Pituitary volume in teenagers with first-presentation borderline personality disorder

This study used magnetic resonance imaging to examine pituitary gland volume (PGV) in teenage patients with a first presentation of borderline personality disorder (BPD). No difference in PGV was observed between healthy controls (n=20) and the total BPD cohort (n=20). However, within the BPD cohort, those exposed to childhood trauma (n=9) tended to have smaller pituitaries (-18%) than those with no history of childhood trauma (n=10). These preliminary findings suggest that exposure to childhood trauma, rather than BPD, per se, might be associated with reduced PGV, possibly reflecting hypothalamic-pituitary-adrenal axis dysfunction.

Pituitary volume predicts future transition to psychosis in individuals at ultra-high risk of developing psychosis

Background We examined pituitary volume before the onset of psychosis in subjects who were at ultra-high risk (UHR) for developing psychosis. Methods Pituitary volume was measured on 1.5-mm, coronal, 1.5-T magnetic resonance images in 94 UHR subjects recruited from admissions to the Personal Assessment and Crisis Evaluation Clinic in Melbourne, Australia and in 49 healthy control subjects. The UHR subjects were scanned at baseline and were followed clinically for a minimum of 1 year to detect transition to psychosis. Results Within the UHR group, a larger baseline pituitary volume was a significant predictor of future transition to psychosis. The UHR subjects who later went on to develop psychosis (UHR-P, n = 31) had a significantly larger (+12%; p = .001) baseline pituitary volume compared with UHR subjects who did not go on to develop psychosis (UHR-NP, n = 63). The survival analysis conducted by Cox regression showed that the risk of developing psychosis during the follow-up increased by 20% for every 10% increase in baseline pituitary volume (p = .002). Baseline pituitary volume of the UHR-NP subjects was smaller not only compared with UHR-P (as described above) but also compared with control subjects (−6%; p = .032). Conclusions The phase before the onset of psychosis is associated with a larger pituitary volume, suggesting activation of the HPA axis.

Whole exome sequencing is an efficient and sensitive method for detection of germline mutations in patients with phaeochromcytomas and paragangliomas

Background Genetic testing is recommended when the probability of a disease-associated germline mutation exceeds 10%. Germline mutations are found in approximately 25% of individuals with phaeochromcytoma (PCC) or paraganglioma (PGL); however, genetic heterogeneity for PCC/PGL means many genes may require sequencing. A phenotype-directed iterative approach may limit costs but may also delay diagnosis, and will not detect mutations in genes not previously associated with PCC/PGL. Objective To assess whether whole exome sequencing (WES) was efficient and sensitive for mutation detection in PCC/PGL. Methods Whole exome sequencing was performed on blinded samples from eleven individuals with PCC/PGL and known mutations. Illumina TruSeq™ (Illumina Inc, San Diego, CA, USA) was used for exome capture of seven samples, and NimbleGen SeqCap EZ v3.0 (Roche NimbleGen Inc, Basel, Switzerland) for five samples (one sample was repeated). Massive parallel sequencing was performed on multiplexed samples. Sequencing data were called using Genome Analysis Toolkit and annotated using annovar. Data were assessed for coding variants in RET, NF1, VHL, SDHD, SDHB, SDHC, SDHA, SDHAF2, KIF1B, TMEM127, EGLN1 and MAX. Target capture of five exome capture platforms was compared. Results Six of seven mutations were detected using Illumina TruSeq™ exome capture. All five mutations were detected using NimbleGen SeqCap EZ v3.0 platform, including the mutation missed using Illumina TruSeq™ capture. Target capture for exons in known PCC/PGL genes differs substantially between platforms. Exome sequencing was inexpensive (<$A800 per sample for reagents) and rapid (results <5 weeks from sample reception). Conclusion Whole exome sequencing is sensitive, rapid and efficient for detection of PCC/PGL germline mutations. However, capture platform selection is critical to maximize sensitivity.