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Population-Scale Proteomics Study Identifies New Genetic-Protein Links

By LabMedica International staff writers
Posted on 06 Oct 2026

Population-scale proteomics is increasingly used to connect genetic variation, protein biology, and health-related traits in studies of complex human disease. More...

These efforts require both analytical depth and sufficient throughput to process large, diverse cohorts, which remains challenging in large-scale proteomic research. Building on this need, a new integrated proteomics approach combines complementary protein-measurement technologies to uncover previously unreported genetic-protein associations in a Singapore population health study.

In the PRECISE-SG100K study, a strategic collaboration involving Thermo Fisher Scientific, Precision Health Research, Singapore, and Nanyang Technological University, Singapore identified more than 2,500 previously unreported genetic-protein associations. Initial results, presented at the Human Proteome Organization (HUPO) World Congress, were based on analysis of the first 10,000 participant samples and combined Thermo Fisher proteomics technologies with PRECISE-SG100K genomic and health data.

The study integrates Olink Proximity Extension Assay (PEA) platforms with the Orbitrap Astral mass spectrometry system and Seer’s Proteograph Product Suite. The Orbitrap Astral platform supports deep discovery proteomics by measuring thousands of proteins directly at high throughput, while Olink PEA technology provides highly sensitive, targeted protein measurements. Together, these complementary approaches extend proteomic coverage and enable protein findings to be analyzed alongside genomic and health information.

Analysis of approximately 10,000 participant samples quantified about 8,800 protein groups. A genetic association analysis identified more than 4,200 proteins whose levels were linked to nearby genetic differences, including significant cis-protein quantitative trait loci. Among these findings, researchers identified 2,762 associations between genetic variation and protein levels that had not been reported across 12 reference studies used for comparison.

Researchers also linked proteins to 71 health-related traits, demonstrating how the integrated dataset could connect molecular findings with clinically relevant characteristics. These findings included identification and confirmation of the relationship between SOST/sclerostin, a biologically validated osteoporosis target, and bone mineral density. The integrated approach is intended to provide additional evidence for investigating disease pathways, potential biomarkers, and therapeutic targets.

The SG100K study has recruited more than 100,000 participants from Singapore’s diverse, multi-ethnic Asian population. It integrates genomic, proteomic, clinical, and other health information to provide insight into healthy states and disease biology. The study is designed to examine how genetics, environment, and lifestyle influence disease risk and treatment response, while addressing underrepresentation of diverse populations in biomedical and translational research.

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