Surg Endosc (2009) 23:700–704 DOI 10.1007/s00464-008-0001-2
TCF7L2 expression in diabetic patients undergoing bariatric surgery A. Katharine Hindle Æ Fred Brody Æ Rahul Tevar Æ Brian Kluk Æ Sarah Hill Æ Timothy McCaffrey Æ Sidney Fu
Received: 21 September 2007 / Accepted: 3 May 2008 / Published online: 21 September 2008 Ó Springer Science+Business Media, LLC 2008
Abstract Introduction The cause of diabetes in morbidly obese patients is multifactorial, including genetic, social, and dietary components. Transcription factor 7-like 2 (TCF7L2) is a gene that is related to the development of diabetes. This pilot study examines TCF7L2 expression in liver samples obtained from morbidly obese patients undergoing bariatric surgery. TCF7L2 expression is compared between diabetic and nondiabetic patients. Methods Liver samples were obtained from 20 morbidly obese patients undergoing bariatric surgery. Samples were flash frozen in liquid nitrogen. Total RNA was extracted from tissue samples using the TRIzol reagent (Invitrogen Inc, Carlsbad, CA). Using the iScript cDNA synthesis kit (Bio-Rad Laboratories, Hercules,CA), cDNA was synthesized. Quantitative polymerase chain reaction (qPCR) was done using SYBR Green qPCR Reagents (Stratagene, Cedar Creek TX) and the 7300 Real-Time PCR system (Applied Biosystems, Foster City CA). Preoperative
A. K. Hindle R. Tevar Department of Surgery, The George Washington University Medical Center, Washington, DC, USA F. Brody (&) S. Hill Department of General Surgery, The George Washington University Medical Center, Washington, DC, USA e-mail:
[email protected] B. Kluk T. McCaffrey S. Fu Department of Biochemistry and Molecular Biology, The George Washington University Medical Center, Washington, DC, USA
123
demographic and gene expression data were correlated using univariate analysis and logistic regression models. Only associations with a p-value less than 0.05 were considered significant. Results For the entire group, there was no correlation between body mass index (BMI) and TCF7L2 expression. In morbidly obese nondiabetic patients, there was a positive correlation between TCF7L2 expression and BMI (R2 = 0.21). In morbidly obese diabetic patients, there was an inverse correlation between TCF7L2 expression and BMI (R2 = 0.58). There was no significant relationship between TCF7L2 expression and age or glycosylated hemoglobin (HbA1c). Conclusions The cause of diabetes is multifactorial but the data from our pilot study documents the relationship of TCF7L2 with type 2 diabetes in morbidly obese patients. Keywords
Bariatric Obesity
Several series document that bariatric surgery resolves type 2 diabetes [1, 2]. However, the mechanisms behind these changes are unclear. The dramatic changes in insulin resistance and/or secretion following weight-loss surgery may produce corresponding changes in the expression patterns of individual genes or sets of related or co-regulated genes. By identifying these genes, the pathophysiology of type 2 diabetes may be discerned. Clearly, obesity and its comorbidities are related genetically in a variety of distinct pathways. Previous reports illustrate that obesity correlates with a decrease in the expression of peroxisome proliferators activated receptor gamma (PPARc) which causes adipocyte maturation and differentiation [3]. Moreover, recent data
Surg Endosc (2009) 23:700–704
show that genetic variants of the transcription factor 7-like 2 (TCF7L2) gene are linked strongly to an increased susceptibility to diabetes [4]. TCF7L2 heterodimerizes with bcatenin to stimulate the expression of the proglucagon gene glu. The mRNA product of glu is post-transcriptionally processed in a cell-type-specific manner to produce glucagon in pancreatic a cells, glucagon-like peptide 1 (GLP1) in gut and brain, and GLP-2 in small intestinal epithelium. GLP-1 stimulates insulin production and secretion, inhibits glucagon release, enhances peripheral insulin sensitivity, and induces satiety [5]. Also, GLP-1 induces pancreatic b-cell proliferation [6]. Interestingly, postprandial plasma GLP-1 protein levels are increased after gastric bypass [7, 8]. Finally, TCF7L2 expression in omental fat is decreased in type 2 diabetic obese patients compared with nondiabetic obese patients. These notable effects help explain the association between TCF7L2 polymorphisms, diabetes, and obesity. To date, very few studies have examined gene expression patterns in morbidly obese humans undergoing bariatric surgery. This study uses extraneous liver samples from morbidly obese diabetic and nondiabetic subjects to investigate the difference in gene expression of TCF7L2 between these two groups of patients.
Patients and methods Subject recruitment Institutional review board approval for this study was obtained from the George Washington University Medical Center Review Board (IRB#050408ER). All morbidly obese patients undergoing bariatric procedures at our institution were given the opportunity to participate in the study. Subjects included in the study were morbidly obese as defined by the 1991 National Institutes of Health (NIH) consensus meeting for obesity: by definition, a patient must have a body mass index (BMI) of greater than 40 kg/m2 or a BMI greater than 35 kg/m2 with at least one comorbidity. Comorbidities include diseases such as type 2 diabetes, hyperlipidemia, hypertension, obstructive sleep apnea, heart disease, stroke, asthma, and back and lower-extremity weight-bearing degenerative problems. Full informed consent was obtained and documented in all patients electing to participate. Demographic data were obtained including age, BMI, history of diagnosis with diabetes by another physician, and HbA1c levels. Definition of diabetes Patients were defined as diabetic or nondiabetic based on the following criteria. A patient was considered diabetic if
701
there was a history of diagnosis and treatment for diabetes or HbA1c level greater than 6.0%. Tissue collection Twenty subjects underwent either a standard Roux-en-Y gastric bypass (RYGBP) or gastric banding procedure. Routine liver biopsies were performed using electrocautery or ultrasonic dissection. Liver and omental specimens were divided and allotted into duplicate cryogenic storage tubes and immediately snap frozen in liquid nitrogen and stored at -80°C. RNA extraction and cDNA synthesis Total RNA was extracted from tissue samples using the TRIzol reagent (Invitrogen Inc, Carlsbad,CA) as previously described [3]. Using the iScript cDNA synthesis kit (BioRad Laboratories, Hercules,CA), cDNA was synthesized. One microliter RNA solution was treated with DNase I for 15 min at room temperature. The DNase was inactivated by adding 25 mM ethylenediamine tetraacetic acid (EDTA) and incubating at 65°C for 10 min. Reverse transcription was then performed on the 1 ll RNA sample by adding iScript reagents including 4 ll 5x iScript reaction mix, 1 ll iScript reverse transcriptase, and sufficient nuclease-free water to a reaction volume of 20 ll. The reaction was incubated at 25°C for 5 min, 42°C for 30 min, and 85°C for 5 min, and then stored at -20°C. PCR and qPCR PCR was performed on all cDNA samples to assess the quality of the cDNA and to create a standard dilution curve for qPCR. The 18S gene was used to normalize expression. Oligonucleotide primers were created for TCF7L2 as well as 18S. PCR was performed in 20-ll tubes by combining 2.5 ll of 109 PCR reaction buffer, 1 ll Taq polymerase, 1 ll 200 pM forward primer, 1 ll 200 pM reverse primer, and DNase/RNase-free water to a total volume of 25 ll. Each primer pair had PCR step times, temperatures, and cycle numbers optimized for maximal product specificity and yield. The completed PCR products were evaluated using 2% agarose gel electrophoresis with ethidium bromide staining. Quantitative PCR (qPCR) was done using SYBR Green qPCR reagents (Stratagene, Cedar Creek TX) and the 7300 Real-Time PCR system (Applied Biosystems, Foster City, CA). A standard curve for the PCR product was created. A dilution series was prepared using concentrations of 1 9 100 to 1 9 10-5 of the original sample. One microliter of each cDNA sample or dilution was mixed with 1 ll 200 pM forward primer, 1ll 200 pM reverse primer, SYBR
123
702
BMI vs TCF7L2 expression - All patients 60 2
R = 0.0413
BMI (kg/m^2)
55 50 45 40 35 30 2.3
2.5
2.7
2.9
3.1
3.3
TCF7L2 expression (normalized)
Fig. 1 BMI and TCF7L2 expression in liver for all patients (n = 20). There is no significant correlation between BMI and TCF7L2 expression for the entire population as a whole. BMI, body mass index BMI vs TCF7L2 expression - Non diabetic patients 60 R2 = 0.2067 55
BMI (kg/m^2)
Green PCR Master Mix, and DNase/RNase-free water to a total volume of 25 ll. Quantitative PCR was then performed using an Applied Biosystems 7300 Real-Time PCR System. Step, cycle, and temperature values were determined using the previously optimized PCR values. The resultant data was analyzed using the accompanying SDS 7700 software. Cycle threshold (Ct) was defined as the cycle number at which a significant increase in the fluorescence signal was first detected. A standard curve was generated using serial dilutions of the standard cDNA on the basis of the linear relationship between the Ct and the logarithm of the starting copy number. Quantification of samples was performed by SDS 7700 software in order to calculate Ct values for each sample using the generated standard curve. Relative expression of each selected gene product for each sample was calculated by comparing Ct values of the target gene with Ct values of the 18S constitutive gene product. The following primers were used: TCF7L2 forward (50 -CATATGGTCCCACC ACATCA-30 ), TCF7L2 reverse (50 -CACTCTGGGACG ATTCCTGT-30 ), 18S forward (50 -CCGCAGCTAGG-AA TAATGGA-30 ), and 18S reverse (50 -CCCTCTTAATCA TGGCCTCA-30 ). qPCRs were performed in triplicate and repeated for confirmation.
Surg Endosc (2009) 23:700–704
50 45 40 35 30 2.3
2.5
2.7
2.9
3.1
3.3
TCF7L2 expression (normalized)
Data analysis Preoperative demographic and gene expression data were correlated using univariate analysis and logistic regression models. Only associations with a p-value less than 0.05 were considered significant.
Fig. 2 BMI and TCF7L2 expression in liver for nondiabetic patients. There is a positive relationship between BMI and TCF7L2 expression (R2 = 0.21). BMI, body mass index BMI vs TCF7L2 expression - Diabetic patients 45
R 2 = 0.5779
44
Results Twenty morbidly obese patients underwent RYGBP or gastric banding and were included in this study. Mean patient age was 41.8 years (22–63 years). Mean BMI was 45.3 kg/m2 (35.3–56.1 kg/m2) and mean HbA1c was 6.3% (4.7–11.5%). In the diabetic group, seven patients were diabetic either by history or by HbA1c [6.0% with mean age of 49.1 years (35–60 years), BMI 43.0 kg/m2 (35.3– 56.1 kg/m2) and HbA1C of 6.4% (5.8–11.5%). In the nondiabetic group, there were 13 patients with an average age was 37.2 years (27–63 years), BMI 46.6 kg/m2 (36–51 kg/m2), and HbA1C of 5.4% (4.7–5.8%). Total RNA was isolated from liver tissue samples, reverse transcribed, and TCF7L2 expression was measured using qPCR. All samples demonstrated expression of TCF7L2 and the 18S ribosomal subunit gene. A linear regression analysis of TCF7L2 was performed using preoperative variables including BMI, age, and HbA1c.
123
BMI (kg/m^2)
43 42 41 40 39 38 37 36 35 2.6
2.7
2.8
2.9
3
3.1
3.2
TCF7L2 expression (normalized)
Fig. 3 BMI and TCF7L2 expression in liver for diabetic patients. There is an inverse relationship between BMI and TCF7L2 expression (R2 = 0.58). BMI, body mass index
There was no significant correlation between TCF7L2 expression and BMI in the study population as a whole (Fig. 1). However, when the diabetic and nondiabetic populations are isolated, TCF7L2 expression was correlated to BMI. In the nondiabetic population there was a positive correlation of TCF7L2 expression with BMI (Fig. 2). In contrast, in the diabetic population, BMI was
Surg Endosc (2009) 23:700–704
inversely correlated with TCF7L2 expression (Fig. 3). Finally, no significant correlation was found between TCF7L2 expression and age or HbA1c.
Discussion Diabetes mellitus is a worldwide epidemic with a global disease burden projected to increase from 150 to 220 million in the year 2010 and 300 million in 2025 [9]. The overwhelming majority of cases appear in the form of type 2 diabetes. Type 2 diabetes is a complex, multifactorial disease in which poorly understood genetic factors combine with environmental risks to influence both insulin secretion and resistance. The molecular pathophysiology of this process remains unclear. Implicated pathways include abnormal pancreatic b-cell development, insulin receptor signaling, fatty acid oxidation, and adipogenesis [10]. Genomic linkage studies have identified many regions of the genome that correlate with diabetes [11]. However, until recently, the phenotypic states do not correlate with the corresponding genomic regions. In spite of our small sample size in this pilot study, there are clear trends between TCF7L2 expression in diabetic and nondiabetic patients. Our data demonstrate that, as BMI increases in diabetic patients, there is a decrease in hepatic expression of TCF7L2. The inverse is true for nondiabetic morbidly obese patients. As BMI increases, there is an increase in TCF7L2 expression. These phenotypic findings provide more evidence that TCF7L2 plays a role in the pathogenesis of diabetes in morbidly obese subjects. These findings also correspond to previous findings that TCF7L2 expression is decreased in the omentum of diabetic obese patients [7]. Skeletal muscle and liver are the primary insulin-responsive tissues that mediate insulin resistance in diabetes. In obesity, adipocyte-derived free fatty acids and cytokines contribute to insulin resistance in liver and muscle tissue [12]. The relationship between liver TCF7L2 expression, GLP-1 expression, and diabetes clearly warrants further investigation. Elucidation of the molecular pathways involved may clarify the pathophysiology of diabetes and the relationship between diabetes and obesity. Overall, an estimated 1.7 billion people worldwide are either overweight or obese, with comorbidities including diabetes, hyperlipidemia, hypertension, and sleep apnea. These factors account for 2.5 million deaths annually. Unfortunately, diets and pharmaceuticals do not provide sustainable weight loss [13, 14]. Today, weight-loss surgery is the only therapeutic intervention that reliably induces significant and sustainable weight loss. A recent meta-analysis of 136 studies (N = 22,094) found that bariatric surgery induces significant, sustained weight loss
703
in the vast majority of patients and eliminates or significantly ameliorates the comorbidities of obesity including diabetes, hyperlipidemia, hypertension, and obstructive sleep apnea [1]. Specifically, 76.8% of patients experience complete resolution of diabetes, defined as discontinuation of diabetes-related medications and maintenance of normal blood glucose as measured by glycosylated hemoglobin (HbA1c) and fasting glucose [1]. The robust resolution of diabetes in bariatric surgical patients provides a unique model to study the metabolic pathways of diabetes. The dramatic changes in insulin resistance and secretion following weight loss surgery may produce corresponding changes in the expression patterns of individual genes or sets of related or co-regulated genes. Identification of these genes may elucidate the regulatory mechanisms of diabetes and engender novel therapies. We have demonstrated that TCF7L2 correlates with obesity in diabetic patients. Future studies will seek to correlate tissue expression of TCF7L2 with expression in blood samples in order to compare pre- and postoperative expression of this gene. Furthermore, high-density oligonucleotide array analyses will be used to ascertain any changes in gene expression patterns following bariatric surgery.
References 1. Buchwald H, Avidor Y, Braunwald E, Jjensen MD, Pories W, Fahrbach K, Schoelles K (2004) Bariatric surgery: a systematic review and meta-analysis. JAMA 292:1724–1737 2. Sjostrom L, Lindroos AK, Peltonen M, Torgerson J, Bouchard C, Carlsson B, Dahlgren S, Larsson B, Narbro K, Sjostrom CD, Sullivan M, Wedel H (2004) Lifestyle, diabetes, and cardiovascular risk factors 10 years after bariatric surgery. N Engl J Med 351:2683–2693 3. Brody F, Hill S, Celinski S, Kar R, Kluk B, Pinzone J, Fu S (2007) Expression of ectonucleotide pyrophosphate phosphodiesterase and peroxisome proliferator activated receptor gamma in morbidly obese patients. Surg Endosc (Epub ahead of print) 4. Grant SFA, Thorleifsson G, Reynisdottir I et al (2006) Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes. Nat Genet 38:320–323 5. Yi F, Brubaker PL, Jin T (2005) TCF-4 mediates cell type-specific regulation of proglucagon gene expression by beta-catenin and glycogen synthase kinase-3beta. J Biol Chem 280(2):1457–1464 6. Prentki M, Nolan CJ (2006) Islet b cell failure in type 2 diabetes. J Clin Invest 116:1802–1812 7. Cauchi S, Meyre D, Dina C, Choquet H, Samson C, Gallina S, Balkau B, Charpentier G, Pattou F, Stetsyuk V, Scharfmann R, Staels B, Fruhbeck G, Froguel P (2006) Transcription factor TCF7L2 genetic study in the French population: expression in human b-cells and adipose tissue and strong association with type 2 diabetes. Diabetes 55:2903–2908 8. Morinigo R, Moize V, Musri M, Lacy AM, Navarro S, Marin JL, Delgado S, Casamitjana R, Vidal J (2006) Glucagon-like peptide1, peptide YY, hunger, and satiety after gastric bypass surgery in morbidly obese subjects. J Clin Endosc Metab 91:1735–1740 9. Zimmet P, Alberti KG, Shaw J (2001) Global and societal implications of the diabetes epidemic. Nature 414:782–787
123
704 10. Mootha VK, Lindgren CM, Eriksson KF, Subramanian A, Sihag S, Lehar J, Puigserver P, Carlsson E, Ridderstrale M, Laurila E, Houstis N, Daly MJ, Patterson N, Mesirov JP, Golub TR, Tamayo P, Spiegelman B, Lander ES, Hirschhorn JN, Altshuler D, Groop LC (2003) PGC-1a-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet 34:267–273 11. Kahn CR, Vicent D, Doria A (1996) Genetics of non-insulindependent (type-II) diabetes mellitus. Ann Rev Med 47: 509–531
123
Surg Endosc (2009) 23:700–704 12. Lazar MA (2005) How obesity causes diabetes: not a tall tale. Science 307:373–375 13. Mokdad AH, Ford ES, Bowman BA, Dietz WH, Vinicor F, Bales VS, Marks JS (2003) Prevalence of obesity, diabetes, and obesityrelated health risk factors, 2001. JAMA 289:76–79 14. North American Association for the Study of Obesity and the National Heart, Lung, and Blood Institute (2000) The practical guide: identification, evaluation, and treatment of overweight and obesity in adults. National Institutes of Health, Bethesda, MD. NIH publication 00-4084
