2026-27 Project (Gore-Langton & Warren-Gash)

How does severe mental illness affect risk of dementia?

SUPERVISORY TEAM

Supervisor

Dr Georgia Gore-Langton at LSHTM
Faculty of Epidemiology & Population Health, Department of Non-communicable Disease Epidemiology
Email: georgia.gore-langton@lshtm.ac.uk

Co-Supervisor

Professor Charlotte Warren-Gash at LSHTM
Faculty of Epidemiology & Population Health, Department of Non-communicable Disease Epidemiology
Email: charlotte.warren-gash@lshtm.ac.uk

PROJECT SUMMARY

Project Summary

People with severe mental illness (SMI) have been found to have a higher risk of all-cause dementia than people without SMI, although results are heterogeneous. While there is more evidence for an association between schizophrenia and dementia, few studies have investigated risk associated with bipolar disorder. There also remains uncertainty around whether SMI independently predisposes to dementia beyond the fact that people with SMI are also more likely to have other risk factors (including cardiovascular disease). This PhD project aims to use large longitudinal electronic health records and causal inference methods to investigate casual questions around SMI and dementia. Addressing these questions will improve understanding of SMI-associated dementia risk, informing potentially modifiable targets for intervention.

Project Key Words

Mental health, dementia, electronic health record

MRC LID Themes

Health Data Science
Translational and Implementation Research

Skills

MRC Core Skills

Quantitative skills

Skills we expect a student to develop/acquire whilst pursuing this project:

Systematic review and meta-analysis skills
Experience cleaning of large linked electronic health record dataset
Experience of the generation of codelists, and cohort study design and analysis methods
Advanced skills in statistical packages such as R or STATA
Causal inference skills, including causal mediation analysis methods
In depth knowledge of the strengths and limitations of using electronic health records for epidemiological research
Experience of research ethics and data security

Routes

Which route/s are available with this project?

1+4 = Yes
+4 = Yes

Possible Master’s programme options identified by supervisory team for 1+4 applicants:

LSHTM – MSc Epidemiology
LSHTM – MSc Health Data Science
LSHTM – MSc Medical Statistics

Full-time/Part-time Study

Is this project available for full-time study? Yes
Is this project available for part-time study? Yes

Location & Travel

Students funded through MRC LID are expected to work on site at their primary institution. At a minimum, all students must meet the institutional research degree regulations and expectations about onsite working and under this scheme they may be expected to work onsite (in-person) more frequently. Students may also be required to travel for conferences (up to 3 over the duration of the studentship), and for any required training for research degree study and training. Other travel expectations and opportunities highlighted by the supervisory team are noted below.

Day-to-day work (primary location) for the duration of this research degree project will be at: LSHTM – Bloomsbury, London

Travel requirements for this project: None

Eligibility/Requirements

Particular prior educational requirements for a student undertaking this project

Minimum standard institutional eligibility criteria for doctoral study at LSHTM
Applicants must hold, or expect to obtain before the start of the PhD, a relevant MSc (Epidemiology, Health Data Science or Medical Statistics) awarded with good grades, or have a combination of relevant qualifications and experience which demonstrates equivalent ability and attainment.
This project can also be awarded as 1+4 (1-year MSc programme + 4-year PhD candidature). Through this route, a relevant BSc awarded with good grades is required.

Other useful information

Potential Industrial CASE (iCASE) conversion? = No

PROJECT IN MORE DETAIL

Scientific description of this research project

Project objectives
Objective 1: To conduct a systematic review of the literature assessing any associations between SMI and dementia risk
Objective 2: To investigate whether SMI is associated with dementia in electronic health records using a matched cohort design.
Objective 3: To apply casual inference methods to investigate potential mediating factors (including cardio-vascular disease and BMI) between SMI and dementia risk

Techniques to be used
Objective 1: A systematic review will first be carried out to assess and appraise existing evidence for any associations between SMI and dementia, including disaggregating bipolar, schizophrenia, and dementia types and Alzheimers Disease.

Objective 2: Informed by findings from the systematic review, the PhD student will design a cohort study to investigate the association between SMI diagnoses and dementia risk using UK primary care electronic health record data from the Clinical Practice Research Datalink (CPRD) Aurum linked to hospital admissions data (Hospital Episode Statistics). Data will be analysed using survival analysis methods such as Cox proportional hazards regression.

Objective 3: The student will apply casual mediation methods to linked primary (CPRD) and secondary (HES) data to investigate the extent to which risk factors such as cardiovascular disease and body mass index mediate an association between SMI and dementia risk.

Confirmed availability of any required databases or specialist materials: LSHTM has a multi-study license, renewed each year, to access linked CPRD data. The supervisory team is highly experienced at accessing and using these datasets and a wealth of helpful material is available through the Electronic Health Records research group (including a regularly updated intranet site).

Potential risks to the project and plans for their mitigation: Any delays in receiving full linked datasets will be mitigated through providing the student with access to a random sample of one million anonymised records on which to generate statistical code.

Additional information from the supervisory team

The supervisory team has provided a recording for prospective applicants who are interested in their project. This recording should be watched before any discussions begin with the supervisory team.

Gore-Langton & Warren-Gash Recording

MRC LID LINKS

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Full list of available projects: MRC LID Projects
For more information about the DTP: MRC LID About Us