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IntroductionApolipoprotein C-III (apoC-III) regulates triglyceride (TG) metabolism. In plasma, apoC-III exists in non-sialylated (apoC-III0a without glycosylation and apoC-III0b with glycosylation), monosialylated (apoC-III1) or disialylated (apoC-III2) proteoforms. Our aim was to clarify the relationship between apoC-III sialylation proteoforms with fasting plasma TG concentrations.MethodsIn 204 non-diabetic adolescent participants, the relative abundance of apoC-III plasma proteoforms was measured using mass spectrometric immunoassay.ResultsCompared with the healthy weight subgroup (n = 16), the ratios of apoC-III0a, apoC-III0b, and apoC-III1 to apoC-III2 were significantly greater in overweight (n = 33) and obese participants (n = 155). These ratios were positively correlated with BMI z-scores and negatively correlated with measures of insulin sensitivity (Si). The relationship of apoC-III1 / apoC-III2 with Si persisted after adjusting for BMI (p = 0.02). Fasting TG was correlated with the ratio of apoC-III0a / apoC-III2 (r = 0.47, p<0.001), apoC-III0b / apoC-III2 (r = 0.41, p<0.001), apoC-III1 / apoC-III2 (r = 0.43, p<0.001). By examining apoC-III concentrations, the association of apoC-III proteoforms with TG was driven by apoC-III0a (r = 0.57, p<0.001), apoC-III0b (r = 0.56. p<0.001) and apoC-III1 (r = 0.67, p<0.001), but not apoC-III2 (r = 0.006, p = 0.9) concentrations, indicating that apoC-III relationship with plasma TG differed in apoC-III2 compared with the other proteoforms.ConclusionWe conclude that apoC-III0a, apoC-III0b, and apoC-III1, but not apoC- III2 appear to be under metabolic control and associate with fasting plasma TG. Measurement of apoC-III proteoforms can offer insights into the biology of TG metabolism in obesity.

Protein biomarkers are essential in assessing pathogenic processes. The impetus for finding new biomarkers has been accelerated by the arrival of the “omics” technologies. However, equally important is the re-discovery of existing biomarkers with these new approaches as novel variants can be discovered that can improve their utility. Presented here is a mass spectrometric immunoassay method for quantitative determination of beta-2-microglobulin - an established biomarker used in the diagnosis of active rheumatoid arthritis and kidney disease, and its structural variant - cleaved at and deficient in lysine-58 (ΔK58-b2m). Beta lactoglobulin was incorporated into the assay as an internal reference standard, serving as normalization point for beta-2-microglobulin quantification. The precision, linearity, and recovery characteristics of the assay were established. The new assay was also benchmarked against existing beta-2-microglobulin ELISA. The assay was utilized to determine the individual concentration of beta-2-microglobulin and its variant across a larger cohort of samples, demonstrating the ability to simultaneously quantify both proteins.

Insulin-like growth factor 1 (IGF1) is an important biomarker for the management of growth hormone disorders. Recently there has been rising interest in deploying mass spectrometric (MS) methods of detection for measuring IGF1. However, widespread clinical adoption of any MS-based IGF1 assay will require increased throughput and speed to justify the costs of analyses, and robust industrial platforms that are reproducible across laboratories. Presented here is an MS-based quantitative IGF1 assay with performance rating of >1,000 samples/day, and a capability of quantifying IGF1 point mutations and posttranslational modifications. The throughput of the IGF1 mass spectrometric immunoassay (MSIA) benefited from a simplified sample preparation step, IGF1 immunocapture in a tip format, and high-throughput MALDI-TOF MS analysis. The Limit of Detection and Limit of Quantification of the resulting assay were 1.5 μg/L and 5 μg/L, respectively, with intra- and inter-assay precision CVs of less than 10%, and good linearity and recovery characteristics. The IGF1 MSIA was benchmarked against commercially available IGF1 ELISA via Bland-Altman method comparison test, resulting in a slight positive bias of 16%. The IGF1 MSIA was employed in an optimized parallel workflow utilizing two pipetting robots and MALDI-TOF-MS instruments synced into one-hour phases of sample preparation, extraction and MSIA pipette tip elution, MS data collection, and data processing. Using this workflow, high-throughput IGF1 quantification of 1,054 human samples was achieved in approximately 9 hours. This rate of assaying is a significant improvement over existing MS-based IGF1 assays, and is on par with that of the enzyme-based immunoassays. Furthermore, a mutation was detected in ∼1% of the samples (SNP: rs17884626, creating an A→T substitution at position 67 of the IGF1), demonstrating the capability of IGF1 MSIA to detect point mutations and posttranslational modifications.

The impetus for discovery and evaluation of protein biomarkers has been accelerated by recent development of advanced technologies for rapid and broad proteome analyses. Mass spectrometry (MS)-based protein assays hold great potential for in vitro biomarker studies. Described here is the development of a multiplex Mass Spectrometric Immunoassay (MSIA) for quantification of apolipoprotein C-I (apoC-I), apolipoprotein C-II (apoC-II), apolipoprotein C-III (apoC-III) and their proteoforms. The multiplex MSIA assay was fast (~40 min) and high-throughput (96 samples at a time). The assay was applied to a small cohort of human plasma samples, revealing the existence of multiple proteoforms for each apolipoprotein C. The quantitative aspect of the assay enabled determination of the concentration for each proteoform individually. Low-abundance proteoforms, such as fucosylated apoC-III, were detected in less than 20% of the samples. The distribution of apoC-III proteoforms varied among samples with similar total apoC-III concentrations. The multiplex analysis of the three apolipoproteins C and their proteoforms using quantitative MSIA represents a significant step forward toward better understanding of their physiological roles in health and disease.