TY - JOUR
T1 - Exploring cognitive and neuroimaging profiles of dementia subtypes of individuals with dementia in the Democratic Republic of Congo
AU - Ikanga, Jean
AU - Patel, Saranya Sundaram
AU - Schwinne, Megan
AU - Obenauf, Caterina
AU - Epenge, Emmanuel
AU - Gikelekele, Guy
AU - Tshengele, Nathan
AU - Kavugho, Immaculee
AU - Mampunza, Samuel
AU - Mananga, Lelo
AU - Teunissen, Charlotte E.
AU - Rojas, Julio C.
AU - Chan, Brandon
AU - Lago, Argentina Lario
AU - Kramer, Joel H.
AU - Boxer, Adam L.
AU - Jeromin, Andreas
AU - Omba, Emile
AU - Alonso, Alvaro
AU - Gross, Alden L.
N1 - Publisher Copyright:
Copyright © 2025 Ikanga, Patel, Schwinne, Obenauf, Epenge, Gikelekele, Tshengele, Kavugho, Mampunza, Mananga, Teunissen, Rojas, Chan, Lario Lago, Kramer, Boxer, Jeromin, Omba, Alonso and Gross.
PY - 2025
Y1 - 2025
N2 - Objective: The 2024 Alzheimer’s Association (AA) research diagnostic criteria for Alzheimer’s Disease (AD) considers fluid biomarkers, including promising blood-based biomarkers for detecting AD. This study aims to identify dementia subtypes and their cognitive and neuroimaging profiles in older adults with dementia in the Democratic Republic of Congo (DRC) using biomarkers and clinical data. Methods: Forty-five individuals with dementia over 65 years old were evaluated using the Community Screening Instrument for Dementia and the informant-based Alzheimer’s Questionnaire. Core AD biomarkers (Aβ42/40 and p-tau181) and non-specific neurodegeneration biomarkers (NfL, GFAP) were measured in blood plasma. Neuroimaging structures were assessed using magnetic resonance imaging (MRI). Dementia subtypes were determined based on plasma biomarker pathology and vascular markers. Biomarker cutoff scores were identified to optimize sensitivity and specificity. Individuals were stratified into one of four dementia subtypes—AD only, non-AD vascular, non-AD other, or mixed – based on combinations of abnormalities in these markers. Results: Among the 45 individuals with dementia, mixed dementia had the highest prevalence (42.4%), followed by AD-only (24.4%), non-AD other dementia (22.2%), and non-AD vascular dementia subtypes (11.1%). Both cognitive and neuroimaging profiles aligned poorly with biomarker classifications in the full sample. Cognitive tests varied across dementia subtypes. The cognitive profile of the AD-only and mixed groups suggested relatively low cognitive performance, while the non-AD and other groups had the best scores on average. Conclusion: Consistent with studies in other settings, our preliminary findings suggest that neurodegenerative plasma biomarkers may help to identify dementia subtypes and provide insight into cognitive and neuroimaging profiles among older adults in the DRC.
AB - Objective: The 2024 Alzheimer’s Association (AA) research diagnostic criteria for Alzheimer’s Disease (AD) considers fluid biomarkers, including promising blood-based biomarkers for detecting AD. This study aims to identify dementia subtypes and their cognitive and neuroimaging profiles in older adults with dementia in the Democratic Republic of Congo (DRC) using biomarkers and clinical data. Methods: Forty-five individuals with dementia over 65 years old were evaluated using the Community Screening Instrument for Dementia and the informant-based Alzheimer’s Questionnaire. Core AD biomarkers (Aβ42/40 and p-tau181) and non-specific neurodegeneration biomarkers (NfL, GFAP) were measured in blood plasma. Neuroimaging structures were assessed using magnetic resonance imaging (MRI). Dementia subtypes were determined based on plasma biomarker pathology and vascular markers. Biomarker cutoff scores were identified to optimize sensitivity and specificity. Individuals were stratified into one of four dementia subtypes—AD only, non-AD vascular, non-AD other, or mixed – based on combinations of abnormalities in these markers. Results: Among the 45 individuals with dementia, mixed dementia had the highest prevalence (42.4%), followed by AD-only (24.4%), non-AD other dementia (22.2%), and non-AD vascular dementia subtypes (11.1%). Both cognitive and neuroimaging profiles aligned poorly with biomarker classifications in the full sample. Cognitive tests varied across dementia subtypes. The cognitive profile of the AD-only and mixed groups suggested relatively low cognitive performance, while the non-AD and other groups had the best scores on average. Conclusion: Consistent with studies in other settings, our preliminary findings suggest that neurodegenerative plasma biomarkers may help to identify dementia subtypes and provide insight into cognitive and neuroimaging profiles among older adults in the DRC.
KW - Democratic Republic of the Congo
KW - biomarkers
KW - cognition
KW - dementia
KW - neuroimaging
UR - https://www.scopus.com/pages/publications/85219169763
U2 - 10.3389/fnagi.2025.1552348
DO - 10.3389/fnagi.2025.1552348
M3 - Article
C2 - 40013096
VL - 17
JO - Frontiers in aging neuroscience
JF - Frontiers in aging neuroscience
M1 - 1552348
ER -