Purpose: To verify the associations between white matter hyperintensities (WMHs), plasma homocysteine (Hcy) levels, and mild cognitive impairment (MCI) in Parkinson’s disease (PD) patients and evaluate the predictive value of combination of WMHs and plasma Hcy levels for MCI.
Patients and methods: In this study, 387 patients with PD were divided into MCI group and non-MCI group. Their cognition was evaluated with a comprehensive neuropsychological evaluation including 10 tests. Five cognitive domains, including the memory, attention/working memory, visuospatial, executive and language domains, were evaluated using two tests for each domain. MCI was determined when at least two tests demonstrated abnormal results, either one impaired test in two different cognitive domains or two impaired tests in a single cognitive domain. Multivariate analysis was performed to determine risk factors for MCI in PD patients. The receiver operating characteristic (ROC) curve was employed to assess the predictive values, and the Z test was employed to compare the area under curve (AUC).
Results: MCI was identified in 195 PD patients with an incidence of 50.4%. Multivariate analysis results showed that PWMHs (OR: 5.162, 95% CI: 2.318~9.527), Hcy levels (OR: 1.189, 95% CI: 1.071~1.405) and MDS-UPDRS part III score (OR: 1.173, 95% CI: 1.062~1.394) were independently correlated with MCI in PD patients after adjusting for confounders. ROC curves showed that the AUCs of PWMHs, Hcy levels and their combination were 0.701 (SE: 0.026, 95% CI: 0.647~0.752), 0.688 (SE: 0.027, 95% CI: 0.635~0.742) and 0.879 (SE: 0.018, 95% CI: 0.844~0.915), respectively. Z test showed that the AUC of combination prediction was significantly higher than those of individual predictions (0.879 vs 0.701, Z=5.629, P < 0.001; 0.879 vs 0.688, Z=5.886, P < 0.001).
Conclusion: The combination of WMHs and plasma Hcy levels could be applied in the prediction of MCI in PD patients.
Keywords: Parkinson’s disease, mild cognitive impairment, white matter hyperintensities, homocysteine, prediction