Patterns of TDP-43 Deposition in Brains with LRRK2 G2019S Mutations.

OBJECTIVE: To assess for TDP-43 deposits in brains with and without a LRRK2 G2019S mutation. BACKGROUND: LRRK2 G2019S mutations have been associated with parkinsonism and a wide range of pathological findings. There are no systematic studies examining the frequency and extent of TDP-43 deposits in neuropathological samples from LRRK2 G2019S carriers. METHODS: Twelve brains with LRRK2 G2019S mutations were available for study from the New York Brain Bank at Columbia University; 11 of them had samples available for TDP-43 immunostaining. Clinical, demographic, and pathological data are reported for 11 brains with a LRRK2 G2019S mutation and compared to 11 brains without GBA1 or LRRK2 G2019S mutations with a pathologic diagnosis of Parkinson's disease (PD) or diffuse Lewy body disease. They were frequency matched by age, gender, parkinsonism age of onset, and disease duration. RESULTS: TDP-43 aggregates were present in 73% (n = 8) of brains with a LRRK2 mutation and 18% (n = 2) of brains without a LRRK2 mutation (P = 0.03). In one brain with a LRRK2 mutation, TDP-43 proteinopathy was the primary neuropathological change. CONCLUSIONS: Extranuclear TDP-43 aggregates are observed with greater frequency in LRRK2 G2019S autopsies compared to PD cases without a LRRK2 G2019S mutation. The association between LRRK2 and TDP-43 should be further explored. © 2023 International Parkinson and Movement Disorder Society.

LRRK2 kinase activity regulates GCase level and enzymatic activity differently depending on cell type in Parkinson's disease.

Leucine-rich repeat kinase 2 (LRRK2) is a kinase involved in different cellular functions, including autophagy, endolysosomal pathways, and immune function. Mutations in LRRK2 cause autosomal-dominant forms of Parkinson's disease (PD). Heterozygous mutations in GBA1, the gene encoding the lysosomal enzyme glucocerebrosidase (GCase), are the most common genetic risk factors for PD. Moreover, GCase function is altered in idiopathic PD and in other genetic forms of the disease. Recent work suggests that LRRK2 kinase activity can regulate GCase function. However, both a positive and a negative correlation have been described. To gain insights into the impact of LRRK2 on GCase, we performed a comprehensive analysis of GCase levels and activity in complementary LRRK2 models, including (i) LRRK2 G2019S knock in (GSKI) mice, (ii) peripheral blood mononuclear cell (PBMCs), plasma, and fibroblasts from PD patients carrying LRRK2 G2019S mutation, (iii) patient iPSCs-derived neurons; (iv) endogenous and overexpressed cell models. In some of these models we found a positive correlation between the activities of LRRK2 and GCase, which was further confirmed in cell lines with genetic and pharmacological manipulation of LRRK2 kinase activity. GCase protein level is reduced in GSKI brain tissues and in G2019S iPSCs-derived neurons, but increased in fibroblasts and PBMCs from patients, suggesting cell-type-specific effects. Overall, our study indicates that LRRK2 kinase activity affects both the levels and the catalytic activity of GCase in a cell-type-specific manner, with important implications in the context of therapeutic application of LRRK2 inhibitors in GBA1-linked and idiopathic PD.

Lipid level alteration in human and cellular models of alpha synuclein mutations.

Lipid profiles in biological fluids from patients with Parkinson's disease (PD) are increasingly investigated in search of biomarkers. However, the lipid profiles in genetic PD remain to be determined, a gap of knowledge of particular interest in PD associated with mutant α-synuclein (SNCA), given the known relationship between this protein and lipids. The objective of this research is to identify serum lipid composition from SNCA A53T mutation carriers and to compare these alterations to those found in cells and transgenic mice carrying the same genetic mutation. We conducted an unbiased lipidomic analysis of 530 lipid species from 34 lipid classes in serum of 30 participants with SNCA mutation with and without PD and 30 healthy controls. The primary analysis was done between 22 PD patients with SNCA+ (SNCA+/PD+) and 30 controls using machine-learning algorithms and traditional statistics. We also analyzed the lipid composition of human clonal-cell lines and tissue from transgenic mice overexpressing the same SNCA mutation. We identified specific lipid classes that best discriminate between SNCA+/PD+ patients and healthy controls and found certain lipid species, mainly from the glycerophosphatidylcholine and triradylglycerol classes, that are most contributory to this discrimination. Most of these alterations were also present in human derived cells and transgenic mice carrying the same mutation. Our combination of lipidomic and machine learning analyses revealed alterations in glycerophosphatidylcholine and triradylglycerol in sera from PD patients as well as cells and tissues expressing mutant α-Syn. Further investigations are needed to establish the pathogenic significance of these α-Syn-associated lipid changes.

Attitudes Toward Telehealth Services Among People Living With Parkinson's Disease: A Survey Study.

BACKGROUND: Telehealth has been widely adopted in providing Parkinson's disease care during the coronavirus disease 2019 pandemic. OBJECTIVE: The aim of this study was to survey people living with Parkinson's disease (PwPD) about their attitudes toward and utilization of telehealth services. METHODS: A survey was administered to PwPD via Parkinson's Foundation and Columbia University mailing lists. RESULTS: Of 1,163 responses, 944 complete responses were analyzed. Telehealth awareness was 90.2% (850/942), and utilization was 82.8% (780/942). More than 40% of PwPD were equally or more satisfied with telehealth compared with in-person visits in all types of services used. The highest satisfaction was observed in speech-language pathology appointments (78.8%, 52/66) followed by mental health services (69.2%, 95/137). CONCLUSIONS: In selected circumstances and indications, such as speech-language pathology and mental health services, telehealth may be a useful tool in the care of PwPD beyond the coronavirus disease 2019 pandemic. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson Movement Disorder Society.

Plasma Metabolite Signature Classifies Male LRRK2 Parkinson's Disease Patients.

Parkinson's disease (PD) is a progressive neurodegenerative disease, causing loss of motor and nonmotor function. Diagnosis is based on clinical symptoms that do not develop until late in the disease progression, at which point the majority of the patients' dopaminergic neurons are already destroyed. While many PD cases are idiopathic, hereditable genetic risks have been identified, including mutations in the gene for LRRK2, a multidomain kinase with roles in autophagy, mitochondrial function, transcription, molecular structural integrity, the endo-lysosomal system, and the immune response. A definitive PD diagnosis can only be made post-mortem, and no noninvasive or blood-based disease biomarkers are currently available. Alterations in metabolites have been identified in PD patients, suggesting that metabolomics may hold promise for PD diagnostic tools. In this study, we sought to identify metabolic markers of PD in plasma. Using a 1H-13C heteronuclear single quantum coherence spectroscopy (HSQC) NMR spectroscopy metabolomics platform coupled with machine learning (ML), we measured plasma metabolites from approximately age/sex-matched PD patients with G2019S LRRK2 mutations and non-PD controls. Based on the differential level of known and unknown metabolites, we were able to build a ML model and develop a Biomarker of Response (BoR) score, which classified male LRRK2 PD patients with 79.7% accuracy, 81.3% sensitivity, and 78.6% specificity. The high accuracy of the BoR score suggests that the metabolomics/ML workflow described here could be further utilized in the development of a confirmatory diagnostic for PD in larger patient cohorts. A diagnostic assay for PD will aid clinicians and their patients to quickly move toward a definitive diagnosis, and ultimately empower future clinical trials and treatment options.

Plasma Glucosylsphingosine in GBA1 Mutation Carriers with and without Parkinson's Disease.

BACKGROUND: Biallelic mutations in the GBA1 gene encoding glucocerebrosidase cause Gaucher's disease, whereas heterozygous carriers are at risk for Parkinson's disease (PD). Glucosylsphingosine is a clinically meaningful biomarker of Gaucher's disease but could not be assayed previously in heterozygous GBA1 carriers. OBJECTIVE: The aim of this study was to assess plasma glucosylsphingosine levels in GBA1 N370S carriers with and without PD. METHODS: Glucosylsphingosine, glucosylceramide, and four other lipids were quantified in plasma from N370S heterozygotes with (n = 20) or without (n = 20) PD, healthy controls (n = 20), idiopathic PD (n = 20), and four N370S homozygotes (positive controls; Gaucher's/PD) using quantitative ultra-performance liquid chromatography tandem mass spectrometry. RESULTS: Plasma glucosylsphingosine was significantly higher in N370S heterozygotes compared with noncarriers, independent of disease status. As expected, Gaucher's/PD cases showed increases in both glucocerebrosidase substrates, glucosylsphingosine and glucosylceramide. CONCLUSIONS: Plasma glucosylsphingosine accumulation in N370S heterozygotes shown in this study opens up its future assessment as a clinically meaningful biomarker of GBA1-PD. © 2021 International Parkinson and Movement Disorder Society.

COVID-19 manifestations in people with Parkinson's disease: a USA cohort.

BACKGROUND: With the explosion of COVID-19 globally, it was unclear if people with Parkinson's disease (PD) were at increased risk for severe manifestations or negative outcomes. OBJECTIVES: To report on people with PD who had suspected or confirmed COVID-19 to understand how COVID-19 manifested in PD patients. METHODS: We surveyed PD patients who reported COVID-19 to their Movement Disorders specialists at Columbia University Irving Medical Center and respondents from an online survey administered by the Parkinson's Foundation that assessed COVID-19 symptoms, general clinical outcomes and changes in motor and non-motor PD symptoms. RESULTS: Forty-six participants with PD and COVID-19 were enrolled. Similar to the general population, the manifestations of COVID-19 among people with PD were heterogeneous ranging from asymptomatic carriers (1/46) to death (6/46). The most commonly reported COVID-19 symptoms were fever/chills, fatigue, cough, weight loss, and muscle pain. Worsening and new onset of motor and non-motor PD symptoms during COVID-19 illness were also reported, including dyskinesia, rigidity, balance disturbances, anxiety, depression, and insomnia. CONCLUSION: We did not find sufficient evidence that PD is an independent risk factor for severe COVID-19 and death. Larger studies with controls are required to understand this further. Longitudinal follow-up of these participants will allow for observation of possible long-term effects of COVID-19 in PD patients.

Subnormal GM1 in PBMCs: Promise for Early Diagnosis of Parkinson's Disease?

The fact that Parkinson's disease (PD) pathologies are well advanced in most PD patients by the time of clinical elucidation attests to the importance of early diagnosis. Our attempt to achieve this has capitalized on our previous finding that GM1 ganglioside is expressed at subnormal levels in virtually all tissues of sporadic PD (sPD) patients including blood cells. GM1 is present in most vertebrate cells, is especially abundant in neurons where it was shown essential for their effective functioning and long term viability. We have utilized peripheral blood mononuclear cells (PBMCs) which, despite their low GM1, we found to be significantly lower in sPD patients compared to age-matched healthy controls. To quantify GM1 (and GD1a) we used high performance thin-layer chromatography combined with cholera toxin B linked to horseradish peroxidase, followed by densitometric quantification. GM1 was also deficient in PBMCs from PD patients with mutations in the glucocerebrosidase gene (PD-GBA), apparently even lower than in sPD. Reasons are given why we believe these results obtained with patients manifesting fully developed PD will apply as well to PD patients in preclinical stages-a topic for future study. We also suggest that these findings point to a potential disease altering therapy for PD once the early diagnosis is established.

Lipidomics Prediction of Parkinson's Disease Severity: A Machine-Learning Analysis.

BACKGROUND: The role of the lipidome as a biomarker for Parkinson's disease (PD) is a relatively new field that currently only focuses on PD diagnosis. OBJECTIVE: To identify a relevant lipidome signature for PD severity markers. METHODS: Disease severity of 149 PD patients was assessed by the Unified Parkinson's Disease Rating Scale (UPDRS) and the Montreal Cognitive Assessment (MoCA). The lipid composition of whole blood samples was analyzed, consisting of 517 lipid species from 37 classes; these included all major classes of glycerophospholipids, sphingolipids, glycerolipids, and sterols. To handle the high number of lipids, the selection of lipid species and classes was consolidated via analysis of interrelations between lipidomics and disease severity prediction using the random forest machine-learning algorithm aided by conventional statistical methods. RESULTS: Specific lipid classes dihydrosphingomyelin (dhSM), plasmalogen phosphatidylethanolamine (PEp), glucosylceramide (GlcCer), dihydro globotriaosylceramide (dhGB3), and to a lesser degree dihydro GM3 ganglioside (dhGM3), as well as species dhSM(20:0), PEp(38:6), PEp(42:7), GlcCer(16:0), GlcCer(24:1), dhGM3(22:0), dhGM3(16:0), and dhGB3(16:0) contribute to PD severity prediction of UPDRS III score. These, together with age, age at onset, and disease duration, also contribute to prediction of UPDRS total score. We demonstrate that certain lipid classes and species interrelate differently with the degree of severity of motor symptoms between men and women, and that predicting intermediate disease stages is more accurate than predicting less or more severe stages. CONCLUSION: Using machine-learning algorithms and methodologies, we identified lipid signatures that enable prediction of motor severity in PD. Future studies should focus on identifying the biological mechanisms linking GlcCer, dhGB3, dhSM, and PEp with PD severity.

Urinary proteome profiling for stratifying patients with familial Parkinson's disease.

The prevalence of Parkinson's disease (PD) is increasing but the development of novel treatment strategies and therapeutics altering the course of the disease would benefit from specific, sensitive, and non-invasive biomarkers to detect PD early. Here, we describe a scalable and sensitive mass spectrometry (MS)-based proteomic workflow for urinary proteome profiling. Our workflow enabled the reproducible quantification of more than 2,000 proteins in more than 200 urine samples using minimal volumes from two independent patient cohorts. The urinary proteome was significantly different between PD patients and healthy controls, as well as between LRRK2 G2019S carriers and non-carriers in both cohorts. Interestingly, our data revealed lysosomal dysregulation in individuals with the LRRK2 G2019S mutation. When combined with machine learning, the urinary proteome data alone were sufficient to classify mutation status and disease manifestation in mutation carriers remarkably well, identifying VGF, ENPEP, and other PD-associated proteins as the most discriminating features. Taken together, our results validate urinary proteomics as a valuable strategy for biomarker discovery and patient stratification in PD.

The impact of COVID-19 and social distancing on people with Parkinson's disease: a survey study.

As the COVID-19 pandemic continues to affect the international community, very little is known about its impact on the health and day-to-day activities of people with Parkinson's disease (PwPD). To better understand the emotional and behavioral consequences of the public health policies implemented to mitigate the spread of SARS-CoV-2 in PwPD, and to explore the factors contributing to accessing alternative health care mechanisms, such as telehealth, we administered an anonymous knowledge, attitude, and practice survey to PwPD and care partners, via the mailing lists of the Parkinson's Foundation and Columbia University Parkinson's Disease Center of Excellence with an average response rate of 19.3%. Sufficient information was provided by 1,342 PwPD to be included in the final analysis. Approximately half of respondents reported a negative change in PD symptoms, with 45-66% reporting mood disturbances. Telehealth use increased from 9.7% prior to the pandemic to 63.5% during the pandemic. Higher income and higher education were associated with telehealth use. Services were more often used for doctor's appointment than physical, occupational, speech, or mental health therapies. Almost half (46%) of PwPD preferred to continue using telehealth always or sometimes after the coronavirus outbreak had ended. Having received support/instruction for telehealth and having a care partner, friend, or family member to help them with the telehealth visit increased the likelihood of continuous use of telehealth after the pandemic ended. Taken together, PD symptoms and management practices were markedly affected by COVID-19. Given the observed demographic limitations of telehealth, expanding its implementation to include additional physical, occupational, psychological, and speech therapies, increasing support for telehealth, as well as reaching underserved (low income) populations is urgently required.

Analysis of Heterozygous PRKN Variants and Copy-Number Variations in Parkinson's Disease.

BACKGROUND: Biallelic PRKN mutation carriers with Parkinson's disease (PD) typically have an earlier disease onset, slow disease progression, and, often, different neuropathology compared to sporadic PD patients. However, the role of heterozygous PRKN variants in the risk of PD is controversial. OBJECTIVES: Our aim was to examine the association between heterozygous PRKN variants, including single-nucleotide variants and copy-number variations (CNVs), and PD. METHODS: We fully sequenced PRKN in 2809 PD patients and 3629 healthy controls, including 1965 late-onset (63.97 ± 7.79 years, 63% men) and 553 early-onset PD patients (43.33 ± 6.59 years, 68% men). PRKN was sequenced using targeted next-generation sequencing with molecular inversion probes. CNVs were identified using a combination of multiplex ligation-dependent probe amplification and ExomeDepth. To examine whether rare heterozygous single-nucleotide variants and CNVs in PRKN are associated with PD risk and onset, we used optimized sequence kernel association tests and regression models. RESULTS: We did not find any associations between all types of PRKN variants and risk of PD. Pathogenic and likely-pathogenic heterozygous single-nucleotide variants and CNVs were less common among PD patients (1.52%) than among controls (1.8%, false discovery rate-corrected P = 0.55). No associations with age at onset and in stratified analyses were found. CONCLUSIONS: Heterozygous single-nucleotide variants and CNVs in PRKN are not associated with PD. Molecular inversion probes allow for rapid and cost-effective detection of all types of PRKN variants, which may be useful for pretrial screening and for clinical and basic science studies targeting specifically PRKN patients. © 2020 International Parkinson and Movement Disorder Society.