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A4813 - Relationships Between Symptom Burden and Peripheral Blood Gene Expression in Sarcoidosis
Author Block: V. Wang, S. Nerella, N. Bhakta, S. Machiraju, L. Koth; Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, CA, United States.
RATIONALE:
Sarcoidosis is a systemic inflammatory disease characterized by non-necrotizing granulomas in involved organs. Sarcoidosis patients may report symptoms including fatigue, dyspnea, depression and cognitive deficits. The presence and severity of these symptoms are variable across patients. The relationship between burden of symptoms and circulating mediators is largely unknown. We previously identified a robust pattern of gene expression changes in whole blood samples from sarcoidosis patients compared to healthy donors. We hypothesized that a genomic analysis of blood from sarcoidosis patients with a range of symptoms would identify gene expression patterns associated with a high versus low symptom burden.
METHODS:
We conducted a cross-sectional analysis. To identify subgroups of sarcoidosis patients with high or low symptom burden, we analyzed the distribution of scores from four different symptom questionnaires (Fatigue Assessment Scale, Shortness of Breath, Patient Health Questionnaire, and Multiple Sclerosis Neuropsychological Questionnaire). These questionnaires solicit symptoms related to fatigue, dyspnea, depression and cognitive deficits, respectively. We grouped patients into either high or low symptoms based on the concordancy of their scores for at least three of the four questionnaires. Whole blood samples were processed for total RNA using the Qiagen RNEasy kit and RNA sequencing was performed using the TruSeq Stranded Total RNA kit by Illumina. Differential gene expression was compared between the symptom high and low sarcoidosis groups.
RESULTS:
We studied 93 sarcoidosis patients and 24 healthy controls. We validated robust gene expression findings in this new sarcoidosis cohort by identifying ~1589 genes differentially expressed between sarcoidosis and health. We next wanted to identify differentially expressed genes between the high (n=17) and low (n=17) symptom sarcoidosis patients. We first performed clustering analysis using genes related to interferon signaling which did not distinguish patients with high or low symptoms.
CONCLUSION:
In this preliminary analysis of a subset of patients with symptom scores at the extreme values, we did not find that the level of interferon-related gene expression distinguished these two groups. We will expand our analysis to incorporate symptom scores related to pain and fibromyalgia in next steps. We will also perform analyses to determine the number of differentially expressed genes that could distinguish between high and low symptoms and whether these genes associate with specific pathways. Exploration of these genes may reveal endotypes of sarcoidosis patients, which could lead to novel therapy approaches.