Unraveling the brain expression of BDNF in a mouse model of Anorexia Nervosa

Unraveling the brain expression of BDNF in a mouse model of Anorexia Nervosa | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Unraveling the brain expression of BDNF in a mouse model of Anorexia Nervosa Nicolas Ramoz, Jingxian CAO, Nicolas Lebrun, Shiou-ping Chen, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6260210/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Oct, 2025 Read the published version in Translational Psychiatry → Version 1 posted 10 You are reading this latest preprint version Abstract Anorexia nervosa (AN) is a complex psychiatric disorder characterized by severe caloric restriction and distorted body image, leading to significant psychological and physiological complications. Brain-derived neurotrophic factor (BDNF) plays a critical role in cognitive function and metabolic regulation. BDNF has been identified as a genetic risk factor for AN. This study examines the effects of food restriction, refeeding and short-term refeeding on the expression of BDNF and its receptor (tropomyosin receptor kinase B TrkB/Ntrk2) in key brain regions involved in reward and cognitive function. We assessed BDNF mRNA levels in the dorsal striatum (DS), nucleus accumbens (NAc), ventral tegmental area (VTA), and prefrontal cortex (PFC) of AN-like mice subjected to different feeding regimes combined with or without physical activity. Cognitive flexibility was assessed using the Y-maze test. Whole RNA sequencing was also performed to analyse gene expression changes. Food restriction induced a transient decrease in cognitive flexibility and significantly decreased BDNF expression in the DS and PFC. Progressive refeeding restored BDNF in the DS but not the PFC. Short refeeding restored BDNF levels to baseline. TrkB expression is increased by restriction only in the PFC. The presence of a running wheel cancelled these effects, suggesting an interaction between physical activity and diet. Pathway analysis of dysregulated genes revealed enrichment in immune regulation and cell-cell communication pathways. These findings highlight the complex relationship between diet, exercise, and brain function in AN and suggest avenues for further research into the clinical relevance of BDNF and TrkB as biomarkers of eating disorders. Biological sciences/Physiology Biological sciences/Neuroscience/Molecular neuroscience Brain Derived Neurotrophic Factor tropomyosin receptor kinase B/Neurotrophic tyrosine kinase receptor type 2 Anorexia nervosa Food restriction Animal model Cognitive flexibility Reward system Figures Figure 1 Figure 2 Figure 3 Introduction Please have a look at courier new font provided for text in article. Anorexia nervosa (AN) is a complex and potentially life-threatening eating disorder characterized by self-imposed dietary restriction and usually excessive physical exercise 1 . Individuals with AN experience severe weight loss due to caloric restriction, leading to a number of somatic complications such as hormonal and metabolic changes, and loss of bone density 2 , 3 . In addition, AN is now considered as a metabo-psychiatric disorder 4 because metabolic changes, such as weight loss and hormonal changes 5 , are often associated with psychiatric symptoms. These include high levels of anxiety and depression associated with intense fear of weight gain, distorted body image, obsessive behaviors related to food and body shape and impaired cognitive flexibility and decision-making, which further complicate the clinical presentation and treatment approach 6 – 8 . The disorder predominantly affects adolescents and young adults, with a higher prevalence in women, accounting for up to 90% of cases 9 . Epidemiological studies estimate that the prevalence of AN to be around 1% in young adult females 10 . Despite various therapeutic approaches, there is currently no cure for AN, and many individuals experience recurrent relapses. It is estimated that 9–52% of patients relapse after treatment 11 , underlining the urgent need to understand the factors that contribute to relapse. Furthermore, given also that AN has the highest mortality rate of any psychiatric disorder 12 – 14 , there is an urgent need to improve treatment outcomes and reduce the high risk of mortality associated with this disorder 13 . Genome-wide association studies (GWAS) and case-controlled studies have identified several genetic risk factors associated with the disorder 4 , 15 – 17 . Among these, a specific allele of the brain-derived neurotrophic factor (BDNF) gene, specifically the Val66Met polymorphism (also known as rs6265), has received considerable attention since 2004 18 , and is now under intense scrutiny 119, 20 . Known for its role in neuronal development, neurogenesis, and synaptic plasticity 21 , 22 , BDNF has recently emerged as a key player in metabolic regulation, influencing processes both centrally in the brain and peripherally. Centrally, BDNF influences hypothalamic circuits that regulate energy balance, appetite, and satiety, contributing to its anorexic effects 23 . Peripherally, BDNF can directly affect metabolic processes, including increasing lipid oxidation and energy expenditure, ultimately leading to weight loss and increased physical activity levels 24 , highlighting a comprehensive effect of BDNF on metabolic health and physical behavior. The Val66Met mutation in the BDNF gene, has been implicated in several metabolic diseases and psychiatric disorders, particularly in AN, affecting both neuroplasticity and metabolic regulation 19 , 20 . In patients with AN, Met variant carriers show altered reward function, as evidenced by increased reward circuit activity in response to images of thinness in the ventral striatum, a key region for reward processing 25 , 26 . Finding animal models that mimic the full spectrum of AN symptoms is challenging due to their specificity to humans. A widely used AN-like rodent model is the activity-based anorexia (ABA) model, which combines time-limited access to food with free and continuous access to a running wheel 27 . This paradigm leads to a paradoxical pattern of behavior in which animals voluntarily increase their physical activity levels while simultaneously reducing food intake, resulting in severe weight loss and physiological and behavioral changes reminiscent of human AN 27 . BDNF expression in brain regions associated with the neurobiological basis of AN has been studied, in part using the ABA paradigm. For example, rodents typically show reduced BDNF expression in the medial prefrontal cortex (mPFC) and amygdala 28 , 29 . The mPFC is involved in decision-making and executive function, which may be impaired in AN, while the amygdala plays a key role in emotional responses and fear, which are elevated in AN 30 . Conversely, increased BDNF levels in the hippocampus, a region involved in memory and stress responses, suggest adaptive or maladaptive responses to food restriction and stress 28 . Levels remain relatively unchanged in the nucleus accumbens (NAc), which is central to reward processing, suggesting that some reward-related behaviors in AN may not be directly related to changes in BDNF in this region 31 . However, the relatively short duration of the ABA protocol may not fully capture the chronicity and complexity of human AN, limiting its translational relevance. This highlights the need for further refinement of this model to better understand the long-term neurobiological effects of AN and to develop more effective treatments. In this study, we used a modified version of the ABA protocol, known as the Food Restriction and Wheel (FRW) model, which incorporates the chronic aspect of AN, a critical feature that closely aligns with the prolonged course of the disorder , 32 , 33 . The FRW model has been well validated, particularly in terms of its metabolic relevance, and effectively mimics the metabolic and endocrine changes observed in AN 32 – 34 . The aim of this study was therefore to investigate the expression levels of BDNF, its receptor tropomyosin receptor kinase B (TrkB, neurotrophic tyrosine kinase, receptor, type 2 Ntrk2) 35 , and its regulator N-acetyltransferase 8 like (Nat8l) in different brain regions. Nat8l, which regulates BDNF expression in the dorsal striatum (DS) 36 , is therefore essential to investigate in order to understand its potential impact on the behavioral and physiological manifestations of AN. The brain regions studied were the DS, the NAc, the ventral tegmental area and the prefrontal cortex (PFC). They were chosen because of their critical role in the regulation of mood, specifically anxiety and depression, reward processing and cognitive function, areas that are commonly affected in people with AN 19 . We focused on chronic food restriction, progressive refeeding and short refeeding periods. Progressive refeeding simulates the treatment phases of AN in hospitalized patients, and short-term refeeding episodes sometimes occur spontaneously in patients with AN. Progressive refeeding represents the nutritional rehabilitation phase, in which a gradual increase in calories is aimed at restoring physiological function and reversing low BMI 37 . Short refeeding, which can occur spontaneously in treatment settings, involves rapid and excessive food intake that can also interfere with recovery 37 . Materials and Methods Animals Seven-week-old C57BL/6 J female mice (Charles River Laboratories, L'Arbresle, France) weighing 18.3 ± 0.1 g were housed in pairs in standard Plexiglas cages, to reduce external stressors such as isolation and hypothermia while ensuring adequate monitoring of food intake and physical activity. For one week, mice had access to food to calculate ad libitum food intake of standard chow (3% fat, 16% protein, 60% carbohydrate, 4% fibre, 2.79 kcal/g; Safe A04, Germany). Cages were maintained in a specific pathogen-free environment at a temperature range of 19 to 21 °C with a 12-hour light-dark cycle (with lights on from 06:00 am to 06:00 pm). Baseline body weight and ad libitum food intake were recorded in each cage during the first week acclimatization period and throughout the protocol. All experimental procedures were in accordance with the guidelines of the European Communities Council Directives (86/609/EEC). In addition, the study protocol was approved by the Regional Ethics Committee (CEEA.34) of the University Paris Cité. Food restriction and refeeding protocols We used the food restriction and wheel protocols 32 . During the acclimatization week, daily food intake was measured during the last five days of ad libitum access to standard chow, to determine mean food consumption. Animals were then randomly divided into four groups based on initial body weight (mean 16.19 ± 0.20 g) at the end of the acclimatization period to homogenise the groups. Groups were designated as ad libitum (AL), ad libitum with wheel (ALW), food restriction (FR) and food restriction with wheel (FRW). FR and FRW groups experienced 30% food restriction for three days followed by 50% for 15 days, based on the calculation of the mean food consumption during the ad libitum phase. To prevent competition between littermates, food was provided directly in the home cages at 4:00 pm daily. ALW and FRW groups had access to a running wheel (diameter: 230 mm; width: 50 mm; 1 revolution = 0.72 m), whose activity was continuously monitored and analyzed during the peripandial period (1:00pm – 6:00pm) (ActiWheel software; Intellibio, Seichamps, France). Body weight was monitored daily, and blood glucose levels were measured three times per week (FreeStyle Optium Neo, Abbott, Netherlands). Three food restriction protocols were performed (Fig S1). In the first experiment, mice (n = 6 per group) were subjected to a 15-day food restriction protocol (Fig S1A). In experiment 2, mice (n = 8 per group) started with a 15-day food restriction protocol followed by a progressive refeeding regimen in which the amount of food was gradually increased every two days for a total period of 10 days (60%, 70%, 80%, 90%, and 100%; Fig S1B). In experiment 3, mice (n = 6 per group) were briefly refed under ad libitum conditions for 24 hours, after the 15-day restriction protocol (Fig S1C). Tissue collection At the end of each experiment, mice were sacrificed using an anaesthetic injection (ketamine/xylazine, ketamine 100 mg/kg and xylazine 10 mg/kg, intraperitoneally), followed by cardiac puncture for blood collection. Blood was centrifuged at 1000 rpm for 10 minutes at -4 °C to separate plasma, which was then frozen on dry ice. Ethylenediaminetetraacetic acid (EDTA, 2mg/mL of blood) was added to the blood to prevent clotting, and polyhexamethylene biguanide (PHMB, 0.4 mM final concentration) was added to the plasma to inhibit protease activity. Brain tissues, including the prefrontal cortex (PFC), dorsal striatum (DS), nucleus accumbens (NAc), and ventral tegmental area (VTA) were microdissected, frozen in liquid nitrogen, and stored at -80°C. Y maze reversal learning protocol In a separate study, 6 mice per group were subjected to the food restriction protocol for 15 days. On day 16, the Y-maze reversal test was performed to assess cognitive flexibility under food restriction and ad libitum conditions. The Y-maze consisted of two arms made of black Plexiglass, each measuring 35 cm long (Fig S1D). The protocol started on the 13 th day of food restriction and consisted of two phases: habituation and testing. During habituation, the mice were habituated to the Y-maze with 15-minute sessions over two days and allowed to explore freely. To familiarize the mice with the reward, they were given half a Miel Pop cereal (Kellogg’s) at feeding time in their home cages. During the testing phase, a small piece of Miel Pop was randomly placed in one of the arms to assess learning. Mice were placed at the intersection of the maze, and the time to choose an arm and the probability of choosing the correct arm (with the reward) were recorded. After entering in an arm, the chosen arm was closed, and the mouse was removed from the maze after 20 seconds. If the correct arm was chosen, the mouse consumed the reward; otherwise, no reward was given. Each mouse underwent 10 sessions per day until an 80% correct choice rate was achieved, indicating successful learning. A reversal learning test was then performed, in which the reward location was switched to the opposite arm. Testing continued until a group reached 80% correct choices in the reversal phase (Fig S1E-F). RNA extraction and cDNA preparation For RNA extraction, tissues were homogenized in TRIzol reagent, followed by phase separation and RNA precipitation. The extracted RNA was washed with ethanol (75%) and resuspended in RNase-free water. The concentration and purity of the RNA was determined spectrophotometrically. Subsequently, cDNA synthesis was performed using the Maxima cDNA synthesis kit (Thermo Fisher scientific, Waltham, MA USA). Quantitative polymerase chain reaction (qPCR) and RNA sequencing Real-time quantitative PCR (qPCR) was performed using the SYBR Green qPCR Master Mix (2X, Roche Diagnostics, Meylan, France) on a 96-well plate (Roche Diagnostics, Meylan, France). The gene PPIA (cyclophilin A) was used as the housekeeping gene for normalization. The purity of the PCR products was assessed using dissociation curves. Data analysis was performed using the comparative threshold (Ct) method, with gene expression normalised to internal controls, and expressed using the 2 − ΔΔ Ct method. PCR primers are described in Supplementary Table 1. RNA sequencing was performed by the GENOM'IC core of the Cochin institute on the prepared samples. RNA sequencing was performed by the GENOM'IC core of the Cochin institute on the prepared samples. Libraries were prepared from 3 μg of extracted total RNA. The captured, purified and clonally amplified libraries were then sequenced on a Novaseq instrument (Illumina) according to the manufacturer's recommendations. Sequence reads were aligned to the mouse genome (mm10) using BWA software. Downstream processing was carried out using the Genome Analysis Toolkit (GATK), SAMtools and Picard Tools (http://picard.sourceforge.net). Fastq files were then aligned using the STAR algorithm (version 2.7.6a), against the Ensembl release 101 reference ( GRCm38 ). Reads were then counted using RSEM (v1.3.1) and the statistical analyses on the read counts were performed using R (version 3.6.3) and the DESeq2 package (DESeq2_1.26.0) to determine the proportion of differentially expressed genes between two conditions. We used the standard DESeq2 normalization method (DESeq2’s median of ratios with the DESeq function), with a pre-filter of reads and genes (reads uniquely mapped on the genome, or up to 10 different loci with a count adjustment, and genes with at least 10 reads in at least 3 different samples). Following the package recommendations, we used the Wald test with the contrast function and the Benjamini-Hochberg FDR control procedure to identify the differentially expressed genes. R scripts and parameters are available on the platform, https://github.com/GENOM-IC-Cochin/RNA-Seq_analysis. Enzyme-linked immunosorbent assay To quantify the total brain-derived neurotrophic factor (BDNF) in plasma, we used the BDNF ELISA kit (R&D Systems, Minneapolis, MN, USA) following the manufacturer’s protocol. Plasma samples were collected and stored at -80°C until assayed. Plasma samples were diluted 1:10 and the assay was performed in duplicate. The precision of the BDNF ELISA assay was assessed by intra- and inter-assay variability. Intra-assay precision was assessed by testing three samples of known concentration 20 times on a single plate, yielding CVs of 3.2%, 2.4%, and 3%. Inter-assay precision was assessed by 20 separate assays performed by at least three technicians on two batches of components, yielding CVs of 7.2%, 4.3%, and 4.7%. Statistical analysis Statistical analyses were performed using GraphPad Prism and R. Data were first tested for normality using the Shapiro-Wilk test to determine the appropriate statistical tests. Outliers were identified and removed using z-score analysis, where data points with a z-score greater than ±3 were considered outliers. For normally distributed data, parametric tests such as one- or two-way analysis of variance (ANOVA) were used to compare group means, followed by post hoc analysis with Tukey's test when appropriate. The unpaired Student’s t-test test was used for comparisons between two groups. The Y-maze results were analysed using repeated measures ANOVA to account for the within-subject variability across sessions. Correlations between variables were assessed using Pearson's correlation coefficients depending on the data distribution. All data are presented as mean ± standard error of the mean (SEM), and a p-value of less than 0.05 was considered statistically significant. RESULTS Body weight and anticipatory activity responses to food restriction and refeeding in in AN-like mice We evaluated body weight and food anticipatory activity (FAA), defined as increased physical activity prior to scheduled feeding, under different feeding protocols (Fig. S1A-C). Mice in the FR and FRW groups exhibited significant body weight loss (~25%) by the end of the fasting period (p < 0.001, F(3,10) = 135.7, Fig. S1A), with no differences between FR and FRW, indicating no effect of wheel access on weight loss. FRW mice showed a significant increase in FAA compared to the ALW group (p = 0.018, F(1,4) = 15.02, Fig. S1A). During progressive refeeding, mice recovered their baseline body weight over 10 days (Fig. S1B), with a concomitant reduction in FAA (Fig. S1B). In the short refeeding group, weight was recovered within one day (Fig. S1C), accompanied by an immediate cessation of FAA (Fig. S1C). Behavioral responses in the Y-maze test Cognitive function was assessed using the Y-maze reversal learning test. During the learning phase, FRW mice acquired the task faster than ALW mice (p = 0.004, t = 5.657 for day 3 and p = 0.011, t = 5.000 for day 10, Fig. 1A). However, there were no significant differences between groups in the reversal phase (Fig. 1A). FRW mice initially showed an impaired response during the first day of reversal learning, as indicated by a more significant reduction in the percentage of correct responses compared to the last day of learning (p = 0.024, F(5, 5) = 1.714, Fig. 1B). However, no permanent deficits were observed as FRW mice quickly relearned the task (p = 0.050, F(5, 5) = 2, Fig. 1C), indicating that they eventually adapt quickly to novel rules Expression of BDNF, TrkB, and Nat8l in different brain regions Plasma BDNF protein concentrations were not different during the restriction period, whereas progressive refeeding resulted in a significant decrease only in FR mice (AL vs FR p = 0.035, t = 2.231), with no significant effect observed in the short-term refeeding group (Fig. 1D). We then quantified the mRNA expression levels of BDNF, TrkB, and Nat8l. In the DS, food restriction significantly reduced BDNF expression (AL vs FR p = 0.014, t = 2.679, Fig. 2A), with no effect of wheel access. Progressive refeeding and short refeeding fully restored BDNF levels (Fig. 2A). TrkB and Natl8l expression was not significantly altered by dietary restriction (Fig. 2C-2E). In the PFC, BDNF expression decreased with dietary restriction (AL vs FR p = 0.040, t = 2.193; ALW vs FRW p = 0.039, t = 2.209, Fig. 2B), but in contrast to DS, progressive refeeding did not restore these levels (ALW vs FRW p = 0.001, t = 3.734, Fig. 2B). However, shortrefeeding with wheel access reversed the reduction (AL vs FR p = 0.029, t = 2.359, Fig. 2B). TrkB expression in the PFC followed different trend than BDNF, with an increase during restriction and normalization by progressive refeeding (TrkB AL vs FR p = 0.007, t = 3.052, Fig. 2D). BDNF, TrkB, and Nat8l expression in the NAc and VTA was not affected by dietary protocols or wheel activity (Fig. S2A-B). Two-ways ANOVA showed that food restriction significantly decreased BDNF expression in both the DS and PFC (p = 0.004, F(1, 20) = 10.56 for DS, p = 0.006, F(1, 20) = 9.619 for PFC, Fig. S3), while no effect was observed on TrkB expression (Fig. S4). In contrast, Nat8l showed a significant interaction effect of restriction combined with running wheel exclusively in the DS (p = 0.005, F(1, 20) = 10.17, Fig. S5). However, no significant effect of wheel access alone was observed (Fig. S3-5). In addition, BDNF expression in both the DS and PFC was positively correlated with body weight and fasting blood glucose levels, a relationship that was not seen in the NAc (Fig. S6-8). This suggests region-specific responses to metabolic changes under chronic food restriction. Whole RNA sequencing in the dorsal striatum and prefrontal cortex RNA sequencing in the DS confirmed the decrease in BDNF under chronic restriction and identified significant gene expression changes between AL and FR groups, as well as and between wheel access groups (ALW vs FRW) (Fig. 3A-D). Food restriction resulted in significant up- and down-regulation of genes (Fig. 3A, Table 1), while wheel access under ad libitum conditions also altered gene expression (Fig. 3B). However, wheel access generally had a minimal effect on gene expression in both ad libitum and restricted conditions (Fig. 3C-D). Pathway enrichment analysis revealed significant changes in key pathways, including "MAPK signalling," "PI3K-Akt signalling," and "Apoptosis", reflecting the broad effects of dietary status on metabolic, neuronal, and immune functions. Similar effects were observed in the restriction and wheel-running groups (Fig. 3E, Supplementary Tables 2 and 3). Cross-comparison of the transcriptomic data with the BDNF protein-protein interaction (PPI) network revealed that most of the differentially expressed genes were involved in metabolism, neuronal development, and immune regulation (Table 2, Supplementary Tables 4 to 8). Gene expression in the PFC followed a similar pattern to that in the DS, with minimal effects of wheel activity (Fig. S9A-D, Table 1). Wheel running reversed gene expression patterns under restriction (Fig. S10A-B, Table S2), with differences in the specific genes affected between the DS and PFC (Table S2). Pathway enrichment in the PFC highlighted immune regulation and cell-cell communication as major processes (Fig. S9E). Discussion Our study shows that chronic food restriction, progressive refeeding, and short-term refeeding modulate BDNF, TrkB, and Nat8l expression in brain regions involved in cognitive and reward functions, with region-specific responses. Notably, refeeding failed to restore BDNF in the PFC, whereas short refeeding induced an increase of BDNF in the same region, suggesting differential responses depending on the type of refeeding. Importantly, TrkB mirrored BDNF patterns in the DS, whereas in the PFC, BDNF and TrkB were regulated in opposite directions. These findings suggest that nutritional status profoundly affects neuroplasticity and reward circuit dynamics, but in a region-specific manner. The Y-maze results suggest that chronic food restriction may impair cognitive flexibility in the short term, but this effect appears to be reversible, as no long-term deficits were observed. Patients with AN often struggle with cognitive flexibility, particularly in task switching 8 . The DS is critical for this function 38 , with BDNF in the DS playing a key role 39 , in addition to BDNF in the PFC 40 . While no long-term cognitive inflexibility was observed in our study, we did find short-term impairments, likely related to reduced BDNF in the DS and PFC due to chronic food restriction. This suggests that reduced BDNF in these regions may contribute to transient cognitive challenges during dietary stress. Our results on plasma BDNF are consistent with previous studies showing that patients with AN exhibit reversible decreased plasma BDNF levels with weight recovery 41 – 43 , supporting not only the relevance of our model in mimicking key physiological aspects of AN but also the potential role of BDNF as a biomarker for the disease. However, no previous study has investigated BDNF mRNA or protein levels in the DS under chronic food restriction, making our study the first to do so. Previous studies have found no significant changes in the PFC, NAc or VTA in both male and female rats under similar conditions 44 . Our results are consistent with these findings in the mesolimbic regions. However, what we observed in the PFC is the opposite, possibly due to species or sex differences. The function of BDNF is not consistent across brain regions, with contrasting effects observed between the hippocampus/PFC and the reward circuits 45 . In areas such as the PFC, higher levels of BDNF are often associated with improved cognitive outcomes and protection against stress-related mood disorders 46 , 47 . However, in the mesolimbic pathway (NAc-VTA) and in the DS, BDNF appears to play a more complex and, in some cases, pro-depressive role 36 , 48 . Our findings contribute to the growing body of evidence suggesting that patients with AN may engage in food restrictive behaviors to modulate mood, possibly through reward pathways 49 . Nat8l, a positive regulator of BDNF expression in the DS, is thought to play a key role in modulating these mood-related effects 36 . Our results show that food restriction combined with wheel running, significantly reduced Nat8l expression in the DS, which may further reduce BDNF levels and contribute to stress susceptibility. Nat8l has been implicated in epigenetic modulation that influences brain resilience to chronic stress 36 . The observed decrease in both Nat8l and BDNF under food restriction conditions suggests that the DS may become more susceptible to stress or fail to properly regulate reward mechanisms that are often disrupted in AN 5 . This may contribute to the persistence of reduced feeding in AN as a maladaptive response to stress 50 , 51 . Further studies are needed to determine whether these changes are part of a protective mechanism or a driver of maladaptive behaviors in AN, and how they might influence potential therapeutic targets aimed at restoring neuroplasticity in these regions. The RNA sequencing results revealed significant gene expression changes in the DS and PFC under chronic food restriction. Key genes such as Fasn , Gap43 , and Trem2 were upregulated in the DS, indicating an adaptive response to metabolic stress, likely related to synaptic plasticity and cellular signalling as shown by GO analysis. In the PFC, genes such as Egr4 and Golph3 were altered, with GO analysis suggesting effects on immune regulation and metabolic processes. These findings suggest that food restriction-induced molecular changes in brain regions involved in cognitive flexibility and reward processing may contribute to the behavioral outcomes observed in AN. Physical activity increases BDNF in the PFC and DS as shown in rodent models. In our study, although physical activity had a limited overall effect on gene expression, it reversed the effects of food restriction on specific genes in the DS and PFC, such as Gap43 , Trem2 , and Arhgef18 . In the DS, genes such as Egr4 and Fasn were reversed by wheel access, suggesting that exercise may play a role in regulating metabolic pathways under chronic restriction. Similarly, Tceal5 and Atat1 in the PFC were modulated by exercise. These results highlight the interaction between nutritional status and physical activity in modulating brain function under metabolic stress. Finally, although BDNF protein can cross the blood-brain barrier 52 , our study suggests that plasma BDNF levels may not accurately reflect region-specific brain changes due to the heterogeneous regulation of BDNF in different brain regions and the lack of consistency with the expression pattern of a single brain region. Future work should focus on proteomic analyses to fully understand how BDNF and TrkB signalling contribute to the neurobiological basis of AN and explore whether other peripheral markers may more accurately reflect brain changes. A limitation of this study is the use of the Y-maze reversal learning task, which may not have been sufficiently challenging enough to fully assess potential deficits in cognitive flexibility. Future studies should consider the use of more challenging tasks, such as the water maze. Food restriction may also induce olfactory sensitisation 53 , which may lead to a bias of the test we have used. In addition, although we measured BDNF mRNA expression in key brain regions, we did not quantify protein in these regions. Direct measurement of BDNF protein levels in the brain would provide a more complete understanding of their relationship with plasma BDNF levels and allow a more accurate cross-comparison between peripheral and central changes under restrictive conditions. In conclusion, chronic food restriction and subsequent refeeding significantly affects brain plasticity in the DS and PFC, regions critical for cognitive function, with implications for the development of more tailored treatment strategies in AN. Understanding these complex interactions between diet, brain plasticity, and physical activity is critical for improving treatment outcomes in this population. Declarations Conflict of Interest PG received during the last 5 years fees for presentations at congresses or participation in scientific boards from Biogen, Janssen, Lundbeck, Merk, Otsuka, Richter and Viatris. The remaining authors declare no competing interests. Contributions Odile Viltart, Nicolas Ramoz, Jingxian Cao and Virginie Tolle designed the experiments. Jingxian Cao, Nicolas Lebrun, Shiou-ping Chen, Chloé Tezenas du Montcel, Céline Cruciani-Guglielmacci and Odile Viltart performed the experiments. Jingxian Cao, Philip Gorwood, Nicolas Ramoz, and Odile Viltart carried out the analysis. The manuscript was drafted by Jingxian Cao, Nicolas Ramoz, and Odile Viltart. All authors discussed results, made figures, and edited the manuscript. Acknowledgements This work was supported by the Fédération pour la Recherche sur le Cerveau (FRC to NR), the Fondation de France – Maladies Psychiatriques (FdF to PG), the Université Paris Cité and the Institut National de la Santé et de la Recherche Médicale (INSERM). JC is a PhD student of a doctoral fellow of the University Paris Cité, ED562 BioSPC. CT is a recipient of a PhD fellowship (FDM202006011161) funded by the Fondation pour la Recherche Médicale (FRM). The authors would like to thank Ludivine Therreau and Gwenaëlle Le Pen of the IPNP PhenoBrain core facility and the staff of the animal facility, for their invaluable help in the handling and managing the animals used in this study. References Micali, N., Hagberg, K. 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Dysregulation of mRNA expression levels by chronic food restriction or wheel running in the dorsal striatum (DS) and prefrontal cortex (PFC) Tissue Down-regulated Up-regulated Top 10 significant DS Restriction 1049 671 H1f2, Gap43, Fads1, Rgs11, Trem2, Arhgef18, Lrrc8c, Golph3,Tcim, Gm19439 Wheel 115 106 Gm26876, Gm4219, Gm44294, Gm49749, Map4k1,Gm5786, Gm37132, nPi19, C230086J09Rik PFC Restriction 632 460 Rskr, Igfn1, Panx2, Akt2, Colq, 4930447C04Rik, Gm29674, Tmem74b Wheel 75 49 Gm37728, Gm9320, 2900076G11Rik, Rps27l, Pomc, A930035D04Rik, Kif11, Rps15a-ps6, Gm4117 Pm20d1 *Genes with an adjusted p-value < 0.05 and a Log2Fold Change 0.5 were selected for inclusion." Table 2. Modulation of mRNA expression levels of genes in protein-protein interaction with BDNF by chronic food restriction or wheel running in the dorsal striatum (DS) and prefrontal cortex (PFC) Tissue Effect of Restriction Effect of Wheel Running DS up-regulated Mme, Atp7a, Fgf22, Ppargc1a, Ror1, Calca, Jak2, Pik3r1, Slc2a1, Musk, Ehd1, Nt5e, Stat3, Htr1b, Nrtn, Gfap, Htr2a, Dnmt3b, Fkbp5, Mc4r, Pkp2, Scn10a Atp7a, Calca down-regulated Tph2, Itgam, Pkp1, Ngfr, Fgf3, Trem2, Nr4a2, Bche, Fgf17, Rasal3, S100b, Cx3cr1, Sec16b, mt-Nd2, Aif1, Tph1, Cck, Mog, Grin3b, Mmp2, Cadps2, Ptn, Rtn4r, Fgf10, Ntsr1, Artn, Stmn2, Esr1, Angpt1, Nfia, Npas4, Fos Grap2 PFC up-regulated Grm8, Tacr1, Ddc, Mmp9, Ppp1r1b, Pkp2, Dnmt3b, Fkbp5, Mc4r, Scn10a Pm20d1, Bmp4, Pomc down-regulated Itgam, Neurog2, Npas4, Trem2, Fgf17, Cx3cr1, Nptx2, Tek, Artn, Bche, Grm3, mt-Nd2 Fgf18, Dynlt1c *Protein-protein interactions were analyzed using string.com. Genes with an adjusted p-value < 0.05 and a Log2Fold Change 0.5 were selected for inclusion." Additional Declarations The authors have declared there is NO conflict of interest to disclose Supplementary Files CaoetalSuppFig3.pdf Figure S3. BDNF mRNA expression in different brain regions under different feeding protocols and physical activity conditions, highlighting the interaction between feeding and wheel access CaoetalSuppFig4.pdf Figure S4. TrkB mRNA expression in different brain regions under different feeding protocols and physical activity conditions, highlighting the interaction between feeding and wheel access CaoetalSuppFig5.pdf Figure S5. Nat8l mRNA expression in different brain regions under different feeding protocols and physical activity conditions, highlighting the interaction between feeding and wheel access CaoetalSupptable1.docx Supplementary Table 1. Primers used for qPCR experiments CaoetalSuppFig7.pdf Figure S7. Correlation between gene expression and metabolic parameters in the prefrontal cortex under different feeding conditions CaoetalSuppFig6.pdf Figure S6. Correlation between gene expression and metabolic parameters in the dorsal striatum under different feeding conditions CaoetalSuppFig10.pdf Figure S10. Cross-comparison of gene expression changes in response to food restriction and wheel running across the dorsal striatum and prefrontal cortex CaoetalSupplementaryTable5.xlsx Supplementary Table 5. Functional Annotation of Differentially Expressed Genes in the prefrontal cortex from Table 2 CaoetalSupptable6.docx Supplementary Table 6. Top gene expression in interaction between chronic food restriction and wheel running. CR: caloric restriction; DS: dorsal striatum; PFC: Prefrontal cortex CaoetalSupplementaryTable7.xlsx Supplementary Table 7. Functional Annotation of Differentially Expressed Genes in the dorsal striatum from Supplementary Table 6 CaoetalSupplementaryTable4.xlsx Supplementary Table 4. Functional Annotation of Differentially Expressed Genes in the dorsal striatum from Table 2 CaoetalSupplementaryTab2.pdf Supplementary Table 2. Functional Annotation of Differentially Expressed Genes in the dorsal striatum from Table 1 CaoetalSuppFig1.pdf Figure S1. Schematic diagrams of the different experiments with body weight and anticipatory activity changes CaoetalSuppFig2.pdf Figure S2: Effects of chronic food restriction, progressive refeeding, and short refeeding on BDNF, TrkB, and Nat8l expression in the nucleus accumbens and ventral tegmental area CaoetalSupplementaryTable3.xlsx Supplementary Table 3. Functional Annotation of Differentially Expressed Genes in the prefrontal cortex from Table 1 CaoetalSupplementaryTable8.xlsx Supplementary Table 8. Functional Annotation of Differentially Expressed Genes in the prefrontal cortex from Supplementary Table 6 CaoetalSuppFig9.pdf Figure S9. RNA sequencing analysis reveals differentially expressed genes in the prefrontal cortex across feeding and physical activity conditions CaoetalSuppFig8.pdf Figure S8. Correlation between gene expression and metabolic parameters in the nucleus accumbens under different feeding conditions Cite Share Download PDF Status: Published Journal Publication published 17 Oct, 2025 Read the published version in Translational Psychiatry → Version 1 posted Editorial decision: revise 06 May, 2025 Review # 2 received at journal 10 Apr, 2025 Review # 1 received at journal 08 Apr, 2025 Reviewer # 2 agreed at journal 27 Mar, 2025 Reviewer # 1 agreed at journal 27 Mar, 2025 Reviewers invited by journal 27 Mar, 2025 Editor assigned by journal 21 Mar, 2025 Submission checks completed at journal 21 Mar, 2025 First submitted to journal 21 Mar, 2025 Unknown event 20 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6260210","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":434714172,"identity":"df3cad94-8a1b-4129-8fb7-1c0bbb02b675","order_by":0,"name":"Nicolas Ramoz","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYDACZiB+AOdVSEAZNgS0JMB5Z2Ba0gjYBNfC2AZj4dFizs788EFCTR2DefvpxIc/51nkybf3Pt3AkHAPpxbLZjZjg4RjhxlkzuRuNpDcJlFscOa42Q2GhGKcWgwO87BJJLAdYJBgyN0mYbhNInGDRBrbDcYfCQS0/KtjkOB/C1Q/RyJx/vxnbEBbCGhJbGNmkJAA2nKwQSKx4QYbIS1AvyT2HeaRkHi72bDhGNBhZ4AOS8Cn5fzhhw8+fKuTk+DP3fjwR01d4vz2Y2w3PuDRAgM8qFzCGkbBKBgFo2AU4AMAZzZQDNMrXBUAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-8070-9938","institution":"INSERM","correspondingAuthor":true,"prefix":"","firstName":"Nicolas","middleName":"","lastName":"Ramoz","suffix":""},{"id":434714173,"identity":"96da9865-d664-4161-9c2d-028e619cb003","order_by":1,"name":"Jingxian CAO","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Jingxian","middleName":"","lastName":"CAO","suffix":""},{"id":434714174,"identity":"3f297841-612f-4410-aacd-fa4e9240dec5","order_by":2,"name":"Nicolas Lebrun","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Nicolas","middleName":"","lastName":"Lebrun","suffix":""},{"id":434714175,"identity":"44e18132-96f9-4579-b15d-10d6cc2e79ef","order_by":3,"name":"Shiou-ping Chen","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Shiou-ping","middleName":"","lastName":"Chen","suffix":""},{"id":434714176,"identity":"217dbfc0-fd9d-40b9-aa34-88bb8130166c","order_by":4,"name":"Chloé Tezenas du Montcel","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Chloé","middleName":"Tezenas","lastName":"du Montcel","suffix":""},{"id":434714177,"identity":"2c932eca-ee37-494a-819b-e2ddb44a0b0d","order_by":5,"name":"Philip Gorwood","email":"","orcid":"https://orcid.org/0000-0003-1845-3676","institution":"GHU Paris","correspondingAuthor":false,"prefix":"","firstName":"Philip","middleName":"","lastName":"Gorwood","suffix":""},{"id":434714178,"identity":"d21312de-1f1b-4b44-94c7-cef9d5582020","order_by":6,"name":"Céline Cruciani-Guglielmacci","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Céline","middleName":"","lastName":"Cruciani-Guglielmacci","suffix":""},{"id":434714179,"identity":"c04c210a-cefa-45be-890e-a583823cefef","order_by":7,"name":"Virginie Tolle","email":"","orcid":"","institution":"Inserm, Paris University","correspondingAuthor":false,"prefix":"","firstName":"Virginie","middleName":"","lastName":"Tolle","suffix":""},{"id":434714180,"identity":"2445c6fe-01c7-4624-b3a2-2908f69b3c8a","order_by":8,"name":"Odile Viltart","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Odile","middleName":"","lastName":"Viltart","suffix":""}],"badges":[],"createdAt":"2025-03-19 09:51:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6260210/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6260210/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41398-025-03618-7","type":"published","date":"2025-10-17T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80712902,"identity":"dc60049d-753a-4ad2-b248-71d1f41d9dc5","added_by":"auto","created_at":"2025-04-16 09:21:03","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":72314,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffects of chronic food restriction and refeeding protocols on cognitive flexibility and plasma BDNF levels\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Y-maze reversal learning test showing the ratio of correct arm choice across learning and reversal phases in ad libitum with wheel (ALW) and food restriction with wheel (FRW) groups. (B) Delta correct ratio between the ad libitum learning and reversal phases. (C) Delta correct ratio between the first and last blocks of the reversal phase. (D) Plasma BDNF protein levels measured by ELISA across dietary protocols. Group names are as follows: \u003cem\u003ead libitum \u003c/em\u003e(AL, black), \u003cem\u003ead libitum \u003c/em\u003ewith wheel (ALW, black), food restriction (FR, red), food restriction with wheel (FRW, red), progressive refeeding (FRpr, green), progressive refeeding with wheel (FRWpr, green), short refeeding (FRsr, yellow), and short refeeding with wheel (FRWsr, yellow). Data are presented as mean ± SEM for each experimental group. Significant differences are indicated as *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001. Statistical significance was determined using multiple t-test, unpaired t-test and one-way ANOVA followed by post-hoc Tukey’s test.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/d45fbd64ba278408d337f1ba.jpg"},{"id":80712096,"identity":"3c991ce2-7b36-4c3e-b007-837c6b4623bb","added_by":"auto","created_at":"2025-04-16 09:13:03","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":109262,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffects of chronic food restriction, progressive refeeding, and short refeeding on BDNF, TrkB, and Nat8l expression in the dorsal striatum and prefrontal cortex\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A, B) BDNF mRNA expression levels in the dorsal striatum (A) and prefrontal cortex (B) under different feeding protocols. (C, D) TrkB mRNA expression levels in the dorsal striatum (C) and prefrontal cortex (D) under different feeding protocols. (E, F) Nat8l mRNA expression levels in the dorsal striatum (E) and prefrontal cortex (F) under different feeding protocols.\u003c/p\u003e\n\u003cp\u003eGroup names are as follows: ad libitum\u003cem\u003e \u003c/em\u003e(AL, black line), ad libitum\u003cem\u003e \u003c/em\u003ewith wheel (ALW, black filled), food restriction (FR, red line), food restriction with wheel (FRW, red filled), progressive refeeding (FRpr, green line), progressive refeeding with wheel (FRWpr, green filled), short refeeding (FRsr, yellow line), and short refeeding with wheel (FRWsr, yellow filled). Data are expressed as mean ± SEM. Significant differences are indicaed as *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001. Statistical significance was determined byoOne-way ANOVA with post-hoc Tukey’s test.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/d8cee1325d124134bc80fe3d.jpg"},{"id":80709784,"identity":"e6eb00f1-e145-44bc-a327-b27e8eaf8471","added_by":"auto","created_at":"2025-04-16 08:57:03","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":121842,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRNA sequencing analysis reveals differentially expressed genes in the dorsal striatum across feeding and physical activity conditions.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-D) Volcano plots show gene expression changes between different comparison groups: \u003cem\u003ead libitum \u003c/em\u003e(AL) \u003cem\u003evs\u003c/em\u003e food restriction (FR) (A), \u003cem\u003ead libitum \u003c/em\u003ewith wheel (ALW) \u003cem\u003evs\u003c/em\u003e food restriction with wheel (FRW) (B), \u003cem\u003ead libitum \u003c/em\u003e(AL) \u003cem\u003evs\u003c/em\u003e \u003cem\u003ead libitum \u003c/em\u003ewith wheel (ALW) (C), and food restriction (FR) \u003cem\u003evs\u003c/em\u003e food restriction with wheel (FRW) (D). Significantly downregulated genes (p \u0026lt; 0.05, log2FC \u0026lt; -0.5) are highlighted in blue, and significantly upregulated genes (p \u0026lt; 0.05, log2FC \u0026gt; 0.5) are in red. (E) Gene Ontology (GO) analysis of enriched pathways using Metascape. The heatmap represents the most significantly enriched biological processes across experimental conditions, including pathways related to cancer, cell proliferation, MAPK signalling, PI3K-Akt signalling, and immune regulation. Statistical significance was determined using Student’s t-test.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/913b82818ac122106ca34bd2.jpg"},{"id":93827681,"identity":"eaa35f22-647d-4691-8a49-16398bb7e35c","added_by":"auto","created_at":"2025-10-18 07:10:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1138161,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/93e2ca58-c5ff-4eb5-9683-3adf3a10e6c9.pdf"},{"id":80709783,"identity":"741ff627-cb73-459b-8d0a-4d9c19fd6dac","added_by":"auto","created_at":"2025-04-16 08:57:03","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":133526,"visible":true,"origin":"","legend":"Figure S3. BDNF mRNA expression in different brain regions under different feeding protocols and physical activity conditions, highlighting the interaction between feeding and wheel access","description":"","filename":"CaoetalSuppFig3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/6e5cf4159a0efb593468d6eb.pdf"},{"id":80709785,"identity":"fc753fc9-2f06-40d7-a993-8e1dfc13afcb","added_by":"auto","created_at":"2025-04-16 08:57:03","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":133143,"visible":true,"origin":"","legend":"Figure S4. TrkB mRNA expression in different brain regions under different feeding protocols and physical activity conditions, highlighting the interaction between feeding and wheel access","description":"","filename":"CaoetalSuppFig4.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/d336a0f68a540754ee67a214.pdf"},{"id":80714099,"identity":"bc1bd236-0b5a-4f73-b0f7-0ec7e957db55","added_by":"auto","created_at":"2025-04-16 09:29:03","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":133380,"visible":true,"origin":"","legend":"Figure S5. Nat8l mRNA expression in different brain regions under different feeding protocols and physical activity conditions, highlighting the interaction between feeding and wheel access","description":"","filename":"CaoetalSuppFig5.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/0960e6b1d2e1e79429b1a1db.pdf"},{"id":80709787,"identity":"616f89ae-3ec3-497a-ab57-bd59b29c45bc","added_by":"auto","created_at":"2025-04-16 08:57:03","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":16113,"visible":true,"origin":"","legend":"Supplementary Table 1. Primers used for qPCR experiments","description":"","filename":"CaoetalSupptable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/22000b9f62928b5135897344.docx"},{"id":80710999,"identity":"f34a8e1d-50db-488a-af7e-ef8be3ba3037","added_by":"auto","created_at":"2025-04-16 09:05:03","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":236386,"visible":true,"origin":"","legend":"Figure S7. Correlation between gene expression and metabolic parameters in the prefrontal cortex under different feeding conditions","description":"","filename":"CaoetalSuppFig7.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/a6110fd7403859e31598da85.pdf"},{"id":80709801,"identity":"eb0c6764-0435-41a1-9bd4-f5acb05f5fba","added_by":"auto","created_at":"2025-04-16 08:57:03","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":234104,"visible":true,"origin":"","legend":"Figure S6. Correlation between gene expression and metabolic parameters in the dorsal striatum under different feeding conditions","description":"","filename":"CaoetalSuppFig6.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/4e865de05e254a790794501c.pdf"},{"id":80712102,"identity":"88e91494-ae7c-45db-8922-c7faa33b825d","added_by":"auto","created_at":"2025-04-16 09:13:03","extension":"pdf","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":270949,"visible":true,"origin":"","legend":"Figure S10. Cross-comparison of gene expression changes in response to food restriction and wheel running across the dorsal striatum and prefrontal cortex","description":"","filename":"CaoetalSuppFig10.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/94a2291ca2241c594df70688.pdf"},{"id":80709797,"identity":"e9b818bf-e2a5-43f6-97cd-8233c504c4cd","added_by":"auto","created_at":"2025-04-16 08:57:03","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":33119,"visible":true,"origin":"","legend":"Supplementary Table 5. Functional Annotation of Differentially Expressed Genes in the prefrontal cortex from Table 2","description":"","filename":"CaoetalSupplementaryTable5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/204c68c51bfe4b3c7b3660f2.xlsx"},{"id":80712100,"identity":"1d3257b7-4575-48d3-927d-6b0644a8745b","added_by":"auto","created_at":"2025-04-16 09:13:03","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":16471,"visible":true,"origin":"","legend":"Supplementary Table 6. Top gene expression in interaction between chronic food restriction and wheel running. CR: caloric restriction; DS: dorsal striatum; PFC: Prefrontal cortex","description":"","filename":"CaoetalSupptable6.docx","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/3c46a1c754a03aaa26307110.docx"},{"id":80710987,"identity":"598e9b64-27d8-4d6a-be46-23df7dab574d","added_by":"auto","created_at":"2025-04-16 09:05:03","extension":"xlsx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":26555,"visible":true,"origin":"","legend":"Supplementary Table 7. Functional Annotation of Differentially Expressed Genes in the dorsal striatum from Supplementary Table 6","description":"","filename":"CaoetalSupplementaryTable7.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/3d89a0e2b0a5b2e352f1d578.xlsx"},{"id":80710995,"identity":"d312bbff-6634-4c41-b311-5eec0972e9f4","added_by":"auto","created_at":"2025-04-16 09:05:03","extension":"xlsx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":94515,"visible":true,"origin":"","legend":"Supplementary Table 4. Functional Annotation of Differentially Expressed Genes in the dorsal striatum from Table 2","description":"","filename":"CaoetalSupplementaryTable4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/765f166bda8047edcb779019.xlsx"},{"id":80712105,"identity":"31a81672-95eb-4614-90d5-80efcc34260c","added_by":"auto","created_at":"2025-04-16 09:13:03","extension":"pdf","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":228024,"visible":true,"origin":"","legend":"Supplementary Table 2. Functional Annotation of Differentially Expressed Genes in the dorsal striatum from Table 1","description":"","filename":"CaoetalSupplementaryTab2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/634bdabddd92850e358992df.pdf"},{"id":80709804,"identity":"feea92d3-e8ee-4bc6-9ef3-2256b7f53361","added_by":"auto","created_at":"2025-04-16 08:57:03","extension":"pdf","order_by":14,"title":"","display":"","copyAsset":false,"role":"supplement","size":229867,"visible":true,"origin":"","legend":"Figure S1. Schematic diagrams of the different experiments with body weight and anticipatory activity changes","description":"","filename":"CaoetalSuppFig1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/d5b58b22e5237237fd0e6dad.pdf"},{"id":80711005,"identity":"86383c6d-204e-4cef-834e-5b36811d508e","added_by":"auto","created_at":"2025-04-16 09:05:03","extension":"pdf","order_by":15,"title":"","display":"","copyAsset":false,"role":"supplement","size":174001,"visible":true,"origin":"","legend":"Figure S2: Effects of chronic food restriction, progressive refeeding, and short refeeding on BDNF, TrkB, and Nat8l expression in the nucleus accumbens and ventral tegmental area","description":"","filename":"CaoetalSuppFig2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/213ac00f8c43d1e367621d94.pdf"},{"id":80709810,"identity":"7697559a-c287-4e9a-83fd-86ce65faeba4","added_by":"auto","created_at":"2025-04-16 08:57:03","extension":"xlsx","order_by":16,"title":"","display":"","copyAsset":false,"role":"supplement","size":18374,"visible":true,"origin":"","legend":"Supplementary Table 3. Functional Annotation of Differentially Expressed Genes in the prefrontal cortex from Table 1","description":"","filename":"CaoetalSupplementaryTable3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/da2f0edd23d8fd7a936fb847.xlsx"},{"id":80709808,"identity":"a5f05de5-19d8-4da9-98d5-a2f4f2bd503b","added_by":"auto","created_at":"2025-04-16 08:57:03","extension":"xlsx","order_by":18,"title":"","display":"","copyAsset":false,"role":"supplement","size":13742,"visible":true,"origin":"","legend":"Supplementary Table 8. Functional Annotation of Differentially Expressed Genes in the prefrontal cortex from Supplementary Table 6","description":"","filename":"CaoetalSupplementaryTable8.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/b49ab87af14b8eb0726953db.xlsx"},{"id":80711014,"identity":"75dbd7e1-51f5-4afd-9c6e-b7bbd45c7ad7","added_by":"auto","created_at":"2025-04-16 09:05:04","extension":"pdf","order_by":19,"title":"","display":"","copyAsset":false,"role":"supplement","size":2984301,"visible":true,"origin":"","legend":"Figure S9. RNA sequencing analysis reveals differentially expressed genes in the prefrontal cortex across feeding and physical activity conditions","description":"","filename":"CaoetalSuppFig9.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/3c83ac3b75a960417fcff7ad.pdf"},{"id":80709816,"identity":"671974f9-921b-43de-809c-acd3b4ef9559","added_by":"auto","created_at":"2025-04-16 08:57:04","extension":"pdf","order_by":20,"title":"","display":"","copyAsset":false,"role":"supplement","size":236009,"visible":true,"origin":"","legend":"Figure S8. Correlation between gene expression and metabolic parameters in the nucleus accumbens under different feeding conditions","description":"","filename":"CaoetalSuppFig8.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6260210/v1/9ac7432bdf2fc6025e46ff82.pdf"}],"financialInterests":"The authors have declared there is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose","formattedTitle":"Unraveling the brain expression of BDNF in a mouse model of Anorexia Nervosa","fulltext":[{"header":"Introduction","content":"\u003cp\u003e \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003ePlease have a look at courier new font provided for text in article.\u003c/span\u003e\u003c/p\u003e \u003cp\u003eAnorexia nervosa (AN) is a complex and potentially life-threatening eating disorder characterized by self-imposed dietary restriction and usually excessive physical exercise\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Individuals with AN experience severe weight loss due to caloric restriction, leading to a number of somatic complications such as hormonal and metabolic changes, and loss of bone density\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. In addition, AN is now considered as a metabo-psychiatric disorder\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e because metabolic changes, such as weight loss and hormonal changes\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, are often associated with psychiatric symptoms. These include high levels of anxiety and depression associated with intense fear of weight gain, distorted body image, obsessive behaviors related to food and body shape and impaired cognitive flexibility and decision-making, which further complicate the clinical presentation and treatment approach\u003csup\u003e\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. The disorder predominantly affects adolescents and young adults, with a higher prevalence in women, accounting for up to 90% of cases\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Epidemiological studies estimate that the prevalence of AN to be around 1% in young adult females\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Despite various therapeutic approaches, there is currently no cure for AN, and many individuals experience recurrent relapses. It is estimated that 9\u0026ndash;52% of patients relapse after treatment\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, underlining the urgent need to understand the factors that contribute to relapse. Furthermore, given also that AN has the highest mortality rate of any psychiatric disorder\u003csup\u003e\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, there is an urgent need to improve treatment outcomes and reduce the high risk of mortality associated with this disorder\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Genome-wide association studies (GWAS) and case-controlled studies have identified several genetic risk factors associated with the disorder\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Among these, a specific allele of the brain-derived neurotrophic factor (BDNF) gene, specifically the Val66Met polymorphism (also known as rs6265), has received considerable attention since 2004\u003csup\u003e18\u003c/sup\u003e, and is now under intense scrutiny\u003csup\u003e119,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eKnown for its role in neuronal development, neurogenesis, and synaptic plasticity\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, BDNF has recently emerged as a key player in metabolic regulation, influencing processes both centrally in the brain and peripherally. Centrally, BDNF influences hypothalamic circuits that regulate energy balance, appetite, and satiety, contributing to its anorexic effects\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Peripherally, BDNF can directly affect metabolic processes, including increasing lipid oxidation and energy expenditure, ultimately leading to weight loss and increased physical activity levels\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, highlighting a comprehensive effect of BDNF on metabolic health and physical behavior.\u003c/p\u003e \u003cp\u003eThe Val66Met mutation in the BDNF gene, has been implicated in several metabolic diseases and psychiatric disorders, particularly in AN, affecting both neuroplasticity and metabolic regulation\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. In patients with AN, Met variant carriers show altered reward function, as evidenced by increased reward circuit activity in response to images of thinness in the ventral striatum, a key region for reward processing\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFinding animal models that mimic the full spectrum of AN symptoms is challenging due to their specificity to humans. A widely used AN-like rodent model is the activity-based anorexia (ABA) model, which combines time-limited access to food with free and continuous access to a running wheel\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. This paradigm leads to a paradoxical pattern of behavior in which animals voluntarily increase their physical activity levels while simultaneously reducing food intake, resulting in severe weight loss and physiological and behavioral changes reminiscent of human AN\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBDNF expression in brain regions associated with the neurobiological basis of AN has been studied, in part using the ABA paradigm. For example, rodents typically show reduced BDNF expression in the medial prefrontal cortex (mPFC) and amygdala\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. The mPFC is involved in decision-making and executive function, which may be impaired in AN, while the amygdala plays a key role in emotional responses and fear, which are elevated in AN\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Conversely, increased BDNF levels in the hippocampus, a region involved in memory and stress responses, suggest adaptive or maladaptive responses to food restriction and stress\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Levels remain relatively unchanged in the nucleus accumbens (NAc), which is central to reward processing, suggesting that some reward-related behaviors in AN may not be directly related to changes in BDNF in this region\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHowever, the relatively short duration of the ABA protocol may not fully capture the chronicity and complexity of human AN, limiting its translational relevance. This highlights the need for further refinement of this model to better understand the long-term neurobiological effects of AN and to develop more effective treatments. In this study, we used a modified version of the ABA protocol, known as the Food Restriction and Wheel (FRW) model, which incorporates the chronic aspect of AN, a critical feature that closely aligns with the prolonged course of the disorder \u003csup\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. The FRW model has been well validated, particularly in terms of its metabolic relevance, and effectively mimics the metabolic and endocrine changes observed in AN\u003csup\u003e\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe aim of this study was therefore to investigate the expression levels of BDNF, its receptor tropomyosin receptor kinase B (TrkB, neurotrophic tyrosine kinase, receptor, type 2 Ntrk2)\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, and its regulator N-acetyltransferase 8 like (Nat8l) in different brain regions. Nat8l, which regulates BDNF expression in the dorsal striatum (DS)\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, is therefore essential to investigate in order to understand its potential impact on the behavioral and physiological manifestations of AN. The brain regions studied were the DS, the NAc, the ventral tegmental area and the prefrontal cortex (PFC). They were chosen because of their critical role in the regulation of mood, specifically anxiety and depression, reward processing and cognitive function, areas that are commonly affected in people with AN\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. We focused on chronic food restriction, progressive refeeding and short refeeding periods. Progressive refeeding simulates the treatment phases of AN in hospitalized patients, and short-term refeeding episodes sometimes occur spontaneously in patients with AN. Progressive refeeding represents the nutritional rehabilitation phase, in which a gradual increase in calories is aimed at restoring physiological function and reversing low BMI\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Short refeeding, which can occur spontaneously in treatment settings, involves rapid and excessive food intake that can also interfere with recovery\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eAnimals\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eSeven-week-old C57BL/6 J female mice (Charles River Laboratories, L\u0026apos;Arbresle, France) weighing 18.3 \u0026plusmn; 0.1 g were housed in pairs in standard Plexiglas cages, to reduce external stressors such as isolation and hypothermia while ensuring adequate monitoring of food intake and physical activity. For one week, mice had access to food to calculate \u003cem\u003ead libitum\u003c/em\u003e food intake of standard chow (3% fat, 16% protein, 60% carbohydrate, 4% fibre, 2.79 kcal/g; Safe A04, Germany). Cages were maintained in a specific pathogen-free environment at a temperature range of 19 to 21 \u0026deg;C with a 12-hour light-dark cycle (with lights on from 06:00 am to 06:00 pm). Baseline body weight and \u003cem\u003ead libitum\u003c/em\u003e food intake were recorded in each cage during the first week acclimatization period and throughout the protocol. All experimental procedures were in accordance with the guidelines of the European Communities Council Directives (86/609/EEC). In addition, the study protocol was approved by the Regional Ethics Committee (CEEA.34) of the University Paris Cit\u0026eacute;.\u003c/p\u003e\n\u003col start=\"2\" type=\"1\"\u003e\n \u003cli\u003eFood restriction and refeeding protocols\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eWe used the food restriction and wheel protocols\u003csup\u003e32\u003c/sup\u003e. During the acclimatization week, daily food intake was measured during the last five days of \u003cem\u003ead libitum\u003c/em\u003e access to standard chow, to determine mean food consumption. Animals were then randomly divided into four groups based on initial body weight (mean 16.19 \u0026plusmn; 0.20 g) at the end of the acclimatization period to homogenise the groups. Groups were designated as \u003cem\u003ead libitum\u003c/em\u003e (AL), \u003cem\u003ead libitum\u003c/em\u003e with wheel (ALW), food restriction (FR) and food restriction with wheel (FRW). FR and FRW groups experienced 30% food restriction for three days followed by 50% for 15 days, based on the calculation of the mean food consumption during the \u003cem\u003ead libitum\u0026nbsp;\u003c/em\u003ephase. To prevent competition between littermates, food was provided directly in the home cages at 4:00 pm daily. ALW and FRW groups had access to a running wheel (diameter: 230 mm; width: 50 mm; 1 revolution = 0.72 m), whose activity was continuously monitored and analyzed during the peripandial period (1:00pm \u0026ndash; 6:00pm) (ActiWheel software; Intellibio, Seichamps, France). Body weight was monitored daily, and blood glucose levels were measured three times per week (FreeStyle Optium Neo, Abbott, Netherlands).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThree food restriction protocols were performed (Fig S1). In the first experiment, mice (n = 6 per group) were subjected to a 15-day food restriction protocol (Fig S1A). In experiment 2, mice (n = 8 per group) started with a 15-day food restriction protocol followed by a progressive refeeding regimen in which the amount of food was gradually increased every two days for a total period of 10 days (60%, 70%, 80%, 90%, and 100%; Fig S1B). In experiment 3, mice (n = 6 per group) were briefly refed under \u003cem\u003ead libitum\u003c/em\u003e conditions for 24 hours, after the 15-day restriction protocol (Fig S1C).\u0026nbsp;\u003c/p\u003e\n\u003col start=\"3\" type=\"1\"\u003e\n \u003cli\u003eTissue collection\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eAt the end of each experiment, mice were sacrificed using an anaesthetic injection (ketamine/xylazine, ketamine 100 mg/kg and xylazine 10 mg/kg, intraperitoneally), followed by cardiac puncture for blood collection. Blood was centrifuged at 1000 rpm for 10 minutes at -4 \u0026deg;C to separate plasma, which was then frozen on dry ice. Ethylenediaminetetraacetic acid (EDTA, 2mg/mL of blood) was added to the blood to prevent clotting, and polyhexamethylene biguanide (PHMB, 0.4 mM final concentration) was added to the plasma to inhibit protease activity. Brain tissues, including the prefrontal cortex (PFC), dorsal striatum (DS), nucleus accumbens (NAc), and ventral tegmental area (VTA) were microdissected, frozen in liquid nitrogen, and stored at -80\u0026deg;C.\u0026nbsp;\u003c/p\u003e\n\u003col start=\"4\" type=\"1\"\u003e\n \u003cli\u003eY maze reversal learning protocol\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eIn a separate study, 6 mice per group were subjected to the food restriction protocol for 15 days. On day 16, the Y-maze reversal test was performed to assess cognitive flexibility under food restriction and \u003cem\u003ead libitum\u003c/em\u003e conditions. The Y-maze consisted of two arms made of black Plexiglass, each measuring 35 cm long (Fig S1D).\u003c/p\u003e\n\u003cp\u003eThe protocol started on the 13\u003csup\u003eth\u003c/sup\u003e day of food restriction and consisted of two phases: habituation and testing. During habituation, the mice were habituated to the Y-maze with 15-minute sessions over two days and allowed to explore freely. To familiarize the mice with the reward, they were given half a Miel Pop cereal (Kellogg\u0026rsquo;s) at feeding time in their home cages.\u003c/p\u003e\n\u003cp\u003eDuring the testing phase, a small piece of Miel Pop was randomly placed in one of the arms to assess learning. Mice were placed at the intersection of the maze, and the time to choose an arm and the probability of choosing the correct arm (with the reward) were recorded. After entering in an arm, the chosen arm was closed, and the mouse was removed from the maze after 20 seconds. If the correct arm was chosen, the mouse consumed the reward; otherwise, no reward was given. Each mouse underwent 10 sessions per day until an 80% correct choice rate was achieved, indicating successful learning.\u003c/p\u003e\n\u003cp\u003eA reversal learning test was then performed, in which the reward location was switched to the opposite arm. Testing continued until a group reached 80% correct choices in the reversal phase (Fig S1E-F).\u003c/p\u003e\n\u003col start=\"5\" type=\"1\"\u003e\n \u003cli\u003eRNA extraction and cDNA preparation\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eFor RNA extraction, tissues were homogenized in TRIzol reagent, followed by phase separation and RNA precipitation. The extracted RNA was washed with ethanol (75%) and resuspended in RNase-free water. The concentration and purity of the RNA was determined spectrophotometrically. Subsequently, cDNA synthesis was performed using the Maxima cDNA synthesis kit (Thermo Fisher scientific, Waltham, MA USA).\u0026nbsp;\u003c/p\u003e\n\u003col start=\"6\" type=\"1\"\u003e\n \u003cli\u003eQuantitative polymerase chain reaction (qPCR) and RNA sequencing\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eReal-time quantitative PCR (qPCR) was performed using the SYBR Green qPCR Master Mix (2X, Roche Diagnostics, Meylan, France) on a 96-well plate (Roche Diagnostics, Meylan, France). The gene PPIA (cyclophilin A) was used as the housekeeping gene for normalization. The purity of the PCR products was assessed using dissociation curves. Data analysis was performed using the comparative threshold (Ct) method, with gene expression normalised to internal controls, and expressed using the 2\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003csup\u003e\u0026Delta;\u0026Delta;\u003c/sup\u003e\u003csup\u003eCt\u003c/sup\u003e method. PCR primers are described in Supplementary Table 1.\u003c/p\u003e\n\u003cp\u003eRNA sequencing was performed by the GENOM\u0026apos;IC core of the Cochin institute on the prepared samples. RNA sequencing was performed by the GENOM\u0026apos;IC core of the Cochin institute on the prepared samples. Libraries were prepared from 3 \u0026mu;g of extracted total RNA. The captured, purified and clonally amplified libraries were then sequenced on a Novaseq instrument (Illumina) according to the manufacturer\u0026apos;s recommendations. Sequence reads were aligned to the mouse genome (mm10) using BWA software. Downstream processing was carried out using the Genome Analysis Toolkit (GATK), SAMtools and Picard Tools (http://picard.sourceforge.net). Fastq files were then aligned using the STAR algorithm (version 2.7.6a), against the Ensembl release 101 reference (\u003ca href=\"http://aug2020.archive.ensembl.org/index.html\"\u003eGRCm38\u003c/a\u003e). Reads were then counted using RSEM (v1.3.1) and the statistical analyses on the read counts were performed using R (version 3.6.3) and the DESeq2 package (DESeq2_1.26.0) to determine the proportion of differentially expressed genes between two conditions. We used the standard DESeq2 normalization method (DESeq2\u0026rsquo;s median of ratios with the DESeq function), with a pre-filter of reads and genes (reads uniquely mapped on the genome, or up to 10 different loci with a count adjustment, and genes with at least 10 reads in at least 3 different samples). Following the package recommendations, we used the Wald test with the contrast function and the Benjamini-Hochberg FDR control procedure to identify the differentially expressed genes. R scripts and parameters are available on the platform, https://github.com/GENOM-IC-Cochin/RNA-Seq_analysis.\u003c/p\u003e\n\u003col start=\"7\" type=\"1\"\u003e\n \u003cli\u003eEnzyme-linked immunosorbent assay\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eTo quantify the total brain-derived neurotrophic factor (BDNF) in plasma, we used the BDNF ELISA kit (R\u0026amp;D Systems, Minneapolis, MN, USA) following the manufacturer\u0026rsquo;s protocol. Plasma samples were collected and stored at -80\u0026deg;C until assayed. Plasma samples were diluted 1:10 and the assay was performed in duplicate. The precision of the BDNF ELISA assay was assessed by intra- and inter-assay variability. Intra-assay precision was assessed by testing three samples of known concentration 20 times on a single plate, yielding CVs of 3.2%, 2.4%, and 3%. Inter-assay precision was assessed by 20 separate assays performed by at least three technicians on two batches of components, yielding CVs of 7.2%, 4.3%, and 4.7%.\u003c/p\u003e\n\u003col start=\"8\" type=\"1\"\u003e\n \u003cli\u003eStatistical analysis\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eStatistical analyses were performed using GraphPad Prism and R. Data were first tested for normality using the Shapiro-Wilk test to determine the appropriate statistical tests. Outliers were identified and removed using z-score analysis, where data points with a z-score greater than \u0026plusmn;3 were considered outliers. For normally distributed data, parametric tests such as one- or two-way analysis of variance (ANOVA) were used to compare group means, followed by post hoc analysis with Tukey\u0026apos;s test when appropriate.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe unpaired Student\u0026rsquo;s t-test test was used for comparisons between two groups. The Y-maze results were analysed using repeated measures ANOVA to account for the within-subject variability across sessions. Correlations between variables were assessed using Pearson\u0026apos;s correlation coefficients depending on the data distribution.\u003c/p\u003e\n\u003cp\u003eAll data are presented as mean \u0026plusmn; standard error of the mean (SEM), and a p-value of less than 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eBody weight and anticipatory activity responses to food restriction and refeeding in in AN-like mice\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe evaluated body weight and food anticipatory activity (FAA), defined as increased physical activity prior to scheduled feeding, under different feeding protocols (Fig. S1A-C). Mice in the FR and FRW groups exhibited significant body weight loss (~25%) by the end of the fasting period (p \u0026lt; 0.001, F(3,10) = 135.7, Fig. S1A), with no differences between FR and FRW, indicating no effect of wheel access on weight loss. FRW mice showed a significant increase in FAA compared to the ALW group (p = 0.018, F(1,4) = 15.02, Fig. S1A).\u003c/p\u003e\n\u003cp\u003eDuring progressive refeeding, mice recovered their baseline body weight over 10 days (Fig. S1B), with a concomitant reduction in FAA (Fig. S1B). In the short refeeding group, weight was recovered within one day (Fig. S1C), accompanied by an immediate cessation of FAA (Fig. S1C).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBehavioral responses in the Y-maze test\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCognitive function was assessed using the Y-maze reversal learning test. During the learning phase, FRW mice acquired the task faster than ALW mice (p = 0.004, t = 5.657 for day 3 and p = 0.011, t = 5.000 for day 10, Fig. 1A). However, there were no significant differences between groups in the reversal phase (Fig. 1A). FRW mice initially showed an impaired response during the first day of reversal learning, as indicated by a more significant reduction in the percentage of correct responses compared to the last day of learning (p = 0.024, F(5, 5) = 1.714, Fig. 1B). However, no permanent deficits were observed as FRW mice quickly relearned the task (p = 0.050, F(5, 5) = 2, Fig. 1C), indicating that they eventually adapt quickly to novel rules\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExpression of BDNF, TrkB, and Nat8l in different brain regions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlasma BDNF protein concentrations were not different during the restriction period, whereas progressive refeeding resulted in a significant decrease only in FR mice (AL vs FR p = 0.035, t = 2.231), with no significant effect observed in the short-term refeeding group (Fig. 1D).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe then quantified the mRNA expression levels of BDNF, TrkB, and Nat8l. In the DS, food restriction significantly reduced BDNF expression (AL \u003cem\u003evs\u003c/em\u003e FR p = 0.014, t = 2.679, Fig. 2A), with no effect of wheel access. Progressive refeeding and short refeeding fully restored BDNF levels (Fig. 2A). TrkB and Natl8l expression was not significantly altered by dietary restriction (Fig. 2C-2E). In the PFC, BDNF expression decreased with dietary restriction (AL \u003cem\u003evs\u003c/em\u003e FR p = 0.040, t = 2.193; ALW \u003cem\u003evs\u003c/em\u003e FRW p = 0.039, t = 2.209, Fig. 2B), but in contrast to DS, progressive refeeding did not restore these levels (ALW \u003cem\u003evs\u003c/em\u003e FRW p = 0.001, t = 3.734, Fig. 2B). However, shortrefeeding with wheel access reversed the reduction (AL \u003cem\u003evs\u003c/em\u003e FR p = 0.029, t = 2.359, Fig. 2B). TrkB expression in the PFC followed different trend than BDNF, with an increase during restriction and normalization by progressive refeeding (TrkB AL \u003cem\u003evs\u003c/em\u003e FR p = 0.007, t = 3.052, Fig. 2D). BDNF, TrkB, and Nat8l expression in the NAc and VTA was not affected by dietary protocols or wheel activity (Fig. S2A-B).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTwo-ways ANOVA showed that food restriction significantly decreased BDNF expression in both the DS and PFC (p = 0.004, F(1, 20) = 10.56 for DS, p = 0.006, F(1, 20) = 9.619 for PFC, Fig. S3), while no effect was observed on TrkB expression (Fig. S4). In contrast, Nat8l showed a significant interaction effect of restriction combined with running wheel exclusively in the DS (p = 0.005, F(1, 20) = 10.17, Fig. S5). However, no significant effect of wheel access alone was observed (Fig. S3-5). In addition, BDNF expression in both the DS and PFC was positively correlated with body weight and fasting blood glucose levels, a relationship that was not seen in the NAc (Fig. S6-8). This suggests region-specific responses to metabolic changes under chronic food restriction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhole RNA sequencing in the dorsal striatum and prefrontal cortex\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRNA sequencing in the DS confirmed the decrease in BDNF under chronic restriction and identified significant gene expression changes between AL and FR groups, as well as and between wheel access groups (ALW \u003cem\u003evs\u003c/em\u003e FRW) (Fig. 3A-D). Food restriction resulted in significant up- and down-regulation of genes (Fig. 3A, Table 1), while wheel access under \u003cem\u003ead libitum\u003c/em\u003e conditions also altered gene expression (Fig. 3B). However, wheel access generally had a minimal effect on gene expression in both ad libitum and restricted conditions (Fig. 3C-D).\u003c/p\u003e\n\u003cp\u003ePathway enrichment analysis revealed significant changes in key pathways, including \u0026quot;MAPK signalling,\u0026quot; \u0026quot;PI3K-Akt signalling,\u0026quot; and \u0026quot;Apoptosis\u0026quot;, reflecting the broad effects of dietary status on metabolic, neuronal, and immune functions. Similar effects were observed in the restriction and wheel-running groups (Fig. 3E,\u0026nbsp;Supplementary Tables 2 and 3).\u003c/p\u003e\n\u003cp\u003eCross-comparison of the transcriptomic data with the BDNF protein-protein interaction (PPI) network revealed that most of the differentially expressed genes were involved in metabolism, neuronal development, and immune regulation (Table 2, Supplementary Tables 4 to 8).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGene expression in the PFC followed a similar pattern to that in the DS, with minimal effects of wheel activity (Fig. S9A-D, Table 1). Wheel running reversed gene expression patterns under restriction (Fig. S10A-B, Table S2), with differences in the specific genes affected between the DS and PFC (Table S2). Pathway enrichment in the PFC highlighted immune regulation and cell-cell communication as major processes (Fig. S9E).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study shows that chronic food restriction, progressive refeeding, and short-term refeeding modulate BDNF, TrkB, and Nat8l expression in brain regions involved in cognitive and reward functions, with region-specific responses. Notably, refeeding failed to restore BDNF in the PFC, whereas short refeeding induced an increase of BDNF in the same region, suggesting differential responses depending on the type of refeeding. Importantly, TrkB mirrored BDNF patterns in the DS, whereas in the PFC, BDNF and TrkB were regulated in opposite directions. These findings suggest that nutritional status profoundly affects neuroplasticity and reward circuit dynamics, but in a region-specific manner. The Y-maze results suggest that chronic food restriction may impair cognitive flexibility in the short term, but this effect appears to be reversible, as no long-term deficits were observed.\u003c/p\u003e \u003cp\u003ePatients with AN often struggle with cognitive flexibility, particularly in task switching\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. The DS is critical for this function\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, with BDNF in the DS playing a key role\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e, in addition to BDNF in the PFC\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. While no long-term cognitive inflexibility was observed in our study, we did find short-term impairments, likely related to reduced BDNF in the DS and PFC due to chronic food restriction. This suggests that reduced BDNF in these regions may contribute to transient cognitive challenges during dietary stress.\u003c/p\u003e \u003cp\u003eOur results on plasma BDNF are consistent with previous studies showing that patients with AN exhibit reversible decreased plasma BDNF levels with weight recovery \u003csup\u003e\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, supporting not only the relevance of our model in mimicking key physiological aspects of AN but also the potential role of BDNF as a biomarker for the disease. However, no previous study has investigated BDNF mRNA or protein levels in the DS under chronic food restriction, making our study the first to do so. Previous studies have found no significant changes in the PFC, NAc or VTA in both male and female rats under similar conditions\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Our results are consistent with these findings in the mesolimbic regions. However, what we observed in the PFC is the opposite, possibly due to species or sex differences.\u003c/p\u003e \u003cp\u003eThe function of BDNF is not consistent across brain regions, with contrasting effects observed between the hippocampus/PFC and the reward circuits\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. In areas such as the PFC, higher levels of BDNF are often associated with improved cognitive outcomes and protection against stress-related mood disorders\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. However, in the mesolimbic pathway (NAc-VTA) and in the DS, BDNF appears to play a more complex and, in some cases, pro-depressive role\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Our findings contribute to the growing body of evidence suggesting that patients with AN may engage in food restrictive behaviors to modulate mood, possibly through reward pathways\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eNat8l, a positive regulator of BDNF expression in the DS, is thought to play a key role in modulating these mood-related effects\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Our results show that food restriction combined with wheel running, significantly reduced Nat8l expression in the DS, which may further reduce BDNF levels and contribute to stress susceptibility. Nat8l has been implicated in epigenetic modulation that influences brain resilience to chronic stress\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. The observed decrease in both Nat8l and BDNF under food restriction conditions suggests that the DS may become more susceptible to stress or fail to properly regulate reward mechanisms that are often disrupted in AN\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. This may contribute to the persistence of reduced feeding in AN as a maladaptive response to stress\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. Further studies are needed to determine whether these changes are part of a protective mechanism or a driver of maladaptive behaviors in AN, and how they might influence potential therapeutic targets aimed at restoring neuroplasticity in these regions.\u003c/p\u003e \u003cp\u003eThe RNA sequencing results revealed significant gene expression changes in the DS and PFC under chronic food restriction. Key genes such as \u003cem\u003eFasn\u003c/em\u003e, \u003cem\u003eGap43\u003c/em\u003e, and \u003cem\u003eTrem2\u003c/em\u003e were upregulated in the DS, indicating an adaptive response to metabolic stress, likely related to synaptic plasticity and cellular signalling as shown by GO analysis. In the PFC, genes such as \u003cem\u003eEgr4\u003c/em\u003e and \u003cem\u003eGolph3\u003c/em\u003e were altered, with GO analysis suggesting effects on immune regulation and metabolic processes. These findings suggest that food restriction-induced molecular changes in brain regions involved in cognitive flexibility and reward processing may contribute to the behavioral outcomes observed in AN.\u003c/p\u003e \u003cp\u003ePhysical activity increases BDNF in the PFC and DS as shown in rodent models. In our study, although physical activity had a limited overall effect on gene expression, it reversed the effects of food restriction on specific genes in the DS and PFC, such as \u003cem\u003eGap43\u003c/em\u003e, \u003cem\u003eTrem2\u003c/em\u003e, and \u003cem\u003eArhgef18\u003c/em\u003e. In the DS, genes such as \u003cem\u003eEgr4\u003c/em\u003e and \u003cem\u003eFasn\u003c/em\u003e were reversed by wheel access, suggesting that exercise may play a role in regulating metabolic pathways under chronic restriction. Similarly, \u003cem\u003eTceal5\u003c/em\u003e and \u003cem\u003eAtat1\u003c/em\u003e in the PFC were modulated by exercise. These results highlight the interaction between nutritional status and physical activity in modulating brain function under metabolic stress.\u003c/p\u003e \u003cp\u003eFinally, although BDNF protein can cross the blood-brain barrier\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e, our study suggests that plasma BDNF levels may not accurately reflect region-specific brain changes due to the heterogeneous regulation of BDNF in different brain regions and the lack of consistency with the expression pattern of a single brain region. Future work should focus on proteomic analyses to fully understand how BDNF and TrkB signalling contribute to the neurobiological basis of AN and explore whether other peripheral markers may more accurately reflect brain changes.\u003c/p\u003e \u003cp\u003eA limitation of this study is the use of the Y-maze reversal learning task, which may not have been sufficiently challenging enough to fully assess potential deficits in cognitive flexibility. Future studies should consider the use of more challenging tasks, such as the water maze. Food restriction may also induce olfactory sensitisation\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e, which may lead to a bias of the test we have used. In addition, although we measured BDNF mRNA expression in key brain regions, we did not quantify protein in these regions. Direct measurement of BDNF protein levels in the brain would provide a more complete understanding of their relationship with plasma BDNF levels and allow a more accurate cross-comparison between peripheral and central changes under restrictive conditions.\u003c/p\u003e \u003cp\u003eIn conclusion, chronic food restriction and subsequent refeeding significantly affects brain plasticity in the DS and PFC, regions critical for cognitive function, with implications for the development of more tailored treatment strategies in AN. Understanding these complex interactions between diet, brain plasticity, and physical activity is critical for improving treatment outcomes in this population.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of Interest\u003c/h2\u003e \u003cp\u003ePG received during the last 5 years fees for presentations at congresses or participation in scientific boards from Biogen, Janssen, Lundbeck, Merk, Otsuka, Richter and Viatris. The remaining authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eContributions\u003c/h2\u003e \u003cp\u003eOdile Viltart, Nicolas Ramoz, Jingxian Cao and Virginie Tolle designed the experiments. Jingxian Cao, Nicolas Lebrun, Shiou-ping Chen, Chlo\u0026eacute; Tezenas du Montcel, C\u0026eacute;line Cruciani-Guglielmacci and Odile Viltart performed the experiments. Jingxian Cao, Philip Gorwood, Nicolas Ramoz, and Odile Viltart carried out the analysis. The manuscript was drafted by Jingxian Cao, Nicolas Ramoz, and Odile Viltart. All authors discussed results, made figures, and edited the manuscript.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eThis work was supported by the F\u0026eacute;d\u0026eacute;ration pour la Recherche sur le Cerveau (FRC to NR), the Fondation de France \u0026ndash; Maladies Psychiatriques (FdF to PG), the Universit\u0026eacute; Paris Cit\u0026eacute; and the Institut National de la Sant\u0026eacute; et de la Recherche M\u0026eacute;dicale (INSERM). JC is a PhD student of a doctoral fellow of the University Paris Cit\u0026eacute;, ED562 BioSPC. CT is a recipient of a PhD fellowship (FDM202006011161) funded by the Fondation pour la Recherche M\u0026eacute;dicale (FRM). The authors would like to thank Ludivine Therreau and Gwena\u0026euml;lle Le Pen of the IPNP PhenoBrain core facility and the staff of the animal facility, for their invaluable help in the handling and managing the animals used in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMicali, N., Hagberg, K. W., Petersen, I. \u0026amp; Treasure, J. L. The incidence of eating disorders in the UK in 2000\u0026ndash;2009: findings from the General Practice Research Database. BMJ Open 3, e002646 (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMainz, V., Schulte-R\u0026uuml;ther, M., Fink, G. R., Herpertz-Dahlmann, B. \u0026amp; Konrad, K. Structural Brain Abnormalities in Adolescent Anorexia Nervosa Before and After Weight Recovery and Associated Hormonal Changes. 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Biol Psychiatry 54, 994\u0026ndash;1005 (2003).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWayda-Zalewska, M. \u003cem\u003eet al.\u003c/em\u003e Emotion Dynamics and Emotion Regulation in Anorexia Nervosa: A Systematic Review of Ecological Momentary Assessment Studies. \u003cem\u003eIJERPH\u003c/em\u003e 19, 13659 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMiller, S. P., Erickson, S. J., Branom, C. \u0026amp; Steiner, H. Habitual Response to Stress in Recovering Adolescent Anorexic Patients. Child Psychiatry Hum Dev 40, 43\u0026ndash;54 (2009).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuarda, A. S., Schreyer, C. C., Boersma, G. J., Tamashiro, K. L. \u0026amp; Moran, T. H. Anorexia nervosa as a motivated behavior: Relevance of anxiety, stress, fear and learning. Physiology \u0026amp; Behavior 152, 466\u0026ndash;472 (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePan, W., Banks, W. A., Fasold, M. B., Bluth, J. \u0026amp; Kastin, A. J. Transport of brain-derived neurotrophic factor across the blood\u0026ndash;brain barrier. Neuropharmacology 37, 1553\u0026ndash;1561 (1998).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eApelbaum, A. F. Rats Habituated to Chronic Feeding Restriction Show a Smaller Increase in Olfactory Bulb Reactivity Compared to Newly Fasted Rats. Chemical Senses 28, 389\u0026ndash;395 (2003).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"719\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 719px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Dysregulation of mRNA expression levels by chronic food restriction or wheel running in the dorsal striatum (DS) and prefrontal cortex (PFC)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTissue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDown-regulated\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUp-regulated\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 388px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTop 10 significant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eDS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003eRestriction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e671\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 388px;\"\u003e\n \u003cp\u003eH1f2, Gap43, Fads1, Rgs11, Trem2, Arhgef18, Lrrc8c, Golph3,Tcim, Gm19439\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003eWheel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 388px;\"\u003e\n \u003cp\u003eGm26876, Gm4219, Gm44294, Gm49749, Map4k1,Gm5786, Gm37132, nPi19, C230086J09Rik\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003ePFC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003eRestriction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 388px;\"\u003e\n \u003cp\u003eRskr, Igfn1, Panx2, Akt2, Colq, 4930447C04Rik, Gm29674, Tmem74b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003eWheel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 388px;\"\u003e\n \u003cp\u003eGm37728, Gm9320, 2900076G11Rik, Rps27l, Pomc, A930035D04Rik, Kif11, Rps15a-ps6, Gm4117 Pm20d1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 719px;\"\u003e\n \u003cp\u003e*Genes with an adjusted p-value \u0026lt; 0.05 and a Log2Fold Change \u0026lt;-0.5 or \u0026gt;0.5 were selected for inclusion.\u0026quot;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"702\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 702px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Modulation of mRNA expression levels of genes in protein-protein interaction with BDNF by chronic food restriction or wheel running in the dorsal striatum (DS) and prefrontal cortex (PFC)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTissue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 146px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 317px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect of Restriction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 163px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect of Wheel Running\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eDS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eup-regulated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 317px;\"\u003e\n \u003cp\u003eMme, Atp7a, Fgf22, Ppargc1a, Ror1, Calca, Jak2, Pik3r1, Slc2a1, Musk, Ehd1, Nt5e, Stat3, Htr1b, Nrtn, Gfap, Htr2a, Dnmt3b, Fkbp5, Mc4r, Pkp2, Scn10a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 163px;\"\u003e\n \u003cp\u003eAtp7a, Calca\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003edown-regulated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 317px;\"\u003e\n \u003cp\u003eTph2, Itgam, Pkp1, Ngfr, Fgf3, Trem2, Nr4a2, Bche, Fgf17, Rasal3, S100b, Cx3cr1, Sec16b, mt-Nd2, Aif1, Tph1, Cck, Mog, Grin3b, Mmp2, Cadps2, Ptn, Rtn4r, Fgf10, Ntsr1, Artn, Stmn2, Esr1, Angpt1, Nfia, Npas4, Fos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 163px;\"\u003e\n \u003cp\u003eGrap2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003ePFC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eup-regulated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 317px;\"\u003e\n \u003cp\u003eGrm8, Tacr1, Ddc, Mmp9, Ppp1r1b, Pkp2, Dnmt3b, Fkbp5, Mc4r, Scn10a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 163px;\"\u003e\n \u003cp\u003ePm20d1, Bmp4, Pomc\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003edown-regulated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 317px;\"\u003e\n \u003cp\u003eItgam, Neurog2, Npas4, Trem2, Fgf17, Cx3cr1, Nptx2, Tek, Artn, Bche, Grm3, mt-Nd2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 163px;\"\u003e\n \u003cp\u003eFgf18, Dynlt1c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 702px;\"\u003e\n \u003cp\u003e*Protein-protein interactions were analyzed using string.com. Genes with an adjusted p-value \u0026lt; 0.05 and a Log2Fold Change \u0026lt;-0.5 or \u0026gt;0.5 were selected for inclusion.\u0026quot;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"translational-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"tp","sideBox":"Learn more about [Translational Psychiatry](http://www.nature.com/tp/)","snPcode":"41398","submissionUrl":"https://mts-tp.nature.com/cgi-bin/main.plex","title":"Translational Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Brain Derived Neurotrophic Factor, tropomyosin receptor kinase B/Neurotrophic tyrosine kinase receptor type 2, Anorexia nervosa, Food restriction, Animal model, Cognitive flexibility, Reward system","lastPublishedDoi":"10.21203/rs.3.rs-6260210/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6260210/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAnorexia nervosa (AN) is a complex psychiatric disorder characterized by severe caloric restriction and distorted body image, leading to significant psychological and physiological complications. Brain-derived neurotrophic factor (BDNF) plays a critical role in cognitive function and metabolic regulation. BDNF has been identified as a genetic risk factor for AN. This study examines the effects of food restriction, refeeding and short-term refeeding on the expression of BDNF and its receptor (tropomyosin receptor kinase B TrkB/Ntrk2) in key brain regions involved in reward and cognitive function. We assessed BDNF mRNA levels in the dorsal striatum (DS), nucleus accumbens (NAc), ventral tegmental area (VTA), and prefrontal cortex (PFC) of AN-like mice subjected to different feeding regimes combined with or without physical activity. Cognitive flexibility was assessed using the Y-maze test. Whole RNA sequencing was also performed to analyse gene expression changes. Food restriction induced a transient decrease in cognitive flexibility and significantly decreased BDNF expression in the DS and PFC. Progressive refeeding restored BDNF in the DS but not the PFC. Short refeeding restored BDNF levels to baseline. TrkB expression is increased by restriction only in the PFC. The presence of a running wheel cancelled these effects, suggesting an interaction between physical activity and diet. Pathway analysis of dysregulated genes revealed enrichment in immune regulation and cell-cell communication pathways. These findings highlight the complex relationship between diet, exercise, and brain function in AN and suggest avenues for further research into the clinical relevance of BDNF and TrkB as biomarkers of eating disorders.\u003c/p\u003e","manuscriptTitle":"Unraveling the brain expression of BDNF in a mouse model of Anorexia Nervosa","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-16 08:56:58","doi":"10.21203/rs.3.rs-6260210/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-05-06T09:30:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-04-11T00:10:56+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-04-08T12:49:14+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-03-28T02:23:36+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-03-27T12:23:29+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-03-27T09:03:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-21T11:40:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-21T11:39:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Translational Psychiatry","date":"2025-03-21T09:15:01+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2025-03-20T10:50:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"translational-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"tp","sideBox":"Learn more about [Translational Psychiatry](http://www.nature.com/tp/)","snPcode":"41398","submissionUrl":"https://mts-tp.nature.com/cgi-bin/main.plex","title":"Translational Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"616f2299-07b6-47bc-9917-49a2467e6ab8","owner":[],"postedDate":"April 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46286885,"name":"Biological sciences/Physiology"},{"id":46286886,"name":"Biological sciences/Neuroscience/Molecular neuroscience"}],"tags":[],"updatedAt":"2025-10-18T07:10:37+00:00","versionOfRecord":{"articleIdentity":"rs-6260210","link":"https://doi.org/10.1038/s41398-025-03618-7","journal":{"identity":"translational-psychiatry","isVorOnly":false,"title":"Translational Psychiatry"},"publishedOn":"2025-10-17 04:00:00","publishedOnDateReadable":"October 17th, 2025"},"versionCreatedAt":"2025-04-16 08:56:58","video":"","vorDoi":"10.1038/s41398-025-03618-7","vorDoiUrl":"https://doi.org/10.1038/s41398-025-03618-7","workflowStages":[]},"version":"v1","identity":"rs-6260210","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6260210","identity":"rs-6260210","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}