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In this retrospective, monocentric cohort study, we tested if an intrathecal free light chain kappa (FLC-k) synthesis reflects not only an IgG but also IgA and IgM synthesis. We also analysed if FLC-k can help to distinguish between an inflammatory process and a blood contamination of cerebrospinal fluid (CSF). A total of 296 patient samples were identified and acquired from patients of the department of Neurology, University Medicine Greifswald (Germany). FLC-k were analysed in paired CSF and serum samples using the Siemens FLC-k kit. To determine an intrathecal FLC-k and immunoglobulin (Ig) A/-M-synthesis we analysed CSF/serum quotients in quotient diagrams, according to Reiber et al. Patient samples were grouped into three cohorts: cohort I (n = 41), intrathecal IgA and/or IgM synthesis; cohort II (n = 16), artificial blood contamination; and the control group (n = 239), no intrathecal immunoglobulin synthesis. None of the samples had intrathecal IgG synthesis, as evaluated with quotient diagrams or oligoclonal band analysis. In cohort I, 98% of patient samples presented an intrathecal synthesis of FLC-k. In cohort II, all patients lacked intrathecal FLC-k synthesis. In the control group, 6.5% presented an intrathecal synthesis of FLC-k. The data support the concept that an intrathecal FLC-k synthesis is independent of the antibody class produced. In patients with an artificial intrathecal Ig synthesis due to blood contamination, FLC-k synthesis is lacking. Thus, additional determination of FLC-k in quotient diagrams helps to discriminate an inflammatory process from a blood contamination of CSF.
A New Laboratory Workflow Integrating the Free Light Chains Kappa Quotient into Routine CSF Analysis
(2022)
We performed this cohort study to test whether further analysis of intrathecal inflammation can be omitted if the free light chain kappa (FLCκ) quotient is within the reference range in the corresponding quotient diagram. FLCκ concentrations were measured in serum and cerebrospinal fluid (CSF) samples. The intrathecal fraction (IF) of FLCκ was calculated in relation to the hyperbolic reference range. 679 patient samples were used as a discovery cohort (DC). The sensitivity and negative predictive value (NPV) of the FLCκ-IF for the detection of an intrathecal humoral immune response (CSF-specific OCB and/or IF IgG/A/M > 0%) was determined. Based on these data, a diagnostic algorithm was developed and prospectively validated in an independent validation cohort (VC, n = 278). The sensitivity of the FLCκ-IF was 98% in the DC and 97% in the VC with a corresponding NPV of 99%. The use of the FLCκ-IF as a first line analysis would have reduced the Ig and OCB analysis by 62% in the DC and 74% in the VC. The absence of a FLCκ-IF predicts the absence of a humoral intrathecal immune response with a very high NPV of 99%. Thus, integration of our proposed algorithm into routine CSF laboratory analysis could help to reduce analytical efforts.
Microbial metabolites measured using NMR may serve as markers for physiological or pathological host–microbe interactions and possibly mediate the beneficial effects of microbiome diversity. Yet, comprehensive analyses of gut microbiome data and the urine NMR metabolome from large general population cohorts are missing. Here, we report the associations between gut microbiota abundances or metrics of alpha diversity, quantified from stool samples using 16S rRNA gene sequencing, with targeted urine NMR metabolites measures from 951 participants of the Study of Health in Pomerania (SHIP). We detected significant genus–metabolite associations for hippurate, succinate, indoxyl sulfate, and formate. Moreover, while replicating the previously reported association between hippurate and measures of alpha diversity, we identified formate and 4-hydroxyphenylacetate as novel markers of gut microbiome alpha diversity. Next, we predicted the urinary concentrations of each metabolite using genus abundances via an elastic net regression methodology. We found profound associations of the microbiome-based hippurate prediction score with markers of liver injury, inflammation, and metabolic health. Moreover, the microbiome-based prediction score for hippurate completely mediated the clinical association pattern of microbial diversity, hinting at a role of benzoate metabolism underlying the positive associations between high alpha diversity and healthy states. In conclusion, large-scale NMR urine metabolomics delivered novel insights into metabolic host–microbiome interactions, identifying pathways of benzoate metabolism as relevant candidates mediating the beneficial health effects of high microbial alpha diversity.