Publication highlights April 2025

This month’s highlighted articles cover a broad range of topics showcasing the scalability and wide applicability of Olink PEA technology to drive impactful biomedical  advances through protein biomarker research.

Rare non-coding gene variants that regulate protein expression

Scientists from Exeter University used whole genome sequencing and proteomic data generated using Olink® Explore 3072 in the UK Biobank Pharma Proteomics Project to explore the role of rare gene variants located outside of protein coding regions on the levels of almost 3,000 proteins in plasma. This study expands on earlier analysis of this dataset that was based on exome-wide sequencing data.

They examined 1.1 billion variants and 123 million noncoding aggregate-based tests, identifying 604 independent rare noncoding single-variant associations identified with circulating protein levels. Of 357 rare noncoding regions found by aggregate testing, 21% were not detectable by single-variant testing alone, showing the importance of this approach. In contrast to some previous suggestions, they also found little evidence of epitope effects impacting the noncoding pQTL associations.

Dynamic protein changes predict rapid development of kidney failure

Researchers from Harvard Medical School used multiple Olink® Target 96 panels to measure changes in circulating protein levels (“deltas”) in diabetes patients sampled at baseline and 3-4 years later. The subjects were followed up for 10 years to compare both deltas and baseline protein levels in association with rapid development of kidney failure (rapid KF).

21 proteins associated with rapid KF at baseline only (disease initiation markers), 15 showed good associations for the deltas only (predictors of disease progression), and 25 were classified as both initiation and progression markers. Multivariate logistic regression analysis showed that addition of just two proteins (TNF-R3 & TNF-R7) to key clinical measurements substantially improved the predictive performance for rapid KF.

Comparison of these results with a previous analysis of the same samples with an aptamer-based technology showed that for the majority of overlapping proteins associated with rapid KF, the associations identified using Olink data had superior prognostic accuracy.

Biomarkers for Brain-Derived Extracellular Vesicles in CSF

While antibodies against transmembrane proteins (TMPs) are used to enrich extracellular vesicles (EVs) derived from specific cell types in liquid biopsy studies, recent evidence suggests that not all TMPs detected in biofluids are associated with EVs. A team from the Wyss Institute at Harvard looked for protein biomarkers for brain cell-derived EVs in human cerebrospinal fluid (CSF) using Olink® Explore HT, which enables the simultaneous measurement of over 5,400 markers, many of which are classed as intracellular or transmembrane proteins.

Most of the cell-type specific markers identified were classed as internal or transmembrane proteins, many of which were added to the extended biomarker library in Olink Explore HT. Only 10% of the predicted transmembrane proteins showed a clear EV fractionation pattern based on their stringent criteria, sounding a cautionary note for current methodology.

The Olink data enabled construction of a searchable database of EV-associated markers including both brain cell type-specific proteins and general EV markers found across multiple cell types.

A novel risk biomarker for symptomatic hemorrhagic transformation

Symptomatic intracranial hemorrhage transformation (s-HT) is a serious complication of ischemic stroke that can have serious neurological consequences. Researchers from Capital Medical University, Beijing used the Olink® Target 96 Inflammation panel to identify differentially expressed proteins in stroke patients with s-HT compared to those with no s-HT.

Seven proteins were significantly upregulated and one downregulated in patients with s-HT and together, these explained ~63% of the variance seen in a principal component analysis. After adjustment for multiple clinical confounders, von Willebrand factor (vWF) was identified as an independent risk factor for s-HT. In a prospective follow-up using ELISA, vWF was validated as a risk marker for s-HT, with a significantly superior predictive value compared to the current clinical risk factor model.