[Genome-wide expression profiling as a clinical tool: are we there yet?]

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.

Molecular diagnosis and prognosis with DNA microarrays

Microarray analysis makes it possible to determine thousands of gene expression values simultaneously. Changes in gene expression, as a response to diseases, can be detected allowing a better understanding and differentiation of diseases at a molecular level. By comparing different kinds of tissue, for example healthy tissue and cancer tissue, the microarray analysis indicates induced gene activity, repressed gene activity or when there is no change in the gene activity level. Fundamental patterns in gene expression are extracted by several clustering and machine learning algorithms. Certain kinds of cancer can be divided into subtypes, with different clinical outcomes, by their specific gene expression patterns. This enables a better diagnosis and tailoring of individual patient treatments.