Interaction of sexual dimorphism and gene dosage imbalance in skeletal deficits associated with Down syndrome

All individuals with Down syndrome (DS), which results from trisomy of human chromosome 21 (Ts21), present with skeletal abnormalities typified by craniofacial features, short stature and low bone mineral density (BMD). Differences in skeletal deficits between males and females with DS suggest a sexual dimorphism in how trisomy affects bone. Dp1Tyb mice contain three copies of all of the genes on mouse chromosome 16 that are homologous to human chromosome 21, males and females are fertile, and therefore are an excellent model to test the hypothesis that gene dosage influences the sexual dimorphism of bone abnormalities in DS. Dp1Tyb as compared to control littermate mice at time points associated with bone accrual (6 weeks) and skeletal maturity (16 weeks) showed deficits in BMD and trabecular architecture that occur largely through interactions between sex and genotype and resulted in lower percent bone volume in all female and Dp1Tyb male mice. Cortical bone in Dp1Tyb as compared to control mice exhibited different changes over time influenced by sex × genotype interactions including reduced cortical area in both male and female Dp1Tyb mice. Mechanical testing analyses suggested deficits in whole bone properties such as bone mass and geometry, but improved material properties in female and Dp1Tyb mice. Sexual dimorphisms and the influence of trisomic gene dosage differentially altered cellular properties of male and female Dp1Tyb bone. These data establish sex, gene dosage, skeletal site and age as important factors in skeletal development of DS model mice, paving the way for identification of the causal dosage-sensitive genes. Skeletal differences in developing male and female Dp1Tyb DS model mice replicated differences in less-studied adolescents with DS and established a foundation to understand the etiology of trisomic bone deficits

Peat Bog Wildfire Smoke Exposure in Rural North Carolina Is Associated with Cardiopulmonary Emergency Department Visits Assessed through Syndromic Surveillance

Background: In June 2008, burning peat deposits produced haze and air pollution far in excess of National Ambient Air Quality Standards, encroaching on rural communities of eastern North Carolina. Although the association of mortality and morbidity with exposure to urban air pollution is well established, the health effects associated with exposure to wildfire emissions are less well understood. Objective: We investigated the effects of exposure on cardiorespiratory outcomes in the population affected by the fire. Methods: We performed a population-based study using emergency department (ED) visits reported through the syndromic surveillance program NC DETECT (North Carolina Disease Event Tracking and Epidemiologic Collection Tool). We used aerosol optical depth measured by a satellite to determine a high-exposure window and distinguish counties most impacted by the dense smoke plume from surrounding referent counties. Poisson log-linear regression with a 5-day distributed lag was used to estimate changes in the cumulative relative risk (RR). Results: In the exposed counties, significant increases in cumulative RR for asthma [1.65 (95% confidence interval, 1.25–2.1)], chronic obstructive pulmonary disease [1.73 (1.06–2.83)], and pneumonia and acute bronchitis [1.59 (1.07–2.34)] were observed. ED visits associated with cardiopulmonary symptoms [1.23 (1.06–1.43)] and heart failure [1.37 (1.01–1.85)] were also significantly increased. Conclusions: Satellite data and syndromic surveillance were combined to assess the health impacts of wildfire smoke in rural counties with sparse air-quality monitoring. This is the first study to demonstrate both respiratory and cardiac effects after brief exposure to peat wildfire smoke

Forests as Commons – Changing Traditions and Governance in Europe

Commons are complex institutions and exist across the world in a wide range of situations regarding locally developed governance and management systems of many different natural resources. For many people commons remain associated with Hardin’s theory concerning the “Tragedy of the Commons” (1968), in which he assumed that local users of a natural resource are unable to formulate governance and management structures concerning their own choices that took into account the long-term sustainability of the resource itself. As a result, Hardin articulated that the tragedy was that the resource would inevitably become degraded in such situations and that the solution was private or public ownership. However, across Europe many forests have for a very long period of time successfully been managed as commons, just as they have in many other parts of the world. This chapter has three main aims: It will provide an introduction to the various types of commons before going on to link the issue of commons to the traditional forest landscapes of Europe, and it will look at how the role of forests and forest landscapes has changed and how it may change further in the future

Genome-Wide Identification of Bcl11b Gene Targets Reveals Role in Brain-Derived Neurotrophic Factor Signaling

B-cell leukemia/lymphoma 11B (Bcl11b) is a transcription factor showing predominant expression in the striatum. To date, there are no known gene targets of Bcl11b in the nervous system. Here, we define targets for Bcl11b in striatal cells by performing chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) in combination with genome-wide expression profiling. Transcriptome-wide analysis revealed that 694 genes were significantly altered in striatal cells over-expressing Bcl11b, including genes showing striatal-enriched expression similar to Bcl11b. ChIP-seq analysis demonstrated that Bcl11b bound a mixture of coding and non-coding sequences that were within 10 kb of the transcription start site of an annotated gene. Integrating all ChIP-seq hits with the microarray expression data, 248 direct targets of Bcl11b were identified. Functional analysis on the integrated gene target list identified several zinc-finger encoding genes as Bcl11b targets, and further revealed a significant association of Bcl11b to brain-derived neurotrophic factor/neurotrophin signaling. Analysis of ChIP-seq binding regions revealed significant consensus DNA binding motifs for Bcl11b. These data implicate Bcl11b as a novel regulator of the BDNF signaling pathway, which is disrupted in many neurological disorders. Specific targeting of the Bcl11b-DNA interaction could represent a novel therapeutic approach to lowering BDNF signaling specifically in striatal cells

Mitochondrial DNA Polymorphism A4917G Is Independently Associated with Age-Related Macular Degeneration

The objective of this study was to determine if MTND2*LHON4917G (4917G), a specific non-synonymous polymorphism in the mitochondrial genome previously associated with neurodegenerative phenotypes, is associated with increased risk for age-related macular degeneration (AMD). A preliminary study of 393 individuals (293 cases and 100 controls) ascertained at Vanderbilt revealed an increased occurrence of 4917G in cases compared to controls (15.4% vs.9.0%, p = 0.11). Since there was a significant age difference between cases and controls in this initial analysis, we extended the study by selecting Caucasian pairs matched at the exact age at examination. From the 1547 individuals in the Vanderbilt/Duke AMD population association study (including 157 in the preliminary study), we were able to match 560 (280 cases and 280 unaffected) on exact age at examination. This study population was genotyped for 4917G plus specific AMD-associated nuclear genome polymorphisms in CFH, LOC387715 and ApoE. Following adjustment for the listed nuclear genome polymorphisms, 4917G independently predicts the presence of AMD (OR = 2.16, 95%CI 1.20–3.91, p = 0.01). In conclusion, a specific mitochondrial polymorphism previously implicated in other neurodegenerative phenotypes (4917G) appears to convey risk for AMD independent of recently discovered nuclear DNA polymorphisms

Using genetic variation and environmental risk factor data to identify individuals at high risk for age-related macular degeneration

A major goal of personalized medicine is to pre-symptomatically identify individuals at high risk for disease using knowledge of each individual's particular genetic profile and constellation of environmental risk factors. With the identification of several well-replicated risk factors for age-related macular degeneration (AMD), the leading cause of legal blindness in older adults, this previously unreachable goal is beginning to seem less elusive. However, recently developed algorithms have either been much less accurate than expected, given the strong effects of the identified risk factors, or have not been applied to independent datasets, leaving unknown how well they would perform in the population at large. We sought to increase accuracy by using novel modeling strategies, including multifactor dimensionality reduction (MDR) and grammatical evolution of neural networks (GENN), in addition to the traditional logistic regression approach. Furthermore, we rigorously designed and tested our models in three distinct datasets: a Vanderbilt-Miami (VM) clinic-based case-control dataset, a VM family dataset, and the population-based Age-related Maculopathy Ancillary (ARMA) Study cohort. Using a consensus approach to combine the results from logistic regression and GENN models, our algorithm was successful in differentiating between high- and low-risk groups (sensitivity 77.0%, specificity 74.1%). In the ARMA cohort, the positive and negative predictive values were 63.3% and 70.7%, respectively. We expect that future efforts to refine this algorithm by increasing the sample size available for model building, including novel susceptibility factors as they are discovered, and by calibrating the model for diverse populations will improve accuracy

A Global Clustering Algorithm to Identify Long Intergenic Non-Coding RNA - with Applications in Mouse Macrophages

Identification of diffuse signals from the chromatin immunoprecipitation and high-throughput massively parallel sequencing (ChIP-Seq) technology poses significant computational challenges, and there are few methods currently available. We present a novel global clustering approach to enrich diffuse CHIP-Seq signals of RNA polymerase II and histone 3 lysine 4 trimethylation (H3K4Me3) and apply it to identify putative long intergenic non-coding RNAs (lincRNAs) in macrophage cells. Our global clustering method compares favorably to the local clustering method SICER that was also designed to identify diffuse CHIP-Seq signals. The validity of the algorithm is confirmed at several levels. First, 8 out of a total of 11 selected putative lincRNA regions in primary macrophages respond to lipopolysaccharides (LPS) treatment as predicted by our computational method. Second, the genes nearest to lincRNAs are enriched with biological functions related to metabolic processes under resting conditions but with developmental and immune-related functions under LPS treatment. Third, the putative lincRNAs have conserved promoters, modestly conserved exons, and expected secondary structures by prediction. Last, they are enriched with motifs of transcription factors such as PU.1 and AP.1, previously shown to be important lineage determining factors in macrophages, and 83% of them overlap with distal enhancers markers. In summary, GCLS based on RNA polymerase II and H3K4Me3 CHIP-Seq method can effectively detect putative lincRNAs that exhibit expected characteristics, as exemplified by macrophages in the study

The App-Runx1 Region Is Critical for Birth Defects and Electrocardiographic Dysfunctions Observed in a Down Syndrome Mouse Model

Down syndrome (DS) leads to complex phenotypes and is the main genetic cause of birth defects and heart diseases. The Ts65Dn DS mouse model is trisomic for the distal part of mouse chromosome 16 and displays similar features with post-natal lethality and cardiovascular defects. In order to better understand these defects, we defined electrocardiogram (ECG) with a precordial set-up, and we found conduction defects and modifications in wave shape, amplitudes, and durations in Ts65Dn mice. By using a genetic approach consisting of crossing Ts65Dn mice with Ms5Yah mice monosomic for the App-Runx1 genetic interval, we showed that the Ts65Dn viability and ECG were improved by this reduction of gene copy number. Whole-genome expression studies confirmed gene dosage effect in Ts65Dn, Ms5Yah, and Ts65Dn/Ms5Yah hearts and showed an overall perturbation of pathways connected to post-natal lethality (Coq7, Dyrk1a, F5, Gabpa, Hmgn1, Pde10a, Morc3, Slc5a3, and Vwf) and heart function (Tfb1m, Adam19, Slc8a1/Ncx1, and Rcan1). In addition cardiac connexins (Cx40, Cx43) and sodium channel sub-units (Scn5a, Scn1b, Scn10a) were found down-regulated in Ts65Dn atria with additional down-regulation of Cx40 in Ts65Dn ventricles and were likely contributing to conduction defects. All these data pinpoint new cardiac phenotypes in the Ts65Dn, mimicking aspects of human DS features and pathways altered in the mouse model. In addition they highlight the role of the App-Runx1 interval, including Sod1 and Tiam1, in the induction of post-natal lethality and of the cardiac conduction defects in Ts65Dn. These results might lead to new therapeutic strategies to improve the care of DS people