Disease mapping using Bayesian hierarchical models

description and analysis of geographically indexed health data with respect to demographic, environmental, behavioural, socioeconomic, genetic, and infectious risk factors (Elliott andWartenberg 2004). Disease maps can be useful for estimating relative risk; ecological analyses, incorporating area and/or individual-level covariates; or cluster analyses (Lawson 2009). As aggregated data are often more readily available, one common method of mapping disease is to aggregate the counts of disease at some geographical areal level, and present them as choropleth maps (Devesa et al. 1999; Population Health Division 2006). Therefore, this chapter will focus exclusively on methods appropriate for areal data...

Treatment failure in celiac disease due to coexistent exocrine pancreatic insufficiency

A 17-year-old white adolescent had a history of chronic diarrhea, delayed puberty, and growth failure. Investigations excluded cystic fibrosis, Shwachman syndrome, and endocrine causes of growth failure. Severe steatorrhea was diagnosed from fecal fat studies, and a jejunal suction biopsy showed total villus atrophy, consistent with a diagnosis of celiac diseases. Following introduction of a gluten-free diet, his appetite and growth improved, but he continued to have abdominal discomfort and loose offensive bowel motions. One year later, severe steatorrhea was present. A repeat jejunal biopsy showed partial recovery of villus architecture. Serum immunoreactive trypsinogen level was low, which was highly suggestive of exocrine pancreatic failure. Results of quantitative pancreatic stimulation test confirmed the presence of primary pancreatic insufficiency. After introduction of oral pancreatic enzyme supplements with meals, his gastrointestinal symptoms resolved and growth velocity accelerated. Previously, primary pancreatic insufficiency has only been described in elderly patients with long-standing untreated celiac disease. This case, however, emphasizes that pancreatic failure can occur with celiac disease at any age. Determination of a serum immunoreactive trypsinogen level should be considered a useful screening tool for pancreatic insufficiency in patients with celiac disease who have not responded to a gluten-free diet.

Comparison of decision tree, support vector machines, and Bayesian network approaches for classification of falls in Parkinson’s disease

Being able to accurately predict the risk of falling is crucial in patients with Parkinson’s dis- ease (PD). This is due to the unfavorable effect of falls, which can lower the quality of life as well as directly impact on survival. Three methods considered for predicting falls are decision trees (DT), Bayesian networks (BN), and support vector machines (SVM). Data on a 1-year prospective study conducted at IHBI, Australia, for 51 people with PD are used. Data processing are conducted using rpart and e1071 packages in R for DT and SVM, con- secutively; and Bayes Server 5.5 for the BN. The results show that BN and SVM produce consistently higher accuracy over the 12 months evaluation time points (average sensitivity and specificity > 92%) than DT (average sensitivity 88%, average specificity 72%). DT is prone to imbalanced data so needs to adjust for the misclassification cost. However, DT provides a straightforward, interpretable result and thus is appealing for helping to identify important items related to falls and to generate fallers’ profiles.

Urinary tract infection of mice to model human disease: Practicalities, implications and limitations

Urinary tract infections (UTIs) are among the most common bacterial infections in humans. Murine models of human UTI are vital experimental tools that have helped to elucidate UTI pathogenesis and advance knowledge of potential treatment and infection prevention strategies. Fundamentally, several variables are inherent in different murine models, and understanding the limitations of these variables provides an opportunity to understand how models may be best applied to research aimed at mimicking human disease. In this review, we discuss variables inherent in murine UTI model studies and how these affect model usage, data analysis and data interpretation. We examine recent studies that have elucidated UTI host–pathogen interactions from the perspective of gene expression, and review new studies of biofilm and UTI preventative approaches. We also consider potential standards for variables inherent in murine UTI models and discuss how these might expand the utility of models for mimicking human disease and uncovering new aspects of pathogenesis

Characterisation of the efficacy of endodontic medications using a three-dimensional fluorescent tooth model: An ex vivo study

The purpose of this study was to establish a three-dimensional fluorescent tooth model to investigate bacterial viability against intra-canal medicaments across the thickness and surface of root dentine. Dental microbial biofilms (Enterococcus faecalis and Streptococcus mutans) were established on the external root surface and bacterial kill was monitored over time against intra-canal medicament (Ca(OH)2 ) using fluorescent microscopy in conjunction with BacLight SYTO9 and propidium iodide stains. An Olympus digital camera fitted to SZX16 fluorescent microscope captured images of bacterial cells in biofilms on the external root surface. Viability of biofilm was measured by calculating the total pixel area of green (viable bacteria) and red (non-viable bacteria) for each image using ImageJ® software. All data generated were assessed for normality and then analysed using a Mann-Whitney t-test. The viability of S. mutans biofilm following Ca(OH)2 treatment showed a significant decline compared with the untreated group (P = 0.0418). No significant difference was seen for E. faecalis biofilm between the Ca(OH)2 and untreated groups indicating Ca(OH)2 medicament is ineffective against E. faecalis biofilm. This novel three-dimensional fluorescent biofilm model provides a new clinically relevant tool for testing of medicaments against dental biofilms.

The association between perception of health during pregnancy and the risk of cardiovascular disease: A prospective study

There is some evidence that self-rated perceptions of health are predictive of objective health outcomes, including cardiovascular disease, and mortality. The objective of this study was to examine the prospective association between perceptions of health during pregnancy and cardiovascular risk factors of mothers 21 years after the pregnancy. Data used were from the Mater University Study of Pregnancy (MUSP), a community-based prospective birth cohort study begun in Brisbane, Australia, in 1981. Logistic regression analyses were conducted. Data were available for 3692 women. Women who perceived themselves as not having a straight forward pregnancy had twice the odds (adjusted OR 2.0, 95% CI 1.1–3.8) of being diagnosed with heart disease 21 years after the pregnancy when compared with women with a straight forward pregnancy (event rate of 5.2 versus 2.6%). Women who experienced complications (other than serious pregnancy complications) during their pregnancy were also at 30% increased odds (adjusted OR 1.3, 95% CI 1.0–1.6) of having hypertension 21years later (event rate of 25.7 versus 20%). As a whole, our study sug- gests that pregnant women who perceived that they had complications and did not have a straight forward preg- nancy were likely to experience poorer cardiovascular outcomes 21years after that pregnancy.

Genetic analysis for a shared biological basis between migraine and coronary artery disease

Objective: To apply genetic analysis of genome-wide association data to study the extent and nature of a shared biological basis between migraine and coronary artery disease (CAD). Methods: Four separate methods for cross-phenotype genetic analysis were applied on data from 2 large-scale genome-wide association studies of migraine (19,981 cases, 56,667 controls) and CAD (21,076 cases, 63,014 controls). The first 2 methods quantified the extent of overlapping risk variants and assessed the load of CAD risk loci in migraineurs. Genomic regions of shared risk were then identified by analysis of covariance patterns between the 2 phenotypes and by querying known genome-wide significant loci. Results: We found a significant overlap of genetic risk loci for migraine and CAD. When stratified by migraine subtype, this was limited to migraine without aura, and the overlap was protective in that patients with migraine had a lower load of CAD risk alleles than controls. Genes indicated by 16 shared risk loci point to mechanisms with potential roles in migraine pathogenesis and CAD, including endothelial dysfunction (PHACTR1) and insulin homeostasis (GIP). Conclusions: The results suggest that shared biological processes contribute to risk of migraine and CAD, but surprisingly this commonality is restricted to migraine without aura and the impact is in opposite directions. Understanding the mechanisms underlying these processes and their opposite relationship to migraine and CAD may improve our understanding of both disorders.

Genetic burden associated with varying degrees of disease severity in endometriosis

Endometriosis is primarily characterized by the presence of tissue resembling endometrium outside the uterine cavity and is usually diagnosed by laparoscopy. The most commonly used classification of disease, the revised American Fertility Society (rAFS) system to grade endometriosis into different stages based on disease severity (I to IV), has been questioned as it does not correlate well with underlying symptoms, posing issues in diagnosis and choice of treatment. Using two independent European genome-wide association (GWA) datasets and top-level classification of the endometriosis cases based on rAFS [minimal or mild (Stage A) and moderate-to-severe (Stage B) disease], we previously showed that Stage B endometriosis has greater contribution of common genetic variation to its aetiology than Stage A disease. Herein, we extend our previous analysis to four endometriosis stages [minimal (Stage I), mild (Stage II), moderate (Stage III) and severe (Stage IV) disease] based on the rAFS classification system and compared the genetic burden across stages. Our results indicate that genetic burden increases from minimal to severe endometriosis. For the minimal disease, genetic factors may contribute to a lesser extent than other disease categories. Mild and moderate endometriosis appeared genetically similar, making it difficult to tease them apart. Consistent with our previous reports, moderate and severe endometriosis showed greater genetic burden than minimal or mild disease. Overall, our results provide new insights into the genetic architecture of endometriosis and further investigation in larger samples may help to understand better the aetiology of varying degrees of endometriosis, enabling improved diagnostic and treatment modalities.

Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis

Common diseases such as endometriosis (ED), Alzheimer's disease (AD) and multiple sclerosis (MS) account for a significant proportion of the health care burden in many countries. Genome-wide association studies (GWASs) for these diseases have identified a number of individual genetic variants contributing to the risk of those diseases. However, the effect size for most variants is small and collectively the known variants explain only a small proportion of the estimated heritability. We used a linear mixed model to fit all single nucleotide polymorphisms (SNPs) simultaneously, and estimated genetic variances on the liability scale using SNPs from GWASs in unrelated individuals for these three diseases. For each of the three diseases, case and control samples were not all genotyped in the same laboratory. We demonstrate that a careful analysis can obtain robust estimates, but also that insufficient quality control (QC) of SNPs can lead to spurious results and that too stringent QC is likely to remove real genetic signals. Our estimates show that common SNPs on commercially available genotyping chips capture significant variation contributing to liability for all three diseases. The estimated proportion of total variation tagged by all SNPs was 0.26 (SE 0.04) for ED, 0.24 (SE 0.03) for AD and 0.30 (SE 0.03) for MS. Further, we partitioned the genetic variance explained into five categories by a minor allele frequency (MAF), by chromosomes and gene annotation. We provide strong evidence that a substantial proportion of variation in liability is explained by common SNPs, and thereby give insights into the genetic architecture of the diseases.

Identification of seven loci affecting mean telomere length and their association with disease

Interindividual variation in mean leukocyte telomere length (LTL) is associated with cancer and several age-associated diseases. We report here a genome-wide meta-analysis of 37,684 individuals with replication of selected variants in an additional 10,739 individuals. We identified seven loci, including five new loci, associated with mean LTL (P < 5 x 10(-8)). Five of the loci contain candidate genes (TERC, TERT, NAF1, OBFC1 and RTEL1) that are known to be involved in telomere biology. Lead SNPs at two loci (TERC and TERT) associate with several cancers and other diseases, including idiopathic pulmonary fibrosis. Moreover, a genetic risk score analysis combining lead variants at all 7 loci in 22,233 coronary artery disease cases and 64,762 controls showed an association of the alleles associated with shorter LTL with increased risk of coronary artery disease (21% (95% confidence interval, 5-35%) per standard deviation in LTL, P = 0.014). Our findings support a causal role of telomere-length variation in some age-related diseases.

Using genomic data to make indirect (and unauthorized) estimates of disease risk

The number of genetic factors associated with common human traits and disease is increasing rapidly, and the general public is utilizing affordable, direct-to-consumer genetic tests. The results of these tests are often in the public domain. A combination of factors has increased the potential for the indirect estimation of an individual's risk for a particular trait. Here we explain the basic principals underlying risk estimation which allowed us to test the ability to make an indirect risk estimation from genetic data by imputing Dr. James Watson's redacted apolipoprotein E gene (APOE) information. The principles underlying risk prediction from genetic data have been well known and applied for many decades, however, the recent increase in genomic knowledge, and advances in mathematical and statistical techniques and computational power, make it relatively easy to make an accurate but indirect estimation of risk. There is a current hazard for indirect risk estimation that is relevant not only to the subject but also to individuals related to the subject; this risk will likely increase as more detailed genomic data and better computational tools become available.

Loci affecting gamma-glutamyl transferase in adults and adolescents show age x SNP interaction and cardiometabolic disease associations

Serum gamma-glutamyl transferase (GGT) activity is a marker of liver disease which is also prospectively associated with the risk of all-cause mortality, cardiovascular disease, type 2 diabetes and cancers. We have discovered novel loci affecting GGT in a genome-wide association study (rs1497406 in an intergenic region of chromosome 1, P = 3.9 x 10(-8); rs944002 in C14orf73 on chromosome 14, P = 4.7 x 10(-13); rs340005 in RORA on chromosome 15, P = 2.4 x 10(-8)), and a highly significant heterogeneity between adult and adolescent results at the GGT1 locus on chromosome 22 (maximum P(HET) = 5.6 x 10(-12) at rs6519520). Pathway analysis of significant and suggestive single-nucleotide polymorphism associations showed significant overlap between genes affecting GGT and those affecting common metabolic and inflammatory diseases, and identified the hepatic nuclear factor (HNF) family as controllers of a network of genes affecting GGT. Our results reinforce the disease associations of GGT and demonstrate that control by the GGT1 locus varies with age.

Shift in disease burden from communicable to non-communicable diseases: Aiming to achieve Universal Health Coverage in Nepal

A major barrier to accessing healthcare services is spending, and the extended time that non-communicable diseases require treatment for means that many people around the world do not have proper access to care. Saval Khanal from Sankalpa Foundation, Nepal, Lennert Veerman and Samantha Hollingworth from the University of Queensland and Lisa Nissen from Queensland University of Technology lay out the results of their study and establish a method to forecast medicine use in Nepal.

The importance of modelling heterogeneity in complex disease: application to NIMH Schizophrenia Genetics Initiative data

As for other complex diseases, linkage analyses of schizophrenia (SZ) have produced evidence for numerous chromosomal regions, with inconsistent results reported across studies. The presence of locus heterogeneity appears likely and may reduce the power of linkage analyses if homogeneity is assumed. In addition, when multiple heterogeneous datasets are pooled, inter-sample variation in the proportion of linked families (alpha) may diminish the power of the pooled sample to detect susceptibility loci, in spite of the larger sample size obtained. We compare the significance of linkage findings obtained using allele-sharing LOD scores (LOD(exp))-which assume homogeneity-and heterogeneity LOD scores (HLOD) in European American and African American NIMH SZ families. We also pool these two samples and evaluate the relative power of the LOD(exp) and two different heterogeneity statistics. One of these (HLOD-P) estimates the heterogeneity parameter alpha only in aggregate data, while the second (HLOD-S) determines alpha separately for each sample. In separate and combined data, we show consistently improved performance of HLOD scores over LOD(exp). Notably, genome-wide significant evidence for linkage is obtained at chromosome 10p in the European American sample using a recessive HLOD score. When the two samples are combined, linkage at the 10p locus also achieves genome-wide significance under HLOD-S, but not HLOD-P. Using HLOD-S, improved evidence for linkage was also obtained for a previously reported region on chromosome 15q. In linkage analyses of complex disease, power may be maximised by routinely modelling locus heterogeneity within individual datasets, even when multiple datasets are combined to form larger samples.

Assessment of the severity of Ebola virus disease in Sierra Leone in 2014–2015

The current Ebola virus disease (EVD) epidemic in West Africa is unprecedented in scale, and Sierra Leone is the most severely affected country. The case fatality risk (CFR) and hospitalization fatality risk (HFR) were used to characterize the severity of infections in confirmed and probable EVD cases in Sierra Leone. Proportional hazards regression models were used to investigate factors associated with the risk of death in EVD cases. In total, there were 17 318 EVD cases reported in Sierra Leone from 23 May 2014 to 31 January 2015. Of the probable and confirmed EVD cases with a reported final outcome, a total of 2536 deaths and 886 recoveries were reported. CFR and HFR estimates were 74·2% [95% credibility interval (CrI) 72·6–75·5] and 68·9% (95% CrI 66·2–71·6), respectively. Risks of death were higher in the youngest (0–4 years) and oldest (≥60 years) age groups, and in the calendar month of October 2014. Sex and occupational status did not significantly affect the mortality of EVD. The CFR and HFR estimates of EVD were very high in Sierra Leone.