Study Protocol - Accurate assessment of kidney function in Indigenous Australians: aims and methods of the eGFR Study

Background: There is an overwhelming burden of cardiovascular disease, type 2 diabetes and chronic kidney disease among Indigenous Australians. In this high risk population, it is vital that we are able to measure accurately kidney function. Glomerular filtration rate is the best overall marker of kidney function. However, differences in body build and body composition between Indigenous and non-Indigenous Australians suggest that creatinine-based estimates of glomerular filtration rate derived for European populations may not be appropriate for Indigenous Australians. The burden of kidney disease is borne disproportionately by Indigenous Australians in central and northern Australia, and there is significant heterogeneity in body build and composition within and amongst these groups. This heterogeneity might differentially affect the accuracy of estimation of glomerular filtration rate between different Indigenous groups. By assessing kidney function in Indigenous Australians from Northern Queensland, Northern Territory and Western Australia, we aim to determine a validated and practical measure of glomerular filtration rate suitable for use in all Indigenous Australians

Boolean Dynamics with Random Couplings

This paper reviews a class of generic dissipative dynamical systems called N-K models. In these models, the dynamics of N elements, defined as Boolean variables, develop step by step, clocked by a discrete time variable. Each of the N Boolean elements at a given time is given a value which depends upon K elements in the previous time step. We review the work of many authors on the behavior of the models, looking particularly at the structure and lengths of their cycles, the sizes of their basins of attraction, and the flow of information through the systems. In the limit of infinite N, there is a phase transition between a chaotic and an ordered phase, with a critical phase in between. We argue that the behavior of this system depends significantly on the topology of the network connections. If the elements are placed upon a lattice with dimension d, the system shows correlations related to the standard percolation or directed percolation phase transition on such a lattice. On the other hand, a very different behavior is seen in the Kauffman net in which all spins are equally likely to be coupled to a given spin. In this situation, coupling loops are mostly suppressed, and the behavior of the system is much more like that of a mean field theory. We also describe possible applications of the models to, for example, genetic networks, cell differentiation, evolution, democracy in social systems and neural networks.Comment: 69 pages, 16 figures, Submitted to Springer Applied Mathematical Sciences Serie

Bilirubin concentration is positively associated with haemoglobin concentration and inversely associated with albumin to creatinine ratio among Indigenous Australians: eGFR Study

This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 12 month embargo from date of publication (August 2017) in accordance with the publisher’s archiving policyLow serum bilirubin concentrations are reported to be strongly associated with cardio-metabolic disease, but this relationship has not been reported among Indigenous Australian people who are known to be at high risk for diabetes and chronic kidney disease (CKD). Hypothesis: serum bilirubin will be negatively associated with markers of chronic disease, including CKD and anaemia among Indigenous Australians. Method: A cross-sectional analysis of 594 adult Aboriginal and Torres Strait Islander (TSI) people in good health or with diabetes and markers of CKD. Measures included urine albumin: creatinine ratio (ACR), estimated glomerular filtration rate (eGFR), haemoglobin (Hb) and glycated haemoglobin (HbA1c). Diabetes was defined by medical history, medications or HbA1c ≥ 6.5% or ≥ 48 mmol/mol. Anaemia was defined as Hb < 130 g/L or < 120 g/L in males and females respectively. A multivariate regression analysis examining factors independently associated with log-bilirubin was performed. Results: Participants mean (SD) age was 45.1 (14.5) years, and included 62.5% females, 71.7% Aboriginal, 41.1% with diabetes, 16.7% with anaemia, 41% with ACR > 3 mg/mmol and 18.2% with eGFR < 60 mL/min/1.73m2. Median bilirubin concentration was lower in females than males (6 v 8 μmol/L, p < 0.001) and in Aboriginal than TSI participants (6 v 9.5 μmol/L, p < 0.001). Six factors explained 35% of the variance of log-bilirubin; Hb and cholesterol (both positively related) and ACR, triglycerides, Aboriginal ethnicity and female gender (all inversely related). Conclusion: Serum bilirubin concentrations were positively associated with Hb and total cholesterol, and inversely associated with ACR. Further research to determine reasons explaining lower bilirubin concentrations among Aboriginal compared with TSI participants are needed

Impact of Chromatin Structures on DNA Processing for Genomic Analyses

Chromatin has an impact on recombination, repair, replication, and evolution of DNA. Here we report that chromatin structure also affects laboratory DNA manipulation in ways that distort the results of chromatin immunoprecipitation (ChIP) experiments. We initially discovered this effect at the Saccharomyces cerevisiae HMR locus, where we found that silenced chromatin was refractory to shearing, relative to euchromatin. Using input samples from ChIP-Seq studies, we detected a similar bias throughout the heterochromatic portions of the yeast genome. We also observed significant chromatin-related effects at telomeres, protein binding sites, and genes, reflected in the variation of input-Seq coverage. Experimental tests of candidate regions showed that chromatin influenced shearing at some loci, and that chromatin could also lead to enriched or depleted DNA levels in prepared samples, independently of shearing effects. Our results suggested that assays relying on immunoprecipitation of chromatin will be biased by intrinsic differences between regions packaged into different chromatin structures - biases which have been largely ignored to date. These results established the pervasiveness of this bias genome-wide, and suggested that this bias can be used to detect differences in chromatin structures across the genome

Novel Data Fusion Method and Exploration of Multiple Information Sources for Transcription Factor Target Gene Prediction

Background. Revealing protein-DNA interactions is a key problem in understanding transcriptional regulation at mechanistic level. Computational methods have an important role in predicting transcription factor target gene genomewide. Multiple data fusion provides a natural way to improve transcription factor target gene predictions because sequence specificities alone are not sufficient to accurately predict transcription factor binding sites. Methods. Here we develop a new data fusion method to combine multiple genome-level data sources and study the extent to which DNA duplex stability and nucleosome positioning information, either alone or in combination with other data sources, can improve the prediction of transcription factor target gene. Results. Results on a carefully constructed test set of verified binding sites in mouse genome demonstrate that our new multiple data fusion method can reduce false positive rates, and that DNA duplex stability and nucleosome occupation data can improve the accuracy of transcription factor target gene predictions, especially when combined with other genome-level data sources. Cross-validation and other randomization tests confirm the predictive performance of our method. Our results also show that nonredundant data sources provide the most efficient data fusion.Peer reviewe

Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling

Cellular signal transduction generally involves cascades of post-translational protein modifications that rapidly catalyze changes in protein-DNA interactions and gene expression. High-throughput measurements are improving our ability to study each of these stages individually, but do not capture the connections between them. Here we present an approach for building a network of physical links among these data that can be used to prioritize targets for pharmacological intervention. Our method recovers the critical missing links between proteomic and transcriptional data by relating changes in chromatin accessibility to changes in expression and then uses these links to connect proteomic and transcriptome data. We applied our approach to integrate epigenomic, phosphoproteomic and transcriptome changes induced by the variant III mutation of the epidermal growth factor receptor (EGFRvIII) in a cell line model of glioblastoma multiforme (GBM). To test the relevance of the network, we used small molecules to target highly connected nodes implicated by the network model that were not detected by the experimental data in isolation and we found that a large fraction of these agents alter cell viability. Among these are two compounds, ICG-001, targeting CREB binding protein (CREBBP), and PKF118–310, targeting β-catenin (CTNNB1), which have not been tested previously for effectiveness against GBM. At the level of transcriptional regulation, we used chromatin immunoprecipitation sequencing (ChIP-Seq) to experimentally determine the genome-wide binding locations of p300, a transcriptional co-regulator highly connected in the network. Analysis of p300 target genes suggested its role in tumorigenesis. We propose that this general method, in which experimental measurements are used as constraints for building regulatory networks from the interactome while taking into account noise and missing data, should be applicable to a wide range of high-throughput datasets.National Science Foundation (U.S.) (DB1-0821391)National Institutes of Health (U.S.) (Grant U54-CA112967)National Institutes of Health (U.S.) (Grant R01-GM089903)National Institutes of Health (U.S.) (P30-ES002109

Invasion genetics of a freshwater mussel (Dreissena rostriformis bugensis) in eastern Europe: High gene flow and multiple introductions

In recent years, the quagga mussel, Dreissena rostriformis bugensis, native to the Dnieper and Bug Limans of the northern Black Sea, has been dispersed by human activities across the basin, throughout much of the Volga River system, and to the Laurentian Great Lakes. We used six published microsatellite markers to survey populations throughout its native and introduced range to identify relationships among potential source populations and introduced ones. Mussels from 12 sites in Eurasia, including the central Caspian Sea and one in North America (Lake Erie), were sampled. Field surveys in the Volga River basin suggested that the species first colonized the middle reach of the river near Kubyshev Reservoir, and thereafter spread both upstream and downstream. Evidence of considerable gene flow among populations was observed and genetic diversity was consistent with a larger, metapopulation that has not experienced bottlenecks or founder effects. We propose that high gene flow, possibly due to multiple invasions, has facilitated establishment of quagga mussel populations in the Volga River system. The Caspian Sea population (D. rostriformis rostriformis (= distincta)) was genetically more distinct than other populations, a finding that may be related to habitat differences. The geographical pattern of genetic divergence is not characteristic of isolation-by-distance but, rather, of long-distance dispersal, most likely mediated by commercial ships\u27 ballast water transfer. © 2005 Nature Publishing Group All rights reserved