Active Psychology & Behaviour Mental Health

Beyond Diagnosis: Investigating How Biologically Informed Risk for Severe Mental Illness Shapes Cognitive Ageing in the General Population

Funder Wellcome Charity-funded
Recipient organisation University of Edinburgh
Funding Not disclosed
Period Oct 2025 — Sept 2028

In plain English

AI plain-English summary

A person’s genetic and biological risk for severe mental illness—even if they never develop a diagnosis—may quietly accelerate their cognitive decline as they age. Current psychiatry treats severe mental illnesses like schizophrenia or bipolar disorder as distinct categories: you either have the diagnosis or you do not. This misses a large group of people who carry the underlying biological liability—visible in their genes, proteins, and metabolism—but never cross the clinical threshold. Recent evidence suggests these individuals still face elevated dementia risk and poorer cognitive performance in later life. This project treats that biological risk as a continuous spectrum, not a binary label. Using multi-omic profiling and brain scans from large population cohorts, the researchers will map how shared and unique molecular signatures of mental illness relate to cognitive ageing and brain structure changes over time. If successful, this work could shift how we detect early cognitive vulnerability. Instead of waiting for a diagnosis, clinicians might one day use biological markers to identify people at risk years earlier, enabling targeted interventions before decline becomes irreversible. The research is fundamentally about refining risk prediction—it does not promise a new drug or therapy, but a more precise way to spot who needs help and when.

View original technical description
Severe mental illnesses (SMIs) are chronic psychiatric disorders characterized by cognitive deficits, emotional distress, and functional impairment. Cognitive dysfunction is increasingly recognized as a core feature of SMIs, significantly impacting long-term outcomes. Recent research indicates that individuals with a high molecular risk for SMIs, even without a clinical diagnosis, exhibit elevated dementia risk and poorer cognitive performance. This suggests that biological liability to SMI, captured through genetic, epigenetic, proteomic, and metabolic markers, exists on a continuum influencing phenotypic changes in aging populations and contributing to early cognitive decline. Traditional categorical diagnostic frameworks often miss this subclinical variation. This project aims to model SMI liability as a continuous biological construct and investigate its association with cognitive aging and brain health. Utilizing multi-omic profiling, neuroimaging, and advanced statistical methods in large-scale population cohorts, we will identify cross-sectional and longitudinal patterns linking common and unique multi-omic risk for SMI with aging-related cognitive and neuroimaging outcomes. Ultimately, this work seeks to enhance the detection of subclinical cognitive vulnerability, enabling earlier identification, targeted interventions, and promotion of healthier aging across populations.

View the original record at the funder ↗

Researchers

Rita Dargham (EPMC Awardee)

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Original classification

PhD Studentship (Basic)

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