METHOD AND MEDICAMENT FOR TREATING AMYOTROPHIC LATERAL SCLEROSIS

Abstract
Provided is a method and a medicament for treating amyotrophic lateral sclerosis (ALS) in a subject in need thereof, comprising administering to the subject an effective amount of one or more active agents selected from the group consisting of a retinoic acid receptor alpha (RARα) agonist, a voltage-gated potassium channel (KCNB2) inhibitor, an adrenergic receptor α2B (ADRA2B) antagonist, a DNA methyltransferase 3 alpha (DNMT3A) antagonist, an insulin like growth factor 1 receptor (IGF1R) inhibitor, a mitogen-activated protein kinase 1 (MAPK1) inhibitor, a nitric oxide synthase 1 (NOS1) inhibitor, a glucocorticoid receptors (NR3C1) antagonist, and a peptidylprolyl Isomerase A (PPIA) antagonist.
Description
FIELD

The present invention relates to the field of medicine, in particular, to a method for treating amyotrophic lateral sclerosis (ALS).


BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a rare neuromuscular disease caused by the degeneration of motor neurons (MNs) in the brain and spinal cord. It is the most common MN disease, with the incidence ranging from 0.6 to 3.8 per 100,000 person-years[1]. Approximately 16,500 persons were diagnosed with ALS in the United States in 2015. The onset of the disease is typically in middle adulthood, with mean survival time in the range of 3-5 years after diagnosis. Although the signs and symptoms of ALS vary due to the difference in the region of neurons being affected, patients usually experience painless progressive muscle weakness and paralysis.


Despite several strategies that have been proposed to classify ALS, the majority of studies categorizes the disease based on its root causes-familial or sporadic. Familial ALS contributes to 10% of the cases and involves mutations in specific genetic loci that are inherited in an autosomal dominant manner. Over 20 genetic risk factors were identified for fALS. Notably, SODI, TARDBP, C9orf72, and FUS have been extensively characterized. According to a pooled summary of mutation frequency in 111 studies, those four major ALS-associated genes could explain 47.7% fALS and 5.2% sALS cases[2], leaving a substantial fraction of the genetic basis of ALS, especially sALS (over 90% of ALS cases), undiscovered. Given the genetic involvement in ALS is heterogeneous, several pathophysiological mechanisms have been hypothesized, including aberrant proteostasis, altered RNA metabolism, nucleocytoplasmic transport defects, mitochondrial dysfunction, DNA repair defects, axonal transport defects, vesicle transport dysregulation, excitotoxicity, oligodendrocyte dysfunction, and neuroinflammation.


Till now, ALS remains an incurable disease due to an inadequate understanding of disease mechanisms. FDA has approved four drugs for the treatment of ALS, including Riluzole, Edaravone, Tiglutik (thickened Riluzole), and Nuedexta. Riluzole—an inhibitor of sodium channel α subunit—is the first FDA-approved neuroprotective agent for ALS and the only drug that prolongs the survival of ALS patients. It functions as an anti-excitotoxic agent and G protein-coupled receptor signaling activator[3]. Unfortunately, riluzole offers limited benefit to the patients by extending survival for 2-3 months. Edaravone is a potent antioxidant that protects nerve cells against reactive oxygen species-induced death. Multiple clinical studies have illustrated its effect on slowing disease progression in small subsets of ALS patients.


SUMMARY

The purpose of the present invention is to provide a therapy or combination therapy for the treatment of amyotrophic lateral sclerosis, as well as drug combinations and kits.


One aspect of the present invention provides a method for treating amyotrophic lateral sclerosis (ALS) in a subject in need thereof, the method comprises administering to the subject an effective amount of one or more active agents selected from the group consisting of a retinoic acid receptor alpha (RARα) agonist, a voltage-gated potassium channel (KCNB2) inhibitor, an adrenergic receptor α2B (ADRA2B) antagonist, a DNA methyltransferase 3 alpha (DNMT3A) antagonist, an insulin like growth factor 1 receptor (IGF1R) inhibitor, a mitogen-activated protein kinase 1 (MAPK1) inhibitor, a nitric oxide synthase 1 (NOS1) inhibitor, a glucocorticoid receptors (NR3C1) antagonist, and a peptidylprolyl Isomerase A (PPIA) antagonist.


In some embodiments, the retinoic acid receptor alpha (RARα) agonist is selected from acitretin and derivative thereof.


In some embodiments, the voltage-gated potassium channel (KCNB2) inhibitor is selected from dalfampridine and derivative thereof.


In some embodiments, the adrenergic receptor a 2B (ADRA2B) antagonist is selected from mirtazapine and derivative thereof.


In some embodiments, the DNA methyltransferase 3 alpha (DNMT3A) antagonist is selected from azacitidine, decitabine and derivatives thereof.


In some embodiments, the insulin like growth factor 1 receptor (IGF1R) inhibitor is selected from AXL-1717 and derivative thereof.


In some embodiments, the mitogen-activated protein kinase 1 (MAPK1) inhibitor is selected from ulixertinib and derivative thereof.


In some embodiments, the nitric oxide synthase 1 (NOS1) inhibitor is selected from ronopterin and derivative thereof.


In some embodiments, the glucocorticoid receptors (NR3C1) antagonist is selected from mifepristones, ORG-34517 and derivatives thereof.


In some embodiments, the peptidylprolyl Isomerase A (PPIA) antagonist is selected from cyclosporine and derivative thereof.


In some embodiments, the method comprises administering to the subject an effective amount of a first active agent and a second active agent, wherein the first active agent and the second active agent are different from each other and are independently selected from the group consisting of the retinoic acid receptor alpha (RARα) agonist, the voltage-gated potassium channel (KCNB2) inhibitor, the adrenergic receptor α2B (ADRA2B) antagonist, the DNA methyltransferase 3 alpha (DNMT3A) antagonist, the insulin like growth factor 1 receptor (IGF1R) inhibitor, the mitogen-activated protein kinase 1 (MAPK1) inhibitor, the nitric oxide synthase 1 (NOS1) inhibitor, the glucocorticoid receptors (NR3C1) antagonist and the peptidylprolyl Isomerase A (PPIA) antagonist.


In some embodiments, the first active agent is the retinoic acid receptor alpha (RARα) agonist and the second active agent is the voltage-gated potassium channel (KCNB2) inhibitor.


In some embodiments, the first active agent is the retinoic acid receptor alpha (RARα) agonist and the second active agent is the adrenergic receptor α2B (ADRA2B) antagonist.


In some embodiments, the first active agent is the voltage-gated potassium channel (KCNB2) inhibitor and the second active agent is the adrenergic receptor α2B (ADRA2B) antagonist.


In some embodiments, the first active agent and the second active agent are administered simultaneously, separately or sequentially.


In some embodiments, the method comprises administering to the subject an effective amount of a first active agent, a second active agent and a third active agent, wherein the first active agent, the second active agent and the third active agent are different from each other and are independently selected from the group consisting of the retinoic acid receptor alpha (RARα) agonist, the voltage-gated potassium channel (KCNB2) inhibitor, the adrenergic receptor α2B (ADRA2B) antagonist, the DNA methyltransferase 3 alpha (DNMT3A) antagonist, the insulin like growth factor 1 receptor (IGF1R) inhibitor, the mitogen-activated protein kinase 1 (MAPK1) inhibitor, the nitric oxide synthase 1 (NOS1) inhibitor, the glucocorticoid receptors (NR3C1) antagonist and the peptidylprolyl Isomerase A (PPIA) antagonist.


In some embodiments, the first active agent is the retinoic acid receptor alpha (RARα) agonist, the second active agent is the voltage-gated potassium channel (KCNB2) inhibitor and the third active agent is the adrenergic receptor α2B (ADRA2B) antagonist.


In some embodiments, the first active agent, the second active agent and the third active agent are administered simultaneously, separately or sequentially.


Another aspect of the present invention provides a combination of two or more active agents selected from the group consisting of a retinoic acid receptor alpha (RARα) agonist, a voltage-gated potassium channel (KCNB2) inhibitor, an adrenergic receptor α2B (ADRA2B) antagonist, a DNA methyltransferase 3 alpha (DNMT3A) antagonist, an insulin like growth factor 1 receptor (IGFIR) inhibitor, a mitogen-activated protein kinase 1 (MAPK1) inhibitor, a nitric oxide synthase 1 (NOS1) inhibitor, a glucocorticoid receptors (NR3C1) antagonist, and a peptidylprolyl Isomerase A (PPIA) antagonist; wherein the combination is used for the treatment of amyotrophic lateral sclerosis.


In some embodiments, the retinoic acid receptor alpha (RARα) agonist is selected from acitretin and derivative thereof.


In some embodiments, the voltage-gated potassium channel (KCNB2) inhibitor is selected from dalfampridine and derivative thereof.


In some embodiments, the adrenergic receptor α2B (ADRA2B) antagonist is selected from mirtazapine and derivative thereof.


In some embodiments, the DNA methyltransferase 3 alpha (DNMT3A) antagonist is selected from azacitidine, decitabine and derivatives thereof.


In some embodiments, the insulin like growth factor 1 receptor (IGF1R) inhibitor is selected from AXL-1717 and derivative thereof.


In some embodiments, the mitogen-activated protein kinase 1 (MAPK1) inhibitor is selected from ulixertinib and derivative thereof.


In some embodiments, the nitric oxide synthase 1 (NOS1) inhibitor is selected from ronopterin and derivative thereof.


In some embodiments, the glucocorticoid receptors (NR3C1) antagonist is selected from mifepristones, ORG-34517 and derivatives thereof.


In some embodiments, the peptidylprolyl Isomerase A (PPIA) antagonist is selected from cyclosporine and derivative thereof.


In some embodiments, the combination comprises a first active agent and a second active agent, wherein the first active agent and the second active agent are different from each other and are independently selected from the group consisting of the retinoic acid receptor alpha (RARα) agonist, the voltage-gated potassium channel (KCNB2) inhibitor, the adrenergic receptor α2B (ADRA2B) antagonist, the DNA methyltransferase 3 alpha (DNMT3A) antagonist, the insulin like growth factor 1 receptor (IGF1R) inhibitor, the mitogen-activated protein kinase 1 (MAPK1) inhibitor, the nitric oxide synthase 1 (NOS1) inhibitor, the glucocorticoid receptors (NR3C1) antagonist and the peptidylprolyl Isomerase A (PPIA) antagonist.


In some embodiments, the first active agent is the retinoic acid receptor alpha (RARα) agonist and the second active agent is the voltage-gated potassium channel (KCNB2) inhibitor.


In some embodiments, the first active agent is the retinoic acid receptor alpha (RARα) agonist and the second active agent is the adrenergic receptor α2B (ADRA2B) antagonist.


In some embodiments, the first active agent is the voltage-gated potassium channel (KCNB2) inhibitor and the second active agent is the adrenergic receptor α2B (ADRA2B) antagonist.


In some embodiments, the combination comprises a first active agent, a second active agent and a third active agent, wherein the first active agent, the second active agent and the third active agent are different from each other and are independently selected from the group consisting of the retinoic acid receptor alpha (RARα) agonist, the voltage-gated potassium channel (KCNB2) inhibitor, the adrenergic receptor α2B (ADRA2B) antagonist, the DNA methyltransferase 3 alpha (DNMT3A) antagonist, the insulin like growth factor 1 receptor (IGF1R) inhibitor, the mitogen-activated protein kinase 1 (MAPK1) inhibitor, the nitric oxide synthase 1 (NOS1) inhibitor, the glucocorticoid receptors (NR3C1) antagonist and the peptidylprolyl Isomerase A (PPIA) antagonist.


In some embodiments, the first active agent is the retinoic acid receptor alpha (RARα) agonist, the second active agent is the voltage-gated potassium channel (KCNB2) inhibitor and the third active agent is the adrenergic receptor α2B (ADRA2B) antagonist.


Another aspect of the present invention provides a pharmaceutical composition comprising any one of the above-mentioned combinations and a pharmaceutically acceptable carrier, wherein the combination may be used for the treatment of amyotrophic lateral sclerosis.


Another aspect of the present invention provides a kit comprising any one of the above-mentioned combinations or the above-mentioned pharmaceutical composition and an instruction for use, wherein the instruction describes the use of the combination or the pharmaceutical composition for treating amyotrophic lateral sclerosis.


In some embodiments, in the kit, the two or more active agents are contained in the same or separate containers.


Another aspect of the present invention provides use of one or more active agents selected from the group consisting of a retinoic acid receptor alpha (RARα) agonist, a voltage-gated potassium channel (KCNB2) inhibitor, an adrenergic receptor α2B (ADRA2B) antagonist, a DNA methyltransferase 3 alpha (DNMT3A) antagonist, an insulin like growth factor 1 receptor (IGF1R) inhibitor, a mitogen-activated protein kinase 1 (MAPK1) inhibitor, a nitric oxide synthase 1 (NOS1) inhibitor, a glucocorticoid receptors (NR3C1) antagonist, and a peptidylprolyl Isomerase A (PPIA) antagonist in the manufacture of a medicament for treating amyotrophic lateral sclerosis.


In some embodiments, the retinoic acid receptor alpha (RARα) agonist is selected from acitretin and derivative thereof.


In some embodiments, the voltage-gated potassium channel (KCNB2) inhibitor is selected from dalfampridine and derivative thereof.


In some embodiments, the adrenergic receptor α2B (ADRA2B) antagonist is selected from mirtazapine and derivative thereof.


In some embodiments, the DNA methyltransferase 3 alpha (DNMT3A) antagonist is selected from azacitidine, decitabine and derivatives thereof.


In some embodiments, the insulin like growth factor 1 receptor (IGF1R) inhibitor is selected from AXL-1717 and derivative thereof.


In some embodiments, the mitogen-activated protein kinase 1 (MAPK1) inhibitor is selected from ulixertinib and derivative thereof.


In some embodiments, the nitric oxide synthase 1 (NOS1) inhibitor is selected from ronopterin and derivative thereof.


In some embodiments, the glucocorticoid receptors (NR3C1) antagonist is selected from mifepristones, ORG-34517 and derivatives thereof.


In some embodiments, the peptidylprolyl Isomerase A (PPIA) antagonist is selected from cyclosporine and derivative thereof.


In some embodiments, said one or more active agents comprise a combination of a first active agent and a second active agent, wherein the first active agent and the second active agent are different from each other and are independently selected from the group consisting of the retinoic acid receptor alpha (RARα) agonist, the voltage-gated potassium channel (KCNB2) inhibitor, the adrenergic receptor α2B (ADRA2B) antagonist, the DNA methyltransferase 3 alpha (DNMT3A) antagonist, the insulin like growth factor 1 receptor (IGF1R) inhibitor, the mitogen-activated protein kinase 1 (MAPK1) inhibitor, the nitric oxide synthase 1 (NOS1) inhibitor, the glucocorticoid receptors (NR3C1) antagonist and the peptidylprolyl Isomerase A (PPIA) antagonist.


In some embodiments, the first active agent is the retinoic acid receptor alpha (RARα) agonist and the second active agent is the voltage-gated potassium channel (KCNB2) inhibitor.


In some embodiments, the first active agent is the retinoic acid receptor alpha (RARa) agonist and the second active agent is the adrenergic receptor α2B (ADRA2B) antagonist.


In some embodiments, the first active agent is the voltage-gated potassium channel (KCNB2) inhibitor and the second active agent is the adrenergic receptor a 2B (ADRA2B) antagonist.


In some embodiments, said one or more active agents comprise a combination of a first active agent, a second active agent and a third active agent, wherein the first active agent, the second active agent and the third active agent are different from each other and are selected from the group consisting of the retinoic acid receptor alpha (RARα) agonist, the voltage-gated potassium channel (KCNB2) inhibitor, the adrenergic receptor α2B (ADRA2B) antagonist, the DNA methyltransferase 3 alpha (DNMT3A) antagonist, the insulin like growth factor 1 receptor (IGFIR) inhibitor, the mitogen-activated protein kinase 1(MAPK1) inhibitor, the nitric oxide synthase 1 (NOS1) inhibitor, the glucocorticoid receptors (NR3C1) antagonist and the peptidylprolyl Isomerase A (PPIA) antagonist.


In some embodiments, the first active agent is the retinoic acid receptor alpha (RARα) agonist, the second active agent is the voltage-gated potassium channel (KCNB2) inhibitor and the third active agent is the adrenergic receptor α2B (ADRA2B) antagonist.


Another aspect of the present invention provides a medicament for use in the treatment of amyotrophic lateral sclerosis, wherein the medicament comprises one or more active agents selected from the group consisting of a retinoic acid receptor alpha (RARα) agonist, a voltage-gated potassium channel (KCNB2) inhibitor, an adrenergic receptor α2B (ADRA2B) antagonist, a DNA methyltransferase 3 alpha (DNMT3A) antagonist, an insulin like growth factor 1 receptor (IGF1R) inhibitor, a mitogen-activated protein kinase 1(MAPK1) inhibitor, a nitric oxide synthase 1 (NOS1) inhibitor, a glucocorticoid receptors (NR3C1) antagonist, and a peptidylprolyl Isomerase A (PPIA) antagonist.


In some embodiments, the retinoic acid receptor alpha (RARα) agonist is selected from acitretin and derivative thereof.


In some embodiments, the voltage-gated potassium channel (KCNB2) inhibitor is selected from dalfampridine and derivative thereof.


In some embodiments, the adrenergic receptor α2B (ADRA2B) antagonist is selected from mirtazapine and derivative thereof.


In some embodiments, the DNA methyltransferase 3 alpha (DNMT3A) antagonist is selected from azacitidine, decitabine and derivatives thereof.


In some embodiments, the insulin like growth factor 1 receptor (IGF1R) inhibitor is selected from AXL-1717 and derivative thereof.


In some embodiments, the mitogen-activated protein kinase 1 (MAPK1) inhibitor is selected from ulixertinib and derivative thereof.


In some embodiments, the nitric oxide synthase 1 (NOS1) inhibitor is selected from ronopterin and derivative thereof.


In some embodiments, the glucocorticoid receptors (NR3C1) antagonist is selected from mifepristones, ORG-34517 and derivatives thereof.


In some embodiments, the peptidylprolyl Isomerase A (PPIA) antagonist is selected from cyclosporine and derivative thereof.


In some embodiments, the medicament comprises a combination of a first active agent and a second active agent, wherein the first active agent and the second active agent are different from each other and are selected from the group consisting of the retinoic acid receptor alpha (RARα) agonist, the voltage-gated potassium channel (KCNB2) inhibitor, the adrenergic receptor α2B (ADRA2B) antagonist, the DNA methyltransferase 3 alpha (DNMT3A) antagonist, the insulin like growth factor 1 receptor (IGF1R) inhibitor, the mitogen-activated protein kinase 1 (MAPK1) inhibitor, the nitric oxide synthase 1 (NOS1) inhibitor, the glucocorticoid receptors (NR3C1) antagonist and the peptidylprolyl Isomerase A (PPIA) antagonist.


In some embodiments, the first active agent is the retinoic acid receptor alpha (RARα) agonist and the second active agent is the voltage-gated potassium channel (KCNB2) inhibitor.


In some embodiments, the first active agent is the retinoic acid receptor alpha (RARα) agonist and the second active agent is the adrenergic receptor α2B (ADRA2B) antagonist.


In some embodiments, the first active agent is the voltage-gated potassium channel (KCNB2) inhibitor and the second active agent is the adrenergic receptor α2B (ADRA2B) antagonist.


In some embodiments, the medicament comprises a combination of a first active agent, a second active agent and a third active agent, wherein the first active agent, the second active agent and the third active agent are different from each other and are selected from the group consisting of the retinoic acid receptor alpha (RARα) agonist, the voltage-gated potassium channel (KCNB2) inhibitor, the adrenergic receptor α2B (ADRA2B) antagonist, the DNA methyltransferase 3 alpha (DNMT3A) antagonist, the insulin like growth factor 1 receptor (IGF1R) inhibitor, the mitogen-activated protein kinase 1 (MAPK1) inhibitor, the nitric oxide synthase 1 (NOS1) inhibitor, the glucocorticoid receptors (NR3C1) antagonist and the peptidylprolyl Isomerase A (PPIA) antagonist.


In some embodiments, the first active agent is the retinoic acid receptor alpha (RARα) agonist, the second active agent is the voltage-gated potassium channel (KCNB2) inhibitor and the third active agent is the adrenergic receptor α2B (ADRA2B) antagonist.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 shows ALS-related datasets in PandaOmics™.



FIG. 2 shows filter setting for high-confidence targets identification.



FIG. 3 shows filter setting for novel targets identification.



FIG. 4 shows schematic representation of scoring-approach validation.



FIG. 5 shows network of dysregulated pathways in CNS comparisons. Each node represents a dysregulated pathway consisting of a set of genes. Nodes with similar gene contents (similarity coefficient >0.35) were connected by edges, and the thickness of node-linking edges is proportional to the similarity between a pair of gene sets. Clusters of pathways were annotated based on the hierarchical level of pathways retrieved from the Reactome database.



FIG. 6 shows network of dysregulated pathways in diMN comparisons. Notations refer to FIG. 5.



FIG. 7 shows flowchart for ALS target discovery and drug repurposing.





DETAILED DESCRIPTION

It should be understood that this invention is not limited to particular embodiments described herein. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present invention will be limited only by the appended claims.


Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present invention, the preferred methods and materials are now described. All publications mentioned herein are to disclose and describe the methods and/or materials in connection with which the publications are cited.


Where a range of values with one or two limits is provided, it is understood that a smaller range between any stated intervening value in that stated range and either limit of that stated range is encompassed within the invention. Where the stated range includes one or two limits, ranges excluding either or both of the limits are also included in the invention.


Terminology

It must be noted that as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise. It is further noted that the claims may be drafted to exclude any optional element. As such, this statement is intended to serve as antecedent basis for use of such exclusive terminology as “solely,” “only” and the like in connection with the recitation of claim elements, or use of a “negative” limitation.


Unless otherwise stated, the term “comprise”, “include”, “contain” and variations of these terms, such as comprising, comprises and comprised, are not intended to exclude further members, components, integers or steps. These terms also encompass the meaning of “consist of” or “consisting of”. The term “consist of” or “consisting of” is a particular embodiment of the term “comprise”, wherein any other non-stated member, component, integer or step is excluded.


The term “about” refers to a range equal to the particular value plus or minus ten percent (+/−10%).


The term “and/or” refers to any one, several or all of the elements connected by the term.


The term “amyotrophic lateral sclerosis (ALS)” is also called classical motor neuron disease (MND), which is a progressive fatal neuromuscular disorder that is characterized by weakness, muscle wasting, and fasciculations (increased reflexes). Cognitive function is retained except where ALS is associated with dementia. The disease primarily affects motor neurons and is characterized by progressive degeneration of the motor neurons in the cerebral cortex, brainstem nuclei and anterior horns of the spinal cord. Individuals afflicted by the disease exhibit weakness of limbs and difficulty in speech and swallowing.


The term “treat”, “treating” or “treatment”, as used herein, refers to alleviating, inhibiting and/or reversing the progress of a disease (such as ALS). The term “treating” is inclusive of any indicia of success in the treatment or amelioration of the disease, including any objective or subjective parameter such as abatement; remission; diminishing of symptoms or making the injury, pathology or condition more tolerable to the subject; delaying or slowing in the rate of progression, etc. Measurement of the treatment or amelioration may be based on, e.g., the results of a physical examination, a pathological test and/or a diagnostic test as known in the art. Treating may also refer to reducing the incidence or onset of a disease, or a recurrence thereof (such as a lengthening in time of remission), as compared to that which would occur in the absence of the measure taken. Clinically, such a treatment can also be called prevention.


The term “active agent”, as used herein, refers to a pharmaceutically active chemical that provides some pharmacologic effect and is used for treating or preventing a disease, such as ALS.


The term “inhibitor” and “antagonist”, as used herein, can be used interchangeably and refer to any molecule that partially or fully blocks or inhibits an activity of a target (such as the protein used as a target in the present invention). In a similar manner, the term “agonist” refers to any molecule that stimulates, activates, enhances an activity of a target (such as the protein used as a target in the present invention).


The term “derivative” of a compound, as used herein, refers to any pharmaceutically acceptable molecule that is derived from (i.e., structurally related to) the compound and has similar or substantially the same activity as the compound, which upon administration to a subject is capable of providing (directly or indirectly) a compound of the active agent or an active metabolite thereof. Examples of the derivatives include, but are not limited to, pharmaceutically acceptable salt, hydrate, solvate, prodrug or metabolite.


The term “pharmaceutically acceptable salt”, as used herein, refers to a relatively nontoxic, inorganic or organic acid salt of a compound of the invention. These salts may be prepared in situ during the final isolation and purification of the compounds or by reacting the purified compound in its free form separately with a suitable organic or inorganic acid and isolating the salt thus formed. Representative acid salts include, but are not limited to, acetate, adipate, aspartate, benzoate, besylate, bicarbonate/carbonate, bisulphate/sulphate, borate, camsylate, citrate, cyclamate, edisylate, esylate, formate, fumarate, gluceptate, gluconate, glucuronate, hexafluorophosphate, hibenzate, hydrochloride/chloride, hydrobromide/bromide, hydroiodide/iodide, isethionate, lactate, malate, maleate, malonate, mesylate, methylsulphate, naphthylate, 2-napsylate, nicotinate, nitrate, orotate, oxalate, palmitate, pamoate, phosphate/hydrogen phosphate/dihydrogen phosphate, pyroglutamate, saccharate, stearate, succinate, tannate, tartrate, tosylate, trifluoroacetate and xinafoate salts. In one embodiment, the pharmaceutically acceptable salt is a hydrochloride/chloride salt.


The term “solvate”, as used herein, refers to a complex of variable stoichiometry formed by a solute (e.g., the active agent of the present invention) and a solvent. Such solvents for the purpose of the invention may not interfere with the biological activity of the solute. Examples of suitable solvents include, but are not limited to, water, methanol, ethanol and acetic acid.


The term “prodrug” of a compound, as used herein, refers to a precursor, which when administered to a biological system, generates said compound as a result. For example, prodrugs can have the structure X-drug wherein X is an inert carrier moiety and drug is the active compound,


The term “metabolite” of a compound, as used herein, refers to a molecule which results from a modification or processing of the compound after administration to a subject. The term “metabolite” may designate a modified or processed drug that retains at least part of the activity of the parent compound.


The term “combination”, as used herein, refers to two or more active agents and/or therapies which may be administered simultaneously or sequentially, in a single dosage form or separately. The two or more active agents and/or therapies in a combination may be administered through different routes and protocols. The two or more active agents in a combination may be formulated together or separately.


The term “simultaneous” or “simultaneously”, as used herein, means the administration of each of the two or more active agents to a subject at the same time. The two or more active agents may be formulated into a single dosage form (fixed dose combination) or separate dosage forms (non-fixed).


The term “separate” or “separately”, as used herein, means the administration of each of the two or more active agents to a subject from separate (non-fixed) dosage forms simultaneously or sequentially in any order. There may be a specified time interval for administration of each active agent.


The term “sequential” or “sequentially”, as used herein, means the administration of each of the two or more active agents to a subject from separate (non-fixed) dosage forms in separate actions. The two administration actions may be linked by a specified time interval. The term “pharmaceutical composition”, as used herein, can be used interchangeably with “pharmaceutical formulation” or “formulation” and refers to a formulation comprising at least one active agent and at least one pharmaceutically acceptable carrier.


The term “pharmaceutically acceptable”, as used herein, refers to those compounds, materials, compositions, and/or dosage forms which are, within the scope of sound medical judgment, suitable for contact with the tissues of a subject without excessive toxicity, irritation, allergic response, or other problem complications commensurate with a reasonable benefit/risk ratio.


The term “pharmacologically acceptable carrier”, as used herein, refers to any carrier that has substantially no long term or permanent detrimental effect when administered to a subject, such as a stabilizer, diluent, additive, auxiliary, excipient and the like. “Pharmaceutically acceptable carrier” should be a pharmaceutically inert material that has substantially no biological activity and constitutes a substantial part of the formulation.


The term “subject”, as used herein, refers to any organism to which the active agent of the composition of the present invention may be administered, e.g., for experimental, diagnostic, prophylactic, and/or therapeutic purposes. Typical subjects include animals (e.g., mammals such as mice, rats, rabbits, non-human primates such as chimpanzees and other apes and monkey species, and humans). The subject may be a mammal, particularly a human, including a male or female, and including a neonatal, infant, juvenile, adolescent, adult or geriatric, and further is inclusive of various races and ethnicities.


The term “therapeutically effective dose” or “effective dose”, as used herein, which can be used interchangeably with “therapeutically effective amount” or “effective amount”, refers to an amount that is effective for treating a disease (such as ALS) as noted through clinical testing and evaluation, patient observation, and/or the like. An “effective amount” can further designate an amount that causes a detectable change in biological or chemical activity. The detectable changes may be detected and/or further quantified by one skilled in the art for the relevant mechanism or process. Moreover, an “effective amount” can designate an amount that maintains a desired physiological state, i.e., reduces or prevents significant decline and/or promotes improvement in the condition.


The term “unit dosage form”, as used herein, refers to physically discrete units (such as capsules, tablets, or loaded syringe cylinders) suitable as unitary dosages for a subject, each unit containing a predetermined quantity of active agent calculated to produce the desired therapeutic effect, in association with the required pharmaceutical carrier.


The term “unit dose”, as used herein, refers to a dose of a substance (such as an active agent of the present invention) in a unit dosage form.


Active Agents for Treating ALS

The inventor discovered through extensive research several targets for treating ALS, including retinoic acid receptor alpha (RARα), voltage-gated potassium channel (KCNB2), adrenergic receptor α2B (ADRA2B), DNA methyltransferase 3 alpha (DNMT3A), insulin like growth factor 1 receptor (IGF1R), mitogen-activated protein kinase 1 (MAPK1), nitric oxide synthase 1 (NOS1), glucocorticoid receptors (NR3C1), and peptidylprolyl Isomerase A (PPIA). An agonist or antagonist of one or more of these targets may be used to treat ALS.


The active agent used to treat ALS can be any one selected from the group consisting of a retinoic acid receptor alpha (RARα) agonist, a voltage-gated potassium channel (KCNB2) inhibitor, an adrenergic receptor α2B (ADRA2B) antagonist, a DNA methyltransferase 3 alpha (DNMT3A) antagonist, an insulin like growth factor 1 receptor (IGF1R) inhibitor, a mitogen-activated protein kinase 1 (MAPK1) inhibitor, a nitric oxide synthase 1 (NOS1) inhibitor, a glucocorticoid receptors (NR3C1) antagonist, and a peptidylprolyl Isomerase A (PPIA) antagonist.


Any one of the above active agents can be used alone or in combination with any one or several other active agents. A combination of active agents may include two, three, four, five or more active agents of the present invention. When two or more active agents are used in combination, they may be administered together or separately, at the same time or sequentially. The two or more active agents in a combination may be administered through different routes and protocols. The two or more active agents in a combination may be formulated together to a single dosage form or be formulated separately to two or more separate formulations (for example, each active agent is formulated to an individual pharmaceutical composition having the same or different dosage form). Any one or any combination of two or more of active agents of the present invention can be administered as the pure chemical or be formulated to a pharmaceutical composition before administration. The medicament of the present invention may comprise any one or a combination of two or more active agents of the present invention.


Retinoic acid receptor alpha (RARα), also known as NR1B1 (nuclear receptor subfamily 1, group B, member 1) is a nuclear receptor a transcriptional activator in the retinoid signaling pathway that in humans is encoded by the RARA gene. A preferred agonist of RARαis acitretin. Acitretin is (2E,4E,6E,8E)-9-(4-methoxy-2,3,6-trimethylphenyl)-3,7-dimethylnona-2,4,6,8-tetraenoic acid, which is sold under the trade name Soriatane® or Neotigason®. Acitretin is a synthetic aromatic analogue of retinoic acid (Vitamin A derivative and an active metabolite of etretinate. Acitretin is an agonist of retinoic acid receptors. Potassium voltage-gated channel subfamily B member 2 (KCNB2) belongs to a family of voltage-gated potassium channel and is encoded by the KONB2 gene in humans. inhibitors of potassium voltage-gated channel subfamily B member 2 (KCNB2) include, but are not limited to, dalfampridine. Dalfampridine is the United States Adopted Name (USAN) for the chemical 4-aminopyridine (4-AP), which is a potassium channel blocker. Dalfampridine is sold under the trade name Ampyra®.


Adrenergic receptor α2B (ADRA2B) is a G-protein coupled receptor. It is a subtype of the adrenergic receptor family and is encoded by the ADRA2B gene in humans. Antagonists of adrenergic receptor α2B (ADRA2B) include, but are not limited to, mirtazapine. Mirtazapine is 1,2,3,4,10,14b-hexahydro-2-methylpyrazino [2,1-2]pyrido [2,3-c][2] benzazepine and is sold under the name of Remeron® or RemeronSolTab®. Mirtazapine functions as a strong antagonist of serotonin receptors and adrenergic receptors, including ADRA2B.


DNA methyltransferase 3 alpha (DNMT3A) is an enzyme that catalyzes the transfer of methyl groups to specific CpG structures in DNA, a process called DNA methylation and is encoded by DNMT3A gene in humans. Antagonists of DNA methyltransferase 3 alpha (DNMT3A) include, but are not limited to, azacitidine and decitabine. Azacitidine is 5-azacytidine and is sold under the trade name Vidaza®. Decitabine is 5-aza-2′-deoxycytidine and is sold under the trade name Dacogen®.


Insulin like growth factor 1 receptor (IGF1R) is a transmembrane receptor that is activated by a hormone called insulin-like growth factor 1 (IGF-1) and by a related hormone called IGF-2. It belongs to the large class of tyrosine kinase receptors. Insulin like growth factor 1 receptor (IGF1R) is encoded by IGF1R gene in humans. Antagonists of insulin like growth factor 1 receptor (IGF1R) include, but are not limited to, AXL-1717, which is also called picropodophyllin with a CAS No. 477-47-4.


Mitogen-activated protein kinase 1 (MAPK1) is a member of the MAP kinase family and is encoded by MAPK1 gene in humans. Antagonists of mitogen-activated protein kinase 1 (MAPK1) include, but are not limited to, ulixertinib. Ulixertinib is also called BVD-523 or VRT752271, and has a CAS No. 869886-67-9.


Nitric oxide synthase 1 (NOS1) is also known as neuronal nitric oxide synthase (nNOS). NOSI synthesizes nitric oxide (NO) from L-arginine and is encoded by the NOSI gene in humans. Antagonist of nitric oxide synthase 1 (NOS1) include, but are not limited to, ronopterin. Ronopterin is also called VAS203 and has a CAS No. 206885-38-3.


Nuclear receptor subfamily 3 group C member 1 (NR3C1) is also known as glucocorticoid receptor and is the receptor to which cortisol and other glucocorticoids bind. Nuclear receptor subfamily 3 group C member 1 (NR3C1) is encoded by the NR3C1 gene in humans. Antagonists of NR3C1 include, but are not limited to, mifepristone and ORG-34517.Mifepristone is also known as RU-486, which is 11β-[p-(dimethylamino) phenyl]-17α-(1-propynyl)estra-4,9-dien-17β-ol-3-one. Mifepristone is sold under the trade name Mifegyne®. ORG-34517 has a CAS No. 189035-07-2.


Peptidylprolyl isomerase A (PPIA) is also known as cyclophilin A (CypA) or rotamase A and is encoded by the PPIA gene in humans. Antagonists of peptidylprolyl isomerase A (PPIA) include, but are not limited to, cyclosporine. Cyclosporine, also spelled cyclosporine and cyclosporin, is a calcineurin inhibitor and is sold under the trade name Neoral®, Sandimmune® or Restasis®.


The amount of each of the active agents in a unit dosage form may be 1-1000 mg, such as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 50, 60, 70, 75, 80, 90, 100, 110, 120, 125, 130, 140, 150, 160, 170, 175, 180, 190, 200, 250, 300, 350, 400, 450, 500, 600, 700, 750, 800, 900, 1000 mg or any range between any two of the above specific values.


In some embodiments, a combination of two active agents (a first active agent and a second active agent) is used to treat ALS. The first active agent and the second active agent are different from each other. The first active agent and the second active agent are select from the group consisting of a retinoic acid receptor alpha (RARα) agonist, a voltage-gated potassium channel (KCNB2) inhibitor, an adrenergic receptor α2B (ADRA2B) antagonist, a DNA methyltransferase 3 alpha (DNMT3A) antagonist, an insulin like growth factor 1 receptor (IGF1R) inhibitor, a mitogen-activated protein kinase 1 (MAPK1) inhibitor, a nitric oxide synthase 1 (NOS1) inhibitor, a glucocorticoid receptors (NR3C1) antagonist, and a peptidylprolyl Isomerase A (PPIA) antagonist. The two active agents may be formulated in a single dosage form or separately.


In some embodiments, the first active agent may be the retinoic acid receptor alpha (RARα) agonist and the second active agent may be other active agent, such as the voltage-gated potassium channel (KCNB2) inhibitor or the adrenergic receptor α2B (ADRA2B) antagonist. In some embodiments, the first active agent may be the voltage-gated potassium channel (KCNB2) inhibitor and the second active agent may be other active agent, such as the adrenergic receptor α2B (ADRA2B) antagonist.


The dosage ratio of the first active agent and the second active agent may be in the range of 1:100-100:1, 1:80-80:1, 1:50-50:1, 1:40-40:1, 1:30-30:1, 1:20-20:1, 1:10-10:1, 1:5-5:1, 1:4-4:1, 1:3-3:1, 1:2-2:1 or 1:1 by molar ratio, for example, in the single dosage form.


The amount of the first active agent in a unit dosage form may be 1-1000 mg, such as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 50, 60, 70, 75, 80, 90, 100, 110, 120, 125, 130, 140, 150, 160, 170, 175, 180, 190, 200, 250, 300, 350, 400, 450, 500, 600, 700, 750, 800, 900, 1000 mg or any range between any two of the above specific values. The amount of the second active agent in a unit dosage form may be 1-1000 mg, such as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 50, 60, 70, 75, 80, 90, 100, 110, 120, 125, 130, 140, 150, 160, 170, 175, 180, 190, 200, 250, 300, 350, 400, 450, 500, 600, 700, 750, 800, 900, 1000 mg or any range between any two of the above specific values.


In some embodiments, a combination of three active agents (a first active agent, a second active agent and a third active agent) is used to treat ALS. The first active agent, the second active agent and the third active agent are different from each other. The first active agent, the second active agent and the third active agent are independently selected from the group consisting of a retinoic acid receptor alpha (RARα) agonist, a voltage-gated potassium channel (KCNB2) inhibitor, an adrenergic receptor α2B (ADRA2B) antagonist, a DNA methyltransferase 3 alpha (DNMT3A) antagonist, an insulin like growth factor 1 receptor (IGF1R) inhibitor, a mitogen-activated protein kinase 1 (MAPK1) inhibitor, a nitric oxide synthase 1 (NOS1) inhibitor, a glucocorticoid receptors (NR3C1) antagonist, and a peptidylprolyl Isomerase A (PPIA) antagonist. The two active agents may be formulated in a single dosage form or separately.


In some embodiments, the first active agent may be the retinoic acid receptor alpha (RARα) agonist, the second active agent may be the voltage-gated potassium channel (KCNB2) inhibitor and the third active agent may be the adrenergic receptor α2B (ADRA2B) antagonist.


The dosage ratio of the first active agent, the second active agent and the third active agent may be 1:100:100-100:100:1, 1:80:80-80:80:1, 1:50:50-50:50:1, 1:30:30-30:30:1, 1:20:20-20:20:1, 1:10: 10-10:10:1, 1:5:5-5:5:1, 1:4:4-4:4:1, 1:3:3-3:3:1, 1:2:2-2:2:1 or 1:1:1 by molar ratio, for example, in the single dosage form.


The amount of the first active agent in a unit dosage form may be 1-1000 mg, such as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 50, 60, 70, 75, 80, 90, 100, 110, 120, 125, 130, 140, 150, 160, 170, 175, 180, 190, 200, 250, 300, 350, 400, 450, 500, 600, 700, 750, 800, 900, 1000 mg or any range between any two of the above specific values. The amount of the second active agent in a unit dosage form may be 1-1000 mg, such as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 50, 60, 70, 75, 80, 90, 100, 110, 120, 125, 130, 140, 150, 160, 170, 175, 180, 190, 200, 250, 300, 350, 400, 450, 500, 600, 700, 750, 800, 900, 1000 mg or any range between any two of the above specific values. The amount of the third active agent in a unit dosage form may be 1-1000 mg, such as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 50, 60, 70, 75, 80, 90, 100, 110, 120, 125, 130, 140, 150, 160, 170, 175, 180, 190, 200, 250, 300, 350, 400, 450, 500, 600, 700, 750, 800, 900, 1000 mg or any range between any two of the above specific values.


Administration

Each of the active agent of the present invention may be administered to the subject via oral, buccal, sublingual, rectal, vaginal, parenteral, intradermal or intranasal or parenteral route. The parenteral administration includes intravenous, intraperitoneal, intradermal, subcutaneous, intramuscular, intracranial, intrathecal, intratumoral, transdermal, transmucosal intraarticular, intra-synovial, intrasternal, intrathecal, intrahepatic, intralesional or intracranial injection or infusion.


The active agent(s) as used herein may be formulated for administration in a pharmaceutical composition in accordance with known techniques. See, for example, Remington, The Science and Practice of Pharmacy (9th Ed. 1995). In the manufacture of a pharmaceutical composition according to the present invention, the active agent is typically admixed with, inter alia, a pharmaceutical acceptable carrier. The carrier must, of course, be acceptable in the sense of being compatible with any other ingredients in the formulation and must not be deleterious to the patient. The carrier may be a solid or a liquid, or both, and is preferably formulated with the compound as a unit-dose formulation, for example, a tablet, which may contain from 0.01% or 0.5% to 95% or 99% by weight of the active agent. One or more active agents may be incorporated in the formulations of the invention, which may be prepared by any of the well-known techniques of pharmacy comprising admixing the components, optionally including one or more accessory ingredients and/or excipients. In some embodiments, any of the compositions, carriers, accessory ingredients excipients and/or the formulations of the invention comprise ingredients that are from either natural or non-natural sources. In other embodiments, any component of the compositions, carriers, accessory ingredients, excipients and/or the formulations of the invention may be provided in a sterile form. Non-limiting examples of a sterile carrier include endotoxin-free water or pyrogen-free water.


In some embodiments, the pharmaceutical composition of the invention is provided as part of a sterile composition/formulation comprising an active agent of the invention and a pharmaceutically acceptable carrier and/or excipient.


Dosage forms suitable for the oral administration include tablet, capsule, powder, pill, granule, suspension, solution or preconcentrate of solution, emulsion or preconcentrates of emulsion. Pharmaceutical acceptable carriers that can be used in an oral dosage form include water, glycols, oils, alcohols, flavoring agents, preservatives, coloring agents and the like. Carriers such as starches, sugars, microcrystalline cellulose, diluents, filler, glidants, granulating agents, lubricants, binders, stabilizers, disintegrating agents and the like can be used to prepare an oral solid preparation such as powder, capsule or tablet.


The diluent includes, but not limited to, microcrystalline cellulose, mannitol, powdered sugar, compressible sugar, dextran, dextrin, spinose, lactose, cellulose powder, sorbitol, sucrose and Talc powder or a combination thereof. The diluent may be 5% to 90% based on the total weight of the oral composition, preferably 10% to 80%, 20%-70%, 30%-60%, 40%-50%.


The disintegrating agent includes, but not limited to, cellulose, alginate, gum, cross-linked polymer, such as cross-linked polyvinylpyrrolidone or crospovidone, croscarmellose sodium, croscarmellose calcium, soybean polysaccharide, sodium starch glycolate, guar gum or any combination thereof. The disintegrating agent may be present in an amount of about 1% to 15%, preferably 2% to 10%, based on the total weight of the oral composition.


The binder includes, but not limited to, starch, cellulose or derivatives thereof, such as microcrystalline cellulose, hydroxypropyl cellulose, hydroxyethyl cellulose and hydroxypropyl methyl cellulose, sucrose, dextrose, corn syrup, polysaccharide, gelatin or any combination thereof. The binder may be present in an amount of 0.01 to 10%, preferably 1% to 10%, based on the total weight of the composition.


The glidant includes, but not limited to, colloidal silicon dioxide, magnesium trisilicate, cellulose powder, talc powder or a combination thereof can be selected. The glidant may be present in an amount of 0.1% to 10%, preferably 0.1% to 0.5%, based on the total weight of the composition.


Dosage forms can be in the form, e.g., of tablets or capsules, and the effective dose may be provided in one or more tablets, capsules or the like, and be provided once a day or throughout the day at intervals, e.g., of 4, 8 or 12 hours. Tablets or capsules, for example, could contain, e.g., 10, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 600, 700, 800, 900, 1,000, 1,100, or 1,250 mg of the active agent. For example, administration to a human subject of the active agent of the present invention may comprise a daily dosage in the range of 100-1,250, 150-1,000, 200-800, or 250-750 mg, which daily dosage can be administered either once a day in its entirety or fractions of which are administered throughout the day in intervals. Liquid formulations can also be prepared so that any dosage may readily and conveniently be dispensed.


Parenteral dosage forms are preferably sterile or capable of being sterilized prior to administration to a subject. Examples of parenteral dosage forms include, but are not limited to, solutions ready for injection, dry products ready to be dissolved or suspended in a pharmaceutically acceptable carrier for injection, suspensions ready for injection, and emulsions.


Some suitable carriers that can be used to provide parenteral dosage forms provided herein include, but are not limited to: water for injection; aqueous vehicles such as, but not limited to, sodium chloride injection, Ringer's injection, dextrose injection; water-miscible carriers such as, but not limited to, ethyl alcohol, polyethylene glycol, and polypropylene glycol; and non-aqueous carriers such as, but not limited to, corn oil, cottonseed oil, peanut oil, sesame oil, ethyl oleate, isopropyl myristate, and benzyl benzoate.


Compounds that increase the solubility of one or more of the active agents disclosed herein can also be incorporated into the parenteral dosage forms provided herein. For example, cyclodextrin and its derivatives can be used to increase the solubility of an active agent of the present invention.


It should be understood that a therapeutically effective dose may be determined by a physician, according to such as the type, stage and/or severity of the disease, the condition, age, body weight, sex and response of the subject to be treated, as well as the route of administration.


A therapeutically effective amount is an amount such that when administered to a subject is sufficient to achieve a plasma concentration of from about 0.01 μg/ml to about 100 μg/ml, from about 0.1 μg/ml to about 10 μg/ml, from about 1 μg/ml to about 5 μg/ml.


When administering the active agent of the present invention to a subject, the therapeutically effective amount of each of the active agents generally may be in the range of about 0.5 to about 250 mg/kg, about 1 to about 250 mg/kg, about 2 to about 200 mg/kg, about 3 to about 120 mg/kg, about 5 to about 250 mg/kg, about 10 to about 200 mg/kg, or about 20 to about 120 mg/kg for each active agent of the present invention. In some embodiments, the therapeutically effective amount may be 0.5 mg/kg, 1 mg/kg, 2 mg/kg, 3 mg/kg, 4 mg/kg, 5 mg/kg, 6 mg/kg, 8 mg/kg, 10 mg/kg, 20 mg/kg, 25 mg/kg, 40 mg/kg, 50 mg/kg, 60 mg/kg, 75 mg/kg, 100 mg/kg, 120 mg/kg, 150 mg/kg, 175 mg/kg, 200 mg/kg, 225 mg/kg, 250 mg/kg or 300 mg/kg.


Each of the active agents of the present invention may be administered once or twice one day; or once every 2, 3, 4, 5, 6, 7, 8, 9 or 10 days or once every 1, 2 or 3 weeks. In some embodiments, each of the active agents of the present invention may be administered in a five times weekly scheme. In the five times weekly scheme, the administration may be done on five consecutive days (once daily) followed by two consecutive days off.


The term “kit”, as used herein, refers to a package and, as a rule, instruction for use. An active agent or a pharmaceutical composition in a kit can be in any of a variety of forms suitable for distribution in a kit. Such forms can include a liquid, powder, tablet, suspension and the like. Two or more active agents may be provided in separate containers suitable for administration separately, or alternatively may be provided in a composition in a single container in the package. The kit may contain an amount sufficient for one or more dosages of agents according to the treatment methods. The instruction for use generally comprises a literal statement of how to treat a disease (such as ALS) with the agents in the kit.


It should be understood that the combination or pharmaceutical composition of the present invention may include other therapeutic agents or therapies, such as biological therapeutic agents and/or chemotherapeutic agents in addition to the active agents of the present invention. The method may include administration of other therapeutic agents or therapies, such as biological therapeutic agents and/or chemotherapeutic agents in addition to administration of the active agents of the present invention. Other therapeutic agents or therapies may be administered simultaneously, separately or sequentially with the therapeutic agents of the present invention.


EXAMPLES
Example 1 Identification of Therapeutic Targets and Drug Repurposing Candidates for Amyotrophic Lateral Sclerosis Using PandaOmics™—an AI-Enabled Biological Target Discovery Platform
1. Abstract

Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disease that results in progressive loss of motor neurons. After decades of research, the pathogenic mechanisms underlying ALS remain ill defined, and there is no effective treatment for the disease. This calls for an urgent need for a new therapeutic regimen. Herein, we applied PandaOmics™, an AI-driven target discovery platform, to analyze the expression profiles of central nervous system (CNS) samples (237 cases; 91 controls) from public datasets, and iPSC-derived motor neurons (diMN) samples (135 cases; 31 controls) from Answer ALS project. Several well-characterized mechanisms in ALS pathology are found to be dysregulated, including the immune system, RNA metabolism, excitotoxicity, as well as programmed cell death. Twenty-three and twelve potential therapeutic targets with multiple levels of novelty are identified from CNS and diMN samples, respectively. Targets identified from CNS data mainly contribute to neuronal cell death and inflammation, which are recognized as late-stage signatures of ALS. In contrast, more diMN targets are attributed to the early-stage signatures. Combining the usage of diMN and post-mortem CNS samples could provide an in-depth understanding of ALS disease progression. To accelerate novel target discovery and drug investigation for ALS, we established the platform ALS.AI (http://als.ai/) for the release of novel therapeutic targets and curated drug repurposing candidates. By integrating all information together, our study could facilitate the identification of new drugs or drug combos for ALS patients and open a new path to search for the cure of other human diseases.


2. Introduction

Thanks to the advances in genomic profiling techniques, numerous genome-wide association studies were conducted to screen for common genetic variants in ALS and have identified novel candidates as genetic predisposition or biomarkers (e.g. ACSL5, KIF5A, ATXN2, and MOBP). Furthermore, the utility of both cellular and animal models with ALS-linked gene variants helps determine the potential interacting partners of those ALS-linked genes, providing multiple lines of evidence for uncovering disease pathology[4]. Here, we applied PandaOmics™—an artificial intelligence (AI)-powered target discovery platform—to explore dysregulated genes and altered pathways across various ALS-related datasets. To enrich the diversity of data sources, we utilized post-mortem central nervous system (CNS) tissues and induced pluripotent stem cell (iPSC)-differentiated motor neurons derived from ALS patients to perform target discovery. By customizing the filter setting, 21 high-confidence and 14 novel candidates were selected as promising ALS therapeutic targets. Proposed targets will be released onto the platform ALS.AI (http://als.ai/). The aim of this study is to demonstrate the utilization of the AI-driven target discovery platform—PandaOmics™—to find therapeutic targets for ALS.


3. Abbreviations





    • AD: Alzheimer's disease;

    • AI: Artificial intelligence;

    • ALS: Amyotrophic lateral sclerosis;

    • fALS: Familial ALS; sALS: Sporadic ALS;

    • CNS: Central nervous system;

    • Cn: Calcineurin;

    • diMN: Direct iPSC-derived motor neuron;

    • ER: Endoplasmic reticulum;

    • iPSC: Induced pluripotent stem cell;

    • KOL: Key opinion leader;

    • LFC: log2-transformed fold change;

    • MN: Motor neuron;

    • NADPH: Nicotinamide adenine dinucleotide phosphate;

    • NO: Nitric oxide;

    • nNOS: Neuronal nitric oxide synthase;

    • PD: Parkinson's disease;

    • UPR: unfolded protein response.





4. Methods
Data Sources and Availability

Microarray and RNA-seq datasets for ALS patients and control samples were retrieved from public repositories and processed by PandaOmics™ for downstream analysis and target identification. Over fifty ALS-related datasets of various tissue sources are available in PandaOmics™ (FIG. 1), including datasets of post-mortem CNS tissues, iPSC-derived neurons, blood, etc. For each dataset, samples can be divided into subgroups based on their clinical subtypes or other phenotypic attributes. In addition, transcriptomics and proteomics data of the direct iPSC-derived motor neurons (diMNs), generated from ALS patients and neurologically healthy subjects in the Answer ALS project[5] were uploaded to PandaOmics™ and incorporated in our analyses. The diMNs are differentiated from the primary peripheral blood mononuclear cell-derived induced pluripotent cell lines. Detailed protocol for the diMN generation was described by Rothstein et al. (2020)[5].


The raw transcriptomics data of CNS comparisons were available in public repositories that could be retrieved by their series identifiers. In addition, transcriptomics and proteomics profiles of the diMN samples were available to investigators upon request and approval from the Answer ALS.


Dataset and Comparison Selection

Given that the degeneration of motor neurons in the brain and spinal cord underlie ALS pathogenesis, CNS tissue datasets were selected for analysis in the present study. Samples carrying one of the four major fALS-linked gene variations (SOD1, TDP-43, FUS, and C9orf72) were classified as the fALS group, and those with unspecified gene variations as the sALS group, yielding five familial as well as seven sporadic ALS case-control comparisons (Table 1).









TABLE 1







ALS case-control comparisons using CNS samples














Data series
Platform
Technology
Source
Mutant gene
# Case
# Control
Year

















Familial









ALS









E−MTAB-
A-MEXP-
Microarray
Motor Cortex
C9orf72
3
3
2013


1925
2246








GSE67196
GPL11154
RNA-seq
Cerebellum
C9orf72
8
8
2015


GSE67196
GPL11154
RNA-seq
Frontal Cortex
C9orf72
8
9
2015


GSE68605
GPL570
Microarray
Motor Neurons
C9orf72
8
3
2015


GSE20589
GPL570
Microarray
Motor Neurons
SOD1
3
7
2010


Sporadic









ALS









GSE122649
GPL18573
RNA-seq
Motor Cortex

26
12
2018


GSE124439
GPL16791
RNA-seq
Frontal Cortex

65
9
2018


GSE124439
GPL16791
RNA-seq
Motor Cortex

80
8
2018


GSE19332
GPL570
Microarray
CNS tissues

3
7
2009


GSE76220
GPL9115
RNA-seq
Spinal Motor

13
8
2015





Neurons






GSE67196
GPL11154
RNA-seq
Cerebellum

10
8
2015


GSE67196
GPL11154
RNA-seq
Frontal Cortex

10
9
2015









The non-Hispanic and non-Latino whites represent the largest ethnic group in the datasets from Answer ALS amounting to over 85% of the total samples. In this regard, diMN samples belonging to this ethnic group with both transcriptomics and proteomics data were selected for the current analysis. The samples were further divided into 25 fALS and 110 sALS based on the presence or absence of the family history of ALS occurrence. As a result, two subtype-dependent comparisons were built using the diMN transcriptomics and proteomics data respectively (Table 2).









TABLE 2







ALS case-control comparisons using diMN samples















#
#
# Detected


ALS subtype
Technology
Source
Case
Control
genes





Transcriptomics







fALS
RNA-seq
direct iPSC-
25
31
37,073




derived motor







neuron





sALS
RNA-seq
direct iPSC-
110
31
37,073




derived motor







neuron





Proteomics







fALS
SWATH-
direct iPSC-
25
31
4,468



MS
derived motor







neuron





sALS
SWATH-
direct iPSC-
110
31
4,468



MS
derived motor







neuron









Pathway Analysis

The degree of pathway dysregulation was determined by the PandaOmics™ proprietary iPANDA algorithm accounting for the differential gene expression and the topological decomposition of pathways[6]. We analyzed both CNS and diMN comparison groups for pathway dysregulation based on Version 73 of the Reactome database. For each group, a pathway was considered as dysregulated when 1) its alteration was unidirectional in greater than or equal to 80% of all the comparisons of the ALS subtype, and 2) the |iPANDA| value reached the threshold of 0.01 in at least one comparison of a subtype. Networks of dysregulated pathways were constructed using EnrichmentMap in Cytoscape. The hierarchical level of pathways retrieved from the Reactome database was employed as the basis for the annotation of pathway clusters in the networks.


Filter Setting for Target Identification

To identify potential targets for ALS, meta-analyses were performed on the five CNS fALS comparisons, seven CNS sALS comparisons, diMN transcriptomics, and proteomics comparisons independently. PandaOmics™ ranks related genes and identifies potential targets with AI hypothesis generation models based on 21 scores from Omics, Text-based, Financial, and Key opinion leader (KOL) categories. In addition, Druggability filters (small molecules, antibodies, safety, novelty), Tissue specificity filters, Target family filters, and Development filters could be applied to further refine the list to meet the user's research goals. For high confidence targets identification, we customized the Druggability filters to screen targets already associated with small molecules and have a median safety level (FIG. 2). Simultaneously, Druggable classes, Omics scores, Text-based scores, Grant Funding, as well as KOL scores (credible attention index and impact factor) were applied. A list of high-confidence druggable targets was ranked in descending order based on their metascores, and the top-50 targets were selected for further investigation.


Similarly, novel ALS targets could be identified without prior knowledge by restricting the Druggability filter to the high novelty level, selecting only the Omics scores, and disabling the Text-based, Financial, and KOL scores (FIG. 3). After recalculating the metascores with the new criteria, the top-50 ranked genes were selected as novel targets for further analysis.


Validation of the Scoring Approach

The “time machine” approach was applied for the validation of the ability of a model to identify the truly novel targets of the disease of interest. The data before a given year was used as training data and the trained model was then evaluated based on the targets entering the clinical phase after the given year (FIG. 4a). Two validation metrics were used to validate the scoring approach. ELFC refers to the log fold change of enrichment shows how much the top of the list is enriched by known targets and is calculated by the formula (I):










ELFC

(
score
)

=


log
2

(



targets
k

·
N


k
·

targets
N



)





(
I
)







where targetsk is the number of known targets for this disease in top-k (or 0.1 if there are none), and targetsN is the total number of known targets for this disease among the genes that are available for a particular PandaOmics score. And HGPV stands for the statistical significance of the effect and shows how likely the same level of enrichment can be achieved from the random distribution and is calculated by the formula (II):










HGPV

(
score
)

=

-


log

1

0


(

1
-

hgcdf

(


targets
k

,
k
,

targets
N

,
N

)


)






(
II
)







where hgcdf is a hypergeometric cumulative distribution function. A score with higher values of ELFC and HGPV corresponds to the higher predictive power of the target-disease association (FIG. 4b).


5. Results
Clustering of Dysregulated Pathways

The Reactome database has provided the hierarchical organization of pathways that related pathways are grouped into broader domains of biological functions[7]. Therefore, all the pathways analyzed here could be classified into 27 biological processes, each of which corresponds to one top-level pathway according to the Reactome hierarchy. In CNS groups, dysregulated pathways in ALS patients are overrepresented in the immune system process (fALS, adjusted p=3.26E-7), signal transduction process (sALS, adjusted p=9.2E-5), and hemostasis (fALS, adjusted p=0.0054). The diMN transcriptomics groups were enriched with dysregulated pathways belonging to the digestion and absorption process (fALS, adjusted p=0.0059), and the process of protein metabolism (sALS, adjusted p=0.0093). The dysregulated pathways in the diMN proteomics groups were overrepresented in the processes of disease (sALS, adjusted p=3.38E-8), DNA repair (fALS, adjusted p=0.0233), and developmental biology (fALS, adjusted p=0.0255). The details of dysregulated pathways in different biological processes are available in Table 3.









TABLE 3







Enrichment of dysregulated pathways in different biological processes.
















#








Dysregulated

pvalue
adjusted p


Main biological

ALS
pathways
Fold
(hypergeometric
(Bonferroni


process
Tissue
subtype
in process
enrichment
test)
correction)
















Immune System
CNS
fALS
41
1.4200
1.02E−08
3.26E−07


Signal
CNS
sALS
40
0.9629
2.87E−06
9.20E−05


Transduction








Hemostasis
CNS
fALS
11
2.4394
1.68E−04
5.39E−03


Gene expression
CNS
sALS
14
1.1109
4.96E−03
1.59E−01


(Transcription)








Metabolism of
CNS
sALS
7
1.7847
1.09E−02
3.48E−01


RNA








Extracellular
CNS
fALS
5
2.4026
1.19E−02
3.81E−01


matrix








organization








Cell-Cell
CNS
fALS
4
2.8563
1.53E−02
4.91E−01


communication








Programmed Cell
CNS
fALS
8
1.3138
1.83E−02
5.85E−01


Death








Cell Cycle
CNS
fALS
15
0.4224
9.76E−02
1.00E+00


Protein
CNS
sALS
1
2.7394
2.41E−01
1.00E+00


localization








Organelle
CNS
fALS
2
0.9281
2.78E−01
1.00E+00


biogenesis and








maintenance








Muscle
CNS
sALS
1
1.3371
3.56E−01
1.00E+00


contraction








Organelle
CNS
sALS
1
0.5581
4.84E−01
1.00E+00


biogenesis and








maintenance








Disease
CNS
fALS
15
−0.0413
6.14E−01
1.00E+00


Programmed Cell
CNS
sALS
2
−0.0652
6.41E−01
1.00E+00


Death








Cellular responses
CNS
sALS
1
−0.1871
7.20E−01
1.00E+00


to external stimuli








Gene expression
CNS
fALS
9
−0.1603
7.63E−01
1.00E+00


(Transcription)








Disease
CNS
sALS
8
−0.1736
7.70E−01
1.00E+00


Transport of
CNS
sALS
2
−0.3075
7.96E−01
1.00E+00


small molecules








DNA Repair
CNS
sALS
2
−0.3662
8.35E−01
1.00E+00


Vesicle-mediated
CNS
fALS
2
−0.3747
8.44E−01
1.00E+00


transport








Metabolism of
CNS
fALS
7
−0.2638
8.56E−01
1.00E+00


proteins








Metabolism
CNS
sALS
9
−0.2488
8.67E−01
1.00E+00


Cellular responses
CNS
fALS
1
−0.4970
8.77E−01
1.00E+00


to external stimuli








Metabolism of
CNS
sALS
3
−0.4901
9.43E−01
1.00E+00


proteins








Transport of
CNS
fALS
2
−0.5715
9.56E−01
1.00E+00


small molecules








Signal
CNS
fALS
25
−0.2409
9.61E−01
1.00E+00


Transduction








Immune System
CNS
sALS
6
−0.4276
9.62E−01
1.00E+00


Developmental
CNS
sALS
1
−0.6884
9.65E−01
1.00E+00


Biology








Metabolism
CNS
fALS
12
−0.3802
9.82E−01
1.00E+00


Developmental
CNS
fALS
1
−0.8072
9.96E−01
1.00E+00


Biology








Cell Cycle
CNS
sALS
1
−0.8467
9.99E−01
1.00E+00


Digestion and
diMN
fALS
2
55.9538
4.50E−04
5.85E−03


absorption
transcriptomics







Metabolism of
diMN
sALS
7
3.3626
7.13E−04
9.27E−03


proteins
transcriptomics







Immune System
diMN
fALS
5
2.6323
8.00E−03
1.04E−01



transcriptomics







Metabolism of
diMN
sALS
3
3.3759
2.93E−02
3.81E−01


RNA
transcriptomics







Transport of
diMN
sALS
3
2.8086
4.19E−02
5.44E−01


small molecules
transcriptomics







Metabolism
diMN
fALS
4
1.5426
6.18E−02
8.03E−01



transcriptomics







Neuronal System
diMN
sALS
2
1.5870
1.80E−01
1.00E+00



transcriptomics







Disease
diMN
sALS
4
0.5150
2.68E−01
1.00E+00



transcriptomics







Immune System
diMN
sALS
3
0.0493
5.57E−01
1.00E+00



transcriptomics







Developmental
diMN
sALS
1
0.1426
5.92E−01
1.00E+00


Biology
transcriptomics







Signal
diMN
fALS
2
−0.2526
7.83E−01
1.00E+00


Transduction
transcriptomics







Signal
diMN
sALS
3
−0.4602
9.39E−01
1.00E+00


Transduction
transcriptomics







Metabolism
diMN
sALS
1
−0.6939
9.70E−01
1.00E+00



transcriptomics







Disease
diMN
sALS
14
5.2248
1.69E−09
3.38E−08



proteomics







DNA Repair
diMN
fALS
6
3.8266
1.17E−03
2.33E−02



proteomics







Developmental
diMN
fALS
6
3.7462
1.28E−03
2.55E−02


Biology
proteomics







Reproduction
diMN
fALS
2
12.5604
8.50E−03
1.70E−01



proteomics







Gene expression
diMN
fALS
7
1.6793
1.30E−02
2.59E−01


(Transcription)
proteomics







Neuronal System
diMN
fALS
4
2.5820
2.35E−02
4.69E−01



proteomics







Cell-Cell
diMN
fALS
2
6.9103
2.50E−02
5.00E−01


communication
proteomics







Muscle
diMN
sALS
1
9.0598
9.54E−02
1.00E+00


contraction
proteomics







Gene expression
diMN
sALS
3
0.9471
1.96E−01
1.00E+00


(Transcription)
proteomics







Programmed Cell
diMN
sALS
1
1.0120
3.97E−01
1.00E+00


Death
proteomics







Transport of
diMN
sALS
1
0.4903
4.96E−01
1.00E+00


small molecules
proteomics







Developmental
diMN
sALS
1
0.3413
5.34E−01
1.00E+00


Biology
proteomics







Metabolism of
diMN
fALS
2
−0.1371
6.86E−01
1.00E+00


proteins
proteomics







Transport of
diMN
fALS
1
−0.1211
6.89E−01
1.00E+00


small molecules
proteomics







Cell Cycle
diMN
fALS
2
−0.2219
7.41E−01
1.00E+00



proteomics







Metabolism of
diMN
sALS
1
−0.2684
7.58E−01
1.00E+00


proteins
proteomics







Disease
diMN
fALS
2
−0.4756
9.08E−01
1.00E+00



proteomics







Signal
diMN
fALS
4
−0.5017
9.74E−01
1.00E+00


Transduction
proteomics







Metabolism
diMN
fALS
1
−0.7881
9.94E−01
1.00E+00



proteomics







Signal
diMN
sALS
1
−0.7888
9.95E−01
1.00E+00


Transduction
proteomics









Furthermore, pathways with similar gene contents can be connected to form clusters. As shown in FIG. 5, the most prominent cluster of the dysregulated pathways in CNS ALS groups relative to healthy groups was associated with activated innate immune system, which consisted of activated pathways of the Toll-like receptor cascades, FCERI signaling, cytokine signaling, and regulation of complement cascade. Moreover, pathways of programmed cell death, and cell cycle pathways associated with G1-S DNA damage checkpoint were activated. Other activated clusters include pathways of the extracellular matrix organization, MET signaling, hemostasis, oncogenic MAPK signaling, ABC transporter disorders, interferon signaling, and carbohydrate metabolism. On the contrary, pathways of FGFR signaling, RNA metabolism, and RNA polymerase III transcription were inhibited. In addition, pathways of RNA polymerase I and II transcription, mitochondrial protein import, and NCAM signaling for neurite out-growth were inhibited as well (Table 4). Notably, there were only a few dysregulated pathways overlapping between fALS and sALS groups (i.e. upregulated pathway of erythropoietin activates PI3-kinase annotated as square in FIG. 5), and most clusters were specific to a sole ALS subtype. For example, the clusters of FGFR signaling, RNA metabolism, and RNA polymerase III transcription mainly contained inhibited pathways identified in the sALS but not the fALS groups.









TABLE 4





Dysregulated pathways in CNS, diMN transcriptomics and diMN proteomics groups.







Dysregulated pathways in CNS comparisons













Main








biological

fALS
fALS
sALS
sALS



process
Pathway
(% iPanda > 0)
(% iPanda < 0)
(% iPanda > 0)
(% iPanda < 0)
Direction





Cell Cycle
APC-C:Cdc20
20
80
28.57
71.43
fALS



mediated




Down



degradation of








Cyclin B







Cell Cycle
Inactivation of
20
80
28.57
71.43
fALS



APC-C via




Down



direct inhibition








of the APC-C








complex







Cell Cycle
Inhibition of the
20
80
28.57
71.43
fALS



proteolytic




Down



activity of APC-








C required for








the onset of








anaphase by








mitotic spindle








checkpoint








components







Cell Cycle
Chk1-
80
20
42.86
14.29
fALS Up



Chk2(Cds1)








mediated








inactivation of








Cyclin B:Cdk1








complex







Cell Cycle
Condensation of
80
0
57.14
42.86
fALS Up



Prometaphase








Chromosomes







Cell Cycle
Cyclin A:Cdk2-
80
20
57.14
42.86
fALS Up



associated








events at S phase








entry







Cell Cycle
Cyclin E
80
20
42.86
57.14
fALS Up



associated








events during








G1-S transition







Cell Cycle
G1-S DNA
80
20
57.14
42.86
fALS Up



Damage








Checkpoints







Cell Cycle
G1-S Transition
80
20
57.14
42.86
fALS Up


Cell Cycle
Mitotic G1
80
20
42.86
57.14
fALS Up



phase and G1-S








transition







Cell Cycle
p53-Dependent
80
20
57.14
42.86
fALS Up



G1 DNA








Damage








Response







Cell Cycle
p53-Dependent
80
20
57.14
42.86
fALS Up



G1-S DNA








damage








checkpoint







Cell Cycle
SCF(Skp2)-
80
20
57.14
42.86
fALS Up



mediated








degradation of








p27-p21







Cell Cycle
Transcriptional
80
0
28.57
57.14
fALS Up



activation of cell








cycle inhibitor








p21







Cell Cycle
Transcriptional
80
0
28.57
57.14
fALS Up



activation of p53








responsive genes







Cell Cycle
G1-S-Specific
40
60
14.29
85.71
sALS



Transcription




Down


Cell-Cell
Adherens
80
0
57.14
42.86
fALS Up


communication
junctions








interactions







Cell-Cell
Cell junction
100
0
28.57
71.43
fALS Up


communication
organization







Cell-Cell
Cell-cell
80
20
28.57
71.43
fALS Up


communication
junction








organization







Cell-Cell
Tight junction
80
20
28.57
71.43
fALS Up


communication
interactions







Cellular
Response of
80
0
28.57
42.86
fALS Up


responses to
EIF2AK1 (HRI)







external
to heme







stimuli
deficiency







Cellular
HSP90
60
40
85.71
14.29
sALS Up


responses to
chaperone cycle







external
for steroid







stimuli
hormone








receptors (SHR)







Developmental
CRMPs in
0
100
71.43
28.57
fALS


Biology
Sema3A




Down



signaling







Developmental
NCAM
40
60
14.29
85.71
sALS


Biology
signaling for




Down



neurite out-








growth







Disease
Interactions of
20
80
42.86
57.14
fALS



Vpr with host




Down



cellular proteins







Disease
Vpr-mediated
20
80
57.14
42.86
fALS



nuclear import




Down



of PICS







Disease
ABC transporter
80
20
71.43
28.57
fALS Up



disorders







Disease
Defective CFTR
80
20
71.43
28.57
fALS Up



causes cystic








fibrosis







Disease
Diseases
80
0
42.86
14.29
fALS Up



associated with








the TLR








signaling








cascade







Disease
Diseases of
80
0
42.86
14.29
fALS Up



Immune System







Disease
Disorders of
80
20
71.43
28.57
fALS Up



transmembrane








transporters







Disease
IkBA variant
80
0
42.86
14.29
fALS Up



leads to EDA-ID







Disease
Signaling by
80
20
71.43
28.57
fALS Up



BRAF and RAF








fusions







Disease
Signaling by
80
20
28.57
71.43
fALS Up



FGFR2 in








disease







Disease
Signaling by
80
20
57.14
42.86
fALS Up



high-kinase








activity BRAF








mutants







Disease
Signaling by
80
20
57.14
42.86
fALS Up



moderate kinase








activity BRAF








mutants







Disease
Uptake and
80
20
42.86
57.14
fALS Up



actions of








bacterial toxins







Disease
Viral mRNA
80
0
71.43
14.29
fALS Up



Translation







Disease
Infection with
80
0
85.71
14.29
fALS Up;



Mycobacterium




sALS Up



tuberculosis







Disease
FGFR3 mutant
60
40
14.29
85.71
sALS



receptor




Down



activation







Disease
Signaling by
60
40
14.29
85.71
sALS



activated point




Down



mutants of








FGFR3







Disease
FCGR3A-
100
0
85.71
14.29
sALS Up



mediated








phagocytosis







Disease
Leishmania
100
0
85.71
14.29
sALS Up



phagocytosis







Disease
Parasite
100
0
85.71
14.29
sALS Up



infection







Disease
Signaling by
20
20
85.71
0
sALS Up



WNT in cancer







Disease
XAV939
20
0
85.71
0
sALS Up



inhibits








tankyrase,








stabilizing








AXIN







DNA Repair
Displacement of
0
100
0
85.71
sALS



DNA




Down



glycosylase by








APEX1







DNA Repair
Fanconi Anemia
40
60
14.29
85.71
sALS



Pathway




Down


Extracellular
ECM
80
20
71.43
28.57
fALS Up


matrix
proteoglycans







organization








Extracellular
Integrin cell
80
20
57.14
42.86
fALS Up


matrix
surface







organization
interactions







Extracellular
Laminin
80
20
42.86
57.14
fALS Up


matrix
interactions







organization








Extracellular
Non-integrin
80
20
57.14
42.86
fALS Up


matrix
membrane-ECM







organization
interactions







Extracellular
Syndecan
80
0
71.43
28.57
fALS Up


matrix
interactions







organization








Gene
Regulation of
80
20
28.57
71.43
fALS Up


expression
MECP2







(Transcription)
expression and








activity







Gene
RUNX1
80
0
42.86
14.29
fALS Up


expression
regulates







(Transcription)
transcription of








genes involved








in differentiation








of myeloid cells







Gene
RUNX3
80
0
57.14
42.86
fALS Up


expression
regulates







(Transcription)
CDKN1A








transcription







Gene
TP53 Regulates
100
0
42.86
57.14
fALS Up


expression
Transcription of







(Transcription)
Cell Cycle








Genes







Gene
TP53 Regulates
80
20
42.86
57.14
fALS Up


expression
Transcription of







(Transcription)
Genes Involved








in G2 Cell Cycle








Arrest







Gene
Transcriptional
80
20
42.86
57.14
fALS Up


expression
Regulation by







(Transcription)
MECP2







Gene
Transcriptional
100
0
57.14
42.86
fALS Up


expression
regulation by the







(Transcription)
AP-2 (TFAP2)








family of








transcription








factors







Gene
Transcriptional
80
20
28.57
71.43
fALS Up


expression
Regulation by







(Transcription)
VENTX







Gene
FOXO-mediated
100
0
85.71
14.29
fALS Up;


expression
transcription of




sALS Up


(Transcription)
cell cycle genes







Gene
RNA
20
80
14.29
85.71
sALS


expression
Polymerase I




Down


(Transcription)
Transcription








Initiation







Gene
RNA
20
80
14.29
85.71
sALS


expression
Polymerase I




Down


(Transcription)
Transcription








Termination







Gene
RNA
80
20
14.29
85.71
sALS


expression
Polymerase II




Down


(Transcription)
Transcription








Termination







Gene
RNA
20
80
14.29
85.71
sALS


expression
Polymerase III




Down


(Transcription)
Abortive And








Retractive








Initiation







Gene
RNA
0
80
0
100
sALS


expression
Polymerase III




Down


(Transcription)
Chain








Elongation







Gene
RNA
20
80
14.29
85.71
sALS


expression
Polymerase III




Down


(Transcription)
Transcription







Gene
RNA
20
80
14.29
85.71
sALS


expression
Polymerase III




Down


(Transcription)
Transcription








Initiation







Gene
RNA
0
80
14.29
85.71
sALS


expression
Polymerase III




Down


(Transcription)
Transcription








Initiation From








Type 1 Promoter







Gene
RNA
0
80
14.29
85.71
sALS


expression
Polymerase III




Down


(Transcription)
Transcription








Initiation From








Type 2 Promoter







Gene
RNA
40
60
0
100
sALS


expression
Polymerase III




Down


(Transcription)
Transcription








Initiation From








Type 3 Promoter







Gene
RNA
0
100
14.29
85.71
sALS


expression
Polymerase III




Down


(Transcription)
Transcription








Termination







Gene
FOXO-mediated
60
40
85.71
14.29
sALS Up


expression
transcription of







(Transcription)
oxidative stress,








metabolic and








neuronal genes







Gene
Regulation of
60
40
85.71
14.29
sALS Up


expression
TP53 Activity







(Transcription)
through








Methylation







Hemostasis
Common
80
20
42.86
57.14
fALS Up



Pathway of








Fibrin Clot








Formation







Hemostasis
Extrinsic
80
20
14.29
57.14
fALS Up



Pathway of








Fibrin Clot








Formation







Hemostasis
Formation of
80
20
42.86
57.14
fALS Up



Fibrin Clot








(Clotting








Cascade)







Hemostasis
Hemostasis
100
0
57.14
42.86
fALS Up


Hemostasis
Intrinsic
80
20
42.86
57.14
fALS Up



Pathway of








Fibrin Clot








Formation







Hemostasis
Platelet
80
20
57.14
42.86
fALS Up



activation,








signaling and








aggregation







Hemostasis
Platelet
80
0
28.57
57.14
fALS Up



Adhesion to








exposed








collagen







Hemostasis
Platelet
80
20
71.43
28.57
fALS Up



Aggregation








(Plug








Formation)







Hemostasis
Platelet
100
0
71.43
28.57
fALS Up



degranulation







Hemostasis
Response to
100
0
71.43
28.57
fALS Up



elevated platelet








cytosolic Ca2+







Hemostasis
Tie2 Signaling
100
0
71.43
28.57
fALS Up


Hemostasis,
GRB2:SOS
80
0
71.43
28.57
fALS Up


Signal
provides linkage







Transduction
to MAPK








signaling for








Integrins







Immune
Antigen
100
0
42.86
57.14
fALS Up


System
activates B Cell








Receptor (BCR)








leading to








generation of








second








messengers







Immune
Antigen
80
20
57.14
42.86
fALS Up


System
processing-








Cross








presentation







Immune
ER-Phagosome
80
20
57.14
42.86
fALS Up


System
pathway







Immune
Antimicrobial
80
20
42.86
57.14
fALS Up


System
peptides







Immune
CD28 co-
80
20
42.86
57.14
fALS Up


System
stimulation







Immune
Interleukin-1
80
20
57.14
42.86
fALS Up


System
family signaling







Immune
DAP12
100
0
42.86
57.14
fALS Up


System
interactions







Immune
DAP12
100
0
42.86
57.14
fALS Up


System
signaling







Immune
Interleukin-1
80
20
57.14
42.86
fALS Up


System
signaling







Immune
Interleukin-17
80
20
57.14
42.86
fALS Up


System
signaling







Immune
Interleukin-18
80
20
42.86
42.86
fALS Up


System
signaling







Immune
NIK-
60
40
14.29
85.71
sALS


System
→noncanonical




Down



NF-kB signaling







Immune
Interleukin-33
60
0
85.71
14.29
sALS Up


System
signaling







Immune
DDX58-IFIH1-
80
20
42.86
57.14
fALS Up


System
mediated








induction of








interferon-alpha-








beta







Immune
TRAF6
80
0
57.14
42.86
fALS Up


System
mediated NF-kB








activation







Immune
Interferon alpha-
80
20
42.86
57.14
fALS Up


System
beta signaling







Immune
Interferon
80
20
42.86
57.14
fALS Up


System
Signaling







Immune
Interleukin
100
0
42.86
57.14
fALS Up


System
receptor SHC








signaling







Immune
ZBP1(DAI)
80
20
57.14
42.86
fALS Up


System
mediated








induction of type








I IFNs







Immune
Dectin-1
60
40
14.29
85.71
sALS


System
mediated




Down



noncanonical








NF-KB signaling







Immune
Interleukin-10
80
20
57.14
42.86
fALS Up


System
signaling







Immune
NOD1-2
60
40
14.29
85.71
sALS


System
Signaling




Down



Pathway







Immune
Nucleotide-
40
60
14.29
85.71
sALS


System
binding domain,




Down



leucine rich








repeat








containing








receptor (NLR)








signaling








pathways







Immune
Interleukin-3,
100
0
42.86
57.14
fALS Up


System
Interleukin-5








and GM-CSF








signaling







Immune
LRR FLII-
80
0
57.14
28.57
fALS Up


System
interacting








protein 1








(LRRFIP1)








activates type I








IFN production







Immune
Fc epsilon
80
20
28.57
71.43
fALS Up


System
receptor








(FCERI)








signaling







Immune
Metal
100
0
57.14
14.29
fALS Up


System
sequestration by








antimicrobial








proteins







Immune
FCERI mediated
80
20
28.57
71.43
fALS Up


System
Ca+2








mobilization







Immune
FCERI mediated
80
20
28.57
71.43
fALS Up


System
MAPK








activation







Immune
Regulation of
100
0
71.43
28.57
fALS Up


System
IFNA signaling







Immune
FCERI mediated
80
20
71.43
28.57
fALS Up


System
NF-kB








activation







Immune
Role of LAT2-
80
20
57.14
42.86
fALS Up


System
NTAL-LAB on








calcium








mobilization







Immune
TNFs bind their
80
20
57.14
28.57
fALS Up


System
physiological








receptors







Immune
Activation of C3
80
0
28.57
28.57
fALS Up


System
and C5







Immune
Complement
100
0
28.57
71.43
fALS Up


System
cascade







Immune
Regulation of
100
0
42.86
57.14
fALS Up


System
Complement








cascade







Immune
Classical
80
0
14.29
85.71
fALS Up;


System
antibody-




sALS



mediated




Down



complement








activation







Immune
IKK complex
100
0
42.86
42.86
fALS Up


System
recruitment








mediated by








RIP1







Immune
MAP kinase
80
20
85.71
14.29
fALS Up


System
activation







Immune
MyD88:MAL(T
80
20
71.43
28.57
fALS Up


System
IRAP) cascade








initiated on








plasma








membrane







Immune
Regulation of
80
0
71.43
28.57
fALS Up


System
TLR by








endogenous








ligand







Immune
Toll Like
80
20
71.43
28.57
fALS Up


System
Receptor 2








(TLR2) Cascade







Immune
Toll Like
80
20
28.57
71.43
fALS Up


System
Receptor 4








(TLR4) Cascade







Immune
Toll Like
80
20
71.43
28.57
fALS Up


System
Receptor








TLR1:TLR2








Cascade







Immune
Toll Like
80
20
71.43
28.57
fALS Up


System
Receptor








TLR6:TLR2








Cascade







Immune
TRIF-mediated
100
0
28.57
57.14
fALS Up


System
programmed cell








death







Metabolism
Glyoxylate
0
80
42.86
57.14
fALS



metabolism and




Down



glycine








degradation







Metabolism
A
80
20
57.14
42.86
fALS Up



tetrasaccharide








linker sequence








is required for








GAG synthesis







Metabolism
Androgen
80
0
28.57
42.86
fALS Up



biosynthesis







Metabolism
Chondroitin
80
20
57.14
42.86
fALS Up



sulfate-dermatan








sulfate








metabolism







Metabolism
Glycosaminoglycan
80
20
57.14
42.86
fALS Up



metabolism







Metabolism
Heparan sulfate-
80
20
42.86
57.14
fALS Up



heparin (HS-








GAG)








metabolism







Metabolism
HS-GAG
80
20
42.86
57.14
fALS Up



biosynthesis







Metabolism
HS-GAG
80
20
42.86
57.14
fALS Up



degradation







Metabolism
Metabolism of
80
20
57.14
42.86
fALS Up



carbohydrates







Metabolism
Metabolism of
80
20
57.14
42.86
fALS Up



fat-soluble








vitamins







Metabolism
Xenobiotics
80
0
57.14
42.86
fALS Up


Metabolism
Arachidonic acid
60
40
14.29
85.71
sALS



metabolism




Down


Metabolism
Complex I
0
80
14.29
85.71
sALS



biogenesis




Down


Metabolism
Cytosolic
20
40
0
85.71
sALS



sulfonation of




Down



small molecules







Metabolism
Glycerophospho
60
40
14.29
85.71
sALS



lipid




Down



biosynthesis







Metabolism
Phase II-
20
60
14.29
85.71
sALS



Conjugation of




Down



compounds







Metabolism
Phospholipid
40
60
14.29
85.71
sALS



metabolism




Down


Metabolism
Respiratory
20
80
14.29
85.71
sALS



electron




Down



transport







Metabolism
Respiratory
20
80
14.29
85.71
sALS



electron




Down



transport, ATP








synthesis by








chemiosmotic








coupling, and








heat production








by uncoupling








proteins







Metabolism
Synthesis of
40
20
14.29
85.71
sALS



Prostaglandins




Down



(PG) and








Thromboxanes








(TX)







Metabolism of
CREB3 factors
0
100
28.57
71.43
fALS


proteins
activate genes




Down


Metabolism of
Attachment of
80
0
28.57
28.57
fALS Up


proteins
GPI anchor to








uPAR







Metabolism of
IRE1alpha
80
20
57.14
42.86
fALS Up


proteins
activates








chaperones







Metabolism of
Metalloprotease
80
20
28.57
71.43
fALS Up


proteins
DUBs







Metabolism of
Post-
80
20
57.14
42.86
fALS Up


proteins
translational








protein








phosphorylation







Metabolism of
Unfolded
80
20
57.14
42.86
fALS Up


proteins
Protein








Response (UPR)







Metabolism of
XBP1(S)
80
20
57.14
42.86
fALS Up


proteins
activates








chaperone genes







Metabolism of
Cooperation of
40
40
14.29
85.71
sALS


proteins
Prefoldin and




Down



TriC-CCT in








actin and tubulin








folding







Metabolism of
Gamma
60
40
14.29
85.71
sALS


proteins
carboxylation,




Down



hypusine








formation and








arylsulfatase








activation







Metabolism of
Post-chaperonin
60
40
14.29
85.71
sALS


proteins
tubulin folding




Down



pathway







Metabolism of
Metabolism of
20
80
14.29
85.71
sALS


RNA
non-coding




Down



RNA







Metabolism of
mRNA Splicing-
60
40
14.29
85.71
sALS


RNA
Minor Pathway




Down


Metabolism of
snRNP
20
80
14.29
85.71
sALS


RNA
Assembly




Down


Metabolism of
Transport of
40
60
14.29
85.71
sALS


RNA
Mature mRNA




Down



derived from an








Intron-








Containing








Transcript







Metabolism of
Transport of
40
60
14.29
85.71
sALS


RNA
Mature




Down



Transcript to








Cytoplasm







Metabolism of
HuR (ELAVL1)
40
20
85.71
0
sALS Up


RNA
binds and








stabilizes mRNA







Metabolism of
Regulation of
20
80
85.71
0
sALS Up


RNA
mRNA stability








by proteins that








bind AU-rich








elements







Metabolism,
Retinoid
80
20
57.14
42.86
fALS Up


Signal
metabolism and







Transduction
transport







Muscle
Phase 0-rapid
40
60
14.29
85.71
sALS


contraction
depolarisation




Down


Organelle
Cilium
20
80
28.57
71.43
fALS


biogenesis and
Assembly




Down


maintenance








Organelle
Organelle
20
80
28.57
71.43
fALS


biogenesis and
biogenesis and




Down


maintenance
maintenance







Organelle
Intraflagellar
20
80
14.29
85.71
fALS


biogenesis and
transport




Down;


maintenance





ALS








Down


Programmed
Activation of
80
0
42.86
28.57
fALS Up


Cell Death
BAD and








translocation to








mitochondria







Programmed
Activation of
80
20
42.86
57.14
fALS Up


Cell Death
BH3-only








proteins







Programmed
Apoptosis
80
20
42.86
42.86
fALS Up


Cell Death
induced DNA








fragmentation







Programmed
CASP8 activity
80
20
14.29
71.43
fALS Up


Cell Death
is inhibited







Programmed
Regulated
100
0
57.14
42.86
fALS Up


Cell Death
Necrosis







Programmed
Regulation of
80
20
14.29
71.43
fALS Up


Cell Death
necroptotic cell








death







Programmed
RIPK1-mediated
100
0
57.14
42.86
fALS Up


Cell Death
regulated








necrosis







Programmed
Apoptotic
100
0
85.71
14.29
fALS Up;


Cell Death
execution phase




sALS Up


Programmed
Release of
20
40
0
85.71
sALS


Cell Death
apoptotic factors




Down



from the








mitochondria







Protein
Mitochondrial
40
60
14.29
85.71
sALS


localization
protein import




Down


Signal
Insulin receptor
20
80
28.57
71.43
fALS


Transduction
recycling




Down


Signal
Signaling by
20
80
42.86
57.14
fALS


Transduction
NTRK2 (TRKB)




Down


Signal
AKT
80
20
57.14
42.86
fALS Up


Transduction
phosphorylates








targets in the








cytosol







Signal
Death Receptor
80
20
57.14
42.86
fALS Up


Transduction
Signalling







Signal
Downregulation
80
20
57.14
28.57
fALS Up


Transduction
of ERBB4








signaling







Signal
G alpha (i)
80
20
42.86
57.14
fALS Up


Transduction
signalling events







Signal
MET activates
80
20
100
0
fALS Up


Transduction
RAP1 and








RAC1







Signal
MET activates
80
20
71.43
28.57
fALS Up


Transduction
RAS signaling







Signal
MET interacts
80
20
57.14
14.29
fALS Up


Transduction
with TNS








proteins







Signal
MET promotes
80
20
71.43
28.57
fALS Up


Transduction
cell motility







Signal
Negative
80
20
57.14
42.86
fALS Up


Transduction
regulation of








MET activity







Signal
Nuclear
100
0
57.14
42.86
fALS Up


Transduction
signaling by








ERBB4







Signal
Regulation of
80
20
28.57
71.43
fALS Up


Transduction
FZD by








ubiquitination







Signal
RHO GTPases
80
20
57.14
42.86
fALS Up


Transduction
Activate








NADPH








Oxidases







Signal
Serotonin
80
20
42.86
57.14
fALS Up


Transduction
receptors







Signal
Signaling by
80
20
42.86
57.14
fALS Up


Transduction
ERBB2







Signal
Signaling by
100
0
71.43
28.57
fALS Up


Transduction
ERBB4







Signal
Signaling by
80
20
71.43
28.57
fALS Up


Transduction
MET







Signal
TNFR1-induced
80
20
57.14
42.86
fALS Up


Transduction
NFkappaB








signaling








pathway







Signal
TNFR1-induced
80
20
42.86
28.57
fALS Up


Transduction
proapoptotic








signaling







Signal
Visual
80
20
57.14
42.86
fALS Up


Transduction
phototransduction







Signal
Erythropoietin
80
0
85.71
14.29
fALS Up;


Transduction
activates




sALS Up



Phosphoinositide-








3-kinase








(PI3K)







Signal
Signaling by
80
20
85.71
14.29
fALS Up;


Transduction
Erythropoietin




sALS Up


Signal
Degradation of
60
0
14.29
85.71
sALS


Transduction
DVL




Down


Signal
Downstream
80
20
14.29
85.71
sALS


Transduction
signaling of




Down



activated FGFR3







Signal
Downstream
80
20
14.29
85.71
sALS


Transduction
signaling of




Down



activated FGFR4







Signal
FGFR1 ligand
40
60
14.29
85.71
sALS


Transduction
binding and




Down



activation







Signal
FGFR2 ligand
20
80
14.29
85.71
sALS


Transduction
binding and




Down



activation







Signal
FGFR2b ligand
20
80
14.29
85.71
sALS


Transduction
binding and




Down



activation







Signal
FGFR2c ligand
40
60
14.29
85.71
sALS


Transduction
binding and




Down



activation







Signal
FGFR3 ligand
60
40
14.29
85.71
sALS


Transduction
binding and




Down



activation







Signal
FGFR3b ligand
60
40
0
85.71
sALS


Transduction
binding and




Down



activation







Signal
FGFR3c ligand
60
40
14.29
85.71
sALS


Transduction
binding and




Down



activation







Signal
FGFR4 ligand
40
60
14.29
85.71
sALS


Transduction
binding and




Down



activation







Signal
FGFRL1
60
40
0
100
sALS


Transduction
modulation of




Down



FGFR1








signaling







Signal
FRS-mediated
60
40
14.29
85.71
sALS


Transduction
FGFR3




Down



signaling







Signal
FRS-mediated
40
60
14.29
85.71
sALS


Transduction
FGFR4




Down



signaling







Signal
Frs2-mediated
60
40
14.29
85.71
sALS


Transduction
activation




Down


Signal
Negative
40
60
14.29
85.71
sALS


Transduction
regulation of




Down



FGFR4








signaling







Signal
Negative
20
40
0
100
sALS


Transduction
regulation of




Down



TCF-dependent








signaling by








DVL-interacting








proteins







Signal
PCP-CE
60
40
14.29
85.71
sALS


Transduction
pathway




Down


Signal
Phospholipase
40
60
14.29
85.71
sALS


Transduction
C-mediated




Down



cascade; FGFR2







Signal
Phospholipase
60
40
14.29
85.71
sALS


Transduction
C-mediated




Down



cascade; FGFR3







Signal
Phospholipase
40
60
14.29
85.71
sALS


Transduction
C-mediated




Down



cascade; FGFR4







Signal
PI-3K
40
60
14.29
85.71
sALS


Transduction
cascade:FGFR4




Down


Signal
Prolonged ERK
60
40
14.29
85.71
sALS


Transduction
activation events




Down


Signal
Retrograde
60
20
0
100
sALS


Transduction
neurotrophin




Down



signalling







Signal
SHC-mediated
80
20
14.29
85.71
sALS


Transduction
cascade:FGFR1




Down


Signal
SHC-mediated
80
20
14.29
85.71
sALS


Transduction
cascade:FGFR2




Down


Signal
SHC-mediated
80
20
14.29
85.71
sALS


Transduction
cascade:FGFR3




Down


Signal
SHC-mediated
80
20
14.29
85.71
sALS


Transduction
cascade:FGFR4




Down


Signal
Signaling by
60
40
14.29
85.71
sALS


Transduction
FGFR




Down


Signal
Signaling by
60
40
14.29
85.71
sALS


Transduction
FGFR3




Down


Signal
Signaling by
60
40
14.29
85.71
sALS


Transduction
FGFR4




Down


Signal
TCF dependent
60
40
14.29
85.71
sALS


Transduction
signaling in




Down



response to








WNT







Signal
WNT mediated
20
20
0
85.71
sALS


Transduction
activation of




Down



DVL







Signal
MET activates
60
20
100
0
sALS Up


Transduction
PTPN11







Signal
RHO GTPases
20
20
85.71
14.29
sALS Up


Transduction
activate IQGAPs







Signal
RHO GTPases
80
20
85.71
14.29
sALS Up


Transduction
Activate WASPs








and WAVEs







Signal
Signaling by
100
0
85.71
14.29
sALS Up


Transduction
Hippo







Signal
Signaling by
60
40
85.71
14.29
sALS Up


Transduction
VEGF







Transport of
Transferrin
20
80
28.57
71.43
fALS


small
endocytosis and




Down


molecules
recycling







Transport of
ABC-family
80
20
71.43
28.57
fALS Up


small
proteins







molecules
mediated








transport







Transport of
Ion channel
60
40
14.29
85.71
sALS


small
transport




Down


molecules








Transport of
VLDL clearance
40
20
85.71
14.29
sALS Up


small








molecules








Vesicle-
Binding and
80
20
57.14
42.86
fALS Up


mediated
Uptake of







transport
Ligands by








Scavenger








Receptors







Vesicle-
Scavenging by
80
20
57.14
42.86
fALS Up


mediated
Class A







transport
Receptors










Dysregulated pathways in diMN transcriptomics comparisons











Main






biological

fALS
sALS



process
Pathway
(iPanda)
(iPanda)
Direction





Developmental
Regulation of signaling by NODAL
−0.0022
−0.0111
sALS


Biology



down


Digestion and
Digestion
0.0132
0.0001
fALS up


absorption






Digestion and
Digestion and absorption
0.0121
0.0001
fALS up


absorption






Digestion and
Digestion of dietary lipid
0.0209
0
fALS up


absorption






Disease
Diseases associated with visual transduction
0
0.0255
sALS up


Disease
Diseases of the neuronal system
0
0.0255
sALS up


Disease
Retinoid cycle disease events
0
0.0255
sALS up


Disease, Signal
Biosynthesis of A2E, implicated in retinal
0
0.0255
sALS up


Transduction
degradation





Immune
Activation of C3 and C5
0.0134
0.0029
fALS up


System






Immune
Alpha-defensins
0.0002
−0.0104
sALS


System



down


Immune
Ficolins bind to repetitive carbohydrate
−0.0187
0
fALS


System
structures on the target cell surface


down


Immune
Lectin pathway of complement activation
−0.0125
0
fALS


System



down


Immune
OAS antiviral response
0.0351
0.0189
fALS up,


System



sALS up


Immune
CREB phosphorylation
0.0186
0.0219
fALS up,


System, Signal



sALS up


Transduction






Metabolism
Acyl chain remodeling of DAG and TAG
0.0272
0
fALS up


Metabolism
Blood group systems biosynthesis
0.0305
0
fALS up


Metabolism
Lipid particle organization
0.0004
−0.0101
sALS






down


Metabolism
PAOs oxidise polyamines to amines
0.0109
0.0007
fALS up


Metabolism
Rhesus blood group biosynthesis
0.0305
0
fALS up


Metabolism of
Activation of the mRNA upon binding of the
0.0005
0.0137
sALS up


proteins
cap-binding complex and e1Fs, and






subsequent binding to 43S





Metabolism of
Cap-dependent Translation Initiation
0.0004
0.0114
sALS up


proteins






Metabolism of
Eukaryotic Translation Initiation
0.0004
0.0111
sALS up


proteins






Metabolism of
Formation of the ternary complex, and
0.0005
0.0161
sALS up


proteins
subsequently, the 43S complex





Metabolism of
GTP hydrolysis and joining of the 60S
0.0003
0.0104
sALS up


proteins
ribosomal subunit





Metabolism of
Ribosomal scanning and start codon
0.0005
0.0141
sALS up


proteins
recognition





Metabolism of
Translation initiation complex formation
0.0005
0.0141
sALS up


proteins






Metabolism of
Major pathway of rRNA processing in the
0.0005
0.0122
sALS up


RNA
nucleolus and cytosol





Metabolism of
rRNA processing
0.0005
0.0122
sALS up


RNA






Metabolism of
rRNA processing in the nucleus and cytosol
0.0005
0.0122
sALS up


RNA






Neuronal
Neurexins and neuroligins
0.0003
0.0351
sALS up


System






Neuronal
Protein-protein interactions at synapses
0.0003
0.0281
sALS up


System






Signal
Activation of the phototransduction cascade
0
−0.0135
sALS


Transduction



down


Signal
Serotonin receptors
−0.0134
−0.003
fALS


Transduction



down


Transport of
Erythrocytes take up carbon dioxide and
0
−0.053
sALS


small
release oxygen


down


molecules






Transport of
Erythrocytes take up oxygen and release
0
−0.053
sALS


small
carbon dioxide


down


molecules






Transport of
O2—CO2 exchange in erythrocytes
0
−0.053
sALS


small



down


molecules














Dysregulated pathways in diMN proteomics comparisons











Main






biological

fALS
sALS



process
Pathway
(iPanda)
(iPanda)
Direction





Cell Cycle,
Meiosis
0.0106
−0.0006
fALS up


Reproduction






Cell Cycle,
Meiotic recombination
0.0154
−0.0007
fALS up


Reproduction






Cell-Cell
Adherens junctions interactions
−0.0106
−0.0006
fALS


communication



down


Cell-Cell
Nectin-Necl trans heterodimerization
−0.0104
−0.0003
fALS


communication



down


Developmental
Inactivation of CDC42 and RAC1
−0.0026
−0.0133
sALS


Biology



down


Developmental
Myogenesis
−0.0174
0
fALS


Biology



down


Developmental
NCAM signaling for neurite out-growth
−0.0104
−0.0003
fALS


Biology



down


Developmental
NCAM1 interactions
−0.026
−0.0005
fALS


Biology



down


Developmental
Neurofascin interactions
−0.037
−0.0008
fALS


Biology



down


Developmental
NrCAM interactions
−0.0123
−0.003
fALS


Biology



down


Developmental
Other semaphorin interactions
−0.0105
0
fALS


Biology



down


Disease
ABC transporter disorders
0.0008
0.012
sALS up


Disease
APOBEC3G mediated resistance to HIV-1
0.001
0.0326
sALS up



infection





Disease
Assembly Of The HIV Virion
0.0009
0.0304
sALS up


Disease
Binding and entry of HIV virion
0.0026
0.0912
sALS up


Disease
Defective CFTR causes cystic fibrosis
0.0008
0.012
sALS up


Disease
Disorders of transmembrane transporters
0.0008
0.012
sALS up


Disease
Early Phase of HIV Life Cycle
0.0006
0.0204
sALS up


Disease
Hh mutants abrogate ligand secretion
0
0.0214
sALS up


Disease
Hh mutants that don't undergo autocatalytic
0
0.0214
sALS up



processing are degraded by ERAD





Disease
InlA-mediated entry of Listeria
−0.0339
−0.0028
fALS




monocytogenes into host cells



down


Disease
Integration of provirus
0.0004
0.0161
sALS up


Disease

Listeria monocytogenes entry into host cells

−0.0109
−0.0009
fALS






down


Disease
Minus-strand DNA synthesis
0.0026
0.0912
sALS up


Disease
Plus-strand DNA synthesis
0.0026
0.0912
sALS up


Disease
Reverse Transcription of HIV RNA
0.0026
0.0912
sALS up


Disease
Uncoating of the HIV Virion
0.0026
0.0912
sALS up


DNA Repair
HDR through Homologous Recombination
0.0202
0
fALS up



(HRR)





DNA Repair
Homologous DNA Pairing and Strand
0.0156
0
fALS up



Exchange





DNA Repair
Presynaptic phase of homologous DNA
0.0147
0
fALS up



pairing and strand exchange





DNA Repair
Resolution of D-Loop Structures
0.0213
0
fALS up


DNA Repair
Resolution of D-loop Structures through
0.0213
0
fALS up



Holliday Junction Intermediates





DNA Repair
Resolution of D-loop Structures through
0.0213
0
fALS up



Synthesis-Dependent Strand Annealing






(SDSA)





Gene
RNA Polymerase III Abortive And Retractive
−0.0114
−0.0022
fALS


expression
Initiation


down


(Transcription)






Gene
RNA Polymerase III Chain Elongation
−0.014
−0.0028
fALS


expression



down


(Transcription)






Gene
RNA Polymerase III Transcription Initiation
−0.0109
−0.0013
fALS


expression
From Type 3 Promoter


down


(Transcription)






Gene
RNA Polymerase III Transcription
−0.0129
−0.0026
fALS


expression
Termination


down


(Transcription)






Gene
RUNX3 regulates p14-ARF
0.117
0.0545
fALS up,


expression



sALS up


(Transcription)






Gene
RUNX3 regulates WNT signaling
−0.0119
0
fALS


expression



down


(Transcription)






Gene
TFAP2 (AP-2) family regulates transcription
−0.0028
−0.0713
sALS


expression
of growth factors and their receptors


down


(Transcription)






Gene
Transcriptional regulation by RUNX3
0.0404
0.0191
fALS up,


expression



sALS up


(Transcription)






Metabolism
CYP2E1 reactions
−0.0109
−0.0047
fALS






down


Metabolism of
Incretin synthesis, secretion, and inactivation
−0.0119
0
fALS


proteins



down


Metabolism of
Protein methylation
−0.0002
−0.0121
sALS


proteins



down


Metabolism of
Synthesis, secretion, and inactivation of
−0.0119
0
fALS


proteins
Glucagon-like Peptide-1 (GLP-1)


down


Muscle
Phase 2-plateau phase
0.0001
0.0125
sALS up


contraction






Neuronal
Activation of GABAB receptors
−0.0166
−0.0001
fALS


System



down


Neuronal
GABA B receptor activation
−0.015
−0.0001
fALS


System



down


Neuronal
GABA receptor activation
−0.0135
−0.0001
fALS


System



down


Neuronal
Adenylate cyclase inhibitory pathway
−0.0259
−0.0001
fALS


System, Signal



down


Transduction






Programmed
Stimulation of the cell death response by
0.0017
0.0101
sALS up


Cell Death
PAK-2p34





Reproduction
Reproduction
0.0106
−0.0006
fALS up


Signal
Binding of TCF-LEF:CTNNB1 to target
−0.0119
0
fALS


Transduction
gene promoters


down


Signal
G-protein activation
−0.0101
−0.0003
fALS


Transduction



down


Signal
G-protein mediated events
−0.0122
−0.0001
fALS


Transduction



down


Signal
Hedgehog ligand biogenesis
0.0001
0.0185
sALS up


Transduction






Transport of
ABC-family proteins mediated transport
0.0006
0.0104
sALS up


small






molecules






Transport of
Bicarbonate transporters
−0.0202
0
fALS


small



down


molecules









The dysregulated pathways in the diMN ALS groups belonged to different biological processes when compared to the CNS groups. For the diMN transcriptomics comparisons, pathways of oxygen and carbon dioxide exchange were found to be inhibited, and pathways of the cap-dependent translation, disease associated with visual transduction, and digestion and absorption were found to be activated in ALS case groups (FIG. 6a). For the diMN proteomics comparisons, the RNA polymerase III transcription and GABA receptor pathways were found to be inhibited (FIG. 6b). On the other hand, pathways of the early phase of HIV life cycle, homologous recombination of DNA repair, and reproduction were activated. The pathways related to signal transduction and its related diseases, transmembrane transporter disorders, and transcriptional regulation by RUNX3 formed the largest cluster due to their shared genes of the ubiquitin-proteasome system, such as the ubiquitin genes (UBC, UBB and UBA52), the proteasome genes (SEM1, RPS27A, and PSM subunits), and the endoplasmic reticulum (ER)-associated degradation genes (VCP, SEL1L, OS9, ERLEC1, and DERL2).


Targets Based on CNS Data

Fourteen high confidence, one novel to ALS and eight novel to all disease targets are selected based on CNS data. They are mainly involved in the biological process of apoptosis and inflammation (Table 5).


CNS Targets and Apoptosis
MAP3K5

Neuronal cell death serves as the ultimate consequence of various ALS pathogenic signatures, such as mitochondrial dysfunction and excitotoxicity. Apoptosis and necroptosis are the two pivotal mechanisms underlying motor neuron loss. Among the CNS comparisons, multiple targets with altered expression profiles contributed to neuronal apoptosis that might serve as therapeutic targets to tackle neurodegeneration. MAP3K5 regulates the activities of p38 and JNK in response to various environmental stresses. Accumulating evidence indicated the contribution of MAP3K5 activation to neurodegeneration. In ALS, lymphocytes isolated from the patients displayed elevated levels of MAP3K5 when compared with healthy individuals. Activated MAP3K5 was markedly increased in the motor neurons of SOD1 transgenic mice. Our data also showed a general upregulation of MAP3K5 in CNS fALS comparisons (80%). Moreover, several studies revealed the linkage between SOD1 mutant and MAP3K5 activation in neuronal cell death. Administration of MAP3K5 inhibitors prolongs survival of SOD1mut mice through blocking MAP3K5 activity and glial activation in the spinal cord[4], indicating the significance of MAP3K5 upregulation in ALS.


NOSI

Following p38 activation by MAP3K5, ALS-driven gene transcription stimulates the activities of toxic enzymes, including neuronal nitric oxide synthase (nNOS). nNOS synthesizes nitric oxide (NO) from L-arginine. It is encoded by NOS1, a target that was overexpressed in over 80% of both fALS and sALS CNS comparisons. NO itself is nontoxic and essential for neural communication. However, mitochondrial dysfunction in ALS stimulates the production of a superoxide anion, which immediately reacts with NO to form a potent oxidant-peroxynitrite. Peroxynitrite is neurotoxic in terms of its action on inhibiting mitochondrial proteins, suppressing ATP synthesis, and DNA damage. In addition, increased NO level in cultured motor neuron cells promoted mutant SOD1 aggregation, and this scenario was prevented by the use of NOS signaling inhibitors. Recent studies also illustrated the overexpression of nNOS as a common event in ALS[8], which aligned with our findings. Taking these facts into account, we speculate that together with MAP3K5 overexpression, upregulation of NOS1 amplifies the production of NO and peroxynitrite, making motor neurons more vulnerable to reactive oxygen species-induced apoptosis.


RARA

In contrast to MAP3K5 and NOS1, RARA was generally downregulated in our CNS sALS comparisons (14.3% upregulated). RARA encodes the nuclear retinoic acid receptors alpha (RARα), a transcriptional activator in the retinoid signaling pathway. RAR functions as a heterodimer by binding with retinoid X receptor (RXR) to activate transcription of their downstream targets, and thus trigger various cellular responses, such as apoptosis, cell differentiation, and embryonic development. Retinoids display critical roles in CNS development via promoting neural patterning, neural differentiation, and motor axon outgrowth[9]. Upon nerve injury, retinoid signaling is activated to promote nerve regeneration, as well as suppress inflammatory cytokine production. Deficiency of RARα was observed in motor neurons from sALS patients, and in lumbar spinal cord tissue of SOD1G93A mice. Goncalves et al. showed that RARαagonist stimulates Aβ clearance and attenuated inflammation in Alzheimer's disease (AD) in vivo, suggesting a potential therapeutic role of RARα as a neuroprotective agent in treating neurodegeneration.


CNS Targets and Inflammation
PTPRC

With evidence in both ALS patients and in vivo models, neuroinflammation has posed a detrimental effect on ALS progression. It is marked by microglial activation, infiltration of macrophages, as well as complement signaling activation in the CNS tissue. Several selected candidates (Table 5) were functionally associated with immune regulation, or with evidence participating in the inflammatory response in neurodegeneration. For instance, upregulation of PTPRC is detected in 80% of CNS fALS and 86% of sALS comparisons. PTPRC encodes CD45, a transmembrane protein tyrosine phosphatase expressed in all leukocytes. CD45 takes a key role in orchestrating T cell antigen receptor signaling. Its depletion could result in severe immunodeficiency due to T cell and B cell dysfunction. Data from a gene co-expression network analysis suggests PTPRC acts as a top hub gene in the immune/microglia module in patients with neurodegeneration. It is noteworthy that entry of immune cells into the brain is strictly controlled by the blood-brain barrier, unless there is a breakage in the barrier. It is proposed PTPRC might serve as a potential biomarker for ALS and its expression is positively correlated with inflammatory cell counts in ALS patients[10]. Furthermore, enrichment of PTPRC protein is also reported in AD human tissue and mouse models, indicating the possible connection between PTPRC and neurodegenerative disease.


NR3C1

Another example is NR3C1, the gene that encodes glucocorticoid receptors. NR3C1 has a dual mode of action by functioning as a modulator of transcription factors and as a transcription factor itself. The expression of NR3C1 in the CNS tissue was found to be generally upregulated in both fALS (80%) and sALS (86%) comparisons. Immunosuppression therapy involving two NR3C1 agonists, viz. methylprednisolone and prednisone, was tested in ALS but none of the patients reached the pre-defined responder criteria after treatment. However, the therapeutic potential of an NR3C1 antagonist (CORT113176) was revealed in the ALS-mimic mouse model by reducing the expression and origin of pro-inflammatory factors. Given the up-regulated expression of NR3C1 in ALS comparisons as well as the supportive preclinical evidence of NR3C1 antagonists, NR3C1 could be a potent actionable candidate for the treatment of ALS patients, especially those with high inflammation markers.


Novel CNS Targets
STUB1

Despite the majority of CNS targets underlying neuronal cell death and inflammation, several targets were functionally correlated with the early-stage ALS characters, especially for novel targets (Table 5). STUB1 was consistently downregulated in both CNS fALS (20% upregulated) and sALS (14.3% upregulated) comparisons. It is a well-known protein with dual roles serving as both co-chaperone and E3 ubiquitin ligase. Growing evidence suggests that the impact of STUB1 on protecting neurons against the cellular toxicity of pathogenic protein aggregates. Overexpressing STUB1 reduces cytotoxicity by promoting mutant SOD1 elimination[11]. Dorfin is recognized for its activity in the ubiquitination of mutant SOD1 proteins but has low stability. STUB1 stabilizes Dorfin in the form of chimeric proteins and enhances its efficacy of mutant SOD1 ubiquitination and degradation in vivo. STUB1 also protects against AD and Parkinson's disease (PD) through increasing the degradation of Aβ plaques and α-Synuclein, respectively. These altogether delineate the importance of STUB1 in acting as a safeguard to prevent neurons from mutant SOD1-induced cytotoxicity.


ATP5F1A

Impaired mitochondrial function is an emerging critical pathophysiological condition that drives neurodegeneration, including ALS. Elevated oxidative stress, reduced ATP production, mitochondrial DNA mutations, and F1F0 ATP synthase malfunction collectively contribute to mitochondrial dysfunction. ATP synthase is responsible for the final stage of oxidative phosphorylation. The imbalance of the F1/F0 ratio in ATP synthase is indicated as a disease driving force in AD and PD. ATP5F1A, encoding F1 subunit alpha, was downregulated in all CNS sALS comparisons. Aligning with our finding, downregulation of ATP5F1A is reported in brain tissue of patients with C9orf72-mediated ALS, and as a consequence of protein ubiquitination induced by poly (GR) peptides[12]. Although limited knowledge is available regarding the relationship between ATP5F1A and ALS, it is worth further examination due to the growing attention on how ATP synthase works in fighting ALS.









TABLE 5







List of therapeutic targets for amyotrophic lateral sclerosis based on CNS data














Gene1
fALS2
sALS2
Proposed therapy3
Protein family
Tissue enrichment4
Proposed ALS mechanism
# Trials










High confidence














ADRA2B
80%
50%
Antagonist (fALS)
GPCR
Low tissue specificity
Protein degradation
1,577


CYBB
80%
86%
Antagonist
Ion channel
Blood, lung, lymphoid tissue
Oxidative stress
0


FLT1*
80%
57%
Antagonist (fALS)
Receptor kinase
Placenta
Inflammation
3,154


HDAC1*
80%
43%
Antagonist (fALS)
Hydrolase
Low tissue specificity
Apoptosis
1,302


IGF1R*
80%
43%
Antagonist (fALS)
Receptor kinase
Low tissue specificity
Apoptosis
269


MAP3K5*
80%
71%
Antagonist (fALS)
Protein kinase
Adrenal gland
Apoptosis
6


MAPK1*
80%
71%
Antagonist (fALS)
CMGC kinase
Brain
Apoptosis
12


MLKL
100% 
43%
Antagonist (fALS)
Tyrosine kinase-like
Vagina
Apoptosis
0


NOS1
80%
86%
Antagonist
Oxidoreductase
Brain and skeletal muscle
Oxidative stress
58


NR3C1*
80%
86%
Antagonist
Nuclear receptor
Low tissue specificity
Inflammation
7,761


PTK2
40%
86%
Antagonist (sALS)
Tyrosine kinase
Low tissue specificity
Protein aggregation
45


PTPRC
80%
86%
Antagonist
Receptor phosphatase
Blood, lymphoid tissue
Inflammation
9


RARA
50%
14%
Agonist (sALS)
Nuclear receptor
Low tissue specificity
Neurogenesis
500


VDR
60%
14%
Agonist (sALS)
Nuclear receptor
Intestine, parathyroid gland
Apoptosis
1,531







Novel to ALS














KCNB2
60%
83%
Antagonist (sALS)
Ion channel
Brain, lymphoid tissue, pituitary
Excitotoxicity
64







gland









Novel to all diseases














AHCYL1
100% 
71%
Antagonist
Enzyme
Low tissue specificity
Apoptosis
0


ATP5F1A
50%
 0%
Agonist (sALS)
Hydrolase
Low tissue specificity
Mitochondrial dysfunction
0


NR2F6
60%
14%
Agonist (sALS)
Nuclear receptor
Low tissue specificity
Inflammation
0


P2RY14
40%
14%
Agonist (sALS)
GPCR
Granulocytes, dendritic cells,
Inflammation
0







placenta




PDIA6
60%
71%
Antagonist (sALS)
Isomerase
Low tissue specificity
Protein aggregation
0


SCYL1*
40%
14%
Agonist (sALS)
Protein kinase
Low tissue specificity
Apoptosis
0


SLC25A10
20%
29%
Agonist
Transporter
Liver
Oxidative stress
0


STUB1*
20%
14%
Agonist
Acyltransferase
Low tissue specificity
Protein degradation
0






1Manually curated aging-associated genes (marked with *) based on pathways suggested by López-Otín et al. or GenAge database (https://genomics.senescence.info/genes/index.html);




2Percentage of comparisons with up-regulated target (LFC > 0) out of five fALS or seven sALS comparisons;




3Therapy proposed based on expression alterations in fALS and/ or sALS comparisons;




4Tissue enrichment (RNA) retrieved from Human Protein Atlas (https://www.proteinatlas.org/).








Targets Based on diMN Data


Seven high confidence, two novel to ALS, and three novel to all disease targets are selected based on diMN data (Table 6)


diMN Targets and Proteostasis Disturbance


ERN1

Accumulation of misfolded proteins, i.e., SOD1 and TDP-43 aggregates, has long been demonstrated as a cause of ALS. Several dysregulated targets identified from diMN comparisons (Table 6) were likely to be associated with impaired proteostasis in ALS and other neurodegenerative diseases, such as ERN1 and PPP3CB. The unfolded protein response (UPR) serves as a critical stress response to cope with ER stress and maintain cell viability. IRE1 is one of the primary sensors for UPR. The mRNA level of ERN1, encoding IRE1, is found to be upregulated in diMN fALS samples (LFC=0.2058, p=0.003). IREI signaling is considered to be pathogenic in AD and PD. The administration of PPAR agonist exerts its protective effect on neurodegeneration through suppression of IRE1-mediated ER stress response. In SOD1G93A mice, IRE1 protein level is elevated with disease progression[13]. Downstream targets of the IRE1 pathway are also reported to be activated in the spinal cord of ALS patients. These altogether confer the therapeutic possibility of targeting ERN1 in ALS.


PPP3CB

Calcineurin (Cn) is a calcium-and calmodulin-dependent serine/threonine phosphatase that participates in Ca2+-dependent signaling transduction to dephosphorylate and activate multiple proteins, such as SSH1, DNM1L, and NFAT. PPP3CB encodes the β-isoform of its catalytic subunit. It has been reported that the activity of Cn is correlated with SOD1 and TDP-43. SOD1 serves as the upstream regulator of Cn and stabilizes its activity via active site interaction. Alteration in the conformation state of SOD1 impairs its interaction with Cn. As a consequence, the weakening of SOD1G93A-Cn interaction in SODG93A mice decreased Cn stability, leading to the defect in TDP-43 dephosphorylation. TDP-43 aggregation—one of the critical pathogenic features in ALS—was therefore detected in the spinal cord tissue[14]. Moreover, trehalose, a natural compound tested to be beneficial in multiple neurodegenerative models, executes its function via activating PPP3CB/Cn. PPP3CB stimulates the activity of transcription factor EB, and eventually promotes autophagy to ameliorate neurodegeneration. Our result further supported these findings by indicating the reduction of PPP3CB protein level in diMN fALS samples (LFC=−0.3048, p=0.0115).


diMN Targets and Compromised Mitochondrial Function


VCP

Cancer, neurodegenerative and cardiovascular diseases are documented as the manifestations of redox imbalance. Mounting evidence indicates the implication of oxidative stress in promoting neurodegeneration. VCP is dysregulated in diMN proteomics comparisons (Table 6). VCP has been evaluated as an ALS-linked gene in the recent decade, and its mutations are reported in 1-2% of ALS patients. Positive correlation is observed between VCP-positive cell count and severity of the disease in ALS patients. Functionally, VCP mutations are closely linked with protein mislocalization, as well as deterioration of mitochondrial function. Knock-in mouse model with VCPR155H mutation resembles the key feature of ALS, including pronounced motor neuron loss, TDP-43 aggregation, and mitochondrial malfunction. As a result, VCP inhibitor has drawn attention due to its favourable outcome on relieving ALS phenotypes. Recently, pharmacological inhibition of VCP effectively corrects mislocalization of RNA-binding proteins, including SOD1 and TDP-43, in VCP mutant motor neurons[15]. Here our finding was aligned with the literature by showing upregulation of VCP in sALS samples (LFC=0.0776, p=0.0411).


G6PD

G6PD, the key cytosolic enzyme responsible for the production of antioxidant NADPH, was also found to be dysregulated in fALS samples (LFC=−0.1416, p=0.0487). Babu et al. reported progressive reduction in G6PD activity during disease development in sALS patients, which is in accordance with our result. NADPH is an essential reducing agent in all organisms. Depletion of NADPH triggers oxidative stress and subsequently induces DNA damage and cell death. In aged mice, increase in G6PD level offers a protective effect against oxidative stress-induced neurodegeneration[16]. Similar results are also observed in an in vivo PD model. Treatment with G6PD agonist restores redox balance in zebrafish and in vitro models. Although it is debatable whether targeting mitochondrial dysfunction is efficient in treating neurodegeneration, these findings enrich our knowledge on the correlation between mitochondrial homeostasis and ALS.









TABLE 6







List of therapeutic targets for amyotrophic lateral sclerosis based on diMN data

















Proposed


Proposed ALS



Gene1
fALS LFC (p)2
sALS LFC (p)2
therapy3
Protein family
Tissue enrichment4
mechanism
# Trials










High confidence














PPIA
  0.1728 (0.0338)
  0.2361 (0.0003)
Antagonist (P)
Isomerase
Low tissue specificity
TDP-43 pathology,
1,376








(inflammation)



DNMT3A
  0.1324 (0.0346)
  0.0773 (0.1172)
Antagonist (T)
Methyltransferase
Low tissue specificity
Apoptosis
1,038


ERN1
  0.2058 (0.003) 
  0.0699 (0.1644)
Antagonist (T)
Protein kinase
Low tissue specificity
Protein aggregation
0


HSPD1*
  0.1363 (0.1365)
  0.1916 (0.0083)
Antagonist (P)
Isomerase
Vagina
FUS pathology,
0








inflammation



RPS6KB1
  0.1558 (0.0297)
  0.1426 (0.0052)
Antagonist (T)
AGC kinase
Low tissue specificity
Protein aggregation
12


VCP
  0.0212 (0.637) 
  0.0776 (0.0411)
Antagonist (P)
Hydrolase
Low tissue specificity
Mitochondrial
0








dysfunction



G6PD
−0.1416 (0.0487)
−0.0847 (0.1337)
Agonist (P)
Oxidoreductase
Testis
Oxidative stress
0







Novel to ALS














KCNS3
  0.3886 (0.0995)
  0.3338 (0.0282)
Antagonist (T)
Ion channel
Skeletal muscle
Excitotoxicity
64


PSMC6*
−0.2636 (0.0402)
−0.1502 (0.0926)
Agonist (P)
Hydrolase
Low tissue specificity
Proteostasis
3







Novel to all diseases














METTL21A
   0.196 (0.0012)
  0.0827 (0.0432)
Antagonist (T)
Methyltransferase
Low tissue specificity
Protein aggregation
0


TOPORS
  0.2161 (0.0135)
  0.1385 (0.0184)
Antagonist (T)
Acyltransferase
Low tissue specificity
Apoptosis
0


PPP3CB*
−0.3048 (0.0115)
−0.1371 (0.1725)
Agonist (P)
Esterase
Skeletal muscle
Protein aggregate
0








degradation






1Manually curated aging-associated genes (marked with *) based on pathways suggested by López-Otín et al. or GenAge database (https://genomics.senescence.info/genes/index.html);




2The therapy was proposed for the underscored subtype(s) based on both expression alteration and TargetID ranking;




3Therapy proposed based on expression alterations using transcriptomics (T) or proteomics (P) data;




4Tissue enrichment (RNA) retrieved from Human Protein Atlas (https://www.proteinatlas.org/).







Potential Repurposing Candidates

With the proposed therapies for each target (Tables 5 and 6), drugs tackling our target genes were curated and evaluated for their safety, mechanism of action (MOA), and blood-brain barrier penetrability. The refined list of repurposing candidates includes thirteen drugs targeting nine different genes (Table 7). All the proposed candidates have been investigated in one or more nervous system disorders with clinical trials ranging from phase 2 to 4 (launched).


Mirtazapine

Mirtazapine functions as a strong antagonist of serotonin receptors and adrenergic receptors, including ADRA2B, to stimulate norepinephrine and serotonin secretion in patients suffering from depression. In current study, ADRA2B was upregulated in 80% of CNS fALS comparisons. Treatment of ADRA2 agonist aggravates disease phenotypes in SOD1G93A mice. In consideration of the above facts, mirtazapine is regarded as one of the repurposing candidates for ALS treatment.


Dalfampridine

Dalfampridine is a potassium ion channel blocker approved to facilitate the mobility of patients with multiple sclerosis. A few studies report KCNS3 as a risk gene in AD and PD. However, there is no direct evidence of the association of potassium ion channel expression upregulation and ALS. Since upregulations of KCNB2 and KCNS3 were detected in our study, dalfampridine could be a potential therapeutic for ALS in light of its good efficacy and acceptable safety profile in treating patients with multiple sclerosis.


Acitretin

Acitretin, an agonist of retinoic acid receptors, has been approved to treat severe psoriasis. Besides, it is under investigation for AD in terms of its anti-amyloidogenic and immune-stimulatory effects. According to the general downregulation in CNS ALS comparisons and the neuroprotective role of RARA, acitretin was proposed for repurposing to treat ALS. Given the adverse effects of causing birth defects, acitretin therefore might be contraindicated in female patients who are pregnant or intend to become pregnant.









TABLE 7







List of repurposing candidates for amyotrophic lateral sclerosis.

















Max

Target
BBB

Natural
Associated neurological


Drug
Target
phase1
Drug MOA
genes2
penetration3
IC504
compound5
diseases6


















Mirtazapine
ADRA2B
Launched
Antagonist of
HTR2A,
0.9855


Depression [NCT00782405],





ADRA2B,
ADRA2B,



Cocaine dependence





HTR2C
ADRA2A,



[NCT00249444],





and HTR2A
HTR2C,



Alcohol dependence






OPRK1,



[NCT00874003], etc.






HRH1






Labetalol
ADRA2B
Launched
ADRA2B
ADRB1,
0.8313
13.2 mg/L in

Stroke [NCT02327793],





antagonist
ADRB2

human

Nicotine dependence








neutrophils

[NCT00000297], Cocaine










dependence [NCT00000291],










Intracerebral hemorrhage










[NCT00963976]


Azacitidine
DNMT3A
Launched
Pyrimidine
DNMT1,
0.8753
0.019 μg/mL

CNS cancer [NCT03666559],





nucleoside
DNMT3A

on mouse

childhood ependymoma





analogue


leukemia

[NCT03206021],








cells

ependymoma










[NCT03572530], etc


Decitabine
DNMT3A
Launched
Pyrimidine
DNMT1,
0.8787
0.1 μM on

Medulloblastoma





nucleoside
DNMT3A,

leukemia

[NCT02332889],





analogue
DNMT3B

cells

neuroblastoma








at 24 h

[NCT00075634]


AXL-1717
IGF1R
P2
IGF1R
IGF1R

1 nM for

Recurrent malignant





inhibitor


IGF1R

astrocytomas










[NCT01721577]


Dalfampridine
KCNB2
Launched
Voltage-gated
KCNA,
0.9544
290 μM for
NPC57565
Multiple sclerosis





potassium
KCNB,

KCNA1

[NCT01480076], Stroke





channel
KCNC,

1.5 mM

[NCT02422940], Spinal cord





blocker
KCND

for KCNB2

injury [NCT00041717], etc.






subfamilies

29 μM for










KCNC1




Ulixertinib
MAPK1
P2
MAPK1
MAP3,

<0.3 nM for

Uveal melanoma





inhibitor
MAPK1

ERK2*

[NCT03417739]


Ronopterin
NOS1
P3
NOS inhibitor
NOS



Traumatic brain injury


Mifepristone
NR3C1
Launched
Antagonist of
PGR,
0.7135
0.2 nM for
SN00064357
Depression [NCT00128479],





NR3C1 and
NR3C1,

NR3C3*

Alcohol dependence





NR3C3
KLK3,

2.6 nM for

[NCT01548417],






NR1I2

NR3C1*

Bipolar disorder










[NCT00043654],










Meningioma










[NCT03015701], etc.


ORG-34517
NR3C1
P2
NR3C1
NR3C1

17.9 nM for

Depression [NCT00212797]





antagonist


NR3C1*




Cyclosporine
PPIA
Launched
Calcineurin
PPIA

7 nM for

Juvenile dermatomyositis





inhibitor


calcineurin

[NCT00323960],










neuroblastoma










[NCT00874315],










retinoblastoma










[NCT00110110], etc


Acitretin
RARA
Launched
Retinoid
RXRA,
10.5841
6.6 μM for

Alzheimer's disease





receptor agonist
RARA,

proliferation

[NCT01078168]






RARB,










RARG,










RXRB,










RXRG,










RBP1






Tamibarotene
RARA
P2
RAR-α agonist
RARA,
0.9589
6.9 nM for

Alzheimer's disease






RARB

RARA

[NCT01120002]






1Maximum phase in ClinicalTrials.gov;




2Retrieved from DrugBank or ChEMBL;




3Predicted probability in DrugBank or inferred based on the disease type the drug was tested in;




4Retrieved from Selleckchem.com (marked by *) or other websites;




5Match of drug name in Super Natural II or NPASS (NPC) database;




6ID of the maximum-phased clinical trial of the disease shown in brackets.







6. Discussion

After decades of research, the involvements of multiple factors and pathogenic variations among ALS patients make it difficult to draw a conclusive pathophysiologic process of ALS. In order to obtain a better understanding of the biology of ALS, integrative multi-omics approaches were applied to dissect the disease physiology. PandaOmics™ is a fully integrated AI-based platform with a wide range of omics and text data sources. Compared to other existing tools for target discovery, PandaOmics™ has several unique advantages with respect to user experience, algorithms, the comprehensive database, and the time machine validation approach. The platform not only offers differential gene expression and pathway analysis but also a ranking of target genes based on a dynamic calculation of the selected datasets, either custom uploaded or pre-processed, in PandaOmics™. More importantly, multi-layer validations were included to estimate each model's performance with respect to the type of experimental data, protein family, disease area, and ability to suggest novel targets, etc. The time machine validation approach clearly demonstrated the power of the platform to find novel targets. With just a few clicks, the platform is able to propose druggable targets using multiple advanced bioinformatics and AI models, accelerating the drug discovery process. Therefore, PandaOmics™ is a unique and user-friendly AI-driven target discovery platform for therapeutic target exploration based on multi-omics data analysis that requires no prior knowledge of computational biology.


With the advance of medical care and improved lifestyles, human life expectancy has been significantly lengthened, which in turn poses significant health-associated challenges in our society due to the shift in demographic structure toward the aged. A wide variety of disorders are proven to be related to biological aging. Despite multiple risk factors being proposed to contribute to ALS, aging remains as one of the most prevalent risk factors[17]. Various molecular and cellular mechanisms, for instance, telomere attrition, mitochondrial dysfunction, and cell senescence contribute to the process of aging. Among our shortlisted therapeutic targets, several are suggested to be aging-associated, such as IGF1R, HDAC1,and PPP3CB. However, the mechanisms of how these targets function during aging remain controversial. For example, IGF1R signaling is beneficial to cognitive and cardiac health in aged rodent models. A population-specific gene expression analysis revealed that IGF1R expression decreased with age in PBMC extracted from Polish Caucasians, and proposed that the decline in IGF1R contributes to pro-inflammatory response. Oppositely, targeting IGF1R by monoclonal antibody expands the lifespan of female mice by 9%, as well as suppresses inflammation and tumorigenesis. Zarse et al. supported this hypothesis by demonstrating that impaired IGF-1 signaling triggers non-glucose metabolism to increase life expectancy.


In the present study, we show that several enriched pathway clusters are closely linked with ALS-driven mechanisms. For example, RNA metabolism was commonly dysregulated in our analysis regardless of tissue type. It is clear that altered RNA metabolism is a key concern in ALS. TDP-43 and FUS are RNA-binding proteins that exert broad impact on RNA metabolism pathways. Mutations in these two genes were proven to induce pathogenic RNA metabolic changes in ALS, such as mRNA translation defect, altered splicing function, and deregulated nonsense-mediated mRNA decay. Independent studies also evaluated the relevance of other ALS genes to RNA metabolism and uncovered that mutant C9orf72 might induce RNA toxicity. In addition, pathways controlling innate immune response and programmed cell death were found to be upregulated in CNS comparisons, in which both neuronal cell death and neuroinflammation are the well-characterized processes in promoting neurodegeneration. The hemostasis and erythropoietin signaling pathways were activated in CNS comparisons, suggesting activated neuro-immune hemostasis network in response to the CNS tissue damage. Excitotoxicity, a pathophysiological condition caused by excessive glutamate stimulation, is suspected as a mediator driving ALS development. This hypothesis is further supported by the action of riluzole, an FDA-approved anti-excitotoxic therapy, in ALS treatment. We also show that GABAergic signaling pathways were downregulated, leading to an increase in glutamate toxicity. It functions to counteract excessive neuronal excitability and offers a calming effect.


It is not surprising that fewer pathways will be uniformly altered in sALS relative to fALS comparisons given the complex genetic bases and the large variations among sporadic ALS individuals (FIG. 1). However, there are some pathway clusters that are specific to sALS, such as the FGFR signaling pathways. Fibroblast growth factors and their receptors play essential roles in the development, maintenance and repair of the nervous system. In adult mammals, FGF signaling is found to increase neuronal survival after spinal cord injury, and support the proliferation of neuronal progenitor cells. The inhibition of FGFR signaling indicates the reduction of neurogenetic effects underlying ALS etiology, which was confirmed in the CNS sALS groups (FIG. 1). However, it was not observed in the CNS fALS groups, which might stem from the lack of association between FGF signaling and C9orf72 mutations that represent the dominant genotype in the fALS comparisons (Table 1).


As the final phase for neurodegeneration, neuronal cell death could be the consequence of apoptosis or necroptosis, an alternative programmed cell death event characterized by inflammation. Neuroinflammation itself could also be a late-stage phenotype in ALS, supported by evidence in both human tissue and animal models[18]. In spite of the fact that both CNS and diMN target lists contain apoptosis-or inflammation-associated genes, we observed the majority of CNS targets (i.e. 61%) contribute to the late-stage signatures of ALS. This observation is in agreement with results obtained from pathway clustering analysis of CNS comparisons, partially due to the impact of late-stage pathological changes in the post-mortem tissues. Furthermore, miscellaneous cell types in CNS samples, consisting of neurons, glial cells, as well as CNS-resident and infiltrated immune cells upon neuronal injury, contribute to the expression profile observed in the analysis. Conversely, targets identified in diMN comparisons are dominantly involved in impaired proteostasis, one of the most well-studied pathophysiologies of early ALS[19]. Unlike CNS samples, transcriptomics and proteomics profiles in diMN ALS samples are solely derived from motor neurons, without the influence of non-neuron cells. Such comparisons could clearly reflect the disease pathology in motor neurons. In the absence of the aging process, it is reasonable that the roles of diMN targets are mainly involved in the early-stage signature of ALS. A recent study for Alzheimer's progression in the human brain highlighted the importance of integrating human data with cell lines and animal models data for a better understanding of different stages of disease development[20]. Therefore, our combinational usage of post-mortem CNS tissue and diMN samples could generate a comprehensive view of ALS pathogenesis.


To facilitate communication and collaboration of ALS research community and patients, we have constructed ALS.AI (http://als.ai/), an online interface for novel target disclosure and drug feedback collection for ALS. As is illustrated in FIG. 7, public or personalized datasets will be firstly analyzed in PandaOmics™ for target identification, followed by the curation and releasing of drugs associated with the identified novel and known targets onto ALS.AI. Feedback on the safety and efficacy of proposed drugs will be collected from ALS patients and KOLs, and the best candidates could be selected for further validation.


The current study has a limited number of fALS samples in both post-mortem and diMN comparisons due to the rarity of fALS incidence. Another limitation is the under-representation of racial groups other than the Caucasians in the present analysis. Future studies should include samples from a wider range of populations. ALS is a progressive disorder contributed by numerous interconnected mechanisms. It would be ideal to assess the pathogenic mechanisms underlying every stage of disease development. Yet data analyzed in the current analysis is likely to represent two stages in ALS—the late-stage in postmortem CNS tissue, and the early-stage reflected in diMN samples, harvested on Day 32. This time frame is generally adopted as the maturation time point of diMNs; therefore, this study model might not well-represent the aging effect in ALS disease progression. Including additional diMN differentiation time points might enhance the comprehensiveness of the analysis.


7. Conclusion

In the present study, we demonstrated the power of PandaOmics™ to find high confidence and novel targets for ALS with our latest AI models based on comprehensive omics data analysis. Several well-characterized mechanisms in ALS pathology are found to be dysregulated, including the immune system, RNA metabolism, excitotoxicity, as well as programmed cell death. Twenty-three and twelve targets are proposed according to the meta-analyses of CNS and diMN data respectively. Targets identified from CNS data mainly contribute to neuronal cell death and inflammation, which are recognized as late-stage signatures of ALS. In contrast, more diMN targets are attributed to the early-stage signatures. Combining the usage of diMN and post-mortem CNS samples could provide an in-depth understanding of ALS disease progression. To accelerate novel target discovery and drug investigation for ALS, targets identified in this study will be disclosed on ALS.AI.


8. References





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Claims
  • 1. A method for treating amyotrophic lateral sclerosis (ALS) in a subject in need thereof, comprising administering to the subject an effective amount of one or more active agents selected from the group consisting of a retinoic acid receptor alpha (RARα) agonist, a voltage-gated potassium channel (KCNB2) inhibitor, an adrenergic receptor α2B (ADRA2B) antagonist, a DNA methyltransferase 3 alpha (DNMT3A) antagonist, an insulin like growth factor 1 receptor (IGF1R) inhibitor, a mitogen-activated protein kinase 1 (MAPK1) inhibitor, a nitric oxide synthase 1 (NOS1) inhibitor, a glucocorticoid receptors (NR3C1) antagonist, and a peptidylprolyl Isomerase A (PPIA) antagonist.
  • 2. The method according to claim 1, wherein: the adrenergic receptor α2B (ADRA2B) antagonist is selected from mirtazapine and derivative thereof;the retinoic acid receptor alpha (RARα) agonist is selected from acitretin and derivative thereof;the voltage-gated potassium channel (KCNB2) inhibitor is selected from dalfampridine and derivative thereof:the DNA methyltransferase 3 alpha (DNMT3A) antagonist is selected from azacitidine, decitabine and derivatives thereof;the insulin like growth factor 1 receptor (IGF1R) inhibitor is selected from AXL-1717 and derivative thereof;the mitogen-activated protein kinase 1 (MAPK1) inhibitor is selected from ulixertinib and derivative thereof;the nitric oxide synthase 1 (NOS1) inhibitor is selected from ronopterin and derivative thereof;the glucocorticoid receptors (NR3C1) antagonist is selected from mifepristones, ORG-34517 and derivatives thereof; and/orthe peptidylprolyl Isomerase A (PPIA) antagonist is selected from cyclosporine and derivative thereof.
  • 3-10. (canceled)
  • 11. The method according to claim 1, comprising administering to the subject an effective amount of a first active agent and a second active agent, wherein the first active agent and the second active agent are different from each other and are independently selected from the group consisting of the retinoic acid receptor alpha (RARα) agonist, the voltage-gated potassium channel (KCNB2) inhibitor, the adrenergic receptor α2B (ADRA2B) antagonist, the DNA methyltransferase 3 alpha (DNMT3A) antagonist, the insulin like growth factor 1 receptor (IGF1R) inhibitor, the mitogen-activated protein kinase 1 (MAPK1) inhibitor, the nitric oxide synthase 1 (NOS1) inhibitor, the glucocorticoid receptors (NR3C1) antagonist and the peptidylprolyl Isomerase A (PPIA) antagonist.
  • 12. The method according to claim 11, wherein: the first active agent is the retinoic acid receptor alpha (RARα) agonist and the second active agent is the adrenergic receptor α2B (ADRA2B) antagonist;the first active agent is the voltage-gated potassium channel (KCNB2) inhibitor and the second active agent is the adrenergic receptor α2B (ADRA2B) antagonist; orthe first active agent is the retinoic acid receptor alpha (RARα) agonist and the second active agent is the voltage-gated potassium channel (KCNB2) inhibitor.
  • 13-14. (canceled)
  • 15. The method according to claim 11, wherein the first active agent and the second active agent are administered simultaneously, separately or sequentially.
  • 16. The method according to claim 1, comprising administering to the subject an effective amount of a first active agent, a second active agent and a third active agent, wherein the first active agent, the second active agent and the third active agent are different from each other and are independently selected from the group consisting of the retinoic acid receptor alpha (RARα) agonist, the voltage-gated potassium channel (KCNB2) inhibitor, the adrenergic receptor α2B (ADRA2B) antagonist, the DNA methyltransferase 3 alpha (DNMT3A) antagonist, the insulin like growth factor 1 receptor (IGF1R) inhibitor, the mitogen-activated protein kinase 1 (MAPK1) inhibitor, the nitric oxide synthase 1 (NOS1) inhibitor, the glucocorticoid receptors (NR3C1) antagonist and the peptidylprolyl Isomerase A (PPIA) antagonist.
  • 17. The method according to claim 16, wherein the first active agent is the retinoic acid receptor alpha (RARα) agonist, the second active agent is the voltage-gated potassium channel (KCNB2) inhibitor and the third active agent is the adrenergic receptor α2B (ADRA2B) antagonist.
  • 18. The method according to claim 16, wherein the first active agent, the second active agent and the third active agent are administered simultaneously, separately or sequentially.
  • 19. A combination of two or more active agents selected from the group consisting of a retinoic acid receptor alpha (RARα) agonist, a voltage-gated potassium channel (KCNB2) inhibitor, an adrenergic receptor α2B (ADRA2B) antagonist, a DNA methyltransferase 3 alpha (DNMT3A) antagonist, an insulin like growth factor 1 receptor (IGF1R) inhibitor, a mitogen-activated protein kinase 1 (MAPK1) inhibitor, a nitric oxide synthase 1 (NOS1) inhibitor, a glucocorticoid receptors (NR3C1) antagonist, and a peptidylprolyl Isomerase A (PPIA) antagonist; wherein the combination is used for the treatment of amyotrophic lateral sclerosis.
  • 20. The combination according to claim 19, wherein: the adrenergic receptor α2B (ADRA2B) antagonist is selected from mirtazapine and derivative thereof;the retinoic acid receptor alpha (RARα) agonist is selected from acitretin and derivative thereof;the voltage-gated potassium channel (KCNB2) inhibitor is selected from dalfampridine and derivative thereof;the DNA methyltransferase 3 alpha (DNMT3A) antagonist is selected from azacitidine, decitabine and derivatives thereof;the insulin like growth factor 1 receptor (IGF1R) inhibitor is selected from AXL-1717 and derivative thereof;the mitogen-activated protein kinase 1 (MAPK1) inhibitor is selected from ulixertinib and derivative thereof;the nitric oxide synthase 1 (NOS1) inhibitor is selected from ronopterin and derivative thereof;the glucocorticoid receptors (NR3C1) antagonist is selected from mifepristones, ORG-34517 and derivatives thereof; and/orthe peptidylprolyl Isomerase A (PPIA) antagonist is selected from cyclosporine and derivative thereof.
  • 21-28. (canceled)
  • 29. The combination according to claim 19, wherein the combination comprises a first active agent and a second active agent, wherein the first active agent and the second active agent are different from each other and are independently selected from the group consisting of the retinoic acid receptor alpha (RARα) agonist, the voltage-gated potassium channel (KCNB2) inhibitor, the adrenergic receptor α2B (ADRA2B) antagonist, the DNA methyltransferase 3 alpha (DNMT3A) antagonist, the insulin like growth factor 1 receptor (IGF1R) inhibitor, the mitogen-activated protein kinase 1 (MAPK1) inhibitor, the nitric oxide synthase 1 (NOS1) inhibitor, the glucocorticoid receptors (NR3C1) antagonist and the peptidylprolyl Isomerase A (PPIA) antagonist.
  • 30. The combination according to claim 29, wherein: the first active agent is the retinoic acid receptor alpha (RARα) agonist and the second active agent is the adrenergic receptor α2B (ADRA2B) antagonist;the first active agent is the voltage-gated potassium channel (KCNB2) inhibitor and the second active agent is the adrenergic receptor α2B (ADRA2B) antagonist; orthe first active agent is the retinoic acid receptor alpha (RARα) agonist and the second active agent is the voltage-gated potassium channel (KCNB2) inhibitor.
  • 31-32. (canceled)
  • 33. The combination according to claim 19, wherein the combination comprises a first active agent, a second active agent and a third active agent, wherein the first active agent, the second active agent and the third active agent are different from each other and are independently selected from the group consisting of the retinoic acid receptor alpha (RARα) agonist, the voltage-gated potassium channel (KCNB2) inhibitor, the adrenergic receptor α2B (ADRA2B) antagonist, the DNA methyltransferase 3 alpha (DNMT3A) antagonist, the insulin like growth factor 1 receptor (IGF1R) inhibitor, the mitogen-activated protein kinase 1 (MAPK1) inhibitor, the nitric oxide synthase 1 (NOS1) inhibitor, the glucocorticoid receptors (NR3C1) antagonist and the peptidylprolyl Isomerase A (PPIA) antagonist.
  • 34. The combination according to claim 33, wherein the first active agent is the retinoic acid receptor alpha (RARα) agonist, the second active agent is the voltage-gated potassium channel (KCNB2) inhibitor and the third active agent is the adrenergic receptor α2B (ADRA2B) antagonist.
  • 35. A pharmaceutical composition comprising the combination of claim 19 and a pharmaceutically acceptable carrier, wherein the combination is used for the treatment of amyotrophic lateral sclerosis.
  • 36. A kit comprising the combination of claim 19 and an instruction for use, wherein the instruction describes the use of the combination or the pharmaceutical composition for treating amyotrophic lateral sclerosis.
  • 37. The kit according to claim 36, wherein the two or more active agents are contained in the same or separate containers.
  • 38-69. (canceled)
Priority Claims (1)
Number Date Country Kind
PCT/CN2021/139736 Dec 2021 WO international
CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims priority to PCT/CN2021/139736 entitled “METHOD AND MEDICAMENT FOR TREATING AMYOTROPHIC LATERAL SCLEROSIS” filed on Dec. 20, 2021, which is incorporated herein by reference in its entirety.

PCT Information
Filing Document Filing Date Country Kind
PCT/CN2022/140288 12/20/2022 WO