A Confluence of Risks: Control and Compliance in the World of Unstructured Data, Big Data and the Cloud

The emergence of powerful new technologies, the existence of large quantities of data, and increasing demands for the extraction of added value from these technologies and data have created a number of significant challenges for those charged with both corporate and information technology management. The possibilities are great, the expectations high, and the risks significant. Organisations seeking to employ cloud technologies and exploit the value of the data to which they have access, be this in the form of "Big Data" available from different external sources or data held within the organisation, in structured or unstructured formats, need to understand the risks involved in such activities. Data owners have responsibilities towards the subjects of the data and must also, frequently, demonstrate that they are in compliance with current standards, laws and regulations. This thesis sets out to explore the nature of the technologies that organisations might utilise, identify the most pertinent constraints and risks, and propose a framework for the management of data from discovery to external hosting that will allow the most significant risks to be managed through the definition, implementation, and performance of appropriate internal control activities.

Bioinformatics-driven identification and examination of candidate genes for non-alcoholic fatty liver disease.

ObjectiveCandidate genes for non-alcoholic fatty liver disease (NAFLD) identified by a bioinformatics approach were examined for variant associations to quantitative traits of NAFLD-related phenotypes.Research Design and MethodsBy integrating public database text mining, trans-organism protein-protein interaction transferal, and information on liver protein expression a protein-protein interaction network was constructed and from this a smaller isolated interactome was identified. Five genes from this interactome were selected for genetic analysis. Twenty-one tag single-nucleotide polymorphisms (SNPs) which captured all common variation in these genes were genotyped in 10,196 Danes, and analyzed for association with NAFLD-related quantitative traits, type 2 diabetes (T2D), central obesity, and WHO-defined metabolic syndrome (MetS).Results273 genes were included in the protein-protein interaction analysis and EHHADH, ECHS1, HADHA, HADHB, and ACADL were selected for further examination. A total of 10 nominal statistical significant associations (P<0.05) to quantitative metabolic traits were identified. Also, the case-control study showed associations between variation in the five genes and T2D, central obesity, and MetS, respectively. Bonferroni adjustments for multiple testing negated all associations.ConclusionsUsing a bioinformatics approach we identified five candidate genes for NAFLD. However, we failed to provide evidence of associations with major effects between SNPs in these five genes and NAFLD-related quantitative traits, T2D, central obesity, and MetS.

Patient, primary care physician and specialist expectations of primary care physician involvement in cancer care.

BACKGROUND: In Canada, many health authorities recommend that primary care physicians (PCP) stay involved throughout their patients' cancer journey to increase continuity of care. Few studies have focused on patient and physician expectations regarding PCP involvement in cancer care. OBJECTIVE: To compare lung cancer patient, PCP and specialist expectations regarding PCP involvement in coordination of care, emotional support, information transmission and symptom relief at the different phases of cancer. DESIGN: Canadian survey of lung cancer patients, PCPs and cancer specialists PARTICIPANTS: A total of 395 patients completed questionnaires on their expectations regarding their PCP participation in several aspects of care, at different phases of their cancer. Also, 45 specialists and 232 community-based PCP involved in these patients' care responded to a mail survey on the same aspects of cancer care. RESULTS: Most specialists did not expect participation of the PCP in coordination of care in the diagnosis and treatment phases (65% and 78% respectively), in contrast with patients (83% and 85%) and PCPs (80% and 59%) (p < 0.0001). At these same phases, the best agreement among the 3 groups was around PCP role in emotional support: 84% and more of all groups had this expectation. PCP participation in symptom relief was another shared expectation, but more unanimously at the treatment phase (p = 0.85). In the advanced phase, most specialists expect a major role of PCP in all aspects of care (from 81% to 97%). Patients and PCP agree with them mainly for emotional support and information transmission. CONCLUSION: Lung cancer patient, PCP and specialist expectations regarding PCP role differ with the phase of cancer and the specific aspect of cancer care. There is a need to reach a better agreement among them and to better define PCP role, in order to achieve more collaborative and integrated cancer care.

Human metabolic individuality in biomedical and pharmaceutical research.

Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.