This repository contains all SQL, R, and Python code used to generate the analyses, tables, and figures for the manuscript “Understanding Comorbidities in Hypermobile Ehlers-Danlos Syndrome: Could a Viral Infection Unmask the Disorder?”, submitted to PLOS Digital Health. All analyses were conducted within the National COVID Cohort Collaborative (N3C) Enclave using de-identified electronic health record data mapped to the OMOP Common Data Model. Due to N3C governance restrictions, raw patient-level data are not included and cannot be exported. The repository is organized into numbered analysis nodes reflecting the execution order used in the N3C Workbench. Nodes alternate between Spark SQL, R, and Python and produce intermediate Spark DataFrames consumed by downstream analyses. Exact cohort definitions, feature extraction logic, and statistical analyses are fully specified in code. This release corresponds to the version of the code used for the submitted manuscript and is intended to support full computational reproducibility by researchers with approved N3C access.