Polygenic associations and causal inferences between serum immunoglobulins and amyotrophic lateral sclerosis

Peripheral immune markers and amyotrophic lateral sclerosis: a Mendelian randomization study

Introduction

The peripheral immune system changes in amyotrophic lateral sclerosis (ALS), but the causal relationship between the two is still controversial.

Methods

In this study, we aimed to estimate the causal relationship between peripheral immune markers and ALS using a two-sample Mendelian randomization method. Genome-wide association study (GWAS) data on peripheral blood immune traits from European populations were used for exposure, and ALS summary statistics were used as the outcome. The causal relationship was evaluated by inverse variance weighting, MR-Egger, and weighted median methods and verified by multiple sensitivity analysis.

Results

We found that the increase of one standard deviation of lymphocyte count is related to reducing ALS risk. CD3 on effector memory CD4+ T cell, HLA DR+ CD4+ T cell, effector memory CD8+ T cell, terminally differentiated CD8+ T cell and CD28- CD8+ T cell is also a protective factor for ALS. Among the circulating immune protein, the increase of one standard deviation of α-2-macroglobulin receptor-associated protein (α-2-MRAP) and C4b showed associated with low risk of ALS, while Interleukin-21 (IL-21) increases the risk of ALS.

Discussion

Our study further reveals the important role of peripheral immune activity in ALS.

Comprehensive analysis of autoimmune-related genes in amyotrophic lateral sclerosis from the perspective of 3P medicine

Background

Although growing evidence suggests close correlations between autoimmunity and amyotrophic lateral sclerosis (ALS), no studies have reported on autoimmune-related genes (ARGs) from the perspective of the prognostic assessment of ALS. The purpose of this study was to investigate whether the circulating ARD signature could be identified as a reliable biomarker for ALS survival for predictive, preventive, and personalized medicine.

Methods

The whole blood transcriptional profiles and clinical characteristics of 454 ALS patients were downloaded from the Gene Expression Omnibus (GEO) database. A total of 4371 ARGs were obtained from GAAD and DisGeNET databases. Wilcoxon test and multivariate Cox regression were applied to identify the differentially expressed and prognostic ARGs. Then, unsupervised clustering was performed to classify patients into two distinct autoimmune-related clusters. PCA method was used to calculate the autoimmune index. LASSO and multivariate Cox regression was performed to establish risk model to predict overall survival for ALS patients. A ceRNA regulatory network was then constructed for regulating the model genes. Finally, we performed single-cell analysis to explore the expression of model genes in mutant SOD1 mice and methylation analysis in ALS patients.

Results

Based on the expressions of 85 prognostic ARGs, two autoimmune-related clusters with various biological features, immune characteristics, and survival outcome were determined. Cluster 1 with a worsen prognosis was more active in immune-related biological pathways and immune infiltration than Cluster 2. A higher autoimmune index was associated with a better prognosis than a lower autoimmune index, and there were significant adverse correlations between the autoimmune index and immune infiltrating cells and immune responses. Nine model genes (KIF17, CD248, ENG, BTNL2, CLEC5A, ADORA3, PRDX5, AIM2, and XKR8) were selected to construct prognostic risk signature, indicating potent potential for survival prediction in ALS. Nomogram integrating risk model and clinical characteristics could predict the prognosis more accurately than other clinicopathological features. We constructed a ceRNA regulatory network for the model genes, including five lncRNAs, four miRNAs, and five mRNAs.

Conclusion

Expression of ARGs is correlated with immune characteristics of ALS, and seven ARG signatures may have practical application as an independent prognostic factor in patients with ALS, which may serve as target for the future prognostic assessment, targeted prevention, patient stratification, and personalization of medical services in ALS.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00299-w.