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Combined analyses of 20 common obesity susceptibility variants.

ABSTRACT: Genome-wide association studies and linkage studies have identified 20 validated genetic variants associated with obesity and/or related phenotypes. The variants are common, and they individually exhibit small-to-modest effect sizes.In this study we investigate the combined effect of these variants and their ability to discriminate between normal weight and overweight/obese individuals. We applied receiver operating characteristics (ROC) curves, and estimated the area under the ROC curve (AUC) as a measure of the discriminatory ability. The analyses were performed cross-sectionally in the population-based Inter99 cohort where 1,725 normal weight, 1,519 overweight, and 681 obese individuals were successfully genotyped for all 20 variants.When combining all variants, the 10% of the study participants who carried more than 22 risk-alleles showed a significant increase in probability of being both overweight with an odds ratio of 2.00 (1.47-2.72), P = 4.0 x 10(-5), and obese with an OR of 2.62 (1.76-3.92), P = 6.4 x 10(-7), compared with the 10% of the study participants who carried less than 14 risk-alleles. Discrimination ability for overweight and obesity, using the 20 single nucleotide polymorphisms (SNPs), was determined to AUCs of 0.53 and 0.58, respectively. When combining SNP data with conventional nongenetic risk factors of obesity, the discrimination ability increased to 0.64 for overweight and 0.69 for obesity. The latter is significantly higher (P < 0.001) than for the nongenetic factors alone (AUC = 0.67).The discriminative value of the 20 validated common obesity variants is at present time sparse and too weak for clinical utility, however, they add to increase the discrimination ability of conventional nongenetic risk factors.

SUBMITTER: Sandholt CH

PROVIDER: S-EPMC2889766 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature

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Combined analyses of 20 common obesity susceptibility variants.

Sandholt Camilla Helene CH Sparsø Thomas T Grarup Niels N Albrechtsen Anders A Almind Katrine K Hansen Lars L Toft Ulla U Jørgensen Torben T Hansen Torben T Pedersen Oluf O

Diabetes 20100128 7

<h4>Objective</h4>Genome-wide association studies and linkage studies have identified 20 validated genetic variants associated with obesity and/or related phenotypes. The variants are common, and they individually exhibit small-to-modest effect sizes.<h4>Research design and methods</h4>In this study we investigate the combined effect of these variants and their ability to discriminate between normal weight and overweight/obese individuals. We applied receiver operating characteristics (ROC) curv ...[more]

PMID: 20110568

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Project description:BackgroundCopy-number variations (CNVs) have been associated with rare and debilitating genomic disorders (GDs) but their impact on health later in life in the general population remains poorly described.MethodsAssessing four modes of CNV action, we performed genome-wide association scans (GWASs) between the copy-number of CNV-proxy probes and 60 curated ICD-10 based clinical diagnoses in 331,522 unrelated white British UK Biobank (UKBB) participants with replication in the Estonian Biobank.ResultsWe identified 73 signals involving 40 diseases, all of which indicating that CNVs increased disease risk and caused earlier onset. We estimated that 16% of these associations are indirect, acting by increasing body mass index (BMI). Signals mapped to 45 unique, non-overlapping regions, nine of which being linked to known GDs. Number and identity of genes affected by CNVs modulated their pathogenicity, with many associations being supported by colocalization with both common and rare single-nucleotide variant association signals. Dissection of association signals provided insights into the epidemiology of known gene-disease pairs (e.g., deletions in BRCA1 and LDLR increased risk for ovarian cancer and ischemic heart disease, respectively), clarified dosage mechanisms of action (e.g., both increased and decreased dosage of 17q12 impacted renal health), and identified putative causal genes (e.g., ABCC6 for kidney stones). Characterization of the pleiotropic pathological consequences of recurrent CNVs at 15q13, 16p13.11, 16p12.2, and 22q11.2 in adulthood indicated variable expressivity of these regions and the involvement of multiple genes. Finally, we show that while the total burden of rare CNVs-and especially deletions-strongly associated with disease risk, it only accounted for ~ 0.02% of the UKBB disease burden. These associations are mainly driven by CNVs at known GD CNV regions, whose pleiotropic effect on common diseases was broader than anticipated by our CNV-GWAS.ConclusionsOur results shed light on the prominent role of rare CNVs in determining common disease susceptibility within the general population and provide actionable insights for anticipating later-onset comorbidities in carriers of recurrent CNVs.

Project description:Objectives:The objective of this study was to investigate the association of four single-nucleotide polymorphisms (SNPs) of the cannabinoid receptor 2 (CNR2) gene, gene-obesity interaction, and haplotype combination with osteoporosis (OP) susceptibility. Methods:Chinese patients with OP were recruited between March 2011 and December 2015 from our hospital. In this study, a total of 1267 post-menopausal female patients (631 OP patients and 636 control patients) were selected. The mean age of all subjects was 69.2 years (sd 15.8). A generalized multifactor dimensionality reduction (GMDR) model and logistic regression model were used to examine the interaction between SNP and obesity on OP. For OP patient-control haplotype analyses, the SHEsis online haplotype analysis software (http://analysis.bio-x.cn/) was employed. Results:The logistic regression model revealed that the C allele of rs2501431 and the G allele of rs3003336 were associated with increased OP risk, compared with those with wild genotype. However, no significant correlations were found when analyzing the association of rs4237 and rs2229579 with OP risk. The GMDR analysis suggested that the interaction model composed of two factors, rs3003336 and abdominal obesity (AO), was the best model with statistical significance (p-value from sign test (Psign) = 0.012), indicating a potential gene-environment interaction between rs3003336 and AO. Overall, the two-locus models had a cross-validation consistency of 10/10 and had a testing accuracy of 0.641. Abdominally obese subjects with the AG or GG genotype have the highest OP risk, compared with subjects with the AA genotype and normal waist circumference (WC) (odds ratio (OR) 2.23, 95% confidence interval (CI) 1.54 to 3.51). Haplotype analysis also indicated that the haplotype containing the rs3003336-G and rs2501431-C alleles was associated with a statistically increased OP risk. Conclusion:Our results suggested that the C allele of rs2501431 and the G allele of rs3003336 of the CNR2 gene, interaction between rs3003336 and AO, and the haplotype containing the rs3003336-G and rs2501431-C alleles were all associated with increased OP risk.Cite this article: Bone Joint Res 2019;8:544-549.

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Combined analyses of 20 common obesity susceptibility variants.

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Combined analyses of 20 common obesity susceptibility variants.

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