Predisposition of Obesity through Genetic and Non-Genetic Risk Fac- tors (original) (raw)
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Future management of human obesity: understanding the meaning of genetic susceptibility
Advances in Genomics and Genetics, 2014
Gene-environment interactions are central to the expression of obesity. The condition is strongly heritable (ie, genetic), and most of the variation in obesity levels between countries and between individuals can be explained by the effects of obesogenic environments on individual genetic susceptibilities. The nature of the obesogenic environmental influences is not clear in detail, but they correlate closely with measures of affluence. The causes of variation in genetic susceptibility are also not clearly defined, but their general nature has become clearer. The failure of genome-wide association studies or large linkage studies to identify or replicate causative genetic variants, together with the segregation of obesity-related traits in families, implicates a heterogenetic mechanism in which rare, dominantly or additively expressed genetic variants are responsible for most of common obesity. The search for rare causative variants continues with some successes, but those identified contribute very little to the overall burden and, assuming heterogenetics, there are many more to find. The time when genomic risk factors provide more information than do currently available markers, such as family history, is a long way off. Genomic studies to date have contributed little, if anything, to the prevention and treatment of common obesity and its associated disorders. This contrasts with the obvious and immediate potential implications of the well-established overall genetic basis of obesity, which have not yet been exploited in the clinical or public health arenas. Genomic studies, which have helped to define the genetic basis of common obesity mainly by exclusion, will in the future play an increasingly important role in understanding and managing obesity, but only with parallel studies of the physiological, behavioral, and economic influences.
Obesity is becoming an escalating global epidemic in many parts of the world and results in a huge rise of sanity costs due to its associate comorbidities. In this sense, body weight regulation depends on a combination of interactions between genetic and environmental factors. Among inheritance factors, body weight is normally a polygenic condition determined by the presence of genes of high prevalence but with a low relevant effect. In the last years, Candidate Genes Analyses and Genome Wide Association Studies (GWAS) have become very useful strategies to detect new polymorphisms and copy number variants (CNVs) associated with obesity and its related comorbidities. From these studies, more than a hundred genetic variants involved in metabolic pathways including adipogenesis, energy intake, lipolysis or energy expenditure have been found. These findings along with epigenetics and nutrigenetics are the basis to the development of new tools that would allow predicting individual obesi...
PLoS ONE, 2013
Objective: Obesity has become a leading preventable cause of morbidity and mortality in many parts of the world. It is thought to originate from multiple genetic and environmental determinants. The aim of the current study was to introduce haplotype-based multi-locus stepwise regression (MSR) as a method to investigate combinations of unlinked single nucleotide polymorphisms (SNPs) for obesity phenotypes. Methods: In 2,122 healthy randomly selected men and women of the EPIC-Potsdam cohort, the association between 41 SNPs from 18 obesity-candidate genes and either body mass index (BMI, mean = 25.9 kg/m 2 , SD = 4.1) or waist circumference (WC, mean = 85.2 cm, SD = 12.6) was assessed. Single SNP analyses were done by using linear regression adjusted for age, sex, and other covariates. Subsequently, MSR was applied to search for the 'best' SNP combinations. Combinations were selected according to specific AIC c and p-value criteria. Model uncertainty was accounted for by a permutation test. Results: The strongest single SNP effects on BMI were found for TBC1D1 rs637797 (b = 20.33, SE = 0.13), FTO rs9939609 (b = 0.28, SE = 0.13), MC4R rs17700144 (b = 0.41, SE = 0.15), and MC4R rs10871777 (b = 0.34, SE = 0.14). All these SNPs showed similar effects on waist circumference. The two 'best' six-SNP combinations for BMI (global p-value = 3.45?10-6 and 6.82?10-6) showed effects ranging from 21.70 (SE = 0.34) to 0.74 kg/m 2 (SE = 0.21) per allele combination. We selected two six-SNP combinations on waist circumference (global p-value = 7.80?10-6 and 9.76?10-6) with an allele combination effect of 22.96 cm (SE = 0.76) at maximum. Additional adjustment for BMI revealed 15 three-SNP combinations (global p-values ranged from 3.09?10-4 to 1.02?10-2). However, after carrying out the permutation test all SNP combinations lost significance indicating that the statistical associations might have occurred by chance. Conclusion: MSR provides a tool to search for risk-related SNP combinations of common traits or diseases. However, the search process does not always find meaningful SNP combinations in a dataset.
PLOS One, 2007
Background. Obesity is a major health problem. Although heritability is substantial, genetic mechanisms predisposing to obesity are not very well understood. We have performed a genome wide association study (GWA) for early onset (extreme) obesity. Methodology/Principal Findings. a) GWA (Genome-Wide Human SNP Array 5.0 comprising 440,794 single nucleotide polymorphisms) for early onset extreme obesity based on 487 extremely obese young German individuals and 442 healthy lean German controls; b) confirmatory analyses on 644 independent families with at least one obese offspring and both parents. We aimed to identify and subsequently confirm the 15 SNPs (minor allele frequency $10%) with the lowest pvalues of the GWA by four genetic models: additive, recessive, dominant and allelic. Six single nucleotide polymorphisms (SNPs) in FTO (fat mass and obesity associated gene) within one linkage disequilibrium (LD) block including the GWA SNP rendering the lowest p-value (rs1121980; log-additive model: nominal p = 1.13610 27 , corrected p = 0.0494; odds ratio (OR) CT 1.67, 95% confidence interval (CI) 1.22-2.27; OR TT 2.76, 95% CI 1.88-4.03) belonged to the 15 SNPs showing the strongest evidence for association with obesity. For confirmation we genotyped 11 of these in the 644 independent families (of the six FTO SNPs we chose only two representing the LD bock). For both FTO SNPs the initial association was confirmed (both Bonferroni corrected p,0.01). However, none of the nine non-FTO SNPs revealed significant transmission disequilibrium. Conclusions/Significance. Our GWA for extreme early onset obesity substantiates that variation in FTO strongly contributes to early onset obesity. This is a further proof of concept for GWA to detect genes relevant for highly complex phenotypes. We concurrently show that nine additional SNPs with initially low p-values in the GWA were not confirmed in our family study, thus suggesting that of the best 15 SNPs in the GWA only the FTO SNPs represent true positive findings. Citation: Hinney A, Nguyen TT, Scherag A, Friedel S, Brö nner G, et al (2007) Genome Wide Association (GWA) Study for Early Onset Extreme Obesity Supports the Role of Fat Mass and Obesity Associated Gene (FTO) Variants. PLoS ONE 2(12): e1361.
Development and Evaluation of a Genetic Risk Score for Obesity
Biodemography and Social Biology, 2013
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Diabetes care, 2015
Abdominal obesity is a major risk factor for type 2 diabetes (T2D). We aimed to examine the association between the genetic predisposition to central obesity, assessed by the waist-to-hip ratio (WHR) genetic score, and T2D risk. The current study included 2,591 participants with T2D and 3,052 participants without T2D of European ancestry from the Nurses' Health Study (NHS) and the Health Professionals Follow-up Study (HPFS). Genetic predisposition to central obesity was estimated using a genetic score based on 14 established loci for the WHR. We found that the central obesity genetic score was linearly related to higher T2D risk. Results were similar in the NHS (women) and HPFS (men). In combined results, each point of the central obesity genetic score was associated with an odds ratio (OR) of 1.04 (95% CI, 1.01-1.07) for developing T2D, and the OR was 1.24 (1.03-1.45) when comparing extreme quartiles of the genetic score after multivariate adjustment. The data indicate that gen...
Therapeutic Advances in Endocrinology and Metabolism
Background: Different genetic and environmental factors can explain the heterogeneity of obesity-induced metabolic alterations between individuals. In this study, we aimed to screen factors that predict metabolically healthy (MHP) and unhealthy (MUP) phenotypes using genetic and lifestyle data in overweight/obese participants. Methods: In this cross-sectional study we enrolled 298 overweight/obese Spanish adults. The Adult Treatment Panel III criteria for metabolic syndrome were used to categorize MHP (at most, one trait) and MUP (more than one feature). Blood lipid and inflammatory profiles were measured by standardized methods. Body composition was determined by dual-energy X-ray absorptiometry. A total of 95 obesity-predisposing single-nucleotide polymorphisms (SNPs) were genotyped by a predesigned next-generation sequencing system. SNPs associated with a MUP were used to compute a weighted genetic-risk score (wGRS). Information concerning lifestyle (dietary intake and physical a...
Risk variants of obesity associated genes demonstrate BMI raising effect in a large cohort
PLOS ONE
Obesity is highly polygenic disease where several genetic variants have been reportedly associated with obesity in different ethnicities of the world. In the current study, we identified the obesity risk or protective association and BMI raising effect of the minor allele of adiponectin, C1Q and collagen domain containing (ADIPOQ), cholesteryl ester transfer protein (CEPT), FTO alpha-ketoglutarate dependent dioxygenase (FTO), leptin (LEP), and leptin receptor (LEPR) genes in a large cohort stratified into four BMI-based body weight categories i.e., normal weight, lean, over-weight, and obese. Based on selected candidate genetic markers, the genotyping of all study subjects was performed by PCR assays, and genotypes and allele frequencies were calculated. The minor allele frequencies (MAFs) of all genetic markers were computed for total and BMI-based body weight categories and compared with MAFs of global and South Asian (SAS) populations. Genetic associations of variants with obesit...