Treatment for asd

Abstract

To provide a therapy for patients with autism spectrum disorder (ASD), targeting a subgroup of specific patients sharing a common etiology.SOLUTION: The present invention relates to a pharmaceutical composition comprising ibudilast and bumetanide for use in the treatment of autism spectrum disorder (ASD), where the composition is administered to a patient showing an overactivation of an NF-κB pathway.SELECTED DRAWING: None

Description

[Technical Field]

[0001] The present invention relates to the treatment of subgroups of ASD. [Background technology]

[0002] Autism spectrum disorders (ASDs) are a group of etiologically and clinically diverse neurodevelopmental disorders (NDDs). According to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria, a diagnosis of ASD is based on core behavioral symptoms, including social communication deficits and repetitive and restrictive behaviors. Based on recent estimates in the United States and Europe, between 1 in 36 and 1 in 89 children aged approximately 8 years have been diagnosed with ASD. Patients diagnosed with ASD, like many other NDDs, exhibit diverse clinical pathologies and genomic abnormalities, hindering the development of effective treatments for individuals with ASD at the population level. As a result, there remains a high unmet need for effective treatments for ASD.

[0003] Given the broad range of molecular etiologies underlying ASD, it is not surprising that there are currently no clinically established treatments that address its core symptoms. The currently FDA-approved medications for ASD (risperidone and aripiprazole) address specific behavioral characteristics, such as irritability, rather than core symptoms. Existing clinical trials target patients diagnosed based on behavioral assessments and often do not qualitatively consider core symptoms or other non-behavioral comorbidities. While some compounds, such as memantine and sulforaphane, have shown clear improvements in individual patients, they have failed to achieve a clearly positive response across patient populations. Therefore, given the clinical, genetic, and molecular heterogeneity observed in ASD, several recent studies, primarily relying on behavioral data, have aimed to characterize subtypes of the disorder within ASD.

[0004] Early studies in preadolescent individuals with autism spectrum disorder (ASD) investigated how morphometric features extracted from structural magnetic resonance imaging (MRI) and distances between standardized facial landmarks describing facial morphology differed among individuals with different cognitive and language abilities. Along these lines, a study by Libero and colleagues suggested the existence of a subgroup of patients with ASD characterized by increased head circumference in early childhood. In another study, behavioral data from 47 preteen children diagnosed with ASD and 58 age-matched typically developing (TD) children were analyzed to characterize potential cognitive subtypes within the ASD population. The authors assessed performance on a variety of tasks related to nonsocial information processing abilities, including spatial working memory, response inhibition, face recognition, and emotion. Using measures obtained from these tasks, they constructed a random forest model that suggested the existence of subgroups of individuals with small but significant differences in resting-state functional connectivity MRI across both the ASD and TD groups.

[0005] Other studies have used electronic medical records of patients older than 15 years to delineate potential systems-level clinical pathology across patients with ASD, beyond neurobehavioral criteria from the DSM. They used hierarchical clustering to group individuals with ASD based on the coexistence of medical comorbidities and identified various patient subgroups, primarily with epileptic seizures, gastrointestinal and auditory disorders, and psychiatric disorders (e.g., episodic mood disorder, bipolar disorder, depression, anxiety disorder, and conduct disorder). More recently, in addition to medical records, they have expanded their analysis using medical claims, familial whole-exome sequencing, and neurodevelopmental gene expression data to characterize mechanistically defined patient subgroups with various clinical, genetic, and transcriptomic features. The results of these studies suggest the existence of subgroups of ASD with distinct clinical and etiological differences driven by various genetic and environmental contributions.

[0006] Recently, various approaches based on bioinformatics and machine learning (ML) have been explored to address the challenges posed by clinical variability and genetic diversity in ASD. Among them, DEPI (R) (Databased Endophenotyping Patient Identification) is a systems biology, multi-omics, and ML-driven platform designed to identify biologically enriched subgroups of NDDs and corresponding potential personalized treatments. DEPI integrates information on risk factors for NDDs, including genetic variants, differential gene expression in large case-control studies, and comorbidities observed across patients with neurodevelopmental disorders, and uses this information to identify pathway-level perturbations associated with clinical pathology observed in patients with NDDs.

[0007] Therefore, such an approach can be used to identify subgroups of ASD patients and provide targeted treatments to these patient groups based on the underlying genetic and molecular disorders. Summary of the Invention [Problem to be solved by the invention]

[0008] Therefore, the desired technical problem is to provide treatments for patients with ASD that target specific patient subgroups that share a common etiology. [Means for solving the problem]

[0009] In one aspect, the present invention relates to a pharmaceutical composition comprising ibudilast and bumetanide for use in the treatment of autism spectrum disorder (ASD), wherein the composition is administered to a patient exhibiting hyperactivation of the NF-κB pathway.

[0010] In another aspect, the present invention relates to a kit comprising a dosage form comprising ibudilast and a dosage form comprising bumetanide for use in treating autism spectrum disorder (ASD), wherein the dosage forms are administered to a patient exhibiting hyperactivation of the NF-κB pathway.

[0011] In yet another aspect, the present invention relates to a method for treating ASD, wherein an effective amount of ibudilast and an effective amount of bumetanide are administered to a patient with ASD exhibiting overactivation of the NF-κB pathway. [Brief explanation of the drawings]

[0012] [Figure 1A] Figure 1A shows a PCA of gene expression profiles from ASD-Phen1 patients (n = 10) and ASD-non-Phen1 patients (n = 10), using statistically significant differentially expressed genes in ASD-Phen1 compared with ASD-non-Phen1. [Figure 1B] Figure 1B shows a PCA of gene expression profiles from ASD-Phen1 patients (n = 10) and ASD-non-Phen1 patients (n = 10), using the top 250 up- and down-expressed genes (sorted by Log2(FC)) in ASD-Phen1 compared to ASD-non-Phen1. DETAILED DESCRIPTION OF THE INVENTION

[0013] In one aspect, the present invention relates to a pharmaceutical composition comprising ibudilast and bumetanide for use in the treatment of autism spectrum disorder (ASD), wherein the composition is administered to a patient exhibiting hyperactivation of the NF-κB pathway.

[0014] In another aspect, the present invention relates to a kit comprising a dosage form comprising ibudilast and a dosage form comprising bumetanide for use in treating autism spectrum disorder (ASD), wherein the dosage forms are administered to a patient exhibiting hyperactivation of the NF-κB pathway.

[0015] In yet another aspect, the present invention relates to a method for treating ASD, wherein an effective amount of ibudilast and an effective amount of bumetanide are administered to a patient with ASD exhibiting overactivation of the NF-κB pathway.

[0016] The pharmaceutical compositions and kits of the present invention comprise ibudilast, an oral anti-inflammatory and neuroprotective agent that is metabolized primarily by the liver and has the chemical structure of Formula I: [ka]

[0017] Ibudilast is a phosphodiesterase (PDE) inhibitor, primarily inhibiting PDE4. Its clinical efficacy has been demonstrated for bronchial asthma and cerebrovascular disease. Ibudilast is currently undergoing clinical trials in the United States (codes: AV-411 or MN-166) for the treatment of progressive multiple sclerosis, as well as other diseases such as amyotrophic lateral sclerosis and drug addiction.

[0018] The dosage form of the pharmaceutical composition or kit of the present invention contains between 2.5 mg and 50 mg of ibudilast and is administered twice daily, so that the total daily dose of ibudilast in the treatment of the present invention is between 5 mg and 100 mg of ibudilast. These amounts are considered effective amounts. In a preferred embodiment, the dosage form of the pharmaceutical composition or kit contains 5 mg or 10 mg of ibudilast, so that ibudilast is preferably administered at a total daily dose of 10 mg or 20 mg.

[0019] The pharmaceutical compositions and kits of the present invention contain bumetanide, also known as 3-(butylamino)-4-phenoxy-5-sulfamoylbenzoic acid. Bumetanide is an inhibitor of NKCC1 and acts as a loop diuretic. Bumetanide is available under the trade names bumex and burinex. Its chemical structure is represented by Formula II below. [ka]

[0020] The dosage forms of the pharmaceutical compositions or kits of the present invention contain between 0.25 mg and 5 mg of bumetanide and are administered twice daily, resulting in a total daily dose of bumetanide of between 0.5 mg and 10 mg in the treatment of the present invention. These amounts are considered effective amounts. In a preferred embodiment, the dosage forms of the pharmaceutical compositions or kits contain 1 mg of bumetanide, so that bumetanide is preferably administered at a total daily dose of 2 mg.

[0021] In some embodiments, instead of bumetanide itself, the pharmaceutical composition or kit dosage form of the invention includes a bumetanide derivative, such as AqB007, AqB011, PF-2178, BUM13, BUM5, or bumepamine.

[0022] In a preferred embodiment, the treatment comprises administering ibudilast in a total daily dose of between 5 mg and 100 mg and bumetanide in a total daily dose of between 0.5 mg and 10 mg. In a particularly preferred embodiment, the treatment comprises administering ibudilast in a total daily dose of between 10 mg and 20 mg and bumetanide in a total daily dose of 2 mg.

[0023] The compositions and kits are for use in the treatment of ASD, ie, the treatment is administered to a patient exhibiting hyperactivation of the NF-κB pathway.

[0024] Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) is a transcription factor involved in cellular responses to stimuli such as stress, cytokines, free radicals, heavy metals, radiation, or bacterial or viral antigens. NF-κB regulates the expression of numerous genes important in the control of apoptosis, tumorigenesis, inflammation, and various autoimmune diseases. NF-κB contains homodimeric and heterodimeric protein complexes formed by the Rel-like domain-containing proteins RELA / p65, RELB, NFκB1 p105, NFκB1 p50 (an N-terminal processing product of precursor p105), REL, and NFκB2 p52, with the heterodimeric p65-p50 complex being the most abundant. NF-κB activation occurs via two major signaling pathways: i) the canonical pathway and ii) the non-canonical NF-κB signaling pathway. The canonical pathway mediates activation of NF-κB1 p50, RELA, and REL, resulting in rapid but transient NF-κB activation, whereas the noncanonical pathway of NF-κB selectively activates NF-κB components sequestered in p100, primarily NF-κB2 p52 and RELB, resulting in slower and sustained activation.

[0025] While not intending to be bound by any particular theory, consistent with its central role in the inflammatory response, NF-κB is thought to be involved in the pathogenesis of some ASD patients who exhibit high levels of inflammation. Following inflammation, proinflammatory cytokines, such as tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and bacterial lipopolysaccharide (LPS), activate NF-κB, leading to the transcription of genes involved in the development and progression of inflammation. Elevated serum concentrations of proinflammatory cytokines have previously been reported in some patients diagnosed with ASD. Therefore, hyperactivation of NF-κB is a useful marker for identifying a subset of ASD patients characterized by high levels of inflammation and therefore susceptible to treatment with ibudilast.

[0026] The overactivation of the NF-κB pathway can be detected by any means known in the art. In one embodiment, the overactivation is detected by detecting increased expression of at least 20 NF-κB-associated genes. As used herein, "NF-κB-associated genes (NF-κB-associated genes)" refers to the overactivation of NF-κB pathway. K The term "NF-κB-associated genes" is understood to refer to genes that are transcriptional target genes of NF-κB. The expression levels of NF-κB-associated genes can be measured by any means known in the art, for example, RNA-seq, rt-PCR.

[0027] Additionally, the NF-κB activation of ABCA1, ABCB1, ABCB4, ABC9, ABC6, ABCG5, and A.S BCG8, ADH1A, ADORA1, ADORA2A, AFP, AGER, AGT, AICDA, ALOX12, AMACR, AMH ANGPT1, APOBEC2, APOC3, APOD, APOE, AQP4, AR, ARFRP1, ART1, ASPH, ASS1, A TP1A2, B2M, BACE1, BAX, BCL2, BCL2A1, BCL2L1, BCL2L11, BCL3, BDKRB1, BDNF BLIMP1 / PRDM1, BLNK, BLR1, BMI1, BMP2, BMP4, BNIP3, BRCA2, BTK, C3, C4A. C4BPA, C69, CALCB, CASP4, CCL1, CCL15, CCL17, CCL19, CCL2, CCL20, CCL22, C.S CL23, CCL28, CCL3, CCL4, CCL5, CCND1, CCND2, CCR5, CCR7, CD209, CD274, CD 38 CD3G, CD40, CD40LG, CD44, CD48, CD54, CD80, CD83, CD86, CDK6, CDX1, CEB PD, CFB, CFLAR, CGM3, CHI3L1, CIDEA, COL1A2, CR2, CREB3, CRP, CSF1, CSF2 CSF3, CTSB, CXCL1, CXCL10, CXCL3, CXCL5, CXCL9, CYP19A1, CYP27B1, CYP2C 11. CYP2E1, CYP7B1, DEFB2, DIO2, DMP1, DNASE1L2, E2F3, EBI3, EDN1, EGFR. ELF3, ENG, EPHA1, EPO, ERBB2, ERVWE1, F3, F8, FABP6, FAM148A, FAS, FASLG, F CER2, FCGRT, FGF8, FN1, FSTL3, FTH1, G6PC, GADD45B, GATA3, GBP1, GCLC, GC LM, GNAI2, GNB2L1, GNRH2, GRM2, GRO-ータ, GRO-ガ、 GSTP1, GZMB, HAMP, HAS1 HBE1, HBZ, HIF1A, HLA-B, HLA-G, HMGN1, HMOX1, HOXA9, HSD11B2, HSP90AA1 IER3, IFNB1, IFNG, IGFBP2, IGHE, IGHG1, IGHG2, IGHG4, IGKC, Iigp1, IL10IL11、IL12A、IL12B、IL13、IL17、IL1A、IL1B、IL1RN、IL2、IL23A、IL27、IL2R A、IL6、IL8、IL8RA、IL8RB、IL9、INHBA、IRF1、IRF2、IRF4、IRF7、JMJD3、JUNB , KC, KCNK5, KCNN2, KISS1, KITLG, KLK3, KLRA1, KRT15, ​​KRT3, KRT5, KRT6B, LAMB2, LBP, LCN2, LEF1, LGALS3, LIPG, LTA, LTB, LYZ, MADCAM1, MBP, MDK, MMP1 、MMP3、MMP9、MTHFR、MUC2、MYB、MYC、MYLK、MYOZ1、NCAM、NFKB1、NFKB2、NFKB IA、NFKBIE、NFKBIZ、NGFB、NK4、NLRP2、NOD2、NOS1、NOS2A、NOX1、NPY1R、NQO1 、NR4A2、NRG1、NUAK2、OLR1、OPN1SW、OPRD1、OPRM1、ORM1、Osterix、OXTR、PA FAH2、PDGFB、PDYN、PENK、PGLYRP1、PGR、PI3KAP1、PIGF、pIgR、PIK3CA、PIM1、 PLA2、PLAU、PLCD1、PLK3、POMC、PPARGC1B、PRF1、PRKACA、PRKCD、PRL、PSMB9 、PSME1、PSME2、PTAFR、PTEN、PTGDS、PTGS2、PTHLH、PTPN1、PTX3、PYCARD、RAG 1、RAG2、RBBP4、REL、RELB、S100A4、S100A6、SAA1、SAA2、SAA3、SAT1、SCNN1A 、SDC4、SELE、SELP、SELS、SENP2、SERPINA1、SERPINA2、SERPINA3、SERPINB1、 SERPINE1、PAI-1、SERPINE2、SH3BGRL、SKALP、PI3、SKP2、SLC11A2、SLC16A1 、SLC3A2、SLC6A6、Slfn2、SNAI1、SOD1、SOD2、SOX9、SPI1、SPP1、ST6GAL1、ST8 SIA1、STAT5A、TACR1、TAP1、TAPBP、TCRB、TERT、TFEC、TFF3、TGM1、TGM2、TIC AM1、TLR2、TLR9、TNC、TNF、TNFAIP3、TNFRSF4、TNFRSF9、TNFSF10、TNFSF13B、The disease is determined by detecting increased expression of at least 20 genes selected from the group consisting of TNFSF15, TNIP1, TNIP3, TP53, TRAF1, TRAF2, TREM1, TRPC1, TWIST1, UPK1B, UPP1, VCAM1, VEGFC, VIM, WT1, XIAP, and YY1.

[0028] In a preferred embodiment, overactivation of the NF-κB pathway is determined by detecting increased expression of at least one gene selected from the group consisting of B2M, BCL2A1, BRCA2, C3, CD48, CFB, F8, FAS, GADD45B, IL1B, IL1RN, KRT5, LGALS3, LYZ, NFKBIZ, NRG1, PSMB9, PTEN, S100A6, SAA2, SAT1, SERPINB1, SH3BGRL, and TNIP3. In a particularly preferred embodiment, hyperactivation of the NF-κB pathway is detected by detecting increased expression of at least six genes selected from the group consisting of B2M, BCL2A1, BRCA2, C3, CD48, CFB, F8, FAS, GADD45B, IL1B, IL1RN, KRT5, LGALS3, LYZ, NFKBIZ, NRG1, PSMB9, PTEN, S100A6, SAA2, SAT1, SERPINB1, SH3BGRL and TNIP3.

[0029] Those skilled in the art know how to measure the expression level of a gene, including how to determine increased expression of a gene. As used herein, increased expression of a gene is detected when the expression level of the gene is at least one standard deviation higher than the average expression level in a control population.

[0030] In another embodiment, overactivation of the NF-κB pathway is determined by detecting increased levels of NF-κB protein in a patient sample. In a preferred embodiment, nuclear NF-κB protein levels are detected, since only nuclear NF-κB protein contributes to promoting the expression of relevant genes.

[0031] In a preferred embodiment, NF-κB protein levels are measured by immunoassay, preferably by enzyme-linked immunosorbent assay (ELISA). In one embodiment, the kit may be the TransAM NF-κB Family Kit (Cat. No. 43296, Active Motif, Inc.).

[0032] Overactivation of the NF-κB pathway is detected when the measured NF-κB protein level is at least one standard deviation higher than the mean protein level in a control population.

[0033] In a preferred embodiment, the patient exhibits overactivation of the NF-κB pathway and overactivation of the NRF2 pathway.

[0034] Nuclear factor erythroid 2-related factor 2 (NRF2), also known as nuclear factor erythroid-derived 2-like 2 (NFE2L2), is a master transcription factor regulator of antioxidant responses, particularly those triggered by injury and inflammation. Multiple interrelated cellular pathways, including the mammalian target of rapamycin (mTOR) pathway and the phosphoinositide 3-kinase-protein kinase B (PI3KAkt) pathway, share NRF2 as a central core node of convergence, both of which have been widely reported to be disrupted in some individuals with autism spectrum disorders (ASD) and neurodevelopmental disorders (NDD). Accordingly, dysregulation of NRF2-related molecular pathways has previously been reported in some patients with ASD who respond to treatment with ibudilast (EP3785733).

[0035] Hyperactivation of the NRF2 pathway can be detected by any means known in the art. In one embodiment, hyperactivation is detected by detecting increased expression of at least 10 NRF2-associated genes. As used herein, the term "NRF2-associated genes" is understood to refer to transcriptional target genes of NRF2. The expression levels of NRF2-associated genes can be measured by any means known in the art, such as RNA-seq and rt-PCR.

[0036] Additionally, the NRF2 promoter genes were ABCB6, ABCB9, ABCC5, ACCN1, ACO1, ACTR10, and AD AMTS12, ADO, AFG3L1P, AIFM2, AKIRIN2, ALOX12P2, ALPI, AMN1, ANKRD11, AN KRD30BL, ANO4, ARID3A, ARRDC3, ATXN1, ATXN3L, AZIN1, AZIN1, BCL2L11, BE ND6, BEND6, BMP10, BRD2, C21orf33, C6orf106, C9orf25, C9orf5, CAMK2D, CA ND1, CASC3, CCDC64, CD226, CD27, CD83, CDK17, CDK6, CEBPA, CHST11, CLIP4 CLLU1OS, CLTC, CMPK1, COL24A1, CPEB2, CPEB3, CREBZF, CWC27, DAD1, DCUN 1D4, DENND4C, DGCR6L, DNAJA2, DST, DSTNP2, DUSP2, DUSP5, EHMT1, EIF4G3. ELN, EPB41, ERC2, EXOC7, FAM157A, FAM76B, FASTKD2, FECH, FLNB, FSD1L, FTH 1, FTL, GABBR2, GATS, GCLC, GCLM, GCNT3, GDF15, GPI, GPNMB, GRM8, GSR, GST M5, GSTP1, HBB, HBE1, HERC1, HGD, HIF1A, HIST1H4H, HMOX1, HMOX1, HRASLS2 HTATIP2, HTRA3, IFRD1, IFT74, IGF2R, IPO7, IRF2, IRF2BPL, KCNN3, KEAP1 KIAA1522, KIFC3, LBR, LINC00273, LINC00299, LOC100130451, LOC1001328 91. LOC100507557, LOC147646, LOC284661, LOC284801, LOC338758, LOC338 799 LOC440461 LOC643723 LOC646329 LRP8 LRRC8D LY9 MAFG MAFG MAP RE3, MAPT, ME1, MESDC1, MFSD11, MIAT, MIR365A, MIR617, MKLN1, MOV10L1, M PPE1, MSL3, MTF2, MYC, NES, NEUROD4, NFE2L2, NKAIN1, NPLOC4, NQO1, NUMBL.NUP153, OR2AT4, P2RY10, PARN, PDCD1LG2, PDCD6IP, PEX5L, PGRMC2, PIP5K1C, PIR, PLA2G6, PMAIP1, P MAIP1, PMF1, PPARGC1B, PPIF, PRDM1, PRDX1, PRKACB, PRKCB, PSMA3, PTGES3, PVRL1, PVT1, RAB10, RAB3 5, RASAL3, RASSF6, RCAN1, RFFL, RNF213, RNF220, ROCK1, RSPH6A, RXRA, SAR1B, SEC61B, SEMA7A, SEMA 7A, SETBP1, SH2D6, SLAMF7, SLC14A2, SLC25A25, SLC3A2, SLC48A1, SLC7A11, SLC9A7P1, SLCO5A1, SORB The method is determined by detecting the overexpression of at least 10 NRF2-related genes selected from the group consisting of S2, SPRY3, SQSTM1, SQSTM1, SQSTM1, SRXN1, SSH1, ST6GALNAC1, STARD13, STXBP4, SUMO1P1, TANK, TBL1X, TBXAS1, TCL6, TEC, TEC, TFE3, THBS1, TKT, TMEM121, TMTC3, TNFRSF1A, TNFRSF8, TNFSF14, TRIM56, TSC22D1, TXN, TXNRD1, TXNRD1, UBC, UBE2E2, UNKL, VCP, VEZF1, VTRNA1-1, WDR81, WIPI2, YWHAG, ZFAT, ZMYND8, ZNF148, ZNF3, ZNF469 and ZNF673.

[0037] In a preferred embodiment, hyperactivation of the NRF2 pathway is detected by detecting increased expression of at least one gene selected from the group consisting of ACTR10, AZIN1, CPEB3, FECH, HBB, MSL3, NFE2L2, PMAIP1, PSMA3, PTGES3, SLC9A7P1 and TANK.

[0038] In another embodiment, hyperactivation of the NRF2 pathway is determined by detecting increased levels of NRF2 protein in a patient sample. In a preferred embodiment, nuclear NRF2 protein levels are detected, since only nuclear NRF2 protein contributes to promoting the expression of related genes.

[0039] In a preferred embodiment, NRF2 protein levels are measured by immunoassay, preferably by enzyme-linked immunosorbent assay (ELISA). In one embodiment, the kit may be a human nuclear factor erythroid 2-related factor 2 (NFE2L2) ELISA kit (catalog number CSB-EL015752HU, Cusabio, TX) or a human NRF2 ELISA kit (catalog number EH348RB, Invitrogen, CA).

[0040] Overactivation of the NRF2 pathway is detected when the measured NRF2 protein level is at least one standard deviation higher than the mean protein level in a control population.

[0041] According to the present invention, gene expression levels or protein levels can be measured in any suitable sample. In a preferred embodiment, the sample is a blood sample, a plasma sample, a peripheral blood mononuclear cell sample, a saliva sample, or a urine sample. The sample may be processed or purified before use according to the present invention. In a preferred embodiment, the sample is a peripheral blood mononuclear cell sample. [Example]

[0042] Example 1: Differential gene expression analysis

[0043] RNA-seq analysis was performed on blood samples collected from 20 patients with ASD, including: i) 10 patients classified as ASD phenotype 1 (ASD-Phen1) (positive for two key criteria: enlarged head circumference (above the 75th percentile) within the first 2 years of life and systematic aggravation of ASD behavioral symptoms during immune-induced episodes such as fever and infectious events (e.g., acute inflammation)) and therefore expected to respond to a pharmaceutical composition containing ibudilast and bumetanide; and ii) 10 age-matched participants not classified as ASD-Phen1 (also known as ASD-non-Phen1) and therefore expected not to respond to such a pharmaceutical composition. Each participant received a separate PAXGene (R) Two tubes containing 2.5 ml of whole blood in RNA tubes were sent to Omega Bioservices in Georgia, USA, for sequencing. RNA extraction was performed using the QIAGEN PAXgene Blood RNA Kit / Mag-Bind. (R) The PX Blood RNA 96 Kit was used, and ERCC Ex-fold RNA Reagent (Cat. No. 4456739) was added to each sample. rRNA and hgbRNA depletion and RNA-seq library generation were performed using the Illumina TruSeq Stranded Total RNA with Ribo-Zero Globin kit. Samples were then sequenced using an Illumina NovaSeq 6000 sequencer, containing 2 × 150 bp constructs.

[0044] Two blood samples from each patient were sequenced in two different batches, considered technical replicates. To ensure there were no batch effects between samples, a quality control procedure was applied by performing principal component analysis (PCA) using the prcomp function in R (Statistical Package).

[0045] Next, differential gene expression analysis between ASD-Phen1 and ASD-non-Phen1 was performed to reveal a transcriptome signature specific to ASD-Phen1. For differential gene expression analysis, the DESeq2 package in R was used, with the CollapseReplicates option following recommended settings for performing multiple sequencing runs from the same amount of extracted RNA, increasing statistical power without introducing confounding batch effects. After differential expression analysis, two PCA plots were created to assess the power of differentially expressed genes to distinguish ASD-Phen1 from ASD-non-Phen1 individuals. One plot used differentially expressed genes with an adjusted p-value <0.05 (using the Benjamini and Hochberg correction method), and the second plot used the top 250 up- and down-regulated genes (sorted by Log2(FC)). This was performed by considering only genes with an average expression level greater than 10 reads across all samples (Figure 1A and Figure 1B). The first two PCA coordinates were then used as features to train a logistic regression model to classify two phenotypes using their transcriptome profiles. These models were validated using a leave-one-out strategy, in which one sample in each iteration was classified using the other samples as the training set. Performance was calculated as the number of correctly classified samples in the entire dataset. To validate the procedure, we performed a permutation test over 1,000 iterations, in which the phenotypes in each iteration were randomly shuffled, and the classification scores were calculated to obtain their null distribution. This permutation test, using leave-one-out cross-validation, confirmed that the observed stratification was significant compared to the null distribution (p = 0.01).

[0046] Example 2: Gene set enrichment analysis

[0047] EnrichR, a comprehensive gene set enrichment analysis web server, was used to examine pathway enrichment of differentially expressed genes (adjusted p-values ​​<0.05) in ASD-Phen1 versus ASD-non-Phen1. Gene sets and pathways from the MsigDB Hallmark 2020, KEGG 2021 Human, Reactome 2022, and WikiPathway 2021 Human databases were used in this analysis. Results showed statistically significant enrichment of differentially expressed genes (adjusted p-values ​​<0.05) in pathways related to NF-κB activation and downstream pro-inflammatory cascades (Table 1), including the NF-κB-associated gene BCL2A1 (log2FC = 1.41, p-value = 2.2E-05, adjusted p-value = 0.043).

[0048] [Table 1]

[0049] Gene set enrichment analysis (GSEA) was also performed on differentially expressed genes in ASD-Phen1 versus ASD-non-Phen1 to verify consistency, including enrichment of NF-κB-related pathways across ASD-Phen1. The fgsea package v1.10.1 in R was used to perform this analysis. A total of 15,497 gene ontologies (GO) and canonical pathways (CP) provided by the human MSigDB version 7.0 (https: / / data.broadinstitute.org / gsea-msigdb / msigdb / release / 7.0 / ) were considered in this analysis. Fisher exact test was used and confirmed that among pathways enriched for differentially expressed genes in ASD-Phen1 patients (Benjamini·Hochberg adjusted p-value < 0.05), NF-κB-related pathways (i.e., those involving NF-κB) were significantly over-represented (p-value = 7E-15, 95% confidence interval = 2.41 to 4.17, odds ratio = 3.19).

[0050] Next, the association between the ASD-Phen1-specific disease transcriptome signature and hyperactivation of NF-κB and NRF2 transcription factors was assessed by evaluating the enrichment of high-confidence targets of NF-κB and NRF2 (based on a two-sided Kolmogorov-Smirnov test) among the top 250 genes with the highest up- or down-regulation (i.e., Log2(FC)) when comparing gene expression between ASD-Phen1 and ASD-non-Phen1 patients. The ks.test function in R (Statistics Package) was used to calculate the enrichment score (ES) and associated significance (two-sided test). Positive or negative ES values ​​suggest that NF-κB / NRF2 gene targets tend to be up- or down-regulated in the transcriptome signature. Target genes of both NF-κB and NRF2 were found to be significantly enriched in the upregulated genes in the ASD-Phen1 group (NF-κB: ES=0.24, p-value=<1E-9) (NRF2: ES=0.21, p-value=5.6E-9).

[0051] A total of 24 NF-κB transcriptional target genes (specifically, B2M, BCL2A1, BRCA2, C3, CD48, CFB, F8, FAS, GADD45B, IL1B, IL1RN, KRT5, LGALS3, LYZ, NFKBIZ, NRG1, PSMB9, PTEN, S100A6, SAA2, SAT1, SERPINB1, SH3BGRL, and TNIP3) were identified as differentially upregulated genes in ASD-Phen1 (p-value < 0.05). Through several power calculations, we estimated that identifying only 20 of the NF-κB transcriptional target genes as differentially upregulated (p-value < 0.05) in ASD-Phen1 would be sufficient to reach statistical significance (p-value < 0.05) in the enrichment analysis. Furthermore, a total of six genes (specifically, BCL2A1, TNIP3, NRG1, C3, IL1RN, and KRT5) were found to be among the top 250 genes with the highest increased expression in ASD-Phen1 patients.

[0052] A total of 12 NRF2 transcriptional target genes (specifically, ACTR10, AZIN1, CPEB3, FECH, HBB, MSL3, NFE2L2, PMAIP1, PSMA3, PTGES3, SLC9A7P1, and TANK) were identified as differentially upregulated genes in ASD-Phen1 (p-value < 0.05). By performing several power calculations, we estimated that only 10 of the NRF2 transcriptional target genes needed to be identified as differentially upregulated (p-value < 0.05) in ASD-Phen1 to reach statistical significance in the enrichment analysis. Furthermore, the HBB gene was identified as being among the top 250 most upregulated genes in ASD-Phen1 patients.

[0053] Example 3: STP1 as a suitable drug candidate to revert the overactivation of NF-κB and NRF2 in ASD-Phen1

[0054] STP1 was obtained by mixing bumetanide and ibudilast at similar dilutions in DMSO solution to a final ratio of 1:1 between the two compounds. Commercially available NPC cell lines (ATCC ACS-5004) and MCF-7 cell lines (ATCC HTB-22) were cultured in accordance with ATCC LGC Standards. (R)The cells were purchased from a provider. Next, a transcriptional signature of STP1 was obtained by treating commercially available NPC and MCF-7 cell lines with either 5 μM STP1 or vehicle (DMSO) control for 6 and 24 hours. Furthermore, LCLs derived from two ASD-Phen1 patients were treated with 5 μM STP1 or DMSO for 48 hours. Each cell line was cultured according to the provider's guidelines until sufficient cell numbers were reached and seeded for treatment with STP1 or DMSO. All treatments were performed in triplicates, with 50,000 cells seeded per well for two time points. RNA was extracted from each well, yielding a total of 36 samples for library construction and sequencing. Total RNA was quantified using a Qubit fluorometric assay (Thermo Fisher Scientific). Libraries were generated from 125 ng of total RNA and sequenced on a NovaSeq 6000 sequencer in single-end mode with a 75-bp read length and 4M reads per sample. Bioinformatics analysis consisted of quality filtering, trimming, and alignment to the reference genome to generate raw data. This raw expression data was finally normalized to each cell line and analyzed. A final list of differentially expressed genes was obtained across cell lines in response to STP1 and DSMO treatment. A weighted average merging method, taking into account Spearman correlation coefficients across individual treatments in each cell type, was applied to combine the individual treatments across cell lines to generate a drug-induced transcriptomic response to STP1. Finally, three distinct transcriptional signatures were obtained: i) STP1 treatment vs. DMSO treatment in MCF-7 and NPC, ii) STP1 treatment vs. DMSO treatment in LCLs from the first patient, and iii) STP1 treatment vs. DMSO treatment in LCLs from the second patient.

[0055] Next, the Kolmogorov-Smirnov test was used to evaluate the effect of STP1 on the activity of NF-κB and NRF2 transcription factors, as measured by the expression levels of their transcriptional target genes in STP1-treated and untreated cell lines. In all three cases, NF-κB and NRF2 target genes were found to be significantly enriched relative to genes downregulated by STP1 (Table 2).

[0056] [Table 2]

Claims

1. A pharmaceutical composition comprising ibudilast and bumetanide for use in the treatment of autism spectrum disorder (ASD), wherein the composition is administered to a patient exhibiting hyperactivation of the NF-κB pathway.

2. 1. A kit comprising a dosage form comprising ibudilast and a dosage form comprising bumetanide for use in the treatment of autism spectrum disorder (ASD), wherein the dosage forms are administered to a patient exhibiting hyperactivation of the NF-κB pathway.

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4. 3. The composition for use according to claim 1 or the kit for use according to claim 2, wherein the overactivation of the NF-κB pathway is determined by detecting increased expression of at least one, preferably at least six, NF-κB-related genes selected from the group consisting of B2M, BCL2A1, BRCA2, C3, CD48, CFB, F8, FAS, GADD45B, IL1B, IL1RN, KRT5, LGALS3, LYZ, NFKBIZ, NRG1, PSMB9, PTEN, S100A6, SAA2, SAT1, SERPINB1, SH3BGRL and TNIP3.

5. The composition for use of claim 1 or the kit for use of claim 2, wherein the overactivation of the NF-κB pathway is determined by detecting an increase in NF-κB protein levels in a patient sample.

6. The composition or kit for use according to claim 5, wherein the NF-κB protein level is measured in the cell nucleus.

7. The composition or kit for use according to claim 5 or 6, wherein the NF-κB protein level is measured by immunoassay, preferably by ELISA.

8. The composition or kit for use described in any one of claims 1 to 7, wherein the composition is administered to a patient exhibiting overactivation of the NF-κB pathway and overactivation of the NRF2 pathway.

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10. The overactivation of the NRF2 pathway is determined by detecting overexpression of at least one NRF2-related gene from the group consisting of ACTR10, AZIN1, CPEB3, FECH, HBB, MSL3, NFE2L2, PMAIP1, PSMA3, PTGES3, SLC9A7P1 and TANK. A composition or kit for use as claimed in claim 8.

11. 9. The composition or kit for use of claim 8, wherein the overactivation of the NRF2 pathway is determined by detecting an increase in NRF2 protein levels in the patient sample.

12. 12. The composition or kit for use according to claim 11, wherein the NRF2 protein level is measured in the cell nucleus.

13. 13. A composition or kit for use according to claim 11 or claim 12, wherein the NRF2 protein level is measured by immunoassay, preferably by ELISA.

14. 14. The composition or kit for use according to any one of claims 1 to 13, wherein the sample is a blood sample, a plasma sample, a peripheral blood mononuclear cell sample, a saliva sample or a urine sample.

15. 15. A composition or kit for use according to any one of claims 1 to 14, wherein the treatment comprises administration of ibudilast in a total dose of between 5 mg and 100 mg per day and bumetanide in a total dose of between 0.5 mg and 10 mg per day.

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