Experimental medicine approaches linking brain and peripheral immune mechanisms mediating comorbid Depression in people with Rheumatoid Arthritis

Supervisors:

Prof Jonathan Cavanagh, School of Infection & Immunity (University of Glasgow)

Prof Neil Basu, School of Infection & Immunity (University of Glasgow)

Prof Marios Philiastides, School of Psychology & Neuroscience (University of Glasgow)

Summary:

Depression comorbid with rheumatoid arthritis results in poor treatment adherence, worse treatment response, increased disability, and increased mortality. Understanding the mechanisms underlying this has proved to be difficult but experimental medicine methodologies offer a way of resolving this. In these studies, we will explore the role of inflammation as a mechanism leveraging the highly specific “biologic” therapies and using state-of-the-art neuroimaging, biomarker technology and machine learning analysis methods.

Specifically, the student will have the opportunity to join a cross-disciplinary group of clinicians and scientists in a series of experimental medicine studies. The studies use the latest neuroimaging and biomarker technologies to understand the mechanisms whereby systemic inflammation drives depression comorbid with enduring musculo-skeletal disorders such as rheumatoid arthritis. In this studentship there will be training opportunities in neuroimaging, biomarker technology and experimental clinical research as well as advanced machine learning analysis techniques.

Multimorbidity, physical activity and sleep in rural and urban populations in Malawi

Supervisors:

Prof Mia Crampin, School of Health & Wellbeing (University of Glasgow)

Prof Stuart Gray, School of Cardiovascular & Metabolic Health (University of Glasgow)

Dr Alison Price, Faculty of Epidemiology and Population Health (London School of Hygiene & Tropical Medicine)

Dr Owen Nkoka, School of Health & Wellbeing (University of Glasgow)

Summary:

People with multimorbidity, both physical and mental long-term conditions, are less likely to meet the physical activity recommendations. Physical activity levels are also associated with the risk of multimorbidity and life expectancy, based on studies in developed countries. In very low-income African countries like Malawi the physical activity levels are generally high, although worryingly they are declining. Similarly to physical activity, poor sleep is known both to be a cause and a consequence of long-term conditions and this is confirmed in early data from a large population-based survey in Malawi, where multimorbidity was associated with poor reported sleep habits (unpublished data). The “Healthy Lives Malawi” Long Term Conditions (LTC) survey, n=50,000, is collecting data including long term conditions, physical measures and interview data on PA and sleep, provides an ideal and unique platform from which to fill several of these knowledge gaps in a sub-group of the sample.  The aims of the current PhD will be to quantify, using accelerometers, physical activity, and sleep patterns in people with multiple long-term conditions, in urban and rural Malawi, and to investigate their likely importance in the prevention and management of these conditions, leading to the potential for further work designing interventions. This will involve a period of up to 18 months being spent in Malawi within the Malawi Epidemiology and Intervention Research Unit.

Dietary Intervention for Multimorbidity Management: An Interventional Development Study

Supervisors:

Dr Bhautesh Jani, School of Health & Wellbeing (University of Glasgow)

Prof Emilie Combet, School of Medicine, Dentistry & Nursing (University of Glasgow)

Prof Naveed Sattar, School of Cardiovascular & Metabolic Health (University of Glasgow)

Prof Frances Mair, School of Health & Wellbeing (University of Glasgow)

Summary:

Living with overweight or obesity is a risk factor for development of multiple chronic conditions (MCCs). People with MCCs are more likely to have poor health outcomes and health services often struggle to provide effective treatment to these individuals. The evidence-base for weight management in the context of MCCs is limited.

This project will explore the feasibility, acceptability, and development of a fully supported diet-based weight loss programme in people with MCCs. As a part of this fellowship, we will engage with people with MCCs to gain a better understanding of their awareness, knowledge and practices related to weight management, as well as existing barriers and opportunities to co-design a diet-based weight management intervention.

We will pilot the intervention in people with MCCs, focusing not only on weight, but also outcomes such as pain, vitality, and well-being. We will measure biological samples to study how weight loss impacts on surrogate disease markers to understand underlying mechanisms.  We will evaluate findings in the light of socio-economic factors that may make weight management more or less easy.

The approach is critically important since excess adiposity is rarely treated and yet may be one of the key “upstream” risk factors driving MCCs.

UNderstanding the Interplay between BURDEN of Treatment and Capacity in Multimorbidity (UNBURDEN)

Supervisors:

Prof Frances Mair, School of Health & Wellbeing (University of Glasgow)

Prof Sara Macdonald, School of Health & Wellbeing (University of Glasgow)

Prof James Lewsey, School of Health & Wellbeing (University of Glasgow)

Prof Carl May, Faculty of Public Health and Policy (London School of Hygiene & Tropical Medicine)

Summary:

Managing multimorbidity is hard work for patients and their supporters.  Overwhelmed patients are less likely to adhere to treatments and are at risk of poorer outcomes. Existing models and measures of treatment burden assume an arithmetical relationship between workload and capacity, but we do not know whether this is correct. We do not know what aspects of patient and caregiver capacity matter in everyday life and this research aims to address this key gap in knowledge.  We plan collaborative work with people with multimorbidity to:

  • Identify, characterize, and understand key factors that influence capacity to self-manage multimorbidity (through qualitative interviews).
  • Explore how the relationship between the person with multimorbidity and healthcare providers influences capacity (through quantitative data analysis of the Understanding Society dataset).
  • Co-design with people with multimorbidity a checklist of capacity factors and/or potential interventions that will be workable and sustainable (through a “living lab” approach with patients, caregivers, and health professionals).

This study will use mixed methods so will involve development of skills in qualitative research methods (including approaches to data collection/analysis and living lab approaches) and quantitative data analysis, including use of statistical software (e.g., R).  The work should appeal to a broad range of health professionals.

Understanding applicability of clinical trials in multimorbidity

Supervisors:

Prof David McAllister, School of Health & Wellbeing (University of Glasgow)

Prof Frances Mair, School of Health & Wellbeing (University of Glasgow)

Dr Peter Hanlon, School of Health & Wellbeing (University of Glasgow)

Prof Bruce Guthrie, Usher Institute (University of Edinburgh)

Summary:

Multimorbidity (where people have more than one condition) is perhaps the major challenge in evidence-based medicine. People with multimorbidity are under-represented in randomised clinical trials, the bedrock methodology of evidence-based medicine. This problem is compounded by the fact that we lack good measures of multimorbidity in clinical trials, so the exact degree of representativeness is unknown. This makes it difficult for trialists to improve representativeness and for clinicians and guideline developers to assess the usefulness of particular trials when deciding about how to treat and prevent disease in people with multimorbidity.

This PhD project aims to assess the representativeness and applicability of clinical trials to people with multimorbidity using a range of novel methods. The candidate will select a clinical area of interest and analyse existing datasets to address the problem of trial representativeness. They will exploit routinely collected healthcare data (e.g., primary care and hospital data) and data from existing randomised controlled trials. The successful student will gain a deeper understanding of evidence-based medicine, as well as skills and knowledge in analysing routinely collected (big) healthcare data and trial data. This will include skills in data handling and in conducting statistical analyses.

This project would be suitable for any health professional in any area who is interested in using data science approaches to study the problem of multimorbidity.

Childhood neurodevelopmental multimorbidity and chronic physical and mental health outcomes in adulthood

Supervisors:

Prof Helen Minnis, School of Health & Wellbeing (University of Glasgow)

Dr Ruchika Gajwani, School of Health & Wellbeing (University of Glasgow)

Dr Michael Fleming, School of Health & Wellbeing (University of Glasgow)

Summary:

Neurodevelopmental (NDD) multimorbidity is frequent among children in the population and can cause considerable psychosocial and emotional burden, impaired quality of life, and socioeconomic inequality. Yet, compared to multimorbidity in adults, the long-term health outcomes associated with childhood neurodevelopmental multimorbidity has received little attention.

There are known associations between individual NDDs in childhood and chronic physical or mental health disorders in adulthood, but the additive or synergistic effects of multiple NDDs on adult health is unknown. While the role of childhood trauma is likely to be significant, further research is required to establish if and how trauma experience interacts with these heritable factors to influence lifespan health trajectories. 

This project will use two longitudinal datasets (the Edinburgh Child Protection Dataset and the Child and Adolescent Twin Study in Sweden) to examine the associations between neurodevelopmental multimorbidity in childhood and chronic physical and mental health conditions in adulthood, and the relative roles of environment and genetics. The supervisory team has extensive experience in researching the interplay between neurodevelopmental multimorbidity and trauma, including the role of genetics. The post-holder will gain from access to statistical and clinical research expertise and training in data linkage and analysing ‘big’ data - including genetically sensitive cohorts.

Understanding the prevention and management of multimorbidity in minority ethnic populations

Supervisors:

Prof Kate O’Donnell, School of Health & Wellbeing (University of Glasgow)

Prof Vittal Katikireddi, School of Health & Wellbeing (University of Glasgow)

Prof Sara Macdonald, School of Health & Wellbeing (University of Glasgow)

Dr Barbara Nicholl, School of Health & Wellbeing (University of Glasgow)

Summary:

Ethnicity is likely to be a major determinant of multimorbidity, but our current understanding is poor. We know little about patterning, disease clusters, underpinning mechanisms or how minority ethnic communities recognise and live with multimorbidity. Much of the current work is from the US, which focus on different communities to those in the UK, in particular Hispanic and Latino populations.

This project will contribute to our knowledge of multimorbidity in minority ethnic populations, particularly in the UK. We propose a mixed methods approach comprising quantitative data analysis; qualitative exploration of the lived experience of multimorbidity in minority ethnic communities; and elucidation of the impact for policy and practice. Supervised by a multidisciplinary team, the successful applicant will be able to work with us to design a PhD that addresses key questions in this area, but which also gives the Fellow a PhD training that meets their career and development needs. This will include training in data science; social science methods; and the application of theory to address key questions of policy and practice. You will also have the opportunity to work with minority ethnic communities to develop research that addresses their needs.

Achieving meaningful measurement of multimorbidity and its impacts among older adults living in care homes

Supervisors:

Dr Terry Quinn, School of Cardiovascular & Metabolic Health (University of Glasgow)

Dr Susan D Shenkin, Usher Institute (University of Edinburgh)

Prof David McAllister, School of Health & Wellbeing (University of Glasgow)

Dr Jenni Burton, School of Cardiovascular & Metabolic Health (University of Glasgow)

Summary:

Older adults living in care homes are recognised to have complex physical and mental health needs. However, evaluating the scale and impact of multimorbidity in the care home sector is challenging. How the concept of multimorbidity is perceived and understood by those directly affected has also not been explored. These are key barriers when designing effective healthcare systems to support homes and residents and when implementing data collection tools to support evidence-based practice. 

This fellowship offers training in a portfolio of methods necessary for applied health and care research including evidence synthesis, individual participant data analysis, use of secondary data and participatory qualitative methods. It aims to identify meaningful ways of measuring multimorbidity and its impacts among older adults living in care homes. The project will bridge the gap between how measurement has taken place in research studies and how this is undertaken in practice, incorporating experience from residents, relatives, and staff around measurement of multimorbidity and its impact. Ultimately this work will help create recommendations to inform practice and policy. 

Poor oral health in childhood as an early predictor of multimorbidity: The Canary in the Mine?

Supervisors:

Dr Andrea Sherriff, School of Medicine, Dentistry & Nursing (University of Glasgow)

Prof David Conway, School of Medicine, Dentistry & Nursing (University of Glasgow)

Dr Lynda Fenton, Public Health Scotland

Dr Barbara Nicholl, School of Health & Wellbeing (University of Glasgow)

Summary:

Children in Scotland have high levels of tooth decay, and by their first year of primary school over 40% of those from the most deprived areas of Scotland have decay compared to 13% in the least deprived areas. Tooth extraction due to decay is the main reason for children to be admitted to hospital for general anaesthetic.  Tooth decay causes pain, infection, problems with eating and communication as well as poor attendance and performance at school but is also considered the “canary in the mine” of non-communicable diseases and could signal higher risk of developing multiple chronic conditions (multi-morbidity) later in childhood into adulthood. To date, there have been very few studies on multimorbidity in children and none that include poor oral health as an early indicator/ risk for multimorbidity.

This project will utilise our established Child Oral Health Data Lab that has linked multiple Scotland-wide health, administrative and educational databases for multiple birth cohorts.  We will develop a multimorbidity index and explore the trends in prevalence and inequalities over time. We will gain an understanding of the role that poor oral health in early life plays in predicting multimorbidity and in clustering with other chronic conditions with similar underlying social determinants using a variety of statistical modelling techniques.

We will work in partnership with parent groups and other key stakeholders to shape and inform future novel interventions in early life to tackle the common causes of these conditions.

Understanding multi-morbidity among people experiencing severe and multiple disadvantage (SMD) using mixed methods

Supervisors:

Prof Andrea Williamson, School of Medicine, Dentistry & Nursing (University of Glasgow)

Prof Sara Macdonald, School of Health & Wellbeing (University of Glasgow)

Dr Emily Tweed, School of Health & Wellbeing (University of Glasgow)

Summary:

Severe and multiple disadvantage (SMD) is a shorthand term for a constellation of adversities which often overlap in the population, including homelessness, involvement in the criminal justice system, problem substance use, and mental ill-health. Though SMD is associated with profound health inequalities, there is little work to date on the scale of – and responses to – multi-morbidity among this population. Addressing this gap would help better design services and policies able to respond to the needs of people with SMD, in order mitigate the health inequalities they experience.

This project would utilize a mixed-methods approach combining quantitative analysis of existing administrative data from health and non-health sources with qualitative work to explore perspectives from experts by experience in SMD and multi-morbidity, and the people who care for them. It would draw on conceptual frameworks from the multi-morbidity literature, such as candidacy and treatment burden, as well as those relating to social inclusion and health inequalities. Candidates would gain expertise in qualitative data collection and analysis, and working with linked administrative datasets, as well as in undertaking highly policy/practice relevant research and collaborating across multiple sectors for knowledge exchange.

Understanding the impact of polypharmacy in patients with multimorbidity and Chronic Kidney Disease

Supervisors:

Dr Samira Bell, School of Medicine (University of Dundee)

Prof Lesley Colvin, School of Medicine (University of Dundee)

Prof Patrick Mark, School of Cardiovascular & Metabolic Health (University of Glasgow)

Summary:

Polypharmacy is a growing public health threat worldwide associated with adverse patient outcomes driven by ageing and multimorbidity. Chronic kidney disease (CKD) usually occurs in the context of multimorbidity and is associated with poorer outcomes when CKD is one of the multimorbid conditions. Polypharmacy occurring in the context of CKD and multimorbidity is an especially important issue as medications used to optimise health outcomes may cause harm either in isolation or when used in combination in patients with CKD due to reduced renal clearance, exacerbated adverse drug interactions and/ or altered metabolism.

The overarching aim of this PhD studentship is to explore factors associated with adverse outcomes from polypharmacy in patients with multimorbidity and how CKD impacts on these. Specific aims will be developed by the candidate with the supervisory team and can include the following:

  1. Understand the literature relating to polypharmacy, multimorbidity and CKD.
  2. Explore risk factors for adverse outcomes from polypharmacy in patients with multimorbidity.
  3. Embed Patient and Public Involvement (PPI) within the project.
  4. Identify, characterize, and understand key factors that influence prescribing practices in patients with CKD and multimorbidity (through qualitative interviews).
  5. Develop an intervention to improve prescribing practices in patients with polypharmacy, CKD and multimorbidity.

Predicting onset of multimorbidity and identification of its causal pathways in diabetes: Practice-oriented prototyping for primary care and public health appli

Supervisors:

Dr Jan R. Boehnke, School of Health Sciences (University of Dundee)

Dr Moneeza Kalhan Siddiqui, School of Medicine (University of Dundee)

Prof Colin Palmer, School of Medicine (University of Dundee) 

Summary:

Multimorbidities pose a significant cost to our societies and adversely affect individuals' quality of life and their ability to participate meaningfully. Since over 85% of people living with diabetes suffer from at least one other long-term health condition, addressing risks for the onset of diabetes and subsequent multimorbidity is critical. Working with supervisors who are specialists in large-scale multimodal data analysis and multimorbidity (including mental health & illness), the PhD will combine approaches from genetic and social epidemiology to prototype practical applications for public health/ primary care for risk prediction; and shed light on causal factors for early targeted intervention.

The PhD combines two under-utilised perspectives: firstly, it aims to not only consider an individual’s clinical and social characteristics as many existing approaches do, but also the interaction of their genes with these characteristics; and secondly it aims to organise the work according to the two different tasks of 'prediction' and 'causal identification', which are in existing work often not fully separated. Dundee is ideally placed to support this challenge- and curiosity-driven research as it is home to the GoDARTS and SHARE cohorts that have been an integral part of high-impact global diabetes genetics research.

Intergenerational multimorbidity and pathways to oral health in early childhood

Supervisors:

Dr Heather Cassie, School of Dentistry (University of Dundee)

Dr Louise Marryat, School of Health Sciences (University of Dundee)

Prof Janet Clarkson, School of Dentistry (University of Dundee)

Summary:

Dental disease is preventable, yet dental decay is the most prevalent disease worldwide. Much of this begins in childhood and is influenced by a range of social and physiological factors. Dental decay affects child general health and quality of life, impairing growth and cognitive development and interfering with nutrition and school attendance. In adulthood multimorbidity is cited as a key factor impacting oral health and raising calls for new models of care, however little is known of its impact on child oral health. As child oral health is inextricably linked to parental oral, physical and mental health, this project will bring together linked administrative and/or cohort data relating to parents and children to explore pathways to oral health in childhood, with specific reference to multimorbidity in both parents and children. Patient and public involvement is a core element of this project. Patient and public representatives will be integral to study design and implementation and will provide data to inform the research questions at all stages.

The post-holder will work with an interdisciplinary team of supervisors, along with parents of children with chronic health conditions, to further develop this proposal. The project will address important practice and policy-relevant research, informing future care pathways for children experiencing multimorbidity. The student will join an innovative and supportive team, developing skills in the use of large complex datasets, advanced statistics, evidence-based healthcare, qualitative and PPI methods and innovative dissemination.

Implementing Genome-Informed Precision Medicine for Multimorbidity associated Polypharmacy

Supervisors:

Dr Alexander Doney, School of Medicine (University of Dundee)

Prof Isla Mackenzie, School of Medicine (University of Dundee)

David Coulson, Director of Pharmacy (NHS Tayside)

Summary:

Patients with more than one long term condition are often exposed to polypharmacy which increases the likelihood of unwanted side effects from medications and further compounds the growing clinical challenge of managing multimorbidity. As understanding grows of how an individual patient’s genotype determines the safety and effectiveness for increasing numbers of commonly prescribed medications, and the technologies for obtaining this information rapidly reduce in cost, healthcare organisations are actively considering how to implement this precision medicine approach. Almost all patients carry at least one genetic variant that influences how a particular medication works so genome-informed precision medicine could have significant beneficial impact in the medical management of multimorbidity with polypharmacy. There are a growing number of precision medicine implementation exemplars being established in NHS Tayside, translating research into clinical practice.  These initiatives are highlighting some of the many challenges in making this technology more widely available for the benefit of patients in the everyday healthcare setting. In this PhD programme, using a mixed methods approach embedded within the MRC Complex Intervention Framework, the candidate will work within these various initiatives to investigate barriers and incentives for making precision medicine more widely available in the NHS as well as exploring a framework for generating evidence of effectiveness in a learning healthcare approach.

Understanding the impact of multiple simultaneous Drug-drug Interactions in Polypharmacy

Supervisors:

Prof Jacob George, School of Medicine (University of Dundee)

Prof Roland Wolf, School of Medicine (University of Dundee)

Prof Bruce Guthrie, Usher Institute (University of Edinburgh)

Prof Chim C Lang, School of Medicine (University of Dundee)

Summary:

There is an increasing prevalence of polypharmacy worldwide and therefore, a potential for adverse Drug-drug interactions (DDI) to occur when multiple drugs are given. Most drug interaction checkers that are currently available and employed by clinicians perform pairwise comparisons. Therefore, even if multiple drugs are entered into the calculator, each relationship is assessed in a pairwise fashion. There is no data on the combined system-wide impact of complex DDIs on individual drug components of treatment regimens involving concomitant delivery of multiple drugs. Many of these commonly prescribed medications are metabolized via the cytochrome P450 system in the liver (Cyp). Drugs that are Cyp inhibitors/inducers/substrates when given together may result in both toxicity from one agent and loss of efficacy in another. In the context of multiple agents, this impact is poorly understood.

The aim of this proposal is to understand the role of DDIs with a focus on how Cytochrome P450 (Cyp) metabolism affects the pharmacokinetics and pharmacocodynamics (PKPD) of multiple drugs when co-prescribed in patients on polypharmacy.The proposal will include literature reviews, a PK/PD sampling study, genetic analysis of Cyp polymorphisms and an analysis of large datasets for validation of prior findings.

Drug related deaths among women in Scotland: Identifying complex and frequently co-occurring physical and mental health conditions, polypharmacy, and social exp

Supervisors:

Dr Louise Marryat, School of Health Sciences (University of Dundee)

Prof Lesley Colvin, School of Medicine (University of Dundee)

Prof Blair Smith, School of Medicine (University of Dundee)

Dr Rosie Seaman, School of Health & Wellbeing (University of Glasgow)

Summary:

Scotland has the highest number of Drug Related Deaths (DRDs) in Europe and DRDS have been increasing. Although the absolute number of DRDs is higher among men, the relative increase in DRDs has been greater among women.  Research examining the relative increase in DRDs among women highlights specific pathways leading to DRD for women, particularly the role physical and mental multimorbidity, polypharmacy, and social experiences including trauma, and relationship difficulties, intimate partner violence, and child custody. Traditionally, research has looked at the presence or absence of single morbid conditions among all women and failed to account for the complexity of co-occurring physical and mental conditions, polypharmacy, and social experiences and how these may differ among women who have and have not had a previous NFO. This project will use an existing and unique population wide administrative data set to address these limitations and inform the development of interventions aimed at reducing NFO and DRD among women in Scotland. Patient and Public Involvement will be integral to this project: alongside broader public engagement e.g. through events such as Dundee’s Soapbox Science, the PhD will also include co-production methods at every stage, seeking input from women with lived experience and relevant stakeholders. The PhD will be based in the Drug Harm Prevention Research Group, University of Dundee, in collaboration with University of Glasgow.

Improving the understanding of serious infection risk, outcomes, and treatment in people with multimorbidity

Supervisors:

Dr Charis Marwick, School of Medicine (University of Dundee)

Dr Huan Wang, School of Medicine (University of Dundee)

Prof Bruce Guthrie, Usher Institute (University of Edinburgh)

Summary:

Risk of E. coli bloodstream infection and associated adverse outcomes are reportedly higher in people with multimorbidity but published reports do not adequately account for physical and/or mental health multimorbidity and frailty. There is limited information about drug-drug and drug-disease interactions in relation to recommended antibiotic therapy for E. coli infection in people with multimorbidity and associated polypharmacy, with implications for clinical policy and practice.

The overall aim is to improve understanding of the interactions between multimorbidity, risk of E. coli infection, antibiotic resistance and adverse outcomes, and the implications for the treatment and prevention of infections.

Objectives can be shaped by student’s interest/focus but broadly include to:

  • Quantify rates of E. coli bloodstream infection, antibiotic-resistant infection and adverse outcomes in people with/without multimorbidity.
  • Examine drug-drug and drug-disease interactions related to antibiotics used for the treatment of E. coli infections in people with multimorbidity and polypharmacy.
  • Explore implications for policy and practice.

Primarily a quantitative data project, which could include statistical analyses using logistic regression, multilevel and time-to-event (including competing risks) modelling, and/or artificial intelligence (AI) approaches, there is scope to do a mixed methods project incorporating interviews, focus groups and/or observations with professional stakeholders and/or patient or public partners. 

Using big data and genomics to reduce harm from polypharmacy

Supervisors:

Prof Ewan Pearson, School of Medicine (University of Dundee)

Prof Jacob George, School of Medicine (University of Dundee)

Summary:

With increasing age and multimorbidity, polypharmacy is common.  In 2010, 20.8% of the Tayside population were prescribed ≥ 5 drugs and 5.8% ≥ 10 drugs, with increased polypharmacy with increasing age, deprivation and care home residence.  Some populations are particularly exposed to polypharmacy – in pilot data from Tayside 30% of patients with Type 2 diabetes are treated with 10 or more drugs.

It is only recently that large clinical databases with linked genomics have become available to enable a ‘big data’ approach to investigate adverse outcomes of polypharmacy, and the impact of genetic variants that alter drug pharmacokinetics and dynamics. 

The overarching aim of this PhD is to identify and reduce harms from polypharmacy in an ageing multimorbid population.  Specific aims will be developed by the candidate with the supervisory team including:

  1. Investigate the scale of known drug-drug interactions in the UK.
  2. Identify novel beneficial and harmful drug-drug interactions in the UK, with a focus on people with diabetes.
  3. To investigate the interaction of known genetic variants in drug metabolism genes on outcomes of commonly used drugs or drug combinations.

This work will underpin future implementation development to reduce prescribing harm, including potential routine use of genetics-guided prescribing.

The fellow will work with large data sets developing skills in Python, SQL and R, statistical modelling including pharmacoepidemiology and pharmacogenomics.    The student will be linked to policy groups including Scottish Polypharmacy Working Group (Guthrie), SMC (George), and Scottish Pharmacogenomics Working group (Pearson).  We welcome applications from people with any clinical discipline.

Predicting harm from prescribed drugs in people with polypharmacy, multimorbidity and frailty

Supervisors:

Prof Bruce Guthrie, Usher Institute (University of Edinburgh)

Dr Atul Anand, Centre for Cardiovascular Science (University of Edinburgh)

Dr Daniel Morales, School of Medicine (University of Dundee)

Summary:

The project is suitable for a student from any discipline wishing to develop skills in quantitative data analysis in the field of prescribing safety. Our current understanding of drug risk is relatively narrow, focusing on pairwise drug-drug and drug-disease interactions, which is of limited relevance in polypharmacy where multiple interactions are typically present, and where interactions with frailty may mediate risk of serious harm. The student will choose which kind of outcome they wish to focus on (e.g., falls, fractures, delirium, acute kidney injury, bleeding). Pharmaco-epidemiological methods used will include nested case-control, cohort with time-varying covariates and accounting for competing mortality risks, and self-controlled case-series, in order to examine the cumulative impact of prescription of multiple drugs with shared side-effects, cumulative risk related to duration of treatment, and exploring how frailty/comorbidity mediate risk of serious harm. The supervisors are clinical academics interested in polypharmacy and pharmaco-epidemiology, have excellent links with national guideline developers and medicine regulators, and will support the student to ensure effective public and patient involvement. The student will therefore gain high-level expertise in applying complex quantitative methods in large datasets to address important clinical questions, and in translating findings into impact on understanding, policy and practice.

Understanding transitions in housing and transitions in care in people with multimorbidity

Supervisors:

Prof Bruce Guthrie, Usher Institute (University of Edinburgh)

Prof Heather Wilkinson, School of Health in Social Science (University of Edinburgh)

Dr Andrew Kingston, Population Health Sciences Institute (Newcastle University)

Summary:

People with multimorbidity commonly experience transitions in housing and/or care including starting or intensifying care-at-home and moves to sheltered or residential care. These may be planned or unplanned, but their frequency and individuals’ and families’ experience of them is poorly understood. The aim of this PhD is to use mixed quantitative and qualitative methods to better understand transitions. The study will use quantitative methods (e.g. multi-state models, multilevel survival analysis) to examine frequencies and predictors of transitions in large routine datasets, and qualitative analysis of interview and case-study data to examine individual, family and professional perceptions of transitions, drawing on relevant social theory as lenses for the analysis (e.g. candidacy theory to understand how individuals, families and professionals perceive who is a ‘candidate’ for transition, which may mediate whether transitions are planned/unplanned). We welcome applications from professionals from any clinical discipline, and the student themselves will shape the project working with the supervisors and public contributors, including deciding the balance of quantitative/qualitative focus. The project will be based in the Advanced Care Research Centre (www.edin.care) which is a highly interdisciplinary environment, providing support for public and patient involvement and translation of research into policy and practice. 

Cardiovascular risk prediction modelling in people with mental illness

Supervisors:

Dr Caroline Jackson, Usher Institute (University of Edinburgh)

Dr Nynke Halbesma, Usher Institute (University of Edinburgh)

Dr Rona Strawbridge, School of Health & Wellbeing (University of Glasgow)

Summary:

People diagnosed with severe mental illness (SMI) have a reduced life expectancy. This is largely due to natural causes of death of which cardiovascular disease is the most common. Robust cardiovascular risk scores are important for identifying high risk patients who would benefit most from treatment. Prediction of cardiovascular risk is usually based on age, sex, smoking status, hypertension, and blood lipid profile, using cardiovascular risk scores. However, the available cardiovascular risk scores such as Framingham have been developed in populations without people with SMI and subsequently underestimate the risk in people with SMI which potentially leads to under treatment. Therefore, tailored cardiovascular risk models for this vulnerable group or general population risk models with SMI status added to the predictors are necessary. The QRISK3 model (a general population score) and PRIMROSE (a tailored score for patients with SMI) have been developed, but neither include depression as a predictor. Before implementation in clinical practice external validation is required to assess performance in terms of discrimination and calibration in other settings. The aim of this PhD project is to evaluate the performance of one or both of the QRISK3 and PRIMROSE models in datasets from within and outside the UK, expand the models to include other mental health disorders and investigate improvement of models through inclusion of novel predictors. 

Co-existing mental and physical multimorbidity, adverse events, and longer term outcomes in hospitalised patients with sepsis

Supervisors:

Dr Nazir Lone, Usher Institute (University of Edinburgh)

Dr Jacques Fleuriot, School of Informatics (University of Edinburgh)

Prof Manu Shankar-Hari, Centre for Inflammation Research (University of Edinburgh)

Summary:

Sepsis is a common, life-threatening condition, causing over 45,000 deaths annually. Sepsis survivors commonly experience new physical and mental health problems. Multimorbidity is common in patients who develop sepsis, of whom 20% of critically ill patients have mental health comorbidity and is associated with higher mortality and post-discharge rehospitalisation. However, the impact of co-existing mental and physical multimorbidity in the context of sepsis is unclear. In particular, its impact on adverse events, outcomes and recovery has not been previously investigated.

The overall aim of the studentship is to evaluate the impact of co-existing mental and physical multimorbidity on in-hospital adverse events and outcomes, and longer-term recovery, for hospitalised patients with sepsis in order to inform improvements in care quality.  

During the studentship, epidemiological analyses will be undertaken to determine associations between co-existing mental illness/physical multimorbidity and both acute outcomes and post-discharge recovery, underpinned by explicit causal frameworks. Subsequently, clusters of mental/physical multimorbidity will be examined using artificial intelligence methods.

The studentship will provide training in epidemiology, causal inference, and machine learning methods. The student will benefit from the vibrant, academic environment in the Usher Institute and synergistic learning from other multimorbidity work undertaken by the team (https://edin.ac/3CqoERz).

Multimorbidity as an index condition for clinical trials, meta-analyses and clinical guidelines-is a paradigm shift needed?

Supervisors:

Prof Gillian Mead, Usher Institute (University of Edinburgh)

Prof Bruce Guthrie, Usher Institute (University of Edinburgh)

Dr Alex Todhunter-Brown, NMAHP Research Unit (Glasgow Caledonian University)

Summary:

Multimorbidity, defined as at least two different chronic diseases, is becoming more common as the population ages, and people from low socioeconomic groups are more likely to have comorbidity. Yet evidence about the effectiveness of treatments typically focuses on single diseases; thus, leading to difficulties translating the results of clinical research into clinical practice. This PhD will address the critical question of whether a paradigm shift is needed in our approach to clinical trial design.  There will be three broad elements to this work a) how Cochrane reviews approach comorbidity, b) exploring in those trials which are included in Cochrane reviews the extent to which patients with comorbidity are represented and c) in large datasets of individual patients, is it possible to identify patterns, or clusters of comorbid disease, who have similar prognosis and respond in similar ways to different treatments?  Patient and public involvement will be integral to this work-right from the start when the research questions are refined, to dissemination and knowledge exchange. This interdisciplinary project is suitable for a clinical researcher from any discipline and represents an outstanding opportunity to work with leading experts in the field of multimorbidity in clinical trials-and to develop into an independent researcher in this field.

Multimorbidity in Pregnancy

Supervisors:

Prof Rebecca Reynolds, Queen’s Medical Research Institute (University of Edinburgh)

Prof Andrew McIntosh, Centre for Clinical Brain Sciences (University of Edinburgh)

Dr Clara Calvert, Usher Institute (University of Edinburgh)

Summary:

Women who have multiple health problems (‘multimorbidity’) prior to pregnancy are at increased risk of adverse pregnancy outcomes. We plan to use data on > 2 million pregnancies to understand more about how different physical and mental health problems cluster together in pregnancy, and how these are linked to pregnancy complications for mother and child. We will start to unpick the potential underlying biological and /or social determinants. The ultimate aim is to produce high quality evidence that would guide clinical practice to prevent pregnancy complications and to optimize long-term maternal and offspring health for pregnant women with multimorbidity.

Gene by environment interactions of multimorbidity across global populations

Supervisors:

Prof Albert Tenesa, Roslin Institute (University of Edinburgh)

Prof Bruce Guthrie, Usher Institute (University of Edinburgh)

Summary:

Multi-morbidity is a major health problem, increases with age, and clearly depends on social economic background as it hits the less well-off a decade or more before the most affluent. Although the genetics of many of the diseases that cluster with age have been studied individually, they have yet to be studied in combination, which will provide new biological insight beyond what can be learned when studying diseases in isolation. Such biological insight can help develop better treatment and management strategies for multi-morbidity. Furthermore, how genes linked to multi-morbidity may be manifest differently depending on individual characteristics including socio-economic background both within countries and across countries has so far not been studied. This project aims to understand how genome-phenome associations specific to multimorbidity vary by socioeconomic status and will capitalise on the power of big data and international collaborations to answer an important question that may help develop tailored strategies to manage and treat multi-morbidity. Students will also learn how to effectively deliver public and patient involvement in the conduct of the research. The project is suitable for students wanting to develop genetic epidemiology skills and with an interest in inequalities and/or gene-environment interaction.

Avoiding social catastrophes in those with multimorbidity

Supervisors:

Prof Peter D Donnelly, School of Medicine (University of St Andrews)

Prof Colin McCowan, School of Medicine (University of St Andrews)

Summary:

A key concern for older adults living with multimorbidity is the concept of frailty and the risk of subsequent falls.  This study will explore data form health care records to identify multimorbidity in older patients and try to identify those at greatest risk of falls using machine learning techniques.

The fellow would also interview patients who had suffered falls to try and learn their “lived experience” and using the common themes from the interviews select models to best match what patients reported happening within their lives.

The fellow will develop knowledge and expertise in machine learning using routine healthcare and how to integrate this in a mixed methods approach with findings from interviews to help best answer key clinical questions. 

 

Why are people with multimorbidity less likely to take up cancer screening opportunities?

Supervisors:

Prof Colin McCowan, School of Medicine (University of St Andrews)

Prof Katie Robb, School of Health & Wellbeing (University of Glasgow)

Dr Sarah Mills, School of Medicine (University of St Andrews)

Summary:

We know that screening for cancer saves lives, but not everyone who is asked to screen does it, whether it is for cervical, bowel or breast cancer.  We know that people value screening and are generally enthusiastic about it, but we do not know enough on who might then decide not to screen or why.

Previous work from the supervisors suggested that women in Glasgow who suffered from multimorbidity were less likely to take part in bowel cervical or breast screening.  However, we did not find out whether it was certain conditions that people had that meant they decided not to take part, or what other reasons there might be.  We also do not know if it will be the same across Scotland or if we see the same thing in men. 

This PhD will use health records related to screening to explore if people with multimorbidity are less likely to take part in breast and cervical screening for women and in bowel screening for both men and women.  We will look to see if there are particular combinations of disease that people have which means they are less likely to take part.

We will also use the data to invite people for interview where we know what conditions they have and whether they take part in screening.  The interviews will help us understand why people with multimorbidity choose not to take part in screening.

This information will allow us to know what groups of people we could potentially target to encourage then to screen but also help us think what might help these people take part in screening programmes.

Neurodevelopmental multimorbidity during the life course

Supervisors:

Dr Silvia Paracchini, School of Medicine (University of St Andrews)

Prof Alex Baldacchino, School of Medicine (University of St Andrews)

Dr Michelle Luciano, School of Philosophy, Psychology and Language Sciences (University of Edinburgh)

Dr Judith Allardyce, The Queens Medical Research Institute (University of Edinburgh)

Summary:

Neurodevelopmental conditions (e.g., dyslexia and ADHD) and psychiatric disorders (e.g., schizophrenia, anxiety, depression, PTSD and substance use disorder) frequently co-occur and are caused by a complex interplay of multiple genetic and environmental factors. In spite of strong correlations, most conditions tend to be studied in isolation.

This project aims to understand the multi-morbid cluster of neurodevelopmental and psychiatric conditions through a longitudinal approach. The projects will combine the detailed assessment of clinical manifestations at different ages with genomic analysis. This approach will allow distinguishing general versus condition-specific risk factors. Access to multiple resources ranging from clinical, longitudinal (e.g., ALSPAC) and multi-layers “omic” cohorts (e.g., UK Biobank) is already in place. The methods will include cutting-edge data science approaches applied to multidimensional (e.g., genomics, clinical and demographic) datasets. The successful candidate will work with four supervisors (Silvia Paracchini, Alex Baldacchino Michelle Luciano and Judith Allardyce) who have expertise in genomics, behavioural genetics, neurodevelopmental and psychiatric disorders. Their affiliations to large international consortium will provide opportunities to develop the project along multiple paths.

In the short term, we aim to increase awareness around the complexity of these conditions, their heterogeneous manifestations along the life course and the interplay of multiple risk factors. The long-term goal is to develop better risk estimates and preventative interventions.

The impact of multimorbidity on trajectories of care for tuberculosis and HIV in East Africa

Supervisors:

Dr Derek Sloan, School of Medicine (University of St Andrews)

Dr Christine Sekaggya-Wiltshire, Infectious Diseases Institute (Makerere University)

Prof Stellah Mpagama, Kilimanjaro Christian Medical University College/Kibong’oto Infectious Diseases Hospital (KIDH)

Dr Adeniyi Fagbamigbe, School of Medicine (University of St Andrews)

Summary:

Tuberculosis (TB) is a major public health problem in Tanzania and Uganda, particularly amongst people who are also living with Human Immunodeficiency Virus (HIV). Multimorbidity with long-term physical and mental health conditions alongside TB/HIV may affect delivery and outcomes of care. However, in East Africa, information is sparse on the extent and impact of multimorbidity in this context, making it difficult to design interventions to address the problem. Data on psychological illness (mood, psychotic, and behavioural disorders) in patients with TB/HIV are particularly lacking.

This project will be sited at the Infectious Diseases Institute, Makerere University, Uganda and Kibong’oto Infectious Diseases Hospital, Tanzania. It has been designed, and will be co-supervised, by clinical and health data science academics at both locations and at the University of St Andrews in Scotland. Retrospective analysis of an existing database will be used to understand patterns of multimorbidity in Ugandan HIV-TB patients, whilst prospective data collection from patients who are newly initiating TB treatment will be used to describe the impact of physical and mental health multimorbidities on trajectories and outcomes of TB care.

Project results will be provided to NTP policymakers, as a direct contribution to improving clinical services for this vulnerable population.