, single nucleotide polymorphism; T2D, type 2 diabetes.
Received March 7, 2008.
Accepted June 24, 2008.
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Abstract
Introduction
