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Genomic Biomarkers Can Provide a Deeper Understanding of Recurrent Pressure Injuries
Letitia Y Graves1, Katelyn R Schwartz, Josie Shiff
1Letitia Y. Graves, PhD, RN, is Assistant Professor, School of Nursing, University of Texas Medical Branch, Galveston, Texas, and Research Health Scientist, Louis Stokes Cleveland Veterans Affairs Medical Center. Katelyn R. Schwartz, MPH, BSN, RN, is Research Nurse, Cleveland VA Medical Center, Cleveland, Ohio. Josie Shiff, MS, is Research Assistant, Cleveland VA Medical Research & Education Foundation. Ernest R. Chan, PhD, is Research Scientist, Case Western Reserve University, Cleveland. Marinella Galea, MD, is Chief, Spinal Cord Injuries and Disorders, James J. Peters VAMC, Bronx, New York, and Associate Professor, Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York. Mary K. Henzel, MD, PhD, is Assistant Chief, Spinal Cord Injuries and Disorders, and Spinal Cord Injury Physiatrist, Louis Stokes Cleveland VA Medical Center. Christine Olney, PhD, RN, is Nurse Scientist, Minneapolis VA Health Care System, Minneapolis, Minnesota. Kath M. Bogie, DPhil, FAIMBE, is Research Career Scientist, Louis Stokes Cleveland Veterans Affairs Medical Center, and Professor, Department of Orthopedics, Case Western Reserve University.
Objective:
To identify genetic biomarkers predisposing individuals with spinal cord injury (SCI) to recurrent pressure injuries (PIs).
Methods:
Repeated measures of the transcriptome profile of veterans with SCI at three Veterans Spinal Cord Injuries and Disorders Centers. Exclusion criteria included having significant active systemic disease at time of enrollment. Researchers obtained comprehensive profiles of clinical and health factors and demographic information relevant to PI history at enrollment and at each follow-up visit by reviewing patients' medical charts. Whole blood samples were collected at 6- to 12-month intervals for 2 to 4 years. In addition to DNA profiling with whole genome sequencing of the patients, RNA sequencing was performed to assess pathways associated with PI risk.
Results:
Whole genome sequencing analysis identified 260 genes that showed increased prevalence of single-nucleotide variations in exonic regions with high (>20) combined annotation-dependent depletion scores between persons with high versus low intramuscular adipose tissue levels when cross-referenced with persons who had recurrent PIs. Gene set enrichment analysis using Hallmark and KEGG (Kyoto Encyclopedia of Genes and Genomes) gene sets of these candidate genes revealed enrichment in genes encoding proteins involved in fatty acid metabolism (P < .01). Further, RNA sequencing revealed upregulated activity in biological senescence pathways and downregulated activity in antimicrobial protection pathways.
Conclusions:
Genomic biomarkers may complement electronic health records to support management of complex interactive health issues such as risk of recurrent PIs in people with SCI. These findings may also be leveraged for homogeneous phenotypic grouping of higher-risk individuals.
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