Evaluating MedDRA-to-ICD terminology mappings.

BACKGROUND: In this era of big data, data harmonization is an important step to ensure reproducible, scalable, and collaborative research. Thus, terminology mapping is a necessary step to harmonize heterogeneous data. Take the Medical Dictionary for Regulatory Activities (MedDRA) and International Classification of Diseases (ICD) for example, the mapping between them is essential for drug safety and pharmacovigilance research. Our main objective is to provide a quantitative and qualitative analysis of the mapping status between MedDRA and ICD. We focus on evaluating the current mapping status between MedDRA and ICD through the Unified Medical Language System (UMLS) and Observational Medical Outcomes Partnership Common Data Model (OMOP CDM). We summarized the current mapping statistics and evaluated the quality of the current MedDRA-ICD mapping; for unmapped terms, we used our self-developed algorithm to rank the best possible mapping candidates for additional mapping coverage. RESULTS: The identified MedDRA-ICD mapped pairs cover 27.23% of the overall MedDRA preferred terms (PT). The systematic quality analysis demonstrated that, among the mapped pairs provided by UMLS, only 51.44% are considered an exact match. For the 2400 sampled unmapped terms, 56 of the 2400 MedDRA Preferred Terms (PT) could have exact match terms from ICD. CONCLUSION: Some of the mapped pairs between MedDRA and ICD are not exact matches due to differences in granularity and focus. For 72% of the unmapped PT terms, the identified exact match pairs illustrate the possibility of identifying additional mapped pairs. Referring to its own mapping standard, some of the unmapped terms should qualify for the expansion of MedDRA to ICD mapping in UMLS.

Rapid affinity purification of intracellular organelles using a twin strep tag.

Cells are internally organized into compartmentalized organelles that execute specialized functions. To understand the functions of individual organelles and their regulations, it is critical to resolve the compositions of individual organelles, which relies on a rapid and efficient isolation method for specific organellar populations. Here, we introduce a robust affinity purification method for rapid isolation of intracellular organelles (e.g. lysosomes, mitochondria and peroxisomes) by taking advantage of the extraordinarily high affinity between the twin strep tag and streptavidin variants. With this method, we can isolate desired organelles with high purity and yield in 3 min from the post-nuclear supernatant of mammalian cells or less than 8 min for the whole purification process. Using lysosomes as an example, we show that the rapid procedure is especially useful for studying transient and fast cellular activities, such as organelle-initiated signaling and organellar contents of small-molecular metabolites. Therefore, our method offers a powerful tool to dissect spatiotemporal regulation and functions of intracellular organelles.