Lipidomic Profiling Reveals Distinct Molecular Signatures Across Clinical Subtypes of Myasthenia Gravis

Longitudinal Serum Proteomic Profiles – A Step Closer to Personalized Monitoring in Dermatomyositis

Dermatomyositis (DM) is a multisystemic immune mediated disease presenting with heterogeneous clinical features. Disease activity relies on biomarkers such as creatine kinase (CK) which can be unreliable, notably in cases with extra-muscular manifestations. Novel proteomic platforms have the potential to identify inflammatory biomarkers for personalized monitoring. The objective of this study was to identify proteins associated with disease activity in DM by using the Olink Target 96 Inflammation panel. Six DM patients from a multicenter inflammatory myopathy registry with available longitudinal biobanked sera were identified. All patients met the 2017 EULAR/ACR criteria for adult idiopathic inflammatory myopathy. Disease activity was categorized based on the International Myositis Assessment and Clinical Study (IMACS) physician global assessment (PhGA) as low (PhGA 0-3) or moderate/high (PhGA 4-10). The IMACS core set measures used for the 2016 ACR/EULAR Total Improvement Score were extracted. Serum samples were analyzed using proximity extension technology (Olink Proteomics Inc., Watertown, MA), simultaneously targeting 92 proteins involved in inflammatory processes. Results were reported as normalized protein expression (NPX) values (log2 scale) with higher NPX values representing higher protein concentrations. Mean NPX difference (ΔNPX) for each protein comparing moderate/high and low disease activity were calculated using paired t-tests with Benjamini-Hochberg correction for multiple testing. Six female DM patients with ages ranging from 34 to 53 years were included (Table 1). Clinical features at timepoint 1 included rash (n=6), muscle weakness (n=5), interstitial lung disease (n=5), Raynaud’s (n=3), arthritis (n=1) and dysphagia (n=1). CK values ranged from 37-6039 U/L. Autoantibodies included anti-MDA5, -TIF1y, -Mi2, -Ro52, and -Ku. At timepoint 1, 5 patients had moderate/high disease activity and at the timepoint 2, 5 patients had low disease activity. Eleven proteins were significantly upregulated when comparing moderate/high vs low disease activity. The strongest ΔNPX was observed for monocyte chemoattractant proteins, MCP-2 (3.0), MCP-1 (2.4), MCP-4 (2.2) (all adj. p=0.02) and C-X-C motif chemokine 11 (CXCL11, 3.0, adj. p=0.05). Other upregulated proteins included CX3CL1 (1.57), CCL11 (1.42), PD-L1 (1.27), IL-4 (1.1), CD40 (0.92), IL-15RA (0.9) and CSF-1 (0.61) (all adj. p=0.05). Table 1. Demographic and clinical characteristics Using serum inflammatory profiles, we identified proteins upregulated in DM patients with moderate/high disease activity compared to low disease activity in a small exploratory cohort. Those included chemokines involved in monocyte and T-cell recruitment that could represent potential biomarkers for disease activity monitoring. Further studies in larger DM cohorts are warranted to evaluate the role of longitudinal proteomic profiling in personalized disease activity monitoring.

Metabolomic profiling in treated mucopolysaccharidosis IH reveals candidate biomarkers and adjunctive therapeutic pathways

Serum Lipidomics Profiling Identify Novel Biomarkers of Distal Symmetrical Polyneuropathy in Type 1 Diabetes.

BACKGROUND Distal symmetrical polyneuropathy (DSPN) is a common complication of type 1 diabetes (T1D), yet validated biomarkers for early detection or prognosis are lacking. Metabolic disturbances driven by chronic hyperglycemia and dyslipidemia contribute to DSPN development and progression. METHODS We used untargeted serum liquid chromatography-mass spectrometry lipidomics to identify DSPN biomarkers. The discovery cohort included 153 individuals with T1D (109 with and 44 without DSPN) and 50 non-diabetic controls. The independent validation cohort included 99 individuals with T1D with established DSPN status. Key lipids were identified using multivariate modelling, followed by ANCOVA and adjusted post hoc tests. RESULTS A total of 543 lipid species were identified in the discovery cohort. Among these, 14 lipids were associated with DSPN. Of which, 6 lipids, namely Cer(d42:1), PC(36:4), LPC(16:0), LPE(18:1), PE(36:2), and PE(O-40:5) or PE(P-40:4), showed a clear pattern among non-diabetic individuals, people affected by T1D with and without DSPN. In the validation cohort, 3 of the 6 initially identified lipids showed the same directional changes as in the discovery cohort. A logistic regression model combining the six lipid biomarkers with HbA1c, diastolic blood pressure, and age achieved AUCs of 0.83 (95% CI, 0.76-0.91) in the discovery cohort and 0.81 (95% CI, 0.73-0.90) in the validation cohort for detecting DSPN in T1D. AUC improvement was not significant by DeLong's test in either cohort (p = 0.086 and 0.089) but was significant when combined using Fisher's method (χ2 = 9.7, p = 0.045). Additionally, 22 lipid species differed significantly between painful and painless DSPN. CONCLUSIONS We identified a reproducible lipidomic signature discriminating DSPN in type 1 diabetes. Painful DSPN was characterized by reduced unsaturated PC/PE and increased sphingolipids, offering new insight into disease pathophysiology.

Detection of miRNA in chronic spontaneous urticaria patients - pilot study

Background Chronic spontaneous urticaria (CSU) is a heterogeneous immune-mediated disorder characterized by recurrent wheals and/or angioedema. Despite advances in understanding its pathogenesis, robust biomarkers for disease stratification remain lacking. MicroRNAs (miRNAs) are key post-transcriptional regulators implicated in immune-mediated diseases and may provide novel insights into CSU. Objective To characterize circulating miRNA expression profiles in CSU and explore their association with clinical phenotypes. Methods Patients were stratified into three groups: urticaria only (n=10), urticaria with angioedema (n=10), and angioedema only (n=10), alongside healthy controls (n=10). Plasma miRNAs were sequenced using the NovaSeq 6000 platform. Data were processed with the nf-core smrnaseq pipeline, followed by multivariate and differential expression analyses in R. Functional enrichment and target prediction analyses were performed using KEGG, Reactome, and WikiPathways. Results Thirty patients (mean age 45.3 years; 76.7% female) were included. Overall, 61 miRNAs were differentially expressed (p < 0.05) across groups, including controls. No miRNAs remained significant after multiple testing correction in pairwise comparisons between clinical subgroups. However, several miRNAs (miR-204-5p, miR-3158-3p, miR-4732-3p, miR-576-5p, and miR-877-5p) showed nominal associations with disease phenotypes. miR-204-5p demonstrated a trend toward reduced expression in patients with urticaria and angioedema (adjusted p = 0.05). Conclusion Circulating miRNA profiles may reflect biological heterogeneity in CSU. Although no subgroup-specific signatures were confirmed after correction for multiple testing, several candidate miRNAs were identified, supporting further investigation of miRNA-based biomarkers in CSU.

Bisphenol A exposure in myasthenia gravis: Potential targets and mechanisms revealed by network toxicology and molecular dynamics

Background Myasthenia gravis (MG) is a B-cell-mediated autoimmune disease characterized by impaired neuromuscular transmission. Although genetic predisposition and thymic abnormalities are well recognized, they cannot fully explain the increasing incidence and regional heterogeneity of MG, highlighting the potential contribution of environmental factors. Bisphenol A (BPA), a ubiquitous endocrine-disrupting chemical, exhibits estrogenic activity, immunomodulatory effects, and mitochondrial toxicity, and has been implicated in multiple autoimmune disorders. However, the potential role of BPA in MG pathogenesis remains largely unexplored. Methods BPA-related targets and MG-associated genes were collected from public databases, and overlapping targets were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore the biological functions and pathways of the overlapping targets. Candidate targets were screened using four machine-learning algorithms, including least absolute shrinkage and selection operator (LASSO) regression, support vector machine-recursive feature elimination (SVM-RFE), random forest (RF), and extreme gradient boosting (XGBoost). Differential expression and diagnostic performance were validated using the Gene Expression Omnibus (GEO) dataset GSE85452. Immune infiltration was assessed using CIBERSORT. Molecular docking and molecular dynamics (MD) simulations were conducted to evaluate the potential binding stability and interaction modes between BPA and key target proteins. In addition, C2C12 myoblasts were treated with different concentrations of BPA for 24 h, and cell viability was assessed using the Cell Counting Kit-8 (CCK-8) assay. Based on the cell viability results, 50 μM BPA was selected for quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western blot analyses of key genes. Results A total of 225 overlapping targets were identified between BPA exposure-related targets and MG-associated genes. Enrichment analyses showed that these targets were mainly associated with ion transport, membrane potential regulation, muscle system processes, immune signaling, apoptosis, endocrine resistance, and AGE–RAGE signaling pathways.Four machine-learning algorithms identified cholinergic receptor nicotinic beta 1 subunit (CHRNB1), KRAS proto-oncogene, GTPase (KRAS), phosphomannomutase 2 (PMM2), and toll-like receptor 4 (TLR4) as candidate targets. Validation in the GSE85452 dataset showed that CHRNB1, PMM2, and TLR4 were significantly upregulated in MG samples compared with control samples, whereas KRAS showed no significant difference. receiver operating characteristic (ROC) analysis further demonstrated that CHRNB1, PMM2, and TLR4 had good diagnostic performance, with area under the ROC curve (AUC) values of 0.827, 0.856, and 0.821,respectively. Immune infiltration analysis revealed altered immune cell infiltration patterns and associations between key targets and specific immune cell subsets. Molecular docking predicted favorable binding of BPA to CHRNB1, PMM2, and TLR4, with binding energies of −7.4, −5.7, and −5.8 kcal/mol, respectively. MD simulations further supported the potential stability of these BPA-target complexes. In vitro experiments showed that BPA reduced C2C12 cell viability in a concentration-dependent manner. qRT-PCR validation showed that treatment with 50 μM BPA significantly upregulated Chrnb1 expression, while downregulating Pmm2 and Tlr4 expression.Western blot analysis further confirmed that BPA exposure significantly decreased the protein expression of TLR4 and PMM2, while increasing that of CHRNB1 in C2C12 cells. Conclusions This study provides integrated computational and experimental evidence that BPA exposure may be associated with MG-related molecular alterations. BPA may affect MG-related biological processes through the regulation of ion transport, neuromuscular signaling, immune activation, and glycosylation-related metabolism. CHRNB1, PMM2, and TLR4 may serve as potential molecular links between BPA exposure and MG-related pathological processes.

The immune microenvironment and population heterogeneity in myasthenia gravis: implications for precision therapeutics

Myasthenia gravis (MG) is a chronic autoimmune disorder of the neuromuscular junction characterized by fluctuating skeletal muscle weakness. Although the pathogenic roles of autoantibodies targeting the acetylcholine receptor (AChR), muscle-specific kinase (MuSK), and certain neuromuscular junction proteins have been well established, increasing evidence indicates that MG onset, progression, and therapeutic response can be shaped by the complex interactions within diverse immune microenvironments. Particularly, population heterogeneity, including differences in antibody subtype, age, sex, genetic susceptibility, ethnicity, thymic pathology, and potential confounders related to differences in healthcare conditions, strongly contributes to variability in its clinical manifestations and targeted therapies. This review discusses current evidence on the roles of the immune microenvironment and individual heterogeneity in shaping the pathogenesis and treatment landscape of MG. Along with the contributions of immunophenotyping, multi-omics techniques, single-cell and spatial transcriptomics, and biomarker discovery in improving our understanding of MG mechanisms, we also evaluated the implications of immune diversity in various populations for established therapies, as well as emerging immune-modulating approaches. This review highlights current knowledge gaps and future research priorities, emphasizing the transition from phenotype-based disease classification toward immune endotype-driven precision medicine within population heterogeneity.