When and how to treat pulmonary non-tuberculous mycobacterial diseases

Nontuberculous mycobacteria are ubiquitous environmental organisms that have been recognised as a cause of pulmonary infection for over 50 years. Traditionally patients have had underlying risk factors for development of disease; however the proportion of apparently immunocompetent patients involved appears to be rising. Not all patients culture-positive for mycobacteria will have progressive disease, making the diagnosis difficult, though criteria to aid in this process are available. The two main forms of disease are cavitary disease (usually involving the upper lobes) and fibronodular bronchiectasis (predominantly middle and lingular lobes). For patients with disease, combination antibiotic therapy for 12-24 months is generally required for successful treatment, and this may be accompanied by drug intolerances and side effects. Published success rates range from 30-82%. As the progression of disease is variable, for some patients, attention to pulmonary hygiene and underlying diseases without immediate antimycobacterial therapy may be more appropriate. Surgery can be a useful adjunct, though is associated with risks. Randomised controlled trials in well described patients would provide stronger evidence-based data to guide therapy of NTM lung diseases, and thus are much needed.

Bayesian methodology for genetics of complex diseases

Genetic research of complex diseases is a challenging, but exciting, area of research. The early development of the research was limited, however, until the completion of the Human Genome and HapMap projects, along with the reduction in the cost of genotyping, which paves the way for understanding the genetic composition of complex diseases. In this thesis, we focus on the statistical methods for two aspects of genetic research: phenotype definition for diseases with complex etiology and methods for identifying potentially associated Single Nucleotide Polymorphisms (SNPs) and SNP-SNP interactions. With regard to phenotype definition for diseases with complex etiology, we firstly investigated the effects of different statistical phenotyping approaches on the subsequent analysis. In light of the findings, and the difficulties in validating the estimated phenotype, we proposed two different methods for reconciling phenotypes of different models using Bayesian model averaging as a coherent mechanism for accounting for model uncertainty. In the second part of the thesis, the focus is turned to the methods for identifying associated SNPs and SNP interactions. We review the use of Bayesian logistic regression with variable selection for SNP identification and extended the model for detecting the interaction effects for population based case-control studies. In this part of study, we also develop a machine learning algorithm to cope with the large scale data analysis, namely modified Logic Regression with Genetic Program (MLR-GEP), which is then compared with the Bayesian model, Random Forests and other variants of logic regression.

Exploring health behaviour determinants of ageing Australians with chronic diseases

Background: Chronic disease presents overwhelming challenges to elderly patients, their families, health care providers and the health care system. The aim of this study was to explore a theoretical model for effective management of chronic diseases, especially type 2 diabetes mellitus and/or cardiovascular disease. The assumed theoretical model considered the connections between physical function, mental health, social support and health behaviours. The study effort was to improve the quality of life for people with chronic diseases, especially type 2 diabetes and/or cardiovascular disease and to reduce health costs. Methods: A cross-sectional post questionnaire survey was conducted in early 2009 from a randomised sample of Australians aged 50 to 80 years. A total of 732 subjects were eligible for analysis. Firstly, factors influencing respondents‘ quality of life were investigated through bivariate and multivariate regression analysis. Secondly, the Theory of Planned Behaviour (TPB) model for regular physical activity, healthy eating and medication adherence behaviours was tested for all relevant respondents using regression analysis. Thirdly, TPB variable differences between respondents who have diabetes and/or cardiovascular disease and those without these diseases were compared. Finally, the TPB model for three behaviours including regular physical activity, healthy eating and medication adherence were tested in respondents with diabetes and/or cardiovascular diseases using Structure Equation Modelling (SEM). Results: This was the first study combining the three behaviours using a TPB model, while testing the influence of extra variables on the TPB model in one study. The results of this study provided evidence that the ageing process was a cumulative effect of biological change, socio-economic environment and lifelong behaviours. Health behaviours, especially physical activity and healthy eating were important modifiable factors influencing respondents‘ quality of life. Since over 80% of the respondents had at least one chronic disease, it was important to consider supporting older people‘s chronic disease self-management skills such as healthy diet, regular physical activity and medication adherence to improve their quality of life. Direct measurement of the TPB model was helpful in understanding respondents‘ intention and behaviour toward physical activity, healthy eating and medication adherence. In respondents with diabetes and/or cardiovascular disease, the TPB model predicted different proportions of intention toward three different health behaviours with 39% intending to engage in physical activity, 49% intending to engage in healthy eating and 47% intending to comply with medication adherence. Perceived behavioural control, which was proven to be the same as self-efficacy in measurement in this study, played an important role in predicting intention towards the three health behaviours. Also social norms played a slightly more important role than attitude for physical activity and medication adherence, while attitude and social norms had similar effects on healthy eating in respondents with diabetes and/or cardiovascular disease. Both perceived behavioural control and intention directly predicted recent actual behaviours. Physical activity was more a volitional control behaviour than healthy eating and medication adherence. Step by step goal setting and motivation was more important for physical activity, while accessibility, resources and other social environmental factors were necessary for improving healthy eating and medication adherence. The extra variables of age, waist circumference, health related quality of life and depression indirectly influenced intention towards the three behaviours mainly mediated through attitude and perceived behavioural control. Depression was a serious health problem that reduced the three health behaviours‘ motivation, mediated through decreased self-efficacy and negative attitude. This research provided evidence that self-efficacy is similar to perceived behavioural control in the TPB model and intention is a proximal goal toward a particular behaviour. Combining four sources of information in the self-efficacy model with the TPB model would improve chronic disease patients‘ self management behaviour and reach an improved long-term treatment outcome. Conclusion: Health intervention programs that target chronic disease management should focus on patients‘ self-efficacy. A holistic approach which is patient-centred and involves a multidisciplinary collaboration strategy would be effective. Supporting the socio-economic environment and the mental/ emotional environment for older people needs to be considered within an integrated health care system.

Prevalence and risk factors of childhood allergic diseases in eight metropolitan cities in China: A multicenter study

Background Several studies conducted during the past two decades suggested increasing trend of childhood allergic diseases in China. However, few studies have provided detailed description of geographic variation and explored risk factors of these diseases. This study investigated the pattern and risk factors of asthma, allergic rhinitis and eczema in eight metropolitan cities in China. Methods We conducted a cross-sectional survey during November-December 2005 in eight metropolitan cities in China. A total of 23791 children aged 6-13 years participated in this survey. Questions from the standard questionnaire of the International Study of Asthma and Allergies in Children (ISAAC) were used to examine the pattern of current asthma, allergic rhinitis and eczema. Logistic regression analyses were performed to assess the risk factors for childhood allergies. Results The average prevalence of childhood asthma, allergic rhinitis and eczema across the eight cities was 3∙3% (95% Confidence interval (CI): 3∙1%, 3∙6%), 9∙8% (95% CI: 9∙4%, 10∙2%) and 5∙5% (95% CI: 5∙2%, 5∙8%), respectively. Factors related to lifestyle, mental health and socio-economic status were found to be associated with the prevalence of childhood allergies. These risk factors were unevenly distributed across cities and disproportionately affected the local prevalence. Conclusions There was apparent geographic variation of childhood allergies in China. Socio-environmental factors had strong impacts on the prevalence of childhood allergies; but these impacts differed across regions. Thus public health policies should specifically target at the local risk factors for each individual area.

A hybrid model for studying spatial aspects of infectious diseases

We consider a hybrid model, created by coupling a continuum and an agent-based model of infectious disease. The framework of the hybrid model provides a mechanism to study the spread of infection at both the individual and population levels. This approach captures the stochastic spatial heterogeneity at the individual level, which is directly related to deterministic population level properties. This facilitates the study of spatial aspects of the epidemic process. A spatial analysis, involving counting the number of infectious agents in equally sized bins, reveals when the spatial domain is nonhomogeneous.

Genetic polymorphisms in the human tissue kallikrein (KLK) locus and their implication in various malignant and non-malignant diseases

The Kallikrein (KLK) gene locus encodes a family of serine proteases and is the largest contiguous cluster of protease-encoding genes attributed an evolutionary age of 330 million years. The KLK locus has been implicated as a high susceptibility risk loci in numerous cancer studies through the last decade. The KLK3 gene already has established clinical relevance as a biomarker in prostate cancer prognosis through its encoded protein, prostate-specific antigen. Data mined through genome-wide association studies (GWAS) and next-generation sequencing point to many important candidate single nucleotide polymorphisms (SNPs) in KLK3 and other KLK genes. SNPs in the KLK locus have been found to be associated with several diseases including cancer, hypertension, cardiovascular disease and atopic dermatitis. Moreover, introducing a model incorporating SNPs to improve the efficiency of prostate-specific antigen in detecting malignant states of prostate cancer has been recently suggested. Establishing the functional relevance of these newly-discovered SNPs, and their interactions with each other, through in silico investigations followed by experimental validation, can accelerate the discovery of diagnostic and prognostic biomarkers. In this review, we discuss the various genetic association studies on the KLK loci identified either through candidate gene association studies or at the GWAS and post-GWAS front to aid researchers in streamlining their search for the most significant, relevant and therapeutically promising candidate KLK gene and/or SNP for future investigations.

Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010 : a systematic analysis for the Global Burden of Disease Study 2010

Background Non-fatal health outcomes from diseases and injuries are a crucial consideration in the promotion and monitoring of individual and population health. The Global Burden of Disease (GBD) studies done in 1990 and 2000 have been the only studies to quantify non-fatal health outcomes across an exhaustive set of disorders at the global and regional level. Neither effort quantified uncertainty in prevalence or years lived with disability (YLDs). Methods Of the 291 diseases and injuries in the GBD cause list, 289 cause disability. For 1160 sequelae of the 289 diseases and injuries, we undertook a systematic analysis of prevalence, incidence, remission, duration, and excess mortality. Sources included published studies, case notification, population-based cancer registries, other disease registries, antenatal clinic serosurveillance, hospital discharge data, ambulatory care data, household surveys, other surveys, and cohort studies. For most sequelae, we used a Bayesian meta-regression method, DisMod-MR, designed to address key limitations in descriptive epidemiological data, including missing data, inconsistency, and large methodological variation between data sources. For some disorders, we used natural history models, geospatial models, back-calculation models (models calculating incidence from population mortality rates and case fatality), or registration completeness models (models adjusting for incomplete registration with health-system access and other covariates). Disability weights for 220 unique health states were used to capture the severity of health loss. YLDs by cause at age, sex, country, and year levels were adjusted for comorbidity with simulation methods. We included uncertainty estimates at all stages of the analysis. Findings Global prevalence for all ages combined in 2010 across the 1160 sequelae ranged from fewer than one case per 1 million people to 350 000 cases per 1 million people. Prevalence and severity of health loss were weakly correlated (correlation coefficient −0·37). In 2010, there were 777 million YLDs from all causes, up from 583 million in 1990. The main contributors to global YLDs were mental and behavioural disorders, musculoskeletal disorders, and diabetes or endocrine diseases. The leading specific causes of YLDs were much the same in 2010 as they were in 1990: low back pain, major depressive disorder, iron-deficiency anaemia, neck pain, chronic obstructive pulmonary disease, anxiety disorders, migraine, diabetes, and falls. Age-specific prevalence of YLDs increased with age in all regions and has decreased slightly from 1990 to 2010. Regional patterns of the leading causes of YLDs were more similar compared with years of life lost due to premature mortality. Neglected tropical diseases, HIV/AIDS, tuberculosis, malaria, and anaemia were important causes of YLDs in sub-Saharan Africa. Interpretation Rates of YLDs per 100 000 people have remained largely constant over time but rise steadily with age. Population growth and ageing have increased YLD numbers and crude rates over the past two decades. Prevalences of the most common causes of YLDs, such as mental and behavioural disorders and musculoskeletal disorders, have not decreased. Health systems will need to address the needs of the rising numbers of individuals with a range of disorders that largely cause disability but not mortality. Quantification of the burden of non-fatal health outcomes will be crucial to understand how well health systems are responding to these challenges. Effective and affordable strategies to deal with this rising burden are an urgent priority for health systems in most parts of the world. Funding Bill & Melinda Gates Foundation.

Nanotechnology in the targeted drug delivery for bone diseases and bone regeneration

Nanotechnology is a vigorous research area and one of its important applications is in biomedical sciences. Among biomedical applications, targeted drug delivery is one of the most extensively studied subjects. Nanostructured particles and scaffolds have been widely studied for increasing treatment efficacy and specificity of present treatment approaches. Similarly, this technique has been used for treating bone diseases including bone regeneration. In this review, we have summarized and highlighted the recent advancement of nanostructured particles and scaffolds for the treatment of cancer bone metastasis, osteosarcoma, bone infections and inflammatory diseases, osteoarthritis, as well as for bone regeneration. Nanoparticles used to deliver deoxyribonucleic acid and ribonucleic acid molecules to specific bone sites for gene therapies are also included. The investigation of the implications of nanoparticles in bone diseases have just begun, and has already shown some promising potential. Further studies have to be conducted, aimed specifically at assessing targeted delivery and bioactive scaffolds to further improve their efficacy before they can be used clinically

Dancing Diseases : an applied theatre response to the challenge of conveying emotionally contradictory messages in HIV education

Health educators face an unusual challenge in relation to HIV: the need to convey two emotionally contradictory messages. On the one hand, there is currently no cure for HIV, which eventually leads to death (emotionally negative message). On the other hand, people with HIV can live long, healthy and productive lives (emotionally positive message). In developing countries where HIV prevalence is high, it is imperative that both messages are conveyed effectively. This article reports on a specific form, Dancing Diseases, implemented as one component of the Life Drama pilot study on Karkar Island, Papua New Guinea. Life Drama is an applied theatre and performance approach to HIV education. The article discusses Dancing Diseases as an example of applied theatre and performance practice, reflects on the participant group’s engagement with the form, and offers some ways in which the form could be refined and used in other health education contexts.

Development of an integrated metabolomic profiling approach for infectious diseases research

Metabolomic profiling offers direct insights into the chemical environment and metabolic pathway activities at sites of human disease. During infection, this environment may receive important contributions from both host and pathogen. Here we apply an untargeted metabolomics approach to identify compounds associated with an E. coli urinary tract infection population. Correlative and structural data from minimally processed samples were obtained using an optimized LC-MS platform capable of resolving ~2300 molecular features. Principal component analysis readily distinguished patient groups and multiple supervised chemometric analyses resolved robust metabolomic shifts between groups. These analyses revealed nine compounds whose provisional structures suggest candidate infection-associated endocrine, catabolic, and lipid pathways. Several of these metabolite signatures may derive from microbial processing of host metabolites. Overall, this study highlights the ability of metabolomic approaches to directly identify compounds encountered by, and produced from, bacterial pathogens within human hosts.