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dc.contributor.authorPathak, Gita
dc.contributor.authorAryal, Subhash
dc.contributor.authorPhillips, Nicole
dc.contributor.authorLicciardone, John
dc.creatorBhatnagar, Shweta
dc.date.accessioned2019-08-22T19:54:05Z
dc.date.available2019-08-22T19:54:05Z
dc.date.issued2019-03-05T17:54:18-08:00
dc.date.submitted2019-02-13T07:29:49-08:00
dc.identifier.urihttps://hdl.handle.net/20.500.12503/27229
dc.description.abstractCandidate Gene Association Study of Low Back Pain Using SNP Derived Gene Expression Profiling: A PRECISION PAIN Research Registry Study Shweta Bhatnagar, Gita Pathak, Subhash Aryal, Nicole Phillips, John Licciardone Abstract Objective: The Global Burden of Disease Study estimated that 632 million persons worldwide are affected by low back pain (LBP), making it the leading cause of disability worldwide. Furthering our understanding of genetic-based risk for LBP may allow for development of targeted gene therapy for pain which may help mitigate the healthcare and financial burden. Inflammatory genes have been implicated in pain disorders. Variability in how these genes are expressed may determine their association in low back pain. This study aims to predict the expression of candidate genes and their association with pain in participants of the PRECISION Pain Research Registry. Hypothesis: Elevated self-reported pain intensity and disability from LBP is associated with the higher expression of inflammatory genes. Methods: The DNA was collected, extracted, and genotyped using the Infinium® Global Screening Array (Illumina). Data were filtered based on standard quality control protocols (Anderson et al., 2010). Gene expression data of monocytes from the Multi-Ethnic Study for Atherosclerosis (MESA) was used for gene expression imputation using PrediXcan. Twenty-six candidate genes involved with inflammation and immune response processes (based on Gene Ontology Analysis) were analyzed. The imputed gene expression levels were transformed to dichotomized gene expression levels, over-expressed and under-expressed. The highly expressed gene levels were then tested for association with PRECISION participant outcomes data, including Roland-Morris Disability Score and a pain intensity score using SPSS. Results: Seven genes showed positive correlation between their predicted expression levels and scores on the Roland-Morris Questionnaire and the pain intensity scale for LBP: STAT-1, STAT-2, HLA-A, CD48, CD209, CLEC4G and SLAMF8. Also, as expected, many of these genes demonstrated co-expression patterns due to their common role in immune mediation. Conclusions: The results demonstrate a positive correlation between the increased expression of inflammatory genes and how the subjects perceived and reported LBP. Understanding the relationship between pain and variability in inflammatory genes could play a role in future precision medicine and pain management.
dc.language.isoen
dc.titleCandidate Gene Association Study of Low Back Pain Using SNP Derived Gene Expression Profiling: A PRECISION PAIN Research Registry Study
dc.typeposter
dc.type.materialtext
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