Sensitivity Limits for in vivo ELISA Measurements of Molecular Biomarker Concentrations

Distinguishing Nanoparticle Aggregation from Viscosity Changes in MPS/MSB Detection of Biomarkers

Magnetic particle spectroscopy (MPS) in the Brownian relaxation regime, also termed magnetic spectroscopy of Brownian motion (MSB), can detect and quantitate very low, sub-nanomolar concentrations of molecular biomarkers. MPS/MSB uses the harmonics of the magnetization induced by a small, low-frequency oscillating magnetic field to provide quantitative information about the magnetic nanoparticles' (mNPs') microenvironment. A key application uses antibody-coated mNPs to produce biomarker-mediated aggregation that can be detected using MPS/MSB. However, relaxation changes can also be caused by viscosity changes. To address this challenge, we propose a metric that can distinguish between aggregation and viscosity. Viscosity changes scale the MPS/MSB harmonic ratios with a constant multiplier across all applied field frequencies. The change in viscosity is exactly equal to the multiplier with generality, avoiding the need to understand the signal explicitly. This simple scaling relationship is violated when particles aggregate. Instead, a separate multiplier must be used for each frequency. The standard deviation of the multipliers over frequency defines a metric isolating viscosity (zero standard deviation) from aggregation (non-zero standard deviation). It increases monotonically with biomarker concentration. We modeled aggregation and simulated the MPS/MSB signal changes resulting from aggregation and viscosity changes. MPS/MSB signal changes were also measured experimentally using 100 nm iron-oxide mNPs in solutions with different viscosities (modulated by glycerol concentration) and with different levels of aggregation (modulated by concanavalin A linker concentrations). Experimental and simulation results confirmed that viscosity changes produced small changes in the standard deviation and aggregation produced larger values of standard deviation. This work overcomes a key barrier to using MPS/MSB to detect biomarkers in vivo with variable tissue viscosity.

One-Sided Multidimensional Statistical Significance Testing: A New Method of Calculating the Statistical Significance of Spectra Used to Demonstrate Magnetic Nanoparticle Sensitivity

Estimating statistical significance of the difference between two spectra or series is a fundamental statistical problem. Multivariate significance tests exist but the limitations preclude their use in many common cases; e.g., one-sided testing, unequal variance and when few repetitions are acquired all of which are required in magnetic spectroscopy of nanoparticle Brownian motion (MSB). We introduce a test, termed the T-S test, that is powerful and exact (exact type I error). It is flexible enough to be one- or two-sided and the one-sided version can specify arbitrary regions where each spectrum should be larger. The T-S test takes the-one or two-sided p-value at each frequency and combines them using Stouffer's method. We evaluated it using simulated spectra and measured MSB spectra. For the single-sided version, mean of the spectrum, A-T, was used as a reference; the T-S test is as powerful when the variance at each frequency is uniform and outperforms when the noise power is not uniform. For the two-sided version, the Hotelling T2 two-sided multivariate test was used as a reference; the two-sided T-S test is only slightly less powerful for large numbers of repetitions and outperforms rather dramatically for small numbers of repetitions. The T-S test was used to estimate the sensitivity of our current MSB spectrometer showing 1 nanogram sensitivity. Using eight repetitions the T-S test allowed 15 pM concentrations of mouse IL-6 to be identified while the mean of the spectra only identified 76 pM.

Measuring protein biomarker concentrations using antibody tagged magnetic nanoparticles

Under physiological conditions biomarker concentrations tend to rise and fall over time e.g. for inflammation. Ex vivo measurements provide a snapshot in time of biomarker concentrations, which is useful, but limited. Approaching real time monitoring of biomarker concentration(s) using a wearable, implantable or injectable in vivo sensor is therefore an appealing target. As an early step towards developing an in vivo biomarker sensor, antibody (AB) tagged magnetic nanoparticles (NPs) are used here to demonstrate the in vitro measurement of ~5 distinct biomarkers with high specificity and sensitivity. In previous work, aptamers were used to target a given biomarker in vitro and generate magnetic clusters that exhibit a characteristic rotational signature quite different from free NPs. Here the method is expanded to detect a much wider range of biomarkers using polyclonal ABs attached to the surface of the NPs. Commercial ABs exist for a wide range of targets allowing accurate and specific concentration measurements for most significant biomarkers. We show sufficient detection sensitivity, using an in-house spectrometer to measure the rotational signatures of the NPs, to assess physiological concentrations of hormones, cytokines and other signaling molecules. Detection limits for biomarkers drawn mainly from pain and inflammation targets were: 10 pM for mouse Granzyme B (mGZM-B), 40 pM for mouse interferon-gamma (mIFN-γ), 7 pM for mouse interleukin-6 (mIL-6), 40 pM for rat interleukin-6 (rIL-6), 40 pM for mouse vascular endothelial growth factor (mVEGF) and 250 pM for rat calcitonin gene related peptide (rCGRP). Much lower detection limits are certainly possible using improved spectrometers and nanoparticles.