The Cognitive and Neuroimaging for Neurodegenerative Disorders (CogNID) Study: Design with Initial Findings from Real-World Clinical Practice

Akram A. Hosseini^1,2*Beili Shao^1,3Abigail Rebecca Lee¹Permesh Dhillon⁴Kehinde Junaid⁵Bruno Gran^1,3Peter Sellars¹Hannah Sargisson¹JeYoung Jung⁶Elizabeta Blagoja Mukaetova-Ladinska⁷

• ¹Department of Neurology, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
• ²Sir Peter Mansfield Image Centre and Academic Neurology, University of Nottingham, Nottingham, United Kingdom
• ³Academic Neurology, Mental Health and Clinical Neuroscience Academic Unit, School of Medicine, University of Nottingham, Nottingham, United Kingdom
• ⁴‎Radiological Sciences, Mental Health and Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, United Kingdom
• ⁵Older Peoples Care Unit, Nottinghamshire Healthcare NHS Foundation Trust, Nottingham, United Kingdom
• ⁶School of Psychology, University of Nottingham, Nottingham, United Kingdom
• ⁷Old Age Psychiatry, University of Leicester, Leicester, United Kingdom

Introduction: Dementia presents with significant heterogeneity across age groups, particularly in early-onset cognitive decline (EOCD), which poses diagnostic and management challenges. The Cognitive and Neuroimaging for Neurodegenerative Disorders (CogNID) study aims to characterise clinical, cognitive, neuroimaging, and biomarker features across a diverse cohort of individuals with cognitive impairment, with a focus on diagnostic complexity, biomarker utility, and mortality. Methods: Out of 680 study participants within this prospective cohort enrolled from the real-world clinics within the National Health Service, who consented to take part in the study, we analysed data from 429 individuals recruited between December 2018 and November from the Memory Clinics, including the early-onset dementia service and associated services. Participants underwent structured cognitive assessments, neuroimaging (MRI/CT), and Cerebrospinal fluid (CSF) biomarker evaluation, where available. Diagnoses were made by multidisciplinary consensus. Group comparisons were conducted between early-onset (EOCD, <65 years) and late-onset cognitive decline (LOCD, ≥65 years). Results: Of the 429 participants, 349 (81.4%) had EOCD and 80 (18.6%) had LOCD. The mean age was 60.05 years, with no significant difference in sex or ethnicity across groups. Depression and anxiety were common (29.6%), as were cardiovascular risk factors. Lumbar punctures were more frequently performed in EOCD (p = 0.03), with 36.4% of tested participants demonstrating biomarker profiles consistent with Alzheimer's disease (A+T+). Functional cognitive disorder (FCD) was more common in EOCD (22.3% vs. 5.0%, p < 0.001). Subgroup analysis revealed significantly lower ACE-III scores and higher pathological CSF findings in Alzheimer's disease versus FCD. Mortality was higher in the LOCD group (11.3% vs. 4.6%, p = 0.03). Conclusion: The CogNID study highlights the clinical and diagnostic heterogeneity of individuals with cognitive impairment, particularly in younger adults. Incorporating neuroimaging and CSF biomarkers into routine clinical pathways enhances diagnostic precision and reveals distinct phenotypic profiles between EOCD and LOCD. These findings underscore the need for harmonised diagnostic protocols, broader biomarker accessibility, and inclusive recruitment strategies in dementia research and clinical services.