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1.  A Genome-Wide Association Study on Obesity and Obesity-Related Traits 
PLoS ONE  2011;6(4):e18939.
Large-scale genome-wide association studies (GWAS) have identified many loci associated with body mass index (BMI), but few studies focused on obesity as a binary trait. Here we report the results of a GWAS and candidate SNP genotyping study of obesity, including extremely obese cases and never overweight controls as well as families segregating extreme obesity and thinness. We first performed a GWAS on 520 cases (BMI>35 kg/m2) and 540 control subjects (BMI<25 kg/m2), on measures of obesity and obesity-related traits. We subsequently followed up obesity-associated signals by genotyping the top ∼500 SNPs from GWAS in the combined sample of cases, controls and family members totaling 2,256 individuals. For the binary trait of obesity, we found 16 genome-wide significant signals within the FTO gene (strongest signal at rs17817449, P = 2.5×10−12). We next examined obesity-related quantitative traits (such as total body weight, waist circumference and waist to hip ratio), and detected genome-wide significant signals between waist to hip ratio and NRXN3 (rs11624704, P = 2.67×10−9), previously associated with body weight and fat distribution. Our study demonstrated how a relatively small sample ascertained through extreme phenotypes can detect genuine associations in a GWAS.
doi:10.1371/journal.pone.0018939
PMCID: PMC3084240  PMID: 21552555
2.  Complex Genetics of Obesity in Mouse Models 
Annual review of nutrition  2008;28:331-345.
Traits related to energy balance and obesity are exceptionally complex, with varying contributions of genetic susceptibility and interacting environmental factors. The use of mouse models has been a powerful driving force in understanding the genetic architecture of polygenic traits such as obesity. However, the use of mouse models for analysis of complex traits is at an important crossroad. Genome-wide association studies in humans are now leading to direct identification of obesity genes. In this review, we focus on three areas representing the current and future roles of mouse models regarding genetics of complex obesity. First, we summarize increasingly powerful ways to harness the strength of mouse models for discovery of genes affecting polygenic obesity. Second, we examine the status of using a systems biology approach to dissect the genetic architecture of obesity. And third, we explore the effects of recent findings indicating increasing levels of complexity in the nature of variation underlying, and the heritability of, complex traits such as obesity.
doi:10.1146/annurev.nutr.27.061406.093552
PMCID: PMC2758097  PMID: 18435591
systems genetics; QTL; eQTL; collaborative cross; genetic variation
3.  Bone Mineral Density-Associated Polymorphisms Are Associated with Obesity-Related Traits in Korean Adults in a Sex-Dependent Manner 
PLoS ONE  2012;7(12):e53013.
Obesity and osteoporosis share common physiological factors, including the presence of atherosclerosis, a risk factor for cardiometabolic disease, as well as a common progenitor that differentiates into both adipocytes and osteoblasts. Among the 23 polymorphisms associated with bone mineral density (BMD) in recent genome-wide association studies (GWASs), an Osterix polymorphism has been identified and associated with childhood obesity in girls. Therefore, we focused on elucidating polymorphisms associated with adulthood obesity in a sex-dependent manner among the previously published BMD-associated polymorphisms from GWASs. We performed 2 screenings of 18 BMD-associated polymorphisms for obesity-related traits in 2,362 adults aged >20 years. We excluded 13 polymorphisms showing deviations from Hardy–Weinberg equilibrium or no association with obesity-related traits (body mass index, waist circumference (WC), and waist-to-hip ratio). Among 5 selected polymorphisms (rs9594738 of RANKL, rs17066364 of NUFIP1, rs7227401 of OSBPL1A, and rs1856057 and rs2982573 of ESR1) analyzed, 2 polymorphisms (rs9594738 and rs17066364) were associated with obesity-related traits. We found sex-dependent associations such that the 4 polymorphisms (excluding rs9594738 of RANKL) were associated with abdominal traits such as WC and waist-to-hip ratio only in men. In addition, when the combined genetic risk score (GRS) for WC increase was calculated with 4 SNPs (rs9594738, rs17066364, rs7227401, and rs1856057) exhibiting similar trends for both sexes, the magnitude of the GRS effect for the WC increase was larger in men than in women (effect size = 0.856 cm, P = 0.0000452 for men; effect size = 0.598 cm, P = 0.00228 for women). In summary, we found 4 polymorphisms, previously related to osteoporosis, to be associated to obesity-related traits in a sex-dependent manner in Korean adults, particularly in men.
doi:10.1371/journal.pone.0053013
PMCID: PMC3531417  PMID: 23300848
4.  An integrated approach of comparative genomics and heritability analysis of pig and human on obesity trait: evidence for candidate genes on human chromosome 2 
BMC Genomics  2012;13:711.
Background
Traditional candidate gene approach has been widely used for the study of complex diseases including obesity. However, this approach is largely limited by its dependence on existing knowledge of presumed biology of the phenotype under investigation. Our combined strategy of comparative genomics and chromosomal heritability estimate analysis of obesity traits, subscapular skinfold thickness and back-fat thickness in Korean cohorts and pig (Sus scrofa), may overcome the limitations of candidate gene analysis and allow us to better understand genetic predisposition to human obesity.
Results
We found common genes including FTO, the fat mass and obesity associated gene, identified from significant SNPs by association studies of each trait. These common genes were related to blood pressure and arterial stiffness (P = 1.65E-05) and type 2 diabetes (P = 0.00578). Through the estimation of variance of genetic component (heritability) for each chromosome by SNPs, we observed a significant positive correlation (r = 0.479) between genetic contributions of human and pig to obesity traits. Furthermore, we noted that human chromosome 2 (syntenic to pig chromosomes 3 and 15) was most important in explaining the phenotypic variance for obesity.
Conclusions
Obesity genetics still awaits further discovery. Navigating syntenic regions suggests obesity candidate genes on chromosome 2 that are previously known to be associated with obesity-related diseases: MRPL33, PARD3B, ERBB4, STK39, and ZNF385B.
doi:10.1186/1471-2164-13-711
PMCID: PMC3562524  PMID: 23253381
Obesity; Synteny; Comparative genomics; Heritability; Back-fat thickness; Subscapular skinfold thickness; Chromosome 2; Pig; Human
5.  Admixture Mapping of Obesity-Related Traits in African Americans: the Atherosclerosis Risk in Communities (ARIC) Study 
Obesity (Silver Spring, Md.)  2009;18(3):563-572.
Obesity is an important cause of morbidity and mortality worldwide. In the U.S., the prevalence of obesity is higher in African Americans than whites, even after adjustment for socioeconomic status. This leads to the hypothesis that differences in genetic background may contribute to racial/ethnic differences in obesity-related traits. We tested this hypothesis by conducting a genome-wide admixture mapping scan using 1,350 ancestry-informative SNPs in 3,531 self-identified blacks from the Atherosclerosis Risk in Communities (ARIC) study. We used these markers to estimate the overall proportions of European ancestry (PEA) for each individual and then scanned for the association between PEA and obesity-related traits (both continuous and dichotomous) at each locus. The median (interquartile range) PEA was 0.151 (0.115). PEA was inversely correlated with continuous body mass index (BMI), weight, and subscapular skinfold thickness, even after adjusting for socioeconomic factors. In contrast, PEA was positively correlated with BMI-adjusted waist circumference. Using admixture mapping on dichotomized traits, we identified a locus on 2p23.3 to be suggestively associated with BMI (locus-specific LOD = 4.11) and weight (locus-specific LOD = 4.07). After adjusting for global PEA, each additional copy of a European ancestral allele at the 2p23.3 peak was associated with a BMI decrease of ∼0.92 kg/m2 (p = 2.9 × 10-5). Further mapping in this region on chromosome 2 may be able to uncover causative variants underlying obesity, which may offer insights into the control of energy homeostasis.
doi:10.1038/oby.2009.282
PMCID: PMC2866099  PMID: 19696751
6.  Neuronal Genes for Subcutaneous Fat Thickness in Human and Pig Are Identified by Local Genomic Sequencing and Combined SNP Association Study 
PLoS ONE  2011;6(2):e16356.
Obesity represents a major global public health problem that increases the risk for cardiovascular or metabolic disease. The pigs represent an exceptional biomedical model related to energy metabolism and obesity in humans. To pinpoint causal genetic factors for a common form of obesity, we conducted local genomic de novo sequencing, 18.2 Mb, of a porcine QTL region affecting fatness traits, and carried out SNP association studies for backfat thickness and intramuscular fat content in pigs. In order to relate the association studies in pigs to human obesity, we performed a targeted genome wide association study for subcutaneous fat thickness in a cohort population of 8,842 Korean individuals. These combined association studies in human and pig revealed a significant SNP located in a gene family with sequence similarity 73, member A (FAM73A) associated with subscapular skin-fold thickness in humans (rs4121165, GC-corrected p-value  = 0.0000175) and with backfat thickness in pigs (ASGA0029495, p-value  = 0.000031). Our combined association studies also suggest that eight neuronal genes are responsible for subcutaneous fat thickness: NEGR1, SLC44A5, PDE4B, LPHN2, ELTD1, ST6GALNAC3, ST6GALNAC5, and TTLL7. These results provide strong support for a major involvement of the CNS in the genetic predisposition to a common form of obesity.
doi:10.1371/journal.pone.0016356
PMCID: PMC3032728  PMID: 21311593
7.  Analysis of the contribution of FTO, NPC1, ENPP1, NEGR1, GNPDA2 and MC4R genes to obesity in Mexican children 
BMC Medical Genetics  2013;14:21.
Background
Recent genome wide association studies (GWAS) and previous positional linkage studies have identified more than 50 single nucleotide polymorphisms (SNPs) associated with obesity, mostly in Europeans. We aimed to assess the contribution of some of these SNPs to obesity risk and to the variation of related metabolic traits, in Mexican children.
Methods
The association of six European obesity-related SNPs in or near FTO, NPC1, ENPP1, NEGR1, GNPDA2 and MC4R genes with risk of obesity was tested in 1,463 school-aged Mexican children (Ncases = 514; Ncontrols = 949). We also assessed effects of these SNPs on the variation of body mass index (BMI), fasting serum insulin levels, fasting plasma glucose levels, total cholesterol and triglyceride levels, in a subset of 1,171 nonobese Mexican children.
Results
We found a significant effect of GNPDA2 rs10938397 on risk of obesity (odds ratio [OR] = 1.30; P = 1.34 × 10-3). Furthermore, we found nominal associations between obesity risk or BMI variation and the following SNPs: ENPP1 rs7754561, MC4R rs17782313 and NEGR1 rs2815752. Importantly, the at-risk alleles of both MC4R rs17782313 and NPC1 rs1805081 showed significant effect on increased fasting glucose levels (β = 0.36 mmol/L; P = 1.47 × 10-3) and decreased fasting serum insulin levels (β = −0.10 μU/mL; P = 1.21 × 10-3), respectively.
Conclusion
Our present results suggest that some obesity-associated SNPs previously reported in Europeans also associate with risk of obesity, or metabolic quantitative traits, in Mexican children. Importantly, we found new associations between MC4R and fasting glucose levels, and between NPC1 and fasting insulin levels.
doi:10.1186/1471-2350-14-21
PMCID: PMC3577489  PMID: 23375129
Obesity; Mexican children; Single nucleotide polymorphism
8.  Non-Replication of Genome-Wide Based Associations between Common Variants in INSIG2 and PFKP and Obesity in Studies of 18,014 Danes 
PLoS ONE  2008;3(8):e2872.
Background
The INSIG2 rs7566605 and PFKP rs6602024 polymorphisms have been identified as obesity gene variants in genome-wide association (GWA) studies. However, replication has been contradictory for both variants. The aims of this study were to validate these obesity-associations through case-control studies and analyses of obesity-related quantitative traits. Moreover, since environmental and genetic factors may modulate the impact of a genetic variant, we wanted to perform such interaction analyses. We focused on physical activity as an environmental risk factor, and on the GWA identified obesity variants in FTO (rs9939609) and near MC4R (rs17782313) as genetic risk factors.
Materials and Methods
The four variants were genotyped in a combined study sample comprising a total of 18,014 subject ascertained from, the population-based Inter99 cohort (n = 6,514), the ADDITION screening cohort (n = 8,662), a population-based study sample (n = 680) and a type 2 diabetic patient group (n = 2,158) from Steno Diabetes Center.
Results
No association with overweight, obesity or obesity-related measures was shown for either the INSIG2 rs7566605 or the PFKP rs6602024 variants. However, an interaction between the INSIG2 rs7566605 variant and the level of self-reported physical activity (pInt = 0.004) was observed. A BMI difference of 0.53 (SE 0.42) kg/m2 was found when comparing physically passive homozygous C-allele carriers with physically passive G-allele carriers. No interactions between the two variants and FTO rs9939609 and MC4R rs17782313 were observed.
Conclusions
The INSIG2 rs7566605 and PFKP rs6602024 polymorphisms play no apparent role in the development of common forms of obesity in the Danish population. However, if replicated, the INSIG2 rs7566605 may influence the level of BMI in combination with the level of physical activity.
doi:10.1371/journal.pone.0002872
PMCID: PMC2483934  PMID: 18682847
9.  Novel Genetic Loci Identified for the Pathophysiology of Childhood Obesity in the Hispanic Population 
PLoS ONE  2012;7(12):e51954.
Genetic variants responsible for susceptibility to obesity and its comorbidities among Hispanic children have not been identified. The VIVA LA FAMILIA Study was designed to genetically map childhood obesity and associated biological processes in the Hispanic population. A genome-wide association study (GWAS) entailed genotyping 1.1 million single nucleotide polymorphisms (SNPs) using the Illumina Infinium technology in 815 children. Measured genotype analysis was performed between genetic markers and obesity-related traits i.e., anthropometry, body composition, growth, metabolites, hormones, inflammation, diet, energy expenditure, substrate utilization and physical activity. Identified genome-wide significant loci: 1) corroborated genes implicated in other studies (MTNR1B, ZNF259/APOA5, XPA/FOXE1 (TTF-2), DARC, CCR3, ABO); 2) localized novel genes in plausible biological pathways (PCSK2, ARHGAP11A, CHRNA3); and 3) revealed novel genes with unknown function in obesity pathogenesis (MATK, COL4A1). Salient findings include a nonsynonymous SNP (rs1056513) in INADL (p = 1.2E-07) for weight; an intronic variant in MTNR1B associated with fasting glucose (p = 3.7E-08); variants in the APOA5-ZNF259 region associated with triglycerides (p = 2.5-4.8E-08); an intronic variant in PCSK2 associated with total antioxidants (p = 7.6E-08); a block of 23 SNPs in XPA/FOXE1 (TTF-2) associated with serum TSH (p = 5.5E-08 to 1.0E-09); a nonsynonymous SNP (p = 1.3E-21), an intronic SNP (p = 3.6E-13) in DARC identified for MCP-1; an intronic variant in ARHGAP11A associated with sleep duration (p = 5.0E-08); and, after adjusting for body weight, variants in MATK for total energy expenditure (p = 2.7E-08) and in CHRNA3 for sleeping energy expenditure (p = 6.0E-08). Unprecedented phenotyping and high-density SNP genotyping enabled localization of novel genetic loci associated with the pathophysiology of childhood obesity.
doi:10.1371/journal.pone.0051954
PMCID: PMC3522587  PMID: 23251661
10.  Genetic Susceptibility to Obesity and Related Traits in Childhood and Adolescence 
Diabetes  2010;59(11):2980-2988.
OBJECTIVE
Large-scale genome-wide association (GWA) studies have thus far identified 16 loci incontrovertibly associated with obesity-related traits in adults. We examined associations of variants in these loci with anthropometric traits in children and adolescents.
RESEARCH DESIGN AND METHODS
Seventeen variants representing 16 obesity susceptibility loci were genotyped in 1,252 children (mean ± SD age 9.7 ± 0.4 years) and 790 adolescents (15.5 ± 0.5 years) from the European Youth Heart Study (EYHS). We tested for association of individual variants and a genetic predisposition score (GPS-17), calculated by summing the number of effect alleles, with anthropometric traits. For 13 variants, summary statistics for associations with BMI were meta-analyzed with previously reported data (Ntotal = 13,071 children and adolescents).
RESULTS
In EYHS, 15 variants showed associations or trends with anthropometric traits that were directionally consistent with earlier reports in adults. The meta-analysis showed directionally consistent associations with BMI for all 13 variants, of which 9 were significant (0.033–0.098 SD/allele; P < 0.05). The near-TMEM18 variant had the strongest effect (0.098 SD/allele P = 8.5 × 10−11). Effect sizes for BMI tended to be more pronounced in children and adolescents than reported earlier in adults for variants in or near SEC16B, TMEM18, and KCTD15, (0.028–0.035 SD/allele higher) and less pronounced for rs925946 in BDNF (0.028 SD/allele lower). Each additional effect allele in the GPS-17 was associated with an increase of 0.034 SD in BMI (P = 3.6 × 10−5), 0.039 SD, in sum of skinfolds (P = 1.7 × 10−7), and 0.022 SD in waist circumference (P = 1.7 × 10−4), which is comparable with reported results in adults (0.039 SD/allele for BMI and 0.033 SD/allele for waist circumference).
CONCLUSIONS
Most obesity susceptibility loci identified by GWA studies in adults are already associated with anthropometric traits in children/adolescents. Whereas the association of some variants may differ with age, the cumulative effect size is similar.
doi:10.2337/db10-0370
PMCID: PMC2963559  PMID: 20724581
11.  Studies of CTNNBL1 and FDFT1 variants and measures of obesity: analyses of quantitative traits and case-control studies in 18,014 Danes 
BMC Medical Genetics  2009;10:17.
Background
A genome-wide scan in unrelated US Caucasians identified rs7001819 upstream of farnesyl-diphosphate farnesyltransferase 1 (FDFT1) and multiple variants within catenin (cadherin-associated protein), β-like 1 (CTNNBL1) to associate strongly with body mass index (BMI). The most significantly associating variants within CTNNBL1 including rs6013029 and rs6020846 were additionally confirmed to associate with morbid obesity in a French Caucasian case-control sample. The aim of this study was to investigate the impact of these three variants on obesity, through analyses of obesity-related quantitative traits, and case-control studies in large study samples of Danes.
Methods
The FDFT1 rs7001819, CTNNBL1 rs6013029 and rs6020846 were genotyped, using TaqMan allelic discrimination, in a combined study sample comprising 18,014 participants ascertained from; the population-based Inter99 cohort (n = 6,514), the ADDITION Denmark screening study cohort (n = 8,662), and a population-based sample (n = 680) and a type 2 diabetic patients group (n = 2,158) from Steno Diabetes Center.
Results
Both CTNNBL1 variants associated with body weight and height with per allele effect sizes of 1.0 [0.3–0.8] kg and 0.6 [0.2–0.9] cm, respectively, for the rs6020846 G-allele. No association was observed with BMI and waist circumference. In case-control studies neither of the CTNNBL1 variants showed association with overweight, obesity or morbid obesity (rs6013029: Odds Ratio (OR)overweight = 1.02 [0.90–1.16], ORobesity = 1.09 [0.95–1.25], ORmorbidobesity = 1.26 [0.91–1.74]; rs6020846: ORoverweight = 1.05 [0.93–1.18], ORobesity= 1.13 [1.00–1.28], ORmorbidobesity = 1.17 [0.86–1.61]). However, in meta-analyses of the present and the previous study, both the rs6013029 T-allele and the rs6020846 G-allele increased the risk of developing morbid obesity (rs6013029: ORcombined = 1.36 [1.12–1.64], p = 0.002; rs6020846: ORcombined = 1.26 [1.06–1.51], p = 0.01), and obesity (rs6013029: ORcombined = 1.17 [1.04–1.31], p = 0.007; rs6020846: ORcombined = 1.17 [1.05–1.30], p = 0.004).
The FDFT1 rs7001819 C-allele showed no association with obesity-related quantitative measures or dichotomous measures of overweight, obesity and morbid obesity.
Conclusion
CTNNBL1 variants associated with body weight and height, and confer the risk of developing obesity in meta-analyses combining the present and a previous study. FDFT1 rs7001819 showed no association with obesity, neither when analysing quantitative traits nor when performing case-control studies of obesity.
doi:10.1186/1471-2350-10-17
PMCID: PMC2669074  PMID: 19245693
12.  Genetic Variants in the Fat and Obesity Associated (FTO) Gene and Risk of Alzheimer's Disease 
PLoS ONE  2012;7(12):e50354.
Background
Recent studies showed that polymorphisms in the Fat and Obesity-Associated (FTO) gene have robust effects on obesity, obesity-related traits and endophenotypes associated with Alzheimer's disease (AD).
Methods
We used 1,877 Caucasian cases and controls from the NIA-LOAD study and 1,093 Caribbean Hispanics to further explore the association of FTO with AD. Using logistic regression, we assessed 42 SNPs in introns 1 and 2, the region previously reported to be associated with AD endophenotypes, which had been derived by genome-wide screenings. In addition, we performed gene expression analyses of neuropathologically confirmed AD cases and controls of two independent datasets (19 AD cases, 10 controls; 176 AD cases, 188 controls) using within- and between-group factors ANOVA of log10 transformed rank invariant normalized expression data.
Results
In the NIALOAD study, one SNP was significantly associated with AD and three additional markers were close to significance (rs6499640, rs10852521, rs16945088, rs8044769, FDR p-value: 0.050.9) with the previously reported SNPs. In the Caribbean Hispanic dataset, we identified three SNPs (rs17219084, rs11075996, rs11075997, FDR p-value: 0.009
Conclusions
Our data support the notion that genetic variation in Introns 1 and 2 of the FTO gene may contribute to AD risk.
doi:10.1371/journal.pone.0050354
PMCID: PMC3520931  PMID: 23251365
Current Genomics  2011;12(3):190-203.
Obesity in humans is a complex polygenic trait with high inter-individual heritability estimated at 40–70%. Candidate gene, DNA linkage and genome-wide association studies (GWAS) have allowed for the identification of a large set of genes and genomic regions associated with obesity. Structural chromosome abnormalities usually result in congenital anomalies, growth retardation and developmental delay. Occasionally, they are associated with hyperphagia and obesity rather than growth delay. We report four new individuals with structural chromosome abnormalities involving 10q22.3-23.2, 16p11.2 and Xq27.1-q28 chromosomal regions with early childhood obesity and developmental delay. We also searched and summarized the literature for structural chromosome abnormalities reported in association with childhood obesity.
doi:10.2174/138920211795677930
PMCID: PMC3137004  PMID: 22043167
Obesity; aCGH; chromosome; deletion; duplication; translocation; fluorescent in situ hybridization; CNV.
Genome Biology  2005;6(7):R59.
In order to evaluate metabolic pathways associated with obesity, global gene-expression data were integrated with phenotypic and genetic segregation analyses, identifying 13 metabolic pathways the genes of which are coordinately regulated in association with obesity. Four genomic regions were found to control the coordinated expression of these pathways and novel genes potentially associated with the identified pathways were identified.
Background
A segregating population of (C57BL/6J × DBA/2J)F2 intercross mice was studied for obesity-related traits and for global gene expression in liver. Quantitative trait locus analyses were applied to the subcutaneous fat-mass trait and all gene-expression data. These data were then used to identify gene sets that are differentially perturbed in lean and obese mice.
Results
We integrated global gene-expression data with phenotypic and genetic segregation analyses to evaluate metabolic pathways associated with obesity. Using two approaches we identified 13 metabolic pathways whose genes are coordinately regulated in association with obesity. Four genomic regions on chromosomes 3, 6, 16, and 19 were found to control the coordinated expression of these pathways. Using criteria that included trait correlation, differential gene expression, and linkage to genomic regions, we identified novel genes potentially associated with the identified pathways.
Conclusion
This study demonstrates that genetic and gene-expression data can be integrated to identify pathways associated with clinical traits and their underlying genetic determinants.
doi:10.1186/gb-2005-6-7-r59
PMCID: PMC1175990  PMID: 15998448
Nucleic Acids Research  2006;34(10):3067-3081.
Genome-wide experimental methods to identify disease genes, such as linkage analysis and association studies, generate increasingly large candidate gene sets for which comprehensive empirical analysis is impractical. Computational methods employ data from a variety of sources to identify the most likely candidate disease genes from these gene sets. Here, we review seven independent computational disease gene prioritization methods, and then apply them in concert to the analysis of 9556 positional candidate genes for type 2 diabetes (T2D) and the related trait obesity. We generate and analyse a list of nine primary candidate genes for T2D genes and five for obesity. Two genes, LPL and BCKDHA, are common to these two sets. We also present a set of secondary candidates for T2D (94 genes) and for obesity (116 genes) with 58 genes in common to both diseases.
doi:10.1093/nar/gkl381
PMCID: PMC1475747  PMID: 16757574
BMC Systems Biology  2011;5(Suppl 2):S13.
Background
Current Genome-Wide Association Studies (GWAS) are performed in a single trait framework without considering genetic correlations between important disease traits. Hence, the GWAS have limitations in discovering genetic risk factors affecting pleiotropic effects.
Results
This work reports a novel data mining approach to discover patterns of multiple phenotypic associations over 52 anthropometric and biochemical traits in KARE and a new analytical scheme for GWAS of multivariate phenotypes defined by the discovered patterns. This methodology applied to the GWAS for multivariate phenotype highLDLhighTG derived from the predicted patterns of the phenotypic associations. The patterns of the phenotypic associations were informative to draw relations between plasma lipid levels with bone mineral density and a cluster of common traits (Obesity, hypertension, insulin resistance) related to Metabolic Syndrome (MS). A total of 15 SNPs in six genes (PAK7, C20orf103, NRIP1, BCL2, TRPM3, and NAV1) were identified for significant associations with highLDLhighTG. Noteworthy findings were that the significant associations included a mis-sense mutation (PAK7:R335P), a frame shift mutation (C20orf103) and SNPs in splicing sites (TRPM3).
Conclusions
The six genes corresponded to rat and mouse quantitative trait loci (QTLs) that had shown associations with the common traits such as the well characterized MS and even tumor susceptibility. Our findings suggest that the six genes may play important roles in the pleiotropic effects on lipid metabolism and the MS, which increase the risk of Type 2 Diabetes and cardiovascular disease. The use of the multivariate phenotypes can be advantageous in identifying genetic risk factors, accounting for the pleiotropic effects when the multivariate phenotypes have a common etiological pathway.
doi:10.1186/1752-0509-5-S2-S13
PMCID: PMC3287479  PMID: 22784570
Twenty-two single-nucleotide polymorphisms (SNPs) in 10 gene regions previously identified in obesity and type 2 diabetes (T2D) genome-wide association studies (GWAS) were evaluated for association with metabolic traits in a sample from an island population of European descent. We performed a population-based study using 18 anthropometric and biochemical traits considered as continuous variables in a sample of 843 unrelated subjects (360 men and 483 women) aged 18–80 years old from the island of Hvar on the eastern Adriatic coast of Croatia. All eight GWAS SNPs in FTO were significantly associated with weight, body mass index, waist circumference and hip circumference; 20 of the 32 nominal P-values remained significant after permutation testing for multiple corrections. The strongest associations were found between the two TCF7L2 GWAS SNPs with fasting plasma glucose and HbA1c levels, all four P-values remained significant after permutation tests. Nominally significant associations were found between several SNPs and other metabolic traits; however, the significance did not hold after permutation tests. Although the sample size was modest, our study strongly replicated the association of FTO variants with obesity-related measures and TCF7L2 variants with T2D-related traits. The estimated effect sizes of these variants were larger or comparable to published studies. This is likely attributable to the homogenous genetic background of the relatively isolated study population.
doi:10.1038/ejhg.2010.178
PMCID: PMC3061997  PMID: 21150882
genetic association; obesity; type 2 diabetes; FTO; TCF7L2; isolated population
PLoS ONE  2011;6(9):e23944.
Background
Obesity and metabolic syndrome results from a complex interaction between genetic and environmental factors. In addition to brain-regulated processes, recent genome wide association studies have indicated that genes highly expressed in adipose tissue affect the distribution and function of fat and thus contribute to obesity. Using a stratified transcriptome gene enrichment approach we attempted to identify adipose tissue-specific obesity genes in the unique polygenic Fat (F) mouse strain generated by selective breeding over 60 generations for divergent adiposity from a comparator Lean (L) strain.
Results
To enrich for adipose tissue obesity genes a ‘snap-shot’ pooled-sample transcriptome comparison of key fat depots and non adipose tissues (muscle, liver, kidney) was performed. Known obesity quantitative trait loci (QTL) information for the model allowed us to further filter genes for increased likelihood of being causal or secondary for obesity. This successfully identified several genes previously linked to obesity (C1qr1, and Np3r) as positional QTL candidate genes elevated specifically in F line adipose tissue. A number of novel obesity candidate genes were also identified (Thbs1, Ppp1r3d, Tmepai, Trp53inp2, Ttc7b, Tuba1a, Fgf13, Fmr) that have inferred roles in fat cell function. Quantitative microarray analysis was then applied to the most phenotypically divergent adipose depot after exaggerating F and L strain differences with chronic high fat feeding which revealed a distinct gene expression profile of line, fat depot and diet-responsive inflammatory, angiogenic and metabolic pathways. Selected candidate genes Npr3 and Thbs1, as well as Gys2, a non-QTL gene that otherwise passed our enrichment criteria were characterised, revealing novel functional effects consistent with a contribution to obesity.
Conclusions
A focussed candidate gene enrichment strategy in the unique F and L model has identified novel adipose tissue-enriched genes contributing to obesity.
doi:10.1371/journal.pone.0023944
PMCID: PMC3168488  PMID: 21915269
Journal of Obesity  2011;2011:845148.
Obesity is a major health problem and an immense economic burden on the health care systems both in the United States and the rest of the world. The prevalence of obesity in children and adults in the United States has increased dramatically over the past decade. Besides environmental factors, genetic factors are known to play an important role in the pathogenesis of obesity. Genome-wide association studies (GWAS) have revealed strongly associated genomic variants associated with most common disorders; indeed there is general consensus on these findings from generally positive replication outcomes by independent groups. To date, there have been only a few GWAS-related reports for childhood obesity specifically, with studies primarily uncovering loci in the adult setting instead. It is clear that a number of loci previously reported from GWAS analyses of adult BMI and/or obesity also play a role in childhood obesity.
doi:10.1155/2011/845148
PMCID: PMC3136227  PMID: 21773009
There is currently a lot of interest in the role of genomic imprinting in mammalian development. Many human diseases, such as cancer, obesity, diabetes and behavioral traits, may be related to imprinted genes. When searching for genes related to complex disorders, the power of genome-wide association analysis can be improved by introducing parent-of-origin effects into the analyses. For quantitative traits, family-based TDT analysis has successfully implemented such an approach. Although attractive for several reasons, TDT-based tests are known to be less powerful than methods based on measured genotype approaches. In this study, we describe a fast, powerful method for detecting parent-of-origin effects in studies of quantitative traits using a measured genotype framework. First, for each locus studied, we estimate the probabilities of an allele's parental origin using multipoint haplotype reconstruction. Next, we introduce the parental origin of these alleles as a covariate in regression models during the second step of GRAMMAR, a fast approximation to the measured genotype approach. We show that, compared with a TDT-based analysis, our method has a higher power to detect a locus exhibiting a parent-of-origin effect. Moreover, our method is applicable to a wider range of data, including pedigree structures that are not very informative for TDT. The method gives no false positives in the absence of parent-of-origin effects, under both additive and dominant models. As this method is an extension of the rapid GRAMMAR analysis, it is fast enough to be suitable for genome-wide association scans.
doi:10.1038/ejhg.2009.167
PMCID: PMC2987227  PMID: 19809476
genome-wide association; quantitative traits; parent-of-origin; power; haplotype
People with obesity, especially extreme obesity, are at risk for many health problems. However, the responsible genes remain unknown in >95% of severe obesity cases. Our previous genome-wide scan of Wagyu x Limousin F2 cattle crosses with extreme phenotypes revealed a molecular marker significantly associated with intramuscular fat deposition. Characterization of this marker showed that it is orthologous to the human gene KIAA1462 located on HSA10p11.23, where a major quantitative trait locus for morbid obesity has been reported. The newly identified mitochondrial poly(A) polymerase associated domain containing 1 (PAPD1) gene, which is located near this marker, is particularly interesting because the polymerase is required for the polyadenylation and stabilization of mammalian mitochondrial mRNAs. In the present study, both cDNA and genomic DNA sequences were annotated for the bovine PAPD1 gene and ten genetic markers were detected in the promoter and exon 1 region. Among seven markers assayed on ~ 250 Wagyu x Limousin F2 animals, two single nucleotide polymorphisms (SNPs) in the promoter region were significantly associated with intramuscular fat (P<0.05). However, there was a significant interaction (P<0.05) between a third SNP, which causes an amino acid change in coding exon 1, and each of these two promoter SNPs on intramuscular fat deposition. In particular, the differences between double heterozygous animals at two polymorphic sites and the slim genotype animals exceeded 2.3 standard deviations for the trait in both cases. Our study provides evidence for a new mechanism – the involvement of compound heterosis in extreme obesity, which warrants further examination.
PMCID: PMC1483122  PMID: 16810331
PAPD1; Nuclear-encoded mitochondrial gene; Polymorphisms; Compound heterosis; Extreme obesity.
Diabetes  2010;59(12):3085-3089.
OBJECTIVE
Childhood obesity strongly predisposes to some adult diseases. Recently, genome-wide association (GWA) studies in Caucasians identified multiple single nucleotide polymorphisms (SNPs) associated with BMI and obesity. The associations of those SNPs with BMI and obesity among other ethnicities are not fully described, especially in children. Among those previously identified SNPs, we selected six (rs7138803, rs1805081, rs6499640, rs17782313, rs6265, and rs10938397, in or near obesity-related genes FAIM2, NPC1, FTO, MC4R, BDNF, and GNPDA2, respectively) because of the relatively high minor allele frequencies in Chinese individuals and tested the associations of the SNPs with BMI and obesity in Chinese children.
RESEARCH DESIGN AND METHODS
We investigated the associations of these SNPs with BMI and obesity in school-aged children. A total of 3,503 children participated in the study, including 1,229 obese, 655 overweight, and 1,619 normal-weight children (diagnosed by the Chinese age- and sex-specific BMI cutoffs).
RESULTS
After age and sex adjustment and correction for multiple testing, the SNPs rs17782313, rs6265, and rs10938397 were associated with BMI (P = 1.0 × 10−5, 0.038, and 0.00093, respectively) and also obesity (P = 5.0 × 10−6, 0.043, and 0.00085, respectively) in the Chinese children. The SNPs rs17782313 and rs10938397 were also significantly associated with waist circumference, waist-to-height ratio, and fat mass percentage.
CONCLUSIONS
Results of this study support obesity-related genes in adults as important genes for BMI variation in children and suggest that some SNPs identified by GWA studies in Caucasians also confer risk for obesity in Chinese children.
doi:10.2337/db10-0273
PMCID: PMC2992769  PMID: 20843981
Obesity (Silver Spring, Md.)  2008;16(Suppl 3):S79-S81.
Obesity is a classical complex trait, influenced by both genetic and lifestyle factors. The number of obesity gene variants is currently unknown but, based on sound evolutionary principles, likely to be many, each with a modest effect on the phenotype. Recent advances in our knowledge of variation in the human genome and high throughput genotyping technologies have made possible genome-wide association (GWA) analysis and the identification of bona fide susceptibility genes for many complex diseases and phenotypes, including obesity and its comorbid conditions. GWA analysis in even larger numbers of individuals through collaborative efforts of many investigators will likely identify those polygenes of moderate and modest effect size that manifest in our typical environment. Once the subset of real-world-relevant obesity susceptibility variants is identified, follow-up studies, including detailed molecular analysis of the loci, stratified analyses, prospective and interventional studies in humans, and mechanistic studies in cells and animals will allow us to define the genetic architecture of the locus and dissect how these genes interact with specific environmental and other factors. The molecular and analytical tools to accomplish these goals are now in hand, but cooperation among investigators will be necessary to amass the requisite numbers of phenotyped and genotyped individuals. Identification of susceptibility genes for obesity and determining how they interact with each other and the environment will lead to new insights into the molecular, cellular, and physiological basis of energy homeostasis, and novel strategies for prevention and treatment.
doi:10.1038/oby.2008.523
PMCID: PMC2703439  PMID: 19037219
BMJ Open  2012;2(3):e000873.
Background
Obesity is a complex trait with both environmental and genetic contributors. Genome-wide association studies have identified several variants that are robustly associated with obesity and body mass index (BMI), many of which are found within genes involved in appetite regulation. Currently, genetic association data for obesity are lacking in Africans—a single genome-wide association study and a few replication studies have been published in West Africa, but none have been performed in a South African population.
Objective
To assess the association of candidate loci with BMI in black South Africans. The authors focused on single nucleotide polymorphisms (SNPs) in the FTO, LEP, LEPR, MC4R, NPY2R and POMC genes.
Design
A genetic association study.
Participants
990 randomly selected individuals from the larger Birth to Twenty cohort (a longitudinal birth cohort study of health and development in Africans).
Measures
The authors genotyped 44 SNPs within the six candidate genes that included known BMI-associated SNPs and tagSNPs based on linkage disequilibrium in an African population for FTO, LEP and NPY2R. To assess population substructure, the authors included 18 ancestry informative markers. Weight, height, sex, sex-specific pubertal stage and exact age collected during adolescence (13 years) were used to identify loci that predispose to obesity early in life.
Results
Sex, sex-specific pubertal stage and exact age together explain 14.3% of the variation in log(BMI) at age 13. After adjustment for these factors, four SNPs were individually significantly associated with BMI: FTO rs17817449 (p=0.022), LEP rs10954174 (p=0.0004), LEP rs6966536 (p=0.012) and MC4R rs17782313 (p=0.045). Together the four SNPs account for 2.1% of the variation in log(BMI). Each risk allele was associated with an estimated average increase of 2.5% in BMI.
Conclusions
The study highlighted SNPs in FTO and MC4R as potential genetic markers of obesity risk in South Africans. The association with two SNPs in the 3′ untranslated region of the LEP gene is novel.
Article summary
Article focus
This is a replication study aiming to reproduce BMI association findings from European cohorts in a South African population.
This study focused on genes linked to appetite control that were previously reported to show association with BMI or obesity and included FTO, LEP, LEPR, MC4R, NPY2R and POMC.
Adolescent data were used to facilitate the identification of genetic loci that predispose to obesity early in life, as it is known that overweight/obese children have an elevated risk of becoming obese adults.
Key messages
We found four SNPs were individually significantly associated with BMI: FTO rs17817449 (p=0.022), LEP rs10954174 (p=0.0004), LEP rs6966536 (p=0.012) and MC4R rs17782313 (p=0.045).
Together the four SNPs account for 2.1% of the variation in log(BMI).
We also demonstrated that an accumulation of risk alleles is linked to a significant increase in BMI—individuals with seven risk alleles had an 11.0% increase in median BMI compared with those with two risk alleles.
Strengths and limitations of this study
This study provides the first preliminary evidence of the role of genetic variants in obesity risk in an adolescent black South African population.
This study was only moderately powered to detect association with BMI, and not all genes were exhaustively investigated.
TagSNP selection would have been enhanced if South African data were available for this approach.
doi:10.1136/bmjopen-2012-000873
PMCID: PMC3358621  PMID: 22614171
Molecular genetics and metabolism  2011;104(4):661-665.
Genetic variation in SIRT1 affects obesity-related phenotypes in several populations. The purpose of this study was to determine whether variation in SIRT1 affects susceptibility to obesity or type 2 diabetes in Pima Indians, a population with very high prevalence and incidence rates of these diseases. Genotypic data from single nucleotide polymorphisms (SNPs) identified by sequencing regions of SIRT1 combined with SNPs in/near SIRT1 from a prior genome-wide association study determined that 4 tag SNPs (rs7895833, rs10509291, rs7896005, and rs4746720) could capture information across this gene and its adjacent 5′ region. The tag SNPs were genotyped in a population-based sample of 3501 Pima Indians (44% had diabetes, 58% female) for association with type 2 diabetes and BMI. Metabolic trait data and adipose biopsies were available on a subset of these subjects. Two tag SNPs, rs10509291 and rs7896005, were nominally associated with type 2 diabetes (P = 0.01, OR = 1.25 95%CI 1.05-1.48, and P = 0.02, OR = 1.17 95%CI 1.02-1.34, respectively; additive P values adjusted for age, sex, birth year, and family membership), but not BMI (adjusted P values 0.52 and 0.45, respectively). Among metabolically characterized subjects with normal glucose tolerance (N = 243), those carrying the diabetes risk allele (T) for rs10509291 and (G) for rs7896005 had a reduced acute insulin response (AIR) to an intravenous glucose bolus (adjusted P = 0.045 and 0.035, respectively). SIRT1 expression in adipose biopsies was negatively correlated with BMI (adjusted P = 0.00001). We conclude that variation in SIRT1 is nominally associated with reduced AIR and increased risk for type 2 diabetes. SIRT1 expression in adipose is correlated with BMI, but it remains unknown whether this is a cause or consequence of obesity.
doi:10.1016/j.ymgme.2011.08.001
PMCID: PMC3224181  PMID: 21871827
SIRT1; type 2 diabetes; insulin secretion; genetic associations

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