General Information
Conflict of Interest
Request Clinical Trials
Associated Trial(s): What type of data are you looking for?: Individual Participant-Level Data, which includes Full CSR and all supporting documentationRequest Clinical Trials
Data Request Status
Status: OngoingResearch Proposal
Project Title: Biomarker discovery in lysosomal storage diseases (Mucopolysaccharidosis, Niemann-Pick type C and Gaucher Disease)
Scientific Abstract:
Background: This Critical Path for Lysosomal Diseases (CPLD) initiative is aimed at developing solutions to solve unmet needs in Lysosomal Storage Diseases (LSD) and develop solutions to facilitate drug development for LSD patients. A major challenge in treating these diseases is the lack of a single test or "biomarker" that can predict how the disease will progress or how well treatments are working. This is partly due to the wide variety of symptoms that LSDs can cause, making it hard to find one test that works for all types.
Objective: The goal of this research is to better understand the brain changes in LSDs and identify reliable biomarkers that could help clinicians track the disease and treatments efficacy, with a primary focus in Niemann Pick Type C (NPC) and Mucopolysaccharidosis.
Study Design: (1) stratify patients based on genetic mutations, to assess their impact on disease severity and treatment response; (2) analyze longitudinal clinical outcomes (e.g., cognitive function, mobility, pulmonary and cardiac function) in relation to genotype and relationship to CNS involvement; and (3) evaluate biochemical biomarkers linked to CNS pathophysiology.
Participants: All individuals with NPC (requested Yoda dataset) and MPS (joint request on Vivli).
Primary Outcome Measure: biomarkers for NPC, MPS and other LSD and evaluation of relationship to disease progression. Exploration of genotype-phenotype relationships.
Secondary outcomes: clinical endpoints.
Statistical tests, including ANOVA, Kruskal-Wallis, Pearson/Spearman correlations.
Brief Project Background and Statement of Project Significance:
This research request seeks access to completed clinical trial datasets to explore genotypic heterogeneity, genotype-phenotype relationships to promote biomarker discovery in MPS and NPC. The Critical Path Institute is a non-profit organization dedicated to the facilitation of drug development. This request is submitted by the Critical Path for Lysosomal Storage diseases (CP-LD). The CPLD pre-consortium fosters collaboration among a broad spectrum LSD stakeholders. By solidifying existing alliances and forging new ones, CPLD seeks to pinpoint obstacles in therapeutic development, fulfill unaddressed needs, and devise strategies for improved patient outcomes.
LSDs are rare genetic disorders that occur when the body is unable to break down certain substances due to missing or malfunctioning enzymes. These enzymes are crucial for breaking down molecules inside cells, particularly within structures called lysosomes. Without proper breakdown, harmful substances accumulate, leading to damage in different parts of the body. LSDs affect approximately 1 in every 5,000 to 7,500 births globally. There are over 70 types of LSDs, and while some affect mainly one organ, most impact the brain and nervous system, leading to a range of symptoms including developmental delays, motor problems, and cognitive difficulties.
Currently, treatments for LSDs do exist, but they vary greatly between different types of the disease. The effectiveness of treatments can depend on how advanced the disease is when treatment begins, and in some cases, available options may not be very effective. A major challenge in treating these diseases is the lack of a single test or "biomarker" that can predict how the disease will progress or how well treatments are working. This is partly due to the wide variety of symptoms that LSDs can cause, making it hard to find one test that works for all types.
However, research is showing promise in identifying markers that could help track the disease's progression, especially in the brain. For example, brain imaging may help doctors see changes in the brain that are linked to disease severity. Changes in brain size, structure, and patterns seen in brain scans could provide important clues. Additionally, measuring specific proteins in the blood, such as neurofilament light chain (NfL), is another approach being studied. These proteins could serve as an easier way to monitor disease progression over time, especially since taking brain scans repeatedly can be difficult due to the complexity of the disease symptoms.
The goal of this research is to better understand the brain changes in LSDs and identify reliable biomarkers that could help clinicians track the disease and see how well treatments are working. This research could ultimately improve the development of new therapies and tools for managing LSDs. By combining brain imaging with blood tests, this study aims to develop more effective ways to follow patients over time and to address the many challenges in treating these diseases. Finding these biomarkers could also help in the development of new treatments, providing hope for patients and families affected by LSDs.
Specific Aims of the Project:
(1) stratify patients based on genetic mutations, to assess their impact on disease severity and treatment response; (2) analyze longitudinal clinical outcomes (e.g., cognitive function, mobility, pulmonary and cardiac function) in relation to genotype and relationship to CNS involvement; and (3) evaluate biochemical biomarkers linked to CNS pathophysiology.
Study Design: Meta-analysis (analysis of multiple trials together)
What is the purpose of the analysis being proposed? Please select all that apply.: New research question to examine treatment effectiveness on secondary endpoints and/or within subgroup populations Participant-level data meta-analysis Meta-analysis using data from the YODA Project and other data sources Research on clinical trial methods Research on comparison group Research on clinical prediction or risk prediction
Software Used: Python, R, RStudio
Data Source and Inclusion/Exclusion Criteria to be used to define the patient sample for your study:
AC-056C501 (YODA)
Vivli data request: NCT00069641, TKT018, TKT008, NCT01155778, NCT02060526, NCT02350816, NCT00630747, NCT01509768, NCT01299727, NCT01047306
All patients will be included, no exclusion criteria at this stage, but the analytical work may discover the need to filter out patients based on data missingness.
Primary and Secondary Outcome Measure(s) and how they will be categorized/defined for your study:
Biomarkers investigations in LSD, including NPC, MPS and other lysosomal storage including evaluation of their utility to track disease progression. Exploration of genotype-phenotype relationships, in the context of disease severity
Primary outcomes measures: clinical scales, cognitive and motor function measures; fluid biomarkers including NfL, oxysterol levels, other available biomarker data. and imaging data.
Secondary outcome measures: seizure burden; neuropsychiatric manifestations; other disease relevant clinical endpoints in the data;.
Main Predictor/Independent Variable and how it will be categorized/defined for your study:
Fluid biomarkers (CSF, blood) and imaging biomarkers and correlation to disease progression.
Clinical endpoints and correlation to biomarkers and/or disease progression.
Genotype-phenotype relationship in context of disease severity.
Other Variables of Interest that will be used in your analysis and how they will be categorized/defined for your study: Other fluid and imaging biomarkers available in the data. Other available clinical endpoints in the data.
Statistical Analysis Plan: Descriptive statistics will be used to summarize patient demographics, genotype distributions, clinical phenotypes, and biomarker levels. Continuous variables (e.g., biomarker concentrations, enzyme activity, clinical severity scores) will be presented as mean +/- standard deviation (or median and interquartile range for non-normally distributed data), while categorical variables (e.g., mutation types, treatment responses) will be expressed as frequencies and percentages. Normality of continuous variables will be assessed using the Shapiro-Wilk test, and appropriate transformations will be applied if needed. To evaluate genotype-phenotype correlations, one-way ANOVA (or Kruskal-Wallis test for non-parametric data) will be used to compare clinical severity scores and biomarker levels across different mutation categories. Post-hoc pairwise comparisons will be conducted using Tukey's test (or Dunn's test for non-parametric data). Pearson or Spearman correlation coefficients will be calculated to assess relationships between IDS mutation types and biomarker concentrations. A multivariate linear regression model will be constructed to determine the independent effect of genotype on clinical severity, adjusting for potential confounders such as age, baseline enzyme activity, and treatment status. We will perform sensitivity analyzes to determine how to handle missing data, with data exclusion as preferred method. If the amount of missing data is too large, we may consider imputations methods.
Narrative Summary:
This Critical Path for Lysosomal Diseases initiative is aimed at developing solutions to solve unmet needs in Lysosomal Storage Diseases (LSD). This research request seeks access to completed clinical trial datasets to explore genotypic heterogeneity, genotype-phenotype relationships to promote biomarker discovery in LSD with a primary focus in Niemann Pick Type C (NPC) and Mucopolysaccharidosis (MPS). Specifically, we aim to: (1) stratify patients based on genetic mutations, to assess genetic impact on disease severity and treatment response; (2) analyze longitudinal clinical outcomes (e.g., cognitive function) in relation to genotype; and (3) evaluate biomarkers to determine their predictive value in monitoring disease progression and response to investigational treatments.
Project Timeline:
Start date: 3 months for data receipt to allow datasets curation
Analysis completion date: 12 months for data receipt but may require DUA extension
Publication: 24 months after receipt, if significant results are generated
NB: the analysis being performed on datasets outside of the YODA request, timelines may be extended depending on data receipt from external sources
Dissemination Plan: We plan to submit our research findings to journals targeted at rare disease scientific community, particularly the lysosomal diseases community such as Orphanet's Journal of Rare Diseases.
Bibliography:
N/A