
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

71883
10.1038/s41598-024-71883-5
Article
Association between obstructive sleep apnea and 24-h urine protein quantification in patients with hypertension
Liu Miaomiao
Heizhati Mulalibieke
Li Nanfang lnanfang2016@sina.com

Gan Lin
Cai Li
Yuan Yujuan
Yao Ling
Li Mei
Li Xiufang
Aierken Xiayire
Wang Hui
Maitituersun Adalaiti
Nuermaimaiti Qiaolifanayi
Nusufujiang Aketiliebieke
Hong Jing
Jiang Wen
https://ror.org/02r247g67 grid.410644.3 Hypertension Center of People’s Hospital of Xinjiang Uygur Autonomous Region; Xinjiang Hypertension Institute; NHC Key Laboratory of Hypertension Clinical Research; Key Laboratory of Xinjiang Uygur Autonomous Region “Hypertension Research Laboratory”; Xinjiang Clinical Medical Research Center for Hypertension (Cardio-Cerebrovascular) Diseases, Address: No. 91 Tianchi Road, Urumqi, 830001 Xinjiang China
6 9 2024
6 9 2024
2024
14 2087614 5 2024
2 9 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
The association between obstructive sleep apnea (OSA) and proteinuria is undetermined, with few studies on hypertension, a high-risk group for renal impairment. Therefore, we aimed to explore whether OSA is an independent risk factor for proteinuria in patients with hypertension. We investigated the cross-sectional association between OSA and proteinuria. Participants were divided into groups by apnea hypopnea index (AHI) category. Multivariable Logistic regression analysis was used to evaluate the association between OSA severity, objectively measured sleep dimensions, and proteinuria which is mainly defined by 24-h urine protein quantification > 300 mg/24 h. Sensitivity analyses were performed by excluding those with comorbidities (primary aldosteronism and homocysteine ≥ 15 μmol/L). Of the 2106 participants, the mean age was 47.57 ± 10.50 years, 67.2% were men, and 75.9% were OSA patients. In total participants, compared with those without OSA, patients with mild OSA, moderate OSA, and severe OSA showed 1.09 (95% CI 0.80–1.40), 1.24 (95% CI 0.89–1.74) and 1.47 (95% CI 1.04–2.08) fold risk for proteinuria with a trend test P trend < 0.05. Each 10-unit increase in the AHI, oxygen desaturation index (ODI), and time spent with oxygen saturation < 90% (T90) was found to be associated with 13%, 10%, and 2% higher likelihood of proteinuria in the crude model, significant in adjusted models. The more severe the OSA is, the higher the risk of proteinuria. AHI and T90 are independently associated with a higher risk of structural renal damage in the population with hypertension.

Keywords

Obstructive sleep apnea
Proteinuria
Hypertension
Subject terms

Cardiovascular diseases
Kidney diseases
Science & Technology Department of Xinjiang Uygur Autonomous Region2022A03012-3 Jiang Wen issue-copyright-statement© Springer Nature Limited 2024
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pmcIntroduction

The debate over the association of obstructive sleep apnea (OSA) with chronic kidney disease (CKD) is a long-standing one, focusing primarily on OSA’s detrimental effects on renal function and structure. The former has a huge number of cross-sectional studies, many longitudinal studies, several systematic reviews, and meta-analyses suggesting OSA can be a risk factor for decreased renal function. In contrast, the latter, that is, whether OSA can cause clinically significant proteinuria, is still in question1. Currently, there are three perspectives on the link between OSA and proteinuria/microalbuminuria. First, the limited epidemiological studies have directly noticed a connection between the two2–5. Second, pathophysiologic researches provide possible mechanisms for OSA-induced renal tissue damage, including sympathetic nervous system overdrive, activation of the renin–angiotensin–aldosterone system, arteries stiffness, atherosclerosis, subclinical inflammation, endothelial dysfunction and glomerular hypertension/hyperfiltration6–9. Third, from a treatment perspective, different types of research articles report a significant reduction or even reversal of proteinuria/albuminuria in patients with OSA after treatment with continuous positive airway pressure10–12. However, there is still a lot of ground to explore the connection between OSA and proteinuria on two issues: (1) There are confounding factors in the study population that could lead to false-positive results, such as hypertension, diabetes mellitus, and obesity, which are high-risk groups for proteinuria; (2) The majority of studies do not use 24-h urine protein quantification as the gold standard for proteinuria.

It is worth noting that the prevalence of renal damage is higher in patient groups with hypertension, or metabolic syndrome13–15. The hypertension associated with OSA is of particular significance because hypertension is a major established risk factor for CKD, particularly in proteinuric CKD16. Given the high prevalence of OSA among patients with hypertension and vice versa16,17, the coexistence of hypertension and OSA may further increase the risk of proteinuria than when present alone, through mechanisms such as intermittent hypoxia, endothelial dysfunction, activation of sympathetic nervous and the renin–angiotensin–aldosterone systems, and increased oxidative stress18,19. However, few studies explored this.

In this study, to test the hypothesis that OSA could be independently associated with the risk of proteinuria in patients with hypertension, we conducted a cross-sectional study in patients with hypertension and suspected OSA who completed polysomnography (PSG), exploring the association of OSA severity and multiple, objectively measured sleep dimensions with 24-h urine protein quantification.

Materials and methods

Study population

We used baseline data from the UROSAH cohort. Methods of this longitudinal study have been described in detail elsewhere20. In this sub-study, we further excluded: (1) patients who had pre-existing kidney disease history of acute renal failure, chronic kidney disease, chronic glomerulonephritis, nephrotic syndrome, urinary calculus, urinary tract infection, neoplasm of kidney and hydronephrosis; (2) patients with other diseases that can cause abnormal urine protein including systemic lupus erythematosus, arteritis, pneumonia and abnormal thyroid function; (3) patients with eGFR < 60 mL/min per 1.73 m2 using the 2009 Chronic Kidney Disease Epidemiology Collaboration creatinine (CKD-EPI) equation21; (4) patients lacking of 24-h urine protein excretion or 24-h urine microalbuminuria.

Data collection

Participants completed a baseline examination between 2011 and 2013, including the demographics: age, gender, office blood pressure (SBP, DBP), 24-h ambulatory blood pressure measurement (ABPM), body mass index (BMI), neck circumference (NC), abdominal circumference (AC), cigarette consumption and alcohol intake (categorized as never, past, and current); medical history: years since hypertension diagnosis, diabetes mellitus, cardiovascular diseases, cerebrovascular disease, primary aldosteronism (PA); biochemical measurements: blood hemoglobin (Hb), high sensitivity C-reactive protein (hs-CRP), homocysteine (Hcy), blood urea nitrogen (BUN), uric acid (UA), serum creatinine (Scr), total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), fasting plasma glucose (FPG), alanine aminotransferase (ALT), aspartate aminotransferase (AST); medication history: antihypertensive agents, anti-diabetic agents, anti-platelet agents, lipid regulating agents.

The details of anthropometric measurements (height, weight, neck circumference, abdominal circumference, SBP, and DBP) and laboratory assays were described in a previously published article20. BMI was calculated as weight divided by the square of height (kg/m2). ABPM was recorded by a Mobil-O-Graph NG device (IEM, Stolberg, Germany). The device was applied to the non-dominant arm for 24 h. BP was measured every 30 min during daytime, and every 60 min at nighttime. Patients were instructed to maintain their usual activities during monitoring, and to stay calm when the device started to work.

Exposure ascertainment

All participants underwent in-laboratory overnight PSG (Compumedics E series, Australia) examination and were usually required to refrain from caffeine, alcohol, or sedative-hypnotic drugs on the day of monitoring, consistent with previous studies22. The sleep monitoring rooms are single chambers that are both comfortable and non-disturbing. They are equipped with sound insulation, light protection, and an adjustable room temperature (18–25 °C). Each room is equipped with a separate sleep equipment computer and a network interface is connected to each monitoring room to receive real-time sleep monitoring data. PSG evaluation included monitoring airflow with nasal pressure and/or thermocouples, respiratory effort with piezoelectric bands at abdominal and chest locations, oxygen saturation measurement with pulse oximetry, surface electrodes connected with standard techniques to obtain chin electromyography and electrooculography. Interpretation of PSG results was performed by a sleep technologist with the license of American Academy of Sleep Medicine (AASM).

Definitions of sleep parameters were based on 2009 clinical guideline of AASM23. Apnea hypopnea index (AHI) was defined as the total number of hypopneas and apneas that occurred per hour of sleep. OSA was defined as an AHI ≥ 5 events per hour, and 5 ≤ AHI < 15, 15 ≤ AHI < 30 and AHI ≥ 30 events per hour were defined as mild, moderate and severe OSA, respectively. The observed parameters for sleep were (1) AHIREM: AHI in a rapid eye movement (REM) stage; (2) AHINREM: AHI in a non-REM stage; (3) Average duration of apnea/hypopnea: average duration of apnea/hypopnea during the total sleep time; (4) Maximum duration of apnea/hypopnea: maximum duration of apnea/hypopnea during the total sleep time; (5) ODI (oxygen desaturation index): the number of oxygen desaturation of ≥ 4% per hour sleep; (6) MSpO2: mean oxygen saturation during the total sleep time; (7) LSpO2: lowest oxygen saturation during the total sleep time; (8) T90: time spent with oxygen saturation < 90% during the total sleep time; (9) TST (total sleep time): the total number of sleeping minutes from ‘lights off’ to ‘lights on’; (10) SE (sleep efficiency): ratio of total sleep time to bed time expressed as a percentage; (11) WASO (wake period after sleep onset: the periods of wakefulness occurring after sleep onset; (12) According to the AASM sleep staging standard, the human sleep process can be divided into three main parts: Wakefulness (Wake), rapid eye movement (REM), and non-rapid eye movement (NREM) which is further divided into three stages (NREM-1, NREM-2, NREM-3).

Outcome ascertainment

For the collection of 24 h urine specimen, all participants were provided a 24-h urine collection container and instructed to discard their first morning’s urine sample and to begin collecting total urine samples immediately thereafter for the following 24 h. Urine specimens are stored at standard refrigerator settings, ranging from 2 to 8 degrees Celsius. None of the collected urine specimens had a pH value < 3 or > 9. Renal damage was defined as 24-h urine protein quantification > 150 mg/24 h (Of the 460 people who developed proteinuria, 23 were identified by 24-h urine microalbuminuria > 30 mg/24 h).

Statistical analysis

Continuous variables were presented as mean ± SD or median (interquartile range) according to the normality test and categorical variables were summarized as numbers and percentages. Statistical significance of differences in baseline characteristics and sleep parameters were assessed according to AHI categories using ANOVA tests, signed-rank tests, or chi-square tests, accordingly.

Before building a multi-variable logistic regression model, the uni-variable logistic regression (Sup. Table S1) was used to screen for variables affecting the outcome and the collinearity between variables was evaluated according to the tolerance and variance inflation factor (VIF). Variables with tolerance < 0.1 or VIF > 10 were considered inappropriate for inclusion in the logistic regression model. Moreover, the least absolute shrinkage and selection operator (LASSO) regression was used to obtain adjusted set (Sup. Figs. S1 and S2). LASSO regression was often used to screen multidimensional variables; some variables were eliminated because they were not associated with proteinuria or because they had strongly collinearity with other variables24. Eventually, two models were constructed to determine the independent predictive value of OSA for renal damage. Model 1 was adjusted for age, gender, SBP, DBP, abdominal circumference, HDL, LDL-C, fasting blood glucose, serum creatinine, homocysteine, cerebrovascular disease, No. of antihypertensive agents, anti-diabetic agents, and anti-platelet agents. Model 2 was adjusted for age, gender, ASBP, ADBP, abdominal circumference, HDL, LDL-C, fasting blood glucose, serum creatinine, homocysteine, cerebrovascular disease, No. of antihypertensive agents, anti-diabetic agents, and anti-platelet agents.

We also performed sensitivity analyses to evaluate the robustness of our results by excluding patients with primary aldosteronism and Hcy ≥ 15 μmol/L. Statistical analyses were performed using Statistical Package for the Social Sciences (SPSS) version 26.0 and R version 4.2.0.

Results

Of 3605 participants in UROSAH, 2106 comprised the current analytical sample as given in Fig. 1.Fig. 1 Flow chart of ascertainment of the study subjects.

Characteristics of the study population

As in Table 1, participants with OSA tended to have lower eGFR and HDL-L and have older age, higher office and 24 h SBP and DBP, BMI, NC, AC, Hb, hsCRP, BUN, UA, TC, TG, LDL-C, FPG, ALT, and longer duration of hypertension. In addition, compared with non-OSA group, OSA group showed higher proportion of male, smokers, drinkers, diabetes, cardiovascular diseases, cerebrovascular disease, and taking antihypertensive agents, anti-diabetic agents, anti-platelet agents, and lipid regulating agents.Table 1 Baseline characteristics of the study participants.

	Overall	AHI < 5	5 ≤ AHI < 15	15 ≤ AHI < 30	AHI ≥ 30	P value	
N	2106	508	644	495	459		
Age (years)	47.57 ± 10.50	43.66 ± 10.33	47.87 ± 9.85	49.58 ± 10.59	49.29 ± 10.33	 < 0.001	
Male sex (n, %)	1482 (67.2)	297 (55.9)	428 (63.4)	374 (72.2)	383 (79.5)	 < 0.001	
Systolic blood pressure (mmhg)	139.22 ± 18.49	137.44 ± 16.87	138.86 ± 19.19	140.40 ± 18.71	140.44 ± 18.80	0.024	
Diastolic blood pressure (mmhg)	92.07 ± 13.45	91.89 ± 12.15	91.57 ± 13.81	91.87 ± 14.38	93.18 ± 13.24	0.216	
24 h-hour SBP (mmhg)	133.35 ± 14.63	130.85 ± 13.77	132.39 ± 13.65	134.55 ± 15.47	136.13 ± 15.37	 < 0.001	
24 h-hour DBP (mmhg)	85.67 ± 10.02	85.14 ± 9.80	84.86 ± 9.35	85.90 ± 10.64	87.15 ± 10.35	0.001	
Body mass index (kg/m2)	27.86 ± 3.80	26.36 ± 3.44	27.57 ± 3.47	28.32 ± 3.74	29.45 ± 3.97	 < 0.001	
Neck circumference (cm)	39.91 ± 3.73	38.56 ± 3.41	39.62 ± 3.39	40.33 ± 3.88	41.37 ± 3.79	 < 0.001	
Abdominal circumference (cm)	99.11 ± 10.70	93.83 ± 10.12	98.25 ± 9.91	101.10 ± 9.94	103.98 ± 10.41	 < 0.001	
Cigarette consumption (current, n,%)	682 (30.9)	129 (24.3)	206 (30.5)	170 (32.8)	177 (36.7)	 < 0.001	
Alcohol intake (current, n, %)	704 (31.9)	143 (26.9)	202 (29.9)	169 (32.6)	190 (39.4)	 < 0.001	
Years since hypertension diagnosis	3.00 (0.75, 7.00)	2.00 (0.33, 6.00)	3.00 (0.67, 7.00)	3.00 (1.00, 7.00)	4.00 (1.00, 10.00)	 < 0.001	
Diabetes mellitus (n, %)	549 (24.9)	86 (16.2)	162 (24.0)	134 (25.9)	167 (34.6)	 < 0.001	
Cardiovascular diseases (n, %)	200 (9.1)	33 (6.2)	61 (9.0)	53 (10.2)	53 (11.0)	0.041	
Cerebrovascular disease (n, %)	421 (19.1)	75 (14.1)	120 (17.8)	114 (22.0)	112 (23.2)	0.001	
Primary aldosteronism (n, %)	264 (12.0)	48 (9.0)	82 (12.1)	70 (13.5)	64 (13.3)	0.098	
Blood hemoglobin (g/dl)	142.80 ± 14.80	140.29 ± 15.15	141.83 ± 14.43	143.43 ± 14.98	146.24 ± 14.05	 < 0.001	
HsCRP (mg/L)	1.97 (0.88, 3.66)	1.59 (0.65, 3.33)	1.97 (0.90, 3.53)	2.13 (0.92, 3.67)	2.19 (1.18, 4.20)	 < 0.001	
Homocysteine (mmol/L)	14.78 (11.03, 19.34)	14.70 (10.37, 20.81)	14.78 (11.29, 19.57)	14.78 (11.30, 18.34)	14.78 (11.36, 19.36)	0.757	
Blood urea nitrogen (mg/dL)	5.00 (4.17, 5.90)	4.74 (3.92, 5.64)	5.00 (4.17, 5.96)	5.11 (4.37, 6.06)	5.08 (4.31, 5.94)	 < 0.001	
Uric acid (μmol/L)	340.0 (279.3, 396.0)	316.8 (255.9, 376.2)	336.4 (279.1, 387.0)	342.0 (282.0, 403.6)	362.0 (309.0, 417.6)	 < 0.001	
Serum creatinine (μmol/L)	73.51 ± 14.49	70.92 ± 13.72	72.82 ± 14.45	74.75 ± 14.96	75.99 ± 14.34	 < 0.001	
eGFR (mL/min/1.73 m2)	99.09 ± 13.44	102.63 ± 13.58	98.89 ± 13.04	97.29 ± 13.28	97.41 ± 13.32	 < 0.001	
Total cholesterol (mmol/L)	4.45 [3.87, 5.04]	4.39 [3.66, 4.91]	4.50 [3.96, 5.09]	4.47 [3.88, 4.98]	4.45 [3.91, 5.10]	0.001	
Triglyceride (mmol/L)	1.69 [1.22, 2.35]	1.53 [1.08, 2.03]	1.69 [1.23, 2.34]	1.78 [1.30, 2.39]	1.83 [1.35, 2.66]	 < 0.001	
HDL-C (mmol/L)	1.07 [0.92, 1.26]	1.10 [0.95, 1.32]	1.07 [0.92, 1.24]	1.07 [0.92, 1.27]	1.03 [0.88, 1.20]	 < 0.001	
LDL-C (mmol/l)	2.59 [2.11, 3.11]	2.53 [2.00, 2.99]	2.66 [2.17, 3.20]	2.59 [2.14, 3.06]	2.59 [2.14, 3.15]	0.001	
Fasting plasma glucose (mmol/L)	5.19 ± 1.36	4.96 ± 1.24	5.12 ± 1.33	5.26 ± 1.30	5.47 ± 1.54	 < 0.001	
ALT (U/L)	23.00 (17.00, 33.00)	22.00 (15.00, 30.50)	23.00 (17.00, 33.00)	23.00 (17.00, 33.00)	24.00 (18.00, 36.00)	 < 0.001	
AST (U/L)	19.00 (16.00, 24.00)	19.00 (16.00, 23.00)	19.00 (17.00, 25.00)	19.00 (16.25, 24.00)	20.00 (17.00, 25.00)	0.073	
Antihypertensive agents	1549 (73.6)	345 (67.9)	476 (73.9)	373 (75.4)	355 (77.3)	0.006	
 ACEIs or ARBs (n, %)	681 (32.3)	153 (30.1)	213 (33.1)	170 (34.3)	145 (31.6)	0.507	
 β-blockers (n,%)	222 (10.5)	45 (8.9)	68 (10.6)	57 (11.5)	52 (11.3)	0.508	
 Calcium channel blockers (n, %)	1216 (57.7)	250 (49.2)	379 (58.9)	290 (58.6)	297 (64.7)	 < 0.001	
 Diuretics (n, %)	108 (5.1)	22 (4.3)	30 (4.7)	23 (4.6)	33 (7.2)	0.158	
No. of antihypertensive agents (≥ 2, n, %)	979 (46.5)	191 (37.6)	288 (44.7)	246 (49.7)	254 (55.3)	 < 0.001	
Anti-diabetic agents (n, %)	184 (8.7)	27 (5.3)	52 (8.1)	47 (9.5)	58 (12.6)	0.001	
Anti-platelet agents (n, %)	370 (17.6)	69 (13.6)	111 (17.2)	97 (19.6)	93 (20.3)	0.025	
Lipid regulating agents (n, %)	431 (20.5)	75 (14.8)	132 (20.5)	116 (23.4)	108 (23.5)	0.001	
OSA obstructive sleep apnea, SBP systolic blood pressure, DBP diastolic blood pressure, HsCRP high sensitivity C-reactive protein, eGFR estimated glomerular filtration rate, HDL-C high density lipoprotein cholesterol, LDL-C low density lipoprotein cholesterol, ALT alanine transaminase, AST aspartate transaminase, ACEIs angiotensin converting enzyme inhibitors, ARBs angiotensin receptor blockers, No. numbers.

Sleep parameters and proteinuria for the study population

Participants with proteinuria had a substantially higher AHI (including AHIREM and AHINREM), ODI, and lower MSpO2 and LSpO2 when comparing sleep parameters to those study subjects without proteinuria (Sup. Table S2).

As given in Table 2, participants with severe OSA tended to have higher proportion of proteinuria and higher 24-h urine protein quantification. The percentage of the number of people with proteinuria in the mild, moderate, and severe OSA groups was 19.9%, 22.8%, and 27.9%, respectively. The 24-h urine protein quantification increased as OSA severity increased, with 73.00 mg/24 h (44.00, 122.75) in mild OSA, 77.00 mg/24 h (46.00, 130.50) in moderate OSA, and 82.50 mg/24 h (49.00, 150.00) in severe OSA, respectively.Table 2 Sleep parameters and proteinuria for the study participants.

	Overall	AHI < 5	5 ≤ AHI < 15	15 ≤ AHI < 30	AHI ≥ 30	P value	
N	2106	508	644	495	459		
Proteinuria (yes, %)	460 (21.8)	91 (17.9)	128 (19.9)	113 (22.8)	128 (27.9)	0.001	
24-h urine protein (mg/24 h)	73.00 (44.00, 126.00)	60.00 (40.00, 101.25)	73.00 (44.00, 122.75)	77.00 (46.00, 130.50)	82.50 (49.00, 150.00)	 < 0.001	
AHI (times/h)	12.60 (5.20, 27.10)	1.60 (0.70, 3.00)	8.90 (6.60, 11.50)	20.35 (17.42, 25.00)	45.40 (34.92, 59.08)	 < 0.001	
AHIREM (times/h)	3.03 (0.85, 6.77)	0.42 (0.00, 1.19)	2.84 (1.31, 4.44)	4.91 (2.68, 8.17)	8.67 (5.04, 12.05)	 < 0.001	
AHINREM (times/h)	7.98 (2.48, 20.12)	0.76 (0.25, 1.63)	5.60 (3.74, 8.01)	15.04 (11.29, 19.16)	36.72 (27.12, 49.04)	 < 0.001	
Average duration of apnea (min)	15.90 (10.30, 20.30)	0.00 (0.00, 13.90)	15.00 (9.50, 18.50)	17.25 (14.60, 21.30)	20.90 (17.67, 25.22)	 < 0.001	
Average duration of hypopnea (min)	19.70 (17.60, 22.20)	17.40 (15.30, 19.80)	19.60 (18.00, 21.90)	20.50 (18.50, 22.80)	21.20 (18.80, 24.00)	 < 0.001	
Max duration of apnea (min)	23.60 (12.70, 36.50)	0.00 (0.00, 16.00)	19.70 (12.20, 28.80)	27.50 (20.00, 38.65)	42.75 (30.00, 58.12)	 < 0.001	
Max duration of hypopnea (min)	34.30 (26.10, 44.40)	22.30 (17.90, 28.00)	31.70 (26.60, 38.50)	38.45 (32.60, 46.80)	45.70 (38.27, 55.65)	 < 0.001	
ODI (times/hour)	16.18 (7.15, 32.03)	4.46 (2.08, 7.43)	12.37 (8.89, 16.53)	24.77 (19.72, 30.75)	52.68 (40.39, 70.52)	 < 0.001	
MSpO2 (%)	92.43 (3.40)	94.17 (1.59)	92.75 (3.03)	91.99 (3.84)	90.52 (3.73)	 < 0.001	
LSpO2 (%)	80.37 (9.05)	87.82 (4.80)	82.50 (5.14)	78.12 (6.83)	71.57 (10.60)	 < 0.001	
T90 (min)	10.37 (1.15, 51.25)	0.37 (0.00, 1.57)	6.68 (2.06, 19.68)	21.40 (8.84, 54.15)	76.42 (34.02, 141.13)	 < 0.001	
TST (min)	378.50 (335.62, 419.88)	378.00 (334.88, 419.62)	377.00 (335.50, 418.62)	374.00 (337.00, 414.75)	384.50 (335.50, 429.50)	0.232	
SE (%)	71.10 (62.30, 79.40)	71.00 (62.05, 79.25)	71.20 (62.75, 78.90)	69.30 (61.52, 78.30)	73.15 (62.87, 81.07)	0.006	
NREM1 (min)	6.20 (4.20, 8.80)	5.35 (3.77, 7.93)	5.80 (3.90, 8.10)	6.70 (4.50, 9.90)	7.50 (4.80, 10.80)	 < 0.001	
NREM2 (min)	63.70 (57.60, 70.10)	62.50 (56.65, 69.00)	63.30 (57.20, 70.10)	64.20 (58.20, 70.00)	65.10 (58.60, 71.10)	0.001	
NREM3 (min)	10.50 (3.50, 17.60)	12.35 (5.20, 19.40)	11.70 (4.30, 18.28)	9.85 (3.25, 16.70)	7.35 (1.00, 14.45)	 < 0.001	
REM (min)	18.10 (14.10, 21.70)	18.50 (14.80, 22.00)	18.30 (14.30, 21.80)	18.00 (14.00, 21.70)	17.35 (13.00, 21.10)	0.010	
WASO (min)	64.50 (36.00, 104.50)	62.50 (35.00, 100.50)	62.50 (36.00, 102.50)	72.00 (40.00, 112.00)	61.50 (32.50, 104.62)	0.060	
AHI apnea–hypopnea index, REM rapid eye movement sleep, AHIREM AHI during REM, NREM non-rapid eye movement sleep, ODI oxygen desaturation index, MSpO2 mean oxygen saturation, LSpO2 lowest oxygen saturation, T90 time spent with oxygen saturation < 90%, TST total sleep time, SE sleep efficiency, WASO wake period after sleep onset.

Association between sleep parameters and proteinuria

Table 3 showed that with increasing severity of OSA, the risk of proteinuria increased, and this trend was observed in the crude model and model 1 with a trend test P-trend < 0.05, in the model 2 with nearly significance.Table 3 Multi-logistic regression analysis for association of OSA and sleep parameters with proteinuria. (OR, 95% CI, P).

	Crude Model	Model 1	Model 2	
OSA severity	
 Non-OSA	1	1	1	
 Mild OSA	1.14, 0.84–1.53, 0.400	1.09, 0.80–1.50, 0.595	1.06, 0.78–1.46, 0.704	
 Moderate OSA	1.36, 1.00–1.85, 0.054	1.24, 0.89–1.74, 0.208	1.18, 0.84–1.66, 0.340	
 Severe OSA	1.77, 1.31–2.40, < 0.001	1.47, 1.04–2.08, 0.030	1.37, 0.97–1.94, 0.079	
 P for trend*	 < 0.001	0.018	0.051	
AHI (times/hour) (per 1 unit increase)	1.01, 1.01–1.02, < 0.001	1.01, 1.00–1.01, 0.003	1.01, 1.00–1.01, 0.009	
AHI (times/hour) (per 5 unit increase)	1.06, 1.04–1.09, < 0.001	1.04, 1.02–1.07, 0.002	1.04, 1.01–1.07, 0.008	
AHI (times/hour) (per 10 unit increase)	1.13, 1.07–1.18, < 0.001	1.09, 1.03–1.15, 0.004	1.08, 1.02–1.14, 0.012	
ODI (times/hour) (per 1 unit increase)	1.01, 1.01–1.01, < 0.001	1.01, 1.00–1.01, 0.011	1.01, 1.00–1.01, 0.046	
ODI (times/hour) (per 10 unit increase)	1.10, 1.06–1.15, < 0.001	1.07, 1.02–1.12, 0.007	1.05, 1.00–1.10, 0.032	
MSpO2 (%) (per 1 unit increase)	0.97, 0.94–1.00, 0.040	0.99, 0.96–1.02, 0.415	0.99, 0.96–1.02, 0.538	
LSpO2 (%) (per 1 unit increase)	0.98, 0.97–0.99, 0.001	0.99, 0.98–1.00, 0.040	0.99, 0.98–1.00, 0.135	
LSpO2 (%) (per 5 unit decrease)	1.09, 1.04–1.16, 0.001	1.06, 1.00–1.12, 0.065	1.04, 0.98–1.11, 0.200	
T90 (minutes) (per 1 unit increase)	1.00, 1.00–1.00, < 0.001	1.00, 1.00–1.00, 0.022	1.00, 1.00–1.00, 0.041	
T90 (minutes) (per 10 unit increase)	1.02, 1.01–1.03, < 0.001	1.02, 1.00–1.03, 0.018	1.01, 1.00–1.03, 0.033	
Model 1: age, gender, SBP, DBP, abdominal circumference, HDL-C, LDL-C, fasting blood glucose, serum creatinine, homocysteine, cerebrovascular disease, and No. of antihypertensive agents, anti-diabetic agents, and anti-platelet agents.

Model 2: age, gender, ASBP, ADBP, abdominal circumference, HDL-C, LDL-C, fasting blood glucose, serum creatinine, homocysteine, cerebrovascular disease, and No. of antihypertensive agents, anti-diabetic agents, and anti-platelet agents.

*Test for trend based on variable containing median value for each quintile.

In hypertensive patients, each 10-unit increase in the AHI and ODI was found to be associated with a 13% and 10% higher likelihood of proteinuria in the crude model, significant in adjusted models. During the total sleep time, for each 10-min extension of time spent with oxygen saturation < 90%, the risk of proteinuria mildly increased 1–2%. Patients with a greater reduction in the lowest oxygen saturation showed a 1.09 (95% CI 1.04–1.16) fold risk for proteinuria in the crude model, compared to their counterparts, but this result was not statistically significant after adjusting for Model 1 and 2.

Subgroup analyses

Patients with age < 45 years old, male gender, BMI ≥ 28 kg/m2, history of DM, the duration of hypertension > 5 years, and hypertension stage III showed 1.14 (95% CI 1.05–1.24, P = 0.003), 1.07 (1.00–1.13, P = 0.045), 1.09 (1.02–1.17, P = 0.014), 1.11 (1.02–1.22, P = 0.022), 1.11 (1.02–1.21, P = 0.015), and 1.11 (1.02–1.21, P = 0.013) fold risk for proteinuria for each 10 additional unit of AHI adjusted in Model 3 (Table 4).Table 4 Stratification analysis of association between AHI (per 10 unit increase) and proteinuria. (OR, 95% CI, P).

	Crude Model	Model1	Model2	
Age	
 < 45 years	1.15, 1.07–1.23, < 0.001	1.14, 1.05–1.25, 0.003	1.14, 1.05–1.24, 0.003	
 ≥ 45 years	1.11, 1.03–1.19, 0.003	1.06, 0.98–1.14, 0.160	1.04, 0.96–1.12, 0.314	
Gender	
 Male	1.11, 1.05–1.18, < 0.001	1.08, 1.01–1.14, 0.023	1.07, 1.00–1.13, 0.045	
 Female	1.12, 0.99–1.26, 0.061	1.09, 0.95–1.25, 0.201	1.09, 0.94–1.24, 0.229	
BMI	
 < 28 kg/m2	1.07, 0.98–1.17, 0.134	1.06, 0.96–1.16, 0.275	1.04, 0.94–1.15, 0.413	
 ≥ 28 kg/m2	1.12, 1.05–1.20, < 0.001	1.10, 1.02–1.18, 0.009	1.09, 1.02–1.17, 0.014	
Diabetes mellitus	
 No	1.07, 1.00–1.15, 0.038	1.05, 0.98–1.13, 0.151	1.04, 0.97–1.12, 0.283	
 Yes	1.16, 1.07–1.26, < 0.001	1.12, 1.02–1.23, 0.015	1.11, 1.02–1.22, 0.022	
Years since hypertension diagnosis	
 < 5 years	1.12, 1.04–1.19, 0.001	1.06, 0.98–1.14, 0.146	1.05, 0.97–1.13, 0.234	
 ≥ 5 years	1.13, 1.05–1.23, 0.002	1.13, 1.03–1.23, 0.007	1.11, 1.02–1.21, 0.015	
Hypertension stages	
 Stage I	1.04, 0.84–1.24, 0.715	1.05, 0.90–1.22, 0.517	1.04, 0.89–1.20, 0.614	
 Stage II	1.12, 1.03–1.21, 0.009	1.07, 0.98–1.17, 0.129	1.05, 0.96–1.15, 0.279	
 Stage III	1.17, 1.08–1.26, < 0.001	1.12, 1.03–1.22, 0.009	1.11, 1.02–1.21, 0.013	
Model 1: age, gender, SBP, DBP, abdominal circumference, HDL-C, LDL-C, fasting blood glucose, serum creatinine, homocysteine, cerebrovascular disease, and No. of antihypertensive agents, anti-diabetic agents, and anti-platelet agents.

Model 2: age, gender, ASBP, ADBP, abdominal circumference, HDL-C, LDL-C, fasting blood glucose, serum creatinine, homocysteine, cerebrovascular disease, and No. of antihypertensive agents, anti-diabetic agents, and anti-platelet agents.

Sensitivity analyses

The result of multi-logistic regression analysis for association between AHI (per 10 unit increase) and proteinuria in participants without PA and Hcy ≥ 15 μmol/L were as follows: (1) Crude model: 1.18, 1.10–1.27, P < 0.001 (OR, 95% CI); Model1: 1.15, 1.07–1.25, P < 0.001; Model 2: 1.14, 1.05–1.23, P < 0.001.

Discussion

This study suggests that OSA or OSA parameters are independently associated with greater odds of proteinuria in a hypertensive population, with the risk increasing as OSA severity increases. Moreover, this research provides novel variable indicating that in addition to AHI, T90 may be a significant metric of proteinuria risk in patients with hypertension, suggesting that the length of nocturnal intermittent hypoxia is one of the possible factors contributing to OSA-related renal tissue damage.

In the late 1980s, Sklar et al. initially reported that OSA may be significantly associated with strongly positive proteinuria; they subsequently confirmed this result in 34 patients with OSA and observed that three patients with treated OSA had improved proteinuria25. This opened the door to exploring the relationship between the two. In non-CKD patients with OSA, Faulx et al. reported that in a multivariate model corrected for BMI and GFR, the AHI ≥ 30 group had the highest albumin-to-creatinine ratio (ACR), which stayed consistent when patients with eGFR < 60 mL/min/1.73 m2 were excluded2. In another study exploring the relationship between OSA and urinary albumin excretion in 507 elderly male patients, significant associations were observed between the respiratory disturbance index and nocturnal hypoxia, and the ACR4. The degree of microalbuminuria was further demonstrated to correlate with the severity of OSA and hypoxia by Bulcun et al.5. Although these reports suggest a link between OSA and proteinuria, there are also studies that provide conflicting evidence26. The point that OSA is an independent risk factor for proteinuria is not unanimously accepted as some of these studies included patients with risk factors that may lead to significant proteinuria, such as hypertension and diabetes mellitus. Therefore, whether proteinuria is secondary to OSA or primary disease is confusing. In addition, it is not clear that the association between OSA and proteinuria is independent of BMI. The presence or severity of OSA did not affect proteinuria in cross-sectional studies exploring OSA and proteinuria in obese patients3. Given that the current findings are limited and contradictory in nature, it is worthwhile to clarify the role of OSA as a risk factor for renal structural damage in a comprehensive and in-depth manner, regardless of whether or not studies of the relationship between OSA and proteinuria are conducted in populations at high risk for proteinuria.

Among the various types of complex mechanisms caused by OSA, there are two prominent pathological mechanisms that contribute to the progression of renal tissue damage, namely hypoxia and glomerular hyperfiltration7. Intermittent hypoxia is an important factor in the development of CKD. Proteinuria has been the most common marker for renal damage since it can be detected earlier than the apparent decline in eGFR and it, as a renal independent risk factor, further aggravates the renal damage27. Nocturnal intermittent hypoxia is the hallmark feature of OSA and likewise, the initiating factor that causes a series of complex pathological changes to the kidney. It is well known that renal damage is one of the common complications of hypertension and DM, and it is also shown in our results that for patients with hypertension and diabetes mellitus, the risk of proteinuria in this population is increased with increasing AHI. This suggests that the presence of OSA may play a synergistic role in the development of proteinuria in this high-risk group, as OSA can further contribute to vascular endothelial damage and atherosclerosis and lead to the destruction of kidney structure and deterioration of renal function28,29. The association between T90 and proteinuria shown in this study appears to be tenuous. Still, it is worth noting that the T90 time was the total duration of all times, not a continuous period of time. Therefore, indicators that truly reflect the burden of hypoxia are needed in the future to explore its relationship with proteinuria further.

In sex-stratification analysis, we found that the link between AHI and proteinuria was observed only in male participants. In our latest publication30, we observed a similar phenomenon that women have a lower HR for CKD than men, which may be due to the protective effect of estrogen. Also, early research has confirmed that hormone replacement therapy may reduce proteinuria31. Besides, UROSAH is a predominantly male patient cohort, so the current female sample size may not be sufficient to observe such a fine-grained relationship. In age-stratification analysis, the relationship between the two is statistically significant in patients with age < 45 years. It may suggest that other confounding factors did not adequately consider contributing to the occurrence of proteinuria when we explored the relationship between AHI and proteinuria in the middle-aged and elderly population, and therefore the results were not significant. Alternatively, it may indicate that AHI causes a small but weak risk of proteinuria compared to other risk factors for kidney disease, which needs to be supported by more research. Upon grouping the study population by the duration and stage of hypertension, patients with a long duration of hypertension and a high stage of hypertension are at an elevated risk of renal structural damage. This risk may be further exacerbated and accelerated by the presence of OSA. Patients with shorter durations and lower stages of hypertension did not exhibit any statistically significant differences; however, their HR was greater than 1, indicating that OSA may continue to be a potential risk factor for renal injury. In the sensitivity analysis, patients with primary aldosteronism and patients with high homocysteine, both of which are risk factors that can lead to proteinuria by causing endothelial dysfunction32,33, were also considered confounders. In order to ensure the authenticity of the results, patients with primary aldosteronism and those with Hcy ≥ 15 μmol/L were precluded.

As previously stated, renal damage manifests in two ways: renal structural damage and diminished renal function. The primary objective of this research is to investigate the correlation between OSA and renal structural injury, an area that has not been well studied. The primary novelty of this study is the utilization of 24-h urinary protein quantification, the gold standard as an observational outcome of urinary protein excretion. This approach not only offers new evidence in the investigation of OSA that may result in renal structural damage, but also serves as a reminder to clinicians that the presence of OSA may exacerbate renal structural damage in patients with hypertension, particularly those with severe OSA, who should actively monitor their urinary protein excretion. Furthermore, we need to make clear the limitations of our study. First, although we can determine the correlation between our risk factors and the disease, their causality is unknown due to its cross-sectional design. Second, UROSAH is a single-center observational study to assess the association of OSA with long term cardiovascular outcomes in patients with hypertension. In this sub-study, although we try to minimize the effect of potential confounding by adjusting for more robust and reliable metrics such as 24-h BP parameters, HDL-C, LDL-C and fasting blood glucose in a multi-adjusted model, there may still residual confounding factors that were not adjusted for. Last but not least, the UROSA cohort is all hypertensive, with an overrepresentation of males, and caution is given in interpreting the results from non-hypertension and female participants.

In summary, our study suggested that OSA is independently associated with a higher risk of proteinuria in the population with hypertension. In the future, prospective cohort studies are needed to confirm the causal relationship between the two.

Supplementary Information

Supplementary Information.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-71883-5.

Acknowledgements

The authors thank the staff and participants involved in this study for their critical contributions.

Author contributions

Conceptualization: N.F.L., M.H., and M.M.L.; Methodology: M.M.L., M.H. and L.G.; Formal analysis: M.M.L.; Investigation and Data collection: M.M.L., L.C., Y.J.Y., L.Y., M.L., X.F.L., X.A., H.W., A.M., Q.N., and A.N.; Writing—original draft preparation: M.M.L.; Writing—review and editing: M.M.L.; Funding acquisition: W.J.; Resources: N.F.L., J.H.; Supervision: N.F.L., M.H.. All authors read and approved the final manuscript.

Funding

This work was supported by Major Science and Technology Special Projects in Xinjiang Uygur Autonomous Region (2022A03012-3).

Data availability

Data will be made available on reasonable request to the corresponding author.

Competing interests

The authors declare no competing interests.

Ethical approval

The research was authorized by the Medical Ethics Committee of the People’s Hospital of Xinjiang Uygur Autonomous Region (No.2019030662) and was conducted in strict compliance with the ethical standards set forth in the Declaration of Helsinki and its subsequent amendments. Written informed consent was submitted by all patients or their legal relatives participating in this study.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

These authors contributed equally: Miaomiao Liua and Mulalibieke Heizhati.
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References

1. Iliescu EA Lam M Pater J Munt PW Do patients with obstructive sleep apnea have clinically significant proteinuria? Clin. Nephrol. 2001 55 3 196 204 11316239
Iliescu, E. A., Lam, M., Pater, J. & Munt, P. W. Do patients with obstructive sleep apnea have clinically significant proteinuria?. Clin. Nephrol. 55(3), 196–204 (2001).11316239
2. Faulx MD Storfer-Isser A Kirchner HL Jenny NS Tracy RP Redline S Obstructive sleep apnea is associated with increased urinary albumin excretion Sleep 2007 30 7 923 929 10.1093/sleep/30.7.923 17682664
Faulx, M. D. et al. Obstructive sleep apnea is associated with increased urinary albumin excretion. Sleep 30(7), 923–929. 10.1093/sleep/30.7.923 (2007).17682664 10.1093/sleep/30.7.923
3. Agrawal V Vanhecke TE Rai B Franklin BA Sangal RB McCullough PA Albuminuria and renal function in obese adults evaluated for obstructive sleep apnea Nephron Clin. Pract. 2009 113 3 c140 c147 10.1159/000232594 19672111
Agrawal, V. et al. Albuminuria and renal function in obese adults evaluated for obstructive sleep apnea. Nephron Clin. Pract. 113(3), c140–c147. 10.1159/000232594 (2009).19672111 10.1159/000232594
4. Canales MT Paudel ML Taylor BC Ishani A Mehra R Steffes M Sleep-disordered breathing and urinary albumin excretion in older men Sleep Breath 2011 15 1 137 144 10.1007/s11325-010-0339-2 20186573
Canales, M. T. et al. Sleep-disordered breathing and urinary albumin excretion in older men. Sleep Breath 15(1), 137–144. 10.1007/s11325-010-0339-2 (2011).20186573 10.1007/s11325-010-0339-2
5. Bulcun E Ekici M Ekici A Cimen DA Kisa U Microalbuminuria in obstructive sleep apnea syndrome Sleep Breath 2015 19 4 1191 1197 10.1007/s11325-015-1136-8 25778945
Bulcun, E., Ekici, M., Ekici, A., Cimen, D. A. & Kisa, U. Microalbuminuria in obstructive sleep apnea syndrome. Sleep Breath 19(4), 1191–1197. 10.1007/s11325-015-1136-8 (2015).25778945 10.1007/s11325-015-1136-8
6. Fine LG Norman JT Chronic hypoxia as a mechanism of progression of chronic kidney diseases: From hypothesis to novel therapeutics Kidney Int. 2008 74 7 867 872 10.1038/ki.2008.350 18633339
Fine, L. G. & Norman, J. T. Chronic hypoxia as a mechanism of progression of chronic kidney diseases: From hypothesis to novel therapeutics. Kidney Int. 74(7), 867–872. 10.1038/ki.2008.350 (2008).18633339 10.1038/ki.2008.350
7. Hanly PJ Ahmed SB Sleep apnea and the kidney: Is sleep apnea a risk factor for chronic kidney disease? Chest 2014 146 4 1114 1122 10.1378/chest.14-0596 25288001
Hanly, P. J. & Ahmed, S. B. Sleep apnea and the kidney: Is sleep apnea a risk factor for chronic kidney disease?. Chest 146(4), 1114–1122. 10.1378/chest.14-0596 (2014).25288001 10.1378/chest.14-0596
8. Ozkok A Kanbay A Odabas AR Covic A Kanbay M Obstructive sleep apnea syndrome and chronic kidney disease: A new cardiorenal risk factor Clin. Exp. Hypertens. 2014 36 4 211 216 10.3109/10641963.2013.804546 24432915
Ozkok, A., Kanbay, A., Odabas, A. R., Covic, A. & Kanbay, M. Obstructive sleep apnea syndrome and chronic kidney disease: A new cardiorenal risk factor. Clin. Exp. Hypertens. 36(4), 211–216. 10.3109/10641963.2013.804546 (2014).24432915 10.3109/10641963.2013.804546
9. Sedaghat S Mattace-Raso FU Hoorn EJ Uitterlinden AG Hofman A Ikram MA Arterial stiffness and decline in kidney function Clin. J. Am. Soc. Nephrol. 2015 10 12 2190 2197 10.2215/CJN.03000315 26563380
Sedaghat, S. et al. Arterial stiffness and decline in kidney function. Clin. J. Am. Soc. Nephrol. 10(12), 2190–2197. 10.2215/CJN.03000315 (2015).26563380 10.2215/CJN.03000315
10. Puckrin R Iqbal S Zidulka A Vasilevsky M Barre P Renoprotective effects of continuous positive airway pressure in chronic kidney disease patients with sleep apnea Int. Urol. Nephrol. 2015 47 11 1839 1845 10.1007/s11255-015-1113-y 26424500
Puckrin, R., Iqbal, S., Zidulka, A., Vasilevsky, M. & Barre, P. Renoprotective effects of continuous positive airway pressure in chronic kidney disease patients with sleep apnea. Int. Urol. Nephrol. 47(11), 1839–1845. 10.1007/s11255-015-1113-y (2015).26424500 10.1007/s11255-015-1113-y
11. Parmaksız E Torun Parmaksız E Reversibility of microalbuminuria with continuous positive airway pressure treatment in obstructive sleep apnea syndrome Int. Urol. Nephrol. 2020 52 9 1719 1724 10.1007/s11255-020-02519-6 32488755
Parmaksız, E. & Torun Parmaksız, E. Reversibility of microalbuminuria with continuous positive airway pressure treatment in obstructive sleep apnea syndrome. Int. Urol. Nephrol. 52(9), 1719–1724. 10.1007/s11255-020-02519-6 (2020).32488755 10.1007/s11255-020-02519-6
12. Chen R Huang ZW Lin XF Lin JF Yang MJ Effect of continuous positive airway pressure on albuminuria in patients with obstructive sleep apnea: A meta-analysis Sleep Breath 2022 26 1 279 285 10.1007/s11325-021-02393-1 33990909
Chen, R., Huang, Z. W., Lin, X. F., Lin, J. F. & Yang, M. J. Effect of continuous positive airway pressure on albuminuria in patients with obstructive sleep apnea: A meta-analysis. Sleep Breath 26(1), 279–285. 10.1007/s11325-021-02393-1 (2022).33990909 10.1007/s11325-021-02393-1
13. Uyar M Davutoğlu V Gündoğdu N Kosovalı D Sarı İ Renal functions in obstructive sleep apnea patients Sleep Breath 2016 20 1 191 195 10.1007/s11325-015-1204-0 26084412
Uyar, M., Davutoğlu, V., Gündoğdu, N., Kosovalı, D. & Sarı, İ. Renal functions in obstructive sleep apnea patients. Sleep Breath 20(1), 191–195. 10.1007/s11325-015-1204-0 (2016).26084412 10.1007/s11325-015-1204-0
14. Lee YJ Jang HR Huh W Kim YG Kim DJ Oh HY Independent contributions of obstructive sleep apnea and the metabolic syndrome to the risk of chronic kidney disease J. Clin. Sleep Med. 2017 13 10 1145 1152 10.5664/jcsm.6758 28760190
Lee, Y. J. et al. Independent contributions of obstructive sleep apnea and the metabolic syndrome to the risk of chronic kidney disease. J. Clin. Sleep Med. 13(10), 1145–1152. 10.5664/jcsm.6758 (2017).28760190 10.5664/jcsm.6758
15. Hui M Li Y Ye J Zhuang Z Wang W Obstructive sleep apnea-hypopnea syndrome (OSAHS) comorbid with diabetes rather than OSAHS alone serves an independent risk factor for chronic kidney disease (CKD) Ann. Palliat. Med. 2020 9 3 858 869 10.21037/apm.2020.03.21 32279514
Hui, M., Li, Y., Ye, J., Zhuang, Z. & Wang, W. Obstructive sleep apnea-hypopnea syndrome (OSAHS) comorbid with diabetes rather than OSAHS alone serves an independent risk factor for chronic kidney disease (CKD). Ann. Palliat. Med. 9(3), 858–869. 10.21037/apm.2020.03.21 (2020).32279514 10.21037/apm.2020.03.21
16. Agodoa LY Appel L Bakris GL Beck G Bourgoignie J Briggs JP Effect of ramipril vs amlodipine on renal outcomes in hypertensive nephrosclerosis: A randomized controlled trial JAMA 2001 285 21 2719 2728 10.1001/jama.285.21.2719 11386927
Agodoa, L. Y. et al. Effect of ramipril vs amlodipine on renal outcomes in hypertensive nephrosclerosis: A randomized controlled trial. JAMA 285(21), 2719–2728. 10.1001/jama.285.21.2719 (2001).11386927 10.1001/jama.285.21.2719
17. Jinchai J Khamsai S Chattakul P Limpawattana P Chindaprasirt J Chotmongkol V How common is obstructive sleep apnea in young hypertensive patients? Intern. Emerg. Med. 2020 15 6 1005 1010 10.1007/s11739-019-02273-3 31970622
Jinchai, J. et al. How common is obstructive sleep apnea in young hypertensive patients?. Intern. Emerg. Med. 15(6), 1005–1010. 10.1007/s11739-019-02273-3 (2020).31970622 10.1007/s11739-019-02273-3
18. Aziz F Chaudhary K The triad of sleep apnea, hypertension, and chronic kidney disease: A spectrum of common pathology Cardiorenal. Med. 2017 7 1 74 82 10.1159/000450796
Aziz, F. & Chaudhary, K. The triad of sleep apnea, hypertension, and chronic kidney disease: A spectrum of common pathology. Cardiorenal. Med. 7(1), 74–82. 10.1159/000450796 (2017).10.1159/000450796
19. Ow CPC Ngo JP Ullah MM Hilliard LM Evans RG Renal hypoxia in kidney disease: Cause or consequence? Acta Physiol. 2018 222 4 e12999 10.1111/apha.12999
Ow, C. P. C., Ngo, J. P., Ullah, M. M., Hilliard, L. M. & Evans, R. G. Renal hypoxia in kidney disease: Cause or consequence?. Acta Physiol. 222(4), e12999. 10.1111/apha.12999 (2018).10.1111/apha.12999
20. Cai X Li N Hu J Wen W Yao X Zhu Q Nonlinear relationship between Chinese visceral adiposity index and new-onset myocardial infarction in patients with hypertension and obstructive sleep apnoea: Insights from a cohort study J. Inflamm. Res. 2022 15 687 700 10.2147/JIR.S351238 35140499
Cai, X. et al. Nonlinear relationship between Chinese visceral adiposity index and new-onset myocardial infarction in patients with hypertension and obstructive sleep apnoea: Insights from a cohort study. J. Inflamm. Res. 15, 687–700. 10.2147/JIR.S351238 (2022).35140499 10.2147/JIR.S351238
21. Levey AS Stevens LA Schmid CH Zhang YL Castro AF 3rd Feldman HI A new equation to estimate glomerular filtration rate Ann. Intern. Med. 2009 150 9 604 612 10.7326/0003-4819-150-9-200905050-00006 19414839
Levey, A. S. et al. A new equation to estimate glomerular filtration rate. Ann. Intern. Med. 150(9), 604–612. 10.7326/0003-4819-150-9-200905050-00006 (2009).19414839 10.7326/0003-4819-150-9-200905050-00006
22. Yang W Shao L Heizhati M Wu T Yao X Wang Y Oropharyngeal microbiome in obstructive sleep apnea: Decreased diversity and abundance J. Clin. Sleep Med. 2019 15 12 1777 1788 10.5664/jcsm.8084 31855163
Yang, W. et al. Oropharyngeal microbiome in obstructive sleep apnea: Decreased diversity and abundance. J. Clin. Sleep Med. 15(12), 1777–1788. 10.5664/jcsm.8084 (2019).31855163 10.5664/jcsm.8084
23. Epstein LJ Kristo D Strollo PJ Jr Friedman N Malhotra A Patil SP Clinical guideline for the evaluation, management and long-term care of obstructive sleep apnea in adults J. Clin. Sleep Med. 2009 5 3 263 276 10.5664/jcsm.27497 19960649
Epstein, L. J. et al. Clinical guideline for the evaluation, management and long-term care of obstructive sleep apnea in adults. J. Clin. Sleep Med. 5(3), 263–276 (2009).19960649 10.5664/jcsm.27497
24. Li Z Sillanpää MJ Overview of LASSO-related penalized regression methods for quantitative trait mapping and genomic selection Theor. Appl. Genet. 2012 125 3 419 435 10.1007/s00122-012-1892-9 22622521
Li, Z. & Sillanpää, M. J. Overview of LASSO-related penalized regression methods for quantitative trait mapping and genomic selection. Theor. Appl. Genet. 125(3), 419–435. 10.1007/s00122-012-1892-9 (2012).22622521 10.1007/s00122-012-1892-9
25. Chaudhary BA Sklar AH Chaudhary TK Kolbeck RC Speir WA Jr Sleep apnea, proteinuria, and nephrotic syndrome Sleep 1988 11 1 69 74 10.1093/sleep/11.1.69 3363272
Chaudhary, B. A., Sklar, A. H., Chaudhary, T. K., Kolbeck, R. C. & Speir, W. A. Jr. Sleep apnea, proteinuria, and nephrotic syndrome. Sleep 11(1), 69–74. 10.1093/sleep/11.1.69 (1988).3363272 10.1093/sleep/11.1.69
26. Casserly LF Chow N Ali S Gottlieb DJ Epstein LJ Kaufman JS Proteinuria in obstructive sleep apnea Kidney Int. 2001 60 4 1484 1489 10.1046/j.1523-1755.2001.00952.x 11576363
Casserly, L. F. et al. Proteinuria in obstructive sleep apnea. Kidney Int. 60(4), 1484–1489. 10.1046/j.1523-1755.2001.00952.x (2001).11576363 10.1046/j.1523-1755.2001.00952.x
27. Ruggenenti P Cravedi P Remuzzi G Mechanisms and treatment of CKD J. Am. Soc. Nephrol. 2012 23 12 1917 1928 10.1681/ASN.2012040390 23100218
Ruggenenti, P., Cravedi, P. & Remuzzi, G. Mechanisms and treatment of CKD. J. Am. Soc. Nephrol. 23(12), 1917–1928. 10.1681/ASN.2012040390 (2012).23100218 10.1681/ASN.2012040390
28. Chen LD Lin L Lin XJ Ou YW Wu Z Ye YM Effect of continuous positive airway pressure on carotid intima-media thickness in patients with obstructive sleep apnea: A meta-analysis PLoS ONE 2017 12 9 e0184293 10.1371/journal.pone.0184293 28863162
Chen, L. D. et al. Effect of continuous positive airway pressure on carotid intima-media thickness in patients with obstructive sleep apnea: A meta-analysis. PLoS ONE 12(9), e0184293. 10.1371/journal.pone.0184293 (2017).28863162 10.1371/journal.pone.0184293
29. Català R Ferré R Cabré A Girona J Porto M Texidó A Masana L Long-term effects of continuous positive airway pressure treatment on subclinical atherosclerosis in obstructive sleep apnoea syndrome Med. Clin. (Barc.) 2016 147 1 1 6 10.1016/j.medcli.2016.03.032 27210810
Català, R. et al. Long-term effects of continuous positive airway pressure treatment on subclinical atherosclerosis in obstructive sleep apnoea syndrome. Med. Clin. (Barc.) 147(1), 1–6. 10.1016/j.medcli.2016.03.032 (2016).27210810 10.1016/j.medcli.2016.03.032
30. Liu M Heizhati M Li N Lin M Gan L Zhu Q The relationship between obstructive sleep apnea and risk of renal impairment in patients with hypertension, a longitudinal study Sleep Med. 2023 109 18 24 10.1016/j.sleep.2023.05.020 37393718
Liu, M. et al. The relationship between obstructive sleep apnea and risk of renal impairment in patients with hypertension, a longitudinal study. Sleep Med. 109, 18–24. 10.1016/j.sleep.2023.05.020 (2023).37393718 10.1016/j.sleep.2023.05.020
31. Szekacs B Vajo Z Varbiro S Kakucs R Vaslaki L Acs N Postmenopausal hormone replacement improves proteinuria and impaired creatinine clearance in type 2 diabetes mellitus and hypertension BJOG 2000 107 8 1017 1021 10.1111/j.1471-0528.2000.tb10406.x 10955435
Szekacs, B. et al. Postmenopausal hormone replacement improves proteinuria and impaired creatinine clearance in type 2 diabetes mellitus and hypertension. BJOG 107(8), 1017–1021. 10.1111/j.1471-0528.2000.tb10406.x (2000).10955435 10.1111/j.1471-0528.2000.tb10406.x
32. Kawashima A Sone M Inagaki N Takeda Y Itoh H Kurihara I Renal impairment is closely associated with plasma aldosterone concentration in patients with primary aldosteronism Eur. J. Endocrinol. 2019 181 3 339 350 10.1530/EJE-19-0047 31319380
Kawashima, A. et al. Renal impairment is closely associated with plasma aldosterone concentration in patients with primary aldosteronism. Eur. J. Endocrinol. 181(3), 339–350. 10.1530/EJE-19-0047 (2019).31319380 10.1530/EJE-19-0047
33. Yun L Xu R Li G Yao Y Li J Cong D Homocysteine and the C677T gene polymorphism of its key metabolic enzyme MTHFR are risk factors of early renal damage in hypertension in a Chinese Han population Medicine (Baltimore) 2015 94 52 e2389 10.1097/MD.0000000000002389 26717388
Yun, L. et al. Homocysteine and the C677T gene polymorphism of its key metabolic enzyme MTHFR are risk factors of early renal damage in hypertension in a Chinese Han population. Medicine (Baltimore) 94(52), e2389. 10.1097/MD.0000000000002389 (2015).26717388 10.1097/MD.0000000000002389
