Anti-asthma drug montelukast induces autistic behaviors via disrupting neuronal retinoic acid signaling.

Anti-asthma drug montelukast induces autistic behaviors via disrupting neuronal retinoic acid signaling - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Search Log in Primary site navigation Search Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice Signal Transduct Target Ther . 2026 Jun 2;11:208. doi: 10.1038/s41392-026-02665-w Anti-asthma drug montelukast induces autistic behaviors via disrupting neuronal retinoic acid signaling Zi-Jian Hao 1, 2, 3, # , Qiong-Hui Wu 4, 5, # , Ya-Li Li 3, # , Zhen-Ming Guo 6, # , Zheng-Wei Li 3, # , Gui Wang 6 , Meng Meng 7 , Shi-Lin Yuan 3 , Yilimire Wufuer 3 , Meng-Huan Zhang 6 , Jie Chen 4 , Ting Yang 4 , Meng-Xia Chen 6 , Jiang Zhu 4 , Wang Qi-Hang 3, 8 , Qiu Li 4 , Shi-Hu Yu 3, 8 , Min Lu 4 , Hai-Yi Xiong 9, 10 , Yu-Ru Feng 4 , Meng-Qi Dong 11 , Jun-Hao Xu 12 , Jia-Lin Xu 13 , Li Chen 4, 5 , Han-Ting Yang 14 , Jing-Kun Miao 9, 10 , Hong Zhu 15 , Bo Yang 15, 16 , Hui-Ying Zhao 7, 17, ✉ , Xiao-Ming Shi 18, ✉ , Shan Bian 6, 19, 20, 21, 22, ✉ , Ting-Yu Li 4, 5, ✉ , Rong-Gui Hu 1, 23, 24, 25, 26, 27, ✉ Author information Article notes Copyright and License information 1 Department of Colorectal Surgery and Oncology and School of Brain Science and Brain Medicine, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China 2 Institute of Science and Technology for Brain-Inspired Intelligence, MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China 3 Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai, China 4 Chongqing Key Laboratory of Child Neurodevelopment and Cognitive Disorders, National Clinical Research Center for Children and Adolescents’ Health and Diseases, Ministry of Education Key Laboratory of Child Development and Disorders, Children’s Hospital of Chongqing Medical University, Chongqing, China 5 Growth, Development, and Mental Health of Children and Adolescence Center, Children’s Hospital of Chongqing Medical University, Chongqing, China 6 Institute for Regenerative Medicine, Medical Innovation Centre and State Key Laboratory of Cardiovascular Diseases, Shanghai Institute of Stem Cell Research and Clinical Translation, Shanghai East Hospital, National Stem Cell Translational Resource Centre & Ministry of Education Stem Cell Resource Centre, Frontier Science Centre for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai, China 7 School of Data and Computer Science, Sun Yat-Sen University, Guangzhou, China 8 University of Chinese Academy of Sciences, Beijing, China 9 Department of Pediatrics, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China 10 Department of Pediatrics, Chongqing Health Center for Women and Children, Chongqing, China 11 College of Public Health and Nursing, Shanghai Aurora College, Shanghai, China 12 Department of Biology, Stanford University, Stanford, CA USA 13 School of Biological Sciences, University of California San Diego, San Diego, CA USA 14 Institute for Translational Brain Research, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China 15 Institute of Pharmacology & Toxicology, Zhejiang Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China 16 School of Medicine, Hangzhou City University, Hangzhou, China 17 Department of Medical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangzhou, China 18 China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China 19 National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hunan Provincial Maternal and Child Health Care Hospital, University of South China, Changsha, China 20 China Regional Research Center, International Center for Genetic Engineering and Biotechnology, Taizhou, China 21 Jiangxi Province Key Laboratory of Organ Development and Epigenetics, Clinical Medical Research Center, Affiliated Hospital of Jinggangshan University, Medical Department of Jinggangshan University, Ji’an, China 22 School of Life Science, Jinggangshan University, Ji’an, China 23 Medical Research and Innovation in Digestive System Tumors, Ministry of Education, Hangzhou, China 24 Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China 25 Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China 26 State Key Laboratory of Transvascular Implantation Devices, Hangzhou, China 27 NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China ✉ Corresponding author. # Contributed equally. Received 2025 Jun 26; Revised 2026 Feb 2; Accepted 2026 Mar 3; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13230969  PMID: 42230569 Abstract Autism spectrum disorders (ASD) affect approximately 1.0% of children worldwide with still increasing global prevalence. The fact that genetic factors contribute to less than 50% of ASD suggests some critical yet enigmatic roles of non-genetic factors in ASD etiology. Here, we reported that montelukast (MTK), a cysteinyl leukotriene receptor antagonist and one of the most commonly prescribed anti-asthma drugs, potently disrupted neuronal retinoic acid (RA) signaling and altered synaptic plasticity of the primary neurons from rat pre-frontal cortex (PFC). Prenatal or early postnatal exposure to MTK induced autistic-like behaviors in wild-type rats, which could be significantly alleviated by supplementing all-trans retinoic acid (atRA). MTK altered neuronal RA signaling and forebrain patterning in brain organoids derived from human embryonic stem cells through antagonizing RA in RA signaling. Meanwhile, molecular docking followed by biochemical validation strongly indicated that MTK could physically interact with RA receptors (RARs), e.g. RA receptor α (RARA). Furthermore, multi-center survey with a large Chinese ASD cohort suggested that MTK administration during early childhood might indeed increase the risk of ASD in children. Altogether, our findings have not only established MTK use as a yet unrecognized risk factor for human ASD, but highlighted the key importance of safer use of medicines to prevent ASD. Subject terms: Molecular neuroscience, Neurodevelopmental disorders, Genome informatics Introduction Autism spectrum disorder (ASD) comprises a group of complex neurodevelopmental conditions characterized by lifelong behavioral abnormalities, including social deficits and repetitive behaviors. 1 Massive research efforts have been undertaken to identify causal or risk factors of ASD, which uncovered thousands of candidate variants in hundreds of potential risk genes, as well as other chromosomal abnormalities, in ASD patients. 2 – 4 However, as decades of genetic and genomics studies with human ASD patients, it is clear that these genetic factors could only account for less than 50% of total cases worldwide, supporting a substantial but yet elusive role of environmental factors in ASD etiology. 5 , 6 Indeed, it is widely hoped that the elimination of these non-genetic risk factors may represent one of the few effective avenues to combat the seemingly ever-increasing prevalence of ASD in newborns worldwide. However, due to the extremely high heterogeneity in etiology and clinical manifestations of ASD, it remains particularly challenging but imminent to identify the environmental factors of ASD and decisively understand how they may affect the neuropsychiatric development of young humans. 7 – 9 Retinoic acid (RA), the active derivative from vitamin A, is both a metabolite and signaling molecule that is essential for cell fate determination and the development of tissues, including the brain, while regulating key biological processes, e.g., immune responses, neurogenesis, and synaptic function. 10 , 11 In particular, RA participates in the patterning of the anterior-posterior (A/P) and dorsal-ventral (D/V) axes of the central nervous system. 12 RA also regulates the proliferation and differentiation of neural precursors during neurogenesis in mice. 13 Previous epidemiological analysis demonstrated that serum vitamin A levels are significantly lower in children affected by ASD than in unaffected children and are negatively correlated with ASD severity. 14 , 15 In our previous work with a mouse model mimicking the Dup15q11 subtype of human ASD, we found that excessive levels of the E3 ubiquitin ligase, UBE3A, led to downregulation of endogenous RA synthesis through hyper-ubiquitination of ALDH1As, the rate-limiting enzyme in RA biogenesis. 16 Notably, supplementation with all-trans RA (a drug form of natural RA analog) in this model alleviated autistic-like behaviors, as well as a mouse model of fragile X syndrome, 17 suggesting that suppression of RA signaling might play a causal role in some ASD subtypes. Consistently, genome-wide association studies (GWAS) with ASD patients have identified mutations in genes of RA signaling pathway, such as retinoic acid receptor alpha ( RARA 18 ), retinoic acid-related orphan receptor alpha ( RORA 19 ), and aldehyde dehydrogenase family 1 member 3 ( ALDH1A3 20 ). More recently, we found that maternal exposure to triclosan, a broadly used antimicrobial found in over 2000 healthcare products, could impair RA signaling and predominantly induce autistic-like behaviors in rats 21 and significantly increase the risk of ASD in humans. 22 This has since prompted us to ask whether there might be some other chemicals that significantly increase the risk of human neuropsychiatric diseases, e.g., ASD, through disrupting RA signaling pathways. Montelukast (MTK), an antagonist of the cysteinyl leukotriene receptor 1 (CysLT1), 23 was approved for clinical use by the US FDA in 1998. MTK has been commonly prescribed to control inflammation and treat asthma or asthma-related symptoms, e.g. wheezing and shortness of breath, as well as allergic rhinitis. 24 With several recent reports that MTK might be associated with various neuropsychiatric events in children and adult users 25 with mechanisms yet unknown, a boxed-warning was issued by FDA in 2020 26 and by National Medical Products Administration (NMPA) of China in 2025. 27 Nevertheless, MTK is still extensively used worldwide with tens of millions of prescriptions annually, available as generic or brand name products. It is left almost totally unaddressed whether and how MTK might affect young human brains and cause some psychiatric effects in pediatric MTK users. In this study, we first performed a chemical screening of FDA-approved drugs that impaired RA signaling in RA-responsive element (RARE)-driven luciferase reporter assay, in which MTK emerged as a potent inhibitor of RA signaling. A case-control study was conducted in multiple centers confirmed potential associations between ASD risk and MTK exposure in humans. To further examine the neuropsychiatric effects of MTK in young mammals, wild-type rats were prenatally or early-postnatally exposed to MTK in clinically relevant dosages, followed by extensive behavioral tests and multi-omics analyses. Anatomical and multi-omics analyses were also performed with cerebral organoids derived from human embryonic stem cells (hESC) exposed to MTK. Finally, in silico and in vitro approaches were taken to predict, and then validate the interaction between MTK and RA receptor α (RARα). Results Montelukast is a negative regulator of the cellular retinoic acid signaling pathway Previously, our work has established a causal link between impaired RA signaling to increased risk of ASD in humans, or autistic-like behaviors in rodent models that were either genetically edited (e.g., UBE3A CNV expansion or FMRP deficiency) or exposed to chemicals like triclosan or disulfiram. 16 , 17 , 21 We screened a panel of 54 FDA-approved drugs (Supplementary Table 1 ) along with four other chemicals (elucidated in Materials and methods) for potential interaction with the RA signaling pathway, using a RARE (RA-responsive e lement) sequence with luciferase reporter driven by a mini-TK (thymidine kinase) promoter in H1299 cells (Fig. 1a , Supplementary Fig. 1a ). H1299 cells were selected for reporter screening due to their low expression of RA-synthesizing retinaldehyde dehydrogenase (RALDH/ALDH1A) family proteins (Fig. 1b ), thus minimizing potential interference from endogenous RA. The Exposure at 10.0 μM for 24 h (Fig. 1c-d ) resulted in >50% suppression of reporter signal in triclosan (TCS) (Supplementary Fig. 1b ) and montelukast (MTK) treatments (Fig. 1e ). TCS was found to inhibit RA signaling pathway in our current (Supplementary Fig. 1c ) and previous study, 21 thus serving as a positive control for the screening. Further cytotoxicity assays indicated that >80% of cells treated with MTK remained viable at the indicated dosage, suggesting that reporter inhibition was due to RA response rather than elevated cell death levels (Fig. 1f ). Subsequent dual luciferase reporter assays in SH-SY5Y neuroblastoma cells further showed that MTK exposure could suppress RA-induced gene expression in a dose-dependent manner (Fig. 1g ). Using a similar RA-responsive humanized Renilla GFP (hrGFP) reporter as in the initial screen in primary PFC neurons of rats (Fig. 1h ), we found that MTK could also suppress RA-dependent activation of the RARE-TK-hrGFP reporter by treatment with RA alone, or D (-)-2-amino-5-phosphonopentanoic acid (D-APV) and sodium channel blocker tetrodotoxin (TTX), which has been proved to promote RA synthesis 16 , 28 (Fig. 1i, j ). The expression level of the control reporter lacking RARE sequence upstream TK promoter was not significantly changed upon chemical treatment (Supplementary Fig. 1d-f ). These results suggested that MTK could suppress RA-induced reporter expression in primary neurons. Fig. 1. Open in a new tab Compound screening assay identifies montelukast as a suppressor of RA signaling pathway. a A Scheme showing the construction of pGL3-3×RARE-TK-luciferase reporter. Three copies of DR5 (direct repeat with 5 bp of spacing) variant of RA responsive elements (RARE) in a reverse-reverse-forward direction are placed upstream to TK (thymidine kinase) promoter that was immediately followed by ORF for firefly luciferase reporter gene (ffLuc). b Immunoblotting analysis confirmed that endogenous RA-synthesizing enzymes, the ALDH1A family proteins, were hardly detectable in H1299 cells, but abundantly expressed in SH-SY5Y cells. c The work-flow of the screening assay. The H1299 cells transfected with the RA reporter construct were plated and cultured in 384-well plates before treatment with the compounds (10.0 μM for 24 h) and RA (3.0 μM for 16 h). Regular luciferase activity assay was then subsequently performed, with the signal of RA signaling (luciferase activity) normalized against that of cell viability (Prestoblue fluorescence assay). d The inhibitory effect of 58 compounds on RA signaling. Each point represents the mean ratio following treatment with each compound in 6 wells from 2 independent experiments. Two hit compounds of the relative inhibition ratio above 50% were highlighted in different colors (TCS in green and MTK in red). e The chemical structure of MTK. f Dose-dependent inhibitory effect of MTK on RA signaling in H1299 cells. While the black curve represents relative luciferase signal (% of the control wells), the red curve indicates the cell viability upon the administration of MTK at given concentrations (from 0.39 to100 μM at 2-fold gradient). The cyan arrow indicates the concentration (12.5 μM) at which RA signaling was obviously reduced whereas most cells (92.1%) remained vital. The experiments were performed with 2 replicates. g The dose-dependent antagonizing effect of MTK at indicated concentrations on RA signaling (RA at 1.0 μM) in SH-SY5Y cells. The signal of RA signaling was quantitated by dual luciferase reporter assay. n = 3 biological replicates from 3 independent experiments. h A schematic view of the pCDH-3×RARE-TK-hrGFP reporter construct. The expression of hrGFP is driven by a thymidine kinase (TK) promoter, upstream of which contains three copies of RA responsive elements (RARE) in a reverse-reverse-forward direction. Representative images ( i ) and quantification of hrGFP expression level ( j ) of cultured rat PFC neurons transfected with RARE-TK-hrGFP reporter under the treatment of indicated compounds. Neurons were treated with 100.0 μM APV and 1.0 μM TTX, or 10.0 μM RA alone, in the presence of DMSO or MTK. n = 21–24 neurons for each treatment group in two independent experiments. Scale bar: 20 µm. Data are presented as means ± SEM. g Two-way repeated-measures analysis of variance (ANOVA) with Bonferroni’s post hoc test. j One-way ANOVA with Tukey’s post hoc test Children with montelukast administration show an increased risk of childhood autism As aberrant down-regulation of RA signaling has been associated with ASD, we investigated possible associations between MTK use and ASD traits in children through retrospective examination of data from the China Multi-center Preschool Autism Program (CMPAP) 29 case-control study (Supplementary Fig. 2 ). A total of 1232 ASD patients (1013 boys and 219 girls) and 1239 control children (763 boys and 476 girls) with regular development (i.e., no history of neurological disease) were recruited based on their participation in the CMPAP from 2018 to 2020. Follow-up questionnaires were issued to parents of all study subjects to collect data regarding pre- and postnatal medicinal drug use in both parents and children. Birth characteristics, parental education level, maternal age at conception, maternal parity, and parental history of mental disorders were adjusted for further analysis (Supplementary Table 2 ). Responses revealed that 11.1% (276/2471) of all children in the study took MTK before age 3, including 9.8% (121/1239) of control children and 12.6% (155/1232 kids) of the ASD group (Table 1 ). Subsequent logistic regression analysis demonstrated that children with MTK exposure in the first three years of their life had an increased risk of ASD (adjusted Odds Ratio, 1.377; 95% CI, 1.032 to 1.838), compared to those without MTK exposure (Table 1 ), suggesting that early-life exposure to MTK might contribute to ASD development. Table 1. Odds ratio of childhood autism after exposure to montelukast within the first three years after birth Exposures and outcomes no. of children/total no. (%) Unadjusted Adjusted a OR (95% CI) p OR (95% CI) p Montelukast ASD TD Unused 1077/1232 (87.4) 1026/1239 (90.2) Ref. Ref. Used 155/1232 (12.6) 121/1239 (9.8) 1.330 (1.033, 1.711) 0.027 1.377 (1.032, 1.838) 0.030 Open in a new tab Model “a” was adjusted for gender, age, maternal education level, paternal education level, parental history of mental disorders, maternal age at conception, maternal parity, premature infant and one-child family. Logistic regression analysis was used to determine the relationship between the variables OR odds ratio, CI confidence interval, ASD autism spectrum disorder, TD typically developing Montelukast administration leads to autistic-like behaviors in rat models by disrupting RA signaling To further investigate the potential association between MTK use and the risk of ASD, we orally administered MTK in pregnant and post-natal Sprague-Dawley (SD) rats using dosages mimicking those applied in humans based on body weight (see Materials and methods). Following two weeks of MTK (4.0 mg/day/kg, oral) from postnatal day 14 (PND14) through PND28, the RA supplementation group received oral gavage of RA at a dose of 6 mg/kg daily for 2 weeks following the conclusion of MTK exposure, and the other two groups were treated with a solvent control. After all interventions were completed, 5–6-week-old male or female offspring were subjected to three-chamber social interaction tests devised to assess animal behaviors similar to ASD-associated deficits in human social interaction. As shown in Fig. 2a , both male and female SD rats in the MTK group spent significantly more time in chambers containing objects or familiar rats, and less time with stranger rats in social interaction sessions compared with the vehicle control group, and RA administration partially reversed the autism-like behavioral changes, including significant improvements in sociability and response to social novelty (Fig. 2b-e , Supplementary Fig. 3a, b ). Similarly, self-grooming tests of repetitive behavior, another manifestation of ASD, showed that rats in the MTK group spent more time in self-grooming than control animals (Fig. 2f ). These results suggested MTK exposure in early life could lead to higher probability in autistic-like behaviors in human. Fig. 2. Open in a new tab Prenatal or early-postnatal exposure to montelukast disrupts RA signaling and induces autistic-like behaviors in rats. a A scheme for oral administration of MTK (4.0 mg/kg body weight) or solvent to rats from postnatal day (PND) 14 to PND 28 every day, the RA supplementation group received 6 mg/kg RA administered orally via gastric lavage for two weeks following the conclusion of MTK exposure. The rats were then subjected to behavioral tests at the age of 6 weeks. Time spent in chamber containing object or living rat ( b ), sociability preference index ( c ), time spent in chamber containing familiar or novel rat ( d ), social novelty preference index ( e ) for the three-chamber test and time spent in self-grooming ( f ) for the repetitive behavioral test performed with rats daily administered with solvent or MTK, rats supplemented with RA. n = 14 for control group (Ctrl); n = 17 for MTK group (MTK 4.0 mg/kg); n = 14 for MTK + RA group (MTK 4.0 mg/kg, RA 6.0 mg/kg). g A scheme for oral administration of MTK (1.0 or 10.0 mg/kg body weight) or solvent to pregnant rats from embryonic day E7.5 to E21.5 every day. The offspring were later subjected to behavioral tests at the age of 5–6 weeks. Time spent in chamber containing object or living rat ( h ), sociability preference index ( i ), time spent in chamber containing familiar or novel rat ( j ), social novelty preference index ( k ) for the three-chamber test and time spent in self-grooming ( l ) for the repetitive behavioral test performed with offspring rats whose mothers were daily administered with solvent, 1.0 or 10.0 mg/kg body weight MTK. n = 19 for control group (Ctrl); n = 20 for 1.0 mg/kg body weight MTK group (MTK 1.0 mg/kg); n = 20 for 10.0 mg/kg body weight MTK group (MTK 10.0 mg/kg). Data are presented as means ± SEM. b , d Two-way repeated-measures ANOVA with Tukey post hoc test. c , e , f One-way ANOVA with Tukey post hoc test. h , j Two-way repeated-measures ANOVA with Dunnett’s post hoc test. i , k , l One-way ANOVA with Dunnett’s post hoc test Similarly, behavioral tests were performed with the 5-6-week-old male or female offspring of pregnant SD rats exposed to MTK (1.0 or 10.0 mg/kg) through oral gavage daily from embryonic day 7.5 (E7.5) to E21.5 (Fig. 2g ). Results showed that rats with maternal exposure to 10.0 mg/kg MTK also exhibited impaired sociability and social novelty compared to offspring of vehicle-treated rats (Fig. 2h-k , Supplementary Fig. 3c, d ). Interestingly, young rats that were maternally (i.e., prenatal) exposed to either 1.0 or 10.0 mg/kg body weight MTK spent significantly more time in self-grooming than vehicle control offspring (Fig. 2l ). Notably, no significant differences in body weight between the MTK exposure and vehicle groups (Supplementary Fig. S3e, h ), nor were any differences detected between these groups in anxiety-like behaviors (i.e., time spent in the central area of open field tests) (Supplementary Fig. 3g, j ). Interestingly, the total distance traveled by rats significantly decreased after MTK exposure during the postnatal period (Supplementary Fig. 3f ); however, the total distance traveled by offspring exposed to MTK during pregnancy showed no significant change (Supplementary Fig. 3i ). Collectively, these data clearly demonstrated that prenatal or early postnatal MTK exposure could elicit autistic-like behaviors in rats. Pathological changes in prefrontal cortex (PFC) are commonly observed in ASD patients. 30 , 31 Moreover, research from our own lab clearly indicated that neuronal RA signaling was impaired in PFC of UBE3A -overexpressing mice 16 or in rats of the triclosan-induced autism model. 21 It was important to note that the exposure to MTK during the postnatal or embryonic period did not significantly alter serum RA levels when compared to that of control rats (Supplementary Fig. 4a, b ), indicating that MTK exposure did not have an obvious effect on the biosynthesis of RA. Western blotting analyses further showed that RA receptor A and B (RARA/B) protein levels were significantly decreased in PFC of rats with postnatal or embryonic MTK exposure and autistic-like behaviors compared to vehicle controls (Supplementary Fig. 4c, d ). Together, these results suggested that MTK exposure prenatally or in early postnatal stages could disrupt RA signaling in the PFC and induce autistic-like behaviors in rats, while spelling no change in RA biogenesis. Montelukast disrupts RA signaling and alters the expression of ASD risk genes in human brain organoids Based on our above findings with rats and primary neurons, together with the known developmental and pathological roles of RA signaling in neurodevelopment, 11 , 32 , 33 we next investigated the possible effects of MTK on developing human brain using human embryonic stem cell (hESC)-derived brain organoids 34 , 35 as a model. As shown in Fig. 3a , MTK exposure began at day 20 (D20), during neural precursor cell (NPC) expansion stage, prior to the onset of neurogenesis (D30). 36 After 40 days of continuous exposure, MTK-treated organoids were smaller than DMSO-treated controls, suggesting that neurogenesis in the brain organoids might be inhibited in the presence of MTK (Fig. 3b, c ). Bulk RNA-seq analysis in D60 organoids (Supplementary Fig. 5a ) identified 46 differentially expressed RA signaling-related genes (RASGs), 37 including RA metabolism genes ( CYP26B1 , RDH10 , RDH16 ), RA transport genes ( RBP1 , CRABP2 ), and RA downstream regulatory targets ( COL1A1 , WNT7B ) between MTK- and DMSO-treated organoids (Supplementary Table 3 ). Meanwhile, the treatment with DEAB (4-[diethylamino]-benzaldehyde), an ALDH1A inhibitor that suppressed endogenous RA biosynthesis, 38 also resulted in significantly smaller cerebral organoids compared to vehicle controls and transcriptional changes in the 45 RASGs (Supplementary Fig. 5b-d ), aligning well with our observations in MTK-treated organoids. Notably, 15 RASGs overlapped with those identified in the MTK treatment group, 13 of which showed similar up- or down-regulation between DEAB and MTK treatments (Fig. 3d ). Further global ribosome profiling analysis confirmed the similar expression patterns of RASGs between MTK- and DEAB-treated organoids (Supplementary Fig. 5e ). These cumulative observations suggested that MTK exposure could disrupt RA signaling and impair neurogenesis in the human brain during early development. Fig. 3. Open in a new tab Montelukast disrupts RA signaling and alters expression of ASD risk genes in human brain organoids. a The schematic procedure of hESC-derived cerebral organoid culture and compound treatment. The hESC H9 colonies were plated into a low-binding 96-well plate with V-shape bottom to induce EB formation. On day 5, EBs were transferred into neural induction medium to promote neurogenesis for 5 days. Then EBs were embedded into matrigel droplets and cultured on orbital shaker until day 60 to promote terminal differentiation. From day 20 to day 60, the organoids were treated with DMSO or MTK and collected for further analysis at indicated time points. RI, ROCK inhibitor; EB, embryonic body; NSC, neural stem cell; NPC, neural progenitor cell. b Representative images of DMSO- and MTK-treated cerebral organoids on day 20, 30, 40, 50, and 60. Scale bars: 500 μm. c Quantification of the mean organoids area at five different time points of terminal differentiation. n = 9–10 organoids per condition. d Heatmap representing changes in the mRNA expression of 15 overlapped differentially expressed RASGs ( P value < 0.05; fold change>1.23) from both MTK- and DEAB-treated organoids on day 60. e PPI network formed by 35 ASD risk genes differentially expressed in MTK-treated brain organoids. Different circle sizes correspond to the betweenness score calculated by Cytoscape analysis. The brain patterning- and RA signaling-related genes are highlighted with blue and red dotted boxes, respectively. Data are presented as means ± SEM. c Two-way repeated-measures ANOVA with Bonferroni’s post hoc test Further investigation of the effects of MTK on the expression of known ASD risk genes (Simons Foundation Autism Research Initiative, SFARI) in our bulk RNA-seq data uncovered 44 of them in the DEGs in MTK-treated organoids, compared to the control group (Supplementary Table 4 , |FC | > 1.23, P < 0.05). Protein-protein interaction (PPI) network analysis ( https://cn.string-db.org/ ) illustrated interactions among these genes, and 35 interaction strings were used for subsequent betweenness centrality (BC) analysis with Cytoscape (Fig. 3e ). Among these nodes, CNTNAP2 had the highest BC score, suggesting its possible function as a hub within the network mediating the effects of MTK on the early development of human brain, particularly from the perspectives of ASD-associated genes. Notably, among these differentially expressed ASD risk genes, some were of established roles in RA signaling pathway (eg. DRD2 ), while some were known to participate in brain patterning. 39 – 41 Montelukast alters the dorsal-ventral patterning and the ratio of excitatory/inhibitory (E/I) neurons in human cerebral organoids Given the above effects of MTK on RA signaling and cerebral organoid development, we next examined our data from bulk RNA-seq for evidence of abnormal expression in region-specific markers for brain patterning. As shown in Fig. 4a, b , significant upregulation of multiple ventral forebrain markers ( OLIG2 , NKX2-1 , DLX2 , DLX5 , and LHX6 ) was observed in MTK-treated organoids, along with the downregulation of several dorsal forebrain markers ( RELN , FEZF2 , EOMES , TBR1 , and PAX6 ), 41 which were subsequently validated through qPCR analyses (Fig. 4a, b ). Similarly, ribosome profiling of MTK- or vehicle-treated D60 cerebral organoids also showed elevated expression of ventral forebrain identity markers (Fig. 4c ), which aligned well with the greater ventral forebrain development, but attenuated dorsal forebrain development observed in DEAB-treated cerebral organoids (Supplementary Fig. 6a-c ). These results suggested that impaired RA signaling might negatively impact dorsal forebrain development. Fig. 4. Open in a new tab Montelukast affects dorsal-ventral patterning and excitatory/inhibitory (E/I) neuron ratio of human cerebral organoids. a Heatmap representing changes in the mRNA expression of brain region-specific DEGs (P value < 0.05; fold change>1.23) from DMSO- and MTK-treated organoids on day 60. b Quantitative real-time PCR analysis of representative brain region-specific DEGs from DMSO- and MTK-treated cerebral organoids on day 60. The expression level was normalized to DMSO-treated group. Data are presented as means ± SEM. Two-way repeated-measures ANOVA with Bonferroni’s post hoc test. n = 3 biological replicates pooled from 9 organoids per treatment. c Heatmap representing changes in the translational expression level of brain region-specific DEGs ( P value < 0.05) from DMSO- and MTK-treated organoids on day 60. d Uniform Manifold Approximation and Projection (UMAP) plot showing all annotated cells (from 27 human cerebral organoids on day 60 treated with DMSO, MTK, or DEAB, 9 organoids in each group. n = 85,663 cells from all organoids were colored by cluster. Each dot represents a single cell; colors correspond to 15 major clusters: IN-CTX-CGE-1, IN-CTX-MGE-2, RG-div, vRG, EN-PFC1, oRG, EN-V1-1, IN-CTX-MGE-1, EN-V1-2, IPC-nEN, IN-CTX-CGE-2, nIN, EN-PFC2, EN-V1-3, and IPC. e UMAP plots displaying the sam e clusters as in (D), separated by treatment group. From left to right: DMSO ( n = 30,719 cells), MTK ( n = 19,956 cells), and DEAB ( n = 34,988 cells). Cluster identities (as defined in panel D) are indicated by color. f Stacked bar chart showing the proportion of each major cluster in DMSO, MTK, and DEAB groups. For each condition (x-axis), bars are divided by cell-type cluster (legend at right), with height indicating the percentage of total cells in that cluster. g Bar graph of relative cluster proportions under MTK or DEAB treatments, normalized to DMSO (set as 100%) for each cluster. Colored bars show MTK (red) and DEAB (yellow) fold-change relative to DMSO. Sample sizes as in (D). h Proportions of excitatory neuron (EN, red) versus inhibitory interneuron (IN, blue)–lineage cells across treatment conditions.The black dashed line marks 50%. Here, EN cells encompass all clusters annotated as excitatory neurons (EN-PFC1, EN-PFC2, EN-V1-1, EN-V1-2, EN-V1-3), and IN cells encompass all clusters annotated as inhibitory lineage (IN-CTX-CGE-1, IN-CTX-CGE-2, IN-CTX-MGE-1, IN-CTX-MGE-2, nIN). i Representative immunofluorescence images of cerebral organoids on day 60 upon DMSO or MTK treatment. Scar bar: 500 μm. EN-V1-1 Excitatory Neuron-Visual Cortex-1, EN-V1-2 Excitatory Neuron-Visual Cortex-2, EN-V1-3 Excitatory Neuron-Visual Cortex-3, EN-PFC1 Excitatory Neuron-Prefrontal Cortex-1, EN-PFC2 Excitatory Neuron-Prefrontal Cortex-2, nIN Newborn Interneuron, IN-CTX-CGE1 Interneuron-Cortex-Caudal Ganglionic Eminence-1, IN-CTX-CGE2 Interneuron-Cortex-Caudal Ganglionic Eminence-2, IN-CTX-MGE1 Interneuron-Cortex-Medial Ganglionic Eminence-1, IN-CTX-MGE2 Interneuron-Cortex-Medial Ganglionic Eminence-2, RG-div Radial Glia-dividing, oRG Outer Radial Glia, vRG Ventricular Radial Glia, IPC Intermediate Progenitor, IPC-nEN Intermediate Progenitor-Newborn Excitatory Neuron To further examine the effects of MTK on the development of different brain regions, single cell (sc)RNA-seq analyses were performed with a total of 85,663 cells from DMSO- (30,719 cells), MTK- (19,956 cells), or DEAB- (34,988 cells) treated human cerebral organoids. Clustering analysis based on cell type-specific markers (see Materials and methods), with UMAP plots for visualization, identified 15 distinct cell populations (Fig. 4d, e , Supplementary Fig. 7 , Supplementary Table 5 ). Similar patterns were observed between the altered cluster proportions in MTK- and DEAB-treated D60 organoids, when compared with those treated with DMSO (Fig. 4f ). The proportion of all subtypes of excitatory neurons (EN), which differentiated from dorsal radial glial cells, decreased significantly in MTK- or DEAB-treated organoids (Fig. 4g ). In contrast, the proportion of most subtypes of inhibitory interneurons (IN), which mainly derived from ventral forebrain neural precursors, increased remarkably following MTK or DEAB exposure compared to those in the control organoids treated with DMSO (Fig. 4g ). As the outcome, the ratio of excitatory neuron proportion/inhibitory neuron proportion was dramatically diminished upon the exposure to MTK or DEAB administration compared to the ratio in control DMSO-treated organoids (Fig. 4h ). We further validated our findings by immunofluorescence staining for the dorsal forebrain neural progenitor marker, PAX6, and ventral forebrain interneuron precursor marker, NKX2-1, in sections from D60 organoids. The NKX2-1 + interneuron precursors were more abundant in MTK-treated organoids compared to the controls. In contrast, PAX6 + dorsal forebrain radial glial cells were decreased (Fig. 4i ). Altogether, these results consistently showed that RA signal blockade by MTK could lead to markedly biased development of the ventral forebrain, potentially at the expense of the dorsal forebrain, while significantly perturbing the balance between the excitatory and inhibitory neurons. Furthermore, we performed immunofluorescence analysis on the rat prefrontal cortex (PFC). Rats exposed to MTK (4.0 mg/kg) exhibited a significant reduction in the population of glutamatergic neurons (labeled with vGLUT1) (Supplementary Fig. 8a, c ), alongside a marked increase in inhibitory GABAergic neurons (labeled with GAD1) (Supplementary Fig. 8b, d ). Remarkably, subsequent supplementation with RA partially ameliorated these neuronal alterations. Concurrently, primary rat neurons were subjected to various pharmacological treatments, and miniature excitatory and inhibitory postsynaptic currents (mEPSCs and mIPSCs) were subsequently recorded (Supplementary Fig. 8e-f ). MTK treatment significantly suppressed the E/I amplitude ratio (Supplementary Fig. 8g ), thereby disrupting neuronal excitatory/inhibitory balance. Notably, when neurons were treated with either APV + TTX or RA, a marked increase in the E/I amplitude ratio was observed (Supplementary Fig. 8g ). Under these conditions, MTK intervention effectively counteracted the elevated E/I amplitude ratio. These results collectively underscored that exposure to MTK did significantly impair neuronal E/I balance, suggesting a key underlying mechanism for the observed behavioral phenotypes. Montelukast inhibits RA signaling through competitive binding to RARα and disrupting RAR-RXR heterodimerization As MTK could suppress RA-dependent transcriptional regulation (e.g., in our above reporter assays or RNA-seq data), but did not significantly affect serum RA levels (i.e., biosynthesis) in rats, we first examined possible competitive interactions with RARA, which is ubiquitously expressed in mouse embryos, 42 essential for early neural differentiation, 12 and has been implicated in ASD. 18 In silico molecular docking simulations suggested that MTK could bind to the same pocket as RA (Fig. 5a ). Subsequent microscale thermophoresis (MST) assays revealed that MTK could directly bind to His-tagged recombinant RARA protein (Supplementary Fig. 9a ) with an estimated Kd of 7.13 ± 2.99 μM (Fig. 5b ), within the concentration range used in our above experiments. Recombinant HA-tagged RARA was then overexpressed in SH-SY5Y cells and confirmed that HA-RARA primarily accumulated in the nucleus by Western blot (Fig. 5c ). We then incubated the nuclear fraction with RA-immobilized beads (Supplementary Fig. 9b ) and eluted RARA with DMSO or 1.0 μM RA. Western blots confirmed that RA could elute significantly greater concentrations of RARA-HA than DMSO (Supplementary Fig. 9c ), thus validating that RA could be used to pull down RARA. Interestingly, MTK could also elute RARA-HA from RA-immobilized beads in a dose-dependent manner (Fig. 5d ), suggesting that MTK could potentially competitively bind to RARA, blocking interaction with RA. As RARs can form heterodimers with retinoid X receptors (RXRs) to regulate gene transcription via interaction with RAREs, 12 , 33 , 43 we treated SH-SY5Y cells with MTK or DMSO and immunoprecipitated RXRB. Western blots indicated that significantly less RARA could be pulled down by RXRB in the presence of MTK (Fig. 5e ), implying that MTK could negatively impact RARA-RXRB heterodimer formation, potentially suppressing their transcriptional regulatory functions. Fig. 5. Open in a new tab Montelukast inhibits RA signaling through competitively binding to RARA and disrupting the RAR-RXR heterodimer. a The in sillico virtual docking simulation analysis for the binding between RARA (green) and montelukast (yellow) compared with retinoic acid (magenta). PDB, protein data bank. b MTK concentration-response curve with His-tagged recombinant RARA protein (RARA-His) in MST assay. The estimated Kd of MTK to RARA-His is shown. n = 4 from 4 independent experiments. c Nuclear and cytoplasmic fraction of SH-SY5Y cells overexpressing RARA-HA. The protein level of RARA-HA in each fraction was detected. Tubulin and Lamin B1 (LMNB1) were the marker proteins in the cytoplasmic and nuclear fractions, respectively. d Immunoblot analysis for the eluted HA-tagged RARA (RARA-HA) protein from RA-immobilized beads by the increasing level of MTK. The concentration of MTK ranged from 0 to 1000 μM. The input sample was from the proteins on RA-immobilized beads before being eluted by MTK. Similar results were observed in 2 independent experiments. e Immunoblot analysis and quantification for the HA-tagged RARA co-immunoprecipitated with Flag-tagged RXRB under the treatment of MTK in SH-SY5Y cells. Cells transfected with RARA-HA and RXRB-Flag plasmids were treated with MTK for 4 h before subjected to co-IP with anti-Flag beads. The grey value ratio of RARA-HA protein co-immunoprecipitated with RXRB-Flag protein was calculated and normalized to DMSO group. Both bands around 70 kDa represent RXRB-Flag. n = 4. f Flow cytometry analysis of SH-SY5Y cells co-transfected with RARA -nYFP and RXRB -cYFP. The median Venus fluorescence intensity was normalized to DMSO treatment group of each mutant of RARA. n = 7–9 from at least three independent experiments. g Synopsis model of MTK inducing ASD via inhibiting RA signaling pathway. CysLT1, cysteinyl leukotriene 1. Data are presented as means ± SD ( b ) or means ± SEM ( e , f ). e One-way ANOVA with Tukey’s post hoc test. f Two-way ANOVA with Bonferroni’s post hoc test To pinpoint the specific RARA residues involved in MTK-RARA interaction, Biovia Discovery Studio 2021 Visualizer ( https://discover.3ds.com/discovery-studio-visualizer-download ) was employed to identify possible hydrogen bonding, hydrophobic interactions, and other non-bonded interactions in RARA binding with MTK or RA (Supplementary Fig. 9d ). Among the five amino acid residues (C235, R276, S287, F302 and K399) with high possibility of interaction with MTK, four were identical (R276, S287, F302) or close to (K234) residues that coordinated interaction with RA (Supplementary Fig. 9d ). We then conducted bimolecular fluorescence complementation (BiFC) assays to test whether these putative MTK-binding sites were essential for RARA-RXRB interaction (Supplementary Fig. 9e ). Flow cytometry analysis of SH-SY5Y cells co-expressing RARA -nVFP and RXRB -cVFP showed that VFP signal was significantly decreased in the presence of MTK compared to DMSO-treated controls (Fig. 5f ). We then generated RARA -nVFP variants with individual mutations at each RA-interacting residue ( RARA C235A , RARA R276A , RARA S287A , RARA F302A and RARA K399A ) and found that fluorescence intensity arising from close proximity of RARA and RXRB was unimpeded by MTK in BiFC assays of RARA C235A , RARA R276A , RARA S287A and RARA F302A (Fig. 5f ), suggesting these residues were responsible for MTK (and RA) binding with RARA. By contrast, RARA K399A showed partially decreased fluorescence, indicated limited, but not abolished, interaction with RXRB. Co-IP assays further verified that MTK disruption of RARA-RXRB interaction was blocked by a RARA C235A/R276A/S287A/F302A quadruple mutant (4 mut) (Supplementary Fig. 9f ). Altogether, these results suggested that MTK could suppress RA signaling potentially through antagonizing endogenous RA in binding to RARA and block the RA-induced formation of RAR-RXR heterodimers. Discussion Here we reported that MTK, an FDA-approved anti-asthma medicine that targets the leukotriene type I receptors, was identified in a screening for inhibitors of the RA signaling pathway. MTK was found to directly bind to the RA receptor, RARA, and disrupt RARA-RXRB heterodimerization, thus disrupting RA-dependent transcriptional regulation. This newly identified effect of MTK increased the risk of ASD in children with MTK use during early childhood, altered brain patterning in human brain organoids, and resulted in autistic-like behaviors in rats (Fig. 5g ). Our findings revealed MTK as a novel environmental risk factor for ASD. Environmental (non-genetic) risk factors are believed to account for over 50% of ASD etiology. 5 , 6 , 44 Early life exposure to chemicals such as endocrine-disrupting chemicals (EDCs) or pollutants might affect brain development and significantly increase the risk of neurodevelopmental disorders and language delay 8 in the offspring, with the underlying mechanisms incompletely understood. It remains particularly challenging to systematically identify such chemical risk factors for ASD as there is no central etiological mechanism for ASD that would afford a screening against a given library. Recently, work by several groups, including our own, has established a causal link between disrupted RA signaling and the etiology of some subtypes of human ASD, 16 , 45 and maternal exposure to triclosan, an anti-microbe agent that we found to be an effective antagonist of cellular RA signaling, could indeed significantly induce autistic-like behaviors in the offspring of rats maternally exposed to the chemical. 21 Therefore, screening chemicals and drugs that disrupt cellular RA signaling would provide a novel avenue to identifying potential environmental risk factors for ASD. In our first screening among 58 drugs and chemicals that may be exposed to pregnant women and newborns, MTK stood out by markedly suppressing cellular RA signaling (Fig. 1 ). Designed to block leukotriene D4 (LTD4)-induced contractions, MTK passed an extensive list of safety tests in animals and humans before the final FDA approval for treating asthma and allergic rhinitis. 46 – 48 For a relatively long period, MTK has kept an excellent safety profile in its clinical applications, including human newborns, which has underscored its increasing global use in either various brand names or generic forms. MTK receives millions of prescriptions alone in the U.S.A. each year, despite a boxed safety warnings required by FDA due to its neuropsychiatric influences in children and adults. 49 , 50 To address its potential psychiatric effects on pediatric users, we carried out a multi-center Chinese cohort study to investigate the possible association between the diagnosed ASD cases and MTK prescriptions within 3 years after birth. Indeed, an increased risk of childhood autism (adjusted Odds Ratio, 1.377; 95% CI, 1.032 to 1.838) was recorded when those exposed to MTK during early life (Table 1 ). Consistently, MTK was found to elicit autistic-like behaviors in rat models after prenatal or early postnatal exposure (Fig. 2 ). We then went on to dissect the mechanism for how MTK disrupted neuronal RA signaling in brain organoids. RA signaling plays critical roles in cell differentiation and tissue development throughout the mammalian lifespan, 12 , 51 , 52 , especially in patterning during early neural development. 40 Since MTK could efficiently down-regulate RA signaling (Fig. 1 ), it was natural to reason that MTK might alter brain patterning during early development, which could ultimately lead to increasing the risk of ASD. Previous studies established the central roles of RA signaling in regulating the emergence of axial patterning of the central nervous system (CNS) in a temporospatial-specific manner. 53 , 54 For instance, RA signaling refines rostro-caudal neural tube identity during the mid/late streak stage in gastrulating embryos by repressing rostral factors, consequently activating caudal factors, inducing caudalization of the neural tube, which limits forebrain development while promoting hindbrain expansion. 54 In the developing telencephalon, RA signaling regulates dorsal/ventral (D/V) patterning, but not anterior/posterior (A/P) patterning, 54 and specifies the intermediate stage of neural progenitors between dorsal and ventral identities. 55 In this study, we found that dorsal forebrain markers were upregulated while ventral forebrain markers were downregulated in MTK- and DEAB-treated organoids with impaired RA signaling. Moreover, cell populations were reduced in the midbrain/hindbrain cluster after MTK or DEAB treatment (Fig. 3 ). Another study investigating RA function in cortical development by Shibata et al. 38 reported that the anterior-posterior neocortical RA gradient is enriched in the prefrontal cortex (PFC) of humans and macaques. Additionally, deficiency of the RA-degrading enzyme CYP26B1 leads to an increase in RA signaling dorsolaterally. Ziffra et al. 56 also found that vitamin A treatment was associated with an increased population of cells expressing SATB2, a dorsal forebrain marker. 45 Altogether, MTK could alter patterning during brain organoid development mainly through disrupting with RA signaling. Integrative analysis of data from bulk RNA-seq, scRNA-seq, as well as immunofluorescence indicated an imbalance in excitatory/inhibitory (E/I) neurons (Fig. 4 ), one of the key features in ASD etiology. 57 , 58 In cerebral organoids derived from induced pluripotent stem cells (iPSCs) isolated from idiopathic ASD patients, the production of excessive GABAergic inhibitory neurons through up-regulation of FOXG1 resulted in an imbalanced glutamatergic/GABAergic neuron ratio. 59 Paulsen and colleagues also observed the asynchronous development of GABAergic neurons and deep layer-projecting excitatory neurons in organoids with reduced expression of three ASD risk genes. 60 The resulting E/I imbalance induced abnormal circuit activity in calcium imaging, which could ultimately lead to ASD. Here, we uncovered the cellular mechanisms underlying MTK-mediated E/I imbalance-induced ASD via inhibition of RA signaling using brain organoids. These studies highlighted the value and potential of brain organoids as a platform by sophisticatedly recapitulating essential features of human brains during early development to assess not only the toxicity of drugs or chemicals but also their possible psychiatric effects. 35 , 61 – 63 The increasing applications of brain organoid techniques are offering unprecedented opportunities to dissect the etiological mechanisms underlying neuropsychiatric disorders, including ASD, testing new drugs for future therapeutic development, and even re-assessing the safety of FDA-approved drugs as indicated above. In the canonical RA signaling pathway, RA plays its role by binding to the retinoic acid receptors (RARs), followed by nuclear translocation and heterodimerization with retinoid X receptors (RXRs) to modulate gene expression driven by RARE motif(s) in the enhancer regions of target genes. 64 In the current study, in silico docking simulations predicted that MTK could directly compete with RA for binding to RARA at exactly the same site. Immunoprecipitation and transactivation assays indicated that MTK could indeed impair RA-RARA interaction via competitive bind and disrupt RAR-RXR heterodimer formation (Fig. 5 ). In principle, such a competitive binding could also occur with the heterodimers formed between the other members of RARs-RXRs, e.g. with even stronger interaction (showing lower Kd for association), which might collectively contribute to the observations made with the experimental or populational studies (Figs. 1 – 3 ). This mechanistical finding is also echoing an early work that implicated functional impacts of missense mutations in RARA in ASD patients. 18 It is truly remarkable to note that MTK was originally developed as an antagonist of the leukotriene receptors, which are located at the cellular membrane, to treat asthma. On one hand, the finding of RARA as a novel interactor of MTK is otherwise fully understandable, since off-target effects are nothing but too common for almost any drug. On the other hand, our work touches several truly critical aspects of current pharmaceutical development, especially when the off-target effect of a commonly prescribed drug is linked to ASD, a psychiatric disorder that is affecting an ever-increasing human population whose genetic compositions are not obviously associated with the disease etiology. By noting that RARA is an intracellular interactor of MTK, some modifications in MTK structure to prevent its entry into the cells might make it “safe” by physically sequestering from its potential partners. In summary, through a systematic screening for chemicals that may impair RA signaling and potentially affect brain development and synapse functionality, here we identified that MTK, an FDA-approved anti-asthma medicine, might be a previously unrecognized risk factor for ASD. This work has multiple important ramifications which include, but are not limited to, highlighting the key importance in regularly assessing the psychiatric and behavioral effects of drugs that are developed for targets supposedly of no obvious relevance in central nerve systems. Besides, brain organoid is once again proven to be a critically important and efficient substitute for human brain during early developmental stages, whose applications, among many others, may help identify and eliminate potential risk factors for psychiatric disorders, with ASD as but one example. Materials and methods Please see detailed information for the Materials and Methods in the supplementary files (Design of the custom compound library, Compound screening, Data processing and analysis, Cell culture and transfection, Compound treatment and fluorescence imaging of neuron, Behavioral tests, Animal tissue collection, Determination of retinoic acid, Western blotting, Immunofluorescence staining, Organoid immunofluorescence, Ribosome profiling, Bulk RNA sequencing, Protein‑protein interaction analysis, Single cell RNA‑seq, RT‑qPCR, Electrophysiology, Nuclear/cytoplasmic fractionation, Protein expression and purification, Microscale thermophoresis). Plasmid construction pGL 3 -3×RARE-TK-luciferase reporter 65 was a kind gift from Dr. Jian-hua Tong. The plasmid pCDH-3×RARE-TK-hrGFP was constructed as previously described. 21 In brief, three copies of RA responsive element (RARE, GTTCACcgaaaGTTCAC) were cloned in a reverse-reverse-forward sequence upstream of a thymidine kinase (TK) promoter, followed by a humanized Renilla reniformis green fluorescent protein (hrGFP) gene. The pRL-TK- Renilla luciferase reporter was purchased from Promega Corporation . For mammalian expression, RARA and RXRB were obtained by PCR amplification from hORFeome V5.1 cDNA library and subsequently insert into BamHI and NotI sites of pcDNA3.1 vector with a C-terminal HA tag, or HindIII and XhoI sites of pcDNA3.0 vector with a C-terminal Flag tag, respectively. DNA sequences of the N-terminal yellow fluorescence protein (nYFP), 155–amino acid, and C-terminal YFP (cYFP), 84–amino acid fragments were PCR amplified from pRK-venus plasmid, which was a kind gift from Dr. Li Xue. These DNA fragments were cloned downstream of RARA and RXRB , respectively, with a linker sequence (GGAGGAGGATCT). The RARA mutants were constructed by site-directed mutagenesis as previously reported. 66 For prokaryotic expression, RARA cDNA was inserted into BamHI and XhoI of pET28a vector with 6× His tag. All constructs were confirmed by DNA sequencing. Dual luciferase reporter assay The SH-SY5Y cells in 24-well plates were transfected with 200 ng pGL3-3 x RARE-TK- luciferase reporter and 20 ng pRL-TK-Renilla luciferase reporter (Promega) per well, with the help of polyethyleneimine (PEI, PolySciencies) in Opti-MEM (Gibco). The medium was then changed to VPSFM with 1% FBS 6 h after transfection. On the next day, 20 h after transfection, the montelukast sodium (TargetMol) was diluted in VPSFM and added to cells. And 6 h later, the cells were supplemented with DMSO or RA (at a final concentration of 1.0 μM) overnight. After 16 h treatment with RA, the cells were Iysed and detected for luminescence using Dual-Luciferase Reporter Assay kit (Promega) according to the manufacturer’s instructions. Study population The research protocol of the clinical study on Chinese cohort was approved by the Ethics Committee of Children’s Hospital of Chongqing Medical University with the approval number (2018) IRB (STUDY) NO. 121. This clinical study was registered in the Chinese Clinical Trial Registry (ChiCTR) (Registration number: ChiCTR2000031194). Participation of the children in this study was voluntary, and informed consent was obtained from their guardians. All procedures were performed in compliance with the Declaration of Helsinki, and the confidentiality of the participants was strictly maintained throughout the study. For the Chinese cohort, a total of 1578 ASD patients and 1555 typically developing (TD) participants aged 2–7 years old from 12 cities (apart from Changchun) in China from China Multicenter Preschool Autism Program (CMPAP) 29 were initially included in the study in 2018–2020. We excluded 402 participants due to the incomplete version of questionnaire, 24 participants out of age range, 101 participants who did not fill in the questionnaire, and 135 participants without the information about montelukast use. The final cohort consisted of 1232 ASD patients (1013 boys and 219 girls) and 1239 TD participants (763 boys and 476 girls). All the ASD patients were diagnosed by a professional developmental pediatrician in their local hospital through a series of structured interviews according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria. Parents of autistic children and typically developing children filled out their questionnaires as required. The questionnaires included questions about the general characteristics of the child, such as name, age, gender, region, premature infant, medication history from birth to 3 years old, whether they were the only child in their family and whether the child with autism is retrogressive; simultaneously, the general characteristics of the parents, such as the maternal parity, maternal age at conception, parental history of mental disorders and their educational background. Animals and oral gavage administration Sprague-Dawley rats were acquired from the Chongqing Medical University Animal Care Center and housed in standard animal cages under specified pathogen-free (SPF) laboratory conditions in the laboratory colony of the Children’s Hospital of Chongqing Medical University (permission number -SCXK(Yu)2017-0012). Rats used for experiments were generated by mating the female rats that weighed more than 220.0 g and aged 9-10 weeks with healthy male rats. Offspring of both male and female were used. All animal experiments were conducted in line with the National Institutes of Health guide for the care and use of Laboratory Animals. The protocol was approved by the Animal Experimentation Ethics Committee of Chongqing Medical University and Shanghai Institute of Biological Sciences. Montelukast sodium (Acros Organics) was dissolved in ethyl alcohol for maximum solubility and then diluted (1:9 ratio) with a 0.9% saline to achieve the desired concentration as 1.0 mg/ml, 4.0 mg/ml and 10.0 mg/ml, before oral administration at the dose of 1.0, 4.0, or 10.0 mg/kg body weight. The pregnant rats were divided into six groups, with at least three rats in each group. Three groups were orally administered daily with either montelukast sodium (1 mg/kg body weight or 10 mg/kg body weight) or solvent since gestation day 7.5 till gestation day 21.5. For the other two groups of rats, their offspring were treated with montelukast sodium (4 mg/kg body weight) or solvent from postnatal day 14 to 28, after postnatal exposure to 4 mg/kg MTK, the RA supplement group received a daily oral gavage of 6.0 mg/kg retinoic acid (Sigma, dissolved in corn oil at 2.5 mg/mL) for 2 weeks. 67 SD rats in the prenatal exposure group were obtained from Chongqing Medical University, while SD rats in the postnatal exposure group were purchased from Chongqing Enbi Biotechnology Co., Ltd. The postnatal period was chosen as within 3 years of human age. 68 All pubs were weighted once a week since they were born. The administration doses for rats were determined referring to the clinical dose in humans. The recommended dose of montelukast sodium for human is 10 mg/day for adults and 4.0 mg/day for children at the age of 1–5 years. 23 The oral administration of montelukast sodium at 10 mg/kg body weight to rats could make the serum level resemble the highest montelukast plasma concentration in humans treated every day with montelukast at the clinical dose of 10.0 mg. 69 The other two lower doses also come within the pharmacological range. Human cerebral organoid culture and compound treatment Human cerebral organoids were derived from human embryonic stem cell line H9 by following the previous protocol described by Lancaster et al. 62 In brief, H9 human embryonic stem cells (WiCell), verified with normal karyotype and contamination-free, were cultured on matrigel-coated plates in mTeSR1 medium (Stem Cell Technologies, 05850). For cerebral organoids differentiation, colonies were dissociated with EDTA and Accutase to acquire single-cell suspension. The suspensions were then plated into a low-binding V-bottom 96-well plate with 9000 cells per well to induce EB formation. For the first 3 days, cells were cultured in mTeSR1 supplemented with 50.0 μM ROCK inhibitor (Selleckchem, S6390). Then, ROCK inhibitor was removed and EBs were transferred into neural induction medium on day 5. This DMEM/F12 (Invitrogen, 11330-032) medium is composed of 1.0% GlutaMAX (Invitrogen, 35050-038), 1.0% N2 (Invitrogen, 17502048), 1.0% MEM-NEAA (Sigma, M7145), and 0.1% heparin supplement (Sigma, H3149). After 6 days, EBs were embedded into Matrigel droplets cultured in improved without vitamin A on orbital shaker until day 20. To promote terminal differentiation, organoids were fed with fresh differentiation medium with the exception of using 2% B27 with vitamin A (Invitrogen, 17504044) and maintained in suspension until harvesting. The differentiation medium contains DMEM:F12/Neurobasal (both Gibco) (1:1), 1.0% N2, 1.0% MEM-NEAA, 2.0% B27 without vitamin A (Invitrogen, 12587010) and 0.1% heparin supplement. The medium with the addition of DMSO or 18.5 μM montelukast or 10.0 μM DEAB was refreshed every day from day 20 to day 60. The size of organoids upon different treatment were imaged on indicated days and measured using ImageJ at different culture time points. Same batches of organoids were treated with different compounds simultaneously, so that they shared the same DMSO-treated group. In silico docking The 3D crystal structure of RARA binding with its ligand retinoic acid was retrieved from the protein data bank (PDB: 3A9E, resolution 2.75 Å). The flexible docking of montelukast to RARA was performed and the docking conformation with the highest binding free energy (−14.5 kcal/mol) was selected. The 2D protein–compound interactions were depicted by utilizing Discovery Studio 2021 visualizer software (Biovia). RA immobilization RA was dissolved into Coupling Buffer (BupH MES Buffered Saline Pack, Thermo Fisher), before mixed with CarboxyLink Coupling Gel (Thermo Fisher), which was equilibrated by Coupling Buffer. The EDC (Thermo Fisher) solution was added to RA/gel slurry the moment it dissolved into Coupling Buffer, followed by 3-hour constant rotation at room temperature. When the reaction solution containing unbound RA drained down to the top of the gel bed, 1.0 M NaCl wash solution was added to the gels 5 times in order to thoroughly wash away unbound RA. RA was immobilized to the gel through a covalent amido bond between the amino group of CarboxyLink Coupling Gel and the carboxyl group of RA. Competitive elution assay After transfection with pcDNA3.1-RARA-HA plasmid for 36 h, the SH-SY5Y cells were subjected to nuclear and cytoplasmic fraction separation. Balanced with Co-IP buffer 3 times, the RA-immobilized beads were incubated in the rest of the nuclear supernatant and rotated at 4 °C overnight. The next day, RA-immobilized beads were washed 5 times with Co-IP buffer containing 1% DMSO. Each time included a 10 min constant rotation in the cold room. Then the beads were equally aliquoted into 1.5 mL EP tubes, 1/10 volume of which were collected as Input sample. The rest were eluted with equal volume of Co-IP buffer supplemented with montelukast sodium or retinoic acid of indicated concentrations at room temperature by shaking at 1000 rpm for 15 minutes. After centrifugation at 2000 × g , the supernatant was collected for western blot analysis. Co‑immunoprecipitation The SH-SY5Y cells were transfected with indicated plasmids for 40 h prior to 4-hour treatment of compounds. The cells were lysed on ice with Co-IP buffer (150.0 mM NaCl, 50.0 mM Tris, 10.0 mM EDTA·Na 2 , 1.0% NP-40, [pH 7.4]) plus protease inhibitor cocktail. After sonication and centrifugation, the supernatant was incubated with anti-Flag M2 beads (Sigma-Aldrich) at 4 °C overnight. 1/10 volume of the lysate was transferred into a new tube before the incubation and used as ‘Input’ sample. On the next day, beads were washed with Co-IP buffer in the cold room 5 times, 10 min-spin included each time. The pelleted beads were resuspended with SDS loading buffer and boiled for 10 min for western blot analysis. Bi-FC assay The cells transfected with pcDNA3.1- RARA -nYFP and pcDNA3.0- RXRB -cYFP plasmids for 40 h before 4 h treatment with DMSO or 12.5 μM montelukast in VP-SFM. The cells were digested and suspended with PBS, and subjected to flow cytometry analysis on Beckman CytoFlex. The median fluorescence intensity of positive cells was calculated using FlowJo software. Statistical analysis For the Chinese cohort, logistic regression analysis was used to determine the relationship between montelukast use within the first three years of life and the risk of ASD. We controlled the following confounding factors in our analysis, including gender, age, maternal education level, paternal education level, parental history of mental disorders, maternal age at conception, maternal parity, premature infant and one-child family. The number of rats or cells subjected to each analysis was stated. Statistical analysis by the unpaired Student’s t -test with Welch’s correction, one-way ANOVA with Dunnett’s or Tukey’s post hoc test, two-way repeated-measures ANOVA with Bonferroni’s or Dunnett’s post hoc test was performed with the use of Prism 8.0 software. All data were means ± SEM except for the MST data as means ± SD. Individual P values were presented. Supplementary information 41392_2026_2665_MOESM1_ESM.docx (9.3MB, docx) Supplementary Materials for Anti-asthma drug Montelukast induces autistic behaviors via disrupting neuronal retinoic acid signaling Acknowledgements The authors are particularly thankful to Dr. Lu Chen of Stanford University for her insightful discussions! We acknowledge the excellent support from Ming Chen and his team members, especially Dr. Shu-Jue Lan in the Chemical Biology Core Facility and Meng Wu in the Molecular Biology Core Facility, support from Wei Bian and her team in the Cell Biology Core Facility in the Center for Excellence in Molecular Cell Science (CEMCS). We thank Dr. Jian-Hua Tong and Dr. Li Xue from Ruijin Hospital in Shanghai Jiao Tong University School of Medicine for sharing the pGL 3 -3×RARE-TK-luciferase reporter and the pRK-Venus plasmid. We thank Min Zhu from the College of Life Sciences at Shanghai Normal University for the great help in uploading sequence data to the GEO database. We also thank Ms. Lin Ye and all the other members of our laboratory for their assistance and support. This work was supported by the National Science and Technology Innovation 2030 Major Project of China (2021ZD0203900), the Noncommunicable Chronic Diseases-National Science and Technology Major Project (2026ZD0553200), the National Natural Science Foundations of China (292253302, 32200777, 32271019, 32300810, 12411530079), and China Postdoctoral Science Foundation (2022M720793, 2023M730446), and Postdoctoral Science Foundation of Chongqing Natural Science Foundation, China (No. CSTB2023NSCQ-BHX0117). We appreciate the advice and assistance from Dr. Isaac Greenhut, PhD, ELS, with language editing. Author contributions R.G.H. conceived and supervised the whole study. T.-Y.L., S.B., X.-M.S., and H.-Y.Z. led the animal study, brain organoid study, cohort study and multiomics analyses, respectively. Z.-J.H., Q.-H.Wu, Y.-L.L., Z.-M.G., Z.-W.L., J.Z., M.-X.C., Q.L., Y.-R.F., S.-H.Y., F.Y., M.-Q.D., J.-H.X, J.-L.X., H.-Y.X., S.-L.Y, M.L., H.Z., B.Y., H.-Y.X., and Y.-M. W. performed the experiments. T-Y. L., J.Z., Q.L. and Q.-H.Wu. collected, organized, and analyzed the Chinese cohort of ASD data, supervised by T.Y., J.C., L.C., and T.-Y.L. G.W. and M.M. analyzed the scRNA-seq data supervised by S.B. and H.-Y.Z. M.-H.Z. analyzed bulk RNA-seq data. Q.-H.Wang performed a docking simulation supervised by H.-T.Y. The HPLC-MS/MS experiment was performed under the supervision by J.-K.M. and T.-Y.L. R.-G.H., S.B., Z.-J.H., Y.-L.L., and Q.-H.Wu wrote the manuscript. All authors read, and approved the final version of the manuscript. Data availability Materials requests should be addressed to Dr. Rong-Gui Hu. Data, including all bulk RNA-seq, ribo-seq, and scRNA-seq data reported in this paper, have been deposited at the Gene Expression Omnibus with accession numbers GEO: GSE241074 , GSE241071 , GSE232669 . Competing interests The authors declare no competing interests. Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. These authors contributed equally: Zi-Jian Hao, Qiong-Hui Wu, Ya-Li Li, Zhen-Ming Guo, Zheng-Wei Li These authors jointly supervised this work: Hui-Ying Zhao, Xiao-Ming Shi, Shan Bian, Ting-Yu Li, Rong-Gui Hu Contributor Information Hui-Ying Zhao, Email: zhaohy8@mail.sysu.edu.cn. Xiao-Ming Shi, Email: shixm@chinacdc.cn. Shan Bian, Email: shan_bian@tongji.edu.cn. Ting-Yu Li, Email: tyli@vip.sina.com. Rong-Gui Hu, Email: coryhu@zju.edu.cn. Supplementary information The online version contains supplementary material available at 10.1038/s41392-026-02665-w. References 1. Lord, C. et al. Autism spectrum disorder. Nat. Rev. Dis. Prim. 6 , 5 (2020). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 2. Muhle, R. A., Reed, H. E., Stratigos, K. A. & Veenstra-VanderWeele, J. The emerging clinical neuroscience of autism spectrum disorder: a review. JAMA Psychiatry 75 , 514–523 (2018). [ DOI ] [ PubMed ] [ Google Scholar ] 3. Bourgeron, T. From the genetic architecture to synaptic plasticity in autism spectrum disorder. Nat. Rev. Neurosci. 16 , 551–563 (2015). [ DOI ] [ PubMed ] [ Google Scholar ] 4. Rodin, R. E. et al. The landscape of somatic mutation in cerebral cortex of autistic and neurotypical individuals revealed by ultra-deep whole-genome sequencing. Nat. Neurosci. 24 , 176–185 (2021). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 5. Hallmayer, J. et al. Genetic heritability and shared environmental factors among twin pairs with autism. Arch. Gen. Psychiatry 68 , 1095–1102 (2011). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 6. Vorstman, J. A. S. et al. Autism genetics: opportunities and challenges for clinical translation. Nat. Rev. Genet. 18 , 362–376 (2017). [ DOI ] [ PubMed ] [ Google Scholar ] 7. Raz, R. et al. Autism spectrum disorder and particulate matter air pollution before, during, and after pregnancy: a nested case-control analysis within the Nurses’ Health Study II Cohort. Environ. Health Perspect. 123 , 264–270 (2015). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 8. Caporale, N. et al. From cohorts to molecules: adverse impacts of endocrine disrupting mixtures. Science 375 , eabe8244 (2022). [ DOI ] [ PubMed ] [ Google Scholar ] 9. Pearson, B. L. et al. Identification of chemicals that mimic transcriptional changes associated with autism, brain aging and neurodegeneration. Nat. Commun. 7 , 11173 (2016). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 10. Chen, L., Lau, A. G. & Sarti, F. Synaptic retinoic acid signaling and homeostatic synaptic plasticity. Neuropharmacology 78 , 3–12 (2014). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 11. Maden, M. Retinoic acid in the development, regeneration and maintenance of the nervous system. Nat. Rev. Neurosci. 8 , 755–765 (2007). [ DOI ] [ PubMed ] [ Google Scholar ] 12. Ghyselinck, N. B. & Duester, G. Retinoic acid signaling pathways. Development 146 , 673–683 (2019). [ DOI ] [ PMC free article ] [ PubMed ] 13. Wang, T. W., Zhang, H. & Parent, J. M. Retinoic acid regulates postnatal neurogenesis in the murine subventricular zone-olfactory bulb pathway. Development 132 , 2721–2732 (2005). [ DOI ] [ PubMed ] [ Google Scholar ] 14. Ranjan, S. & Nasser, J. A. Nutritional status of individuals with autism spectrum disorders: do we know enough? Adv. Nutr. 6 , 397–407 (2015). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 15. Liu, X. et al. Correlation between nutrition and symptoms: nutritional survey of children with autism spectrum disorder in Chongqing, China. Nutrients 8 , 294 (2016). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 16. Xu, X. et al. Excessive UBE3A dosage impairs retinoic acid signaling and synaptic plasticity in autism spectrum disorders. Cell Res. 28 , 48–68 (2018). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 17. Yang, L. et al. Retinoic acid supplementation rescues the social deficits in Fmr1 knockout mice. Front. Genet. 13 , 928393 (2022). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 18. Chen, S. et al. An interactome perturbation framework prioritizes damaging missense mutations for developmental disorders. Nat. Genet. 50 , 1032–1040 (2018). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 19. Sayad, A., Noroozi, R., Omrani, M. D., Taheri, M. & Ghafouri-Fard, S. Retinoic acid-related orphan receptor alpha (RORA) variants are associated with autism spectrum disorder. Metab. Brain Dis. 32 , 1595–1601 (2017). [ DOI ] [ PubMed ] [ Google Scholar ] 20. Moreno-Ramos, O. A., Olivares, A. M., Haider, N. B., de Autismo, L. C. & Lattig, M. C. Whole-exome sequencing in a South American cohort links ALDH1A3, FOXN1 and retinoic acid regulation pathways to autism spectrum disorders. PLoS One 10 , e0135927 (2015). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 21. Hao, Z. et al. Maternal exposure to triclosan constitutes a yet unrecognized risk factor for autism spectrum disorders. Cell Res. 29 , 866–869 (2019). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 22. Wu, Q. et al. Early life exposure to triclosan from antimicrobial daily necessities may increase the potential risk of autism spectrum disorder: a multicenter study in China. Ecotoxicol. Environ. Saf. 247 , 114197 (2022). [ DOI ] [ PubMed ] [ Google Scholar ] 23. Wermuth, H. R., Badri, T., and Takov, V. Montelukast , (In StatPearls (StatPearls Publishing), 2020). [ PubMed ] 24. Nayak, A. A review of Montelukast in the treatment of asthma and allergic rhinitis. Expert Opin. Pharmacother. 5 , 679–686 (2004). [ DOI ] [ PubMed ] [ Google Scholar ] 25. Law, S. W. Y., Wong, A. Y. S., Anand, S., Wong, I. C. K. & Chan, E. W. Neuropsychiatric events associated with leukotriene-modifying agents: a systematic review. Drug Saf. 41 , 253–265 (2018). [ DOI ] [ PubMed ] [ Google Scholar ] 26. Lee, Y. J. & Kim, C. K. Montelukast use over the past 20 years: monitoring of its effects and safety issues. Clin. Exp. Pediatr. 63 , 376–381 (2020). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 27. Administration, N. M. P. Announcement on revising the instructions for montelukast preparations. Vol. JGXX-2025-10186 (2025). 28. Aoto, J., Nam, C. I., Poon, M. M., Ting, P. & Chen, L. Synaptic signaling by all-trans retinoic acid in homeostatic synaptic plasticity. Neuron 60 , 308–320 (2008). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 29. Yang, T. et al. China Multi-Center Preschool Autism Project (CMPAP): design and methodologies to identify clinical symptom features and biomarkers of autism spectrum disorders. Front Psychiatry 11 , 613519 (2020). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 30. Duffney, L. J. et al. Autism-like deficits in Shank3-deficient mice are rescued by targeting actin regulators. Cell Rep. 11 , 1400–1413 (2015). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 31. Stoner, R. et al. Patches of disorganization in the neocortex of children with autism. N. Engl. J. Med. 370 , 1209–1219 (2014). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 32. Niederreither, K. & Dollé, P. Retinoic acid in development: towards an integrated view. Nat. Rev. Genet. 9 , 541–553 (2008). [ DOI ] [ PubMed ] [ Google Scholar ] 33. Cunningham, T. J. & Duester, G. Mechanisms of retinoic acid signalling and its roles in organ and limb development. Nat. Rev. Mol. Cell Biol. 16 , 110–123 (2015). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 34. Zhou, Y., Song, H. & Ming, G. L. Genetics of human brain development. Nat. Rev. Genet. 25 , 26–45 (2024). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 35. Corsini, N. S. & Knoblich, J. A. Human organoids: new strategies and methods for analyzing human development and disease. Cell 185 , 2756–2769 (2022). [ DOI ] [ PubMed ] [ Google Scholar ] 36. Renner, M. et al. Self-organized developmental patterning and differentiation in cerebral organoids. Embo j. 36 , 1316–1329 (2017). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 37. Balmer, J. E. & Blomhoff, R. Gene expression regulation by retinoic acid. J. Lipid Res 43 , 1773–1808 (2002). [ DOI ] [ PubMed ] [ Google Scholar ] 38. Shibata, M. et al. Regulation of prefrontal patterning and connectivity by retinoic acid. Nature 598 , 483–488 (2021). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 39. De Santis, R., Etoc, F., Rosado-Olivieri, E. A. & Brivanlou, A. H. Self-organization of human dorsal-ventral forebrain structures by light induced SHH. Nat. Commun. 12 , 6768 (2021). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 40. Petros, T. J., Tyson, J. A. & Anderson, S. A. Pluripotent stem cells for the study of CNS development. Front. Mol. Neurosci. 4 , 30 (2011). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 41. Kanton, S., Treutlein, B. & Camp, J. G. Single-cell genomic analysis of human cerebral organoids. Methods Cell Biol. 159 , 229–256 (2020). [ DOI ] [ PubMed ] [ Google Scholar ] 42. Dollé, P., Ruberte, E., Leroy, P., Morriss-Kay, G. & Chambon, P. Retinoic acid receptors and cellular retinoid binding proteins. I. A systematic study of their differential pattern of transcription during mouse organogenesis. Development 110 , 1133–1151 (1990). [ DOI ] [ PubMed ] [ Google Scholar ] 43. Kumar, S. & Duester, G. SnapShot: retinoic acid signaling. Cell 147 , 1422–1422.e1421 (2011). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 44. Sandin, S. et al. The familial risk of autism. Jama 311 , 1770–1777 (2014). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 45. Zhang, Z., et al. The fragile X mutation impairs homeostatic plasticity in human neurons by blocking synaptic retinoic acid signaling. Sci. Transl. Med. 10 (2018). [ DOI ] [ PMC free article ] [ PubMed ] 46. Nayak, A. & Langdon, R. B. Montelukast in the treatment of allergic rhinitis: an evidence-based review. Drugs 67 , 887–901 (2007). [ DOI ] [ PubMed ] [ Google Scholar ] 47. Schoors, D. F. et al. Single dose pharmacokinetics, safety and tolerability of MK-0476, a new leukotriene D4-receptor antagonist, in healthy volunteers. Br. J. Clin. Pharm. 40 , 277–280 (1995). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 48. Storms, W. et al. Clinical safety and tolerability of montelukast, a leukotriene receptor antagonist, in controlled clinical trials in patients aged > or = 6 years. Clin. Exp. Allergy 31 , 77–87 (2001). [ DOI ] [ PubMed ] [ Google Scholar ] 49. Schumock, G. T. et al. Association between leukotriene-modifying agents and suicide: what is the evidence? Drug Saf. 34 , 533–544 (2011). [ DOI ] [ PubMed ] [ Google Scholar ] 50. Clarridge, K., Chin, S., Eworuke, E. & Seymour, S. A boxed warning for montelukast: the FDA perspective. J. Allergy Clin. Immunol. Pr. 9 , 2638–2641 (2021). [ DOI ] [ PubMed ] [ Google Scholar ] 51. Manna, P. R. et al. Up-regulation of steroid biosynthesis by retinoid signaling: Implications for aging. Mech. Ageing Dev. 150 , 74–82 (2015). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 52. Iturbide, A. et al. Retinoic acid signaling is critical during the totipotency window in early mammalian development. Nat. Struct. Mol. Biol. 28 , 521–532 (2021). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 53. Durston, A. J. et al. Retinoic acid causes an anteroposterior transformation in the developing central nervous system. Nature 340 , 140–144 (1989). [ DOI ] [ PubMed ] [ Google Scholar ] 54. Simeone, A. et al. Retinoic acid induces stage-specific antero-posterior transformation of rostral central nervous system. Mech. Dev. 51 , 83–98 (1995). [ DOI ] [ PubMed ] [ Google Scholar ] 55. Marklund, M. et al. Retinoic acid signalling specifies intermediate character in the developing telencephalon. Development 131 , 4323–4332 (2004). [ DOI ] [ PubMed ] [ Google Scholar ] 56. Ziffra, R. S. et al. Single-cell epigenomics reveals mechanisms of human cortical development. Nature 598 , 205–213 (2021). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 57. Gogolla, N. et al. Common circuit defect of excitatory-inhibitory balance in mouse models of autism. J. Neurodev. Disord. 1 , 172–181 (2009). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 58. Zhong, S. et al. A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex. Nature 555 , 524–528 (2018). [ DOI ] [ PubMed ] [ Google Scholar ] 59. Mariani, J. et al. FOXG1-dependent dysregulation of GABA/glutamate neuron differentiation in autism spectrum disorders. Cell 162 , 375–390 (2015). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 60. Paulsen, B. et al. Autism genes converge on asynchronous development of shared neuron classes. Nature 602 , 268–273 (2022). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 61. Li, C. et al. Single-cell brain organoid screening identifies developmental defects in autism. Nature 621 , 373–380 (2023). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 62. Chiaradia, I. & Lancaster, M. A. Brain organoids for the study of human neurobiology at the interface of in vitro and in vivo. Nat. Neurosci. 23 , 1496–1508 (2020). [ DOI ] [ PubMed ] [ Google Scholar ] 63. Kelley, K. W. & Pașca, S. P. Human brain organogenesis: toward a cellular understanding of development and disease. Cell 185 , 42–61 (2022). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 64. Rhinn, M. & Dollé, P. Retinoic acid signalling during development. Development 139 , 843–858 (2012). [ DOI ] [ PubMed ] [ Google Scholar ] 65. Zhao, Q. et al. Rapid induction of cAMP/PKA pathway during retinoic acid-induced acute promyelocytic leukemia cell differentiation. Leukemia 18 , 285–292 (2004). [ DOI ] [ PubMed ] [ Google Scholar ] 66. Liu, H. & Naismith, J. H. An efficient one-step site-directed deletion, insertion, single and multiple-site plasmid mutagenesis protocol. BMC Biotechnol. 8 , 91 (2008). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 67. Liu, H. et al. Valproic acid induces autism-like synaptic and behavioral deficits by disrupting histone acetylation of prefrontal cortex ALDH1A1 in rats. Front. Neurosci. 15 , 641284 (2021). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 68. Sengupta, P. The laboratory rat: relating its age with human’s. Int. J. Prev. Med. 4 , 624–630 (2013). [ PMC free article ] [ PubMed ] [ Google Scholar ] 69. Marschallinger, J. et al. Structural and functional rejuvenation of the aged brain by an approved anti-asthmatic drug. Nat. Commun. 6 , 8466 (2015). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Supplementary Materials 41392_2026_2665_MOESM1_ESM.docx (9.3MB, docx) Supplementary Materials for Anti-asthma drug Montelukast induces autistic behaviors via disrupting neuronal retinoic acid signaling Data Availability Statement Materials requests should be addressed to Dr. Rong-Gui Hu. Data, including all bulk RNA-seq, ribo-seq, and scRNA-seq data reported in this paper, have been deposited at the Gene Expression Omnibus with accession numbers GEO: GSE241074 , GSE241071 , GSE232669 . Articles from Signal Transduction and Targeted Therapy are provided here courtesy of Nature Publishing Group ACTIONS View on publisher site PDF (4.7 MB) Cite Collections Permalink RESOURCES Similar articles Cited by other articles Links to NCBI Databases Follow NCBI NCBI on X (formerly known as Twitter) NCBI on Facebook NCBI on LinkedIn NCBI on GitHub NCBI RSS feed Connect with NLM NLM on X (formerly known as Twitter) NLM on Facebook NLM on YouTube National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894 Web Policies FOIA HHS Vulnerability Disclosure Help Accessibility Careers NLM NIH HHS USA.gov Back to Top

Related documents

• Anti-asthma drug montelukast induces autistic behaviors via disrupting neuronal retinoic acid signaling#257185
• A Study of Oxytocin for the Treatment of Social Impairment in Individuals With High Functioning Autism Spectrum Disorder#831293
• Intranasal Oxytocin in the Treatment of Autism#1072680
• A Pilot Treatment Study of Insulin-Like Growth Factor-1 (IGF-1) in Autism Spectrum Disorder#828114
• Sulforaphane for the Treatment of Young Men With Autism Spectrum Disorder#1137487