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      Liquid Chromatography–Mass Spectrometry Analysis of Frataxin Proteoforms in Whole Blood as Biomarkers of the Genetic Disease Friedreich’s Ataxia

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          Abstract

          Friedreich’s ataxia (FRDA) is caused primarily by expanded GAA repeats in intron 1 of both alleles of the FXN gene, which causes transcriptional silencing and reduced expression of frataxin mRNA and protein. FRDA is characterized by slowly progressive ataxia and cardiomyopathy. Symptoms generally appear during adolescence, and patients slowly progress to wheelchair dependency usually in the late teens or early twenties with death on average in the 4th decade. There are two known mature proteoforms of frataxin. Mitochondrial frataxin (frataxin-M) is a 130-amino acid protein with a molecular weight of 14,268 Da, and there is an alternatively spliced N-terminally acetylated 135-amino acid form (frataxin-E) with a molecular weight of 14,953 Da found in erythrocytes. There is reduced expression of frataxin in the heart and brain, but frataxin is not secreted into the systemic circulation, so it cannot be analyzed in serum or plasma. Blood is a readily accessible biofluid that contains numerous different cell types that express frataxin. We have found that pig blood can serve as an excellent surrogate matrix to validate an assay for frataxin proteoforms because pig frataxin is lost during the immunoprecipitation step used to isolate human frataxin. Frataxin-M is expressed in blood cells that contain mitochondria, whereas extra-mitochondrial frataxin-E is found in erythrocytes. This means that the analysis of frataxin in whole blood provides information on the concentration of both proteoforms without having to isolate the individual cell types. In the current study, we observed that the distributions of frataxin levels for a sample of 25 healthy controls and 50 FRDA patients were completely separated from each other, suggesting 100% specificity and 100% sensitivity for distinguishing healthy controls from FRDA cases, a very unusual finding for a biomarker assay. Additionally, frataxin levels were significantly correlated with the GAA repeat length and age of onset with higher correlations for extra-mitochondrial frataxin-E than those for mitochondrial frataxin-M. These findings auger well for using frataxin levels measured by the validated stable isotope dilution ultrahigh-performance liquid chromatography–multiple reaction monitoring/mass spectrometry assay to monitor therapeutic interventions and the natural history of FRDA. Our study also illustrates the utility of using whole blood for protein disease biomarker discovery and validation.

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          Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.

          Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools. Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project.
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            Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019

            Background Given the projected trends in population ageing and population growth, the number of people with dementia is expected to increase. In addition, strong evidence has emerged supporting the importance of potentially modifiable risk factors for dementia. Characterising the distribution and magnitude of anticipated growth is crucial for public health planning and resource prioritisation. This study aimed to improve on previous forecasts of dementia prevalence by producing country-level estimates and incorporating information on selected risk factors. Methods We forecasted the prevalence of dementia attributable to the three dementia risk factors included in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 (high body-mass index, high fasting plasma glucose, and smoking) from 2019 to 2050, using relative risks and forecasted risk factor prevalence to predict GBD risk-attributable prevalence in 2050 globally and by world region and country. Using linear regression models with education included as an additional predictor, we then forecasted the prevalence of dementia not attributable to GBD risks. To assess the relative contribution of future trends in GBD risk factors, education, population growth, and population ageing, we did a decomposition analysis. Findings We estimated that the number of people with dementia would increase from 57·4 (95% uncertainty interval 50·4–65·1) million cases globally in 2019 to 152·8 (130·8–175·9) million cases in 2050. Despite large increases in the projected number of people living with dementia, age-standardised both-sex prevalence remained stable between 2019 and 2050 (global percentage change of 0·1% [–7·5 to 10·8]). We estimated that there were more women with dementia than men with dementia globally in 2019 (female-to-male ratio of 1·69 [1·64–1·73]), and we expect this pattern to continue to 2050 (female-to-male ratio of 1·67 [1·52–1·85]). There was geographical heterogeneity in the projected increases across countries and regions, with the smallest percentage changes in the number of projected dementia cases in high-income Asia Pacific (53% [41–67]) and western Europe (74% [58–90]), and the largest in north Africa and the Middle East (367% [329–403]) and eastern sub-Saharan Africa (357% [323–395]). Projected increases in cases could largely be attributed to population growth and population ageing, although their relative importance varied by world region, with population growth contributing most to the increases in sub-Saharan Africa and population ageing contributing most to the increases in east Asia. Interpretation Growth in the number of individuals living with dementia underscores the need for public health planning efforts and policy to address the needs of this group. Country-level estimates can be used to inform national planning efforts and decisions. Multifaceted approaches, including scaling up interventions to address modifiable risk factors and investing in research on biological mechanisms, will be key in addressing the expected increases in the number of individuals affected by dementia. Funding Bill & Melinda Gates Foundation and Gates Ventures.
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              Alzheimer disease in the United States (2010-2050) estimated using the 2010 census.

              To provide updated estimates of Alzheimer disease (AD) dementia prevalence in the United States from 2010 through 2050. Probabilities of AD dementia incidence were calculated from a longitudinal, population-based study including substantial numbers of both black and white participants. Incidence probabilities for single year of age, race, and level of education were calculated using weighted logistic regression and AD dementia diagnosis from 2,577 detailed clinical evaluations of 1,913 people obtained from stratified random samples of previously disease-free individuals in a population of 10,800. These were combined with US mortality, education, and new US Census Bureau estimates of current and future population to estimate current and future numbers of people with AD dementia in the United States. We estimated that in 2010, there were 4.7 million individuals aged 65 years or older with AD dementia (95% confidence interval [CI] = 4.0-5.5). Of these, 0.7 million (95% CI = 0.4-0.9) were between 65 and 74 years, 2.3 million were between 75 and 84 years (95% CI = 1.7-2.9), and 1.8 million were 85 years or older (95% CI = 1.4-2.2). The total number of people with AD dementia in 2050 is projected to be 13.8 million, with 7.0 million aged 85 years or older. The number of people in the United States with AD dementia will increase dramatically in the next 40 years unless preventive measures are developed.
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                Author and article information

                Journal
                Anal Chem
                Anal Chem
                ac
                ancham
                Analytical Chemistry
                American Chemical Society
                0003-2700
                1520-6882
                17 February 2023
                28 February 2023
                : 95
                : 8
                : 4251-4260
                Affiliations
                []Penn/CHOP Friedreich’s Ataxia Center of Excellence , Philadelphia, Pennsylvania 19104, United States
                []Center of Excellence in Environmental Toxicology, Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania , Philadelphia, Pennsylvania 19104, United States
                [§ ]Agilent Technologies Inc. , 5301 Stevens Creek Blvd., Santa Clara, California 95051, United States
                []Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania , Philadelphia, Pennsylvania, 19104, United States
                []Departments of Pediatrics and Neurology, Children’s Hospital of Philadelphia and University of Pennsylvania , Philadelphia, Pennsylvania 19104, United States
                Author notes
                [* ]Email: ianblair@ 123456upenn.edu . Phone: +1-610-529-0610. Fax: +1-215-573-9889.
                Author information
                https://orcid.org/0000-0001-5117-2038
                https://orcid.org/0000-0003-0366-8658
                Article
                10.1021/acs.analchem.3c00091
                9979142
                36800320
                75c74788-654b-4182-9942-5bd6b4d8f698
                © 2023 The Authors. Published by American Chemical Society

                Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works ( https://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 06 January 2023
                : 30 January 2023
                Funding
                Funded by: National Institute of Neurological Disorders and Stroke, doi 10.13039/100000065;
                Award ID: U01NS114143
                Funded by: Food and Drug Administration, doi 10.13039/100009210;
                Award ID: FD-R-0006029
                Funded by: National Center for Advancing Translational Sciences, doi 10.13039/100006108;
                Award ID: R21TR003035
                Funded by: National Institute of Environmental Health Sciences, doi 10.13039/100000066;
                Award ID: P30ES013508
                Categories
                Article
                Custom metadata
                ac3c00091
                ac3c00091

                Analytical chemistry
                Analytical chemistry

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