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Geselecteerde datamodellen

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1103 Zoekresultaten.
Relevantie Beoordeling Nieuwe eerst Oude eerst

Eligibility Type 2 Diabetes NCT00641251

- 21-04-18 - 1 Formulier, 2 Itemgroepen, 15 Data-elementen, 1 Taal
Itemgroepen: Inclusion Criteria, Exclusion Criteria
DSS: Diabetes Surgery Study - Intensive Medical Management of Type 2 Diabetes, With and Without Gastric Bypass Surgery; ODM derived from: https://clinicaltrials.gov/show/NCT00641251

Eligibility Type 2 Diabetes NCT00508599

- 21-04-18 - 1 Formulier, 2 Itemgroepen, 18 Data-elementen, 1 Taal
Itemgroepen: Inclusion Criteria, Exclusion Criteria
The Effects of Two Days of Bedrest on Insulin Resistance in Type 2 Diabetics; ODM derived from: https://clinicaltrials.gov/show/NCT00508599

Eligibility Diabetes Mellitus, Type 2 NCT00541697

- 21-04-18 - 1 Formulier, 2 Itemgroepen, 10 Data-elementen, 1 Taal
Itemgroepen: Inclusion Criteria, Exclusion Criteria
Eze/Simva Switch Study in Diabetics (0653A-807); ODM derived from: https://clinicaltrials.gov/show/NCT00541697

Eligibility Diabetes NCT00184613

- 09-08-16 - 1 Formulier, 2 Itemgroepen, 11 Data-elementen, 1 Taal
Itemgroepen: Inclusion Criteria, Exclusion Criteria
Comparison of Insulin Glargine Against Insulin Aspart Infused Under the Skin in Patients With Type 2 Diabetes; ODM derived from: https://clinicaltrials.gov/show/NCT00184613

German Center for Diabetes Research (DZD) - Core Data Set - Base set

- 15-07-24 - 2 Formulieren, 8 Itemgroepen, 147 Data-elementen, 2 Talen
Itemgroepen: IG.1, IG.2, IG.3, IG.4, IG.5, IG.6, IG.7, Fragebogen
The German Center for Diabetes Research (DZD) has created a core data set for research on diabetes. It is published with permission by the DZD. The complete metadata and SOP are registered at DOI 10.5281/zenodo.7360000 For more information on the work of the DZD see: www.dzd-ev.de/en or contact: studien@dzd-ev.de German Center for Diabetes Research (DZD) Head Office at Helmholtz Zentrum München Ingolstädter Landstr. 1 85764 Neuherberg, Germany The German and English version of the Baecke Questionnaire in this core data set is based on the original paper by Baecke et al (https://doi.org/10.1093/ajcn/36.5.936), redistributed by ten Velde et al. (https://doi.org/10.1371/journal.pone.0256448), and the German translation and modification by Wagner & Singer (2003). The questionnaire was selectively modified by the German Diabetes Center (DDZ). Changes in this version 4 (15.07.2024) compared to version 3 (26.02.2024) include the addition of the parameters defined in the core data set of the German Centers for Health Research (DZG) (ID of MDM entry: 45851), the addition of laterality-specific blindness and an update of the terminology coding. The coding of the DZG parameters is currently under revision and not included in this current version. The coding of those DZG parameters that were already included in the DZD CDS will be provisionally retained.

Optional Set

3 Itemgroepen 46 Data-elementen

dbGaP phs000925 PAGE: IPM BioMe Biobank - Eligibility

- 28-04-24 - 5 Formulieren, 1 Itemgroep, 1 Data-element, 1 Taal
Itemgroep: IG.elig
Principal Investigator: Ruth Loos, PhD, The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA MeSH: Cardiovascular Diseases,Obesity,Diabetes Mellitus, Type 2,Glucose,Kidney Failure, Chronic,Cholesterol, HDL,Cholesterol, LDL,Triglycerides,Coronary Disease,Myocardial Infarction,Inflammation,Stroke,Body Height https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000925 The Institute for Personalized Medicine (IPM) Bio*Me* Biobank is a consented, EMR-linked medical care setting biorepository of the Mount Sinai Medical Center (MSMC) drawing from a population of over 70,000 inpatients and 800,000 outpatient visits annually. MSMC serves diverse local communities of upper Manhattan, including Central Harlem (86% African American), East Harlem (88% Hispanic Latino), and Upper East Side (88% Caucasian/white) with broad health disparities. IPM Bio*Me* Biobank populations include 28% African American, 38% Hispanic Latino predominantly of Caribbean origin, 23% Caucasian/White. IPM BioMe Biobank disease burden is reflective of health disparities with broad public health impact. Biobank operations are fully integrated in clinical care processes, including direct recruitment from clinical sites waiting areas and phlebotomy stations by dedicated Biobank recruiters independent of clinical care providers, prior to or following a clinician standard of care visit. Recruitment currently occurs at a broad spectrum of over 30 clinical care sites. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study (phs000356).

pht005176.v1.p1

1 Itemgroep 4 Data-elementen

pht005178.v1.p1

1 Itemgroep 6 Data-elementen

pht006203.v1.p1

1 Itemgroep 6 Data-elementen

pht005177.v1.p1

1 Itemgroep 5 Data-elementen

dbGaP phs000867 The Finland-United States Investigation of NIDDM Genetics (FUSION) Study - Eligibility

- 16-03-24 - 8 Formulieren, 1 Itemgroep, 2 Data-elementen, 1 Taal
Itemgroep: IG.elig
Principal Investigator: Michael Boehnke, University of Michigan, Ann Arbor, MI, USA MeSH: Diabetes Mellitus, Type 2 https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000867 The Finland-United States Investigation of NIDDM Genetics (FUSION) study is a long-term effort to identify genetic variants that predispose to type 2 diabetes (T2D) or that impact the variability of T2D-related quantitative traits. The initial effort involved linkage analysis of affected-sibling-pair (ASP) families based on over 5,000 individuals living in Finland, and association fine mapping based on these family members and additional T2D cases and controls. We completed a genome-wide association scan on 1161 T2D cases and 1174 normal glucose tolerant (NGT) controls. Individual-level data is available for the 919 T2D cases and 787 NGT controls who reconsented to the use of their data or are deceased (phs000100). In addition, we selected these 919 T2D cases and a matched set of 919 NGT controls (774 overlapping with GWAS) for targeted sequencing of 78 genes associated with glucose, insulin, and/or lipids. 400 of these T2D cases were also chosen for whole-exome sequencing (phs000702).

pht001126.v2.p1

1 Itemgroep 3 Data-elementen

pht004481.v1.p1

1 Itemgroep 3 Data-elementen

pht004482.v1.p1

1 Itemgroep 4 Data-elementen

pht004483.v1.p1

1 Itemgroep 21 Data-elementen

pht004484.v1.p1

1 Itemgroep 3 Data-elementen

pht004485.v1.p1

1 Itemgroep 3 Data-elementen

dbGaP phs000840 GoT2D - Eligibility

- 09-03-24 - 5 Formulieren, 1 Itemgroep, 1 Data-element, 1 Taal
Itemgroep: IG.elig
Principal Investigator: David Altshuler, Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA MeSH: Type 2 Diabetes Mellitus https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000840 The Genetics of Type 2 Diabetes Consortium (GoT2D) is a collaboration between the University of Michigan, the Broad Institute and the Wellcome Trust Centre for Human Genetics. The overall aim is to extend upon recent efforts, such as genome-wide association studies (GWAS) and large scale meta-analyses. While they have proved successful at mapping genomic loci that influence human diseases, like type 2 diabetes, much of the heritability remains unexplained. In this study, we use next generation sequencing and genotyping technologies to query for lower frequency variants in the human genome. Thereby, allowing a deeper characterization of the spectrum of alleles associated with type 2 diabetes risk, and a better assessment of the genes that play a role in the etiology of type 2 diabetes development. We studied 1,326 T2D cases and 1,331 normoglycemic controls from Northern and Central Europe (Sweden, Finland, UK, and Germany). To efficiently characterize the entire genome sequence of each individual, we performed low-coverage (~5x) whole-genome sequencing, augmented by deep coverage (~100x) sequencing of the exome (Fuchsberger et al, 2016), and dense (2.5M) single nucleotide polymorphism (SNP) genotyping using the HumanOmni2.5 array. The data deposited in dbGaP will include all the Swedish, Finnish, and UK samples, but the German data will be deposited in the European Genome-phenome Archive (EGA), by virtue of the project specific funding requirements.

pht005641.v1.p1

1 Itemgroep 4 Data-elementen

pht005643.v1.p1

1 Itemgroep 20 Data-elementen

pht005644.v1.p1

1 Itemgroep 6 Data-elementen

pht005642.v1.p1

1 Itemgroep 3 Data-elementen

dbGaP phs000961 eMERGE III: Columbia GENIE (Genomic Integration with EHR) - pht005331.v1.p1

- 31-01-24 - 5 Formulieren, 1 Itemgroep, 3 Data-elementen, 1 Taal
Itemgroep: pht005331
Principal Investigator: Chunhua Weng, PhD, Department of Biomedical Informatics, Columbia University, College of Physicians and Surgeons, New York, NY, USA MeSH: NA,Renal Insufficiency, Chronic,Alzheimer Disease,Aortic Aneurysm, Abdominal,Asthma,Attention Deficit Disorder with Hyperactivity,Clostridium difficile,Dermatitis, Atopic,Diabetes Mellitus, Type 2,Heart Diseases,Herpes Zoster,Hypothyroidism,Methicillin-Resistant Staphylococcus aureus,Prostatic Hyperplasia https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000961 The Columbia GENIE study contributes and shares phenotype and genotype data for individuals who were treated with our healthcare facilities and consented to share their data with dbGaP for scientific discovery. Some of these individuals have kidney or neurological problems and some are healthy volunteers from the Washington Height patient community. The purpose of this NOMAS study is to obtain information about physical features of the brain, carotid arteries, and heart. Some of our patients are pediatric patients with cardiac conditions. The study sample consists of four patient cohorts: - Northern Manhattan Study (NOMAS), N=1072 - Pediatric Cardiac Genomic Consortium (PCGC), n=374 - Caribbean Hispanics with Familial and Sporadic Late Onset Alzheimer's disease (Caribbean Hispanics/AD), n=330 - Alzheimer's Disease Sequencing Project (ADSP, n=44) - Genetics of Chronic Kidney Disease Study, n=1256

pht005332.v1.p1

1 Itemgroep 23 Data-elementen

pht005333.v1.p1

1 Itemgroep 3 Data-elementen

Eligibility

1 Itemgroep 3 Data-elementen

pht005330.v1.p1

1 Itemgroep 4 Data-elementen

dbGaP phs000984 Pharmacogenomics of Metformin Dose Response in T2DM Patients - Eligibility

- 13-12-23 - 8 Formulieren, 1 Itemgroep, 3 Data-elementen, 1 Taal
Itemgroep: IG.elig
Principal Investigator: Rex Chisholm, PhD, Northwestern University MeSH: Diabetes Mellitus, Type 2 https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000984 Type 2 Diabetes Mellitus (T2DM) is a chronic and sometimes debilitating disease that affects millions of adults in the USA. Metformin is commonly prescribed for T2DM; yet some T2DM patients do not tolerate it or respond well. This pharmacogenomics study will examine response, as both change in T2DM patients' weight and hemoglobin A1c (HbA1c) levels, to different doses of metformin, by extracting this data from the electronic health record (EHR), for T2DM subjects taking metformin found by prescription orders in the EHR, and identified as cases with the EHR phenotype algorithm published by Kho et. al. in 2012 (PMID: 22101970 as part of the eMERGE (electronic Medical Records and Genomics; dbGaP phs000237, phs000297, phs000360, phs000368, phs000888, and phs000948) project.

pht005008.v1.p1

1 Itemgroep 5 Data-elementen

pht005009.v1.p1

1 Itemgroep 5 Data-elementen

pht005010.v1.p1

1 Itemgroep 9 Data-elementen

pht005011.v1.p1

1 Itemgroep 5 Data-elementen

pht005702.v1.p1

1 Itemgroep 4 Data-elementen

pht005703.v1.p1

1 Itemgroep 5 Data-elementen

dbGaP phs001167 Type 2 Diabetes in African Americans, GWAS and Exome Sequencing - pht005639.v1.p1

- 12-12-23 - 8 Formulieren, 1 Itemgroep, 6 Data-elementen, 1 Taal
Itemgroep: pht005639
Principal Investigator: Donald Bowden, PhD, Center for Human Genomics, Center for Diabetes Research, Wake Forest University School of Medicine, Winston-Salem, NC, USA MeSH: Diabetes Mellitus, Type 2 https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001167 *The T2D Seq GWAS AA Cohort is utilized in the following dbGaP sub-studies.* To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs001167 T2D Seq GWAS AA Cohort.- phs000140 CIDR T2D Bowdens - phs001102 T2D GENES AA

pht005640.v1.p1

1 Itemgroep 4 Data-elementen

pht000630.v2.p1

1 Itemgroep 24 Data-elementen

pht000631.v2.p1

1 Itemgroep 18 Data-elementen

pht000911.v2.p1

1 Itemgroep 6 Data-elementen

pht005637.v1.p1

1 Itemgroep 8 Data-elementen

pht005638.v1.p1

1 Itemgroep 10 Data-elementen

dbGaP phs000974 NHLBI TOPMed: Whole Genome Sequencing and Related Phenotypes in the Framingham Heart Study - Eligibility

- 01-12-23 - 4 Formulieren, 1 Itemgroep, 1 Data-element, 1 Taal
Itemgroep: IG.elig
Principal Investigator: Vasan Ramachandran, Department of Medicine, Boston University School of Medicine, Boston, MA, USA MeSH: Cardiovascular Diseases,Atherosclerosis,Atrial Fibrillation,Death, Sudden, Cardiac,Diabetes Mellitus, Type 2,Heart Failure,Blood Pressure,Hypertension,Body Mass Index,Adiposity,Lipids,Pulmonary Disease, Chronic Obstructive,Renal Insufficiency, Chronic,Stroke,Osteoporosis,Risk Factors,Biological Markers,Biomarkers, Pharmacological https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000974 The Framingham Heart Study (FHS) is a prospective cohort study of 3 generations of subjects who have been followed up to 65 years to evaluate risk factors for cardiovascular disease. Its large sample of ~15,000 men and women who have been extensively phenotyped with repeated examinations make it ideal for the study of genetic associations with cardiovascular disease risk factors and outcomes. DNA samples have been collected and immortalized since the mid-1990s and are available on ~8000 study participants in 1037 families. These samples have been used for collection of GWAS array data and exome chip data in nearly all with DNA samples, and for targeted sequencing, deep exome sequencing and light coverage whole genome sequencing in limited numbers. Additionally, mRNA and miRNA expression data, DNA methylation data, metabolomics and other 'omics data are available on a sizable portion of study participants. This project will focus on deep whole genome sequencing (mean 30X coverage) in ~4100 subjects and imputed to all with GWAS array data to more fully understand the genetic contributions to cardiovascular, lung, blood and sleep disorders. Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs000007.

pht004909.v3.p3

1 Itemgroep 2 Data-elementen

pht004910.v4.p3

1 Itemgroep 2 Data-elementen

pht004911.v3.p3

1 Itemgroep 9 Data-elementen

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