Flow chart of meta-analysis for exclusion/inclusion of studies.

<p>Flow chart of meta-analysis for exclusion/inclusion of studies.</p

Meta-analysis of the association between rs17782313 polymorphism (or proxy) near the <i>MC4R</i> gene and obesity risk under an additive genetic model.

<p>Meta-analysis of the association between rs17782313 polymorphism (or proxy) near the <i>MC4R</i> gene and obesity risk under an additive genetic model.</p

Association between Common Polymorphism near the <em>MC4R</em> Gene and Obesity Risk: A Systematic Review and Meta-Analysis

<div><h3>Background</h3><p>Genome-wide association studies on Europeans have shown that two polymorphisms (rs17782313, rs12970134) near the melanocortin 4 receptor (<em>MC4R</em>) gene were associated with increased risk of obesity. Subsequently studies among different ethnic populations have shown mixed results with some confirming and others showing inconsistent results, especially among East Asians and Africans. We performed a comprehensive meta-analysis of various studies from different ethnic populations to assess the association of the <em>MC4R</em> polymorphism with obesity risk.</p> <h3>Methods</h3><p>We retrieved all published literature that investigated association of MC4R variants with obesity from PubMed and Embase. Pooled odds ratio (OR) with 95% confidence interval (CI) was calculated using fixed- or random-effects model.</p> <h3>Results</h3><p>A total of 61 studies (80,957 cases/220,223 controls) for rs17782313 polymorphism (or proxy) were included in the meta-analysis. The results suggested that rs17782313 polymorphism was significantly associated with obesity risk (OR = 1.18, 95%CI = 1.15–1.21, <em>p</em><0.001). Similar trends were observed among subgroups of Europeans and East Asians, adults and children, studies with high quality score, and for each five <em>MC4R</em> polymorphisms independently.</p> <h3>Conclusions</h3><p>The present meta-analysis confirms the significant association of <em>MC4R</em> polymorphism with risk of obesity. Further studies should be conducted to identify the causal variant and the underlying mechanisms of the identified association.</p> </div

Meta-analysis of association between <i>MC4R</i> polymorphism and obesity risk under an additive model.

<p><i>Note</i>s OR, odds ratio; CI, confidence interval; <i>P</i>_Z-test; <i>P</i> value for Z test; <i>P</i>_H, <i>P</i> value based on Q test for between-study heterogeneity.</p>a<p>The rs17782313 polymorphism is used in the data analysis since it is in high linkage disequilibrium with four other SNPs, rs12970134, rs571312, rs17700144 and rs4450508 (D′ ranging from 0.90 to 1.00, r² ranging from 0.60 to 0.93 in CEU, CHB and JPT populations).</p>b<p>See the Methods section.</p>c<p>There are five studies containing data on more than one <i>MC4R</i> polymorphisms.</p

Characteristics of the studies included in the meta-analysis.

a<p>And/or current under antihypertensive treatment.</p>b<p>In the lower third of the distribution of population blood pressures.</p>*<p>1, age; 2, sex; 3, BMI; 4, heart rate; 5, interaction variables; 6, follow-up years; 7,△-BMI; 8, type 2 diabetes; 9, smoking; 10, alcohol drinking; 11, creatinine; 12,triglyceride; 13, high density lipoprotein; 14,total cholesterol.</p

Funnel plot of the association between<i>STK39</i> rs3754777 variant and hypertension.

<p>Funnel plot of the association between<i>STK39</i> rs3754777 variant and hypertension.</p

Flow chart depicting exclusion/inclusion of individual articles (or studies) for meta-analysis.

<p>Flow chart depicting exclusion/inclusion of individual articles (or studies) for meta-analysis.</p

Meta-analysis of the association between <i>STK39</i> rs3754777 variant and hypertension.

<p>Meta-analysis of the association between <i>STK39</i> rs3754777 variant and hypertension.</p

Study of 11 BMI-Associated Loci Identified in GWAS for Associations with Central Obesity in the Chinese Children

<div><p>Objective</p><p>Recent genome-wide association studies have identified many single nucleotide polymorphisms (SNPs) associated with body mass index (BMI)/generalized obesity. In this study, we aimed to examine the associations of identified SNPs with risk of central obesity in a child population from China.</p><p>Methods</p><p>We genotyped 11 SNPs (<i>FTO</i> rs9939609, <i>MC4R</i> rs17782313, <i>GNPDA2</i> rs10938397, <i>BDNF</i> rs6265, <i>FAIM2</i> rs7138803, <i>NPC1</i> rs1805081, <i>SEC16B</i> rs10913469, <i>SH2B1</i> rs4788102, <i>PCSK1</i>rs6235, <i>KCTD15</i> rs29941, <i>BAT2</i> rs2844479) in the Chinese children (<i>N</i> = 3502, age range 6–18 years) from the Beijing Child and Adolescent Metabolic Syndrome (BCAMS). Based on the age- and sex- specific waist circumference (WC) standards generated in the BCAMS study, 1196 central obese cases and 2306 controls were identified.</p><p>Results</p><p>Of 11 studied SNPs, four SNPs and genetic risk score (GRS) based on them were statistically significantly associated with central obesity by WC criteria (<i>FTO</i> rs9939609: OR = 1.29, 95%CI = 1.10–1.50, <i>p</i> = 0.001; <i>MC4R</i> rs17782313: OR = 1.27, 95%CI = 1.12–1.44, <i>p</i> = 1.32×10⁻⁴; <i>GNPDA2</i> rs10938397: OR = 1.22, 95%CI = 1.09–1.37, <i>p</i> = 4.09×10⁻⁴; <i>BDNF</i> rs6265: OR = 1.20, 95%CI = 1.08–1.34, <i>p</i> = 8.86×10⁻⁴; GRS: OR = 1.25, 95%CI 1.16–1.34, <i>p</i> = 2.58×10⁻⁹) after adjustment for sex, age, pubertal stage, physical activity and family history of obesity. Similar observations were made using weight-to-height ratio (WHtR) criterion. However, other SNPs were not associated with central obesity by WC as well as WHtR criterion.</p><p>Conclusions</p><p>Our study replicates the statistically significant association of four SNPs (<i>FTO</i> rs9939609, <i>MC4R</i> rs17782313, <i>GNPDA2</i> rs10938397, <i>BDNF</i> rs6265) with risk of central obesity in the Chinese children.</p></div

Basic characteristics of participants in the case-control study based on WHtR criteria.

<p>Basic characteristics of participants in the case-control study based on WHtR criteria.</p