| Literature DB >> 32487123 |
Rajka Maria Liscic1,2, Antonella Alberici3, Nigel John Cairns4, Maurizio Romano5, Emanuele Buratti6.
Abstract
Amyotrophic lateral sclerosis (ALS) and Frontotemporal Degeneration (FTD) are neurodegenerative disorders, related by deterioration of motor and cognitive functions and short survival. Aside from cases with an inherited pathogenic mutation, the causes of the disorders are still largely unknown and no effective treatment currently exists. It has been shown that FTD may coexist with ALS and this overlap occurs at clinical, genetic, and molecular levels. In this work, we review the main pathological aspects of these complex diseases and discuss how the integration of the novel pathogenic molecular insights and the analysis of molecular interaction networks among all the genetic players represents a critical step to shed light on discovering novel therapeutic strategies and possibly tailoring personalized medicine approaches to specific ALS and FTD patients.Entities:
Keywords: ALS; Dementia FTLD; FTD; Genetics; Motor neuron disease TDP-43; Stem cell
Mesh:
Year: 2020 PMID: 32487123 PMCID: PMC7268618 DOI: 10.1186/s13024-020-00373-9
Source DB: PubMed Journal: Mol Neurodegener ISSN: 1750-1326 Impact factor: 14.195
Main genes and cellular components/processes implicated in the pathogenesis of ALS and FTD
| RNA metabolism | TARDBP, FUS, hnRNPA1, hnRNPA2B1, MATR3, ATXN2, TAF15, SETX, EWSR1, ELP3, ANG |
| Protein trafficking and Proteostasis | C9ORF72, CHMP2B, FIG 4, TBK1, UBQLN2, SQSTM1, SIGMAR1, OPTN, VCP, ALS2, VAPB |
| DNA repair | EWSR1, FUS, SETX, TAF15, TARDBP |
| Mitochondria and Oxidative stress: | SOD1, CHCHD10, C19ORF12 |
| Immune response/Inflammation: | GRN, TREM2, TYROBP |
| Stress granule assembly | ATXN2, C9ORF72, MAPT |
| Glia and Neurons metabolism | GRN, SIGMAR1, SOD1, TREM2, TYROBP |
| Vacuolar transport | C9ORF72, CHMP2B, GRN, TMEM106B, VCP, OPTN, UNC13A |
| Axo-dendritic transport | KIF5A, MAPT, SPG11 |
Fig. 1Genetic overlap between ALS and FTD. To this date, more than 50 genes have been associated with ALS and FTD. The Venn diagram summarizes the number of specifically altered genes in each disease and the observed overlap between the two pathologies
ALS-FTD genotype/phenotype correlations for genes and presence of TDP-43 inclusions
| Gene | Genetic overlap ALS/FTD | TDP inclusions | References |
|---|---|---|---|
| SETX | ALS | Yes | [ |
| ATXN2 | ALS | Yes | [ |
| SOD1 | ALS | Yes | [ |
| VABP | ALS | NR | -- |
| ALS2 | ALS | NR | -- |
| ANG | ALS | Yes | [ |
| SQSTM1 | ALS | Yes | [ |
| C21ORF2 | ALS | NR | – |
| MATR3 | ALS | Yes | [ |
| EWSR1 | ALS | NR | -- |
| TAF15 | ALS | NR | -- |
| HNRPA1 | ALS | Yes | [ |
| HNRNPA2B1 | ALS | Yes | [ |
| OPTN | ALS | Yes | [ |
| TUBA4A | ALS-FTD | NR | [ |
| TARDBP | ALS-FTD | Yes | [ |
| C9ORF72 | ALS-FTD | Yes | [ |
| DCTN1 | ALS-FTD | Yes | [ |
| TUBA4A | ALS-FTD | NR | [ |
| TBK1 | ALS-FTD | Yes | [ |
| CHCHD10 | ALS-FTD | Yes | [ |
| CCNF | ALS-FTD | Yes | [ |
| FUS | ALS>FTD | NR | [ |
| UBQLN2 | ALS>FTD | Yes | [ |
| SIGMAR1 | ALS>FTD | NR | -- |
| TIA1 | ALS>FTD | NR | -- |
| CHMP2B | FTD>ALS | NR | [ |
| VCP | FTD>ALS | Yes | [ |
| GRN | FTD | Yes | [ |
| MAPT | FTD | NR | -- |
| TMEM106B | FTD | Yes | [ |
The evidence for mutations linking each gene to the ALS-FTD spectrum is reported (ALS only; FTD only; both ALS-FTD; majority of ALS cases: ALS>FTD; majority of ALS cases: FTD>ALS). NR not reported
Fig. 2Factors affecting the disease- and clinical- phenotypes of ALS and FTD pathologies. Schematic diagram of the various exogenous and endogenous factors potentially affecting the age at onset, the disease phenotypes, as well as the clinical phenotypes
Effect of the genetic modifiers of ALS and FTD
| GRN | SORT1 | rs646776 C-minor allele => decreased GRN plasma expression | [ |
| GRN | TMEM106B | rs1990622 C-minor allele => lower risk (older age at onset) | [ |
| C9ORF72 | TMEM106B | rs1990622 C-minor allele => earlier onset | [ |
| rs3173615 G minor allele => Homozygosity protects from developing FTD but not from developing MND | [ | ||
| -- | TMEM106B | rs1990622 T-major allele => poorer cognitive performance in FTLD-TDP patients not in ALS patients | [ |
| -- | TMEM106B | rs1990622 C-minor allele => protective effect on cognitive aging | [ |
Fig. 3Actual and potential therapeutic approaches to treat ALS and FTD pathologies. This schematic diagram recapitulates the major pharmacological therapeutic approaches that have been tested or are currently approved for treatment of ALS patients (highlighted in red). In addition, it shows the main novel approaches that are currently under development based on recent discoveries in the field of stem-cell/gene therapy and the molecular pathology of these diseases. As shown in this figure, they range from small functional molecules and RNAs against specific protein/RNA-based targets, stem-cell approaches, to transcranial magnetic stimulation (TMS) or transcranial direct current stimulation (tDCS)
Hurdles on the road of developing novel treatments for ALS and FTD
| • Unknown etiology of sporadic cases. | |
| • High degree of heterogeneity at clinical, neuropathological level. | |
| • High degree of genetic heterogeneity both at allele and at locus level. | |
| • Unknown reason(s) for the selective vulnerability of cell types (i.e., specific motor neurons, frontal, and temporal neurons). | |
| • Unknown influence of exogenous factors on the onset and progression of the diseases. | |
| • Unknown influence of endogenous modifier factors on the onset and progression of disease. |
Future directions to improve the translation of individual genetic information into novel and personalized treatments for ALS and FTD
| • Gaining novel insights into molecular mechanisms of ALS and FTD pathophysiology by better integration of Clinical, Neuropathological, Neuroimaging, Next-Generation Sequencing, Proteomics, Pharmacogenetics studies. | |
| • Characterization of common and divergent mechanisms leading to ALS and FTD. | |
| • Revamp of ALS and FTD disease classification system according to the novel genetic and molecular information to identify subgroups of patients that might respond to treatments at a higher (or lower) rate than the population average. | |
| • Identification of reliable biomarkers for diagnosing, monitoring the response to therapy, and predicting disease progression. | |
| • Development of robust animal models and protocols to minimize eventual off target effects. | |
| • Optimization of ASOs' delivery across the blood-brain barrier. | |
| • Decrease/bypass the viral vectors' immunogenicity and the eventual pre-existing immunity to AAV. |