Lack of Association Between a Common Polymorphism Near the INSIG2 Gene and BMI,Myocardial Infarction,and Cardiovascular Risk Factors

Epidemiological studies revealed an increasing prevalence of and a steep increase in obesity, a risk factor for cardiovascular disease. Because significant influence of a polymorphism, rs7566605, near the INSIG2 gene on BMI has been shown in the general population and in obesity cohorts, we hypothesized that this polymorphism might also act through an elevated BMI on the development of coronary artery disease (CAD) or myocardial infarction (MI). We pursued two strategies: First, the polymorphism rs7566605 was investigated for association with BMI, CAD/MI, and cardiovascular risk factors in a large German cohort at high risk for CAD and MI (n = 1,460 MI patients) as compared to unrelated healthy controls (n = 1,215); second, we extended our analyses on the families of MI patients and performed family‐based association testing (n = 5,390 individuals). The polymorphism rs7566605 was analyzed using TaqMan technology. No deviation from Hardy–Weinberg equilibrium could be observed, and the call rate was 98.2%. No significant associations of rs7566605 with CAD/MI, BMI, and classical cardiovascular risk factors could be detected in the full sample size or in the subgroups. A total of 6,878 individuals were investigated in a population of German MI patients and their family members. Although the number of individuals was large enough, no influence of the rs7566605 INSIG2 polymorphism was detected on BMI and CAD/MI. We therefore conclude that in our sample the SNP rs7566605 near the INSIG2 gene does not influence BMI and is not associated directly with CAD/MI or indirectly through cardiovascular risk factors.     

INSIG2 SNPs Associated With Obesity and Glucose Homeostasis Traits in Hispanics: The IRAS Family Study

The genome‐wide association study by Herbert et al. identified the INSIG2 single‐nucleotide polymorphism (SNP) rs7566605 as contributing to increased BMI in ethnically distinct cohorts. The present study sought to further clarify the matter, by testing whether SNPs of INSIG2 influenced quantitative adiposity or glucose homeostasis traits in Hispanics of the Insulin Resistance Atherosclerosis Family Study (IRASFS). Using a tagging SNP approach, rs7566605 and 31 additional SNPs were genotyped in 1,425 IRASFS Hispanics. SNPs were tested for association with six adiposity measures: BMI, waist circumference (WAIST), waist‐to‐hip ratio (WHR), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and VAT to SAT ratio (VSR). SNPs were also tested for association with fasting glucose (GFAST), fasting insulin (FINS), and three measures obtained from the frequently sampled intravenous glucose tolerance test: insulin sensitivity (S_I), acute insulin response (AIR), and disposition index (DI). Most prominent association was observed with direct computed tomography (CT)‐measured adiposity phenotypes, including VAT, SAT, and VSR (P values range from 0.007 to 0.044 for rs17586756, rs17047718, rs17047731, rs9308762, rs12623648, and rs11673900). Multiple SNP associations were observed with all glucose homeostasis traits (P values range from 0.001 to 0.031 for rs17047718, rs17047731, rs2161829, rs10490625, rs889904, and rs12623648). Using BMI as a covariate in evaluation of glucose homeostasis traits slightly reduced their association. However, association with adiposity and glucose homeostasis phenotypes is not significant following multiple comparisons adjustment. Trending association after multiple comparisons adjustment remains suggestive of a role for genetic variation of INSIG2 in obesity, but these results require validation.     

Association of INSIG2 Polymorphism with Overweight and LDL in Children

Background

Dyslipidemia and overweight are common issues in children. Identifying genetic markers of risk could lead to targeted interventions. A polymorphism of SNP rs7566605 near insulin-induced gene 2 (INSIG2) has been identified as a strong candidate gene for obesity, through its feedback control of lipid synthesis.

Objective

To identify polymorphisms in INSIG2 which are associated with overweight (BMI ≥ 85% for age) and dyslipidemia in children. Hypothesis: The C allele of rs7566605 would be significantly associated with BMI and LDL.

Design/Methods

We genotyped 15 SNPs in/near INSIG2 in 1,058 healthy children (53% non-Hispanic white (NHW), 37% overweight) participating in a school based study. Genotype was compared with BMI and lipid markers, adjusting for age, gender, and puberty.

Results

We found a significant association between the SNP rs12464355 and LDL in NHW children, p < 0.001. The G allele is protective (lower LDL). A different SNP was associated with overweight in NHW: rs17047757. SNP rs7566605 was not associated with overweight or lipid levels.

Conclusions

We identified novel genetic associations between INSIG2 and both overweight and LDL in NHW children. Polymorphisms in INSIG2 may be important in the development of obesity through its effects on lipid regulation.     

The association of a SNP upstream of INSIG2 with body mass index is reproduced in several but not all cohorts

A SNP upstream of the INSIG2 gene, rs7566605, was recently found to be associated with obesity as measured by body mass index (BMI) by Herbert and colleagues. The association between increased BMI and homozygosity for the minor allele was first observed in data from a genome-wide association scan of 86,604 SNPs in 923 related individuals from the Framingham Heart Study offspring cohort. The association was reproduced in four additional cohorts, but was not seen in a fifth cohort. To further assess the general reproducibility of this association, we genotyped rs7566605 in nine large cohorts from eight populations across multiple ethnicities (total n = 16,969). We tested this variant for association with BMI in each sample under a recessive model using family-based, population-based, and case-control designs. We observed a significant (p < 0.05) association in five cohorts but saw no association in three other cohorts. There was variability in the strength of association evidence across examination cycles in longitudinal data from unrelated individuals in the Framingham Heart Study Offspring cohort. A combined analysis revealed significant independent validation of this association in both unrelated (p = 0.046) and family-based (p = 0.004) samples. The estimated risk conferred by this allele is small, and could easily be masked by small sample size, population stratification, or other confounders. These validation studies suggest that the original association is less likely to be spurious, but the failure to observe an association in every data set suggests that the effect of SNP rs7566605 on BMI may be heterogeneous across population samples.     

Replication of Association Between a Common Variant Near Melanocortin‐4 Receptor Gene and Obesity‐related Traits in Asian Sikhs

Recent genome‐wide association studies (GWAS) in Asian Indians reported strong associations of variants near melanocortin‐4 receptor (MC4R) and MLX interacting protein‐like (MLXIPL) genes with insulin resistance and several obesity‐related quantitative traits (QTs). Here, we evaluated the association of two variants (rs12970134 and rs4450508) near MC4R and a nonsynonymous (Gln241His) variant (rs3812316) in MLXIPL gene with type 2 diabetes (T2D) and obesity‐related QTs in our case–control cohort (n = 1,528; 745 T2D cases and 783 controls) from a Sikh population from North India. We have successfully replicated the association of MC4R (rs12970134) with BMI (P = 0.0005), total weight (WT) (P = 0.001), and waist circumference (WC) (P = 0.001). These associations remained significant after controlling for multiple testing by applying Bonferroni's correction. However, our data did not confirm the association of rs3812316 in the MLXIPL gene with triglyceride (TG) levels. These observations demonstrate that the genetic variation in MC4R locus can have a moderate contribution in the regional fat deposition and development of central obesity in Asian Indians.     

Low‐density lipoprotein receptor‐related protein 1 variant interacts with saturated fatty acids in puerto ricans

Objective:

Low‐density lipoprotein receptor‐related protein 1 (LRP1) is a multifunctional endocytic receptor that is highly expressed in adipocytes and the hypothalamus. Animal models and in vitro studies support a role for LRP1 in adipocyte metabolism and leptin signaling, but genetic polymorphisms have not been evaluated for obesity in people.

Design and Methods:

We examined whether dietary fats (eg., saturated, polyunsaturated) modulated the association of LRP1 rs1799986 with anthropometric traits. We studied a population‐based sample of Puerto Ricans (n = 920, aged 45–74 y) living in the Boston area.We examined whether dietary fats (eg., saturated, polyunsaturated) modulated the association of LRP1 rs1799986 with anthropometric traits. We studied a population‐based sample of Puerto Ricans (n = 920, aged 45–74 y) living in the Boston area.

Results:

In multivariable linear regression models, we dichotomized saturated fat intake and found significant interaction terms between total saturated fatty acids and LRP1 rs1799986 genotype for BMI (P=0.006) and hip (P = 0.002). High intake of saturated fat was associated with higher BMI (P = 0.001), waist (P = 0.008) and hip (P=0.003) in minor allele carriers (CT+TT) compared to CC participants. Further analysis of dichotomized individual saturated fatty acids revealed that interactions were strongest for two individual longer chain fatty acids. High intake of palmitic acid (C16:0; P = 0.0007) and high stearic acid intake (C18:0; P = 0.005) were associated with higher BMI in T carriers. Interactions were not detected for polyunsaturated fatty acids.

Conclusions:

Gene–diet interactions at the LRP1 locus support the hypothesis that susceptibility to weight gain based on saturated fatty acids is modified by genotype and possibly by chain length. These results may facilitate the development of a panel of genetic candidates for use in optimizing dietary recommendations for obesity management.     

Apolipoprotein A5 and Lipoprotein Lipase Interact to Modulate Anthropometric Measures in Hispanics of Caribbean Origin

Apolipoprotein A5 (APOA5) and lipoprotein lipase (LPL) proteins interact functionally to regulate lipid metabolism, and single‐nucleotide polymorphisms (SNPs) for each gene have also been associated independently with obesity risk. Evaluating gene combinations may be more effective than single SNP analyses in identifying genetic risk, but insufficient minor allele frequency (MAF) often limits evaluations of potential epistatic relationships. Populations with multiple ancestral admixtures may provide unique opportunities for evaluating genetic interactions. We examined relationships between LPL m107 (rs1800590) and APOA5 S19W (rs3135506) and lipid and anthropometric measures in Caribbean origin Hispanics (n = 1,019, aged 45–75 years) living in the Boston metropolitan area. Significant interaction terms between LPL m107 and APOA5 S19W were observed for BMI (P = 0.003) and waist circumference (P = 0.019). Higher BMI (P = 0.001), waist (P = 0.011) and hip (P = 0.026) circumference were observed in minor allele (G) carriers for LPL m107 who also carried the APOA5 S19W minor allele (G). Additionally, extreme obesity (BMI ≥ 40 kg/m²) risk was higher (odds ratio = 4.02; 95% confidence interval: 1.81–8.91; global P = 0.008) for minor allele carriers for both SNPs (LPL TG+GG, APOA5 CG+GG) compared to major allele carriers for both SNPs. In summary, we identified significant interactions for APOA5 S19W and LPL m107 for obesity in Caribbean Hispanics. Population‐specific MAFs increase the difficulties of replicating gene–gene interactions, but may support the hypothesis that combinations of frequencies in selected genes could heighten obesity susceptibility in a given population. Analyses of gene–gene interactions may improve understanding of genetically based obesity risk, and underscore the need for further study of groups with multiple ancestral admixtures.     

Body adiposity index and other indexes of body composition in the SAPHIR study: Association with cardiovascular risk factors

Objective:

The accuracy of anthropometric surrogate markers such as the body adiposity index (BAI) and other common indexes like the body mass index (BMI), waist‐to‐hip ratio (WHR) and waist‐to‐height ratio (WHtR) to predict metabolic sequelae is essential for its use in clinical practice.

Design and Methods:

Thus, we evaluated the strength of BAI and other indexes to relate with anthropometric parameters, adipocytokines, blood lipids, parameters of glucose‐homeostasis and blood pressure in 1,770 patients from the Salzburg Atherosclerosis Prevention Program in Subjects at High Individual Risk (SAPHIR) study in a crosssectional design. Measurements were BAI, BMI, WHR, WHtR, abdominal subcutaneous and visceral adipose tissue (aSAT and VAT), total body adipose tissue mass, body weight, waist‐ and hip circumference (WC and HC), leptin, adiponectin, high‐density lipoprotein‐cholesterol (HDL‐C), low‐density lipoprotein‐cholesterol (LDL‐C), triglycerides (TG), fasting plasma glucose, fasting plasma insulin, the homeostasis model assessment of insulin resistance (HOMAIR), systolic and diastolic blood pressure.

Results and Conclusions:

BAI was significantly associated with leptin and HC. We conclude that BAI was the best calculator for leptin. BAI was inferior to BMI to predict anthropometric parameters other than HC, adiponectin, blood lipids, parameters of glucose homeostasis, and blood pressure in this cross‐sectional study.     

Novel Obesity Risk Loci Do Not Determine Distribution of Body Fat Depots: A Whole‐body MRI/MRS study

A recent meta‐analysis of genome‐wide association studies has identified six new risk‐loci for common obesity. We studied whether these risk loci influence the distribution of body fat depots. We genotyped 1,469 nondiabetic subjects for the single‐nucleotide polymorphisms (SNPs) TMEM18 rs6548238, KCTD15 rs11084753, GNPDA2 rs10938397, SH2B1 rs7498665, MTCH2 rs10838738, and NEGR1 rs2815752. We assessed BMI, waist circumference, total body fat, and lean body mass (bioimpedance). All subjects underwent an oral glucose tolerance test (OGTT) for estimation of insulin sensitivity. In 332 subjects, we measured total adipose tissue (TAT), visceral adipose tissue (VAT), nonvisceral adipose tissue (NVAT), liver fat content, and intramyocellular lipids (IMCLs) using whole‐body magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS). In the dominant inheritance model, the risk alleles of TMEM18 rs6548238 and MTCH2 rs10838738 were nominally associated with higher BMI (P = 0.04, both). The risk allele of TMEM18 rs6548238 was additionally associated with higher waist circumference and total body fat (P ≤ 0.03), the risk allele of NEGR1 rs2815752 with higher waist circumference (P = 0.05) and unexpectedly with lower BMI (P = 0.01). In the MR cohort, we found an association of the risk allele of SH2B1 rs7498665 with higher VAT (P = 0.009) and of GNPDA2 rs10938397 with increased IMCLs (P = 0.03). After Bonferroni correction for multiple comparisons (corrected α‐level: P = 0.0085), none of the SNPs was significantly associated with measures of adiposity or body fat distribution (all P > 0.009, dominant inheritance model). Therefore, our results suggest that these new obesity SNPs, despite their influence on BMI, are neither associated with a metabolically unfavorable nor with a favorable body composition.     

Independent Association of Hip Circumference with Metabolic Profile in Different Ethnic Groups

Objective: In whites, a larger hip circumference has been shown to be associated with a better metabolic profile, after adjustment for BMI and waist circumference. Our aim was to investigate this association in a variety of ethnic groups, some highly susceptible to type 2 diabetes. Research Methods and Procedures: We measured weight, height, waist and hip circumferences, systolic and diastolic blood pressure, fasting and 2‐hour postload glucose, triglycerides, and high‐density lipoprotein‐cholesterol in 1020 Melanesians, 767 Micronesians, 3697 Indians, and 2710 Creoles from Pacific and Indian Ocean islands. Leptin and body fat percentage were determined in Indian and Creole Mauritians only. Results: In all ethnic groups, larger hip circumference was associated with lower glucose and triglyceride levels in both sexes and higher high‐density lipoprotein levels in women only, after adjustment for waist circumference, BMI, and age. Adjustment for height or leptin did not materially change the results. Discussion: In conclusion, we confirmed the protective association of relatively larger hips in four nonwhite ethnic groups. Leptin does not seem to play a mediating role in this association.     

Polymorphisms in the SCD1 gene: associations with body fat distribution and insulin sensitivity

Objective: Obesity and insulin resistance are major risk factors for metabolic diseases and are influenced by lifestyle and genetics. The lipogenic enzyme, stearoyl‐coenzyme A‐desaturase (SCD), is related to obesity. Further, SCD1‐deficent mice are protected against obesity and insulin resistance. We hypothesized that genetic polymorphisms in the SCD1 gene would be associated with obesity, insulin sensitivity, and estimated SCD activity in humans. Research Methods and Procedures: The study population was 1143 elderly Swedish men taking part of a population‐based cohort study, the Uppsala Longitudinal Study of Adult Men. Associations between single nucleotide polymorphisms and obesity (waist circumference and BMI), insulin sensitivity (assessed by hyperinsulinemic euglycemic clamp), and estimated SCD activity (fatty acid ratios) were analyzed using linear regression analysis. Results: Subjects homozygous for the rare alleles of rs10883463, rs7849, rs2167444, and rs508384 had decreased BMI and waist circumference and improved insulin sensitivity. The rare allele of rs7849 demonstrated the strongest effect on both insulin sensitivity [regression coefficient (β) = 1.19, p = 0.007] and waist circumference (β = ?4.4, p = 0.028), corresponding to 23% higher insulin sensitivity and 4 cm less waist circumference. Conclusion: This study indicates that genetic variations in the SCD1 gene are associated with body fat distribution and insulin sensitivity, results that accord well with animal data. These results need confirmation in other populations with a larger sample size.     

INSIG1 influences obesity-related hypertriglyceridemia in humans

In our analysis of a quantitative trait locus (QTL) for plasma triglyceride (TG) levels [logarithm of odds (LOD) = 3.7] on human chromosome 7q36, we examined 29 single nucleotide polymorphisms (SNPs) across INSIG1, a biological candidate gene in the region. Insulin-induced genes (INSIGs) are feedback mediators of cholesterol and fatty acid synthesis in animals, but their role in human lipid regulation is unclear. In our cohort, the INSIG1 promoter SNP rs2721 was associated with TG levels (P = 2 × 10⁻³ in 1,560 individuals of the original linkage cohort, P = 8 × 10⁻⁴ in 920 unrelated individuals of the replication cohort, combined P = 9.9 × 10⁻⁶). Individuals homozygous for the T allele had 9% higher TG levels and 2-fold lower expression of INSIG1 in surgical liver biopsy samples when compared with individuals homozygous for the G allele. Also, the T allele showed additional binding of nuclear proteins from HepG2 liver cells in gel shift assays. Finally, the variant rs7566605 in INSIG2, the only homolog of INSIG1, enhances the effect of rs2721 (P = 0.00117). The variant rs2721 alone explains 5.4% of the observed linkage in our cohort, suggesting that additional, yet-undiscovered genes and sequence variants in the QTL interval also contribute to alterations in TG levels in humans.     

A variant in the LRRFIP1 gene is associated with adiposity and inflammation

Inflammation is an important factor linking abdominal obesity with insulin resistance and related cardiometabolic risk. A genome‐wide association study of adiposity‐related traits performed in the Quebec Family Study (QFS) revealed that a single‐nucleotide polymorphism (SNP) in the LRRFIP1 gene (rs11680012) was associated with abdominal adiposity (P = 4.6 × 10^–6).

Objective:

The objective of this study was to assess the relationship between polymorphisms in LRRFIP1 gene and adiposity (BMI, fat mass (FM), waist circumference (WC), and computed tomography‐derived areas of total, subcutaneous and visceral abdominal adipose tissue) and markers of inflammation (C‐reactive protein (CRP) and interleukin‐6 (IL‐6)).

Design and Methods:

Using Sequenom, 16 tag SNPs in the LRRFIP1 gene, capturing 78% of the genetic variation, were genotyped in 926 participants of the QFS.

Results:

Eight SNPs (rs7575941, rs3769053, rs11689421, rs3820808, rs11680012, rs3806505, rs6739130, and rs11686141) showed evidence of association with at least two adiposity phenotypes and plasma levels of one marker of inflammation. The strongest evidence of association was observed with rs11680012, which explained 1.8–3.4% of the variance in areas of abdominal adiposity and 2.0% of the variation in CRP levels. Carriers of the rare allele of rs11680012 had ～30% more abdominal adiposity (P values between 2.7 × 10^–4 and 3.8 × 10^–6) and 75% higher CRP levels (P = 1.6 × 10^–4) than the common allele in age and sex adjusted data. Rs11680012 is a G/C SNP converting an arginine into a threonine and this amino acid substitution may potentially alter exonic splicing.

Conclusion:

This gene may therefore represent a potential interesting target to investigate in further functional studies on adiposity and inflammation.     

Lipoprotein Oxidation and Plasma Vitamin E in Nondiabetic Normotensive Obese Patients

Objective: To correlate the susceptibility of low‐(LDL) and very‐low‐density lipoprotein to oxidation in vitro and the concentrations of serum antibodies against malondialdehyde‐modified LDL and plasma vitamin E with the anthropometric and laboratory characteristics of obesity. Research Methods and Procedures: A total of 75 nondiabetic, normotensive obese patients were assigned to one of four groups according to their body mass index (BMI): moderately obese (30 ≤ BMI ≤ 34.9 kg/m², n = 11), severely obese (35 ≤ BMI ≤ 39.9 kg/m², n = 20), morbidly obese (40 ≤ BMI ≤ 50 kg/m², n = 29), and very severely obese (BMI > 50 kg/m², n = 15). Results: The oxidation lag time for LDL from patients with a BMI ≥35 kg/m² was shorter than that for LDL from non‐obese controls (n = 13), whereas very‐low‐density lipoprotein oxidation lag times were not significantly different. The serum antibodies against modified LDL were similar in all groups, whereas the plasma vitamin E concentrations of obese patients were decreased (p ≤ 0.01). There was a negative correlation between LDL oxidation lag time and BMI (r = ?0.35, p = 0.0008), and between plasma vitamin E and BMI (r = ?0.53, p < 0.0001) and waist‐to‐hip ratio (r = ?0.40, p = 0.0003). Discussion: The LDL of nondiabetic, normotensive obese patients is more readily oxidized, and plasma vitamin E concentrations are low. These are both risk factors for coronary heart disease.     

No association between INSIG2 Gene rs7566605 polymorphism and being overweight in Japanese population

Obesity is a complex trait reflecting numerous genetic and environmental factors. Recently, a common genetic polymorphism (rs7566605) associated with a higher BMI was found in proximity to the insulin induced protein 2 (INSIG2 ) gene, with replication in four unrelated populations living in Western countries. We investigated the susceptibility to the polymorphism amongst the general Japanese population (n = 1976). The frequency of appearance of the single-nucleotide polymorphism (SNP) in the Japanese (G allele; 0.652, C allele; 0.348) was not different from that found in subjects of European origin as reported previously. However, the BMI levels in each of these genotypes did not differ significantly (GG; 23 +/- 3, GC; 24 +/- 3, CC; 24 +/- 3 kg/m(2), P = 0.906). In a separate analysis according to sex (male; P = 0.462, female; P = 0.879), age decade (40s; P = 0.057, 50s; P = 0.998, 60s; P = 0.622, 70s; 0.425, respectively), and tertiles of the BMI (1st; P = 0.409, 2nd; P = 0.088, 3rd; P = 0.780), the differences did not achieve statistical significance. The frequency of obesity did not differ among the genotypes (25 kg/m(2); 30.3, 30.8, 28.2%, P = 0.729, 30 kg/m(2); 2.9, 3.8, 2.8%, P = 0.549). No associations were also observed for related plasma markers; high-molecular weight (HMW) adiponectin (P = 0.510), high-sensitive C-reactive protein (P = 0.788), resistin (P = 0.937) and homeostasis of minimal assessment of insulin resistance (P = 0.634). These results indicate a lack of association between SNP rs7566605 and being overweight among the Japanese (in the middle-aged and elderly population).     

OPRM1 Gene Is Associated With BMI in Uyghur Population

To test the hypothesis that µ‐opioid receptor (OPRM1) gene might be involved in the prevalence of obesity, a population‐based association study was carried out in Uyghur population. Overall 10 tagging single‐nucleotide polymorphisms (tSNPs) in OPRM1 gene were genotyped. We showed that genotypes of rs1799971 in exon 1, and rs514980 and rs7773995 in intron 1 were significantly associated with the BMI. The BMI significantly decreased by the copy of minor allele carriers of rs1799971 which is a nonsynonymous functional polymorphism, whereas the BMI significantly increased by the copy of minor allele carriers of rs514980 and rs7773995. Subsequently, subjects were subsequently divided into case (BMI ≥ 28) and control group (BMI < 24). Significant associations were again observed at rs1799971, rs514980, and rs7773995, regardless of controlling for covariates age and gender or not. The stronger evidence for association was found under the additive model for each of the three SNPs. The per‐allele odds ratio of the minor allele for obesity was 0.75 (95% confidence interval 0.58–0.96, P = 0.023) for rs1799971, 1.68 (95% confidence interval 1.14–2.49, P = 0.009) for rs514980, and 1.80 (95% confidence interval 1.14–2.85, P = 0.012) for rs7773995, respectively. Our observations give the evidence that OPRM1 gene is involved in the prevalence of obesity in Uyghurs.     

High allelic burden of four obesity SNPs is associated with poorer weight loss outcomes following gastric bypass surgery

Genome‐wide association and linkage studies have identified multiple susceptibility loci for obesity. We hypothesized that such loci may affect weight loss outcomes following dietary or surgical weight loss interventions. A total of 1,001 white individuals with extreme obesity (BMI >35 kg/m²) who underwent a preoperative diet/behavioral weight loss intervention and Roux‐en‐Y gastric bypass surgery were genotyped for single‐nucleotide polymorphisms (SNPs) in or near the fat mass and obesity‐associated (FTO), insulin induced gene 2 (INSIG2), melanocortin 4 receptor (MC4R), and proprotein convertase subtilisin/kexin type 1 (PCSK1) obesity genes. Association analysis was performed using recessive and additive models with pre‐ and postoperative weight loss data. An increasing number of obesity SNP alleles or homozygous SNP genotypes was associated with increased BMI (P < 0.0006) and excess body weight (P < 0.0004). No association between the amounts of weight lost from a short‐term dietary intervention and any individual obesity SNP or cumulative number of obesity SNP alleles or homozygous SNP genotypes was observed. Linear mixed regression analysis revealed significant differences in postoperative weight loss trajectories across groups with low, intermediate, and high numbers of obesity SNP alleles or numbers of homozygous SNP genotypes (P < 0.0001). Initial BMI interacted with genotype to influence weight loss with initial BMI <50 kg/m², with evidence of a dosage effect, which was not present in individuals with initial BMI ≥50 kg/m². Differences in metabolic rate, binge eating behavior, and other clinical parameters were not associated with genotype. These data suggest that response to a surgical weight loss intervention is influenced by genetic susceptibility and BMI.