Anti-drug antibodies (ADA) reduce the efficacy of immunotherapies in multiple sclerosis (MS) and are associated with increased disease progression risk. Blood biomarkers predicting immunogenicity to biopharmaceuticals represent an unmet clinical need. Patients with relapsing remitting (RR)MS were recruited before (baseline), three, and 12 (M12) months after commencing interferon-beta treatment. Neutralising ADA-status was determined at M12, and patients were stratified at baseline according to their M12 ADA-status (ADA-positive/ADA-negative). Patients stratified as ADA-positive were characterised by an early dampened response to interferon-beta (prior to serum ADA detection) and distinct proinflammatory transcriptomic/proteomic peripheral blood signatures enriched for 'immune response activation' including phosphoinositide 3-kinase-γ and NFκB-signalling pathways both at baseline and throughout the treatment course, compared to ADA-negative patients. These immunogenicity-associated proinflammatory signatures significantly overlapped with signatures of MS disease severity. Thus, whole blood molecular profiling is a promising tool for prediction of ADA-development in RRMS and could provide insight into mechanisms of immunogenicity.
- MeSH
- biologické markery krev MeSH
- dospělí MeSH
- interferon beta * terapeutické užití imunologie MeSH
- lidé středního věku MeSH
- lidé MeSH
- proteomika * MeSH
- relabující-remitující roztroušená skleróza * farmakoterapie imunologie krev MeSH
- roztroušená skleróza farmakoterapie imunologie krev MeSH
- stupeň závažnosti nemoci MeSH
- transkriptom * MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
Altered cholesterol, oxysterol, sphingolipid, and fatty acid concentrations are reported in blood, cerebrospinal fluid, and brain tissue of people with relapsing-remitting multiple sclerosis (RRMS) and are linked to disease progression and treatment responses. CD4 + T cells are pathogenic in RRMS, and defective T-cell function could be mediated in part by liver X receptors (LXRs)-nuclear receptors that regulate lipid homeostasis and immunity. RNA-sequencing and pathway analysis identified that genes within the 'lipid metabolism' and 'signalling of nuclear receptors' pathways were dysregulated in CD4 + T cells isolated from RRMS patients compared with healthy donors. While LXRB and genes associated with cholesterol metabolism were upregulated, other T-cell LXR-target genes, including genes involved in cellular lipid uptake (inducible degrader of the LDL receptor, IDOL), and the rate-limiting enzyme for glycosphingolipid biosynthesis (UDP-glucosylceramide synthase, UGCG) were downregulated in T cells from patients with RRMS compared to healthy donors. Correspondingly, plasma membrane glycosphingolipids were reduced, and cholesterol levels increased in RRMS CD4 + T cells, an effect partially recapitulated in healthy T cells by in vitro culture with T-cell receptor stimulation in the presence of serum from RRMS patients. Notably, stimulation with LXR-agonist GW3965 normalized membrane cholesterol levels, and reduced proliferation and IL17 cytokine production in RRMS CD4 + T-cells. Thus, LXR-mediated lipid metabolism pathways were dysregulated in T cells from patients with RRMS and could contribute to RRMS pathogenesis. Therapies that modify lipid metabolism could help restore immune cell function.
- MeSH
- CD4-pozitivní T-lymfocyty * imunologie metabolismus MeSH
- cholesterol metabolismus MeSH
- dospělí MeSH
- glykosfingolipidy metabolismus MeSH
- jaterní receptor X * metabolismus MeSH
- lidé středního věku MeSH
- lidé MeSH
- metabolismus lipidů * MeSH
- relabující-remitující roztroušená skleróza * imunologie metabolismus MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
There are no blood-based biomarkers distinguishing patients with relapsing-remitting (RRMS) from secondary progressive multiple sclerosis (SPMS) although evidence supports metabolomic changes according to MS disease severity. Here machine learning analysis of serum metabolomic data stratified patients with RRMS from SPMS with high accuracy and a putative score was developed that stratified MS patient subsets. The top differentially expressed metabolites between SPMS versus patients with RRMS included lipids and fatty acids, metabolites enriched in pathways related to cellular respiration, notably, elevated lactate and glutamine (gluconeogenesis-related) and acetoacetate and bOHbutyrate (ketone bodies), and reduced alanine and pyruvate (glycolysis-related). Serum metabolomic changes were recapitulated in the whole blood transcriptome, whereby differentially expressed genes were also enriched in cellular respiration pathways in patients with SPMS. The final gene-metabolite interaction network demonstrated a potential metabolic shift from glycolysis toward increased gluconeogenesis and ketogenesis in SPMS, indicating metabolic stress which may trigger stress response pathways and subsequent neurodegeneration.
- Publikační typ
- časopisecké články MeSH
Background: Neutralizing anti-drug antibodies (ADA) can greatly reduce the efficacy of biopharmaceuticals used to treat patients with multiple sclerosis (MS). However, the biological factors pre-disposing an individual to develop ADA are poorly characterized. Thus, there is an unmet clinical need for biomarkers to predict the development of immunogenicity, and subsequent treatment failure. Up to 35% of MS patients treated with beta interferons (IFNβ) develop ADA. Here we use machine learning to predict immunogenicity against IFNβ utilizing serum metabolomics data. Methods: Serum samples were collected from 89 MS patients as part of the ABIRISK consortium-a multi-center prospective study of ADA development. Metabolites and ADA were quantified prior to and after IFNβ treatment. Thirty patients became ADA positive during the first year of treatment (ADA+). We tested the efficacy of six binary classification models using 10-fold cross validation; k-nearest neighbors, decision tree, random forest, support vector machine and lasso (Least Absolute Shrinkage and Selection Operator) logistic regression with and without interactions. Results: We were able to predict future immunogenicity from baseline metabolomics data. Lasso logistic regression with/without interactions and support vector machines were the most successful at identifying ADA+ or ADA- cases, respectively. Furthermore, patients who become ADA+ had a distinct metabolic response to IFNβ in the first 3 months, with 29 differentially regulated metabolites. Machine learning algorithms could also predict ADA status based on metabolite concentrations at 3 months. Lasso logistic regressions had the greatest proportion of correct classifications [F1 score (accuracy measure) = 0.808, specificity = 0.913]. Finally, we hypothesized that serum lipids could contribute to ADA development by altering immune-cell lipid rafts. This was supported by experimental evidence demonstrating that, prior to IFNβ exposure, lipid raft-associated lipids were differentially expressed between MS patients who became ADA+ or remained ADA-. Conclusion: Serum metabolites are a promising biomarker for prediction of ADA development in MS patients treated with IFNβ, and could provide novel insight into mechanisms of immunogenicity.
- MeSH
- biologické markery krev MeSH
- interferon beta škodlivé účinky terapeutické užití MeSH
- leukocyty mononukleární imunologie metabolismus MeSH
- lidé MeSH
- membránové lipidy metabolismus MeSH
- membránové mikrodomény MeSH
- metabolom * MeSH
- metabolomika * metody MeSH
- neutralizující protilátky krev imunologie MeSH
- prognóza MeSH
- protilátky krev imunologie MeSH
- roztroušená skleróza krev diagnóza farmakoterapie MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
