Investigation of Shared Genetic Risk Factors Between Parkinson's Disease and Cancers

in Movement Disorders (2023), n/a(n/a),

Abstract Background Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties ... [more ▼]

Abstract Background Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties. Objective We used results from genome-wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors. Methods We used individual data for participants of European ancestry from the Courage-PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta-Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross-phenotypes polygenic risk score (PRS) analyses. Results We confirmed a previously reported positive genetic correlation of PD with melanoma (Gcorr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (Gcorr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly driven by rs183211 located in an intron of the NSF gene (17q21.31). Conclusions We show evidence in favor of a contribution of pleiotropic genes to the association between PD and specific cancers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA. [less ▲]

GRN Mutations Are Associated with Lewy Body Dementia

in Movement Disorders (2022)

ABSTRACT Background Loss-of-function mutations in GRN are a cause of familial frontotemporal dementia, and common variants within the gene have been associated with an increased risk of developing ... [more ▼]

ABSTRACT Background Loss-of-function mutations in GRN are a cause of familial frontotemporal dementia, and common variants within the gene have been associated with an increased risk of developing Alzheimer's disease and Parkinson's disease. Although TDP-43-positive inclusions are characteristic of GRN-related neurodegeneration, Lewy body copathology has also been observed in many GRN mutation carriers. Objective The objective of this study was to assess a Lewy body dementia (LBD) case–control cohort for pathogenic variants in GRN and to test whether there is an enrichment of damaging mutations among patients with LBD. Methods We analyzed whole-genome sequencing data generated for 2591 European-ancestry LBD cases and 4032 neurologically healthy control subjects to identify disease-causing mutations in GRN. Results We identified six heterozygous exonic GRN mutations in seven study participants (cases: n = 6; control subjects: n = 1). Each variant was predicted to be pathogenic or likely pathogenic. We found significant enrichment of GRN loss-of-function mutations in patients with LBD compared with control subjects (Optimized Sequence Kernel Association Test P = 0.0162). Immunohistochemistry in three definite LBD cases demonstrated Lewy body pathology and TDP-43-positive neuronal inclusions. Conclusions Our findings suggest that deleterious GRN mutations are a rare cause of familial LBD. © 2022 International Parkinson Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA. [less ▲]

Dairy Intake and Parkinson's Disease: A Mendelian Randomization Study

in Movement Disorders (2022)

Abstract Background Previous prospective studies highlighted dairy intake as a risk factor for Parkinson's disease (PD), particularly in men. It is unclear whether this association is causal or explained ... [more ▼]

Abstract Background Previous prospective studies highlighted dairy intake as a risk factor for Parkinson's disease (PD), particularly in men. It is unclear whether this association is causal or explained by reverse causation or confounding. Objective The aim is to examine the association between genetically predicted dairy intake and PD using two-sample Mendelian randomization (MR). Methods We genotyped a well-established instrumental variable for dairy intake located in the lactase gene (rs4988235) within the Courage-PD consortium (23 studies; 9823 patients and 8376 controls of European ancestry). Results Based on a dominant model, there was an association between genetic predisposition toward higher dairy intake and PD (odds ratio [OR] per one serving per day = 1.70, 95 confidence interval = 1.12–2.60, P = 0.013) that was restricted to men (OR = 2.50 [1.37–4.56], P = 0.003; P-difference with women = 0.029). Conclusions Using MR, our findings provide further support for a causal relationship between dairy intake and higher PD risk, not biased by confounding or reverse causation. Further studies are needed to elucidate the underlying mechanisms. © 2022 International Parkinson and Movement Disorder Society [less ▲]

GP2: The Global Parkinson's Genetics Program

in Movement Disorders (2021), 36(4), 842-851

To facilitate the rapid expansion of our understanding of the genetic architecture of PD, both in terms of the depth and global context of this knowledge, we have created the Global Parkinson's Genetics ... [more ▼]

To facilitate the rapid expansion of our understanding of the genetic architecture of PD, both in terms of the depth and global context of this knowledge, we have created the Global Parkinson's Genetics Program (GP2; www.gp2.org). GP2 is the first supported resource project of the Aligning Science Across Parkinson's (ASAP) initiative, an audacious effort supporting PD research.9 GP2 is geared toward creating a worldwide collaborative effort that will first dramatically accelerate the identification of genetic contributors to disease and second establish a network of researchers who can best leverage this understanding to research, diagnose, and treat PD worldwide. Here we describe our mission, the path we have proposed to achieve this, and the core principles of data democratization, transparency, and diversity. [less ▲]

Parkinson’s disease phenotypes in patient neuronal cultures and brain organoids improved by 2-Hydroxypropyl-b-Cyclodextrin treatment

in Movement Disorders (2021)

Age at Onset of LRRK2 p.Gly2019Ser Is Related to Environmental and Lifestyle Factors

in Movement Disorders (2020), 35(10), 1854-1858

GBA variants in Parkinson’s disease: clinical, metabolomic and multimodal neuroimaging phenotypes

in Movement Disorders (2020), 35(12), 2201-2210

Background: Alterations in the GBA gene (NM_000157.3) are the most important genetic risk factor for Parkinson’s disease. Biallelic GBA mutations cause the lysosomal storage disorder Gaucher´s disease ... [more ▼]

Background: Alterations in the GBA gene (NM_000157.3) are the most important genetic risk factor for Parkinson’s disease. Biallelic GBA mutations cause the lysosomal storage disorder Gaucher´s disease. The GBA variants p.E365K and p.T408M are associated with Parkinson’s but not with Gaucher´s disease. The pathophysiological role of these variants needs to be further explored. Objective: This study analyzed the clinical, neuropsychological, metabolic and neuroimaging phenotypes of Parkinson’s disease patients carrying the GBA variants p.E365K and p.T408M. Methods: GBA was sequenced in 56 mid-stage Parkinson’s disease patients. Carriers of GBA variants were compared to non-carriers regarding clinical history and symptoms, neuropsychological features, metabolomics and multimodal neuroimaging. Blood plasma gas chromatography coupled to mass spectrometry, [18F]FDopa PET, [18F]FDG PET, and resting-state fMRI were performed. Results: Sequence analysis detected 13 heterozygous GBA variant carriers (seven with p.E365K, six with p.T408M). One patient carried a GBA mutation (p.N409S) and was excluded. Clinical history and symptoms were not significantly different between groups. Global cognitive performance was lower in variant carriers. Metabolomic group differences were suggestive of more severe Parkinson’s disease-related alterations in carriers versus non-carriers. [18F]FDopa and [18F]FDG PET showed signs of a more advanced disease; [18F]FDG PET and fMRI showed similarities with Lewy body dementia and Parkinson’s disease dementia in carriers. Conclusions: This is the first study to comprehensively assess (neuro-)biological phenotypes of GBA variants in Parkinson’s disease. Metabolomics and neuroimaging detected more significant group differences than clinical and behavioral evaluation. These alterations could be promising to monitor effects of disease-modifying treatments targeting glucocerebrosidase metabolism. [less ▲]

Genotype-phenotype relations for the Parkinson’s disease genes SNCA, LRRK2, VPS35: MDSGene Review.

in Movement Disorders (2018), 33(12), 1857-1870

This comprehensive MDSGene review is devoted to the three autosomal-dominant PD forms: PARK-SNCA, PARK-LRRK2, and PARK-VPS35. It follows MDSGene's standardized data extraction protocol, screened a total ... [more ▼]

This comprehensive MDSGene review is devoted to the three autosomal-dominant PD forms: PARK-SNCA, PARK-LRRK2, and PARK-VPS35. It follows MDSGene's standardized data extraction protocol, screened a total of 2,972 citations, and is based on fully curated phenotypic and genotypic data on 937 patients with dominantly inherited PD attributed to 44 different mutations in SNCA, LRRK2, or VPS35. All of these data are also available in an easily searchable online database (www.mdsgene.org), which additionally provides descriptive summary statistics on phenotypic and genetic data. Despite the high degree of missingness of phenotypic features and unsystematic reporting of genotype data in the original literature, the present review recapitulates many of the previously described findings including later onset of disease (median age at onset: ∼49 years) compared to recessive forms of PD of an overall excellent treatment response. Our systematic review validates previous reports showing that SNCA mutation carriers have a younger age at onset compared to LRRK2 and VPS35 (P < 0.001). SNCA mutation carriers often have additional psychiatric symptoms, and although not exclusive to only LRRK2 or VPS35 mutation carriers, LRRK2 mutation carriers have a typical form of PD, and, lastly, VPS35 mutation carriers have good response to l-dopa. [less ▲]

The Levodopa Response Trial and the Parkinson Disease Digital Biomarker Challenge: Monitoring symptoms of Parkinson’s disease in the lab and home using wearable sensors

in Movement Disorders (2018, October 03), 33(S2), 525

Objective: To leverage a community of researchers and shared wearable data to develop algorithms to estimate the severity of PD specific symptoms. Background: People with Parkinson’s disease (PwPD) often ... [more ▼]

Objective: To leverage a community of researchers and shared wearable data to develop algorithms to estimate the severity of PD specific symptoms. Background: People with Parkinson’s disease (PwPD) often experience fluctuations in motor symptom severity. Wearable sensors have the potential to help clinicians monitor symptoms over time, outside the clinic. However, to gather accurate and clinically-relevant measures, there is a need to develop robust algorithms based on clinically- labelled data. Methods: The Levodopa Response Trial captured three-axis acceleration from two wrist-worn sensors and a smartphone located at the waist from 29 PwPD continuously over 4 days. On day 1, in an in-clinic visit, participants performed clinical assessments and motor tasks on their regular medication regimen. During these visits, a clinician also provided symptom severity scores for tremor, bradykinesia, and dyskinesia. On days 2 & 3, sensor data was collected while participants were at home. On day 4, participants returned to the clinic for the same assessments as day 1, but arrived without having taken their medication for at least 10 hours. Leveraging this dataset, Sage Bionetworks, the Michael J Fox Foundation and the Robert Wood Johnson Foundation launched the PD Digital Biomarker DREAM Challenge which made a subset of the data available to researchers to develop robust and accurate algorithms for the estimation of specific symptoms’ severity. Results: Teams participating in the challenge used several technical approaches, from signal processing to deep learning. 35 submissions were received for the estimation of action tremor severity. Teams achieved an area under the precision-recall curve (AUPR) of 0.444 to 0.75. As for dyskinesia during movement, 37 submissions were received and the teams achieved an AUPR of 0.175 to 0.477. Finally, 39 submissions were received for the estimation of bradykinesia and the teams achieved an AUPR of 0.413 to 0.95. Null expectations for the testing datasets were 0.432, 0.195, and 0.266, respectively. Conclusions: Making datasets available to the community leverages the creativity of different groups to develop robust and accurate algorithms for the estimation of PD symptom severity. This will lead to better quality and interpretability of data collected in unsupervised settings within the community. [less ▲]

Distinct metabolomic signature in cerebrospinal fluid in early parkinson's disease: Early Parkinson'S CSF Metabolic Signature

in Movement Disorders (2017)

Objective: The purpose of this study was to profile cerebrospinal fluid (CSF) from early-stage PD patients for disease-related metabolic changes and to determine a robust biomarker signature for early ... [more ▼]

Objective: The purpose of this study was to profile cerebrospinal fluid (CSF) from early-stage PD patients for disease-related metabolic changes and to determine a robust biomarker signature for early-stage PD diagnosis. Methods: By applying a non-targeted and mass spectrometry-driven approach, we investigated the CSF metabolome of 44 early-stage sporadic PD patients yet without treatment (DeNoPa cohort). We compared all detected metabolite levels with those measured in CSF of 43 age- and gender-matched healthy controls. After this analysis, we validated the results in an independent PD study cohort (T€ubingen cohort). Results: We identified that dehydroascorbic acid levels were significantly lower and fructose, mannose, and threonic acid levels were significantly higher (P <.05) in PD patients when compared with healthy controls. These changes reflect pathological oxidative stress responses, as well as protein glycation/glycosylation reactions in PD. Using a machine learning approach based on logistic regression, we successfully predicted the origin (PD patients vs healthy controls) in a second (n518) as well as in a third and completely independent validation set (n536). The biomarker signature is composed of the three markers—mannose, threonic acid, and fructose—and allows for sample classification with a sensitivity of 0.790 and a specificity of 0.800. Conclusion: We identified PD-specific metabolic changes in CSF that were associated with antioxidative stress response, glycation, and inflammation. Our results disentangle the complexity of the CSF metabolome to unravel metabolome changes related to earlystage PD. The detected biomarkers help understanding PD pathogenesis and can be applied as biomarkers to increase clinical diagnosis accuracy and patient care in early-stage PD. [less ▲]