ID
45542
Description
Principal Investigator: John D. Kriesel, MD, University of Utah School of Medicine, Salt Lake City, Utah, USA MeSH: Multiple Sclerosis, Chronic Progressive,Encephalitis, Herpes Simplex,Subacute Sclerosing Panencephalitis https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000715 Deep sequencing allows for a rapid, accurate characterization of microbial DNA and RNA sequences in many types of samples. Deep sequencing (also called next generation sequencing or NGS) is being developed to assist with the diagnosis of a wide variety of infectious diseases. In this study, seven frozen brain samples (n = 7) from deceased subjects with recent encephalitis were investigated. RNA from each sample was extracted, randomly reverse transcribed, and sequenced. The sequence analysis was performed in a blinded fashion and confirmed with pathogen-specific PCR. This analysis successfully identified measles virus sequences in two brain samples and herpes simplex virus type-1 sequences in three brain samples. No pathogen was identified in the other two brain specimens. These results were concordant with pathogen-specific PCR and partially concordant with prior neuropathological examinations, demonstrating that deep sequencing can accurately identify viral infections in frozen brain tissue (Chan et al., 2014). Data from the primary progressive multiple sclerosis (PPMS) brain specimens (n = 14) and Normal Control brain specimens (n = 14) are also submitted here. All the subjects studied here (encephalitis, PPMS, and controls) were selected from existing collections at the Rocky Mountain and UCLA brain banks. These selections were performed by the directors at the two centers (Dr. Corboy at RM and Nagra at UCLA) based on clinic information provided at the time of collection. All the specimens are from deidentified deceased individuals. The submitting investigators have no identifying information on any of these subjects. To avoid confusion, the dbGaP Subject IDs are identical to the brain bank identifying numbers.
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Versions (1)
- 4/1/23 4/1/23 - Simon Heim
Détendeur de droits
John D. Kriesel, MD, University of Utah School of Medicine, Salt Lake City, Utah, USA
Téléchargé le
4 de enero de 2023
DOI
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Licence
Creative Commons BY 4.0
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dbGaP phs000715 NINDS MS and ADEM Deep Sequencing Studies
Eligibility Criteria
- StudyEvent: SEV1
- Eligibility Criteria
- Subject - Consent - Affection Status Information
- Subject - Sample Mapping
- The dataset provides basic sociodemographic information and information about the collected tissue, e.g. anatomical location of tissue collection, time past between death and tissue collection, year specimen were collected by brain bank, known comorbidities.
- Sample - Attribute Information
Similar models
Eligibility Criteria
- StudyEvent: SEV1
- Eligibility Criteria
- Subject - Consent - Affection Status Information
- Subject - Sample Mapping
- The dataset provides basic sociodemographic information and information about the collected tissue, e.g. anatomical location of tissue collection, time past between death and tissue collection, year specimen were collected by brain bank, known comorbidities.
- Sample - Attribute Information
C0680251 (UMLS CUI [1,2])
C0205396 (UMLS CUI [1,2])
C0014038 (UMLS CUI [1,3])
C0751964 (UMLS CUI [1,4])
C1550040 (UMLS CUI [1,5])
C2708733 (UMLS CUI [1,6])
C4064021 (UMLS CUI [1,7])
C0751967 (UMLS CUI [1,2])
C0026769 (UMLS CUI [1,3])