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Influence of Gender and Age on the Peripheral Immune Response in Stroke

Ross, Amy Miner PhD, RN, CNS; Lee, Christopher S. PhD, RN; Lutsep, Helmi MD

The Journal of Cardiovascular Nursing: July/August 2016 - Volume 31 - Issue 4 - p 331–335
doi: 10.1097/JCN.0000000000000252
ARTICLES: Biobehavioral
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Background: Women and men have unique stroke risk factors and can experience different poststroke infections.

Objective: The aim of this study is to determine the influence of gender, age, and risk factors on the peripheral immune response in stroke/transient ischemic attack (TIA).

Method: A total of 192 adult acute stroke/TIA cases were analyzed for age, gender, risk factors for stroke/TIA, and white blood cell with differential count. χ2 Test and analysis of variance were conducted to test for differences between genders and age groups related to stroke risk factors and the immune response. Growth modeling was used to test for trended differences in the immune response.

Results: Women were 4 years older than men; fewer women had strokes in the younger age group (<79 years) and more men currently smoked. Trended lymphocyte percentages for the young and old (slope, P = .04; pattern, P = .02) and admission monocyte percentages by gender were significantly different (P = .01).

Conclusions: Age influenced trended lymphocyte numbers and gender influenced monocyte percentage on admission.

Amy Miner Ross, PhD, RN, CNS Assistant Professor, School of Nursing, Oregon Health & Science University, Portland.

Christopher S. Lee, PhD, RN Associate Professor, School of Nursing, Oregon Health & Science University, Portland.

Helmi Lutsep, MD Professor, School of Medicine, Oregon Health & Science University, Portland.

The authors have no funding or conflicts of interest to disclose.

Correspondence Amy Miner Ross, PhD, RN, CNS, School of Nursing, Oregon Health & Science University, 3455 SW US Veterans Hospital Rd, Mail code SN-6S, Portland, OR 97239 (rossam@ohsu.edu).

Stroke can result in devastating neurological deficits, with people living with disabilities for many years.1,2 Older age, gender, and infection are associated with poorer outcomes after stroke.3–5 The peripheral immune response after stroke onset is tied to an increased rate of infection.6 In general, after stroke, women have worse outcomes than men do.3 There are noted gender differences in risk factors for stroke3,7 and in types of infection after stroke.8,9 Relatively little is known about the interactions of age, gender, risk factors, and infection in the context of stroke. Therefore, the purpose of this study was to determine the associations between gender, age, and risk factors on the immune response, as a proxy for the increased risk of infection, in stroke/transient ischemic attack (TIA).

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Background

Just as in other disease processes, there are several sex-based (ie, chromosome activation or the influence of sex hormones) and gender-based (ie, differences between men and women that are determined by cultural and societal factors)10 differences in stroke. Some of the factors that lead to stroke are socioculturally based, like risk factors, and some are based in heritability (ie, epigenetics).11 Gender differences related to risk factors for stroke have generally shown that more men than women smoked3,7 and had hypertension and diabetes.7 The research on the presence of risk factors for stroke and the association with individual immune cell changes in the peripheral immune response is conflicting.12,13 Risk factors have been associated with individual immune cell changes in the peripheral immune response after stroke,12 but others have found that risk factors do not influence the presence of alterations in the peripheral immune response on hospital admission for stroke nor the trajectories of the peripheral immune response after stroke.13

Women have a lower incidence of stroke than men do when younger than 55 years, and after that, the incidence of stroke is equalized.14 However, other data have shown that after age 80 years, women’s incidence of stroke surpasses that of men.11 And women are an average of 4 years older than men at the time of their first stroke.1,14 Up to age 85 years, women have better survival rates than men do; after 85 years of age, their survival rate drops from 75% to 41%.3

Mortality and disability in stroke also differ by gender, with women having more lasting disability and higher death rates (13% higher) than men do.1,2 Fatality from stroke at 1 month is also higher in women than in men, 24.7% and 19.7%, respectively.1

When stroke patients are classified by the modified Rankin Scale (mRS) (a common neurological deficit outcome scale used in stroke) on discharge, those with higher mRS (ie, mRS = 3–5) have significantly higher white blood cell (WBC) counts on admission than do those with lower mRS (ie, mRS = 1–2).15 The WBC counts on admission in this study regardless of mRS classification were less than 11,000/mm3 (ie, the upper limit of normal).15 The researchers concluded that higher WBC counts on admission may denote a worse than expected outcome.15

Worsening outcomes have been linked to the presence of infection early in acute stroke onset.4,5 Infection type varies by gender, with men more commonly having pneumonia and women having urinary tract infection.8,9 Previous research has shown that the peripheral immune response after stroke is influenced by the presence of infection; however, WBC count was within normal limits possibly owing to the general lymphocytopenia.16 Peripheral immunosuppression is defined as an alteration in lymphocyte numbers that reflects changes in T- and B-cell subtype numbers (ie, T-regulator cell decrease, Th1-cell increase, and B-cell decrease).17 Peripheral immunosuppression is thought to be a result of sympathetic autonomic nervous system stimulation (by norepinephrine) of T-cell areas in lymphoid tissue while avoiding B-cell areas, thereby producing an elevation of T cells and a lowering of B cells and a generalized lymphocytopenia.6 Peripheral immunosuppression is considered a mediator of the increased risk for infection after stroke and is correlated with a down-regulation of the innate and adaptive immune system in animals.6 In addition, sex hormones seem to regulate peripheral immunosuppression without changing the peripheral immune response in the early hours after stroke in animals.18 If gender is associated with worse outcome and differing types of infection, then it is possible that immune responses differ by the accumulative influence of gender and infection in stroke as well.

Taken together, this evidence seems to show an age-gender interaction based on the idea that nonhormonal factors play a role in ischemic sensitivity.3,11

The effect of age, gender, and risk factors on the immune response (a proxy for risk of infection) in stroke is not known. The purpose of this study is to determine these associations.

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Method

An extant database with 192 adult (age >18 years) acute ischemic stroke/TIA patients was reviewed, and all acute ischemic stroke cases were included for analysis after institutional review board approval was obtained. This extant database included 500 cases from 2008 through 2010 of all types of stroke from a nonmetro primary stroke center. This extant database was used because the standard of care was consistent throughout this period. All patients were admitted within 24 hours of their stroke symptom onset. Variables included age; gender; history of diabetes, hypertension, smoking, hyperlipidemia, and previous stroke/TIA; peripheral immune response (ie, WBC count and percentages of neutrophils, lymphocytes, and monocytes) measured on admission and at 24, 72, and 96 hours after stroke onset. Some stroke patients were discharged before the end of the period that the peripheral immune response variables were collected; therefore, the analysis is truncated at 96 hours after the onset of stroke symptoms to be sure that an adequate number of cases were available for analysis.

Analysis included mean, standard error of the mean, standard deviation, median, skewness and kurtosis, and t tests on age. The median age of the sample was 78 years; this was used to create age categories to describe the demographics of the sample and to test main effects. χ2 Analysis was conducted on gender, history of diabetes, hypertension, smoking, hyperlipidemia, and previous stroke/TIA. Growth modeling was used on longitudinal data to estimate trends over a period. This analysis tests differences between groups on the intercepts (i), the slope of the change (s), and the pattern of the curve representing the trend of the change (q). Growth modeling was conducted to test the interactions between the independent variables of age category, gender, and risk factors for stroke on the dependent variables of the peripheral immune response. On the basis of previous findings, we (a) combined TIA and stroke cases as the dependent variables were not statistically different between these 2 groups,19 (b) did not separate TIA and stroke cases to test for differences between groups as a proxy for severity as the number of TIA cases were too small for comparative analysis,13,16 and (c) controlled for confounders, first-time versus recurrent stroke/TIA and presence and absence of infection, in the growth model.13,16

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Results

The demographics of this sample are shown in the Table. It was coincidental that there were equal numbers of men and women in the database used. Women, on average, were 4 years older than men (P = .038). There were more men than women with stroke/TIA in the younger than 79 years age group and more women than men in the 79 years or older age group (P = .043). All risk factors for stroke were equally prevalent between men and women, with the exception of more men than women currently smoking (P = .019). Therefore, smoking was the only risk factor added into the analysis as a confounder. First-time versus recurrent and presence or absence of infection were known confounders in the database.13,16

TABLE De

TABLE De

Based on growth modeling and controlling for confounders (ie, first-time vs recurrent stroke/TIA, presence or absence of infection and currently smoking), the intercept slopes and nonlinear patterns of change were similar comparing older and younger adults with respect to WBC counts and neutrophil and monocyte percentages (data not shown). In contrast, the slopes and patterns of change in lymphocyte percentages were different when comparing older and younger adults (Figure, panel A). Specifically, for those 79 years or older, lymphocyte percentages decreased to their lowest point at 72 hours and then showed an upswing at 96 hours. For those younger than 79 years, lymphocyte percentages remained stable between admission and 24 hours and then took a downslope with the lowest point at 96 hours after stroke/TIA. Significant differences were seen between these 2 age groups at 24 and 72 hours (P = .0012 and .020, respectively).

FIGURE. Diffe

FIGURE. Diffe

Based on growth modeling and controlling for same confounders as the above analysis, the intercept slopes and nonlinear patterns of change were similar comparing women and men with respect to WBC counts and neutrophil and lymphocyte percentages (data not shown). In contrast, the slopes and patterns of change in monocyte percentages were different when comparing women and men (Figure, panel B). Specifically, women had lower values of monocyte percentages at admission that increased steadily through the course of hospitalization, whereas men had higher values of monocyte percentages that remained steady over the course of hospitalization. Significant differences were seen between women and men on admission (P = .012).

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Discussion

Based on these data, there is an effect of age and gender on the peripheral immune response in stroke/TIA. First, patients who were 79 years or older had significantly lower lymphocyte percentages than did those in the younger age group. Second, men had significantly higher monocyte percentages on admission than women did. The sample for this study reflects the demographics of previously reported stroke studies (ie, more men than women were currently smoking; women were, on average, 4 years older than men; and there were more women than men in the older age category).1,3,7,12,14 The demographic findings add to the generalizability of the findings to the stroke population as a whole.

Interestingly, after controlling for confounders (first-time vs recurrent stroke, presence and absence of infection), the slope and pattern of the trend of the lymphocyte percentages, but not the starting place, were associated with age groups. Essentially, immunosuppression is the dampening of the lymphocyte response by T-cell subtype after the onset of stroke.6 Lymphocytes are the effector cells of the adaptive immune system and are activated when there is an infectious threat.20 The findings of this study are hypothesis generating in nature with examples to follow. If immunosuppression is associated with the older age group, then the older age group would likely not be able to mount a defense against infection.18 The findings of this study support the notion that immunosuppression (ie, the decreased trend in the percentage of lymphocytes) in the stroke population a few days after onset of stroke may increase the risk of infection by aspiration or urinary dysfunction in the older patients.9,18 Conversely, this may mean that patients who are younger have a more intact immune response and therefore are not at an increased risk of infection because of decreased lymphocyte numbers. The protection in younger stroke patients may be a result of lymphocyte numbers approaching normal in the first several days after stroke. It is interesting that in the younger age group, the lymphocyte numbers are lower at 96 hours and may reflect late phase lymphocyte margination or immunosuppression. If immunosuppression is a result of activation of the lymphoid tissue by the sympathetic autonomic nervous system, this may be evidence that older patients are unable to sustain a normal response in the face of norepinephrine secretion.

Because the sample differences between men and women showed a significant difference in those people who were currently smoking, smoking was added into the analysis of the trends and helped to elucidate the changes in monocyte percentages. Monocytes are 1 of the 2 effector cells of the innate immune system (the other, neutrophils) and account for the readied response to injury and infectious threat by using the major activity of this cell type, phagocytosis.20 Smoking can immediately activate and increase monocyte and neutrophil percentages,12 and more men than women are current smokers.3,7 In this study, after controlling for confounders (ie, first-time vs recurrent stroke/TIA, presence or absence of infection, and currently smoking), monocyte percentages were significantly higher on admission in men than in women and the slope of the trend essentially differs. This may reflect the additive effect of more men than women currently and recently smoking on admission in general. This may be a population norm for the peripheral immune response in stroke and not reflect a significant change in the way different gender’s immune systems respond to the stroke event.

By and large, the WBC counts in both the age category trends and the gender trends show that the mean of the WBC count was within normal limits. This is similar to the findings previously reported.13,16 Only at 72 and at 96 hours were the variances of the WBC counts outside the limits of normal (ie, 5000–10 000 WBC counts per cubic millimeter of blood). This may reflect those patients with infection developing after the stroke event. However, the WBC count did not fall into the expectations that conditions complicated by infection have WBC counts over 10,000 WBC counts per cubic millimeter of blood.20

The limitations of this study are retrospective collection of the data, the dichotomous categories for the risk factor assessments, and the lack of specification about infection types. These limitations can be overcome in future research studies where participants are enrolled prospectively; risk factors are assessed as multicategorical, stratified rank, or continuous data; and infection types and emergence of infection in particular poststroke timeframes are specified. In addition, it would be pertinent in future research to assess stroke severity using the National Institutes of Health Stroke Scale and stroke outcome using the mRS (a measure of the effect or severity of stroke deficits) and prospectively collect data on the immune response and its ties to preclinical measures (eg, interleukins and T-cell subtypes).

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Conclusions and Recommendations

We found trend differences in the peripheral immune response that can be attributed to age and gender. It is of interest that age alone influenced the slope and pattern of change in lymphocyte numbers and that this may account for infection susceptibility in older patients and their higher morbidity and mortality. Gender may influence monocyte percentage, and this may be attributed to the concomitant risk factor profile of the patients. This adds to the knowledge that there are specific immune response in stroke groups that are demographically different from each other.

It is critically important for nurses to be aware of possible windows of risk for infection and effect measures to prevent infection in susceptible stroke patients. Nurses should know that the hallmark for assessment for infection or impending infection, the WBC count rising above the upper limits of normal, might not appear in the WBC with differential panel that they monitor in stroke patients. Rather, nurses should monitor lymphocyte percentages in the post–acute ischemic stroke patient to determine the individual window of risk of infection. To this end, nurses will need to monitor other signs of infection in the patient with normal laboratory values (eg, lung sounds, chest x-rays, and urine analyses) to determine who is at risk for pneumonia and urinary tract infection. Future research related to the identification of groups of stroke patients who are susceptible to infection using age, gender, and preclinical and clinical immune measures will allow nurses to target these stroke patients improving neurological outcomes and comorbidity with early intervention.

  • There are trend differences in the peripheral immune response in stroke that can be attributed to age and gender.
  • It is of interest that age alone influenced the slope and pattern of change in lymphocyte numbers and that this may account for infection susceptibility in older patients with stroke and their higher morbidity and mortality. Monitoring lymphocyte percentages and their changes over the first 24 hours after stroke may provide an early alert of susceptibility to infection and provide an early treatment window.
  • Gender may influence monocyte percentage, and this may be attributed to the concomitant risk factor profile of the stroke patients.
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Keywords:

leukocytes; lymphocytes; monocytes; neutrophils; stroke

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