Spectroscopic changes associated with mild cognitive impairment and dementia in Parkinson's disease

MRS in neurodegenerative dementias, prodromal syndromes and at-risk states: A systematic review of the literature

BACKGROUND

In recent years, MRS has benefited from increased MRI field strengths, new acquisition protocols and new processing techniques. This review aims to determine how this has altered our understanding of MRS neurometabolic markers in neurodegenerative dementias.

METHODS

Our systematic review of human in vivo MRS literature since 2002 pertains to Alzheimer's disease (AD), dementia with Lewy bodies (DLB), Parkinson's disease dementia, frontotemporal dementia (FTD), prodromal and 'at-risk' states. Studies using field strengths of 3 T or more were included.

RESULTS

Of 85 studies, AD and/or mild cognitive impairment (MCI) were the most common conditions of interest (58 papers, 68%). Only 14 (16%) studies included other dementia syndromes and 13 (15%) investigated 'at-risk' cohorts. Earlier findings of lower N-acetylaspartate and higher myo-inositol were confirmed. Additionally, lower choline and creatine in AD and MCI were reported, though inconsistently. Previously challenging-to-measure metabolites (glutathione, glutamate and gamma-aminobutyric acid) were reportedly lower in AD, FTD and DLB compared with controls.

DISCUSSION

Increasing field strength alongside targeted acquisition protocols has revealed additional metabolite changes. Most studies were small and regional metabolite differences between dementia types may not have been captured due to the predominant placement of voxels in the posterior cingulate cortex. The standard of data collection, quality control and analysis is improving due to greater consensus regarding acquisition and processing techniques. Ongoing harmonization of techniques, creation of larger and longitudinal cohorts, and placement of MRS voxels in more diverse regions will strengthen future research.

Identification of metabolic correlates of mild cognitive impairment in Parkinson's disease using magnetic resonance spectroscopic imaging and machine learning

OBJECTIVE

To investigate metabolic changes of mild cognitive impairment in Parkinson's disease (PD-MCI) using proton magnetic resonance spectroscopic imaging (¹H-MRSI).

METHODS

Sixteen healthy controls (HC), 26 cognitively normal Parkinson's disease (PD-CN) patients, and 34 PD-MCI patients were scanned in this prospective study. Neuropsychological tests were performed, and three-dimensional ¹H-MRSI was obtained at 3 T. Metabolic parameters and neuropsychological test scores were compared between PD-MCI, PD-CN, and HC. The correlations between neuropsychological test scores and metabolic intensities were also assessed. Supervised machine learning algorithms were applied to classify HC, PD-CN, and PD-MCI groups based on metabolite levels.

RESULTS

PD-MCI had a lower corrected total N-acetylaspartate over total creatine ratio (tNAA/tCr) in the right precentral gyrus, corresponding to the sensorimotor network (p = 0.01), and a lower tNAA over myoinositol ratio (tNAA/mI) at a part of the default mode network, corresponding to the retrosplenial cortex (p = 0.04) than PD-CN. The HC and PD-MCI patients were classified with an accuracy of 86.4% (sensitivity = 72.7% and specificity = 81.8%) using bagged trees.

CONCLUSION

¹H-MRSI revealed metabolic changes in the default mode, ventral attention/salience, and sensorimotor networks of PD-MCI patients, which could be summarized mainly as 'posterior cortical metabolic changes' related with cognitive dysfunction.

Does Prefrontal Glutamate Index Cognitive Changes in Parkinson's Disease?

Introduction

Cognitive impairment is a highly prevalent non-motor feature of Parkinson's disease (PD). A better understanding of the underlying pathophysiology may help in identifying therapeutic targets to prevent or treat dementia. This study sought to identify metabolic alterations in the prefrontal cortex (PFC), a key region for cognitive functioning that has been implicated in cognitive dysfunction in PD.

Methods

Proton Magnetic Resonance Spectroscopy was used to investigate metabolic changes in the PFC of a cohort of cognitively normal individuals without PD (CTL), as well as PD participants with either normal cognition (PD-NC), mild cognitive impairment (PD-MCI), or dementia (PDD). Ratios to Creatine (Cre) resonance were obtained for glutamate (Glu), glutamine and glutamate combined (Glx), N-acetylaspartate (NAA), myoinositol (mI), and total choline (Cho), and correlated with cognitive scores across multiple domains (executive function, learning and memory, language, attention, visuospatial function, and global cognition) administered to the PD participants only.

Results

When individuals retain cognitive capabilities, the presence of Parkinson's disease does not create metabolic disturbances in the PFC. However, when cognitive symptoms are present, PFC Glu/Cre ratios decrease with significant differences between the PD-NC and PPD groups. In addition, Glu/Cre ratios and memory scores were marginally associated, but not after Bonferroni correction.

Conclusion

These preliminary findings indicate that fluctuations in prefrontal glutamate may constitute a biomarker for the progression of cognitive impairments in PD. We caution for larger MRS investigations of carefully defined PD groups.

Magnetic Resonance Imaging Markers for Cognitive Impairment in Parkinson’s Disease: Current View

Cognitive impairment (CI) ranging from mild cognitive impairment (MCI) to dementia is a common and disturbing complication in patients with Parkinson’s disease (PD). Numerous studies have focused on neuropathological mechanisms underlying CI in PD, along with the identification of specific biomarkers for CI. Magnetic resonance imaging (MRI), a promising method, has been adopted to examine the changes in the brain and identify the candidate biomarkers associated with CI. In this review, we have summarized the potential biomarkers for CI in PD which have been identified through multi-modal MRI studies. Structural MRI technology is widely used in biomarker research. Specific patterns of gray matter atrophy are promising predictors of the evolution of CI in patients with PD. Moreover, other MRI techniques, such as MRI related to small-vessel disease, neuromelanin-sensitive MRI, quantitative susceptibility mapping, MR diffusion imaging, MRI related to cerebrovascular abnormality, resting-state functional MRI, and proton magnetic resonance spectroscopy, can provide imaging features with a good degree of prediction for CI. In the future, novel combined biomarkers should be developed using the recognized analysis tools and predictive algorithms in both cross-sectional and longitudinal studies.

Proton Magnetic Resonance Spectroscopy for Diagnosis of Non-Motor Symptoms in Parkinson's Disease

BACKGROUND

The current diagnosis of Parkinson's disease (PD) is mainly based on the typical clinical manifestations. However, 60% dopaminergic neurons have died when the typical clinical manifestations occur. Predictive neurobiomarkers may help identify those PD patients having non-motor disorders or in different stage and achieving the aim of early diagnosis. Up to date, few if any neuroimaging techniques have been described useful for non-movement disorders diagnosis in PD patients. Here, we investigated the alteration of metabolites in PD patients in different stage of PD and non-motor symptoms including sleep, gastrointestinal and cognitive dysfunction, by using the 1H-MRS.

METHODS

A total of 48 subjects were included between 2017 and 2019: 37 PD (15 men, age 47-82 years) and 11 healthy people (8 men, age 49-74 years). All participants underwent MRI and multi-voxel ¹H-MRS examination within 3 days in admission. Six kinds of metabolites, such as creatine (Cr), N-acetyl aspartate/creatine (NAA/Cr), N-acetyl aspartate/choline (NAA/Cho), choline/creatine (Cho/Cr), lipid/creatine (LL/Cr), and myo-Inositol/creatine ratio (mI/Cr) were tested among the PD group and the control groups. Statistical analyses and correlation analyses were performed by using SPSS. The p < 0.05 was considered statistically significant.

RESULTS

Compared late PD group with a control group or early group, higher Cr ratio and lower NAA/Cr ratio were observed in the late PD group (p < 0.05). The mI/Cr in the late PD group was also lower than that in the early PD group (p < 0.05). Regarding the relationship between metabolites and NMS, Cho/Cr was higher in the sleep disorder group, whereas mI/Cr was lower in the gastrointestinal dysfunction group in comparison with the non-symptom groups. Moreover, Cr, Cho/Cr, mI/Cr, and LL/Cr were identified to have higher concentrations in the cognitive group in thalamus.

CONCLUSIONS

Proton magnetic resonance spectroscopy is an advanced tool to quantify the metabolic changes in PD. Three biomarkers (Cr, NAA/Cr, and mI/Cr) were detected in the late stage of PD, suggesting that these markers might be potential to imply the progression of PD. In addition, subgroups analysis showed that MRS of thalamus is a sensitive region for the detection of cognitive decline in PD, and the alteration of neurochemicals (involving Cr, Cho, mI, and LL) may be promising biomarkers to predict cognitive decline in PD.

Frontal lobe metabolic alterations characterizing Parkinson's disease cognitive impairment

BACKGROUND AND PURPOSE

Diagnosis of Parkinson's disease (PD) cognitive impairment at early stages is challenging compared to the stage of PD dementia where functional impairment is apparent and easily diagnosed. Hence, to evaluate potential early stage cognitive biomarkers, we assessed frontal lobe metabolic alterations using in vivo multi-voxel proton magnetic resonance spectroscopic imaging (¹H-MRSI).

METHOD

Frontal metabolism was studied in patients with PD with normal cognition (PD-CN) (n = 26), with cognitive impairment (PD-CI) (n = 27), and healthy controls (HC) (n = 30) using a single slice (two-dimensional) ¹H-MRSI at 3 T. The acquired spectra were post-processed distinctly for voxels corresponding to the bilateral middle/superior frontal gray matter (GM) and frontal white matter (WM) regions (delineated employing neuromorphometrics atlas) using the LC-Model software.

RESULT

Significant (post hoc p < 0.016) reduction in the concentration of N-acetyl aspartate (NAA) in the middle and superior frontal GMs and total choline (tCho) and total creatine (tCr) in the frontal WM was observed in PD-CI compared to PD-CN and HC, while that in HC and PD-CN groups were comparable. The NAA and tCr/tCho metabolite concentrations showed significant (p < 0.05) positive correlations with cognitive test scores in the frontal GM and WM, respectively. The receiver operating curve (ROC) analysis revealed significant (p < 0.05) "area under curve" for NAA/tNAA in the frontal GM and tCho in the frontal WM.

CONCLUSION

The frontal metabolic profile is altered in cognitively impaired PD compared with cognitively normal PD. Neuronal function loss (NAA), altered energy metabolism (Cr), and cholinergic (Cho) neural transmission are implicated in PD cognitive pathology. Frontal neuro-metabolism may promisingly serve as PD cognitive biomarker.

A Dietary Ketone Ester Normalizes Abnormal Behavior in a Mouse Model of Alzheimer's Disease

Because of a decreased sensitivity toward insulin, a key regulator of pyruvate dehydrogenase (PDH), Alzheimer’s patients have lower brain glucose utilization with reductions in Tricarboxylic Acid (TCA) cycle metabolites such as citrate, a precursor to n-acetyl-aspartate. In the 3xTgAd mouse model of Alzheimer’s disease (AD), aging mice also demonstrate low brain glucose metabolism. Ketone metabolism can overcome PDH inhibition and restore TCA cycle metabolites, thereby enhancing amino acid biosynthesis. A ketone ester of d-β-hydroxybutyrate was incorporated into a diet (Ket) and fed to 3xTgAd mice. A control group was fed a calorically matched diet (Cho). At 15 months of age, the exploratory and avoidance-related behavior patterns of the mice were evaluated. At 16.5 months of age, the animals were euthanized, and their hippocampi were analyzed for citrate, α-ketoglutarate, and amino acids. In the hippocampi of the Ket-fed mice, there were higher concentrations of citrate and α-ketoglutarate as well as higher concentrations of glutamate, aspartate and n-acetyl-aspartate compared with controls. There were positive associations between (1) concentrations of aspartate and n-acetyl-aspartate (n = 14, R = 0.9327), and (2) α-ketoglutarate and glutamate (n = 14, R = 0.8521) in animals maintained on either diet. Hippocampal n-acetyl-aspartate predicted the outcome of several exploratory and avoidance-related behaviors. Ketosis restored citrate and α-ketoglutarate in the hippocampi of aging mice. Higher concentrations of n-acetyl-aspartate corresponded with greater exploratory activity and reduced avoidance-related behavior.

Apathy as a behavioural marker of cognitive impairment in Parkinson's disease: a longitudinal analysis

Background

Understanding the longitudinal course of non-motor symptoms, and finding markers to predict cognitive decline in Parkinson’s disease (PD), are priorities. Previous work has demonstrated that apathy is one of the only behavioural symptoms that differentiates people with PD and intact cognition from those with mild cognitive impairment (MCI-PD). Other psychiatric symptoms emerge as dementia in PD develops.

Objective

We explored statistical models of longitudinal change to detect apathy as a behavioural predictor of cognitive decline in PD.

Methods

We followed 104 people with PD intermittently over 2 years, undertaking a variety of motor, behavioural and cognitive measures. We applied a linear mixed effects model to explore behavioural factors associated with cognitive change over time. Our approach goes beyond conventional modelling based on a random-intercept and slope approach, and can be used to examine the variability in measures within individuals over time.

Results

Global cognitive scores worsened during the two-year follow-up, whereas the longitudinal evolution of self-rated apathy scores and other behavioural measures was negligible. Level of apathy was negatively (− 0.598) correlated with level of cognitive impairment and participants with higher than average apathy scores at baseline also had poorer cognition. The model indicated that departure from the mean apathy score at any point in time was mirrored by a corresponding departure from average global cognitive score.

Conclusion

High levels of apathy are predictive of negative cognitive and behavioural outcomes over time, suggesting that apathy may be a behavioural indicator of early cognitive decline. This has clinical and prognostic implications.

Electronic supplementary material

The online version of this article (10.1007/s00415-019-09538-z) contains supplementary material, which is available to authorized users.

Can neuroimaging predict dementia in Parkinson's disease?

Dementia in Parkinson's disease affects 50% of patients within 10 years of diagnosis but there is wide variation in severity and timing. Thus, robust neuroimaging prediction of cognitive involvement in Parkinson's disease is important: (i) to identify at-risk individuals for clinical trials of potential new treatments; (ii) to provide reliable prognostic information for individuals and populations; and (iii) to shed light on the pathophysiological processes underpinning Parkinson's disease dementia. To date, neuroimaging has not made major contributions to predicting cognitive involvement in Parkinson's disease. This is perhaps unsurprising considering conventional methods rely on macroscopic measures of topographically distributed neurodegeneration, a relatively late event in Parkinson's dementia. However, new technologies are now emerging that could provide important insights through detection of other potentially relevant processes. For example, novel MRI approaches can quantify magnetic susceptibility as a surrogate for tissue iron content, and increasingly powerful mathematical approaches can characterize the topology of brain networks at the systems level. Here, we present an up-to-date overview of the growing role of neuroimaging in predicting dementia in Parkinson's disease. We discuss the most relevant findings to date, and consider the potential of emerging technologies to detect the earliest signs of cognitive involvement in Parkinson's disease.

Biomarkers for dementia and mild cognitive impairment in Parkinson's disease

Cognitive decline is one of the most frequent and disabling nonmotor features of Parkinson's disease. Around 30% of patients with Parkinson's disease experience mild cognitive impairment, a well-established risk factor for the development of dementia. However, mild cognitive impairment in patients with Parkinson's disease is a heterogeneous entity that involves different types and extents of cognitive deficits. Because it is not currently known which type of mild cognitive impairment confers a higher risk of progression to dementia, it would be useful to define biomarkers that could identify these patients to better study disease progression and possible interventions. In this sense, the identification among patients with Parkinson's disease and mild cognitive impairment of biomarkers associated with dementia would allow the early detection of this process. This review summarizes studies from the past 25 years that have assessed the potential biomarkers of dementia and mild cognitive impairment in Parkinson's disease patients. Despite the potential importance, no biomarker has as yet been validated. However, features such as low levels of epidermal and insulin-like growth factors or uric acid in plasma/serum and of Aß in CSF, reduction of cerebral cholinergic innervation and metabolism measured by PET mainly in posterior areas, and hippocampal atrophy in MRI might be indicative of distinct deficits with a distinct risk of dementia in subgroups of patients. Longitudinal studies combining the existing techniques and new approaches are needed to identify patients at higher risk of dementia. © 2016 International Parkinson and Movement Disorder Society.

Basic Principles and Clinical Applications of Magnetic Resonance Spectroscopy in Neuroradiology

Magnetic resonance spectroscopy is a powerful tool to assist daily clinical diagnostics. This review is intended to give an overview on basic principles of the technology, discuss some of its technical aspects, and present typical applications in daily clinical routine in neuroradiology.

Validation of the Chinese version of Addenbrooke's cognitive examination-revised for screening mild Alzheimer's disease and mild cognitive impairment

BACKGROUND/AIMS

As a suitable test to screen for Alzheimer's disease (AD) or mild cognitive impairment (MCI), studies to validate the Chinese version of Addenbrooke's Cognitive Examination-Revised (ACE-R) are rare.

METHODS

A total of 151 subjects were recruited and the neuropsychological assessments were employed. One-way analysis of variance and Bonferroni correction were used to compare scores of different psychometric scales. Intraclass correlation coefficient (ICC) and Cronbach's coefficient α were used to evaluate the reliability of psychometric scales. The validity of ACE-R to screen for mild AD and amnestic subtype of MCI (a-MCI) was assessed by receiver operating characteristic (ROC) curves.

RESULTS

The Chinese ACE-R had good reliability (inter-rater ICC = 0.994; test-retest ICC = 0.967) as well as reliable internal consistency (Cronbach's coefficient α = 0.859). With its cutoff of 67/68, the sensitivity (0.920) and specificity (0.857) were lower than for the Mini-Mental State Examination (MMSE) cutoff (sensitivity 1.000 and specificity 0.937) to screen for mild AD. However, the sensitivity of ACE-R to screen for a-MCI was superior to the MMSE with a cutoff of 85/86. The specificity of ACE-R was lower than that of the MMSE to screen for a-MCI. The area under the ROC curve of ACE-R was much larger than that of the MMSE (0.836 and 0.751) for detecting a-MCI rather than mild AD.

CONCLUSION

The Chinese ACE-R is a reliable assessment tool for cognitive impairment. It is more sensitive and accurate in screening for a-MCI rather than for AD compared to the MMSE.

Comparison of activities of daily living impairments in Parkinson's disease patients as defined by the Pill Questionnaire and assessments by neurologists

OBJECTIVES

To compare the clinical judgment of experienced neurologists after interviewing Parkinson's disease (PD) patients and their caregivers with the use of the Pill Questionnaire to determine the presence of impairments on activities of daily living (ADL).

BACKGROUND

ADL impairment is a criterion for the diagnosis of dementia associated with PD. The Pill Questionnaire has been recommended as a screening tool to assess ADL impairment in PD patients, but its usefulness and validity have not been fully investigated.

METHODS

We recruited idiopathic PD patients from 12 hospitals in Taiwan, and the patients underwent clinical assessments, a neuropsychological test battery and the Unified Parkinson Disease Rating Scale evaluation. The Pill Questionnaire was administered by study assistants. Patient and caregiver interviews were performed by experienced neurologists who were blinded to the Pill Questionnaire results.

RESULTS

In total, 284 PD patients (mean age 71.8±9 years, mean education 8.7±5.3 years, mean disease duration 5.4±5.3 years) were recruited. 63 patients showed ADL impairment by the Pill Questionnaire, and 108 patients showed ADL impairment by neurologists' clinical interviews. κ Statistics showed moderate agreement between the two methods (κ=0.521, p<0.001). Of the 108 patients who were diagnosed with ADL impairment by neurologists, only 56 patients (51.9%) showed impairment according to the Pill Questionnaire. Most of the missed patients had milder cognitive impairment and lower motor disability.

CONCLUSIONS

A comprehensive interview is essential to determine the presence of ADL impairment in PD patients, especially in patients with early PD.

Magnetic resonance spectroscopy in the diagnosis of dementia with Lewy bodies

Dementia with Lewy bodies (DLB) is considered to be the second most frequent primary degenerative dementing illness after Alzheimer's disease (AD). DLB, together with Parkinson's disease (PD), Parkinson's disease with dementia (PDD) belong to α-synucleinopathies—a group of neurodegenerative diseases associated with pathological accumulation of the α-synuclein protein. Dementia due to PD and DLB shares clinical symptoms and neuropsychological profiles. Moreover, the core features and additional clinical signs and symptoms for these two very similar diseases are largely the same. Neuroimaging seems to be a promising method in differential diagnosis of dementia studies. The development of imaging methods or other objective measures to supplement clinical criteria for DLB is needed and a method which would accurately facilitate diagnosis of DLB prior to death is still being searched. Proton magnetic resonance spectroscopy (¹H-MRS) provides a noninvasive method of assessing an in vivo biochemistry of brain tissue. This review summarizes the main results obtained from the application of neuroimaging techniques in DLB cases focusing on ¹H-MRS.

Measuring functional impact of cognitive impairment: validation of the Parkinson's disease cognitive functional rating scale

BACKGROUND

Little is known on the impact of cognitive impairment on instrumental activities of daily living (IADL) in pre-dementia stages of Parkinson's disease (PD).

OBJECTIVE

To investigate the clinimetric properties, applicability and responsiveness of a brief questionnaire (twelve-item; maximum score = 24) for rating functional abnormalities associated to cognitive impairment in non-demented PD patients (ND-PD).

METHODS

Two studies were carried-out: (1) a clinimetric study validated the Parkinson's Disease-Cognitive Functional Rating Scale (PD-CFRS) against the Older Americans Resource Survey (OARS-IADL) in 53 ND-PD patients and 53 matched controls; (2) A prospective multicenter 6-month responsiveness study involving 120 ND-PD patients explored sensitivity to change.

RESULTS

In the clinimetric study the PD-CFRS showed intermediate concurrent validity (ICC = 0.50), high test-retest (ICC = 0.82), inter-rater reliability (ICC = 0.80) and internal consistency (Cronbach's α = 0.79), and higher coefficient of variation to detect dysfunction in ND-PD patients (PD-CFRS 86.6% vs. OARS-IADL 8.1%). There was a strong relationship between the PD-CFRS and the global cognitive status determined with the PD-Cognitive Rating Scale (r = -0.72, p < 0.0001). The responsiveness study recruited 63 patients with normal cognition and 57 with mild cognitive impairment (MCI); an increase of 2 points in the PD-CFRS after 6 months was associated with a clinically significant worsening of the cognitive functional status. According to a discriminant analysis a PD-CFRS cut-off score of ≥3 was found to be optimal for detecting functional impairment in PD-MCI patients.

CONCLUSIONS

Cognitive impairment exerts measurable impact on IADL in ND-PD patients that can be reliable measured with the PD-CFRS, a PD-validated instrument that can be useful in clinical and research settings.

Predictors of mild cognitive impairment in early-stage Parkinson's disease

Aim

The aim of this study was to identify mild cognitive deficits in Parkinson's disease (PD) prior to extensive neurodegeneration and to evaluate the extent to which dopamine depletion and other disease-related predictors can explain cognitive profiles.

Methods

Neuropsychological performances of 40 nondemented early-stage PD patients and 42 healthy controls were compared across on or off dopaminergic medications. Stepwise regression evaluated cognitive predictors of early-stage PD and disease-related predictors of PD cognition (levodopa dose, disease duration, Unified Parkinson's Disease Rating Scale score, sleep, quality of life, and mood) across on and off states.

Results

Neuropsychological performance was lower in PD patients across cognitive domains with significant memory, naming, visuomotor, and complex attention/executive deficits, but with intact visuospatial, simple attention, and phonemic fluency functions. However, medication effects were absent except for simple attention. Regression analyses revealed age, working memory, and memory recall to be the best cognitive predictors of PD, while age, quality of life, disease duration, and anxiety predicted PD cognition in the off state.

Conclusion

Nondemented early-stage PD patients presented with extensive mild cognitive deficits including prominent memory impairment. The profile was inconsistent with expected isolated frontostriatal dysfunction previously attributed to dopamine depletion and this highlights the need to further characterize extranigral sources of mild cognitive impairment in PD.