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.

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.

Study Overview

• Status: Recruiting
• Conditions: Age-Related Osteoporosis
• Intervention / Treatment: Other: Sample collection for gene expression

• Study Type: Observational
• Enrollment (Estimated): 550

Contacts and Locations

• Study Contact: Name: Cheryl L Ackert-Bicknell, PhD; Phone Number: 3037246623; Email: CHERYL.ACKERT-BICKNELL@CUANSCHUTZ.EDU

Study Locations

• United States
  • Colorado
    • Aurora, Colorado, United States, 80045
      • Recruiting
      • Univeristy of Colorado Denver
      • Contact: Cheryl L Ackert-Bicknell@cuAnschutz.edu, PhD; Phone Number: 303-724-6623; Email: cheryl.ackert-bicknell@cuanschutz.edu
      • Contact: Reed A Ayers, PhD; Phone Number: 303-724-1158; Email: reed.ayers@cuanschutz.edu
      • Principal Investigator: Cheryl L Ackert-Bicknell, PhD
      • Principal Investigator: David Ou Yang, MD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

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. Patients Patients will be recruited through the Spine Center at the University of Colorado Hospital.

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?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

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

Other: Sample collection for gene expression; 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Gene and transcript quantification	The abundances (in transcripts per million, TPM) of all known transcripts will be quantified in each bone sample via next generation RNA-sequencing.	Baseline
Genotypes	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.	Baseline

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Expression quantitative trait loci (eQTL)	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.	Baseline
Co-localization	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.	Baseline
Expression-phenotype correlation	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.	Baseline
Co-expression Network	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.	Baseline

Collaborators and Investigators

• Sponsor: University of Colorado, Denver
• Collaborators: University of Virginia
• Investigators: Principal Investigator: Cheryl L Ackert-Bicknell, PhD, University of Colorado, Denver

Study record dates

Study Major Dates

• Study Start (Estimated): April 1, 2024
• Primary Completion (Estimated): August 30, 2030
• Study Completion (Estimated): August 30, 2030

Study Registration Dates

• First Submitted: July 7, 2023
• First Submitted That Met QC Criteria: July 7, 2023
• First Posted (Actual): July 14, 2023

Study Record Updates

• Last Update Posted (Actual): April 3, 2024
• Last Update Submitted That Met QC Criteria: April 2, 2024
• Last Verified: April 1, 2024

More Information

Terms related to this study

• Keywords: Bone mineral density, gene transcription, spine, genetic disease
• Additional Relevant MeSH Terms: Metabolic Diseases; Musculoskeletal Diseases; Bone Diseases; Bone Diseases, Metabolic; Osteoporosis
• Other Study ID Numbers: 23-0602

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No