Comparison of the modes of action of Apremilast and Roflumilast

The phosphodiesterase 4 (PDE4) family are cAMP specific phosphodiesterases that play an important role in the inflammatory response and is the major PDE type found in inflammatory cells. A significant number of PDE4 specific inhibitors have been developed and are currently being investigated for use as therapeutic agents. Apremilast, a small molecule inhibitor of PDE 4 is in development for chronic inflammatory disorders and has shown promise for the treatment of psoriasis, psoriatic arthritis as well as other inflammatory diseases. It has been found to be safe and well tolerated in humans and in March 2014 it was approved by the US food and drug administration for the treatment of adult patients with active psoriatic arthritis. The only other PDE4 inhibitor on the market is Roflumilast and it is used for treatment of respiratory disease. Roflumilast is approved in the EU for the treatment of COPD and was recently approved in the US for treatment to reduce the risk of COPD exacerbations. Roflumilast is also a selective PDE4 inhibitor, administered as an oral tablet once daily, and is thought to act by increasing cAMP within lung cells. As both (Apremilast and Roflumilast) compounds selectively inhibit PDE4 but are targeted at different diseases, there is a need for a clear understanding of their mechanism of action (MOA). Differences and similarity of MOA should be defined for the purposes of labelling, for communication to the scientific community, physicians, and patients, and for an extension of utility to other diseases and therapeutic areas. In order to obtain a complete comparative picture of the MOA of both inhibitors, additional molecular and cellular biology studies are required to more fully elucidate the signalling mediators downstream of PDE4 inhibition which result in alterations in pro- and anti-inflammatory gene expression. My studies were conducted to directly compare Apremilast with Roflumilast, in order to substantiate the differences observed in the molecular and cellular effects of these compounds, and to search for other possible differentiating effects. Therefore the main aim of this thesis was to utilise cutting-edge biochemical techniques to discover whether Apremilast and Roflumilast work with different modes of action. In the first part of my thesis I used novel genetically encoded FRET based cAMP sensors targeted to different intracellular compartments, in order to monitor cAMP levels within specific microdomains of cells as a consequence of challenge with Apremilast and Roflumilast, which revealed that Apremilast and Roflumilast do regulate different pools of cAMP in cells. In the second part of my thesis I focussed on assessing whether Apremilast and Roflumilast cause differential effects on the PKA phosphorylation state of proteins in cells. I used various biochemical techniques (Western blotting, Substrate kinase arrays and Reverse Phase Protein array and found that Apremilast and Roflumilast do lead to differential PKA substrate phosphorylation. For example I found that Apremilast increases the phosphorylation of Ribosomal Protein S6 at Ser240/244 and Fyn Y530 in the S6 Ribosomal pathway of Rheumatoid Arthritis Synovial fibroblast and HEK293 cells, whereas Roflumilast does not. This data suggests that Apremilast has distinct biological effects from that of Roflumilast and could represent a new therapeutic role for Apremilast in other diseases. In the final part of my thesis, Phage display technology was employed in order to identify any novel binding motifs that associate with PDE4 and to identify sequences that were differentially regulated by the inhibitors in an attempt to find binding motifs that may exist in previously characterised signalling proteins. Petide array technology was then used to confirm binding of specific peptide sequences or motifs. Results showed that Apremilast and Roflumilast can either enhance or decrease the binding of PDE4A4 to specific peptide sequences or motifs that are found in a variety of proteins in the human proteome, most interestingly Ubiquitin-related proteins. The data from this chapter is preliminary but may be used in the discovery of novel binding partners for PDE4 or to provide a new role for PDE inhibition in disease. Therefore the work in this thesis provides a unique snapshot of the complexity of the cAMP signalling system and is the first to directly compare action of the two approved PDE4 inhibitors in a detailed way.

Non-invasive monitoring of changes in exhaled markers of airway inflammation in Thoroughbred racehorses

Exhaled breath (EB) and exhaled breath condensate (EBC) contain numerous volatile gases and a wide-array of non-volatile compounds, several of which have been investigated as markers of lower airway inflammation in human and veterinary medicine and have been used to diagnose and monitor diseases associated with pulmonary inflammation. The identification of reliable biomarkers within EB and EBC is an active research focus with the common goal of establishing non-invasive and repeatable assessment of respiratory health and disease in mammals. The application of EB and EBC analysis holds considerable appeal in the investigation of respiratory disease in Thoroughbred racehorses, as inflammatory airway disease (IAD) is a common cause for poor performance in this population of animals. This study documented that EB and EBC samples can be safely collected from Thoroughbred racehorses in their own environment, without adverse effect or interference with the horse’s training regimen. The use of off-line collection and analysis of exhaled gases via chemiluminescence is suitable for the measurement of exhaled carbon monoxide, but is not appropriate for analyzing exhaled nitric oxide in horses. Significant changes in the concentration of exhaled CO and the pH of EBC occurred in response to strenuous exercise and when exercising in different environmental temperatures. Exhaled CO was associated with tracheal mucus score (and the number of neutrophils in the mucus) and EBC pH was significantly different in horses with evidence of neutrophilic IAD compared to horses without IAD. Numerous physiological and environmental variables were identified as confounding factors in the assessment of both exhaled CO and EBC pH, with respiratory rate prior to EB collection, and during EBC collection, consistently identified as an explanatory variable influencing the concentration of exhaled biomarkers. Further studies in EB and EBC analysis in horses need to focus on objectively accounting for key respiratory dynamics during sample collection.

The impact of denture related disease on the oral microbiome of denture wearers

Advances in healthcare over the last 100 years has resulted in an ever increasing elderly population. This presents greater challenges for adequate systemic and oral healthcare delivery. With increasing age there is a natural decline in oral health, leading to the loss of teeth and ultimately for some having to wear denture prosthesis. It is currently estimated that approximately one fifth of the UK and US populations have some form of removable prosthesis. The microbiology of denture induced mucosal inflammation is a pivotal factor to consider in denture care management, similar to many other oral diseases of microbial influence, such as caries, gingivitis and periodontitis. Dentures support the growth of microbial biofilms, structures commonly known as denture plaque. Microbiologically, denture stomatitis (DS) is a disease primarily considered to be of yeast aetiology, with the literature disproportionately focussed on Candida spp. However, the denture surface is capable of carrying up to 1011 microbes per milligram, the majority of which are bacteria. Thus it is apparent that denture plaque is more diverse than we assume. There is a fundamental gap in our understanding of the bacterial composition of denture plaque and the role that they may play in denture related disease such as DS. This is categorised as inflammation of the oral mucosa, a disease affecting around half of all denture wearers. It has been proposed that bacteria and fungi interact on the denture surface and that these polymicrobial interactions lead to synergism and increased DS pathogenesis. Therefore, understanding the denture microbiome composition is the key step to beginning to understand disease pathogenesis, and ultimately help improve treatments and identify novel targets for therapeutic and preventative strategies. A group of 131 patients were included within this study in which they provided samples from their dentures, palatal mucosa, saliva and dental plaque. Microbes residing on the denture surface were quantified using standard Miles and Misra culture technique which investigated the presence of Candida, aerobes and anaerobes. These clinical samples also underwent next generation sequencing using the Miseq Illumina platform to give a more global representation of the microbes present at each of these sites in the oral cavity of these denture wearers. This data was then used to compare the composition and diversity of denture, mucosal and dental plaque between one another, as well as between healthy and diseased individuals. Additional comparisons included denture type and the presence or absence of natural teeth. Furthermore, microbiome data was used to assess differences between patients with varying levels of oral hygiene. The host response to the denture microbiome was investigated by screening the patients saliva for the presence and quantification of a range of antimicrobial peptides that are associated with the oral cavity. Based on the microbiome data an in vitro biofilm model was developed that reflected the composition of denture plaque. These biofilms were then used to assess quantitative and compositional changes over time and in response to denture cleansing treatments. Finally, the systemic implications of denture plaque were assessed by screening denture plaque samples for the presence of nine well known respiratory pathogens using quantitative PCR. The results from this study have shown that the bacterial microbiome composition of denture wearers is not consistent throughout the mouth and varies depending on sample site. Moreover, the presence of natural dentition has a significant impact on the microbiome composition. As for healthy and diseased patients the data suggests that compositional changes responsible for disease progression are occurring at the mucosa, and that dentures may in fact be a reservoir for these microbes. In terms of denture hygiene practices, sleeping with a denture in situ was found to be a common occurrence. Furthermore, significant shifts in denture microbiome composition were found in these individuals when compared to the denture microbiome of those that removed their denture at night. As for the host response, some antimicrobial peptides were found to be significantly reduced in the absence of natural dentition, indicating that the oral immune response is gradually impaired with the loss of teeth. This study also identified potentially serious systemic implications in terms of respiratory infection, as 64.6% of patients carried respiratory pathogens on their denture. In conclusion, this is the first study to provide a detailed understanding of the oral microbiome of denture wearers, and has provided evidence that DS development is more complex than simply a candidal infection. Both fungal and bacterial kingdoms clearly play a role in defining the progression of DS. The biofilm model created in this study demonstrated its potential as a platform to test novel actives. Future use of this model will aid in greater understanding of host: biofilm interactions. Such findings are applicable to oral health and beyond, and may help to identify novel therapeutic targets for the treatment of DS and other biofilm associated diseases.