LRRK2 G2019S variant is associated with transcriptional changes in Parkinson's disease human myeloid cells under proinflammatory environment.

The G2019S mutation in the leucine-rich repeat kinase 2 (LRRK2) gene is a major risk factor for the development of Parkinson's disease (PD). LRRK2, although ubiquitously expressed, is highly abundant in cells of the innate immune system. Given the importance of central and peripheral immune cells in the development of PD, we sought to investigate the consequences of the G2019S mutation on microglial and monocyte transcriptome and function. We have generated large-scale transcriptomic profiles of isogenic human induced microglial cells (iMGLs) and patient derived monocytes carrying the G2019S mutation under baseline culture conditions and following exposure to the proinflammatory factors IFNγ and LPS. We demonstrate that the G2019S mutation exerts a profound impact on the transcriptomic profile of these myeloid cells, and describe corresponding functional differences in iMGLs. The G2019S mutation led to an upregulation in lipid metabolism and phagolysosomal pathway genes in untreated and LPS/IFNγ stimulated iMGLs, which was accompanied by an increased phagocytic capacity of myelin debris. We also identified dysregulation of cell cycle genes, with a downregulation of the E2F4 regulon. Transcriptomic characterization of human-derived monocytes carrying the G2019S mutation confirmed alteration in lipid metabolism associated genes. Altogether, these findings reveal the influence of G2019S on the dysregulation of the myeloid cell transcriptome under proinflammatory conditions.

Mutations in the gene PRRT2 cause paroxysmal kinesigenic dyskinesia with infantile convulsions.

Paroxysmal kinesigenic dyskinesia with infantile convulsions (PKD/IC) is an episodic movement disorder with autosomal-dominant inheritance and high penetrance, but the causative genetic mutation is unknown. We have now identified four truncating mutations involving the gene PRRT2 in the vast majority (24/25) of well-characterized families with PKD/IC. PRRT2 truncating mutations were also detected in 28 of 78 additional families. PRRT2 encodes a proline-rich transmembrane protein of unknown function that has been reported to interact with the t-SNARE, SNAP25. PRRT2 localizes to axons but not to dendritic processes in primary neuronal culture, and mutants associated with PKD/IC lead to dramatically reduced PRRT2 levels, leading ultimately to neuronal hyperexcitability that manifests in vivo as PKD/IC.

FDG PET in the differential diagnosis of parkinsonian disorders.

The differential diagnosis of parkinsonian disorders can be challenging, especially early in the disease course. PET imaging with [(18)F]-fluorodeoxyglucose (FDG) has been used to identify characteristic patterns of regional glucose metabolism in patient cohorts with idiopathic Parkinson's disease (PD), as well as variant forms of parkinsonism such as multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBGD). In this study, we assessed the utility of FDG PET in the differential diagnosis of individual patients with clinical parkinsonism. 135 parkinsonian patients were referred for FDG PET to determine whether their diagnosis could be made accurately based upon their scans. Imaging-based diagnosis was obtained by visual assessment of the individual scans and also by computer-assisted interpretation. The results were compared with 2-year follow-up clinical assessments made by independent movement disorders specialists who were blinded to the original PET findings. We found that blinded computer assessment agreed with clinical diagnosis in 92.4% of all subjects (97.7% early PD, 91.6% late PD, 96% MSA, 85% PSP, 90.1% CBGD, 86.5% healthy control subjects). Concordance of visual inspection with clinical diagnosis was achieved in 85.4% of the patients scanned (88.4% early PD, 97.2% late PD, 76% MSA, 60% PSP, 90.9% CBGD, 90.9% healthy control subjects). This study demonstrates that FDG PET performed at the time of initial referral for parkinsonism accurately predicted the clinical diagnosis of individual patients made at subsequent follow-up. Computer-assisted methodologies may be particularly helpful in situations where experienced readers of FDG PET images are not readily available.