Chronic pain, analgesic prescribing, and cognitive decline

Precision Medicine Project - Chronic pain, analgesic prescribing, and cognitive decline

Supervisor(s): Dr Chloe Fawns-Ritchie, Prof Riccardo Marioni, Prof Simon Cox, Prof Sara Hägg (Karolinska Intitutet) & Dr Barbara Nicholl (University of Glasgow)
Centre/Institute: School of Philosophy, Psychology and Language Sciences

Background: 

Chronic pain, typically defined as pain lasting more than 3 months, is the leading cause of disability worldwide [1]. Chronic pain, which increases substantially with age, is consistently associated with lower cognitive function and it is increasingly associated with elevated rates of cognitive decline and dementia [2]. The mechanisms connecting chronic pain to cognitive decline remain poorly understood.

Opioids and other analgesics, which are commonly prescribed to manage pain, are often proposed as potential contributors to cognitive decline, possibly via their adverse effects on respiratory, cardiovascular and inflammatory systems as well as their direct impact on the central nervous system [2]. The evidence linking analgesics to cognitive outcomes is mixed. Some studies find that certain types of analgesics, particularly opioids, exacerbate cognitive decline. Others find no significant association or even potential protective effects [3,4]. These studies are often small, examine short-term analgesic use, and focus on only one type of analgesic at a time, despite the common long-term and combined use of multiple analgesics in the management of chronic pain. 

Chronic pain is complex. It can manifest as a symptom of disease (chronic secondary pain) and as a disease in its own right (chronic primary pain) and is shaped by, and in turn influences, a wide range of sociodemographic, biological and psychological factors. Despite this complexity, chronic pain is often treated as one homogenous group in research. The mixed evidence linking analgesic use and cognitive decline may partly stem from variations in cognitive trajectories arising from differences in the nature of the chronic pain, the patterns of pain prescribing, as well as the interactions between pain and analgesic drugs with other factors such as comorbidities, genetic risk factors, epigenetic modifications, and alterations in brain structure. 

Aims

This PhD will leverage data from three well-characterised longitudinal studies (UK Biobank, n=500,000; Generation Scotland, n=24,000; and Lothian Birth Cohort 1936, n=1,091) to investigate the pathways linking chronic pain and analgesic prescribing to cognitive decline and dementia. These cohorts provide extensive and repeated measures of cognitive function, health status, sociodemographic factors, as well as genomic and neuroimaging data. Crucially, all are linked to electronic health records (EHR), enabling retrospective and prospective access to prescribing and other health outcome data. Structural Equation Modelling (SEM) and other advanced statistical techniques will be used that enable the modelling of complex relationships among multiple variables, both between and within individuals, as well as formal assessment of the magnitude and significance of various mediators and moderators. The key aims are to:

  1. investigate the influence of different types of analgesics (e.g., opioids, non-opioid analgesics) and prescribing patterns (e.g., duration, dosage, and co-prescribing) on concurrent cognitive function, cognitive trajectories, and dementia; 
  2. investigate whether observed relationships between analgesics and cognitive variables differ by characteristics of chronic pain (e.g., primary or secondary pain, severity and impact, duration) 

This project will also allow for the investigation of genetic risk factors, neurostructural variation, and epigenetic biomarkers of health and ageing as potential mediators and moderators of the relationship between analgesics and cognitive variables. 

Training outcomes

This project offers students the opportunity to develop a broad set of precision medicine skills applicable across multiple health disciplines by building expertise in the areas of psychology; cognitive, brain and biological ageing; epidemiology; health data science; and complex statistical modelling. The student will benefit from comprehensive internal and external training opportunities in advanced longitudinal modelling and the application of EHR data in research. There will also be opportunities to develop skills using genomic/epigenetic and neuroimaging data, along with lab visits, including to the Molecular Epidemiology of Ageing lab at the Karolinska Institute. 

References

  1. James RJE, Walsh DA, Ferguson E: General and disease-specific pain trajectories aspredictors of social and political outcomes in arthritis and cancer. BMC Med 2018, 16(1):51.
  2. Warner NS, Mielke M, Verdoorn BP, Knopman DS, Hooten WM, Habermann EB, Warner DO: Pain, Opioid Analgesics, and Cognition: A Conceptual Framework in Older Adults. Pain medicine (Malden, Mass) 2022.
  3. Akhurst J, Lovell M, Peacock A, Bruno R: A Systematic Review and Meta-Analysis of Cognitive Performance among People with Chronic Use of Opioids for Chronic Non-Cancer Pain. Pain Medicine 2021, 22(4):979-993.
  4. Lopes De Oliveira T, Tang B, Bai G, Sjölander A, Jylhävä J, Finkel D, Pedersen NL, Hassing LB, Reynolds CA, Karlsson IK, Hägg S: Effects from medications on functional biomarkers of aging in three longitudinal studies of aging in Sweden. Aging Cell 2024, 23(6):e14132.

Apply Now

Click here to Apply Now

  • The deadline for 25/26 applications is Monday 13th January 2025
  • Applicants must apply to a specific project. Please ensure you include details of the project on the Recruitment Form below, which you must submit to the research proposal section of your EUCLID application. 
  • Please ensure you upload as many of the requested documents as possible, including a CV, at the time of submitting your EUCLID application.  
Document

 

Q&A Sessions

Supervisor(s) of each project will be holding a 30 minute Q&A session in the first two weeks of December. 

If you have any questions regarding this project, you are invited to attend the session on Wednesday 4th December at 10am GMT via Microsoft Teams. Click here to join the session.