Phelan-McDermid syndrome data network: Integrating patient reported outcomes with clinical notes and curated genetic...

Area of Science:

• Neuroscience
• Genetics
• Bioinformatics

Background:

• Heterogeneous patient data hinders neuropsychiatric disorder research, especially for rare conditions like Phelan-McDermid Syndrome (PMS).
• Paucity of clinical data for rare disorders like PMS complicates understanding disease origins and progression.
• Phelan-McDermid Syndrome is a rare genetic disorder associated with autism and intellectual disability.

Purpose of the Study:

• To describe the Phelan-McDermid Syndrome Data Network (PMS_DN), a platform designed to facilitate research into PMS.
• To integrate heterogeneous patient phenotype data (PROs, clinical notes) with genetic information for PMS research.
• To provide authorized investigators with access to integrated PMS data and statistical tools for phenotype-genotype correlation and progression studies.

Main Methods:

• Integrating patient-reported outcomes (PRO) and clinical notes with curated genetic data.
• Developing a web portal (https://pmsdn.hms.harvard.edu) for authorized investigator access.
• Utilizing distributed research networks like PCORnet PopMedNet for aggregate data sharing.

Main Results:

• As of October 31, 2016, PMS_DN integrated data from 112 patients' clinical notes, 176 patients' genetic reports, and 415 patients' PRO data.
• The platform facilitates research into phenotype-genotype correlation and disease progression in PMS.
• PMS_DN is hosted on a scalable cloud environment, adhering to privacy regulations.

Conclusions:

• The PMS_DN platform effectively integrates diverse patient data to overcome research challenges in rare disorders like PMS.
• The initiative empowers patients and families in data management and research direction.
• PMS_DN fosters collaborative research by providing access to integrated data and promoting data sharing through networks.