BaySTDetect: detecting unusual temporal patterns in small area data via Bayesian model choice

Space-time modeling of small area data is often used in epidemiology for mapping chronic disease rates and by government statistical agencies for producing local estimates of, for example, unemployment or crime rates. Although there is typically a general temporal trend, which affects all areas similarly, abrupt changes may occur in a particular area, e.g. due to emergence of localized predictors/risk factor(s) or impact of a new policy. Detection of areas with "unusual" temporal patterns is therefore important as a screening tool for further investigations. In this paper, we propose BaySTDetect, a novel detection method for short-time series of small area data using Bayesian model choice between two competing space-time models. The first model is a multiplicative decomposition of the area effect and the temporal effect, assuming one common temporal pattern across the whole study region. The second model estimates the time trends independently for each area. For each area, the posterior probability of belonging to the common trend model is calculated, which is then used to classify the local time trend as unusual or not. Crucial to any detection method, we provide a Bayesian estimate of the false discovery rate (FDR). A comprehensive simulation study has demonstrated the consistent good performance of BaySTDetect in detecting various realistic departure patterns in addition to estimating well the FDR. The proposed method is applied retrospectively to mortality data on chronic obstructive pulmonary disease (COPD) in England and Wales between 1990 and 1997 (a) to test a hypothesis that a government policy increased the diagnosis of COPD and (b) to perform surveillance. While results showed no evidence supporting the hypothesis regarding the policy, an identified unusual district (Tower Hamlets in inner London) was later recognized to have higher than national rates of hospital readmission and mortality due to COPD by the National Health Service, which initiated various local enhanced services to tackle the problem. Our method would have led to an early detection of this local health issue.     

Clinical Utility of a Coronary Heart Disease Risk Prediction Gene Score in UK Healthy Middle Aged Men and in the Pakistani Population

BackgroundNumerous risk prediction algorithms based on conventional risk factors for Coronary Heart Disease (CHD) are available but provide only modest discrimination. The inclusion of genetic information may improve clinical utility.MethodsWe tested the use of two gene scores (GS) in the prospective second Northwick Park Heart Study (NPHSII) of 2775 healthy UK men (284 cases), and Pakistani case-control studies from Islamabad/Rawalpindi (321 cases/228 controls) and Lahore (414 cases/219 controls). The 19-SNP GS included SNPs in loci identified by GWAS and candidate gene studies, while the 13-SNP GS only included SNPs in loci identified by the CARDIoGRAMplusC4D consortium.ResultsIn NPHSII, the mean of both gene scores was higher in those who went on to develop CHD over 13.5 years of follow-up (19-SNP p=0.01, 13-SNP p=7x10^-3). In combination with the Framingham algorithm the GSs appeared to show improvement in discrimination (increase in area under the ROC curve, 19-SNP p=0.48, 13-SNP p=0.82) and risk classification (net reclassification improvement (NRI), 19-SNP p=0.28, 13-SNP p=0.42) compared to the Framingham algorithm alone, but these were not statistically significant. When considering only individuals who moved up a risk category with inclusion of the GS, the improvement in risk classification was statistically significant (19-SNP p=0.01, 13-SNP p=0.04). In the Pakistani samples, risk allele frequencies were significantly lower compared to NPHSII for 13/19 SNPs. In the Islamabad study, the mean gene score was higher in cases than controls only for the 13-SNP GS (2.24 v 2.34, p=0.04). There was no association with CHD and either score in the Lahore study.ConclusionThe performance of both GSs showed potential clinical utility in European men but much less utility in subjects from Pakistan, suggesting that a different set of risk loci or SNPs may be required for risk prediction in the South Asian population.     

Assessment of Zoonotic Transmission of Giardia and Cryptosporidium between Cattle and Humans in Rural Villages in Bangladesh

Giardia and Cryptosporidium are important causes of diarrhoea in Bangladesh. The high prevalence of both parasites in humans and cattle in rural Bangladesh and the common use of water ponds by village inhabitants and their animals suggest a potential for zoonotic transmission. Direct transmission of Giardia and Cryptosporidium between cattle and their handlers and indirect transmission through water ponds was investigated. Faecal/stool samples were collected from 623 calves and 125 calf handlers in a cross-sectional survey. In two villages, water samples were collected monthly from water ponds and faecal/stool samples were collected monthly from inhabitants and their cattle. Giardia cysts and Cryptosporidium oocysts were detected in water samples and in faecal/stool samples and positive samples were genotyped, to determine their human or animal origin. The prevalence of Giardia and Cryptosporidium in calves was 22% and 5% respectively. In calf handlers, the prevalence of Giardia and Cryptosporidium was 11.2% and 3.2% respectively. Both in the cross-sectional survey and in the longitudinal study in the villages, G. duodenalis assemblage E was most prevalent in calves, while in humans assemblage AII, BIII and BIV were found. In cattle, Cryptosporidium parvum, C. bovis and C. andersoni were identified, but no Cryptosporidium sequences were obtained from humans. Giardia and Cryptosporidium were detected in 14/24 and 12/24 water samples respectively. G. duodenalis assemblage E and BIV (-like), as well as C. andersoni and C. hominis were identified. Although the presence of Giardia and Cryptosporidium in both water ponds suggests that water-borne transmission of Giardia and Cryptosporidium is possible, the genotyping results indicate that there is no significant direct or indirect (water-borne) transmission of Giardia between cattle and people in this area of rural Bangladesh. No conclusions could be drawn for Cryptosporidium, because of the low number of sequences that were obtained from human and water samples.     

Investigation of immunomodulatory and anti-inflammatory effects of eriodictyol through its cellular anti-oxidant activity

Many studies have been performed to assess the potential utility of natural products as immunomodulatory agents to enhance host responses against infection or to ameliorate immune-based pathologies. To determine whether eriodictyol has immunomodulatory effects and clarify which types of immune effector cells are stimulated in vitro, we investigated the stimulatory effect of eriodictyol on spleen cells isolated from BALB/c mice. Eriodictyol significantly stimulated splenocyte proliferation. However, only B lymphocytes (not T lymphocytes) could be stimulated by eriodictyol in a dose-related manner. Studies assessing potential effect of eriodictyol on innate immunity reported that eriodictyol enhanced significantly the killing activity of natural killer (NK) cells, T lymphocytes, and macrophages. We also demonstrated that eriodictyol inhibited nitric oxide (NO) production and lysosomal enzyme activity in murine peritoneal macrophages cultured ex-vivo, suggesting a potential anti-inflammatory effect in situ. Eriodictyol revealed also a cellular anti-oxidant activity in splenocytes and macrophages. Furthermore, eriodictyol increased catalase activity in spleen cells. From this data, it can be concluded that eriodictyol exhibited an immunomodulatory effect that could be ascribed in part to a cytoprotective effect related to its anti-oxidant activity.     

Imaging- and Flow Cytometry-based Analysis of Cell Position and the Cell Cycle in 3D Melanoma Spheroids

Three-dimensional (3D) tumor spheroids are utilized in cancer research as a more accurate model of the in vivo tumor microenvironment, compared to traditional two-dimensional (2D) cell culture. The spheroid model is able to mimic the effects of cell-cell interaction, hypoxia and nutrient deprivation, and drug penetration. One characteristic of this model is the development of a necrotic core, surrounded by a ring of G1 arrested cells, with proliferating cells on the outer layers of the spheroid. Of interest in the cancer field is how different regions of the spheroid respond to drug therapies as well as genetic or environmental manipulation. We describe here the use of the fluorescence ubiquitination cell cycle indicator (FUCCI) system along with cytometry and image analysis using commercial software to characterize the cell cycle status of cells with respect to their position inside melanoma spheroids. These methods may be used to track changes in cell cycle status, gene/protein expression or cell viability in different sub-regions of tumor spheroids over time and under different conditions.