Communication du Professeur GEDA au XXVIIIème Congrès du GRAL
White matter abnormalities can be associated with psychiatric disorders in two major settings. Neuroimaging studies indicate that primary psychiatric disorders such as mood disorders are associated with white matter abnormalities. On the other hand psychiatric disorders such as depression, apathy, etc. can occur in the context of neurological diseases that disrupt white matter connections. Depression, apathy, and related disorders that take place in old age can be manifestations of white matter abnormalities.
To examine neuropsychiatric symptoms in old age and mild cognitive impairment (MCI).
Design / Methods.
A population-based cohort study in the setting of the Mayo Clinic Study of Aging.
Baseline Neuropsychiatric Inventory Questionnaire data were available for 1,587 cognitively normal persons aged 70 years older. We followed the cohort (N=1,587) to incident mild cognitive impairment (N=365) or censoring variables (N=179) for a median of 5 years. The following baseline neuropsychiatric symptoms significantly predicted incident MCI, after adjusting for age, sex, education and medical comorbidity: agitation (HR=3.06; 95% CI=1.89–4.93), apathy (HR=2.26; 95% CI=1.49–3.41), anxiety (HR=1.87; 95% CI=1.28–2.73), irritability (HR=1.84; 95% CI=1.31–2.58), and depression (HR=1.63; 95% CI=1.23–2.16). Delusion (HR=0.55; 95% CI=0.08–3.95) and hallucination (HR=1.48; 95% CI=0.37–5.99) did not predict incident MCI. A secondary analysis showed that euphoria (HR=11.3; 95% CI=3.44–37.2), disinhibition (HR=5.18; 95% CI=2.24–12.0) and nighttime behavior (HR=2.04; 95% CI=1.11–3.76) were significant predictors of non-amnestic MCI but not of amnestic MCI. By contrast, depression predicted amnestic MCI (HR=1.74; 95% CI=1.22–2.47) but not non-amnestic MCI (HR=1.18; 95% CI=0.64–2.16).
Baseline Non-psychotic symptoms were associated with increased risk of incident MCI. These baseline psychiatric symptoms were of similar or greater magnitude as biomarkers (genetic and structural MRI) in predicting the risk of incident MCI.