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Identification of unique genomic signatures in patients with fibromyalgia and chronic pain

ABSTRACT: Fibromyalgia is a chronic pain syndrome characterized by widespread pain. The pathophysiology of fibromyalgia is not clearly understood and there are no specific biomarkers available for accurate diagnosis. Here we define genomic signatures using high throughput RNA sequencing on 96 fibromyalgia and 93 matched controls. Our findings revealed two major fibromyalgia-associated expression signatures. The first group included 44 patients with a signature enriched for gene expression associated with extracellular matrix and downregulation of RhoGDI signaling pathway. The second group included 31 patients and showed a profound reduction in the expression of inflammatory mediators with an increased expression of genes involved in the CLEAR signaling pathway. These results suggest defective tissue homeostasis associated with the extra-cellular matrix and cellular program that regulates lysosomal biogenesis and participates in macromolecule clearance in fibromyalgia. Further elucidation of these pathways will lead to development of accurate diagnostic markers, and effective therapeutic options for fibromyalgia.

ORGANISM(S): Homo sapiens

PROVIDER: GSE221921 | GEO | 2024/02/21

REPOSITORIES: GEO

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Project description:Objective – Following destabilization of the medial meniscus (DMM), mice develop experimental osteoarthritis (OA) and associated pain behaviors that are dependent on the stage of disease. We aimed to describe changes in gene expression in knee-innervating dorsal root ganglia (DRG) after surgery, in order to identify molecular pathways associated with three pre-defined pain phenotypes: “post-surgical pain”, “early-stage OA pain”, and “persistent OA pain”. Design – We performed DMM or sham surgery in 10-week old male C57BL/6 mice and harvested L3-L5 DRG 4, 8, and 16 weeks after surgery or from age-matched naïve mice (n=3/group). RNA was extracted and an Affymetrix Mouse Transcriptome Array 1.0 was performed. Three pain phenotypes were defined: “post-surgical pain” (sham and DMM 4-week vs. 14-week old naïve), “early OA pain” (DMM 4-week vs. sham 4-week), and “persistent OA pain” (DMM 8- and 16-week vs. naïve and sham 8- and 16-week). ‘Top hit’ genes were defined as p<0.001. Pathway analysis (Ingenuity Pathway Analysis) was conducted using differentially expressed genes defined as p<0.05. In addition, we performed qPCR for Ngf and immunohistochemistry for F4/80+ macrophages in the DRG. Results – For each phenotype, top hit genes identified a small number of differentially expressed genes, some of which have been previously associated with pain (7/67 for “post-surgical pain”; 2/14 for “early OA pain”; 8/37 for “persistent OA pain”). Overlap between groups was limited, with 8 genes differentially regulated (p<0.05) in all three phenotypes. Pathway analysis showed that in the persistent OA pain phase many of the functions of differentially regulated genes are related to immune cell recruitment and activation. Genes previously linked to OA pain (CX3CL1, CCL2, TLR1, and NGF) were upregulated in this phenotype and contributed to activation of the neuroinflammation canonical pathway. In separate sets of mice, we confirmed that Ngf was elevated in the DRG 8 weeks after DMM (p=0.03), and numbers of F4/80+ macrophages were increased 16 weeks after DMM (p=0.002 vs. Sham). Conclusion- These transcriptomics findings support the idea that distinct molecular pathways discriminate early from persistent OA pain. Pathway analysis suggests neuroimmune interactions in the DRG contribute to initiation and maintenance of pain in OA. We grouped samples based on pain phenotype in the DMM mouse model of osteoarthritis. Group 1: post-surgical pain (DMM and sham +4 week samples); Group 2: post-surgical control (Naïve +4 week samples); Group 3: Early osteoarthritis pain (DMM +4 week samples); Group 4: Early controls (sham+4 and naive+4 week samples); Group 5: Persistent pain (DMM+8 and DMM+16 week samples); Group 6: Persistent controls (sham+8, naive+8, sham+16, and naive +16 samples). We compared Group 1 vs Group 2; Group 3 vs Group 4; and Group 5 vs Group 6 to draw the conclusions presented in our manuscript.

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Identification of unique genomic signatures in patients with fibromyalgia and chronic pain

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