Project description:PurposeThis study aimed to evaluate the associations of GJD2 (rs634990, rs524952) and RASGRF1 (rs8027411, rs4778879, rs28412916) gene polymorphisms with refractive errors.MethodsThe study included 373 subjects with refractive errors (48 myopia, 239 myopia with astigmatism, 14 hyperopia, and 72 hyperopia with astigmatism patients) and 104 ophthalmologically healthy subjects in the control group. A quantitative real-time polymerase chain reaction (qPCR) method was chosen for genotyping. Statistical calculations and analysis of results were performed with IBM SPSS Statistics 27 software.ResultsThe correlations in monozygotic (MZ) twin pairs were higher compared to DZ pairs, indicating genetic effects on hyperopia and astigmatism. The heritability (h2) of hyperopia and astigmatism was 0.654 for the right eye and 0.492 for the left eye. The GJD2 rs634990 TT genotype increased the incidence of hyperopia with astigmatism by 2.4-fold and the CT genotype decreased the incidence of hyperopia with astigmatism by 0.51-fold (p < 0.05). The GJD2 rs524952 AT genotype reduced the incidence of hyperopia with astigmatism by 0.53-fold (p < 0.05). Haplotype analysis of SNPs in the GJD2 gene revealed two statistically significant haplotypes: ACTAGG for rs634990 and TTTAGA for rs524952, which statistically significantly reduced the incidence of hyperopia and hyperopia with astigmatism by 0.41-fold (95% CI: 0.220-0.765) and 0.383-fold (95% CI: 0.199-0.737), respectively (p < 0.05). It was also found that, in the presence of haplotypes ACTAGG for rs634990 and TATAGA for rs524952, the possibility of hyperopia was reduced by 0.4-fold (p < 0.05).Conclusionsthe heritability of hyperopia and hyperopia with astigmatism was 0.654-0.492, according to different eyes in patients between 20 and 40 years. The GJD2 rs634990 was identified as an SNP, which has significant associations with the co-occurrence of hyperopia and astigmatism. Patients with the GJD2 gene rs634990 TT genotype were found to have a 2.4-fold higher risk of develop hyperopia with astigmatism.

Project description:PurposeThe South Australian Aboriginal Birth Cohort (SAABC) is a prospective, longitudinal birth cohort established to: (1) estimate Aboriginal child dental disease compared with population estimates; (2) determine the efficacy of an early childhood caries intervention in early versus late infancy; (3) examine if efficacy was sustained over time and; (4) document factors influencing social, behavioural, cognitive, anthropometric, dietary and educational attainment over time.ParticipantsThe original SAABC comprised 449 women pregnant with an Aboriginal child recruited February 2011 to May 2012. At child age 2 years, 324 (74%) participants were retained, at age 3 years, 324 (74%) participants were retained and at age 5 years, 299 (69%) participants were retained. Fieldwork for follow-up at age 7 years is underway, with funding available for follow-up at age 9 years.Findings to dateAt baseline, 53% of mothers were aged 14-24 years and 72% had high school or less educational attainment. At age 3 years, dental disease experience was higher among children exposed to the intervention later rather than earlier in infancy. The effect was sustained at age 5 years, but rates were still higher than general child population estimates. Experiences of racism were high among mothers, with impacts on both tooth brushing and toothache. Compared with population estimates, levels of self-efficacy and self-rated oral health of mothers at baseline were low.Future plansOur data have contributed to a better understanding of the environmental, behavioural, dietary, biological and psychosocial factors contributing to Aboriginal child oral and general health, and social and emotional well-being. This is beneficial in charting the trajectory of cohort participants' health and well-being overtime, particularly in identifying antecedents of chronic diseases which are highly prevalent among Aboriginal Australians. Funding for continued follow-up of the cohort will be sought.Trial registration numberACTRN12611000111976; Post-results.

Project description:BACKGROUND:Despite the growing interest in the relation between adiposity in children and different lifestyle clusters, few studies used a longitudinal design to examine a large range of behaviors in various contexts, in particular eating- and sleep-related routines, and few studies have examined these factors in young children. The objectives of this study were to identify clusters of boys and girls based on diet, sleep and activity-related behaviors and their family environment at 2 and 5?years of age, and to assess whether the clusters identified varied across maternal education levels and were associated with body fat at age 5. METHODS:At 2 and 5?years, respectively, 1436 and 1195 parents from the EDEN mother-child cohort completed a questionnaire including behavioral data. A latent class analysis aimed to uncover gender-specific behavioral clusters. Body fat percentage was estimated by anthropometric and bioelectrical impedance measurements. Association between cluster membership and body fat was assessed with mutivariable linear regression models. RESULTS:At 2?years, two clusters emerged that were essentially characterized by opposite eating habits. At 5?years, TV exposure was the most distinguishing feature, but the numbers and types of clusters differed by gender. An association between cluster membership and body fat was found only in girls at 5?years of age, with girls in the cluster defined by very high TV exposure and unfavorable mealtime habits (despite high outdoor playing and walking time) having the highest body fat. Girls whose mother had low educational attainment were more likely to be in this high-risk cluster. Girls who were on a cluster evolution path corresponding to the highest TV viewing time and the least favorable mealtime habits from 2 to 5?years of age had higher body fat at 5?years. CONCLUSIONS:Efforts to decrease TV time and improve mealtime routines may hold promise for preventing overweight in young children, especially girls growing up in disadvantaged families. These preventive efforts should start as early in life as possible, ideally before the age of two, and should be sustained over the preschool years.

Project description:All subjects were recruited at Centennial Women?s Hospital and the Perinatal Research Center in Nashville, TN beginning in 2003. Pregnant women were enrolled during their first clinical visit after obtaining informed consent as described previously. Demographic and clinical data specific to the fetus was collected from clinical records. Gestational age of the neonate was determined by maternal reporting of the last menstrual period and corroboration by ultrasound dating. Accurate knowledge of gestational age (GA) is essential for proper monitoring and care of neonates. However, accurate GA measures are often not available. DNA methylation has previously been shown to associate with GA, and has been used to accurately predict chronological age in adults. In the current study, we examine whether DNA methylation in cord blood can be used to predict gestational age at birth. Results: We found that GA can be accurately predicted from DNA methylation of neonatal cord blood and blood spot samples (DNAm GA), using 148 CpG sites selected through elastic net regression in six training datasets (N=207). We evaluated predictive accuracy in six testing datasets (N=1,202), and found that the accuracy of DNAm GA meets or exceeds accuracy of gestational age estimates based on established methods. We also found an increased DNAm GA, relative to clinical GA, was associated with increased birthweight percentile (p=.00057), adjusting for GA, sex, and ancestry, suggesting that DNAm GA could represent developmental age more accurately than clinical estimates of GA. Conclusions: Further development of this predictor could provide a method of accurate neonatal estimation of GA for use in resource-limited populations, or in cases where GA cannot be estimated clinically. When clinical estimates are available, the predictor can be used to test hypotheses related to developmental age and other early life circumstances, and may provide increased accuracy beyond clinical estimates.

Project description:All subjects were recruited at Centennial Women?s Hospital and the Perinatal Research Center in Nashville, TN beginning in 2003. Pregnant women were enrolled during their first clinical visit after obtaining informed consent as described previously. Demographic and clinical data specific to the fetus was collected from clinical records. Gestational age of the neonate was determined by maternal reporting of the last menstrual period and corroboration by ultrasound dating. Accurate knowledge of gestational age (GA) is essential for proper monitoring and care of neonates. However, accurate GA measures are often not available. DNA methylation has previously been shown to associate with GA, and has been used to accurately predict chronological age in adults. In the current study, we examine whether DNA methylation in cord blood can be used to predict gestational age at birth. Results: We found that GA can be accurately predicted from DNA methylation of neonatal cord blood and blood spot samples (DNAm GA), using 148 CpG sites selected through elastic net regression in six training datasets (N=207). We evaluated predictive accuracy in six testing datasets (N=1,202), and found that the accuracy of DNAm GA meets or exceeds accuracy of gestational age estimates based on established methods. We also found an increased DNAm GA, relative to clinical GA, was associated with increased birthweight percentile (p=.00057), adjusting for GA, sex, and ancestry, suggesting that DNAm GA could represent developmental age more accurately than clinical estimates of GA. Conclusions: Further development of this predictor could provide a method of accurate neonatal estimation of GA for use in resource-limited populations, or in cases where GA cannot be estimated clinically. When clinical estimates are available, the predictor can be used to test hypotheses related to developmental age and other early life circumstances, and may provide increased accuracy beyond clinical estimates. 36 Umbilical cord blood samples were collected in EDTA tubes soon after placental delivery. Blood samples were centrifuged at 3,000 RPM to separate plasma, and buffy coats were aliquoted and stored at -80oC. DNA was extracted using the DNeasy Kit (Qiagen). DNA methylation was interrogated for each sample using the HumanMethylation450 BeadChip (Illumina).

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Longitudinal association between sleep features and refractive errors in preschoolers from the EDEN birth-cohort.

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