Go to The Journal of Clinical Investigation
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact
  • Physician-Scientist Development
  • Current issue
  • Past issues
  • By specialty
    • COVID-19
    • Cardiology
    • Immunology
    • Metabolism
    • Nephrology
    • Oncology
    • Pulmonology
    • All ...
  • Videos
  • Collections
    • In-Press Preview
    • Resource and Technical Advances
    • Clinical Research and Public Health
    • Research Letters
    • Editorials
    • Perspectives
    • Physician-Scientist Development
    • Reviews
    • Top read articles

  • Current issue
  • Past issues
  • Specialties
  • In-Press Preview
  • Resource and Technical Advances
  • Clinical Research and Public Health
  • Research Letters
  • Editorials
  • Perspectives
  • Physician-Scientist Development
  • Reviews
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact

Usage Information

PIK3CA-associated developmental disorders exhibit distinct classes of mutations with variable expression and tissue distribution
Ghayda Mirzaa, et al.
Ghayda Mirzaa, et al.
View: Text | PDF
Research Article Genetics

PIK3CA-associated developmental disorders exhibit distinct classes of mutations with variable expression and tissue distribution

  • Text
  • PDF
Abstract

Mosaicism is increasingly recognized as a cause of developmental disorders with the advent of next-generation sequencing (NGS). Mosaic mutations of PIK3CA have been associated with the widest spectrum of phenotypes associated with overgrowth and vascular malformations. We performed targeted NGS using 2 independent deep-coverage methods that utilize molecular inversion probes and amplicon sequencing in a cohort of 241 samples from 181 individuals with brain and/or body overgrowth. We identified PIK3CA mutations in 60 individuals. Several other individuals (n = 12) were identified separately to have mutations in PIK3CA by clinical targeted-panel testing (n = 6), whole-exome sequencing (n = 5), or Sanger sequencing (n = 1). Based on the clinical and molecular features, this cohort segregated into three distinct groups: (a) severe focal overgrowth due to low-level but highly activating (hotspot) mutations, (b) predominantly brain overgrowth and less severe somatic overgrowth due to less-activating mutations, and (c) intermediate phenotypes (capillary malformations with overgrowth) with intermediately activating mutations. Sixteen of 29 PIK3CA mutations were novel. We also identified constitutional PIK3CA mutations in 10 patients. Our molecular data, combined with review of the literature, show that PIK3CA-related overgrowth disorders comprise a discontinuous spectrum of disorders that correlate with the severity and distribution of mutations.

Authors

Ghayda Mirzaa, Andrew E. Timms, Valerio Conti, Evan August Boyle, Katta M. Girisha, Beth Martin, Martin Kircher, Carissa Olds, Jane Juusola, Sarah Collins, Kaylee Park, Melissa Carter, Ian Glass, Inge Krägeloh-Mann, David Chitayat, Aditi Shah Parikh, Rachael Bradshaw, Erin Torti, Stephen Braddock, Leah Burke, Sondhya Ghedia, Mark Stephan, Fiona Stewart, Chitra Prasad, Melanie Napier, Sulagna Saitta, Rachel Straussberg, Michael Gabbett, Bridget C. O’Connor, Catherine E. Keegan, Lim Jiin Yin, Angeline Hwei Meeng Lai, Nicole Martin, Margaret McKinnon, Marie-Claude Addor, Luigi Boccuto, Charles E. Schwartz, Agustina Lanoel, Robert L. Conway, Koenraad Devriendt, Katrina Tatton-Brown, Mary Ella Pierpont, Michael Painter, Lisa Worgan, James Reggin, Raoul Hennekam, Karen Tsuchiya, Colin C. Pritchard, Mariana Aracena, Karen W. Gripp, Maria Cordisco, Hilde Van Esch, Livia Garavelli, Cynthia Curry, Anne Goriely, Hulya Kayserilli, Jay Shendure, John Graham Jr., Renzo Guerrini, William B. Dobyns

×

Usage data is cumulative from December 2024 through December 2025.

Usage JCI PMC
Text version 1,323 1,409
PDF 189 210
Figure 586 4
Table 356 0
Supplemental data 66 125
Citation downloads 124 0
Totals 2,644 1,748
Total Views 4,392
(Click and drag on plot area to zoom in. Click legend items above to toggle)

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

Advertisement

Copyright © 2025 American Society for Clinical Investigation
ISSN 2379-3708

Sign up for email alerts