Altered serum stress neuropeptide levels in critically ill individuals and associations with lymphocyte populations

Neuropeptides 47 (2013) 25–36

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Altered serum stress neuropeptide levels in critically ill individuals and associations with lymphocyte populations Meropi D.A. Mpouzika a,1, Elizabeth D.E. Papathanassoglou b,⇑,1, Margarita Giannakopoulou c, Evangelos Bozas d, Nicos Middleton b, Sofia Boti e, Elisabeth I. Patiraki c, Andreas Karabinis f a

Technological Educational Institute (TEI) of Athens, Department of Nursing B0 , Faculty of Health and Caring Professions, Greece Cyprus University of Technology, Department of Nursing, Siakolas Centre for Health Studies, Latsia, Nicosia 2252, Cyprus c University of Athens, School of Nursing, Athens, Greece d University of Athens, School of Nursing, Paediatrics Research Laboratory, Athens, Greece e University of Athens, School of Medicine, Department of Pathophysiology, Athens, Greece f Surgical Care Unit, Onassis Cardiac Surgery Center, Athens, Greece b

a r t i c l e

i n f o

Article history: Received 20 March 2012 Accepted 19 July 2012 Available online 12 September 2012 Keywords: Stress Neuropeptides Neuropeptide Y Substance P Lymphocyte Critical illness

a b s t r a c t Objective: Potential physiological correlates of stress and the role of stress neuropeptides, other than those of the hypothalamic-pituitary–adrenal axis, in critical illness have not been addressed. We investigated: (a) serum levels of stress neuropeptides (ACTH, substance P (SP), neuropeptide Y (NPY), cortisol, prolactin) in critically ill individuals compared to matched controls, (b) associations with lymphocyte counts, (c) associations among stress neuropeptide levels, and (d) associations with perceived intensity of stress, critical illness severity and survival. Methods: Correlational design with repeated measures. Thirty-six critically ill patients were followed up for 14 days compared to 36 healthy matched controls. Stress was assessed by the ICUESS scale. Correlations, cross-sectional comparisons and multiple regression models were pursued. Results: For the first time, we report lower SP (Difference of means (DM) = 2928–3286 ng/ml, p < 0.001) and NPY (DM = 0.77–0.83 ng/ml, p < 0.0001) levels in critically ill individuals compared to controls. Cortisol levels were higher (DM = 140–173 ng/ml, p < 0.0001) and lymphocyte population counts (p < 0.002) were lower in patients throughout the study. NPY levels associated with lymphocyte (r = 0.411–0.664, p < 0.04), T-lymphocyte (r = 0.403–0.781, p < 0.05), T-helper (r = 0.492–0.690, p < 0.03) and T-cytotoxic cell populations (r = 0.39–0.740, p < 0.03). On day 1, cortisol levels exhibited associations with lymphocyte (r = 0.452, p = 0.01), T-cell (r = 0.446, p = 0.02), T-helper (r = 0.428, p = 0.026) and T-cytotoxic cells (r = 0.426, p = 0.027). ACTH levels associated with NK cell counts (r = 0.326–0.441, p < 0.05). Associations among stress neuropeptides levels were observed throughout (p < 0.05). ACTH levels associated with disease severity (r = 0.340–0.387, p < 0.005). A trend for an association between ACTH levels and intensity of stress was noted (r = 0.340, p = 0.057). Conclusion: The significantly lowered NPY and SP levels and the associations with cortisol, ACTH and lymphocytes suggest that the role of these peptides in critical illness merit further investigation. Future studies need to address associations between these neuropeptides and functional immune cell responses and inflammatory markers in critical illness. Ó 2012 Elsevier Ltd. All rights reserved.

Abbreviations: ACTH, adrenocortocotropic hormone; CD, complex of differentiation; CNS, central nervous system; ECLIA, Electrochemiluminescence assay; ELISA, enzymelinked immunosorbent assay; GCS, Glasgow Coma Scale; HPA, hypothalamic-pituitary-adrenal; MODS, multiple organ dysfunction syndrome & multiple organ dysfunction score; MOF, multi organ failure scoring system; NK, natural killers; NPY, neuropeptide Y; PRL, prolactin; SP, substance P. ⇑ Corresponding author. Address: University of Athens, School of Nursing, 123 Papadiamantopoulou Street, 11527 Athens, Greece. Tel.: +357 22001643, 22001608; fax: +357 22001833. E-mail addresses: [email protected] (M.D.A. Mpouzika), [email protected] (E.D.E. Papathanassoglou), [email protected] (M. Giannakopoulou), [email protected] (E. Bozas), [email protected] (N. Middleton), sofi[email protected] (S. Boti), [email protected] (E.I. Patiraki), [email protected] (A. Karabinis). 1 Drs. M. Mpouzika and E. Papathanassoglou contributed to this study equally. 0143-4179/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.npep.2012.07.007

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1. Introduction Critical illness is characterized by excessive stress, physiological as well as psychological (Dünser and Hasibeder, 2009; Uhlig and Kallus, 2004). Cellular and organismic responses to stress are key factors for the outcome of critical illness, since uncompensated stress may precipitate the pathophysiologic cascade of multiple organ dysfunction (MODS), which is a fatal syndrome with no effective means of treatment or prevention to date (Cobb et al., 2008; Fink and Evans, 2002; Papathanassoglou et al., 2010). Stress responses are not specific to the type of stressor. Either psychological or physiological stimuli activate equally the hypothalamicpituitary–adrenal (HPA) axis and specific sub-cortical and cortical centres that may elicit similar bodily responses (Scantamburlo et al., 2001). Ample research results reveal that critically ill individuals experience intense stress states, ranging from anxiety and fear to terror and panic (Lusk and Lash, 2005). Moreover, scarce but remarkable research evidence suggests improved patient outcomes in critical illness through use of psychological support approaches (Papathanassoglou, 2010). Stress neuropeptides, including NPY (Gray, 2008; Parker and Balasubramaniam, 2008), SP (O’Connor et al., 2004; Tavano et al., 2012; Wang et al., 2012), PRL (Bolyakov and Paduch, 2011) and ACTH (Fantidis, 2010; Ottaviani et al., 1999) have been involved in the development of disease. Moreover, although emotional stress, has been established as a factor in the development of pathophysiologic effects in a number of disease states (McEwen and Gianaros, 2010), including heart disease (Adameova et al., 2009), cancer (Godbout and Glaser, 2006) and inflammatory states (Cámara et al., 2009), the organismic effects of stress in critical care remain to be investigated (Papathanassoglou et al., 2010). The investigation of stress effects in critical illness may provide new insight for the improvement of patient outcomes. Nonetheless, the study of stress in critical illness is intricate, due to lack of specific assessment tools, but mainly due to constraints in patient communication related to endotracheal intubation, neurological status, sedation and weakness (Happ et al., 2011). Ideally, indirect measures of stress assessment (i.e., stress hormone quantification) could provide more direction for the care of these patients. Nonetheless, the study of stress in critical illness is still in its infancy (Papathanassoglou et al., 2011). In the present study we investigated, for the first time, levels and associations of neuropeptides typically involved in stress responses in critically ill individuals. Although the study of stress neuropeptides in critical illness may be beset with many limitations, mainly due to the pleiotropic nature of these peptides, and the still unclear association between central nervous system (CNS) and peripheral levels in humans (Egleton and Davis, 2005), it may nevertheless provide valuable insight into stress and cellular responses in critical illness. The widespread localization of stress neuropeptidic receptors – including NPY, SP, PRL and endorphins – on peripheral tissues, including immune cells (Gonzalez-Rey and Delgado, 2007; Mak et al., 2011; Sharp, 2003; Snoek et al., 2010; Xu et al., 2010; Wheway et al., 2007), and evidence on the involvement of these peptides in pathophysiologic phenomena central to critical illness survival suggest that the study of stress neuropeptides is of interest in critical care (Papathanassoglou et al., 2010). Systemic effects of neuropeptides relevant to critical illness include vasoactive actions (Hodges et al., 2009; Gonzalez et al., 2004), regulation of immunity (Zukowska et al., 2003), modulation of endothelial responses (Abdel-Samad et al., 2007) and oxidative stress (Li et al., 2008). Deregulation of immunity is one of the most prominent derangements in critical illness, which has been linked to increased mortality and morbidity (Marshall et al., 2008). Immune responses are

highly integrated with neuroendocrine activation (Roszman and Brooks, 1997), and these two mechanisms should not be studied in isolation (Dimitrijevic´ and Stanojevic´, 2011). Most neuropeptides exert significant immunomodulatory actions (Ottaviani et al., 1999). For example, NPY is involved in immunocyte recruitment and adhesion (Dimitrijevic´ and Stanojevic´, 2011), it enhances the Th2 immune response (Kawamura et al., 1998); whereas its effects on lymphocyte proliferation are bimodal (Wheway et al., 2007). SP stimulates CD4+ and CD8+ T cells (Ikeda et al., 2007), it drives secretion of several immunomodulatory cytokines, including interleukin (IL)-1, IL-2, IL-3, IL-6 and tumor necrosis factor (TNF)-a, and it is involved in immune cell trafficking (Katsanos et al., 2008; Rameshwar, 1997). PRL receptors are expressed on both B- and T-lymphocytes, and alterations in plasma PRL may be implicated in immune disorders (Luca, 1997). Sporadic research evidence, implicates some of the vasoactive stress neuropeptides, including NPY and SP, in the pathophysiology of sepsis and shock in critical illness. Specifically, elevated NPY levels have been reported in humans with sepsis and septic shock (Arnalich et al., 1995), and experimental sepsis appears to induce long-lasting increases in NPY levels (Kuncová et al., 2011; Wang et al., 1992), correlated with changes in the systemic vascular resistance (Kuncová et al., 2011). In human sepsis, contradictory results on SP levels have been reported (Arnalich et al., 1995; Beer et al., 2002). However, NPY and SP levels and potential correlates have not been explored in critically ill individuals without sepsis and shock. In addition, apart from being vasoactive peptides, NPY and SP are also involved in immunity, inflammation and stress (Bhatia, 2010; Holler et al., 2008). Therefore, it is important to study their levels in critical illness states. The multisociety task force for critical care research (Deutschman et al., 2012) has recently identified the need to extend therapeutic manipulation of the neuro-inflammatory state beyond current approaches. The study of stress neuropeptides and of their effects on immunity and inflammation in the critically ill may provide new insight towards this end. The aims of the present study were to explore levels of stress neuropeptides in non-septic critically ill patients, with or at risk for multiple organ dysfunction, and potential associations between stress neuropeptide levels and immunity, disease severity and survival. Specifically, we investigated: (a) serum levels of stress neuropeptides (ACTH, neuropeptide Y (NPY), substance P (SP), cortisol and prolactin) in critically ill individuals compared to healthy matched controls, (b) bi-variate associations among stress neuropeptide levels, (c) potential associations with lymphocyte populations (total lymphocytes, B- and T-cell and natural killer cell lymphocyte populations), and (d) potential associations with disease severity and survival and perceived intensity of stress.

2. Materials and methods 2.1. Research design An exploratory correlational design with repeated measures and cross-sectional comparisons was employed. The study received institutional review approval by the University of Athens, Department of Nursing and the scientific board of the hospital where it was carried out. The study was performed at a large Metropolitan hospital in Athens, Greece. Patient recruitment took place during a period of one year. Before commencement of study procedures, all patients (or their legal representatives) and control subjects signed an informed written consent. In order to establish reliability of laboratory analyses and an appropriate sampling frame for serum neuropeptide measurements, a pilot investigation

M.D.A. Mpouzika et al. / Neuropeptides 47 (2013) 25–36

with 20 healthy volunteers and 5 critically ill patients preceded data collection. 2.2. Study groups A convenience sample of thirty-six consecutive adult critically ill patients with diverse admission diagnoses was studied. In order to include individuals who were severely ill, patients with or at risk for multiple organ dysfunction were targeted. The principal admission criterion was a multiple organ failure score (MOF) P5 at the MOF severity scoring system (Goris et al., 1985) and patients’ or legal representatives’ written informed consent. Although ICUESS stress scores were assessed, they were not included in admission criteria, since only a small percentage of ICU patients were expected to be able to respond to the scale, due to communication limitations related to presence of endotracheal tube, compromised neurological status and frailty. The decision to recruit patients despite their inability to communicate was made in order for the sample to be representative of the typical ICU patients’ population (Happ et al., 2011). Critically ill patients with sepsis, shock (regardless of etiology), patients with delirium and patients who received corticosteroids were excluded. Although patients with trauma were included, since such patients comprise a significant proportion of the typical critically ill patients’ population, we excluded patients if they exhibited physical signs of shock. Blood samples were drawn every 48 h at 9 a.m. approximately through an arterial catheter for a maximum period of 15 days since admission to the protocol. Thirty-six healthy volunteers, matched for gender, race and approximately for age (±5 years) with study subjects were studied. Exclusion criteria for the control group included high levels of reported psychological stress (Hamilton stress scale score P45) (Marshall et al., 1995) presence of organ dysfunction, hypotension, inflammation or infection and administration of corticosteroids. The decision to employ the Hamilton stress scale in control subjects was based on the lack of universal stress scales that can be used in both healthy and critically ill groups (Papathanassoglou et al., 2010). To establish an appropriate sampling frame for control subjects a pilot investigation of consecutive serum neuropeptide measurements was performed for two consecutive days during morning hours in 20 healthy volunteers. Based on the finding of no statistically significant differences (paired T test) in neuropeptide levels (SP: t = 1.12, p = 0.266; NPY: t = 0.932, p = 0.227), the decision was made to collect only one sample from matched controls. Moreover, through a focused literature search we were unable to locate evidence of daily variations in the neuropeptides studied in healthy populations. One single blood sample was acquired from control subjects at 9 a.m. approximately. 2.3. Neuropeptide levels and lymphocyte quantification Peripheral blood samples were centrifuged at 3000 rpm for 20 min and the serum stored at 20 °C. Immunophenotyping of the peripheral blood mononuclear cells was performed by using the fluorochrome monoclonal antibodies FITC (Fluorescein-isothiocyanate) and PE (Phycoerythrin) (Becton Dickinson, San Rose, CA, USA) for the detection of surface antigens (CD3, CD19, CD16/56, CD4, CD95, CD8, CD45, CD14). Fifteen thousand cells were analyzed per sample at a FACScalibur flow cytometer (Becton Dickinson, San Rose, CA, USA). Lymphocyte subpopulations were identified by forward and side scatter parameters. Percentages of positive cells of gated population were expressed as population counts per sample. Cortisol (ng/ml), ACTH (pg/ml) and prolactin (ng/ml) levels were quantified by an Electrochemiluminescence Immunoassay

27

(ECLIA) with the Elecsys 2010–Roche analyzer (Roche, Bohemia, NY, USA). NPY and SP levels were quantified by commercially available enzyme-linked immunosorbent assay (ELISA) kits (Phoenix Pharmaceuticals Inc., Burlinngame, USA and Assay Designs Inc, Ann Arbor, USA, respectively). All assays were run in duplicate. Intra-assay coefficients of variation were less than 5%. 2.4. Assessment of disease severity and stress In critically ill subjects, the MOF (Multiple Organ Failure System) (Goris et al., 1985), MODS (Multiple Organ Dysfunction Score) (Marshall et al., 1995), APACHE II (Knaus et al., 1985) and GCS (Glasgow Coma Scale) were employed to assess disease severity. In critically ill patients, the intensive care unit environmental stress (ICUESS) scale (Carr and Powers, 1986) was employed for stress assessment. The ICUESS scale has been previously validated in critically patients (Ballard, 1981; Novaes et al., 1999) and was validated for use in Greek through a translation and back-translation process, establishment of content validity through a group of experts and a pilot study with a group (n = 20) of critically ill patients. In control subjects, psychological stress levels were evaluated by the Hamilton scale (Hamilton, 1960). 2.5. Statistical analysis Levels of, and association between, serum stress neuropeptides and lymphocyte populations were examined at the following time points: (1) the first day in the study, (2) the day of maximum severity, (3) the day of minimum severity and (4) the last day in the study (i.e. either the 14th day of the study, or the last day of survival in the ICU). MODS scores were used to determine the days of maximum and minimum severity. Variable values were expressed as mean ± standard deviation and average values in patients were compared with the values in controls by independent samples t test. Pearson’s correlation coefficients (r) were reported for bivariate associations. Range of r values are reported in cases where associations were explored serially at consecutive days. In cases of significant departure from normality criteria, logarithmic transformation of variables was performed. A nominal significance level a = 0.05, was used, and Bonferroni adjustment was used in cases of multiple bivariate comparisons. To explore the effect of disease severity on the associations studied, subgroups of patients based on MOF severity score (7 6 MOF < 7) were contrasted. Potential differences in the study variables between the high- and low-severity groups were explored by t-test. Moreover, since the presence of trauma injuries could be a confounder as trauma is a factor in stress and neuroendocrine responses, variable values in patients with trauma were compared to those with no trauma by t-test. To explore a potential effect of gender, male patients were compared to female patients with regard to immunocyte counts, neuropeptide levels and severity. To test potential effects of medications differences in lymphocyte counts and neuropeptide levels were investigated with regard to the administration of opioids, non-opioid analgesia, sedation, neuromascular blocking agents, inotropes and vasodilators. Moreover, due to lack of previous data, bi-variate associations among stress neuropeptides and between stress neuropeptides and lymphocyte populations were tested in the control group in order to provide a reference for the interpretation of results in study subjects. Taking into account the known vasoactive effects of several of the neuropeptides examined, associations with systolic and mean arterial pressures were explored, as well as with the use of vasoactive medication. The aforementioned strategy of analysis is in line with previous studies exploring neuropeptide/hormone levels in critical illness (Beer et al., 2002; Marx et al., 2003). Moreover, due to the repeated

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measures design of the study (Papathanassoglou et al., 2001), the association of each serum stress neuropeptide with lymphocyte populations was explored, before and after adjusting for the effect of all others, in multiple patient-level random-effects regression models to allow for within-patient clustering in the data. As a result of the use of log-transformation in the dependent as well independent variables, the estimated effect was expressed as the ratio in levels of lymphocyte populations per 1 SD increase in log-transformed levels of serum stress neuropeptides. The intra-class correlation coefficient ICC (defined as the ratio of the between-patient to total variance) was used to quantify the amount of clustering. Evidence of monotonic trend across repeated measurements was investigated by including a time parameter in the models, which was retained if the coefficient was statistically significant at the 10% level. Alternatively, models were repeated to include an autoregressive structure in the residuals. In all cases, Hausman specification tests were performed to compare the coefficients of interest as estimated in random-effect models to the equivalent fixed-effect model. Models were repeated with the inclusion of gender and age to explore potential effects on the observed associations. In a similar manner, the extent to which severity (as indexed by MOF, MODS or APACHE II scores) was related to serum levels of stress neuropeptides was also explored in random-effects models, while Cox proportional hazard models with time-varying covariates were used to investigate the association of neuropetides with survival before and after controlling for the effect of severity. These models were also adjusted for gender and age. Statistical analyses were performed in the Statistical Package for Social Sciences (SPSS version 18) and Stata/SE 11.0.

Table 1 Demographic characteristics, 14-day survival and primary admission diagnoses of study subjects.

3. Results 3.1. Study and control subjects Study subjects had a variety of primary admission diagnoses (Table 1). Average severity scores appear in Table 2. Seventy-five percent were male and all were Caucasian. The average age of patients was 51.55 ± 18.85 years (range 21–86 years). Fifty-five percent of patients were receiving sedatives (either midazolam or propofol), and 66.4% received opioid analgesia (either fentanyl or remifentanyl). Neuromuscular blocking agents were administered to 17% of patients, whereas 67.3% of patients received low dose inotropic agents and 7.7% received low-dose vasodilatating agents. Nineteen percent of patients died within the 14 day follow-up. Control subjects were healthy volunteers who were matched for gender, race and approximately for age (±5 years), with the study group. Their average age was 52.36 ± 17.63 years, not statistically significantly different than the patient group. To explore a potential confounding effect of gender, male patients were compared to female patients. No statistically significant differences were noted with regard to background variables, neuropeptide levels, lymphocyte counts, disease severity and stress scores except for a non-statistically significant trend for decreased B cell counts in women (data not shown as they are not pertinent to the primary aims of the study). When patients with trauma and no trauma were compared, no statistically significant differences were noted with regard to background variables, lymphocyte counts and stress scores (data not shown as they are not pertinent to the primary aims of the study). Trauma patients exhibited statistically significantly lower APACHE II severity scores throughout the study (19.26 ± 5.4 vs. 24.77 ± 6.01, p = 0.09). Neuropeptide levels did not differ statistically significantly between the trauma and no trauma groups, with the exception of prolactin levels which were higher in trauma patients on the first day of the study (17.82 ± 15.62, vs. 6.66 ± 6.60 ng/ml,

a

Age

Gender

Survivala

Diagnosis

37 54 31 64 64 62 48 47 63 80 22 77 40 56 38 60 38 25 78 79 34 73 87 83 27 47 48 33 23 73

F F M M M M F M M M M F M M M F M M M F M M M M M F M M M M

S S S D S S D S S D S D S S S S S S S S S D S S S S S S S S

73 34 49 51 72 55

M F M M M F

S D S S D S

Tibia fracture, Liver laceration Craniocerebral injury, Cerebral hematoma Craniocerebral injury, Cervical fracture Respiratory infection, COPD, Heart failure Subdural hemorrhage Cirrhosis Arterial embolism (lower extremities) Pulmonary embolism, Meningioma Subdural hemorrhage Cerebral artery aneurysm Multiple trauma Acute respiratory distress, Renal failure Craniocerebral injury Cerebral mass Multiple trauma Postoperative respiratory distress Multiple trauma Craniocerebral injury Pancreatic cancer, Pancreatitis Myasthenia Multiple trauma Craniocerebral injury Aortic aneurysm surgical reconstruction Renal failure, Diabetes mellitus, Hepatitis C Epidural hematoma Cerebral hematoma Multiple trauma Multiple trauma Craniocerebral injury, Epidural hematoma Acute myocardial infraction, Respiratory infection Aortic valve replacement Cerebral hematoma Cerebral hematoma Cerebral abscess Craniocerebral injury Craniocerebral injury, Aspiration

S, Survival; D, Death in the 14-day study follow-up period.

p = 0.009) and on the day of maximum disease severity (16.27 ± 14.67 vs. 7.32 ± 6.22 ng/ml, p = 0.005). No statistically significant differences in neuropeptide levels and lymphocyte cell counts were noted with regard to the administration of opioids, non-opioid analgesia, sedation, neuromascular blocking agents inotropes and vasodilators, with the exception of increased B and NK cell numbers on the first day of the study in patients who received opioid analgesia (B cells: 67.37 ± 55.26 vs. 168.4 ± 151.36, p = 0.025, NK cells: 101.00 ± 57 vs. 207 ± 203, p = 0.038). Subgroups of patients based on MOF severity score (7 6 MOF < 7) were compared by t-test. No significant differences were noted between the high- and low- severity groups with regards to neuropeptide levels and cell numbers. Ratings on the behavioral pain scale were significantly lower in the high-severity group (T = 2.228, p = 0.031), presumably due to more sufficient sedation and analgesia in this group. 3.2. Differences with regard to serum stress neuropeptide levels in study and control subjects Beginning from the first throughout the last day of the study, serum cortisol levels were higher and serum SP and NPY levels were lower in patients compared to controls (cortisol: DM = 140– 173 ng/ml, p < 0.0001, NPY: DM = 0.77–0.83 ng/ml, p < 0.0001, SP: DM = 2928–3286 ng/ml, p < 0.001, Table 3). ACTH/ cortisol ratios were lower in critically ill individuals compared to controls,

29

M.D.A. Mpouzika et al. / Neuropeptides 47 (2013) 25–36 Table 2 Clinical data (Mean ± SD) of study subjectsa.

a

Variable

1st day

Day of maximum severity

Day of minimum severity

Last day

MOF MODS APACHE II GCS

5.40 ± 0.89 4.40 ± 2.30 14.80 ± 5.71 5.22 ± 3.81

5.73 ± 1.12 6.33 ± 2.86 20.3 ± 7.26 5.26 ± 3.75

4.74 ± 1.75 5.48 ± 2.54 19.67 ± 5.99 5.42 ± 4.1

4.58 ± 1.97 5.88 ± 5.5 19.13 ± 7.43 6.91 ± 4.95

APACHE II, Acute Physiology and Chronic Health Evaluation II; GCS, Glasgow Coma Scale; MOF, MultiOrgan Failure Score; MODS, Multiple-Organ Dysfunction Score.

Table 3 Serum levels of stress neuropeptides (Mean ± SD) in study subjects compared to controls (T-test, n = 36).

* **

Variable (net cell count)

1st Day

Day of maximum severity

Day of least severity

Last day

Controls

ACTH (pg/ml) CORTISOL (ng/ml) PRL (ng/ml) NPY (ng/ml) SP (ng/ml)

14.71 ± 18.63 393.46 ± 444.79** 13.33 ± 11.61 0.70 ± 0.31** 265.1 ± 210*

16.92 ± 22.26 484.48 ± 502.63** 13.81 ± 12.69 0.70 ± 0.19** 297.35 ± 220.58*

30.22 ± 40.73 362.34 ± 408.79** 13.13 ± 9.35 0.71 ± 0.21** 290.50 ± 228.83*

13.55 ± 15.93 346.78 ± 367.1** 10.42 ± 5.16 0.54 ± 0.21** 435.81 ± 281.2

37.33 ± 35.07 131.1 ± 70.59 18.11 ± 10.32 1.51 ± 0.6 3551 ± 1404.69

p < 0.05. p < 0.002 (Bonferroni adjustment).

Table 4 Lymphocyte populations (Mean ± SD)a in study subjects compared to controls (T-test, n = 36).

Total lymphocytes T lymphocytes B lymphocytes Natural killer cells T helper lymphocytes T cytotoxic lymphocytes a * **

1st Day

Day of maximum severity

Day of least severity

Last day

Controls

2164.85 ± 3280.05** 1132.75 ± 1135.63** 118.97 ± 145.90** 912.49 ± 2040.12 599.74 ± 406.24** 524.60 ± 747.96**

2605.60 ± 3882.66** 1287.88 ± 1321.83** 108.53 ± 158.58* 1209.15 ± 2418.38 649.60 ± 454.43** 635.68 ± 878.39*

2179.87 ± 3026.32** 1218.18 ± 1066.31** 170.62 ± 175.35** 790.95 ± 1917.28 670.71 ± 423.95** 526.49 ± 697.60**

2158.00 ± 3005.79** 1205.69 ± 1017.86** 135.68 ± 128.22** 816.64 ± 1907.46 671.24 ± 354.99** 530.44 ± 681.60**

2488.86 ± 1036.48 1848.92 ± 749.54 322.42 ± 226.66 310.69 ± 204.36 1090 ± 401.95 714.17 ± 379.95

Population counts per 15  103 cells analyzed at the flow cytometer, p < 0.05. p < 0.002 (Bonferroni adjustment).

(ACTH/ cortisol: DM = 0.12–0.14, p < 0.05). Although, ACTH levels exhibited a trend for lower values in study subjects, the differences were not statistically significant. No significant differences between study and control subjects were observed with regard to serum prolactin levels (Table 3). No statistically significant differences in serum neuropeptide levels were noted with regard to the administration of vasoactive drugs and inotropes (p > 0.3). Moreover, we did not observe any significant associations between neuropeptide levels and systolic as well as mean arterial blood pressure measurements either within or across patients (p > 0.18).

3.3. Differences in lymphocyte populations in study and controls subjects Total lymphocyte populations, B and T lymphocyte sub-population counts, as well as helper and cytotoxic T lymphocyte populations were statistically significantly lower in patients compared to control subjects throughout the study (p < 0.002, Table 4). Indicatively, for first day measurements, mean differences in lymphocyte counts in patients compared to controls were: Total lymphocyte counts (DM = 1193.42, p 6 0.001), B cells (DM = 198.14, p 6 0.001) T cells (DM = 980,137, p 6 0.001) helper T cells (DM = 586.86, p 6 0.001) and cytotoxic T cells (DM = 368.99, p 6 0.001). Overall, these differences were exacerbated as patients’ disease severity exacerbated. Natural killer (NK) cell populations exhibited great variability in critically ill patients and although mean populations were consistently at least approximately triple the average population in controls these differences were not

statistically significant (p > 0.05, Table 4). No differences were observed with regard to T helper/T cytotoxic lymphocyte ratios.

3.4. Bi-variate associations between stress neuropeptide levels and lymphocyte populations Of the neuropeptides studied, NPY levels exhibited the stronger and more consistent associations with total lymphocyte and sub-population counts (Table 5). Specifically, NPY levels exhibited positive medium to large associations with total lymphocyte populations (r: 0.411–0.664 (range of values), p < 0.04), T-lymphocyte (r: 0.403–0.781, p < 0.05), as well as with T-helper cell populations (r: 0.492–0.690, p < 0.03) and T-cytotoxic cell populations (r: 0.397–0.740, p < 0.03). During the first day of the study, cortisol levels exhibited negative associations with total lymphocyte (r = 0.452, p = 0.01), T cell (r = 0.446, p = 0.02), T helper (r = 0.428, p = 0.026) and T cytotoxic cell populations (r = 0.426, p = 0.027) (Table 5). However, no similar associations were observed at different times (i.e. the day of minimum and maximum severity, or the last day of the study). There was evidence of strong positive associations with NK cell populations during the last day of the study (r = 0.634, p = 0.015) and during the day of minimum severity (r = 0.351, p = 0.04). ACTH levels exhibited noteworthy positive associations with NK cell (r = 0.326–0.441, p < 0.05) during the first two days of the study (Table 5), which remained significant during the day of minimum severity (r = 0.4–0.460, p = 0.01) and the last day of the study (r = 0.663–0.707, p < 0.02), but not at the day of maximum severity.

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Table 5 Bi-variate associations between serum stress neuropeptide levels and lymphocyte populations (Pearson’s r correlation coefficients, n = 36). Total lymphocytes ACTH CORTISOL PRL NPY SP ⁄, ⁄⁄

0.073 0.452⁄ 0.240 0.664⁄ 0.187

T lymphocytes

B lymphocytes

0.083 0.446⁄ 0.248 0.781⁄⁄ 0.104

0.359 0.316 0.208 0.075 0.156

Natural killer cells

⁄

⁄

Natural killer sub-population ⁄

0.441 0.059 0.09 0.389⁄ 0.068

0.427 0.024 0.016 0.0659⁄ 0.283

T helper

T cytotoxic

0.380 0.428⁄ 0.222 0.680⁄⁄ 0.382⁄

0.071 0.326⁄ 0.220 0.736⁄⁄ 0.190

P-value <0.05 and <0.002 (Bonferroni adjustment) respectively for Pearson’s r correlation coefficients for the 1st day measurements.

With regard to prolactin levels no significant associations with immune cell populations were noted at the beginning of the study and at the day of maximum severity. Some noteworthy negative associations with lymphocyte (r = 0.614, p = 0.026), T-helper (r = 0.613, p = 0.023) and T-cell counts (r = 0.614, p = 0.026) were noted at the last day of the study. As for SP levels, an association with T-helper cell populations (r = 0.382, p = 0.04) was noted at the beginning of the study. At

the day of minimum severity, associations were noted with T-cell (r = 0.403, p = 0.03) and T-helper cell populations (r = 0.492, p = 0.009). When patients were categorized according to disease severity (7 6 MOF < 7) some of the aforementioned associations were replicated in both severity groups, despite significantly lower power to detect statistically significant associations. Specifically, in the high severity group (n = 12), NPY levels showed a trend for association

Table 6 Ratio of lymphocyte populations (log-scale) per 1 SD increase in log-transformed stress neuropeptide levels. Univariable modela Coefficient

95% CI

p-value

ICC

Total lymphocytes ACTH Cortisol PRL NPYb SPb

1.24 1.06 0.98 1.08 1.13

(1.09, (0.93, (0.82, (0.97, (0.98,

1.42) 1.19) 1.16) 1.21) 1.31)

0.60 <0.01 0.39 0.77 0.14 0.09

T lymphocytes ACTH Cortisol PRL NPYb SPb

1.18 1.04 0.94 1.15 1.12

(1.03, (0.91, (0.80, (1.02, (0.96,

1.36) 1.17) 1.11) 1.30) 1.31)

B lymphocytes ACTH Cortisol PRL NPY SP

1.10 1.03 0.99 1.09 1.08

(0.87, (0.84, (0.72, (0.72, (0.75,

Natural killer cells ACTH Cortisol PRL NPY SP

1.45 1.16 0.97 0.96 1.20

Natural killers sub-population ACTHb Cortisolb PRLb NPYb SPb T helper ACTH Cortisol PRL NPYb SP T cytotoxic ACTH Cortisol PRL NPY SPb a b c

Multivariable modela c

Coefficient

95% CI

p-value

0.73 0.68 0.68 0.94 0.73

1.11 0.92 1.08 1.13 1.20

(0.99, (0.82, (0.91, (1.02, (1.07,

1.25) 1.03) 1.28) 1.26) 1.34)

0.07 0.17 0.39 0.02 <0.01

0.02 0.58 0.46 0.02 0.16

0.53 0.64 0.59 0.57 0.91 0.70

1.09 0.97 1.06 1.23 1.17

(0.95, (0.85, (0.89, (1.07, (1.02,

1.26) 1.10) 1.26) 1.41) 1.35)

0.24 0.62 0.54 <0.01 0.03

1.40) 1.27) 1.37) 1.62) 1.57)

0.41 0.76 0.69 0.69 0.67

0.70 0.81 0.81 0.81 0.76 0.70

0.87 0.95 1.10 1.09 1.19

(0.56, (0.64, (0.67, (0.69, (0.76,

1.35) 1.41) 1.79) 1.70) 1.87)

0.53 0.80 0.70 0.72 0.44

(1.19, (0.96, (0.74, (0.75, (0.97,

1.77) 1.40) 1.28) 1.22) 1.50)

0.71 <0.001 0.13 0.84 0.74 0.10

0.72 0.70 0.72 0.85 0.76

1.36 1.05 0.84 1.02 1.10

(1.08, (0.85, (0.64, (0.81, (0.87,

1.71) 1.30) 1.10) 1.29) 1.39)

0.01 0.66 0.21 0.85 0.44

1.46 1.38 1.07 0.92 1.29

0.83 (1.07, (1.07, (0.71, (0.65, (0.93,

2.00) 1.78) 1.59) 1.29) 1.79)

0.02 0.01 0.76 0.62 0.13

0.72 0.72 0.72 0.87 0.82

1.45 1.50 0.55 0.97 1.06

(1.01, (1.11, (0.34, (0.74, (0.76,

2.06) 2.03) 0.86) 1.29) 1.47)

0.04 <0.01 0.01 0.85 0.73

1.12 1.01 0.96 1.25 1.17

0.40 (0.94, (0.86, (0.80, (1.06, (0.97,

1.32) 1.17) 1.15) 1.47) 1.41)

0.20 0.97 0.66 0.01 0.11

0.40 0.36 0.36 0.83 0.57

1.11 0.99 1.13 1.30 1.16

(0.93, (0.84, (0.93, (1.08, (0.96,

1.32) 1.16) 1.37) 1.56) 1.39)

0.27 0.88 0.23 <0.01 0.12

1.15 1.09 0.90 1.23 1.12

0.64 (0.98, (0.94, (0.73, (0.99, (0.96,

1.37) 1.26) 1.11) 1.52) 1.31)

0.09 0.27 0.34 0.07 0.13

0.69 0.67 0.65 0.80 0.83

1.03 1.02 1.06 1.14 1.11

(0.90, (0.89, (0.87, (1.00, (0.96,

1.19) 1.16) 1.30) 1.30) 1.27)

0.66 0.82 0.57 0.05 0.16

ICCc 0.92

0.84

0.76

0.80

0.90

0.75

0.91

Before and after mutual adjustment for the effect of all other variables in random-effects models. Models also inclue a time parameter. Intraclass correlation coefficient showing the ratio of between-cluster to total variance.

31

M.D.A. Mpouzika et al. / Neuropeptides 47 (2013) 25–36 Table 7 Bi-variate associations among serum stress neuropeptide levels ((Pearson’s r correlation coefficients, n = 36). CORTISOL 1st Day

Last day

PRL Max severity

ACTH 0.225 0.426 0.026 CORTISOL PRL NPY ⁄, ⁄⁄

NPY

Min severity

1st Day

Last day

Max severity

0.242

0.036 0.07 0.240 0.155 0.232 0.213

SP

Min severity

1st Day

Last day

Max severity

Min severity

0.101 0.058

0.195 0.221 0.089 0.262 0.356⁄ 0.199 0.470⁄⁄ 0.146 0.249 0.576 0.220 0.154

1st Day

Last day

Max severity

0.222 0.065 0.047 0.222 0.11 0.135 ⁄ 0.388 0.075 0.386⁄ 0.219 0.289 0.236

Min severity 0.141 0.314 0.091 0.124

p-value <0.05 and <0.002 respectively for Pearson’ r correlation coefficients between levels on the 1st and last day, as well as for the days of maximum and least severity).

with with T-helper cell numbers (r = 0.846, p = 0.052) and a significant inverse association with NK cell numbers (r = 0.893, p = 0.007). In the low severity group (n = 24), NPY levels associated with T cell (r = 0.573, p = 0.008), and T-helper cell numbers (r = 0.531, p = 0.016). 3.5. Multivariable models of the association of stress neuropeptide levels with lymphocyte populations The above associations were largely replicated when multivariable patient-level random effects models were used to explore the association between serum stress neuropeptide levels and lymphocyte populations, taking into account the repeated measurements and adjusting for the effects of all others (Table 6). Specifically, the association of NPY levels with lymphocyte T cell and T helper populations and SP levels with total lymphocyte and T cell populations appeared significant even in the multivariable models. ACTH, cortisol and PRL levels displayed stronger associations with NK populations. When models were repeated with the inclusion of gender and age, the observed associations remained essentially unchanged. 3.6. Bi-variate associations between stress neuropeptides in study subjects Regarding first day measurements, an inverse association between cortisol and NPY levels was observed (r = 0.356, p = 0.036), along with a positive association between SP and prolactin levels (r = 0.388, p = 0.034). These associations were replicated at the day of maximum severity (cortisol-NPY, r = 0.470, p = 0.01, PRL-SP: r = 0.386, p = 0.039, but not during the day of minimum severity and at the last day of the study, despite a trend for an inverse association between prolactin and NPY levels (r = 0.576, p = 0.08). The association between prolactin and SP

levels (r = 0.441, p = 0.031) and between cortisol and NPY levels (r = 0.470, p = 0.024) were replicated when patients were categorized according to disease severity (7 6 MOF 6 7), despite significantly lower power to detect statistically significant associations. Remarkably, no significant associations between ACTH and cortisol levels were noted throughout the study (Table 7). 3.7. Bi-variate associations among stress neuropeptide levels in control subjects In control subjects, ACTH levels exhibited positive statistically significant associations with cortisol (r = 0.471, p = 0.004) and prolactin levels (r = 0.465, p = 0.003) – results not shown in detail. Apart from ACTH, cortisol levels correlated with prolactin (r = 0.483, p = 0.003) and NPY levels (r = 0.520, p = 0.04). No significant associations were noted with regard to substance P levels.

Table 8 Ratio of serum stress neuropeptide levels per 1 unit increase in severity scales. 95% CI

p-value

ICCa

Per 1 unit in MODS ACTH 1.10 Cortisol 1.04 PRL 0.99 NPY 0.99 SP 0.97

(1.01, (0.96, (0.92, (0.94, (0.89,

1.19) 1.12) 1.06) 1.05) 1.06)

0.03 0.37 0.70 0.70 0.48

0.64 0.60 0.85 0.51 0.61

Per 1 unit in APACHE ACTH 1.02 Cortisol 1.01 PRL 0.99 NPY 1.00 SP 1.00

(0.98, (0.97, (0.96, (0.97, (0.97,

1.06) 1.04) 1.02) 1.02) 1.04)

0.25 0.68 0.64 0.78 0.88

0.64 0.61 0.86 0.53 0.62

Coefficient

a Intra-class correlation coefficient showing the ratio of between-cluster to total variance.

Table 9 Hazard Ratios of death per 1 SD increase in log-transformed serum stress neuropeptide levelsa. Hazard Ratio

a

95% CI

p-value

Male Aged >45

0.49 3.50

(0.10, 2,27) (0.34, 35.98)

0.36 0.29

MODS APACHE

1.27 1.18

(1.05, 1.53) (1.04, 1.32)

0.015 0.006

ACTH Cortisol PRL NPY SP Gender only Age only

1.29 2.88 1.01 1.01 9.27 5.42 9.81

(0.45, 3.71) (0.76, 10.90) (0.66,1.55) (0.57, 1.78) (1.05, 82.20) (1.13, 26.10) (1.07, 90.03)

0.63 0.12 0.95 0.98 0.045 0.035 0.044

After adjustment for severity MODS

APACHE

0.99 (0.27, 3.68) 2.48 (0.69, 8.91) 1.25 (0.76, 2.04) 1.07 (0.56, 2.07) 19.43 (1.72, 218.93) 7.59 (2.42, 23.80) 16.95 (0.96, 298.94)

1.05 (0.30, 3.70) 2.16 (0.76, 6.14) 1.03 (0.65, 1.61) 1.33 (0.65, 2.68) 10.91 (0.75, 157.47) 9.45 (0.95, 93.80) 13.33 (0.76, 234.82)

Estimated in Cox proportional hazard regression models with robust standard errors before and after adjusting for severity as indexed by different severity scales.

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M.D.A. Mpouzika et al. / Neuropeptides 47 (2013) 25–36

3.8. Associations between stress neuropeptide levels and lymphocyte populations in control subjects NPY levels associated positively with total lymphocyte (r = 0.669, p = 0.009), T cell (r = 0.693, p = 0.006), T-helper (r = 0.628, p = 0.016) and T-cytotoxic (r = 0.723, p = 0.003) populations. No significant associations were noted between SP levels and immune cell populations – results not shown in detail. 3.9. Associations between stress neuropeptide levels and intensive care unit environmental stress ratings Only a fraction of study patients (n = 15) were able to respond to the ICUESS scale at the day of minimum disease severity, by either verbal or non-verbal communication. A non-significant trend for a positive association between ACTH levels and ICUESS ratings was noted (r = 0.340, p = 0.057). 3.10. Associations with survival and severity of multiple organ dysfunction Of the neuropeptides studied, only ACTH levels exhibited a consistent positive association with the severity of multiple organ dysfunction throughout the study (r = 0.340–0.387). This association was also confirmed in patient-level random effects regression models (Table 8). Moreover, in the patient-level random effects regression model, a statistical significant interaction between gender and MODS severity score was noted with regard to PRL levels. Specifically, multiple organ dysfunction severity was associated with decreased PRL levels in female (ratio of 0.82 per 1 unit increase in MODS, 95% CI = 0.71–0.95) but not in male patients (ratio of 1.03 per 1 unit increase in MODS, 95% CI = 0.96–1.11; p-value for interaction <0.01). Despite a trend for higher ACTH, cortisol and SP levels in patients who did not survive these were not statistically significantly associated with survival in Cox proportional hazard regression models (Table 9). However, further adjusting for gender and age, strengthened the HR estimates for the associations between SP and mortality (HR: 9.27 (1.05–82.2), p = 0.045; Table 9). 4. Discussion The main findings of this study included: (a) significantly lower SP and NPY levels and significantly higher cortisol levels in critically ill subjects compared to healthy matched controls, (b) significant differences in lymphocyte populations in critically ill subjects compared to healthy matched controls, (c) significant associations between stress neuropeptide levels and lymphocyte populations, especially with regard to NPY levels, in critically ill subjects. Moreover, despite our initial hypothesis of an association between stress neuropeptide levels and reported ICU stress, we observed only a non-significant trend for a moderate positive association between stress ratings and ACTH levels, at those patients who were able to respond to the questionnaire at the day of minimum disease severity. These results need to be interpreted with caution due to the limitations of this study which stem from the small sample size, the correlational design, the pleiotropic nature of the neuropeptides studied, and the absence of robust psychological stress assessment tools for use in critical care settings, as well as the lack of universal stress assessment tools that can be used in both critically ill and healthy populations. Moreover, the well-known complexity and heterogeneity of critically ill patients’ populations give rise to various confounding variables, which are difficult to be accounted for in clinical setting research (Deutschman et al., 2012). These include patient history, autonomic activation status and medication variations. Although, in the present study, no

significant effects of medications, trauma and disease severity on either neuropeptide levels or their associations were detected, testing of such associations with larger samples is needed in the future. Moreover, the large variations in neuropeptide levels observed in this study are in line with variations observed in hormone levels in critically ill populations (Langouche and Van den Berghe, 2006; Sharshar et al., 2011), and it may be associated with heterogeneity in background factors (Deutschman et al., 2012). Patients’ heterogeneity is inherent in critical care studies and it may be a factor in the wide variability in neuroendocrine responses observed in these patients (Sharshar et al., 2011). Although in the present study we chose not to measure immunoregulatory cytokines due to their well-studied wide variation in critical illness and their inconsistent associations with patient outcomes (Matuschak 1996), in the future, concomitant quantification of a wide array of cytokines along with neuropeptides and functional T cell response testing and/ or inflammatory markers may provide further insight into immunoregulation in critical illness. Therefore these results must be viewed as indicative of the need for further research. If these results are viewed in association with recent evidence from experimental models, an intricate interplay between stress neuropeptides and some of the predominant pathophysiologic alterations of critical illness appears to be implied (Papathanassoglou et al., 2010). 4.1. NPY levels and association with lymphocyte populations NPY is widely distributed in the central, peripheral and enteric nervous systems, and it may be elicited by sympathetic nerve fibers, immune cells and platelets (Jonsdottir, 2000; Fleur, 1999). NPY may provide a link between the immune and autonomic systems, since sympathetic nerve fibers containing NPY innervate lymphoid organs (Bellinger et al., 2008; Kuncová et al., 2011). Although, by virtue of being a stress peptide, it would be reasonable to anticipate increased NPY levels in critical illness, decreased levels were observed in our sample of critically ill individuals. To the extent of our knowledge this is the first report of decreased serum NPY levels in critically ill individuals. Only one previous study reported NPY levels in critically ill humans with sepsis. In contrast to our findings, significantly increased NPY-like immunoreactivity in patients with sepsis and septic shock compared to healthy individuals was observed (Arnalich et al., 1995). This discrepancy with our findings may be attributed to the fact that no septic or patients with shock were included in the present study. Although NPY levels in normotensive patients without sepsis have received little interest, it appears that, in animal models, NPY is released into the circulation during development of shock (Wang et al., 1992) and that NPY levels may correlate with changes in the systemic vascular resistance (Kuncová et al., 2011). At an earlier study, no significant changes in plasma NPY levels were noted in patients with soft tissue injury (Onuoha and Alpar, 1999). Perivascular nerve NPY, being a potent vasoconstrictor (Pernow et al., 1987), may contribute to the compensatory mechanism attempting to normalize arterial pressure during immediate stages of endotoxemia (Kuncová et al., 2011; Wang et al., 1992). It has also been demonstrated that NPY infusion improves hemodynamics and survival in rat endotoxic shock (Felies et al., 2004; Hauser et al., 1993), and that NPY may reduce the febrile phase of endotoxic shock (Felies et al., 2004). Inflammation might also account for the suppressed NPY levels in our sample, since all patients had evidence of a systemic inflammatory response as is typical in critically ill patients’ populations (Marshall et al., 2008). Evidence in animal models suggests that NPY is down-regulated during inflammation, at least on peripheral blood mononuclear cells (Holler et al., 2008). In conclusion, in light of previous evidence, our results may suggest that NPY kinetics in critical illness may be very different depending

M.D.A. Mpouzika et al. / Neuropeptides 47 (2013) 25–36

on the presence or absence of sepsis and shock and the degree of inflammation. The finding of suppressed NPY levels in critically ill subjects is worth-exploring. At a recent review, it has been suggested that the potentially protective role of some stress-attenuating neuropeptides, such as NPY, against pathophysiologic phenomena in critical illness needs to be investigated (Papathanassoglou et al., 2010). Critical illness demonstrates an intricate neuroendocrine activation pattern with an increase and a subsequent marked suppression of hypothalamic peptide levels (Van den Berghe et al., 1998). Given the important role of NPY in the regulation of secretion of pituitary hormones (Fleur, 1999) any putative associations between NPY down-regulation and HPA suppression in critical illness are worth-exploring. However, no inferences regarding central nervous system NPY can be based on our findings, since peripheral and central regulation of NPY may be very distinct. An intricate interplay between central and peripheral neuropeptide levels, their respective receptor systems and cytokine networks may be in place in critical illness (Rosmaninho-Salgado et al., 2007). Another relevant aspect of NPY physiology is its role in preventing pathologic anxiety and fear (Papathanassoglou et al., 2010; Zukowska-Grojec et al., 1991). Although this is presumable, suppressed NPY levels may increase patients’ susceptibility to high levels of perceived psychological stress. The observed associations between NPY levels and immune cell populations, which were also replicated in control subjects, with the exception of the association with NK populations, may be interpreted on the basis of NPY’s involvement in immunity. NPY appears to profoundly affect immune processes, nonetheless, its actions on immunity may be dual, both pro- and anti-inflammatory, possibly depending on relative concentrations and cell types (Kuncová et al., 2011). With regard to the function of T cells, NPY appears to have a bimodal role: it is both essential for T cell activation and at the same time it down-regulates excessive T cell reactivity (Wheway et al., 2007). The finding of significant associations between NPY levels and T-helper cells which was replicated both at the day-to-day analysis and at the multivariate mixed effects analysis may be viewed in line with NPY’s role in CD4+ T lymphocyte mobilization (Bedoui et al., 2001), and in T helper cell responses (Wheway et al., 2005). Moreover, we report significant associations with cytotoxic T cell and NK cell numbers. Although NPY’s effects on CD8 activity has not received much attention, there is evidence on NPY’s effect on NK activity. Results are contradictory reporting both inhibitory and stimulating effects of NPY on NK cells (De la Fuente et al., 2001; Nair et al., 1993), presumably in part owing to different experimental models and concentrations examined (Bedoui et al., 2001). Based on these results, the role of NPY in the regulation of immunity in critical illness is worth exploring. 4.2. SP levels and associations with lymphocyte populations The finding of lower SP levels in critically ill subjects compared to healthy matched controls is remarkable given that SP would be expected to increase in stress states (Iversen, 1998). To the extent of our knowledge, no previous evidence exists on SP levels in critically ill patients without sepsis. Two previous studies that examined SP levels in patients with sepsis reported contradicting results. At a study with twenty-two patients with sepsis, lower SP levels were detected the day after the onset of sepsis (Arnalich et al., 1995); whereas, at a study with serial measurements in sixty-one patients with sepsis after visceral surgery, SP levels were reported to be higher than in control subjects (Beer et al., 2002). Although, the clinical significance of lowered SP in critically ill subjects is not clear, its role in immune responses merits investigation, since SP exerts a stimulatory effect on T and NK cells (Feistritzer

33

et al., 2003; Blum et al., 2003), and it stimulates the production of inflammatory cytokines (Costa et al., 2006). Although, at the present study, the association between SP levels and T cell and T-helper cell populations was significant only sporadically, the in vivo effect of SP on T and NK cells and pro-inflammatory cytokines in critical illness merits investigation. Signaling through the SP neurokinin-1 (NK-1) receptor appears to modulate pro-inflammatory mediators in experimental models of sepsis (Hegde et al., 2010). Remarkably, SP’s effect in sepsis appears to be bimodal since SP-deficient mice appear to be protected from polymicrobial sepsis (Puneet et al., 2006), while, conversely, blocking the NK-1 receptor may account for less efficient clearance of bacteria (Verdrengh and Tarkowski, 2008). Therefore, it is worth-exploring whether lowered SP levels may protect critically ill patients from an exaggerated systemic inflammatory response and/ or whether they may contribute to compromised immunity. Although, one previous study reported significantly higher SP levels at late stages of sepsis in non-surviving septic patients compared to survivors (Beer et al., 2002) we did not to observe any significant association between SP levels and either survival or disease severity. 4.3. ACTH, cortisol and prolactin levels and associations with lymphocyte populations, SP and NPY Previously reported observations on decreased lymphocyte and subpopulation counts (Ward et al., 2008), increased cortisol levels, non-significantly lowered ACTH (Arafah, 2006; Van den Berghe et al., 1998) and prolactin (Van den Berghe, 2002) levels, lowered ACTH/ cortisol ratios (Lesur et al., 2010) and dissociation between ACTH and cortisol levels (Bornstein and Chrousos, 1999) in critically ill subjects were replicated here. The intermittent associations between cortisol and NPY levels reported here, which were also replicated in healthy controls, are worth-noticing since this neuropeptide appears to participate in the alternative pathways, other than hypothalamic CRH, for cortisol secretion, which have been suggested to be important in critical illness (Arafah, 2006). Specifically, both NPY and SP appear to have either stimulatory or inhibitory effects on cortisol secretion, presumably depending on the activation status of the HPA axis (Coiro et al., 1992; Prasad et al., 2006; Morgan et al., 2001; Antonijevic et al., 2000). The significant associations between ACTH, cortisol and prolactin, which were observed in controls were not replicated at any point in critically ill subjects. This discrepancy is probably due to the profound neuroendocrine disruption evident in critical illness (Bornstein and Chrousos, 1999). The observed negative associations of cortisol with total lymphocyte and subpopulation counts and some positive associations with NK populations during the last day and the day of minimum severity are in line with recent results of stress hormone infusion in humans which resulted in inhibition of T cells and pronounced reduction of all lymphocyte subpopulations, except for NK cells, which were increased (Januszkiewicz et al., 2001). Cortisol’s role in critical illness and immunity is intricate. Recent evidence suggests that although physiological concentrations are associated with enhancement of immunity, the high concentrations observed during critical illness are associated with suppression of immunity (Charmandari et al., 2004). Therefore, based on these results previously reported associations between cortisol levels and lymphocyte apoptosis in critical illness (Papathanassoglou et al., 2003) merit further investigation. The association between ACTH levels and natural killer cell populations, which was also confirmed through the multiple regression model, merits further investigation. Although such associations have not been previously reported in critically ill subjects, this finding is in line with experimental evidence that ACTH increases NK activity (van Ierssel et al., 1996). Likewise some

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M.D.A. Mpouzika et al. / Neuropeptides 47 (2013) 25–36

sporadic negative associations between prolactin and total lymphocyte and T helper cell populations, although not replicated at the multiple regression model, merit further investigation since prolactin may mediate cellular immune dysfunction in critical illness (Oberbeck et al., 2003). 4.4. Associations with survival and clinical severity Despite the significantly suppressed NPY and SP levels in critically ill subjects, no significant association with severity or mortality was observed. This finding, however, should be considered with caution, due to the small sample size and the small variability in disease severity within the time frame of the study. The positive association between ACTH levels and multiple organ dysfunction severity reported here is in line with the concept that neuroendocrine activation and disruption in critical illness may precipitate multiple organ dysfunction. Although cortisol responses to ACTH testing have been employed as a means of outcome prediction in critical illness (de Jong et al., 2011), the association of ACTH levels with severity and survival is less clear in the literature. 5. Conclusions The observation of significantly lowered NPY and SP levels in critically ill individuals without sepsis and significant associations with hypothalamic-pituitary axis peptides and lymphocyte subpopulations suggests that the role of these peptides in the critically ill merits further investigation. Specifically, based on the positive associations between NPY and lymphocyte populations, the role of NPY in the regulation of immunity in critical illness needs to be explored. Moreover, based on the association of NPY with total lymphocyte and T cell subpopulation counts, the role of NPY in the intriguing interplay between exaggerated systemic inflammation and immunosuppression in critically ill individuals needs to investigated. Future studies need to address the association of pro- and anti-inflammatory cytokines with neuropeptides in critical illness, as well associations with functional immune cell responses and inflammatory markers. Authors’ contributions M.D.A.B. contributed to data collection, laboratory analysis, interpretation of data and manuscript preparation. E.D.E.P. contributed to the conception, design of the study, statistical analysis, interpretation of findings and manuscript preparation. M.G., E.B. and S.B. carried out laboratory analyses and contributed to the design and interpretation of results. N.M. contributed to statistical analysis. E.I.P. and A.K. contributed to the design of the study. All authors read and approved the final manuscript. Acknowledgment Supported by the Cyprus University of Technology Faculty Grant to E.D.E.P and by the University of Athens ELKE Grants 70/ 4/5688 & 70/4/6403 to E.D.E.P. and M.G. respectively. References Abdel-Samad, D., Jacques, D., Perreault, C., Provost, C., 2007. NPY regulates human endocardial endothelial cell function. Peptides 28, 281–287. Adameova, A., Abdellatif, Y., Dhalla, N.S., 2009. Role of the excessive amounts of circulating catecholamines and glucocorticoids in stress-induced heart disease. Can. J. Physiol. Pharmacol. 87, 493–514. Antonijevic, I.A., Murck, H., Bohlhalter, S., Frieboes, R.M., Holsboer, F., Steiger, A., 2000. Neuropeptide Y promotes sleep and inhibits ACTH and cortisol release in young men. Neuropharmacology 39, 1474–1481.

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