- Email: [email protected]
Heterogeneous effects of gene polymorphism on type 2 diabetes risk: Lesson from the PPARγ2 Pro12Ala
Nutrition, Metabolism & Cardiovascular Diseases (2007) 17, 629e631
www.elsevier.com/locate/nmcd
EDITORIAL
Heterogeneous effects of gene polymorphism on type 2 diabetes risk: Lesson from the PPARg2 Pro12Ala Although it is known that genes modulate the risk of type 2 diabetes, the real impact of most of them is still unknown [1]. The dissection of the genetic architecture of type 2 diabetes, as of many other human complex traits, has been difficult because it is polygenic (i.e. several genes, each with a modest effect, are involved) and heterogeneous (i.e. different genes are involved in different individuals). In addition, geneeenvironment and geneegene interactions are likely to be in the picture, making the scenario even more difficult to unravel. Geneeenvironment interaction implies a change in the direction or magnitude of the effect of a genetic variant according to environmental changes [2]. The ability to determine the precise mode of interaction is highly dependent on study features including sample size, how well genetic and non-genetic exposures are measured and the statistical tools employed. The traditional approach to test for interaction by using logistical regression modelling is limited by its inadequacies to deal with many factors. Indeed, as the number of genetic and environmental factors increases, so the number of possible interactions grows exponentially, resulting in a dramatic loss of statistical power. Discussing new statistical approaches aimed at unravelling the interactions between genes and environment is out of the scope of this editorial and here it is just enough to remind the reader that two different strategies namely, recursive partitioning and multifactor dimensionality reduction, have been proposed [3,4] and recently reviewed [5]. Since studies focusing on how genes interact with environmental factors in modulating the expression of specific phenotype are difficult to
design and carry out, most investigations in the field have attempted to catch the effect of single genes considered on their own. Among the several genetic polymorphisms so far described as diabetogenic, the Peroxisome Proliferator Activated Receptor-g2 (PPARg2) Pro12Ala is certainly one of the most well characterized [6]. PPARg2 is a transcription factor, expressed almost exclusively in adipose tissue which, by binding to Peroxisome Proliferator Responsive Element located in the promoter region of target genes, regulates adipocyte differentiation, lipid metabolism and insulin sensitivity [6]. Compared to the more frequent Pro12, the Ala12 variant has a reduced ability to trans-activate PPRE-containing promoters (i.e. a ‘‘loss of function’’ variation) [7]. Very intensive work has been carried out by many groups aimed at investigating the role of the Ala12 variant in modulating the risk of type 2 diabetes [6]. Although several studies have indicated a protective role of this variant, data obtained so far have been quite conflicting. We specifically addressed this issue by performing a comprehensive meta-analysis of all published studies for a total of 42,910 individuals [8]. Overall, Ala12 carriers showed a 19% risk reduction of type 2 diabetes, thus confirming data obtained in previous smaller meta-analyses [9e11]. Nonetheless, the association between Pro12Ala polymorphism and type 2 diabetes was extremely heterogeneous across all studies [8]. When the effect of covariates was investigated by meta-regression analysis, approximately 50% of the observed heterogeneity was accounted for by the mean BMI of controls in each study, with risk reduction being greater when BMI was lower [8]. Meta-regression of mean data only indicates
0939-4753/$ - see front matter ª 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.numecd.2007.07.001
630 ecological correlation and does not necessarily indicate causality. However, it is of note that our finding is in line with a recently published prospective study [12] showing that the protective effect of the Ala12 variant on the progression from impaired glucose tolerance to type 2 diabetes is greater when BMI is lower. The Ala12 variant has been repeatedly reported to be associated with increased BMI, a strong predictor itself of altered glucose homeostasis. It could therefore be argued that Ala12 carriers are protected from type 2 diabetes only when, because of environmental and/or additional genetic background, the detrimental effect of the Ala12 variant on obesity is not observable, allowing its beneficial effect on insulin sensitivity and lipid metabolism to end up in a reduced risk of type 2 diabetes. In the meta-analysis we performed, the association between Pro12Ala and type 2 diabetes was heterogeneous also when considering only studies carried out in Europe. In fact -according to a North to South gradient- risk reduction for Ala12 carriers was greater in Northern Europe (25%), barely significant in Central Europe (10%) and non-existent (0%) in Southern Europe [8]. In these circumstances, heterogeneity was not accounted for by BMI, thus suggesting that other environmental and genetic factors might have played a role. According to this hypothesis, in this issue of the journal Scacchi et al. [13] suggest that the different effect in different populations of the Pro12Ala polymorphism is partly due to different dietary habits. By analysing data from several (including some so far unpublished) populations, the authors confirm the overall protective role of the Ala12 variant against type 2 diabetes risk but also report that the different disease prevalence observed in populations with the same frequency of the Ala12 allele is paralleled by differences in the environmental risk factors, with particular emphasis on dietary fat intake. Indeed, single studies have shown that the Pro12Ala polymorphism interacts with diet in modulating insulin resistance, excess body weight and type 2 diabetes [14e17]. The scenario depicted by all previous and present [13] data clearly suggests that the Pro12Ala polymorphism may not be sufficient to significantly affect per se the risk of type 2 diabetes. Rather, it is likely to play a role by interacting with additional environmental and supposedly genetic factors, which may be different in different populations. If, after being specifically tested by large collaborative studies, this hypothesis turns out to be true, it would not only help a better understanding of the complex pathophysiology of type 2 diabetes but would also pave the way for translational
Editorial human investigation by providing new tools for early identification of subject subgroups at high risk for type 2 diabetes, and for tailoring specific treatments of diabetes and its devastating complications.
References [1] Almind K, Doria A, Kahn CR. Putting the genes for type II diabetes on the map. Nat Med 2001;7:277e9. [2] Cooper RS. Geneeenvironment interactions and the etiology of common complex disease. Ann Intern Med 2003;139: 437e40. [3] Young SS, GE N. Recursive partitioning analysis of complex disease pharmacogenetic studies. I. Motivation and overview. Pharmacogenomics 2005;6:65e75. [4] Moore JH. Computational analysis of geneegene interactions using multifactor dimensionality reduction. Expert Rev Mol Diagn 2004;4:795e803. [5] Cocozza S. Methodological aspects of the assessment of geneenutrient interactions at the population level. Nutr Metab Cardiovasc Dis 2007;17:82e8. [6] Stumvoll M, Haring H. The peroxisome proliferatoractivated receptor-gamma2 Pro12Ala polymorphism. Diabetes 2002;51:2341e7. [7] Deeb SS, Fajas L, Nemoto M, Pihlajamaki J, Mykkanen L, Kuusisto J, et al. A Pro12Ala substitution in PPARgamma2 associated with decreased receptor activity, lower body mass index and improved insulin sensitivity. Nat Genet 1998;20:284e7. [8] Ludovico O, Pellegrini F, Di Paola R, Minenna A, Mastroianno S, Cardellini M, et al. Type 2 diabetes risk given by PPARg2 Ala12 variant is heterogeneous across different populations. Obesity 2007;15:1e6. [9] Altshuler D, Hirschhorn JN, Klannemark M, Lindgren CM, Vohl MC, Nemesh J, et al. The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat Genet 2000;26:76e80. [10] Lohmueller KE, Pearce CL, Pike M, Lander ES, Hirschhorn JN. Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat Genet 2003;33:177e82. [11] Parikh H, Groop L. Candidate genes for type 2 diabetes. Rev Endocr Metab Disord 2004;5:151e76. [12] Florez JC, Jablonski KA, Sun MW, Bayley N, Kahn SE, Shamoon H, et al, Diabetes Prevention Program Research Group. Effects of the type 2 diabetes-associated PPARG P12A polymorphism on progression to diabetes and response to troglitazone. J Clin Endocrinol Metab 2007;92: 1502e9. [13] Scacchi R, Pinto A, Rickards O, Pacella A, De Stefano GF, Cannella C, et al. An analysis of peroxisome proliferatoractivated receptor gamma (PPAR-gamma2) Pro12Ala polymorphism distribution and prevalence of type 2 diabetes mellitus (T2DM) in world populations in relation to dietary habits. Nutr Metab Cardiovasc Dis 2007. [14] Luan J, Browne PO, Harding AH, Halsall DJ, O’Rahilly S, Chatterjee VK, et al. Evidence for geneenutrient interaction at the PPARgamma locus. Diabetes 2001;50:686e9. [15] Memisoglu A, Hu FB, Hankinson SE, Manson JE, De Vivo I, Willett WC, et al. Interaction between a peroxisome proliferator-activated receptor gamma gene polymorphism and dietary fat intake in relation to body mass. Hum Mol Genet 2003;12:2923e9.
Editorial
631
[16] Pisabarro RE, Sanguinetti C, Stoll M, Prendez D. High incidence of type 2 diabetes in peroxisome proliferator-activated receptor gamma2 Pro12Ala carriers exposed to a high chronic intake of trans fatty acids and saturated fatty acids. Diabetes Care 2004;27: 2251e2. [17] Vaccaro O, Lapice E, Monticelli A, Giacchetti M, Castaldo I, Galasso R, et al. Pro12Ala polymorphism of the PPARgamma2 locus modulates the relationship between energy intake and body weight in type 2 diabetic patients. Diabetes Care 2007 May;30:1156e61.
Vittorio Tassi Research laboratory of Diabetes and Endocrine Diseases, CSS Scientific Institute, San Giovanni Rotondo, Italy
Sabrina Prudente Research Laboratory of Diabetes and Endocrine Diseases, CSS Scientific Institute, San Giovanni Rotondo, Italy
CSS-Mendel Institute, Viale Regina Margherita 261, 00198 Rome, Italy
CSS-Mendel Institute, Viale Regina Margherita 261, 00198 Rome, Italy Ornella Ludovico Unit of Endocrinology, CSS Scientific Institute, San Giovanni Rotondo, Italy
Vincenzo Trischitta* Research laboratory of Diabetes and Endocrine Diseases, CSS Scientific Institute, San Giovanni Rotondo, Italy
Department of Clinical Sciences, ‘‘Sapienza’’ University of Rome, Rome, Italy *Corresponding author. Tel.: þ39 06 44160534; fax þ39 06 44160548. E-mail address: [email protected] 8 May 2007
www.elsevier.com/locate/nmcd
EDITORIAL
Heterogeneous effects of gene polymorphism on type 2 diabetes risk: Lesson from the PPARg2 Pro12Ala Although it is known that genes modulate the risk of type 2 diabetes, the real impact of most of them is still unknown [1]. The dissection of the genetic architecture of type 2 diabetes, as of many other human complex traits, has been difficult because it is polygenic (i.e. several genes, each with a modest effect, are involved) and heterogeneous (i.e. different genes are involved in different individuals). In addition, geneeenvironment and geneegene interactions are likely to be in the picture, making the scenario even more difficult to unravel. Geneeenvironment interaction implies a change in the direction or magnitude of the effect of a genetic variant according to environmental changes [2]. The ability to determine the precise mode of interaction is highly dependent on study features including sample size, how well genetic and non-genetic exposures are measured and the statistical tools employed. The traditional approach to test for interaction by using logistical regression modelling is limited by its inadequacies to deal with many factors. Indeed, as the number of genetic and environmental factors increases, so the number of possible interactions grows exponentially, resulting in a dramatic loss of statistical power. Discussing new statistical approaches aimed at unravelling the interactions between genes and environment is out of the scope of this editorial and here it is just enough to remind the reader that two different strategies namely, recursive partitioning and multifactor dimensionality reduction, have been proposed [3,4] and recently reviewed [5]. Since studies focusing on how genes interact with environmental factors in modulating the expression of specific phenotype are difficult to
design and carry out, most investigations in the field have attempted to catch the effect of single genes considered on their own. Among the several genetic polymorphisms so far described as diabetogenic, the Peroxisome Proliferator Activated Receptor-g2 (PPARg2) Pro12Ala is certainly one of the most well characterized [6]. PPARg2 is a transcription factor, expressed almost exclusively in adipose tissue which, by binding to Peroxisome Proliferator Responsive Element located in the promoter region of target genes, regulates adipocyte differentiation, lipid metabolism and insulin sensitivity [6]. Compared to the more frequent Pro12, the Ala12 variant has a reduced ability to trans-activate PPRE-containing promoters (i.e. a ‘‘loss of function’’ variation) [7]. Very intensive work has been carried out by many groups aimed at investigating the role of the Ala12 variant in modulating the risk of type 2 diabetes [6]. Although several studies have indicated a protective role of this variant, data obtained so far have been quite conflicting. We specifically addressed this issue by performing a comprehensive meta-analysis of all published studies for a total of 42,910 individuals [8]. Overall, Ala12 carriers showed a 19% risk reduction of type 2 diabetes, thus confirming data obtained in previous smaller meta-analyses [9e11]. Nonetheless, the association between Pro12Ala polymorphism and type 2 diabetes was extremely heterogeneous across all studies [8]. When the effect of covariates was investigated by meta-regression analysis, approximately 50% of the observed heterogeneity was accounted for by the mean BMI of controls in each study, with risk reduction being greater when BMI was lower [8]. Meta-regression of mean data only indicates
0939-4753/$ - see front matter ª 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.numecd.2007.07.001
630 ecological correlation and does not necessarily indicate causality. However, it is of note that our finding is in line with a recently published prospective study [12] showing that the protective effect of the Ala12 variant on the progression from impaired glucose tolerance to type 2 diabetes is greater when BMI is lower. The Ala12 variant has been repeatedly reported to be associated with increased BMI, a strong predictor itself of altered glucose homeostasis. It could therefore be argued that Ala12 carriers are protected from type 2 diabetes only when, because of environmental and/or additional genetic background, the detrimental effect of the Ala12 variant on obesity is not observable, allowing its beneficial effect on insulin sensitivity and lipid metabolism to end up in a reduced risk of type 2 diabetes. In the meta-analysis we performed, the association between Pro12Ala and type 2 diabetes was heterogeneous also when considering only studies carried out in Europe. In fact -according to a North to South gradient- risk reduction for Ala12 carriers was greater in Northern Europe (25%), barely significant in Central Europe (10%) and non-existent (0%) in Southern Europe [8]. In these circumstances, heterogeneity was not accounted for by BMI, thus suggesting that other environmental and genetic factors might have played a role. According to this hypothesis, in this issue of the journal Scacchi et al. [13] suggest that the different effect in different populations of the Pro12Ala polymorphism is partly due to different dietary habits. By analysing data from several (including some so far unpublished) populations, the authors confirm the overall protective role of the Ala12 variant against type 2 diabetes risk but also report that the different disease prevalence observed in populations with the same frequency of the Ala12 allele is paralleled by differences in the environmental risk factors, with particular emphasis on dietary fat intake. Indeed, single studies have shown that the Pro12Ala polymorphism interacts with diet in modulating insulin resistance, excess body weight and type 2 diabetes [14e17]. The scenario depicted by all previous and present [13] data clearly suggests that the Pro12Ala polymorphism may not be sufficient to significantly affect per se the risk of type 2 diabetes. Rather, it is likely to play a role by interacting with additional environmental and supposedly genetic factors, which may be different in different populations. If, after being specifically tested by large collaborative studies, this hypothesis turns out to be true, it would not only help a better understanding of the complex pathophysiology of type 2 diabetes but would also pave the way for translational
Editorial human investigation by providing new tools for early identification of subject subgroups at high risk for type 2 diabetes, and for tailoring specific treatments of diabetes and its devastating complications.
References [1] Almind K, Doria A, Kahn CR. Putting the genes for type II diabetes on the map. Nat Med 2001;7:277e9. [2] Cooper RS. Geneeenvironment interactions and the etiology of common complex disease. Ann Intern Med 2003;139: 437e40. [3] Young SS, GE N. Recursive partitioning analysis of complex disease pharmacogenetic studies. I. Motivation and overview. Pharmacogenomics 2005;6:65e75. [4] Moore JH. Computational analysis of geneegene interactions using multifactor dimensionality reduction. Expert Rev Mol Diagn 2004;4:795e803. [5] Cocozza S. Methodological aspects of the assessment of geneenutrient interactions at the population level. Nutr Metab Cardiovasc Dis 2007;17:82e8. [6] Stumvoll M, Haring H. The peroxisome proliferatoractivated receptor-gamma2 Pro12Ala polymorphism. Diabetes 2002;51:2341e7. [7] Deeb SS, Fajas L, Nemoto M, Pihlajamaki J, Mykkanen L, Kuusisto J, et al. A Pro12Ala substitution in PPARgamma2 associated with decreased receptor activity, lower body mass index and improved insulin sensitivity. Nat Genet 1998;20:284e7. [8] Ludovico O, Pellegrini F, Di Paola R, Minenna A, Mastroianno S, Cardellini M, et al. Type 2 diabetes risk given by PPARg2 Ala12 variant is heterogeneous across different populations. Obesity 2007;15:1e6. [9] Altshuler D, Hirschhorn JN, Klannemark M, Lindgren CM, Vohl MC, Nemesh J, et al. The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat Genet 2000;26:76e80. [10] Lohmueller KE, Pearce CL, Pike M, Lander ES, Hirschhorn JN. Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat Genet 2003;33:177e82. [11] Parikh H, Groop L. Candidate genes for type 2 diabetes. Rev Endocr Metab Disord 2004;5:151e76. [12] Florez JC, Jablonski KA, Sun MW, Bayley N, Kahn SE, Shamoon H, et al, Diabetes Prevention Program Research Group. Effects of the type 2 diabetes-associated PPARG P12A polymorphism on progression to diabetes and response to troglitazone. J Clin Endocrinol Metab 2007;92: 1502e9. [13] Scacchi R, Pinto A, Rickards O, Pacella A, De Stefano GF, Cannella C, et al. An analysis of peroxisome proliferatoractivated receptor gamma (PPAR-gamma2) Pro12Ala polymorphism distribution and prevalence of type 2 diabetes mellitus (T2DM) in world populations in relation to dietary habits. Nutr Metab Cardiovasc Dis 2007. [14] Luan J, Browne PO, Harding AH, Halsall DJ, O’Rahilly S, Chatterjee VK, et al. Evidence for geneenutrient interaction at the PPARgamma locus. Diabetes 2001;50:686e9. [15] Memisoglu A, Hu FB, Hankinson SE, Manson JE, De Vivo I, Willett WC, et al. Interaction between a peroxisome proliferator-activated receptor gamma gene polymorphism and dietary fat intake in relation to body mass. Hum Mol Genet 2003;12:2923e9.
Editorial
631
[16] Pisabarro RE, Sanguinetti C, Stoll M, Prendez D. High incidence of type 2 diabetes in peroxisome proliferator-activated receptor gamma2 Pro12Ala carriers exposed to a high chronic intake of trans fatty acids and saturated fatty acids. Diabetes Care 2004;27: 2251e2. [17] Vaccaro O, Lapice E, Monticelli A, Giacchetti M, Castaldo I, Galasso R, et al. Pro12Ala polymorphism of the PPARgamma2 locus modulates the relationship between energy intake and body weight in type 2 diabetic patients. Diabetes Care 2007 May;30:1156e61.
Vittorio Tassi Research laboratory of Diabetes and Endocrine Diseases, CSS Scientific Institute, San Giovanni Rotondo, Italy
Sabrina Prudente Research Laboratory of Diabetes and Endocrine Diseases, CSS Scientific Institute, San Giovanni Rotondo, Italy
CSS-Mendel Institute, Viale Regina Margherita 261, 00198 Rome, Italy
CSS-Mendel Institute, Viale Regina Margherita 261, 00198 Rome, Italy Ornella Ludovico Unit of Endocrinology, CSS Scientific Institute, San Giovanni Rotondo, Italy
Vincenzo Trischitta* Research laboratory of Diabetes and Endocrine Diseases, CSS Scientific Institute, San Giovanni Rotondo, Italy
Department of Clinical Sciences, ‘‘Sapienza’’ University of Rome, Rome, Italy *Corresponding author. Tel.: þ39 06 44160534; fax þ39 06 44160548. E-mail address: [email protected] 8 May 2007