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Article

Impact of Intermittent Hypoxia Related to Obstructive Sleep Apnoea Syndrome on Low-Grade Inflammation in Hypertensive Patients: Potential Implications for Cardiovascular Risk

by
Matthieu Hein
1,2,*,
Benjamin Wacquier
1,
Matteo Conenna
1,
Jean-Pol Lanquart
1 and
Camille Point
1
1
Hôpital Universitaire de Bruxelles, Service de Psychiatrie et Laboratoire du Sommeil, Université Libre de Bruxelles, ULB, 1070 Brussels, Belgium
2
Laboratoire de Psychologie Médicale et Addictologie (ULB312), Université Libre de Bruxelles, ULB, 1020 Brussels, Belgium
*
Author to whom correspondence should be addressed.
Life 2024, 14(5), 592; https://doi.org/10.3390/life14050592
Submission received: 5 April 2024 / Revised: 1 May 2024 / Accepted: 3 May 2024 / Published: 6 May 2024
(This article belongs to the Special Issue Obstructive Sleep Apnea and Related Disorders: Pathophysiological Traits and Strategies for Treatment)
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Versions Notes

Abstract

:
There is evidence for a particular relationship between low-grade inflammation (LGI) and intermittent hypoxia (IH) related to obstructive sleep apnoea syndrome (OSAS). However, despite the potential deleterious cardiovascular consequences associated with this LGI in hypertensive patients, few studies have investigated the impact of IH related to OSAS on CRP levels in this subpopulation. In total, 1404 hypertensive patients were selected retrospectively from the Sleep Laboratory database. CRP levels ≥3 mg/L but <10 mg/L were used as cut-offs to identify hypertensive patients with LGI. Logistic regressions were conducted to examine the risk of LGI associated with IH related to OSAS in hypertensive patients. LGI was frequent (33.8%) in hypertensive patients. After adjustment for confounders, multivariate logistic regressions revealed that only moderate to severe OSAS (apnoea–hypopnoea index ≥ 15/h) with high IH (oxygen desaturation index ≥ 15/h) [OR 1.51 (95% CI 1.06–2.14)] was significantly associated with LGI in hypertensive patients (p-value = 0.045). Consistent with our hypothesis, our results demonstrated the existence of a particular subtype of hypertensive patients at high cardiovascular risk characterised by the presence of LGI induced by IH hypoxia related to moderate to severe OSAS, which justifies the establishment of adequate management of this pathology to allow better cardiovascular prevention in this subpopulation.

1. Introduction

In the literature, there are many arguments in favour of a particular relationship between hypertension and some inflammatory markers such as C-reactive protein (CRP) [1]. Indeed, hypertensive patients have higher CRP levels than normotensive subjects [2]. In addition, the presence of high CRP levels is associated with a higher risk of developing hypertension in the general population, whereas individuals with high CRP levels have greater hypertension-related complications than those with low CRP levels [3,4]. However, in individuals with high CRP levels, the occurrence of this higher risk of developing hypertension and having hypertension-related complications may be explained by the activation of some deleterious pathophysiological mechanisms: alteration of the renin–angiotensin–aldosterone system, plaque remodelling, oxidative stress, endothelial dysfunction, opsonisation of oxidized LDL cholesterol, prothrombotic state, activation of complement cascade and vascular wall damage [5]. Moreover, in hypertensive patients, the presence of high CRP levels appears to be associated with a more frequent development of comorbid cardiovascular diseases and a less favourable cardiovascular outcome [6,7,8] through the occurrence or worsening of some specific complications related to the pathophysiology of hypertension that are deleterious to the cardiovascular system (vascular stiffness, atherosclerosis and end-organ damage) [9]. In addition, it has been shown that the reduction in these high CRP levels following the use of statins and/or some antihypertensive medications may have a beneficial effect in terms of cardiovascular prevention in hypertensive patients [10,11]. Thus, to avoid these deleterious cardiovascular consequences related to high CRP levels (defined in the literature as ≥3 mg/L but <10 mg/L) [12], it seems necessary to identify the conditions associated with the presence of low-grade inflammation in hypertensive patients in order to allow the establishment of better cardiovascular prevention strategies in this particular subpopulation.
In the general population, it has been shown that some sleep disorders are associated with the presence of high CRP levels [13,14,15]. Among these sleep disorders, obstructive sleep apnoea syndrome (OSAS) seems to play a central role in the development of this chronic low-grade inflammation [16,17]. Indeed, sleep alterations specific to OSAS (intermittent hypoxia, excessive sleep fragmentation and sleep deprivation) may promote inadequate activation of the inflammatory cascade inducing the occurrence of high CRP levels [16,17]. However, even if this particular relationship between OSAS and high CRP levels has been demonstrated in the general population [18], there are few data on this specific problem in hypertensive patients despite the frequent co-occurrence between these two pathologies [19,20]. Furthermore, the only studies currently available mainly investigated the impact of OSAS severity (based only on the apnoea–hypopnoea index [AHI]) on CRP levels in hypertensive patients [21,22,23]. However, in the literature, some studies seem to indicate that in the case of OSAS, the polysomnographic parameters related to intermittent hypoxia (such as the oxygen desaturation index [ODI]) could be more specific predictors than the AHI for the presence of high CRP levels [24,25]. Furthermore, alongside this potential central role played in the development of low-grade inflammation, these polysomnographic parameters related to intermittent hypoxia also appear to be directly involved in the activation of other mechanisms harmful to the cardiovascular system (sympathetic hyperexcitation, production of reactive oxygen species, metabolic dysregulation and endothelial dysfunction) [26]. These elements therefore seem to indicate that rather than focusing solely on the AHI, it would also be interesting to study the impact of intermittent hypoxia related to OSAS on CRP levels in hypertensive patients in order to enable a better understanding of less favourable cardiovascular outcomes associated with low-grade inflammation in this particular subpopulation.
This study aimed to investigate the impact of intermittent hypoxia related to OSAS on CRP levels in hypertensive patients. The hypothesis of this study was that unlike other conditions (mild OSAS or moderate to severe OSAS with low intermittent hypoxia), only moderate to severe OSAS with high intermittent hypoxia is significantly associated with low-grade inflammation (CRP levels ≥3 mg/L but <10 mg/L) in hypertensive patients. The goal of this approach was to highlight a particular subtype of hypertensive patients at high cardiovascular risk characterised by the presence of low-grade inflammation induced by high intermittent hypoxia related to moderate to severe OSAS to open new management perspectives for this particular subpopulation.

2. Materials and Methods

2.1. Population

From the database of polysomnographic recordings performed between 1 January 2002 and 31 December 2020 at the Erasme Hospital Sleep Laboratory, 1404 hypertensive patients according to the diagnostic criteria of the World Health Organization were selected retrospectively based on the inclusion and exclusion criteria defined for this study (Table 1) [27,28]. These hypertensive patients had stayed consecutively at the Erasme Hospital Sleep Laboratory to benefit from a complete assessment of their sleep (Figure 1). Only hypertensive patients were recruited in this study because the aim was to focus on this particular subpopulation where cardiovascular outcome may be negatively impacted by the presence of high CRP levels [6,7,8]. The Supplementary Data—Annex S1 contains a detailed description of the recruitment procedure for these hypertensive patients from outpatient sleep medicine consultations to admission for polysomnographic recordings at the Sleep Laboratory.

2.2. Methods

2.2.1. Medical and Psychiatric Assessment

Upon admission to the Sleep Laboratory, all hypertensive patients selected for this study benefited from a complete somatic check-up (clinical interview, review of medical records and complementary tests [blood test, urine analysis, electrocardiogram and electroencephalogram]) in order to screen for their potential medical comorbidities. In addition, during this somatic assessment, repeated measurements of blood pressure and a check of potential antihypertensive medications prescribed were carried out to confirm the diagnosis of hypertension and its status (untreated, controlled and uncontrolled) in all patients selected for this study (Supplementary Data—Annex S2). CRP levels used in this study were defined using blood tests performed during this somatic check-up (Roche CRP4_Cobas with minimum detection level of 0.3 mg/L) [29] in order to exclude patients with CRP levels ≥10 mg/L that may be induced by other pathological conditions (such as infections or inflammatory diseases) [30]. Based on these measured CRP levels, low-grade inflammation was defined as absent when CRP levels were <3 mg/L and as present when CRP levels were ≥3 mg/L but <10 mg/L [31].
Afterwards, to allow identification of their potential psychiatric comorbidities, all hypertensive patients selected for this study benefited from a systematic psychiatric interview based on diagnostic criteria from DSM-IV-TR (before 2013) and DSM 5 (after 2013) by a psychiatrist assigned to the Sleep Laboratory [32,33].
Finally, the subjective complaints of all hypertensive patients selected for this study were assessed using a series of self-questionnaires: Beck Depression Inventory (reduced to 13 items), Epworth Sleepiness Scale and Insomnia Severity Index (Supplementary Data—Annex S3) [34,35,36].

2.2.2. Sleep Evaluation and Study

In all hypertensive patients selected for this study, sleep habits and sleep-related complaints were systematically investigated by a psychiatrist assigned to the Sleep Laboratory during a semi-structured interview to identify potential symptoms suggestive of sleep pathologies. After this specific interview focused on sleep, all these hypertensive patients underwent polysomnographic recording meeting the criteria of the American Academy of Sleep Medicine [37]. The Supplementary Data—Annex S4 contains a detailed description of the stay conditions at the Sleep Laboratory and polysomnography montage used for the recordings. Finally, based on recommendations from the American Academy of Sleep Medicine (Supplementary Data—Annex S5), technical reports for these polysomnographic recordings were produced after visual scoring by specialised technologists [38,39].
Concerning obstructive respiratory events, obstructive apnoeas were scored if the decrease in air flow was ≥90% for at least 10 s, whereas obstructive hypopnoeas were scored if the decrease in airflow was ≥30% for at least 10 seconds with a decrease in oxygen saturation of 3% or followed by micro-arousal [40]. The AHI corresponds to the total number of obstructive apnoeas and hypopnoeas divided by the period of sleep in hours [40]. Concerning the parameters related to intermittent hypoxia, oxygen desaturations were scored if oxygen saturation showed a ≥3% decrease from baseline [40]. The ODI corresponds to the total number of oxygen desaturations divided by the period of sleep in hours [40].
Following this comprehensive sleep assessment, all hypertensive patients selected for this study therefore benefited from a systematic diagnosis of their potential comorbid sleep pathologies: insomnia disorder, OSAS (absent [AHI < 5/h], mild [AHI 5–14/h], moderate to severe [AHI ≥15/h]), intermittent hypoxia (low [ODI < 15/h], high [ODI ≥ 15/h]), moderate to severe periodic limb movement syndrome (periodic limb movement index ≥ 15/h), restless legs syndrome and short sleep duration (<6 h) [41,42,43,44,45,46].

2.3. Statistical Analyses

Statistical analyses were performed using Stata 14. The normal distribution of the data was verified using histograms, boxplots and quantile–quantile plots. The equality of variances was checked using Levene’s test.
During analyses, hypertensive patients without low-grade inflammation (CRP levels < 3 mg/L) were included in the control group and hypertensive patients with low-grade inflammation (CRP levels ≥ 3 mg/L but <10 mg/L) were included in the subject group [12,31].
Continuous data were described by their median (P25–P75) and analysed by Wilcoxon tests (non-parametric tests) since most of these data were not distributed symmetrically. Concerning categorical data, percentages were used for descriptive analyses and Chi² tests for group comparisons.
Univariate logistic regression analyses were used to investigate the risk of low-grade inflammation associated with OSAS status (categorised: no, mild, moderate to severe with low intermittent hypoxia, moderate to severe with high intermittent hypoxia) and potential confounding factors (Supplementary Data—Annex S6). Afterwards, during multivariate logistic regression analyses, risk of low-grade inflammation associated with OSAS status was adjusted only for significant confounding factors during univariate analyses. In order to take into account the potential impact of these confounding factors, risk of low-grade inflammation associated with OSAS status was therefore adjusted after hierarchical introduction:
-
For gender, the presence of obesity and smoking status in model 1.
-
For gender, the presence of obesity, smoking status, presence of type 2 diabetes, presence of dyslipidaemia and aspirin therapy in model 2.
-
For gender, the presence of obesity, smoking status, presence of type 2 diabetes, presence of dyslipidaemia, aspirin therapy and Epworth Sleepiness Scale scores in model 3.
Finally, after this hierarchical introduction of confounding factors significantly associated with low-grade inflammation, the adequacy of the final multivariate model was verified by the Hosmer and Lemeshow test and the specificity of the model by Link Test.
Based on the conditions of use of the multivariate logistic regression analyses characterized by the need to have at least 10 subjects per predictor included in models [47,48], each of the two groups of hypertensive patients for this study had to contain at least 170 subjects (10 subjects * 17 potential predictors) to ensure the validity of the analyses performed, which was largely achieved in this study.
A p-value < 0.05 was considered significant.

2.4. Data Collected

The data collected for this study were sleep latency, sleep efficiency, sleep period time, total sleep time, % stage 1, %stage 2, % stage 3, % REM, % wake after sleep onset, REM latency, number of awakenings, micro-arousal index, apnoea–hypopnoea index, oxygen desaturation index, total time under 90% oxygen, index of periodic limb movements, sex, age, body mass index, systolic blood pressure, diastolic blood pressure, CRP levels, total cholesterol, triglyceride levels, HDL cholesterol levels, blood glucose at admission, smoking, alcohol consumption, caffeine consumption, antihypertensive treatments, antidiabetic treatments, cholesterol-lowering treatments, aspirin therapy, psychiatric history, current psychiatric pathologies, somatic history, current somatic pathologies, history of sleep pathologies, current sleep pathologies, Beck Depression Inventory score (13 items), Epworth Sleepiness Scale score and Insomnia Severity Index score. Only patients without missing data for these different variables were included in this study.

3. Results

The summary of the main results of this study is available in Table 2.

3.1. Polysomnographic Data (Table 3)

Compared to those without low-grade inflammation, hypertensive patients with low-grade inflammation present a decrease in the index of periodic limb movements during sleep (2 [0–12] vs. 1 [0–10], p = 0.033) and an increase in REM latency (84.2 [60.0–132.0] vs. 87.5 [60.9–153.8)], p = 0.036), ODI (3 [1–10] vs. 4 [1–15], p = 0.001) and total time under 90% of oxygen saturation (4.3 [0.0–36.5] vs. 13.0 [0.5–78.0], p < 0.001). There were no significant differences for other polysomnographic parameters.
Table 3. Polysomnographic data (n = 1404).
Table 3. Polysomnographic data (n = 1404).
Whole Sample (n = 1404)Subjects without LGI (n = 929)Subjects with LGI (n = 475)p-Value
Sleep latency (min)26.3 (14.4–50.5)25.0 (14.3–49.0)28.0 (14.7–51.0)0.256
Sleep efficiency (%)76.6 (66.2–83.9)76.8 (66.7–83.9)76.3 (65.2–84.0)0.680
Sleep period time (min)449.5 (408.5–482.8)451.0 (410.5–485.5)445.7 (406.0–478.5)0.173
Total sleep time (min)376.0 (326.4–416.5)379.0 (327.5–418.0)373.0 (322.0–414.5)0.231
% stage 18.1 (5.4–11.5)8.2 (5.6–11.2)7.9 (5.2–11.8)0.470
% stage 254.9 (47.2–61.4)55.0 (47.4–61.3)54.8 (46.2–61.7)0.755
% Stage 32.3 (0.1–7.9)2.3 (0.1–7.6)2.6 (0.2–8.2)0.325
% REM15.5 (10.9–19.3)15.6 (11.3–19.4)15.2 (10.2–19.3)0.115
REM latency (min)85.0 (60.0–137.5)84.2 (60.0–132.0)87.5 (60.9–153.8)0.036
% wake after sleep onset14.0 (8.4–22.6)13.9 (8.4–22.4)14.2 (8.1–23.2)0.987
Number of awakenings32 (22–47)32 (22–47)32 (21–48)0.487
Micro-arousal index13 (8–22)13 (8–21)14 (8–25)0.119
Apnoea–hypopnoea index7 (2–22)7 (2–21)8 (2–28)0.151
Oxygen desaturation index3 (1–11)3 (1–10)4 (1–15)0.001
Total time under 90% of SaO2 (min)6.3 (0.3–49.8)4.3 (0.0–36.5)13.0 (0.5–78.0)<0.001
PLMS index2 (0–11)2 (0–12)1 (0–10)0.033
Median (P25–P75)Median (P25–P75)Median (P25–P75)Wilcoxon test
LGI = low-grade inflammation, REM = rapid eye movement sleep, SaO2 = oxygen saturation, PLMS = periodic limb movements during sleep.

3.2. Univariate Analyses (Table 4)

In our sample, low-grade inflammation was present in 33.8% of hypertensive patients (n = 475). Female gender (p < 0.001), obesity (p < 0.001), smoking (p = 0.018), type 2 diabetes (p < 0.001), dyslipidaemia status (p = 0.001), aspirin therapy (p = 0.021), Epworth Sleepiness Scale scores (p = 0.036) and OSAS status (p = 0.03) were significantly associated with a higher risk of low-grade inflammation in hypertensive patients. Moreover, hypertensive patients with low-grade inflammation had higher body mass indexes (28.4 [25.3–32.1] vs. 32.2 [28.4–37.1], p < 0.001)—CRP levels (1.2 [0.1–1.9] vs. 4.9 [3.8–7.0], p < 0.001)—Epworth Sleepiness Scale scores (9 [5–13] vs. 9 [6–14], p = 0.005) than those without low-grade inflammation. There were no significant differences for other demographic parameters.
Table 4. Univariate analyses (n = 1404).
Table 4. Univariate analyses (n = 1404).
VariablesCategories%Subjects without LGISubjects
with LGI		p-Value
Chi²		OR
(CI 95%)		p-Value
GenderFemale (n = 435)
male (n = 969)		31.0%
69.0%		25.2%
74.8%		42.3%
57.7%		<0.0011
0.46 (0.36 to 0.58)		<0.001
Age (years)<50 (n = 574)
≥50 (n = 830)		40.9%
59.1%		40.8%
59.2%		41.1%
58.9%		0.9261
0.99 (0.79 to 1.24)		0.926
BMI (kg/m²)<30 (n = 738)
≥30 (n = 666)		52.5%
47.5%		62.1%
37.9%		33.9%
66.1%		<0.0011
3.20 (2.54 to 4.03)		<0.001
SmokingNo (n = 1131)
Yes (n = 273)		80.6%
19.4%		82.4%
17.6% 		77.1%
22.9% 		0.0181
1.39 (1.06 to 1.82)		0.018
AlcoholNo (n = 887)
Yes (n = 517)		63.2%
36.8%		62.3%
37.7%		64.8%
35.2%		0.3551
0.90 (0.71 to 1.13)		0.355
CaffeineNo (n = 279)
Yes (n = 1125)		19.9%
80.1%		21.1%
78.9%		17.5%
82.5%		0.1071
1.26 (0.95 to 1.68)		0.108
Type 2 diabetesNo (n = 1106)
Yes (n = 298)		78.8%
21.2%		81.6%
18.4%		73.3%
26.7%		<0.0011
1.62 (1.24 to 2.10)		<0.001
Dyslipidaemia statusNo (n = 526)
Untreated (n = 488)
Treated (n = 390)		37.5%
34.8%
27.7%		37.6%
32.0%
30.4%		37.3%
40.2%
22.5%		0.0011
1.27 (0.98 to 1.64)
0.75 (0.56 to 0.99)		0.001
Hypertension statusUntreated (n = 533)
Controlled (n = 527)
Uncontrolled (n = 344)		38.0%
37.5%
24.5%		39.3%
37.9%
22.8%		35.4%
36.8%
27.8%		0.1041
1.08 (0.84 to 1.40)
1.35 (1.02 to 1.80)		0.104
Number of antihypertensive treatments0 (n = 533)
1 (n = 510)
2 (n = 236)
≥3 (n = 125)		38.0%
36.3%
16.8%
8.9%		39.3%
36.1%
16.6%
8.0%		35.4%
36.8%
17.3%
10.5%		0.3161
1.13 (0.88 to 1.47)
1.16 (0.84 to 1.60)
1.45 (0.97 to 2.16)		0.318
Cardiovascular comorbiditiesNo (n = 1119)
Yes (n = 285)		79.7%
20.3%		79.9%
20.1%		79.4%
20.6%		0.8251
1.03 (0.78 to 1.36)		0.825
Aspirin therapyNo (n = 1084)
Yes (n = 320)		77.2%
22.8%		75.4%
34.6%		80.8%
19.2%		0.0201
0.72 (0.55 to 0.95)		0.021
OSAS statusNo (n = 566)
Mild (n = 362)
Moderate to severe with ODI < 15/h (n = 217)
Moderate to severe without ODI ≥ 15/h (n = 259)		40.3%
25.8%
15.5%
18.4%		40.6%
27.3%
16.3%
15.8%		39.8%
22.7%
13.9%
23.6%		0.0031
0.85 (0.64 to 1.13)
0.87 (0.62 to 1.22)
1.52 (1.12 to 2.05)		0.003
Insomnia disorderNo (n = 469)
Sleep deprivation alone (n = 314)
Insomnia without short sleep duration (n = 367)
Insomnia with short sleep duration (n = 254)		33.4%
22.4%
26.1%
18.1%		34.8%
21.9%
25.7%
17.6%		30.7%
23.4%
27.0%
18.9%		0.5081
1.21 (0.89 to 1.64)
1.18 (0.89 to 1.58)
1.21 (0.88 to 1.68)		0.509
Sleep movement disordersNo (n = 1112)
Moderate to severe PLMs alone (n = 110)
RLS alone or combined with PLMs (n = 182)		79.2%
7.8%
13.0%		78.2%
8.0%
13.8%		81.3%
7.6%
11.1%		0.3251
0.91 (0.60 to 1.39)
0.77 (0.55 to 1.09)		0.326
ESS<11 (n = 843)
≥11 and <14 (n = 245)
≥14 (n = 316)		60.0%
17.5%
22.5%		61.8%
17.8%
20.4%		56.6%
16.8%
26.6%		0.0351
1.03 (0.76 to 1.40)
1.42 (1.08 to 1.85)		0.036
Major depressionNo (n = 783)
Remitted (n = 295)
Current (n = 326)		55.8%
21.0%
23.2%		56.8%
20.8%
22.4%		53.7%
21.5%
24.8%		0.4851
1.09 (0.82 to 1.45)
1.17 (0.90 to 1.54)		0.485
LGINo (n = 929)
Yes (n = 475)		66.2%
33.8%
Median
(P25–P75)		 Wilcoxon test
Age (years)52 (45–60) 53 (45–60)52 (45–59)0.380
BMI (kg/m²)29.6 (26.2–33.8) 28.4 (25.3–32.1)32.2 (28.4–37.1)<0.001
CRP (mg/L)1.9 (1.0–3.8) 1.2 (0.1–1.9)4.9 (3.8–7.0)<0.001
ESS9 (6–13) 9 (5–13)9 (6–14)0.005
ISI14 (9–18) 14 (9–17)14 (10–18)0.164
BDI4 (2–8) 4 (2–8)4 (2–8)0.056
LGI = low-grade inflammation, BMI = body mass index, OSAS = obstructive sleep apnoea syndrome, ODI = oxygen desaturation index, PLMs = periodic limb movements during sleep, RLS = restless legs syndrome, CRP = C-reactive protein, ESS = Epworth Sleepiness Scale, ISI = Insomnia Severity Index, BDI = Beck Depression Inventory.

3.3. Multivariate Analyses (Table 5)

After adjustment by hierarchical introduction of significant confounding factors identified during the univariate analyses, multivariate logistic regression analyses demonstrated that unlike mild OSAS [OR 0.95 (95% CI 0.70–1.30)] and moderate to severe OSAS with low intermittent hypoxia [OR 0.93 (95% CI 0.64–1.35)], only moderate to severe OSAS with high intermittent hypoxia [OR 1.51 (95% CI 1.06–2.14)] was significantly associated with a higher risk of low-grade inflammation in hypertensive patients (p-value = 0.045).
Table 5. Multivariate analyses (n = 1404).
Table 5. Multivariate analyses (n = 1404).
VariablesModel 1
OR Adjusted
(CI 95%)		p-ValueModel 2
OR Adjusted
(CI 95%)		p-ValueModel 3
OR Adjusted
(CI 95%)		p-Value
OSAS
No
Mild
Moderate to severe with ODI < 15/h
Moderate to severe without ODI ≥ 15/h
1
0.92 (0.68 to 1.25)
0.88 (0.61 to 1.27)
1.50 (1.06 to 2.13)		0.023
1
0.95 (0.70 to 1.30)
0.93 (0.64 to 1.34)
1.51 (1.06 to 2.14)		0.041
1
0.95 (0.70 to 1.30)
0.93 (0.64 to 1.35)
1.51 (1.06 to 2.14)		0.045
Model 1 = model adjusted for gender, BMI and smoking. Model 2 = model adjusted for gender, BMI, smoking, type 2 diabetes, dyslipidaemia and aspirin therapy. Model 3 = model adjusted for gender, BMI, smoking, type 2 diabetes, dyslipidaemia, aspirin therapy and ESS scores. BMI = body mass index, OSAS = obstructive sleep apnoea syndrome, ODI = oxygen desaturation index.

4. Discussion

In our study, we highlighted that in hypertensive patients, the prevalence of low-grade inflammation (CRP levels ≥3 mg/L but <10 mg/L) was 33.8%, which seems to indicate that this problem is more important in this particular subpopulation than in the general population (17.6–21.6%) [49,50]. However, in hypertensive patients, the presence of some specific pathophysiological mechanisms favouring inadequate activation of the inflammatory cascade (activation of complement, change in the phenotype of circulating immune cells and activation of inflammasome) could provide a better understanding of this difference in the prevalence of low-grade inflammation with the general population [51]. Moreover, this prevalence is higher than that of 21.1% highlighted by Iwashima et al. (2007) [52] and lower than that of 50.2% demonstrated by Cortez et al. (2016) [6], which could be explained by the application of different inclusion and exclusion criteria in these two studies. First, in the study of Iwashima et al. (2007) [52], individuals with secondary hypertension were excluded. However, the application of this exclusion criteria may have led to an underestimation of the prevalence of low-grade inflammation since some of the most frequent causes of secondary hypertension (such as OSAS) are associated with alterations in inflammatory mechanisms characterized by the occurrence of high CRP levels [21,53]. Second, in the study of Cortez et al. (2016) [6], the main inclusion criterion was the presence of resistance to antihypertensive medications. However, the application of this inclusion criterion may have favoured an overestimation of the prevalence of low-grade inflammation since some of the pathophysiological alterations related to high CRP levels (alteration of the renin–angiotensin–aldosterone system, oxidative stress and endothelial dysfunction) seem to play a major role in the development of resistance to antihypertensive medications [5,54,55]. Furthermore, consistent with the limited data available in the literature, the prevalence of low-grade inflammation demonstrated in our study is similar to that highlighted by Rizzo et al. (2009) (34.7%) and Zdrojewski et al. (2006) (32.0%) [56,57], which seems to confirm that low-grade inflammation is present in about a third of hypertensive patients. However, in this particular subpopulation, the presence of low-grade inflammation is associated with less favourable cardiovascular prognosis, which justifies the implementation of adequate cardiovascular prevention strategies to avoid these deleterious cardiovascular consequences related to high CRP levels in hypertensive patients [58].
Furthermore, we demonstrated that the prevalence of OSAS was 59.7% in our sample of hypertensive patients, which seems to confirm the frequent occurrence of this pathology in this particular subpopulation [59]. Yet, consistent with the literature, we highlighted that mild OSAS was not associated with the presence of a low-grade inflammation level in hypertensive patients. Indeed, in this particular subpopulation, there are arguments in favour of a potential implication of OSAS severity in the occurrence of low-grade inflammation since only moderate to severe OSAS seems to be associated with the presence of high CRP levels in hypertensive patients [20,21]. However, similarly to some subpopulations [60,61,62], this assessment of OSAS severity based solely on the AHI does not appear to be a sufficiently specific predictor for the presence of low-grade inflammation in hypertensive patients. Indeed, in our study, we demonstrated that, unlike moderate to severe OSAS with high intermittent hypoxia, moderate to severe OSAS with low intermittent hypoxia is not associated with low-grade inflammation in hypertensive patients, which seems to confirm that rather than focusing solely on the AHI, it is also necessary to take into account the polysomnographic markers related to intermittent hypoxia (such as the ODI) when assessing the impact of OSAS severity on CRP levels [60,61,62]. In addition, in hypertensive patients with moderate to severe OSAS, this central role played by intermittent hypoxia in the occurrence of low-grade inflammation could be explained by the fact that unlike hypopnoeas associated with micro-arousals, only hypopnoeas associated with oxygen desaturation appear to be involved in the development of cardiovascular risk factors [63]. Pathophysiologically, this occurrence of low-grade inflammation associated only with obstructive respiratory events inducing intermittent hypoxia may explain the activation of several deleterious mechanisms (induction of oxidative stress, reactive oxygen species production, activation of critical proinflammatory transcription factors, elevated expression of proinflammatory cytokines and chemokines, recruitment and infiltration of proinflammatory M1 macrophages) favouring inadequate activation of the inflammatory cascade [16,17,64]. Thus, in this study, we demonstrated the existence of a particular subtype of hypertensive patients at high cardiovascular risk characterised by the presence of low-grade inflammation induced by high intermittent hypoxia related to moderate to severe OSAS, which justifies systematic screening for this pathology in hypertensive patients with low-grade inflammation [65].
Among the treatments currently available, continuous positive airway pressure (CPAP) involves air that is pressurised by an electronic device and delivered during sleep via a nasal or orinasal mask, acting as a pneumatic stent of the airway that suppresses the hypoxic episodes related to OSAS [66]. Moreover, in the literature, it has been shown that in hypertensive patients with moderate to severe OSAS, the adequate use of CPAP (≥4 h per night) could allow a better cardiovascular outcome through an indirect improvement in atherosclerosis following the inhibition of inflammatory processes (such as high CRP levels) related to OSAS [67,68]. Furthermore, alongside this adequate use of CPAP (≥4 h per night), the duration of CPAP treatment could also play a major role in reducing cardiovascular risk for hypertensive patients with moderate to severe OSAS since, according to available studies, CRP levels appear to show a significant reduction after only a minimum of 3 months of CPAP treatment [69,70]. Moreover, complementary to this CPAP treatment in hypertensive patients with moderate to severe OSAS, the establishment of both lifestyle changes (such as weight loss in the case of overweight or obesity, smoking cessation, reduced alcohol consumption and regular physical activity) and appropriate antihypertensive therapy is essential in order to avoid the maintenance of pathophysiological mechanisms favouring the persistence of low-grade inflammation in this particular subpopulation [71,72]. Thus, in this particular subtype of hypertensive patients at high cardiovascular risk highlighted in our study, the implementation of effective combined treatments for hypertension and moderate to severe OSAS with high intermittent hypoxia (adequate treatment with CPAP [≥4 h per night and ≥3 months] combined with lifestyle changes and appropriate management of hypertension) seems to be fundamental in order to enable better cardiovascular outcomes through a reduction in low-grade inflammation induced by this pathology [73].

Limitations

Since the design of our study was retrospective, the results obtained must be confirmed by carrying out future prospective studies. In addition, since this study focused only on hypertension, its results cannot be generalised to other cardiovascular pathologies. Furthermore, despite the existence of other potential markers of low-grade inflammation, we decided to use CRP because this molecule is one of the most frequently used for patients with cardiovascular diseases and presents validated cut-offs to easily assess its potential impact on cardiovascular risk [31,74]. Finally, in order to avoid as much as possible any risk of selection bias during retrospective recruitment for this study, all hypertensive patients eligible according to the inclusion and exclusion criteria were included. Nevertheless, despite this systematic inclusion, only hypertensive patients who stayed consecutively at the Erasme Hospital Sleep Laboratory between 1 January 2002 and 31 December 2020 are present in our database, which may potentially limit the generalization of our results to all hypertensive patients.

5. Conclusions

In this study, we highlighted that low-grade inflammation is a frequent problem (33.8%) in hypertensive patients. Moreover, we demonstrated the existence of a particular subtype of hypertensive patients at high cardiovascular risk characterised by the presence of low-grade inflammation (CRP levels ≥ 3 mg/L but <10 mg/L) induced by high intermittent hypoxia related to moderate to severe OSAS. These results seem to indicate that adequate management (diagnosis and treatment) of moderate to severe OSAS with high intermittent hypoxia is essential in hypertensive patients to allow better cardiovascular outcomes. Finally, future prospective studies must be conducted to confirm the results of our study and to allow the development of new therapeutic strategies more specific to this particular subgroup of hypertensive patients.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/life14050592/s1, Annex S1: Procedure for outpatient recruitment of hypertensive patients; Annex S2: Blood pressure measurement method; Annex S3: Description of self-questionnaires; Annex S4: Stay conditions at the Sleep Laboratory and applied polysomnography montage; Annex S5: Scoring criteria for periodic limb movements; Annex S6: Description of the confounding factors included in the univariate analyses.

Author Contributions

Conceptualization: M.H. and C.P.; methodology: M.H., B.W., M.C., J.-P.L. and C.P.; formal analysis: M.H., M.C. and C.P.; investigation: M.H. and C.P.; software: B.W. and J.-P.L.; data curation: M.H., B.W., M.C., J.-P.L. and C.P.; writing—original draft preparation: M.H., B.W., M.C., J.-P.L. and C.P.; supervision: C.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of Erasme Hospital (Reference: P2023/552—Submission date: 12 December 2023—Approval date: 16 January 2024).

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on reasonable request from the corresponding author.

Acknowledgments

This study would not have been possible without the support of the technical staff from the Erasme Hospital Sleep Laboratory.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

AHIapnoea–hypopnoea index
CPAPcontinuous positive airway pressure
CRPC-reactive protein
DSMDiagnostic and Statistical Manual of Mental Disorders
ODIoxygen desaturation index
OSASobstructive sleep apnoea syndrome

References

  1. Xiao, L.; Harrison, D.G. Inflammation in Hypertension. Can. J. Cardiol. 2020, 36, 635–647. [Google Scholar] [CrossRef] [PubMed]
  2. Kanclerska, J.; Wieckiewicz, M.; Nowacki, D.; Szymanska-Chabowska, A.; Poreba, R.; Mazur, G.; Martynowicz, H. Sleep architecture and vitamin D in hypertensives with obstructive sleep apnea: A polysomnographic study. Dent. Med. Probl. 2024, 61, 43–52. [Google Scholar] [CrossRef] [PubMed]
  3. Jayedi, A.; Rahimi, K.; Bautista, L.E.; Nazarzadeh, M.; Zargar, M.S.; Shab-Bidar, S. Inflammation markers and risk of developing hypertension: A meta-analysis of cohort studies. Heart 2019, 105, 686–692. [Google Scholar] [CrossRef]
  4. Hage, F.G. C-reactive protein and hypertension. J. Hum. Hypertens. 2014, 28, 410–415. [Google Scholar] [CrossRef]
  5. Adukauskienė, D.; Čiginskienė, A.; Adukauskaitė, A.; Pentiokinienė, D.; Šlapikas, R.; Čeponienė, I. Clinical relevance of high sensitivity C-reactive protein in cardiology. Medicina 2016, 52, 1–10. [Google Scholar] [CrossRef] [PubMed]
  6. Cortez, A.F.; Muxfeldt, E.S.; Cardoso, C.R.; Salles, G.F. Prognostic Value of C-Reactive Protein in Resistant Hypertension. Am. J. Hypertens. 2016, 29, 992–1000. [Google Scholar] [CrossRef]
  7. Liu, H.H.; Cao, Y.X.; Sun, D.; Jin, J.L.; Zhang, H.W.; Guo, Y.L.; Zhu, C.G.; Wu, N.Q.; Gao, Y.; Dong, Q.T.; et al. High-sensitivity C-reactive protein and hypertension: Combined effects on coronary severity and cardiovascular outcomes. Hypertens. Res. 2019, 42, 1783–1793. [Google Scholar] [CrossRef]
  8. Maio, R.; Perticone, M.; Suraci, E.; Sciacqua, A.; Sesti, G.; Perticone, F. Endothelial dysfunction and C-reactive protein predict the incidence of heart failure in hypertensive patients. ESC Heart Fail. 2021, 8, 399–407. [Google Scholar] [CrossRef]
  9. Silvestre-Roig, C.; Braster, Q.; Ortega-Gomez, A.; Soehnlein, O. Neutrophils as regulators of cardiovascular inflammation. Nat. Rev. Cardiol. 2020, 17, 327–340. [Google Scholar] [CrossRef]
  10. Kim-Mitsuyama, S.; Soejima, H.; Yasuda, O.; Node, K.; Jinnouchi, H.; Yamamoto, E.; Sekigami, T.; Ogawa, H.; Matsui, K. Reduction in hsCRP levels is associated with decreased incidence of cardiovascular events in Japanese hypertensive women but not in men. Sci. Rep. 2020, 10, 17040. [Google Scholar] [CrossRef]
  11. Fang, M.; Qian, Q.; Zhao, Z.; Zhu, L.; Su, J.; Li, X. High-Sensitivity C-Reactive Protein Combined with Low-Density Lipoprotein Cholesterol as the Targets of Statin Therapy in Patients with Acute Coronary Syndrome. Int. Heart J. 2018, 59, 300–306. [Google Scholar] [CrossRef] [PubMed]
  12. Amezcua-Castillo, E.; González-Pacheco, H.; Sáenz-San Martín, A.; Méndez-Ocampo, P.; Gutierrez-Moctezuma, I.; Massó, F.; Sierra-Lara, D.; Springall, R.; Rodríguez, E.; Arias-Mendoza, A.; et al. C-Reactive Protein: The Quintessential Marker of Systemic Inflammation in Coronary Artery Disease-Advancing toward Precision Medicine. Biomedicines 2023, 11, 2444. [Google Scholar] [CrossRef] [PubMed]
  13. Imani, M.M.; Sadeghi, M.; Farokhzadeh, F.; Khazaie, H.; Brand, S.; Dürsteler, K.M.; Brühl, A.; Sadeghi-Bahmani, D. Evaluation of Blood Levels of C-Reactive Protein Marker in Obstructive Sleep Apnea: A Systematic Review, Meta-Analysis and Meta-Regression. Life 2021, 11, 362. [Google Scholar] [CrossRef] [PubMed]
  14. Zhang, Y.; Zhao, W.; Liu, K.; Chen, Z.; Fei, Q.; Ahmad, N.; Yi, M. The causal associations of altered inflammatory proteins with sleep duration, insomnia and daytime sleepiness. Sleep 2023, 46, zsad207. [Google Scholar] [CrossRef]
  15. Jiménez-Jiménez, F.J.; Alonso-Navarro, H.; García-Martín, E.; Agúndez, J.A.G. Inflammatory factors and restless legs syndrome: A systematic review and meta-analysis. Sleep Med. Rev. 2023, 68, 101744. [Google Scholar] [CrossRef] [PubMed]
  16. Lv, R.; Liu, X.; Zhang, Y.; Dong, N.; Wang, X.; He, Y.; Yue, H.; Yin, Q. Pathophysiological mechanisms and therapeutic approaches in obstructive sleep apnea syndrome. Signal Transduct. Target. Ther. 2023, 8, 218. [Google Scholar] [PubMed]
  17. Alterki, A.; Abu-Farha, M.; Al Shawaf, E.; Al-Mulla, F.; Abubaker, J. Investigating the Relationship between Obstructive Sleep Apnoea, Inflammation and Cardio-Metabolic Diseases. Int. J. Mol. Sci. 2023, 24, 6807. [Google Scholar] [CrossRef] [PubMed]
  18. Van der Touw, T.; Andronicos, N.M.; Smart, N. Is C-reactive protein elevated in obstructive sleep apnea? a systematic review and meta-analysis. Biomarkers 2019, 24, 429–435. [Google Scholar] [CrossRef]
  19. Willame, H.; Wacquier, B.; Point, C.; Dosogne, M.; Al Faker, M.; Loas, G.; Hein, M. The association between type 2 diabetes and anhedonic subtype of major depression in hypertensive individuals. J. Clin. Hypertens. 2022, 24, 156–166. [Google Scholar] [CrossRef] [PubMed]
  20. Hein, M.; Wacquier, B.; Lanquart, J.P.; Loas, G. Risk of Cardiovascular Disease in Apnoeic Individuals: Role of Comorbid Insomnia Disorder. Life 2022, 12, 944. [Google Scholar] [CrossRef]
  21. Li, F.; Huang, H.; Song, L.; Hao, H.; Ying, M. Effects of Obstructive Sleep Apnea Hypopnea Syndrome on Blood Pressure and C-Reactive Protein in Male Hypertension Patients. J. Clin. Med. Res. 2016, 8, 220–224. [Google Scholar] [CrossRef] [PubMed]
  22. Thomopoulos, C.; Tsioufis, C.; Dimitriadis, K.; Tsiachris, D.; Tousoulis, D.; Manolis, A.; Alchanatis, M.; Kallikazaros, I.; Stefanadis, C. Obstructive sleep apnoea syndrome is associated with enhanced sub-clinical inflammation and asymmetric dimethyl-arginine levels in hypertensives. J. Hum. Hypertens. 2009, 23, 65–67. [Google Scholar] [CrossRef] [PubMed]
  23. Qian, X.; Yin, T.; Li, T.; Kang, C.; Guo, R.; Sun, B.; Liu, C. High levels of inflammation and insulin resistance in obstructive sleep apnea patients with hypertension. Inflammation 2012, 35, 1507–1511. [Google Scholar] [CrossRef] [PubMed]
  24. Wang, J.; Xu, H.; Guo, C.; Duan, X.; Hu, F.; Yang, W.; Cui, J.; Song, L.; Chun, Y.; Yuan, J.; et al. Association between severity of obstructive sleep apnea and high-sensitivity C-reactive protein in patients with hypertrophic obstructive cardiomyopathy. Clin. Cardiol. 2020, 43, 803–811. [Google Scholar] [CrossRef]
  25. Fukuoka, R.; Kohno, T.; Kohsaka, S.; Yanagisawa, R.; Kawakami, T.; Hayashida, K.; Kanazawa, H.; Yuasa, S.; Maekawa, Y.; Sano, M.; et al. Nocturnal intermittent hypoxia and short sleep duration are independently associated with elevated C-reactive protein levels in patients with coronary artery disease. Sleep Med. 2017, 29, 29–34. [Google Scholar] [CrossRef] [PubMed]
  26. Więckiewicz, M.; Lavigne, G.; Martynowicz, H. Decrypting the putative interrelation between sleep bruxism, masticatory muscle pain and sleep breathing disorders: Nosology and the role of hypoxia. Dent. Med. Probl. 2024, 61, 165–167. [Google Scholar] [CrossRef] [PubMed]
  27. Mills, K.T.; Bundy, J.D.; Kelly, T.N.; Reed, J.E.; Kearney, P.M.; Reynolds, K.; Chen, J.; He, J. Global disparities of hypertension prevalence and control: A systematic analysis of population-based studies from 90 countries. Circulation 2016, 134, 441–450. [Google Scholar] [CrossRef] [PubMed]
  28. Draelants, L.; Point, C.; Wacquier, B.; Lanquart, J.P.; Loas, G.; Hein, M. 10-Year Risk for Cardiovascular Disease Associated with COMISA (Co-Morbid Insomnia and Sleep Apnea) in Hypertensive Subjects. Life 2023, 13, 1379. [Google Scholar] [CrossRef] [PubMed]
  29. Bernier, V.; Debarge, M.H.; Hein, M.; Ammendola, S.; Mungo, A.; Loas, G. Major Depressive Disorder, Inflammation, and Nutrition: A Tricky Pattern? Nutrients 2023, 15, 3438. [Google Scholar] [CrossRef] [PubMed]
  30. Pearson, T.A.; Mensah, G.A.; Alexander, R.W.; Anderson, J.L.; Cannon, R.O.; Criqui, M.; Fadl, Y.Y.; Fortmann, S.P.; Hong, Y.; Myers, G.L.; et al. Markers of inflammation and cardiovascular disease: Application to clinical and public health practice: A statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation 2003, 107, 499–511. [Google Scholar] [CrossRef]
  31. Castro, A.R.; Silva, S.O.; Soares, S.C. The Use of High Sensitivity C-Reactive Protein in Cardiovascular Disease Detection. J. Pharm. Pharm. Sci. 2018, 21, 496–503. [Google Scholar] [CrossRef] [PubMed]
  32. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 4th ed.; Text Rev; American Psychiatric Publishing: Arlington, VA, USA, 2000. [Google Scholar]
  33. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 5th ed.; American Psychiatric Publishing: Washington, DC, USA, 2013. [Google Scholar]
  34. Beck, A.T.; Steer, R.A.; Ball, R.; Ranieri, W. Comparison of Beck Depression Inventories -IA and -II in psychiatric outpatients. J. Pers. Assess. 1996, 67, 588–597. [Google Scholar] [CrossRef]
  35. Johns, M.W. A new method for measuring daytime sleepiness: The Epworth sleepiness scale. Sleep 1991, 14, 540–545. [Google Scholar] [CrossRef] [PubMed]
  36. Morin, C.M. Insomnia: Psychological Assessment and Management; Guilford Press: New York, NY, USA, 1993. [Google Scholar]
  37. Kushida, C.A.; Littner, M.R.; Morgenthaler, T.; Alessi, C.A.; Bailey, D.; Coleman, J.; Friedman, L.; Hirshkowitz, M.; Kapen, S.; Kramer, M.; et al. Practice Parameters for the Indications for Polysomnography and Related Procedures: An Update for 2005. Sleep 2005, 28, 499–521. [Google Scholar] [CrossRef] [PubMed]
  38. Iber, C.; Ancoli-Israel, S.; Chesson, A.; Quan, S.F.; for the American Academy of Sleep Medicine. The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications, 1st ed.; American Academy of Sleep Medicine: Westchester, IL, USA, 2007. [Google Scholar]
  39. Ferri, R.; Koo, B.B.; Picchietti, D.L.; Fulda, S. Periodic leg movements during sleep: Phenotype, neurophysiology, and clinical significance. Sleep Med. 2017, 31, 29–38. [Google Scholar] [CrossRef] [PubMed]
  40. Berry, R.B.; Budhiraja, R.; Gottlieb, D.J.; Gozal, D.; Iber, C.; Kapur, V.K.; Marcus, C.L.; Mehra, R.; Parthasarathy, S.; Quan, S.F.; et al. Rules for scoring respiratory events in sleep: Update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events. Deliberations of the Sleep Apnea Definitions Task Force of the American Academy of Sleep Medicine. J. Clin. Sleep Med. 2012, 8, 597–619. [Google Scholar] [CrossRef] [PubMed]
  41. Edinger, J.D.; Bonnet, M.H.; Bootzin, R.R.; Doghramji, K.; Dorsey, C.M.; Espie, C.A.; Jamieson, A.O.; McCall, W.V.; Morin, C.M.; Stepanski, E.J.; et al. Derivation of research diagnostic criteria for insomnia: Report of an American Academy of Sleep Medicine Work Group. Sleep 2004, 27, 1567–1596. [Google Scholar] [CrossRef] [PubMed]
  42. Fleetham, J.; Ayas, N.; Bradley, D.; Ferguson, K.; Fitzpatrick, M.; George, C.; Hanly, P.; Hill, F.; Kimoff, J.; Kryger, M.; et al. Canadian Thoracic Society guidelines: Diagnosis and treatment of sleep disordered breathing in adults. Can. Respir. J. 2006, 13, 387–392. [Google Scholar] [CrossRef]
  43. Muraki, I.; Tanigawa, T.; Yamagishi, K.; Sakurai, S.; Ohira, T.; Imano, H.; Kitamura, A.; Kiyama, M.; Sato, S.; Shimamoto, T.; et al. Nocturnal intermittent hypoxia and C reactive protein among middle-aged community residents: A cross-sectional survey. Thorax 2010, 65, 523–527. [Google Scholar] [CrossRef]
  44. Haba-Rubio, J.; Marti-Soler, H.; Tobback, N.; Andries, D.; Marques-Vidal, P.; Vollenweider, P.; Preisig, M.; Heinzer, R. Clinical significance of periodic limb movements during sleep: The HypnoLaus study. Sleep Med. 2018, 41, 45–50. [Google Scholar] [CrossRef]
  45. Allen, R.P.; Picchietti, D.L.; Garcia-Borreguero, D.; Ondo, W.G.; Walters, A.S.; Winkelman, J.W.; Zucconi, M.; Ferri, R.; Trenkwalder, C.; Lee, H.B.; et al. Restless legs syndrome/Willis-Ekbom disease diagnostic criteria: Updated International Restless Legs Syndrome Study Group (IRLSSG) consensus criteria--history, rationale, description, and significance. Sleep Med. 2014, 15, 860–873. [Google Scholar] [CrossRef] [PubMed]
  46. Hein, M.; Lanquart, J.P.; Loas, G.; Hubain, P.; Linkowski, P. Insomnia with short sleep duration as risk factor for type 2 diabetes: A systematic review of the literature. Rev. Med. Brux. 2020, 41, 98–104. [Google Scholar] [CrossRef]
  47. Peduzzi, P.; Concato, J.; Feinstein, A.R.; Holford, T.R. Importance of events per independent variable in proportional hazards regression analysis. II. Accuracy and precision of regression estimates. J. Clin. Epidemiol. 1995, 48, 1503–1510. [Google Scholar] [CrossRef] [PubMed]
  48. Peduzzi, P.; Concato, J.; Kemper, E.; Holford, T.R.; Feinstein, A.R. A simulation study of the number of events per variable in logistic regression analysis. J. Clin. Epidemiol. 1996, 49, 1373–1379. [Google Scholar] [CrossRef] [PubMed]
  49. Delongui, F.; Kallaur, A.P.; Oliveira, S.R.; Bonametti, A.M.; Grion, C.M.; Morimoto, H.K.; Simão, A.N.; Magalhães, G.G.; Reiche, E.M. Serum levels of high sensitive C reactive protein in healthy adults from southern Brazil. J. Clin. Lab. Anal. 2013, 27, 207–210. [Google Scholar] [CrossRef] [PubMed]
  50. Vu, T.H.; Liu, K.; Lloyd-Jones, D.M.; Stamler, J.; Pirzada, A.; Shah, S.J.; Garside, D.B.; Daviglus, M.L. Favorable Levels of All Major Cardiovascular Risk Factors at Younger Ages and High-Sensitivity C-Reactive Protein 39 Years Later—The Chicago Healthy Aging Study. Prev. Med. Rep. 2015, 2, 235–240. [Google Scholar] [CrossRef] [PubMed]
  51. Aboukhater, D.; Morad, B.; Nasrallah, N.; Nasser, S.A.; Sahebkar, A.; Kobeissy, F.; Boudaka, A.; Eid, A.H. Inflammation and hypertension: Underlying mechanisms and emerging understandings. J. Cell. Physiol. 2023, 238, 1148–1159. [Google Scholar] [CrossRef] [PubMed]
  52. Iwashima, Y.; Horio, T.; Kamide, K.; Rakugi, H.; Ogihara, T.; Kawano, Y. C-reactive protein, left ventricular mass index, and risk of cardiovascular disease in essential hypertension. Hypertens. Res. 2007, 30, 1177–1185. [Google Scholar] [CrossRef] [PubMed]
  53. Rossi, G.P.; Bisogni, V.; Rossitto, G.; Maiolino, G.; Cesari, M.; Zhu, R.; Seccia, T.M. Practice Recommendations for Diagnosis and Treatment of the Most Common Forms of Secondary Hypertension. High Blood Press. Cardiovasc. Prev. 2020, 27, 547–560. [Google Scholar]
  54. Barbaro, N.R.; Fontana, V.; Modolo, R.; De Faria, A.P.; Sabbatini, A.R.; Fonseca, F.H.; Anhê, G.F.; Moreno, H. Increased arterial stiffness in resistant hypertension is associated with inflammatory biomarkers. Blood Press. 2015, 24, 7–13. [Google Scholar] [CrossRef]
  55. Hwang, A.Y.; Dietrich, E.; Pepine, C.J.; Smith, S.M. Resistant Hypertension: Mechanisms and Treatment. Curr. Hypertens. Rep. 2017, 19, 56. [Google Scholar] [CrossRef] [PubMed]
  56. Rizzo, M.; Corrado, E.; Coppola, G.; Muratori, I.; Mezzani, A.; Novo, G.; Novo, S. The predictive role of C-reactive protein in patients with hypertension and subclinical atherosclerosis. Intern. Med. J. 2009, 39, 539–545. [Google Scholar] [CrossRef] [PubMed]
  57. Zdrojewski, T.; Chwojnicki, K.; Bandosz, P.; Konarski, R.; Wyrzykowski, B. Distribution of C-reactive protein and its relation to arterial hypertension in a country representing a high-risk region for cardiovascular diseases. Blood Press. 2006, 15, 20–26. [Google Scholar] [CrossRef] [PubMed]
  58. Virdis, A.; Dell’Agnello, U.; Taddei, S. Impact of inflammation on vascular disease in hypertension. Maturitas 2014, 78, 179–183. [Google Scholar] [CrossRef] [PubMed]
  59. Hein, M.; Lanquart, J.P.; Hubain, P.; Loas, G. Risk of resistant hypertension associated with restless legs syndrome and periodic limb movements during sleep: A study on 673 treated hypertensive individuals. Sleep Med. 2019, 63, 46–56. [Google Scholar] [CrossRef] [PubMed]
  60. Svensson, M.; Venge, P.; Janson, C.; Lindberg, E. Relationship between sleep-disordered breathing and markers of systemic inflammation in women from the general population. J. Sleep Res. 2012, 21, 147–154. [Google Scholar] [CrossRef] [PubMed]
  61. Arnardottir, E.S.; Maislin, G.; Schwab, R.J.; Staley, B.; Benediktsdottir, B.; Olafsson, I.; Juliusson, S.; Romer, M.; Gislason, T.; Pack, A.I. The interaction of obstructive sleep apnea and obesity on the inflammatory markers C-reactive protein and interleukin-6: The Icelandic Sleep Apnea Cohort. Sleep 2012, 35, 921–932. [Google Scholar] [CrossRef] [PubMed]
  62. Gouveris, H.; Bahr, K.; Jahn, C.; Matthias, C.; Simon, P. The Apnea-Hypopnea Index Underestimates Systemic Inflammation in Women with Sleep-Disordered Breathing. J. Women’s Health 2018, 27, 920–926. [Google Scholar]
  63. Punjabi, N.M.; Newman, A.B.; Young, T.B.; Resnick, H.E.; Sanders, M.H. Sleep-disordered breathing and cardiovascular disease: An outcome-based definition of hypopneas. Am. J. Respir. Crit. Care Med. 2008, 177, 1150–1155. [Google Scholar] [CrossRef] [PubMed]
  64. Lavalle, S.; Masiello, E.; Iannella, G.; Magliulo, G.; Pace, A.; Lechien, J.R.; Calvo-Henriquez, C.; Cocuzza, S.; Parisi, F.M.; Favier, V.; et al. Unraveling the Complexities of Oxidative Stress and Inflammation Biomarkers in Obstructive Sleep Apnea Syndrome: A Comprehensive Review. Life 2024, 14, 425. [Google Scholar] [CrossRef]
  65. Archontogeorgis, K.; Nena, E.; Papanas, N.; Steiropoulos, P. Biomarkers to improve diagnosis and monitoring of obstructive sleep apnea syndrome: Current status and future perspectives. Pulm. Med. 2014, 2014, 930535. [Google Scholar] [CrossRef]
  66. Hein, M.; Mungo, A.; Hubain, P.; Loas, G. Excessive daytime sleepiness in adolescents: Current treatment strategies. Sleep Sci. 2020, 13, 157–171. [Google Scholar]
  67. Jin, F.; Liu, J.; Zhang, X.; Cai, W.; Zhang, Y.; Zhang, W.; Yang, J.; Lu, G.; Zhang, X. Effect of continuous positive airway pressure therapy on inflammatory cytokines and atherosclerosis in patients with obstructive sleep apnea syndrome. Mol. Med. Rep. 2017, 16, 6334–6339. [Google Scholar] [CrossRef] [PubMed]
  68. Panoutsopoulos, A.; Kallianos, A.; Kostopoulos, K.; Seretis, C.; Koufogiorga, E.; Protogerou, A.; Trakada, G.; Kostopoulos, C.; Zakopoulos, N.; Nikolopoulos, I. Effect of CPAP treatment on endothelial function and plasma CRP levels in patients with sleep apnea. Med. Sci. Monit. 2012, 18, CR747–CR751. [Google Scholar] [CrossRef] [PubMed]
  69. Guo, Y.; Pan, L.; Ren, D.; Xie, X. Impact of continuous positive airway pressure on C-reactive protein in patients with obstructive sleep apnea: A meta-analysis. Sleep Breath. 2013, 17, 495–503. [Google Scholar] [CrossRef] [PubMed]
  70. Xie, X.; Pan, L.; Ren, D.; Du, C.; Guo, Y. Effects of continuous positive airway pressure therapy on systemic inflammation in obstructive sleep apnea: A meta-analysis. Sleep Med. 2013, 14, 1139–1150. [Google Scholar] [CrossRef] [PubMed]
  71. Cai, A.; Wang, L.; Zhou, Y. Hypertension and obstructive sleep apnea. Hypertens. Res. 2016, 39, 391–395. [Google Scholar] [CrossRef]
  72. Parati, G.; Lombardi, C.; Hedner, J.; Bonsignore, M.R.; Grote, L.; Tkacova, R.; Lévy, P.; Riha, R.; Bassetti, C.; Narkiewicz, K.; et al. Recommendations for the management of patients with obstructive sleep apnoea and hypertension. Eur. Respir. J. 2013, 41, 523–538. [Google Scholar] [CrossRef] [PubMed]
  73. Hopps, E.; Caimi, G. Obstructive Sleep Apnea Syndrome: Links Between Pathophysiology and Cardiovascular Complications. Clin. Investig. Med. 2015, 38, E362–E370. [Google Scholar] [CrossRef]
  74. Gupta, L.; Thomas, J.; Ravichandran, R.; Singh, M.; Nag, A.; Panjiyar, B.K. Inflammation in Cardiovascular Disease: A Comprehensive Review of Biomarkers and Therapeutic Targets. Cureus 2023, 15, e45483. [Google Scholar] [CrossRef]
Life 14 00592 g001
Figure 1. Selection diagram of hypertensive patients included in this study.
Figure 1. Selection diagram of hypertensive patients included in this study.
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Table 1. Inclusion and exclusion criteria.
Table 1. Inclusion and exclusion criteria.
Inclusion CriteriaExclusion Criteria
Hypertension according to the diagnostic criteria of the World Health Organization: mean systolic blood pressure ≥140 mmHg or mean diastolic blood pressure ≥90 mmHg or self-reported diagnosis of clinically demonstrated hypertension or taking antihypertensive medicationAcute and/or uncontrolled hepatic, pancreatic, pulmonary, cardiovascular, renal or infectious diseases
Age ≥ 18 years oldPast or current severe psychiatric diseases (psychotic disorder, bipolar disorder and substance use disorder)
CRP levels < 10 mg/LPast or current cancer, autoimmune or inflammatory diseases
Absence of pregnancyPast or current malformation or lesion (head trauma, lesions of cerebral respiratory centres, craniofacial malformations and abnormal chest deformities)
Central disorders of hypersomnolence, OSAS already known or course of treatment before Sleep Laboratory and sleep apnoea syndrome with predominantly central component
CRP = C-reactive protein, OSAS = obstructive sleep apnoea syndrome.
Table 2. Summary of main results.
Table 2. Summary of main results.
AnalysesResults
Comparison of polysomnographic parametersHypertensive patients with low-grade inflammation have higher parameters related to intermittent hypoxia (oxygen desaturation index and total time under 90% of oxygen saturation) than those without low-grade inflammation.
Prevalence of low-grade inflammation in hypertensive individuals 33.8%
Univariate analyses Confounding factors identified: gender, body mass index, smoking, type 2 diabetes, dyslipidaemia status, aspirin therapy and Epworth Sleepiness Scale scores.
Multivariate analysesUnlike mild OSAS and moderate to severe OSAS with low intermittent hypoxia, only moderate to severe OSAS with high intermittent hypoxia was significantly associated with higher risk of low-grade inflammation in hypertensive patients after adjustment for confounding factors.
OSAS = obstructive sleep apnoea syndrome.
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MDPI and ACS Style

Hein, M.; Wacquier, B.; Conenna, M.; Lanquart, J.-P.; Point, C. Impact of Intermittent Hypoxia Related to Obstructive Sleep Apnoea Syndrome on Low-Grade Inflammation in Hypertensive Patients: Potential Implications for Cardiovascular Risk. Life 2024, 14, 592. https://doi.org/10.3390/life14050592

AMA Style

Hein M, Wacquier B, Conenna M, Lanquart J-P, Point C. Impact of Intermittent Hypoxia Related to Obstructive Sleep Apnoea Syndrome on Low-Grade Inflammation in Hypertensive Patients: Potential Implications for Cardiovascular Risk. Life. 2024; 14(5):592. https://doi.org/10.3390/life14050592

Chicago/Turabian Style

Hein, Matthieu, Benjamin Wacquier, Matteo Conenna, Jean-Pol Lanquart, and Camille Point. 2024. "Impact of Intermittent Hypoxia Related to Obstructive Sleep Apnoea Syndrome on Low-Grade Inflammation in Hypertensive Patients: Potential Implications for Cardiovascular Risk" Life 14, no. 5: 592. https://doi.org/10.3390/life14050592

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