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Recent data from mainly homogeneous European and African populations implicate a 140-bp region 5' to the transcriptional start site of LCT (the lactase gene) as a regulatory site for lactase persistence and nonpersistence. Because there are no studies of US nonhomogeneous populations, we performed genotype/phenotype analysis of the -13910 and -22018 LCT single nucleotide polymorphisms (SNPs) in New England children, mostly of European ancestry.Duodenal biopsies were processed for disaccharidase activities, RNA quantification by reverse transcription polymerase chain reaction (RT-PCR), allelic expression ratios by PCR, and genotyping and SNP analysis. Results were compared with clinical information.Lactase activity and mRNA levels, and sucrase-to-lactase ratios of enzyme activity and mRNA, showed robust correlations with genotype. None of the other LCT SNPs showed as strong a correlation with enzyme or mRNA levels as did -13910. Data were consistent, with the -13910 being the causal sequence variant instead of -22018. Four individuals heterozygous for -13910T/C had allelic expression patterns similar to individuals with -13910C/C genotypes; of these, 2 showed equal LCT expression from the 2 alleles and a novel variant (-13909CA) associated with lactase persistence.The identification of -13910C/C genotype is likely to predict lactase nonpersistence, consistent with prior published studies. A -13910T/T genotype will frequently, but not perfectly, predict lactase persistence in this mixed European-ancestry population; a -13910T/C genotype will not predict the phenotype. A long, rare haplotype in 2 individuals with -13910T/C genotype but equal allele-specific expression contains a novel lactase persistence allele present at -13909.

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.

Studies indicate that estrogen receptor β, encoded by the ESR2 gene on chromosome 14q, may play a role in ovarian carcinogenesis. Using the genetic structure data generated by the Breast and Prostate Cohort Consortium (BPC3), we have comprehensively characterized the role of haplotype diversity in ESR2 and risk of ovarian cancer. Five haplotypes with a frequency of ≥5% were observed in White subjects and five haplotype tagging SNPs (htSNP) were selected to capture the locus diversity with a minimum Rh2 of 0.81. The htSNPs were genotyped in 574 White controls, 417 White invasive ovarian cancer cases, and 123 White borderline ovarian cancer cases from case-control studies carried out in Los Angeles County from 1994 through 2004. No statistically significant association was observed between the five htSNPs and related haplotypes and risk of ovarian cancer overall. Haplotype D was associated with a nonstatistically significant increased risk of invasive ovarian cancer overall (odds ratio, 1.38; 95% confidence interval, 0.93-2.02; P = 0.11) relative to the most common haplotype and a statistically significant increased risk of invasive clear cell ovarian cancer (odds ratio, 3.88; 95% confidence interval, 1.28-11.73; P = 0.016). Haplotype D was also reported by the BPC3 to be associated with increased risk of breast cancer. This haplotype warrants further investigation to rule out any effect with invasive ovarian cancer risk. (Cancer Epidemiol Biomarkers Prev 2008;17(2):393–6)

Stature (adult height) is one of the most heritable human traits, yet few genes, if any, have been convincingly associated with adult height variation in the general population. Here, we selected 150 tag SNPs from eight candidate genes in the growth hormone (GH)/insulin-like growth factor-1 (IGF1) axis (GHR, GHRH, GHRHR, IGF1, IGFALS, IGFBP3, JAK2, STAT5B), and genotyped them in approximately 2,200 individuals ascertained for short or tall stature. Nominally significant tag SNPs were then tested in three additional replication cohorts, including a family-based panel to rule out spurious associations owing to population stratification. Across the four height cohorts (N = 6,075 individuals), we did not observe any consistent associations between stature and common variants (or =5% minor allele frequency) in these eight genes, including a common deletion of the growth hormone receptor gene exon 3. Tests of epistatic interactions between these genes did not yield any results beyond those expected by chance. Although we have not tested all genes in the GH/IGF1 axis, our results indicate that common variation in these GH/IGF1 axis genes is not a major determinant of stature, and suggest that if common variation contributes to adult height variation in the general population, the variants are in other, possibly unanticipated genes.

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.

Because GnRH and its receptor (GnRHR) are pivotal regulators of the reproductive endocrine axis and mutations in GNRHR lead to hypogonadotropic hypogonadism, we investigated whether genetic variation in GNRHR or GNRH1 affects pubertal timing in the general population. To screen for missense mutations in these genes that might affect pubertal timing, we resequenced the coding regions of these genes in 48 probands with late but otherwise normal pubertal development. No missense variants were found in either gene, except for a previously identified single nucleotide polymorphism (SNP) in GNRH1 that was not associated with late pubertal development. To search for common variants that might affect pubertal timing, we took a haplotype-based association approach. To identify common haplotypes in these genes, we genotyped 41 SNPs in DNA from commercially available European-derived multigenerational pedigrees and participants in a multiethnic cohort (MEC). Two blocks of strong linkage disequilibrium were identified that spanned GNRHR and one was identified spanning GNRH1; within each block, more than 80% of chromosomes carried one of a few common haplotypes. A set of haplotype-tagging SNPs that mark these common haplotypes in all five ethnic groups within the MEC were defined and used to perform association studies among 125 trios (probands with late pubertal development and their parents) and 506 women from the MEC who had early (menarche11 yr of age, n = 216) or late (menarcheor = 15 yr of age, n = 290) pubertal development. Three SNPs in GNRHR showed modest association with late pubertal development in the trios; among the 506 women, a different SNP was associated with late menarche, and one rare haplotype was associated with early age of menarche. All of the observed associations were relatively modest and only nominally statistically significant; replication is needed to determine their validity. We conclude that genetic variation in GNRH1 and GNRHR is not likely to be a substantial modulator of pubertal timing in the general population.

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 etiology of growth impairment in Crohn's disease (CD) has been inadequately explained by nutritional, hormonal, and/or disease-related factors, suggesting that genetics may be an additional contributor. The aim of this cross-sectional study was to investigate genetic variants associated with linear growth in pediatric-onset CD. We genotyped 951 subjects (317 CD patient-parent trios) for 64 polymorphisms within 14 CD-susceptibility and 23 stature-associated loci. Patient height-for-age Z-score-1.64 was used to dichotomize probands into growth-impaired and nongrowth-impaired groups. The transmission disequilibrium test (TDT) was used to study association to growth impairment. There was a significant association between growth impairment in CD (height-for-age Z-score-1.64) and a stature-related polymorphism in the dymeclin gene DYM (rs8099594) (OR = 3.2, CI [1.57-6.51], p = 0.0007). In addition, there was nominal over-transmission of two CD-susceptibility alleles, 10q21.1 intergenic region (rs10761659) and ATG16L1 (rs10210302), in growth-impaired CD children (OR = 2.36, CI [1.26-4.41] p = 0.0056 and OR = 2.45, CI [1.22-4.95] p = 0.0094, respectively). Our data indicate that genetic influences due to stature-associated and possibly CD risk alleles may predispose CD patients to alterations in linear growth. This is the first report of a link between a stature-associated locus and growth impairment in CD.

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.

Context: Although the timing of puberty is a highly heritable trait, little is known about the genes that regulate pubertal timing in the general population. Several genes have been identified that, when mutated, cause disorders of delayed or absent puberty such as hypogonadotropic hypogonadism (HH).Objective: Because severe variants in HH-related genes cause a severe puberty phenotype, we hypothesized that common subtle variation in these genes could contribute to the population variation in pubertal timing.Design: We assessed common genetic variation in 10 HH-related genes in 1801 women from the Hawaii and Los Angeles Multiethnic Cohort with either early (age < 11 yr) or late (age > 14 yr) menarche and in other replication samples. In addition to these common variants, we also studied the most frequently reported HH mutations to assess their role in the population variation in pubertal timing.Setting and Patients/Other Participants: Within the general community, 1801 women from the Hawaii and Los Angeles Multiethnic Cohort participated.Main Outcome Measures: We assessed the association of genetic variation with age at menarche.Results: We found no significant association between any of the variants tested and age at menarche, although we cannot rule out modest effects of these variants or of other variants at long distances from the coding region. In several self-reported racial/ethnic groups represented in our study, we observed an association between estimated genetic ancestry and age at menarche.Conclusions: Our results suggest that common variants near 10 HH-related loci do not play a substantial role in the regulation of age at menarche in the general population.

As we move forward from the current generation of genome-wide association (GWA) studies, additional cohorts of different ancestries will be studied to increase power, fine map association signals, and generalize association results to additional populations. Knowledge of genetic ancestry as well as population substructure will become increasingly important for GWA studies in populations of unknown ancestry. Here we propose genotyping pooled DNA samples using genome-wide SNP arrays as a viable option to efficiently and inexpensively estimate admixture proportion and identify ancestry informative markers (AIMs) in populations of unknown origin. We constructed DNA pools from African American, Native Hawaiian, Latina, and Jamaican samples and genotyped them using the Affymetrix 6.0 array. Aided by individual genotype data from the African American cohort, we established quality control filters to remove poorly performing SNPs and estimated allele frequencies for the remaining SNPs in each panel. We then applied a regression-based method to estimate the proportion of admixture in each cohort using the allele frequencies estimated from pooling and populations from the International HapMap Consortium as reference panels, and identified AIMs unique to each population. In this study, we demonstrated that genotyping pooled DNA samples yields estimates of admixture proportion that are both consistent with our knowledge of population history and similar to those obtained by genotyping known AIMs. Furthermore, through validation by individual genotyping, we demonstrated that pooling is quite effective for identifying SNPs with large allele frequency differences (i.e., AIMs) and that these AIMs are able to differentiate two closely related populations (HapMap JPT and CHB)., Author Summary Many association studies have been published looking for genetic variants contributing to a variety of human traits such as obesity, diabetes, and height. Because the frequency of genetic variants can differ across populations, it is important to have estimates of genetic ancestry in the individuals being studied. In this study, we were able to measure genetic ancestry in populations of mixed ancestry by genotyping pooled, rather than individual, DNA samples. This represents a rapid and inexpensive means for modeling genetic ancestry and thus could facilitate future association or population-genetic studies in populations of unknown ancestry for which whole-genome data do not already exist.