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1.  Large Copy-Number Variations Are Enriched in Cases With Moderate to Extreme Obesity 
Diabetes  2010;59(10):2690-2694.
OBJECTIVE
Obesity is an increasingly common disorder that predisposes to several medical conditions, including type 2 diabetes. We investigated whether large and rare copy-number variations (CNVs) differentiate moderate to extreme obesity from never-overweight control subjects.
RESEARCH DESIGN AND METHODS
Using single nucleotide polymorphism (SNP) arrays, we performed a genome-wide CNV survey on 430 obese case subjects (BMI >35 kg/m2) and 379 never-overweight control subjects (BMI <25 kg/m2). All subjects were of European ancestry and were genotyped on the Illumina HumanHap550 arrays with ∼550,000 SNP markers. The CNV calls were generated by PennCNV software.
RESULTS
CNVs >1 Mb were found to be overrepresented in case versus control subjects (odds ratio [OR] = 1.5 [95% CI 0.5–5]), and CNVs >2 Mb were present in 1.3% of the case subjects but were absent in control subjects (OR = infinity [95% CI 1.2–infinity]). When focusing on rare deletions that disrupt genes, even more pronounced effect sizes are observed (OR = 2.7 [95% CI 0.5–27.1] for CNVs >1 Mb). Interestingly, obese case subjects who carry these large CNVs have moderately high BMI and do not appear to be extreme cases. Several CNVs disrupt known candidate genes for obesity, such as a 3.3-Mb deletion disrupting NAP1L5 and a 2.1-Mb deletion disrupting UCP1 and IL15.
CONCLUSIONS
Our results suggest that large CNVs, especially rare deletions, confer risk of obesity in patients with moderate obesity and that genes impacted by large CNVs represent intriguing candidates for obesity that warrant further study.
doi:10.2337/db10-0192
PMCID: PMC3279563  PMID: 20622171
2.  A genome wide association study of plasma uric acid levels in obese cases and never-overweight controls 
Obesity (Silver Spring, Md.)  2013;21(9):E490-E494.
Objective
To identify plasma uric acid related genes in extremely obese and normal weight individuals using genome wide association studies (GWAS).
Design and Methods
Using genotypes from a GWAS focusing on obesity and thinness, we performed quantitative trait association analyses (PLINK) for plasma uric acid levels in 1,060 extremely obese individuals [body mass index (BMI) >35 kg/m2] and normal-weight controls (BMI<25kg/m2). In 961 samples with uric acid data, 924 were females.
Results
Significant associations were found in SLC2A9 gene SNPs and plasma uric acid levels (rs6449213, P=3.15×10−12). DIP2C gene SNP rs877282 also reached genome wide significance(P=4,56×10−8). Weaker associations (P<1×10−5) were found in F5, PXDNL, FRAS1, LCORL, and MICAL2genes. Besides SLC2A9, 3 previously identified uric acid related genes ABCG2 (rs2622605, P=0.0026), SLC17A1 (rs3799344, P=0.0017), and RREB1 (rs1615495, P =0.00055) received marginal support in our study.
Conclusions
Two genes/chromosome regions reached genome wide association significance (P< 1× 10−7, 550K SNPs) in our GWAS : SLC2A9, the chromosome 2 60.1 Mb region (rs6723995), and the DIP2C gene region. Five other genes (F5, PXDNL, FRAS1, LCORL, and MICAL2) yielded P<1× 10−5. Four previous reported associations were replicated in our study, including SLC2A9, ABCG2, RREB, and SLC17A1.
doi:10.1002/oby.20303
PMCID: PMC3762924  PMID: 23703922
uric acid; genome wide association study; obesity
3.  Nutrient preference and diet-induced adiposity in C57BL/6ByJ and 129P3/J mice 
Physiology & behavior  2001;72(4):603-613.
Purified carbohydrates and fats are usually palatable to humans and other animals, and their consumption often induces weight gain and accumulation of fat. In this study, we examined consumption of complex carbohydrates (cornstarch and Polycose) and fats (soybean oil and margarine) in mice from two inbred strains, C57BL/6ByJ and 129P3/J. At lower concentrations of liquid nutrients tested using two-bottle tests, when the amounts consumed had negligible energy content, the C57BL/6ByJ mice had higher acceptance of Polycose and soybean oil. This was probably due to strain differences in chemosensory perception of Polycose and oil. At higher concentrations, the mice consumed a substantial part of their daily energy from the macronutrient sources, however, there were no or only small strain differences in nutrient consumption. These small differences were probably due to strain variation in body size. The two strains also did not differ in chow intake. Despite similar energy intakes, access to the nutrients resulted in greater body weight (BW) gain in the C57BL/6ByJ mice than in the 129P3/J mice. The diet-induced weight gain was examined in detail in groups of 2-month-old C57BL/6ByJ and 129P3/J mice given ether chow, or chow and margarine to eat. Access to margarine did not increase total energy consumption of either strain. It increased BW and adiposity of the C57BL/6ByJ mice, but only after they reached the age of ~3 months. There were no differences in BW and adiposity between control and margarine-exposed 129P3/J mice. The results suggest that diet-induced adiposity in the B6 mice depends on age and does not depend on hyperphagia.
PMCID: PMC3341942  PMID: 11282146
Carbohydrate; Fat; Polycose; Starch; Energy intake; Obesity; Mouse strains; Genotype
4.  Correction: A Genome-Wide Association Study on Obesity and Obesity-Related Traits 
PLoS ONE  2012;7(2):10.1371/annotation/a34ee94e-3e6a-48bd-a19e-398a4bb88580.
doi:10.1371/annotation/a34ee94e-3e6a-48bd-a19e-398a4bb88580
PMCID: PMC3293772
5.  Loci on Chromosomes 2, 4, 9, and 16 for body weight, body length, and adiposity identified in a genome scan of an F2 intercross between the 129P3/J and C57BL/6ByJ mouse strains 
Mice have proved to be a powerful model organism for understanding obesity in humans. Single gene mutants and genetically modified mice have been used to identify obesity genes, and the discovery of loci for polygenic forms of obesity in the mouse is an important next step. To pursue this goal, the inbred mouse strains 129P3/J (129) and C57BL/6ByJ (B6), which differ in body weight, body length, and adiposity, were used in an F2 cross to identify loci affecting these phenotypes. Linkages were determined in a two-phase process. In the first phase, 169 randomly selected F2 mice were genotyped for 134 markers that covered all autosomes and the X Chromosome (Chr). Significant linkages were found for body weight and body length on Chr 2. In addition, we detected several suggestive linkages on Chr 2 (adiposity), 9 (body weight, body length, and adiposity), and 16 (adiposity), as well as two suggestive sex-dependent linkages for body length on Chrs 4 and 9. In the second phase, 288 additional F2 mice were genotyped for markers near these regions of linkage. In the combined set of 457 F2 mice, six significant linkages were found: Chr 2 (Bwq5, body weight and Bdln3, body length), Chr 4 (Bdln6, body length, males only), Chr 9 (Bwq6, body weight and Adip5, adiposity), and Chr 16 (Adip9, adiposity), as well as several suggestive linkages (Adip2, adiposity on Chr 2; Bdln4 and Bdln5, body length on Chr 9). In addition, there was a suggestive linkage to body length in males on Chr 9 (Bdln4). For adiposity, there was evidence for epistatic interactions between loci on Chr 9 (Adip5) and 16 (Adip9). These results reinforce the concept that obesity is a complex trait. Genetic loci and their interactions, in conjunction with sex, age, and diet, determine body size and adiposity in mice.
doi:10.1007/s00335-002-2170-y
PMCID: PMC1435867  PMID: 12856282
6.  FTO gene SNPs associated with extreme obesity in cases, controls and extremely discordant sister pairs 
Background
FTO is a gene located in chromosome region 16q12.2. Recently two studies have found associations of several single nucleotide polymorphisms (SNPs) in FTO with body mass index (BMI) and obesity, particularly rs1421085, rs17817449, and rs9939609.
Methods
We examined these three SNPs in 583 extremely obese women with current BMI greater than 35 kg/m2 and lifetime BMI greater than 40 kg/m2, and 544 controls who were currently normal weight (BMI<25 kg/m2) and had never been overweight during their lifetimes.
Results
We detected highly significant associations of obesity with alleles in all three SNPs (p < 10-9). The strongest association was with rs1421085 (p = 3.04 × 10-10, OR = 1.75, CI = 1.47–2.08). A subset of 99 cases had extremely discordant sisters with BMI<25 kg/m2. The discordant sisters differed in allele and genotype frequencies in parallel with the overall case and control sample. The strongest association was with rs17817449 (z = 3.57, p = 3.6 × 10-4).
Conclusion
These results suggest common variability in FTO is associated with increased obesity risk or resistance and may in part account for differences between closely related individuals.
doi:10.1186/1471-2350-9-4
PMCID: PMC2254593  PMID: 18218107
8.  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

Results 1-8 (8)