A121: In Search of Infectious Triggers of Periodic Fever, Aphthous Stomatitis, Pharyngitis and Adenitis Syndrome
Authors: Freeman Samuel , Bhatt Ami , Pedamallu Chandra , King Sandra , Duke Fujiko , Jung Joonil , Lawton Maranda , Anderson Edwin , Fuhlbrigge Robert C. , Kenna Margaret , Licameli Greg , Meyerson Matthew , Dedeoglu Fatma 
Published: March 2014

Background/Purpose:

Periodic fever, aphthous stomatitis, pharyngitis and adenitis (PFAPA) syndrome is the most prevalent pediatric autoinflammatory fever disorder. As there is no known genetic cause or confirmatory test, diagnosis of PFAPA is challenging. Clockwork interval between episodes is a characteristic feature, which aids in diagnosis. The true prevalence and the etiology of PFAPA are not known, but genetic factors leading to immune dysregulation as well as infectious agents have been suggested as causative factors. Oral corticosteroids abort the episodes in majority of patients, and in recent years, tonsillectomy has been shown to be effective in inducing remission. Our center has a significant success rate with tonsillectomy in PFAPA patients. Using unbiased next‐generation sequencing, we investigated the presence of potential infectious agents and gene expression signatures in tonsils from patients with PFAPA, chronic tonsillitis and obstructive sleep apnea (OSA).

Methods:

Tonsil tissue from 3 age‐matched groups of pediatric patients was collected (6 PFAPA, 4 chronic tonsillitis and 4 OSA). Patients with PFAPA had characteristic periodic fevers in addition to at least 2 out of the 3 other described features. Total RNA extracted from punch biopsies of tonsil samples was subjected to massively parallel RNA sequencing (RNA‐Seq). The PathSeq software was used to identify and quantify microbial sequences. We compared the microbiome in PFAPA cases to those present in controls in order to identify differentially abundant microbes. RNA‐Seq data was also processed for gene expression analysis, and these data were analyzed using comparative marker analysis and unsupervised machine learning methods.

Results:

Computational analysis of bacterial and viral species present in PFAPA tonsillar biopsies did not reveal a known or novel candidate pathogen. Unbiased characterization of human viruses in cases and controls revealed human coxsackievirus, parechovirus and adenovirus C sequencing reads at low abundance in a subset of samples, without enrichment of any of these viruses in PFAPA cases. Unsupervised machine learning methods did not support the presence of a conserved microbial signature specific for PFAPA. We also performed comparative marker selection to identify genes whose expression is up or down regulated in PFAPA vs. control cases. This analysis showed differential expression of several genes, including genes involved in the innate immune response, in PFAPA tonsils vs. controls.

Conclusion:

Characterization of the tonsillar microbiome in PFAPA and control patients with this unbiased, highly sensitive sequencing‐based analysis did not demonstrate a microbial signature that was strongly correlated with PFAPA, although the power of this study is limited by the small sample size. On the other hand, the differential expression of innate immunity related genes in PFAPA samples strengthen the hypothesis of the existence of similar effector mechanisms between PFAPA and other periodic fever syndromes.