Pharmacogenomics (PGx) can provide optimized treatment to individual patients while potentially reducing healthcare costs. However, widespread implementation remains absent. We performed a pilot study of PGx screening in Dutch outpatient hospital care to identify the barriers and facilitators to implementation experienced by patients (n = 165), pharmacists (n = 58) and physicians (n = 21). Our results indeed suggest that the current practical experience of healthcare practitioners with PGx is limited, that proper education is necessary, that patients want to know the exact implications of the results, that healthcare practitioners heavily rely on their computer systems, that healthcare practitioners encounter practical problems in the systems used, and a new barrier was identified, namely that there is an unclear allocation of responsibilities between healthcare practitioners about who should discuss PGx with patients and apply PGx results in healthcare. We observed a positive attitude toward PGx among all the stakeholders in our study, and among patients, this was independent of the occurrence of drug-gene interactions during their treatment. Facilitators included the availability of and adherence to Dutch Pharmacogenetics Working Group guidelines. While clinical decision support (CDS) is available and valued in our medical center, the lack of availability of CDS may be an important barrier within Dutch healthcare in general.

Inherited neurological disorders, such as spinocerebellar ataxia (SCA) and fragile X (FraX), are frequently caused by short tandem repeat (STR) expansions. The detection and assessment of STRs is important for diagnostics and prognosis. We tested the abilities of nanopore long-read sequencing (LRS) using a custom panel including the nine most common SCA-related genes and FraX and created raw data to report workflow. Using known STR lengths for 23 loci in 12 patients, a pipeline was validated to detect and report STR lengths. In addition, we assessed the capability to detect SNVs, indels, and the methylation status in the same test. For the 23 loci, 22 were concordant with known STR lengths, while for the last, one of three replicates differed, indicating an artefact. All positive control STRs were detected as likely pathogenic, with no additional findings after a visual assessment of repeat motifs. Out of 226 SNV and Indel variants, two were false positive and one false negative (accuracy 98.7%). In all FMR1 controls, a methylation status could be determined. In conclusion, LRS is suitable as a diagnostic workflow for STR analysis in neurological disorders and can be generalized to other diseases. The addition of SNV/Indel and methylation detection promises to allow for a one-test-fits-all workflow.

The Solve-RD project brings together clinicians, scientists, and patient representatives from 51 institutes spanning 15 countries to collaborate on genetically diagnosing (“solving”) rare diseases (RDs). The project aims to significantly increase the diagnostic success rate by co-analyzing data from thousands of RD cases, including phenotypes, pedigrees, exome/genome sequencing, and multiomics data. Here we report on the data infrastructure devised and created to support this co-analysis. This infrastructure enables users to store, find, connect, and analyze data and metadata in a collaborative manner. Pseudonymized phenotypic and raw experimental data are submitted to the RD-Connect Genome-Phenome Analysis Platform and processed through standardized pipelines. Resulting files and novel produced omics data are sent to the European Genome-Phenome Archive, which adds unique file identifiers and provides long-term storage and controlled access services. MOLGENIS “RD3” and Café Variome “Discovery Nexus” connect data and metadata and offer discovery services, and secure cloud-based “Sandboxes” support multiparty data analysis. This successfully deployed and useful infrastructure design provides a blueprint for other projects that need to analyze large amounts of heterogeneous data.

The genetic predisposition of Inflammatory bowel disease (IBD) in the germline is well-established, while the potential role of somatic mutations in IBD remains underexplored. We aim to identify somatic mutations in intestinal mucosa and study their potential role in IBD pathogenesis. We identified somatic mutations using 538 intestinal biopsies and 268 blood samples from 268 IBD patients and 51 intestinal biopsies from 19 non-IBD controls. Mutations were called from RNA-seq data and whole exome sequencing data using Mutect2 software. Pathogenicity of mutations was predicted using the Variant Interpretation Pipeline. Mutation frequency and patterns were compared between IBD and controls, and within IBD-subgroups, considering both inflammation status and tissue of origin. IBD-affected tissue exhibited a significantly higher burden of somatic mutations compared to controls (p=0.02), with a striking enrichment for predicted likely pathogenic or pathogenic (pLP-P) mutations (p=2.07e-09). Notably, within IBD biopsies, pLP-P mutations were enriched in very early onset-IBD (VEO-IBD) genes (p≤2.2e-16) and primary immune deficiency (PID) genes (p≤2.2e-16), showing a 5.5-fold increase compared to non-IBD. Inflamed tissue showed an increase in mutations in PID and IBD-GWAS associated genes. Additionally, we identified pathogenic mutations in many IBD genes, such as the stop-gained mutation (c.517C>T) in HPS1 , and many pLP-P mutations across the JAK-STAT pathway. Our analysis reveals widespread accumulation of pLP-P somatic mutations in IBD-affected tissue compared to non-IBD controls, with significant enrichment in genes that cause monogenic VEO-IBD. These findings suggest that somatic mutations can contribute to the initiation and perpetuation of inflammation in IBD.