OC 65.5 - Platelet-specific gene dysregulation and intron retention in a patient with syndromic thrombocytopenia

Background: Inherited thrombocytopenia (IT) is caused by genetic variation in key genes involved in platelet formation. The current gold standard for genetic diagnosis involves a gene panel test but some patients don’t obtain a diagnosis after screening these known genes. Even when applying whole genome sequencing (WGS), it remains very difficult to pinpoint their underlying genetic cause. We aim to implement platelet RNAseq to enhance the diagnostic rate.

Aims: This pilot study combines blood cell RNA sequencing with WGS data to diagnose a patient with syndromic IT.

Methods: RNA was extracted from platelets, neutrophils, monocytes and T-cells for total RNAseq. Expression outlier and intron retention detection were performed using the machine learning-based outlier detection methods OUTRIDER and IRFinder, respectively.

Results: A 16-year-old boy was diagnosed with Paris-Trousseau (thrombocytopenia, syndactyly, mild dysmorphia and psychomotor deterioration) but no deletion of FLI1 was found. FLI1 and other known IT genes carried no pathogenic variants. His platelets showed an altered gene expression profile compared to 20 healthy controls (Figure 1). Gene expression analysis identified 2982 downregulated genes in platelets (log2FC<-1) that were enriched for platelet function pathways. Remarkably, the transcriptomes of his other blood cells didn’t show such extensive alterations. The outlier detection method using 169 platelet samples, including controls and other platelet disorder patients, identified 46 significantly downregulated genes in platelets from this patient (including MPL, GP9 and ITGA2B). Further inspection of platelet RNAseq data showed a significant genome-wide intron retention that was absent in RNA from other blood cells (Figure 2). Pathway analysis for genes with increased intron retention (n=423) showed enrichment for mRNA processing. We are currently investigating WGS rare variants in known splicing-related genes.

Conclusion(s): We identified a platelet-specific gene expression and intron retention defect in an IT patient that could support WGS data analysis to identify the disease-causing variant.