Seppi, Klaus

ABSTRACT Background The second consensus criteria for the diagnosis of multiple system atrophy (MSA) are widely recognized as the reference standard for clinical research, but lack sensitivity to diagnose the disease at early stages. Objective To develop novel Movement Disorder Society (MDS) criteria for MSA diagnosis using an evidence‐based and consensus‐based methodology. Methods We identified shortcomings of the second consensus criteria for MSA diagnosis and conducted a systematic literature review to answer predefined questions on clinical presentation and diagnostic tools relevant for MSA diagnosis. The criteria were developed and later optimized using two Delphi rounds within the MSA Criteria Revision Task Force, a survey for MDS membership, and a virtual Consensus Conference. Results The criteria for neuropathologically established MSA remain unchanged. For a clinical MSA diagnosis a new category of clinically established MSA is introduced, aiming for maximum specificity with acceptable sensitivity. A category of clinically probable MSA is defined to enhance sensitivity while maintaining specificity. A research category of possible prodromal MSA is designed to capture patients in the earliest stages when symptoms and signs are present, but do not meet the threshold for clinically established or clinically probable MSA. Brain magnetic resonance imaging markers suggestive of MSA are required for the diagnosis of clinically established MSA. The number of research biomarkers that support all clinical diagnostic categories will likely grow. Conclusions This set of MDS MSA diagnostic criteria aims at improving the diagnostic accuracy, particularly in early disease stages. It requires validation in a prospective clinical and a clinicopathological study. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 369 nominally genome-wide significant loci ( P < 5 × 10 −8 ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 −10 ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r G = −0.32, SE = 0.05, P = 6.5 × 10 −12 ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure. ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS

ABSTRACTBackground: In 2015, the International Parkinson and Movement Disorder Society published clinical diagnostic criteria for Parkinson's disease (PD). Although recent validation studies suggest high accuracy, one unmet need is for highly specific criteria for clinical trials in early/de novo PD.Objectives: The objective of this study was to generate and test a PD diagnostic criteria termed “clinically established early PD.”Methods: We modified the Movement Disorder Society criteria to increase specificity for early PD by removing all disease duration components and changing red flags to absolute exclusions. We then estimated the sensitivity/specificity of clinically established early PD criteria in patients with disease duration <5 years, selected from a 626‐patient validation study.Results: After documentation of parkinsonism, 18 individual exclusion criteria are assessed that preclude the diagnosis of “clinically established early PD.” Among 212 PD and 152 non‐PD patients, the estimated specificity was 95.4%, with 69.8% sensitivity.Conclusions: We describe high‐specificity criteria for de novo PD, which are freely available for use in clinical trials. © 2018 International Parkinson and Movement Disorder Society

ABSTRACT Background : PSP is a neuropathologically defined disease entity. Clinical diagnostic criteria, published in 1996 by the National Institute of Neurological Disorders and Stroke/Society for PSP, have excellent specificity, but their sensitivity is limited for variant PSP syndromes with presentations other than Richardson's syndrome. Objective : We aimed to provide an evidence‐ and consensus‐based revision of the clinical diagnostic criteria for PSP. Methods : We searched the PubMed, Cochrane, Medline, and PSYCInfo databases for articles published in English since 1996, using postmortem diagnosis or highly specific clinical criteria as the diagnostic standard. Second, we generated retrospective standardized clinical data from patients with autopsy‐confirmed PSP and control diseases. On this basis, diagnostic criteria were drafted, optimized in two modified Delphi evaluations, submitted to structured discussions with consensus procedures during a 2‐day meeting, and refined in three further Delphi rounds. Results : Defined clinical, imaging, laboratory, and genetic findings serve as mandatory basic features, mandatory exclusion criteria, or context‐dependent exclusion criteria. We identified four functional domains (ocular motor dysfunction, postural instability, akinesia, and cognitive dysfunction) as clinical predictors of PSP. Within each of these domains, we propose three clinical features that contribute different levels of diagnostic certainty. Specific combinations of these features define the diagnostic criteria, stratified by three degrees of diagnostic certainty (probable PSP, possible PSP, and suggestive of PSP). Clinical clues and imaging findings represent supportive features. Conclusions : Here, we present new criteria aimed to optimize early, sensitive, and specific clinical diagnosis of PSP on the basis of currently available evidence. © 2017 International Parkinson and Movement Disorder Society