Kappa Free Light Chains and IgG Combined in a Novel Algorithm for the Detection of Multiple Sclerosis

Background: It is well known that the cerebrospinal fluid (CSF) concentrations of free light chains (FLC) and immunoglobulin G (IgG) are elevated in multiple sclerosis patients (MS). Therefore, in this study we aimed to develop a model based on the concentrations of free light chains and IgG to predict multiple sclerosis. We tried to evaluate the diagnostic usefulness of the novel kappa IgG index and lambda IgG index, here presented for the first time, and compare them with the kappa FLC index and the lambda FLC index in multiple sclerosis patients. Methods: CSF and serum samples were obtained from 76 subjects who underwent lumbar puncture for diagnostic purposes and, as a result, were divided into two groups: patients with multiple sclerosis (n= 34) and patients with other neurological disorders (control group;n= 42). The samples were analyzed using turbidimetry and isoelectric focusing. The kappa IgG index, lambda IgG index, kappa FLC index, and lambda FLC index were calculated using specific formulas. Results: The concentrations of CSF kappa FLC, CSF lambda FLC, and serum kappa FLC and the values of kappa FLC index, lambda FLC index, and kappa IgG index were significantly higher in patients with multiple sclerosis compared to controls. CSF kappa FLC concentration and the values of kappa FLC index, lambda FLC index, and kappa IgG index differed in patients depending on their pattern type of oligoclonal bands. kappa FLC concentration was significantly higher in patients with pattern type 2 and type 3 in comparison to those with pattern type 1 and type 4. The kappa FLC index, lambda FLC index, and kappa IgG index were significantly higher in patients with pattern type 2 in comparison to those with pattern type 4. The kappa FLC index and kappa IgG index were significantly higher in patients with pattern type 2 in comparison to those with pattern type 1, and in patients with pattern type 3 compared to those with pattern type 4. The kappa IgG index was markedly elevated in patients with pattern type 3 compared to those with pattern type 1. In the total study group, kappa FLC, lambda FLC, kappa FLC index, lambda FLC index, kappa IgG index, and lambda IgG index correlated with each other. The kappa IgG index showed the highest diagnostic power (area under the curve, AUC) in the detection of multiple sclerosis. The kappa FLC index and kappa IgG index showed the highest diagnostic sensitivity, and the kappa IgG index presented the highest ability to exclude multiple sclerosis. Conclusion: This study provides novel information about the diagnostic significance of four markers combined in the kappa IgG index. More investigations in larger study groups are needed to confirm that the kappa IgG index can reflect the intrathecal synthesis of immunoglobulins and may improve the diagnosis of multiple sclerosis.