Transcriptomics and Metabolomics in Amyotrophic Lateral Sclerosis

Lower Airway Dysbiosis Augments Lung Inflammatory Injury in Mild-to-Moderate Chronic Obstructive Pulmonary Disease

Rationale: Chronic obstructive pulmonary disease (COPD) is associated with high morbidity, mortality, and healthcare costs. Cigarette smoke is a causative factor; however, not all heavy smokers develop COPD. Microbial colonization and infections are contributing factors to disease progression in advanced stages. Objectives: We investigated whether lower airway dysbiosis occurs in mild-to-moderate COPD and analyzed possible mechanistic contributions to COPD pathogenesis. Methods: We recruited 57 patients with a >10 pack-year smoking history: 26 had physiological evidence of COPD, and 31 had normal lung function (smoker control subjects). Bronchoscopy sampled the upper airways, lower airways, and environmental background. Samples were analyzed by 16S rRNA gene sequencing, whole genome, RNA metatranscriptome, and host RNA transcriptome. A preclinical mouse model was used to evaluate the contributions of cigarette smoke and dysbiosis on lower airway inflammatory injury. Measurements and Main Results: Compared with smoker control subjects, microbiome analyses showed that the lower airways of subjects with COPD were enriched with common oral commensals. The lower airway host transcriptomics demonstrated differences in markers of inflammation and tumorigenesis, such as upregulation of IL-17, IL-6, ERK/MAPK, PI3K, MUC1, and MUC4 in mild-to-moderate COPD. Finally, in a preclinical murine model exposed to cigarette smoke, lower airway dysbiosis with common oral commensals augments the inflammatory injury, revealing transcriptomic signatures similar to those observed in human subjects with COPD. Conclusions: Lower airway dysbiosis in the setting of smoke exposure contributes to inflammatory injury early in COPD. Targeting the lower airway microbiome in combination with smoking cessation may be of potential therapeutic relevance.

Metabolomics identifies shared lipid pathways in independent amyotrophic lateral sclerosis cohorts

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease lacking effective treatments. This is due, in part, to a complex and incompletely understood pathophysiology. To shed light, we conducted untargeted metabolomics on plasma from two independent cross-sectional ALS cohorts versus control participants to identify recurrent dysregulated metabolic pathways. Untargeted metabolomics was performed on plasma from two ALS cohorts (cohort 1, n = 125; cohort 2, n = 225) and healthy controls (cohort 1, n = 71; cohort 2, n = 104). Individual differential metabolites in ALS cases versus controls were assessed by Wilcoxon, adjusted logistic regression and partial least squares-discriminant analysis, while group lasso explored sub-pathway level differences. Adjustment parameters included age, sex and body mass index. Metabolomics pathway enrichment analysis was performed on metabolites selected using the above methods. Additionally, we conducted a sex sensitivity analysis due to sex imbalance in the cohort 2 control arm. Finally, a data-driven approach, differential network enrichment analysis (DNEA), was performed on a combined dataset to further identify important ALS metabolic pathways. Cohort 2 ALS participants were slightly older than the controls (64.0 versus 62.0 years, P = 0.009). Cohort 2 controls were over-represented in females (68%, P < 0.001). The most concordant cohort 1 and 2 pathways centred heavily on lipid sub-pathways, including complex and signalling lipid species and metabolic intermediates. There were differences in sub-pathways that were enriched in ALS females versus males, including in lipid sub-pathways. Finally, DNEA of the merged metabolite dataset of both ALS and control cohorts identified nine significant subnetworks; three centred on lipids and two encompassed a range of sub-pathways. In our analysis, we saw consistent and important shared metabolic sub-pathways in both ALS cohorts, particularly in lipids, further supporting their importance as ALS pathomechanisms and therapeutics targets.

The Role of Small Heat Shock Proteins in Protein Misfolding Associated Motoneuron Diseases

Motoneuron diseases (MNDs) are neurodegenerative conditions associated with death of upper and/or lower motoneurons (MNs). Proteostasis alteration is a pathogenic mechanism involved in many MNDs and is due to the excessive presence of misfolded and aggregated proteins. Protein misfolding may be the product of gene mutations, or due to defects in the translation process, or to stress agents; all these conditions may alter the native conformation of proteins making them prone to aggregate. Alternatively, mutations in members of the protein quality control (PQC) system may determine a loss of function of the proteostasis network. This causes an impairment in the capability to handle and remove aberrant or damaged proteins. The PQC system consists of the degradative pathways, which are the autophagy and the proteasome, and a network of chaperones and co-chaperones. Among these components, Heat Shock Protein 70 represents the main factor in substrate triage to folding, refolding, or degradation, and it is assisted in this task by a subclass of the chaperone network, the small heat shock protein (sHSPs/HSPBs) family. HSPBs take part in proteostasis by bridging misfolded and aggregated proteins to the HSP70 machinery and to the degradative pathways, facilitating refolding or clearance of the potentially toxic proteins. Because of its activity against proteostasis alteration, the chaperone system plays a relevant role in the protection against proteotoxicity in MNDs. Here, we discuss the role of HSPBs in MNDs and which HSPBs may represent a valid target for therapeutic purposes.

Therapeutic Approaches to Amyotrophic Lateral Sclerosis from the Lab to the Clinic

Amyotrophic Lateral Sclerosis (ALS) is a terminal neuro-degenerative disorder that is clinically recognized as a gradual degeneration of the upper and lower motor neurons, with an average duration of 3 to 5 years from initiation of symptoms to death. The mechanisms underlying the pathogenesis and progression of the disease are multifactorial. Therefore, to find effective treatments, it is necessary to understand this heterogeneity underlying the progression of ALS. Recent developments in gene therapy have opened a new avenue to treat this condition, especially for the characterized genetic types. Gene therapy methods have been studied in a variety of pre-clinical settings and clinical trials, and they may be a promising path for developing an effective and safe ALS cure. A growing body of evidence demonstrates abnormalities in energy metabolism at the cellular and whole-body level in animal models and in people living with ALS. The use and incorporation of high-throughput "omics" methods has radically transformed our thought about ALS, strengthening our understanding of the disease's dynamic molecular architecture, differentiating distinct patient subtypes, and creating a reasonable basis for the identification of biomarkers and novel individualised treatments. Future clinical and laboratory trials would also focus on the diverse relationships between metabolism and ALS to address the issue of whether targeting deficient metabolism in ALS is an effective way to change disease progression. In this review, we focus on the detailed pathogenesis of ALS and highlight principal genes, i.e., SOD1, TDP-43, C9orf72, and FUS, targeted therapeutic approaches of ALS. An attempt is made to provide up-to-date information on clinical outcomes, including various biomarkers which are thought to be important players in early ALS detection.

From Multi-Omics Approaches to Precision Medicine in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a devastating and fatal neurodegenerative disorder, caused by the degeneration of upper and lower motor neurons for which there is no truly effective cure. The lack of successful treatments can be well explained by the complex and heterogeneous nature of ALS, with patients displaying widely distinct clinical features and progression patterns, and distinct molecular mechanisms underlying the phenotypic heterogeneity. Thus, stratifying ALS patients into consistent and clinically relevant subgroups can be of great value for the development of new precision diagnostics and targeted therapeutics for ALS patients. In the last years, the use and integration of high-throughput "omics" approaches have dramatically changed our thinking about ALS, improving our understanding of the complex molecular architecture of ALS, distinguishing distinct patient subtypes and providing a rational foundation for the discovery of biomarkers and new individualized treatments. In this review, we discuss the most significant contributions of omics technologies in unraveling the biological heterogeneity of ALS, highlighting how these approaches are revealing diagnostic, prognostic and therapeutic targets for future personalized interventions.