Scientists Skip DNA Extraction to Score Type 1 Diabetes Risk Straight From Serum

A simple change in how blood samples are handled could make genetic testing for type 1 diabetes dramatically cheaper and easier, according to a new proof-of-principle study published in the Journal of Translational Medicine. Researchers at the University of Exeter have demonstrated that a well-established genetic risk score for type 1 diabetes can be calculated directly from serum—the straw-colored fluid left behind after blood clots—without any of the expensive and time-consuming DNA purification steps that standard genotyping protocols normally require. The finding, reported by Benjamin Spurrier, Richard Oram, Nicholas Thomas, Jonathan Locke and colleagues, could pave the way for laboratories to combine genetic and antibody testing from a single tube of blood, streamlining workflows and cutting costs in both clinical settings and large-scale research biobanks.

The type 1 diabetes genetic risk score, or T1D-GRS, is a tool that has already proven its worth in diabetes prediction and classification. It aggregates information from ten single nucleotide polymorphisms, or SNPs—individual positions in the genome where the DNA letter varies between people and where certain variants shift the probability of developing the autoimmune form of diabetes. Because the score draws on genetic variants that remain stable throughout life, it can help distinguish type 1 from type 2 diabetes in young adults and identify individuals at elevated risk long before symptoms appear. Crucially, the T1D-GRS and islet autoantibodies, the immune markers that signal the body’s attack on insulin-producing cells, act as independent predictors of diabetes, which makes pairing them particularly powerful for screening and diagnostic purposes.

The obstacle has always been practical rather than scientific. To calculate the score, laboratories traditionally need genomic DNA extracted from white blood cells, which involves purification, quantification and storage steps that add expense at every turn, before a single genotyping reaction has even been set up. The Exeter team reasoned that this entire pipeline might be unnecessary. Serum, the very material already used for islet autoantibody assays, contains extracellular DNA released from cells that burst during the clotting process. If that DNA were sufficient for genotyping, the same tube of blood could serve both the antibody test and the genetic score, eliminating the need for a separate DNA extraction altogether.

There was a catch, however, and it lay in the biochemistry of clotting. The extracellular DNA in serum comes from leukocytes that rupture as the blood clots, so the amount of genomic DNA available depends on how long the sample is allowed to clot before being spun down in a centrifuge. Many standard serum processing protocols specify clotting times of less than thirty minutes, a window that previous work suggested may be inadequate for releasing enough genomic DNA into the fluid. The researchers therefore designed their study to answer two linked questions: whether a direct-from-serum genotyping method could calculate the ten-SNP T1D-GRS accurately, and how strongly the answer depended on clotting time.

The technical setup was deliberately conventional, which is part of the method’s appeal. The team used TaqMan SNP genotyping assays, a widely adopted fluorescence-based qPCR chemistry, together with TaqPath ProAmp Master Mix, in tiny five-microliter reactions containing just one microliter of either purified DNA or raw serum. Plates, prepared on a Biomek i7 Automated Workstation and run for fifty cycles on a QuantStudio 12K Flex Real-Time PCR System, included positive and no-template controls, and genotypes were called automatically using commercial software. In other words, nothing exotic was required—only standard reagents, standard instruments and a single microliter of serum per SNP.

Accuracy came first. In a cohort of 116 matched serum and whole-blood-derived DNA samples sent to the Exeter Genomics Laboratory from across the UK and Ireland, all with clotting times exceeding 24 hours, both biospecimens achieved call rates above 95 percent across all ten SNPs on the first pass, with no repeated reactions. A complete T1D-GRS was obtained from 84.5 percent of serum samples compared with 96.6 percent of purified DNA samples, a statistically significant difference, but among the 94 samples where both approaches yielded a complete score, the results agreed perfectly—100 percent concordance. In a subset of 32 samples with sequencing data available, the serum-derived scores were again fully concordant, confirming that the shortcut does not come at the cost of correctness.

The clotting-time experiment revealed where the method’s limits lie. The team analyzed 122 serum samples with recorded clotting times ranging from 12 to 475 minutes, running every sample in duplicate on separate qPCR runs to check reproducibility. Splitting the cohort at the thirty-minute mark produced a striking contrast. Samples clotted for thirty minutes or less achieved a genotyping success rate of just 68.8 percent, a replicate discordance rate of 28.8 percent, and yielded a complete ten-SNP score in only 7.4 percent of cases. Samples clotted for longer than thirty minutes, by comparison, reached a 97 percent genotyping success rate, only 2.2 percent replicate discordance, and complete scores in 77.8 percent of samples—a difference the authors report as highly significant. Performance in this longer-clotting group closely matched that of the samples clotted for more than 24 hours.

The explanation, the researchers argue, is straightforward: insufficient clotting time leaves too little extracellular DNA in the serum for reliable amplification. This aligns with earlier findings that PCR-based genotyping from samples containing very low DNA concentrations—below roughly 56 picograms—is unreliable. The practical message for laboratories hoping to combine genetic and biochemical testing is that serum should be allowed to clot for more than thirty minutes before processing, a duration that does not compromise autoantibody assays. Where additional tests sensitive to proteolysis, glycolysis or other degradation processes are needed, the authors suggest an intermediate clotting window of more than thirty minutes but under about three hours may offer the optimal balance between DNA release and analyte preservation.

The implications extend well beyond the immediate assay. A direct-from-serum approach could unlock cost-effective genotyping in the many large frozen serum biobanks around the world where no extracted DNA exists, allowing researchers to mine decades of stored samples for genetic risk information without retrieving new blood draws. Although the study tested only ten SNPs, the low input volume of one microliter per SNP suggests the same logic could scale to larger genotyping panels or alternative genotyping chemistries. For clinical laboratories that lack DNA-extraction capability, the proof-of-principle result points toward direct, automated assays that run antibody and genetic tests in parallel from a single serum sample. The work was supported by the National Institute for Health and Care Research Exeter Biomedical Research Centre, and the authors note existing research funding and licensing arrangements with Randox Laboratories to develop a T1D-GRS assay, underscoring the translational momentum behind the approach. If the method holds up in broader validation, the humble serum tube—already the workhorse of clinical chemistry—may become a one-stop source for both immune and genetic markers of diabetes risk.

Subject of Research: A direct-from-serum genotyping method for calculating a type 1 diabetes genetic risk score

Article Title: A direct-from-serum method for calculating a type 1 diabetes genetic risk score

Article References: Spurrier, B., Oram, R. A., Thomas, N. J., & Locke, J. M. (2026). A direct-from-serum method for calculating a type 1 diabetes genetic risk score. Journal of Translational Medicine, 24(1), Article 1148. https://doi.org/10.1186/s12967-026-08930-4

Image Credits: AI Generated

DOI: 10.1186/s12967-026-08930-4

Keywords: type 1 diabetes, genetic risk score, serum, genotyping, TaqMan, qPCR, SNP, islet autoantibodies, DNA extraction, clotting time, biobanks, precision medicine