Blood transcriptional profiles could serve as biomarkers of clinical changes in subjects at-risk for or diagnosed with diabetes. However, transcriptional variation over time is poorly understood due to the impracticality of frequent longitudinal phlebotomy in large patient cohorts. We have developed a novel transcriptome assessment method that could be applied to fingerstick blood samples self-collected by study volunteers. FifteenL of blood from a fingerstick yielded sufficient RNA to analyse >176 transcripts by high-throughput quantitative polymerase chain reaction (PCR). We enrolled 13 subjects with type 1 diabetes and 14 controls to perform weekly collections at home for a period of 6 months. Subjects returned an average of 24 of 26 total weekly samples, and transcript data were obtained successfully for >99% of samples returned. A high degree of correlation between fingerstick data and data from a standard 3 mL venipuncture sample was observed. Increases in interferon-stimulated gene expression were associated with self-reported respiratory infections, indicating that real-world transcriptional changes can be detected using this assay. In summary, we show that longitudinal monitoring of gene expression is feasible using ultra-low-volume blood samples self-collected by study participants at home, and can be used to monitor changes in gene expression frequently over extended periods.