RESUMO
Pathogenic variants in the UBQLN2 gene cause X-linked dominant amyotrophic lateral sclerosis and/or frontotemporal dementia characterised by ubiquilin 2 aggregates in neurons of the motor cortex, hippocampus, and spinal cord. However, ubiquilin 2 neuropathology is also seen in sporadic and familial amyotrophic lateral sclerosis and/or frontotemporal dementia cases not caused by UBQLN2 pathogenic variants, particularly C9orf72-linked cases. This makes the mechanistic role of mutant ubiquilin 2 protein and the value of ubiquilin 2 pathology for predicting genotype unclear. Here we examine a cohort of 44 genotypically diverse amyotrophic lateral sclerosis cases with or without frontotemporal dementia, including eight cases with UBQLN2 variants (resulting in p.S222G, p.P497H, p.P506S, p.T487I (two cases), and p.P497L (three cases)). Using multiplexed (5-label) fluorescent immunohistochemistry, we mapped the co-localisation of ubiquilin 2 with phosphorylated TDP-43, dipeptide repeat aggregates, and p62, in the hippocampus of controls (n = 6), or amyotrophic lateral sclerosis with or without frontotemporal dementia in sporadic (n = 20), unknown familial (n = 3), SOD1-linked (n = 1), FUS-linked (n = 1), C9orf72-linked (n = 5), and UBQLN2-linked (n = 8) cases. We differentiate between i) ubiquilin 2 aggregation together with phosphorylated TDP-43 or dipeptide repeat proteins, and ii) ubiquilin 2 self-aggregation promoted by UBQLN2 pathogenic variants that cause amyotrophic lateral sclerosis/and frontotemporal dementia. Overall, we describe a hippocampal protein aggregation signature that fully distinguishes mutant from wildtype ubiquilin 2 in amyotrophic lateral sclerosis with or without frontotemporal dementia, whereby mutant ubiquilin 2 is more prone than wildtype to aggregate independently of driving factors. This neuropathological signature can be used to assess the pathogenicity of UBQLN2 gene variants and to understand the mechanisms of UBQLN2-linked disease.
RESUMO
BACKGROUND: Atlas-based voxel features have the potential to aid motor outcome prognostication after stroke, but are seldom used in clinically feasible prediction models. This could be because neuroimaging feature development is a non-standardized, complex, multistep process. This is a barrier to entry for researchers and poses issues for reproducibility and validation in a field of research where sample sizes are typically small. OBJECTIVES: The primary aim of this review is to describe the methodologies currently used in motor outcome prediction studies using atlas-based voxel neuroimaging features. Another aim is to identify neuroanatomical regions commonly used for motor outcome prediction. METHODS: A Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol was constructed and OVID Medline and Scopus databases were searched for relevant studies. The studies were then screened and details about imaging modality, image acquisition, image normalization, lesion segmentation, region of interest determination, and imaging measures were extracted. RESULTS: Seventeen studies were included and examined. Common limitations were a lack of detailed reporting on image acquisition and the specific brain templates used for normalization and a lack of clear reasoning behind the atlas or imaging measure selection. A wide variety of sensorimotor regions relate to motor outcomes and there is no consensus use of one single sensorimotor atlas for motor outcome prediction. CONCLUSION: There is an ongoing need to validate imaging predictors and further improve methodological techniques and reporting standards in neuroimaging feature development for motor outcome prediction post-stroke.