Dynamics and prognostic value of serum neurofilament light chain in Guillain-Barré syndrome.

BACKGROUND: Neurofilament light chain (NfL) is a biomarker for axonal damage in several neurological disorders. We studied the longitudinal changes in serum NfL in patients with Guillain-Barré syndrome (GBS) in relation to disease severity, electrophysiological subtype, treatment response, and prognosis. METHODS: We included patients with GBS who participated in a double-blind, randomised, placebo-controlled trial that evaluated the effects of a second course of intravenous immunoglobulin (IVIg) on clinical outcomes. Serum NfL levels were measured before initiation of treatment and at one, two, four, and twelve weeks using a Simoa HD-X Analyzer. Serum NfL dynamics were analysed using linear mixed-effects models. Logistic regression was employed to determine the associations of serum NfL with clinical outcome and the prognostic value of serum NfL after correcting for known prognostic markers included in the modified Erasmus GBS Outcome Score (mEGOS). FINDINGS: NfL levels were tested in serum from 281 patients. Serum NfL dynamics were associated with disease severity and electrophysiological subtype. Strong associations were found between high levels of serum NfL at two weeks and inability to walk unaided at four weeks (OR = 1.74, 95% CI = 1.27-2.45), and high serum NfL levels at four weeks and inability to walk unaided at 26 weeks (OR = 2.79, 95% CI = 1.72-4.90). Baseline serum NfL had the most significant prognostic value for ability to walk, independent of predictors included in the mEGOS. The time to regain ability to walk unaided was significantly longer for patients with highest serum NfL levels at baseline (p = 0.0048) and week 2 (p < 0.0001). No differences in serum NfL were observed between patients that received a second IVIg course vs. IVIg and placebo. INTERPRETATION: Serum NfL levels are associated with disease severity, axonal involvement, and poor outcome in GBS. Serum NfL potentially represents a biomarker to monitor neuronal damage in GBS and an intermediate endpoint to evaluate the effects of treatment. FUNDING: Prinses Beatrix Spierfonds W.OR19-24.

Targeted multiomics in childhood-onset SLE reveal distinct biological phenotypes associated with disease activity: results from an explorative study.

OBJECTIVE: To combine targeted transcriptomic and proteomic data in an unsupervised hierarchical clustering method to stratify patients with childhood-onset SLE (cSLE) into similar biological phenotypes, and study the immunological cellular landscape that characterises the clusters. METHODS: Targeted whole blood gene expression and serum cytokines were determined in patients with cSLE, preselected on disease activity state (at diagnosis, Low Lupus Disease Activity State (LLDAS), flare). Unsupervised hierarchical clustering, agnostic to disease characteristics, was used to identify clusters with distinct biological phenotypes. Disease activity was scored by clinical SELENA-SLEDAI (Safety of Estrogens in Systemic Lupus Erythematosus National Assessment-Systemic Lupus Erythematosus Disease Activity Index). High-dimensional 40-colour flow cytometry was used to identify immune cell subsets. RESULTS: Three unique clusters were identified, each characterised by a set of differentially expressed genes and cytokines, and by disease activity state: cluster 1 contained primarily patients in LLDAS, cluster 2 contained mainly treatment-naïve patients at diagnosis and cluster 3 contained a mixed group of patients, namely in LLDAS, at diagnosis and disease flare. The biological phenotypes did not reflect previous organ system involvement and over time, patients could move from one cluster to another. Healthy controls clustered together in cluster 1. Specific immune cell subsets, including CD11c+ B cells, conventional dendritic cells, plasmablasts and early effector CD4+ T cells, differed between the clusters. CONCLUSION: Using a targeted multiomic approach, we clustered patients into distinct biological phenotypes that are related to disease activity state but not to organ system involvement. This supports a new concept where choice of treatment and tapering strategies are not solely based on clinical phenotype but includes measuring novel biological parameters.

Population Pharmacokinetic Modelling of Intravenous Immunoglobulin Treatment in Patients with Guillain-Barré Syndrome.

BACKGROUND AND OBJECTIVE: Intravenous immunoglobulin (IVIg) at a standard dosage is the treatment of choice for Guillain-Barré syndrome. The pharmacokinetics, however, is highly variable between patients, and a rapid clearance of IVIg is associated with poor recovery. We aimed to develop a model to predict the pharmacokinetics of a standard 5-day IVIg course (0.4 g/kg/day) in patients with Guillain-Barré syndrome. METHODS: Non-linear mixed-effects modelling software (NONMEM®) was used to construct a pharmacokinetic model based on a model-building cohort of 177 patients with Guillain-Barré syndrome, with a total of 589 sequential serum samples tested for total immunoglobulin G (IgG) levels, and evaluated on an independent validation cohort that consisted of 177 patients with Guillain-Barré syndrome with 689 sequential serum samples. RESULTS: The final two-compartment model accurately described the daily increment in serum IgG levels during a standard IVIg course; the initial rapid fall and then a gradual decline to steady-state levels thereafter. The covariates that increased IgG clearance were a more severe disease (as indicated by the Guillain-Barré syndrome disability score) and concomitant methylprednisolone treatment. When the current dosing regimen was simulated, the percentage of patients who reached a target ∆IgG > 7.3 g/L at 2 weeks decreased from 74% in mildly affected patients to only 33% in the most severely affected and mechanically ventilated patients (Guillain-Barré syndrome disability score of 5). CONCLUSIONS: This is the first population-pharmacokinetic model for standard IVIg treatment in Guillain-Barré syndrome. The model provides a new tool to predict the pharmacokinetics of alternative regimens of IVIg in Guillain-Barré syndrome to design future trials and personalise treatment.

Gene signature fingerprints stratify SLE patients in groups with similar biological disease profiles: a multicentre longitudinal study.

OBJECTIVES: Clinical phenotyping and predicting treatment responses in SLE patients is challenging. Extensive blood transcriptional profiling has identified various gene modules that are promising for stratification of SLE patients. We aimed to translate existing transcriptomic data into simpler gene signatures suitable for daily clinical practice. METHODS: Real-time PCR of multiple genes from the IFN M1.2, IFN M5.12, neutrophil (NPh) and plasma cell (PLC) modules, followed by a principle component analysis, was used to identify indicator genes per gene signature. Gene signatures were measured in longitudinal samples from two childhood-onset SLE cohorts (n = 101 and n = 34, respectively), and associations with clinical features were assessed. Disease activity was measured using Safety of Estrogen in Lupus National Assessment (SELENA)-SLEDAI. Cluster analysis subdivided patients into three mutually exclusive fingerprint-groups termed (1) all-signatures-low, (2) only IFN high (M1.2 and/or M5.12) and (3) high NPh and/or PLC. RESULTS: All gene signatures were significantly associated with disease activity in cross-sectionally collected samples. The PLC-signature showed the highest association with disease activity. Interestingly, in longitudinally collected samples, the PLC-signature was associated with disease activity and showed a decrease over time. When patients were divided into fingerprints, the highest disease activity was observed in the high NPh and/or PLC group. The lowest disease activity was observed in the all-signatures-low group. The same distribution was reproduced in samples from an independent SLE cohort. CONCLUSIONS: The identified gene signatures were associated with disease activity and were indicated to be suitable tools for stratifying SLE patients into groups with similar activated immune pathways that may guide future treatment choices.

Novel approach to monitor intravenous immunoglobulin pharmacokinetics in humans using polymorphic determinants in IgG1 constant domains.

Clinical efficacy of intravenous immunoglobulin treatment (IVIg) is related to its pharmacokinetic (PK) profile. Its usual evaluation, by measuring serum total IgG levels, is imprecise, because IVIg cannot be distinguished from endogenous IgG. We developed ELISAs to specifically monitor the PK of IVIg using the polymorphic determinants G1m(a), G1m(x), and G1m(f). The specificity of the IgG1 allotype assays was sufficient to determine IVIg concentrations as low as 0.1 mg/mL in sera from individuals not expressing the respective markers. IVIg was quantified in posttreatment serum from patients with Guillain-Barré syndrome (GBS) by measuring IgG1 allotypes not expressed endogenously. After serotyping, 27/28 GBS patients were found eligible for IVIg monitoring using one or two genetic markers. In 17 cases, IVIg levels could be determined by both anti-G1m(a) and anti-G1m(x) measurement, showing significant correlation. Longitudinal monitoring of IVIg PK in seven GBS patients showed potential differences in clearance of total IgG versus IVIg-derived IgG, highlighting that total IgG measurements may not accurately reflect IVIg PK. To summarize, anti-IgG1 allotype assays can discriminate between endogenous IgG and therapeutic polyclonal IgG. These assays will be an important tool to better understand the variability in IVIg PK and treatment response of all patients treated with IVIg.