Age-Related Changes in Density, Arborization and Expression of NMDA Receptors of Somatostatin Martinotti Neurons in the Mouse mPFC

Age-Related Changes in Density, Arborization and Expression of NMDA Receptors of Somatostatin Martinotti Neurons in the Mouse mPFC | 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 Research Article Age-Related Changes in Density, Arborization and Expression of NMDA Receptors of Somatostatin Martinotti Neurons in the Mouse mPFC Blanca Sánchez-Moreno, Yaiza Gramuntell, Patrycja Klimczak, Evelina Bäcker, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7657662/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Aging is associated with progressive alterations in cortical circuits that compromise cognitive function. Somatostatin-positive (SST+) Martinotti interneurons, which regulate pyramidal cell activity in the medial prefrontal cortex (mPFC), are particularly relevant for inhibitory control, yet their age-related vulnerability remains poorly understood. Here, we examined SST+ Martinotti cells in mice at 3, 9, and 16 months of age, focusing on neuronal density, dendritic arborization, and expression of NMDA receptor subunits GluN1 and GluN2B. Our findings reveal a significant decline in SST+ cell density in aged male mice, whereas female mice displayed an increase in dendritic arborization with age. Analysis of NMDA receptor puncta showed a reduction in GluN1 density and puncta size in older animals, particularly in females. In contrast, GluN2B puncta density decreased in both sexes, while puncta size increased, suggesting greater clustering with aging. These results indicate that SST+ Martinotti cells undergo structural and molecular remodeling in a sex-dependent manner, which may disturb excitatory-inhibitory balance in the mPFC. Such alterations could underlie age-related deficits in prefrontal function and highlight SST+ interneurons as critical targets of cortical aging. aging NMDA receptors GluN1 GluN2B Somatostatin mPFC Figures Figure 1 Figure 2 Figure 3 Introduction Aging is a natural process characterized by a progressive decline of physiological, behavioral, and social functions over time. During aging, the brain undergoes multiple molecular and cellular changes, including reduced mitochondrial fitness, metabolic alterations, increased oxidative stress, and accumulated DNA damage (Feltes 2025). Changes in synaptic plasticity caused by these brain processes contribute to neuronal miscommunication (Ridderinkhof and Krugers 2022). Moreover, those age-related brain changes raise the risk of mental illnesses like schizophrenia and depression in addition to accelerating the onset of neurodegenerative diseases (Sikora et al. 2021). One of the brain regions most susceptible to age-related changes is the prefrontal cortex (PFC), which plays a crucial role in cognitive functions such as working memory, executive functions, and goal-directed behavior. Earlier work suggests that aging does not lead to significant neuronal loss but rather to synaptic changes (Morrison and Baxter 2012). For instance, both humans (de Brabander et al. 1998; Uylings and de Brabander 2002) and animals (Grill and Riddle 2002; Markham and Juraska 2002) show age-related reductions in dendritic length and complexity, particularly in the apical and basal dendrites of the PFC excitatory pyramidal neurons. Additionally, aging is associated with a selective loss of glutamatergic axospinous synapses, especially in thin spines, whereas more stable mushroom and stubby spines remain largely unaffected (Dumitriu et al. 2010). Moreover, the excitatory/inhibitory balance in the PFC appears to shift with age, resulting in elevated inhibitory activity (McQuail et al. 2015). The PFC contains 10–20% inhibitory GABAergic interneurons in addition to excitatory neurons (Xu et al. 2019). These interneurons can be classified into three non-overlapping types in the rodent neocortex: parvalbumin-expressing (PV+), 5-HT3A receptor-expressing, and somatostatin-expressing (SST+) interneurons (Riedemann 2019). SST + interneurons constitute around 30% of all GABAergic interneurons, although their proportion in the PFC is higher than in other cortices (Kim et al. 2017). SST + cells can be divided into two distinct populations: Martinotti and non-Martinotti cells. Martinotti cells represent 55–100% of all somatostatin interneurons and are mainly located in layers 2/3 and 5 but can be found sparsely in layers 4 and 6. They are characterized by dense axonal projections into layer 1, where they make extensive lateral arborizations (Riedemann 2019; Yavorska and Wehr 2016). Non-Martinotti cells include SST + cells with a bitufted or basket cell anatomy with local axons projecting to close neurons in deep layers (Urban-Ciecko and Barth 2016). SST + interneurons are involved in learning (Cummings and Clem 2020) and working memory (Abbas et al. 2018; Kim et al. 2016), processes, which are affected during aging. Additionally, SST + interneurons appear to be selectively vulnerable in different disorders, such as Alzheimer's disease (Waller et al. 2020), schizophrenia, and bipolar disorder type 1 (Wang et al. 2011). The glutamatergic system markedly declines during aging, both in humans and animal models, showing reduced levels of glutamate in several cortical regions (Hädel et al. 2013; Huang et al. 2017; Kaiser et al. 2005; Saransaari and Oja 1995; Schubert et al. 2004). Most of this glutamatergic transmission is mediated by ionotropic receptors, of which the best studied are the NMDARs. NMDARs are tetrameric receptors composed of four subunits. There are always two obligatory GluN1 subunits and two GluN2 or GluN3 subunits. There are four different GluN2 (GluN2A-D) and two GluN3 (GluN3A-B) subunits (Hansen et al. 2017). The activation of these receptors must be tightly regulated, since their physiological stimulation is essential for neuronal survival, but overstimulation can cause glutamate toxicity and, thus, cell death (Gasiorowska et al. 2021). Some studies have found a reduction in NMDAR density in the PFC of aged rats (Mitchell and Anderson 1998) and a reduction in the expression of GluN2A in the same region of aged humans (Lu et al. 2004), but these studies did not discriminate the neuronal populations affected. We have studied SST + interneurons in the mice hippocampus, and we have shown a decrease in GluN2B, but not of GluN1 subunit expression, during aging (Gramuntell et al. 2021). However, it is not yet known how NMDAR subunit expression is affected during aging in the various neuronal population of the PFC. Sex significantly influences brain structure and function, making it relevant to our study. Sex differences have been found in SST + cell density in multiple subcortical structures, including the amygdala and the thalamus (Kim et al. 2017). Moreover, NMDAR subunit distribution in the PFC seems to be affected by sex: female rats express higher levels of GluN1, while males express higher levels of the GluN2A subunit (Wang et al. 2015). No differences have been found in the GluN2B subunit (Page and Coutellier 2018). The goal of the current study was to determine how age affects the structure of STT + interneurons in the medial PFC (mPFC) of male and female mice. Additionally, we have examined the expression of two NMDAR subunits (GluN1 and GluN2B) within this specific interneuron population. The GIN transgenic mice, which constitutively express the Green Fluorescence Protein (GFP) in the Martinotti cells of the mPFC (Gilabert-Juan et al. 2013), will be used for this purpose. Materials and Methods Animals Thirty transgenic mice [GIN (GFP-expressing Inhibitory Neurons), Tg(GadGFP)45704Swn] (Jackson Laboratories, Bar Harbor, Maine, United States) were used in this study. They constitutively express the green fluorescent protein (GFP) in a subpopulation of SST-expressing interneurons (Oliva et al., 2000). Mice were bred and maintained in the animal facility of the Universitat de València and were divided into 3 age groups (3 months, 9 months, and 16 months old). All groups contained 5 males and 5 females. Animals were maintained under controlled conditions of temperature (25°C) and humidity (50%), with food and water ad libitum and on a standard light/dark cycle (12 h cycle). All animal experimentation was conducted in accordance with Directive 2010/63/EU of the European Parliament and of the Council of 22 September 2010 on the protection of animals used for scientific purposes and was approved by the Committee on Bioethics of the Universitat de València. Every effort was made to minimize the number of animals used and their suffering. Histological Procedures of mice tissue When they reached 3, 9, or 16 months old, mice were deeply anesthetized with pentobarbital and perfused transcardially, first for 1 min with saline (NaCl 0.9%) and then for 30 min with 4% paraformaldehyde in sodium phosphate buffer 0.1 M, pH 7.4 (PB). The left hemisphere was cut in 100 µm thick coronal sections with a vibratome (Leica VT 1000E, Leica, Nussloch, Germany) to analyze dendritic arborization in GFP-expressing interneurons. The right hemisphere was cut in 50 µm-thick coronal sections for the study of the expression of NMDARs in the SST + interneurons. Analysis of the GFP + cell density and dendritic arborization One subseries of sections from each animal was processed “free floating” for GFP immunohistochemistry. Sections were first washed three times with phosphate-buffered saline (PBS) for 10 min per washing. After that, sections were incubated for 1 min in an antigen unmasking solution (0.01 M citrate buffer, pH 6) at 100°C. Then, sections were washed as described above. To block non-specific unions, sections were treated for 1 h with 10% normal donkey serum (NDS) (Jackson ImmunoResearch Laboratories, West Grove, PA, United States) in PBS with 0.2% Triton-X100 (Sigma–Aldrich, St. Louis, MO, United States). Sections were washed 3 times in PBS and were incubated for 48 h at 4°C with primary antibody (chicken anti-GFP IgY, Abcam, 1:2000) diluted in PBS 0.2% Triton-X100. After washing, sections were incubated for 2 h at room temperature with a fluorescent secondary antibody (donkey anti-chicken CF488A, Biotum, 1:800) diluted in PBS 0.2% Triton-X100. Sections were then rinsed with PB 0.1 M, mounted on slides, and coverslipped using Dako fluorescent mounting medium (Agilent, Santa Clara, CA, United States). For the study of GFP + interneurons density, we used a Leica TCS SP5 confocal microscope with a 10x objective and a 4 µm Z-step size. The area of the infralimbic and the prelimbic regions of the mPFC were delimited and the number of GFP + interneurons inside the area were counted. For the dendritic arborization analysis, a 40x objective and a 2 µm Z-step size was used. Six isolated GFP + interneurons with their soma located either in the infralimbic or the prelimbic area of the medial prefrontal cortex were selected. In order to be analyzed, GFP-expressing cells had to fulfill the following features: (1) the cell must not show any truncated dendrites, (2) the dendritic arbor of the cell must show at least one process with a length greater than 80 µm, and (3) the soma must be located at least 30 µm deep from the surface of the tissue. The stacks obtained were then processed using FIJI software (NIH) to obtain 2D and 3D reconstruction of dendritic arbor, in which the distance of the branching and terminal points was analyzed (Arshadi et al. 2021). To determine the degree of dendritic arborization, we used the Sholl analysis, measuring the number of intersections of the dendrites with circles of increasing radius (20 µm each in our study) centered in the soma (Ferreira et al. 2014; Sholl 1953). Analysis of GluN1 and GluN2B Expression The immunohistochemical protocol employed was similar to that described above for GFP immunohistochemistry. For every subunit of NMDAR (GluN1 and GluN2B), we used different subseries of sections. Sections were incubated with either rabbit anti-GluN1 (Alomone, 1:400) or rabbit anti-GluN2B (Alomone, 1:4000) together with chicken anti-GFP IgY (Abcam, 1:500) primary antibodies for 48 h at 4°C. After washing, sections were incubated for 2 h at room temperature with donkey anti-rabbit (Biotium, A555, 1:800) and donkey anti-chicken (Biotium, CF488A, 1:800) secondary antibodies. Sections were then rinsed with PB 0.1 M, mounted on slides, and coverslipped using Dako fluorescent mounting medium (Agilent, United States). Controls were performed omitting the anti-GluN1 or anti-GluN2B antibody, as well as incubating with these antibodies previously pre-absorbed overnight with an excess of its immunogenic peptide (GluN1 blocking peptide, Alomone, Jerusalem, Israel) or (GluN2B blocking peptide, Alomone, Jerusalem, Israel), respectively. No immunolabeling was observed in these controls. We used a Leica TCS SP5 confocal microscope with a 63x objective, 3.5x digital zoom, and a 0.5 µm Z-step size for the study of GluN1 + and GluN2B + puncta on the somata and the periphery of GFP-expressing interneurons. Six isolated GFP + somata from the prelimbic area and six isolated GFP + somata from the infralimbic area per animal were selected randomly and pooled together for the analysis. The images were analyzed using Fiji software as follows: 3 consecutive planes were selected in the center of the cell soma, and a Z-projection was performed. The images were converted to 8-bit deep images and binarized using a threshold to delineate the cell soma. This outline was expanded 0.5 µm to obtain two regions, the cell somata (the original outline) and the periphery (between both outlines). Afterwards, the background was subtracted with a rolling value of 50, and a Gaussian Blur with a sigma value of 1 was applied. Then, a macro based on (Guirado et al. 2018) was applied to binarize the image to delineate the GluN1 or GluN2B immunoreactive puncta (larger than 0.04 µm 2 ). We calculated the density of puncta, the percentage of the area covered by them, and the mean size of the puncta. Statistics The statistical analysis was based on the indications of (Diester et al. 2019), first by analyzing the pooled data from both sexes and then the data from females and males separately. After checking the normality and homoscedasticity of the data, a two-way ANOVA test was used to analyze the dendritic arborization profile, and a one-way ANOVA or a Kruskal-Wallis test was used to analyze the density of GFP + cells and the density, area covered, and size of the GluN1 or GluN2B puncta. Significant one-way ANOVAs were followed by Tukey post hoc tests. For graphical representations, mean ± SEM was used in all cases. Results Somatostatin + cell density is decreased in mPFC of male aged mice The GFP-expressing neurons in the GIN mouse used in the present study preferentially label Martinotti cells in layers II/III and Va of the PFC (Oliva et al., 2020; Ma et al., 2006; Gilabert-Juan et al., 2013). We first analyzed the density of these cells in the mPFC at 3-, 9- and 16-month-old animals (Figs. 1a1-d1). No differences were found when pooling both sexes together ( p = 0.2, Fig. 1g1) or in females (p = 0.26, Fig. 1g3). Nevertheless, a significant decrease in cell density was found between 3- and 16-month-old (* p = 0.020, Fig. 1g2) and 9- and 16-month-old (* p = 0.032, Fig. 1g2) male mice. The dendritic arborization of somatostatin + neurons is increased in female aged mice To determine the effect of aging on dendritic arborization of Martinotti cells in the mPFC, a Sholl analysis was performed (Figs. 1a2-f2). When pooling females and males together, the analysis showed a more elaborate arborization profile in 16-month-old mice, compared to 3- and 9-month-old mice (** p = 0.0011, Fig. 1h1). There were specific significant arborization increases at 100 µm from the soma between 9- and 16-month-old animals (* p = 0.029, Fig. 1h1); and at 180 µm between 3- and 16-month-old animals (* p = 0.048, Fig. 1h1) and 9- and 16-month-old animals (* p = 0.037, Fig. 1h1). When females were analyzed separately, 16-month-old mice showed an increased arborization compared to 3- and 9-month-old mice (** p = 0.0023, Fig. 1h3). There were significant differences at 120 µm between 3- and 16-month-old females (* p = 0.046, Fig. 1H3); and at 160 µm between 3- and 16-month-old females (* p = 0.043, Fig. 1h3). However, there were no discernible differences in the arborization profile of males ( p = 0.25, Fig. 1h2), suggesting that the female group was responsible for the initial differences seen when the two sexes were examined together. The density of GluN1 puncta in somatostatin + decreases in the mPFC of old mice, and the clustering increases We analyzed the size of GluN1 immunoreactive puncta, the density and the area covered by these structures in the somata (Figs. 2a-c) and periphery (Figs. 2c-f) of Martinotti cells. The analysis of the density of GluN1 immunoreactive puncta in the somata of Martinotti cells indicated a significant decrease between 3- and 16-month-old mice when females and males were pooled together (* p = 0.018, Fig. 2g1). No significant differences were found when males ( p = 0.38, Fig. 2g2) and females ( p = 0.062, Fig. 2g3) were analyzed separately. The analysis of the area covered by GluN1 + puncta showed no significant changes due to aging when both sexes were pooled together ( p = 0.44, Fig. 2h1), in males ( p = 0.36, Fig. 2h2) or in females ( p = 0.93, Fig. 2h3). We occasionally noticed the presence of bigger structures made of clustered GluN1 + puncta in 16-month-old mice. The analysis of the mean size of GluN1 + puncta indicated a significant increase between 3- and 16-month-olds when both sexes were pooled (** p = 0.007, Fig. 2i1) and in females (* p = 0.025, Fig. 2i3), but not in males (p = 0.12, Fig. 2i2). In the cell periphery, the analysis of the density of GluN1 immunoreactive puncta indicated a significant decrease when females and males were pooled together between 3- and 9-month-old mice (* p = 0.019, Fig. 2j1) but not separately in males (p = 0.089, Fig. 2j2) nor in females (p = 0.14, Fig. 2j3). The analysis of the area covered by GluN1 puncta indicated a significant decrease between 3- and 9-month-old mice when both sexes were pooled (* p = 0.036, Fig. 2K1) but not separately in males (p = 0.072, Fig. 2k2) nor in females (p = 0.29, Fig. 2k3). However, the analysis of the mean size of GluN1 puncta showed no differences when females and males were analyzed together ( p = 0.18, Fig. 2l1), in males (p = 0.31, Fig. 2l2) nor in females ( p = 0.34, Fig. 2l3). + Figure 2 Analysis of the effect of aging on GluN1 receptor distribution in the somata and periphery of SST + interneurons. a-f GFP and GluN1 inmunostaining in 3-month-old ( a ), 9-month-old ( b ), 16-month-old ( c ) male mice and in 3-month-old ( d ), 9-month-old ( e ), 16-month-old ( f ) female mice. Scale bar: 10 µm. g-l Density, percentage of area covered and mean size of GluN1 inmunoreactive puncta in the somata ( g, h, i ) and periphery ( j, k, l) of SST + cells in male and female mice ( 1 ), male mice ( 2 ) and female mice ( 3 ). Data presented as mean ± SEM The density of GluN2B punta decreases with aging in the mPFC of male and female mice, and the clustering increases We analyzed the size of GluN2B immunoreactive puncta and the density and area covered by these structures both in the somata (Figs. 3 a-c) and periphery (Figs. 3 d-f) of Martinotti cells. The analysis of the density of GluN2B immunoreactive puncta in the somata of Martinotti cells indicated a significant decrease between 3- and 16-month-old mice when both sexes were pooled together (**** p < 0.0001, Fig. 3g1), in males (* p = 0.022, Fig. 3g2) and in females (** p = 0.0096, Fig. 3g3). Additionally, a significant decrease was found between 9- and 16-month-old mice when both sexes were pooled together (**** p < 0.0001, Fig. 3g1) and in males (* p = 0.049, Fig. 3g2), but not in females (p = 0.30. Figure 2g3). However, the analysis of the area covered by GluN2B puncta showed no differences in pooled females and males ( p = 0.87, Fig. 3h1) in males ( p = 0.83, Fig. 3h2) and in females ( p = 0.25, Fig. 3h3). Larger structures made of clustered GluN2B + puncta were commonly seen in 16-month-old mice, as well as in 9-month-old mice. The analysis of the mean size of GluN2B puncta indicated a significant increase between 3- and 16-month-old mice when both sexes were pooled together, (**** p < 0.0001 Fig. 3i1), in males (** p = 0.0044, Fig. 3i2) and in females (** p = 0.0018, Fig. 3i3). A significant difference was also found between 9- and 16-month-old mice when both sexes were pooled together (* p = 0.014, Fig. 3i1) and in females (* p = 0.012, Fig. 3i3), but not in males (p = 0.10, Fig. 3i2). In the cell periphery, the analysis of the density of GluN2B immunoreactive puncta indicated a significant increase between 3- and 16-month-old mice when both sexes were pooled together (** p = 0.0034, Fig. 3j1) and in males (* p = 0.027, Fig. 3j2). Additionally, a significant increase was found between 9- and 16-month-old mice when both sexes were pooled together (** p = 0.0034, Fig. 3j1), but not in males (p = 0.071, Fig. 3j2). No significant differences were found in females (p = 0.25, Fig. 3j3). The analysis of the area covered by GluN2B puncta showed no differences in pooled females and males ( p = 0.058, Fig. 3k1, or in females ( p = 0.87, Fig. 3K3), but it is decreased in old male mice ( p = 0.046, Fig. 3k2). The analysis of the mean size of the GluN2B puncta showed a significant decrease between 3- and 16-month-old mice when both sexes were pooled together (* p = 0.048, Fig. 3l1), but no differences were found when males (p = 0.081, Fig. 3l2) and females (p = 0.044, Fig. 3l3) were analyzed separately. Discussion This study illustrates age-related modifications in the density and architecture of SST + interneurons of the mice mPFC. In males, the cell density significantly decreased from 3-month-old to older mice. According to a prior study, after adolescence, the density of SST + neurons in the female mice's mPFC rises (Du et al. 2018). This article also showed a decrease in SST + cells in the cingulate cortex of males, which appears similar to the present findings in the mPFC. We measured neuronal densities at 16 months, whereas they measured them at 12 months. It is also important to note that while we focused our analysis in SST + cells, most of which are Martinotti cells, in the entire mPFC, Du and colleagues examined all SST neurons in the infralimbic, prelimbic, and cingulate regions separately. These differences may be the cause of the disparities. It's also important to remember that testosterone, but not estrogen, increases the expression of the SST RNA (Argente et al. 1990; Chowen et al. 1993), and decline of this hormone during male aging may have an effect on cell survival (Veiga et al. 2004). Furthermore, we have demonstrated previously that chronic stress reduces the density of SST + neurons in the mPFC of male mice (Gilabert-Juan et al. 2013); consequently, it is possible that aging has similar effects. In reference to the enhanced dendritic arborization observed in 16-month-old females, we have found in former studies that male mice exposed to chronic stress had altered dendritic arborization of SST + neurons in the mPFC, hippocampus, and amygdala (Gilabert-Juan et al. 2013; 2011; 2017). Additionally, we have described that as female mice age, the dendritic spine density in hippocampal SST + cells decreases (Gramuntell et al. 2021). Given that a drop in estrogen levels can lead to higher stress response and decreased excitatory neural activity (Foster and Kumar 2025; McEwen et al. 2016), the dendritic structural changes observed in the present study in aged females but not in males may also be due to hormonal changes. Previous work from our laboratories has described that the structure, connectivity and plasticity of hippocampal SST + interneurons is modulated by estrogen (Perez-Rando et al. 2022). Additionally, it has been noted that SST + neurons in the mPFC can be modulated by changes in the signaling of certain neurotransmitters, such as the endogenous opioid system (Wang et al. 2019), which declines during aging (Hamm and Knisely 1985). This suggests that these neurons are highly plastic and responsive to extracellular signals. It's interesting to note that glutamate receptors seem to mediate some of the effects of estrogens on rodent and monkey PFC structure and connectivity (Hao et al. 2006; Khan et al. 2013). Female mice with low estradiol levels show greater basal glutamatergic transmission in the mPFC than female mice with high estradiol levels. Estradiol also controlled synaptic plasticity, favoring synaptic potentiation in a way that was dependent on GluN2B. Furthermore, GluN2B-mediated NMDA receptor transmission was enhanced by estrogen receptor β activation, which restored synaptic potentiation (Galvin and Ninan 2014). Although we did not control for the females' estrous cycle in this study, which may have an impact on some metrics and be one of its drawbacks, it is plausible that some of the aging-related alterations that have been noted were brought on by the decline in estrogens (Nicholson et al. 2020). The PFC is highly involved in the encoding of working memory, a form of short-term memory that consists of the temporary arrangement, processing, and storage of information that collectively directs reasoning and goal-directed behavior (Arnsten et al. 2012; Goldman-Rakic 1995). Estradiol replacement therapy can help women, female nonhuman primates, and rodents with working memory problems associated with aging and menopause (Hampson 2018). In rats' mPFC, GluN2B RNA expression changes as they age (Gandy et al. 2023) and decreases in ovariectomized rats when compared to control rats (Morissette et al. 2008). This suggests that the NMDA subunit may play a part in the decline in working memory, despite some studies suggesting the opposite in excitatory neurons (McQuail et al. 2016). Additionally, it has been shown that GluN2B alterations in the PFC are linked to the restoration of working memory when estradiol is administered (Hara et al. 2018). In male rats, the protein levels of the GluN2B subunit in the mPFC showed a significant decline with aging in some studies (Zhao et al. 2009) or not significant changes in others (Liu et al. 2008). Measuring the amount of protein or RNA in various cellular fractions or compartments may yield different results because, as our study has demonstrated, aging-associated changes may be more connected to structural conformation and cellular distribution rather than to the control of protein or RNA expression. Although excitatory neurons were the primary target of these described alterations, given our findings on the changes of GluN2B subunit restructures in SST + neurons with age, it is plausible that these interneurons also contribute significantly to working memory function through NMDA receptors. The changes observed in the structure and number of GluN1 puncta are less significant than the ones for GluN2B. As discussed above, changes in GluN2B during aging have been broadly reported, but the GluN1 subunit of the NMDA receptors seem to have less modifications with age. Lower levels of GluN1 in fast-spiking interneurons of the mPFC of male mice during aging have been associated with less cognitive flexibility (McQuail et al. 2021). Furthermore, the impact of aging on the expression of GluN1 subunits with distinct splice cassettes varied significantly, displaying a different proportion of GluN1 proteins along the lifespan (Das and Magnusson 2011). These changes in the protein subtypes content may also be responsible for the receptor conformation changes observed in our study. However, another study found no evidence of a change in GluN1 subunit expression with aging (Zhao et al. 2009); this might be due to changes in splice variants and conformation. Our study was limited by the age of the animals, with the oldest being 16 months—an age at which cognitive decline in rodents begins, though these animals are not typically considered elderly (Foster and Kumar 2025). However, most transgenic animals in this strain did not survive much beyond this point and showed health issues like tumors and hair loss. There are no previous studies examining cognitive tasks in older animals of this strain, and regrettably, we were unable to conduct behavioral tests. All things considered, our findings contribute to a better understanding of how aging affects the number of SST + cells, their structural plasticity and the composition and expression of NMDAR in the mPFC of male and female mice. The study of these receptors is crucial because behavioral and cognitive dysfunctions may be caused by changes in their expression, conformation, and physiology and may result in neural balance dysregulation related to aging decline. Declarations Funding: This work was supported by the projects PID2021-127595OB-I00 and PID2021-126258OA-I00 financed by the Spanish Ministry of Science and Innovation (AEI/10.13039/501100011033, “FEDER Una manera de hacer Europa”), SI3-PJI-2021-00417, Universidad Autónoma de Madrid - Comunidad Autónoma de Madrid (Programa de estímulo a la investigación de jóvenes doctores), the Valencian Regional Government (CIPROM/2023/28), the Fundación Mutua Madrileña, the Fundación Alicia Koplowitz, and The Spanish Network of Stress Research (REIS) (to J.N. and J. G-J.); B. S-M. is a recipient of a predoctoral fellowship from the Spanish Ministry of Universities Predoctoral Fellowship Program (FPU). References Abbas AI, Sundiang MJM, Henoch B, et al (2018) Somatostatin interneurons facilitate hippocampal-prefrontal synchrony and prefrontal spatial encoding. Neuron 100(4):926–939.e3. https://doi.org/10.1016/j.neuron.2018.09.029 Argente J, Chowen-Breed JA, Steiner RA, Clifton DK (1990) Somatostatin messenger RNA in hypothalamic neurons is increased by testosterone through activation of androgen receptors and not by aromatization to estradiol. Neuroendocrinology 52(4):342–349. https://doi.org/10.1159/000125618 Arnsten AFT, Wang MJ, Paspalas CD (2012) Neuromodulation of thought: flexibilities and vulnerabilities in prefrontal cortical network synapses. Neuron 76(1):223–239. https://doi.org/10.1016/j.neuron.2012.08.038 Arshadi C, Günther U, Eddison M, Harrington KIS, Ferreira TA (2021) SNT: a unifying toolbox for quantification of neuronal anatomy. Nat Methods 18(4):374–377. https://doi.org/10.1038/s41592-021-01105-7 de Brabander JM, Kramers RJ, Uylings HB (1998) Layer-specific dendritic regression of pyramidal cells with ageing in the human prefrontal cortex. Eur J Neurosci 10(4):1261–1269. https://doi.org/10.1046/j.1460-9568.1998.00137.x Chowen JA, Argente J, González-Parra S, García-Segura LM (1993) Differential effects of the neonatal and adult sex steroid environments on the organization and activation of hypothalamic growth hormone-releasing hormone and somatostatin neurons. Endocrinology 133(6):2792–2802. https://doi.org/10.1210/endo.133.6.7902269 Cummings KA, Clem RL (2020) Prefrontal somatostatin interneurons encode fear memory. Nat Neurosci 23(1):61–74. https://doi.org/10.1038/s41593-019-0552-7 Das SR, Magnusson KR (2011) Changes in expression of splice cassettes of NMDA receptor GluN1 subunits within the frontal lobe and memory in mice during aging. Behav Brain Res 222(1):122–133. https://doi.org/10.1016/j.bbr.2011.03.045 Diester CM, Banks ML, Neigh GN, Negus SS (2019) Experimental design and analysis for consideration of sex as a biological variable. Neuropsychopharmacology 44(13):2159–2162. https://doi.org/10.1038/s41386-019-0458-9 Du X, Serena K, Hwang WJ, et al (2018) Prefrontal cortical parvalbumin and somatostatin expression and cell density increase during adolescence and are modified by BDNF and sex. Mol Cell Neurosci 88:177–188. https://doi.org/10.1016/j.mcn.2018.02.001 Dumitriu D, Hao J, Hara Y, et al (2010) Selective changes in thin spine density and morphology in monkey prefrontal cortex correlate with aging-related cognitive impairment. J Neurosci 30(22):7507–7515. https://doi.org/10.1523/JNEUROSCI.6410-09.2010 Feltes BC (2025) Analyzing different aging theories in the context of the brain: DNA damage, inflammation, redox imbalance, and neurodevelopment intertwine. Biogerontology 26(3):105. https://doi.org/10.1007/s10522-025-10243-w Ferreira TA, Blackman AV, Oyrer J, et al (2014) Neuronal morphometry directly from bitmap images. Nat Methods 11(10):982–984. https://doi.org/10.1038/nmeth.3125 Foster TC, Kumar A (2025) Sex, senescence, senolytics, and cognition. Front Aging Neurosci 17:1555872. https://doi.org/10.3389/fnagi.2025.1555872 Galvin C, Ninan I (2014) Regulation of the mouse medial prefrontal cortical synapses by endogenous estradiol. Neuropsychopharmacology 39(9):2086–2094. https://doi.org/10.1038/npp.2014.56 Gandy HM, Hollis F, Hernandez CM, McQuail JA (2023) Aging or chronic stress impairs working memory and modulates GABA and glutamate gene expression in prelimbic cortex. Front Aging Neurosci 15:1306496. https://doi.org/10.3389/fnagi.2023.1306496 Gasiorowska A, Wydrych M, Drapich P, et al (2021) The biology and pathobiology of glutamatergic, cholinergic, and dopaminergic signaling in the aging brain. Front Aging Neurosci 13:654931. https://doi.org/10.3389/fnagi.2021.654931 Gilabert-Juan J, Bueno-Fernandez C, Castillo-Gomez E, Nacher J (2017) Reduced interneuronal dendritic arborization in CA1 but not in CA3 region of mice subjected to chronic mild stress. Brain Behav 7(2):e00534. https://doi.org/10.1002/brb3.534 Gilabert-Juan J, Castillo-Gomez E, Guirado R, Moltó MD, Nacher J (2013) Chronic stress alters inhibitory networks in the medial prefrontal cortex of adult mice. Brain Struct Funct 218(6):1591–1605. https://doi.org/10.1007/s00429-012-0479-1 Gilabert-Juan J, Castillo-Gomez E, Pérez-Rando M, Moltó MD, Nacher J (2011) Chronic stress induces changes in the structure of interneurons and in the expression of molecules related to neuronal structural plasticity and inhibitory neurotransmission in the amygdala of adult mice. Exp Neurol 232(1):33–40. https://doi.org/10.1016/j.expneurol.2011.07.009 Goldman-Rakic PS (1995) Cellular basis of working memory. Neuron 14(3):477–485. https://doi.org/10.1016/0896-6273(95)90304-6 Gramuntell Y, Klimczak P, Coviello S, Perez-Rando M, Nacher J (2021) Effects of aging on the structure and expression of NMDA receptors of somatostatin expressing neurons in the mouse hippocampus. Front Aging Neurosci 13:782737. https://doi.org/10.3389/fnagi.2021.782737 Grill JD, Riddle DR (2002) Age-related and laminar-specific dendritic changes in the medial frontal cortex of the rat. Brain Res 937(1–2):8–21. https://doi.org/10.1016/s0006-8993(02)02457-5 Guirado R, Carceller H, Castillo-Gómez E, Castrén E, Nacher J (2018) Automated analysis of images for molecular quantification in immunohistochemistry. Heliyon 4(6):e00669. https://doi.org/10.1016/j.heliyon.2018.e00669 Hädel S, Wirth C, Rapp M, Gallinat J, Schubert F (2013) Effects of age and sex on the concentrations of glutamate and glutamine in the human brain. J Magn Reson Imaging 38(6):1480–1487. https://doi.org/10.1002/jmri.24123 Hamm RJ, Knisely JS (1985) Environmentally induced analgesia: an age-related decline in an endogenous opioid system. J Gerontol 40(3):268–274. https://doi.org/10.1093/geronj/40.3.268 Hampson E (2018) Estrogens, aging, and working memory. Curr Psychiatry Rep 20(12):109. https://doi.org/10.1007/s11920-018-0972-1 Hansen KB, Yi F, Perszyk RE, Menniti FS, Traynelis SF (2017) NMDA receptors in the central nervous system. In: Burnashev N, Szepetowski P (eds) NMDA receptors: methods and protocols. Springer. https://doi.org/10.1007/978-1-4939-7321-7_1 Hao J, Rapp PR, Leffler AE, et al (2006) Estrogen alters spine number and morphology in prefrontal cortex of aged female rhesus monkeys. J Neurosci 26(9):2571–2578. https://doi.org/10.1523/JNEUROSCI.3440-05.2006 Hara Y, Crimins JL, Puri R, et al (2018) Estrogen alters the synaptic distribution of phospho-GluN2B in the dorsolateral prefrontal cortex while promoting working memory in aged rhesus monkeys. Neuroscience 394:303–315. https://doi.org/10.1016/j.neuroscience.2018.09.021 Huang D, Liu D, Yin J, Qian T, Shrestha S, Ni H (2017) Glutamate-glutamine and GABA in brain of normal aged and patients with cognitive impairment. Eur Radiol 27(7):2698–2705. https://doi.org/10.1007/s00330-016-4669-8 Kaiser LG, Schuff N, Cashdollar N, Weiner MW (2005) Age-related glutamate and glutamine concentration changes in normal human brain: 1H MR spectroscopy study at 4 T. Neurobiol Aging 26(5):665–672. https://doi.org/10.1016/j.neurobiolaging.2004.07.001 Khan MM, Dhandapani KM, Zhang QG, Brann DW (2013) Estrogen regulation of spine density and excitatory synapses in rat prefrontal and somatosensory cerebral cortex. Steroids 78(6):614–623. https://doi.org/10.1016/j.steroids.2012.12.005 Kim D, Jeong H, Lee J, et al (2016) Distinct roles of parvalbumin- and somatostatin-expressing interneurons in working memory. Neuron 92(4):902–915. https://doi.org/10.1016/j.neuron.2016.09.023 Kim Y, Yang GR, Pradhan K, et al (2017) Brain-wide maps reveal stereotyped cell type-based cortical architecture and subcortical sexual dimorphism. Cell 171(2):456–469.e22. https://doi.org/10.1016/j.cell.2017.09.020 Liu P, Smith PF, Darlington CL (2008) Glutamate receptor subunits expression in memory-associated brain structures: regional variations and effects of aging. Synapse 62(11):834–841. https://doi.org/10.1002/syn.20563 Lu T, Pan Y, Kao S-Y, et al (2004) Gene regulation and DNA damage in the ageing human brain. Nature 429(6994):883–891. https://doi.org/10.1038/nature02661 Markham JA, Juraska JM (2002) Aging and sex influence the anatomy of the rat anterior cingulate cortex. Neurobiol Aging 23(4):579–588. https://doi.org/10.1016/s0197-4580(02)00004-0 McEwen BS, Nasca C, Gray JD (2016) Stress effects on neuronal structure: hippocampus, amygdala, and prefrontal cortex. Neuropsychopharmacology 41(1):3–23. https://doi.org/10.1038/npp.2015.171 McQuail JA, Beas BS, Kelly KB, et al (2016) NR2A-containing NMDARs in the prefrontal cortex are required for working memory and associated with age-related cognitive decline. J Neurosci 36(50):12537–12548. https://doi.org/10.1523/JNEUROSCI.2332-16.2016 McQuail JA, Beas BS, Kelly KB, Hernandez CM, Bizon JL, Frazier CJ (2021) Attenuated NMDAR signaling on fast-spiking interneurons in prefrontal cortex contributes to age-related decline of cognitive flexibility. Neuropharmacology 197:108720. https://doi.org/10.1016/j.neuropharm.2021.108720 McQuail JA, Frazier CJ, Bizon JL (2015) Molecular aspects of age-related cognitive decline: the role of GABA signaling. Trends Mol Med 21(7):450–460. https://doi.org/10.1016/j.molmed.2015.05.002 Mitchell JJ, Anderson KJ (1998) Age-related changes in [3H]MK-801 binding in the Fischer 344 rat brain. Neurobiol Aging 19(3):259–265. https://doi.org/10.1016/s0197-4580(98)00058-x Morissette M, Le Saux M, Di Paolo T (2008) Effect of oestrogen receptor alpha and beta agonists on brain N-methyl-D-aspartate receptors. J Neuroendocrinol 20(8):1006–1014. https://doi.org/10.1111/j.1365-2826.2008.01754.x Morrison JH, Baxter MG (2012) The aging cortical synapse: hallmarks and implications for cognitive decline. Nat Rev Neurosci 13(4):240–250. https://doi.org/10.1038/nrn3200 Nicholson K, MacLusky NJ, Leranth C (2020) Synaptic effects of estrogen. Vitamins Horm 114:167–210. https://doi.org/10.1016/bs.vh.2020.06.002 Page CE, Coutellier L (2018) Adolescent stress disrupts the maturation of anxiety-related behaviors and alters the developmental trajectory of the prefrontal cortex in a sex- and age-specific manner. Neuroscience 390:265–277. https://doi.org/10.1016/j.neuroscience.2018.08.030 Perez-Rando M, Guirado R, Tellez-Merlo G, Carceller H, Nacher J (2022) Estradiol regulates polysialylated form of the neural cell adhesion molecule expression and connectivity of O-LM interneurons in the hippocampus of adult female mice. Neuroendocrinology 112(1):51–67. https://doi.org/10.1159/000515052 Ridderinkhof KR, Krugers HJ (2022) Horizons in human aging neuroscience: from normal neural aging to mental (fr)agility. Front Hum Neurosci 16:815759. https://doi.org/10.3389/fnhum.2022.815759 Riedemann T (2019) Diversity and function of somatostatin-expressing interneurons in the cerebral cortex. Int J Mol Sci 20(12):2952. https://doi.org/10.3390/ijms20122952 Saransaari P, Oja SS (1995) Age-related changes in the uptake and release of glutamate and aspartate in the mouse brain. Mech Ageing Dev 81(2–3):61–71. https://doi.org/10.1016/0047-6374(95)01583-l Schubert F, Gallinat J, Seifert F, Rinneberg H (2004) Glutamate concentrations in human brain using single voxel proton magnetic resonance spectroscopy at 3 Tesla. NeuroImage 21(4):1762–1771. https://doi.org/10.1016/j.neuroimage.2003.11.014 Sholl DA (1953) Dendritic organization in the neurons of the visual and motor cortices of the cat. J Anat 87(Pt 4):387–406 Sikora E, Bielak-Zmijewska A, Dudkowska M, et al (2021) Cellular senescence in brain aging. Front Aging Neurosci 13:646924. https://doi.org/10.3389/fnagi.2021.646924 Urban-Ciecko J, Barth AL (2016) Somatostatin-expressing neurons in cortical networks. Nat Rev Neurosci 17(7):401–409. https://doi.org/10.1038/nrn.2016.53 Uylings HBM, de Brabander JM (2002) Neuronal changes in normal human aging and Alzheimer’s disease. Brain Cogn 49(3):268–276. https://doi.org/10.1006/brcg.2001.1500 Veiga S, Melcangi RC, Doncarlos LL, Garcia-Segura LM, Azcoitia I (2004) Sex hormones and brain aging. Exp Gerontol 39(11–12):1623–1631. https://doi.org/10.1016/j.exger.2004.05.008 Waller R, Mandeya M, Viney E, Simpson JE, Wharton SB (2020) Histological characterization of interneurons in Alzheimer’s disease reveals a loss of somatostatin interneurons in the temporal cortex. Neuropathology 40(4):336–346. https://doi.org/10.1111/neup.12649 Wang AY, Lohmann KM, Yang CK, et al (2011) Bipolar disorder type 1 and schizophrenia are accompanied by decreased density of parvalbumin- and somatostatin-positive interneurons in the parahippocampal region. Acta Neuropathol 122(5):615–626. https://doi.org/10.1007/s00401-011-0881-4 Wang X, Liu P, Ma L, Wang F (2019) Opioid signal transduction regulates the dendritic morphology of somatostatin and parvalbumin interneurons in the medial prefrontal cortex. Neuroreport 30(8):592–599. https://doi.org/10.1097/WNR.0000000000001254 Wang Y, Ma Y, Hu J, et al (2015) Prenatal chronic mild stress induces depression-like behavior and sex-specific changes in regional glutamate receptor expression patterns in adult rats. Neuroscience 301:363–374. https://doi.org/10.1016/j.neuroscience.2015.06.008 Xu P, Chen A, Li Y, Xing X, Lu H (2019) Medial prefrontal cortex in neurological diseases. Physiol Genomics 51(9):432–442. https://doi.org/10.1152/physiolgenomics.00006.2019 Yavorska I, Wehr M (2016) Somatostatin-expressing inhibitory interneurons in cortical circuits. Front Neural Circuits 10:76. https://doi.org/10.3389/fncir.2016.00076 Zhao X, Rosenke R, Kronemann D, et al (2009) The effects of aging on N-methyl-D-aspartate receptor subunits in the synaptic membrane and relationships to long-term spatial memory. Neuroscience 162(4):933–945. https://doi.org/10.1016/j.neuroscience.2009.05.018 Additional Declarations No competing interests reported. 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14:23:22","extension":"html","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":91193,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7657662/v1/d9140a75d89d27a2fe8498ec.html"},{"id":94439927,"identity":"51e2396f-02fa-4e28-9e01-43883cb3d807","added_by":"auto","created_at":"2025-10-27 14:23:17","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":321739,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eAnalysis of the effect of aging on SST+ cell density and dendritic arborization. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003ea-f\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e GFP inmunostaining (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) and dendritic arborization reconstruction (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) in 3-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e), 9-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e), 16-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ec\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) male mice and in 3-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e), 9-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ee\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e), 16-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ef\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) female mice. Scale bar: 100 µm. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003eg\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e SST+ cell density in the mPFC of male and female mice (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003eg1\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e), male mice (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003eg2\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) and female mice (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003eg3\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e). \u003c/em\u003e\u003cem\u003e\u003cstrong\u003eh\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Sholl analysis of GFP SST+ interneurons of male and female mice (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003eh1\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e), male mice (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003eh2\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) and female mice (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003eh3\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e). Data presented as mean ± SEM\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7657662/v1/2d046d4d10097da8583a9ba5.jpg"},{"id":94438983,"identity":"d0376bd0-df56-4fae-b555-23168f13518f","added_by":"auto","created_at":"2025-10-27 14:22:12","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":517149,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eAnalysis of the effect of aging on GluN1 receptor distribution in the somata and periphery of SST+ interneurons.\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e a-f\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e GFP and GluN1 inmunostaining in 3-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e), 9-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e), 16-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ec\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) male mice and in 3-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e), 9-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ee\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e), 16-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ef\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) female mice. Scale bar: 10 µm. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003eg-l\u003c/strong\u003e\u003c/em\u003e\u003cem\u003eDensity, percentage of area covered and mean size of GluN1 inmunoreactive puncta in the somata (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003eg, h, i\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) and periphery (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ej, k, l)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e of SST+ cells in male and female mice (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e), male mice (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) and female mice (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e). Data presented as mean ± SEM\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7657662/v1/3667f4a999e8cb03e94f6309.jpg"},{"id":94439327,"identity":"95f517a1-f09e-4cd0-bf5d-ab875e9ee1c0","added_by":"auto","created_at":"2025-10-27 14:22:36","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":460991,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eAnalysis of the effect of aging on GluN2B receptor distribution in the somata and periphery of SST+ interneurons. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003ea-f\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e GFP and GluN2B inmunostaining in 3-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e), 9-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e), 16-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ec\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) male mice and in 3-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e), 9-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ee\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e), 16-month-old (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ef\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) female mice. Scale bar: 10 µm. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003eg-l \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eDensity, percentage of area covered and mean size of GluN2B inmunoreactive puncta in the somata (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003eg, h, i\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) and periphery (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003ej, k, l)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e of SST+ cells in male and female mice (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e), male mice (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) and female mice (\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e). Data presented as mean ± SEM\u003c/em\u003e\u003c/p\u003e","description":"","filename":"figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7657662/v1/adb8247301eca8fb9e56b656.jpg"},{"id":97673728,"identity":"cf4647a8-54ef-4a52-a2f0-68bcb8e22e45","added_by":"auto","created_at":"2025-12-08 09:41:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1999441,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7657662/v1/46013f8f-873f-44de-bfd8-3dc8b9b29286.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Age-Related Changes in Density, Arborization and Expression of NMDA Receptors of Somatostatin Martinotti Neurons in the Mouse mPFC","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAging is a natural process characterized by a progressive decline of physiological, behavioral, and social functions over time. During aging, the brain undergoes multiple molecular and cellular changes, including reduced mitochondrial fitness, metabolic alterations, increased oxidative stress, and accumulated DNA damage (Feltes 2025). Changes in synaptic plasticity caused by these brain processes contribute to neuronal miscommunication (Ridderinkhof and Krugers 2022). Moreover, those age-related brain changes raise the risk of mental illnesses like schizophrenia and depression in addition to accelerating the onset of neurodegenerative diseases (Sikora et al. 2021).\u003c/p\u003e\u003cp\u003eOne of the brain regions most susceptible to age-related changes is the prefrontal cortex (PFC), which plays a crucial role in cognitive functions such as working memory, executive functions, and goal-directed behavior. Earlier work suggests that aging does not lead to significant neuronal loss but rather to synaptic changes (Morrison and Baxter 2012). For instance, both humans (de Brabander et al. 1998; Uylings and de Brabander 2002) and animals (Grill and Riddle 2002; Markham and Juraska 2002) show age-related reductions in dendritic length and complexity, particularly in the apical and basal dendrites of the PFC excitatory pyramidal neurons. Additionally, aging is associated with a selective loss of glutamatergic axospinous synapses, especially in thin spines, whereas more stable mushroom and stubby spines remain largely unaffected (Dumitriu et al. 2010). Moreover, the excitatory/inhibitory balance in the PFC appears to shift with age, resulting in elevated inhibitory activity (McQuail et al. 2015).\u003c/p\u003e\u003cp\u003eThe PFC contains 10\u0026ndash;20% inhibitory GABAergic interneurons in addition to excitatory neurons (Xu et al. 2019). These interneurons can be classified into three non-overlapping types in the rodent neocortex: parvalbumin-expressing (PV+), 5-HT3A receptor-expressing, and somatostatin-expressing (SST+) interneurons (Riedemann 2019). SST\u0026thinsp;+\u0026thinsp;interneurons constitute around 30% of all GABAergic interneurons, although their proportion in the PFC is higher than in other cortices (Kim et al. 2017). SST\u0026thinsp;+\u0026thinsp;cells can be divided into two distinct populations: Martinotti and non-Martinotti cells. Martinotti cells represent 55\u0026ndash;100% of all somatostatin interneurons and are mainly located in layers 2/3 and 5 but can be found sparsely in layers 4 and 6. They are characterized by dense axonal projections into layer 1, where they make extensive lateral arborizations (Riedemann 2019; Yavorska and Wehr 2016). Non-Martinotti cells include SST\u0026thinsp;+\u0026thinsp;cells with a bitufted or basket cell anatomy with local axons projecting to close neurons in deep layers (Urban-Ciecko and Barth 2016). SST\u0026thinsp;+\u0026thinsp;interneurons are involved in learning (Cummings and Clem 2020) and working memory (Abbas et al. 2018; Kim et al. 2016), processes, which are affected during aging. Additionally, SST\u0026thinsp;+\u0026thinsp;interneurons appear to be selectively vulnerable in different disorders, such as Alzheimer's disease (Waller et al. 2020), schizophrenia, and bipolar disorder type 1 (Wang et al. 2011).\u003c/p\u003e\u003cp\u003eThe glutamatergic system markedly declines during aging, both in humans and animal models, showing reduced levels of glutamate in several cortical regions (H\u0026auml;del et al. 2013; Huang et al. 2017; Kaiser et al. 2005; Saransaari and Oja 1995; Schubert et al. 2004). Most of this glutamatergic transmission is mediated by ionotropic receptors, of which the best studied are the NMDARs. NMDARs are tetrameric receptors composed of four subunits. There are always two obligatory GluN1 subunits and two GluN2 or GluN3 subunits. There are four different GluN2 (GluN2A-D) and two GluN3 (GluN3A-B) subunits (Hansen et al. 2017). The activation of these receptors must be tightly regulated, since their physiological stimulation is essential for neuronal survival, but overstimulation can cause glutamate toxicity and, thus, cell death (Gasiorowska et al. 2021). Some studies have found a reduction in NMDAR density in the PFC of aged rats (Mitchell and Anderson 1998) and a reduction in the expression of GluN2A in the same region of aged humans (Lu et al. 2004), but these studies did not discriminate the neuronal populations affected. We have studied SST\u0026thinsp;+\u0026thinsp;interneurons in the mice hippocampus, and we have shown a decrease in GluN2B, but not of GluN1 subunit expression, during aging (Gramuntell et al. 2021). However, it is not yet known how NMDAR subunit expression is affected during aging in the various neuronal population of the PFC.\u003c/p\u003e\u003cp\u003eSex significantly influences brain structure and function, making it relevant to our study. Sex differences have been found in SST\u0026thinsp;+\u0026thinsp;cell density in multiple subcortical structures, including the amygdala and the thalamus (Kim et al. 2017). Moreover, NMDAR subunit distribution in the PFC seems to be affected by sex: female rats express higher levels of GluN1, while males express higher levels of the GluN2A subunit (Wang et al. 2015). No differences have been found in the GluN2B subunit (Page and Coutellier 2018).\u003c/p\u003e\u003cp\u003eThe goal of the current study was to determine how age affects the structure of STT\u0026thinsp;+\u0026thinsp;interneurons in the medial PFC (mPFC) of male and female mice. Additionally, we have examined the expression of two NMDAR subunits (GluN1 and GluN2B) within this specific interneuron population. The GIN transgenic mice, which constitutively express the Green Fluorescence Protein (GFP) in the Martinotti cells of the mPFC (Gilabert-Juan et al. 2013), will be used for this purpose.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eAnimals\u003c/h2\u003e\u003cp\u003eThirty transgenic mice [GIN (GFP-expressing Inhibitory Neurons), Tg(GadGFP)45704Swn] (Jackson Laboratories, Bar Harbor, Maine, United States) were used in this study. They constitutively express the green fluorescent protein (GFP) in a subpopulation of SST-expressing interneurons (Oliva et al., 2000). Mice were bred and maintained in the animal facility of the Universitat de Val\u0026egrave;ncia and were divided into 3 age groups (3 months, 9 months, and 16 months old). All groups contained 5 males and 5 females. Animals were maintained under controlled conditions of temperature (25\u0026deg;C) and humidity (50%), with food and water ad libitum and on a standard light/dark cycle (12 h cycle). All animal experimentation was conducted in accordance with Directive 2010/63/EU of the European Parliament and of the Council of 22 September 2010 on the protection of animals used for scientific purposes and was approved by the Committee on Bioethics of the Universitat de Val\u0026egrave;ncia. Every effort was made to minimize the number of animals used and their suffering.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eHistological Procedures of mice tissue\u003c/h3\u003e\n\u003cp\u003eWhen they reached 3, 9, or 16 months old, mice were deeply anesthetized with pentobarbital and perfused transcardially, first for 1 min with saline (NaCl 0.9%) and then for 30 min with 4% paraformaldehyde in sodium phosphate buffer 0.1 M, pH 7.4 (PB). The left hemisphere was cut in 100 \u0026micro;m thick coronal sections with a vibratome (Leica VT 1000E, Leica, Nussloch, Germany) to analyze dendritic arborization in GFP-expressing interneurons. The right hemisphere was cut in 50 \u0026micro;m-thick coronal sections for the study of the expression of NMDARs in the SST\u0026thinsp;+\u0026thinsp;interneurons.\u003c/p\u003e\n\u003ch3\u003eAnalysis of the GFP + cell density and dendritic arborization\u003c/h3\u003e\n\u003cp\u003eOne subseries of sections from each animal was processed \u0026ldquo;free floating\u0026rdquo; for GFP immunohistochemistry. Sections were first washed three times with phosphate-buffered saline (PBS) for 10 min per washing. After that, sections were incubated for 1 min in an antigen unmasking solution (0.01 M citrate buffer, pH 6) at 100\u0026deg;C. Then, sections were washed as described above. To block non-specific unions, sections were treated for 1 h with 10% normal donkey serum (NDS) (Jackson ImmunoResearch Laboratories, West Grove, PA, United States) in PBS with 0.2% Triton-X100 (Sigma\u0026ndash;Aldrich, St. Louis, MO, United States).\u003c/p\u003e\u003cp\u003eSections were washed 3 times in PBS and were incubated for 48 h at 4\u0026deg;C with primary antibody (chicken anti-GFP IgY, Abcam, 1:2000) diluted in PBS 0.2% Triton-X100. After washing, sections were incubated for 2 h at room temperature with a fluorescent secondary antibody (donkey anti-chicken CF488A, Biotum, 1:800) diluted in PBS 0.2% Triton-X100. Sections were then rinsed with PB 0.1 M, mounted on slides, and coverslipped using Dako fluorescent mounting medium (Agilent, Santa Clara, CA, United States).\u003c/p\u003e\u003cp\u003eFor the study of GFP\u0026thinsp;+\u0026thinsp;interneurons density, we used a Leica TCS SP5 confocal microscope with a 10x objective and a 4 \u0026micro;m Z-step size. The area of the infralimbic and the prelimbic regions of the mPFC were delimited and the number of GFP\u0026thinsp;+\u0026thinsp;interneurons inside the area were counted.\u003c/p\u003e\u003cp\u003eFor the dendritic arborization analysis, a 40x objective and a 2 \u0026micro;m Z-step size was used. Six isolated GFP\u0026thinsp;+\u0026thinsp;interneurons with their soma located either in the infralimbic or the prelimbic area of the medial prefrontal cortex were selected. In order to be analyzed, GFP-expressing cells had to fulfill the following features: (1) the cell must not show any truncated dendrites, (2) the dendritic arbor of the cell must show at least one process with a length greater than 80 \u0026micro;m, and (3) the soma must be located at least 30 \u0026micro;m deep from the surface of the tissue. The stacks obtained were then processed using FIJI software (NIH) to obtain 2D and 3D reconstruction of dendritic arbor, in which the distance of the branching and terminal points was analyzed (Arshadi et al. 2021). To determine the degree of dendritic arborization, we used the Sholl analysis, measuring the number of intersections of the dendrites with circles of increasing radius (20 \u0026micro;m each in our study) centered in the soma (Ferreira et al. 2014; Sholl 1953).\u003c/p\u003e\n\u003ch3\u003eAnalysis of GluN1 and GluN2B Expression\u003c/h3\u003e\n\u003cp\u003eThe immunohistochemical protocol employed was similar to that described above for GFP immunohistochemistry. For every subunit of NMDAR (GluN1 and GluN2B), we used different subseries of sections. Sections were incubated with either rabbit anti-GluN1 (Alomone, 1:400) or rabbit anti-GluN2B (Alomone, 1:4000) together with chicken anti-GFP IgY (Abcam, 1:500) primary antibodies for 48 h at 4\u0026deg;C. After washing, sections were incubated for 2 h at room temperature with donkey anti-rabbit (Biotium, A555, 1:800) and donkey anti-chicken (Biotium, CF488A, 1:800) secondary antibodies. Sections were then rinsed with PB 0.1 M, mounted on slides, and coverslipped using Dako fluorescent mounting medium (Agilent, United States).\u003c/p\u003e\u003cp\u003eControls were performed omitting the anti-GluN1 or anti-GluN2B antibody, as well as incubating with these antibodies previously pre-absorbed overnight with an excess of its immunogenic peptide (GluN1 blocking peptide, Alomone, Jerusalem, Israel) or (GluN2B blocking peptide, Alomone, Jerusalem, Israel), respectively. No immunolabeling was observed in these controls.\u003c/p\u003e\u003cp\u003eWe used a Leica TCS SP5 confocal microscope with a 63x objective, 3.5x digital zoom, and a 0.5 \u0026micro;m Z-step size for the study of GluN1\u0026thinsp;+\u0026thinsp;and GluN2B\u0026thinsp;+\u0026thinsp;puncta on the somata and the periphery of GFP-expressing interneurons. Six isolated GFP\u0026thinsp;+\u0026thinsp;somata from the prelimbic area and six isolated GFP\u0026thinsp;+\u0026thinsp;somata from the infralimbic area per animal were selected randomly and pooled together for the analysis.\u003c/p\u003e\u003cp\u003eThe images were analyzed using Fiji software as follows: 3 consecutive planes were selected in the center of the cell soma, and a Z-projection was performed. The images were converted to 8-bit deep images and binarized using a threshold to delineate the cell soma. This outline was expanded 0.5 \u0026micro;m to obtain two regions, the cell somata (the original outline) and the periphery (between both outlines). Afterwards, the background was subtracted with a rolling value of 50, and a Gaussian Blur with a sigma value of 1 was applied. Then, a macro based on (Guirado et al. 2018) was applied to binarize the image to delineate the GluN1 or GluN2B immunoreactive puncta (larger than 0.04 \u0026micro;m\u003csup\u003e2\u003c/sup\u003e). We calculated the density of puncta, the percentage of the area covered by them, and the mean size of the puncta.\u003c/p\u003e\n\u003ch3\u003eStatistics\u003c/h3\u003e\n\u003cp\u003eThe statistical analysis was based on the indications of (Diester et al. 2019), first by analyzing the pooled data from both sexes and then the data from females and males separately. After checking the normality and homoscedasticity of the data, a two-way ANOVA test was used to analyze the dendritic arborization profile, and a one-way ANOVA or a Kruskal-Wallis test was used to analyze the density of GFP\u0026thinsp;+\u0026thinsp;cells and the density, area covered, and size of the GluN1 or GluN2B puncta. Significant one-way ANOVAs were followed by Tukey post hoc tests. For graphical representations, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM was used in all cases.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eSomatostatin\u0026thinsp;+\u0026thinsp;cell density is decreased in mPFC of male aged mice\u003c/h2\u003e\u003cp\u003eThe GFP-expressing neurons in the GIN mouse used in the present study preferentially label Martinotti cells in layers II/III and Va of the PFC (Oliva et al., 2020; Ma et al., 2006; Gilabert-Juan et al., 2013). We first analyzed the density of these cells in the mPFC at 3-, 9- and 16-month-old animals (Figs.\u0026nbsp;1a1-d1). No differences were found when pooling both sexes together (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.2, Fig.\u0026nbsp;1g1) or in females (p\u0026thinsp;=\u0026thinsp;0.26, Fig.\u0026nbsp;1g3). Nevertheless, a significant decrease in cell density was found between 3- and 16-month-old (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020, Fig.\u0026nbsp;1g2) and 9- and 16-month-old (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.032, Fig.\u0026nbsp;1g2) male mice.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eThe dendritic arborization of somatostatin + neurons is increased in female aged mice\u003c/h3\u003e\n\u003cp\u003eTo determine the effect of aging on dendritic arborization of Martinotti cells in the mPFC, a Sholl analysis was performed (Figs.\u0026nbsp;1a2-f2). When pooling females and males together, the analysis showed a more elaborate arborization profile in 16-month-old mice, compared to 3- and 9-month-old mice (**\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0011, Fig.\u0026nbsp;1h1). There were specific significant arborization increases at 100 \u0026micro;m from the soma between 9- and 16-month-old animals (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.029, Fig.\u0026nbsp;1h1); and at 180 \u0026micro;m between 3- and 16-month-old animals (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.048, Fig.\u0026nbsp;1h1) and 9- and 16-month-old animals (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.037, Fig.\u0026nbsp;1h1). When females were analyzed separately, 16-month-old mice showed an increased arborization compared to 3- and 9-month-old mice (**\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0023, Fig.\u0026nbsp;1h3). There were significant differences at 120 \u0026micro;m between 3- and 16-month-old females (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.046, Fig.\u0026nbsp;1H3); and at 160 \u0026micro;m between 3- and 16-month-old females (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.043, Fig.\u0026nbsp;1h3). However, there were no discernible differences in the arborization profile of males (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.25, Fig.\u0026nbsp;1h2), suggesting that the female group was responsible for the initial differences seen when the two sexes were examined together.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe density of GluN1 puncta in somatostatin\u0026thinsp;+\u0026thinsp;decreases in the mPFC of old mice, and the clustering increases\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe analyzed the size of GluN1 immunoreactive puncta, the density and the area covered by these structures in the somata (Figs.\u0026nbsp;2a-c) and periphery (Figs.\u0026nbsp;2c-f) of Martinotti cells. The analysis of the density of GluN1 immunoreactive puncta in the somata of Martinotti cells indicated a significant decrease between 3- and 16-month-old mice when females and males were pooled together (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018, Fig.\u0026nbsp;2g1). No significant differences were found when males (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.38, Fig.\u0026nbsp;2g2) and females (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.062, Fig.\u0026nbsp;2g3) were analyzed separately. The analysis of the area covered by GluN1\u0026thinsp;+\u0026thinsp;puncta showed no significant changes due to aging when both sexes were pooled together (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.44, Fig.\u0026nbsp;2h1), in males (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.36, Fig.\u0026nbsp;2h2) or in females (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.93, Fig.\u0026nbsp;2h3). We occasionally noticed the presence of bigger structures made of clustered GluN1\u0026thinsp;+\u0026thinsp;puncta in 16-month-old mice. The analysis of the mean size of GluN1\u0026thinsp;+\u0026thinsp;puncta indicated a significant increase between 3- and 16-month-olds when both sexes were pooled (**\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007, Fig.\u0026nbsp;2i1) and in females (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.025, Fig.\u0026nbsp;2i3), but not in males (p\u0026thinsp;=\u0026thinsp;0.12, Fig.\u0026nbsp;2i2).\u003c/p\u003e\u003cp\u003eIn the cell periphery, the analysis of the density of GluN1 immunoreactive puncta indicated a significant decrease when females and males were pooled together between 3- and 9-month-old mice (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.019, Fig.\u0026nbsp;2j1) but not separately in males (p\u0026thinsp;=\u0026thinsp;0.089, Fig.\u0026nbsp;2j2) nor in females (p\u0026thinsp;=\u0026thinsp;0.14, Fig.\u0026nbsp;2j3). The analysis of the area covered by GluN1 puncta indicated a significant decrease between 3- and 9-month-old mice when both sexes were pooled (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036, Fig.\u0026nbsp;2K1) but not separately in males (p\u0026thinsp;=\u0026thinsp;0.072, Fig.\u0026nbsp;2k2) nor in females (p\u0026thinsp;=\u0026thinsp;0.29, Fig.\u0026nbsp;2k3). However, the analysis of the mean size of GluN1 puncta showed no differences when females and males were analyzed together (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.18, Fig.\u0026nbsp;2l1), in males (p\u0026thinsp;=\u0026thinsp;0.31, Fig.\u0026nbsp;2l2) nor in females (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.34, Fig.\u0026nbsp;2l3).\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e+\u003c/h2\u003e\u003cp\u003e\u003cb\u003eFigure 2\u003c/b\u003e \u003cem\u003eAnalysis of the effect of aging on GluN1 receptor distribution in the somata and periphery of SST\u0026thinsp;+\u0026thinsp;interneurons.\u003c/em\u003e \u003cb\u003ea-f\u003c/b\u003e \u003cem\u003eGFP and GluN1 inmunostaining in 3-month-old (\u003c/em\u003e\u003cb\u003ea\u003c/b\u003e\u003cem\u003e), 9-month-old (\u003c/em\u003e\u003cb\u003eb\u003c/b\u003e\u003cem\u003e), 16-month-old (\u003c/em\u003e\u003cb\u003ec\u003c/b\u003e\u003cem\u003e) male mice and in 3-month-old (\u003c/em\u003e\u003cb\u003ed\u003c/b\u003e\u003cem\u003e), 9-month-old (\u003c/em\u003e\u003cb\u003ee\u003c/b\u003e\u003cem\u003e), 16-month-old (\u003c/em\u003e\u003cb\u003ef\u003c/b\u003e\u003cem\u003e) female mice. Scale bar: 10 \u0026micro;m.\u003c/em\u003e \u003cb\u003eg-l\u003c/b\u003e \u003cem\u003eDensity, percentage of area covered and mean size of GluN1 inmunoreactive puncta in the somata (\u003c/em\u003e\u003cb\u003eg, h, i\u003c/b\u003e\u003cem\u003e) and periphery (\u003c/em\u003e\u003cb\u003ej, k, l)\u003c/b\u003e \u003cem\u003eof SST\u0026thinsp;+\u0026thinsp;cells in male and female mice (\u003c/em\u003e\u003cb\u003e1\u003c/b\u003e\u003cem\u003e), male mice (\u003c/em\u003e\u003cb\u003e2\u003c/b\u003e\u003cem\u003e) and female mice (\u003c/em\u003e\u003cb\u003e3\u003c/b\u003e\u003cem\u003e). Data presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe density of GluN2B punta decreases with aging in the mPFC of male and female mice, and the clustering increases\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe analyzed the size of GluN2B immunoreactive puncta and the density and area covered by these structures both in the somata (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-c) and periphery (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003ed-f) of Martinotti cells. The analysis of the density of GluN2B immunoreactive puncta in the somata of Martinotti cells indicated a significant decrease between 3- and 16-month-old mice when both sexes were pooled together (****\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, Fig.\u0026nbsp;3g1), in males (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022, Fig.\u0026nbsp;3g2) and in females (**\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0096, Fig.\u0026nbsp;3g3). Additionally, a significant decrease was found between 9- and 16-month-old mice when both sexes were pooled together (****\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, Fig.\u0026nbsp;3g1) and in males (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.049, Fig.\u0026nbsp;3g2), but not in females (p\u0026thinsp;=\u0026thinsp;0.30. Figure\u0026nbsp;2g3). However, the analysis of the area covered by GluN2B puncta showed no differences in pooled females and males (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.87, Fig.\u0026nbsp;3h1) in males (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.83, Fig.\u0026nbsp;3h2) and in females (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.25, Fig.\u0026nbsp;3h3). Larger structures made of clustered GluN2B\u0026thinsp;+\u0026thinsp;puncta were commonly seen in 16-month-old mice, as well as in 9-month-old mice. The analysis of the mean size of GluN2B puncta indicated a significant increase between 3- and 16-month-old mice when both sexes were pooled together, (****\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 Fig.\u0026nbsp;3i1), in males (**\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0044, Fig.\u0026nbsp;3i2) and in females (**\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0018, Fig.\u0026nbsp;3i3). A significant difference was also found between 9- and 16-month-old mice when both sexes were pooled together (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.014, Fig.\u0026nbsp;3i1) and in females (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012, Fig.\u0026nbsp;3i3), but not in males (p\u0026thinsp;=\u0026thinsp;0.10, Fig.\u0026nbsp;3i2).\u003c/p\u003e\u003cp\u003eIn the cell periphery, the analysis of the density of GluN2B immunoreactive puncta indicated a significant increase between 3- and 16-month-old mice when both sexes were pooled together (**\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0034, Fig.\u0026nbsp;3j1) and in males (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.027, Fig.\u0026nbsp;3j2). Additionally, a significant increase was found between 9- and 16-month-old mice when both sexes were pooled together (**\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0034, Fig.\u0026nbsp;3j1), but not in males (p\u0026thinsp;=\u0026thinsp;0.071, Fig.\u0026nbsp;3j2). No significant differences were found in females (p\u0026thinsp;=\u0026thinsp;0.25, Fig.\u0026nbsp;3j3). The analysis of the area covered by GluN2B puncta showed no differences in pooled females and males (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.058, Fig.\u0026nbsp;3k1, or in females (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.87, Fig.\u0026nbsp;3K3), but it is decreased in old male mice (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.046, Fig.\u0026nbsp;3k2). The analysis of the mean size of the GluN2B puncta showed a significant decrease between 3- and 16-month-old mice when both sexes were pooled together (*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.048, Fig.\u0026nbsp;3l1), but no differences were found when males (p\u0026thinsp;=\u0026thinsp;0.081, Fig.\u0026nbsp;3l2) and females (p\u0026thinsp;=\u0026thinsp;0.044, Fig.\u0026nbsp;3l3) were analyzed separately.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study illustrates age-related modifications in the density and architecture of SST\u0026thinsp;+\u0026thinsp;interneurons of the mice mPFC. In males, the cell density significantly decreased from 3-month-old to older mice. According to a prior study, after adolescence, the density of SST\u0026thinsp;+\u0026thinsp;neurons in the female mice's mPFC rises (Du et al. 2018). This article also showed a decrease in SST\u0026thinsp;+\u0026thinsp;cells in the cingulate cortex of males, which appears similar to the present findings in the mPFC. We measured neuronal densities at 16 months, whereas they measured them at 12 months. It is also important to note that while we focused our analysis in SST\u0026thinsp;+\u0026thinsp;cells, most of which are Martinotti cells, in the entire mPFC, Du and colleagues examined all SST neurons in the infralimbic, prelimbic, and cingulate regions separately. These differences may be the cause of the disparities. It's also important to remember that testosterone, but not estrogen, increases the expression of the \u003cem\u003eSST\u003c/em\u003e RNA (Argente et al. 1990; Chowen et al. 1993), and decline of this hormone during male aging may have an effect on cell survival (Veiga et al. 2004). Furthermore, we have demonstrated previously that chronic stress reduces the density of SST\u0026thinsp;+\u0026thinsp;neurons in the mPFC of male mice (Gilabert-Juan et al. 2013); consequently, it is possible that aging has similar effects.\u003c/p\u003e\u003cp\u003eIn reference to the enhanced dendritic arborization observed in 16-month-old females, we have found in former studies that male mice exposed to chronic stress had altered dendritic arborization of SST\u0026thinsp;+\u0026thinsp;neurons in the mPFC, hippocampus, and amygdala (Gilabert-Juan et al. 2013; 2011; 2017). Additionally, we have described that as female mice age, the dendritic spine density in hippocampal SST\u0026thinsp;+\u0026thinsp;cells decreases (Gramuntell et al. 2021). Given that a drop in estrogen levels can lead to higher stress response and decreased excitatory neural activity (Foster and Kumar 2025; McEwen et al. 2016), the dendritic structural changes observed in the present study in aged females but not in males may also be due to hormonal changes. Previous work from our laboratories has described that the structure, connectivity and plasticity of hippocampal SST\u0026thinsp;+\u0026thinsp;interneurons is modulated by estrogen (Perez-Rando et al. 2022). Additionally, it has been noted that SST\u0026thinsp;+\u0026thinsp;neurons in the mPFC can be modulated by changes in the signaling of certain neurotransmitters, such as the endogenous opioid system (Wang et al. 2019), which declines during aging (Hamm and Knisely 1985). This suggests that these neurons are highly plastic and responsive to extracellular signals.\u003c/p\u003e\u003cp\u003eIt's interesting to note that glutamate receptors seem to mediate some of the effects of estrogens on rodent and monkey PFC structure and connectivity (Hao et al. 2006; Khan et al. 2013). Female mice with low estradiol levels show greater basal glutamatergic transmission in the mPFC than female mice with high estradiol levels. Estradiol also controlled synaptic plasticity, favoring synaptic potentiation in a way that was dependent on GluN2B. Furthermore, GluN2B-mediated NMDA receptor transmission was enhanced by estrogen receptor β activation, which restored synaptic potentiation (Galvin and Ninan 2014). Although we did not control for the females' estrous cycle in this study, which may have an impact on some metrics and be one of its drawbacks, it is plausible that some of the aging-related alterations that have been noted were brought on by the decline in estrogens (Nicholson et al. 2020).\u003c/p\u003e\u003cp\u003eThe PFC is highly involved in the encoding of working memory, a form of short-term memory that consists of the temporary arrangement, processing, and storage of information that collectively directs reasoning and goal-directed behavior (Arnsten et al. 2012; Goldman-Rakic 1995). Estradiol replacement therapy can help women, female nonhuman primates, and rodents with working memory problems associated with aging and menopause (Hampson 2018). In rats' mPFC, GluN2B RNA expression changes as they age (Gandy et al. 2023) and decreases in ovariectomized rats when compared to control rats (Morissette et al. 2008). This suggests that the NMDA subunit may play a part in the decline in working memory, despite some studies suggesting the opposite in excitatory neurons (McQuail et al. 2016). Additionally, it has been shown that GluN2B alterations in the PFC are linked to the restoration of working memory when estradiol is administered (Hara et al. 2018). In male rats, the protein levels of the GluN2B subunit in the mPFC showed a significant decline with aging in some studies (Zhao et al. 2009) or not significant changes in others (Liu et al. 2008). Measuring the amount of protein or RNA in various cellular fractions or compartments may yield different results because, as our study has demonstrated, aging-associated changes may be more connected to structural conformation and cellular distribution rather than to the control of protein or RNA expression. Although excitatory neurons were the primary target of these described alterations, given our findings on the changes of GluN2B subunit restructures in SST\u0026thinsp;+\u0026thinsp;neurons with age, it is plausible that these interneurons also contribute significantly to working memory function through NMDA receptors.\u003c/p\u003e\u003cp\u003eThe changes observed in the structure and number of GluN1 puncta are less significant than the ones for GluN2B. As discussed above, changes in GluN2B during aging have been broadly reported, but the GluN1 subunit of the NMDA receptors seem to have less modifications with age. Lower levels of GluN1 in fast-spiking interneurons of the mPFC of male mice during aging have been associated with less cognitive flexibility (McQuail et al. 2021). Furthermore, the impact of aging on the expression of GluN1 subunits with distinct splice cassettes varied significantly, displaying a different proportion of GluN1 proteins along the lifespan (Das and Magnusson 2011). These changes in the protein subtypes content may also be responsible for the receptor conformation changes observed in our study. However, another study found no evidence of a change in GluN1 subunit expression with aging (Zhao et al. 2009); this might be due to changes in splice variants and conformation.\u003c/p\u003e\u003cp\u003eOur study was limited by the age of the animals, with the oldest being 16 months\u0026mdash;an age at which cognitive decline in rodents begins, though these animals are not typically considered elderly (Foster and Kumar 2025). However, most transgenic animals in this strain did not survive much beyond this point and showed health issues like tumors and hair loss. There are no previous studies examining cognitive tasks in older animals of this strain, and regrettably, we were unable to conduct behavioral tests.\u003c/p\u003e\u003cp\u003eAll things considered, our findings contribute to a better understanding of how aging affects the number of SST\u0026thinsp;+\u0026thinsp;cells, their structural plasticity and the composition and expression of NMDAR in the mPFC of male and female mice. The study of these receptors is crucial because behavioral and cognitive dysfunctions may be caused by changes in their expression, conformation, and physiology and may result in neural balance dysregulation related to aging decline.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This work was supported by the projects PID2021-127595OB-I00 and PID2021-126258OA-I00 financed by the Spanish Ministry of Science and Innovation (AEI/10.13039/501100011033, \u0026ldquo;FEDER Una manera de hacer Europa\u0026rdquo;), SI3-PJI-2021-00417, Universidad Aut\u0026oacute;noma de Madrid - Comunidad Aut\u0026oacute;noma de Madrid (Programa de est\u0026iacute;mulo a la investigaci\u0026oacute;n de j\u0026oacute;venes doctores), the Valencian Regional Government (CIPROM/2023/28), the Fundaci\u0026oacute;n Mutua Madrile\u0026ntilde;a, the Fundaci\u0026oacute;n Alicia Koplowitz, and The Spanish Network of Stress Research (REIS) (to J.N. and J. G-J.); B. S-M. is a recipient of a predoctoral fellowship from the Spanish Ministry of Universities Predoctoral Fellowship Program (FPU).\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbbas AI, Sundiang MJM, Henoch B, et al (2018) Somatostatin interneurons facilitate hippocampal-prefrontal synchrony and prefrontal spatial encoding. Neuron 100(4):926\u0026ndash;939.e3. https://doi.org/10.1016/j.neuron.2018.09.029\u003c/li\u003e\n\u003cli\u003eArgente J, Chowen-Breed JA, Steiner RA, Clifton DK (1990) Somatostatin messenger RNA in hypothalamic neurons is increased by testosterone through activation of androgen receptors and not by aromatization to estradiol. Neuroendocrinology 52(4):342\u0026ndash;349. https://doi.org/10.1159/000125618\u003c/li\u003e\n\u003cli\u003eArnsten AFT, Wang MJ, Paspalas CD (2012) Neuromodulation of thought: flexibilities and vulnerabilities in prefrontal cortical network synapses. Neuron 76(1):223\u0026ndash;239. https://doi.org/10.1016/j.neuron.2012.08.038\u003c/li\u003e\n\u003cli\u003eArshadi C, G\u0026uuml;nther U, Eddison M, Harrington KIS, Ferreira TA (2021) SNT: a unifying toolbox for quantification of neuronal anatomy. Nat Methods 18(4):374\u0026ndash;377. https://doi.org/10.1038/s41592-021-01105-7\u003c/li\u003e\n\u003cli\u003ede Brabander JM, Kramers RJ, Uylings HB (1998) Layer-specific dendritic regression of pyramidal cells with ageing in the human prefrontal cortex. Eur J Neurosci 10(4):1261\u0026ndash;1269. https://doi.org/10.1046/j.1460-9568.1998.00137.x\u003c/li\u003e\n\u003cli\u003eChowen JA, Argente J, Gonz\u0026aacute;lez-Parra S, Garc\u0026iacute;a-Segura LM (1993) Differential effects of the neonatal and adult sex steroid environments on the organization and activation of hypothalamic growth hormone-releasing hormone and somatostatin neurons. Endocrinology 133(6):2792\u0026ndash;2802. https://doi.org/10.1210/endo.133.6.7902269\u003c/li\u003e\n\u003cli\u003eCummings KA, Clem RL (2020) Prefrontal somatostatin interneurons encode fear memory. Nat Neurosci 23(1):61\u0026ndash;74. https://doi.org/10.1038/s41593-019-0552-7\u003c/li\u003e\n\u003cli\u003eDas SR, Magnusson KR (2011) Changes in expression of splice cassettes of NMDA receptor GluN1 subunits within the frontal lobe and memory in mice during aging. Behav Brain Res 222(1):122\u0026ndash;133. https://doi.org/10.1016/j.bbr.2011.03.045\u003c/li\u003e\n\u003cli\u003eDiester CM, Banks ML, Neigh GN, Negus SS (2019) Experimental design and analysis for consideration of sex as a biological variable. Neuropsychopharmacology 44(13):2159\u0026ndash;2162. https://doi.org/10.1038/s41386-019-0458-9\u003c/li\u003e\n\u003cli\u003eDu X, Serena K, Hwang WJ, et al (2018) Prefrontal cortical parvalbumin and somatostatin expression and cell density increase during adolescence and are modified by BDNF and sex. Mol Cell Neurosci 88:177\u0026ndash;188. https://doi.org/10.1016/j.mcn.2018.02.001\u003c/li\u003e\n\u003cli\u003eDumitriu D, Hao J, Hara Y, et al (2010) Selective changes in thin spine density and morphology in monkey prefrontal cortex correlate with aging-related cognitive impairment. J Neurosci 30(22):7507\u0026ndash;7515. https://doi.org/10.1523/JNEUROSCI.6410-09.2010\u003c/li\u003e\n\u003cli\u003eFeltes BC (2025) Analyzing different aging theories in the context of the brain: DNA damage, inflammation, redox imbalance, and neurodevelopment intertwine. Biogerontology 26(3):105. https://doi.org/10.1007/s10522-025-10243-w\u003c/li\u003e\n\u003cli\u003eFerreira TA, Blackman AV, Oyrer J, et al (2014) Neuronal morphometry directly from bitmap images. Nat Methods 11(10):982\u0026ndash;984. https://doi.org/10.1038/nmeth.3125\u003c/li\u003e\n\u003cli\u003eFoster TC, Kumar A (2025) Sex, senescence, senolytics, and cognition. Front Aging Neurosci 17:1555872. https://doi.org/10.3389/fnagi.2025.1555872\u003c/li\u003e\n\u003cli\u003eGalvin C, Ninan I (2014) Regulation of the mouse medial prefrontal cortical synapses by endogenous estradiol. Neuropsychopharmacology 39(9):2086\u0026ndash;2094. https://doi.org/10.1038/npp.2014.56\u003c/li\u003e\n\u003cli\u003eGandy HM, Hollis F, Hernandez CM, McQuail JA (2023) Aging or chronic stress impairs working memory and modulates GABA and glutamate gene expression in prelimbic cortex. Front Aging Neurosci 15:1306496. https://doi.org/10.3389/fnagi.2023.1306496\u003c/li\u003e\n\u003cli\u003eGasiorowska A, Wydrych M, Drapich P, et al (2021) The biology and pathobiology of glutamatergic, cholinergic, and dopaminergic signaling in the aging brain. Front Aging Neurosci 13:654931. https://doi.org/10.3389/fnagi.2021.654931\u003c/li\u003e\n\u003cli\u003eGilabert-Juan J, Bueno-Fernandez C, Castillo-Gomez E, Nacher J (2017) Reduced interneuronal dendritic arborization in CA1 but not in CA3 region of mice subjected to chronic mild stress. Brain Behav 7(2):e00534. https://doi.org/10.1002/brb3.534\u003c/li\u003e\n\u003cli\u003eGilabert-Juan J, Castillo-Gomez E, Guirado R, Molt\u0026oacute; MD, Nacher J (2013) Chronic stress alters inhibitory networks in the medial prefrontal cortex of adult mice. Brain Struct Funct 218(6):1591\u0026ndash;1605. https://doi.org/10.1007/s00429-012-0479-1\u003c/li\u003e\n\u003cli\u003eGilabert-Juan J, Castillo-Gomez E, P\u0026eacute;rez-Rando M, Molt\u0026oacute; MD, Nacher J (2011) Chronic stress induces changes in the structure of interneurons and in the expression of molecules related to neuronal structural plasticity and inhibitory neurotransmission in the amygdala of adult mice. Exp Neurol 232(1):33\u0026ndash;40. https://doi.org/10.1016/j.expneurol.2011.07.009\u003c/li\u003e\n\u003cli\u003eGoldman-Rakic PS (1995) Cellular basis of working memory. Neuron 14(3):477\u0026ndash;485. https://doi.org/10.1016/0896-6273(95)90304-6\u003c/li\u003e\n\u003cli\u003eGramuntell Y, Klimczak P, Coviello S, Perez-Rando M, Nacher J (2021) Effects of aging on the structure and expression of NMDA receptors of somatostatin expressing neurons in the mouse hippocampus. Front Aging Neurosci 13:782737. https://doi.org/10.3389/fnagi.2021.782737\u003c/li\u003e\n\u003cli\u003eGrill JD, Riddle DR (2002) Age-related and laminar-specific dendritic changes in the medial frontal cortex of the rat. Brain Res 937(1\u0026ndash;2):8\u0026ndash;21. https://doi.org/10.1016/s0006-8993(02)02457-5\u003c/li\u003e\n\u003cli\u003eGuirado R, Carceller H, Castillo-G\u0026oacute;mez E, Castr\u0026eacute;n E, Nacher J (2018) Automated analysis of images for molecular quantification in immunohistochemistry. Heliyon 4(6):e00669. https://doi.org/10.1016/j.heliyon.2018.e00669\u003c/li\u003e\n\u003cli\u003eH\u0026auml;del S, Wirth C, Rapp M, Gallinat J, Schubert F (2013) Effects of age and sex on the concentrations of glutamate and glutamine in the human brain. J Magn Reson Imaging 38(6):1480\u0026ndash;1487. https://doi.org/10.1002/jmri.24123\u003c/li\u003e\n\u003cli\u003eHamm RJ, Knisely JS (1985) Environmentally induced analgesia: an age-related decline in an endogenous opioid system. J Gerontol 40(3):268\u0026ndash;274. https://doi.org/10.1093/geronj/40.3.268\u003c/li\u003e\n\u003cli\u003eHampson E (2018) Estrogens, aging, and working memory. Curr Psychiatry Rep 20(12):109. https://doi.org/10.1007/s11920-018-0972-1\u003c/li\u003e\n\u003cli\u003eHansen KB, Yi F, Perszyk RE, Menniti FS, Traynelis SF (2017) NMDA receptors in the central nervous system. In: Burnashev N, Szepetowski P (eds) NMDA receptors: methods and protocols. Springer. https://doi.org/10.1007/978-1-4939-7321-7_1\u003c/li\u003e\n\u003cli\u003eHao J, Rapp PR, Leffler AE, et al (2006) Estrogen alters spine number and morphology in prefrontal cortex of aged female rhesus monkeys. J Neurosci 26(9):2571\u0026ndash;2578. https://doi.org/10.1523/JNEUROSCI.3440-05.2006\u003c/li\u003e\n\u003cli\u003eHara Y, Crimins JL, Puri R, et al (2018) Estrogen alters the synaptic distribution of phospho-GluN2B in the dorsolateral prefrontal cortex while promoting working memory in aged rhesus monkeys. Neuroscience 394:303\u0026ndash;315. https://doi.org/10.1016/j.neuroscience.2018.09.021\u003c/li\u003e\n\u003cli\u003eHuang D, Liu D, Yin J, Qian T, Shrestha S, Ni H (2017) Glutamate-glutamine and GABA in brain of normal aged and patients with cognitive impairment. Eur Radiol 27(7):2698\u0026ndash;2705. https://doi.org/10.1007/s00330-016-4669-8\u003c/li\u003e\n\u003cli\u003eKaiser LG, Schuff N, Cashdollar N, Weiner MW (2005) Age-related glutamate and glutamine concentration changes in normal human brain: 1H MR spectroscopy study at 4 T. Neurobiol Aging 26(5):665\u0026ndash;672. https://doi.org/10.1016/j.neurobiolaging.2004.07.001\u003c/li\u003e\n\u003cli\u003eKhan MM, Dhandapani KM, Zhang QG, Brann DW (2013) Estrogen regulation of spine density and excitatory synapses in rat prefrontal and somatosensory cerebral cortex. Steroids 78(6):614\u0026ndash;623. https://doi.org/10.1016/j.steroids.2012.12.005\u003c/li\u003e\n\u003cli\u003eKim D, Jeong H, Lee J, et al (2016) Distinct roles of parvalbumin- and somatostatin-expressing interneurons in working memory. Neuron 92(4):902\u0026ndash;915. https://doi.org/10.1016/j.neuron.2016.09.023\u003c/li\u003e\n\u003cli\u003eKim Y, Yang GR, Pradhan K, et al (2017) Brain-wide maps reveal stereotyped cell type-based cortical architecture and subcortical sexual dimorphism. Cell 171(2):456\u0026ndash;469.e22. https://doi.org/10.1016/j.cell.2017.09.020\u003c/li\u003e\n\u003cli\u003eLiu P, Smith PF, Darlington CL (2008) Glutamate receptor subunits expression in memory-associated brain structures: regional variations and effects of aging. Synapse 62(11):834\u0026ndash;841. https://doi.org/10.1002/syn.20563\u003c/li\u003e\n\u003cli\u003eLu T, Pan Y, Kao S-Y, et al (2004) Gene regulation and DNA damage in the ageing human brain. Nature 429(6994):883\u0026ndash;891. https://doi.org/10.1038/nature02661\u003c/li\u003e\n\u003cli\u003eMarkham JA, Juraska JM (2002) Aging and sex influence the anatomy of the rat anterior cingulate cortex. Neurobiol Aging 23(4):579\u0026ndash;588. https://doi.org/10.1016/s0197-4580(02)00004-0\u003c/li\u003e\n\u003cli\u003eMcEwen BS, Nasca C, Gray JD (2016) Stress effects on neuronal structure: hippocampus, amygdala, and prefrontal cortex. Neuropsychopharmacology 41(1):3\u0026ndash;23. https://doi.org/10.1038/npp.2015.171\u003c/li\u003e\n\u003cli\u003eMcQuail JA, Beas BS, Kelly KB, et al (2016) NR2A-containing NMDARs in the prefrontal cortex are required for working memory and associated with age-related cognitive decline. J Neurosci 36(50):12537\u0026ndash;12548. https://doi.org/10.1523/JNEUROSCI.2332-16.2016\u003c/li\u003e\n\u003cli\u003eMcQuail JA, Beas BS, Kelly KB, Hernandez CM, Bizon JL, Frazier CJ (2021) Attenuated NMDAR signaling on fast-spiking interneurons in prefrontal cortex contributes to age-related decline of cognitive flexibility. Neuropharmacology 197:108720. https://doi.org/10.1016/j.neuropharm.2021.108720\u003c/li\u003e\n\u003cli\u003eMcQuail JA, Frazier CJ, Bizon JL (2015) Molecular aspects of age-related cognitive decline: the role of GABA signaling. Trends Mol Med 21(7):450\u0026ndash;460. https://doi.org/10.1016/j.molmed.2015.05.002\u003c/li\u003e\n\u003cli\u003eMitchell JJ, Anderson KJ (1998) Age-related changes in [3H]MK-801 binding in the Fischer 344 rat brain. Neurobiol Aging 19(3):259\u0026ndash;265. https://doi.org/10.1016/s0197-4580(98)00058-x\u003c/li\u003e\n\u003cli\u003eMorissette M, Le Saux M, Di Paolo T (2008) Effect of oestrogen receptor alpha and beta agonists on brain N-methyl-D-aspartate receptors. J Neuroendocrinol 20(8):1006\u0026ndash;1014. https://doi.org/10.1111/j.1365-2826.2008.01754.x\u003c/li\u003e\n\u003cli\u003eMorrison JH, Baxter MG (2012) The aging cortical synapse: hallmarks and implications for cognitive decline. Nat Rev Neurosci 13(4):240\u0026ndash;250. https://doi.org/10.1038/nrn3200\u003c/li\u003e\n\u003cli\u003eNicholson K, MacLusky NJ, Leranth C (2020) Synaptic effects of estrogen. Vitamins Horm 114:167\u0026ndash;210. https://doi.org/10.1016/bs.vh.2020.06.002\u003c/li\u003e\n\u003cli\u003ePage CE, Coutellier L (2018) Adolescent stress disrupts the maturation of anxiety-related behaviors and alters the developmental trajectory of the prefrontal cortex in a sex- and age-specific manner. Neuroscience 390:265\u0026ndash;277. https://doi.org/10.1016/j.neuroscience.2018.08.030\u003c/li\u003e\n\u003cli\u003ePerez-Rando M, Guirado R, Tellez-Merlo G, Carceller H, Nacher J (2022) Estradiol regulates polysialylated form of the neural cell adhesion molecule expression and connectivity of O-LM interneurons in the hippocampus of adult female mice. Neuroendocrinology 112(1):51\u0026ndash;67. https://doi.org/10.1159/000515052\u003c/li\u003e\n\u003cli\u003eRidderinkhof KR, Krugers HJ (2022) Horizons in human aging neuroscience: from normal neural aging to mental (fr)agility. Front Hum Neurosci 16:815759. https://doi.org/10.3389/fnhum.2022.815759\u003c/li\u003e\n\u003cli\u003eRiedemann T (2019) Diversity and function of somatostatin-expressing interneurons in the cerebral cortex. Int J Mol Sci 20(12):2952. https://doi.org/10.3390/ijms20122952\u003c/li\u003e\n\u003cli\u003eSaransaari P, Oja SS (1995) Age-related changes in the uptake and release of glutamate and aspartate in the mouse brain. Mech Ageing Dev 81(2\u0026ndash;3):61\u0026ndash;71. https://doi.org/10.1016/0047-6374(95)01583-l\u003c/li\u003e\n\u003cli\u003eSchubert F, Gallinat J, Seifert F, Rinneberg H (2004) Glutamate concentrations in human brain using single voxel proton magnetic resonance spectroscopy at 3 Tesla. NeuroImage 21(4):1762\u0026ndash;1771. https://doi.org/10.1016/j.neuroimage.2003.11.014\u003c/li\u003e\n\u003cli\u003eSholl DA (1953) Dendritic organization in the neurons of the visual and motor cortices of the cat. J Anat 87(Pt 4):387\u0026ndash;406\u003c/li\u003e\n\u003cli\u003eSikora E, Bielak-Zmijewska A, Dudkowska M, et al (2021) Cellular senescence in brain aging. Front Aging Neurosci 13:646924. https://doi.org/10.3389/fnagi.2021.646924\u003c/li\u003e\n\u003cli\u003eUrban-Ciecko J, Barth AL (2016) Somatostatin-expressing neurons in cortical networks. Nat Rev Neurosci 17(7):401\u0026ndash;409. https://doi.org/10.1038/nrn.2016.53\u003c/li\u003e\n\u003cli\u003eUylings HBM, de Brabander JM (2002) Neuronal changes in normal human aging and Alzheimer\u0026rsquo;s disease. Brain Cogn 49(3):268\u0026ndash;276. https://doi.org/10.1006/brcg.2001.1500\u003c/li\u003e\n\u003cli\u003eVeiga S, Melcangi RC, Doncarlos LL, Garcia-Segura LM, Azcoitia I (2004) Sex hormones and brain aging. Exp Gerontol 39(11\u0026ndash;12):1623\u0026ndash;1631. https://doi.org/10.1016/j.exger.2004.05.008\u003c/li\u003e\n\u003cli\u003eWaller R, Mandeya M, Viney E, Simpson JE, Wharton SB (2020) Histological characterization of interneurons in Alzheimer\u0026rsquo;s disease reveals a loss of somatostatin interneurons in the temporal cortex. Neuropathology 40(4):336\u0026ndash;346. https://doi.org/10.1111/neup.12649\u003c/li\u003e\n\u003cli\u003eWang AY, Lohmann KM, Yang CK, et al (2011) Bipolar disorder type 1 and schizophrenia are accompanied by decreased density of parvalbumin- and somatostatin-positive interneurons in the parahippocampal region. Acta Neuropathol 122(5):615\u0026ndash;626. https://doi.org/10.1007/s00401-011-0881-4\u003c/li\u003e\n\u003cli\u003eWang X, Liu P, Ma L, Wang F (2019) Opioid signal transduction regulates the dendritic morphology of somatostatin and parvalbumin interneurons in the medial prefrontal cortex. Neuroreport 30(8):592\u0026ndash;599. https://doi.org/10.1097/WNR.0000000000001254\u003c/li\u003e\n\u003cli\u003eWang Y, Ma Y, Hu J, et al (2015) Prenatal chronic mild stress induces depression-like behavior and sex-specific changes in regional glutamate receptor expression patterns in adult rats. Neuroscience 301:363\u0026ndash;374. https://doi.org/10.1016/j.neuroscience.2015.06.008\u003c/li\u003e\n\u003cli\u003eXu P, Chen A, Li Y, Xing X, Lu H (2019) Medial prefrontal cortex in neurological diseases. Physiol Genomics 51(9):432\u0026ndash;442. https://doi.org/10.1152/physiolgenomics.00006.2019\u003c/li\u003e\n\u003cli\u003eYavorska I, Wehr M (2016) Somatostatin-expressing inhibitory interneurons in cortical circuits. Front Neural Circuits 10:76. https://doi.org/10.3389/fncir.2016.00076\u003c/li\u003e\n\u003cli\u003eZhao X, Rosenke R, Kronemann D, et al (2009) The effects of aging on N-methyl-D-aspartate receptor subunits in the synaptic membrane and relationships to long-term spatial memory. Neuroscience 162(4):933\u0026ndash;945. https://doi.org/10.1016/j.neuroscience.2009.05.018\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"aging, NMDA receptors, GluN1, GluN2B, Somatostatin, mPFC","lastPublishedDoi":"10.21203/rs.3.rs-7657662/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7657662/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Aging is associated with progressive alterations in cortical circuits that compromise cognitive function. Somatostatin-positive (SST+) Martinotti interneurons, which regulate pyramidal cell activity in the medial prefrontal cortex (mPFC), are particularly relevant for inhibitory control, yet their age-related vulnerability remains poorly understood. Here, we examined SST+ Martinotti cells in mice at 3, 9, and 16 months of age, focusing on neuronal density, dendritic arborization, and expression of NMDA receptor subunits GluN1 and GluN2B. Our findings reveal a significant decline in SST+ cell density in aged male mice, whereas female mice displayed an increase in dendritic arborization with age. Analysis of NMDA receptor puncta showed a reduction in GluN1 density and puncta size in older animals, particularly in females. In contrast, GluN2B puncta density decreased in both sexes, while puncta size increased, suggesting greater clustering with aging. These results indicate that SST+ Martinotti cells undergo structural and molecular remodeling in a sex-dependent manner, which may disturb excitatory-inhibitory balance in the mPFC. Such alterations could underlie age-related deficits in prefrontal function and highlight SST+ interneurons as critical targets of cortical aging.","manuscriptTitle":"Age-Related Changes in Density, Arborization and Expression of NMDA Receptors of Somatostatin Martinotti Neurons in the Mouse mPFC","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-27 10:46:48","doi":"10.21203/rs.3.rs-7657662/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7ec26f79-615a-471d-b3ad-84888a14531a","owner":[],"postedDate":"October 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-06T18:08:24+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-27 10:46:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7657662","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7657662","identity":"rs-7657662","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}