Treatment of ASD

Abstract

The invention relates to a pharmaceutical composition comprising ibudilast and bumetanide for use in the treatment of autism spectrum disorders (ASD), the composition being administered to a patient having overactivation of an NF-κB pathway. Figure for abstract: Fig. 1

Description

Title of the invention: Treatment of ASD Field of invention

[0001] The invention relates to treatments for ASD subgroups.

[0002] Context

[0003] Autism spectrum disorders (ASD) are an etiologically and clinically heterogeneous group of neurodevelopmental disorders (NDDs). According to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria, the diagnosis of ASD is based on core behavioral symptoms such as impaired social communication and repetitive and restrictive behaviors. According to recent estimates in the United States and Europe, one in 36 to 89 children aged approximately 8 years is diagnosed with ASD. Patients diagnosed with ASD, like many other NDDs, have a variety of clinical manifestations and genomic alterations, which hinders the development of effective population-level treatments for individuals with ASD. Therefore, there remains a significant unmet need for effective treatments for ASD.

[0004] Given the broad spectrum of molecular etiologies underlying patients diagnosed with ASD, it is not surprising that no clinically proven treatments to treat the core symptoms of ASD exist to date. The drug treatments currently approved by the FDA for use in ASD—risperidone and aripiprazole—treat certain behavioral features such as irritability rather than the core symptoms. Existing clinical trials target patients diagnosed based on behavioral assessments, often without qualitatively considering core symptoms or other nonbehavioral comorbidities. Several compounds, such as memantine and sulforaphane, although showing marked improvement in some patients, fail to achieve a clear positive response in the overall patient population.Given the clinical, genetic and molecular heterogeneity observed in ASD, several recent studies have therefore aimed to characterize disease subtypes in ASD, although relying mainly on behavioral data.

[0005] Previous studies on prepubertal individuals with ASD have investigated how morphometric features extracted from structural magnetic resonance imaging (MRI) and distances between standardized facial landmarks describing facial morphology vary across individuals with distinct cognitive and linguistic skills. In this light, a study conducted by Libero and colleagues suggested the existence of a subgroup of patients with ASD characterized by an enlarged head circumference in early childhood. In another study, behavioral data from 47 preadolescent children diagnosed with ASD and 58 age-matched children with typical development (TD) were analyzed to characterize potential cognitive subtypes within the ASD population. The authors assessed performance on various tasks related to nonsocial information processing skills, including spatial working memory, response inhibition, face recognition, and affect.Using the measures obtained from these tasks, they developed a random tree model and suggested the existence of subgroups of individuals within the ASD and TD groups with small but significant differences in resting-state functional connectivity MRIs.

[0006] Other studies have used electronic medical records of patients older than 15 years to delineate potential systems-level clinical manifestations in patients with ASD beyond DSM neurobehavioral criteria. They grouped individuals with ASD based on the co-occurrence of medical comorbidities using hierarchical clustering, identifying various subgroups of patients who primarily present with seizures, gastrointestinal and auditory disorders, and psychiatric disorders such as episodic mood disorders, bipolar disorders, depression, anxiety, and behavioral disorders.More recently, in addition to medical records, they expanded their analysis by using data from healthcare claims, familial whole-exome sequencing, and neurodevelopmental gene expression to characterize a mechanistically defined subgroup of patients with different clinical, genetic, and transcriptomic features. The results of these studies suggest the existence of ASD subgroups with distinct clinical and etiological differences due to different genetic and environmental contributions.

[0007] Recently, various bioinformatics and machine learning (ML) based approaches have been explored to address the challenges posed by clinical variability and genetic heterogeneity of ASD. Among these, DEPI® (Databased Endophenotyping Patient Identification) is a systems biology, multi-omics, and machine learning-based platform designed for the identification of biologically enriched subgroups of patients with ASD and potential corresponding personalized treatments. The DEPI platform integrates information on ASD risk factors, including genetic variants, differentially expressed genes in large-scale case-control studies, and comorbidities observed in patients with neurodevelopmental disorders, and uses this information to identify pathway disturbances associated with clinical manifestations observed in patients with NDD.

[0008] Such an approach could therefore be used to identify subgroups of patients with ASD and provide targeted treatments for these patient groups based on the underlying genetic and molecular disorders.

[0009] Objective technical problem

[0010] The objective technical problem is therefore the provision of treatments for patients with ASD that target specific subgroups of patients sharing a common etiology. Summary of the invention

[0011] In one aspect, the invention relates to a pharmaceutical composition comprising ibudilast and bumetanide for use in the treatment of autism spectrum disorders (ASD), the composition being administered to a patient having overactivation of an NF-kB pathway.

[0012] In another aspect, the invention relates to a kit comprising a dosage form comprising ibudilast and a dosage form comprising bumetanide for use in the treatment of autism spectrum disorders (ASD), the dosage forms being administered to a patient having overactivation of an NF-kB pathway.

[0013] In yet another aspect, the invention relates to a method of treating ASD, wherein an effective amount of ibudilast and an effective amount of bumetanide are administered to an ASD patient exhibiting overactivation of an NF-kB pathway. Brief description of the figures

[0014] [Fig.l] shows the PCA of gene expression profiles of ASD-Phenl (n = 10) and ASD-non-Phenl (n = 10) patients using A) statistically significantly differentially expressed genes and B) the 250 most up- and down-regulated genes (sorted by Log2(FC)) in ASD-Phenl versus ASD-non-Phenl. Detailed description

[0015] In one aspect, the invention relates to a pharmaceutical composition comprising ibudilast and bumetanide for use in the treatment of autism spectrum disorders (ASD), the composition being administered to a patient having overactivation of an NF-kB pathway.

[0016] In another aspect, the invention relates to a kit comprising a dosage form comprising ibudilast and a dosage form comprising bumetanide for use in the treatment of autism spectrum disorders (ASD), dosage forms being administered to a patient with overactivation of an NF-kB pathway.

[0017] In yet another aspect, the invention relates to a method of treating ASD, wherein an effective amount of ibudilast and an effective amount of bumetanide are administered to an ASD patient exhibiting overactivation of an NF-kB pathway.

[0018] The pharmaceutical composition and kit according to the invention comprise ibudilast. Ibudilast is an oral anti-inflammatory and neuroprotective agent, metabolized mainly by the liver, having the following chemical structure of Formula I

[0019] Ibudilast is a phosphodiesterase (PDE) inhibitor, primarily inhibiting PDE4. The clinical efficacy of ibudilast has been proven in bronchial asthma and cerebrovascular disorders. Ibudilast is currently undergoing clinical trials in the United States for the treatment of progressive multiple sclerosis and other conditions such as amyotrophic lateral sclerosis and substance dependence (codes: AV-411 or MN-166).

[0020] The pharmaceutical composition or dosage form of the kit according to the invention comprises between 2.5 mg and 50 mg of ibudilast and are administered twice daily, such that the total daily dose of ibudilast in the treatment according to the invention is between 5 and 100 mg of ibudilast. These amounts are considered effective amounts. In preferred embodiments, the pharmaceutical composition or dosage form of the kit comprises 5 or 10 mg of ibudilast, such that ibudilast is preferably administered at a total daily dose of 10 or 20 mg.

[0021] The pharmaceutical composition and kit according to the invention comprise bumetanide, also known as 3-(butylamino)-4-phenoxy-5-sulfamoylbenzoic acid. Bumetanide is an NKCC1 inhibitor and acts as a loop diuretic. It is available under the trade names bumex and burinex, among others. Its chemical structure is represented below by Formula II

[0022] The pharmaceutical composition or dosage form of the kit according to the invention comprises between 0.25 mg and 5 mg of bumetanide and are administered twice daily, such that the total daily dose of bumetanide in the treatment according to the invention is between 0.5 and 10 mg of bumetanide. These amounts are considered effective amounts. In preferred embodiments, the pharmaceutical composition or dosage form of the kit comprises 1 mg of bumetanide, such that bumetanide is preferably administered at a total daily dose of 2 mg.

[0023] In some embodiments, instead of bumetanide itself, the pharmaceutical composition or dosage form of the kit according to the invention comprises bumetanide derivatives, such as AqB007, AqBOll, PF-2178, BUM13, BUM5 or bumepamine.

[0024] In a preferred embodiment, the treatment comprises administering a total daily dose of between 5 mg and 100 mg of ibudilast and a total daily dose of between 0.5 and 10 mg of bumetanide. In a particularly preferred embodiment, the treatment comprises administering a total daily dose of between 10 mg and 20 mg of ibudilast and a total daily dose of 2 mg of bumetanide.

[0025] The compositions and kits are for use in the treatment of ASD, wherein the treatment, i.e., the composition and dosage forms of the kit, is administered to a patient exhibiting overactivation of an NF-kB pathway.

[0026] Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kB) is a transcription factor involved in cellular responses to stimuli such as stress, cytokines, free radicals, heavy metals, irradiation, or bacterial or viral antigens. NF-kB regulates the expression of a large number of genes essential for the regulation of apoptosis, tumorigenesis, inflammation, and various autoimmune diseases. NF-kB comprises a homo- or heterodimeric protein complex formed by the Rel-like domain-containing proteins RELA / p65, RELB, NFKB1 p105, NFKB1 p50 (the N-terminal processed product of the precursor p105), REL, and NFKB2 p52, the heterodimeric p65-p50 complex being the most abundant. NF-kB activation occurs via two main signaling pathways: i) the canonical pathway; and ii) non-canonical NF-kB signaling pathways. The canonical pathway mediates the activation of NF-kB 1 p50, RELA, and REL, and leads to rapid but transient activation of NF-kB, whereas the non-canonical NF-kB pathway selectively activates NF-kB members sequestered by p100, primarily NF-kB2 p52 and RELB, and is characteristically slow and persistent.

[0027] Without wishing to be bound by any theory, it would appear that, consistent with its central role in the inflammatory response, NF-kB is involved in the etiology of the disorder in some ASD patients with high levels of inflammation. Following inflammation, pro-inflammatory cytokines such as tumor necrosis factor (TNF)a, interleukin (IL)-1 [3 and bacterial lipopolysaccharide (LPS) activate NF-kB, leading to the transcription of genes involved in the development and progression of inflammation. Elevated serum levels of pro-inflammatory cytokines have previously been reported in some patients diagnosed with ASD. NF-kB overactivation is therefore a useful marker to identify a subset of ASD patients characterized by high levels of inflammation and thus responsive to ibudilast treatment.

[0028] Overactivation of an NF-kB pathway may be detected by any means known in the art. In one embodiment, overactivation is detected by detecting upregulation of the expression of at least twenty NF-kB-associated genes. The term "NF-kB-associated genes" is herein understood to mean genes that are transcriptional target genes of NF-kB. The expression level of NF-kB-associated genes may be measured by any means known in the art, e.g., RNA-seq, rt-PCR.

[0029] In one embodiment, overactivation of an NF-kB pathway is determined by detecting the positive regulation of at least 20 genes selected from the group including ABCA1, ABCB1, ABCB4, ABCB9, ABCC6, ABCAG, ABCAG, ADOI, ABCA, ADOG, 8 ADORA2A, AFP, AGER, AGT, AICDA, ALOX12, AMACR, AMH, ANGPT1, APOBEC2, APOC3, APOD, APOE, AQP4, AR, ARFRP1, ART1, ASPH, ASS1, ATP1A2, B2M, BACE1, BA, BCL21, BCL21, BCL21, BCL22 BCL2L11, BCL3, BDKRB1, BDNF, BLIMP1 / PRDM1, BLNK, BLR1, BMI1, BMP2, BMP4, BNIP3, BRCA2, BTK, C3, C4A, C4BPA, C69, CALCB, CASP4, CCL1, CCL15, CCL17, CCL17, CCL, CCL1 CCL22, CCL23, CCL28, CCL3, CCL4, CCL5, CCND1, CCND2, CCR5, CCR7, CD209, CD274, CD38, CD3G, CD40, CD40LG, CD44, CD48, CD54, CD80, CD83, CD86, CD44, CD48, CD54, CD80, CD83, CD86, CDKAR, CEB, CD6, CCB CGM3, CHI3L1, CIDEA, COL1A2, CR2, CREB3, CRP, CSF1, CSF2, CSF3, CTSB, CXCL1, CXCL10, CXCL3, CXCL5, CXCL9, CYP19A1, CYP27B1, CYP2C11, CYP21, CYP21, DYP21, DYP7B DIO2, DMP1, DNASE1L2, E2F3, EBI3, EDN1, EGFR, <h2 style=";text-align:left;direction:ltr">ELF3, ENG, EPHA1, EPO, ERBB2, ERVWE1, F3, F8, FABP6, FAM148A, FAS, FASLG, FCER2, FCGRT, FGF8, FN1, FSTL3, FTH1, G6PC, GADD45B, GATA3, GBP1, GCLC, GCLM, GNAI2, GNB2L1, GNRH2, GRM2, GRO-bêta, GRO-gamma, GSTP1, GZMB, HAMP, HAS1, HBE1, HBZ, HIF1A, HLA-B, HLA-G, HMGN1, HM0X1, H0XA9, HSD11B2, HSP90AA1, IER3, IFNB1, IFNG, IGFBP2, IGHE, IGHG1, IGHG2, IGHG4, IGKC, ligpl, IL10, IL11, IL12A, IL12B, IL13, IL17, ILIA, IL1B, IL1RN, IL2, IL23A, IL27, IL2RA, 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, MMPI, MMP3, MMP9, MTHFR, MUC2, MYB, MYC, MYLK, MY0Z1, NCAM, NFKB1, NFKB2, NFKBIA, NFKBIE, NFKBIZ, NGFB, NK4, NLRP2, NOD2, NOS1, NOS2A, NOX1, NPY1R, NQO1, NR4A2, NRG1, NUAK2, OLR1, OPN1SW, OPRD1, OPRM1, 0RM1, Osterix, OXTR, PAFAH2, PDGFB, PDYN, PENK, PGLYRP1, PGR, PI3KAP1, PIGF, plgR, PIK3CA, PIM1, PLA2, PLAU, PLCD1, PLK3, POMC,PPARGC1B, PRF1, PRKACA, PRKCD, PRL, PSMB9, PSME1, PSME2, PTAFR, PTEN, PTGDS, PTGS2, PTHLH, PTPN1, PTX3, PYCARD, RAG1, RAG2, RBBP4, REL, RELB, S100A4, S100A6, SAA1, SAA2, SAA3, SAT1, SCNN1A, SDC4, SELE, SELP, SELS, SENP2, SERPINA1, SERPINA2, SERPINA3, SERPINB1, SERPINE1, PALI, SERPINE2, SH3BGRL, SKALP, PI3, SKP2, SLC11A2, SLC16A1, SLC3A2, SLC6A6, Slfn2, SNAI1, SOD1, SOD2, SOX9, SPI1, SPP1, ST6GAL1, ST8SIA1, STAT5A, TACR1, TAPI, TAPBP, TCRB, TERT, TFEC, TFF3, TGM1, TGM2, TICAM1, TLR2, TLR9, TNC, TNF, TNFAIP3, TNFRSF4, TNFRSF9, TNFSF10, TNFSF13B, TNFSF15, TNIP1, TNIP3, TP53, TRAF1, TRAF2, TREM1, TRPC1, TWIST1, UPK1B, UPP1, VCAM1, VEGFC, VIM, WT1, XIAP et YYL ,

[0030] In a preferred embodiment, overactivation of an NF-kB pathway is determined by detecting the upregulation 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, overactivation of an NF-kB pathway is determined by detecting the upregulation 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.

[0031] A person skilled in the art knows how to determine the level of expression of a gene, including positive regulation of gene expression. Positive regulation of expression of a gene is detected here if the expression level of a gene is greater than at least one standard deviation of the average expression in a control population.

[0032] In another embodiment, overactivation of the NF-kB pathway is determined by detecting an increased level of NF-kB protein in a patient sample. In a preferred embodiment, the level of nuclear NF-kB protein is detected since only nuclear NF-kB will contribute to promoting the expression of associated genes.

[0033] In a preferred embodiment, the NF-κB protein level is measured by an immunoassay, preferably by an enzyme-linked immunosorbent assay (ELISA). In one embodiment, the kit may be the TransAM NF-κB Family Kit (catalog number 43296, Active Motif, Inc.).

[0034] Overactivation of an NF-kB pathway is detected when the measured NF-kB protein level is at least one standard deviation higher than the mean protein level in a control population.

[0035] In a preferred embodiment, the patient has overactivation of an NF-kB pathway and overactivation of an NRF2 pathway.

[0036] Nuclear factor erythroid 2-related factor 2 (NRF2), also known as nuclear factor erythroid 2-like 2-derived nuclear factor, encoded by the NFE2L2 gene, is a master transcription factor that regulates antioxidant responses triggered, among others, by injury and inflammation. Several interdependent cellular pathways share NRF2 as a central node of convergence, including the mammalian target of rapamycin (mTOR) pathway and the phosphoinositide 3-kinase-protein kinase B (PI3KAkt) pathway, both of which have been widely described to be disrupted in some patients with autism spectrum disorders (ASD) and neurodevelopmental disorders (NDD). Accordingly, dysregulation of NRF2-related molecular pathways has already been reported in some patients with ASD who respond to ibudilast treatment (EP 3,785,733).

[0037] Overactivation of an NRF2 pathway may be detected by any means known in the art. In one embodiment, overactivation is detected by detecting upregulation of the expression of at least 10 NRF2-associated genes. The term "NRF2-associated genes" is herein understood to mean genes that are transcriptional target genes of NRF2. The expression level of NRF2-associated genes may be measured by any means known in the art, e.g., RNA-seq, rt-PCR.

[0038] In one embodiment, overactivation of an NRF2 pathway is determined by detecting overexpression of at least 10 NRF2-associated genes selected from the group comprising ABCB6, ABCB9, ABCC5, ACCN1, ACO1, ACTR10, ADAMTS12, ADO, AFG3L1P, AIFM2, AKIRIN2, ALOX12P2, ALPI, AMN1, ANKRD11, ANKRD30BL, ANO4, ARID3A, ARRDC3, ATXN1, ATXN3L, AZIN1, AZIN1, BCL2L11, BEND6, BEND6, BMP10, BRD2, C21orf33, C6orfl06, C9orf25, C9orf5, CAMK2D, CANDI, CASC3, CCDC64, CD226, CD27, CD83, CDK17, CDK6, CEBPA, CHST11, CLIP4, CLLU1OS, CLTC, CMPK1, COL24A1, CPEB2, CPEB3, CREBZF, CWC27, DAD1, DCUN1D4, DENND4C, DGCR6L, DNAJA2, DST, DSTNP2, DUSP2, DUSP5, EHMT1, EIF4G3, ELN, EPB41, ERC2, EXOC7, FAM157A, FAM76B, FASTKD2, FECH, FLNB, FSD1L, FTH1, FTL, GABBR2, GATS, GCLC, GCLM, GCNT3, GDF15, GPI, GPNMB, GRM8, GSR, GSTM5, GSTP1, HBB, HBE1, HERC1, HGD, HIF1A, HIST1H4H, HM0X1, HMOX1, HRASLS2, HTATIP2, HTRA3, IFRD1, IFT74, IGF2R, IPO7, IRF2, IRF2BPL, KCNN3, KEAP1, KIAA1522, KIFC3, LBR, LINC00273, LINC00299, LOC100130451, LOC100132891, LOC100507557, LOC147646, LOC284661, LOC284801, LOC338758, LOC338799, LOC440461, LOC643723, LOC646329, LRP8, LRRC8D, LY9, MAFG, MAFG, MAPRE3, MAPT, ME1, MESDC1, MFSD11, MIAT, MIR365A, MIR617, MKLN1,<h2 style=";text-align:left;direction:ltr">MOV10L1, MPPE1, MSL3, MTF2, MYC, NES, NEUROD4, NFE2L2, NKAIN1, NPLOC4, NQO1, NUMBL, NUP153, OR2AT4, P2RY10, PARN, PDCD1LG2, PDCD6IP, PEX5L, PGRMC2, PIP5K1C, PIR, PLA2G6, PMAIP1, PMAIP1, PMF1, PPARGC1B, PPIF, PRDM1, PRDX1, PRKACB, PRKCB, PSMA3, PTGES3, PVRL1, PVT1, RAB10, RAB35, RASAL3, RASSF6, RCAN1, RFFL, RNF213, RNF220, ROCK1, RSPH6A, RXRA, SAR1B, SEC61B, SEMA7A, SEMA7A, SETBP1, SH2D6, SLAMF7, SLC14A2, SLC25A25, SLC3A2, SLC48A1, SLC7A11, SLC9A7P1, SLCO5A1, SORBS2, 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 et ZNF673. ,<h2 style=";text-align:left;direction:ltr">

[0039] In a preferred embodiment, overactivation of an NRF2 pathway is detected by detecting the upregulation of at least one gene selected from the group consisting of ACTR10, AZIN1, CPEB3, FECH, HBB, MSL3, NFE2L2, PMAIP1, PSMA3, PTGES3, SLC9A7P1 and TANK.

[0040] In another embodiment, overactivation of the NRF2 pathway is determined by detecting an increased level of NRF2 protein in a patient sample. In a preferred embodiment, the level of nuclear NRF2 protein is detected since only nuclear NRF2 will contribute to promoting the expression of associated genes.

[0041] In a preferred embodiment, the NRF2 protein level is measured by an immunoassay, preferably by an enzyme-linked immunosorbent assay (ELISA). In one embodiment, the kit may be the Human Nuclear Factor Erythroid 2-Related Factor 2(NFE2L2) ELISA Kit (Cat. No. CSB-EL015752HU, Cusabio, TX) or the Human NRF2 ELISA Kit (Cat. No. EH348RB, Invitrogen, CA).

[0042] Overactivation of the NRF2 pathway is detected when the measured NRF2 protein level is at least one standard deviation higher than the average protein level in a control population.

[0043] According to the invention, a gene expression level or a protein level can be determined in any suitable sample. In preferred embodiments, 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 treated or purified before use according to the invention. In a preferred embodiment, the sample is a peripheral blood mononuclear cell sample. Examples

[0044] Examples 1: Analysis of differential gene expression

[0045] RNA-seq analysis was performed using blood samples obtained from 20 ASD patients, including: i) 10 patients classified as ASD phenotype 1 (ASD-Phenl) (positive for two main criteria: enlarged head circumference (above the 75th percentile) during the first two years of life, and systematic worsening of ASD behavioral symptoms during episodes of immune challenges such as fever and infectious events (e.g., acute inflammation); and thus expected to respond to a pharmaceutical composition comprising ibudilast and bumetanide; and ii) 10 age-matched participants not classified as ASD-Phenl (aka ASD-non-Phenl), thus not expected to respond to such a pharmaceutical composition. From each participant, two tubes each containing 2.5 ml of whole blood in PAXGene® RNA tubes were delivered and sequenced at Omega Bioservices' facility in Georgia (USA).RNA extraction was performed using the QIAGEN PAXgene Blood RNA Kit / Mag-Bind® PX Blood RNA 96 and ERCC Ex-fold RNA Reagent (Cat: 4456739) was added to each sample. rRNA and hgbRNA depletion and RNA-seq library preparation were performed using the Illumina TruSeq Stranded Total RNA Kit with Ribo-Zero Globin. Samples were then sequenced using the Illumina NovaSeq 6000 sequencer, with a 2xl50bp configuration.

[0046] The two blood samples obtained from each patient were sequenced in two different batches and considered as technical replicates. Procedures for Quality control was applied to confirm the absence of batch effects among the samples, by performing principal component analyses (PCA) using the prcomp R function (stats package).

[0047] A differential gene expression analysis between ASD-Phenl and ASD-non-Phenl was then performed to characterize the transcriptomic signature of the ASD-Phenl-specific disease. The R package DESeq2 was used for differential gene expression analysis, using the CollapseReplicates option following the recommended configuration for multiple sequencing runs from the same amount of extracted RNA, to increase statistical power without introducing confounding batch effects.Following differential expression analysis, two PCA plots were produced to assess the power of expressed genes to differentially discriminate individuals with Phenl-ASD versus individuals with non-Phenl-ASD, first using differentially expressed genes with an adjusted p-value (according to the Benjamini and Hochberg correction method) lower than 0.05, and second using the 250 most up- / down-regulated genes (sorted by Log2(FC)); this was done by considering only genes with a median expression level across samples greater than 10 reads ([Fig. 1]). The first two PCA coordinates were then used as features to train a logistic regression model to classify the two phenotypes using their transcriptomic profile.The models were validated using a leave-one-out strategy where, at each iteration, one sample is classified using the others as a training set. Performance is calculated as the number of correctly classified samples in the entire dataset. To validate the procedure, we implemented a permutation test over 1,000 iterations where, at each iteration, the phenotypes were randomly shuffled and the classification score was calculated to obtain their null distribution. This permutation test using leave-one-out cross-validation confirmed the significance of the observed stratification against the null distribution (p = 0.01).

[0048] Example 2: Gene set enrichment analyses

[0049] EnrichR, a comprehensive gene set enrichment analysis web server, was used to explore pathway enrichment of differentially expressed genes (adjusted p-value less than 0.05) in TSA-Phenl compared to TSA-non-Phenl. Gene sets and pathways from the MsigDB Hallmark 2020, KEGG 2021 Human, Reactome 2022, and WikiPathway 2021 Human databases were used in this analysis, which showed statistically significant enrichment (adjusted p-value < 0.05) of differentially expressed genes on pathways related to NF-kB activation and downstream pro-inflammatory cascades (Table 1), including including the NF-kB-associated gene BCL2A1 (log2FC = 1.41; p-value = 2.2E-05; adjusted p-value = 0.043).

[0050] Table 1 NF-kB pathways are significantly enriched for genes showing statistically significant differential expression in TSA-Phenl compared to TSA-non-Phenl GeneSet_DB Expression value - P Value adjusted Coefficient ratio MsigDB_Hallmark_20 20 TNF-alpha signaling via NF-kB 0.004 0.017 24.99 Reactome_2022 MyD88:MAL(TIRAP) cascade initiated on the membrane R-HSA-166058 0.001 0.026 45.18 Reactome_2022 Toll-type receptor 4 (T LR4) Cascade R-HSA-166016 0.002 0.026 35.96 Reactome_2022 Toll-type receptor cascades R-HSA-168898 0.003 0.026 30.98 WikiPathway_2021_H human Survival signaling of NF-kB induced by photodynamic therapy WP3617 0.017 0.028 65.22 Reactome_efficiency in TL2D2D / 28 R-HSA-5602498 0.008 0.045 138.71 Reactome_2022 TLR regulation by endogenous ligand R-HSA-5686938 0.009 0.045 130.54 Reactome_2022 IRA deficiency (TLR244) R-HSA-5603041 0.009 0.045 130.54 Reactome_2022 TRAF6-mediated NF-kB activation R-HSA-933542 0.012 0.050 92.44

[0051] A gene set enrichment analysis (GSEA) was also performed for the differentially expressed genes of ASD-Phenl versus ASD-non-Phenl to validate the consistency with the enrichment of NF-kB-related pathways among ASD-Phenl. The R package fgsea vl.10.1 was used to run the analysis. A total of 15,497 gene ontologies (GOs) and canonical pathways (CPs) were considered in the analysis, as provided by MSigDB human version 7.0 (https: / / data.broadinstitute.Org / gsea-msigdb / msigdb / release / 7.0 / ). A test Fisher's exact was used to confirm a significant overrepresentation of NF-kB-related pathways (i.e., those involving NF-kB) among the enriched pathways (Benjamini-Hochberg adjusted p-value < 0.05) for differentially expressed genes in ASD-Phenl patients (p-value = 7E-15; 95% conf. inter. = 2.41 - 4.17; odds ratio = 3.19).

[0052] The association between the disease-specific transcriptomic signature ASD-Phenl and overactivation of NF-kB and NRF2 transcription factors was then assessed by evaluating the enrichment (based on the two-sided Kolmogorov-Smimov test) of high-confidence NF-kB and NRF2 targets among the 250 most up- or down-regulated genes (i.e., Log2(FC)) when comparing gene expression between ASD-Phenl and ASD-non-Phenl patients. The R function ks.test (stats package) was used to calculate the enrichment score (ES) and the associated significance (two-sided test). Positive or negative ES values ​​indicate that NF-kB / NRF2 gene targets tend to be up- or down-regulated in the transcriptomic signature.The target genes NF-kB and NRF2 were found to be significantly enriched in upregulated genes in the ASD-Phenl group (NF-kB: ES = 0.24 and p-value = < 1E-9; NRF2: ES = 0.21 and p-value = 5.6E-9).

[0053] A total of twenty-four NF-kB transcriptional target genes, particularly 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 found to be differentially upregulated genes in the ASD-Phenl group (p-value < 0.05). By performing some power calculations, we estimated that only twenty NF-kB transcriptional target genes would have been needed to be differentially upregulated in the ASD-Phenl group (p-value < 0.05) to reach statistical significance in the enrichment analysis (p-value < 0.05). In addition, a total of six genes, specifically BCL2A1, TNIP3, NRG1, C3, IL1RN, and KRT5, were found to be among the top 250 most upregulated genes in patients in the ASD-Phenl group.

[0054] A total of twelve NRF2 transcriptional target genes, specifically ACTR10, AZIN1, CPEB3, FECH, HBB, MSL3, NFE2L2, PMAIP1, PSMA3, PTGES3, SLC9A7P1 and TANK, were found to be differentially upregulated genes in the ASD-Phenl group (p-value < 0.05). By performing some power calculations, we estimated that only ten NRF2 transcriptional target genes would have been needed to be differentially upregulated in the ASD-Phenl group (p-value < 0.05) to reach statistical significance in the analysis enrichment (p-value < 0.05). In addition, the HBB gene was found to be among the 250 most upregulated genes in patients in the ASD-Phenl group.

[0055] Example 3: STP1 as a suitable drug candidate to reverse the overactivation of NF-kB and NRF2 in the ASD-Phenl group

[0056] STP1 was obtained by diluting and mixing bumetanide and ibudilast equally to obtain a final ratio of 1:1 of the two individual compounds in the DMSO solution. Commercial NPC (ATCC ACS-5004) and MCF-7 (ATCC HTB-22) cell lines were purchased from the supplier ATCC LGC Standards®. The transcriptional signature of STP1 was then obtained by treating the commercial NPC and MCF-7 cell lines with a final concentration of 5- / / M STP1 or vehicle control (DMSO) for 6 and 24 hours. In addition, LCLs derived from two patients in the ASD-Phenl group were treated with 5 ^M STP1 or DMSO for 48 hours. Each cell line was cultured according to the supplier's instructions until a sufficient number of cells was reached to be seeded for treatment with STP1 or DMSO. All treatments were performed in triplicate, seeding 50,000 cells / well at both time points.RNA was extracted from each well, obtaining a total of 36 samples for library preparation and sequencing. Total RNA was quantified using the Qubit fluorometric assay (Thermo Fisher Scientific). Libraries were prepared from 125 ng of total RNA and sequenced on a NovaSeq 6000 sequencer in single-end mode with a read length of 75 bp and 4 M reads per sample. Bioinformatics analysis consisted of quality filtering, trimming, and alignment to the reference genome to generate raw data. Raw expression data were finally normalized and analyzed for each cell line. A final list of differentially expressed genes for each STP1 treatment or DSMO treatment was obtained across all cell lines.A weighted average merging method that takes into account Spearman correlation between individual cell type treatments was applied to generate drug-induced transcriptomic responses for STP1 by combining individual treatments across cell lines. Finally, a total of three different transcriptional signatures were obtained: i) STP1 or DMSO treatment in MCF-7 and NPC; ii) STP1 or DMSO treatment in LCL derived from the first patient; iii) STP1 or DMSO treatment in LCL derived from the second patient.

[0057] The Kolmogorov-Smimov test was then used to assess the effect of STP1 on the activity of the transcription factors NF-kB and NRF2, measured by the expression of their transcriptional targets in the treated and untreated cell lines. NF-kB and NRF2 target genes were found to be significantly enriched in STP1 downregulated genes in all three cases (Table 2).

[0058] Table 2. Results of enrichment analyses of NRF2 and NF-kB gene targets for different cell lines treated with STP1 Transcriptomic signatures ES NRF2 p-value ES nf-kb p-value commercial NPC and MCF7 cell lines treated with S TPI (5 pM) -0.13 8E-4 -0.08 0.02 First patient-derived LCL treated with STP1 (5 pM) -0.19 2E-7 -0.15 7E-7 Second patient-derived LCL treated with STP1 (5 pM) -0.17 4E-6 -0.15 6E-7

Claims

Claims

1. A pharmaceutical composition comprising ibudilast and bumetanide for use in the treatment of autism spectrum disorders (ASD), wherein the composition is administered to a patient having overactivation of an NF-kB pathway.

2. A kit comprising a dosage form comprising ibudilast and a dosage form comprising bumetanide for use in the treatment of autism spectrum disorders (ASD), wherein the dosage forms are administered to a patient having overactivation of an NF-kB pathway.

3. A composition for use according to claim 1 or a kit for use according to claim 2, wherein overactivation of an NF-kB pathway is determined by detecting the upregulation of at least 20 NF-kB-associated genes selected from the group consisting of ABCA1, ABCB1, ABCB4, ABCB9, ABCC6, ABCG5, ABCG8, ADH1A, ADORAI, ADORA2A, AFP, AGER, AGT, AICDA, ALOX12, AMACR, AMH, ANGPT1, APOBEC2, APOC3, APOD, APOE, AQP4, AR, ARFRP1, ART1, ASPH, ASS1, ATP1A2, 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, CCL23, CCL28, CCL3, CCL4, CCL5, CCND1, CCND2, CCR5, CCR7, CD209, CD274, CD38, CD3G, CD40, CD40LG, CD44, CD48, CD54, CD80, CD83, CD86, CDK6, CDX1, CEBPD, CFB, CFLAR, CGM3, CHI3L1, CIDEA, COL1A2, CR2, CREB3, CRP, CSF1, CSF2, CSF3, CTSB, CXCL1, CXCL10, CXCL3,CXCL5, CXCL9, CYP19A1, CYP27B1, CYP2C11, CYP2E1, CYP7B1, DEFB2, DIO2, DMP1, DNASE1L2, E2F3, EBI3, EDN1, EGFR, ELF3, ENG, EPHA1, EPO, ERBB2, ERVWE1, F3, F8, FABP6, FAM148A, FAS, FASLG, FCER2, FCGRT, FGF8, FN1, FSTL3, FTH1, G6PC, GADD45B, GATA3, GBP1, GCLC, GCLM, GNAI2, GNB2L1, GNRH2, GRM2, GRO-bêta, GRO-gamma, GSTP1, GZMB, HAMP, HAS1, HBE1, HBZ, HIF1A, HLA-B, HLA-G, HMGN1, HM0X1, HOXA9, HSD11B2, HSP90AA1, IER3, IFNB1, IFNG, IGFBP2, [Revendication 4] [Revendication 5] IGHE, IGHG1, IGHG2, IGHG4, IGKC, ligpl, IL10, IL11, IL12A, IL12B, IL13, IL17, ILIA, IL1B, IL1RN, IL2, IL23A, IL27, IL2RA, 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, MMPI, MMP3, MMP9, MTHFR, MUC2, MYB, MYC, MYLK, MY0Z1, NCAM, NFKB1, NFKB2, NFKBIA, NFKBIE, NFKBIZ, NGFB, NK4, NLRP2, NOD2, NOS1, NOS2A, N0X1, NPY1R, NQO1, NR4A2, NRG1, NUAK2, OLR1, OPN1SW, OPRD1, OPRM1, 0RM1, Osterix, OXTR, PAFAH2, PDGFB, PDYN, PENK, PGLYRP1, PGR, PI3KAP1, PIGF, plgR, PIK3CA, PIM1, PLA2, PLAU, PLCD1, PLK3, POMC, PPARGC1B,PRF1,PRKACA, PRKCD, PRL, PSMB9, PSME1, PSME2, ​​PTAFR, PTEN, PTGDS, PTGS2, PTHLH, PTPN1, PTX3, PYCARD, RAG1, RAG2, RBBP4, REL, RELB, S100A4, S100A6, SAA1, SAA2, SAA3, SAT1, SCNN1A, SDC4, SELE, SELP, SELS, SENP2, SERPINA1, SERPINA2, SERPINA3, SERPINB1, SERPINE1, PALI, SERPINE2, SH3BGRL, SKALP, PI3, SKP2, SLC11A2, SLC16A1,SLC3A2, SLC6A6, Slfn2, SNAI1, SOD1, SOD2, SOX9, SPI1, SPP1, ST6GAL1, ST8SIA1, STAT5A, TACR1, TAPI, TAPBP, TCRB, TERT, TFEC, TFF3, TGM1, TGM2, TICAM1, TLR2, TLR9, TNC, TNF, TNFAIP3, TNFRSF4, TNFRSF9, TNFSF10, TNFSF13B, TNFSF15, TNIP1, TNIP3, TP53, TRAF1, TRAF2, TREM1, TRPC1, TWIST1, UPK1B, UPP1, VCAM1, VEGFC, VIM, WT1, XIAP and YYL, The composition of claim 1 or the kit for use of claim 2, wherein overactivation of an NF-kB pathway is determined by detecting the upregulation of at least one, preferably at least six NF-kB associated 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. A composition for use according to claim 1 or a kit for use according to claim 2, wherein overactivation of the NF-kB pathway is determined by detecting an increased level of NF-kB protein in a sample from the patient.

6.

7.

8.

9. A composition or kit for use according to claim 5, wherein the level of nuclear NF-kB protein is measured. A composition or kit for use according to claim 5 or 6, wherein the level of NF-kB protein is measured by an immunoassay, preferably by an ELISA. A composition or kit for use according to any one of claims 1 to 7, wherein the composition is administered to a patient having overactivation of an NF-kB pathway and overactivation of an NRF2 pathway.The composition or kit for use according to claim 8, wherein overactivation of an NRF2 pathway is determined by detecting overexpression of at least 10 NRF2-associated genes selected from the group consisting of ABCB6, ABCB9, ABCC5, ACCN1, ACO1, ACTR10, ADAMTS12, ADO, AFG3L1P, AIFM2, AKIRIN2, ALOX12P2, ALPI, AMN1, ANKRD11, ANKRD30BL, ANO4, ARID3A, ARRDC3, ATXN1, ATXN3L, AZIN1, AZIN1, BCL2L11, BEND6, BEND6, BMP10, BRD2, C21orf33, C6orfl06, C9orf25, C9orf5, CAMK2D, CANDI, CASC3, CCDC64, CD226, CD27, CD83, CDK17, CDK6, CEBPA, CHST11, CLIP4, CLLU1OS, CLTC, CMPK1, COL24A1, CPEB2, CPEB3, CREBZF, CWC27, DAD1, DCUN1D4, DENND4C, DGCR6L, DNAJA2, DST, DSTNP2, DUSP2, DUSP5, EHMT1, EIF4G3, ELN, EPB41, ERC2, EXOC7, FAM157A, FAM76B, FASTKD2, FECH, FLNB, FSD1L, FTH1, FTL, GABBR2, GATS, GCLC, GCLM, GCNT3, GDF15, GPI, GPNMB, GRM8, GSR, GSTM5, GSTP1, HBB, HBE1, HERC1, HGD, HIF1A, HIST1H4H, HM0X1, HM0X1, HRASLS2, HTATIP2, HTRA3, IFRD1, IFT74, IGF2R, IPO7, IRF2, IRF2BPL, KCNN3,KEAP1, KIAA1522, KIFC3, LBR, LINC00273, LINC00299, LOC100130451, LOC100132891, LOC100507557, LOC147646, LOC2846431, LOC21,2830 LOC338799, LOC440461, LOC643723, LOC646329, LRP8, LRRC8D, LY9, MAFG, MAFG, MAPRE3, MAPT, ME1, MESDC1, MFSD11, MIAT, MIR365,A, MOMPEN617 MSL3, MTF2, MYC, NES, NEUROD4, NFE2L2, NKAIN1, NPLOC4, NQO1, NUMBL, NUP153, OR2AT4, P2RY10, PARN, PDCD1LG2, PDCD6IP, PEX5L, PGRMCLA,PG6C1C, PIP5K PMAIP1, PMF1, PPARGC1B, PPIF, PRDM1, PRDX1, PRKACB, PRKCB, PSMA3, PTGES3, PVRL1, PVT1, RAB10, RAB35, RASAL3, RASSF6, RCAN1, RFFL, RNF213, RNF220, ROCK1, RSPH6A, RXRA, SAR1B, SEC61B, SEMA7A, SEMA7A, SETBP1, SH2D6, SLAMF7, SLC14A2, SLC25A25, SLC3A2, SLC48A1, SLC7A11, SLC9A7P1, SLCO5A1, SORBS2, 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.

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

11. A composition or kit for use according to claim 8, wherein overactivation of the NRF2 pathway is determined by detecting an increased level of NRF2 protein in a patient sample.

12. A composition or kit for use according to claim 11, wherein the level of nuclear NRF2 protein is measured.

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

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