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ERA is a digital repository of original research produced at The University of Edinburgh. The archive contains documents written by, or affiliated with, academic authors, or units, based at Edinburgh that have sufficient quality to be collected and preserved by the Library, but which are not controlled by commercial publishers. Holdings include full-text digital doctoral theses, masters dissertations, project reports, briefing papers and out-of-print materials.

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Towards a data-driven personalised approach to gestational diabetes care
(2026-05-26) Kirkwood, Jasmine R.; Reynolds, Rebecca; Wake, Debbie; Lindsay, Robert; Manataki, Areti; Medical Research Scotland; MyWay Digital Health
INTRODUCTION: Gestational diabetes mellitus (GDM) is high blood glucose that is first recognised during pregnancy and is one of the most common pregnancy complications. GDM is managed through lifestyle modification and may require pharmacological therapy to normalise blood glucose levels. Self monitoring blood glucose readings are reviewed at clinical appointments, where treatment may be escalated. Current care in Scotland is time-consuming and does not utilise the potential of risk-stratification and digital tools. This thesis proposes an alternative method of care that does so by risk stratifying women with GDM based on their need for insulin and remotely monitoring them through a digital tool. METHODS & RESULTS: This is an interdisciplinary mixed-methods thesis, the quantitative methods focusing on the development of a need for an insulin treatment prediction model, and the qualitative methods focusing on the design of a digital tool to support both women and clinicians in the management of GDM. To aid with readability, the results chapters’ methods and results are reported together. In the first result chapter I report the findings of a scoping review of 17 studies describing 44 machine learning models to predict the need for pharmacological therapy in GDM from four electronic databases between 1st July 2007 and 31st August 2024. All published literature were binary classifiers with 61.4% (27/44) of models predicting need for any pharmacological therapy and 38.6% (17/44) predicting need for insulin. Models had a median area under the receiver operator curve (AUROC) of 0.75. Common clinical variables were found to be predictors, such as history of GDM, gestational week at GDM diagnosis, pregestational body mass index (BMI), maternal age, HbA1c, fasting – and 1-hr-glucose from a 75g oral glucose tolerance test (OGTT), with logistic regression being a popular algorithm. There was a lack of external validation and clinical implementation. In the following two results chapters, I present my quantitative analyses. From a database of 30,666 pregnancy episodes in Greater Glasgow and Clyde, I selected 10,694 pregnancy episodes that had a booking date and received care between 1st April 2022 to 31st December 2023. The selected data were cleaned, and a cohort of singleton pregnancies that were complicated by GDM (10.4%, 1,109) was identified alongside a complementary non-GDM cohort (89.6%, 9,585). The maternal characteristics and pregnancy outcomes were described. In the descriptive analysis of 10,694 singleton pregnancies in Glasgow, the rate of GDM was high (10.4%, 1,109) despite only screening women with a BMI ≥ 35kg/m2. Women with pregnancies complicated by GDM were older (GDM: mean[SD] 32 [5.3], non-GDM: 31 [5.4] years, p<0.001), had a higher BMI (32 [7.4], 27 [5.8] kg/m2, p<0.001), and more likely to live in the most deprived areas (Scottish Index of Multiple Deprivation quantile 1, 45.4%(504), 39.5% (3,789), compared to those without GDM. Among women with GDM, those managing it through diet were younger than those who required pharmacological treatment (Diet: 32 [5.4], Metformin: 33 [4.8], Insulin: 33 [5.3] years, p = 0.001). Women requiring insulin had a higher BMI (32 [7.2], 32 [7.6], 35 [7.5]kg/m2, p<0.001). HbA1c at booking was higher in the insulin-treated GDM (35 [3.3] mmol/L, 35 [3.1] mmol/L, 36 [3.8] mmol/L, p=0.038) as were fasting OGTT results (5.2 [0.5] , 5.3 [0.46] , 5.6[0.57] mmol/L, p<0.001) which was taken earlier (26 [6], 24 [5.6] ,23 [5.6] gestational weeks, p<0.001) . Caesarean birth rates were higher in GDM pregnancies (53.5%(593) vs. 40.0%(3,834), p < 0.001), with insulin-treated GDM showing increased elective Caesarean rates (29.8%(239), 35.9%(79), 41.4%(36), p=0.033). Large for gestational age (LGA) was more common in GDM-complicated pregnancies (15.0%(166), 9.0%(841), p<0.001). Neonatal unit admissions were higher in GDM pregnancies compared to non-GDM (41.2%(158), 9.4%(899), p<0.001). Although admissions were more frequent in GDM managed with insulin, the difference was not statistically significant (13.8%(111), 14.1%(31), 18.4%(16), p=0.513). The penultimate results chapter uses the results of the scoping review and statistical analysis to direct the development of machine learning models for predicting insulin for GDM. Two algorithms (logistic regression and Classification and Regression Tree (CART)) using univariate feature selection and least absolute shrinkage and selection operation (LASSO) were compared. Synthetic Minority Oversampling Technique (SMOTE) was used to address the unbalanced data. Using a complete case analysis, 996 GDM complicated pregnancy episodes were included in the dataset which split into 70% for training and 30% for testing. The training performance was assessed using 10-fold cross-validation, and the final model performance was validated on the unseen test data. Both models generalised well, and overall were sensitive but not specific. The logistic regression had a mean 10-fold cross validation AUROC in train data of 0.79 [0.07] and AUROC of 0.71 on the unseen data. The CART model had mean 10-fold cross validation AUROC in train data of 0.78 [0.02] and AUROC of 0.71 on the unseen data. In the final results Chapter, a user-centred digital tool, ‘MyGDM’, was designed from ethnographic observation and 11 semi-structured interviews with end-users (6 healthcare professionals and 5 women with GDM). The initial design was evaluated in feedback sessions with 31 participants (17 healthcare professionals, 14 researchers) and 13 questionnaires with women with GDM. MyGDM has a clinical dashboard linked to a patient-facing app, aiming to enhance clinical workflows, identify off-target blood glucose levels and provide GDM-specific information. The initial design drew upon existing literature and insights from 11 semi-structured interviews conducted with HCPs and women with GDM. In a survey of 13 women with GDM, every participant reported that the tool would fit well into their lifestyles and aid in managing their GDM. Educational resources, along with the ‘request a call’ feature, were particularly well received, with 61.5% (8 out of 13) and 69.2% (9 out of 13) indicating they were very likely or likely to utilise these options, respectively. End-user evaluations of the interactive design were favourable, confirming that it effectively met their needs. CONCLUSION: GDM care could be personalised through risk-stratification and digital tools. There is an opportunity to translate the key concepts explored in this thesis into a clinically implementable model of care for GDM.
Methods for utilising genomic diversity in tropical dairy breeding
(The University of Edinburgh. Royal (Dick) School of Veterinary Studies, 2026-05-26) Mafra Fortuna, Gabriela; Gorjanc, Gregor; Prendergast, James; Biotechnology and Biological Sciences Research Council (BBSRC); Genus ABS; EASTBIO BBSRC Doctoral Training Partnership
Dairy production plays a crucial role in addressing food insecurity and poverty in tropical regions by providing high-value protein and generating income for millions of smallholder farmers. It also empowers women and girls, strengthening rural communi- ties, and contributing to sustainable economic development. Tropical dairy production commonly relies on crossbreeding environmentally-adapted local Bos indicus (indicine) breeds with high-yielding exotic breeds, usually from Bos taurus (taurine) origin. This strategy aims to increase productivity by leveraging breed complementarity and heterosis. However, crossbred performance is highly variable, to the point of instability. This instability undermines the success of crossbreeding by posing short-term challenges to production management and long-term challenges to the optimisation of selective breeding. This thesis explores three fundamental aspects behind the challenges of tropical cross- breeding strategies: (i) the genetic distance between environmentally-adapted local breeds and high-yielding exotic breeds, (ii) the lack of statistical methods tailored to dealing with such genetic distance, and (iii) the genotype-by-environment (G×E) interaction that underlies the instability in crossbred performance across environments. These fundamental aspects address the long-standing objective of breeders to effectively utilise genetic variation in tropical dairy breeding. The work presented here seeks to introduce novel methods for uncovering and leveraging the genetic variation available in tropical dairy systems. The thesis is structured as follows. Chapter 1 provides a review of the evolutionary and breeding history of cattle. It outlines the origins of genetic divergence between populations adapted to the tropical climates of the Global South and those favoured in the Global North. The chapter also introduces the concepts of Ancestral Recombination Graphs (ARG) and multiplicative models; two methodological approaches used throughout the thesis to analyse genetic diversity, the effects of genetic diversity on phenotypic performance, and the effects of G×E interaction. Particular focus is paid to the inherent differences between pedigree and genomic-based models, and the benefits of ARG-based inference. The chapter concludes by stating the research objectives and the thesis structure. Chapter 2 investigates global patterns of genetic diversity and population structure in cattle. This chapter demonstrates how the fast-evolving field of ARG reconstruction can benefit livestock genomics, providing an information-rich new format for storing and analysing genomic data. The results show that tree-sequence-based ARGs capture fine-scale population structure across cattle populations worldwide. In particular, local ancestry inference with ARGs enables the assignment of breed-of-origin that can inform crossbred genomic evaluation, especially in contexts of complex ancestry composition. Chapter 3 introduces a novel ARG-based statistical model for estimating haplotype and ancestry-specific mutation effects considering the genome sequence context. The genomic distance between indicine and taurine cattle breeds underlies variation in their adaptation and performance. The distinct selective pressures experienced by these populations over time have shaped the genomic context in which mutations occur, resulting in ancestry-specific mutations and their effects. These differences limit the predictive accuracy of crossbreeding and multi-breed genetic evaluations, as current methods often assume mutations and their effects are shared across populations. By capturing the historical recombination, mutation, and coalescence processes that shape genetic variation, ARGs offer a biologically informed basis for modelling mutation effects. The proposed model, initially developed for a single, non-recombining genomic region, achieves predictive accuracy comparable to standard SNP-based approaches while reducing computational demands and providing additional biological insights. This work lays the foundation for future expansion to more complex scenarios including multiple recombining regions. Another limitation addressed in this thesis is the instability of crossbred performance across environments arising from G×E interaction, which is often ignored in tropical dairy systems. G×E interaction reflects the variable genotype performance between environments, and when not managed, reduces the predictability of the deviation in trait expression. This phenomenon increases genetic variance and alters genotype ranking across environments, hindering the optimisation of production. Chapter 4 develops a novel framework for decomposing genetic variance that exposes the variation due to G×E interaction. The framework leverages a rotated multiplicative model and subsequent visualisation approaches commonly used in plant breeding but rarely explored by animal breeders. The outputs of this analysis express the genetic variance in a way that is more accessible and actionable for breeding decisions, providing the means to identify broadly and specifically adapted individuals. Using stochastic simulations, the chapter demonstrates how G×E interaction affects crossbreeding outcomes and how adaptability patterns of underutilised genetic diversity in the exotic population can improve crossbreeding responses to specific environments. This result indicates that the correlation between environments secures genetic resources despite different breeding objectives in these environments. The chapter serves as a recommendation on how to apply the framework to inform breeding decisions, focusing on leveraging useful genetic diversity to produce crossbred that are stable yet responsive to changes in environment. Overall, my thesis introduces new methodologies to the context of dairy breeding that contribute to the analysis and understanding of genetic diversity and provides practical tools for uncovering useful genetic variation and analysing its effect on adaptation and performance in tropical environments. Chapter 5 provides a general discussion of the opportunities and challenges for future work in tropical dairy breeding.
Psychological support for post-viral fatigue: evidence from a systematic review and lived experiences of Long COVID using interpretative phenomenological analysis, a portfolio thesis
(The University of Edinburgh, 2026-05-26) Clark, Andrea; Brett, Caroline; Revell, Emily R.
Post-viral fatigue syndromes (PVFS), including myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and Long Covid, are persistent conditions associated with substantial functional impairment and no definitive treatments. Psychological support has been one area of interest, but its role has been debated, particularly in relation to Cognitive Behavioural Therapy (CBT). This has led to growing interest in alternative approaches, such as ‘third-wave’ therapies. However, the evidence base for these approaches in PVFS has not previously been systematically reviewed. In addition, while psychological input is increasingly offered to people with Long Covid in the National Health Service (NHS), little is known about how such support is experienced by individuals with lived experience of PVFS. This thesis therefore aimed to advance understanding of psychological approaches to PVFS by: (1) systematically reviewing the evidence for third-wave therapies in this population and (2) qualitatively exploring how people with Long Covid experience one-to-one psychological or other mental health support within the NHS. The systematic review identified ten eligible studies (two randomised controlled trials [RCTs], two quasi-experimental, four pre–post, two case series) investigating interventions including acceptance and commitment therapy (ACT), mindfulness-based cognitive therapy (MBCT), and mindfulness-based stress reduction (MBSR). Findings indicated improvements in fatigue and quality of life in several studies, with large effect sizes in some studies and sustained gains at 3-12 month follow-up. Anxiety outcomes improved across most studies, whereas evidence for depression and mindfulness were less consistent. However, study quality was low to moderate, with small samples, heterogeneous designs and interventions, and limited fidelity checks, such as therapist competence. The review concluded that third wave therapies show preliminary promise but require further high-quality investigation. The empirical study adopted an Interpretative Phenomenological Analysis (IPA) approach to explore the lived experience of adults with Long Covid who had received one-to-one psychological or other mental health support. Semi-structured interviews were conducted with eight participants with a diagnosis of Long Covid. Analysis identified four themes. The first, The Weight of Waiting, described the emotional distress during the waiting period for accessing support. The second, Being Believed and Validated, captured the relief and significance of having symptoms acknowledged and taken seriously within therapeutic encounters. The third, Therapeutic Fit, reflected the importance of relational connection, collaboration, and flexibility in shaping whether support felt helpful or misaligned. The fourth, Grief, Adjustment and Acceptance, outlined how mental health support provided space to process losses associated with the impact of Long Covid on everyday life and to gradually adapt to life with ongoing symptoms. Findings highlighted the importance of responsive, person-centred support for individuals with Long Covid. Taken together, these studies contribute nuanced insights into the role of psychological support for individuals living with PVFS. Findings provide a preliminary indication that acceptance- and mindfulness-based approaches may benefit this population, while the lived experience research underscores the need for person-centred psychological interventions that are collaborative, validating, and responsive to the challenges of living with Long Covid. This thesis portfolio highlights the importance of integrating patient perspectives into service development and points toward clinical recommendations that prioritise evidence based, person-centred care.
Understanding the balance between osteogenesis and bone marrow adipogenesis in the aetiology of bone disease in experimental chronic kidney disease
(The University of Edinburgh. Royal (Dick) School of Veterinary Studies, 2026-05-26) Promruk, Worachet; Farquharson, Colin; Cawthorn, William; Stephen, Louise; Biotechnology and Biological Sciences Research Council (BBSRC); Chulabhorn Royal Academy
Chronic kidney disease–mineral and bone disorder (CKD-MBD) involves irreversible renal impairment that disrupts mineral balance and leads to skeletal complications collectively known as renal osteodystrophy (ROD). Increased bone marrow adipose tissue (BMAT) is a consistent feature in both patients and animal models of CKD, although its regulation remains unclear. Elevated levels of the Wnt signalling inhibitors sclerostin and dickkopf-1 (DKK1) have been implicated, as they suppress osteogenesis while promoting adipogenesis. This study examined the relationship between BMAT accumulation and bone structure in CKD, with a focus on whether disease progression alters bone marrow mesenchymal stromal cell (BMSC) fate commitment to osteogenic or adipogenic precursors and their subsequent differentiation into mature osteoblasts or adipocytes. I further examined the effects of CKD-related factors—including parathyroid hormone (PTH), fibroblast growth factor 23 (FGF23), phosphate, sclerostin, and indoxyl sulfate—on BMSC differentiation. Furthermore, I evaluated whether dual inhibition of sclerostin and DKK1 with a bispecific antibody could prevent bone loss and limit BMAT expansion in a CKD mouse model. Eight-week-old male C57BL/6J mice were fed a 0.2% adenine-supplemented diet for up to 5-weeks to induce CKD, while control mice received the same diet without adenine. CKD onset was confirmed by elevated plasma blood urea nitrogen, creatinine, PTH and FGF23 from week 3. After 5-weeks, trabecular bone mineral density and microarchitecture were significantly reduced, and cortical bone area and thickness declined as early as week 3. BMAT in the proximal tibia increased progressively, showing a significant rise by week 5 and was negatively correlated with trabecular bone volume. In early CKD (weeks 1–2), BMSCs exhibited greater adipogenic capacity, although the proportions of osteogenic and adipogenic progenitors were unchanged. In vitro, low doses of PTH enhanced osteogenesis, while indoxyl sulfate impaired both osteogenic and adipogenic differentiation; FGF23, phosphate, and sclerostin had no direct effects. Treatment with a bispecific antibody targeting sclerostin and DKK1 for 6-weeks improved trabecular and cortical bone parameters and prevented BMAT expansion in CKD mice. In summary, BMAT accumulation during CKD progresses with disease duration and is not driven by early changes in precursor populations. Systemic CKD factors may modulate stromal cell fate over time, and dual inhibition of sclerostin and DKK1 represents a potential therapeutic strategy for the maintenance of bone health in CKD-MBD.
Acknowledging the whole and the spaces in-between: uncovering mental colonialism through integrative holistic psychotherapy in Kuwait
(The University of Edinburgh, 2026-05-26) Al Rayes , Dima; De Andrade, Marisa; Ross, Anna
Psychotherapy has long been criticized for its lack of inclusivity, particularly among minority and marginalized populations, due to its reductionist biomedical methodologies and limited engagement with holistic approaches (Ali-Faisal, 2020; Barona & Santos Barona, 2003). This study explores the experiences of Kuwaiti healthcare practitioners with psychotherapeutic models examining how integrative, holistic practices can enhance inclusivity in therapeutic settings. Grounded in Participatory Action Research (PAR), six Kuwaiti practitioners, three psychotherapists and three yoga therapists, engaged in three iterative workshops that explored the holistic practices of breathwork, meditation, and bodywork, which are pertinent to Yoga Integrative Therapy (YIT). The collaborative workshops revealed significant tensions in participants' previous experiences with the psychotherapeutic paradigm, including its dominant construction of psychological normality and standardized approaches to care. Conversely, holistic practices, integrated through a person-centered, client-driven lens, were found to help develop an inclusive environment, underscoring the potential of integrative approaches to meet diverse needs. The research also uncovered a “silent narrative” that marked the persistent yet unspoken presence of colonialism, driven by epistemic injustice and mental colonization. Through PAR's responsive and fluid framework, the research acknowledged these silences as a form of epistemic presence, rather than absence. The study offers several recommendations for future research, asserting the importance of initiating more inquiries which will integrate decolonial and holistic approaches within psychotherapy with different demographics and contexts; expanding the current conceptualizations surrounding inclusiveness to include more nuanced definitions, perhaps exploring the notions of person-centeredness, client-drivenness, and holistic care; offering recommendations for practice and policy; and exploring the silent narrative of colonialism in relation to inclusive care.