Disease prevention versus data privacy : using landcover maps to inform spatial epidemic models

The availability of epidemiological data in the early stages of an outbreak of an infectious disease is vital for modelers to make accurate predictions regarding the likely spread of disease and preferred intervention strategies. However, in some countries, the necessary demographic data are only available at an aggregate scale. We investigated the ability of models of livestock infectious diseases to predict epidemic spread and obtain optimal control policies in the event of imperfect, aggregated data. Taking a geographic information approach, we used land cover data to predict UK farm locations and investigated the influence of using these synthetic location data sets upon epidemiological predictions in the event of an outbreak of foot-and-mouth disease. When broadly classified land cover data were used to create synthetic farm locations, model predictions deviated significantly from those simulated on true data. However, when more resolved subclass land use data were used, moderate to highly accurate predictions of epidemic size, duration and optimal vaccination and ring culling strategies were obtained. This suggests that a geographic information approach may be useful where individual farm-level data are not available, to allow predictive analyses to be carried out regarding the likely spread of disease. This method can also be used for contingency planning in collaboration with policy makers to determine preferred control strategies in the event of a future outbreak of infectious disease in livestock

Rapid Visualisation of Microarray Copy Number Data for the Detection of Structural Variations Linked to a Disease Phenotype

Whilst the majority of inherited diseases have been found to be caused by single base substitutions, small insertions or deletions (<1Kb), a significant proportion of genetic variability is due to copy number variation (CNV). The possible role of CNV in monogenic and complex diseases has recently attracted considerable interest. However, until the development of whole genome, oligonucleotide micro-arrays, designed specifically to detect the presence of copy number variation, it was not easy to screen an individual for the presence of unknown deletions or duplications with sizes below the level of sensitivity of optical microscopy (3–5 Mb). Now that currently available oligonucleotide micro-arrays have in excess of a million probes, the problem of copy number analysis has moved from one of data production to that of data analysis. We have developed CNViewer, to identify copy number variation that co-segregates with a disease phenotype in small nuclear families, from genome-wide oligonucleotide micro-array data. This freely available program should constitute a useful addition to the diagnostic armamentarium of clinical geneticists

Robust diagnostic genetic testing using solution capture enrichment and a novel variant-filtering interface.

Targeted hybridization enrichment prior to next-generation sequencing is a widespread method for characterizing sequence variation in a research setting, and is being adopted by diagnostic laboratories. However, the number of variants identified can overwhelm clinical laboratories with strict time constraints, the final interpretation of likely pathogenicity being a particular bottleneck. To address this, we have developed an approach in which, after automatic variant calling on a standard unix pipeline, subsequent variant filtering is performed interactively, using AgileExomeFilter and AgilePindelFilter (http://dna.leeds.ac.uk/agile), tools designed for clinical scientists with standard desktop computers. To demonstrate the method's diagnostic efficacy, we tested 128 patients using (1) a targeted capture of 36 cancer-predisposing genes or (2) whole-exome capture for diagnosis of the genetically heterogeneous disorder primary ciliary dyskinesia (PCD). In the cancer cohort, complete concordance with previous diagnostic data was achieved across 793 variant genotypes. A high yield (42%) was also achieved for exome-based PCD diagnosis, underscoring the scalability of our method. Simple adjustments to the variant filtering parameters further allowed the identification of a homozygous truncating mutation in a presumptive new PCD gene, DNAH8. These tools should allow diagnostic laboratories to expand their testing portfolios flexibly, using a standard set of reagents and techniques

Developing Hollow-Channel Gold Nanoflowers as Trimodal Intracellular Nanoprobes

Gold nanoparticles-enabled intracellular surface-enhanced Raman spectroscopy (SERS) provides a sensitive and promising technique for single cell analysis. Compared with spherical gold nanoparticles, gold nanoflowers, i.e., flower-shaped gold nanostructures, can produce a stronger SERS signal. Current exploration of gold nanoflowers for intracellular SERS has been considerably limited by the difficulties in preparation, as well as background signal and cytotoxicity arising from the surfactant capping layer. Recently, we have developed a facile and surfactant-free method for fabricating hollow-channel gold nanoflowers (HAuNFs) with great single-particle SERS activity. In this paper, we investigate the cellular uptake and cytotoxicity of our HAuNFs using a RAW 264.7 macrophage cell line, and have observed effective cellular internalization and low cytotoxicity. We have further engineered our HAuNFs into SERS-active tags, and demonstrated the functionality of the obtained tags as trimodal nanoprobes for dark-field and fluorescence microscopy imaging, together with intracellular SERS

A mechanistic spatio-temporal framework for modelling individual-to-individual transmission—With an application to the 2014-2015 West Africa Ebola outbreak

In recent years there has been growing availability of individual-level spatio-temporal disease data, particularly due to the use of modern communicating devices with GPS tracking functionality. These detailed data have been proven useful for inferring disease transmission to a more refined level than previously. However, there remains a lack of statistically sound frameworks to model the underlying transmission dynamic in a mechanistic manner. Such a development is particularly crucial for enabling a general epidemic predictive framework at the individual level. In this paper we propose a new statistical framework for mechanistically modelling individual-to-individual disease transmission in a landscape with heterogeneous population density. Our methodology is first tested using simulated datasets, validating our inferential machinery. The methodology is subsequently applied to data that describes a regional Ebola outbreak in Western Africa (2014-2015). Our results show that the methods are able to obtain estimates of key epidemiological parameters that are broadly consistent with the literature, while revealing a significantly shorter distance of transmission. More importantly, in contrast to existing approaches, we are able to perform a more general model prediction that takes into account the susceptible population. Finally, our results show that, given reasonable scenarios, the framework can be an effective surrogate for susceptible-explicit individual models which are often computationally challenging

HIF-driven SF3B1 induces KHK-C to enforce fructolysis and heart disease.

Fructose is a major component of dietary sugar and its overconsumption exacerbates key pathological features of metabolic syndrome. The central fructose-metabolising enzyme is ketohexokinase (KHK), which exists in two isoforms: KHK-A and KHK-C, generated through mutually exclusive alternative splicing of KHK pre-mRNAs. KHK-C displays superior affinity for fructose compared with KHK-A and is produced primarily in the liver, thus restricting fructose metabolism almost exclusively to this organ. Here we show that myocardial hypoxia actuates fructose metabolism in human and mouse models of pathological cardiac hypertrophy through hypoxia-inducible factor 1α (HIF1α) activation of SF3B1 and SF3B1-mediated splice switching of KHK-A to KHK-C. Heart-specific depletion of SF3B1 or genetic ablation of Khk, but not Khk-A alone, in mice, suppresses pathological stress-induced fructose metabolism, growth and contractile dysfunction, thus defining signalling components and molecular underpinnings of a fructose metabolism regulatory system crucial for pathological growth

Mutations in GPAA1, Encoding a GPI Transamidase Complex Protein, Cause Developmental Delay, Epilepsy, Cerebellar Atrophy, and Osteopenia.

Approximately one in every 200 mammalian proteins is anchored to the cell membrane through a glycosylphosphatidylinositol (GPI) anchor. These proteins play important roles notably in neurological development and function. To date, more than 20 genes have been implicated in the biogenesis of GPI-anchored proteins. GPAA1 (glycosylphosphatidylinositol anchor attachment 1) is an essential component of the transamidase complex along with PIGK, PIGS, PIGT, and PIGU (phosphatidylinositol-glycan biosynthesis classes K, S, T, and U, respectively). This complex orchestrates the attachment of the GPI anchor to the C terminus of precursor proteins in the endoplasmic reticulum. Here, we report bi-allelic mutations in GPAA1 in ten individuals from five families. Using whole-exome sequencing, we identified two frameshift mutations (c.981_993del [p.Gln327Hisfs∗102] and c.920delG [p.Gly307Alafs∗11]), one intronic splicing mutation (c.1164+5C>T), and six missense mutations (c.152C>T [p.Ser51Leu], c.160_161delinsAA [p.Ala54Asn], c.527G>C [p.Trp176Ser], c.869T>C [p.Leu290Pro], c.872T>C [p.Leu291Pro], and c.1165G>C [p.Ala389Pro]). Most individuals presented with global developmental delay, hypotonia, early-onset seizures, cerebellar atrophy, and osteopenia. The splicing mutation was found to decrease GPAA1 mRNA. Moreover, flow-cytometry analysis of five available individual samples showed that several GPI-anchored proteins had decreased cell-surface abundance in leukocytes (FLAER, CD16, and CD59) or fibroblasts (CD73 and CD109). Transduction of fibroblasts with a lentivirus encoding the wild-type protein partially rescued the deficiency of GPI-anchored proteins. These findings highlight the role of the transamidase complex in the development and function of the cerebellum and the skeletal system

Latent variables and structural equation models for longitudinal relationships: an illustration in nutritional epidemiology

<p>Abstract</p> <p>Background</p> <p>The use of structural equation modeling and latent variables remains uncommon in epidemiology despite its potential usefulness. The latter was illustrated by studying cross-sectional and longitudinal relationships between eating behavior and adiposity, using four different indicators of fat mass.</p> <p>Methods</p> <p>Using data from a longitudinal community-based study, we fitted structural equation models including two latent variables (respectively baseline adiposity and adiposity change after 2 years of follow-up), each being defined, by the four following anthropometric measurement (respectively by their changes): body mass index, waist circumference, skinfold thickness and percent body fat. Latent adiposity variables were hypothesized to depend on a cognitive restraint score, calculated from answers to an eating-behavior questionnaire (TFEQ-18), either cross-sectionally or longitudinally.</p> <p>Results</p> <p>We found that high baseline adiposity was associated with a 2-year increase of the cognitive restraint score and no convincing relationship between baseline cognitive restraint and 2-year adiposity change could be established.</p> <p>Conclusions</p> <p>The latent variable modeling approach enabled presentation of synthetic results rather than separate regression models and detailed analysis of the causal effects of interest. In the general population, restrained eating appears to be an adaptive response of subjects prone to gaining weight more than as a risk factor for fat-mass increase.</p

Non-homologous DNA end joining in normal and cancer cells and its dependence on break structures

DNA double-strand breaks (DSBs) are a serious threat to the cell, for if not or miss-repaired, they can lead to chromosomal aberration, mutation and cancer. DSBs in human cells are repaired via non-homologous DNA end joining (NHEJ) and homologous recombination repair pathways. In the former process, the structure of DNA termini plays an important role, as does the genetic constitution of the cells, through being different in normal and pathological cells. In order to investigate the dependence of NHEJ on DSB structure in normal and cancer cells, we used linearized plasmids with various, complementary or non-complementary, single-stranded or blunt DNA termini, as well as whole-cell extract isolated from normal human lymphocytes, chronic myeloid leukemia K562 cells and lung cancer A549 cells. We observed a pronounced variability in the efficacy of NHEJ reaction depending on the type of ends. Plasmids with complementary and blunt termini were more efficiently repaired than the substrate with 3' protruding single-strand ends. The hierarchy of the effectiveness of NHEJ was on average, from the most effective to the least, A549/ normal lymphocytes/ K562. Our results suggest that the genetic constitution of the cells together with the substrate terminal structure may contribute to the efficacy of the NHEJ reaction. This should be taken into account on considering its applicability in cancer chemo- or radiotherapy by pharmacologically modulating NHEJ cellular responses