Geneelifestyle interaction on risk of type 2 diabetes

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1 , Metabolism & Cardiovascular Diseases (2007) 17, 104e124 REVIEW Geneelifestyle interaction on risk of type 2 diabetes Paul W. Franks, Jose-Luis Mesa, Anne Helen Harding, Nicholas J. Wareham* Medical Research Council Epidemiology Unit, Elsie Widdowson Laboratories, 120 Fulbourn Road, Cambridge, CB1 9NL, UK Received 24 March 2006; received in revised form 4 April 2006; accepted 9 April 2006 KEYWORDS Geneelifestyle interaction; Diabetes Abstract: The descriptive epidemiology of type 2 diabetes suggests that genee lifestyle interactions are critical to the development of the condition. However, unravelling the molecular detail of these interactions is a complex task. The existing literature is based on small intervention studies or cross-sectional observational quantitative trait studies. Our systematic review of the literature identified some evidence of interactions, most notably for a common variant in the -gamma gene which appears to interact with the nature of dietary fat intake. Other interactions have been reported for adrenoceptors, uncoupling proteins, fatty acid binding proteins, apolipoproteins and lipoprotein lipase. There are, to date, no reports based on the ideal design which is a case-control nested within a cohort. To limit the likelihood of false discovery, such studies would need to be large and the search for interaction should be restricted to a priori biologically driven hypotheses. Additional designs that examine differential response to lifestyle change or test interaction in the context of quantitative trait studies would complement the nested case-control approach, but the emphasis here should be on precision of measurement of both phenotype and lifestyle behaviour. ª 2006 Elsevier B.V. All rights reserved. Introduction * Corresponding author. Tel.: þ ; fax: þ address: nick.wareham@mrc-epid.cam.ac.uk (N.J. Wareham). The descriptive epidemiology of type 2 diabetes and its pattern of inheritance provide strong evidence that the disorder originates from an interaction between genetic and lifestyle risk factors [1]. It is not the intention of this article /$ - see front matter ª 2006 Elsevier B.V. All rights reserved. doi: /j.numecd

2 Geneelifestyle interaction on risk of type 2 diabetes 105 to review this evidence since it has been described previously in multiple papers. A much more challenging and complex task is to unravel the basis for these interactions and to identify which genes and which genetic variants are responsible for the interaction with lifestyle behaviour. Thus in this paper, we have set out to describe the current literature on specific geneelifestyle interactions on the risk of type 2 diabetes. Our approach has been epidemiological and we have focused on observational and experimental studies in populations. We have put less emphasis on animal or molecular studies, but these obviously provide the justification for examining specific interactions or assist in the interpretation of the results, most particularly with respect to implications for causal inference, an issue to which we return in the discussion. Epidemiological designs for investigating geneelifestyle interaction on type 2 diabetes risk There is an accepted range of different designs that can be used to assess geneelifestyle interactions in population-based studies [1]. Some would argue that the strongest evidence comes from the examination of differential response to lifestyle intervention change in the context of a randomised controlled trial where individuals have been selected on the basis of a risk genotype. As this review will demonstrate, there are no studies of this type currently but this is an approach that could be taken in the future. An alternative approach is to investigate differential response to intervention in the context of a trial in which individuals are not selected by genotype. This can be an efficient and effective approach when risk genotypes are common, but can be underpowered when variants are less common or if multiple hypotheses are tested since trials tend to be relatively small and expensive to conduct. The selection of high-risk individuals for a trial increases the number of incident cases that emerge during the course of the trial and increases power. However, there is the obvious disadvantage that the selection by characteristics such as glucose intolerance may mean that there is covert selection by genotype, limiting the generalisability of the results. The final, and perhaps most important issue related to trial evidence, is that such studies are usually short-term and reflect the immediate metabolic response to lifestyle change. Whilst this is important for informing possible selection of individuals for targeted preventive advice, there is an alternative rationale for ing geneelifestyle interaction, which is to increase aetiological understanding. In this regard the focus is on how lifestyle factors over a lifetime increase the risk of development of diabetes and how that risk is modified by genetic factors. To that end, only an observational approach can address this issue with the ideal design being a casecontrol nested within a cohort. There are few examples of this and most are underpowered. The nested approach is required in order to diminish the likelihood of recall bias, which would affect a cross-sectional case-control since the report of historical physical activity and dietary intake is highly likely to be biased in individuals who know that they have type 2 diabetes. In the nested case-control, the recall of exposure predates the occurrence of the attribution of the disease label, removing the issue of recall bias whilst maintaining the efficiencies of the case-control approach. However, the design requirements are quite exacting as information about levels of physical activity and dietary intake needs to be assessed in a large cohort of people free of diabetes at baseline and followed up over time until some develop the condition. Since most researchers do not have access to such cohorts, alternative cross-sectional designs have been employed where the outcome is not diabetes itself, but a quantitative trait related to risk of the condition, either a measure of glucose tolerance or insulin resistance. In this article we include papers that have reported geneelifestyle interactions using any of these designs. Systematic review Our systematic review identified more than 100 epidemiological studies. Describing all of these studies is beyond the scope of this review. Therefore, we have restricted our discussion to the classes of genes that have been reported on at least three occasions. We conducted our literature review using the National Library of Medicine s medical publications database (PubMed), grey matter (e.g., PhD thesis bibliographies) and via ancestral searching of published and unpublished bibliographies. In PubMed the following search terms were complied and combined as necessary (i.e., genetic þ PA or nutrition). Limits were set to human studies for searches: Genetic exposure (genetic): gene* OR genotype OR SNP OR polymorphism OR autosome OR chromosome OR linkage. exposure (PA): exercise OR physical activity OR energy expenditure OR fitness OR sport. Dietary/al

3 106 P.W. Franks et al. exposure (nutrition): diet) OR nutrient) OR nutrition. Wherever possible, abstracts were obtained and reviewed for each to determine their relevance to this review. From those that were identified, the full manuscript was obtained and reviewed and relevant data extracted. Prevention Study, a randomised controlled trial of lifestyle intervention in people at high risk of type 2 diabetes. In this, Ala12 allele carriers were less likely to develop type 2 diabetes than Pro12 allele homozygotes during the course of the trial [13]. Peroxisome-proliferated activator receptor gamma (-gamma) -gamma mrna is expressed primarily in white adipocytes, placenta and macrophages. As is the case with other nuclear receptors, -gamma is constructed from a number of distinct functional domains. The transcription of -gamma is regulated largely through the availability and binding potential of specific ligands. The synthetic ligands of -gamma are the thiazolidinediones (TZDs), which are a powerful class of insulin sensitising drugs. The endogenous ligands are the prostaglandins, and the natural exogenous ligands include long-chain (>20 carbon atoms) polyunsaturated fatty acids (PUFA). -gamma is involved in cellular processes that include adipocytes proliferation and differentiation, insulin sensitisation through recruitment of metabolically active adipocytes, and inhibition of lipolysis. The proline to alanine substitution at codon 12 (Pro12Ala) of the -gamma gene is believed to alter transcriptional activity owing to its location in the functional binding domain [2], and has been associated with risk of type 2 diabetes and its intermediate traits [3]. The initial association studies with type 2 diabetes found a risk reduction of approximately 20% in carriers of the minor Ala allele by comparison with Pro homozygotes [4]. Although a number of other -gamma variants have been studied [5], most epidemiological studies have focused on the Pro12Ala variant. Indeed, in studies of geneelifestyle interaction, no other variants have been considered to date. As shown in Table 1, several [6e8], but not all [3], studies have reported evidence for interaction between Pro12Ala and the nature of dietary fat intake on insulin resistance, BMI, or type 2 diabetes. It has also been suggested that physical activity and dietary fatty acids act synergistically with Pro12Ala to modulate insulin levels [9]. Several intervention studies have reported greater improvements in glucose tolerance and insulin levels in Ala12 carriers following 3e6 months of structured exercise training by comparison with Pro12 homozygotes [10e12]. These observations are supported by data from the Finnish Diabetes b-adrenergic receptors (ADRB) b-adrenergic receptors (ADRB) are expressed in white adipose tissue and bind the endogenous catecholamines epinephrine and norepinephrine. ADRBs signal to the interior of cells via the stimulatory guanine nucleotide-binding protein 309. Activation of all three ADRB isoforms (b1-, b2-, b3-) stimulates lipolysis, while inhibition of the ADRB2 reduces lipolysis. The ADRB2 gene contains a short open reading frame located 102 base pairs upstream of the receptor coding block in the 5 0 leader cistron which encodes a 19 amino acid peptide that inhibits the cellular expression of ADRB2 by obstructing the translation of mrna. Several common polymorphisms within the open reading frame have been described, including two common variants in the extracellular domain of the receptor (Gly16Arg and Gln27Glu). ADRB3 regulates both catecholamine-stimulated thermogenesis in brown adipose tissue and lipolysis in white adipose tissue, especially in visceral sites. A tryptophan to arginine (Trp64Arg) missense mutation identified in the ADRB3 gene alters the conformation of the first intracellular loop and the migration of the receptor to the cell surface, resulting in a significant decrease in receptor sensitivity [14,15]. Studies examining interaction between variants in the ADRB isoforms and lifestyle factors are shown in Table 2. The initial investigation of geneelifestyle interaction at the ADRB2 locus and diabetes-related traits was reported by Meirhaeghe et al. [16]. In this, interaction between self-report physical activity and the Gln27Glu polymorphism was observed for anthropometric measures of obesity in French men. In a subsequent using objective measures of physical activity, Meirhaeghe et al. [17] reported interaction between Gly16Arg on plasma NEFA levels in British men and women. Martinez et al. [18] reported evidence for interaction on BMI between the Gln27Glu polymorphism (ADRB2) and carbohydrate intake in Spanish adults, whereas Corbalan et al. [19] reported data showing interaction between Gln27Glu and physical activity on weight loss. Two intervention studies have reported evidence that the Gln27Glu variant may

4 Table 1 Study Poirier et al., 2000 [3] Luan et al., 2001 [6] Robitaille et al., 2003 [8] Pisabarro et al., 2004 [64] case-control Franks et al., 2004 [9] Nemoto et al., 2002 [2] Studies of gene-lifestyle interaction on type 2 diabetes and related traits: Peroxisome proliferator-activated receptor genes Study Exposure Outcome Polymorphism Main results population yr Healthy 592 individuals (259 men and 333 women) yr Healthy 720 related individuals (313 men and 407 women) yr Healthy 56 individuals (16 men and 140 women) 21e62 yr Mix of obese and healthy 506 individuals yr Non-diabetic 105 Native Japanese 145 second generation Japanese American (Nisei) 54e92 yr 151 with type 2 diabetes, 99 with NGT P:S ratio (food frequency P:S ratio (food frequency Total and saturated dietary fat intake (3-d food records) Trans and saturated fatty acids intake (food frequency Heart rate monitored physical activity and P:S ratio (food frequency Westernised lifestyle Fasting and 2 hour glucose and AUC insulin Fasting insulin Glucose Diabetes Fasting insulin Fasting insulin SNP: Pro12Ala 11: : :0.02 SNP: Pro12Ala 11: þ 22:0.21 SNP: Pro12Ala 11: : :0.02 SNP: Pro12Ala 11: þ 22:0.21 SNP: Pro12Ala 11: : :0.01 SNP: Pro12Ala Genotype frequency 11: : :0.004 No HWE test reported No significant interaction between genotype and P:S ratio on OGTT glucose or insulin AUCs. Fasting insulin was inversely related to P: S ratio in Ala12 carriers, but not in Pro12 homozygotes (interaction term P < 0.01). Plasma glucose levels were positively related to saturated fat intake in Pro12 homozygotes, but not in Ala12 carriers (genotype saturated fat interaction P ¼ 0.03). Intakes of trans and saturated fatty acids were positively related to type 2 diabetes only in Ala carriers (P < 0.01). No test for interaction. Among Ala allele carriers, but not Pro homozygotes, there was interaction between physical activity and P:S ratio on fasting insulin (P ¼ 0.038). Nisei Pro12 homozygotes with diabetes had higher fasting insulin than native Japanese Pro12 homozygotes with diabetes (P ¼ 0.04). Fasting insulin was similar for Nisei and native Japanese Ala12 carriers with diabetes. No test for interaction. (continued on next page) Geneelifestyle interaction on risk of type 2 diabetes 107

5 Table 1 (continued) Study Study population Memisoglu et al., 2003 [7] Kahara et al., 2003 [10] Weiss et al., 2005 [11] Adamo et al., 2005 [12] Lindi et al., 2002 [13] Randomized controlled trial Lindi et al., 2003 [65] Randomized controlled trial 2141 women 56 yr 123 individuals 21e69 yr Healthy Japanese 72 individuals 50e75 yr Healthy 139 individuals 40e70 yr Diabetic patients 490 individuals 49 9yr Overweight with IGT 150 individuals (76 men and 74 women) 49 8 yr Healthy Exposure Outcome Polymorphism Main results Dietary fat intake (food frequency 3-month aerobic exercise training 6-month supervised endurance exercise training 3-month supervised exercise (resistance and aerobic) training Diet and exercise intervention (Finnish Diabetes Prevention Study) with 3 yr follow-up n-3 fatty acid supplementation: fish oil capsules (3.6 g/ d ¼ 2.4 g EPA þ DHA) compared with placebo olive oil capsules for 3 months BMI IRI and HOMA-IR AUC insulin Glucose Diabetes Fasting glucose and insulin SNP: Pro12Ala 11: þ 22:0.24 SNP: Pro12Ala Genotype frequency 11: þ 22:0.05 No HWE test reported SNP: Pro12Ala Genotype frequency 11: :0.16 SNP: Pro12Ala Genotype frequency 11: :0.16 SNP: Pro12Ala Genotype frequency 11: : :0.03 SNP: Pro12Ala Genotype frequency 11: : :0.03 Intake of total fat was positively associated with BMI in Pro/Pro homozygotes but not in Ala12 carriers (interaction term P ¼ 0.003). MUFA was inversely associated with BMI in Ala12 carriers but not in Pro/Pro homozygotes (interaction term: P ¼ 0.003). Ala carriers, compared with Pro homozygotes, had a significant decrease in IRI and HOMA-IR after exercise (P < 0.05). No test for interaction. Endurance training resulted in a significantly greater improvement in insulin AUC in Pro12Ala heterozygous men as compared with Pro12 homozygous men (interaction term P ¼ 0.001). Exercise training induced a significantly greater improvement in glycaemia in Ala carriers, compared to Pro/Pro individuals (P < 0.05). No test for interaction None of the Ala12 homozygotes in the treatment group (n ¼ 6) developed diabetes while 3/7 of the Ala12 homozygotes in the control group developed diabetes. No test for interaction No evidence of different effects of n-3 supplementation by genotype on fasting glucose or insulin. Greater decrease in triacylglycerols in Ala carriers after n-3 supplementation compared to Pro/Pro. No test for interaction 108 P.W. Franks et al.

6 Robitaille et al., 2004 [66] Tai et al., 2005 [67] Paradis et al., 2005 [68] 632 men yr Healthy 2106 individuals (1003 men and 1103 women) yr Healthy 20 men yr Healthy Dietary fat and saturated fat intake (food frequency PUFA intake (food frequency First 4-wk period ingestion of low P:S diet (0.3). Next 4-wk a high P:S diet (1.0) Waist circumference Triglyceride Total cholesterol SNP: L162V Genotype frequency 11: þ 22:0.20 SNP: L162V 11: þ 22:0.135 SNP: L162V Genotype frequency L homozygotes V carriers No HWE test reported Fat or saturated fat intake was related to waist circumference in 162L homozygotes, but not in 162V carriers (interaction term P < 0.01). 162V carriers, but not 162L homozygotes, had lower plasma TG (interaction term P ¼ 0.048) and apociii (interaction term P < 0.01) concentrations when consuming a high PUFA diet. 162V carriers, but not 162L homozygotes, had lower plasma total cholesterol and apoa1 when consuming a high P:S ratio (interaction term P < 0.04). No interaction was observed in fasting insulin or glucose Abbreviations (apply to Tables 1e4): AUC, area under the curve; BMI, body mass index; CAD, coronary heart disease; CHO, carbohydrate; HDL-C, high-density lipoprotein cholesterol; HL, hepatic lipase; HWE, HardyeWeinberg equilibrium; HOMA-IR, homeostasis model of insulin resistance; IRI, insulin resistance index; IGT, impaired glucose tolerance; LDL, low-density lipoprotein; MUFA, monounsaturated fatty acid; NEFA, non-esterified fatty acids; NGT, normal glucose tolerance; OGTT, oral glucose tolerance test; PUFA, polyunsaturated fatty acid; P:S ratio, polyunsaturated to saturated fatty acid ratio; QT, quantitative trait; SFA, saturated fatty acid; S i, insulin sensitivity; SNP, single nucleotide polymorphism; SSPG, steadystate plasma glucose; TG, triglyceride. Geneelifestyle interaction on risk of type 2 diabetes 109

7 Table 2 Studies of gene-lifestyle interaction on type 2 diabetes and related traits: Adrenergic receptor genes Study Study population Exposure Outcome Polymorphism Main results Corbalan et al., 2002 [19] case-control Martinez et al., 2003 [18] case-control Meirhaeghe et al., 2001 [17] Macho-Azcarate et al., 2002 [21] Cross-over intervention Ukkola et al., 2001 [20] Tchernof et al., 2000 [24] 252 women yr Obese (BMI>30 kg/m 2 ) and control (BMI < 25 kg/m 2 ) 247 women yr Obese (BMI>30 kg/m 2 ) and control (BMI < 25 kg/m 2 ) 604 individuals without known diabetes 40e65 yr 8 obese Glu27Glu women 7 obese Gln27Gln women 24 men 21 2yr Healthy, monozygotic Caucasian twins 24 women yr Obese postmenopausal (Questionnaire and interview) Habitual carbohydrate intake (food frequency (Objectively assessed) 1-h treadmill exercise Diet containing 4.2 MJ per day above measured baseline energy intake, 6 d per week for 100 d. Diet-only weight reduction programme (1200 kcal/d) for an average follow-up period of months. Obesity Obesity NEFA levels Triglyceride AUC insulin Glucose disposal ADRB2 SNP: Gln27Glu : 11 ¼ ¼ 0.62 In HWE ADRB2 SNP: Gln27Glu : 11 ¼ ¼ 0.62 In HWE ADRB2 SNP: Gly16Arg : 11: : : 0.12 ADRB2 SNP: Gln27Glu ADRB2 SNP: Gln27Glu Gln27Gln: 10 Glu27: 14 ADRB3 SNP: Trp64Arg 11: :0.46 A statistically significant interaction between recreational energy expenditure and the 27Glu allele was demonstrated (interaction term P ¼ 0.005) Females with the Glu27 variant and a higher CHO intake (>49% energy) had a higher obesity risk (OR ¼ 2.56, interaction term P ¼ 0.058) The effect of the Arg16Arg genotype on the suppression of NEFA levels was modified by physical activity level (interaction term P < 0.05) Plasma triglycerides (P ¼ 0.001) and serum insulin (P < 0.05) remained higher in the Glu27Glu group vs. the Gln27Gln group. No gene exercise interactions. The Glu27 carriers experienced a greater increase in insulin AUC during the OGTT (P < 0.01) than the Gln27 homozygotes. No test for interaction. Trp64 homozygotes and Arg64 carriers had similar improvements in glucose disposal and insulin levels during the clamp. 110 P.W. Franks et al.

8 Kim et al., 2004 [22] Ukkola and Bouchard, 2004 [69] Kahara et al., 2002 [23] Shiwaku et al., 2003 [25] Salopuro et al., 2004 [26] Randomized controlled trial Siitonen et al., 2004 [70] Randomized controlled trial 70 men yr Overweight-obese patients with CAD 24 men 21 2yr Healthy, monozygotic Caucasian twins 106 individuals 21e69 yr Healthy Japanese 85 women yr Healthy Japanese 469 individuals 55 7 yr Overweight with IGT 506 individuals 55 7yr Overweight with IGT 12-wk reduction of energy intake from 2263 kcal/d to 1963 kcal/d Diet containing 4.2 MJ per day above measured baseline energy intake, 6 d per week for 100 d. 3-month aerobic exercise training Diet and exercise 3-month diet and exercise intervention Diet and exercise intervention (Finnish Diabetes Prevention Study) with 3 yr follow-up Diet and exercise intervention (Finnish Diabetes Prevention Study) with 3 yr follow-up. AUC glucose Fasting insulin, AUC glucose and insulin Fasting glucose BMI, fasting glucose and insulin Diabetes Diabetes ADRB3 SNP: Trp64Arg 11: : 0.29 ADRB3 SNP: Trp64Arg ADRB3 SNP: Trp64Arg 11: : :0.06 No HWE test reported ADRB3 SNP: Trp64Arg 11: : 0.20 ADRB3 SNP: Trp64Arg Genotype frequency 11: : 0.14 No HWE test reported ADRB2 SNP: 12Glu9 11: : :0.20 OGTT glucose AUC decreased significantly 6.9% and OGTT insulin AUC tended to decrease only in Trp homozygotes. No test for interaction No evidence of differences in response to overfeeding of fasting plasma insulin, OGTT glycaemic and insulin areas. Fasting plasma glucose only decreased significantly in Trp carriers after the exercise training (P < 0.05). No test for interaction Significant reductions were found in body weight, BMI, waist circumference, and blood pressure in wild type but not in Trp64Arg mutants. No gene intervention interaction in relation to insulin, glucose or HOMA-IR. No test for interaction No significant gene environment interaction in relation to type 2 diabetes. The Glu9 allele was a significant predictor of type 2 diabetes in the control group, but not in the intervention group (interaction term P ¼ 0.003). Geneelifestyle interaction on risk of type 2 diabetes 111

9 112 P.W. Franks et al. modify the effects of nutrients and physical activity on insulin sensitivity [20]. By contrast, Macho- Azcarate et al. [21] did not find evidence for geneelifestyle interaction at this locus. studies of ADRB3 variants have also yielded inconsistent results. Some studies of dietary [22] and physical activity interventions [23] have reported reductions in fasting plasma glucose and insulin in Trp64 carriers, but not in Arg64 homozygotes, although no formal tests for interaction were undertaken in these studies. By contrast, no support for geneelifestyle interaction on type 2 diabetes-related traits at the Trp64Arg locus was found in a number of other studies [20,24e26]. Uncoupling proteins (UCP) Uncoupling proteins (UCPs) comprise a complex of three homologous isoforms (UCP 1, 2, 3) that inhibit the synthesis of ATP following oxidative phosphorylation by dissipating energy as heat and by reducing the mitochondrial membrane potential. UCP1 is solely expressed in brown adipose tissue, which is of low abundance in humans, whereas UCP2 and UCP3 are expressed predominantly in skeletal muscle. Because of their role in thermogenesis, the UCP class of genes have been proposed as plausible candidates for obesity and type 2 diabetes [27]. Table 3 shows the studies that have assessed the interaction between lifestyle exposures and UCP gene variants. In a case-control of 401 morbidly obese and 231 normal-weight French, Otabe and colleagues reported associations between a variant at the UCP3 locus (e55 C/T) and obesity [28]. When stratified by genotype, the authors observed association between selfreported physical activity and BMI in C allele homozygotes, but no significant association was observed in carriers of the minor T allele. The authors interpreted these findings as evidence of geneelifestyle interaction, although no formal statistical test to determine this was reported. A subsequent prospective in Danish found no evidence for a genetic main effect or interaction with physical activity at UCP2 or UCP3 (including the e55 C/T variant) for weight change [29]. Two intervention studies have been reported that assessed interactions between lifestyle factors and UCP gene variants [22,23]. In the first, Kahara et al. [23] reported decreased fasting plasma glucose levels following exercise intervention only in UCP1 A-3826G heterozygotes. No tests for interaction or Hardy-Weinberg equilibrium were reported. In studies of UCP3, no interaction was observed between calorie restriction and the UCP3 e55c/t polymorphism on insulin sensitivity [22]. Only one randomised controlled trial of the UCP genes has been reported [26]. In this, interactions between lifestyle intervention and a UCP1 polymorphism (A-3826G) on type 2 diabetes and related metabolic traits were reported. However, because UCP1 is expressed solely in brown adipose tissue, it is a particularly poor candidate gene for human disease. Thus, it is difficult to determine the merit of studies that have tested the effect of this variant in humans. Possible explanations for apparent associations between variants at this locus and disease could be long range LD with variants in other genes, that UCP1 is active in other tissues and evidence is yet to emerge to demonstrate this, or that the reported associations and interactions are false positive. Lipid metabolism genes Polymorphisms in numerous lipid metabolism genes have been related with variation in lipid and insulin levels. Because these genes do not fall into a specific class, the following section describes the epidemiological studies that pertain to geneelifestyle interactions on lipid-related phenotypes (Table 4). Hepatic lipase gene The hepatic lipase gene (LIPC ) encodes a liverspecific enzyme that controls lipoprotein metabolism in the liver. LIPC hydrolyses triglycerides and acts as a ligand facilitator for receptor-mediated uptake of lipoproteins. Because intra-hepatic lipids are associated with insulin resistance in humans [30], LIPC has been proposed as a candidate gene for type 2 diabetes and associated traits. Several cross-sectional interaction studies have been reported for variants in LIPC (Table 4). In a of over 2000 middle-aged men and women, Ordovas et al reported a significant interaction between the C-514T genotype and dietary fat intake on HDL cholesterol, such that the association between fat intake and HDL levels was weaker in individuals homozygous for the e514t genotype than in e514c carriers. A second in more than 2,000 Asian adults found a similar interaction at this locus with fat intake on triglyceride levels [31], whilst a third [32] reported stronger associations between saturated fat (SFA) intake and HDL cholesterol levels in T allele carriers compared with C allele homozygotes.

10 Table 3 Studies of gene-lifestyle interaction on type 2 diabetes and related traits: Uncoupling protein genes Study Study population Exposure Outcome Polymorphism Main results Kahara et al., 2002 [23] Salopuro et al., 2004 [26] Randomized controlled trial Otabe et al., 2000 [28] casecontrol Berentzen et al., 2005 [29] Prospective cohort Kim et al., 2004 [22] 106 individuals 21e 69 yr Healthy Japanese 469 individuals 55 7 yr Overweight with IGT 231 healthy individuals 401 morbidly obese 568 obese men 717 controls 224 individuals (114 men and 110 women) yr Obeseoverweight with metabolic syndrome or CAD 3-month aerobic exercise training Diet and exercise intervention (Finnish Diabetes Prevention Study) with 3 yr follow-up. ( (self-administered Calorie restriction ( 300 kcal/day) program for 12 wk Glucose Diabetes BMI Change in BMI AUC glucose and insulin UCP1 SNP: A-3826G 11: : : 0.26 No HWE test reported UCP1 SNP: A-3826G 11: þ 22:0.40 UCP3 SNP: -55C/T 11: : 35 22: 0.05 UCP3 SNP: -55C/T 11: : 38 22: 0.07 UCP3 SNP: -55C/T : 11: þ 22:0.54 After the exercise training, plasma glucose levels decreased only in AG heterozygotes (P < 0.01). No test for interaction The A-3826G polymorphism was not associated to a higher risk of type 2 diabetes. No gene group interaction was observed. In morbidly obese individuals with the CC genotype, BMI was inversely associated with physical activity (P ¼ 0.015). No test for interaction No interaction between physical activity and UCP variants in relation to changes in BMI. Subjects decreased the OGTT glycaemic and insulin areas in both wild and mutated genotypes. No gene nutrient interaction. Geneelifestyle interaction on risk of type 2 diabetes 113

11 Table 4 Studies of gene-lifestyle interaction on type 2 diabetes and related traits: lipid regulating genes Study Study population Exposure Outcome Polymorphism Main results Ordovas et al., 2002 [71] Tai et al., 2003 [31] Zhang et al., 2005 [32] Bos et al., 2005 [72] Hokanson et al., 2003 [33] Prospective cohort 2130 individuals Predominantly white subjects yr Healthy 2170 individuals 1324 Chinese 471 Malays 375 Indians yr Healthy 706 US men with type 2 diabetes 40e75 yr 429 individuals 70 6yr Caucasian 966 individuals yr Dietary fat intake (food frequency Dietary fat intake (food frequency Dietary fat intake (food frequency Dietary fat intake (food frequency (Questionnaire) HDL-C Triglyceride HDL-C Hepatic lipase CHD risk LIPC SNP: C-514T 11: : :0.03 LIPC SNP: C-514T Chinese 11: : :0.13 Malays 11: : :0.17 Indians 11: : :0.07 LIPC SNP: C-514T 11: : 0.37 LIPC SNP: C-480T 11: : :0.03 LIPC SNP: C-480T 11: : :0.11 HDL-C concentrations were lowest among individuals with the TT genotype and total fat intakes 30%, and no differences were observed between CC and CT individuals (interaction term P < 0.001). TT homozygotes showed higher TG concentrations only when fat intake supplied >30% of total energy (interaction gene fat intake P ¼ 0.001). The T allele was associated with higher HDL-C concentrations only in men who had higher SFA intake (interaction term P ¼ 0.003). Total dietary fat was positively associated with HL activity. This association was stronger in subjects with the T allele than in those with the CC genotype (interaction gene fat intake P ¼ 0.04). Vigorous physical activity did not alter the CHD risk in individuals with the C allele. However, a reduced risk of CHD due to vigorous physical activity was found for individuals with the TT genotype (interaction term P ¼ 0.003). 114 P.W. Franks et al.

12 Teran-Garcia et al., 2005 [34] Gomez et al., 2005 [35] Cross-over intervention Todorova et al., 2004 [36] Randomized controlled trial Zacharova et al., 2005 [73] Randomized controlled trial 443 white individuals and 219 black individuals Non-diabetic 59 individuals (30 men and 29 women) yr Healthy 490 individuals 55 7yr Overweight with IGT 770 individuals with IGT 55 8yr Individuals from several populations: Canada, Germany, Austria, Finland, Sweden, Norway, Denmark, Israel and Spain 20-wk aerobic exercise training program 3 diets 4-wk each. SFA diet, CHO diet, and MUFA (Mediterranean) diet. Diet and exercise intervention (Finnish Diabetes Prevention Study) with 3 yr follow-up. Drug administration Randomised controlled trial of acarbose administration with 3 yr followup. Insulin sensitivity Glucose Diabetes Diabetes LIPC SNP: C-514T Whites 11: : : 0.04 Blacks 11: : : 0.23 LIPC SNP: C-514T LIPC SNP: G-250A 11: : :0.07 LIPC SNP: G-250A 11: : : 0.06 Training-induced improvements in S i both in blacks and whites were greater in CC homozygotes than in the TT genotype (P ¼ and P ¼ 0.002, respectively). No test for interaction. SSPG was significantly higher in men, but not women, carriers of the T allele after the consumption of the SFA diet than after the CHO diet or the Mediterranean diet. In the control group, 23.0% of the subjects with the G-250G genotype and 19.4% of the subjects with the - 250A allele converted to diabetes (P ¼ 0.507). In the intervention group, 13.0% of the subjects with the G-250G genotype and 1.0% of the subjects with the -250A allele converted to diabetes (P ¼ 0.001). Significant interaction between the genotype and the group (P ¼ 0.024). The A-250A genotype was a predictor of conversion to type 2 diabetes only in the placebo group (P ¼ 0.032). The genotype acarbose interaction was P ¼ (continued on next page) Geneelifestyle interaction on risk of type 2 diabetes 115

13 Table 4 (continued) Study Study population Exposure Outcome Polymorphism Main results Pratley et al., 2000 [41] Agren et al., 2001 [74] Dworatzek et al., 2004 [42] Cross-over intervention Marin et al., 2005 [43] Cross-over intervention Brown et al., 2003 [46] Salas et al., 1998 [48] Cross-over intervention 9 Thr54 homozygotes 9 Ala54 homozygotes Healthy Pima Indians 8 Thr54 homozygotes 7 Ala54 homozygotes Healthy 22 individuals 30 2yr Healthy 59 individuals 21 2yr Healthy 182 men and 154 women yr Mestizo (a mixture of Caucasian and Amerindian ethnic groups) 41 men 21 2yr Healthy Mixed meal (35% of daily energy requirements, 50 g of fat) and a high fat challenge (1362 kcal, 129 g of fat). Oral fat loading test (52 g/ 70 kg body wt.) Ingestion of 3 different fats (butter, safflower oil, and olive oil). 3 diets 4-wk each. SFA diet, CHO diet, and MUFA (Mediterranean) diet. SFA intake (semi-quantitative food-frequency Three 28-d diets: high SFA diet, low fat diet, and high MUFA diet. Insulin and glucose levels Post-load insulin levels AUC glucose and insulin Glucose Cholesterol Post-load insulin FABP2 SNP: Ala54Thr FABP2 SNP: Ala54Thr FABP2 SNP: Ala54Thr 11: : :0.09 FABP2 SNP: Ala54Thr 11: : : 0.07 APOC3 SNPs: T-455C and - 625Tdel (both in linkage disequilibrium each other) APOC3 SNP: SstI polymorphism 11: : 0.32 Insulin responses to the test meals tended to be higher in Thr54 homozygotes. Glucose and TG responses were not different. No evidence of gene diet interaction. The responses of chylomicron fatty acids correlated positively with postprandial insulin response in the Thr54 homozygotes and inversely in Ala54 homozygotes. No test for interaction. Chylomicron cholesterol values were higher in Thr54 carriers than in Ala54 homozygotes after olive oil administration (gene diet interaction P < 0.05). No gene diet interaction in insulin or glucose AUCs. SSPG was significantly higher in Ala54Thr subjects after the SFA diet than after the CHO diet or the Mediterranean diet (interaction term P ¼ 0.05). In homozygotes for the -455T-625T alleles, but not APOC3-455C-625del alleles, saturated fat intake was associated with a 13% increase in total cholesterol and a 20% increase in LDL cholesterol (interaction term P < 0.01). Significantly higher 2-hr insulin post- OGTT in S2 allele carriers than in S1 homozygotes following a high saturated fat diet (P ¼ 0.012). No gene nutrient interaction (P ¼ 0.642). 116 P.W. Franks et al.

14 Perez-Jimenez et al., 2002 [47] Cross-over intervention Corella et al., 2001 [53] Campos et al., [51] Bernstein et al., 2002 [52] Hagberg et al., 1999 [54] Moreno et al., 2004a [75] Cross-over intervention 59 individuals (30 men and 29 women) yr Healthy 396 women and 513 men yr 420 healthy Costa Ricans 1708 individuals 35e74 yr 51 men 45e80 yr Healthy 84 individuals (58 men and 26 women) yr Healthy Caucasian A 28 d high-sfa diet intervention (self-administered SFA intake (semi-quantitative foodfrequency (Questionnaire) 9-month endurance exercise Three diets for 4 wk each: a SFA-rich diet (38% fat, 20% SFA), followed by a CHO-rich diet (30% fat, 55% CHO) or a MUFA-rich diet (38% fat, 22% MUFA) Glucose HDL-C HDL-C HDL-C LDL APOC3 SNP: SstI polymorphism 11: : 0.39 APOE 32, 33, 34 isoforms E3/E3: 0.76 E4/E3: 0.13 E2/E3: 0.10 APOE 32, 33, 34 isoforms E3/E3:0.67 E4/E3:0.18 E2/E3:0.12 APOE 32, 33, 34 isoforms E3/E3:0.65 E4/E3:0.23 E2/E3:0.12 APOE 32, 33, 34 isoforms E3/E3:0.79 E4/E3:0.09 E2/E3:0.12 Overall, no evidence of difference in SSPG levels between carriers and noncarriers of S2 allele. Sub-group analysis indicated that in men only, the S2 allele was associated with increased SSPG levels. No test for interaction. HDL-C levels differed across APOE genotypes in sedentary men, with the E2 carriers showing higher levels than E4 carriers. Conversely, in active men, it was observed the opposite effect, with E4 carriers showing the highest HDL-C concentrations (interaction term P < 0.001). Increased % high-intensity activity had greater protective effects in the APOE4 group regarding HDL-C compared with either the APOE2 or APOE3 (interaction P < 0.05). The increases in plasma HDL-C and HDL2-C levels remained greater in APO E2 versus E3 and E4 men, after adjusting for body weight changes. No test for interaction. After the CHO diet, a significant increase in LDL particle size was noted with respect to the MUFA diet in APOE 4/3 subjects, whereas a significant decrease was observed in the APOE 3/ 3 individuals (interaction term P ¼ 0.035). (continued on next page) Geneelifestyle interaction on risk of type 2 diabetes 117

15 Table 4 (continued) Study Study population Exposure Outcome Polymorphism Main results Moreno et al., 2004b [76] Cross-over intervention Moreno et al., 2005 [77] Cross-over intervention Boer et al., 1999 [59] Senti et al., 2001 [60] Garenc et al., 2001 [61] 55 men yr Healthy 43 individuals (22 men and 21 women) yr Healthy 379 individuals 20e59 yr 520 men 25e74 yr Healthy 741 black and white individuals Non-diabetic Three diets for 4 wk each: a SFA-rich diet (38% fat, 20% SFA), followed by a CHO-rich diet (30% fat, 55% CHO) or a MUFA-rich diet (38% fat, 22% MUFA) Three diets for 4 wk each: a SFA-rich diet (38% fat, 20% SFA), followed by a CHO-rich diet (30% fat, 55% CHO) or a MUFA-rich diet (38% fat, 22% MUFA) (Questionnaire) (Questionnaire) 20-wk aerobic exercise training program HDL and LDL- C Total cholesterol HDL and TG BMI APOE SNP: -219G/T polymorphism in APOE3/E3 subjects 11: : :0.18 APOE SNP: -219G/T polymorphism in APOE3/E3 subjects 11: : : 0.23 LPL D9N mutation Non-carriers 96% Carriers 4% LPL HindIII polymorphism H H 0.10 H H H+H LPL SNP: S447X Blacks 11: :0.15 Whites 11: :0.18 A significant genotype diet interaction effect was observed on apo B, HDL-C, and LDL concentrations. Only carriers of the -219G allele improved S i when MUFA- or CHO-rich diets are consumed instead of a SFArich diet (interaction term P ¼ 0.039). Physically inactive D9N carriers had higher total cholesterol and apo B levels and lower HDL-C levels compared to non-carriers. This was not the case for physically active D9N carriers. No test for interaction. No interaction was observed between HindIII polymorphism and physical activity regarding HDL-C or TG levels. White women, but not men, carrying the X447 allele exhibited greater reductions of body mass index, fat mass, and percent body fat; in black women, the carriers exhibited a greater reduction of abdominal visceral fat and a greater increase in post-heparin LPL activity. No test for interaction. 118 P.W. Franks et al.

16 Geneelifestyle interaction on risk of type 2 diabetes 119 In the only prospective interaction at the LIPC locus (C-480T), an inverse association between physical activity and CHD risk was reported in T allele homozygotes but not in C allele carriers [33]. Four intervention studies have examined whether the effect of exercise or diet on metabolic phenotypes is dependent on LIPC genotype. In one report using data from the HERITAGE family, a 20-week exercise intervention program, improvements in insulin sensitivity were observed only in e514c allele homozygotes [34]. A second reported increased steady-state plasma glucose levels following intervention with a high SFA diet in male carriers of the e514t allele [35]. Although no effect of fat intake on steady-state plasma glucose levels was observed in C allele homozygotes, these observations were not supported by formal tests of interaction. In the Finnish Diabetes Prevention Study, a randomised controlled trial of lifestyle intervention in people with impaired glucose tolerance, Todorova et al. [36] reported that the G-250A polymorphism modified the risk of developing type 2 diabetes, such that carriers of the e250a allele derived the greatest risk reduction. Fatty acid binding protein 2 The fatty acid-binding protein 2 (FABP2) gene encodes the intestinal FABP protein, which is involved in fat absorption and transportation. A common amino-acid substitution (Ala54/Thr54) at codon 54 has been reported in several populations, with the frequency of the Thr54 allelic ranging between 20e40%. This is the only genotype at the FABP2 locus to have been repeatedly studied in the context of gene-nutrient interaction [37]. Functional studies have shown that the in vitro binding affinity of the protein for long-chain fatty acids is roughly two-fold higher in Thr54 expressing cells by comparison with cells expressing the recumbent Ala54 protein [38], and the rate of fatty acid transport across cells expressing Thr54 is increased [39]. In early epidemiological studies of Pima Indians, Baier et al. [38] reported that individuals carrying the Thr54 allele had higher fasting plasma insulin concentrations, lower insulin-stimulated glucose uptake rates, higher insulin response to oral glucose and a mixed meal, and higher fat oxidation rates compared with Pimas who were homozygous at Ala54. These observations have been supported by subsequent studies [40]. To our knowledge there are no cross-sectional studies which examined interactions between FABP2 variants and lifestyle factors. Several intervention studies have been reported that explored whether variants at the FABP2 locus modifies the effect of diet or exercise on metabolic traits [41e43], although these have all been physiological studies in small samples. The largest intervention of FABP2 genotypes was undertaken by Marin et al. [43] in which 59 individuals were fed a high SFA diet (38% of energy from fat/20% of energy from SFAs) and subsequently randomised to either a low-fat and high-carbohydrate diet (28% of energy from fat/<10% of energy from SFAs) and a highmonounsaturated fatty acid (MUFA) diet (38% of energy from fat/22% of energy from MUFAs). On completion of the diet, volunteers crossed over to receive the alternative diet. Each diet phase lasted 4 weeks. Although differences in steady-state plasma glucose levels between diets were observed for Thr54 allele carriers (n ¼ 31), no differences were observed in Ala54 homozygotes (n ¼ 28). The test of diet x genotype interaction was of borderline statistical significance where steady-state plasma glucose was the outcome; where NEFA was the outcome, the interaction term reached a level of conventional statistical significance (P ¼ 0.015). Many other outcomes were also tested for interaction that were not significant. No adjustment for multiple permutation testing was made. Apolipoproteins Apolipoprotein ApoC-III a very low density lipoprotein (VLDL) protein synthesized in liver and intestine, and consists of 79 amino acids. ApoCIII inhibits lipoprotein lipase and hepatic clearance of triglyceride-rich lipoproteins in vitro. Thus, elevations in ApoCIII result in increased triglyceride levels. Several common polymorphisms have been identified in the APOC3 gene promoter region, which are in high LD with variants in other APOC isoforms and which functionally affect intestinal synthesis and transcription activity of APOA1. Variants within the APOC3 gene clusters have been associated with lipid levels and myocardial infarction in a wide range of ethnic and age groups [44]. The C-482T polymorphism in the APOC3 promoter is also associated with insulin and glucose levels after an oral glucose tolerance test (OGTT) in young healthy men [45]. In cross-sectional data, Brown and colleagues [46] reported significant interactions between the T-455C and e625tdel variants (in high LD with each other) and habitual SFA intake on total and LDL cholesterol levels. Several small-scale studies have reported evidence for gene-nutrient interaction

17 120 P.W. Franks et al. at the APOC3 locus (Table 4). In men (n ¼ 30), but not in women (n ¼ 29), Perez-Jimenez et al. [47] suggested that 28-day SFA intake may influence the relationship between the SstI polymorphism at APOC3, but no specific data were shown in this paper to support this view. Elsewhere, Salas et al. [48] fed 41 male volunteers three different diets. The first was high in SFA [15% protein, 47% carbohydrate, 38% fat (20% saturated)], the second was a National Cholesterol Education Program Step 1 diet (15% protein, 57% carbohydrate, 28% fat [<10% saturated]), and the third was rich in MUFA (15% protein, 47% carbohydrate, 38% fat [22% MUFA, <10% SFA]). No evidence of statistical interaction between diet and genotype was observed for fasting or post-challenge glucose or insulin levels. However, the sample sizes in these analyses were extremely small, making it difficult to determine the relevance of these observations. Apolipoprotein E (apoe) binds in a liganddependent manner to the LDL receptor and the LDL-receptor-related protein. Thus apoe promotes uptake of triglyceride-rich lipoproteins from the circulation, efflux of intra-cellular cholesterol, and reverse cholesterol transport. ApoE is present in 3 main isoforms (apoe2, apoe3, and apoe4). These proteins determine changes in apoe plasma concentrations and differ in their affinity to the receptors. Variants in the proximal promoter region of the APOE gene have been described, of which one, e219g/t, is associated with transcriptional activity [49]. The same variant has also been cross-sectionally associated with insulin resistance [50]. In studies of gene-nutrient interaction, Campos et al. [51] tested interaction between habitual SFA intake and APOE genotype on plasma lipoprotein levels and low density lipoprotein (LDL) particle size in 420 randomly selected free-living Costa Ricans (Table 4). Their data indicated that the APOE2 allele may modulate the effect of habitual SFA intake on VLDL cholesterol and HDL cholesterol in a population with an average habitual total fat intake of less than 30%. In two cross-sectional studies, interaction between physical activity APOE isoforms on HDL cholesterol levels have been reported, where the association between physical activity and HDL cholesterol levels is strongest in carriers of the APOE2 allele than in carriers of either the APOE2 or APOE3 alleles [52,53]. One intervention [54] reported a greater increase in HDL cholesterol levels in APOE2 carriers compared to carriers of the APOE3 and APOE4 alleles after a 9-month endurance exercise training program. However, no tests for interaction were reported. Lipoprotein lipase Lipoprotein lipase (LPL) plays a role in the hydrolysis of triglyceride-rich lipoproteins, and is sensitive to changes in energy flux. Data in twins [55] indicate that the changes in adipose tissue LPL activity in response to acute exercise is more similar in monozygotic than in dizygotic twins, suggesting that the response is under the control of genetic factors. A number of polymorphisms have been described in the human LPL gene. Of these, the S447X (Ser447Ter) variant, located in exon 9 of the gene, encodes an LPL that lacks the COOHterminal Ser-Gly dipeptide. In case-control data, an association between S447X and risk of premature CHD [33] has been observed, and the cross-sectional association at this locus with reduced levels of triglycerides in obese individuals has also been reported [56]. Elsewhere, variants at the LPL locus (D9N mutation and the HindIII polymorphism) have been reported to associate with changes in HDL cholesterol and plasma triglyceride levels [57,58]. Several studies have assessed the association between physical activity lipid levels stratified by LPL gene variants (Table 4), although few formally test for interaction. In cross-sectional data, the association between the D9N variant and lipid levels (total cholesterol, apob, and HDL cholesterol) was assessed in sedentary and active individuals [59]. Although an association between genotype and lipid levels was evident in sedentary people, no association was observed in active individuals. This led the authors to conclude that physical activity counteracts the affects of the risk allele at D9N on lipid levels. However, no formal test of interaction was undertaken to quantify whether the differences in lipid levels by genotype differed significantly between activity groups. Elsewhere, an absence of interaction was observed between the LPL HindIII polymorphism and physical activity on HDL cholesterol and triglyceride levels in Spanish individuals [60]. By contrast, Garenc et al. [61] reported that the LPL S447X polymorphism influences the training-induced changes in body fat and post-heparin LPL activity in women but not in men. Discussion This review has demonstrated that despite reasonably strong evidence that interactions between genetic and lifestyle factors underlie the distribution of type 2 diabetes in populations, the evidence base concerning the details of these interactions is extremely small. Our tables of published studies mostly include cross-sectional