Data from 10,000 PRECISE-SG100K participants demonstrate how combining mass spectrometry and proximity extension assays expands biomarker discovery.
Initial findings from the PRECISE-SG100K study have identified more than 2,500 previously unreported associations between genetic variation and protein levels, researchers announced at the Human Proteome Organization 2026 World Congress.
The research stems from a strategic collaboration involving Precision Health Research, Singapore (PRECISE), Nanyang Technological University, Singapore, and Thermo Fisher Scientific. By integrating discovery mass spectrometry and targeted affinity-based assays with large-scale genomic and clinical data, the initiative aims to clarify disease mechanisms and identify candidate biomarkers and therapeutic targets.
Findings from the First 10,000 Samples
The presented data reflect an analysis of the first 10,000 participant samples from the PRECISE-SG100K cohort, an effort that has recruited more than 100,000 individuals across Singapore’s multi-ethnic Asian population.
Across these initial samples, researchers quantified approximately 8,800 protein groups. A subsequent genetic association analysis identified more than 4,200 proteins with significant cis-protein quantitative trait loci, indicating their circulating levels correlate with nearby genetic variants.
Of those identified, 2,762 genetic-protein associations had not been documented across 12 reference studies used for comparative benchmarking. In addition, investigators linked measured proteins to 71 health-related traits, including confirming the established relationship between the osteoporosis target SOST/sclerostin and bone mineral density.
“Our ability to connect additional protein biology insights to genetic variation and, ultimately, health-related traits gives us a new set of hypotheses to investigate as we work to understand disease biology in Singapore’s diverse Asian population and translate those insights more broadly,” says John Chambers, PhD, chief scientific officer at PRECISE and principal investigator of the SG100K study, in a release.
Combining Discovery and Targeted Proteomic Platforms
To capture a broad view of the circulating proteome, the study applied complementary proteomic workflows to the same cohort samples.
Untargeted discovery proteomics was performed using the Thermo Scientific Orbitrap Astral mass spectrometry platform paired with Seer Proteograph Product Suite sample preparation, enabling high-throughput direct protein quantification. For targeted analysis, researchers used Olink Proximity Extension Assay technology alongside other affinity-based profiling tools.
According to study leaders, deploying both platforms simultaneously helps resolve the historical operational trade-off between analytical depth and sample throughput in population-scale studies.
“Every new connection between our genes, proteins and health and disease states adds another piece to the complex puzzle of human biology,” says Karen Nelson, chief scientific officer at Thermo Fisher Scientific, in a release. “Researchers no longer have to choose between depth and scale. Combining a deep discovery mass spectrometry-based approach and targeted technologies such as Olink with genomic and health data can reveal previously unseen biology and help build a stronger foundation for discovery, new biomarkers and potential therapeutic strategies.”
Implications for Clinical Research and Biobanks
As one of Southeast Asia’s largest population health cohorts, PRECISE-SG100K is designed to evaluate how genetics, lifestyle, and environment contribute to chronic conditions such as diabetes, hypertension, and cancer, while addressing the historical underrepresentation of Asian cohorts in global genomic datasets.
The newly uncovered associations expand the repository of genetically anchored protein markers available to clinical laboratories, academic researchers, and drug developers seeking to prioritize disease pathways and validate novel diagnostic targets. Moving forward, the study will continue longitudinal follow-up of participants to track health outcomes and further refine these biological associations.
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