Breaking barriers to proteomics at scale: the nELISA platform profiles hundreds of circulating proteins in high throughput and at low cost

Despite the great promises of proteomics, the low abundance of many signalling proteins in circulation, such as cytokines and metabolic mediators, renders mass spectrometry-based analysis challenging. Targeted approaches using affinity binders provide more sensitive quantification of these proteins, but have been challenging to multiplex due to cross-reactivity between reagents (rCR) when scaling content beyond ~25-plex. Recent advances using the Proximity Extension Assay have helped avoid issues with rCR, but high cost and low throughput have limited their widespread adoption for large-scale applications. The nELISA is a high-throughput, highly multiplexed immunoassay platform capable of profiling 1536 samples per instrument per day at a fraction of the cost of other platforms. This is achieved by miniaturizing the sandwich immunoassay, whereby antibody pairs are pre-packaged at the surface of color-coded microparticles that can be readout by high-throughput flow cytometry. We recently demonstrated the nELISA"s ability to profile 10,000 cell culture supernatants in 1 week to reveal immune phenotypes from PBMCs; here, we describe its use in profiling circulating proteins to identify biomarkers of disease, and compare our findings to xMAP (Luminex) and PEA (Olink) platforms.

We profiled circulating protein abundance in 44 plasma samples across 4 diseases (type 2 diabetes, colorectal cancer, COVID19, rheumatoid arthritis) and healthy controls using 3 platforms, nELISA (191-plex), PEA (92-plex), and xMAP (48-plex). For targets shared across platforms, nELISA and PEA measurements were generally well-correlated, with a median Spearman correlation of 0.71. In line with this, both platforms distinguished healthy and disease phenotypes, and identified individual protein markers with differing expression patterns between healthy and disease states. In contrast, correlations were significantly lower when comparing PEA (0.53) or nELISA (0.45) to xMAP, purportedly due to well-known cross-reactivity issues with the latter.

We then performed a follow up study on an independent set of 96 samples, which we profiled with an expanded nELISA panel (275-plex), as well as a 384-plex PEA panel (Olink Explore). Unsurprisingly, the expanded content of both platforms resulted in the identification of an additional set of biomarkers not available in the initial screen. Among proteins quantified in both sample sets, approximately 40% of biomarkers were validated using the nELISA, but fewer markers were validated by PEA: this may be due to differences in sensitivity between different PEA panels, and/or the use of different reagents in the different panels. In contrast, nELISA reagents and platform sensitivity were maintained regardless of plex level. Of note, the cost of profiling was 15X more expensive using PEA than nELISA. Thus, the nELISA provides a new, high-throughput and cost-effective means of profiling circulating proteins for large-scale studies.