A hybrid approach to selecting susceptible single nucleotide polymorphisms for complex disease analysis

An increasingly popular and promising way for complex disease diagnosis is to employ artificial neural networks (ANN). Single nucleotide polymorphisms (SNP) data from individuals is used as the inputs of ANN to find out specific SNP patterns related to certain disease. Due to the large number of SNPs, it is crucial to select optimal SNP subset and their combinations so that the inputs of ANN can be reduced. With this observation in mind, a hybrid approach - a combination of genetic algorithms (GA) and ANN (called GANN) is used to automatically determine optimal SNP set and optimize the structure of ANN. The proposed GANN algorithm is evaluated by using both a synthetic dataset and a real SNP dataset of a complex disease.

Mapping the genotype-phenotype relationship in complex disease.

Computational methods to identify harmful variations in humans perform well for rare diseases such as Huntington's but not for common diseases like hypertension or diabetes. A modelling approach that takes protein context into account was illustrated to identify harmful variants involved in complex diseases.

Identification of novel therapeutics for complex diseases from genome-wide association data

Human genome sequencing has enabled the association of phenotypes with genetic loci, but our ability to effectively translate this data to the clinic has not kept pace. Over the past 60 years, pharmaceutical companies have successfully demonstrated the safety and efficacy of over 1,200 novel therapeutic drugs via costly clinical studies. While this process must continue, better use can be made of the existing valuable data. In silico tools such as candidate gene prediction systems allow rapid identification of disease genes by identifying the most probable candidate genes linked to genetic markers of the disease or phenotype under investigation. Integration of drug-target data with candidate gene prediction systems can identify novel phenotypes which may benefit from current therapeutics. Such a drug repositioning tool can save valuable time and money spent on preclinical studies and phase I clinical trials.

Mixed-initiative decision support for care planning based on clinical practice guidelines

Care Plan On-Line (CPOL) is an intranet based system that supports a “Coordinated Care” model for chronic/complex disease management. CPOL combines provision of solicited and unsolicited advice features based on integration of the electronic medical record (EMR) with its decision support logic. The objective is to support General Practitioners (GPs) in formulating a 12-month care plan of services such that: (a) the plan is proactive and patient-centered; (b) the GP is kept in awareness of project- and diseasespecific clinical practice guidelines; and (c) the support integrates with GP workflow in a natural fashion. A key feature of our approach is to blur the distinction of EMR and decision support by presenting guidelines in layers with the top-most being a problem-oriented presentation of patient status, progressing on through to patient-independent supporting evidence. In conjunction with a degree of automated inclusion of care planning services, the system demonstrates mixed user and software initiative. We describe the CPOL deployment setting, the challenges of guideline-based clinical decision support, our approach to guideline delivery, and the CPOL architecture.

New approaches to gene discovery with animal models of obesity and diabetes

DNA-based approaches to the discovery of genes contributing to the development of type 2 diabetes have not been very successful despite substantial investments of time and money. The multiple gene-gene and gene-environment interactions that influence the development of type 2 diabetes mean that DNA approaches are not the ideal tool for defining the etiology of this complex disease. Gene expression-based technologies may prove to be a more rewarding strategy to identify diabetes candidate genes. There are a number of RNA-based technologies available to identify genes that are differentially expressed in various tissues in type 2 diabetes. These include differential display polymerase chain reaction (ddPCR), suppression subtractive hybridization (SSH), and cDNA microarrays. The power of new technologies to detect differential gene expression is ideally suited to studies utilizing appropriate animal models of human disease. We have shown that the gene expression approach, in combination with an excellent animal model such as the Israeli sand rat (Psammomys obesus), can provide novel genes and pathways that may be important in the disease process and provide novel therapeutic approaches. This paper will describe a new gene discovery, beacon, a novel gene linked with energy intake. As the functional characterization of novel genes discovered in our laboratory using this approach continues, it is anticipated that we will soon be able to compile a definitive list of genes that are important in the development of obesity and type 2 diabetes.

Applications of aptamers in nanodelivery systems in cancer, eye and inflammatory diseases

Aptamers are an interesting class of molecules that have potential in many facets of human health. They are characterized by high affinity and specificity to their targets, are small in size, have similar properties to antibodies, but are made synthetically. All of these properties, among others, give aptamers the potential to diagnose, image and treat like no other molecules. By combining the unique properties of aptamers with the ever expanding field of nanotechnology and all it has to offer, we are entering a very promising new area of targeted nanodelivery treatments. These treatments have found success in the complex disease processes of cancer, eye and inflammatory diseases.

Prevention of childhood obesity

Childhood obesity is a complex disease with different genetic, metabolic, environmental and behavioural components that are interrelated and potentially confounding, thus making causal pathways difficult to define. Given the tracking of obesity and the associated risk factors, childhood is an important period for prevention. To date, evidence would support preventative interventions that encourage physical activity and a healthy diet, restrict sedentary activities and offer behavioural support. However, these interventions should involve not only the child but the whole family, school and community. If the current global obesity epidemic is to be halted, further large-scale, well-designed prevention studies are required, particularly within settings outside of the USA, in order to expand the currently limited evidence base upon which clinical recommendations and public health approaches can be formulated. This must be accompanied by enhanced monitoring of paediatric obesity prevalence and continued support from all stakeholders at global, national, regional and local levels.

Phylogenetic analysis of beak and feather disease virus across a host ring-species complex

Pathogens have been hypothesized to play a major role in host diversity and speciation. Susceptibility of hybrid hosts to pathogens is thought to be a common phenomenon that could promote host population divergence and subsequently speciation. However, few studies have tested for pathogen infection across animal hybrid zones while testing for codivergence of the pathogens in the hybridizing host complex. Over 8 y, we studied natural infection by a rapidly evolving single-strand DNA virus, beak and feather diseases virus (BFDV), which infects parrots, exploiting a host-ring species complex (Platycercus elegans) in Australia. We found that host subspecies and their hybrids varied strikingly in both BFDV prevalence and load: both hybrid and phenotypically intermediate subspecies had lower prevalence and load compared with parental subspecies, while controlling for host age, sex, longitude and latitude, as well as temporal effects. We sequenced viral isolates throughout the range, which revealed patterns of genomic variation analogous to Mayr's ring-species hypothesis, to our knowledge for the first time in any host-pathogen system. Viral phylogeny, geographic location, intraspecific host density, and parrot community diversity and composition did not explain the differences in BFDV prevalence or load between subpopulations. Overall, our analyses suggest that functional host responses to infection, or force of infection, differ between subspecies and hybrids. Our findings highlight the role of host hybridization and clines in altering host-pathogen interactions, dynamics that can have important implications for models of speciation with gene flow, and offer insights into how pathogens may adapt to diverging host populations.

Intervention fidelity for a complex behaviour change intervention in community pharmacy addressing cardiovascular disease risk

BACKGROUND: Delivery of cardiovascular disease (CVD) prevention programs by community pharmacists appears effective and enhances health service access. However, their capacity to implement complex behavioural change processes during patient counselling remains largely unexplored. This study aims to determine intervention fidelity by pharmacists for behavioural components of a complex educational intervention for CVD prevention. After receiving training to improve lifestyle and medicines adherence, pharmacists recruited 70 patients aged 50-74 years without established CVD, and taking antihypertensive or lipid lowering therapy. Patients received five counselling sessions, each at monthly intervals. Researchers assessed biomedical and behavioural risk factors at baseline and six months. Pharmacists documented key outcomes from counselling after each session. Most patients (86%) reported suboptimal cardiovascular diets, 41% reported suboptimal medicines adherence, and 39% were physically inactive. Of those advised to complete the intervention, 85% attended all five sessions. Pharmacists achieved patient agreement with most recommended goals for behaviour change, and overwhelmingly translated goals into practical behavioural strategies. Barriers to changing behaviours were regularly documented, and pharmacists reported most behavioural strategies as having had some success. Meaningful improvements to health behaviours were observed post-intervention. Findings support further exploration of pharmacists' potential roles for delivering interventions with complex behaviour change requirements.

Coronary heart disease trends in England and Wales from 1984 to 2004 : concealed levelling of mortality rates among young adults

Background: Trends in cardiovascular risk factors among UK adults present a complex picture. Ominous increases in obesity and diabetes among young adults raise concerns about subsequent coronary heart disease (CHD) mortality rates in this group.

Objective: To examine recent trends in age-specific mortality rates from CHD, particularly those among younger adults.

Methods and results: Mortality data from 1984 to 2004 were used to calculate age-specific mortality rates for British adults aged 35+ years, and joinpoint regression was used to assess changes in trends. Overall, the age-adjusted mortality rate decreased by 54.7% in men and by 48.3% in women. However, among men aged 35–44 years, CHD mortality rates in 2002 increased for the first time in over two decades. Furthermore, the recent declines in CHD mortality rates seem to be slowing in both men and women aged 45–54. Among older adults, however, mortality rates continued to decrease steadily throughout the period.

Conclusions: The flattening mortality rates for CHD among younger adults may represent a sentinel event. Deteriorations in medical management of CHD appear implausible. Thus, unfavourable trends in risk factors for CHD, specifically obesity and diabetes, provide the most likely explanation for the observed trends.

A systematic grounded approach to the development of complex interventions : The Australian WorkHealth Program – Arthritis as a case study

Despite demands for evidence-based research and practice, little attention has been given to systematic approaches to the development of complex interventions to tackle workplace health problems. This paper outlines an approach to the initial stages of a workplace program development which integrates health promotion and disease management. The approach commences with systematic and genuine processes of obtaining information from key stakeholders with broad experience of these interventions. This information is constructed into a program framework in which practice-based and research-informed elements are both valued. We used this approach to develop a workplace education program to reduce the onset and impact of a common chronic disease – osteoarthritis.

To gain information systematically at a national level, a structured concept mapping workshop with 47 participants from across Australia was undertaken. Participants were selected to maximise the whole-of-workplace perspective and included health education providers, academics, clinicians and policymakers. Participants generated statements in response to a seeding statement: Thinking as broadly as possible, what changes in education and support should occur in the workplace to help in the prevention and management of arthritis? Participants grouped the resulting statements into conceptually coherent groups and a computer program was used to generate a ‘cluster map’ along with a list of statements sorted according to cluster membership.

In combination with research-based evidence, the concept map informed the development of a program logic model incorporating the program's guiding principles, possible service providers, services, training modes, program elements and the causal processes by which participants might benefit. The program logic model components were further validated through research findings from diverse fields, including health education, coaching, organisational learning, workplace interventions, workforce development and osteoarthritis disability prevention.

In summary, wide and genuine consultation, concept mapping, and evidence-based program logic development were integrated to develop a whole-of-system complex intervention in which potential effectiveness and assimilation into the workplace for which optimised.

Obstructive jaundice secondary to neuroendocrine tumour in a patient with von Recklinghausen's disease

Neurofibromatosis type 1 (NF1) is an autosomal dominant genetic disorder, with variable clinical manifestations and unpredictable course, associated with an increased incidence of various tumours. Plexiform neurofibromas are hallmark lesions of NF1; they are slow-growing tumours, which account for substantial morbidity, including disfigurement and functional impairment, and may even be life-threatening. Neuroendocrine tumours (NETs), a rare diverse group of neoplasms, are occasionally associated with neurofibromatosis. Pancreatic NETs are tumours with an incidence of less than 1/100 000 population/year and complex patterns of behaviour, which often need complicated strategies for optimal management. We present the case of a young adult with NF1, having a unique concurrence of plexiform neurofibroma involving the liver with an ampullary NET, and we discuss step by step the management in a specialist centre.

Seeking the views of health professionals on translating chronic disease self-management models into practice

Abstract
Few studies have investigated the views of health professionals with respect to their use of chronic disease self-management (CDSM) in the workplace.
Objective
This qualitative study, conducted in an Australian health care setting, examined health professional's formal self-management (SM) training and their views and experiences on the use of SM techniques when working with people living with a chronic illness.
Methods
Purposive sample of 31 health care professionals from a range of service types participated in semi-structured interviews.
Results
The majority of participants (65%) had received no formal training in SM techniques. Participants reported a preference for an eclectic approach to SM, relying primarily on five elements: collaborative care, self-responsibility, client's individual situation, structured support and linking with community agencies. Problems with CDSM centred on medication management, complex measuring devices and limited efficacy with some patient groups.
Conclusion
This study provides valuable information with respect to the use of CDSM within the workplace from the unique perspective of a range of healthcare providers within an Australian health care setting.
Practice implications
Training implications, with respect to CDSM and patient care, are discussed, together with how these findings contribute to the debate concerning how SM principles are translated into healthcare settings.

Analysis of protein sequence and interaction data for candidate disease gene prediction

Linkage analysis is a successful procedure to associate diseases with specific genomic regions. These regions are often large, containing hundreds of genes, which make experimental methods employed to identify the disease gene arduous and expensive. We present two methods to prioritize candidates for further experimental study: Common Pathway Scanning (CPS) and Common Module Profiling (CMP). CPS is based on the assumption that common phenotypes are associated with dysfunction in proteins that participate in the same complex or pathway. CPS applies network data derived from protein–protein interaction (PPI) and pathway databases to identify relationships between genes. CMP identifies likely candidates using a domain-dependent sequence similarity approach, based on the hypothesis that disruption of genes of similar function will lead to the same phenotype. Both algorithms use two forms of input data: known disease genes or multiple disease loci. When using known disease genes as input, our combined methods have a sensitivity of 0.52 and a specificity of 0.97 and reduce the candidate list by 13-fold. Using multiple loci, our methods successfully identify disease genes for all benchmark diseases with a sensitivity of 0.84 and a specificity of 0.63. Our combined approach prioritizes good candidates and will accelerate the disease gene discovery process.