Detection of nonrandom association of alleles from the distribution of the number of heterozygous loci in a sample.

The distribution of the number of heterozygous loci in two randomly chosen gametes or in a random diploid zygote provides information regarding the nonrandom association of alleles among different genetic loci. Two alternative statistics may be employed for detection of nonrandom association of genes of different loci when observations are made on these distributions: observed variance of the number of heterozygous loci (s2k) and a goodness-of-fit criterion (X2) to contrast the observed distribution with that expected under the hypothesis of random association of genes. It is shown, by simulation, that s2k is statistically more efficient than X2 to detect a given extent of nonrandom association. Asymptotic normality of s2k is justified, and X2 is shown to follow a chi-square (chi 2) distribution with partial loss of degrees of freedom arising because of estimation of parameters from the marginal gene frequency data. Whenever direct evaluations of linkage disequilibrium values are possible, tests based on maximum likelihood estimators of linkage disequilibria require a smaller sample size (number of zygotes or gametes) to detect a given level of nonrandom association in comparison with that required if such tests are conducted on the basis of s2k. Summarization of multilocus genotype (or haplotype) data, into the different number of heterozygous loci classes, thus, amounts to appreciable loss of information.

Concept, design and implementation of a cardiovascular gene-centric 50 k SNP array for large-scale genomic association studies.

A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a "cosmopolitan" tagging approach to capture the genetic diversity across approximately 2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.

NETWORK TOPOLOGY IN HUMAN PROTEIN INTERACTION DATA PREDICTS FUNCTIONAL ASSOCIATION

High-throughput assays, such as yeast two-hybrid system, have generated a huge amount of protein-protein interaction (PPI) data in the past decade. This tremendously increases the need for developing reliable methods to systematically and automatically suggest protein functions and relationships between them. With the available PPI data, it is now possible to study the functions and relationships in the context of a large-scale network. To data, several network-based schemes have been provided to effectively annotate protein functions on a large scale. However, due to those inherent noises in high-throughput data generation, new methods and algorithms should be developed to increase the reliability of functional annotations. Previous work in a yeast PPI network (Samanta and Liang, 2003) has shown that the local connection topology, particularly for two proteins sharing an unusually large number of neighbors, can predict functional associations between proteins, and hence suggest their functions. One advantage of the work is that their algorithm is not sensitive to noises (false positives) in high-throughput PPI data. In this study, we improved their prediction scheme by developing a new algorithm and new methods which we applied on a human PPI network to make a genome-wide functional inference. We used the new algorithm to measure and reduce the influence of hub proteins on detecting functionally associated proteins. We used the annotations of the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) as independent and unbiased benchmarks to evaluate our algorithms and methods within the human PPI network. We showed that, compared with the previous work from Samanta and Liang, our algorithm and methods developed in this study improved the overall quality of functional inferences for human proteins. By applying the algorithms to the human PPI network, we obtained 4,233 significant functional associations among 1,754 proteins. Further comparisons of their KEGG and GO annotations allowed us to assign 466 KEGG pathway annotations to 274 proteins and 123 GO annotations to 114 proteins with estimated false discovery rates of <21% for KEGG and <30% for GO. We clustered 1,729 proteins by their functional associations and made pathway analysis to identify several subclusters that are highly enriched in certain signaling pathways. Particularly, we performed a detailed analysis on a subcluster enriched in the transforming growth factor β signaling pathway (P<10-50) which is important in cell proliferation and tumorigenesis. Analysis of another four subclusters also suggested potential new players in six signaling pathways worthy of further experimental investigations. Our study gives clear insight into the common neighbor-based prediction scheme and provides a reliable method for large-scale functional annotations in this post-genomic era.

Ethnic Minority Children’s Active Commuting to School and Association with Physical Activity and Pedestrian Safety Behaviors

Background: Children's active commuting to school, i.e. walking or cycling to school, was associated with greater moderate-to-vigorous physical activity, although studies among ethnic minorities are sparse. Objectives: Among a low-income, ethnic minority sample of fourth grade students from eight public schools, we examined (1) correlates of active commuting to school and (2) the relationship between active commuting to school and moderate-to-vigorous physical activity. Methods: We conducted a cross-sectional analysis of baseline measurements from a sample of participants (n=149) aged 9-12 years from a walk to school intervention study in Houston, Texas. The primary outcome was the weekly rate of active commuting to school. Daily moderate-to-vigorous physical activity, measured by accelerometers, was a secondary outcome. Child self-efficacy (alpha=0.75), parent self-efficacy (alpha=0.88), and parent outcome expectations (alpha=0.78) were independent variables. Participant characteristics (age, gender, race/ethnicity, distance from home to school, acculturation, and BMI percentile) were independent sociodemographic variables. We used mixed-model regression analyses to account for clustering by school and a stepwise procedure with backward elimination of non-significant interactions and covariates to identify significant moderators and predictors. School-level observations of student pedestrians were assessed and compared using chi-square tests of independence. Results: Among our sample, which was 61.7% Latino, the overall rate of active commuting to school was 43%. In the mixed model for active commuting to school, parent self-efficacy (std. beta = 0.18, p=0.018) and age (std. beta = 0.18, p=0.018) were positively related. Latino students had lower rates of active commuting to school than non-Latinos ( 16.5%, p=0.040). Distance from home to school was inversely related to active commuting to school (std. beta = 0.29, p<0.001). In the mixed model for moderate-to-vigorous physical activity, active commuting to school was positively associated (std. beta = 0.31, p <0.001). Among the Latino subsample, child acculturation was negatively associated with active commuting to school (std. beta = -0.23, p=0.01). With regard to school-level pedestrian safety observations, 37% of students stopped at the curb and 2.6% looked left-right-left before crossing the street. Conclusion: Although still below national goals, the rate of active commuting was relatively high, while the rate of some pedestrian safety behaviors was low among this low-income, ethnic minority population. Programs and policies to encourage safe active commuting to school are warranted and should consider the influence of parents, acculturation, and ethnicity.

Mutation and association analysis of the PVR and PVRL2 genes in patients with non-syndromic cleft lip and palate.

Orofacial clefts (OFC; MIM 119530) are among the most common major birth defects. Here, we carried out mutation screening of the PVR and PVRL2 genes, which are both located at an OFC linkage region at 19q13 (OFC3) and are closely related to PVRL1, which has been associated with both syndromic and non-syndromic cleft lip and palate (nsCLP). We screened a total of 73 nsCLP patients and 105 non-cleft controls from the USA for variants in PVR and PVRL2, including all exons and encompassing all isoforms. We identified four variants in PVR and five in PVRL2. One non-synonymous PVR variant, A67T, was more frequent among nsCLP patients than among normal controls, but this difference did not achieve statistical significance.

Association of retinoic acid receptor genes with meningomyelocele.

BACKGROUND: Neural tube defects (NTDs) occur in as many as 0.5-2 per 1000 live births in the United States. One of the most common and severe neural tube defects is meningomyelocele (MM) resulting from failed closure of the caudal end of the neural tube. MM has been induced by retinoic acid teratogenicity in rodent models. We hypothesized that genetic variants influencing retinoic acid (RA) induction via retinoic acid receptors (RARs) may be associated with risk for MM. METHODS: We analyzed 47 single nucleotide polymorphisms (SNPs) that span across the three retinoic acid receptor genes using the SNPlex genotyping platform. Our cohort consisted of 610 MM families. RESULTS: One variant in the RARA gene (rs12051734), three variants in the RARB gene (rs6799734, rs12630816, rs17016462), and a single variant in the RARG gene (rs3741434) were found to be statistically significant at p < 0.05. CONCLUSION: RAR genes were associated with risk for MM. For all associated SNPs, the rare allele conferred a protective effect for MM susceptibility.

Association of putative enteroaggregative Escherichia coli virulence genes and biofilm production in isolates from travelers to developing countries.

Enteroaggregative Escherichia coli (EAEC) is an emerging enteric pathogen that causes acute and chronic diarrhea among children, human immunodeficiency virus-infected patients, and travelers to developing regions of the world. The pathogenesis of EAEC strains involves the production of biofilm. In this study, we determined the association between presence of putative EAEC virulence genes and biofilm formation in 57 EAEC isolates (as defined by HEp-2 adherence) from travelers with diarrhea and in 18 EAEC isolates from travelers without diarrhea. Twelve nondiarrheagenic E. coli isolates from healthy travelers were used as controls. Biofilm formation was measured by using a microtiter plate assay with the crystal violet staining method, and the presence of the putative EAEC virulence genes aap, aatA, aggR, astA, irp2, pet, set1A, and shf was determined by PCR. EAEC isolates were more likely to produce biofilm than nondiarrheagenic E. coli isolates (P = 0.027), and the production of biofilm was associated with the virulence genes aggR, set1A, aatA, and irp2, which were found in 16 (40%), 17 (43%), 10 (25%), and 27 (68%) of the biofilm producers versus only 4 (11%), 6 (6%), 2 (6%), and 15 (43%) in non-biofilm producers (P = 0.008 for aggR, P = 0.0004 for set1A, P = 0.029 for aatA, and P = 0.04 for irp2). Although the proportion of EAEC isolates producing biofilm in patients with diarrhea (51%) was similar to that in patients without diarrhea (61%), biofilm production was related to the carriage of aggR (P = 0.015), set1A (P = 0.001), and aatA (P = 0.025). Since aggR is a master regulator of EAEC, the presence of aap (P = 0.004), astA (P = 0.001), irp2 (P = 0.0006), pet (P = 0.002), and set1A (P = 0.014) in an aggR versus an aggR-lacking background was investigated and was also found to be associated with biofilm production. This study suggests that biofilm formation is a common phenomenon among EAEC isolates derived from travelers with or without diarrhea and that multiple genes associated with biofilm formation are regulated by aggR.

Association of folate receptor (FOLR1, FOLR2, FOLR3) and reduced folate carrier (SLC19A1) genes with meningomyelocele.

BACKGROUND: Meningomyelocele (MM) results from lack of closure of the neural tube during embryologic development. Periconceptional folic acid supplementation is a modifier of MM risk in humans, leading toan interest in the folate transport genes as potential candidates for association to MM. METHODS: This study used the SNPlex Genotyping (ABI, Foster City, CA) platform to genotype 20 single polymorphic variants across the folate receptor genes (FOLR1, FOLR2, FOLR3) and the folate carrier gene (SLC19A1) to assess their association to MM. The study population included 329 trio and 281 duo families. Only cases with MM were included. Genetic association was assessed using the transmission disequilibrium test in PLINK. RESULTS: A variant in the FOLR2 gene (rs13908), three linked variants in the FOLR3 gene (rs7925545, rs7926875, rs7926987), and two variants in the SLC19A1 gene (rs1888530 and rs3788200) were statistically significant for association to MM in our population. CONCLUSION: This study involved the analyses of selected single nucleotide polymorphisms across the folate receptor genes and the folate carrier gene in a large population sample. It provided evidence that the rare alleles of specific single nucleotide polymorphisms within these genes appear to be statistically significant for association to MM in the patient population that was tested.

HLA-DPB1 and DPB2 are genetic loci for systemic sclerosis: a genome-wide association study in Koreans with replication in North Americans.

OBJECTIVE: To identify systemic sclerosis (SSc) susceptibility loci via a genome-wide association study. METHODS: A genome-wide association study was performed in 137 patients with SSc and 564 controls from Korea using the Affymetrix Human SNP Array 5.0. After fine-mapping studies, the results were replicated in 1,107 SSc patients and 2,747 controls from a US Caucasian population. RESULTS: The single-nucleotide polymorphisms (SNPs) (rs3128930, rs7763822, rs7764491, rs3117230, and rs3128965) of HLA-DPB1 and DPB2 on chromosome 6 formed a distinctive peak with log P values for association with SSc susceptibility (P=8.16x10(-13)). Subtyping analysis of HLA-DPB1 showed that DPB1*1301 (P=7.61x10(-8)) and DPB1*0901 (P=2.55x10(-5)) were the subtypes most susceptible to SSc in Korean subjects. In US Caucasians, 2 pairs of SNPs, rs7763822/rs7764491 and rs3117230/rs3128965, showed strong association with SSc patients who had either circulating anti-DNA topoisomerase I (P=7.58x10(-17)/4.84x10(-16)) or anticentromere autoantibodies (P=1.12x10(-3)/3.2x10(-5)), respectively. CONCLUSION: The results of our genome-wide association study in Korean subjects indicate that the region of HLA-DPB1 and DPB2 contains the loci most susceptible to SSc in a Korean population. The confirmatory studies in US Caucasians indicate that specific SNPs of HLA-DPB1 and/or DPB2 are strongly associated with US Caucasian patients with SSc who are positive for anti-DNA topoisomerase I or anticentromere autoantibodies.

Quantification of the spatiotemporal microstructural organization of the human brain association, projection and commissural pathways across the lifespan using diffusion tensor tractography.

Using diffusion tensor tractography, we quantified the microstructural changes in the association, projection, and commissural compact white matter pathways of the human brain over the lifespan in a cohort of healthy right-handed children and adults aged 6-68 years. In both males and females, the diffusion tensor radial diffusivity of the bilateral arcuate fasciculus, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate fasciculus, corticospinal, somatosensory tracts, and the corpus callosum followed a U-curve with advancing age; fractional anisotropy in the same pathways followed an inverted U-curve. Our study provides useful baseline data for the interpretation of data collected from patients.

Genes in glucose metabolism and association with spina bifida.

The authors test single nucleotide polymorphisms (SNPs) in coding sequences of 12 candidate genes involved in glucose metabolism and obesity for associations with spina bifida. Genotyping was performed on 507 children with spina bifida and their parents plus anonymous control DNAs from Hispanic and Caucasian individuals. The transmission disequilibrium test was performed to test for genetic associations between transmission of alleles and spina bifida in the offspring (P < .05). A statistically significant association between Lys481 of HK1 (G allele), Arg109Lys of LEPR (G allele), and Pro196 of GLUT1 (A allele) was found ( P = .019, .039, and .040, respectively). Three SNPs on 3 genes involved with glucose metabolism and obesity may be associated with increased susceptibility to spina bifida.

THE ASSOCIATION BETWEEN CANCER-RELATED-FATIGUE, RESPONSE TO FATIGUE TREATMENT, AND CYTOKINES AND THEIR RECEPTORS, IN PATIENTS WITH ADVANCED CANCER

Background: Inflammation is implicated in the development of cancer related fatigue (CRF). However there is limited literature on the mediators of inflammation (namely), cytokines and their receptors, associated with clinically significant fatigue and response to treatment. Methods: We reviewed 37 advanced cancer patients with fatigue (≥4/10), who participated in two Randomized Controlled Trials, of anti-inflammatory agents (Thalidomide and Dexamethasone) for CRF. Responders showed improvement in FACIT-F subscale at the end of study (Day 15). Baseline patient characteristics and symptoms were assessed by FACIT-F, ESAS; serum cytokines [IL-1β and receptor antagonist (IL-1RA), IL-6, IL-6R, TNF-α and sTNF-R1 and R2, IL-8, IL-10, IL-17] levels measured by Luminex. Data were analyzed using principal component analysis (PCA) [reporting cumulative variance (variance) for the first four components] to determine their association with fatigue and response to treatment. Results: Females were 54%. Mean (SD) was as follows for age, 61(14); baseline FACIT (F) scores, 21.4(8.6); ESAS Fatigue item, 6.5(1.9); and FACIT-F change, 6.4(9.7); ESAS (fatigue) change, -2 (2.41). Baseline median in pg/mL for IL-6, TNF-α, IL-1β were 31.9; 18.9; 0.55, respectively. Change in IL-6 negatively correlated with change in FACIT-F scores (p=0.02). Baseline CRF (FACIT-F score) was associated with IL-6, IL-6R and IL-17, Variance = 78% whereas IL-10, IL-1RA, TNF-α and IL-1β were associated with improvement of CRF, Variance=74%. Conversely, IL-6 and IL-8 were associated with no improvement or worsening of CRF, Variance= 93%. Conclusions: Change in IL-6 negatively correlated with change in FACIT-F scores. IL-6, IL-6R and IL-17 are associated with CRF while IL-6 and IL-8 were associated with no improvement of CRF. Further studies are warranted confirm our findings.

Development of a Bayesian Joint Logistic Model to Better Study the Association between Haplotypes and Disease

In 2011, there will be an estimated 1,596,670 new cancer cases and 571,950 cancer-related deaths in the US. With the ever-increasing applications of cancer genetics in epidemiology, there is great potential to identify genetic risk factors that would help identify individuals with increased genetic susceptibility to cancer, which could be used to develop interventions or targeted therapies that could hopefully reduce cancer risk and mortality. In this dissertation, I propose to develop a new statistical method to evaluate the role of haplotypes in cancer susceptibility and development. This model will be flexible enough to handle not only haplotypes of any size, but also a variety of covariates. I will then apply this method to three cancer-related data sets (Hodgkin Disease, Glioma, and Lung Cancer). I hypothesize that there is substantial improvement in the estimation of association between haplotypes and disease, with the use of a Bayesian mathematical method to infer haplotypes that uses prior information from known genetics sources. Analysis based on haplotypes using information from publically available genetic sources generally show increased odds ratios and smaller p-values in both the Hodgkin, Glioma, and Lung data sets. For instance, the Bayesian Joint Logistic Model (BJLM) inferred haplotype TC had a substantially higher estimated effect size (OR=12.16, 95% CI = 2.47-90.1 vs. 9.24, 95% CI = 1.81-47.2) and more significant p-value (0.00044 vs. 0.008) for Hodgkin Disease compared to a traditional logistic regression approach. Also, the effect sizes of haplotypes modeled with recessive genetic effects were higher (and had more significant p-values) when analyzed with the BJLM. Full genetic models with haplotype information developed with the BJLM resulted in significantly higher discriminatory power and a significantly higher Net Reclassification Index compared to those developed with haplo.stats for lung cancer. Future analysis for this work could be to incorporate the 1000 Genomes project, which offers a larger selection of SNPs can be incorporated into the information from known genetic sources as well. Other future analysis include testing non-binary outcomes, like the levels of biomarkers that are present in lung cancer (NNK), and extending this analysis to full GWAS studies.

Commentary on "Exploring the Association Between Household Food Insecurity, Parental Self-Efficacy and Fruit and Vegetable Parenting Practices Among Parents of 5- to 8-Year-Old Overweight Children"

Invited commentary of an article that discusses the association between parental factors and food insecurity by Angela Hilmers, Karen Cullen, Carolyn Moore and Teresia O’Connor.