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Clinical Trials/NCT05946278
NCT05946278
Recruiting
Not Applicable

Identification and Characterization of Genetic Regulators of Bone Health That Are Unique to Vertebral Bone.

University of Colorado, Denver1 site in 1 country550 target enrollmentApril 2024

Overview

Phase
Not Applicable
Intervention
Not specified
Conditions
Age-Related Osteoporosis
Sponsor
University of Colorado, Denver
Enrollment
550
Locations
1
Primary Endpoint
Gene and transcript quantification
Status
Recruiting
Last Updated
2 years ago

Overview

Brief Summary

Osteoporosis is an age related disease in which a person's bone slowly becomes weaker with time. The bones may become so weak that they break easily such as a fall from standing height. The most commonly broke bones in osteoporosis are those of the hip, the spine or the wrist. Osteoporosis runs in families meaning that genetic differences explain why some people break bones in old age and other do not. Genetic studies have been done that show the the genes associated with spine (vertebral) fractures (broken bones) and hip fractures are different, suggesting that osteoporosis of the spine is not the exact same disease as osteoporosis of the hip. Genetic studies tell us what part of the genome (i.e. genes) are associated with a disease, but do not tell us how these genes act biologically to cause that disease. In this study, we seek to determine how the genes uniquely associated with spine osteoporosis behave in normal and aged bone, to determine how they interact with each other as a team to impact spine bone. In this study, we will measure gene activity (so called gene expression) in bone samples taken from people undergoing major spine deformity surgery. We will using genetic data from these patients to determine how gene activity is controlled in bone and how that relates to measures of bone health such as bone mineral density data. The results of this study will provide critical data regarding how osteoporosis of the spine happens, and these data will be used to find better and safer treatments to prevent bone fractures of the spine that happen with age.

Registry
clinicaltrials.gov
Start Date
April 2024
End Date
August 30, 2030
Last Updated
2 years ago
Study Type
Observational
Sex
All

Investigators

Responsible Party
Sponsor

Eligibility Criteria

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.

Outcomes

Primary Outcomes

Gene and transcript quantification

Time Frame: Baseline

The abundances (in transcripts per million, TPM) of all known transcripts will be quantified in each bone sample via next generation RNA-sequencing.

Genotypes

Time Frame: Baseline

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.

Secondary Outcomes

  • Co-localization(Baseline)
  • Expression-phenotype correlation(Baseline)
  • Co-expression Network(Baseline)
  • Expression quantitative trait loci (eQTL)(Baseline)

Study Sites (1)

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