Chronic intermittent hypoxia exposure induces a unique microglial transcriptome in 5XFAD mice

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Marino, Andrea C. Ewald, Jaidynne N. Lash, Erin C. McCann, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6203482/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Nov, 2025 Read the published version in Molecular Neurobiology → Version 1 posted 10 You are reading this latest preprint version Abstract Clinical observations suggest that obstructive sleep apnea (OSA) and Alzheimer’s disease (AD) pathology may be linked; however, causal mechanisms and relationships are unclear. To investigate the potential interaction between amyloidosis and intermittent hypoxia (IH), a hallmark of OSA, starting at 4-months of age 5XFAD mice were exposed to chronic IH (CIH) consisting of 20 episodes per hour of hypoxia for 12 hours/day, daily for 4- (males) or 6-months (females). CIH did not induce significant changes in amyloid burden or the number of astrocytes in males or females, but there was a slight decrease in the number of microglia observed in the cortex of 5XFAD mice of both sexes. To further explore this effect, we performed bulk RNA sequencing on isolated microglia. In WT mice, the most robust gene changes induced by CIH were identified in male microglia, many of which were pro-inflammatory. In microglia from 5XFAD mice, compared to NX, CIH exposure induced comparatively more DEGs in males. Further, in genes that were upregulated by CIH in WT vs 5XFAD mice of both sexes, there was an enrichment of pathways associated with oxidative phosphorylation, aerobic and cellular respiration, and ATP synthesis. These changes indicate that CIH has a more robust effect on the microglial transcriptome in 5XFAD mice than in WT mice, suggesting that the synergy between AD and OSA pathologies may be driven by metabolic changes in the microglial transcriptome. These observations are particularly interesting given the known sex differences in OSA and AD pathology in human disease. neuroinflammation intermittent hypoxia microglia amyloid Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction As the world’s population ages, identifying and leveraging known risk factors associated with cognitive decline are of increasing importance as they could lessen the significant financial, medical, and caregiver strains on society. Targeting chronic diseases that can become a co-morbidity to diseases of aging, like Alzheimer’s disease (AD) and related dementias, later in life may acutely improve patient health and modulate disease severity or onset. One of these potential co-morbidities is obstructive sleep apnea (OSA), which affects an estimated 1 billion people worldwide [ 1 ]. OSA is a form of sleep disordered breathing in which the airway is partially or completely blocked multiple times per hour during sleep, resulting in periods of intermittent hypoxia, hypercapnia, and sleep fragmentation [ 2 ]. Untreated, OSA can result in daytime sleepiness, fatigue, and diminished cognition [ 3 , 4 ]. The primary treatment for OSA is the use of a continuous positive airway pressure (CPAP) device, worn during sleep, that keeps the airway open to help regulate blood gases. CPAP is effective in reducing symptoms and improving perceived health-related quality of life, but there is no evidence of significantly improved cognition in those with mild to moderate OSA [ 5 – 9 ]. CPAP is only effective, however, if individuals are willing to use it, but only an estimated 30–60% of patients reliably use their CPAP devices, despite recent advances that make the equipment more comfortable and user friendly [ 10 – 12 ]. Neuroimaging studies have been used to probe the impact of OSA symptomology on brain structure. OSA correlates with thickening of several grey matter areas, and can be stratified by the primary symptom type (hypoxia vs sleep disturbance) [ 13 – 15 ]. Also, white matter changes and reduced attention are exacerbated in individuals over 60 years old with severe OSA [ 16 , 17 ]. Correlations between OSA and dementia have been identified [ 18 , 19 ], so there is increasing interest in OSA as a potential contributor to neurodegenerative disorders, including AD [ 20 , 21 ]. AD is a progressive disease thought to be driven by amyloid β (Aβ) plaque deposition, thought to begin decades prior to symptom onset, and the formation of neurofibrillary tau tangles (NFTs) [ 22 ]. A recent meta-analysis found that OSA was associated with elevated AD biomarkers in both the blood (total amyloid, Aβ 40 , Aβ 42 , and total tau) and cerebral spinal fluid (CSF) [ 23 ]. Recent lipidomic analyses have identified a unique signature in the CSF and blood of individuals with AD and severe comorbid OSA [ 24 , 25 ] that is thought to be mediated by hypoxia-mediated inflammation, although additional studies are needed to confirm this. Further, positron emission tomography (PET) neuroimaging shows increased levels of amyloid in individuals with OSA [ 26 ]. APOE ε4, a major genetic risk factor for AD, is a secondary risk factor for cognitive decline, which is exacerbated with worsening OSA severity [ 27 , 28 ]. Both OSA and AD cause neuroinflammation; while the mechanism for each pathology alone is thought to involve the activation of toll light receptor-4 (TLR4), the NACHT-, LRR-, and pyrin (PYD)-domain-containing protein 3 (NLRP3) inflammasome, ASC spec formation and astrocyte activation, the cellular interaction between these pathologies remains unclear [ 29 – 33 ]. Given the paucity of sufficiently powered human studies, and the large overlapping populations between AD and OSA, we and others have turned to mouse models to examine the intersection of these disorders. One study examined the synergism of these pathologies using 1 month of CIH exposure, and found increased markers of astrocyte activation in the APP/PS1 mouse model, another amyloid AD mouse model [ 34 ]. Here, we employed the 5XFAD mouse model of AD [ 35 ] which develops rapid accumulation of amyloid pathology, and we exposed males and females to CIH for 4 or 6 months, respectively, to investigate the long term effects of CIH on the glial response to amyloid pathology and disease burden. Materials and Methods Animal Care and Use Wildtype (WT) females (C57BL/6J; JAX Stock #000664) were crossed with 5XFAD [ 35 ] male mice obtained from the Mutant Mouse Resource and Research Center at JAX (B6SJL-Tg (APPSwFlLon, PSEN1*M146L*L286V)6799Vas/Mmjax; JAX Stock #034840) and group housed in the University of Wisconsin-Madison School of Veterinary Medicine vivarium according to UW-Madison IACUC approved protocols #V005173 and #M006091. Mice were maintained on a 12-hour light/12-hour dark cycle with food and water provided ad libitum. Animals were anesthetized and perfused with cold Phosphate Buffered Saline (PBS) before tissue preparation. Females were harvested at 10-months of age while males were harvested at 8-months of age due to increasingly aggressive behavior that prevented group housing beyond this time. Chronic intermittent hypoxia (CIH) Beginning at 4-months of age and until they reached the study endpoint, mice were exposed to intermittent hypoxia (IH) or room air (normoxia, NX) during their period presumptive sleep, as described previously [ 33 ]. IH was achieved by alternating inspired oxygen levels between 6% O 2 and 21% O 2 over 90 second intervals. Mice subjected to NX conditions were exposed to the same noise and airflow as IH exposed mice, but inspired O 2 levels oscillated between 21% and 21% O 2 . Microglia isolation As described previously [ 36 , 37 ], following cardiac perfusion, cerebral brain tissue was mechanically dissociated and placed in cold HBSS (Fisher #12-022-CM). Samples were then enzymatically digested with papain (from papaya latex, Sigma #P4762-500MG) and DNAse (Invitrogen #12185010) at 37°C, gravity fed through filters and myelin was separated from the cells using 26% percoll solution (Cytiva #17089101) and centrifuged at 2100 rpm, at 4°C for 15 minutes. The pellet was resuspended and incubated with anti-CD11b magnetic beads (Miltenyi Biotech #130-093-634) in IMAG (0.5% BSA and 2 mM EDTA in PBS) and run through primed magnetic columns (Miltenyi Biotech catalog #130-042-201). The isolated microglia were stored in TriZol (Invitrogen, 15596026) at -80°C. RNA isolation and sequencing analyses RNA isolation from n = 5 independent samples for each sex, genotype and treatment was performed per the manufacturer’s instructions (Invitrogen, 15596026). Total RNA was sent to Novogene USA for bulk mRNA sequencing (NovaSeq6000 PE150, Illumina) and was aligned to the GRCm38/mm10 mouse genome. As we have reported previously [ 38 ], gene count files were imported into R and genes with a CPM > 1 in 3 samples were included. Differential expression analysis was calculated between groups using EdgeR [ 39 ]. PCA plots were used to identify outliers (Fig S1 -2) One female normoxia sample was identified as an outlier in several comparisons. Statistically significant comparisons had a false discovery rate (FDR) 1. Gene ontology analyses were completed using the PANTHER Overrepresentation test [ 40 ] within the STRING analysis tool [ 41 ] using a high confidence (minimum required interaction score = 0.7); like GO terms are grouped at a similarity of 0.8. Tissue fixation and Immunofluorescence staining Following perfusion with cold PBS, tissue was fixed in 4% paraformaldehyde for 48 hours, rinsed with PBS, and sunk in 30% sucrose for 48 hours. Tissue was oriented and then frozen in a 2:1 30% sucrose/Tissue Tek OCT compound (Sakura #4583) solution and stored at -80°C. Brains were sectioned into 40 µm (Leica) sections and stored in cryoprotection buffer (30% ethylene glycol, 30% sucrose in PBS). Sections were selected, blocked in confocal blocking buffer (3% BSA, 0.15% Triton-X100 in PBS) for 1 hour and incubated with primary antibody to Iba-1 (Abcam ab5076; 1:1750) or GFAP (Alexa Fluor 488 Conjugated, Invitrogen 53-9892-82; 1:1000) overnight at 4°C. Floating sections were rinsed with PBS and incubated at room temperature with Alexa Fluor 488 Donkey anti-Goat secondary antibody (Abcam ab150129; 1:500), Methoxy-X04 (Tocris Biological #4920; 1:1000) and TO-PRO-3 (Thermo Fisher #T3605; 1:1000) in confocal blocking buffer. Sections were rinsed with PBS and mounted with Fluoromount G (SouthernBiotech, Cat. No. 0100-001) and #1 coverslips (Fisherbrand, Cat. No. 12541035) on superfrost slides (Fisherbrand Cat. No. 12-550-15). Confocal microscopy Immunofluorescent stained slides were imaged on a Nikon A1R + in the Optical Imaging Core at the University of Wisconsin-Madison. Images were obtained as Z-stack using a 20X objective (NA = 0.75) at a step depth of 0.7 µm. Imaris Analysis As described previously [ 42 ], confocal images were loaded into Imaris (Bitplane 9.5.1) for analysis. The Iba-1 or GFAP (microglia or astrocyte respectively) and TO-PRO-3 channels were colocalized, and used to obtain a cell count and spatial coordinates for cells in the 3-dimensional images using the “spots” function. Plaque analyses were completed by generating 3-dimensional surfaces of methoxy-X04 + plaques. The number of spots within 30 µm of all plaque surfaces in the image was then calculated. Plaque quantification in the cortex Tiled, single plane images of methoxy-X04 staining were obtained on a Zeiss Imager.M2 microscope and exported into ImageJ [ 43 ] as a TIFF file. Cortex ROIs were traced for each section. A percentile threshold (0.4% (females) or 0.5% (males)) and particulate size threshold of 100 pixels was used to quantify the percent area occupied by plaques. Statistics Males and females were analyzed separately for all experiments. Statistical analyses were completed in Graph Pad Prism (Dotmatics) with a significance threshold of p < 0.05 for two-tailed unpaired t-tests and 2-way ANOVAs. Tukey post-hoc comparison tests were used for multiple comparisons at the same significance threshold. ROUT testing was used to identify and remove outliers (Q = 1%). Results CIH decreases body mass in male 5XFAD mice but increases it in female 5XFAD mice Since metabolic dysfunction is associated with OSA and AD [ 1 , 44 – 47 ], we recorded weight at the study endpoint. Females were sacrificed at 10-months of age and males at 8-months. In females, CIH exposure significantly increased the weight of WT mice, whereas female normoxia-exposed 5XFAD mice weighed significantly less than their WT counterparts, as expected (2-way ANOVA, p < 0.0001, Fig. 1 A). Interestingly, CIH exposure tended to decrease the weight of 5XFAD females further, although this did not reach statistical significance ( p = 0.0898). In contrast, in males, CIH exposure significantly decreased body weight in both WT and 5XFAD mice (2-way ANOVA, p < 0.0001; Fig. 1 B), and there was no difference in body weight in NX-exposed WT and 5XFAD male mice at this age. Plaque number and size are unaffected by CIH in 8-month-old males and 10-month-old females Tissues were stained with methoxy-X04 to label β amyloid plaques and imaged in 2 ways: 1) a Z-stack image of a high-powered field (HPF) in the cortex, and 2) a large, single plane tiled image that encompassed the entirety of the cortex in that section. Images of the HPF were analyzed in Imaris (Bitplane) to quantify plaque number and characteristics. These analyses in 10-month-old female (Fig. 2 A) and 8-month-old male (Fig. 2 F) 5XFAD mice indicated no significant differences induced by CIH treatment either in the number of plaques present (Fig. 2 B, G) or their size (C, H) (Unpaired t -test, p > 0.05). The large tiled images (Fig. 2 D, I) were quantified in Image J and are reported as a percent of the cortex ROI (Fig. 2 E, J). Although not significant, there was a trend towards an increase in the total plaque area in the cortex of female 5XFAD mice that were exposed to CIH (Unpaired t -test, p = 0.1086), but this difference was not observed in males (Unpaired t -test, p > 0.05). CIH does not affect astrogliosis, but trends towards decreasing microgliosis with amyloid deposition in 5XFAD mice Gliosis is an integral component to AD pathology, so we quantified the number of astrocytes and microglia per HPF in the cortex. Reactive (GFAP + ) astrocytes were quantified in Imaris. Consistent with other reports [ 35 , 48 ], there was an increase in reactive astrocytes in the cortex of both male and female 5XFAD mice when compared to WT (Fig. 3 B, D; Two-way ANOVA with Tukey multiple comparisons, p < 0.0001). However, CIH did not change the number of reactive astrocytes in either male or female 5XFAD mice compared to the NX-exposed counterparts (females, p = 0.6937; males, p = 0.6877). The microglial response to amyloid deposition was quantified in the same manner. As expected, the 5XFAD genotype significantly increased microglia number in the cortex (Two-way ANOVA, p < 0.001), and this tended to be decreased by CIH exposure in both males and females, although it did not reach statistical significance (Two-way ANOVA, females, p = 0.0864; males, p = 0.0589; Fig. 4 C, E). Further, since microglia cluster around plaques, an additional analysis of their relative localization was performed. Despite the trends in the overall number of microglia in each sex, there was no significant difference in the localization of microglia in relation to plaques between NX- and CIH-exposed female (Unpaired t -test, p = 0.1632, Fig. 4 D) or male (Unpaired t -test, p = 0.2051, Fig. 4 F) 5XFAD mice. CIH drives transcriptional changes related to metabolism in microglia To investigate the transcriptional changes associated with CIH exposure in WT and 5XFAD mice, we performed bulk RNA sequencing analyses on immunomagnetically isolated microglia; differentially expressed genes (DEGs) were identified as those which had an FDR 1. The total number of significant DEGs for each comparison are shown in Tables 1 and 2 . Table 1 The number of significant DEGs in microglial RNA-seq data from female mice. Significant comparisons had an FDR 1 Comparison #Upregulated #Downregulated WT NX WT CIH 2 6 WT NX 5X NX 1050 963 WT CIH 5X CIH 1342 630 5X NX 5X CIH 2 7 Table 2 The number of significant DEGs in microglial RNA-seq data from male mice. Significant comparisons had an FDR 1 Comparison #Upregulated #Downregulated WT NX WT CIH 316 149 WT NX 5X NX 973 396 WT CIH 5X CIH 1779 1153 5X NX 5X CIH 1 0 We first analyzed the effect of genotype in microglia from NX-exposed females, by comparing WT and 5XFAD microglia (WT NX vs 5XFAD NX; Fig. 5 A). There were 2,013 significant DEGs; 1,050 were upregulated and 963 were downregulated (See supplemental file 1 for full gene list). These DEGs included genes that characterize disease associated microglia (DAM) [ 49 ], as well as pathways related to TREM2-APOE [ 50 ] and aging [ 51 ]. Next, we compared the effect of CIH on WT female microglia (WT NX vs WT CIH), and 8 genes were differentially expressed: LOC118568479 was the most upregulated gene (LFC = 3.84) and Erdr1_1 was the most downregulated (LFC= -3.28, Volcano plot, Fig. 5 B). Comparing the effect of CIH on microglia from 5XFAD females (5XFAD NX vs 5XFAD CIH), there were a total of 9 DEGs, 7 were upregulated. The most upregulated was Ptpn5 (LFC = 3.42), and of the 2 downregulated genes, the greatest change was in Rn7sk (LFC= -4.35) (Volcano plot, Fig. 5 C). We next assessed whether CIH had differential effects on microglia from WT females compared to 5XFAD females (WT CIH vs 5XFAD CIH; Fig. 5 D). There were over 1000 genes up- and down-regulated (See supplemental file 1 for full gene list), which like the normoxia comparison, were due primarily to the effect of the 5XFAD genotype and consistent with those reported by us and others [ 48 , 49 ]. To further examine the effect of CIH with respect to the microglial response to plaque pathology in female 5XFAD, we cross referenced the DEGs between the WT NX vs 5XFAD NX and WT CIH vs 5XFAD CIH comparisons (see Supplemental file 3). 1,442 genes were shared between the comparisons, 571 genes were specific to the WT NX vs 5XFAD NX comparison, and 530 genes were unique to the WT CIH vs 5XFAD CIH analysis (Fig. 5 E). We performed gene ontology (GO) analyses on the up- and down-regulated genes that were unique to each respective comparison. The DEGs that were uniquely downregulated in the WT NX vs 5XFAD NX comparison were most enriched for system development, multicellular organism development, and anatomical structure development, as well as circulatory system development and cell motility, migration, morphogenesis and adhesion (Fig. 5 F). The DEGs that were uniquely upregulated in the WT NX vs 5XFAD NX comparison included enrichment for the defense response, the innate immune response, and the response to interferon-β (Fig. 5 G). When we examined the DEGs that were unique to the WT CIH vs 5XFAD CIH comparison, no GO terms were identified for the downregulated genes. However, those that were uniquely upregulated in the WT CIH vs 5XFAD CIH comparison were significantly enriched for the GO terms associated with behavior and memory, regulation of cellular components, oxidative phosphorylation and precursor metabolite generation (Fig. 5 H). In all, the comparisons between the effect of genotype and each respective treatment highlights that CIH can influence processes associated with metabolism, learning and memory. We used the same analysis pipeline to examine the data from male microglia. The 5XFAD genotype had a significant effect on NX-exposed animals, with 973 genes being upregulated and 396 downregulated. These changes included the key genes associated with the 5XFAD genotype (Fig. 6 A; see supplemental file 2 for full gene list). We then analyzed the effect of CIH on microglia from WT animals. CIH had a more significant effect on WT male microglia than it did on WT female microglia. In WT males, a total of 465 genes were differentially expressed; 149 were downregulated and 316 were upregulated (Fig. 6 B). Those that were significantly decreased included the type-I interferon associated neuroinflammatory genes Cxcl10 (Log 2 FC= -1.20), Ccl5 (Log 2 FC= -1.18), Ifitm2 (Log 2 FC= -1.17), Ifitm3 (Log 2 FC= -1.25), and Ifitm6 (Log 2 FC= -1.60). The Xlr3a gene was the most upregulated (Log 2 FC = 4.76). Notably, several genes encoding solute and amino acid transporters were significantly upregulated (See supplemental file 2 for full gene list). We then compared the effect of the 5XFAD genotype on microglia from CIH-exposed males. In the comparison of CIH-exposed WT and 5XFAD mice, over 2900 genes were differentially expressed; 1,779 were upregulated and 1,153 were downregulated (Fig. 6 C), compared to less than 1400 genes that were differentially expressed due to the 5XFAD genotype in NX-exposed males (Fig. 6 A). CIH alone had little to no effect on the male 5XFAD microglial transcriptome compared to NX; only 1 gene ( tcap (Log2FC = 1.15) was differentially upregulated (Fig. 6 D). While the comparison of CIH-treated WT and 5XFAD mice still included the hallmark changes associated with the 5XFAD genotype, key DAM genes that were upregulated in 5XFAD NX mice were less upregulated upon CIH exposure, suggesting that CIH may dampen the DAM gene profile in the microglia of male 5XFAD mice. To further examine alterations to the DAM profile in males, we investigated the effect of the 5XFAD genotype in microglia from NX-exposed male WT and 5XFAD mice (Fig. 6 E, left) and the effect of CIH on male WT and 5XFAD mice by cross referencing all of the DEGs (up- and down-regulated) between these comparisons (Fig. 6 E). Surprisingly, 955 genes were shared between them, thought there were 1,965 genes unique to the WT CIH vs 5XFAD CIH comparison and 414 genes that were unique to the WT NX vs 5XFAD NX comparison (see Supplemental file 3). We analyzed these differences using a gene ontology (GO) enrichment analysis, and a summary of the top 10 significantly enriched pathways are presented in Figs. 6 F-H. None of the genes that were unique to the WT vs 5XFAD NX comparison were downregulated. However, the upregulated genes fell into categories associated with pathways involved in cell projection and neuron and axon development (Fig. 6 F). The genes that were uniquely decreased in microglia from the WT CIH vs 5XFAD CIH comparison were enriched for gene categories involved in locomotion, cellular metabolic processes, protein modification, catalytic activity, macromolecule biosynthesis, transcription and nitrogen compound metabolism (Fig. 6 G). Notably, the upregulated genes unique to the WT CIH vs 5XFAD CIH comparison were enriched for GO pathways associated with oxidative phosphorylation, aerobic and cellular respiration and ATP synthesis (Fig. 6 G). Together, comparisons between the effect of genotype and treatment highlight the idea that CIH treatment alters oxidative phosphorylation and cell respiration, among others, in 5XFAD microglia. Interestingly, the DEGs in 5XFAD microglia from the NX comparison, but not the CIH comparison, suggests that microtubule structure and microglial morphology may be more impacted by the 5XFAD genotype, although the significance of this requires additional investigation. Discussion There is a strong clinical correlation between AD and OSA. But despite high prevalence of both disorders, their relationship remains poorly understood. Insights into this interaction could be leveraged as an early intervention strategy to mitigate or lessen future cognitive decline. Accordingly, the goal of our experiments here was to study the effects of the CIH associated with sleep disordered breathing in an animal model of early amyloid pathology. We initiated CIH exposure at 4-months of age, an early stage of pathology in the 5XFAD mouse model, and continued it daily until sacrifice. As we expected, we found that CIH exposure reduced body weight in 5XFAD male and female mice. In contrast to our initial hypothesis, however, the combination of amyloid pathology and CIH did not significantly alter amyloid plaque deposition (Fig. 2 ), nor the number of astrocytes (Fig. 3 ) or microglia (Fig. 4 ) in the cortex. CIH also did not alter the way microglia clustered around amyloid plaques, in 5XFAD of either sex. But as expected, there were significant transcriptomic changes induced by CIH exposure in microglia from WT animals, although this is the first report of these transcriptomic alterations in murine microglia. CIH exposure also significantly altered the microglia transcriptome associated with amyloid pathology compared to CIH exposure in WT microglia (Figs. 5 & 6 ). Few DEGs were induced by CIH in 5XFAD microglia (compared to 5XFAD NX-exposed microglia) from either female (Fig. 5 ) or male (Fig. 6 ) mice, likely because the effect of the 5XFAD genotype is a stronger driver of transcriptomic changes in microglia than CIH. We chose to model the intermittent hypoxia aspect of SDB in the present studies. Although intrathoracic pressure swings, sleep fragmentation, intermittent hypercapnia, and augmented sympathetic drive (among others) also characterize SDB [ 52 , 53 ], most SDB morbidities can be modeled in rodents with CIH exposure alone [ 54 , 55 ]. The use of CIH in animal models permits mechanistic investigations of individual SDB features that are not possible in humans where multifactorial traits cannot be readily disentangled. The duration, interval and severity of the intermittent hypoxia are critical determinants of its potential to exert neuroprotective or pathologic effects [ 56 – 58 ]. However, a limitation of this CIH model is that it is unclear whether the mice also experienced sleep fragmentation [ 29 , 59 ], and if so, for how long, as this is also thought to contribute to cognitive decline in the aging population [ 60 , 61 ] and may interact with amyloid pathology [ 62 ]. Further, recent work suggests that cognitive changes associated with CIH in mouse models may be mediated by activation of the NLRP3 inflammasome [ 63 ], a major mediator of inflammation that accompanies AD and aging [ 64 ]. In fact, NLRP3-mediated neuroinflammation is thought to reduce microglial phagocytosis of Aβ [ 65 ], providing another potential link between AD and OSA co-morbidity. Previous data suggests a significant interaction between OSA and AD in other amyloid AD mouse models exposed to a much shorter duration of CIH (a few days or weeks vs 4- or 6-months in our studies). For example, in 10-11-month-old APP/PS1 mice, exposure to CIH for 4-weeks induced astrogliosis in the cortex [ 34 ]. Further, recent work using the APP NL-G-F knock-in mouse identified changes in Aβ, hyperphosphorylated tau, and β-Secretase 1 (BACE-1) in male mice two weeks following a 4-day CIH protocol [ 66 ]. Multiple groups have identified spatial learning and memory deficits induced by CIH based on reductions in behavioral performance, postsynaptic density and long-term potentiation in the hippocampus in two separate AD model paradigms: APP/PS1 mice after 2-weeks of CIH treatment and a tau mouse model after 8-weeks of CIH exposure [ 67 , 68 ]. When compared to our findings, these data support the idea that changes in the neuroinflammatory response are likely temporally dependent as we did not identify changes in pathology or gliosis by microscopy in the multi-month CIH timepoints we assessed here. Previous work by us and others [ 38 , 69 ] suggests the effects of CIH are sex-dependent. In the present report, females demonstrated few microglial transcriptomic changes when the effects of CIH treatment were compared to NX in 5XFAD animals. However, analysis of the comparisons made between WT and 5XFAD mice in the CIH condition identified an enrichment of GO terms associated with learning and memory as well as oxidative phosphorylation in the upregulated DEGs. These changes suggest there may be an effect of CIH exposure on metabolic processes, and may hint at a mechanism for the behavioral changes often associated with AD [ 48 ]. The differential expression of pro-inflammatory genes in isolated microglia from WT males following CIH treatment aligns with what our group and others have shown in both in vitro and in vivo models [32, reviewed in 33]. The comparison of NX vs CIH treatment of 5XFAD male mice only resulted in the identification of a single DEG ( tcap ) which, given current literature, does not clarify how CIH and the 5XFAD genotype interact. More DEGs may be identified if there is a critical window for interaction between CIH treatment duration and amyloid pathology progression. To further investigate this interaction in our existing dataset we analyzed the comparisons made between WT and 5XFAD mice in the NX and CIH conditions. Notably, CIH appeared to dampen the DAM profile established in 5XFAD microglia. The identification of GO pathways associated with oxidative phosphorylation and ATP synthesis in 5XFAD CIH mice versus the WT CIH comparisons, but not within the NX genotype comparisons, may suggest that CIH influences the metabolic response of microglia. As AD and SDB pathologies become more prevalent, the processes underlying their clinical association become of increasing importance. We sought to model SDB during the early accumulation phase of amyloid pathology. While there were no gross pathologic changes detected in the cortex of male or female 5XFAD mice, the effects on the microglia transcriptome, particularly in metabolic pathways, were mechanistically informative. Given the sex differences in OSA (males disproportionately affected) [ 69 ] and AD (females disproportionately affected) [ 70 ] and that there was an interaction between CIH and 5XFAD on the microglial transcriptome is intriguing and will require future analyses of potential hormonal contributions as the mice in the present study were gonadally intact. In sum, our results highlight the need for and importance of additional studies to examine the effect of longer term CIH exposure on later stages of AD pathology using tau mouse models, the role of gonadal hormones, and investigating other aspects of SDB beyond CIH, such as sleep fragmentation. Declarations Acknowledgements Special thanks to the University of Wisconsin Optical Imaging Core and the Research Animal Resources and Compliance (RARC) staff. Funding Sources This research was funded by NIH R21AG068652, P30-AG534255 UWADRCDP, R01AG070973, R01AG083883, Vilas Faculty Early-Career Investigator Award (TKU), NIH R01HL142752, NIH R21HD112147 (TLB, JJW), R01HL142752 NIA supplement (TKU, TLB, JJW), T32NS105602 and Herman H. Shapiro Wisconsin Distinguished Graduate Fellowship in Medicine (KMM) . Author Contributions JJW, TLB, and TKU conceptualized the project. ACE and ABR managed the IH exposures. KMM, ACE, PZR, TW handled the animals. KMM, ACE, JNL, ECM, SR, PZR, TW, ALW analyzed data. ACE performed microglia isolations and ACE and KMM performed RNA sequencing analyses. KMM stained, imaged and analyzed tissues. KMM drafted the manuscript; all authors had an opportunity to make edits. Data Availability Sequencing data are available on GEO (accession #GSE272491). Please contact authors to request any additional data. 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Weight (in grams) of female, 10-month old (A) and male, 8-month old (B) mice at harvest. Two-way ANOVA with Tukey multiple comparisons *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, ***\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001, ****\u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6203482/v1/49d3905532c37c87506fdd83.png"},{"id":81046808,"identity":"7a54cef1-e1e4-4c3d-944b-4e8b67b0f51e","added_by":"auto","created_at":"2025-04-21 15:02:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3093739,"visible":true,"origin":"","legend":"\u003cp\u003ePlaque load and plaque morphology are unchanged with CIH exposure. Imaris surfaces generated from methoxy-X04 stained, confocal z-stack images of a high-power field in the cortex of NX or CIH treated 5XFAD female or male mice (A, F). Imaris quantification of the number of plaques per field and average plaque volume per image, each data point represents 6 images (B,C,G,H). Tiled images of normoxia or CIH treated 5XFAD female or male mice (D, I). ImageJ quantification of the percent area of the cortex that contains plaques (E,J; each point represents 3 sections per animal). There were no differences detected by unpaired \u003cem\u003et\u003c/em\u003e-test, \u003cem\u003ep\u003c/em\u003e\u0026gt;0.05. Scale bar is 70 µm (A, F) and 1000 µm (D, I)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6203482/v1/ec2e2093a423578feb350a3a.png"},{"id":81047486,"identity":"fb1e5882-f423-4025-adc6-b30a5d357127","added_by":"auto","created_at":"2025-04-21 15:10:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":317583,"visible":true,"origin":"","legend":"\u003cp\u003eThe astrocyte response to amyloid deposition is unchanged by CIH exposure. Sections were stained with anti-GFAP antibodies (astrocytes), TO-PRO-3 (nuclei) and methoxy-X04 (plaques) and then imaged by confocal microscopy (A, C). Images were analyzed in Imaris (Bitplane) by colocalization. Each point represents 3 images per animal. There was no significant effect of CIH exposure by two-way ANOVA with Tukey multiple comparisons; \u003cem\u003ep\u003c/em\u003e\u0026gt;0.05. Scale bar is 70 µm\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6203482/v1/2de137969d2fe91be46a9d30.png"},{"id":81047485,"identity":"83ab08f7-54f4-4783-ae98-b1a2d90cc463","added_by":"auto","created_at":"2025-04-21 15:10:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":479407,"visible":true,"origin":"","legend":"\u003cp\u003eThe microglial response is slightly depressed with CIH exposure. Representative images of cortical sections from NX and CIH WT and 5XFAD mice stained with anti-iba-1 (microglia), TO-PRO-3 (nuclei) and methoxy-X04 (plaques) and then imaged by confocal microscopy (A (female), B (male)). Images were analyzed in Imaris (Bitplane) by colocalization (C, E). Microglia quantity and percentage of microglia 30 µm in female (C, D) and male (E, F) WT and 5XFAD mice exposed to NX or CIH. Each data point represents 3 images per animal. No significant effect of CIH exposure by two-way ANOVA with Tukey multiple comparisons, \u003cem\u003ep\u003c/em\u003e\u0026gt;0.05. Scale bar is 70 µm\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6203482/v1/ec8a8eb8717ee94eee684fc5.png"},{"id":81047487,"identity":"2f47de3b-6725-4e2a-aa8a-9a92cdaf081c","added_by":"auto","created_at":"2025-04-21 15:10:11","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":13345730,"visible":true,"origin":"","legend":"\u003cp\u003eCIH exposure drives few changes in gene expression by RNA sequencing in WT females but induces a unique gene program in 5XFAD females. RNA was isolated from CD11b+ cells immunomagnetically-isolated from the cortex of 10-month-old WT and 5XFAD female mice. Volcano plots with significant DEGs compared by genotype (A,D) and treatment (B,C) for all genes with FDR\u0026lt;0.05 and LFC\u0026gt;1. Venn diagram showing the number of overlapping and unique genes between the female WT and 5XFAD comparisons in NX and CIH treatment (E). Biological processes gene ontology (GO) analyses of those genes specific to the female WT NX vs 5XFAD NX comparison that are down- (F) and up-regulated (G). Biological processes GO analyses of those genes specific to the female WT CIH vs 5XFAD CIH comparison that are up-regulated (H).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6203482/v1/8f94dc53842c20fa2f06bb03.png"},{"id":81046822,"identity":"cadb4f25-3c7e-4377-b74b-85832604bc21","added_by":"auto","created_at":"2025-04-21 15:02:11","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":15784503,"visible":true,"origin":"","legend":"\u003cp\u003eCIH exposure in males drives significant differential expression by RNA sequencing. RNA was isolated from CD11b+ cells immunomagnetically-isolated from the cortex of 8-month-old WT and 5XFAD male mice. Volcano plots with significant DEGs compared by genotype (A,D) and treatment (B,C) for all genes FDR\u0026lt;0.05, LFC\u0026gt;1. Venn diagram showing the number of overlapping and unique genes between the male WT and 5XFAD comparisons in NX and CIH treatment (E). Biological processes gene ontology (GO) analyses of those genes specific to the male WT NX vs 5XFAD NX comparison that are down- (F) and up-regulated (G). Biological processes GO analyses of those genes specific to the male WT CIH vs 5XFAD CIH comparison that are up-regulated (H).\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6203482/v1/4c19731a3b545c68def4aa68.png"},{"id":96711230,"identity":"24ec10be-154f-40dd-b79c-e6028dbf20c8","added_by":"auto","created_at":"2025-11-25 10:11:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":58694608,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6203482/v1/3b124e78-fb11-4810-b7d5-9d7296ebf752.pdf"},{"id":81046810,"identity":"bda163a6-44d2-467b-9ebf-af63af116cca","added_by":"auto","created_at":"2025-04-21 15:02:11","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":351155,"visible":true,"origin":"","legend":"","description":"","filename":"SuppFile1CIHSeqFemaleSummary.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6203482/v1/a3f91ef31be45eac35a31996.xlsx"},{"id":81047490,"identity":"f31a92f5-6f02-4669-90f5-bd8b2a64b756","added_by":"auto","created_at":"2025-04-21 15:10:11","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":447919,"visible":true,"origin":"","legend":"","description":"","filename":"SuppFile2CIHSeqMaleSummary.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6203482/v1/f2c42e096da2b93241fa4425.xlsx"},{"id":81047797,"identity":"76164e58-d762-4fd1-8a1f-e1aa91ca4b17","added_by":"auto","created_at":"2025-04-21 15:18:11","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1065385,"visible":true,"origin":"","legend":"","description":"","filename":"SuppFile3betweencomparisons.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6203482/v1/e560a3bcf49c9927b97bfa58.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Chronic intermittent hypoxia exposure induces a unique microglial transcriptome in 5XFAD mice","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAs the world\u0026rsquo;s population ages, identifying and leveraging known risk factors associated with cognitive decline are of increasing importance as they could lessen the significant financial, medical, and caregiver strains on society. Targeting chronic diseases that can become a co-morbidity to diseases of aging, like Alzheimer\u0026rsquo;s disease (AD) and related dementias, later in life may acutely improve patient health and modulate disease severity or onset. One of these potential co-morbidities is obstructive sleep apnea (OSA), which affects an estimated 1\u0026nbsp;billion people worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. OSA is a form of sleep disordered breathing in which the airway is partially or completely blocked multiple times per hour during sleep, resulting in periods of intermittent hypoxia, hypercapnia, and sleep fragmentation [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Untreated, OSA can result in daytime sleepiness, fatigue, and diminished cognition [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The primary treatment for OSA is the use of a continuous positive airway pressure (CPAP) device, worn during sleep, that keeps the airway open to help regulate blood gases. CPAP is effective in reducing symptoms and improving perceived health-related quality of life, but there is no evidence of significantly improved cognition in those with mild to moderate OSA [\u003cspan additionalcitationids=\"CR6 CR7 CR8\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. CPAP is only effective, however, if individuals are willing to use it, but only an estimated 30\u0026ndash;60% of patients reliably use their CPAP devices, despite recent advances that make the equipment more comfortable and user friendly [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Neuroimaging studies have been used to probe the impact of OSA symptomology on brain structure. OSA correlates with thickening of several grey matter areas, and can be stratified by the primary symptom type (hypoxia vs sleep disturbance) [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Also, white matter changes and reduced attention are exacerbated in individuals over 60 years old with severe OSA [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Correlations between OSA and dementia have been identified [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], so there is increasing interest in OSA as a potential contributor to neurodegenerative disorders, including AD [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAD is a progressive disease thought to be driven by amyloid β (Aβ) plaque deposition, thought to begin decades prior to symptom onset, and the formation of neurofibrillary tau tangles (NFTs) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. A recent meta-analysis found that OSA was associated with elevated AD biomarkers in both the blood (total amyloid, Aβ\u003csub\u003e40\u003c/sub\u003e, Aβ\u003csub\u003e42\u003c/sub\u003e, and total tau) and cerebral spinal fluid (CSF) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Recent lipidomic analyses have identified a unique signature in the CSF and blood of individuals with AD and severe comorbid OSA [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] that is thought to be mediated by hypoxia-mediated inflammation, although additional studies are needed to confirm this. Further, positron emission tomography (PET) neuroimaging shows increased levels of amyloid in individuals with OSA [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. APOE ε4, a major genetic risk factor for AD, is a secondary risk factor for cognitive decline, which is exacerbated with worsening OSA severity [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Both OSA and AD cause neuroinflammation; while the mechanism for each pathology alone is thought to involve the activation of toll light receptor-4 (TLR4), the NACHT-, LRR-, and pyrin (PYD)-domain-containing protein 3 (NLRP3) inflammasome, ASC spec formation and astrocyte activation, the cellular interaction between these pathologies remains unclear [\u003cspan additionalcitationids=\"CR30 CR31 CR32\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGiven the paucity of sufficiently powered human studies, and the large overlapping populations between AD and OSA, we and others have turned to mouse models to examine the intersection of these disorders. One study examined the synergism of these pathologies using 1 month of CIH exposure, and found increased markers of astrocyte activation in the APP/PS1 mouse model, another amyloid AD mouse model [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Here, we employed the 5XFAD mouse model of AD [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] which develops rapid accumulation of amyloid pathology, and we exposed males and females to CIH for 4 or 6 months, respectively, to investigate the long term effects of CIH on the glial response to amyloid pathology and disease burden.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAnimal Care and Use\u003c/h2\u003e \u003cp\u003eWildtype (WT) females (C57BL/6J; JAX Stock #000664) were crossed with 5XFAD [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] male mice obtained from the Mutant Mouse Resource and Research Center at JAX (B6SJL-Tg (APPSwFlLon, PSEN1*M146L*L286V)6799Vas/Mmjax; JAX Stock #034840) and group housed in the University of Wisconsin-Madison School of Veterinary Medicine vivarium according to UW-Madison IACUC approved protocols #V005173 and #M006091. Mice were maintained on a 12-hour light/12-hour dark cycle with food and water provided ad libitum. Animals were anesthetized and perfused with cold Phosphate Buffered Saline (PBS) before tissue preparation. Females were harvested at 10-months of age while males were harvested at 8-months of age due to increasingly aggressive behavior that prevented group housing beyond this time.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eChronic intermittent hypoxia (CIH)\u003c/h3\u003e\n\u003cp\u003eBeginning at 4-months of age and until they reached the study endpoint, mice were exposed to intermittent hypoxia (IH) or room air (normoxia, NX) during their period presumptive sleep, as described previously [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. IH was achieved by alternating inspired oxygen levels between 6% O\u003csub\u003e2\u003c/sub\u003e and 21% O\u003csub\u003e2\u003c/sub\u003e over 90 second intervals. Mice subjected to NX conditions were exposed to the same noise and airflow as IH exposed mice, but inspired O\u003csub\u003e2\u003c/sub\u003e levels oscillated between 21% and 21% O\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e\n\u003ch3\u003eMicroglia isolation\u003c/h3\u003e\n\u003cp\u003eAs described previously [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], following cardiac perfusion, cerebral brain tissue was mechanically dissociated and placed in cold HBSS (Fisher #12-022-CM). Samples were then enzymatically digested with papain (from papaya latex, Sigma #P4762-500MG) and DNAse (Invitrogen #12185010) at 37\u0026deg;C, gravity fed through filters and myelin was separated from the cells using 26% percoll solution (Cytiva #17089101) and centrifuged at 2100 rpm, at 4\u0026deg;C for 15 minutes. The pellet was resuspended and incubated with anti-CD11b magnetic beads (Miltenyi Biotech #130-093-634) in IMAG (0.5% BSA and 2 mM EDTA in PBS) and run through primed magnetic columns (Miltenyi Biotech catalog #130-042-201). The isolated microglia were stored in TriZol (Invitrogen, 15596026) at -80\u0026deg;C.\u003c/p\u003e\n\u003ch3\u003eRNA isolation and sequencing analyses\u003c/h3\u003e\n\u003cp\u003eRNA isolation from n\u0026thinsp;=\u0026thinsp;5 independent samples for each sex, genotype and treatment was performed per the manufacturer\u0026rsquo;s instructions (Invitrogen, 15596026). Total RNA was sent to Novogene USA for bulk mRNA sequencing (NovaSeq6000 PE150, Illumina) and was aligned to the GRCm38/mm10 mouse genome. As we have reported previously [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], gene count files were imported into R and genes with a CPM\u0026thinsp;\u0026gt;\u0026thinsp;1 in 3 samples were included. Differential expression analysis was calculated between groups using EdgeR [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. PCA plots were used to identify outliers (Fig \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e-2) One female normoxia sample was identified as an outlier in several comparisons. Statistically significant comparisons had a false discovery rate (FDR)\u0026thinsp;\u0026lt;\u0026thinsp;5% and a log\u003csub\u003e2\u003c/sub\u003eFC\u0026thinsp;\u0026gt;\u0026thinsp;1. Gene ontology analyses were completed using the PANTHER Overrepresentation test [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] within the STRING analysis tool [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] using a high confidence (minimum required interaction score\u0026thinsp;=\u0026thinsp;0.7); like GO terms are grouped at a similarity of 0.8.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eTissue fixation and Immunofluorescence staining\u003c/h3\u003e\n\u003cp\u003eFollowing perfusion with cold PBS, tissue was fixed in 4% paraformaldehyde for 48 hours, rinsed with PBS, and sunk in 30% sucrose for 48 hours. Tissue was oriented and then frozen in a 2:1 30% sucrose/Tissue Tek OCT compound (Sakura #4583) solution and stored at -80\u0026deg;C. Brains were sectioned into 40 \u0026micro;m (Leica) sections and stored in cryoprotection buffer (30% ethylene glycol, 30% sucrose in PBS). Sections were selected, blocked in confocal blocking buffer (3% BSA, 0.15% Triton-X100 in PBS) for 1 hour and incubated with primary antibody to Iba-1 (Abcam ab5076; 1:1750) or GFAP (Alexa Fluor 488 Conjugated, Invitrogen 53-9892-82; 1:1000) overnight at 4\u0026deg;C. Floating sections were rinsed with PBS and incubated at room temperature with Alexa Fluor 488 Donkey anti-Goat secondary antibody (Abcam ab150129; 1:500), Methoxy-X04 (Tocris Biological #4920; 1:1000) and TO-PRO-3 (Thermo Fisher #T3605; 1:1000) in confocal blocking buffer. Sections were rinsed with PBS and mounted with Fluoromount G (SouthernBiotech, Cat. No. 0100-001) and #1 coverslips (Fisherbrand, Cat. No. 12541035) on superfrost slides (Fisherbrand Cat. No. 12-550-15).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eConfocal microscopy\u003c/h2\u003e \u003cp\u003eImmunofluorescent stained slides were imaged on a Nikon A1R\u0026thinsp;+\u0026thinsp;in the Optical Imaging Core at the University of Wisconsin-Madison. Images were obtained as Z-stack using a 20X objective (NA\u0026thinsp;=\u0026thinsp;0.75) at a step depth of 0.7 \u0026micro;m.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eImaris Analysis\u003c/h3\u003e\n\u003cp\u003eAs described previously [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], confocal images were loaded into Imaris (Bitplane 9.5.1) for analysis. The Iba-1 or GFAP (microglia or astrocyte respectively) and TO-PRO-3 channels were colocalized, and used to obtain a cell count and spatial coordinates for cells in the 3-dimensional images using the \u0026ldquo;spots\u0026rdquo; function. Plaque analyses were completed by generating 3-dimensional surfaces of methoxy-X04\u003csup\u003e+\u003c/sup\u003e plaques. The number of spots within 30 \u0026micro;m of all plaque surfaces in the image was then calculated.\u003c/p\u003e\n\u003ch3\u003ePlaque quantification in the cortex\u003c/h3\u003e\n\u003cp\u003eTiled, single plane images of methoxy-X04 staining were obtained on a Zeiss Imager.M2 microscope and exported into ImageJ [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] as a TIFF file. Cortex ROIs were traced for each section. A percentile threshold (0.4% (females) or 0.5% (males)) and particulate size threshold of 100 pixels was used to quantify the percent area occupied by plaques.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatistics\u003c/h2\u003e \u003cp\u003eMales and females were analyzed separately for all experiments. Statistical analyses were completed in Graph Pad Prism (Dotmatics) with a significance threshold of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for two-tailed unpaired t-tests and 2-way ANOVAs. Tukey post-hoc comparison tests were used for multiple comparisons at the same significance threshold. ROUT testing was used to identify and remove outliers (Q\u0026thinsp;=\u0026thinsp;1%).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCIH decreases body mass in male 5XFAD mice but increases it in female 5XFAD mice\u003c/h2\u003e \u003cp\u003eSince metabolic dysfunction is associated with OSA and AD [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR45 CR46\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], we recorded weight at the study endpoint. Females were sacrificed at 10-months of age and males at 8-months. In females, CIH exposure significantly increased the weight of WT mice, whereas female normoxia-exposed 5XFAD mice weighed significantly less than their WT counterparts, as expected (2-way ANOVA, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Interestingly, CIH exposure tended to decrease the weight of 5XFAD females further, although this did not reach statistical significance (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0898). In contrast, in males, CIH exposure significantly decreased body weight in both WT and 5XFAD mice (2-way ANOVA, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), and there was no difference in body weight in NX-exposed WT and 5XFAD male mice at this age.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePlaque number and size are unaffected by CIH in 8-month-old males and 10-month-old females\u003c/h2\u003e \u003cp\u003eTissues were stained with methoxy-X04 to label β amyloid plaques and imaged in 2 ways: 1) a Z-stack image of a high-powered field (HPF) in the cortex, and 2) a large, single plane tiled image that encompassed the entirety of the cortex in that section. Images of the HPF were analyzed in Imaris (Bitplane) to quantify plaque number and characteristics. These analyses in 10-month-old female (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) and 8-month-old male (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF) 5XFAD mice indicated no significant differences induced by CIH treatment either in the number of plaques present (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, G) or their size (C, H) (Unpaired \u003cem\u003et\u003c/em\u003e-test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The large tiled images (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD, I) were quantified in Image J and are reported as a percent of the cortex ROI (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE, J). Although not significant, there was a trend towards an increase in the total plaque area in the cortex of female 5XFAD mice that were exposed to CIH (Unpaired \u003cem\u003et\u003c/em\u003e-test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1086), but this difference was not observed in males (Unpaired \u003cem\u003et\u003c/em\u003e-test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCIH does not affect astrogliosis, but trends towards decreasing microgliosis with amyloid deposition in 5XFAD mice\u003c/b\u003e \u003c/p\u003e \u003cp\u003eGliosis is an integral component to AD pathology, so we quantified the number of astrocytes and microglia per HPF in the cortex. Reactive (GFAP\u003csup\u003e+\u003c/sup\u003e) astrocytes were quantified in Imaris. Consistent with other reports [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], there was an increase in reactive astrocytes in the cortex of both male and female 5XFAD mice when compared to WT (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, D; Two-way ANOVA with Tukey multiple comparisons, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). However, CIH did not change the number of reactive astrocytes in either male or female 5XFAD mice compared to the NX-exposed counterparts (females, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.6937; males, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.6877).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe microglial response to amyloid deposition was quantified in the same manner. As expected, the 5XFAD genotype significantly increased microglia number in the cortex (Two-way ANOVA, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and this tended to be decreased by CIH exposure in both males and females, although it did not reach statistical significance (Two-way ANOVA, females, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0864; males, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0589; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC, E). Further, since microglia cluster around plaques, an additional analysis of their relative localization was performed. Despite the trends in the overall number of microglia in each sex, there was no significant difference in the localization of microglia in relation to plaques between NX- and CIH-exposed female (Unpaired \u003cem\u003et\u003c/em\u003e-test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1632, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD) or male (Unpaired \u003cem\u003et\u003c/em\u003e-test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.2051, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF) 5XFAD mice.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eCIH drives transcriptional changes related to metabolism in microglia\u003c/h2\u003e \u003cp\u003eTo investigate the transcriptional changes associated with CIH exposure in WT and 5XFAD mice, we performed bulk RNA sequencing analyses on immunomagnetically isolated microglia; differentially expressed genes (DEGs) were identified as those which had an FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and Log\u003csub\u003e2\u003c/sub\u003eFC\u0026thinsp;\u0026gt;\u0026thinsp;1. The total number of significant DEGs for each comparison are shown in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe number of significant DEGs in microglial RNA-seq data from female mice. Significant comparisons had an FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05, LFC\u0026thinsp;\u0026gt;\u0026thinsp;1\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eComparison\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e#Upregulated\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e#Downregulated\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWT NX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWT CIH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWT NX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5X NX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e963\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWT CIH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5X CIH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e630\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5X NX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5X CIH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe number of significant DEGs in microglial RNA-seq data from male mice. Significant comparisons had an FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05, LFC\u0026thinsp;\u0026gt;\u0026thinsp;1\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eComparison\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e#Upregulated\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e#Downregulated\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWT NX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWT CIH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWT NX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5X NX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e973\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e396\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWT CIH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5X CIH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1153\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5X NX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5X CIH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe first analyzed the effect of genotype in microglia from NX-exposed females, by comparing WT and 5XFAD microglia (WT NX vs 5XFAD NX; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). There were 2,013 significant DEGs; 1,050 were upregulated and 963 were downregulated (See supplemental file 1 for full gene list). These DEGs included genes that characterize disease associated microglia (DAM) [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], as well as pathways related to TREM2-APOE [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] and aging [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Next, we compared the effect of CIH on WT female microglia (WT NX vs WT CIH), and 8 genes were differentially expressed: \u003cem\u003eLOC118568479\u003c/em\u003e was the most upregulated gene (LFC\u0026thinsp;=\u0026thinsp;3.84) and \u003cem\u003eErdr1_1\u003c/em\u003e was the most downregulated (LFC= -3.28, Volcano plot, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Comparing the effect of CIH on microglia from 5XFAD females (5XFAD NX vs 5XFAD CIH), there were a total of 9 DEGs, 7 were upregulated. The most upregulated was \u003cem\u003ePtpn5\u003c/em\u003e (LFC\u0026thinsp;=\u0026thinsp;3.42), and of the 2 downregulated genes, the greatest change was in \u003cem\u003eRn7sk\u003c/em\u003e (LFC= -4.35) (Volcano plot, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). We next assessed whether CIH had differential effects on microglia from WT females compared to 5XFAD females (WT CIH vs 5XFAD CIH; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). There were over 1000 genes up- and down-regulated (See supplemental file 1 for full gene list), which like the normoxia comparison, were due primarily to the effect of the 5XFAD genotype and consistent with those reported by us and others [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. To further examine the effect of CIH with respect to the microglial response to plaque pathology in female 5XFAD, we cross referenced the DEGs between the WT NX vs 5XFAD NX and WT CIH vs 5XFAD CIH comparisons (see Supplemental file 3). 1,442 genes were shared between the comparisons, 571 genes were specific to the WT NX vs 5XFAD NX comparison, and 530 genes were unique to the WT CIH vs 5XFAD CIH analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE). We performed gene ontology (GO) analyses on the up- and down-regulated genes that were unique to each respective comparison. The DEGs that were uniquely downregulated in the WT NX vs 5XFAD NX comparison were most enriched for system development, multicellular organism development, and anatomical structure development, as well as circulatory system development and cell motility, migration, morphogenesis and adhesion (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). The DEGs that were uniquely upregulated in the WT NX vs 5XFAD NX comparison included enrichment for the defense response, the innate immune response, and the response to interferon-β (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG). When we examined the DEGs that were unique to the WT CIH vs 5XFAD CIH comparison, no GO terms were identified for the downregulated genes. However, those that were uniquely upregulated in the WT CIH vs 5XFAD CIH comparison were significantly enriched for the GO terms associated with behavior and memory, regulation of cellular components, oxidative phosphorylation and precursor metabolite generation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH). In all, the comparisons between the effect of genotype and each respective treatment highlights that CIH can influence processes associated with metabolism, learning and memory.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe used the same analysis pipeline to examine the data from male microglia. The 5XFAD genotype had a significant effect on NX-exposed animals, with 973 genes being upregulated and 396 downregulated. These changes included the key genes associated with the 5XFAD genotype (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA; see supplemental file 2 for full gene list). We then analyzed the effect of CIH on microglia from WT animals. CIH had a more significant effect on WT male microglia than it did on WT female microglia. In WT males, a total of 465 genes were differentially expressed; 149 were downregulated and 316 were upregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Those that were significantly decreased included the type-I interferon associated neuroinflammatory genes \u003cem\u003eCxcl10\u003c/em\u003e (Log\u003csub\u003e2\u003c/sub\u003eFC= -1.20), \u003cem\u003eCcl5\u003c/em\u003e (Log\u003csub\u003e2\u003c/sub\u003eFC= -1.18), \u003cem\u003eIfitm2\u003c/em\u003e (Log\u003csub\u003e2\u003c/sub\u003eFC= -1.17), \u003cem\u003eIfitm3\u003c/em\u003e (Log\u003csub\u003e2\u003c/sub\u003eFC= -1.25), and \u003cem\u003eIfitm6\u003c/em\u003e (Log\u003csub\u003e2\u003c/sub\u003eFC= -1.60). The \u003cem\u003eXlr3a\u003c/em\u003e gene was the most upregulated (Log\u003csub\u003e2\u003c/sub\u003eFC\u0026thinsp;=\u0026thinsp;4.76). Notably, several genes encoding solute and amino acid transporters were significantly upregulated (See supplemental file 2 for full gene list). We then compared the effect of the 5XFAD genotype on microglia from CIH-exposed males. In the comparison of CIH-exposed WT and 5XFAD mice, over 2900 genes were differentially expressed; 1,779 were upregulated and 1,153 were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC), compared to less than 1400 genes that were differentially expressed due to the 5XFAD genotype in NX-exposed males (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). CIH alone had little to no effect on the male 5XFAD microglial transcriptome compared to NX; only 1 gene (\u003cem\u003etcap\u003c/em\u003e (Log2FC\u0026thinsp;=\u0026thinsp;1.15) was differentially upregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). While the comparison of CIH-treated WT and 5XFAD mice still included the hallmark changes associated with the 5XFAD genotype, key DAM genes that were upregulated in 5XFAD NX mice were less upregulated upon CIH exposure, suggesting that CIH may dampen the DAM gene profile in the microglia of male 5XFAD mice.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo further examine alterations to the DAM profile in males, we investigated the effect of the 5XFAD genotype in microglia from NX-exposed male WT and 5XFAD mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE, left) and the effect of CIH on male WT and 5XFAD mice by cross referencing all of the DEGs (up- and down-regulated) between these comparisons (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). Surprisingly, 955 genes were shared between them, thought there were 1,965 genes unique to the WT CIH vs 5XFAD CIH comparison and 414 genes that were unique to the WT NX vs 5XFAD NX comparison (see Supplemental file 3). We analyzed these differences using a gene ontology (GO) enrichment analysis, and a summary of the top 10 significantly enriched pathways are presented in Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF-H. None of the genes that were unique to the WT vs 5XFAD NX comparison were downregulated. However, the upregulated genes fell into categories associated with pathways involved in cell projection and neuron and axon development (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). The genes that were uniquely decreased in microglia from the WT CIH vs 5XFAD CIH comparison were enriched for gene categories involved in locomotion, cellular metabolic processes, protein modification, catalytic activity, macromolecule biosynthesis, transcription and nitrogen compound metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG). Notably, the upregulated genes unique to the WT CIH vs 5XFAD CIH comparison were enriched for GO pathways associated with oxidative phosphorylation, aerobic and cellular respiration and ATP synthesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG). Together, comparisons between the effect of genotype and treatment highlight the idea that CIH treatment alters oxidative phosphorylation and cell respiration, among others, in 5XFAD microglia. Interestingly, the DEGs in 5XFAD microglia from the NX comparison, but not the CIH comparison, suggests that microtubule structure and microglial morphology may be more impacted by the 5XFAD genotype, although the significance of this requires additional investigation.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThere is a strong clinical correlation between AD and OSA. But despite high prevalence of both disorders, their relationship remains poorly understood. Insights into this interaction could be leveraged as an early intervention strategy to mitigate or lessen future cognitive decline. Accordingly, the goal of our experiments here was to study the effects of the CIH associated with sleep disordered breathing in an animal model of early amyloid pathology. We initiated CIH exposure at 4-months of age, an early stage of pathology in the 5XFAD mouse model, and continued it daily until sacrifice. As we expected, we found that CIH exposure reduced body weight in 5XFAD male and female mice. In contrast to our initial hypothesis, however, the combination of amyloid pathology and CIH did not significantly alter amyloid plaque deposition (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), nor the number of astrocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) or microglia (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) in the cortex. CIH also did not alter the way microglia clustered around amyloid plaques, in 5XFAD of either sex. But as expected, there were significant transcriptomic changes induced by CIH exposure in microglia from WT animals, although this is the first report of these transcriptomic alterations in murine microglia. CIH exposure also significantly altered the microglia transcriptome associated with amyloid pathology compared to CIH exposure in WT microglia (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e \u0026amp; \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Few DEGs were induced by CIH in 5XFAD microglia (compared to 5XFAD NX-exposed microglia) from either female (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) or male (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) mice, likely because the effect of the 5XFAD genotype is a stronger driver of transcriptomic changes in microglia than CIH.\u003c/p\u003e \u003cp\u003eWe chose to model the intermittent hypoxia aspect of SDB in the present studies. Although intrathoracic pressure swings, sleep fragmentation, intermittent hypercapnia, and augmented sympathetic drive (among others) also characterize SDB [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], most SDB morbidities can be modeled in rodents with CIH exposure alone [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. The use of CIH in animal models permits mechanistic investigations of individual SDB features that are not possible in humans where multifactorial traits cannot be readily disentangled. The duration, interval and severity of the intermittent hypoxia are critical determinants of its potential to exert neuroprotective or pathologic effects [\u003cspan additionalcitationids=\"CR57\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. However, a limitation of this CIH model is that it is unclear whether the mice also experienced sleep fragmentation [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e], and if so, for how long, as this is also thought to contribute to cognitive decline in the aging population [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e] and may interact with amyloid pathology [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Further, recent work suggests that cognitive changes associated with CIH in mouse models may be mediated by activation of the NLRP3 inflammasome [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], a major mediator of inflammation that accompanies AD and aging [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. In fact, NLRP3-mediated neuroinflammation is thought to reduce microglial phagocytosis of Aβ [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e], providing another potential link between AD and OSA co-morbidity.\u003c/p\u003e \u003cp\u003ePrevious data suggests a significant interaction between OSA and AD in other amyloid AD mouse models exposed to a much shorter duration of CIH (a few days or weeks vs 4- or 6-months in our studies). For example, in 10-11-month-old APP/PS1 mice, exposure to CIH for 4-weeks induced astrogliosis in the cortex [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Further, recent work using the APP NL-G-F knock-in mouse identified changes in Aβ, hyperphosphorylated tau, and β-Secretase 1 (BACE-1) in male mice two weeks following a 4-day CIH protocol [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Multiple groups have identified spatial learning and memory deficits induced by CIH based on reductions in behavioral performance, postsynaptic density and long-term potentiation in the hippocampus in two separate AD model paradigms: APP/PS1 mice after 2-weeks of CIH treatment and a tau mouse model after 8-weeks of CIH exposure [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. When compared to our findings, these data support the idea that changes in the neuroinflammatory response are likely temporally dependent as we did not identify changes in pathology or gliosis by microscopy in the multi-month CIH timepoints we assessed here.\u003c/p\u003e \u003cp\u003ePrevious work by us and others [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e] suggests the effects of CIH are sex-dependent. In the present report, females demonstrated few microglial transcriptomic changes when the effects of CIH treatment were compared to NX in 5XFAD animals. However, analysis of the comparisons made between WT and 5XFAD mice in the CIH condition identified an enrichment of GO terms associated with learning and memory as well as oxidative phosphorylation in the upregulated DEGs. These changes suggest there may be an effect of CIH exposure on metabolic processes, and may hint at a mechanism for the behavioral changes often associated with AD [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. The differential expression of pro-inflammatory genes in isolated microglia from WT males following CIH treatment aligns with what our group and others have shown in both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e models [32, reviewed in 33]. The comparison of NX vs CIH treatment of 5XFAD male mice only resulted in the identification of a single DEG (\u003cem\u003etcap\u003c/em\u003e) which, given current literature, does not clarify how CIH and the 5XFAD genotype interact. More DEGs may be identified if there is a critical window for interaction between CIH treatment duration and amyloid pathology progression. To further investigate this interaction in our existing dataset we analyzed the comparisons made between WT and 5XFAD mice in the NX and CIH conditions. Notably, CIH appeared to dampen the DAM profile established in 5XFAD microglia. The identification of GO pathways associated with oxidative phosphorylation and ATP synthesis in 5XFAD CIH mice versus the WT CIH comparisons, but not within the NX genotype comparisons, may suggest that CIH influences the metabolic response of microglia.\u003c/p\u003e \u003cp\u003eAs AD and SDB pathologies become more prevalent, the processes underlying their clinical association become of increasing importance. We sought to model SDB during the early accumulation phase of amyloid pathology. While there were no gross pathologic changes detected in the cortex of male or female 5XFAD mice, the effects on the microglia transcriptome, particularly in metabolic pathways, were mechanistically informative. Given the sex differences in OSA (males disproportionately affected) [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e] and AD (females disproportionately affected) [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e] and that there was an interaction between CIH and 5XFAD on the microglial transcriptome is intriguing and will require future analyses of potential hormonal contributions as the mice in the present study were gonadally intact. In sum, our results highlight the need for and importance of additional studies to examine the effect of longer term CIH exposure on later stages of AD pathology using tau mouse models, the role of gonadal hormones, and investigating other aspects of SDB beyond CIH, such as sleep fragmentation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSpecial thanks to the University of Wisconsin Optical Imaging Core and the Research Animal Resources and Compliance (RARC) staff. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by NIH R21AG068652, P30-AG534255 UWADRCDP, R01AG070973, R01AG083883, Vilas Faculty Early-Career Investigator Award (TKU), NIH R01HL142752, NIH R21HD112147 (TLB, JJW), R01HL142752 NIA supplement (TKU, TLB, JJW), T32NS105602 and Herman H. Shapiro Wisconsin Distinguished Graduate Fellowship in Medicine (KMM)\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJJW, TLB, and TKU conceptualized the project. ACE and ABR managed the IH exposures. KMM, ACE, PZR, TW handled the animals. KMM, ACE, JNL, ECM, SR, PZR, TW, ALW analyzed data. ACE performed microglia isolations and ACE and KMM performed RNA sequencing analyses. KMM stained, imaged and analyzed tissues. KMM drafted the manuscript; all authors had an opportunity to make edits.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSequencing data are available on GEO (accession #GSE272491). 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Arch Gen Psychiatry 62:685\u0026ndash;691. https://doi.org/10.1001/archpsyc.62.6.685\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"molecular-neurobiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"moln","sideBox":"Learn more about [Molecular Neurobiology](https://www.springer.com/journal/12035)","snPcode":"12035","submissionUrl":"https://submission.nature.com/new-submission/12035/3","title":"Molecular Neurobiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"neuroinflammation, intermittent hypoxia, microglia, amyloid ","lastPublishedDoi":"10.21203/rs.3.rs-6203482/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6203482/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eClinical observations suggest that obstructive sleep apnea (OSA) and Alzheimer\u0026rsquo;s disease (AD) pathology may be linked; however, causal mechanisms and relationships are unclear. To investigate the potential interaction between amyloidosis and intermittent hypoxia (IH), a hallmark of OSA, starting at 4-months of age 5XFAD mice were exposed to chronic IH (CIH) consisting of 20 episodes per hour of hypoxia for 12 hours/day, daily for 4- (males) or 6-months (females). CIH did not induce significant changes in amyloid burden or the number of astrocytes in males or females, but there was a slight decrease in the number of microglia observed in the cortex of 5XFAD mice of both sexes. To further explore this effect, we performed bulk RNA sequencing on isolated microglia. In WT mice, the most robust gene changes induced by CIH were identified in male microglia, many of which were pro-inflammatory. In microglia from 5XFAD mice, compared to NX, CIH exposure induced comparatively more DEGs in males. Further, in genes that were upregulated by CIH in WT vs 5XFAD mice of both sexes, there was an enrichment of pathways associated with oxidative phosphorylation, aerobic and cellular respiration, and ATP synthesis. These changes indicate that CIH has a more robust effect on the microglial transcriptome in 5XFAD mice than in WT mice, suggesting that the synergy between AD and OSA pathologies may be driven by metabolic changes in the microglial transcriptome. These observations are particularly interesting given the known sex differences in OSA and AD pathology in human disease.\u003c/p\u003e","manuscriptTitle":"Chronic intermittent hypoxia exposure induces a unique microglial transcriptome in 5XFAD mice","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-21 15:02:06","doi":"10.21203/rs.3.rs-6203482/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-07T13:33:14+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-07T01:48:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"277681777302187036591807714665320264216","date":"2025-04-28T14:11:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-23T20:14:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"211848136595123278116212445345002165235","date":"2025-03-31T09:05:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"299855275445414133433437269424270073877","date":"2025-03-31T09:02:08+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-31T08:55:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-22T07:59:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-22T07:58:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"Molecular Neurobiology","date":"2025-03-11T13:14:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"molecular-neurobiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"moln","sideBox":"Learn more about [Molecular Neurobiology](https://www.springer.com/journal/12035)","snPcode":"12035","submissionUrl":"https://submission.nature.com/new-submission/12035/3","title":"Molecular Neurobiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"f980474b-11d7-4c83-a685-c7136b4ff330","owner":[],"postedDate":"April 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-24T15:59:52+00:00","versionOfRecord":{"articleIdentity":"rs-6203482","link":"https://doi.org/10.1007/s12035-025-05390-7","journal":{"identity":"molecular-neurobiology","isVorOnly":false,"title":"Molecular Neurobiology"},"publishedOn":"2025-11-19 15:56:53","publishedOnDateReadable":"November 19th, 2025"},"versionCreatedAt":"2025-04-21 15:02:06","video":"","vorDoi":"10.1007/s12035-025-05390-7","vorDoiUrl":"https://doi.org/10.1007/s12035-025-05390-7","workflowStages":[]},"version":"v1","identity":"rs-6203482","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6203482","identity":"rs-6203482","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}