RESUMO
BACKGROUND: First-degree relatives of people with dementia (FH+) are at increased risk of developing Alzheimer's disease (AD). Here, we investigate "estimated years to onset of dementia" (EYO) as a surrogate marker of preclinical disease progression and assess its associations with multi-modal neuroimaging biomarkers. METHODS: 89 FH+ participants in the PREVENT-Dementia study underwent longitudinal MR imaging over 2 years. EYO was calculated as the difference between the parental age of dementia diagnosis and the current age of the participant (mean EYO = 23.9 years). MPRAGE, ASL and DWI data were processed using Freesurfer, FSL-BASIL and DTI-TK. White matter lesion maps were segmented from FLAIR scans. The SPM Sandwich Estimator Toolbox was used to test for the main effects of EYO and interactions between EYO, Time, and APOE-ε4+. Threshold free cluster enhancement and family wise error rate correction (TFCE FWER) was performed on voxelwise statistical maps. RESULTS: There were no significant effects of EYO on regional grey matter atrophy or white matter hyperintensities. However, a shorter EYO was associated with lower white matter Fractional Anisotropy and elevated Mean/Radial Diffusivity, particularly in the corpus callosum (TFCEFWERp < 0.05). The influence of EYO on white matter deficits were significantly stronger compared to that of normal ageing. APOE-ε4 carriers exhibited hyperperfusion with nearer proximity to estimated onset in temporo-parietal regions. There were no interactions between EYO and time, suggesting that EYO was not associated with accelerated imaging changes in this sample. CONCLUSIONS: Amongst cognitively normal midlife adults with a family history of dementia, a shorter hypothetical proximity to dementia onset may be associated with incipient brain abnormalities, characterised by white matter disruptions and perfusion abnormalities, particularly amongst APOE-ε4 carriers. Our findings also confer biological validity to the construct of EYO as a potential stage marker of preclinical progression in the context of sporadic dementia. Further clinical follow-up of our longitudinal sample would provide critical validation of these findings.
Assuntos
Encéfalo/diagnóstico por imagem , Demência/diagnóstico por imagem , Demência/prevenção & controle , Imagem Multimodal/métodos , Adulto , Idade de Início , Doença de Alzheimer/diagnóstico por imagem , Doença de Alzheimer/epidemiologia , Doença de Alzheimer/genética , Doença de Alzheimer/prevenção & controle , Apolipoproteína E4/genética , Demência/epidemiologia , Demência/genética , Imagem de Tensor de Difusão/métodos , Feminino , Seguimentos , Humanos , Estudos Longitudinais , Imageamento por Ressonância Magnética/métodos , Masculino , Pessoa de Meia-Idade , Neuroimagem/métodos , Reino Unido/epidemiologiaRESUMO
Objective: To test the hypothesis that among cognitively healthy individuals, distinct groups exist in terms of amyloid and phosphorylated-tau accumulation rates; that if rapid accumulator groups exist, their membership can be predicted by Alzheimer's disease (AD) risk factors, and that time points of significant increase in AD protein accumulation will be evident. Methods: The analysis reports data from 263 individuals from the BIOCARD and 184 individuals from the Baltimore Longitudinal Study of Aging with repeated cerebrospinal fluid (CSF) and positron emission tomography (PET) sampling, respectively. We used latent class mixed-effect models to identify distinct classes of amyloid (CSF and PET) and p-Tau (CSF) accumulation rates and generalized additive modeling to investigate non-linear changes to AD biomarkers. Results: For both amyloid and p-Tau latent class models we confirmed the existence of two separate classes: accumulators and non-accumulators. The accumulator and non-accumulator groups differed significantly in terms of baseline AD protein levels and slope of change. APOE ε4 carrier status and episodic memory predicted amyloid class membership. Non-linear models revealed time points of significant increase in the rate of amyloid and p-Tau accumulation whereby APOE ε4 carrier status associated with earlier age at onset of rapid accumulation. Conclusions: The current analysis demonstrates the existence of distinct classes of amyloid and p-Tau accumulators. Predictors of class membership were identified but the overall accuracy of the models was modest, highlighting the need for additional biomarkers that are sensitive to early disease phenotypes.