ID

44948

Description

https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001833.v1.p1 NCT00794352 The goal of "Comprehensive Multimodal Analysis of Neuroimmunological Diseases of the CNS" is to define the pathophysiological mechanisms underlying the development of disability in immune-mediated disorders of the central nervous system (CNS) and to distinguish these from physiological (and often beneficial) responses of the human immune system to CNS injury. The long-term objective of the trial is to acquire knowledge that would allow us to therapeutically inhibit the pathogenic mechanisms and enhance repair mechanisms in immune-mediated CNS diseases, thereby minimizing the extent of CNS tissue damage and promoting recovery. To date, 460 patients with a confirmed diagnosis of multiple sclerosis (MS) have been enrolled into the natural history clinical trial. In addition to standardized clinical, functional, neuroimaging and molecular/immunological data, blood samples were also collected for genetic research. However, only 299 study participants with confirmed MS currently have whole genome sequencing data available. In addition to the genome-wide data available for the 299 MS patients, this dbGaP submission provides demographic and phenotypic information for each subject collected at various points throughout the trial. We include race and family history of MS collected at the baseline visit as well as age and measures of disease severity collected at the most recent visit. As these data were randomized into discovery and validation cohorts, we also indicate the assigned group in the phenotypic data. It is hoped that these data may be applied to the development of clinically-useful tools such as diagnostic tests and new, sensitive scales of neurological disability, disease severity and CNS tissue destruction. Principal Investigator: Bibiana Bielekova, PhD. National Institutes of Health, Bethesda, MD, USA Funding Sources: Intramural Research Program of the National Institute of Allergy and Infectious Diseases. National Institutes of Health, Bethesda, MD, USA Acknowledgement Statement: Please cite/reference the use of dbGaP data by including the dbGaP accession phs001833.v1.p1.

Lien

https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001833.v1.p1

Mots-clés

  1. 22/04/2022 22/04/2022 - Martin Dugas
  2. 12/05/2022 12/05/2022 - Martin Dugas
  3. 12/10/2022 12/10/2022 - Adrian Schulz
  4. 26/06/2023 26/06/2023 - Dr. Christian Niklas
Détendeur de droits

Bibiana Bielekova, PhD. National Institutes of Health, Bethesda, MD, USA

Téléchargé le

12 mai 2022

DOI

Pour une demande vous connecter.

Licence

Creative Commons BY 4.0

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dbGaP phs001833 Genetic Model of MS Severity Predicts Future Accumulation of Disability

Dataset pht009152.v1.p1: MS_Severity_Subject_Phenotypes: This subject phenotypes data table includes multiple sclerosis disease severity scale, self-reported family history of multiple sclerosis, subject gender, age, race, and cohort information.

Data dictionary
Description

Data dictionary

Subject ID
Description

SUBJECT_ID

Type de données

string

Alias
UMLS CUI [1,1]
C2348585
MS Disease Severity Scale
Description

MSDSS

Type de données

float

Alias
UMLS CUI [1,1]
C0026769
UMLS CUI [1,2]
C0521117
Self-reported sex
Description

SEX

Type de données

integer

Alias
UMLS CUI [1,1]
C0150831
Subject age at most recent visit
Description

AGE

Type de données

float

Unités de mesure
  • years
Alias
UMLS CUI [1,1]
C0001779
years
Self-reported race
Description

RACE

Type de données

text

Alias
UMLS CUI [1,1]
C0034510
Self-reported family history of MS
Description

FHX_MS

Type de données

integer

Alias
UMLS CUI [1,1]
C0241889
UMLS CUI [1,2]
C0026769
Indicator for training and validation cohort split
Description

COHORT

Type de données

text

Alias
UMLS CUI [1,1]
C0599755

Similar models

Dataset pht009152.v1.p1: MS_Severity_Subject_Phenotypes: This subject phenotypes data table includes multiple sclerosis disease severity scale, self-reported family history of multiple sclerosis, subject gender, age, race, and cohort information.

Name
Type
Description | Question | Decode (Coded Value)
Type de données
Alias
Item Group
Data dictionary
SUBJECT_ID
Item
Subject ID
string
C2348585 (UMLS CUI [1,1])
MSDSS
Item
MS Disease Severity Scale
float
C0026769 (UMLS CUI [1,1])
C0521117 (UMLS CUI [1,2])
Item
Self-reported sex
integer
C0150831 (UMLS CUI [1,1])
Code List
Self-reported sex
CL Item
Female (1)
CL Item
Male (2)
AGE
Item
Subject age at most recent visit
float
C0001779 (UMLS CUI [1,1])
Item
Self-reported race
text
C0034510 (UMLS CUI [1,1])
Code List
Self-reported race
CL Item
Black or African American (Black or African American)
CL Item
White (White)
CL Item
Asian (Asian)
CL Item
More than one race (More than one race)
CL Item
Unknown or Not reported (Unknown or Not reported)
Item
Self-reported family history of MS
integer
C0241889 (UMLS CUI [1,1])
C0026769 (UMLS CUI [1,2])
Code List
Self-reported family history of MS
CL Item
1=No/Unknown Family History (1)
CL Item
2=Reported Family History (2)
Item
Indicator for training and validation cohort split
text
C0599755 (UMLS CUI [1,1])
Code List
Indicator for training and validation cohort split
CL Item
training (training)
CL Item
validation (validation)

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