Subthalamic nucleus-language network connectivity predicts dopaminergic modulation of speech function in Parkinson's disease.

Speech impediments are a prominent yet understudied symptom of Parkinson's disease (PD). While the subthalamic nucleus (STN) is an established clinical target for treating motor symptoms, these interventions can lead to further worsening of speech. The interplay between dopaminergic medication, STN circuitry, and their downstream effects on speech in PD is not yet fully understood. Here, we investigate the effect of dopaminergic medication on STN circuitry and probe its association with speech and cognitive functions in PD patients. We found that changes in intrinsic functional connectivity of the STN were associated with alterations in speech functions in PD. Interestingly, this relationship was characterized by altered functional connectivity of the dorsolateral and ventromedial subdivisions of the STN with the language network. Crucially, medication-induced changes in functional connectivity between the STN's dorsolateral subdivision and key regions in the language network, including the left inferior frontal cortex and the left superior temporal gyrus, correlated with alterations on a standardized neuropsychological test requiring oral responses. This relation was not observed in the written version of the same test. Furthermore, changes in functional connectivity between STN and language regions predicted the medication's downstream effects on speech-related cognitive performance. These findings reveal a previously unidentified brain mechanism through which dopaminergic medication influences speech function in PD. Our study sheds light into the subcortical-cortical circuit mechanisms underlying impaired speech control in PD. The insights gained here could inform treatment strategies aimed at mitigating speech deficits in PD and enhancing the quality of life for affected individuals.

AI-based differential diagnosis of dementia etiologies on multimodal data.

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an AI model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations, and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a micro-averaged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the micro-averaged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in various clinical settings and drug trials, with promising implications for person-level management.

Mag-Net: Rapid enrichment of membrane-bound particles enables high coverage quantitative analysis of the plasma proteome.

Membrane-bound particles in plasma are composed of exosomes, microvesicles, and apoptotic bodies and represent ~1-2% of the total protein composition. Proteomic interrogation of this subset of plasma proteins augments the representation of tissue-specific proteins, representing a "liquid biopsy," while enabling the detection of proteins that would otherwise be beyond the dynamic range of liquid chromatography-tandem mass spectrometry of unfractionated plasma. We have developed an enrichment strategy (Mag-Net) using hyper-porous strong-anion exchange magnetic microparticles to sieve membrane-bound particles from plasma. The Mag-Net method is robust, reproducible, inexpensive, and requires <100 µL plasma input. Coupled to a quantitative data-independent mass spectrometry analytical strategy, we demonstrate that we can collect results for >37,000 peptides from >4,000 plasma proteins with high precision. Using this analytical pipeline on a small cohort of patients with neurodegenerative disease and healthy age-matched controls, we discovered 204 proteins that differentiate (q-value < 0.05) patients with Alzheimer's disease dementia (ADD) from those without ADD. Our method also discovered 310 proteins that were different between Parkinson's disease and those with either ADD or healthy cognitively normal individuals. Using machine learning we were able to distinguish between ADD and not ADD with a mean ROC AUC = 0.98 ± 0.06.

Comprehensive proteomics of CSF, plasma, and urine identify DDC and other biomarkers of early Parkinson's disease.

Parkinson's disease (PD) starts at the molecular and cellular level long before motor symptoms appear, yet there are no early-stage molecular biomarkers for diagnosis, prognosis prediction, or monitoring therapeutic response. This lack of biomarkers greatly impedes patient care and translational research-L-DOPA remains the standard of care more than 50 years after its introduction. Here, we performed a large-scale, multi-tissue, and multi-platform proteomics study to identify new biomarkers for early diagnosis and disease monitoring in PD. We analyzed 4877 cerebrospinal fluid, blood plasma, and urine samples from participants across seven cohorts using three orthogonal proteomics methods: Olink proximity extension assay, SomaScan aptamer precipitation assay, and liquid chromatography-mass spectrometry proteomics. We discovered that hundreds of proteins were upregulated in the CSF, blood, or urine of PD patients, prodromal PD patients with DAT deficit and REM sleep behavior disorder or anosmia, and non-manifesting genetic carriers of LRRK2 and GBA mutations. We nominate multiple novel hits across our analyses as promising markers of early PD, including DOPA decarboxylase (DDC), also known as L-aromatic acid decarboxylase (AADC), sulfatase-modifying factor 1 (SUMF1), dipeptidyl peptidase 2/7 (DPP7), glutamyl aminopeptidase (ENPEP), WAP four-disulfide core domain 2 (WFDC2), and others. DDC, which catalyzes the final step in dopamine synthesis, particularly stands out as a novel hit with a compelling mechanistic link to PD pathogenesis. DDC is consistently upregulated in the CSF and urine of treatment-naïve PD, prodromal PD, and GBA or LRRK2 carrier participants by all three proteomics methods. We show that CSF DDC levels correlate with clinical symptom severity in treatment-naïve PD patients and can be used to accurately diagnose PD and prodromal PD. This suggests that urine and CSF DDC could be a promising diagnostic and prognostic marker with utility in both clinical care and translational research.

Multiple biomarkers improve diagnostic accuracy across Lewy body and Alzheimer's disease spectra.

OBJECTIVE: More than half of neurodegenerative disease patients have multiple pathologies at autopsy; however, most receive one diagnosis during life. We used the α-synuclein seed amplification assay (αSyn-SAA) and CSF biomarkers for amyloidosis and Alzheimer's disease (AD) neuropathological change (ADNC) to determine the frequency of co-pathologies in participants clinically diagnosed with Lewy body (LB) disease or AD. METHODS: Using receiver operating characteristic analyses on retrospective CSF samples from 150 participants determined αSyn-SAA accuracy, sensitivity, and specificity for identifying clinically defined LB disease and predicting future change in clinical diagnosis. CSF biomarkers helped determine the frequency of concomitant Lewy body pathology, ADNC, and/or amyloidosis in participants with LB disease and AD, across clinical spectra. RESULTS: Following a decade-long follow-up, the clinically or autopsy-defined diagnosis changed for nine participants. αSyn-SAA demonstrated improved accuracy (91.3%), sensitivity (89.3%), and specificity (93.3%) for identifying LB disease compared to all non-LB disease, highlighting the limitations of clinical diagnosis alone. When examining biomarkers of co-pathology, amyloidosis was present in 18%, 48%, and 71% (χ2(2) = 13.56, p = 0.001) and AD biomarkers were present in 0%, 8.7%, and 42.9% (χ2(2) = 18.44, p < 0.001) of LB disease participants with different stages of cognitive impairment respectively. Co-occurring biomarkers for αSyn-SAA and amyloidosis were present in 12% and 14% of AD compared to 43% and 57% LB disease participants with different stages of cognitive impairment (χ2(3) = 13.87, p = 0.003). INTERPRETATION: Our study shows that using a combination of αSyn-SAA and AD biomarkers can identify people with αSyn, ADNC, and co-pathology better and earlier than traditional clinical diagnostic criteria alone.

Impaired 24-h activity patterns are associated with an increased risk of Alzheimer's disease, Parkinson's disease, and cognitive decline.

BACKGROUND: Sleep-wake regulating circuits are affected during prodromal stages in the pathological progression of both Alzheimer's disease (AD) and Parkinson's disease (PD), and this disturbance can be measured passively using wearable devices. Our objective was to determine whether accelerometer-based measures of 24-h activity are associated with subsequent development of AD, PD, and cognitive decline. METHODS: This study obtained UK Biobank data from 82,829 individuals with wrist-worn accelerometer data aged 40 to 79 years with a mean (± SD) follow-up of 6.8 (± 0.9) years. Outcomes were accelerometer-derived measures of 24-h activity (derived by cosinor, nonparametric, and functional principal component methods), incident AD and PD diagnosis (obtained through hospitalization or primary care records), and prospective longitudinal cognitive testing. RESULTS: One hundred eighty-seven individuals progressed to AD and 265 to PD. Interdaily stability (a measure of regularity, hazard ratio [HR] per SD increase 1.25, 95% confidence interval [CI] 1.05-1.48), diurnal amplitude (HR 0.79, CI 0.65-0.96), mesor (mean activity; HR 0.77, CI 0.59-0.998), and activity during most active 10 h (HR 0.75, CI 0.61-0.94), were associated with risk of AD. Diurnal amplitude (HR 0.28, CI 0.23-0.34), mesor (HR 0.13, CI 0.10-0.16), activity during least active 5 h (HR 0.24, CI 0.08-0.69), and activity during most active 10 h (HR 0.20, CI 0.16-0.25) were associated with risk of PD. Several measures were additionally predictive of longitudinal cognitive test performance. CONCLUSIONS: In this community-based longitudinal study, accelerometer-derived metrics were associated with elevated risk of AD, PD, and accelerated cognitive decline. These findings suggest 24-h rhythm integrity, as measured by affordable, non-invasive wearable devices, may serve as a scalable early marker of neurodegenerative disease.

Speech patterns during memory recall relates to early tau burden across adulthood.

INTRODUCTION: Early cognitive decline may manifest in subtle differences in speech. METHODS: We examined 238 cognitively unimpaired adults from the Framingham Heart Study (32-75 years) who completed amyloid and tau PET imaging. Speech patterns during delayed recall of a story memory task were quantified via five speech markers, and their associations with global amyloid status and regional tau signal were examined. RESULTS: Total utterance time, number of between-utterance pauses, speech rate, and percentage of unique words significantly correlated with delayed recall score although the shared variance was low (2%-15%). Delayed recall score was not significantly different between ß-amyoid-positive (Aß+) and -negative (Aß-) groups and was not associated with regional tau signal. However, longer and more between-utterance pauses, and slower speech rate were associated with increased tau signal across medial temporal and early neocortical regions. DISCUSSION: Subtle speech changes during memory recall may reflect cognitive impairment associated with early Alzheimer's disease pathology. HIGHLIGHTS: Speech during delayed memory recall relates to tau PET signal across adulthood. Delayed memory recall score was not associated with tau PET signal. Speech shows greater sensitivity to detecting subtle cognitive changes associated with early tau accumulation. Our cohort spans adulthood, while most PET imaging studies focus on older adults.

Evaluation of ATNPD Framework and Biofluid Markers to Predict Cognitive Decline in Early Parkinson Disease.

BACKGROUND AND OBJECTIVES: In Parkinson disease (PD), Alzheimer disease (AD) copathology is common and clinically relevant. However, the longitudinal progression of AD CSF biomarkers-ß-amyloid 1-42 (Aß42), phosphorylated tau 181 (p-tau181), and total tau (t-tau)-in PD is poorly understood and may be distinct from clinical AD. Moreover, it is unclear whether CSF p-tau181 and serum neurofilament light (NfL) have added prognostic utility in PD, when combined with CSF Aß42. First, we describe longitudinal trajectories of biofluid markers in PD. Second, we modified the AD ß-amyloid/tau/neurodegeneration (ATN) framework for application in PD (ATNPD) using CSF Aß42 (A), p-tau181 (T), and serum NfL (N) and tested ATNPD prediction of longitudinal cognitive decline in PD. METHODS: Participants were selected from the Parkinson's Progression Markers Initiative cohort, clinically diagnosed with sporadic PD or as controls, and followed up annually for 5 years. Linear mixed-effects models (LMEMs) tested the interaction of diagnosis with longitudinal trajectories of analytes (log transformed, false discovery rate [FDR] corrected). In patients with PD, LMEMs tested how baseline ATNPD status (AD [A+T+N±] vs not) predicted clinical outcomes, including Montreal Cognitive Assessment (MoCA; rank transformed, FDR corrected). RESULTS: Participants were 364 patients with PD and 168 controls, with comparable baseline mean (±SD) age (patients with PD = 62 ± 10 years; controls = 61 ± 11 years]; Mann-Whitney Wilcoxon: p = 0.4) and sex distribution (patients with PD = 231 male individuals [63%]; controls = 107 male individuals [64%]; χ2: p = 1). Patients with PD had overall lower CSF p-tau181 (ß = -0.16, 95% CI -0.23 to -0.092, p = 2.2e-05) and t-tau than controls (ß = -0.13, 95% CI -0.19 to -0.065, p = 4e-04), but not Aß42 (p = 0.061) or NfL (p = 0.32). Over time, patients with PD had greater increases in serum NfL than controls (ß = 0.035, 95% CI 0.022 to 0.048, p = 9.8e-07); slopes of patients with PD did not differ from those of controls for CSF Aß42 (p = 0.18), p-tau181 (p = 1), or t-tau (p = 0.96). Using ATNPD, PD classified as A+T+N± (n = 32; 9%) had worse cognitive decline on global MoCA (ß = -73, 95% CI -110 to -37, p = 0.00077) than all other ATNPD statuses including A+ alone (A+T-N-; n = 75; 21%). DISCUSSION: In patients with early PD, CSF p-tau181 and t-tau were low compared with those in controls and did not increase over 5 years of follow-up. Our study shows that classification using modified ATNPD (incorporating CSF Aß42, CSF p-tau181, and serum NfL) can identify biologically relevant subgroups of PD to improve prediction of cognitive decline in early PD.

Post-translational modifications linked to preclinical Alzheimer's disease-related pathological and cognitive changes.

INTRODUCTION: In this study, we leverage proteomic techniques to identify communities of proteins underlying Alzheimer's disease (AD) risk among clinically unimpaired (CU) older adults. METHODS: We constructed a protein co-expression network using 3869 cerebrospinal fluid (CSF) proteins quantified by SomaLogic, Inc., in a cohort of participants along the AD clinical spectrum. We then replicated this network in an independent cohort of CU older adults and related these modules to clinically-relevant outcomes. RESULTS: We discovered modules enriched for phosphorylation and ubiquitination that were associated with abnormal amyloid status, as well as p-tau181 (M4: ß = 2.44, p < 0.001, M7: ß = 2.57, p < 0.001) and executive function performance (M4: ß = -2.00, p = 0.005, M7: ß = -2.39, p < 0.001). DISCUSSION: In leveraging CSF proteomic data from individuals spanning the clinical spectrum of AD, we highlight the importance of post-translational modifications for early cognitive and pathological changes.

Cerebellar Volume and Disease Staging in Parkinson's Disease: An ENIGMA-PD Study.

BACKGROUND: Increasing evidence points to a pathophysiological role for the cerebellum in Parkinson's disease (PD). However, regional cerebellar changes associated with motor and non-motor functioning remain to be elucidated. OBJECTIVE: To quantify cross-sectional regional cerebellar lobule volumes using three dimensional T1-weighted anatomical brain magnetic resonance imaging from the global ENIGMA-PD working group. METHODS: Cerebellar parcellation was performed using a deep learning-based approach from 2487 people with PD and 1212 age and sex-matched controls across 22 sites. Linear mixed effects models compared total and regional cerebellar volume in people with PD at each Hoehn and Yahr (HY) disease stage, to an age- and sex- matched control group. Associations with motor symptom severity and Montreal Cognitive Assessment scores were investigated. RESULTS: Overall, people with PD had a regionally smaller posterior lobe (dmax = -0.15). HY stage-specific analyses revealed a larger anterior lobule V bilaterally (dmax = 0.28) in people with PD in HY stage 1 compared to controls. In contrast, smaller bilateral lobule VII volume in the posterior lobe was observed in HY stages 3, 4, and 5 (dmax = -0.76), which was incrementally lower with higher disease stage. Within PD, cognitively impaired individuals had lower total cerebellar volume compared to cognitively normal individuals (d = -0.17). CONCLUSIONS: We provide evidence of a dissociation between anterior "motor" lobe and posterior "non-motor" lobe cerebellar regions in PD. Whereas less severe stages of the disease are associated with larger motor lobe regions, more severe stages of the disease are marked by smaller non-motor regions. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Reliability of remote National Alzheimer's Coordinating Center Uniform Data Set data.

INTRODUCTION: The National Alzheimer's Coordinating Center (NACC) Uniform Data Set (UDS) neuropsychological battery is being used to track cognition in participants across the country, but it is unknown if scores obtained through remote administration can be combined with data obtained in person. METHODS: The remote UDS battery includes the blind version of the Montreal Cognitive Assessment (MoCA), Number Span, Semantic and Phonemic Fluency, and Craft Story. For these tests, we assessed intraclass correlation coefficients (ICCs) between in-person and remote scores in 3838 participants with both in-person and remote UDS assessments, and we compared annual score changes between modalities in a subset that had two remote assessments. RESULTS: All tests exhibited moderate to good reliability between modalities (ICCs = 0.590-0.787). Annual score changes were also comparable between modalities except for Craft Story Immediate Recall, Semantic Fluency, and Phonemic Fluency. DISCUSSION: Our findings generally support combining remote and in-person scores for the majority of UDS tests.

An Explainable Geometric-Weighted Graph Attention Network for Identifying Functional Networks Associated with Gait Impairment.

One of the hallmark symptoms of Parkinson's Disease (PD) is the progressive loss of postural reflexes, which eventually leads to gait difficulties and balance problems. Identifying disruptions in brain function associated with gait impairment could be crucial in better understanding PD motor progression, thus advancing the development of more effective and personalized therapeutics. In this work, we present an explainable, geometric, weighted-graph attention neural network (xGW-GAT) to identify functional networks predictive of the progression of gait difficulties in individuals with PD. xGW-GAT predicts the multi-class gait impairment on the MDS-Unified PD Rating Scale (MDS-UPDRS). Our computational- and data-efficient model represents functional connectomes as symmetric positive definite (SPD) matrices on a Riemannian manifold to explicitly encode pairwise interactions of entire connectomes, based on which we learn an attention mask yielding individual- and group-level explainability. Applied to our resting-state functional MRI (rs-fMRI) dataset of individuals with PD, xGW-GAT identifies functional connectivity patterns associated with gait impairment in PD and offers interpretable explanations of functional subnetworks associated with motor impairment. Our model successfully outperforms several existing methods while simultaneously revealing clinically-relevant connectivity patterns. The source code is available at https://github.com/favour-nerrise/xGW-GAT.

Quantitative estimate of cognitive resilience and its medical and genetic associations.

BACKGROUND: We have proposed that cognitive resilience (CR) counteracts brain damage from Alzheimer's disease (AD) or AD-related dementias such that older individuals who harbor neurodegenerative disease burden sufficient to cause dementia remain cognitively normal. However, CR traditionally is considered a binary trait, capturing only the most extreme examples, and is often inconsistently defined. METHODS: This study addressed existing discrepancies and shortcomings of the current CR definition by proposing a framework for defining CR as a continuous variable for each neuropsychological test. The linear equations clarified CR's relationship to closely related terms, including cognitive function, reserve, compensation, and damage. Primarily, resilience is defined as a function of cognitive performance and damage from neuropathologic damage. As such, the study utilized data from 844 individuals (age = 79 ± 12, 44% female) in the National Alzheimer's Coordinating Center cohort that met our inclusion criteria of comprehensive lesion rankings for 17 neuropathologic features and complete neuropsychological test results. Machine learning models and GWAS then were used to identify medical and genetic factors that are associated with CR. RESULTS: CR varied across five cognitive assessments and was greater in female participants, associated with longer survival, and weakly associated with educational attainment or APOE ε4 allele. In contrast, damage was strongly associated with APOE ε4 allele (P value < 0.0001). Major predictors of CR were cardiovascular health and social interactions, as well as the absence of behavioral symptoms. CONCLUSIONS: Our framework explicitly decoupled the effects of CR from neuropathologic damage. Characterizations and genetic association study of these two components suggest that the underlying CR mechanism has minimal overlap with the disease mechanism. Moreover, the identified medical features associated with CR suggest modifiable features to counteract clinical expression of damage and maintain cognitive function in older individuals.

An Explainable Geometric-Weighted Graph Attention Network for Identifying Functional Networks Associated with Gait Impairment.

One of the hallmark symptoms of Parkinson's Disease (PD) is the progressive loss of postural reflexes, which eventually leads to gait difficulties and balance problems. Identifying disruptions in brain function associated with gait impairment could be crucial in better understanding PD motor progression, thus advancing the development of more effective and personalized therapeutics. In this work, we present an explainable, geometric, weighted-graph attention neural network (xGW-GAT) to identify functional networks predictive of the progression of gait difficulties in individuals with PD. xGW-GAT predicts the multi-class gait impairment on the MDS-Unified PD Rating Scale (MDS-UPDRS). Our computational- and data-efficient model represents functional connectomes as symmetric positive definite (SPD) matrices on a Riemannian manifold to explicitly encode pairwise interactions of entire connectomes, based on which we learn an attention mask yielding individual- and group-level explain-ability. Applied to our resting-state functional MRI (rs-fMRI) dataset of individuals with PD, xGW-GAT identifies functional connectivity patterns associated with gait impairment in PD and offers interpretable explanations of functional subnetworks associated with motor impairment. Our model successfully outperforms several existing methods while simultaneously revealing clinically-relevant connectivity patterns. The source code is available at https://github.com/favour-nerrise/xGW-GAT.

Parkinson's Progression Markers Initiative: A Milestone-Based Strategy to Monitor Parkinson's Disease Progression.

BACKGROUND: Identifying a meaningful progression metric for Parkinson's disease (PD) that reflects heterogeneity remains a challenge. OBJECTIVE: To assess the frequency and baseline predictors of progression to clinically relevant motor and non-motor PD milestones. METHODS: Using data from the Parkinson's Progression Markers Initiative (PPMI) de novo PD cohort, we monitored 25 milestones across six domains ("walking and balance"; "motor complications"; "cognition"; "autonomic dysfunction"; "functional dependence"; "activities of daily living"). Milestones were intended to be severe enough to reflect meaningful disability. We assessed the proportion of participants reaching any milestone; evaluated which occurred most frequently; and conducted a time-to-first-event analysis exploring whether baseline characteristics were associated with progression. RESULTS: Half of participants reached at least one milestone within five years. Milestones within the cognitive, functional dependence, and autonomic dysfunction domains were reached most often. Among participants who reached a milestone at an annual follow-up visit and remained active in the study, 82% continued to meet criteria for any milestone at one or more subsequent annual visits and 55% did so at the next annual visit. In multivariable analysis, baseline features predicting faster time to reaching a milestone included age (p < 0.0001), greater MDS-UPDRS total scores (p < 0.0001), higher GDS-15 depression scores (p = 0.0341), lower dopamine transporter binding (p = 0.0043), and lower CSF total α-synuclein levels (p = 0.0030). Symptomatic treatment was not significantly associated with reaching a milestone (p = 0.1639). CONCLUSION: Clinically relevant milestones occur frequently, even in early PD. Milestones were significantly associated with baseline clinical and biological markers, but not with symptomatic treatment. Further studies are necessary to validate these results, further assess the stability of milestones, and explore translating them into an outcome measure suitable for observational and therapeutic studies.

Impact of the Dopamine System on Long-Term Cognitive Impairment in Parkinson Disease: An Exploratory Study.

Background: Little is known about the impact of the dopamine system on development of cognitive impairment (CI) in Parkinson disease (PD). Objectives: We used data from a multi-site, international, prospective cohort study to explore the impact of dopamine system-related biomarkers on CI in PD. Methods: PD participants were assessed annually from disease onset out to 7 years, and CI determined by applying cut-offs to four measures: (1) Montreal Cognitive Assessment; (2) detailed neuropsychological test battery; (3) Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) cognition score; and (4) site investigator diagnosis of CI (mild cognitive impairment or dementia). The dopamine system was assessed by serial Iodine-123 Ioflupane dopamine transporter (DAT) imaging, genotyping, and levodopa equivalent daily dose (LEDD) recorded at each assessment. Multivariate longitudinal analyses, with adjustment for multiple comparisons, determined the association between dopamine system-related biomarkers and CI, including persistent impairment. Results: Demographic and clinical variables associated with CI were higher age, male sex, lower education, non-White race, higher depression and anxiety scores and higher MDS-UPDRS motor score. For the dopamine system, lower baseline mean striatum dopamine transporter values (P range 0.003-0.005) and higher LEDD over time (P range <0.001-0.01) were significantly associated with increased risk for CI. Conclusions: Our results provide preliminary evidence that alterations in the dopamine system predict development of clinically-relevant, cognitive impairment in Parkinson's disease. If replicated and determined to be causative, they demonstrate that the dopamine system is instrumental to cognitive health status throughout the disease course. TRIAL REGISTRATION: Parkinson's Progression Markers Initiative is registered with ClinicalTrials.gov (NCT01141023).

Metrologically Traceable Quantification of 3 Apolipoprotein E Isoforms in Cerebrospinal Fluid.

BACKGROUND: APOE genotype is associated with Alzheimer disease. Thus, the concentration of apolipoprotein E (apoE) isoforms in cerebrospinal fluid (CSF) could be altered in dementia. However, conflicting results have been obtained in different studies. Carefully validated and standardized assays could improve the interpretation of research findings, allow their replication in other laboratories, and generalize their application. METHODS: To evaluate this hypothesis, we aimed to develop, validate, and standardize a new measurement procedure using LC-MS/MS. Purified recombinant apoE protein standards (E2, E3, E4) were thoroughly characterized and used to assign the concentration of a matrix-matched calibration material that contained each apoE isoform, which ensured the metrological traceability of results. RESULTS: The assay of each isoform in human CSF was precise (≤11%CV) and of moderate throughput (approximately 80 samples per day). It demonstrated good linearity and parallelism for lumbar CSF, ventricular CSF, and bovine CSF. The use of an SI-traceable matrix-matched calibrator enabled precise and accurate measurements. There was no association observed between total apoE concentration and the number of Ɛ4 alleles in a cohort of 322 participants. However, the concentration of each isoform was significantly different in heterozygotes, with E4 > E3 > E2. Isoform concentrations were associated with cognitive and motor symptoms but contributed negligibly to a predictive model of cognitive impairment that included established CSF biomarkers. CONCLUSIONS: Our method simultaneously measures each apoE isoform in human CSF with excellent precision and accuracy. A secondary matrix-matched material has been developed and is available to other laboratories to improve interlaboratory agreement.

Reduced and Delayed Cerebrovascular Reactivity in Patients with Parkinson's Disease.

BACKGROUND: Cerebrovascular dysfunction in Parkinson's disease (PD) is heterogeneous and may contribute to disease pathophysiology or progression. There is a need to understand the mechanisms by which cerebrovascular dysfunction is altered in participants with PD. OBJECTIVES: The objective of this study is to test the hypothesis that participants with PD exhibit a significant reduction in the ability of the cerebral vessels to dilate in response to vasoactive challenges relative to healthy controls (HC). METHODS: The current study uses a vasodilatory challenge while participants undergo functional magnetic resonance imaging to quantify the amplitude and delay of cerebrovascular reactivity in participants with PD relative to age and sex-matched HC. An analysis of covariance was used to evaluate differences in cerebrovascular reactivity amplitude and latency between PD participants and HC. RESULTS: A significant main effect of group was observed for whole-brain cerebrovascular reactivity amplitude (F(1, 28) = 4.38, p = 0.046, Hedge's g = 0.73) and latency (F(1, 28) = 16.35, p < 0.001, Hedge's g = 1.42). Participants with PD exhibited reduced whole-brain amplitude and increased latencies in cerebrovascular reactivity relative to HC. The evaluation of regional effects indicates that the largest effects were observed in the cuneus, precuneus, and parietal regions. CONCLUSIONS: PD participants exhibited reduced and delayed cerebrovascular reactivity. This dysfunction may play an important role in chronic hypoxia, neuroinflammation, and protein aggregation, mechanisms that could lead to disease progression. Cerebrovascular reactivity may serve as an important biomarker and target for future interventions. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Gait and balance in apolipoprotein Ɛ4 allele carriers in older adults and Parkinson's disease.

Background: Gait and balance impairments are among the most troublesome and heterogeneous in Parkinson's disease (PD). This heterogeneity may, in part, reflect genetic variation. The apolipoprotein E (APOE) gene has three major allelic variants (ε2, ε3 and ε4). Previous work has demonstrated that older adult (OA) APOE ε4 carriers demonstrate gait deficits. This study compared gait and balance measures between APOE ε4 carriers and non-carriers in both OA and PD. Methods: 334 people with PD (81 APOE ε4 carriers and 253 non-carriers) and 144 OA (41 carriers and 103 non-carriers) were recruited. Gait and balance were assessed using body-worn inertial sensors. Two-way analyses of covariance (ANCOVA) compared gait and balance characteristics between APOE ε4 carriers and non-carriers in people with PD and OA, controlling for age, gender, and testing site. Results: Gait and balance were worse in people with PD compared to OA. However, there were no differences between APOE ε4 carriers and non-carriers in either the OA or PD group. In addition, there were no significant group (OA/PD) by APOE ε4 status (carrier/non-carrier) interaction effects for any measures of gait or balance. Conclusions: Although we found expected impairments in gait and balance in PD compared to OA, gait and balance characteristics did not differ between APOE ε4 carriers and non-carriers in either group. While APOE status did not impact gait and balance in this cross-sectional study, future work is needed to determine whether progression of gait and balance deficits is faster in PD APOE Ɛ4 carriers.

Assessment of heterogeneity among participants in the Parkinson's Progression Markers Initiative cohort using α-synuclein seed amplification: a cross-sectional study.

BACKGROUND: Emerging evidence shows that α-synuclein seed amplification assays (SAAs) have the potential to differentiate people with Parkinson's disease from healthy controls. We used the well characterised, multicentre Parkinson's Progression Markers Initiative (PPMI) cohort to further assess the diagnostic performance of the α-synuclein SAA and to examine whether the assay identifies heterogeneity among patients and enables the early identification of at-risk groups. METHODS: This cross-sectional analysis is based on assessments done at enrolment for PPMI participants (including people with sporadic Parkinson's disease from LRRK2 and GBA variants, healthy controls, prodromal individuals with either rapid eye movement sleep behaviour disorder (RBD) or hyposmia, and non-manifesting carriers of LRRK2 and GBA variants) from 33 participating academic neurology outpatient practices worldwide (in Austria, Canada, France, Germany, Greece, Israel, Italy, the Netherlands, Norway, Spain, the UK, and the USA). α-synuclein SAA analysis of CSF was performed using previously described methods. We assessed the sensitivity and specificity of the α-synuclein SAA in participants with Parkinson's disease and healthy controls, including subgroups based on genetic and clinical features. We established the frequency of positive α-synuclein SAA results in prodromal participants (RBD and hyposmia) and non-manifesting carriers of genetic variants associated with Parkinson's disease, and compared α-synuclein SAA to clinical measures and other biomarkers. We used odds ratio estimates with 95% CIs to measure the association between α-synuclein SAA status and categorical measures, and two-sample 95% CIs from the resampling method to assess differences in medians between α-synuclein SAA positive and negative participants for continuous measures. A linear regression model was used to control for potential confounders such as age and sex. FINDINGS: This analysis included 1123 participants who were enrolled between July 7, 2010, and July 4, 2019. Of these, 545 had Parkinson's disease, 163 were healthy controls, 54 were participants with scans without evidence of dopaminergic deficit, 51 were prodromal participants, and 310 were non-manifesting carriers. Sensitivity for Parkinson's disease was 87·7% (95% CI 84·9-90·5), and specificity for healthy controls was 96·3% (93·4-99·2). The sensitivity of the α-synuclein SAA in sporadic Parkinson's disease with the typical olfactory deficit was 98·6% (96·4-99·4). The proportion of positive α-synuclein SAA was lower than this figure in subgroups including LRRK2 Parkinson's disease (67·5% [59·2-75·8]) and participants with sporadic Parkinson's disease without olfactory deficit (78·3% [69·8-86·7]). Participants with LRRK2 variant and normal olfaction had an even lower α-synuclein SAA positivity rate (34·7% [21·4-48·0]). Among prodromal and at-risk groups, 44 (86%) of 51 of participants with RBD or hyposmia had positive α-synuclein SAA (16 of 18 with hyposmia, and 28 of 33 with RBD). 25 (8%) of 310 non-manifesting carriers (14 of 159 [9%] LRRK2 and 11 of 151 [7%] GBA) were positive. INTERPRETATION: This study represents the largest analysis so far of the α-synuclein SAA for the biochemical diagnosis of Parkinson's disease. Our results show that the assay classifies people with Parkinson's disease with high sensitivity and specificity, provides information about molecular heterogeneity, and detects prodromal individuals before diagnosis. These findings suggest a crucial role for the α-synuclein SAA in therapeutic development, both to identify pathologically defined subgroups of people with Parkinson's disease and to establish biomarker-defined at-risk cohorts. FUNDING: PPMI is funded by the Michael J Fox Foundation for Parkinson's Research and funding partners, including: Abbvie, AcureX, Aligning Science Across Parkinson's, Amathus Therapeutics, Avid Radiopharmaceuticals, Bial Biotech, Biohaven, Biogen, BioLegend, Bristol-Myers Squibb, Calico Labs, Celgene, Cerevel, Coave, DaCapo Brainscience, 4D Pharma, Denali, Edmond J Safra Foundation, Eli Lilly, GE Healthcare, Genentech, GlaxoSmithKline, Golub Capital, Insitro, Janssen Neuroscience, Lundbeck, Merck, Meso Scale Discovery, Neurocrine Biosciences, Prevail Therapeutics, Roche, Sanofi Genzyme, Servier, Takeda, Teva, UCB, VanquaBio, Verily, Voyager Therapeutics, and Yumanity.