Estimation of Spatial Variation in Risk Using Matched Case‐control Data

A common problem in environmental epidemiology is to estimate spatial variation in disease risk after accounting for known risk factors. In this paper we consider this problem in the context of matched case‐control studies. We extend the generalised additive model approach of Kelsall and Diggle (1998) to studies in which each case has been individually matched to a set of controls. We discuss a method for fitting this model to data, apply the method to a matched study on perinatal death in the North West Thames region of England and explain why, if spatial variation is of particular scientific interest, matching is undesirable.     

DNA double strand break repair in human bladder cancer is error prone and involves microhomology-associated end-joining

In human cells DNA double strand breaks (DSBs) can be repaired by the non-homologous end-joining (NHEJ) pathway. In a background of NHEJ deficiency, DSBs with mismatched ends can be joined by an error-prone mechanism involving joining between regions of nucleotide microhomology. The majority of joins formed from a DSB with partially incompatible 3′ overhangs by cell-free extracts from human glioblastoma (MO59K) and urothelial (NHU) cell lines were accurate and produced by the overlap/fill-in of mismatched termini by NHEJ. However, repair of DSBs by extracts using tissue from four high-grade bladder carcinomas resulted in no accurate join formation. Junctions were formed by the non-random deletion of terminal nucleotides and showed a preference for annealing at a microhomology of 8 nt buried within the DNA substrate; this process was not dependent on functional Ku70, DNA-PK or XRCC4. Junctions were repaired in the same manner in MO59K extracts in which accurate NHEJ was inactivated by inhibition of Ku70 or DNA-PK_cs. These data indicate that bladder tumour extracts are unable to perform accurate NHEJ such that error-prone joining predominates. Therefore, in high-grade tumours mismatched DSBs are repaired by a highly mutagenic, microhomology-mediated, alternative end-joining pathway, a process that may contribute to genomic instability observed in bladder cancer.     

Genotypic characterization of Neisseria meningitidis using pyrosequencing™

Pyrosequencing involves the synthesis of single-stranded deoxyribonucleic acid leading to rapid and accurate analysis of nucleotide sequences. This article describes the development of typing assays for the characterization of Neisseria meningitidis using Pyrosequencing. This involved developing methods for the nucleotide sequence analysis of important variable regions contained on a major capsule gene and on outer membrane protein genes that are used for grouping, typing, and subtyping meningococci. To achieve this, primers were designed for amplification of three genes, siaD, porB, and porA from the four main serogroups B, C, Y, and W135. To facilitate throughput and reproducibility, the method was also automated. Data from 717 isolates have shown that Pyrosequencing can be used for the single nucleotide polymorphism and sequence-analysis characterization of meningococci.     

Point-source modelling using matched case-control data

We describe an extension to matched case-control studies of the parametric modelling framework developed by Diggle (1990) and Diggle and Rowlingson (1994) to investigate raised risk around putative sources of environmental pollution. We use a conditional likelihood approach for the family of risk functions considered in Diggle and Rowlingson (1994). We show that the likelihood surface that results from these models may be highly irregular, and provide a Bayesian analysis in which we investigate the posterior distribution using Markov chain Monte Carlo. An analysis of one-one matched data that were collected to investigate the relationship between respiratory disease and distance to roads in East London is presented.     

Biologically meaningful expression profiling across species using heterologous hybridization to a cDNA microarray

Background  

Unravelling the path from genotype to phenotype, as it is influenced by an organism's environment, is one of the central goals in biology. Gene expression profiling by means of microarrays has become very prominent in this endeavour, although resources exist only for relatively few model systems. As genomics has matured into a comparative research program, expression profiling now also provides a powerful tool for non-traditional model systems to elucidate the molecular basis of complex traits.     

The geographic distribution of Loa loa in Africa: results of large-scale implementation of the Rapid Assessment Procedure for Loiasis (RAPLOA)

Background

Loiasis is a major obstacle to ivermectin treatment for onchocerciasis control and lymphatic filariasis elimination in central Africa. In communities with a high level of loiasis endemicity, there is a significant risk of severe adverse reactions to ivermectin treatment. Information on the geographic distribution of loiasis in Africa is urgently needed but available information is limited. The African Programme for Onchocerciasis Control (APOC) undertook large scale mapping of loiasis in 11 potentially endemic countries using a rapid assessment procedure for loiasis (RAPLOA) that uses a simple questionnaire on the history of eye worm.

Methodology/Principal Findings

RAPLOA surveys were done in a spatial sample of 4798 villages covering an area of 2500×3000 km centred on the heartland of loiasis in Africa. The surveys showed high risk levels of loiasis in 10 countries where an estimated 14.4 million people live in high risk areas. There was a strong spatial correlation among RAPLOA data, and kriging was used to produce spatially smoothed contour maps of the interpolated prevalence of eye worm and the predictive probability that the prevalence exceeds 40%.

Conclusion/Significance

The contour map of eye worm prevalence provides the first global map of loiasis based on actual survey data. It shows a clear distribution with two zones of hyper endemicity, large areas that are free of loiasis and several borderline or intermediate zones. The surveys detected several previously unknown hyperendemic foci, clarified the distribution of loiasis in the Central African Republic and large parts of the Republic of Congo and the Democratic Republic of Congo for which hardly any information was available, and confirmed known loiasis foci. The new maps of the prevalence of eye worm and the probability that the prevalence exceeds the risk threshold of 40% provide critical information for ivermectin treatment programs among millions of people in Africa.