Correction to: Relevance of biomarkers across different neurodegenerative diseases

An amendment to this paper has been published and can be accessed via the original article

Correction to: Relevance of biomarkers across different neurodegenerative diseases.

An amendment to this paper has been published and can be accessed via the original article

Genome-wide association study of REM sleep behavior disorder identifies polygenic risk and brain expression effects

Rapid-eye movement (REM) sleep behavior disorder (RBD), enactment of dreams during REM sleep, is an early clinical symptom of alpha-synucleinopathies and defines a more severe subtype. The genetic background of RBD and its underlying mechanisms are not well understood. Here, we perform a genome-wide association study of RBD, identifying five RBD risk loci near SNCA, GBA, TMEM175, INPP5F, and SCARB2. Expression analyses highlight SNCA-AS1 and potentially SCARB2 differential expression in different brain regions in RBD, with SNCA-AS1 further supported by colocalization analyses. Polygenic risk score, pathway analysis, and genetic correlations provide further insights into RBD genetics, highlighting RBD as a unique alpha-synucleinopathy subpopulation that will allow future early intervention

The IPDGC/GP2 Hackathon - an open science event for training in data science, genomics, and collaboration using Parkinson’s disease data

Open science and collaboration are necessary to facilitate the advancement of Parkinson's disease (PD) research. Hackathons are collaborative events that bring together people with different skill sets and backgrounds to generate resources and creative solutions to problems. These events can be used as training and networking opportunities, thus we coordinated a virtual 3-day hackathon event, during which 49 early-career scientists from 12 countries built tools and pipelines with a focus on PD. Resources were created with the goal of helping scientists accelerate their own research by having access to the necessary code and tools. Each team was allocated one of nine different projects, each with a different goal. These included developing post-genome-wide association studies (GWAS) analysis pipelines, downstream analysis of genetic variation pipelines, and various visualization tools. Hackathons are a valuable approach to inspire creative thinking, supplement training in data science, and foster collaborative scientific relationships, which are foundational practices for early-career researchers. The resources generated can be used to accelerate research on the genetics of PD

Neurofilament light levels predict clinical progression and death in multiple system atrophy

Disease-modifying treatments are currently being trialed in multiple system atrophy (MSA). Approaches based solely on clinical measures are challenged by heterogeneity of phenotype and pathogenic complexity. Neurofilament light chain protein has been explored as a reliable biomarker in several neurodegenerative disorders but data in multiple system atrophy have been limited. Therefore, neurofilament light chain is not yet routinely used as an outcome measure in MSA. We aimed to comprehensively investigate the role and dynamics of neurofilament light chain in multiple system atrophy combined with cross-sectional and longitudinal clinical and imaging scales and for subject trial selection. In this cohort study we recruited cross-sectional and longitudinal cases in multicentre European set-up. Plasma and cerebrospinal fluid neurofilament light chain concentrations were measured at baseline from 212 multiple system atrophy cases, annually for a mean period of 2 years in 44 multiple system atrophy patients in conjunction with clinical, neuropsychological and MRI brain assessments. Baseline neurofilament light chain characteristics were compared between groups. Cox regression was used to assess survival; ROC analysis to assess the ability of neurofilament light chain to distinguish between multiple system atrophy patients and healthy controls. Multivariate linear mixed effects models were used to analyse longitudinal neurofilament light chain changes and correlated with clinical and imaging parameters. Polynomial models were used to determine the differential trajectories of neurofilament light chain in multiple system atrophy. We estimated sample sizes for trials aiming to decrease NfL levels. We show that in multiple system atrophy, baseline plasma neurofilament light chain levels were better predictors of clinical progression, survival, and degree of brain atrophy than the NfL rate of change. Comparative analysis of multiple system atrophy progression over the course of disease, using plasma neurofilament light chain and clinical rating scales, indicated that neurofilament light chain levels rise as the motor symptoms progress, followed by deceleration in advanced stages. Sample size prediction suggested that significantly lower trial participant numbers would be needed to demonstrate treatment effects when incorporating plasma neurofilament light chain values into multiple system atrophy clinical trials in comparison to clinical measures alone. In conclusion, neurofilament light chain correlates with clinical disease severity, progression, and prognosis in multiple system atrophy. Combined with clinical and imaging analysis, neurofilament light chain can inform patient stratification and serve as a reliable biomarker of treatment response in future multiple system atrophy trials of putative disease-modifying agents.European Union’s Horizon 2020 research and innovation programm

The IPDGC/GP2 Hackathon - an open science event for training in data science, genomics, and collaboration using Parkinson's disease data

Open science and collaboration are necessary to facilitate the advancement of Parkinson's disease (PD) research. Hackathons are collaborative events that bring together people with different skill sets and backgrounds to generate resources and creative solutions to problems. These events can be used as training and networking opportunities, thus we coordinated a virtual 3-day hackathon event, during which 49 early-career scientists from 12 countries built tools and pipelines with a focus on PD. Resources were created with the goal of helping scientists accelerate their own research by having access to the necessary code and tools. Each team was allocated one of nine different projects, each with a different goal. These included developing post-genome-wide association studies (GWAS) analysis pipelines, downstream analysis of genetic variation pipelines, and various visualization tools. Hackathons are a valuable approach to inspire creative thinking, supplement training in data science, and foster collaborative scientific relationships, which are foundational practices for early-career researchers. The resources generated can be used to accelerate research on the genetics of PD.This project was supported by the Global Parkinson’s Genetics Program (GP2). GP2 is funded by the Aligning Science Against Parkinson’s (ASAP) initiative and implemented by The Michael J. Fox Foundation for Parkinson’s Research (https://gp2.org).Open Access funding provided by the National Institutes of Health (NIH).This research was supported in part by the Intramural Research Program of the NIH, National Institute on Aging (NIA), National Institutes of Health, Department of Health and Human Services; project numbers ZO1 AG000535 and ZO1 AG000949, as well as the National Institute of Neurological Disorders and StrokePeer reviewe

The effect of digital technology development on economic growth

The effect of digital technology development on economic growth / I. Irtyshcheva [ets.] // International Journal of Data and Network Science. – 2021. – Vol. 5, № 1. – P. 25–36.The article simulates the impact of the digital technologies’ development on economic growth, which makes it possible to find ways to improve the quality of various spheres of life and identify areas of the economy, the accelerated digitalization of which will ensure an increase in gross domestic product (GDP). The research used groupings of economic activities that directly influence the development of the digital economy. Using the data of regression models, the coefficients of GDP elasticity from the development of the studied sectors were calculated and used to forecast GDP under the development influence of the studied sectors while maintaining the existing trends. The dynamics of the e-commerce market development in Ukraine, the dynamics of production volumes of products (services) of the main types of economic activities in the field of digital transformation of the economy in Ukraine, the dynamics of financial results of enterprises in the information and telecommunications sector in Ukraine, the dynamics of capital investments in the field of information and communications of Ukraine, the dynamics of foreign investment in the development of the type of economic activity “information and telecommunications” in Ukraine, the dynamics of the development of the main areas of digitalization of the Ukrainian economy in 2010-2018 and the dynamics of GDP in actual prices were revealed. A correlation and regression analysis of the impact of the main indicators of the digital technologies sectors development on Ukraine's GDP is also carried out. The forecast extrapolation trend of production growth volumes of products and services in the information sector of Ukraine was built. A forecast of GDP growth in Ukraine has been constructed, taking into account the processes of digitalization of the economy in accordance with certain trends. The forecast dynamics of changes in GDP under the influence of the IT sector development until 2023 was also illustrated. It was found that Ukraine lags significantly behind most developed countries in terms of the level of industrial production development of information and communication technologies and equipment, Ukraine is completely import-dependent in this area. It has been proved that stimulating the development of information and communication technologies has significant prospects for activating digitalization processes in all spheres of the economy and society and increasing GDP

Comparison of maternal and child health status between Niigata Prefecture, Japan and Khabarovsk Territory, Russia : Neonatal and infant mortality rates and levels of early-pregnancy notification

This report compares the change in infant and neonatal mortality rates and levels of early pregnancy reporting rates in Japan (focusing on Niigata Prefecture) and Russia (focusing on Khabarovsk Territory). This report was endorsed by a memorandum of understanding (MOU) between Niigata University of Health and Welfare and Far Eastern State of Medical University. The indicators of infant and child health status have been improving year on year in Russia. It is considered that the enhancement of the quality and quantity of the perinatal medical care system, especially the introduction of general perinatal centers across Russia, is the main factor in these improvements

Perspectives in fluid biomarkers in neurodegeneration from the 2019 biomarkers in neurodegenerative diseases course - A joint PhD student course at University College London and University of Gothenburg

Until relatively recently, a diagnosis of probable Alzheimer's disease (AD) and other neurodegenerative disorders was principally based on clinical presentation, with post-mortem examination remaining a gold standard for disease confirmation. This is in sharp contrast to other areas of medicine, where fluid biomarkers, such as troponin levels in myocardial infarction, form an integral part of the diagnostic and treatment criteria. There is a pressing need for such quantifiable and easily accessible tools in neurodegenerative diseases. In this paper, based on lectures given at the 2019 Biomarkers in Neurodegenerative Diseases Course, we provide an overview of a range of cerebrospinal fluid (CSF) and blood biomarkers in neurodegenerative disorders, including the 'core' AD biomarkers amyloid β (Aβ) and tau, as well as other disease-specific and general markers of neuroaxonal injury. We then highlight the main challenges in the field, and how those could be overcome with the aid of new methodological advances, such as assay automation, mass spectrometry and ultrasensitive immunoassays. As we hopefully move towards an era of disease-modifying treatments, reliable biomarkers will be essential to increase diagnostic accuracy, allow for earlier diagnosis, better participant selection and disease activity and treatment effect monitoring