Multivariate Analysis of F-18-DMFP PET Data to Assist the Diagnosis of Parkinsonism

An early and differential diagnosis of parkinsonian syndromes still remains a challenge mainly due to the similarity of their symptoms during the onset of the disease. Recently, F-18-Desmethoxyfallypride (DMFP) has been suggested to increase the diagnostic precision as it is an effective radioligand that allows us to analyze post-synaptic dopamine D2/3 receptors. Nevertheless, the analysis of these data is still poorly covered and its use limited. In order to address this challenge, this paper shows a novel model to automatically distinguish idiopathic parkinsonism from non-idiopathic variants using DMFP data. The proposed method is based on a multiple kernel support vector machine and uses the linear version of this classifier to identify some regions of interest: the olfactory bulb, thalamus, and supplementary motor area. We evaluated the proposed model for both, the binary separation of idiopathic and non-idiopathic parkinsonism and the multigroup separation of parkinsonian variants. These systems achieved accuracy rates higher than 70%, outperforming DaTSCAN neuroimages for this purpose. In addition, a system that combined DaTSCAN and DMFP data was assessed

Evaluation of the interaction between LRRK2 and PARK16 loci in determining risk of Parkinson's disease: analysis of a large multicenter study

A recent study MacLeod et al. has shown that an interaction between variants at the LRRK2 and PARK16 loci influences risk of development of Parkinson's disease (PD). Our study examines the proposed interaction between LRRK2 and PARK16 variants in modifying PD risk using a large multicenter series of PD patients (7715) and controls (8261) from sites participating in the Genetic Epidemiology of Parkinson's Disease Consortium. Our data does not support a strong direct interaction between LRRK2 and PARK16 variants; however, given the role of retromer and lysosomal pathways in PD, further studies are warranted

Large-scale assessment of polyglutamine repeat expansions in Parkinson disease

Objectives: We aim to clarify the pathogenic role of intermediate size repeat expansions of SCA2, SCA3, SCA6, and SCA17 as risk factors for idiopathic Parkinson disease (PD). Methods: We invited researchers from the Genetic Epidemiology of Parkinson's Disease Consortium to participate in the study. There were 12,346 cases and 8,164 controls genotyped, for a total of 4 repeats within the SCA2, SCA3, SCA6, and SCA17 genes. Fixed- and random-effects models were used to estimate the summary risk estimates for the genes. We investigated between-study heterogeneity and heterogeneity between different ethnic populations. Results: We did not observe any definite pathogenic repeat expansions for SCA2, SCA3, SCA6, and SCA17 genes in patients with idiopathic PD from Caucasian and Asian populations. Furthermore, overall analysis did not reveal any significant association between intermediate repeats and PD. The effect estimates (odds ratio) ranged from 0.93 to 1.01 in the overall cohort for the SCA2, SCA3, SCA6, and SCA17 loci. Conclusions: Our study did not support a major role for definite pathogenic repeat expansions in SCA2, SCA3, SCA6, and SCA17 genes for idiopathic PD. Thus, results of this large study do not support diagnostic screening of SCA2, SCA3, SCA6, and SCA17 gene repeats in the common idiopathic form of PD. Likewise, this largest multicentered study performed to date excludes the role of intermediate repeats of these genes as a risk factor for PD

Embracing monogenic Parkinson's disease: the MJFF Global Genetic PD Cohort

© 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.Background: As gene-targeted therapies are increasingly being developed for Parkinson's disease (PD), identifying and characterizing carriers of specific genetic pathogenic variants is imperative. Only a small fraction of the estimated number of subjects with monogenic PD worldwide are currently represented in the literature and availability of clinical data and clinical trial-ready cohorts is limited. Objective: The objectives are to (1) establish an international cohort of affected and unaffected individuals with PD-linked variants; (2) provide harmonized and quality-controlled clinical characterization data for each included individual; and (3) further promote collaboration of researchers in the field of monogenic PD. Methods: We conducted a worldwide, systematic online survey to collect individual-level data on individuals with PD-linked variants in SNCA, LRRK2, VPS35, PRKN, PINK1, DJ-1, as well as selected pathogenic and risk variants in GBA and corresponding demographic, clinical, and genetic data. All registered cases underwent thorough quality checks, and pathogenicity scoring of the variants and genotype-phenotype relationships were analyzed. Results: We collected 3888 variant carriers for our analyses, reported by 92 centers (42 countries) worldwide. Of the included individuals, 3185 had a diagnosis of PD (ie, 1306 LRRK2, 115 SNCA, 23 VPS35, 429 PRKN, 75 PINK1, 13 DJ-1, and 1224 GBA) and 703 were unaffected (ie, 328 LRRK2, 32 SNCA, 3 VPS35, 1 PRKN, 1 PINK1, and 338 GBA). In total, we identified 269 different pathogenic variants; 1322 individuals in our cohort (34%) were indicated as not previously published. Conclusions: Within the MJFF Global Genetic PD Study Group, we (1) established the largest international cohort of affected and unaffected individuals carrying PD-linked variants; (2) provide harmonized and quality-controlled clinical and genetic data for each included individual; (3) promote collaboration in the field of genetic PD with a view toward clinical and genetic stratification of patients for gene-targeted clinical trials. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.Michael J. Fox Foundation for Parkinson's Research. Grant Number: ID 15015.02. NIHR Cambridge Biomedical Research Centre. Grant Number: BRC-1215-20014info:eu-repo/semantics/publishedVersio

Support Vector Components Analysis

In this paper we propose a novel method for learning a distance metric in the process of training Support Vector Machines (SVMs) with the radial basis function kernel. A transformation matrix is adapted in such a way that the SVM dual objective of a classification problem is optimized. By using a wide transformation matrix the method can effectively be used as a means of supervised dimensionality reduction. We compare our method with other algorithms on a toy dataset and on PET-scans of patients with various Parkinsonisms, finding that our method either outperforms or performs on par with the other algorithms