Serum IgE Reactivity Profiling in an Asthma Affected Cohort

BACKGROUND: Epidemiological evidence indicates that atopic asthma correlates with high serum IgE levels though the contribution of allergen specific IgE to the pathogenesis and the severity of the disease is still unclear. METHODS: We developed a microarray immunoassay containing 103 allergens to study the IgE reactivity profiles of 485 asthmatic and 342 non-asthmatic individuals belonging to families whose members have a documented history of asthma and atopy. We employed k-means clustering, to investigate whether a particular IgE reactivity profile correlated with asthma and other atopic conditions such as rhinitis, conjunctivitis and eczema. RESULTS: Both case-control and parent-to-siblings analyses demonstrated that while the presence of specific IgE against individual allergens correlated poorly with pathological conditions, particular reactivity profiles were significantly associated with asthma (p<10E-09). An artificial neural network (ANN)-based algorithm, calibrated with the profile reactivity data, correctly classified as asthmatic or non-asthmatic 78% of the individual examined. Multivariate statistical analysis demonstrated that the familiar relationships of the study population did not affect the observed correlations. CONCLUSIONS: These findings indicate that asthma is a higher-order phenomenon related to patterns of IgE reactivity rather than to single antibody reactions. This notion sheds new light on the pathogenesis of the disease and can be readily employed to distinguish asthmatic and non-asthmatic individuals on the basis of their serum reactivity profile

Transcription Factors Bind Thousands of Active and Inactive Regions in the Drosophila Blastoderm

Identifying the genomic regions bound by sequence-specific regulatory factors is central both to deciphering the complex DNA cis-regulatory code that controls transcription in metazoans and to determining the range of genes that shape animal morphogenesis. We used whole-genome tiling arrays to map sequences bound in Drosophila melanogaster embryos by the six maternal and gap transcription factors that initiate anterior–posterior patterning. We find that these sequence-specific DNA binding proteins bind with quantitatively different specificities to highly overlapping sets of several thousand genomic regions in blastoderm embryos. Specific high- and moderate-affinity in vitro recognition sequences for each factor are enriched in bound regions. This enrichment, however, is not sufficient to explain the pattern of binding in vivo and varies in a context-dependent manner, demonstrating that higher-order rules must govern targeting of transcription factors. The more highly bound regions include all of the over 40 well-characterized enhancers known to respond to these factors as well as several hundred putative new cis-regulatory modules clustered near developmental regulators and other genes with patterned expression at this stage of embryogenesis. The new targets include most of the microRNAs (miRNAs) transcribed in the blastoderm, as well as all major zygotically transcribed dorsal–ventral patterning genes, whose expression we show to be quantitatively modulated by anterior–posterior factors. In addition to these highly bound regions, there are several thousand regions that are reproducibly bound at lower levels. However, these poorly bound regions are, collectively, far more distant from genes transcribed in the blastoderm than highly bound regions; are preferentially found in protein-coding sequences; and are less conserved than highly bound regions. Together these observations suggest that many of these poorly bound regions are not involved in early-embryonic transcriptional regulation, and a significant proportion may be nonfunctional. Surprisingly, for five of the six factors, their recognition sites are not unambiguously more constrained evolutionarily than the immediate flanking DNA, even in more highly bound and presumably functional regions, indicating that comparative DNA sequence analysis is limited in its ability to identify functional transcription factor targets

Post-Socialist Transition and the Intergenerational Transmission of Education in Kyrgyzstan

We investigate long-term trends in the intergenerational transmission of education in a low income country undergoing a transition from socialism to a market economy. We draw on evidence from Kyrgyzstan using data from three household surveys collected in 1993, 1998 and 2011. We find that Kyrgyzstan, like Eastern European middle income transition economies, generally maintained high educational mobility, comparable to the levels during Soviet times. However, we find that the younger cohorts, who were exposed to the transition during their school years, experienced a rapid decline in educational mobility. We also document that gender differences in schooling and educational mobility, found among older-aged individuals, disappeared in the younger population