Phenotyping Down syndrome: discovery and predictive modelling with electronic medical records

Nguyen, T. Q., Kerley, C. I., Key, A. P., Maxwell-Horn, A. C., Wells, Q. S., Neul, J. L., Cutting, L. E., & Landman, B. A. (2024). Phenotyping Down syndrome: discovery and predictive modelling with electronic medical records. Journal of Intellectual Disability Research. https://doi.org/10.1111/JIR.13124

A comprehensive two-part study utilizing electronic medical records from Vanderbilt University Medical Center investigated health conditions in individuals with Down syndrome (DS), particularly those with congenital heart disease (CHD). The first part of the study examined a large cohort of DS individuals, revealing a higher prevalence of specific health issues such as heart failure, pulmonary heart disease, and hypothyroidism compared to controls and those with other intellectual and developmental disabilities. The second part focused on DS patients with CHD, identifying conditions like congestive heart failure and valvular heart disease that increased the likelihood of surgical interventions. These findings highlight the complex health profiles of individuals with DS, suggesting the need for tailored medical approaches to better manage their multiple health challenges.

Figure 1. Study 1 examined novel conditions co-occurring with Down syndrome (DS). (a) The phenome-disease association study (PheDAS)analysis identified electronic medical record (EMR) phecodes that are significantly associated with DS in our cohort. (b) The clinical novelty ofeach identified phecode was assessed by calculating itsNovelty Finding Index(NFI), a relative novelty measure that compares the reliability ofthe association to how‘well studied’the phecode is on PubMed.