Markov counting models for correlated binary responses

We propose a class of continuous-time Markov counting processes for analyzing correlated binary data and establish a correspondence between these models and sums of exchangeable Bernoulli random variables. Our approach generalizes many previous models for correlated outcomes, admits easily interpretable parameterizations, allows different cluster sizes, and incorporates ascertainment bias in a natural way. We demonstrate several new models for dependent outcomes and provide algorithms for computing maximum likelihood estimates. We show how to incorporate cluster-specific covariates in a regression setting and demonstrate improved fits to well-known datasets from familial disease epidemiology and developmental toxicology

A Spatial Simulation Approach to Account for Protein Structure When Identifying Non-Random Somatic Mutations

Background: Current research suggests that a small set of "driver" mutations are responsible for tumorigenesis while a larger body of "passenger" mutations occurs in the tumor but does not progress the disease. Due to recent pharmacological successes in treating cancers caused by driver mutations, a variety of of methodologies that attempt to identify such mutations have been developed. Based on the hypothesis that driver mutations tend to cluster in key regions of the protein, the development of cluster identification algorithms has become critical. Results: We have developed a novel methodology, SpacePAC (Spatial Protein Amino acid Clustering), that identifies mutational clustering by considering the protein tertiary structure directly in 3D space. By combining the mutational data in the Catalogue of Somatic Mutations in Cancer (COSMIC) and the spatial information in the Protein Data Bank (PDB), SpacePAC is able to identify novel mutation clusters in many proteins such as FGFR3 and CHRM2. In addition, SpacePAC is better able to localize the most significant mutational hotspots as demonstrated in the cases of BRAF and ALK. The R package is available on Bioconductor at: http://www.bioconductor.org/packages/release/bioc/html/SpacePAC.html Conclusion: SpacePAC adds a valuable tool to the identification of mutational clusters while considering protein tertiary structureComment: 16 pages, 8 Figures, 4 Table

Natural ventilation reduces high TB transmission risk in traditional homes in rural KwaZulu-Natal, South Africa

Background: Transmission of drug susceptible and drug resistant TB occurs in health care facilities, and community and households settings, particularly in highly prevalent TB and HIV areas. There is a paucity of data regarding factors that may affect TB transmission risk in household settings. We evaluated air exchange and the impact of natural ventilation on estimated TB transmission risk in traditional Zulu homes in rural South Africa. Methods: We utilized a carbon dioxide decay technique to measure ventilation in air changes per hour (ACH). We evaluated predominant home types to determine factors affecting ACH and used the Wells-Riley equation to estimate TB transmission risk. Results: Two hundred eighteen ventilation measurements were taken in 24 traditional homes. All had low ventilation at baseline when windows were closed (mean ACH = 3, SD = 3.0), with estimated TB transmission risk of 55.4% over a ten hour period of exposure to an infectious TB patient. There was significant improvement with opening windows and door, reaching a mean ACH of 20 (SD = 13.1, p < 0.0001) resulting in significant decrease in estimated TB transmission risk to 9.6% (p < 0.0001). Multivariate analysis identified factors predicting ACH, including ventilation conditions (windows/doors open) and window to volume ratio. Expanding ventilation increased the odds of achieving ≥12 ACH by 60-fold. Conclusions: There is high estimated risk of TB transmission in traditional homes of infectious TB patients in rural South Africa. Improving natural ventilation may decrease household TB transmission risk and, combined with other strategies, may enhance TB control efforts

Survival from XDR-TB Is Associated with Modifiable Clinical Characteristics in Rural South Africa

Drug-resistant tuberculosis (TB) is a major threat to global public health. Patients with extensively drug-resistant TB (XDR-TB), particularly those with HIV-coinfection, experience high and accelerated mortality with limited available interventions. To determine modifiable factors associated with survival, we evaluated XDR-TB patients from a community-based hospital in rural South Africa where a large number of XDR-TB cases were first detected.A retrospective case control study was conducted of XDR-TB patients diagnosed from 2005-2008. Survivors, those alive at 180 days from diagnostic sputum collection date, were compared with controls who died within 180 days. Clinical, laboratory and microbiological correlates of survival were assessed in 69 survivors (median survival 565 days [IQR 384-774] and 73 non-survivors (median survival 34 days [IQR 18-90]). Among 129 HIV+ patients, multivariate analyses of modifiable factors demonstrated that negative AFB smear (AOR 8.4, CI 1.84-38.21), a lower laboratory index of routine laboratory findings (AOR 0.48, CI 0.22-1.02), CD4>200 cells/mm(3) (AOR 11.53, 1.1-119.32), and receipt of antiretroviral therapy (AOR 20.9, CI 1.16-376.83) were independently associated with survival from XDR-TB.Survival from XDR-TB with HIV-coinfection is associated with less advanced stages of both diseases at time of diagnosis, absence of laboratory markers indicative of multiorgan dysfunction, and provision of antiretroviral therapy. Survival can be increased by addressing these modifiable risk factors through policy changes and improved clinical management. Health planners and clinicians should develop programmes focusing on earlier case finding and integration of HIV and drug-resistant TB diagnostic, therapeutic, and preventive activities

Mutation of A DNA Repair Enzyme Causes Lupus in Mice

A replication study of a previous genome-wide association study (GWAS) suggested that a SNP linked to the POLβ gene is associated with systemic lupus erythematosus (SLE). This SNP is correlated with decreased expression of Pol β, a key enzyme in the base excision repair (BER) pathway. To determine whether decreased Pol β activity results in SLE, we constructed a mouse model of POLβ that encodes an enzyme with slow DNA polymerase activity. We show that mice expressing this hypomorphic POLβ allele develop an autoimmune pathology that strongly resembles SLE. Of note, the mutant mice have shorter immunoglobulin heavy-chain junctions and somatic hypermutation is dramatically increased. These results demonstrate that decreased Pol β activity during the generation of immune diversity leads to lupus-like disease in mice, and suggest that decreased expression of Pol β in humans is an underlying cause of SLE