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Start Over Author "Yeske, P." Topic mitochondrial diseases
3 results on '"Yeske, P."'

1. The evolution of the mitochondrial disease diagnostic odyssey.

Author

Thompson JLP, Karaa A, Pham H, Yeske P, Krischer J, Xiao Y, Long Y, Kramer A, Dimmock D, Holbert A, Gorski C, Engelstad KM, Buchsbaum R, Rosales XQ, and Hirano M

Subjects
Humans, Reproducibility of Results, Mitochondrial Diseases diagnosis, Mitochondrial Diseases genetics
Abstract

Background: Mitochondrial diseases often require multiple years and clinicians to diagnose. We lack knowledge of the stages of this diagnostic odyssey, and factors that affect it. Our goals are to report the results of the 2018 Odyssey2 (OD2) survey of patients with a medical diagnosis of mitochondrial disease; and to propose steps to reduce the odyssey going forward, and procedures to evaluate them., Methods: Data are from the NIH-funded NAMDC-RDCRN-UMDF OD2 survey (N = 215). The main outcomes are Time from symptom Onset to mitochondrial disease Diagnosis (TOD) and Number of Doctors Seen during this diagnostic process (NDOCS)., Results: Expert recoding increased analyzable responses by 34% for final mitochondrial diagnosis and 39% for prior non-mitochondrial diagnosis. Only one of 122 patients who initially saw a primary care physician (PCP) received a mitochondrial diagnosis, compared to 26 of 86 (30%) who initially saw a specialist (p < 0.001). Mean TOD overall was 9.9 ± 13.0 years, and mean NDOCS 6.7 ± 5.2. Mitochondrial diagnosis brings extensive benefits through treatment changes and increased membership in and support of advocacy groups., Conclusions: Because TOD is long and NDOCS high, there is great potential for shortening the mitochondrial odyssey. Although prompt patient contact with primary mitochondrial disease specialists, or early implementation of appropriate tests, may shorten the diagnostic odyssey, specific proposals for improvement require testing and confirmation with adequately complete, unbiased data across all its stages, and appropriate methods. Electronic Health Record (EHRs) may help by accessing diagnostic codes early, but their reliability and diagnostic utility have not been established for this group of diseases., (© 2023. The Author(s).)

Published
2023
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2. Short report: Vaccine attitudes in the age of COVID-19 for a population of children with mitochondrial disease.

Author

Gordon-Lipkin E, Marcum CS, Kruk S, Thompson E, Yeske P, Martin L, and McGuire PJ

Subjects
Child, Humans, COVID-19 Vaccines, Attitude, COVID-19 epidemiology, COVID-19 prevention & control, Vaccines, Mitochondrial Diseases prevention & control
Abstract

Background: Children with developmental disabilities are vulnerable to morbidity associated with COVID-19., Aims: To understand attitudes toward routine childhood vaccinations versus the COVID-19 vaccine in a population of families affected by mitochondrial disease (MtD), a form of developmental disability., Methods and Procedures: An online survey was administered via several advocacy groups for children with MtD., Outcomes and Result: Eighty-six percent of families reported being up to date with the childhood vaccine schedule and seventy percent reported that their affected child receives the annual flu shot. However, only fifty percent reported that the benefits of the COVID-19 vaccine outweighed the risk for their affected child. One quarter of families expressed concern that their child may become sick or deteriorate after the COVID-19 vaccine. In comparison to other routine childhood vaccines, families expressed less confidence in the COVID-19 vaccine., Conclusions and Implications: Families affected by this population of developmental disabilities are more comfortable with the vaccines included in the routine childhood immunization schedule than with the newly introduced COVID-19 vaccine, even despite this group's vulnerability., Competing Interests: Conflicts of Interest The authors have no conflicts of interest to disclose., (Published by Elsevier Ltd.)

Published
2022
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3. Mitochondrial Disease Sequence Data Resource (MSeqDR): a global grass-roots consortium to facilitate deposition, curation, annotation, and integrated analysis of genomic data for the mitochondrial disease clinical and research communities

Author

Xiaowu Gai, Jeremy Leipzig, Aurora Pujol, Richard G. Boles, Deanna M. Church, Finley Macrae, Erin Rooney Riggs, Michio Hirano, Mariangela Santorsola, Yaffa R. Rubinstein, Rosanna Clima, Marie T. Lott, Penelope E. Bonnen, Christine M. Stanley, David Dimmock, Heidi L. Rehm, Marni J. Falk, Giuseppe Gasparre, Holger Prokisch, Shamima Rahman, Claire A. Sheldon, Anu Suomalainen, Hakon Hakonarson, Sarah E. Calvo, Melissa A. Parisi, Alphons P. M. Stassen, Zhe Zhang, Katrina Gwinn, Johan L.K. Van Hove, Lee-Jun C. Wong, Lisa D. Brooks, Virginia Brilhante, William C. Copeland, Jeana T. DaRe, Curt Scharfe, Michael A. Gonzalez, Johan T. den Dunnen, I.F.M. de Coo, Iris L. Gonzalez, Claudia Calabrese, Yasushi Okazaki, Vamsi K. Mootha, Lynne A. Wolfe, Douglas S. Kerr, Doron M. Behar, Bert Smeets, John Christodoulou, Juan C. Perin, Stephan Züchner, Lishuang Shen, Eric A. Shoubridge, Sihoun Hahn, Danuta Krotoski, Sharon F. Terry, Domenico Simone, David Ralph, Renkui Bai, Olga Derbenevoa, Honey V. Reddi, Eric A. Pierce, Daniel Navarro-Gomez, Gregory M. Enns, Vincent Procaccio, Russell P. Saneto, Mannis van Oven, Philip E. Yeske, David R. Thorburn, Bruce H. Cohen, Maria Lvova, Robert Shelton, Douglas C. Wallace, Maria Angela Diroma, Marcella Attimonelli, Dong Li, Elizabeth M. McCormick, Amy Goldstein, Mark A. Tarnopolsky, Patrick F. Chinnery, Donna Maglott, Richard J. Rodenburg, Jirair K. Bedoyan, Richard G.H. Cotton, Richard H. Haas, Jan A.M. Smeitink, Grant A. Mitchell, Isabelle Thiffault, Sherri J. Bale, RS: CARIM - R2 - Cardiac function and failure, RS: GROW - Developmental Biology, Genetica & Celbiologie, Klinische Genetica, RS: GROW - R4 - Reproductive and Perinatal Medicine, Falk M.J., Shen L., Gonzalez M., Leipzig J., Lott M.T., Stassen A.P.M., Diroma M.A., Navarro-Gomez D., Yeske P., Bai R., Boles R.G., Brilhante V., Ralph D., DaRe J.T., Shelton R., Terry S.F., Zhang Z., Copeland W.C., van Oven M., Prokisch H., Wallace D.C., Attimonelli M., Krotoski D., Zuchner S., Gai X., Bale S., Bedoyan J., Behar D., Bonnen P., Brooks L., Calabrese C., Calvo S., Chinnery P., Christodoulou J., Church D.t, Clima R., Cohen B.H., Cotton R.G., de Coo I.F.M., Derbenevoa O., den Dunnen J.T., Dimmock D., Enns G., Gasparre G., Goldstein A., Gonzalez I., Gwinn K., Hahn S., Haas R.H., Hakonarson H., Hirano M., Kerr D., Li D., Lvova M., Macrae F., Maglott D., McCormick E., Mitchell G., Mootha V.K., Okazaki Y., Pujol A., Parisi M., Perin J.C., Pierce E.A., Procaccio V., Rahman S., Reddi H., Rehm H., Riggs E., Rodenburg R., Rubinstein Y., Saneto R., Santorsola M., Scharfe C., Sheldon C., Shoubridge E.A., Simone D., Smeets B., Smeitink J.A., Stanley C., Suomalainen A., Tarnopolsky M., Thiffault I., Thorburn D.R., Hove J.V., Wolfe L., Wong L.J., and Genetic Identification

Subjects
Male, Mitochondrial DNA, Mitochondrial Diseases, DATABASE, Endocrinology, Diabetes and Metabolism, Mitochondrial disease, Genomics, mitochondrial DNA, Computational biology, Biology, Biochemistry, Genome, Article, 03 medical and health sciences, Annotation, User-Computer Interface, 0302 clinical medicine, Endocrinology, Data visualization, Human Phenotype Ontology, Databases, Genetic, Genetics, medicine, Humans, Exome, Molecular Biology, 030304 developmental biology, 0303 health sciences, Internet, business.industry, Information Dissemination, Computational Biology, Metabolic Disorders Radboud Institute for Molecular Life Sciences [Radboudumc 6], medicine.disease, 3. Good health, Data sharing, Phenotype, Genome, Mitochondrial, Female, business, 030217 neurology & neurosurgery, Software
Abstract

Success rates for genomic analyses of highly heterogeneous disorders can be greatly improved if a large cohort of patient data is assembled to enhance collective capabilities for accurate sequence variant annotation, analysis, and interpretation. Indeed, molecular diagnostics requires the establishment of robust data resources to enable data sharing that informs accurate understanding of genes, variants, and phenotypes. The "Mitochondrial Disease Sequence Data Resource (MSeqDR) Consortium" is a grass-roots effort facilitated by the United Mitochondria] Disease Foundation to identify and prioritize specific genomic data analysis needs of the global mitochondrial disease clinical and research community. A central Web portal (https://mseqdr.org) facilitates the coherent compilation, organization, annotation, and analysis of sequence data from both nuclear and mitochondrial genomes of individuals and families with suspected mitochondria! disease. This Web portal provides users with a flexible and expandable suite of resources to enable variant-, gene-, and exome-level sequence analysis in a secure, Web-based, and user-friendly fashion. Users can also elect to share data with other MSeqDR Consortium members, or even the general public, either by custom annotation tracks or through the use of a convenient distributed annotation system (DAS) mechanism. A range of data visualization and analysis tools are provided to facilitate user interrogation and understanding of genomic, and ultimately phenotypic, data of relevance to mitochondrial biology and disease. Currently available tools for nuclear and mitochondrial gene analyses include an MSeqDR GBrowse instance that hosts optimized mitochondrial disease and mitochondrial DNA (mtDNA) specific annotation tracks, as well as an MSeqDR locus-specific database (LSDB) that curates variant data on more than 1300 genes that have been implicated in mitochondrial disease and/or encode mitochondria-localized proteins. MSeqDR is integrated with a diverse array of mtDNA data analysis tools that are both freestanding and incorporated into an online exome-level dataset curation and analysis resource (GEM.app) that is being optimized to support needs of the MSeqDR community. In addition, MSeqDR supports mitochondrial disease phenotyping and ontology tools, and provides variant pathogenicity assessment features that enable community review, feedback, and integration with the public ClinVar variant annotation resource. A centralized Web-based informed consent process is being developed, with implementation of a Global Unique Identifier (GUID) system to integrate data deposited on a given individual from different sources. Community-based data deposition into MSeqDR has already begun. Future efforts will enhance capabilities to incorporate phenotypic data that enhance genomic data analyses. MSeqDR will fill the existing void in bioinformatics tools and centralized knowledge that are necessary to enable efficient nuclear and mtDNA genomic data interpretation by a range of shareholders across both clinical diagnostic and research settings. Ultimately, MSeqDR is focused on empowering the global mitochondrial disease community to better define and explore mitochondrial diseases. (C) 2014 Elsevier Inc. All rights reserved.

Published
2015

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