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Exploring Amyotrophic Lateral Sclerosis (ALS) with PercayAI’s AI Tools 


Part II: Understanding familial and sporadic ALS

July 30,2020

Welcome to our newest blog series where we investigate Amyotrophic Lateral Sclerosis (ALS) using our AI knowledge mapping tools. Check back for our next installment, in which we analyze transcriptomics from spinal cord samples collected from patients as well as a mouse model.

New to our ALS series? Read part one here. 

In this second post in our Exploring ALS series, we will begin to dig into some clinical transcriptomics data from patients with ALS. While there are many unknowns to explore within the ALS research space, the specific angle we will take for this analysis is to compare the molecular signatures of sporadic versus familial ALS. 

Sporadic ALS, representing about 90% of cases, means the cause of disease is unknown. This is in contrast to familial ALS, in which one of several known germline mutations are present, often resulting in multiple affected family members. To better understand the mechanisms underlying these two categories of ALS, Dangond et al. performed transcriptomics analyses using postmortem tissue samples from spinal cord grey matter of ALS patients. The following two analyses will examine the molecular signature of sporadic and familial ALS, each as compared to non-diseased controls.


Exploring Sporadic ALS:

The knowledge map of sporadic ALS shows the following upregulated processes/pathways:

  • Immune processes in blue

  • Lipid-related themes in purple

  • Detoxification pathways in green

  • Stress response in teal

  • Neuronal signaling in gold

  • Cellular growth processes in red

The knowledge map of sporadic ALS shows the following downregulated processes/pathways:

  • Neural growth/maintenance pathways in yellow

  • Immune/inflammatory regulation in purple

  • Differentiation signaling in orange

  • Autophagy/ubiquitination in black

Key Takeaways:

Upregulation of immune, detoxification, and stress response themes are consistent with a compensatory response to the neuromuscular damage that takes place in ALS. In contrast, downregulation of crucial maintenance/repair processes such as autophagy/ubiquitination and neural growth may contribute to disease progression and are areas of investigation for treatment. The presence of immune signaling and growth/differentiation in both up- and down-regulated analyses suggests a more complex (dys)regulation of these themes. This is to be expected, given the coordinated positive and negative regulation of these fundamental processes. Perhaps some of the most notable results are the upregulation of genes related to demyelination/neuropathy (in purple), and the downregulation of genes related to myocytes and the neural injury response (in yellow).


Exploring Familial ALS:

The knowledge map of familial ALS shows the following upregulated processes/pathways:

  • Immune related themes in blue

  • Growth/differentiation themes in orange

  • Transcriptional regulation in green

  • Metabolic processes in purple

The knowledge map of familial ALS shows the following downregulated processes/pathways:

  • Immune related themes in purple

  • Neural associated themes in green

  • Cancer related processes in orange

  • Growth signaling in yellow

  • Steroid/hormone signaling in blue

Key Takeaways:

As we observed in the sporadic ALS analysis, familial ALS also involves a complex interplay of both up- and downregulation of immune and growth/differentiation processes. Of particular interest is the upregulation of genes related to the neuroprotective BDNF-NTRK2 signaling pathway and myogenesis (both in orange). One might expect these themes to be a compensatory protective response to the progressive neuromuscular damage in ALS; however, there is evidence that BDNF signaling may facilitate motor neuron death in ALS due to glutamate excitotoxicity. Similarly, the downregulation of genes related to NMDA glutamate receptor activity (in green) may represent either mechanistic or compensatory changes related to ALS pathophysiology, as the role of NMDA receptors in ALS is an area of investigation.

How do Sporadic and Familial ALS Compare?

While familial and sporadic ALS have different initial causes and some differences in disease progression, they share many of the same manifestations. To better understand the cellular/molecular similarities and differences between the two forms of ALS, we used PercayAI’s concept level comparison tool. The knowledge maps below show only the conserved biological concepts in familial and sporadic ALS.

The following processes/pathways are upregulated in both familial and sporadic ALS:

  • Immune related themes in blue

  • Growth/differentiation processes in orange

  • Lipid related themes in purple

The following processes/pathways are downregulated in both familial and sporadic ALS:

  • Immune related themes in purple

  • Growth signaling pathways in yellow

  • Cancer-related themes in orange

  • A single neural gliosis theme in green

Key Takeaways:

Despite different etiologies, transcriptomics analyses of familial and sporadic ALS share similar stress, inflammatory, and degeneration signatures.  Both familial and sporadic ALS have changes in immune processes. One of the largest and most conserved upregulated themes (as demonstrated by a greater number of concepts remaining in the sphere) is Histocompatibility (in blue). There is evidence that MHC class I genes may play a role in ALS. The largest and most conserved theme in the downregulated dataset includes genes related to gliosis, which is known to occur during late stages of ALS. 


Familial and sporadic ALS share lipid metabolism themes. Specifically, apolipoprotein metabolism is believed to be associated with ALS as well as other neurodegenerative diseases. The growth/differentiation processes and the cancer-related themes represent numerous signaling pathways that are activated/inhibited during neurodegeneration, and perhaps as a compensatory response to neuronal damage.



Let us know what you think

The findings highlighted in this post just scratch the surface. If you have additional thoughts on these analyses, see something interesting we missed, or have any other feedback on the results from this post, we’d love to hear from you! 


Stay tuned for the next post in this ALS series, where we will take a look at a mouse model of ALS and assess how well it models human disease.

*We are launching this webpage to share knowledge maps to encourage hypotheses generation. We invite you to share your ideas, insights, and feedback (“Feedback”) to help us create hypotheses in connection with therapies, treatments, and solutions. Please click on the links below which cover our Right to Use Feedback, and important Disclaimers. By submitting Feedback, you agree that you have read and agree to these terms. Thank you for your participation in this project.


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