Project 1:
A Platform for Clinical Trial Readiness for Heredity Spastic Paraplegia
Clinical trial readiness platform builds comprehensive natural history studies across the age span, defines clinical and patient-reported outcome measures, and identifies biomarkers such as neurofilament light chain to prepare for gene-based and other disease-modifying therapies.
In the SP-CERN Natural History Study, the study population will consist of patients of all ages with:
(A) a clinical and molecular diagnosis of SPG3A (ATL1), SPG4 (SPAST), or SPG5A (CYP7B1)
(B) a clinical and molecular diagnosis of SPG47 (AP4B1), SPG50 (AP4M1), SPG51 (AP4E1), SPG52 (AP4S1), SPG49 (TECPR2), SPG56 (CYP2U1), SPG83 (HPDL), & GPT2 Deficiency.
(C) a clinical diagnosis of hereditary spastic paraplegia
Project 2:
Genome Resources and Studies for SP-CERN
Genetics lies at the core of hereditary spastic paraplegia (HSP). Despite the identification of more than 80 causative genes - half of which were discovered through the efforts of SP-CERN consortium members - approximately 40% of HSP patients have yet to identify their causative gene. This gap impedes clinical studies, biomarker research, and the progression of future clinical trials. The SP-CERN - RDCRC will prioritize establishing a robust genetic foundation by systematically collecting blood, DNA, and RNA samples and generating advanced long-read genomic data as part of the core protocol.
This Project proposes an integrated set of genomics approaches to further elucidate HSP genetics and improve the quality of diagnostic efforts. Given the development of gene-targeting therapies for neurodegenerative diseases like HSP, there is a renewed urgency in uncovering the complete genetic basis of HSP.
Project 3:
Digital Surrogates for Disease Progression in Hereditary Spastic Paraplegia
Hereditary spastic paraplegias (HSPs) are a diverse group of over 80 rare neurogenetic disorders, representing the most common cause of inherited spasticity and related disabilities worldwide. All HSPs are characterized by progressive lower limb spasticity, weakness, and significant motor impairment.
Clinical Research Project 3 aims to create and validate digital biomarkers that accurately reflect disease progression in HSP, enabling more sensitive and specific outcome measures for clinical trials. Wearable activity monitors and inertial sensors as digital surrogates gather details about disease manifestations in a more individualized and finer-grained way, using sophisticated algorithms harnessing artificial intelligence and machine learning to integrate the resulting wealth of data with other kinds of clinical information. This type of deep phenotyping will provide more specificity, new types of big data, and potential connections between HSP subforms and genetic variations, in support of Project 1.