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Genetics and the Clinical Approach to Paragangliomas

  • K. -M. Schulte*
  • , N. Talat
  • , G. Galata
  • , S. Aylwin
  • , L. Izatt
  • , G. Eisenhofer
  • , A. Barthel
  • , S. R. Bornstein
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

This study analyses new information on gene mutations in paragangliomas and puts them into a clinical context. A suspicion of malignancy is critical to determine the workup and surgical approach in adrenal (A-PGL) and extra-adrenal (E-PGL) paragangliomas (PGLs). Malignancy rates vary with location, family history, and gene tests results. Currently there is no algorithm incorporating the above information for clinical use. A sum of 1 821 articles were retrieved from PubMed using the search terms “paraganglioma genetics”. Thirty-seven articles were selected of which 9 were analyzed. It was found that 599/2 487 (24%) patients affected with paragangliomas had a germline mutation. Of these 30.2% were mutations in SDHB, 25% VHL, 19.4% RET, 18.4% SDHD, 5.0% NF1, and 2.0% SDHC genes. A family history was positive in 18.1–64.3% of patients. Adrenal PGLs accounted for 55.1% in mutation (+) and 81.0% in mutation (−) patients (RR 1.2, p<0.0001). Bilateral A-PGLs accounted for 56.4% in mutation (+) and 3.2% in mutation (−) patients (RR 8.7, p<0.0001). E-PGL were found in 33.6% of mut+ and 17.3% of mut– (RR 1.7, p<0.0001). In mutation (+) patients PGLs malignancy varied with location, adrenal (6.4%) thoraco-abdominal E-PGL (38%), H & N E-PGL (10%). Malignancy rates were 8.2% in mutation (−) and lower in mutation (+) PGLs except for SDHB 36.5% and SDHC 8.3%. Exclusion of a mutation lowered the probability of malignancy significantly in E-PGL (RR 0.03 (95% CI 0.1–0.6); p<0.001). Mutation analysis provides valuable preoperative information to assess the risk of malignancy in A-PG and E-PGLs and should be considered in the work up of all E-PGL lesions.
Original languageEnglish
Pages (from-to)964-973
Number of pages10
JournalHormone and Metabolic Research
Volume46
Issue number13
DOIs
Publication statusPublished - Dec 2014

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Family
  • Genetic Predisposition to Disease
  • Humans
  • Mutation/genetics
  • Mutation Rate
  • Paraganglioma/genetics

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