RESUMO
The Movement Disorder Society Task Force (MDS-TF) has proposed diagnostic criteria for mild cognitive impairment in Parkinson's disease (PD-MCI). We hypothesized that the risk of dementia (PDD) varies across the different cutoff schemes allowed. A longitudinal study followed 121 non-demented PD patients for up to 4.5 years. In Part One, unique groups of patients were identified as PD-MCI at baseline using the MDS-TF requirement of two impaired cognitive test scores, with both scores classified as impaired at either (i) 2 s.d., (ii) 1.5 s.d. or (iii) 1 s.d. below normative data; relative risk (RR) of PDD was assessed at each criterion. In Part Two, the whole sample was reassessed and (i) RR of PDD determined when two impairments at 1.5 s.d. existed within a single cognitive domain, followed by (ii) RR of PDD in the unique group whose two impairments at 1.5 s.d. did not exist within a single domain (i.e., only across two domains). Twenty-one percent of patients converted to PDD. Part One showed that the 1.5 s.d. criterion at baseline is optimal to maximize progression to PDD over 4 years. Part Two, however, showed that the 1.5 s.d. cutoff produced a high RR of PDD only when two impairments were identified within a single cognitive domain (7.2, 95% confidence interval (CI)=3.4-16.6, P<0.0001; 51% converted). The RR when the 1.5 s.d. impairments occurred only across two different domains, was nonsignificant (1.7, CI=0.5-7.4, P=0.13; 11% converted) and similar to using a 1 s.d. criterion (1.9, CI=0.3-4.3, P=0.13; 8% converted). If the intent of a PD-MCI diagnosis is to detect increased risk of PDD in the next 4 years, optimal criteria should identify at least two impairments at 1.5 s.d. within a single cognitive domain.
RESUMO
INTRODUCTION: Parkinson's Disease (PD) is classified as a motor disorder, but most patients develop cognitive impairment, and eventual dementia (PDD). Predictive neurobiomarkers may be useful in the identification of those patients at imminent risk of PDD. Given the compromised cerebral integrity in PDD, we investigated whether brain metabolites track disease progression over time. METHODS: Proton Magnetic Resonance Spectroscopy (MRS) was used to identify brain metabolic changes associated with cognitive impairment and dementia in PD. Forty-nine healthy participants and 130 PD patients underwent serial single voxel proton MRS and neuropsychological testing. At baseline patients were classified as either having normal cognitive status (PDN, n = 77), mild cognitive impairment (PDMCI, n = 33), or dementia (PDD, n = 20). Posterior cingulate cortex (PCC) was examined to quantify N-acetylaspartate (NAA), choline (Cho), creatine (Cr), and myo-inositol (mI). A hierarchical Bayesian model was used to assess whether cognitive ability and other covariates were related to baseline MRS values and changes in MRS over time. RESULTS: At baseline, relative to controls, PDD had significantly decreased NAA/Cr and increased Cho/Cr. However, these differences did not remain significant after accounting for age, sex, and MDS-UPDRS III. At follow-up, no significant changes in MRS metabolite ratios were detected, with no relationship found between MRS measures and change in cognitive status. CONCLUSIONS: Unlike Alzheimer's disease, single voxel MR spectroscopy of the PCC failed to show any significant association with cognitive status at baseline or over time. This suggests that MRS of PCC is not a clinically useful biomarker for tracking or predicting cognitive impairment in Parkinson's disease.