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Phenotyping polyclonal kappa and lambda light chain molecular mass distributions in patient serum using mass
David R Barnidge1, Surendra Dasari, Marina Ramirez-Alvarado
1Department of Laboratory Medicine and Pathology, ‡Biomedical Statistics and Informatics, §Department of Biochemistry and Molecular Biology, ∥Department of Immunology, and ⊥Department of Medicine, Mayo Clinic , Rochester, Minnesota 55905, United States.
Abstract:
We previously described a microLC-ESI-Q-TOF MS method for identifying monoclonal immunoglobulins in serum and then tracking them over time using their accurate molecular mass. Here we demonstrate how the same methodology can be used to identify and characterize polyclonal immunoglobulins in serum. We establish that two molecular mass distributions observed by microLC-ESI-Q-TOF MS are from polyclonal kappa and lambda light chains using a combination of theoretical molecular masses from gene sequence data and the analysis of commercially available purified polyclonal IgG kappa and IgG lambda from normal human serum. A linear regression comparison of kappa/lambda ratios for 74 serum samples (25 hypergammaglobulinemia, 24 hypogammaglobulinemia, 25 normal) determined by microflowLC-ESI-Q-TOF MS and immunonephelometry had a slope of 1.37 and a correlation coefficient of 0.639. In addition to providing kappa/lambda ratios, the same microLC-ESI-Q-TOF MS analysis can determine the molecular mass for oligoclonal light chains observed above the polyclonal background in patient samples. In 2 patients with immune disorders and hypergammaglobulinemia, we observed a skewed polyclonal molecular mass distribution which translated into biased kappa/lambda ratios. Mass spectrometry provides a rapid and simple way to combine the polyclonal kappa/lambda light chain abundance ratios with the identification of dominant monoclonal as well as oligoclonal light chain immunoglobulins. We anticipate that this approach to evaluating immunoglobulin light chains will lead to improved understanding of immune deficiencies, autoimmune diseases, and antibody responses.
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