Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1–3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region4, 5, 6, 7, 8, 9, 10, 11. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods—recursive partitioning and regression...

Polymorphism in codon 17 of the CTLA-4 gene (+49 A/G) is not associated with susceptibility to rheumatoid arthritis in British Caucasians

The role of the CTLA-4 antigen in the development of autoimmune diseases is well documented, with several autoimmune disorders showing association or linkage with the CTLA-4 locus. Its role in the aetiology of rheumatoid arthritis (RA) however, remains unclear, as the functional studies of the B7-CTLA-4 pathway in mouse models of RA and genetic studies in humans have given contrasting results. We have studied the single nucleotide polymorphism at position +49 (A/G) of the CTLA-4 gene, in a cohort of 421 RA cases and 452 healthy controls from the UK. Despite the high statistical power to detect even a weak susceptibility effect, no significant association was found. We also analysed the distribution of the allele and genotype frequencies with respect to the presence of the shared epitope (a known RA susceptibility factor) and found no statistically significant differences. We conclude that, although the importance of the B7-CTLA-4 interaction in the development of RA can not be excluded, the CTLA-4 gene is unlikely to be a predisposing factor to this disease.

Interethnic studies of TNF polymorphisms confirm the likely presence of a second MHC susceptibility locus in ankylosing spondylitis

The objective of this study was to investigate TNF promoter region polymorphisms for association with susceptibility to ankylosing spondylitis (AS). The TNF -238 and -308 polymorphisms were genotyped in 306 English AS cases and 204 ethnically matched healthy B27-positive controls, and 96 southern German AS cases, 58 B27-positive and 251 B27-negative ethnically matched controls. Additionally, the TNF -376 polymorphism was genotyped in the southern German cases and controls. In the southern German AS patients a significant reduction in TNF -308.2 alleles was seen, compared with B27 positive controls (odds ratio 0.4, P= 0.03, 95% confidence interval 0.2-0.9), but no difference in allele frequencies was observed at TNF -238. Significant association between AS and both TNF -238 and TNF -308 was excluded in the English cases. These results confirm previous observations in the southern German population of association between TNF promoter region polymorphisms and AS, but the lack of association in the English population suggests that these polymorphisms themselves are unlikely to be directly involved. More likely, a second, non-HLA-B, MHC locus is involved in susceptibility to AS in these two populations.

Susceptibility to ankylosing spondylitis

Sir The association between HLA‐B27 (B27) and ankylosing spondylitis (AS) has been known for 25 yr. Familial aggregation in AS is well established, and first‐degree relatives of AS patients have been shown to be at increased risk of developing the disease. The recurrence risk in siblings of AS patients is quite uncertain, previous studies have variously reported recurrence risks between 6.9 and 27% [1, 2]. Accurate knowledge of the sibling recurrence risk is important both to advise families of the likelihood of disease recurrence, and in genetic statistical analyses utilizing Risch's recurrence risk ratio [3]. This study was designed to determine the risk of developing AS in siblings and to determine the role of the major histocompatibility complex in familial recurrence of AS....

Polymorphisms of the CYP2D6 gene increase susceptibility to ankylosing spondylitis

Ankylosing spondylitis (AS) is a common and highly familial rheumatic disorder. The sibling recurrence risk ratio for the disease is 63 and heritability assessed in twins > 90%. Although MHC genes, including HLA-B27, contribute only 20-50% of the genetic risk for the disease, no non-MHC gene has yet been convincingly demonstrated to influence either susceptibility to the disease or its phenotypic expression. Previous linkage and association studies have suggested the presence of a susceptibility gene for AS close to, or within, the cytochrome P450 2D6 gene (CYP2D6, debrisoquine hydroxylase) located at chromosome 22q13.1. We performed a linkage study of chromosome 22 in 200 families with AS affected sibling-pairs. Association of alleles of the CYP2D6 gene was examined by both case-control and within-family means. For case-control studies, 617 unrelated individuals with AS (361 probands from sibling-pair and parent-case trio families and 256 unrelated non-familial sporadic cases) and 402 healthy ethnically matched controls were employed. For within-family association studies, 361 families including 161 parent-case trios and 200 affected sibling-pair families were employed. Homozygosity for poor metabolizer alleles was found to be associated with AS. Heterozygosity for the most frequent poor metabolizer allele (CYP2D6*4) was not associated with increased susceptibility to AS. Significant within-family association of CYP2D6*4 alleles and AS was demonstrated. Weak linkage was also demonstrated between CYP2D6 and AS. We postulate that altered metabolism of a natural toxin or antigen by the CYP2D6 gene may increase susceptibility to AS.

Modelling of the evaporation of a droplet suspended in a binary atmosphere

The process of spray drying is applied in a number of contexts. One such application is the production of a synthetic rock used for storage of nuclear waste. To establish a framework for a model of the spray drying process for this application, we here develop a model describing evaporation from droplets of pure water, such that the model may be extended to account for the presence of colloid within the droplet. We develop a spherically-symmetric model and formulate continuum equations describing mass, momentum, and energy balance in both the liquid and gas phases from first principles. We establish appropriate boundary conditions at the surface of the droplet, including a generalised Clapeyron equation that accurately describes the temperature at the surface of the droplet. To account for experiment design, we introduce a simplified platinum ball and wire model into the system using a thin wire problem. The resulting system of equations is transformed in order to simplify a finite volume solution scheme. The results from numerical simulation are compared with data collected for validation, and the sensitivity of the model to variations in key parameters, and to the use of Clausius–Clapeyron and generalised Clapeyron equations, is investigated. Good agreement is found between the model and experimental data, despite the simplicity of the platinum phase model.

Risk analysis of prostate cancer in PRACTICAL, a multinational consortium, using 25 known prostate cancer susceptibility loci

Background Genome-wide association studies have identified multiple genetic variants associated with prostate cancer risk which explain a substantial proportion of familial relative risk. These variants can be used to stratify individuals by their risk of prostate cancer. Methods We genotyped 25 prostate cancer susceptibility loci in 40,414 individuals and derived a polygenic risk score (PRS).We estimated empirical odds ratios (OR) for prostate cancer associated with different risk strata defined by PRS and derived agespecific absolute risks of developing prostate cancer by PRS stratum and family history. Results The prostate cancer risk for men in the top 1% of the PRS distribution was 30.6 (95% CI, 16.4-57.3) fold compared with men in the bottom 1%, and 4.2 (95% CI, 3.2-5.5) fold compared with the median risk. The absolute risk of prostate cancer by age of 85 years was 65.8% for a man with family history in the top 1% of the PRS distribution, compared with 3.7% for a man in the bottom 1%. The PRS was only weakly correlated with serum PSA level (correlation = 0.09). Conclusions Risk profiling can identify men at substantially increased or reduced risk of prostate cancer. The effect size, measured by OR per unit PRS, was higher in men at younger ages and in men with family history of prostate cancer. Incorporating additional newly identified loci into a PRS should improve the predictive value of risk profiles. Impact:We demonstrate that the risk profiling based on SNPs can identify men at substantially increased or reduced risk that could have useful implications for targeted prevention and screening programs.

Spatio-temporal modelling of cancer data in Queensland using Bayesian methods

Cancer is the leading contributor to the disease burden in Australia. This thesis develops and applies Bayesian hierarchical models to facilitate an investigation of the spatial and temporal associations for cancer diagnosis and survival among Queenslanders. The key objectives are to document and quantify the importance of spatial inequalities, explore factors influencing these inequalities, and investigate how spatial inequalities change over time. Existing Bayesian hierarchical models are refined, new models and methods developed, and tangible benefits obtained for cancer patients in Queensland. The versatility of using Bayesian models in cancer control are clearly demonstrated through these detailed and comprehensive analyses.

Atheroma: Is calcium important or not? A modelling study of stress within the atheromatous fibrous cap in relation to position and size of calcium deposits

Atheromatous plaque rupture h the cause of the majority of strokes and heart attacks in the developed world. The role of calcium deposits and their contribution to plaque vulnerability are controversial. Some studies have suggested that calcified plaque tends to be more stable whereas others have suggested the opposite. This study uses a finite element model to evaluate the effect of calcium deposits on the stress within the fibrous cap by varying their location and size. Plaque fibrous cap, lipid pool and calcification were modeled as hyperelastic, Isotropic, (nearly) incompressible materials with different properties for large deformation analysis by assigning time-dependent pressure loading on the lumen wall. The stress and strain contours were illustrated for each condition for comparison. Von Mises stress only increases up to 1.5% when varying the location of calcification in the lipid pool distant to the fibrous cap. Calcification in the fibrous cap leads to a 43% increase of Von Mises stress when compared with that in the lipid pool. An increase of 100% of calcification area leads to a 15% stress increase in the fibrous cap. Calcification in the lipid pool does not increase fibrous cap stress when it is distant to the fibrous cap, whilst large areas of calcification close to or in the fibrous cap may lead to a high stress concentration within the fibrous cap, which may cause plaque rupture. This study highlights the application of a computational model on a simulation of clinical problems, and it may provide insights into the mechanism of plaque rupture.

Statistical modelling and power analysis for detecting trends in total suspended sediment loads

The export of sediments from coastal catchments can have detrimental impacts on estuaries and near shore reef ecosystems such as the Great Barrier Reef. Catchment management approaches aimed at reducing sediment loads require monitoring to evaluate their effectiveness in reducing loads over time. However, load estimation is not a trivial task due to the complex behaviour of constituents in natural streams, the variability of water flows and often a limited amount of data. Regression is commonly used for load estimation and provides a fundamental tool for trend estimation by standardising the other time specific covariates such as flow. This study investigates whether load estimates and resultant power to detect trends can be enhanced by (i) modelling the error structure so that temporal correlation can be better quantified, (ii) making use of predictive variables, and (iii) by identifying an efficient and feasible sampling strategy that may be used to reduce sampling error. To achieve this, we propose a new regression model that includes an innovative compounding errors model structure and uses two additional predictive variables (average discounted flow and turbidity). By combining this modelling approach with a new, regularly optimised, sampling strategy, which adds uniformity to the event sampling strategy, the predictive power was increased to 90%. Using the enhanced regression model proposed here, it was possible to detect a trend of 20% over 20 years. This result is in stark contrast to previous conclusions presented in the literature. (C) 2014 Elsevier B.V. All rights reserved.

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region.

Numerical modelling of particle deposition in idealized porous channels

This project provides a steppingstone to comprehend the mechanisms that govern particulate fouling in metal foam heat exchangers. The method is based on development of an advanced Computational Fluid Dynamics model in addition to performing analytical validation. This novel method allows an engineer to better optimize heat exchanger designs, thereby mitigating fouling, reducing energy consumption caused by fouling, economize capital expenditure on heat exchanger maintenance, and reduce operation downtime. The robust model leads to the establishment of an alternative heat exchanger configuration that has lower pressure drop and particulate deposition propensity.

Modelling growth rate of Penaeus monodon Fabricius in intensively managed ponds: effects of temperature, pond age and stocking density

Records of shrimp growth and water quality made during 12 crops from each of 48 ponds, over a period of 6.5 years, were provided by a Queensland, Australia, commercial shrimp farm, These data were analysed with a new growth model derived from the Gompertz model. The results indicate that water temperature, mortality and pond age significantly affect growth rates. After 180 days, shrimp reach 34 g at constant 30 degrees C, but only 15 g after the same amount of time at 20 degrees C. Mortality, through thinning the density of shrimp in the ponds, increased the growth rate, but the effect is small. With continual production, growth rates at first remained steady, then appeared to decrease for the sixth and seventh crop, after which they have increased steadily with each crop. It appears that conservative pond management, together with a gradual improvement in husbandry techniques, particularly feed management, brought about this change. This has encouraging implications for the long-term sustainability of the farming methods used. The growth model can be used to predict productivity, and hence, profitability, of new aquaculture locations or new production strategies.

Agent-based modelling of worker interactions and related impacts on workplace dynamics

This study uses agent based modelling to simulate the worker interactions within a workplace and to investigate how the interactions can have impact on the workplace dynamics. Two new models (Bounded Confidence with Bias model and Relative Agreement with Bias model) are built based on the theoretical foundation of two existing models. A new factor, namely bias, is added into the new models which raises several issues to be studied.

Predicting health programme participation: A gravity‐based, hierarchical modelling approach

Statistical analyses of health program participation seek to address a number of objectives compatible with the evaluation of demand for current resources. In this spirit, a spatial hierarchical model is developed for disentangling patterns in participation at the small area level, as a function of population-based demand and additional variation. For the former, a constrained gravity model is proposed to quantify factors associated with spatial choice and account for competition effects, for programs delivered by multiple clinics. The implications of gravity model misspecification within a mixed effects framework are also explored. The proposed model is applied to participation data from a no-fee mammography program in Brisbane, Australia. Attention is paid to the interpretation of various model outputs and their relevance for public health policy.