Cognitive Changes and Neural Correlates After Rehabilitation of Masticatory Function in Elderly -an Intervention Study

Description

• Dementia is a general term of several neurodegenerative diseases that jointly affects approximately 7% of the general population older than 65 years, and 30% older than 80 years (O'Brien, 2003). Importantly, these statistics are expected to almost double every 20 years (Prince, 2013), making disorders of cognition a priority for healthcare (O'Brien, 2014).
  • Animal and human studies have shown associations with mastication and cognitive function through the medial temporal lobe (i.e., hippocampus) and its role in learning and memory. (Ono, 2010. Weijenberg, 2011. Ohkubo, 2012. Teixeira, 2014. Klineberg, 2014)
  • Although tooth loss and loss of oral function is widespread in older people, it is still an underexplored modifiable risk factor contributing to the development of dementia.
  • We aim to conduct an intervention study on elderly people where rehabilitation of masticatory functions is performed and evaluated, with cognitive measures and brain imaging, to investigate a "cause-effect" relationship between mastication and cognition in humans.
  • Our hypothesis is that rehabilitation of masticatory function will improve cognition primarily in the performance of episodic memory and executive function tests along with the corresponding neural changes mainly in hippocampus and prefrontal cortex.
  • A total of eighty (80) participants, 65-80 years of age, indicated for prosthodontic rehabilitation at Eastmaninstitutet (Stockholm, Sweden) will be randomly assigned to either the experimental or the control group. The difference between the groups is that the participants in the experimental group will begin with the rehabilitation immediately after the first measurement while the control group will do one more measurement before the onset of the rehabilitation procedure. The two measurements conducted before treatment in the control group are to rule out for test-retest effects. Three months and one year after completed prosthodontic treatment participants will conduct the last measurements, as a post-test to evaluate potential treatment effect.
  • The neuropsychological assessments will be conducted together with MRI assessments, oral health-related quality of life instrument, chewing function test (two coloured chewing gum) and saliva samples recorded at different time points (i.e., pre-test, post-test 1, post-test 2, post-test 3) in both the groups.
  • The data from the study will be entered in a Microsoft Excel sheet and exported to Statistics is a software package SPSS Inc, Statistica, StatSoft Inc (or similar advanced analytics software package for analysis). The result from the cognitive testing will be analysed as repeated measure Analysis of covariance (ANCOVAs) with groups (experimental and control) and time (pre- and post-rehabilitation) as factors. Group-by-time interaction, main effect of group, and main effect of time will be evaluated. To compare the magnitude of gains, the effect size (partial eta-square) will also be calculated. We will use time-length between pre- and post-tests as a covariate of interest with aiming to better control group differences. To predict the intervention outcomes, we will develop models that mainly predicts cognitive test measures (neuropsychological assessments). Predictive ability is defined as the amount of variance in the outcome that can be explained by pre-test cognitive status (slope method). Explained variance in outcome will be obtained by analysing linear regressions.
  • Preprocessing and statistical analyses of MRI data will be performed with Statistical Parametric Mapping (SPM) run in Matlab (MathWorks). Movement correction will be performed by realign and unwarp to the first image in the series. To consider group-specific anatomical brain differences, all patients will be normalized to Monteral Neurological Institute (MNI) echoplanar-imaging template. Cortical thickness measures will not be normalized but rather used in their raw form. For cortical segmentation, a Freesurfer pipeline will be applied to the MRI images to produce regional cortical thickness and volumetric measures. To investigate rehabilitating-related changes repeated measures ANCOVAs will be performed with the groups (experimental and control) and time (pre- and post-rehabilitation) as factors. We will control for multiple comparisons with the Bonferroni-Holm method.

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