Four patterns of oligoclonal bands

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frodo
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Four patterns of oligoclonal bands

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

https://www.mdpi.com/2076-3425/10/6/324

Abstract

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 κIgG index and λIgG index, here presented for the first time, and compare them with the κFLC index and the λFLC 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 κIgG index, λIgG index, κFLC index, and λFLC index were calculated using specific formulas.

Results:

The concentrations of CSF κFLC, CSF λFLC, and serum κFLC and the values of κFLC index, λFLC index, and κIgG index were significantly higher in patients with multiple sclerosis compared to controls. CSF κFLC concentration and the values of κFLC index, λFLC index, and κIgG index differed in patients depending on their pattern type of oligoclonal bands.

κFLC 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 κFLC index, λFLC index, and κIgG index were significantly higher in patients with pattern type 2 in comparison to those with pattern type 4. The κFLC index and κIgG 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 κIgG index was markedly elevated in patients with pattern type 3 compared to those with pattern type 1.

In the total study group, κFLC, λFLC, κFLC index, λFLC index, κIgG index, and λIgG index correlated with each other. The κIgG index showed the highest diagnostic power (area under the curve, AUC) in the detection of multiple sclerosis. The κFLC index and κIgG index showed the highest diagnostic sensitivity, and the κIgG 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 κIgG index. More investigations in larger study groups are needed to confirm that the κIgG index can reflect the intrathecal synthesis of immunoglobulins and may improve the diagnosis of multiple sclerosis.
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