Reverse Phenotyping Core
2 other identifiers
observational
1,000
1 country
1
Brief Summary
Background: Genes tell a person's body how to grow and work. All people have variations in their genes. Some of these cause differences that show up in a person's traits or their health, others do not. Researchers want to gather more data on people based on their genes. They want to use this data to learn more about diseases and possible treatments. Objectives: To develop a cohort of participants who can be contacted again for phenotyping and collect their genetic data. To share those data with other researchers and make them searchable. Eligibility: People already enrolled in a wide variety of protocols. They will be of varying health status, age, and sex. They will have had or plan to have exome or genome sequencing under their protocol. They can be re-contacted by the research team for possible other studies. Design: Participants will give basic details like contact and demographic information. Participants may answer questions about their personal health history, their family medical history, or their thoughts or reactions to data. Participants may have basic health tests. Their height, weight, or blood pressure may be checked. Participants may have tests of heart function. They may have an ultrasound or other non-invasive test. Participants may provide blood, urine, or other samples. Participants may have scans or other tests. Participants will get the results of all clinical tests in a letter. If any tests are abnormal, someone from the study will call the participant to explain what the results mean and what to do about them. Participants will get genetic testing results only if researchers think they could affect the health of the participant or their relatives.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Jan 2020
Longer than P75 for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
August 14, 2018
CompletedFirst Posted
Study publicly available on registry
August 15, 2018
CompletedStudy Start
First participant enrolled
January 23, 2020
CompletedPrimary Completion
Last participant's last visit for primary outcome
June 1, 2028
ExpectedStudy Completion
Last participant's last visit for all outcomes
December 29, 2028
May 4, 2026
April 30, 2026
8.4 years
August 14, 2018
May 1, 2026
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Hypotheses from RPC to be tested
RPC will generate data regarding phenotypic consequences of genetic variants
yearly
Study Arms (1)
Reverse Phenotyping Core
Individuals undergoing phenotyping by the Reverse Phenotyping Core (RPC)
Eligibility Criteria
Individuals who have undergone genome sequencing under separate protocol
You may qualify if:
- Participants in the RPC Genomic Data Archive must be re-contactable by the primary study team (e.g., the collaborator who contributes their data must be able to contact the participants).
- All participants must be \>= 4 years old.
- Health Perceptions Survey Criterion: Only adult participants who are able to provide consent for themselves will be eligible for this portion of the study.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
National Institutes of Health Clinical Center
Bethesda, Maryland, 20892, United States
Related Publications (5)
Wilczewski CM, Obasohan J, Paschall JE, Zhang S, Singh S, Maxwell GL, Similuk M, Wolfsberg TG, Turner C, Biesecker LG, Katz AE. Genotype first: Clinical genomics research through a reverse phenotyping approach. Am J Hum Genet. 2023 Jan 5;110(1):3-12. doi: 10.1016/j.ajhg.2022.12.004.
PMID: 36608682BACKGROUNDGarnai SJ, Brinkmeier ML, Emery B, Aleman TS, Pyle LC, Veleva-Rotse B, Sisk RA, Rozsa FW, Ozel AB, Li JZ, Moroi SE, Archer SM, Lin CM, Sheskey S, Wiinikka-Buesser L, Eadie J, Urquhart JE, Black GCM, Othman MI, Boehnke M, Sullivan SA, Skuta GL, Pawar HS, Katz AE, Huryn LA, Hufnagel RB; Genomic Ascertainment Cohort; Camper SA, Richards JE, Prasov L. Variants in myelin regulatory factor (MYRF) cause autosomal dominant and syndromic nanophthalmos in humans and retinal degeneration in mice. PLoS Genet. 2019 May 2;15(5):e1008130. doi: 10.1371/journal.pgen.1008130. eCollection 2019 May.
PMID: 31048900BACKGROUNDManthiram K, Preite S, Dedeoglu F, Demir S, Ozen S, Edwards KM, Lapidus S, Katz AE; Genomic Ascertainment Cohort; Feder HM Jr, Lawton M, Licameli GR, Wright PF, Le J, Barron KS, Ombrello AK, Barham B, Romeo T, Jones A, Srinivasalu H, Mudd PA, DeBiasi RL, Gul A, Marshall GS, Jones OY, Chandrasekharappa SC, Stepanovskiy Y, Ferguson PJ, Schwartzberg PL, Remmers EF, Kastner DL. Common genetic susceptibility loci link PFAPA syndrome, Behcet's disease, and recurrent aphthous stomatitis. Proc Natl Acad Sci U S A. 2020 Jun 23;117(25):14405-14411. doi: 10.1073/pnas.2002051117. Epub 2020 Jun 9.
PMID: 32518111BACKGROUNDJohnston JJ, Brennan ML, Radenbaugh B, Yoo SJ, Hernandez SM; NHGRI Reverse Phenotyping Core; Lewis KL, Katz AE, Manolio TA, Biesecker LG. The ACMG SF v3.0 gene list increases returnable variant detection by 22% when compared with v2.0 in the ClinSeq cohort. Genet Med. 2022 Mar;24(3):736-743. doi: 10.1016/j.gim.2021.11.012. Epub 2021 Nov 18.
PMID: 34906458BACKGROUNDSpontarelli K, Young VC, Sweazey R, Padro A, Lee J, Bueso T, Hernandez RM, Kim J, Katz A, Rossignol F, Turner C, Wilczewski CM, Maxwell GL, Holmgren M, Bailoo JD, Yano ST, Artigas P. ATP1A1-linked diseases require a malfunctioning protein product from one allele. Biochim Biophys Acta Mol Cell Res. 2024 Jan;1871(1):119572. doi: 10.1016/j.bbamcr.2023.119572. Epub 2023 Sep 1.
PMID: 37659504BACKGROUND
Related Links
Study Officials
- PRINCIPAL INVESTIGATOR
Clesson E Turner, M.D.
National Human Genome Research Institute (NHGRI)
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- OTHER
- Sponsor Type
- NIH
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
August 14, 2018
First Posted
August 15, 2018
Study Start
January 23, 2020
Primary Completion (Estimated)
June 1, 2028
Study Completion (Estimated)
December 29, 2028
Last Updated
May 4, 2026
Record last verified: 2026-04-30
Data Sharing
- IPD Sharing
- Will share
- Shared Documents
- STUDY PROTOCOL
- Time Frame
- Data in dbGap is stored per NIH policy. Data in the Reverse Phenotyping Core/TGAC browser will be stored for the remainder of the protocol (18-HG-0129) and the time the study is closed, a proposal to the IRB will be made to keep the data or destroy it.
- Access Criteria
- dbGap is a controlled-access database with view-only access to summary-level information and individual-level genotype and sequence data associated with phenotypic features. The Reverse Phenotyping Core/TGAC browser allows researchers to identify particular genotypes or ranges of genotypes, while preserving the privacy of study participants by only displaying aggregate data for one or a limited number of loci in a search. The browser is located on NIH servers and searchable only by investigators in the NIH s intramural research program or external collaborators who have contributed sequence data.
We are actively depositing data into the database of genotypes and phenotypes (dbGaP), which is designed with tiered access to clinical data. That is, there is open, public access to summary clinical data of study participants and qualified investigators may apply for access to individual, coded clinical results. Such access is limited to authorized medical researchers and redistribution and security policies are strict. Broad future use of the data deposited into dbGaP (as opposed to restricted use for specific disorders) will be permitted. Sequence traces for individual genes will be available publicly (deposited in GenBank); however, these sequence traces will not be linked to a participant's identifiable information, nor to the sequence traces of other genes sequenced in that participant's sample. Coded genomic data are available to data contributors and NIH intramural investigators through the Reverse Phenotyping Core browser (18-HG-0129; https://rpc.nhgri.nih.gov/).