Genetic Regulators of Bone Health That Are Unique to Vertebral Bone
Identification and Characterization of Genetic Regulators of Bone Health That Are Unique to Vertebral Bone.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Cheryl L Ackert-Bicknell, PhD
- Phone Number: 3037246623
- Email: CHERYL.ACKERT-BICKNELL@CUANSCHUTZ.EDU
Study Locations
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Colorado
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Aurora, Colorado, United States, 80045
- Recruiting
- Univeristy of Colorado Denver
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Contact:
- Cheryl L Ackert-Bicknell@cuAnschutz.edu, PhD
- Phone Number: 303-724-6623
- Email: cheryl.ackert-bicknell@cuanschutz.edu
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Contact:
- Reed A Ayers, PhD
- Phone Number: 303-724-1158
- Email: reed.ayers@cuanschutz.edu
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Principal Investigator:
- Cheryl L Ackert-Bicknell, PhD
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Principal Investigator:
- David Ou Yang, MD
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Men and women between the ages of 18 and 85 undergoing a multi-level spinal fusion (i.e. a T10 (or higher) fusion to the pelvis) -OR- a 3 column osteotomy with a corpectomy from for short segment surgeries -OR- a vertebral column resection (VCR) involving a corpectomy -OR- any deformity correction surgery wherein the attending surgeon determines that a large amount of bone containing trabecular elements will be removed and discarded.
- Willing and able to provide informed consent
Exclusion Criteria:
- End stage renal disease.
- Any history of cancer.
- Reliance on a wheelchair for 70% or greater of their mobility for longer than 12 months.
- Quadra or paraplegia due to spinal cord injury.
- Current use of epilepsy medications.
- Confirmed Marfans, osteogenesis imperfecta or other genetic syndrome known to impact bone formation (Guacher's, Vit D independent rickets, etc).
- Current glucocorticoid use lasting longer than 3 months, or greater than 6 months lifetime use.
- Current or suspected current infection associated with orthopedic hardware.
- HIV or Hep C positive and or currently on anti-viral medications.
- History of gastric bypass surgery and or weigh loss exceeding 100 pounds.
- Primary or secondary hyperparathyroidism.
- Paget's disease
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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Patients undergoing deformity correction surgery
Patients undergoing deformity correction surgery undergoing a multi-level spinal fusion (i.e. a T10 (or higher) fusion to the pelvis) -OR- a 3 column osteotomy with a corpectomy from for short segment surgeries -OR- a vertebral column resection (VCR) involving a corpectomy -OR- any deformity correction surgery wherein the attending surgeon determines that a large amount of bone containing trabecular elements will be removed and discarded
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This is a cross-sectional sample collection study.
Vertebral bone tissue that would otherwise be discarded is collected from patients undergoing surgery to correct a spine deformity and gene expression is measure in these tissues.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Gene and transcript quantification
Time Frame: Baseline
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The abundances (in transcripts per million, TPM) of all known transcripts will be quantified in each bone sample via next generation RNA-sequencing.
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Baseline
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Genotypes
Time Frame: Baseline
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Low coverage whole genome sequence data will be obtained from all participants and the yielded outcome will be high quality genotypes for millions of single nucleotide polymorphism (SNPs) across the patient's genome.
As this is low coverage genotyping, the coverage rate will be between 1 and 0.4X representation for each spot in the genome per patients, so the data will be imputed to ensure coverage to 1X for all patients.
Each patient will be genotyped and therefore, data on a per participant level will be yielded.
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Baseline
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Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Expression quantitative trait loci (eQTL)
Time Frame: Baseline
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Using the imputed genotyping data and the gene expression data, regions of the genomes where there is local control (so called cis-regulatory elements) of for each gene expressed in bone will be identified.
The outcome deliverable will be a list of genes for which there is local genetic control of that gene's expression and the single nucleotide polymorphism(s) likely to be involved.
Each entry in this list is an Expression quantitative trait loci (eQTL).
This analysis uses all data from all participants in aggregate and the yielded results will be at the level of averages for the cohort, not at the individual participant level.
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Baseline
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Co-localization
Time Frame: Baseline
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Expression quantitative trait loci that co-localize with previously published bone mineral density genome wide association study associations will be identified.
Co-localizing genes will be prioritized for additional analyses.
This analysis uses all data from all participants in aggregate and the yielded results will be at the level of averages for the cohort, not at the individual participant level.
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Baseline
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Expression-phenotype correlation
Time Frame: Baseline
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For the genes for which a prioritized Expression quantitative trait loci from the co-localization analysis was identified, bone mineral density and other measures of bone mass and quality will be will be tested for correlation with the gene expression measures.
This analysis uses all data from all participants in aggregate and the yielded results will be at the level of averages for the cohort, not at the individual participant level.
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Baseline
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Co-expression Network
Time Frame: Baseline
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The participant level gene expression data, as collected from bone samples, will be used to construct networks of gene-gene interaction.
This will yield modules of highly correlated gene expression.
Bone mineral density data obtained from the patient electronic medical record will be used to identify modules that correlate with bone mineral density.This analysis uses all data from all participants in aggregate and the yielded results will be at the level of averages for the cohort, not at the individual participant level.
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Baseline
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Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Principal Investigator: Cheryl L Ackert-Bicknell, PhD, University of Colorado, Denver
Study record dates
Study Major Dates
Study Start (Estimated)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 23-0602
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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