Deciphering autism heterogeneity: a molecular stratification approach in four mouse models

doi:10.21203/rs.3.rs-4235527/v1

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Deciphering autism heterogeneity: a molecular stratification approach in four mouse models

https://doi.org/10.21203/rs.3.rs-4235527/v1

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published 04 Oct, 2024

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Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by impairments in social interaction, communication, as well as restrained or stereotyped behaviors. The inherent heterogeneity within the autism spectrum poses challenges for developing effective pharmacological treatments targeting core features. Successful clinical trials require the identification of robust markers to enable patient stratification. In this study, we identified molecular markers within the oxytocin and immediate early gene families across five interconnected brain structures of the social circuit. We used wild-type and four heterogeneous ASD mouse models, each exhibiting unique behavioral features along the autism spectrum. While dysregulations in the oxytocin family were model-specific, immediate early genes displayed widespread alterations, reflecting global changes in social plasticity in the four models. Through integrative analysis, we identified Egr1, Foxp1, Homer1a, Oxt and Oxtr as five robust and discriminant molecular markers that allowed successful stratification of the four models. Importantly, our stratification demonstrated predictive values when challenged with a fifth mouse model or identifying subgroups of mice potentially responsive to oxytocin treatment. Beyond providing insights into oxytocin and immediate early gene mRNA dynamics, this proof-of-concept study represents a significant step toward potential stratification of individuals with ASD. This work has implications for the success of clinical trials and the development of personalized medicine in autism.

Biological sciences/Neuroscience

Health sciences/Biomarkers

Health sciences/Diseases/Psychiatric disorders/Autism spectrum disorders

Autism spectrum disorder

social interaction

molecular markers

oxytocin

synaptic plasticity

patient stratification

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition, with a prevalence of 1% [1]. ASD is characterized by impairments in social communication and interaction, as well as repetitive or stereotyped behaviors [2], associated with various co-occurring features. Despite the identification of over thousands of genes associated with ASD, the etiology of most cases remains idiopathic. Early behavioral interventions address social features, but heavily relies on intensive and costly training [3, 4]. Although atypical antipsychotics have gained approval for targeting some co-occurring features, their efficacy is often limited, and they are associated with side effects [5, 6]. To date, clinical trials for drugs specifically targeting core features have encountered setbacks due to their lack of efficacy [7, 8]. The failure of these trials can be attributed to the inherent heterogeneity observed across the spectrum. This inherent diversity within the patient population underscores the critical necessity for stratification within the ASD spectrum. The success of future trials relies on the stratification of subgroups within the autism spectrum, which necessitates the identification of reliable markers.

The neuropeptides oxytocin (OT) and its paralog vasopressin (AVP), along with their corresponding receptors, regulate social behaviors across the lifespan [9–12]. These neuropeptides are predominantly synthesized in neurons of the paraventricular (PVN) and supraoptic (SON) nuclei of the hypothalamus [13–16] and project extensively to brain structures involved in emotional and social circuit, such as the prefrontal cortex and striatum, where their receptors are expressed, or the pituitary [17–19]. There is emerging evidence suggesting a potential link between dysregulation of the oxytocin system and the etiology of ASD (for reviews [20–23]), particularly the association with pathogenic variants in oxytocin (OXT), oxytocin receptor (OXTR), and vasopressin receptor 1A (AVPR1A) genes (SFARI Gene). Additionally, decreased OXT and OXTR mRNA levels have been reported in the brains of individuals with ASD or related conditions [24, 25] and mouse models of ASD [23, 26]. Notably, deletion of these genes in mice has been shown to induce autism-like traits (for review [8]). Nevertheless, the administration of OT has yielded inconsistent effects on social traits in individuals with ASD [8, 27, 28]. Intriguingly, a study has suggested that the concentration of OT in the blood of individuals diagnosed with autism could predict the outcome of oxytocin administration [29]. However, OT peptides are rapidly released in response to both social and non-social cues [30–34], as well as stressful conditions [35–39]. It remains unclear whether the OT and AVP system can serve as shared or specific molecular markers for individuals with ASD.

Individuals with ASD exhibit global alterations in synaptic plasticity, as evidenced by multiple studies [40–43]. Synaptic plasticity, a vital adaptive process responding to various stimuli, including social interactions [44–46], plays a pivotal role in shaping neural circuits. Immediate early gene (IEG) mRNAs constitute a key component of this process, as they are rapidly transcribed, and translated within 30 minutes to 2 hours in response to diverse stimuli. Following this initial response, IEGs orchestrate long-term plasticity, notably by initiating the second wave of late genes within 4 to 24 hours for some IEG that are transcription factors. Notably, IEGs emerge as central factors potentially influencing impairments in social interactions. Dysregulation of the expression levels of IEGs has been observed in both plasma and brain tissues of people with ASD [47–51]. These dysregulations are not limited to clinical observations, as animal models of ASD also display altered IEG expression [52–54]. Whether specific IEGs can serve as predictive markers for distinct autism subtypes remains an open avenue for investigation.

In this study, we used three distinct genetic mouse models — Shank3, Fmr1 and Oprm1 knockout (KO) mice — alongside mice subjected to early chronic social isolation, encompassing diverse etiologies to replicate the autism spectrum. Our investigation revealed that each model exhibited a distinctive behavioral signature, mimicking the complexity of the spectrum. We pinpointed Oxt, Oxtr, Foxp1, Egr1, and Homer1a as robust molecular markers within the OT and IEG gene families. These markers exhibited specific responses to social interactions in wild-type (WT) mice and significant dysregulations in the aforementioned four mouse models across five structures of the social circuit. Using these five markers, we successfully demonstrate the first proof-of-concept for the stratification of mouse models, differentiating subtypes within the spectrum of autism. The identification of these specific markers offers a promising avenue for tailoring personalized medical help to individuals with autism.

Animals

All mouse breeding, care and experimental procedures were in accordance with the European and French Directives and approved by the local ethical committee CEEA Val de Loire N°19 and the French ministry of teaching, research and innovation (APAFIS #18035-2018121213436249). Two months old socially naive males and females from Oprm1 KO (JAX stock #007559) [55], Shank3 KO (JAX stock #017688) [56], Fmr1 KO and females Fmr1^+/− (provided by Rob Willensem; [57]), Arc KO (JAX stock #007662) [58] and WT animals were maintained on a 12-hour light/dark regular cycle, with food and water ad libitum and controlled temperature (21°C) and humidity (50%). Mice were raised in the mixed C57BL/6J;129S2 background in social groups of 3–4 individuals. Animals named “isolated”, were exposed to chronic social isolation after weaning and for at least 4 weeks prior to behavioral tests.

Behavior experiments

All behavioral tests were sequentially performed in a dim light quiet room, using standardized equipment and are detailed in the supplementary methods. Briefly, social interactions were performed in the 3-chambered and in the reciprocal social interaction tests with a sex- and age-matched unknown mouse or a cage mate in an open field. Non-social interactions were tested with an object also in open field arenas. Perseveration and cognitive flexibility in a spatial task was assessed in the Y-maze test while repetitive and stereotyped behaviors were examined in the motor stereotypy test, assays that have been previously characterized for mouse models of ASD [59].

Quantitative PCR

Mice were dissected at basal conditions or 0.75 (45 minutes), 2 or 6 hours following a social or an object interaction. Within 5 minutes, 1 mm thick brain slices were generated using a coronal mouse brain matrix. Prefrontal cortex (PFC), nucleus accumbens (NAC), caudate putamen (CPU), paraventricular (PVN) and supraoptic (SON) nuclei (Figure S1E) were collected using a 2 mm diameter puncher (two punches for lateralized regions) and immediately frozen until further use. Total RNAs were extracted according to the ZymoResearch's instructions (Direct-zol™ RNA Microprep and Miniprep kit). The cDNAs were generated from 0.5 µg or 0.25 µg of total RNAs using the SensiFast reverse transcriptase kit and quantitative PCR (qPCR) was performed in triplicates according to ONEGreen Fast® kit with 1 µL of cDNA and 1 µM of each validated couple of primers (Table S1). The following qPCR protocol was applied for 40 cycles: 95°C for 5s, 60°C for 15s, and 60°C for 30s. All materials, reagents, protocols and suppliers are detailed in Table S2.

Data modeling and correlations

All statistical analyses were performed using R (version 4.2.2) [60]. Animal outliers (+/- 3 standard deviations) were removed. Variability between cohorts (Figure S1) was assessed using Principal Component Analysis (PCA) with the FactoMineR package [61], and for qPCR, corrections were applied using the ComBat sva package [62]. For behavioral data, Kruskal-Wallis tests with Dunn's post hoc tests were conducted using the rstatix package [63]. P-values were adjusted with Benjamini-Hochberg correction [64]. A complete linear model was fitted for qPCR data, encompassing variables such as time, social interaction or mouse line, and their interactions. Post-hoc tests, based on estimated marginal means with Tukey p-value correction, were conducted using the emmeans package [65] to compare social interaction at each time point, the different time point for each interaction, and mouse models to WT mice. In addition, the analyses were conducted separately as PCA revealed distinct clusters among the structures: one comprising PFC, NAC, and CPU, and the other involving PVN and SON (Figure S1). Additionally, in WT mice, clustering of genes and median expressions was performed using the pheatmap package. Furthermore, integration of qPCR and behavioral data was performed using DIABLO (Multiblock (s)PLS-DA) implemented in the mixOmics package [66, 67]. The compromise parameter was set at 0.75 to maximize correlation between qPCR and behavioral datasets. Linear discriminant analysis (LDA) was performed using Egr1, Foxp1, Homer1a, Oxt and Oxtr, on each mouse with less than 5 missing values across all structures, using the MASS package [68]. LDA predicted the class membership of Arc KO mice that were not considered during model fitting (i.e., the model with most similarities). Finally, on the data of Shank3 and Fmr1 KO mice and only on the OT markers, hierarchical clustering on the principal components of PCA (HCPC) was performed using the FactoMineR package [61].

Distinct behavioral profiles across autism spectrum in four mouse models

We examined the behavioral profiles of Fmr1 and Shank3 KO mice, modeling Fragile X and Phelan-McDermid syndromes, respectively, along with Oprm1 KO and chronically isolated mice (Figs. 1, S2-S3, Table S3), all previously published as mouse models of ASD and neurodevelopmental conditions [56, 69–71]. To capture a comprehensive view of their social responses, we exposed these models to distinct social interactions: one involving a family member (e.g. a cage mate, "SI mate") and the other with an unknown conspecific ("SI unknown"), mimicking the daily life of individuals with autism. Additionally, we included a non-social interaction condition with an object ("NSI object"), as control.

In the open field, none of the models exhibited altered behavior following SI mate or NSI object (Table S3). Fmr1 KO mice demonstrated robust social impairments, indicated by a decrease in both total time and mean duration engaged in nose contacts with an unknown mouse both in the reciprocal and three-chambered tests (Fig. 1A, D). This impairment was also observed in heterozygous females in the sociability phase of the three-chambered test (Figure S2A-C). In contrast, Shank3 KO mice displayed impaired social novelty, evident in their lack of preference for a new mouse over a familiar one (Fig. 1B). Surprisingly, Oprm1 KO and isolated mice did not exhibit the expected social impairments as reported previously [69, 71]. Under standard conditions, Oprm1 KO mice only displayed a lack of mate preference in the three-chambered test (Fig. 1C). Elevating light intensity from 15 to 40 lux to strengthen anxious-like behavior revealed social interaction impairments with an unknown animal in Oprm1 KO mice, as evidenced by a reduction in the time spent in nose contact during both the sociability and social novelty phase of the three-chambered tests, as opposed to WT mice tested in dim light conditions (Figure S2D-F). This finding suggests a potential manifestation of induced social impairments or social anxiety — a phenotype situated at the periphery of the autism spectrum.

Regarding stereotyped behaviors, Shank3 KO mice spent more time in self-grooming, accompanied by an increased number of head shakes and a decrease in the time spent digging and in the number of rearing events compared to WT mice (Figs. 1E-F, S3A-B). Conversely, Oprm1 and Fmr1 KO mice demonstrated a reduction in self-grooming time, while isolated mice exhibited a decreased number of head shakes (Fig. 1E-F). Concerning co-occurring features, none of the models exhibited impaired cognitive flexibility in the Y maze, nor did they show locomotion impairments in the open field (Figure S3C-D). Notably, Shank3 KO mice displayed anxious-like behaviors, spending more time in the periphery of the open field arena compared to WT mice (Figure S3E).

In summary, the four models presented distinct behavioral features, with Fmr1 and Shank3 KO mice displaying the most severe phenotypes along the autism spectrum.

Identification of specific molecular markers of social interactions in WT mice

Given that molecular markers for social interactions remain unknown, our primary objective was to identify them, starting with WT mice. We focused on two mRNA families, recognized as potential markers of autism [8, 23, 42, 72]: the OT family, encompassing Oxt and Avp, and their receptors (Oxtr, Avpr1a, Avpr1b), and IEGs and neurotrophic factors, including Arc, Egr1, Fos, Fosb, Jun, Homer1a, Foxp1, Gdnf and Bdnf. We investigated their kinetic profiles up to 6 hours after SI mate, SI unknown, and NSI object, as well as 6 hours following acute social isolation, a condition with negative social valence. We studied their profiles across five key structures within the social circuit: the paraventricular (PVN) and supraoptic nuclei (SON) of the hypothalamus, the caudate putamen (CPU) and nucleus accumbens (NAC) of the striatum, and the medial prefrontal cortex (PFC). To ensure the specificity of our findings, we ruled out circadian or sex biases within the two mRNA families (Figure S4A, Table S4). Notably, none of these mRNAs displayed distinct patterns within a 6-hour period or between males and females, except for Foxp1, which exhibited sexually dimorphic expression in the SON. Interestingly, Arc in the SON was the only mRNAs down-regulated by acute social isolation from cage mates (Figure S4B).

Markers were selected based on significant differences observed between one SI and NSI object, between SI unknown and SI mate, as well as differences between time points exclusively for one SI (Figures S5-S7). We applied a minimum criterion of significance, requiring differences to be present in at least two different brain structures. Consequently, we identified key markers, specifically Avp, Avpr1a, Oxt and Oxtr mRNAs within the OT family, along with Arc, Egr1, Fos, Foxp1 and Homer1a within the IEG family. Notably, SI unknown at 45 minutes emerged as the most distinct stimulus with a rapid and transient increase of mRNAs at 45 minutes, such as Oxtr expression in the NAC and CPU and Egr1, and Homer1a in the PVN and SON (Figs. 2, S5-S7, Table S4). In contrast, SI mate induced sustained regulations, like Avp and Oxt mRNAs in the PVN and SON. Overall, no single structure or mRNA distinctly stood out for a particular social stimulus (Fig. 2). Remarkably, our dataset revealed robust correlations between mRNAs, such as a 0.92 positive correlation between Oxt and Avp (Figure S8A-B). Noteworthy, Foxp1, Homer1a and Egr1 displayed a negative correlation with Oxt and Avp (Figure S8C), suggesting a potential interplay between them.

In summary, we identified Arc, Avp, Avpr1a, Egr1, Fos, Foxp1, Homer1a, Oxt and Oxtr as specific molecular markers of social interactions in WT mice. These markers were selected to assess their levels in the four mouse models, both under basal conditions and following SI unknown at 45 minutes — the most discriminant interaction and time point.

Distinct dysregulations within the oxytocin family among mouse models

Previous studies have proposed OT, AVP, or their receptors as potential common biomarkers of autism [8, 23, 72]. To explore shared dysregulations within the OT family, using Oprm1, Fmr1, Shank3 KO and isolated mice, we assessed alterations in Oxt, Avp, Oxtr and Avpr1a expression following SI unknown at 45 minutes and under basal conditions (Figs. 3, S9-S10, Table S5). In the CPU, Avp was not induced across all four mouse models, as well as Oxtr in three models, compared to WT animals (Fig. 3A). Additionally, we identified two shared dysregulations between two models — Avpr1a in the SON and Oxt in the NAC (Figures S9-S10). However, the majority of dysregulations were rather specific for each mouse model. Fmr1 KO mice displayed a global decrease in the expression of all four mRNAs in the PVN, along with Avp, Oxt, Oxtr in the NAC, and Oxt and Avpr1a in the SON (Figs. 3B, S9-S10). In contrast, isolated mice exhibited an overall increase in Avp, Oxt and Oxtr expression in the PFC (Fig. 3C). Shank3 KO mice did not show additional dysregulations, while in the CPU, Oxt and Avpr1a were also down-regulated in Oprm1 KO mice (Figure S9).

To explore the potential for shared dysregulations beyond the initial OT family, we extended our assessment to include Cd38, involved in OT secretion, and Avpr1b, along with generalist enzymes involved in peptide biosynthesis (Pcsk1, Pcsk2, Pcsk5 and Cpe) and degradation (Lnpep, Ctsa and Rnpep; Figure S11, Table S5). Strikingly, only three shared dysregulations — Cpe, Ctsa, Rnpep in the NAC — were observed among two models (Figure S11). Once again, the majority of dysregulations demonstrated model specificity. In addition to the shared dysregulations, Fmr1 KO mice exhibited 6 unique down-regulations, particularly in the NAC and PVN. Isolated mice displayed mostly up-regulations in the PVN and PFC, along with up- and down-regulations in other structures. Shank3 KO mice showed a down-regulation of Cd38 in the NAC and PFC. Notably, none of these mRNAs were affected in Oprm1 KO mice. To identify the most discriminant mRNAs for model stratification, we applied stringent criteria, requiring a minimum of 6 total and 4 unique dysregulations across three structures and three models. Within the OT family, only Oxt, Avp and Oxtr met these criteria, spanning four structures and four models (Figures S9-S11).

In conclusion, Oxt, Avp and Oxtr emerge as the most discriminant markers within the OT family among the four models. These findings highlight their potential utility in stratifying autism mouse models based on their unique molecular signatures, rather than revealing shared mechanisms.

Widespread dysregulations in social plasticity across mouse models

Akin to the OT family, we investigated dysregulations in social plasticity by testing Arc, Egr1, Fos, Foxp1 and Homer1a — markers identified in WT mice — across the four models following SI unknown at 45 minutes and under basal conditions. Our results revealed extensive dysregulations in IEGs across all five structures and mouse models (Figs. 4, S12-S13, Table S5). We identified 6 shared dysregulations in all four models (SON: Fos, Foxp1 and Homer1a; PVN, Egr1 and Homer1a; CPU: Foxp1), as well as 4 additional dysregulations in three models (SON: Egr1; PFC: Homer1a; NAC: Fos; CPU: Homer1a). However, the underlying causes of these dysregulations varied among the mouse models. In the PVN and SON, IEGs remained at basal levels following SI unknown in Oprm1 KO mice, while in the other models, IEGs were already induced under basal conditions compared to WT mice. Conversely, in the CPU and PFC, the opposite trend was observed. Applying the same criteria as the OT family, we identified Egr1, Fos, Foxp1 and Homer1a, with Homer1a standing out with 16 total and 7 unique dysregulations across all five structures and all four models. Surprisingly, in contrast to the findings in WT animals, Arc was only dysregulated in the PFC of Shank3 KO mice (Figure S12).

In conclusion, our study unveils widespread defects in social plasticity across the models. Egr1, Fos, Foxp1 and Homer1a emerge as the most dysregulated IEGs in the four mouse models, providing valuable markers for model stratification.

Molecular stratification of mouse models using Egr1, Foxp1, Homer1a, Oxt and Oxtr

Integration of qPCR data in the four ASD mouse models following SI unknown aimed to verify connections between our mRNA candidates and specific behavioral parameters (Figure S14). Component 1 of this analysis unveiled a positive association (SON: Foxp1) and negative associations (CPU and PFC: Fos and Homer1a; PFC: Foxp1) with the time spent and mean duration of nose contacts (Figure S14A). These associations were primarily driven by isolated mice, aligning with the observed increase in nose contacts within this specific cohort (Figure S14C). Conversely, positive associations were found between Fos and Homer1a in the PFC and Fos in the CPU, with the number of rearing events and Oprm1 KO mice, indicating a potential opposition between spatial exploration and social interaction. Additionally, grooming behavior was associated with Shank3 KO mice, thus validating our analysis (Figure S14B). This association showed a positive correlation with Homer1a in the PVN and a negative correlation with Oxtr in the PFC. All together, these findings confirm the roles of Fos, Foxp1, Homer1a and Oxtr as molecular markers linked to core autism-like features in mice.

In the last analysis, we crossed data from WT mice and the four mouse models, identifying Egr1, Foxp1, Homer1a, Oxt and Oxtr, as the most dysregulated molecular markers. Avp was excluded due to its high correlation with Oxt that could bias the model towards their shared dysregulations. Employing these five robust molecular markers, we conducted a proof-of-concept for potential stratification among the four mouse models (Fig. 5). The linear discriminant analysis (LDA) integrated molecular data from these markers across the five brain structures in the four models under basal conditions and following SI unknown (Fig. 5A-B). The analysis unveiled distinct classifications, identifying Oprm1 KO (LD1) and isolated mice (LD2) as different models. Although Shank3 and Fmr1 KO mice clustered together, they exhibited individual characteristics (LD3). Among the markers, levels of Oxt (LD1-3) and Homer1a in the CPU (LD1), as well as Homer1a in the NAC (LD2-3) and SON (LD1) exerted the most significant influence on the stratification, followed by Oxtr across the structures.

To challenge our stratification, we tested Arc KO mice, previously documented to manifest social interaction impairments [58, 73]. Based on the five markers, LDA predicted that Arc KO mice would be the closest to Fmr1 KO mice, followed by Shank3 KO mice (Fig. 5A). Indeed, Arc KO mice displayed an intermediate phenotype, showing social interaction impairments coupled with increased self-grooming (Figure S15). Both molecular and behavioral data confirmed Arc KO mice as a valid mouse model with ASD features. Additionally, we employed our stratification to predict the potential responsiveness of subgroups (e.g., Fmr1 and Shank3 KO mice) to treatment administration (Fig. 5C). Solely considering the Oxt and Oxtr markers, we pinpointed cluster 1, consisting of Fmr1 KO and Shank3 KO mice with low levels of Oxt and Oxtr, suggesting a potential positive response to oxytocin treatment in this subgroup.

In conclusion, this study showed the first successful proof-of-concept for the stratification of four mouse models using five molecular markers, providing a potential framework for stratification of individuals with autism.

Our findings elucidate distinct dynamics in the expression patterns of the two mRNA families across five brain structures in response to two types of social interactions in WT mice. Notably, SI mate elicited a sustained pattern of expression, unlike NSI object, which displayed a rapid and transient increase, indicating a response to the novelty of the test environment, or no response. SI unknown exhibited a unique pattern within 45 minutes, setting it apart from the other two stimuli. Furthermore, our results suggest a distinct molecular mechanism of activation for each social interaction in these five structures. SI unknown predominantly impacts the OT family in the CPU, NAC and PVN, as well as the IEG family in the PVN, SON and PFC. Conversely, SI mate primarily influences the OT family in the PVN, along with the IEG family in the PFC. While previous studies have highlighted the role of the CPU in facilitating mate interactions as a habitual behavior, and the NAC in orchestrating responses to SI unknown [74], our results reveal a more intricate and nuanced molecular mechanism across these structures.

Surprisingly, our findings unveiled a remarkably high positive correlation between Oxt and Avp mRNA levels in both WT mice and mouse models. Oxt and Avp, being paralog genes, are located only 11 kbp apart from each other (4 kbp in humans). Despite the identification of specific elements in this intergenic region in vitro that potentially promote neuron specificity [75], our results suggest that both mRNAs undergo similar regulation, and common regulatory elements may have been evolutionarily conserved. The robust correlation observed between Oxt and Avp mRNAs emphasizes the importance of considering both peptides in research studies.

Within the OT system, our results revealed distinct molecular dysregulations in each mouse model. Particularly, levels of Oxt and Avp mRNAs, as well as Oxtr across the structures delineated the four mouse models. Noteworthy, Shank3 KO mice exhibited Cd38 downregulation in the PFC and NAC. Given its association with social memory and recognition impairments [76], and the social novelty phenotype displayed by Shank3 KO mice, our results position Cd38 as a potential marker of social memory-related conditions. In contrast to the OT family, our results underscore widespread IEG dysregulations across brain structures in all four models, confirming synaptic plasticity impairment as a major hallmark of ASD. Notably, Egr1, Foxp1 and Homer1a emerge as the most robust markers of social interactions in WT animals and the most dysregulated IEGs in the four models. These findings align with their previous association with ASD in both individuals with autism and mouse models [52, 77–81].

Our results revealed robust impairments in social interaction with an unknown conspecific in Fmr1 and Shank3 KO mice, accompanied by pronounced motor stereotypies in Shank3 KO mice, aligning with previous reports [82, 83]. Conversely, Oprm1 KO and chronically isolated mice did not exhibit the expected social impairments [69, 71]. Their phenotype may have been influenced by the experimenter’s sex [84], predominantly females in this study, as well as by experimental conditions designed to reduce animal stress. Indeed, a slight increase in light induced social impairments in Oprm1 KO mice. Recently, it has been proposed that housing conditions and the duration of social isolation may interfere with social impairments previously observed in chronically isolated animals [85, 86]. Interestingly, none of the mouse models exhibited impaired social interaction with a cage mate, aligning with reports suggesting that interactions within the family environment were more manageable for children with ASD [87]. Notably, the stratification of the models using the five molecular markers — Egr1, Foxp1, Homer1a, Oxt, and Oxtr — consistently aligned with behavioral data. This analysis accurately predicted the molecular underpinnings of the observed behavioral differences between Oprm1 KO and isolated mice and the other two models, as well as Arc KO mice. Despite their distinct profiles, it unveiled shared dysregulations in both Fmr1 and Shank3 KO mice, providing valuable insights into potential links with their respective social phenotypes and responsiveness to treatments.

In conclusion, our study offers valuable insights into the dynamics of OT and IEG mRNAs in WT animals and their dysregulations in mouse models of ASD across five structures within the social and emotional neuronal circuit. Our findings not only enable the stratification of the four mouse models, but also allow for the identification of subgroups within these models. The stratification of other mouse models of ASD, such as Cntnap2, Magel2 or Oxtr KO mice [88–90], and different species, including Shank3 KO rats [91], would enhance the predictive value of the five molecular markers in individuals affected by autism. Exploring additional structures within this circuit, such as the amygdala and lateral septum, could further contribute to the stratification of models. Nevertheless, future research employing omic approaches beyond the oxytocin and synaptic plasticity families is essential to identify more molecular markers and potentially uncover novel therapeutic targets. This study represents the first proof-of-concept for the potential stratification of individuals with autism using mouse models, with the aim of improving the success of clinical trials and personalized treatment for ASD. Additionally, our work holds promise for precise and faster ASD diagnostics, complementing behavioral screenings [2]. The development of these molecular markers into screening assays (e.g., secreted molecules dependent of Egr1 or Foxp1 transcription factor activity), using accessible fluids like blood or cerebrospinal fluid, could streamline diagnostics, as demonstrated by the feasibility of detecting elevated Arc proteins or low OT peptides in the blood of children with ASD [29, 50].

Conflict of interest

The authors declare no conflict of interest.

Author contributions

CG, AD, OV, LD, EP and LP designed and performed the experiments; CG, AD, OV, LD, EP and LP contributed to the data collection; CG, AD, OV, LD, GL and LP contributed to the interpretation of data; GL performed all statistical analysis, data modeling and integration; CG, GL and LP wrote the original drafts; CG, AD, OV, LD, EP, GL and LP reviewed and edited the manuscript; LP contributed to the funding acquisition, project conceptualization and supervision.

ACKNOWLEDGEMENTS

Mouse breeding and care was performed at INRAE Animal Physiology Facility (https://doi.org/10.15454/1.5573896321728955E12). This work has benefited from the facilities and expertise of the “Informatique Scientifique Locale et Analyses de Données” (ISLANDe) of the UMR PRC, INRAE. We used ChatGPT, developed by OpenAI, for assistance with English editing. We thank Dr E. Valjent, Dr R. Yvinec, Dr P. Crepieux, Dr P. Chamero, Dr A. Carvalho and Dr J. Collet for their advice on the manuscript.

This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 851231). This work was supported by the INRAE “SOCIALOME” project (PAF_29). LPP, CG and AD acknowledge the LabEx MabImprove (grant ANR-10-LABX-53-01) for the financial support of CG and AD PhD’s co-fund.

Data availability statement

All the data are available in supplementary Tables. Movies of behavioral experiments are available upon request.

Supplementary information is available at MP’s website.

ASD autism spectrum disorders

AVP vasopressin

CPU caudate putamen

HCPC hierarchical clustering on the principal components of PCA

IEG immediate early gene

KO knockout

LDA linear discriminant analysis

NAC nucleus accumbens

NSI non-social interaction

OT oxytocin

PCA Principal Component Analysis

PFC prefrontal cortex

PVN paraventricular nucleus of the hypothalamus

SI social interaction

SON supraoptic nucleus of the hypothalamus

WT wild-type

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The authors have declared there is NO conflict of interest to disclose

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TableS1Primers.xlsx
Table S1
TableS2Materialsandreagents.xlsx
Table S2
TableS3behavior.xlsx
Table S3
TableS4qPCRWT.xlsx
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TableS5qPCRASD.xlsx
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Deciphering autism heterogeneity: a molecular stratification approach in four mouse models

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Journal Publication

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Abstract

Figures

INTRODUCTION

MATERIALS AND METHODS

Animals

Behavior experiments

Quantitative PCR

Data modeling and correlations

RESULTS

Distinct behavioral profiles across autism spectrum in four mouse models

Identification of specific molecular markers of social interactions in WT mice

Distinct dysregulations within the oxytocin family among mouse models

Widespread dysregulations in social plasticity across mouse models

DISCUSSION

Declarations

Conflict of interest

Author contributions

ACKNOWLEDGEMENTS

Data availability statement

Abbreviations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1