Nature Communications (Nov 2023)

Molecular EPISTOP, a comprehensive multi-omic analysis of blood from Tuberous Sclerosis Complex infants age birth to two years

  • Franz Huschner,
  • Jagoda Głowacka-Walas,
  • James D. Mills,
  • Katarzyna Klonowska,
  • Kathryn Lasseter,
  • John M. Asara,
  • Romina Moavero,
  • Christoph Hertzberg,
  • Bernhard Weschke,
  • Kate Riney,
  • Martha Feucht,
  • Theresa Scholl,
  • Pavel Krsek,
  • Rima Nabbout,
  • Anna C. Jansen,
  • Bořivoj Petrák,
  • Jackelien van Scheppingen,
  • Josef Zamecnik,
  • Anand Iyer,
  • Jasper J. Anink,
  • Angelika Mühlebner,
  • Caroline Mijnsbergen,
  • Lieven Lagae,
  • Paolo Curatolo,
  • Julita Borkowska,
  • Krzysztof Sadowski,
  • Dorota Domańska-Pakieła,
  • Magdalena Blazejczyk,
  • Floor E. Jansen,
  • Stef Janson,
  • Malgorzata Urbanska,
  • Aleksandra Tempes,
  • Bart Janssen,
  • Kamil Sijko,
  • Konrad Wojdan,
  • Sergiusz Jozwiak,
  • Katarzyna Kotulska,
  • Karola Lehmann,
  • Eleonora Aronica,
  • Jacek Jaworski,
  • David J. Kwiatkowski

DOI
https://doi.org/10.1038/s41467-023-42855-6
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 15

Abstract

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Abstract We present a comprehensive multi-omic analysis of the EPISTOP prospective clinical trial of early intervention with vigabatrin for pre-symptomatic epilepsy treatment in Tuberous Sclerosis Complex (TSC), in which 93 infants with TSC were followed from birth to age 2 years, seeking biomarkers of epilepsy development. Vigabatrin had profound effects on many metabolites, increasing serum deoxycytidine monophosphate (dCMP) levels 52-fold. Most serum proteins and metabolites, and blood RNA species showed significant change with age. Thirty-nine proteins, metabolites, and genes showed significant differences between age-matched control and TSC infants. Six also showed a progressive difference in expression between control, TSC without epilepsy, and TSC with epilepsy groups. A multivariate approach using enrollment samples identified multiple 3-variable predictors of epilepsy, with the best having a positive predictive value of 0.987. This rich dataset will enable further discovery and analysis of developmental effects, and associations with seizure development in TSC.