In a recent Journal of Participatory Medicine paper, DIYgenomics founder Melanie Swan and her colleagues propose "citizen science genomics as a model for crowdsourced preventive medicine research." By combining personal genomic data with clinical biomarker data, Swan et al. aim to quantify the "impact[s] of various interventions on a predefined endpoint," using a "genome-phenotype-outcome methodology." Access to the large consumer datasets generated by genetic testing companies, the authors say, equips researchers with a wealth of information for future large-scale preventative medicine studies. "The combination of multiple health data streams, the anticipated data deluge, and the challenges and expense of recruiting subjects for studies all suggest that there could be a benefit to supplementing traditional randomized clinical trials with other techniques," the authors write. The team demonstrates the applicability of its approach to determine whether "simple interventions may be effective in reducing homocysteine in individuals with high baseline levels, particularly in the presence of a polymorphism in the MTHFR variant rs1801133." In its paper, the group also addresses issues related to ethical reviews and informed consent, as well as how to enroll citizen participants.