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Erschienen in: Wiener Medizinische Wochenschrift 15-16/2022

Open Access 08.02.2022 | main topic

Cerebrospinal fluid kappa free light chains as biomarker in multiple sclerosis—from diagnosis to prediction of disease activity

verfasst von: Harald Hegen, PD, MD, PhD, Klaus Berek, Florian Deisenhammer

Erschienen in: Wiener Medizinische Wochenschrift | Ausgabe 15-16/2022

Summary

Multiple sclerosis (MS) is a chronic immune-mediated disorder of the central nervous system that shows a high interindividual heterogeneity, which frequently poses challenges regarding diagnosis and prediction of disease activity. In this context, evidence of intrathecal inflammation provides an important information and might be captured by kappa free light chains (κ-FLC) in the cerebrospinal fluid (CSF). In this review, we provide an overview on what is currently known about κ‑FLC, its historical development, the available assays and current evidence on its diagnostic and prognostic value in MS. Briefly, intrathecal κ‑FLC synthesis reaches similar diagnostic accuracy compared to the well-established CSF-restricted oligoclonal bands (OCB) to identify patients with MS, and recent studies even depict its value for prediction of early MS disease activity. Furthermore, detection of κ‑FLC has significant methodological advantages in comparison to OCB detection.
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Introduction

Multiple sclerosis (MS) is a chronic inflammatory immune-mediated disease of the central nervous system (CNS) that mainly affects young adults and bears the risk of physical and cognitive disability [1].
Diagnosis of MS requires the combination of clinical signs and symptoms with paraclinical findings obtained by magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) analysis [2]. Evidence of intrathecal immunoglobulin G (IgG) synthesis in the CSF, although not specific for MS, increases diagnostic certainty in the appropriate clinical setting [3] and substitutes for dissemination in time according to current diagnostic criteria [2].
Besides establishing MS diagnosis, one of the main challenges for neurologists counselling patients with MS is weighing benefits versus risks of certain disease-modifying therapies (DMTs) [4]. An ever-increasing number of DMTs have been proven to reduce the number of relapses, accumulation of disability and brain MRI activity [5] and current treatment concepts recognize the importance of early treatment towards suppressing disease activity below the level of detectability [6]. However, the interindividual courses of MS are extremely variable [7] and there is also a certain risk for treatment-associated adverse events. Since criteria guiding decisions when to start treatment in early MS and, in case, whether to choose a moderately or a highly efficacious DMT are still controversially debated, there is an urgent need of biomarkers to predict disease activity [4, 8]. So far, the number of brain MRI lesions and the presence of intrathecal IgG synthesis in the CSF imply some prognostic value [9].
As depicted above, the value of CSF analysis for diagnosis of MS and for prediction of disease activity after the first demyelinating CNS event is unquestioned. However, for the detection of intrathecal IgG synthesis as a marker for intrathecal B cell activity, several different laboratory methods have been developed in the last half century. Quantitative methods that require the measurement of IgG concentrations in CSF and serum followed by calculation of certain formulae such as IgG index [10], Reiber [11] or Auer & Hegen formulae [12] referring patient’s individual values to a predefined upper normal limit are mainly hampered by their low sensitivity. The detection of oligoclonal IgG bands (OCB) by isoelectric focusing (IEF) followed by immunoblotting is nowadays the gold standard. This technique compares paired CSF and blood samples of each individual patient. Intrathecal IgG synthesis is present if OCB are present in CSF without corresponding bands in serum [13]. It ensures a high diagnostic sensitivity and specificity both of approximately 90% [14]. However, this method enables only a qualitative determination of intrathecal IgG synthesis (i.e., returns either a positive or a negative result), is technically demanding, time-consuming, costly and rater-dependent [13].

Kappa free light chains in the CSF as an emerging biomarker

Besides intact immunoglobulins that consist of light chains and heavy chains bound together via disulfide bonds and noncovalent interactions [15], B cells also produce light chains in 10–40% excess over heavy chains and secrete them as free forms into the blood circulation [16]. These free light chains (FLC) have a molecular weight of approximately 24 kD and consists of two immunoglobulin domains, a constant region that specifies the isotype of free light chain (either κ or λ) and a variable domain (Fig. 1; [15]). If bound, the variable light chain domain is part of the immunoglobulin antigen binding site; the function in the free forms is not fully elucidated [16]. κ‑FLC exist mainly in the form of monomers, whereas λ‑FLC are present as covalent dimers [16]. In the last few years, a multitude of studies have highlighted the value of κ‑FLC in CSF as another biomarker—instead of immunoglobulins—for intrathecal B cell activity in patients with MS, not least due to significant methodological advantages.

History of FLC detection

FLCs were discovered more than 150 years ago, when in 1847 Henry Bence Jones described a protein in the urine of a patient with severe bone pain and fractures that precipitated upon addition of nitric acid [17]. The so-called Bence Jones proteins evolved to an important diagnostic marker for patients with multiple myeloma. More than 100 years after its discovery, the Bence Jones protein was identified as monoclonal FLC [18]. Developments in laboratory methods brought up protein electrophoresis and immunofixation electrophoresis; however, these methods still had limited sensitivity so that low level FLC under physiological or oligosecretory conditions, e.g., in immune-mediated diseases, were not detectable, and allowed only qualitative determination [18]. Attempts to quantify FLC were initially hindered by difficulties of producing antibodies specific to FLC that do not cross-react with light chains bound in intact immunoglobulins. The breakthrough was achieved in 2001 by Bradwell and coworkers who dissociated light chains from heavy chains and then raised antibodies directed against unique epitopes on FLC that are normally “hidden” in the conformational structure of an intact immunoglobulin [19]. These anti-human FLC-specific antibodies could then be used to develop assays that exclusively detect FLC at least a hundred times more sensitive than previous methods with detection limits down to approximately 1 mg/L. Nowadays, FLC can be measured in serum as well as in CSF by use of two types of detection antibodies: either polyclonal [19] or monoclonal [20] detection antibodies.

Elevated κ-FLC in the CSF of patients with MS

κ‑FLC in the CSF—similar to immunoglobulins or other proteins—originate either from blood by diffusion across the blood–CSF barrier or are produced within the intrathecal compartment under pathological conditions [21]. Conceptually, it seems necessary to determine the locally synthesized κ‑FLC fraction separate from the blood-derived fraction (as it is also done for IgG). Most studies calculated the κ‑FLC index that considers the CSF/serum albumin quotient (Qalb) which is an established marker for the blood–CSF barrier function [22] and corrects for the absolute serum κ‑FLC level. The κ‑FLC index is determined by following formula [23, 24]:
$$\kappa -FLC\,\textit{index}=\frac{\kappa -\mathrm{FLC}_{\mathrm{CSF}}/\kappa -\mathrm{FLC}_{\text{Serum}}}{Q_{\mathrm{alb}}}$$
It has been consistently shown that the κ‑FLC index reaches a high diagnostic accuracy to identify patients with MS. An overview of current evidence—retrieved in a systematic literature search [2340]—is provided in Table 1. For the κ‑FLC index, diagnostic sensitivity ranges from 52 to 98% (weighted average: 87%) and specificity ranges from 68 to 100% (weighted average: 89%). For OCB, sensitivity ranges from 37 to 100% (weighted average: 84%) and specificity from 74 to 100% (weighted average: 90%). The reported sensitivity of OCB is in accordance with a previous meta-analysis [41]. Applying a difference-in-differences model showed that the mean difference of diagnostic sensitivity between κ‑FLC index and OCB was +2% and of specificity was −2%, i.e., overall the diagnostic accuracy of κ‑FLC index and OCB was equal.
Table 1
Diagnostic value of κ‑free light chain index in patients with multiple sclerosis
Reference
Type of controlsa
No. of control subjects
No. of MS patients
McDonald criteria
Laboratory method
κ‑FLC index
cut-off
Elevated κ‑FLC index in MS, n
Sensitivity, %
Normal κ‑FLC index in controls, n
Specificity, %
OCB positive in MS, n
Sensitivity, %
OCB negative in controls, n
Specificity, %
[25]
NIND/IND/PIND
1149
75
2010
Ne/N Latex
9.58
69
92
1115
97
71
95
1072
93
[26]
299
146
2010/2017
Tu/Freelite
5.8
76
52
282
94
54
37
299
100
[28]
197
45
2017
6.6
42
93
172
87
40
89
179
91
[29]
NIND/IND
105
71
Not specified
Ne/N Latex
12.3
68
96
105
100
65
92
99
94
[30]
85
37
Not specified
Ne/Freelite
5.9
28
76
77
91
33
89
69
81
[31]
253
67
2010
10.463
58
87
193
76
63
94
187
74
[33]
83
59
Not specified
Tu/Freelite
12.45
46
78
64
77
46
78
66
80
[32]
258
127
2017
Ne/N Latex
5.0
122
96
208
81
123
97
214
83
[24]
219
284
2005/2010
Tu/Freelite
6.6
264
93
181
83
245
86
202
92
[34]
42
34
2017
9.4
32
94
29
68
34
100
38
90
[35]
240
133
2017
Ne/N Latex
5.0
124
93
205
85
127
96
204
85
[27]
456
84
2017
Tu/Freelite
6.2
75
89
383
85
71
85
405
89
[36]
NIND
368
41
2001/2005
Ne/Freelite
5.9
40
98
318
86
39
95
338
92
[23]
60
60
2005
5.9
56
93
57
95
56
93
59
98
[37]
97
96
2010
T/Freelite
7.5
87
91
88
91
79
82
91
94
[40]
30
68
2017
N/Freelite
3.09
49
72
30
100
38
56
30
100
[38]
50
80
2010
N/N Latex
5.3
77
96
48
96
73
91
49
98
[39]
HC/SC
60
62
2010
7.15
56
90
60
100
54
87
60
100
A search of the electronic database PubMed was performed on November 17, 2021 using the terms “multiple sclerosis” and “free light chains” and limited to the time period between January 1, 2005 and November 17, 2021. Titles and abstracts of identified articles written in English were screened and the full text of potentially relevant articles were assessed for inclusion criteria. Studies were included if they were original articles investigating the diagnostic value of κ‑FLC index in patients with MS compared to other neurological diseases and used nephelometry/turbidimetry for κ‑FLC measurement. κ-FLC kappa free light chain, OCB oligoclonal bands
Following original articles were included: [25] Senel 2019, [26] Ferraro 2020, Eur J Neurol, [28] Sanz Diaz 2021, [29] Pieri 2017, [30] Valencia-Vera 2018, [31] Gurtner 2018, [33] Bayart 2018, [32] Crespi 2019, [24] Leurs 2020, [34] Gudowska-Sawczuk 2020, [35] Vecchio 2020, [27] Ferraro 2020, Diagnostics (Basel), [36] Presslauer 2008, [23] Presslauer 2016, [37] Christiansen 2018, [40] Altinier 2019, [38] Emersic 2019 and [39] Duell 2020.
The diagnostic value of κ‑FLC index and OCB was compared by a difference-in-differences model. Therefore, for each study, the difference of diagnostic sensitivity of κ‑FLC index and OCB (∆sensitivity), as well as the difference of diagnostic specificity of κ‑FLC index and OCB (∆specificity) was calculated. Then, also the sum of ∆sensitivity and ∆specificity was calculated (∆overall). Finally, the mean of all ∆values was calculated. This statistical analysis revealed a mean ∆sensitivity of 2%, ∆specificity of −2%, and ∆overall of 0%. This result indicate that there is no difference in the diagnostic performance of κ‑FLC index and OCB to discriminate patients with MS from controls
HC healthy controls, IND inflammatory neurological disease controls (other than MS), MS multiple sclerosis, Ne Nephelometry, NIND non-inflammatory neurological disease controls, PIND peripheral inflammatory neurological disease controls, SC symptomatic controls, Tu Turbidimetry, κ‑FLC kappa free light chain, OCB oligoclonal bands
aControl population of studies were labelled/categorized according to the “Consensus definitions and application guidelines for control groups in cerebrospinal fluid biomarker studies in multiple sclerosis” [42]
The wide range of diagnostic sensitivity and specificity for both the κ‑FLC index and OCB arises from a certain heterogeneity between studies. It is evident that specificity of κ‑FLC index is lowered when patients with inflammatory neurological disease (IND) were included into the control group. κ‑FLC in CSF are—similar to CSF-restricted OCB—a sign of intrathecal inflammation and thus can support the diagnosis of MS, but they are not specific for MS. The spectrum of diseases which show intrathecal κ‑FLC synthesis is probably identical to that with CSF-restricted OCB, even though studies on the frequency of intrathecal κ‑FLC synthesis in other neurological disease are still rare. Apart from a mixture of different IND as part of control populations (Table 1) that had κ‑FLC synthesis in up to 32%, dedicated disease-specific studies exist only for a few entities, e.g., neuroborreliosis [43, 44].

κ-FLC index associated with early MS disease activity

There are only a few studies on the predictive value of the κ‑FLC index in MS. An overview is given in Table 2. These studies reported that the presence of intrathecal κ‑FLC synthesis is associated with conversion from CIS to MS [4549] and that the κ‑FLC index predicted the time to conversion to MS as well as disability progression [49, 50]. However, these studies had some methodological limitations. A multivariate approach that considers other already known risk factors especially MRI activity is critical to identify the independent prognostic effect of the κ‑FLC index and to weigh its impact on the outcome.
Table 2
Prognostic value of κ‑free light chain index in patients with multiple sclerosis
Ref
Age
(years)
mean
±SD
Fem.
(%)
McDonald
criteria
OCB
(%)
FU
(months)
median
End-
point
Patients reaching endpoint
Patients not reaching endpoint
Assay
Cut-off
κ‑FLC
index
Statistical analyses
Main findings
No.
κ‑FLC index
OCB
No.
κ‑FLC index
OCB
Positive N
Sensitivity %
Positive N
Sensitivity %
Negative N
Specificity %
Negative N
Specificity %
[51]
NA
NA
2001
NA
55
(mean)
Conv. to CDMS
24
10
42
NA
NA
0
Ne/Freelite
> 50
Mann
Whitney U
Time to CDMS did not differ between patients with high (> 50) and low (< 50) κ‑FLC index
[48]
35
(min 15–max 62)
88
NA
62
>24
Conv. to CDMS
38
35
92
NA
NA
39
25
64
NA
NA
Ne/Freelite
> 10.62
Cox
regression
κ‑FLC index predicted time to CDMS (HR 5.3)
[50]
34 ± 11
64
2017
92
47
(mean)
MSSS
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Ne/
N latex
NA
Linear
regression
κ‑FLC index predicted MSSS
[47]
42 ± 11
78
2010
NA
39
Conv. to MSa
12
12
100
NA
NA
11
3
27
NA
NA
Ne/Freelite
≥10.6
Cox
regression
κ‑FLC index predicted time to MS
(50% of patients with κ‑index ≥ 10.6 converting in 21 months)
[49]
30 ± 9
86
2017
82
79
EDSS progressionb
18
NA
NA
17
94
10
NA
NA
4
40
Ne/Freelite
NA
Spearman
correlation
κ‑FLC index correlated with shorter time to EDSS progression (r = −0.55)
Conv. to CDMS
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
κ‑FLC index correlated with shorter time to CDMS (r = −0.59)
[52]
33 ± 10
68
2017
90
47
Conv. to CDMS
38
13
34
50
44
88
Ne/
N latex
> 100
Cox
regression
κ‑FLC index predicted time to CDMS
(11 vs. 36 months in patients with high [>100] vs. low [≤ 100] κ‑FLC index)
Predictive value of κ‑FLC index was superior to that of OCB
36
95
36
95
10
20
7
14
≥ 6.6
EDSS ≥ 3
8
2
25
78
61
78
> 100
Mann
Whitney U
κ‑FLC index did not differ between patients reaching EDSS ≥ 3 or not at the end of follow-up
7
88
8
100
11
14
9
12
≥ 6.6
A search of the electronic database PubMed was performed on November 17, 2021 using the terms “multiple sclerosis” AND “free light chains” AND “prognosis”, “predict” or “conversion” limited to the time period between January 1, 2005 and November 17, 2021. Titles and abstracts of identified articles written in English were screened and the full text of potentially relevant articles were assessed for inclusion criteria. Studies were included if they were original articles investigating the prognostic value of κ‑FLC index in patients with clinically isolated syndrome in terms of various endpoints (e.g., conversion to MS) and used nephelometry/turbidimetry for κ‑FLC measurement. Following original articles were included: [51] Presslauer 2014, [48] Menéndez-Valladares 2015, [50] Vecchio 2019, [47] Gaetani 2020, [49] Salavisa 2020 and [52] Berek 2021
CDMS clinically definite multiple sclerosis, Conv. conversion, EDSS Expanded Disability Status Scale, Fem. females, FLC free light chain, FU follow-up, HR hazard ratio, MSSS Multiple Sclerosis Severity Score, MS multiple sclerosis, N nephelometry, NA not available, No. number, OCB oligoclonal bands, ref reference, SD standard deviation
aConversion to MS was defined by clinical or radiological means
bEDSS progression was defined as an increase in EDSS score of ⩾ 1.5 points from a baseline EDSS score of 0, ⩾ 1.0 point from a baseline EDSS score of 1.0–5.5, or ⩾ 0.5 point from a baseline EDSS score ⩾ 6.0, confirmed after 6 months of follow-up
There is one recent study that fulfills these requirements providing class II evidence that in patients with early MS, high κ‑FLC index is an independent risk factor for early second clinical attack. A cohort of 88 patients with a first CNS demyelinating event (mostly monofocal, 45% myelitis, 30% optic neuritis, 24% affection of brainstem/cerebellum), at a mean age of 33 years and with a female predominance of 68% were followed over 4 years. In all, 38 (43%) patients converted to clinically definite MS (CDMS) within the observation period. In multivariate Cox regression analysis adjusting for age, sex, MRI lesion load and activity at baseline, administration of corticosteroids at baseline and DMT during follow-up revealed that κ‑FLC index predicts time to second clinical attack. This study showed that patients with κ‑FLC index > 100 at baseline had a twice as high probability for a second clinical attack within 12 months than patients with low κ‑FLC index; within 24 months, the chance in patients with high κ‑FLC index was 4 times as high as in patients with low κ‑FLC index. The median time to second attack was 11 months in patients with high κ‑FLC index, whereas 36 months in those with low κ‑FLC index [52].

Advantages of κ-FLC index compared to OCB

Current evidence suggests that determination of κ‑FLC index has some advantages over OCB detection. Even though it seems that there is no relevant difference with regard to diagnostic accuracy (Table 1), κ‑FLC can be easily measured by nephelometry which is—in contrast to the detection of OCB—a reliable, labor-saving and cost-efficient method [20]. Moreover, κ‑FLC index returns a metric result covering a range from approximately 1 up to 500 [23], i.e., it is a quantitative parameter, while OCB status is dichotomous returning either a positive or negative result as assessed by visual inspection [13]. The advantage of a metric result seems important especially for predicting disease activity. In the most recent study on the predictive value of κ‑FLC index—as previously mentioned [52]—which included patients with a first CNS demyelinating event, OCB were detected in 95% of patients who converted to CDMS during the 4‑year follow-up (CDMS converters), whereas non-converters were OCB positive also in 86% of cases. As a continuous variable, κ‑FLC index overcame the weak performance of OCB by further stratification. κ‑FLC index also significantly differed between OCB-positive CDMS converters and OCB-positive nonconverters and predicted CDMS conversion also within the cohort of OCB-positive patients [52]. Despite these promising results and clear methodological advantages of κ‑FLC index over OCB, the latter is still considered the gold standard. Before κ‑FLC index might be introduced into clinical routine, a few issues still need to be clarified, e.g., whether calculation of intrathecal κ‑FLC synthesis is superior to determination of absolute κ‑FLC concentrations in CSF or which cut-off should be applied. These two open issues are discussed in the following.

Open issues

Determining κ-FLC index or absolute CSF κ-FLC values

As mentioned above, one might argue that determining the locally synthesized fraction of κ‑FLC separate from the blood-derived fraction is necessary to capture an intrathecal inflammatory process. And indeed, the majority of studies used the κ‑FLC index (Table 1) or calculated an intrathecal κ‑FLC fraction by empirically determined Qalb-dependent reference limits [25, 43, 51, 53], whereas some studies included the CSF/serum κ‑FLC ratio (Qκ‑FLC) [30, 38, 5458]. Other authors determined the absolute CSF κ‑FLC concentrations [31] arguing that the contribution of blood-derived FLC to the total CSF FLC concentration is low in cases with intrathecal synthesis. In fact, the intrathecal fraction of κ‑FLC is greater than 80% in most MS patients [23], and around 15% of CIS/MS patients showed even higher absolute κ‑FLC concentrations in CSF than in serum that proves an intrathecal synthesis per se [59]. To further elaborate this research question, a recent study separated patients into low and high CSF κ‑FLC categories (based on median values) and observed that CSF κ‑FLC concentration, Qκ‑FLC and κ‑FLC index showed similar diagnostic performance in the high category, but not in the low category with inferiority of CSF κ‑FLC and to some extent also of Qκ‑FLC. This is in line with a previous study reporting that QFLC depends almost exclusively on the amount of intrathecally synthesized FLC in cases of intrathecal B cell activity (defined by presence of oligoclonal FLC bands), whereas a correlation of Qalb and QFLC was observed in cases of absent intrathecal B cell activity (defined by negative oligoclonal FLC bands) [56]. Thus, there is evidence that the impact of serum κ‑FLC levels and Qalb is negligible in patients with strong intrathecal κ‑FLC synthesis, but probably not in patients with only low or modest intrathecal κ‑FLC production. Further studies applying multivariate statistics are required to compare these different approaches.

Establishing cut-off values

Before κ‑FLC index can be introduced into clinical routine, cut-offs have to be established. Different cut-off values might apply depending on the clinical question, e.g., to provide an upper reference limit as determined in a control population (either healthy or e.g. a symptomatic control [42]), to differentiate MS from other IND or to classify patients according to their risk for future disease activity. The so far published cut-off values differentiating MS from other neurological diseases ranged from 3.09 to 12.45 (Table 1). As κ‑FLC index values indeed vary between diseases with high values in MS, followed by other IND and then by non-IND [32, 35, 60], different cut-off values might be useful. For example, one study showed that patients with MS had κ‑FLC index of approximately 90, whereas patients with neuromyelitis optica spectrum disease that is relevant differential diagnosis of MS had values of roughly 20 and control patients values of 4 [60].
Studies that address reproducibility of κ‑FLC index using different assays, platforms and cut-offs between centers are needed, too. Although some work has already been performed in terms of absolute serum κ‑FLC concentrations, this is still lacking for κ‑FLC index. κ‑FLC index might show different robustness, as a ratio (of the CSF/serum κ‑FLC concentration, used for calculation of the κ‑FLC index) is usually less prone to laboratory variations.

Conclusions

κ‑FLC are a promising biomarker that might replace OCB detection. With regard to its diagnostic value, κ‑FLC index shows a high accuracy similar to that of OCB, but has also significant methodological advantages as an easy, reliable, fast, labor- and cost-saving method. With regard to its prognostic value, the benefit could evolve—either stand alone or in combination with others—to identify early MS patients with a higher risk for further disease activity, e.g., shorter time to a second attack. These patients could be advised to start DMT early or use highly effective DMT, as there is evidence that the time to the second attack has a prognostic impact on long-term disability [61, 62] and that early treatment significantly delays conversion to CDMS as well as disability progression [6365]. Conversely, there is a certain proportion of patients showing a mild disease course who may not need a potentially harmful, psychologically distressing and, last but not least, costly DMT.
Whereas the high diagnostic value is already supported by a multitude of studies, further studies are still required to replicate the independent prognostic value of κ‑FLC index in early MS. Apart from harmonization efforts as depicted above to establish a widely applicable cut-off to definite positivity, potential influential factors such as corticosteroid treatment [52, 66], DMT or different disease phases (relapse versus stable remission) on κ‑FLC index also have to be explored.
Thus, there is convincing evidence that κ‑FLC index reliably indicates intrathecal inflammation in MS, might replace OCB determination and probably takes us one step closer to tailored medicine in MS.

Conflict of interest

H. Hegen has participated in meetings sponsored by, received speaker honoraria or travel funding from Bayer, Biogen, Merck, Novartis, Sanofi-Genzyme, Siemens, Teva, and received honoraria for acting as consultant for Biogen, Novartis and Teva. K. Berek has participated in meetings sponsored by and received travel funding from Roche, Teva and Biogen. F. Deisenhammer has participated in meetings sponsored by or received honoraria for acting as an advisor/speaker for Alexion, Almirall, Biogen, Celgene, Genzyme-Sanofi, Merck, Novartis Pharma, Roche, and Teva. His institution has received research grants from Biogen and Genzyme Sanofi. He is section editor of the MSARD Journal (Multiple Sclerosis and Related Disorders).
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Literatur
2.
Zurück zum Zitat Thompson AJ, Banwell BL, Barkhof F, Carroll WM, Coetzee T, Comi G, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 2018;17(2):162–73.PubMedCrossRef Thompson AJ, Banwell BL, Barkhof F, Carroll WM, Coetzee T, Comi G, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 2018;17(2):162–73.PubMedCrossRef
3.
Zurück zum Zitat Arrambide G, Tintore M, Espejo C, Auger C, Castillo M, Río J, et al. The value of oligoclonal bands in the multiple sclerosis diagnostic criteria. Brain. 2018;141(4):1075–84.PubMedCrossRef Arrambide G, Tintore M, Espejo C, Auger C, Castillo M, Río J, et al. The value of oligoclonal bands in the multiple sclerosis diagnostic criteria. Brain. 2018;141(4):1075–84.PubMedCrossRef
4.
Zurück zum Zitat Ontaneda D, Tallantyre E, Kalincik T, Planchon SM, Evangelou N. Early highly effective versus escalation treatment approaches in relapsing multiple sclerosis. Lancet Neurol. 2019;18(10):973–80.PubMedCrossRef Ontaneda D, Tallantyre E, Kalincik T, Planchon SM, Evangelou N. Early highly effective versus escalation treatment approaches in relapsing multiple sclerosis. Lancet Neurol. 2019;18(10):973–80.PubMedCrossRef
6.
Zurück zum Zitat Giovannoni G. Disease-modifying treatments for early and advanced multiple sclerosis: a new treatment paradigm. Curr Opin Neurol. 2018;31(3):233–43.PubMedCrossRef Giovannoni G. Disease-modifying treatments for early and advanced multiple sclerosis: a new treatment paradigm. Curr Opin Neurol. 2018;31(3):233–43.PubMedCrossRef
7.
Zurück zum Zitat Weinshenker BG, Bass B, Rice GP, Noseworthy J, Carriere W, Baskerville J, et al. The natural history of multiple sclerosis: a geographically based study. I. Clinical course and disability. Brain. 1989;112(Pt 1):133–46.PubMedCrossRef Weinshenker BG, Bass B, Rice GP, Noseworthy J, Carriere W, Baskerville J, et al. The natural history of multiple sclerosis: a geographically based study. I. Clinical course and disability. Brain. 1989;112(Pt 1):133–46.PubMedCrossRef
9.
Zurück zum Zitat Tintore M, Rovira A, Río J, Otero-Romero S, Arrambide G, Tur C, et al. Defining high, medium and low impact prognostic factors for developing multiple sclerosis. Brain. 2015;138(Pt 7):1863–74.PubMedCrossRef Tintore M, Rovira A, Río J, Otero-Romero S, Arrambide G, Tur C, et al. Defining high, medium and low impact prognostic factors for developing multiple sclerosis. Brain. 2015;138(Pt 7):1863–74.PubMedCrossRef
10.
Zurück zum Zitat Link H, Tibbling G. Principles of albumin and IgG analyses in neurological disorders. III. Evaluation of IgG synthesis within the central nervous system in multiple sclerosis. Scand J Clin Lab Invest. 1977;37(5):397–401.PubMedCrossRef Link H, Tibbling G. Principles of albumin and IgG analyses in neurological disorders. III. Evaluation of IgG synthesis within the central nervous system in multiple sclerosis. Scand J Clin Lab Invest. 1977;37(5):397–401.PubMedCrossRef
11.
Zurück zum Zitat Reiber H. Flow rate of cerebrospinal fluid (CSF)—a concept common to normal blood-CSF barrier function and to dysfunction in neurological diseases. J Neurol Sci. 1994;122(2):189–203.PubMedCrossRef Reiber H. Flow rate of cerebrospinal fluid (CSF)—a concept common to normal blood-CSF barrier function and to dysfunction in neurological diseases. J Neurol Sci. 1994;122(2):189–203.PubMedCrossRef
12.
Zurück zum Zitat Auer M, Hegen H, Zeileis A, Deisenhammer F. Quantitation of intrathecal immunoglobulin synthesis—a new empirical formula. Eur J Neurol. 2016;23(4):713–21.PubMedCrossRef Auer M, Hegen H, Zeileis A, Deisenhammer F. Quantitation of intrathecal immunoglobulin synthesis—a new empirical formula. Eur J Neurol. 2016;23(4):713–21.PubMedCrossRef
13.
Zurück zum Zitat Freedman MS, Thompson EJ, Deisenhammer F, Giovannoni G, Grimsley G, Keir G, et al. Recommended standard of cerebrospinal fluid analysis in the diagnosis of multiple sclerosis: a consensus statement. Arch Neurol. 2005;62:865–70.PubMedCrossRef Freedman MS, Thompson EJ, Deisenhammer F, Giovannoni G, Grimsley G, Keir G, et al. Recommended standard of cerebrospinal fluid analysis in the diagnosis of multiple sclerosis: a consensus statement. Arch Neurol. 2005;62:865–70.PubMedCrossRef
14.
Zurück zum Zitat Hegen H, Zinganell A, Auer M, Deisenhammer F. The clinical significance of single or double bands in cerebrospinal fluid isoelectric focusing. A retrospective study and systematic review. Plos One. 2019;14(4):e215410.PubMedPubMedCentralCrossRef Hegen H, Zinganell A, Auer M, Deisenhammer F. The clinical significance of single or double bands in cerebrospinal fluid isoelectric focusing. A retrospective study and systematic review. Plos One. 2019;14(4):e215410.PubMedPubMedCentralCrossRef
15.
Zurück zum Zitat Abbas AK, Lichtman AH, Pillai S. Cellular and molecular immunology. 6th ed. 2007: Elsevier Saunders. Abbas AK, Lichtman AH, Pillai S. Cellular and molecular immunology. 6th ed. 2007: Elsevier Saunders.
16.
Zurück zum Zitat Nakano T, Matsui M, Inoue I, Awata T, Katayama S, Murakoshi T. Free immunoglobulin light chain: its biology and implications in diseases. Clin Chim Acta. 2011;412(11/12):843–9.PubMedCrossRef Nakano T, Matsui M, Inoue I, Awata T, Katayama S, Murakoshi T. Free immunoglobulin light chain: its biology and implications in diseases. Clin Chim Acta. 2011;412(11/12):843–9.PubMedCrossRef
18.
Zurück zum Zitat Jenner E. Serum free light chains in clinical laboratory diagnostics. Clin Chim Acta. 2014;427:15–20.PubMedCrossRef Jenner E. Serum free light chains in clinical laboratory diagnostics. Clin Chim Acta. 2014;427:15–20.PubMedCrossRef
19.
Zurück zum Zitat Bradwell AR, Carr-Smith HD, Mead GP, Tang LX, Showell PJ, Drayson MT, et al. Highly sensitive, automated immunoassay for immunoglobulin free light chains in serum and urine. Clin Chem. 2001;47(4):673–80.PubMedCrossRef Bradwell AR, Carr-Smith HD, Mead GP, Tang LX, Showell PJ, Drayson MT, et al. Highly sensitive, automated immunoassay for immunoglobulin free light chains in serum and urine. Clin Chem. 2001;47(4):673–80.PubMedCrossRef
20.
Zurück zum Zitat Te Velthuis H, Knop I, Stam P, van den Broek M, Bos HK, Hol S, et al. N Latex FLC—new monoclonal high-performance assays for the determination of free light chain kappa and lambda. Clin Chem Lab Med. 2011;49(8):1323–32.CrossRef Te Velthuis H, Knop I, Stam P, van den Broek M, Bos HK, Hol S, et al. N Latex FLC—new monoclonal high-performance assays for the determination of free light chain kappa and lambda. Clin Chem Lab Med. 2011;49(8):1323–32.CrossRef
21.
Zurück zum Zitat Reiber H. Dynamics of brain-derived proteins in cerebrospinal fluid. Clin Chim Acta. 2001;310(2):173–86.PubMedCrossRef Reiber H. Dynamics of brain-derived proteins in cerebrospinal fluid. Clin Chim Acta. 2001;310(2):173–86.PubMedCrossRef
22.
Zurück zum Zitat Deisenhammer F, Bartos A, Egg R, Gilhus NE, Giovannoni G, Rauer S, et al. Guidelines on routine cerebrospinal fluid analysis. Report from an EFNS task force. Eur J Neurol. 2006;13(9):913–22.PubMedCrossRef Deisenhammer F, Bartos A, Egg R, Gilhus NE, Giovannoni G, Rauer S, et al. Guidelines on routine cerebrospinal fluid analysis. Report from an EFNS task force. Eur J Neurol. 2006;13(9):913–22.PubMedCrossRef
23.
Zurück zum Zitat Presslauer S, Milosavljevic D, Huebl W, Aboulenein-Djamshidian F, Krugluger W, Deisenhammer F, et al. Validation of kappa free light chains as a diagnostic biomarker in multiple sclerosis and clinically isolated syndrome: a multicenter study. Mult Scler. 2016;22(4):502–10.PubMedCrossRef Presslauer S, Milosavljevic D, Huebl W, Aboulenein-Djamshidian F, Krugluger W, Deisenhammer F, et al. Validation of kappa free light chains as a diagnostic biomarker in multiple sclerosis and clinically isolated syndrome: a multicenter study. Mult Scler. 2016;22(4):502–10.PubMedCrossRef
24.
Zurück zum Zitat Leurs CE, Twaalfhoven H, Lissenberg-Witte BI, van Pesch V, Dujmovic I, Drulovic J, et al. Kappa free light chains is a valid tool in the diagnostics of MS: a large multicenter study. Mult Scler. 2020;26(8):912–23.PubMedCrossRef Leurs CE, Twaalfhoven H, Lissenberg-Witte BI, van Pesch V, Dujmovic I, Drulovic J, et al. Kappa free light chains is a valid tool in the diagnostics of MS: a large multicenter study. Mult Scler. 2020;26(8):912–23.PubMedCrossRef
25.
Zurück zum Zitat Senel M, Mojib-Yezdani F, Braisch U, Bachhuber F, Lewerenz J, Ludolph AC, et al. CSF free light chains as a marker of intrathecal immunoglobulin synthesis in multiple sclerosis: a blood-CSF barrier related evaluation in a large cohort. Front Immunol Front. 2019;10:641.CrossRef Senel M, Mojib-Yezdani F, Braisch U, Bachhuber F, Lewerenz J, Ludolph AC, et al. CSF free light chains as a marker of intrathecal immunoglobulin synthesis in multiple sclerosis: a blood-CSF barrier related evaluation in a large cohort. Front Immunol Front. 2019;10:641.CrossRef
26.
Zurück zum Zitat Ferraro D, Trovati A, Bedin R, Natali P, Franciotta D, Santangelo M, et al. Cerebrospinal fluid kappa and lambda free light chains in oligoclonal band-negative patients with suspected multiple sclerosis. Eur J Neurol. 2020;27(3):461–7.PubMedCrossRef Ferraro D, Trovati A, Bedin R, Natali P, Franciotta D, Santangelo M, et al. Cerebrospinal fluid kappa and lambda free light chains in oligoclonal band-negative patients with suspected multiple sclerosis. Eur J Neurol. 2020;27(3):461–7.PubMedCrossRef
27.
Zurück zum Zitat Ferraro D, Bedin R, Natali P, Franciotta D, Smolik K, Santangelo M, et al. Kappa index versus CSF oligoclonal bands in predicting multiple sclerosis and infectious/inflammatory CNS disorders. Diagnostics. 2020;10(10):856.PubMedCentralCrossRef Ferraro D, Bedin R, Natali P, Franciotta D, Smolik K, Santangelo M, et al. Kappa index versus CSF oligoclonal bands in predicting multiple sclerosis and infectious/inflammatory CNS disorders. Diagnostics. 2020;10(10):856.PubMedCentralCrossRef
28.
Zurück zum Zitat Sanz Diaz CT, de Las Heras Flórez S, Carretero Perez M, Hernández Pérez MÁ, Martín García V. Evaluation of kappa index as a tool in the diagnosis of multiple sclerosis: implementation in routine screening procedure. Front Neurol. 2021;12:676527.PubMedPubMedCentralCrossRef Sanz Diaz CT, de Las Heras Flórez S, Carretero Perez M, Hernández Pérez MÁ, Martín García V. Evaluation of kappa index as a tool in the diagnosis of multiple sclerosis: implementation in routine screening procedure. Front Neurol. 2021;12:676527.PubMedPubMedCentralCrossRef
29.
Zurück zum Zitat Pieri M, Storto M, Pignalosa S, Zenobi R, Buttari F, Bernardini S, et al. KFLC index utility in multiple sclerosis diagnosis: further confirmation. J Neuroimmunol. 2017;309:31–3.PubMedCrossRef Pieri M, Storto M, Pignalosa S, Zenobi R, Buttari F, Bernardini S, et al. KFLC index utility in multiple sclerosis diagnosis: further confirmation. J Neuroimmunol. 2017;309:31–3.PubMedCrossRef
30.
Zurück zum Zitat Valencia-Vera E, Martinez-Escribano Garcia-Ripoll A, Enguix A, Abalos-Garcia C, Segovia-Cuevas MJ. Application of κ free light chains in cerebrospinal fluid as a biomarker in multiple sclerosis diagnosis: development of a diagnosis algorithm. Clin Chem Lab Med. 2018;56(4):609–13.PubMedCrossRef Valencia-Vera E, Martinez-Escribano Garcia-Ripoll A, Enguix A, Abalos-Garcia C, Segovia-Cuevas MJ. Application of κ free light chains in cerebrospinal fluid as a biomarker in multiple sclerosis diagnosis: development of a diagnosis algorithm. Clin Chem Lab Med. 2018;56(4):609–13.PubMedCrossRef
31.
Zurück zum Zitat Gurtner KM, Shosha E, Bryant SC, Andreguetto BD, Murray DL, Pittock SJ, et al. CSF free light chain identification of demyelinating disease: comparison with oligoclonal banding and other CSF indexes. Clin Chem Lab Med. 2018;56(7):1071–80.PubMedCrossRef Gurtner KM, Shosha E, Bryant SC, Andreguetto BD, Murray DL, Pittock SJ, et al. CSF free light chain identification of demyelinating disease: comparison with oligoclonal banding and other CSF indexes. Clin Chem Lab Med. 2018;56(7):1071–80.PubMedCrossRef
32.
Zurück zum Zitat Crespi I, Vecchio D, Serino R, Saliva E, Virgilio E, Sulas MG, et al. K index is a reliable marker of Intrathecal synthesis, and an alternative to IgG index in multiple sclerosis diagnostic work-up. J Clin Med. 2019;8(4):446.PubMedCentralCrossRef Crespi I, Vecchio D, Serino R, Saliva E, Virgilio E, Sulas MG, et al. K index is a reliable marker of Intrathecal synthesis, and an alternative to IgG index in multiple sclerosis diagnostic work-up. J Clin Med. 2019;8(4):446.PubMedCentralCrossRef
33.
Zurück zum Zitat Bayart JL, Muls N, van Pesch V. Free kappa light chains in neuroinflammatory disorders: complement rather than substitute? Acta Neurol Scand. 2018;138(4):352–8.PubMedCrossRef Bayart JL, Muls N, van Pesch V. Free kappa light chains in neuroinflammatory disorders: complement rather than substitute? Acta Neurol Scand. 2018;138(4):352–8.PubMedCrossRef
34.
Zurück zum Zitat Gudowska-Sawczuk M, Tarasiuk J, Kułakowska A, Kochanowicz J, Mroczko B. Kappa free light chains and IgG combined in a novel algorithm for the detection of multiple sclerosis. Brain Sci Multidiscip Digit Publ Inst. 2020;10(6):324. Gudowska-Sawczuk M, Tarasiuk J, Kułakowska A, Kochanowicz J, Mroczko B. Kappa free light chains and IgG combined in a novel algorithm for the detection of multiple sclerosis. Brain Sci Multidiscip Digit Publ Inst. 2020;10(6):324.
35.
Zurück zum Zitat Vecchio D, Bellomo G, Serino R, Virgilio E, Lamonaca M, Dianzani U, et al. Intrathecal kappa free light chains as markers for multiple sclerosis. Sci Rep. 2020;10(1):20329–20326.PubMedPubMedCentralCrossRef Vecchio D, Bellomo G, Serino R, Virgilio E, Lamonaca M, Dianzani U, et al. Intrathecal kappa free light chains as markers for multiple sclerosis. Sci Rep. 2020;10(1):20329–20326.PubMedPubMedCentralCrossRef
36.
Zurück zum Zitat Presslauer S, Milosavljevic D, Brücke T, Bayer P, Hübl W, Hübl W. Elevated levels of kappa free light chains in CSF support the diagnosis of multiple sclerosis. J Neurol. 2008;255(10):1508–14.PubMedCrossRef Presslauer S, Milosavljevic D, Brücke T, Bayer P, Hübl W, Hübl W. Elevated levels of kappa free light chains in CSF support the diagnosis of multiple sclerosis. J Neurol. 2008;255(10):1508–14.PubMedCrossRef
37.
Zurück zum Zitat Christiansen M, Gjelstrup MC, Stilund M, Christensen T, Petersen T, Jon Møller H. Cerebrospinal fluid free kappa light chains and kappa index perform equal to oligoclonal bands in the diagnosis of multiple sclerosis. Clin Chem Lab Med. 2018; 57(2):210–20. https://doi.org/10.1515/cclm-2018-0400.CrossRefPubMed Christiansen M, Gjelstrup MC, Stilund M, Christensen T, Petersen T, Jon Møller H. Cerebrospinal fluid free kappa light chains and kappa index perform equal to oligoclonal bands in the diagnosis of multiple sclerosis. Clin Chem Lab Med. 2018; 57(2):210–20. https://​doi.​org/​10.​1515/​cclm-2018-0400.CrossRefPubMed
38.
Zurück zum Zitat Emersic A, Anadolli V, Krsnik M, Rot U. Intrathecal immunoglobulin synthesis: the potential value of an adjunct test. Clin Chim Acta. 2019;489:109–16.PubMedCrossRef Emersic A, Anadolli V, Krsnik M, Rot U. Intrathecal immunoglobulin synthesis: the potential value of an adjunct test. Clin Chim Acta. 2019;489:109–16.PubMedCrossRef
40.
Zurück zum Zitat Altinier S, Puthenparampil M, Zaninotto M, Toffanin E, Ruggero S, Gallo P, et al. Free light chains in cerebrospinal fluid of multiple sclerosis patients negative for IgG oligoclonal bands. Clin Chim Acta. 2019;496:117–20.PubMedCrossRef Altinier S, Puthenparampil M, Zaninotto M, Toffanin E, Ruggero S, Gallo P, et al. Free light chains in cerebrospinal fluid of multiple sclerosis patients negative for IgG oligoclonal bands. Clin Chim Acta. 2019;496:117–20.PubMedCrossRef
41.
Zurück zum Zitat Dobson R, Ramagopalan S, Davis A, Giovannoni G. Cerebrospinal fluid oligoclonal bands in multiple sclerosis and clinically isolated syndromes: a meta-analysis of prevalence, prognosis and effect of latitude. J Neurol Neurosurg Psychiatry. 2013;84(8):909–14.PubMedCrossRef Dobson R, Ramagopalan S, Davis A, Giovannoni G. Cerebrospinal fluid oligoclonal bands in multiple sclerosis and clinically isolated syndromes: a meta-analysis of prevalence, prognosis and effect of latitude. J Neurol Neurosurg Psychiatry. 2013;84(8):909–14.PubMedCrossRef
42.
Zurück zum Zitat Teunissen C, Menge T, Altintas A, Álvarez-Cermeño JC, Bertolotto A, Berven FS, et al. Consensus definitions and application guidelines for control groups in cerebrospinal fluid biomarker studies in multiple sclerosis. Mult Scler. 2013;19(13):1802–9.PubMedCrossRef Teunissen C, Menge T, Altintas A, Álvarez-Cermeño JC, Bertolotto A, Berven FS, et al. Consensus definitions and application guidelines for control groups in cerebrospinal fluid biomarker studies in multiple sclerosis. Mult Scler. 2013;19(13):1802–9.PubMedCrossRef
43.
Zurück zum Zitat Hegen H, Milosavljevic D, Schnabl C, Manowiecka A, Walde J, Deisenhammer F, et al. Cerebrospinal fluid free light chains as diagnostic biomarker in neuroborreliosis. Clin Chem Lab Med. 2018;56(8):1383–91.PubMedCrossRef Hegen H, Milosavljevic D, Schnabl C, Manowiecka A, Walde J, Deisenhammer F, et al. Cerebrospinal fluid free light chains as diagnostic biomarker in neuroborreliosis. Clin Chem Lab Med. 2018;56(8):1383–91.PubMedCrossRef
44.
Zurück zum Zitat Tjernberg I, Johansson M, Henningsson AJ. Diagnostic performance of cerebrospinal fluid free light chains in Lyme neuroborreliosis—a pilot study. Clin Chem Lab Med. 2019;57(12):2008–18.PubMedCrossRef Tjernberg I, Johansson M, Henningsson AJ. Diagnostic performance of cerebrospinal fluid free light chains in Lyme neuroborreliosis—a pilot study. Clin Chem Lab Med. 2019;57(12):2008–18.PubMedCrossRef
45.
Zurück zum Zitat Schwenkenbecher P, Konen FF, Wurster U, Witte T, Gingele S, Sühs K‑W, et al. Reiber’s diagram for kappa free light chains: the new standard for assessing intrathecal synthesis? Diagnostics. 2019;9(4):194.PubMedCentralCrossRef Schwenkenbecher P, Konen FF, Wurster U, Witte T, Gingele S, Sühs K‑W, et al. Reiber’s diagram for kappa free light chains: the new standard for assessing intrathecal synthesis? Diagnostics. 2019;9(4):194.PubMedCentralCrossRef
46.
Zurück zum Zitat Schwenkenbecher P, Konen FF, Wurster U, Jendretzky KF, Gingele S, Sühs K‑W, et al. The persisting significance of oligoclonal bands in the dawning era of kappa free light chains for the diagnosis of multiple sclerosis. Int J Mol Sci. 2018;19(12):3796.PubMedCentralCrossRef Schwenkenbecher P, Konen FF, Wurster U, Jendretzky KF, Gingele S, Sühs K‑W, et al. The persisting significance of oligoclonal bands in the dawning era of kappa free light chains for the diagnosis of multiple sclerosis. Int J Mol Sci. 2018;19(12):3796.PubMedCentralCrossRef
47.
Zurück zum Zitat Gaetani L, Di Carlo M, Brachelente G, Valletta F, Eusebi P, Mancini A, et al. Cerebrospinal fluid free light chains compared to oligoclonal bands as biomarkers in multiple sclerosis. J Neuroimmunol. 2020;339:577108.PubMedCrossRef Gaetani L, Di Carlo M, Brachelente G, Valletta F, Eusebi P, Mancini A, et al. Cerebrospinal fluid free light chains compared to oligoclonal bands as biomarkers in multiple sclerosis. J Neuroimmunol. 2020;339:577108.PubMedCrossRef
48.
Zurück zum Zitat Menéndez-Valladares P, García-Sánchez MI, Cuadri Benítez P, Lucas M, Adorna Martínez M, Carranco Galán V, et al. Free kappa light chains in cerebrospinal fluid as a biomarker to assess risk conversion to multiple sclerosis. Mult Scler J. 2015;1:2055217315620935. Menéndez-Valladares P, García-Sánchez MI, Cuadri Benítez P, Lucas M, Adorna Martínez M, Carranco Galán V, et al. Free kappa light chains in cerebrospinal fluid as a biomarker to assess risk conversion to multiple sclerosis. Mult Scler J. 2015;1:2055217315620935.
49.
Zurück zum Zitat Salavisa M, Paixão P, Ladeira AF, Mendes A, Correia AS, Viana JF, et al. Prognostic value of kappa free light chains determination in first-ever multiple sclerosis relapse. J Neuroimmunol. 2020;347:577355.PubMedCrossRef Salavisa M, Paixão P, Ladeira AF, Mendes A, Correia AS, Viana JF, et al. Prognostic value of kappa free light chains determination in first-ever multiple sclerosis relapse. J Neuroimmunol. 2020;347:577355.PubMedCrossRef
50.
Zurück zum Zitat Vecchio D, Crespi I, Virgilio E, Naldi P, Campisi MP, Serino R, et al. Kappa free light chains could predict early disease course in multiple sclerosis. Mult Scler Relat Disord. 2019;30:81–4.PubMedCrossRef Vecchio D, Crespi I, Virgilio E, Naldi P, Campisi MP, Serino R, et al. Kappa free light chains could predict early disease course in multiple sclerosis. Mult Scler Relat Disord. 2019;30:81–4.PubMedCrossRef
51.
Zurück zum Zitat Presslauer S, Milosavljevic D, Huebl W, Parigger S, Schneider-Koch G, Bruecke T. Kappa free light chains: diagnostic and prognostic relevance in MS and CIS. Plos One. 2014;9(2):e89945.PubMedPubMedCentralCrossRef Presslauer S, Milosavljevic D, Huebl W, Parigger S, Schneider-Koch G, Bruecke T. Kappa free light chains: diagnostic and prognostic relevance in MS and CIS. Plos One. 2014;9(2):e89945.PubMedPubMedCentralCrossRef
52.
Zurück zum Zitat Berek K, Bsteh G, Auer M, Di Pauli F, Grams A, Milosavljevic D, et al. Kappa free light chains in cerebrospinal fluid predict early multiple sclerosis disease activity. Neurol Neuroimmunol Neuroinflamm. 2021;8(4):e1005.PubMedPubMedCentralCrossRef Berek K, Bsteh G, Auer M, Di Pauli F, Grams A, Milosavljevic D, et al. Kappa free light chains in cerebrospinal fluid predict early multiple sclerosis disease activity. Neurol Neuroimmunol Neuroinflamm. 2021;8(4):e1005.PubMedPubMedCentralCrossRef
53.
Zurück zum Zitat Reiber H, Zeman D, Kušnierová P, Mundwiler E, Bernasconi L. Diagnostic relevance of free light chains in cerebrospinal fluid—the hyperbolic reference range for reliable data interpretation in quotient diagrams. Clin Chim Acta. 2019;497:153–62.PubMedCrossRef Reiber H, Zeman D, Kušnierová P, Mundwiler E, Bernasconi L. Diagnostic relevance of free light chains in cerebrospinal fluid—the hyperbolic reference range for reliable data interpretation in quotient diagrams. Clin Chim Acta. 2019;497:153–62.PubMedCrossRef
54.
Zurück zum Zitat Makshakov G, Nazarov V, Kochetova O, Surkova E, Lapin S, Evdoshenko E. Diagnostic and prognostic value of the cerebrospinal fluid concentration of immunoglobulin free light chains in clinically isolated syndrome with conversion to multiple sclerosis. Plos One. 2015;10(11):e143375.PubMedPubMedCentralCrossRef Makshakov G, Nazarov V, Kochetova O, Surkova E, Lapin S, Evdoshenko E. Diagnostic and prognostic value of the cerebrospinal fluid concentration of immunoglobulin free light chains in clinically isolated syndrome with conversion to multiple sclerosis. Plos One. 2015;10(11):e143375.PubMedPubMedCentralCrossRef
55.
Zurück zum Zitat Senel M, Tumani H, Lauda F, Presslauer S, Mojib-Yezdani R, Otto M, et al. Cerebrospinal fluid immunoglobulin kappa light chain in clinically isolated syndrome and multiple sclerosis. Plos One. 2014;9(4):e88680.PubMedPubMedCentralCrossRef Senel M, Tumani H, Lauda F, Presslauer S, Mojib-Yezdani R, Otto M, et al. Cerebrospinal fluid immunoglobulin kappa light chain in clinically isolated syndrome and multiple sclerosis. Plos One. 2014;9(4):e88680.PubMedPubMedCentralCrossRef
56.
Zurück zum Zitat Zeman D, Kušnierová P, Bartoš V, Hradílek P, Kurková B, Zapletalová O. Quantitation of free light chains in the cerebrospinal fluid reliably predicts their intrathecal synthesis. Ann Clin Biochem. 2016;53(Pt 1):174–6.PubMedCrossRef Zeman D, Kušnierová P, Bartoš V, Hradílek P, Kurková B, Zapletalová O. Quantitation of free light chains in the cerebrospinal fluid reliably predicts their intrathecal synthesis. Ann Clin Biochem. 2016;53(Pt 1):174–6.PubMedCrossRef
57.
Zurück zum Zitat Duranti F, Pieri M, Centonze D, Buttari F, Bernardini S, Dessi M. Determination of κFLC and κ Index in cerebrospinal fluid: a valid alternative to assess intrathecal immunoglobulin synthesis. J Neuroimmunol. 2013;263(1–2):116–20.PubMedCrossRef Duranti F, Pieri M, Centonze D, Buttari F, Bernardini S, Dessi M. Determination of κFLC and κ Index in cerebrospinal fluid: a valid alternative to assess intrathecal immunoglobulin synthesis. J Neuroimmunol. 2013;263(1–2):116–20.PubMedCrossRef
58.
Zurück zum Zitat Vasilj M, Kes VB, Vrkic N, Vukasovic I. Relevance of KFLC quantification to differentiate clinically isolated syndrome from multiple sclerosis at clinical onset. Clin Neurol Neurosurg. 2018;174:220–9.PubMedCrossRef Vasilj M, Kes VB, Vrkic N, Vukasovic I. Relevance of KFLC quantification to differentiate clinically isolated syndrome from multiple sclerosis at clinical onset. Clin Neurol Neurosurg. 2018;174:220–9.PubMedCrossRef
60.
Zurück zum Zitat Cavalla P, Caropreso P, Limoncelli S, Bosa C, Pasanisi MB, Schillaci V, et al. Kappa free light chains index in the differential diagnosis of multiple sclerosis from neuromyelitis optica spectrum disorders and other immune-mediated central nervous system disorders. J Neuroimmunol. 2020;339:577122.PubMedCrossRef Cavalla P, Caropreso P, Limoncelli S, Bosa C, Pasanisi MB, Schillaci V, et al. Kappa free light chains index in the differential diagnosis of multiple sclerosis from neuromyelitis optica spectrum disorders and other immune-mediated central nervous system disorders. J Neuroimmunol. 2020;339:577122.PubMedCrossRef
61.
Zurück zum Zitat Scalfari A, Neuhaus A, Degenhardt A, Rice GP, Muraro PA, Daumer M, et al. The natural history of multiple sclerosis: a geographically based study 10: relapses and long-term disability. Brain. 2010;133(Pt 7):1914–29.PubMedPubMedCentralCrossRef Scalfari A, Neuhaus A, Degenhardt A, Rice GP, Muraro PA, Daumer M, et al. The natural history of multiple sclerosis: a geographically based study 10: relapses and long-term disability. Brain. 2010;133(Pt 7):1914–29.PubMedPubMedCentralCrossRef
62.
Zurück zum Zitat Tremlett H, Yousefi M, Devonshire V, Rieckmann P, Zhao Y, UBC Neurologists. Impact of multiple sclerosis relapses on progression diminishes with time. Neurology. 2009;73(20):1616–23.PubMedPubMedCentralCrossRef Tremlett H, Yousefi M, Devonshire V, Rieckmann P, Zhao Y, UBC Neurologists. Impact of multiple sclerosis relapses on progression diminishes with time. Neurology. 2009;73(20):1616–23.PubMedPubMedCentralCrossRef
63.
Zurück zum Zitat Kappos L, Polman CH, Freedman MS, Edan G, Hartung HP, Miller DH, et al. Treatment with interferon beta-1b delays conversion to clinically definite and McDonald MS in patients with clinically isolated syndromes. Neurology. 2006;67(7):1242–9.PubMedCrossRef Kappos L, Polman CH, Freedman MS, Edan G, Hartung HP, Miller DH, et al. Treatment with interferon beta-1b delays conversion to clinically definite and McDonald MS in patients with clinically isolated syndromes. Neurology. 2006;67(7):1242–9.PubMedCrossRef
64.
Zurück zum Zitat Comi G, Filippi M, Barkhof F, Durelli L, Edan G, Fernandez O, et al. Effect of early interferon treatment on conversion to definite multiple sclerosis: a randomised study. Lancet. 2001;357(9268):1576–82.PubMedCrossRef Comi G, Filippi M, Barkhof F, Durelli L, Edan G, Fernandez O, et al. Effect of early interferon treatment on conversion to definite multiple sclerosis: a randomised study. Lancet. 2001;357(9268):1576–82.PubMedCrossRef
65.
Zurück zum Zitat Jacobs LD, Beck RW, Simon JH, Kinkel RP, Brownscheidle CM, Murray TJ, et al. Intramuscular interferon beta-1a therapy initiated during a first demyelinating event in multiple sclerosis. CHAMPS Study Group. N Engl J Med. 2000;343(13):898–904.PubMedCrossRef Jacobs LD, Beck RW, Simon JH, Kinkel RP, Brownscheidle CM, Murray TJ, et al. Intramuscular interferon beta-1a therapy initiated during a first demyelinating event in multiple sclerosis. CHAMPS Study Group. N Engl J Med. 2000;343(13):898–904.PubMedCrossRef
66.
Zurück zum Zitat Konen FF, Wurster U, Witte T, Jendretzky KF, Gingele S, Tumani H, et al. The impact of immunomodulatory treatment on kappa free light chains as biomarker in neuroinflammation. Cells. 2020;9(4):842.PubMedCentralCrossRef Konen FF, Wurster U, Witte T, Jendretzky KF, Gingele S, Tumani H, et al. The impact of immunomodulatory treatment on kappa free light chains as biomarker in neuroinflammation. Cells. 2020;9(4):842.PubMedCentralCrossRef
Metadaten
Titel
Cerebrospinal fluid kappa free light chains as biomarker in multiple sclerosis—from diagnosis to prediction of disease activity
verfasst von
Harald Hegen, PD, MD, PhD
Klaus Berek
Florian Deisenhammer
Publikationsdatum
08.02.2022
Verlag
Springer Vienna
Erschienen in
Wiener Medizinische Wochenschrift / Ausgabe 15-16/2022
Print ISSN: 0043-5341
Elektronische ISSN: 1563-258X
DOI
https://doi.org/10.1007/s10354-022-00912-7

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