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Genes and individual responsiveness to exercise-induced fat loss
CHAPTER ELEVEN
Genes and individual responsiveness to exercise-induced fat loss ska-Dunieca, Pawel Cięszczyka, Ildus I. Ahmetovb,c,d Agata Leon a
Faculty of Physical Education, Gdansk University of Physical Education and Sport, Gdansk, Poland Department of Molecular Biology and Genetics, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia c Laboratory of Molecular Genetics, Kazan State Medical University, Kazan, Russia d Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom b
11.1 Introduction Regular physical activity has significant benefits for health, including reduction of the risk of cardiovascular diseases, hypertension, metabolic diseases (e.g., type 2 diabetes), certain forms of cancer, fatty liver disease, pulmonary diseases, hormonal disturbances, osteoarticular diseases, and psychiatric illness. Additionally, properly selected exercises are key component of the total daily energy expenditure and as such contribute to improve body composition and help control weight (Rankinen and Bouchard, 2008). According to the World Health Organization (WHO), the number of people with overweight and obesity is increasing rapidly worldwide and is described as an epidemic, consequently, the prevention of weight gain is very important public health problem (Bray and Bellanger, 2006). An accumulation of additional amounts of triglycerides (TGL) in adipose tissue is a consequence of a chronic excess of energy intake compared to energy expenditure. The imbalance of energy homeostasis can be affected by both caloric intake and physical activity, which may be dependent on developmental, behavioral, and environmental factors (Rank et al., 2012). Additionally, genetic factors play a key role in the regulation of body weight, since there are genes involved in the regulation of energy expenditure, appetite, lipid metabolism, adipogenesis, thermogenesis, and cell differentiation (Deram and Villares, 2009). The reported heritability of obesity varies depending on the phenotype studied, but tends to range from 31% to 90% (Min et al., 2013). In most individuals, the genetic background of obesity is complex and multifactorial, involving the interaction of numerous genes and gene-environment interactions. As with other complex phenotypes, rare examples of mono- and oligogenic causes for obesity that serve as models for understanding the difficult hormonal and neural networks that regulate energy homeostasis have been reported (Walley et al., 2006; Chung, 2012). Sports, Exercise, and Nutritional Genomics https://doi.org/10.1016/B978-0-12-816193-7.00011-7
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However, the large number of single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWASs) and candidate gene studies, appeared to explain only 2%–4% of the obesity status (El-Sayed Moustafa and Froguel, 2013). As a result, individual genetic variations cannot account for the present increasing obesity epidemic. As the environment conditions become increasingly obesogenic, measurable variation in individual obesity levels becomes apparent. Such differences in individual phenotype at these extremes of adiposity likely reflect allelic variation at genes that affect energy intake and expenditure (Chung, 2012). Decades of physiological research in physical activity has resulted in relatively good knowledge of the functional response of human body to exercise. Although the physiological reactions after regular exercises are quite well described, the genetic background of these reactions still remains mostly unknown (Leo nska-Duniec, 2013). The process of exercise-induced adaptation in human body involves a number of signaling mechanisms, initiating replication of specific DNA sequences, enabling its following translation, and finally generating new proteins. The physiological effects of these adaptations are determined by volume, intensity, and frequency of physical activity (Coffey and Hawley, 2007). It is well known that individuals vary in their responses to similar training: from a lack of adaptive response to extreme overload. Current studies have shown that people with the same genotypes respond similarly to exercises in comparison to those with different genotypes, indicating that some genes play a key role in determination of individual differences in response to physical activities. An understanding of the genetic determinants will allow to clarify the criteria of physical activities for individuals. In the future, this knowledge should help to identify persons who are expected to respond well or poorly to exercise, thus making training programs much more efficient (possibility of accurate prediction of the training results including weight loss and improve health) and safer (early prevention of possible overload, injuries, cardiomyopathies, sudden death, etc.) (Leo nska-Duniec, 2013). At first, studies performed in families, adoptees, and twins have clearly shown there is a genetic contribution to obesity. However, they do not offer insight into the specific gene variation underlying heritable traits. Currently, new technologies allow scientists to study the structure and function of genes at a molecular level. The search for genetic markers associated with obesity was firstly carried out using candidate-gene association studies or linkage analysis. Although these were promising methods in the discovery of genes for syndromic and monogenic obesity, the success of finding genes for common obesity susceptibility was limited, with very few reproducible results (Rankinen et al., 2006; Herrera and Lindgren, 2010). The considerable advances in the discovery of genetic loci that are linked with obesity-related traits were made in 2007 (Frayling et al., 2007; Scuteri et al., 2007). This was possible through analytical and technical progress allowing for GWASs (Herrera and Lindgren, 2010). GWASs allow for the analysis of the whole genome polymorphic sites to link genetic markers, usually SNPs, to
Genes and individual responsiveness to exercise-induced fat loss
physiological traits (Kim et al., 2011). At present, more than 700 genes and chromosomal regions have been described to take part in body weight and energy metabolism regulation, whereas gene-environment interaction in relation to weight change has been studied less frequently (Locke et al., 2015). Numerous evidences suggest that genetic factors play a significant role in how individuals respond to exercise. As some specific genetic factors for body weight have recently been identified, there is increasing interest in whether and how genetic susceptibility might interact with lifestyle factors such as physical activity (Li et al., 2010; Ahmad et al., 2013). This chapter summarizes the current evidence on the role of the gene variants on the characteristics and range of the body’s adaptive response to training. We studied the most reliable candidate genetic markers that are involved in energy balance pathways and body composition changes in response to training programs.
11.2 Gene variants and exercise-induced fat loss 11.2.1 FTO gene The first described obesity-susceptibility gene, with the largest influence on higher body mass index (BMI) to date, was the fat mass and obesity-associated gene (FTO) (Frayling et al., 2007; Scuteri et al., 2007). Recently, studies concerning the relationship between FTO and weight have been frequently replicated, not only for BMI, but also for obesity risk, body fat percentage, waist circumference, type 2 diabetes, and other types of obesity. Subsequently, these associations are replicable across different age groups, as well as multiple ethnic populations (Loos, 2012). Currently, a common FTO A/T polymorphism (rs9939609) is one of the most often investigated genetic variant in the context of genetic conditioning for a predisposition to body weight excess. The human FTO gene is located in chromosome region 16q12.2 (Frayling et al., 2007), and the product of the gene is a nuclear protein—2-oxoglutarate (2-OG) Fe(II) dependent demethylase (Loos and Yeo, 2014). The up-to-date results establish that the enzyme is able to remove methyl groups from DNA and RNA nucleotides in vitro with the highest affinity for single stranded RNA molecules (Almen et al., 2012; Loos and Yeo, 2014). It was suggested that the FTO gene can influence the activity of pathways controlling daily food intake, and what is more nutrient preference (Loos and Yeo, 2014). The FTO A/T polymorphism is located in the first intron of the gene, which is related with an enhanced risk of excessive weight gain, increasing the risk by 20%– 30%. It has been revealed that carrier status of one or two copies of the risk (A) allele is related with increases in body mass of average 1.2 and 3.0 kg, respectively (Frayling et al., 2007). Numerous studies have reported that the FTO effect on obesity-related traits is reduced by approximately 30% in physically active compared to sedentary adults (Li et al., 2010; Kilpel€ainen et al., 2011; Ahmad et al., 2013; Loos and Yeo, 2014).
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In other studies, the effect size of FTO variants is up to 80% lower in physically active individuals (Rampersaud et al., 2008; Vimaleswaran et al., 2009). However, not all studies have demonstrated the gene physical activity interaction (Hakanen et al., 2009; Jonsson et al., 2009; Lappalainen et al., 2009). Although, Leo nska-Duniec et al. (2018a) have confirmed the association between the FTO A/T polymorphism and increased BMI, none of the examined obesity-related parameters changed significantly across the FTO genotypes during a 12-week training program (Leo nska-Duniec et al., 2018a).
11.2.2 MC4R gene The melanocortin-4 receptor gene (MC4R) encodes a 332-amino-acid, which belongs to a family of seven trans-membrane G-protein-coupled receptors (GPCRs). The protein is well-known major regulator of food intake and energy expenditure. Polymorphisms within the MC4R coding region have been described to be related with obesity in humans (Hebebrand et al., 2010). In addition, variants outside of the coding region probably influence its expression and have been linked with a predisposition to excess of body weight (Evans et al., 2014). GWAS conducted in Caucasian revealed that the variant rs17782313 (C/T polymorphism), mapped 188 kb downstream of the MC4R (Loos et al., 2008), also shows a strong connection with obesity-related traits (Xi et al., 2012). This association has been confirmed in multiple populations including children, adolescence, and adults (Loos, 2012; Xi et al., 2012). The risk (C) allele is connected with an increased intakes of total energy and dietary fat, and as a result higher prevalence of obesity (Qi et al., 2008). Each copy of the C allele is linked with an increase in BMI of 0.22 kg/m2 in adults (Loos et al., 2008). What is more, the risk allele was also associated with average 14% enhance risk of type 2 diabetes (Qi et al., 2008). It has been described that effect of the gene on obesity-related traits may be reduced by living a physically active lifestyle. Li et al. (2010) genotyped 12 SNPs in obesity-susceptibility loci including rs17782313 in a group of 20,430 European participants and showed that genetic predisposition to increased BMI and obesity is attenuated by a physically active lifestyle (Li et al., 2010). However, other study did not show association between the polymorphism and selected body composition measurements in 242 participants undergoing a 9-month lifestyle intervention (Haupt et al., 2009). In a study performed on 111,421 adults of European descent, Ahmad et al. (2013) analyzed 12 loci connected with obesity-related traits and also did not reveal evidence of the polymorphism rs17782313 physical activity interactions (Ahmad et al., 2013). Additionally, Leo nska-Duniec et al. (2017) could not notice the near MC4R C/T polymorphism physical activity interaction in a group of 201 Polish women taking part in 12-week training program (Leo nska-Duniec et al., 2017).
Genes and individual responsiveness to exercise-induced fat loss
11.2.3 PPARG, PPARD, and PPARGC1A genes The peroxisome proliferator-activated receptors genes (PPAR) are frequently investigated genetic markers in the context of athletic predisposition and health-related fitness phenotypes due to the multiple physiological roles of proteins encoded by them (Maciejewska-Karłowska, 2013). PPAR proteins are lipid-activated nuclear receptors which are the member of the nuclear hormone receptor superfamily (Desvergne and Wahli, 1999). The transcriptional activity of PPARs is mediated by PPAR retinoid X receptor (RXR) heterodimers which bind to specific DNA sequence elements termed PPREs (PPAR response elements) in their target genes’ regulatory region. The major role of PPARs is the transcriptional regulation of proteins involved in lipid and carbohydrate metabolism. Additionally, PPARs effect expression of genes active in vascular biology, tissue repair, cell proliferation, and differentiation (Yessoufou and Wahli, 2010). Three PPAR isotypes have been described so far, which exhibit a different tissue distribution, functions, and to some extent different ligand specificities: (i) PPARα encoded by the PPARA gene located on chromosome 22, (ii) PPARδ (also called PPARβ) by the PPARD gene on chromosome 6, and (iii) PPARγ by the PPARG gene on chromosome 3 (Maciejewska-Karłowska, 2013). Peroxisome proliferator-activated receptor gamma, coactivator 1 alpha (PGC1), encoded by the PPARGC1A gene, is a transcriptional coactivator of the PPAR superfamily. This protein interacts with PPARγ which enables its interaction with many others transcriptional factors. PGC1 is involved in mitochondrial biogenesis, glucose utilization, fatty acid (FA) oxidation, thermogenesis, gluconeogenesis, and insulin signaling. Peroxisome proliferator-activated receptor gamma, coactivator 1 beta (PGC1), encoded by the PPARGC1B gene, together with the PPARGC1A gene, encodes homologous proteins that, through nuclear transcription factor coactivation, regulate adipogenesis, insulin signaling, lipolysis, mitochondrial biogenesis, angiogenesis, and hepatic gluconeogenesis (Franks et al., 2014). The PPARs and their transcriptional coactivators’ gene polymorphisms due to their role in lipid and carbohydrate metabolism are frequently described as genetic markers which influence obesity and other disease-related phenotypes obesity. Currently, especially PPARG, PPARD, and PPARGC1A genes are considered in the context of their potential impact on functional response of the human body to exercise. Zarebska et al. (2014) have checked if body mass changes observed in physically active participants will be modulated by the PPARG Pro12Ala (rs1801282) genotype. The results suggest that PPARG genotype may modulate training-induced body mass measurements changes: after completion of the training program Pro12/Pro12 homozygotes were characterized by a greater decrease of body fat mass measurements in comparison with 12Ala allele carriers. These results indicate that the PPARG 12Ala variant may
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weaken the training-induced positive effects on body mass measurements (Zarebska et al., 2014). Other interventional studies have shown that diet and physical activity connection on fasting insulin differ between PPARG Pro12Ala genotypes. The beneficial additive results of exercise and healthy diet were noticed only in homozygotes for the Pro12 allele. Meanwhile, in 12Ala allele carriers association between diet and exercise were more complicated and the change in fasting insulin level was only attenuated when both exposures of diet and activity were simultaneously elevated (Franks et al., 2004). The studies of PPARD polymorphisms have been mainly focused on three SNPs: rs2267668 with its locus in intron 3, rs2016520 with its locus in the 50 untranslated region of exon 4, and rs1053049 with its locus in the 30 untranslated region of exon 9. Leo nskaDuniec et al. (2018b) correlate the distribution of genotypes, alleles, and haplotypes described in mentioned above PPARD polymorphisms in female participants engaged in a 12-week training program. With reference to PPARD rs2267668 genotypes, there were two significant genotype training interactions in which a greater decrease of cholesterol (Chol) over training was observed in the rs2267668 G allele carriers and a significant increase of TGL levels in the AA homozygotes. Moreover, carriers of a rs2016520 PPARD C allele exhibited a significant decrease in Chol from training with accompanying decreases in TGL. There was also overrepresentation of PPARD rs1053049 TT homozygotes in the group with higher posttraining TGL levels. Moreover (rs2267668/rs2016520/rs1053049) G/C/T haplotype displayed smaller posttraining body mass decrease, suggesting that harboring this specific G/C/T haplotype is unfavorable for achieving the desired training-induced body mass changes. On the other hand, the G/C/C haplotype was significantly associated with posttraining increase in fat free mass (FFM) and with lower levels of Chol as well as TGL as observed in the blood of the participants in response to applied training (Leo nska-Duniec et al., 2018b). Associations of PPARGC1A polymorphisms with a range of cardiovascular and metabolic traits, including type 2 diabetes, insulin resistance, glucose concentrations, dyslipidaemia, obesity, and aerobic fitness, have been reported, as have interactions between gene variants and lifestyle factors including regular physical activity (Franks et al., 2014). The PPARGC1A rs8192678 Gly/Gly genotype has been associated with greater increases of an individual’s anaerobic threshold, slow muscle fibers, mitochondrial activity, as well as reduction of total Chol and low-density lipoprotein (LDL) after lifestyle intervention including regular aerobic training than PPARGC1A rs8192678 Ser allele carriers. Additionally, PPARGC1A rs8192678 Ser allele carriers had no response in changes of slow twitch muscle fibers, total Chol and LDL after aerobic training (Stefan et al., 2007; Steinbacher et al., 2015; Tobina et al., 2017). These observations led to the suggestion that the rs8192678 Gly allele may be a key element associated with the efficiency of aerobic metabolism (Stefan et al., 2007).
Genes and individual responsiveness to exercise-induced fat loss
11.2.4 LEP and LEPR genes Leptin, an adipocyte-derived hormone, which plays key role in regulating appetite by its inhibitory effects on food intake and increases in energy expenditure by stimulating metabolic rate and physical activity to maintain energy balance (Lenard and Berthoud, 2008). Leptin signaling is mediated by its specific receptor, a single transmembrane protein which belongs to class I cytokine receptor family (Considine et al., 1996). Leptin acts as an afferent signal in a negative feedback loop by binding to leptin receptor regulating the size of adipose tissue (Sahu, 2004). Several polymorphisms of both genes coding leptin (LEP) and leptin receptor (LEPR) have been studied in various populations for their potential association with obesity. That common variants also may modify the effects of regular physical activity on various obesity-related traits such as glucose homeostasis (Lakka et al., 2004). Among these SNPs, the leptin concentration is affected by the LEP A19G polymorphism (rs2167270) of the untranslated region of exon 1. The genotype GG is connected with significantly lower leptin concentrations in comparison with the genotype AA (Hager et al., 1998). In a study performed on 242 European-derived participants, Walsh et al. (2012) revealed that homozygous for the G allele may be receiving additional health benefits as a result of expending more energy in vigorous intensity physical activity due to their genetic predispositions than carriers of the A allele (Walsh et al., 2012). Additionally, Leo nskaDuniec et al. (2018c) have suggested that the LEP rs2167270 genotype may contribute to improvements in glucose homeostasis in response to a 12-week aerobic training program. A training-related decrease in plasma glucose concentration in the LEP AG heterozygotes differed significantly from the change in the AA and GG homozygotes (Leo nska-Duniec et al., 2018c). Variants of LEPR have also been described to influence leptin receptor activity. One of them is LEPR A668G (rs1137101), which is located in exon 6, a supposed leptinbinding region, and as a result impacts binding capacity of leptin receptor to leptin (Chagnon et al., 1999). The G allele has been connected with greater muscle volume than participants with the AA genotype and greater subcutaneous fat volume response to a resistance training program (Walsh et al., 2012). Additionally, the significant interaction between regular physical activity and LEPR rs1137101 for LDL level has been described. As opposed to AG and GG, AA homozygotes have demonstrated a training-related decrease in LDL plasma levels (Leo nska-Duniec et al., 2018c).
11.2.5 ADIPOQ gene One of the most frequently investigated adipose tissue-derived hormones is adiponectin, which is an important antiinflammatory and insulin-sensitizing peptide, which promotes lipid oxidation in tissues such as skeletal muscle and liver (Yamauchi et al., 2001, 2002).
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The hormone also directs antiatherosclerotic properties, as it strongly inhibits expression of adhesion molecules and growth factors (Kadowaki and Yamauchi, 2005). In humans, adiponectin is encoded by the ADIPOQ gene which is located on chromosome 3q27 (Takahashi et al., 2000). Nowadays, among genetic variants of the ADIPOQ gene which have been described in the context of genetic conditioning for a predisposition to obesity in some ethnic populations, +276 G>T SNP (rs1501299) and 11377 G >C SNP (rs266729) are the most frequently investigated polymorphisms associated with serum levels of adiponectin (Enns et al., 2011). The studies suggest that the ADIPOQ genotypes analyzed individually or in combination can modulate training-induced body mass measurement changes: after the training program, carriers of the rs1501299 T allele and rs266729 C allele were characterized by a greater reduction in fat mass and body mass compared with G allele carriers. Moreover, ADIPOQ polymorphisms were associated with changes in lipid profile in response to training. From this evidence, it could be concluded that rs1501299 G and rs266728 G variants may be considered as a disadvantageous factor in the context of training-induced effects on body mass traits (Kyriakou et al., 2008; Passariello et al., 2010; Leo nska-Duniec et al., 2018d).
11.2.6 ADRB2 and ADRB3 genes The proteins encoded by the β2-adrenergic receptor (ADRB2) and the β3-adrenergic receptor (ADRB3) genes belong to the family of β-adrenergic receptors, which mediate catecholamine-induced activation of adenylate cyclase through the action of G proteins. They are located in adipose tissue and involved in energy homeostasis through the mediation of the both lipolysis and thermogenesis rate. Thus genes encoding these receptors are interesting candidates for explaining part of the genetic predisposition to obesity in humans (Park et al., 2005). Additionally, many studies have shown that variation within ADRB genes contributes to interindividual changes of body composition in response to regular physical exercise (Sakane et al., 1997; Corbala´n et al., 2002; Shiwaku et al., 2003; Masuo and Lambert, 2011; Leo nska-Duniec et al., 2018e). The ADRB2 is a major lipolytic receptor in adipocytes and genetic polymorphisms in the gene may reduce lipolysis and predispose to obesity. The most frequent variants result in amino acid changes investigated in relation to obesity are at codon 16 (Arg16Gly, rs1042713) and codon 27 (Gln27Glu, rs1042714). The Gly16 allele has been associated with lower receptor density and hence reduced efficiency in comparison with the Arg16 allele, which may influence the propensity to higher BMI (Chou et al., 2012). In a study of overweight men participated in a 24-month weight loss program consisting of lowcalorie diet and everyday aerobic exercise showed a higher frequency of the Gly16 allele in men resistant to weight loss and those who regained body weight after successful initial weight loss at 6 months (Masuo et al., 2005). Numerous studies have also shown that the
Genes and individual responsiveness to exercise-induced fat loss
Glu27 allele may limit ADRB2 down-regulation and thus affect body weight (Lange et al., 2005). Corbala´n et al. (2002) described that women who were more active during their free time and were carriers of the Glu27 allele had higher body weight compared to noncarriers, suggesting that these women may be more resistant to losing weight (Corbala´n et al., 2002). The ADRB3 is the key receptor mediating catecholamine-stimulated thermogenesis in adipose tissue (Emorine et al., 1989). In humans low ADRB3 activity could promote obesity through decreased function in adipose tissue. A Trp64Arg (rs4994) variant in codon 64 of this gene has been associated with a tendency toward excess of body weight, insulin resistance, and type 2 diabetes (Clement et al., 1995; Widen et al., 1995). Many studies have shown increased BMI (average 0.28 kg/m2) in carriers of the Arg64 allele only among sedentary participants, but not in physically active subjects, where genotypic differences in BMI were not found (Fujisawa et al., 1998; Kurokawa et al., 2001; Marti et al., 2002). Other studies have shown that women with the Arg64 allele who participated in lifestyle intervention combining exercise and low-calorie diet lost less weight than women without the allele, suggesting that the Arg64 allele is connected with difficulty in losing weight through diet and training program (Sakane et al., 1997; Shiwaku et al., 2003). However, Phares et al. (2004) have shown that the Arg64 carriers experienced a great loss of fat mass and trunk fat following 24 weeks of aerobic exercise training compared to noncarriers and demonstrated an opposite allelic response to exercise.
11.2.7 ACSL1 gene Mouse studies have revealed that Acyl-CoA synthetase (ACSL) acts to convert long chain FA to acyl-CoA, and thus enhancing FA transport across the plasma membrane and providing substrates for most downstream pathways that metabolize FA. ACSL1 is one of five ACSL isoforms, each encoded by a separate gene. As such, ACSL1 is highly expressed in tissues that undergo high rates of metabolism, including muscle, adipose tissue, and liver cells (Mashek et al., 2006). The ACSL1 deficiency has been shown to reduce FA oxidation and increase glucose utilization (Ellis et al., 2010), negatively impacting metabolic health (Li et al., 2009). The current studies provide evidences in humans of ACSL1 SNPs associated with fasting glucose, diabetes, subclinical atherosclerosis and suggest links among these traits and acyl-CoA synthesis (Manichaikul et al., 2016). A SNP in this gene, rs9997745, has been shown to modify the risk of metabolic disease (Phillips et al., 2010). A second SNP, rs6552828, explained 6.1% of the variance in VO2max changes following aerobic training in the HERITAGE Family Study (Bouchard et al., 2011). In the latest not published study, a third SNP, rs116143768, was showed a genome-wide significant association (P ¼ 1.18 109) with fat loss following a 12-week aerobic training, with rare T allele carriers losing 31.4% of their fat
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mass, and CC homozygotes losing only 3.8%. From this evidence, it could be concluded that T allele may be considered as a favorable factor in the context of training-induced effects on body mass traits. However, more experimental studies are needed to establish the association between the ACSL1 SNPs and physical activity.
11.2.8 INSIG2 gene Insulin-induced gene 2 (INSIG2), located on chromosome 2q14, has been functionally linked to lipid metabolism, mostly due to its role in endogenous Chol and FA synthesis feedback inhibition. An endoplasmic reticulum membrane bound protein, encoded by INSIG2 gene, inhibits the proteolytic activation of sterol response element-binding proteins (SREPs) in response to Chol or insulin (Gong et al., 2006). Polymorphisms within INSIG2 have been associated with BMI, in particular, rs7566605 in the promotor region of this gene was linked to baseline subcutaneous fat mass in females and BMI (Lyon et al., 2007; Orkunoglu-Suer et al., 2008). In previous researches, the C allele was associated with a gain in subcutaneous fat mass following resistance training in males (Orkunoglu-Suer et al., 2008), and following a generalized health 1 year intervention in obese children (Reinehr et al., 2008). The results of the latest not published study performed on 116 Caucasian women fit with the previous research, as CC genotypes was associated with an increase in BMI in response to a 12-week aerobic training. These data suggest that exercise training may indeed lead to poorer health outcomes in INSIG2 C carriers, in that even limited localized exercise may trigger an increase in adiposity (Orkunoglu-Suer et al., 2008).
11.2.9 FABP2 gene Fatty acid-binding proteins (FABPs) are small intracellular polypeptides found in many tissues, involved in FA transfer and metabolism (Hsu and Storch, 1996) and encoded by a family of different genes. The fatty acid-binding protein 2 gene (FABP2) is located in the 4q28-4q31 chromosomal region, and encodes the intestinal form of FA-binding protein (IFABP), and is only expressed in the small intestine epithelial cells (enterocytes). IFABP protein plays a key role in the facilitation of cellular uptake and intracellular transport of dietary long-chain FA (Hertzel and Bernlohr, 2000; Furuhashi and Hotamisligil, 2008). Among the well-known SNPs associated with adiposity is the G to A polymorphism (rs1799883) of codon 54 in exon 2 results in the exchanges an alanine (Ala) in the small helical region of the protein for threonine (Thr). Various studies have suggested that this substitution is a functional mutation, which results in modified FA absorption, it could in turn affect the lipid metabolism and correlate with cardiovascular disease (CVD) risk (Baier et al., 1995). Because of the role of the Ala54Thr polymorphism of the FABP2 gene, it is considered that can modify interindividual responses to a particular diet and training program (Takakura et al., 2005; de Luis et al., 2006). Takakura et al. (2005) have
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showed that subjects with Ala/Thr and Thr/Thr genotype, adjusted resting metabolic rate (RMR) was significantly lower than the subjects with Ala/Ala genotype. Subjects with the Thr54 allele showed significantly greater waist circumference after diet and exercise therapy than subjects with Ala/Ala genotype (Takakura et al., 2005). This result may be supported by other studies, which described that carriers of the Thr54 allele, compared to Ala/Ala homozygotes, failed to have a significant reduction in fat mass, LDL levels, and leptin levels after a lifestyle modification program consisting of diet and physical activity (de Luis et al., 2006).
11.3 Conclusions Obesity is a multifactorial abnormality which have well-confirmed strong genetic basis but requires environmental influences caloric intake and physical activity to demonstrate. Numerous studies have shown the role of lifestyle including exercise and dietary factors in weight control (Qi and Cho, 2008). However, the problem is in defining the genes and polymorphisms related to obesity, and describing by which mechanisms they exert their effect. In view of the fact that DNA variants do not completely explain the heritability of obesity, more studies with appropriate designs and statistical power should be undertaken using the latest genomics methods in sequencing and genotyping, combined with epigenomics, transcriptomics, proteomics, and metabolomics (Qi and Cho, 2008; Perusse et al., 2013). Based on the literature, we speculate that in the near future, more studies should be also focused on identifying genetic markers referring to other obesity-related traits, for example, resistance to stress and pain, increased appetite and nutrient preference, as well as temperament. Another important question is the role of the gene variants on the characteristics and range of the body’s adaptive response to training. It is well known that the adaptive changes in the human body in response to regular physical exercises show great individual variance. Consequently, losing weight and changes in obesity-related traits in response to training programs may be more effective for some genotypes than others. However, the genetic background of these reactions still remains mostly unknown. One of the major aims of exercise genomics is to finally be able to define molecular markers, which by themselves or in combination with other biomarkers would make it possible to predict the benefits from exercise program or physically active lifestyle. Understanding the genetic background of physiological processes would have an enormous impact not only on individualization of exercise programs to be more efficient and safer, but also better recovery, traumatology, medical care, diet, supplementation, and many other areas (Perusse et al., 2013). Currently, some studies have tried to answer these questions, however, they still represent only the first steps towards a understanding of the genetic factors that influence obesity-related traits, and gene variants physical activity interactions, so continuing researches are necessary.
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Nevertheless, the search for genetic markers of functional response of human body to physical activities is very complicated and obtained results may be contradictory. There could be several reasons for this inconsistency: (i) heterogeneity between study populations, (ii) differences in daily food intake and nutrient preference, (iii) discrepancy in the volume, intensity and frequency of exercises and in methods of measuring physical activity, (iv) relatively small size of study group what may not possess sufficient statistical power for meaningful analysis and interpretation. The major problem in this kind of research is the experiment organization consisting of conduction of regular physical activity, food intake control, examination of genotype distribution, and measurement of body composition, physiological, and biochemistry parameters before and after the realization of training program. As a consequence, there is a limitation of the number of people participating in lasting few weeks or even months lifestyle interventions, and the results are hard to replicate in independent studies. The importance of genetic studies in modern sport increases every year. Consequently, it is significant to discuss the achievements, hopes, and fears associated with the rapid development of molecular biology in sport and medicine sciences.
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Genes and individual responsiveness to exercise-induced fat loss ska-Dunieca, Pawel Cięszczyka, Ildus I. Ahmetovb,c,d Agata Leon a
Faculty of Physical Education, Gdansk University of Physical Education and Sport, Gdansk, Poland Department of Molecular Biology and Genetics, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia c Laboratory of Molecular Genetics, Kazan State Medical University, Kazan, Russia d Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom b
11.1 Introduction Regular physical activity has significant benefits for health, including reduction of the risk of cardiovascular diseases, hypertension, metabolic diseases (e.g., type 2 diabetes), certain forms of cancer, fatty liver disease, pulmonary diseases, hormonal disturbances, osteoarticular diseases, and psychiatric illness. Additionally, properly selected exercises are key component of the total daily energy expenditure and as such contribute to improve body composition and help control weight (Rankinen and Bouchard, 2008). According to the World Health Organization (WHO), the number of people with overweight and obesity is increasing rapidly worldwide and is described as an epidemic, consequently, the prevention of weight gain is very important public health problem (Bray and Bellanger, 2006). An accumulation of additional amounts of triglycerides (TGL) in adipose tissue is a consequence of a chronic excess of energy intake compared to energy expenditure. The imbalance of energy homeostasis can be affected by both caloric intake and physical activity, which may be dependent on developmental, behavioral, and environmental factors (Rank et al., 2012). Additionally, genetic factors play a key role in the regulation of body weight, since there are genes involved in the regulation of energy expenditure, appetite, lipid metabolism, adipogenesis, thermogenesis, and cell differentiation (Deram and Villares, 2009). The reported heritability of obesity varies depending on the phenotype studied, but tends to range from 31% to 90% (Min et al., 2013). In most individuals, the genetic background of obesity is complex and multifactorial, involving the interaction of numerous genes and gene-environment interactions. As with other complex phenotypes, rare examples of mono- and oligogenic causes for obesity that serve as models for understanding the difficult hormonal and neural networks that regulate energy homeostasis have been reported (Walley et al., 2006; Chung, 2012). Sports, Exercise, and Nutritional Genomics https://doi.org/10.1016/B978-0-12-816193-7.00011-7
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However, the large number of single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWASs) and candidate gene studies, appeared to explain only 2%–4% of the obesity status (El-Sayed Moustafa and Froguel, 2013). As a result, individual genetic variations cannot account for the present increasing obesity epidemic. As the environment conditions become increasingly obesogenic, measurable variation in individual obesity levels becomes apparent. Such differences in individual phenotype at these extremes of adiposity likely reflect allelic variation at genes that affect energy intake and expenditure (Chung, 2012). Decades of physiological research in physical activity has resulted in relatively good knowledge of the functional response of human body to exercise. Although the physiological reactions after regular exercises are quite well described, the genetic background of these reactions still remains mostly unknown (Leo nska-Duniec, 2013). The process of exercise-induced adaptation in human body involves a number of signaling mechanisms, initiating replication of specific DNA sequences, enabling its following translation, and finally generating new proteins. The physiological effects of these adaptations are determined by volume, intensity, and frequency of physical activity (Coffey and Hawley, 2007). It is well known that individuals vary in their responses to similar training: from a lack of adaptive response to extreme overload. Current studies have shown that people with the same genotypes respond similarly to exercises in comparison to those with different genotypes, indicating that some genes play a key role in determination of individual differences in response to physical activities. An understanding of the genetic determinants will allow to clarify the criteria of physical activities for individuals. In the future, this knowledge should help to identify persons who are expected to respond well or poorly to exercise, thus making training programs much more efficient (possibility of accurate prediction of the training results including weight loss and improve health) and safer (early prevention of possible overload, injuries, cardiomyopathies, sudden death, etc.) (Leo nska-Duniec, 2013). At first, studies performed in families, adoptees, and twins have clearly shown there is a genetic contribution to obesity. However, they do not offer insight into the specific gene variation underlying heritable traits. Currently, new technologies allow scientists to study the structure and function of genes at a molecular level. The search for genetic markers associated with obesity was firstly carried out using candidate-gene association studies or linkage analysis. Although these were promising methods in the discovery of genes for syndromic and monogenic obesity, the success of finding genes for common obesity susceptibility was limited, with very few reproducible results (Rankinen et al., 2006; Herrera and Lindgren, 2010). The considerable advances in the discovery of genetic loci that are linked with obesity-related traits were made in 2007 (Frayling et al., 2007; Scuteri et al., 2007). This was possible through analytical and technical progress allowing for GWASs (Herrera and Lindgren, 2010). GWASs allow for the analysis of the whole genome polymorphic sites to link genetic markers, usually SNPs, to
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physiological traits (Kim et al., 2011). At present, more than 700 genes and chromosomal regions have been described to take part in body weight and energy metabolism regulation, whereas gene-environment interaction in relation to weight change has been studied less frequently (Locke et al., 2015). Numerous evidences suggest that genetic factors play a significant role in how individuals respond to exercise. As some specific genetic factors for body weight have recently been identified, there is increasing interest in whether and how genetic susceptibility might interact with lifestyle factors such as physical activity (Li et al., 2010; Ahmad et al., 2013). This chapter summarizes the current evidence on the role of the gene variants on the characteristics and range of the body’s adaptive response to training. We studied the most reliable candidate genetic markers that are involved in energy balance pathways and body composition changes in response to training programs.
11.2 Gene variants and exercise-induced fat loss 11.2.1 FTO gene The first described obesity-susceptibility gene, with the largest influence on higher body mass index (BMI) to date, was the fat mass and obesity-associated gene (FTO) (Frayling et al., 2007; Scuteri et al., 2007). Recently, studies concerning the relationship between FTO and weight have been frequently replicated, not only for BMI, but also for obesity risk, body fat percentage, waist circumference, type 2 diabetes, and other types of obesity. Subsequently, these associations are replicable across different age groups, as well as multiple ethnic populations (Loos, 2012). Currently, a common FTO A/T polymorphism (rs9939609) is one of the most often investigated genetic variant in the context of genetic conditioning for a predisposition to body weight excess. The human FTO gene is located in chromosome region 16q12.2 (Frayling et al., 2007), and the product of the gene is a nuclear protein—2-oxoglutarate (2-OG) Fe(II) dependent demethylase (Loos and Yeo, 2014). The up-to-date results establish that the enzyme is able to remove methyl groups from DNA and RNA nucleotides in vitro with the highest affinity for single stranded RNA molecules (Almen et al., 2012; Loos and Yeo, 2014). It was suggested that the FTO gene can influence the activity of pathways controlling daily food intake, and what is more nutrient preference (Loos and Yeo, 2014). The FTO A/T polymorphism is located in the first intron of the gene, which is related with an enhanced risk of excessive weight gain, increasing the risk by 20%– 30%. It has been revealed that carrier status of one or two copies of the risk (A) allele is related with increases in body mass of average 1.2 and 3.0 kg, respectively (Frayling et al., 2007). Numerous studies have reported that the FTO effect on obesity-related traits is reduced by approximately 30% in physically active compared to sedentary adults (Li et al., 2010; Kilpel€ainen et al., 2011; Ahmad et al., 2013; Loos and Yeo, 2014).
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In other studies, the effect size of FTO variants is up to 80% lower in physically active individuals (Rampersaud et al., 2008; Vimaleswaran et al., 2009). However, not all studies have demonstrated the gene physical activity interaction (Hakanen et al., 2009; Jonsson et al., 2009; Lappalainen et al., 2009). Although, Leo nska-Duniec et al. (2018a) have confirmed the association between the FTO A/T polymorphism and increased BMI, none of the examined obesity-related parameters changed significantly across the FTO genotypes during a 12-week training program (Leo nska-Duniec et al., 2018a).
11.2.2 MC4R gene The melanocortin-4 receptor gene (MC4R) encodes a 332-amino-acid, which belongs to a family of seven trans-membrane G-protein-coupled receptors (GPCRs). The protein is well-known major regulator of food intake and energy expenditure. Polymorphisms within the MC4R coding region have been described to be related with obesity in humans (Hebebrand et al., 2010). In addition, variants outside of the coding region probably influence its expression and have been linked with a predisposition to excess of body weight (Evans et al., 2014). GWAS conducted in Caucasian revealed that the variant rs17782313 (C/T polymorphism), mapped 188 kb downstream of the MC4R (Loos et al., 2008), also shows a strong connection with obesity-related traits (Xi et al., 2012). This association has been confirmed in multiple populations including children, adolescence, and adults (Loos, 2012; Xi et al., 2012). The risk (C) allele is connected with an increased intakes of total energy and dietary fat, and as a result higher prevalence of obesity (Qi et al., 2008). Each copy of the C allele is linked with an increase in BMI of 0.22 kg/m2 in adults (Loos et al., 2008). What is more, the risk allele was also associated with average 14% enhance risk of type 2 diabetes (Qi et al., 2008). It has been described that effect of the gene on obesity-related traits may be reduced by living a physically active lifestyle. Li et al. (2010) genotyped 12 SNPs in obesity-susceptibility loci including rs17782313 in a group of 20,430 European participants and showed that genetic predisposition to increased BMI and obesity is attenuated by a physically active lifestyle (Li et al., 2010). However, other study did not show association between the polymorphism and selected body composition measurements in 242 participants undergoing a 9-month lifestyle intervention (Haupt et al., 2009). In a study performed on 111,421 adults of European descent, Ahmad et al. (2013) analyzed 12 loci connected with obesity-related traits and also did not reveal evidence of the polymorphism rs17782313 physical activity interactions (Ahmad et al., 2013). Additionally, Leo nska-Duniec et al. (2017) could not notice the near MC4R C/T polymorphism physical activity interaction in a group of 201 Polish women taking part in 12-week training program (Leo nska-Duniec et al., 2017).
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11.2.3 PPARG, PPARD, and PPARGC1A genes The peroxisome proliferator-activated receptors genes (PPAR) are frequently investigated genetic markers in the context of athletic predisposition and health-related fitness phenotypes due to the multiple physiological roles of proteins encoded by them (Maciejewska-Karłowska, 2013). PPAR proteins are lipid-activated nuclear receptors which are the member of the nuclear hormone receptor superfamily (Desvergne and Wahli, 1999). The transcriptional activity of PPARs is mediated by PPAR retinoid X receptor (RXR) heterodimers which bind to specific DNA sequence elements termed PPREs (PPAR response elements) in their target genes’ regulatory region. The major role of PPARs is the transcriptional regulation of proteins involved in lipid and carbohydrate metabolism. Additionally, PPARs effect expression of genes active in vascular biology, tissue repair, cell proliferation, and differentiation (Yessoufou and Wahli, 2010). Three PPAR isotypes have been described so far, which exhibit a different tissue distribution, functions, and to some extent different ligand specificities: (i) PPARα encoded by the PPARA gene located on chromosome 22, (ii) PPARδ (also called PPARβ) by the PPARD gene on chromosome 6, and (iii) PPARγ by the PPARG gene on chromosome 3 (Maciejewska-Karłowska, 2013). Peroxisome proliferator-activated receptor gamma, coactivator 1 alpha (PGC1), encoded by the PPARGC1A gene, is a transcriptional coactivator of the PPAR superfamily. This protein interacts with PPARγ which enables its interaction with many others transcriptional factors. PGC1 is involved in mitochondrial biogenesis, glucose utilization, fatty acid (FA) oxidation, thermogenesis, gluconeogenesis, and insulin signaling. Peroxisome proliferator-activated receptor gamma, coactivator 1 beta (PGC1), encoded by the PPARGC1B gene, together with the PPARGC1A gene, encodes homologous proteins that, through nuclear transcription factor coactivation, regulate adipogenesis, insulin signaling, lipolysis, mitochondrial biogenesis, angiogenesis, and hepatic gluconeogenesis (Franks et al., 2014). The PPARs and their transcriptional coactivators’ gene polymorphisms due to their role in lipid and carbohydrate metabolism are frequently described as genetic markers which influence obesity and other disease-related phenotypes obesity. Currently, especially PPARG, PPARD, and PPARGC1A genes are considered in the context of their potential impact on functional response of the human body to exercise. Zarebska et al. (2014) have checked if body mass changes observed in physically active participants will be modulated by the PPARG Pro12Ala (rs1801282) genotype. The results suggest that PPARG genotype may modulate training-induced body mass measurements changes: after completion of the training program Pro12/Pro12 homozygotes were characterized by a greater decrease of body fat mass measurements in comparison with 12Ala allele carriers. These results indicate that the PPARG 12Ala variant may
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weaken the training-induced positive effects on body mass measurements (Zarebska et al., 2014). Other interventional studies have shown that diet and physical activity connection on fasting insulin differ between PPARG Pro12Ala genotypes. The beneficial additive results of exercise and healthy diet were noticed only in homozygotes for the Pro12 allele. Meanwhile, in 12Ala allele carriers association between diet and exercise were more complicated and the change in fasting insulin level was only attenuated when both exposures of diet and activity were simultaneously elevated (Franks et al., 2004). The studies of PPARD polymorphisms have been mainly focused on three SNPs: rs2267668 with its locus in intron 3, rs2016520 with its locus in the 50 untranslated region of exon 4, and rs1053049 with its locus in the 30 untranslated region of exon 9. Leo nskaDuniec et al. (2018b) correlate the distribution of genotypes, alleles, and haplotypes described in mentioned above PPARD polymorphisms in female participants engaged in a 12-week training program. With reference to PPARD rs2267668 genotypes, there were two significant genotype training interactions in which a greater decrease of cholesterol (Chol) over training was observed in the rs2267668 G allele carriers and a significant increase of TGL levels in the AA homozygotes. Moreover, carriers of a rs2016520 PPARD C allele exhibited a significant decrease in Chol from training with accompanying decreases in TGL. There was also overrepresentation of PPARD rs1053049 TT homozygotes in the group with higher posttraining TGL levels. Moreover (rs2267668/rs2016520/rs1053049) G/C/T haplotype displayed smaller posttraining body mass decrease, suggesting that harboring this specific G/C/T haplotype is unfavorable for achieving the desired training-induced body mass changes. On the other hand, the G/C/C haplotype was significantly associated with posttraining increase in fat free mass (FFM) and with lower levels of Chol as well as TGL as observed in the blood of the participants in response to applied training (Leo nska-Duniec et al., 2018b). Associations of PPARGC1A polymorphisms with a range of cardiovascular and metabolic traits, including type 2 diabetes, insulin resistance, glucose concentrations, dyslipidaemia, obesity, and aerobic fitness, have been reported, as have interactions between gene variants and lifestyle factors including regular physical activity (Franks et al., 2014). The PPARGC1A rs8192678 Gly/Gly genotype has been associated with greater increases of an individual’s anaerobic threshold, slow muscle fibers, mitochondrial activity, as well as reduction of total Chol and low-density lipoprotein (LDL) after lifestyle intervention including regular aerobic training than PPARGC1A rs8192678 Ser allele carriers. Additionally, PPARGC1A rs8192678 Ser allele carriers had no response in changes of slow twitch muscle fibers, total Chol and LDL after aerobic training (Stefan et al., 2007; Steinbacher et al., 2015; Tobina et al., 2017). These observations led to the suggestion that the rs8192678 Gly allele may be a key element associated with the efficiency of aerobic metabolism (Stefan et al., 2007).
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11.2.4 LEP and LEPR genes Leptin, an adipocyte-derived hormone, which plays key role in regulating appetite by its inhibitory effects on food intake and increases in energy expenditure by stimulating metabolic rate and physical activity to maintain energy balance (Lenard and Berthoud, 2008). Leptin signaling is mediated by its specific receptor, a single transmembrane protein which belongs to class I cytokine receptor family (Considine et al., 1996). Leptin acts as an afferent signal in a negative feedback loop by binding to leptin receptor regulating the size of adipose tissue (Sahu, 2004). Several polymorphisms of both genes coding leptin (LEP) and leptin receptor (LEPR) have been studied in various populations for their potential association with obesity. That common variants also may modify the effects of regular physical activity on various obesity-related traits such as glucose homeostasis (Lakka et al., 2004). Among these SNPs, the leptin concentration is affected by the LEP A19G polymorphism (rs2167270) of the untranslated region of exon 1. The genotype GG is connected with significantly lower leptin concentrations in comparison with the genotype AA (Hager et al., 1998). In a study performed on 242 European-derived participants, Walsh et al. (2012) revealed that homozygous for the G allele may be receiving additional health benefits as a result of expending more energy in vigorous intensity physical activity due to their genetic predispositions than carriers of the A allele (Walsh et al., 2012). Additionally, Leo nskaDuniec et al. (2018c) have suggested that the LEP rs2167270 genotype may contribute to improvements in glucose homeostasis in response to a 12-week aerobic training program. A training-related decrease in plasma glucose concentration in the LEP AG heterozygotes differed significantly from the change in the AA and GG homozygotes (Leo nska-Duniec et al., 2018c). Variants of LEPR have also been described to influence leptin receptor activity. One of them is LEPR A668G (rs1137101), which is located in exon 6, a supposed leptinbinding region, and as a result impacts binding capacity of leptin receptor to leptin (Chagnon et al., 1999). The G allele has been connected with greater muscle volume than participants with the AA genotype and greater subcutaneous fat volume response to a resistance training program (Walsh et al., 2012). Additionally, the significant interaction between regular physical activity and LEPR rs1137101 for LDL level has been described. As opposed to AG and GG, AA homozygotes have demonstrated a training-related decrease in LDL plasma levels (Leo nska-Duniec et al., 2018c).
11.2.5 ADIPOQ gene One of the most frequently investigated adipose tissue-derived hormones is adiponectin, which is an important antiinflammatory and insulin-sensitizing peptide, which promotes lipid oxidation in tissues such as skeletal muscle and liver (Yamauchi et al., 2001, 2002).
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The hormone also directs antiatherosclerotic properties, as it strongly inhibits expression of adhesion molecules and growth factors (Kadowaki and Yamauchi, 2005). In humans, adiponectin is encoded by the ADIPOQ gene which is located on chromosome 3q27 (Takahashi et al., 2000). Nowadays, among genetic variants of the ADIPOQ gene which have been described in the context of genetic conditioning for a predisposition to obesity in some ethnic populations, +276 G>T SNP (rs1501299) and 11377 G >C SNP (rs266729) are the most frequently investigated polymorphisms associated with serum levels of adiponectin (Enns et al., 2011). The studies suggest that the ADIPOQ genotypes analyzed individually or in combination can modulate training-induced body mass measurement changes: after the training program, carriers of the rs1501299 T allele and rs266729 C allele were characterized by a greater reduction in fat mass and body mass compared with G allele carriers. Moreover, ADIPOQ polymorphisms were associated with changes in lipid profile in response to training. From this evidence, it could be concluded that rs1501299 G and rs266728 G variants may be considered as a disadvantageous factor in the context of training-induced effects on body mass traits (Kyriakou et al., 2008; Passariello et al., 2010; Leo nska-Duniec et al., 2018d).
11.2.6 ADRB2 and ADRB3 genes The proteins encoded by the β2-adrenergic receptor (ADRB2) and the β3-adrenergic receptor (ADRB3) genes belong to the family of β-adrenergic receptors, which mediate catecholamine-induced activation of adenylate cyclase through the action of G proteins. They are located in adipose tissue and involved in energy homeostasis through the mediation of the both lipolysis and thermogenesis rate. Thus genes encoding these receptors are interesting candidates for explaining part of the genetic predisposition to obesity in humans (Park et al., 2005). Additionally, many studies have shown that variation within ADRB genes contributes to interindividual changes of body composition in response to regular physical exercise (Sakane et al., 1997; Corbala´n et al., 2002; Shiwaku et al., 2003; Masuo and Lambert, 2011; Leo nska-Duniec et al., 2018e). The ADRB2 is a major lipolytic receptor in adipocytes and genetic polymorphisms in the gene may reduce lipolysis and predispose to obesity. The most frequent variants result in amino acid changes investigated in relation to obesity are at codon 16 (Arg16Gly, rs1042713) and codon 27 (Gln27Glu, rs1042714). The Gly16 allele has been associated with lower receptor density and hence reduced efficiency in comparison with the Arg16 allele, which may influence the propensity to higher BMI (Chou et al., 2012). In a study of overweight men participated in a 24-month weight loss program consisting of lowcalorie diet and everyday aerobic exercise showed a higher frequency of the Gly16 allele in men resistant to weight loss and those who regained body weight after successful initial weight loss at 6 months (Masuo et al., 2005). Numerous studies have also shown that the
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Glu27 allele may limit ADRB2 down-regulation and thus affect body weight (Lange et al., 2005). Corbala´n et al. (2002) described that women who were more active during their free time and were carriers of the Glu27 allele had higher body weight compared to noncarriers, suggesting that these women may be more resistant to losing weight (Corbala´n et al., 2002). The ADRB3 is the key receptor mediating catecholamine-stimulated thermogenesis in adipose tissue (Emorine et al., 1989). In humans low ADRB3 activity could promote obesity through decreased function in adipose tissue. A Trp64Arg (rs4994) variant in codon 64 of this gene has been associated with a tendency toward excess of body weight, insulin resistance, and type 2 diabetes (Clement et al., 1995; Widen et al., 1995). Many studies have shown increased BMI (average 0.28 kg/m2) in carriers of the Arg64 allele only among sedentary participants, but not in physically active subjects, where genotypic differences in BMI were not found (Fujisawa et al., 1998; Kurokawa et al., 2001; Marti et al., 2002). Other studies have shown that women with the Arg64 allele who participated in lifestyle intervention combining exercise and low-calorie diet lost less weight than women without the allele, suggesting that the Arg64 allele is connected with difficulty in losing weight through diet and training program (Sakane et al., 1997; Shiwaku et al., 2003). However, Phares et al. (2004) have shown that the Arg64 carriers experienced a great loss of fat mass and trunk fat following 24 weeks of aerobic exercise training compared to noncarriers and demonstrated an opposite allelic response to exercise.
11.2.7 ACSL1 gene Mouse studies have revealed that Acyl-CoA synthetase (ACSL) acts to convert long chain FA to acyl-CoA, and thus enhancing FA transport across the plasma membrane and providing substrates for most downstream pathways that metabolize FA. ACSL1 is one of five ACSL isoforms, each encoded by a separate gene. As such, ACSL1 is highly expressed in tissues that undergo high rates of metabolism, including muscle, adipose tissue, and liver cells (Mashek et al., 2006). The ACSL1 deficiency has been shown to reduce FA oxidation and increase glucose utilization (Ellis et al., 2010), negatively impacting metabolic health (Li et al., 2009). The current studies provide evidences in humans of ACSL1 SNPs associated with fasting glucose, diabetes, subclinical atherosclerosis and suggest links among these traits and acyl-CoA synthesis (Manichaikul et al., 2016). A SNP in this gene, rs9997745, has been shown to modify the risk of metabolic disease (Phillips et al., 2010). A second SNP, rs6552828, explained 6.1% of the variance in VO2max changes following aerobic training in the HERITAGE Family Study (Bouchard et al., 2011). In the latest not published study, a third SNP, rs116143768, was showed a genome-wide significant association (P ¼ 1.18 109) with fat loss following a 12-week aerobic training, with rare T allele carriers losing 31.4% of their fat
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mass, and CC homozygotes losing only 3.8%. From this evidence, it could be concluded that T allele may be considered as a favorable factor in the context of training-induced effects on body mass traits. However, more experimental studies are needed to establish the association between the ACSL1 SNPs and physical activity.
11.2.8 INSIG2 gene Insulin-induced gene 2 (INSIG2), located on chromosome 2q14, has been functionally linked to lipid metabolism, mostly due to its role in endogenous Chol and FA synthesis feedback inhibition. An endoplasmic reticulum membrane bound protein, encoded by INSIG2 gene, inhibits the proteolytic activation of sterol response element-binding proteins (SREPs) in response to Chol or insulin (Gong et al., 2006). Polymorphisms within INSIG2 have been associated with BMI, in particular, rs7566605 in the promotor region of this gene was linked to baseline subcutaneous fat mass in females and BMI (Lyon et al., 2007; Orkunoglu-Suer et al., 2008). In previous researches, the C allele was associated with a gain in subcutaneous fat mass following resistance training in males (Orkunoglu-Suer et al., 2008), and following a generalized health 1 year intervention in obese children (Reinehr et al., 2008). The results of the latest not published study performed on 116 Caucasian women fit with the previous research, as CC genotypes was associated with an increase in BMI in response to a 12-week aerobic training. These data suggest that exercise training may indeed lead to poorer health outcomes in INSIG2 C carriers, in that even limited localized exercise may trigger an increase in adiposity (Orkunoglu-Suer et al., 2008).
11.2.9 FABP2 gene Fatty acid-binding proteins (FABPs) are small intracellular polypeptides found in many tissues, involved in FA transfer and metabolism (Hsu and Storch, 1996) and encoded by a family of different genes. The fatty acid-binding protein 2 gene (FABP2) is located in the 4q28-4q31 chromosomal region, and encodes the intestinal form of FA-binding protein (IFABP), and is only expressed in the small intestine epithelial cells (enterocytes). IFABP protein plays a key role in the facilitation of cellular uptake and intracellular transport of dietary long-chain FA (Hertzel and Bernlohr, 2000; Furuhashi and Hotamisligil, 2008). Among the well-known SNPs associated with adiposity is the G to A polymorphism (rs1799883) of codon 54 in exon 2 results in the exchanges an alanine (Ala) in the small helical region of the protein for threonine (Thr). Various studies have suggested that this substitution is a functional mutation, which results in modified FA absorption, it could in turn affect the lipid metabolism and correlate with cardiovascular disease (CVD) risk (Baier et al., 1995). Because of the role of the Ala54Thr polymorphism of the FABP2 gene, it is considered that can modify interindividual responses to a particular diet and training program (Takakura et al., 2005; de Luis et al., 2006). Takakura et al. (2005) have
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showed that subjects with Ala/Thr and Thr/Thr genotype, adjusted resting metabolic rate (RMR) was significantly lower than the subjects with Ala/Ala genotype. Subjects with the Thr54 allele showed significantly greater waist circumference after diet and exercise therapy than subjects with Ala/Ala genotype (Takakura et al., 2005). This result may be supported by other studies, which described that carriers of the Thr54 allele, compared to Ala/Ala homozygotes, failed to have a significant reduction in fat mass, LDL levels, and leptin levels after a lifestyle modification program consisting of diet and physical activity (de Luis et al., 2006).
11.3 Conclusions Obesity is a multifactorial abnormality which have well-confirmed strong genetic basis but requires environmental influences caloric intake and physical activity to demonstrate. Numerous studies have shown the role of lifestyle including exercise and dietary factors in weight control (Qi and Cho, 2008). However, the problem is in defining the genes and polymorphisms related to obesity, and describing by which mechanisms they exert their effect. In view of the fact that DNA variants do not completely explain the heritability of obesity, more studies with appropriate designs and statistical power should be undertaken using the latest genomics methods in sequencing and genotyping, combined with epigenomics, transcriptomics, proteomics, and metabolomics (Qi and Cho, 2008; Perusse et al., 2013). Based on the literature, we speculate that in the near future, more studies should be also focused on identifying genetic markers referring to other obesity-related traits, for example, resistance to stress and pain, increased appetite and nutrient preference, as well as temperament. Another important question is the role of the gene variants on the characteristics and range of the body’s adaptive response to training. It is well known that the adaptive changes in the human body in response to regular physical exercises show great individual variance. Consequently, losing weight and changes in obesity-related traits in response to training programs may be more effective for some genotypes than others. However, the genetic background of these reactions still remains mostly unknown. One of the major aims of exercise genomics is to finally be able to define molecular markers, which by themselves or in combination with other biomarkers would make it possible to predict the benefits from exercise program or physically active lifestyle. Understanding the genetic background of physiological processes would have an enormous impact not only on individualization of exercise programs to be more efficient and safer, but also better recovery, traumatology, medical care, diet, supplementation, and many other areas (Perusse et al., 2013). Currently, some studies have tried to answer these questions, however, they still represent only the first steps towards a understanding of the genetic factors that influence obesity-related traits, and gene variants physical activity interactions, so continuing researches are necessary.
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Nevertheless, the search for genetic markers of functional response of human body to physical activities is very complicated and obtained results may be contradictory. There could be several reasons for this inconsistency: (i) heterogeneity between study populations, (ii) differences in daily food intake and nutrient preference, (iii) discrepancy in the volume, intensity and frequency of exercises and in methods of measuring physical activity, (iv) relatively small size of study group what may not possess sufficient statistical power for meaningful analysis and interpretation. The major problem in this kind of research is the experiment organization consisting of conduction of regular physical activity, food intake control, examination of genotype distribution, and measurement of body composition, physiological, and biochemistry parameters before and after the realization of training program. As a consequence, there is a limitation of the number of people participating in lasting few weeks or even months lifestyle interventions, and the results are hard to replicate in independent studies. The importance of genetic studies in modern sport increases every year. Consequently, it is significant to discuss the achievements, hopes, and fears associated with the rapid development of molecular biology in sport and medicine sciences.
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