Abstract

Introduction: High-throughput proteomics with novel affinity reagents for detection of specific proteins is used increasingly in cardiovascular cohort studies and clinical trials. Hypothesis: A detailed comparison of aptamer- vs antibody-based platforms and their associations with cardiometabolic traits (e.g. cholesterol, HbA1c, BMI, blood pressure, atherosclerotic risk) will highlight critical platform differences. Methods: We first compare SomaScan ® 1.3K (“Soma1.3K”, N=1301 reagents) and Olink ® Explore (“Olink”, N=1472 reagents) platforms in 568 adults from the Jackson Heart Study. We also compare Olink to the expanded SomaScan ® 5K (“Soma5K”, N=4979 reagents) in 209 participants from the HERITAGE study. Results: When comparing reagents from each platform that target the same protein, 234/616 such matched reagents are highly correlated, implying accuracy. We alternatively assess accuracy by leveraging whole genome sequencing data: Olink reagents associate with variants near the coding gene ( cis protein quantitative trait loci) for a greater proportion of their protein targets — 40% versus 28% for Soma1.3K (Figure). Principal components analysis reveals 95% of total variance is explained using fewer components on Olink, suggesting Soma1.3K covers more axes of variation. Finally, Olink demonstrates more protein associations (false discovery rate < 5%) with cardiometabolic phenotypes. When limited to matched reagents, Olink identifies more cardiometabolic associations, particularly when measurements are poorly correlated with Soma1.3K. However, on the expanded Soma5K, we identify significantly more proteins associated with cardiometabolic traits. Notably, Olink still finds more associations among poorly correlated, matched reagents. Conclusions: Our data show that antibody-based proteomics may provide greater accuracy and phenotypic associations while aptamers have higher precision and breadth of protein coverage.

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