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Funded Studies

Technology for Clinicogenetic Studies of LRRK2 G2019S in Tunisia

Objective/Rationale:
We seek to create and enhance a secure database, accessible by collaborators with customizable, user-friendly, web-based entry for clinical, genetic and pedigree information. This system will also support a native “Global Statistical Test” capability.
Additionally, it will include all the security, workflow and audit features one would expect from a professional clinical database or datamart.

Project Description: 
The informatics system (IS) incorporates all of the ‘clinical research forms’ (CRF) originally proposed, as well as questionnaires added in response to the initial MJFF cohort meeting (June 2009). This includes the environmental questions (Geoparkinson questionnaire, the PD-RFQ (on pesticides at work, in non-work settings, smoking and tobacco, and caffeine)), autonomic assessments (SCOPA-AUT), activities of daily living (Schwab and England), and cognitive tests (MOCA, FAB). In addition, the database includes forms for the olfactory supplement (October 2009). The database is currently being populated with CRF data from more than 450 individuals.

Relevance to Diagnosis/Treatment of Parkinson’s Disease:  
Our long-term objective is to create a ‘global statistical test’ (GST) of phenoconversion, i.e., to prospectively predict when LRRK2 G2019S carriers will experience motor impairment significant enough to allow a neurological diagnosis of Parkinson’s disease (Clarke et al., 2004; Hueng et al., 2007). GST development requires that appropriate variables are selected and weighted in the analysis. A priori, this requires that variable responses are informative, and that the data is sufficiently powered in filtered subsets, e.g., by genotype, by familial versus sporadic disease etc. Selection of the most informative variables would be simplified if basic descriptive statistics were automated in the database (‘real time’ statistics).

Anticipated Outcome:
This tool should greatly enhance the LRRK2 Tunisia cohort research currently being undertaken by Dr. Farrer and his research team. This tool goes beyond being a mere CRF repository and becomes a powerful tool for data analysis including, but not limited to, genotype data, cohort “pedigrees and real time statistics. It is hope that this will allow more focused use of Clinical Research Forms and associated tests. Moreover, the tools can be broadly adapted to other cohort studies on PD.  Lastly, it is hoped that it can be of real assistance over time if or LRRK2 research moves forward to clinical solutions.
 


Researchers

  • Sandy Fliderman, BA

    Farmingdale, NY United States


  • Matthew Farrer, PhD

    Gainesville, FL United States


  • Michael Edward Moore, MA

    Farmingdale, NY United States


  • Maurice Freedman, BA

    New York, NY United States


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