Copeptin is associated with microalbuminuria and renal function in the general Japanese population

Abstract

An association between copeptin (precursor molecule of arginine vasopressin) and markers for renal function has been reported, but data on the Japanese population has been limited. In this study, we investigated whether elevated copeptin levels are associated with microalbuminuria and renal dysfunction in the general Japanese population. A total of 1,262 participants (842 female and 420 male) were enrolled. Multiple regression analysis was performed to assess the association of copeptin levels (logarithm) with estimated glomerular filtration rate (eGFR) and the urine albumin-to-creatinine ratio (UACR) after adjusting for age, BMI, and lifestyle variables. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using logistic regression methods in which chronic kidney disease (CKD) was the dependent variable. The copeptin levels differed significantly with sex, but were not found to be related to age or the span of time from preceding meal to blood sampling. In female participants, copeptin level was negatively correlated with eGFR (beta = –0.100, p-value = 0.006) and positively correlated with UACR (beta = 0.099, p-value = 0.003). In male participants, a negative correlation (beta = –0.140, p-value = 0.008) was observed for eGFR. In both females and males, those with high copeptin levels had more than double the ORs of CKD (OR = 2.1–2.9) adjusted for CKD-related factors. The present study found elevated copeptin levels to be associated with renal function loss in the Japanese population and microalbuminuria in female. Moreover, it was evident that high copeptin levels are associated with CKD. These results suggest that copeptin could be considered a marker of renal function.

THE PREVALENCE OF CHRONIC KIDNEY DISEASE (CKD) is increasing worldwide, affecting approximately 10% of the population [1]. Poor kidney function is associated with an increased risk of cardiovascular events and death [2]. Now, adequate hydration is known to be essential for kidney health [3]. Several observational studies have suggested that appropriate fluid intake may have beneficial effects in limiting the deterioration in renal function [4, 5].

Dehydration and a moderate increase in plasma osmolality are the primary stimuli for vasopressin (or antidiuretic hormone) secretion by the posterior pituitary. Arginine vasopressin (AVP) regulates water reabsorption by mobilizing aquaporins in the renal collecting duct via vasopressin 2 receptor (V2R); therefore, it is responsible for maintaining osmotic pressure within a narrow range [6, 7]. However, the measurement of endogenous plasma AVP level is difficult due to technical limitations and is not widely reported. In contrast, copeptin, a 39-glycosylated amino acid, is the C-terminal portion of the precursor AVP and is easily measured due to its excellent stability. Therefore, copeptin can be used as a reliable substitute for vasopressin [8]. An association between copeptin and markers for renal function has been reported in patients with microalbuminuria [9], CKD [10, 11], diabetes [12, 13], and autosomal dominant polycystic kidney disease (ADPKD) [14, 15] and those at high risk of CKD.

However, reports on the association of copeptin levels with renal function in the Japanese population are limited to patients with ADPKD. In this study, we investigated whether elevated copeptin levels are associated with microalbuminuria and renal dysfunction in the general Japanese population.

Materials and Methods

Participants

The Japan Multi-Institutional Collaborative Cohort Study was launched in 2005 to investigate gene-environmental interactions in lifestyle-related diseases [16]. This study included individuals enrolled in the Japan Multi-Institutional Collaborative Cohort Study second survey in the Kyoto area from 2013 to 2017. A total of 3,913 participants were eligible for analysis. After routine health checkups of all subjects, copeptin level was measured in 1,300 of these 3,913 participants. Among them, 38 were excluded due to the lack of other data, after which 1,262 (842 female and 420 male participants) were included in the analysis. The study was approved by the Institutional Ethics Committee of Kyoto Prefectural University of Medicine (approval number: RBMR-E-36-14, 2013) and conducted following the principles of the Declaration of Helsinki. All participants provided written informed consent before participation.

Clinical and biochemical analyses

The following lifestyle-related and medical information obtained through self-administered questionnaires were evaluated as previously reported: alcohol consumption level (ethanol/day), smoking (assessed as Brinkman index: number of cigarettes smoked per day × total number of years smoked), sleep duration (h/day), current medications, and metabolic equivalents (METs) [17]. The alcohol content of each type of beverage (Japanese sake, beer, shochu, whiskey, and wine) was calculated, and alcohol consumption was determined in terms of the number of drinks per day, which was then converted into 23 g of ethanol. Furthermore, blood chemistry data and early morning spot urine samples collected on the day of the survey were assessed. The estimated glomerular filtration rate (eGFR) was calculated using the following equation: eGFR (mL/min/1.73 m²) = 194 × creatinine^–1.094 × year^–0.287 (for men) and eGFR (mL/min/1.73 m²) = 194 × creatinine^–1.094 × year^–0.287 × 0.739 (for women) [18]. The prevalence of CKD was determined for CKD stages 3–5 (defined as eGFR <60 mL/min/1.73 m²). Urinary albumin and creatinine levels were measured simultaneously, from which the urine albumin-to-creatinine ratio (UACR) was calculated and expressed in milligrams per gram of creatinine. In addition, anthropometric data obtained from health checkups were also collected. Body mass index (BMI) was calculated as weight divided by the square of height (kg/m²).

Anamnesis and medication history were noted using self-administered questionnaires. Hypertension was defined as a systolic/diastolic blood pressure ≥140/90 mmHg and/or the current use of medication for hypertension. Diabetes mellitus was defined as a glycated hemoglobin (HbA1c) level ≥6.5% and/or the current use of medication for diabetes. Dyslipidemia was defined as low-density lipoprotein cholesterol (LDL-C) ≥140 mg dL^–1 and/or high-density lipoprotein cholesterol (HDL-C) <40 mg dL^–1 and/or the current use of medication for dyslipidemia.

Copeptin plasma concentrations were measured using an automated KRYPTOR analyzer and a time-resolved amplified cryptate emission (TRACE) technology assay (Thermo Fisher Diagnostics K.K., Japan), according to the instruction provided by the manufacturer [19].

Statistical analysis

Continuous variables are expressed as mean ± standard deviation (SD), and categorical data are expressed as sums and percentages. Inter-group comparisons were performed using Welch’s t-tests for continuous variables and chi-squared or Fisher’s exact tests for categorical variables (hypertension, diabetes mellitus, and dyslipidemia). Spearman’s rank correlation analysis was performed to assess the relationship between copeptin levels and lifestyle variables, including eGFR and UACR.

Multiple regression analysis was performed to assess the association of copeptin levels (logarithm) with eGFR and UACR after adjusting for other variables. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using logistic regression methods in which CKD was the dependent variable and year, BMI, Brinkman index, alcohol intake, METs, sleep duration, hypertension, diabetes mellitus, and dyslipidemia were the independent variables. All data were analyzed using SPSS version 25 (IBM Corp, Armonk, NY), and p < 0.05 was considered statistically significant.

Results

A total of 1,262 participants were divided into female and male groups, including 842 and 420 participants, respectively. The mean age was 56.7 ± 9.83 years for female participants and 59.5 ± 10.2 years for male participants. Prevalence of CKD (eGFR <60 mL/min/1.73 m²) was detected in 11.9% of female participants and 24.0% of male participants. The copeptin levels differed significantly with sex: 4.09 ± 3.48 pmol/L in female participants and 6.93 ± 0.10 pmol/L in male participants (p < 0.001). Characteristics of participants according to sex and CKD were shown in Table 1. Histograms of copeptin levels in female and male participants are shown in Supplemental Figs. 1 and 2.

Table 1 Characteristics of participants according to sex and CKD

	Female, N = 842					Male, N = 420
	CKD (–), N = 742		CKD (+), N = 100		p-value	CKD (–), N = 319		CKD (+), N = 101		p-value
	mean/N	SD/%	mean/N	SD/%		mean/N	SD/%	mean/N	SD/%
Age (years), mean, SD	56.0	9.8	61.8	8.3	<0.001	57.9	10.4	64.6	7.4	<0.001
BMI, mean, SD	21.3	3.2	22.5	3.3	0.001	23.3	3.0	24.0	3.3	0.043
Brinkman index, mean, SD	58.5	188	64.4	182	0.766	479	533	554	609	0.233
Alcohol intake (g/day), mean, SD	7.0	13.2	4.0	7.4	0.025	23.6	30.0	21.2	24.0	0.452
METs (h/day), mean, SD	15.1	10.2	14.8	7.8	0.796	14.2	10.4	15.5	12.7	0.305
Sleep duration (h/day), mean, SD	6.4	1.0	6.4	0.9	0.868	6.5	1.1	6.6	1.0	0.585
Hypertension, N, %	164	22.1%	32	32.0%	0.032	139	43.6%	61	60.4%	0.004
Diabetes mellitus, N, %	24	3.2%	3	3.0%	1.000	33	10.3%	16	15.8%	0.154
Dyslipidemia, N, %	312	42.0%	59	59.0%	0.002	138	43.3%	54	53.5%	0.086
Copeptin [pmol/L], mean, SD	3.93	3.26	5.28	4.64	<0.001	6.23	4.45	9.12	6.46	<0.001
eGFR, mean, SD	75.4	10.4	55.0	7.4	<0.001	74.1	9.9	54.5	8.0	<0.001
UACR, mean, SD	5.8	7.2	28.4	130	<0.001	5.7	10.5	18.8	68.3	0.001

BMI, body mass index; METs, metabolic equivalents; eGFR, estimated glomerular filtration rate; UACR, the urine albumin-to-creatinine ratio.

We examined the correlation between copeptin level and CKD-related factors, such as age, BMI, Brinkman index, alcohol intake, METs, sleep duration, eGFR, and UACR (Table 2). In female participants, no significant association was observed between copeptin levels and age, alcohol intake, and METs; however, a significant positive correlation with BMI, Brinkman index, and UACR and a significant negative correlation with eGFR and sleep duration were detected. In male participants, the relationship between copeptin levels and age, BMI, Brinkman index, alcohol intake, METs, and sleep duration was not significant, but copeptin levels showed a positive correlation with UACR and a negative correlation with eGFR. No correlation between copeptin levels and the span of time from preceding meal to blood sampling was detected in either group. A scatter plot is shown in Supplemental Fig. 3.

Table 2 Correlations between copeptin level and CKD-related factors

Female			Age	BMI	Brinkman index	Alcohol intake	METs	Sleep duration	eGFR	UACR
	Copeptin [pmol/L]	Coefficient	–0.004	0.127	0.079	–0.042	0.033	–0.092	–0.068	0.237
		p-value	0.906	<0.001	0.022	0.223	0.345	0.008	0.050	<0.001
Male			Age	BMI	Brinkman index	Alcohol intake	METs	Sleep duration	eGFR	UACR
	Copeptin [pmol/L]	Coefficient	0.041	0.051	–0.006	0.007	0.078	–0.079	–0.149	0.212
		p-value	0.402	0.298	0.909	0.892	0.110	0.106	0.002	<0.001

The relationships between copeptin levels, eGFR, and UACR were analyzed using multiple regression analysis (Table 3), which included the adjustment for age, BMI, Brinkman index, alcohol intake, METs, sleep duration, hypertension, diabetes mellitus, and dyslipidemia. In female participants, copeptin level was negatively correlated with eGFR (beta = –0.100, p-value = 0.006) and positively correlated with UACR (beta = 0.099, p-value = 0.003). In male participants, a negative correlation (beta = –0.140, p-value = 0.008) was observed for eGFR, while no significant difference was observed for UACR.

Table 3 Comparison of the association of copeptin and kidney faction (eGFR and UACR)

Female		Beta	p-value
	eGFR	–0.100	0.006
	UACR	0.099	0.003
Male		Beta	p-value
	eGFR	–0.140	0.008
	UACR	0.057	0.254

Adjust for age, BMI, Brinkman index, alcohol intake, METs, sleep duration, hypertension, diabetes mellitus, dyslipidemia

The dependent variable; copeptin (continuous)

Table 4 shows the association between copeptin levels and CKD. The effect of high copeptin levels on the odds of developing CKD was examined using logistic regression analysis. Female and male participants were divided based on copeptin levels (≥10.96 pmol/L and ≥17.18 pmol/L, respectively) based on the mean ≥2 SD. Model 1 (age), model 2 (age, BMI, Brinkman index, alcohol intake, METs, sleep duration), model 3 (age, BMI, Brinkman index, alcohol intake, METs, sleep duration, hypertension, diabetes mellitus, and dyslipidemia) were assessed. For female participants, OR = 2.340 (95% CI: 1.331–4.113), OR = 2.173 (95% CI: 1.215–3.886), and OR = 2.232 (95% CI: 1.234–4.038) were detected in models 1, 2, and 3, respectively, whereas for male participants, the corresponding values in the three models were OR = 2.976 (95% CI: 1.656–5.348), OR = 2.869 (95% CI: 1.571–5.238), and OR = 2.836 (95% CI: 1.546–5.204).

Table 4 The relationship between high copeptin levels and CKD

	Female			Male
	OR	95% CI	p-value	OR	95% CI	p-value
Model 1	2.340	1.331–4.113	0.003	2.976	1.656–5.348	<0.001
Model 2	2.173	1.215–3.886	0.009	2.869	1.571–5.238	0.001
Model 3	2.232	1.234–4.038	0.008	2.836	1.546–5.204	0.001

OR, odds ratio; CI, confidence interval

High copeptin levels was based on the mean ≥2 SD. Female ≥10.96 pmol/L, Male ≥17.18 pmol/L.

Model 1 was adjusted for age

Model 2 was adjusted for age, BMI, Brinkman index, alcohol intake, METs, sleep duration

Model 3 was adjusted for age, BMI, Brinkman index, alcohol intake, METs, sleep duration, hypertension, diabetes mellitus, dyslipidemia

Discussion

A key finding of this study is that elevated copeptin levels are generally associated with worsening renal function, which is independent of traditionally considered risk factors, in the Japanese population. This outcome is consistent with the previous reports dealing with the French [20] and Nordic [11] populations. These longitudinal studies have shown that the copeptin level independently predicts the new-onset CKD and faster eGFR decline over time. This study is the first to report that high levels of copeptin are associated with CKD and that copeptin levels were negatively correlated with eGFR in Japanese participants. However, UACR was only relevant in female. Consistent with another study [21], copeptin levels in this study were significantly higher in male than in female. Sexual disparity of copeptin have already been reported to exist at birth [22]. Sex differences in copeptin levels may contribute to the higher urine osmolality in male [23]. These differences may be related to sex differences in the relationship between copeptin levels and UACR, but cannot be clearly explained by the present results. On the other hand, it has been reported that there was no interaction between copeptin and sex or renal function, and that the association between copeptin concentrations and UACR was essentially similar in men and women and independent of renal function [9]. The fact that there was a difference between female and male in this study may be due to the small number of participants with high UACR and the sample size. Copeptin levels also were not found to be related to the span of time from preceding meal to blood sampling (Supplemental Fig. 3), even though copeptin levels are likely to fluctuate in response to changes in plasma osmolality since copeptin is a precursor to AVP. This finding may be due to most of our blood samples having been collected more than 2 hours after the preceding meal. We adjusted the data for variable lifestyle-related factors, such as BMI, Brinkman index, alcohol intake, METs, sleep duration, and dyslipidemia, and extended the validity of the association between copeptin levels and renal function in the Japanese population. Whether the relationship between AVP (measured as copeptin) and disease onset is causal or due to co-variation of both remains unclear.

Although a cause-and-effect relationship could not be established in this cross-sectional study, the relationship between copeptin and renal function may be attributed to three possibilities: first, since copeptin is cleared by renal excretion, copeptin levels would tend to increase as renal function declines; second, AVP- and/or V2R-mediated signals may impair renal function; and third, copeptin may reflect volume status, i.e., volume depletion tends to cause high copeptin levels associated with high creatinine levels. AVP acts mainly at the renal level by binding to its V2R in the collecting tubules. Several animal studies have shown that chronic exposure to increased AVP action results in progressively deteriorating renal function [24]. In another study, the administration of a V2R agonist to rats and humans revealed that the V2R-mediated action of vasopressin plays an important role in albuminuria with or without diabetes [25]. Tolvaptan, which is a vasopressin V2R antagonist, was inversely associated with a decline in renal function in patients with ADPKD in human studies [26, 27]. It has also been shown that vasopressin V2R antagonists inhibit cyst growth and the development of kidney disease [28]. Although it cannot be concluded from these studies and findings that AVP acts directly, it is speculated that at least V2R-mediated signals affect renal function.

AVP is involved in the regulation of water reabsorption and is therefore altered by hyperhydration and dehydration. Vasopressin inhibition by water intake reduced proteinuria in rats with renal failure [29]. In humans, water intake, which readily decreases circulating AVP/copeptin levels, may inhibit CKD progression [30]. On the other hand, in rats, antihypertensive treatment (angiotensin-converting enzyme inhibition or angiotensin II type 1 receptors) attenuated the V2R-stimulated increase of albuminuria [25]. This albuminuric effect is attributed to increased glomerular leakage and is mediated, at least in part, by the renin-angiotensin system (RAS) in addition to functional vasopressin V2R. This may suggest that water intake may inhibit CKD not only through its AVP inhibition but also through RAS inhibition [30]. Although drinking more water has been associated with improved kidney function in human studies [4, 5], there are few data on kidney outcomes from intervention studies modifying vasopressin secretion or action. Elevated copeptin levels may be a surrogate marker of dehydration.

This study had some limitations. Its cross-sectional design and inclusion of only Japanese participants may limit its applicability to other racial/ethnic populations. Further studies involving other racial/ethnic groups are required to validate our findings. As the temporal order of copeptin and CKD-related markers is unclear, we expect that future follow-up surveys will lead to results that show a possible causal relationship between copeptin and renal dysfunction. Additionally, the mean cut-off value for copeptin has not been established, there may be unmeasured confounding, and copeptin was assessed in a single measurement, which is subject to measurement error. However, a large number of participants and the implementation of a population-based cohort design are the strengths of the present study.

In conclusion, the present study detected elevated copeptin levels to be associated with renal function loss in the Japanese population and microalbuminuria in female. Moreover, it was evident that high copeptin levels are associated with CKD. These results suggest that copeptin could be considered a marker of renal function.

Disclosure

This study was supported by Grants-in-Aid for Scientific Research for Priority Areas of Cancer (No. 17015018) and Innovative Areas (No. 221S0001) and by the Japan Society for the Promotion of Science (JSPS) KAKENHI Grant (No. 16H06277 and 22H04923 [CoBiA]) from the Japanese Ministry of Education, Culture, Sports, Science and Technology. None of the authors have any potential conflicts of interest associated with this research.

Supplemental Fig. 1

Histogram for copeptin plasma concentration in Japanese female participants.

Supplemental Fig. 2

Histogram for copeptin plasma concentration in Japanese male participants.

Supplemental Fig. 3

The scatter plot between copeptin and the time of the preceding meal in both female and male.

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