Objectives Differences in DNA methylation have been associated with early life adversity, suggesting that alterations in methylation function as one pathway through which adverse early environments are biologically embedded. This study examined associations between exposure to institutional care, quantified as the percent time in institutional care at specified follow-up assessment ages, and DNA methylation status in two stress-related genes: FKBP5 and SLC6A4. Materials and Methods We analyzed data from the Bucharest Early Intervention Project, which is a prospective study in which children reared in institutional settings were randomly assigned (mean age 22 months) to either newly created foster care or care as usual (to remain in their current placement) and prospectively followed. A group of children from the same geographic area, with no history of institutionalized caregiving, were also recruited. DNA methylation status was determined in DNA extracted from buccal epithelial cells of children at age 12. Results An inverse association was identified such that more time spent in institutional care was associated with lower DNA methylation at specific CpG sites within both genes. Discussion These results suggest a lasting impact of early severe social deprivation on methylation patterns in these genes, and contribute to a growing literature linking early adversity and epigenetic variation in children.

Socioeconomic status (SES) is a fundamental contributor to health, and a key factor underlying racial disparities in disease. However, SES data are rarely included in genetic studies due in part to the difficultly of collecting these data when studies were not originally designed for that purpose. The emergence of large clinic-based biobanks linked to electronic health records (EHRs) provides research access to large patient populations with longitudinal phenotype data captured in structured fields as billing codes, procedure codes, and prescriptions. SES data however, are often not explicitly recorded in structured fields, but rather recorded in the free text of clinical notes and communications. The content and completeness of these data vary widely by practitioner. To enable gene-environment studies that consider SES as an exposure, we sought to extract SES variables from racial/ethnic minority adult patients (n=9,977) in BioVU, the Vanderbilt University Medical Center biorepository linked to de-identified EHRs. We developed several measures of SES using information available within the de-identified EHR, including broad categories of occupation, education, insurance status, and homelessness. Two hundred patients were randomly selected for manual review to develop a set of seven algorithms for extracting SES information from de-identified EHRs. The algorithms consist of 15 categories of information, with 830 unique search terms. SES data extracted from manual review of 50 randomly selected records were compared to data produced by the algorithm, resulting in positive predictive values of 80.0% (education), 85.4% (occupation), 87.5% (unemployment), 63.6% (retirement), 23.1% (uninsured), 81.8% (Medicaid), and 33.3% (homelessness), suggesting some categories of SES data are easier to extract in this EHR than others. The SES data extraction approach developed here will enable future EHR-based genetic studies to integrate SES information into statistical analyses. Ultimately, incorporation of measures of SES into genetic studies will help elucidate the impact of the social environment on disease risk and outcomes.

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Advances in CRISPR technology and the announcement of the first gene-edited babies have sparked a global dialogue about the future of heritable genome editing (HGE). There has been an international call for public input to inform a substantive debate about benefits and risks of HGE. This study investigates the views of the sickle cell disease (SCD) community. We utilized a mixed-methods approach to examine SCD stakeholders' views in the United States. We found SCD stakeholders hold a nuanced view of HGE. Assuming the technology is shown to be safe and effective, they are just as supportive of HGE as genetics professionals, but more supportive than the general public. However, they are also concerned about the potential implications of HGE, despite this support. As discourse surrounding HGE advances, it is crucial to engage disease communities and other key stakeholders whose lives could be altered by these interventions.