Neurofilament light, glial fibrillary acidic protein, and tau in a regional epilepsy cohort: High plasma levels are rare but related to seizures

OBJECTIVE: Higher levels of biochemical blood markers of brain injury have been described immediately after tonic-clonic seizures and in drug-resistant epilepsy, but the levels of such markers in epilepsy in general have not been well characterized. We analyzed neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and tau in a regional hospital-based epilepsy cohort and investigated what proportion of patients have levels suggesting brain injury, and whether certain epilepsy features are associated with high levels. METHODS: Biomarker levels were measured in 204 patients with an epilepsy diagnosis participating in a prospective regional biobank study, with age and sex distribution correlating closely to that of all patients seen for epilepsy in the health care region. Absolute biomarker levels were assessed between two patient groups: patients reporting seizures within the 2 months preceding inclusion and patients who did not have seizures for more than 1 year. We also assessed the proportion of patients with above-normal levels of NfL. RESULTS: NfL and GFAP, but not tau, increased with age. Twenty-seven patients had abnormally high levels of NfL. Factors associated with such levels were recent seizures (p = .010) and epileptogenic lesion on radiology (p = .001). Levels of NfL (p = .006) and GFAP (p = .032) were significantly higher in young patients (1 year. NfL and GFAP correlated weakly with the number of days since last seizure (NfL: rs  = -.228, p = .007; GFAP: rs  = -.167, p = .048) in young patients. NfL also correlated weakly with seizure frequency in the last 2 months (rs  = .162, p = .047). SIGNIFICANCE: Most patients with epilepsy do not have biochemical evidence of brain injury. The association with seizures merits further study; future studies should aim for longitudinal sampling and examine whether individual variations in NfL or GFAP levels could reflect seizure activity

High levels of kappa free light chain synthesis predict cognitive decline in relapsing-remitting multiple sclerosis

BACKGROUND: Evolving evidence suggests that measurement of cerebrospinal fluid (CSF) kappa free light chain (KFLC) synthesis has high diagnostic sensitivity and specificity for multiple sclerosis (MS), but its prognostic ability is less investigated. The usefulness of KFLC in predicting cognitive impairment (CI) is still unknown. METHODS: In a monocentric longitudinal retrospecitve cohort study, KFLC-index ([CSF KFLC/serum KFLC]/[CSF albumin/serum albumin]) measured by latex-enhanced immunonephelometry was prospectively determined as part of the diagnostic workup in patients with early relapsing-remitting MS (RRMS, n=77). The ability of KFLC-index to predict information processing speed (IPS) worsening as assessed with the symbol digit modalities test (SDMT) was investigated in univariable and multivariable models. RESULTS: In patients with KFLC-index>100 (n=31), 11 subjects (35.5%) showed reduced SDMT scores by ≥8 points at follow-up (mean follow-up time 7.3 ± 2.6 years), compared with their baseline scores (p=0.01). Baseline KFLC-index>100 was strongly associated with a higher hazard of SDMT score reduction at follow-up (adjusted hazard ratio 10.5, 95% confidence interval 2.2-50.8, p=0.003; median time to SDMT reduction 7 years). CONCLUSION: Intrathecal KFLC synthesis has become an attractive diagnostic tool for MS. We show for the first time that in a real-world setting of early RRMS, KFLC-index predicted cognitive decline. Whether this predictive ability of KFLC-index also concerns other cognitive domains than IPS, warrants further investigations

Increased intrathecal neurofilament light and immunoglobulin M predict severe disability in relapsing-remitting multiple sclerosis

Background: Emerging evidence supports that determination of intrathecal immunoglobulin M (IgM) synthesis (ITMS) and neurofilament light (NfL) concentration in cerebrospinal fluid (CSF) may be clinically useful as disease severity biomarkers in relapsing-remitting multiple sclerosis (RRMS). Methods: Monocentric observational longitudinal cohort study in which prospectively collected data were retrospectively retrieved. Included were patients with RRMS (n=457) who had a diagnostic investigation including analysis of ITMS and CSF neurofilament light (cNfL). ITMS was calculated with the linear index formula, the intrathecal fraction of IgM according to Reiber (IgMIF), and by qualitative determination of oligoclonal IgM bands (OCMB). Univariable and multivariable models were performed to predict Evidence of Disease Activity-3 (EDA-3) status within 24 months from onset, and the risk of Expanded Disability Status Score (EDSS) ≥3 and ≥6. Results: All investigated methods to calculate ITMS significantly predicted evidence of disease activity (EDA-3) within 24 months. IgMIF>0% showed the strongest association with EDA-3 status (adjusted hazard ratio [aHR] 3.7, 95%CI 2.7-5, p0.1 or OCMB with increased cNfL were strong predictors of EDSS≥3 (for cNfL+/IgM-index+: aHR 4.6, 95%CI 2.6-8.2, p<0.001) and EDSS≥6 (aHR 8.2, 95%CI 2.3-30, p<0.001). Conclusions: In a real-world setting, ITMS was a useful biomarker in early RRMS to predict disabling MS and its prognostic value was even stronger in combination with cNfL. Our data suggest that determination of ITMS and cNfL should be included in the diagnostic work-up of RRMS for prognostic purposes and in decisions of disease-modifying therapy

Intrathecal kappa free light chain synthesis is associated with worse prognosis in relapsing-remitting multiple sclerosis

BACKGROUND: While kappa free light chain (KFLC) index has become a useful diagnostic biomarker in multiple sclerosis (MS), its prognostic properties are less explored. B cells play a crucial role in MS pathogenesis, but the impact from increased intrathecal production of immunoglobulins and KFLC remains to be determined. Recently, it has become evident that insidious worsening is not confined to progressive MS but is also common in relapsing-remitting MS (RRMS), a feature known as progression independent of relapse activity (PIRA). METHODS: We retrospectively identified 131 patients with clinically isolated syndrome or early RRMS who had determined KFLC index as part of their diagnostic workup. Demographic and clinical data were extracted from the Swedish MS registry. Associations of baseline KFLC index with evidence of disease activity (EDA) and PIRA were investigated in multivariable cox proportional hazards regression models. RESULTS: KFLC index was significantly higher in PIRA (median 148.5, interquartile range [IQR] 106.9-253.5) compared with non-PIRA (78.26, IQR 28.93-186.5, p = 0.009). In a multivariable cox regression model adjusted for confounders, KFLC index emerged as an independent risk factor for PIRA (adjusted hazard ratio [aHR] 1.005, 95% confidence interval [CI] 1.002-1.008, p = 0.002). Dichotomized by the cut-off value KFLC index > 100, patients with KFLC index > 100 had an almost fourfold increase in the risk for developing PIRA. KFLC index was also predictive of evidence of disease activity during follow-up. CONCLUSIONS: Our data indicate that high KFLC index at baseline is predictive of PIRA, EDA-3, and overall worse prognosis in MS

No increase of serum neurofilament light in relapsing-remitting multiple sclerosis patients switching from standard to extended-interval dosing of natalizumab

BACKGROUND: Accumulating evidence supports the efficacy of administering natalizumab (NZ) with extended-interval dosing (EID) in patients with relapsing-remitting multiple sclerosis (RRMS). OBJECTIVES: We switched NZ dosing from 4-week to 6-week intervals in patients with RRMS, and investigated the effect on serum neurofilament light chain (sNfL) concentrations. METHODS: We included two cohorts of patients with RRMS treated with NZ: one received the standard-interval dosing (4 weeks) at baseline, and were switched to 6-week intervals (EID4-6, N = 45). The other cohort received EID (5- or 6-week intervals) both at baseline and during follow-up (EID5/6, N = 25). Serum samples were collected in the EID4-6 cohort at every NZ infusion, for 12 months. The primary outcome was the change in sNfL concentrations after switching to EID. RESULTS: The baseline mean sNfL concentration in the EID4-6 cohort was 10.5 ng/L (standard deviation (SD) = 6.1), and it remained unchanged at 12 months. Moreover, individual sNfL concentrations did not change significantly after extending the NZ dosing intervals. In addition, the EID4-6 and EID5/6 cohorts had similar baseline sNfL concentrations. CONCLUSION: We concluded that extending the NZ dosing interval did not increase axonal damage, as determined with sNfL, in patients with RRMS

Frequency of Mycobacterium tuberculosis-specific CD8+T-cells in the course of anti-tuberculosis treatment

Anti-tuberculosis drug treatment is known to affect the number, phenotype, and effector functionality of antigen-specific T-cells. In order to objectively gauge Mycobacterium tuberculosis (MTB)-specific CD8+ T-cells at the single-cell level, we developed soluble major histocompatibility complex (MHC) class I multimers/peptide multimers, which allow analysis of antigen-specific T-cells without ex vivo manipulation or functional tests. We constructed 38 MHC class I multimers covering some of the most frequent MHC class I alleles (HLA-A*02:01, A*24:02, A*30:01, A*30:02, A*68:01, B*58:01, and C*07:01) pertinent to a South African or Zambian population, and presenting the following MTB-derived peptides: the early expressed secreted antigens TB10.4 (Rv0288), Ag85B (Rv1886c), and ESAT-6 (Rv3875), as well as intracellular enzymes, i.e., glycosyltransferase 1 (Rv2957), glycosyltransferase 2 (Rv2958c), and cyclopropane fatty acid synthase (Rv0447c). Anti-TB treatment appeared to impact on the frequency of multimer-positive CD8+ T-cells, with a general decrease after 6 months of therapy. Also, a reduction in the total central memory CD8+ T-cell frequencies, as well as the antigen-specific compartment in CD45RA - CCR7+ T-cells was observed. We discuss our findings on the basis of differential dynamics of MTB-specific T-cell frequencies, impact of MTB antigen load on T-cell phenotype, and antigen-specific T-cell responses in tuberculosis. (c) 2015 The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases

Cerebrospinal fluid amyloid precursor protein as a potential biomarker of fatigue in multiple sclerosis: A pilot study

BACKGROUND: Fatigue is the major cause of disability in MS. Fatigue has been suggested to be primary, part of the neurological disease; it can also be secondary to other diseases outside the CNS or exist as a separate comorbidity. The only forms of measurement currently available are through subjective standardized questionnaires, which are not able to identify primary MS-related fatigue. Therefore, there is a need for objective biomarkers of fatigue in MS. This study explored the viability of 17 possible biomarkers of primary fatigue in MS. Our chosen biomarker panel represents the function and health of different parts of the CNS. METHODS: We evaluated 31 MS patients and 17 healthy controls using the Fatigue Severity Scale (FSS) and Insomnia Severity Index (ISI). We assessed clinical parameters and collected CSF from all participants to analyze 17 biomarkers, some of which in multiple targeted sequences, reflecting structural and functional changes in the brain. Based on FSS scores, MS was divided into MS-Fatigue (MS-F, FSS ≥ 4) and MS-NoFatigue (MS-NoF, FSS < 4). RESULTS: MS-F had significantly lower levels of amyloid precursor protein (APP) peptides than MS-NoF (p = 0.005, p = 0.011). The only biomarker correlating with FSS in any group was APP in MS (r = -0.47, -0.52; p = 0.007, 0.002). APP did not correlate with any clinical parameter in MS but correlated with multiple markers. In MS, FSS correlated with the ISI and months since diagnosis. CONCLUSION: Although the mechanisms remain unknown, altered APP metabolism in MS seems to be associated with fatigue. APP should be evaluated as a biomarker of the role of structural MS pathology in the development of fatigue in individual MS patients

Human Leukocyte Antigen Class 1 Phenotype Distribution and Analysis in Persons from Central Uganda with Active Tuberculosis and Latent Mycobacterium tuberculosis Infection

Background: The Ugandan population is heavily affected by infectious diseases and Human leukocyte antigen (HLA) diversity plays a crucial role in the host-pathogen interaction and affects the rates of disease acquisition and outcome. The identification of HLA class 1 alleles and determining which alleles are associated with tuberculosis (TB) outcomes would help in screening individuals in TB endemic areas for susceptibility to TB and to predict resistance or progression to TB which would inevitably lead to better clinical management of TB. Aims: To be able to determine the HLA class 1 phenotype distribution in a Ugandan TB cohort and to establish the relationship between these phenotypes and active and latent TB. Methods: Blood samples were drawn from 32 HIV negative individuals with active TB and 45 HIV negative individuals with latent MTB infection. DNA was extracted from the blood samples and the DNA samples HLA typed by the polymerase chain reaction-sequence specific primer method. The allelic frequencies were determined by direct count. Results: HLA-A*02, A*01, A*74, A*30, B*15, B*58, C*07, C*03 and C*04 were the dominant phenotypes in this Ugandan cohort. There were differences in the distribution of HLA types between the individuals with active TB and the individuals with LTBI with only HLA-A*03 allele showing a statistically significant difference (p=0.0136). However, after FDR computation the corresponding q-value is above the expected proportion of false discoveries (q-value 0.2176). Key findings: We identified a number of HLA class I alleles in a population from Central Uganda which will enable us to carry out a functional characterization of CD8+ T-cell mediated immune responses to MTB. Our results also suggest that there may be a positive association between the HLA-A*03 allele and TB implying that individuals with the HLA-A*03 allele are at a higher risk of developing active TB

Separation of Test-Free Propositional Dynamic Logics over Context-Free Languages

For a class L of languages let PDL[L] be an extension of Propositional Dynamic Logic which allows programs to be in a language of L rather than just to be regular. If L contains a non-regular language, PDL[L] can express non-regular properties, in contrast to pure PDL. For regular, visibly pushdown and deterministic context-free languages, the separation of the respective PDLs can be proven by automata-theoretic techniques. However, these techniques introduce non-determinism on the automata side. As non-determinism is also the difference between DCFL and CFL, these techniques seem to be inappropriate to separate PDL[DCFL] from PDL[CFL]. Nevertheless, this separation is shown but for programs without test operators.Comment: In Proceedings GandALF 2011, arXiv:1106.081

Human Leukocyte Antigen Class 1 Phenotype Distribution and Analysis in Persons from Central Uganda with Active Tuberculosis and Latent Mycobacterium tuberculosis Infection

Background: The Ugandan population is heavily affected by infectious diseases and Human leukocyte antigen (HLA) diversity plays a crucial role in the host-pathogen interaction and affects the rates of disease acquisition and outcome. The identification of HLA class 1 alleles and determining which alleles are associated with tuberculosis (TB) outcomes would help in screening individuals in TB endemic areas for susceptibility to TB and to predict resistance or progression to TB which would inevitably lead to better clinical management of TB. Aims: To be able to determine the HLA class 1 phenotype distribution in a Ugandan TB cohort and to establish the relationship between these phenotypes and active and latent TB. Methods: Blood samples were drawn from 32 HIV negative individuals with active TB and 45 HIV negative individuals with latent MTB infection. DNA was extracted from the blood samples and the DNA samples HLA typed by the polymerase chain reaction-sequence specific primer method. The allelic frequencies were determined by direct count. Results: HLA-A*02, A*01, A*74, A*30, B*15, B*58, C*07, C*03 and C*04 were the dominant phenotypes in this Ugandan cohort. There were differences in the distribution of HLA types between the individuals with active TB and the individuals with LTBI with only HLA-A*03 allele showing a statistically significant difference (p=0.0136). However, after FDR computation the corresponding q-value is above the expected proportion of false discoveries (q-value 0.2176). Key findings: We identified a number of HLA class I alleles in a population from Central Uganda which will enable us to carry out a functional characterization of CD8+ T-cell mediated immune responses to MTB. Our results also suggest that there may be a positive association between the HLA-A*03 allele and TB implying that individuals with the HLA-A*03 allele are at a higher risk of developing active TB