Investigating Disease Heritability Through Electronic Medical Records

Understanding Disease Heritability

Recent research has focused on the potential of electronic medical records (EMRs) to assess disease heritability. Heritability refers to the extent to which genetics influence the development of diseases or conditions, which can significantly impact their prevention and treatment. Traditional methods of estimating heritability involve collecting genetic data alongside a patient’s medical characteristics and family history. However, these methods can be labor-intensive and may require input from multiple family members, often capturing only a limited range of factors that contribute to disease development.

The Role of Electronic Medical Records

EMRs, which are extensively utilized in the healthcare sector, encompass a vast array of patient data that can help infer familial connections across large populations. If EMRs prove to be reliable, they could offer a cost-effective alternative to traditional genetic studies for estimating disease heritability.

Study Overview

A recent study published in *Cell* delved into the feasibility of using EMRs to estimate heritability for various conditions. Researchers sourced electronic medical records from three medical centers in the United States. They established patient relationships by analyzing birth records, emergency contact information, and next-of-kin data, using an algorithm for sorting. Heritability was estimated based on the strength of the association between specific conditions and their prevalence among related individuals, focusing on conditions with at least 1,000 cases.

Methodology and Findings

The researchers grouped conditions into pairs according to their classifications, such as categorizing anemias into sickle cell anemia and other types. They considered relationships up to the fourth degree, including great-nieces and great-great-grandparents. The results were compared with findings from genetic studies on the same conditions where applicable.

In total, the analysis covered over 3.5 million patients, revealing more than 5.8 million unique familial relationships. Strong associations were found for conditions such as sickle cell disease, anxiety and depression, and open-angle glaucoma among family members. Conversely, heritability was lower for other anemias, speech disorders, and middle-ear inflammation.

Comparative Analysis with Genetic Studies

The heritability estimates derived from this study closely matched those obtained from genetic studies, particularly for common conditions. However, there are limitations to this approach. The algorithm struggled to differentiate between half-siblings and full siblings, as well as adopted and biological family members. Additionally, since the data analyzed was not genetic, not all associations can be confidently interpreted as measures of heritability. For instance, while injuries from vehicle collisions showed strong familial associations, they likely lack a significant genetic component.

Future Implications

Future research may find this EMR-based approach beneficial in identifying risk factors associated with the heritability of specific conditions, potentially addressing some limitations of genetic studies. By refining this methodology, researchers could develop a more affordable alternative to traditional genetic studies on heritability.

Author and Reference

Written by Raishard Haynes, MBS
Reference: Polubriaginof, F.C.G. et al. (2018). Disease Heritability Inferred from Familial Relationships Reported in Medical Records. *Cell*. DOI: https://doi.org/10.1016/j.cell.2018.04.032