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Background: A low birth weight has been extensively related to poor adult health outcomes. Birth weight can be seen as a proxy for environmental conditions during prenatal development. Identical twin pairs discordant for birth weight provide an extraordinary model for investigating the association between birth weight and adult life health while controlling for not only genetics but also postnatal rearing environment. We performed an epigenome-wide profiling on blood samples from 150 pairs of adult monozygotic twins discordant for birth weight to look for molecular evidence of epigenetic signatures in association with birth weight discordance. Results: Our association analysis revealed no CpG site with genome-wide statistical significance (FDR < 0.05) for either qualitative (larger or smaller) or quantitative discordance in birth weight. Even with selected samples of extremely birth weight discordant twin pairs, no significant site was found except for 3 CpGs that displayed age-dependent intra-pair differential methylation with FDRs 0.014 (cg26856578, p = 3.42e-08), 0.0256 (cg15122603, p = 1.25e-07) and 0.0258 (cg16636641, p = 2.05e-07). Among the three sites, intra-pair differential methylation increased with age for cg26856578 but decreased with age for cg15122603 and cg16636641. There was no genome-wide statistical significance for sexdependent effects on intra-pair differential methylation in either the whole samples or the extremely discordant twins. Conclusions: Genome-wide DNA methylation profiling did not reveal epigenetic signatures of birth weight discordance although some sites displayed age-dependent intra-pair differential methylation in the extremely discordant twin pairs. [ABSTRACT FROM AUTHOR]

Background: Reduced forced expiratory volume in 1 second (FEV1) and the ratio of FEV1 toforced vital capacity (FVC) are strong predictors of mortality and lung function is higher among individuals with exceptional longevity. However, genetic factors associated with lung function in individuals with exceptional longevity have not been identified. Method: We conducted a genome wide association study (GWAS) to identify novel genetic variants associated with lung function in the Long Life Family Study (LLFS) (n = 3,899). Replication was performed using data from the CHARGE/SpiroMeta consortia. The association between SNPs and FEV1 and FEV1/FVC was analyzed using a linear mixed effects model adjusted for age, age2, sex, height, field center, ancestry principal components and kinship structure to adjust for family relationships separately for ever smokers and never smokers. In the linkage analysis, we used the residuals of the FEV1 and FEV1/FVC, adjusted for age, sex, height, ancestry principal components (PCs), smoking status, pack-years, and field center. Results: We identified nine SNPs in strong linkage disequilibrium in the CYP2U1 gene to be associated with FEV1 and a novel SNP (rs889574) associated with FEV1/FVC, none of which were replicated in the CHARGE/SpiroMeta consortia. Using linkage analysis, we identified a novel linkage peak in chromosome 2 at 219 cM for FEV1/FVC (LOD: 3.29) and confirmed a previously reported linkage peak in chromosome 6 at 28 cM (LOD: 3.33) for FEV1. Conclusion: Future studies need to identify the rare genetic variants underlying the linkage peak in chromosome 6 for FEV1. [ABSTRACT FROM AUTHOR]

Background: Despite twinning being common in Africa, few prospective twin studies have been conducted. We studied twinning rate, perinatal mortality and the clinical characteristics of newborn twins in urban Guinea-Bissau. Methods: The study was conducted at the Bandim Health Project (BHP), a health and demographic surveillance site in Bissau, the capital of Guinea-Bissau. The cohort included all newborn twins delivered at the National Hospital Simão Mendes and in the BHP study area during the period September 2009 to August 2011 as well as singleton controls from the BHP study area. Data regarding obstetric history and pregnancy were collected at the hospital. Live children were examined clinically. For a subset of twin pairs zygosity was established by using genetic markers. Results: Out of the 5262 births from mothers included in the BHP study area, 94 were twin births, i.e. a community twinning rate of 18/1000. The monozygotic rate was 3.4/1000. Perinatal mortality among twins vs. singletons was 218/1000 vs. 80/1000 (RR = 2.71, 95% CI: 1.93-3.80). Among the 13783 hospital births 388 were twin births (28/1000).The hospital perinatal twin mortality was 237/1000. Birth weight < 2000g (RR = 4.24, CI: 2.39-7.51) and caesarean section (RR = 1.78, CI: 1.06-2.99) were significant risk factors for perinatal twin mortality. Male sex (RR = 1.38, CI: 0.97-1.96), unawareness of twin pregnancy (RR = 1.64, CI:0.97-2.78) and high blood pressure during pregnancy (RR = 1.77, CI: 0.88-3.57) were borderline non-significant. Sixty-five percent (245/375) of the mothers who delivered at the hospital were unaware of their twin pregnancy. Conclusions: Twins had a very high perinatal mortality, three-fold higher than singletons. A birth weight < 2000g was the strongest risk factor for perinatal death, and unrecognized twin pregnancy was common. Urgent interventions are needed to lower perinatal twin mortality in Guinea-Bissau. [ABSTRACT FROM AUTHOR]

Genetic association analysis on complex phenotypes under a longitudinal design involving pedigrees encounters the problem of correlation within pedigrees, which could affect statistical assessment of the genetic effects. Approaches have been proposed to integrate kinship correlation into the mixed-effect models to explicitly model the genetic relationship. These have proved to be an efficient way of dealing with sample clustering in pedigree data. Although current algorithms implemented in popular statistical packages are useful for adjusting relatedness in the mixed modeling of genetic effects on the mean level of a phenotype, they are not sufficiently straightforward to handle the kinship correlation on the time-dependent trajectories of a phenotype. We introduce a 2-level hierarchical linear model to separately assess the genetic associations with the mean level and the rate of change of a phenotype, integrating kinship correlation in the analysis. We apply our method to the Genetic Analysis Workshop 18 genome-wide association studies data on chromosome 3 to estimate the genetic effects on systolic blood pressure measured over time in large pedigrees. Our method identifies genetic variants associated with blood pressure with estimated inflation factors of 0.99, suggesting that our modeling of random effects efficiently handles the genetic relatedness in pedigrees. Application to simulated data captures important variants specified in the simulation. Our results show that the method is useful for genetic association studies in related samples using longitudinal design.

Background: The etiology of multifactorial human diseases involves complex interactions between numerous environmental factors and alleles of many genes. Efficient statistical tools are demanded in identifying the genetic and environmental variants that affect the risk of disease development. This paper introduces a retrospective polytomous logistic regression model to measure both the main and interaction effects in genetic association studies of human discrete and continuous complex traits. In this model, combinations of genotypes at two interacting loci or of environmental exposure and genotypes at one locus are treated as nominal outcomes of which the proportions are modeled as a function of the disease trait assigning both main and interaction effects and with no assumption of normality in the trait distribution. Performance of our method in detecting interaction effect is compared with that of the case-only model., Results: Results from our simulation study indicate that our retrospective model exhibits high power in capturing even relatively small effect with reasonable sample sizes. Application of our method to data from an association study on the catalase -262C/T promoter polymorphism and aging phenotypes detected significant main and interaction effects for age-group and allele T on individual's cognitive functioning and produced consistent results in estimating the interaction effect as compared with the popular case-only model., Conclusion: The retrospective polytomous logistic regression model can be used as a convenient tool for assessing both main and interaction effects in genetic association studies of human multifactorial diseases involving genetic and non-genetic factors as well as categorical or continuous traits.