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Brain properties predict proximity to symptom onset in sporadic Alzheimer's disease.

ABSTRACT: See Tijms and Visser (doi:10.1093/brain/awy113) for a scientific commentary on this article.Alzheimer's disease is preceded by a lengthy 'preclinical' stage spanning many years, during which subtle brain changes occur in the absence of overt cognitive symptoms. Predicting when the onset of disease symptoms will occur is an unsolved challenge in individuals with sporadic Alzheimer's disease. In individuals with autosomal dominant genetic Alzheimer's disease, the age of symptom onset is similar across generations, allowing the prediction of individual onset times with some accuracy. We extend this concept to persons with a parental history of sporadic Alzheimer's disease to test whether an individual's symptom onset age can be informed by the onset age of their affected parent, and whether this estimated onset age can be predicted using only MRI. Structural and functional MRIs were acquired from 255 ageing cognitively healthy subjects with a parental history of sporadic Alzheimer's disease from the PREVENT-AD cohort. Years to estimated symptom onset was calculated as participant age minus age of parental symptom onset. Grey matter volume was extracted from T1-weighted images and whole-brain resting state functional connectivity was evaluated using degree count. Both modalities were summarized using a 444-region cortical-subcortical atlas. The entire sample was divided into training (n = 138) and testing (n = 68) sets. Within the training set, individuals closer to or beyond their parent's symptom onset demonstrated reduced grey matter volume and altered functional connectivity, specifically in regions known to be vulnerable in Alzheimer's disease. Machine learning was used to identify a weighted set of imaging features trained to predict years to estimated symptom onset. This feature set alone significantly predicted years to estimated symptom onset in the unseen testing data. This model, using only neuroimaging features, significantly outperformed a similar model instead trained with cognitive, genetic, imaging and demographic features used in a traditional clinical setting. We next tested if these brain properties could be generalized to predict time to clinical progression in a subgroup of 26 individuals from the Alzheimer's Disease Neuroimaging Initiative, who eventually converted either to mild cognitive impairment or to Alzheimer's dementia. The feature set trained on years to estimated symptom onset in the PREVENT-AD predicted variance in time to clinical conversion in this separate longitudinal dataset. Adjusting for participant age did not impact any of the results. These findings demonstrate that years to estimated symptom onset or similar measures can be predicted from brain features and may help estimate presymptomatic disease progression in at-risk individuals.

SUBMITTER: Vogel JW

PROVIDER: S-EPMC5972641 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ImportanceAlzheimer disease (AD) develops during several decades. Presymptomatic individuals might be the best candidates for clinical trials, but their identification is challenging because they have no symptoms.ObjectiveTo assess whether a sporadic parental estimated years to symptom onset calculation could be used to identify information about amyloid-? (A?) levels in asymptomatic individuals with a parental history of AD dementia.Design, setting, and participantsThis cohort study analyzed A?1-42 in cerebrospinal fluid (CSF) specimens from 101 cognitively normal individuals who had a lumbar puncture as part of the Presymptomatic Evaluation of Novel or Experimental Treatments for Alzheimer Disease (PREVENT-AD) cohort from September 1, 2011, through November 30, 2016 (374 participants were enrolled in the cohort during this period). The study estimated each participant's proximity to his/her parent's symptom onset by subtracting the index relative's onset age from his/her current age. The association between proximity to parental symptom onset and A? levels was then assessed using apolipoprotein E ?4 (APOE4) status and sex as interactive terms. These analyses were performed again in 2 independent cohorts using CSF and Pittsburgh compound B carbon 11-labeled positron emission tomography (PIB-PET) A? biomarkers: the Adult Children Study (ACS) and the Wisconsin Registry for Alzheimer Prevention (WRAP) cohorts.Main outcomes and measuresThe association between proximity to parental symptom onset and A? burden in asymptomatic individuals with a parental history of sporadic AD.ResultsThe present analysis included a subset of 101 PREVENT-AD individuals (mean [SD] age, 61.8 [5.1] years; 30 [29.7%] male), 128 ACS participants (112 participants underwent CSF measurement: mean [SD] age, 63.4 [5.1] years; 31 [27.7%] male; and 107 underwent PIB-PET: mean [SD] age, 64.6 [5.3] years; 27 [25.2%] male), and 135 WRAP participants (85 participants underwent CSF measurement: mean [SD] age, 59.9 [6.0] years; 27 [31.8%] male; and 135 underwent PIB-PET: mean [SD] age, 59.6 [6.1] years; 43 [31.9%] male). In the PREVENT-AD cohort, individuals approaching their parent's onset age had lower CSF A?1-42 levels (range, 402-1597; B?=?-9.09, P?=?.04). This association was stronger in APOE4 carriers (B?=?-17.9, P?=?.03) and women (B?=?-19.8, P?=?.02). In the ACS cohort, the main association was replicated using PIB-PET data, and the sex interaction was replicated using CSF and PIB-PET data. In the WRAP cohort, the results were not replicated using cross-sectional data, but the main association and the APOE interaction were replicated using PIB-PET longitudinal data.Conclusions and relevanceThese results suggest that proximity to parental symptom onset may help estimate A? biomarker changes in women or APOE4 carrier asymptomatic individuals with a parental history of sporadic AD.

Project description:White matter alterations are present in the majority of patients with Alzheimer's disease type dementia. However, the spatiotemporal pattern of white matter changes preceding dementia symptoms in Alzheimer's disease remains unclear, largely due to the inherent diagnostic uncertainty in the preclinical phase and increased risk of confounding age-related vascular disease and stroke in late-onset Alzheimer's disease. In early-onset autosomal-dominantly inherited Alzheimer's disease, participants are destined to develop dementia, which provides the opportunity to assess brain changes years before the onset of symptoms, and in the absence of ageing-related vascular disease. Here, we assessed mean diffusivity alterations in the white matter in 64 mutation carriers compared to 45 non-carrier family non-carriers. Using tract-based spatial statistics, we mapped the interaction of mutation status by estimated years from symptom onset on mean diffusivity. For major atlas-derived fibre tracts, we determined the earliest time point at which abnormal mean diffusivity changes in the mutation carriers were detectable. Lastly, we assessed the association between mean diffusivity and cerebrospinal fluid biomarkers of amyloid, tau, phosphorylated-tau, and soluble TREM2, i.e. a marker of microglia activity. Results showed a significant interaction of mutations status by estimated years from symptom onset, i.e. a stronger increase of mean diffusivity, within the posterior parietal and medial frontal white matter in mutation carriers compared with non-carriers. The earliest increase of mean diffusivity was observed in the forceps major, forceps minor and long projecting fibres-many connecting default mode network regions-between 5 to 10 years before estimated symptom onset. Higher mean diffusivity in fibre tracts was associated with lower grey matter volume in the tracts' projection zones. Global mean diffusivity was correlated with lower cerebrospinal fluid levels of amyloid-β1-42 but higher levels of tau, phosphorylated-tau and soluble TREM2. Together, these results suggest that regionally selective white matter degeneration occurs years before the estimated symptom onset. Such white matter alterations are associated with primary Alzheimer's disease pathology and microglia activity in the brain.

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Brain properties predict proximity to symptom onset in sporadic Alzheimer's disease.

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