Neural stem cells as potential mediators of prenatal dietary stress through epigenetic mechanisms

Itsuki Kageyama; Hiroya Yamada; Mirai Yamazaki; Takuya Wakasugi; Yuri Kamiya; Masaki Ohshiro; Manaka Ito; Yoshiki Tsuboi; Takashi Watanabe; Genki Mizuno; Yoshitaka Ando; Hiroaki Ishikawa; Koji Suzuki; Koji Ohashi; Eiji Munetsuna

doi:10.1016/j.stemcr.2026.102996

. 2026 Jul 2;21(7):102996. doi: 10.1016/j.stemcr.2026.102996

Neural stem cells as potential mediators of prenatal dietary stress through epigenetic mechanisms

Itsuki Kageyama ^1,², Hiroya Yamada ^1,^7,^∗, Mirai Yamazaki ¹, Takuya Wakasugi ¹, Yuri Kamiya ¹, Masaki Ohshiro ³, Manaka Ito ³, Yoshiki Tsuboi ², Takashi Watanabe ⁴, Genki Mizuno ⁵, Yoshitaka Ando ³, Hiroaki Ishikawa ³, Koji Suzuki ², Koji Ohashi ³, Eiji Munetsuna ^1,⁶

PMCID: PMC13385421 PMID: 42392085

Summary

The developmental origins of health and disease (DOHaD) hypothesis suggests that environmental exposures during development can induce long-term health effects, yet the cellular origin of such persistence remains unclear. Here, we suggest that neural stem cells (NSCs) may develop aberrant properties that persist with possible involvement of epigenetic mechanisms linking maternal dietary stress to neurocognitive impairments. In a rat model of maternal high-fructose corn syrup intake, offspring showed hippocampus-dependent memory deficits and reduced neurogenesis. NSCs from fetal and adolescent hippocampi exhibited persistent dysfunction with transcriptomic dysregulation. Mechanistically, transient downregulation of DNA methyltransferase 3A in fetal NSCs was associated with sustained repression of secreted phosphoprotein 1, encoding intracellular osteopontin (iOPN). iOPN overexpression partially restored NSC function, supporting a potential causal link. Our study proposes a DOHaD framework in which stem cells with lasting alterations may retain epigenetic traces of early life stress, with implications for organ systems and disease risk.

Keywords: DOHaD, fructose, osteopontin, DNA methylation, stem cell programming, epigenetics

Graphical abstract

Highlights

•
Maternal dietary stress impairs offspring memory and neurogenesis
•
Persistent epigenetic changes are induced in neural stem cells
•
Neural stem cell dysfunction persists beyond fetal stages
•
This study supports a stem cell-centered framework for developmental programming

Environmental exposures during development can have lasting health effects, but the cellular origin of this persistence remains unclear. Neural stem cells may retain epigenetic traces of early life stress, supporting a role in developmental programming.

Introduction

The developmental origins of health and disease (DOHaD) hypothesis posits that environmental conditions during early development can program long-term disease susceptibility (Barker, 1998; Van den Bergh, 2011; Siddeek and Simeoni, 2022). Among these, maternal dietary imbalance—such as excess fructose consumption—is increasingly recognized as a critical contributor to metabolic and neurological dysfunction in offspring (Ando et al., 2022; Munetsuna et al., 2021; Smith et al., 2022; Thompson and DeBosch, 2021; Yamada et al., 2019; Yamazaki et al., 2018). While epidemiological and experimental studies have shown that early life nutritional insults can have lasting effects on brain development and cognition (Freitas-Vilela et al., 2018; Galera et al., 2018; Gould et al., 2018; Roseboom et al., 2011; Yamazaki et al., 2018), the cellular origin and mechanistic underpinnings of such persistent outcomes remain poorly understood.

Recent advances in DOHaD research have implicated epigenetic modifications—including DNA methylation and chromatin remodeling—as key mechanisms linking prenatal environmental exposures to lifelong physiological change (Van den Bergh, 2011; Bianco-Miotto et al., 2017; Siddeek and Simeoni, 2022). However, most studies have focused on differentiated tissues or mature cell types, overlooking the possibility that undifferentiated, self-renewing stem cells might act as the source of long-term programming. We hypothesized that stem cells may retain molecular traces of developmental exposures, which could later influence tissue function and health.

Neural stem cells (NSCs), which are essential for brain development and plasticity (Chen et al., 2025; Jin, 2016; Zhao et al., 2008), offer a compelling model to examine this concept. NSCs retain epigenetic marks, possess lineage potential, and persist into adulthood to support neurogenesis (Li and Guo, 2021; Ma et al., 2010; Podobinska et al., 2017). Thus, even modest epigenetic reprogramming of NSCs by environmental stress might be propagated across developmental stages, potentially contributing to neurodevelopmental and cognitive disorders. Previous studies have shown that early life adversity and maternal dietary challenges can alter hippocampal neurogenesis and cognitive function in offspring (Bilbo and Tsang, 2010; Oomen et al., 2010; Yamazaki et al., 2018). In addition, hippocampal transcriptomic alterations as well as gene-specific epigenetic regulation of individual loci such as brain-derived neurotrophic factor have been reported following such exposures (Roth et al., 2009; Suri et al., 2013; Wei et al., 2012; Yamazaki et al., 2018). However, these studies have largely focused on tissue-level or differentiated neuronal outcomes. Yet the role of NSCs in mediating DOHaD-related outcomes has remained largely unexplored.

In this study, we explored the possibility that maternal high-fructose corn syrup (HFCS) intake produces long-lasting changes in hippocampal NSCs, with epigenetic factors potentially contributing to altered neurogenesis and behavior in offspring. We identified a transient downregulation of the de novo DNA methyltransferase (Dnmt3a) in fetal NSCs, which is associated with sustained hypomethylation and reduced expression of secreted phosphoprotein 1 (Spp1)—encoding intracellular osteopontin (iOPN), a key regulator of NSC function. These epigenetic changes resulted in functional impairments in NSC proliferation and neural differentiation that are already present at the fetal stage and persist into the postnatal period and adulthood. Behaviorally, these molecular and cellular alterations may contribute to hippocampus-dependent cognitive dysfunction in adult offspring. Together, our findings suggest that NSCs can serve as important mediators of environmental programming, providing a framework to understand the cellular basis of DOHaD.

Results

Maternal HFCS intake impairs hippocampus-dependent memory and adult neurogenesis in offspring

Dams were fed with normal water or 20% HFCS solution immediately after pregnancy (Figure 1A). Maternal HFCS intake had no effect on the body weight and caloric intake of either dams or offspring among the groups during the experimental period (Figures 1B–1G). In addition, a pair-feeding study that was conducted with 20% glucose solution also revealed no significant difference in the body weight or caloric intake (Figures S1A–S1G). To examine whether maternal HFCS exposure affects cognitive function in offspring, we subjected adult rats to the novel object recognition (NOR) test (Figures 1H–1J). Offspring from HFCS-fed dams showed significantly reduced recognition memory compared with control, as evidenced by decreased exploration preference during the testing phase (Figure 1J; p < 0.0001, Cohen’s d = 2.02, 95% confidence interval [CI], 1.15–2.87). To investigate the underlying neurobiological basis, we examined hippocampal neurogenesis by bromodeoxyuridine (BrdU) incorporation and immunohistochemical staining for NeuN. HFCS offspring exhibited a significant reduction in the number of BrdU⁺ NeuN⁺ cells in the dentate gyrus (DG) of the hippocampus (Figures 1K–1M), suggesting impaired adult neurogenesis (Figure 1M; p < 0.0001, Cohen’s d = 6.84, 95% CI, 3.92–9.72). No significant effects on cognitive behavior or neurogenesis were observed in the glucose group (Figures S1H–S1J).

Persistent NSC dysfunction induced by maternal HFCS exposure

We next evaluated NSC function by isolating hippocampal NSCs from fetal (embryonic day [E] 20.5) and adolescent (postnatal day [PD]30) offspring (Figure 2A). Neurosphere assays revealed that NSCs from HFCS offspring formed fewer and smaller neurospheres across developmental stages compared with controls (Figures 2B–2D). Quantification showed reduced neurosphere number and diameter at E20.5 (number: p < 0.01, Cohen’s d = 1.71, 95% CI, 0.48–2.89; diameter: p < 0.05, Cohen’s d = 1.02, 95% CI, −0.08–2.09) and PD30 (number: p < 0.0001, Cohen’s d = 3.15, 95% CI, 1.78–4.48; diameter: p < 0.01, Cohen’s d = 1.36, 95% CI, 0.36–2.33). Immunocytochemistry further demonstrated decreased rates of neuronal differentiation and shortened neurite length in NSCs from HFCS-exposed offspring (Figures 2C–2E), indicating persistent deficits in NSC proliferation and neural differentiation. The differentiation rate and total neurite length were decreased at E20.5 (differentiation: p < 0.0001, Cohen’s d = 2.25, 95% CI, 1.12–3.34; neurite length: p < 0.05, Cohen’s d = 1.14, 95% CI, 0.09–2.16) and PD30 (differentiation: p < 0.0001, Cohen’s d = 4.93, 95% CI, 3.18–6.64; neurite length: p < 0.0001, Cohen’s d = 3.20, 95% CI, 1.78–4.58). No such effects were observed in the glucose group (Figure S3).

Transcriptomic dysregulation in fetal NSCs following HFCS exposure at E20.5

Transcriptome profiling of hippocampal NSCs at E20.5 identified 198 differentially expressed genes (DEGs; false discovery rate <0.05), including 111 upregulated and 87 downregulated genes in HFCS-exposed offspring (Figure 3A). Among the up- or down-regulated genes, a list of genes with high expression variability is provided in the supporting information (Tables S1 and S2). Gene Ontology analysis revealed enrichment of DEGs related to cell division and neuronal development (Figure 3B). Gene set enrichment analysis further showed upregulation of pathways associated with negative regulation of cell division and downregulation of axonogenesis and neurogenesis-related gene sets (Figures 3C and 3D). Notably, pathways involved in DNA methylation and epigenetic gene regulation were also dysregulated.

Maternal HFCS intake suppresses Dnmt3a and downregulates Spp1 in NSCs

Among genes included in the enriched DNA methylation-related gene set identified by GSEA, Dnmt3a emerged as the most significantly downregulated gene (Figure 3D; Table S3). qPCR, western blotting, and enzymatic assays confirmed decreased Dnmt3a mRNA, protein, and DNMT activity in fetal NSCs from HFCS offspring (Figures 4A–4D). Full-length, uncropped western blot images are provided (Figure S7). We investigated the expression of 12 genes based on DEGs that were suggested to be associated with NSC function (Figure 4E; Figure S4). In particular, Spp1, a gene involved in NSC maintenance, was downregulated at E20.5 (Figures 4E and 4F). Methylation analysis of the Spp1 promoter showed reduced CpG methylation at key regulatory regions unlike other 11 genes (Figures 4G–4I; Figure S4). Hippocampal expression of Dnmt3a and Spp1 was not altered between the two groups (gene and protein expression: Figures 4J and 4K respectively). The DNA methylation level of Spp1 was also unchanged (Figure 4L). Dnmt3a knockdown in NSCs using small interfering RNA (siRNA) recapitulated the reduction in Spp1 expression and promoter hypomethylation (Figures 4M–4O), confirming that Dnmt3a directly regulates Spp1 epigenetically. These findings suggest that transient suppression of Dnmt3a during fetal development programs long-term Spp1 repression in NSCs. Supporting this finding, Yagi M et al. reported that Dnmt3a knockout reduced Spp1 expression in the heart and liver (Figure 4P) (Yagi et al., 2020). Collectively, reduced expression of Dnmt3a may lead to DNA hypomethylation of the Spp1 promoter, leading to decreased Spp1 expression.

Persistent repression of Spp1 in postnatal NSCs

At PD30, Dnmt3a expression and activity had normalized in HFCS offspring (Figures 5A–5D), yet Spp1 expression remained reduced unlike other 11 genes and the Spp1 promoter remained hypomethylated (Figures 5E–5G; Figure S5), indicating a sustained epigenetic imprint established during fetal life. At several other CpG sites as well, hypomethylation persisted from E20.5 to PD30 (Figure S6). Analysis of hippocampal tissue at PD30 showed no significant differences between the two groups (Figures 5H–5J). These data indicate that the transient decrease in DNMT activity at E20.5 leads to the hypomethylation of Spp1, which persists until PD30.

Functional relevance of Spp1 in NSCs

siRNA-mediated knockdown of Spp1 in NSCs reduced neurosphere size and number, impaired neural differentiation, and shortened neurite length (Figure 6), confirming that Spp1 is essential for NSC function.

iOPN restores NSC function impaired by maternal HFCS intake

To determine whether restoring Spp1 function could rescue HFCS-induced NSCs deficits, we overexpressed iOPN in NSCs using a signal peptide-deleted construct. Although secreted osteopontin (sOPN) treatment had no effect (Figures 7A–7D), iOPN overexpression rescued NSC proliferation and differentiation in HFCS offspring (Figures 7E–7H). Quantitative analyses confirmed the restoration of neurosphere formation and neuronal differentiation in HFCS-derived NSCs (Figures 7G and 7H; sphere number: p < 0.01, Cohen’s d = 3.28, 95% CI, 0.52–5.93; differentiation rate: p < 0.05, Cohen’s d = 2.54, 95% CI, 0.52–4.47). These results establish iOPN as the key effector downstream of Spp1 in maintaining NSC function after environmental stress. Together, these findings demonstrate that maternal HFCS intake epigenetically programs NSCs by transiently suppressing Dnmt3a, resulting in persistent repression of Spp1 and long-term deficits in neurogenesis and cognition.

Discussion

Our study suggests that NSCs may develop aberrant properties that persist as long-term traces of maternal dietary stress, with possible involvement of epigenetic mechanisms. Specifically, we observed that transient suppression of Dnmt3a in fetal hippocampal NSCs was associated with sustained repression of Spp1 via promoter hypomethylation, which may contribute to impaired NSC function and cognitive deficits that may extend into adulthood. These findings suggest that NSCs could encode and transmit the effects of prenatal environmental exposure, supporting a potential framework for stem cell-centered developmental programming within the DOHaD paradigm.

Previous DOHaD studies have primarily focused on tissue-level DNA methylation analysis to investigate how prenatal environmental factors shape long-term health risks (Ando et al., 2022; Burdge et al., 2007; Lillycrop et al., 2008; Munetsuna et al., 2021; Smith et al., 2022; Somm et al., 2009; Thompson and DeBosch, 2021; Yamada et al., 2019; Yamazaki et al., 2018; Yuan et al., 2018). However, this approach has fundamental limitations. Many tissues undergo continuous turnover, where differentiated cells are gradually replaced by new ones over time (Banjac et al., 2023; Cho et al., 2019; O’Brien, 2022). Therefore, it seems unlikely that DNA methylation abnormalities acquired at fetal stage are consistently maintained throughout life. Moreover, because tissue-level methylation analysis primarily reflects the epigenetic state of differentiated cells, it is difficult to determine how fetal epigenetic changes persist over time and contribute to long-term effects. However, our study supports the possibility that the epigenetic memory of DOHaD may be retained in stem cells. Specifically, we observed that maternal HFCS exposure induces persistent DNA methylation abnormalities in hippocampal NSCs, which may contribute to long-term neurodevelopmental impairments. It is considered that, because NSCs possess self-renewing capacity unlike differentiated cells, NSCs may have the ability to maintain and transmit epigenetic alterations through life.

NSCs can be broadly classified into two distinct populations: those that are actively involved in tissue formation during development and those that persist throughout life to maintain tissue homeostasis (Llorente et al., 2022; de Morree and Rando, 2023; Obernier and Alvarez-Buylla, 2019; Urbán and Guillemot, 2014). Our findings suggest that both populations may be affected by maternal HFCS exposure. Disruptions in the developmental NSC pool could lead to abnormalities in early neurogenesis and brain structure formation, while impairments in the lifelong NSC pool may compromise adult neurogenesis, contributing to long-term cognitive decline. Given that NSCs play a critical role in both neurodevelopment and neural maintenance, our results suggest that prenatal HFCS exposure may have lasting consequences on brain function by dysregulating both developmental and lifelong NSC populations.

The reduction in adult DG neurogenesis observed in this study is consistent with the involvement of NSCs. Although this readout reflects the combined outcome of multiple sequential processes and may also be influenced by niche-derived signals, our findings demonstrating impaired NSC proliferation and neuronal differentiation support a primary contribution of intrinsic NSC dysfunction. Notably, a previous maternal HFCS exposure study reported no persistent increase in hippocampal pro-inflammatory cytokine expression at PD21 or PD60 (Yamazaki et al., 2023), and increased apoptosis was not detected in a related fructose exposure model (Yamazaki et al., 2018). These findings suggest that the reduced neurogenesis observed here is unlikely to be solely explained by chronic neuroinflammation or enhanced cell death. Taken together, our data support a model in which intrinsic alterations in NSCs are a major contributor to the observed phenotype.

A key molecular insight from this study is evidence for a potential Dnmt3a-Spp1 regulatory axis as a mediator of this epigenetic memory. Dnmt3A is a de novo DNA methyltransferase that plays a pivotal role in the establishment of epigenomic patterns during development (Chen and Zhang, 2020; Okano et al., 1999). Although Dnmt3a expression was significantly reduced at E20.5, it had returned to baseline levels by PD30. Nevertheless, the hypomethylation and reduced expression of Spp1 persisted at PD30, suggesting that a temporary disruption of epigenetic regulation during development can result in sustained functional abnormalities—a phenomenon suggestive of epigenetic memory. Importantly, we identified the intracellular isoform of osteopontin (iOPN), encoded by Spp1, as essential for NSC maintenance. Functional impairment induced by maternal HFCS exposure or Spp1 knockdown was rescued by iOPN overexpression, but not by extracellular sOPN, underscoring the specificity of intracellular mechanisms. These results support the possibility that transient epigenetic disruptions during development may lead to long-lasting functional consequences in stem cell populations, not only by affecting canonical stem cell regulators but also by altering non-traditional but functionally critical genes. This expands the conceptual framework of DOHaD by positioning stem cells—and their epigenetic memory—as key mediators of long-term effects of early life environmental exposures. These insights may extend beyond the nervous system. Other long-lived stem cell populations, such as hematopoietic or mesenchymal stem cells, might similarly retain epigenetic memory of prenatal exposures. This broader framework may help explain how environmental stressors during gestation exert multisystemic and lifelong effects, from metabolic disease to immune dysfunction. Targeting such epigenetic memory in stem cells could become a novel strategy for mitigating DOHaD-related health outcomes.

Although promoter CpG methylation is often associated with transcriptional repression, this relationship is context dependent (de Mendoza et al., 2022). In the present study, reduced Dnmt3a expression was associated with hypomethylation of the Spp1 promoter accompanied by decreased Spp1 expression. This counterintuitive observation suggests that Dnmt3a may not regulate Spp1 transcription through a simple linear promoter methylation-dependent mechanism. One possible explanation is that loss of methylation facilitates the binding of methylation-sensitive repressors, thereby attenuating transcription. Alternatively, Dnmt3a downregulation may influence broader chromatin regulatory mechanisms. These findings support a context-dependent and potentially indirect epigenetic regulatory mechanism underlying the Dnmt3a-Spp1 relationship.

From an evolutionary perspective, retaining environmental information specifically in long-lived, self-renewing stem cells may offer a strategic advantage by allowing the organism to anticipate postnatal environments and stably adjust developmental and physiological trajectories over time. Within the framework of the DOHaD hypothesis, it may not be merely transient cellular responses, but epigenetic memory embedded in stem cells that may serve as a foundational mechanism to imprint prenatal environmental conditions into the long-term functional settings of metabolic, endocrine, and immune systems, thereby enhancing survival and reproductive success.

However, when postnatal environments deviate from prenatal expectations, such stem cell-encoded memories may become maladaptive, increasing susceptibility to disease and highlighting the evolutionary trade-off between adaptation and plasticity.

Thus, the retention of environmental information in stem cells—cells that not only persist throughout life but also continually regenerate tissues—may represent a fundamental mechanism through which early life experiences exert lasting effects on health and disease risk.

This study has several limitations. While we identified a transient reduction in DNMT activity in NSCs and focused on Spp1 as a key epigenetically regulated gene, it is possible that other functionally important genes are also epigenetically altered. Further comprehensive epigenomic analyses, such as whole-genome bisulfite sequencing or chromatin immunoprecipitation sequencing, are warranted to explore additional targets. In addition, future cell type-specific and niche-focused analyses in vivo will be required to more precisely delineate intrinsic and extrinsic mechanisms underlying the observed phenotype. Moreover, as this study was conducted using an animal model, future epidemiological research will be essential to evaluate the translational relevance of these findings to human health.

In conclusion, our results suggest that maternal HFCS consumption during pregnancy may induce lasting alterations in NSCs, potentially involving epigenetic mechanisms and contributing to long-term impairments in neurogenesis and cognition. These findings suggest that stem cells could act as mediators within the DOHaD framework and raise the possibility that interventions aimed at epigenetic regulation in stem cells may help mitigate the long-term consequences of early life environmental stressors.

Resource availability

Lead contact

Requests for further information, resources, and reagents should be directed to and will be fulfilled by the lead contact, Hiroya Yamada (hyamada@fujita-hu.ac.jp).

Materials availability

This study did not generate new unique reagents.

Data and code availability

All data reported in this paper will be shared by the lead contact upon request. This study did not generate any unique code. The RNA-seq data analyzed in this paper were obtained from GEO under accession number GSE111172 (Yagi et al., 2020). The microarray data generated in this study have been deposited in GEO under accession number GSE332845. Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Acknowledgments

This study was supported by Grants-in-Aid for Scientific Research (B) (grant numbers 20H04134 and 24K02692), Scientific Research (C) (grant numbers 22K10494), and Young Scientists (grant number 23K13917) from the Japan Society for the Promotion of Science (JSPS), funded by the Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan.

Author contributions

Conceptualization, H.Y. and E.M.; methodology, M.Y., Y.T., G.M., Y.A., H.I., K.S., and K.O.; investigation, I.K., T. Wakasugi, Y.K., M.O., and M.I.; writing – original draft, I.K., H.Y., and E.M.; writing – review and editing, H.Y. and E.M.; funding acquisition, Y.A., H.Y., and E.M.; resources, T. Watanabe; supervision, H.Y. and E.M.

Declaration of interests

The authors declare no competing interests.

STAR★Methods

Key resources table

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies

Rabbit anti-NeuN	Abcam	Cat # ab128886; RRID: AB_2744676
Rabbit anti-βIII Tubulin (TUJ1)	Abcam	Cat # ab18207; RRID: AB_444319
Rabbit anti-SOX2	Abcam	Cat # ab97959; RRID: AB_2341193
Rabbit anti-GFAP	Abcam	Cat # ab7260; RRID: AB_305808
Rabbit anti-CD11b	Abcam	Cat # ab75476; RRID: AB_1310048
Mouse anti-NESTIN	Abcam	Cat # ab6142; RRID: AB_305313
HRP-Mouse anti-β-actin	Abcam	Cat # ab49900; RRID: AB_867494
HRP-Goat anti-mouse	Abcam	Cat # ab97023; RRID: AB_10679675
HRP-Goat anti-rabbit	Cell Signaling Technology	Cat # 7074; RRID: AB_2099233
Rabbit anti-DNMT3A	Cell Signaling Technology	Cat # 3598; RRID: AB_2277449
Alexa Fluor 488-goat anti-mouse	Thermo Fisher Scientific	Cat # A-11017; RRID: AB_2534084
Alexa Fluor 594-goat anti-rabbit	Thermo Fisher Scientific	Cat # A-11072; RRID: AB_2534116
Mouse anti-BrdU	Millipore	Cat # MAB4072; RRID: AB_95024
Mouse anti-OPN	Santa Cruz Biotechnology	Cat # sc-21742; RRID: AB_2194997

Chemicals, peptides, and recombinant proteins

5-Bromo-2′-deoxyuridine (BrdU)	Sigma-Aldrich	Cat #B5002
Recombinant Rat Osteopontin	R&D Systems	Cat # 6359-OP

Deposited data

Microarray data	This paper	GSE332845
RNA-seq data	(Yagi et al., 2020)	GSE111172

Experimental models: Organisms/strains

Sprague-Dawley rat	Japan SLC, Inc.	N/A
The primary rat hippocampal neural stem cells (NSCs)	This paper	N/A

Oligonucleotides

See Tables S4 and S5 for primer sequences	N/A	N/A

Software and algorithms

ImageJ	National Institutes of Health	https://imagej.nih.gov/ij
Fiji	National Institutes of Health	https://fiji.sc/
Metascape	(Zhou et al., 2019)	https://www.metascape.org
Gene Set Enrichment Analysis	(Subramanian et al., 2005)	https://www.gsea-msigdb.org/gsea/index.jsp
PyroMark Assay Design 2.0	Qiagen	N/A
PyroMark Q24 Advanced	Qiagen	N/A
JMP	SAS	https://www.jmp.com/en_us/home.html
R	R Consortium	http://www.R-project.org
RStudio	RStudio	https://posit.co

Open in a new tab

Experimental model and study participant details

Animals

The study protocol was approved by the Fujita Health University Animal Ethics Committee. We established an animal model of maternal high fructose consumption as previously described (Ando et al., 2022, 2024). All animals were housed in an environmentally controlled cage at room temperature (23 ± 3°C) under a 12:12 h light-dark cycle. 8-week-old male and female Sprague-Dawley rats (Japan SLC, Hamamatsu, Japan) were acclimatized for 1 week, after which one male rat was housed with one female rat. Gestation was confirmed based on the presence of a vaginal plug, after which female rats were allocated to 2 experimental groups: one group receiving distilled water, one group receiving 20% HFCS solution. All animals had ad libitum access to their respective water and standard chow (MF; Oriental Yeast, Tokyo, Japan). 20% HFCS solution was prepared using 75% HFCS (Japan Corn Starch, Tokyo, Japan) and distilled water. HFCS solution was administered throughout gestation from vaginal plug identification until gestational day 20.5, after which it was replaced with distilled water for the remainder of gestation. In addition, paired feeding experiments using a 20% glucose solution were conducted. This group was used exclusively for supplemental experiments (Figures S1–S3). The glucose solution was prepared using D-(+)-glucose dissolved in distilled water at a final concentration of 20%. Rats in the glucose group were provided ad libitum access to the glucose solution and standard chow under the same housing conditions as described above.

Method details

Behavior, novel-object recognition assay

Novel object recognition (NOR) tests were performed as previously described (Yamazaki et al., 2018). Rats were subjected to a training session followed by a testing session 24 h later, in which one familiar object was replaced with a novel object. Exploration time for each object was recorded, and recognition memory was expressed as the percentage of time spent exploring the novel object relative to the total exploration time.

Immunohistochemistry and quantification of BrdU-labeled cells

To label proliferating cells, rats received intraperitoneal injections of BrdU (100 mg/kg; Sigma-Aldrich, St. Louis, MO, USA) twice daily at 8-h intervals for 5 consecutive days (postnatal days 21–25). Animals were euthanized 3 weeks after the final injection. Brains were collected, fixed in 4% paraformaldehyde, cryoprotected in sucrose, and sectioned coronally at 40 μm. Every eighth section (320 μm apart) throughout the dentate gyrus was processed for BrdU and NeuN double immunofluorescence staining to identify newly generated neurons, as previously described (Tozuka et al., 2005). BrdU⁺ NeuN⁺ cells were quantified in the subgranular zone and granule cell layer of the dentate gyrus, and counts were pooled across both upper and lower blades. Six sections per animal were analyzed at ×20 magnification using a BZ-X800 microscope (Keyence). BrdU⁺ NeuN⁺ cells were considered newly generated neurons that survived and matured after BrdU labeling.

Isolation and culture of primary hippocampal NSCs

Hippocampi were removed from male rat offspring (E20.5 and PD30) and dissociated using Neural Tissue Dissociation Kit P (Miltenyi Biotec, Bergisch Gladbach, Germany) according to the manufacturer’s instructions. In PD30 hippocampi, density gradient centrifugation using Percoll (Sigma-Aldrich) was performed to remove non-cellular components. After the last centrifuge, the pellet was suspended in KBM neural stem cell medium (Kohjin Bio, Saitama, Japan) supplemented with EGF and bFGF (Kohjin Bio) and seeded into culture plates. NSCs were grown as neurospheres in ultra-low attachment plates (Corning, NY, USA) or plated on poly-L-ornithine/laminin-coated plastic plates. The medium was changed every 2-3 days, and cells were cultured for 7 days. NSC-enriched populations were obtained by culturing for 7 days in undifferentiated maintenance medium (Figure S2). This culture condition was applied prior to all experiments evaluating NSCs.

Proliferation and neural differentiation analysis

Proliferation of NSCs was assessed by neurosphere assay. NSCs were seeded in 96-well plates at a density of 2.0 × 10³ cells/well and cultured under floating conditions in neural stem cell maintenance medium supplemented with EGF and bFGF for 7 days. Neurosphere formation was evaluated by measuring sphere diameter, and spheres larger than 30 μm were included in the analysis. For morphometric and differentiation assays, NSCs were seeded on poly-L-ornithine/laminin-coated 96-well plates at a density of 4.0 × 10⁴ cells/well. After preculture, cells were switched to neural induction medium and differentiated for 9 days, with medium replacement every 3 days. Differentiated neurons were identified by immunostaining for βIII-tubulin (TUJ1), and the percentage of TUJ1⁺ cells was calculated based on nuclear staining. Morphological evaluation of neurons was performed using the ImageJ plugin NeuronJ (version 1.4.3; NIH) with reference to other reports (Griffin et al., 2020; Ho et al., 2011). Images acquired with a ×20 objective lens were used to semi-automatically trace neurites and calculate the total neurite length per cell. The mean total neurite length per cell was calculated for each sample and used for comparison between groups.

Immunostaining for characterization of NSCs

For characterization of primary NSCs, the medium was removed completely, and primary neurospheres were fixed with 4% paraformaldehyde at room temperature for 30 min. After that, neurospheres were blocked with a blocking solution consisting of 0.2% bovine serum albumin (Santa Cruz Biotechnology, Dallas, TX), 0.1% Triton X100 (Wako Pure Chemicals, Osaka, Japan), and 0.1% NaN3 (Katayama Chemical, Osaka, Japan) at room temperature for 1 h and incubated with primary antibodies overnight at 4°C. Neurospheres were washed with PBS and incubated with secondary antibodies at room temperature for 2 h. The following antibodies were used: primary antibodies, Nestin (Abcam, Cambridge, UK, ab6142), SRY-box transcription factor 2 (SOX2) (Abcam, ab97959), glial fibrillary acidic protein (GFAP) (Abcam, ab7260), βIII tubulin (TUJ1) (Abcam, ab18207), Cluster of differentiation molecule 11b (CD11b) (Abcam, ab75476), secondary antibodies, Alexa Fluor 488 (Thermo Fisher Scientific) or Alexa Fluor 594 (Thermo Fisher Scientific). The nuclei were stained with Hoechst (Thermo Fisher Scientific) at room temperature for 15 min. Imaging was performed using a BZ-X800 microscope (Keyence).

Transcriptome analysis

Microarray analysis was performed as previously described (Ando et al., 2024; Yamazaki et al., 2024). Total RNA from E20.5 NSCs was analyzed using Clariom S Rat Arrays (Thermo Fisher Scientific). Differentially expressed genes (DEGs) were defined as those with FDR-corrected p < 0.05, absolute fold-change >2, and signal intensity >4. Gene Ontology (GO) analysis was performed using Metascape (Zhou et al., 2019). Gene set enrichment analysis (GSEA) was performed using GSEA v4.3.2 (Subramanian et al., 2005).

qPCR

Total RNA was isolated from the hippocampal tissues and NSCs using TRIzol reagent (Thermo Fisher Scientific). For mRNA expression analysis, total RNA was reverse transcribed into cDNA using M-MLV Reverse Transcriptase (Nippon Gene, Tokyo, Japan) with random hexamers as primers (TaKaRa, Otsu, Japan). qPCR was performed using the THUNDERBIRD Next SYBR qPCR Mix (Toyobo, Osaka, Japan) in the QuantStudio 7 Flex system (Thermo Fisher Scientific, MA, USA). The PCR primers used in this study were listed in Supporting Information (Table S4). The levels of target genes were normalized by using β-actin (Actb) as an internal control and relative gene expression was calculated using the 2^−ΔΔCt method.

Western blotting

Hippocampal tissues and NSCs were homogenized in RIPA buffer (Wako Pure Chemicals) with Protease Inhibitor Cocktails (Thermo Fisher Scientific), and the protein concentrations were measured using the Pierce BCA Protein Assay Kit (Thermo Fisher Scientific). Proteins were separated by SDS-PAGE and transferred onto PVDF membranes. The membranes were blocked with PVDF Blocking Reagent (Toyobo) at room temperature for 60 min. After blocking, primary antibodies were incubated overnight at 4°C, followed by incubation with the appropriate secondary antibodies at room temperature for 2 h. The following primary antibodies were used: β-actin (Abcam, ab49900), DNMT3A (Cell Signaling Technology, MA, USA, 3598), OPN (Santa Cruz, sc-21742). Chemiluminescent signals were detected using an Amersham ImageQuant 800 system (GE Healthcare, Chicago, IL, USA), and band intensities were quantified using a FUSION Chemiluminescence Imaging System (M&S Instruments, Osaka, Japan).

DNMT activity analysis

Nuclear proteins were extracted using EpiQuik Nuclea Cell Extraction Kit (Epigentek, NY, USA). Hippocampal NSCs were pooled from three offspring derived from the same dam, and thus the biological replicate n corresponds to the number of dams. DNMT activity was quantified using 5 μg of freshly prepared nuclear proteins from NSCs with the fluorometric EpiQuik DNMT Activity Assay Ultra Kit (Epigentek) according to the manufacturer’s instructions. In this assay, strip wells were coated with cytosine-rich DNA substrates. During the 2 h reaction, the DNMT enzyme from the nuclear extract samples transfers a methyl group from the methyl donor molecule AdoMet to cytosine, to methylate the DNA substrate. The methylated DNA were then recognized by anti 5-methylcytosine antibodies. The methylated DNA content proportional to enzyme activity was quantified fluorescently using 530 nm excitation and 590 nm emission readings from a microplate reader (Arvo; PerkinElmer, MA, USA).

Luciferase assay

Plasmid constructs were generated according to our previous reports (Munetsuna et al., 2021), the Spp1 promoter prediction region (Spp1 gene exon I upstream 1000bp or 1500bp) was inserted into the pGL4.10 [luc2] vector (Promega, WI, USA). We generated the PCR fragment of the Spp1 gene exon I upstream 1000bp or 1500bp region by using the following primers: forward (1000bp): 5′-GCTCGCTAGCCTCGATGCTGTTCACTGTACCAAC-3′, reverse forward (1500bp): 5′-GCTCGCTAGCCTCGATATTTAAAACAGAATTTTGTAGG-3′, reverse (1000bp and 1500bp): 5′-CCGGATTGCCAAGCTCGGACCTCCCAGAATTTAA-3′. Rat E20.5 hippocampal NSCs were cultured to determine Spp1 promoter region. After cells had grown to 70–90% confluency, NSCs were transfected with pGL4.10 [luc2] vector inserted Spp1 upstream region and the pGL4.74 [hRluc/TK] vector for internal transfection control using NEON electroporation system (1600 V, 10 ms, 3 pulses) (Thermo Fisher Scientific). After transfection, NSCs were seeded into 96-well plates and incubated for 48 h. Luciferase activity was measured using a luminometer (Arvo; PerkinElmer) and the Dual-Luciferase Reporter Assay System (Promega) in accordance with the manufacturer’s instructions.

Analysis of CpG methylation

CpG methylation was analyzed by bisulfite pyrosequencing as previously described (Ando et al., 2024; Kageyama et al., 2022; Yamazaki et al., 2018). Genomic DNA was extracted from hippocampal NSCs using NucleoSpin Tissue (TaKaRa, Otsu, Japan) and bisulfite-converted using the EpiTect Fast DNA Bisulfite Kit (Qiagen, Hilden, Germany). Bisulfite-modified DNA was amplified by PCR using methylation-specific primers designed with PyroMark Assay Design SW 2.0 (Qiagen) (Table S5). Quantitative methylation analysis was performed using a PyroMark Q24 Advanced system (Qiagen).

Small interfering RNAs (siRNA) experiments and transfection

siRNAs targeting Dnmt3a and Spp1 were synthesized by Thermo Fisher Scientific. The following sequences were used: siDnmt3a, 5′-ACAAGGAAGUUUACACCGATT-3′ (sense), 5′-UCGGUGUAAACUUCCUUGUAA-3′ (antisense), siSpp1, 5′-GUAAGGAAGAUGAUAGGUATT-3′ (sense), 5′-UACCUAUCAUCUUCCUUACTC-3′ (antisense). Rat E20.5 hippocampal NSCs were incubated with siRNA or scramble RNA (Scr) at 37°C for 24 h. Cells were transfected with 30 nM of siRNAs using the Lipofectamine RNAiMAX reagent (Thermo Fisher Scientific).

sOPN treatment and iOPN transfection

To assess the effects of sOPN on NSC function, we used OPN recombinant protein (R&D Systems, MN, USA, 6359-OP-050). After seeding NSCs and preculture, neurosphere assay and neural differentiation induction were performed. All experiments were performed in OPN treated medium (0.02, 0.20, 1.00 μg/ml). Plasmid was generated to overexpress iOPN for assessment of its effects on NSC function. As previously described (Leavenworth et al., 2015; Shinohara et al., 2008), OPN sequences removed the signal peptide sites were cloned into pLL3.7 vector. We generated the PCR fragment of the iOPN by using the following primers: forward: 5′-AATTTAAATCGGATCATGCTCCCGGTGAAAGTG-3′, reverse: 5′-TCGCGGCCGCGGATCTTAATTGACCTCAGAAGATG-3′. The vector was introduced into the NSCs using NEON electroporation system (1600 V, 10 ms, 3 pulses) (Thermo Fisher Scientific), followed by drug selection with puromycin for 5 days. After selection, for assessment of NSC function, cells were seeded as required for each experiment. Plasmid-transfected cells expressed GFP; therefore, GFP⁺ neurospheres were used to assess proliferation, and TUJ1⁺ GFP⁺ cells were used to evaluate neural differentiation and morphology.

Statistical analysis

All data are expressed as means ± SD. Statistical analyses were performed using JMP v.14 (SAS Institute, NC, USA) or R version 4.5.2 (R Foundation for Statistical Computing, Vienna, Austria). Body weight and caloric intake were analyzed using one-way ANOVA followed by Bonferroni post hoc test, whereas other comparisons were performed using Student’s t test. Statistical significance was set at p < 0.05. Effect sizes for pairwise comparisons were calculated using Cohen’s d, and 95% confidence intervals were estimated. For multiple comparisons, p values were adjusted using the Holm–Bonferroni method. The experimental unit for all in vivo and ex vivo experiments was the individual animal. The number of dams (litters) and offspring is indicated in the figure legends; typically, 1–3 offspring per dam were included per group. For BrdU quantification, multiple sections per brain were analyzed and summed to generate a single value per animal. For NSC functional assays, multiple wells derived from the same animal were averaged to yield one value per animal. Offspring were derived from multiple independent litters; however, litter was not included as a factor in the statistical models. For in vitro experiments, the number of independent experiments is indicated in the figure legends.

Published: July 2, 2026

Footnotes

Supplemental information can be found online at https://doi.org/10.1016/j.stemcr.2026.102996.

Supplemental information

Document S1. Figures S1–S7 and Tables S1–S5

mmc1.pdf^{(1.1MB, pdf)}

Document S2. Article plus supplemental information

mmc2.pdf^{(25.6MB, pdf)}

References

Ando Y., Yamada H., Munetsuna E., Yamazaki M., Kageyama I., Teshigawara A., Nouchi Y., Fujii R., Mizuno G., Sadamoto N., et al. Maternal high-fructose corn syrup consumption causes insulin resistance and hyperlipidemia in offspring via DNA methylation of the Pparα promoter region. J. Nutr. Biochem. 2022;103 doi: 10.1016/j.jnutbio.2022.108951. [DOI] [PubMed] [Google Scholar]
Ando Y., Munetsuna E., Yamada H., Ikeya M., Teshigawara A., Kageyama I., Nouchi Y., Wakasugi T., Yamazaki M., Mizuno G., et al. Impact of maternal fructose intake on liver stem/progenitor cells in offspring: Insights into developmental origins of health and disease. Life Sci. 2024;336 doi: 10.1016/j.lfs.2023.122315. [DOI] [PubMed] [Google Scholar]
Banjac I., Maimets M., Jensen K.B. Maintenance of high-turnover tissues during and beyond homeostasis. Cell Stem Cell. 2023;30:348–361. doi: 10.1016/j.stem.2023.03.008. [DOI] [PubMed] [Google Scholar]
Barker D.J. In utero programming of chronic disease. Clin. Sci. (Lond). 1998;95:115–128. [PubMed] [Google Scholar]
Bianco-Miotto T., Craig J.M., Gasser Y.P., van Dijk S.J., Ozanne S.E. Epigenetics and DOHaD: from basics to birth and beyond. J. Dev. Orig. Health Dis. 2017;8:513–519. doi: 10.1017/S2040174417000733. [DOI] [PubMed] [Google Scholar]
Bilbo S.D., Tsang V. Enduring consequences of maternal obesity for brain inflammation and behavior of offspring. FASEB J. 2010;24:2104–2115. doi: 10.1096/fj.09-144014. [DOI] [PubMed] [Google Scholar]
Burdge G.C., Slater-Jefferies J., Torrens C., Phillips E.S., Hanson M.A., Lillycrop K.A. Dietary protein restriction of pregnant rats in the F0 generation induces altered methylation of hepatic gene promoters in the adult male offspring in the F1 and F2 generations. Br. J. Nutr. 2007;97:435–439. doi: 10.1017/S0007114507352392. [DOI] [PMC free article] [PubMed] [Google Scholar]
Chen Z., Zhang Y. Role of Mammalian DNA Methyltransferases in Development. Annu. Rev. Biochem. 2020;89:135–158. doi: 10.1146/annurev-biochem-103019-102815. [DOI] [PubMed] [Google Scholar]
Chen L., Li Z., Wang W., Zhou Y., Li W., Wang Y. Adult hippocampal neurogenesis: New avenues for treatment of brain disorders. Stem Cell Rep. 2025;20 doi: 10.1016/j.stemcr.2025.102600. [DOI] [PMC free article] [PubMed] [Google Scholar]
Cho I.J., Lui P.P., Obajdin J., Riccio F., Stroukov W., Willis T.L., Spagnoli F., Watt F.M. Mechanisms, Hallmarks, and Implications of Stem Cell Quiescence. Stem Cell Rep. 2019;12:1190–1200. doi: 10.1016/j.stemcr.2019.05.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
de Mendoza A., Nguyen T.V., Ford E., Poppe D., Buckberry S., Pflueger J., Grimmer M.R., Stolzenburg S., Bogdanovic O., Oshlack A., et al. Large-scale manipulation of promoter DNA methylation reveals context-specific transcriptional responses and stability. Genome Biol. 2022;23:163. doi: 10.1186/s13059-022-02728-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
de Morree A., Rando T.A. Regulation of adult stem cell quiescence and its functions in the maintenance of tissue integrity. Nat. Rev. Mol. Cell Biol. 2023;24:334–354. doi: 10.1038/s41580-022-00568-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
Freitas-Vilela A.A., Pearson R.M., Emmett P., Heron J., Smith A.D.A.C., Emond A., Hibbeln J.R., Castro M.B.T., Kac G. Maternal dietary patterns during pregnancy and intelligence quotients in the offspring at 8 years of age: Findings from the ALSPAC cohort. Matern. Child Nutr. 2018;14 doi: 10.1111/mcn.12431. [DOI] [PMC free article] [PubMed] [Google Scholar]
Galera C., Heude B., Forhan A., Bernard J.Y., Peyre H., Van der Waerden J., Pryor L., Bouvard M.-P., Melchior M., Lioret S., et al. Prenatal diet and children’s trajectories of hyperactivity-inattention and conduct problems from 3 to 8 years: the EDEN mother-child cohort. J. Child Psychol. Psychiatry. 2018;59:1003–1011. doi: 10.1111/jcpp.12898. [DOI] [PubMed] [Google Scholar]
Gould J.M., Smith P.J., Airey C.J., Mort E.J., Airey L.E., Warricker F.D.M., Pearson-Farr J.E., Weston E.C., Gould P.J.W., Semmence O.G., et al. Mouse maternal protein restriction during preimplantation alone permanently alters brain neuron proportion and adult short-term memory. Proc. Natl. Acad. Sci. USA. 2018;115:E7398–E7407. doi: 10.1073/pnas.1721876115. [DOI] [PMC free article] [PubMed] [Google Scholar]
Griffin S.M., Pickard M.R., Hawkins C.P., Williams A.C., Fricker R.A. Nicotinamide restricts neural precursor proliferation to enhance catecholaminergic neuronal subtype differentiation from mouse embryonic stem cells. PLoS One. 2020;15 doi: 10.1371/journal.pone.0233477. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ho S.-Y., Chao C.-Y., Huang H.-L., Chiu T.-W., Charoenkwan P., Hwang E. NeurphologyJ: an automatic neuronal morphology quantification method and its application in pharmacological discovery. BMC Bioinf. 2011;12:230. doi: 10.1186/1471-2105-12-230. [DOI] [PMC free article] [PubMed] [Google Scholar]
Jin X. The role of neurogenesis during development and in the adult brain. Eur. J. Neurosci. 2016;44:2291–2299. doi: 10.1111/ejn.13251. [DOI] [PubMed] [Google Scholar]
Kageyama I., Yamada H., Munetsuna E., Yamazaki M., Ando Y., Mizuno G., Fujii R., Nouchi Y., Wakasugi T., Sakakibara T., et al. Differential effects of excess high-fructose corn syrup on the DNA methylation of hippocampal neurotrophic factor in childhood and adolescence. PLoS One. 2022;17 doi: 10.1371/journal.pone.0270144. [DOI] [PMC free article] [PubMed] [Google Scholar]
Leavenworth J.W., Verbinnen B., Wang Q., Shen E., Cantor H. Intracellular osteopontin regulates homeostasis and function of natural killer cells. Proc. Natl. Acad. Sci. USA. 2015;112:494–499. doi: 10.1073/pnas.1423011112. [DOI] [PMC free article] [PubMed] [Google Scholar]
Li Y., Guo W. Neural Stem Cell Niche and Adult Neurogenesis. Neuroscientist. 2021;27:235–245. doi: 10.1177/1073858420939034. [DOI] [PubMed] [Google Scholar]
Lillycrop K.A., Phillips E.S., Torrens C., Hanson M.A., Jackson A.A., Burdge G.C. Feeding pregnant rats a protein-restricted diet persistently alters the methylation of specific cytosines in the hepatic PPAR alpha promoter of the offspring. Br. J. Nutr. 2008;100:278–282. doi: 10.1017/S0007114507894438. [DOI] [PMC free article] [PubMed] [Google Scholar]
Llorente V., Velarde P., Desco M., Gómez-Gaviro M.V. Current Understanding of the Neural Stem Cell Niches. Cells. 2022;11 doi: 10.3390/cells11193002. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ma D.K., Marchetto M.C., Guo J.U., Ming G.l., Gage F.H., Song H. Epigenetic choreographers of neurogenesis in the adult mammalian brain. Nat. Neurosci. 2010;13:1338–1344. doi: 10.1038/nn.2672. [DOI] [PMC free article] [PubMed] [Google Scholar]
Munetsuna E., Yamada H., Yamazaki M., Ando Y., Mizuno G., Hattori Y., Kageyama I., Teshigawara A., Nouchi Y., Ishikawa H., et al. Maternal fructose intake predisposes rat offspring to metabolic disorders via abnormal hepatic programming. FASEB J. 2021;35 doi: 10.1096/fj.202101276R. [DOI] [PubMed] [Google Scholar]
Obernier K., Alvarez-Buylla A. Neural stem cells: origin, heterogeneity and regulation in the adult mammalian brain. Development. 2019;146 doi: 10.1242/dev.156059. [DOI] [PMC free article] [PubMed] [Google Scholar]
O’Brien L.E. Tissue Homeostasis and Non-Homeostasis: From Cell Life Cycles to Organ States. Annu. Rev. Cell Dev. Biol. 2022;38:395–418. doi: 10.1146/annurev-cellbio-120420-114855. [DOI] [PMC free article] [PubMed] [Google Scholar]
Okano M., Bell D.W., Haber D.A., Li E. DNA methyltransferases Dnmt3a and Dnmt3b are essential for de novo methylation and mammalian development. Cell. 1999;99:247–257. doi: 10.1016/s0092-8674(00)81656-6. [DOI] [PubMed] [Google Scholar]
Oomen C.A., Soeters H., Audureau N., Vermunt L., van Hasselt F.N., Manders E.M.M., Joëls M., Lucassen P.J., Krugers H. Severe early life stress hampers spatial learning and neurogenesis, but improves hippocampal synaptic plasticity and emotional learning under high-stress conditions in adulthood. J. Neurosci. 2010;30:6635–6645. doi: 10.1523/JNEUROSCI.0247-10.2010. [DOI] [PMC free article] [PubMed] [Google Scholar]
Podobinska M., Szablowska-Gadomska I., Augustyniak J., Sandvig I., Sandvig A., Buzanska L. Epigenetic Modulation of Stem Cells in Neurodevelopment: The Role of Methylation and Acetylation. Front. Cell. Neurosci. 2017;11:23. doi: 10.3389/fncel.2017.00023. [DOI] [PMC free article] [PubMed] [Google Scholar]
Roseboom T.J., Painter R.C., van Abeelen A.F.M., Veenendaal M.V.E., de Rooij S.R. Hungry in the womb: what are the consequences? Lessons from the Dutch famine. Maturitas. 2011;70:141–145. doi: 10.1016/j.maturitas.2011.06.017. [DOI] [PubMed] [Google Scholar]
Roth T.L., Lubin F.D., Funk A.J., Sweatt J.D. Lasting epigenetic influence of early-life adversity on the BDNF gene. Biol. Psychiatry. 2009;65:760–769. doi: 10.1016/j.biopsych.2008.11.028. [DOI] [PMC free article] [PubMed] [Google Scholar]
Shinohara M.L., Kim H.-J., Kim J.-H., Garcia V.A., Cantor H. Alternative translation of osteopontin generates intracellular and secreted isoforms that mediate distinct biological activities in dendritic cells. Proc. Natl. Acad. Sci. USA. 2008;105:7235–7239. doi: 10.1073/pnas.0802301105. [DOI] [PMC free article] [PubMed] [Google Scholar]
Siddeek B., Simeoni U. Epigenetics provides a bridge between early nutrition and long-term health and a target for disease prevention. Acta Paediatr. 2022;111:927–934. doi: 10.1111/apa.16258. [DOI] [PMC free article] [PubMed] [Google Scholar]
Smith E.V.L., Dyson R.M., Weth F.R., Berry M.J., Gray C. Maternal Fructose Intake, Programmed Mitochondrial Function and Predisposition to Adult Disease. Int. J. Mol. Sci. 2022;23 doi: 10.3390/ijms232012215. [DOI] [PMC free article] [PubMed] [Google Scholar]
Somm E., Schwitzgebel V.M., Toulotte A., Cederroth C.R., Combescure C., Nef S., Aubert M.L., Hüppi P.S. Perinatal exposure to bisphenol a alters early adipogenesis in the rat. Environ. Health Perspect. 2009;117:1549–1555. doi: 10.1289/ehp.11342. [DOI] [PMC free article] [PubMed] [Google Scholar]
Subramanian A., Tamayo P., Mootha V.K., Mukherjee S., Ebert B.L., Gillette M.A., Paulovich A., Pomeroy S.L., Golub T.R., Lander E.S., Mesirov J.P. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA. 2005;102:15545–15550. doi: 10.1073/pnas.0506580102. [DOI] [PMC free article] [PubMed] [Google Scholar]
Suri D., Veenit V., Sarkar A., Thiagarajan D., Kumar A., Nestler E.J., Galande S., Vaidya V.A. Early stress evokes age-dependent biphasic changes in hippocampal neurogenesis, BDNF expression, and cognition. Biol. Psychiatry. 2013;73:658–666. doi: 10.1016/j.biopsych.2012.10.023. [DOI] [PMC free article] [PubMed] [Google Scholar]
Thompson M.D., DeBosch B.J. Maternal Fructose Diet-Induced Developmental Programming. Nutrients. 2021;13:3278. doi: 10.3390/nu13093278. [DOI] [PMC free article] [PubMed] [Google Scholar]
Tozuka Y., Fukuda S., Namba T., Seki T., Hisatsune T. GABAergic excitation promotes neuronal differentiation in adult hippocampal progenitor cells. Neuron. 2005;47:803–815. doi: 10.1016/j.neuron.2005.08.023. [DOI] [PubMed] [Google Scholar]
Urbán N., Guillemot F. Neurogenesis in the embryonic and adult brain: same regulators, different roles. Front. Cell. Neurosci. 2014;8:396. doi: 10.3389/fncel.2014.00396. [DOI] [PMC free article] [PubMed] [Google Scholar]
Van den Bergh B.R.H. Developmental programming of early brain and behaviour development and mental health: a conceptual framework. Dev. Med. Child Neurol. 2011;53:19–23. doi: 10.1111/j.1469-8749.2011.04057.x. [DOI] [PubMed] [Google Scholar]
Wei L., Simen A., Mane S., Kaffman A. Early life stress inhibits expression of a novel innate immune pathway in the developing hippocampus. Neuropsychopharmacology. 2012;37:567–580. doi: 10.1038/npp.2011.239. [DOI] [PMC free article] [PubMed] [Google Scholar]
Yagi M., Kabata M., Tanaka A., Ukai T., Ohta S., Nakabayashi K., Shimizu M., Hata K., Meissner A., Yamamoto T., et al. Identification of distinct loci for de novo DNA methylation by DNMT3A and DNMT3B during mammalian development. Nat. Commun. 2020;11:3199. doi: 10.1038/s41467-020-16989-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
Yamada H., Munetsuna E., Yamazaki M., Mizuno G., Sadamoto N., Ando Y., Fujii R., Shiogama K., Ishikawa H., Suzuki K., et al. Maternal fructose-induced oxidative stress occurs viaTfam and Ucp5 epigenetic regulation in offspring hippocampi. FASEB J. 2019;33:11431–11442. doi: 10.1096/fj.201901072R. [DOI] [PubMed] [Google Scholar]
Yamazaki M., Yamada H., Munetsuna E., Ishikawa H., Mizuno G., Mukuda T., Mouri A., Nabeshima T., Saito K., Suzuki K., et al. Excess maternal fructose consumption impairs hippocampal function in offspring via epigenetic modification of BDNF promoter. FASEB J. 2018;32:2549–2562. doi: 10.1096/fj.201700783RR. [DOI] [PubMed] [Google Scholar]
Yamazaki M., Yamada H., Munetsuna E., Ando Y., Kageyama I., Sadamoto N., Nouchi Y., Teshigawara A., Mizuno G., Ishikawa H., et al. Interaction between Prenatal and Postnatal Exposure to High-Fructose Corn Syrup Increases Gene Expression of Tnfa in Hippocampus of Offspring. J. Nutr. Sci. Vitaminol. 2023;69:237–242. doi: 10.3177/jnsv.69.237. [DOI] [PubMed] [Google Scholar]
Yamazaki M., Yamada H., Munetsuna E., Ando Y., Mizuno G., Teshigawara A., Ichikawa H., Nouchi Y., Kageyama I., Wakasugi T., et al. Approaches to nutritional research using organoids; fructose treatment induces epigenetic changes in liver organoids. J. Nutr. Biochem. 2024;131 doi: 10.1016/j.jnutbio.2024.109671. [DOI] [PubMed] [Google Scholar]
Yuan X., Tsujimoto K., Hashimoto K., Kawahori K., Hanzawa N., Hamaguchi M., Seki T., Nawa M., Ehara T., Kitamura Y., et al. Epigenetic modulation of Fgf21 in the perinatal mouse liver ameliorates diet-induced obesity in adulthood. Nat. Commun. 2018;9:636. doi: 10.1038/s41467-018-03038-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zhao C., Deng W., Gage F.H. Mechanisms and functional implications of adult neurogenesis. Cell. 2008;132:645–660. doi: 10.1016/j.cell.2008.01.033. [DOI] [PubMed] [Google Scholar]
Zhou Y., Zhou B., Pache L., Chang M., Khodabakhshi A.H., Tanaseichuk O., Benner C., Chanda S.K. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat. Commun. 2019;10:1523. doi: 10.1038/s41467-019-09234-6. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Document S1. Figures S1–S7 and Tables S1–S5

mmc1.pdf^{(1.1MB, pdf)}

Document S2. Article plus supplemental information

mmc2.pdf^{(25.6MB, pdf)}

Data Availability Statement

[bib1] Ando Y., Yamada H., Munetsuna E., Yamazaki M., Kageyama I., Teshigawara A., Nouchi Y., Fujii R., Mizuno G., Sadamoto N., et al. Maternal high-fructose corn syrup consumption causes insulin resistance and hyperlipidemia in offspring via DNA methylation of the Pparα promoter region. J. Nutr. Biochem. 2022;103 doi: 10.1016/j.jnutbio.2022.108951. [DOI] [PubMed] [Google Scholar]

[bib2] Ando Y., Munetsuna E., Yamada H., Ikeya M., Teshigawara A., Kageyama I., Nouchi Y., Wakasugi T., Yamazaki M., Mizuno G., et al. Impact of maternal fructose intake on liver stem/progenitor cells in offspring: Insights into developmental origins of health and disease. Life Sci. 2024;336 doi: 10.1016/j.lfs.2023.122315. [DOI] [PubMed] [Google Scholar]

[bib3] Banjac I., Maimets M., Jensen K.B. Maintenance of high-turnover tissues during and beyond homeostasis. Cell Stem Cell. 2023;30:348–361. doi: 10.1016/j.stem.2023.03.008. [DOI] [PubMed] [Google Scholar]

[bib4] Barker D.J. In utero programming of chronic disease. Clin. Sci. (Lond). 1998;95:115–128. [PubMed] [Google Scholar]

[bib6] Bianco-Miotto T., Craig J.M., Gasser Y.P., van Dijk S.J., Ozanne S.E. Epigenetics and DOHaD: from basics to birth and beyond. J. Dev. Orig. Health Dis. 2017;8:513–519. doi: 10.1017/S2040174417000733. [DOI] [PubMed] [Google Scholar]

[bib7] Bilbo S.D., Tsang V. Enduring consequences of maternal obesity for brain inflammation and behavior of offspring. FASEB J. 2010;24:2104–2115. doi: 10.1096/fj.09-144014. [DOI] [PubMed] [Google Scholar]

[bib8] Burdge G.C., Slater-Jefferies J., Torrens C., Phillips E.S., Hanson M.A., Lillycrop K.A. Dietary protein restriction of pregnant rats in the F0 generation induces altered methylation of hepatic gene promoters in the adult male offspring in the F1 and F2 generations. Br. J. Nutr. 2007;97:435–439. doi: 10.1017/S0007114507352392. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib9] Chen Z., Zhang Y. Role of Mammalian DNA Methyltransferases in Development. Annu. Rev. Biochem. 2020;89:135–158. doi: 10.1146/annurev-biochem-103019-102815. [DOI] [PubMed] [Google Scholar]

[bib10] Chen L., Li Z., Wang W., Zhou Y., Li W., Wang Y. Adult hippocampal neurogenesis: New avenues for treatment of brain disorders. Stem Cell Rep. 2025;20 doi: 10.1016/j.stemcr.2025.102600. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib11] Cho I.J., Lui P.P., Obajdin J., Riccio F., Stroukov W., Willis T.L., Spagnoli F., Watt F.M. Mechanisms, Hallmarks, and Implications of Stem Cell Quiescence. Stem Cell Rep. 2019;12:1190–1200. doi: 10.1016/j.stemcr.2019.05.012. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib24] de Mendoza A., Nguyen T.V., Ford E., Poppe D., Buckberry S., Pflueger J., Grimmer M.R., Stolzenburg S., Bogdanovic O., Oshlack A., et al. Large-scale manipulation of promoter DNA methylation reveals context-specific transcriptional responses and stability. Genome Biol. 2022;23:163. doi: 10.1186/s13059-022-02728-5. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib25] de Morree A., Rando T.A. Regulation of adult stem cell quiescence and its functions in the maintenance of tissue integrity. Nat. Rev. Mol. Cell Biol. 2023;24:334–354. doi: 10.1038/s41580-022-00568-6. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib12] Freitas-Vilela A.A., Pearson R.M., Emmett P., Heron J., Smith A.D.A.C., Emond A., Hibbeln J.R., Castro M.B.T., Kac G. Maternal dietary patterns during pregnancy and intelligence quotients in the offspring at 8 years of age: Findings from the ALSPAC cohort. Matern. Child Nutr. 2018;14 doi: 10.1111/mcn.12431. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib13] Galera C., Heude B., Forhan A., Bernard J.Y., Peyre H., Van der Waerden J., Pryor L., Bouvard M.-P., Melchior M., Lioret S., et al. Prenatal diet and children’s trajectories of hyperactivity-inattention and conduct problems from 3 to 8 years: the EDEN mother-child cohort. J. Child Psychol. Psychiatry. 2018;59:1003–1011. doi: 10.1111/jcpp.12898. [DOI] [PubMed] [Google Scholar]

[bib14] Gould J.M., Smith P.J., Airey C.J., Mort E.J., Airey L.E., Warricker F.D.M., Pearson-Farr J.E., Weston E.C., Gould P.J.W., Semmence O.G., et al. Mouse maternal protein restriction during preimplantation alone permanently alters brain neuron proportion and adult short-term memory. Proc. Natl. Acad. Sci. USA. 2018;115:E7398–E7407. doi: 10.1073/pnas.1721876115. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib15] Griffin S.M., Pickard M.R., Hawkins C.P., Williams A.C., Fricker R.A. Nicotinamide restricts neural precursor proliferation to enhance catecholaminergic neuronal subtype differentiation from mouse embryonic stem cells. PLoS One. 2020;15 doi: 10.1371/journal.pone.0233477. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib16] Ho S.-Y., Chao C.-Y., Huang H.-L., Chiu T.-W., Charoenkwan P., Hwang E. NeurphologyJ: an automatic neuronal morphology quantification method and its application in pharmacological discovery. BMC Bioinf. 2011;12:230. doi: 10.1186/1471-2105-12-230. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib17] Jin X. The role of neurogenesis during development and in the adult brain. Eur. J. Neurosci. 2016;44:2291–2299. doi: 10.1111/ejn.13251. [DOI] [PubMed] [Google Scholar]

[bib18] Kageyama I., Yamada H., Munetsuna E., Yamazaki M., Ando Y., Mizuno G., Fujii R., Nouchi Y., Wakasugi T., Sakakibara T., et al. Differential effects of excess high-fructose corn syrup on the DNA methylation of hippocampal neurotrophic factor in childhood and adolescence. PLoS One. 2022;17 doi: 10.1371/journal.pone.0270144. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib19] Leavenworth J.W., Verbinnen B., Wang Q., Shen E., Cantor H. Intracellular osteopontin regulates homeostasis and function of natural killer cells. Proc. Natl. Acad. Sci. USA. 2015;112:494–499. doi: 10.1073/pnas.1423011112. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib20] Li Y., Guo W. Neural Stem Cell Niche and Adult Neurogenesis. Neuroscientist. 2021;27:235–245. doi: 10.1177/1073858420939034. [DOI] [PubMed] [Google Scholar]

[bib21] Lillycrop K.A., Phillips E.S., Torrens C., Hanson M.A., Jackson A.A., Burdge G.C. Feeding pregnant rats a protein-restricted diet persistently alters the methylation of specific cytosines in the hepatic PPAR alpha promoter of the offspring. Br. J. Nutr. 2008;100:278–282. doi: 10.1017/S0007114507894438. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib22] Llorente V., Velarde P., Desco M., Gómez-Gaviro M.V. Current Understanding of the Neural Stem Cell Niches. Cells. 2022;11 doi: 10.3390/cells11193002. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib23] Ma D.K., Marchetto M.C., Guo J.U., Ming G.l., Gage F.H., Song H. Epigenetic choreographers of neurogenesis in the adult mammalian brain. Nat. Neurosci. 2010;13:1338–1344. doi: 10.1038/nn.2672. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib26] Munetsuna E., Yamada H., Yamazaki M., Ando Y., Mizuno G., Hattori Y., Kageyama I., Teshigawara A., Nouchi Y., Ishikawa H., et al. Maternal fructose intake predisposes rat offspring to metabolic disorders via abnormal hepatic programming. FASEB J. 2021;35 doi: 10.1096/fj.202101276R. [DOI] [PubMed] [Google Scholar]

[bib27] Obernier K., Alvarez-Buylla A. Neural stem cells: origin, heterogeneity and regulation in the adult mammalian brain. Development. 2019;146 doi: 10.1242/dev.156059. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib28] O’Brien L.E. Tissue Homeostasis and Non-Homeostasis: From Cell Life Cycles to Organ States. Annu. Rev. Cell Dev. Biol. 2022;38:395–418. doi: 10.1146/annurev-cellbio-120420-114855. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib29] Okano M., Bell D.W., Haber D.A., Li E. DNA methyltransferases Dnmt3a and Dnmt3b are essential for de novo methylation and mammalian development. Cell. 1999;99:247–257. doi: 10.1016/s0092-8674(00)81656-6. [DOI] [PubMed] [Google Scholar]

[bib30] Oomen C.A., Soeters H., Audureau N., Vermunt L., van Hasselt F.N., Manders E.M.M., Joëls M., Lucassen P.J., Krugers H. Severe early life stress hampers spatial learning and neurogenesis, but improves hippocampal synaptic plasticity and emotional learning under high-stress conditions in adulthood. J. Neurosci. 2010;30:6635–6645. doi: 10.1523/JNEUROSCI.0247-10.2010. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib31] Podobinska M., Szablowska-Gadomska I., Augustyniak J., Sandvig I., Sandvig A., Buzanska L. Epigenetic Modulation of Stem Cells in Neurodevelopment: The Role of Methylation and Acetylation. Front. Cell. Neurosci. 2017;11:23. doi: 10.3389/fncel.2017.00023. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib32] Roseboom T.J., Painter R.C., van Abeelen A.F.M., Veenendaal M.V.E., de Rooij S.R. Hungry in the womb: what are the consequences? Lessons from the Dutch famine. Maturitas. 2011;70:141–145. doi: 10.1016/j.maturitas.2011.06.017. [DOI] [PubMed] [Google Scholar]

[bib33] Roth T.L., Lubin F.D., Funk A.J., Sweatt J.D. Lasting epigenetic influence of early-life adversity on the BDNF gene. Biol. Psychiatry. 2009;65:760–769. doi: 10.1016/j.biopsych.2008.11.028. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib34] Shinohara M.L., Kim H.-J., Kim J.-H., Garcia V.A., Cantor H. Alternative translation of osteopontin generates intracellular and secreted isoforms that mediate distinct biological activities in dendritic cells. Proc. Natl. Acad. Sci. USA. 2008;105:7235–7239. doi: 10.1073/pnas.0802301105. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib35] Siddeek B., Simeoni U. Epigenetics provides a bridge between early nutrition and long-term health and a target for disease prevention. Acta Paediatr. 2022;111:927–934. doi: 10.1111/apa.16258. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib36] Smith E.V.L., Dyson R.M., Weth F.R., Berry M.J., Gray C. Maternal Fructose Intake, Programmed Mitochondrial Function and Predisposition to Adult Disease. Int. J. Mol. Sci. 2022;23 doi: 10.3390/ijms232012215. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib37] Somm E., Schwitzgebel V.M., Toulotte A., Cederroth C.R., Combescure C., Nef S., Aubert M.L., Hüppi P.S. Perinatal exposure to bisphenol a alters early adipogenesis in the rat. Environ. Health Perspect. 2009;117:1549–1555. doi: 10.1289/ehp.11342. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib38] Subramanian A., Tamayo P., Mootha V.K., Mukherjee S., Ebert B.L., Gillette M.A., Paulovich A., Pomeroy S.L., Golub T.R., Lander E.S., Mesirov J.P. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA. 2005;102:15545–15550. doi: 10.1073/pnas.0506580102. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib39] Suri D., Veenit V., Sarkar A., Thiagarajan D., Kumar A., Nestler E.J., Galande S., Vaidya V.A. Early stress evokes age-dependent biphasic changes in hippocampal neurogenesis, BDNF expression, and cognition. Biol. Psychiatry. 2013;73:658–666. doi: 10.1016/j.biopsych.2012.10.023. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib40] Thompson M.D., DeBosch B.J. Maternal Fructose Diet-Induced Developmental Programming. Nutrients. 2021;13:3278. doi: 10.3390/nu13093278. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib41] Tozuka Y., Fukuda S., Namba T., Seki T., Hisatsune T. GABAergic excitation promotes neuronal differentiation in adult hippocampal progenitor cells. Neuron. 2005;47:803–815. doi: 10.1016/j.neuron.2005.08.023. [DOI] [PubMed] [Google Scholar]

[bib42] Urbán N., Guillemot F. Neurogenesis in the embryonic and adult brain: same regulators, different roles. Front. Cell. Neurosci. 2014;8:396. doi: 10.3389/fncel.2014.00396. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib5] Van den Bergh B.R.H. Developmental programming of early brain and behaviour development and mental health: a conceptual framework. Dev. Med. Child Neurol. 2011;53:19–23. doi: 10.1111/j.1469-8749.2011.04057.x. [DOI] [PubMed] [Google Scholar]

[bib43] Wei L., Simen A., Mane S., Kaffman A. Early life stress inhibits expression of a novel innate immune pathway in the developing hippocampus. Neuropsychopharmacology. 2012;37:567–580. doi: 10.1038/npp.2011.239. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib44] Yagi M., Kabata M., Tanaka A., Ukai T., Ohta S., Nakabayashi K., Shimizu M., Hata K., Meissner A., Yamamoto T., et al. Identification of distinct loci for de novo DNA methylation by DNMT3A and DNMT3B during mammalian development. Nat. Commun. 2020;11:3199. doi: 10.1038/s41467-020-16989-w. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib45] Yamada H., Munetsuna E., Yamazaki M., Mizuno G., Sadamoto N., Ando Y., Fujii R., Shiogama K., Ishikawa H., Suzuki K., et al. Maternal fructose-induced oxidative stress occurs viaTfam and Ucp5 epigenetic regulation in offspring hippocampi. FASEB J. 2019;33:11431–11442. doi: 10.1096/fj.201901072R. [DOI] [PubMed] [Google Scholar]

[bib46] Yamazaki M., Yamada H., Munetsuna E., Ishikawa H., Mizuno G., Mukuda T., Mouri A., Nabeshima T., Saito K., Suzuki K., et al. Excess maternal fructose consumption impairs hippocampal function in offspring via epigenetic modification of BDNF promoter. FASEB J. 2018;32:2549–2562. doi: 10.1096/fj.201700783RR. [DOI] [PubMed] [Google Scholar]

[bib47] Yamazaki M., Yamada H., Munetsuna E., Ando Y., Kageyama I., Sadamoto N., Nouchi Y., Teshigawara A., Mizuno G., Ishikawa H., et al. Interaction between Prenatal and Postnatal Exposure to High-Fructose Corn Syrup Increases Gene Expression of Tnfa in Hippocampus of Offspring. J. Nutr. Sci. Vitaminol. 2023;69:237–242. doi: 10.3177/jnsv.69.237. [DOI] [PubMed] [Google Scholar]

[bib48] Yamazaki M., Yamada H., Munetsuna E., Ando Y., Mizuno G., Teshigawara A., Ichikawa H., Nouchi Y., Kageyama I., Wakasugi T., et al. Approaches to nutritional research using organoids; fructose treatment induces epigenetic changes in liver organoids. J. Nutr. Biochem. 2024;131 doi: 10.1016/j.jnutbio.2024.109671. [DOI] [PubMed] [Google Scholar]

[bib49] Yuan X., Tsujimoto K., Hashimoto K., Kawahori K., Hanzawa N., Hamaguchi M., Seki T., Nawa M., Ehara T., Kitamura Y., et al. Epigenetic modulation of Fgf21 in the perinatal mouse liver ameliorates diet-induced obesity in adulthood. Nat. Commun. 2018;9:636. doi: 10.1038/s41467-018-03038-w. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib50] Zhao C., Deng W., Gage F.H. Mechanisms and functional implications of adult neurogenesis. Cell. 2008;132:645–660. doi: 10.1016/j.cell.2008.01.033. [DOI] [PubMed] [Google Scholar]

[bib51] Zhou Y., Zhou B., Pache L., Chang M., Khodabakhshi A.H., Tanaseichuk O., Benner C., Chanda S.K. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat. Commun. 2019;10:1523. doi: 10.1038/s41467-019-09234-6. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Neural stem cells as potential mediators of prenatal dietary stress through epigenetic mechanisms

Itsuki Kageyama

Hiroya Yamada

Mirai Yamazaki

Takuya Wakasugi

Yuri Kamiya

Masaki Ohshiro

Manaka Ito

Yoshiki Tsuboi

Takashi Watanabe

Genki Mizuno

Yoshitaka Ando

Hiroaki Ishikawa

Koji Suzuki

Koji Ohashi

Eiji Munetsuna

Summary

Graphical abstract

Highlights

Introduction

Results

Maternal HFCS intake impairs hippocampus-dependent memory and adult neurogenesis in offspring

Figure 1.

Persistent NSC dysfunction induced by maternal HFCS exposure

Figure 2.

Transcriptomic dysregulation in fetal NSCs following HFCS exposure at E20.5

Figure 3.

Maternal HFCS intake suppresses Dnmt3a and downregulates Spp1 in NSCs

Figure 4.

Persistent repression of Spp1 in postnatal NSCs

Figure 5.

Functional relevance of Spp1 in NSCs

Figure 6.

iOPN restores NSC function impaired by maternal HFCS intake

Figure 7.

Discussion

Resource availability

Lead contact

Materials availability

Data and code availability

Acknowledgments

Author contributions

Declaration of interests

STAR★Methods

Key resources table

Experimental model and study participant details

Animals

Method details

Behavior, novel-object recognition assay

Immunohistochemistry and quantification of BrdU-labeled cells

Isolation and culture of primary hippocampal NSCs

Proliferation and neural differentiation analysis

Immunostaining for characterization of NSCs

Transcriptome analysis

qPCR

Western blotting

DNMT activity analysis

Luciferase assay

Analysis of CpG methylation

Small interfering RNAs (siRNA) experiments and transfection

sOPN treatment and iOPN transfection

Statistical analysis

Footnotes

Supplemental information

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases