Neurofibromatosis Type 1 Big Data
Research type
Research Study
Full title
Using Big Data to Comprehensively Delineate the Neurobehavioral Phenotype of Children with Neurofibromatosis Type 1
IRAS ID
300472
Contact name
Shruti Garg
Contact email
Sponsor organisation
University of Mancheste
Duration of Study in the UK
2 years, 0 months, 0 days
Research summary
Neurofibromatosis Type 1 (NF1) is a rare disease affecting approximately 1:3500 people worldwide and is characterized by a range of tumor and non-tumor presentations, primarily neurobehavioral functioning impairments. People with NF1 exhibit greater cognitive impairments, learning disabilities, behavioral problems and socioeconomic difficulties compared with neurotypical individuals. Research around the neurobehavioral outcomes of NF1 individuals is well demonstrated however the predominant focus has been on between-group differences with individuals without NF1 and as such there are crucial gaps within the knowledge base. Gaps include how neurobehavioral functioning changes over time/with age, how cognitive impairment relates to academic, behavioral and socioemotional functioning, and an examination of subgroup differences and norms. Further barriers to knowledge production include small sample sizes and a lack of resources for analysis.
This study proposes to address the critical knowledge gaps with the use of integrative data analysis; the combination of existing, anonymised, international, neuropsychological datasets of individuals with NF1 to create a ‘Big Data’ set (n ≅ 2183, aged 2-18) which benefits from increased statistical power and reproducibility. Statistical methods will examine 1) neurobehavioral trajectories of change across age, its predictors, and how functioning varies compared to the traditional growth curve 2) relationships between cognitive, academic and socioemotional functioning and 3) NF1 subpopulations with differing profiles and predictors via a person-centred approach to differences within-group. Datasets shared by clinicians across the world using routinely-collected data will be pooled to create the first consortium of NF1 data from 13 sites across the globe. The findings will guide future research, patient management and crucially, treatment. The vast range of predictors examined will help in targeting specific treatments and support rather than a blanket approach, plus will delineate precise areas for further investigation. Moreover, the findings will help to establish norms for individuals with NF1 and their families.
REC name
East Midlands - Leicester Central Research Ethics Committee
REC reference
22/EM/0027
Date of REC Opinion
11 Feb 2022
REC opinion
Favourable Opinion