Evidence map›Paper›PMID 40661287›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Cognitive and Neuroimaging for Neurodegenerative Disorders: A Cohort Study Design with Initial Findings.

Akram A Hosseini, Beili Shao, Abigail Rebecca Lee, Permesh Dhillon, Kehinde Junaid, Bruno Gran, Peter Sellars, Hannah Sargisson, JeYoung Jung, Elizabeta Mukaetova-Ladinska

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Akram A HosseiniDepartment of Neurology, Research and Innovation, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom.ORCID 0000-0003-0133-9842
Beili ShaoDepartment of Neurology, Research and Innovation, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom.ORCID 0009-0009-5333-370X
Abigail Rebecca LeeDepartment of Neurology, Research and Innovation, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom.
Permesh DhillonRadiological Sciences, Mental Health and Clinical Neuroscience, School of Medicine, University of Nottingham, United Kingdom.
Kehinde JunaidOld Age Psychiatry, Nottinghamshire Healthcare NHS Foundation Trust, Nottingham, United Kingdom.
Bruno GranDepartment of Neurology, Research and Innovation, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom.
Peter SellarsDepartment of Neurology, Research and Innovation, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom.
Hannah SargissonDepartment of Neurology, Research and Innovation, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom.
JeYoung JungDepartment of Psychology, University of Nottingham, Nottingham, United Kingdom.
Elizabeta Mukaetova-LadinskaOld Age Psychiatry, University of Leicester, Leicester, United Kingdom.

Funding

SARS-CoV-2 and Precursors of Alzheimer's Disease and Related Dementias: An Ultrahigh Field (7T) MRI Study in a Diverse Multinational CohortR56AG074467 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI GIRARD, TIMOTHY D, HOSSEINI, AKRAM A. · 2021 to 2021
$3.5M
NIA NIH HHS R56 AG074467
6 · The paper itself

Abstract

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 2024 from the Memory Clinics, including the young-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.

Indexed as

cognitive impairmentcohortdementianeurodegenerative disordersneuroimaging

Identifiers

PMID40661287
PMCPMC12258771

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.