Alex Dregan is Reader in Psychiatric Epidemiology at the Institute of Psychiatry, Psychology & Neuroscience, King's College London. He is an epidemiologist and public health data scientist whose work focuses on the mental–physical interface in multiple long-term conditions, and on how depression shapes the onset, accumulation and progression of physical illness across the life course. He trained in life-course epidemiology at the Institute of Education, University of London, where his doctoral work used the 1970 British Cohort Study to document the long reach of childhood public care into adult life. He is PhD Admissions Tutor at the IoPPN and a member of the UKRI-funded Population Mental Health Consortium. He also contributes to the national NIHR infrastructure for multimorbidity and mental health research, through the Methodologies workstream of the Multiple Long-Term Conditions Cross-NIHR Collaboration and the Mind and Body workstream of the Mental Health Translational Research Collaboration.

His research has been supported by UKRI, through both the MRC and the ESRC, as well as the NIHR, and the National Institutes of Health. He has particular expertise in large-scale linked electronic health records and pooled cohort data, and led an MRC-funded programme that harmonised the 1946, 1958 and 1970 British birth cohorts into a single resource for tracing the life-course role of depression in physical multimorbidity. He was a co-I on MELD-B, funded through the NIHR's Artificial Intelligence for Multiple and Long-Term Conditions programme, where he led the analysis of Clinical Practice Research Datalink data to identify the early clusters of conditions that prove most burdensome to the people living with them. He is a co-I on an ESRC-funded study of multiple long-term conditions among sexual minority populations, leading the CPRD analyses of their prevalence and pathway.

His methodological work concerns mainly causal inferences within real-world clinical data, and the study designs that make this possible, from natural experiments evaluating large-scale interventions such as NHS Talking Therapies for people with long-term conditions, to cluster randomised trials embedded directly within general practice electronic records (eCRT2). His substantive research spans the aetiology and trajectory of mental health-related multimorbidity, the comparative effectiveness of antidepressant treatment strategies and the burden of polypharmacy, and inequalities in multimorbidity by ethnicity, sexual orientation and deprivation. His international collaborations include work with the Grover Lab at Beth Israel Deaconess Medical Center, Harvard Medical School and with Susan Jick and the Boston Collaborative Drug Surveillance Program at Boston University.

Research Interests 

• Depression-related multimorbidity and the mental–physical interface across the life course

• Causal inference using linked electronic health records (CPRD Aurum linked to HES, ONS mortality and Cancer Registry)

• Comparative effectiveness of antidepressant treatment strategies, polypharmacy and treatment burden

• Health inequalities in mental health multimorbidity by ethnicity, sexual orientation and socioeconomic deprivation

• Natural experiments and EHR-embedded cluster randomised trials for evaluating large-scale interventions

• Advanced epidemiological and AI methods: latent class analysis, causal mediation, machine learning and prognostic modelling

• Life-course epidemiology using the UK birth cohorts (1946, 1958, 1970) and UK Biobank