Gene–gene interaction between PPARγ2 and ADRβ3 increases obesity risk in children and adolescents

Ochoa, María C.; Marti, Amelia; Azcona, Cristina; Chueca, M.; Oyarzábal, M.; Pelach, R; Patiño, Ana; Moreno-Aliaga, María J.; Martínez-González, M Á; Martínéz, J. Alfredo

doi:10.1038/sj.ijo.0802803

Cited by 66 publications

(61 citation statements)

References 24 publications

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“…There is growing evidence that gene-gene interactions are important contributors to genetic variation in complex human diseases. [1][2][3][4][5][6] However, detecting gene-gene interactions remains a challenge due to the lack of powerful statistical methods. The most commonly used statistical approach for studying gene-gene interactions is to use a regression framework in which a pair of markers and their interaction terms are included as predictors.…”

Section: Introductionmentioning

confidence: 99%

Gene-based interaction analysis by incorporating external linkage disequilibrium information

Wang

Edmondson

et al. 2010

Eur J Hum Genet

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Gene-gene interactions have an important role in complex human diseases. Detection of gene-gene interactions has long been a challenge due to their complexity. The standard method aiming at detecting SNP-SNP interactions may be inadequate as it does not model linkage disequilibrium (LD) among SNPs in each gene and may lose power due to a large number of comparisons. To improve power, we propose a principal component (PC)-based framework for gene-based interaction analysis. We analytically derive the optimal weight for both quantitative and binary traits based on pairwise LD information. We then use PCs to summarize the information in each gene and test for interactions between the PCs. We further extend this gene-based interaction analysis procedure to allow the use of imputation dosage scores obtained from a popular imputation software package, MACH, which incorporates multilocus LD information. To evaluate the performance of the gene-based interaction tests, we conducted extensive simulations under various settings. We demonstrate that gene-based interaction tests are more powerful than SNP-based tests when more than two variants interact with each other; moreover, tests that incorporate external LD information are generally more powerful than those that use genotyped markers only. We also apply the proposed gene-based interaction tests to a candidate gene study on high-density lipoprotein. As our method operates at the gene level, it can be applied to a genome-wide association setting and used as a screening tool to detect gene-gene interactions.

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Section: Introductionmentioning

confidence: 99%

Gene-based interaction analysis by incorporating external linkage disequilibrium information

Wang

Edmondson

et al. 2010

Eur J Hum Genet

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“…9,12,14,[30][31][32][33][34] In this regard, the current study showed that LPL Ser447Stop polymorphism, despite its functional role in promoting increases in LPL and the attendant lipid storage in adipocyte, 17,35 beneficially modified the association between obesity and the ADRB1 Arg389Gly polymorphism, particularly in white subjects. In the total sample, interactions between the two polymorphisms were significant in adulthood and for the longitudinal change.…”

Section: Discussionmentioning

confidence: 61%

Influence of lipoprotein lipase gene Ser447Stop and β1-adrenergic receptor gene Arg389Gly polymorphisms and their interaction on obesity from childhood to adulthood: the Bogalusa Heart Study

Chen

Srinivasan

et al. 2006

Int J Obes

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Objective: To investigate the influence of lipoprotein lipase (LPL) Ser447Stop and b 1 -adrenergic receptor (ADRB1) Arg389Gly gene polymorphisms, individually and in combination, on obesity from childhood to adulthood. Design and subjects: A community-based cohort of 1331 subjects (30% black and 70% white subjects) was followed over an average period of 23 years from childhood (age range: 4-17 years) to adulthood (age range:18-44 years). Measurement: Body mass index (BMI, kg/m 2 ) and LPL Ser447Stop and the ADRB1 Arg389Gly genotypes. Results: The frequency of the ADRB1 Gly389 allele was 0.25 in white subjects vs 0.39 in black subjects (Po0.001); 0.08 vs 0.05 (P ¼ 0.280) for the LPL Stop447 allele. There was no association between the LPL Stop447 allele and BMI among white and black subjects either in childhood and adulthood levels or annual change from childhood to adulthood. The ADRB1 Gly389 allele was associated with lower BMI only in black adults (P ¼ 0.017). Further, the interaction effect of the LPL Stop447 allele and ADRB1 Gly389 allele on adult BMI or its annual change was significant in white subjects and in the total sample (P ¼ 0.03-0.006). Childhood values tended to show a similar trend. Having both ADRB1 Gly389 allele and LPL Stop447 allele was associated with 71% (95% confidence interval: 26-89%) less odds for developing obesity from childhood to adulthood after adjusting for age, race, sex, and childhood BMI. Conclusion: While Gly389 allele of the ADRB1 gene lowers obesity in black subjects, this allele in conjunction with Stop447 allele of the LPL gene lowers obesity in adults and attenuates the development of obesity from childhood to adulthood. These findings underscore the importance of gene-gene interaction in the assessment of genetic influences on complex traits such as obesity.

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“…These include the ADRA2B, 18,19 ADRB1, 20,21 ADRB2 18,22-29 and ADRB3 genes. 18,19,28,30,31 Remarkably, most clinically effective antipsychotic drugs are potent ADRA1 antagonists. 32 A possible role of the ADRA1A promoter region in the development of schizophrenia was found in an isolated Spanish population, 33 but not in the Chinese population.…”

Section: Introductionmentioning

confidence: 99%

ADRA1A gene is associated with BMI in chronic schizophrenia patients exposed to antipsychotics

et al. 2009

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Noradrenaline and adrenaline are neurotransmitters of the sympathetic nervous system that interact with various adrenergic receptor (ADR) subtypes, and this regulates the basal metabolic rate, thermogenesis and efficiency of energy utilization. We examined a possible role of the gene coding for ADRA1A receptor in weight gain in schizophrenia subjects exposed to antipsychotics. A total of 401 schizophrenia in-patients treated with antipsychotics for 42 years were recruited and a final 394 DNA samples were genotyped. Their body mass indexes (BMIs) were recorded for 12 months and parameterized to be correlated in regression. Among the 58 single-nucleotide polymorphisms (SNPs) genotyped, 44 valid SNPs, which had minor allele frequency X0.03, were analyzed in statistics. Linear regression model with age, gender, diabetes, use of typical antipsychotics and use of atypical antipsychotics as covariates, with or without gender interaction, showed evidence of associations between the ADRA1A gene and BMI. Most of the SNPs associated with BMI are located in the promoter and intron regions, and being female appeared to enhance the gene effect. Our study suggests that the ADRA1A gene is involved in weight gain among schizophrenia patients treated with antipsychotics. Further molecular dissection of the ADRA1A gene warrants better understanding on weight gain mechanisms in schizophrenia.

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Gene–gene interaction between PPARγ2 and ADRβ3 increases obesity risk in children and adolescents

Cited by 66 publications

References 24 publications

Gene-based interaction analysis by incorporating external linkage disequilibrium information

Gene-based interaction analysis by incorporating external linkage disequilibrium information

Influence of lipoprotein lipase gene Ser447Stop and β1-adrenergic receptor gene Arg389Gly polymorphisms and their interaction on obesity from childhood to adulthood: the Bogalusa Heart Study

ADRA1A gene is associated with BMI in chronic schizophrenia patients exposed to antipsychotics

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