Kappa free light chain index as a diagnostic biomarker in multiple sclerosis: A real‐world investigation

Kappa free light chain (KFLC) index, a measure for intrathecal production of free kappa chains, has been increasingly recognized for its diagnostic potential in multiple sclerosis (MS) as a quantitative alternative to IgG oligoclonal bands (OCBs). Our objective was to investigate the sensitivity, specificity, and overall diagnostic accuracy of KFLC index in MS. KFLC index was prospectively determined as part of the diagnostic workup in patients with suspected MS (n = 327) between May 2013 and February 2020. Patients with clinically isolated syndrome (CIS), radiologically isolated syndrome (RIS), and MS had markedly higher KFLC index (44.6, IQR 16–128) compared with subjects with other neuro‐inflammatory disorders (ONID) and symptomatic controls (SC) (2.19, IQR 1.68–2.98, p < 0.001). KFLC index had a sensitivity of 0.93 (95% CI 0.88–0.95) and specificity of 0.87 (95% CI 0.8–0.92) to discriminate CIS/RIS/MS from ONID and SC (AUC 0.94, 95% CI 0.91–0.97, p < 0.001). KFLC index and intrathecal fraction (IF) KFLC had similar accuracies to detect MS. Treatment with disease‐modifying therapy (DMT) did not influence the level of KFLC index and it was not affected by demographic factors or associated with degenerative or inflammatory biomarkers in cerebrospinal fluid (CSF). KFLC index in MS diagnostics has methodological advantages compared to OCB and is independent to subjective interpretation. Moreover, it is an attractive diagnostic tool since the diagnostic specificity and sensitivity of KFLC index are similar with that of OCBs and KFLCIF and better than for IgG index. We show that KFLC index was influenced neither by DMT nor by demographic factors or other inflammatory or degenerative processes in MS as determined by biomarkers in CSF.


| INTRODUC TI ON
Cerebrospinal fluid (CSF) analysis is an important part of the diagnostic workup of multiple sclerosis (MS) (Arrambide & Tintore, 2016). Assessment of paired CSF and plasma/serum samples for oligoclonal immunoglobulin G (IgG) bands (OCBs) using isoelectric focusing (IEF) or agarose gel electrophoresis combined with either silver staining or western blotting is the single most wellstudied and therefore most important CSF diagnostic test in MS (Andersson et al., 1994;Freedman et al., 2005;Stangel et al., 2013).
While not specific for MS, the presence of intrathecal IgG synthesis is strongly suggestive of the diagnosis (Andersson et al., 1994). It has also been shown to have an important prognostic value in patients with radiologically isolated syndrome (RIS) and clinically isolated syndrome (CIS) to predict progression to definite MS (Kuhle et al., 2015;Tintoré et al., 2008), with intrathecal IgM production predicting both conversion and future relapses (Pfuhl et al., 2019;Sola et al., 2011). CSF assessment has gained increasing importance since presence of OCBs was reincorporated into the 2017 revision of McDonald criteria of MS (Thompson et al., 2018). In patients with a typical CIS and clinical or magnetic resonance imaging (MRI) demonstration of dissemination in space, the presence of CSFspecific OCBs may represent dissemination in time (DIT) and therefore allow a diagnosis of MS (Thompson et al., 2018). However, IEF poses several limitations. These include time-consuming manual handling and the potential for subjective interpretation (Hassan-Smith et al., 2014). Due to these limitations, there is an unmet need for additional, more objective, and quantifiable biomarkers to improve diagnostic precision, thereby facilitating early initiation of treatment.
Immunoglobulin light chains are small polypeptides that serve as subunits of antibodies. During an inflammation, mobilized Blymphocytes produce intact immunoglobulins and an excess of kappa and lambda light chains are secreted as free light chains (Presslauer et al., 2008). Determination of elevated KFLC index is a simple and quantitative method to measure the increased intrathecal immunoglobulin production that characterizes MS (Duranti et al., 2013;Kaplan et al., 2010). Different metrics have been previously utilized and compared for the determination of the intrathecal fraction (IF) of KFLC synthesis (Duell et al., 2020). Similar to previous work regarding immunoglobulin intrathecal fraction (Reiber, 1998), an alternative method was recently proposed based on a nonlinear quotient diagram with a hyperbolic reference range (Reiber et al., 2019). This nonlinear method aimed at reducing the risk of falsepositive and false-negative interpretations associated with the linear index and depending on the patients' individual albumin quotient (QAlb) value (Reiber & Peter, 2001).
The primary aim of this exploratory study was to compare the diagnostic properties of KFLC index with those of IgG OCBs and IgG index and to determine whether disease activity, disability, and therapeutic intervention influence the KFLC index, as well as to add information on whether KFLC index may complement or even replace IEF and OCB determination in clinical practice. In addition, we investigated whether KFLC index was associated with other inflammatory or degenerative biomarkers in CSF. Furthermore, we aimed to utilize the nonlinear hyperbolic reference range and compare its performance to that of KFLC index in MS diagnostics.

| Patients and controls
Patients (n = 343) who had prospectively determined KFLC in CSF and serum between May 2013 and February 2020 were retrospectively identified at the Department of Neurology, Sahlgrenska University Hospital, Gothenburg, Sweden. After exclusion of duplicates (n = 16), the study population comprised 327 patients: clinically/radiologically isolated syndrome (CIS/RIS [n = 20]), relapsing-remitting MS (RRMS, n = 161), primary progressive MS (PPMS, n = 19), secondary progressive MS (SPMS, n = 23), other neuro-inflammatory disease controls (ONID, n = 29, acute disseminated encephalomyelitis [ADEM] n = 1, acute unspecified myelitis n = 8, neurologic Lyme disease n = 5, chronic inflammatory demyelinating polyneuropathy [CIDP] n = 2, neuro-inflammatory disease not otherwise specified n = 7, myelin oligodendrocyte glycoprotein associated disorder (MOGAD) n = 3, aquaporin-4 (AQP4) associated neuromyelitis optica spectrum disease [NMOSD] n = 2, autoimmune encephalitis n = 1), and patients designated symptomatic controls (SC) who had MS-suspected symptoms but the diagnostic workup was negative (n = 75) (Thompson et al., 2018). All controls were pooled into one group (n = 104) and patients with CIS/RIS and MS formed the MS study group (n = 223). All patients with MS fulfilled the 2017 McDonald criteria (Thompson et al., 2018). The study was not pre-registered, no randomization was performed to allocate subjects in the study. Board-certified laboratory technicians, who were blinded to the clinical status, using strict procedures for quality control and runapproval, performed the analyses. CSF-specific OCBs were determined using an in-house IEF method on 7.7% polyacrylamide gels and subsequent silver staining.
Paired patient serum and CSF samples were run on adjacent lanes, and CSF-specific OCBs were defined as extra bands in the gamma zone, which were not present in the corresponding serum sample.
For quality control, a positive CSF sample with known CSF-specific OCBs was run on each gel.

| Determination of other inflammatory and degenerative biomarkers in CSF
Neurofilament light (NFL), glial fibrillary acidic protein (GFAP), and tau were measured in CSF as part of the diagnostic routine for MS investigations. NFL was analyzed using a sensitive sandwich enzyme-linked immunosorbent assay (ELISA) method (NF-light® ELISA kit; UmanDiagnostics AB; Catalog # 10-7001 CE), GFAP and tau (INNOTEST® hTAU Ag; Product # 81572) were measured by ELISA, as previously described (Novakova et al., 2018;Rosengren et al., 1994). Chemokine (C-X-C motif) ligand 13 (CXCL13) was analyzed on the discretion of the physician in a subgroup of the included subjects (n = 37). It was measured in CSF by ELISA (Human CXCL13/ BLC/BCA-1 Immunoassay; R&D Systems Inc., Catalog # DCX130), according to the manufacturer's instructions. The average intra-and inter-assay coefficients of variation were ⩽10% and the LLoQ was 7.8 pg/mL. as part of another research project (Novakova et al., 2017). CHI3L1 was analyzed in CSF with solid phase sandwich ELISA (Human Chitinase 3-like 1 Quantikine ELISA Kit; R&D Systems Inc., Catalog # DC3L10). The intra-assay coefficient of variation was below 7% and the LLoQ was 8.15 pg/mL. CSF chitotriosidase activities were measured with an in-house method (Rosén et al., 2014). CSF neurogranin was measured using an in-house ELISA (Wellington et al., 2016).

| Disability and disease activity determined with MRI
Disability was determined with Expanded Disability Status Scale (EDSS) (Kurtzke, 1983). MRI of the brain and spinal cord without and with gadolinium contrast i.v. was performed on 1.5 or 3.0 T machines, according to Swedish radiological guidelines (Vagberg et al., 2017). The recorded type and number of MS lesions were according to the review of the neuroradiologist. Since contrast enhancement on MRI is limited to a period of 6 weeks (mean 3.07 weeks) (Cotton et al., 2003), blood and CSF samples obtained during this period were considered active (n = 97).

| Treatment
In a subset of MS patients treated with either fingolimod (n = 20) or alemtuzumab (n = 15), KFLC index was retrospectively analyzed in frozen samples before and 12 (fingolimod) or 24 (alemtuzumab) months after initiation of treatment.

| Statistics
Statistical analyses were performed with GraphPad prism version 9.1.0 and IBM SPSS version 27 (IBM Corp. 2011). Nonparametric tests were used since KFLC index was non-normally distributed, as determined by the Shapiro-Wilk test. Adjustment for age, sex, and disease duration was performed using a quantile regression analysis. Grubbs' test (significance level α = 0.05, two-sided) was performed to detect outliers. One significant outlier was detected and was not excluded from the analysis. Mann-Whitney test was used The correlation between KFLC index and other CSF biomarkers was determined by the spearman correlation coefficient. Wilcoxon matched-pairs signed rank test was used to compare KFLC index at baseline and follow-up in the two treatment groups. Reiberograms were constructed and KFLC IF was computed using the online software found on www.albaum.it (Reiber, 2020). Sample size and power calculations were performed using IBM SPSS statistics version 27 (p < 0.001, effect size 0,124, observed power 1.0 [100%]).
Statistical significance was assumed at p < 0.05.

| Ethics
The study material was retrieved from medical records of persons that underwent diagnostic investigation of suspected MS, recommended at the Sahlgrenska University Hospital. In addition, we used CSF data from a subgroup of patients who also participated in research projects with extended investigation of inflammatory and degenerative biomarkers (Novakova et al., 2017). They all gave informed consent. All individual data from the different sources were made anonymous to the authors by the replacement of the personal identity numbers by unique number codes for use in the present study. The study was approved by the Swedish ethical review agency (Dnr: 2020-06851).

| RE SULTS
Demographic and clinical characteristics are presented in Table 1.
Overall, there was no significant age difference between the MS and the control group. However, patients with CIS/RIS and RRMS were significantly younger than patients with progressive MS (p < 0.001). Within the control group, symptomatic controls were younger than ONID patients (p < 0.001). Except for PPMS, the proportion of women were higher than men in all subgroups. Age, sex, and disease duration did not significantly influence KFLC index levels.

| Diagnostic Performance of KFLC index
We devised an ROC curve to assess the optimal cutoff value of KFLC index in our cohort and determine the sensitivity and specificity of KFLC index in comparison to OCBs and IgG index

| KFLC index and the hyperbolic reference range have similar overall diagnostic accuracies
In the MS study group, 214 (96%) subjects showed KFLC IF >0%, whereas nine (4%) subjects did not (Figure 3a). Since 16 (  Of these, three had CIS/RIS, one had PPMS, three had SPMS, and 10 had RRMS.

| No correlation between KFLC index and disability, or activity on MRI
KFLC index did not show any significant difference between RRMS patients who had contrast-enhancing lesions on MRI at the time of sampling compared with patients who did not exhibit signs of MRI activity (Figure 5a).
KFLC index did not correlate with the EDSS score at the time of presentation.
F I G U R E 5 KFLC index, MRI activity, and treatment effect. There was no significant difference in KFLC index levels in RRMS patients with or without signs of MRI activity (4A), or at baseline compared with follow-up in RRMS patients treated with fingolimod (n = 20) or alemtuzumab (n = 15). Box represents IQR. Bar indicates median, whereas +indicates mean.

| No effect on KFLC index from diseasemodifying treatment
In an analysis before and after 12 (fingolimod) or 24 (alemtuzumab) months after treatment, RRMS patients treated with fingolimod (n = 20) or alemtuzumab (n = 15) did not demonstrate any difference in KFLC index (Figure 5b).

| DISCUSS ION
We report real-world data on the diagnostic utility of KFLC index in the clinical practice of MS from a large, single-center cohort. All data were collected prospectively between 2013 and 2020 and were obtained and analyzed retrospectively. We confirm KFLC index as a highly useful diagnostic biomarker in MS. In accordance with previous reports, our findings suggest that KFLC index has higher sensitivity than OCBs to discriminate CIS/RIS/MS patients from controls and comparable specificity (Christiansen et al., 2018;Desplat-Jégo et al., 2005;Duell et al., 2020;Duranti et al., 2013;Leurs et al., 2020;Passerini et al., 2016;Pieri et al., 2017;Presslauer et al., 2008).
Furthermore, we confirm that KFLC index has high diagnostic accuracy to predict intrathecal immunoglobulin synthesis via IEF (Süße et al., 2018) and that KFLC index may contribute to the identification of OCB-negative MS patients (Ferraro et al., 2020).
As the relation of KFLC quotient to QAlb is hypothetically not constant, the index may not be constant either. Therefore, statistics with the relative index values may be biased and could be replaced by the QAlb-related intrathecal fraction of KFLC.
Although KFLC IF showed slightly higher sensitivity than KFLC index to detect MS, it had lower specificity, and the overall diagnostic accuracy (AUC) was identical. We were thus unable to confirm in our cohort previous reports about the superiority of KFLC IF over the linear index in MS diagnostics (Schwenkenbecher et al., 2019;Süße et al., 2020). Determination of KFLC IF has the advantage of high sensitivity to detect intrathecal Ig production as well as the consideration of the difference in molecular sizes between the free kappa chain and albumin using a nonlinear relation of KFLC influx into the CSF relative to the QAlb. However, our analyses focused on the diagnostic accuracy to detect MS in a real-world cohort. This may explain the lack of superiority, as the specificity of KFLC IF is lower compared to the linear index. It remains therefore to be determined which method is the most appropriate for use in routine clinical practice.
We show that KFLC index seemed essentially unaffected by other pathological processes in MS as determined by degenerative and inflammatory biomarkers in CSF. It was also independent of demographic factors, disease activity, disease severity, and of treatment with DMT. Thus, KFLC index was not associated with markers of inflammatory disease activity such as contrast-enhancing lesions on MRI or levels of CXCL13, CHI3L1, chitotriosidase, and neurogranin in CSF. Neither did we find a correlation with concurrent disabil- to be relatively independent from other pathological processes.
Interestingly however, KFLC levels in blood were previously shown to decrease in response to treatment with corticosteroids in patients with an acute MS relapse (Konen et al., 2020

ACK N OWLED G M ENTS
The study was supported by grants from the Swedish State Support for Clinical Research (ALFGBG-722081), Regional FoU grant Västra Götalandsregionen (260 101 and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program (outside submitted work). JL has received travel support and/or lecture honoraria and has served on scientific advisory boards for Biogen, Novartis, and Sanofi Genzyme; and has received unconditional research grants from Biogen and Novartis.

DATA AVA I L A B I L I T Y S TAT E M E N T
The data that support the findings of this study are available from the corresponding author upon reasonable request.