PhD in Personalised Medicine in Diabetes Care
Job No:
G91
Location:
Darlinghurst, Sydney
Supervisor: Dr Alex Viardot
Personalized Medicine For Diabetes
The increasing prevalence of obesity and type 2 diabetes (T2D) has reached epidemic proportions, and new ways of prevention and effective treatment are urgently needed. T2D is a chronic disease accounting for 95% of diabetes worldwide, and is characterized by an insufficient compensatory insulin secretion to insulin resistance. In contrast to other diseases, it consists of a number of subgroups differing in phenotype, manifestation and disease mechanisms. Personalised medicine represents a novel approach for defining both disease subtypes and biomarkers that could identify those patients who are most likely to benefit from a specific treatment. It can be used in prevention, detection, individualised treatment and monitoring of diseases. In today’s treatment algorithms, little attention is given to the huge variation in phenotype in these patients, who might have significant differences in insulin resistance, beta-cell function, gut hormone levels, systemic inflammation and central control of metabolism including the autonomic nervous system. No treatment decision is currently made on this basis, but rather on the available evidence as to which treatment the biggest numbers of patients respond. However, phenotypic assessments complemented with genomic data may well enable identification of a subtype with specific treatment options which could avoid ineffective and time wasting treatments, and ultimately lead to a more targeted and rational treatment strategy in T2D.
In addition to the above, many patients are thought to be misdiagnosed for type of diabetes, which results in suboptimal treatment and worse clinical outcome. This includes many cases of monogenetic forms of diabetes, most commonly Maturity Onset Diabetes of the Young (MODY) who never had genetic testing and are presumed either T1D or T2D. Many of these patients present clinically in-between T1D and T2D, and treatment allocation is most commonly based on clinical judgment and also on their response to the chosen treatment regimen. Monogenetic diabetes may make up 1-5% of patients in a large diabetes clinic. There are clear advantages of diagnosing these monogenetic forms of diabetes: In many patients, insulin may not be required and could be substituted with oral agents. In addition, families should be screened and additional affected patients could be identified and appropriately treated at an early stage. However, genetic testing is still not widely available, is expensive, and routine tests may not detect all the known genetic mutations if they are not specifically looked for.
The aims of this project include novel approaches to carefully phenotype individual patients with T1D or T2D to:
1.) Identify the most commonly affected mechanisms of disease in T2D, leading to the definition of specific disease-subtypes
2.) Screen for gene variants associated with these phenotypic features. Identification of specific risk genes could eventually assist or even replace future clinical assessment for stratifying these patients into their specific subgroups.
3.) Test the effect of allocating these T2D patients to suitably targeted treatment options considering the specific pathophysiology.
4.) Prospectively collect data to track treatment responders and non-responders in order to identify gene polymorphisms which could serve as predictors and be used to build new treatment algorithms, using a pharmacogenomic approach.
5.) Set up a genetic testing facility in our clinical genomics centre to be able to screen patients for monogenetic diabetes
6.) Analyse genome data and try to find new candidate genes for T1D
In summary, these new strategies could test a new methodology of personalized medicine which could prove to be more health protective and cost effective in the long term, and provide a new treatment algorithm for T2D for the future. Screening for the most common forms of monogenetic diabetes would allow identifying so far undiagnosed patients and allow tailoring their treatment specifically for their gene defect. The project would involve conducting clinical research with a strong link to the genome sequencing and bioinformatics facilities.