Unravelling the link between infection and non-communicable diseases to enable a paradigm shift in the prevention and treatment of chronic disease

About the Project

Title: Unravelling the link between infection and non-communicable diseases to enable a paradigm shift in the prevention and treatment of chronic disease

Synopsis: This project aims to investigate whether exposure to specific infections across the life course contributes to the development of major chronic diseases, and whether vaccination or immune responses modify these risks. Using large-scale linked health records and cohort data (CPRD, SAIL, UK Biobank), it will systematically identify and evaluate infection-chronic disease relationships.

Details: Potential links between infections and non-communicable diseases (NCD) have been recognised for decades. For example, observational epidemiological studies have demonstrated an increased risk of myocardial infarction, stroke and venous thromboembolism after both viral and bacterial infections, most recently exemplified by studies of vascular events after COVID-19, thought to be due to the inflammatory and/or pro-thrombotic effects of the viral infection.1

There is also increasing evidence for a direct causal role of several different infections in a range of non-communicable, chronic diseases. For example:

• the proven causal association between sexual transmission of certain subtypes of herpes papilloma virus (HPV) and cervical cancer, leading to the introduction of vaccination against HPV in teenagers;
• mounting evidence for a causal link between Epstein Barr virus (EBV) infection and later development of multiple sclerosis (MS) via the immune mechanism of molecular mimicry, with clinical trials now underway to investigate whether anti-EBV treatments or vaccines are effective in prevention or treatment of MS.
• analyses of large-scale, population-wide linked health records suggest a causal association of shingles vaccine (Shingrix) with reduced dementia diagnoses, suggesting that shingles vaccine may prevent – or slow progress of – dementia;2
• several studies have shown links between toxoplasmosis and later development of schizophrenia, with the suggestion that chronic toxoplasma infection might trigger or worsen psychosis, opening up the possibility of new treatments to prevent or treat schizophrenia.

Access to and appropriate analysis of linked health records from whole populations, and of data from large population-based longitudinal studies with bio-samples,3 could be used to address systematically the potential associations between exposure to infections at different points across the life course and the later development of a wide range of chronic diseases (including cancers, vascular diseases, neurodegenerative diseases and serious mental health disorders). Similarly, these large-scale data assets could be used to study the potential protective effect of vaccination against various infections and later chronic disease.

This PhD project aims to use large scale UK population datasets to systematically investigate potential causal / protective associations of a wide range of infections (mainly viruses) and disease outcomes.

The project has three main objectives.

1. To identify associations between exposure to selected pathogens – particularly those capable of latent infection, and the subsequent development of chronic diseases.
2. To examine whether vaccination and/or treatment against these pathogens is associated with altered risk of later chronic disease.
3. To explore life-course timing of infectious exposure and identify potential critical windows during which infections may have long-term health consequences.

The project will apply advanced causal inference approaches, longitudinal modelling and quasi-experimental designs to: the Clinical Practice Research Datalink (CPRD) and Secure Anonymised Information Linkage (SAIL) Databank for population-based longitudinal studies examining infection histories, vaccination records and subsequent disease outcomes across millions of individuals; and data from UK Biobank, which combines extensive phenotyping, genetic data and stored biological samples with linked health records.

This research is inherently interdisciplinary, integrating infectious diseases and health data science. It has the potential to disrupt conventional models of NCD causation and identify novel preventive strategies, including vaccination or targeted therapies against specific pathogens.

Potential impact: By leveraging large-scale, longitudinal routine healthcare data and biomarker-based cohort data, this work seeks to inform targeted prevention and treatment strategies, early identification of high-risk patients, and clinical decision-making to improve care and resilience among individuals.

Training: Core technical areas of learning will include epidemiology, health data science, and computational approaches in using large datasets from different sources and modalities, and science-policy and clinical translation, including working in the Safe Haven with electronic health records. The student will develop or extend their programming expertise in programming languages, such as R or Python. We will encourage developing and sharing code for the wider scientific community through platforms such as GitHub. Transferable skills in scientific communication and collaboration will be fostered via the interdisciplinary supervisory team and participation in different conferences and through publications. The student will be able to leverage the existing training courses from other Doctoral Training Programmes as well.

Recruitment: A student with relevant background (probably MSc) in epidemiology and / or data science and with significant quantitative / analytic capabilities preferred

Apply: All applications must be submitted through the Future Medicine PhD fellowships website.

Funding Notes

Students will receive a stipend at UKRI levels, plus £30K in travel and research funds across all three years of the fellowship. All University fees will be covered.

The fellowships are open to students who are eligible for home fees at Edinburgh - i.e. you must be a UK national, or have settled status, and have. been "ordinarily resident" in the UK for the three years immediately before the start of the fellowship. Other international applicants are not eligible for these fellowships.