Mechanistic Phenotypes: An Aggregative Phenotyping Strategy to Identify Disease Mechanisms Using GWAS Data

A single mutation can alter cellular and global homeostatic mechanisms and give rise to multiple clinical diseases. We hypothesized that these disease mechanisms could be identified using low minor allele frequency (MAF<0.1) non-synonymous SNPs (nsSNPs) associated with “mechanistic phenotypes”, comprised of collections of related diagnoses. We studied two mechanistic phenotypes: (1) thrombosis, evaluated in a population of 1,655 African Americans; and (2) four groupings of cancer diagnoses, evaluated in 3,009 white European Americans. We tested associations between nsSNPs represented on GWAS platforms and mechanistic phenotypes ascertained from electronic medical records (EMRs), and sought enrichment in functional ontologies across the top-ranked associations. We used a two-step analytic approach whereby nsSNPs were first sorted by the strength of their association with a phenotype. We tested associations using two reverse genetic models and standard additive and recessive models. In the second step, we employed a hypothesis-free ontological enrichment analysis using the sorted nsSNPs to identify functional mechanisms underlying the diagnoses comprising the mechanistic phenotypes. The thrombosis phenotype was solely associated with ontologies related to blood coagulation (Fisher''s p = 0.0001, FDR p = 0.03), driven by the F5, P2RY12 and F2RL2 genes. For the cancer phenotypes, the reverse genetics models were enriched in DNA repair functions (p = 2×10−5, FDR p = 0.03) (POLG/FANCI, SLX4/FANCP, XRCC1, BRCA1, FANCA, CHD1L) while the additive model showed enrichment related to chromatid segregation (p = 4×10−6, FDR p = 0.005) (KIF25, PINX1). We were able to replicate nsSNP associations for POLG/FANCI, BRCA1, FANCA and CHD1L in independent data sets. Mechanism-oriented phenotyping using collections of EMR-derived diagnoses can elucidate fundamental disease mechanisms.     

Synthesising 30 Years of Mathematical Modelling of Echinococcus Transmission

Background

Echinococcosis is a complex zoonosis that has domestic and sylvatic lifecycles, and a range of different intermediate and definitive host species. The complexities of its transmission and the sparse evidence on the effectiveness of control strategies in diverse settings provide significant challenges for the design of effective public health policy against this disease. Mathematical modelling is a useful tool for simulating control packages under locally specific transmission conditions to inform optimal timing and frequency of phased interventions for cost-effective control of echinococcosis. The aims of this review of 30 years of Echinococcus modelling were to discern the epidemiological mechanisms underpinning models of Echinococcus granulosus and E. multilocularis transmission and to establish the need to include a human transmission component in such models.

Methodology/Principal Findings

A search was conducted of all relevant articles published up until July 2012, identified from the PubMED, Web of Knowledge and Medline databases and review of bibliographies of selected papers. Papers eligible for inclusion were those describing the design of a new model, or modification of an existing mathematical model of E. granulosus or E. multilocularis transmission. A total of 13 eligible papers were identified, five of which described mathematical models of E. granulosus and eight that described E. multilocularis transmission. These models varied primarily on the basis of six key mechanisms that all have the capacity to modulate model dynamics, qualitatively affecting projections. These are: 1) the inclusion of a ‘latent’ class and/or time delay from host exposure to infectiousness; 2) an age structure for animal hosts; 3) the presence of density-dependent constraints; 4) accounting for seasonality; 5) stochastic parameters; and 6) inclusion of spatial and risk structures.

Conclusions/Significance

This review discusses the conditions under which these mechanisms may be important for inclusion in models of Echinococcus transmission and proposes recommendations for the design of dynamic human models of transmission. Accounting for the dynamic behaviour of the Echinococcus parasites in humans will be key to predicting changes in the disease burden over time and to simulate control strategies that optimise public health impact.     

Network-Level Structural Abnormalities of Cerebral Cortex in Type 1 Diabetes Mellitus

Type 1 diabetes mellitus (T1DM) usually begins in childhood and adolescence and causes lifelong damage to several major organs including the brain. Despite increasing evidence of T1DM-induced structural deficits in cortical regions implicated in higher cognitive and emotional functions, little is known whether and how the structural connectivity between these regions is altered in the T1DM brain. Using inter-regional covariance of cortical thickness measurements from high-resolution T1-weighted magnetic resonance data, we examined the topological organizations of cortical structural networks in 81 T1DM patients and 38 healthy subjects. We found a relative absence of hierarchically high-level hubs in the prefrontal lobe of T1DM patients, which suggests ineffective top-down control of the prefrontal cortex in T1DM. Furthermore, inter-network connections between the strategic/executive control system and systems subserving other cortical functions including language and mnemonic/emotional processing were also less integrated in T1DM patients than in healthy individuals. The current results provide structural evidence for T1DM-related dysfunctional cortical organization, which specifically underlie the top-down cognitive control of language, memory, and emotion.     

Association between Gestational Weight Gain and Postpartum Diabetes: Evidence from a Community Based Large Cohort Study

We have investigated the prospective association between excess gestational weight gain (GWG) and development of diabetes by 21 years post-partum using a community-based large prospective cohort study in Brisbane, Australia. There were 3386 mothers for whom complete data were available on GWG, pre-pregnancy BMI and self-reported diabetes 21 years post-partum. We used The Institute of Medicine (IOM) definition to categorize GWG as inadequate, adequate and excessive. We found 839 (25.78%) mothers gained inadequate weight, 1,353 (39.96%) had adequate weight gain and 1,194 (35.26%) had gained excessive weight during pregnancy. At 21 years post-partum, 8.40% of mothers self-reported a diagnosis of diabetes made by their doctor. In the age adjusted model, we found mothers who gained excess weight during pregnancy were 1.47(1.11,1.94) times more likely to experience diabetes at 21 years post-partum compared to the mothers who gained adequate weight. This association was not explained by the potential confounders including maternal age, parity, education, race, smoking, TV watching and exercise. However, this association was mediated by the current BMI. There was no association for the women who had normal BMI before pregnancy and gained excess weight during pregnancy. The findings of this study suggest that women who gain excess weight during pregnancy are at greater risk of being diagnosed with diabetes in later life. This relationship is likely mediated through the pathway of post-partum weight-retention and obesity. This study adds evidence to the argument that excessive GWG during pregnancy for overweight mothers has long term maternal health implications.     

Spatial Interactions between Successive Eye and Arm Movements: Signal Type Matters

Spatial interactions between consecutive movements are often attributed to inhibition of return (IOR), a phenomenon in which responses to previously signalled locations are slower than responses to unsignalled locations. In two experiments using peripheral target signals offset by 0°, 90°, or 180°, we show that consecutive saccadic (Experiment 1) and reaching (Experiment 3) responses exhibit a monotonic pattern of reaction times consistent with the currently established spatial distribution of IOR. In contrast, in two experiments with central target signals (i.e., arrowheads pointing at target locations), we find a non-monotonic pattern of reaction times for saccades (Experiment 2) and reaching movements (Experiment 4). The difference in the patterns of results observed demonstrates different behavioral effects that depend on signal type. The pattern of results observed for central stimuli are consistent with a model in which neural adaptation is occurring within motor networks encoding movement direction in a distributed manner.     

Probing antioxidant activity of 2′-hydroxychalcones: Crystal and molecular structures, in vitro antiproliferative studies and in vivo effects on glucose regulation

In order to better understand the antioxidant behavior of a series of polyphenolic 2′-hydroxychalcones, we describe the results of several chemical and biological studies, in vitro and in vivo. Single crystal X-ray methods elucidated their molecular structures and important intermolecular interactions such as H-bonding and molecular stacking in the crystal structures that contribute to our knowledge in explaining antioxidant activity. The results of experiments using the 1,1-diphenyl-2-dipicrylhydrazyl (DPPH) UV–vis spectroscopic method indicate that a hydroxyl group in position 5′ induces the highest antioxidant activity. Consequently, 2,2′,5′-trihydroxychalcone was selected for further study in vitro towards ROS scavenging in L-6 myoblasts and THP-1 human monocytes, where it shows an excellent antioxidant activity in a concentration range lower than that reported by most studies of related molecules. In addition, this chalcone shows a very selective activity: it inhibits the proliferation of leukemic cells, but it does not affect the normal L-6 myoblasts and human fibroblasts. In studying 2,2′,5′-trihydroxychalcone's effect on weight gain and serum glucose and insulin levels in Zucker fatty (fa⁻/fa⁻) rats we found that supplementing the diet with a 10 mg/kg dose of this chalcone (3 times weekly) blunted the increase in glucose that co-occurs with weight gain over the 6-week treatment period. It is concluded that 2,2′,5′-trihydroxychalcone has the potential to serve as a protective agent for some debilitating diseases.     

Patterns of diversity and adaptation in Glomeromycota from three prairie grasslands

Arbuscular mycorrhizal (AM) fungi are widespread root symbionts that often improve the fitness of their plant hosts. We tested whether local adaptation in mycorrhizal symbioses would shape the community structure of these root symbionts in a way that maximizes their symbiotic functioning. We grew a native prairie grass (Andropogon gerardii) with all possible combinations of soils and AM fungal inocula from three different prairies that varied in soil characteristics and disturbance history (two native prairie remnants and one recently restored). We identified the AM fungi colonizing A. gerardii roots using PCR amplification and cloning of the small subunit rRNA gene. We observed 13 operational taxonomic units (OTUs) belonging to six genera in three families. Taxonomic richness was higher in the restored than the native prairies with one member of the Gigaspora dominating the roots of plants grown with inocula from native prairies. Inoculum source and the soil environment influenced the composition of AM fungi that colonized plant roots. Correspondingly, host plants and AM fungi responded significantly to the soil–inoculum combinations such that home fungi often had the highest fitness and provided the greatest benefit to A. gerardii. Similar patterns were observed within the soil–inoculum combinations originating from two native prairies, where five sequence types of a single Gigaspora OTU were virtually the only root colonizers. Our results indicate that indigenous assemblages of AM fungi were adapted to the local soil environment and that this process occurred both at a community scale and at the scale of fungal sequence types within a dominant OTU.     

Pseudomonas fluorescens NZI7 repels grazing by C. elegans,a natural predator

The bacteriovorous nematode Caenorhabditis elegans has been used to investigate many aspects of animal biology, including interactions with pathogenic bacteria. However, studies examining C. elegans interactions with bacteria isolated from environments in which it is found naturally are relatively scarce. C. elegans is frequently associated with cultivation of the edible mushroom Agaricus bisporus, and has been reported to increase the severity of bacterial blotch of mushrooms, a disease caused by bacteria from the Pseudomonas fluorescens complex. We observed that pseudomonads isolated from mushroom farms showed differential resistance to nematode predation. Under nutrient poor conditions, in which most pseudomonads were consumed, the mushroom pathogenic isolate P. fluorescens NZI7 was able to repel C. elegans without causing nematode death. A draft genome sequence of NZI7 showed it to be related to the biocontrol strain P. protegens Pf-5. To identify the genetic basis of nematode repellence in NZI7, we developed a grid-based screen for mutants that lacked the ability to repel C. elegans. The mutants isolated in this screen included strains with insertions in the global regulator GacS and in a previously undescribed GacS-regulated gene cluster, ‘EDB'' (‘edible''). Our results suggest that the product of the EDB cluster is a poorly diffusible or cell-associated factor that acts together with other features of NZI7 to provide a novel mechanism to deter nematode grazing. As nematodes interact with NZI7 colonies before being repelled, the EDB factor may enable NZI7 to come into contact with and be disseminated by C. elegans without being subject to intensive predation.