Progress in Neuro-Psychopharmacology & Biological Psychiatry 54 (2014) 275–283

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Progress in Neuro-Psychopharmacology & BiologicalPsychiatry

Telomere shortening and immune activity in war veterans withposttraumatic stress disorder

Mladen Jergović a,⁎, Marko Tomičević b, Anđelko Vidović c, Krešo Bendelja a, Ana Savić a, Valerija Vojvoda a,Dijana Rac b, Davorka Lovrić-Čavar b, Sabina Rabatić d, Tanja Jovanovic e, Ante Sabioncello d

a Centre for Research and Knowledge Transfer in Biotechnology, University of Zagreb, Zagreb, Croatiab Dr. Josip Benčević General Hospital, Slavonski Brod, Croatiac Dubrava University Hospital, Zagreb, Croatiad Institute of Immunology, Department for Cellular Immunology, Zagreb, Croatiae Emory University, Department of Psychiatry & Behavioral Sciences, Atlanta, GA, USA

Abbreviations: BDI, Beck Depression Inventory; BMI, BAdministered PTSD Scale; LPS, lipopolysaccharide; LTL, leuMini International Neuropsychiatric Interview; PBMCs, pcells; PHA, phytohemagglutinin; PMA, phorbol-12-mygrammed death 1; PTSD, posttraumatic stress disordInventory.⁎ Corresponding author at: Centre for research and kno

gy, University of Zagreb, Rockfellerova Ulica 10, Zagreb, CE-mail address: mjergovi@unizg.hr (M. Jergović).

http://dx.doi.org/10.1016/j.pnpbp.2014.06.0100278-5846/© 2014 Elsevier Inc. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history:

Received 4 May 2014Received in revised form 11 June 2014Accepted 23 June 2014Available online 28 June 2014

Keywords:ImmunityImmunosenescencePosttraumatic stress disorderTelomeres

Background: There is increasing evidence that chronic stress accelerates telomere erosion in leukocytes/peripheralblood mononuclear cells (PBMCs). However, functional changes associated with telomere shortening are poorlyunderstood. We hypothesized that war veterans with PTSD would have shorter telomeres in PBMCs and thatthese cells might exhibit changes in measures of immune reactivity such as proliferation, cytokine productionand expression of regulators of immune responses.Methods:Wemeasured relative telomere length and basal telomerase activity in PBMCs of 62 individuals (PTSDpatients (N = 30); age-matched healthy controls (N = 17), elderly volunteers (N = 15)). In parallel, we haveassessed proliferation of activated T cells, interferon (IFN)-γ, interleukin (IL)-2, IL-4, tumor necrosis factor(TNF)-α and IL-6 cytokine production and expression of programmed death 1 (PD-1) receptor and its ligandPD-L1 on activated T cells.

Results:Middle-aged war veterans with current PTSD had shorter PBMC telomere length than their age-matchedhealthy controls while the elderly had the shortest telomeres. There was no difference in telomerase activity be-tween PTSD patients and healthy controls while telomerase activity was significantly lower in the elderly. Whilethe elderly group exhibited robust changes in immune activity such as increased production of proinflammatorycytokines (TNF-α, IL-6) and reduced proliferation of all T cells, the PTSD group showed reduced proliferative re-sponse of CD8+ T cells to high concentrations of mitogen and reduced spontaneous production of IL-2 and IFN-γ.Conclusions: This study adds to the accumulating evidence that psychological trauma and chronic stress are asso-ciated with accelerated telomere attrition. However, changes in immune function associated with stress-relatedtelomere shortening are not well understood. Although much less pronounced in PTSD patients than in elderlypersons, reduced proliferative responses of T cells accompanied by shorter telomeres might be a sign of earlyimmunosenescence. Togetherwith reduced production of Th1 cytokines, observed immune changesmay contrib-ute to health risks associated with PTSD.

© 2014 Elsevier Inc. All rights reserved.

1. Introduction

Telomeres are repeating hexameric sequences of DNA that are foundat the ends of linear chromosomes in associationwith a complex of pro-teins; their role is to maintain chromosome integrity and stability

odyMass Index; CAPS, Cliniciankocyte telomere length;M.I.N.I.,eripheral blood mononouclearristate-13-acetate; PD-1, pro-er; STAI, State-Trait Anxiety

wledge transfer in biotechnolo-roatia. Tel.: +385 16414359.

(Blackburn, 2001). Telomeric DNA is lost due to the incomplete termi-nal synthesis of the lagging DNA strand during cell division (Newlon,1988). The rate of telomere loss is slowed by the enzyme telomerase,an RNA-dependent DNA polymerase that synthesizes telomeric repeatsand thus maintains telomeres during cell replication (Greider andBlackburn, 1985). Telomerase is expressed in cells of the germinalline, stem cells and some leukocytes but repressed in normal somaticcells (Gomez et al., 2012), thus telomeres progressively shorten withaging (Counter et al., 1992). In addition to replicative DNA loss, telo-mere shortening can also result from exposure to genotoxic stressorssuch as reactive oxygen species and UV radiation (Morgan, 2013).When telomeres reach a critically short length, they are recognized asdouble-stranded DNA breaks that activate the p53 tumor suppressorprotein resulting in cell senescence or apoptosis (Collado et al. 2007).

276 M. Jergović et al. / Progress in Neuro-Psychopharmacology & Biological Psychiatry 54 (2014) 275–283

Inverse correlation between telomere length in various human tissuesand age-related diseases is well described (von Zglinicki and Martin-Ruiz, 2005). Although telomerase is active in some (mostly activated)leukocytes, telomeres in leukocytes shorten with age and leukocytetelomere length (LTL) is considered a reliable marker of biological age(Müezzinler et al. 2013) that predicts the onset of age-related diseases(Epel et al., 2009; Fitzpatrick et al., 2007; Panossian et al., 2003) andmortality (Cawthon et al., 2003; Kimura et al., 2008).

The first evidence that psychological stress may impact telomeremaintenance came from a studywhich described shorter telomere lengthof peripheral blood mononuclear cells (PBMCs) in mothers of chronicallyill children (Epel et al., 2004). PBMCs include twomajor subpopulations ofleukocytes, namely lymphocytes and monocytes, but no granulocytes. Inrecent years, telomere shortening has been implicated in various psychi-atric conditions such asmooddisorders (Simonet al., 2006), posttraumat-ic stress disorder (PTSD) (O'Donovan et al., 2011), and in individuals thathave experienced childhood trauma (Shalev et al., 2013). Most of thesestudies measured telomere length in leukocytes/PBMCs of the partici-pants but lacked parallel assessment of functional reactivity of thesecells with shortened telomeres. To our knowledge only one study(Damjanovic et al., 2007) assessed functional consequences of telomereshortening of PBMCs in human subjects undergoing chronic stress andfound that telomere erosionwas associatedwith declining immune func-tion in caregivers of Alzheimer's disease patients.

With this in mind, the aim of the current study was to measure telo-mere length in PBMCs of Croatianwar veterans with PTSD and to assessimmune reactivity of these cells in the context of immunosenescence(Aw et al., 2007), i.e., age-dependent decline of immune function. Forthis purpose, the study included a comparison group of elderly persons(age N 80).

PTSD is a trauma-related disorder that may develop after exposureto one or more traumatic events (American Psychiatric Association,2013) and is associated with various biological and behavioral changesthat constitute a higher risk for developing somatic illness (Barrett et al.,2002; Boscarino, 2004) and higher mortality (Xue et al., 2012). Studiesof the immune system in PTSD have produced conflicting results al-though there is evidence for increased peripheral inflammation mani-fested by increased levels of pro-inflammatory cytokines (IL-1β, IL-6and tumor necrosis factor (TNF)-α) (Baker et al., 2012; Pace andHeim, 2011). Immune dysregulation in PTSD and other chronic stressmodels seems to resemble changes induced by biological aging(Alvarez-Rodríguez et al., 2012; Andrews and Neises, 2012).

The present studymeasured relative telomere length and basal telo-merase activity in PBMCs of patients with PTSD, age-matched healthycontrols and a group of elderly volunteers. In parallel, we assessed pro-liferation of activated T cells, and cytokine production by unstimulatedor stimulated monocytes and T cells. In addition, we measured expres-sion of programmed death 1 (PD-1) receptor and its ligand PD-L1, neg-ative regulators of immune responses (Keir et al., 2008), on activated Tcells. PD-1 is a member of the CD28/CTLA-4 family of T cell regulators,expressed on the surface of activated T cells, B cells and myeloid cells(Agata et al., 1996; Ishida et al., 1992). The main ligand for PD-1, PD-L1 induces a co-inhibitory signal in activated T-cells and promotes T-cell apoptosis, anergy and functional exhaustion (Shi et al., 2013).Thus, PD-1 and PD-L1 interaction is important for co-inhibition duringthe T-cell initiation of an immune response, and the importance ofthis interaction is highlighted by the autoimmune phenotype of PD-1knockout mice (Nishimura et al., 1999, 2001).

2. Materials and methods

2.1. Participants

PTSD patients (N = 30) were Croatian male combat veterans, re-cruited among outpatients at the “Dr. Josip Benčević” General Hospital,Slavonski Brod, Croatia. Healthy controls (N= 17) were men of similar

age from the same area. The elderly control group consisted of 15 per-sons (male N = 2, female N = 13) aged 80 or older.

War veterans met diagnostic criteria for PTSD based on the ICD-10(WHO, 1992). They were severely traumatized during the war inCroatia (1991–1995) and have undergone several forms of psychiatrictreatment since the war ended. For purposes of this study assessmentsof war veterans and healthy controls were made by structured inter-views, the Croatian versions of the Mini International NeuropsychiatricInterview (M.I.N.I.; (Sheehan et al., 1998)) and the Clinician Adminis-tered PTSD Scale (CAPS) (Blake et al., 1995). Assessments were madeby psychiatrists who had been trained in the administration of the spe-cific instruments. The participants from these groups also underwent aphysical examination in order to assess for symptoms or signs of acuteor chronic physical illnesses.

War veterans and healthy controls completed a questionnairewhichincluded: basic demographic characteristics, weight, height, alcoholconsumption, smoking, physical activity, presence of acute or chronicphysical illness, andmedication use. They were then asked to completerating scales for depression and anxiety symptoms. Depressionsymptoms were assessed with the Beck Depression Inventory (BDI)(Beck et al. 1988) and current anxiety level (state and trait anxiety)was determined by the Spielberger State-Trait Anxiety Inventory(STAI) (Spielberger et al. 1970).

Participants from the control group were excluded from the study ifthey had a history of acute psychosis, dementia, schizophrenia, mooddisorders, or personality disorders. The exclusion criteria for war vet-erans as well as healthy controls included: substance abuse, symptomsor signs of acute or chronic physical illnesses, including infectious, aller-gic or endocrine disorders.

A blood draw was performed after the initial psychiatric interviewand physical examination but before the structured psychiatric inter-view and completion of questionnaire and rating scales to minimizethe influence of acute stress on the results.

A group of elderly controls was recruited from an aged care nursinghome in„ Slavonski Brod”. They volunteered to participate in the study.Data obtained from this group served as a biological control for telomereshortening and age-related changes in immune reactivity. The onlyinclusion criteria were age N 80 and no history or current neoplasticdisorders or autoimmune diseases.

The study was approved by the Ethics Committee of the “Dr. JosipBenčević” General Hospital, Slavonski Brod, Croatia, and writteninformed consent was obtained from all subjects.

2.2. Blood sampling

Fasting whole blood of the participants was collected byvenipuncture in sodium heparin treated tubes (BD Biosciences,Heidelberg, Germany), between 7 and 9 AM. Peripheral blood mono-nuclear cells (PBMCs) were isolated on a Ficoll-Paque™ gradient (GEHealthcare Life Sciences, Uppsala, Sweden). Upon separation, mono-nuclear cells were washed, resuspended in freezing medium (10%FCS, 10% DMSO, 80% RPMI 1640) and transferred within a freezingcontainer (Sigma-Aldrich, St. Louis, USA) to −80 °C overnight, thenstored in liquid nitrogen until further processing.

2.3. Measurement of telomere length and telomerase activity

Genomic DNA was isolated from PBMCs by standard phenol–chloroform extraction (Sambrook and Russell, 2006). Concentrationand purity of the genomic DNA were determined by 260/280 UVspectrophotometry. Relative telomere length was measured by mul-tiplex quantitative PCR method as previously described (Cawthon,2009). Briefly, this method describes the relative telomere lengthas the ratio (T/S) of the telomere repeat copy number (T) to a singlecopy gene (S). This ratio is measured relative to a standard DNAwhich in this case was a pooled DNA sample of several healthy

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controls. Telomere length assay was performed in triplicate withintraassay variability CV = 7.56% and interassay variability acrossPCR plates CV = 11.21%. Basal telomerase activity was measuredwith a commercially available kit (TRAPeze® RT TelomeraseDetection Kit, Merck Millipore, Billerica, USA) according to the man-ufacturer instructions. This assay is a two-step PCR reaction thatmeasures telomerase enzymatic activity, rather than the expressionof telomerase protein. In the first step of the reaction, the telomeraseenzyme present in the samples adds a number of telomeric repeats(TTAGGG) onto the 3-end of a substrate oligonucleotide (telomerasesubstrate, TS). In the second step, the extended products areamplified by the Taq polymerase, using RT-PCR. The activity of eachsample is detected by using fluorescence energy transfer (ET)primers generating fluorescently labeled TRAP (Telomeric RepeatAmplification Protocol) products. The fluorescence emission pro-duced is directly proportional to the amount of TRAP productgenerated.

2.4. Proliferation of T cells

Frozen PBMCs were quickly thawed in a water bath at 37 °C, resus-pended in pre-warmed RPMI 1640 medium and counted. 3 × 106

PBMCs were stained with 1 μM CFSE dye (Life Technologies, Carlsbad,USA) and 1 × 106 cells/well were cultured in 24-well flat-bottom platesin 1 ml of RPMI 1640 medium with 10% FBS and neomycin. For eachsubject one well was left unstimulated and two were stimulated withphytohemagglutinin (PHA) (Sigma-Aldrich, Taufkirchen, Germany)concentrations 1 μg/ml and 10 μg/ml. PHA is a plant lectin whichactivates T cells by direct cross-linking of the T cell receptor (TCR)(Kruisbeek et al., 2004) thus mimicking antigen specific TCR activation.Proliferative function of PBMCs is well preserved after cryopreservation(Weinberg et al., 2009).

After 72 h of incubation (37 °C, 5% CO2) cells were washed withstaining buffer (Dulbecco PBS, 1% FBS, 0.1% NaN3) and stained with an-tibodies Alexa Fluor® 647 (AF 647)-conjugated anti-CD3 (HIT3a),APCy7 conjugated anti-CD4 (OKT4), and PerCP conjugated anti-CD8(SK1) (Biolegend, San Diego, USA). Following antibody staining, sam-ples were washedwith staining buffer and fixedwith 1% formaldehyde.

All flow cytometric samples were run on a LSRII flow cytometer (BDBiosciences, Heidelberg, Germany) and data were analyzed with FlowJosoftware (Tree Star, Ashland, USA). Positivity gates were set usingisotype and fluorescence minus one controls (Tung et al., 2008) wereneeded. Dead cells were excluded from the analysis by staining withLIVE/DEAD® Fixable Violet Dead Cell Stain Kit (Life Technologies)according to the manufacturer instructions.

2.5. PD-1 and PDL-1 expression on activated T cells

Cryopreservation has been shown to decrease PD-1 and PDL-1expression on PBMCs (Campbell et al., 2009), therefore we measuredexpression of PD-1 and PDL-1 on activated T cells, allowing them to re-cover for 24 h in culture media after thawing. Upon recovery,1 × 106 cells/well were cultured in 24-well flat-bottom plates in 1 mlof RPMI 1640 medium with 10% FBS and neomycin and stimulatedwith 1 μg/ml PHA. After 24 h of incubation (37 °C, 5% CO2) cells werestained with antibodies PerCP conjugated anti-CD3 (SK7), BrilliantViolet 570 conjugated anti-CD4 (RPA-T4), Alexa Fluor 488 conjugatedanti-CD8 (SK1), APC conjugated anti-CD274 (29E.2A3) and PE/Cy7 con-jugated anti-CD279 (EH12.2H7) (Biolegend), fixed and analyzed on aflow cytometer.

2.6. Cytokine production

For measurement of T cell cytokine production, 0.5 × 106 PBMCswere cultured in 96-well flat-bottom plates in 200 μl of RPMI 1640 me-dium with 10% FBS and neomycin. One well was left unstimulated and

one was stimulated with 50 ng/ml phorbol-12-myristate-13-acetate(PMA) and 0.75 ng/ml ionomycin. PMA activates protein kinase Cwhile ionomycin is a calcium ionophore, and stimulation with thesecompounds bypasses the TCR complex and leads to activation of sev-eral intracellular signaling pathways (Olsen and Sollid, 2013). Cellswere incubated for 5 h (37 °C, 5% CO2) with 10 μg/ml Brefeldin A(BFA) to prevent secretion of produced cytokines. BFA inhibits pro-tein transport from the Golgi apparatus to the endoplasmic reticu-lum and is more effective in blocking cytokine secretion thanfrequently used monensin (Schuerwegh et al., 2001). After incuba-tion, cells were washed with staining buffer and stained with PerCPconjugated anti-CD3 (SK7) antibody. Cells were than washed and re-suspended in permeabilization buffer (Dulbecco PBS, 1% FBS, 0.1%NaN3, 0.1% saponin) and stained with antibodies for intracellularmarkers: APC conjugated anti-IL-2 (MQ1-17H12), FITC conjugatedanti-IFN-γ (4S.B3) and PE conjugated anti-IL-4 (8D4-8) (Biolegend).Finally, cells were washed in permeabilization buffer, fixed and ana-lyzed on a flow cytometer.

The protocol for measurement of monocyte cytokine productionwas similar; 100 ng/ml lipopolysaccharide (LPS) was used for stimula-tion and incubation lasted for 6 h. LPS is a component of the outermem-brane of gram negative bacteria which activates monocytes by Toll-likereceptor-4 recognition (Pålsson-McDermott and O'Neill, 2004). Anti-bodies used for monocyte staining were FITC conjugated anti-CD68(Y1/82A), APC conjugated anti-TNF-α (Mab11) and PE conjugatedanti-IL-6 (MQ2-13A5) (Biolegend).

2.7. Statistical analyses

Participants' demographic characteristics with categorical data werecompared using the Fisher exact test for a 2 × 2 contingency table. Dis-tribution normality for all continuous variables was assessed per groupby visual inspection of the data (shape and symmetry of distribution,outliers, P–P plot) and by Shapiro–Wilk's W-tests. Exploratory analyseswere done by nonparametric tests, correlations were performed bySpearman's rank order correlations and subgroup analyses were per-formed with Mann–Whitney U tests. Continuous variables related toparticipants' characteristics (age, BMI) and psychometric tests (CAPS,STAI, BDI) were normally distributed, as well as telomere length. Linearregression with forward stepwise selection was used to test the associ-ation of PTSD patient's characteristics (age, BMI, smoking, alcohol in-take), drugs, comorbidity, and psychometric tests scores (CAPS, STAI,BDI) with telomere length (used as dependent variable). Theabovementioned analyses were performed with Statistica, v6 (StatSoftInc., Tulsa, USA).

Since the distribution of most biological variables was typicallyskewed, we used a nonparametric resampling procedure with 5000replications obtained from the complete study sample for all biologicalvariables and tests applied. Descriptive and inferential statistics werecalculated from the original dataset using bootstrap (resampling withreplacement) methods. Results are presented as means (an estimateof populationmeanbased on 5000 bootstrap samples)± SD of the sam-pling distribution (the estimate of the sample SE).When testing the dif-ferences among three groups (i.e. means), two-tailed p-values weredetermined as proportions of 5000 randomized trials in which thesum of squared differences between three group means were as largeas or larger than the observed sum of squared differences. To minimizethe possibility of type I error because of the multiple comparisons per-formed, we used the false discovery rate method (FDR) (Benjaminiand Hochberg, 1995). FDR threshold value (d) was calculated with sig-nificance level (α) set to 0.05 for a total of 21 comparisons related to bi-ological data. If differences among three means were still significant,posthoc comparisons between groups were performed and p-valueswere corrected by the Bonferroni method. All sampling and computa-tions were programmed using extended Resampling Stats language

278 M. Jergović et al. / Progress in Neuro-Psychopharmacology & Biological Psychiatry 54 (2014) 275–283

and run by Statistics 101, v 2.8 resampling statistics software (http://www.statistics101.net).

3. Results

3.1. Characteristics of participants

As shown in Table 1, the PTSD and healthy control groups did not dif-fer in respect to age, marital status and smoking habit. PTSD patientswere less educated, and a substantial proportion of them were retired.There was no difference in body mass index and regular exercise be-tween the groups while alcohol consumption was more frequent inhealthy controls. Current PTSD was confirmed with CAPS for all of theparticipants in the PTSD group. As expected, depression (BDI scores)and anxiety (STAI scores) symptoms were more pronounced in thePTSD group. A number of PTSD patients took analgesics during thepast week (non-steroidal anti-inflammatory drugs, N = 18, 60%;opioid analgesics, N = 3, 10%). Some of them were takinghypolipidemics (N = 3, 10%), antihypertensives (N = 3, 10%), andproton pump inhibitor (N = 1, 3%). The majority of PTSD patients(N = 28, 93%) were treated with psychotropic medication: antide-pressants (N = 27, 90%), mood stabilizers (N = 7, 23%), anxiolytics(N = 26, 87%), hypnotics (N = 22, 73%), and antipsychotics (N =14, 47%). Only four patients were without any comorbid psychiatriccondition, 24 (80%) had major depression, 13 (43%) had panic disor-der, 9 (30%) had obsessive compulsive disorder, and 7 (23%)were di-agnosed with social phobia.

3.2. Telomere length and telomerase activity

As shown in Fig. 1a PTSD patients had shorter average telomerelength (0.86 ± 0.031, N = 28) than their age-matched controls (1.03± 0.041, N = 17), and elderly volunteers had the shortest telomeres(0.67 ± 0.036, N = 14). Fig. 2b illustrates basal telomerase activity of

Table 1

Characteristics of participants. Bold entries are statistically significant p-values.

Variables PTSD patients (N = 30)

Age, yearsa 45.9 ± 1.12Body mass indexa 27.13 ± 4Educationb

Elementary/high 29 (96.4)University 1 (3.4)

Marital statusb

Married 25 (86.2)Single/divorced 4 (13.8)

Work statusb

Employed 1 (3.4)Unemployed/retired 29 (96.4)

Tobacco useb

Yes 17 (58.6)No 12 (41.4)

Alcohol useb

Yes 5 (20)No 24 (80)

Daily physical exerciseb 1 (3.33)BDI scorea 29.38 ± 8.7CAPS scorea

Re-experiencing 17.3 ± 5.7Avoidance 23.4 ± 7.5Hyperarousal 15.8 ± 4.8Total 56.7 ± 14.8

STAI-Statea, score 54.5 ± 9.9STAI-Traita, score 57.9 ± 8.9

a Data presented as mean (an estimate of population mean based on 5000 bootstrap sampletailed p-values are obtained as proportion of sampling distribution of absolute differences betworiginal group means.

b Data presented as n (%). The associated p-values are Fisher's exact two-tailed probabilities

the study groups expressed as the log value of the estimated numberof telomeric repeats added to an oligonucleotide substrate. There wasno difference in telomerase activity between PTSD patients (3.94 ±0.038, N= 30) and healthy controls (3.96 ± 0.044, N= 14) but elderlyindividuals (1.26 ± 0.11, N = 13) had much lower telomerase activitythan both PTSD patients and healthy controls.

3.3. Proliferation

As shown in Table 2, the percentage of proliferating CD4+ and CD8+

T cells after stimulation with mitogen was significantly lower in the el-derly group in comparison to healthy controls and PTSD patients at bothconcentrations of PHA. At the concentration of 10 μg/ml PHA PTSD pa-tients exhibited decreased proliferation of CD8+ but not CD4+ T cellscompared to healthy controls. There was no difference in proliferationbetween PTSD and healthy controls at PHA concentration of 1 μg/ml.

3.4. PD-1 and PDL-1 expression on activated T cells

Percentages of CD4+ and CD8+ T cells expressing PD-L1 in studygroups are presented in Fig. 2. PD-L1+ T cells followed a trend withhealthy controls having the highest percentages (CD4+, 70.0 ± 4.62;CD8+, 71.4± 3.22, N=16), followed by lower percentages in PTSD pa-tients (CD4+, 59.7± 3.53; CD8+, 64.1± 3.26, N=27) and elderly per-sons having the lowest percentages of these cells (CD4+, 44.3 ± 5.63;CD8+, 47.6± 5.33; N= 14). However, statistical significance of the ob-served differences was reached only when comparing percentages ofPD-L1+ T cells between elderly persons and healthy controls; the differ-ence between PTSD patients and healthy controls was not significant(see Fig. 2). Elderly controls also had significantly lower percentagesof CD8+ PD-L1+ cells than PTSD patients (Fig. 2).

Percentages of PD-1+ T cells were recorded as follows: healthy con-trols (CD4+, 34.9 ± 3.41; CD8+, 49.1 ± 0.51; N = 16), PTSD patients(CD4+, 29.5 ± 1.89; CD8+, 50.2 ± 0.86; N = 27), and elderly controls

Healthy controls (N = 17) p

47.2 ± 1.71 0.50227.3 ± 2.62 0.883

11 (64.7) 0.00486 (35.3)

13 (76.5) 0.05954 (23.5)

15 (88.2) b0.0012 (11.8)

9 (52.9) 0.7088 (47.1)

11 (64.7) b0.0016 (35.3)1 (5.88) 0.8674.9 ± 5.4 b0.001

39.0 ± 0.2 0.00136.9 ± 6.7 0.001

s) ± SD of the sampling distribution (the estimate of the sample SE). The associated two-een 5000 randomized group means that are at least as extreme as the difference between

.

Fig. 1. a) Relative telomere length of PBMCs, three group comparison p b 0.001, false discovery rate (FDR) d= 0.005, and individual comparisons (P:C, p= 0.008; P:E, p= 0.003;C:E, p b 0.001), and b) basal telomerase activity of PBMCs, three group comparison p b 0.001, FDR d= 0.005, and individual comparisons (P:C, p = 0.83; P:E, p b 0.001; C:E, p b 0.001).Group means (an estimate of population mean based on 5000 bootstrap samples) are represented as horizontal lines. For details on analyses see the Statistical analyses section.

279M. Jergović et al. / Progress in Neuro-Psychopharmacology & Biological Psychiatry 54 (2014) 275–283

(CD4+, 25.3± 3.02; CD8+, 51.4 ± 1.31; N= 14). There were no statis-tically significant differences in percentages of PD-1+ T cells betweenstudy groups (CD4+: three group comparison p = 0.051, FDR d =0.036; CD8+: three group comparison p = 0.232, FDR d = 0.043).

3.5. Cytokine production

Cytokineproduction of PMA/ionomycin stimulated andunstimulatedT cells is shown in Table 3. There were no differences between the studygroups in the percentages of cells producing individual Th1/Th2 cyto-kines after stimulation. Percentages of stimulated lymphocytes simulta-neously producing both IFN-γ and IL-2 were also evenly distributedamong study groups (controls, 2.98± 0.33%; PTSD, 3.99± 0.58%; elder-ly, 2.82 ± 0.47%; three group comparison p = 0.182, FDR d = 0.041).Spontaneous (i.e. unstimulated) production of IFN-γ and IL-2was signif-icantly lower in PTSD patients than in the other two groups (Table 3).

Fig. 2. PD-L1 expression on CD4+ (gray triangles) and CD8+ T cells (black dots). CD4+ Tcells: three group comparison p = 0.002, false discovery rate (FDR) d = 0.019, and indi-vidual comparisons (P:C, p = 0.075; P:E, p = 0.251; C:E, p = 0.008). CD8+ T cells: threegroup comparison p b 0.001, FDR d= 0.014, and individual comparisons (P:C, p= 0.374;P:E, p = 0.029; C:E, p = 0.004). The numbers on axes represent percentages of positivecells. Group means (an estimate of population mean based on 5000 bootstrap samples)are represented as horizontal lines. For details on analyses see the Statistical analysessection.

As shown in Table 4 there were no differences in LPS stimulatedmonocyte cytokine production between the study groups but elderlypersons exhibited high spontaneous production of both IL-6 and TNF-α proinflammatory cytokines.

3.6. Correlational, subgroup and regression analyses

Telomere length, telomerase activity and immunological variablesdid not correlate with individual clusters of CAPS scores or with BDI orSTAI scores (tested with Spearman's rank order correlations). Therewas no correlation betweenmeasured telomere length of PTSD patientsand immunological variables while telomerase activity was negativelycorrelated with IFN-γ production (Spearman's r = −0.47, p = 0.018),which is expected since IFN-γ signaling was shown to down-regulatetelomerase activity (Lee et al., 2005). As opposed to our expectations,age did not correlate with telomere length in individual groups(controls, Spearman's r = −0.23, p = 0.376, N = 17; PTSD, r =−0.31, p = 0.104, N = 28; elderly, r = 0.01, p = 0.961, N = 14)probably because each group did not vary much in age. Because of thedocumented influence of smoking on telomere length, we also testedif there was a difference between smokers and non-smokers.Current smokers in the PTSD group (N = 15) had shorter telomerelength [median (interquartile range); 0.80 (0.65–0.96)] than non-smokers [N = 12; 0.95 (0.85–1.03)] (Mann–Whitney U = 41, p =0.017). During exploratory analyses we also found that PTSD patientswho took mood stabilizers had shorter telomeres [0.64 (0.56–0.92) vs.0.91 (0.80–1.00); Mann–Whitney U= 24.5, p= 0.020]. In order to an-alyze all of these factors, we performed linear regression analysis withforward stepwise selection to test the association of PTSD patients'characteristics, medication, comorbidity, and psychometric test scoreswith telomere length. Continuous predictors were age, BMI, CAPS(three clusters), STAI (state and trait), and BDI, all normally distributed;dichotomous predictors were smoking, alcohol intake, medication (8variables), and comorbidity (4 variables). Missing values were replacedwith means. A significant model emerged [F(2,27)= 7.364, p = 0.003,R2 = 0.305] with mood stabilizers (beta = −0.377, p = 0.029) andsmoking (beta = −0.358, p = 0.037) as significant predictors oftelomere length. In subsequent analyses we excluded 7 patients whowere taking mood stabilizers (with two missing values giving a totalof 21 PTSD patients) and compared telomere length to controls (N =17) using ANCOVA with age and smoking as covariates. The differencebetween patients and controls remained significant [F(1,34) = 8.070,p = 0.008].

Table 2

Proliferation of PHA stimulated T cells expressed as % of proliferating cells. Data are presented as mean (an estimate of population mean based on 5000 bootstrap samples) ± SD of thesampling distribution (the estimate of the sample SE). Bold entries are statistically significant p-values.

Variable PTSDN = 30

ControlsN = 17

ElderlyN = 15

Three groupcomparisona

Individual comparisonsp-valuesb

d0.05 p P:C P:E C:E

CD3+CD4+

(1 μg/ml PHA)9.4 ± 1.11 14.0 ± 2.24 4.9 ± 0.96 0.017 0.002 0.132 0.051 0.008

CD3+CD8+

(1 μg/ml PHA)11.5 ± 1.39 16.0 ± 2.03 3.9 ± 0.97 0.004 b0.001 0.191 0.002 0.001

CD3+CD4+

(10 μg/ml PHA)18.0 ± 2.70 25.8 ± 4.19 11.7 ± 2.50 0.025 0.019 0.315 0.372 0.041

CD3+CD8+

(10 μg/ml PHA)16.2 ± 1.96 25.1 ± 2.85 7.7 ± 2.11 0.004 b0.001 0.047 0.034 0.001

a The difference is considered significant at α = 0.05 if p-value is less than the corresponding d value computed using the FDR technique.b p-Values corrected according to the Bonferroni method.

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4. Discussion

In the present study, we report that middle-aged war veterans withcurrent PTSD have shorter PBMC telomere length than age-matchedhealthy controls (Fig. 1). Among variousmeasures of immune reactivityreported in this study, PTSD patients showed reduced spontaneousproduction of Th1 cytokines (IFN-γ and IL-2) and reduced proliferativeresponse of CD8+ T cells to high concentrations of mitogen.

Similar to our findings, telomere shortening in leukocytes of civilianPTSD sufferers has recently been reported (Ladwig et al., 2013;O'Donovan et al., 2011). There are several mechanisms through whichneuroendocrine alterations in PTSD could affect telomere length. Telo-merase activity has been shown to be reduced in human T lymphocytesexposed to cortisol (Choi et al., 2009), but measurements of telomeraseactivity in human chronic stress models provide contradictory findings,with reports of higher (Damjanovic et al., 2007) and lower basal telome-rase activities (Epel et al., 2004). In our sample there was no differencein telomerase activity between PTSD patients and healthy controls butas telomerase activity is dynamic and can be influenced by acute stress(Epel et al., 2010) we consider it less informative than telomere length.Oxidative stress accelerates telomere attrition (Kawanishi and Oikawa,2004) and levels of oxidative stress have been shown to be increasedduring progression of PTSD-like behavior in a rodent model (Wilsonet al., 2013). However, measurements of oxidative stress parametersin human PTSD sufferers offer conflicting results (Ceprnja et al., 2011;Tezcan et al., 2003). Another possibility is that excess of inflammatoryactivities in PTSD (Gill et al., 2009) might increase cell turnover andlead to replicative telomere shortening (Allsopp et al., 1995). However,production of pro-inflammatory cytokines (IL-6 and TNF-α) by mono-cytes of PTSD patients was not increased in our study (Table 4). Onecannot exclude the possibility that PTSD veterans experienced moreantigenic stress during their military service which would also increasecell turnover (Mueller and Ahmed, 2009).

It must be noted that telomere length can be influenced by variousbiological and behavioral factors: hereditability (Prescott et al., 2011),age (von Zglinicki and Martin-Ruiz, 2005), sex (Barrett and Richardson,2011), smoking (Valdes et al., 2005), obesity (Lee et al., 2011), physicalactivity (Savela et al., 2013), alcohol consumption (Pavanello et al.,2012), infection (Ilmonen et al., 2008) and various chronic diseases(Fitzpatrick et al., 2007; Hohensinner et al., 2011; Xie et al., 2013). Asin other studies, it was impossible to control for all these factors, butPTSD patients and controls did not differ with respect to age, bodymass index, smoking habits and physical activity (Table 1). All of theabovementioned factors were taken into account in a regression modelwhich showed that telomere length in the PTSD sample was associatedwith smoking and the use of mood stabilizers. Subsequent analyseswere performed with patients that were free of mood stabilizers and

the difference in telomere length was preserved. Comorbid disorderswere not associatedwith telomere length and therewere no correlationsbetween the level of PTSD, anxiety or depression symptoms and telo-mere length. It has been shown that biological changes in war veteranscould be trauma related regardless of PTSD diagnosis (de Kloet et al.,2007). Inclusion of traumatized veterans without PTSDwould have clar-ified if telomere shorteningwas associatedwith trauma itself rather thanPTSD. Moreover, although childhood trauma has been shown to affecttelomere lengthwedid not assess its possible contribution in the presentstudy.

As with the mechanisms through which chronic stress acceleratestelomere attrition, the functional alterations associated with telomereshortening are also not well understood. Therefore, we aimed to assesscellular function associated with telomere shortening in PTSD sufferers.Our results suggest that telomere shortening in PBMCs of middle-agedPTSD patients is not associated with large changes in immune reactivityas the only changes observed in the PTSD group were reduced prolifer-ation of CD8+ T cells at PHA concentration of 10 μg/ml (Table 2) andslightly decreased spontaneous production of IL-2 and IFN-γ. Sup-pressed Th1 cytokine responses have been implicated in stress-relateddisorders (Elenkov, 2004; Hou et al., 2013) but the data on humanPTSD subjects is inconclusive. Reduced serum IL-2 levels have been re-ported in earthquake survivors (either with PTSD or non-PTSD) (Songet al., 2007) while IFN-γ levels were reported to be higher in superna-tants of stimulated cell cultures of abused women and in women withcurrent PTSD symptoms (Woods et al., 2005). In contrast, reduced pro-duction of IFN-γ and IL-4 has been observed in men with a past historyof PTSD (Kawamura et al., 2001). A key advantage of our study is thatwemeasured the ability of the cells to produce cytokines directly by flowcytometric intracellular staining whereas most of the studiesconcerning cytokine production in PTSD subjects have been performedon serum or cell culture supernatant samples. IL-6 has been shown tobe associated with DNA damage induced senescence of humankeratinocytes, melanocytes, monocytes, and fibroblasts (Coppé et al.,2010). Thus, it is somewhat surprising that our PTSD patients withshortened telomeres did not exhibit increased production of inflamma-tory cytokines. Most of the studies showing increased levels of inflam-matory cytokines in PTSD have been performed on serum or plasmasamples (Baker et al., 2012), therefore our results indicate that cellsother than PBMCs could be major contributors to the increased levelsof these cytokines in circulation. Particularly fibroblasts are prone to senes-cent transformation into proinflammatory cells; a condition known assenescence-associated secretory phenotype (SASP) (Coppé et al., 2010).

In the current study, PTSD patients tended to have lower percent-ages of PD-L1+ T cells (Fig. 2) but the differencewas not statistically sig-nificant (p= 0.08). However, this trendneeds to be investigated furtherin larger sample sizes, given that PD-1 and PD-L1 are important negative

Table 3

Unstimulated (u) and PMA/Ionomycin stimulated (s) cytokine production expressed as % of Th1/Th2 cytokine producing lymphocytes. Data are presented as mean (an estimate ofpopulation mean based on 5000 bootstrap samples) ± SD of the sampling distribution (the estimate of the sample SE). Bold entries are statistically significant p-values.

Variablea PTSDN = 25

ControlsN = 15

ElderlyN = 13

Three groupcomparisona

Individual comparisonsp-valuesb

d0.05 p P:C P:E C:E

IFN-γ (u) 0.29 ± 0.02 0.41 ± 0.04 0.42 ± 0.05 0.029 0.020 0.010 0.002 0.999IL-4 (u) 0.39 ± 0.04 0.65 ± 0.09 0.50 ± 0.05 0.031 0.036IL-2 (u) 0.47 ± 0.03 0.62 ± 0.05 0.71 ± 0.07 0.021 0.008 0.048 0.004 0.595IFN-γ (s) 13.1 ± 1.19 16.0 ± 1.60 16.7 ± 1.82 0.045 0.242IL-2 (s) 17.6 ± 2.15 21.0 ± 1.98 12.5 ± 2.33 0.033 0.045IL-4 (s) 2.13 ± 0.17 2.16 ± 0.23 2.48 ± 2.26 0.029 0.036

a The difference is considered significant at α = 0.05 if p-value is less than the corresponding d value computed using the FDR technique.b p-Values corrected according to the Bonferroni method.

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regulators of immune responses with great clinical significance in auto-immunity (Mozaffarian et al., 2008) and cancer (Velcheti et al., 2014).One previous study examined immune function associated with telo-mere shortening in a human chronic stress model (Damjanovic et al.,2007) and found significantly lower T cell proliferation but a higher pro-duction of immune-regulatory cytokines (TNF-α and IL-10). This studywas performed on a group of caregivers of Alzheimer's disease patientswith a mean age of 65 years which could be the reason why the ob-served changes in immune reactivity were more pronounced than inour group of PTSD veteranswith amean age of 45.9 years. Genetic stud-ies in mice have demonstrated that short telomeres rather than averagetelomere length are associated with age-related degenerative defects(Armanios et al., 2009; Hemann et al., 2001). Thus it appears that telo-meres inmost of the PBMCs of our patient sample did not reach a criticallength at which there would be marked changes in immune reactivity,which could be the reason why there were no correlations betweentelomere length and immune activity measures within the PTSDgroup. Additionally, immunosenescence might be affected by other,non-telomere related mechanisms (Su et al., 2013). As expected, the el-derly group in the current study (Ershler and Keller, 2000; Hohensinneret al., 2011; Weng, 2008) had increased spontaneous production of in-flammatory cytokines IL-6 and TNF-α (Table 4), extremely reduced pro-liferative capacity of T cells (Table 2) and reduced production of IL-2(Table 3), in addition to having short telomeres and low telomerase ac-tivity (Fig. 1). Comparing the elderly group to the middle-aged healthycontrols revealed several new interesting findings. To our knowledgethis is the first report of an age-dependent decrease of PD-L1 on activat-ed T cells (Fig. 2). PD-1/PD-L1 interaction might play an important rolein the increased prevalence of autoimmunity and cancers in the elderly(Vadasz et al., 2013). Interestingly, while the number of IL-2 producingcells was significantly reduced, the number of highly importantpolyfunctional T cells (Ciuffreda et al., 2008; Qiu et al., 2012) producingIFN-γ and IL-2 appeared to be well preserved in the elderly.

A limitation of the current study is that the elderly group consistedmostly of females. It is widely believed that females have longer telo-meres thanmales, although results from studies have been contradictory

Table 4

Monocyte unstimulated (u) and LPS stimulated (s) cytokine production expressed as % of cytok5000 bootstrap samples) ± SD of the sampling distribution (the estimate of the sample SE). B

Variable PTSDN = 30

ControlsN = 17

ElderlyN = 14

TNF-α (u) 2.04 ± 0.24 2.74 ± 0.37 4.02 ± 0.37IL-6 (u) 3.02 ± 0.32 3.78 ± 0.34 8.80 ± 1.60TNF-α (s) 61.7 ± 3.64 72.1 ± 3.27 66.8 ± 5.27IL-6 (s) 52.7 ± 2.55 56.7 ± 2.28 61.2 ± 3.68

a The difference is considered significant at α = 0.05 if p-value is less than the correspondib p-Values corrected according to the Bonferroni method.

(Gardner et al., 2014), therefore we can assume that the observed differ-ences between the elderly group and healthy controls would be evenmore pronounced if the elderly were all males. We included this groupas biological controls for an aging immune system, thus they did not un-dergo a psychiatric examination. Also various medications used by theparticipants in this group could have influenced some of the immune re-lated measurements. Persons older than 80 years were selected in orderto be certain that the immunosenescent profile would be apparent.

Aside fromnot taking childhood trauma into account, another short-coming of the study is that due to ethical considerations, themajority ofPTSD patients were medicated at the time of the study. However, addi-tional analyses performed suggest thatmedication did not substantiallyaccount for the observed group differences in telomere length.

Due tomultiple comparisons performedwewere concerned in com-mitting type I error, and that is why we involved both FDR andBonferroni corrections at different stages of analyses. This conservativeapproach raises the possibility of type II error, especially due to smallsample sizes. However, since all relevant statistical parameters are em-phasized, with some comparisons being close to statistical significance,one can calculate sample sizes needed to achieve sufficient statisticalpower to be able to test if observed differences are significant. Thiscould be a valuable starting point for future replicate studies.

5. Conclusions

Telomere shortening of leukocytes/PBMCs is an emerging biomarkerof chronic stress related disorders. The mechanisms of stress relatedtelomere attrition are not well understood and research on functionalchanges associated with this telomere shortening is scarce. Our resultssuggest that telomere shortening in the PBMCs of middle-agedwar vet-erans with PTSD is associated with changes in the immune activity ofthese cells that are not as pronounced as in elderly persons, but maycontribute to health risks associated with PTSD. Further prospectivestudies are needed to elucidate the functional immune changes associ-ated with stress related telomere shortening.

ine producing cells. Data are presented asmean (an estimate of populationmean based onold entries are statistically significant p-values.

Three group comparisona Individual comparisons p-valuesb

d0.05 p P:C P:E C:E

0.025 0.019 0.132 0.051 0.0080.012 b0.001 0.191 0.002 0.0010.048 0.2670.038 0.140

ng d value computed using the FDR technique.

282 M. Jergović et al. / Progress in Neuro-Psychopharmacology & Biological Psychiatry 54 (2014) 275–283

Acknowledgments

This study was financed primarily by a grant from the Ministry ofScience, Education and Sports of the Republic of Croatia (021-0212432-2434 to AS). The authors would like to thank Prof. Ivan Đikićand Koraljka Husnjak of the Institute of Biochemistry II, Goethe Univer-sityMedical School, Frankfurt, Germany for their financial and technicalaid in performing this study. The study was also in part supported byEFIS–Immunology Letters fellowship to MJ.

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