12hr collection period
COLLECTION: Dried plasma spots utilized for self administered sample collections.
LCMS: HPLC-QTOF utilizing a 30 minute gradient, alternating ms1 and ms2 DDA
REDUCTION: Features from ms1 data extracted with LC, MZ and Z determined. Peptides identified by OMSSA and current UniProt all organism database with known natural variants included.
ANALYSIS: Implemented CPTAC suggested quality metrics. Features from ms1 aggregated, normalized and associated to peptide IDs. Proteins realized according to published methods.
3500 ms1 features
561 ms2 peptides
281 possible proteins
6 orders dynamic range
Consumer-level personalized health monitoring is rapidly advancing as technology and public interest in this area continues to grow. To date, most consumer-level health monitoring is limited to either well regulated easy-to-measure metrics such as heart rate and blood pressure, or overly complex sources, such genomic data which has been made more accessible through direct-to-consumer companies that are pressured by regulators to limit the analytical conclusions. While regulation has limited the average consumer's access to personal analytics, it has not stopped the hobby enthusiast or scientific researcher. However, few options exist for the collection of personal proteomic data. Here, we demonstrate the feasibility for individuals to measure their own proteome, utilizing existing sample collection methods, contract research laboratories, and open source software.
While admittedly the utility of this approach is limited at this time, this proof-of-concept study demonstrates that personal proteomic data can be collected by individuals without the need for extensive infrastructure, resources or cost. It is our estimate that the one-off hobby enthusiast could obtain rich plasma proteomic data for less than 0 per sample. Furthermore, establishment of a high throughput service could bring down those costs significantly, possibly driving the cost to well below $100 per sample.