Non-motor symptom burden in patients with Parkinson's disease with impulse control disorders and compulsive behaviours : results from the COPPADIS cohort

The study was aimed at analysing the frequency of impulse control disorders (ICDs) and compulsive behaviours (CBs) in patients with Parkinson's disease (PD) and in control subjects (CS) as well as the relationship between ICDs/CBs and motor, nonmotor features and dopaminergic treatment in PD patients. Data came from COPPADIS-2015, an observational, descriptive, nationwide (Spain) study. We used the validated Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease-Rating Scale (QUIP-RS) for ICD/CB screening. The association between demographic data and ICDs/CBs was analyzed in both groups. In PD, this relationship was evaluated using clinical features and treatment-related data. As result, 613 PD patients (mean age 62.47 ± 9.09 years, 59.87% men) and 179 CS (mean age 60.84 ± 8.33 years, 47.48% men) were included. ICDs and CBs were more frequent in PD (ICDs 12.7% vs. 1.6%, p < 0.001; CBs 7.18% vs. 1.67%, p = 0.01). PD patients had more frequent previous ICDs history, premorbid impulsive personality and antidepressant treatment (p < 0.05) compared with CS. In PD, patients with ICDs/CBs presented younger age at disease onset, more frequent history of previous ICDs and premorbid personality (p < 0.05), as well as higher comorbidity with nonmotor symptoms, including depression and poor quality of life. Treatment with dopamine agonists increased the risk of ICDs/CBs, being dose dependent (p < 0.05). As conclusions, ICDs and CBs were more frequent in patients with PD than in CS. More nonmotor symptoms were present in patients with PD who had ICDs/CBs compared with those without. Dopamine agonists have a prominent effect on ICDs/CBs, which could be influenced by dose

Identification of sixteen novel candidate genes for late onset Parkinson’s disease

Background Parkinson’s disease (PD) is a neurodegenerative movement disorder affecting 1–5% of the general population for which neither effective cure nor early diagnostic tools are available that could tackle the pathology in the early phase. Here we report a multi-stage procedure to identify candidate genes likely involved in the etiopathogenesis of PD. Methods The study includes a discovery stage based on the analysis of whole exome data from 26 dominant late onset PD families, a validation analysis performed on 1542 independent PD patients and 706 controls from different cohorts and the assessment of polygenic variants load in the Italian cohort (394 unrelated patients and 203 controls). Results Family-based approach identified 28 disrupting variants in 26 candidate genes for PD including PARK2, PINK1, DJ-1(PARK7), LRRK2, HTRA2, FBXO7, EIF4G1, DNAJC6, DNAJC13, SNCAIP, AIMP2, CHMP1A, GIPC1, HMOX2, HSPA8, IMMT, KIF21B, KIF24, MAN2C1, RHOT2, SLC25A39, SPTBN1, TMEM175, TOMM22, TVP23A and ZSCAN21. Sixteen of them have not been associated to PD before, were expressed in mesencephalon and were involved in pathways potentially deregulated in PD. Mutation analysis in independent cohorts disclosed a significant excess of highly deleterious variants in cases (p = 0.0001), supporting their role in PD. Moreover, we demonstrated that the co-inheritance of multiple rare variants (≥ 2) in the 26 genes may predict PD occurrence in about 20% of patients, both familial and sporadic cases, with high specificity (> 93%; p = 4.4 × 10− 5). Moreover, our data highlight the fact that the genetic landmarks of late onset PD does not systematically differ between sporadic and familial forms, especially in the case of small nuclear families and underline the importance of rare variants in the genetics of sporadic PD. Furthermore, patients carrying multiple rare variants showed higher risk of manifesting dyskinesia induced by levodopa treatment. Conclusions Besides confirming the extreme genetic heterogeneity of PD, these data provide novel insights into the genetic of the disease and may be relevant for its prediction, diagnosis and treatment

Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Background Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. Methods We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. Findings Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). Interpretation These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. Funding The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources)

Effective elastin-like recombinamers coating on poly(vinylidene) fluoride membranes for mesenchymal stem cell culture

Bone’s inherent piezoelectricity is a key factor in regulating bone growth and mesenchymal stem cells (MSCs) fate towards the osteogenic lineage. The piezoelectric polymer poly(vinylidene) fluoride (PVDF) was thus used to manufacture electroactive membranes by means of non-solvent induced phase separation (NIPS), producing porous membranes with approximately 90% of γ-phase for MSCs culture. The combination of the porous surface and PVDF hydrophobicity hinders cell adhesion and requires a coating to improve cell culture conditions. A layer-by-layer (LbL) method was used to deposit elastin-like recombinamers (ELRs) containing RGD sequences applying click cross-linking chemistry. ELRs potential was confirmed by comparing traditional fibronectin adsorption with ELRs LbL on PVDF electroactive membranes. Porcine bone marrow MSCs preferred ELRs-coated surfaces, which enhanced initial cell adhesion and improved proliferation after 7 days. These findings lead to new possibilities for regenerative therapies in the area of bone tissue engineering, offering the advantages of MSC commitment towards the osteogenic lineage by applying electro-mechanical stimulation on electroactive substrates.This work was supported by the Spanish State Research Agency (AEI) through Projects PID2019-106000RB-C21/AEI/10.13039/501100011033 and PID2019-106099RB-C43/AEI/10.13039/501100011033 (including FEDER funds). Maria Guillot-Ferriols received government funding for her doctoral thesis [grant number BES-2017-080398FPI]. The CIBER-BBN initiative is funded by the VI National R&D&I Plan 2008-2011, Iniciativa Ingenio 2010, Consolider Program. CIBER actions are financed by the Instituto de Salud Carlos III with assistance from the European Regional Development Fund. The authors are grateful for the funding from the Spanish Government (MAT2016-78903-R, RTI2018-096320-B-C22), Junta de Castilla y Leon (VA317P18), Interreg V Espana Portugal POCTEP (0624_2IQBIONEURO_6_E) and Centro en Red de Medicina Regenerativa y Terapia Celular de Castilla y Leon. This work was also supported by the Portuguese Foundation for Science and Technology (FCT) in the framework of the Strategic Funding UID/FIS/04650/2020. The authors thank FCT and FEDER funds (COMPETE 2020) under projects PTDC/BTM-MAT/28237/2017, PTDC/EMD-EMD/28159/2017 and PTDC/FIS-MAC/28157/2017. Carlos M. Costa is grateful to the FCT [grant number FRH/BPD/112547/2015]. Financial support was also received from the Basque Government under the ELKARTEK, HAZITEK and PIBA (PIBA-2018-06) programs

Finding genetically-supported drug targets for Parkinson’s disease using Mendelian randomization of the druggable genome

Parkinson’s disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation. We use Mendelian randomization to investigate over 3,000 genes that encode druggable proteins and predict their efficacy as drug targets for Parkinson’s disease. We use expression and protein quantitative trait loci to mimic exposure to medications, and we examine the causal effect on Parkinson’s disease risk (in two large cohorts), age at onset and progression. We propose 23 drug-targeting mechanisms for Parkinson’s disease, including four possible drug repurposing opportunities and two drugs which may increase Parkinson’s disease risk. Of these, we put forward six drug targets with the strongest Mendelian randomization evidence. There is remarkably little overlap between our drug targets to reduce Parkinson’s disease risk versus progression, suggesting different molecular mechanisms. Drugs with genetic support are considerably more likely to succeed in clinical trials, and we provide compelling genetic evidence and an analysis pipeline to prioritise Parkinson’s disease drug development

Applications of the European Parkinson’s Disease Association sponsored Parkinson’s Disease Composite Scale (PDCS)

This study was addressed to determine the presence of Parkinson disease (PD) manifestations, their distribution according to motor subtypes, and the relationships with health-related quality of life (QoL) using the recently validated European Parkinson’s Disease Association sponsored Parkinson’s Disease Composite Scale (PDCS). Frequency of symptoms was determined by the scores of items (present if &gt;0). Using ROC analysis and Youden method, MDS-UPDRS motor subtypes were projected on the PDCS to achieve a comparable classification based on the PDCS scores. The same method was used to estimate severity levels from other measures in the study. The association between the PDCS and QoL (PDQ-39) was analyzed by correlation and multiple linear regression. The sample consisted of 776 PD patients. We found that the frequency of PD manifestations with PDCS and MDS-UPDRS were overlapping, the average difference between scales being 5.5% only. Using the MDS-UPDRS subtyping, 215 patients (27.7%) were assigned as Tremor Dominant (TD), 60 (7.7%) Indeterminate, and 501 (64.6%) Postural Instability and Gait Difficulty (PIGD) in this cohort. With this classification as criterion, the analogous PDCS-based ratio provided these cut-off values: TD subtype, ≥1.06; Indeterminate, &lt;1.06 but &gt;0.65; and PIGD, &lt;0.65. The agreement between the two scales on this classification was substantial (87.6%; kappa = 0.69). PDCS total score cut-offs for PD severity were: 23/24 for mild/moderate and 41/42 for moderate/severe. Moderate to high correlations (r = 0.35–0.80) between PDCS and PDQ-39 were obtained, and the four PDCS domains showed a significant independent influence on QoL. The conclusions are: (1) the PDCS assessed the frequency of PD symptoms analogous to the MDS-UPDRS; (2) motor subtypes and severity levels can be determined with the PDCS; (3) a significant association between PDCS and QoL scores exists. © 2019, The Author(s)

Predictors of clinically significant quality of life impairment in Parkinson's disease

Quality of life (QOL) plays an important role in independent living in Parkinson's disease (PD) patients, being crucial to know what factors impact QoL throughout the course of the disease. Here we identified predictors of QoL impairment in PD patients from a Spanish cohort. PD patients recruited from 35 centers of Spain from the COPPADIS cohort from January 2016, to November 2017, were followed up during 2 years. Health-related QoL (HRQoL) and global QoL (GQoL) were assessed with the 39-item Parkinson's disease Questionnaire (PDQ-39) and the EUROHIS-QOL 8-item index (EUROHIS-QOL8), respectively, at baseline (V0) and at 24 months ± 1 month (V2). Clinically significant QoL impairment was defined as presenting an increase (PDQ-39SI) or decrement (EUROHIS-QOL8) at V2 ≥ 10% of the score at baseline (V0). A comparison with a control group was conducted for GQoL. GQoL did not change significantly in PD patients (N = 507; p = 0.686) or in the control group (N = 119; p = 0.192). The mean PDQ-39SI was significantly increased in PD patients (62.7 ± 8.5 years old; 58.8% males; N = 500) by 21.6% (from 16.7 ± 13 to 20.3 ± 16.4; p < 0.0001) at V2. Ninety-three patients (18.6%) presented a clinically significant HRQoL impairment at V2. To be younger (OR = 0.896; 95% CI 0.829-0.968; p = 0.006), to be a female (OR = 4.181; 95% CI 1.422-12.290; p = 0.009), and to have a greater increase in BDI-II (Beck Depression Inventory-II) (OR = 1.139; 95% CI 1.053-1.231; p = 0.001) and NMSS (Non-Motor Symptoms Scale) (OR = 1.052; 95% CI 1.027-1.113; p < 0.0001) total scores from V0 to V2 were associated with clinically significant HRQoL impairment at the 2-year follow-up (Hosmer-Lemeshow test, p = 0.665; R = 0.655). An increase in ≥5 and ≥10 points of BDI-II and NMSS total score at V2 multiplied the probability of presenting clinically significant HRQoL impairment by 5 (OR = 5.453; 95% CI 1.663-17.876; p = 0.005) and 8 (OR = 8.217; 95% CI, 2.975-22.696; p = 0.002), respectively. In conclusion, age, gender, mood, and non-motor impairment were associated with clinically significant HRQoL impairment after the 2-year follow-up in PD patients

Non-motor symptoms burden, mood, and gait problems are the most significant factors contributing to a poor quality of life in non-demented Parkinson's disease patients: Results from the COPPADIS Study Cohort

[Objective] To identify factors related to a poor health-related and global quality of life (QoL) in a cohort of non-demented Parkinson's disease (PD) patients and compare to a control group.[Methods] The data correspond to the baseline evaluation of the COPPADIS-2015 Study, an observational, 5-year follow-up, multicenter, evaluation study. Three instruments were used to assess QoL: (1) the 39-item Parkinson's disease Questionnaire (PDQ-39), (2) a subjective rating of global QoL (PQ-10), and (3) the EUROHIS-QOL 8-item index (EUROHIS-QOL8). Multiple linear regression methods were used to evaluate the direct impact of different variables on these QoL measures.[Results] QoL was worse in PD patients (n = 692; 62.6 ± 8.9 years old, 60.3% males) than controls (n = 206; 61 ± 8.3 years old, 49.5% males): PDQ-39, 17.1 ± 13.5 vs 4.4 ± 6.3 (p < 0.0001); PQ-10, 7.3 ± 1.6 vs 8.1 ± 1.2 (p < 0.0001); EUROHIS-QOL8, 3.8 ± 0.6 vs 4.2 ± 0.5 (p < 0.0001). A high correlation was observed between PDQ-39 and Non-Motor Symptoms Scale (NMSS) (r = 0.72; p < 0.0001), and PDQ-39 and Beck Depression Inventory-II (BDI-II) (r = 0.65; p < 0.0001). For health-related QoL (PDQ-39), non-motor symptoms burden (NMSS), mood (BDI-II), and gait problems (Freezing Of Gait Questionnaire [FOGQ]) provided the highest contribution to the model (β = 0.32, 0.28, and 0.27, respectively; p < 0.0001); whereas mood and gait problems contributed the most to global QoL (PQ-10, β = -0.46 and −0.21, respectively; EUROHIS-QOL8, β = -0.44 and −0.23, respectively).[Conclusions] QoL is worse in PD patients than in controls. Mood, non-motor symptoms burden, and gait problems seem to be the most relevant factors affecting health-related and global perceived QoL in non-demented PD patients.Peer reviewe