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For those not of a technical bent, there is a great deal of confusion surrounding the terms 'interoperability' and 'integration', especially when it comes to the exchange of information in 'black-box' systems. The average depositor of data doesn't want (or need) to know how data and meta data move around a system as long as what they put in eventually gets to where it should be, in the form it should be and can be seen by the appropriate people. However, a basic understanding of the similarities and differences between 'interoperable' systems and 'integrated' systems and the pros and cons of each approach when it comes to depositing, preserving and discovering data will help users and administrators make informed decisions when it comes to the specification of data management systems, and will help inform their day-to-day data management practices. This poster is intended to highlight those similarities and differences, pros and cons.

Background: Evidence suggests that in utero exposure to undernutrition and overnutrition might affect adiposity in later life. Epigenetic modification is suggested as a plausible mediating mechanism. Methods: We used multivariable linear regression and a negative control design to examine offspring epigenome-wide DNA methylation in relation to maternal and offspring adiposity in 1018 participants. Results: Compared with neonatal offspring of normal weight mothers, 28 and 1621 CpG sites were differentially methylated in offspring of obese and underweight mothers, respectively [false discovert rate (FDR)-corrected P-value

Maternal smoking during pregnancy has been found to influence newborn DNA methylation in genes involved in fundamental developmental processes. It is pertinent to understand the degree to which the offspring methylome is sensitive to the intensity and duration of prenatal smoking. An investigation of the persistence of offspring methylation associated with maternal smoking and the relative roles of the intrauterine and postnatal environment is also warranted. In the Avon Longitudinal Study of Parents and Children, we investigated associations between prenatal exposure to maternal smoking and offspring DNA methylation at multiple time points in approximately 800 mother-offspring pairs. In cord blood, methylation at 15 CpG sites in seven gene regions (AHRR, MYO1G, GFI1, CYP1A1, CNTNAP2, KLF13 and ATP9A) was associated with maternal smoking, and a dose-dependent response was observed in relation to smoking duration and intensity. Longitudinal analysis of blood DNA methylation in serial samples at birth, age 7 and 17 years demonstrated that some CpG sites showed reversibility of methylation (GFI1, KLF13 and ATP9A), whereas others showed persistently perturbed patterns (AHRR, MYO1G, CYP1A1 and CNTNAP2). Of those showing persistence, we explored the effect of postnatal smoke exposure and found that the major contribution to altered methylation was attributed to a critical window of in utero exposure. A comparison of paternal and maternal smoking and offspring methylation showed consistently stronger maternal associations, providing further evidence for causal intrauterine mechanisms. These findings emphasize the sensitivity of the methylome to maternal smoking during early development and the long-term impact of such exposure.

Multiple differentially methylated sites and regions associated with adiposity have now been identified in large-scale cross sectional studies. We tested for replication of associations between previously identified CpG sites at HIF3A and adiposity in 1,000 mother-offspring pairs from the Avon Longitudinal Study of Parents and Children. Availability of methylation and adiposity measures at multiple time points, as well as genetic data, allowed us to assess the temporal associations between adiposity and methylation and to make inferences regarding causality and directionality.Overall, our results were discordant with those expected if HIF3A methylation has a causal effect on BMI and provided more evidence for causality in the reverse direction i.e. an effect of BMI on HIF3A methylation. These results are based on robust evidence from longitudinal analyses and were also partially supported by Mendelian randomization analysis, although this latter analysis was underpowered to detect a causal effect of BMI on HIF3A methylation. Our results also highlight an apparent long-lasting inter-generational influence of maternal BMI on offspring methylation at this locus, which may confound associations between own adiposity and HIF3A methylation. Further work is required to replicate and uncover the mechanisms underlying both the direct and inter-generational effect of adiposity on DNA methylation.

DNA methylation based biomarkers of aging are highly correlated with actual age. Departures of methylation-estimated age from actual age can be used to define epigenetic measures of child development or age acceleration in adults. Very little is known about genetic or environmental determinants of these epigenetic measures of aging. We obtained DNA methylation profiles using Infinium HumanMethylation450 BeadChips across five time points in 1018 mother-child pairs from the Avon Longitudinal Study of Parents and Children. Using the Horvath age estimation method, we calculated epigenetic age for these samples. Age acceleration (AA) was defined as the residuals from regressing epigenetic age on actual age. AA was tested for associations with cross-sectional clinical variables in children. We identified associations between AA and sex, birth weight, birth by caesarean section and several maternal characteristics in pregnancy, namely smoking, weight, BMI, selenium and cholesterol level. Offspring of non-drinkers had higher AA on average but this difference appeared to resolve during childhood. The associations between sex, birth weight and AA found in ARIES were replicated in an independent cohort (GOYA). In children, epigenetic AA measures are associated with several clinically relevant variables, and early life exposures appear to be associated with changes in AA during adolescence. Further research into epigenetic aging, including the use of causal inference methods, is required to better our understanding of aging.

In order to tailor web-content to the requirements of a device, it is necessary to access information about the attributes of both the device and the web content Profiles containing such information from heterogeneous sources may use many different terms to represent the same concept (eg Resolution/Screen_Res/Res). This can present problems for applications which try to interpret the semantics of these terms In this thesis, we present an architecture which, when given profiles describing a device and web service, can identify terms that are present in an ontology of recognised terms in the domain of device capabilities and web service requirements The architecture can semi-automatically identify unknown terms by combining the results of several schemamatching applications. The ontology can be expanded based on end-user’s interaction with the semi-automatic matchers and thus over time the application’s ontology will grow to include previously unknown terms.