SYNGR4 and PLEKHB1 deregulation in motor neurons of amyotrophic lateral sclerosis models: potential contributions to pathobiology

Circulating proteomic biomarkers for diagnosing sporadic amyotrophic lateral sclerosis: a cross-sectional study

JOURNAL/nrgr/04.03/01300535-202408000-00039/figure1/v/2023-12-16T180322Z/r/image-tiff Biomarkers are required for the early detection, prognosis prediction, and monitoring of amyotrophic lateral sclerosis, a progressive disease. Proteomics is an unbiased and quantitative method that can be used to detect neurochemical signatures to aid in the identification of candidate biomarkers. In this study, we used a label-free quantitative proteomics approach to screen for substantially differentially regulated proteins in ten patients with sporadic amyotrophic lateral sclerosis compared with five healthy controls. Substantial upregulation of serum proteins related to multiple functional clusters was observed in patients with sporadic amyotrophic lateral sclerosis. Potential biomarkers were selected based on functionality and expression specificity. To validate the proteomics profiles, blood samples from an additional cohort comprising 100 patients with sporadic amyotrophic lateral sclerosis and 100 healthy controls were subjected to enzyme-linked immunosorbent assay. Eight substantially upregulated serum proteins in patients with sporadic amyotrophic lateral sclerosis were selected, of which the cathelicidin-related antimicrobial peptide demonstrated the best discriminative ability between patients with sporadic amyotrophic lateral sclerosis and healthy controls (area under the curve [AUC] = 0.713, P < 0.0001). To further enhance diagnostic accuracy, a multi-protein combined discriminant algorithm was developed incorporating five proteins (hemoglobin beta, cathelicidin-related antimicrobial peptide, talin-1, zyxin, and translationally-controlled tumor protein). The algorithm achieved an AUC of 0.811 and a P-value of < 0.0001, resulting in 79% sensitivity and 71% specificity for the diagnosis of sporadic amyotrophic lateral sclerosis. Subsequently, the ability of candidate biomarkers to discriminate between early-stage amyotrophic lateral sclerosis patients and controls, as well as patients with different disease severities, was examined. A two-protein panel comprising talin-1 and translationally-controlled tumor protein effectively distinguished early-stage amyotrophic lateral sclerosis patients from controls (AUC = 0.766, P < 0.0001). Moreover, the expression of three proteins (FK506 binding protein 1A, cathelicidin-related antimicrobial peptide, and hemoglobin beta-1) was found to increase with disease progression. The proteomic signatures developed in this study may help facilitate early diagnosis and monitor the progression of sporadic amyotrophic lateral sclerosis when used in combination with current clinical-based parameters.

Therapy of autoimmune inflammation in sporadic amyotrophic lateral sclerosis: Dimethyl fumarate and H-151 downregulate inflammatory cytokines in the cGAS-STING pathway

In sporadic amyotrophic lateral sclerosis (sALS), IL-17A- and granzyme-positive cytotoxic T lymphocytes (CTL), IL-17A-positive mast cells, and inflammatory macrophages invade the brain and spinal cord. In some patients, the disease starts following a trauma or a severe infection. We examined cytokines and cytokine regulators over the disease course and found that, since the early stages, peripheral blood mononuclear cells (PBMC) exhibit increased expression of inflammatory cytokines IL-12A, IFN-γ, and TNF-α, as well as granzymes and the transcription factors STAT3 and STAT4. In later stages, PBMCs upregulated the autoimmunity-associated cytokines IL-23A and IL-17B, and the chemokines CXCL9 and CXCL10, which attract CTL and monocytes into the central nervous system. The inflammation is fueled by the downregulation of IL-10, TGFβ, and the inhibitory T-cell co-receptors CTLA4, LAG3, and PD-1, and, in vitro, by stimulation with the ligand PD-L1. We investigated in two sALS patients the regulation of the macrophage transcriptome by dimethyl fumarate (DMF), a drug approved against multiple sclerosis and psoriasis, and the cyclic GMP-AMP synthase/stimulator of interferon genes (cGAS/STING) pathway inhibitor H-151. Both DMF and H-151 downregulated the expression of granzymes and the pro-inflammatory cytokines IL-1β, IL-6, IL-15, IL-23A, and IFN-γ, and induced a pro-resolution macrophage phenotype. The eicosanoid epoxyeicosatrienoic acids (EET) from arachidonic acid was anti-inflammatory in synergy with DMF. H-151 and DMF are thus candidate drugs targeting the inflammation and autoimmunity in sALS via modulation of the NFκB and cGAS/STING pathways.

Blood leukocyte transcriptional modules and differentially expressed genes associated with disease severity and age in COVID-19 patients

Since the molecular mechanisms determining COVID-19 severity are not yet well understood, there is a demand for biomarkers derived from comparative transcriptome analyses of mild and severe cases, combined with patients' clinico-demographic and laboratory data. Here the transcriptomic response of human leukocytes to SARS-CoV-2 infection was investigated by focusing on the differences between mild and severe cases and between age subgroups (younger and older adults). Three transcriptional modules correlated with these traits were functionally characterized, as well as 23 differentially expressed genes (DEGs) associated to disease severity. One module, correlated with severe cases and older patients, had an overrepresentation of genes involved in innate immune response and in neutrophil activation, whereas two other modules, correlated with disease severity and younger patients, harbored genes involved in the innate immune response to viral infections, and in the regulation of this response. This transcriptomic mechanism could be related to the better outcome observed in younger COVID-19 patients. The DEGs, all hyper-expressed in the group of severe cases, were mostly involved in neutrophil activation and in the p53 pathway, therefore related to inflammation and lymphopenia. These biomarkers may be useful for getting a better stratification of risk factors in COVID-19.