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. 2026 May 12;54:101253. doi: 10.1016/j.bbih.2026.101253

Inflammatory reprogramming of immature oligodendrocytes perturbs myelination and neurodevelopment in a dual-hit model of preterm brain injury

Xueling Ma a,b, Wen Jia a,b, Xingdao Zhang a,b, Yuan Shi a,⁎
PMCID: PMC13213655  PMID: 42210979

Abstract

Background

Preterm infants are highly susceptible to white matter injury, in part due to exposure to perinatal inflammation and/or hypoxia. These insults disrupt oligodendrocyte (OL) lineage maturation, leading to impaired myelination and neurodevelopmental deficits; however, the underlying mechanisms remain incompletely understood.

Methods

A dual-hit rat model was established to recapitulate key features of preterm brain injury. Myelination, behavior, and brain function and structure were assessed. The early developmental trajectory of immature OLs was tracked, and the cells were isolated for transcriptomic profiling.

Results

The dual-hit model exhibited delayed myelination, accompanied by long-term behavioral abnormalities, reduced hippocampal functional connectivity, and decreased hippocampal gray matter volume. A marked surge in immature OL death was observed around postnatal day 9. Transcriptomic profiling at this developmentally vulnerable time point revealed pronounced inflammatory reprogramming within immature OLs.

Conclusions

Perinatal inflammation combined with postnatal hypoxia delays myelination and leads to persistent behavioral and brain structural and functional alterations, with immature OLs loss and inflammatory reprogramming emerging as potential drivers of preterm brain injury.

Graphical abstract

A dual-hit model of preterm brain injury demonstrates that extensive loss and inflammatory reprogramming of pre-myelinating oligodendrocytes during a vulnerable developmental window impair oligodendrocyte maturation and contribute to long-term neurodevelopmental deficits (This figure was created using BioRender.com).

graphic file with name ga1.jpg

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Highlights

  • •

    A dual-hit rat model recapitulates key features of preterm brain injury.

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    Early myelination defects cause long-term alterations in brain functional connectivity, gray matter development, and behavior.

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    Lineage tracking reveals extensive immature oligodendrocyte loss after perinatal injury.

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    Transcriptomic profiling reveals inflammatory reprogramming of immature oligodendrocytes.

1. Introduction

Preterm birth affects approximately 14 million infants worldwide each year, with nearly 15% occurring before 32 weeks of gestation (Ohuma et al., 2023). Although advances in perinatal medicine have improved survival, neurodevelopmental sequelae remain common—more than half of extremely (<28 weeks) and very preterm (28–32 weeks) survivors experience motor, cognitive, behavioral, or emotional impairments (Volpe, 2019; Anderson and Doyle, 2003). Understanding how early-life insults disrupt brain development is essential for improving neurodevelopmental outcomes.

White-matter injury (WMI) is the hallmark neuropathology of preterm brain injury (Cheong et al., 2020). A central mechanism underlying WMI is the loss of, and maturational arrest within, the oligodendrocyte (OL) lineage. The OL lineage progresses from OL precursor cells (OPCs) to pre-myelinating OLs (pre-OLs), often referred to as immature OLs, and ultimately to mature, myelinating OLs. In humans, myelination begins at approximately 30 weeks of gestation and follows a well-defined spatiotemporal program (van Tilborg et al., 2018) with marked regional asynchrony (Dubois et al., 2008). Preterm birth occurs within this critical developmental window, when pre-OLs predominate in the white matter and are highly susceptible to hypoxia, ischemia, inflammation, and oxidative stress. These insults result in extensive pre-OLs loss and transient depletion of the myelinating pool. Although OPCs proliferate and repopulate the lineage, their differentiation is delayed or arrested, resulting in hypomyelination (Salmaso et al., 2014; Barateiro et al., 2016). In rodents, by comparison, neurogenesis is largely completed before birth, whereas gliogenesis initiates in late embryonic stages and becomes prominent postnatally (Kriegstein and Alvarez-Buylla, 2009). Oligodendrocyte lineage cells proliferate, migrate, and differentiate primarily during the first 2 postnatal weeks, corresponding to approximately 23–37 weeks of human gestation— a developmental window characterized by the predominance and heightened vulnerability of pre-OLs (Salmaso et al., 2014). Traditionally, pre-OLs have been viewed primarily as precursors that differentiate into mature OLs to form myelin. However, recent transcriptomic evidence indicates that under pathological conditions, distinct pre-OL subpopulations characterized by inflammation-related gene expression can arise (Moyon et al., 2015; Kirby and Castelo-Branco, 2021). Despite these observations, studies addressing such inflammation-related pre-OLs remain limited. Importantly, whether such pre-OL subtypes emerge in the context of preterm brain injury, and how their presence may relate to disease progression, remain largely unknown.

Although numerous preclinical models have been developed, each captures only a subset of the complex pathophysiology underlying preterm brain injury (Jantzie and Robinson, 2015). Under normal conditions, the intrauterine immune environment transitions from a proinflammatory to an anti-inflammatory state during pregnancy and returns to a proinflammatory state before labor; preterm birth disrupts this trajectory, prematurely exposing the fetal brain to inflammatory stress (Humberg et al., 2020). Maternal lipopolysaccharide (LPS)–induced chorioamnionitis is a well-established trigger of preterm birth and subsequent neurodevelopmental deficits (Jantzie and Robinson, 2015). In parallel, the preterm brain is highly vulnerable to hypoxia due to immature cerebrovascular autoregulation and respiratory instability (Salmaso et al., 2014; Rhee et al., 2018). Guided by this dual-insult framework, we established a model combining prenatal inflammation with postnatal hypoxia to better recapitulate preterm brain injury, with LPS administered at E18.5 to model late-gestational inflammatory priming and hypoxia applied during P3–P11 to target the peak window of oligodendrocyte vulnerability. Using this dual-hit model, we aimed to delineate how immature OL development is perturbed in the preterm brain.

2. Methods and materials

2.1. Reagents

Lipopolysaccharide (E. coli O55:B5, L2880) was purchased from Sigma-Aldrich (USA). For immunostaining, the following primary antibodies were used: anti-MBP (ab11159, Abcam), anti-NF200 (ab207176, Abcam), anti-SYN1 (20258-1-AP, Proteintech), and anti-MAP2 (67015-1-Ig, Proteintech). The secondary antibodies included goat anti-rabbit IgG [Cy5] (ab6564, Abcam), goat anti-mouse IgG [FITC] (ab6785, Abcam), and goat anti-rabbit IgG [Alexa Fluor 555] (ab150078, Abcam). For flow cytometry, the following antibodies were used: anti-O4 [Alexa Fluor 405] (FAB1326V, NovusBio) and anti-PDGFRα [Alexa Fluor 647] (NBP2-73303AF647, NovusBio). The Neonatal Brain Dissociation Kit (DHABE-5003) was purchased from RWD Life Science (China). The Annexin V–FITC Apoptosis Detection Kit I was purchased from BD Biosciences (USA). The primer sequences used in this study are provided below.

Gene Forward Reverse
Ugt8 TGTGCTTCTGCTTGGTGCTGTC TCCATTAACTGTGCTGTGCGTACTC
Mog GCTACGCAGGACAGTTCAGAGTG GGAGATATACGGCACGGCAGTTC
Mbp ACCACTCTGGAAAGCGAGAATTAGC ACTGTCTTCTGAGGCGGTCTGAG
Plp1 TCTTTGGAGCGGGTGTGTCATTG CACCAGGAGCCATACAACAGTCAG
Pdgfra AAGATTGTGCCGCTGAGTTCGTC GCTACTGTTGTTCTCCTCGGTTCTG
Cspg4 GGCAGCCTCATGGTGATCCT TCGGTGTTCCACAGGGACAC
Gapdh AGTTCAACGGCACAGTCAAGGC CGACATACTCAGCACCAGCATCAC
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2.2. Animal models

Adult Sprague–Dawley (SD) rats were housed under standard conditions with free access to food and water. Female rats (12–14 weeks old) were paired with males overnight (8:00 p.m.–8:00 a.m.), and the presence of a vaginal plug the next morning was designated as embryonic day 0.5 (E0.5). Pregnant females were housed individually until parturition. Dams were randomly assigned to Control, LPS, or LPS + hypoxia groups. A hypoxia-only group was not included, as the study was designed to evaluate the impact of postnatal hypoxia in the context of prenatal inflammation, a clinically relevant scenario in preterm brain injury. On E18.5, Control dams received saline (1 mL/kg), while the LPS and LPS + hypoxia groups received LPS (200 μg/kg, i.p.). Litter sizes were standardized to 10–12 pups per dam to minimize variability in nutritional status. Offspring in the LPS + hypoxia group were exposed to 8 ± 1% O2 for 2.5 h/day from postnatal day 3 (P3) to P11. Specifically, all pups from LPS + hypoxia group were exposed to hypoxia, while dams remained in the original cages and were not exposed to hypoxia. To control for maternal separation effects, pups from the Control and LPS-only groups were also separated from the dam for 2.5h/day. After modeling, pups were weaned at 3 weeks of age. Only male offspring were used for experiments, except for pups younger than P7, whose sex could not be reliably determined. The decision was based on prior clinical and experimental evidence indicating increased male vulnerability to preterm brain injury and adverse neurodevelopmental outcomes (Mayoral et al., 2009; Hill and Fitch, 2012; Kozhemiako et al., 2020; Kelly et al., 2023). Behavioral testing commenced at 6 weeks of age. Samples were obtained from multiple independent litters, and detailed litter information is provided in Table S1. All experimental procedures were approved by the Animal Ethics Committee of Chongqing Medical University.

2.3. Immunofluorescence staining

Rats were anesthetized with 2% pentobarbital sodium (0.25 mL/100 g, i.p.) and transcardially perfused with pre-warmed saline followed by 4% paraformaldehyde (PFA). Brains were removed, post-fixed in 4% PFA at 4 °C for 12 h, and processed for paraffin embedding. Coronal sections (4 μm) were prepared at hippocampal levels. Sections were deparaffinized, rehydrated, and subjected to antigen retrieval using proteinase K (20 μg/mL, 37 °C, 15 min). After permeabilization with 0.3% Triton X-100 in PBS, sections were blocked with 5% bovine serum albumin (BSA) for 30 min at room temperature, then incubated overnight at 4 °C with primary antibodies diluted in 5% BSA. After washing, sections were incubated with fluorescent secondary antibodies for 2 h at room temperature in the dark, followed by nuclear counterstaining with DAPI (1:500, 5 min). Slides were mounted using an anti-fade medium and imaged under an upright fluorescence microscope (Olympus, Japan). Quantitative analysis was performed using ImageJ software.

2.4. Transmission electron microscopy (TEM)

Rats were anesthetized and perfused with pre-warmed saline, followed by 2% PFA + 2.5% glutaraldehyde fixative. Brains were removed, and coronal tissue blocks (∼1 mm3) containing the corpus callosum were dissected and stored in the same fixative at 4 °C until further processing. Samples were rinsed in 0.1 M phosphate buffer (pH 7.4), post-fixed in 1% osmium tetroxide for 2 h at 4 °C, dehydrated through graded ethanol and acetone, and embedded in epoxy resin. Semi-thin sections were used for localization, and ultrathin sections (∼60 nm) were prepared using an ultramicrotome. Sections were examined under a transmission electron microscope (JEM-1400Plus, JEOL) at 8000 × magnification. For morphometric analysis, five fields per sample were imaged, and 20 myelinated axons per field were analyzed using ImageJ (G-ratio plugin). The g-ratio was calculated as the ratio of axon diameter to fiber diameter.

2.5. Behavioral assessment

Behavioral tests were conducted and analyzed by investigators blinded to group assignments. Behavioral tests were conducted in a fixed sequence. To minimize carry-over effects, tests were arranged to reduce cumulative stress and fatigue: the open field test and novel object recognition test was performed on day 1, the elevated plus maze on day 2, Morris water maze training began on day 3, and rotarod testing was conducted after completion of the water maze, with a 5-day recovery interval. Exploratory and anxiety-like behaviors were assessed using the open field test and the elevated plus maze. In the open field test, each rat was placed in a square arena (100 × 100 cm) for 5.5 min, with the first 30 s excluded from analysis. Locomotor activity and zone entries were automatically recorded using ANY-maze software. In the elevated plus maze, rats were placed at the center of the apparatus and allowed to explore for 5 min. The time spent in and the number of entries into the open arms were recorded. Spatial learning and memory were assessed using the Morris water maze. The circular pool (160 cm in diameter) was divided into four quadrants, and a hidden platform was positioned 2 cm below the water surface in one fixed quadrant during training. The water temperature was maintained at 23–25 °C throughout the experiment. Rats underwent five consecutive days of training to locate the platform and were released from different quadrants each day in a fixed order. Escape latency and path length were recorded. On day 6, the platform was removed for a 60-s probe trial to assess memory retention. Time spent in the target quadrant and the number of platform crossings were quantified using ANY-maze software. Recognition memory was assessed using the novel object recognition test, with preference for the novel object calculated based on exploration time during the test phase. Motor coordination and balance were evaluated using the rotarod test, and performance was quantified as the time spent on the rotating rod. The open field test, novel object recognition test, elevated plus maze, and Morris water maze, were video-recorded and analyzed using ANY-maze (system ID: PA20190830FA). Rotarod performance was assessed using an automated rotarod system (RTR, BYZ-007, Bozhiyuan, China).

2.6. Magnetic resonance imaging (MRI) and data analysis

At 8 weeks of age, rats from the Control and LPS + hypoxia groups underwent multimodal MRI using a 7.0 T small-animal scanner (Bruker, Germany). Animals were anesthetized with 4% isoflurane in oxygen and scanned using a four-channel head coil. Respiration and heart rate were continuously monitored to ensure physiological stability. Two imaging modalities were acquired sequentially: (1) Resting-state functional MRI (rs-fMRI) (T2-weighted EPI): TR = 2735 ms, TE = 19.8 ms, matrix = 100 × 100, 47 slices (0.6 mm), voxel size = 0.35 × 0.35 mm2, flip angle = 60°, 300 vol (2) T2-weighted structural imaging (RARE): TR = 10,428 ms, TE = 40 ms, matrix = 192 × 192, voxel size = 0.18 × 0.18 mm2, slice thickness = 0.3 mm, 94 slices.

Data preprocessing and analysis: Image quality was inspected prior to analysis. For rs-fMRI data, preprocessing was performed in SPM12 (MATLAB), including image rescaling ( × 10), slice-timing and motion correction, and two-step spatial normalization using an enlarged rat Sigma template. Data were smoothed (Gaussian kernel = 6 mm), and the amplitude of low-frequency fluctuation (ALFF) (0.01–0.08 Hz) (Biswal et al., 1995; Zang et al., 2007) values were computed using RESTplus. For T2-weighted images, voxel-based morphometry (VBM) (Ashburner and Friston, 2000) was performed using PCNN for skull stripping, ITK-SNAP for manual mask correction, and SPM for segmentation and normalization. Images were smoothed with an 8 mm Gaussian kernel. Group comparisons were conducted using two-sample t-tests (FDR <0.01), and results were visualized with xjView and MRIcron.

2.7. Flow cytometry and O4+ cell sorting

All procedures were performed on ice, and the interval between tissue isolation and data acquisition was kept within 1.5 h. Brains were collected from P1–P11 rats (males only for > P7) after PBS perfusion. The olfactory bulb and cerebellum were removed, and the meninges were carefully stripped. Tissues were dissociated using the Neonatal Brain Dissociation Kit (RWD, China) according to the manufacturer's instructions. The resulting cell suspension was passed through a 70-μm strainer, centrifuged (500×g, 5 min), and resuspended in HBSS at 5 × 106 cells/mL. Cells were incubated with rat Fc-block (1 μL, 10 min, 4 °C), followed by staining with O4–AF405 (2 μL) and PDGFRα–AF647 (1 μL) for 15 min at 4 °C in the dark. After washing, cells were labeled with Annexin V–FITC and propidium iodide (PI) in 1 × Annexin V binding buffer to assess apoptosis. Flow cytometric analysis was performed on a BD FACSAria™ III system, with compensation calibrated using single-stained controls. For cell sorting, O4+ cells were isolated under sterile, low-pressure conditions using a 100-μm nozzle and collected for downstream RNA extraction and sequencing.

2.8. RNA-seq and analysis

For bulk RNA-seq, telencephalic tissues were collected from P11 rats as described previously. Total RNA was extracted using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer's instructions. For Low-input RNA-seq, O4+ cells were isolated by fluorescence-activated cell sorting. Total RNA was extracted using a column-based RNA purification kit (Animal Tissue RNA Purification Kit, TRK1002, LC Bio Technology Co., Ltd., Hangzhou, China). cDNA synthesis and amplification were then performed using a SMART-seq–based protocol.

Library construction and sequencing for all samples were performed by LC Bio Technology Co., Ltd. (Hangzhou, China). The amplified cDNA was fragmented using dsDNA Fragmentase (NEB, M0348S) at 37 °C for 30 min. Sequencing libraries were then generated following standard workflows, including end repair, A-tailing, ligation of indexed adapters, and PCR amplification. RNA libraries were sequenced on an Illumina NovaSeq 6000 platform to generate paired-end reads, which were filtered using Cutadapt (v1.9) to remove adapters and low-quality reads, followed by quality assessment with FastQC (v0.11.9). Clean reads were aligned to the reference genome using HISAT2 (v2.0.4), transcripts were assembled and quantified with StringTie (v1.3.4d) and gffcompare (v0.9.8), and differential gene expression analysis was performed using edgeR, and P values were adjusted for multiple testing using the Benjamini–Hochberg method (Benjamini and Hochberg, 2018). Genes with a false discovery rate (FDR) < 0.05 and |fold change| >2 were considered significantly differentially expressed. GO and KEGG pathway enrichment analyses were subsequently performed. Two online platforms (https://www.bioinformatics.com.cn (Tang et al., 2023), https://www.omicstudio.cn/tool) were used to visualize results.

2.9. RT-qPCR

Total RNA was extracted from RNAlater-preserved tissues using TRIzol (Invitrogen). Briefly, tissues were homogenized in 1 mL TRIzol, phase-separated with chloroform, and centrifuged at 12,000×g, 4 °C for 15 min. The aqueous phase was precipitated with isopropanol, washed with 75% ethanol, air-dried, and dissolved in RNase-free water. RNA quantity and purity were assessed using a Nanophotometer (IMPLEN), and samples with A260/A280 ≈ 2.0 were used. For cDNA synthesis, 1 μg RNA was reverse-transcribed using PrimeScript RT Master Mix (Takara, RR036A) according to the manufacturer's protocol. RT-qPCR was performed using TB Green Premix Ex TaqII (Takara) in 10-μL reactions containing 0.4 μM primers, ROX reference dye, and 1 μL cDNA, run in duplicate. Gene expression levels were calculated using the 2ˆ-ΔΔCt method with GAPDH as the internal control.

2.10. Statistics

All data are presented as mean ± SEM unless otherwise specified. Comparisons between two groups were performed using an unpaired two-tailed Student's t-test. For comparisons among three groups, one-way ANOVA followed by Tukey's post-hoc test was used to determine statistical significance. For data involving repeated measurements across time and multiple treatment groups, a mixed-effects model (REML) was used with time as the within-subject factor and treatment group as the between-subject factor. When the assumption of sphericity was violated, the Geisser–Greenhouse correction was applied to adjust degrees of freedom. When significant main effects were detected, Šídák's multiple comparisons test was performed to evaluate pairwise differences at each time point. For experiments involving independent samples across multiple time points, data were analyzed using two-way ANOVA, followed by Šídák's multiple comparisons test at each time point. Detailed statistical methods and values are provided in Table S2. All statistical analyses were conducted using GraphPad Prism (v8.3.0). A p-value <0.05 was considered statistically significant.

3. Results

3.1. Late-gestational LPS exposure combined with postnatal hypoxia impairs myelination

A dual-hit rat model was established as illustrated in Fig. 1A. Maternal LPS administration induced preterm delivery approximately one day earlier than in control dams (Fig. S1A) and significantly reduced the number of live pups (Fig. S1B). During hypoxia exposure, neonatal rats exhibited transient abnormal behaviors, including agitation, tail clamping, and rightward circling, followed by reduced spontaneous activity, limb tremors, and cyanosis. These symptoms gradually resolved after return to normoxic conditions. Postnatal body-weight gain did not differ significantly among groups (Fig. S1C).

Fig. 1.

Fig. 1

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Late-gestational LPS exposure combined with postnatal hypoxia impairs myelination. (A) Experimental paradigm. (B) Immunofluorescence staining for MBP in the cortex at P11 and 8 weeks of age (n = 3 per group). (C) Quantification of MBP fluorescence intensity shown in (B). (D) Immunofluorescence staining for MBP and NF200 in the cortex and corpus callosum at 4 weeks of age. The schematic on the right shows the selected field of view. (n = 3-4 per group). (E) Quantification of MBP and NF200 fluorescence intensity shown in (D). (F) Representative transmission electron microscopy (TEM) images of the corpus callosum. (G) Regression analysis of G-ratio according to axon diameter. G-ratio is defined as the ratio of the inner axonal diameter to the total outer diameter (n = 3 per group). For all immunofluorescence experiments, 5 fields of view were randomly selected within the target area for each sample, and the final data for each sample were generated by averaging the data from these 5 fields of view. Data were presented as mean ± SEM. ∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001.

Immunofluorescence staining for myelin basic protein (MBP) revealed a marked reduction in cortical MBP intensity at P11 in the LPS + hypoxia group compared with controls, despite the overall low level of myelination at this early developmental stage (Fig. 1B and C). At 4 weeks of age, MBP expression in both the cortex and corpus callosum remained significantly decreased in the LPS + hypoxia group (Fig. 1D and E), indicating a sustained impairment. Consistent with these findings, transmission electron microscopy (TEM) at 4 weeks revealed thinner myelin sheaths in the LPS + hypoxia group than in both the Control and LPS-only groups (Fig. 1F and G), further confirming disrupted myelin development following the dual-hit insult. However, at 8 weeks of age, myelination levels appeared comparable among groups (Fig. 1B and C), suggesting a catch-up of myelination at later developmental stages.

3.2. Dual-hit exposure amplifies transcriptional deficits in myelination

To assess early transcriptional alterations, RNA-seq was performed on forebrain tissue collected at P11. Principal component analysis (PCA) revealed a markedly greater separation between the LPS + hypoxia and Control groups than between the LPS-only and Control groups (Fig. 2A), indicating a stronger global transcriptomic impact following hypoxia exposure. Differentially expressed genes (DEGs) identified in the LPS versus Control comparison (Fig. S2A) were enriched in GO terms such as neuron differentiation, sequence-specific DNA binding, and DNA-binding transcription factor activity (Fig. 2B), with enriched pathways primarily involved in synaptic regulation (Fig. S2C and D).

Fig. 2.

Fig. 2

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Dual-hit exposure amplifies transcriptional deficits in myelination at P11. (A) Two-dimensional principal component analysis (PCA) of RNA-seq data, n=6 per group. (B) Gene Ontology (GO) enrichment analysis of differentially expressed genes (DEGs) between the LPS and Control groups, displaying the top 20 enriched GO terms. (C) GO enrichment analysis of DEGs between the LPS + hypoxia and Control groups, showing the top 20 enriched GO terms. (D) Circular plot illustrating significantly enriched GO terms (LPS + hypoxia vs Control) related to myelination and oxygen transport, along with their associated DEGs. (E) KEGG pathway enrichment analysis of DEGs (LPS + hypoxia vs Control), presenting the top 20 enriched pathways. (F) cnet plot showing significantly enriched KEGG pathways (LPS + hypoxia vs Control) related to myelin lipid biosynthesis and synaptic function, together with the corresponding DEGs. (G) RT–qPCR validation of the relative expression level of selected oligodendrocyte lineage markers. Data were presented as mean ± SEM. ∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001.

In contrast, DEGs identified in the LPS + hypoxia versus Control comparison (Fig. S2B) were strongly enriched for GO terms directly associated with myelin structure and formation, many of which exhibited high rich factors (Fig. 2C). Key myelin-associated genes—including Mbp, myelin-associated oligodendrocyte basic protein (Mobp), proteolipid protein 1 (Plp1), and myelin-associated glycoprotein (Mag)—were all significantly downregulated in the LPS + hypoxia group (Fig. 2D). Moreover, enzymes essential for myelin lipid synthesis, such as UDP glycosyltransferase 8 (Ugt8), also showed marked reductions in expression. In addition, oxygen transport–related GO terms were significantly enriched, driven by the upregulation of hemoglobin subunit genes in the LPS + hypoxia group, reflecting a hypoxic transcriptional response (Fig. 2D). KEGG pathway enrichment analysis further supported the impairment of myelin lipid biosynthesis. The most significantly enriched pathway in the LPS + hypoxia versus Control comparison was ether lipid metabolism, which includes Ugt8 as a key DEG. KEGG results also revealed broad transcriptional disruption of genes involved in sphingolipid synthesis, along with alterations in multiple synapse-related pathways (Fig. 2E and F).

Finally, RT–qPCR of oligodendrocyte lineage markers confirmed these transcriptomic findings. Expression of OPC markers (Pdgfra, Cspg4 (encoding NG2)) did not differ significantly between groups, whereas mature oligodendrocyte–associated genes (Mbp, Mog, Plp1, Ugt8) were markedly reduced in the LPS + hypoxia group (Fig. 2G), consistent with impaired myelination programs identified by RNA-seq. Notably, although immunofluorescence analysis at P11 showed no significant difference in MBP protein levels between the LPS and Control groups (Fig. 1B and C), RT–qPCR revealed that Mbp mRNA expression was already altered at this stage.

3.3. Long-term behavioral and hippocampal circuit abnormalities after early-life insults

To comprehensively evaluate long-term behavioral and brain structural and functional alterations in the dual-hit model, we first conducted a series of behavioral tests. In the open-field test, both total distance traveled and time spent in the central zone were significantly reduced in the LPS and LPS + hypoxia groups compared with controls, indicating decreased locomotor activity and increased anxiety-like behavior (Fig. 3A and B). The elevated plus-maze test further showed that both LPS-treated groups spent less time in the open arms and made fewer open-arm entries (Fig. 3C and D), supporting heightened anxiety-like behavior. In the rotarod test, the Control and LPS-only groups remained on the rod longer than the LPS + hypoxia group, indicating impaired motor coordination and balance following the dual-hit insult (Fig. 3E). Spatial learning and memory were assessed using the Morris water maze. During the training phase, the LPS + hypoxia group required significantly more time to locate the hidden platform than control rats on days 4 and 5 (Fig. 3F). In the probe trial (day 6), both LPS-treated groups spent less time in the target quadrant compared with controls (Fig. 3G and H), indicating impaired spatial memory. Consistently, the novel object recognition test showed both LPS-treated groups exhibited a weaker preference for the novel object, indicating impaired recognition memory (Fig. S3A and B).

Fig. 3.

Fig. 3

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Long-term behavioral and hippocampal circuit abnormalities after early-life insults. (A) Representative trajectories of the open-field test. (B) Quantification of total distance traveled and time spent in the center zone in the open-field test shown in(A). (C) Representative heatmap of the elevated plus maze test, warmer colors indicate longer time spent in the area. (D) Quantification of time spent in the open arms and the number of open-arm entries shown in (C). (E) Quantification of the latency to fall from the rod in the rotarod test. (F) Escape latency over five consecutive days of training to locate the hidden platform, ∗ or ∗∗ indicates the difference between LPS + hypoxia and control group is significantly different, no significant difference was observed between LPS and Control group at all five consecutive days. (G) Heatmap of the probe trial on day 6, warmer colors indicate longer time spent in the area. (H) Quantification of time spent in the target quadrant during the probe trial shown in (G). For all behavioral tests, nControl = 16, nLPS = 21, nLPS + hypoxia = 21. (I) Resting-state fMRI (rs-fMRI) analysis. Three clusters showing significant differences in global mean ALFF (mALFF) between the LPS + hypoxia and Control groups are highlighted in red. (J) Voxel-based morphometry (VBM) of T2-weighted images. The left panel shows a schematic diagram of gray matter segmentation. A cluster showing significantly decreased gray matter volume (GMV) in the LPS + hypoxia group is highlighted in red. (K) Summary of clusters with significant differences, “regions mainly involved” indicates that more than one-third of the voxels were located within the specified brain region. Dentate gyrus, DG; Cornu ammonis, CA. For all MRI analyses, significance threshold: P < 0.001,n = 6 per group. (L) Representative images of the number of SYN1-positive puncta in the hippocampal CA3 region (n = 5 per group). Images were acquired using a 60 × oil-immersion objective. (M) Quantification of SYN1-positive puncta shown in (L). Data were presented as mean ± SEM. ∗∗P < 0.01, ∗∗∗P < 0.001, ∗∗∗∗P < 0.0001. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

We next applied multimodal MRI to evaluate alterations in gray matter volume and functional connectivity. Rs-fMRI at 8 weeks of age identified three brain clusters showing significant differences in global mean ALFF (mALFF) between the LPS + hypoxia and Control groups (Fig. 3I). Regions with reduced mALFF in the LPS + hypoxia group were primarily located in the bilateral dentate gyrus (DG) and cornu ammonis 3 (CA3) of the hippocampus, regions essential for memory encoding and information processing (Lisman et al., 2017). VBM further revealed significantly decreased gray matter volume (GMV) in the left CA3 region in the LPS + hypoxia group (Fig. 3J), suggesting impaired hippocampal gray matter development. Detailed information of the clusters with significant differences in mALFF and GMV is shown in Fig. 3K.

To further evaluate synaptic development in the CA3 region, where both mALFF and GMV changes were observed, we co-labeled Synapsin-1 (SYN1) and Microtubule-Associated Protein 2 (MAP2). The LPS + hypoxia group exhibited markedly fewer SYN1-positive puncta in the CA3 region than controls (Fig. 3L and M), indicating reduced synapse density, which may underlie the memory impairments observed in the behavioral assays.

3.4. Immature OL loss during a critical developmental window precedes delayed myelination

To investigate the reason for delayed myelination, we performed in situ CC1 staining, which revealed a marked reduction in mature OLs at P11 in the LPS + hypoxia group (Fig. 4A and B), indicating impaired OL lineage maturation. Given the spatiotemporal heterogeneity of brain development, we next used flow cytometry to dynamically track whole-brain OL lineage progression from P1 to P11 (Fig. 4C). The gating strategy is shown in Fig. S4A–C. Because maternal LPS exposure resulted in delivery approximately 1 day earlier, samples from the LPS + hypoxia group were collected based on corrected post-conceptional age to ensure developmental stage matching. At actual P1, maternal LPS exposure markedly reduced OPC numbers, and their proportion did not recover at corrected P1 (Fig. S4D). At this stage, immature OLs were scarce across groups (Fig. S4E).

Fig. 4.

Fig. 4

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Immature OL loss during a critical developmental window precedes delayed myelination. (A) Number of CC1-positive cells in the corpus callosum at the standard hippocampal level (n = 3 per group). (B) Quantification of CC1-positive cells shown in (A). (C) Flow cytometric gating strategy. (D, E) Dynamic changes in the proportions and viability of OPCs from P1 to P11. (F, G) Dynamic changes in the proportions and viability of immature OLs from P1 to P11. (H) Annexin V/propidium iodide (PI) staining of immature OLs at P9. For flow cytometric analyses, n = 6–14 per group per time point. Data are presented as mean ± SEM. ∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001,∗∗∗∗P < 0.0001.

As shown in Fig. 4D and E, at P1, offspring from LPS-treated dams exhibited significantly reduced OPC numbers and viability, indicating that prenatal LPS induced early OPC loss. At P3, the OPC proportion increased in the LPS + hypoxia group, likely reflecting compensatory proliferation aimed at restoring homeostasis (Hughes et al., 2013). From P5–P11, OPC proportions remained relatively stable between groups, except for a modest decrease in viability at P9 and P11.

In contrast, immature OLs exhibited more pronounced alterations across this developmental window (Fig. 4F and G). Although their abundance was low at P1, increased cell death was evident in the LPS + hypoxia group. From P3 to P7, the proportion of immature OLs gradually increased in both groups but remained consistently lower in the LPS + hypoxia group. Notably, a critical “switch point” emerged at P9. In control rats, immature OLs predominantly progressed toward maturation, leading to reduced O4 antigenicity (Barateiro et al., 2016; Flores-Obando et al., 2018), and a corresponding decline in the O4+ population. In contrast, the LPS + hypoxia group exhibited extensive immature OL death at P9 (Fig. 4H), indicating heightened vulnerability during this key transition stage of OL lineage progression.

3.5. Transcriptomic profiling reveals inflammatory reprogramming of immature OLs after dual-hit exposure

To characterize transcriptional changes in immature OLs following dual-hit exposure, we performed RNA sequencing on O4+ immature OLs isolated at P9 (Fig. 5A). Gene expression density plots showed comparable distributions of FPKM values across samples, indicating consistent sequencing depth and data quality (Fig. 5B). PCA showed clear separation between groups, demonstrating substantial global transcriptomic differences in immature OLs after dual-hit exposure (Fig. 5C).

Fig. 5.

Fig. 5

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Transcriptomic profiling reveals inflammatory reprogramming of immature OLs after dual-hit exposure. (A) Schematic overview of the low-input RNA-seq performed on FACS-isolated immature OLs. (B) Density plots showing the distribution of FPKM values across samples. (C) Two-dimensional PCA of transcriptomic profiles. (D) GO enrichment analysis of DEGs in immature OLs, showing the top 20 enriched GO terms. Red arrows highlight GO terms associated with myelination and oligodendrocyte/neural development. (E) Circos plot depicting DEGs associated with enriched GO terms related to myelination and inflammatory processes. (F) KEGG pathway enrichment analysis of DEGs in immature OLs. The top 20 enriched pathways are shown. Red arrows indicate inflammation-related pathways. (G) cnet plot showing DEGs contributing to inflammation-associated KEGG pathways. (H) cnet plot showing DEGs contributing to KEGG pathways associated with myelin lipid biogenesis. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Among the top 100 DEGs (Fig. S5A), key regulators of OL maturation and myelin formation were markedly downregulated (blue arrows), whereas inflammatory mediators, including Il1b, Ccl7, and Cxcl10, were strongly upregulated in the LPS + hypoxia group. Interestingly, the expression of inhibitory regulators is also increased (e.g., Nfkbia, Il1r2), suggesting concurrent engagement of negative feedback mechanisms that restrain inflammation. GO enrichment analysis of DEGs revealed significant enrichment of biological processes related to myelination and oligodendrocyte differentiation (Fig. 5D). In parallel, multiple inflammation-related GO terms were also significantly enriched, largely driven by genes such as Il1b, Ccl7, Cxcl10, and Mapk7 (Fig. 5E). Pathway analysis further demonstrated enrichment of TNF signaling, IL-17 signaling, Toll-like receptor signaling, and cytosolic DNA–sensing pathways (Fig. 5F), indicating activation of inflammatory signaling programs within immature OLs. The key genes contributing to these significantly enriched inflammation-related pathways are shown in Fig. 5G. In parallel, a distinct set of DEGs drives the enrichment of pathways involved in myelin lipid biogenesis (Fig. 5H).

Collectively, these transcriptomic data indicate that perinatal inflammation and hypoxia not only lead to the death of immature OLs but also reprogram the surviving cells toward an immune-responsive phenotype, providing a potential mechanistic basis for impaired myelination.

4. Discussion

Pre-OLs are the primary cellular targets in preterm WMI, yet how combined perinatal insults shape OL lineage fate during this vulnerable window remains incompletely understood. In this study, we established a dual-hit model combining prenatal LPS exposure with postnatal intermittent hypoxia, which resulted in delayed myelination and persistent brain structural and functional alterations. Through dynamic tracking of OL lineage progression, we identified a pronounced surge of pre-OL death at P9. Transcriptomic profiling of O4+ pre-OLs at P9 revealed activation of inflammatory signaling pathways and suppression of myelination-associated programs. Together, these findings support a model in which early pre-OL loss, coupled with inflammatory reprogramming, impairs myelination.

Inflammation and hypoxia frequently coexist in preterm infants and represent major risk factors for WMI (Volpe, 2009). Inflammation at the feto-maternal interface contributes to a substantial fraction of preterm births (Humberg et al., 2020), and LPS-based chorioamnionitis models recapitulate long-term neural functional abnormalities in offspring (Jantzie and Robinson, 2015). Hypoxia is likewise clinically relevant, as immature cerebrovascular autoregulation and respiratory instability increase postnatal hypoxic exposure (Volpe, 2009, 2019). Consistent with prior reports, prenatal LPS alone caused behavioral changes (Oskvig et al., 2012; Fernández de Cossío et al., 2017) but only modest alterations in myelination in our study, whereas combined LPS exposure and hypoxia led to a pronounced delay in myelination, supporting the concept that compounded insults exert greater effects on white matter development.

Our data show that myelination catches up by 8 weeks, whereas behavioral changes persist, indicating that transient early myelination disruption can leave lasting functional changes. Beyond accelerating conduction, myelin supports axonal metabolism (Shimizu et al., 2018) and promotes angiogenesis (Yuen et al., 2014). Therefore, early myelination deficits may disrupt axonal maturation and neuronal migration, resulting in enduring alterations in brain function (Volpe, 2009; Pujol et al., 2004; Wehrle et al., 2018; Smyser et al., 2019). Interestingly, behavioral outcomes showed a domain-specific dissociation following single-versus double-hit insults. In the Morris water maze, probe trial performance was comparable between LPS and LPS + hypoxia groups, whereas acquisition latency was increased only in the dual-hit group, indicating a selective impairment in spatial learning efficiency rather than memory retention, which reflect distinct aspects of hippocampus-dependent cognition (Othman et al., 2022). Anxiety-like behavior, assessed by the open field and elevated plus maze, was similarly affected by prenatal LPS alone, suggesting that emotional circuits are primarily sensitive to prenatal inflammation. This indicates that amygdala–hippocampus–prefrontal networks (La-Vu et al., 2020) are vulnerable to perinatal inflammatory perturbations, where maternal inflammation can alter neuronal excitability and synaptic function, leading to persistent behavioral abnormalities (Cismaru et al., 2016). In contrast, rotarod performance showed a graded deficit, with the most pronounced impairment in the dual-hit group, indicating an additional impact of postnatal hypoxia on motor coordination. This effect may reflect increased vulnerability of cerebellar and sensorimotor pathways, which depend on intact white matter connectivity and are known to be susceptible to early hypoxic injury (Biran et al., 2011; Sathyanesan et al., 2018). Together, these findings indicate that prenatal inflammation and postnatal hypoxia differentially affect behavioral domains, with emotional and memory-related processes being sensitive to prenatal inflammation, and spatial learning and motor coordination showing additional vulnerability in the context of delayed myelination.

Consistent with the behavioral results, multimodal MRI revealed reduced hippocampal mALFF and GMV in the LPS + hypoxia group, indicating persistent abnormalities in regional development and intrinsic activity (Zhu et al., 2022) despite myelination recovery. Given the presence of a default mode network-like organization in rats (Lu et al., 2012), future studies may assess whether hippocampal structural changes co-evolve with network hypoconnectivity.

Central nervous system myelination is a stepwise, regionally orchestrated developmental program. Neural stem cells generate OPCs under lineage-defining transcription factors (e.g., Olig1/2, Sox10, Nkx2.2) (Richardson et al., 2006). OPCs migrate along the vasculature while maintaining a self-renewing pool (Calver et al., 1998; Nishiyama et al., 2021; Tsai et al., 2016). As development progresses, a subset of OPCs exit the cell cycle and differentiate into pre-myelinating and mature OLs that express myelin structural proteins (Emery, 2010). Importantly, preterm birth coincides with the vulnerable window of OL lineage development. Although OLs have long been viewed as “victims” of inflammatory injury, recent studies in multiple sclerosis and neurodegenerative disorders have identified subsets of immature OLs that express inflammation-related genes (e.g., IL-1β, IL-6) (Kirby and Castelo-Branco, 2021; Jäkel et al., 2019; Falcão et al., 2018; Kenigsbuch et al., 2022). These immune-responsive states can be induced by cytokines such as TNF, IFN-γ, and IL-17 (Wang et al., 2017; Kirby et al., 2019), are associated with reduced myelination capacity and may reinforce neuroinflammation through crosstalk with microglia and astrocytes (Wang et al., 2017; Desu et al., 2021). Consistent with this framework, transcriptomic profiling of O4+ pre-OLs in our model showed robust upregulation of inflammatory mediators (e.g., Il1b, Ccl7, Cxcl10) and enrichment of TNF, IL-17, Toll-like receptor, and cytosolic DNA-sensing pathways, accompanied by suppression of myelination-associated genes.

Mechanistically, inflammation-related pre-OLs are active participants rather than passive bystanders. Following inflammatory reprogramming, the canonical myelination functions of pre-OLs are suppressed, while their interactions with microglia, macrophages, and T cells are enhanced, thereby amplifying inflammatory signaling and further impairing myelination. Prior work suggests inflammation-related pre-OLs can express IL-1β and CCL2 to promote chemotaxis toward inflammatory sites (Moyon et al., 2015), upregulate pattern recognition receptors (PRRs) and engage innate immune signaling (Bsibsi et al., 2012). In addition, they can secrete chemokines (e.g., CCL7 (Wang et al., 2017) and CXCL1/2/3/8 (Parthasarathy and Philipp, 2017)) to recruit activated T cells, B cells, and NK cells, and produce pro-inflammatory cytokines, including IL-1β (Moyon et al., 2015), IL-6 (Ramesh et al., 2012), IL-17 (Tzartos et al., 2008), thereby amplifying inflammatory circuits that can further compromise myelination (Hirano, 2021; McGeachy et al., 2019). Extending these observations to preterm WMI, our data indicate that a similar immune-responsive OL population emerges in a developmental context and may link neuroinflammation to delayed myelination. However, whether inflammation-related pre-OLs in the neonatal brain are functionally equivalent to those described in aging, multiple sclerosis, and other diseases remains an important open question. Given the heightened plasticity of neonatal pre-OLs, inflammation-associated states may represent transient developmental adaptations rather than sustained immune-like phenotypes seen in the mature brain, underscoring the need for temporally resolved single-cell and functional analyses across developmental and disease settings.

Several limitations of this study should be acknowledged. First, a hypoxia-only group was not included, which limits our ability to fully disentangle the independent effects of postnatal hypoxia from prenatal inflammation. Although our model was designed to capture their combined impact in a clinically relevant context, a hypoxia-only group will be helpful to define the relative contribution of each insult more precisely. Second, only male offspring were included, limiting the assessment of sex-dependent differences in susceptibility and response. Although males are considered more vulnerable to adverse neurodevelopmental outcomes, the absence of female subjects precludes direct evaluation of sex-specific mechanisms. Third, the mechanisms driving inflammatory reprogramming of immature OLs remain unresolved. Our findings raise the possibility that extensive pre-OL death reshapes the local immune and extracellular-matrix microenvironment, while previous studies suggest that peripheral inflammation may directly reprogram immature OLs. For example, in multiple sclerosis, activated Th1 and Th17 cells infiltrate the central nervous system through a compromised blood–brain barrier and secrete cytokines such as IFN-γ, IL-17, and TNF, which are known to drive fate changes in pre-OLs (Wang et al., 2017; Kirby et al., 2019; Angelini et al., 2023). However, whether similar mechanisms predominate in the developing brain after perinatal inflammation and hypoxia remains unclear. Addressing these questions will help advance our understanding of disrupted oligodendrocyte lineage maturation and impaired myelination in preterm white matter injury.

5. Conclusion

This study established a dual-hit model of preterm brain injury characterized by impaired myelination and persistent behavioral and brain structural and functional alterations. The loss and inflammatory reprogramming of immature OLs emerge as potential drivers of preterm brain injury.

Ethics approval statement

All animal procedures were approved by the Animal Ethics Committee of Chongqing Medical University.

Funding statement

This work was supported by the National Key Research and Development Program of China (2022YFC2704802).

CRediT authorship contribution statement

Xueling Ma: Conceptualization, Data curation, Formal analysis, Investigation, Writing – original draft. Wen Jia: Data curation, Investigation. Xingdao Zhang: Data curation, Investigation. Yuan Shi: Funding acquisition, Supervision, Writing – review & editing.

Declaration of competing interest

The authors declare no conflicts of interest. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

We are grateful to Dr. Xiaojin Luan for sharing her expertise in primary cell isolation by flow cytometry, to Dr. Yu Guo for his assistance with the rat MRI, and to the Electron Microscopy Core Facility of Chongqing Medical University for their support. We are grateful to LC Bio Technology CO.,Ltd for assisting with sequencing. This work is supported by the National Key Research and Development Program of China (2022YFC2704802).

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.bbih.2026.101253.

Appendix A. Supplementary data

The following are the Supplementary data to this article:

Multimedia component 1
mmc1.docx (1.6MB, docx)
Multimedia component 2
mmc2.xlsx (13KB, xlsx)
Multimedia component 3
mmc3.xlsx (19.7KB, xlsx)

Data availability

The raw RNA-seq data generated in this study have been deposited in the NCBI Gene Expression Omnibus (GEO) database under accession number GSE331070. MRI data are available from the corresponding author upon reasonable request.

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Associated Data

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

Supplementary Materials

Multimedia component 1
mmc1.docx (1.6MB, docx)
Multimedia component 2
mmc2.xlsx (13KB, xlsx)
Multimedia component 3
mmc3.xlsx (19.7KB, xlsx)

Data Availability Statement

The raw RNA-seq data generated in this study have been deposited in the NCBI Gene Expression Omnibus (GEO) database under accession number GSE331070. MRI data are available from the corresponding author upon reasonable request.

Articles from Brain, Behavior, & Immunity - Health are provided here courtesy of Elsevier

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