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Published online before print July 18, 2007, 10.1097/PSY.0b013e3180cc2c61
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Psychosomatic Medicine 69:551-559 (2007)
© 2007 American Psychosomatic Society

ORIGINAL ARTICLES

Effects of Chronic Stress and Interleukin-10 Gene Polymorphisms on Antibody Response to Tetanus Vaccine in Family Caregivers of Patients With Alzheimer’s Disease

Jian Li, MD, PhD, Linda G. Cowden, RN, Janice D. King, HT(ASCP), David A. Briles, PhD, Harry W. Schroeder, Jr, MD, PhD, Alan B. Stevens, PhD, Rodney T. Perry, PhD, Zuomin Chen, MD, Micah S. Simmons, MS, Howard W. Wiener, PhD, Hemant K. Tiwari, PhD, Lindy E. Harrell, MD, PhD and Rodney C. P. Go, PhD

From the Department of Epidemiology and International Health (J.L., L.G.C., R.T.P., Z.C., M.S.S., H.W.W., R.C.P.G.), School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama; Department of Microbiology and Immunology (J.D.K., D.A.B.), University of Alabama at Birmingham, Birmingham, Alabama; Departments of Clinical Immunology and Medicine (H.W.S.), University of Alabama at Birmingham, Birmingham, Alabama; Department of Medicine (A.B.S.), Texas A&M University System Health Science Center, Huston, TX; Department of Biostatistics (H.K.T.), Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, Alabama; Department of Neurology (L.E.H.), School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama.

Address correspondence and reprint requests to Jian Li, Department of Epidemiology and International Health, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Objective: To assess the effects of psychological stress on the antibody response to tetanus vaccine adjusting for cytokine gene polymorphisms and other nongenetic factors in caregivers of patients with Alzheimer’s disease (AD).

Methods: A family-based follow-up study was conducted in 119 spouses and offspring of community-dwelling patients with AD. Psychological stress was measured by the Perceived Stress Scale (PSS) and the Center for Epidemiologic Studies Depression (CES-D) scale at baseline and 1 month after the vaccination. Nutritional status, health behaviors, comorbidity, and stress-buffering factors were assessed by self-administered questionnaires, 10 single nucleotide polymorphisms (SNP) from six selected cytokines genotyped, and anti-tetanus toxoid immunoglobulin G (IgG) concentrations tested using enzyme-linked immunosorbent assays. The effects of stress and other potential confounders were assessed by mixed models that account for familial correlations.

Results: The baseline PSS score, the baseline CES-D score, the interleukin-10–1082 A>G SNP GG genotype, and the baseline anti-tetanus IgG were inversely associated with antibody fold increase.

Conclusion: Both psychological stress and cytokine gene polymorphisms affected antibody fold increase. The study provided additional support for the detrimental effects of psychological stress on the antibody response to tetanus vaccine.

Key Words: psychological stress • cytokine genes • antibody response • vaccine

Abbreviations: AD = Alzheimer’s disease; CES-D = Center for Epidemiologic Studies Depression; PSS = Perceived Stress Scale; ELISA = enzyme-linked immunosorbent assays; SNP = single nucleotide polymorphisms.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
The detrimental effects of chronic psychological stress on vaccine-induced antibody response have been documented in different populations (1,2), with the most consistent reports found in spousal caregivers of patients with dementia (3–9). One of the major pathways through which chronic psychological stress affects immune functions is the chronic activation of the hypothalamic-pituitary-adrenal (HPA) axis, resulting in the chronic elevation of systemic glucocorticoids (10–12). At higher than physiological concentration, glucocorticoids can lead to a wide range of immune dysregulations, with one of the notable changes including the inhibition of cytokine synthesis and the imbalance of the Th1/Th2 cytokine network (10–12). Several lines of evidence have indicated that the stress-induced imbalance of the Th1/Th2 cytokine network underlies a wide range of immune changes and diseases among people subject to chronic stress (13–16).

Stress is commonly measured by subjective assessments using standard questionnaires, such as Perceived Stress Scale (PSS) (17) and the Center for Epidemiologic Study Depression (CES-D) scale (18) or objective stress biomarkers, such as salivary cortisol (7,19–21). Studies using those stress measures have reported inconsistent effects of stress on vaccine-induced antibody response. Whereas Vedhara et al. (7) found that the mean salivary cortisol concentrations were inversely correlated with the immunoglobulin G (IgG) antibody titers to one viral strain in the influenza vaccine in spousal dementia caregivers, Burns et al. (22) reported that undergraduate students with low titer to hepatitis vaccine had significantly lower cortisol levels compared with those with higher antibody titer. Moreover, many dementia caregiver studies found no correlation between antibody response to influenza vaccine and subjective stress measures (4,5,7,8); neither was antibody response associated with caregiving variables, including years spent caregiving, the number of hours spent on caregiving daily, or the extent of the patients’ cognitive impairment (4,8). However, when caregiving status was used as a surrogate for stress levels, it was consistently reported that compared with the age- and gender-matched noncaregivers, the current and former caregivers had weaker vaccine-induced antibody response (4,8).

One of the reasons for those inconsistencies lies in the complexity of assessing psychological stress and antibody response. The commonly used questionnaires measure global stress and depressive symptoms rather than caregiving-specific stress; thus, the differences in stress levels between caregivers and noncaregivers can be attributed to life events other than caregiving. The same is true for objective measures such as salivary cortisol because the HPA axis can be activated by stressors other than dementia caregiving. In addition to psychological stress, antibody response can be influenced by other factors such as comorbidity and nutrition (23). Furthermore, vaccine-induced antibody response is influenced by genetic factors (23). Various human leukocyte antigen (HLA) loci and cytokine gene polymorphisms have been found to be associated with the responsiveness to several vaccines (24–26). Twin studies have further estimated that genetic effects account for about 60% of the variation in the antibody levels in response to the hepatitis B vaccines and at least 40% of the variation in anti-tetanus IgG titers after vaccination with tetanus toxoid (TT) (27,28). More importantly, twin studies have demonstrated that a) non-HLA genes, such as cytokines, have played major roles in response to vaccines that primarily induce antibody production and b) >50% of the variations in antibody levels are determined by the non-HLA loci (27,28). Taken together, the differences in the antibody response between the caregivers and the noncaregivers are the result of the complex interplay between stress due to caregiving and other causes, other nongenetic factors, and host genetic make-up. Thus, it is critical to account for other genetic and nongenetic factors to better delineate the effect of stress on antibody response.

The current study examined the effects of psychological stress on the antibody response to tetanus vaccine adjusting for cytokine gene polymorphisms and other nongenetic factors in the spouses and offspring of community-dwelling patients with Alzheimer’s disease (AD). First, given that in many families both the spouses and the adult offspring are directly or indirectly involved with the caregiving for the community-dwelling patients with AD, it is important to study the variability of stress among family members. The family study design also provided a unique advantage in controlling for many unmeasured environmental exposures and genes shared by family members and in estimating the degrees to which one’s genetic make-up influence the antibody response. Second, because the cross-talk between the neuroendocrine and immune system is mediated through Th1/Th2 cytokines and cytokine productions are under genetic control (10–12), a number of antagonistic and synergistic Th1 (interleukin (IL)-1ß, IL-2, IL-12, tumor necrosis factor (TNF)-{alpha},) and Th2 (IL-10, IL-4) cytokines were chosen. Those cytokines have been found to play roles in influencing antibody response to a variety of vaccines (26,29,30). Finally, psychological stress was assessed by the PSS (17) and depressive symptoms by the CES-D scale (18). It is important to note that those scales do not capture caregiving-specific stress bur rather global stress, which allowed us to study the effect of stress in a broader context. Moreover, recent intervention research aimed at improving caregiver’s mental health outcome (31,32) pointed to the importance of examining stress-buffering factors such as social support (33–35), social activities (36), and positive aspects of caregiving (37). Other nongenetic confounders included age, gender, comorbidity, nutritional status, and baseline anti-TT IgG. We hypothesized that people with different stress levels would have differential antibody response to the tetanus vaccine after adjusting for the cytokine genes, stress-buffering factors, and other nongenetic factors.


   METHODS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Study Population
The study population consisted of 47 Caucasian families, with a total sample size of 119 individuals. Each family consisted of the spouse of the community-dwelling patient with AD and one or two of their biological offspring. Twenty-five families contained one spouse and two offspring and 22 families contained one spouse and one offspring. Between February 2005 and February 2006, 178 families were initially approached in the Memory Disorders Clinic at the University of Alabama at Birmingham (UAB) where the family members accompanied the patients with AD for follow-up visits, 43 of whom agreed to participate after subsequent phone contacts. Four families were recruited from the previous participants in the MIRAGE study (Multi-Institutional Research on Alzheimer’s disease Genetic Epidemiology, UAB site). The study was approved by the Institutional Review Board of UAB.

To be eligible for the study, the spouses had to be community-dwelling and take care of the patients with AD at home, be able to give consent, and live within a 2- to 4-hour driving distance from Birmingham, Alabama. The offspring had to be at least 19 years of age to give legal consent. Additionally, all the family caregivers were limited to Caucasians to avoid population stratification. An individual was excluded from participation for any of the following conditions: vaccination with TT within the past 3 years, allergy to vaccine components or a history of a neurological reaction after a previous vaccine dose, major psychiatric illnesses or degenerative neurological disorders, autoimmune diseases, human immunodeficiency virus infection, splenectomized patients, transplant recipients, serious trauma within the previous 6 months, primary immunodeficiency, chemotherapy or radiation treatment for cancer within the past 5 years, immunosuppressant medications within the past 3 months, history of blood coagulation disorder, and pregnancy or lactation.

Collection of Nongenetic Factors
The nongenetic information was collected using seven well-validated instruments, including Social Support (33–35), Social Activities (36), Positive Aspects of Caregiving (37), Caregiver Health and Health Behaviors (38,39), Mini Nutritional Assessment (MNA) (40), PSS (17), and CES-D scale (18). The PSS and CES-D were administered face-to-face with the study participants at baseline and 1 month after vaccination during home visits, whereas the rest of the questionnaires were mailed to the participants after they gave verbal consent over the phone and were collected at the first home visit. The average time between the dates when the questionnaires were mailed to the study participants and the dates when the questionnaires were collected at the first home visit was 3 weeks.


Perceived Stress
The PSS (17) measures the degree to which situations in one’s life are perceived as stressful and has been commonly used in caregiver studies. There are ten questions asking how often one felt or thought a certain way in the past month, with five responses ranging from never, almost never, sometimes, fairly often, to very often. A total score is obtained by summing across all 10 items. The possible scores range from 0 to 40, with higher scores indicating higher stress levels.

Depressive Symptoms
The CES-D short form (18,41) measures the current levels of depressive symptoms. It contains 10 of the original 20 items, including 1) I was bothered by things that don’t usually bother me, 2) I had trouble keeping my mind on what I was doing, 3) I felt depressed, 4) I felt that everything I did was an effort, 5) I felt hopeful about the future, 6) I felt fearful, 7) My sleep was restless, 8) I was happy, 9) I felt lonely, 10) I could not get "going." The questionnaire has a 4-point scale indicating the frequency of their occurrence in the past week. The summation of all 10 items generates a total score ranging from 0 to 30, with higher scores indicating greater frequencies or numbers of depressive symptoms.

Social Support
The Social Support scale measures four broad categories of social support construct: received support with separate items for emotional, tangible, informational subscales; satisfaction with the support, with separate items for the overall satisfaction with tangible, emotional, and informational support received (34); social network of family, friends, and confidants (35); and negative interactions with others (33). An overall total social support score is calculated by summing 15 questions. The score ranges between 0 and 53, with higher scores indicating higher levels of social support.

Social Activities
The Social Activities scale measures the impact of caregiving on one’s ability to engage in desirable social/leisure activities (36). The form consists of seven questions asking the caregivers how often they have been able to participate in various social/leisure activities (e.g., quiet time, attending church). The response to these items should be summed to form a total score ranging from 0 to 14, with higher scores indicating greater amounts of time for social/leisure activities.

Positive Aspects of Caregiving
The Positive Aspects of Caregiving scale contains 11 items phrased as statements about the caregivers’ mental state in relationship to the caregiving experience and their ability to cope with the caregiving-related stress by emphasizing the positivity of the experiences (37). The response options are on a 5-point agree/disagree scale. The total scores range from 0 to 36, with higher scores indicating more positive feelings toward caregiving.

Health Behaviors and Comorbidity
The Caregiver Health and Health Behavior instrument assesses caregivers general and perceived health, comorbidities, and preventive health behavior (38,39). The section that measures comorbidity included 12 disease conditions; the total score ranges from 0 to 12, with higher scores indicating higher numbers of comorbidity.

Nutritional Status
The MNA (40) includes anthropometric measurements, a dietary questionnaire, global assessment, and self-assessment. The possible scores range between 0 and 30. The nutritional assessment consists of three categories: malnourished =<17; at risk of malnutrition = 17 to 23.5; and well nourished =≥24.

Home Visits for Blood Collection and Stress Assessment
There were two home visits. On the first visit, the research staff conducted informed consent. Then, 30 ml of venous blood was drawn followed by the injection of 0.5 ml TT adsorbed (Aventis Pasteur, Swiftwater, PA, USA) administered intramuscularly into the deltoid muscle on one arm. Weight, height, midarm, and calf circumferences were also measured. On the second visit scheduled 4 weeks after the vaccination, the same amount of blood (30 ml) was drawn. On both visits, the research staff conducted face-to-face interviews using the PSS and CES-D scale.

Antibody Testing
Sera samples were analyzed for their content of antibodies reactive with the TT antigen using an enzyme-linked immunosorbent assays (ELISA) (42). Paired pre- and postvaccination serum samples were tested for anti-TT IgG in duplicates for the total sample of 119 vaccinees. Microtiter 96-well plates (NUNC Roskilde, Denmark) were coated overnight at 4°C in phosphate-buffered saline (PBS) at pH = 7.2 with 1 µg/ml TT (Aventis Pasteur, Swiftwater PA, USA). All assays included a control plate coated with bovine serum albumin (BSA) to verify the specificity of the assays for the coating antigen. The low levels of reactivity with the BSA plates were subtracted from the values on the antigen-coated plates. Plates were washed with PBS containing 0.05% Tween 20 (ELISA wash buffer). The plates were blocked with PBS containing 1% BSA for 1 hour at room temperature followed by incubation with the subjects’ prediluted sera (1:500 for the prevaccination samples and 1:4000 for the postvaccination samples; a few samples were diluted at 1:90 and 1:250 for the pre- and postvaccination samples, respectively) overnight at 4°C, then washed with ELISA wash buffer. The plates were incubated with a secondary antibody biotin-conjugated goat antihuman immunoglobulin antiserum IgG (H + L) (Southern Biotechnology Associates, Birmingham, AL) for 1 hour at room temperature. After another rewash with ELISA wash buffer, plates were incubated with streptavidin-alkaline phosphatase (Southern Biotechnology Associates, Birmingham, AL) for 1 hour at room temperature. After the final wash with ELISA wash buffer, the plates were developed with p-nitrophenyl phosphate (Sigma, St. Louis, MO, USA) and absorbance was read at 405 nm in a microplate reader. All antibodies against TT were standardized to human antibodies with a known concentration.

Single Nucleotide Polymorphisms Genotyping
Ten single nucleotide polymorphisms (SNP) on six cytokine genes (IL-1ß, IL-2, IL-4, IL-10, IL-12ß, TNF-{alpha}) were genotyped with the ABI 7500 Fast Real-Time PCR System using the Taqman 5' nuclease assay for allelic discrimination. The Applied Biosystems (ABI) assay-on-demand service was used to order probes and primers for the 10 cytokine SNP available publicly at www.appliedbiosystems.com. The total volume for PCR reactions was 5 µl, including 1 µl genomic DNA (33 ng/µl), 1.25 µl sterile water, 2.5 µl of TaqMan Universal PCR Master Mix, and 0.25 µl TaqMan SNP Genotyping Assay Mix containing 18 µM of a given primer and 4 µM of a given probe. Plates were preread, run, and postread on the 7500 Fast real-time PCR System. Standard mode conditions were used for all the assays. Sequence Detection software version 1.3 (Applied Biosystems) was applied for the allelic discrimination analysis.

Statistical Analysis

Outcome Variable
The pre- and postvaccination anti-TT IgG (pre-IgG and post-IgG) concentrations were log10 transformed to achieve normality for the residuals of the models before analyses. The outcome variable is the TT-induced antibody fold increase, defined as log10 (post-IgG/pre-IgG).

Nongenetic Factors
The baseline CES-D and PSS scores were the main exposures of interest. Nine other covariates were also adjusted for, including gender, age, baseline anti-TT IgG, nutrition score, comorbidity score, positive aspects of caregiving score, social support score, social activities score, and the days between the two home visits.

Genetic Analysis
Mendelian transmission of the 10 SNP markers was checked using the MARKERINFO procedure in S.A. G. E; any errors were corrected or set to missing values before the analysis. Hardy-Weinberg equilibrium was confirmed for all loci using the Mantel-Haenszel exact {chi}2 goodness-of-fit tests in 47 spouses. The additive and dominant effects of each of the 10 SNP markers on the antibody fold increase were assessed one at a time in the presence of all of the above nongenetic covariates. SNPs that were significant in the multivariable setting were entered together with all the other nongenetic covariates to form the full models.

Full Models
There were two full models: the CES-D model and the PSS model. The CES-D and the PSS scores, although highly correlated, measure two independently predictive constructs (17): PSS for perceived stress and CES-D for depressive symptoms. Therefore, the effects of PSS and CES-D were assessed in different models. Except for the stress measures, the two models share the same genetic and nongenetic covariates described above.

The association between antibody response and the genetic and nongenetic factors were performed using the Proc Mixed procedure in SAS (SAS Institute, Cary, NC), with the unstructured covariance matrix specified to account for the familial correlations. The significance levels used an {alpha} of 0.05.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
DISCUSSION
 NOTES
 REFERENCES
 
Baseline Caregiver Characteristics
Table 1 describes the baseline characteristics of the family caregivers. Overall, the mean ± standard deviation age was 57.1 ± 16.0 years; 60% of the participants were females; only two people reported using alcohol and smoking cigarettes in the past month at the time of sample ascertainment; the most common self-reported disease conditions were arthritis (32.8%), hypertension (27.7%), heart disease (14.3%), and psychiatric disorders (12.6%). According to the MNA, an overwhelming majority of the participants were well nourished (84%) and none of them was malnourished. Medication usage indicated that 24.4% of the caregivers took ≥3 prescription drugs per day, but the specific drug names were not obtained. The CES-D and PSS scores were 7.6 ± 4.9 and 14.8 ± 6.1, respectively. The scores for the stress-buffering factors were 19.7 ± 4.8 for social support, 8.1 ± 3.1 for social activities, and 25.4 ±6.7 for positive aspects of caregiving. The geometric mean for the baseline antitetanus IgG concentrations was 7.0 µg/ml (95% Confidence Interval range: 0.1–104.3). The average days between the two home visits were 27 ± 5 days.


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  		TABLE 1. Baseline Characteristics of Family Caregivers

 

Cytokine SNP Association
Univariate analyses conducted in both additive and dominant models showed that none of the cytokine genes was associated with the baseline antitetanus IgG (data not shown). In the multivariable setting, the dominant effect of IL-10–1082 A>G SNP (GG versus GA + AA) was associated with the antibody fold increase in the presence of all other nongenetic covariates in both the PSS model (p = .01) and the CES-D model (p = .0004) (Table 2). Thus, the model that contained the dominant effects of the IL-10–1082 A>G SNP and all other nongenetic covariates formed the final models.


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  		TABLE 2. Genotype Frequencies of Selected Cytokines and Their Association With the Baseline Antitetanus IgG and the Antibody Fold Increase in Family Caregivers

 

Predictors of Antibody Response
The log-transformed geometric means of the pre- and postvaccination antitetanus IgG concentrations declined by age (p < .0001 for pre-IgG; p = .0008 for post-IgG), whereas the crude antibody fold increase increased by age (p = .03). Overall, 70.6% of the people had protective immunity at baseline and 96.6% reached protective immunity after vaccination (data not shown).

Univariate analyses examining the association between baseline antitetanus IgG levels and the baseline nongenetic factors (CES-D score, PSS score, age, gender, nutrition, comorbidity, social support, social activities, and positive aspects of caregiving) showed that only age (p < .0001) and comorbidity score (p = .02) were significantly associated (data not shown). When further univariate analyses were performed between those same nongenetic factors and the antibody fold increase (Table 3), age became a positive predictor (p = .03), whereas the baseline antitetanus IgG (p < .0001) and the baseline CES-D scores (p = .03) were negative predictors; the baseline PSS score was not a significant predictor for antibody fold increase in the univariate analysis (p = .15).


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  		TABLE 3. Univariate Analysis on Nongenetic Factors and Antibody Fold Increase

 

In the full models, the baseline antitetanus IgG levels, the GG genotype of the IL-10–1082 A>G SNP, the baseline PSS scores, and the baseline CES-D scores were significant predictors for the antibody fold increase (Table 4). In both the CES-D and the PSS models, the baseline IgG levels were inversely associated with the antibody fold increase (p < .0001); people with the GG genotype of the IL-10–1082 A>G SNP had lower antibody fold increase compared with those with the AA + AG genotype (p = .01). The PSS and the CES-D scores had a negative impact on the antibody fold increase, with every point increase in the PSS score associated with 6.2% less antibody fold increase (p = .01) and every point increase in the CES-D score associated with 7.0% less antibody fold increase (p = .004).


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  		TABLE 4. Predictors for Antibody Fold Increase in Family Caregivers

 


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
NOTES
 REFERENCES
 
The current study found that the baseline CES-D score, the baseline PSS score, the GG genotype of the IL-10–1082 A>G SNP, and the baseline antitetanus IgG levels were inversely associated with antibody fold increase in response to tetanus vaccine adjusting for other potential confounders. Because the CES-D and PSS scores reflect general stress and not caregiving-specific stress, these findings have broader implication for the detrimental effect of global stress on vaccine-induced antibody response. Moreover, these findings demonstrate that antibody response is under the influences of key cytokine genes and other nongenetic factors.

It is important to note that, in this study, stress was assessed differently from previous ones (4,8). First, instead of using caregiving status as a proxy for stress, the current study analyzed CES-D scores and the PSS scores as independent predictors and was thus able to directly quantify the separate effects of the PSS and the CES-D scores on the antibody response in the family caregivers. The results showed that every point increase in the CES-D score translated into about 7% less antibody fold increase and every point increase in the PSS score about 6% less antibody fold increase. Second, the association between stress and the antibody response was adjusted for a number of immunoregulatory cytokine genes and some nongenetic factors that have influence on immune response, including age, gender, nutritional status, comorbidity, baseline antitetanus IgG levels, and stress-buffering factors. A good case in point is comorbidity. Some previous reports on the difference in antibody response between caregivers and noncaregivers may be partially explained by the fact that the noncaregivers are typically healthier than caregivers. In this study, adjusting for comorbidity provides better control for the confounding by health status than using caregiver status itself. Further, the differences in the univariate analyses and multivariate analyses pointed to the importance of covariate adjustment. For instance, the PSS score was not significant in univariate analysis but became significant in the presence of other genetic and nongenetic factors, suggesting the presence of genetic or nongenetic confounders. In addition to covariate adjustment in statistical models, the current study adopted a family study design that included both the spouse and the offspring of the patients with AD. In this study, whereas all the spouses lived with patients with AD at home and were the primary caregivers, the majority of the offspring lived in close proximity to their parents and helped with the caregiving on a regular basis. The inclusion of the offspring who live close to their parents provided the unique advantage in accounting for many unmeasured environmental exposures and genes shared by the family members, thus strengthening the control for confounding. Finally, most previous studies examined vaccine-induced antibody response as a dichotomous variable, such as beyond certain thresholds (2–9). The current study, however, assesses the antibody fold increase as a continuous variable, which provides greater power in detecting factors with moderate effects.

It is important to adjust for the baseline antitetanus IgG levels because everyone in the current study had the tetanus vaccination previously, e.g., 71% of the study participants had protective antitetanus IgG levels at baseline. Furthermore, the postvaccination antibody titer is known to be determined by the prevaccination antibody titer: the lower the prevaccination titer, the higher the postvaccination levels (43,44). Danilova et al. (44) found that in healthy Russian young men, those with prevaccination anti-TT IgG concentrations ≥17 µg/ml were unable to mount a three-fold increase after the vaccination. The negative association between the baseline antitetanus IgG and the antibody fold increase is consistent with those findings. More importantly, in this study, elderly people (>65 years) had much lower baseline antitetanus IgG levels compared with younger people. Thus, adjusting for the baseline levels also eliminates the confounding by age with the antibody fold increase, allowing for better assessment for the effects of the baseline PSS scores, the baseline CES-D scores, and the IL-10–1082 A>G SNP on the antibody fold increase without the confounding by age and the baseline antitetanus IgG levels.

Furthermore, the findings suggested that individuals carrying the GG genotype of the IL-10–1082 A>G SNP has lower antibody fold increase compared with those carrying the AG + AA genotypes. The IL-10–1082 A>G SNP has also been found to influence the antibody response to hepatitis A and hepatitis B vaccines (29) and the high IL-10 production was associated with low antibody response to influenza vaccine in the elderly (45). IL-10 is a critical anti-inflammatory cytokine that activates B cells, promotes B cell survival, proliferation, and differentiation, induces immunoglobulin class switching to the IgG isotype, and enhances antibody response (46). In addition to its direct actions on B cells, IL-10 exerts its immunoregulatory influence by inhibiting key proinflammatory cytokines such as TNF-{alpha}, IL-1ß (46). More importantly, the expression of IL-10 is regulated at the transcriptional level and polymorphisms at the promoter regions of both cytokines are associated with the variability in their production. For the IL-10–1082 A>G SNP compared with the –1082 G allele, the –1082A alleles confer higher binding affinity for the transcription factor PU.1, which inhibits gene expression and leads to decreased IL-10 transcription activity in individuals carrying this allele (47). Turner et al. (48) reported a decreased IL-10 production in positive individuals with –1082A, but these results were not confirmed by other studies (49,50). Taken together, the individual differences in the production of IL-10 and other cytokines produced during antibody response combined with the synergistic and antagonistic actions in the Th1/Th2 cytokine network may determine the magnitude of the antibody fold increase.

The effects of the IL-10–1082 A>G SNP were consistent in both the CES-D and the PSS models. However, there are some unresolved issues. First, this study did not measure cytokine levels. Therefore, we cannot determine the associations among the IL-10 polymorphisms, the cytokine levels, and the antibody response. Second, due to its anti-inflammatory effects, IL-10 has been studied as a potential treatment for chronic inflammatory diseases for which steroid is the standard therapy. Clinical studies found that a single dose of IL-10 resulted in a 20% increase in plasma cortisol levels within 24 hours (46). It remains to be seen how the cytokines and the stress hormone cortisol interact with each other in vivo during stress reactions to influence antibody response.

Consistent with the literature, gender is not a significant predictor for antibody response. Nor were any of the stress-buffering factors, including social support, social activities, and positive aspects of caregiving. Vedhara et al. (9) found that an 8-week stress management intervention helped improve the caregiver’s immune response to the influenza vaccine. However, the current study did not provide stress intervention but assessed the association between the stress-buffering factors measured at baseline and the antibody fold increase. This may explain why we did not observe the expected beneficial effects from those factors. Another possibility is that the current study lacks the power to adequately assess the effects of the stress-buffering factors because testing stress-buffering effects requires testing interactions. Other factors, including nutritional status, comorbidity, and time between obtaining the two blood samples, were not associated with antibody fold increase in univariate or multivariate analyses. There were only two smokers and two alcohol drinkers in this sample. The lack of variability in those two variables did not allow us to adjust for them in the full models.

This study had several limitations. First, to prevent population stratification, the study participants were restricted to Caucasians—a restriction that limits the generalizability of the study to other ethnic populations. Population stratification is a spurious genetic association due to the differences in the allele frequencies present in different ethnic populations. A good case in point is the IL-10–1082 A>G SNP. The A and G alleles are almost equally distributed in Caucasians, but unevenly distributed in other ethnic populations. Had other ethnic populations being included, the association between the IL-10–1082 A>G SNP may not have been detected due to the much lower frequency of the G allele, or a spurious association may have been detected due to the differences in the allele frequencies in different ethnic population but not because of any real genetic impact on antibody response. A further restriction is that, because the caregivers are a highly stressed sample, the results may not be generalizable to more normative samples. Furthermore, one of the most common reasons for declining participation in the study was "already too stressed out to handle a study." It was very likely that those with the highest stress levels were self-selected out of the study, resulting in an inadequate representation of individuals with the highest stress levels. Had the highly stressed caregivers been included in the study, we would expect to see much stronger effects of stress on the antibody response than what was observed in the current study. Only 5.3% of the caregivers in this study had clinical depression based on the CES-D score of ≥15 (41,51), compared with the REACH (Resources for Enhancing Alzheimer’s Caregiver Health) Caucasian cohort where 24.5% in the control group and 10.5% in the experimental group after intervention were classified as having clinical depression using the same CES-D score cut-off (32). The mean PSS score in the current study also seemed to be lower compared with another caregiver study by Glaser et al. (8): 14.8 ± 6.1 versus 16.7 ± 2.82. Third, we did not measure caregiving variables, such as including years spent caregiving, the number of hours spent on caregiving daily, or the extent of the patients’ cognitive impairment. However, the majority of the caregiving literature has found no association between antibody response and those variables (4,8). Moreover, we are more interested in examining the effects of global stress in a context broader than caregiving-specific stress. Finally, we did not do analyses on a dichotomous outcome indicating whether or not an individual has reached protective tetanus immunity because the tetanus vaccine is highly immunogenetic and only four people in the study failed to reach that level after the vaccination.

The original power calculation suggested 50 families with one spouse and two offspring were needed to test the genetic association. In reality, 25 families with one spouse and two offspring and 22 families with one spouse and one offspring were recruited. This may increase the chance of random error. However, the strength of the associations, covariate adjustment, the consistency of the results from both the CES-D and the PSS models, and the internal validity of the associations suggest our results are valid, but replication of these results in an independent larger study would lead to greater support for our hypotheses regarding psychological stress and IL-10–1082 A>G SNP on the antibody response to TT.

In conclusion, the major findings from the current family-based association study were that the baseline CES-D score, the baseline PSS score, and the GG genotype of the IL-10–1082 A>G SNP were inversely associated with the antibody response to the tetanus vaccine adjusting for other potential confounders. The results provided additional evidence on the detrimental effects of psychological stress on the antibody response to the tetanus vaccine. It also demonstrated that antibody response is under the influences of both genetic and nongenetic factors. From the public health perspective, it is imperative to raise the awareness of the harmful effects of chronic stress among healthcare professionals and caregivers alike, so that the caregivers can seek proper counseling and support that will help them maintain a strong and healthy immune system as they care for their loved ones.

We are grateful for the support and trust of the caregivers who participated in this study. We also thank the staff in UAB Memory Disorder Clinic and UAB Alzheimer’s Disease Center for their support and cooperation with the recruitment.


   NOTES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
REFERENCES
 
Current address: Jian Li, Global Product Safety, Eli Lilly and Company, DC 2139, Indianapolis, IN 46285. E-mail: lijianx{at}lilly.com

This research was supported by Grant NS045934-06 from the National Institute of Neurological Disorders and Stroke and Grant 2RO1 AG09029-15 from the National Institute of Aging.

Received for publication October 9, 2006; revision received March 21, 2007.

DOI:10.1097/PSY.0b013e3180cc2c61


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 

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