Association of serum copeptin levels with pulmonary complications and heart right ventricular functions in common variable immunodeficiency

Abstract

Background and aims

Common variable immunodeficiency (CVID) represents the most frequently diagnosed symptomatic primary immunodeficiency (PID), marked by a heterogeneous presentation involving infectious and non-infectious symptoms. This study investigated the association between serum copeptin levels and right ventricular functions (RVF) and pulmonary complications in patients diagnosed with CVID.

Methods

The study analyzed data from 60 individuals with a confirmed diagnosis of CVID and 30 age- and sex-matched healthy volunteers (HVs). Clinical and biochemical parameters were sourced from existing hospital records.CVID patients were categorized into two subgroups: those with and without pulmonary complications. Comparisons of serum copeptin levels were made between these groups and between the overall CVID cohort and healthy controls. RVF was evaluated using tricuspid annular plane systolic excursion (TAPSE) and supplementary echocardiographic indicators.

Results

The CVID group had a median age of 40 years (interquartile range [IQR]: 30–55), with 51.7% being male, while the HVs group had a median age of 37 years (IQR: 28–47.5), with 60% male. No significant differences in age (p = 0.226) or sex distribution (p = 0.45) were observed between the groups. CVID with pulmonary complications (CVID-P) exhibited significantly elevated copeptin levels compared to those without such complications (p < 0.001). According to ROC analysis, a copeptin cut-off value of 11 pmol/L significantly differentiated patients with CVID-P from those without pulmonary complications (p < 0.001). Moreover, overall copeptin levels were significantly higher in the CVID group than in HVs (p < 0.001). A copeptin cut-off value of 21 pmol/L effectively distinguished CVID patients with low TAPSE from those with normal TAPSE values (p < 0.001). Pulmonary complications and low TAPSE were independently associated with increased copeptin levels (p = 0.006 and p = 0.004, respectively).

Conclusion

The development of pulmonary complications and RV dysfunction were associated with elevated serum copeptin levels in CVID. Measuring serum copeptin concentration may be a useful biomarker in diagnosing and prognosis pulmonary diseases and RV dysfunction in CVID.

Background

Common variable immunodeficiency (CVID) is the most common symptomatic primary immunodeficiency (PID) [1]. CVID is characterized by hypogammaglobulinemia and reduced or absent antibody responses to antigens [2]. The incidence is approximately 1:50.000–1:25.000 [3]. CVID is a heterogeneous immunodeficiency group with a wide clinical spectrum. Clinical presentations include recurrent bacterial infections, autoimmunity, lymphoproliferative disorders, enteropathy, allergic diseases, and malignancy [4]. Cardiovascular disorders are rare among clinical manifestations of CVID [5]. Cardiovascular diseases are a major health problem worldwide, and heart failure (HF) is among the leading causes of cardiovascular mortality [6]. Since the left ventricular is usually considered in cardiological evaluation, the right ventricular (RV) has remained in the shadow of the left ventricular, but in recent years, it has been understood that the RV is a determining factor for survival, especially in pathologies such as HF and pulmonary hypertension, and its evaluation is necessary [7]. Right HF patients with preserved ejection fraction (EF) constitute approximately 50% of the HF population and are associated with increased mortality [8]. Approximately 1/3 of patients with CVID have chronic lung disease at the time of diagnosis, which frequently includes bronchiectasis, obstructive and restrictive lung diseases, and nonsarcoid granulomatous diseases [9]. In CVID, chronic pulmonary complications such as bronchiectasis due to recurrent respiratory tract infections may lead to RV strain and dysfunction [10, 11]. Copeptin is a 39-amino acid neuropeptide derived from the C-terminus of vasopressin prohormone released from the hypothalamus [12]. Many pathological and physiological stimuli, including pain, hypoxemia, hypoglycemia, infection, stroke, and shock, trigger copeptin release. Elevated serum copeptin levels are associated with poor prognosis in various diseases, including myocardial infarction, respiratory diseases, HF, stroke, and diabetes mellitus [13]. Serum copeptin level is not routinely measured in the diagnosis and follow-up of CVID. In two previous studies, it was emphasized that serum copeptin levels were increased in acute exacerbation of chronic obstructive pulmonary disease (AECOPD) and patients with RV dysfunction, and serum copeptin may be an interesting marker in these patient groups [14, 15].

This study investigated the potential association between copeptin levels and right ventricular functions (RVF) and pulmonary complications in patients with CVID. Identifying such a relationship may contribute to early diagnosis, individualized treatment, and improved clinical management in this patient population.

In this way, a specific parameter for the development of RV dysfunction and pulmonary complications in the follow-up of patients with CVID may guide clinical practice.

Materials and methods

Study design

This prospective cohort investigation was conducted at Necmettin Erbakan University Faculty of Medicine Hospital in Konya, Türkiye. Ethical clearance was obtained from the institution’s ethics review board (approval number: 2020/2962). Between December 2020 and January 2022, clinical data were collected from hospital records for patients and healthy volunteers (HVs) who met the study’s eligibility criteria. Inclusion criteria for the patient group required individuals to be 18 years or older and have a confirmed diagnosis of CVID. Exclusion criteria encompassed a previous history of myocardial infarction or cerebrovascular events that might influence serum copeptin concentrations, a left ventricular EF below 50%, the presence of moderate to severe aortic or mitral valve disease, and a diagnosis of pulmonary arterial hypertension (PAH). The HVs of inclusion criteria were ≥ 18 years and had no known chronic medical conditions. All HVs were fully informed about the nature and purpose of the study, and written informed consent was obtained from each participant before inclusion (Fig. 1).

Fig. 1.

Flow chart of patient inclusion in this study. CVID common variable immunodeficiency

Data collecting

Demographic characteristics (including age and sex), body mass index (BMI), comorbid conditions (hypertension, diabetes mellitus, cardiovascular diseases, hypercholesterolemia, smoker, cardiac family history etc.), past medical history of pulmonary and cardiac manifestations (bronchiectasis, fibrosis, arrhythmia etc.), laboratory datas (creatinine, immunoglobulin levels and flow cytometric values) and echocardiographic characteristics were extracted from the hospital’s electronic medical records.

Immunoglobulin measurements

Serum immunoglobulin levels were determined using nephelometric methods (Siemens BNII System, Erlangen, Germany). IgE results were expressed in international units (IU)/mL. IgG, IgM, and IgA measurements were expressed in mg/dL; IgG (mg/dl): 700–1600, IgM (mg/dl): 46–304, IgA (mg/dl): 70–400. An estimate of the glomerular filtration rate (eGFR) was derived using the Modification of Diet in Renal Disease (MDRD) method to assess kidney function [16].

Flow cytometric analysis

At the time of initial diagnosis, peripheral venous blood samples (2 mL) were obtained from a cohort of 60 individuals with confirmed CVID. The samples were anticoagulated with EDTA and processed within six hours of collection. Quantification of B and T lymphocyte subsets was performed using multicolor flow cytometry. Cellular analyses were conducted on a BD FACS Canto II Flow Cytometry System (BD Biosciences). The distribution of lymphocyte subpopulations was reported as percentages within reference intervals: CD3⁺ T cells (57–85%), CD3⁺CD4⁺ T cells (30–61%), CD3⁺CD8⁺ T cells (12–42%), CD19⁺ B cells (6–29%), and CD3⁻CD16⁺56⁺ natural killer (NK) cells (4–25%).

Echocardiography

Transthoracic echocardiographic evaluation was conducted using a Philips Epiq 7 C ultrasound system (Bothell, WA, USA) with a 5–1 MHz transducer. Two experienced cardiologists obtained all echocardiographic measurements using the standard protocols and imaging recommendations of the American Society of Echocardiography (ASE) [17]. Measurements were obtained with the patient in the left lateral decubitus position.

Left ventricular EF was calculated using Simpson’s biplane method. Standard imaging views were acquired, including parasternal long-axis, parasternal short-axis, apical four-chamber, and apical long-axis. All images were captured at a frame rate greater than 60 frames per second and recorded over a minimum of five cardiac cycles. Mitral inflow velocities, including early diastolic (E) and late diastolic (A) waves, were measured by pulsed-wave (PW) Doppler from the apical four-chamber view, positioning the sample volume approximately 1 cm below the mitral valve leaflet tips. Measurements were averaged over 5 to 10 cardiac cycles. Tissue Doppler-derived E/E′ ratios were obtained separately for both the septal and lateral mitral annular walls to assess left ventricular diastolic function.RV systolic and diastolic functions were evaluated. Diastolic RV parameters included systolic myocardial velocity (RV SM), early diastolic myocardial velocity (RV EM), late diastolic myocardial velocity (RV AM), and systolic RV parametre included tricuspid annular plane systolic excursion (TAPSE). Pulmonary artery systolic pressure (PAPs) was estimated from tricuspid regurgitation velocity. Left ventricular systolic and diastolic functions were comprehensively assessed. Ejection fraction was measured to evaluate left ventricular systolic function. The Ratio of mitral inflow (E)/ velocity to tissue Doppler (E’) (mitral E/E’ ratio ) was measured to evaluate left ventricular diastolic function.

Blood sampling

This study was conducted in a group of clinically stable outpatients with CVID who did not have conditions such as infection or renal failure. A 5 mL venous blood sample was collected from the antecubital vein of outpatients without the use of any medication that could affect serum copeptin levels, intravenous fluid infusion, or diagnostic imaging procedures. The samples were transferred to heparin-containing tubes and immediately stored on ice at 4 °C. The plasma was then separated by centrifugation at 4,000 rpm for five minutes and stored at -40 °C until analysis. All samples were brought to room temperature and thawed prior to measurement.

Serum copeptin measurement

Serum copeptin concentrations were quantified using a commercially available enzyme-linked immunosorbent assay (ELISA) kit (Catalog No: E-EL-H0851 96T; Elabscience, Texas, USA), which operates on the principle of competitive ELISA. The microplate included in the kit was pre-coated with human copeptin peptide (CPP). During the assay, biotinylated anti-human CPP antibodies in the sample or standard compete with a fixed amount of coated antigen for binding sites. After the competitive binding step, unbound substances were removed through washing. Horseradish peroxidase (HRP)-conjugated avidin was added to each well and incubated, followed by tetramethylbenzidine (TMB) substrate. A stop solution terminated the enzymatic reaction, and the resulting colorimetric change was measured spectrophotometrically at 450 ± 2 nm. Copeptin concentrations in the samples were determined by comparing the optical density (OD) values to a standard calibration curve. The copeptin assay’s lower detection limit was 2.44 pmol/L, and its functional sensitivity—defined by a coefficient of variation (CV) below 10%—was above 1.5 pmol/L. Among HVs, the mean copeptin level was 6.8 pmol/L with a standard deviation (SD) of 3.

Statistical analysis

All statistical procedures were executed using SPSS software (IBM, version 22.0; Armonk, NY, USA). The normality of distribution for continuous variables was assessed using the Kolmogorov-Smirnov and Shapiro-Wilk tests. For variables with a normal distribution, results were reported as the mean ± SD; non-normally distributed variables were described using the median and interquartile range (IQR). Categorical variables were absolute counts (n) and corresponding percentages (%). Relationships among categorical variables were evaluated using the Chi-square (χ²) test. For comparisons of continuous variables, the independent samples Student’s t-test was employed when data were normally distributed. In cases of non-normal distribution, the Mann-Whitney U test was utilized. The relationships between continuous variables were examined through Pearson or Spearman correlation, selected according to the normality of the data. The point-biserial correlation assessed the relationships between continuous and binary categorical variables. Logistic regression models were applied to determine the prognostic significance of serum copeptin in terms of pulmonary complications and RV dysfunction. Multivariate regression analysis was used to evaluate the relationship between immunological parameters and copeptin. The most appropriate cut-off points were assessed based on calculated sensitivity and specificity values, which were performed by receiver operating characteristic (ROC) curve analysis. A p-value of less than 0.05 was considered indicative of statistical significance.

Results

Study population

A total of 60 patients with CVID and 30 HVs were included in the study. The median (IQR) age of patients with CVID was 40 ( 30–55) years, and 31 (51.7%) were male.

Arterial hypertension (11.7%) and hypercholesterolemia (10%) were the most common cardiovascular risk factors. Arrhythmia (5%) was the most common cardiac manifestation (Table 1).

Table 1.

Demographic and clinical characteristics of patients with CVID

Characteristic	Patients (n = 60)
Sex, n (%)
Female	29 (48.3)
Male	31 (51.7)
Age, median (IQR), years	40 (30–55)
Cardiovascular risk factors, n (%)	15 (%25)
Arterial hypertension	7 (11.7)
Hypercholesterolemia	6 (10)
Diabetes mellitus	5 (8.3)
Smoker	5(8.3)
Cardiac family history	3 (5)
Obesity	5 (8.3)
Cardiac manifestations, n (%)	6 (10)
Arrhythmia	3 (5)
Pericardial diseases	2 (3.3)
Congenital heart diseases	1 (1.6)
Pulmonary complications, n (%)
Bronchiectasis	20 (33.3)
Fibrosis	10 (16.7)
GLILD	2 (3.3)
Obstructive lung diseases	16 (26.7)
Restrictive lung diseases	6 (10)
Laboratory values
Creatinine, median (IQR), mg/dL	0.8 (0.7–0.9)
GFR, median (IQR), mL/min/1.73 m2	107 (86–120)
Basal IgG, median (IQR), mg/dL	3.95 (1.7–5.3)
Basal IgM, median (IQR), mg/dL	0.25 (0.18–0.5)
Basal IgA, median (IQR), mg/dL	0.3 (0.23–0.97)
Basal IgE, median (IQR), IU/mL	18 (15.4–19)
CD3+ T cell, median, (IQR), %	77.5 (70.2–85)
CD19+ B cell, median, (IQR), %	6 (2–11)
CD3+CD4+ T cell, median, (IQR), %	34.5 (27.5–45)
CD3+ CD8+ T cell, median, (IQR), %	39.5 (32–50)
CD3− CD16+ CD56+ NK cells, median, (IQR), %	7 (5-9.7)
Copeptin, median (IQR), (pmol/L)	14 (10–21)

CVID common variable immunodeficiency, IQR interquartile range, GLILD granulomatous lymphocytic interstitial lung disease, GFR glomerular filtration rate, IgG, immunoglobulin G, IgM, immunoglobulin M, IgA immunoglobulin A, IgE immunoglobulin E, NK natural killer

Demographic, clinical and echocardiographic characteristics of patients with CVID and HVs

The median (IQR) age of HVs was 37 (28–47.5) years, and 18 (60%) were male. There was no significant difference between patients with CVID and HVs in terms of age (p = 0.226) or sex (p = 0.45). Median GFR and creatinine levels were similar in both groups, and there were no statistically significant differences (respectively, p = 0.13, p = 0.40).

In RV diastolic functions of patients with CVID, the median (IQR) RVSM was 13 (12-14.1) cm/sn, the median (IQR) RVEM was 14.8 (14.5–15.1) cm/sn, the median (IQR) RVAM was 13.5 (11.3–16.1) cm/sn and the median TAPSE was 2.2 (2-2.3) cm/sn.

RVSM, RVEM, RVAM, and TAPSE levels were higher in the patients with CVID than in HVs, but there was no statistically significant difference. In other echocardiographic parameters, there was no statistically significant difference between these groups. Serum copeptin levels were significantly higher in the patients with CVID than in HVs (p < 0.001) (Table 2).

Table 2.

Demographic, clinical and echocardiographic characteristics of patients with CVID and HVs

Variables	CVID patients n = 60	Healthy volunteers n = 30	P
Sex, n (%) Female	29 (48.3)	12 (40)	0.45
Male	31 (51.7)	18 (60)
Age, median (IQR), years	40 (30–55)	37 (28-47.5)	0.226
Creatinin, median (IQR), mg/dL	0.8 (0.7–0.9)	0.76 (0.7–0.81)	0.13
GFR, median (IQR), mL/min/1.73 m2	107 (86–120)	114 (94.7–126)	0.40
RVSM, median (IQR), (cm/sn)	13 (12-14.1)	11.8 (11.5–12)	0.08
RVEM, median (IQR), (cm/sn)	14.8 (14.5–15.1)	13 (11.3–14)	0.075
RVAM, median (IQR), (cm/sn)	13.5 (11.3–16.1)	8.77 (8.4–9.2)	0.077
TAPSE, median (IQR), (mm)	2.2 (2-2.3)	2.1 (1.9–2.5)	0.87
PAP, median (IQR), (mmHg)	28 (25–30)	23.5 (22–25)	0.25
EF, median (IQR)	60 (50–60)	63 (60–65)	0.065
E/E’ Septal, median (IQR)	7.3 (6.5–8.2)	5.75 (5.6–5.9)	0.07
E/E’ Lateral, median (IQR)	6.5 (6-7.1)	5.67 (5.5–5.8)	0.076
LVESD, median (IQR), (cm)	2.6 (2.3–2.97)	2.82 (2.5–3.1)	0.16
LVEDD, median (IQR), (cm)	4.4 (4.1–4.7)	4.6 (4.33–4.86)	0.17
Aortic diameter, median, (IQR), (cm)	2.4 (2.2–2.7)	3 (2.83–3.4)	0.09
Copeptin, median (IQR), (pmol/L)	14 (10-21.7)	5.8 (4.6–9.6)	< 0.001

Bold p< 0.05 value indicate statistically significant differences

CVID common variable immunodeficiency, HVs healthy volunteers, IQR interquartile range, GFR glomerular filtration rate, RVSM systolic myocardial velocity, RVEM early diastolic myocardial velocity, RVAM late diastolic myocardial velocity, TAPSE tricuspid annular plane systolic excursion, PAP pulmonary artery pressure, EF ejection fraction, E/E’ ratio of mitral inflow (E), velocity to tissue Doppler (E’), LVESD, left ventricular end systolic diameter, LVEDD left ventricular end diastolic diameter

*Intergroup comparisons were conducted using the chi-square, and independent samples T tests, as appropriate

TAPSE is easily obtainable and is a measure of RV longitudinal function, and TAPSE < 16 mm indicates RV systolic dysfunction [18]. Patients with CVID were divided into 2 groups: 10 (16.6%) with low TAPSE (< 16 mm) and 50 (84.4%) without low TAPSE. Median (IQR) copeptin levels were higher in the group with low TAPSE, and this difference was statistically significant (respectively, 22.5 pmol/L vs. 12.5 pmol/L, IQR (21.5–27 vs. 8.8–18 ), p = 0.007) (Fig. 2). ROC analysis identified a cut-off copeptin level of 21 pmol/L for distinguishing the CVID patients with low TAPSE from the CVID patients without low TAPSE, with 80% sensitivity and 94% specificity (area under the curve [AUC] 0.953; 95% CI, 0.900–1.000; p < 0.001) (Fig. 3).

Fig. 2.

Distribution of plasma copeptin concentrations according to subgroup of reduced TAPSE in CVID. Data are presented as medians with 25th and 75th percentiles. TAPSE tricuspid annular plane systolic excursion

Fig. 3.

ROC curves revealing valuable discrimination of CVID patients with reduced TAPSE of < 16 mm by serum concentrations of copeptin. ROC receiver-operating characteristic, TAPSE tricuspid annular plane systolic excursion

Copeptin and echocardiographic right ventricular function parameters

Pearson correlation analysis was used to determine the relationship between copeptin and RVF in CVID patients. A strong negative correlation was found between TAPSE and copeptin (Table 3). In logistic regression analysis on CVID patients, low TAPSE was determined as an independent risk factor for the copeptin elevation (odds ratio (OR) = 0.738; 95% confidence interval (CI) = 0.610–0.910; p = 0.004) (Table 4).

Table 3.

Multiple correlations between echocardiographic right ventricular functions and copeptin

Parameter	Correlation coefficients (Pearson)	P
TAPSE (mm)	r= -0.72	< 0.001
RVSM (cm/sn)	r = 0.118	0.36
RVEM (cm/sn)	r = 0.08	0.54
RVAM (cm/sn)	r = 0.07	0.6

Bold p< 0.05 value indicate statistically significant differences

TAPSE tricuspid annular plane systolic excursion, RVSM systolic myocardial velocity, RVEM early diastolic myocardial velocity, RVAM late diastolic myocardial velocity

Table 4.

Logistic regression model to evaluate associations with copeptin

	(OR)	(CI)	P
TAPSE (< 16 mm)	0.738	0.610–0.910	0.004
Pulmonary Complications	0.912	0.825–0.968	0.006

TAPSE tricuspid annular plane systolic excursion, OR odds ratio, CI 95% confidence interval

Demographic and clinical findings of CVID patients with and without pulmonary complications

The patients with CVID were divided into 2 groups: those with pulmonary complications (CVID-P) and those without pulmonary complications. Among all the patients with CVID, 50% (n = 30) had at least one concomitant pulmonary disease. Bronchiectasis (n = 20 [33.3%]) was the most common pulmonary complication (Table 1). More patients with CVID-P were women (n = 18 [60%]); the median (IQR) age of patients with CVID-P was 40.5 years [32–60]. There were no significant differences between patients with CVID-P and patients with CVID without pulmonary complications in terms of sex (p = 0.21), median age (p = 0.110), BMI(p = 0.405), or comorbidity (p = 0.76). Median (IQR) basal immunoglobulin (Ig) G was lower in the CVID-P group, but there was no statistically significant difference (p = 0.093). There was no statistically significant difference between the two groups in terms of other median (IQR) baseline Ig values. The relationship between pulmonary disease and B and T lymphocyte subgroups was examined; no significant difference was found between the two groups (Table 5).

Table 5.

Demographic and clinical characteristics of patients with CVID and with and without pulmonary complications

Variable	CVID-P n = 30	CVID-non P n = 30	P*
Sex, n (%)
Female	18 (60)	14 (46.7)	0.21
Male	12 (40)	16 (53.3)
Age, median (IQR), years	40.5 (32–60)	38 (27–47)	0.11
BMI, median (IQR), kg/m2	24 (18–32)	26 (19–33)	0.405
**Comorbidity	7 (23.3)	8 (26.7)	0.76
Basal IgG, median (IQR), mg/dL	2.6 (1.5–5.3)	4.45 (2.4–5.45)	0.093
Basal IgM, median (IQR), mg/dL	0.2 (0.18–0.5)	0.29 (0.17–0.5)	0.912
Basal IgA, median (IQR), mg/dL	0.30 (0.2–1.2)	0.35 (0.25–0.9)	0.28
Basal IgE, median (IQR), IU/mL	17.5 (14.7–19.2)	18 (15.7–19)	0.88
CD3+ T cell, median, (IQR), %	77.5 (69.5–85)	68 (63–80)	0.71
CD19+ B cell, median, (IQR), %	6 (2–10)	7 (1–13)	0.57
CD3+CD4+ T cell, median, (IQR), %	33 (22–42)	35 (29–45)	0.188
CD3+ CD8+ T cell, median, (IQR), %	42.5 (33.7–53)	38 (30–49)	0.151
CD3− CD16+ CD56+ NK cells, median, (IQR), %	7 (5.7–9.2)	7 (5-12.5)	0.84
Copeptin, median (IQR), (pmol/L)	19 (14–22)	10 (7–13)	< 0.001

CVID-P common variable immunodeficiency with pulmonary complications, CVID-non P common variable immunodeficiency without pulmonary complications, IQR interquartile range, BMI body mass index, IgG immunoglobulin G, IgM immunoglobulin M, IgA immunoglobulin A, IgE immunoglobulin E, NK natural killer

*Intergroup comparisons were conducted using the chi-square, and Mann–Whitney U tests, as appropriate

**Comorbidity; Hypertension, diabetes mellitus, cardiovascular diseases, hyperlipidemia, etc.

Relationship between copeptin and pulmonary complications

In the patients with CVID-P, the median (IQR) serum copeptin level was 19 pmol/L [14–22]. Copeptin levels were significantly higher in the patients with CVID-P than in CVID patients without pulmonary disease (p < 0.001) (Fig. 4).

Fig. 4.

Distribution of plasma copeptin concentrations in CVID with and without pulmonary complications. Data are presented as medians with 25th and 75th percentiles. CVID-P, common variable immunodeficiency with pulmonary complications; CVID-non P, common variable immunodeficiency without pulmonary complications

ROC analysis identified a cut-off copeptin level of 11 pmol/L for distinguishing the patients with CVID-P from the CVID patients without pulmonary disease, with 70% sensitivity and 96% specificity (area under the curve [AUC] 0.881; 95% CI, 0.812–0.951; p < 0.001) (Fig. 5). Pearson correlation analysis was used to determine the relationship between copeptin and pulmonary diseases in CVID patients. A moderate positive correlation was found between copeptin and the development of pulmonary complications (r = 0.553, P < 0.001).

Fig. 5.

ROC curves revealing valuable discrimination of CVID with pulmonary complications by serum concentrations of copeptin. ROC, receiver-operating characteristic; CVID, common variable immunodeficiency

In a logistic regression analysis of CVID patients, the presence of pulmonary complications was identified as an independent risk factor for copeptin elevation (odds ratio (OR) = 0.912; 95% confidence interval (CI) = 0.825–0.968; P = 0.006) (Table 4).

Relationship between immune parameters and copeptin

The relationship between copeptin and B and T lymphocyte subgroups was examined. However, there was no statistically significant difference (Table 6).

Table 6.

Multivariable linear regression model to evaluate associations with copeptin and

immunological parameters

Parameter	B		Standard error	Beta	T	P
Creatinin	-13.902		16.593	-0.196	–0.838	0.406
GFR	-0.127		0.092	-0.281	-1.382	0.173
IgG	-0.714		1.703	− 0.0.083	-0.419	0.677
IgM	-2.019		3.994	-0.079	-0.505	0.616
IgA	5.596		5.518	0.228	1.014	0.316
IgE	0.135		0.154	0.143	0.877	0.385
CD3+ T cell	0.099		0.442	0.066	0.224	0.824
CD3+CD4+ T cell	-0.008		0.333	-0.007	-0.023	0.981
CD3+ CD8+ T cell	-0.025		0.322	-0.019	-0.076	0.940
CD19+ B cell	-0.107		0.532	-0.039	-0.202	0.841
NK cells	0.319		0.648	0.091	0.492	0.625

GFR glomerular filtration rate, IgG immunoglobulin G, IgM immunoglobulin M, IgA immunoglobulin A, IgE immunoglobulin E, NK CD3- CD16+ CD56+ natural killer

Discussion

In this study, serum copeptin levels were significantly higher in CVID patients with low TAPSE values ​​compared to CVID patients without low TAPSE values. The presence of lower than normal TAPSE values in the patients with CVID constituted an independent risk factor for the copeptin rise. Another remarkable finding of our study is that serum copeptin levels were significantly higher in the patients with CVID-P than in the patients with CVID and without pulmonary complications. The presence of pulmonary disease in the patients with CVID constituted an independent risk factor for the copeptin rise.

The arginine vasopressin (AVP) system is a neuroendocrine structure that plays a key role in maintaining fluid-electrolyte balance and haemodynamic stability in the body. AVP is synthesised in the paraventricular and supraoptic nuclei of the hypothalamus and transported to the posterior pituitary (neurohypophysis) via axons. Here, it is stored for release into the circulation in response to physiological signals such as changes in plasma osmolality or stimuli related to the circulatory system. AVP is derived from a precursor molecule called preprovasopressin. This precursor structure also contains copeptin along with AVP. The conversion of the hormone into its active components occurs through a multi-step maturation mechanism involving a series of enzymatic processes. In the first step of this process, the signal peptide is cleaved off, followed by the separation of AVP and copeptin into their functional forms. As a result, AVP and kopeptin are released into the circulation simultaneously in response to physiological stimuli [19, 20]. Under physiological conditions, the release of AVP is primarily regulated by plasma osmolality [21]. However, it is not only osmotic changes; vasoactive substances such as angiotensin II and norepinephrine can also directly stimulate AVP secretion [22]. This situation shows that the AVP system is closely related not only to fluid balance but also to cardiovascular stability. Copeptin is a stable biomarker representative of the hormone AVP [19]. However, AVP is difficult to measure directly; therefore, copeptin, which is secreted together with it, is used as a more reliable and easily measurable alternative [20]. Copeptin is stable in EDTA plasma at room temperature for up to 14 days and in citrate and heparin plasma for 7 days [23]. No complex preanalytical steps are required for its detection [24]. Copeptin can be easily measured ex vivo by manually or fully automatically chemiluminescence [25]. The test requires a minimum of serum or plasma and analysis time 20 to 30 min [24].

In inflammatory conditions, inflammatory mediators such as interleukin (IL)-1 and tumor necrosis factor-α can trigger AVP secretion. As a result, copeptin levels also rise [26].

IL-2 and norepinephrine can also stimulate AVP release from the hypothalamus [27].

In a previous study, AVP and, consequently, copeptin levels were higher in patients with severe sepsis and septic shock than in patients with infection without inflammation [26].

In another study conducted with sepsis patients, plasma copeptin levels were higher in septic shock patients than in healthy controls [28]. In a study conducted on individuals with advanced chronic liver disease (ACLD), it was emphasised that plasma copeptin levels showed an independent relationship with IL-6 levels and that systemic inflammation could be one of the underlying factors behind increased AVP levels in decompensated ACLD [29].

Another study reported that increasing doses of intravenous recombinant IL-6 strongly stimulated the hypothalamic-pituitary-adrenal axis and induced systemic AVP secretion [30].For these reasons, copeptin may be considered clinically significant due to its significant relationship with neuroendocrine stress and inflammatory responses in non-cardiovascular conditions.

CVID is a complex disease that is characterised not only by antibody deficiency but also by systemic and organ-specific inflammatory complications. Autoimmune, granulomatous, and interstitial lung diseases, as well as gastrointestinal diseases caused by inflammation, are important in terms of mortality and morbidity. This information supports our study, which suggests that copeptin should not be overlooked in CVID, a disease group that may be accompanied by inflammation.

In healthy controls, median copeptin concentrations were reported 4.7 (IQR 2.9–7.6) pmol/L [31, 32]. Similarly, in this study, the median copeptin was 5.79 pmol/L in HVs.In addition, copeptin shows minimal interindividual differences (age, sex, eGFR, etc.) [32]. The prevalence of HF in the adult population is reported to be around 1–2% [33]. HF is associated with a elevated mortality rate and HF treatment imposes a large economic burden on healthcare systems [34]. In a previous study, the predictive ability of copeptin for the entire spectrum of HF was investigated and it was emphasised that it was independently associated with mortality in all symptomatic stages of HF and was the strongest predictor of death in New York Heart Association (NYHA) class II and III [35]. In another study of patients with HF symptoms, the association between plasma concentrations of copeptin and mortality was evaluated, and elevated copeptin concentrations were associated with an increased risk of all-cause mortality [36].

A wide variety of congenital and structural cardiovascular diseases have been reported in primary immunodeficiencies (Atrial septal defect, ventricular septum defect, patent ductus arteriosus, mitral, tricuspid, and pulmonary insufficiency, HF, bradycardia, ischemic heart disease, etc.). CVID is not usually associated with cardiovascular diseases [5]. The possible association between CVID and cardiac manifestations might be due to immune dysregulation like autoimmunity.

In a case report, a patient with CVID of acute giant cell myocarditis diagnosed by endomyocardial biopsy was mentioned, and it is an autoimmune myocarditis [37].

Cases of acute pericarditis in CVID have been reported in earlier research. It was noted that all patients had a history of recurrent respiratory infections, and in one case, bacterial growth was detected during the episode of acute pericarditis, suggesting a possible infectious etiology in this context [38]. Moreover, prior investigations have proposed a role for autoimmunity in the pathogenesis of pericardial diseases [39, 40].

In a former research with 337 CVID patients, 9.1% with cardiac manifestations were found. Pericardial disease was reported in 1.7%, arrhythmia in 1.1%, and congenital heart disease in 1.1% [41]. Similarly, in this study, cardiac manifestations were found in 10% of CVID patients, arrhythmia in 5%, pericardial disease in 3.3%, and congenital heart disease in 1.6%.

Studies have generally focused on left-sided HF with either reduced or preserved EF; however, RVF were shown to be an independent predictor of survival in a study of patients with stable HF [42].

Transthoracic echocardiography is the standard diagnostic technique for evaluating RVF due to its widespread availability, easy applicability, and low cost [43]. TAPSE is the main parameter for assessing RVF by transthoracic echocardiography [44]. Preceding investigations have shown that TAPSE is strongly correlated with RVF and is the dominant parameter in the evaluation of RVF [45, 46]. A prior research has shown that copeptin concentrations are inversely related to TAPSE. Moreover, it has been shown that clinically significant stages of RV dysfunction, defined by TAPSE below 18–14 mm, were reliably distinguished by copeptin concentrations [15]. Similarly, in the present study, copeptin was found to be elevated in CVID patients with TAPSE values lower than 16 mm and an inverse relationship was found between TAPSE and copeptin. This suggests that copeptin may be a predictive biomarker in the evaluation of RVF in CVID patients.

Chronic lung diseases are the leading cause of mortality and morbidity in patients with CVID [47]. According to earlier studies, the prevalence of chronic lung disease in individuals with CVID ranges from 28 to 62% [48, 49]. Among the pulmonary complications associated with CVID, the most common lung disease diagnosed is %40 bronchiectasis [50]. In previous study, bronchiectasis was reported 28.5% in patients with CVID [51]. In this study, bronchiectasis was detected at a rate of 33.3%. Bronchiectasis results from progressive damage to the bronchial wall secondary to recurrent lower respiratory tract infections and inflammation, progressing before the start of immünoglobulin replacement treatment (IgRT) and sometimes despite adequate IgRT [52]. Pulmonary diseases may progress without signs of infection, therefore monitoring of pulmonary complications with imaging, pulmonary function tests and microbial culture methods is recommended in CVID [53].

There are studies on the effect of copeptin on prediction and prognosis in pulmonary diseases. In a study conducted with acute pulmonary embolism patients, copeptin level was found to be significantly higher than in healthy control group. Moreover, copeptin was significantly higher in PE-related death and who developed RV disfunction at one-year follow-up. Addition, similarly in this study, there was moderate and negative correlation between copeptin and TAPSE [54]. In a earlier study, copeptin was reported to be a prognostic marker in AECOPD [55]. In another study, it was emphasized that copeptin levels were elevated in patients with lower respiratory tract infection, and copeptin levels were higher in patients with AECOPD and acute bronchitis due to lower respiratory tract infection than in the control group [56]. In another multicentre study, copeptin was found to be a predictive biomarker of two-year mortality in stable chronic obstructive pulmonary disease independent of selected pulmonary risk factors [57]. In this study, supporting this informations, it was determined that copeptin may be predictive of pulmonary complications in CVID.

Granulomatous lymphocytic interstitial lung disease (GLILD) is a complex interstitial lung disease characterised by granulomatous and lymphocytic infiltration, seen particularly in patients with CVID (approximately 20%) [58]. There is no specific biomarker unique to GLILID, but certain laboratory, radiological, and immunological findings are considered helpful biomarkers in the diagnosis and monitoring process [59]. Peribronchial and interstitial chronic inflammation are among the most commonly observed histopathological features in GLILD [58]. A study conducted in association with GLILD indicates that this condition frequently co-occurs with granulomatous and inflammatory processes [59]. In this study, two patients had a diagnosis of GLILD. Plasma copeptin levels were 30 pmol/L and 20 pmol/L respectively. These values were above the cut-off values established for pulmonary diseases. However, there was no statistically significant difference in copeptin levels and other parameters between CVID patients diagnosed with GLILD and CVID patients with other pulmonary diseases. This may be related to the small number of patients with GLILD. Nevertheless, this finding supports the importance of copeptin as a biomarker in diffuse lung parenchymal diseases such as GLILD, where diagnosis is challenging in CVID.

Previous studies have described RV dysfunction in patients with chronic lung disease [60]. Hypoxaemia plays an important role in affecting RVF [61]. In patients with bronchiectasis, chronic hypoxaemia may lead to an increase in pulmonary vascular resistance and cause RV dysfunction [62]. In a former research, it was suggested that haemodynamic changes may occur in the lungs of patients with bronchiectasis. When the systemic-pulmonary anastomoses that develop in granulomatous areas at the sites of destruction of the bronchial wall in bronchiectasis expand, oxygenated blood shunts from the high-pressure systemic bronchial and intercostal arteries to the low-pressure pulmonary circulation. Chronic shunt flow can lead to elevated PAPs and thus RV dysfunction [63]. As in this study, these data support that the development of pulmonary complications and RV dysfunction should not be ignored considering that pulmonary diseases are frequently observed in CVID.

For some diseases, diagnosis and prognosis can be very demanding and time-consuming. So clinicians need new biomarkers for faster treatment decisions and prognostic evaluation [13]. A new biomarker should be practical, reliable, easy to measure, fast and cheap. Therefore, copeptin is proposed as a prognostic biomarker that may help early diagnosis and diagnostic accuracy in different diseases. In CVID, an algorithmic diagnostic approach is applied at specific intervals to monitor malignancy, autoimmunity, and granulomatous diseases (Clinical examination, every 3–6 months complete blood count, liver function tests, IgG level, annual lymphadenopathy/splenomegaly check, chest CT scan every 1–2 years, annual gastrointestinal system screening (as needed), etc.) [64].

According to this study, the following new copeptin cut-off values are recommended to contribute to the algorithmic diagnostic approach in CVID: plasma copeptin levels greater than 21 pmol/L (with over 90% specificity for RV dysfunction); plasma copeptin levels greater than 11 pmol/L (with over 90% specificity for pulmonary complications).

These mentioned cases indicate that copeptin may be an important biomarker in the monitoring of the development of RV dysfunction classified with TAPSE < 16 mm in CVID patients and in the follow-up of the development of pulmonary diseases, which is one of the frequently observed complications in CVID.

This study had some limitations. First, this cross-sectional study was a single-center study with a limited sample size. Second, although the study was prospectively planned, copeptin levels and echocardiographic parameters were measured at only one time point. Serial measurements would have better reflected time-dependent changes in disease activity or treatment response. Third, did not include long-term follow-up analyses of any patients. Despite these limitations, our study may shed light on future studies on the role of copeptin as a predictive biomarker for developing pulmonary diseases and RV dysfunction in patients with CVID. However, large-scale multicenter studies are needed to re-evaluate our findings.

Conclusion

Early diagnosis and treatment are important for reducing CVID-related complications. Thus, there is a need to monitor the development of pulmonary and cardiac complications to prevent diagnostic delays and provide adequate pharmacologic treatment to patients with CVID, both at the time of diagnosis and during clinical follow-up.

Serum copeptin levels were elevated during the development of pulmonary diseases and RV dysfunction in CVID. Measuring serum copeptin concentration may help predict the diagnosis and prognosis of pulmonary diseases and RV dysfunction in CVID. Further studies are needed to elucidate the role of copeptin as a valuable biomarker in patients with CVID.

Abbreviations

CVID

Common variable immunodeficiency

HVs

Healthy volunteers

HF

Heart failure

IQR

Interquartile range

BMI

Body mass index

AVP

Arginine vasopressin

EF

Ejection fraction

RV

Right ventricular

AECOPD

Chronic obstructive pulmonary disease

RVF

Right ventricular functions

MDRD

The modification of the diet in renal disease

OR

Odds ratio

Egfr

Estimate the glomerular filtration rate

ROC

Receiver operating characteristic

CVID-P

CVID with pulmonary complications

TAPSE

Tricuspid annular plane systolic excursion

RVSM

Systolic myocardial velocity

RVEM

Early diastolic myocardial velocity

RVAM

Late diastolic myocardial velocity

IgRT

Immünoglobulin replacement treatment

SD

Standard deviation

PAPs

Pulmonary artery systolic pressure

GLILD

Granulomatous lymphocytic interstitial lung disease

Author contributions

MK and FÇ conceptualized and designed the study. MK and ŞA performed data acquisition and analysis. FSA, RE and EY interpreted the results. BF, MD and YA revised the manuscript critically for intellectual content.ST drafted the initial manuscript. All authors reviewed and approved the final manuscript.

Funding

This study was not supported by any funding source.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

This study was approved by the local ethics committee of Necmettin Erbakan University Medical Faculty Hospital, Konya, Türkiye (decision no. 2020/2962). All procedures were conducted in accordance with the Declaration of Helsinki.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.