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Updated: Mar 27, 2026

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
Published on: April 4, 2018
Return of genome-informed risk-assessment results for common conditions to 23,840 adults and children: An eMERGE
Lucinda P Lawson1, Cynthia A Prows2, Josh Cortopassi3
1Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; Division of Allergy and Immunology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Abstract:
Incorporating genetic risk factors to assess health risk and inform screening is critical for advancing precision medicine. The Electronic Medical Records and Genomics (eMERGE) Network conducted a large-scale study returning genome-informed risk assessments (GIRAs) to 23,840 participants (ages 3-75) across ten clinical sites. Risk for 11 common conditions was assessed using polygenic risk scores (PRSs), monogenic variants, and family history, with results placed in the electronic health record and returned to participants. Non-high-risk and family history-only high-risk results were delivered via patient portal, secure email, or mail. High-risk results involving PRSs, monogenic variants, or BOADICEAs (integrated breast cancer risk scores) were attempted to be returned one-on-one (1:1) via phone, video, or in person. Here, we evaluate the frequency and drivers of high-risk GIRAs, the feasibility of completing 1:1 returns, and factors associated with completing 1:1 delivery. Nearly 35% of participants (8,305) received high-risk results, most (76%) for a single condition. The most common triggers were family history and high PRS. Of those with high-risk GIRAs, 4,911 qualified for 1:1 return, with return completion rates equaling 78.5% for adults and 67.5% for children. The primary barrier to completing a 1:1 return session was the inability to contact participants. Among variables potentially impacting return success, homeownership, "good health," highest education level, and lack of health insurance all were significantly associated with successful 1:1 return with large effect sizes. This study demonstrates the feasibility of large-scale GIRA return in diverse clinical settings and highlights barriers that may impact equitable delivery of high-risk results.
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