APOE, thought disorder, and SPARE-AD predict cognitive decline in established Parkinson's disease

Hypoperfusion in Alzheimer's Disease-Prone Regions and Dementia Conversion in Parkinson's Disease

PURPOSE OF THE REPORT

Although early detection of individuals at risk of dementia conversion is important in patients with Parkinson's disease (PD), there is still no consensus on neuroimaging biomarkers for predicting future cognitive decline. We aimed to investigate whether cerebral perfusion patterns on early-phase 18 F-N-(3-fluoropropyl)-2β-carboxymethoxy-3β-(4-iodophenyl) nortropane ( 18 F-FP-CIT) PET have the potential to serve as a neuroimaging predictor for early dementia conversion in patients with PD.

MATERIALS AND METHODS

In this retrospective analysis, we enrolled 187 patients with newly diagnosed PD who underwent dual-phase 18 F-FP-CIT PET at initial assessment and serial cognitive assessments during the follow-up period (>5 years). Patients with PD were classified into 2 groups: the PD with dementia (PDD)-high-risk (PDD-H; n = 47) and the PDD-low-risk (PDD-L; n = 140) groups according to dementia conversion within 5 years of PD diagnosis. We explored between-group differences in the regional uptake in the early-phase 18 F-FP-CIT PET images. We additionally performed a linear discriminant analysis to develop a prediction model for early PDD conversion.

RESULTS

The PDD-H group exhibited hypoperfusion in Alzheimer's disease (AD)-prone regions (inferomedial temporal and posterior cingulate cortices, and insula) compared with the PDD-L group. A prediction model using regional uptake in the right entorhinal cortex, left amygdala, and left isthmus cingulate cortex could optimally distinguish the PDD-H group from the PDD-L group.

CONCLUSIONS

Regional hypoperfusion in the AD-prone regions on early-phase 18 F-FP-CIT PET can be a useful biomarker for predicting early dementia conversion in patients with PD.

Genetic and phenotypic characterization of Parkinson's disease at the clinic-wide level

Observational studies in Parkinson's disease (PD) deeply characterize relatively small numbers of participants. The Molecular Integration in Neurological Diagnosis Initiative seeks to characterize molecular and clinical features of every PD patient at the University of Pennsylvania (UPenn). The objectives of this study are to determine the feasibility of genetic characterization in PD and assess clinical features by sex and GBA1/LRRK2 status on a clinic-wide scale. All PD patients with clinical visits at the UPenn PD Center between 9/2018 and 12/2022 were eligible. Blood or saliva were collected, and a clinical questionnaire administered. Genotyping at 14 GBA1 and 8 LRRK2 variants was performed. PD symptoms were compared by sex and gene groups. 2063 patients were approached and 1,689 (82%) were enrolled, with 374 (18%) declining to participate. 608 (36%) females were enrolled, 159 (9%) carried a GBA1 variant, and 44 (3%) carried a LRRK2 variant. Compared with males, females across gene groups more frequently reported dystonia (53% vs 46%, p = 0.01) and anxiety (64% vs 55%, p < 0.01), but less frequently reported cognitive impairment (10% vs 49%, p < 0.01) and vivid dreaming (53% vs 60%, p = 0.01). GBA1 variant carriers more frequently reported anxiety (67% vs 57%, p = 0.04) and depression (62% vs 46%, p < 0.01) than non-carriers; LRRK2 variant carriers did not differ from non-carriers. We report feasibility for near-clinic-wide enrollment and characterization of individuals with PD during clinical visits at a high-volume academic center. Clinical symptoms differ by sex and GBA1, but not LRRK2, status.

Spontaneous brain activity in the hippocampal regions could characterize cognitive impairment in patients with Parkinson's disease

OBJECTIVE

This study aimed to investigate whether spontaneous brain activity can be used as a prospective indicator to identify cognitive impairment in patients with Parkinson's disease (PD).

METHODS

Resting-state functional magnetic resonance imaging (RS-fMRI) was performed on PD patients. The cognitive level of patients was assessed by the Montreal Cognitive Assessment (MoCA) scale. The fractional amplitude of low-frequency fluctuation (fALFF) was applied to measure the strength of spontaneous brain activity. Correlation analysis and between-group comparisons of fMRI data were conducted using Rest 1.8. By overlaying cognitively characterized brain regions and defining regions of interest (ROIs) based on their spatial distribution for subsequent cognitive stratification studies.

RESULTS

A total of 58 PD patients were enrolled in this study. They were divided into three groups: normal cognition (NC) group (27 patients, average MoCA was 27.96), mild cognitive impairment (MCI) group (21 patients, average MoCA was 23.52), and severe cognitive impairment (SCI) group (10 patients, average MoCA was 17.3). It is noteworthy to mention that those within the SCI group exhibited the most advanced chronological age, with an average of 74.4 years, whereas the MCI group displayed a higher prevalence of male participants at 85.7%. It was found hippocampal regions were a stable representative brain region of cognition according to the correlation analysis between the fALFF of the whole brain and cognition, and the comparison of fALFF between different cognitive groups. The parahippocampal gyrus was the only region with statistically significant differences in fALFF among the three cognitive groups, and it was also the only brain region to identify MCI from NC, with an AUC of 0.673. The paracentral lobule, postcentral gyrus was the region that identified SCI from NC, with an AUC of 0.941. The midbrain, hippocampus, and parahippocampa gyrus was the region that identified SCI from MCI, with an AUC of 0.926.

CONCLUSION

The parahippocampal gyrus was the potential brain region for recognizing cognitive impairment in PD, specifically for identifying MCI. Thus, the fALFF of parahippocampal gyrus is expected to contribute to future study as a multimodal fingerprint for early warning.

Clinical biomarkers for Lewy body diseases

Synucleinopathies are a group of neurodegenerative disorders characterized by pathologic aggregates of neural and glial α-synuclein (α-syn) in the form of Lewy bodies (LBs), Lewy neurites, and cytoplasmic inclusions in both neurons and glia. Two major classes of synucleinopathies are LB disease and multiple system atrophy. LB diseases include Parkinson's disease (PD), PD with dementia, and dementia with LBs. All are increasing in prevalence. Effective diagnostics, disease-modifying therapies, and therapeutic monitoring are urgently needed. Diagnostics capable of differentiating LB diseases are based on signs and symptoms which might overlap. To date, no specific diagnostic test exists despite disease-specific pathologies. Diagnostics are aided by brain imaging and cerebrospinal fluid evaluations, but more accessible biomarkers remain in need. Mechanisms of α-syn evolution to pathologic oligomers and insoluble fibrils can provide one of a spectrum of biomarkers to link complex neural pathways to effective therapies. With these in mind, we review promising biomarkers linked to effective disease-modifying interventions.

Cognitive heterogeneity in Parkinson's disease: A mechanistic view

Cognitive impairment occurs in most individuals with Parkinson's disease (PD), exacting a high toll on patients, their caregivers, and the healthcare system. In this review, we begin by summarizing the current clinical landscape surrounding cognition in PD. We then discuss how cognitive impairment and dementia may develop in PD based on the spread of the pathological protein alpha-synuclein (aSyn) from neurons in brainstem regions to those in the cortical regions of the brain responsible for higher cognitive functions, as first proposed in the Braak hypothesis. We appraise the Braak hypothesis from molecular (conformations of aSyn), cell biological (cell-to-cell spread of pathological aSyn), and organ-level (region-to-region spread of aSyn pathology at the whole brain level) viewpoints. Finally, we argue that individual host factors may be the most poorly understood aspect of this pathological process, accounting for substantial heterogeneity in the pattern and pace of cognitive decline in PD.

Age-Related Association Between APOE ɛ4 and Cognitive Progression in de novo Parkinson's Disease

BACKGROUND

APOE ɛ4 genotype was correlated with exacerbation of pathology and higher risk of dementia in Parkinson's disease (PD). Meanwhile, the differential influence of APOE ɛ4 on cognition in young and old individuals interpreted as antagonistic pleiotropy.

OBJECTIVE

To examine whether the effect of APOE ɛ4 on cognitive progression in de novo PD is age dependent.

METHODS

In this study, 613 de novo PD patients were recruited from Parkinson's Progression Markers Initiative (PPMI). To examine the age-dependent relationship between APOE ɛ4 and cognitive changes, we added 3-way interaction of APOE ɛ4*baseline age*time to the linear mixed-effect (LME) models and evaluated the specific roles of APOE ɛ4 in the middle age group and elderly group separately. Cox regression was utilized to examine the progression of cognition in age-stratified PD participants.

RESULTS

Age significantly modified relationship between APOE ɛ4 and cognitive changes in most cognitive domains (pinteraction <0.05). In the elderly group, APOE ɛ4 carriers showed steeper decline in global cognition (p = 0.001) as well as in most cognitive domains, and they had a greater risk of cognitive progression (adjusted HR 1.625, 95% CI 1.143-2.310, p = 0.007), compared with non-carriers. However, in the middle age group, no significant relationships between APOE ɛ4 and cognitive decline can be detected.

CONCLUSION

Our results indicated that the APOE ɛ4 allele has an age-dependent effect on cognitive decline in PD patients. The underlying mechanisms need to be investigated in the future.

Nomogram for Prediction of Postoperative Delirium after Deep Brain Stimulation of Subthalamic Nucleus in Parkinson’s Disease under General Anesthesia

Introduction. Postoperative delirium can increase cognitive impairment and mortality in patients with Parkinson’s disease. The purpose of this study was to develop and internally validate a clinical prediction model of delirium after deep brain stimulation of the subthalamic nucleus in Parkinson’s disease under general anesthesia. Methods. We conducted a retrospective observational cohort study on the data of 240 patients with Parkinson’s disease who underwent deep brain stimulation of the subthalamic nucleus under general anesthesia. Demographic characteristics, clinical evaluation, imaging data, laboratory data, and surgical anesthesia information were collected. Multivariate logistic regression was used to develop the prediction model for postoperative delirium. Results. A total of 159 patients were included in the cohort, of which 38 (23.90%) had postoperative delirium. Smoking (OR 4.51, 95% CI 1.56–13.02, $p<0.01$ ) was the most important risk factor; other independent predictors were orthostatic hypotension (OR 3.42, 95% CI 0.90–13.06, $p=0.07$ ), inhibitors of type-B monoamine oxidase (OR 3.07, 95% CI 1.17–8.04, $p=0.02$ ), preoperative MRI with silent brain ischemia or infarction (OR 2.36, 95% CI 0.90–6.14, $p=0.08$ ), Hamilton anxiety scale score (OR 2.12, 95% CI 1.28–3.50, $p<0.01$ ), and apolipoprotein E level in plasma (OR 1.48, 95% CI 0.95–2.29, $p=0.08$ ). The area under the receiver operating characteristic curve (AUC) was 0.76 (95% CI 0.66–0.86). A nomogram was established and showed good calibration and clinical predictive capacity. After bootstrap for internal verification, the AUC was 0.74 (95% CI 0.66–0.83). Conclusion. This study provides evidence for the independent inducing factors of delirium after deep brain stimulation of the subthalamic nucleus in Parkinson’s disease under general anesthesia. By predicting the development of delirium, our model may identify high-risk groups that can benefit from early or preventive intervention.

Mild cognitive impairment in patients with Parkinson’s disease: An updated mini-review and future outlook

Mild cognitive impairment (MCI) is one of the common non-motor symptoms in patients with Parkinson’s disease (PD). MCI is the transition stage between normal aging and full-blown dementia and is also a powerful predictor of dementia. Although the concept of MCI has been used to describe some of the PD symptoms for many years, there is a lack of consistent diagnostic criteria. Moreover, because of the diverse patterns of the cognitive functions, each cognitive impairment will have a different progression. In this review, we overviewed the diagnostic criteria for PD-MCI, primarily focused on the heterogeneity of PD-MCI patients’ cognitive function, including various types of cognitive functions and their progression rates. A review of this topic is expected to be beneficial for clinical diagnosis, early intervention, and treatment. In addition, we also discussed the unmet needs and future vision in this field.

Plasma MIA, CRP, and Albumin Predict Cognitive Decline in Parkinson's Disease

OBJECTIVE

Using a multi-cohort, discovery-replication-validation design, we sought new plasma biomarkers that predict which individuals with Parkinson's disease (PD) will experience cognitive decline.

METHODS

In 108 discovery cohort PD individuals and 83 replication cohort PD individuals, we measured 940 plasma proteins on an aptamer-based platform. Using proteins associated with subsequent cognitive decline in both cohorts, we trained a logistic regression model to predict which patients with PD showed fast (> = 1 point drop/year on Montreal Cognitive Assessment [MoCA]) versus slow (< 1 point drop/year on MoCA) cognitive decline in the discovery cohort, testing it in the replication cohort. We developed alternate assays for the top 3 proteins and confirmed their ability to predict cognitive decline - defined by change in MoCA or development of incident mild cognitive impairment (MCI) or dementia - in a validation cohort of 118 individuals with PD. We investigated the top plasma biomarker for causal influence by Mendelian randomization (MR).

RESULTS

A model with only 3 proteins (melanoma inhibitory activity protein [MIA], C-reactive protein [CRP], and albumin) separated fast versus slow cognitive decline subgroups with an area under the curve (AUC) of 0.80 in the validation cohort. The individuals with PD in the validation cohort in the top quartile of risk for cognitive decline based on this model were 4.4 times more likely to develop incident MCI or dementia than those in the lowest quartile. Genotypes at MIA single nucleotide polymorphism (SNP) rs2233154 associated with MIA levels and cognitive decline, providing evidence for MIA's causal influence.

CONCLUSIONS

An easily obtained plasma-based predictor identifies individuals with PD at risk for cognitive decline. MIA may participate causally in development of cognitive decline. ANN NEUROL 2022.

HDL Accessory Proteins in Parkinson’s Disease—Focusing on Clusterin (Apolipoprotein J) in Regard to Its Involvement in Pathology and Diagnostics—A Review

Parkinson’s disease (PD)—a neurodegenerative disorder (NDD) characterized by progressive destruction of dopaminergic neurons within the substantia nigra of the brain—is associated with the formation of Lewy bodies containing mainly α-synuclein. HDL-related proteins such as paraoxonase 1 and apolipoproteins A1, E, D, and J are implicated in NDDs, including PD. Apolipoprotein J (ApoJ, clusterin) is a ubiquitous, multifunctional protein; besides its engagement in lipid transport, it modulates a variety of other processes such as immune system functionality and cellular death signaling. Furthermore, being an extracellular chaperone, ApoJ interacts with proteins associated with NDD pathogenesis (amyloid β, tau, and α-synuclein), thus modulating their properties. In this review, the association of clusterin with PD is delineated, with respect to its putative involvement in the pathological mechanism and its application in PD prognosis/diagnosis.

Cognition and serotonin in Parkinson's disease

Cognitive impairment affects up to 80% of patients with Parkinson's disease (PD) and is associated with poor quality of life. PD cognitive dysfunction includes poor working memory, impairments in executive function and difficulty in set-shifting. The pathophysiology underlying cognitive impairment in PD is still poorly understood, but there is evidence to support involvements of the cholinergic, dopaminergic, and noradrenergic systems. Only rivastigmine, an acetyl- and butyrylcholinesterase inhibitor, is efficacious for the treatment of PD dementia, which limits management of cognitive impairment in PD. Whereas the role of the serotonergic system in PD cognition is less understood, through its interactions with other neurotransmitters systems, namely, the cholinergic system, it may be implicated in cognitive processes. In this chapter, we provide an overview of the pharmacological, clinical and pathological evidence that implicates the serotonergic system in mediating cognition in PD.

Association Between White Matter Connectivity and Early Dementia in Patients With Parkinson Disease

OBJECTIVES

Several clinical and neuroimaging biomarkers have been proposed to identify individuals with Parkinson's disease (PD) who are at risk for ongoing cognitive decline. This study aimed to explore whether white matter (WM) connectivity disruption is associated with dementia conversion in patients with newly diagnosed PD with mild cognitive impairment (PD-MCI).

METHODS

Seventy-five patients with drug-naïve PD-MCI who underwent serial cognitive assessments during the follow-up period (>5 years) were enrolled for the neuroimaging analyses. The patients were classified into either the PD with dementia (PDD) high-risk group (PDD-H, n = 38) or low-risk group (PDD-L, n = 37), depending on whether they converted to dementia within 5 years of PD diagnosis. We conducted degree-based statistic analyses based on a graph-theoretical concept to identify the subnetworks whose WM connectivity was disrupted in the PDD-H group compared with the PDD-L group.

RESULTS

The PDD-H group showed poorer cognitive performance on frontal/executive, visual memory/visuospatial, and attention/working memory/language function than the PDD-L group at baseline assessment. The PDD-H group exhibited more severely disrupted WM connectivity in both frontal and posterior cortical regions with eight hub nodes in the degree-based statistic analysis. The strength of structural connectivity within the identified subnetworks was correlated with the composite scores of frontal/executive function domain (γ = 0.393) and the risk score of PDD conversion within 5 years (γ = -0.480).

CONCLUSIONS

This study demonstrated that disrupted WM connectivity in frontal and posterior cortical regions, which correlated with frontal/executive dysfunction, is associated with early dementia conversion in PD-MCI.

The reduction of hippocampal volume in Parkinson's disease

The volume of the hippocampus decreases more slowly than the volume of the cortex during normal aging. We explored changes in the hippocampus-to-cortex volume (HV:CTV) ratio with increasing age in non-demented Parkinson's disease (PD) patients as compared to healthy controls (HC). We also evaluated the association between the HV:CTV ratio and cognitive outcomes. Altogether 130 participants without dementia aged 51-88 years were consecutively enrolled, including 54 PD patients (mean age 67, standard deviation (SD) 8 years) and 76 HC (mean age 69, SD 7 years). All participants underwent structural magnetic resonance examination and psychological evaluation. Hippocampal and cortex volumes were determined from T1 and FLAIR scans using FreeSurfer software, and the HV:CTV ratio was calculated. Regression lines for age-dependence of the HV:CTV ratio for PD and HC groups were calculated. We further assessed the association between the HV:CTV ratio and cognitive tests examining hippocampus-related cognitive functions. PD patients and age-matched HC showed a significant difference in age-dependence of HV:CTV ratio (p value = 0.012), with a decreasing slope in PD and increasing slope in HC. In the PD group, a significant correlation (R = 0.561, p = 0.024) was observed between the HV:CTV ratio and the Digit Symbol-Coding test. The reduction of HV:CTV ratio is accelerated in pathological aging due to PD pathology. The HV:CTV ratio was associated with impaired processing speed, i.e., the cognitive function that is linked to subcortical alterations of both associated basal ganglia circuitry and the hippocampus.

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.

The impact of common genetic variants in cognitive decline in the first seven years of Parkinson's disease: A longitudinal observational study

INTRODUCTION

Cognitive impairment is a common feature of Parkinson's disease and is a significant determinant of patients' quality of life and dependence. The pattern and progression of cognitive symptoms vary greatly between individuals, and genetic biomarkers may help to predict the severity and trajectory of cognitive impairment in groups of patients.

METHODS

The study included 171 patients from a longitudinal population-based incident Parkinson's disease study from South Western Norway. All participants were followed from the time of diagnosis for up to seven years, undertaking repeated batteries of clinical and neuropsychological tests, measuring global cognitive impairment, executive function, attention, verbal learning and memory, and visuospatial skills. We used linear mixed regression analyses to explore associations between the function in specific cognitive domains over time and common genetic variants in APOE, MAPT, COMT and BDNF.

RESULTS

The COMT¹⁵⁸Val/Val allele wasassociatedwith faster decline in executive function (p = 0.028), verbal learning and memory (p = 0.029), and visuospatial skills (p = 0.027). The BDNF, MAPT and APOE genotypes were not significantly associated with longitudinal changes in individual cognitive domains, however carriers of the APOE-ε4 allele were shown to be at increased risk of mild cognitive impairment and dementia within the study period (OR3.03; p = 0.006).

CONCLUSIONS

This population-based study of newly diagnosed patients provides new evidence that COMTVal¹⁵⁸Met effects cognitive outcomes limited to discrete domains and APOE-ε4 status predicts a poor overall cognitive prognosis. Together, these data contribute to our understanding of the biology underlying the heterogeneity observed in the progression of PD.

Brain age and Alzheimer's-like atrophy are domain-specific predictors of cognitive impairment in Parkinson's disease

Recently, it was shown that patients with Parkinson's disease (PD) who exhibit an "Alzheimer's disease (AD)-like" pattern of brain atrophy are at greater risk for future cognitive decline. This study aimed to investigate whether this association is domain-specific and whether atrophy associated with brain aging also relates to cognitive impairment in PD. SPARE-AD, an MRI index capturing AD-like atrophy, and atrophy-based estimates of brain age were computed from longitudinal structural imaging data of 178 PD patients and 84 healthy subjects from the LANDSCAPE cohort. All patients underwent an extensive neuropsychological test battery. Patients diagnosed with mild cognitive impairment or dementia were found to have higher SPARE-AD scores as compared to patients with normal cognition and healthy controls. All patient groups showed increased brain age. SPARE-AD predicted impairment in memory, language and executive functions, whereas advanced brain age was associated with deficits in attention and working memory. Data suggest that SPARE-AD and brain age are differentially related to domain-specific cognitive decline in PD. The underlying pathomechanisms remain to be determined.

Are Parkinson's Disease Patients the Ideal Preclinical Population for Alzheimer's Disease Therapeutics?

Concomitant neuropathological hallmarks of Alzheimer's Disease (AD) are common in the brains of people with Parkinson's disease (PD). Furthermore, AD biomarkers are associated with cognitive decline and dementia in PD patients during life. Here, we highlight the considerable overlap between AD and PD, emphasizing neuropathological, biomarker, and mechanistic studies. We suggest that precision medicine approaches may successfully identify PD patients most likely to develop concomitant AD. The ability to identify PD patients at high risk for future concomitant AD in turn provides an ideal cohort for trials of AD-directed therapies in PD patients, aimed at delaying or preventing cognitive symptoms.

APOE genotype regulates pathology and disease progression in synucleinopathy

Apolipoprotein E (APOE) ε4 genotype is associated with increased risk of dementia in Parkinson's disease (PD), but the mechanism is not clear, because patients often have a mixture of α-synuclein (αSyn), amyloid-β (Aβ), and tau pathologies. APOE ε4 exacerbates brain Aβ pathology, as well as tau pathology, but it is not clear whether APOE genotype independently regulates αSyn pathology. In this study, we generated A53T αSyn transgenic mice (A53T) on Apoe knockout (A53T/EKO) or human APOE knockin backgrounds (A53T/E2, E3, and E4). At 12 months of age, A53T/E4 mice accumulated higher amounts of brainstem detergent-insoluble phosphorylated αSyn compared to A53T/EKO and A53T/E3; detergent-insoluble αSyn in A53T/E2 mice was undetectable. By immunohistochemistry, A53T/E4 mice displayed a higher burden of phosphorylated αSyn and reactive gliosis compared to A53T/E2 mice. A53T/E2 mice exhibited increased survival and improved motor performance compared to other APOE genotypes. In a complementary model of αSyn spreading, striatal injection of αSyn preformed fibrils induced greater accumulation of αSyn pathology in the substantia nigra of A53T/E4 mice compared to A53T/E2 and A53T/EKO mice. In two separate cohorts of human patients with PD, APOE ε4/ε4 individuals showed the fastest rate of cognitive decline over time. Our results demonstrate that APOE genotype directly regulates αSyn pathology independent of its established effects on Aβ and tau, corroborate the finding that APOE ε4 exacerbates pathology, and suggest that APOE ε2 may protect against αSyn aggregation and neurodegeneration in synucleinopathies.

APOE4 exacerbates α-synuclein pathology and related toxicity independent of amyloid

The apolipoprotein E (APOE) ε4 allele is the strongest genetic risk factor for late-onset Alzheimer's disease mainly by driving amyloid-β pathology. Recently, APOE4 has also been found to be a genetic risk factor for Lewy body dementia (LBD), which includes dementia with Lewy bodies and Parkinson's disease dementia. How APOE4 drives risk of LBD and whether it has a direct effect on α-synuclein pathology are not clear. Here, we generated a mouse model of synucleinopathy using an adeno-associated virus gene delivery of α-synuclein in human APOE-targeted replacement mice expressing APOE2, APOE3, or APOE4. We found that APOE4, but not APOE2 or APOE3, increased α-synuclein pathology, impaired behavioral performances, worsened neuronal and synaptic loss, and increased astrogliosis at 9 months of age. Transcriptomic profiling in APOE4-expressing α-synuclein mice highlighted altered lipid and energy metabolism and synapse-related pathways. We also observed an effect of APOE4 on α-synuclein pathology in human postmortem brains with LBD and minimal amyloid pathology. Our data demonstrate a pathogenic role of APOE4 in exacerbating α-synuclein pathology independent of amyloid, providing mechanistic insights into how APOE4 increases the risk of LBD.

The Cerebellum Is a Common Key for Visuospatial Execution and Attention in Parkinson's Disease

Cognitive decline affects the clinical course in patients with Parkinson's disease (PD) and contributes to a poor prognosis. However, little is known about the underlying network-level abnormalities associated with each cognitive domain. We aimed to identify the networks related to each cognitive domain in PD using resting-state functional magnetic resonance imaging (MRI). Forty patients with PD and 15 normal controls were enrolled. All subjects underwent MRI and the Mini-Mental State Examination. Furthermore, the cognitive function of patients with PD was assessed using the Montreal Cognitive Assessment (MoCA). We used independent component analysis of the resting-state functional MRI for functional segmentation, followed by reconstruction to identify each domain-related network, to predict scores in PD using multiple regression models. Six networks were identified, as follows: the visuospatial-executive-domain-related network (R² = 0.54, p < 0.001), naming-domain-related network (R² = 0.39, p < 0.001), attention-domain-related network (R² = 0.86, p < 0.001), language-domain-related network (R² = 0.64, p < 0.001), abstraction-related network (R² = 0.10, p < 0.05), and orientation-domain-related network (R² = 0.64, p < 0.001). Cerebellar lobule VII was involved in the visuospatial-executive-domain-related and attention-domain-related networks. These two domains are involved in the first three listed nonamnestic cognitive impairment in the diagnostic criteria for PD with dementia (PDD). Furthermore, Brodmann area 10 contributed most frequently to each domain-related network. Collectively, these findings suggest that cerebellar lobule VII may play a key role in cognitive impairment in nonamnestic types of PDD.

Advances in the development paradigm of biosample-based biosensors for early ultrasensitive detection of alzheimer's disease

This review highlights current developments, challenges, and future directions for the use of invasive and noninvasive biosample-based small biosensors for early diagnosis of Alzheimer's disease (AD) with biomarkers to incite a conceptual idea from a broad number of readers in this field. We provide the most promising concept about biosensors on the basis of detection scale (from femto to micro) using invasive and noninvasive biosamples such as cerebrospinal fluid (CSF), blood, urine, sweat, and tear. It also summarizes sensor types and detailed analyzing techniques for ultrasensitive detection of multiple target biomarkers (i.e., amyloid beta (Aβ) peptide, tau protein, Acetylcholine (Ach), microRNA137, etc.) of AD in terms of detection ranges and limit of detections (LODs). As the most significant disadvantage of CSF and blood-based detection of AD is associated with the invasiveness of sample collection which limits future strategy with home-based early screening of AD, we extensively reviewed the future trend of new noninvasive detection techniques (such as optical screening and bio-imaging process). To overcome the limitation of non-invasive biosamples with low concentrations of AD biomarkers, current efforts to enhance the sensitivity of biosensors and discover new types of biomarkers using non-invasive body fluids are presented. We also introduced future trends facing an infection point in early diagnosis of AD with simultaneous emergence of addressable innovative technologies.

APOE and MAPT Are Associated With Dementia in Neuropathologically Confirmed Parkinson's Disease

Introduction: Cognitive decline and dementia are common and debilitating non-motor phenotypic features of Parkinson's disease with a variable severity and time of onset. Common genetic variation of the Apolipoprotein E (APOE) and micro-tubule associated protein tau (MAPT) loci have been linked to cognitive decline and dementia in Parkinson's disease, although studies have yielded mixed results. To further elucidate the influence of APOE and MAPT variability on dementia in Parkinson's disease, we genotyped postmortem brain tissue samples of clinically and pathologically well-characterized Parkinson's donors and performed a survival analysis of time to dementia.

Methods: We included a total of 152 neuropathologically confirmed Parkinson's disease donors with or without clinical dementia during life. We genotyped known risk variants tagging the APOE ε4 allele and MAPT H1/H2 inversion haplotype. Cox proportional hazards regression analyses adjusted for age at onset, sex and genetic principal components were performed to assess the association between the genetic variants and time from motor onset to onset of dementia.

Results: We found that both the APOE ε4 allele (HR 1.82, 95 % CI 1.16–2.83, p = 0.009) and MAPT H1-haplotype (HR 1.71, 95 % CI 1.06–2.78, p = 0.03) were associated with earlier development of dementia in patients with Parkinson's disease.

Conclusion: Our results provide further support for the importance of APOE ε4 and MAPT H1-haplotype in the etiology of Parkinson's disease dementia, with potential future relevance for risk stratification and patient selection for clinical trials of therapies targeting cognitive decline in Parkinson's disease.

Mapping the Interactive Effects of ApoE Gene Polymorphism on Caudate Functional Connectivity in Mild Cognitive Impairment Associated With Parkinson's Disease

Introduction

Cognitive impairment (CI) is a frequent non-motor symptom of Parkinson’s disease (PD). Caudate and Apolipoprotein E (ApoE) are biomarkers linked to CI in PD. There is little known about whether ApoE affects caudate in mild CI of PD (PD-MCI). We investigated the possible interactive effect of ApoE genotypes on caudate functional connectivity (FC) in PD-MCI.

Methods

A total of 95 PD-MCI patients and 99 matched healthy controls underwent extensive neuropsychological assessment and magnetic resonance imaging. The two groups were separated into three subgroups according to their genotyping. Functional data were analyzed with FC analysis.

Results

Decreased FC between the caudate and the bilateral inferior orbit frontal gyrus and bilateral middle occipital gyrus (MOG) was found between groups, along with poor performance in general, executive, episodic memory, language, and visual–spatial function. Decreased FC between the caudate and right MOG, right middle temporal gyrus, and right superior occipital gyrus was found as an interaction effect. The FC values of ε4 carriers with PD-MCI were much lower than the other carriers, and FC was positively correlated with the impairment of global and language function.

Conclusion

These results support the idea that altered FC between the bilateral caudate and posterior cortical regions was interactively influenced by ApoE genotype and PD-MCI status, and the ε4 subtype associated with underlying pathology of global cognitive decline and semantic fluency impairment in an interactive manner. Gene-based imaging approaches might strengthen the credibility in imaging genetic associations, which might provide new powerful insights into the neural mechanisms underlying PD-MCI.

Mining genetic and transcriptomic data using machine learning approaches in Parkinson's disease

High-throughput techniques have generated abundant genetic and transcriptomic data of Parkinson’s disease (PD) patients but data analysis approaches such as traditional statistical methods have not provided much in the way of insightful integrated analysis or interpretation of the data. As an advanced computational approach, machine learning, which enables people to identify complex patterns and insight from data, has consequently been harnessed to analyze and interpret large, highly complex genetic and transcriptomic data toward a better understanding of PD. In particular, machine learning models have been developed to integrate patient genotype data alone or combined with demographic, clinical, neuroimaging, and other information, for PD outcome study. They have also been used to identify biomarkers of PD based on transcriptomic data, e.g., gene expression profiles from microarrays. This study overviews the relevant literature on using machine learning models for genetic and transcriptomic data analysis in PD, points out remaining challenges, and suggests future directions accordingly. Undoubtedly, the use of machine learning is amplifying PD genetic and transcriptomic achievements for accelerating the study of PD. Existing studies have demonstrated the great potential of machine learning in discovering hidden patterns within genetic or transcriptomic information and thus revealing clues underpinning pathology and pathogenesis. Moving forward, by addressing the remaining challenges, machine learning may advance our ability to precisely diagnose, prognose, and treat PD.

Factor analysis-derived cognitive profile predicting early dementia conversion in PD

OBJECTIVES

To investigate which baseline neuropsychological profile predicts the risk of developing dementia in early-stage Parkinson disease (PD).

METHODS

We retrospectively reviewed detailed medical records of 350 drug-naive patients with early-stage PD (follow-up >3 years) who underwent a detailed neuropsychological test at initial assessment. Factor analysis was conducted to determine cognitive profiles that yielded 4 cognitive function factors: factor 1, visual memory/visuospatial; factor 2, verbal memory; factor 3, frontal/executive; and factor 4, attention/working memory/language. Subsequently, we assessed the effect of these cognitive function factors on the risk for dementia conversion. We also constructed a nomogram to calculate the risk for developing dementia over a 5-year follow-up period based on these cognitive profiles.

RESULTS

Cox regression analysis demonstrated that a higher composite score of factor 1 (hazard ratio [HR] 0.558, 95% confidence interval [CI] 0.427-0.730), factor 2 (HR 0.768, 95% CI 0.596-0.991), and factor 3 (HR 0.425, 95% CI 0.305-0.593) was associated with a lower risk for dementia conversion, while factor 3 had the most predictive power. The nomogram had a fair ability (Heagerty integrated area under the curve 0.763) to estimate the risk for dementia conversion within 5 years. The composite scores of factor 3 contributed more to the occurrence of dementia in PD than those of the other cognitive function factors.

CONCLUSIONS

These findings suggest that these factor analysis-derived cognitive profiles can be used to predict dementia conversion in early-stage PD. In addition, frontal/executive dysfunction contributes most to the occurrence of dementia in PD.

A novel method of evaluating semantic intrusion errors to distinguish between amyloid positive and negative groups on the Alzheimer's disease continuum

BACKGROUND

The development and validation of clinical outcome measures to detect early cognitive decline associated with Alzheimer's disease (AD) biomarkers is imperative. Semantic intrusions on the Loewenstein Acevedo Scales of Semantic Interference and Learning (LASSI-L) has outperformed widely used cognitive measures as an early correlate of elevated brain amyloid in prodromal AD and has distinguished those with amnestic mild cognitive impairment (aMCI) and high amyloid load from aMCI attributable to other non-AD conditions.

METHODS

Since intrusion errors on memory tasks vary widely, we employed a novel method that accounts for the percentage of intrusion errors (PIE) in relation to total responses. Individuals with either high or low amyloid load across the spectrum of aMCI and dementia and amyloid negative cognitively normal older adults (CN) were studied.

RESULTS

Mean PIE on indices sensitive to proactive semantic interference (PSI) and failure to recover from proactive semantic interference (frPSI) could distinguish amyloid positive from amyloid negative aMCI and dementia groups. Number of correct responses alone, while able to differentiate the different diagnostic groups, did not differentiate amyloid positive aMCI from their counterparts without amyloid pathology.

CONCLUSIONS

PIE, a novel and sensitive index of early memory dysfunction, demonstrated high levels of sensitivity and specificity in differentiating CN from amyloid positive persons with preclinical AD. Mean levels of PIE are higher for amyloid positive aMCI and dementia participants relative to their amyloid negative counterparts.

Pathological Influences on Clinical Heterogeneity in Lewy Body Diseases

PD, PD with dementia, and dementia with Lewy bodies are clinical syndromes characterized by the neuropathological accumulation of alpha-synuclein in the CNS that represent a clinicopathological spectrum known as Lewy body disorders. These clinical entities have marked heterogeneity of motor and nonmotor symptoms with highly variable disease progression. The biological basis for this clinical heterogeneity remains poorly understood. Previous attempts to subtype patients within the spectrum of Lewy body disorders have centered on clinical features, but converging evidence from studies of neuropathology and ante mortem biomarkers, including CSF, neuroimaging, and genetic studies, suggest that Alzheimer's disease beta-amyloid and tau copathology strongly influence clinical heterogeneity and prognosis in Lewy body disorders. Here, we review previous clinical biomarker and autopsy studies of Lewy body disorders and propose that Alzheimer's disease copathology is one of several likely pathological contributors to clinical heterogeneity of Lewy body disorders, and that such pathology can be assessed in vivo. Future work integrating harmonized assessments and genetics in PD, PD with dementia, and dementia with Lewy bodies patients followed to autopsy will be critical to further refine the classification of Lewy body disorders into biologically distinct endophenotypes. This approach will help facilitate clinical trial design for both symptomatic and disease-modifying therapies to target more homogenous subsets of Lewy body disorders patients with similar prognosis and underlying biology. © 2019 International Parkinson and Movement Disorder Society.

Gray Matter Changes in Parkinson's and Alzheimer's Disease and Relation to Cognition

PURPOSE OF REVIEW

We summarize structural (s)MRI findings of gray matter (GM) atrophy related to cognitive impairment in Alzheimer's disease (AD) and Parkinson's disease (PD) in light of new analytical approaches and recent longitudinal studies results.

RECENT FINDINGS

The hippocampus-to-cortex ratio seems to be the best sMRI biomarker to discriminate between various AD subtypes, following the spatial distribution of tau pathology, and predict rate of cognitive decline. PD is clinically far more variable than AD, with heterogeneous underlying brain pathology. Novel multivariate approaches have been used to describe patterns of early subcortical and cortical changes that relate to more malignant courses of PD. New emerging analytical approaches that combine structural MRI data with clinical and other biomarker outcomes hold promise for detecting specific GM changes in the early stages of PD and preclinical AD that may predict mild cognitive impairment and dementia conversion.

Characterization of Parkinson's disease using blood-based biomarkers: A multicohort proteomic analysis

BACKGROUND

Parkinson's disease (PD) is a progressive neurodegenerative disease affecting about 5 million people worldwide with no disease-modifying therapies. We sought blood-based biomarkers in order to provide molecular characterization of individuals with PD for diagnostic confirmation and prediction of progression.

METHODS AND FINDINGS

In 141 plasma samples (96 PD, 45 neurologically normal control [NC] individuals; 45.4% female, mean age 70.0 years) from a longitudinally followed Discovery Cohort based at the University of Pennsylvania (UPenn), we measured levels of 1,129 proteins using an aptamer-based platform. We modeled protein plasma concentration (log10 of relative fluorescence units [RFUs]) as the effect of treatment group (PD versus NC), age at plasma collection, sex, and the levodopa equivalent daily dose (LEDD), deriving first-pass candidate protein biomarkers based on p-value for PD versus NC. These candidate proteins were then ranked by Stability Selection. We confirmed findings from our Discovery Cohort in a Replication Cohort of 317 individuals (215 PD, 102 NC; 47.9% female, mean age 66.7 years) from the multisite, longitudinally followed National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP) Cohort. Analytical approach in the Replication Cohort mirrored the approach in the Discovery Cohort: each protein plasma concentration (log10 of RFU) was modeled as the effect of group (PD versus NC), age at plasma collection, sex, clinical site, and batch. Of the top 10 proteins from the Discovery Cohort ranked by Stability Selection, four associations were replicated in the Replication Cohort. These blood-based biomarkers were bone sialoprotein (BSP, Discovery false discovery rate [FDR]-corrected p = 2.82 × 10-2, Replication FDR-corrected p = 1.03 × 10-4), osteomodulin (OMD, Discovery FDR-corrected p = 2.14 × 10-2, Replication FDR-corrected p = 9.14 × 10-5), aminoacylase-1 (ACY1, Discovery FDR-corrected p = 1.86 × 10-3, Replication FDR-corrected p = 2.18 × 10-2), and growth hormone receptor (GHR, Discovery FDR-corrected p = 3.49 × 10-4, Replication FDR-corrected p = 2.97 × 10-3). Measures of these proteins were not significantly affected by differences in sample handling, and they did not change comparing plasma samples from 10 PD participants sampled both on versus off dopaminergic medication. Plasma measures of OMD, ACY1, and GHR differed in PD versus NC but did not differ between individuals with amyotrophic lateral sclerosis (ALS, n = 59) versus NC. In the Discovery Cohort, individuals with baseline levels of GHR and ACY1 in the lowest tertile were more likely to progress to mild cognitive impairment (MCI) or dementia in Cox proportional hazards analyses adjusting for age, sex, and disease duration (hazard ratio [HR] 2.27 [95% CI 1.04-5.0, p = 0.04] for GHR, and HR 3.0 [95% CI 1.24-7.0, p = 0.014] for ACY1). GHR's association with cognitive decline was confirmed in the Replication Cohort (HR 3.6 [95% CI 1.20-11.1, p = 0.02]). The main limitations of this study were its reliance on the aptamer-based platform for protein measurement and limited follow-up time available for some cohorts.

CONCLUSIONS

In this study, we found that the blood-based biomarkers BSP, OMD, ACY1, and GHR robustly associated with PD across multiple clinical sites. Our findings suggest that biomarkers based on a peripheral blood sample may be developed for both disease characterization and prediction of future disease progression in PD.

Apolipoprotein E and Alzheimer disease: pathobiology and targeting strategies

Polymorphism in the apolipoprotein E (APOE) gene is a major genetic risk determinant of late-onset Alzheimer disease (AD), with the APOE*ε4 allele conferring an increased risk and the APOE*ε2 allele conferring a decreased risk relative to the common APOE*ε3 allele. Strong evidence from clinical and basic research suggests that a major pathway by which APOE4 increases the risk of AD is by driving earlier and more abundant amyloid pathology in the brains of APOE*ε4 carriers. The number of amyloid-β (Aβ)-dependent and Aβ-independent pathways that are known to be differentially modulated by APOE isoforms is increasing. For example, evidence is accumulating that APOE influences tau pathology, tau-mediated neurodegeneration and microglial responses to AD-related pathologies. In addition, APOE4 is either pathogenic or shows reduced efficiency in multiple brain homeostatic pathways, including lipid transport, synaptic integrity and plasticity, glucose metabolism and cerebrovascular function. Here, we review the recent progress in clinical and basic research into the role of APOE in AD pathogenesis. We also discuss how APOE can be targeted for AD therapy using a precision medicine approach.

Frontal atrophy as a marker for dementia conversion in Parkinson's disease with mild cognitive impairment

This study aimed to investigate the cortical neural correlates of dementia conversion in Parkinson's disease with mild cognitive impairment (PD-MCI). We classified 112 patients with drug-naïve early stage PD meeting criteria for PD-MCI into either PD with dementia (PDD) converters (n = 34) or nonconverters (n = 78), depending on whether they developed dementia within 4 years of PD diagnosis. Cortical thickness analyses were performed in 34 PDD converters and 34 matched nonconverters. Additionally, a linear discriminant analysis was performed to distinguish PDD converters from nonconverters using cortical thickness of the regions that differed between the two groups. The PDD converters had higher frequencies of multiple domain MCI and amnestic MCI with storage failure, and poorer cognitive performances on frontal/executive, memory, and language function domains than did the nonconverters. Cortical thinning extending from the posterior cortical area into the frontal region was observed in PDD converters relative to nonconverters. The discriminant analysis showed that the prediction model with two cortical thickness variables in the right medial superior frontal and left olfactory cortices optimally distinguished PDD converters from nonconverters. Our data suggest that cortical thinning in the frontal areas including the olfactory cortex is a marker for early dementia conversion in PD-MCI.

Mind the gaps: What we don't know about cognitive impairment in essential tremor

INTRODUCTION

Although the hallmark feature of essential tremor (ET) is tremor, there is growing appreciation that cognitive impairment also occurs, including increased prevalence of mild cognitive impairment (MCI) and increased prevalence and incidence of dementia. With emerging knowledge of ET-cognitive impairment, come fundamental questions regarding its course, bases, predictors and clinical outcomes. Studies in the general population and in Parkinson's disease (PD), a related movement disorder, offer a starting point from which to begin filling these clinically important knowledge gaps.

METHODS

A PubMed search (June 2018) identified articles for this review.

RESULTS

Much of our knowledge of cognitive impairment in ET is of the static condition (e.g., prevalence of cognitive impairment in ET), with nearly no information on its bases, predictors and dynamics (i.e., course, and clinical outcomes). In PD, where such data have been published, rates of cognitive decline and conversion to MCI/dementia are higher than in the general population. Predictors of cognitive change in PD and the general population have also been identified, yet they only partially overlap one another.

CONCLUSION

The predictors and dynamics of cognitive impairment have been investigated fairly extensively in the general population, to a somewhat lesser extent in PD, and are emerging only now in ET. We suggest that longitudinal studies specific to ET are needed, and we outline variables to be considered in these investigations. Increased knowledge of ET-cognitive impairment will facilitate meaningful counseling of patients and their families.

APOE-ε4 associates with hippocampal volume, learning, and memory across the spectrum of Alzheimer's disease and dementia with Lewy bodies

INTRODUCTION

Although the apolipoprotein E ε4-allele (APOE-ε4) is a susceptibility factor for Alzheimer's disease (AD) and dementia with Lewy bodies (DLB), its relationship with imaging and cognitive measures across the AD/DLB spectrum remains unexplored.

METHODS

We studied 298 patients (AD = 250, DLB = 48; 38 autopsy-confirmed; NCT01800214) using neuropsychological testing, volumetric magnetic resonance imaging, and APOE genotyping to investigate the association of APOE-ε4 with hippocampal volume and learning/memory phenotypes, irrespective of diagnosis.

RESULTS

Across the AD/DLB spectrum: (1) hippocampal volumes were smaller with increasing APOE-ε4 dosage (no genotype × diagnosis interaction observed), (2) learning performance as assessed by total recall scores was associated with hippocampal volumes only among APOE-ε4 carriers, and (3) APOE-ε4 carriers performed worse on long-delay free word recall.

DISCUSSION

These findings provide evidence that APOE-ε4 is linked to hippocampal atrophy and learning/memory phenotypes across the AD/DLB spectrum, which could be useful as biomarkers of disease progression in therapeutic trials of mixed disease.

Dementia with Lewy bodies and Parkinson's disease-dementia: current concepts and controversies

Dementia with Lewy bodies (DLB) and Parkinson's disease-dementia (PDD), although sharing many clinical, neurochemical and morphological features, according to DSM-5, are two entities of major neurocognitive disorders with Lewy bodies of unknown etiology. Despite considerable clinical overlap, their diagnosis is based on an arbitrary distinction between the time of onset of motor and cognitive symptoms: dementia often preceding parkinsonism in DLB and onset of cognitive impairment after onset of motor symptoms in PDD. Both are characterized morphologically by widespread cortical and subcortical α-synuclein/Lewy body plus β-amyloid and tau pathologies. Based on recent publications, including the fourth consensus report of the DLB Consortium, a critical overview is given. The clinical features of DLB and PDD include cognitive impairment, parkinsonism, visual hallucinations, and fluctuating attention. Intravitam PET and post-mortem studies revealed more pronounced cortical atrophy, elevated cortical and limbic Lewy pathologies (with APOE ε4), apart from higher prevalence of Alzheimer pathology in DLB than PDD. These changes may account for earlier onset and greater severity of cognitive defects in DLB, while multitracer PET studies showed no differences in cholinergic and dopaminergic deficits. DLB and PDD sharing genetic, neurochemical, and morphologic factors are likely to represent two subtypes of an α-synuclein-associated disease spectrum (Lewy body diseases), beginning with incidental Lewy body disease-PD-nondemented-PDD-DLB (no parkinsonism)-DLB with Alzheimer's disease (DLB-AD) at the most severe end, although DLB does not begin with PD/PDD and does not always progress to DLB-AD, while others consider them as the same disease. Both DLB and PDD show heterogeneous pathology and neurochemistry, suggesting that they share important common underlying molecular pathogenesis with AD and other proteinopathies. Cognitive impairment is not only induced by α-synuclein-caused neurodegeneration but by multiple regional pathological scores. Recent animal models and human post-mortem studies have provided important insights into the pathophysiology of DLB/PDD showing some differences, e.g., different spreading patterns of α-synuclein pathology, but the basic pathogenic mechanisms leading to the heterogeneity between both disorders deserve further elucidation. In view of the controversies about the nosology and pathogenesis of both syndromes, there remains a pressing need to differentiate them more clearly and to understand the processes leading these synucleinopathies to cause one disorder or the other. Clinical management of both disorders includes cholinesterase inhibitors, other pharmacologic and nonpharmacologic strategies, but these have only a mild symptomatic effect. Currently, no disease-modifying therapies are available.