Biochemical biomarkers for multiple sclerosis

INTRODUCTION

Multiple sclerosis (MS) is the most frequent demyelinating disease of the central nervous system. Although there is currently no definite cure for MS, new therapies have recently been developed based on a continuous search for new biomarkers.

DEVELOPMENT

MS diagnosis relies on the integration of clinical, imaging and laboratory findings as there is still no singlepathognomonicclinical feature or diagnostic laboratory biomarker. The most commonly laboratory test used is the presence of immunoglobulin G oligoclonal bands (OCB) in cerebrospinal fluid of MS patients. This test is now included in the 2017 McDonald criteria as a biomarker of dissemination in time. Nevertheless, there are other biomarkers currently in use such as kappa free light chain, which has shown higher sensitivity and specificity for MS diagnosis than OCB. In addition, other potential laboratory tests involved in neuronal damage, demyelination and/or inflammation could be used for detecting MS.

CONCLUSIONS

CSF and serum biomarkers have been reviewed for their use in MS diagnosis and prognosis to stablish an accurate and prompt MS diagnosis, crucial to implement an adequate treatment and to optimize clinical outcomes over time.

Diagnostic significance of IgG and albumin indices versus oligoclonal band types in demyelinating disorders

AIMS

The laboratory diagnosis of demyelinating inflammatory disorders (DIDs) relies on both intrathecal oligoclonal band (OCB) positivity and IgG index. Although OCB typing remains the gold-standard test for DIDs, it can be laborious and ambiguous, complicating diagnostics, and unduly increasing diagnostic time. We examined whether serum or cerebrospinal fluid (CSF) parameters can classify OCB types and, thus, be used as a replacement test to standard OCB typing.

METHODS

We retrospectively analysed >1000 prospectively collected samples of patients with DIDs and quantified albumin and IgG levels in the CSF and serum. We determined OCB types by isoelectric focusing combined with immunofixation and evaluated the diagnostic accuracies of IgG and albumin indices in discriminating OCB types by receiver operating characteristic curves and multinomial regression.

RESULTS

An IgG index cut-off of 0.589 differentiated types 2/3 from types 1/4 (area under the curve 0.780, 95% CI 0.761 to 0.812, p<0.001; specificity: 71.10%, sensitivity: 73.45%). Albumin quotient cut-off values of 6.625 and of 6.707 discriminated type 1 from type 4 and type 2 from type 3, respectively (specificity: <55%, sensitivity: <75%). Female sex, age, IgG index, CSF IgG and serum albumin were associated with different OCB types.

CONCLUSIONS

Our study reveals that IgG and albumin index can differentiate OCB types with adequate accuracy, especially if refined by age and gender.

Recent advances in development of nanomedicines for multiple sclerosis diagnosis

Multiple sclerosis (MS) is a neurodegenerative disease with a high morbidity and disease burden. It is characterized by the loss of the myelin sheath, resulting in the disruption of neuron electrical signal transmissions and sensory and motor ability deficits. The diagnosis of MS is crucial to its management, but the diagnostic sensitivity and specificity are always a challenge. To overcome this challenge, nanomedicines have recently been employed to aid the diagnosis of MS with an improved diagnostic efficacy. Advances in nanomedicine-based contrast agents in magnetic resonance imaging scanning of MS lesions, and nanomedicine-derived sensors for detecting biomarkers in the cerebrospinal fluid biopsy, or analyzing the composition of exhaled breath gas, have demonstrated the potential of using nanomedicines in the accurate diagnosis of MS. This review aims to provide an overview of recent advances in the application of nanomedicines for the diagnosis of MS and concludes with perspectives of using nanomedicines for the development of safe and effective MS diagnostic nanotools.

Diagnostic relevance of free light chains in cerebrospinal fluid - The hyperbolic reference range for reliable data interpretation in quotient diagrams

BACKGROUND

Free light chains, type kappa (FLC-K), in cerebrospinal fluid (CSF) were compared to oligoclonal IgG in many studies for sensitive detection of immune reactions in brain. The missing consensus about CSF data interpretation prevents reliable conclusions. This can be overcome by a theory-based hyperbolic reference range in CSF/serum quotient diagrams.

METHODS

Mean Quotients for FLC-K, Q_Kappa, and albumin, QAlb, of grouped, biochemically defined controls (N = 433) are fitted with the hyperbolic function Q_Kappa(mean) = a/b (QAlb² + b²)^0.5 - c by a generally applicable procedure excluding outliers.

RESULTS

With Q_Kappa(mean), the coefficient of variation CV (22.5%) and the reference range (Q_Kappa(mean) ± 3 CV) we got the discrimination line Q_Kappa(lim) = (3.27(QAlb² + 33)^0.5-8.2) ×10^-3 in a FLC-K Reibergram. Intrathecal FLC-K was found in 8% of another control group without OCB (N = 388) but was missed in 7% of patients with definite Multiple sclerosis (N = 95). In MS the mean intrathecal fraction was threefold larger for FLC-K (95%) compared to total IgG (36%). Similar mean quantities of intrathecal FLC-K contradict an immunological conversion between a Clinically isolated syndrome and MS.

DISCUSSION

The hyperbolic reference range is superior to linear FLC-K Index (10 to 15% false negatives) and exponential curves (30% false positive interpretations for controls) in the analytical range of MS data, with excellent data fit for up to ten-fold larger QAlb values. Dynamics of the small molecule FLC-K contribute to the understanding of molecular size dependent barrier functions.