XClose

UCL Great Ormond Street Institute of Child Health

Home

Great Ormond Street Institute of Child Health

Menu

Neurodevelopment, communication and wellbeing outcomes for children treated with novel therapies

Project title 
Neurodevelopment, communication and wellbeing outcomes for children treated with novel therapies for Spinal Muscular Atrophy

Supervisors names
Michelle de Haan
Catalina Suarez

Background and Objectives/Aims
Spinal muscular atrophy is a genetic neuromuscular condition that creates life-impacting, major motor difficulties (e.g., difficulties swallowing, breathing, playing) that affect life expectancy and quality of life. Spinal muscular atrophy type 1 (SMA1) appears within the first 6 months; it is the most common and  severe form wherein children do not achieve motor milestones such as sitting or walking. Historically, children with  this type of SMA do not survive beyond their second  birthdays. Fortunately, today, children are potentially able to live longer and have improved motor outcomes due to the development of novel disease-modifying and gene replacement therapies. However, the longer term neurodevelopmental, communication, and wellbeing outcomes of children with SMA1 who have been treated with these novel therapies are still largely unknown. Here, we aim to deep phenotype treated SMA1 children. Our investigations will cover specific neuropsychological domains, including speech/language, social communication and interaction, spontaneous play, memory,  and executive functions as well as neurophysiological measures of cognitive ability that are relatively independent of motor or speech difficulties.  We will compare children who received different forms of treatment, and will consider the role of different variables, including disease severity, age at diagnosis and treatment initiation, disease duration before treatment, number of SMN2 gene copies, and socio-cultural-environmental factors.
 

Methods:
Participants will be children diagnosed with SMA1 recruited through Great Ormond Street Hospital, and healthy peers and children with other neurodevelopmental disorders as potential comparison groups.

Measures will include a variety of standard neuropsychological measures and questionnaires, direct behavioural observations using standardised approaches, and  electroencephalography (EEG) in passive novelty-detection tasks.

Project outcomes
We aim to develop a gold standard protocol for developmental follow up which can be used to predict outcomes and evaluate treatments.  The student will receive the chance to acquire a diverse set of skills in neuropsychological assessment, EEG acquisition and analysis, and applying these in children of a wide age range and ability levels.

RELATION TO MENTAL HEALTH: The project fits the broad definition of inclusive ‘genetics with detailed clinical phenotypic assessments’ and includes a consideration mental wellbeing.

Timeline:

  • Fall 2024:  Training-assessments & library skills; literature review 
  • Jan 2025:  Start of Data collection; start of systematic review on the topic.
  • Jan 2026: Submit systematic review for publication
  • March 2026: Complete MPhil/PhD upgrade
  • Jan 2027:  Complete data collection and finalise analysis plan; 
  • Feb-August 2027: data analysis; write up of thesis; identify examiners.
  • Fall 2027 Submit completed thesis 

References:
1. Katus, L., Mason, L…..de Haan, M. and the BRIGHT team (2020). ERP markers are associated with neurodevelopmental outcomes in 1-5 month old infants in rural Africa and the UK. Neuroimage, 210:116591. doi: 10.1016/j.neuroimage.2020.116591. 
2.Masson, R, Brusa, C., Scoto, M., Baranello, G. (2021) Brain, cognition, and language development in spinal muscular atrophy type 1: a scoping review. Dev Med Child Neurol ;63(5):527-536. doi: 10.1111/dmcn.14798. 
3.Servas, L., Baranello, G., et al. (2021). Therapeutic interventions for spinal muscular atrophy: preclinical and early clinical development opportunities Expert Opin Investig Drug30(5):519-527. doi: 10.1080/13543784.2021.1904889. 
 

Contact
Michelle de Haan m.de-haan@ucl.ac.uk