Associations of markers in 11 obesity candidate genes with maximal weight loss and weight regain in the SOS bariatric surgery cases

A Corrigendum to this article was published on 10 July 2012

Abstract

Purpose:

To test whether DNA sequence variation in 11 obesity genes is associated with maximum weight loss and weight regain over 6 years of follow-up in bariatric surgery patients of the Swedish obese subjects (SOS) intervention study.

Methods:

A total of 1443 subjects were available for analysis (vertical banded gastroplasty: n=966, banding: n=293 and gastric bypass: n=184). Single-nucleotide polymorphisms (SNPs) from the following 11 genes were included: ADIPOQ, BDNF, FTO, GNB3, LEP, LEPR, MC4R, NR3C1, PPARG, PPARGC1A and TNF. General linear models were used to analyze associations between the SNPs and maximum weight loss and weight regain.

Results:

The average maximum weight loss was 33.7 kg (s.d. 13.3; min −95.5 kg, max +2.0 kg), which was reached 2.2 (s.d. 1.6) years after the surgery. Subjects regained approximately 12 kg (range 0.0–51.4 kg) by year 6. After correcting for multiple testing, the FTO SNP rs16945088 remained significantly associated with maximum weight loss (P=0.0002), as minor allele carriers lost approximately 3 kg less compared with common allele homozygotes. This association was particularly evident in the banding surgery patients (P<0.0001), whereas no significant association was found in the gastric bypass subjects. No other SNPs were associated with maximum weight loss. Furthermore, no SNPs were significantly associated with weight regain.

Conclusion:

The FTO SNP rs16945088 was associated with maximum weight loss after banding surgery. We found no evidence that obesity-risk SNPs in FTO or other obesity candidate genes derived from genome-wide association studies are associated with maximum weight loss or weight regain over 6 years of follow-up in bariatric surgery patients. The potential role of other obesity genes remains to be investigated.

Introduction

Obesity is associated with increased morbidity and mortality, as well as elevated risk factors for cardiovascular diseases.1 Thus, preventing and treating obesity has become a major public health goal. Despite all preventive and therapeutic attempts, recidivism after weight reduction is nearly universal. Bariatric surgery has been considered to be the most reliable method of accomplishing long-term weight loss.2, 3 In addition to weight loss, improvement or long-term remission of comorbidities, particularly type 2 diabetes, hypertension and dyslipidemia, has been reported after bariatric surgery.4 Decreased mortality rates, particularly deaths from diabetes, heart disease, and cancer, as well as decreased incidence of cancer in women have also been reported.2, 5, 6

Although bariatric surgery produces substantial short-term weight loss in the majority of patients, after reaching maximum weight loss many patients begin to gradually regain weight over several years, and individual weight losses at term vary considerably.7 As it is neither possible nor desirable to surgically treat all obese individuals, it is important to establish methods that can help health-care providers identify patients who will benefit the most from treatment. Lancaster et al.8 reported that weight loss in 100 patients, 13–15 years after gastric bypass surgery, ranged from +13.6 to −93.6 kg, demonstrating the marked variability in surgery-induced long-term weight loss. This high degree of variability in postoperative weight loss may be caused in part by a genetic predisposition to resist weight loss. Indeed, previous studies have suggested that response to long-term negative energy balance is a heritable trait. Seven pairs of young adult male identical twins completed a negative energy balance protocol during which they exercised twice a day, on 9 out of 10 days, over a period of 93 days while being kept on a constant daily energy and nutrient intake.9 There was 6.8 times (F ratio) more variance for the changes in body weight between genotypes (between pairs) than within genotypes (within pairs) despite the large individual differences in the response, suggesting that there is a genetic component in the response to long-term negative energy balance. These observations were strongly supported by a weight-loss experiment involving 14 pairs of premenopausal female identical twin pairs who were subjected to 28 days of a very-low-calorie diet (1.6 MJ day−1) in an inpatient metabolic unit.10 There was about 13 times more variability between pairs than within pairs for the changes in body weight induced by the low-calorie diet.

Obesity is known to be a complex trait, influenced by multiple genetic and environmental factors. To date, 17 common obesity loci have been identified through genome-wide association studies (GWASs)11 and associations have been confirmed for several candidate genes.12 However, it is unclear whether DNA sequence variation in these same genes affects the outcome of weight loss interventions. Therefore, we tested whether single-nucleotide polymorphisms (SNPs) in 11 obesity candidate genes that have shown associations with obesity-related phenotypes in at least five studies were associated with maximum weight loss and with weight regain over 6 years of follow-up in bariatric surgery patients of the Swedish obese subjects (SOS) intervention study.

Materials and methods

Design of the SOS study

The SOS study has previously been described in detail.4 In brief, the SOS study is a prospective, non-randomized clinical trial of the health effects of intentional weight reduction in the severely obese. Inclusion criteria included age (37–60 years at accrual) and body mass index (BMI 34 kg m−2 for males and 38 kg m−2 for females). Exclusion criteria, described elsewhere,13 were minimal and aimed at ensuring that subjects in the surgery group could tolerate the operation. Between 1987 and 2001, a total of 4047 severely obese subjects were included from the registry study and from waiting lists at surgical departments. Among those, 2010 eligible subjects desiring surgery constituted the surgery group, whereas the matched control group of 2037 subjects was offered conventional treatment at their primary health-care center. Surgical treatment included vertical banded gastroplasty (n=1368), banding (n=377) or gastric bypass (n=265). Baseline examinations took place 4 weeks before surgery and the intervention study began on the day of the surgically treated subject's operation. Follow-up examinations (at 0.5, 1, 2, 3, 4, 6, 8 and 10 years) were conducted in relation to the date of surgery. Seven regional ethics review boards approved the study protocol. Informed consent was obtained from all subjects.

The present study sample was comprised of subjects from the surgical treatment group only. Of those, only subjects with full genotype and complete body weight data from all follow-up visits during the first 6 years post-surgery were included. A total of 1443 subjects were available for analysis by the end of 2007 (vertical banded gastroplasty: n=966, banding: n=293 and gastric bypass: n=184).

Genes and SNP selection

SNPs (n=236 total) from the following genes were selected for the present study: adiponectin, C1Q and collagen domain containing (ADIPOQ, n=16 SNPs); brain-derived neurotrophic factor (BDNF, n=14); fat mass and obesity associated (FTO, n=25); guanine nucleotide binding protein (G protein), beta polypeptide 3 (GNB3, n=16); leptin (LEP, n=9); leptin receptor (LEPR, n=33); melanocortin 4 receptor (MC4R, n=17); nuclear receptor subfamily 3, group C, member 1 (NR3C1, n=21); peroxisome proliferator-activated receptor gamma (PPARG, n=26); peroxisome proliferator-activated receptor gamma, coactivator 1 alpha (PPARGC1A, n=49); and tumor necrosis factor (TNF, n=10). These genes were selected based on their established and replicated associations with obesity-related phenotypes. The BDNF, FTO and MC4R loci have been associated with obesity in GWAS reports, with multiple studies validating the associations in FTO and MC4R and animal studies supporting the function of BDNF in obesity.11 According to the 2005 version of the Human Obesity Gene Map, six of the genes have shown associations in 10 or more studies, including PPARG (30 studies), LEPR (16), GNB3 (14), ADIPOQ (11), LEP (11) and NR3C1 (10), while TNF and PPARGC1A have shown independent associations with obesity-related phenotypes in nine and four studies, respectively.12 The tagSNPs were selected from the Caucasian data set of the International HapMap consortium14 (data release 23 January 2008) using the pairwise algorithm of the Tagger program.15 The pairwise linkage disequilibrium (LD) threshold for the LD clusters was set to r20.85 and minimum minor allele frequency to 10%.

Genotyping

The SNPs were genotyped using the Illumina (San Diego, CA, USA) GoldenGate chemistry and Sentrix Array Matrix technology on BeadStation 500GX. Genotype calling was done with the Illumina BeadStudio software and each call was confirmed manually. For quality control purposes, five CEPH control DNA samples (NA10851, NA10854, NA10857, NA10860 and NA10861; all samples included in the HapMap Caucasian panel) were genotyped in triplicate. Concordance between the replicates as well as with genotypes from the HapMap database was 100%.

Definition of maximum weight loss and weight regain phenotypes

Maximum weight loss was calculated as the difference between pre-surgery body weight and the lowest body weight recorded on the check-up visits 1, 2, 3, 4 and 6 years post-surgery. Weight regain was defined as the difference between body weight recorded at year 6 follow-up visit and the lowest body weight recorded on year 1, 2, 3, 4 and 6 check-ups.

Statistical analysis

All statistical analyses were performed with SAS version 9.1 (SAS Institute, Cary, NC, USA). Means and s.d.'s were computed for all characteristics at baseline by surgery group. Differences in continuous and categorical variables between surgery groups were assessed using t-tests and chi-square tests, respectively. Hardy–Weinberg equilibrium was tested by comparing observed and expected genotype frequencies using the ALLELE procedure in SAS. Because of the large number of tested SNPs, a Bonferroni-corrected (0.05/265) P-value threshold of P=0.0002 was used to indicate deviation from Hardy–Weinberg equilibrium. The pairwise LD among the SNPs was assessed using the ldmax program available in the GOLD software package (http://www.sph.umich.edu/csg/abecasis/GOLD/download/).16

General linear models (PROC GLM in SAS) were used to test associations between the SNPs and maximum weight loss and weight regain. In the maximum weight loss models, each SNP was tested individually with baseline values of age and body weight, sex, surgery type, and time point of maximum weight loss included as covariates. In the weight regain models, each SNP was tested individually with baseline age, minimum weight, sex, surgery type and weight regain time included as covariates. As patients with gastric bypass showed greater weight loss and lesser weight regain than those operated with banding surgery, we also ran analyses stratified by the type of surgery: banding procedures group (vertical banded gastroplasty and banding) or gastric bypass patients only. When the above models were tested in the gastric bypass group only, type of surgery was no longer included as a covariate. Genotype effect size (R2) was defined as the proportion of total phenotypic variance explained by the genotype.

As multiple SNPs were used in the association analyses, we applied a multiple testing correction as proposed by Nyholt.17 Briefly, the method uses spectral decomposition of matrices of pairwise LDs (r) to estimate the variance of eigenvalues. The effective number of independent SNPs for each candidate gene can be calculated based on the ratio of the observed eigenvalue variance and its maximum value. The effective number of SNPs (sum of all candidate genes) can then be used to adjust the standard α level (for example, 5%). Thus, in our study, the corrected threshold for statistical significance was set to P<0.00033 as the total effective number of SNPs was 150.

Results

The gene-specific pairwise LDs among all the SNPs can be found in Supplementary Table S1. The allele frequency distributions among the SOS SNPs were similar to those previously reported in obese Caucasian populations,18 but differed from those previously reported in non-obese Caucasians. For example, frequencies of the obesity risk alleles of FTO SNPs rs8050136 and rs1121980 were 0.488 and 0.512, respectively, in SOS subjects, while the respective frequencies in non-obese Caucasian subjects from the HERITAGE Family Study19 were 0.367 and 0.388, respectively (P<3 × 10−10). A similar pattern was observed with three other SNPs derived from the obesity GWAS reports (Supplementary Table S2).

The basic characteristics of SOS subjects with complete data are summarized by surgical procedure in Table 1. Subjects who underwent gastric bypass surgery were heavier at baseline compared with subjects who were operated with banding procedures. The average maximum weight loss was approximately 34 kg (33.7±13.3 kg; range −95.5 to +2.0 kg) in the total sample, which corresponded to a 28% weight change (27.9±9.7%; range −60.4 to +1.9%). Subjects who underwent gastric bypass surgery experienced a significantly larger maximum weight loss and percent weight change than did the other surgery groups, whose mean values did not differ (Table 1). Overall, the subjects reached maximum weight loss approximately 2 years (2.2±1.6 years) after surgery, and this value did not differ between the gastric bypass and banding procedures groups. The average weight regain in the total sample was approximately 12 kg (11.8±9.3 kg; range 0.0–51.4 kg). Subjects who underwent gastric bypass regained significantly less weight than did subjects operated with vertical banded gastroplasty (Table 1).

Table 1 Basic characteristics of SOS subjects with DNA and follow-up data for year 6 (n=1443) by surgery group

Altogether, 12 SNPs in the ADIPOQ, FTO, LEP, LEPR, MC4R, PPARGC1A and TNF gene loci were nominally (P<0.05) associated with maximum weight loss (Table 2). After correcting for multiple testing, only the FTO SNP rs16945088 remained statistically significantly associated with maximum weight loss, as the maximum weight loss for minor allele carriers was approximately 3 kg less compared with common allele homozygotes (Figure 1). The association between rs16945088 and maximum weight loss was particularly evident in the patients who were operated with banding surgery (P<0.0001), while no association was found in the gastric bypass group (Figure 1). An LD plot and the associations with maximum weight loss and weight regain for all of the FTO SNPs are shown in Supplementary Figure S1.

Table 2 SNPs showing nominal associations with maximum weight loss or weight regain after bariatric surgery in the total sample of SOS
Figure 1
figure1

Association of FTO rs16945088 genotype with maximum weight loss experienced after bariatric surgery in Swedish obese subjects. Associations are shown in the total sample, as well as stratified by the surgery technique (banding procedures and gastric bypass). The number of subjects in each group is indicated inside each histogram bar.

SNPs in BDNF, GNB3, NR3C1 and PPARG genes were not associated with maximum weight loss (Supplementary Table S3). Thirteen SNPs from GNB3, LEP, FTO, NR3C1, PPARG and PPARGC1A showed nominal associations with weight regain in the total sample (Table 2), but none of them remained significant after correction for multiple testing. Furthermore, none of the SNPs previously associated with body weight phenotypes in GWAS reports20, 21, 22, 23 were associated with either maximum weight loss or weight regain in the present study (Table 3). The associations between all 236 SNPs and maximum weight loss and weight regain are summarized in Supplementary Tables S3 and S4.

Table 3 The association (P-value) of selected SNPsa with maximum weight loss and weight regain after bariatric surgery in the total sample of SOS subjects and by banding procedures groups or gastric bypass subjects only

Discussion

The major finding of this study is that the minor allele at the FTO rs16945088 locus is associated with less weight loss after bariatric surgery. In SOS subjects who underwent banding procedures, the maximum weight loss experienced by FTO rs16945088 G-allele carriers was 4.1 kg less compared with common allele homozygotes (A/A). The minor allele frequency of the FTO rs16945088 locus was just over 5% in the SOS bariatric subjects. Estimates from the International HapMap data show the minor allele frequency to be approximately 8% in European Caucasians (CEU).14 Additionally, the FTO SNP rs16945088 seems to be independent of the previously identified FTO obesity risk markers, as indicated by low pairwise LDs (r2<0.055) and the fact that the SNPs are located in different haplotype blocks than the obesity-risk SNPs (Supplementary Figure S1).

None of the gene variants were associated with weight regain 6 years after bariatric surgery. Although we did not find any associations between DNA sequence variation and longitudinal weight changes in SOS bariatric surgery patients, we found significant differences in allele frequencies when compared with non-obese populations: prevalence of the obesity risk-promoting alleles was consistently higher among the SOS subjects. Thus, the effect of increased frequency of obesity-risk alleles on body weight is still observed in the SOS cohort. These results may suggest that the mechanisms and genetic factors involved in weight loss and weight regain after bariatric surgery may differ from those involved in the development of obesity and weight maintenance.

FTO variants and weight changes after lifestyle interventions

We found that FTO rs8050136 genotype was not associated with either maximum weight loss or weight regain after bariatric surgery in the present study. In cross-sectional analyses of almost 1500 non-diabetic subjects of the Tübingen Family Study, the A allele of FTO SNP rs8050136 was associated with a higher BMI and a higher prevalence of obesity.24 However, there was no influence of the FTO rs8050136 polymorphism on changes in body weight 9 months into the Tübingen Lifestyle Intervention Program (n=204), an intervention aimed at a weight loss of 5% through dietary restrictions and 3 h of weekly exercise.24 After the lifestyle intervention, risk allele carriers lost an equal amount of weight as the non-carriers, but still had a higher BMI compared with non-risk allele homozygotes. Similarly, in the Finnish Diabetes Prevention Study, an FTO gene variant (rs9939609) was associated with baseline BMI in women, but did not modify weight change achieved by long-term (4 years) lifestyle intervention.25 The lack of association between FTO rs9939609 genotype and weight loss over time in lifestyle interventions was replicated in analyses of 1-year follow-up data in the Diabetes Prevention Program26 and in a study of German obese children and adolescents examined 1 year after entering an outpatient obesity intervention program.27

On the other hand, results from the HERITAGE Family Study show that sequence variation in the FTO gene was associated with exercise training-induced changes in body composition. In the sedentary state (baseline), FTO rs8050136 A/A homozygotes were significantly heavier and fatter than the other genotypes in Caucasian men.19 Furthermore, FTO rs8050136 genotype was associated with body fat responses to 20 weeks of endurance training in HERITAGE Caucasians (n=481), as carriers of the C allele showed three times greater fat mass and percent body fat losses than A/A homozygotes (P<0.0005).19 Overall, the FTO rs8050136 genotype explained 2% of the variance in adiposity changes.

FTO SNPs rs8050136 and rs9939609 tag the same cluster of 37 SNPs (pairwise r2>0.8 between SNPs in HapMap CEU) in Caucasians, including five of the FTO SNPs typed in the SOS cohort. According to the data from HapMap14 in Caucasians, the significant FTO rs16945088 marker found in the present study is not in LD with any of the previously described FTO common variants associated with obesity (pairwise r2<0.5 between SNPs in HapMap CEU).

Variation in other obesity candidate genes and weight changes after lifestyle interventions

Numerous replicated associations of gene variants with obesity-related phenotypes have been reported.11, 12 However, the associations of these variants with weight reduction and weight regain over time have been examined less extensively. Although associated with BMI and prevalence of obesity at baseline, the MC4R rs17782313 polymorphism was not associated with body weight changes induced by a 9-month lifestyle intervention aimed at a weight loss of 5%.28 In the present study, MC4R rs17782313 was not associated with either maximum weight loss or weight regain 6 years after bariatric surgery. The Pro12Ala polymorphism of the PPARG gene (rs1801282) was associated with weight regain but not weight loss in 70 postmenopausal women who were treated with a hypocaloric diet for 6 months. The weight regain after 12 months of follow-up was 2.6 kg greater in women with the Ala allele compared with women homozygous for the Pro allele.29 Conversely, the Pro12Ala polymorphism was associated with weight loss after 3 years of lifestyle intervention in 225 subjects with impaired glucose tolerance in the Finnish Diabetes Prevention Study, as subjects homozygous for the Ala allele (n=6) experienced an over 2-fold greater weight loss compared with subjects with other genotypes.30 In 95 middle-aged and overweight Japanese women, six PPARG SNPs (rs2959272, rs1386835, rs709158, rs1175540, rs1175544 and rs1797912) were associated with weight loss after a 14-week intervention consisting of calorie restriction (1200 kcal day−1).31 The rs1175544 marker had the strongest association, accounting for 7% of the total weight loss variance, while rs1801282 (Pro12Ala) was not associated with weight loss in these women. The PPARG Pro12Ala polymorphism showed no associations with maximal weight loss or weight regain after 6 years in the current study. In addition, variation in the adiponectin (ADIPOQ) and leptin receptor (LEPR) loci was reported to be associated with weight loss during a 3-year diabetes prevention trial with acarbose.32, 33 We found no association of ADIPOQ or LEPR SNPs with maximal weight loss or weight regain 6 years after bariatric surgery. These results suggest that common variants in obesity candidate genes exhibit inconsistent effects on the success of lifestyle modification in achieving weight loss, with several studies showing no association.

Variation in obesity candidate genes and weight changes after bariatric surgery

Few studies have examined whether common variants of obesity candidate genes are associated with weight changes achieved through bariatric surgery. Aside from the FTO rs16945088 marker, we found no associations of sequence variants in 10 other obesity candidate genes with maximum weight loss and weight regain over a 6-year period after bariatric surgery in SOS subjects. A possible explanation for the mostly negative results is that a different set of genes contributes to inter-individual differences in bariatric surgery-induced weight loss than those predisposing to weight gain over time and the development of obesity. In addition, it is also possible that SOS may lack the necessary statistical power to show such associations. However, the SOS study is the largest longitudinal bariatric surgery study and is larger than most of the lifestyle intervention studies referred to above, wherein a few significant associations were found.

It is important to note that previous studies have shown that patients experienced the most dramatic weight loss during the first 6 months after laparoscopic adjustable gastric banding (LAGB), as they were most compliant with the prescribed hypocaloric diet during this time period.34 Thus, the physiological and genetic mechanisms involved may not be the same as those for weight changes after surgery over longer periods of time. A study of 167 morbidly obese subjects found significant associations of G-174C interleukin-6 (rs603573) and G-866A uncoupling protein 2 (UCP2, rs1800795) genotype with weight loss 6 months after (LAGB) surgery.35 After the 6-month follow-up, the G-174G interleukin 6 genotype experienced a significantly greater percent BMI change (−17.5%±7.1) than G-174C (−15.5%±6.5) and C-174C genotypes (−12.4%±6.5), and the A-866A UCP2 genotype showed a significantly greater percent BMI change (−20.1%±6.0) compared with the G-866G (−15.3%±7.1) and G-866A (−15.7%±6.0) genotypes, respectively.35 Weight loss was lower in carriers of Gly972Arg insulin receptor substrate-1 (IRS1) genotype (−12.9%±4.9 BMI change) than Gly972Gly carriers (−16.4%±7.0), but not statistically significant (P=0.06). No differences in weight loss were found between genotypes of the peroxisome proliferator-activated receptor gamma (PPARG) Pro12Ala polymorphism (rs1801282).35 We found no association between the PPARG Pro12Ala polymorphism and weight loss (P=0.6084) or weight regain (P=0.7318) over 6 years of follow-up in SOS.

A study of 300 severely obese subjects who underwent LAGB found that women who carried eight MC4R variants lost less weight 3 years after surgery than non-carriers.36 Conversely, polymorphisms from the guanine nucleotide binding protein alpha stimulating activity polypeptide 1 (GNAS1) and beta polypeptide 3 (GNB3) genes were not associated with 3-year weight loss in these subjects.37 Lastly, a study of 77 patients receiving LAGB and 227 receiving laparoscopic mini-gastric bypass found that UCP2 rs660339 (Ala55Val) was associated with LAGB-induced weight loss: T allele carriers lost more weight at 12 (4 BMI units more) and 24 months (3 BMI units more) compared with patients with the CC genotype.38 No association was found in laparoscopic mini-gastric bypass patients despite experiencing a greater weight loss than LAGB patients. These results suggest that the physiological and genetic factors influencing weight loss after bariatric surgery may differ by surgery type. It remains to be seen whether the genetic factors influencing weight change are similar between various weight loss methods such as exercise, diet and bariatric surgery.

Conclusions

The reasons for the high variability in body weight response to bariatric surgery are unknown, and the failure of surgical techniques, particularly banding procedures, may be somewhat attributed to poor compliance with dietary instructions.39, 40 However, the possibility that genetic factors affect the success of bariatric surgery remains unsettled. A reliable preoperative method of profiling patients who will successfully sustain weight loss has not been established. Such a prediction would allow for more optimal outcomes in patients, as well as allow others to avoid unnecessary adverse effects and costs. We found evidence that the rs16945088 marker in the FTO gene locus is associated with maximum weight loss after gastric banding surgery. Variants in 10 other obesity candidate genes showed no associations with weight loss or weight regain in the SOS cohort. Thus, the current evidence is mixed and inconclusive, and it is possible that the genes involved in weight loss and regain are different from those identified as obesity genes in cross-sectional studies. Further studies are needed on multiple candidate and novel genes, as well as environmental factors predictive of the surgical outcomes in large numbers of bariatric surgery patients.

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Acknowledgements

This work was supported by grants from the Coypu Foundation, the Swedish Research Council (K2010-55X-11285-13), the Swedish foundation for Strategic Research to Sahlgrenska Center for Cardiovascular and Metabolic Research, the Swedish Diabetes foundation and the Swedish federal government under the LUA/ALF agreement. C Bouchard is partially supported by the George A Bray Chair in Nutrition.

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Correspondence to C Bouchard.

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Sarzynski, M., Jacobson, P., Rankinen, T. et al. Associations of markers in 11 obesity candidate genes with maximal weight loss and weight regain in the SOS bariatric surgery cases. Int J Obes 35, 676–683 (2011). https://doi.org/10.1038/ijo.2010.166

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Keywords

  • severe obesity
  • polymorphism
  • genetics
  • longitudinal study
  • intervention

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