OCULAR MANIFESTATIONS OF PORETTI-BOLTSHAUSER SYNDROME: FINDINGS FROM MULTIMODAL IMAGING AND ELECTROPHYSIOLOGY

Retin Cases Brief Rep. 2022 May 1;16(3):270-274. doi: 10.1097/ICB.0000000000000991. Epub 2020 Mar 17.

Abstract

Background/purpose: Poretti-Boltshauser syndrome is a rare, nonprogressive neurologic syndrome with characteristic cerebellar cysts on neuroimaging due to mutations in LAMA1. The ophthalmic findings in Poretti-Boltshauser syndrome are not well described. Here, we report the ophthalmic findings from multimodal imaging and electrophysiology of a patient with genetically confirmed Poretti-Boltshauser syndrome.

Methods: A 3-year-old boy with confirmed mutations in LAMA1 underwent examination under anesthesia with electroretinography and multimodal imaging including fundus photography, fluorescein angiography, optical coherence tomography, and optical coherence tomography angiography.

Results: Dilated fundus examination was notable for retinal vascular anomalies, including a large area of nonperfusion in the temporal macula with corresponding retinal thinning on optical coherence tomography. There was an absence of a distinct foveal avascular zone and decreased density of both the superficial and deep vascular plexuses in the macula on optical coherence tomography angiography. There was diffuse loss of choriocapillaris architecture and decreased choroidal thickness.

Conclusion: Patients with Poretti-Boltshauser syndrome may possess chorioretinal thinning and retinal vascular abnormalities appreciable on examination and multimodal imaging. These findings suggest a role for LAMA1 in retinal and choroidal vascular development.

Publication types

  • Case Reports

MeSH terms

  • Abnormalities, Multiple*
  • Apraxias / congenital
  • Child, Preschool
  • Cogan Syndrome
  • Fluorescein Angiography / methods
  • Humans
  • Macula Lutea*
  • Male
  • Multimodal Imaging
  • Retinal Vessels
  • Tomography, Optical Coherence / methods
  • Visual Acuity

Supplementary concepts

  • Apraxia, oculomotor, Cogan type