Proposal to Add FDG-PET as an Outcome Measure for Clinical Trials in Patients With Prodromal Lewy Body Dementia

Lewy body dementia (DLB), the most common form of neurodegenerative dementia after Alzheimer disease (AD), is frequently preceded years earlier by idiopathic REM sleep behavior disorder (iRBD), a predictor also of other synucleinopathies, specifically Parkinson disease (PD) and multiple systems atrophy. Research criteria for prodromal DLB consider Lewy body–associated mild cognitive impairment (MCI-LB)1 and recognize… Continue reading Proposal to Add FDG-PET as an Outcome Measure for Clinical Trials in Patients With Prodromal Lewy Body Dementia

Mapping Essential Tremor to a Common Brain Network Using Functional Connectivity Analysis

AI SummaryThe study found that while brain abnormalities in essential tremor (ET) are located in various regions, they are connected to a common functional network. The cerebellum was identified as the central hub of this network, which is similar to the therapeutic network for ET. The study suggests that this network could be useful for… Continue reading Mapping Essential Tremor to a Common Brain Network Using Functional Connectivity Analysis

Advances in Diagnosis and Prognosis of Parkinson Disease: Value of CSF Proteomics

AI SummaryThe biological definition of Parkinson disease is still uncertain. Recent advances in fluid biomarkers, such as α-synuclein amplification assays in CSF, have helped detect α-synucleinopathy, a biological feature of PD. However, these assays are not yet quantitative and may not capture other alterations in PD. They also have poor sensitivity for certain genetic forms… Continue reading Advances in Diagnosis and Prognosis of Parkinson Disease: Value of CSF Proteomics

High-Throughput CSF Proteomics and Machine Learning to Identify Proteomic Signatures for Parkinson Disease Development and Progression

AI SummaryThis study used CSF proteomic data to identify signatures of Parkinson’s disease and assess their clinical usefulness. The proteomic signatures were validated and shown to predict cognitive and motor decline in patients with Parkinson’s disease, regardless of genetic status. The study demonstrates the potential of high-throughput proteomics and machine learning in understanding the development… Continue reading High-Throughput CSF Proteomics and Machine Learning to Identify Proteomic Signatures for Parkinson Disease Development and Progression

Pearls & Oy-sters: ATX-FGF14 Mimicking Autoimmune Pathology

ATX-FGF14 (formerly spinocerebellar ataxia 27, OMIM #193003) is an autosomal dominant condition caused by a pathogenic variant in the fibroblast growth factor 14 (FGF14, OMIM #601515) gene located on chromosome 13. The phenotypic expression can vary in patients with the same genotype, often delaying diagnosis, especially in probands without known affected relatives and/or with limited… Continue reading Pearls & Oy-sters: ATX-FGF14 Mimicking Autoimmune Pathology

A deep look into the progression of Parkinson’s Disease

AI SummaryScientists have used advanced imaging techniques to study how the protein alpha-synuclein disrupts cellular metabolism in Parkinson’s disease.Scientists have used cutting-edge imaging techniques to shed light on the progression of Parkinson’s disease by studying how the main culprit, the protein alpha-synuclein, disrupts cellular metabolism.