The Relationship Between White-matter Alterations And Cognitive Status In Parkinson’s Disease

Chapter I:Background and ObjectiveCognitive impairment, an important non-motor feature of Parkinson’s disease(PD), has recently gained increasing recognition. It can range from mild cognitive impairment (MCI) to dementia. It is estimated that MCI occur in20%to30%of the patients with PD, even among those newly diagnosed, and predict future cognitive decline, including progression to PD with dementia (PDD). MCI is one of key risk factors for PDD. Beside the disability it creates, PDD doubles the mortality risk of PD and increased caregiver burden. Early diagnosis of MCI will create a potential new target for therapeutic intervention, which may be more effective at slowing progression for PDD.A rapid and easily applied screening test sensitive to cognitive impairment in PD is a more practical approach for clinicians. Only few screening measures have been developed to assess global cognitive functioning in PD, but each has its own limitations. The Mini-Mental State Examination (MMSE) remains the most commonly used screening instrument for PD, but its use in this population has been questioned, both because the MMSE relies heavily on intact verbal rather than visuospatial skills, and because it lacks items to assess executive functions and complex attention. Recently, a new cognitive screening instrument, the Montreal Cognitive Assessment (MoCA), was designed to address some of the limitations of the MMSE. It assesses a broader range of cognitive domains than the MMSE and is more challenging from a cognitive standpoint overall. The MoCA has been shown to be more sensitive than the MMSE for the detection of MCI and mild AD in the general population. The domains of executive and visuospatial function are known to be affected in early PD. Owing to inclusion of complex visuospatial, executive function and attention items into the MoCA, it is implied that MoCA maybe more sensitive than MMSE in evaluating cognitive deficits in PD. There were four studies that used the MoCA in PD populations, and all suggest that the MoCA may be a more appreciate screening instrument for cognitive impairment seen in PD, which is according to our findings. However, these studies have some limitations. However, all of them did not have matched non-PD control group, so it cannot be confirmed whether the non-PD elderly individuals having normal MMSE scores would have demonstrated similar levels of deficits on the MoCA scores. In our study, we hypothesized that the MoCA would be more sensitive than the more widely used MMSE to cognitive impairment in the individuals with PD, and included matched health controls to compare the specificity and sensitivity of two instuments in detecting cognitive impairment of PD.Structural MR imaging results are usually normal in PD patients, even in those undergoing a long disease duration. Single-photon emission CT and Positron-emission tomography, nuclear medicine techniques, provide the best diagnostic sensitivity and specificity, however high cost and low availability of equipment limited their vability. Diffusion tensor imaging (DTI), an MRI technique, can indirectly evaluate the integrity of white-matter tracts by measuring water diffusion and its directionality in three dimensions. Due to its capability of detecting the microstructural alteration of the white matter before volume loss becomes evident, DTI is increasingly being used to measure white-matter tissue microstructure in vivo in various neurological diseases such as multiple system atrophy, diffuse Lewy body disease, multiple sclerosis and amyotrophic lateral sclerosis. However, there are few studies characterizing white matter diffusion changes in patients with PD. Some recent DTI studies showed the evidence that reduced FA in patients with PD in front lobes, premotor areas, the cingulum, in the corpus callosum and the superior longitudinal fasciculus, in the region of interest along a line between the substantia nigra and the lower part of the putamen/caudate complex, suggesting widespread microstructural damage to white matter occurs in early stages of PD.The pathological process of cognitive impairment in PD patients is still unclear. The impaired cognitive domains of PDD are different from that of Alzheimer disease (AD). A wide variety of cognitive deficits in the patients with PD have been reported, even early in the course of the disease, including visuospatial, attention, memory and executive function. Specifically, deficits in attention, visuospatial and executive functions tend to predominate in PDD, however memory and language impairments play a less significant role than they do in AD, so that a "subcortical"cognitive impairment pattern dominates in PDD. White matter comprises many tracts interconnecting parts of the brain, and it play important roles in higher brain functions. White matter alterations are described to contribute to dementia in Alzheimer disease. To our knowledge, there still have no neuropathological studies detecting the relationship between white matter damage and cognitive status in Parkinson’s disease. Quantitative studies of white matter in vivo may be helpful to elucidate the pathological process of cognitive deficits in PD. Diffusion tensor imaging (DTI) can provide quantitative measures of the microstructural integrity of white matter and can ewaluates the microstructural alterations of the white matter via water diffusion in vivo. When white-matter pathology disrupts the coherent orientation of axons, FA of tissue will decrease. Several DTI studies in PD patients have reported decreased fractional anisotropy (FA) and increased mean diffusivity (MD) of white matter, including the frontal lobe, and superior cerebellar peduncle, which implied degradation of the microstructure. Some MRI studies investigated the relationship between white matter and cognitive status in PD. For example, some previous studies found that PDD had significantly higher levels of white matter alterations than the PD without dementia. These findings suggest that white matter alterations may contribute to dementia in PD. However, the effect of white matter alterations on cognitive impairment of the patients with PD is still unclear.As far as we know, only a few studies investigated the relationship between white matter alteration and cognitive status in PD by using diffusion tensor imaging, and only one of them studied the relationship between white matter alteration and cognitive status in PD including PD-MCI, and PDD at the same time. However, there were some limitations in this study published in2011:for example, they did not assess detailed neuropsychological status of patients such as executive, amnestic, visuospatial, attention, and language deficits, so they did not define patients with PD-MCI based on1.5standard deviation below mean score in neuropsychological tests; all MRI scans of this study were acquired on the same1.5Tesla clinical scanner, which probably provide less accruable data compared to3.0Tesla clinical scanner. In our study, we defined PD-MCI based on Neuropsychoclogical test battery, acquired all data from3.0T MR, and drawing the ROIs, a simple and practical measure which could easily be implemented in any clinical radiological setting, aimed to investigate the relationship between white matter alteration and cognitive status including both PD-MCI and PDD. We hypothesized that abnormalities of white matter microstructure is related to the cognitive impairment in PD. In this study, we compared the white-matter alteration among the PD patients with different cognitive status by DTI to elucidate the probably pathological process of conginite impairment in PD.Chapter Ⅱ:Materials and Methods2.1SubjectsSixty-four patients with idiopathic PD (34men and30women; mean age,64.41±10.433years) were enrolled. The diagnosis of possible or probable PD was confirmed by a movement disorders specialist according to established criteria. Basic demographic and clinical information, including the Unified Parkinson’s Disease Rating Scale (UPDRS) and the Hoehn and Yahr stage were obtained from all PD subjects. Exclusion Criteria include:(1) Patients who had undergone deep brain stimulation (DBS) were excluded.(2) Subjects whose MR imaging finding suggests a diagnosis of atypical parkinsonism were excluded.(3) Subjects who had other brain disorders, or underlying diseases that could affect the brain such as uncontrolled hypertension and chronic kidney diseases, were excluded.(4) Subjects who scored above20on the Hamilton Depression Scale (HAMD) were excluded, because of the concern that depression can affect scores on neuropsychologic testing.(5) The patients who could not have MRI performed were excluded.All patients underwent a neuropsychological test battery, and then were divided into three groups according to their cognitive status:(1) Parkinson’s Disease-Cognitively Normal (PD-CogNL). Subjects were found to be cognitively intact and reported no functional deficit due to cognitive problems. They did not meet criteria for MCI or dementia as outlined below.(2) Parkinson’s Disease-Mild Cognitive Impairment (PD-MCI). Criteria for PD-MCI were along the lines of Petersen et al. Individuals had subjective cognitive complaint(s), demonstrated a deficit of at least1.5standard deviation (SD) below the normative data mean score in at least one of four cognitive domains assessed in the battery, but cognitive deficits did not result in significant functional decline. Table1shows the neuropsychological test battery with the associated cognitive domains.(3) PD with dementia (PDD). PDD was diagnosed by the criteria of the task force of the Movement Disorder Society (MDS-TF). Based on the aforementioned above criteria, were enrolled24PD-CogNL,30PD-MCI and10PDD cases.21age-and sex-matched healthy control persons were recruited. All of them had negative anamnesis for neurologic and psychiatric disorders, no relative with a diagnosis of parkinsonism, no abnormalities on structural MR imaging, and no condition that might impair cognition (i.e., head injury, and substance abuse). Controls were assessed with the Mini-Mental State Examination and had a total score greater than26.2.2Neuropsychoclogical testSubjects were administered some Neuropsychoclogical tests following standard procedures by trained research staff. The tests included the Mini-Mental State Examination (MMSE); the Beijing Montreal Cognitive Assessment(MoCA); the Chinese revision of the Wechsler Adult Intelligence Scale(WAIS-RC); the Chinese revision of the Wechsler Memory Scale(WMS); the Diagnostic and Statistical Manual IV(DSM-IV) and the Hamilton Depression Scale. Patients were encouraged to take their regularly scheduled PD medications during the study visit so that they would be evaluated in their "on" state. The MMSE and the Beijing MoCA assess a range of cognitive skills on a scale of0to30points with higher scores indicating better performance and a suggested impairment cutoff of a score less than26on either test. One point was added to an individual’s score of MoCA if she/he had twelve years or fewer of formal education, for a total maximum of30points. Seeing that the items included in two instruments vary by type and level of difficulty, and identical items receive differential weighting, an item-by-item comparison is unsuitable for this study. As an alternative, we divided individual items into four widely used cognitive domains (visuospatial, memory, language, and orientation) based on previous researches. The visuospatial items included design copy(both tests) and figure drawing to command (MoCA only). The memory items included recall of either three (MMSE) or five (MoCA) previously presented words. The language items included phrase/sentence repetition, naming (both tests), verbal commands, and reading comprehension (MMSE only). The MoCA also includes a fifth executive function/attention domain comprised of items for phonemic fluency, visuospatial sequencing/alternation based on auditory span,verbal abstraction, and target detection using auditory attention for the number "1". Because of differential weighting of the serial subtraction items in two tests, we leaved out this item to permit more direct comparisons between instruments.2.3MRI Acquisition ProtocolAll MRI scans were acquired on the same3.0Tesla clinical scanner (GE Signa HDxt America) with8Channel head coil. Head motion was minimised with restraining foam pads provided by the manufacturer. High-resolution T1-weighted MRI was acquired axially using fast-spin echo sequence with the parameters of288×224acquisition,240mm field of view, TE27.3ms and TR1794ms. Diffusion tensor images were then obtained using single-shot echo-planar acquisition from16gradient directions with the following parameters:130×128acquisition matrix with704slices,240mm field of view,3.4×3.4×3mm3voxels, TE87.9ms, TR12s, b-factor of1000s/mm2, without cardiac gating.2.4ROIs Analysis of FAAll images were post-processed on a AW4.4workstation using a program of the Functool image analysis software (GE Healthcare). FA values were obtained from various white matter regions on the DTI scan using regions of interest (ROIs), positioned as shown in Fig1. ROIs setting and measurement of FA values were performed by an experienced neuroradiologist blinded to the profiles of patients. The FA values of ROIs were compared between the four groups. Temporal white matter ROIs (50mm2) was sampled posterolaterally to the lateral fissure on the most caudal slice where the lateral fissure was present. Frontal white matter (50mm2), anterior/posterior cingulate bundle (20mm2), genu and splenium of the corpus callosum (20mm2), and superior longitudinal fasciculus (50mm2) were sampled on the slice that included a fully volumed lateral ventricule. ROIs of parietal white matter (50mm2) were positioned in the white matter posterior to the central sulcus on the most caudal slice where it was visible. The occipital white matter (50mm2) was placed within the optic radiations on the most caudal slice where the occipital horn of the lateral ventricle was imaged. An ROI positioned on the corticospinal tract (20mm2) at the level of the red nucleus, an ROI positioned on the corticospinal tract at the level of the internal capsule (20mm2).2.5Statistical AnalysisStatistical analyses were carried out using SPSS software. Statistical analysis of demographic and clinical data was performed using analysis of variance with post-hoc Turkey’s HSD test for continuous variables, Kruskal-Wallis test with post-hoc Mann-Whitney U-tests for noncontinuous variables, and v2test for categorical data. The receiver operating characteristic (ROC) analyses were used to examine the ability of the two tests to differentiate between PD and control subjects by the total scores and cognitive domains. FA values were compared among the four groups using one-way ANOVA. Fisher’s PLSD was used for post-hoc analysis. The Unified Parkinoson’s Disease Rating Scale (UPDRS) motor score, Hoehn-yahr stage and each FA value that showed significant differences in the first analysis were then used as variables for Logistic regression analysis, and corrected the influence of UPDRS motor score and Hoehn-yahr stage. We also examined correlation analysis between FA values that showed a significant difference and the different status of PD patients. A two-sided significance level of P<0.05was considered to be statistical significant.Chapter III:ResultThere were no significant differences on age, gender, disease duration, or education years among PD-CogNL, PD-MCI, PDD and controls. Both the UPDRS motor score and Hoehn-Yahr stage were significantly higher in PDD (P<0.01), and PD-MCI (P<0.05) compared to patients with PD-CogNL.3.1A comparison of MoCA and MMSE for screening cognitive deficits in the patients with Parkinson’s diseaseCompared with controls, the PD group had significantly lower total scores on both the MoCA and the MMSE. The scores’ranges of the MoCA in both PD group and controls were broader than that of the MMSE. In addition, within-group comparisons indicated that both the PD (Wilcoxon z=-6.707; P<0.01) and controls (Wilcoxon z=-3.147; P<0.05) scores lower on the MoCA compared to the MMSE. When we evaluated the congntive function of the patients with PD by MoCA,76.6%of them were abnormal, however when evaluated by MMSE, only29.7%were abnormal. Among45PD patients having normal MMSE scores,66.7%of them met predefined criteria for cognitive impairment based on their MoCA score. We examined performance of the two groups on total scores and five cognitive domains by ROC analysis. The area under the curve (AUC) values showed that both instruments could significantly differentiate PD from controls on total scores; however, the MoCA score yielded higher sensitivity than the MMSE while maintaining a comparable level of specificity. Both tests accomplished group discrimination on orientation domain successfully. On the contrary, only the MoCA yielded significant AUC values for visuospatial, memory, and language scores, with higher sensitivity and specificity relative to the comparable MMSE domains. Moreover, executive function/attention score of the MoCA yielded a significant AUC for group discrimination.3.2The white matter alterations in the patients with PD without dementiaIn the patients with PD without dementia (Hoehn and Yahr stages I and II), the FA were decresed in some white matter regions, such as bilateral temporal, left anterior cingulate bundle and splenium of the corpus callosum.3.3FA values comparison among PD patients with different cognitive status:Median FA values for each of the white matter regions in four groups are showed in table3-6. Compared to controls, PDD and PD-MCI showed a significant FA reduction in left frontal, right temporal white matter and bilateral anterior cingulated bundles; PD-MCI showed a significant FA reduction in temporal white matter and genu of the corpus callosum; PD-CogNL showed significant FA reduction in left occipital white matter and left anterior cingulated bundle. PDD showed a significant FA reduction in left anterior cingulated bundle, splenium of the corpus callosum compared to other three groups. Even after considering the influence of UPDRS motor score and Hoehn-yahr stage, the FA reduction in left anterior cingulated bundle and genu of the corpus callosum remained significant. However, no significant FA difference was demonstrated for other areas between the four groups. There were significant negative correlations between cognitive status of PD and FA values of some white matter, such as:left frontal, right temporal, left occipital white matter, bilateral anterior cingulated bundles and splenium of the corpus callosum.Chapter IV:Conclusion 4.1Cognitive impairment is a common non-motor feature of Parkinson’s disease (PD), even among those in the early stages of disease, and single domainmild cognitive impairment is more common than multiple domainsmild cognitive impairment. It is important to recognize cognitive impairment in the patients with PD.4.2The Montreal Cognitive Assessment (MoCA) achieved higher sensitivity to screening cognitive impairment in the patients with PD without sacrificing specificity in tototal score and many domains relative to the Mini-Mental State Examination (MMSE). MoCA appears to be the preferable measure for screening cognitive impairment in the patients with PD.4.3In the patients with PD without dementia, the FA were decresed in some white matter regions, which implied widespread microstrutural damage occurs already in the early stages of PD. DTI is helpful to evaluate the white matter damage in PD.4.4The patients with PD had significant micro structural alteration in the some white matter, and correlated with the cognitive status of patients. White matter damage especially in the left anterior cingulate bundle and genu of the corpus callosum probably underlies the cognitive impairments of PD to some extent.