# Oxidative and Inflammatory Mechanisms Induced by Intermittent Hypoxia Leading to Vascular Alterations in Rodents: A Systematic Review and Meta-Analysis

Marc Adrien Reveyaz, Célian Peyronnel, Quentin Boëte, Joey Fournier, Claire Arnaud, Elise Belaïdi, Olfa Harki, Jean-Louis Pépin, Charles Khouri, Gilles Faury, et al.

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Marc Adrien Reveyaz, Célian Peyronnel, Quentin Boëte, Joey Fournier, Claire Arnaud, et al. Oxidative and Inflammatory Mechanisms Induced by Intermittent Hypoxia Leading to Vascular Alterations in Rodents: A Systematic Review and Meta-Analysis. Oxidative Medicine and Cellular Longevity, 2026, 2026 (1), pp.9967028. 10.1155/omcl/9967028. inserm-05485479

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Research Article

# Oxidative and Inflammatory Mechanisms Induced by Intermittent Hypoxia Leading to Vascular Alterations in Rodents: A Systematic Review and Meta-Analysis

Marc Adrien Reveyaz ID,<fnref n="1" /> Célian Peyronnel ID,<fnref n="1" /> Quentin Boëte ID,<fnref n="1" /> Joey Fournier ID,<fnref n="2" />

Claire Arnaud ID,<fnref n="1" /> Elise Belaïdi ID,<fnref n="3" /> Olfa Harki ID,<fnref n="1" /> Jean-Louis Pépin ID,<fnref n="1" />

Charles Khouri ID,<fnref n="1" />,<fnref n="2" /> Gilles Faury ID,<fnref n="1" /> and Anne Briançon-Marjollet ID<fnref n="1" />

Correspondence should be addressed to Anne Briançon-Marjollet; anne.briancon@univ-grenoble-alpes.fr

Received 19 November 2024; Revised 6 October 2025; Accepted 2 December 2025

Academic Editor: Priya Gusain

Copyright © 2026 Marc Adrien Reveyaz et al. Oxidative Medicine and Cellular Longevity published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

**Objectives:** Obstructive sleep apnea (OSA) and the related intermittent hypoxia (IH) are recognized as major cardiovascular risk factors. In a previous meta-analysis, we confirmed the impact of IH on structural and functional remodeling of vessels in rodent models of IH. Here, we conducted a systematic review and meta-analysis to investigate the molecular mechanisms related to vascular remodeling induced by IH and to analyze the impacts of patterns of exposure on the effect of IH.

**Methods:** We searched PubMed, Web of Science, and EMBASE and included 52 articles, among them 44 concerning wild type (WT) rodents and eight concerning apolipoprotein E knockout (ApoE⁻/⁻) mice. We used standardized mean difference (SMD) to compare results between studies. A hypoxic score was designed and calculated, and metaregressions were performed to explore the impact of IH exposure parameters on the selected outcomes.

**Results:** IH induced an increase in oxidative stress, inflammation markers, leucocyte infiltration, and apoptosis, and a decrease in endothelial nitric oxide synthase (eNOS) expression and activity in arteries of WT mice. In metaregressions, inflammation and oxidative stress markers were associated with total duration of IH exposure, and eNOS was associated with hypoxic score. In ApoE⁻/⁻ mice, inflammation markers were significantly increased in atherosclerotic plaques, but leukocyte infiltration and oxidative stress were not modified by IH. Rodent characteristics had only few impacts on the outcomes.

**Conclusions:** Our meta-analysis confirms that IH, independently of measured confounders, has a major impact on oxidо-inflammatory mechanisms in vessels, and that the duration of IH can modulate these effects. Our findings strengthen our understanding of molecular mechanisms associated with vascular alterations in IH/OSA.

**Keywords:** apoptosis; inflammation; intermittent hypoxia; meta-analysis; oxidative stress; systematic review; vascular alterations

## 1. Introduction

Obstructive sleep apnea (OSA) is characterized by repeated breathing interruptions during sleep, caused by upper airway closures often due to surrounding tissue collapse. These episodes, ranging from a few to over 30 per hour [1], pose a significant public health challenge affecting up to 1 billion

people globally with daytime sleepiness, accidents, and negative impacts on other serious diseases. OSA is now recognized as a significant risk factor for cardiovascular and metabolic diseases, including hypertension, atherosclerosis, myocardial infarction, stroke, and type 2 diabetes [2], which all appear related to the intermittent hypoxia (IH) it generates [1, 3]. While the apnea-hypopnea index (AHI), that is, the number of apnea and

<footnote n="1">¹HP2 Laboratory, CHU Grenoble Alpes, Université Grenoble Alpes, INSERM, Grenoble 38000, France</footnote>

<footnote n="2">²Pharmacovigilance Unit and Clinical Pharmacology Department, Grenoble Alpes University Hospital, Grenoble, France</footnote>

<footnote n="3">³LBTI UMR 5305, Laboratory of Tissue Biology and Therapeutic Engineering, University Lyon 1, CNRS, Lyon 69367, France</footnote>
hypopnea events per hour of sleep, remains the standard for assessing OSA severity, recent studies increasingly suggest that new indexes such as the hypoxic burden (HB) or the sleep breathing impairment index (SBII), both related to nocturnal hypoxic load, may better reflect cardiovascular risk [4-8].

Because many of the extracellular, cellular, and molecular mechanisms leading to OSA impacts on cardiovascular health or outcomes are often difficult to investigate in patients, studies using rodent models have been used over the last few decades to explore IH-related cardiac and vascular impacts. Our two recent meta-analyses about the structural and functional consequences of IH on blood vessels and heart in rodent models revealed that (i) IH elevates blood pressure, thickens artery walls, impairs vascular reactivity/motricity (at least, in part, through endothelial dysfunction), and promotes atherosclerosis [9], and (ii) IH induces cardiac dysfunction and fibrosis and increases sensitivity to myocardial infarction, notably with severe hypoxia being harmful, while moderate hypoxia (fraction of inspired oxygen [FiO₂] > 7%, <5 h/day) offers heart protection [10].

The mechanisms by which the OSA/IH mediates vascular structure-function changes have also been explored. Oxidative stress, inflammation, and nitric oxide (NO) dysregulation in blood vessels have been found to positively correlate with OSA/IH [1, 2, 11, 12], suggesting that these effects might be key factors in understanding OSA-related impacts on cardiovascular disease. The dysregulation of the pro-oxidant/antioxidant balance by IH results in increases in both reactive oxygen species (ROS) and reactive nitrogen species (RNS), leading to increases of plasma biomarkers of oxidative stress including malondialdehyde (MDA, a lipid peroxidation end-product), isoprostanes, advanced oxidation protein products (AOPPs), and DNA oxidation products (8-hydroxy-2-deoxyguanosine, 8-OHdG) [12]. This oxidative stress may trigger vascular inflammation, characterized by activated leukocytes and endothelial cells and increased proinflammatory transcription factors and cytokines such as nuclear factor kappa B (NF-κB), tumor necrosis factor (TNF-α), and interleukin (IL) -6 [1, 2, 12]. Oxidative stress and inflammation may then, in turn, activate downstream signaling pathways leading to the increased apoptosis of endothelial cells observed in OSA patients [13] and to altered endothelial NO synthase (eNOS) expression and activity, leading to reduced NO bioavailability [12, 14] which, together with eNOS uncoupling, further contributes to increased oxidative stress [15, 16].

There are, however, some notable differences observed between rodent studies related to the impacts of experimental IH on oxidative stress, inflammation, and/or eNOS expression. Such differences could be due, in part, to variability in the impact of IH resulting from endogenous/biological variability between subjects or to methodological reasons. In particular, IH exposure duration appears to be a major determinant of the nature and magnitude of the impact of IH. For example, Zhou et al. [17] demonstrated that eNOS expression was increased after 3 days of IH but was not different than the normoxia controls (N) after 1 or 3 weeks of IH exposure and then ultimately decreased after 8 weeks of IH. By contrast, in the same study, biomarkers of oxidative stress (TNFα and 3-nitrotyrosine) were only increased after 8 weeks of IH and were not

significantly different than controls at the earlier time points [17]. Philippi et al. [18] performed a time-course study over 3-56 days of IH and observed that the impact of IH on vessel diameter, collagen deposition, and eNOS expression was variable depending on the duration of IH exposure. In addition to variability related to IH duration, differences between studies might also be explained by the different patterns of IH exposure. For example, in two studies which both used mice exposed to 28 days of IH, the opposing effects on eNOS expression observed might be explained by the difference in both the hypoxia severities (10% vs. 5%) and the IH cycle durations (1 vs. 3 min) that were used [19, 20].

For these reasons, we conducted this systematic review and meta-analysis in order to clarify the respective importance and impact of the cellular mechanisms in the various rodent IH models, including effects on oxidative stress, inflammation, apoptosis, eNOS expression, and function in arteries, and to explore, using subgroup analyses and metaregressions, the main factors involved in the heterogeneity of effects reported, including those related to the rodent models and IH cycle patterns that were used.

## 2. Methods

The protocol for the meta-analysis was recorded on PROSPERO under the number CRD42020169940 (https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020169940). Owing to the large amount of available data, our previous publication specifically reported on the impacts of IH on structural and functional vascular outcomes [9], and the remaining data related to the potential cellular mechanisms underlying these vascular outcomes is reported in the present meta-analysis.

### 2.1. *Search Methods and Study Selection.*
We searched PubMed, Web of Science, and EMBASE for articles published through March 31, 2025, using the terms "Intermittent hypoxia" AND "Rodent" OR "mice" OR "rat" (see PROSPERO for the exact query). We also searched for related keywords and MeSH terms. After the initial search, we screened titles and abstracts to identify relevant articles. Eligibility was based on studies written in English that examined systemic artery outcomes of IH in rodents related to oxidative stress, inflammation, or apoptosis. Full manuscripts were then reviewed for inclusion and exclusion criteria, with two authors independently screening references. Discrepancies were resolved through intrateam discussion.

We included only controlled studies on rodents exposed to chronic IH compared to normoxic controls (21% FiO₂). IH was defined as repeated hypoxia-reoxygenation cycles within a day, and chronic IH as the repetition of these cycles for at least 1 day. Wild type (WT) rodents—mice or rats, male or female, age ≥ 4 weeks, and lean or obese—were included. We excluded studies with continuous hypoxia (no normoxia), hypoxia combined with hypo/hypercapnia, those using hypo/hyperbaric conditions, prenatal or perinatal exposure, and transgenic animals, except for apolipoprotein E knockout (ApoE⁻/⁻) mice used for atherogenesis studies. Studies involving pulmonary or cerebral vessels were also excluded.
Mandatory outcomes were assessment of oxidative stress, inflammation, leukocyte infiltration, apoptosis, or eNOS (expression, phosphorylation, or activity) in arterial tissues (blood measurements were excluded). Oxidative stress markers included dihydroethidium (DHE), 4-hydroxy-2-nonenal (4-HNE), MDA, superoxide anions, nitrotyrosine, AOPP, or pro/antioxidant enzymes (NADPH oxidase [NOX], xanthine oxidase, superoxide dismutase [SOD], catalase, or glutathione peroxidase). Inflammation markers included mRNA or protein expression of IL-6, TNF-α, IL-1β, interferon gamma (IFNγ), monocyte chemoattractant protein-1 (MCP-1), intercellular adhesion molecule-1 (ICAM-1), NF-κB, inducible NO synthase (iNOS), or cyclooxygenase 2 (COX-2). Apoptosis markers include TUNEL staining, or expression of caspase-3, B-cell leukemia/lymphoma 2 protein (BCL-2), or Bcl-2-associated X protein (BAX). Leukocyte infiltration and atherosclerotic plaques were evaluated in WT and ApoE<sup>-/-</sup> mice.

**2.2. Assessment of a Hypoxic Score.** To mirror the sleep-apnea patient-specific HB in animal studies, we developed a self-referential score, reflecting the characteristics of the IH exposure in the set of the studies selected. While we recognized that the HB used in clinical settings for patients with OSA largely relies on $O_2$ desaturation, this was not available in the vast majority of animal studies. Accordingly, we developed a “hypoxic score,” with the aim to provide the best possible quantification of the cumulative intensity of hypoxia exposure based on accessible characteristics common to all the included animal studies. This hypoxic score included the following five parameters: (1) $FiO_2$ during hypoxia (X1), (2) hypoxic phase duration (X2), (3) reoxygenation phase duration (X3), (4) daily hypoxic exposure time (X4), and (5) total exposure duration (X5). We assumed that a lower $FiO_2$, a greater duration of the hypoxia phase, or an increase in the number of days of exposure all increased the hypoxic load, while a longer reoxygenation duration would likely be a mitigating factor of hypoxic load. We thus categorized each of the five hypoxic exposure parameter values into terciles or halves based on study data, assigning a score from 1 (lowest) to 3 (highest) for each parameter. The hypoxic score was thus calculated as $X1 + X2 - X3 + X4 + X5$, with X3 (reoxygenation duration) subtracted as it, again, is theoretically a mitigating factor that opposes the hypoxia load. A higher score indicates a more severe hypoxic load (Supporting Information 1 and Supporting Information 2: Figure S8).

**2.3. Methodological Quality Assessment.** Study quality was assessed using the SYRCLE tool [21]. This tool evaluates selection bias (sequence generation, baseline characteristics, and allocation concealment), performance bias (randomized animal housing and investigator blinding), detection bias (random outcome assessment and blinding of assessors), attrition bias (incomplete data), and reporting bias (selective reporting). Bias risk is rated as high, low, or unclear. Four authors independently scored the studies, and disagreements were resolved through consensus.

**2.4. Statistical Analyses.** We conducted separate meta-analyses for WT rodents and ApoE<sup>-/-</sup> mice, using standardized mean

difference (SMD) and 95% confidence intervals (CIs) for each outcome. An SMD >0.8 was considered large, 0.5–0.8 moderate, and 0.2–0.5 small [22]. If standard deviations (SDs) were missing, we estimated them from CIs or standard errors [23] or imputed them using SD from the other arm when reported. If no SD was reported in any arm, the study was excluded from the analysis. Results were visualized with Orchard plots, an innovative data visualization tool well adapted for displaying the results of a large number of outcomes (Supporting Information 2: Figure S1). For consistency, we inverted SMD signs for antioxidants (SOD and catalase) and antiapoptotic (BCL-2) and excluded studies with extreme SMD values (>10 or <-10) to limit outlier influence. Random-effects meta-analyses were performed using the restricted maximum-likelihood estimator, with hierarchical models for multiarm studies. For outcomes with >10 studies, we explored heterogeneity via subgroup analyses and metaregressions based on population characteristics (age, sex, and weight) and IH protocols ($FiO_2$, phase durations, and exposure time). Metaregressions for WT rodents also accounted for species (rat/mice). Funnel plot asymmetry for primary outcomes was assessed with Egger's test ($p<0.1$ for publication bias). We performed a sensitivity analysis by excluding studies with missing and imputed SDs.

Analyses were performed using R statistical software (v4.1.1).

## 3. Results

Our systematic literature review yielded 4187 references through March 31, 2025, among which we ultimately selected 52 articles for inclusion in the meta-analysis, including 44 studies in WT rodents and eight studies in ApoE<sup>-/-</sup> mice (Figure 1). Supporting Information 3: Table S1, Supporting Information 2: Figure S2, and Supporting Information 1 present vascular outcomes available across the studies, the settings of hypoxic exposure, and the experimental designs.

**3.1. Impact of IH on Inflammation in WT Mice.** We examined inflammation markers (gene/protein expression and protein activity) in WT mice, including IL-6, TNFα, IFNγ, MCP-1, IL-1β, TGFβ, ICAM-1, NFκB, HIF-1, iNOS, and COX-2. IH significantly increased these markers in arterial walls (SMD 2.32 [1.3; 3.33]; Figure 2A and Supporting Information 2: Figure S3A), in parallel with elevated leukocyte infiltration (SMD 2.35 [0.44; 4.26]; Figure 2B and Supporting Information 2: Figure S3B). Following metaregression analyses, leukocyte infiltration correlated with IH exposure duration (slope estimate = 0.03, $p = 0.022$) and with $FiO_2$ during hypoxia (slope estimate = 3.04, $p = 0.048$; Table 1 and Figure 2C,D), suggesting that arterial leukocyte infiltration is related to both IH severity and duration. Inflammation markers tended to be associated with duration of the hypoxic phase (slope estimate = -0.03, $p = 0.064$) and with total duration of exposure (slope = 0.01, $p = 0.081$; Table 1).

**3.2. Impact of IH on Oxidative Stress, eNOS, and Apoptosis.** Oxidative stress was assessed via expression and activity of enzymes (SOD, catalase, NOX, glutathione peroxidase, and xanthine oxidase) and markers including MDA, superoxide
<figure><img src="image_3.png" /><figcaption>FIGURE 1: Flow diagram of the study. IH, intermittent hypoxia; WT, wild type. ApoE<sup>-/-</sup>, apolipoprotein E knockout.</figcaption></figure>

<figure><img src="image_4.png" /><figcaption>FIGURE 2: Intermittent hypoxia increases inflammation in systemic vessels of wild type animals. Orchard plots showing standardized mean differences (SMD) for (A) inflammation markers and (B) leukocyte infiltration in arterial walls. (C, D) Association of leucocyte infiltration with total duration of IH (slope = 0.03, *p* = 0.022) and with $FiO_2$ (slope = 3.04, *p* = 0.048), respectively. *k* represents the number of effect sizes per estimate.</figcaption></figure>
<table><caption>TABLE 1: Metaregression analyses for the main outcomes: inflammation markers, oxidative stress, eNOS level, leukocyte infiltration in WT animals, and leukocytes infiltration in ApoE<sup>-/-</sup> mice.</caption><thead><tr><th rowspan="2">Moderator</th><th colspan="2">Inflammation markers</th><th colspan="2">Oxidative stress</th><th colspan="2">eNOS</th><th colspan="2">Leukocyte infiltration (WT)</th><th colspan="2">Leukocyte infiltration (ApoE<sup>-/-</sup>)</th></tr><tr><th>Slope</th><th>p-value</th><th>Slope</th><th>p-value</th><th>Slope</th><th>p-value</th><th>Slope</th><th>p-value</th><th>Slope</th><th>p-value</th></tr></thead><tbody><tr><td>Species</td><td>1.01</td><td>0.363</td><td>0.31</td><td>0.746</td><td>-1.43</td><td>0.262</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td></tr><tr><td>Age</td><td>0.00</td><td>0.860</td><td>0.00</td><td>0.945</td><td>0.00</td><td>0.964</td><td>0.25</td><td>0.689</td><td>-0.34</td><td>0.284</td></tr><tr><td>Body weight</td><td>-0.02</td><td>0.122</td><td>-0.01</td><td>0.178</td><td>0.02</td><td>0.006*</td><td>NA</td><td>NA</td><td>0.83</td><td>0.423</td></tr><tr><td>FiO<sub>2</sub></td><td>0.01</td><td>0.808</td><td>-0.06</td><td>0.174</td><td>-0.14</td><td>0.279</td><td>3.04</td><td>0.048*</td><td>-0.30</td><td>0.831</td></tr><tr><td>Duration of hypoxic phase</td><td>-0.03</td><td>0.064</td><td>0.00</td><td>0.785</td><td>0.00</td><td>0.892</td><td>-0.01</td><td>0.567</td><td>-0.09</td><td>0.001*</td></tr><tr><td>Duration of reoxygenation phase</td><td>0.01</td><td>0.421</td><td>0.00</td><td>0.785</td><td>0.00</td><td>0.929</td><td>-0.01</td><td>0.567</td><td>0.14</td><td>0.284</td></tr><tr><td>Duration of IH per day</td><td>-0.20</td><td>0.467</td><td>-0.01</td><td>0.956</td><td>0.21</td><td>0.351</td><td>0.39</td><td>0.497</td><td>2.07</td><td>0.000**</td></tr><tr><td>Duration of exposure</td><td>0.01</td><td>0.081</td><td>0.02</td><td>0.018*</td><td>-0.05</td><td>0.104</td><td>0.03</td><td>0.022*</td><td>-0.18</td><td>0.158</td></tr><tr><td>Hypoxic score</td><td>0.30</td><td>0.212</td><td>0.62</td><td>0.004*</td><td>0.76</td><td>0.085</td><td>0.45</td><td>0.757</td><td>0.45</td><td>0.834</td></tr></tbody></table>

Note: FiO₂, inspiratory oxygen fraction.

Abbreviation: IH, intermittent hypoxia.

*p*<0.05.

**p*<0.001.

anions, oxidized proteins, nitrotyrosine amounts, or DHE staining. IH significantly increased oxidative stress (SMD 1.41 [0.56; 2.25]; Figure 3A and Supporting Information 2: Figure S4A), which correlated with total IH duration (estimate 0.02, *p* = 0.018) and with hypoxic score (estimate = 0.67, *p* = 0.002) in metaregression analyses (Figure 3B,C and Table 1). IH also decreased eNOS expression, phosphorylation, or activity (SMD -1.12 [-2.16; -0.09]; Figure 3D and Supporting Information 3: Figure S4B), which was correlated with body weight in metaregressions (estimate = 0.02, *p* = 0.006) and tended to be associated with hypoxic score (estimate 0.76, *p* = 0.085). Despite the small number of studies, apoptosis levels assessed by TUNEL staining, caspase-3, BAX, and BCL-2 expression were significantly elevated after IH (SMD 4.2 [2.5; 5.9]; Figure 3E and Supporting Information 2: Figure S4C).

### 3.3. Impact of IH on ApoE<sup>-/-</sup> Mice.
In ApoE<sup>-/-</sup> mice, due to the low number of studies, only three outcomes could be analyzed. IH significantly increased inflammation markers (SMD 3.32 [1.25; 5.4]; Figure 4A and Supporting Information 2: Figure S5A) but had no significant effect on leukocyte infiltration (SMD 2.23 [-1.39; 5.85]) or oxidative stress (SMD 2.87 [-2.16; 7.9]; Figure 4B,C, and Supporting Information 2: Figure S5B,C). In metaregressions, leukocyte infiltration correlated with both hypoxic phase duration (estimate 0.09, *p* = 0.001) and daily exposure time (estimate 2.07, *p*<0.001; Figure 4D and Table 1).

### 3.4. Risk of Bias and Small Study Effect.
Using the SYRCLE tool [21], bias risk was considered as low for 25%–50% of studies for sequence generation, baseline characteristics, incomplete outcome data, and selective outcome reporting. On the other hand, the risk was high for 33% of studies for incomplete outcome data (Supporting Information 2: Figure S6 and Supporting Information 4: Table S2). For all other SYRCLE items, ≥95% of studies scored as unclear as the information was almost never mentioned in publications. Funnel plots revealed

asymmetry and significant Egger tests, indicating small study effects (Supporting Information 2: Figure S7).

## 4. Discussion

IH is a major feature of OSA and the major source of the cardiovascular complications associated with this condition. Our previous meta-analyses reported that IH increased arterial pressure, impaired vasodilation, and induced vascular remodeling, with some result heterogeneity related to the researcher networks [9, 24]. The current meta-analysis aimed to further explore the impact of IH patterns and severity on major cellular and molecular mechanisms known to drive the vascular structure/function changes: inflammation, oxidative stress, eNOS (activity or expression), and apoptosis. A second objective of the present work was to verify whether the IH-induced modulation of these mechanisms was dependent on hypoxia duration and/or hypoxic score, and therefore, whether the parameters of the IH protocol substantially impacted the results. As a deepening of our previous meta-analysis of the functional impact of IH on vessels [9], this new meta-analysis does provide valuable insights into the underlying molecular mechanisms that could represent therapeutic options to treat vascular dysfunction in OSA patients.

### 4.1. Impact of IH on the Vascular Molecular Mechanisms Targeted in the Present Meta-Analysis.
Our results show that IH is associated with a significant increase in inflammation (including leukocyte infiltration) and oxidative stress markers in arterial walls of WT rodent models, consistent with systemic inflammation and oxidative stress seen in OSA patients [1, 2, 25, 26]. Despite a low number of studies reducing the level of evidence, in our meta-analysis, IH also significantly increased inflammation in atherosclerotic plaques in ApoE<sup>-/-</sup> mice, supporting previous findings [9] and reinforcing OSA as a major atherosclerosis risk factor [27, 28]. Key inflammation markers such as TNF-α and NF-κB and oxidative markers such as nitrotyrosine residues and NOX expression/activity were
<figure><img src="image_5.png" /><figcaption>FIGURE 3: Intermittent hypoxia increases oxidative stress and apoptosis in systemic vessels of wild type animals. Orchard plots showing standardized mean differences (SMD) for (A) oxidative stress, (B, C) correlation between oxidative stress and total duration of IH exposure (days, slope 0.02, *p* = 0.018) and with hypoxic score (estimate 0.67, *p* = 0.002), respectively. (D) eNOS expression and activity and (E) apoptosis in arterial walls. *k* represents the number of effect sizes per estimate.</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>FIGURE 4: Effect of intermittent hypoxia in ApoE<sup>-/-</sup> mice. Orchard plots showing standardized mean differences (SMD) for (A) inflammation markers, (B) leukocyte infiltration, and (C) oxidative stress. *k* represents the number of effect sizes per estimate. (D) Correlation between leukocyte infiltration and duration of hypoxic phase (slope 0.09, *p* = 0.01).</figcaption></figure>

frequently reported to be increased in vessels or blood of OSA patients [29–33], while antioxidant defenses such as SOD were diminished [34, 35]. In the rodent models and the studies included in the present meta-analysis, the simultaneous rise in oxidative stress and inflammation supports the view of an intertwining of these two mechanisms through mutual stimulation, as widely described in the literature [1, 11, 36]. Moreover, oxidative stress was associated with total duration of exposure to IH and to the hypoxic score, while leukocyte infiltration was associated with $FiO_2$ and duration of exposure. These results point out the impact of the hypoxic load and, in particular, the duration of IH exposure on the stimulation of molecular and cellular mechanisms associated with the progression of cardiovascular disease in OSA. This is consistent with the findings from our previous meta-analysis in rodent models, showing that the increases in mean arterial pressure and intima–media thickness after IH exposure tend to correlate with IH exposure duration [9]. From a technical point of view, our meta-analysis, thus, suggests that experimental designs with longer IH exposure and more severe IH patterns may

be more appropriate to explore OSA–related cardiovascular pathophysiology. In clinical practice, this suggests that the time-course of the disease, which may be hard to evaluate in many newly diagnosed OSA patients, could be an important factor associated with the severity of vascular disease. Our results are also consistent with and strengthen recent findings in patients that the severity of hypoxia—as evaluated by the HB or by the SBII [4–8]—may be the most relevant determinant to evaluate the severity of the cellular, molecular, and functional consequences of OSA on the cardiovascular system.

Regarding NO signaling, the present meta-analysis revealed that IH significantly reduces eNOS expression or activity, consistent with the impaired acetylcholine-induced vasodilation present in IH-exposed mice, as demonstrated in our previous meta-analysis [9]. This also mirrors the clinical finding of reduced NO bioavailability in OSA patients [12, 14, 16]. Hypoxic conditions in OSA contribute to the depletion of the eNOS cofactor tetrahydrobiopterin (BH4) and the eNOS substrate L-arginine, leading to eNOS uncoupling—a state favoring superoxide anion instead of NO production by
were not reported, thus, reducing the quality of the meta-analysis. A sensitivity analysis was performed which demonstrated that exclusion of these studies did not significantly modify the results (Supporting Information 2: Figure S9), suggesting that imputation of the missing SDs did not have an important impact on our findings. Finally, other factors, such as nonreported laboratory conditions and/or author group biases, might also potentially explain some of the heterogeneity observed [24].

Another important point is that, due to the relatively low number of studies for each parameter, we used composite outcomes merging several different molecules, RNA or protein expression, or enzyme activity to compute the impacts on inflammation, oxidative stress, and eNOS, and these pooled composite outcomes may account for some of the variability observed. More generally, our meta-analysis included only a limited number of studies, in particular for ApoE<sup>-/-</sup> mice as well as for leukocyte infiltration and apoptosis in WT mice. The results obtained in ApoE<sup>-/-</sup> mice should, thus, be interpreted with caution and also because only three parameters could be meta-analyzed in this population. More studies are thus needed to gain sufficient statistical power for individual meta-analysis for these parameters. Together with possible biases, interspecies variability, and the rather severe hypoxic protocols used in many studies (corresponding to very severe desaturations when translated to human OSA patients), the significance of some results and the potential translation to the human physiopathological mechanisms related to OSA are limited.

Finally, one of our main objectives was to assess the impact of patterns of IH cycles on the vascular response to IH. However, the variability of the IH protocols between studies was limited with a large number of studies employing alternating 5% FiO₂/30 s–21% FiO₂/30 s for 8 h per day, for 2–8 weeks. Further studies with more variability in IH protocols are, thus, needed to more firmly establish the impact of different IH patterns in rodents on vessel parameters and outcomes.

## 5. Conclusions

Consistent with our previous meta-analysis documenting the impact of IH on vascular functional and structural remodeling, our new work provides robust evidence for a deleterious impact of IH on arterial inflammation, oxidative stress, and eNOS expression. Although this analysis had some limitations, including a low number of studies for some parameters and some potential biases which may moderate the interpretation of our findings, our results highlight the importance IH exposure duration and overall hypoxic score and strongly suggest that IH per se is likely a major contributor to the vascular alterations observed in OSA patients. This meta-analysis further suggests that future improvement of our present understanding of the consequences of IH on the cardiovascular system, and the mechanisms involved, will require additional studies allowing robust comparisons of different hypoxic loads (mainly through variation of IH severities and/or durations) on selected parameters and outcomes. This will require the use of rigorous methodology, following SYRCLE's recommendations

to limit study biases, and both male and female animals to investigate any sex effect.

## Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

## Conflicts of Interest

The authors declare no conflicts of interest.

## Author Contributions

Marc Adrien Reveyaz and Célian Peyronnel should be listed as co-first authors.

## Funding

This work was funded by the University Grenoble Alpes, the INSERM, the Fondation Agir pour les Maladies Chroniques, the Fondation du Souffle, and the Fondation de l'Avenir pour la Recherche Appliquée.

## Acknowledgments

The authors thank Pr Walter A. Boyle III (Washington University School of Medicine, Saint Louis, MO, USA) for English proofreading.

## Supporting Information

Additional supporting information can be found online in the Supporting Information section.

*Supporting Information 1.* This manuscript includes supplementary methods, supplementary results, two supplementary tables, and 9 supplementary figures in attached files.

*Supporting Information 2.* Figure S1: Orchard plot example showing the meaning of the different parts of the plot. Figure S2: Description of the number of studies included for each of the four IH parameters: (A) FiO₂ during hypoxic phase (in %), (B) duration of hypoxic phase (in seconds), (C) duration of IH exposure per day (in hours), (D) duration of reoxygenation (in seconds), and (E) total duration of IH exposure (in days). Figure S3: Forest plots for (A) inflammation markers and (B) leukocyte infiltration in wild type mice. Figure S4: Forest plots for (A) oxidative stress, (B) eNOS activity, and (C) apoptosis in vascular wall in wild type mice. Figure S5: Forest plots for (A) inflammation markers, (B) leukocyte infiltration, and (C) oxidative stress in ApoE<sup>-/-</sup> mice. Figure S6: Risk of study bias analyzed with the SYRCLE tool. For each item, the percentage of studies scored low/unclear/high risk of bias is shown. Figure S7: Funnel plots showing publication bias for the main outcomes: inflammation markers (A), eNOS (B), oxidative stress (C) in WT mice, and leukocyte infiltration in ApoE<sup>-/-</sup> mice (D). The reported *p*-values correspond to the Egger regression test. Figure S8: Tercile distribution of studies and calculation of hypoxic score. The studies were distributed depending on the settings for each of the five hypoxic cycles parameters: (A) FiO₂ during hypoxic phase (in %), (B) duration of each hypoxic
phase (in seconds), (C) duration of IH exposure per day (in hours), (D) total duration of IH exposure (in days), and (E) duration of reoxygenation (seconds). The values were divided into two or three parts based on the calculation of halves or terciles and a score between 1 and 3 was assigned according to the distribution of studies into these two or three parts for the five parameters studied, in order to calculate a hypoxic score (F). Figure S9: Forest plot showing the SMDs for the main outcomes after sensitivity analysis (exclusion of the studies with imputed SD).

*Supporting Information* **3.** Table S1: Full description of included studies, parameters evaluated, and details of hypoxic score calculation.

*Supporting Information* **4.** Table S2: Syr cycle analysis for the risk of bias of included studies.

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