Research Article: Prediction models for dementia and neuropathology in the oldest old: the Vantaa 85+ cohort study

Date Published: January 22, 2019

Publisher: BioMed Central

Author(s): Anette Hall, Timo Pekkala, Tuomo Polvikoski, Mark van Gils, Miia Kivipelto, Jyrki Lötjönen, Jussi Mattila, Mia Kero, Liisa Myllykangas, Mira Mäkelä, Minna Oinas, Anders Paetau, Hilkka Soininen, Maarit Tanskanen, Alina Solomon.

http://doi.org/10.1186/s13195-018-0450-3

Abstract

We developed multifactorial models for predicting incident dementia and brain pathology in the oldest old using the Vantaa 85+ cohort.

We included participants without dementia at baseline and at least 2 years of follow-up (N = 245) for dementia prediction or with autopsy data (N = 163) for pathology. A supervised machine learning method was used for model development, considering sociodemographic, cognitive, clinical, vascular, and lifestyle factors, as well as APOE genotype. Neuropathological assessments included β-amyloid, neurofibrillary tangles and neuritic plaques, cerebral amyloid angiopathy (CAA), macro- and microscopic infarcts, α-synuclein pathology, hippocampal sclerosis, and TDP-43.

Prediction model performance was evaluated using AUC for 10 × 10-fold cross-validation. Overall AUCs were 0.73 for dementia, 0.64–0.68 for Alzheimer’s disease (AD)- or amyloid-related pathologies, 0.72 for macroinfarcts, and 0.61 for microinfarcts. Predictors for dementia were different from those in previous reports of younger populations; for example, age, sex, and vascular and lifestyle factors were not predictive. Predictors for dementia versus pathology were also different, because cognition and education predicted dementia but not AD- or amyloid-related pathologies. APOE genotype was most consistently present across all models. APOE alleles had a different impact: ε4 did not predict dementia, but it did predict all AD- or amyloid-related pathologies; ε2 predicted dementia, but it was protective against amyloid and neuropathological AD; and ε3ε3 was protective against dementia, neurofibrillary tangles, and CAA. Very few other factors were predictive of pathology.

Differences between predictors for dementia in younger old versus oldest old populations, as well as for dementia versus pathology, should be considered more carefully in future studies.

The online version of this article (10.1186/s13195-018-0450-3) contains supplementary material, which is available to authorized users.

Partial Text

The oldest old constitute the largest and fastest growing population with dementia [1], but they are less often the focus of dementia prevention studies. Cohort studies with participants aged 85+ years [2–7] have investigated individual risk factors in association with dementia, but the predictive value of more complex multifactorial risk profiles in the oldest old is still unclear. Several dementia risk scores have been developed in younger populations, but they tend to perform poorly for predicting dementia in the oldest old age groups [8, 9]. The association of vascular and lifestyle-related factors with dementia risk, for example, has been shown to vary with age [10], and risk profiles predictive of subsequent dementia can differ between midlife and older age [9].

This is the first study combining longer-term dementia and neuropathology multicomponent prediction models among the oldest old. The dementia risk profile in this age group was very different from risk profiles previously described at younger ages. Predictors of dementia did not necessarily predict pathology. APOE genotype was the most consistent predictor across all models, but with different impact for different alleles.

 

Source:

http://doi.org/10.1186/s13195-018-0450-3

 

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