Investigating the epidemiology of canine health using data science techniques

Research into dog health has historically relied on small scale cross-sectional studies or specialised medical and clinical data, which are subject to bias and are difficult to generalise to the wider canine population. The digital era presents an opportunity to collect sources of Big Data for health surveillance and research, defined as data that is high volume, velocity or variability. Data science techniques have made accessing, managing and analysing such datasets more achievable. Large scale cohort studies are needed to estimate the incidence of disease and to identify factors associated with long-term canine health. This project was primarily based on dog owner questionnaires from Dogslife, an internet-based cohort of Labrador Retrievers in the UK set up in 2010. In this thesis, I designed data cleaning methods for Dogslife and validated some of them on veterinary and human medical records and investigated the epidemiology of canine health using Dogslife data, Google Trends and 16S ribosomal RNA gene sequencing data derived from canine faecal samples. A decision-making algorithm for identifying, correcting or removing implausible values in growth measurements was designed and tested in combination with five different data cleaning methods, which were then applied to five datasets. The algorithm was most effective in combination with non-linear mixed effects models and increased the average sensitivity and specificity of the models alone by 7.68% and 0.42% respectively. This method was adaptable and had several useful functions including allowing for individual growth trajectories, preserving data where possible and removing duplications. A vomiting outbreak was evident in UK dogs between December 2019 and March 2020 in data from Dogslife and Google Trends search queries. The odds of a vomiting incident being reported to Dogslife was 1.51 (95% CI: 1.24 – 1.84) in comparison to the same time period in previous years (December to March, 2010 to 2019). Dogslife data identified risks for a dog experiencing a vomiting episode and differences in owner-decision making when seeking veterinary attention for vomiting during the outbreak. Compared with previous years (March 23rd to July 4th, 2010 to 2019), the COVID-19 restrictions study period (March 23rd to July 4th 2020) was associated with owners reporting increases in their dogs’ exercise and worming and decreases in insurance, titbit-feeding and vaccination. Odds of owners reporting that their dogs had an episode of coughing (0.20, 95% CI: 0.04 – 0.92) and that they took their dogs to a veterinarian with an episode of any illness (0.58, 95% CI: 0.45 – 0.76) were lower during the COVID-19 restrictions compared to before. A longitudinal sub-study of Dogslife Labrador Retriever puppies was designed to investigate associations between environmental and health factors and the development of the canine microbiome. When their puppies were three to four, seven and 12 months of age, owners submitted digestive health questionnaires and faecal samples from their puppies, which were used to produce 16S ribosomal RNA gene sequencing data. Dogs’ faecal microbiota were successfully characterised for each wave of sample collection at the different dog ages. The largest source of variation in the composition of dogs’ microbiomes was explained by differences between individual dogs, explaining approximately 50%. Additional associations were found between age, sex, coat colour, UK geographical region, household type, coprophagia, contact with other animals, recent antibiotic use and recent diarrhoea and various differences in the diversity and composition of the microbiome. Owner-derived data can be used alongside other sources of Big Data and provides valid and valuable information for the surveillance of veterinary health that contains detail about environmental factors not typically present in medical records or clinical studies. Such information is becoming easier to handle and analyse with the use of data science techniques. Furthermore, cohort studies can be used for the recruitment of participants to sub-studies that aim to answer a specialised question, such as microbiome research

Is it time to stop sweeping data cleaning under the carpet?:A novel algorithm for outlier management in growth data

All data are prone to error and require data cleaning prior to analysis. An important example is longitudinal growth data, for which there are no universally agreed standard methods for identifying and removing implausible values and many existing methods have limitations that restrict their usage across different domains. A decision-making algorithm that modified or deleted growth measurements based on a combination of pre-defined cut-offs and logic rules was designed. Five data cleaning methods for growth were tested with and without the addition of the algorithm and applied to five different longitudinal growth datasets: four uncleaned canine weight or height datasets and one pre-cleaned human weight dataset with randomly simulated errors. Prior to the addition of the algorithm, data cleaning based on non-linear mixed effects models was the most effective in all datasets and had on average a minimum of 26.00% higher sensitivity and 0.12% higher specificity than other methods. Data cleaning methods using the algorithm had improved data preservation and were capable of correcting simulated errors according to the gold standard; returning a value to its original state prior to error simulation. The algorithm improved the performance of all data cleaning methods and increased the average sensitivity and specificity of the non-linear mixed effects model method by 7.68% and 0.42% respectively. Using non-linear mixed effects models combined with the algorithm to clean data allows individual growth trajectories to vary from the population by using repeated longitudinal measurements, identifies consecutive errors or those within the first data entry, avoids the requirement for a minimum number of data entries, preserves data where possible by correcting errors rather than deleting them and removes duplications intelligently. This algorithm is broadly applicable to data cleaning anthropometric data in different mammalian species and could be adapted for use in a range of other domains

Faith, empowerment, church and community mobilisation advocacy: insights from Tearfund’s partner in Uganda

Tearfund, a Christian faith-based international non-governmental organisation, has for 15 years supported local churches to mobilise communities through a process called Church and Community Mobilisation (CCM). The CCM advocacy pilot project in Uganda led to improvements in service delivery. In this paper, Tearfund and Making All Voices Count staff discuss recent research that examines the role of local churches, CCM and CCM advocacy in fostering transparency, citizen empowerment, inclusion and government responsiveness. The key themes they examine are social capital and the distinctive nature of faith-based mobilisation; faith and empowerment, both individual and collective; community mobilisation, strategic advocacy and shifting the power dynamics between local-level government officials and citizens; and scaling up local-level accountability successes to the national level.DFIDUSAIDSidaOmidyar Networ

Disorder predispositions and protections of Labrador Retrievers in the UK

Abstract The Labrador Retriever is one of the most popular dog breeds worldwide, therefore it is important to have reliable evidence on the general health issues of the breed. Using anonymised veterinary clinical data from the VetCompass Programme, this study aimed to explore the relative risk to common disorders in the Labrador Retriever. The clinical records of a random sample of dogs were reviewed to extract the most definitive diagnoses for all disorders recorded during 2016. A list of disorders was generated, including the 30 most common disorders in Labrador Retrievers and the 30 most common disorders in non-Labrador Retrievers. Multivariable logistic regression was used to report the odds of each of these disorders in 1462 (6.6%) Labrador Retrievers compared with 20,786 (93.4%) non-Labrador Retrievers. At a specific-level of diagnostic precision, after accounting for confounding, Labrador Retrievers had significantly increased odds of 12/35 (34.3%) disorders compared to non-Labrador Retrievers; osteoarthritis (OR 2.83) had the highest odds. Conversely, Labrador Retrievers had reduced odds of 7/35 (20.0%) disorders; patellar luxation (OR 0.18) had the lowest odds. This study provides useful information about breed-specific disorder predispositions and protections, which future research could evaluate further to produce definitive guidance for Labrador Retriever breeders and owners

Insights into the Spectrum of Activity and Mechanism of Action of MGB-BP-3

MGB-BP-3 is a potential first-in-class antibiotic, a Strathclyde Minor Groove Binder (S-MGB), that has successfully completed Phase IIa clinical trials for the treatment of Clostridioides difficile associated disease. Its precise mechanism of action and the origin of limited activity against Gram-negative pathogens are relatively unknown. Herein, treatment with MGB-BP-3 alone significantly inhibited the bacterial growth of the Gram-positive, but not Gram-negative, bacteria as expected. Synergy assays revealed that inefficient intracellular accumulation, through both permeation and efflux, is the likely reason for lack of Gram-negative activity. MGB-BP-3 has strong interactions with its intracellular target, DNA, in both Gram-negative and Gram-positive bacteria, revealed through ultraviolet–visible (UV–vis) thermal melting and fluorescence intercalator displacement assays. MGB-BP-3 was confirmed to bind to dsDNA as a dimer using nano-electrospray ionization mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy. Type II bacterial topoisomerase inhibition assays revealed that MGB-BP-3 was able to interfere with the supercoiling action of gyrase and the relaxation and decatenation actions of topoisomerase IV of both Staphylococcus aureus and Escherichia coli. However, no evidence of stabilization of the cleavage complexes was observed, such as for fluoroquinolones, confirmed by a lack of induction of DSBs and the SOS response in E. coli reporter strains. These results highlight additional mechanisms of action of MGB-BP-3, including interference of the action of type II bacterial topoisomerases. While MGB-BP-3′s lack of Gram-negative activity was confirmed, and an understanding of this presented, the recognition that MGB-BP-3 can target DNA of Gram-negative organisms will enable further iterations of design to achieve a Gram-negative active S-MGB

Epigenetic priming of immune/inflammatory pathways activation and abnormal activity of cell cycle pathway in a perinatal model of white matter injury

Prenatal inflammatory insults accompany prematurity and provoke diffuse white matter injury (DWMI), which is associated with increased risk of neurodevelopmental pathologies, including autism spectrum disorders. DWMI results from maturation arrest of oligodendrocyte precursor cells (OPCs), a process that is poorly understood. Here, by using a validated mouse model of OPC maturation blockade, we provide the genome-wide ID card of the effects of neuroinflammation on OPCs that reveals the architecture of global cell fate issues underlining their maturation blockade. First, we find that, in OPCs, neuroinflammation takes advantage of a primed epigenomic landscape and induces abnormal overexpression of genes of the immune/inflammatory pathways: these genes strikingly exhibit accessible chromatin conformation in uninflamed OPCs, which correlates with their developmental, stage-dependent expression, along their normal maturation trajectory, as well as their abnormal upregulation upon neuroinflammation. Consistently, we observe the positioning on DNA of key transcription factors of the immune/inflammatory pathways (IRFs, NFkB), in both unstressed and inflamed OPCs. Second, we show that, in addition to the general perturbation of the myelination program, neuroinflammation counteracts the physiological downregulation of the cell cycle pathway in maturing OPCs. Neuroinflammation therefore perturbs cell identity in maturing OPCs, in a global manner. Moreover, based on our unraveling of the activity of genes of the immune/inflammatory pathways in prenatal uninflamed OPCs, the mere suppression of these proinflammatory mediators, as currently proposed in the field, may not be considered as a valid neurotherapeutic strategy

Antidepressants for the prevention of depression following first-episode psychosis (ADEPP): study protocol for a multi-centre, double-blind, randomised controlled trial

Background: Depressive episodes are common after first-episode psychosis (FEP), affecting more than 40% of people, adding to individual burden, poor outcomes, and healthcare costs. If the risks of developing depression were lower, this could have a beneficial effect on morbidity and mortality, as well as improving outcomes. Sertraline is a selective serotonin reuptake inhibitor and a common first-line medication for the treatment of depression in adults. It has been shown to be safe when co-prescribed with antipsychotic medication, and there is evidence that it is an effective treatment for depression in established schizophrenia. We present a protocol for a multi-centre, double-blind, randomised, placebo-controlled clinical trial called ADEPP that aims to investigate the efficacy and cost-effectiveness of sertraline in preventing depression after FEP. Methods: The recruitment target is 452 participants between the ages of 18 and 65 years who are within 12 months of treatment initiation for FEP. Having provided informed consent, participants will be randomised to receive either 50 mg of sertraline daily or matched placebo for 6 months, in addition to treatment as usual. The primary outcome measure will be a comparison of the number of new cases of depression between the treatment and placebo arms over the 6-month intervention phase. Secondary outcomes include suicidal behaviour, anxiety, rates of relapse, functional outcome, quality of life, and resource use. Discussion: The ADEPP trial will test whether the addition of sertraline following FEP is a clinically useful, acceptable, and cost-effective way of improving outcomes following FEP. Trial registration: ISRCTN12682719 registration date 24/11/2020

A theoretical model of inflammation- and mechanotransduction- driven asthmatic airway remodelling

Inflammation, airway hyper-responsiveness and airway remodelling are well-established hallmarks of asthma, but their inter-relationships remain elusive. In order to obtain a better understanding of their inter-dependence, we develop a mechanochemical morphoelastic model of the airway wall accounting for local volume changes in airway smooth muscle (ASM) and extracellular matrix in response to transient inflammatory or contractile agonist challenges. We use constrained mixture theory, together with a multiplicative decomposition of growth from the elastic deformation, to model the airway wall as a nonlinear fibre-reinforced elastic cylinder. Local contractile agonist drives ASM cell contraction, generating mechanical stresses in the tissue that drive further release of mitogenic mediators and contractile agonists via underlying mechanotransductive signalling pathways. Our model predictions are consistent with previously described inflammation-induced remodelling within an axisymmetric airway geometry. Additionally, our simulations reveal novel mechanotransductive feedback by which hyper-responsive airways exhibit increased remodelling, for example, via stress-induced release of pro-mitogenic and procontractile cytokines. Simulation results also reveal emergence of a persistent contractile tone observed in asthmatics, via either a pathological mechanotransductive feedback loop, a failure to clear agonists from the tissue, or a combination of both. Furthermore, we identify various parameter combinations that may contribute to the existence of different asthma phenotypes, and we illustrate a combination of factors which may predispose severe asthmatics to fatal bronchospasms