Incidentalomas during imaging for primary hyperparathyroidism—incidence and clinical outcomes

Background: Imaging for pre-operative localisation of parathyroid glands in primary hyperparathyroidism is now routine. This has led to the detection of incidental lesions (incidentalomas) in other organs, the nature of which is not well characterised. The aim of this study was to determine the incidence, characteristics and outcomes in patients who had incidental findings on parathyroid imaging. Methods: Records of patients who underwent imaging for primary hyperparathyroidism over 2 years were reviewed to identify incidental lesions detected on parathyroid imaging. Patients with persistent or renal hyperparathyroidism were excluded. Details on the management of detected incidentalomas were obtained from patient records. Results: Incidentalomas were identified in 17 of 170 patients (10 %) undergoing parathyroid imaging. Incidentalomas included thyroid (n = 11), breast (n = 3), lateral compartment of the neck (n = 1), lung (n = 1) and clavicle (n = 1). However, no disease of clinical significance needing treatment was detected on further investigation. Conclusions: Although a significant proportion of patients undergoing parathyroid imaging had incidental lesions detected, these seem to be of little clinical significance. The morbidity and cost of further interventions on these incidentalomas need to be weighed against the benefits of routine imaging in improving outcomes of first-time surgery in patients with primary hyperparathyroidism. Keywords: Parathyroid gland, Primary hyperparathyroidism, Imaging, Incidentaloma

Massively parallel functional annotation of 3' untranslated regions

Functional characterization of noncoding sequences is crucial for understanding the human genome and learning how genetic variation contributes to disease. 3'2 untranslated regions (UTRs) are an important class of noncoding sequences, but their functions

Massively parallel functional annotation of 3′ untranslated regions

Functional characterization of noncoding sequences is crucial for understanding the human genome and learning how genetic variation contributes to disease. 3' untranslated regions (UTRs) are an important class of noncoding sequences, but their functions remain largely uncharacterized. We developed a method for massively parallel functional annotation of sequences from 3' UTRs (fast-UTR) and used this approach to measure the effects of a total of >450 kilobases of 3' UTR sequences from >2,000 human genes on steady-state mRNA abundance, mRNA stability and protein production. We found widespread regulatory effects on mRNA that were coupled to effects on mRNA stability and protein production. Furthermore, we discovered 87 novel cis-regulatory elements and measured the effects of genetic variation within known and novel 3' UTR motifs. This work shows how massively parallel approaches can improve the functional annotation of noncoding sequences, advance our understanding of cis-regulatory mechanisms and quantify the effects of human genetic variation