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A 3-month-old patient presented for evaluation by plastic surgery with marked trigonocephaly and was subsequently diagnosed with metopic craniosynostosis. During presurgical evaluation, the patient was found to have two variants of the NOTCH3 gene, resulting in the diagnosis of lateral meningocele (Lehman) syndrome. Due to the increased possibility of stroke associated with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, the patient underwent only anterior calvarial vault remodeling without fronto-orbital advancement for correction of her craniosynostosis. This unique constellation of symptoms, and its impact on operative management, has not been previously described in the literature.

Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, P = 3.4 × 10(-11)) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, P = 1.2 × 10(-10)). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, P = 6.9 × 10(-8)). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial P = 9.7 × 10(-7)), five of which reached genome-wide significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.

Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 × 10⁻⁸): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity. © 2009 Nature America, Inc. All rights reserved.

Motivation: Adjustment for population structure is necessary to avoid bias in genetic association studies of susceptibility variants for complex diseases. Population structure may differ from one genomic region to another due to the variability of individual ancestry associated with migration, random genetic drift or natural selection. Current association methods for correcting population stratification usually involve adjustment of global ancestry between study subjects. Results: We suggest interrogating local population structure for fine mapping to more accurately locate true casual genes by better adjusting the confounding effect due to local ancestry. By extensive simulations on genome-wide datasets, we show that adjusting global ancestry may lead to false positives when local population structure is an important confounding factor. In contrast, adjusting local ancestry can effectively prevent false positives due to local population structure and thus can improve fine mapping for disease gene localization. We applied the local and global adjustments to the analysis of datasets from three genome-wide association studies, including European Americans, African Americans and Nigerians. Both European Americans and African Americans demonstrate greater variability in local ancestry than Nigerians. Adjusting local ancestry successfully eliminated the known spurious association between SNPs in the LCT gene and height due to the population structure existed in European Americans. Contact: xiaofeng.zhu@case.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Genome-wide association (GWA) studies have identified common variants that are associated with a variety of traits and diseases, but most studies have been performed in European-derived populations. Here, we describe the first genome-wide analyses of imputed genotype and copy number variants (CNVs) for anthropometric measures in African-derived populations: 1188 Nigerians from Igbo-Ora and Ibadan, Nigeria, and 743 African-Americans from Maywood, IL. To improve the reach of our study, we used imputation to estimate genotypes at approximately 2.1 million single-nucleotide polymorphisms (SNPs) and also tested CNVs for association. No SNPs or common CNVs reached a genome-wide significance level for association with height or body mass index (BMI), and the best signals from a meta-analysis of the two cohorts did not replicate in approximately 3700 African-Americans and Jamaicans. However, several loci previously confirmed in European populations showed evidence of replication in our GWA panel of African-derived populations, including variants near IHH and DLEU7 for height and MC4R for BMI. Analysis of global burden of rare CNVs suggested that lean individuals possess greater total burden of CNVs, but this finding was not supported in an independent European population. Our results suggest that there are not multiple loci with strong effects on anthropometric traits in African-derived populations and that sample sizes comparable to those needed in European GWA studies will be required to identify replicable associations. Meta-analysis of this data set with additional studies in African-ancestry populations will be helpful to improve power to detect novel associations.

The failure of researchers to replicate genetic-association findings is most commonly attributed to insufficient statistical power, population stratification, or various forms of between-study heterogeneity or environmental influences.(1) Here, we illustrate another potential cause for nonreplications that has so far not received much attention in the literature. We illustrate that the strength of a genetic effect can vary by age, causing "age-varying associations." If not taken into account during the design and the analysis of a study, age-varying genetic associations can cause nonreplication. By using the 100K SNP scan of the Framingham Heart Study, we identified an age-varying association between a SNP in ROBO1 and obesity and hypothesized an age-gene interaction. This finding was followed up in eight independent samples comprising 13,584 individuals. The association was replicated in five of the eight studies, showing an age-dependent relationship (one-sided combined p = 3.92 x 10(-9), combined p value from pediatric cohorts = 2.21 x 10(-8), combined p value from adult cohorts = 0.00422). Furthermore, this study illustrates that it is difficult for cross-sectional study designs to detect age-varying associations. If the specifics of age- or time-varying genetic effects are not considered in the selection of both the follow-up samples and in the statistical analysis, important genetic associations may be missed.

OBJECTIVE—Functional studies suggest that the nonsynonymous K121Q polymorphism in the ectoenzyme nucleotide pyrophosphate phosphodiesterase 1 (ENPP1) may confer susceptibility to insulin resistance; genetic evidence on its effect on type 2 diabetes, however, has been conflicting. We therefore conducted a new meta-analysis that includes novel unpublished data from the ENPP1 Consortium and recent negative findings from large association studies to address the contribution of K121Q to type 2 diabetes. RESEARCH DESIGN AND METHODS—After a systematic review of the literature, we evaluated the effect of ENPP1 K121Q on diabetes risk under three genetic models using a random-effects approach. Our primary analysis consisted of 30 studies comprising 15,801 case and 26,241 control subjects. Due to considerable heterogeneity and large differences in allele frequencies across populations, we limited our meta-analysis to those of self-reported European descent and, when available, included BMI as a covariate. RESULTS—We found a modest increase in risk of type 2 diabetes for QQ homozygotes in white populations (combined odds ratio [OR] 1.38 [95% CI 1.10–1.74], P = 0.005). There was no evidence of publication bias, but we noted significant residual heterogeneity among studies (P = 0.02). On meta-regression, 16% of the effect was accounted for by the mean BMI of control subjects. This association was stronger in studies in which control subjects were leaner but disappeared after adjustment for mean control BMI (combined OR 0.93 [95% CI 0.75–1.15], P = 0.50). CONCLUSIONS—The ENPP1 Q121 variant increases risk of type 2 diabetes under a recessive model of inheritance in whites, an effect that appears to be modulated by BMI.

The neuropeptide Y (NPY) family of peptides and receptors regulate food intake. Inherited variation in this pathway could influence susceptibility to obesity and its complications, including type 2 diabetes. We genotyped a set of 71 single nucleotide polymorphisms (SNPs) that capture the most common variation in NPY, PPY, PYY, NPY1R, NPY2R, and NPY5R in 2,800 individuals of recent European ancestry drawn from the near extremes of BMI distribution. Five SNPs located upstream of NPY2R were nominally associated with BMI in men (P values = 0.001–0.009, odds ratios [ORs] 1.27–1.34). No association with BMI was observed in women, and no consistent associations were observed for other genes in this pathway. We attempted to replicate the association with BMI in 2,500 men and tested these SNPs for association with type 2 diabetes in 8,000 samples. We observed association with BMI in men in only one replication sample and saw no association in the combined replication samples (P = 0.154, OR = 1.09). Finally, a 9% haplotype was associated with type 2 diabetes in men (P = 1.73 × 10−4, OR = 1.36) and not in women. Variation in this pathway likely does not have a major influence on BMI, although small effects cannot be ruled out; NPY2R should be considered a candidate gene for type 2 diabetes in men.

The common missense single nucleotide polymorphism (SNP) K121Q in the ectoenzyme nucleotide pyrophosphate phosphodiesterase (ENPP1) gene has recently been associated with type 2 diabetes in Italian, U.S., and South-Asian populations. A three-SNP haplotype, including K121Q, has also been associated with obesity and type 2 diabetes in French and Austrian populations. We set out to confirm these findings in several large samples. We genotyped the haplotype K121Q (rs1044498), rs1799774, and rs7754561 in 8,676 individuals of European ancestry with and without type 2 diabetes, in 1,900 obese and 930 lean individuals of European ancestry from the U.S. and Poland, and in 1,101 African-American individuals. Neither the K121Q missense polymorphism nor the putative risk haplotype were significantly associated with type 2 diabetes or BMI. Two SNPs showed suggestive evidence of association in a meta-analysis of our European ancestry samples. These SNPs were rs7754561 with type 2 diabetes (odds ratio for the G-allele, 0.85 [95% CI 0.78–0.92], P = 0.00003) and rs1799774 with BMI (homozygotes of the delT-allele, 0.6 [0.42–0.88], P = 0.007). However, these findings are not supported by other studies. We did not observe a reproducible association between these three ENPP1 variants and BMI or type 2 diabetes.

A general question for linkage disequilibrium-based association studies is how power to detect an association is compromised when tag SNPs are chosen from data in one population sample and then deployed in another sample. Specifically, it is important to know how well tags picked from the HapMap DNA samples capture the variation in other samples. To address this, we collected dense data uniformly across the four HapMap population samples and eleven other population samples. We picked tag SNPs using genotype data we collected in the HapMap samples and then evaluated the effective coverage of these tags in comparison to the entire set of common variants observed in the other samples. We simulated case-control association studies in the non-HapMap samples under a disease model of modest risk, and we observed little loss in power. These results demonstrate that the HapMap DNA samples can be used to select tags for genome-wide association studies in many samples around the world.

Population stratification occurs in case-control association studies when allele frequencies differ between cases and controls because of ancestry. Stratification may lead to false positive associations, although this issue remains controversial. Empirical studies have found little evidence of stratification in European-derived populations, but potentially significant levels of stratification could not be ruled out. We studied a European American panel discordant for height, a heritable trait that varies widely across Europe. Genotyping 178 SNPs and applying standard analytical methods yielded no evidence of stratification. But a SNP in the gene LCT that varies widely in frequency across Europe was strongly associated with height (P < 10(-6)). This apparent association was largely or completely due to stratification; rematching individuals on the basis of European ancestry greatly reduced the apparent association, and no association was observed in Polish or Scandinavian individuals. The failure of standard methods to detect this stratification indicates that new methods may be required.

In the study of complex traits, the utility of linkage analysis and single marker association tests can be limited for researchers attempting to elucidate the complex interplay between a gene and environmental covariates. For these purposes, tests of gene-environment interactions are needed. In addition, recent studies have indicated that haplotypes, which are specific combinations of nucleotides on the same chromosome, may be more suitable as the unit of analysis for statistical tests than single genetic markers. The difficulty with this approach is that, in standard laboratory genotyping, haplotypes are often not directly observable. Instead, unphased marker phenotypes are collected. In this article, we present a method for estimating and testing haplotype-environment interactions when linkage phase is potentially ambiguous. The method builds on the work of Schaid et al. [2002] and is applicable to any trait that can be placed in the generalized linear model framework. Simulations were run to illustrate the salient features of the method. addition, the method was used to test for haplotype-smoking exposure interaction with data from the Childhood Asthma Management Program. Copyright (C) 2003 S. Karger AG, Basel.

The obesity epidemic is attributable to dietary and behavioral trends acting on a person's genetic makeup to determine body mass and susceptibility to obesity-related disease. Common forms of obesity have a strong hereditary component, yet genetic pathways that contribute to obesity have not yet been elucidated. Many genetic association studies have been reported, but few have been successfully replicated. New research tools and large studies will lead to an understanding of genes and their interaction to cause obesity, which may help guide successful interventions and treatments.

Asthma originates from genetic and environmental factors with about half the risk of disease attributable to heritable causes. Genome-wide association studies, mostly in populations of European ancestry, have identified numerous asthma-associated single nucleotide polymorphisms (SNPs). Studies in populations with diverse ancestries allow both for identification of robust associations that replicate across ethnic groups and for improved resolution of associated loci due to different patterns of linkage disequilibrium between ethnic groups. Here we report on an analysis of 745 African-American subjects with asthma and 3,238 African-American control subjects from the Candidate Gene Association Resource (CARe) Consortium, including analysis of SNPs imputed using 1,000 Genomes reference panels and adjustment for local ancestry. We show strong evidence that variation near RAD50/IL13, implicated in studies of European ancestry individuals, replicates in individuals largely of African ancestry. Fine mapping in African ancestry populations also refined the variants of interest for this association. We also provide strong or nominal evidence of replication at loci near ORMDL3/GSDMB, IL1RL1/IL18R1, and 10p14, all previously associated with asthma in European or Japanese populations, but not at the PYHIN1 locus previously reported in studies of African-American samples. These results improve the understanding of asthma genetics and further demonstrate the utility of genetic studies in populations other than those of largely European ancestry.

RATIONALE: Asthma has substantial morbidity and mortality and a strong genetic component, but identification of genetic risk factors is limited by availability of suitable studies. \ud \ud OBJECTIVES: To test if population-based cohorts with self-reported physician-diagnosed asthma and genome-wide association (GWA) data could be used to validate known associations with asthma and identify novel associations.\ud \ud METHODS: The APCAT (Analysis in Population-based Cohorts of Asthma Traits) consortium consists of 1,716 individuals with asthma and 16,888 healthy controls from six European-descent population-based cohorts. We examined associations in APCAT of thirteen variants previously reported as genome-wide significant (P

Genome-wide genotyping of a cohort using pools rather than individual samples has long been proposed as a cost-saving alternative for performing genome-wide association (GWA) studies. However, successful disease gene mapping using pooled genotyping has thus far been limited to detecting common variants with large effect sizes, which tend not to exist for many complex common diseases or traits. Therefore, for DNA pooling to be a viable strategy for conducting GWA studies, it is important to determine whether commonly used genome-wide SNP array platforms such as the Affymetrix 6.0 array can reliably detect common variants of small effect sizes using pooled DNA. Taking obesity and age at menarche as examples of human complex traits, we assessed the feasibility of genome-wide genotyping of pooled DNA as a single-stage design for phenotype association. By individually genotyping the top associations identified by pooling, we obtained a 14- to 16-fold enrichment of SNPs nominally associated with the phenotype, but we likely missed the top true associations. In addition, we assessed whether genotyping pooled DNA can serve as an inexpensive screen as the second stage of a multi-stage design with a large number of samples by comparing the most cost-effective 3-stage designs with 80% power to detect common variants with genotypic relative risk of 1.1, with and without pooling. Given the current state of the specific technology we employed and the associated genotyping costs, we showed through simulation that a design involving pooling would be 1.07 times more expensive than a design without pooling. Thus, while a significant amount of information exists within the data from pooled DNA, our analysis does not support genotyping pooled DNA as a means to efficiently identify common variants contributing small effects to phenotypes of interest. While our conclusions were based on the specific technology and study design we employed, the approach presented here will be useful for evaluating the utility of other or future genome-wide genotyping platforms in pooled DNA studies.

The relevance of loci associated with blood lipids recently identified in European populations in individuals of African ancestry is unknown. We tested association between lipid traits and 36 previously described single-nucleotide polymorphisms (SNPs) in 1,466 individuals of African ancestry from Spanish Town, Jamaica. For the same allele and effect direction as observed in individuals of European ancestry, SNPs at three loci (1p13, 2p21, and 19p13) showed statistically significant association (p < 0.05) with LDL, two loci (11q12 and 20q13) showed association with HDL cholesterol, and two loci (11q12 and 2p24) showed association with triglycerides. The most significant association was between a SNP at 1p13 and LDL cholesterol (p = 4.6 × 10−8). This SNP is in a linkage disequilibrium region containing four genes (CELSR2, PSRC1, MYBPHL, and SORT1) and was recently shown to relate to risk for myocardial infarction. Overall, the results of this study suggest that much of the genetic variation which influences blood lipids is shared across ethnic groups.

To identify genetic variants associated with birth weight, we meta-analyzed six genome-wide association (GWA) studies (n = 10,623 Europeans from pregnancy/birth cohorts) and followed up two lead signals in 13 replication studies (n = 27,591). rs900400 near LEKR1 and CCNL1 (P = 2 × 10 35) and rs9883204 in ADCY5 (P = 7 × 10 15) were robustly associated with birth weight. Correlated SNPs in ADCY5 were recently implicated in regulation of glucose levels and susceptibility to type 2 diabetes, providing evidence that the well-described association between lower birth weight and subsequent type 2 diabetes has a genetic component, distinct from the proposed role of programming by maternal nutrition. Using data from both SNPs, we found that the 9% of Europeans carrying four birth weight-lowering alleles were, on average, 113g (95% CI 89-137g) lighter at birth than the 24% with zero or one alleles (P trend = 7 × 10 30). The impact on birth weight is similar to that of a mother smoking 4-5 cigarettes per day in the third trimester of pregnancy. © 2010 Nature America, Inc. All rights reserved.

Genome-wide association studies have identified many common genetic variants that are associated with polygenic traits, and have typically been performed with individuals of recent European ancestry. In these populations, many common variants are tightly correlated, with the perfect or near-perfect proxies for the functional or true variant showing equivalent evidence of association, considerably limiting the resolution of fine mapping. Populations with recent African ancestry often have less extensive and/or different patterns of linkage disequilibrium (LD), and have been proposed to be useful in fine-mapping studies. Here, we strongly replicate and fine map in populations of predominantly African ancestry the association between variation at the FTO locus and body mass index (BMI) that is well established in populations of European ancestry. We genotyped single nucleotide polymorphisms that are correlated with the signal of association in individuals of European ancestry but that have varying degrees of correlation in African-derived individuals. Most of the variants, including one previously proposed as functionally important, have no significant association with BMI, but two variants, rs3751812 and rs9941349, show strong evidence of association (P = 2.58 x 10(-6) and 3.61 x 10(-6) in a meta-analysis of 9881 individuals). Thus, we have both strongly replicated this association in African-ancestry populations and narrowed the list of potentially causal variants to those that are correlated with rs3751812 and rs9941349 in African-derived populations. This study illustrates the potential of using populations with different LD patterns to fine map associations and helps pave the way for genetically guided functional studies at the FTO locus.

Variation in the peroxisome proliferator-activated receptor γ gene alters the risk for adiposity in adults, with evidence of interaction with diet. We investigated the age-related association between the Pro12Ala variant (rs1801282) and diet in obesity-related traits in children. The Pro12Ala variant was assayed in 2102 young children aged 1 to 6 years and in 794 periadolescent children aged 10 to 12 years of Greek origin. In both cohorts, no differences were found in obesity traits between the Ala allele carriers and Pro/Pro homozygotes. Sex-stratified analysis showed that, in periadolescent boys, Ala carriers exhibited lower measures of skinfolds (triceps: 16.9 ± 6.9 vs 19.4 ± 7.9 mm, P = .01; subscapular: 9.6 ± 4.5 vs 11.2 ± 5.4 mm, P = .02). On the other hand, young girls who were Ala carriers presented higher measures of triceps skinfold thickness (10.5 ± 3.0 vs 9.9 ± 2.8 mm, P = .04). Nominal gene-diet interactions were revealed in periadolescents for saturated fatty acid (SFA) intake and skinfolds (P for interaction = .05). In Pro/Pro homozygous young girls, SFA and total fat (TF) intake was positively associated with higher body mass index (BMI) (P = .01), waist circumference (P = .02), and skinfold thickness (triceps-SFA: P = 10⁻⁵, triceps-TF: P = 10⁻⁹, subscapular-SFA: P = 10⁻⁶, subscapular-TF: P = 10⁻⁴). For Pro/Pro homozygotes, unsaturated fat intake was inversely associated with BMI (P = .04) in young girls, and with BMI (P = .03), waist circumference (P = .03), and triceps (P = .02) in periadolescent boys. Our results suggest that adiposity in children is influenced by the Pro12Ala polymorphism in a sex-specific and age-dependent manner. We also demonstrate evidence of an age-dependent gene-diet (SFA, TF) interaction, suggesting that the type of fat intake modifies the effect of the Pro12 allele on obesity-related measures.

Background: Variation in the peroxisome-proliferator-activated receptor γ (PPARγ) gene has been reported to alter the risk for adiposity in adults. Methods: We investigated the gender related association between the Pro12Ala variant (rs1801282) in obesity and insulin resistance traits in 794 peri-adolescent children aged 10–12 years of Greek origin from the Gene and Diet Attica Investigation (GENDAI) cohort. Results: Gender stratified analysis suggested that in peri-adolescent boys, Ala carriers exhibited lower measures of skinfold (triceps: 16.9±6.9 vs. 19.4±7.9 mm, p=0.014; subscapular: 9.6±4.5 vs. 11.2±5.4 mm, p=0.016) and lower adiponectin concentrations (3.9±1.3 vs. 4.7±2.4 μg/mL, p=0.05). In peri-adolescent girls, Ala carriers had lower insulin concentrations (7.3±3.7 vs. 8.5±4.4 μU/mL, p=0.026) and lower values of homeostasis model assessment of insulin resistance (HOMA-IR) (1.5±0.8 vs. 1.8±0.96, p=0.019). Linear regression analysis revealed that the presence of the Ala allele in boys was a nominally significant predictor of obesity indices, including skin-folds (triceps: β±SE: –2.3±1.1, p=0.032; subscapular: β±SE: –2.3±1.1, p=0.04) and adiponectin concentrations (β±SE: –0.7±0.4, p=0.05) after adjusting for potential covariates. In girls, the Ala allele was a predictor of insulin concentrations (β±SE: –1.2±0.6, p=0.037) and HOMA-IR (β±SE: –0.24±0.13, p=0.037).Conclusions: Our results suggest that adiposity in children is influenced by the Pro12Ala polymorphism in a gender specific manner. Clin Chem Lab Med 2009;47:1047–50.

Functional studies suggest that the nonsynonymous K121Q polymorphism in the ectoenzyme nucleotide pyrophosphate phosphodiesterase 1 (ENPP1) may confer susceptibility to insulin resistance; genetic evidence on its effect on type 2 diabetes, however, has been conflicting. We therefore conducted a new meta-analysis that includes novel unpublished data from the ENPP1 Consortium and recent negative findings from large association studies to address the contribution of K121Q to type 2 diabetes.After a systematic review of the literature, we evaluated the effect of ENPP1 K121Q on diabetes risk under three genetic models using a random-effects approach. Our primary analysis consisted of 30 studies comprising 15,801 case and 26,241 control subjects. Due to considerable heterogeneity and large differences in allele frequencies across populations, we limited our meta-analysis to those of self-reported European descent and, when available, included BMI as a covariate.We found a modest increase in risk of type 2 diabetes for QQ homozygotes in white populations (combined odds ratio [OR] 1.38 [95% CI 1.10-1.74], P = 0.005). There was no evidence of publication bias, but we noted significant residual heterogeneity among studies (P = 0.02). On meta-regression, 16% of the effect was accounted for by the mean BMI of control subjects. This association was stronger in studies in which control subjects were leaner but disappeared after adjustment for mean control BMI (combined OR 0.93 [95% CI 0.75-1.15], P = 0.50).The ENPP1 Q121 variant increases risk of type 2 diabetes under a recessive model of inheritance in whites, an effect that appears to be modulated by BMI.

New strategies for prevention and treatment of type 2 diabetes (T2D) require improved insight into disease etiology. We analyzed 386,731 common single-nucleotide polymorphisms (SNPs) in 1464 patients with T2D and 1467 matched controls, each characterized for measures of glucose metabolism, lipids, obesity, and blood pressure. With collaborators (FUSION and WTCCC/UKT2D), we identified and confirmed three loci associated with T2D—in a noncoding region near CDKN2A and CDKN2B , in an intron of IGF2BP2 , and an intron of CDKAL1 —and replicated associations near HHEX and in SLC30A8 found by a recent whole-genome association study. We identified and confirmed association of a SNP in an intron of glucokinase regulatory protein (GCKR) with serum triglycerides. The discovery of associated variants in unsuspected genes and outside coding regions illustrates the ability of genome-wide association studies to provide potentially important clues to the pathogenesis of common diseases.

The neuropeptide Y (NPY) family of peptides and receptors regulate food intake. Inherited variation in this pathway could influence susceptibility to obesity and its complications, including type 2 diabetes. We genotyped a set of 71 single nucleotide polymorphisms (SNPs) that capture the most common variation in NPY, PPY, PYY, NPY1R, NPY2R, and NPY5R in 2,800 individuals of recent European ancestry drawn from the near extremes of BMI distribution. Five SNPs located upstream of NPY2R were nominally associated with BMI in men (P values = 0.001-0.009, odds ratios [ORs] 1.27-1.34). No association with BMI was observed in women, and no consistent associations were observed for other genes in this pathway. We attempted to replicate the association with BMI in 2,500 men and tested these SNPs for association with type 2 diabetes in 8,000 samples. We observed association with BMI in men in only one replication sample and saw no association in the combined replication samples (P = 0.154, OR = 1.09). Finally, a 9% haplotype was associated with type 2 diabetes in men (P = 1.73 x 10(-4), OR = 1.36) and not in women. Variation in this pathway likely does not have a major influence on BMI, although small effects cannot be ruled out; NPY2R should be considered a candidate gene for type 2 diabetes in men.

Publisher Summary A full working knowledge of disease, genetic mechanisms, epidemiology, genotyping, and statistical analysis is essential for successful study of complex disease. There have been major advances in the understanding of genetic mechanisms of disease and translation of this understanding to clinical practice. This chapter discusses genetic models and describes the basic methods currently used to conduct complex trait inheritance research. The future discoveries will be made by teams of researchers cooperating to integrate all parts, including clinicians, laboratory scientists, biostatisticians, bioinformaticians, and pharmaceutical designers. The thoughtful application of discoveries to cure or ameliorate diseases will be a great challenge to clinicians as we enter a new age of genomic medicine. It will lead to new insights into pathophysiology and to the development of new approaches to diagnosis, prevention, and treatment.

Obesity is a heritable trait and a risk factor for many common diseases such as type 2 diabetes, heart disease, and hypertension. We used a dense whole-genome scan of DNA samples from the Framingham Heart Study participants to identify a common genetic variant near the INSIG2 gene associated with obesity. We have replicated the finding in four separate samples composed of individuals of Western European ancestry, African Americans, and children. The obesity-predisposing genotype is present in 10% of individuals. Our study suggests that common genetic polymorphisms are important determinants of obesity.

The Human Genome Project and its spin-offs are making it increasingly feasible to determine the genetic basis of complex traits using genome-wide association studies. The statistical challenge of analyzing such studies stems from the severe multiple-comparison problem resulting from the analysis of thousands of SNPs. Our methodology for genome-wide family-based association studies, using single SNPs or haplotypes, can identify associations that achieve genome-wide significance. In relation to developing guidelines for our screening tools, we determined lower bounds for the estimated power to detect the gene underlying the disease-susceptibility locus, which hold regardless of the linkage disequilibrium structure present in the data. We also assessed the power of our approach in the presence of multiple disease-susceptibility loci. Our screening tools accommodate genomic control and use the concept of haplotype-tagging SNPs. Our methods use the entire sample and do not require separate screening and validation samples to establish genome-wide significance, as population-based designs do.

Identification of genetic variants affecting complex traits such as obesity is confounded by many types of bias, especially when effect sizes are small. Given our findings of a positive association between rs7566605 and body mass index in four out of five separate samples, a false positive finding cannot be ruled out with certainty but seems unlikely. Meta-analyses of multiple large studies will help refine the estimate of the effects of rs7566605 on body mass index.

A SNP upstream of the INSIG2 gene, rs7566605, was recently found to be associated with obesity as measured by body mass index (BMI) by Herbert and colleagues. The association between increased BMI and homozygosity for the minor allele was first observed in data from a genome-wide association scan of 86,604 SNPs in 923 related individuals from the Framingham Heart Study offspring cohort. The association was reproduced in four additional cohorts, but was not seen in a fifth cohort. To further assess the general reproducibility of this association, we genotyped rs7566605 in nine large cohorts from eight populations across multiple ethnicities (total n = 16,969). We tested this variant for association with BMI in each sample under a recessive model using family-based, population-based, and case-control designs. We observed a significant (p < 0.05) association in five cohorts but saw no association in three other cohorts. There was variability in the strength of association evidence across examination cycles in longitudinal data from unrelated individuals in the Framingham Heart Study Offspring cohort. A combined analysis revealed significant independent validation of this association in both unrelated (p = 0.046) and family-based (p = 0.004) samples. The estimated risk conferred by this allele is small, and could easily be masked by small sample size, population stratification, or other confounders. These validation studies suggest that the original association is less likely to be spurious, but the failure to observe an association in every data set suggests that the effect of SNP rs7566605 on BMI may be heterogeneous across population samples., Author Summary Obesity is an epidemic in the United States of America and developing world, portending an epidemic of related diseases such as diabetes and heart disease. While diet and lifestyle contribute to obesity, half of the population variation in body mass index, a common measure of obesity, is determined by inherited factors. Many studies have reported that common sequence variants in genes are associated with an increased risk for obesity, yet most of these are not reproducible in other study cohorts, suggesting that some are false. Recently, Herbert et al. reported a slightly increased risk of obesity for people carrying two copies of the minor allele at a common variant near INSIG2. We present our attempts to further evaluate this potential association with obesity in additional populations. We find evidence of increased risk of obesity for people carrying two copies of the minor allele in five out of nine cohorts tested, using both family- and population-based testing. We indicate possible reasons for the varied results, with the hope of encouraging a combined analysis across study cohorts to more precisely define the effect of this INSIG2 gene variant.