Defining Smallness for Gestational Age in the Early Years of the Danish Medical Birth Registry

Background: Being born small for gestational age (SGA) is associated with decreased insulin sensitivity and increased blood pressure in childhood, but the association with clinical disease in early adulthood is less certain. The Danish Medical Birth Registry has registered all births in Denmark since 1973, but due to variable data quality, data is most often used only from 1981 onwards, and birth registers in other countries may have similar problems for the early years. We wanted to examine whether the data can be used for identification of children born SGA and used in future research. Methodology/Principal Findings: All persons born between 1974 and 1996 were identified in the Danish Medical Birth Registry (n = 1.704.890). Immigrants and children without data on gestational age and birth weight were excluded, and a total of 1.348.106 children were included in the analysis. The difference between the different variables used in the history of the registry were examined, and the quality of data in the birth registry from 1974-1981 was examined and compared to subsequent years. Data on birth weight and gestational age in the early years of the registry is inconsistent, and the identification of children born SGA is inaccurate, with 49 % false-positives. The biggest source of error is due to the rough and inaccurate intervals used for gestational age. By using –3 standard deviations as a cut-off for the identification of children born SGA, the number of false-positives was reduced to 9%, while the amount of false-negatives were increased. Conclusion: Choosing –3 standard deviations for identifying children born SGA is a viable, though not optimal solution fo

Gene-Centric Characteristics of Genome-Wide Association Studies

BACKGROUND: The high-throughput genotyping chips have contributed greatly to genome-wide association (GWA) studies to identify novel disease susceptibility single nucleotide polymorphisms (SNPs). The high-density chips are designed using two different SNP selection approaches, the direct gene-centric approach, and the indirect quasi-random SNPs or linkage disequilibrium (LD)-based tagSNPs approaches. Although all these approaches can provide high genome coverage and ascertain variants in genes, it is not clear to which extent these approaches could capture the common genic variants. It is also important to characterize and compare the differences between these approaches. METHODOLOGY/PRINCIPAL FINDINGS: In our study, by using both the Phase II HapMap data and the disease variants extracted from OMIM, a gene-centric evaluation was first performed to evaluate the ability of the approaches in capturing the disease variants in Caucasian population. Then the distribution patterns of SNPs were also characterized in genic regions, evolutionarily conserved introns and nongenic regions, ontologies and pathways. The results show that, no mater which SNP selection approach is used, the current high-density SNP chips provide very high coverage in genic regions and can capture most of known common disease variants under HapMap frame. The results also show that the differences between the direct and the indirect approaches are relatively small. Both have similar SNP distribution patterns in these gene-centric characteristics. CONCLUSIONS/SIGNIFICANCE: This study suggests that the indirect approaches not only have the advantage of high coverage but also are useful for studies focusing on various functional SNPs either in genes or in the conserved regions that the direct approach supports. The study and the annotation of characteristics will be helpful for designing and analyzing GWA studies that aim to identify genetic risk factors involved in common diseases, especially variants in genes and conserved regions

Modeling of Molecular Interaction between Apoptin, BCR-Abl and CrkL - An Alternative Approach to Conventional Rational Drug Design

In this study we have calculated a 3D structure of apoptin and through modeling and docking approaches, we show its interaction with Bcr-Abl oncoprotein and its downstream signaling components, following which we confirm some of the newly-found interactions by biochemical methods. Bcr-Abl oncoprotein is aberrantly expressed in chronic myelogenous leukaemia (CML). It has several distinct functional domains in addition to the Abl kinase domain. The SH3 and SH2 domains cooperatively play important roles in autoinhibiting its kinase activity. Adapter molecules such as Grb2 and CrkL interact with proline-rich region and activate multiple Bcr-Abl downstream signaling pathways that contribute to growth and survival. Therefore, the oncogenic effect of Bcr-Abl could be inhibited by the interaction of small molecules with these domains. Apoptin is a viral protein with well-documented cancer-selective cytotoxicity. Apoptin attributes such as SH2-like sequence similarity with CrkL SH2 domain, unique SH3 domain binding sequence, presence of proline-rich segments, and its nuclear affinity render the molecule capable of interaction with Bcr-Abl. Despite almost two decades of research, the mode of apoptin’s action remains elusive because 3D structure of apoptin is unavailable. We performed in silico threedimensional modeling of apoptin, molecular docking experiments between apoptin model and the known structure of Bcr- Abl, and the 3D structures of SH2 domains of CrkL and Bcr-Abl. We also biochemically validated some of the interactions that were first predicted in silico. This structure-property relationship of apoptin may help in unlocking its cancer-selective toxic properties. Moreover, such models will guide us in developing of a new class of potent apoptin-like molecules with greater selectivity and potency